• History & Evolution
• Biosynthesis & dietary uptake
• Nicotinic acid and the microbiome
• Nicotinic acid and immunity
• Nicotinic acid and cardiometabolism
• Nicotinic acid and pharmacology
• Nicotinic acid and 5P medicine
• References

History & Evolution

1867: first synthesis | 1937: defined as vitamin B3 | 1950s: discovery of lipid-lowering effect

First synthesized in 1867 by Huber, nicotinic acid gained biomedical relevance in the 1930s through research on pellagra, a severe vitamin B3 or tryptophan deficiency characterized by the “3Ds”: dermatitis, diarrhea, and dementia. In 1937, a team led by Conrad Elvehjem isolated nicotinic acid from liver extract and used it to cure “black tongue”, the canine equivalent of pellagra. Soon after, nicotinic acid and nicotinamide were confirmed as pellagra curative factors in humans and established as essential components of niacin, also known as vitamin B₃ (Matthews 1938; Bieganowski et al. 2004). These findings laid the foundation for recognizing their fundamental role in cellular redox metabolism and energy homeostasis.

In the 1950s, nicotinic acid gained additional importance as a pharmacological agent when Rudolf Altschul demonstrated that gram dose supplementation lowered plasma cholesterol. It became the first effective lipid lowering drug, shown to reduce low-density lipoprotein (LDL) cholesterol, increase high-density lipoprotein (HDL) cholesterol, and promote regression of xanthomas -lipid-rich deposits that develop under the skin, well before the protective role of HDL was fully understood (Carlson 2005). Unlike nicotinamide, nicotinic acid exhibits distinct lipid modifying effects but is also associated with the niacin flush characteristic of high dose vitamin B₃ uptake, which drove the development of modified and extended release formulations to improve tolerability (Carlson 2005).

Today, nicotinic acid is recognized as both an essential form of vitamin B₃ and a historically important drug, with its role in NAD⁺ biology linking early nutritional discoveries to modern research on metabolism and disease.

Biosynthesis vs. dietary uptake

Nicotinic acid contributes to vitamin B₃ supply through dietary intake and endogenous biosynthesis, ultimately sustaining cellular pools of cofactors NAD⁺ and NADP+. In the diet, nicotinic acid is found in foods such as meat, fish and nuts (Zeman et al. 2015).

After intestinal absorption, nicotinic acid directly enters NAD⁺ biosynthesis via the Preiss–Handler pathway, where it is converted by nicotinic acid phosphoribosyltransferase 1 (NAPRT1) to nicotinic acid mononucleotide (NAMN) and subsequently incorporated into NAD⁺ and NADP⁺ (Oyama et al. 2024).

In addition, NAD⁺ can be synthesized from tryptophan via the kynurenine pathway. Tryptophan is metabolized through multiple enzymatic steps to quinolinic acid, which is then converted to NAMN and enters NAD⁺ biosynthesis at the same metabolic node as the Preiss–Handler pathway (Fukuwatari et al. 2013). This de novo route is considered metabolically inefficient in humans (Goldsmith et al. 1961) and nutritionally demanding, requiring several micronutrient cofactors (McCormick 1989). Dietary processing strongly affects nicotinic acid bioavailability, as illustrated by maize based diets lacking alkaline treatment, in which niacin remains poorly absorbable (Carpenter 1983).

Because NAD⁺ acts as a central redox cofactor, including its role in the tricarboxylic acid cycle, adequate nicotinic acid availability is essential for mitochondrial respiration and energy metabolism (Oyama et al. 2024).

Excess nicotinic acid that is not incorporated into NAD⁺ or NADP⁺ pools undergoes hepatic detoxification, primarily through methylation to N¹ methylnicotinamide, followed by oxidation and conjugation to form nicotinuric acid, which is ultimately excreted in the urine (Neuvonen et al. 1991).

Nicotinic acid and the microbiome

The gut microbiome contributes to host nicotinic acid and NAD⁺ metabolism, forming a bidirectional metabolic exchange between host tissues and gut bacteria. While dietary nicotinic acid is largely absorbed in the upper intestine, circulating host derived nicotinamide, which is continuously generated through NAD⁺ consuming reactions, can reach the gut lumen, where it is converted by the microbial enzyme nicotinamide deamidase (YNDase) into nicotinic acid. Microbiome derived nicotinic acid can then re enter host metabolism and support Preiss–Handler–dependent NAD⁺ biosynthesis, thereby helping to maintain systemic NAD⁺ homeostasis even under conditions of low dietary intake (Chellappa et al. 2022).

Beyond systemic metabolism, microbiome derived nicotinic acid exerts local effects in the intestine. Recent work in mice demonstrated that bacterially produced nicotinic acid shapes colonic epithelial identity and regionalization, partly through nuclear receptor signaling, and protects against epithelial injury in preclinical models (Rispal et al. 2026). These findings link microbial nicotinic acid production to intestinal barrier integrity and susceptibility to inflammatory damage.

Nicotinic acid and immunity

Nicotinic acid directly modulates immune and inflammatory responses primarily through activation of the G protein–coupled receptor GPR109A (HCAR2), which is expressed on macrophages, epithelial cells, and other immune relevant cell types (Kostylina et al. 2008; Lukasova et al. 2011). In macrophages, cell culture and animal models demonstrated that nicotinic acid–GPR109A signaling promotes an anti inflammatory phenotype with reduced release of NF κB–dependent mediators such as TNF α and IL 6 (Digby et al. 2012; Si et al. 2014). These effects contribute to the anti atherosclerotic properties of nicotinic acid by simultaneously modulating macrophage inflammation and foam cell formation (Lukasova et al. 2011; Si et al. 2014). In contrast, GPR109A activation in cutaneous immune cells mediates prostaglandin release and underlies the characteristic niacin flush observed in humans (Morrow et al. 1989; Benyó et al. 2005).

Beyond the periphery, neuronal and glial cell culture studies have shown that nicotinic acid suppresses NF κB–driven inflammatory signaling, suggesting a role in regulating neuroinflammation (Wuerch et al. 2023). In addition, silk based biomaterial scaffolds incorporating nicotinic acid have emerged as localized anti inflammatory delivery systems, where controlled release reduces inflammatory responses and improves tissue compatibility in preclinical models (Zakeri Siavashani et al. 2019).

Nicotinic acid and cardiometabolism

Nicotinic acid has long been recognized as a potent modulator of dyslipidemia, particularly in the context of metabolic syndrome and type 2 diabetes (Carlson 2005; Keenan 2024). At pharmacological doses, nicotinic acid lowers very low-density lipoprotein (VLDL), LDL, triglycerides, and lipoprotein(a), the latter being a lipoprotein fraction that is largely refractory to pharmacological and lifestyle based interventions (Capuzzi et al. 1998; Carlson 2005; Zeman et al. 2015). In parallel, nicotinic acid produces the most pronounced increase in HDL cholesterol among available lipid modifying agents, largely by reducing hepatic apolipoprotein A-1 catabolism and enhancing macrophage cholesterol efflux via ATP-binding cassette transporter A1 (ABCA1) (Carlson 2005).

These lipid effects arise primarily from inhibition of adipose tissue lipolysis, resulting in reduced plasma free fatty acid availability and secondary reductions in hepatic triglyceride synthesis and VLDL secretion (Carlson 2005). Early monotherapy trials, including the Coronary Drug Project, demonstrated reductions in cardiovascular events, stroke risk, and mortality (Keenan 2024). In contrast, large contemporary outcome trials (AIM HIGH and HPS2 THRIVE) failed to show incremental benefit when nicotinic acid was added to intensive statin therapy, despite robust lipid improvements (Zeman et al. 2015).

These results prompted a reevaluation of nicotinic acid in cardiovascular prevention but have also been widely criticized. Major limitations include conditions under maximally optimized statin therapy, use of sustained release formulations, fasting or bedtime dosing, potential GPR109A desensitization and metabolic counter regulation, limited treatment duration, and population specific safety signals, particularly in HPS2 THRIVE (Zeman et al. 2015; Keenan 2024). Together, these factors suggest that the neutral outcomes of contemporary trials may reflect context dependent inefficacy, rather than a lack of intrinsic cardiometabolic potential.

Nicotinic acid and pharmacology

Pharmacologically, nicotinic acid acts through both receptor mediated signaling and integration into NAD⁺ dependent metabolic pathways. Activation of GPR109A mediates acute anti lipolytic and anti inflammatory effects but also causes the characteristic cutaneous flushing, driven by prostaglandin D₂ and E₂ release from epidermal Langerhans cells (Zeman et al. 2015). Consequently, formulation and dosing are critical: immediate release nicotinic acid is effective but poorly tolerated, whereas sustained release formulations reduce flushing at the cost of increased hepatotoxicity. Extended release preparations were developed to balance efficacy and safety and have demonstrated long term lipid efficacy as monotherapy in humans under appropriate monitoring (Capuzzi et al. 1998).

Beyond receptor signaling, pharmacological nicotinic acid rapidly feeds into NAD⁺ metabolism, activating peroxisome proliferator-activated receptors (PPAR)α and PPARδ dependent programs that regulate fatty acid oxidation and carnitine homeostasis in animal and mechanistic cell based studies (Couturier et al. 2014). Human tracer studies further show that intermittent, postprandial dosing favorably remodels lipid trafficking, markedly reducing hepatic and cardiac lipid exposure without sustained metabolic escape (Montastier et al. 2025). Together, these findings define nicotinic acid pharmacology as dose , formulation , and context dependent, extending beyond classical lipid endpoints.

Nicotinic acid and 5P medicine

Therapeutic use of nicotinic acid exemplifies a context dependent metabolic intervention whose effects depend on dose, formulation, timing, and individual metabolic state, spanning cardiometabolic, immune, and neurological pathways. Through its role as a precursor of NAD⁺, nicotinic acid supports cellular energy metabolism, mitochondrial function, and redox homeostasis, processes that decline with aging and contribute to reduced metabolic resilience, making nicotinic acid a potential aging relevant metabolic supplement, particularly for supporting stress adaptation rather than lifespan extension per se (Yang et al. 2019; Oyama et al. 2024).

From a preventive cardiometabolic perspective, clinical studies demonstrate improvements in dyslipidemia and, with short acting postprandial dosing, enhanced adipose tissue fatty acid trapping with reduced hepatic and cardiac lipid exposure (Montastier et al. 2025). The precision and personalization dimensions of 5P medicine are underscored by large inter individual differences in lipid response (Zeman et al. 2015), flushing susceptibility (Benyó et al. 2005), glucose handling (Zeman et al. 2015), and inflammatory tone, while the immune dimension reflects context dependent modulation of macrophage activity (Lukasova et al. 2011; Digby et al. 2012). Emerging evidence further suggests nicotinic acid as a supportive strategy in neurological disorders, including Alzheimer’s disease, Parkinson’s disease, glioblastoma, and amyotrophic lateral sclerosis. These interests are largely driven by nicotinic acid’s role as a precursor of NAD⁺ (Wuerch et al. 2023). Together, these findings position nicotinic acid as a context dependent metabolic modulator whose clinical value emerges from precision in dose, timing, and patient stratification, rather than uniform application.

References

Benyó, Z. et al.: GPR109A (PUMA-G/HM74A) mediates nicotinic acid-induced flushing (2005) The Journal of clinical investigation | https://doi.org/10.1172/JCI23626.

Bieganowski, P. et al.: Discoveries of nicotinamide riboside as a nutrient and conserved NRK genes establish a Preiss-Handler independent route to NAD+ in fungi and humans (2004) Cell | https://doi.org/10.1016/S0092-8674(04)00416-7.

Capuzzi, D.M. et al.: Efficacy and safety of an extended-release niacin (Niaspan): a long-term study (1998) The American journal of cardiology | https://doi.org/10.1016/S0002-9149(98)00731-0.

Carlson, L.A.: Nicotinic acid: the broad-spectrum lipid drug. A 50th anniversary review (2005) Journal of internal medicine | https://doi.org/10.1111/j.1365-2796.2005.01528.x.

Carpenter, K.J.: The relationship of pellagra to corn and the low availability of niacin in cereals (1983) Experientia. Supplementum | https://doi.org/10.1007/978-3-0348-6540-1_12.

Chellappa, K. et al.: NAD precursors cycle between host tissues and the gut microbiome (2022) Cell metabolism | https://doi.org/10.1016/j.cmet.2022.11.004.

Couturier, A. et al.: Pharmacological doses of niacin stimulate the expression of genes involved in carnitine uptake and biosynthesis and improve the carnitine status of obese Zucker rats (2014) BMC pharmacology & toxicology | https://doi.org/10.1186/2050-6511-15-37.

Digby, J.E. et al.: Anti-inflammatory effects of nicotinic acid in human monocytes are mediated by GPR109A dependent mechanisms (2012) Arteriosclerosis, thrombosis, and vascular biology | https://doi.org/10.1161/ATVBAHA.111.241836.

Fukuwatari, T. et al.: Nutritional aspect of tryptophan metabolism (2013) International journal of tryptophan research : IJTR | https://doi.org/10.4137/IJTR.S11588.

Goldsmith, G.A. et al.: Efficiency of Tryptophan as a Niacin Precursor in Man (1961) The Journal of Nutrition | https://doi.org/10.1093/jn/73.2.172.

Keenan, J.: The Niacin Rebirth: Revisiting the Potential of Nicotinic Acid Therapy for Cardiovascular Disease and Niacin Supplementation for Healthy Aging (2024) Medical Research Archives | https://doi.org/10.18103/mra.v12i7.5521.

Kostylina, G. et al.: Neutrophil apoptosis mediated by nicotinic acid receptors (GPR109A) (2008) Cell death and differentiation | https://doi.org/10.1038/sj.cdd.4402238.

Lukasova, M. et al.: Nicotinic acid inhibits progression of atherosclerosis in mice through its receptor GPR109A expressed by immune cells (2011) The Journal of clinical investigation | https://doi.org/10.1172/JCI41651.

Matthews, R.S.: PELLAGRA AND NICOTINIC ACID (1938) Journal of the American Medical Association | https://doi.org/10.1001/jama.1938.02790390004002.

McCormick, D.B.: Two interconnected B vitamins: riboflavin and pyridoxine (1989) Physiological reviews | https://doi.org/10.1152/physrev.1989.69.4.1170.

Montastier, É. et al.: Nicotinic acid increases adipose tissue dietary fatty acid trapping and reduces postprandial hepatic and cardiac fatty acid uptake in prediabetes (2025) European journal of pharmacology | https://doi.org/10.1016/j.ejphar.2025.177563.

Morrow, J.D. et al.: Release of markedly increased quantities of prostaglandin D2 in vivo in humans following the administration of nicotinic acid (1989) Prostaglandins | https://doi.org/10.1016/0090-6980(89)90088-9.

Neuvonen, P.J. et al.: The bioavailability of sustained release nicotinic acid formulations (1991) British journal of clinical pharmacology | https://doi.org/10.1111/j.1365‑2125.1991.tb03933.x.

Oyama, T. et al.: Supplementation of Nicotinic Acid and Its Derivatives Up-Regulates Cellular NAD+ Level Rather than Nicotinamide Derivatives in Cultured Normal Human Epidermal Keratinocytes (2024) Life (Basel, Switzerland) | https://doi.org/10.3390/life14030413.

Rispal, J. et al.: Microbiome-produced nicotinic acid controls colon regional identity and injury susceptibility (2026) Cell | https://doi.org/10.1016/j.cell.2026.02.007.

Si, Y. et al.: Niacin inhibits vascular inflammation via downregulating nuclear transcription factor-κB signaling pathway (2014) Mediators of inflammation | https://doi.org/10.1155/2014/263786.

Wuerch, E. et al.: The Promise of Niacin in Neurology (2023) Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics | https://doi.org/10.1007/s13311-023-01376-2.

Yang, N.-C. et al.: The Lifespan Extension Ability of Nicotinic Acid Depends on Whether the Intracellular NAD+ Level Is Lower than the Sirtuin-Saturating Concentrations (2019) International journal of molecular sciences | https://doi.org/10.3390/ijms21010142.

Zakeri Siavashani, A. et al.: Silk based scaffolds with immunomodulatory capacity: anti-inflammatory effects of nicotinic acid (2019) Biomaterials science | https://doi.org/10.1039/C9BM00814D.

Zeman, M. et al.: Niacin in the Treatment of Hyperlipidemias in Light of New Clinical Trials: Has Niacin Lost its Place? (2015) Medical science monitor : international medical journal of experimental and clinical research | https://doi.org/10.12659/MSM.893619.

• History & Evolution
• Biosynthesis & dietary uptake
• Dimethylglycine and cardiology
• Dimethylglycine and diabetes
• Dimethylglycine and neurology
• Dimethylglycine and immunity
• Dimethylglycine and oncology
• Dimethylglycine and 5P medicine
• References

History & Evolution

1943: discovery | 1950-1960: description as endurance enhancer | 1974: marketed as supplement

Dimethylglycine (DMG) was first described in 1943 (Cupp et al. 2003). It gained attention in the 1950s-1960s through studies conducted in the Soviet Union claiming improved oxygen use, reduced fatigue, and enhanced physical performance (Wolfsegger et al. 2021). This led to its widespread use among Russian athletes and cosmonauts. During this period, DMG was often incorrectly marketed as vitamin B15 or pangamic acid, in which it was sometimes included (Cupp et al. 2003).
DMG entered the U.S. supplement market in 1974, and similar performance claims appeared in American reports in 1975 (Wolfsegger et al. 2021). In 1982, the Food and Drug Administration (FDA) banned pangamic acid due to inconsistent composition and unsupported health benefits, but DMG itself remained legal (Cupp et al. 2003). Today, DMG is recognized not as a vitamin but as a natural metabolite in one carbon metabolism.

Biosynthesis vs. dietary uptake

DMG is a naturally occurring amino acid derivative present in the cells of all plants and animals. Small amounts are obtained through the diet, particularly from legumes, grains, and meat (Yao et al. 2022; Cupp et al. 2003). Dietary DMG that is not immediately metabolized in the liver enters the circulation and is delivered to peripheral tissues (Svingen et al. 2013)
In humans, most DMG arises from endogenous metabolism rather than direct dietary intake (Cupp et al. 2003). DMG is formed when choline is metabolized along the choline–betaine–glycine pathway. A key step in this path is the remethylation of homocysteine mainly in liver and kidney tissue: the enzyme betaine homocysteine methyltransferase (BHMT) transfers a methyl group from betaine to homocysteine, generating methionine and DMG (McGregor et al. 2001). Notably, DMG inhibits BHMT via negative a feedback loop (Svingen et al. 2013).
Once formed, DMG is rapidly oxidized in mitochondria by dimethylglycine dehydrogenase (DMGDH) to produce sarcosine, linking DMG metabolism directly to the folate dependent one carbon cycle (McAndrew et al. 2008). Under normal physiological conditions, circulating DMG levels remain low. A small fraction of unmetabolized DMG is excreted in urine (Svingen et al. 2013). Elevated DMG occurs when DMGDH function is impaired (McAndrew et al. 2008) or when BHMT activity is altered (McGregor et al. 2001).

Dimethylglycine and cardiology

Observational cohort studies consistently link plasma DMG levels with cardiovascular outcomes. In patients with recent acute coronary syndrome, higher baseline DMG was associated with increased risk of acute myocardial infarction, heart failure, and death over ~2.5 years (Lever et al. 2012). Similarly, in a large cohort with stable angina pectoris, DMG correlated with traditional coronary artery disease risk factors and independently predicted incident myocardial infarction during ~4.6 years of follow up (Svingen et al. 2013).
Furthermore, two cohorts of patients with suspected stable angina pectoris or acute myocardial infarction showed that elevated DMG was associated with higher all-cause and cardiovascular mortality, with stronger effects in acute myocardial infarction. DMG improved risk prediction in both groups (Svingen et al. 2015).
In pregnant women carrying fetuses with confirmed congenital heart disease, decreased maternal serum DMG emerged as a potential prenatal diagnostic marker (Xie et al. 2025). Mechanistically, high plasma DMG levels may be linked to the regulation of lipid and energy metabolism.
Experimental evidence suggests that activation of peroxisome proliferator activated receptor alpha (PPARα) reduces transcription of enzymes involved in DMG catabolism, potentially contributing to elevated circulating DMG concentrations (Svingen et al. 2015). However, the exact biological mechanisms underlying the observed associations between DMG and cardiovascular outcomes remain to be fully elucidated.

Dimethylglycine and diabetes

Observational human data indicate that low plasma DMG is associated with higher blood glucose. A genome-wide-association study identified a strong signal at the DMGDH locus that associated with lower DMG and higher insulin, HOMA IR and incident diabetes risk. This suggests that DMG deficiency may contribute to diabetes development and that DMGDH inhibition or DMG supplementation could be explored therapeutically (Magnusson et al. 2015). Additional metabolomics work shows DMG levels differ between normal glucose tolerance and impaired glucose regulation, positioning DMG as a risk associated marker in early dysglycemia (Liu et al. 2024).
Beyond these findings, maternal metabolic studies indicate that mothers carrying twins with low plasma DMG/betaine ratios have a decreased risk of gestational diabetes, suggesting that DMG-betaine balance may modulate glucose metabolism during pregnancy (Gong et al. 2021). Although all human evidence is observational and mechanistic or interventional studies are missing. The metabolic link becomes even clearer in the context of liver disease. The same ratio, this time assessed directly in hepatic tissue, proved highly relevant in a study of metabolic dysfunction associated steatotic liver disease (MASLD) in mice. The impaired DMG/betaine ratio was closely linked to disrupted one carbon remethylation (Pacana et al. 2015). These liver findings support the idea that altered DMG metabolism is part of a broader metabolic dysfunction relevant to both hepatic disease and diabetes.

Dimethylglycine and neurology

DMG supplements are often advertised as supporting cognitive function, mood, memory, or neurotransmitter synthesis, but scientific evidence for neurological benefits remains limited. Preclinical data show some promising mechanistic effects: in a BTBR mouse model of autism spectrum disorder (ASD), supplementation with DMG and B vitamins reduced ASD like behaviors, potentially through multifactor effects including decreased oxidative stress and inflammation, improved gut microbiota and gut permeability, altered body composition, reduced hepatic steatosis, and enhanced mitochondrial function in both liver and brain (Cimmino et al. 2025). However, these findings did not translate into clinical benefit. A double blind, placebo controlled trial in children with autism or pervasive developmental disorder reported no behavioral improvements in 33 of 37 participants receiving DMG (Kern et al. 2001). Similarly, a randomized, placebo controlled pilot study in patients with progressive multiple sclerosis found no effects of DMG on disability, fatigue, or cognitive and motor performance (Wolfsegger et al. 2021). Recent data strengthen the mechanistic rationale for DMG in neurodegeneration, particularly Alzheimer’s disease (AD). DMG was identified as the most effective of twelve metabolites in restoring catalase function, a key antioxidant enzyme impaired in AD, by preventing its aggregation, enhancing activity, stabilizing its native fold, and reducing amyloid like fibrils. Together, these effects suggest that DMG may help counter oxidative stress, a major driver of AD pathology (Devi et al. 2026). However, despite these mechanistic insights, human studies, including interventional trials or metabolomics guided supplementation studies, are still lacking, and no clinical evidence currently supports neurological benefits of DMG.

Dimethylglycine and immunity

DMG shows consistent immunomodulatory effects in animal studies, but human evidence remains limited. In a rabbit model, DMG supplementation markedly increased antibody titers to influenza and Salmonella typhi vaccines and enhanced lymphocyte proliferation, indicating stronger humoral and cellular immunity (Reap et al. 1990). A feline study also reported immunological shifts after DMG-containing supplementation, with reduced neutrophils and increased lymphocytes, possibly reflecting changes in B cell or NK cell activity (Shahril Agus et al. 2025). DMG may further influence immune tolerance: in a rat model of recurrent implantation failure, reduced DMG was linked to lower Treg cell levels and impaired endometrial receptivity, whereas supplementation helped restore immune balance (Liu et al. 2026).
In humans, only one small double blind trial from 1981 showed increased antibody responses and higher leukocyte inhibition factor activity after DMG intake, suggesting enhanced immunity (Graber et al. 1981). However, this finding has never been replicated, and no modern clinical trials confirm immune boosting effects. Thus, while animal data are supportive, evidence in humans remains preliminary and inconclusive.

Dimethylglycine and oncology

Evidence on an influence of DMG in cancer studies is mixed and appears highly context dependent. Large cohort studies report no association between circulating DMG levels and cancer risk, including two nested case-control studies on pancreatic cancer in Asian populations (Huang et al. 2017) and colorectal cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort (Nitter et al. 2014). In contrast, DMG is elevated in several tumor related settings. Urinary DMG was significantly increased in hepatocellular carcinoma (HCC) in a West African cohort and correlated with clinical stage, suggesting potential utility for surveillance (Ladep et al. 2014). Higher DMG has also been detected in esophageal tumor margins (Jianyong et al. 2017) and in fecal samples of colorectal cancer patients (Lin et al. 2016). One population study in individuals with hypertension reported a positive association between serum DMG and overall cancer risk (Zhang et al. 2023).
These divergent findings may reflect differences in population characteristics, disease stage, or sample types. Mechanistically, DMG participates in one carbon metabolism, supporting amino acid and nucleotide synthesis and cellular methylation reactions. When primary dietary methyl donors (choline, methionine, creatine) are insufficient, DMG can act as a secondary methyl donor. Because dysregulated methylation is a hallmark of cancer, shifts in DMG availability may influence tumor biology, although causal evidence is still limited (Zhang et al. 2023).

Dimethylglycine and 5P medicine

DMG is a molecular entry point into individualized, systems-oriented healthcare aligning with the principles of 5P medicine. Altered DMG levels have been linked to cardiometabolic risk and conditions such as myocardial infarction, diabetes (Magnusson et al. 2015), and metabolic dysfunction-associated liver disease (Pacana et al. 2015). Hence, DMG is positioned as potential early predictive marker even though causal evidence is still missing. Disease specific and matrix dependent patterns, like elevated urinary DMG in hepatocellular carcinoma (Ladep et al. 2014), increased fecal DMG in colorectal cancer (Lin et al. 2016), or reduced maternal DMG in pregnancies with congenital heart disease (Xie et al. 2025), highlight its relevance for more precise diagnostics or stratification. Because DMG metabolism is shaped by nutrition (Yao et al. 2022; Cupp et al. 2003), liver and kidney function (McGregor et al. 2001), genetics (McAndrew et al. 2008), and microbiome (Cimmino et al. 2025; Liu et al. 2024; Wang et al. 2022), individual interpretation is essential. Overall, DMG reflects interconnected pathways such as methylation, mitochondrial function, and cardiometabolic regulation, making it a valuable indicator of metabolic stress and early dysregulation.

References

Cimmino, F. et al.: Autism spectrum disorders and nutritional interventions: dimethylglycine and B-vitamins effects on behaviour, inflammation, microbiota and mitochondria in liver and brain synapses (2025) Biomedicine & pharmacotherapy | https://doi.org/10.1016/j.biopha.2025.118477.

Cupp, M.J. et al.: Dimethylglycine (N,N-Dimethylglycine) (2003) | https://doi.org/10.1007/978-1-59259-303-3_9.

Devi, A.P. et al.: Dimethylglycine as a Potent Modulator of Catalase Stability and Activity in Alzheimer’s Disease (2026) Biophysica | https://doi.org/10.3390/biophysica6010002.

Gong, X. et al.: Maternal Plasma Betaine in Middle Pregnancy Was Associated with Decreased Risk of GDM in Twin Pregnancy: A Cohort Study (2021) Diabetes, metabolic syndrome and obesity : targets and therapy | https://doi.org/10.2147/DMSO.S312334.

Graber, C.D. et al.: Immunomodulating properties of dimethylglycine in humans (1981) The Journal of Infectious Diseases | https://doi.org/10.1093/infdis/143.1.101.

Huang, J. et al.: Abstract 2273: Serum choline, methionine, betaine, dimethylglycine, and trimethylamine-N-oxide in relation to pancreatic cancer risk in two nested case-control studies in Asian populations (2017) Cancer Research | https://doi.org/10.1158/1538-7445.AM2017-2273.

Jianyong, Z. et al.: Rapid discrimination of human oesophageal squamous cell carcinoma by mass spectrometry based on differences in amino acid metabolism (2017) Scientific Reports | https://doi.org/10.1038/s41598-017-03375-8.

Kern, J.K. et al.: Effectiveness of N,N-dimethylglycine in autism and pervasive developmental disorder (2001) Journal of child neurology | https://doi.org/10.1177/088307380101600303.

Ladep, N.G. et al.: Discovery and validation of urinary metabotypes for the diagnosis of hepatocellular carcinoma in West Africans (2014) Hepatology | https://doi.org/10.1002/hep.27264.

Lever, M. et al.: Betaine and secondary events in an acute coronary syndrome cohort (2012) PLOS ONE | https://doi.org/10.1371/journal.pone.0037883.

Lin, Y. et al.: NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in patients with colorectal cancer (2016) Oncotarget | https://doi.org/10.18632/oncotarget.8762.

Liu, F.-T. et al.: Endometrial microbiota-dimethylglycine-Treg cell axis affects endometrial receptivity in recurrent implantation failure (2026) Science China. Life sciences | https://doi.org/10.1007/s11427-025-3138-x.

Liu, Y. et al.: Changes in Isoleucine, Sarcosine, and Dimethylglycine During OGTT as Risk Factors for Diabetes (2024) The Journal of Clinical Endocrinology & Metabolism | https://doi.org/10.1210/clinem/dgae018.

Magnusson, M. et al.: Dimethylglycine Deficiency and the Development of Diabetes (2015) Diabetes | https://doi.org/10.2337/db14-1863.

McAndrew, R.P. et al.: Molecular basis of dimethylglycine dehydrogenase deficiency associated with pathogenic variant H109R (2008) Journal of inherited metabolic disease | https://doi.org/10.1007/s10545-008-0999-2.

McGregor, D.O. et al.: Dimethylglycine accumulates in uremia and predicts elevated plasma homocysteine concentrations (2001) Kidney International | https://doi.org/10.1046/j.1523-1755.2001.00743.x.

Nitter, M. et al.: Plasma methionine, choline, betaine, and dimethylglycine in relation to colorectal cancer risk in the European Prospective Investigation into Cancer and Nutrition (EPIC) (2014) Annals of oncology : official journal of the European Society for Medical Oncology | https://doi.org/10.1093/annonc/mdu185.

Pacana, T. et al.: Dysregulated Hepatic Methionine Metabolism Drives Homocysteine Elevation in Diet-Induced Nonalcoholic Fatty Liver Disease (2015) PLOS ONE | https://doi.org/10.1371/journal.pone.0136822.

Reap, E.A. et al.: Stimulation of the immune response by dimethylglycine, a nontoxic metabolite (1990) The Journal of laboratory and clinical medicine | PMID: 1691258.

Shahril Agus, S.A. et al.: Effect of N, N-Dimethylglycine (DMG) Supplementation on Haematological Parameters and Frequency of CD4+ and CD8+ T Cells in Cats Post-vaccination (2025) Pertanika Journal of Tropical Agricultural Science | https://doi.org/10.47836/pjtas.48.3.12.

Svingen, G.F.T. et al.: Plasma dimethylglycine and risk of incident acute myocardial infarction in patients with stable angina pectoris (2013) Arteriosclerosis, thrombosis, and vascular biology | https://doi.org/10.1161/ATVBAHA.113.301714.

Svingen, G.F.T. et al.: Elevated plasma dimethylglycine is a risk marker of mortality in patients with coronary heart disease (2015) European Journal of Preventive Cardiology | https://doi.org/10.1177/2047487314529351.

Wang, Z. et al.: Heat stress-induced intestinal barrier damage and dimethylglycine alleviates via improving the metabolism function of microbiota gut brain axis (2022) Ecotoxicology and Environmental Safety | https://doi.org/10.1016/j.ecoenv.2022.114053.

Wolfsegger, T. et al.: N,N-Dimethylglycine in patients with progressive multiple sclerosis: result of a pilot double-blind, placebo, controlled randomized clinical trial (2021) Neurological research and practice | https://doi.org/10.1186/s42466-021-00126-z.

Xie, B. et al.: Identification of serum N,N-dimethylglycine as a potential biomarker for prenatal diagnosis of congenital heart disease using 1HNMR and UPLC-MS/MS metabonomics (2025) Analytical and Bioanalytical Chemistry | https://doi.org/10.1007/s00216-025-06084-8.

Yao, H. et al.: Effects of dietary dimethylglycine supplementation on laying performance, egg quality, and tissue index of hens during late laying period (2022) Poultry Science | https://doi.org/10.1016/j.psj.2021.101610.

Zhang, H. et al.: The association of serum dimethylglycine with the risk of cancer (2023) | https://doi.org/10.21203/rs.3.rs-3371052/v1.

• History & Evolution
• Biosynthesis & dietary uptake
• Fructose and the microbiome
• Fructose and cardiometabolism
• Fructose and neurology
• Fructose and oncology
• Fructose and 5P medicine
• References

History & Evolution

1847: isolation | 1880s: stereochemistry | 1956: clinics | 1970s: industry | 2004: health concerns

Fructose entered the world of chemistry in 1847, when Augustin Pierre Dubrunfaut isolated it from sucrose (Rödel 1974). For decades it was also called levulose because its solution rotates plane polarized light to the left. In the 1880s-1890s, Emil Fischer revolutionized carbohydrate science by mapping relationships among glucose, fructose, and mannose and introducing Fischer projections, which fixed the stereochemical language we still use (Horton 2013). A clinical turn came in 1956-1963, when physicians characterized hereditary fructose intolerance (HFI), a recessive disorder of aldolase B, and explained the syndrome’s biochemistry (Chambers et al. 1956). The role of fructose in the food industry became prominent in the early 1970s after work on glucose isomerase brought about commercial high fructose corn syrup (HFCS) (Horton 2013). In 2004, after decades of increasing intake of HFCS sweetened beverages, their link with U.S. obesity trends was brought to light (Bray et al. 2004), catalyzing an enduring debate about the ethics of adding fructose and other sweeteners to our foods.

When it does make it into our plates and glasses, fructose has advantageous properties compared to glucose: it is generally ~1.2 to 1.7 times sweeter than sucrose (Fontvieille et al. 1989), thus requiring less fructose for the same sensation. However, this advantage is most pronounced in cold matrices. Classic psychophysical work shows fructose’s relative sweetness climbs at low temperatures and drops when heated (Green et al. 2015). The mechanistic study of the fate of fructose in the body further added fuel to the polemic, with the discovery that fructose is a substrate for hepatic lipogenesis.

Biosynthesis vs. dietary uptake

Fructose is a naturally occurring monosaccharide that can be produced endogenously in humans via the polyol pathway, where glucose is converted to sorbitol and then to fructose (Delannoy et al. 2025). In diet, fructose is abundant in fruits, honey, and some vegetables and is specifically present in processed foods as part of sucrose or in the form of HFCS (Flores Monar et al. 2025).
After ingestion, fructose is absorbed in the small intestine primarily via facilitated diffusion through the GLUT5 transporter located on the apical membrane of enterocytes (Taylor et al. 2021). Once inside the enterocyte, fructose is transported across the basolateral membrane into the portal circulation by GLUT2 (Jung et al. 2022). From the portal vein, fructose is delivered mainly to the liver, which serves as the central site of fructose metabolism.

Within the liver, fructose undergoes rapid phosphorylation by ketohexokinase (KHK) to form fructose-1-phosphate (F1P) (Flores Monar et al. 2025; Jung et al. 2022). Consequently, fructose-1-phosphate is cleaved by aldolase B into dihydroxyacetone phosphate (DHAP) and glyceraldehyde, intermediates which enter glycolysis or gluconeogenesis. A substantial fraction of these metabolites is directed toward de novo lipogenesis, contributing to triglyceride synthesis. A low flux of intermediates is directed towards the hexosamine biosynthetic pathway, supporting the formation of sugar nucleotides required for proper protein glycosylation. This essential regulatory process controls protein folding, receptor signaling and immune function (Paneque et al. 2023).

Unlike glucose, fructose metabolism does not stimulate insulin secretion or leptin production, which has implications for energy homeostasis and lipid accumulation (Taylor et al. 2021; Flores Monar et al. 2025). Under normal physiological conditions, almost all absorbed fructose is processed during first-pass metabolism, so urinary excretion is negligible (Macdonald et al. 1978; Jung et al. 2022). However, in cases of fructose malabsorption or hereditary fructose intolerance, unmetabolized fructose may appear in urine and cause gastrointestinal symptoms (Simões et al. 2025; Febbraio et al. 2021).

Fructose and the microbiome

When the small intestine’s first-pass capacity to absorb fructose is exceeded, particularly with high loads of free fructose from HFCS-sweetened foods and beverages, unabsorbed fructose reaches the distal gut and becomes directly available to the microbiota (Jung et al. 2022; Febbraio et al. 2021). Chronic high free-fructose intake shifts microbial communities toward simple-sugar-degrading bacteria and away from key fiber-degrading taxa (Simões et al. 2025). By contrast, fructose in whole fruits is delivered within a fiber-rich matrix that slows its arrival in the distal gut and supports saccharolytic commensal bacteria (Simões et al. 2025; Febbraio et al. 2021). Microbial fermentation of unabsorbed fructose generates gases typical of malabsorption and produces short-chain fatty acids (SCFAs) (Febbraio et al. 2021; Simões et al. 2025). Among SCFAs, acetate is particularly relevant because it enters the portal circulation and serves as a substrate for hepatic acetyl-CoA, thereby fueling de novo lipogenesis and linking microbial activity to liver fat accumulation.

In contrast, butyrate generally exerts anti-inflammatory and barrier-supporting effects in the colon. High-fructose diets also shift microbial metabolism toward cardiometabolic risk-associated metabolites such as trimethylamine N-oxide (TMAO) in mice (Jung et al. 2022).
In the same luminal environment, unabsorbed fructose can non-enzymatically be combined to dietary peptides and incretins through fructosylation. These fructose-derived advanced glycation end products (FruAGE) activate receptors for advanced glycation end products (RAGE) and amplify inflammatory signaling locally and systemically (DeChristopher 2024). As dysbiosis progresses, SCFA imbalance and microbial activity reduce gut barrier integrity, leading to a “leaky gut” with increased permeability. Translocated lipopolysaccharide (LPS) and other microbial components then reach the liver, activate toll-like receptor (TLR) 4 on Kupffer cells, trigger tumor-necrosis factor (TNF)-driven inflammatory cascades, and propagate hepatic injury and metabolic dysfunction (Febbraio et al. 2021; Simões et al. 2025). Together, these processes link chronic high fructose exposure, microbial dysbiosis, impaired barrier function, and immune activation to a broad spectrum of metabolic and inflammatory diseases across the gut-organ axis.

Fructose and cardiometabolism

Over the past four decades, HFCS in processed foods and beverages has markedly increased dietary fructose exposure beyond normal physiological handling. This change parallels rising rates of obesity, type 2 diabetes, metabolic dysfunction-associated steatotic liver disease (MASLD) and cardiovascular disease, implicating industrial sweeteners as important contributors to cardiometabolic risk (Febbraio et al. 2021; DeChristopher 2024; Jung et al. 2022). Unlike fructose in whole fruits and honey, HFCS provides large amounts of free fructose in liquid form, bypassing the fiber matrix that normally slows absorption (Flores Monar et al. 2025; Jung et al. 2022). When intake is high, small-intestinal first-pass clearance saturates and excess fructose reaches the liver in substantial amounts (Jung et al. 2022; Febbraio et al. 2021).
In the liver, KHK-driven fructose phosphorylation bypasses phosphofructokinase and rapidly generates fructose-1-phosphate. This unregulated flux promotes lipogenesis while depleting adenosine-triphosphate (ATP) and trapping inorganic phosphate, activating adenosine-monophosphate (AMP) deaminase (AMPD) and increasing uric acid production. Elevated uric acid together with reactive oxygen species has been shown to promote endothelial dysfunction, inflammation and a pro-steatotic, pro-inflammatory hepatic milieu in animal models (Febbraio et al. 2021; Jung et al. 2022; Flores Monar et al. 2025). At the same time, fructose weakly stimulates insulin and satiety hormones such as glucagon-like peptide (GLP)-1, lessening satiation and fostering increased energy intake and positive energy balance (Flores Monar et al. 2025).

These mechanisms collectively drive hepatic steatosis, dyslipidemia and insulin resistance, core features of metabolic syndrome (DeChristopher 2024; Febbraio et al. 2021). Epidemiological data further link chronic high-fructose intake to hypertension, hyperuricemia and elevated cardiovascular risk independently of body mass index (Febbraio et al. 2021; Jung et al. 2022; DeChristopher 2024). Although the relative contribution of HFCS versus sucrose remains debated (Feinman et al. 2013) decades of excessive fructose consumption, particularly from sugar-sweetened beverages, represent a key factor in the growing burden of cardiometabolic disease (DeChristopher 2024; Flores Monar et al. 2025; Jung et al. 2022).

Fructose and neurology

In the hypothalamus of mice, chronic fructose exposure alters energy sensing and shifts neuropeptide signaling toward orexigenic, or appetite-stimulating pathways, thus directly linking high-fructose intake to positive energy balance and the metabolic changes in humans described above (Payant et al. 2021). The developing brain is especially vulnerable: in mice, early-life high-fructose diets impair microglial phagocytic activity, and reduce clearance of synapses and apoptotic neurons disrupts circuit refinement, leading to lasting deficits in learning and emotional regulation (Zelenka 2025). In the mature rodent brain, the hippocampus emerges as a key target of fructose-induced injury, with early mitochondrial dysfunction, oxidative stress, neuroinflammation, and impaired neuronal insulin signaling. Some changes persist after dietary normalization and result in long-term memory impairment (Flores Monar et al. 2025; DeChristopher 2024).

Within this framework, Alzheimer’s disease (AD) has been hypothesized to be driven, at least in part, by overactivation of cerebral fructose metabolism, largely through endogenous fructose production via the polyol pathway. In neuronal models, fructose metabolism via KHK C causes energy depletion and uric acid generation, leading to mitochondrial oxidative stress, impaired mitophagy, reduced oxidative phosphorylation, cerebral glucose hypometabolism, and insulin resistance. Chronic energy failure promotes uric acid-driven neuroinflammation via NF-κB and TLR4 in rodents and humans (Shao et al. 2016). Disruption of plasticity-related pathways causes synaptic dysfunction in rodents. Amyloid/tau pathology might come secondary to oxidative stress and impaired protein repair also in humans. These processes might ultimately lead to neuronal dysfunction (Johnson et al. 2020).

High sugar and high-fructose intake, high glycemic load, excess salt, alcohol, obesity, diabetes, aging, and traumatic brain injury may all enhance endogenous fructose production by inducing aldose reductase and fructokinase in the brain. Consistently, the levels of sorbitol and fructose, as well as the activity of AMPD2 and production of ammonia are all increased in the brains of patients with AD. In both animal and human studies, high sugar intake was linked to cognitive decline, hippocampal inflammation, and reduced brain volume (Johnson et al. 2020; Flores Monar et al. 2025).

Fructose and oncology

High fructose intake has been associated with an increased risk of several cancers, with particularly strong epidemiological links to pancreatic cancer. Many tumor types overexpress the fructose transporter GLUT5, and elevated GLUT5 together with KHK expression indicates active fructose utilization by cancer cells (Jung et al. 2022; Febbraio et al. 2021). At the level of host tissues and the tumor microenvironment, fructose acts prominently along the gut-liver axis. Mouse models revealed that dietary fructose enhances epithelial cell survival and drives villus elongation in the intestine. The expanded absorptive surface area leads to increasing nutrient uptake and adiposity in the context of a Western diet (Taylor et al. 2021; Febbraio et al. 2021).
In the liver, fructose-induced fibrosis and inflammation promote an immunosuppressive milieu that weakens CD8⁺ T cell-mediated immunosurveillance and favors hepatocellular carcinoma development (Febbraio et al. 2021).

Fructose can also drive tumor growth through cell non-autonomous fructolysis in animal models: KHK-C-expressing hepatocytes convert fructose into circulating lysophosphatidylcholines (LPCs) that are taken up by cancer cells to support phosphatidylcholine synthesis and membrane biogenesis, with fructose supplementation enhancing tumor growth even without overt weight gain or insulin resistance (Fowle-Grider et al. 2024). In parallel, many cancers undergo intrinsic metabolic reprogramming to exploit fructose. Under glucose-poor, fructose-rich conditions, cancer cells can use fructose as an alternative carbon source to sustain central carbon metabolism, de novo lipid and nucleic acid synthesis, and the Warburg effect, with aberrant fructose utilization activating oncogenic mechanistic target of rapamycin complex (mTORC) 1 signaling and suppressing anti-tumor immunity (Ting 2024; Zhao et al. 2025). Different tumors deploy these pathways in distinct ways, for example, pancreatic cancer channels fructose primarily into nucleotide synthesis via the non-oxidative pentose phosphate pathway, whereas hepatocellular carcinoma may rely on acetate derived from microbial fructose metabolism. Inhibition of fructose metabolism in such fructose-adapted cancer cells reduces malignancy (Ting 2024).

Fructose and 5P medicine

High intake of HFCS over long periods is a major, yet modifiable, risk factor for metabolic, neurological, and oncological conditions (Febbraio et al. 2021; Jung et al. 2022; DeChristopher 2024). Because diet is a central driver, fructose is an instructive example of how individuals can participate in shaping their health. Fructose from whole fruits, delivered with fiber and antioxidants, shows neutral or beneficial effects on metabolic biomarkers, whereas fructose from sugar-sweetened beverages and juices correlates with higher inflammatory markers, dyslipidemia, and intrahepatic fat (DeChristopher 2024; Jung et al. 2022). Experimental data indicate that HFCS-like, fructose-rich sweeteners induce reward-related and metabolic disturbances at lower exposure than sucrose, suggesting stronger reinforcing and pathological effects when fructose/glucose ratios are very high (DeChristopher 2024; Levy et al. 2015). Nonetheless, the most robust strategy for obesity, diabetes, and metabolic syndrome remains a general reduction of total carbohydrate intake, not merely swapping fructose for glucose (Feinman et al. 2013).

When symptoms are present precision medicine gains importance. In inflammatory bowel disease and fructose malabsorption, several strategies improve gastrointestinal symptoms and breath hydrogen in clinical studies. These include fructose-restricted and low-FODMAP diets, microbiota-directed therapies (probiotics, fecal microbiota transplantation), and oral xylose isomerase, which converts fructose to glucose (Simões et al. 2025). Regarding the gut-liver axis, KHK inhibitors, which are tested in clinical trials, lower de novo lipogenesis and improve metabolic markers (Jung et al. 2022). Epidemiological data also suggests that targeting brain KHK C or AMPD2, together with uric acid-lowering strategies, could enable to reduce the risk of dementia in the population (Johnson et al. 2020).

References

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Chambers, R.A. et al.: Idiosyncrasy to fructose (1956) Lancet (London, England) | https://doi.org/10.1016/S0140-6736(56)92196-1.

DeChristopher, L.R.: 40 years of adding more fructose to high fructose corn syrup than is safe, through the lens of malabsorption and altered gut health-gateways to chronic disease (2024) Nutrition Journal | https://doi.org/10.1186/s12937-024-00919-3.

Delannoy, P. et al.: Aldose reductase, fructose and fat production in the liver (2025) Biochemical Journal | https://doi.org/10.1042/BCJ20240748.

Febbraio, M.A. et al.: “Sweet death”: Fructose as a metabolic toxin that targets the gut-liver axis (2021) Cell Metabolism | https://doi.org/10.1016/j.cmet.2021.09.004.

Feinman, R.D. et al.: Fructose in perspective (2013) Nutrition & Metabolism | https://doi.org/10.1186/1743-7075-10-45.

Flores Monar, G.V. et al.: Mindful Eating: A Deep Insight Into Fructose Metabolism and Its Effects on Appetite Regulation and Brain Function (2025) Journal of Nutrition and Metabolism | https://doi.org/10.1155/jnme/5571686.

Fontvieille, A.M. et al.: Relative sweetness of fructose compared with sucrose in healthy and diabetic subjects (1989) Diabetes care | https://doi.org/10.2337/diacare.12.7.481.

Fowle-Grider, R. et al.: Dietary fructose enhances tumour growth indirectly via interorgan lipid transfer (2024) Nature | https://doi.org/10.1038/s41586-024-08258-3.

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Macdonald, I. et al.: Some effects, in man, of varying the load of glucose, sucrose, fructose, or sorbitol on various metabolites in blood (1978) The American Journal of Clinical Nutrition | https://doi.org/10.1093/ajcn/31.8.1305.

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• Foreword
• How metabolomics is improving healthcare: 6 must-read studies from 2025
• Hepatology: functional detox capacity beyond fibrosis
• Cardiometabolic health: anticipating disease before symptoms
• Cohorts and mGWAS: from genetic signals to functional meaning
• Oncology: detecting cancer before its manifestation
• Neuropsychiatry and microbiome: modulating behavior through microbial metabolism
• Nanomedicine: designing safer therapies through metabolomics & lipidomics
• The next steps for metabolomics in 5P medicine

Foreword by Alice Limonciel, Chief Scientific Officer at biocrates

After decades of development, we are on the cusp of integrating metabolomics into medical practice. Numerous examples already exist in clinical settings, the result of the dedicated labor of passionate scientists and clinicians who recognized the potential of this omic and applied it across all areas of medicine. However, the broad adoption of metabolomics on a scale comparable to what we now see with genomics requires the development of robust, transferable, and scalable technology, which has been the mission of biocrates for the past 20 years.

In 2025, we chose to showcase the wide-ranging potential of metabolomics for all aspects of 5P medicine, from preventing chronic disease in a single individual through personalized strategies to enabling multiomic analyses in large cohort studies.

For this article, Franziska Hörburger selected six studies published in 2025 by biocrates’ community of users. These examples pave the way for the imminent implementation of metabolomics beyond the research lab and into clinical practice and our everyday lives. They span multiple regions, therapeutic areas, and dimensions of the future implementation of metabolomics in medicine and drug development.
These scientists are part of a community of early adopters of metabolomics, a technology that will transform how we understand and practice medicine. May this article inspire you and your team to join this community in 2026!

How metabolomics is improving healthcare: 6 must read studies from 2025

5P medicine – preventive, predictive, precision, population-based, and participatory – represents a paradigm shift in healthcare. It moves away from reactive treatment toward proactive, patient-centric strategies built on molecular insights. At its core, 5P medicine leverages high-quality standardized technologies to capture biology in unprecedented detail. It enables clinicians and researchers to predict disease risk, personalize interventions, while engaging patients in their individual health journey and at the population scale.

Among the molecular technologies shaping modern medicine, metabolomics stands out. While genomics can predict disease risk, it offers only a static view, like a snapshot of predisposition. Metabolomics, in contrast, captures the biochemical fingerprints of life, reflecting the dynamic interplay of genes, environment, lifestyle, microbiome, and pharmacological influences. This real-time perspective makes metabolomics indispensable for understanding complex chronic diseases, where genetic information alone cannot explain onset, progression, or therapeutic response.

Figure 1: Molecular health beyond genetic predisposition

When metabolomics is combined with other omics technologies, such as genomics or proteomics, the picture becomes even richer. Proteomics adds information about enzyme abundance and signaling networks, complementing metabolomics’ readout of pathway activity and flux. Together, these layers create a detailed system-level view of health and pathology, connecting genetic predisposition to molecular function and clinical phenotype. This integrated approach transforms omics from isolated data streams into actionable insights, connecting molecular complexity and medical decision-making based on the 5P concept.

Applying metabolomics within the 5P framework can be summarized in three steps. First, screen samples using broad metabolomics and lipidomics profiling. Second, leverage data to uncover biological meaning. This involves interpreting metabolite patterns, sums, and ratios, and linking them to pathways and literature. Third, translate insights into solutions: providing predictive biomarkers, metabotypes, risk scores, and decision-support tools that transform medicine from reactive to proactive.

Figure 2: Workflow for applying metabolomics in the 5P framework

This vision is not theoretical; it is already happening. Across biological matrices, continents and disciplines, researchers and clinicians are using biocrates’ technology to deliver actionable insights in fields as varied as hepatology, oncology, neuropsychiatry, cardiometabolic health, population studies, and nanomedicine.

Here we review six publications from 2025 in high-impact journals that illustrate how one standardized platform can drive breakthroughs aligned with the principles of 5P medicine.

Hepatology: functional detox capacity beyond fibrosis

Sugimoto et al.: Hepatic stellate cells control liver zonation, size and functions via R-spondin 3. Nature (2025), 640(8059):752–761 | https://doi.org/10.1038/s41586-025-08677-w Figure under creative commons license CC BY 4.0.

Sugimoto and colleagues uncovered how hepatic stellate cells orchestrate liver zonation and detoxification through the signaling molecule R-spondin 3 (RSPO3), a key regulator of the WNT pathway. When RSPO3 is lost, hepatocyte zonation collapses and regenerative capacity declines. Beyond structural changes, RSPO3 profoundly influences detoxification by modulating cytochrome P450 activity, which in turn alters circulating metabolite profiles. Liver tissue of RSPO3-deficient mice featured striking shifts in bile acid composition, particularly taurocholic, tauromuricholic, and taurochenodeoxycholic acids.

Furthermore, changes in steroid metabolism, lipid oxidation, and xenobiotic accumulation have been revealed. These metabolomic signatures predict functional liver capacity, drug metabolism potential, and ultimately toxicity risk. By identifying RSPO3 as both a prognostic and mechanistic marker, this work opens the door to early intervention, personalized risk stratification, and tailored therapeutic approaches for liver fibrosis, particularly in alcoholic liver disease and metabolic dysfunction associated liver disease.

Cardiometabolic health: anticipating disease before symptoms

Zieleniewska et al.: Preclinical Atherosclerosis and Prediabetes: A Cross-Sectional Metabolic Assessment In Apparently Healthy Population. Cardiovascular Diabetology (2025), 24(1), 280 | https://doi.org/10.1186/s12933-025-02841-2 Figure under creative commons license CC BY-NC-ND 4.0.

Cardiovascular disease and diabetes often develop silently over years, making early detection critical. The metabolic foundation of preclinical atherosclerosis compared to prediabetes was explored in 447 participants from the Bialystok PLUS cohort.

The analysis uncovered distinct and shared metabolic signatures in plasma for both conditions. Prediabetes exerted a broader impact on amino acid metabolism, lipid signaling and enzymatic activities than atherosclerosis. Glutamic acid, lactic acid, and alanine were strongly associated with prediabetes, indicating dysglycemia. Atherosclerosis was linked to lipid remodeling patterns captured by MetaboINDICATORs, including the ratio of polyunsaturated (PUFA)-lysophosphatidylcholines versus saturated fatty acids, the sum of steroid hormones, and cholesteryl ester (CE) classes such as monounsaturated CEs and long-chain fatty acids CEs. Trimethylamine N-oxide (TMAO) emerged as a unique link between prediabetes and its interaction with vascular pathology. At the same time, glutaminase activity, assessed through the glutamate/glutamine ratio, stood out as a robust shared predictor of both conditions. Metabolite set enrichment analysis observed converging disturbances in glutathione and folate metabolism, mitochondrial function, redox regulation and inflammation.

Cohorts and mGWAS: from genetic signals to functional meaning

Kodate et al.: Simulating metabolic pathways to enhance interpretations of metabolome genome-wide association studies. Scientific Reports (2025), 15(1), 17035 | https://doi.org/10.1038/s41598-025-01634-7 Figure under creative commons license CC BY-NC-ND 4.0.

Metabolome-genome-wide association studies (mGWAS) link genetic variation to metabolite concentrations in large cohorts. It provides great predictive power of risk models and enables rational intervention based on individual metabolic architecture. However, this powerful approach has some limitations: observed associations may reflect indirect effects through unmeasured metabolites, and the biological significance of many variants remains uncertain. To overcome these challenges, Kodate and colleagues combined mGWAS with mechanistic metabolic simulations, creating a framework that moves beyond correlation to causation.

By systematically adjusting enzyme reaction rates to mimic genetic variants, the team simulated their impact on plasma metabolite levels and validated most variant-metabolite pairs identified by mGWAS. For example, homocysteine was confirmed as a metabolite strongly influenced by methylenetetrahydrofolate reductase (MTHFR) activity. Both mGWAS and simulation agreed that reduced MTHFR activity increases homocysteine levels, reinforcing its role in folate and methionine metabolism. These simulations also revealed additional fluctuations that mGWAS had missed, suggesting that some associations could gain significance with larger sample sizes. Importantly, the study categorized enzymes into three tiers based on their influence on metabolite concentrations, highlighting variants with minimal biological impact and prioritizing those with strong functional relevance. This distinction is critical for guiding preventive strategies and therapeutic development.

Oncology: detecting cancer before its manifestation

Schulze et al.: Metabolomic liquid biopsy dynamics predict early-stage HCC and actionable candidates of human hepatocarcinogenesis. JHEP Reports (2025), 7(5):101340 | https://doi.org/10.1016/j.jhepr.2025.101340. Figure under creative commons license CC BY 4.0.

Hepatocellular carcinoma (HCC) develops through progressive metabolic reprogramming that begins long before tumors become radiologically or clinically detectable. In a global cohort of 654 patients, serum metabolome profiling captured these early, system-level alterations and predicted malignant transformation before overt tumor manifestation.

Across chronic liver disease, cirrhosis, initial HCC, and advanced HCC, amino acid-, lipid-, and nucleotide-related pathways were systematically deregulated, with aspartic acid, glutamic acid, taurine, and hypoxanthine emerging as key markers. In a phase II biomarker case-control study, a blood-based metabolite signature achieved an area under the curve (AUC) of 94% for distinguishing early-stage HCC from cirrhotic controls, with independent validation in an external cohort. Multiomics integration links these circulating markers to enzymatic nodes such as RRM2, GMPS, and BCAT1 – targets for precision oncology. By providing a validated, minimal-invasive liquid biopsy that outperforms current surveillance tools, serum metabolomics enables predictive identification of cancer risk, chemoprevention strategies, and personalized monitoring.

Neuropsychiatry and microbiome: modulating behavior through microbial metabolism

Park et al.: Gut microbiota and brain-resident CD4+ T cells shape behavioral outcomes in autism spectrum disorder. Nature Communications (2025), 16(1), 1–17 | https://doi.org/10.1038/s41467-025-61544-0 Figure under creative commons license CC BY 4.0.

Autism spectrum disorder (ASD) emerges from complex interactions between neurodevelopment, immune regulation, and the gut microbiome. Metabolites serve as critical messengers of this gut-immune-brain axis, influencing neuroinflammation and neurotransmitter flux. In a recent study, the absence of gut microbiota in male mice ameliorated ASD-associated behaviors and reduced inflammatory brain-resident CD4⁺ T cells, while depletion of these T cells further mitigated neuroinflammation and behavioral abnormalities. Fecal metabolomics in a mouse model of ASD revealed several microbial and metabolic regulators of ASD, particularly those affecting the glutamate/gamma-amino-butyric acid (GABA) ratio and neurotoxic intermediates such as 3-hydroxyglutaric acid.

While GABA levels remained stable, the glutamate/GABA ratio was significantly elevated in ASD mice treated with a broad-spectrum antibiotic cocktail (vancomycin, neomycin, metronidazole), a group that also showed enrichment of Lactobacillus species compared to neurotypical controls. Strikingly, beneficial microbiota, derived from healthy mice or administered as probiotics, reversed this imbalance. These findings underscore how metabolites from live bacteria can drive or mitigate ASD-like behaviors by altering excitatory/inhibitory signaling and immune tone. Ultimately, the study demonstrates that gut microbiota can override genetic predisposition in ASD, highlighting a powerful opportunity for metabolomics-informed interventions that rebalance neuroactive metabolites, suppress neuroinflammation, and improve behavioral outcomes.

Nanomedicine: designing safer therapies through metabolomics & lipidomics

Shaw et al.: Inflammatory disease progression shapes nanoparticle biomolecular corona-mediated immune activation profiles. Nature Communications (2025),16(1), 924 | https://doi.org/10.1038/s41467-025-56210-4 Figure under creative commons license CC BY 4.0.

Polymeric nanoparticles (NPs) are engineered to carry, protect, and deliver bioactive molecules or modulate biological responses. Their biological identity, the biomolecular corona, is not fixed by formulation alone but is dynamically shaped by the host environment. Multiomics analysis showed that, during acute systemic inflammation, plasma proteins, lipids, and metabolites change profoundly.

As a result, nanoparticle coronas are reshaped. They feature elevated levels of clotting factors, inflammatory proteins, cytoskeletal components, and lipids such as phosphatidylcholines, sphingomyelins, lysophosphatidylcholines, and fatty acids. These molecular signatures reflect heightened inflammatory activity and trigger immune pathways like TLR4/MyD88/NF-κB. This activation leads to the release of pro-inflammatory cytokines, including TNFα and IL-6. Together, these findings show how metabolic variability determines nanoparticle-based therapeutic efficacy and toxicity risk. The concept of a “personalized biomolecular corona” underscores the need to design nanomedicines that account for patient-specific metabolic states. Incorporating metabolomic profiling into nanoparticle development helps anticipate immune responses, optimize timing, and improve safety.

The next steps for metabolomics in 5P medicine

What unites these global studies performed in various species and matrices beyond their drive to bring medicine to a higher level, is their use of the metabolomics kit technology developed by biocrates.
Across a wide range of applications, our standardized kits provide the reproducible and quality-controlled methods that enable multiomics integration, cohort comparability, and regulatory-compliant workflows.

While 2025 saw the broad application of our MxP® Quant 500 and MxP® Quant 500 XL kits, 2026 will be the year of the MxP® Quant 1000 kit. Our broadest panel to date, this kit expands quantitative analysis to up to 1,233 metabolites from 49 biochemical classes, showing coverage comparable to untargeted metabolomics approaches, yet with the reproducibility and sensitivity of a targeted workflow.

To follow our next steps, make sure to register for our monthly newsletter.

For additional insights also explore a curated selection of 2025 publications from our Biognosys Group partners, Biognosys and PreOmics.

• History & Evolution
• Biosynthesis & dietary uptake
• p-cresol glucuronide and nephrology
• p-cresol glucuronide and cardiometabolic disease
• p-cresol glucuronide and neurology
• p-cresol glucuronide and cancer
• p-cresol glucuronide and 5P medicine
• References

History & Evolution

Early 1990s: first studies on p-cresol

p-cresol glucuronide is a modified form of the gut-microbial metabolite p-cresol, synthesized in the liver to promote excretion through the urine. p-cresol is derived from bacterial proteolytic fermentation of tyrosine (Diether et al. 2019). Early uremia research often (mis)attributed circulating toxicity to unconjugated p-cresol, but improved analytics overturned this view. The current paradigm is that gut-derived p-cresol is rapidly conjugated across the colonic mucosa and in the liver, yielding chiefly p-cresol sulfate (pCS) and a smaller pool of p-cresol glucuronide (pCG), with free p-cresol usually undetectable (Soulage et al. 2022). The notion of unconjugated p-cresol as a uremic toxin is a “historical artefact” (Soulage et al. 2022) arising from acid or heat deproteinization that hydrolyzed conjugates during sample preparation.

Because research centered on pCS, pCG received comparatively little attention. A practical reason is that authentic pCG only became readily available as a commercial reference standard in the late 2000s (Koppe et al. 2017), slowing targeted quantification and mechanistic work until vendors supplied it. Despite higher total concentrations of pCS, differing albumin affinities leave pCS and pCG with comparably sized free fractions in serum (Liabeuf et al. 2013). Over time, pCG has moved from an overlooked “detox conjugate” to a recognized and valuable measure linking microbiome and host health.

Biosynthesis vs. dietary uptake

There appears to be no significant dietary pCG intake. However, diet shapes pCG levels indirectly by modulating colonic proteolysis. More total protein and aromatic amino acids increase substrate load, while fiber (Salmean et al. 2015), resistant starch (Snelson et al. 2024), and certain prebiotics (Meijers et al. 2010) steer carbon toward short-chain fatty acids (SCFA) and away from tyrosine fermentation (Snelson et al. 2024).

In the gut, tyrosine is first converted to 4-hydroxyphenylacetic acid and then decarboxylated to p-cresol, after which p-cresol crosses the mucosa and enters the portal circulation. During first-pass metabolism in the colon and the liver, phase II enzymes rapidly conjugate p-cresol: sulfotransferases yield pCS (Rong et al. 2021; Stachulski et al. 2023) and UDP-glucuronosyltransferases (UGTs) yield pCG (Rong et al. 2020). In the bloodstream, renal organic anion transporters OAT1/3 take up pCG and pCS for tubular secretion, leading to excretion through the urine. When kidney function or transporter capacity is reduced, both conjugates accumulate systemically (Wu et al. 2017), supporting their classification as uremic toxins.

p-cresol glucuronide and nephrology

In nephrology, pCG is clinically relevant: as glomerular filtration and tubular secretory capacity fall, pCG accumulates in serum, reaching even higher levels in hemodialysis (Peters et al. 2023; Liabeuf et al. 2013). Accordingly, pCG is considered a microbiome-derived uremic toxin linking gut ecology with renal outcomes.

Chronic kidney disease (CKD) reduces gut microbial diversity and induces compositional shifts (Peters et al. 2023). In a prospective cohort, pCG associated with greater estimated glomerular filtration rate (eGFR) loss over six years, showing that higher pCG tracks kidney decline (Peters et al. 2023). Furthermore, total and free pCG in serum rise with CKD severity, and higher pCG predicts overall and cardiovascular mortality, with risk prediction similar to pCS (Liabeuf et al. 2013). Beyond reflecting burden, pCG can perturb proximal tubular phenotype, inducing epithelial–mesenchymal transition markers, transporter dysregulation, and cellular stress in human renal proximal tubular cells. Notably, pCS did not affect cellular stress in the same system (Mutsaers et al. 2015).

Together, these lines of evidence support ongoing evaluation of pCG as a diagnostic and prognostic biomarker across CKD stages (Choudhary et al. 2025).

p-cresol glucuronide and cardiometabolic disease

Compared with its sulfate counterpart and the parent phenol, pCG appears less cytotoxic across human kidney, liver, and blood cell models; a pattern consistent with glucuronidation serving primarily as detoxification (Zhu et al. 2021; Bertarini et al. 2025). Nevertheless, its cardiometabolic relevance remains unsettled, with context-dependent findings that do not point uniformly toward a role as toxin or detoxicant.

In a prospective analysis in CKD patients, the total p-cresol burden (pCS + pCG) in serum associated with mortality and cardiovascular disease (CVD). Importantly the conjugation pattern mattered: a lower pCS/pCG ratio, so a relative shift toward glucuronidation, was independently associated with higher risks of mortality and CVD (Poesen et al. 2016). At the same time, metabolic effects diverged between conjugates, since in mouse and cellular models, pCG did not induce insulin resistance, whereas pCS did (Koppe et al. 2017). In liver models, the parent compound p-cresol induced pronounced oxidative stress, glutathione depletion, and necrotic cell death. In contrast, pCG showed minimal cytotoxicity in hepatocytes and behaved as a detoxification product rather than a toxin, making it unlikely to mediate the hepatic toxic effects attributed to p-cresol (Zhu et al. 2021).

Diet–microbiome evidence links pCG to hypertension and diabetes biology. In diabetic mice, uremic toxins, including pCG, were elevated in plasma. Resistant starch supplementation lowered pCG, strengthened the intestinal barrier and dampened renal inflammation as indicated by fewer neutrophils and lower complement activation. Finally, resistant starch reduced albuminuria, supporting a renoprotective effect of pCG in diabetes (Snelson et al. 2024).

In humans, low fiber intake associated with higher circulating pCG and higher blood pressure. In a randomized trial, SCFA-enriched fiber reduced both plasma pCG and blood pressure, consistent with a microbiota-mediated shift toward reduced tyrosine fermentation (Xu et al. 2025).

p-cresol glucuronide and neurology

As a host–microbe co-metabolite, pCG sits on the gut–brain axis. Although glucuronides are often considered inert (Bertarini et al. 2025), converging evidence suggests that pCG can be biologically active at the cerebral endothelium. In mice, pCG strengthened blood–brain barrier (BBB) integrity and reshaped the whole-brain transcriptome (Stachulski et al. 2023; Bertarini et al. 2025).

In human brain microvascular endothelial cells, pCG alone had little effect but prevented LPS-induced barrier permeability when co-applied, acting as a functional antagonist at toll-like receptor 4 (TLR4) (Stachulski et al. 2023). These findings support a context-dependent, neuroprotective role against pro-inflammatory stimuli under physiological conditions (Bertarini et al. 2025).

Population data are bidirectional: higher urinary p-cresol, pCS, and pCG have been reported in autistic children (Bertarini et al. 2025; Gabriele et al. 2014), whereas in children with CKD, pCG did not associate with neurological outcomes (Ebrahimi et al. 2025). In Parkinson’s disease cohorts, serum pCG was elevated alongside p-cresol and pCS in patients (Paul et al. 2023) and plasma pCG positively correlated with motor symptom severity (Chen et al. 2023). Evidences from Alzheimer’s disease (AD) research showed higher pCG levels in patients together with adverse brain aging and cognitive decline (Gordon et al. 2024).

p-cresol glucuronide and cancer

Metabolomics has contributed to placing pCG on the oncology map, not as a causal driver, but rather as a non-invasive urinary biomarker. In renal cell carcinoma, an independent validation cohort confirmed higher urinary pCG at diagnosis and still elevated one year post-nephrectomy (Oto et al. 2025). In colorectal cancer, urinary profiles of pCG across disease and recovery windows after surgery showed upregulation in disease stage 3-4 and downregulation in stage 0-2, suggesting stage-linked pCG variation (Fu et al. 2024; Liesenfeld et al. 2015). Similarly, a prospective study of bladder cancer (BC) patients validated urinary pCG as a diagnostic biomarker, and notably within non-muscle-invasive BC (NMIBC), as a staging biomarker (Oto et al. 2022).

p-cresol glucuronide and 5P medicine

Biomarkers predict treatment response, monitor progression, stratify risk, and enable precision care, serving several aims of 5P medicine. In blood, pCG levels rise with declining renal function and pCG has been suggested as diagnostic and prognostic marker across CKD stages (Choudhary et al. 2025).

Owing to its excretion fate, pCG is also a relevant marker in urine, a compelling non-invasive matrix for predictive and diagnostic applications in oncology (Liesenfeld et al. 2015; Oto et al. 2022). Urine reflects renal excretion, including short-term changes induced by diet or drugs, more rapidly than blood.

As a biomarker, pCG is also actionable. Diet and microbiome interventions, especially fermentable fibers/resistant starch, can lower circulating pCG levels (Snelson et al. 2024; Xu et al. 2025), supporting the preventive, predictive and participatory pillars of 5P medicine. Especially in combination with other uremic toxins like indoxyl sulfate or p-cresol sulfate , pCG can sharpen risk predictions, clarify mechanisms, and improve precision healthcare.

References

Bertarini, L. et al.: Para-Cresol and the Brain: Emerging Role in Neurodevelopmental and Neurodegenerative Disorders and Therapeutic Perspectives (2025) ACS pharmacology & translational science | https://doi.org/10.1021/acsptsci.5c00289.

Chen, S.-J. et al.: Plasma metabolites of aromatic amino acids associate with clinical severity and gut microbiota of Parkinson’s disease (2023) npj Parkinson’s Disease | https://doi.org/10.1038/s41531-023-00612-y.

Choudhary, B.B. et al.: Novel molecular biomarkers in kidney diseases: bridging the gap between early detection and clinical implementation (2025) Journal of Pharmacy and Pharmacology | https://doi.org/10.1093/jpp/rgaf096.

Diether, N.E. et al.: Microbial Fermentation of Dietary Protein: An Important Factor in Diet⁻Microbe⁻Host Interaction (2019) Microorganisms | https://doi.org/10.3390/microorganisms7010019.

Ebrahimi, M. et al.: Investigation of a targeted panel of gut microbiome-derived toxins in children with chronic kidney disease (2025) Pediatric Nephrology | https://doi.org/10.1007/s00467-024-06580-6.

Fu, C. et al.: The Potential of Metabolomics in Colorectal Cancer Prognosis (2024) Metabolites | https://doi.org/10.3390/metabo14120708.

Gabriele, S. et al.: Urinary p-cresol is elevated in young French children with autism spectrum disorder: a replication study (2014) Biomarkers | https://doi.org/10.3109/1354750X.2014.936911.

Gordon, S. et al.: Metabolites and MRI-Derived Markers of AD/ADRD Risk in a Puerto Rican Cohort (2024) Research square | https://doi.org/10.21203/rs.3.rs-3941791/v1.

Koppe, L. et al.: p-Cresyl glucuronide is a major metabolite of p-cresol in mouse: in contrast to p-cresyl sulphate, p-cresyl glucuronide fails to promote insulin resistance (2017) Nephrology Dialysis Transplantation | https://doi.org/10.1093/ndt/gfx089.

Liabeuf, S. et al.: Does p-cresylglucuronide have the same impact on mortality as other protein-bound uremic toxins? (2013) PLoS ONE | https://doi.org/10.1371/journal.pone.0067168.

Liesenfeld, D.B. et al.: Changes in urinary metabolic profiles of colorectal cancer patients enrolled in a prospective cohort study (ColoCare) (2015) Metabolomics | https://doi.org/10.1007/s11306-014-0758-3.

Meijers, B.K.I. et al.: p-Cresyl sulfate serum concentrations in haemodialysis patients are reduced by the prebiotic oligofructose-enriched inulin (2010) Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association – European Renal Association | https://doi.org/10.1093/ndt/gfp414.

Mutsaers, H.A.M. et al.: Proximal tubular efflux transporters involved in renal excretion of p-cresyl sulfate and p-cresyl glucuronide: Implications for chronic kidney disease pathophysiology (2015) Toxicology in vitro : an international journal published in association with BIBRA | https://doi.org/10.1016/j.tiv.2015.07.020.

Oto, J. et al.: LC-MS metabolomics of urine reveals distinct profiles for non-muscle-invasive and muscle-invasive bladder cancer (2022) World Journal of Urology | https://doi.org/10.1007/s00345-022-04136-7.

Oto, J. et al.: Validation of urine p-cresol glucuronide as renal cell carcinoma non-invasive biomarker (2025) Journal of Proteomics | https://doi.org/10.1016/j.jprot.2024.105357.

Paul, K.C. et al.: Untargeted serum metabolomics reveals novel metabolite associations and disruptions in amino acid and lipid metabolism in Parkinson’s disease (2023) Molecular Neurodegeneration | https://doi.org/10.1186/s13024-023-00694-5.

Peters, B.A. et al.: Association of the gut microbiome with kidney function and damage in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) (2023) Gut Microbes | https://doi.org/10.1080/19490976.2023.2186685.

Poesen, R. et al.: Metabolism, Protein Binding, and Renal Clearance of Microbiota-Derived p-Cresol in Patients with CKD (2016) Clinical journal of the American Society of Nephrology : CJASN | https://doi.org/10.2215/CJN.00160116.

Rong, Y. et al.: Characterizations of Human UDP-Glucuronosyltransferase Enzymes in the Conjugation of p-Cresol (2020) Toxicological Sciences | https://doi.org/10.1093/toxsci/kfaa072.

Rong, Y. et al.: Characterization of human sulfotransferases catalyzing the formation of p-cresol sulfate and identification of mefenamic acid as a potent metabolism inhibitor and potential therapeutic agent for detoxification (2021) Toxicology and applied pharmacology | https://doi.org/10.1016/j.taap.2021.115553.

Salmean, Y.A. et al.: Fiber supplementation lowers plasma p-cresol in chronic kidney disease patients (2015) Journal of renal nutrition : the official journal of the Council on Renal Nutrition of the National Kidney Foundation | https://doi.org/10.1053/j.jrn.2014.09.002.

Snelson, M. et al.: Dietary resistant starch enhances immune health of the kidney in diabetes via promoting microbially-derived metabolites and dampening neutrophil recruitment (2024) Nutrition & Diabetes | https://doi.org/10.1038/s41387-024-00305-2.

Soulage, C.O. et al.: The very last dance of unconjugated p-cresol… historical artefact of uraemic research (2022) Nephrology Dialysis Transplantation | https://doi.org/10.1093/ndt/gfab325.

Stachulski, A.V. et al.: A host-gut microbial amino acid co-metabolite, p-cresol glucuronide, promotes blood-brain barrier integrity in vivo (2023) Tissue Barriers | https://doi.org/10.1080/21688370.2022.2073175.

Wu, W. et al.: Key Role for the Organic Anion Transporters, OAT1 and OAT3, in the in vivo Handling of Uremic Toxins and Solutes (2017) Scientific Reports | https://doi.org/10.1038/s41598-017-04949-2.

Xu, C. et al.: Lack of dietary fibre increases gut microbiome-derived uremic toxins that contribute to increased blood pressure (2025) medRxiv | https://doi.org/10.1101/2025.09.16.25335853.

Zhu, S. et al.: Effects of p-Cresol on Oxidative Stress, Glutathione Depletion, and Necrosis in HepaRG Cells: Comparisons to Other Uremic Toxins and the Role of p-Cresol Glucuronide Formation (2021) Pharmaceutics | https://doi.org/10.3390/pharmaceutics13060857.

The International Conference on the Bioscience of Lipids (ICBL) 2025 in Innsbruck brought together leading researchers investigating lipid metabolism in health and disease. One session focused on peroxisomal lipid metabolism, emphasizing peroxisome biogenesis disorders (PBDs) and demonstrating how disruptions in peroxisomal lipid processing contribute to clinical phenotypes – and how lipidomics provides critical insights into these mechanisms.

Peroxisomes were first linked to human disease in 1973, when Dr. Sidney Goldfischer observed that kidney and liver tissue from Zellweger syndrome (ZS) patients lacked these organelles (Goldfischer et al. 1973). The first biomarker for peroxisomal disorders was identified over 40 years ago (Moser et al. 1984), and the first gene defect over 30 years ago (Shimozawa et al. 1992). Before their biochemical basis was understood, the main peroxisome biogenesis disorders (PBDs) – Zellweger spectrum syndrome (ZSS) and rhizomelic chondrodysplasia punctata (RCDP) – had already been described, representing the first malformation syndromes traced to metabolic errors (Steinberg et al. 2006).

Today, treatments remain largely supportive, targeting seizures, liver dysfunction, hearing, vision, and developmental needs. The recognition of milder, longer-living PBD patients has spurred renewed interest in experimental therapies, such as oral bile acid supplementation in ZS (Setchell et al. 1992), though plasmalogen precursor supplementation in RCDP has shown limited benefit (Steinberg et al. 2006; Das et al. 1992).

PEX genes in peroxisome biogenesis

Peroxisome formation begins in the endoplasmic reticulum (ER), which delivers lipids and membrane proteins to form ER-derived pre-peroxisomal vesicles. These vesicles fuse to create nascent peroxisomes, giving them a lipid composition similar to the ER, enriched in phosphatidylcholines (PCs) and phosphatidylethanolamines (PEs) but lacking cardiolipins (Mast et al. 2020). Fusion also assembles the peroxisomal translocon, enabling import of soluble matrix proteins from the cytosol, which are essential for peroxisomal functions like lipid metabolism and reactive oxygen species (ROS) regulation. Peroxisomes then undergo fission and segregation to maintain a stable cellular population (Tabak et al. 2013; Mast et al. 2020).

Proper formation depends on peroxins, encoded by PEX genes, which control all stages of biogenesis, from protein import to division and turnover. Mutations in PEX genes disrupt peroxisome assembly, causing PBDs such as ZSS, characterized by metabolic dysfunctions including impaired very long-chain fatty acid (VLCFA) metabolism (Mast et al. 2020).

The sentinels of the cell

Peroxisomes are essential organelles in the cell, often referred to as “sentinels” due to their crucial role in maintaining lipid homeostasis and protecting cells from oxidative stress. Each peroxisome contains more than 50 enzymes involved in various metabolic pathways, with a particular emphasis on lipid metabolism. One of their key functions is the β-oxidation of VLCFAs (≥C22) (Mast et al. 2020). These fatty acids, both saturated and unsaturated, are exclusively degraded in the peroxisome. This process is essential not only for the metabolism of VLCFAs but also for the synthesis of bile acids and the inactivation of compounds such as prostaglandins (Steinberg et al. 2006). The peroxisomal breakdown of fatty acids contributes to the generation of metabolic intermediates that are used in other biosynthetic pathways, ensuring efficient lipid metabolism throughout the cell.

In addition to fatty acid degradation, peroxisomes are vital for the synthesis of plasmalogens. The first two steps of this ether phospholipid biosynthesis occur exclusively within peroxisomes. Plasmalogens comprise a significant fraction of membrane phospholipids in mammalian cells. For example, 80-90% of the ethanolamine phospholipids in myelin are plasmalogens, playing a critical role in maintaining membrane fluidity and structural integrity. Plasmalogens are also involved in protecting cells from oxidative damage, like antioxidants, helping to neutralize ROS (Brosche et al. 1998; Steinberg et al. 2006). Beyond this, plasmalogens are essential for various cellular processes such as membrane fusion, ion transport, and cholesterol efflux, all of which are crucial for maintaining cellular health and function, particularly in the brain and nervous system (Steinberg et al. 2006; Farooqui et al. 2001).

Beyond lipid metabolism, peroxisomes are involved in a wide array of other metabolic processes, including amino acid metabolism, glyoxylate metabolism, and bile acid metabolism (Steinberg et al. 2006), which are all integral to the overall metabolic flexibility of the cell. The peroxisomal involvement in bile acid synthesis is essential for the digestion and absorption of dietary lipids, further highlighting the organelle’s pivotal role in lipid metabolism (Steinberg et al. 2006). Through the enzyme catalase, peroxisomes also play a critical role in metabolizing hydrogen peroxide (H₂O₂), a byproduct of various cellular processes. This detoxification is essential for protecting cells, particularly those with high metabolic activity, from oxidative stress (Okumoto et al. 2020).

Interestingly, peroxisomal ROS production and regulation also play a significant role in cell signaling. The redox status of the cell can regulate various signaling pathways, particularly those involved in immune responses, stress adaptation, and inflammation. For instance, peroxisomal ROS can modulate the activity of redox-sensitive transcription factors such as NF-κB , which governs the expression of genes involved in inflammation and immune response (Fransen et al. 2012). Thus, peroxisomes not only act as the cell’s “sentinels” by controlling ROS but also influence key signaling pathways that govern cellular stress responses.

The spectrum of PBDs

PBDs are a group of heterogeneous autosomal recessive disorders caused by defects in the assembly of peroxisomes linked to PEX genes, leading to multiple enzyme deficiencies and a range of metabolic dysfunctions. Among the 16 PEX genes, mutations in 14 have been identified as causing PBDs (Braverman et al. 2013), and there are 13 known complementation groups associated with defects in specific PEX genes (Steinberg et al. 2006). PBDs are categorized into two broad types: Zellweger syndrome spectrum and rhizomelic chondrodysplasia punctata (RCDP), with ZS being the most severe disorder (Braverman et al. 2013).

PBDs present with a wide spectrum of symptoms, ranging from severe developmental abnormalities to milder manifestations. Peroxisomes are ubiquitous in the body, hence ZS affects nearly every organ system, causing craniofacial abnormalities (Steinberg et al. 2006), neurological degeneration, and retinal degeneration, which often results in childhood blindness (Omri et al. 2025). Other conditions in the ZS spectrum include neonatal adrenoleukodystrophy and infantile Refsum disease, which exhibit intermediate phenotypes (Braverman et al. 2013). RCDP is characterized by skeletal dysplasia and growth retardation (Steinberg et al. 2006). The diversity of phenotypes highlights the complex nature of these disorders, which involve both lipid metabolism dysfunction and peroxisomal enzyme deficiencies.

The pathophysiology of ZS is largely due to defects in peroxisomal function, leading to disrupted lipid metabolism. Key issues include the accumulation of VLCFAs and plasmalogen deficiency, both of which are critical for maintaining membrane integrity and protecting cells from oxidative stress. In ZS, the brain accumulates VLCFAs and cholesterol esters. Additionally, the brain of ZS patients shows excessive polyunsaturated fatty acids (>C32), which are predominantly found in PCs . This accumulation of lipids plays a key role in pathogenesis, particularly in neuronal function and neurodegeneration (Steinberg et al. 2006). The depletion of plasmalogens further exacerbates membrane instability, leading to the functional decline of neurons and photoreceptors (Omri et al. 2025).

RCDP is caused by mutations in the PEX7 gene, coding for peroxin-7, which is crucial for the peroxisomal import of matrix proteins. Plasmalogen biosynthesis is impaired, leading to deficient plasmalogen levels in tissues such as the brain, liver, and muscle, while VLCFAs remain normal. The deficiency in plasmalogen synthesis is especially severe in RCDP and is linked to skeletal dysplasia (Steinberg et al. 2006; Bams-Mengerink et al. 2006).

The diagnostic approach for PBDs relies on measuring VLCFA levels and plasmalogen content, along with PEX gene sequencing to identify the specific mutations involved (Steinberg et al. 2006). Despite long-standing efforts, researchers are still busy unravelling the metabolic and cellular mechanisms underlying the clinical phenotypes.

The metabolic disruptions at the root of clinical symptoms

Understanding how genetic defects in PEX genes translate into metabolic disruptions is central to deciphering the clinical manifestations of PBDs. One of the most studied models is the PEX1-G844D knock-in mouse, which represents the common human PEX1-c.2528G>A allele (encoding PEX1-G843D). This model exhibits features of milder ZSS, including retinal degeneration (Hiebler et al. 2014).

In this model, one month after birth, PEX1-G844D retinal pigment epithelium (RPE) tissues already showed altered lipid composition, which can disrupt membrane fluidity and impair the function of membrane-bound proteins critical for nutrient transport, waste removal, and the visual cycle. A set of membrane-associated lipids was dysregulated, with PCs , phosphatidylinositols (PIs) and sphingomyelin (SM) species abnormally distributed between dorsal and ventral poles. Additionally, there was a significant increase in VLCFAs and a reduction in plasmalogens and docosahexaenoic acid (DHA)-containing lipids, highlighting disrupted peroxisomal lipid metabolism (Omri et al. 2025). These early lipid disturbances likely contribute to disrupted RPE membrane trafficking critical for photoreceptor support (Storm et al. 2020) and set the stage for progressive retinal degeneration.

Figure 2: Abundance and spatial distribution of membrane-associated lipids in WT or PEX1 mutant tissue at 1 month of age. Group 1: Lipids that are distributed heterogeneously in WT, with higher abundance at the ventral pole. Group 2: Lipids with altered lipid patterns in mutants compared to the WT and higher abundance in the dorsal pole. The lipid pattern of mutants is characterized by increased levels of VLCFAs along with decreased plasmalogens and DHA-associated lipids. At 3 months of age, tissue of mutants show structural aberrations, including membrane blebs and immune cell infiltration. The lipid pattern shown at 1 month of age is further intensified with an additional trend toward increasing PUFAs. Figure is based on findings from Omri et al. 2025.

By three months, structural abnormalities featured enlarged, disorganized RPE cells and plasma membrane blebbing, indicative of cellular stress (Martins et al. 2024). This was accompanied by subretinal inflammation, with infiltration of immune cells absent in control tissues. Spatial lipidomic analysis showed a trend toward increased polyunsaturated fatty acids, along with persistent decreases in DHA-containing lipids and further accumulation of VLCFAs. These findings suggest that early lipid remodeling precedes both inflammation and structural damage, potentially serving as a predictive marker of retinal degeneration. The initial accumulation of dysregulated lipids in the dorsal pole, followed by a more generalized spread, indicates that these lipid changes may initiate or drive the progression of tissue damage (Omri et al. 2025).

Building on these findings, unpublished data from PEX16-deficient mice presented at ICBL 2025 by Braverman and colleagues suggest a similar sequence of events. In these hypomorphic PEX16 models, mice exhibited reduced PEX16 transcript and protein and abnormal peroxisomal metabolites across multiple tissues. The earliest detectable changes were in lipid patterns, which were subsequently followed by structural alterations, mirroring the sequence observed in the retina of PEX1-G844D mice. In addition, there was increased infiltration of hematopoietic stem cells and early inflammatory responses in both brain and eyes, features not commonly seen in ZSD patients. Together, these findings support the notion that peroxisomal lipid dysregulation triggers oxidative stress and inflammation, which act as central drivers of clinical phenotypes, including neurodegeneration and retinal damage.

Using targeted lipidomics to decipher disease mechanisms

Targeted lipidomics using the biocrates MxP® Quant 1000 kit enables precise quantification of more than 40 free fatty acids and 906 complex lipids from 25 biochemical classes, assessing VLCFAs, plasmalogens, and DHA-containing lipids. With up to 325 lipid-based metabolite sums and ratios, this approach allows researchers to detect early lipid changes before structural damage occurs, map region-specific alterations, and correlate them with oxidative stress, inflammation, and cellular dysfunction. The kit also covers amino acid metabolism, glyoxylate metabolism, and bile acid metabolism, and is thus an excellent fit for holistic studies of metabolic effects of peroxisomal diseases. By providing reproducible, quantitative data, targeted lipidomics helps identifying biomarkers of disease progression, understanding mechanistic links between mutations and clinical phenotypes, and evaluating the impact of potential therapies in both preclinical models and patient samples.

References

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Braverman, N. E. et al.: Peroxisome biogenesis disorders: Biological, clinical and pathophysiological perspectives (2013) Develop mental Disabilities Research Reviews | https://doi.org/10.1002/ddrr.1113.

Brosche, T. et al.: The biological significance of plasmalogens in defense against oxidative damage (1998) Experimental Gerontology | https://doi.org/10.1016/s0531-5565(98)00014-x.

Das, A. K. et al.: Dietary ether lipid incorporation into tissue plasmalogens of humans and rodents (1992) Lipids | https://doi.org/10.1007/BF02536379.

Farooqui, A. A. et al.: Plasmalogens: workhorse lipids of membranes in normal and injured neurons and glia (2001) The Neuroscientist | https://doi.org/10.1177/107385840100700308.

Fransen, M. et al.: Role of peroxisomes in ROS/RNS-metabolism: implications for human disease (2012) Biochimica et biophysica acta | https://doi.org/10.1016/j.bbadis.2011.12.001.

Goldfischer, S. et al.: Peroxisomal and mitochondrial defects in the cerebro-hepato-renal syndrome (1973) Science (New York, N.Y.) | https://doi.org/10.1126/science.182.4107.62.

Hiebler, S. et al.: The Pex1-G844D mouse: a model for mild human Zellweger spectrum disorder (2014) Molecular genetics and metabolism | https://doi.org/10.1016/j.ymgme.2014.01.008.

Martins, B. et al.: Contribution of extracellular vesicles for the pathogenesis of retinal diseases: shedding light on blood-retinal barrier dysfunction (2024) Journal of biomedical science | https://doi.org/10.1186/s12929-024-01036-3.

Mast, F. D. et al.: Peroxisome prognostications: Exploring the birth, life, and death of an organelle (2020) Journal of Cell Biology | https://doi.org/10.1083/jcb.201912100.

Moser, A. E. et al.: The cerebrohepatorenal (Zellweger) syndrome. Increased levels and impaired degradation of very-long-chain fatty acids and their use in prenatal diagnosis (1984) The New England journal of medicine | https://doi.org/10.1056/NEJM198405033101802.

Okumoto, K. et al.: The peroxisome counteracts oxidative stresses by suppressing catalase import via Pex14 phosphorylation (2020) eLife | https://doi.org/10.7554/eLife.55896.

Omri, S. et al.: Spatial characterization of RPE structure and lipids in the PEX1-p.Gly844Asp mouse model for Zellweger spectrum disorder (2025) Journal of lipid research | https://doi.org/10.1016/j.jlr.2025.100771.

Setchell, K. D. et al.: Oral bile acid treatment and the patient with Zellweger syndrome (1992) Hepatology | https://doi.org/10.1002/hep.1840150206.

Shimozawa, N. et al.: A human gene responsible for Zellweger syndrome that affects peroxisome assembly (1992) Science (New York, N.Y.) | https://doi.org/10.1126/science.1546315.

Steinberg, S. J. et al.: Peroxisome biogenesis disorders (2006) Biochimica et biophysica acta | https://doi.org/10.1016/j.bbamcr.2006.09.010.

Storm, T. et al.: Membrane trafficking in the retinal pigment epithelium at a glance (2020) Journal of cell science | https://doi.org/10.1242/jcs.238279.

Tabak, H. F. et al.: Peroxisome formation and maintenance are dependent on the endoplasmic reticulum (2013) Annual Review of Biochemistry | https://doi.org/10.1146/annurev-biochem-081111-125123.

• History & Evolution
• Biosynthesis & dietary uptake
• cAMP and cell signaling
• cAMP and neurology
• cAMP and oncology
• cAMP and 5P medicine
• References

History & Evolution

1957 – 1958: discovery of role as second messenger | 1971: Nobel Prize

Earl Sutherland and colleagues identified cyclic adenosine monophosphate (cAMP) as a second messenger that relays hormone signals inside cells. This work earned Sutherland the Nobel Prize in Physiology or Medicine in 1971 (Kresge et al. 2005). Over the next decades, cAMP emerged as a universal signaling molecule, coordinating metabolism, gene expression, cardiac contractility, neurotransmission, and immune responses across tissues and species (Patra et al. 2023). Remarkably, cAMP levels can rise and fall within seconds, allowing cells to respond dynamically to external stimuli (Jiang et al. 2007). In humans, everyday substances like caffeine modulate cAMP signaling by subtly amplifying the molecule’s effects on alertness and metabolism (Barcelos et al. 2020). Its influence also extends beyond multicellular organisms: bacteria use cAMP to regulate their nutrient uptake (You et al. 2013), while in social amoebae such as Dictyostelium discoideum, cAMP acts as a “social molecule”, guiding collective movement and aggregation (Brimson et al. 2025).

Biosynthesis vs. dietary uptake

There is no indication that cAMP is absorbed from the diet. In contrast, cAMP is synthetized from ATP by adenylyl cyclase (AC), a plasma membrane-bound intracellular enzyme. The activity of AC is sensitive to numerous stimuli, including hormones and neurotransmitters, through the action of a G-protein-coupled receptor (GPCR), comprising several regulatory subunits; e.g. the stimulatory Gαs subunit, and the inhibitory Gαi subunit (Yadav et al. 2025). Activated AC converts adenosine triphosphate (ATP) into cAMP, which functions as a second messenger to drive downstream signaling. After the signal is transduced, cAMP signaling is terminated primarily by phosphodiesterases (PDE) that hydrolyze it to 5’-adenosine monophosphate (AMP), a form that lacks signaling activity (Patra et al. 2023). Although cAMP is primarily expected within cells, it is also quantifiable in blood, urine (Piec et al. 2017), saliva (Henkin et al. 2007) and cerebrospinal fluid (Oeckl et al. 2012).

cAMP and cell signalling

cAMP is a ubiquitous second messenger that translates extracellular cues into precise cellular actions. Its principal effector is protein kinase A (PKA): cAMP binding activates PKA, which phosphorylates serine/threonine residues on target proteins. A classic example is phosphorylation of the cAMP response element-binding protein (CREB), which regulates gene transcription (Patra et al. 2023). cAMP also engages exchange protein directly activated by cAMP (EPAC) (Rooij et al. 1998), influencing cell adhesion, cell-cell junctions, exocytosis/secretion, cell differentiation and proliferation, gene expression, apoptosis, and cardiac hypertrophy (Wang et al. 2017). Beyond enzymes, cAMP modulates ion flux by acting on cyclic nucleotide-gated (CNG) channels and hyperpolarization-activated cyclic nucleotide-gated (HCN) channels (Patra et al. 2023).

Because cAMP is used by many pathways, cells must control their signals in both time and space to preserve specificity. Spatial control comes from compartmentalization into multiprotein “signalosomes.” A-kinase anchoring proteins (AKAPs) tether PKA with selected effectors, phosphodiesterases (PDEs), and phosphatases to build microdomains or even smaller nanodomains at defined cellular sites. Within these domains, PKA phosphorylation activates nearby PDEs, which locally degrade cAMP and close a negative-feedback loop that terminates the signal (Yadav et al. 2025). Compartmentalization can be further reinforced by liquid-liquid phase separation (LLPS), the spontaneous condensation of biomolecules into reversible, membrane-less droplets. LLPS is governed by features such as intrinsically disordered regions and multivalency, by post-translational modifications, ligand/metabolite binding, local concentration, and the physicochemical environment (Folkmanaite et al. 2025). The quick assembly and disassembly of condensates at specific sites enables highly dynamic organization of signaling molecules. The spatial reach of a cAMP signal is ultimately set by phosphatase localization and activity, which define the functional boundary for PKA phosphorylation. Temporally, phosphatases reverse PKA phosphorylation to reset targets and limit the duration of cAMP effects (Conca et al. 2025).

cAMP and and oncology

The role of cAMP in cancer is intricate and often paradoxical. Its effects depend on genetic background, tumor type and stage, and microenvironmental influences. In many settings, increased cAMP-PKA/EPAC signaling promotes tumor growth, invasion, and therapy resistance (Zhang et al. 2024). Genetic alterations such as activating guanine nucleotide-binding protein alpha stimulating (GNAS) mutations or PKA fusion proteins (DNAJB1–PRKACA) drive persistent activation of this axis in gastrointestinal (Behmanesh et al. 2025) and liver cancers (Ahmed et al. 2022). PKA can regulate cytoskeletal dynamics (Howe 2004) and stress responses (Zhang et al. 2020). EPAC1 enhances adhesion, migration, glycolytic reprogramming, and metastasis in multiple cancer types. At the same time, EPAC activation has been shown to suppress migration in certain models (Zhang et al. 2024).

Downstream effector CREB integrates the signals at the transcriptional level and functions mainly as a tumor promoter (Ahmed et al. 2022). Its overexpression and hyperactivation are common in both solid and hematological malignancies, where it supports proliferation, angiogenesis, survival, and therapy resistance. High CREB activity is linked to poor prognosis and metastasis, and inhibition of CREB has been shown to reduce tumor growth and restore treatment sensitivity (Zhang et al. 2020).

The tumor microenvironment (TME) plays a decisive role in shaping cAMP responses. Low pH, a hallmark of the TME, stimulates proton-sensitive GPCRs that drive cAMP accumulation. Cancer-associated fibroblasts and immune cells can further modulate cAMP signaling through cytokine and growth factor release, while neuronal inputs via sympathetic and parasympathetic fibers add another regulatory layer. Together, these interactions promote angiogenesis, invasion, and immune evasion, including suppression of NK cell activity (Zhang et al. 2024).

cAMP and neurology

In the nervous system cAMP shapes how neurons grow, connect, and adapt. Boosting cAMP promotes neuronal survival and axon regrowth after spinal cord injury and shapes the activity of glial cells that support repair in the central nervous system (CNS) (Boczek et al. 2019; Zhou et al. 2022).

cAMP is also essential for synaptic plasticity and circuit excitability. Globally, it enhances presynaptic neurotransmitter release, while locally it adjusts inhibitory synapses, striking a balance that allows efficient encoding of learning and memory (Lee 2015). In astrocytes, cAMP triggers glycogen breakdown and the astrocyte-neuron lactate shuttle, fueling neurons during high demand. This lactate not only supports excitability and long-term potentiation but also feeds back to regulate noradrenaline release, linking metabolism and neuromodulation. Antidepressants and monoamines further elevate astrocytic cAMP, leading to CREB-driven production of neurotrophic factors which support plasticity, neuroprotection, and mood regulation. Importantly, the timing and duration of cAMP signals matter: acute bursts and chronic elevations can produce opposite effects on astrocytic functions (Zhou et al. 2019).

Disruptions in cAMP signaling are recognized as a common thread across neurodevelopmental and neurodegenerative disorders. Variants in PKA or PDE4D disrupt synaptic signaling and have been linked to autism, Fragile X syndrome, and Alzheimer’s disease (Bhattacharya et al. 2025). Even sleep loss lowers hippocampal cAMP and weakens memory. Promisingly, new PDE4D inhibitors are being developed to restore cAMP balance and improve cognition (Bhattacharya et al. 2025).

Beyond the nervous system itself, cAMP-PKA signaling is now emerging as a key mediator of gut-brain communication. Microbial metabolites can tune host cAMP activity, activating vagal pathways and modulating immune and endocrine responses. In turn, altered cAMP signaling feeds back on microbiota composition, creating a reciprocal network that influences neurodevelopment, neurotransmitter control, and behavioral traits. This bidirectional regulation has direct relevance for amyloid-β aggregation, mitochondrial function, and microglial activation (Deng et al. 2025).

cAMP in immunity and inflammation

In the immune system, cAMP regulates both innate and adaptive cell activities and serves as a central checkpoint in inflammation. Elevating cAMP signaling typically produces anti-inflammatory effects, while reduced cAMP activity favors immune activation. In phagocytes such as monocytes, macrophages, and neutrophils, cAMP dampens the release of pro-inflammatory cytokines and chemokines, restrains phagocytosis, and limits intracellular killing, thereby shaping the intensity of the inflammatory response (Raker et al. 2016).

cAMP is also a key mediator of resolution. It coordinates crosstalk with specialized pro-resolving mediators, regulates granulocyte recruitment, and fine-tunes apoptosis and clearance of dying cells. Importantly, cAMP drives macrophage polarization toward anti-inflammatory phenotypes, a hallmark of inflammation resolution (Tavares et al. 2020). When dysregulated, these processes contribute to chronic disease states; for instance, altered cAMP signaling influences both the onset and progression of ulcerative colitis (Cheng et al. 2024).

cAMP and 5P medicine

Modulation of cAMP pathways offers a powerful entry point for biomarker-driven interventions, directly aligning with the principles of 5P medicine. In oncology, expression of phosphodiesterase 4D (PDE4D) and corresponding protein abundance have been identified as a predictive biomarker of chemotherapy response in hypopharyngeal cancer, underscoring the value of cAMP turnover in treatment stratification (Kawata-Shimamura et al. 2022). In neurodevelopmental disease, the selective PDE4D inhibitor BPN14770 (zatolmilast) has shown clinical benefit in Fragile X syndrome (Berry-Kravis, Gurney 2020). Chronic inflammatory diseases also illustrate this principle: in chronic obstructive pulmonary disease, inhibition of PDE4 superfamily members is integrated into precision strategies where biomarker data guide treatment decisions in defined patient subgroups (Bolger 2023). Together, these findings highlight how targeting cAMP signaling can move beyond experimental insight toward practical applications in precision and personalized therapeutics.

References

Ahmed, M. B. et al.: cAMP Signaling in Cancer: A PKA-CREB and EPAC-Centric Approach (2022) Cells | https://doi.org/10.3390/cells11132020.

Barcelos, R. P. et al.: Caffeine effects on systemic metabolism, oxidative-inflammatory pathways, and exercise performance (2020) Nutrition research (New York, N.Y.) | https://doi.org/10.1016/j.nutres.2020.05.005.

Berry-Kravis et al.: Positive Results Reported in Phase II Fragile X Clinical Trial of PDE4D Inhibitor Zatolmilast from Tetra Therapeutics (2020) | https://www.fraxa.org/positive-results-reported-in-phase-ii-fragile-x-clinical-trial-of-pde4d-inhibitor-from-tetra-therapeutics/

Behmanesh, M. A. et al.: Unraveling the link between GNAS R201 mutation and colorectal cancer (2025) Scientific Reports | https://doi.org/10.1038/s41598-025-17399-y.

Bhattacharya, A. et al.: The promise of cyclic AMP modulation to restore cognitive function in neurodevelopmental disorders (2025) Current Opinion in Neurobiology | https://doi.org/10.1016/j.conb.2024.102966.

Boczek, T. et al.: Regulation of Neuronal Survival and Axon Growth by a Perinuclear cAMP Compartment (2019) Journal of Neuroscience | https://doi.org/10.1523/JNEUROSCI.2752-18.2019.

Bolger, G. B.: Therapeutic Targets and Precision Medicine in COPD: Inflammation, Ion Channels, Both, or Neither? (2023) International Journal of Molecular Sciences | https://doi.org/10.3390/ijms242417363.

Brimson, C. A. et al.: Collective oscillatory signaling in Dictyostelium discoideum acts as a developmental timer initiated by weak coupling of a noisy pulsatile signal (2025) Developmental cell | https://doi.org/10.1016/j.devcel.2024.11.016.

Cheng, H. et al.: Cyclic adenosine 3′, 5′-monophosphate (cAMP) signaling is a crucial therapeutic target for ulcerative colitis (2024) Life Sciences | https://doi.org/10.1016/j.lfs.2024.122901.

Conca, F. et al.: Phosphatases Control the Duration and Range of cAMP/PKA Microdomains (2025) Function (Oxford, England) | https://doi.org/10.1093/function/zqaf007.

Deng, F. et al.: Exploring the interaction between the gut microbiota and cyclic adenosine monophosphate-protein kinase A signaling pathway: a potential therapeutic approach for neurodegenerative diseases (2025) Neural Regeneration Research | https://doi.org/10.4103/NRR.NRR-D-24-00607.

Folkmanaite, M. et al.: Compartmentalisation in cAMP signalling: A phase separation perspective (2025) British Journal of Pharmacology | https://doi.org/10.1111/bph.70145.

Henkin, R. I. et al.: cAMP and cGMP in human parotid saliva: relationships to taste and smell dysfunction, gender, and age (2007) The American Journal of the Medical Sciences | https://doi.org/10.1097/MAJ.0b013e3180de4d97.

Howe, A. K.: Regulation of actin-based cell migration by cAMP/PKA (2004) Biochimica et biophysica acta | https://doi.org/10.1016/j.bbamcr.2004.03.005.

Jiang, L. I. et al.: Use of a cAMP BRET sensor to characterize a novel regulation of cAMP by the sphingosine 1-phosphate/G13 pathway (2007) The Journal of biological chemistry | https://doi.org/10.1074/jbc.M609695200.

Kawata-Shimamura, Y. et al.: Biomarker discovery for practice of precision medicine in hypopharyngeal cancer: a theranostic study on response prediction of the key therapeutic agents (2022) BMC Cancer | https://doi.org/10.1186/s12885-022-09853-1.

Kresge, N. et al.: Earl W. Sutherland’s Discovery of Cyclic Adenine Monophosphate and the Second Messenger System (2005) Journal of Biological Chemistry | https://doi.org/10.1016/S0021-9258(19)48258-6.

Lee, D.: Global and local missions of cAMP signaling in neural plasticity, learning, and memory (2015) Frontiers in Pharmacology | https://doi.org/10.3389/fphar.2015.00161.

Oeckl, P. et al.: Simultaneous LC-MS/MS analysis of the biomarkers cAMP and cGMP in plasma, CSF and brain tissue (2012) Journal of Neuroscience Methods | https://doi.org/10.1016/j.jneumeth.2011.09.032.

Patra, C. et al.: Biochemistry, cAMP (2023) | https://www.ncbi.nlm.nih.gov/books/NBK535431/

Piec, I. et al.: A LC-MS/MS method for the diagnostic measurement of cAMP in plasma and urine (2017) | https://ueaeprints.uea.ac.uk/id/eprint/65479/.

Raker, V. K. et al.: The cAMP Pathway as Therapeutic Target in Autoimmune and Inflammatory Diseases (2016) Frontiers in Immunology | https://doi.org/10.3389/fimmu.2016.00123.

Rooij, J. de et al.: Epac is a Rap1 guanine-nucleotide-exchange factor directly activated by cyclic AMP (1998) Nature | https://doi.org/10.1038/24884.

Tavares, L. P. et al.: Blame the signaling: Role of cAMP for the resolution of inflammation (2020) Pharmacological Research | https://doi.org/10.1016/j.phrs.2020.105030.

Wang, P. et al.: Exchange proteins directly activated by cAMP (EPACs): Emerging therapeutic targets (2017) Bioorganic & Medicinal Chemistry Letters | https://doi.org/10.1016/j.bmcl.2017.02.065.

Yadav, R. et al.: GPCR signaling via cAMP nanodomains (2025) Biochemical Journal | https://doi.org/10.1042/BCJ20253088.

You, C. et al.: Coordination of bacterial proteome with metabolism by cyclic AMP signalling (2013) Nature | https://doi.org/10.1038/nature12446.

Zhang, H. et al.: Complex roles of cAMP-PKA-CREB signaling in cancer (2020) Experimental hematology & oncology | https://doi.org/10.1186/s40164-020-00191-1.

Zhang, H. et al.: cAMP-PKA/EPAC signaling and cancer: the interplay in tumor microenvironment (2024) Journal of Hematology & Oncology | https://doi.org/10.1186/s13045-024-01524-x.

Zhou, G. et al.: Multifaceted Roles of cAMP Signaling in the Repair Process of Spinal Cord Injury and Related Combination Treatments (2022) Frontiers in Molecular Neuroscience | https://doi.org/10.3389/fnmol.2022.808510.

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• History & Evolution
• Biosynthesis & dietary uptake
• Methylmalonic acid and the microbiome
• Methylmalonic acid and vitamin B12 deficiency
• Methylmalonic acid and neurology
• Methylmalonic acid and 5P medicine
• References

History & Evolution

1963: First clinical description in pernicious anemia | 1967: Discovery of methylmalonic aciduria | 1968: Vitamin B12 responders in methylmalonyl-CoA deficiency | 1993: Methylmalonic acid (MMA) as biomarker for vitamin B12 deficiency

Methylmalonic acid (MMA) was first linked to human disease in 1963, when researchers observed elevated urinary levels in patients with pernicious anemia (Barness et al. 1963), a rare and fatal disease marked by progressive anemia and neurological decline (American Chemical Society 2025). In 1967, MMA was identified as the hallmark of a newly described inborn error of metabolism, methylmalonic aciduria (Oberholzer et al. 1967). The underlying cause—methylmalonyl-CoA mutase deficiency—was discovered soon after in 1968 (Rosenberg et al. 1968a). However, not all cases were due to a defect in the enzyme itself. Some patients showed a biochemical response to vitamin B12 supplementation, leading to the identification of B12-responsive subtypes (Rosenberg et al. 1968b).

Accordingly, in 1993, MMA was established as a sensitive biomarker for detecting early or subclinical vitamin B12 deficiency, often before B12 levels dropped (Allen et al. 1993). Recognizing its diagnostic value, MMA measurement was added to the U.S. newborn screening panel in 2006 to detect methylmalonic acidemia. More recently, large population studies linked elevated MMA to cognitive decline (Clarke et al. 2007), depressive symptoms and increased mortality (Cao et al. 2024), underscoring its broader relevance in aging and public health (Tejero et al. 2024).

Biosynthesis vs. dietary uptake

MMA is a short-chain dicarboxylic acid and an intermediate in the catabolism of certain amino acids, fatty acids and cholesterol. It is not obtained from the diet but is synthesized endogenously as part of normal human metabolism. The primary biosynthetic route to MMA occurs in the mitochondria through the conversion of propionyl-coenzyme A (CoA).

In this pathway, propionyl-CoA is first carboxylated to D-methylmalonyl-CoA by propionyl-CoA carboxylase, a biotin-dependent enzyme. D-methylmalonyl-CoA is then converted to its L-isomer by methylmalonyl-CoA epimerase (Tejero et al. 2024). Subsequently, the L-isomer is converted to succinyl-CoA by methylmalonyl-CoA mutase (MUT), a mitochondrial enzyme that requires the active coenzyme form of vitamin B12, adenosylcobalamin (Takahashi-Iñiguez et al. 2012). Finally, the resulting succinyl-CoA enters the tricarboxylic acid cycle (Tejero et al. 2024).

When MUT activity is impaired due to genetic mutations or functional vitamin B12 deficiency, methylmalonyl-CoA cannot be efficiently converted into succinyl-CoA. As a result, it accumulates and is hydrolyzed to free MMA, which then appears in plasma (Allen et al. 1993).

Under normal physiological conditions, plasma MMA concentrations are low (typically <0.3 µmol/L in adults), reflecting efficient MUT activity and adequate cobalamin status. Elevated MMA is one of the earliest and most specific indicators of intracellular B12 deficiency, and unlike homocysteine, its levels are not influenced by folate or vitamin B6 status (O’Leary et al. 2010).

Once produced, MMA is not reused; instead, it is filtered by the kidneys and eliminated in urine. Renal function therefore plays a critical role in regulating plasma MMA levels, and mild elevations can also be observed in renal impairment (Supakul et al. 2020).

Methylmalonic acid and the microbiome

Emerging evidence suggests that circulating levels of MMA can be shaped by the gut microbiome, complicating their use as a straightforward biomarker of B12 deficiency in clinical settings.

Recent studies have shown that certain gut microbial communities are significantly associated with serum MMA concentrations, independently of host B12 status. For example, in healthy adults, oral antibiotic treatment led to a reduction in serum MMA, implying that gut bacteria contribute to its circulating pool (Miller et al. 2025).

Microbial co-abundance guilds (groups of taxa with correlated abundance patterns) have been found to associate with either serum MMA or B12, but not both. This suggests that different microbial profiles influence MMA through mechanisms beyond B12 availability, such as enhanced propionate production or altered short-chain fatty acid (SCFA) metabolism (Miller et al. 2025). Among SCFAs, propionate uniquely accounted for a significant portion of the variance in MMA levels, further highlighting the specificity of this microbial-metabolite link.

The clinical relevance of this microbiota–MMA axis has become particularly evident in metabolic disease. In gestational diabetes mellitus (GDM), integrated multiomics approaches have revealed close correlations between the fecal microbiota and plasma metabolome. Specifically, plasma levels of MMA were strongly associated with alterations in gut microbiota composition (Dong et al. 2020).

Moreover, case reports in patients with small intestinal bacterial overgrowth further support a microbial contribution to elevated MMA: in such individuals, broad-spectrum antibiotics normalized MMA levels, suggesting that gut bacteria capable of producing propionate—and potentially MMA itself—can significantly elevate systemic concentrations (Tejero et al. 2024).

Together, these findings challenge the long-held assumption that elevated MMA is a direct marker of B12 deficiency. Instead, gut microbial activity, particularly through propionate-producing pathways, may represent an additional, independent source of MMA in the circulation of the host.

Methylmalonic acid and vitamin B12 deficiency

Despite growing interest in its microbial origins, MMA’s primary clinical role remains as the most specific functional marker of vitamin B12 (cobalamin) status. When B12 is insufficient at the cellular level, related metabolic processes begin to fail, such as the conversion of methylmalonyl-CoA to succinyl-CoA. As a result, MMA levels in the blood often increase before B12 falls below the classical deficiency cut-off of 200 pg/mL, making it a useful marker of “functional” deficiency in patients whose total B12 level remains within the low-normal range (201–350 pg/mL) (Ankar et al. 2025; Office of Dietary Supplements 2024).

In a 2015 article, Fedosov et al. recommend the inclusion of MMA as part of a comprehensive diagnostic panel alongside total serum B12, holotranscobalamin (active B12) and homocysteine to monitor B12 status (Fedosov et al. 2015).

Functionally, MMA is more than a diagnostic tool: it is implicated in the pathology of B12 deficiency. Elevated MMA disrupts normal lipid metabolism and mitochondrial energy production, contributing to myelin sheath instability and neurotoxicity (Ankar et al. 2025). These mechanisms are thought to underlie many of the neurological symptoms associated with B12 deficiency, including peripheral neuropathy, ataxia, cognitive dysfunction and dementia-like presentations (Langan et al. 2017; Brito et al. 2017; Ankar et al. 2025)

Methylmalonic acid and neurology

MMA accumulation following decreased conversion of methylmalonyl-CoA to succinyl-CoA also impairs TCA cycle flux. This contributes to mitochondrial dysfunction and promotes oxidative stress through inhibition of respiratory chain complexes and lipid peroxidation. These effects are particularly damaging to the central nervous system, which relies heavily on mitochondrial ATP production and intact myelin structure for normal function (Denley et al. 2025).

High MMA levels associate with a range of neurological conditions, including depression and cognitive impairment, as well as increased risk of neurodegenerative disease. In a large cross-sectional analysis of the U.S. National Health and Nutrition Examination Survey (NHANES) data, higher circulating MMA was independently associated with increased depressive symptoms and a ~25% increase in all-cause mortality, even after adjusting for serum B12 and folate levels (Cao et al. 2024). Additional analyses have confirmed that elevated MMA is more prevalent among individuals with dementia and Alzheimer’s disease than in cognitively healthy controls (Refsum et al. 2003; O’Leary et al. 2012). Clinical observations also suggest a high co-occurrence of elevated MMA and subclinical B12 deficiency in patients presenting with neuropsychiatric complaints, including memory loss, fatigue and mood disorders (Nalder et al. 2021; Moore et al. 2012)

Longitudinal data support these findings. In the Oxford Age and Nutrition Project, doubling of baseline MMA concentrations (from 0.25 to 0.50 µM) was associated with a 50% faster rate of cognitive decline (Clarke et al. 2007). Similarly, the Chicago Memory and Aging Project found that higher MMA levels predicted steeper six-year decline in memory and executive function (Tangney et al. 2009). In children, elevated MMA was also linked to reduced cognitive performance in later years (Kvestad et al. 2017).

In a clinical trial involving elderly Chilean participants with vitamin B12 deficiency and elevated levels of MMA, B12 repletion led to increased serum concentrations of acylcarnitines, plasmalogens, phospholipids, and decreased methionine and cysteine. This metabolite shifts are indicative of enhanced mitochondrial function and one-carbon metabolism and coincided with improved peripheral nerve conduction, suggesting a direct link between B12 status, metabolic repair and neural function (Brito et al. 2017).

Methylmalonic acid and aging

MMA accumulates progressively with age, even in individuals without overt B12 deficiency or renal dysfunction (O’Leary et al., 2012; Clarke et al., 2007). This age-related rise in MMA has been linked to cognitive decline, physical frailty and increased mortality (Cao et al., 2024; Tangney et al., 2009).

Mechanistically, elevated MMA interferes with mitochondrial function, impairs cellular energy metabolism, promotes oxidative stress and triggers pro-inflammatory signaling (Tejero et al. 2024). These effects mirror several hallmarks of aging, including mitochondrial dysfunction, chronic inflammation and disrupted intercellular communication (López-Otín et al. 2023).

Further findings also connect MMA to cancer progression. In elderly individuals, elevated circulating MMA creates a systemic environment that promotes tumor aggressiveness by inducing transcriptional programs such as SRY-Box Transcription Factor 4 (SOX4) and driving processes like epithelial-to-mesenchymal transition (Gomes et al. 2020). This positions MMA as a molecular bridge between aging and cancer biology, suggesting that targeting MMA accumulation may offer a novel strategy to counteract both age-related decline and tumor progression.

Methylmalonic acid and 5P medicine

MMA is a valuable tool in predictive and preventive medicine. As one of the earliest markers of functional vitamin B12 deficiency, rising MMA levels can signal risk for neurological decline, frailty and even cancer progression, often before symptoms appear. When combined with genetic or metabolic information, MMA helps deliver precision medicine, distinguishing between inherited disorders, functional B12 deficiency or microbiome-related causes. This allows for early, targeted interventions such as B12 supplementation or microbiome-based strategies to prevent further damage. Finally, MMA empowers both clinicians and patients to take informed action, shifting care from reaction to prevention.

References

Allen, R.H. et al.: Metabolic abnormalities in cobalamin (vitamin B12) and folate deficiency (1993) FASEB journal : official publication of the Federation of American Societies for Experimental Biology | DOI: 10.1096/fasebj.7.14.7901104.

Ankar, A. et al.: Vitamin B12 Deficiency (2025) | https://www.ncbi.nlm.nih.gov/books/NBK441923/.

Barness, L.A. et al.: Methylmalonate excretion in a patient with pernicious anemia (1963) The New England journal of medicine | DOI: 10.1056/NEJM196301172680309.

Brito, A. et al.: The Human Serum Metabolome of Vitamin B-12 Deficiency and Repletion, and Associations with Neurological Function in Elderly Adults (2017) The Journal of nutrition | DOI: 10.3945/jn.117.248278.

Cao, B. et al.: Associations of methylmalonic acid and depressive symptoms with mortality: a population-based study (2024) Translational Psychiatry | DOI: 10.1038/s41398-024-03015-6.

Clarke, R. et al.: Low vitamin B-12 status and risk of cognitive decline in older adults (2007) The American Journal of Clinical Nutrition | DOI: 10.1093/ajcn/86.5.1384.

Denley, M.C.S. et al.: Mitochondrial dysfunction drives a neuronal exhaustion phenotype in methylmalonic aciduria (2025) Communications Biology | DOI: 10.1038/s42003-025-07828-z.

Dong, L. et al.: Integrated microbiome-metabolome analysis reveals novel associations between fecal microbiota and hyperglycemia-related changes of plasma metabolome in gestational diabetes mellitus (2020) RSC advances | DOI: 10.1039/C9RA07799E.

Fedosov, S.N. et al.: Combined indicator of vitamin B12 status: modification for missing biomarkers and folate status and recommendations for revised cut-points (2015) Clinical chemistry and laboratory medicine | DOI: 10.1515/cclm-2014-0818.

Gomes, A.P. et al.: Age-induced accumulation of methylmalonic acid promotes tumour progression (2020) Nature | DOI: 10.1038/s41586-020-2630-0.

Kvestad, I. et al.: Vitamin B-12 status in infancy is positively associated with development and cognitive functioning 5 y later in Nepalese children (2017) The American Journal of Clinical Nutrition | DOI: 10.3945/ajcn.116.144931.

Langan, R.C. et al.: Vitamin B12 Deficiency: Recognition and Management (2017) American family physician | PMID: 28925645.

López-Otín, C. et al.: Hallmarks of aging: An expanding universe (2023) Cell | DOI: 10.1016/j.cell.2022.11.001.

Miller, J.W. et al.: Serum Methylmalonic Acid Is Associated With Gut Microbial Co-Abundance Guilds and Circulating Propionate in Healthy Adults (2025) Current Developments in Nutrition | DOI: 10.1016/j.cdnut.2025.107421.

Moore, E. et al.: Cognitive impairment and vitamin B12: a review (2012) International psychogeriatrics | DOI: 10.1017/S1041610211002511.

Nalder, L. et al.: Vitamin B12 and Folate Status in Cognitively Healthy Older Adults and Associations with Cognitive Performance (2021) The journal of nutrition, health & aging | DOI: 10.1007/s12603-020-1489-y.

Oberholzer, V.G. et al.: Methylmalonic aciduria. An inborn error of metabolism leading to chronic metabolic acidosis (1967) Archives of disease in childhood | DOI: 10.1136/adc.42.225.492.

Office of Dietary Supplements: Office of Dietary Supplements – Vitamin B12 (2024) | https://ods.od.nih.gov/factsheets/VitaminB12-HealthProfessional/.

O’Leary, F. et al.: Vitamin B12 in health and disease (2010) Nutrients | DOI: 10.3390/nu2030299.

O’Leary, F. et al.: Vitamin B₁₂ status, cognitive decline and dementia: a systematic review of prospective cohort studies (2012) British Journal of Nutrition | DOI: 10.1017/S0007114512004175.

Refsum, H. et al.: Low vitamin B-12 status in confirmed Alzheimer’s disease as revealed by serum holotranscobalamin (2003) Journal of neurology, neurosurgery, and psychiatry | DOI: 10.1136/jnnp.74.7.959.

Rosenberg, L.E. et al.: Methylmalonic aciduria. An inborn error leading to metabolic acidosis, long-chain ketonuria and intermittent hyperglycinemia (1968a) The New England journal of medicine | DOI: 10.1056/NEJM196806132782404.

Rosenberg, L.E. et al.: Methylmalonic aciduria: metabolic block localization and vitamin B 12 dependency (1968b) Science (New York, N.Y.) | DOI: 10.1126/science.162.3855.805.

Supakul, S. et al.: Diagnostic Performances of Urinary Methylmalonic Acid/Creatinine Ratio in Vitamin B12 Deficiency (2020) Journal of Clinical Medicine | DOI: 10.3390/jcm9082335.

Takahashi-Iñiguez, T. et al.: Role of vitamin B12 on methylmalonyl-CoA mutase activity (2012) Journal of Zhejiang University. Science. B | DOI: 10.1631/jzus.B1100329.

Tangney, C.C. et al.: Biochemical indicators of vitamin B12 and folate insufficiency and cognitive decline (2009) Neurology | DOI: 10.1212/01.wnl.0000341272.48617.b0.

Tejero, J. et al.: Methylmalonic acid in aging and disease (2024) Trends in endocrinology and metabolism: TEM | DOI: 10.1016/j.tem.2023.11.001.

• History & Evolution
• Biosynthesis & dietary uptake
• UDCA and the microbiome
• UDCA and signaling
• UDCA as therapeutic drug
• UDCA and 5P medicine
• References

History & Evolution

1902: discovery in bear bile (Hammarsten) | 1927: isolation and naming (Shoda) | 1980s: approval for liver diseases

Ursodeoxycholic acid (UDCA) is a secondary bile acid with a long history in traditional medicine and modern hepatology. First identified in bear bile by Hammarsten in 1902 and isolated by Shoda in 1927, UDCA takes its name from Ursus, Latin for bear (Lazaridis et al. 2001). It became clinically relevant in the 1980s, when synthetic UDCA was approved for treating cholestatic liver diseases such as primary biliary cholangitis (PBC) (Ishizaki et al. 2005). Today, UDCA is recognized as a key therapeutic bile acid with a range of anti-apoptotic, cytoprotective and immunomodulatory functions (Lazaridis et al. 2001; Amaral et al. 2009).

Biosynthesis vs. dietary uptake

Bile acids are formed from cholesterol in the liver and secreted into the intestine. Gut microbiota metabolize these bile acids through deconjugation, dehydroxylation and epimerization (Keely et al. 2019). In this way, the secondary bile acid UDCA is produced in the colon through microbial transformation of the primary bile acid chenodeoxycholic acid (CDCA), first through deconjugation via bile salt hydrolases, then via epimerization at the 7-position (Daruich et al. 2019; Ridlon et al. 2015). Once formed, UDCA is passively absorbed in the colon and returns to the liver through the portal circulation. There, it is reconjugated with taurine or glycine into glyco- or tauro-ursodeoxycholic acid (GUDCA and TUDCA, respectively) as part of the enterohepatic circulation (Lazaridis et al. 2001). This recycling loop helps maintain bile acid pool stability and amplifies the systemic availability of UDCA. TUDCA and other conjugated forms of UDCA are increasingly recognized for their cytoprotective and anti-inflammatory properties (Daruich et al. 2019).

UDCA is not only a product of gut microbiota, but also a substrate for further transformation. The major metabolite of UDCA is lithocholic acid (LCA), which has been regarded as the most cytotoxic of the secondary bile acids, especially in the liver (Hofmann 2004). However, this view is increasingly being challenged. Emerging evidence suggests that the beneficial effects of UDCA on epithelial integrity and inflammation may, at least in part, depend on its microbial conversion to LCA (Lajczak-McGinley et al. 2020; Keely et al. 2019).

Additionally, UDCA can be reconverted into isoUDCA by microbial and hepatic enzymes. The ratio of isoUDCA to UDCA has been proposed as a potential biomarker of bile acid pool dynamics and therapeutic efficacy, particularly in cholestatic liver diseases (Beuers et al. 1991). This ratio reflects the delicate interplay between microbial metabolism and host bile acid handling; factors critical for maintaining bile acid homeostasis and preventing liver injury (Marschall et al. 2001).

UDCA and the microbiome

UDCA is both a product of microbial activity and a potent modulator of the gut microbiome itself. While its formation depends on bacterial enzymes, UDCA also feeds back into the intestinal environment, influencing microbial composition and function. This bidirectional relationship underlies many of UDCA’s therapeutic effects.

One of the key microbiome-level impacts of UDCA is its ability to shift microbial communities toward more balanced and less pro-inflammatory configurations (Wahlström et al. 2016). For instance, in experimental models of colitis, UDCA and its taurine-conjugated form TUDCA have been shown to normalize the Firmicutes-to-Bacteroidetes ratio, which can be indicative of microbial balance often disrupted in inflammatory and metabolic conditions. Such rebalancing may reflect reduced bile acid toxicity, improved mucosal barrier function, and downstream effects on immune regulation (Keely et al. 2019).

These microbiome changes are not only compositional but also functional. UDCA treatment is associated with a reduction in microbial pathways linked to harmful metabolites like enterobactin and lactate, while supporting bile acid transformations that favor anti-inflammatory and cytoprotective signaling (Lee et al. 2024).

Altogether, UDCA’s ability to modulate the microbiome reflects a broader mechanism of action that goes beyond its direct effects on bile flow or hepatocyte protection. Its role in shaping a gut ecosystem that supports intestinal and systemic homeostasis – an aspect of its therapeutic profile that is gaining increasing attention.

UDCA and signaling

In addition to its choleretic (promoting bile synthesis and bile flow) and cytoprotective effects, UDCA is increasingly recognized as a signaling molecule that modulates a range of nuclear- and membrane-bound receptors in human tissues (Marchianò et al. 2023). Although a relatively weak agonist compared to more hydrophobic bile acids like LCA or deoxycholic acid (DCA), which passively diffuse into epithelial colonic cells and activate nuclear receptors, UDCA exerts regulatory effects through both direct receptor engagement and indirect metabolic reshaping of the bile acid pool (Hanafi et al. 2018). These interactions contribute to UDCA’s therapeutic profile in liver and intestinal diseases (Lin et al. 2025).

Key receptor and signaling interactions

• Takeda G protein-coupled receptor 5 (TGR5, also known as GPBAR1): UDCA modestly activates this G-protein-coupled receptor, especially in enteroendocrine and immune cells. TGR5 activation enhances secretion of glucagon-like peptide-1 (GLP-1), supports glucose homeostasis, and suppresses pro-inflammatory cytokines such as tumor necrosis factor-alpha (TNF-α) (Hanafi et al. 2018), reinforcing UDCA’s metabolic and anti-inflammatory effects (Lin et al. 2025; Guzior et al. 2021).

• Farnesoid X Receptor (FXR): While UDCA is not a strong FXR agonist, it modulates FXR signaling indirectly by altering bile acid pool composition, notably by reducing antagonists like LCA (Hanafi et al. 2018). In inflammatory settings, UDCA can selectively downregulate FXR expression while upregulating FXR target genes like SHP, in turn influencing genes such as CYP7A1 and BSEP involved in bile acid synthesis and transport (Lin et al. 2025; Guzior et al. 2021).

• Pregnane X and Vitamin D Receptors (PXR and VDR): UDCA does not directly activate these receptors, but by reducing LCA – a potent ligand for both – it may help regulate detoxification pathways, epithelial integrity and immune homeostasis. These are especially relevant in gut-liver disorders and cholestasis (Hanafi et al. 2018; Keely et al. 2019).

There is also an epigenetic layer to UDCA’s anti-inflammatory and anti-tumorigenic mechanisms: UDCA downregulates miRNA-21, a pro-inflammatory and pro-carcinogenic microRNA that is upregulated by lipopolysaccharide (LPS) and in chronic liver inflammation (Peng et al. 2024).

UDCA as therapeutic drug

UDCA is a cornerstone therapy for chronic cholestatic liver diseases such as PBC, with growing relevance in metabolic and immunological conditions (Keely et al. 2019). While its core mechanisms are hepatoprotective and choleretic, UDCA also engages complex signaling and microbiome-modulating pathways that may benefit extrahepatic disorders like inflammatory bowel disease (Lin et al. 2025). As research evolves, combination therapies and system-level understanding will likely expand UDCA’s clinical applications across liver and gut health.

UDCA’s therapeutic effects stem from its ability to balance the bile acid pool, stabilize hepatocyte membranes, reduce oxidative stress and modulate immune responses (Kumar et al. 2001). These actions translate into anti-apoptotic, cytoprotective, choleretic and immunomodulatory benefits (Keely et al. 2019). In PBC, long-term UDCA therapy (13–15 mg/kg/day) improves liver biochemistry, slows histological progression and reduces the need for liver transplantation. It is most effective when started early and has become the standard of care (Kumar et al. 2001).

UDCA is also used in primary sclerosing cholangitis (PSC), though its benefits are modest and may be enhanced when combined with endoscopic therapy. It is the treatment of choice in intrahepatic cholestasis of pregnancy (ICP) and shows benefit in cystic fibrosis–associated liver disease, graft-versus-host disease, and pediatric cholestasis by reducing bile acid toxicity and supporting bile flow (Ted George O. Achufusi et al. 2023).

In metabolic dysfunction-associated steatohepatitis (MASH), UDCA alone has limited therapeutic efficacy but can enhance the effects of FXR/TGR5 agonists. Recent research showed that combining UDCA with such agents led to reversal of liver inflammation and fibrosis, improved bile acid signaling and greater metabolic gene regulation than either treatment alone (Marchianò et al. 2023). This positions UDCA as a synergistic component in multi-targeted approaches for metabolic liver diseases.

UDCA and 5P medicine

UDCA and its derivatives align well with all principles of 5P medicine:

• Predictive and personalized medicine: The isoUDCA/UDCA ratio has emerged as a potential biomarker for therapeutic response and bile acid pool dynamics in cholestatic liver diseases (Beuers et al. 1991). These profiles reflect microbial-host interactions and support individualized monitoring strategies (Marschall et al. 2001)

• Precision medicine: UDCA is an approved treatment for PBC, PSC and ICP (Kumar et al. 2001; Ted George O. Achufusi et al. 2023). It modulates bile acid receptors (FXR, TGR5), transporters and inflammatory responses (Hanafi et al. 2018; Keely et al. 2019). In MASH, UDCA is being tested in combination with receptor agonists like BAR502 (Marchianò et al. 2023). It also reshapes bile acid pools, reducing hepatotoxic intermediates such as LCA (Hanafi et al. 2018), thus acting as both a treatment and response-modifying agent.

• Participatory medicine: UDCA’s oral administration and safety profile allow patients to engage in long-term, proactive care. It is widely used to prevent gallstones in post-bariatric patients (Gideon M. Hirschfield et al. 2017) and treat pregnancy-related cholestasis (Kumar et al. 2001).

• Population-based medicine: UDCA is included in international clinical guidelines for PBC and other liver diseases (Lindor et al. 2019; Gideon M. Hirschfield et al. 2017). Its safety and efficacy support preventive use, although global access and cost remain variable.

References

Amaral, J.D. et al.: Bile acids: regulation of apoptosis by ursodeoxycholic acid (2009) Journal of Lipid Research | DOI: 10.1194/jlr.R900011-JLR200.

Beuers, U. et al.: Formation of iso-ursodeoxycholic acid during administration of ursodeoxycholic acid in man (1991) Journal of hepatology | DOI: 10.1016/0168-8278(91)90870-H.

Daruich, A. et al.: Review: The bile acids urso- and tauroursodeoxycholic acid as neuroprotective therapies in retinal disease (2019) Molecular Vision | PMID: 31700226

Gideon M. Hirschfield et al.: EASL Clinical Practice Guidelines: The diagnosis and management of patients with primary biliary cholangitis (2017) Journal of Hepatology | DOI: 10.1016/j.jhep.2017.03.022.

Guzior, D.V. et al.: Review: microbial transformations of human bile acids (2021) Microbiome | DOI: 10.1186/s40168-021-01101-1.

Hanafi, N.I. et al.: Overview of Bile Acids Signaling and Perspective on the Signal of Ursodeoxycholic Acid, the Most Hydrophilic Bile Acid, in the Heart (2018) Biomolecules | DOI: 10.3390/biom8040159.

Hofmann, A.F.: Detoxification of lithocholic acid, a toxic bile acid: relevance to drug hepatotoxicity (2004) Drug metabolism reviews | DOI: 10.1081/dmr-200033475.

Ishizaki, K. et al.: Hepatoprotective bile acid ‘ursodeoxycholic acid (UDCA)’ Property and difference as bile acids (2005) Hepatology Research | DOI: 10.1016/j.hepres.2005.09.029.

Keely, S.J. et al.: Ursodeoxycholic acid: a promising therapeutic target for inflammatory bowel diseases? (2019) American journal of physiology. Gastrointestinal and liver physiology | DOI: 10.1152/ajpgi.00163.2019.

Kumar, D. et al.: Use of ursodeoxycholic acid in liver diseases (2001) Journal of Gastroenterology and Hepatology | DOI: 10.1046/j.1440-1746.2001.02376.x.

Lajczak-McGinley, N.K. et al.: The secondary bile acids, ursodeoxycholic acid and lithocholic acid, protect against intestinal inflammation by inhibition of epithelial apoptosis (2020) Physiological Reports | DOI: 10.14814/phy2.14456.

Lazaridis, K.N. et al.: Ursodeoxycholic acid ‘mechanisms of action and clinical use in hepatobiliary disorders’ (2001) Journal of hepatology | DOI: 10.1016/S0168-8278(01)00092-7.

Lee, J. et al.: The gut microbiome predicts response to UDCA/CDCA treatment in gallstone patients: comparison of responders and non-responders (2024) Scientific Reports | DOI: 10.1038/s41598-024-53173-2.

Lin, X. et al.: Crosstalk Between Bile Acids and Intestinal Epithelium: Multidimensional Roles of Farnesoid X Receptor and Takeda G Protein Receptor 5 (2025) International Journal of Molecular Sciences | DOI: 10.3390/ijms26094240.

Lindor, K.D. et al.: Primary Biliary Cholangitis: 2018 Practice Guidance from the American Association for the Study of Liver Diseases (2019) Hepatology | DOI: 10.1002/hep.30145.

Marchianò, S. et al.: Combinatorial therapy with BAR502 and UDCA resets FXR and GPBAR1 signaling and reverses liver histopathology in a model of NASH (2023) Scientific Reports | DOI: 10.1038/s41598-023-28647-4.

Marschall, H.-U. et al.: Isoursodeoxycholic acid: metabolism and therapeutic effects in primary biliary cirrhosis (2001) Journal of lipid research | DOI: 10.1016/S0022-2275(20)31635-7.

Peng, C.-Y. et al.: Ursodeoxycholic Acid Modulates the Interaction of miR-21 and Farnesoid X Receptor and NF-κB Signaling (2024) Biomedicines | DOI: 10.3390/biomedicines12061236.

Ridlon, J.M. et al.: The human gut sterolbiome: bile acid-microbiome endocrine aspects and therapeutics (2015) Acta pharmaceutica Sinica. B | DOI: 10.1016/j.apsb.2015.01.006.

Ted George O. Achufusi et al.: Ursodeoxycholic Acid (2023) | PMID: 31424887

Wahlström, A. et al.: Intestinal Crosstalk between Bile Acids and Microbiota and Its Impact on Host Metabolism (2016) Cell Metabolism | DOI: 10.1016/j.cmet.2016.05.005.

Lifestyle and diet are widely recognized as significant determinants of health, driving demand for personalized health solutions (Rafiq et al. 2021). As individuals look for ways to actively manage their well-being, consumer tests such as microbiome sequencing for gut health or proteomics-based longevity assessments are gaining traction. These tests often combine biological measurements with self-reported dietary questionnaires to deliver tailored diet recommendations (Brennan 2017; Guasch-Ferré et al. 2018; Rafiq et al. 2021).

However, self-reported data is prone to inaccuracies, as consumers frequently misestimate their intake of vegetables, red meat, and other foods (Brennan 2017). Scientific research highlights the limitations of self-reported dietary data, with error rates for caloric intake and food portion size ranging from 30% to 88% (Rafiq et al. 2021). These misestimations stem from factors such as memory bias, cultural differences, and the inherent complexity of assessing habitual diets (Gibson et al. 2017).

Analyzing metabolites in biological samples, such as blood, urine, or saliva, can address these challenges. Metabolomics provides a snapshot of an individual’s current nutritional and physiological state, offering a robust, unbiased alternative to complement and validate traditional questionnaires (Gibson et al. 2017; Brennan 2017; Guasch-Ferré et al. 2018). By bridging the gap between subjective data and objective biomarkers, metabolomics enables more accurate diet assessments and personalized nutrition recommendations. This integrated approach deepens our understanding of the dietary impacts on health, facilitating more effective lifestyle interventions aimed at disease prevention.

How dietary patterns shape health through metabolic profiles

Metabolomics research shows that dietary intake is better reflected through food group biomarkers than isolated nutrients. Synergistic interactions between dietary components influence the metabolic response, and metabolomics captures these complex relationships. Studies consistently identify metabolite signatures linked to various food groups, including fruits, vegetables, high-fiber grains, meats, seafood, legumes, nuts, dairy, and caffeinated beverages (Rafiq et al. 2021).

For example, betaine and betaine-related metabolites are associated with fruits and vegetables, with proline betaine linked to citrus fruit consumption and tryptophan betaine to legume consumption (Pekkinen et al. 2015; Lever et al. 2010). High-fiber diets contribute to the production of short-chain fatty acids (SCFAs) by gut microbiota, essential for maintaining gut health and metabolic regulation (Nogal et al. 2021). Meats and seafood provide amino acids and carnitines, along with metabolites such as trimethylamine N-oxide (TMAO), a marker linked to cardiovascular risk (Gatarek et al. 2021; Wang et al. 2022). Fish intake is reflected by the concentrations of omega-3 fatty acids, with eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) being the most reliable indicators. The vitamin B3-related trigonelline is considered a biomarker of coffee intake due to its high concentrations in coffee and related products (Mohamadi et al. 2018).

Metabolic profiling of these food groups helps identify dietary patterns that align with either protective or detrimental health outcomes:

• Risk-associated diets
  Diets high in processed meats, sugary foods, and refined grains – characteristic of a typical Western diet – are associated with obesity, metabolic disorders, cardiovascular disease, cancer and inflammation (Clemente-Suárez et al. 2023). 

• Protective diets
  Diets rich in vegetables, whole grains, and fish correlate with metabolomic profiles characterized by beneficial metabolites like betaines, omega-3 fatty acids, and short-chain fatty acids (SCFAs) (Emwas et al. 2021; Nogal et al. 2021; Pekkinen et al. 2015; Rafiq et al. 2021). Two typical examples are the Mediterranean and Nordic diets, which differ primarily in their preferred oils: extra virgin olive oil in the Mediterranean, and rapeseed oil in Nordic countries, which contains oleic acid, linoleic acid and alpha-linolenic acid. The Nordic diet emphasizes rye, barley, and oats as staple whole grains and favors berries over other fruit.

While specific metabolite markers can be used to provide insights into dietary habits, such as naringenin as a biomarker for grapefruit intake, they do not necessarily reflect overall dietary quality or health outcomes. In the context of disease prevention and nutritional research, it is more meaningful to assess whether an individual follows a healthy dietary pattern as a whole, rather than pinpointing the exact source of nutrients. Whether vitamins come from a grapefruit or a kiwi is ultimately less important than ensuring a diet is nutrient-rich, diverse, and aligned with established health guidelines.

To objectively assess diet quality, standardized scoring systems known as diet quality indices have been developed. These evaluate overall dietary patterns based on adherence to established nutritional guidelines, incorporating both nutrient density and food group composition. They are widely used in epidemiological studies, public health assessments, and clinical research toanalyze the impact of diet on chronic diseases, longevity, and overall health. A large cohort study by Kim et al. identified 17 metabolites that were significantly associated with better diet scores across four major healthy dietary indices (Healthy Eating Index, Alternative Healthy Eating Index, Dietary Approaches to Stop Hypertension and alternate Mediterranean diet). The study shows how metabolite concentrations directly reflect dietary habits because the molecules taken up with the diet feed into the universal core metabolic pathways (Kim et al. 2021). Furthermore, these metabolites might serve as biomarkers for healthy dietary patterns, providing an objective way to measure diet quality and its impact on health.

The science of well-being – how diet and stress influence metabolic health

In addition to reflecting dietary patterns, certain metabolites and their ratios serve as biomarkers for specific conditions and diseases, providing valuable insights into overall well-being and metabolic health.

Betaine and choline are obtained from the diet or synthesized de novo, with choline serving as a precursor for betaine. Both are vital methyl-donor nutrients involved in lipid metabolism, liver function, and the methylation cycle (Chang et al. 2022), and their uptake and balance are critical for metabolic health. While adequate choline intake supports lipid transport and hepatic function (Chang et al. 2022), excess serum choline is associated with metabolic syndrome risk factors such as dyslipidemia, hyperglycemia and cardiovascular disease. The increased risk for cardiovascular disease is linked to the microbiome: some gut bacteria convert choline (and sometimes betaine) to trimethylamine, which is taken up by the human host and further oxidized to TMAO. Trimethylamine and TMAO are both known risk factors for cardiovascular disease (Jang et al. 2021). In contrast, higher betaine levels correlate with favorable lipid and glycemic profiles (Gao et al. 2019). Consequently, optimal dietary intake of choline and betaine significantly reduces the risk of hepatic steatosis and improves indicators of metabolic syndrome (Gao et al. 2019; Chang et al. 2022).

A nutritional study with more than 10,000 participants in Spain found a correlation between eating habits and mood. A diet including fruit, nuts, legumes, and a high ratio of monounsaturated to saturated fats associated with better mood and lower risk of depression (Sánchez-Villegas et al. 2009).

Beyond diet, lifestyle factors — especially stress — are key factors affecting overall well-being. Sustained stress can elevate circulating cortisol levels, contributing to allostatic load, a state where chronic physiological strain disrupts the body’s regulatory networks. High cortisol levels have been linked to mood disorders, anxiety, sleep disturbances, and metabolic imbalances (Rodriquez et al. 2019).

Quality sleep is crucial for stress management, with γ-aminobutyric acid (GABA) playing a key role as a neurotransmitter known for its calming effects. Low GABA levels correlate with reduced sleep quality, though human trial data on the benefits of GABA supplementation remain inconclusive. The microbiome is also a major GABA producer. More research with standardized methodologies is needed to determine the interplay between stress, sleep, and metabolism, and the efficacy of nutritional interventions for stress resilience and metabolic health (Hepsomali et al. 2020).

Metabotyping – tailored health solutions

Metabotyping identifies metabolic phenotypes based on a wide range of factors, including diet, anthropometric measures, clinical parameters, metabolomics data, and the gut microbiota (Hillesheim et al. 2020). This comprehensive approach gains further depth by integrating metabolomics with other omics technologies – such as genomics, transcriptomics, and proteomics – as well as fitness tracking devices. Wearable technologies that monitor physical activity, heart rate variability, and sleep patterns provide valuable complementary insights (Kelly et al. 2020).
This comprehensive approach can be used to provide customized dietary guidance. For instance, individuals with similar metabotypes may share common metabolic responses to specific foods or nutrients, enabling interventions that are highly targeted and effective. Furthermore, metabotyping can identify individuals at higher risk for metabolic diseases like type 2 diabetes or cardiovascular disorders by analyzing biomarkers such as glucose tolerance, lipid profiles, and inflammatory markers (Palmnäs et al. 2020).

Figure 1: Personalized nutrition using metabolomics

Interestingly, research on personalized nutrition has uncovered significant individual variability in metabolic responses to identical foods. Studies have shown that, even when consuming the same meals, individuals display highly variable postprandial glucose responses, shaped by their distinct metabolic and microbiome profiles. While some experience sharp glucose spikes, others exhibit minimal increases, emphasizing the crucial role of gut microbiome composition and metabolic phenotypes in glycemic regulation (Zeevi et al. 2015).

Building on this, further research has shown that individuals in different metabotype subgroups exhibit varying glucose responses to an oral glucose tolerance test. Those classified in “intermediate” and “unfavorable” metabotypes tend to have significantly higher postprandial glucose concentrations, with the unfavorable subgroup displaying the highest glycemic response (Dahal et al. 2022).

Additionally, dietary fiber interventions reveal differential metabolic benefits depending on metabotype. While a 12-week fiber intervention led to modest reductions in metabolic risk factors overall, individuals with poorer baseline metabolic health experienced the greatest improvements in insulin levels, cholesterol, and blood pressure. These findings suggest that targeted dietary interventions may be particularly beneficial for those with higher metabolic risk (Dahal et al. 2022).

Dried blood spot sampling innovations – analytics with the donor in mind

One challenge of incorporating metabolomics into consumer health testing is the logistics of sample collection and transport. A scalable approach relies on accessible samples. Plasma samples, though widely used in research, require professional blood draws, rapid processing, and cold-chain logistics to preserve sample integrity. These requirements are impractical for at-home consumer tests.

Dried blood sampling addresses these limitations by offering a simple, reliable alternative for metabolite analysis. Dried blood sampling involves collecting small volumes of blood through a finger-prick, which are then dried on specialized devices. These samples are stable at ambient temperatures, eliminating the need for refrigeration or expedited transport.

Innovative dried blood sampling methods include volumetric absorptive microsampling (VAMS) devices such as the widely tested Mitra® tips, and newer technologies like the capillary-based qDBS Capitainer® and the TASSO-M20™ devices, which eliminate the need for a finger prick (Couacault et al. 2024). These technologies facilitate the straightforward collection of precise and predefined blood volumes, even by untrained individuals.

Figure 2: At home sampling with classical DBS cards vs. Mitra® devices as a volumetric alternative

Metabolomic studies confirm the reliability of dried blood in measuring key biomarkers of nutrition and wellbeing (Protti et al. 2022; Kok et al. 2019). Metabolites like vitamin D, SCFAs, and amino acids remain stable in dried blood samples, ensuring accurate quantification. A key advantage of VAMS is its ability to preserve the stability of small molecules, which are particularly informative for assessing an individual’s health (Qiu et al. 2023).

Dried blood sampling offers a scalable solution for integrating advanced metabolomics into precision nutrition, making personalized health insights more accessible to a broader audience. By combining user-friendly devices and robust analytical capabilities, this method has the potential to revolutionize precision health monitoring.

Companies offering consumer health tests have begun to implement these new technologies into their product line. For example, the medical diagnostic laboratory biovis, operating mainly in central Europe via medical practitioners, has recently launched the Prevent 360 test analyzing more than 70 metabolites from dried blood Mitra devices to provide comprehensive insight into the patient‘s health and well-being. Considering the advantages of combining these sampling devices with metabolomics, more companies are bound to follow their example.

Advancing consumer testing options with metabolomics tools

Metabolomic analysis of dried blood samples requires robust absolute quantification of metabolites of different classes in a single run. Ideally, this should be standardized so local laboratories can perform measurements in different countries. The biocrates SMartIDQ alpha kit represents a major step forward in this regard. Specifically optimized for high throughput use with dried blood samples, this kit measures a comprehensive panel of health-related metabolites, enabling detailed nutritional and metabolic assessments.

For interpretation, it is important to consider not only the single metabolite concentrations, but also their sums and ratios. which help extract the biological significance of individual differences, linking metabolomics data to biological pathways and enzyme activities.

In conditions such as hepatic encephalopathy and liver cirrhosis, the Fischer ratio decreases due to impaired liver function. This occurs as AAAs accumulate since the liver is the only organ that catabolizes them, while BCAAs are preferentially used in the muscles for energy metabolism. The progressive decline reflects worsening liver function and metabolic imbalance (Fischer et al. 1975; Soeters et al. 1976).

The MetaboINDICATOR tool that accompanies biocrates kit software provides such advanced data interpretation by calculating more than 120 predefined sums and ratios of metabolite concentrations. The combination of cutting-edge technology and advanced tools enables laboratories and healthcare providers to deliver meaningful, personalized insights to consumers, combining state-of-the-art science and practical applications in precision health.

Empowering health monitoring through metabolomics

Predictive insights from metabolomics can identify early markers of disease risk, enabling timely interventions and fostering a proactive approach to health management. Personalized recommendations, based on robust metabolomic data, empower individuals to make informed dietary and lifestyle changes tailored to their unique health profiles. This preventive approach significantly reduces the burden of chronic disease, supporting public health objectives and aligning with integrative medicine’s focus on addressing the root causes of illness together with individualized treatment. The SMartIDQ alpha kit exemplifies how metabolomics can bring the integrative medicine approach into everyday life. Metabolomics is central to the future of 5P medicine – predictive, personalized, preventive, population-based, and participatory –advancing both nutrition science and consumer health solutions.

References