The team conducted a PRISMA-guided systematic search of Medline, Embase, Cochrane, and Web of Science from database inception through October 17, 2024. To be included, studies had to enroll adults with diagnosed metabolic syndrome, include both female and male participants or individuals with non-binary gender identities, and report sex- or gender-stratified biomarker measurements in any human body fluid with a statistical comparison. The final pool comprised 24 cross-sectional studies, 5 cohort studies, 1 case-control study, and 6 interventional trials, collectively covering 67,846 female and 50,858 male participants. The authors also performed formal risk-of-bias assessments and synthesized findings narratively, grouping results by body fluid and biomarker class rather than forcing heterogeneous data into a single meta-analytic estimate.

The pattern that emerged was strikingly consistent across populations. Male participants with metabolic syndrome more frequently displayed higher fasting blood glucose, higher triglycerides, higher uric acid, and higher cardiovascular risk scores, a combination the authors characterize as a more insulin-resistant and atherogenic profile. In practical terms, the male metabolic signature points toward impaired glucose handling, fat-circulation problems in the bloodstream, and elevated long-term heart disease risk. Indices such as the triglyceride-glucose index and the Framingham Risk Score, both widely used in clinical and research settings, tended to read higher in men, reinforcing the picture of a metabolically harsher internal environment despite an identical diagnosis.

Women with metabolic syndrome, by contrast, more often retained higher levels of what the researchers describe as protective biomarkers. Female participants showed higher concentrations of high-density lipoprotein cholesterol, the lipoprotein fraction conventionally associated with reverse cholesterol transport and cardiovascular protection, along with higher apolipoprotein-A, the structural protein component of HDL particles. Women also more frequently exhibited elevated adiponectin, an adipose-derived hormone with insulin-sensitizing and anti-inflammatory properties, and higher leptin, the satiety-signaling adipokine whose levels typically track fat mass. Antioxidant vitamins and measures of total antioxidant status were likewise more often preserved in female participants, suggesting that even after a metabolic syndrome diagnosis, women’s hormonal and antioxidant defenses erode more slowly than men’s.

The mechanistic backdrop for this divergence is almost certainly multifactorial. Sex hormones, particularly estrogen’s influence on lipid metabolism, adipose tissue distribution, and insulin sensitivity, are prime candidates, since women’s relative protection tends to diminish after menopause. Differences in visceral versus subcutaneous fat deposition, which are strongly sex-dimorphic, alter the flux of free fatty acids to the liver and the secretion profile of adipokines. Uric acid handling in the kidney differs by sex, influenced by both hormonal regulation and genetic factors on the X chromosome. The review does not pin down a single cause, and the authors are careful not to overclaim; what it does establish is that the divergence is reproducible across diverse populations and study designs, which is precisely the property a biomarker needs before it can anchor clinical decision-making.

Perhaps the most sobering finding is not about sex differences at all, but about where the evidence comes from. Nearly every included study measured biomarkers in whole blood or its derivatives, serum and plasma. Exactly one study examined saliva. Not a single study evaluated urine, sweat, or interstitial fluid in a sex-stratified metabolic syndrome context. This is a remarkable blind spot given that the field of non-invasive monitoring is advancing rapidly, with wearable sensors under development that aim to read metabolic state from sweat or interstitial fluid rather than from repeated needle sticks. The review was conducted as part of the MiWear project, a European consortium funded under the HORIZON-EIC-2022 PATHFINDER CHALLENGES program to build mid-infrared wearables for non-invasive biomarker monitoring, and the authors’ emphasis on non-blood biofluids reflects that engineering ambition: a wearable that reads sweat or interstitial fluid is only as trustworthy as the sex-specific calibration data behind it.

The gender dimension of the review proved even thinner than the fluid dimension. None of the 36 included studies reported data on gender-related dimensions, including gender identities, even though the search protocol explicitly allowed for non-binary participants. This means the entire evidence base conflates sex, the biological variable, with gender, the social construct that shapes diet, physical activity, healthcare access, medication adherence, and stress exposure, all of which feed back into metabolic health. The authors argue that future studies must explicitly account for gender-related determinants, because a biomarker threshold that works for one population may silently misclassify another if the social and behavioral context differs. In an era when risk algorithms are being embedded in clinical software, the absence of gender-stratified validation is not an academic quibble; it is a potential source of systematic error.

The clinical stakes are considerable. Current diagnostic criteria for metabolic syndrome, harmonized across bodies such as the World Health Organization, the International Diabetes Federation, and the American Heart Association, apply largely uniform cut-points, with modest adjustments such as different waist circumference thresholds for men and women. If the underlying biomarker landscape diverges as substantially as this review indicates, then single-threshold approaches may under- or over-estimate risk in one sex. A man with metabolic syndrome may warrant more aggressive glucose-lowering and lipid management earlier in his disease course, while a woman whose HDL and adiponectin remain comparatively preserved may follow a different trajectory that current scores fail to capture. Sex-sensitive reference ranges for fasting glucose, triglycerides, uric acid, HDL-C, and inflammatory markers such as C-reactive protein could sharpen risk stratification for both groups, and the authors explicitly call for sex- and gender-sensitive risk algorithms and monitoring technologies.

There are caveats worth keeping in view. Most of the included studies were cross-sectional, capturing a snapshot rather than a trajectory, and only six were interventional, meaning the evidence says more about how biomarkers differ at a point in time than about how those differences evolve with treatment. Heterogeneity in MetS diagnostic criteria, assay methods, and adjustment for confounders such as age, medication use, and menopausal status limited the authors to narrative synthesis rather than pooled effect sizes. The review also could not disentangle how much of the observed divergence reflects biology versus differential healthcare exposure, a question that only prospectively designed, gender-aware cohort studies can answer. Still, the consistency of direction across 118,704 participants lends the central findings considerable weight.

What the review ultimately delivers is a map with a large blank region. The blood-borne, sex-dimorphic signature of metabolic syndrome is now well documented: men skew toward insulin resistance and atherogenic lipid profiles, women toward preserved HDL, adipokines, and antioxidant capacity. Everything beyond the bloodstream, saliva, urine, sweat, interstitial fluid, and the social variables that shape metabolic health, remains largely uncharted. As non-invasive wearable diagnostics move from prototype to clinic, the authors’ prescription is clear: measure across fluids, stratify by sex, and account for gender, or risk building the next generation of metabolic monitoring tools on data that describe only half the population, and only one of its fluids.

Subject of Research: Sex-specific differences in metabolic syndrome biomarkers across human body fluids

Article Title: Sex-specific differences in metabolic syndrome-related biomarkers across body fluids: a systematic review

Article References: Soroush, N., Meij, S. D., Peeters, E., Hamamou, A., & Oertelt-Prigione, S. (2026). Sex-specific differences in metabolic syndrome-related biomarkers across body fluids: a systematic review. Biology of Sex Differences. https://doi.org/10.1186/s13293-026-01000-w

Image Credits: AI Generated

DOI: 10.1186/s13293-026-01000-w

Keywords: metabolic syndrome, sex differences, biomarkers, systematic review, insulin resistance, HDL cholesterol, adipokines, cardiovascular risk, body fluids, gender-sensitive medicine, wearable sensors, precision medicine