The trials were generally small, short and geographically concentrated, and none measured cardiovascular events, so the results concern blood lipid markers rather than proven clinical protection against heart disease or stroke. The analysis, registered prospectively and conducted in line with systematic-review guidance, searched five electronic databases from their inception through March 6, 2026, and also examined references and citations. Eleven included studies used parallel-group designs and two used crossover designs.

The participants included adults with type 2 diabetes, hyperlipidemia, hemodialysis, knee osteoarthritis, rheumatoid arthritis or non-alcoholic fatty liver disease, as well as healthy postmenopausal women, overweight or obese adults with at least one metabolic risk factor, and otherwise healthy adults with slightly elevated LDL cholesterol. Interventions included whole or ground sesame seeds, sesame oil and 200-milligram sesamin capsules, while controls ranged from matched placebos and usual diets to sunflower oil. The pooled reduction in total cholesterol was statistically significant, with a mean difference of −11.65 milligrams per deciliter and a 95% confidence interval from −18.73 to −4.57.

Statistical heterogeneity was moderate at 57.7%. The result was significant among trials using sesame oil or seed, which showed a reduction of 10.86 milligrams per deciliter, but not in the two sesamin trials, whose point estimate was larger but highly uncertain. Both healthy participants and those with medical conditions showed significant reductions, and formal tests did not establish that the two groups differed.

The total-cholesterol estimate remained statistically significant when individual studies were removed in sensitivity analyses, although excluding one high-risk-of-bias trial attenuated it to 8.21 milligrams per deciliter. LDL cholesterol produced the review’s most consistent lipid finding. Sesame-based interventions led to a pooled reduction of 9.14 milligrams per deciliter, with a 95% confidence interval of −14.40 to −3.89 and moderate heterogeneity of 44.0%.

The estimate remained statistically significant after any single trial was omitted and remained significant after two studies using sunflower oil as the comparator were excluded. Subgroup estimates were similar in healthy participants and those with medical conditions. As with total cholesterol, statistically significant reductions were confined to interventions lasting at least eight weeks, but the formal difference between shorter and longer trials did not meet the threshold for a definitive subgroup effect.

Triglycerides did not change significantly overall. The pooled difference was −14.15 milligrams per deciliter, but its 95% confidence interval extended from −29.04 to 0.74 and heterogeneity was substantial at 63.4%. The result was sensitive to the removal of individual studies, illustrating the limited stability of the pooled estimate.

Trials involving participants with medical conditions showed a significant reduction of 22.79 milligrams per deciliter, whereas the three estimates in healthy participants indicated a small, nonsignificant change in the opposite direction. Because the difference between groups was borderline, the analysis included only three healthy estimates, and the groups also differed in baseline triglycerides and intervention characteristics, the reviewers treated this pattern as hypothesis-generating rather than proof of a distinct response by health status. Sesame also had no significant overall effect on HDL cholesterol, with a mean difference of 0.38 milligrams per deciliter and a 95% confidence interval of −1.62 to 2.38.

A small increase appeared in trials lasting fewer than eight weeks, while longer trials showed no change. Although the formal test for this duration difference was nominally significant, the review treated it cautiously because the analysis included multiple subgroup comparisons across four lipid outcomes, increasing the possibility of chance findings. The investigators also found no consistent concentration-response relationship for total or LDL cholesterol.

Delivered lignan content was quantified in only six of the 13 trials, while differences in preparation, dose, duration, participant health and product composition prevented formal dose-response modelling. Using the GRADE framework, the reviewers rated the evidence as moderate certainty for the LDL-cholesterol reduction, low certainty for the total-cholesterol reduction, very low certainty for triglycerides and moderate certainty for HDL cholesterol. The LDL result was downgraded only for imprecision because its confidence interval did not extend beyond the prespecified clinically important difference of 4 milligrams per deciliter.

Evidence for total cholesterol was downgraded for risk of bias and imprecision, while the triglyceride evidence was downgraded for risk of bias, inconsistency and imprecision. Risk-of-bias assessments classified three trials as low risk, eight as raising some concerns and two as high risk. Concerns arose mainly from the randomization process and missing outcome data.

The investigators examined funnel plots and used Egger’s regression tests to assess possible small-study effects. Neither analysis provided evidence of such effects for any of the four lipid outcomes, and the pooled total- and LDL-cholesterol estimates remained statistically significant in leave-one-out analyses. These checks do not prove that publication bias was absent because both approaches have limited power with only 12 or 13 estimates.

The sensitivity analyses also showed that the triglyceride result could become significant after omitting either of two particular studies, while the overall HDL-cholesterol estimate remained nonsignificant regardless of which single study was removed. Excluding the two sunflower-oil comparator trials did not materially alter the total-cholesterol result and only slightly attenuated the LDL-cholesterol reduction. Laboratory and animal experiments offer possible explanations for the cholesterol findings but do not establish clinical effects in people.

Sesamin, a major sesame lignan, has been reported in preclinical work to inhibit cholesterol synthesis, influence intestinal absorption and promote cholesterol efflux. These proposed pathways are consistent with the possibility that sustained exposure could influence lipid metabolism, but many remain supported mainly by cell or animal evidence. The review used only human randomized evidence for its pooled results, and no included trial measured cardiovascular events such as myocardial infarction or stroke.

The findings therefore concern surrogate lipid markers, not proof that sesame prevents cardiovascular disease or provides an alternative to established lipid-lowering treatment. Several limitations constrain the conclusions. The evidence base contained only 13 trials and 690 participants, and individual studies ranged from 30 to 103 people.

Most interventions lasted five to 12 weeks, none exceeded 12 weeks, and only two directly tested purified sesamin. Nine studies were conducted in Iran, two in Japan and one each in Taiwan and Australia, limiting generalizability to other populations and dietary patterns. Seven trials used matched placebos, four used no sesame without a specific placebo, and two used sunflower oil, meaning some estimates reflected the relative effects of sesame and another dietary oil.

Most studies did not quantify the actual lignan content of their preparations, and two low-risk sesame-oil trials were funded by a sesame manufacturer. Long-term efficacy, safety, optimal dose and the effect of different processing methods remain uncertain. Overall, the review identifies sesame as a potentially useful dietary adjunct with a selective, modest effect on atherogenic cholesterol rather than a comprehensive treatment for dyslipidemia.

The strongest result was an average LDL-cholesterol reduction of about 9 milligrams per deciliter, supported by moderate-certainty evidence, while total cholesterol fell by about 12 milligrams per deciliter on lower-certainty evidence. There was no demonstrated overall benefit for triglycerides or HDL cholesterol, and the apparent advantages of longer treatment or purified sesamin remain uncertain. The authors call for larger, longer, low-risk-of-bias trials that measure bioactive compound content, compare seeds, oil and sesamin directly, recruit populations beyond the current geographic concentration and evaluate clinical cardiovascular endpoints.

Subject of Research: Effects of sesame seeds, sesame oil and sesamin on serum lipid profiles in adults

Article Title: Effects of Sesame ( Sesamum indicum L.) and Its Lignan Sesamin on the Serum Lipid Profile: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

Article References: Inthachat, W., Chupeerach, C., Trachootham, D., & Temviriyanukul, P. (2026). Effects of Sesame (Sesamum indicum L.) and Its Lignan Sesamin on the Serum Lipid Profile: A Systematic Review and Meta-Analysis of Randomized Controlled Trials. Journal of Agriculture and Food Research, Article 103379. https://doi.org/10.1016/j.jafr.2026.103379

Image Credits: AI Generated

DOI: 10.1016/j.jafr.2026.103379

Keywords: sesame, sesamin, cholesterol, LDL cholesterol, triglycerides, HDL cholesterol, randomized trials, meta-analysis, lipid profile, dietary interventions, Effects, Sesamum

The investigators calculated UHR by dividing the first available serum uric acid concentration after admission, expressed in micromoles per liter, by the first available HDL-C concentration, expressed in millimoles per liter. Because the numerical value depends on the units used, the study’s estimated inflection point of 166.17 is specific to that unit convention. The cohort included 104 men and 200 women. Of the fractures, 214 were intertrochanteric and 90 were femoral neck fractures; 296 injuries resulted from falls, five from accidents and three from other mechanisms. Most patients received closed or open reduction and internal fixation, while smaller groups received hemiarthroplasty or total hip arthroplasty. Survival status after discharge was established through telephone contact with family members, allowing the researchers to examine whether a ratio derived from routine laboratory measurements was associated with subsequent mortality. As a retrospective observational study, however, it could not determine whether the ratio itself caused differences in outcomes.

When UHR was analyzed as a continuous variable in a conventional Cox proportional-hazards model, its unadjusted association with mortality was statistically significant at P = 0.0213. That relationship weakened after adjustment for age and sex and was no longer significant in the fully adjusted model, which also accounted for the age-adjusted Charlson Comorbidity Index, coronary heart disease, arrhythmia and dementia. The fully adjusted continuous-UHR result was P = 0.1413. Dividing participants into low, medium and high UHR tertiles produced a similar pattern: crude mortality was 18.00% in the low group, 30.69% in the middle group and 32.04% in the high group, but neither adjusted category comparison nor the adjusted trend test reached statistical significance. The fully adjusted hazard ratio for the high versus low tertile was 1.54, with a 95% confidence interval of 0.84–2.84 and P = 0.1624. These results therefore do not support describing UHR as an independent predictor under a linear or tertile-based parameterization.

Those conventional results motivated the researchers to examine whether a straight-line model was masking a different functional shape. Using restricted cubic splines for visual assessment and an exploratory two-piecewise Cox model, the team estimated an inflection point at a UHR of 166.17 under the study’s micromole-per-liter-to-millimole-per-liter convention. Below that value, each one-unit increase in UHR was associated with a hazard ratio for death of 1.01, with a 95% confidence interval of 1.00–1.03 and P = 0.0326. Above the inflection point, the estimated additional slope was effectively flat and not statistically significant, with P = 0.8050. A likelihood-ratio test comparing the single-slope and two-piecewise models favored the nonlinear specification, P = 0.037. The analysis therefore identified a possible association concentrated within the lower portion of the observed UHR range, rather than a consistent increase in mortality risk across the entire range.

The fitted shape should not be mistaken for proof of a biological threshold. “Plateau” is a description of the model’s estimated curve, not a demonstration that a specific mechanism switches on at 166.17. Nor does the flat slope above that point mean that patients with higher UHR have the same absolute mortality risk as those with low UHR. It means only that, within this dataset, additional increases above the estimated inflection point were not detectably associated with further increases in the modeled hazard. The threshold and both slopes were estimated from the same small cohort, creating scope for overfitting and optimism. For the fully adjusted continuous-UHR model there were approximately 11.7 deaths per regression parameter, while models using tertiles or two UHR slopes had approximately 10.3. Those conventional ratios do not capture the additional uncertainty introduced by choosing an inflection point from the same data.

Groups also differed in ways that complicate simple interpretations of the tertile results. The proportion of men increased from 18.00% in the low-UHR group to 37.62% in the middle group and 46.60% in the high group, although women still slightly outnumbered men in the highest group, 55 to 48. Fracture classification, prevalence of coronary heart disease, time to admission and surgical treatment also varied across tertiles. Time to admission followed a non-monotonic pattern—66.49, 190.73 and 83.06 hours from low to high UHR—so the difference cannot be interpreted as a dose-response relationship or as a consequence of UHR. The higher crude mortality in the highest tertile is compatible with a plateau above the estimated inflection point because a null slope above 166.17 means that additional increases within the higher range were not detectably associated with further risk. It does not erase differences accumulated across lower UHR values. Nevertheless, because the fully adjusted tertile comparison was not significant, UHR cannot be described as an independent predictor on the basis of these data.

UHR is attractive as a candidate marker because it combines two inexpensive measurements already obtained in routine care. The investigators noted that uric acid has been associated in prior research with adverse outcomes in cardiovascular disease, metabolic syndrome and chronic kidney disease, while HDL-C has been linked with vascular functions including anti-inflammatory and antioxidant activity and cholesterol reverse transport. The ratio was proposed as a possible combined indicator of metabolic and inflammatory disturbance accompanying hip fracture and therefore as a marker that might supplement conventional prognostic assessment. However, this study did not measure inflammasome activation, cytokines, oxidative injury or HDL function. Links involving oxidative stress, inflammation, endothelial dysfunction or reduced HDL-related antioxidant capacity remain possible biological explanations rather than demonstrated mechanisms in these patients.

Several limitations constrain how far the findings can be generalized. The cohort came from one trauma center and included 304 participants and 82 deaths, limiting statistical precision and generalizability. UHR was measured only once after admission for an acute fracture. Trauma, fasting status, hydration, renal function, medications and perioperative stress may alter uric acid or HDL-C, so the admission value may not represent a patient’s pre-fracture metabolic state. The analysis also could not adjudicate cardiovascular, infectious, malignant or other causes of death because only all-cause mortality was available. Residual confounding from lifestyle, medication use, renal function, frailty, sarcopenia and socioeconomic conditions remains possible. The study did not evaluate whether UHR adds information beyond established clinical, frailty, muscle, inflammatory or nutritional assessments, and it did not test whether adding the ratio would improve discrimination, calibration or clinical decision-making.

A value of 166.17 is therefore a cohort- and unit-specific estimated inflection point, not a validated clinical benchmark, and patients with values above it should not automatically receive intensified treatment on the basis of UHR alone. The researchers called for prospective multicenter studies to confirm the functional form of the association, repeat UHR measurements after the acute stress period, validate any threshold externally and determine whether UHR adds useful prognostic information beyond established measures. Until then, the result is best understood as hypothesis-generating evidence: an accessible candidate marker with an exploratory nonlinear signal, but no demonstrated independent predictive value for guiding care after hip fracture.

Subject of Research: Association between admission uric acid-to-HDL cholesterol ratio and long-term mortality in older adults after hip fracture surgery

Article Title: Admission uric acid to HDL-C ratio and long-term mortality after hip fracture in older adults: a retrospective cohort study

Article References: Han, S., Fu, Y.-H., Ke, C., & Zhang, B.-F. (2026). Admission uric acid to HDL-C ratio and long-term mortality after hip fracture in older adults: a retrospective cohort study. Frontiers in Medicine, 13, Article 1906596. https://doi.org/10.3389/fmed.2026.1906596

Image Credits: AI Generated

DOI: 10.3389/fmed.2026.1906596

Keywords: hip fracture, uric acid, HDL cholesterol, UHR, older adults, mortality, retrospective cohort, nonlinear association, survival analysis, prognostic biomarker, Admission, uric

The index in question, known as the CHG index, is calculated as the natural logarithm of total cholesterol multiplied by fasting plasma glucose, divided by twice the HDL cholesterol level. Each component captures a different facet of metabolic health. Fasting glucose reflects how well the liver regulates blood sugar and how effectively pancreatic beta cells are functioning. Total cholesterol and HDL cholesterol together describe the lipid environment: high total cholesterol paired with low HDL is the classic signature of atherogenic dyslipidemia, the lipid disturbance that typically accompanies insulin resistance. By multiplying these values together, the index integrates lipid burden, reverse cholesterol transport capacity, and glycemic status into a single number that can be derived from blood tests already performed in virtually every health checkup.

What makes the new research notable is the population it examined. Most studies of metabolic risk indices have included people across all body mass index categories or focused on those who are overweight or obese. Lean individuals have been largely marginalized in metabolic research, precisely because their normal weight is assumed to signal metabolic health. Yet clinicians have long recognized a phenotype called metabolically obese normal weight—people who appear lean on the outside but harbor visceral fat accumulation and peripheral insulin resistance on the inside. Their cardiovascular and atherosclerotic risks can rival those of people with overt obesity, but because conventional risk scoring relies heavily on anthropometric measures like BMI, this population is chronically underidentified.

The research team, led by Junling Ding and Zhimao Cai of Shenzhen Second People’s Hospital, drew on a multicenter retrospective cohort of health examination participants screened between 2010 and 2016 at 32 sites across 11 Chinese cities. From an initial pool of more than 211,000 adults, they applied strict eligibility criteria: participants had to be at least 45 years old, have a BMI between 18.5 and 23.9 kilograms per square meter, and be free of prediabetes and diabetes at baseline. After excluding those with missing or implausible laboratory values, the final analytic cohort comprised 19,981 adults with a mean age of about 56 years, roughly 43 percent of them men. Participants were followed for an average of 3.19 years, during which the researchers tracked new cases of prediabetes, defined as fasting glucose reaching 5.6 millimoles per liter or higher, and self-reported diagnosed diabetes.

The results were unambiguous. In fully adjusted Cox proportional hazards models that accounted for age, sex, blood pressure, BMI, LDL cholesterol, kidney and liver markers, and family history of diabetes, each one-unit increase in the CHG index was associated with a 2.20-fold increase in the hazard of developing prediabetes or diabetes. When participants were divided into quartiles, those in the second, third, and fourth quartiles faced 42 percent, 86 percent, and 91 percent higher risks, respectively, compared with the lowest quartile. Kaplan-Meier survival curves showed the groups diverging early in follow-up, with the highest-quartile group consistently showing the lowest probability of remaining free of dysglycemia.

The most intriguing finding emerged when the researchers used smooth curve fitting and two-piecewise regression to probe the shape of the relationship. Rather than a straight line, the association displayed a clear inflection point at a CHG index value of 5.07. Below that threshold, each unit increase in the index was associated with a staggering 6.39-fold increase in risk. Above it, the association essentially vanished, with a hazard ratio of 1.02 that was statistically indistinguishable from no effect. A log-likelihood ratio test confirmed that the nonlinear model fit the data significantly better than a linear one.

The authors interpret this threshold effect as a possible biological saturation phenomenon. In the early phase of metabolic deterioration, rising fasting glucose, increasing total cholesterol, and falling HDL cholesterol jointly reflect accelerating insulin resistance and progressive beta-cell exhaustion, so each increment in the index corresponds to a disproportionately rapid rise in disease risk. Once metabolic dysregulation passes a critical severity, the system may have already entered a state of advanced decompensation, where further increases in the index no longer translate into additional risk elevation. In other words, the index may be most useful precisely in the window when intervention can still prevent disease—a potentially valuable property for a screening tool.

Subgroup analyses added further nuance. The association was stronger in women than in men, with hazard ratios of 2.65 and 1.77 respectively, and stronger in participants under 60 than in those 60 and older, with hazard ratios of 2.51 and 1.65. The authors suggest that sex differences in body fat distribution, which are well documented and linked to differential cardiometabolic risk, may explain the gender gap, while age-related changes such as sarcopenia, hormonal shifts, and cumulative exposure to multiple risk factors may dilute the relative contribution of the CHG index in older adults. Family history of diabetes did not meaningfully modify the association. A sensitivity analysis using E-values, which quantify how strong an unmeasured confounder would need to be to explain away an observed association, yielded a value of 3.82, suggesting the findings are reasonably robust.

Mechanistically, the index makes physiological sense. Elevated fasting glucose directly signals impaired hepatic glucose homeostasis and declining beta-cell function. In insulin-resistant states, increased hepatic de novo lipogenesis and very-low-density lipoprotein secretion, combined with reduced reverse cholesterol transport, produce exactly the pattern of raised total cholesterol and reduced HDL that pushes the index upward. These lipid abnormalities not only promote atherosclerosis but also exacerbate pancreatic lipotoxicity, further compromising beta-cell function. Chronic low-grade inflammation and oxidative stress, which are intertwined with both dyslipidemia and hyperglycemia, may mediate part of the pathway, and the authors note that related molecular mechanisms—including sirtuin proteins, inflammatory cascades, and programmed cell death pathways—are increasingly implicated in diabetic complications.

The study has limitations that temper enthusiasm. As a retrospective observational cohort, it cannot establish causality, and because the population was exclusively Chinese, generalizability to other ethnic groups remains uncertain. Residual confounding from unmeasured factors such as diet, physical activity, and socioeconomic status cannot be excluded, and smoking and drinking data were missing for more than 76 percent of participants, preventing their inclusion in adjusted models. The average follow-up of just over three years may also miss longer-term risk trajectories. Still, the core message is compelling: a number that costs almost nothing to compute from routine blood work may reveal hidden metabolic vulnerability in lean adults whom conventional screening would overlook. The authors call for large prospective cohorts to confirm the findings and establish causality, but if the results hold, the CHG index could become a practical tool for catching prediabetes early in a population that has too often been told its normal weight means it has nothing to worry about.

Subject of Research: The nonlinear association between the CHG metabolic index and incident prediabetes and diabetes in normal-weight middle-aged and older Chinese adults

Article Title: Nonlinear association of cholesterol, high-density lipoprotein, and glucose index with the risk of prediabetes and diabetes in normal-weight middle-aged and older Chinese adults: a multicenter retrospective cohort study

Article References: Ding, J., Cai, Z., Wang, X., Qin, L., & Chen, W. (2026). Nonlinear association of cholesterol, high-density lipoprotein, and glucose index with the risk of prediabetes and diabetes in normal-weight middle-aged and older Chinese adults: a multicenter retrospective cohort study. Frontiers in Nutrition, 13, Article 1949954. https://doi.org/10.3389/fnut.2026.1949954

Image Credits: AI Generated

DOI: 10.3389/fnut.2026.1949954

Keywords: CHG index, prediabetes, diabetes, normal weight, insulin resistance, HDL cholesterol, fasting glucose, cohort study, nonlinear association, threshold effect, metabolic health, China

The study, a retrospective cohort analysis of 1,063 singleton pregnancies delivered between January and December 2024, set out to test whether TyHGB could serve as an early-warning biomarker for GDM. The index is an extension of the well-known triglyceride-glucose (TyG) index, a widely used surrogate for insulin resistance. TyHGB adds two more ingredients to the TyG formula: HDL cholesterol, the anti-inflammatory lipoprotein fraction involved in lipid regulation, and pre-pregnancy body mass index, a measure of systemic adiposity. Specifically, TyHGB is calculated as the ratio of triglycerides to HDL cholesterol, plus 0.7 times fasting plasma glucose in millimoles per liter, plus 0.1 times pre-pregnancy BMI in kilograms per square meter. Each component captures a different facet of the metabolic dysfunction that underlies GDM, which shares its core pathology — pancreatic beta-cell dysfunction and increased insulin resistance — with type 2 diabetes.

All participants underwent first-trimester blood testing before 14 weeks of gestation, with fasting venous samples analyzed for liver enzymes, total cholesterol, triglycerides, LDL and HDL cholesterol, fasting plasma glucose, and glycated hemoglobin. The women were then screened for GDM at 24 to 28 weeks using the standard 75-gram oral glucose tolerance test (OGTT), with diagnosis based on the International Association of the Diabetes in Pregnancy Study Groups criteria: fasting glucose of 92 mg/dL or higher, one-hour post-load glucose of 180 mg/dL or higher, or two-hour post-load glucose of 153 mg/dL or higher. Women with pre-existing type 1 or type 2 diabetes, multiple pregnancies, endocrine disorders, chronic hypertension, and other major complications were excluded to isolate the effect of the index in a broadly healthy obstetric population.

Of the 1,063 women enrolled, 190 — or 17.87 percent — were newly diagnosed with GDM. The median maternal age was 31 years, and the median pre-pregnancy BMI was 26.17 kg/m². When the researchers divided the cohort into tertiles based on TyHGB values, a striking gradient emerged: GDM prevalence rose from 6.59 percent in the lowest tertile to 18.72 percent in the middle tertile and 28.09 percent in the highest tertile. Women in the top tertile also carried higher triglycerides, LDL cholesterol, liver enzymes, fasting glucose, and pre-pregnancy BMI, along with lower HDL cholesterol, consistent with a broader pattern of metabolic dysregulation.

To determine whether TyHGB was an independent predictor rather than a proxy for other risk factors, the team built a series of multivariable logistic regression models with increasing levels of adjustment. In the fully adjusted model — controlling for maternal age, assisted reproductive conception, gravidity, total cholesterol, LDL cholesterol, alanine aminotransferase, aspartate aminotransferase, and glycated hemoglobin — each one-unit increase in TyHGB was associated with a 1.62-fold increase in the odds of GDM (95 percent confidence interval: 1.29 to 2.03). Compared with women in the lowest tertile, those in the highest tertile had nearly four times the odds of developing GDM (odds ratio 3.97, 95 percent CI: 2.19 to 7.21), and the dose-response relationship across tertiles was statistically significant, indicating a steady rise in risk with rising index values.

The diagnostic performance of TyHGB was then benchmarked against conventional markers using receiver operating characteristic (ROC) analysis. The area under the ROC curve (AUC) for TyHGB was 0.675 (95 percent CI: 0.646 to 0.703), with an optimal cut-off value of 5.995 determined by Youden’s index. At this threshold, the index achieved a sensitivity of 66.32 percent — correctly flagging about two-thirds of women who went on to develop GDM — and a specificity of 63.12 percent. Crucially, TyHGB outperformed maternal age (AUC 0.596), pre-pregnancy BMI (AUC 0.610), fasting plasma glucose (AUC 0.618), and the TyG index alone (AUC 0.615), suggesting that the composite formula extracts more predictive signal from the same routine blood draw than any single component could.

Subgroup analyses revealed an important nuance about who benefits most from this early signal. The association between TyHGB and GDM remained robust among women under 35 years of age, those with pre-pregnancy BMI below 25, and women who conceived spontaneously. However, in women with pre-pregnancy BMI of 25 or higher, the association was attenuated and no longer statistically significant, with a statistically significant interaction between BMI and the index. The researchers interpret this pattern as evidence that in low-risk populations — where obesity and advanced maternal age do not dominate the risk picture — subtle early glycemic and lipid disturbances are often missed by traditional screening tools, and TyHGB may fill that gap. In women already carrying strong conventional risk factors, those factors may mask the incremental value of the new index.

The biological rationale for TyHGB rests on the central role of insulin resistance in GDM. The TyG component reflects the interplay between blood glucose and triglyceride metabolism, both of which are disrupted when cells become less responsive to insulin. HDL cholesterol participates in anti-inflammatory and lipid regulatory processes, and impaired HDL function can aggravate lipotoxicity and worsen insulin resistance, further destabilizing glucose homeostasis. Pre-pregnancy BMI captures systemic adiposity, which a large-scale meta-analysis of more than 960,000 pregnant women linked to a 4 percent increase in GDM incidence per unit of BMI. By combining these parameters into a single number, TyHGB compensates for the limited accuracy of any one marker alone, and previous validation studies in Chinese and Korean populations have reported similar associations, with odds ratios ranging from 1.88 to 2.09.

The authors acknowledge several limitations. As a single-center retrospective study, the findings require external validation in larger prospective cohorts before broad clinical implementation. The study lacked data on lifestyle and socioeconomic factors such as diet, physical activity, sleep quality, and psychological status, which could influence glucose metabolism. TyHGB was measured only once, in early pregnancy, so dynamic metabolic changes across gestation were not captured. The cohort included only singleton pregnancies, and information on glucose-interfering medications was not systematically recorded. Moreover, with a moderate AUC of 0.675, TyHGB cannot serve as a standalone diagnostic test; its role is as an auxiliary tool for early risk stratification rather than a replacement for the OGTT.

Even with those caveats, the implications are significant. The current standard for GDM diagnosis — the OGTT performed at 24 to 28 weeks — arrives late in pregnancy, leaving little window for preventive intervention before complications can develop, and imposes considerable time and economic burdens on pregnant women. A simple index calculable from blood work already obtained in the first trimester could allow clinicians to flag high-risk patients months earlier, enabling targeted surveillance, individualized risk stratification, and proactive lifestyle or pharmacological measures at a stage when they may still alter the disease trajectory. Given that GDM now affects roughly 15 percent of pregnancies worldwide, with prevalence in China around 14.8 percent and regional rates ranging from 10.5 percent in Changsha to 19.7 percent in Beijing, a low-cost early screening tool could have substantial public health impact. The TyHGB index, the authors conclude, represents a promising, cost-effective, and widely applicable addition to routine antenatal screening protocols — one that could help lower GDM incidence and ultimately improve outcomes for both mothers and their babies.

Subject of Research: A composite metabolic index for predicting gestational diabetes risk in early pregnancy

Article Title: TyG indicator–TyHGB and the risk of gestational diabetes mellitus: a retrospective cohort study

Article References: Li, X., Bu, W., Liang, W., Ji, Z., Chen, Y., Xuan, Y., & Hu, X. (2026). TyG indicator–TyHGB and the risk of gestational diabetes mellitus: a retrospective cohort study. Frontiers in Nutrition, 13, Article 1967930. https://doi.org/10.3389/fnut.2026.1967930

Image Credits: AI Generated

DOI: 10.3389/fnut.2026.1967930

Keywords: gestational diabetes, TyHGB index, insulin resistance, pregnancy, first trimester screening, triglycerides, HDL cholesterol, fasting glucose, body mass index, biomarker, oral glucose tolerance test, maternal health

The research, published in Frontiers in Allergy, examined perimenopausal women aged 45 to 60 years and compared them against patients with chronic non-fungal sinusitis, a control group that shares many symptoms but lacks the fungal mass at the heart of the disease. The team focused on two metabolic markers that have become central to modern cardiovascular and endocrine research: high-density lipoprotein cholesterol, the so-called good cholesterol, and a composite index known as TyG-BMI, which combines the triglyceride-glucose index with body mass index to capture insulin resistance and overall metabolic burden. Both markers are inexpensive to measure, which makes any association with a fungal sinus disease immediately interesting from a screening standpoint.

Fungal ball sinusitis, sometimes called fungus ball or aspergilloma of the paranasal sinuses, belongs to the non-invasive category of fungal sinus disease. Unlike invasive fungal infections that threaten immunocompromised patients, a fungal ball grows slowly within a blocked sinus cavity, forming a compact tangle of hyphae that surgeons must physically remove. The condition typically affects one sinus, most often the maxillary sinus, and produces chronic nasal obstruction, foul discharge, facial pressure and, in some cases, the sensation of a foreign body deep in the cheek. Because its symptoms mimic ordinary chronic rhinosinusitis, diagnosis frequently arrives only when computed tomography reveals characteristic calcifications or when the removed tissue is examined under a microscope.

The study design was straightforward but carefully targeted. The researchers enrolled fungal ball sinusitis patients treated at their single center between 2015 and 2025, then narrowed the analysis to perimenopausal women aged 45 to 60, using patients with chronic non-fungal sinusitis as the comparison group. Biochemical indicators were compared between the two groups, participants were sorted into quartiles based on their TyG-BMI values, and logistic regression models were used to identify which factors independently predicted fungal ball disease. Receiver operating characteristic curves, a standard tool for judging diagnostic performance, were then applied to test whether the metabolic markers could actually predict the condition.

The demographic findings alone tell a compelling story. Across the decade of cases, fungal ball sinusitis showed a steadily increasing trend, and the patient population skewed heavily toward middle-aged and elderly individuals. Women made up 63.96 percent of cases compared with 36.04 percent of men, and the peak age of female illness clustered tightly between 45 and 60 years, precisely the window of perimenopause. This concentration is exactly the kind of pattern that makes researchers suspect hormonal and metabolic mechanisms rather than simple exposure, since perimenopause is accompanied by falling estrogen levels, redistribution of body fat, rising insulin resistance and deteriorating lipid profiles.

When the researchers compared blood values between the two groups, the differences were clear. Women with fungal ball sinusitis had significantly lower HDL cholesterol levels and significantly higher TyG and TyG-BMI values than women with chronic non-fungal sinusitis. The relationship held up in a dose-response pattern: as TyG-BMI quartiles rose, HDL cholesterol fell progressively, and the prevalence of fungal ball sinusitis climbed in step. In statistical terms, the trend was significant at P less than 0.05, meaning the probability that these gradients arose by chance is small.

The logistic regression analysis then isolated the two markers as independent risk factors, each holding its predictive power after accounting for the other. Higher HDL cholesterol was protective: each unit increase was associated with an odds ratio of 0.482, with a 95 percent confidence interval of 0.282 to 0.823 and a P value of 0.008, meaning women with better HDL levels had roughly half the odds of fungal ball disease. Higher TyG-BMI, by contrast, carried risk, with an odds ratio of 1.192 per quartile step, a 95 percent confidence interval of 1.008 to 1.409 and a P value of 0.04. In plain language, the more insulin-resistant and metabolically burdened a woman was, the more likely she was to harbor a fungal ball in her sinuses, and the healthier her cholesterol profile, the lower that likelihood became.

One finding deserves careful interpretation. When the researchers combined TyG-BMI and HDL cholesterol into a single predictive model and tested it with ROC analysis, the combined model showed only limited predictive value for fungal ball sinusitis. This means the markers are statistically associated with the disease and may illuminate its biology, but they cannot yet serve as a reliable diagnostic test in the clinic. Association is not prediction, and a screening tool built on these numbers would miss too many cases and flag too many healthy women to be useful on its own. The authors instead frame their results as a call for targeted metabolic monitoring and early intervention, positions that could plausibly lower fungal ball risk if the underlying mechanisms hold up in future work.

What might those mechanisms be? The study was observational and retrospective, so it cannot prove causation, but the biology offers several plausible threads. Insulin resistance, which TyG-BMI captures, is known to alter mucosal immunity, promote low-grade systemic inflammation and change the composition of airway secretions, all of which could make the sinus environment more hospitable to fungal colonization. HDL cholesterol, meanwhile, does far more than ferry lipids; it modulates inflammation and immune cell function, and low HDL is a recognized hallmark of metabolic syndrome. Falling estrogen during perimenopause worsens both insulin resistance and lipid profiles, which could explain why the disease concentrates in this demographic window. A clogged, inflamed, metabolically altered sinus cavity may simply be easier for ambient fungal spores to colonize and harder for the immune system to clear.

The clinical takeaway is that fungal ball sinusitis should no longer be viewed as a purely local problem of the nose. For perimenopausal women with stubborn unilateral sinus symptoms, especially those with known metabolic risk, the study suggests that clinicians may want to look at the whole metabolic picture rather than treating the sinus in isolation. The rising annual incidence recorded at this single center over ten years adds urgency, because a disease that grows quietly in midlife women is a disease that health systems will increasingly encounter. Larger multicenter prospective studies will be needed to confirm the association, test whether metabolic intervention actually reduces risk, and determine whether TyG-BMI and HDL cholesterol can eventually earn a place in clinical prediction models. For now, the message is that the sinuses and the metabolism are more connected than anyone suspected, and the blood panel drawn for a routine midlife checkup may one day help flag the women who need a closer look up their nasal passages.

Subject of Research: Metabolic risk factors for fungal ball sinusitis in perimenopausal women

Article Title: Metabolic risk factors for fungal ball sinusitis in perimenopausal women

Article References: Wang, S.-Y., Xu, W., Liu, Y.-X., Jiang, L., Xu, Y., Teng, F.-Y., Hu, X.-Y., & Li, H.-X. (2026). Metabolic risk factors for fungal ball sinusitis in perimenopausal women. Frontiers in Allergy, 7, 1900638. https://doi.org/10.3389/falgy.2026.1900638

Image Credits: AI Generated

DOI: 10.3389/falgy.2026.1900638

Keywords: fungal ball sinusitis, perimenopausal women, TyG-BMI, HDL cholesterol, insulin resistance, chronic rhinosinusitis, metabolic syndrome, Frontiers in Allergy, retrospective study, sinus disease, estrogen, logistic regression

The study, led by Madhulika L. Mahashabde and Sai Karthik Guniganti of the Department of General Medicine at Dr. D.Y. Patil Vidyapeeth in Pune, enrolled 110 adults with type 2 diabetes and compared four candidate markers head to head. The prespecified composite outcome captured the presence of at least one of the three major microvascular complications of diabetes: diabetic retinopathy, diabetic kidney disease and diabetic peripheral neuropathy. Among the participants, 64, or 58.2 percent, had at least one such complication. The researchers then asked a deceptively simple question with profound clinical implications: which of these four blood-based numbers best separates patients with microvascular damage from those without it?

The answer, measured by the area under the receiver operating characteristic curve, or AUC, was remarkable. The triglyceride-glucose index, known as TyG, achieved an AUC of 0.993 with a 95 percent confidence interval stretching from 0.984 to 1.000, a figure so close to perfect discrimination that the authors themselves flag it as unusually high. Glycated haemoglobin, the gold-standard marker of long-term blood sugar control, reached 0.971. The triglyceride-to-HDL-cholesterol ratio followed at 0.959. The homeostatic model assessment of insulin resistance, HOMA-IR, which requires a fasting insulin measurement and has long been considered the reference standard for quantifying insulin resistance in research settings, trailed at 0.810.

Statistical rigour underpinned these comparisons. The team used DeLong confidence intervals for each AUC and then applied DeLong’s test for all six pairwise comparisons, adjusting the resulting p-values with the Holm-Bonferroni method to control the family-wise error rate. After this adjustment, TyG, TG/HDL-C and HbA1c each outperformed HOMA-IR with adjusted p-values below 0.001, while no statistically significant differences separated the three leading markers from one another. In other words, the two insulin-free surrogates, calculated from fasting biochemistry that costs a fraction of an insulin assay, performed at least as well as the established glycemic marker and clearly better than the insulin-based index they were designed to replace.

The biological logic behind these indices is worth unpacking. Insulin resistance drives a characteristic lipid pattern: the liver pumps out more very-low-density lipoprotein particles, triglycerides rise, and high-density lipoprotein cholesterol falls. The TyG index captures this by combining fasting triglycerides with fasting plasma glucose in a logarithmic formula, reflecting the fact that insulin-resistant tissue allows both circulating fats and sugars to accumulate. The TG/HDL-C ratio distils the same physiology into a single fraction. Because insulin resistance is increasingly recognised as a contributor to microvascular complications, including retinopathy, nephropathy and neuropathy, these surrogates may be flagging the underlying metabolic milieu that damages small vessels, rather than merely the degree of glycemic excursion that HbA1c measures.

Exploratory cut-offs emerged from the analysis using the Youden index, which maximises the sum of sensitivity and specificity. For TyG, the cut-off was 9.23 or above, at which the index showed 93.8 percent sensitivity and 100 percent specificity for identifying prevalent microvascular complications. For TG/HDL-C, the exploratory threshold was 3.40 or above. These figures, if they hold up under external validation, would mean a single fasting blood panel could triage patients for complication screening without waiting for an insulin assay or even a glycated haemoglobin result.

Beyond discrimination, the researchers examined whether these markers add genuine incremental value to existing models. Multivariable associations were assessed using Firth’s penalised-likelihood regression, a technique designed for small samples where conventional maximum-likelihood logistic regression can produce unstable or infinitely large coefficient estimates. Each one-standard-deviation rise in TyG and TG/HDL-C remained significantly associated with the composite outcome after Firth penalisation, with p-values of 0.002 and 0.003 respectively. Calibration was assessed using the intercept, slope and Brier score, and decision curve analysis explored the net benefit of using each marker at various threshold probabilities. Adding TyG to a base model containing HbA1c and HOMA-IR yielded an integrated discrimination improvement, or IDI, of 0.219, indicating that TyG carries information about microvascular complications that the established markers do not fully capture.

The authors are careful, and rightly so, about the limits of what this study can claim. The unusually high AUCs, particularly TyG’s 0.993, may reflect the disease spectrum of a tertiary-care referral population, where patients tend to have more advanced disease and more pronounced metabolic derangement than the general diabetic population. The researchers explicitly state that these figures should be regarded as upper bounds rather than realistic expectations of performance in community settings. The cross-sectional design means the study identifies prevalent complications at a single point in time; it makes no claim of predictive or screening performance, and the exploratory cut-offs require prospective, multicentre external validation before any triage use.

India carries a disproportionate share of the global diabetes burden, and microvascular complications, including blindness, kidney failure requiring dialysis and disabling neuropathy, impose enormous human and economic costs. If the Pune findings replicate in larger, multicentre, prospective cohorts, the implications for resource-constrained health systems could be transformative. A fasting blood panel already drawn for routine lipid and glucose monitoring could double as a complication triage tool, flagging patients who need retinal imaging, urinary albumin-to-creatinine ratio testing or nerve conduction studies, without adding a single new test to the workflow.

For now, the study stands as a provocative proof of concept from Western India: two numbers calculated from tests already sitting in every clinic’s biochemistry report, the triglyceride-glucose index and the triglyceride-to-HDL-cholesterol ratio, matched glycated haemoglobin and beat the insulin-based HOMA-IR in identifying the microvascular fingerprints of type 2 diabetes. The road from exploratory cut-offs to validated triage tools runs through prospective validation, but the destination, a cheaper, faster and more accessible way to spot diabetes’ most feared complications, is one worth watching closely.

Subject of Research: Triglyceride–glucose index and triglyceride/HDL-cholesterol ratio versus HbA1c and HOMA-IR for identifying microvascular complications in type 2 diabetes: a cross-sectional comparative diagnostic accuracy study from Western India

Article Title: Triglyceride–glucose index and triglyceride/HDL-cholesterol ratio versus HbA1c and HOMA-IR for identifying microvascular complications in type 2 diabetes: a cross-sectional comparative diagnostic accuracy study from Western India

Article References: Mahashabde, M. L., & Guniganti, S. K. (2026). Triglyceride–glucose index and triglyceride/HDL-cholesterol ratio versus HbA1c and HOMA-IR for identifying microvascular complications in type 2 diabetes: a cross-sectional comparative diagnostic accuracy study from Western India. BMC Endocrine Disorders. https://doi.org/10.1186/s12902-026-02674-4

Image Credits: AI Generated

DOI: 10.1186/s12902-026-02674-4

Keywords: Type 2 Diabetes, Insulin Resistance, TyG Index, HbA1c, Diagnostic Accuracy, Diabetic Complications, Clinical Research, Endocrinology, Triglyceride, glucose, index, HDL-cholesterol

The research, led by Huibao Lyu, Yiting Zhang, and colleagues at Guangdong Medical University and Jieyang People’s Hospital in China, focused on the triglyceride-high-density cholesterol-glucose-body index, abbreviated as TyHGB. This index weaves together four parameters that virtually every clinic already measures: triglycerides, high-density lipoprotein cholesterol, fasting plasma glucose, and body mass index. Rather than viewing each value in isolation, the index integrates them into a single score that captures the intertwined disturbances in blood fat handling, sugar metabolism, and body composition that precede overt metabolic disease.

The study team set out to answer a question that had never been formally addressed: does a higher TyHGB score predict the future development of impaired fasting glucose, the critical prediabetic stage defined by fasting glucose between 5.6 and 6.9 millimoles per liter, in adults whose baseline glucose and lipid profiles are entirely normal? To find out, the researchers conducted a secondary retrospective analysis of a multicenter cohort, drawing on a fully anonymized, open-access dataset from the Dryad repository originally collected under ethical approval from the Rich Healthcare Group Ethics Review Board.

The scale of the analysis is striking. The investigators included 57,097 Chinese adults who were initially free of impaired fasting glucose, all of whom had baseline fasting plasma glucose below 5.6 millimoles per liter and lipid profiles below dyslipidemia thresholds. In other words, every participant started the study in the metabolic safe zone by conventional standards. The researchers calculated each person’s baseline TyHGB index from triglycerides, high-density lipoprotein cholesterol, fasting glucose, and body mass index, then tracked who developed impaired fasting glucose over time.

During a median follow-up of 2.97 years, 5,491 participants, or 9.62 percent of the cohort, developed incident impaired fasting glucose. That means nearly one in ten adults with normal baseline labs crossed into the prediabetic range within roughly three years. The central finding was unambiguous: a higher TyHGB index was significantly associated with an elevated risk of this transition. In the fully adjusted Cox proportional hazards model, each 1-unit increase in the TyHGB index carried a hazard ratio of 2.41, with a 95 percent confidence interval of 2.30 to 2.52, meaning the risk more than doubled with every unit of the index.

The quartile analysis made the gradient even more vivid. Compared with participants in the lowest quartile of the TyHGB index, those in the highest quartile faced a hazard ratio of 5.85, with a 95 percent confidence interval of 5.26 to 6.51. Adults in the top quarter of the index were nearly six times more likely to develop impaired fasting glucose than those in the bottom quarter, despite all of them beginning the study with glucose and lipid values that no clinician would flag as abnormal. The association held across prespecified subgroups, although the effect sizes varied across several clinical strata, and the results remained robust in sensitivity analyses designed to test the stability of the primary finding.

One of the most technically interesting aspects of the study involved the shape of the relationship. The researchers employed restricted cubic splines, a flexible modeling technique that allows the association between an exposure and an outcome to bend rather than forcing it into a straight line. The spline analysis revealed a significant nonlinear, piecewise relationship, with the test for nonlinearity yielding a p value below 0.001. The curve showed a threshold inflection point at a TyHGB index of 6.97. Below this value, the association between the index and impaired fasting glucose risk was comparatively gentle; above it, the risk climbed steeply. Piecewise models confirmed this threshold effect, suggesting that the index may behave less like a linear dial and more like a tripwire that marks a point of accelerating metabolic deterioration.

The biological logic behind the TyHGB index rests on the concept of insulin resistance, the metabolic state in which tissues respond sluggishly to insulin and the body compensates by pumping out more of the hormone. Elevated triglycerides combined with reduced high-density lipoprotein cholesterol form a classic lipid signature of insulin resistance, even when both values remain within the normal laboratory range. Fasting glucose reflects how well the insulin-glucose feedback loop is holding, and body mass index captures the adiposity that drives much of the metabolic disturbance. By multiplying these components together, the index amplifies the signal of subclinical metabolic dysfunction that any single parameter would miss. The study team also used the triglyceride-glucose index and its body mass index extension, known as TyG-BMI, as conceptual building blocks, and the TyHGB index represents a refinement that incorporates the protective high-density lipoprotein fraction as well.

The methodological rigor of the analysis deserves attention. The investigators adhered to the Strengthening the Reporting of Observational Studies in Epidemiology guidelines, used multivariate imputation by Chained Equations to handle missing data, checked multicollinearity with variance inflation factors, and validated the proportional hazards assumption underlying the Cox models. They also ran logistic regression models alongside the survival analyses to quantify the association in odds terms, and conducted subgroup and sensitivity analyses to evaluate the robustness of the primary associations. The study was exempt from further institutional review board approval because it used a fully anonymized public dataset, and the authors declared no competing interests and no use of generative artificial intelligence in preparing the manuscript.

The authors are careful about what their findings do and do not establish. A higher TyHGB index was associated with incident impaired fasting glucose among Chinese adults with normal baseline fasting glucose and lipid levels, but whether the index provides additional clinical value beyond conventional risk factors requires prospective validation and formal predictive-performance assessment, including receiver operating characteristic analysis of the area under the curve. The study population was Chinese, the follow-up was under three years, and the design was observational, so causation cannot be inferred. Still, the implications are compelling for a health system that routinely measures all four components of the index at negligible cost. If future prospective studies confirm the threshold behavior observed here, the TyHGB index could become a routine early-warning score, identifying adults whose normal lab reports conceal an accelerating metabolic risk long before their fasting glucose crosses the prediabetic line.

Subject of Research: Metabolic Disease

Article Title: Triglyceride-high-density cholesterol-glucose-body index and risk of impaired fasting glucose in normolipidemic adults: a secondary analysis of a multicenter cohort

Article References: Lyu, H., Zhang, Y., Lu, Y., Lin, R., Luo, Z., Li, S., Zhang, H., Yang, D., He, Q., & Zhang, L. (2026). Triglyceride-high-density cholesterol-glucose-body index and risk of impaired fasting glucose in normolipidemic adults: a secondary analysis of a multicenter cohort. BMC Endocrine Disorders. https://doi.org/10.1186/s12902-026-02667-3

Image Credits: AI Generated

DOI: 10.1186/s12902-026-02667-3

Keywords: TyHGB index, impaired fasting glucose, prediabetes, insulin resistance, triglycerides, HDL cholesterol, fasting plasma glucose, body mass index, cohort study, metabolic syndrome, normolipidemic adults, risk prediction

The research, published in Physiological Reports, examined 49 healthy females aged 18 to 45 years, dividing them into three groups: those with natural menstrual cycles, those taking second-generation combined oral contraceptive pills, and those on third-generation formulations. The findings were striking. Fasting glucose concentrations were approximately 10 percent higher in second-generation pill users and roughly 12.5 percent higher in third-generation users compared to naturally cycling women. Even more dramatic, fasting triglycerides were elevated by 56 to 70 percent in pill users relative to their naturally cycling counterparts. These are not trivial differences for a population of young, healthy, normal-weight women.

What makes this study particularly valuable is the rigor with which the researchers controlled for variables that have plagued previous investigations. Earlier studies on oral contraceptives and metabolism have produced wildly inconsistent results—some reporting benefits, others harm, and still others no effect at all. The McMaster team identified several reasons for this confusion. Many prior studies failed to account for the phase of the pill cycle or menstrual cycle at which blood samples were drawn. Others compared short-term users to long-term users without accounting for the body’s adaptation over time. And critically, several lacked a proper control group of naturally cycling individuals, making it impossible to disentangle the effects of the pill from natural hormonal variation.

To address these methodological gaps, the researchers implemented what they describe as rigorous temporal controls. Participants attended two laboratory visits timed to coincide with their low-hormone and high-hormone phases. For naturally cycling women, this meant the early follicular phase (days 3 to 7) and the mid-luteal phase (approximately 7 days after ovulation, confirmed with at-home ovulation kits). For pill users, visits were scheduled during the placebo week and during the third week of active pill use—the highest hormone week for those on triphasic formulations. Blood samples were collected in a fasted state at consistent times of day, and all participants underwent dual-energy X-ray absorptiometry (DXA) scans to assess body composition with precision.

The results extended beyond glucose and triglycerides. The researchers also found that appendicular lean mass index—a measure of skeletal muscle mass in the arms and legs normalized to height—was approximately 10 percent lower in both pill-user groups compared to naturally cycling women. However, when lean mass was expressed as a percentage of total body mass rather than height, this difference disappeared, suggesting that the naturally cycling group may simply have had larger and leaner lower bodies rather than a fundamentally different muscle distribution. Leg lean mass also trended toward being lower in pill users, though this did not reach statistical significance.

One of the most intriguing findings emerged from an exploratory sub-analysis. When all participants were pooled into a single group, the researchers observed a moderate negative correlation between appendicular lean mass index and fasting glucose concentrations—but only during the high-hormone phase. This suggests that skeletal muscle mass may play a more active role in glucose regulation during certain hormonal contexts than previously appreciated. Skeletal muscle is responsible for as much as 75 percent of glucose uptake from the bloodstream following a carbohydrate-containing meal, making it a critical player in metabolic health. Previous research has shown that lower muscle mass predicts impaired fasting glucose in elderly women, and the current findings hint that this relationship may extend to younger populations under specific hormonal conditions.

The mechanisms behind these metabolic differences likely involve the synthetic estrogen ethinyl estradiol, which is contained in both second- and third-generation oral contraceptives. Endogenous 17β estradiol—the naturally produced form of estrogen—plays a beneficial role in energy metabolism. It facilitates insulin secretion, stimulates glucose uptake from the bloodstream, reduces hepatic glucose release, promotes the shift from lipid storage to lipid oxidation, and lowers circulating triglyceride concentrations. Crucially, chronic exposure to ethinyl estradiol dramatically suppresses the body’s own estrogen production. The researchers previously confirmed that circulating 17β estradiol concentrations were significantly lower in both pill-user groups compared to naturally cycling women during the high-hormone phase. It is therefore plausible that pill users simply had less natural estrogen available to perform these metabolic protective functions.

The divergence between pill generations adds another layer of complexity. Third-generation users had approximately 40 percent higher HDL cholesterol concentrations compared to second-generation users, and there was a trend toward a lower total cholesterol to HDL ratio in the third-generation group. This difference likely relates to the type of progestin used in each formulation. Second-generation pills contain androgenic progestins that may antagonize the lipid effects of ethinyl estradiol, while the less androgenic progestins in third-generation pills may instead enhance them. This finding underscores the importance of distinguishing not just between pill users and non-users, but between different generations and formulations of the pill itself.

Importantly, the researchers caution that the magnitude of these differences, while statistically significant, remains modest in absolute terms. Average fasting glucose in all three groups remained well below the clinical threshold for concern, and only one participant across the entire study met the criteria for metabolic syndrome. For young, healthy, normal-weight women, the pill is unlikely to meaningfully increase the risk of developing metabolic disease. However, the researchers note that these subtle shifts could become clinically relevant for individuals with preexisting risk factors. A woman whose fasting glucose sits at 5.1 millimoles per liter before starting the pill, for example, could cross the threshold into the elevated range with the kind of increase observed in this study.

As metabolic syndrome rates continue to rise worldwide—particularly among women aged 18 to 45, the demographic most likely to use oral contraceptives—these findings carry significant public health implications. They also suggest that researchers may need to reconsider how they design studies involving female participants. Rather than excluding pill users to control for hormonal variability, the authors propose that expanding eligibility criteria to include both naturally cycling women and pill users could actually increase female participation in physiological research while improving the relevance and generalizability of the results. Future work, they note, should also examine how newer long-acting hormonal contraceptives, such as hormonal intrauterine devices, influence metabolism and body composition, as their popularity has surged over the past decade.

Subject of Research: The effects of combined oral contraceptive pills on fasting glucose, lipid metabolism, and body composition in young healthy females

Article Title: Elevated fasting glucose and triglycerides in combined oral contraceptive users compared to naturally cycling females

Article References: Karaguesian, C., Williams, J. S., MacDonald, M. J., & Bell, K. E. (2026). Elevated fasting glucose and triglycerides in combined oral contraceptive users compared to naturally cycling females. Physiological Reports, 14(19), Article e71135. https://doi.org/10.14814/phy2.71135

Image Credits: AI Generated

DOI: 10.14814/phy2.71135

Keywords: oral contraceptives, fasting glucose, triglycerides, metabolic syndrome, estrogen, body composition, HDL cholesterol, insulin resistance, menstrual cycle, women's health, DXA, skeletal muscle

The study, led by Hezhi Wen and colleagues at the Health Management Center of the Second Affiliated Hospital of Zhejiang University School of Medicine, drew on 16,572 adults who underwent at least two consecutive annual health examinations between 2022 and 2025. All participants had complete baseline measurements of serum uric acid and HDL cholesterol, and none showed evidence of carotid artery lesions on baseline ultrasound. The researchers calculated UHR by dividing serum uric acid in micromoles per liter by HDL cholesterol in millimoles per liter, then tracked who developed carotid intima-media thickening or plaque during follow-up.

The biological logic behind the ratio is elegant. Uric acid, the terminal product of purine metabolism, promotes atherogenesis through oxidative stress, activation of the NLRP3 inflammasome, endothelial dysfunction, and proliferation of vascular smooth muscle cells. HDL cholesterol counteracts these processes through reverse cholesterol transport, antioxidant activity, and anti-inflammatory signaling. Because the two components push vascular health in opposite directions, the ratio between them may capture the net balance between oxidative-inflammatory burden and lipoprotein-mediated vascular protection as a single number.

Over the follow-up period, 4,454 incident carotid artery lesions occurred. In the fully adjusted Cox proportional hazards model, which accounted for age, sex, body mass index, systolic and diastolic blood pressure, fasting blood glucose, triglycerides, total cholesterol, creatinine, and estimated glomerular filtration rate, each one-standard-deviation increment in baseline UHR was independently associated with a 6 percent higher hazard of incident carotid lesions (hazard ratio 1.06, 95 percent confidence interval 1.01 to 1.11; p = 0.015). Restricted cubic spline analysis showed no significant departure from linearity once confounding was addressed, and the association survived Winsorization at alternative percentiles, exclusion of first-year events to minimize reverse causation, and bootstrap internal validation with 1,000 resamples.

The dose-response relationship differed from the J-shaped or U-shaped patterns often reported for serum uric acid alone in clinical populations. In this general health examination cohort, the adjusted curve showed a modest protective trend at low UHR values, followed by a progressive rise above the median, reaching a hazard ratio of approximately 1.20 at the upper extreme of the observed distribution. The authors attribute the absence of a J-shape to the cohort’s rigorous exclusion of prevalent cardiovascular disease and preserved kidney function, which means low UHR here likely reflects favorable metabolic health rather than cachexia, malnutrition, or xanthine oxidase inhibitor therapy.

Exploratory sex-stratified analyses revealed a striking asymmetry. Among male participants, the association remained statistically significant (hazard ratio 1.07, 95 percent confidence interval 1.02 to 1.12; p = 0.010), but among females it vanished entirely (hazard ratio 0.98, 95 percent confidence interval 0.93 to 1.04; p = 0.524). Yet the formal test for a multiplicative UHR-by-sex interaction did not reach significance (p = 0.261), precluding definitive conclusions about sex-specific effects. The authors point to the well-established uricosuric effect of estrogen and sex differences in HDL metabolism, which produced extreme sex imbalance across UHR trajectory groups: 96.9 percent of the High UHR group was male, while 79.7 percent of the Low UHR group was female. This collinearity between UHR and sex, combined with the substantially compressed female UHR distribution (one standard deviation of 71.08 units versus 114.83 in males), limited statistical power in the female subgroup.

The researchers also applied latent class growth analysis to annual UHR measurements, identifying three trajectory groups: Low (51.7 percent), Moderate (36.3 percent), and High (12.0 percent). In unadjusted models, both the Moderate and High trajectory groups showed significantly higher hazard of incident carotid lesions relative to the Low reference group. But after full adjustment for individual metabolic components, these trajectory-based associations attenuated to non-significance, suggesting that trajectory membership captured distinct cardiometabolic phenotype clusters whose variance overlapped with traditional risk factors. Notably, baseline UHR modeled as a continuous variable retained independent predictive value, indicating that in health examination populations where metabolic parameters are routinely monitored, a single baseline measurement may provide adequate information about long-term UHR exposure without repeated testing.

The incremental predictive performance analysis delivered the study’s most sobering message. Adding UHR to a base model already containing traditional cardiovascular risk factors produced a negligible change in the C-statistic (delta C = 0.0003 overall, 0.0006 in males). Integrated discrimination improvement was essentially zero, and continuous net reclassification improvement was marginal at best. Although individual predicted event probabilities changed significantly in males (median improvement of 0.1 percent, p = 0.008), decision curve analysis at a two-year prediction horizon showed that the UHR-added model and the base model yielded nearly identical net benefit across all clinically relevant risk thresholds, with curves overlapping almost completely. The authors conclude that UHR does not improve population-level discrimination or clinical decision-making.

This negative finding tempers enthusiasm for UHR as a clinical screening biomarker, even as it confirms the ratio’s independent prognostic information. The base model already achieved a C-statistic of 0.73 to 0.74, and the established difficulty of improving discrimination in models performing adequately explains the negligible delta. The authors prioritized more robust metrics such as the C-statistic and decision curve analysis over NRI and IDI, which are sensitive to model specification and prone to false positive findings when discrimination improvement is negligible.

The study has important limitations. The mean follow-up of 2.7 years is insufficient to capture true de novo atherosclerotic development, which occurs over decades; many incident cases likely represent progression of pre-existing subclinical disease. Requiring at least two consecutive annual health examinations excluded roughly 75 percent of the initial cohort, introducing selection bias toward more health-conscious participants with better healthcare access and higher socioeconomic status. Single-center recruitment, unavailability of data on urate-lowering and lipid-lowering agents, and the smaller female subgroup further constrain generalizability. Future studies with larger female cohorts, menopausal substratification, and longer follow-up are needed to clarify sex-specific effects and determine whether UHR offers clinical utility in higher-risk populations where its variability may be greater.

Subject of Research: Cardiovascular Research

Article Title: Uric acid-to-HDL-cholesterol ratio and incident carotid atherosclerosis: a retrospective cohort study

Article References: Wen, H., Shao, K., Li, Y., Cai, R., & Sun, T. (2026). Uric acid-to-HDL-cholesterol ratio and incident carotid atherosclerosis: a retrospective cohort study. Frontiers in Nutrition, 13, Article 1951708. https://doi.org/10.3389/fnut.2026.1951708

Image Credits: AI Generated

DOI: 10.3389/fnut.2026.1951708

Keywords: carotid atherosclerosis, uric acid-to-HDL-cholesterol ratio, cardiovascular risk prediction, biomarker, retrospective cohort study, Frontiers in Nutrition, Zhejiang University, HDL cholesterol, uric acid, Cox proportional hazards, Uric, acid-to-HDL-cholesterol

Infections are among the most feared complications of advanced liver disease. When cirrhosis decompensates—through ascites, variceal bleeding, or hepatic encephalopathy—an infection is frequently the trigger or the accelerant. Bacterial translocation from the gut, impaired clearance of microbes by the reticuloendothelial system, and systemic inflammation converge to make cirrhotic patients exquisitely susceptible. Once an infection takes hold, the clinical trajectory often steepens sharply: in the Graz cohort, patients who developed an infection faced a mortality rate of 41 percent during follow-up. Identifying who is most vulnerable before the first fever appears is therefore a central clinical challenge, and the standard prognostic instruments—the Model for End-stage Liver Disease (MELD) score and the Child-Pugh classification—capture liver dysfunction but say little about immune competence.

HDL and apolipoprotein A-I bring exactly that missing dimension. Far from being a passive cholesterol shuttle, HDL is an active participant in innate immunity. It binds and neutralizes lipopolysaccharide, the toxic lipid component of Gram-negative bacterial cell walls, sequestering it away from the lipopolysaccharide-binding protein pathway that would otherwise amplify inflammatory signaling. Apolipoprotein A-I, which constitutes roughly 70 percent of HDL protein mass, contributes to this endotoxin-binding capacity and also modulates leukocyte behavior, supporting anti-inflammatory polarization of monocytes and macrophages. In chronic liver disease, both the quantity and the quality of HDL deteriorate: hepatic lipase and lecithin-cholesterol acyltransferase activity decline, apolipoprotein composition shifts, and the particle becomes pro-inflammatory rather than protective. Low HDL-C in cirrhosis is thus not merely a metabolic footnote but a potential readout of a compromised endotoxin-buffering system.

The Graz team, led by Florian Rainer, Markus Trieb, Angela Horvath, Gunther Marsche, Vanessa Stadlbauer, and Rudolf E. Stauber, designed the study as a single-centre cohort with a built-in temporal validation. A total of 311 patients with cirrhosis were enrolled, divided into a training cohort of 225 and a separate validation cohort of 86 recruited later. At baseline, researchers measured HDL cholesterol and apolipoprotein A-I alongside standard clinical chemistry. The primary endpoint was strictly defined: an infection requiring antibiotic therapy within 12 months. Infections occurred in 24 percent of the training cohort and 31 percent of the validation cohort, consistent with the substantial infectious burden known to accompany decompensated cirrhosis.

The statistical machinery applied was appropriately rigorous for a prognostic biomarker study. Cox regression models estimated the association between baseline biomarker levels and time to first infection, producing both crude and adjusted hazard ratios. Discriminative performance was quantified with Harrell’s C-index and with censoring-adjusted, time-dependent receiver operating characteristic analyses at the 12-month horizon. When HDL-C or apoA-I were added to the MELD score in the training cohort, both biomarkers significantly improved discrimination, and the combined biomarker models achieved higher C-indices and numerically higher 12-month area-under-the-curve values than MELD or Child-Pugh alone. In other words, the lipid markers carried prognostic information that the established liver scores did not.

From the training data, the team derived exploratory cut-offs: HDL-C below 40.4 milligrams per deciliter and apoA-I below 98.5 milligrams per deciliter identified groups with higher infection risk. These thresholds sit close to conventional clinical boundaries for low HDL, suggesting that the biomarker signal is not confined to extreme values but operates across the range routinely seen in cirrhotic patients. Lower levels of both markers were significantly associated with infection risk in both the training and validation cohorts, lending the core association a degree of robustness that single-cohort findings often lack.

The validation results, however, temper the enthusiasm. In the 86-patient temporal validation cohort, the discriminative performance of the biomarker-based models attenuated: they performed comparably to, rather than better than, the established MELD and Child-Pugh scores. This pattern is familiar in biomarker research. Models fitted to one dataset routinely shrink when applied to another, as overfitting, cohort composition, disease stage, and chance all conspire to erode apparent performance. The Graz investigators are explicit about this limitation: the findings support HDL-C and apoA-I as candidate prognostic biomarkers of infection susceptibility, but external validation in independent centres and prospective assessment of clinical utility are required before any recommendation for routine use can be made.

The mechanistic interpretation is where the story becomes scientifically rich. Cirrhosis dismantles the liver’s role as the body’s endotoxin filter. Portal hypertension widens the gut mucosal barrier, allowing bacterial products to translocate into portal blood, while the diseased hepatic reticuloendothelial system clears them less efficiently. HDL, by binding lipopolysaccharide and promoting its delivery to the liver for detoxification, acts as a circulating countermeasure. When HDL-C and apoA-I fall—whether through impaired hepatic synthesis, malnutrition, inflammation-driven catabolism, or qualitative particle dysfunction—the endotoxin-buffering reserve thins. The result is a patient whose plasma can no longer adequately sequester bacterial toxins, priming the innate immune system for the exaggerated inflammatory responses that characterize spontaneous bacterial peritonitis and sepsis in cirrhosis. Low HDL in this context may be a biomarker of both a depleted defense and a liver too sick to rebuild it.

There are also therapeutic implications, though the authors are careful to label them as requiring dedicated investigation. HDL-raising interventions exist—niacin, statins, CETP inhibitors, lifestyle measures—but their history in cardiology is cautionary: raising HDL-C pharmacologically has repeatedly failed to translate into clinical benefit, and the qualitative functionality of the particle matters as much as its concentration. In cirrhosis, the relevant question is not whether HDL-C can be numerically elevated but whether the endotoxin-binding and immune-modulatory functions of apoA-I can be restored. Apolipoprotein A-I infusions and HDL-like synthetic particles have shown endotoxin-neutralizing capacity in experimental sepsis models, offering a speculative route from biomarker to therapy. Whether such approaches could reduce infection risk in cirrhotic patients remains an open question that no current evidence answers.

What the Graz study delivers now is a candidate risk stratification tool built from two inexpensive, widely available laboratory measurements. A clinician seeing a decompensated cirrhotic patient with HDL-C under 40 milligrams per deciliter and apoA-I under 100 milligrams per deciliter gains a signal—beyond MELD and Child-Pugh—that this individual sits in a higher infection-risk stratum and may warrant heightened surveillance, earlier diagnostic workup for subtle infection, and closer follow-up. The association between infection and a 41 percent mortality rate during follow-up underscores the stakes. Until external validation confirms the cut-offs and prospective trials demonstrate that acting on them improves outcomes, HDL-C and apoA-I remain promising candidates rather than established instruments. But the study adds a compelling chapter to the growing recognition that lipoproteins are not just cardiovascular currency—they are immunological actors whose decline in cirrhosis may announce, months in advance, the infections that decompensate and kill.

Subject of Research: Lipoprotein-related biomarkers HDL-C and apoA-I predict infection risk in patients with liver cirrhosis

Article Title: Lipoprotein-related biomarkers HDL-C and apoA-I predict infection risk in patients with liver cirrhosis

Article References: Rainer, F., Trieb, M., Horvath, A., Douschan, P., Scharnagl, H., Heinemann, Á., Marsche, G., Stadlbauer, V., & Stauber, R. E. (2026). Lipoprotein-related biomarkers HDL-C and apoA-I predict infection risk in patients with liver cirrhosis. Scientific Reports. https://doi.org/10.1038/s41598-026-74841-5

Image Credits: AI Generated

DOI: 10.1038/s41598-026-74841-5

Keywords: liver cirrhosis, HDL cholesterol, apolipoprotein A-I, biomarkers, infection risk, immunology, Scientific Reports, Lipoprotein-related, HDL-C, apoA-I, predict, infection