OCT is a workhorse of modern ophthalmology. The technique uses low-coherence light waves to build cross-sectional images of the retina, resolving its ten distinct layers with micrometer precision. Because the retina is embryologically and physiologically an outpost of the central nervous system, its delicate microvasculature offers what the researchers describe as a noninvasive, side-effect-free quick look into the brain. Ophthalmologists already rely on OCT to screen for glaucoma, diabetic retinopathy, and macular degeneration. What the new study adds is the suggestion that the same scan, already fast and comparatively cheap, might also carry a hidden cardiovascular report card.

The research team, led by Martin Hänsel, Julian Deseoe, and Susanne Wegener of the University Hospital Zurich, focused on two inner retinal layers: the retinal nerve fiber layer (RNFL), a thin sheet of axons funneling visual signals toward the optic nerve, and the ganglion cell-inner plexiform layer (GCIPL), which contains the cell bodies and synaptic connections of retinal neurons. Earlier studies had shown that patients who had already survived a stroke or heart attack tend to have thinner RNFL and GCIPL measurements. The open question was whether thinning could be detected before the event, in seemingly healthy people, and whether it carried information beyond conventional risk factors.

To answer it, the team mined the UK Biobank, a population-based cohort of more than half a million adults aged 40 to 69 recruited between 2006 and 2010. Roughly a tenth of participants underwent OCT imaging with a spectral-domain Topcon device using a standardized 6 by 6 millimeter macular raster scan of 128 B-scans. Custom segmentation software automatically delineated the retinal boundaries, and the investigators applied strict quality control, discarding the poorest 20 percent of images based on quality scores, excluding participants who reported eye disease, and requiring complete data on cardiovascular risk factors. After these filters, 51,293 participants remained, of whom 1,506, or 2.9 percent, had already experienced a stroke or myocardial infarction before their eye scan.

The first finding concerned the past rather than the future. Participants with prior cardiovascular disease had measurably thinner inner retinas than their event-free peers: the RNFL averaged 28.97 micrometers in the CVD group versus 29.70 micrometers in those without, the GCIPL 72.99 versus 74.21 micrometers, and a photoreceptor-related measure called ISOS.RPE also differed significantly. The other layers examined showed no such difference. The researchers then turned to the 49,787 participants with no prior cardiovascular events and asked a forward-looking question: did retinal thickness at baseline predict who would go on to suffer a major adverse cardiovascular event, a composite of stroke, myocardial infarction, and cardiovascular death, during follow-up?

The answer was yes. In cause-specific hazard models, which properly account for the competing risk of dying from non-cardiovascular causes, each standard deviation increase in RNFL thickness was associated with an 8 percent lower risk of a future event (adjusted hazard ratio 0.92, 95 percent confidence interval 0.89 to 0.96, p < 0.001), while each standard deviation of additional GCIPL thickness carried a 4 percent reduction (adjusted hazard ratio 0.96, 95 percent confidence interval 0.92 to 1.00, p = 0.04). Crucially, these associations survived adjustment for a wide range of traditional cardiovascular risk factors, including age, sex, blood pressure, diabetes, cholesterol, body mass index, smoking, and atrial fibrillation. The relationship was linear, with no evidence of nonlinear effects, and it did not differ between men and women.

The absolute differences were striking when participants were sorted into thin, medium, and thick groups. Over ten years, people with the thinnest RNFL had a cumulative incidence of major cardiovascular events of 5.19 percent, nearly double the 2.78 percent seen in those with the thickest RNFL. The same gradient appeared for the GCIPL: 4.76 percent of the thinnest group suffered an event within a decade, compared with 2.42 percent of the thickest group, roughly a halving of risk across the retinal spectrum.

Perhaps the most intriguing technical detail is a double dissociation between the two layers and the two event types. RNFL thickness was more strongly associated with myocardial infarction (adjusted hazard ratio 0.94, p = 0.02), while GCIPL thickness was more strongly linked to incident stroke (adjusted hazard ratio 0.90, p = 0.003), with the complementary layer showing weaker, non-significant associations in each case. The authors propose a microvascular explanation. The RNFL is fed primarily by the radial peripapillary capillary plexus, whose capillaries run parallel to the nerve fibers, whereas the GCIPL is supplied by the superficial vascular plexus with a lobular architecture. Because atherosclerosis is a systemic disease, subclinical narrowing of the central retinal artery and its branches would chronically starve these layers of oxygen, and the two distinct vascular bed architectures may respond differently to the risk factor profiles that predispose to coronary versus cerebral events. A recent Mendelian randomization study supports the idea of shared underlying causes between retinal layer thickness and cardiovascular disease.

How much does the eye scan actually add to prediction? The honest answer: modestly. Adding RNFL and GCIPL thickness to a simple model based on age and sex alone nudged the area under the receiver operating characteristic curve for 10-year event prediction from 0.708 to 0.710, a statistically significant but small improvement, with even smaller gains when the layers were added to fully adjusted models. The authors are candid about this gap between statistical significance and clinical relevance. They also emphasize that their cohort excluded people over 69, precisely the age group with the highest cardiovascular risk, as well as anyone with pre-existing eye disease, and that the observational design cannot establish causation. Whether RNFL and GCIPL thinning actually contributes to disease or merely mirrors it in the retinal microcirculation remains unresolved.

Still, the study offers practical building blocks for the future. The team generated age- and sex-specific normative values for RNFL and GCIPL thickness in healthy adults, giving clinicians a reference frame should retinal measurements ever be folded into risk screening, particularly for people with a family history of cardiovascular disease. The authors sketch a roadmap for improving performance: combining layer thickness with OCT angiography measures such as vessel density, tracking individual retinal trajectories over time rather than single snapshots, and disentangling ischemic from hemorrhagic stroke, which was not done here. Prospective validation studies will be needed before any ophthalmology practice doubles as a cardiac screening station. For now, the message is one of cautious excitement: the eye has long been called a window to the soul, but a growing body of evidence suggests it may also be a window to the heart, and the view is getting clearer with every scan.

Subject of Research: Retinal layer thickness measured by optical coherence tomography as a predictor of future major adverse cardiovascular events in the UK Biobank cohort

Article Title: Retinal layer thickness as a potential marker for future cardiovascular events – a UK Biobank cohort study using optical coherence tomography

Article References: Retinal layer thickness as a potential marker for future cardiovascular events – a UK Biobank cohort study using optical coherence tomography. (n.d.). https://doi.org/10.1007/s00415-026-14175-4

Image Credits: AI Generated

DOI: 10.1007/s00415-026-14175-4

Keywords: optical coherence tomography, retinal nerve fiber layer, ganglion cell-inner plexiform layer, cardiovascular risk prediction, UK Biobank, stroke, myocardial infarction, major adverse cardiovascular events, retinal microvasculature, risk screening, Journal of Neurology, population cohort study

The study drew on the National Health and Nutrition Examination Survey, or NHANES, covering survey cycles from 2007 to 2018, with mortality outcomes linked to the National Death Index through December 31, 2019. After applying survey weights, the analytic cohort represented approximately 106.9 million US adults, with a mean age of 47.2 years. Rather than relying on body mass index alone, the investigators stratified participants into four distinct body composition phenotypes using two measurements: BMI, which captures overall mass relative to height, and the waist-to-height ratio, which serves as a practical proxy for central or abdominal adiposity. The four groups were obesity with central adiposity, obesity without central adiposity, normal weight with central adiposity, and normal weight without central adiposity.

The distribution of these phenotypes across the American population proved revealing in its own right. A slim majority, 53.3 percent of the weighted cohort, fell into the normal weight without central adiposity category, the presumed metabolically healthy baseline. Another 33.9 percent carried both a high BMI and a high waist-to-height ratio, the classic pattern of generalized obesity. But two smaller and often overlooked groups drew the researchers’ attention: 8.1 percent of adults had normal BMI values but prominent central fat stores, a phenomenon sometimes called normal weight central adiposity, while 4.7 percent were obese by BMI yet lacked significant abdominal fat accumulation. These last two groups complicate the simple arithmetic of conventional obesity screening.

The central outcome of the investigation was cardiovascular-kidney-metabolic multimorbidity, defined as the coexistence of two or more of the following conditions: hypertension, hyperlipidemia, diabetes, chronic kidney disease, or established cardiovascular disease. This clustering of cardiometabolic disorders, increasingly framed under the umbrella of cardiovascular-kidney-metabolic syndrome, has been recognized by the American Heart Association as a major and growing driver of cardiovascular events and death. The syndrome reflects the intimate physiological coupling of the heart, kidneys, and metabolic organs: insulin resistance accelerates atherosclerosis, declining kidney function worsens volume overload and hypertension, and adipose tissue dysfunction amplifies inflammatory signaling that damages vascular beds throughout the body.

When the researchers tabulated multimorbidity prevalence across body composition phenotypes, a clear hierarchy emerged. Normal weight individuals with central adiposity had the highest rate of cardiovascular-kidney-metabolic multimorbidity at 46.5 percent, meaning nearly half of these apparently slim adults already carried at least two of the five defining conditions. This exceeded the multimorbidity burden observed in people with obesity with central adiposity, and it dwarfed the rates seen in the two phenotypes without abdominal fat excess. In other words, the single group that conventional BMI-based screening would most reliably classify as low risk was, by this metric, the sickest.

Mortality analyses sharpened the message considerably. Using survey-weighted Cox proportional hazards models, which allow researchers to estimate the association between a characteristic and the timing of death while adjusting for confounding factors and accounting for the complex sampling design of NHANES, the team found that normal weight adults with central adiposity faced an adjusted hazard ratio of 1.87 for all-cause mortality compared with the reference group, a statistically significant elevation with a 95 percent confidence interval of 1.08 to 3.25 and a p value of 0.025. Even more dramatic was the association with cardiovascular death: the adjusted hazard ratio reached 7.76, with a 95 percent confidence interval of 1.01 to 59.76 and a p value of 0.049. While the wide confidence interval reflects the relatively small number of events in this subgroup and should temper strong causal interpretation, the direction and magnitude of the association are consistent with a substantially elevated cardiovascular risk.

Kaplan-Meier survival curves, a standard technique for visualizing the probability of surviving over time across groups, reinforced the statistical models. Participants who combined cardiovascular-kidney-metabolic multimorbidity with the normal weight central adiposity phenotype demonstrated the poorest long-term survival of any group in the analysis, with the difference between curves reaching statistical significance at p less than 0.001. This convergence of evidence, spanning prevalence estimates, adjusted hazard modeling, and nonparametric survival analysis, points toward a coherent conclusion: the combination of a slim silhouette and a protruding waistline represents a particularly dangerous metabolic signature when it coexists with clustered cardiometabolic disease.

The biological plausibility behind these findings rests on the distinct behavior of visceral adipose tissue compared with subcutaneous fat. Fat deposited around internal organs is not an inert energy reservoir; it is a hormonally and immunologically active tissue that drains directly into the portal circulation, delivering free fatty acids and inflammatory cytokines to the liver and promoting insulin resistance, dyslipidemia, and hepatic steatosis. Visceral fat accumulation is also closely linked to ectopic fat deposition in the liver, pancreas, and heart itself, mechanisms that have been implicated in the progression of metabolic dysfunction-associated steatotic liver disease, type 2 diabetes, and atherosclerotic cardiovascular disease. A person with a normal BMI but a high waist-to-height ratio may therefore harbor a metabolically hostile internal environment that is invisible to weight-based screening, while some individuals with obesity and preserved fat distribution may be relatively protected.

The study arrives at a moment when the scientific community is actively rethinking how obesity itself should be defined. A recent international commission has proposed diagnostic criteria for clinical obesity that move beyond BMI toward measures of fat distribution and organ dysfunction, and prior research has repeatedly shown that waist-to-height ratio outperforms BMI as a screening tool for cardiometabolic risk factors. The new findings extend this literature into the specific arena of cardiovascular-kidney-metabolic multimorbidity and long-term survival in a nationally representative population. The authors conclude that normal weight individuals with central adiposity bear the greatest CKM burden and mortality risk, a result that highlights the limitations of BMI-based risk assessment and argues for incorporating simple anthropometric measures of central fat, such as the waist-to-height ratio, into routine clinical screening. For clinicians, the practical implication is straightforward: a tape measure around the waist may identify high-risk patients that the scale alone would miss, and for the public, the reassuring sight of a normal number on the bathroom scale should not be mistaken for a clean bill of cardiometabolic health.

Subject of Research: The association of body composition phenotypes with cardiovascular-kidney-metabolic multimorbidity and long-term mortality in a US population-based cohort

Article Title: Body composition phenotypes are key predictors of cardiovascular-kidney-metabolic multimorbidity and long-term mortality: insights from a population-based cohort study

Article References: Kong, G., Intaran, M. A. U., Soh, E. S. W., Yazicioglu, Y., Goh, R., Nagarajan, S., Wang, J.-W., Zhou, X., Zhou, X.-D., Zheng, M.-H., Chan, M. Y., Mehta, A., le Roux, C. W., Mamas, M. A., Khan, M. S., & Chew, N. W. S. (2026). Body composition phenotypes are key predictors of cardiovascular-kidney-metabolic multimorbidity and long-term mortality: insights from a population-based cohort study. Clinical Research in Cardiology. https://doi.org/10.1007/s00392-026-03010-5

Image Credits: AI Generated

DOI: 10.1007/s00392-026-03010-5

Keywords: cardiovascular-kidney-metabolic syndrome, central adiposity, body mass index, waist-to-height ratio, obesity, NHANES, multimorbidity, mortality, visceral fat, cardiometabolic risk, population-based cohort study, risk screening