The study, published in BMC Psychiatry, followed 242,947 UK Biobank participants aged 40 to 70 who were free of schizophrenia, anxiety disorders, and bipolar disorder at baseline. Rather than collapsing the eight LE8 components into a single composite score, the research team used latent profile analysis, a person-centred method that identifies subgroups of individuals who share similar configurations across multiple measured variables. The approach is grounded in finite mixture modeling: participants are assigned probabilistically to latent classes, and model fit is evaluated with tools such as the Akaike and Bayesian information criteria, entropy values that quantify classification accuracy, and a bootstrap likelihood ratio test that compares successive class solutions. In this case, the five-profile solution achieved an entropy of 0.95—well above the 0.80 threshold for excellent classification—while the six-profile solution converged to a suboptimal fit, supporting the choice of five.

The five profiles that emerged were strikingly heterogeneous. The first, labeled the Low LE8 score group, averaged a composite score of 55.96 and was dominated by near-universal current smoking, reflected in a nicotine exposure score of just 0.06 out of 100. The second profile, characterized by elevated adiposity, blood pressure, and glucose, contained the oldest participants, with a mean age of 59.31 years, and showed markedly poor metabolic markers despite relatively preserved lifestyle behaviors. The third and largest group, comprising roughly 31 percent of the cohort, combined low physical activity with poor sleep health while maintaining near-average metabolic indicators. The fourth profile showed elevated blood pressure and dyslipidemia as its primary deficits, with otherwise favorable behaviors. The fifth, the High LE8 score group, averaged 80.59 and exhibited consistently positive standardized scores across nearly all dimensions, along with the youngest mean age of 52.45 years and the most favorable socioeconomic indicators.

Over a median follow-up of 13.8 years, the researchers identified 11,419 incident cases of anxiety disorders, 341 cases of bipolar disorder, and 40 cases of schizophrenia, using ICD-10 codes drawn from hospital inpatient records, primary care data, death registries, and self-reported medical histories. Cox proportional hazards regression, adjusted for age, sex, ethnicity, education, household income, the Townsend Deprivation Index, employment status, long-standing illness, alcohol intake, and family history of severe depression, revealed that all four comparison profiles carried significantly lower anxiety risk than the Low LE8 score group. The High LE8 score group showed the strongest protection, with a hazard ratio of 0.65, translating to a 35 percent risk reduction. The elevated blood pressure and dyslipidemia group followed at 0.68, while the adiposity-glucose and inactivity-sleep groups showed hazard ratios of 0.77 and 0.78, respectively.

The bipolar disorder findings were even more dramatic in relative terms. Despite the smaller number of cases, all four comparison profiles showed substantial risk reductions ranging from 49 to 63 percent. The elevated blood pressure and dyslipidemia group had the lowest hazard ratio at 0.37, followed by the inactivity-sleep group and the High LE8 score group, both at 0.41, and the adiposity-glucose group at 0.51. Notably, the pattern was not simply a monotonic function of total LE8 score. The elevated blood pressure and dyslipidemia group, despite a mean composite score of 70.93 that was lower than the High LE8 group’s 80.59, showed the strongest bipolar protection. This dissociation between composite score and profile-specific risk is precisely what the latent profile approach is designed to detect and what conventional scoring methods would obscure.

The biological plausibility of these associations rests on well-characterized pathways linking cardiovascular health to brain function. Chronic nicotine exposure pharmacologically activates the hypothalamic-pituitary-adrenal axis and increases sympathetic arousal, which may paradoxically heighten long-term vulnerability to anxiety and mood instability despite the subjective anxiolytic effects that drive smoking behavior. Physical inactivity is associated with reduced brain-derived neurotrophic factor-mediated hippocampal neuroplasticity, while poor dietary quality has been linked to elevated systemic inflammatory markers and oxidative stress. In the sleep-inactivity profile, chronic sleep insufficiency has been shown to impair prefrontal cortical regulation of amygdalar reactivity, and physical inactivity may limit the exercise-mediated downregulation of stress axes and anti-inflammatory signaling. These converging mechanisms offer a coherent framework for why the Low LE8 score group, with its convergence of adverse exposures, carried the highest neuropsychiatric burden.

The schizophrenia results demand careful interpretation. With only 40 incident cases, the analysis was severely underpowered, and the authors explicitly frame these findings as exploratory. Beyond the statistical limitation, the UK Biobank cohort largely excludes the typical age of onset for schizophrenia, which typically emerges in late adolescence and early adulthood. Ninety percent of the 40 cases occurred after age 50, and 55 percent after age 60, meaning the captured cases almost exclusively represent late-onset presentations, which are thought to involve neurodegenerative processes rather than the neurodevelopmental abnormalities that predominate in early-onset disease. A further complication, which the authors call a therapeutic paradox, is that atypical antipsychotics induce metabolic side effects including weight gain, sedation, and glycemic elevation, potentially introducing reverse causality into observational data. The absence of significant associations should therefore not be read as evidence that lifestyle and metabolic health are irrelevant to schizophrenia risk.

Several sensitivity analyses bolstered confidence in the primary findings. To minimize reverse causation, participants diagnosed within the first six months, one, two, three, and five years of follow-up were sequentially excluded, with consistent results across all thresholds. Multiple imputation by chained equations was used to include participants with missing LE8 or covariate data, yielding a substantially larger analytic sample with concordant findings. When conventional LE8 total score categories—low, moderate, and high—were used as an alternative exposure, higher scores were associated with lower anxiety and bipolar risk in a monotonic gradient, but this approach could not distinguish the profile-specific patterns that the latent analysis revealed. Subgroup analyses stratified by sex, age, ethnicity, socioeconomic status, education, employment, illness status, alcohol intake, and family history of depression produced broadly consistent results, with the anxiety findings particularly stable across virtually all strata.

The clinical implications are tentative but intriguing. If distinct health patterns carry differential neuropsychiatric risk, then prevention strategies might be tailored to profile rather than to composite score. For individuals in the Low LE8 score group, integrated interventions combining smoking cessation with comprehensive lifestyle modification could be prioritized. For the largest subgroup—the inactivity-sleep cluster—structured exercise programs combined with sleep hygiene interventions represent a plausible target. The authors emphasize that these observational findings generate hypotheses for future interventional studies rather than prescribing immediate clinical action, and that the profile-specific risk patterns require prospective validation before implementation in practice.

Limitations temper the enthusiasm. The cohort is 96.21 percent white and generally affluent, limiting generalizability to more diverse populations. LE8 components were assessed only at baseline, so changes in health behaviors over the follow-up period could not be captured. Unmeasured confounders, including genetic predisposition, social support networks, and environmental stressors, cannot be entirely excluded despite comprehensive covariate adjustment. Neuropsychiatric disease identification relied on clinical diagnoses recorded in healthcare databases, potentially under-ascertaining milder cases that never receive clinical attention. And the bipolar disorder findings, while consistent in direction across all four comparison profiles, rest on only 341 incident cases, limiting the precision of individual estimates. Nevertheless, the study demonstrates that the architecture of health—how behaviors and biomarkers co-occur within individuals—may carry information about neuropsychiatric vulnerability that a single summary number cannot convey, and it positions person-centred, pattern-based approaches as a promising frontier for understanding how modifiable lifestyle factors shape the risk of mental illness.

Subject of Research: Associations between latent Life's Essential 8 cardiovascular health profiles and incident neuropsychiatric diseases in the UK Biobank

Article Title: Life’s essential 8 health profiles and risk of incident neuropsychiatric diseases: a nationwide prospective cohort study

Article References: Huangfu, H., Jia, H., Chen, C., Xu, Y., Zhou, X., Tang, Y., & Gao, X. (2026). Life’s essential 8 health profiles and risk of incident neuropsychiatric diseases: a nationwide prospective cohort study. BMC Psychiatry, 26(1), Article 714. https://doi.org/10.1186/s12888-026-08341-1

Image Credits: AI Generated

DOI: 10.1186/s12888-026-08341-1

Keywords: Life's Essential 8, UK Biobank, latent profile analysis, anxiety disorders, bipolar disorder, schizophrenia, cardiovascular health, neuropsychiatric diseases, lifestyle factors, Cox proportional hazards, sleep health, physical activity

The NIH All of Us program is one of the most ambitious biomedical data collection efforts ever attempted. Launched as part of a national push toward precision medicine, it aims to gather health, lifestyle and environmental information from more than a million participants across the United States, with deliberate oversampling of communities that have historically been underrepresented in medical research. Participants contribute survey responses covering diet, physical activity, smoking and alcohol use, alongside electronic health record data, physical measurements and, for many, genomic information. For dermatology researchers, this represents a rare opportunity: most rosacea studies are conducted in single clinics with hundreds of patients, while a database of this scale allows investigators to examine associations across tens of thousands of individuals drawn from wildly different backgrounds.

Rosacea itself is far more than simple facial redness. Clinicians recognize several overlapping subtypes, including erythematotelangiectatic rosacea, marked by persistent flushing and visible blood vessels; papulopustular rosacea, which produces acne-like bumps; phymatous rosacea, which can cause thickening of the skin, most famously around the nose; and ocular rosacea, which affects the eyes and eyelids. The condition follows a relapsing-remitting course, flaring in response to triggers that vary from person to person. Common culprits include sun exposure, heat, emotional stress, spicy foods, alcohol and hot beverages. Because the disease is so heterogeneous, large-scale data is essential for separating genuine risk factors from anecdotal associations that have accumulated over decades of clinical observation.

The pathophysiology of rosacea involves a complex interplay of innate immune dysregulation, neurovascular abnormalities and disruption of the skin’s microbial and physical barriers. Research over the past two decades has implicated elevated levels of antimicrobial peptides such as cathelicidin, heightened reactivity of transient receptor potential channels that sense heat and irritation, and an altered relationship with Demodex mites that colonize facial hair follicles. Chronic inflammation in rosacea has also been linked, in other studies, to systemic comorbidities including gastrointestinal disorders, cardiovascular disease and metabolic conditions, which is precisely the kind of association that a database as broad as All of Us is positioned to interrogate. Understanding whether rosacea is purely a skin disease or a visible marker of broader inflammatory states remains an open and clinically important question.

By analyzing lifestyle and dietary variables alongside rosacea status, the Northwestern team’s approach reflects a growing recognition that the social determinants of health, the conditions in which people live, work and eat, shape dermatologic outcomes in ways that prescriptions alone cannot address. The concept, articulated in influential public health literature, holds that researchers must consider the causes of the causes. For rosacea, this could mean examining how obesity, smoking status, alcohol consumption, diet quality and physical activity correlate with disease presence and severity across a diverse population. It could also mean investigating whether treatment patterns differ systematically by demographic group, a question with direct implications for health equity in dermatology.

Treatment for rosacea currently spans a layered arsenal. Topical agents such as metronidazole, azelaic acid and ivermectin target the inflammatory and mite-related components of the disease, while brimonidine and oxymetazoline constrict dilated facial blood vessels to reduce persistent redness. Oral antibiotics, particularly low-dose doxycycline, remain a mainstay for moderate to severe cases, and isotretinoin is occasionally used off-label for refractory disease. Laser and intense pulsed light therapies address the vascular changes that medications cannot fully reverse. Skincare routines built around gentle cleansing and barrier repair are considered foundational. Yet adherence varies enormously, and many patients cycle through multiple therapies before finding a regimen that controls their flares. Mapping real-world treatment patterns across a large cohort could reveal gaps between guideline recommendations and what patients actually receive.

The All of Us database is particularly valuable for this kind of research because of its demographic breadth. Traditional rosacea studies have often focused on fair-skinned populations of European descent, partly because the condition is easiest to diagnose visually in lighter skin. In skin of color, erythema can be subtle or absent, and rosacea is frequently misdiagnosed or overlooked, contributing to delays in treatment. A dataset that deliberately includes diverse racial and ethnic groups offers the chance to characterize how rosacea presents, and how it is managed, across the full spectrum of skin tones. The authors’ affiliation with related research subjects including race and ethnicity, obesity, risk factors and nutrition suggests the analysis was structured around exactly these dimensions.

As with any database study, the methodology carries inherent constraints that readers should keep in mind. All of Us relies substantially on participant-reported survey data and electronic health records, both of which are subject to misclassification: rosacea diagnoses may be inconsistently coded, and dietary recall is notoriously imprecise. Observational associations drawn from such data can identify correlations but cannot by themselves establish causation, and unmeasured confounders may influence any observed relationships. The authors note that no new datasets were generated or analyzed within the current study, indicating that the work functions as a secondary analysis of existing program data. Short reports of this kind are often best understood as hypothesis-generating contributions that lay groundwork for more targeted prospective studies rather than as definitive answers.

Nevertheless, the significance of the approach is hard to overstate. Dermatology has historically lagged behind other medical specialties in leveraging large-scale real-world data, in part because skin disease is so visually heterogeneous and because many conditions are managed outside hospital record systems. Studies that mine national biobanks for dermatologic signals are helping to close that gap, and rosacea, with its tangled mix of triggers, comorbidities and treatment options, is an ideal candidate for this kind of investigation. If lifestyle and dietary factors can be more firmly linked to disease activity, clinicians may one day pair pharmacologic treatment with concrete behavioral guidance, much as they now do for acne or psoriasis.

For the millions of people who live with rosacea, research of this kind carries practical hope. The condition affects quality of life out of proportion to its medical severity, with documented impacts on self-esteem, social interaction and even employment in customer-facing roles. Flares are unpredictable, triggers are personal, and the emotional burden of a visibly inflamed face is easy to underestimate. A rigorous, population-scale accounting of which habits, foods and treatments actually matter, grounded in a dataset built to reflect the diversity of the American public, moves the field closer to personalized management strategies. The Northwestern team’s analysis, published as volume 318, article 433 of the Archives of Dermatological Research, is a step toward that future, and it signals that chronic skin disease is finally getting the big-data attention it deserves.

Subject of Research: Population-scale analysis of rosacea risk factors, lifestyle and dietary associations, and treatment patterns using the NIH All of Us database

Article Title: Rosacea and associated factors: a comprehensive analysis of lifestyle, dietary, and treatment patterns using the NIH All of Us database

Article References: Marzouk, S., Musabji, A., Issa, R., Saleeb, J., Hassan, O., Alkhalili, S., Hassan, T., Muttar, S., & Lio, P. (2026). Rosacea and associated factors: a comprehensive analysis of lifestyle, dietary, and treatment patterns using the NIH All of Us database. Archives of Dermatological Research, 318(1), Article 433. https://doi.org/10.1007/s00403-026-04952-6

Image Credits: AI Generated

DOI: 10.1007/s00403-026-04952-6

Keywords: rosacea, NIH All of Us, dermatology, skin disease, lifestyle factors, diet, treatment patterns, inflammation, health equity, population health, chronic skin condition, precision medicine

The research, published in BMC Medicine by a team led by Sixian Liu and Jieyun Yin of Soochow University together with colleagues at Sichuan University, mined the UK Biobank, one of the world’s richest biomedical databases. The team defined the starting point of their disease model as either a first live birth or the diagnosis of an adverse pregnancy outcome, whichever came first. From there, they tracked women through a sequence of health states: the appearance of a first cardio-renal-metabolic disease, the accumulation of a second condition to reach multimorbidity, and ultimately death. This staged framing matters because it treats chronic disease not as a single event but as a process with distinct, measurable transitions.

Statistically, the investigators relied on multi-state models, a class of survival-analysis techniques that estimate the hazard — the instantaneous risk — of moving from one health state to the next, while adjusting for confounders such as age, socioeconomic status and other baseline characteristics. The approach allowed them to quantify not only whether adverse pregnancy outcomes raise risk, but at which point in the disease cascade that risk is concentrated. It also enabled them to test for interaction, asking whether the effect of a complicated pregnancy depends on what a woman does afterwards in terms of diet, smoking, alcohol, physical activity and body shape.

The headline numbers are sobering. Women with a history of adverse pregnancy outcomes progressed from a healthy initial state to a first cardio-renal-metabolic disease at a rate of 19.84 percent, compared with 15.56 percent among women without such a history — and the adjusted hazards ratio of 3.32 means their risk of making that transition was more than three times higher. That first transition proved to be the steepest part of the curve. Once a first disease had appeared, the excess risk of progressing to full multimorbidity persisted but moderated, with a hazards ratio of 1.41, and the risk of dying after multimorbidity was elevated at 1.65.

The mortality findings add a darker dimension. Women with adverse pregnancy outcomes faced a higher hazard of dying even before any cardio-renal-metabolic diagnosis, with an adjusted hazards ratio of 1.46 for the transition from the initial state directly to death, and a ratio of 1.28 for death after a first disease, though the latter estimate carried wider statistical uncertainty. Across nearly every stage of the model, the progression percentages were higher in the adverse-outcomes group, painting a consistent picture of a population whose pregnancies left a durable physiological signature.

What elevates the study beyond a simple risk tally is its treatment of lifestyle as a modifying force rather than a background variable. The researchers found a significant interaction between adverse pregnancy outcomes and high-risk lifestyle factors, with alcohol consumption, insufficient physical activity and unhealthy body shape emerging as the pivotal players during the transition from the initial state to a first cardio-renal-metabolic disease. In other words, the damage associated with a complicated pregnancy was not a fixed sentence; it interacted with behaviors that women and their clinicians can actually change.

The biological plausibility of such a long shadow is grounded in vascular and metabolic physiology. Hypertensive disorders of pregnancy are thought to reveal, and possibly worsen, underlying vulnerabilities in endothelial function — the health of the thin cell layer lining blood vessels — while gestational diabetes signals impaired glucose regulation that may predate the pregnancy itself. Pregnancy thus functions as a natural stress test for the cardiovascular, renal and metabolic systems. A woman who fails that test may carry forward subtle deficits in insulin sensitivity, blood pressure regulation and kidney filtration that silently accumulate until they cross diagnostic thresholds years or decades later.

The multi-state prediction component of the study carries practical weight. By combining adverse pregnancy outcome status with the number of lifestyle risk factors, the model showed that the probability of disease progression increased as risks stacked up. This has direct implications for how medicine organizes care. Obstetric histories are frequently recorded and then forgotten once a patient transitions to primary or specialty adult care, yet the findings argue that a history of gestational diabetes or preeclampsia should function as a lifelong flag — a reason for earlier screening, tighter monitoring of blood pressure and glucose, and more aggressive counseling on alcohol, activity and weight.

There are, of course, limits to what an observational cohort can prove. The UK Biobank population is not fully representative, and lifestyle factors were measured at baseline rather than tracked continuously across four decades, so changes in behavior over time are imperfectly captured. Residual confounding can never be excluded, and the interaction analyses, while statistically significant, describe associations rather than guaranteed causal pathways. Still, the sheer size of the cohort, the length of follow-up and the consistency of the hazard estimates across transitions give the findings considerable weight.

The broader message is one of opportunity. Cardio-renal-metabolic multimorbidity is among the most burdensome and expensive patterns of chronic disease in aging populations, and it rarely arrives unannounced. This study suggests that for millions of women, the first warning sign appears not in middle age but in a delivery room — in a blood pressure reading or a glucose tolerance test. Treating adverse pregnancy outcomes as the beginning of a long-term prevention program, rather than the end of a pregnancy complication, could shift the entire trajectory of women’s cardiovascular, kidney and metabolic health, and the lifestyle levers identified here offer a concrete place to start.

Subject of Research: The association between adverse pregnancy outcomes, lifestyle factors and long-term cardio-renal-metabolic multimorbidity risk in women

Article Title: Association of adverse pregnancy outcomes history and lifestyle factors with cardio-renal-metabolic multimorbidity: a prospective cohort study

Article References: Liu, S., Long, L., Peng, Y., Guo, N., Gu, Y., Yang, M., & Yin, J. (2026). Association of adverse pregnancy outcomes history and lifestyle factors with cardio-renal-metabolic multimorbidity: a prospective cohort study. BMC Medicine. https://doi.org/10.1186/s12916-026-05224-w

Image Credits: AI Generated

DOI: 10.1186/s12916-026-05224-w

Keywords: adverse pregnancy outcomes, cardio-renal-metabolic multimorbidity, UK Biobank, gestational diabetes, hypertensive disorders of pregnancy, lifestyle factors, chronic kidney disease, type 2 diabetes, cardiovascular disease, multi-state models, epidemiology, women's health

The research, led by Gaurav N. Pathak and corresponding author Shawn G. Kwatra, arrives at a moment of growing scientific and commercial interest in prurigo nodularis. For decades the disease was under-recognized, lumped in with generic chronic itch and treated with little more than moisturizers and antihistamines. That changed when the United States Food and Drug Administration approved the first systemic therapies specifically for the condition, transforming it from an orphan diagnosis into a focal point of immunodermatology. Yet as therapeutic options have expanded, a parallel body of evidence has made clear that the burden of the disease is not distributed evenly across populations.

Earlier work cited by the team, including a landmark study of more than 900 prurigo nodularis patients published in the Journal of the American Academy of Dermatology, documented ethnic differences in the comorbidities that accompany the disease. Patients with skin of color have historically faced delays in diagnosis, differences in how the disease presents on darker skin, and unequal access to specialty care, a broader pattern of racial disparity in dermatology that has been catalogued in recent reviews in the same journal. Understanding whether Black and white patients differ in the clinical profile of prurigo nodularis itself, rather than merely in the care they receive, is a critical step toward equitable treatment.

The All of Us Research Program provides an unusually powerful lens for such a comparison. Launched by the National Institutes of Health, the program has enrolled hundreds of thousands of participants across the United States with the explicit goal of reflecting the country’s diversity, collecting electronic health records, survey data on lifestyle and environment, and in many cases genomic information. The dataset is available to registered researchers through the All of Us Researcher Workbench, and the authors of the new analysis have made their data and code available as a featured workspace on that platform, an unusual degree of transparency that allows other investigators to scrutinize and extend their findings.

Cross-sectional designs of this kind compare groups at a single point in time, which makes them efficient for mapping differences in disease characteristics, comorbid conditions, and lifestyle variables such as smoking status, body mass index, and sleep. In prurigo nodularis research, such variables matter enormously. Chronic itch is known to intertwine with metabolic and psychiatric health, and the relentless itch-scratch cycle that defines the disease disrupts sleep, degrades quality of life, and may feed into systemic inflammation. Identifying which of these factors differ by race could point to mechanisms, and to interventions, that are currently being missed.

The study also sits within a rapidly evolving genetic and immunological picture of the disease. A 2023 study published in the Journal of Investigative Dermatology, co-authored by members of the same broader research community, developed a polygenic risk score for prurigo nodularis that predicted racial and genetic susceptibility to the condition, providing evidence that inherited risk contributes to who develops the disease. On the immunological side, prurigo nodularis is now understood as a type 2 inflammatory disorder driven by signaling pathways involving interleukins and neural itch fibers, the same biology targeted by the newest approved drugs.

Cardiovascular health has emerged as another front. A global cohort study published in EBioMedicine in 2024 reported increased cardiovascular risks and mortality among prurigo nodularis patients, suggesting that the disease’s systemic inflammation extends well beyond the skin. If lifestyle and cardiometabolic factors differ between Black and white patients with the condition, as the new cross-sectional analysis set out to test, that could have direct consequences for how clinicians monitor and counsel patients, and for which comorbidities are screened for in different populations.

The research team’s composition reflects the clinical stakes. Kwatra, whose Maryland Itch Center specializes in refractory chronic itch, has received grant funding from the Skin of Color Society and serves as a consultant or advisor to numerous pharmaceutical companies developing itch therapies, including AbbVie, Celldex Therapeutics, Galderma, Incyte, Novartis, Pfizer, Regeneron, and Kiniksa. That combination of academic focus on itch biology and frontline experience with diverse patient populations is precisely the vantage point from which questions about racial differences in disease presentation become answerable rather than anecdotal.

What makes the new analysis notable methodologically is its grounding in a cohort designed for exactly this kind of equity-focused question. Traditional dermatology datasets skew heavily toward white patients seen in academic centers, which has historically limited the generalizability of findings and obscured diseases like prurigo nodularis as they appear in skin of color. By contrast, the All of Us program’s deliberate recruitment of populations underrepresented in biomedical research, combined with its standardized surveys and linked health records, allows investigators to compare clinical characteristics and lifestyle factors across racial groups within a single, consistently measured framework.

The work also underscores a shift in how the dermatology research community approaches itch. Once dismissed as a symptom rather than a disease, chronic itch of the nodular type is now the subject of dedicated research centers, validated severity instruments, targeted biologics, and genetic risk models. The new study’s contribution lies in insisting that this progress be examined through the lens of race, ensuring that as therapies advance, the differences in disease burden, comorbidity patterns, and lifestyle context between Black and white patients are documented rather than assumed. With the data and code publicly available on the All of Us Researcher Workbench, the analysis invites replication and extension, a model of open science for a condition whose true population-level contours are only now coming into focus.

Subject of Research: Racial differences in clinical characteristics and lifestyle factors among patients with prurigo nodularis

Article Title: Differences in clinical characteristics and lifestyle factors between black and white patients with prurigo nodularis patients: a cross-sectional analysis

Article References: Pathak, G. N., Akiska, Y. M., Pathak, S. S., & Kwatra, S. G. (2026). Differences in clinical characteristics and lifestyle factors between black and white patients with prurigo nodularis patients: a cross-sectional analysis. Archives of Dermatological Research, 318(1), Article 504. https://doi.org/10.1007/s00403-026-04912-0

Image Credits: AI Generated

DOI: 10.1007/s00403-026-04912-0

Keywords: prurigo nodularis, chronic itch, racial disparities, dermatology, All of Us Research Program, skin of color, health equity, cross-sectional study, comorbidities, lifestyle factors, type 2 inflammation, polygenic risk score

The oxidative balance score, or OBS, is a composite measure designed to capture a person’s total oxidant-antioxidant profile in a single number. Rather than focusing on one nutrient or one behavior, the score aggregates multiple dietary components — including vitamins, minerals, and other antioxidant or pro-oxidant factors — alongside non-dietary contributors such as physical activity, smoking status, and obesity. Each component is assigned a value reflecting whether it pushes the body’s chemistry toward oxidative damage or toward antioxidant protection, and the values are summed. A higher score signals a predominance of antioxidant exposures over pro-oxidant ones. The approach acknowledges that oxidative stress in real life is the net result of many simultaneous influences, not the effect of any single molecule in isolation.

To test whether this integrated measure predicts future metabolic disease, the research team drew on participants in the third phase of the Tehran Lipid and Glucose Study, conducted between 2006 and 2008. Two analytic cohorts were assembled: 1,950 adults who were free of both type 2 diabetes and prediabetes at baseline, followed for the incidence of prediabetes over a median of 7.3 years, and 2,325 adults free of type 2 diabetes, followed for the incidence of full-blown diabetes over a median of 9.6 years. All participants provided written informed consent, and the protocol was approved by the ethics research committee of Maragheh University of Medical Sciences in accordance with the Declaration of Helsinki.

The scale of disease progression during follow-up was striking. Nearly half of the participants — 44.3 percent — progressed to prediabetes, while 14.6 percent developed type 2 diabetes. These figures underscore why prevention research in this population matters: the transition from normal glucose metabolism to disordered glucose handling was the rule rather than the exception over the observation window, making the cohort a rich testing ground for identifying modifiable risk factors.

Using Cox proportional hazards regression, the investigators calculated hazard ratios comparing participants across tertiles of the oxidative balance score, adjusting for potential confounders. The results were consistent and statistically significant. A higher overall OBS was associated with a 19 percent lower risk of developing prediabetes, with a hazard ratio of 0.81 and a 95 percent confidence interval of 0.67 to 0.99, and a statistically significant trend across score categories. For type 2 diabetes the association was even stronger: higher overall OBS corresponded to a 39 percent lower risk, with a hazard ratio of 0.61 and a confidence interval of 0.43 to 0.86, and a trend P value of 0.005.

When the team decomposed the score into its dietary and lifestyle components, a revealing pattern emerged. The lifestyle portion of the score — encompassing physical activity, smoking, and obesity — showed a robust independent relationship with diabetes risk. Participants in the highest tertile of the lifestyle OBS had a 41 percent lower risk of developing type 2 diabetes, with a hazard ratio of 0.59 and a confidence interval of 0.45 to 0.78. In contrast, the dietary OBS alone showed no statistically meaningful association with the risk of either prediabetes or type 2 diabetes in this cohort.

That divergence between the dietary and lifestyle components is one of the study’s most thought-provoking findings. It suggests that the behavioral factors with systemic physiological reach — staying physically active, avoiding smoking, and maintaining healthy body weight — may dominate the protective signal, while the contribution of dietary antioxidants, at least as captured by the OBS framework in this population, was too weak to detect on its own. This does not necessarily mean that antioxidant-rich foods are irrelevant; it may reflect the limitations of estimating nutrient intake from dietary assessment, the complexity of how food antioxidants are absorbed and utilized, or the possibility that dietary effects on glucose metabolism operate through pathways other than oxidative balance.

From a biological standpoint, the results fit a coherent mechanistic picture. Oxidative stress arises when reactive oxygen species overwhelm the body’s antioxidant defenses, damaging lipids, proteins, and DNA. In metabolic tissue, this damage impairs insulin signaling in muscle and liver, stresses the insulin-producing beta cells of the pancreas, and promotes the low-grade inflammation that accompanies insulin resistance. Beta cells are particularly vulnerable because they possess comparatively low levels of endogenous antioxidant enzymes. A lifestyle that keeps reactive oxygen species in check — through exercise, weight control, and avoidance of cigarette smoke — could therefore preserve insulin sensitivity and beta-cell function long enough to delay or prevent the clinical onset of dysglycemia.

The study’s strengths include its prospective design, its long follow-up, and its use of a population-based cohort drawn from the Tehran Lipid and Glucose Study, one of the region’s most established longitudinal health investigations. By measuring exposure before disease onset, the design avoids the reverse-causation problems that plague cross-sectional studies, in which disease itself alters antioxidant status. The use of hazard ratios across score tertiles, with formal tests for trend, provides a dose-response dimension that strengthens the plausibility of a protective relationship. Nevertheless, as with all observational research, residual confounding cannot be excluded, and the findings demonstrate association rather than proven causation.

The practical implications are considerable. Prediabetes and type 2 diabetes affect hundreds of millions of people worldwide, and rates continue to climb in middle-income countries undergoing rapid nutritional and lifestyle transitions — the very context this study captures. If a favorable oxidative balance, maintained largely through everyday behaviors, genuinely lowers the risk of progressing to dysglycemia, then the OBS could serve as a useful screening and counseling tool, summarizing in one metric how a patient’s combined exposures tilt toward protection or harm. The authors conclude that a higher oxidative balance score, reflecting a predominance of antioxidant over pro-oxidant exposures, acts as a protective factor against the development of both prediabetes and type 2 diabetes. For now, the message for the public aligns squarely with long-standing guidance: move more, keep weight in check, and avoid smoking — habits that, according to this twelve-year analysis, may quietly defend the body’s glucose machinery against the cumulative wear of oxidative stress.

Subject of Research: The association between oxidative balance score and the incidence of prediabetes and type 2 diabetes in adults

Article Title: The association between oxidative balance score and risk of developing prediabetes and type 2 diabetes in adults: a 12-year population-based cohort study

Article References: Hosseini, M. S., Hosseini-Esfahani, F., Bahadoran, Z., Koochakpoor, G., Mirmiran, P., & Azizi, F. (2026). The association between oxidative balance score and risk of developing prediabetes and type 2 diabetes in adults: a 12-year population-based cohort study. BMC Endocrine Disorders. https://doi.org/10.1186/s12902-026-02610-6

Image Credits: AI Generated

DOI: 10.1186/s12902-026-02610-6

Keywords: oxidative balance score, oxidative stress, prediabetes, type 2 diabetes, antioxidants, cohort study, insulin resistance, lifestyle factors, physical activity, obesity, smoking, Tehran Lipid and Glucose Study

Skeletal muscle is the body’s largest organ, making up roughly 40 percent of total body mass, and its quality is now understood to be a barometer of systemic metabolic health. As people age or become physically deconditioned, fat gradually replaces muscle tissue, accumulating both between muscle fibers as adipocytes and inside the fibers themselves as lipid droplets. Using sensitive magnetic resonance imaging, the researchers quantified this fat in four regions of the thigh and followed participants for years. The results were stark: infiltration in every thigh region showed a dose-dependent relationship with all-cause mortality and with the incidence of diseases spanning cancers, cardiovascular disease, digestive, respiratory, endocrine, neurological, psychiatric, musculoskeletal, genitourinary, eye, ear, and skin conditions. Notably, the link persisted even after adjusting for body mass index, showing that TMFI captures a health risk that conventional weight measures miss entirely.

The magnitude of the effect is striking. Individuals in the highest quarter of thigh muscle fat lost more years of life after age 40 than those in the lowest quarter, and people who developed diseases at younger ages carried significantly more intramuscular fat than those who fell ill later or remained disease-free. The associations were also age- and sex-dependent, appearing more pronounced in men and in adults under 60. According to the authors, this suggests that muscle quality may be an early warning system—flagging vulnerability years or even decades before a diagnosis is ever made.

Perhaps the most consequential finding involves lifestyle. The team showed that the relationship between unhealthy habits and poor outcomes runs, in substantial part, through the muscle itself. Physical inactivity, poor diet quality, obesity, smoking, alcohol consumption, and abnormal sleep duration were each linked to higher TMFI, and mediation analyses revealed that TMFI statistically transmits the effects of these lifestyle factors onto mortality and disease incidence. Sleep followed a U-shaped curve, with the lowest muscle fat observed at roughly 7.5 hours per night, while physical activity and body weight showed nonlinear thresholds. In practical terms, keeping thigh muscle free of fat may be one of the central mechanisms by which healthy living protects the body.

To understand why some people accumulate more intramuscular fat than others, the researchers turned to genetics. In a genome-wide association study of more than 46,000 individuals of European ancestry, they identified 79 lead genetic variants across 47 loci—the majority never before connected to muscle fat. Mapping analyses converged on dozens of genes enriched for traits involving body size, fat distribution, and inflammatory diseases, with strong expression in skeletal muscle, visceral omentum adipose tissue, and reproductive organs. Several newly implicated genes are biologically compelling: ATG7, a core autophagy gene known to govern lipid droplet metabolism, and XYLB, which activates carbohydrate-driven lipogenic pathways, suggest that fat infiltration arises from fundamental disruptions in how muscle handles energy.

Genetic risk proved clinically meaningful in its own right. A polygenic risk score built from the GWAS predicted elevated all-cause mortality and nearly every major category of disease in an independent cohort of over 362,000 people. Critically, genetics and lifestyle interacted: the damaging effect of unhealthy habits was amplified in individuals with high genetic susceptibility, with both multiplicative and additive interaction patterns. The message is that people genetically prone to fatty muscle have the most to gain from exercise, diet, and sleep interventions—and the most to lose from neglecting them.

Drilling down to the cellular level, the team integrated their genetic data with single-cell transcriptomes from nearly 34,000 cells of the vastus lateralis, the largest quadriceps muscle. Among six major cell types, only myogenic cells showed significant genetic relevance to TMFI, and within this lineage, classic slow-twitch myofibers scored highest, followed by fast-twitch myofibers and unusual slow-twitch fibers carrying endothelial molecular features. This cellular picture aligns with muscle physiology: slow-twitch fibers burn fat oxidatively, and their loss—or a shift toward less oxidative fast fibers—reduces lipid clearance, permitting fat to accumulate. Damage to myofibers can also coax resident fibro/adipogenic progenitors into becoming adipocytes, seeding fat deposits within the tissue.

Multi-tissue analyses of gene expression added another layer. By combining GTEx expression quantitative trait loci with the TMFI genetic data through Mendelian randomization and transcriptome-wide association approaches, the researchers pinpointed genes whose activity in nine different tissues was consistently tied to muscle fat. Four genes—SPATA20, PWP2, RPA2, and ZNF100—showed directionally consistent associations across every tissue examined, hinting at fundamental cellular processes such as ribosome assembly, DNA replication, and transcriptional regulation as unexpected contributors to muscle composition.

The blood told an equally rich story. Of 2,923 circulating proteins measured with the Olink platform, 977 were significantly associated with TMFI, and 211 of 251 metabolites measured by nuclear magnetic resonance showed associations. Fat-related proteins such as leptin and FABP4 rose with infiltration, while protective factors like NTRK3, which promotes lipolysis and blocks adipocyte precursor differentiation, fell. Metabolically, lower cholesterol ester content within very large HDL particles signaled impaired lipid transport, and GlycA—a systemic inflammation marker—was strongly elevated. Tissue mapping traced the strongest protein signals to immune tissues, liver, and brain, painting TMFI as a whole-body phenomenon in which inflammation, hepatic fat, and even central nervous system health feed into muscle deterioration.

The team then harnessed deep learning, training one-dimensional convolutional neural networks to predict TMFI from protein or metabolite profiles alone. The proteomic signature achieved a test-set correlation of 0.71 with measured muscle fat—a remarkable result implying that a simple blood draw could one day estimate a person’s muscle fat burden without an MRI. Both blood-derived signatures predicted mortality and systemic disease incidence in independent cohorts of hundreds of thousands of participants, confirming that circulating molecules genuinely capture the biology of fat-infiltrated muscle and its consequences.

The genetic work also surfaced therapeutic leads. Searching the Drug-Gene Interaction Database, the team found that 58 TMFI-linked genes are targeted by 901 drugs, with 15 compounds hitting at least three genes. Among them are vasodilators such as dipyridamole and pentoxifylline, which improve microcirculation and have documented muscle-protective effects, and methylene blue, known to enhance mitochondrial function. More sobering, several common chemotherapy agents—cisplatin, paclitaxel, doxorubicin, and others—appear as potential promoters of muscle fat, consistent with reports that these drugs reduce muscle mass and increase intramuscular fat in cancer patients, a population in which TMFI is already linked to worse prognosis.

The authors caution that the cohort was largely European, middle-aged, and healthier than average, that TMFI was measured at a single time point, and that the study establishes associations rather than proving causation. Still, the breadth of the analysis—spanning epidemiology, genomics, single-cell biology, proteomics, metabolomics, and machine learning—makes this the first systematic portrait of what fat inside thigh muscle means for human health. If future studies confirm these mechanisms, the humble thigh scan could become a routine clinical tool, and preserving lean, fat-free muscle could take its place alongside blood pressure and cholesterol as a cornerstone of preventive medicine.

Subject of Research: Thigh muscle fat infiltration and its multi-omics determinants and health consequences

Article Title: Integrative Analysis Uncover the Effects and Multi‐Omics Features of Thigh Muscle Fat Infiltration

Article References: Zhang, Y., Dang, Q., Zong, X., Chen, H., Wen, S., Xu, S., Wang, K., Wang, X., Zhu, J., Zhu, Z., Ding, C., Ruan, G., & Zhang, Y. (2026). Integrative Analysis Uncover the Effects and Multi‐Omics Features of Thigh Muscle Fat Infiltration. Aging Cell, 25(9), Article e70690. https://doi.org/10.1111/acel.70690

Image Credits: AI Generated

DOI: 10.1111/acel.70690

Keywords: thigh muscle fat infiltration, UK Biobank, skeletal muscle quality, all-cause mortality, genome-wide association study, polygenic risk score, proteomics, metabolomics, single-cell transcriptomics, magnetic resonance imaging, lifestyle factors, aging