Twin Research and Human Genetics

Importance: In adolescence, attempts to lose weight are common, but their long-term impacts on mental and physical health are not known. Objective: To investigate the association between adolescent dieting and exercising to lose weight and adult trajectories of depressive symptoms and body mass index (BMI). Design: A longitudinal cohort study of children born between April 5 and 11, 1970, and followed up to age 51 years. Setting: Adolescents in the 1970 British Cohort Study in England, Wales and Scotland. Participants: A total of 4,650 adolescents with available exposure data. Exposures: Self-reported lifetime dieting or exercising for weight loss measured at age 16 years. Main Outcomes and Measures: Depressive symptoms measured with the nine-item Malaise Inventory, and BMI derived from self-reported height and weight, at ages 26, 30, 34, 42, 46, and 51 years. Results: Among 4,650 adolescents (56.7% girls, 97.7% White), 1,938 (41.7%) had dieted and 343 (7.4%) had exercised for weight loss by age 16 years. In fully adjusted analyses controlling for a wide range of child- and family-based confounders including prior BMI and emotional difficulties, there was evidence that adolescents who had dieted had higher adult depressive symptom trajectories (adjusted mean difference [aMD] 0.13, 95% CI 0.03-0.24, p=0.015) and higher and increasing adult BMI trajectories than those who had not dieted. There was also evidence that adolescents who exercised for weight loss had higher adult depressive symptom (aMD 0.18, 95% CI 0.02-0.34, p=0.031), and BMI trajectories (aMD 0.37, 95% CI -0.03, 0.78, p=0.071), though evidence of the latter was weak. Conclusions and Relevance: Behaviours aimed at weight loss occurring in adolescence might be a shared risk factor for depressive symptoms and high BMI in adulthood. If causal, these findings could suggest that reducing pressures to lose weight in adolescence may help prevent poor mental and physical health across the lifecourse.

Autism development involves multiple genetic and early-life environmental factors. Studying the placenta's gene expression profile may reveal key mechanistic pathways in autism development. Here, using a nested case-cohort design within an Australian population-derived prebirth cohort study (n=1074), we identified 1,644 differentially expressed genes (DEGs; FDR<0.05) in the placenta of children with autism diagnosis (n=43), compared to those without (n=120). The top enriched pathways related to mitochondrial translation, oxidative stress, RNA processing and transcription regulation. CYP1A1, the most important xenobiotic-metabolising enzyme of the placenta, was the top downregulated DEG in the placenta of children with autism, while immuno-regulatory human leukocyte antigen (HLA)-related genes were among the top upregulated DEGs. A machine learning-based approach predicted autism from the transcriptomic data with a median sensitivity of 0.57 (2.5th-97.5th centiles: 0.29, 0.76) and median specificity of 0.92 (2.5th-97.5th centiles: 0.78, 0.98). Weighted Gene Correlation Network Analysis identified eight affected placental gene modules, with the largest five modules being enriched primarily for mitochondrial bioenergetics, oxidative phosphorylation and RNA processing pathways. This placental transcriptomic signature of impaired mitochondrial function and gene transcription regulation among infants subsequently diagnosed with autism has profound implications for understanding both risk factors and prediction, suggesting the possibility of identifying modifiable prenatal pathways to improve autism outcomes.

Background Literature investigating mediation of the association between child abuse and dementia has largely considered composite adverse childhood experience scores rather than individual adverse experiences, despite evidence that different experiences have different impacts on dementia risk. Additionally, prior studies consider mediators in isolation, despite known associations between mediators which may impact indirect pathways from child abuse to dementia. Objectives To investigate whether potentially modifiable health and lifestyle factors mediate the association between child abuse and dementia. Methods We used data from the English Longitudinal Study of Ageing to investigate associations between child abuse and dementia (N:5,448). Indirect pathways through four mediator categories (education, health behaviours, mental health and cardiovascular health) were examined. We used regression modelling to estimate associations between child abuse, mediators and dementia, and causal mediation analysis using the g-formula to estimate the joint indirect effect through the mediators. Results Individuals who experienced child abuse had, on average, an 80% higher hazard of dementia, compared to those who did not (RTE HR:1.80, 95% CI:1.21-2.39). Mental health mediators showed strong associations with both child abuse and dementia. Evidence for other mediators was weaker. Education, health behaviours, mental health and cardiovascular health mediated approximately 18% of the association. Sensitivity analysis revealed that almost all this mediation occurred through mental health. Conclusions Child abuse was associated with higher risk of dementia. Joint mediation analysis suggested that education, health behaviours, cardiovascular health, and mental health accounted for a relatively small proportion of the observed association, with most mediation occurring through mental health. Future research must focus on other potential pathways from child abuse to dementia, including biological and social mechanisms.

Background: Unintended pregnancies can introduce stress and shift life trajectories. Social support may buffer these effects, yet its influence during an unintended pregnancy and into the early parenthood period is not clear. This study aimed to understand the types and gaps of social support experienced throughout this period. Methods: This study utilized interview data under the RISE UP study in The Hague, the Netherlands. 13 mothers and 8 partners who experienced an unintended pregnancy participated in semi structured interviews between 2024 and 2025. Interviews were thematically analyzed using House's social support framework. Results: Different types of support were highlighted across the entire timeline from pregnancy to early parenthood, underlining its dynamic nature. Emotional and instrumental support stood out the most throughout. A key form of emotional support was knowing that support is available, even if not needed immediately. Conclusions: Perceived support during unintended pregnancy is shaped more by contextual factors than by pregnancy intention. While emotional and instrumental support are valued throughout, their form differs by the family's unique circumstances, emphasizing the need for tailored support across the perinatal and postpartum periods.

Background: Documentation burden significantly impacts nursing workload and well-being, with nurses spending an estimated 20-40% of their time on documentation. Ambient AI technologies offer potential to reduce documentation time by mapping real-time nurse-patient conversations to structured EHR data entries with human-in-the-loop verification. Methods: This protocol describes a pragmatic, EHR-embedded randomized controlled trial evaluating the effectiveness of an Ambient AI tool in reducing nursing documentation time across three inpatient medical/surgical units. The study employs a closed-cohort, stepped-wedge, unit-randomized design, integrating the intervention into routine clinical workflows. The primary outcome is documentation time per shift hour, derived from EHR audit logs. Secondary outcomes include documentation burden, professional well-being, and perceived usability. Results: The trial is being implemented within a shared governance model that integrates executive oversight, operational feasibility, and research rigor. Multidisciplinary workgroups coordinate technical integration, user experience, and analytics, ensuring alignment between operational priorities and pragmatic trial objectives. Early implementation has highlighted the importance of adapting training and analytic strategies to address differential intervention exposure, as well as the need for rapid operational responses to late-emerging technical issues. Discussion: This protocol demonstrates the feasibility of embedding a randomized pragmatic trial within a health system-led operational deployment of Ambient AI for inpatient nursing documentation. The approach highlights the necessity of adapting existing outpatient provider-focused AI implementation strategies for inpatient nursing, emphasizing the unique nature of different nursing care environments. Recruitment challenges and the integration of research with operational workflows are discussed as key considerations for future pragmatic AI trials in nursing. Keywords: Artificial Intelligence; Ambient AI; Nursing Documentation; Documentation Burden; Large Language Models; Speech Recognition Software; Stepped-Wedge Design ClinicalTrials.gov Identifier NCT07456241V4: 2026-05-27 https://clinicaltrials.gov/study/NCT07456241

Abstract Background: The influence of taurine on biological ageing remains unclear, particularly whether it acts as a causal driver or a functional biomarker. We aimed to disentangle the distinct roles of plasma taurine relative abundance, dietary taurine supply, and genetic metabolic capacity on all-cause mortality and unhealthy ageing. Methods: This prospective study used data from the Korean Genome and Epidemiology Study (2001~2022). A subcohort of 2,321 participants (mean age 56.5 years; 51.4% female) with complete metabolomic, dietary, and genomic data was analyzed. Three independent pathways were evaluated: (1) plasma taurine/total amino acid (AA) ratio, (2) dietary taurine to protein ratio, and (3) a weighted genetic risk score (GRS) from 21 SNPs in taurine biosynthesis and transport genes. Primary outcomes were all-cause mortality and unhealthy ageing (Physiological Healthy Ageing Index [PHAI] score [&le;] 25th percentile). Results: A higher plasma taurine/total AA ratio was consistently associated with improved ageing outcomes. Participants in the highest quartile showed 29% lower all-cause mortality (Hazard Ratio [HR], 0.71; 95% Confidence Interval [CI], 0.52-0.98; P for trend = .04) and lower risk of PHAI-based unhealthy ageing (HR, 0.77; 95% CI, 0.59-1.00; P for trend = .04) versus the lowest quartile. Dietary taurine-to-protein ratio was not associated with mortality (P for trend = .70), nor was the GRS (P for trend = .74). Conclusions: The protective association of taurine was linked to its relative abundance within the systemic amino acid pool, rather than dietary intake or genetic predisposition, supporting taurine as a functional biomarker of metabolic efficiency rather than a deterministic causal driver of ageing.

ABSTRACT IMPORTANCE Childhood obesity is a growing global health concern associated with adverse physical, psychiatric, and neurodevelopmental outcomes. Although previous neuroimaging studies have linked obesity to widespread alterations in brain structure and function, it remains unclear how well multimodal neuroimaging measures and genetic markers can predict future weight gain and inform early intervention strategies. OBJECTIVE To evaluate the predictive utility of multimodal MRI measures and polygenic risk scores for obesity in estimating proportional body weight at baseline and predicting weight gain over one year in preadolescent children. DESIGN, SETTING, AND PARTICIPANTS This study used data from the Adolescent Brain Cognitive Development (ABCD) Study, a large-scale, multisite longitudinal cohort of children aged 9 to 10 years (N = 11,880). Analyses included baseline data collected between 2016 and 2018, and one-year follow-up data collected between 2018 and 2020 across multiple imaging sites. MAIN OUTCOMES AND MEASURES Elastic net regression models were applied to structural MRI (including diffusion tensor imaging) and resting-state functional MRI data to predict baseline triponderal mass index (TMI), a weight-for-height measure that more accurately reflects adiposity in children than body-mass index (BMI). Longitudinal classification models were developed to predict excess weight gain relative to normative developmental trajectories at one-year follow-up. Models were evaluated with and without the inclusion of polygenic risk scores and other non-imaging covariates. Generalizability was assessed using leave-one-site-out cross-validation. RESULTS Structural MRI measures predicted baseline TMI with an R^2 of 0.21, whereas resting-state functional MRI measures predicted TMI with an R^2 of 0.08. Classification models predicted one-year weight gain with area under the receiver operating characteristic curve (AUC) values of 0.73 for structural MRI and 0.60 for resting-state functional MRI. Including polygenic risk scores and other covariates improved model performance (structural MRI: R^2 = 0.25, AUC = 0.75; resting-state functional MRI: R^2 = 0.15, AUC = 0.69). Leave-one-site-out cross-validation revealed reduced generalizability across imaging sites (structural MRI R^2 = 0.13-0.17; resting-state functional MRI R^2 = 0.02-0.09; structural MRI AUC = 0.73-0.74; resting-state functional MRI AUC = 0.60-0.67). CONCLUSIONS AND RELEVANCE Multimodal MRI measures were associated with proportional body weight and demonstrated modest predictive utility for future weight gain in preadolescent children, explaining up to one fifth of the variance in weight-related outcomes. The addition of genetic and non-imaging variables improved prediction accuracy, underscoring the multifactorial nature of childhood obesity. However, the observed decline in performance under site-wise cross-validation highlights the need to address site-related variability to enhance reproducibility and generalizability in neuroimaging-based predictive models of pediatric obesity.

Orofacial clefts (OFCs), including cleft lip (CL), cleft palate (CP), and cleft lip with cleft palate (CLP), are among the most common craniofacial malformations in humans, with a birth prevalence of approximately 1 in 1,000 live births globally. Non-syndromic forms of OFC are predominantly genetic, with significant variability in prevalence across populations. Understanding the genetic underpinnings of OFCs remains a key public health priority, given the substantial medical and societal burden of these conditions. Recent genome-wide association studies (GWAS) have implicated numerous genetic loci, but challenges remain due to genetic heterogeneity and complex gene-environment interactions. This study aimed to identify sex-specific genetic risk factors for cleft lip with or without cleft palate (CL/P) through a meta-analysis of whole genome sequencing (WGS) data from 1,922 case-parent trios across eight diverse cohorts. Our approach revealed four SNPs in three distinct regions that showed genome-wide significant sex-specific effects. However, despite each of these SNPs passing standard quality control filters, follow-up analyses showed that these signals most likely were technical artifacts caused by sequencing errors, in particular mis-mapped reads due to sequence similarities with the sex chromosomes. These findings highlight the necessity for careful scrutiny when studying differences between the sexes in genetic association studies.

Background: Mortality analysis traditionally focuses on the single underlying cause of death (UCD), which obscures the wider morbidity process at the end of life. Multiple causes of death (MCoD) data, recording all conditions on the death certificate, are increasingly used as a proxy for end-of-life multimorbidity, yet how accurately they represent it remains underinvestigated. We assessed whether recorded causes reflect end-of-life health conditions or rather the chain of events leading to death. Methods: Using linked Danish registers (Population, Cause of Death, Chronic Diseases, and Cancer), we studied residents aged 50+ diagnosed with COPD, dementia, diabetes, or cancer who died in 2010-2022 (ranging from 38779 to 224330 per disease cohort). We examined how often each diagnosed disease appeared on the certificate, its location and selection as the UCD, factors associated with its appearance (logistic regression), disease-specific mortality (multiple decrement life tables), and disease associations (Cause of Death Association Indicator, CDAI). Results: Cancers appeared on the death certificate far more often than chronic diseases (around 75% versus 19-58%) and were usually recorded in Part 1 and selected as the UCD, whereas chronic diseases were rarely the UCD. The odds of a disease appearing depended on factors such as age at and time since diagnosis. When a diagnosed disease was recorded, the certificate traced a coherent path to death; when it was absent, ill-defined causes became more common. The CDAI highlighted specific association pathways between diseases. Conclusions: MCoD data capture only part of the chronic disease burden present at death and should be interpreted cautiously as a proxy for end-of-life multimorbidity. They are, however, well suited to describing the pathways leading to death.

High-dimensional Mendelian randomization (MR) screens can prioritize candidate dietary and immune pathways for insomnia, but their interpretation is constrained by multiple testing, cross-dataset instability, and limited correspondence between genetic constructs and measured population variables. We conducted an exploratory cross-design analysis that combined MR screening of 231 dietary traits and 731 immune phenotypes, targeted cross-release genetic follow-up in FinnGen R12 and R13, and population-based analyses in NHANES and CHARLS. The targeted R13 follow-up prioritised an omelette-related dietary signal (OR 0.773, 95% CI 0.651-0.917; within-layer FDR q=0.00783), a mixed-fruit signal (OR 1.285, 95% CI 1.102-1.498; within-layer FDR q=0.00683), and CD33- and HLA-DR-related immune-cell traits. In NHANES, mapped omelet/scrambled-egg intake was associated with lower odds of sleep problems in 2017-March 2020 (OR 0.746, 95% CI 0.600-0.927; FDR=0.033) and doctor-reported sleep disorder in 2005-2006 (any intake: OR 0.313, 95% CI 0.157-0.624; FDR=0.008; per 50 g: OR 0.721, 95% CI 0.569-0.914; FDR=0.019). Mixed-fruit proxies were not directionally concordant. Higher C-reactive protein (CRP) was associated with sleep problems in NHANES (OR 1.192, 95% CI 1.085-1.309; FDR=0.001) and frequent restless sleep in CHARLS (OR 1.097, 95% CI 1.049-1.147; FDR<0.001). These findings provide exploratory genetic prioritization and population-based association evidence for selected dietary constructs and systemic inflammatory proxies. They do not establish a causal diet-immune-insomnia mechanism, confirm flow-cytometry immune-cell phenotypes, or support dietary intervention recommendations.

Background & Aims The adoption of plant-based diets in the United Kingdom (UK) is increasing, which has potential health benefits, but may increase risk of inadequate intakes of some nutrients. We aimed to assess differences in biomarkers of nutritional status and disease across diet groups in UK adults. Methods This cross-sectional analysis included 124 omnivores, 131 flexitarians, 71 pescatarians, 124 vegetarians, and 183 vegans from the Feeding the Future (FEED) follow-up study (2024-2025). Capillary blood samples were collected and analysed for: haemoglobin; lipid measures (low- and high-density lipoprotein cholesterol (LDL-C and HDL-C), non-HDL-C, total cholesterol, and triglycerides); vitamins B12 and D. We estimated age- and sex-adjusted arithmetic or geometric mean concentrations and 95% confidence intervals of these biomarkers across diet groups. Participants taking lipid-lowering medications were excluded for analysis of lipid markers (n = 85). Results We observed differences in concentrations of cholesterol, triglycerides, and vitamin B12 across diet groups (P heterogeneity for all [&le;] 0.03). Cholesterol markers (mmol/L) were lower with greater exclusion of animal foods (omnivores vs vegans, total cholesterol = -0.8; LDL-C = -0.7; HDL-C = -0.2). Triglyceride concentrations (mmol/L) were similar across groups, with slightly higher values in vegetarians (+0.2) and vegans (+0.1) compared with omnivores. Vitamin B12 concentrations (pmol/L) were highest in vegans and lowest in vegetarians compared to omnivores. Supplement users had higher vitamin B12 and D concentrations in all groups (P heterogeneity between strata = <0.001), while non-supplementing vegetarians and vegans had lower, but not deficient, vitamin B12 concentrations compared to omnivores (P heterogeneity between diet groups = <0.001). Conclusions In this contemporary UK cohort, those following plant-based diets had more favourable blood lipid profiles, with little evidence of vitamin B12 or D deficiency, or anaemia. Supplement use was associated with higher vitamin B12 and D concentrations, particularly among vegetarians and vegans.

Introduction: Multimorbidity clusters have been associated with increased dementia risk. While lifestyle factors may modify dementia risk, their role in multimorbidity clusters remains unclear. Method: Data from UK Biobank was used to identify clusters of chronic conditions using latent class analysis, assess their associations with dementia risk using Cox regression, and potential moderating effects of lifestyle factors. Results: We included 465,175 participants (mean age (SD) = 56.52 (8.01), 53.87 % female). Five clusters were identified and significantly associated with increased dementia risk, with the cardiometabolic (HR = 2.14, p < 0.001) and mental health cluster (HR =1.99, p < 0.001) exhibiting the highest risk. Only moderate physical activity lowered dementia risk in the pain-dominated multimorbidity cluster (HR = 0.77, p = 0.039). Discussion: Lifestyle factors including physical activity may protect against dementia in specific multimorbidity clusters. Future research involving objective and multiple lifestyle measures is needed.

Background: Healthcare-associated infections (HAIs) remain a major patient safety challenge in sub-Saharan Africa, where gaps in infection prevention and control (IPC) practices persist. Nursing and midwifery students are particularly vulnerable during clinical training, yet evidence on their IPC knowledge and compliance in Ghana remains limited. Objective: To assess knowledge of nosocomial infections and compliance with standard precautions among third-year nursing and midwifery students at Kwame Nkrumah University of Science and Technology (KNUST), Ghana. Methods: A descriptive cross-sectional study was conducted among 150 third-year nursing and midwifery students at KNUST, Kumasi, Ghana, between 28 June and 9 July 2021. Data were collected using a structured questionnaire adapted from WHO and CDC guidelines. Knowledge was assessed using a 19-item scale and compliance using a 17-item Likert-type scale. Chi-square tests, Fisher's exact test, and Spearman's rank correlation were used to examine associations between knowledge and compliance. Results: Overall, 143 respondents (95.3%) demonstrated high knowledge of nosocomial infections and standard precautions (mean score: 16.44/19; SD: 1.59). High compliance with standard precautions was reported by 112 respondents (74.7%; mean score: 59.13/68; SD: 5.89). Compliance was strongest for hand hygiene and glove use but lower for PPE use during splash-risk procedures and safe needle-handling practices. No statistically significant association was found between categorized knowledge and compliance levels (df = 1, p = 0.491; Fisher's exact p = 0.679). However, a modest positive correlation was observed between continuous knowledge and compliance scores (Spearman's rho = 0.326, p < 0.001). Conclusion: Although knowledge of nosocomial infections was high, compliance varied across standard precaution domains, with notable gaps in PPE use and safe needle-handling practices. Practical training, simulation-based learning, and supervised clinical reinforcement are needed to bridge the knowledge practice gap in nursing and midwifery education in Ghana.

Despite the importance of population descriptors in human genomics research, many scientists struggle to translate evolving ethical guidelines into their computational workflows. To characterize this gap between recommendations and implementation, we conducted a mixed-methods survey of early-career researchers to assess how they understand and implement the landmark 2023 NASEM report on the use of population descriptors in human genetics research. We show that while exposure to the report fosters ethical awareness, fundamental misconceptions about race and ancestry persist across academic disciplines, and trainees face structural bottlenecks, including legacy data constraints and a lack of technical confidence. To address this gap, we offer actionable, stakeholder-specific recommendations across the research lifecycle ranging from decision-support tools to "bring-your-own-data" workshops to leadership from academic journals, scientific societies, and trainee mentors. Ultimately, we argue that to promote scientific rigor and reduce bias in genetic discoveries, the scientific ecosystem must invest in the infrastructure necessary to empower the next generation of researchers.

Motivation: Linkage disequilibrium score (LDSC) regression is a popular method to estimate heritability for complex traits using summary statistics and linkage disequilibrium (LD) reference panels, offering a practical alternative to methods requiring individual-level data. Despite its widespread use, LDSC regression can produce biased heritability estimates. The properties of LDSC regression were investigated using summary statistics from several large-scale Alzheimer's disease (AD) studies and a variety of LD reference panels. These heritability estimates were compared with those obtained from individual-level data. Results: When LDSC regression was applied to summary statistics obtained from meta-analysis, it led to an underestimation of heritability. This can occur if meta-analysis is used to combine studies of different ancestries leading to the caveat of the lack of an appropriate LD reference panel. Additionally meta-analyses often include studies with different phenotype definitions, that not only impacts heritability estimates but also makes them uninterpretable. Summary statistics generated from imputed variants, even those with high imputation accuracy, can lead to underestimation of heritability. For example, the heritability estimates for AD were reduced from 0.265 (se 0.148) to 0.160 (se 0.041) when imputed variants (INFO>0.9) were included compared to analyzing only genotype array variants. A decrease in heritability estimates was also observed when individual-level imputed variant data were analyzed using GCTA-GREML. Our findings highlight the caveats of estimating heritability using meta-analysis summary statistics or imputed data instead of genotyped or sequence data.

Universities provide a key opportunity to deliver social prescribing, a care pathway that aims to connect people with non-medical forms of support within the community to address their social, emotional, and practical needs. However, it is unclear whether students in the UK are aware of social prescribing and whether it would be an acceptable form of support. We surveyed 775 university students across the UK who completed a questionnaire measuring awareness and perceptions of social prescribing. We described awareness and attitudes and used logistic regression to explore how they differed according to individual characteristics. We found an awareness-attitude paradox. Only 25% of students were aware of social prescribing, but attitudes were overwhelmingly positive once explained: 97% thought it could support mental health and wellbeing; 95% believed universities should offer it; and 89% would accept social prescribing if offered by a healthcare professional. Students who were older, postgraduates, and had English as their first language were among those with higher odds of being aware of social prescribing, but positive attitudes were more evenly reported across the sample. Our findings indicate that implementation efforts should prioritise awareness-raising and clear referral pathways, rather than increasing students' willingness to engage with social prescribing.

Neuropsychiatric polygenic indices (NPGIs) are used as genetic predictors of poor mental health. However, NPGIs are also associated with environmental factors which could affect mental health in adulthood, including the rearing environment. Hence, their "genetic" effects are both direct and environmentally mediated. There is a need to identify alternative genetic predictors without environmental signal. Endophenotype-based polygenic indices (EPGIs) trained on brain structure and function are under-studied alternatives which, due to their relative biological proximity, may exhibit associations with mental health outcomes which are less environmentally mediated than those of NPGIs. Using four representative UK samples (Understanding Society; UKHLS, NCDS, BCS70 and MCS) we employ sex-stratified path models to estimate the direct and environmentally mediated effects of eleven NPGIs and 30 EPGIs on adult mental health, focussing on the rearing environment. The depression NPGI is consistently associated with mental health symptoms across most sex-stratified sub-samples (best meta-analysis beta = 0.091, p 0.001) but demonstrates 1.6 - 24.5% environmental mediation. Seven other NPGIs and three EPGIs show sample- and sex-specific associations with mental health symptoms. NPGIs for attention deficit hyperactivity disorder, depression and substance use disorder are robustly associated with measures of the rearing environment, which in turn are frequently associated with mental health symptoms. Sensitivity analyses find that NPGI associations vary substantially depending on who is included in the sample. In conclusion, the rearing environment likely mediates a substantial portion of NPGIs' so-called "genetic" effects on mental health symptoms, but EPGIs are not currently powerful enough to replace them.

Summary Background: Spatial variation in heat-related mortality remains poorly understood, particularly at fine geographical scales. We conducted a nationwide small-area study to examine the association between spatial variation in heat-related mortality and environmental, demographic, health, and socio-economic factors. Methods: We obtained daily all-cause mortality data for people aged [&ge;] 65 years during the summers of 2011-2023 and linked them with municipality-level daily temperature estimates from the ERA5-Land reanalysis dataset. We applied a two-stage Bayesian hierarchical model to estimate small-area heat-related mortality and assess the contribution of community characteristics to spatial variability. Findings: Heat-related mortality showed marked geographical differences, with the highest rates in southern and southeastern Italy. Across municipalities, the relative risk at the 90th temperature percentile, relative to the minimum mortality temperature, ranged from 1.06 to 1.33. The heat-attributable fraction exceeded 6% in several southern municipalities, while excess mortality surpassed 8 deaths per 1,000 inhabitants in parts of the Po Valley, Tuscany, Apulia, and Sicily. National heat-attributable mortality peaked in 2022, with an estimated 17,828 deaths (95% credible intervals: 17,339, 18,285) among older adults. Municipalities with higher average temperatures, less green space, higher obesity prevalence, and more residents aged [&ge;] 85 years had higher heat-related mortality. Educational attainment and employment were among the strongest modifiers of spatial variation. Interpretation: Our findings highlight substantial small-area differences in heat-related mortality across Italy and identify socio-economic deprivation as a key determinant of vulnerability. Heat is likely to disproportionately affect disadvantaged communities, reinforcing the need for adaptation strategies addressing social inequality. Funding: Imperial College Research Fellowship; Italian Ministry of Health PNC (CUP J55I22004450001); NIHR Imperial Biomedical Research Center (BRC NIHR203323).

Cystic fibrosis (CF) is characterized by defective CFTR-mediated chloride transport, resulting in elevated sweat chloride concentrations. As people with CF (PwCF) now live longer due to highly effective CFTR modulators, exercise has become integral to maintaining health, yet it introduces additional physiological demands on salt and fluid balance. In this study, we used a wearable microfluidic biosensor (CF Patch) to quantify sweat rate and chloride loss during exercise performed both in the supervised laboratory and remote free-living in PwCF and healthy volunteers (HV). Participants completed exercise sessions under both conditions, with continuous heart rate monitoring and sweat collection with real-time measurement of sweat characteristics. Sweat volume and chloride concentration were assessed by colorimetric image analysis, enabling estimation of total fluid and chloride loss at the end of each exercise session. PwCF exercised for a longer duration at a lower average heart rate during remote exercise compared to laboratory exercise though exercise volume (average heart rate x duration) was greater during remote exercise. There was a positive association between exercise volume and both fluid and chloride loss for both PwCF and HV. PwCF exhibited greater chloride loss for a given exercise volume compared to HV, though fluid loss was similar. Further, compared to HV, PwCF demonstrated significantly greater intra- and interindividual variability in sweat chloride loss across the remote exercise sessions. Collectively, these findings provide evidence for the feasibility and physiological validity of remote exercise assessment and establish the feasibility and physiological validity of wearable sweat sensing for remote monitoring of fluid and electrolyte dynamics during real-world exercise. In addition, the variability of chloride loss in response to exercise suggests utility of the CF Patch in providing personalized fluid and salt repletion data for PwCF and advances the translational potential of digital sweat diagnostics for personalized CF care.

Abstract Background. Chronic low-level exposure to lead, cadmium, mercury, and arsenic remains a determinant of premature mortality in the U.S. general population, but previous hazard-ratio analyses do not characterize how exposure shifts the lower tail of the survival distribution, where premature mortality is concentrated. Objectives. We estimated the association of whole-blood lead, whole-blood total mercury, urinary cadmium, and the sum of urinary inorganic and methylated arsenic species with the 10th, 25th, and 50th conditional quantiles of follow-up time to all-cause mortality among U.S. adults aged 40 years and older. Methods. NHANES Continuous 1999 to 2018 was linked to the National Death Index through December 31, 2019 (n = 29,652). Censored quantile regression was fit per metal on the log2 scale at quantiles {tau}{0.10, 0.25, 0.50}. A restricted-cubic-spline (RCS) censored-quantile-regression was fit for blood lead and urinary cadmium to investigate the threshold effect. Results. Over a median follow-up of 9.1 years, 7,215 deaths were ascertained. A doubling of urinary cadmium was associated with -1.57 years of follow-up (95% CI: -2.08, -1.07) at the 10th conditional quantile, -1.50 (-2.04, -0.96) at the 25th, and -1.49 (-1.93, -1.04) at the median (Benjamini Hochberg q < 0.001 throughout). A doubling of whole-blood lead was associated with -0.70 years (95% CI: -0.99, -0.40) at the 10th conditional quantile, -0.62 (-0.92,-0.31) at the 25th, and -0.61 years (-0.89, -0.34) at the median; the absolute loss was largest at {tau} = 0.10 for both metals. Urinary arsenic-metabolite sum was not associated with conditional follow-up at the estimable quantiles. Despite adjustment for dark and fatty-fish intake or DHA/EPA, whole-blood total mercury was associated with longer follow-up (i.e., negatively associated with mortality risk), possibly due to residual confounding by broader dietary or socioeconomic factors, rather than a true protective effect. The cadmium association was additionally robust to the mutual adjustment of lead. Discussion. Low-to-moderate urinary cadmium and whole-blood lead were associated with fewer years of follow-up survival at the lower-tail and median conditional quantiles of survival, with the largest absolute losses at the lower tail of the conditional survival distribution, where premature mortality is concentrated. These findings support continued reductions in U.S. cadmium exposure and lead with particular benefit for adults most vulnerable to premature death.