Disparities in the adverse health effects due to ambient environmental exposures have long been documented in the environmental epidemiology literature. A growing body of environmental epidemiology literature has focused on how detrimental aspects of the physical environment (e.g., poor housing quality) and social environment (e.g., chronic social stressors) can exacerbate the adverse health effects of environmental exposures (e.g., air pollution, heat). However, the literature on protective factors which might mitigate adverse health effects of environmental exposure is more limited. We borrow from the climate resilience and disaster preparedness literature to discuss how protective community assets may be identified, operationalized, and understood in environmental epidemiologic research. We outline two major pathways through which community assets may protect environmental health: by reducing overall exposure (mediation) and by reducing susceptibility (effect modification). This framework can help environmental epidemiologists and other public health researchers select and understand appropriate community assets to test as effect modifiers or mediators of associations between environmental exposures and adverse health outcomes. We present examples of community assets organized into five domains and highlight pragmatic challenges that may arise when considering assets in large-scale epidemiologic research-for example, limitations on availability of publicly available data at meaningful spatial scales, and challenges interpreting available community asset data. Finally, we posit that research focused on community assets can inform scalable, impactful health-promoting interventions.
The American College of Epidemiology (ACE) Ethics and Policy Committee was newly formed in 2023 through the merger of separate Ethics and Policy Committees, and over the last three years has been involved with sponsored symposia, collaborations, policy consultations, education, mentoring, and capacity building. The purpose of this reflection paper is to highlight the achievements of the Committee and further highlight its ethics and policy work and presentations. Speakers with diverse expertise were invited to present at consecutive ACE Annual Meetings. Invited symposia speakers presented along the themes of climate change (PT, CH, JH), causal inference in epidemiology (JH, SW, DW, WL), and integrity in epidemiologic research (IB, DS, WA), aligning with the overall theme of each Annual Meeting. At the same time, the Committee's work involved: (i) consultation on policy and position statements developed by the International Network for Epidemiology in Policy (INEP); (ii) education on ethics in epidemiology and public health through the Ethics Syllabi Collection Project; (iii) mentoring graduate-level epidemiology students as part of the ACE Scholars Program; and (iv) developing and strengthening ethics guidance and resources. The sociopolitical landscape and ongoing global health crises have challenged the foundations of epidemiology and its credibility as a scientific discipline to serve public health and maintain the public's trust. Using a principle-based approach, we examined the ethical considerations in each of the themed symposia and highlight the key principles, values, and professional virtues including justice, respect for persons and their communities, beneficence, transparency, accountability, veracity, excellence, and integrity, among others. We provide recommendations on how to focus research efforts and ethically engage with interdisciplinary colleagues and varied audiences while under pressure to be an advocate or policy expert, and counter misinformation. Our reflection paper demonstrates contemporary ethical reflection through the collective work of the Committee with symposia presenters who together represent expertise in epidemiology, public health, bioethics, health disparities, law, bioinformatics, medicine, and occupational and environmental health. Other work of the Committee involved developing more formalized approaches to policy consultations and furthering our efforts in education, mentoring, and capacity building. The ethical intersections of epidemiology and public health remind us of their shared goal which is to improve population health. Despite the attacks on science and the ongoing public scrutiny of these disciplines, the Committee is committed to ongoing collaborations, policy consultations, education, mentoring, and capacity building in broad and specialized areas of epidemiology and public health and supports the ethical analysis of contemporary issues using established and emerging ethical principles, approaches, and frameworks.
The relationship between exposure to perfluoroalkyl substances (PFAS) and birthweight remains unclear. Pooling data across multiple cohorts can increase power, leading to more representative populations and exposure distributions, but confounding by cohort can be a major source of bias. To understand this potential bias, we assessed the relationship between exposure to five PFAS and birthweight utilizing data from 5480 mother-infant dyads across 17 Environmental influences on Child Health Outcomes (ECHO) Cohort sites. The relationship was assessed in several ways: covariate-adjusted models without cohort adjustment as well as adjustment via fixed and random effects. Findings from analysis with cohort adjustment resulted in significantly inverse relationships for four of the five PFAS considered. Adjustment via fixed and random effects produced similar findings. Failure to adjust for cohort resulted in bias of varying direction and magnitude depending on the PFAS considered. Results were supported in simulated data. In this study, we saw evidence of confounding bias by cohort even after adjustment for covariates, while adjustment by both fixed and random effects for cohort resulted in comparable results.
The childhood environment is critical for brain development. However, most neuroimaging studies examine individual environmental measures (e.g., socioeconomic status) or a limited set of exposures, obscuring how the combination of complex, real-world exposures jointly influence brain development. Here we investigated how white matter shape and tissue properties are linked to the childhood exposome, a multidimensional measure capturing over 300 environmental exposures. Using multi-shell diffusion MRI from 8,183 children (ages 9-10) in the ABCD study, we quantified microstructural and macrostructural properties across 62 person-specific white matter tracts. The exposome showed widespread and highly replicable associations with both white matter microstructure and macrostructure: more advantaged environments were associated with larger tract macrostructure and lower orientation dispersion. Principal component analysis revealed that the dominant axis of exposome-white matter covariation aligns with the cortical sensorimotor-association hierarchy, such that tracts spanning this hierarchy exhibit the strongest associations with the exposome. Multivariate models demonstrated that patterns of white matter features explained 25% of the variance in the exposome in unseen individuals. Notably, white matter-based prediction of cognition was markedly reduced after accounting for the exposome (~82% reduction in explained variance), indicating that brain-cognition associations overlap substantially with variance captured by the exposome. These findings generalized to independent data from the Healthy Brain Network (n=869), which differs substantially from ABCD in MRI acquisition, participant selection, and childhood environments. Together, these results suggest that white matter architecture strongly reflects the childhood environment.
BackgroundSystemic lupus erythematous (SLE) shares many common epidemiologic features with other autoimmune diseases or diseases associated with an underlying Epstein-Barr virus (EBV) infection. It was hypothesized that the geographic variation of mortality from SLE would reveal a similar pattern as Hodgkin lymphoma (HL), multiple sclerosis (MS), Crohn's disease (CD), and ulcerative colitis (UC).MethodsUsing the vital statistics of 21 countries from 1951-2022, overall and age-specific death rates from the 5 diseases were calculated for each individual country. The death rates of different countries were compared using linear regression analysis.ResultsWhereas other autoimmune diseases or diseases associated with an underlying EBV infection, such as HL, MS, CD, and UC, showed remarkably similar geographic variations, the geographic distribution of SLE did not fit this overall pattern. High death rates from SLE were not clearly associated with developing versus developed countries, northern versus southern latitude, or any specific continent. However, similar geographic distributions of SLE were consistently found among consecutive age groups, ranging from 0-4 to 85+ years.ConclusionsThe similarities in the geographic distributions of death rates from HL, MS, CD, and UC suggest that these 4 diseases share a set of one or more common environmental risk factors. Other environmental risk factors besides EBV infection must contribute to the varying occurrence of SLE across the globe. These risk factors start exerting their influence at a very young age of less than 5 years.
Police violence is increasingly recognized as a public health crisis, disproportionately affecting Black, Indigenous, and other communities of color due to long-standing patterns of racialized surveillance and disinvestment. Environmental stressors such as heat have also been linked to increased aggression, stress reactivity, and violence, suggesting that as climate change drives more frequent and intense extremes in temperature, these conditions may amplify existing risks of fatal police encounters. This study evaluated whether extreme ambient temperatures were associated with fatal police violence and whether structural neighborhood deprivation modified this relationship. Our nationwide case-crossover analysis examined daily maximum temperature and fatal police violence in the United States (2013-2024) using data from Mapping Police Violence. We estimated odds ratios across percentiles of the temperature distribution and analyses were stratified by neighborhood-level measures of deprivation, using Index of Concentration at the Extremes metrics for education, income, racialized income, and homeownership. Our main analysis revealed that compared to the median temperature (23.5 °C), the odds of fatal police violence at the 5th temperature percentile were reduced by 12% (95 percent CI: 0.806 to 0.955), while the odds at the 99th percentile were increased by 11% (CI: 1.037 to 1.185). While there was limited evidence of effect modification by neighborhood deprivation metrics, we found neighborhoods with higher levels of deprivation were disproportionately burdened by fatal police violence. These findings highlight the importance of temperature as a determinant of fatal police violence, suggesting that policies that address neighborhood deprivation and fatal policing may be needed on a warming planet.
Exposure to extreme temperatures and fine particulate matter is hazardous to human health, especially among children. With growing evidence on the impact of these environmental hazards on child health-including increased risks of respiratory illnesses, heat-related illnesses, and developmental challenges-there is a substantial need to identify high-risk areas for potential adverse pediatric health outcomes. In this study, we developed pediatric vulnerability indices at the census tract scale across the contiguous United States (CONUS) using five dimensionality reduction methods, including unsupervised machine learning and deep learning approaches. We integrated these indices with data on extreme temperature (2012-2024), PM2.5, and black carbon exposures from 2010 to 2020, enabling spatial analysis of environmental hazards and pediatric vulnerability. Among the five methods tested, principal component analysis (PCA) was selected for its balanced representation of 12 vulnerability factors, which explained 23% of the variance in the data. We observed that co-exposure to extreme temperature and air pollutant exposures were highest in the West, Southwest, and certain parts of the South and Northeast. Approximately 36% of the CONUS showed statistically significant hotspots of co-exposures to higher temperatures and air pollutants, concentrated in the West, Northwest, and Southwest. High-risk areas for pediatric vulnerability and co-exposure to environmental hazards were identified in both urban and rural communities, including indigenous lands and agricultural regions. These findings can aid policymakers and public health officials as a preliminary resource in developing heat action plans and allocating cooling centers to protect children living in the most affected communities. Children are particularly vulnerable to health issues associated with high temperatures and air pollution. In this study, we sought to identify the areas in the United States that pose the greatest risk to children from both extreme heat and air pollution. We created an index to measure children's vulnerability across neighborhoods, using data on family income, access to healthcare, and other social factors. We also looked at data on high temperatures and air pollution from 2012 to 2024. The results of this work indicate that children living in the West, Southwest, and certain parts of the South and Northeast are at a higher risk of adverse health outcomes due to extreme temperatures and air pollution. Approximately one‐third of the country's area experienced both high temperatures and high air pollution simultaneously. These areas included both cities and rural places, as well as indigenous lands and farming communities. Our results help decision‐makers and health officials as a preliminary resource for allocating resources, such as cooling centers, and for developing plans to protect children during periods of extreme heat and high air pollution.
Cognitive impairment is a major public health concern among older adults. This study examined the associations of purpose in life (PIL), personal growth (PG), and life satisfaction (LS) with cognitive impairment risk, as well as potential underlying pathways. The study population comprised 1,179 U.S. women (aged 77-93 years) from the Women's Health Initiative Memory Study - Epidemiology of Cognitive Health Outcomes (WHIMS-ECHO) cohort who completed psychological well-being assessments in 2012 and were followed until 2021. Cognitive status was evaluated annually using standardized assessments and central adjudication. Over an average of 5.4 years of follow-up, 355 participants were classified with MCI (175) or dementia (180). The association between PIL and cognitive impairment was largely mediated by lower perceived stress and higher physical activity (61%), rendering the direct effect non-significant. Women in the highest PG quartile had a 33% lower risk of impairment (HR = 0.67, 95% CI: 0.46-0.96). Mediation analyses showed both direct and indirect effects of PG. No association was found for LS. PG and PIL were linked to lower cognitive impairment risk, primarily via stress reduction and physical activity. Targeting these factors may promote cognitive health among aging populations.
BACKGROUND: Alzheimer’s disease (AD) remains a major therapeutic challenge, characterized by high clinical trial failure rates and limited efficacy of current treatments. Drug repurposing offers a faster, lower-risk route to new therapies; however, existing computational approaches often prioritize predictive accuracy over mechanistic novelty and interpretability, both of which are critical for clinical translation. RESULTS: We introduce a quality-diversity Automated Machine Learning (AutoML) framework that integrates biologically informed graph neural network (GNN) embeddings with a MAP-Elites-guided search to discover predictive yet mechanistically distinct therapeutic hypotheses. Drugs and genes are embedded using GraphSAGE and variational graph autoencoders trained on the Alzheimer’s Knowledge Base (AlzKB), with a clustering loss used to anchor known AD entities and define dimensions of biological novelty. In an AD case study using matched ADSP GWAS-derived features, our framework successfully recovered known drug–gene relationships and identified robust consensus candidates across independent validation runs. Most notably, the search consistently prioritized Triclosan—a recently identified environmental risk factor for AD neuroinflammation—and the Ketamine/Quazepam pair, suggesting a model-driven preference for restoring synaptic E/I balance. Furthermore, exploratory leads such as Exemestane and Felodipine were identified in underrepresented biological niches, supported by enrichment in oxidative stress and autophagy pathways. The framework demonstrated high stability across multiple random seeds and a 48% reduction in computational cost compared to standard multi-objective evolutionary baselines. CONCLUSIONS: Beyond AD, this framework offers a generalizable strategy for integrating biomedical knowledge graphs with diversity-enhancing AutoML to accelerate the discovery of mechanistically novel drug candidates across complex polygenic diseases.
Climate change intensifies temperature extremes, increasing daily variations between high and low temperatures (intraday temperature variation). These variations can influence environmental exposures, such as ambient air pollution and pollen, and indoor behaviors, including heating use, potentially elevating asthma exacerbation risk. Neighborhood context may modify these effects, particularly in disinvested or racially segregated areas where adaptive capacity is limited. We conducted a case-crossover study using conditional logistic regressions to estimate associations between intraday temperature variation and asthma exacerbations among children in Philadelphia, PA (2011-2016). Cases were identified from electronic health records at the Children's Hospital of Philadelphia. Analyses were stratified by season: Spring/Summer (March-August) and Fall/Winter (October-February). We assessed nonlinear and lagged (up to 7 days) effects, defining reference thresholds as 4 °F for Spring/Summer and 3 °F for Fall/Winter. Models were further stratified by present-day racialized economic segregation and historical redlining. In Spring/Summer, greater intraday temperature variation on lag day 4 was associated with increased odds of asthma exacerbation (OR = 1.20, 95% CI: 1.08-1.34). In Fall/Winter, greater variation was associated with decreased odds (OR = 0.81, 95% CI: 0.68-0.98). No statistically significant effect modification was observed by segregation or redlining. Intraday temperature variation was associated with pediatric asthma exacerbations, with stronger adverse effects during warmer months. These findings highlight the importance of addressing temperature variation in public health and clinical strategies aimed at protecting children with asthma in a changing climate.
High-throughput affinity-based proteomics has advanced biomedical research, yet fundamental, persistent discordance between mainstream platforms (SomaScan and Olink) routinely undermines the replication of findings. This platform-driven non-replication complicates downstream biological validation and biomarker prioritization. Here, we develop a machine learning-based framework for cross-platform protein value imputation to resolve this translational bottleneck. Using paired proteomic data measured by both SomaScan and Olink from 5,325 participants of the Multi-Ethnic Study of Atherosclerosis, we developed models to impute cross-platform measurements and applied them to two independent and demographically distinct cohorts (Cardiovascular Health Study [N=3,171] and UK Biobank [UKB; N=41,405]) for external validation. Our bi-directional model 1) established an imputation performance-based protein fidelity index, validated against gold-standard measurements from Atherosclerosis Risk in Communities study (N=101) and Nurses' Health Study (N=54), 2) enabled imputation of platform-exclusive protein measurements, and 3) facilitated calibration of overlapping proteins. We demonstrate the utility of this framework through three applications: 1) fidelity-informed analyses enhanced the replication of biomarker discovery, 2) recovery of SomaScan signals that were previously inaccessible in UKB's original Olink measurements, and 3) improved replication performance for overlapping proteins. Our study offers a translational roadmap that allows researchers to achieve reliable epidemiological replication, target specific assays for future optimization, and prioritize biological signal over platform noise.
Pancreatic cancer disproportionately affects Black individuals in the United States, but they have limited representation in genetic studies of pancreatic ductal adenocarcinoma (PDAC). To address this gap, we performed admixture mapping and genome-wide association analysis (GWAS) in genetically inferred African ancestry individuals (1,030 cases and 889 controls). Admixture mapping identified three regions with a significantly higher proportion of African ancestry in cases compared to controls (5q33.3, 10p1, 22q12.3). GWAS identified a genome-wide significant association at 5p15.33 (CLPTM1L, rs383009:T>C, T Allele Frequency=0.51, OR:1.45, P value=1.24×10-8), a locus previously associated with PDAC. Known loci at 5p15.33, 7q32.3, 8q24.21 and 7q25.1 also replicated (P value <0.01). Multi-ancestral fine-mapping identified two potential causal SNPs (rs3830069 and rs2735940) at 5p15.33. Collectively these findings identified novel PDAC risk loci and expanded our understanding of this deadly cancer in underrepresented populations, emphasizing the multifactorial nature of PDAC risk including inherited genetic and non-genetic factors. To understand how genetic variation contributes to PDAC risk in Black people in North American, we studied individuals of genetically-inferred African ancestry. We identified novel risk loci and differences in the contribution of known loci. This demonstrates that ancestry-informed genetic analyses improve our understanding of PDAC risk and enhances discovery.
Information on childhood cancer burden is crucial for effective cancer policy planning. Unfortunately, observed paediatric cancer data are not available in every country, and previous global burden estimates have not discretely reported several common cancers of childhood. We aimed to inform efforts to address childhood cancer burden globally by analysing results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2023, which now include nine additional cancer causes compared with previous GBD analyses. GBD 2023 data sources for cancer estimation included population-based cancer registries, vital registration systems, and verbal autopsies. For childhood cancers (defined as those occurring at ages 0-19 years), mortality was estimated using cancer-specific ensemble models and incidence was estimated using mortality estimates and modelled mortality-to-incidence ratios (MIRs). Years of life lost (YLLs) were estimated by multiplying age-specific cancer deaths by the standard life expectancy at the age of death. Prevalence was estimated using survival estimates modelled from MIRs and multiplied by sequelae-specific disability weights to estimate years lived with disability (YLDs). Disability-adjusted life-years (DALYs) were estimated as the sum of YLLs and YLDs. Estimates are presented globally and by geographical and resource groupings, and all estimates are presented with 95% uncertainty intervals (UIs). Globally, in 2023, there were an estimated 377 000 incident childhood cancer cases (95% UI 288 000-489 000), 144 000 deaths (131 000-162 000), and 11·7 million (10·7-13·2) DALYs due to childhood cancer. Deaths due to childhood cancer decreased by 27·0% (15·5-36·1) globally, from 197 000 (173 000-218 000) in 1990, but increased in the WHO African region by 55·6% (25·5-92·4), from 31 500 (24 900-38 500) to 49 000 (42 600-58 200) between 1990 and 2023. In 2023, age-standardised YLLs due to childhood cancer were inversely correlated with country-level Socio-demographic Index. Childhood cancer was the eighth-leading cause of childhood deaths and the ninth-leading cause of DALYs among all cancers in 2023. The percentage of DALYs due to uncategorised childhood cancers was reduced from 26·5% (26·5-26·5) in GBD 2017 to 10·5% (8·1-13·1) with the addition of the nine new cancer causes. Target cancers for the WHO Global Initiative for Childhood Cancer (GICC) comprised 47·3% (42·2-52·0) of global childhood cancer deaths in 2023. Global childhood cancer burden remains a substantial contributor to global childhood disease and cancer burden and is disproportionately weighted towards resource-limited settings. The estimation of additional cancer types relevant in childhood provides a step towards alignment with WHO GICC targets. Efforts to decrease global childhood cancer burden should focus on addressing the inequities in burden worldwide and support comprehensive improvements along the childhood cancer diagnosis and care continuum. St Jude Children's Research Hospital, Gates Foundation, and St Baldrick's Foundation.
Early life exposure to organophosphate esters (OPEs), a class of flame retardants and plasticizers, may be associated with adverse neurobehavioral outcomes. Due to OPEs' relatively short biological half-life in humans, it is important to evaluate exposure-response associations using repeated measures during gestation and childhood. We examined the associations between OPE biomarkers and social skill/problem behavior using data from 236 caregiver-adolescent dyads in the Health Outcomes and Measures of the Environment (HOME) Study. We included urinary concentrations of four OPE biomarkers [bis-2-chloroethyl-phosphate (BCEP), bis(1,3-dichloro-2-propyl)-phosphate (BDCIPP), di-n-butyl-phosphate (DNBP), diphenyl-phosphate (DPHP)] measured up to 9 times (3 in gestation and 6 in childhood) and calculated cumulative exposure measures during gestation, childhood, and the lifetime. Social and behavioral outcomes at age 12 years were assessed using the Social Skills Improvement System (SSiS) completed by adolescents and caregivers. We used quantile g-computation regression to evaluate joint associations between the OPE biomarker mixture and SSiS scores, while adjusting for covariates. Overall, we observed null associations between OPE biomarkers and adolescent social skill/problem behavior scores, but the effect measure modification by adolescent sex was statistically significant. Every quartile increase in childhood/lifetime OPE biomarker mixture was associated with improved caregiver-reported problem behavior among females (Ψchildhood -3.44 (95%CI: -6.05, -0.84); Ψlifetime -3.82 (95%CI: -6.43, -1.22)). Every quartile increase in lifetime OPE biomarker mixture was associated with impaired social skill scores in males (Ψlifetime -3.59 (95%CI: -6.79, -0.40). Further studies with a larger sample size will help provide additional insights into OPE exposures early in life and subsequent sex-specific associations with adolescent social skill/problem behavior scores.
Higher exposure to greenspace has been associated with reduced mortality rates in predominantly White samples. However, the specific contribution of different types of greenspace exposures to these associations and whether the associations vary by race and ethnicity have not been studied. Our main objective was to quantify the association between specific types of greenspaces and all-cause mortality risk among participants of the Multi-Ethnic Study of Atherosclerosis (MESA). We analyzed data from 6,795 MESA participants, with baseline interviews in 2000 and follow-up through 2018. Deep learning algorithms were applied to Street View images to estimate percent of residential greenspace type (e.g., %Trees and %Grass) within a 500 m buffer for each follow-up year. We used Cox models to estimate hazard ratios (HR) for the association between % of each greenspace metric and mortality, adjusting for demographic and socioeconomic factors. Among 6,748 individuals (mean baseline age 62 years [SD 10]) totaling 973,608 person-years, we observed 1898 (28.1%) deaths during 19 years of follow-up. In fully-adjusted models, exposure to %Other green (fields, flowers, and plants) was associated with lower mortality (0.89, 95% CI: 0.84, 0.94), while %Grass showed a similar but less consistent inverse association (0.91, 95% CI: 0.83, 0.99). This protective association was particularly notable among participants living in neighborhoods with low socioeconomic status (%Other green 0.86, 95% CI: 0.77, 0.97). No associations were observed for %Trees. Our results suggest that greater exposure to certain greenspace types may be associated with a reduced mortality risk among MESA participants.
Glucuronidation is an important detoxification pathway that operates in balance with gastrointestinal microbial β-glucuronidase (GUS) activity, which can regenerate bioactive metabolites from their glucuronidated forms. How this host-microbe interaction shapes the distribution and pool of glucuronidated metabolites (i.e., the glucuronidome) remains poorly understood. In this study, we employed pattern-filtering data science approaches in conjunction with untargeted LC-MS/MS metabolomics to map the glucuronidome in urine, serum, and colon/fecal samples from gnotobiotic and conventional mice, and in humans. We find that microbial colonization and GUS activity compress the colonic glucuronidome and expand urinary glucuronidome diversity, revealing a compartmental redistribution of glucuronidated metabolites. Reverse metabolomics of known glucuronidated chemicals and glucuronidation pattern filtering searches in public metabolomics datasets exposed the diversity of glucuronidated metabolites in human and mouse ecosystems. In summary, we present a glucuronidation fingerprint resource that provides broader access to and analysis of the glucuronidome. Together, this work establishes a scalable analytical framework and provides mechanistic insight into how microbial activity reshapes systemic glucuronidation, with implications for drug metabolism, diet-microbe interactions, and biomarker discovery.
BACKGROUND: Alterations to the gut microbiome have been linked to cardiometabolic disease, like type 2 diabetes and hypertension, in adults, but few studies have investigated these associations in adolescents. We examined the relation between the gut microbiome and cardiometabolic risk in adolescence and determined whether sex and race/ethnicity modified these associations. METHODS: In 144 adolescents (age range: 11–14 years) from the Health Outcomes and Measures of the Environment (HOME) Study, we quantified gut microbiome alpha diversity using the Shannon index and species’ relative abundances (i.e., centered log-ratio normalized abundances) in stool DNA that underwent metagenomic sequencing. We assessed adolescent cardiometabolic risk using a cardiometabolic risk summary score, its individual components (i.e., visceral fat, leptin to adiponectin ratio, HOMA-IR, triglyceride to high-density lipoprotein cholesterol ratio, and systolic blood pressure), as well as total cholesterol and hemoglobin A1c. We used linear regression models to estimate covariate-adjusted cross-sectional associations of the Shannon diversity index and species’ relative abundances with cardiometabolic risk, and examine differences in these associations by sex and race/ethnicity. At the species level, the false discovery rate (FDR) correction, with q-value < 0.20, was considered statistically significant. RESULTS: Among all adolescents, a higher Shannon diversity index was associated with lower systolic blood pressure [β: -0.18 (95% CI: -0.35, -0.01)] in covariate-adjusted models. However, the associations of the Shannon diversity index with cardiometabolic risk did not differ significantly by sex or race/ethnicity. Although associations of the relative abundances of species, prevalent in at least 10% of samples, with cardiometabolic risk were not statistically significant tamong all adolescents after correcting for multiple comparisons (qFDR ≥ 0.20), sex modified the association of the relative abundance of Ruminococcus lactaris with HOMA-IR (qinteraction = 0.151), with positive association among females [β: 2.05 (95% CI: 0.93, 3.17), q = 0.155] and suggestive negative association among males [β: -0.84 (95% CI: -1.59, -0.09), q = 0.983]. Associations of the relative abundances of Streptococcus parasanguinis (qinteraction = 0.097), Enterocloster SGB14313 (qinteraction = 0.097), and Alistipes ihumii (qinteraction = 0.097) with total cholesterol also differed between female and male adolescents. We observed differences between adolescents of non-Hispanic black and non-Hispanic white race/ethnicity in the association of the relative abundance of Lachnospira pectinoschiza (qinteraction = 0.028) with total cholesterol. CONCLUSIONS: Our findings suggest that the gut microbiome is associated with cardiometabolic risk in adolescence in a sex-specific manner, and may differ by race and ethnicity.
Phthalates are ubiquitous endocrine disrupting chemicals previously linked with behavioral problems in children. We investigated associations of gestational phthalate exposure with problem behaviors and social skills in adolescents using the Health Outcomes and Measures of the Environment (HOME) Study. Parent offspring pairs (n = 216) were recruited between 2003 and 2006 in Cincinnati, Ohio. Maternal urine samples collected at 16- and 26-weeks' gestation were analyzed for nine phthalate metabolites. At the 12-year follow-up, adolescents and caregivers completed the Social Skills Improvement System (SSiS), which measures social skills (SSiS-SS) and problem behaviors (SSiS-PB). Multivariable linear regressions were performed for each phthalate metabolite controlling for potential confounders including maternal age, child race and ethnicity, maternal depression, marital status, income, child sex, cotinine, polybrominated diphenyl ether 47, and lead. Regressions were performed for the overall sample and stratified by sex. We evaluated mixture effects using quantile g-computation models. No individual phthalates were significantly associated with either the caregiver or adolescent reported SSiS-SS score. Mono-isobutyl phthalate (MiBP) was significantly associated with increased adolescent reported SSiS-PB score (β: 5.94, 95% CI: 0.75, 11.12, p = 0.03). In our sex-stratified analysis we found evidence for a detrimental association with phthalates and both SSiS-SS and SSiS-PB in male adolescents only. This was consistent in the linear and quantile g-computation models. We found evidence for sex specific associations between gestational phthalate exposures and social skills and problem behaviors in adolescents. This extends previous research on phthalates and child behavior into adolescence and suggests sex specific effects of phthalates.
This study aimed to investigate the association between dietary total antioxidant capacity (TAC) and the risks of clinical outcomes, including surgery, gastrointestinal cancer, and mortality, among middle-aged and older individuals with IBD. Nationwide prospective cohort study. We included middle-aged and older participants with IBD when recruited in the UK Biobank. Dietary TAC was calculated by the oxygen radical absorbance capacity from the food by repeated dietary recalls. The outcomes representing IBD prognosis include IBD-related surgery, gastrointestinal cancer, and death events. Hazard ratios (HRs) with 95% confidence intervals (CIs) were estimated using Cox proportional hazard models. Polymorphism of antioxidant-related enzymes genes was ascertained via genotype data. With a median follow-up period of 10.9 years, we documented 174 cases of IBD-related surgery, 52 gastrointestinal cancer, and 189 death events among 2487 IBD participants. Compared to the lowest quartile of dietary TAC, participants in the highest quartile presented lower risks of IBD-related surgery (HR 0.53; 95% CI 0.34-0.84; P-trend = 0.005) and all-cause mortality (HR 0.61; 95% CI 0.39-0.96; P-trend = 0.014). Compared to the lowest decile, participants in the higher deciles of dietary TAC had a lower risk of gastrointestinal cancer (HR 0.39; 95% CI 0.19-0.83; P = 0.014). We also found genetic variants in catalase gene CAT and antioxidant transporter gene SLC2A14 modified the association between dietary TAC and IBD prognosis. Higher dietary TAC was associated with better prognosis of middle-aged and older individuals with IBD, including lower risk of related surgery, gastrointestinal cancer, and all-cause mortality, suggesting the importance of adherence to high-TAC diet in IBD management.
Earlier menopause is a risk factor for several age-related diseases, including dementia. The biological pathways linking menopause timing to later-life brain aging are not understood. Leveraging large-scale plasma proteomics in postmenopausal women from the UK Biobank (N=15,012), earlier menopause was associated with upregulation of pro-inflammatory and extracellular matrix degradation pathways, plus accelerated aging across proteomic clocks of organ and cellular aging, including brain and oligodendrocyte aging. Elevated GDF15, a canonical aging marker, was the top protein correlate of earlier menopause. We observed robust replication of menopause timing proteomic shifts in the Women's Health Initiative Long Life Study (N=1,210). In UKB, proteins associated with earlier menopause, including GDF15, exhibited concordant associations with incident dementia risk and brain atrophy, cerebral small vessel disease burden, and white matter microstructural integrity. Collectively, our findings identify proteomic signatures linking ovarian aging to brain aging, providing a framework to inform interventions to reduce dementia risk.