Ultraprocessed Food Intake during the Transition to Adulthood Varies According to Sociodemographic Characteristics and Maternal Intake in Cebu, Philippines.

BACKGROUND: Ultraprocessed foods (UPFs) are associated with elevated risk of noncommunicable disease, but little is known about UPF intake and the individual-, household-, and community-level factors associated with it among adolescents in low- or middle-income countries. OBJECTIVES: We estimated the association of UPF intake across adolescence with sociodemographic characteristics and maternal UPF intake in a Filipino cohort. METHODS: Data were from 4 waves (1994-2005) of the Cebu Longitudinal Health and Nutrition Survey (n = 2068); participants were aged 11, 15, 18, and 21 y. Foods from 24-h recalls were classified using NOVA. We used 2-part multilevel models to estimate time-varying associations of the odds and amount (percentage daily kilocalories) of UPF intake with sociodemographic characteristics and maternal UPF intake (none, below median among UPF-consuming mothers ["low"], at or above median ["high"]). RESULTS: Median UPF intake (interquartile range [IQR]) among adolescents was 7.3% (IQR: 0, 17.2%) of daily kilocalories at age 11 y and 10.6% (IQR: 3.6, 19.6%) at 21 y. The odds and amount of adolescent UPF intake were positively associated with female sex, years of schooling, and household wealth and inversely associated with household size. The odds-but not amount-of adolescent UPF intake was positively associated with maternal education and urbanicity and inversely associated with the distance from a household's primary store/market. The association between odds of adolescent UPF intake and school enrollment was positive in adolescence but disappeared in early adulthood. Compared with offspring whose mothers did not consume UPFs, the odds of UPF intake among those whose mothers had low- or high-UPF intake was greater in adolescence, but there was no association once offspring became adults. At all ages, maternal UPF intake was positively associated with the amount of offspring intake. CONCLUSIONS: Adolescent UPF intake varied across sociodemographic characteristics and was positively associated with maternal UPF intake, but not after adolescents entered adulthood.

Methylation patterns associated with C-reactive protein in racially and ethnically diverse populations.

Systemic low-grade inflammation is a feature of chronic disease. C-reactive protein (CRP) is a common biomarker of inflammation and used as an indicator of disease risk; however, the role of inflammation in disease is not completely understood. Methylation is an epigenetic modification in the DNA which plays a pivotal role in gene expression. In this study we evaluated differential DNA methylation patterns associated with blood CRP level to elucidate biological pathways and genetic regulatory mechanisms to improve the understanding of chronic inflammation. The racially and ethnically diverse participants in this study were included as 50% White, 41% Black or African American, 7% Hispanic or Latino/a, and 2% Native Hawaiian, Asian American, American Indian, or Alaska Native (total n = 13,433) individuals. We replicated 113 CpG sites from 87 unique loci, of which five were novel (CADM3, NALCN, NLRC5, ZNF792, and cg03282312), across a discovery set of 1,150 CpG sites associated with CRP level (p < 1.2E-7). The downstream pathways affected by DNA methylation included the identification of IFI16 and IRF7 CpG-gene transcript pairs which contributed to the innate immune response gene enrichment pathway along with NLRC5, NOD2, and AIM2. Gene enrichment analysis also identified the nuclear factor-kappaB transcription pathway. Using two-sample Mendelian randomization (MR) we inferred methylation at three CpG sites as causal for CRP levels using both White and Black or African American MR instrument variables. Overall, we identified novel CpG sites and gene transcripts that could be valuable in understanding the specific cellular processes and pathogenic mechanisms involved in inflammation.

Dietary quality and dietary greenhouse gas emissions in the USA: a comparison of the planetary health diet index, healthy eating index-2015, and dietary approaches to stop hypertension.

BACKGROUND: The Planetary Health Diet Index (PHDI) measures adherence to the dietary pattern presented by the EAT-Lancet Commission, which aligns health and sustainability targets. There is a need to understand how PHDI scores correlate with dietary greenhouse gas emissions (GHGE) and how this differs from the carbon footprints of scores on established dietary recommendations. The objectives of this study were to compare how the PHDI, Healthy Eating Index-2015 (HEI-2015) and Dietary Approaches to Stop Hypertension (DASH) relate to (a) dietary GHGE and (b) to examine the influence of PHDI food components on dietary GHGE. METHODS: We used life cycle assessment data from the Database of Food Recall Impacts on the Environment for Nutrition and Dietary Studies to calculate the mean dietary GHGE of 8,128 adult participants in the 2015-2016 and 2017-2018 cycles of the National Health and Nutrition Examination Survey (NHANES). Poisson regression was used to estimate the association of (a) quintiles of diet score and (b) standardized dietary index Z-scores with dietary GHGE for PHDI, HEI-2015, and DASH scores. In secondary analyses, we used Poisson regression to assess the influence of individual PHDI component scores on dietary GHGE. RESULTS: We found that higher dietary quality on all three indices was correlated with lower dietary GHGE. The magnitude of the dietary quality-dietary GHGE relationship was larger for PHDI [-0.4, 95% CI (-0.5, -0.3) kg CO2 equivalents per one standard deviation change] and for DASH [-0.5, (-0.4, -0.6) kg CO2-equivalents] than for HEI-2015 [-0.2, (-0.2, -0.3) kg CO2-equivalents]. When examining PHDI component scores, we found that diet-related GHGE were driven largely by red and processed meat intake. CONCLUSIONS: Improved dietary quality has the potential to lower the emissions impacts of US diets. Future efforts to promote healthy, sustainable diets could apply the recommendations of the established DASH guidelines as well as the new guidance provided by the PHDI to increase their environmental benefits.

Adherence to the Planetary Health Diet Index and correlation with nutrients of public health concern: an analysis of NHANES 2003-2018.

BACKGROUND: The Planetary Health Diet Index (PHDI) is a novel measure adapted to quantify alignment with the dietary evidence presented by the EAT-Lancet Commission on Food, Planet, Health. OBJECTIVES: To examine how population-level health and sustainability of diet as measured by the PHDI changed from 2003 to 2018, and to assess how PHDI correlated with inadequacy for nutrients of public health concern (iron, calcium, potassium, and fiber) in the United States. METHODS: We estimated survey-weighted trends in PHDI scores and median intake of PHDI components in a nationally representative sample of 33,859 adults aged 20+ y from 8 cycles (2003-2018) of the National Health and Nutrition Examination Survey with 2 d of dietary recall data. We used the National Cancer Institute method to examine how PHDI correlated with inadequate intake of iron, calcium, potassium, and fiber. RESULTS: Out of a theoretical range of 0-140, the median PHDI value increased by 4.2 points over the study period, from 62.7 (95% confidence interval [CI]: 62.0, 63.4) points in 2003-2004 to 66.9 (66.2, 67.7) points in 2017-2018 (P-trend < 0.001), although most of this change occurred before 2011-2012 and plateaued thereafter. For adequacy components that are encouraged for consumption, nonstarchy vegetable intake significantly decreased over time, whereas whole grains, nuts and seeds, and unsaturated oils increased. For moderation components with recommended limits for consumption, poultry and egg intake increased, but red and processed meat, added sugars, saturated fats, and starchy vegetables decreased over time. Higher PHDI values were associated with a lower probability of iron, fiber, and potassium inadequacy. CONCLUSIONS: Although there have been positive changes over the past 20 y, there is substantial room for improving the health and sustainability of the United States diet. Shifting diets toward EAT-Lancet recommendations would improve nutrient adequacy for iron, fiber, and potassium. Policy action is needed to support healthier, more sustainable diets in the United States and globally.

Dietary quality and cardiometabolic indicators in the USA: A comparison of the Planetary Health Diet Index, Healthy Eating Index-2015, and Dietary Approaches to Stop Hypertension.

BACKGROUND: The Planetary Health Diet Index (PHDI) measures adherence to the sustainable dietary guidance proposed by the EAT-Lancet Commission on Food, Planet, Health. To justify incorporating sustainable dietary guidance such as the PHDI in the US, the index needs to be compared to health-focused dietary recommendations already in use. The objectives of this study were to compare the how the Planetary Health Diet Index (PHDI), the Healthy Eating Index-2015 (HEI-2015) and Dietary Approaches to Stop Hypertension (DASH) relate to cardiometabolic risk factors. METHODS AND FINDINGS: Participants from the National Health and Nutrition Examination Survey (2015-2018) were assigned a score for each dietary index. We examined disparities in dietary quality for each index. We used linear and logistic regression to assess the association of standardized dietary index values with waist circumference, blood pressure, HDL-C, fasting plasma glucose (FPG) and triglycerides (TG). We also dichotomized the cardiometabolic indicators using the cutoffs for the Metabolic Syndrome and used logistic regression to assess the relationship of the standardized dietary index values with binary cardiometabolic risk factors. We observed diet quality disparities for populations that were Black, Hispanic, low-income, and low-education. Higher diet quality was associated with improved continuous and binary cardiometabolic risk factors, although higher PHDI was not associated with high FPG and was the only index associated with lower TG. These patterns remained consistent in sensitivity analyses. CONCLUSIONS: Sustainability-focused dietary recommendations such as the PHDI have similar cross-sectional associations with cardiometabolic risk as HEI-2015 or DASH. Health-focused dietary guidelines such as the forthcoming 2025-2030 Dietary Guidelines for Americans can consider the environmental impact of diet and still promote cardiometabolic health.

2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association.

BACKGROUND: The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS: The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS: Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS: The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Mendelian randomization with incomplete measurements on the exposure in the Hispanic Community Health Study/Study of Latinos.

Mendelian randomization has been widely used to assess the causal effect of a heritable exposure variable on an outcome of interest, using genetic variants as instrumental variables. In practice, data on the exposure variable can be incomplete due to high cost of measurement and technical limits of detection. In this paper, we propose a valid and efficient method to handle both unmeasured and undetectable values of the exposure variable in one-sample Mendelian randomization analysis with individual-level data. We estimate the causal effect of the exposure variable on the outcome using maximum likelihood estimation and develop an expectation maximization algorithm for the computation of the estimator. Simulation studies show that the proposed method performs well in making inference on the causal effect. We apply our method to the Hispanic Community Health Study/Study of Latinos, a community-based prospective cohort study, and estimate the causal effect of several metabolites on phenotypes of interest.

Liver integrity and the risk of Alzheimer's disease and related dementias.

INTRODUCTION: We examined midlife (1990-1992, mean age 57) and late-life (2011-2013, mean age 75) nonalcoholic fatty liver disease (NAFLD) and aminotransferase with incident dementia risk through 2019 in the Atherosclerosis Risk in Communities (ARIC) Study. METHODS: We characterized NAFLD using the fatty liver index and fibrosis-4, and we categorized aminotransferase using the optimal equal-hazard ratio (HR) approach. We estimated HRs for incident dementia ascertained from multiple data sources. RESULTS: Adjusted for demographics, alcohol consumption, and kidney function, individuals with low, intermediate, and high liver fibrosis in midlife (HRs: 1.45, 1.40, and 2.25, respectively), but not at older age, had higher dementia risks than individuals without fatty liver. A U-shaped association was observed for alanine aminotransferase with dementia risk, which was more pronounced in late-life assessment. DISCUSSION: Our findings highlight dementia burden in high-prevalent NAFLD and the important feature of late-life aminotransaminase as a surrogate biomarker linking liver hypometabolism to dementia. Highlights Although evidence of liver involvement in dementia development has been documented in animal studies, the evidence in humans is limited. Midlife NAFLD raised dementia risk proportionate to severity. Late-life NAFLD was not associated with a high risk of dementia. Low alanine aminotransferase was associated with an elevated dementia risk, especially when measured in late life.

Branched chain amino acids harbor distinct and often opposing effects on health and disease.

BACKGROUND: The branched chain amino acids (BCAA) leucine, isoleucine, and valine are essential nutrients that have been associated with diabetes, cancers, and cardiovascular diseases. Observational studies suggest that BCAAs exert homogeneous phenotypic effects, but these findings are inconsistent with results from experimental human and animal studies. METHODS: Hypothesizing that inconsistencies between observational and experimental BCAA studies reflect bias from shared lifestyle and genetic factors in observational studies, we used data from the UK Biobank and applied multivariable Mendelian randomization causal inference methods designed to address these biases. RESULTS: In n = 97,469 participants of European ancestry (mean age = 56.7 years; 54.1% female), we estimate distinct and often opposing total causal effects for each BCAA. For example, of the 117 phenotypes with evidence of a statistically significant total causal effect for at least one BCAA, almost half (44%, n = 52) are associated with only one BCAA. These 52 associations include total causal effects of valine on diabetic eye disease [odds ratio = 1.51, 95% confidence interval (CI) = 1.31, 1.76], valine on albuminuria (odds ratio = 1.14, 95% CI = 1.08, 1.20), and isoleucine on angina (odds ratio = 1.17, 95% CI = 1.31, 1.76). CONCLUSIONS: Our results suggest that the observational literature provides a flawed picture of BCAA phenotypic effects that is inconsistent with experimental studies and could mislead efforts developing novel therapeutics. More broadly, these findings motivate the development and application of causal inference approaches that enable 'omics studies conducted in observational settings to account for the biasing effects of shared genetic and lifestyle factors.

The three branched chain amino acids (BCAAs) leucine, isoleucine, and valine are important building blocks of muscle proteins that are obtained from the diet. Many studies in human populations have examined whether BCAAs affect health and disease. These human studies report results that are inconsistent with results from highly controlled animal studies. Because interest in the therapeutic targeting of BCAAs is growing, we wanted to better understand these discrepancies. Briefly, we used data from a large database that captured many diseases (e.g., cardiovascular disease, cancers, and respiratory disease) and new statistical methods. Our results showed that discrepancies between human studies and animal studies may reflect errors in the ways human studies were designed and conducted. As a result, these human studies may provide a flawed picture of BCAA effects that could mislead efforts developing novel therapeutics.

Ancestral diversity in lipoprotein(a) studies helps address evidence gaps.

INTRODUCTION: The independent and causal cardiovascular disease risk factor lipoprotein(a) (Lp(a)) is elevated in >1.5 billion individuals worldwide, but studies have prioritised European populations. METHODS: Here, we examined how ancestrally diverse studies could clarify Lp(a)'s genetic architecture, inform efforts examining application of Lp(a) polygenic risk scores (PRS), enable causal inference and identify unexpected Lp(a) phenotypic effects using data from African (n=25 208), East Asian (n=2895), European (n=362 558), South Asian (n=8192) and Hispanic/Latino (n=8946) populations. RESULTS: Fourteen genome-wide significant loci with numerous population specific signals of large effect were identified that enabled construction of Lp(a) PRS of moderate (R2=15% in East Asians) to high (R2=50% in Europeans) accuracy. For all populations, PRS showed promise as a 'rule out' for elevated Lp(a) because certainty of assignment to the low-risk threshold was high (88.0%-99.9%) across PRS thresholds (80th-99th percentile). Causal effects of increased Lp(a) with increased glycated haemoglobin were estimated for Europeans (p value =1.4×10-6), although inverse effects in Africans and East Asians suggested the potential for heterogeneous causal effects. Finally, Hispanic/Latinos were the only population in which known associations with coronary atherosclerosis and ischaemic heart disease were identified in external testing of Lp(a) PRS phenotypic effects. CONCLUSIONS: Our results emphasise the merits of prioritising ancestral diversity when addressing Lp(a) evidence gaps.

Coronary heart disease and ischemic stroke polygenic risk scores and atherosclerotic cardiovascular disease in a diverse, population-based cohort study.

The predictive ability of coronary heart disease (CHD) and ischemic stroke (IS) polygenic risk scores (PRS) have been evaluated individually, but whether they predict the combined outcome of atherosclerotic cardiovascular disease (ASCVD) remains insufficiently researched. It is also unclear whether associations of the CHD and IS PRS with ASCVD are independent of subclinical atherosclerosis measures. 7,286 White and 2,016 Black participants from the population-based Atherosclerosis Risk in Communities study who were free of cardiovascular disease and type 2 diabetes at baseline were included. We computed previously validated CHD and IS PRS consisting of 1,745,179 and 3,225,583 genetic variants, respectively. Cox proportional hazards models were used to test the association between each PRS and ASCVD, adjusting for traditional risk factors, ankle-brachial index, carotid intima media thickness, and carotid plaque. The hazard ratios (HR) for the CHD and IS PRS were significant with HR of 1.50 (95% CI: 1.36-1.66) and 1.31 (95% CI: 1.18-1.45) respectively for the risk of incident ASCVD per standard deviation increase in CHD and IS PRS among White participants after adjusting for traditional risk factors. The HR for the CHD PRS was not significant with an HR of 0.95 (95% CI: 0.79-1.13) for the risk of incident ASCVD in Black participants. The HR for the IS PRS was significant with an HR of 1.26 (95%CI: 1.05-1.51) for the risk of incident ASCVD in Black participants. The association of the CHD and IS PRS with ASCVD was not attenuated in White participants after adjustment for ankle-brachial index, carotid intima media thickness, and carotid plaque. The CHD and IS PRS do not cross-predict well, and predict better the outcome for which they were created than the composite ASCVD outcome. Thus, the use of the composite outcome of ASCVD may not be ideal for genetic risk prediction.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association.

BACKGROUND: The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS: The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS: Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS: The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Selecting Clustering Algorithms for Identity-By-Descent Mapping.

Groups of distantly related individuals who share a short segment of their genome identical-by-descent (IBD) can provide insights about rare traits and diseases in massive biobanks using IBD mapping. Clustering algorithms play an important role in finding these groups accurately and at scale. We set out to analyze the fitness of commonly used, fast and scalable clustering algorithms for IBD mapping applications. We designed a realistic benchmark for local IBD graphs and utilized it to compare the statistical power of clustering algorithms via simulating 2.3 million clusters across 850 experiments. We found Infomap and Markov Clustering (MCL) community detection methods to have high statistical power in most of the scenarios. They yield a 30% increase in power compared to the current state-of-art approach, with a 3 orders of magnitude lower runtime. We also found that standard clustering metrics, such as modularity, cannot predict statistical power of algorithms in IBD mapping applications. We extend our findings to real datasets by analyzing the Population Architecture using Genomics and Epidemiology (PAGE) Study dataset with 51,000 samples and 2 million shared segments on Chromosome 1, resulting in the extraction of 39 million local IBD clusters. We demonstrate the power of our approach by recovering signals of rare genetic variation in the Whole-Exome Sequence data of 200,000 individuals in the UK Biobank. We provide an efficient implementation to enable clustering at scale for IBD mapping for various populations and scenarios.Supplementary Information: The code, along with supplementary methods and figures are available at https://github.com/roohy/localIBDClustering.

Genetic pleiotropy underpinning adiposity and inflammation in self-identified Hispanic/Latino populations.

BACKGROUND: Concurrent variation in adiposity and inflammation suggests potential shared functional pathways and pleiotropic disease underpinning. Yet, exploration of pleiotropy in the context of adiposity-inflammation has been scarce, and none has included self-identified Hispanic/Latino populations. Given the high level of ancestral diversity in Hispanic American population, genetic studies may reveal variants that are infrequent/monomorphic in more homogeneous populations. METHODS: Using multi-trait Adaptive Sum of Powered Score (aSPU) method, we examined individual and shared genetic effects underlying inflammatory (CRP) and adiposity-related traits (Body Mass Index [BMI]), and central adiposity (Waist to Hip Ratio [WHR]) in HLA participating in the Population Architecture Using Genomics and Epidemiology (PAGE) cohort (N = 35,871) with replication of effects in the Cameron County Hispanic Cohort (CCHC) which consists of Mexican American individuals. RESULTS: Of the > 16 million SNPs tested, variants representing 7 independent loci were found to illustrate significant association with multiple traits. Two out of 7 variants were replicated at statistically significant level in multi-trait analyses in CCHC. The lead variant on APOE (rs439401) and rs11208712 were found to harbor multi-trait associations with adiposity and inflammation. CONCLUSIONS: Results from this study demonstrate the importance of considering pleiotropy for improving our understanding of the etiology of the various metabolic pathways that regulate cardiovascular disease development.

Large-scale genome-wide association study of coronary artery disease in genetically diverse populations.

We report a genome-wide association study (GWAS) of coronary artery disease (CAD) incorporating nearly a quarter of a million cases, in which existing studies are integrated with data from cohorts of white, Black and Hispanic individuals from the Million Veteran Program. We document near equivalent heritability of CAD across multiple ancestral groups, identify 95 novel loci, including nine on the X chromosome, detect eight loci of genome-wide significance in Black and Hispanic individuals, and demonstrate that two common haplotypes at the 9p21 locus are responsible for risk stratification in all populations except those of African origin, in which these haplotypes are virtually absent. Moreover, in the largest GWAS for angiographically derived coronary atherosclerosis performed to date, we find 15 loci of genome-wide significance that robustly overlap with established loci for clinical CAD. Phenome-wide association analyses of novel loci and polygenic risk scores (PRSs) augment signals related to insulin resistance, extend pleiotropic associations of these loci to include smoking and family history, and precisely document the markedly reduced transferability of existing PRSs to Black individuals. Downstream integrative analyses reinforce the critical roles of vascular endothelial, fibroblast, and smooth muscle cells in CAD susceptibility, but also point to a shared biology between atherosclerosis and oncogenesis. This study highlights the value of diverse populations in further characterizing the genetic architecture of CAD.

Strengthening Causal Inference in Exposomics Research: Application of Genetic Data and Methods.

Advances in technologies to measure a broad set of exposures have led to a range of exposome research efforts. Yet, these efforts have insufficiently integrated methods that incorporate genetic data to strengthen causal inference, despite evidence that many exposome-associated phenotypes are heritable. Objective: We demonstrate how integration of methods and study designs that incorporate genetic data can strengthen causal inference in exposomics research by helping address six challenges: reverse causation and unmeasured confounding, comprehensive examination of phenotypic effects, low efficiency, replication, multilevel data integration, and characterization of tissue-specific effects. Examples are drawn from studies of biomarkers and health behaviors, exposure domains where the causal inference methods we describe are most often applied. Discussion: Technological, computational, and statistical advances in genotyping, imputation, and analysis, combined with broad data sharing and cross-study collaborations, offer multiple opportunities to strengthen causal inference in exposomics research. Full application of these opportunities will require an expanded understanding of genetic variants that predict exposome phenotypes as well as an appreciation that the utility of genetic variants for causal inference will vary by exposure and may depend on large sample sizes. However, several of these challenges can be addressed through international scientific collaborations that prioritize data sharing. Ultimately, we anticipate that efforts to better integrate methods that incorporate genetic data will extend the reach of exposomics research by helping address the challenges of comprehensively measuring the exposome and its health effects across studies, the life course, and in varied contexts and diverse populations. https://doi.org/10.1289/EHP9098.

Predicted gene expression in ancestrally diverse populations leads to discovery of susceptibility loci for lifestyle and cardiometabolic traits.

One mechanism by which genetic factors influence complex traits and diseases is altering gene expression. Direct measurement of gene expression in relevant tissues is rarely tenable; however, genetically regulated gene expression (GReX) can be estimated using prediction models derived from large multi-omic datasets. These approaches have led to the discovery of many gene-trait associations, but whether models derived from predominantly European ancestry (EA) reference panels can map novel associations in ancestrally diverse populations remains unclear. We applied PrediXcan to impute GReX in 51,520 ancestrally diverse Population Architecture using Genomics and Epidemiology (PAGE) participants (35% African American, 45% Hispanic/Latino, 10% Asian, and 7% Hawaiian) across 25 key cardiometabolic traits and relevant tissues to identify 102 novel associations. We then compared associations in PAGE to those in a random subset of 50,000 White British participants from UK Biobank (UKBB50k) for height and body mass index (BMI). We identified 517 associations across 47 tissues in PAGE but not UKBB50k, demonstrating the importance of diverse samples in identifying trait-associated GReX. We observed that variants used in PrediXcan models were either more or less differentiated across continental-level populations than matched-control variants depending on the specific population reflecting sampling bias. Additionally, variants from identified genes specific to either PAGE or UKBB50k analyses were more ancestrally differentiated than those in genes detected in both analyses, underlining the value of population-specific discoveries. This suggests that while EA-derived transcriptome imputation models can identify new associations in non-EA populations, models derived from closely matched reference panels may yield further insights. Our findings call for more diversity in reference datasets of tissue-specific gene expression.

Population-based genetic effects for developmental stuttering.

Despite a lifetime prevalence of at least 5%, developmental stuttering, characterized by prolongations, blocks, and repetitions of speech sounds, remains a largely idiopathic speech disorder. Family, twin, and segregation studies overwhelmingly support a strong genetic influence on stuttering risk; however, its complex mode of inheritance combined with thus-far underpowered genetic studies contribute to the challenge of identifying and reproducing genes implicated in developmental stuttering susceptibility. We conducted a trans-ancestry genome-wide association study (GWAS) and meta-analysis of developmental stuttering in two primary datasets: The International Stuttering Project comprising 1,345 clinically ascertained cases from multiple global sites and 6,759 matched population controls from the biobank at Vanderbilt University Medical Center (VUMC), and 785 self-reported stuttering cases and 7,572 controls ascertained from The National Longitudinal Study of Adolescent to Adult Health (Add Health). Meta-analysis of these genome-wide association studies identified a genome-wide significant (GWS) signal for clinically reported developmental stuttering in the general population: a protective variant in the intronic or genic upstream region of SSUH2 (rs113284510, protective allele frequency = 7.49%, Z = -5.576, p = 2.46 × 10-8) that acts as an expression quantitative trait locus (eQTL) in esophagus-muscularis tissue by reducing its gene expression. In addition, we identified 15 loci reaching suggestive significance (p < 5 × 10-6). This foundational population-based genetic study of a common speech disorder reports the findings of a clinically ascertained study of developmental stuttering and highlights the need for further research.

Changes in nonnutritive sweetener intake in a cohort of preschoolers after the implementation of Chile's Law of Food Labelling and Advertising.

BACKGROUND: The first phase of Chile's Law of Food Labelling and Advertising showed important declines in the sugar content of packaged foods, but it is unknown whether the law led to an increase in nonnutritive sweetener (NNS) intake, particularly among preschool children. OBJECTIVES: Estimate the changes in preschoolers' NNS intake after the first phase of the Chilean law. METHODS: We used 24-h dietary recalls collected in 2016 (pre-law) and 2017 (post-law) from a cohort of preschoolers (n = 875). The primary caretaker was the respondent of the recalls. Information on NNS was obtained from nutrition facts panels collected annually and linked to dietary data. We used logistic regression to estimate the changes in the proportion of preschoolers who consume NNS and two-part models to estimate the changes in mean intake. We determined the percentage of children that surpassed the acceptable daily intake (ADI) of each NNS using the National Cancer Institute method. RESULTS: The proportion of consumers of at least one NNS increased from 77.9% to 92.0% (p-value < 0.01). The mean intake increased for sucralose, aspartame, acesulfame-K and steviol glycosides (+20.3, +15.1, +6.1 and +3.3 mg/day, respectively). In addition, NNS dietary sources changed for sucralose and steviol glycosides, becoming industrialized juices and dairy beverages more relevant while tabletop NNS became less relevant. None of the children surpassed the ADI. CONCLUSIONS: NNS intake increased in preschoolers after the first phase of a national policy that promoted sugar reformulation.