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Most transcriptome-wide association studies (TWASs) so far focus on European ancestry and lack diversity. To overcome this limitation, we aggregated genome-wide association study (GWAS) summary statistics, whole-genome sequences and expression quantitative trait locus (eQTL) data from diverse ancestries. We developed a new approach, TESLA (multi-ancestry integrative study using an optimal linear combination of association statistics), to integrate an eQTL dataset with a multi-ancestry GWAS. By exploiting shared phenotypic effects between ancestries and accommodating potential effect heterogeneities, TESLA improves power over other TWAS methods. When applied to tobacco use phenotypes, TESLA identified 273 new genes, up to 55% more compared with alternative TWAS methods. These hits and subsequent fine mapping using TESLA point to target genes with biological relevance. In silico drug-repurposing analyses highlight several drugs with known efficacy, including dextromethorphan and galantamine, and new drugs such as muscle relaxants that may be repurposed for treating nicotine addiction.

Background: The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure. Methods: We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants. Results: Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings ( P -8 ). Among them, a rare intergenic variant at novel locus, LOC100506274 , was associated with lower systolic blood pressure in stage-1 (beta [SE]=−32.6 [6.0]; P =4.99×10 -8 ) but not stage-2 analysis ( P =0.11). Furthermore, a novel common variant at the known INSR locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=−0.36 [0.07]; P =4.18×10 -7 ) and attained genome-wide significance in stage-2 (beta [SE]=−0.29 [0.03]; P =7.28×10 -23 ). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings ( P -6 and P -4 , respectively). Discussion: We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.

Streptococcus mutans has been implicated as the primary pathogen in childhood caries (tooth decay). While the role of polymicrobial communities is appreciated, it remains unclear whether other microorganisms are active contributors or interact with pathogens. Here, we integrate multi-omics of supragingival biofilm (dental plaque) from 416 preschool-age children (208 males and 208 females) in a discovery-validation pipeline to identify disease-relevant inter-species interactions. Sixteen taxa associate with childhood caries in metagenomics-metatranscriptomics analyses. Using multiscale/computational imaging and virulence assays, we examine biofilm formation dynamics, spatial arrangement, and metabolic activity of Selenomonas sputigena, Prevotella salivae and Leptotrichia wadei, either individually or with S. mutans. We show that S. sputigena, a flagellated anaerobe with previously unknown role in supragingival biofilm, becomes trapped in streptococcal exoglucans, loses motility but actively proliferates to build a honeycomb-like multicellular-superstructure encapsulating S. mutans, enhancing acidogenesis. Rodent model experiments reveal an unrecognized ability of S. sputigena to colonize supragingival tooth surfaces. While incapable of causing caries on its own, when co-infected with S. mutans, S. sputigena causes extensive tooth enamel lesions and exacerbates disease severity in vivo. In summary, we discover a pathobiont cooperating with a known pathogen to build a unique spatial structure and heighten biofilm virulence in a prevalent human disease.

Supplementary Tables 1-8 from Smoking and Selected DNA Repair Gene Polymorphisms in Controls: Systematic Review and Meta-Analysis

Background: When the case-only study design is used to estimate statistical interaction between genetic (G) and environmental (E) exposures, G and E must be independent in the underlying population, or the case-only estimate of interaction (COR) will be biased. Few studies have examined the occurrence of G–E association in published control group data.Methods: To examine the assumption of G–E independence in empirical data, we conducted a systematic review and meta-analysis of G–E associations in controls for frequently investigated DNA repair genes (XRCC1 Arg399Gln, Arg194Trp, or Arg280His, XPD Lys751Gln, and Asp312Asn, and XRCC3 Thr241Met), and smoking (ever/never smoking, current/not current smoker, smoking duration, smoking intensity, and pack-years).Results: Across the 55 included studies, single nucleotide polymorphisms SNP-smoking associations in controls (ORz) were not reliably at the null value of 1.0 for any SNP-smoking combinations. Two G–E combinations were too heterogeneous for summary estimates: XRCC1 399 and ever-never smoking (N = 21), and XPD 751 and pack-years (N = 12). ORz ranges for these combinations were: [ORz (95% confidence interval (CI)] 0.7 (0.4, 1.2)–1.9 (1.2, 2.8) and 0.8 (0.5, 1.3)–2.3 (0.8, 6.1), respectively). Estimates for studies considered homogeneous (Cochran's Q P-value Conclusions: We recommend the independence assumption be evaluated in the population underlying any potential case-only study, rather than in a proxy control group(s) or pooled controls.Impact: These results suggest that G–E association in controls may be population-specific. Increased access to control data would improve evaluation of the independence assumption. Cancer Epidemiol Biomarkers Prev; 19(12); 3055–86. ©2010 AACR.

Background: Multiple primary cancers account for approximately 16% of all incident cancers in the United States. Although genome-wide association studies (GWAS) have identified many common genetic variants associated with various cancer sites, no study has examined the association of these genetic variants with risk of multiple primary cancers (MPC).Methods: As part of the National Human Genome Research Institute (NHGRI) Population Architecture using Genomics and Epidemiology (PAGE) study, we used data from the Multiethnic Cohort (MEC) and Women's Health Initiative (WHI). Incident MPC (IMPC) cases (n = 1,385) were defined as participants diagnosed with more than one incident cancer after cohort entry. Participants diagnosed with only one incident cancer after cohort entry with follow-up equal to or longer than IMPC cases served as controls (single-index cancer controls; n = 9,626). Fixed-effects meta-analyses of unconditional logistic regression analyses were used to evaluate the associations between 188 cancer risk variants and IMPC risk. To account for multiple comparisons, we used the false-positive report probability (FPRP) to determine statistical significance.Results: A nicotine dependence–associated and lung cancer variant, CHRNA3 rs578776 [OR, 1.16; 95% confidence interval (CI), 1.05–1.26; P = 0.004], and two breast cancer variants, EMBP1 rs11249433 and TOX3 rs3803662 (OR, 1.16; 95% CI, 1.04–1.28; P = 0.005 and OR, 1.13; 95% CI, 1.03–1.23; P = 0.006), were significantly associated with risk of IMPC. The associations for rs578776 and rs11249433 remained (P < 0.05) after removing subjects who had lung or breast cancers, respectively (P ≤ 0.046). These associations did not show significant heterogeneity by smoking status (Pheterogeneity ≥ 0.53).Conclusions: Our study has identified rs578776 and rs11249433 as risk variants for IMPC.Impact: These findings may help to identify genetic regions associated with IMPC risk. Cancer Epidemiol Biomarkers Prev; 23(11); 2568–78. ©2014 AACR.

Supplementary Table 1. Summary of Study Design and Case/Control Definitions for participating studies. Supplementary Table 2. Distribution of the incident index and second cancer site among incident multiple primary cancer cases, stratified by study and cancer latency. Supplemental Table 3. Detailed distribution of incident index and second cancer site among incident multiple primary cancer cases for WHI study. Supplemental Table 4. Detailed distribution of incident index and second cancer site among incident multiple primary cancer cases for MEC study. Supplemental Table 5. Frequency and cancer site of IMPC cases with 3 or more cancers. Supplementary Table 6. Meta-analysis of the non-significant associations (p{greater than or equal to}0.05) between 178 risk variants for other cancers and incident multiple primary cancer risk. Supplementary Table 7. Ten SNPsa associated with other cancers and multiple primary cancer risk by race/ethnicityb

Inadequate representation of non-European ancestry populations in genome-wide association studies (GWAS) has limited opportunities to isolate functional variants. Fine-mapping in multi-ancestry populations should improve the efficiency of prioritizing variants for functional interrogation. To evaluate this hypothesis, we leveraged ancestry architecture to perform comparative GWAS and fine-mapping of obesity related phenotypes in European ancestry populations from the UK Biobank (UKBB) and multi-ancestry samples from the Population Architecture for Genetic Epidemiology (PAGE) consortium with comparable sample sizes. In 10 of the investigated regions with genome wide significant associations for obesity related traits, fine-mapping in our ancestrally diverse sample led to 95% and 99% credible sets (CS) with fewer variants than in the European ancestry sample. Lead fine-mapped variants in PAGE regions had higher average coding scores, and higher average posterior probabilities for causality compared to UKBB. Importantly, 99% CS in PAGE loci contained strong expression quantitative trait loci (eQTLs) in adipose tissues or harbored more variants in tighter linkage disequilibrium (LD) with eQTLs. Results also suggested three novel candidates for functional effect on waist-to-hip ratio adjusted for BMI (WHRBMI-adj) (rs5781117 near gene RP11-392O17.1, rs10187501 in gene COBLL1, and rs1964599 near gene CCDC92), all within the 99% CS. Leveraging ancestrally diverse populations with heterogeneous ancestry architectures, coupled with functional annotation, increased fine mapping efficiency and performance, and reduced the set of candidate variants for consideration for future functional studies. Significant overlap in genetic causal variants across populations suggest generalizability of genetic mechanisms underpinning obesity related traits across populations.

Growth in early infancy is hypothesized to affect chronic disease risk factors later in life. To date, most reports draw on European-ancestry cohorts with few repeated observations in early infancy. We investigated the association between infant growth before 6 months and lipid levels in adolescents in a Hispanic/Latino cohort. We characterized infant growth from birth to 5 months in male (n = 311) and female (n = 285) infants from the Santiago Longitudinal Study (1991–1996) using 3 metrics: weight (kg), length (cm), and weight-for-length (g/cm). Superimposition by translation and rotation (SITAR) and latent growth mixture models (LGMMs) were used to estimate the association between infant growth characteristics and lipid levels at age 17 years. We found a positive relationship between the SITAR length velocity parameter before 6 months of age and high-density lipoprotein cholesterol levels in adolescence (11.5, 95% confidence interval; 3.4, 19.5), indicating higher high-density lipoprotein cholesterol levels occurring with faster length growth. The strongest associations from the LGMMs were between higher low-density lipoprotein cholesterol and slower weight-for-length growth, following a pattern of associations between slower growth and adverse lipid profiles. Further research in this window of time can confirm the association between early infant growth as an exposure and adolescent cardiovascular disease risk factors.

BACKGROUND AND AIMS: Adipose tissue secretes adipokines such as adiponectin and leptin, playing important roles in energy metabolism. The longitudinal associations between such adipokines and body fat accumulation have not been established, especially during adolescence and young adulthood and in diverse populations. The study aims to assess the longitudinal association between body fat measured with dual X-ray absorptiometry and plasma adipokines from adolescence to young adulthood. METHODS AND RESULTS: Among Hispanic/Latino participants (N=537) aged 16.8 (SD: 0.3) years of the Santiago Longitudinal Study, we implemented structural equation modeling to estimate the sex-specific associations between adiposity (body fat percent (BF%) and proportion of trunk fat (PTF)) and adipokines (adiponectin and leptin levels) during adolescence (16y) and these values after 6 years of follow-up (22y). In addition, we further investigated whether the associations differed by baseline insulin resistance (IR) status. We found evidence for associations between 16y BF% and 22y leptin levels (β(SE): 0.58(0.06) for females; 0.53(0.05) for males), between 16y PTF and 22y adiponectin levels (β(SE): −0.31(0.06) for females; −0.18(0.06) for males) and between 16y adiponectin levels and 22y BF% (β(SE): 0.12(0.04) for both females and males). CONCLUSION: We observed dynamic relationships between adiposity and adipokines levels from late adolescence to young adulthood in a Hispanic/Latino population further demonstrating the importance of this period of the life course in the development of obesity.

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 (UKBB(50k)) for height and body mass index (BMI). We identified 517 associations across 47 tissues in PAGE but not UKBB(50k), 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 UKBB(50k) 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.

Introduction: Measures of pulmonary function are associated with cardiovascular disease risk; however, the underlying mechanism remains unclear. Hypothesis: We hypothesize that protein biomarkers are associated with pulmonary function decline, as well as the risk of subsequent incident coronary heart disease (CHD), heart failure (HF), and mortality. Methods: We included participants from the Atherosclerosis Risk in Communities (ARIC) study with plasma proteome measured by SOMAscan and spirometric measures (forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC)) at both visits 2 (1990-1992) and 5 (2011-2013). Cross-sectional associations of protein levels with FEV1 and FVC at both visits were assessed using multivariable linear regression. The decline of FEV1 was evaluated among proteins related to cross-sectional FEV1 and FVC measures. The FEV1-decline-related proteins were further probed into the effects on incident CHD, HF, and mortality, using Cox proportional hazard models post-visit 2. Results: Out of 4,677 proteins, 364 were cross-sectionally associated with both FEV1 and FVC at visit 2 (n=11,354, age 57, 23% blacks, and 56% women) and 5 (n=3,517, age 75, 17% blacks, and 58% women) at FDR Figure ). Gamma-aminobutyric acid receptor-associated protein showed the greatest effect with FEV1 decline, and its per SD increase was associated with 20% higher risk of HF and mortality. Compared to HF and mortality, FEV1 decline-related proteins were less associated with incident CHD. Conclusions: Twenty-seven proteins related to pulmonary function decline were heavily associated with the risk of HF and mortality, suggesting shared etiology between those conditions.

Introduction: The aromatic amino acids tyrosine and phenylalanine may increase type 2 diabetes risk, but few studies have examined whether these critical molecular precursors exert additional phenotypic effects and whether these effects are independent of insulin resistance. We evaluated associations between two aromatic amino acids - tyrosine and phenylalanine - with a broad range of phenotypic categories in the UK Biobank using polygenic risk score (PRS) instrumental variables that are robust to confounding and reverse causation and tested for mediation by glycated hemoglobin (HbA1c) as a measure of insulin resistance. Hypothesis: We hypothesized that tyrosine and phenylalanine would show broad phenotypic effects and that many of these effects would be mediated by HbA1c. Methods: We constructed PRS (Crosspred) using all nominally significant and common (minor allele frequency >5%) variants from genome-wide association studies (SAIGE) of unrelated European ancestry participants in the UK Biobank. We evaluated associations with 273 curated phenotypes spanning 20 categories, including endocrine, circulatory, and cancer related traits. We corrected for multiple comparisons using false discovery rate Results: A total of 108,554 participants had tyrosine or phenylalanine measured at baseline (mean age=57 years; 54% (58,880/108,554) female). PRS were predictive of tyrosine (R 2 =0.28) and phenylalanine (R 2 =0.26). Tyrosine and phenylalanine PRS showed significant associations with 121/273 (44%) and 124/273 (45%) of phenotypes, respectively, including chronic kidney disease, serum testosterone, lymphocyte count, and myocardial infarction (MI; n=3,349 cases, mean years of follow-up=11). For incident MI, every one standard deviation increase in the tyrosine PRS increased the odds of MI by 4.4% (total effect odds ratio (OR) = 1.044 (95% confidence interval (CI): 1.002, 1.089). The direct effect of the tyrosine PRS on incident MI was slightly decreased (OR= 1.040 (95% CI: 0.997, 1.084) when extending the statistical model to examine mediation by HbA1c, with an estimated indirect effect of 1.004 (95% CI: 1.003, 1.006) and an estimated percent mediated by HbA1c of 9.95% (95% CI: -0.04%, 19.90%). Findings were consistent for phenylalanine, where the percent of the total effect mediated by HbA1c was 8.94% (95% CI: -1.93, 19.80%). Conclusions: The effect of tyrosine and phenylalanine on incident MI may primarily operate through pathways other than glucose dysregulation.

Objective: There is known heterogeneity in the relationship between diet quality and cardiovascular disease by self-reported race and sex, which may underlie inequities in cardiovascular health. Methods: We used data from 2,832 participants in the Coronary Artery Risk Development in Young Adults (CARDIA) study (2005-06, aged 37-55, 57% women, 45% Black). Using fasted blood samples, we obtained ultra-high-performance liquid chromatography high resolution mass spectrometry untargeted metabolomics and derived an a priori diet quality score using a validated diet history questionnaire, based on classification of 46 food groups with potential beneficial (n=20), adverse (n=13), or neutral (n=13) implications for cardiovascular health. We tested effect modification of associations between metabolites and diet quality by race and sex, separately, using multivariable-adjusted linear regression for 7,522 metabolite peaks, accounting for multiple comparisons, adjusted for batch, field center, demographics, lifestyle behaviors, total energy intake, hypertension and diabetes status, medication use, and BMI. We also used race- and sex-stratified multivariate Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) analyses to examine how metabolites distinguish by diet quality 1 st and 4 th quartiles. We identified differing metabolite pathways by race and sex through biochemical pathway analysis (Mummichog version 1.0.10) from regression and OPLS-DA models. Results: In linear regression, race significantly modified metabolite-diet quality associations for 231 metabolite peaks; sex modified associations for 1 peak (FDR Conclusions: Metabolite pathways were statistically different by self-reported race, and to a lesser extent, by sex. Differences in metabolite-diet quality associations may reflect differences in contextual or social variables, and potentially, heterogeneity in metabolism.

The US prevalence of severe obesity [(SevO), body mass index [BMI] ≥40 kg/m 2 )] is increasing at an alarming rate; women and Hispanic Latino populations have experienced among the greatest increases. While genome-wide association studies (GWAS) have identified >1000 loci associated with body mass index, the function of much of this variation is unknown. Gene expression measures can ] link genetic variation and disease highlighting pathways for targeted therapeutic intervention, but to-date, few studies have examined the role of gene expression to identify molecular signatures associated with SevO. To this end, we leveraged extant whole blood (WB) RNA sequencing (RNAseq) data in 75 SevO cases and 116 controls (with BMI = 18-25) collected from randomly selected Mexican Americans in the Cameron County Hispanic Cohort (CCHC) to identify patterns associated with SevO. We used established protocols and alignment, yielding 18,565 genes after quality control. We applied DESeq2 to assess DE associated with SevO, using a negative binomial regression model with a gene-specific dispersion parameter, adjusted for sex, age, T2D, hypertension, hypercholesterolemia, and 10 probabilistic estimation of expression residual (PEER) factors. After FDR correction, 124 genes were significantly DE, including top genes C1RL , IL4R, and RGS16 . We identified several replications of the 124 genes in a transcriptomic follow-up study of 52 SevO cases and 59 normal weight controls- 20 genes displayed directionally consistent and FDR significant evidence of replication. We additionally identified several replications of the 124 genes in subcutaneous adipose tissue (SAT) from 19 NYC community volunteers, including for RGS16 , C1RL , and IL4R. 2- sample MR assessed causal associations between SevO and gene dysregulation, using SevO GWAS from DIAMANTE and CCHC eQTLs. Upregulated IL4R demonstrate pleiotropy, among other genes (e.g., REM2, ENGASE, and SCAP ). Collectively, these data demonstrate how transcriptomic studies may elevate understanding of SevO and inform efforts to reduce health disparities associated with SevO in HL populations.

Background: Obesity is a strong risk factor for cardiovascular disease. The excess heart failure (HF) risk associated with obesity is uniquely unexplained by traditional risk mediators. We sought to identify proteomic signatures that reflect mechanistic pathways associated with obesity-related HF. Methods: We quantified 4955 plasma proteins in stored plasma samples of ARIC Visit 2 (1990-1992) participants without HF using an aptamer-based platform (SOMAScan v4.0). We used Cox regression to identify the proteins associated with incident HF, stratified by obesity (BMI≥30 kg/m 2 ). We used Bonferroni-corrected p-values to assess statistical significance in 2/3 discovery and 1/3 validation subsets. We assessed the biological pathways overexpressed by these proteins using a canonical pathway analysis. Results: We included 9940 participants (28% with obesity, mean age 57 years, 55% female, 22% Black adults). Over a median 21-year follow-up, 2,345 HF events (886 in obesity) occurred. In the discovery subset with obesity, we identified 110 proteins associated with incident HF after demographic adjustment, 19 proteins (7 specific to obesity, Figure B) had robust HF associations after additional adjustment for lifestyle and cardiometabolic risk factors (p-5 ) (Figure A). Of 19 proteins, 12 were also linked to prevalent obesity status. Angiopoietin-2 was associated with higher risk of HF and higher odds of obesity. Conversely, ephrin type-A receptor 4 and seizure 6-like protein were linked to lower HF risk and lower odds of obesity. Lipid and bile acid metabolism (inhibited), cytokine signaling and wound healing pathways (activated) were overexpressed by HF-associated proteins in those with obesity. Conclusion: We identified established and novel proteins associated with HF risk in obesity. Many proteins linked to incident HF in obesity are also strongly associated with prevalent obesity. Formal mediation analysis can help elucidate the potential role of these proteins in the development of obesity-related HF.

Obesity remains a global public health burden, with 4.7 million premature deaths globally attributed to obesity. Severe obesity (SevO: defined as body mass index (BMI)≥40) is a major risk factor for other comorbidities, including heart disease and Type 2 Diabetes, which disproportionately impact historically marginalized populations, including Hispanic/Latinos. Based on BRFSS data, 24.5% of US Hispanic/Latino adults are projected to have severe obesity by 2030. However, the etiology of the underlying metabolic dysfunction remains unknown. To address this gap, we identified metabolites associated with SevO in genotyped participants aged ≥20 with 25 < BMI ≥ 40 and metabolic data in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). We investigated cross-sectional associations between Blom-transformed metabolites and baseline SevO, adjusting for age, study center, background group, smoking status, and principal components of ancestry, stratified by sex (SUGEN), and meta-analyzed (SAS 9.4). For the top 20 metabolites, we extracted publicly available HCHS/SOL metabolite GWAS (mGWAS) summary statistics to derive metaboQTLs, and summary statistics from a multi-population meta-analysis of SevO (N>70,000) and implemented forward MR analysis using the MendelianRandomization R package (v0.3.0), which provides various robust causal estimation methods for summary data. Anthropometry and data for 640 known Metabolon metabolites were available for 551 females (mean age: 43.3 years, 27% SevO) and 371 males (mean age 43.4 years, 15% SevO). We identified Bonferroni-corrected significant SevO associations (p Cytidine is a pyrimidine nucleoside consisting of D-ribose and cytosine, which is a precursor of cytidine triphosphate required in the one-carbon metabolism pathway to convert phosphatidylcholine (PC) to phosphatidylethanolamine (PE). PC biosynthesis is higher in adipose tissue macrophages in obese mice and humans. Indoleproprionate is a microbial metabolite of tryptophan produced by gut bacteria. Indoleproprionate levels have been shown to be associated with higher microbiome diversity and lower incidence of T2D. Our work points to future efforts to validate findings in other cohorts, including reverse MR to further elucidate the causal relationship between metabolites and severe obesity.

Aims/hypothesis: Type 2 diabetes is a growing global public health challenge. Investigating quantitative traits, including fasting glucose, fasting insulin and HbA1c, that serve as early markers of type 2 diabetes progression may lead to a deeper understanding of the genetic aetiology of type 2 diabetes development. Previous genome-wide association studies (GWAS) have identified over 500 loci associated with type 2 diabetes, glycaemic traits and insulin-related traits. However, most of these findings were based only on populations of European ancestry. To address this research gap, we examined the genetic basis of fasting glucose, fasting insulin and HbA1c in participants of the diverse Population Architecture using Genomics and Epidemiology (PAGE) Study. Methods: We conducted a GWAS of fasting glucose (n = 52,267), fasting insulin (n = 48,395) and HbA1c (n = 23,357) in participants without diabetes from the diverse PAGE Study (23% self-reported African American, 46% Hispanic/Latino, 40% European, 4% Asian, 3% Native Hawaiian, 0.8% Native American), performing transethnic and population-specific GWAS meta-analyses, followed by fine-mapping to identify and characterise novel loci and independent secondary signals in known loci. Results: Four novel associations were identified (p < 5 × 10−9), including three loci associated with fasting insulin, and a novel, low-frequency African American-specific locus associated with fasting glucose. Additionally, seven secondary signals were identified, including novel independent secondary signals for fasting glucose at the known GCK locus and for fasting insulin at the known PPP1R3B locus in transethnic meta-analysis. Conclusions/interpretation: Our findings provide new insights into the genetic architecture of glycaemic traits and highlight the continued importance of conducting genetic studies in diverse populations. Data availability: Full summary statistics from each of the population-specific and transethnic results are available at NHGRI-EBI GWAS catalog (https://www.ebi.ac.uk/gwas/downloads/summary-statistics).

A growing body of work has addressed human adaptations to diverse environments using genomic data, but few studies have connected putatively selected alleles to phenotypes, much less among underrepresented populations such as Amerindians. Studies of natural selection and genotype–phenotype relationships in underrepresented populations hold potential to uncover previously undescribed loci underlying evolutionarily and biomedically relevant traits. Here, we worked with the Tsimane and the Moseten, two Amerindian populations inhabiting the Bolivian lowlands. We focused most intensively on the Tsimane, because long-term anthropological work with this group has shown that they have a high burden of both macro and microparasites, as well as minimal cardiometabolic disease or dementia. We therefore generated genome-wide genotype data for Tsimane individuals to study natural selection, and paired this with blood mRNA-seq as well as cardiometabolic and immune biomarker data generated from a larger sample that included both populations. In the Tsimane, we identified 21 regions that are candidates for selective sweeps, as well as 5 immune traits that show evidence for polygenic selection (e.g., C-reactive protein levels and the response to coronaviruses). Genes overlapping candidate regions were strongly enriched for known involvement in immune-related traits, such as abundance of lymphocytes and eosinophils. Importantly, we were also able to draw on extensive phenotype information for the Tsimane and Moseten and link five regions (containing PSD4 , MUC21 and MUC22 , TOX2 , ANXA6 , and ABCA1 ) with biomarkers of immune and metabolic function. Together, our work highlights the utility of pairing evolutionary analyses with anthropological and biomedical data to gain insight into the genetic basis of health-related traits.

BACKGROUND Metabolic regulation plays a significant role in energy homeostasis, and adolescence is a crucial life stage for the development of cardiometabolic disease (CMD). This study aims to investigate the genetic determinants of metabolic biomarkers-adiponectin, leptin, ghrelin, and orexin-and their associations with CMD risk factors. METHODS We characterized the genetic determinants of the biomarkers among Hispanic/Latino adolescents of the Santiago Longitudinal Study (SLS) and identified the cumulative effects of genetic variants on adiponectin and leptin using biomarker polygenic risk scores (PRS). We further investigated the direct and indirect effect of the biomarker PRS on downstream body fat percent (BF%) and glycemic traits using structural equation modeling. RESULTS We identified putatively novel genetic variants associated with the metabolic biomarkers. A substantial amount of biomarker variance was explained by SLS-specific PRS, and the prediction was improved by including the putatively novel loci. Fasting blood insulin and insulin resistance were associated with PRS for adiponectin, leptin, and ghrelin, and BF% was associated with PRS for adiponectin and leptin. We found evidence of substantial mediation of these associations by the biomarker levels. CONCLUSIONS The genetic underpinnings of metabolic biomarkers can affect the early development of CMD, partly mediated by the biomarkers. IMPACT This study characterized the genetic underpinnings of four metabolic hormones and investigated their potential influence on adiposity and insulin biology among Hispanic/Latino adolescents. Fasting blood insulin and insulin resistance were associated with polygenic risk score (PRS) for adiponectin, leptin, and ghrelin, with evidence of some degree of mediation by the biomarker levels. Body fat percent (BF%) was also associated with PRS for adiponectin and leptin. This provides important insight on biological mechanisms underlying early metabolic dysfunction and reveals candidates for prevention efforts. Our findings also highlight the importance of ancestrally diverse populations to facilitate valid studies of the genetic architecture of metabolic biomarker levels.

Many common and rare variants associated with hematologic traits have been discovered through imputation on large-scale reference panels. However, the majority of genome-wide association studies (GWASs) have been conducted in Europeans, and determining causal variants has proved challenging. We performed a GWAS of total leukocyte, neutrophil, lymphocyte, monocyte, eosinophil, and basophil counts generated from 109,563,748 variants in the autosomes and the X chromosome in the Trans-Omics for Precision Medicine (TOPMed) program, which included data from 61,802 individuals of diverse ancestry. We discovered and replicated 7 leukocyte trait associations, including (1) the association between a chromosome X, pseudo-autosomal region (PAR), noncoding variant located between cytokine receptor genes (CSF2RA and CLRF2) and lower eosinophil count; and (2) associations between single variants found predominantly among African Americans at the S1PR3 (9q22.1) and HBB (11p15.4) loci and monocyte and lymphocyte counts, respectively. We further provide evidence indicating that the newly discovered eosinophil-lowering chromosome X PAR variant might be associated with reduced susceptibility to common allergic diseases such as atopic dermatitis and asthma. Additionally, we found a burden of very rare FLT3 (13q12.2) variants associated with monocyte counts. Together, these results emphasize the utility of whole-genome sequencing in diverse samples in identifying associations missed by European-ancestry-driven GWASs.

Platelets play a key role in thrombosis and hemostasis. Platelet count (PLT) and mean platelet volume (MPV) are highly heritable quantitative traits, with hundreds of genetic signals previously identified, mostly in European ancestry populations. We here utilize whole genome sequencing (WGS) from NHLBI’s Trans-Omics for Precision Medicine initiative (TOPMed) in a large multi-ethnic sample to further explore common and rare variation contributing to PLT (n = 61 200) and MPV (n = 23 485). We identified and replicated secondary signals at MPL (rs532784633) and PECAM1 (rs73345162), both more common in African ancestry populations. We also observed rare variation in Mendelian platelet-related disorder genes influencing variation in platelet traits in TOPMed cohorts (not enriched for blood disorders). For example, association of GP9 with lower PLT and higher MPV was partly driven by a pathogenic Bernard-Soulier syndrome variant (rs5030764, p.Asn61Ser), and the signals at TUBB1 and CD36 were partly driven by loss of function variants not annotated as pathogenic in ClinVar (rs199948010 and rs571975065). However, residual signal remained for these gene-based signals after adjusting for lead variants, suggesting that additional variants in Mendelian genes with impacts in general population cohorts remain to be identified. Gene-based signals were also identified at several genome-wide association study identified loci for genes not annotated for Mendelian platelet disorders (PTPRH, TET2, CHEK2), with somatic variation driving the result at TET2. These results highlight the value of WGS in populations of diverse genetic ancestry to identify novel regulatory and coding signals, even for well-studied traits like platelet traits.

Common genetic variants explain less variation in complex phenotypes than inferred from family-based studies, and there is a debate on the source of this 'missing heritability'. We investigated the contribution of rare genetic variants to tobacco use with whole-genome sequences from up to 26,257 unrelated individuals of European ancestries and 11,743 individuals of African ancestries. Across four smoking traits, single-nucleotide-polymorphism-based heritability ([Formula: see text]) was estimated from 0.13 to 0.28 (s.e., 0.10-0.13) in European ancestries, with 35-74% of it attributable to rare variants with minor allele frequencies between 0.01% and 1%. These heritability estimates are 1.5-4 times higher than past estimates based on common variants alone and accounted for 60% to 100% of our pedigree-based estimates of narrow-sense heritability ([Formula: see text], 0.18-0.34). In the African ancestry samples, [Formula: see text] was estimated from 0.03 to 0.33 (s.e., 0.09-0.14) across the four smoking traits. These results suggest that rare variants are important contributors to the heritability of smoking.

BackgroundThe cumulative socioeconomic status (SES) model posits that childhood and adult experiences accumulate to influence disease risk. While individual SES indicators such as education and income are independently associated with incident type 2 diabetes (T2D), the association of cumulative SES and incident T2D is unclear, especially in African American adults.MethodsWe utilized cohort data of African American participants (n=3681, mean age 52.6 years) enrolled in the Jackson Heart Study from 2000 to 2013 free of T2D or cardiovascular disease at baseline (2000-2004). Cumulative SES scores at baseline were derived using six SES indicators (education, wealth, income, occupation, employment status, and mother's education) categorized as low, middle, and high. Incident T2D was defined at exam 2 (2005-2008) or exam 3 (2009-2013) based on fasting glucose ≥126mg/dL, HbA1c≥6.5, reported diabetic medication use, or self-reported physician diagnosis. Proportional hazards regression, allowing for interval censoring, was used to estimate the association between cumulative SES and incident T2D (hazard ratio(HR), 95% confidence interval (CI)) after adjustment for covariates. Sex and age differences were tested using interaction terms.ResultsThere were 544 incident T2D cases. The association between low (versus high) cumulative SES and incident T2D was not significant (HR 1.04 [95% CI 0.85, 1.28]) and did not differ by sex (p value for interaction>0.05). However, there were differences by (age p value for interaction=0.0052 for middle-aged adults and 0.0186 for older adults). Low (versus high) cumulative SES was associated a greater hazard of incident T2D among those 20-46 years (HR 1.12 [95% CI 1.03, 1.21]), 47-59 years (HR 1.25 [95% CI 1.06, 1.47]) and those 60-93 years (HR 1.39 [95% CI 1.09, 1.78]) after adjustment for sex and family history of diabetes. Associations attenuated after adding behavioral and lifestyle risk factors.ConclusionThe association of low cumulative SES and incident T2D differed by age, which may suggest interventionist should consider impacts of SES on T2D by age.

Author(s): Justice, Anne E; Young, Kristin; Gogarten, Stephanie M; Sofer, Tamar; Graff, Misa; Love, Shelly Ann M; Wang, Yujie; Klimentidis, Yann C; Cruz, Miguel; Guo, Xiuqing; Hartwig, Fernando; Petty, Lauren; Yao, Jie; Allison, Matthew A; Below, Jennifer E; Buchanan, Thomas A; Chen, Yii-Der Ida; Goodarzi, Mark O; Hanis, Craig; Highland, Heather M; Hsueh, Willa A; Ipp, Eli; Parra, Esteban; Palmas, Walter; Raffel, Leslie J; Rotter, Jerome I; Tan, Jingyi; Taylor, Kent D; Valladares, Adan; Xiang, Anny H; Sanchez-Johnsen, Lisa; Isasi, Carmen R; North, Kari E | Abstract: Central obesity is a leading health concern with a great burden carried by ethnic minority populations, especially Hispanics/Latinos. Genetic factors contribute to the obesity burden overall and to inter-population differences. We aimed to identify loci associated with central adiposity measured as waist-to-hip ratio (WHR), waist circumference (WC), and hip circumference (HIP) adjusted for body mass index (adjBMI), using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL); determine if differences in associations differ by background group within HCHS/SOL; and determine whether previously reported associations generalize to HCHS/SOL. Our analyses included 7472 women and 5200 men of mainland (Mexican, Central and South American) and Caribbean (Puerto Rican, Cuban, and Dominican) background residing in the US. We performed genome-wide association analyses stratified and combined across sexes using linear mixed-model regression. We identified 16 variants for WHRadjBMI, 22 for WCadjBMI, and 28 for HIPadjBMI that reached suggestive significance (P l 1x10-6). Many loci exhibited differences in strength of associations by ethnic background and sex. We brought a total of 66 variants forward for validation in cohorts (N = 34 161) with participants of Hispanic/Latino, African and European descent. We confirmed 4 novel loci (P l 0.05 and consistent direction of effect, and P l 5x10-8 after meta-analysis), including 2 for WHRadjBMI (rs13301996, rs79478137); 1 for WCadjBMI (rs3168072); and 1 for HIPadjBMI (rs28692724). Also, we generalized previously reported associations to HCHS/SOL, (8 for WHRadjBMI; 10 for WCadjBMI; 12 for HIPadjBMI). Our study highlights the importance of large-scale genomic studies in ancestrally diverse Hispanic/Latino populations for identifying and characterizing central obesity-susceptibility that may be ancestry-specific.

Studies have shown that genetic variations can influence metabolic response to nutrient intake, and that diets rich in fructose contribute to hyperuricemia. In this pilot study, our aim was to determine the variability of serum urate in response to an acute fructose challenge and to investigate if genetic variants would affect this response in young to middle-aged adults who self-reported as Black or White. Fifty-seven participants consumed a fructose-rich beverage after an overnight fast. Blood was drawn at five time points (baseline, 30, 60, 120, and 180 min after consumption). Thirty urate-related single nucleotide polymorphisms (SNPs) were analyzed for their associations with baseline serum urate and its percent changes, using a two-step modeling approach followed by meta-analysis. At baseline, serum urate (mg/dL, mean ± SD) was higher in Whites (5.60 ± 1.01 vs. 5.37 ± 0.96), men (6.17 ± 1.14 vs. 5.24 ± 0.79), and those with obesity (5.69 ± 1.08 vs. 5.42 ± 1.06 vs. 5.34 ± 0.80). Three SNPs were significantly associated with baseline serum urate or its percent changes, and six SNPs were nominally associated with percent changes in serum urate. In summary, our results showed that genetic variants could play a role in short-term urate metabolism.

BackgroundHeterogeneity in the long-term metabolic response to dietary macronutrient composition can be partially explained by genetic factors. However, few studies have demonstrated reproducible gene-diet interactions (GDIs), likely due in part to measurement error in dietary intake estimation as well as insufficient capture of rare genetic variation. Discovery analyses in ancestry-diverse cohorts that include rare genetic variants from whole-genome sequencing (WGS) could help identify genetic variants modifying the effects of dietary macronutrient composition on glycemic phenotypes.ObjectiveWe aimed to identify macronutrient GDIs across the genetic frequency spectrum associated with continuous glycemic traits in genetically and culturally diverse cohorts.MethodsWe analyzed N=33,187 diabetes-free participants from 10 cohorts in the NHLBI Trans-Omics for Precision Medicine (TOPMed) program with WGS, self-reported diet, and glycemic traits (fasting glucose [FG], insulin [FI], and hemoglobin A1c [HbA1c]). We fit multivariable-adjusted linear mixed models for the main effect of diet, modeled as an isocaloric substitution of carbohydrate for fat, and for its interactions with genetic variants genome-wide. Tests were performed for both common variants and gene-based rare variant sets in each cohort followed by a combined cohort meta-analysis.ResultsIn main effect models, participants consuming more calories from carbohydrate at the expense of fat had modestly lower glycemic trait values (β per 250 kcal substitution for FG: −0.030 mmol/L, p=2.7×10−6; lnFI: −0.008 log(pmol/L), p=0.17; HbA1c: −0.013 %, p=0.025). In GDI analyses, a common African ancestry-enriched variant (rs79762542; 78 kb upstream of the FRAS1 gene) reached study-wide significance (p = 1.14×10−8) indicating a higher HbA1c with greater proportion of calories from carbohydrate vs. fat among minor allele carriers only. This interaction was replicated in the UK Biobank cohort. Simulations revealed that there is (1) a substantial impact of measurement error on statistical power for GDI discovery at these sample sizes, especially for rare genetic variants, and (2) over 150,000 samples may be necessary to identify similar macronutrient GDIs under realistic assumptions about effect size and measurement error.ConclusionsOur analysis identified a potential genetic interaction modifying the dietary macronutrient-HbA1c association while highlighting the importance of precise exposure measurement and significantly increased sample size to identify additional similar effects.

Diabetic kidney disease (DKD) is recognized as an important public health challenge. However, its genomic mechanisms are poorly understood. To identify rare variants for DKD, we conducted a whole-exome sequencing (WES) study leveraging large cohorts well-phenotyped for chronic kidney disease (CKD) and diabetes. Our two-stage whole-exome sequencing study included 4372 European and African ancestry participants from the Chronic Renal Insufficiency Cohort (CRIC) and Atherosclerosis Risk in Communities (ARIC) studies (stage-1) and 11 487 multi-ancestry Trans-Omics for Precision Medicine (TOPMed) participants (stage-2). Generalized linear mixed models, which accounted for genetic relatedness and adjusted for age, sex, and ancestry, were used to test associations between single variants and DKD. Gene-based aggregate rare variant analyses were conducted using an optimized sequence kernel association test (SKAT-O) implemented within our mixed model framework. We identified four novel exome-wide significant DKD-related loci through initiating diabetes. In single variant analyses, participants carrying a rare, in-frame insertion in the DIS3L2 gene (rs141560952) exhibited a 193-fold increased odds (95% confidence interval: 33.6, 1105) of DKD compared with non-carriers (P = 3.59 × 10-9). Likewise, each copy of a low-frequency KRT6B splice-site variant (rs425827) conferred a 5.31-fold higher odds (95% confidence interval: 3.06, 9.21) of DKD (P = 2.72 × 10-9). Aggregate gene-based analyses further identified ERAP2 (P = 4.03 × 10-8) and NPEPPS (P = 1.51 × 10-7), which are both expressed in the kidney and implicated in renin-angiotensin-aldosterone system modulated immune response. In the largest WES study of DKD, we identified novel rare variant loci attaining exome-wide significance. These findings provide new insights into the molecular mechanisms underlying DKD.

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.

Summary Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3 bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380 ), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.

The Trans-Omics for Precision Medicine (TOPMed) programme seeks to elucidate the genetic architecture and biology of heart, lung, blood and sleep disorders, with the ultimate goal of improving diagnosis, treatment and prevention of these diseases. The initial phases of the programme focused on whole-genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here we describe the TOPMed goals and design as well as the available resources and early insights obtained from the sequence data. The resources include a variant browser, a genotype imputation server, and genomic and phenotypic data that are available through dbGaP (Database of Genotypes and Phenotypes)1. In the first 53,831 TOPMed samples, we detected more than 400 million single-nucleotide and insertion or deletion variants after alignment with the reference genome. Additional previously undescribed variants were detected through assembly of unmapped reads and customized analysis in highly variable loci. Among the more than 400 million detected variants, 97% have frequencies of less than 1% and 46% are singletons that are present in only one individual (53% among unrelated individuals). These rare variants provide insights into mutational processes and recent human evolutionary history. The extensive catalogue of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and noncoding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and reach of genome-wide association studies to include variants down to a frequency of approximately 0.01%., The goals, resources and design of the NHLBI Trans-Omics for Precision Medicine (TOPMed) programme are described, and analyses of rare variants detected in the first 53,831 samples provide insights into mutational processes and recent human evolutionary history.

Polygenic risk scores (PRSs) aggregate the effects of genetic variants across the genome and are used to predict risk of complex diseases, such as obesity. Current PRSs only include common variants (minor allele frequency (MAF) ≥1%), whereas the contribution of rare variants in PRSs to predict disease remains unknown. Here, we examine whether augmenting the standard common variant PRS (PRScommon) with a rare variant PRS (PRSrare) improves prediction of obesity. We used genome-wide genotyped and imputed data on 451,145 European-ancestry participants of the UK Biobank, as well as whole exome sequencing (WES) data on 184,385 participants. We performed single variant analyses (for both common and rare variants) and gene-based analyses (for rare variants) for association with BMI (kg/m2), obesity (BMI ≥ 30 kg/m2), and extreme obesity (BMI ≥ 40 kg/m2). We built PRSscommon and PRSsrare using a range of methods (Clumping+Thresholding [C+T], PRS-CS, lassosum, gene-burden test). We selected the best-performing PRSs and assessed their performance in 36,757 European-ancestry unrelated participants with whole genome sequencing (WGS) data from the Trans-Omics for Precision Medicine (TOPMed) program. The best-performing PRScommon explained 10.1% of variation in BMI, and 18.3% and 22.5% of the susceptibility to obesity and extreme obesity, respectively, whereas the best-performing PRSrare explained 1.49%, and 2.97% and 3.68%, respectively. The PRSrare was associated with an increased risk of obesity and extreme obesity (ORobesity = 1.37 per SDPRS, Pobesity = 1.7x10-85; ORextremeobesity = 1.55 per SDPRS, Pextremeobesity = 3.8x10-40), which was attenuated, after adjusting for PRScommon (ORobesity = 1.08 per SDPRS, Pobesity = 9.8x10-6; ORextremeobesity= 1.09 per SDPRS, Pextremeobesity = 0.02). When PRSrare and PRScommon are combined, the increase in explained variance attributed to PRSrare was small (incremental Nagelkerke R2 = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRSrare to PRScommon provided little improvement to the prediction of obesity (PRSrare AUC = 0.591; PRScommon AUC = 0.708; PRScombined AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRSrare provides limited improvement over PRScommon in the prediction of obesity risk, based on these large populations.

Human genetic studies support an inverse causal relationship between leukocyte telomere length (LTL) and coronary artery disease (CAD), but directionally mixed effects for LTL and diverse malignancies. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by expansion of hematopoietic cells bearing leukemogenic mutations, predisposes both hematologic malignancy and CAD. TERT (which encodes telomerase reverse transcriptase) is the most significantly associated germline locus for CHIP in genome-wide association studies. Here, we investigated the relationship between CHIP, LTL, and CAD in the Trans-Omics for Precision Medicine (TOPMed) program ( n = 63,302) and UK Biobank ( n = 47,080). Bidirectional Mendelian randomization studies were consistent with longer genetically imputed LTL increasing propensity to develop CHIP, but CHIP then, in turn, hastens to shorten measured LTL (mLTL). We also demonstrated evidence of modest mediation between CHIP and CAD by mLTL. Our data promote an understanding of potential causal relationships across CHIP and LTL toward prevention of CAD.

Introduction: Despite decades of research linking obesity with cardiovascular disease (CVD) and its risk factors, major research gaps remain, with few studies evaluating the often-described but poorly understood heterogeneity in CVD risk observed within obese populations. One plausible, but largely unexplored source of heterogeneity in obesity-associated CVD risk is the impact of body fat distribution (central versus overall obesity), obesity duration and severity. Longitudinally assessed anthropometric measures and GWAS derived from these exposures may improve understanding of functional properties of loci associated with obesity and downstream influences on CVD. Methods: We respond to these research gaps by using 25 years of Atherosclerosis Risk in Communities (N=14,514, mean baseline age=54 years; 55% Female; 25.73% African-American) data and latent class mixed models to derive four longitudinal measures of obesity distribution, duration, and severity, operationalized as obesity subtypes. Genome wide association studies on the subclasses were conducted using logistic multi-variate regression models to test for associations between variants and BMI. Meta-analyses across race and sex were conducted in METAL. Functional properties of single nucleotide polymorphisms (SNP) were assessed in FUMA. Results: The four obesity subclasses were: decline (4.1%), stable/slow decline (67.8%) [referent], moderate increase (24.6%), and rapid increase (3.6%). The lead SNP from the decline group was known, on chromosome 7 (rs1196508, beta (SE) = -0.44 (0.089), p = 6.84x10 -7 , minor allele frequency (MAF) = 0.36), and nearest to a tyrosine phosphatase receptor, PTPRZ1 , in the central nervous system. We combined moderate and rapid increase for analyses; they shared a common top, unknown, SNP on chromosome 5 (rs76956550, beta (SE) = -0.37 (0.074), MAF=0.12), nearest to PGAM5P1 . The top SNP within the rapid increase group was unknown, on chromosome 14 (rs580888, beta(SE) = -0.57 (0.11), MAF=0.35), and nearest to the OTX2 gene, a transcription factor involved in production of dopaminergic neurons. Mutations of this gene are associated with pituitary hormone deficiency. Conclusion: Our GWAS of obesity subclasses demonstrated unique genetic and functional properties between groups, supporting the contention that CVD risk may differ across obese individuals. We intend to replicate our novel association of OTX2 with BMI, waist-to-hip ratio, and waist circumference in people who rapidly gained weight in other large longitudinal cohorts.

Background: The burden of type 2 diabetes (T2D) is disproportionately higher among racial and ethnic minorities, particularly African American individuals who have low socioeconomic status (SES). According to the cumulative SES life-course model, stressful experiences in early life and later life can accumulate to influence disease risk. Yet, little is known about the association between cumulative SES, or the combined effects of different SES phenotypes (i.e., education, wealth, income, etc.), over the life course and development of T2D. Objective: To estimate the association of cumulative SES and incident T2D among men and women without T2D and cardiovascular disease at baseline (2000-2004) from the Jackson Heart Study (JHS) (n=3078). Methods: Using cohort data from JHS (mean age 52.8 years; 1969 women, 1109 men), we derived standardized cumulative SES scores at baseline, conceptualized using 6 SES indicators (e.g. educational attainment, wealth, income, occupation, employment status and mother’s education) and dichotomized the score as high SES (median and above - referent) and low SES (below the median). Incident T2D was defined at exam 2 (2005-2008) or exam 3 (2009-2013) based on a fasting glucose ≥126 mg/dL, or HbA1c ≥ 6.5, or those who had been on diabetic medication 2 weeks prior to these visits, or those who reported a physician diagnosis. Interval censoring proportional hazards regression was used to estimate the association between cumulative SES and incident T2D using hazard ratios (HR, 95% confidence interval-CI), where time-to-event was approximated as the interval between the first visit and the visit in which T2D was ascertained. Sex differences were evaluated using interaction terms and descriptive statistics. The fully-adjusted model included baseline covariates: age, waist circumference, health behaviors, and family history of diabetes. Results: There were 544 total incident T2D cases and 65% (351) of cases were characterized as having low SES. The dichotomized cumulative score was associated with incident T2D ( p Conclusion: Low cumulative SES was not significantly associated with development of T2D when adjusting for potential confounders. Future work should consider examination of adverse experiences related to low SES and other environmental factors such as built environment and neighborhood SES.

Introduction: Experimental and observational evidence suggests that aberrant branched chain amino acid (BCAA; leucine, isoleucine, and valine) metabolism promotes insulin resistance and downstream disease, prompting interest in BCAA catabolism as a treatment target. Most published research has evaluated the three BCAAs in combination, although each BCAA may harbor distinct phenotypic effects, as valine is glucogenic, leucine is ketogenic, and isoleucine is glucogenic and ketogenic. Methods: Because studies examining individual phenotypic effects of BCAAs that account for the effects of other BCAAs have been limited by high correlation between BCAAs and strong confounding by dietary patterns and shared genetic loci, we applied a novel causal inference method developed to address these limitations: multivariable Mendelian randomization (MVMR). In a study of UK Biobank European ancestry participants, we examined 1,468 phenotypes that included metabolic, cardiovascular, cancer, cognitive, hematopoietic, and musculoskeletal domains. Polygenic risk score (PRS) instrumental variables were constructed using genotypic and circulating BCAA phenotypic data in European ancestry UK Biobank participants and the Crosspred method was used to correct for overfitting. Significant independent causal effects were defined as estimates with P- values< 1.1x10 -5 [0.05/(1,468 phenotypes*3 BCAAs)]. Results: The n=97,469 participants with measured BCAAs were on average middle aged (mean age=57), female (54%), and overweight [mean body mass index (BMI)=27]. Each BCAA PRS strongly predicted its circulating concentrations ( P- value-100 ). MVMR methods did not identify any phenotypes for which all three BCAAs showed evidence of a directionally consistent and significant independent causal effect. However, there were numerous instances where BCAAs harbored independent and directionally inconsistent statistically significant effects. For example, significant positive causal effects for valine independent of isoleucine and leucine and significant negative causal effects for leucine independent of valine and isoleucine were identified for BMI, glycated hemoglobin, and type 2 diabetes; no significant independent causal effects for isoleucine with BMI, glycated hemoglobin, and type 2 diabetes were identified. In contrast, models without control for the effects of other BCAAs suggested that isoleucine, leucine and valine each had significant positive causal effects on BMI, glycated hemoglobin, and type 2 diabetes. When examining other phenotypes using MVMR, heterogeneity in the effects of individual BCAAs was detected for cardiovascular and cognitive phenotypes, among others. Conclusion: BCAAs may harbor distinct and opposing effects on metabolism, health, and disease, motivating further studies that examine the independent effects of these essential amino acids.

Background: Disordered eating is associated with elevated cardiometabolic risks, yet most studies have been conducted in clinical settings with small European-ancestry samples. We investigated disordered eating and cardiometabolic risks in a large population-based sample of women in China. Methods: Participants included 1,999 Chinese women (aged 18-50 years) from the 2015 wave of the China Health and Nutrition Survey. Assessment for general disordered eating was via the SCOFF screener. Additional questions from the Eating Disorder Examination-Questionnaire were included to assess three disordered eating characteristics (i.e., restraint, shape concern, and weight concern). Ten cardiometabolic risk factors (i.e., body mass index [BMI], waist circumference/height ratio [WHR], systolic blood pressure [SBP], diastolic blood pressure [DBP], HbA1c, glucose, total cholesterol, high-density lipoprotein cholesterol [HDL-C], low-density cholesterol, and triglycerides [TG]) were measured by trained staff or with automatic biochemistry analyzer. Generalized linear models were used to examine associations between general disordered eating and each disordered eating characteristic with all 10 cardiometabolic risk factors. Poisson regression models were conducted to examine associations between general disordered eating and each disordered eating characteristic with the total number of cardiometabolic risk factors. We adjusted for potential confounders (age, urbanization index, education level, and alcohol use) and dependencies between individuals in the same household and community in regression models. A significance level of p Results: General disordered eating was significantly associated with higher BMI ( p =.0040), WHR ( p =.0205), and lower HDL-C ( p =.0065). For specific disordered eating characteristics, a higher restraint score was significantly associated with higher BMI ( p =.0383). A higher shape concern score was significantly associated with higher BMI ( p p p= .0013), DBP ( p= .0006), TG ( p= .0438), and lower HDL-C ( p= .0002). A higher weight concern score was significantly associated with higher BMI ( p p p= .0098), DBP ( p= .0066), HbA1c ( p= .0428), glucose ( p= .0410), TG ( p= .0144), and lower HDL-C ( p p s Conclusions: Our findings suggest that disordered eating is associated with a higher level of cardiometabolic risks in Chinese women, corroborating previous findings in other ancestries. For women with disordered eating symptoms, especially shape and weight concerns, healthcare providers should screen for their risks of cardiometabolic diseases. Future studies should investigate mechanisms underlying this comorbidity.

Background: Obesity increases the risk of multiple morbidities and is patterned by socioeconomic status (SES). Lower SES is associated with greater burden of obesity, especially among African American adults. Epigenetic research has provided novel insights into human biology and health; however, few studies have examined whether epigenetic loci mediate the association between SES and obesity. Objective: We sought to determine the union of epigenetic sites associated with cumulative SES and body mass index (BMI) among African American adults from the Atherosclerosis Risk in Communities (ARIC) study, and to examine differences by sex. Hypothesis: Several Cytosine-phosphate-guanine (CpG) sites will be associated with both cumulative SES and BMI, which will provide suggestive evidence of epigenetic mechanisms mediating the association between SES and obesity. Also, sex differences will be detected. Methods: Methylation data from venous blood of 2,684 African American adults (1702 women, 982 men) in the ARIC study (mean age 56.61) was collected from either visit 2 (1990-1992) or visit 3 (1993-1995) using the Illumina HumanMethylation 450k array. For each participant, we created a cumulative SES score comprised of education, income, and occupation from visit 1 (1987-1989). Each SES indicator had 3 categories, which were given a score of 0 (low), 0.5 (medium), or 1 (high), then all SES indicator scores were summed (mean 1.47, SD 0.76, range: 0-3). BMI values (mean 30.12, SD 6.26, range 14.68-62.35) from the same visit as the methylation typing, were then inverse rank normalized. Linear regression analyses were used to test the association of cumulative SES scores and the association of BMI residuals with CpG sites, respectively. Analyses were stratified by sex and combined using inverse variance fixed-effect meta-analysis. The final model adjusted for age, age 2 , alcohol use, smoking, genetic principal components and time between visits. Statistical significance was determined as p -7 . Results: Among men and women combined, 3,843 CpG sites were associated with cumulative SES and 212 CpG sites were associated with BMI. Thirty (n=30) CpG sites were statistically significant for both cumulative SES and BMI. Of the 30 sites, 15 sites were previously identified in epigenetic studies of obesity/BMI, and 11 sites were previously identified for other cardiometabolic traits. Sites were statistically more significant among women. Conclusion: Our findings suggest shared patterns of epigenetic variation between SES and BMI and differences by sex. As a follow up, we will replicate our study findings in other cohort studies and test the hypothesis that the effect of SES on obesity is mediated through methylation. Indeed, such findings could reveal how SES gets “under the skin” to influence obesity. Such knowledge could help us better identify therapeutic targets for intervention.

Primary congenital glaucoma (PCG) and anterior segment defects (ASDs) are rare ocular malformations diagnosed early in life which can cause blindness. Pathogenic variants in several genes have been linked to these conditions, but little is known about nongenetic risk factors. We investigated the association between maternal nutrition and PCG and ASDs in the National Birth Defects Prevention Study, a large population-based, multicenter case-control study of major birth defects in the United States. Mothers of cases (n = 152) and control infants without a birth defect (n = 9,178) completed an interview which included a food frequency questionnaire capturing usual dietary intake in the year before pregnancy. Maternal nutrition was assessed through individual nutrient intake, calculating a Diet Quality Index for Pregnancy (DQI-P) score for each mother, and using latent class analysis to empirically derive four dietary patterns. We calculated adjusted odds ratios (aORs) and 95% confidence intervals (CI) using logistic regression. The results for individual nutrients varied, with some having an inverse or U-shaped pattern of association with increasing intake. The DQI-P was not associated with risk of PCG and ASDs (aOR 0.91; CI 0.49-1.66, highest vs. lowest quartile). The dietary pattern analysis suggested lower odds among women with a Prudent and Mexican dietary pattern (aOR 0.82, 95% CI 0.52-1.29; aOR 0.80, 95% CI 0.36-1.78, respectively) compared to those with a Western dietary pattern. We found that higher intake of some nutrients and certain dietary patterns may be inversely associated with PCG and ASDs, though caution is urged due to imprecision of estimates.

Faster rates of age-related cognitive decline might result in early onset of cognitive impairment and dementia. The relationship between ethanol intake and cognitive decline, although studied extensively, remains poorly understood. Previous studies used single measurements of ethanol, and few were conducted in diverse populations. We assessed the association of 9-year trajectories of ethanol intake (1987–1998) with 15-year rate of decline in cognitive performance from mid- to late life (1996–2013) among 2,169 Black and 8,707 White participants of the US Atherosclerosis Risk in Communities study using multivariable linear regression models. We hypothesized that stable, low to moderate drinking would be associated with lesser 15-year cognitive decline, and stable, heavy drinking with greater 15-year cognitive decline. Stable, low to moderate drinking (for Blacks, adjusted mean difference (MD) = 0.03 (95% confidence interval (CI): −0.13, 0.19); for Whites, adjusted MD = 0.02 (95% CI: −0.05, 0.08)) and stable, heavy drinking (for Blacks, adjusted MD = 0.08 (95% CI: −0.34, 0.50); for Whites, adjusted MD = −0.03 (95% CI: −0.18, 0.11)) in midlife compared with stable never-drinking were not associated with 15-year decline in general cognitive function from mid- to late life. No association was observed for the stable former and “mostly” drinking trajectories with 15-year cognitive decline. Stable low, low to moderate, and stable heavy drinking in midlife are not associated with lesser and greater cognitive decline, respectively, from mid- to late life among Black and White adults.

Background: High-risk human papillomavirus (hrHPV) testing is utilized in primary cervical cancer screening, generally along with cytology, to triage abnormalities to colposcopy. Most screening-based hrHPV testing involves pooled detection of any hrHPV or of HPV16/18. Cervical neoplasia progression risks based on extended hrHPV genotyping—particularly non-16/18 hrHPV types—are not well characterized. HPV genotype-specific incidence of high-grade cervical intraepithelial neoplasia or more severe (CIN2+) following an abnormal screening result was examined. Methods: We assessed a US-based prospective, multiracial, clinical cohort of 343 colposcopy patients with normal histology (n = 226) or CIN1 (n = 117). Baseline cervical samples underwent HPV DNA genotyping, and participants were followed up to 5 years. Genotype-specific CIN2+ incidence rates (IR) were estimated with accelerated failure time models. Five-year CIN2+ risks were estimated nonparametrically for hierarchical hrHPV risk groups (HPV16; else HPV18/45; else HPV31/33/35/52/58; else HPV39/51/56/59/68). Results: At enrollment, median participant age was 30.1 years; most (63%) were hrHPV-positive. Over follow-up, 24 participants progressed to CIN2+ (7.0%). CIN2+ IR among hrHPV-positive participants was 3.4/1,000 person-months. CIN2+ IRs were highest for HPV16 (8.3), HPV33 (7.8), and HPV58 (4.9). Five-year CIN2+ risk was higher for HPV16 (0.34) compared with HPV18/45 (0.12), HPV31/33/35/52/58 (0.12), and HPV39/51/56/59/68 (0.16) (P = 0.05). Conclusions: Non-16/18 hrHPV types are associated with differential CIN2+ progression rates. HPV16, 33, and 58 exhibited the highest rates over 5 years. HPV risk groups warrant further investigation in diverse US populations. Impact: These novel data assessing extended HPV genotyping in a diverse clinical cohort can inform future directions to improve screening practices in the general population.

Periodontitis is a chronic multifactorial inflammatory disease associated with microbial dysbiosis and characterized by progressive destruction of the periodontal tissues. Such chronic infectious inflammatory disease is recognized as a major public health problem worldwide with measurable impact in systemic health. It has become evident that the periodontal disease phenotypes are not only determined by the microbiome effect, but the extent of the tissue response is also driven by the host genome and epigenome patterns responding to various environmental exposures. More recently there is mounting evidence indicating that epigenetic reprogramming in response to combined intrinsic and environmental exposures, might be particularly relevant due its plasticity and potential application towards precision health. The complex epigenetic crosstalk is reflected in the prognosis and progress of periodontal diseases and may also lead to a favorable landscape for cancer development. This review discusses epigenomics modifications focusing on the role of DNA methylation and pathways linking microbial infection and inflammatory pathways, which are also associated with carcinogenesis. There is a more clear vision whereas 'omics' technologies applied to unveil relevant epigenetic factors could play a significant role in the treatment of periodontal disease in a personalized mode, evidencing that public health approach should coexist with precision individualized treatment.

Background Research examining the role of obesity in cardiovascular disease (CVD) often fails to adequately consider heterogeneity in obesity severity, distribution, and duration. Methods and Results We here use multivariate latent class mixed models in the biracial Atherosclerosis Risk in Communities study (N=14 514; mean age=54 years; 55% female) to associate obesity subclasses (derived from body mass index, waist circumference, self‐reported weight at age 25, tricep skinfold, and calf circumference across up to four triennial visits) with total mortality, incident CVD, and CVD risk factors. We identified four obesity subclasses, summarized by their body mass index and waist circumference slope as decline (4.1%), stable/slow decline (67.8%), moderate increase (24.6%), and rapid increase (3.6%) subclasses. Compared with participants in the stable/slow decline subclass, the decline subclass was associated with elevated mortality (hazard ratio [HR] 1.45, 95% CI 1.31, 1.60, P P P =0.0002), and coronary heart disease (HR 1.36, 95% CI 1.14, 1.63, P =0.0008), adjusting for baseline body mass index and CVD risk factor profile. The moderate increase latent class was not associated with any significant differences in CVD risk as compared to the stable/slow decline latent class and was associated with a lower overall risk of mortality (HR 0.85, 95% CI 0.80, 0.90, P P =0.004). Conclusions Consideration of heterogeneity and longitudinal changes in obesity measures is needed in clinical care for a more precision‐oriented view of CVD risk.

Background Obesity and related comorbidities are major health concerns among many US immigrant populations. Emerging evidence suggests a potential involvement of the gut microbiome. Here, we evaluated gut microbiome features and their associations with immigration, dietary intake, and obesity in 2640 individuals from a population-based study of US Hispanics/Latinos. Results The fecal shotgun metagenomics data indicate that greater US exposure is associated with reduced ɑ-diversity, reduced functions of fiber degradation, and alterations in individual taxa, potentially related to a westernized diet. However, a majority of gut bacterial genera show paradoxical associations, being reduced with US exposure and increased with fiber intake, but increased with obesity. The observed paradoxical associations are not explained by host characteristics or variation in bacterial species but might be related to potential microbial co-occurrence, as seen by positive correlations among Roseburia, Prevotella, Dorea, and Coprococcus. In the conditional analysis with mutual adjustment, including all genera associated with both obesity and US exposure in the same model, the positive associations of Roseburia and Prevotella with obesity did not persist, suggesting that their positive associations with obesity might be due to their co-occurrence and correlations with obesity-related taxa, such as Dorea and Coprococcus. Conclusions Among US Hispanics/Latinos, US exposure is associated with unfavorable gut microbiome profiles for obesity risk, potentially related to westernized diet during acculturation. Microbial co-occurrence could be an important factor to consider in future studies relating individual gut microbiome taxa to environmental factors and host health and disease.

BACKGROUND: Few studies have focused on the role of adverse childhood experiences (ACEs) in relation to genetic susceptibility to obesity. OBJECTIVE: We aimed to examine the interaction between the presence of ACEs (i.e., physical, psychological and sexual abuse) before the age of 18 and BMI polygenic score. METHODS: Data came from the National Longitudinal Study of Adolescence to Adult Health (Add Health) wave IV (2007/2008) where saliva samples were collected for DNA genotyping and information on BMI and ACEs were obtained from 5854 European American (EA), 2073 African American (AA) and 1448 Hispanic American (HA) participants aged 24 to 32 years old. Polygenic scores were calculated as the sum of the number of risk alleles of BMI-related SNPs which were weighted by effect size. A race/ethnicity-stratified mixed-effects linear regression model was used to test for differential association between BMI polygenic score by the presence of ACEs across race/ethnic groups. RESULTS: We did not find any evidence of significant interaction between ACEs and polygenic score in relation to BMI among EA (p = 0.289), AA (p = 0.618) or HA (p = 0.870). In main effects models, polygenic score was positively associated with BMI in all race/ethnic groups, yet the presence of ACEs was associated with increased BMI only among EA. CONCLUSION: We did not find any evidence that ACEs exacerbate genetic predisposition to increased BMI in early adulthood.

Background United States (US) Hispanic/Latinos experience a disproportionate burden of obesity, which may in part be related to demographic or sociocultural factors, including acculturation to an US diet or inactive lifestyle. Therefore, we sought to describe the association between adulthood weight histories and demographic and sociocultural factors in a large diverse community-based cohort of US Hispanic/Latinos. Methods We estimated the effect of several factors on weight gain across adulthood, using multivariable linear mixed models to leverage 38,759 self-reported current body weights and weight histories recalled for 21, 45 and 65 years of age, from 15,203 adults at least 21 years of age at the baseline visit of the Hispanic Community Health Study/Study of Latinos (2008–2011). Results The average rate of weight gain was nearly 10 kg per decade in early adulthood, but slowed to Conclusions Using self-reported and weight history data in a diverse sample of US Hispanic/Latinos, we revealed that both demographic and sociocultural factors were associated with the patterning of adulthood weight gain in this sample. Given the steep rate of weight gain in this population and the fact that many Hispanic/Latinos living in the US immigrated as adults, efforts to promote weight maintenance across the life course, including after immigration, should be a top priority for promoting Hispanic/Latino health and addressing US health disparities more broadly.