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The epithelial NaWe explored the association of low frequency and rare variants in the genes encoding ENaC subunits, with systolic blood pressure, diastolic blood pressure, mean arterial pressure, and pulse pressure. Using whole-genome sequencing data from 14 studies participating in the Trans-Omics in Precision Medicine Whole-Genome Sequencing Program, and sequence kernel association tests.We found that variants inOur results suggest that variants in extrarenal ENaCs, in addition to ENaCs expressed in kidneys, influence blood pressure and kidney function.

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.

BACKGROUND AND AIMS: Identify novel metabolite associations with blood pressure (BP) salt-sensitivity and hypertension. METHODS AND RESULTS: The Genetic Epidemiology Network of Salt Sensitivity (GenSalt) Replication study includes 698 Chinese participants who underwent a 3-day baseline examination followed by a 7-day low-sodium feeding and 7-day high-sodium feeding. Latent mixture models identified three trajectories of blood pressure (BP) responses to the sodium interventions. We selected 50 most highly salt-sensitive and 50 most salt-resistant participants for untargeted metabolomics profiling. Multivariable adjusted mixed logistic regression models tested the associations of baseline metabolites with BP salt-sensitivity. Multivariable adjusted mixed linear regression models tested the associations of BP salt-sensitivity with metabolite changes during the sodium interventions. Identified metabolites were tested for associations with hypertension among 1,249 Bogalusa Heart Study (BHS) participants using multiple logistic regression. Fifteen salt-sensitivity metabolites were associated with hypertension in the BHS. Baseline values of serine, 2-methylbutyrylcarnitine and isoleucine directly associated with high salt-sensitivity. Among them, serine indirectly associated with hypertension while 2-methylbutyrylcarnitine and isoleucine directly associated with hypertension. Baseline salt-sensitivity status predicted changes in 14 metabolites when switching to low-sodium or high-sodium interventions. Among them, glutamate, 1-carboxyethylvaline, 2-methylbutyrylcarnitine, 3-methoxytyramine sulfate, glucose, alpha-ketoglutarate, hexanoylcarnitine, gamma-glutamylisoleucine, gamma-glutamylleucine, and gamma-glutamylphenylalanine directly associated with hypertension. Conversely, serine, histidine, threonate and 5-methyluridine indirectly associated with hypertension. Together, these metabolites explained an additional 7% of hypertension susceptibility when added to a model including traditional risk factors. CONCLUSIONS: Our findings contribute to the molecular characterization of BP response to sodium and provide novel biological insights into salt-sensitive hypertension.

Metabolomics genome wide association study (GWAS) help outline the genetic contribution to human metabolism. However, studies to date have focused on relatively healthy, population-based samples of White individuals. Here, we conducted a GWAS of 537 blood metabolites measured in the Chronic Renal Insufficiency Cohort (CRIC) Study, with separate analyses in 822 White and 687 Black study participants. Trans-ethnic meta-analysis was then applied to improve fine-mapping of potential causal variants. Mean estimated glomerular filtration rate was 44.4 and 41.5 mL/min/1.73m(2) in the White and Black participants, respectively. There were 45 significant metabolite associations at 19 loci, including novel associations at PYROXD2, PHYHD1, FADS1-3, ACOT2, MYRF, FAAH, and LIPC. The strength of associations were unchanged in models additionally adjusted for estimated glomerular filtration rate and proteinuria, consistent with a direct biochemical effect of gene products on associated metabolites. At several loci, trans-ethnic meta-analysis, which leverages differences in linkage disequilibrium across populations, reduced the number and/or genomic interval spanned by potentially causal single nucleotide polymorphisms compared to fine-mapping in the White participant cohort alone. Across all validated associations, we found strong concordance in effect sizes of the potentially causal single nucleotide polymorphisms between White and Black study participants. Thus, our study identifies novel genetic determinants of blood metabolites in chronic kidney disease, demonstrates the value of diverse cohorts to improve causal inference in metabolomics GWAS, and underscores the shared genetic basis of metabolism across race.

Background and Purpose: Stroke is the leading cause of death and long-term disability worldwide. Previous genome-wide association studies identified 51 loci associated with stroke (mostly ischemic) and its subtypes among predominantly European populations. Using whole-genome sequencing in ancestrally diverse populations from the Trans-Omics for Precision Medicine (TOPMed) Program, we aimed to identify novel variants, especially low-frequency or ancestry-specific variants, associated with all stroke, ischemic stroke and its subtypes (large artery, cardioembolic, and small vessel), and hemorrhagic stroke and its subtypes (intracerebral and subarachnoid). Methods: Whole-genome sequencing data were available for 6833 stroke cases and 27 116 controls, including 22 315 European, 7877 Black, 2616 Hispanic/Latino, 850 Asian, 54 Native American, and 237 other ancestry participants. In TOPMed, we performed single variant association analysis examining 40 million common variants and aggregated association analysis focusing on rare variants. We also combined TOPMed European populations with over 28 000 additional European participants from the UK BioBank genome-wide array data through meta-analysis. Results: In the single variant association analysis in TOPMed, we identified one novel locus 13q33 for large artery at whole-genome-wide significance ( P −9 ) and 4 novel loci at genome-wide significance ( P −8 ), all of which need confirmation in independent studies. Lead variants in all 5 loci are low-frequency but are more common in non-European populations. An aggregation of synonymous rare variants within the gene C6orf26 demonstrated suggestive evidence of association for hemorrhagic stroke ( P −6 ). By meta-analyzing European ancestry samples in TOPMed and UK BioBank, we replicated several previously reported stroke loci including PITX2 , HDAC9 , ZFHX3 , and LRCH1 . Conclusions: We represent the first association analysis for stroke and its subtypes using whole-genome sequencing data from ancestrally diverse populations. While our findings suggest the potential benefits of combining whole-genome sequencing data with populations of diverse genetic backgrounds to identify possible low-frequency or ancestry-specific variants, they also highlight the need to increase genome coverage and sample sizes.

Introduction: Uncontrolled high dose aspirin use impairs kidney function. Short-term low dose aspirin treatment has also been associated with kidney function in older patients. We aimed to evaluate the association of regular aspirin use with kidney function in middle-aged adults and to identify factors modifying the association. Methods: We performed cross-sectional analyses among 1,261 participants of the 2016 Bogalusa Heart Study (BHS) visit. Regular aspirin use was self-reported and confirmed by serum biomarker, salicyluric glucuronide . Aspirin users were categorized at the median of salicyluric glucuronide levels into low and high dose users. A total of 887 known metabolites were profiled from the serum. Estimated glomerular filtration rate (eGFR) was calculated using the CKD-Epi equation. We tested associations of aspirin use with eGFR and examined interactions of aspirin with serum metabolites on eGFR. Age, sex, race, education, smoking, drinking, physical activity, BMI, blood pressure, and fasting glucose were adjusted in all analyses. Results: The mean age of BHS participants was 48.2, and 133 (10.5%) were self-reported aspirin users. Serum salicyluric glucuronide level was significantly correlated with self-reported aspirin usage (P=2.00х10 -21 ). After adjusting for all covariables, mean eGFR for never, low dose, and high dose aspirin users were 92.9, 90.2, and 89.9 mL/min/1.73m 2 , respectively (P for trend=0.004). After Bonferroni correction, 28 metabolites modified the associations of aspirin use with eGFR (P-5 ), of which, 26 increased the aspirin's nephrotoxicity effect, while behenoylsphingomyelin and tricosanoylsphingomyelin significantly attenuated the eGFR lowering effect of aspirin (Table). Conclusion: Aspirin use is associated with decreased eGFR among middle-aged adults, and this association was modified by dietary, gut microbiome, and biomarkers of kidney disease, cardiovascular disease, and cancer. The findings may help develop better use strategies for regular users.

Introduction: Current guidelines recommend ≥2 servings of fish/week for the prevention of atherosclerotic cardiovascular disease (ASCVD). However, a recent large meta-analysis suggested that the benefit may exist only for persons with a prior ASCVD event. Whether coronary artery calcium (CAC) can help to identify individuals who are likely to benefit from habitual fish consumption is unknown. Hypothesis: CAC will stratify persons who may and may not benefit from habitual fish consumption. Methods: There were 4977 participants in the Multi-Ethnic Study of Atherosclerosis who reported their frequency of fish intake and underwent CAC scanning at Visit 1. Adjusted Cox proportional hazards regression models stratified by the presence/absence of CAC assessed the association between fish intake and incident ASCVD over a median follow-up of 15.7 years. Results: The mean age was 61 years old, 53% were women, 26% were Black, and 49% of participants had prevalent CAC. A similar proportion of individuals reported consuming ≥2 servings of fish/week for those with CAC=0 and CAC >0 (35% versus 33%, p=0.12). The absolute ASCVD event rate for those with 0 (Figure 1). Each additional serving of fish/week was associated with a 9% lower risk of ASCVD for participants with CAC=0 (HR=0.91, 95% CI: 0.83-0.99) whereas there was no significant association for persons with CAC >0 (HR=1.03, 95% CI: 0.99-1.07). Conclusions: A higher amount of fish consumption was associated with a lower risk of incident ASCVD for participants with CAC=0, but not those with CAC >0, although the absolute ASCVD event rate was low for persons with CAC=0 regardless of fish consumption frequency.

Introduction: Mechanisms for metabolically healthy obesity (MHO) are not well studied. Methods: We performed cross-sectional analyses among 1,261 participants of the Bogalusa Heart Study 2013-2016 survey. A total of 887 known serum metabolites were profiled using an untargeted approach. Participants who met all the following five criteria were considered metabolically healthy, otherwise, unhealthy: 1) SBP Results: Among 648 obese participants (BMI≥30 kg/m 2 ), 66 (10.2%) had MHO. After Bonferroni correction, 26 metabolites differed between MHO and metabolically unhealthy obesity (MUO) groups. Amino acids serine , glycine, and histidine , fatty acid N-linoleoylserine , 4 sphingolipids, and 3 plasmalogens were significantly higher among MHO individuals. These metabolites are functionally relevant to metabolic health ( Table ). Carbohydrates mannose , lactate, and pyruvate , urate , amino acids glutamate , 1-carboxyethylvaline , 1-carboxyethylleucine , 3-methyl-2-oxovalerate , and 3-methyl-2-oxobutyrate , PE(18:0/18:2(9Z,12Z)) , and 5 diacylglycerols were significantly higher in the MUO group. These metabolites are mostly food additives or reduce gut microbiota diversity ( Table ). Furthermore, histidine was associated with metabolic health only among overweight and obese participants. Odds ratios of being metabolically healthy per SD increase of histidine among normal weight, overweight, and obese participants were 1.05 (95% CI: 0.83-1.32), 1.54 (95% CI: 1.10-2.14), and 2.12 (95% CI: 1.56-2.89), respectively (P for group difference=1.41E-4). Conclusion: We identified potential intervention targets to improve metabolic health in obesity.

Background: Despite known associations of epigenetic age acceleration (EAA), or increased DNA methylation (DNAm)-based age relative to chronological age, with Alzheimer’s disease, few studies have investigated the relation of EAA with midlife cognitive function. We examined cross-sectional associations of EAA with cognition among the 1,252 middle-aged participants of the Bogalusa Heart Study 2013-2016 study visit. Methods: Whole-blood DNA methylation data was generated using the Illumina HumanMethylation450 BeadChip. Four EAA measures, including extrinsic EAA (EEAA), intrinsic EAA (IEAA), PhenoAA and GrimAA, were derived from the methylation data. Cognitive function was assessed by a standard battery of eight neurocognitive tests covering five cognition domains, and a global cognition score was calculated. Associations of EAA measures with cognitive function were assessed by 3 multivariable models sequentially adding (i) demographics (age, sex, race, education) and vocabulary; (ii) lifestyle behaviors (smoking, alcohol drinking, and depression), and (iii) clinical measures (blood pressure, lipids, body mass index, glycated hemoglobin, medication, and white blood cell count. Results: After Bonferroni correction (α=1.39E-3), PhenoAA and GrimAA were significantly associated with decreased processing speed (lower Digit coding test score) and decreased working memory (higher trail making test A score). GrimAA was also associated with lower global cognition score ( Table ). EEAA was associated with decreased processing speed (lower Digit coding test). After adjusting for lifestyle and clinical measures, such associations were slightly attenuated but remained at least nominally significant. IEAA was not associated with any cognitive test results. Conclusions: EAA measured by PhenoAA, GrimAA, and EEAA were significantly associated with decreased processing speed, working memory, and/or global cognition. The associations were independent of known cognitive decline risk factors.

Background In individuals with chronic kidney disease (CKD), healthy dietary patterns are inversely associated with CKD progression. Metabolomics, an approach that measures many small molecules in biofluids, can identify biomarkers of healthy dietary patterns. Objectives We aimed to identify known metabolites associated with greater adherence to 4 healthy dietary patterns in CKD patients. Methods We examined associations between 486 known plasma metabolites and Healthy Eating Index (HEI)-2015, Alternative Healthy Eating Index (AHEI)-2010, the Dietary Approaches to Stop Hypertension (DASH) diet, and alternate Mediterranean diet (aMED) in 1056 participants (aged 21-74 y at baseline) in the Chronic Renal Insufficiency Cohort (CRIC) Study. Usual dietary intake was assessed using a semiquantitative FFQ. We conducted multivariable linear regression models to study associations between healthy dietary patterns and individual plasma metabolites, adjusting for sociodemographic characteristics, health behaviors, and clinical factors. We used principal component analysis to identify groups of metabolites associated with individual food components within healthy dietary patterns. Results After Bonferroni correction, we identified 266 statistically significant diet-metabolite associations (HEI: n = 60; AHEI: n = 78; DASH: n = 77; aMED: n = 51); 78 metabolites were associated with >1 dietary pattern. Lipids with a longer acyl chain length and double bonds (unsaturated) were positively associated with all 4 dietary patterns. A metabolite pattern low in saturated diacylglycerols and triacylglycerols, and a pattern high in unsaturated triacylglycerols was positively associated with intake of healthy food components. Plasmalogens were negatively associated with the consumption of nuts and legumes and healthy fat, and positively associated with the intake of red and processed meat. Conclusions We identified many metabolites associated with healthy dietary patterns, indicative of food consumption. If replicated, these metabolites may be considered biomarkers of healthy dietary patterns in patients with CKD.

Chronic kidney disease (CKD) was responsible for 1.2 million deaths globally in 2016. Despite the large and growing burden of CKD, treatment options are limited and generally only preserve kidney function. Characterizing molecular precursors to incident and progressive CKD could point to critically needed prevention and treatment strategies. Clonal hematopoiesis of indeterminate potential (CHIP) is typically characterized by the clonal expansion of blood cells carrying somatic mutations in specific driver genes. An age-related disorder, CHIP is rare in the young but common in older adults. Recent studies have identified causal associations between CHIP and atherosclerotic cardiovascular disease which are most likely mediated by inflammation, a hallmark of CKD. Animal evidence has supported causal effects of CHIP on kidney injury, inflammation, and fibrosis, providing impetus for human research. Although prospective epidemiologic studies investigating associations of CHIP with development and progression of CKD are few, intriguing findings have been reported. CHIP was significantly associated with kidney function decline and end stage kidney disease in the general population, although effect sizes were modest. Recent work suggests larger associations of CHIP with kidney disease progression in CKD patients, but further investigations in this area are needed. In addition, the accumulating literature has identified some heterogeneity in associations between CHIP and kidney endpoints across study populations, but reasons for these differences remain unclear. The current review provides an in-depth exploration into this nascent area of research, develops a conceptual framework linking CHIP to CKD, and discusses the clinical and public health implications of this work.

Introduction: Dietary protein and carbohydrate intake have been associated with blood pressure (BP). However, molecular mechanisms for these associations are not well studied. Hypothesis: We hypothesize that novel metabolites – intermediate products of metabolic reactions of diet or genetic factors, may play a role in BP regulation during dietary protein and carbohydrate interventions. Methods: In the Protein and Blood Pressure (ProBP) trial, 80 participants were randomly assigned to take 40 grams/day of soy protein, milk protein, or carbohydrate supplementation each for 8 weeks in a cross-over design. We analyzed the associations of serum metabolites with BP at baseline and each dietary intervention, respectively. Age, sex, race, education, smoking, drinking, and body mass index were adjusted in all analyses. ProBP findings were evaluated for replication among 1206 participants of the Bogalusa Heart Study. Results: After Bonferroni correction for 77 independent metabolite clusters, we identified 17 metabolites (1 at baseline, 8 at carbohydrate diet, 4 at milk protein diet, and 5 at soy protein diet) positively associated with BP (PTable ). Of the 12 metabolites, glycerol and hexadecadienoate (16:2n6) were associated with BP in previous studies, and all other metabolite-BP associations were novel. Conclusions: Several novel metabolites may play an important role in BP regulation during dietary protein and carbohydrate intake.

Cross-sectional studies have reported that high sodium sensitivity is more common among individuals with hypertension. Experimental studies have also reported various animal models with sodium-resistant hypertension. It is unknown, however, whether sodium sensitivity and resistance precede the development of hypertension. We conducted a feeding study, including a 7-day low-sodium diet (1180 mg/day) followed by a 7-day high-sodium diet (7081 mg/day), among 1718 Chinese adults with blood pressure (BP) P P =0.006 for nonlinear trend). Furthermore, a J-shaped association between systolic BP responses to sodium intake and incident hypertension was identified ( P

Genetic information may help to identify individuals at increased risk for hypertension in early life, prior to the manifestation of elevated blood pressure (BP) values. We examined 369 Black and 832 White Bogalusa Heart Study (BHS) participants recruited in childhood and followed for approximately 37 years. The multi-ancestry genome-wide polygenic risk scores (PRSs) for systolic BP (SBP), diastolic BP (DBP), and hypertension were tested for an association with incident hypertension and stage 2 hypertension using Cox proportional hazards models. Race-stratified analyses were adjusted for baseline age, age2, sex, body mass index, genetic principal components, and BP. In Black participants, each standard deviation increase in SBP and DBP PRS conferred a 38% (p = 0.009) and 22% (p = 0.02) increased risk of hypertension and a 74% (p < 0.001) and 50% (p < 0.001) increased risk of stage 2 hypertension, respectively, while no association was observed with the hypertension PRSs. In Whites, each standard deviation increase in SBP, DBP, and hypertension PRS conferred a 24% (p < 0.05), 29% (p = 0.01), and 25% (p < 0.001) increased risk of hypertension, and a 27% (p = 0.08), 29% (0.01), and 42% (p < 0.001) increased risk of stage 2 hypertension, respectively. The addition of BP PRSs to the covariable-only models generally improved the C-statistics (p < 0.05). Multi-ancestry BP PRSs demonstrate the utility of genomic information in the early life prediction of hypertension.

Background: Genetic information may help to identify individuals in childhood who are at increased risk for cardiometabolic disease. Methods: We included 1201 BHS (Bogalusa Heart Study) participants (832 White participants and 369 Black participants) who were followed up to 42.3 years, starting at a mean age of 9.8 years. A validated genome-wide polygenic risk score (PRS) was tested for association with midlife body mass index (BMI), fasting plasma glucose, and systolic blood pressure using multiple linear regression models. Cox proportional hazards models tested associations of the PRS with incident obesity, diabetes, and hypertension. All analyses were conducted according to race and adjusted for baseline age, sex, ancestry, and BMI. Results: The constructed PRS was significantly and modestly correlated with midlife BMI in both White and Black participants, with correlation coefficients of 0.27 ( P =1.94×10 −8 ) and 0.16 ( P =5.50×10 −3 ), respectively. In White participants, per SD increase of PRS was associated with an average 1.29 kg/m 2 higher BMI ( P =4.44×10 −9 ), 2.82 mg/dL higher fasting plasma glucose ( P =1.17×10 −3 ), and 1.09 mm Hg higher systolic blood pressure ( P =3.57×10 −2 ) at midlife. The PRS also conferred a 26% higher increased risk of obesity ( P =3.50×10 −6 ) in White participants. In addition, the variance in midlife BMI explained increased from 0.1973 to 0.2293 when PRS was added to the model including age, sex, principal components, and baseline BMI ( P Conclusions: Adiposity-related genetic information independently predicted cardiometabolic health in White BHS participants. Null associations observed in Black BHS participants highlight the urgent need for PRS development in multi-ancestry populations.

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.

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.

OBJECTIVES Heart disease is the most common cause of death in patients with nonalcoholic fatty liver disease (NAFLD). Emerging data have shown that NAFLD may affect subclinical myocardial remodeling, mainly left ventricular hypertrophy; however, evidence from the prospective studies is still lacking. METHODS Prospective analyses were performed to investigate the association of fatty liver index (FLI) with left ventricular mass (LVM) among 1962 participants from the Bogalusa Heart Study (BHS, 1995-2010) and 1547 participants from the Cardiovascular Risk in Young Finns Study (YFS, 2001-2011) free of cardiovascular diseases (CVD) at baseline. LVM was assessed by two-dimensional guided M-mode echocardiography and indexed (LVMI) to body height (m2.7). Multivariable regression models were applied after adjustment for traditional CVD risk factors. RESULTS In both cohorts, we observed significant and positive associations between FLI and LVM (BHS: β=0.59, P

Objectives The purpose of this study was to identify predictors of healthy arterial aging (long-term coronary artery calcification [CAC] of 0) among individuals with metabolic syndrome (Me...

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: 2-aminoadipic acid (2-AAA) secreted during adipogenesis is a novel marker for diabetes. Hypothesis: 2-AAA mediates the associations between body mass index (BMI) and metabolic measures, and the effect of 2-AAA can be modified by environmental factors. Methods: We performed cross-sectional analyses among all 1,252 participants in the Bogalusa Heart Study 2016 survey. Serum 2-AAA and 110 xenobiotics were profiled through untargeted UPLC-MS/MS. Mediation effects of 2-AAA on the associations between BMI and metabolic traits were estimated by comparing the BMI-traits associations before and after controlling for 2-AAA. P value for a mediation effect was estimated by 1,000,000 times Monte-Carlo simulation. We further performed interaction analyses to identify xenobiotics that modify the effect of 2-AAA on metabolic traits. Age, sex, race, education, smoking, drinking, and use of lipid, glucose, or blood pressure lowering medications were adjusted in all analyses. Results: After Bonferroni correction, 2-AAA significantly mediated the association of BMI with high density lipoprotein cholesterol (HDLC) (beta= -0.03 mg/dL, p=1.70х10 -4 ), log transformed triglyceride (lgTG) (beta=0.002, p=1х10 -6 ), fasting glucose (beta=0.05 mg/dL, p=2.87х10 -3 ), and hemoglobin A1c (HbA1c) (beta=0.002%, p=8.50х10 -4 ). The proportions of associations explained by 2-AAA ranged from 5.12% for HDLC to 13.23% for lgTG. When stratified by race and medication usage, the mediation effects were stronger among Whites and those not taking medications (P for interaction 4-acetaminophen sulfate (P for interaction=3.03х10 -5 ), a metabolite of commonly used over-the-counter analgesics. Conclusion: 2-AAA mediated the effect of BMI on metabolic traits, and this effect was modified by environmental factors.

Aims Left ventricular diastolic dysfunction (LVDD) is an early heart failure with preserved ejection fraction (HFpEF) phenotype that is reversible. Identifying dietary predictors associated with LVDD in diverse populations may help broadly improve HFpEF primary prevention. Methods and results This longitudinal analysis included 456 individuals of the Bogalusa Heart Study (27% Black, 63% women, baseline age = 36.1 ± 4.4 years). Diet was measured at baseline through food frequency questionnaires. LVDD was defined at follow‐up (median = 12.9 years) through echocardiographic measurement of the E/A ratio, E/e′ ratio, isovolumic relaxation time, and deceleration time. Multivariable‐adjusted logistic regression estimated the risk of LVDD according to dietary predictor, adjusting for traditional cardiovascular disease risk factors. Compared with the lowest tertile, participants in the middle tertile of total protein (OR = 3.30, 95% CI: 1.46, 7.45) and animal protein (OR = 2.91, 95% CI: 1.34, 6.34) consumption experienced the highest risk of LVDD. There was a 77% and 56% lower risk of LVDD for persons in the middle vs. lowest tertile of vegetable (OR = 0.23, 95% CI: 0.11, 0.49) and legume consumption (OR = 0.44, 95% CI: 0.22, 0.85), respectively. Total protein, animal protein, processed meat, and egg consumption indicated a quadratic trend towards increased risk of LVDD, while legume and vegetable intake conferred a quadratic trend towards decreased risk of LVDD (all quadratic P

OBJECTIVE: Dietary factors mediate racial disparities in hypertension. However, the physiological mechanisms underlying this relationship are incompletely understood. We sought to assess the association between 1-methylhistidine (1-MH), a metabolite marker of animal protein consumption, and blood pressure (BP) in a community-based cohort of black and white middle-aged adults. METHODS: This analysis consisted of 655 participants of the Bogalusa Heart Study (25% black, 61% women, aged 34–58 years) who were not taking antihypertensive medication. Fasting serum 1-MH was measured using liquid chromatography-tandem mass spectroscopy. Animal food intakes were quantified by food-frequency questionnaires. Multivariable linear regression assessed the association between 1-MH and BP in combined and race-stratified analyses, adjusting for demographic, dietary, and cardiometabolic factors. RESULTS: A significant dose–response relationship was observed for the association of red meat (P-trend

Age-related declines in physical performance predict cognitive impairment, disability, chronic disease exacerbation, and mortality. We conducted a metabolome-wide association study of physical performance among Bogalusa Heart Study participants. Bonferroni corrected multivariate-adjusted linear regression was employed to examine cross-sectional associations between single metabolites and baseline gait speed (N=1,227) and grip strength (N=1,164). In a sub-sample of participants with repeated assessments of gait speed (N=282) and grip strength (N=201), significant metabolites from the cross-sectional analyses were tested for association with change in physical performance over 2.9 years of follow-up. Thirty-five and seven metabolites associated with baseline gait speed and grip strength respectively, including six metabolites that associated with both phenotypes. Three metabolites associated with preservation or improvement in gait speed over follow-up, including: sphingomyelin (40:2) (P=2.6×10-4) and behenoyl sphingomyelin (d18:1/22:0) and ergothioneine (both P

BACKGROUND AND AIMS: Dyslipidemia has been identified as a major risk factor for cardiovascular disease. We aimed to identify metabolites and metabolite modules showing novel association with lipids among Bogalusa Heart Study (BHS) participants using untargeted metabolomics. METHODS AND RESULTS: Untargeted ultrahigh performance liquid chromatography-tandem mass spectroscopy was used to quantify serum metabolites of 1 243 BHS participants (816 whites and 427 African-Americans). The association of single metabolites with lipids was assessed using multiple linear regression models to adjust for covariables. Weighted correlation network analysis was utilized to identify modules of co-abundant metabolites and examine their covariable adjusted correlations with lipids. All analyses were conducted according to race and using Bonferroni-corrected α-thresholds to determine statistical significance. Thirteen metabolites with known biochemical identities showing novel association achieved Bonferroni-significance, p < 1.04×10(−5), and showed consistent effect directions in both whites and African-Americans. Twelve were from lipid sub-pathways including fatty acid metabolism (arachidonoylcholine, dihomo-linolenoyl-choline, docosahexaenoylcholine, linoleoylcholine, oleoylcholine, palmitoylcholine, and stearoylcholine), monohydroxy fatty acids (2-hydroxybehenate, 2-hydroxypalmitate, and 2-hydroxystearate), and lysoplasmalogens [1-(1-enyl-oleoyl)-GPE (P-18:1) and 1-(1enyl-stearoyl)-GPE (P-18:0)]. The gamma-glutamylglutamine, peptide from the gamma-glutamyl amino acid sub-pathway, were also identified. In addition, four metabolite modules achieved Bonferroni-significance, p < 1.39×10(−3), in both whites and African-Americans. These four modules were largely comprised of metabolites from lipid sub-pathways, with one module comprised of metabolites which were not identified in the single metabolite analyses. CONCLUSION: The current study identified 13 metabolites and 4 metabolite modules showing novel association with lipids, providing new insights into the physiological mechanisms regulating lipid levels.