No abstract

Summary paragraphThe Trans-Omics for Precision Medicine (TOPMed) program seeks to elucidate the genetic architecture and disease biology of heart, lung, blood, and sleep disorders, with the ultimate goal of improving diagnosis, treatment, and prevention. The initial phases of the program focus on whole genome sequencing of individuals with rich phenotypic data and diverse backgrounds. Here, we describe TOPMed goals and design as well as resources and early insights from the sequence data. The resources include a variant browser, a genotype imputation panel, and sharing of genomic and phenotypic data via dbGaP. In 53,581 TOPMed samples, >400 million single-nucleotide and insertion/deletion variants were detected by alignment with the reference genome. Additional novel variants are detectable through assembly of unmapped reads and customized analysis in highly variable loci. Among the >400 million variants detected, 97% have frequency <1% and 46% are singletons. These rare variants provide insights into mutational processes and recent human evolutionary history. The nearly complete catalog of genetic variation in TOPMed studies provides unique opportunities for exploring the contributions of rare and non-coding sequence variants to phenotypic variation. Furthermore, combining TOPMed haplotypes with modern imputation methods improves the power and extends the reach of nearly all genome-wide association studies to include variants down to ~0.01% in frequency.

We thank Dr O'Rourke et al, Drs Safar and Jankowski, and Dr Weber et al for their interest in our recent article. 1 Dr O'Rourke et al comment that the "comprehensive battery of measures of aortic stiffness and wave reflection" described in previous communications on this cohort were not mentioned. We reported results for all relevant tonometry data available from the Framingham Heart Study offspring and original cohorts at the noted examination cycles. Although we have assessed additional hemodynamic measures during subsequent examinations in the Framingham offspring and third-generation cohorts, because of insufficient follow-up, we have not yet assessed relations with outcomes for those measures. Dr O'Rourke et al suggest that we dismissed multiple studies that showed wave reflection to be important in predicting outcome. There have been several studies in highly selected patient groups that have shown a relation between augmentation index (AI) and prevalent or incident cardiovascular disease. However, as summarized in a recent editorial, 2 even in patients with prevalent cardiovascular disease, the preponderance of evidence suggests no independent association between AI and events in a model that includes standard risk factors. Dr O'Rourke et al note that we made no mention of a previous study from Framingham that evaluated dicrotic notch position as a measure of arterial stiffness. 3 Kannel et al 3 detailed the considerable limitations of dicrotic notch position as a measure of arterial stiffness or wave reflection and found no relation between dicrotic notch location and incident stroke in a model that included systolic blood pressure.Dr O'Rourke et al speculate that the brachial artery wall cannot be applanated (flattened) against bone during tonometry. To minimize this potential limitation, we trained operators to stay proximal and medial to the aponeurosis, while pinning the brachial artery against the substantial bony backing provided by the distal humerus. Analyses were performed by trained reviewers blinded to clinical characteristics. Dr O'Rourke et al indicate that in other studies, mean values of pressure amplification and AI were higher than those we reported. The studies cited by Dr O'Rourke used the SphygmoCor transfer function, which overestimates aortic-brachial amplification. 4 Drs Safar and Jankowski and Dr Weber et al note that pulse pressure (PP) is a better predictor of atherosclerotic than heart failure events. They requested results for AI, central PP, and PP amplification after excluding 57 heart failure events. To respond, we ran the requested models excluding heart failure events and did not find significant relations with outcome (PϾ0.7 for all). They further note that presentation of hazard ratios for peripheral blood pressure would allow better assessment of the predictive value of central versus peripheral blood pressure. In the base risk factor model without tonometry variables, peripheral systolic pressure was associated with a hazard ratio of 1.23 (95% confidence interval, 1...

Age is the dominant risk factor for most chronic human diseases; yet the mechanisms by which aging confers this risk are largely unknown. 1 Recently, the age-related acquisition of somatic mutations in regenerating hematopoietic stem cell populations leading to clonal expansion was associated with both hematologic cancer 2 – 4 and coronary heart disease 5 , a phenomenon termed ‘Clonal Hematopoiesis of Indeterminate Potential’ (CHIP). 6 Simultaneous germline and somatic whole genome sequence analysis now provides the opportunity to identify root causes of CHIP. Here, we analyze high-coverage whole genome sequences from 97,691 participants of diverse ancestries in the NHLBI TOPMed program and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid, and inflammatory traits specific to different CHIP genes. Association of a genome-wide set of germline genetic variants identified three genetic loci associated with CHIP status, including one locus at TET2 that was African ancestry specific. In silico -informed in vitro evaluation of the TET2 germline locus identified a causal variant that disrupts a TET2 distal enhancer resulting in increased hematopoietic stem cell self-renewal. Overall, we observe that germline genetic variation shapes hematopoietic stem cell function leading to CHIP through mechanisms that are both specific to clonal hematopoiesis and shared mechanisms leading to somatic mutations across tissues.

Reduced glomerular filtration rate defines chronic kidney disease and is associated with cardiovascular and all-cause mortality. We conducted a meta-analysis of genome-wide association studies for estimated glomerular filtration rate (eGFR), combining data across 133,413 individuals with replication in up to 42,166 individuals. We identify 24 new and confirm 29 previously identified loci. Of these 53 loci, nineteen associate with eGFR among individuals with diabetes. Using bioinformatics, we show that identified genes at eGFR loci are enriched for expression in kidney tissues and in pathways relevant for kidney development and transmembrane transporter activity, kidney structure, and regulation of glucose metabolism. Chromatin state mapping and DNase I hypersensitivity analyses across adult tissues demonstrate preferential mapping of associated variants to regulatory regions in kidney but not extra-renal tissues. These findings suggest that genetic determinants of eGFR are mediated largely through direct effects within the kidney and highlight important cell types and biologic pathways.