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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.

BackgroundLarge-scale Parkinson’s disease (PD) genome-wide association studies (GWAS) and meta-analyses have, until recently, only been conducted on subjects with European-ancestry. Consequently, polygenic risk scores (PRS) constructed using PD GWAS data are likely to be less predictive when applied to non-European cohorts.MethodsUsing GWAS data from Nalls et al. 2019, we constructed a PD PRS for a Latino PD cohort (LARGE-PD) and tested it for association with PD status. We validated the PRS performance through testing the PD PRS in an independent cohort of Latino PD patients and by repeating the PRS analysis in LARGE-PD with the addition of 440 external Peruvian controls. To explore the global distribution of PD PRS, we utilized 1000 Genomes Project (1KGP) and Peruvian Genome Project (PGP) data to estimate PD risk allele frequencies. We also tested SNCA haplotypes for association with PD risk using logistic regression in LARGE-PD and a European-ancestry PD cohort from the International Parkinson Disease Genomics Consortium (IPDGC).ResultsThe GWAS-significant PD PRS had an area under the receiver-operator curve (AUC) of 0.668 (95% CI: 0.640-0.695) and explained 2.2% of the phenotypic variance on the liability scale in LARGE-PD. The inclusion of external Peruvian data as controls mitigated this result, dropping the AUC 0.632 (95% CI: 0.607-0.657). In 1KGP Latinos, we found the PD PRS to exhibit a bias by ancestry. At the SNCA locus, haplotypes differ by ancestry. Ancestry-specific SNCA haplotypes were associated with PD status in both LARGE-PD and the IPDGC cohort (p-value < 0.05). Apart from rs356182, these haplotypes share as little as 14% of their variants.ConclusionThe PD PRS has potential for PD risk prediction in Latinos, but variability caused by admixture patterns and bias in the PD PRS calculated using only European-ancestry data limits its utility. The inclusion of diverse subjects can help elucidate PD risk loci and improve risk prediction in non-European cohorts. In the case of the SNCA locus, by leveraging a Latino cohort, we provide orthogonal evidence for rs356182 causality.

OBJECTIVE This work was undertaken in order to identify Parkinson's disease (PD) risk variants in a Latino cohort, to describe the overlap in the genetic architecture of PD in Latinos compared to European-ancestry subjects, and to increase the diversity in PD genome-wide association (GWAS) data. METHODS We genotyped and imputed 1,497 PD cases and controls recruited from nine clinical sites across South America. We performed a GWAS using logistic mixed models; variants with a p-value

The genetic determinants of fasting glucose (FG) and fasting insulin (FI) have been studied mostly through genome and exome arrays, resulting in over 100 associated variants. We extended this work with a high-coverage whole genome sequencing (WGS) analysis from fifteen cohorts in the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. More than 23,000 non-diabetic individuals from five self-reported race/ethnicities (African, Asian, European, Hispanic and Samoan) were included for each trait. We analyzed 60M variants in race/ethnicity-specific and pooled single variant and rare variant aggregate tests. Twenty-two variants across sixteen gene regions were found significantly associated with FG or FI, eight of which were rare (Minor Allele Frequency, MAFG6PC2locus we identified a distinct FG signal at rare variant rs2232326 (MAF=0.01) after conditioning on known common variants. Functional annotations show rs2232326 to be disruptive and likely damaging while being weakly transcribed in islets. A pair of FG-associated variants were identified near theSLC30A8locus. These variants, one of which was rare (MAF=0.001) and Asian race/ethnicity-specific, were shown to be in islet-specific active enhancer regions. Other associated regions include rare variants nearROBO1andPTPRT, and common variants nearMTNR1B, GCK, GCKR, FOXA2, APOB, TCF7L2, andADCY5. We provide a catalog of nucleotide-resolution genomic variation spanning intergenic and intronic regions down to a minor allele count of 20, creating a foundation for future sequencing-based investigation of glycemic traits.

Type 2 diabetes is increasing in all ancestry groups1. Part of its genetic basis may reside among the rare (minor allele frequency 2. We analyzed high-coverage (mean depth 38.2x) whole genome sequencing from 9,639 individuals with T2D and 34,994 controls in the NHLBI’s Trans-Omics for Precision Medicine (TOPMed) program2 to show that rare, non-coding variants that are poorly captured by genotyping arrays or imputation panels contribute h2=53% (P=4.2×10−5) to the genetic component of risk in the largest (European) ancestry subset. We coupled sequence variation with islet epigenomic signatures3 to annotate and group rare variants with respect to gene expression4, chromatin state5 and three-dimensional chromatin architecture6, and show that pancreatic islet regulatory elements contribute to T2D genetic risk (h2=8%, P=2.4×10−3). We used islet annotation to create a non-coding framework for rare variant aggregation testing. This approach identified five loci containing rare alleles in islet regulatory elements that suggest novel biological mechanisms readily linked to hypotheses about variant-to-function. Large scale whole genome sequence analysis reveals the substantial contribution of rare, non-coding variation to the genetic architecture of T2D and highlights the value of tissue-specific regulatory annotation for variant-to-function discovery.

To date, over 90 Parkinson’s disease (PD) risk variants have been reported from genome-wide association studies (GWAS). However, these GWAS efforts have been limited to individuals of European and East Asian ancestry. We performed the first GWAS of Latino PD patients from South America, comparing 807 cases against 690 controls followed by association testing of suggestive loci in a replication cohort of 1,234 cases and 439,522 controls. We demonstrated that SNCA plays a significant role in PD etiology in a Latino cohort and identified a suggestive locus near NRROS on chromosome 3 that appeared to be driven by Peruvian subjects. We also characterized the overlap of PD genetic architecture between Europeans and Latinos with a replication of significant variants identified by Nalls et al. in their 2019 GWAS1, finding 80% concordance in direction of effect. We then leveraged the population history of Latinos via admixture mapping, identifying a significant locus on chromosome 14 in a joint test of ancestries, driven by the Native American ancestral background, and a significant locus on chromosome 6 in our test of African ancestry, containing the genes STXBP6 and RPS6KA2, respectively. Ultimately, our work reflects the most comprehensive characterization of PD genetic architecture in Latinos to date.

Background: Parkinson's disease is the second most common neurodegenerative disorder and affects people from all ethnic backgrounds, yet little is known about the genetics of Parkinson's disease in non-European populations. In addition, the overall identification of copy number variants at a genome-wide level has been understudied in Parkinson's disease patients. Objectives: To understand the genome-wide burden of copy number variants in Latinos and its association with Parkinson's disease. Methods: We used genome-wide genotyping data from 747 Parkinson's disease patients and 632 ancestry matched controls from the Latin American Research Consortium on the Genetics of Parkinson's disease. Results: Genome-wide copy number burden analysis showed no difference between patients vs. controls, whereas patients were significantly enriched for copy number variants overlapping known Parkinson's disease genes compared to controls (Odds Ratio: 3.97 [1.69 - 10.5], P = 0.018). PARK2 showed the strongest copy number burden, with 20 copy number variant carriers. These patients presented an earlier age of disease onset compared to patients with other copy number variants (median age at onset: 31 years vs. 57 years, P = 7.46 x 10-7). Conclusions: We found that Parkinson's disease patients are significantly enriched with copy number variants affecting known Parkinson's disease genes. We also identified that out of 250 patients with early-onset disease, 5.6% carried a copy number variant on PARK2 in our cohort. Our study is the first to analyze genome-wide copy number variants association in Latino Parkinson's disease patients and provides insights about this complex disease in this understudied population.

De novo mutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole-genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) Program, we called 93,325 single-nucleotide DNMs across 1,465 trios from an array of diverse human populations, and used them to directly estimate and analyze DNM counts, rates, and spectra. We find a significant positive correlation between local recombination rate and local DNM rate, and that DNM rate explains a substantial portion (8.98 to 34.92%, depending on the model) of the genome-wide variation in population-level genetic variation from 41K unrelated TOPMed samples. Genome-wide heterozygosity does correlate with DNM rate, but only explains h 2 ), which suggest that variation in DNM rate is significantly shaped by nonadditive genetic effects and the environment.

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

de novoMutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) program, we directly estimate and analyze DNM counts, rates, and spectra from 1,465 trios across an array of diverse human populations. Using the resulting call set of 86,865 single nucleotide DNMs, we find a significant positive correlation between local recombination rate and local DNM rate, which together can explain up to 35.5% of the genome-wide variation in population level rare genetic variation from 41K unrelated TOPMed samples. While genome-wide heterozygosity does correlate weakly with DNM count, we do not find significant differences in DNM rate between individuals of European, African, and Latino ancestry, nor across ancestrally distinct segments within admixed individuals. However, interestingly, we do find significantly fewer DNMs in Amish individuals compared with other Europeans, even after accounting for parental age and sequencing center. Specifically, we find significant reductions in the number of T→C mutations in the Amish, which seems to underpin their overall reduction in DNMs. Finally, we calculate near-zero estimates of narrow sense heritability (h2), which suggest that variation in DNM rate is significantly shaped by non-additive genetic effects and/or the environment, and that a less mutagenic environment may be responsible for the reduced DNM rate in the Amish.SignificanceHere we provide one of the largest and most diverse humande novomutation (DNM) call sets to date, and use it to quantify the genome-wide relationship between local mutation rate and population-level rare genetic variation. While we demonstrate that the human single nucleotide mutation rate is similar across numerous human ancestries and populations, we also discover a reduced mutation rate in the Amish founder population, which shows that mutation rates can shift rapidly. Finally, we find that variation in mutation rates is not heritable, which suggests that the environment may influence mutation rates more significantly than previously realized.