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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%.

Importance: Latino populations have one of the highest prevalences of type 2 diabetes worldwide., Objectives: To investigate the association between rare protein-coding genetic variants and prevalence of type 2 diabetes in a large Latino population and to explore potential molecular and physiological mechanisms for the observed relationships., Design, Setting, and Participants: Whole-exome sequencing was performed on DNA samples from 3756 Mexican and US Latino individuals (1794 with type 2 diabetes and 1962 without diabetes) recruited from 1993 to 2013. One variant was further tested for allele frequency and association with type 2 diabetes in large multiethnic data sets of 14,276 participants and characterized in experimental assays., Main Outcome and Measures: Prevalence of type 2 diabetes. Secondary outcomes included age of onset, body mass index, and effect on protein function., Results: A single rare missense variant (c.1522G>A [p.E508K]) was associated with type 2 diabetes prevalence (odds ratio [OR], 5.48; 95% CI, 2.83-10.61; P = 4.4 × 10(-7)) in hepatocyte nuclear factor 1-α (HNF1A), the gene responsible for maturity onset diabetes of the young type 3 (MODY3). This variant was observed in 0.36% of participants without type 2 diabetes and 2.1% of participants with it. In multiethnic replication data sets, the p.E508K variant was seen only in Latino patients (n = 1443 with type 2 diabetes and 1673 without it) and was associated with type 2 diabetes (OR, 4.16; 95% CI, 1.75-9.92; P = .0013). In experimental assays, HNF-1A protein encoding the p.E508K mutant demonstrated reduced transactivation activity of its target promoter compared with a wild-type protein. In our data, carriers and noncarriers of the p.E508K mutation with type 2 diabetes had no significant differences in compared clinical characteristics, including age at onset. The mean (SD) age for carriers was 45.3 years (11.2) vs 47.5 years (11.5) for noncarriers (P = .49) and the mean (SD) BMI for carriers was 28.2 (5.5) vs 29.3 (5.3) for noncarriers (P = .19)., Conclusions and Relevance: Using whole-exome sequencing, we identified a single low-frequency variant in the MODY3-causing gene HNF1A that is associated with type 2 diabetes in Latino populations and may affect protein function. This finding may have implications for screening and therapeutic modification in this population, but additional studies are required.

Two workshops (2001, 2003) were held by the National Institutes of Health (NIH) to examine the need to train more biostatisticians in the U.S. to meet the increasing opportunities in the biomedical research enterprise. The supply of new PhD graduates in biostatistics in the U.S. has been relatively steady for the past two decades while the demand has increased dramatically. These workshops concluded that a renewed effort must be made in the U.S., led in part by the NIH, to add to and expand the existing training programs to increase the supply. This article summarizes those two workshops and their recommendations. Some progress has been made through a new biostatistics training program with emphasis in bioinformatics sponsored by the National Institute of General Medical Sciences (NIGMS).

We present a simple algorithm that uses self-reported ethnicity information, pedigree structure, and affection status to group families into genetically more homogeneous subsets. This algorithm should prove useful to researchers who wish to perform genetic analyses on more-homogeneous subsets when they suspect that ignoring heterogeneity could lead to false-positive results or loss of power. We applied our algorithm to the self-reported ethnicity information of 159 families from the Veterans Affairs Cooperative Study of schizophrenia. We compared these estimates of population membership with those obtained using the program structure in an analysis of 378 microsatellite markers. We found excellent concordance between family classifications determined using self-reported ethnicity information and our algorithm and those determined using genetic marker data and structure; 158 of the 159 families had concordant classifications. In addition, the degree of admixture estimated using our algorithm and self-reported ethnicity information correlated well with that predicted using the genotype information.

The Finland-United States Investigation Of NIDDM Genetics (FUSION) study aims to identify genetic variants that predispose to type 2 diabetes by studying affected sibling pair families from Finland. Chromosome 20 showed our strongest initial evidence for linkage. It currently has a maximum logarithm of odds (LOD) score of 2.48 at 70 cM in a set of 495 families. In this study, we searched for diabetes susceptibility variant(s) at 20q13 by genotyping single nucleotide polymorphism (SNP) markers in case and control DNA pools. Of 291 SNPs successfully typed in a 7.5-Mb interval, the strongest association confirmed by individual genotyping was with SNP rs2144908, located 1.3 kb downstream of the primary beta-cell promoter P2 of hepatocyte nuclear factor-4 alpha (HNF4A). This SNP showed association with diabetes disease status (odds ratio [OR] 1.33, 95% CI 1.06-1.65, P = 0.011) and with several diabetes-related traits. Most of the evidence for linkage at 20q13 could be attributed to the families carrying the risk allele. We subsequently found nine additional associated SNPs spanning a 64-kb region, including the P2 and P1 promoters and exons 1-3. Our results and the independent observation of association of SNPs near the P2 promoter with diabetes in a separate study population of Ashkenazi Jewish origin suggests that variant(s) located near or within HNF4A increases susceptibility to type 2 diabetes.

Several prior reports have suggested that chromosomal region 13q32 may harbor a schizophrenia susceptibility gene. In an attempt to replicate this finding, we assessed linkage between chromosome 13 markers and schizophrenia in 166 families, each with two or more affected members. The families, assembled from multiple centers by the Department of Veterans Affairs Cooperative Studies Program, included 392 sampled affected subjects and 216 affected sib pairs. By DSM-III-R criteria, 360 subjects (91.8%) had a diagnosis of schizophrenia and 32 (8.2%) were classified as schizoaffective disorder, depressed. The families had mixed ethnic backgrounds. The majority were northern European-American families (n = 62, 37%), but a substantial proportion were African-American kindreds (n = 60, 36%). Chromosome 13 markers, spaced at intervals of approximately 10 cM over the entire chromosome and 2-5 cM for the 13q32 region were genotyped and the data analyzed using semi-parametric affected only linkage analysis. For the combined sample (with race broadly defined and schizophrenia narrowly defined) the maximum LOD score was 1.43 (Z-score of 2.57; P = 0.01) at 79.0 cM between markers D13S1241 (76.3 cM) and D13S159 (79.5 cM). Both ethnic groups showed a peak in this region. The peak is within 3 cM of the peak reported by Brzustowicz et al. [1999: Am J Hum Genet 65:1096-1103]., (Copyright 2002 Wiley-Liss, Inc.)