Improving power of association tests using multiple sets of imputed genotypes from distributed reference panels

The accuracy of genotype imputation depends upon two factors: the sample size of the reference panel and the genetic similarity between the reference panel and the target samples. When multiple reference panels are not consented to combine together, it is unclear how to combine the imputation results to optimize the power of genetic association studies. We compared the accuracy of 9,265 Norwegian genomes imputed from three reference panels—1000 Genomes phase 3 (1000G), Haplotype Reference Consortium (HRC), and a reference panel containing 2,201 Norwegian participants from the population‐based Nord Trøndelag Health Study (HUNT) from low‐pass genome sequencing. We observed that the population‐matched reference panel allowed for imputation of more population‐specific variants with lower frequency (minor allele frequency (MAF) between 0.05% and 0.5%). The overall imputation accuracy from the population‐specific panel was substantially higher than 1000G and was comparable with HRC, despite HRC being 15‐fold larger. These results recapitulate the value of population‐specific reference panels for genotype imputation. We also evaluated different strategies to utilize multiple sets of imputed genotypes to increase the power of association studies. We observed that testing association for all variants imputed from any panel results in higher power to detect association than the alternative strategy of including only one version of each genetic variant, selected for having the highest imputation quality metric. This was particularly true for lower frequency variants (MAF < 1%), even after adjusting for the additional multiple testing burden.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/139954/1/gepi22067_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/139954/2/gepi22067.pd

Deep-coverage whole genome sequences and blood lipids among 16,324 individuals.

Large-scale deep-coverage whole-genome sequencing (WGS) is now feasible and offers potential advantages for locus discovery. We perform WGS in 16,324 participants from four ancestries at mean depth &gt;29X and analyze genotypes with four quantitative traits-plasma total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides. Common variant association yields known loci except for few variants previously poorly imputed. Rare coding variant association yields known Mendelian dyslipidemia genes but rare non-coding variant association detects no signals. A high 2M-SNP LDL-C polygenic score (top 5th percentile) confers similar effect size to a monogenic mutation (~30 mg/dl higher for each); however, among those with severe hypercholesterolemia, 23% have a high polygenic score and only 2% carry a monogenic mutation. At these sample sizes and for these phenotypes, the incremental value of WGS for discovery is limited but WGS permits simultaneous assessment of monogenic and polygenic models to severe hypercholesterolemia

Identification of CFTR variants in Latino patients with cystic fibrosis from the Dominican Republic and Puerto Rico

BackgroundIn cystic fibrosis (CF), the spectrum and frequency of CFTR variants differ by geography and race/ethnicity. CFTR variants in White patients are wellâ described compared with Latino patients. No studies of CFTR variants have been done in patients with CF in the Dominican Republic or Puerto Rico.MethodsCFTR was sequenced in 61 Dominican Republican patients and 21 Puerto Rican patients with CF and greater than â â â â 60â mmol/L sweat chloride. The spectrum of CFTR variants was identified and the proportion of patients with 0, 1, or 2 CFTR variants identified was determined. The functional effects of identified CFTR variants were investigated using clinical annotation databases and computational prediction tools.ResultsOur study found 10% of Dominican patients had two CFTR variants identified compared with 81% of Puerto Rican patients. No CFTR variants were identified in 69% of Dominican patients and 10% of Puerto Rican patients. In Dominican patients, there were 19 identified CFTR variants, accounting for 25 out of 122 disease alleles (20%). In Puerto Rican patients, there were 16 identified CFTR variants, accounting for 36 out of 42 disease alleles (86%) in Puerto Rican patients. Thirty CFTR variants were identified overall. The most frequent variants for Dominican patients were p.Phe508del and p.Ala559Thr and for Puerto Rican patients were p.Phe508del, p.Arg1066Cys, p.Arg334Trp, and p.I507del.ConclusionsIn this first description of the CFTR variants in patients with CF from the Dominican Republic and Puerto Rico, there was a low detection rate of two CFTR variants after full sequencing with the majority of patients from the Dominican Republic without identified variants.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/153634/1/ppul24549.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/153634/2/ppul24549_am.pd

Enhanced genetic maps from family-based disease studies: population-specific comparisons

Abstract Background Accurate genetic maps are required for successful and efficient linkage mapping of disease genes. However, most available genome-wide genetic maps were built using only small collections of pedigrees, and therefore have large sampling errors. A large set of genetic studies genotyped by the NHLBI Mammalian Genotyping Service (MGS) provide appropriate data for generating more accurate maps. Results We collected a large sample of uncleaned genotype data for 461 markers generated by the MGS using the Weber screening sets 9 and 10. This collection includes genotypes for over 4,400 pedigrees containing over 17,000 genotyped individuals from different populations. We identified and cleaned numerous relationship and genotyping errors, as well as verified the marker orders. We used this dataset to test for population-specific genetic maps, and to re-estimate the genetic map distances with greater precision; standard errors for all intervals are provided. The map-interval sizes from the European (or European descent), Chinese, and Hispanic samples are in quite good agreement with each other. We found one map interval on chromosome 8p with a statistically significant size difference between the European and Chinese samples, and several map intervals with significant size differences between the African American and Chinese samples. When comparing Palauan with European samples, a statistically significant difference was detected at the telomeric region of chromosome 11p. Several significant differences were also identified between populations in chromosomal and genome lengths. Conclusions Our new population-specific screening set maps can be used to improve the accuracy of disease-mapping studies. As a result of the large sample size, the average length of the 95% confidence interval (CI) for a 10 cM map interval is only 2.4 cM, which is considerably smaller than on previously published maps.http://deepblue.lib.umich.edu/bitstream/2027.42/112826/1/12881_2010_Article_748.pd

Large scale meta-analysis characterizes genetic architecture for common psoriasis associated variants

Psoriasis is a complex disease of skin with a prevalence of about 2%. We conducted the largest meta-analysis of genome-wide association studies (GWAS) for psoriasis to date, including data from eight different Caucasian cohorts, with a combined effective sample size amp;gt;39,000 individuals. We identified 16 additional psoriasis susceptibility loci achieving genome-wide significance, increasing the number of identified loci to 63 for European-origin individuals. Functional analysis highlighted the roles of interferon signalling and the NFkB cascade, and we showed that the psoriasis signals are enriched in regulatory elements from different T cells (CD8(+) T-cells and CD4(+) T-cells including T(H)0, T(H)1 and T(H)17). The identified loci explain similar to 28% of the genetic heritability and generate a discriminatory genetic risk score (AUC = 0.76 in our sample) that is significantly correlated with age at onset (p = 2 x 10(-89)). This study provides a comprehensive layout for the genetic architecture of common variants for psoriasis.Funding Agencies|National Institutes of Health [R01AR042742, R01AR050511, R01AR054966, R01AR063611, R01AR065183]; Foundation for the National Institutes of Health; Dermatology Foundation; National Psoriasis Foundation; Arthritis National Research Foundation; Ann Arbor Veterans Affairs Hospital; Dawn and Dudley Holmes Foundation; Babcock Memorial Trust; Medical Research Council [MR/L011808/1]; German Ministry of Education and Research (BMBF); Doris Duke Foundation [2013106]; National Institute of Health [K08AR060802, R01AR06907]; Taubman Medical Research Institute; Department of Health via the NIHR comprehensive Biomedical Research Center; Kings College London; KCH NHS Foundation Trust; Barbara and Neal Henschel Charitable Foundation; Heinz Nixdorf Foundation; Estonian Ministry of Education and Research [IUT20-46]; Centre of Translational Genomics of University of Tartu (SP1GVARENG); European Regional Development Fund (Centre of Translational Medicine, University of Tartu); German Federal Ministry of Education and Research (BMBF); National Human Genome Research Institute of the National Institutes of Health [R44HG006981]; International Psoriasis Council</p

Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution.

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF &lt;5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants

Genome-wide trans-ancestry meta-analysis provides insight into the genetic architecture of type 2 diabetes susceptibility.

To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS), including 26,488 cases and 83,964 controls of European, east Asian, south Asian and Mexican and Mexican American ancestry. We observed a significant excess in the directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven new T2D susceptibility loci. Furthermore, we observed considerable improvements in the fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterization of complex trait loci and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry

Rare variant associations with waist-to-hip ratio in European-American and African-American women from the NHLBI-Exome Sequencing Project

Waist-to-hip ratio (WHR), a relative comparison of waist and hip circumferences, is an easily accessible measurement of body fat distribution, in particular central abdominal fat. A high WHR indicates more intra-abdominal fat deposition and is an established risk factor for cardiovascular disease and type 2 diabetes. Recent genome-wide association studies have identified numerous common genetic loci influencing WHR, but the contributions of rare variants have not been previously reported. We investigated rare variant associations with WHR in 1510 European-American and 1186 African-American women from the National Heart, Lung, and Blood Institute-Exome Sequencing Project. Association analysis was performed on the gene level using several rare variant association methods. The strongest association was observed for rare variants in IKBKB (P=4.0 × 10−8) in European-Americans, where rare variants in this gene are predicted to decrease WHRs. The activation of the IKBKB gene is involved in inflammatory processes and insulin resistance, which may affect normal food intake and body weight and shape. Meanwhile, aggregation of rare variants in COBLL1, previously found to harbor common variants associated with WHR and fasting insulin, were nominally associated (P=2.23 × 10−4) with higher WHR in European-Americans. However, these significant results are not shared between African-Americans and European-Americans that may be due to differences in the allelic architecture of the two populations and the small sample sizes. Our study indicates that the combined effect of rare variants contribute to the inter-individual variation in fat distribution through the regulation of insulin response