111 research outputs found
Sequencing of 53,831 diverse genomes from the NHLBI TOPMed Program
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%
Five Blood Pressure Loci Identified by an Updated Genome-Wide Linkage Scan: Meta-Analysis of the Family Blood Pressure Program
Background A preliminary genome-wide linkage analysis of blood pressure in the Family Blood Pressure Program (FBPP) was reported previously. We harnessed the power and ethnic diversity of the final pooled FBPP dataset to identify novel loci for blood pressure thereby enhancing localization of genes containing less common variants with large effects on blood pressure levels and hypertension. Methods We performed one overall and 4 race-specific meta-analyses of genome-wide blood pressure linkage scans using data on 4,226African-American, 2,154 Asian, 4,229 Caucasian, and 2,435 Mexican- American participants (total N = 13,044). Variance components models were fit to measured (raw) blood pressure levels and two types of antihypertensive medication adjusted blood pressure phenotypes within each of 10 subgroups defined by race and network. A modified Fisher's method was used to combine the P values for each linkage marker across the 10 subgroups. Results Five quantitative trait loci (QTLs) were detected on chromosomes 6p22.3, 8q23.1, 20q13.12, 21q21.1, and 21q21.3 based on significant linkage evidence (defined by logarithm of odds (lod) score ≥3) in at least one meta-analysis and lod scores ≥1 in at least 2 subgroups defined by network and race. The chromosome 8q23.1 locus was supported by Asian-, Caucasian-, and Mexican-American-specific meta-analyses. Conclusions The new QTLs reported justify new candidate gene studies. They may help support results from genome-wide association studies (GWAS) that fall in these QTL regions but fail to achieve the genome-wide significance. American Journal of Hypertension advance online publication 9 December 2010;doi:10.1038/ajh.2010.23
Five blood pressure loci identified by an updated genome-wide linkage scan: meta-analysis of the Family Blood Pressure Program.
BACKGROUND: A preliminary genome-wide linkage analysis of blood pressure in the Family Blood Pressure Program (FBPP) was reported previously. We harnessed the power and ethnic diversity of the final pooled FBPP dataset to identify novel loci for blood pressure thereby enhancing localization of genes containing less common variants with large effects on blood pressure levels and hypertension.
METHODS: We performed one overall and 4 race-specific meta-analyses of genome-wide blood pressure linkage scans using data on 4,226 African-American, 2,154 Asian, 4,229 Caucasian, and 2,435 Mexican-American participants (total N = 13,044). Variance components models were fit to measured (raw) blood pressure levels and two types of antihypertensive medication adjusted blood pressure phenotypes within each of 10 subgroups defined by race and network. A modified Fisher's method was used to combine the P values for each linkage marker across the 10 subgroups.
RESULTS: Five quantitative trait loci (QTLs) were detected on chromosomes 6p22.3, 8q23.1, 20q13.12, 21q21.1, and 21q21.3 based on significant linkage evidence (defined by logarithm of odds (lod) score ≥3) in at least one meta-analysis and lod scores ≥1 in at least 2 subgroups defined by network and race. The chromosome 8q23.1 locus was supported by Asian-, Caucasian-, and Mexican-American-specific meta-analyses.
CONCLUSIONS: The new QTLs reported justify new candidate gene studies. They may help support results from genome-wide association studies (GWAS) that fall in these QTL regions but fail to achieve the genome-wide significance
Genome-wide Linkage and Regional Association Study of Obesity-related Phenotypes: The GenSalt study
ObjectiveTo identify chromosomal regions harboring quantitative trait loci (QTL) for waist circumference (WC) and body mass index (BMI).Design and MethodsWe conducted a genome-wide linkage scan and regional association study WC and BMI among 633 Chinese families.ResultsA significant linkage signal for WC was observed at 22q13.31–22q13.33 in the overall analysis (LOD=3.13). Follow-up association study of 22q13.31–13.33 revealed an association between the TBC1D22A gene marker rs16996195 and WC (false discovery rate (FDR)-Q<0.05). In gender-stratified analysis, suggestive linkage signals were attained for WC at 2p24.3–2q12.2 and 22q13.33 among females (LOD=2.54 and 2.15, respectively). Among males, 6q12–6q13 was suggestively linked to BMI (LOD= 2.03). Single marker association analyses at these regions identified male-specific relationships of 6 single nucleotide polymorphisms (SNPs) at 2p24.3–2q12.2 (rs100955, rs13020676, rs13014034, rs12990515, rs17024325 and rs2192712) and 5 SNPs at 6q12–6q13 (rs7747318, rs7767301, rs12197115, rs12203049, and rs9454847) with the obesity-related phenotypes (all FDR-Q<0.05). At chromosome 6q12–6q13, markers rs7755450 and rs11758293 predicted BMI in females (both FDR-Q<0.05).ConclusionsWe described genomic regions on chromosomes 2, 6, and 22 which may harbor important obesity-susceptibility loci. Follow-up study of these regions revealed several novel variants associated with obesity related traits. Future work to confirm these promising findings is warranted
Prediction of adult class II/III obesity from childhood BMI: the i3C consortium
Background and objectives: Adult class II/III obesity (BMI ≥ 35 kg/m2) has significant adverse health outcomes. Early prevention and treatment are critical, but prospective childhood risk estimates are lacking. This study aimed to define the prospective risk of adult class II/III obesity, using childhood BMI.Methods: Children ages 3–19 years enrolled in cohorts of the International Childhood Cardiovascular Cohort (i3C) consortium with measured BMI assessments in childhood and adulthood were included. Prospective risk of adult class II/III obesity was modeled based on childhood age, sex, race, and BMI.Results: A total of 12,142 individuals (44% male, 85% white) were assessed at median age 14 [Interquartile range, IQR: 11, 16] and 33 [28, 39] years. Class II/III adult obesity developed in 6% of children with normal weight; 29% of children with overweight; 56% of children with obesity; and 80% of children with severe obesity. However, 38% of the 1440 adults with class II/III obesity (553/1440) were normal weight as children. Prospective risk of adult class II/III obesity varied by age, sex, and race within childhood weight status classifications, and is notably higher for girls, black participants, and those in the United States. The risk of class II/III obesity increased with older adult age.Conclusions: Children with obesity or severe obesity have a substantial risk of adult class II/III obesity, and observed prospective risk estimates are now presented by age, sex, race, and childhood BMI. Clinical monitoring of children’s BMI for adult class II/III obesity risk may be especially important for females and black Americans.</p
Recent methods for polygenic analysis of genome-wide data implicate an important effect of common variants on cardiovascular disease risk
<p>Abstract</p> <p>Background</p> <p>Traditional genome-wide association studies are generally limited in their ability explain a large portion of genetic risk for most common diseases. We sought to use both traditional GWAS methods, as well as more recently developed polygenic genome-wide analysis techniques to identify subsets of single-nucleotide polymorphisms (SNPs) that may be involved in risk of cardiovascular disease, as well as estimate the heritability explained by common SNPs.</p> <p>Methods</p> <p>Using data from the Framingham SNP Health Association Resource (SHARe), three complimentary methods were applied to examine the genetic factors associated with the Framingham Risk Score, a widely accepted indicator of underlying cardiovascular disease risk. The first method adopted a traditional GWAS approach - independently testing each SNP for association with the Framingham Risk Score. The second two approaches involved polygenic methods with the intention of providing estimates of aggregate genetic risk and heritability.</p> <p>Results</p> <p>While no SNPs were independently associated with the Framingham Risk Score based on the results of the traditional GWAS analysis, we were able to identify cardiovascular disease-related SNPs as reported by previous studies. A predictive polygenic analysis was only able to explain approximately 1% of the genetic variance when predicting the 10-year risk of general cardiovascular disease. However, 20% to 30% of the variation in the Framingham Risk Score was explained using a recently developed method that considers the joint effect of all SNPs simultaneously.</p> <p>Conclusion</p> <p>The results of this study imply that common SNPs explain a large amount of the variation in the Framingham Risk Score and suggest that future, better-powered genome-wide association studies, possibly informed by knowledge of gene-pathways, will uncover more risk variants that will help to elucidate the genetic architecture of cardiovascular disease.</p
A Bivariate Genome-Wide Approach to Metabolic Syndrome: STAMPEED Consortium
OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants
Genome-Wide Association Study of Lp-PLA2 Activity and Mass in the Framingham Heart Study
Lipoprotein-associated phospholipase A2 (Lp-PLA2) is an emerging risk factor and therapeutic target for cardiovascular disease. The activity and mass of this enzyme are heritable traits, but major genetic determinants have not been explored in a systematic, genome-wide fashion. We carried out a genome-wide association study of Lp-PLA2 activity and mass in 6,668 Caucasian subjects from the population-based Framingham Heart Study. Clinical data and genotypes from the Affymetrix 550K SNP array were obtained from the open-access Framingham SHARe project. Each polymorphism that passed quality control was tested for associations with Lp-PLA2 activity and mass using linear mixed models implemented in the R statistical package, accounting for familial correlations, and controlling for age, sex, smoking, lipid-lowering-medication use, and cohort. For Lp-PLA2 activity, polymorphisms at four independent loci reached genome-wide significance, including the APOE/APOC1 region on chromosome 19 (p = 6×10−24); CELSR2/PSRC1 on chromosome 1 (p = 3×10−15); SCARB1 on chromosome 12 (p = 1×10−8) and ZNF259/BUD13 in the APOA5/APOA1 gene region on chromosome 11 (p = 4×10−8). All of these remained significant after accounting for associations with LDL cholesterol, HDL cholesterol, or triglycerides. For Lp-PLA2 mass, 12 SNPs achieved genome-wide significance, all clustering in a region on chromosome 6p12.3 near the PLA2G7 gene. Our analyses demonstrate that genetic polymorphisms may contribute to inter-individual variation in Lp-PLA2 activity and mass
NRXN3 Is a Novel Locus for Waist Circumference: A Genome-Wide Association Study from the CHARGE Consortium
Central abdominal fat is a strong risk factor for diabetes and cardiovascular disease. To identify common variants influencing central abdominal fat, we conducted a two-stage genome-wide association analysis for waist circumference (WC). In total, three loci reached genome-wide significance. In stage 1, 31,373 individuals of Caucasian descent from eight cohort studies confirmed the role of FTO and MC4R and identified one novel locus associated with WC in the neurexin 3 gene [NRXN3 (rs10146997, p = 6.4×10−7)]. The association with NRXN3 was confirmed in stage 2 by combining stage 1 results with those from 38,641 participants in the GIANT consortium (p = 0.009 in GIANT only, p = 5.3×10−8 for combined analysis, n = 70,014). Mean WC increase per copy of the G allele was 0.0498 z-score units (0.65 cm). This SNP was also associated with body mass index (BMI) [p = 7.4×10−6, 0.024 z-score units (0.10 kg/m2) per copy of the G allele] and the risk of obesity (odds ratio 1.13, 95% CI 1.07–1.19; p = 3.2×10−5 per copy of the G allele). The NRXN3 gene has been previously implicated in addiction and reward behavior, lending further evidence that common forms of obesity may be a central nervous system-mediated disorder. Our findings establish that common variants in NRXN3 are associated with WC, BMI, and obesity
MST1R kinase accelerates pancreatic cancer progression via effects on both epithelial cells and macrophages
The MST1R (RON) kinase is overexpressed in >80% of human pancreatic cancers, but its role in pancreatic carcinogenesis is unknown. In this study, we examined the relevance of Mst1r kinase to Kras driven pancreatic carcinogenesis using genetically engineered mouse models. In the setting of mutant Kras, Mst1r overexpression increased acinar-ductal metaplasia (ADM), accelerated the progression of pancreatic intraepithelial neoplasia (PanIN), and resulted in the accumulation of (mannose receptor C type 1) MRC1+, (arginase 1) Arg+ macrophages in the tumor microenvironment. Conversely, absence of a functional Mst1r kinase slowed PanIN initiation, resulted in smaller tumors, prolonged survival and a reduced tumor-associated macrophage content. Mst1r expression was associated with increased production of its ligand Mst1, and in orthotopic models, suppression of Mst1 expression resulted in reduced tumor size, changes in macrophage polarization and enhanced T cell infiltration. This study demonstrates the functional significance of Mst1r during pancreatic cancer initiation and progression. Further, it provides proof of concept that targeting Mst1r can modulate pancreatic cancer growth and the microenvironment. This study provides further rationale for targeting Mst1r as a therapeutic strategy
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