688 research outputs found

    The Value of Rare Genetic Variation in the Prediction of Common Obesity in European Ancestry Populations

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    Polygenic risk scores (PRSs) aggregate the effects of genetic variants across the genome and are used to predict risk of complex diseases, such as obesity. Current PRSs only include common variants (minor allele frequency (MAF) ≥1%), whereas the contribution of rare variants in PRSs to predict disease remains unknown. Here, we examine whether augmenting the standard common variant PRS (PRScommon) with a rare variant PRS (PRSrare) improves prediction of obesity. We used genome-wide genotyped and imputed data on 451,145 European-ancestry participants of the UK Biobank, as well as whole exome sequencing (WES) data on 184,385 participants. We performed single variant analyses (for both common and rare variants) and gene-based analyses (for rare variants) for association with BMI (kg/m2), obesity (BMI ≥ 30 kg/m2), and extreme obesity (BMI ≥ 40 kg/m2). We built PRSscommon and PRSsrare using a range of methods (Clumping+Thresholding [C+T], PRS-CS, lassosum, gene-burden test). We selected the best-performing PRSs and assessed their performance in 36,757 European-ancestry unrelated participants with whole genome sequencing (WGS) data from the Trans-Omics for Precision Medicine (TOPMed) program. The best-performing PRScommon explained 10.1% of variation in BMI, and 18.3% and 22.5% of the susceptibility to obesity and extreme obesity, respectively, whereas the best-performing PRSrare explained 1.49%, and 2.97% and 3.68%, respectively. The PRSrare was associated with an increased risk of obesity and extreme obesity (ORobesity = 1.37 per SDPRS, P obesity = 1.7x10-85; ORextremeobesity = 1.55 per SDPRS, P extremeobesity = 3.8x10-40), which was attenuated, after adjusting for PRScommon (ORobesity = 1.08 per SDPRS, P obesity = 9.8x10-6; ORextremeobesity= 1.09 per SDPRS, P extremeobesity = 0.02). When PRSrare and PRScommon are combined, the increase in explained variance attributed to PRSrare was small (incremental Nagelkerke R2 = 0.24% for obesity and 0.51% for extreme obesity). Consistently, combining PRSrare to PRScommon provided little improvement to the prediction of obesity (PRSrare AUC = 0.591; PRScommon AUC = 0.708; PRScombined AUC = 0.710). In summary, while rare variants show convincing association with BMI, obesity and extreme obesity, the PRSrare provides limited improvement over PRScommon in the prediction of obesity risk, based on these large populations

    Novel genetic loci associated with hippocampal volume

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    The hippocampal formation is a brain structure integrally involved in episodic memory, spatial navigation, cognition and stress responsiveness. Structural abnormalities in hippocampal volume and shape are found in several common neuropsychiatric disorders. To identify the genetic underpinnings of hippocampal structure here we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent loci significantly associated with hippocampal volume, four of them novel. Of the novel loci, three lie within genes (ASTN2, DPP4 and MAST4) and one is found 200 kb upstream of SHH. A hippocampal subfield analysis shows that a locus within the MSRB3 gene shows evidence of a localized effect along the dentate gyrus, subiculum, CA1 and fissure. Further, we show that genetic variants associated with decreased hippocampal volume are also associated with increased risk for Alzheimer’s disease (rg ¼ 0.155). Our findings suggest novel biological pathways through which human genetic variation influences hippocampal volume and risk for neuropsychiatric illness

    Variant-specific inflation factors for assessing population stratification at the phenotypic variance level

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    In modern Whole Genome Sequencing (WGS) epidemiological studies, participant-level data from multiple studies are often pooled and results are obtained from a single analysis. We consider the impact of differential phenotype variances by study, which we term \u27variance stratification\u27. Unaccounted for, variance stratification can lead to both decreased statistical power, and increased false positives rates, depending on how allele frequencies, sample sizes, and phenotypic variances vary across the studies that are pooled. We develop a procedure to compute variant-specific inflation factors, and show how it can be used for diagnosis of genetic association analyses on pooled individual level data from multiple studies. We describe a WGS-appropriate analysis approach, implemented in freely-available software, which allows study-specific variances and thereby improves performance in practice. We illustrate the variance stratification problem, its solutions, and the proposed diagnostic procedure, in simulations and in data from the Trans-Omics for Precision Medicine Whole Genome Sequencing Program (TOPMed), used in association tests for hemoglobin concentrations and BMI

    Associations of NINJ2 sequence variants with incident ischemic stroke in the Cohorts for Heart and Aging in Genomic Epidemiology (CHARGE) consortium

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    Background<p></p> Stroke, the leading neurologic cause of death and disability, has a substantial genetic component. We previously conducted a genome-wide association study (GWAS) in four prospective studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and demonstrated that sequence variants near the NINJ2 gene are associated with incident ischemic stroke. Here, we sought to fine-map functional variants in the region and evaluate the contribution of rare variants to ischemic stroke risk.<p></p> Methods and Results<p></p> We sequenced 196 kb around NINJ2 on chromosome 12p13 among 3,986 European ancestry participants, including 475 ischemic stroke cases, from the Atherosclerosis Risk in Communities Study, Cardiovascular Health Study, and Framingham Heart Study. Meta-analyses of single-variant tests for 425 common variants (minor allele frequency [MAF] ≥ 1%) confirmed the original GWAS results and identified an independent intronic variant, rs34166160 (MAF = 0.012), most significantly associated with incident ischemic stroke (HR = 1.80, p = 0.0003). Aggregating 278 putatively-functional variants with MAF≤ 1% using count statistics, we observed a nominally statistically significant association, with the burden of rare NINJ2 variants contributing to decreased ischemic stroke incidence (HR = 0.81; p = 0.026).<p></p> Conclusion<p></p> Common and rare variants in the NINJ2 region were nominally associated with incident ischemic stroke among a subset of CHARGE participants. Allelic heterogeneity at this locus, caused by multiple rare, low frequency, and common variants with disparate effects on risk, may explain the difficulties in replicating the original GWAS results. Additional studies that take into account the complex allelic architecture at this locus are needed to confirm these findings

    Genomewide Association Study of Statin-Induced Myopathy in Patients Recruited Using the UK Clinical Practice Research Datalink.

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    Statins can be associated with myopathy. We have undertaken a genomewide association study (GWAS) to discover and validate genetic risk factors for statin-induced myopathy in a "real-world" setting. One hundred thirty-five patients with statin myopathy recruited via the UK Clinical Practice Research Datalink were genotyped using the Illumina OmniExpress Exome version 1.0 Bead Chip and compared with the Wellcome Trust Case-Control Consortium (n = 2,501). Nominally statistically significant single nucleotide polymorphism (SNP) signals in the GWAS (P T in the SLCO1B1 gene) SNP was genomewide significant in the severe myopathy (creatine kinase > 10 × upper limit of normal or rhabdomyolysis) group (P = 2.55 × 10-9 ; odds ratio 5.15; 95% confidence interval 3.13-8.45). The association with SLCO1B1 was present for several statins and replicated in the independent validation cohorts. The data highlight the role of SLCO1B1 c.521C>T SNP as a replicable genetic risk factor for statin myopathy. No other novel genetic risk factors with a similar effect size were identified

    Common folate gene variant, MTHFR C677T, is associated with brain structure in two independent cohorts of people with mild cognitive impairment

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    AbstractA commonly carried C677T polymorphism in a folate-related gene, MTHFR, is associated with higher plasma homocysteine, a well-known mediator of neuronal damage and brain atrophy.As homocysteine promotes brain atrophy, we set out to discover whether people carrying the C677T MTHFR polymorphism which increases homocysteine, might also show systematic differences in brain structure.Using tensor-based morphometry, we tested this association in 359 elderly Caucasian subjects with mild cognitive impairment (MCI) (mean age: 75±7.1years) scanned with brain MRI and genotyped as part of Alzheimer's Disease Neuroimaging Initiative. We carried out a replication study in an independent, non-overlapping sample of 51 elderly Caucasian subjects with MCI (mean age: 76±5.5years), scanned with brain MRI and genotyped for MTHFR, as part of the Cardiovascular Health Study. At each voxel in the brain, we tested to see where regional volume differences were associated with carrying one or more MTHFR ‘T’ alleles.In ADNI subjects, carriers of the MTHFR risk allele had detectable brain volume deficits, in the white matter, of up to 2–8% per risk T allele locally at baseline and showed accelerated brain atrophy of 0.5–1.5% per T allele at 1year follow-up, after adjusting for age and sex. We replicated these brain volume deficits of up to 5–12% per MTHFR T allele in the independent cohort of CHS subjects.As expected, the associations weakened after controlling for homocysteine levels, which the risk gene affects. The MTHFR risk variant may thus promote brain atrophy by elevating homocysteine levels.This study aims to investigate the spatially detailed effects of this MTHFR polymorphism on brain structure in 3D, pointing to a causal pathway that may promote homocysteine-mediated brain atrophy in elderly people with MCI

    Whole exome sequencing study identifies novel rare and common Alzheimer's-Associated variants involved in immune response and transcriptional regulation

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    Correction: Volume: 25 Issue: 8 Pages: 1901-1903 DOI: 10.1038/s41380-019-0529-7The Alzheimer's Disease Sequencing Project (ADSP) undertook whole exome sequencing in 5,740 late-onset Alzheimer disease (AD) cases and 5,096 cognitively normal controls primarily of European ancestry (EA), among whom 218 cases and 177 controls were Caribbean Hispanic (CH). An age-, sex- andAPOEbased risk score and family history were used to select cases most likely to harbor novel AD risk variants and controls least likely to develop AD by age 85 years. We tested ~1.5 million single nucleotide variants (SNVs) and 50,000 insertion-deletion polymorphisms (indels) for association to AD, using multiple models considering individual variants as well as gene-based tests aggregating rare, predicted functional, and loss of function variants. Sixteen single variants and 19 genes that met criteria for significant or suggestive associations after multiple-testing correction were evaluated for replication in four independent samples; three with whole exome sequencing (2,778 cases, 7,262 controls) and one with genome-wide genotyping imputed to the Haplotype Reference Consortium panel (9,343 cases, 11,527 controls). The top findings in the discovery sample were also followed-up in the ADSP whole-genome sequenced family-based dataset (197 members of 42 EA families and 501 members of 157 CH families). We identified novel and predicted functional genetic variants in genes previously associated with AD. We also detected associations in three novel genes:IGHG3(p = 9.8 x 10(-7)), an immunoglobulin gene whose antibodies interact with beta-amyloid, a long non-coding RNAAC099552.4(p = 1.2 x 10(-7)), and a zinc-finger proteinZNF655(gene-based p = 5.0 x 10(-6)). The latter two suggest an important role for transcriptional regulation in AD pathogenesis.Peer reviewe

    Chromosome Xq23 Is Associated with Lower Atherogenic Lipid Concentrations and Favorable Cardiometabolic Indices

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    Autosomal genetic analyses of blood lipids have yielded key insights for coronary heart disease (CHD). However, X chromosome genetic variation is understudied for blood lipids in large sample sizes. We now analyze genetic and blood lipid data in a high-coverage whole X chromosome sequencing study of 65,322 multi-ancestry participants and perform replication among 456,893 European participants. Common alleles on chromosome Xq23 are strongly associated with reduced total cholesterol, LDL cholesterol, and triglycerides (min P = 8.5 × 10−72), with similar effects for males and females. Chromosome Xq23 lipid-lowering alleles are associated with reduced odds for CHD among 42,545 cases and 591,247 controls (P = 1.7 × 10−4), and reduced odds for diabetes mellitus type 2 among 54,095 cases and 573,885 controls (P = 1.4 × 10−5). Although we observe an association with increased BMI, waist-to-hip ratio adjusted for BMI is reduced, bioimpedance analyses indicate increased gluteofemoral fat, and abdominal MRI analyses indicate reduced visceral adiposity. Co-localization analyses strongly correlate increased CHRDL1 gene expression, particularly in adipose tissue, with reduced concentrations of blood lipids

    Druggable proteins influencing cardiac structure and function: Implications for heart failure therapies and cancer cardiotoxicity

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    Dysfunction of either the right or left ventricle can lead to heart failure (HF) and subsequent morbidity and mortality. We performed a genome-wide association study (GWAS) of 16 cardiac magnetic resonance (CMR) imaging measurements of biventricular function and structure. Cis-Mendelian randomization (MR) was used to identify plasma proteins associating with CMR traits as well as with any of the following cardiac outcomes: HF, non-ischemic cardiomyopathy, dilated cardiomyopathy (DCM), atrial fibrillation, or coronary heart disease. In total, 33 plasma proteins were prioritized, including repurposing candidates for DCM and/or HF: IL18R (providing indirect evidence for IL18), I17RA, GPC5, LAMC2, PA2GA, CD33, and SLAF7. In addition, 13 of the 25 druggable proteins (52%; 95% confidence interval, 0.31 to 0.72) could be mapped to compounds with known oncological indications or side effects. These findings provide leads to facilitate drug development for cardiac disease and suggest that cardiotoxicities of several cancer treatments might represent mechanism-based adverse effects
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