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

2017 ◽  
Author(s):  
Pradeep Natarajan ◽  
Gina M. Peloso ◽  
S. Maryam Zekavat ◽  
May Montasser ◽  
Andrea Ganna ◽  
...  

Deep-coverage whole genome sequencing at the population level is now feasible and offers potential advantages for locus discovery, particularly in the analysis rare mutations in non-coding regions. Here, we performed whole genome sequencing in 16,324 participants from four ancestries at mean depth >29X and analyzed correlations of genotypes with four quantitative traits – plasma levels of total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides. We conducted a discovery analysis including common or rare variants in coding as well as non-coding regions and developed a framework to interpret genome sequence for dyslipidemia risk. Common variant association yielded loci previously described with the exception of a few variants not captured earlier by arrays or imputation. In coding sequence, rare variant association yielded known Mendelian dyslipidemia genes and, in non-coding sequence, we detected no rare variant association signals after application of four approaches to aggregate variants in non-coding regions. We developed a new, genome-wide polygenic score for LDL-C and observed that a high polygenic score conferred similar effect size to a monogenic mutation (~30 mg/dl higher LDL-C for each); however, among those with extremely high LDL-C, a high polygenic score was considerably more prevalent than a monogenic mutation (23% versus 2% of participants, respectively).


2019 ◽  
Author(s):  
Zilin Li ◽  
Xihao Li ◽  
Yaowu Liu ◽  
Jincheng Shen ◽  
Han Chen ◽  
...  

AbstractWhole genome sequencing (WGS) studies are being widely conducted to identify rare variants associated with human diseases and disease-related traits. Classical single-marker association analyses for rare variants have limited power, and variant-set based analyses are commonly used to analyze rare variants. However, existing variant-set based approaches need to pre-specify genetic regions for analysis, and hence are not directly applicable to WGS data due to the large number of intergenic and intron regions that consist of a massive number of non-coding variants. The commonly used sliding window method requires pre-specifying fixed window sizes, which are often unknown as a priori, are difficult to specify in practice and are subject to limitations given genetic association region sizes are likely to vary across the genome and phenotypes. We propose a computationally-efficient and dynamic scan statistic method (Scan the Genome (SCANG)) for analyzing WGS data that flexibly detects the sizes and the locations of rare-variants association regions without the need of specifying a prior fixed window size. The proposed method controls the genome-wise type I error rate and accounts for the linkage disequilibrium among genetic variants. It allows the detected rare variants association region sizes to vary across the genome. Through extensive simulated studies that consider a wide variety of scenarios, we show that SCANG substantially outperforms several alternative rare-variant association detection methods while controlling for the genome-wise type I error rates. We illustrate SCANG by analyzing the WGS lipids data from the Atherosclerosis Risk in Communities (ARIC) study.



2019 ◽  
Vol 104 (5) ◽  
pp. 802-814 ◽  
Author(s):  
Zilin Li ◽  
Xihao Li ◽  
Yaowu Liu ◽  
Jincheng Shen ◽  
Han Chen ◽  
...  


2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Yury A. Barbitoff ◽  
Dmitrii E. Polev ◽  
Andrey S. Glotov ◽  
Elena A. Serebryakova ◽  
Irina V. Shcherbakova ◽  
...  


2020 ◽  
Vol 29 (6) ◽  
pp. 967-979 ◽  
Author(s):  
Revital Bronstein ◽  
Elizabeth E Capowski ◽  
Sudeep Mehrotra ◽  
Alex D Jansen ◽  
Daniel Navarro-Gomez ◽  
...  

Abstract Inherited retinal degenerations (IRDs) are at the focus of current genetic therapeutic advancements. For a genetic treatment such as gene therapy to be successful, an accurate genetic diagnostic is required. Genetic diagnostics relies on the assessment of the probability that a given DNA variant is pathogenic. Non-coding variants present a unique challenge for such assessments as compared to coding variants. For one, non-coding variants are present at much higher number in the genome than coding variants. In addition, our understanding of the rules that govern the non-coding regions of the genome is less complete than our understanding of the coding regions. Methods that allow for both the identification of candidate non-coding pathogenic variants and their functional validation may help overcome these caveats allowing for a greater number of patients to benefit from advancements in genetic therapeutics. We present here an unbiased approach combining whole genome sequencing (WGS) with patient-induced pluripotent stem cell (iPSC)-derived retinal organoids (ROs) transcriptome analysis. With this approach, we identified and functionally validated a novel pathogenic non-coding variant in a small family with a previously unresolved genetic diagnosis.



2018 ◽  
Author(s):  
Zagaa Odgerel ◽  
Nora Hernandez ◽  
Jemin Park ◽  
Ruth Ottman ◽  
Elan D. Louis ◽  
...  

ABSTRACTEssential tremor (ET) is one of the most common movement disorders. The etiology of ET remains largely unexplained. Whole genome sequencing (WGS) is likely to be of value in understanding a large proportion of ET with Mendelian and complex disease inheritance patterns. In ET families with Mendelian inheritance patterns, WGS may lead to gene identification where WES analysis failed to identify the causative variant due to incomplete coverage of the entire coding region of the genome. Alternatively, in ET families with complex disease inheritance patterns with gene x gene and gene x environment interactions enrichment of functional rare coding and non-coding variants may explain the heritability of ET. We performed WGS in eight ET families (n=40 individuals) enrolled in the Family Study of Essential Tremor. The analysis included filtering WGS data based on allele frequency in population databases, rare variant classification and association testing using the Mixed-Model Kernel Based Adaptive Cluster (MM-KBAC) test and prioritization of candidate genes identified within families using phenolyzer. WGS analysis identified candidate genes for ET in 5/8 (62.5%) of the families analyzed. WES analysis in a subset of these families in our previously published study failed to identify candidate genes. In one family, we identified a deleterious and damaging variant (c.1367G>A, p.(Arg456Gln)) in the candidate gene, CACNA1G, which encodes the pore forming subunit of T-type Ca(2+) channels, CaV3.1, and is expressed in various motor pathways and has been previously implicated in neuronal autorhythmicity and ET. Other candidate genes identified include SLIT3 (family D), which encodes an axon guidance molecule and in three families, phenolyzer prioritized genes that are associated with hereditary neuropathies (family A, KARS, family B, KIF5A and family F, NTRK1). This work has identified candidate genes and pathways for ET that can now be prioritized for functional studies.



PLoS ONE ◽  
2019 ◽  
Vol 14 (8) ◽  
pp. e0220512 ◽  
Author(s):  
Zagaa Odgerel ◽  
Shilpa Sonti ◽  
Nora Hernandez ◽  
Jemin Park ◽  
Ruth Ottman ◽  
...  


Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 379-379
Author(s):  
Marsha M Wheeler ◽  
Barbara A Konkle ◽  
Crystal Watson ◽  
Glenn F. Pierce ◽  
Deborah A Nickerson ◽  
...  

Abstract Background. Hemophilia A is a rare X-linked bleeding disorder resulting from deficiency in coagulation factor VIII. Numerous genetic variants (>2000) affecting the F8 gene have been implicated as causative of hemophilia A, including structural variants (SVs) such as copy number variants (CNVs) and large intra-chromosomal inversions caused by recombination between distant regions with high homology to sequences within F8 intron 1 or intron 22. SVs detected in patients with hemophilia are associated with more severe disease, and different types of SVs may inform inhibitor risk. For the vast majority of patients, causative variants can be identified using targeted DNA sequencing of F8 coding regions and/or the use of methods which detect known SVs (e.g. inverse shifting PCR, long-range PCR, MLPA). However, these approaches fail to explain 1-3% of hemophilia A cases. We hypothesized that a dedicated structural variant analysis at the F8 locus using whole genome sequencing data could identify previously undetected deleterious F8 gene variants in unsolved cases of hemophilia A. Methods. Cases were selected from the My Life, Our Future (MLOF) hemophilia study cohort recently whole genome sequenced by the NHLBI TOPMed program. In this study, we performed a custom SV analyses using whole genome sequencing (WGS) data from 11 cases of severe hemophilia A (factor VIII activity level < 1%) that remained genetically unexplained after exhausting all available laboratory testing methods. Two of the eleven unsolved severe hemophilia A cases (18%) were reported to have had an inhibitor. Results. SV analyses of the F8 genomic region revealed previously undetected deletions and inversions in 6 out of the 11 cases. In these 6 samples, SV calls were supported by multiple sequencing reads (> 25 reads) and multiple types of read evidence (read depth, paired-end and/or split read evidence). Two deletions within intron 6 were detected in a single hemophilia A case, a finding which suggests F8 intron 6 may contain one or more regulatory elements critical for F8 expression. Three distinct large inversions predicted to disrupt the F8 structural gene were detected in five other cases; a 720Kb inversion with breakpoints in F8 intron 6 and SPRY3 intron 1 (n=1), a 20Mb inversion with breakpoints in F8 intron 1 and INTS6L intron 8 (n=1), and a 7.4Kb inversion with breakpoints in F8 intron 25 and the SMIM9 intron 1 (n=3). These events are novel in hemophilia and were also not present in the larger, sequenced My Life, Our Future dataset (N=2186), supporting these SVs as likely causative of severe hemophilia A. Both cases with inhibitors had the F8 intron 25-SMIM9 inversion. Conclusions. This work demonstrates that dedicated analyses of WGS for SVs originating in non-coding regions can identify novel variants in previously unsolved cases of hemophilia A. We conclude that any genetic studies of diseases caused by loss-of-function variants should consider dedicated analyses for SVs. We predict additional deleterious SVs remain to be discovered in rare unexplained cases of hemophilia. Disclosures Konkle: BioMarin: Consultancy; Bioverativ: Research Funding; CSL Behring: Consultancy; Genentech: Consultancy; Spark: Consultancy, Research Funding; Pfizer: Research Funding; Gilead: Consultancy; Sangamo: Research Funding; Shire: Research Funding. Johnsen:CSL Behring: Consultancy; Octapharma: Consultancy.



2015 ◽  
Vol 6 (1) ◽  
Author(s):  
Masao Nagasaki ◽  
◽  
Jun Yasuda ◽  
Fumiki Katsuoka ◽  
Naoki Nariai ◽  
...  


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