Gonçalo R. Abecasis

Bio: Gonçalo R. Abecasis is an academic researcher from University of Michigan. The author has contributed to research in topics: Genome-wide association study & Population. The author has an hindex of 179, co-authored 595 publications receiving 230323 citations. Previous affiliations of Gonçalo R. Abecasis include Johns Hopkins University School of Medicine & Wellcome Trust Centre for Human Genetics.

Association of mitochondrial DNA copy number with cardiometabolic diseases in a large cross-sectional study of multiple ancestries

Abstract: Aims We tested the hypothesis that mitochondrial DNA copy number (CN) is associated with cardiometabolic disease (CMD) traits. Methods and results We determined the cross-sectional association of mtDNA CN measured in whole blood with several CMD traits in 65,996 individuals (mean age 60, 54% women, and 79% European descent). Cohort- and ancestry/ethnicity-specific association analysis was performed adjusting for trait- and cohort-specific covariates. Age was slightly positively associated with age (0.03 s.d. / 10 years (95% CI=0.01, 0.05)) before 65 years, while every 10 years older age was associated with 0.14 s.d. lower level of mtDNA CN after 65 years (95% CI= -0.18, -0.10). In meta-analysis without adjustment for white blood cell (WBC) and differential count in participants of European descent (N=52,491), low mtDNA CN was associated with increased odds of obesity (OR with 95% CI=1.13 (1.11, 1.16), P=3.3e-30) and hypertension (OR=1.05 (1.03, 1.08), P=4.0e-07). Further adjusting for WBC and differential count in the same participants of European descent (N=44,035), associations became non-significant (P>0.05) for hypertension, attenuated for obesity (ORwithout cell count=1.15 (1.12, 1.18) versus ORcell count=1.06 (1.03, 1.08)) but strengthened for hyperlipidemia (ORwithout cell counts =1.03 (1.00, 1.06) versus ORcell counts =1.06 (1.03, 1.09)). The magnitude and directionality of most associations were consistent between participants of European descent and other ethnicity/ancestry origins. Conclusion Low levels of mtDNA CN in peripheral blood were associated with an increased risk of CMD diseases.

Transethnic analysis of psoriasis susceptibility in South Asians and Europeans enhances fine-mapping in the MHC and genomewide

Abstract: Because transethnic analysis may facilitate prioritization of causal genetic variants, we performed a genomewide association study (GWAS) of psoriasis in South Asians (SAS), consisting of 2,590 cases and 1,720 controls. Comparison with our existing European-origin (EUR) GWAS showed that effect sizes of known psoriasis signals were highly correlated in SAS and EUR (Spearman ρ = 0.78; p

ANGPTL7, a therapeutic target for increased intraocular pressure and glaucoma

Abstract: Glaucoma is a leading cause of blindness. Current glaucoma medications work by lowering intraocular pressure (IOP), a risk factor for glaucoma, but most treatments do not directly target the pathological changes leading to increased IOP, which can manifest as medication resistance as disease progresses. To identify physiological modulators of IOP, we performed genome- and exome-wide association analysis in >129,000 individuals with IOP measurements and extended these findings to an analysis of glaucoma risk. We report the identification and functional characterization of rare coding variants (including loss-of-function variants) in ANGPTL7 associated with reduction in IOP and glaucoma protection. We validated the human genetics findings in mice by establishing that Angptl7 knockout mice have lower (~2 mmHg) basal IOP compared to wild-type, with a trend towards lower IOP also in heterozygotes. Conversely, increasing murine Angptl7 levels via injection into mouse eyes increases the IOP. We also show that acute Angptl7 silencing in adult mice lowers the IOP (~2-4 mmHg), reproducing the observations in knockout mice. Collectively, our data suggest that ANGPTL7 is important for IOP homeostasis and is amenable to therapeutic modulation to help maintain a healthy IOP that can prevent onset or slow the progression of glaucoma.

Identifying tagging SNPs for African specific genetic variation from the African Diaspora Genome

Abstract: A primary goal of The Consortium on Asthma among African-ancestry Populations in the Americas (CAAPA) is to develop an “African Diaspora Power Chip” (ADPC), a genotyping array consisting of tagging SNPs, useful in comprehensively identifying African specific genetic variation. This array is designed based on the novel variation identified in 642 CAAPA samples of African ancestry with high coverage whole genome sequence data (~30x depth). This novel variation extends the pattern of variation catalogued in the 1000 Genomes and Exome Sequencing Projects to a spectrum of populations representing the wide range of West African genomic diversity. These individuals from CAAPA also comprise a large swath of the African Diaspora population and incorporate historical genetic diversity covering nearly the entire Atlantic coast of the Americas. Here we show the results of designing and producing such a microchip array. This novel array covers African specific variation far better than other commercially available arrays, and will enable better GWAS analyses for researchers with individuals of African descent in their study populations. A recent study cataloging variation in continental African populations suggests this type of African-specific genotyping array is both necessary and valuable for facilitating large-scale GWAS in populations of African ancestry.

Fast and accurate short read alignment with Burrows–Wheeler transform

Abstract: Motivation: The enormous amount of short reads generated by the new DNA sequencing technologies call for the development of fast and accurate read alignment programs. A first generation of hash table-based methods has been developed, including MAQ, which is accurate, feature rich and fast enough to align short reads from a single individual. However, MAQ does not support gapped alignment for single-end reads, which makes it unsuitable for alignment of longer reads where indels may occur frequently. The speed of MAQ is also a concern when the alignment is scaled up to the resequencing of hundreds of individuals. Results: We implemented Burrows-Wheeler Alignment tool (BWA), a new read alignment package that is based on backward search with Burrows–Wheeler Transform (BWT), to efficiently align short sequencing reads against a large reference sequence such as the human genome, allowing mismatches and gaps. BWA supports both base space reads, e.g. from Illumina sequencing machines, and color space reads from AB SOLiD machines. Evaluations on both simulated and real data suggest that BWA is ~10–20× faster than MAQ, while achieving similar accuracy. In addition, BWA outputs alignment in the new standard SAM (Sequence Alignment/Map) format. Variant calling and other downstream analyses after the alignment can be achieved with the open source SAMtools software package. Availability: http://maq.sourceforge.net Contact: [email protected]

Fast gapped-read alignment with Bowtie 2

Abstract: As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.

PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses

Abstract: Whole-genome association studies (WGAS) bring new computational, as well as analytic, challenges to researchers. Many existing genetic-analysis tools are not designed to handle such large data sets in a convenient manner and do not necessarily exploit the new opportunities that whole-genome data bring. To address these issues, we developed PLINK, an open-source C/C++ WGAS tool set. With PLINK, large data sets comprising hundreds of thousands of markers genotyped for thousands of individuals can be rapidly manipulated and analyzed in their entirety. As well as providing tools to make the basic analytic steps computationally efficient, PLINK also supports some novel approaches to whole-genome data that take advantage of whole-genome coverage. We introduce PLINK and describe the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation. In particular, we focus on the estimation and use of identity-by-state and identity-by-descent information in the context of population-based whole-genome studies. This information can be used to detect and correct for population stratification and to identify extended chromosomal segments that are shared identical by descent between very distantly related individuals. Analysis of the patterns of segmental sharing has the potential to map disease loci that contain multiple rare variants in a population-based linkage analysis.

Initial sequencing and analysis of the human genome.

Abstract: The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.

The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data

Abstract: Next-generation DNA sequencing (NGS) projects, such as the 1000 Genomes Project, are already revolutionizing our understanding of genetic variation among individuals. However, the massive data sets generated by NGS—the 1000 Genome pilot alone includes nearly five terabases—make writing feature-rich, efficient, and robust analysis tools difficult for even computationally sophisticated individuals. Indeed, many professionals are limited in the scope and the ease with which they can answer scientific questions by the complexity of accessing and manipulating the data produced by these machines. Here, we discuss our Genome Analysis Toolkit (GATK), a structured programming framework designed to ease the development of efficient and robust analysis tools for next-generation DNA sequencers using the functional programming philosophy of MapReduce. The GATK provides a small but rich set of data access patterns that encompass the majority of analysis tool needs. Separating specific analysis calculations from common data management infrastructure enables us to optimize the GATK framework for correctness, stability, and CPU and memory efficiency and to enable distributed and shared memory parallelization. We highlight the capabilities of the GATK by describing the implementation and application of robust, scale-tolerant tools like coverage calculators and single nucleotide polymorphism (SNP) calling. We conclude that the GATK programming framework enables developers and analysts to quickly and easily write efficient and robust NGS tools, many of which have already been incorporated into large-scale sequencing projects like the 1000 Genomes Project and The Cancer Genome Atlas.