David Altshuler

Bio: David Altshuler 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 162, co-authored 345 publications receiving 201782 citations. Previous affiliations of David Altshuler include Vertex Pharmaceuticals & Massachusetts Institute of Technology.

A comprehensive haplotype analysis of CYP19 and breast cancer risk: the Multiethnic Cohort

Abstract: The CYP19 gene encodes for aromatase (P450arom), a key steroidogenic enzyme that catalyzes the final step of estrogen biosynthesis. Apart from rare mutations in CYP19 which result in severe phenotypes associated with estrogen insufficiency, little is known about whether common variation in CYP19 is associated with risk of hormone-related diseases. In this study, we employed a haplotype-based approach to search for common disease-associated variants in this candidate breast cancer susceptibility gene among African-American, Hawaiian, Japanese, Latina and White women in the Multiethnic Cohort Study (MEC). We utilized 74 densely spaced single-nucleotide polymorphisms (SNPs) (one every approximately 2.6 kb) spanning 189.4 kb of the CYP19 locus to characterize linkage disequilibrium (LD) and haplotype patterns among 69-70 individuals from each ethnic population. We detected four regions of strong LD (blocks 1-4) that were quite closely conserved across populations. Within each block there was a limited diversity of common haplotypes (5 to 10 with a frequency >/=5%) and most haplotypes were observed to be shared across populations. Twenty-five haplotype-tagging SNPs (htSNPs) were selected to predict the common haplotypes with high probability (average Rh2=0.92) and genotyped in a breast cancer case-control study in the MEC (cases, n=1355; controls, n=2580). We first performed global tests for differences in risk according to the common haplotypes and observed significant haplotype-effects in block 2 [P=0.01; haplotypes 2b (OR=1.23; 95% CI, 1.07-1.40), 2d (OR=1.28; 95% CI, 1.01-1.62)]. We also found a common long-range haplotype comprised of block-specific haplotypes 2b and 3c to be associated with increased risk of breast cancer (haplotype 2b-3c: OR=1.31; 95% CI, 1.11-1.54). Our findings suggest the hypothesis that women with the long-range CYP19 haplotype 2b-3c may be carriers of a predisposing breast cancer susceptibility allele.

High-Density Lipoprotein-Mimicking Nanodiscs for Chemo-immunotherapy against Glioblastoma Multiforme.

Abstract: Glioblastoma multiforme (GBM) is an aggressive primary brain tumor, for which there is no cure. Treatment effectiveness for GBM has been limited due to tumor heterogeneity, an immunosuppressive tumor microenvironment (TME), and the presence of the blood-brain barrier, which hampers the transport of chemotherapeutic compounds to the central nervous system (CNS). High-density lipoprotein (HDL)-mimicking nanodiscs hold considerable promise to achieve delivery of bioactive compounds into tumors. Herein, we tested the ability of synthetic HDL nanodiscs to deliver chemotherapeutic agents to the GBM microenvironment and elicit tumor regression. To this end, we developed chemo-immunotherapy delivery vehicles based on sHDL nanodiscs loaded with CpG, a Toll-like receptor 9 (TLR9) agonist, together with docetaxel (DTX), a chemotherapeutic agent, for targeting GBM. Our data show that delivery of DTX-sHDL-CpG nanodiscs into the tumor mass elicited tumor regression and antitumor CD8+ T cell responses in the brain TME. We did not observe any overt off-target side effects. Furthermore, the combination of DTX-sHDL-CpG treatment with radiation (IR), which is the standard of care for GBM, resulted in tumor regression and long-term survival in 80% of GBM-bearing animals. Mice remained tumor-free upon tumor cell rechallenge in the contralateral hemisphere, indicating the development of anti-GBM immunological memory. Collectively, these data indicate that sHDL nanodiscs constitute an effective drug delivery platform for the treatment of GBM, resulting in tumor regression, long-term survival, and immunological memory when used in combination with IR. The proposed delivery platform has significant potential for clinical translation.

A Genome-Wide Association Study Identifies LIPA as a Susceptibility Gene for Coronary Artery Disease

Abstract: Background—eQTL analyses are important to improve the understanding of genetic association results. We performed a genome-wide association and global gene expression study to identify functionally ...

Common SNPs in HMGCR in Micronesians and Whites Associated With LDL-Cholesterol Levels Affect Alternative Splicing of Exon13

Abstract: Background— Variation in LDL-cholesterol (LDL-C) among individuals is a complex genetic trait involving multiple genes and gene-environment interactions. Methods and Results— In a genome-wide association study (GWAS) to identify genetic variants influencing LDL-C in an isolated population from Kosrae, we observed associations for SNPs in the gene encoding 3hydroxy-3-methylglutaryl (HMG)-coenzyme A (CoA) reductase (HMGCR). Three of these SNPs (rs7703051, rs12654264, and rs3846663) met the statistical threshold of genome-wide significance when combined with data from the Diabetes Genetics Initiative GWAS. We followed up the association results and identified a functional SNP in intron13 (rs3846662), which was in linkage disequilibrium with the SNPs of genome-wide significance and affected alternative splicing of HMGCR mRNA. In vitro studies in human lymphoblastoid cells demonstrated that homozygosity for the rs3846662 minor allele was associated with up to 2.2-fold lower expression of alternatively spliced HMGCR mRNA lacking exon13, and minigene transfection assays confirmed that allele status at rs3846662 directly modulated alternative splicing of HMGCR exon13 (42.9±3.9 versus 63.7±1.0%Δexon13/total HMGCR mRNA, P =0.02). Further, the alternative splice variant could not restore HMGCR activity when expressed in HMGCR deficient UT-2 cells. Conclusion— We identified variants in HMGCR that are associated with LDL-C across populations and affect alternative splicing of HMGCR exon13.

Increased Burden of Cardiovascular Disease in Carriers of APOL1 Genetic Variants

Abstract: Rationale:Two distinct alleles in the gene encoding apolipoprotein L1 (APOL1), a major component of high-density lipoprotein, confer protection against Trypanosoma brucei rhodesiense infection and also increase risk for chronic kidney disease. Approximately 14% of Americans with African ancestry carry 2 APOL1 risk alleles, accounting for the high chronic kidney disease burden in this population. Objective:We tested whether APOL1 risk alleles significantly increase risk for atherosclerotic cardiovascular disease (CVD) in African Americans. Methods and Results:We sequenced APOL1 in 1959 randomly selected African American participants in the Jackson Heart Study (JHS) and evaluated associations between APOL1 genotypes and renal and cardiovascular phenotypes. Previously identified association between APOL1 genotypes and chronic kidney disease was confirmed (P=2.4×10−6). Among JHS participants with 2 APOL1 risk alleles, we observed increased risk for CVD (50/763 events among participants without versus 37/280 e...

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.

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Abstract: Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

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.

limma powers differential expression analyses for RNA-sequencing and microarray studies

Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.