Showing papers by "David Altshuler published in 2004"

Assessing the impact of population stratification on genetic association studies.

Abstract: Population stratification refers to differences in allele frequencies between cases and controls due to systematic differences in ancestry rather than association of genes with disease. It has been proposed that false positive associations due to stratification can be controlled by genotyping a few dozen unlinked genetic markers. To assess stratification empirically, we analyzed data from 11 case-control and case-cohort association studies. We did not detect statistically significant evidence for stratification but did observe that assessments based on a few dozen markers lack power to rule out moderate levels of stratification that could cause false positive associations in studies designed to detect modest genetic risk factors. After increasing the number of markers and samples in a case-cohort study (the design most immune to stratification), we found that stratification was in fact present. Our results suggest that modest amounts of stratification can exist even in well designed studies.

Errα and Gabpa/b specify PGC-1α-dependent oxidative phosphorylation gene expression that is altered in diabetic muscle

Abstract: Recent studies have shown that genes involved in oxidative phosphorylation (OXPHOS) exhibit reduced expression in skeletal muscle of diabetic and prediabetic humans. Moreover, these changes may be mediated by the transcriptional coactivator peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α). By combining PGC-1α-induced genome-wide transcriptional profiles with a computational strategy to detect cis-regulatory motifs, we identified estrogen-related receptor α (Errα) and GA repeat-binding protein α as key transcription factors regulating the OXPHOS pathway. Interestingly, the genes encoding these two transcription factors are themselves PGC-1α-inducible and contain variants of both motifs near their promoters. Cellular assays confirmed that Errα and GA-binding protein a partner with PGC-1α in muscle to form a double-positive-feedback loop that drives the expression of many OXPHOS genes. By using a synthetic inhibitor of Errα, we demonstrated its key role in PGC-1α-mediated effects on gene regulation and cellular respiration. These results illustrate the dissection of gene regulatory networks in a complex mammalian system, elucidate the mechanism of PGC-1α action in the OXPHOS pathway, and suggest that Errα agonists may ameliorate insulin-resistance in individuals with type 2 diabetes mellitus.

Methods for high-density admixture mapping of disease genes.

Abstract: Admixture mapping (also known as “mapping by admixture linkage disequilibrium,” or MALD) has been proposed as an efficient approach to localizing disease-causing variants that differ in frequency (because of either drift or selection) between two historically separated populations. Near a disease gene, patient populations descended from the recent mixing of two or more ethnic groups should have an increased probability of inheriting the alleles derived from the ethnic group that carries more disease-susceptibility alleles. The central attraction of admixture mapping is that, since gene flow has occurred recently in modern populations (e.g., in African and Hispanic Americans in the past 20 generations), it is expected that admixture-generated linkage disequilibrium should extend for many centimorgans. High-resolution marker sets are now becoming available to test this approach, but progress will require (a) computational methods to infer ancestral origin at each point in the genome and (b) empirical characterization of the general properties of linkage disequilibrium due to admixture. Here we describe statistical methods to estimate the ancestral origin of a locus on the basis of the composite genotypes of linked markers, and we show that this approach accurately estimates states of ancestral origin along the genome. We apply this approach to show that strong admixture linkage disequilibrium extends, on average, for 17 cM in African Americans. Finally, we present power calculations under varying models of disease risk, sample size, and proportions of ancestry. Studying ∼2,500 markers in ∼2,500 patients should provide power to detect many regions contributing to common disease. A particularly important result is that the power of an admixture mapping study to detect a locus will be nearly the same for a wide range of mixture scenarios: the mixture proportion should be 10%–90% from both ancestral populations.

A High-Density Admixture Map for Disease Gene Discovery in African Americans

Abstract: Admixture mapping (also known as “mapping by admixture linkage disequilibrium,” or MALD) provides a way of localizing genes that cause disease, in admixed ethnic groups such as African Americans, with ∼100 times fewer markers than are required for whole-genome haplotype scans. However, it has not been possible to perform powerful scans with admixture mapping because the method requires a dense map of validated markers known to have large frequency differences between Europeans and Africans. To create such a map, we screened through databases containing ∼450,000 single-nucleotide polymorphisms (SNPs) for which frequencies had been estimated in African and European population samples. We experimentally confirmed the frequencies of the most promising SNPs in a multiethnic panel of unrelated samples and identified 3,011 as a MALD map (1.2 cM average spacing).We estimate that this map is ∼70% informative in differentiating African versus European origins of chromosomal segments. This map provides a practical and powerful tool, which is freely available without restriction, for screening for disease genes in African American patient cohorts. The map is especially appropriate for those diseases that differ in incidence between the parental African and European populations.

Genome coverage and sequence fidelity of ϕ29 polymerase‐based multiple strand displacement whole genome amplification

Abstract: Major efforts are underway to systematically define the somatic and germline genetic variations causally associated with disease. Genome-wide genetic analysis of actual clinical samples is, however, limited by the paucity of genomic DNA available. Here we have tested the fidelity and genome representation of f29 polymerase-based genome amplification (f29MDA) using direct sequencing and high density oligonucleotide arrays probing >10 000 SNP alleles. Genome representation was comprehensive and estimated to be 99.82% complete, although six regions encompassing a maximum of 5.62 Mb failed to amplify. There was no degradation in the accuracy of SNP genotyping and, in direct sequencing experiments sampling 500 000 bp, the estimated error rate (9.5 3 10 ‐6 ) was the same as in paired unamplified samples. The detection of cancer-associated loss of heterozygosity and copy number changes, including homozygous deletion and gene amplification, were similarly robust. These results suggest that f29MDA yields high fidelity, near-complete genome representation suitable for high resolution genetic analysis.

The multiethnic cohort study: exploring genes, lifestyle and cancer risk

Abstract: The search for the causes of cancer and means of cancer prevention has entered a new era as recent developments allow correlation of environmental and behavioural exposures, genetic variation and patient outcomes. The Multiethnic Cohort Study was designed to take advantage of these advances to prospectively explore the roles of lifestyle and genetic susceptibility in the occurrence of cancer. The ethnic diversity of the cohort in this study provides a wide range of dietary exposures and genetic variation, thereby providing a unique dimension to this research.

Haplotype Structure and Genotype-Phenotype Correlations of the Sulfonylurea Receptor and the Islet ATP-Sensitive Potassium Channel Gene Region

Abstract: The genes for the sulfonylurea receptor (SUR1; encoded by ABCC8) and its associated islet ATP-sensitive potassium channel (Kir6.2; encoded by KCNJ11) are adjacent to one another on human chromosome 11. Multiple studies have reported association of the E23K variant of Kir6.2 with risk of type 2 diabetes. Whether and how E23K itself-or other variant(s) in either of these two closely linked genes-influences type 2 diabetes remains to be fully determined. To better understand genotype-phenotype correlation at this important candidate gene locus, we 1) characterized haplotype structures across the gene region by typing 77 working, high-frequency markers spanning 207 kb and both genes; 2) performed association studies of E23K and nearby markers in >3,400 patients (type 2 diabetes and control) not previously reported in the literature; and 3) analyzed the resulting data for measures of insulin secretion. These data independently replicate the association of E23K with type 2 diabetes with an odds ratio (OR) in the new data of 1.17 (P = 0.003) as compared with an OR of 1.14 provided by meta-analysis of previously published, nonoverlapping data (P = 0.0002). We find that the E23K variant in Kir6.2 demonstrates very strong allelic association with a coding variant (A1369S) in the neighboring SUR1 gene (r(2) > 0.9) across a range of population samples, making it difficult to distinguish which gene and polymorphism in this region are most likely responsible for the reported association. We show that E23K is also associated with decreased insulin secretion in glucose-tolerant control subjects, supporting a mechanism whereby beta-cell dysfunction contributes to the common form of type 2 diabetes. Like peroxisome proliferator-activated receptor gamma, the SUR1/Kir6.2 gene region both contributes to the inherited risk of type 2 diabetes and encodes proteins that are targets for hypoglycemic medications, providing an intriguing link between the underlying mechanism of disease and validated targets for pharmacological treatment.

Corticosteroid pharmacogenetics: association of sequence variants in CRHR1 with improved lung function in asthmatics treated with inhaled corticosteroids

Abstract: Corticosteroids mediate a variety of immunological actions and are commonly utilized in the treatment of a wide range of diseases. Unfortunately, therapy with this class of medications is associated with a large proportion of non-responders and significant side effects. Inhaled corticosteroids are the most commonly used asthma controller therapy. However, asthmatic response to corticosteroids also varies widely between individuals. We investigated the genetic contribution to the variation in response to inhaled corticosteroid therapy in asthma. The association of longitudinal change in lung function and single nucleotide polymorphisms from candidate genes crucial to the biologic actions of corticosteroids were evaluated in three independent asthmatic clinical trial populations utilizing inhaled corticosteroids as the primary therapy in at least one treatment arm. Variation in one gene, corticotropin-releasing hormone receptor 1 (CRHR1) was consistently associated with enhanced response to therapy in each of our three populations. Individuals homozygous for the variants of interest manifested a doubling to quadrupling of the lung function response to corticosteroids compared with lack of the variants (P-values ranging from 0.006 to 0.025 for our three asthmatic populations). As the primary receptor mediating the release of adrenocorticotropic hormone, which regulates endogenous cortisol levels, CRHR1 plays a pivotal, pleiotropic role in steroid biology. These data indicate that genetic variants in CRHR1 have pharmacogenetic effects influencing asthmatic response to corticosteroids, provide a rationale for predicting therapeutic response in asthma and other corticosteroid-treated diseases, and suggests this gene pathway as a potential novel therapeutic target.

Association testing in 9,000 people fails to confirm the association of the insulin receptor substrate-1 G972R polymorphism with type 2 diabetes

Abstract: The insulin receptor substrate (IRS)-1 is an important component of the insulin signal transduction cascade. Several reports suggest that a Gly→Arg change in codon 972 is associated with type 2 diabetes and related traits, and a recent meta-analysis reported a modest but nominally significant association with type 2 diabetes (odds ratio [OR] 1.25 in favor of carriers of the Arg allele [95% CI 1.05–1.48). To test the reproducibility of the model in a recent meta-analysis, we examined genotype-phenotype correlation in three large Caucasian samples (not previously reported for this variant) totaling 9,000 individuals (estimated to have >95% power to obtain a P P = 0.60). Genotype at G972R had no significant effect on various measures of insulin secretion or insulin resistance in a set of Scandinavian samples in whom we had detailed phenotypic data. In contrast, the well-documented associations of peroxisome proliferator-activated receptor γ P12A and Kir6.2 E23K with type 2 diabetes are both robustly observed in these 9,000 subjects, including an additional (previously unpublished) confirmation of Kir6.2 E23K and type 2 diabetes in the Polish and North American samples (combined OR 1.15 [1.05–1.26], P = 0.001). Despite genotyping 9,000 people and >95% power to reproduce the estimated OR from the recent meta-analysis, we were unable to replicate the association of the IRS-1 G972R polymorphism with type 2 diabetes.

Common variation in BRCA2 and breast cancer risk: a haplotype-based analysis in the Multiethnic Cohort

Abstract: It is well established that rare mutations in BRCA2 predispose to familial breast cancer, but whether common variants at this locus contribute more modest risk to sporadic breast cancer has not been thoroughly investigated. We performed a haplotype-based study of BRCA2 among women in the Multiethnic Cohort Study (MEC), genotyping 50 SNPs spanning 109.4 kb of the BRCA2 gene. Twenty-one haplotype-tagging SNPs (including seven missense SNPs) were selected to predict the common BRCA2 haplotypes and were genotyped in a breast cancer case-control study nested in the MEC (cases, n=1715; controls, n=2502). Compared to non-carriers, we observed nominally significant positive associations for homozygous carriers of specific haplotypes in blocks 2 (haplotype 2c: OR=1.50; 95% CI, 1.08-2.09) and 3 (haplotype 3d: OR=1.50; 95% CI, 1.01-2.24). These results could be explained on the basis of a single marker in intron 24 (SNP 42: rs206340) that was correlated with these haplotypes and the homozygous state was associated with a significantly increased risk of breast cancer (AA versus GG genotypes: OR=1.59, 95% CI, 1.18-2.16; nominal P=0.005). This association was modestly stronger among women with advanced disease (OR=2.00, 95% CI, 1.30-3.08; P=0.002). In this exploratory analysis, we found little indication that common variation in BRCA2 dramatically impacts sporadic breast cancer risk. However, a significant elevation in risk was observed among approximately 6% of women who carried a specific haplotype pattern and may harbor a susceptibility allele at the BRCA2 locus.

Methods Of Regulating Metabolism And Mitochondrial Function

Abstract: The invention relates to novel methods of regulating metabolism and mitochondrial biogenesis. Some aspects of the invention relate to methods of treating or preventing diseases in a patient associated with reduced mitochondrial function, to methods of identifying agents to treat such diseases, and to methods of diagnosing such diseases. Other aspects of the invention relate to a set of coordinately-regulated genes which regulate oxidative phosphorylation.

Statistical concerns about the GSEA procedure - Reply

Abstract: To the editor: Mootha et al.1 propose a statistical method (Gene Set Enrichment Analysis; GSEA) to discern changes in expression levels of sets of genes selected a priori in transcriptional profiling experiments. Although consideration of groups of genes is an interesting strategy, the proposed test statistic may not necessarily determine “...if the members of a given gene set are enriched among the most differentially expressed genes between two classes”1. Situations will probably arise when using GSEA in which genes with the highest values of the difference metric will be ignored solely due to the size of the selected gene sets, unrelated to any biological context of the genes comprising the set. By way of illustration, consider the following hypothetical example. Assume that a given data set consists of three potentially interesting sets of genes S1, S2 and S3, of respective sizes n, 5n and 4n genes, where n is any integer. Assume also that all of the genes in S1 are ranked higher (i.e., they have greater differences in expression) than the genes in S2, which in turn are ranked higher than the genes in S3. The GSEA procedure yields enrichment scores (ES)1 of 3n, 4n and 0 for S1, S2 and S3, respectively. The maximum ES1 is 4n and is attributed to S2. S2 will therefore be singled out as the candidate for further investigation over S1, even though S1 comprises the highest ranked genes. This does not seem reasonable, because S2 has been chosen only by virtue of containing a larger number of genes. In other words, GSEA can be at odds with the picture suggested by the gene ranking. A second observation, using the same illustrative example as above, gives another counterintuitive result. In the absence of a defined third gene set (S3), the ES for S2 = 0 and the ES for S1 remains positive. Therefore, S1, and not S2, is chosen by GSEA, a result opposite to that of the previous scenario. An unusual situation has arisen in which a choice or preference between sets of high ranking is affected simply by the presence or absence of a lower ranking set. The behavior of GSEA can not be dismissed as one of the usual power issues encountered due to noise in data, small sample size or lack of robustness to model assumptions. The simple example outlined here indicates that the power of the test statistic is sensitive to the a priori definition of the hypotheses of interest. These limitations should be clearly understood in applying and interpreting the results of the approach.

Organizational challenges in clinical genomic research

Abstract: Genome sequence data are enabling clinical genomic investigation, in which the characteristics of human patients are explored using comprehensive inventories of biomolecules. Successful investigators must navigate rapid technological change, collect and analyse large volumes of data, and engage systems of clinical care. Such projects will increasingly rely on fully integrated multidisciplinary teams, demanding new organizational models in academic biomedical research.

Procedes de regulation du metabolisme et de la fonction mitochondriale

Abstract: Cette invention concerne de nouveaux procedes permettant de reguler le metabolisme et la biogenese mitochondriale. Certains aspects de cette invention concernent des methodes de traitement ou de prevention de maladies chez un patient associees a une fonction mitochondriale alteree, des methodes d'identification d'agents servant a traiter ces maladies ainsi que des methodes de diagnostic de ces maladies. D'autres aspects de cette invention concernent un ensemble de genes regules de facon coordonnee qui regulent la phosphorylation oxydative.