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David Altshuler

Publications and source records attributed to David Altshuler.

At least 55 records · Page 3Linked to original sources
PubMed2004

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

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.

Aged↗
PubMed2004

Organizational challenges in clinical genomic research.

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.

Academies and Institutes↗
PubMed2004

Genome coverage and sequence fidelity of phi29 polymerase-based multiple strand displacement whole genome amplification.

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 phi29 polymerase-based genome amplification (phi29MDA) 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 x 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 phi29MDA yields high fidelity, near-complete genome representation suitable for high resolution genetic analysis.

Alleles↗
PubMed2004

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

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.

Administration, Inhalation↗
PubMed2004

Erralpha and Gabpa/b specify PGC-1alpha-dependent oxidative phosphorylation gene expression that is altered in diabetic muscle.

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 gamma coactivator-1alpha (PGC-1alpha). By combining PGC-1alpha-induced genome-wide transcriptional profiles with a computational strategy to detect cis-regulatory motifs, we identified estrogen-related receptor alpha (Erralpha) and GA repeat-binding protein alpha as key transcription factors regulating the OXPHOS pathway. Interestingly, the genes encoding these two transcription factors are themselves PGC-1alpha-inducible and contain variants of both motifs near their promoters. Cellular assays confirmed that Erralpha and GA-binding protein a partner with PGC-1alpha in muscle to form a double-positive-feedback loop that drives the expression of many OXPHOS genes. By using a synthetic inhibitor of Erralpha, we demonstrated its key role in PGC-1alpha-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-1alpha action in the OXPHOS pathway, and suggest that Erralpha agonists may ameliorate insulin-resistance in individuals with type 2 diabetes mellitus.

Animals↗
PubMed2004

A high-density admixture map for disease gene discovery in african americans.

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 approximately 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 approximately 450000 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 3011 as a MALD map (1.2 cM average spacing). We estimate that this map is approximately 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.

Black or African American↗
PubMed2004

Methods for high-density admixture mapping of disease genes.

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 approximately 2500 markers in approximately 2500 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.

Alleles↗
PubMed2004

Assessing the impact of population stratification on genetic association studies.

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.

Case-Control Studies↗
PubMed2004

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

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 < 0.05 for the OR of 1.25 estimated in the meta-analysis). In our combined sample, comprising 4,279 case and 3,532 control subjects, as well as 1,189 siblings discordant for type 2 diabetes, G972R was not associated with type 2 diabetes (OR 0.96 [0.84-1.10], 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 gamma 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.

Amino Acid Substitution↗
PubMed2004

Haplotype structure and genotype-phenotype correlations of the sulfonylurea receptor and the islet ATP-sensitive potassium channel gene region.

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.

ATP-Binding Cassette Transporters↗
PubMed2003

Human genome sequence variation and the search for genes influencing stroke.

BACKGROUND: Technological progress spurred by the Human Genome Project is accelerating the pace of genetic studies of common diseases, including stroke. Stroke clinicians will soon need to interpret increasingly complex genetic studies. SUMMARY OF REVIEW: Linkage analysis and epidemiological association are 2 fundamental methods of identifying gene variants affecting common diseases such as stroke. Combining these methods with advanced molecular genetic techniques, 3 recently published studies have made important contributions to the genetics of common vascular diseases: identification of the location of a gene for stroke on chromosome 5q12 and identification of gene variants that may increase risk of myocardial infarction. Driven by genomic technology, future studies will be increasingly comprehensive and systematic in their assessment of the contribution of genetics to the clinical course of stroke. The scale and complexity of such studies will require large-scale collaboration among stroke physicians, geneticists, and biostatisticians. CONCLUSIONS: Rapid improvements in technology and study design are likely to elucidate the role of inherited genetic variation in complex diseases such as stroke. Understanding the methods of population-based genetic investigation and the patterns of human genome variation will enable stroke physicians to follow these future developments.

Genetic Linkage↗
PubMed2003

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

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.

Adult↗
PubMed2003

Quality and completeness of SNP databases.

To address the quality and completeness of single-nucleotide polymorphism (SNP) databases, we resequenced 173 kb (spanning 17 loci) in 150 chromosomes of west African and European ancestry. Over 88% of SNPs in the public (TSC and BAC overlap) and Celera databases were confirmed in independent resequencing. Approximately 45% of all human heterozygosity is attributable to SNPs already available from the two databases, and of SNPs with minor-allele frequencies >10%, more than half are represented.

Alleles↗
PubMed2003

PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes.

DNA microarrays can be used to identify gene expression changes characteristic of human disease. This is challenging, however, when relevant differences are subtle at the level of individual genes. We introduce an analytical strategy, Gene Set Enrichment Analysis, designed to detect modest but coordinate changes in the expression of groups of functionally related genes. Using this approach, we identify a set of genes involved in oxidative phosphorylation whose expression is coordinately decreased in human diabetic muscle. Expression of these genes is high at sites of insulin-mediated glucose disposal, activated by PGC-1alpha and correlated with total-body aerobic capacity. Our results associate this gene set with clinically important variation in human metabolism and illustrate the value of pathway relationships in the analysis of genomic profiling experiments.

Animals↗
PubMed2003

The inherited basis of diabetes mellitus: implications for the genetic analysis of complex traits.

Diabetes encompasses a heterogeneous group of diseases, each with a substantial genetic component. We review the division of diabetes into different subtypes based on clinical phenotype, the fruitful pursuit of genes underlying monogenic forms of the disease, the successes and drawbacks of whole-genome linkage scans in type 1 and type 2 diabetes, and the recent identification of several diabetes genes by large association studies. We use the lessons learned from this extensive body of evidence to illustrate general implications for the genetic analysis of complex traits.

Diabetes Mellitus, Type 1↗
PubMed2003

Choosing haplotype-tagging SNPS based on unphased genotype data using a preliminary sample of unrelated subjects with an example from the Multiethnic Cohort Study.

We describe an approach for picking haplotype-tagging single nucleotide polymorphisms (htSNPs) that is presently being taken in two large nested case-control studies within a multiethnic cohort (MEC), which are engaged in a search for associations between risk of prostate and breast cancer and common genetic variations in candidate genes. Based on a preliminary sample of 70 control subjects chosen at random from each of the 5 ethnic groups in the MEC we estimate haplotype frequencies using a variant of the Excoffier-Slatkin E-M algorithm after genotyping a high density of SNPs selected every 3-5 kb in and surrounding a candidate gene. In order to evaluate the performance of a candidate set of htSNPS (which will be genotyped in the much larger case-control sample) we treat the haplotype frequencies estimate above as known, and carry out a formal calculation of the uncertainty of the number of copies of common haplotypes carried by an individual, summarizing this calculation as a coefficient of determination, R2h. A candidate set of htSNPS of a given size is chosen so as to maximize the minimum value of R2h over the common haplotypes, h.

Aromatase↗
PubMed2003

Modeling and E-M estimation of haplotype-specific relative risks from genotype data for a case-control study of unrelated individuals.

The US National Cancer Institute has recently sponsored the formation of a Cohort Consortium (http://2002.cancer.gov/scpgenes.htm) to facilitate the pooling of data on very large numbers of people, concerning the effects of genes and environment on cancer incidence. One likely goal of these efforts will be generate a large population-based case-control series for which a number of candidate genes will be investigated using SNP haplotype as well as genotype analysis. The goal of this paper is to outline the issues involved in choosing a method of estimating haplotype-specific risk estimates for such data that is technically appropriate and yet attractive to epidemiologists who are already comfortable with odds ratios and logistic regression. Our interest is to develop and evaluate extensions of methods, based on haplotype imputation, that have been recently described (Schaid et al., Am J Hum Genet, 2002, and Zaykin et al., Hum Hered, 2002) as providing score tests of the null hypothesis of no effect of SNP haplotypes upon risk, which may be used for more complex tasks, such as providing confidence intervals, and tests of equivalence of haplotype-specific risks in two or more separate populations. In order to do so we (1) develop a cohort approach towards odds ratio analysis by expanding the E-M algorithm to provide maximum likelihood estimates of haplotype-specific odds ratios as well as genotype frequencies; (2) show how to correct the cohort approach, to give essentially unbiased estimates for population-based or nested case-control studies by incorporating the probability of selection as a case or control into the likelihood, based on a simplified model of case and control selection, and (3) finally, in an example data set (CYP17 and breast cancer, from the Multiethnic Cohort Study) we compare likelihood-based confidence interval estimates from the two methods with each other, and with the use of the single-imputation approach of Zaykin et al. applied under both null and alternative hypotheses. We conclude that so long as haplotypes are well predicted by SNP genotypes (we use the Rh2 criteria of Stram et al. [1]) the differences between the three methods are very small and in particular that the single imputation method may be expected to work extremely well.

Algorithms↗