Showing papers by "David Altshuler published in 2005"

A haplotype map of the human genome

Abstract: Inherited genetic variation has a critical but as yet largely uncharacterized role in human disease. Here we report a public database of common variation in the human genome: more than one million single nucleotide polymorphisms (SNPs) for which accurate and complete genotypes have been obtained in 269 DNA samples from four populations, including ten 500-kilobase regions in which essentially all information about common DNA variation has been extracted. These data document the generality of recombination hotspots, a block-like structure of linkage disequilibrium and low haplotype diversity, leading to substantial correlations of SNPs with many of their neighbours. We show how the HapMap resource can guide the design and analysis of genetic association studies, shed light on structural variation and recombination, and identify loci that may have been subject to natural selection during human evolution.

Efficiency and power in genetic association studies

Abstract: We investigated selection and analysis of tag SNPs for genome-wide association studies by specifically examining the relationship between investment in genotyping and statistical power. Do pairwise or multimarker methods maximize efficiency and power? To what extent is power compromised when tags are selected from an incomplete resource such as HapMap? We addressed these questions using genotype data from the HapMap ENCODE project, association studies simulated under a realistic disease model, and empirical correction for multiple hypothesis testing. We demonstrate a haplotype-based tagging method that uniformly outperforms single-marker tests and methods for prioritization that markedly increase tagging efficiency. Examining all observed haplotypes for association, rather than just those that are proxies for known SNPs, increases power to detect rare causal alleles, at the cost of reduced power to detect common causal alleles. Power is robust to the completeness of the reference panel from which tags are selected. These findings have implications for prioritizing tag SNPs and interpreting association studies.

Calibrating a coalescent simulation of human genome sequence variation

Abstract: Population genetic models play an important role in human genetic research, connecting empirical observations about sequence variation with hypotheses about underlying historical and biological causes. More specifically, models are used to compare empirical measures of sequence variation, linkage disequilibrium (LD), and selection to expectations under a "null" distribution. In the absence of detailed information about human demographic history, and about variation in mutation and recombination rates, simulations have of necessity used arbitrary models, usually simple ones. With the advent of large empirical data sets, it is now possible to calibrate population genetic models with genome-wide data, permitting for the first time the generation of data that are consistent with empirical data across a wide range of characteristics. We present here the first such calibrated model and show that, while still arbitrary, it successfully generates simulated data (for three populations) that closely resemble empirical data in allele frequency, linkage disequilibrium, and population differentiation. No assertion is made about the accuracy of the proposed historical and recombination model, but its ability to generate realistic data meets a long-standing need among geneticists. We anticipate that this model, for which software is publicly available, and others like it will have numerous applications in empirical studies of human genetics.

Replication of putative candidate-gene associations with rheumatoid arthritis in >4,000 samples from North America and Sweden: association of susceptibility with PTPN22, CTLA4, and PADI4.

Abstract: Candidate-gene association studies in rheumatoid arthritis (RA) have lead to encouraging yet apparently inconsistent results. One explanation for the inconsistency is insufficient power to detect modest effects in the context of a low prior probability of a true effect. To overcome this limitation, we selected alleles with an increased probability of a disease association, on the basis of a review of the literature on RA and other autoimmune diseases, and tested them for association with RA susceptibility in a sample collection powered to detect modest genetic effects. We tested 17 alleles from 14 genes in 2,370 RA cases and 1,757 controls from the North American Rheumatoid Arthritis Consortium (NARAC) and the Swedish Epidemiological Investigation of Rheumatoid Arthritis (EIRA) collections. We found strong evidence of an association of PTPN22 with the development of anti-citrulline antibody–positive RA (odds ratio [OR] 1.49; P=.00002), using previously untested EIRA samples. We provide support for an association of CTLA4 (CT60 allele, OR 1.23; P=.001) and PADI4 (PADI4_94, OR 1.24; P=.001) with the development of RA, but only in the NARAC cohort. The CTLA4 association is stronger in patients with RA from both cohorts who are seropositive for anti-citrulline antibodies (P=.0006). Exploration of our data set with clinically relevant subsets of RA reveals that PTPN22 is associated with an earlier age at disease onset (P=.004) and that PTPN22 has a stronger effect in males than in females (P=.03). A meta-analysis failed to demonstrate an association of the remaining alleles with RA susceptibility, suggesting that the previously published associations may represent false-positive results. Given the strong statistical power to replicate a true-positive association in this study, our results provide support for PTPN22, CTLA4, and PADI4 as RA susceptibility genes and demonstrate novel associations with clinically relevant subsets of RA.

Demonstrating stratification in a European American population.

Abstract: Population stratification occurs in case-control association studies when allele frequencies differ between cases and controls because of ancestry. Stratification may lead to false positive associations, although this issue remains controversial. Empirical studies have found little evidence of stratification in European-derived populations, but potentially significant levels of stratification could not be ruled out. We studied a European American panel discordant for height, a heritable trait that varies widely across Europe. Genotyping 178 SNPs and applying standard analytical methods yielded no evidence of stratification. But a SNP in the gene LCT that varies widely in frequency across Europe was strongly associated with height (P < 10(-6)). This apparent association was largely or completely due to stratification; rematching individuals on the basis of European ancestry greatly reduced the apparent association, and no association was observed in Polish or Scandinavian individuals. The failure of standard methods to detect this stratification indicates that new methods may be required.

Comparison of Fine-Scale Recombination Rates in Humans and Chimpanzees

Abstract: We compared fine-scale recombination rates at orthologous loci in humans and chimpanzees by analyzing polymorphism data in both species. Strong statistical evidence for hotspots of recombination was obtained in both species. Despite ∼99% identity at the level of DNA sequence, however, recombination hotspots were found rarely (if at all) at the same positions in the two species, and no correlation was observed in estimates of fine-scale recombination rates. Thus, local patterns of recombination rate have evolved rapidly, in a manner disproportionate to the change in DNA sequence.

The Case for Selection at CCR5-Δ32

Abstract: The C-C chemokine receptor 5, 32 base-pair deletion (CCR5-D32) allele confers strong resistance to infection by the AIDS virus HIV. Previous studies have suggested that CCR5-D32 arose within the past 1,000 y and rose to its present high frequency (5%–14%) in Europe as a result of strong positive selection, perhaps by such selective agents as the bubonic plague or smallpox during the Middle Ages. This hypothesis was based on several lines of evidence, including the absence of the allele outside of Europe and long-range linkage disequilibrium at the locus. We reevaluated this evidence with the benefit of much denser genetic maps and extensive control data. We find that the pattern of genetic variation at CCR5-D32 does not stand out as exceptional relative to other loci across the genome. Moreover using newer genetic maps, we estimated that the CCR5-D32 allele is likely to have arisen more than 5,000 y ago. While such results can not rule out the possibility that some selection may have occurred at C-C chemokine receptor 5 (CCR5), they imply that the pattern of genetic variation seen at CCR5-D32 is consistent with neutral evolution. More broadly, the results have general implications for the design of future studies to detect the signs of positive selection in the human genome.

The Case for Selection at CCR5-Δ32

Abstract: The C-C chemokine receptor 5, 32 base-pair deletion (CCR5-Δ32) allele confers strong resistance to infection by the AIDS virus HIV. Previous studies have suggested that CCR5-Δ32 arose within the past 1,000 y and rose to its present high frequency (5%–14%) in Europe as a result of strong positive selection, perhaps by such selective agents as the bubonic plague or smallpox during the Middle Ages. This hypothesis was based on several lines of evidence, including the absence of the allele outside of Europe and long-range linkage disequilibrium at the locus. We reevaluated this evidence with the benefit of much denser genetic maps and extensive control data. We find that the pattern of genetic variation at CCR5-Δ32 does not stand out as exceptional relative to other loci across the genome. Moreover using newer genetic maps, we estimated that the CCR5-Δ32 allele is likely to have arisen more than 5,000 y ago. While such results can not rule out the possibility that some selection may have occurred at C-C chemokine receptor 5 (CCR5), they imply that the pattern of genetic variation seen atCCR5-Δ32 is consistent with neutral evolution. More broadly, the results have general implications for the design of future studies to detect the signs of positive selection in the human genome.

A candidate gene approach to searching for low-penetrance breast and prostate cancer genes.

Abstract: Most cases of breast and prostate cancer are not associated with mutations in known high-penetrance genes, indicating the involvement of multiple low-penetrance risk alleles. Studies that have attempted to identify these genes have met with limited success. The National Cancer Institute Breast and Prostate Cancer Cohort Consortium--a pooled analysis of multiple large cohort studies with a total of more than 5,000 cases of breast cancer and 8,000 cases of prostate cancer--was therefore initiated. The goal of this consortium is to characterize variations in approximately 50 genes that mediate two pathways that are associated with these cancers--the steroid-hormone metabolism pathway and the insulin-like growth factor signalling pathway--and to associate these variations with cancer risk.

Systematic evaluation of genetic variation at the androgen receptor locus and risk of prostate cancer in a multiethnic cohort study.

Abstract: Repeat length of the CAG microsatellite polymorphism in exon 1 of the androgen receptor (AR) gene has been associated with risk of prostate cancer in humans. This association has been the focus of >20 primary epidemiological publications and multiple review articles, but a consistent and reproducible association has yet to be confirmed. We systematically addressed possible causes of false-negative and false-positive association in >4,000 individuals from a multiethnic, prospective cohort study of prostate cancer, comprehensively studying genetic variation by microsatellite genotyping, direct resequencing of exons in advanced cancer cases, and haplotype analysis across the 180-kb AR genomic locus. These data failed to confirm that common genetic variation in the AR gene locus influences risk of prostate cancer. A systematic approach that assesses both coding and noncoding genetic variation in large and diverse patient samples can help clarify hypotheses about association between genetic variants and disease.

Association Testing of Variants in the Hepatocyte Nuclear Factor 4α Gene With Risk of Type 2 Diabetes in 7,883 People

Abstract: Two recent publications reported association of common polymorphisms in the P2 promoter of hepatocyte nuclear factor 4α (HNF4α) (the MODY1 gene) with risk for type 2 diabetes. We attempted to reproduce this putative association by genotyping 11 single nucleotide polymorphism (SNPs) spanning the HNF4α coding region and the P2 promoter in >3,400 patients and control subjects from Sweden, Finland, and Canada. One SNP that was consistently associated in the two previous reports (rs1884613, in the P2 promoter region) also trended in the same direction in our sample, albeit with a lower estimated odds ratio (OR) of 1.11 ( P = 0.05, one-tailed). We genotyped this SNP (rs1884613) in an additional 4,400 subjects from North America and Poland. In this sample, the association was not confirmed and trended in the opposite direction (OR 0.88). Meta-analysis of our combined sample of 7,883 people (three times larger than the two initial reports combined) yielded an OR of 0.97 ( P = 0.27). Finally, we provide an updated analysis of haplotype structure in the region to guide any further investigation of common variation in HNF4α. Although our combined results fail to replicate the previously reported association of common variants in HNF4α with risk for type 2 diabetes, we cannot exclude an effect smaller than that originally proposed, heterogeneity among samples, variation in as-yet-unmeasured genotypic or environmental modifiers, or true association secondary to linkage disequilibrium (LD) with as-yet-undiscovered variant(s) in the region.

Association of Common Variation in the HNF1α Gene Region With Risk of Type 2 Diabetes

Abstract: It is currently unclear how often genes that are mutated to cause rare, early-onset monogenic forms of disease also harbor common variants that contribute to the more typical polygenic form of each disease. The gene for MODY3 diabetes, HNF1alpha, lies in a region that has shown linkage to late-onset type 2 diabetes (12q24, NIDDM2), and previous association studies have suggested a weak trend toward association for common missense variants in HNF1alpha with glucose-related traits. Based on genotyping of 79 common SNPs in the 118 kb spanning HNF1alpha, we selected 21 haplotype tag single nucleotide polymorphisms (SNPs) and genotyped them in >4,000 diabetic patients and control subjects from Sweden, Finland, and Canada. Several SNPs from the coding region and 5' of the gene demonstrated nominal association with type 2 diabetes, with the most significant marker (rs1920792) having an odds ratio of 1.17 and a P value of 0.002. We then genotyped three SNPs with the strongest evidence for association to type 2 diabetes (rs1920792, I27L, and A98V) in an additional 4,400 type 2 diabetic and control subjects from North America and Poland and compared our results with those of the original sample and of Weedon et al. None of the results were consistently observed across all samples, with the possible exception of a modest association of the rare (3-5%) A98V variant. These results indicate that common variants in HNF1alpha either play no role in type 2 diabetes, a very small role, or a role that cannot be consistently observed without consideration of as yet unmeasured genetic or environmental modifiers.

Clarifying the PROGINS Allele Association in Ovarian and Breast Cancer Risk: A Haplotype-Based Analysis

Abstract: Background: The PROGINS allele of the progesterone receptor (PGR) gene has been associated with an increased risk of ovarian cancer and a decreased risk of breast cancer. We set out to refine the association between common variation at the PGR gene locus and these two diseases. Methods: We characterized the haplotype structure of the PGR gene by genotyping 54 single-nucleotide polymorphisms (SNPs) in 349 women. We then selected a subset of 17 haplotypetagging SNPs that captured variation across the locus and typed them in 267 ovarian cancer case patients and 397 control subjects from two case‐control studies and in 1715 breast cancer case patients and 2505 control subjects from a cohort study. Results: The PGR locus was characterized by four blocks of strong linkage disequilibrium. Two SNPs in block 4 were associated with an increased risk of ovarian cancer among homozygous carriers as compared with noncarriers: rs1042838 (PROGINS allele; odds ratio [OR] 3.23, 95% confidence interval [CI] 1.19 to 8.75, P .022) and rs608995 (minor allele; OR 3.10, 95% CI 1.63 to 5.89, P<.001). The PROGINS allele was observed on a subset of chromosomes carrying the minor allele at rs608995, and its association with ovarian cancer was fully explained by its association with rs608995. In addition, rs608995 fell on two common haplotypes (4-D and 4-E), whose association with ovarian cancer was the same as that of rs608995. These same two haplotypes were associated with a non‐statistically significantly reduced risk of breast cancer. Conclusions: Variation in PGR was associated with ovarian cancer risk, although the strongest result was not with the PROGINS allele. Instead, any causal allele(s) are likely in or downstream of block 4 and carried on haplotypes 4-D and 4-E. There was some evidence that the same variation was associated with a reduced risk of breast cancer, but the association was not statistically significant. [J Natl Cancer Inst

Genetic Variation in the HSD17B1 Gene and Risk of Prostate Cancer

Abstract: Steroid hormones are believed to play an important role in prostate carcinogenesis, but epidemiological evidence linking prostate cancer and steroid hormone genes has been inconclusive, in part due to small sample sizes or incomplete characterization of genetic variation at the locus of interest. Here we report on the results of a comprehensive study of the association between HSD17B1 and prostate cancer by the Breast and Prostate Cancer Cohort Consortium, a large collaborative study. HSD17B1 encodes 17β-hydroxysteroid dehydrogenase 1, an enzyme that converts dihydroepiandrosterone to the testosterone precursor Δ5-androsterone-3β,17β-diol and converts estrone to estradiol. The Breast and Prostate Cancer Cohort Consortium researchers systematically characterized variation in HSD17B1 by targeted resequencing and dense genotyping; selected haplotype-tagging single nucleotide polymorphisms (htSNPs) that efficiently predict common variants in U.S. and European whites, Latinos, Japanese Americans, and Native Hawaiians; and genotyped these htSNPs in 8,290 prostate cancer cases and 9,367 study-, age-, and ethnicity-matched controls. We found no evidence that HSD17B1 htSNPs (including the nonsynonymous coding SNP S312G) or htSNP haplotypes were associated with risk of prostate cancer or tumor stage in the pooled multiethnic sample or in U.S. and European whites. Analyses stratified by age, body mass index, and family history of disease found no subgroup-specific associations between these HSD17B1 htSNPs and prostate cancer. We found significant evidence of heterogeneity in associations between HSD17B1 haplotypes and prostate cancer across ethnicity: one haplotype had a significant (p < 0.002) inverse association with risk of prostate cancer in Latinos and Japanese Americans but showed no evidence of association in African Americans, Native Hawaiians, or whites. However, the smaller numbers of Latinos and Japanese Americans in this study makes these subgroup analyses less reliable. These results suggest that the germline variants in HSD17B1 characterized by these htSNPs do not substantially influence the risk of prostate cancer in U.S. and European whites.

A Haplotype-Based Case-Control Study of BRCA1 and Sporadic Breast Cancer Risk

Abstract: Rare, highly penetrant germ line mutations in BRCA1 strongly predispose women to a familial form of breast and ovarian cancer. Whether common variants (either coding or noncoding) at this locus contribute to the more common form of the disease is not yet known. We tested common variation across the BRCA1 locus in African American, Native Hawaiian, Japanese, Latino, and White women in the Multiethnic Cohort Study. Specifically, 28 single nucleotide polymorphisms (SNPs) spanning the BRCA1 gene were used to define patterns of common variation in these populations. The majority of SNPs were in strong linkage disequilibrium with one another, indicating that our survey captured most of the common inherited variation across this gene. Nine tagging SNPs, including five missense SNPs, were selected to predict the common BRCA1 variants and haplotypes among the non-African American groups (five additional SNPs were required for African Americans) and genotyped in a breast cancer case-control study nested in the Multiethnic Cohort Study (cases, n = 1,715; controls, n = 2,502). We found no evidence for significant associations between common variation in BRCA1 and risk of breast cancer. Given the large size of our study population and detailed analysis of the locus, this result indicates either that common variants in BRCA1 do not substantially influence sporadic breast cancer risk, or that unmeasured heterogeneity in the breast cancer phenotype or unmeasured interactions with genetic or environmental exposures obscure our ability to detect any influence that may be present.

Association Testing of the Protein Tyrosine Phosphatase 1B Gene (PTPN1) With Type 2 Diabetes in 7,883 People

Abstract: Protein tyrosine phosphatase (PTP)-1B, encoded by the PTPN1 gene, inactivates the insulin signal transduction cascade by dephosphorylating phosphotyrosine residues in insulin signaling molecules. Due to its chromosomal location under a chromosome 20 linkage peak and the metabolic effects of its absence in knockout mice, it is a candidate gene for type 2 diabetes. Recent studies have associated common sequence variants in PTPN1 with type 2 diabetes and diabetes-related phenotypes. We sought to replicate the association of common single nucleotide polymorphisms (SNPs) and haplotypes in PTPN1 with type 2 diabetes, fasting plasma glucose, and insulin sensitivity in a large collection of subjects. We assessed linkage disequilibrium, selected tag SNPs, and typed these markers in 3,347 cases of type 2 diabetes and 3,347 control subjects as well as 1,189 siblings discordant for type 2 diabetes. Despite power estimated at >95% to replicate the previously reported associations, no statistically significant evidence of association was observed between PTPN1 SNPs or common haplotypes with type 2 diabetes or with diabetic phenotypes.

MEF2A sequence variants and coronary artery disease: a change of heart?

Abstract: Rare mutations in MEF2A have been proposed as a cause of coronary artery disease (CAD) and myocardial infarction (MI). In this issue of the JCI, Pennacchio and colleagues report sequencing MEF2A in 300 patients with premature CAD and in controls. Only 1 CAD patient was found to carry a missense mutation not found in controls. The specific 21-bp deletion in MEF2A previously proposed as causal for CAD and/or MI was observed in unaffected individuals and did not segregate with CAD in families. These results do not support the hypothesis that mutations in MEF2A are a cause of CAD and/or MI but do illustrate general principles regarding the difficulty of connecting genetic variation to common diseases.

Transferability of Tag SNPs to Capture Common Genetic Variation in DNA Repair Genes Across Multiple Populations

Abstract: Genetic association studies can be made more cost-effective by exploiting linkage disequilibrium patterns between nearby single-nucleotide polymorphisms (SNPs). The International HapMap Project now offers a dense SNP map across the human genome in four population samples. One question is how well tag SNPs chosen from a resource like HapMap can capture common variation in independent disease samples. To address the issue of tag SNP transferability, we genotyped 2,783 SNPs across 61 genes (with a total span of 6 Mb) involved in DNA repair in 466 individuals from multiple populations. We picked tag SNPs in samples with European ancestry from the Centre d'Etude du Polymorphisme Humain, and evaluated coverage of common variation in the other samples. Our comparative analysis shows that common variation in non-African samples can be captured robustly with only marginal loss in terms of the maximum r2. We also evaluated the transferability of specified multi-marker haplotypes as predictors for untyped SNPs, and demonstrate that they provide equivalent coverage compared to single-marker tests (pairwise tags) while requiring fewer SNPs for genotyping. The efficacy of a tagging-based approach in studying genotype-phenotype correlations in complex traits is strongly supported by our empirical results.

Harvesting Medical Information from the Human Family Tree

Abstract: Working with 71 individuals from three diverse human populations, [ Hinds et al .][1] have characterized more than 1.5 million individual differences in human DNA sequences. In a Perspective, [Altshuler and Clark][2] discuss the significance of these findings, their correlation with data from the International Haplotype Map Project, and what both data sets mean for understanding complex human diseases caused by multiple factors. [1]: http://www.sciencemag.org/cgi/content/short/307/5712/1072 [2]: http://www.sciencemag.org/cgi/content/full/307/5712/1052

Response to Wang et al.

Abstract: We appreciate the opportunity to correct a typographical error in our commentary (1) “MEF2A sequence variants and coronary heart disease: a change of heart?”. Specifically, the number of nonsynonymous changes found in controls should have read “1 in 500,” not “0 in 500” as in our published article. (This is because the 21-nt deletion was seen in controls.) Based on the then-available counts (5/500 in cases and 1/500 in controls), the 2-tailed P value we provided (P > 0.2) is correct. The accompanying letter from Weng et al. adds to and clarifies their recent study (2), providing more detailed information about ascertainment of variants in cases and controls. First, all exons were resequenced in cases, but only certain exons were resequenced in controls. Second, several additional missense changes were identified in both cases and controls. Taking these data into account, it appears that there have been 7 missense changes identified in cases and 5 in controls, including 3 found uniquely in cases, 1 found uniquely in controls, and 4 found in both groups. Moreover, the incomplete ascertainment in controls by Weng et al. (2) means that the current estimate of the frequency of MEF2A missense mutations in controls is a lower bound; additional missense changes in controls (which might have been found by more complete resequencing) would shift the combined data in the direction away from association between MEF2A variation and cardiac disease. Finally, we note that the major prevailing bias in the association literature is publication bias; that is, there is a greater likelihood that positive claims of association will be published as compared with studies that provide no evidence of association (3). Counteracting this bias requires that we encourage the publication and dispassionate evaluation of all relevant data, whether or not the data support an association.