Genome-wide Statistical Significance Research Articles

Next-Generation Genome-Wide Association Studies

As investigators plan the next round of genome-wide association studies (GWAS), cohorts of more than 100 000 individuals are being proposed as the solution to the “missing heritability” from first-generation studies.1–6 Although such studies will undoubtedly reveal many additional common alleles contributing to human disease, consideration of the intrinsic design of GWAS, our knowledge of the genetic architecture of disease and the results of GWAS to date suggests that complementary strategies will be necessary to uncover all of the heritability. ### First-Generation GWAS The outcomes of GWAS to date were largely anticipated.1 By design, the approach offers an unbiased assessment of the role of common alleles in disease syndromes, and there are numerous examples of successful GWAS in which multiple loci have been unequivocally associated with specific diseases. Even in genetically heterogeneous syndromes with major mendelian contributions, shared common alleles that operate downstream to affect trait expression may be detectable.7,8 In less heritable traits, GWAS may offer the only evidence of any genetic contribution. Many of the most successful studies to date have explained only a proportion of the heritability, whereas for some key disease phenotypes no loci have been identified that achieve genome-wide statistical significance.3,7–9 Serendipitous identification of large-effect size common alleles has occurred, but these may represent common modifiers of multiple mendelian genes, genes with large interactions with environmental factors or simply very homogeneous phenotypes.10,11 Article see p 359 Although the “small effect” alleles identified in GWAS may be important at a population level, a rigorous understanding of the role of such contributions will require much more comprehensive definition the genetic architecture for each trait. Epistatic interactions among common alleles, or between common …

Comprehensive field synopsis and systematic meta-analyses of genetic association studies in cutaneous melanoma.

Although genetic studies have reported a number of loci associated with cutaneous melanoma (CM) risk, a comprehensive synopsis of genetic association studies published in the field and systematic meta-analysis for all eligible polymorphisms have not been reported. We systematically annotated data from all genetic association studies published in the CM field (n = 145), including data from genome-wide association studies (GWAS), and performed random-effects meta-analyses across all eligible polymorphisms on the basis of four or more independent case-control datasets in the main analyses. Supplementary analyses of three available datasets derived from GWAS and GWAS-replication studies were also done. Nominally statistically significant associations between polymorphisms and CM were graded for the strength of epidemiological evidence on the basis of the Human Genome Epidemiology Network Venice criteria. All statistical tests were two-sided. Forty-two polymorphisms across 18 independent loci evaluated in four or more datasets including candidate gene studies and available GWAS data were subjected to meta-analysis. Eight loci were identified in the main meta-analyses as being associated with a risk of CM (P < .05) of which four loci showed a genome-wide statistically significant association (P < 1 × 10(-7)), including 16q24.3 (MC1R), 20q11.22 (MYH7B/PIGU/ASIP), 11q14.3 (TYR), and 5p13.2 (SLC45A2). Grading of the cumulative evidence by the Venice criteria suggested strong epidemiological credibility for all four loci with genome-wide statistical significance and one additional gene at 9p23 (TYRP1). In the supplementary meta-analyses, a locus at 9p21.3 (CDKN2A/MTAP) reached genome-wide statistical significance with CM and had strong epidemiological credibility. To the best of our knowledge, this is the first comprehensive field synopsis and systematic meta-analysis to identify genes associated with an increased susceptibility to CM.

Significance analysis and statistical dissection of variably methylated regions

It has recently been proposed that variation in DNA methylation at specific genomic locations may play an important role in the development of complex diseases such as cancer. Here, we develop 1- and 2-group multiple testing procedures for identifying and quantifying regions of DNA methylation variability. Our method is the first genome-wide statistical significance calculation for increased or differential variability, as opposed to the traditional approach of testing for mean changes. We apply these procedures to genome-wide methylation data obtained from biological and technical replicates and provide the first statistical proof that variably methylated regions exist and are due to interindividual variation. We also show that differentially variable regions in colon tumor and normal tissue show enrichment of genes regulating gene expression, cell morphogenesis, and development, supporting a biological role for DNA methylation variability in cancer.

Meta-analysis of genome-wide linkage scans for renal function traits

Several genome scans have explored the linkage of chronic kidney disease phenotypes to chromosomic regions with disparate results. Genome scan meta-analysis (GSMA) is a quantitative method to synthesize linkage results from independent studies and assess their concordance. We searched PubMed to identify genome linkage analyses of renal function traits in humans, such as estimated glomerular filtration rate (GFR), albuminuria, serum creatinine concentration and creatinine clearance. We contacted authors for numerical data and extracted information from individual studies. We applied the GSMA nonparametric approach to combine results across 14 linkage studies for GFR, 11 linkage studies for albumin creatinine ratio, 11 linkage studies for serum creatinine and 4 linkage studies for creatinine clearance. No chromosomal region reached genome-wide statistical significance in the main analysis which included all scans under each phenotype; however, regions on Chromosomes 7, 10 and 16 reached suggestive significance for linkage to two or more phenotypes. Subgroup analyses by disease status or ethnicity did not yield additional information. While heterogeneity across populations, methodologies and study designs likely explain this lack of agreement, it is possible that linkage scan methodologies lack the resolution for investigating complex traits. Combining family-based linkage studies with genome-wide association studies may be a powerful approach to detect private mutations contributing to complex renal phenotypes.

Abstract LB-441: The genome wide gene-environment interaction analysis for asbestos exposure on lung cancer susceptibility

Abstract Asbestos exposure is a known risk factor for lung cancer. Although recent genome wide association studies (GWAS) have identified a few novel loci for lung cancer risk, little is known about genome wide gene-environment interactions and lung cancer risk. To determine genetic variations involved in the interactions of gene-asbestos exposure on lung cancer risk, we conducted genome wide gene-environment interaction analyses at levels of single nucleotide polymorphisms (SNPs), genes and pathways, using the Texas lung cancer GWAS dataset. This dataset included 307,870 SNPs from 1,154 lung cancer cases and 1,137 cancer-free controls. The initial SNP-level p values for interactions between genetic variants and self-reported asbestos exposure were estimated by unconditional logistic regression models adjusted for age, sex, smoking status and pack-years. The p value for the most significant SNP rs12706823 was 1.37 × 10–4 and did not reach the genome-wide statistical significance. Using a versatile gene-based test approach to estimate the interactions at the gene level, we found the top significant gene was RNF121and was located on 11q13.4 (p value = 4 × 10–4). Interestingly, most of the genes with top significant p values were located in 11q13. When we used an improved gene set enrichment analysis approach (i-GSEA), however, we found a total of 249 pathways containing 16,079 genes, of which the Fas signaling pathway was the most significant pathway, significantly involved in the interactions between genetic variations and self-reported asbestos exposure (nominal p value &amp;lt; 0.001; false discovery rate (FDR) &amp;lt; 0.05). We believe our analysis is the first to comprehensively describe the genome wide gene-asbestos exposure interaction on lung cancer risk at the levels of SNPs, genes and pathways. Our findings suggested that the current designed GWAS may have a limited power to detect gene-environment interactions at the SNP or gene levels, but the pathway-based approach may be more powerful in performing genome wide gene-environment analyses. (This study was supported by NIH grants R01 ES 11740, R01CA 131274, R01CA055769, R01CA127219, R01CA121197 and P30CA016672) Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr LB-441. doi:10.1158/1538-7445.AM2011-LB-441

Genome-wide association study identifies genetic loci associated with iron deficiency.

The existence of multiple inherited disorders of iron metabolism in man, rodents and other vertebrates suggests genetic contributions to iron deficiency. To identify new genomic locations associated with iron deficiency, a genome-wide association study (GWAS) was performed using DNA collected from white men aged ≥25 y and women ≥50 y in the Hemochromatosis and Iron Overload Screening (HEIRS) Study with serum ferritin (SF) ≤ 12 µg/L (cases) and iron replete controls (SF>100 µg/L in men, SF>50 µg/L in women). Regression analysis was used to examine the association between case-control status (336 cases, 343 controls) and quantitative serum iron measures and 331,060 single nucleotide polymorphism (SNP) genotypes, with replication analyses performed in a sample of 71 cases and 161 controls from a population of white male and female veterans screened at a US Veterans Affairs (VA) medical center. Five SNPs identified in the GWAS met genome-wide statistical significance for association with at least one iron measure, rs2698530 on chr. 2p14; rs3811647 on chr. 3q22, a known SNP in the transferrin (TF) gene region; rs1800562 on chr. 6p22, the C282Y mutation in the HFE gene; rs7787204 on chr. 7p21; and rs987710 on chr. 22q11 (GWAS observed P<1.51×10−7 for all). An association between total iron binding capacity and SNP rs3811647 in the TF gene (GWAS observed P = 7.0×10−9, corrected P = 0.012) was replicated within the VA samples (observed P = 0.012). Associations with the C282Y mutation in the HFE gene also were replicated. The joint analysis of the HEIRS and VA samples revealed strong associations between rs2698530 on chr. 2p14 and iron status outcomes. These results confirm a previously-described TF polymorphism and implicate one potential new locus as a target for gene identification.

Updated Genetic Score Based on 34 Confirmed Type 2 Diabetes Loci Is Associated With Diabetes Incidence and Regression to Normoglycemia in the Diabetes Prevention Program

OBJECTIVEOver 30 loci have been associated with risk of type 2 diabetes at genome-wide statistical significance. Genetic risk scores (GRSs) developed from these loci predict diabetes in the general population. We tested if a GRS based on an updated list of 34 type 2 diabetes–associated loci predicted progression to diabetes or regression toward normal glucose regulation (NGR) in the Diabetes Prevention Program (DPP).RESEARCH DESIGN AND METHODSWe genotyped 34 type 2 diabetes–associated variants in 2,843 DPP participants at high risk of type 2 diabetes from five ethnic groups representative of the U.S. population, who had been randomized to placebo, metformin, or lifestyle intervention. We built a GRS by weighting each risk allele by its reported effect size on type 2 diabetes risk and summing these values. We tested its ability to predict diabetes incidence or regression to NGR in models adjusted for age, sex, ethnicity, waist circumference, and treatment assignment.RESULTSIn multivariate-adjusted models, the GRS was significantly associated with increased risk of progression to diabetes (hazard ratio [HR] = 1.02 per risk allele [95% CI 1.00–1.05]; P = 0.03) and a lower probability of regression to NGR (HR = 0.95 per risk allele [95% CI 0.93–0.98]; P < 0.0001). At baseline, a higher GRS was associated with a lower insulinogenic index (P < 0.001), confirming an impairment in β-cell function. We detected no significant interaction between GRS and treatment, but the lifestyle intervention was effective in the highest quartile of GRS (P < 0.0001).CONCLUSIONSA high GRS is associated with increased risk of developing diabetes and lower probability of returning to NGR in high-risk individuals, but a lifestyle intervention attenuates this risk.

Toward an understanding of hypertension resistance

PHYSIOLOGISTS HAVE LONG APPRECIATED the central role of renal salt excretion in the control of blood pressure (4). Maintenance of a constant intravascular fluid volume and blood pressure depends on the ability of the kidneys to regulate urinary sodium excretion through the concerted action of several parallel sodium transport mechanisms. While abnormal function of any one transport process can usually be compensated for, there is a price. That is, a greater than normal change in arterial blood pressure must occur for natriuresis to be brought into balance with an increased Na intake. This concept has been reinforced though the study of rare Mendelian diseases of hypertension or hypotension, since all of the monogenic blood pressure syndromes characterized to date are caused by mutations in genes that influence sodium homeostasis (8). Individuals with these disorders often develop dramatic phenotypes of hypertension or salt wasting, usually through the inheritance of alleles harboring single nucleotide mutations. In recent years, considerable effort has been directed toward understanding whether these genes or others contribute substantially to blood pressure variation in the population as a whole. The approach for a number of these analyses has involved the unbiased search for associations between common genetic polymorphisms and blood pressure through genomewide association (GWA) studies. In some cases, GWA scans have confirmed the involvement of signaling pathways known to regulate renal salt excretion (10), or uncovered novel potential targets for antihypertensive therapy (6). In other examples, however, they have failed to identify common variants that reach genome-wide statistical significance (7, 11). More recent efforts by large-scale consortia have yielded success at identifying new associations (6). However, questions remain regarding the effect size of individual variants (3), and, in general, GWA studies have only identified a fraction of the total predicted genetic component for a variety of complex disease traits. Thus a shift in attention away from common polymorphisms, and toward the analysis of rare variants has been called for, so that their relative contributions may be assessed (3). In a genetic tour-de-force, Ji et al. (5) recently took such an approach, testing whether rare mutations in kidney salt transport genes might contribute substantially to blood pressure variation in the general population. The authors recognized that the heterozygous carrier state for Bartter’s and Gitelman’s syndromes, two Mendelian salt-wasting disorders, should be prevalent in at least 1% of individuals worldwide. Thus they asked whether rare coding variants in genes mutated in these disorders affect blood pressure in a large study population, the Framingham Offspring Cohort. They chose to sequence the exons of three candidates that affect renal sodium transport: SLC12A1 [Na-K-Cl cotransporter (NKCC2), mutated in type 1 Bartter’s syndrome], KCNJ1 (ROMK, mutated in type 2 Bartter’s syndrome), and SLC12A3 [Na-Cl cotransporter (NCC), mutated in Gitelman’s syndrome]. To select for relevant coding variants, Ji et al. first identified carriers for mutations in NKCC2, ROMK, and NCC already proven previously to cause hereditary salt wasting. As a second strategy, the authors applied stringent criteria to identify additional variants that could be inferred with confidence to lead to loss of function. To make the cutoff, a variant had to change an evolutionarily conserved residue and be present in the study population at a low frequency (to favor alleles under purifying selection). This approach identified 30 mutations across 49 subjects in 3,000 individuals. The authors found that carriers for one of the proven or inferred mutations in NKCC2, NCC, or ROMK had

Genome-wide association study identifies a novel susceptibility locus at 6p21.3 among familial CLL

AbstractPrior genome-wide association (GWA) studies have identified 10 susceptibility loci for risk of chronic lymphocytic leukemia (CLL). To identify additional loci, we performed a GWA study in 407 CLL cases (of which 102 had a family history of CLL) and 296 controls. Moreover, given the strong familial risk of CLL, we further subset our GWA analysis to the CLL cases with a family history of CLL to identify loci specific to these familial CLL cases. Our top hits from these analyses were evaluated in an additional sample of 252 familial CLL cases and 965 controls. Using all available data, we identified and confirmed an independent association of 4 single-nucleotide polymorphisms (SNPs) that met genome-wide statistical significance within the IRF8 (interferon regulatory factor 8) gene (combined P values ≤ 3.37 × 10−8), located in the previously identified 16q24.1 locus. Subsetting to familial CLL cases, we identified and confirmed a new locus on chromosome 6p21.3 (combined P value = 6.92 × 10−9). This novel region harbors the HLA-DQA1 and HLA-DRB5 genes. Finally, we evaluated the 10 previously reported SNPs in the overall sample and replicated 8 of them. Our findings support the hypothesis that familial CLL cases have additional genetic variants not seen in sporadic CLL. Additional loci among familial CLL cases may be identified through larger studies.

Novel Breast Cancer Susceptibility Locus at 9q31.2: Results of a Genome-Wide Association Study

Genome-wide association studies have identified several common genetic variants associated with breast cancer risk. It is likely, however, that a substantial proportion of such loci have not yet been discovered. We compared 296,114 tagging single-nucleotide polymorphisms in 1694 breast cancer case subjects (92% with two primary cancers or at least two affected first-degree relatives) and 2365 control subjects, with validation in three independent series totaling 11,880 case subjects and 12,487 control subjects. Odds ratios (ORs) and associated 95% confidence intervals (CIs) in each stage and all stages combined were calculated using unconditional logistic regression. Heterogeneity was evaluated with Cochran Q and I(2) statistics. All statistical tests were two-sided. We identified a novel risk locus for breast cancer at 9q31.2 (rs865686: OR = 0.89, 95% CI = 0.85 to 0.92, P = 1.75 × 10(-10)). This single-nucleotide polymorphism maps to a gene desert, the nearest genes being Kruppel-like factor 4 (KLF4, 636 kb centromeric), RAD23 homolog B (RAD23B, 794 kb centromeric), and actin-like 7A (ACTL7A, 736 kb telomeric). We also identified two variants (rs3734805 and rs9383938) mapping to 6q25.1 estrogen receptor 1 (ESR1), which were associated with breast cancer in subjects of northern European ancestry (rs3734805: OR = 1.19, 95% CI = 1.11 to 1.27, P = 1.35 × 10(-7); rs9383938: OR = 1.18, 95% CI = 1.11 to 1.26, P = 1.41 × 10(-7)). A variant mapping to 10q26.13, approximately 300 kb telomeric to the established risk locus within the second intron of FGFR2, was also associated with breast cancer risk, although not at genome-wide statistical significance (rs10510102: OR = 1.12, 95% CI = 1.07 to 1.17, P = 1.58 × 10(-6)). These findings provide further evidence on the role of genetic variation in the etiology of breast cancer. Fine mapping will be needed to identify causal variants and to determine their functional effects.

Maternal Genome-Wide DNA Methylation Patterns and Congenital Heart Defects

The majority of congenital heart defects (CHDs) are thought to result from the interaction between multiple genetic, epigenetic, environmental, and lifestyle factors. Epigenetic mechanisms are attractive targets in the study of complex diseases because they may be altered by environmental factors and dietary interventions. We conducted a population based, case-control study of genome-wide maternal DNA methylation to determine if alterations in gene-specific methylation were associated with CHDs. Using the Illumina Infinium Human Methylation27 BeadChip, we assessed maternal gene-specific methylation in over 27,000 CpG sites from DNA isolated from peripheral blood lymphocytes. Our study sample included 180 mothers with non-syndromic CHD-affected pregnancies (cases) and 187 mothers with unaffected pregnancies (controls). Using a multi-factorial statistical model, we observed differential methylation between cases and controls at multiple CpG sites, although no CpG site reached the most stringent level of genome-wide statistical significance. The majority of differentially methylated CpG sites were hypermethylated in cases and located within CpG islands. Gene Set Enrichment Analysis (GSEA) revealed that the genes of interest were enriched in multiple biological processes involved in fetal development. Associations with canonical pathways previously shown to be involved in fetal organogenesis were also observed. We present preliminary evidence that alterations in maternal DNA methylation may be associated with CHDs. Our results suggest that further studies involving maternal epigenetic patterns and CHDs are warranted. Multiple candidate processes and pathways for future study have been identified.

Evaluation of polygenic risk scores for predicting breast and prostate cancer risk

Recently, polygenic risk scores (PRS) have been shown to be associated with certain complex diseases. The approach has been based on the contribution of counting multiple alleles associated with disease across independent loci, without requiring compelling evidence that every locus had already achieved definitive genome-wide statistical significance. Whether PRS assist in the prediction of risk of common cancers is unknown. We built PRS from lists of genetic markers prioritized by their association with breast cancer (BCa) or prostate cancer (PCa) in a training data set and evaluated whether these scores could improve current genetic prediction of these specific cancers in independent test samples. We used genome-wide association data on 1,145 BCa cases and 1,142 controls from the Nurses' Health Study and 1,164 PCa cases and 1,113 controls from the Prostate Lung Colorectal and Ovarian Cancer Screening Trial. Ten-fold cross validation was used to build and evaluate PRS with 10 to 60,000 independent single nucleotide polymorphisms (SNPs). For both BCa and PCa, the models that included only published risk alleles maximized the cross-validation estimate of the area under the ROC curve (0.53 for breast and 0.57 for prostate). We found no significant evidence that PRS using common variants improved risk prediction for BCa and PCa over replicated SNP scores.

Genome-wide association study of Stevens-Johnson Syndrome and Toxic Epidermal Necrolysis in Europe

BackgroundStevens-Johnson syndrome (SJS) and Toxic Epidermal Necrolysis (TEN) are rare but extremely severe cutaneous adverse drug reactions in which drug-specific associations with HLA-B alleles were described.ObjectivesTo investigate genetic association at a genome-wide level on a large sample of SJS/TEN patients.MethodsWe performed a genome wide association study on a sample of 424 European cases and 1,881 controls selected from a Reference Control Panel.ResultsSix SNPs located in the HLA region showed significant evidence for association (OR range: 1.53-1.74). The haplotype formed by their risk allele was more associated with the disease than any of the single SNPs and was even much stronger in patients exposed to allopurinol (ORallopurinol = 7.77, 95%CI = [4.66; 12.98]). The associated haplotype is in linkage disequilibrium with the HLA-B*5801 allele known to be associated with allopurinol induced SJS/TEN in Asian populations.ConclusionThe involvement of genetic variants located in the HLA region in SJS/TEN is confirmed in European samples, but no other locus reaches genome-wide statistical significance in this sample that is also the largest one collected so far. If some loci outside HLA play a role in SJS/TEN, their effect is thus likely to be very small.

Editorial: Identifying the genetic and environmental influences on psychological outcomes

Editorial: Identifying the genetic and environmental influences on psychological outcomes

Meta-Analysis of Genome-Wide Association Studies

Individual genome-wide association studies have only limited power to find novel loci underlying complex traits and common diseases. With relatively modest sample and effect sizes, a true association between genotype and phenotype may never meet genome-wide statistical significance (P < 5 x 10(-8)) in a single study. Through meta-analysis, novel susceptibility loci can be discovered by effectively summing the statistical evidence of individually underpowered studies. Most genetic discoveries for complex traits are now made through meta-analysis collaborations, which so far have been restricted to single-locus analyses, testing for main effects at a single polymorphism at a time. A key benefit of this approach is that individual-level genotype (and phenotype) data do not need to be exchanged between research groups. In this article, we focus on meta-analysis at individual single-nucleotide polymorphisms (SNPs), paying particular attention to how imputation uncertainty can be incorporated into the association analysis and subsequent meta-analysis. Probably the most important aspect of genome-wide association meta-analysis is harmonization of the study results. As studies differ in design, sample collection, genotyping platforms, and association analysis methods, it is important that the association results (per SNP) of each study can be formatted, exchanged, and analyzed in such a way that the statistical evidence can be combined appropriately and that no valuable information is lost. Without minimizing the importance of having a clear phenotype definition (and corresponding measurements), we will assume that investigators representing the various studies have made sensible agreements about phenotype definitions, necessary sample exclusions, and appropriate covariate modeling.

Family-Based Genome-Wide Association Scan of Attention-Deficit/Hyperactivity Disorder

Genes likely play a substantial role in the etiology of attention-deficit/hyperactivity disorder (ADHD). However, the genetic architecture of the disorder is unknown, and prior genome-wide association studies (GWAS) have not identified a genome-wide significant association. We have conducted a third, independent, multisite GWAS of DSM-IV-TR ADHD. Families were ascertained at Massachusetts General Hospital (MGH; N = 309 trios), Washington University at St. Louis (WASH-U; N = 272 trios), and University of California at Los Angeles (UCLA; N = 156 trios). Genotyping was conducted with the Illumina Human1M or Human1M-Duo BeadChip platforms. After applying quality control filters, association with ADHD was tested with 835,136 SNPs in 735 DSM-IV ADHD trios from 732 families. Our smallest p value (6.7E-07) did not reach the threshold for genome-wide statistical significance (5.0E-08), but one of the 20 most significant associations was located in a candidate gene of interest for ADHD (SLC9A9, rs9810857, p = 6.4E-6). We also conducted gene-based tests of candidate genes identified in the literature and found additional evidence of association with SLC9A9. We and our colleagues in the Psychiatric GWAS Consortium are working to pool together GWAS samples to establish the large data sets needed to follow-up on these results and to identify genes for ADHD and other disorders.

Genome-wide Analysis of Genetic Loci Associated With Alzheimer Disease

Genome-wide association studies (GWAS) have recently identified CLU, PICALM, and CR1 as novel genes for late-onset Alzheimer disease (AD). To identify and strengthen additional loci associated with AD and confirm these in an independent sample and to examine the contribution of recently identified genes to AD risk prediction in a 3-stage analysis of new and previously published GWAS on more than 35,000 persons (8371 AD cases). In stage 1, we identified strong genetic associations (P < 10(-3)) in a sample of 3006 AD cases and 14,642 controls by combining new data from the population-based Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (1367 AD cases [973 incident]) with previously reported results from the Translational Genomics Research Institute and the Mayo AD GWAS. We identified 2708 single-nucleotide polymorphisms (SNPs) with P < 10(-3). In stage 2, we pooled results for these SNPs with the European AD Initiative (2032 cases and 5328 controls) to identify 38 SNPs (10 loci) with P < 10(-5). In stage 3, we combined data for these 10 loci with data from the Genetic and Environmental Risk in AD consortium (3333 cases and 6995 controls) to identify 4 SNPs with P < 1.7x10(-8). These 4 SNPs were replicated in an independent Spanish sample (1140 AD cases and 1209 controls). Genome-wide association analyses were completed in 2007-2008 and the meta-analyses and replication in 2009. Presence of Alzheimer disease. Two loci were identified to have genome-wide significance for the first time: rs744373 near BIN1 (odds ratio [OR],1.13; 95% confidence interval [CI],1.06-1.21 per copy of the minor allele; P = 1.59x10(-11)) and rs597668 near EXOC3L2/BLOC1S3/MARK4 (OR, 1.18; 95% CI, 1.07-1.29; P = 6.45x10(-9)). Associations of these 2 loci plus the previously identified loci CLU and PICALM with AD were confirmed in the Spanish sample (P < .05). However, although CLU and PICALM were confirmed to be associated with AD in this independent sample, they did not improve the ability of a model that included age, sex, and APOE to predict incident AD (improvement in area under the receiver operating characteristic curve from 0.847 to 0.849 in the Rotterdam Study and 0.702 to 0.705 in the Cardiovascular Health Study). Two genetic loci for AD were found for the first time to reach genome-wide statistical significance. These findings were replicated in an independent population. Two recently reported associations were also confirmed. These loci did not improve AD risk prediction. While not clinically useful, they may implicate biological pathways useful for future research.

Consanguinity mapping of congenital heart disease in a South Indian population.

BackgroundParental consanguinity is a risk factor for congenital heart disease (CHD) worldwide, suggesting that a recessive inheritance model may contribute substantially to CHD. In Bangalore, India, uncle-niece and first cousin marriages are common, presenting the opportunity for an international study involving consanguinity mapping of structural CHD. We sought to explore the recessive model of CHD by conducting a genome-wide linkage analysis utilizing high-density oligonucleotide microarrays and enrolling 83 CHD probands born to unaffected consanguineous parents.Methodology/Principal FindingsIn this linkage scan involving single nucleotide polymorphism (SNP) markers, the threshold for genome-wide statistical significance was set at the standard log-of-odds (LOD) score threshold of 3.3, corresponding to 1995∶1 odds in favor of linkage. We identified a maximal single-point LOD score of 3.76 (5754∶1 odds) implicating linkage of CHD with the major allele (G) of rs1055061 on chromosome 14 in the HOMEZ gene, a ubiquitously expressed transcription factor containing leucine zipper as well as zinc finger motifs. Re-sequencing of HOMEZ exons did not reveal causative mutations in Indian probands. In addition, genotyping of the linked allele (G) in 325 U.S. CHD cases revealed neither genotypic nor allele frequency differences in varied CHD cases compared to 605 non-CHD controls.Conclusions/SignificanceDespite the statistical power of the consanguinity mapping approach, no single gene of major effect could be convincingly identified in a clinically heterogeneous sample of Indian CHD cases born to consanguineous parents. However, we are unable to exclude the possibility that noncoding regions of HOMEZ may harbor recessive mutations leading to CHD in the Indian population. Further research involving large multinational cohorts of patients with specific subtypes of CHD is needed to attempt replication of the observed linkage peak on chromosome 14. In addition, we anticipate that a targeted re-sequencing approach may complement linkage analysis in future studies of recessive mutation detection in CHD.

Longitudinal age-dependent effect on systolic blood pressure

Age-dependent genetic effects on susceptibility to hypertension have been documented. We present a novel variance-component method for the estimation of age-dependent genetic effects on longitudinal systolic blood pressure using 57,827 Affymetrix single-nucleotide polymorphisms (SNPs) on chromosomes 17-22 genotyped in 2,475 members of the Offspring Cohort of the Framingham Heart Study. We used the likelihood-ratio test statistic to test the main genetic effect, genotype-by-age interaction, and simultaneously, main genetic effect and genotype-by-age interactions (2 degrees of freedom (df) test) for each SNP. Applying Bonferroni correction, three SNPs were significantly associated with longitudinal blood pressure in the analysis of main genetic effects or in combined 2-df analyses. For the associations detected using the simultaneous 2-df test, neither main effects nor genotype-by-age interaction p-values reached genome-wide statistical significance. The value of the 2-df test for screening genetic interaction effects could not be established in this study.

X Chromosomal Variation Is Associated with Slow Progression to AIDS in HIV-1-Infected Women

AIDS has changed from a mostly male-specific health problem to one that predominantly affects females. Although sex differences in HIV-1 susceptibility are beyond doubt, the extent to which sex affects the onset and progression of AIDS has remained elusive. Here, we provide evidence for an influence of X chromosomal variation on the course of retroviral infection, both in HIV-1-infected patients and in the rhesus macaque model of AIDS. A two-stage, microsatellite-based GWAS of SIV-infected monkeys revealed MHC class I markers and a hitherto-unknown X chromosomal locus as being associated with a nominal score measuring progression to AIDS (Fisher's exact p < 10(-6)). The X chromosomal association was subsequently confirmed in HIV-1-infected patients with published SNP genotype data. SNP rs5968255, located at human Xq21.1 in a conserved sequence element near the RPS6KA6 and CYLC1 genes, was identified as a significant genetic determinant of disease progression in females (ANOVA p = 8.8 x 10(-5)), but not in males (p = 0.19). Heterozygous female carriers of the C allele showed significantly slower CD4 cell decline and a lower viral load at set point than TT homozygous females and than males. Inspection of HapMap revealed that the CT genotype is significantly more frequent among Asians than among Europeans or Africans. Our results suggest that, in addition to the individual innate and adaptive immunity status, sex-linked genetic variation impacts upon the rate of progression to AIDS. Elucidating the mechanisms underlying this sex-specific effect will promote the development of antiretroviral therapies with high efficacy in both sexes.