Shape-IT: new rapid and accurate algorithm for haplotype inference

Abruptio placentae risk and genetic variations in mitochondrial biogenesis and oxidative phosphorylation: replication of a candidate gene association study

BACKGROUND

Abruptio placentae is a complex multifactorial disease that is associated with maternal and neonatal death and morbidity. Abruptio placentae's high recurrence rate, high prevalence of heritable thrombophilia among women with abruptio placentae, and aggregation of cases in families of women with the disease support the possibility of a genetic predisposition. Previous genome-wide and candidate gene association studies have identified single nucleotide polymorphisms in mitochondrial biogenesis and oxidative phosphorylation genes that potentially are associated with abruptio placentae risk. Perturbations in mitochondrial biogenesis and oxidative phosphorylation, which results in mitochondrial dysfunction, can lead to the impairment of differentiation and invasion of the trophoblast and to several obstetrics complications that include abruptio placentae.

OBJECTIVE

The purpose of this study was to determine whether the results of a candidate genetic association study that indicated a link between DNA variants (implicated in mitochondrial biogenesis and oxidative phosphorylation) and abruptio placentae could be replicated.

STUDY DESIGN

The study was conducted among participants (507 abruptio placentae cases and 1090 control subjects) of the Placental Abruption Genetic Epidemiology study. Weighted genetic risk scores were calculated with the use of abruptio placentae risk-increasing alleles of 11 single nucleotide polymorphisms in 9 mitochondrial biogenesis and oxidative phosphorylation genes (CAMK2B, NR1H3, PPARG, PRKCA, THRB, COX5A, NDUFA10, NDUFA12, and NDUFC2), which previously was reported in the Peruvian Abruptio Placentae Epidemiology study, a study with similar design and study population to the Placental Abruption Genetic Epidemiology study. Logistic regression models were fit to examine associations of weighted genetic risk scores (quartile 1, <25th percentile; quartile 2, 25-50th percentile; quartile 3, 50-70th percentile, and quartile 4, >75th percentile) with risk of abruptio placentae, adjusted for population admixture (the first 4 principal components), maternal age, infant sex, and preeclampsia. The weighted genetic risk score was also modeled as a continuous predictor. To assess potential effect modification, analyses were repeated among strata that were defined by preeclampsia status, maternal age (≥35 vs 18-34 years), and infant sex.

RESULTS

Abruptio placentae cases were more likely to have preeclampsia, shorter gestational age, and lower infant birthweight. Participants in quartile 2 (score, 12.6-13.8), quartile 3 (score, 13.9-15.0) and quartile 4 (score, ≥15.1) had a genetic risk score of 1.45-fold (95% confidence interval, 1.04-2.02; P=.03), a 1.42-fold (95% confidence interval, 1.02-1.98; P=.04), and a 1.75-fold (95% confidence interval, 1.27-2.42; P=7.0E-04) higher odds of abruptio placentae, respectively, compared with those in quartile 1 (score,<12.6; P-for trend=.0003). The risk of abruptio placentae was 1.12-fold (95% confidence interval, 1.05-1.19; P=3.0×1004) higher per 1-unit increase in the score. Among women with preeclampsia, those in quartile 4 had a 3.92-fold (95% confidence interval, 1.48-10.36; P=.01) higher odds of abruptio placentae compared with women in quartile 1. Among normotensive women, women in quartile 4 had a 1.57-fold (95% confidence interval, 1.11-2.21; P=.01) higher odds of abruptio placentae compared with those in quartile 1 (P-for interaction=.12). We did not observe differences in associations among strata defined by maternal age or infant sex.

CONCLUSION

In this study, we replicated previous findings and provide strong evidence for DNA variants that encode for genes that are involved in mitochondrial biogenesis and oxidative phosphorylation pathways, which confers risk for abruptio placentae. These results shed light on the mechanisms that implicate DNA variants that encode for proteins in mitochondrial function that are responsible for abruptio placentae risk. Therapeutic efforts to reduce risk of abruptio placentae can be enhanced by improved biologic understanding of maternal mitochondrial biogenesis/oxidative phosphorylation pathways and identification of women who would be at high risk for abruptio placentae.

A Recurrent BRCA2 Mutation Explains the Majority of Hereditary Breast and Ovarian Cancer Syndrome Cases in Puerto Rico

Breast cancer is the most common cause of cancer diagnosis in women and is responsible for considerable mortality among the women of Puerto Rico. However, there are few studies in Puerto Rico on the genetic factors influencing risk. To determine the contribution of pathogenic mutations in BRCA1 and BRCA2, we sequenced these genes in 302 cases from two separate medical centers, who were not selected for age of onset or family history. We identified nine cases that are carriers of pathogenic germline mutation. This represents 2.9% of unselected cases and 5.6% of women meeting National Comprehensive Cancer Network (NCCN) criteria for BRCA testing. All of the identified pathogenic mutations were in the BRCA2 gene and the most common mutation is the p.Glu1308Ter (E1308X) mutation in BRCA2 found in eight out of nine cases, representing 89% of the pathogenic carriers. The E1308X mutation has been identified in breast and ovarian cancer families in Spain, and analysis of flanking DNA polymorphisms shows that all E1308X carriers occur on the same haplotype. This is consistent with BRCA2 E1308X being a founder mutation for the Puerto Rican population. These results will contribute to better inform genetic screening and counseling of breast and ovarian cancer cases in Puerto Rico and Puerto Rican populations in mainland United States.

Disease networks identify specific conditions and pleiotropy influencing multimorbidity in the general population

Multimorbidity is an emerging topic in public health policy because of its increasing prevalence and socio-economic impact. However, the age- and gender-dependent trends of disease associations at fine resolution, and the underlying genetic factors, remain incompletely understood. Here, by analyzing disease networks from electronic medical records of primary health care, we identify key conditions and shared genetic factors influencing multimorbidity. Three types of diseases are outlined: "central", which include chronic and non-chronic conditions, have higher cumulative risks of disease associations; "community roots" have lower cumulative risks, but inform on continuing clustered disease associations with age; and "seeds of bursts", which most are chronic, reveal outbreaks of disease associations leading to multimorbidity. The diseases with a major impact on multimorbidity are caused by genes that occupy central positions in the network of human disease genes. Alteration of lipid metabolism connects breast cancer, diabetic neuropathy and nutritional anemia. Evaluation of key disease associations by a genome-wide association study identifies shared genetic factors and further supports causal commonalities between nervous system diseases and nutritional anemias. This study also reveals many shared genetic signals with other diseases. Collectively, our results depict novel population-based multimorbidity patterns, identify key diseases within them, and highlight pleiotropy influencing multimorbidity.

User considerations in assessing pharmacogenomic tests and their clinical support tools

Pharmacogenomic (PGx) testing is gaining recognition from physicians, pharmacists and patients as a tool for evidence-based medication management. However, seemingly similar PGx testing panels (and PGx-based decision support tools) can diverge in their technological specifications, as well as the genetic factors that determine test specificity and sensitivity, and hence offer different values for users. Reluctance to embrace PGx testing is often the result of unfamiliarity with PGx technology, a lack of knowledge about the availability of curated guidelines/evidence for drug dosing recommendations, and an absence of wide-spread institutional implementation efforts and educational support. Demystifying an often confusing and variable PGx marketplace can lead to greater acceptance of PGx as a standard-of-care practice that improves drug outcomes and provides a lifetime value for patients. Here, we highlight the key underlying factors of a PGx test that should be considered, and discuss the current progress of PGx implementation.

Misidentification of runs of homozygosity islands in cattle caused by interference with copy number variation or large intermarker distances

Background

Runs of homozygosity (ROH) islands are stretches of homozygous sequence in the genome of a large proportion of individuals in a population. Algorithms for the detection of ROH depend on the similarity of haplotypes. Coverage gaps and copy number variants (CNV) may result in incorrect identification of such similarity, leading to the detection of ROH islands where none exists. Misidentified hemizygous regions will also appear as homozygous based on sequence variation alone. Our aim was to identify ROH islands influenced by marker coverage gaps or CNV, using Illumina BovineHD BeadChip (777 K) single nucleotide polymorphism (SNP) data for Austrian Brown Swiss, Tyrol Grey and Pinzgauer cattle.

Methods

ROH were detected using clustering, and ROH islands were determined from population inbreeding levels for each marker. CNV were detected using a multivariate copy number analysis method and a hidden Markov model. SNP coverage gaps were defined as genomic regions with intermarker distances on average longer than 9.24 kb. ROH islands that overlapped CNV regions (CNVR) or SNP coverage gaps were considered as potential artefacts. Permutation tests were used to determine if overlaps between CNVR with copy losses and ROH islands were due to chance. Diversity of the haplotypes in the ROH islands was assessed by haplotype analyses.

Results

In Brown Swiss, Tyrol Grey and Pinzgauer, we identified 13, 22, and 24 ROH islands covering 26.6, 389.0 and 35.8 Mb, respectively, and we detected 30, 50 and 71 CNVR derived from CNV by using both algorithms, respectively. Overlaps between ROH islands, CNVR or coverage gaps occurred for 7, 14 and 16 ROH islands, respectively. About 37, 44 and 52% of the ROH islands coverage in Brown Swiss, Tyrol Grey and Pinzgauer, respectively, were affected by copy loss. Intersections between ROH islands and CNVR were small, but significantly larger compared to ROH islands at random locations across the genome, implying an association between ROH islands and CNVR. Haplotype diversity for reliable ROH islands was lower than for ROH islands that intersected with copy loss CNVR.

Conclusions

Our findings show that a significant proportion of the ROH islands in the bovine genome are artefacts due to CNV or SNP coverage gaps.

Electronic supplementary material

The online version of this article (10.1186/s12711-018-0414-x) contains supplementary material, which is available to authorized users.

Developmental and genetic regulation of the human cortex transcriptome illuminate schizophrenia pathogenesis

Genome-wide association studies have identified 108 schizophrenia risk loci, but biological mechanisms for individual loci are largely unknown. Using developmental, genetic and illness-based RNA sequencing expression analysis in human brain, we characterized the human brain transcriptome around these loci and found enrichment for developmentally regulated genes with novel examples of shifting isoform usage across pre- and postnatal life. We found widespread expression quantitative trait loci (eQTLs), including many with transcript specificity and previously unannotated sequence that were independently replicated. We leveraged this general eQTL database to show that 48.1% of risk variants for schizophrenia associate with nearby expression. We lastly found 237 genes significantly differentially expressed between patients and controls, which replicated in an independent dataset, implicated synaptic processes, and were strongly regulated in early development. These findings together offer genetics- and diagnosis-related targets for better modeling of schizophrenia risk. This resource is publicly available at http://eqtl.brainseq.org/phase1 .

Disease-specific regulation of gene expression in a comparative analysis of juvenile idiopathic arthritis and inflammatory bowel disease

BACKGROUND

The genetic and immunological factors that contribute to differences in susceptibility and progression between sub-types of inflammatory and autoimmune diseases continue to be elucidated. Inflammatory bowel disease and juvenile idiopathic arthritis are both clinically heterogeneous and known to be due in part to abnormal regulation of gene activity in diverse immune cell types. Comparative genomic analysis of these conditions is expected to reveal differences in underlying genetic mechanisms of disease.

METHODS

We performed RNA-Seq on whole blood samples from 202 patients with oligoarticular, polyarticular, or systemic juvenile idiopathic arthritis, or with Crohn's disease or ulcerative colitis, as well as healthy controls, to characterize differences in gene expression. Gene ontology analysis combined with Blood Transcript Module and Blood Informative Transcript analysis was used to infer immunological differences. Comparative expression quantitative trait locus (eQTL) analysis was used to quantify disease-specific regulation of transcript abundance.

RESULTS

A pattern of differentially expressed genes and pathways reveals a gradient of disease spanning from healthy controls to oligoarticular, polyarticular, and systemic juvenile idiopathic arthritis (JIA); Crohn's disease; and ulcerative colitis. Transcriptional risk scores also provide good discrimination of controls, JIA, and IBD. Most eQTL are found to have similar effects across disease sub-types, but we also identify disease-specific eQTL at loci associated with disease by GWAS.

CONCLUSION

JIA and IBD are characterized by divergent peripheral blood transcriptomes, the genetic regulation of which displays limited disease specificity, implying that disease-specific genetic influences are largely independent of, or downstream of, eQTL effects.

Development and application of an integrated allele-specific pipeline for methylomic and epigenomic analysis (MEA)

BACKGROUND

Allele-specific transcriptional regulation, including of imprinted genes, is essential for normal mammalian development. While the regulatory regions controlling imprinted genes are associated with DNA methylation (DNAme) and specific histone modifications, the interplay between transcription and these epigenetic marks at allelic resolution is typically not investigated genome-wide due to a lack of bioinformatic packages that can process and integrate multiple epigenomic datasets with allelic resolution. In addition, existing ad-hoc software only consider SNVs for allele-specific read discovery. This limitation omits potentially informative INDELs, which constitute about one fifth of the number of SNVs in mice, and introduces a systematic reference bias in allele-specific analyses.

RESULTS

Here, we describe MEA, an INDEL-aware Methylomic and Epigenomic Allele-specific analysis pipeline which enables user-friendly data exploration, visualization and interpretation of allelic imbalance. Applying MEA to mouse embryonic datasets yields robust allele-specific DNAme maps and low reference bias. We validate allele-specific DNAme at known differentially methylated regions and show that automated integration of such methylation data with RNA- and ChIP-seq datasets yields an intuitive, multidimensional view of allelic gene regulation. MEA uncovers numerous novel dynamically methylated loci, highlighting the sensitivity of our pipeline. Furthermore, processing and visualization of epigenomic datasets from human brain reveals the expected allele-specific enrichment of H3K27ac and DNAme at imprinted as well as novel monoallelically expressed genes, highlighting MEA's utility for integrating human datasets of distinct provenance for genome-wide analysis of allelic phenomena.

CONCLUSIONS

Our novel pipeline for standardized allele-specific processing and visualization of disparate epigenomic and methylomic datasets enables rapid analysis and navigation with allelic resolution. MEA is freely available as a Docker container at https://github.com/julienrichardalbert/MEA .

Genetic variations and risk of placental abruption: A genome-wide association study and meta-analysis of genome-wide association studies

INTRODUCTION

Accumulating epidemiological evidence points to strong genetic susceptibility to placental abruption (PA). However, characterization of genes associated with PA remains incomplete. We conducted a genome-wide association study (GWAS) of PA and a meta-analysis of GWAS.

METHODS

Participants of the Placental Abruption Genetic Epidemiology (PAGE) study, a population based case-control study of PA conducted in Lima, Peru, were genotyped using the Illumina HumanCore-24 BeadChip platform. Genotypes were imputed using the 1000 genomes reference panel, and >4.9 million SNPs that passed quality control were analyzed. We performed a GWAS in PAGE participants (507 PA cases and 1090 controls) and a GWAS meta-analysis in 2512 participants (959 PA cases and 1553 controls) that included PAGE and the previously reported Peruvian Abruptio Placentae Epidemiology (PAPE) study. We fitted population stratification-adjusted logistic regression models and fixed-effects meta-analyses using inverse-variance weighting.

RESULTS

Independent loci (linkage-disequilibrium<0.80) suggestively associated with PA (P-value<5e-5) included rs4148646 and rs2074311 in ABCC8, rs7249210, rs7250184, rs7249100 and rs10401828 in ZNF28, rs11133659 in CTNND2, and rs2074314 and rs35271178 near KCNJ11 in the PAGE GWAS. Similarly, independent loci suggestively associated with PA in the GWAS meta-analysis included rs76258369 near IRX1, and rs7094759 and rs12264492 in ADAM12. Functional analyses of these genes showed trophoblast-like cell interaction, as well as networks involved in endocrine system disorders, cardiovascular diseases, and cellular function.

CONCLUSIONS

We identified several genetic loci and related functions that may play a role in PA risk. Understanding genetic factors underlying pathophysiological mechanisms of PA may facilitate prevention and early diagnostic efforts.

Polygenic risk score of sporadic late-onset Alzheimer's disease reveals a shared architecture with the familial and early-onset forms

OBJECTIVE

To determine whether the extent of overlap of the genetic architecture among the sporadic late-onset Alzheimer's Disease (sLOAD), familial late-onset AD (fLOAD), sporadic early-onset AD (sEOAD), and autosomal dominant early-onset AD (eADAD).

METHODS

Polygenic risk scores (PRSs) were constructed using previously identified 21 genome-wide significant loci for LOAD risk.

RESULTS

We found that there is an overlap in the genetic architecture among sEOAD, fLOAD, and sLOAD. The highest association of the PRS and risk (odds ratio [OR] = 2.27; P = 1.29 × 10-7) was observed in sEOAD, followed by fLOAD (OR = 1.75; P = 1.12 × 10-7) and sLOAD (OR = 1.40; P = 1.21 × 10-3). The PRS was associated with cerebrospinal fluid ptau181-Aβ42 on eADAD (P = 4.36 × 10-2).

CONCLUSION

Our analysis confirms that the genetic factors identified for LOAD modulate risk in sLOAD and fLOAD and also sEOAD cohorts. Specifically, our results suggest that the burden of these risk variants is associated with familial clustering and earlier onset of AD. Although these variants are not associated with risk in the eADAD, they may be modulating age at onset.

Parkinson disease polygenic risk score is associated with Parkinson disease status and age at onset but not with alpha-synuclein cerebrospinal fluid levels

BACKGROUND

The genetic architecture of Parkinson's Disease (PD) is complex and not completely understood. Multiple genetic studies to date have identified multiple causal genes and risk loci. Nevertheless, most of the expected genetic heritability remains unexplained. Polygenic risk scores (PRS) may provide greater statistical power and inform about the genetic architecture of multiple phenotypes. The aim of this study was to test the association between PRS and PD risk, age at onset and cerebrospinal fluid (CSF) biomarkers (α-synuclein, Aβ_1-42, t-tau and p-tau).

METHODS

The weighted PRS was created using the genome-wide loci from Nalls et al., 2014 PD GWAs meta-analysis. The PRS was tested for association with PD status, age at onset and CSF biomarker levels in 829 cases and 432 controls of European ancestry.

RESULTS

The PRS was associated with PD status (p = 5.83×10^-08) and age at onset (p = 5.70×10^-07). The CSF t-tau levels showed a nominal association with the PRS (p = 0.02). However, CSF α-synuclein, amyloid beta and phosphorylated tau were not found to be associated with the PRS.

CONCLUSION

Our study suggests that there is an overlap in the genetic architecture of PD risk and onset, although the different loci present different weights for those phenotypes. In our dataset we found a marginal association of the PRS with CSF t-tau but not with α-synuclein CSF levels, suggesting that the genetic architecture for the CSF biomarker levels is different from that of PD risk.

A strategy to improve phasing of whole-genome sequenced individuals through integration of familial information from dense genotype panels

Background

Haplotype reconstruction (phasing) is an essential step in many applications, including imputation and genomic selection. The best phasing methods rely on both familial and linkage disequilibrium (LD) information. With whole-genome sequence (WGS) data, relatively small samples of reference individuals are generally sequenced due to prohibitive sequencing costs, thus only a limited amount of familial information is available. However, reference individuals have many relatives that have been genotyped (at lower density). The goal of our study was to improve phasing of WGS data by integrating familial information from haplotypes that were obtained from a larger genotyped dataset and to quantify its impact on imputation accuracy.

Results

Aligning a pre-phased WGS panel [~5 million single nucleotide polymorphisms (SNPs)], which is based on LD information only, to a 50k SNP array that is phased with both LD and familial information (called scaffold) resulted in correctly assigning parental origin for 99.62% of the WGS SNPs, their phase being determined unambiguously based on parental genotypes. Without using the 50k haplotypes as scaffold, that value dropped as expected to 50%. Correctly phased segments were on average longer after alignment to the genotype phase while the number of switches decreased slightly. Most of the incorrectly assigned segments, and subsequent switches, were due to singleton errors. Imputation from 50k SNP array to WGS data with improved phasing had a marginal impact on imputation accuracy (measured as r²), i.e. on average, 90.47% with traditional techniques versus 90.65% with pre-phasing integrating familial information. Differences were larger for SNPs located in chromosome ends and rare variants. Using a denser WGS panel (~13 millions SNPs) that was obtained with traditional variant filtering rules, we found similar results although performances of both phasing and imputation accuracy were lower.

Conclusions

We present a phasing strategy for WGS data, which indirectly integrates familial information by aligning WGS haplotypes that are pre-phased with LD information only on haplotypes obtained with genotyping data, with both LD and familial information and on a much larger population. This strategy results in very few mismatches with the phase obtained by Mendelian segregation rules. Finally, we propose a strategy to further improve phasing accuracy based on haplotype clusters obtained with genotyping data.

Electronic supplementary material

The online version of this article (doi:10.1186/s12711-017-0321-6) contains supplementary material, which is available to authorized users.

Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC.

Comprehensive assessment showed no associations of variants at the SLC10A1 locus with susceptibility to persistent HBV infection among Southern Chinese

The sodium taurocholate cotransporting polypeptide (NTCP) encoded by SLC10A1 was recently demonstrated to be a functional receptor for hepatitis B virus (HBV). The role of SLC10A1 polymorphisms, particularly the Ser267Phe variant (rs2296651) in exon 4, has been frequently investigated in regard to risk of persistent HBV infection. However, these investigations have generated conflicting results. To examine whether common genetic variation at the SLC10A1 locus is associated with risk of persistent HBV infection, haplotype-tagging and imputed single nucleotide polymorphisms (SNPs) were assessed in two case-control sample sets, totally including 2,550 cases (persistently HBV infected subjects, PIs) and 2,124 controls (spontaneously recovered subjects, SRs) of Southern Chinese ancestry. To test whether rare or subpolymorphic SLC10A1 variants are associated with disease risk, the gene's exons in 244 cases were sequenced. Overall, we found neither SNPs nor haplotypes of SLC10A1 showed significant association in the two sample sets. Furthermore, no significant associations of rare variants or copy number variation covering SLC10A1 were observed. Finally, expression quantitative trait locus analyses revealed that SNPs potentially affecting SLC10A1 expression also showed no significant associations. We conclude that genetic variation at the SLC10A1 locus is not likely a major risk factor of persistent HBV infection among Southern Chinese.

Identification of a novel locus associated with skin colour in African-admixed populations

Skin pigmentation is a complex trait that varies largely among populations. Most genome-wide association studies of this trait have been performed in Europeans and Asians. We aimed to uncover genes influencing skin colour in African-admixed individuals. We performed a genome-wide association study of melanin levels in 285 Hispanic/Latino individuals from Puerto Rico, analyzing 14 million genetic variants. A total of 82 variants with p-value ≤1 × 10⁻⁵ were followed up in 373 African Americans. Fourteen single nucleotide polymorphisms were replicated, of which nine were associated with skin colour at genome-wide significance in a meta-analysis across the two studies. These results validated the association of two previously known skin pigmentation genes, SLC24A5 (minimum p = 2.62 × 10⁻¹⁴, rs1426654) and SLC45A2 (minimum p = 9.71 × 10⁻¹⁰, rs16891982), and revealed the intergenic region of BEND7 and PRPF18 as a novel locus associated with this trait (minimum p = 4.58 × 10⁻⁹, rs6602666). The most significant variant within this region is common among African-descent populations but not among Europeans or Native Americans. Our findings support the advantages of analyzing African-admixed populations to discover new genes influencing skin pigmentation.

Genome-wide two-locus interaction analysis identifies multiple epistatic SNP pairs that confer risk of prostate cancer: A cross-population study

Prostate cancer is one of the most common carcinomas among adult males. Recently, genome-wide association studies (GWAS) have identified several susceptibility genes of prostate cancer. However, these single locus results can only explain a small proportion of the genetic etiology. In order to understand how multiple genetic variants may contribute to the penetrance of prostate cancer, we conducted a genome-wide SNP-SNP interaction study in four populations, involving 5,269 cases and 5,289 controls. We exhaustively evaluated all pairs of SNP-SNP interactions for 661,658 SNPs that were consensus in all four groups, and then performed a meta-analysis to combine the results. We found multiple variants within region 7p21.3 and 18p11.22 significantly interacted with each other and reached genome-wide significance levels. The most significant epistasis was between rs1105255 (intergenic, near RBSG3) and rs651431 (intergenic, near VAPA) (p = 1.4 × 10^-14 ). Notably, VAPA was identified to be the protein-coding transcripts as PTEN competing endogenous RNA in prostate cancer. And PTEN is a critical tumor suppressor gene frequently altered in cancers. In addition, 7p21.3 involves several pseudogenes, whose parental genes are cancer-related. Recently, growing evidence strongly suggests they are of multifaceted involvements in the pathogenesis of cancer. Multiple regulatory elements were found within 7p21.3 and 18p11.22, indicating the variants might regulate the nearby genes and confer risk of disease. Additionally, we also found several other significant epistasis, most of which were near or in cancer-related genes. Drug target enrichment analysis suggested genes in top epistasis significantly overlapped with target genes of FDA-approved drugs for treatment of prostate cancer.

Genome-wide interaction study of dust mite allergen on lung function in children with asthma

BACKGROUND

Childhood asthma is likely the result of gene-by-environment (G × E) interactions. Dust mite is a known risk factor for asthma morbidity. Yet, there have been no genome-wide G × E studies of dust mite allergen on asthma-related phenotypes.

OBJECTIVE

We sought to identify genetic variants whose effects on lung function in children with asthma are modified by the level of dust mite allergen exposure.

METHODS

A genome-wide interaction analysis of dust mite allergen level and lung function was performed in a cohort of Puerto Rican children with asthma (Puerto Rico Genetics of Asthma and Lifestyle [PRGOAL]). Replication was attempted in 2 independent cohorts, the Childhood Asthma Management Program (CAMP) and the Genetics of Asthma in Costa Rica Study.

RESULTS

Single nucleotide polymorphism (SNP) rs117902240 showed a significant interaction effect on FEV₁ with dust mite allergen level in PRGOAL (interaction P = 3.1 × 10^-8), and replicated in the same direction in CAMP white children and CAMP Hispanic children (combined interaction P = .0065 for replication cohorts and 7.4 × 10^-9 for all cohorts). Rs117902240 was positively associated with FEV₁ in children exposed to low dust mite allergen levels, but negatively associated with FEV₁ in children exposed to high levels. This SNP is on chromosome 8q24, adjacent to a binding site for CCAAT/enhancer-binding protein beta, a transcription factor that forms part of the IL-17 signaling pathway. None of the SNPs identified for FEV₁/forced vital capacity replicated in the independent cohorts.

CONCLUSIONS

Dust mite allergen exposure modifies the estimated effect of rs117902240 on FEV₁ in children with asthma. Analysis of existing data suggests that this SNP may have transcription factor regulatory functions.

Genome-wide association study identifies SESTD1 as a novel risk gene for lithium-responsive bipolar disorder

Lithium is the mainstay prophylactic treatment for bipolar disorder (BD), but treatment response varies considerably across individuals. Patients who respond well to lithium treatment might represent a relatively homogeneous subtype of this genetically and phenotypically diverse disorder. Here, we performed genome-wide association studies (GWAS) to identify (i) specific genetic variations influencing lithium response and (ii) genetic variants associated with risk for lithium-responsive BD. Patients with BD and controls were recruited from Sweden and the United Kingdom. GWAS were performed on 2698 patients with subjectively defined (self-reported) lithium response and 1176 patients with objectively defined (clinically documented) lithium response. We next conducted GWAS comparing lithium responders with healthy controls (1639 subjective responders and 8899 controls; 323 objective responders and 6684 controls). Meta-analyses of Swedish and UK results revealed no significant associations with lithium response within the bipolar subjects. However, when comparing lithium-responsive patients with controls, two imputed markers attained genome-wide significant associations, among which one was validated in confirmatory genotyping (rs116323614, P=2.74 × 10(-8)). It is an intronic single-nucleotide polymorphism (SNP) on chromosome 2q31.2 in the gene SEC14 and spectrin domains 1 (SESTD1), which encodes a protein involved in regulation of phospholipids. Phospholipids have been strongly implicated as lithium treatment targets. Furthermore, we estimated the proportion of variance for lithium-responsive BD explained by common variants ('SNP heritability') as 0.25 and 0.29 using two definitions of lithium response. Our results revealed a genetic variant in SESTD1 associated with risk for lithium-responsive BD, suggesting that the understanding of BD etiology could be furthered by focusing on this subtype of BD.

Pairwise Kinship Analysis by the Index of Chromosome Sharing Using High-Density Single Nucleotide Polymorphisms

We developed a new approach for pairwise kinship analysis in forensic genetics based on chromosomal sharing between two individuals. Here, we defined "index of chromosome sharing" (ICS) calculated using 174,254 single nucleotide polymorphism (SNP) loci typed by SNP microarray and genetic length of the shared segments from the genotypes of two individuals. To investigate the expected ICS distributions from first- to fifth-degree relatives and unrelated pairs, we used computationally generated genotypes to consider the effect of linkage disequilibrium and recombination. The distributions were used for probabilistic evaluation of the pairwise kinship analysis, such as likelihood ratio (LR) or posterior probability, without allele frequencies and haplotype frequencies. Using our method, all actual sample pairs from volunteers showed significantly high LR values (i.e., ≥ 108); therefore, we can distinguish distant relationships (up to the fifth-degree) from unrelated pairs based on LR. Moreover, we can determine accurate degrees of kinship in up to third-degree relationships with a probability of > 80% using the criterion of posterior probability ≥ 0.90, even if the kinship of the pair is totally unpredictable. This approach greatly improves pairwise kinship analysis of distant relationships, specifically in cases involving identification of disaster victims or missing persons.

Multiple breast cancer risk variants are associated with differential transcript isoform expression in tumors

Genome-wide association studies have identified over 70 single-nucleotide polymorphisms (SNPs) associated with breast cancer. A subset of these SNPs are associated with quantitative expression of nearby genes, but the functional effects of the majority remain unknown. We hypothesized that some risk SNPs may regulate alternative splicing. Using RNA-sequencing data from breast tumors and germline genotypes from The Cancer Genome Atlas, we tested the association between each risk SNP genotype and exon-, exon–exon junction- or transcript-specific expression of nearby genes. Six SNPs were associated with differential transcript expression of seven nearby genes at FDR < 0.05 (BABAM1, DCLRE1B/PHTF1, PEX14, RAD51L1, SRGAP2D and STXBP4). We next developed a Bayesian approach to evaluate, for each SNP, the overlap between the signal of association with breast cancer and the signal of association with alternative splicing. At one locus (SRGAP2D), this method eliminated the possibility that the breast cancer risk and the alternate splicing event were due to the same causal SNP. Lastly, at two loci, we identified the likely causal SNP for the alternative splicing event, and at one, functionally validated the effect of that SNP on alternative splicing using a minigene reporter assay. Our results suggest that the regulation of differential transcript isoform expression is the functional mechanism of some breast cancer risk SNPs and that we can use these associations to identify causal SNPs, target genes and the specific transcripts that may mediate breast cancer risk.

Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

Genome-wide association studies (GWASs) have identified hundreds of susceptibility genes, including shared associations across clinically distinct autoimmune diseases. We performed an inverse χ(2) meta-analysis across ten pediatric-age-of-onset autoimmune diseases (pAIDs) in a case-control study including more than 6,035 cases and 10,718 shared population-based controls. We identified 27 genome-wide significant loci associated with one or more pAIDs, mapping to in silico-replicated autoimmune-associated genes (including IL2RA) and new candidate loci with established immunoregulatory functions such as ADGRL2, TENM3, ANKRD30A, ADCY7 and CD40LG. The pAID-associated single-nucleotide polymorphisms (SNPs) were functionally enriched for deoxyribonuclease (DNase)-hypersensitivity sites, expression quantitative trait loci (eQTLs), microRNA (miRNA)-binding sites and coding variants. We also identified biologically correlated, pAID-associated candidate gene sets on the basis of immune cell expression profiling and found evidence of genetic sharing. Network and protein-interaction analyses demonstrated converging roles for the signaling pathways of type 1, 2 and 17 helper T cells (TH1, TH2 and TH17), JAK-STAT, interferon and interleukin in multiple autoimmune diseases.

Epistasis amongst PTPN2 and genes of the vitamin D pathway contributes to risk of juvenile idiopathic arthritis

Juvenile idiopathic arthritis (JIA) is a leading cause of childhood-onset disability. Although epistasis (gene-gene interaction) is frequently cited as an important component of heritability in complex diseases such as JIA, there is little compelling evidence that demonstrates such interaction. PTPN2, a vitamin D responsive gene, is a confirmed susceptibility gene in JIA, and PTPN2 has been suggested to interact with vitamin D pathway genes in type 1 diabetes. We therefore, tested for evidence of epistasis amongst PTPN2 and the vitamin D pathway genes GC, VDR, CYP24A1, CYP2R1, and DHCR7 in two independent JIA case-control samples (discovery and replication). In the discovery sample (318 cases, 556 controls), we identified evidence in support of epistasis across six gene-gene combinations (e.g., GC rs1155563 and PTPN2 rs2542151, ORint=0.45, p=0.00085). Replication was obtained for three of these combinations. That is, for GC and PTPN2, CYP2R1 and VDR, and VDR and PTPN2, similar epistasis was observed using the same SNPs or correlated proxies in an independent JIA case-control sample (1008 cases, 9287 controls). Using SNP data imputed across a 4 MB region spanning each gene, we obtained highly significant evidence for epistasis amongst all 6 gene-gene combinations identified in the discovery sample (p-values ranging from 5.6×10(-9) to 7.5×10(-7)). This is the first report of epistasis in JIA risk. Epistasis amongst PTPN2 and vitamin D pathway genes was both demonstrated and replicated.

Second-generation Irish genome-wide association study for amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a heritable neurological disease for which the underlying genetic etiology is only partially understood. In Ireland, 83%-90% of cases are currently unexplained. Through large international collaborations, genome-wide association studies (GWASs) have succeeded in identifying a number of genomic loci that contribute toward ALS risk and age at onset. However, for the large proportion of risk that remains unexplained, population specificity of pathogenic variants could interfere with the detection of disease-associated loci. Single-population studies are therefore an important complement to larger international collaborations. In this study, we conduct a GWAS for ALS risk and age at onset in a large Irish ALS case-control cohort, using genome-wide imputation to increase marker density. Despite being adequately powered to detect associations of modest effect size, the study did not identify any locus associated with ALS risk or age at onset above the genome-wide significance threshold. Several speculative associations were, however, identified at loci that have been previously implicated in ALS. The lack of any clear association supports the conclusion that ALS is likely to be caused by multiple rare genetic risk factors. The findings of the present study highlight the importance of ongoing genetic research into the cause of ALS and its likely future challenges.

HapTree: a novel Bayesian framework for single individual polyplotyping using NGS data

As the more recent next-generation sequencing (NGS) technologies provide longer read sequences, the use of sequencing datasets for complete haplotype phasing is fast becoming a reality, allowing haplotype reconstruction of a single sequenced genome. Nearly all previous haplotype reconstruction studies have focused on diploid genomes and are rarely scalable to genomes with higher ploidy. Yet computational investigations into polyploid genomes carry great importance, impacting plant, yeast and fish genomics, as well as the studies of the evolution of modern-day eukaryotes and (epi)genetic interactions between copies of genes. In this paper, we describe a novel maximum-likelihood estimation framework, HapTree, for polyploid haplotype assembly of an individual genome using NGS read datasets. We evaluate the performance of HapTree on simulated polyploid sequencing read data modeled after Illumina sequencing technologies. For triploid and higher ploidy genomes, we demonstrate that HapTree substantially improves haplotype assembly accuracy and efficiency over the state-of-the-art; moreover, HapTree is the first scalable polyplotyping method for higher ploidy. As a proof of concept, we also test our method on real sequencing data from NA12878 (1000 Genomes Project) and evaluate the quality of assembled haplotypes with respect to trio-based diplotype annotation as the ground truth. The results indicate that HapTree significantly improves the switch accuracy within phased haplotype blocks as compared to existing haplotype assembly methods, while producing comparable minimum error correction (MEC) values. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2–5.

While human and other eukaryotic genomes typically contain two copies of every chromosome, plants, yeast and fish such as salmon can have strictly more than two copies of each chromosome. By running standard genotype calling tools, it is possible to accurately identify the number of “wild type” and “mutant” alleles (A, C, G, or T) for each single-nucleotide polymorphism (SNP) site. However, in the case of two heterozygous SNP sites, genotype calling tools cannot determine whether “mutant” alleles from different SNP loci are on the same or different chromosomes. While the former would be healthy, in many cases the latter can cause loss of function; it is therefore necessary to identify the phase—the copies of a chromosome on which the mutant alleles occur—in addition to the genotype. This necessitates efficient algorithms to obtain accurate and comprehensive phase information directly from the next-generation-sequencing read data in higher ploidy species. We introduce an efficient statistical method for this task and show that our method significantly outperforms previous ones, in both accuracy and speed, for phasing triploid and higher ploidy genomes. Our method performs well on human diploid genomes as well, as demonstrated by our improved phasing of the well known NA12878 (1000 Genomes Project).

Breakdown of methods for phasing and imputation in the presence of double genotype sharing

In genome-wide association studies, results have been improved through imputation of a denser marker set based on reference haplotypes and phasing of the genotype data. To better handle very large sets of reference haplotypes, pre-phasing with only study individuals has been suggested. We present a possible problem which is aggravated when pre-phasing strategies are used, and suggest a modification avoiding the resulting issues with application to the MaCH tool, although the underlying problem is not specific to that tool. We evaluate the effectiveness of our remedy to a subset of Hapmap data, comparing the original version of MaCH and our modified approach. Improvements are demonstrated on the original data (phase switch error rate decreasing by 10%), but the differences are more pronounced in cases where the data is augmented to represent the presence of closely related individuals, especially when siblings are present (30% reduction in switch error rate in the presence of children, 47% reduction in the presence of siblings). The main conclusion of this investigation is that existing statistical methods for phasing and imputation of unrelated individuals might give results of sub-par quality if a subset of study individuals nonetheless are related. As the populations collected for general genome-wide association studies grow in size, including relatives might become more common. If a general GWAS framework for unrelated individuals would be employed on datasets with some related individuals, such as including familial data or material from domesticated animals, caution should also be taken regarding the quality of haplotypes. Our modification to MaCH is available on request and straightforward to implement. We hope that this mode, if found to be of use, could be integrated as an option in future standard distributions of MaCH.

An integrative variant analysis pipeline for accurate genotype/haplotype inference in population NGS data

Next-generation sequencing is a powerful approach for discovering genetic variation. Sensitive variant calling and haplotype inference from population sequencing data remain challenging. We describe methods for high-quality discovery, genotyping, and phasing of SNPs for low-coverage (approximately 5×) sequencing of populations, implemented in a pipeline called SNPTools. Our pipeline contains several innovations that specifically address challenges caused by low-coverage population sequencing: (1) effective base depth (EBD), a nonparametric statistic that enables more accurate statistical modeling of sequencing data; (2) variance ratio scoring, a variance-based statistic that discovers polymorphic loci with high sensitivity and specificity; and (3) BAM-specific binomial mixture modeling (BBMM), a clustering algorithm that generates robust genotype likelihoods from heterogeneous sequencing data. Last, we develop an imputation engine that refines raw genotype likelihoods to produce high-quality phased genotypes/haplotypes. Designed for large population studies, SNPTools' input/output (I/O) and storage aware design leads to improved computing performance on large sequencing data sets. We apply SNPTools to the International 1000 Genomes Project (1000G) Phase 1 low-coverage data set and obtain genotyping accuracy comparable to that of SNP microarray.

Genotype-based test in mapping cis-regulatory variants from allele-specific expression data

Identifying and understanding the impact of gene regulatory variation is of considerable importance in evolutionary and medical genetics; such variants are thought to be responsible for human-specific adaptation and to have an important role in genetic disease. Regulatory variation in cis is readily detected in individuals showing uneven expression of a transcript from its two allelic copies, an observation referred to as allelic imbalance (AI). Identifying individuals exhibiting AI allows mapping of regulatory DNA regions and the potential to identify the underlying causal genetic variant(s). However, existing mapping methods require knowledge of the haplotypes, which make them sensitive to phasing errors. In this study, we introduce a genotype-based mapping test that does not require haplotype-phase inference to locate regulatory regions. The test relies on partitioning genotypes of individuals exhibiting AI and those not expressing AI in a 2×3 contingency table. The performance of this test to detect linkage disequilibrium (LD) between a potential regulatory site and a SNP located in this region was examined by analyzing the simulated and the empirical AI datasets. In simulation experiments, the genotype-based test outperforms the haplotype-based tests with the increasing distance separating the regulatory region from its regulated transcript. The genotype-based test performed equally well with the experimental AI datasets, either from genome-wide cDNA hybridization arrays or from RNA sequencing. By avoiding the need of haplotype inference, the genotype-based test will suit AI analyses in population samples of unknown haplotype structure and will additionally facilitate the identification of cis-regulatory variants that are located far away from the regulated transcript.

Genome-wide association scan and phased haplotype construction for quantitative trait loci affecting boar taint in three pig breeds

Background

Boar taint is the undesirable smell and taste of pork meat derived from some entire male pigs. The main causes of boar taint are the two compounds androstenone and skatole (3-methyl-indole). The steroid androstenone is a sex pheromone produced in the testis of the boars. Skatole is produced from tryptophan by bacteria in the intestine of the pigs. In many countries pigs are castrated as piglets to avoid boar taint, however, this is undesirable for animal welfare reasons. Genetic variations affecting the level of boar taint have previously been demonstrated in many breeds. In the study presented in this paper, markers and haplotypes, which can be applied to DNA-based selection schemes in order to reduce or eliminate the boar taint problem, are identified.

Results

Approximately 30,000 SNPs segregating in 923 boars from three Danish breeds; Duroc, Landrace, and Yorkshire, were used to conduct genome wide association studies of boar taint compounds. At 46 suggestive quantitative trait loci (QTL), 25 haplotypes and three single markers with effects were identified. Furthermore, 40% of the haplotypes mapped to previously identified regions. Haplotypes were also analysed for effects of slaughter weight and meat content. The most promising haplotype was identified on Sus scrofa chromosome 1. The gain in fixed effect of having this haplotype on level of androstenone in Landrace was identified to be high (1.279 μg/g). In addition, this haplotype explained 16.8% of the phenotypic variation within the trait. The haplotype was identified around the gene CYB5A which is known to have an indirect impact on the amount of androstenone. In addition to CYB5A, the genes SRD5A2, LOC100518755, and CYP21A2 are candidate genes for other haplotypes affecting androstenone, whereas, candidate genes for the indolic compounds were identified to be SULT1A1 and CYP2E1.

Conclusions

Despite the small sample size, a total of 25 haplotypes and three single markers were identified including genomic regions not previously reported. The haplotypes that were analysed showed large effects on trait level. However, little overlap of QTL between breeds was observed.

Haplotype inference

The information carried by combination of alleles on the same chromosome, called haplotypes, is of crucial interest in several fields of modern genetics as population genetics or association studies. However, this information is usually lost by sequencing and needs, therefore, to be recovered by inference. In this chapter, we give a brief overview on the methods able to tackle this problem and some practical concerns to apply them on real data.

Methylenetetrahydrofolate reductase genetic polymorphisms and toxicity to 5-FU-based chemoradiation in rectal cancer

BACKGROUND

There is a large degree of variation in tumour response and host toxicities associated with neoadjuvant chemoradiation for rectal cancer patients. We performed a complimentary pharmacogenetic study to investigate germline polymorphisms of genes involved in 5-fluorouracil (5-FU) and irinotecan pathways and their potential association with clinical outcomes and toxicities from neoadjuvant chemoradiation in patients with rectal cancer treated in a prospective genotype-directed study.

METHODS

The germline DNA of 131 patients was genotyped for 10 variants in TYMS, MTHFR, DPYD, UGT1A1, ABCC1 and SLCO1B1 genes. Ninety-six patients were treated with 5-FU/radiotherapy (RT) and 35 received 5-FU/RT/irinotecan. Relationships between genetic variants and adverse events, tumour response, overall and disease-free survivals were assessed.

RESULTS

MTHFR 1298A>C and MTHFR diplotypes (for 677C>T and 1298A>C) were associated with chemoradiation-related toxicity when 5-FU was used alone. MTHFR haplotypes (677C-1298C) and diplotypes (CA-TA and TA-TA) showed, respectively, a protective and a negative effect on the incidence of severe diarrhoea or mucositis. No association was observed between genetic markers and drug response.

CONCLUSION

MTHFR polymorphisms can potentially predict toxicity in patients treated with 5-FU as a single chemotherapeutic drug.

Haplotype phasing: existing methods and new developments

Determination of haplotype phase is becoming increasingly important as we enter the era of large-scale sequencing because many of its applications, such as imputing low-frequency variants and characterizing the relationship between genetic variation and disease susceptibility, are particularly relevant to sequence data. Haplotype phase can be generated through laboratory-based experimental methods, or it can be estimated using computational approaches. We assess the haplotype phasing methods that are available, focusing in particular on statistical methods, and we discuss the practical aspects of their application. We also describe recent developments that may transform this field, particularly the use of identity-by-descent for computational phasing.

SNiPlay: a web-based tool for detection, management and analysis of SNPs. Application to grapevine diversity projects

BACKGROUND

High-throughput re-sequencing, new genotyping technologies and the availability of reference genomes allow the extensive characterization of Single Nucleotide Polymorphisms (SNPs) and insertion/deletion events (indels) in many plant species. The rapidly increasing amount of re-sequencing and genotyping data generated by large-scale genetic diversity projects requires the development of integrated bioinformatics tools able to efficiently manage, analyze, and combine these genetic data with genome structure and external data.

RESULTS

In this context, we developed SNiPlay, a flexible, user-friendly and integrative web-based tool dedicated to polymorphism discovery and analysis. It integrates:1) a pipeline, freely accessible through the internet, combining existing softwares with new tools to detect SNPs and to compute different types of statistical indices and graphical layouts for SNP data. From standard sequence alignments, genotyping data or Sanger sequencing traces given as input, SNiPlay detects SNPs and indels events and outputs submission files for the design of Illumina's SNP chips. Subsequently, it sends sequences and genotyping data into a series of modules in charge of various processes: physical mapping to a reference genome, annotation (genomic position, intron/exon location, synonymous/non-synonymous substitutions), SNP frequency determination in user-defined groups, haplotype reconstruction and network, linkage disequilibrium evaluation, and diversity analysis (Pi, Watterson's Theta, Tajima's D).Furthermore, the pipeline allows the use of external data (such as phenotype, geographic origin, taxa, stratification) to define groups and compare statistical indices.2) a database storing polymorphisms, genotyping data and grapevine sequences released by public and private projects. It allows the user to retrieve SNPs using various filters (such as genomic position, missing data, polymorphism type, allele frequency), to compare SNP patterns between populations, and to export genotyping data or sequences in various formats.

CONCLUSIONS

Our experiments on grapevine genetic projects showed that SNiPlay allows geneticists to rapidly obtain advanced results in several key research areas of plant genetic diversity. Both the management and treatment of large amounts of SNP data are rendered considerably easier for end-users through automation and integration. Current developments are taking into account new advances in high-throughput technologies.SNiPlay is available at: http://sniplay.cirad.fr/.

The importance of phase information for human genomics

Contemporary sequencing studies often ignore the diploid nature of the human genome because they do not routinely separate or 'phase' maternally and paternally derived sequence information. However, many findings - both from recent studies and in the more established medical genetics literature - indicate that relationships between human DNA sequence and phenotype, including disease, can be more fully understood with phase information. Thus, the existing technological impediments to obtaining phase information must be overcome if human genomics is to reach its full potential.

Multiple-cohort genetic association study reveals CXCR6 as a new chemokine receptor involved in long-term nonprogression to AIDS

BACKGROUND

The compilation of previous genomewide association studies of AIDS shows a major polymorphism in the HCP5 gene associated with both control of the viral load and long-term nonprogression (LTNP) to AIDS.

METHODS

To look for genetic variants that affect LTNP without necessary control of the viral load, we reanalyzed the genomewide data of the unique LTNP Genomics of Resistance to Immunodeficiency Virus (GRIV) cohort by excluding "elite controller" patients, who were controlling the viral load at very low levels (<100 copies/mL).

RESULTS

The rs2234358 polymorphism in the CXCR6 gene was the strongest signal (P=2.5 x 10(-7); odds ratio, 1.85) obtained for the genomewide association study comparing the 186 GRIV LTNPs who were not elite controllers with 697 uninfected control subjects. This association was replicated in 3 additional independent European studies, reaching genomewide significance of P(combined)=9.7 x 10(-10). This association with LTNP is independent of the CCR2-CCR5 locus and the HCP5 polymorphisms.

CONCLUSIONS

The statistical significance, the replication, and the magnitude of the association demonstrate that CXCR6 is likely involved in the molecular etiology of AIDS and, in particular, in LTNP, emphasizing the power of extreme-phenotype cohorts. CXCR6 is a chemokine receptor that is known as a minor coreceptor in human immunodeficiency virus type 1 infection but could participate in disease progression through its role as a mediator of inflammation.