Strategies for phasing and imputation in a population isolate.

In the search for genetic associations with complex traits, population isolates offer the advantage of reduced genetic and environmental heterogeneity. In addition, cost-efficient next-generation association approaches have been proposed in these populations where only a subsample of representative individuals is sequenced and then genotypes are imputed into the rest of the population. Gene mapping in such populations thus requires high-quality genetic imputation and preliminary phasing. To identify an effective study design, we compare by simulation a range of phasing and imputation software and strategies. We simulated 1,115,604 variants on chromosome 10 for 477 members of the large complex pedigree of Campora, a village within the established isolate of Cilento in southern Italy. We assessed the phasing performance of identical by descent based software ALPHAPHASE and SLRP, LD-based software SHAPEIT2, SHAPEIT3, and BEAGLE, and new software EAGLE that combines both methodologies. For imputation we compared IMPUTE2, IMPUTE4, MINIMAC3, BEAGLE, and new software PBWT. Genotyping errors and missing genotypes were simulated to observe their effects on the performance of each software. Highly accurate phased data were achieved by all software with SHAPEIT2, SHAPEIT3, and EAGLE2 providing the most accurate results. MINIMAC3, IMPUTE4, and IMPUTE2 all performed strongly as imputation software and our study highlights the considerable gain in imputation accuracy provided by a genome sequenced reference panel specific to the population isolate.

Interactive effect between ATPase-related genes and early-life tobacco smoke exposure on bronchial hyper-responsiveness detected in asthma-ascertained families.

BACKGROUND: A positional cloning study of bronchial hyper-responsiveness (BHR) at the 17p11 locus in the French Epidemiological study on the Genetics and Environment of Asthma (EGEA) families showed significant interaction between early-life environmental tobacco smoke (ETS) exposure and genetic variants located in DNAH9. This gene encodes the heavy chain subunit of axonemal dynein, which is involved with ATP in the motile cilia function.Our goal was to identify genetic variants at other genes interacting with ETS in BHR by investigating all genes belonging to the 'ATP-binding' and 'ATPase activity' pathways which include DNAH9, are targets of cigarette smoke and play a crucial role in the airway inflammation. METHODS: Family-based interaction tests between ETS-exposed and unexposed BHR siblings were conducted in 388 EGEA families. Twenty single-nucleotide polymorphisms (SNP) showing interaction signals (p≤5.10-3) were tested in the 253 Saguenay-Lac-Saint-Jean (SLSJ) families. RESULTS: One of these SNPs was significantly replicated for interaction with ETS in SLSJ families (p=0.003). Another SNP reached the significance threshold after correction for multiple testing in the combined analysis of the two samples (p=10-5). Results were confirmed using both a robust log-linear test and a gene-based interaction test. CONCLUSION: The SNPs showing interaction with ETS belong to the ATP8A1 and ABCA1 genes, which play a role in the maintenance of asymmetry and homeostasis of lung membrane lipids.

Clinical and demographic factors and outcome of amyotrophic lateral sclerosis in relation to population ancestral origin.

BACKGROUND: To review how the phenotype and outcome of amyotrophic lateral sclerosis (ALS) change with variations in population ancestral origin (PAO). Knowledge of how PAO modifies ALS phenotype may provide important insight into the risk factors and pathogenic mechanisms of the disease. METHODS: We performed a systematic review and meta-analysis of the literature concerning differences in phenotype and outcome of ALS that relate to PAO. RESULTS: A review of 3111 records identified 78 population-based studies. The 40 that were included covered 40 geographical areas in 10 subcontinents. Around 12,700 ALS cases were considered. The results highlight the phenotypic heterogeneity of ALS at time of onset [age, sex ratio (SR), bulbar onset], age at diagnosis, occurrence of comorbidities in the first year after diagnosis, and outcome (survival). Subcontinent is a major explanatory factor for the variability of the ALS phenotype in population-based studies. Some markers of ALS phenotype were homogeneously distributed in western countries (SR, mean age at onset/diagnosis) but their distributions in other subcontinents were remarkably different. Other markers presented variations in European subcontinents (familial ALS, bulbar onset) and in other continents. As a consequence, ALS outcome strongly varied, with a median survival time from onset ranging from 24 months (Northern Europe) to 48 months (Central Asia). DISCUSSION: This review sets the scene for a collaborative study involving a wide international consortium to investigate, using a standard methodology, the link between ancestry, environment, and ALS phenotype.

A New Correction for Multiple Testing in Gene-Gene Interaction Studies.

A major problem in gene-gene interaction studies in large marker panels is how to correct for multiple testing while accounting for the dependence between marker pairs due to the presence of linkage disequilibrium. The "gold standard" approach is to perform permutations of case/control labels. However, this is often not feasible in practice, due to computational demands. Here, we propose a correction based on the effective number of independent tests of interaction between marker pairs. This number depends on the effective number of independent single-marker tests. We tested its validity using simulated samples, as well as that of another correction of marker pair tests. We showed that our approach was valid while the other correction strongly underestimated the effective number of independent tests. Our method provides estimates of the effective number of independent tests close to those reported in the literature for a Genome-Wide Interaction Study on a 550K chip. Our correction method is quick and simple, and can be applied whatever the marker panel and the underlying linkage disequilibrium pattern.

FSuite: exploiting inbreeding in dense SNP chip and exome data.

UNLABELLED: FSuite is a user-friendly pipeline developed for exploiting inbreeding information derived from human genomic data. It can make use of single nucleotide polymorphism chip or exome data. Compared with other software, the advantage of FSuite is that it provides a complete suite of scripts to describe and use the inbreeding information. It includes a module to detect inbred individuals and estimate their inbreeding coefficient, a module to describe the proportion of different mating types in the population and the individual probability to be offspring of different mating types that can be useful for population genetic studies. It also allows the identification of shared regions of homozygosity between affected individuals (homozygosity mapping) that can be used to identify rare recessive mutations involved in monogenic or multifactorial diseases. AVAILABILITY AND IMPLEMENTATION: FSuite is developed in Perl and uses R functions to generate graphical outputs. This pipeline is freely available under GNU GPL license at: http://genestat.cephb.fr/software/index.php/FSuite.

Genetic variants in DNA repair pathways and risk of upper aerodigestive tract cancers: combined analysis of data from two genome-wide association studies in European populations.

DNA repair pathways are good candidates for upper aerodigestive tract cancer susceptibility because of their critical role in maintaining genome integrity. We have selected 13 pathways involved in DNA repair representing 212 autosomal genes. To assess the role of these pathways and their associated genes, two European data sets from the International Head and Neck Cancer Epidemiology consortium were pooled, totaling 1954 cases and 3121 controls, with documented demographic, lifetime alcohol and tobacco consumption information. We applied an innovative approach that tests single nucleotide polymorphism (SNP)-sets within DNA repair pathways and then within genes belonging to the significant pathways. We showed an association between the polymerase pathway and oral cavity/pharynx cancers (P-corrected = 4.45 × 10(-) (2)), explained entirely by the association with one SNP, rs1494961 (P = 2.65 × 10(-) (4)), a missense mutation V306I in the second exon of HELQ gene. We also found an association between the cell cycle regulation pathway and esophagus cancer (P-corrected = 1.48 × 10(-) (2)), explained by three SNPs located within or near CSNK1E gene: rs1534891 (P = 1.27 × 10(-) (4)), rs7289981 (P = 3.37 × 10(-) (3)) and rs13054361 (P = 4.09 × 10(-) (3)). As a first attempt to investigate pathway-level associations, our results suggest a role of specific DNA repair genes/pathways in specific upper aerodigestive tract cancer sites.

Comparative power of family-based association strategies to detect disease-causing variants under two-locus models.

Not accounting for interaction in association analyses may reduce the power to detect the variants involved. We investigate the powers of different designs to detect under two-locus models the effect of disease-causing variants among several hundreds of markers using family-based association tests by simulation. This setting reflects realistic situations of exploration of linkage regions or of biological pathways. We define four strategies: (S1) single-marker analysis of all Single Nucleotide Polymorphisms (SNPs), (S2) two-marker analysis of all possible SNPs pairs, (S3) lax preliminary selection of SNPs followed by a two-marker analysis of all selected SNP pairs, (S4) stringent preliminary selection of SNPs, each being later paired with all the SNPs for two-marker analysis. Strategy S2 is never the best design, except when there is an inversion of the gene effect (flip-flop model). Testing individual SNPs (S1) is the most efficient when the two genes act multiplicatively. Designs S3 and S4 are the most powerful for nonmultiplicative models. Their respective powers depend on the level of symmetry of the model. Because the true genetic model is unknown, we cannot conclude that one design outperforms another. The optimal approach would be the two-step strategy (S3 or S4) as it is often the most powerful, or the second best.

Could inbred cases identified in GWAS data succeed in detecting rare recessive variants where affected sib-pairs have failed?

To detect fully penetrant rare recessive variants that could constitute Mendelian subentities of complex diseases, we propose a novel strategy, the HBD-GWAS strategy, which can be applied to genome-wide association study (GWAS) data. This strategy first involves the identification of inbred individuals among cases using the genome-wide SNP data and then focuses on these inbred affected individuals and searches for genomic regions of shared homozygosity by descent that could harbor rare recessive disease-causing variants. In this second step, analogous to homozygosity mapping, a heterogeneity lod-score, HFLOD, is computed to quantify the evidence of linkage provided by the data. In this paper, we evaluate this strategy theoretically under different scenarios and compare its performances with those of linkage analysis using affected sib-pair (ASP) data. If cases affected by these Mendelian subentities are not enriched in the sample of cases, the HBD-GWAS strategy has almost no power to detect them, unless they explain an important part of the disease prevalence. The HBD-GWAS strategy outperforms the ASP linkage strategy only in a very limited number of situations where there exists a strong allelic heterogeneity. When several rare recessive variants within the same gene are involved, the ASP design indeed often fails to detect the gene, whereas, by focusing on inbred individuals using the HBD-GWAS strategy, the gene might be detected provided very large samples of cases are available.

Lung cancer and DNA repair genes: multilevel association analysis from the International Lung Cancer Consortium.

Lung cancer (LC) is the leading cause of cancer-related death worldwide and tobacco smoking is the major associated risk factor. DNA repair is an important process, maintaining genome integrity and polymorphisms in DNA repair genes may contribute to susceptibility to LC. To explore the role of DNA repair genes in LC, we conducted a multilevel association study with 1655 single nucleotide polymorphisms (SNPs) in 211 DNA repair genes using 6911 individuals pooled from four genome-wide case-control studies. Single SNP association corroborates previous reports of association with rs3131379, located on the gene MSH5 (P = 3.57 × 10-5) and returns a similar risk estimate. The effect of this SNP is modulated by histological subtype. On the log-additive scale, the odds ratio per allele is 1.04 (0.84-1.30) for adenocarcinomas, 1.52 (1.28-1.80) for squamous cell carcinomas and 1.31 (1.09-1.57) for other histologies (heterogeneity test: P = 9.1 × 10(-)(3)). Gene-based association analysis identifies three repair genes associated with LC (P < 0.01): UBE2N, structural maintenance of chromosomes 1L2 and POLB. Two additional genes (RAD52 and POLN) are borderline significant. Pathway-based association analysis identifies five repair pathways associated with LC (P < 0.01): chromatin structure, DNA polymerases, homologous recombination, genes involved in human diseases with sensitivity to DNA-damaging agents and Rad6 pathway and ubiquitination. This first international pooled analysis of a large dataset unravels the role of specific DNA repair pathways in LC and highlights the importance of accounting for gene and pathway effects when studying LC.

Genetic association and gene-environment interaction: a new method for overcoming the lack of exposure information in controls.

The use of a reference control panel in genome-wide association studies is an interesting solution to the problem of how to reduce costs. In such designs, data on relevant environmental factors are usually collected only in cases, making it more difficult to deal with potential gene-environment interactions when testing for genetic association. However, under certain circumstances, neglecting an existing interaction with the environment may be detrimental in terms of statistical power to detect the genetic factor. In this paper, the authors propose a novel method based on a multinomial logistic regression model to overcome the lack of environmental exposure information in controls, by contrasting both exposed and unexposed cases with the control sample. For each case group, a genetic effect-size parameter is estimated, and the genetic association and the gene-environment interaction are tested jointly. The authors evaluate the performance of this method through asymptotic computations and simulations of cases and population controls under different models. In the presence of a gene-environment interaction, this approach outperforms other available methods that test for genetic association and gene-environment interaction either separately or jointly. Interestingly, it even has better power than the joint test requiring full knowledge of the environmental information in both cases and controls.

Meta-analysis of genome-wide linkage studies in celiac disease.

OBJECTIVE: A meta-analysis of genome-wide linkage studies allows us to summarize the extensive information available from family-based studies, as the field moves into genome-wide association studies. METHODS: Here we apply the genome scan meta-analysis (GSMA) method, a rank-based, model-free approach, to combine results across eight independent genome-wide linkages performed on celiac disease (CD), including 554 families with over 1,500 affected individuals. We also investigate the agreement between signals we identified from this meta-analysis of linkage studies and those identified from genome-wide association analysis using a hypergeometric distribution. RESULTS: Not surprisingly, the most significant result was obtained in the HLA region. Outside the HLA region, suggestive evidence for linkage was obtained at the telomeric region of chromosome 10 (10q26.12-qter; p = 0.00366), and on chromosome 8 (8q22.2-q24.21; p = 0.00491). Testing signals of association and linkage within bins showed no significant evidence for co-localization of results. CONCLUSION: This meta-analysis allowed us to pool the results from available genome-wide linkage studies and to identify novel regions potentially harboring predisposing genetic variation contributing to CD. This study also shows that linkage and association studies may identify different types of disease-predisposing variants.

Variation in worldwide incidence of amyotrophic lateral sclerosis: a meta-analysis.

Background: To assess the worldwide variation of amyotrophic lateral sclerosis (ALS) incidence, we performed a systematic review and meta-analysis of population-based data published to date. Methods: We reviewed Medline and Embase up to June 2015 and included all population-based studies of newly diagnosed ALS cases, using multiple sources for case ascertainment. ALS crude and standardized incidence (on age and sex using the US 2010 population) were calculated. Random effect meta-analysis and meta-regression were performed using the subcontinent as the main study level covariate. Sources of heterogeneity related to the characteristics of the study population and the study methodology were investigated. Results: Among 3216 records, 44 studies were selected, covering 45 geographical areas in 11 sub-continents. A total of 13 146 ALS cases and 825 million person-years of follow-up (PYFU) were co-nsidered. The overall pooled worldwide crude ALS incidence was at 1.75 (1.55-1.96)/100 000 PYFU; 1.68 (1.50-1.85)/100 000 PYFU after standardization. Heterogeneity was identified in ALS standardized incidence between North Europe [1.89 (1.46-2.32)/100 000 PYFU] and East Asia [0.83 (0.42-1.24)/100 000 PYFU, China and Japan P = 0.001] or South Asia [0.73 (0.58-0.89)/100 000/PYFU Iran, P = 0.02]. Conversely, homogeneous rates have been reported in populations from Europe, North America and New Zealand [pooled ALS standardized incidence of 1.81 (1.66-1.97)/100 000 PYFU for those areas]. Conclusion: This review confirms a heterogeneous distribution worldwide of ALS, and sets the scene to sustain a collaborative study involving a wide international consortium to investigate the link between ancestry, environment and ALS incidence.

Linkage disequilibrium screening for multiple sclerosis implicates JAG1 and POU2AF1 as susceptibility genes in Europeans.

By combining all the data available from the Genetic Analysis of Multiple sclerosis in EuropeanS (GAMES) project, we have been able to identify 17 microsatellite markers showing consistent evidence for apparent association. As might be expected five of these markers map within the Major Histocompatibility Complex (MHC) and are in LD with HLA-DRB1. Individual genotyping of the 12 non-MHC markers confirmed association for three of them--D11S1986, D19S552 and D20S894. Association mapping across the candidate genes implicated by these markers in 937 UK trio families revealed modestly associated haplotypes in JAG1 (p=0.019) on chromosome 20p12.2 and POU2AF1 (p=0.003) on chromosome 11q23.1.

Can whole-exome sequencing data be used for linkage analysis?

Whole-exome sequencing (WES) has become the strategy of choice to identify causal variants in monogenic disorders. However, the list of candidate variants can be quite large, including false positives generated by sequencing errors. To reduce this list of candidate variants to the most relevant ones, a cost-effective strategy would be to focus on regions of linkage identified through linkage analysis conducted with common polymorphisms present in WES data. However, the non-uniform exon coverage of the genome and the lack of knowledge on the power of this strategy have largely precluded its use so far. To compare the performance of linkage analysis conducted with WES and SNP chip data in different situations, we performed simulations on two pedigree structures with, respectively, a dominant and a recessive trait segregating. We found that the performance of the two sets of markers at excluding regions of the genome were very similar, and there was no real gain at using SNP chip data compared with using the common SNPs extracted from WES data. When analyzing the real WES data available for these two pedigrees, we found that the linkage information derived from the WES common polymorphisms was able to reduce by half the list of candidate variants identified by a simple filtering approach. Conducting linkage analysis with WES data available on pedigrees and excluding among the candidate variants those that fall in excluded linkage regions is thus a powerful and cost-effective strategy to reduce the number of false-positive candidate variants.

Impact of the diagnosis definition on linkage detection.

Previous genome scan linkage analyses of the disease Kofendrerd Personality Disorder (KPD) with microsatellites led to detect some regions on chromosomes 1, 3, 5, and 9 that were identical for the three populations AI, KA, and DA but with large differences in significance levels. These differences in results may be explained by the different diagnosis definitions depending on the presence/absence of 12 traits that were used in the 3 populations AI, KA, and DA. Heterogeneity of linkage was thus investigated here according to the absence/presence of each of the 12 traits in the 3 populations. For this purpose, two methods, the triangle test statistic and the predivided sample test were applied to search for genetic heterogeneity. Three regions with a strong heterogeneity of linkage were detected: the region on chromosome 1 according to the presence/absence of the traits a and b, the region on chromosome 3 for the trait b, and the region on chromosome 9 for the traits k and l. These 3 regions were the same as those detected by linkage analyses. No novel region was detected by the heterogeneity tests. Concerning chromosome 1, linkage analyses showed a much stronger evidence of linkage for traits a and b and for a combination of these traits than for KPD. Moreover, there was no indication of linkage to any of the other traits used to define the diagnosis of KPD. A genetic factor located on the chromosome 1 may have been detected here which would be involved specifically in traits a and b or in a combination of these traits.

Detection of susceptibility loci by genome-wide linkage analysis.

The objective of this study is to evaluate the efficacy of a model-free linkage statistics for finding evidence of linkage using two different maps and to illustrate how the comparison of results from several populations might provide insight into the underlying genetic etiology of the disease of interest. The results obtained in terms of detection of the risk loci and threshold for declaring linkage and power are very similar for a dense SNP map and a sparser microsatellite map. The populations differed in terms of family ascertainment and diagnosis criteria, leading to different power to detect the individual underlying disease loci. Our results for the individual replicates are consistent with the disease model used in the simulation.

Modeling the effect of a genetic factor for a complex trait in a simulated population.

Genetic Analysis Workshop 14 simulated data have been analyzed with MASC(marker association segregation chi-squares) in which we implemented a bootstrap procedure to provide the variation intervals of parameter estimates. We model here the effect of a genetic factor, S, for Kofendrerd Personality Disorder in the region of the marker C03R0281 for the Aipotu population. The goodness of fit of several genetic models with two alleles for one locus has been tested. The data are not compatible with a direct effect of a single-nucleotide polymorphism (SNP) (SNP 16, 17, 18, 19 of pack 153) in the region. Therefore, we can conclude that the functional polymorphism has not been typed and is in linkage disequilibrium with the four studied SNPs. We obtained very large variation intervals both of the disease allele frequency and the degree of dominance. The uncertainty of the model parameters can be explained first, by the method used, which models marginal effects when the disease is due to complex interactions, second, by the presence of different sub-criteria used for the diagnosis that are not determined by S in the same way, and third, by the fact that the segregation of the disease in the families was not taken into account. However, we could not find any model that could explain the familial segregation of the trait, namely the higher proportion of affected parents than affected sibs.

High level of inbreeding in final phase of 1000 Genomes Project.

The 1000 Genomes Project provides a unique source of whole genome sequencing data for studies of human population genetics and human diseases. The last release of this project includes more than 2,500 sequenced individuals from 26 populations. Although relationships among individuals have been investigated in some of the populations, inbreeding has never been studied. In this article, we estimated the genomic inbreeding coefficient of each individual and found an unexpected high level of inbreeding in 1000 Genomes data: nearly a quarter of the individuals were inbred and around 4% of them had inbreeding coefficients similar or greater than the ones expected for first-cousin offspring. Inbred individuals were found in each of the 26 populations, with some populations showing proportions of inbred individuals above 50%. We also detected 227 previously unreported pairs of close relatives (up to and including first-cousins). Thus, we propose subsets of unrelated and outbred individuals, for use by the scientific community. In addition, because admixed populations are present in the 1000 Genomes Project, we performed simulations to study the robustness of inbreeding coefficient estimates in the presence of admixture. We found that our multi-point approach (FSuite) was quite robust to admixture, unlike single-point methods (PLINK).

Homozygous STIL mutation causes holoprosencephaly and microcephaly in two siblings.

Holoprosencephaly (HPE) is a frequent congenital malformation of the brain characterized by impaired forebrain cleavage and midline facial anomalies. Heterozygous mutations in 14 genes have been identified in HPE patients that account for only 30% of HPE cases, suggesting the existence of other HPE genes. Data from homozygosity mapping and whole-exome sequencing in a consanguineous Turkish family were combined to identify a homozygous missense mutation (c.2150G>A; p.Gly717Glu) in STIL, common to the two affected children. STIL has a role in centriole formation and has previously been described in rare cases of microcephaly. Rescue experiments in U2OS cells showed that the STIL p.Gly717Glu mutation was not able to fully restore the centriole duplication failure following depletion of endogenous STIL protein indicating the deleterious role of the mutation. In situ hybridization experiments using chick embryos demonstrated that expression of Stil was in accordance with a function during early patterning of the forebrain. It is only the second time that a STIL homozygous mutation causing a recessive form of HPE was reported. This result also supports the genetic heterogeneity of HPE and increases the panel of genes to be tested for HPE diagnosis.

Meta and pooled analysis of European coeliac disease data.

Four full genome scans have been carried out by the partners of the European cluster on coeliac disease as well as follow-up studies of candidate regions. No region outside HLA showed significant linkage to the disease in any single study. We first applied a meta-analysis based on a modification of Genome Screen Meta-Analysis to take into account the different linkage statistics, the arbitrariness of bin cutoff points, as well as the sample size of each study. We then performed a pooled linkage analysis of all families and raw genotypes. Besides the HLA region, already known to harbour a risk factor for coeliac disease, both approaches leave very little doubt on the presence of a genetic risk factor in the 5q31-33 region. This region was suggested by several individual studies, but did not reach statistical values high enough to be conclusive when data sets were analysed separately.