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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., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Genetic studies of eczema have identified many genes, which explain only 14% of the heritability. Missing heritability may be partly due to ignored gene-gene (G-G) interactions., Objective: Our aim was to detect new interacting genes involved in eczema., Methods: The search for G-G interaction in eczema was conducted using a two-step approach, which included as a first step, a biological selection of genes, which are involved either in the skin or epidermis development or in the collagen metabolism, and as a second step, an interaction analysis of the selected genes. Analyses were carried out at both SNP and gene levels in three asthma-ascertained family samples: the discovery dataset of 388 EGEA (Epidemiological study on the Genetics and Environment of Asthma) families and the two replication datasets of 253 SLSJ (Saguenay-Lac-Saint-Jean) families and 207 MRCA (Medical Research Council) families., Results: One pair of SNPs, rs2287807 in COL5A3 and rs17576 in MMP9, that were detected in EGEA at P ≤ 10 -5 showed significant interaction by meta-analysis of EGEA, SLSJ and MRCA samples (P = 1.1 × 10 -8 under the significant threshold of 10 -7 ). Gene-based analysis confirmed strong interaction between COL5A3 and MMP9 (P = 4 × 10 -8 under the significant threshold of 4 × 10 -6 ) by meta-analysis of the three datasets. When stratifying the data on asthma, this interaction remained in both groups of asthmatic and non-asthmatic subjects., Conclusion: This study identified significant interaction between two new genes, COL5A3 and MMP9, which may be accounted for by a degradation of COL5A3 by MMP9 influencing eczema susceptibility. Further confirmation of this interaction as well as functional studies is needed to better understand the role of these genes in eczema., (© 2017 John Wiley & Sons Ltd.)

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., (© 2018 WILEY PERIODICALS, INC.)

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., (© The Author 2016. Published by Oxford University Press on behalf of the International Epidemiological Association)

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.

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.

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).

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., (© 2015 John Wiley & Sons Ltd/University College London.)

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.

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., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

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., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

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., (© 2012 Wiley Periodicals, Inc.)

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.

Genome-wide association studies (GWAS), although efficient to detect genes involved in complex diseases, are not designed to measure the real effect of the genes. This is illustrated here by the example of IL2RA in multiple sclerosis (MS). Association between IL2RA and MS is clearly established, although the functional variation is still unknown: the effect of IL2RA might be better described by several SNPs than by a single one. This study investigates whether a pair of SNPs better explains the observed linkage and association data than a single SNP. In total, 522 trio families and 244 affected sib-pairs were typed for 26 IL2RA SNPs. For each SNP and pairs of SNPs, the phased genotypes of patients and controls were compared to determine the SNP set offering the best risk discrimination. Consistency between the genotype risks provided by the retained set and the identical by descent allele sharing in affected sib-pairs was assessed. After controlling for multiple testing, the set of SNPs rs2256774 and rs3118470, provides the best discrimination between the case and control genotype distributions (P-corrected=0.009). The relative risk between the least and most at-risk genotypes is 3.54 with a 95% confidence interval of [2.14-5.94]. Furthermore, the linkage information provided by the allele sharing between affected sibs is consistent with the retained set (P=0.80) but rejects the SNP reported in the literature (P=0.006). Establishing a valid modeling of a disease gene is essential to test its potential interaction with other genes and to reconstruct the pathophysiological pathways.

Although variations in allele frequencies at common SNPs have been extensively studied in different populations, little is known about the stratification of rare variants and its impact on association tests. In this paper, we used Affymetrix 500K genotype data from the WTCCC to investigate if variants in three different frequency categories (below 1%, between 1 and 5%, above 5%) show different stratification patterns in the UK population. We found that these patterns are indeed different. The top principal component extracted from the rare variant category shows poor correlations with any principal component or combination of principal components from the low frequency or common variant categories. These results could suggest that a suitable solution to avoid false positive association due to population stratification would involve adjusting for the respective PCs when testing for variants in different allele frequency categories. However, we found this was not the case both on type 2 diabetes data and on simulated data. Indeed, adjusting rare variant association tests on PCs derived from rare variants does no better to correct for population stratification than adjusting on PCs derived from more common variants. Mixed models perform slightly better for low frequency variants than PC based adjustments but less well for the rarest variants. These results call for the need of new methodological developments specifically devoted to address rare variant stratification issues in association tests.

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., (Copyright © 2013 S. Karger AG, Basel.)

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.

Both genetic and environmental factors contribute to multiple sclerosis, the most common neurodegenerative disorder with onset in young adults. The objective of the current study is, based on the hypothesis that environmentally predisposed individuals are at risk for multiple sclerosis, to investigate whether they also carry genetic variants within the vitamin D machinery. Using medical files and DNA samples from 583 trios (a patient and both parents) of the French Multiple Sclerosis Genetics Group as well as data from the French Statistics Bureau, we aimed to assess whether: (1) a seasonality of birth was observed in French multiple sclerosis patients; (2) three single nucleotide polymorphisms within the promoter region of the vitamin D receptor were associated with multiple sclerosis susceptibility; and (3) the combination of a high risk month of birth and vitamin D receptor polymorphisms were correlated to multiple sclerosis incidence. We observed a significantly reduced number of individuals born in November who were later diagnosed as multiple sclerosis patients. However, we found no association between the three studied vitamin D receptor polymorphisms and multiple sclerosis. In conclusion, our data suggest that high levels of vitamin D during the third trimester of pregnancy could be a protective factor for multiple sclerosis.

A recent investigation reported, for the first time, an association between variants in the IFIH1-GCA-KCNH7 locus and multiple sclerosis (MS). We sought to replicate this genetic association in MS with a new independent MS cohort composed of French Caucasian MS trio families. The two most significant IFIH1 single nucleotide polymorphisms, rs1990760 and rs2068330, reported as involved in MS susceptibility, were genotyped in 591 French Caucasian MS trio families, and analyzed using the transmission/disequilibrium test. No association with MS was found (rs1990760, P=0.45 and rs2068330, P=0.27). Similarly, no significant association was detected after stratification for HLA-DRB1*1501 carriers. Reasons that may explain this discrepancy between the original report and our study are discussed.

We consider the problem of detection of modifier genes that lead to variations in a disease-related continuous variable (DRCV), such as the age of onset or a measure of disease severity, in a strategy of candidate genes. We propose a novel method, the ordered transmission disequilibrium test (OTDT), to test for a relation between the clinical heterogeneity expressed by a DRCV and marker genotypes of a candidate gene. The OTDT applies to trio families with one patients and his parents, all three genotyped at a bi-allelic marker M. The OTDT aims to find a critical value of the DRCV which separates the sample of families in two subsamples in which the transmission rates are significantly different. We investigate the power of the method by simulations under various genetic models and covariate distributions and compare it with a linear regression analysis.

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., (Copyright 2009 S. Karger AG, Basel.)

Most of the published works so far have aimed at finding genes associated with multiple sclerosis (MS) susceptibility. Very few studies have attempted to correlate disease features with DNA variants. In a well-characterized sample (651 patients) representative of multiple sclerosis natural history, we engaged a comprehensive study of the role of human leukocyte antigen (HLA) in the course of the disease. We investigated the role of HLA-DRB1*15 allele in samples stratified according to severity evaluated by the Multiple Sclerosis Severity Score (MSSS), time to reach EDSS 6.0 and disease type. We found that HLA-DRB1*15 genotype does not influence MS severity even among patients presenting with a given type of the disease. However, we show for the first time that HLA-DRB1*15 allele modulates the course of MS for relapsing-remitting (RR) onset patients likely by precipitating the secondary progressive (SP) phase.

Multiple sclerosis (MS) is the most common chronic inflammatory neurologic disorder diagnosed in young adults and, due to its chronic course, is responsible for a substantial economic burden. MS is considered to be a multifactorial disease in which both genetic and environmental factors intervene. The well-established human leukocyte antigen (HLA) association does not completely explain the genetic impact on disease susceptibility. However, identification and validation of non-HLA-genes conferring susceptibility to MS has proven to be difficult probably because of the small individual contribution of each of these genes. Recently, associations with two single nucleotide polymorphisms (SNPs) in the IL2RA gene (rs12722489, rs2104286) and one SNP in the IL7RA gene (rs6897932) have been reported by several groups. These three SNPs were genotyped in a French and a German population of MS patients using the hME assay by the matrix-assisted laser desorption/ionization time of flight technology (Sequenom, San Diego, CA, USA). We show that these SNPs do contribute to the risk of MS in these two unrelated European MS patient populations with odds ratios varying from 1.1 to 1.5. The discovery and validation of new genetic risk factors in independent populations may help toward the understanding of MS pathogenesis by providing valuable information on biological pathways to be investigated.

Hereditary spastic paraplegias (HSPs) are genetically and phenotypically heterogeneous. Both "uncomplicated" and "complicated" forms have been described, with autosomal dominant, autosomal recessive, and X-linked inheritance. Hitherto, ten autosomal dominant "uncomplicated" HSP (ADHSP) loci have been mapped. Here, we report linkage of ADHSP with markers of the 8p21.1-q13.3 chromosomal region in a large French family, including 29 examined at-risk individuals. The age at onset varied from 8 to 60 years with a mean of 31.6 +/- 16.4 years. Multipoint and two-point LOD-score calculations as well as haplotype reconstruction in this region gave support to the location of this novel ADHSP locus (SPG37) in a 43.5 cM genetic interval flanked by loci D8S1839 and D8S1795. The region was shared by all definitely (n = 13), probably (n = 3) and possibly (n = 2) affected patients with a maximum LOD score of 4.20 at the D8S601 locus. Two candidate genes, encoding the kinesin family member 13B and neuregulin 1 (isoforms SMDF and GFF2), were screened for mutations, but no disease-causing alterations were identified. Interestingly, another region, on chromosome 10q22.3-23.31, was found to segregate in all affected patients (but not in probably or possibly affected subjects) and in a high proportion of healthy at risk individuals, suggesting that this locus might act as a modifier of the phenotype.

Meckel syndrome (MKS) is a rare autosomal recessive lethal condition characterized by central nervous system malformations, polydactyly, multicystic kidney dysplasia, and ductal changes of the liver. Three loci have been mapped (MKS1-MKS3), and two genes have been identified (MKS1/FLJ20345 and MKS3/TMEM67), whereas the gene at the MKS2 locus remains unknown. To identify new MKS loci, a genomewide linkage scan was performed using 10-cM-resolution microsatellite markers in eight families. The highest heterogeneity LOD score was obtained for chromosome 12, in an interval containing CEP290, a gene recently identified as causative of Joubert syndrome (JS) and isolated Leber congenital amaurosis. In view of our recent findings of allelism, at the MKS3 locus, between these two disorders, CEP290 was considered a candidate, and homozygous or compound heterozygous truncating mutations were identified in four families. Sequencing of additional cases identified CEP290 mutations in two fetuses with MKS and in four families presenting a cerebro-reno-digital syndrome, with a phenotype overlapping MKS and JS, further demonstrating that MKS and JS can be variable expressions of the same ciliopathy. These data identify a fourth locus for MKS (MKS4) and the CEP290 gene as responsible for MKS.

Clinical heterogeneity of a disease may reflect an underlying genetic heterogeneity, which may hinder the detection of trait loci. Consequently, many statistical methods have been developed that allow for the detection of linkage and/or association signals in the presence of heterogeneity.This report describes the work of two parallel investigations into similar approaches to ordered subset analysis, based on an observed covariate, in the framework of family-based association analysis using Genetic Analysis Workshop 15 simulated data.With an appropriate choice of covariate, both approaches allow detection of two loci that are undetectable by the classical transmission-disequilibrium test. For a third locus, detectable by the classical transmission-disequilibrium test, a substantial increase of power of detection is shown.

The group that formed on the theme of linkage analyses of rheumatoid arthritis RA and related phenotypes (Group 10) in the Genetic Analysis Workshop 15 comprised 18 sets of investigators. Two data sets were available: one was a real set provided by the North American Rheumatoid Arthritis Consortium and collaborators in Canada, France (European Consortium Of Rheumatoid Arthritis Families) and the UK; the other was a simulated data set modelled after the real data set. Whereas a majority of the investigators analyzed the RA affection status as a binary phenotype, a few contributions considered data on correlated quantitative traits such as anti-cyclic citrullinated peptide and rheumatoid factor-immunoglobulin M. The different investigators applied a wide spectrum of linkage methods. As expected, most methods could identify the human leukocyfeantigen region on chromosome 6 as a major genetic factor for RA. In addition, some novel chromosomal regions provided significant evidence of linkage in multiple contributions in the group. In this report, we discuss the different strategies explored by the different investigators with the common goal of improving the power to detect linkage., (. (c) 2007 Wiley-Liss, Inc.)

Three LOD score statistics are often used for genome-wide linkage analysis: the maximum LOD score, the LOD score statistic proposed by Kong and Cox, both based on the allele-sharing between affected sib pairs, and the maximization of the LOD score function of Morton on two genetic models and an heterogeneity parameter.Using only identity-by-descent sharing between affected sibs as linkage information, we studied the behavior of these three statistics under the null hypothesis in the rheumatoid arthritis simulated data (Genetic Analysis Workshop 15 Problem 3 - simulating model known). Distributions under the null hypothesis show that identical values of the statistics correspond to very different genome-wide p-values: comparison and interpretation of several linkage statistics cannot be done on the observed value. The Kong and Cox LOD score statistic had slightly better power to detect the HLA region involved in rheumatoid arthritis compared to the other methods. In a second step, we show that performing the analysis under a greater number of genetic models in the hope of better scanning the space of models, does not increase the power of detection.

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.

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.

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.

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.

Multiple sclerosis (MS) is a debilitating neuroimmunological and neurodegenerative disorder. Despite substantial evidence for polygenic inheritance of the disease, the major histocompatibility complex is the only region that clearly and consistently demonstrates linkage and association in MS studies. The goal of this study was to identify additional chromosomal regions that harbor susceptibility genes for MS. With a panel of 390 microsatellite markers genotyped in 245 U.S. and French multiplex families (456 affected relative pairs), this is the largest genomic screen for MS conducted to date. Four regions met both of our primary criteria for further interest (heterogeneity LOD [HLOD] and Z scores >2.0): 1q (HLOD=2.17; Z=3.38), 6p (HLOD=4.21; Z=2.26), 9q (HLOD; Z=2.71), and 16p (HLOD=2.64; Z=2.05). Two additional regions met only the Z score criterion: 3q (Z=2.39) and 5q (Z=2.17). Further examination of the data by country (United States vs. France) identified one additional region demonstrating suggestive linkage in the U.S. subset (18p [HLOD=2.39]) and two additional regions generating suggestive linkage in the French subset (1p [HLOD=2.08] and 22q [HLOD=2.06]). Examination of the data by human leukocyte antigen (HLA)-DR2 stratification identified four additional regions demonstrating suggestive linkage: 2q (HLOD=3.09 in the U.S. DR2- families), 6q (HLOD=3.10 in the French DR2- families), 13q (HLOD=2.32 in all DR2+ families and HLOD=2.17 in the U.S. DR2+ families), and 16q (HLOD=2.32 in all DR2+ families and HLOD=2.13 in the U.S. DR2+ families). These data suggest several regions that warrant further investigation in the search for MS susceptibility genes.

Coeliac disease is an enteropathy due to an intolerance to gluten. The association between HLA-DQ genes and CD is well established. The majority of patients carry the HLA-DQ heterodimer encoded by DQA1*05/DQB1*02, either in cis or in trans. The remaining patients carry either part of the DQ heterodimer or DQA1*03-DQB1*0302. The aim of the study was to estimate the risks associated with different DQ genotypes in European populations. HLA information was available for 470 trio families from four countries: France (117), Italy (128), and Norway and Sweden (225). Five DQA1-DQB1 haplotypes were considered and control haplotype frequencies were estimated from the set of parental haplotypes not transmitted to the affected child. The possible genotypes were grouped into five genotype groups, based on the hierarchy of risk reported in the literature. A north-south gradient in the genotype group frequencies is observed in probands: homogeneity is strongly rejected between all country pairs. For each country, the relative risks associated with each genotype group were computed taking into account the control haplotype frequencies. Homogeneity of relative risks between countries was tested pairwise by maximum likelihood ratio statistics. The hypothesis of homogeneity of relative risks is rejected (P is approximately 10(-6)) for all country pairs. In conclusion, the gradient in the genotype group frequencies in probands is not only due to differences in haplotype frequencies but also due to differences in genotype relative risks in the studied populations; the relative risks associated with each DQ genotype group are different between northern and southern European countries; neither are they ordered in the same way., (Copyright 2004 Blackwell Munksgaard)

Multiple sclerosis (MS) is a demyelinating autoimmune disease with a strong yet complex genetic component. To date only the HLA-DR locus, and specifically the HLA-DR15 allele, has been identified and confirmed as influencing the risk of developing MS. Genomic screens on several datasets have been performed and have identified several chromosomal regions with interesting results, but none have yet been confirmed. We tested seven of the most-promising regions (on chromosomes 1p, 2p, 3p, 3q, 5q, 19q, and Xp) identified from several genomic screens in a dataset of 98 multiplex MS families from the United States and 90 multiplex MS families from France. The results did not confirm linkage to 2p, 3q, 5q, or Xp in the overall dataset, or in subsets defined by geographic origin or HLA-DR15 status. Regions on 1p34, 3p14, and 19q13 produced lod scores >0.90 in at least one subset of the data, suggesting that these regions should be examined in more detail.

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.

We report the results of a genome-wide screen for linkage disequilibrium (LD) in multiple sclerosis (MS) performed on 200 cases, 200 controls and 200 case-parent trios from France employing pooled DNA methodology. A total of 3510 microsatellite markers supplied through the GAMES collaborative were analysed and ranked according to their evidence for association. The most promising 117 markers were then followed up in a two-step validation process. In the first step, additional PCR of the DNA pools was performed in order to refine the ranking order. In the second step, markers were genotyped in individual cases and parents from the trio families. Seven markers showing nominally significant allele frequency differences between affected and unaffected emerged-D6S265, D12S1064, TNFa, D7S1824, D14S1426, D14S605 and D21S2051. These potential associations will require confirmation in further studies.

Multiple sclerosis is a chronic inflammatory disease of the central nervous system with a genetic component. Until now, the more consistent association with the disease is found with the major histocompatibility complex, especially HLA-DRB1*1501-DQB1*0602 haplotype. In this report, we demonstrate the interaction of Cytotoxic T Lymphocyte-associated antigen 4 (CTLA-4 [CD152]) gene with DRB1*15 haplotype in multiple sclerosis genetic susceptibility. Our data were obtained from two European independent family-based studies including 610 multiple sclerosis family trios. Ann Neurol 2003;54:119-122