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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. [ABSTRACT FROM PUBLISHER]

Gene–environment interactions are likely to be involved in the susceptibility to multifactorial diseases but are difficult to detect. Available methods usually concentrate on some particular genetic and environmental factors. In this paper, we propose a new method to determine whether a given exposure is susceptible to interact with unknown genetic factors. Rather than focusing on a specific genetic factor, the degree of familial aggregation is used as a surrogate for genetic factors. A test comparing the recurrence risks in sibs according to the exposure of indexes is proposed and its power is studied for varying values of model parameters. The Exposed versus Unexposed Recurrence Analysis (EURECA) is valuable for common diseases with moderate familial aggregation, only when the role of exposure has been clearly outlined. Interestingly, accounting for a sibling correlation for the exposure increases the power of EURECA. An application on a sample ascertained through one index affected with type 2 diabetes is presented where gene–environment interactions involving obesity and physical inactivity are investigated. Association of obesity with type 2 diabetes is clearly evidenced and a potential interaction involving this factor is suggested in Hispanics (P=0.045), whereas a clear gene–environment interaction is evidenced involving physical inactivity only in non-Hispanic whites (P=0.028). The proposed method might be of particular interest before genetic studies to help determine the environmental risk factors that will need to be accounted for to increase the power to detect genetic risk factors and to select the most appropriate samples to genotype. [ABSTRACT FROM AUTHOR]

In the context of genomewide association studies where hundreds of thousand of polymorphisms are tested, stringent thresholds on the raw association test P-values are generally used to limit false-positive results. Instead of using thresholds based on raw P-values as in Bonferroni and sequential Sidak (SidakSD) corrections, we propose here to use a weighted-Holm procedure with weights depending on allele frequency of the polymorphisms. This method is shown to substantially improve the power to detect associations, in particular by favoring the detection of rare variants with high genetic effects over more frequent ones with lower effects. [ABSTRACT FROM AUTHOR]

Abstract: Background: Disparities in the spectrum of mutations within the cystic fibrosis (CF) transmembrane conductance regulator (CFTR) gene are commonly observed in populations from different ethnical and/or geographical origins. The occurrence of CF in Brittany (western France) is one of the highest in populations from Caucasian origin (<1/2000 in specific areas). The W846X2, 1078delT and G551D mutations, as well as the I1027T polymorphism in cis with the ΔF508 mutation (currently referred to as p.F508del) are particularly frequent in this area. We investigated the age of the respective variants in the region of interest. Methods: Several polymorphic markers surrounding the CFTR gene were genotyped. Allele frequencies as well as mutation rates and other parameters were used to calculate the respective age of the most recent common ancestors in the region of interest by a previously employed, simple likelihood-based method. Results: Following haplotype reconstruction and simulation, the ages were estimated to be approximately 600, 1000, 1200 and 600 years, respectively (with a 95% confidence interval). Conclusions: These datings thus provide historical insights in the context of understanding population migrations. They also underline the usefulness of this method for estimating the age of rare mutations with a limited number of carriers. [Copyright &y& Elsevier]

Haplotypes are now widely used in association studies between markers and disease susceptibility locus. However, when a large number of markers are considered, the number of possible haplotypes increases leading to two problems: an increased number of degrees of freedom that may result in a lack of power and the existence of rare haplotypes that may be difficult to take into account in the statistical analysis. In a recent paper, Durrant et al proposed a method, CLADHC, to group haplotypes based on distance matrices and showed that this could considerably increase the power of the association test as compared to either single-locus analysis or haplotype analysis without prior grouping. Although the authors considered different one-disease-locus susceptibility models in their simulations, they did not study the impact of the linkage disequilibrium (LD) pattern and of the susceptibility allele frequency on their conclusions. Here, we show, using haplotype data from five regions of the genome of different lengths and with different LD patterns, that, when a single disease susceptibility locus is simulated, the prior grouping of haplotypes based on the algorithm of Durrant et al does not increase the power of association testing except in very particular situations of LD patterns and allele frequencies.European Journal of Human Genetics (2006) 14, 202–206. doi:10.1038/sj.ejhg.5201501; published online 23 November 2005 [ABSTRACT FROM AUTHOR]

Haplotype frequency estimation in population data is an important problem in genetics and different methods including expectation maximisation (EM) methods have been proposed. The statistical properties of EM methods have been extensively assessed for data sets with no missing values. When numerous markers and/or individuals are tested, however, it is likely that some genotypes will be missing. Thus, it is of interest to investigate the behaviour of the method in the presence of incomplete genotype observations. We propose an extension of the EM method to handle missing genotypes, and we compare it with commonly used methods (such as ignoring individuals with incomplete genotype information or treating a missing allele as any other allele). Simulations were performed, starting from data sets of haematopoietic stem cell donors genotyped at three HLA loci. We deleted some data to create incomplete genotype observations in various proportions. We then compared the haplotype frequencies obtained on these incomplete data sets using the different methods to those obtained on the complete data. We found that the method proposed here provides better estimations, both qualitatively and quantitatively, but increases the computation time required. We discuss the influence of missing values on the algorithm's efficiency and the advantages and disadvantages of deleting incomplete genotypes. We propose guidelines for missing data handling in routine analysis.European Journal of Human Genetics (2004) 12, 805-812. doi:10.1038/sj.ejhg.5201233 Published online 14 July 2004 [ABSTRACT FROM AUTHOR]

Testing for random mating in human populations is difficult due to confounding factors such as ethnic preference and population stratification. With HLA, the high level of polymorphism is an additional problem since it is rare for couples to share the same haplotype. Focus on an ethnically homogeneous population, where levels of polymorphism at HLA loci are more limited, may provide the best situation in which to detect non-random mating. However, such populations are often genetic isolates where there may be inbreeding to an extent that is difficult to quantify and account for. We have developed a test for random mating at a multiallelic locus that is robust to stratification and inbreeding. This test relies on the availability of genotypic information from the parents of both spouses. The focus of the test is on families where there is allele sharing between the parents of both spouses, so that potential spouses could share an allele. Denoting the shared allele at the locus of interest by A, then under the assumption of random mating, heterozygous parents AX should transmit allele A equally as frequently as allele X to their offspring. When there is positive (negative) assortative mating, A will be transmitted more (less) often than X. The power of the test has been computed in a number of situations. Data on high resolution HLA haplotypes from the Hutterite population were reinvestigated by the proposed test. The test detects significant negative assortative mating when the parental origin of the shared haplotype is taken into account. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented in response to the article "Polymorphisms at PRSS1-PRSS2 and CLDN2-MORC4 loci associate with alcoholic and non-alcoholic chronic pancreatitis in a European replication study" by M.H. Derikx and others in a 2015 issue.

Abstract: Alzheimer''s disease is a genetically complex disorder, for which new putative susceptibility genes are constantly proposed in the literature. We selected 16 candidate genes involved in biological pathways closely related to the pathology, and for which a genetic association with Alzheimer''s disease was previously detected: ACE, BACE1, BDNF, ECE1, HSPG2, IDE, IL1a, IL6, IL10, MAPT, PLAU, PrnP, PSEN1, SORL1, TFCP2 and TGFb1. The variants originally associated with the disease were genotyped in a French Caucasian sample including 428 cases and 475 controls and tested for association in order to replicate the initial results. Despite a careful replication study design, we failed to validate the initial findings for any of these variants, with the possible exception of MAPT, SORL1 and TFCP2 for which some nominal but inconsistent evidence of association was observed. [Copyright &y& Elsevier]

Recent epidemiological, biological and genetic data indicate a relationship between cholesterol and Alzheimer's disease (AD) including the association of polymorphisms of ABCA1 (a gene that is known to participate in cholesterol and phospholipid transport) with AD prevalence. Based on these data, we postulated that genetic variation in the related and brain-specific ABCA2 gene leads to increase risk of AD. A large case–control study was conducted where the sample was randomly divided into a hypothesis-testing sample (230 cases/286 controls) and a validation sample (210 cases/233 controls). Among the 45 SNPs we tested, one synonymous SNP (rs908832) was found significantly associated with AD in both samples. Additional analyses performed on the whole sample showed a very strong association between this marker and early-onset AD (OR = 3.82, 95% C.I. = [2.00 – 7.30], P = 5 × 10 −5 ). Further research is needed to understand the functional role of this polymorphism. However, together with the reported associations of AD with APOE, CYP46A1 and ABCA1, the present result adds a very significant support for the role of cholesterol and phospholipid homeostasis in AD and a rationale for testing novel cholesterol homeostasis-related therapeutic strategies in AD. [ABSTRACT FROM AUTHOR]

Alzheimer''s disease (AD) is a genetically complex neurodegenerative disorder and the leading cause of dementia of the elderly. Recently, Hu et al. suggested that a trinucleotide deletion in intron 13 of the APBB1 gene was a factor protecting against late-onset AD. We report here the results of a case/control study aimed at replicating this association. Our study included 461 AD patients and 397 matched controls. We compared the allele and genotype frequencies of the polymorphism between the two groups but did not find any statistically significant difference (P=0.08 and P=0.09, respectively). By contrast, adjusting for age and sex, we found a slight risk associated with the deletion (odds ratio=1.47, 95% confidence interval=1.05–2.04). Stratification by age showed that the risk effect associated with the deletion concerned subjects aged less than 65 years. [Copyright &y& Elsevier]

Polymorphisms in the Nicastrin (NCSTN) gene have recently been associated with familial early-onset Alzheimer''s disease (AD). The authors genotyped four NCTSN polymorphisms in a large cohort of 489 AD cases (including 158 sporadic early-onset AD cases and 95 familial early-onset AD cases) and 386 controls but failed to replicate the association between NCSTN haplotype B and AD. [Copyright &y& Elsevier]