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E Génin

Publications and source records attributed to E Génin.

At least 19 recordsLinked to original sources
PubMed2001

Modeling of HLA class II susceptibility to Type I diabetes reveals an effect associated with DPB1.

In this report, we present evidence that the HLA class II DPB1 locus (or a locus with alleles in linkage disequilibrium with DPB1) contributes to Type I diabetes (IDDM) susceptibility in addition to the contribution of the HLA DR and DQ loci. The marker association segregation chi-square (MASC) method, which fits both genotype frequency and affected sib-pair identity-by-descent (IBD) distributions, was applied to 257 sib pairs affected with IDDM. Fitting DR-DQ as the sole HLA susceptibility loci was strongly rejected. Next, we considered the DPB1 contribution to disease susceptibility. Published reports indicate a predisposing role for alleles DPB1*0301 and DPB1*0202, including our previous stratification analyses of association data on this sample. IDDM probands were stratified into those not carrying the alleles DPB1*0301 and DPB1*0202 (group DPB1-A), and those carrying at least one copy of either allele (group DPB1-B). Both groups of probands have almost identical frequencies of DR and DQ haplotypes but significantly different IBD distributions in the subset of families with probands who do not carry the highly predisposing DR3/DR4 genotype. In these data, DPB1 (or a locus in linkage disequilibrium), in addition to DR-DQ, is involved in IDDM susceptibility and affects IBD in the HLA region. Addition of DPB1 in a genetic model of IDDM gives a better fit to the data than consideration of DR-DQ alone. Our results are consistent with previous reports implicating DPB1 in IDDM susceptibility.

Alleles↗
PubMed2001

Maximum identity length contrast: a powerful method for susceptibility gene detection in isolated populations.

We report the results of our analysis of the Genetic Analysis Workshop 12 simulated data set. Focusing on the isolated populations, we compare the efficiency of a new method, the maximum identity length contrast statistic (MILC) with the maximum likelihood score (MLS) in a genome screen strategy. MILC is a method based on the contrast of haplotype identity between transmitted and nontransmitted haplotypes in trios. It uses information on linkage and association. We found that MILC allows the detection of a risk factor corresponding to candidate gene 1 where the MLS fails, though the same population replicates were used. Interestingly, the association between this risk factor and the disease could not have been detected with the TDT at a genome-wide level.

Chromosome Mapping↗
PubMed2001

Cladistic analysis of haplotypes as an attempt to detect disease susceptibility.

We report the results of our analyses of the Genetic Analysis Workshop 12 simulated data set, using phylogenetic methods to reconstruct the history of haplotypes. We selected candidate gene 1 and 6, drawn from the isolate population. In a first step, haplotypes were inferred using family data. In a second step, cladistic approaches were performed to select the most parsimonious trees under various conditions of character state transformation and ancestral hypotheses, in order to check whether the affected status is more frequent in some clades than in others. Sites which are synapormophies of such clades can be viewed as candidate sites for the disease susceptibility. The method seems to be efficient for the candidate gene 1, but not for the candidate gene 6. Effects of the genetic model underlying the affection status are discussed, particularly dominance, penetrance, and, in the context of this simulated data, procedure followed to generate haplotypes. These preliminary results deserve further investigations.

Chromosome Mapping↗
PubMed2001

Selection of single nucleotide polymorphisms for association studies in candidate genes.

Comparison of polymorphic sites such as single nucleotide polymorphisms (SNPs) within a gene between cases and controls may be useful for establishing a role of this gene in disease susceptibility. The approach includes two steps: the first step is the discovery of the different SNPs within the candidate gene and the second step is the association testing per se that can be done on the entire set of sites discovered or on a subset of these sites only. Selecting a subset of sites may increase the power to detect the association with the candidate gene since a smaller number of tests would then be performed. We proposed a strategy to select sites within a candidate gene and applied it on the Genetic Analysis Workshop 12 candidate gene data. Using these selected sites, we detected an association with candidate genes 1 and 6.

Alleles↗
PubMed2001

Investigation of a candidate gene, environment, and G x E interaction using case-control and case-parent study designs.

We investigated the independent contributions of a candidate gene and an environmental factor, and the presence of gene x environment (G x E) interaction, in the etiology of a disease in the Genetic Analysis Workshop (GAW) 12 problem 2 simulated data using a two-stage approach utilizing both case-control and case-parent study designs. Using the case-control design, several SNPs within candidate gene 1 (CG1) and environmental factor 1 (dichotomized using the 75th percentile as a cut-off) (EXP) were independently associated with disease status, in models adjusted for age and sex. We found evidence of gene x environment (G x E) interaction between EXP and two single-nucleotide polymorphisms (SNPs) within CG1 using the case-control design. Using the case-parent study design in the same population, we detected association between SNPs within CG1 and disease, but no G x E interaction was detected.

Adult↗
PubMed2000

Use of closely related affected individuals for the genetic study of complex diseases in founder populations.

We propose a method, the maximum identity length contrast (MILC) statistic, to locate genetic risk factors for complex diseases in founder populations. The MILC approach compares the identity length of parental haplotypes that are transmitted to affected offspring with the identity length of those that are not transmitted to affected offspring. Initially, the statistical properties of the method were assessed using randomly selected affected individuals with unknown relationship. Because both nuclear families with multiple affected sibs and large pedigrees are often available in founder populations, we performed simulations to investigate the properties of the MILC statistic in the presence of closely related affected individuals. The simulation showed that the use of closely related affected individuals greatly enhances the power of the statistic. For a given sample size and type I error, the use of affected sib pairs, instead of affected individuals randomly selected from the population, could increase the power by a factor of two. This increase was related to an increase of kinship-coefficient contrast between haplotype groups when closely related individuals were considered. The MILC approach allows the simultaneous use of affected individuals from a founder population and affected individuals with any kind of relationship, close or remote. We used the MILC approach to analyze the role of HLA in celiac disease and showed that the effect of HLA may be detected with the MILC approach by typing only 11 affected individuals, who were part of a single large Finnish pedigree.

Celiac Disease↗
PubMed2000

A robust test for assortative mating.

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.

Alleles↗
PubMed1999

Detection and modeling of disease susceptibility locus effects: how much can be learned from contrast of populations?

We report the results of our analyses of the GAW11 Problem 2 data set, using information from three different populations. In the first part of the paper, we used classical population genetic tests to compare affected individuals from the different populations, stratifying on the environmental factors. Thanks to existing linkage disequilibrium in one population, we found one of the disease susceptibility loci. In the second part of the paper, we used the marker association segregation chi 2 method to model the role of this disease susceptibility locus in the different populations and draw some inferences regarding the model used at that locus to generate the data.

Chromosome Mapping↗
PubMed1999

Detection of polymorphism in the RING3 gene by high-throughput fluorescent SSCP analysis.

We describe the use of a high-throughput, fluorescent, polymorphism-detection system, based on single-strand conformation polymorphism to screen for polymorphism in the RING3 gene. This is the first extensive mutation screen of this major histocompatibility complex-linked gene, and the entire coding region and intron-exon junctions were examined by multiplexing over 3000 polymerase chain reaction products. These techniques should be applicable for analysis of variation in other human genes. Investigation of DNA from acute lymphoblastic leukemia (ALL) and chronic myeloid leukemia (CML) patients, as well as healthy individuals revealed low levels of polymorphism across the RING3 gene. Comparison of the distribution of genotypes at each polymorphic site between patients and healthy individuals revealed a single site which significantly deviates from Hardy-Weinberg proportions.

Fluorescent Dyes↗
PubMed1998

Modelling the major histocompatibility complex susceptibility to RA using the MASC method.

To explain the association between HLA-DRB1 gene and rheumatoid arthritis (RA), two main hypotheses have been proposed. The first, the shared epitope hypothesis, assumes a direct role of DRB1 in RA susceptibility. The second hypothesis assumes a recessive disease susceptibility gene in linkage disequilibrium with DRB1. To investigate these two hypotheses, we analysed data on the HLA-DRB1 and TNF-LT loci in 49 affected sib-pairs. We used the Marker Association Segregation Chi-square (MASC) method in which the genotype distribution of markers among index cases and the haplotype sharing in affected sib-pairs are jointly taken into account. With DRB1 data alone, both hypotheses were shown to fit but with analysis of TNF data, both hypotheses were strongly rejected. Thus the TNF data provided additional information for a better understanding of genetic susceptibility to RA than was previously possible using only HLA-DR data. A theoretical standpoint is addressed here on the advisability of using different linked markers in a candidate region for modelling the contribution of this region in disease susceptibility.

Adolescent↗
PubMed1998

Optimization of genome search strategies for homozygosity mapping: influence of marker spacing on power and threshold criteria for identification of candidate regions.

Mapping of genes involved in rare recessive diseases is usually difficult because of the lack of families with more than one affected progeny. The problem may be avoided by using inbred affected individuals and the strategy of homozygosity mapping. In practice, the use of homozygosity mapping in a genome-wide scan requires that a set of markers regularly spaced and spanning the whole genome are tested. Investigators are then faced to the problem of choosing the spacing of markers. To help solve this problem, we give some useful clues by computing (1) the expected length of the region of identity by descent around the disease locus, (2) the distribution, given the spacing of markers, of the number of affected individuals expected not to be homozygous at the marker closest to the disease locus and, (3) the expected type-one error. We show that even if the markers are very closely spaced, it is not unlikely that some affected individuals in the sample will not be homozygous at the marker closest to the disease locus. Excluding a region by the criterion that all affected individuals in the sample are not homozygous may then dramatically increase the rate of false negatives. We thus propose to relax the criterion to declare a region candidate, based on the sample size and the spacing of markers.

Chromosome Mapping↗
PubMed1998

Genetic studies of polymorphisms in ten non-insulin-dependent diabetes mellitus candidate genes in Tamil Indians from Pondichery.

We report a study of 10 candidate genes presumably involved in diabetes or insulin resistance or obesity among Pondicherian Tamil Indians, an isolated population with a high prevalence of diabetes. Forty-nine families with at least two affected patients in the sibship (567 individuals) were selected and tested by PCR-RFLP techniques for reported mutations in 10 diabetes or obesity candidate genes: glucagon receptor, insulin receptor substrate 1, insulin receptor, human beta 3 adrenergic receptor, fatty acid binding protein 2, mitochondrial tRNA(Leu(UUR)), sulphonylurea receptor, human uncoupling protein and the glycogen-associated regulatory subunit of protein phosphatase-1. Glucokinase gene was also screened for mutations. No mutations were found in glucokinase, glucagon receptor and mitochondrial genes in any of the 49 probands. Frequencies of polymorphisms at other loci were similar to those reported in Caucasian populations, except for 4 of the loci at which a higher frequency of variants was observed: human beta 3 adrenergic receptor, human uncoupling type 1 protein, fatty acid binding protein 2 and the glycogen-associated regulatory subunit of protein phosphatase-1. However, no evidence of association between any of these gene variants and non-insulin-dependent diabetes mellitus (NIDDM) or quantitative traits related to NIDDM (including body mass index, waist/hip ratio, insulinaemia, glycaemia, triglycerides and total cholesterol) was found in our sample. These results suggest that none of these gene variants commonly found in the Pondicherian Tamil population of South India is a major NIDDM predisposing locus, although it cannot be excluded that they may contribute to the polygenic background of the metabolic syndrome in Pondichery.

Adult↗
PubMed1997

Caution in the interpretation of MLS.

We study the statistical properties of the maximum likelihood score (MLS) test. We show that the criteria for reaching conclusions about linkage are not the same for single point analysis as for multipoint, where the maximization is performed over an additional parameter, the position in the marker interval where the MLS is computed. In addition, this test is shown to be very sensitive to errors in allele frequencies and recombination fraction.

Alleles↗
PubMed1997

Heterogeneity of marker allele frequencies hinders interpretation of linkage analysis: illustration on chromosome 18 markers.

In the first part of our study we tested linkage with chromosome 18 markers in a sample of bipolar I sib pairs. We did not obtain evidence for linkage but showed that we could not exclude the presence of a disease locus (having even a non-negligible effect). The limitation of the sib-pair sample size, and consequently of the conclusions, was a result of our care in assuring that the linkage analysis was free of possible errors in the marker allele frequencies. In the second part, we illustrated the possible impact of such heterogeneity in a single data set when applying the multipoint (APM) method. An Amish pedigree included in the study of Berrettini et al. was analyzed under two sets of marker allele frequencies. One set corresponds to estimates from the entire data set and the second to estimates from the Amish pedigree only. Very different values for the APM statistics were obtained. Although the real frequencies are unknown for this family belonging to an isolated population, this example illustrates that heterogeneity in the populations from which familial data are collected may artificially increase evidence for linkage and hinder interpretation of the analysis.

Alleles↗
PubMed1997

Information provided by pairs of distantly affected relatives to search for genes involved in rare autosomal dominant diseases.

When dominant mutations of different genes may lead to the same disease, it is often difficult to detect in a particular patient which gene is involved. A strategy is to make genealogical extensions to find affected relatives that should have inherited the same mutation. In particular, for diseases with late age of onset or short survival time, only poor information may be obtained from close relatives of probands and it can be particularly efficient to make genealogical extensions to detect pairs of distantly related affected individuals. Such a pair of affecteds may provide information concerning the region of the genome where the mutated gene should map. Two situations may be encountered depending on whether or not prior information on the location of mutated genes involved in the disease are available. If we already know, from previous linkage studies, that a gene located in a given region R of the genome may be involved in the disease, the problem is then to confirm that it is indeed a mutation of this gene that is involved in the affected pair. Once the implication of a gene in region R has been confirmed the affected pair of relatives may give information to restrict the length of this region R. In this paper we discuss these two points by deriving analytically first the lod score expected and second the expected reduction of the length of the region where the mutation is suspected to map as a function of the number of meioses between the two affected individuals and of the polymorphism of the markers available in the region.

Chromosome Aberrations↗
PubMed1996

Association studies in consanguineous populations.

To study the genetic determinism of multifactorial diseases in large panmictic populations, a strategy consists in looking for an association with markers closely linked to candidate genes. A distribution of marker genotypes different in patients and controls may indicate that the candidate gene is involved in the disease. In panmictic populations, the power to detect the role of a candidate gene depends on the gametic disequilibrium with the marker locus. In consanguineous populations, we show that it depends on the inbreeding coefficient F as well. Inbreeding increases the power to detect the role of a recessive or quasi-recessive disease-susceptibility factor. The gain in power turns out to be greater for small values of the gametic disequilibrium. Moreover, even in the absence of gametic disequilibrium, the presence of inbreeding may allow to detect the role of a recessive factor. Ignoring inbreeding when it exists may lead to reject falsely a recessive model if the mode of inheritance is inferred on the distribution of genotypes among patients.

Case-Control Studies↗
PubMed1996

Consanguinity and the sib-pair method: an approach using identity by descent between and within individuals.

To test for linkage between a trait and a marker, one can consider identical marker alleles in related individuals, for instance, sibs. For recessive diseases, it has been shown that some information may be gained from the identity by descent (IBD) of the two alleles of an affected inbred individual at the marker locus. The aim of this paper is to extend the sib-pair method of linkage analysis to the situation of sib pairs sampled from consanguineous populations. This extension takes maximum advantage of the information provided by both the IBD pattern between sibs and allelic identity within each sib of the pair. This is possible through the use of the condensed identity coefficients. Here, we propose a new test of linkage based on a chi2. We compare the performance of this test with that of the classical chi2 test based on the distribution of sib pairs sharing 0, 1, or 2 alleles IBD. For sib pairs from first-cousin matings, the proposed test can better detect the role of a disease-susceptibility (DS) locus. Its power is shown to be greater than that of the classical test, especially for models where the DS allele may be common and incompletely penetrant; that is to say for situations that may be encountered in multifactorial diseases. A study of the impact of inbreeding on the expected proportions of sib pairs sharing 0, 1, or 2 alleles IBD is also performed here. Ignoring inbreeding, when in fact inbreeding exists, increases the rate of type I errors in tests of linkage.

Chromosome Mapping↗