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F Clerget-Darpoux

Publications and source records attributed to F Clerget-Darpoux.

At least 91 records · Page 5Linked to original sources
PubMed1995

Testing parental imprinting in insulin-dependent diabetes mellitus by the marker-association-segregation-chi 2 method.

Among patients with insulin-dependent diabetes mellitus (IDDM), an excess of DR3 and DR4 alleles is classically described when compared with the general population. In addition, an excess of maternal DR3 and paternal DR4 alleles among patients (DR3DR4) is observed. In order to explain these observations, two alternative hypotheses can be tested: maternal effect and parental imprinting. Maternal effect has been tested and not rejected on a sample of 416 caucasians affected with IDDM. Under this hypothesis, the children of a DR3 mother are expected to have an earlier exposure and, hence, an earlier age at onset. However, we did not observe such a difference in age at onset in this data set. Using the marker-association-segregation-chi 2 method, we have tested four hypotheses with different parental effects of two susceptibility alleles, alpha 0 and beta 0, at two different closely linked loci. Under the hypothesis that best fitted the data, the probability of being affected depended on the parental inheritance of the susceptibility alleles, suggesting parental imprinting (i.e., differential role of maternal and paternal allele), without evidence for a cis-trans effect. We conclude that parental imprinting on a specific allelic combination may explain the observations on the HLA genotypes of the patients and their relatives.

Chi-Square Distribution↗
PubMed1995

[Phenotype of familial forms of early-onset Alzheimer's disease linked to chromosome 14. Clinical and neuropsychological characteristics of a large group].

We report the clinical features and neuropsychological data of chromosome-14 linked early-onset Alzheimer's disease in a large family (FAD-RO1). Information available in the literature from eight additional chromosome 14-linked Alzheimer's disease kindreds was compared with the data obtained from six kindreds with amyloid precursor protein gene mutations (APP). In the chromosome 14-linked families the disease has an earlier onset and a shorter duration than in families with APP mutations, with an age at death lower than sixty years of age. Seizures, myoclonus and extra pyramidal signs were frequently present in the cases of FAD-RO1 as in six chromosome 14-linked kindreds, but these features were absent in two other ones. The high frequency of seizures (> 80%) in FAD-RO1 and two other chromosome 14-linked kindreds is remarkable. Seizures and myoclonus were encountered at a lower prevalence in APP kindreds. This review suggests that some clinical features are more prevalent in chromosome 14-linked than in APP kindreds but a phenotypic heterogeneity does exist within and between families. The profile of deterioration of the neuropsychological performances, as illustrated by the FAD-RO1 members, shows that chromosome 14-linked kindreds do not demonstrate a specific expression in comparison to APP kindreds. Memory was first impaired. Deficits in visuo-spatial and visuopractic abilities were then noted. Finally the verbal performance deteriorated.

Adult↗
PubMed1994

High risk genotypes for celiac disease.

It is known that celiac disease is strongly associated with an HLA class II component and that most patients carry the dimer DQA1*0501, DQB1*0201. We show in this study that the risk for a carrier of this heterodimer is independent from the number of possible heterodimers, from whether DQA1*0501 and DQB1*0201 are in cis or trans position and from the number of DQA1*0501 (one or two) but strongly depends on the number of DQB1*0201. In the Tunisian population we studied, the risk of developing celiac disease is estimated to be 6.8 times greater for those having a double dose of DQB1*0201 than for other dimer carriers. We replicated this result in published data of four other populations (Italy, Czekoslovakia, United Kingdom, Norway).

Adolescent↗
PubMed1994

Interactive effect of two candidate genes in a disease: extension of the marker-association-segregation chi(2) method.

For elucidating the genetic component of multifactorial diseases, it is important to investigate the effect of several factors and the possible interaction between them. In particular, for many diseases it is interesting to study the interactive effect of two genes. In this context, the marker-association-segregation chi 2 method (MASC), initially proposed to detect the involvement of a candidate gene in multifactorial diseases, is developed here to investigate the involvement of two candidate genes and to model the joint effect of these two genes. In particular, it is possible to precisely determine whether the joint effect of both genes is multiplicative. This extension simultaneously uses information on two markers, one for each candidate gene, at both the population and the familial segregation level. We show here that there can be an important gai of power to detect the effect of a second gene in a disease when information is used simultaneously on two markers instead of studying each marker separately. This extension of MASC is then applied on a sample of insulin-dependent diabetes (IDD) families typed for the markers of two candidate regions: HLA and that of the insulin gene (INS). This analysis allows us to confirm the involvement of INS in IDD, and the best-fitting model is a multiplicative (noninteractive) effect of HLA and INS, with a biallelic locus for INS and a complementation model for HLA.

Alleles↗
PubMed1993

Is a single mutation at the same locus responsible for all affected cases in a large Alzheimer pedigree (FAD4)?

Analysis of marker segregation in the large Alzheimer pedigree, FAD4, leads to the conclusion, with a type I error of 5%, of linkage heterogeneity between two branches of the pedigree: the disease cosegregates with chromosome 21 markers flanking the APP area in one branch and not in the other one. Thus, we conclude that a single mutation in the chromosome 21 region surrounding APP cannot be responsible for all the affected cases in this pedigree.

Alleles↗
PubMed1993

Investigation of the HLA component involved in rheumatoid arthritis (RA) by using the marker association-segregation chi-square (MASC) method: rejection of the unifying-shared-epitope hypothesis.

In order to investigate the HLA component involved in rheumatoid arthritis (RA), we tested genetic models by the marker association-segregation chi 2 (MASC) method, using the HLA genotypic distribution observed in a sample of 97 RA patients. First we tested models assuming the involvement of a susceptibility gene linked to the DR locus. We showed that the present data are compatible with a simple model assuming the effect of a recessive allele of a biallelic locus linked to the DR locus and without any assumption of synergistic effect. Then we considered models assuming the direct involvement of the DR allele products, and we tested the unifying-shared-epitope hypothesis, which has been proposed. Under this hypothesis the DR alleles are assumed to be directly involved in the susceptibility to the disease because of the presence of similar or identical amino acid sequences in position 70-74 of the third hypervariable region of the DRBI molecules, shared by the RA-associated DR alleles DR4Dw4, DR4Dw14, and DR1. This hypothesis was strongly rejected with the present data. In the case of the direct involvement of the DR alleles, hypotheses more complex than the unifying-shared-epitope hypothesis would have to be considered.

Adult↗
PubMed1993

Conclusions of segregation analysis for family data generated under two-locus models.

Susceptibility to a disease may involve the interactive effect of two genes. What conclusions will be drawn by segregation analysis in such a case? To answer this question, we considered a set of two-locus models and the corresponding exact distribution for 300 families. We investigated the conclusions and parameter estimations obtained for this sample, by comparing the likelihood expectations of the unified model and of more restricted models. In many cases, segregation analysis leads to the conclusion of a major gene effect, with or without a polygenic component--usually without a polygenic component in multiplicative models (i.e., where two genes have a multiplicative effect) and with such a component in nonmultiplicative models. For all the models considered, existence of a major gene effect is supported by transmission probability tests; there is evidence for transmission and agreement with the hypothesis of Mendelian transmission. Accordingly, there is no means of detecting that the effect of a major gene, with or without a polygenic component, does not correspond to the correct model. In addition, the parameter estimates for the major gene do not correspond to the characteristics of either of the two genes of the true model. This may substantially affect further linkage analysis.

Alleles↗
PubMed1992

Strategies based on marker information for the study of human diseases.

The goals and the ways of using genetic marker information when studying human disease are very different according to whether the disease or sub-entity of the disease is mendelian or if a 'disease gene' in the sense of a rare mutated allele does not exist but rather common genetic risk factors, each one normal if considered alone. In the former case, genetic markers are used in the aim of localizing the defective gene and a systematic screening of the genome seems to be an efficient strategy provided there is not too much ambiguity in the correspondence between phenotypes and genotypes. In the latter case, the goal is to find risk factors allowing us to predict better the risk for an individual and to define different risk groups resulting in greater power to show the potential role of other factors (genetic or environmental). In this situation, the use of the lod score method with random markers presents several disadvantages: first, the multiple testing problem is particularly crucial; second, false rejection of linkage may be induced by misspecification of the model describing the genetic basis of the disease; and last, the power of detecting linkage may be low. A strategy focusing on 'candidate gene' markers may be then more efficient.

Chromosome Mapping↗
PubMed1992

Proximal spinal muscular atrophy (SMA) types II and III in the same sibship are not caused by different alleles at the SMA locus on 5q.

Proximal spinal muscular atrophy (SMA) is a group of progressive muscular diseases recently mapped to chromosome 5q. SMA is usually classified into types I-III, and there are cases of two types of SMA in the same sibship. Becker and others later proposed that these sibships might be due to the existence of several alleles at the same locus predisposing to the different forms of the disease. In a sample of four sibships in which both SMA type II and SMA type III occur, this hypothesis was clearly rejected for the SMA locus on 5q, by using information on the segregation of linked markers (P less than .001). Thus the difference between SMA type II and SMA type III is not due to different alleles at the SMA locus on 5q. This finding is suggestive of an involvement of other factors, genetic or environmental, in the determination of disease severity in SMA.

Alleles↗
PubMed1992

Linkage of familial breast cancer to chromosome 17q21 may not be restricted to early-onset disease.

Lod scores for linkage between familial breast and ovarian cancer and markers on chromosome 17q21 are more frequently positive among families with disease diagnosed at younger ages than they are among older-onset families, suggesting that linkage is restricted to early-onset disease. However, for late-onset cases, the relative probability of sporadic rather than inherited disease is higher than previously suggested. If this correction is made, then later-onset families are much less informative; linkage heterogeneity based on age at onset is no longer significant; and for the sample of families as a whole, linkage is significant at a recombination fraction since demonstrated to be close to the correct local. There is probably more than one gene for inherited breast cancer, but heterogeneity may not be due to age at disease onset.

Adult↗
PubMed1991

A test based on the exact probability distribution of the chi 2 statistic--incorporation into the MASC method.

The MASC method (Clerget-Darpoux et al. 1988) to test genetic models in HLA associated disease makes use of a test of goodness-of-fit on categorized data. This test is composed of a sum of independent chi 2s, which are applicable only when expectations in each category are not too small. The commonly used approach to solve this problem is to combine classes in order to raise expectations. This, however, means losing some of the information contained in the data and may decrease greatly the power of discrimination between models. A test based on the exact probability distribution of a test statistic, namely the chi 2, has been implemented to avoid this dilemma.

Chi-Square Distribution↗
PubMed1991

Linkage analysis in spinal muscular atrophy, by six closely flanking markers on chromosome 5.

The proximal spinal muscular atrophies (SMA) represent the second most common autosomal recessive disorder, after cystic fibrosis. The gene responsible for chronic SMA has recently been mapped to chromosome 5q by using genetic linkage studies. Among six markers mapping to this region, five were shown to be linked with the SMA locus in 39 chronic SMA families each containing at least two affected individuals. Multilocus analysis by the method of location score was used to establish the best estimate of the SMA gene location. Our data suggest that the most likely location for SMA is between loci D5S6 and D5S39. The genetic distances between these two markers are estimated to be 6.4 cM in males and 11.9 cM in females. Since meiosis were informative with D5S39 and D5S6 in 92% and 87% of SMA families, respectively, it is hoped that the present study will contribute to the calculation of genetic risk in SMA families.

Chromosome Mapping↗