Biomedical subjects
Publications and source records attributed to M C Babron.
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.
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.
The apolipoprotein E (ApoE)-epsilon4 allele is associated in a dose dependent manner to an increased risk for Alzheimer's disease. However, the ApoE-epsilon4 allele effect does not account for all patients with Alzheimer's disease, and the existence of other genetic risk factors has been postulated. Kamboh et al reported an association between Alzheimer's disease and the A allele of alpha1-antichymotrypsin (Aact) gene, which was not confirmed in a larger series more recently analysed. The ApoE and Aact genotypes were analysed in 314 patients with Alzheimer's disease and 173 healthy controls, confirming the dose dependent effect of the ApoE-epsilon4 allele. Nevertheless, even using odds ratios adjusted for age and sex, there was no significant effect of the Aact genotype on Alzheimer's disease or on the ApoE-epsilon4 allele associated risk for Alzheimer's disease.
The distribution of apolipoprotein E (APOE) genotypes as a function of age and sex has been examined in a French population of 417 Alzheimer disease (AD) patients and 1,030 control subjects. When compared to the APOE epsilon3 allele, an increased risk associated with the APOE epsilon4 allele (odds ratio [OR] [epsilon4] = 2.7 with 95% confidence interval [CI] = 2.0-3.6; P < .001) and a protective effect of the APOE epsilon2 allele (OR[epsilon2] = 0.5 with 95% CI = 0.3-0.98; P = .012) were retrieved. An effect of the epsilon4 allele dosage on susceptibility was confirmed (OR[epsilon4/epsilon4] vs. the epsilon3/epsilon3 genotype = 11.2 [95% CI = 4.0-31.6]; OR[epsilon3/epsilon4] vs. the epsilon3/epsilon3 genotype = 2.2 [95% CI = 1.5-3.5]). The frequency of the epsilon4 allele was lower in male cases than in female cases, but, since a similar difference was found in controls, this does not lead to a difference in OR between sex. ORs for the epsilon4 allele versus the epsilon3 allele, OR(epsilon4), were not equal in all age classes: OR(epsilon4) in the extreme groups with onset at < 60 years or > 79 years were significantly lower than those from the age groups 60-79 years. In epsilon3/epsilon4 individuals, sex-specific lifetime risk estimates by age 85 years (i.e., sex-specific penetrances by age 85 years) were 0.14 (95% CI 0.04-0.30) for men and 0.17 (95% CI 0.09-0.28) for women.
Segregation analysis of Alzheimer disease (AD) in 92 families ascertained through early-onset ( < or = age 60 years) AD (EOAD) probands has been carried out, allowing for a mixture in AD inheritance among probands. The goal was to quantify the proportion of probands that could be explained by autosomal inheritance of a rare disease allele "a" at a Mendelian dominant gene (MDG). Our data provide strong evidence for a mixture of two distributions; AD transmission is fully explained by MDG inheritance in < 20% of probands. Male and female age-of-onset distributions are significantly different for "AA" but not for "aA" subjects. For "aA" subjects the estimated penetrance value was close to 1 by age 60. For "AA" subjects, it reaches, by age 90, 10% (males) and 30% (females). We show a clear cutoff in the posterior probability of being an MDG case.
The power to detect linkage by the LOD-score method is investigated here for diseases that depend on the effects of two genes. The classical strategy is, first, to detect a major-gene (MG) effect by segregation analysis and, second, to seek for linkage with genetic markers by the LOD-score method using the MG parameters. We already showed that segregation analysis can lead to evidence for a MG effect for many two-locus models, with the estimates of the MG parameters being very different from those of the two genes involved in the disease. We show here that use of these MG parameter estimates in the LOD-score analysis may lead to a failure to detect linkage for some two-locus models. For these models, use of the sib-pair method gives a non-negligible increase of power to detect linkage. The linkage-homogeneity test among subsamples differing for the familial disease distribution provides evidence of parameter misspecification, when the MG parameters are used. Moreover, for most of the models, use of the MG parameters in LOD-score analysis leads to a large bias in estimation of the recombination fraction and sometimes also to a rejection of linkage for the true recombination fraction. A final important point is that a strong evidence of an MG effect, obtained by segregation analysis, does not necessarily imply that linkage will be detected for at least one of the two genes, even with the true parameters and with a close informative marker.
Characteristics of familial aggregation of Alzheimer's Disease were studied in 92 families ascertained through a clinically diagnosed proband with an onset below age 60 years. In each family data were systematically collected on the sibships of the proband, of his father, and of his mother. A total of 926 relatives were included and 81% of the living relatives (i.e., 251 individuals) were directly examined. The estimated cumulative risk among first degree relatives was equal to 35% by age 89 years (95% confidence interval 22 to 47%). This result does not support the hypothesis that an autosomal dominant gene, fully penetrant by age 90 years, is segregating within all these pedigrees. Despite the fact that all probands were selected for an onset before age 60 years it was shown that two types of families could be delineated with respect to age at onset among affected relatives: all secondary cases with an onset below age 60 years were contributed by a particular group of families (type 1 families), whereas all secondary cases with an onset after age 60 years were contributed by another group of families (type 2 families). Although genetic interpretation of these findings is not straightforward, they support the hypothesis of etiologic heterogeneity in the determination of early-onset Alzheimer's disease.
Susceptibility genes are identified for a simulated complex trait by a systematic genome search for linkage between disease and a genetic marker in the presence of gametic disequilibrium. The transmission/disequilibrium tests TDTa or TDTg for multiallelic markers compare transmitted and nontransmitted alleles or the genotypes formed by the two transmitted alleles and the genotypes formed by the two nontransmitted alleles, respectively. With these two tests we were able to identify the two markers D1G31 and D5G23. Under the simulating model these are in fact two susceptibility genes involved in the disease.
The aim of this study is to compare the power of the transmission disequilibrium test (TDT) to that of the identity-by-descent (IBD) distribution test. The relative powers of these tests depend both on the underlying genetic model and on the available family data. Families with two affected sibs are always more informative than those with one affected child and one unaffected child. The IBD test is always more powerful in the first situation and, contrary to the TDT, is independent of the presence of gametic disequilibrium. When there is strong linkage disequilibrium, the TDT can be more powerful than the IBD test. In that case, linkage can be detected by the TDT even in families with only one affected child.
Two susceptibility genes, in linkage disequilibrium with alleles of the markers D1G31 and D5G23, have been identified for the disease in the simulated data set of Problem 1. Here we apply the MASC (marker association segregation chi-square) method to model the joint effect of these two genes, by testing two-locus models. The model we obtain, that is the most parsimonious and that best fits the data, corresponds to a direct involvement of the alleles D1G31-8 and D5G23-7, with a nonmultiplicative effect of the two alleles. This was indeed assumed in the true model used for simulating the data.
Apolipoprotein E, type epsilon 4 allele (ApoE epsilon 4), is associated with late-onset sporadic Alzheimer's disease (AD) in French patients. The association is highly significant (0.45 AD versus 0.12 controls for epsilon 4 allele frequencies). These data support the involvement of ApoE epsilon 4 allele as a very important risk factor for the clinical expression of AD.
Marfan syndrome (MFS) is an autosomal dominant connective-tissue disorder characterized by skeletal, ocular and cardiovascular defects of highly variable expressivity. The diagnosis relies solely on clinical criteria requiring anomalies in at least two systems. By excluding the chromosome 15 disease locus, fibrillin 1 (FBN1), in a large French family with typical cardiovascular and skeletal anomalies, we raised the issue of genetic heterogeneity in MFS and the implication of a second locus (MFS2). Linkage analyses, performed in this family, have localized MFS2 to a region of 9 centiMorgans between D3S1293 and D3S1283, at 3p24.2-p25. In this region, the highest lod score was found with D3S2336, of 4.89 (theta = 0.05). By LINKMAP analyses, the most probable position for the second locus in MFS was at D3S2335.
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).
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.
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We show that the null hypothesis in the Affected-Pedigree-Member (APM) method is composed of two sub-hypotheses: no linkage and correct marker allele distribution. As a result, the APM method is not robust to misspecification of marker allele frequencies.
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.
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.