Disease Susceptibility Genes - their Identification by Multiple Case Family Studies

A Rare Variant Nonparametric Linkage Method for Nuclear and Extended Pedigrees with Application to Late-Onset Alzheimer Disease via WGS Data

To analyze family-based whole-genome sequence (WGS) data for complex traits, we developed a rare variant (RV) non-parametric linkage (NPL) analysis method, which has advantages over association methods. The RV-NPL differs from the NPL in that RVs are analyzed, and allele sharing among affected relative-pairs is estimated only for minor alleles. Analyzing families can increase power because causal variants with familial aggregation usually have larger effect sizes than those underlying sporadic diseases. Differing from association analysis, for NPL only affected individuals are analyzed, which can increase power, since unaffected family members can be susceptibility variant carriers. RV-NPL is robust to population substructure and admixture, inclusion of nonpathogenic variants, as well as allelic and locus heterogeneity and can readily be applied outside of coding regions. In contrast to analyzing common variants using NPL, where loci localize to large genomic regions (e.g., >50 Mb), mapped regions are well defined for RV-NPL. Using simulation studies, we demonstrate that RV-NPL is substantially more powerful than applying traditional NPL methods to analyze RVs. The RV-NPL was applied to analyze 107 late-onset Alzheimer disease (LOAD) pedigrees of Caribbean Hispanic and European ancestry with WGS data, and statistically significant linkage (LOD ≥ 3.8) was found with RVs in PSMF1 and PTPN21 which have been shown to be involved in LOAD etiology. Additionally, nominally significant linkage was observed with RVs in ABCA7, ACE, EPHA1, and SORL1, genes that were previously reported to be associated with LOAD. RV-NPL is an ideal method to elucidate the genetic etiology of complex familial diseases.

Optimal allele-sharing statistics for genetic mapping using affected relatives

The choice of allele-sharing statistics can have a great impact on the power of robust affected relative methods. Similarly, when allele-sharing statistics from several pedigrees are combined, the weight applied to each pedigree's statistic can affect power. Here we describe the direct connection between the affected relative methods and traditional parametric linkage analysis, and we use this connection to give explicit formulae for the optimal sharing statistics and weights, applicable to all pedigree types. One surprising consequence is that under any single gene model, the value of the optimal allele-sharing statistic does not depend on whether observed sharing is between more closely or more distantly related affected relatives. This result also holds for any multigene model with loci unlinked, additivity between loci, and all loci having small effect. For specific classes of two-allele models, we give the most powerful statistics and optimal weights for arbitrary pedigrees. When the effect size is small, these also extend to multigene models with additivity between loci. We propose a useful new statistic, S(rob dom), which performs well for dominant and additive models with varying phenocopy rates and varying predisposing allele frequency. We find that the statistic S(_#alleles), performs well for recessive models with varying phenocopy rates and varying redisposing allele frequency. We also find that for models with large deviation from null sharing, the correspondence between allele-sharing statistics and the models for which they are optimal may also depend on which method is used to test for linkage.

Interactive effect of HLA and Gm tested in a study of 135 juvenile insulin-dependent diabetic families

Interaction between HLA and Gm for susceptibility to insulin-dependent diabetes (IDD) has been studied in 135 IDD families comparing HLA and Gm phenotype distributions in patients and sibling controls. The association analysis comparing the 135 index cases to 124 sibling controls did not show any significant interaction, but only a tendency for Gm 4,5 phenotypes to be more frequent in IDD patients, particularly in those who carried DR3/X. The sib pair analysis of 16 pairs of affected sibs did not show any distortion of segregation of Gm. On the other hand, among 98 sib pairs of one affected and one nonaffected sib, there was a significant distortion in favour of sib pairs with non-identical Gm phenotypes. However, no interaction between HLA and Gm was found. These results provide suggestive evidence that Gm or a locus very close to Gm could be involved in susceptibility to IDD.

Investigation of the mode of inheritance of the HLA associated diseases by the method of antigen genotype frequencies among diseased individuals

Statistical features of the method of antigen genotype frequencies among the diseased, for single and multiple disease associations at a locus, will be presented. A methodology to determine when a true intermediate mode of inheritance can be distinguished from strict recessive or additive inheritance will be developed. The effect of sporadics and ascertainment bias on the observed antigen genotype frequencies will be investigated. Data on ankylosing spondylitis, multiple sclerosis and dermatitis herpetiformis are very close to expectations for an additive (or dominant) mode of inheritance for the HLA-linked disease-predisposing gene, and data on hemochromatosis, insulin dependent diabetes mellitus and celiac disease are close to recessive expectations. If an intermediate model does apply in any of these cases, it must be an intermediate model that is fairly close to a strict recessive or dominant model; as appropriate. DR data for insulin dependent diabetes mellitus (IDDM) strongly indicate that there are two separate "disease" alleles, which exhibit negative complementation, predisposing individuals to IDDM, where the mode of inheritance of the "disease" alleles considered separately is close to recessive. In general, this method cannot rule out the existence of sporadics or a second disease-predisposing gene, when the penetrance values over the two disease-predisposing genes are strictly additive, for diseases showing agreement with additive (or dominant) modes of inheritance.

The distribution of HLA haplotypes in families with one untyped parent

For non-Mendelian diseases, the distribution of shared haplotypes in multiplex sibships provides a powerful tool to investigate the hypothesis that disease susceptibility genes map in the neighborhood of the HLA complex. Occasionally, ambiguous sibships arise because all offspring inherit an HLA haplotype that is identical in state from an untyped parent. The scoring procedure developed here uses the population frequency of the haplotype as well as the sibship size to estimate the probability that, with respect to the untyped parent, all sibs are identical by descent. The resulting score from an ambiguous sibship can then be combined with scores from unambiguous sibships to form the statistic suggested by Green & Woodrow. It is shown that failure to include this type of ambiguous sibship may result in a significant loss of information.

HLA haplotype study of 53 juvenile insulin-dependent diabetic (I.D.D.) families

R4 heterozygotes was observed. By contrast, the observed frequency of patients homozygous for DR3 or DR4 was not increased, but even slightly decreased. The data support a model of inheritance comprising at least two closely linked specifically "diabetic" loci (most of the time marked by B18, BfF1, DR3 and B15, BfS, DR4) and a non-specifically "diabetic" haplotype favouring auto-immunisation (most of the time marked by B8, BfS, DR3). This model is discussed in the light of the presented data and of those of the literature.