Population genetics linkage disequilibrium and linkage

For some diseases, a given HLA allele may be strongly associated with disease in some populations but not in others. This apparent discrepancy may reflect the different distribution of alleles in different populations. For example, DR3 (DRBI *030I-DQB1ยป0201) is associated with IDDM in most populations but not in Japan, where DR3 is extremely rare. Another possible explanation for discrepancies in the observed disease associations in different populations are differences in the patterns of linkage disequilibrium (see below). For example, DPB1*0401 is increased among IDDM patients in China but not in other populations. This association can be attributed to strong linkage disequilibrium with DR3 in Chinese populations; these alleles at DRBI and DPB1 are not in linkage disequilibrium in other populations. For diseases involving an infectious pathogen, differences in HLA associations in different populations could, in principle, be attributed to genetic differences in the pathogen. In the Gambia, DRBI* 1302 appears to confer resistance to severe malaria whereas in Kenya, DRB1*0101 but not DRBI *1302 appears to be protective. The most common strain of Plasmodium falciparum responsible for malaria in these two African countries is different; this difference may account for the difference in the observed HLA associations.

In some cases, the differing incidences of a given disease in different populations or countries can be attributed, at least in part, to the differences in the frequency of the relevant HLA alleles. Pemphigus vulgaris, for example, is frequent among Ashkenazi Jewish populations; one explanation may be that the disease-associated DR4 allele, DRB1*0402, is the most common DR4 allele in this population but is an infrequent DR4 subtype in other populations. For some HLA-associated diseases, several different alleles may confer susceptibility to varying extents; thus, if a high susceptibility allele found in a variety of populations is rare or is absent in a given population, the most strongly associated allele in this population may be one that appears to be neutral or weakly predisposing in the other populations.

As noted above, the phenomenon of linkage disequilibrium (LD), the nonrandom association of particular alleles at linked loci, can complicate the interpretation of disease association studies. Some DRB1-DQA1-DQB1 haplotypes (specific combinations of linked alleles) are very much more frequent than any other combination of alleles. In any given population, the number of observed haplotypes is typically a very small proportion of all possible haplotypic combinations. Within a given population, the association of particular DRB1, DQA1 and DQB1 alleles can be almost absolute. For example, DRB1 *0301 (found in Africans, Caucasians and, more rarely, in Asians) is coupled, almost invariably to DQA1 * 0501 and DQB1*0201 whereas DRB1* 0302 (found only in Africans) is coupled to DQAl* 0401 and DQB1*0402. The set of DRBl*0405-con-taining haplotypes illustrate the population-related patterns of linkage disequilibrium. In Caucasians, this allele is coupled to DQA1*0301 and DQB1 * 0302. Among Africans, DRB1*0405 can be coupled to DQA1*0301 and DQB1*0201 and in the Japanese, it is coupled to DQA1*0301 and DQB1* 0401. In the Philippines, DRB1*0405 is coupled to DQA1 *0101 and DQB1*0503.

Strong linkage disequilibrium between closely linked loci such as DRB1, DQA1 and DQB1 (DQA1 and DQB1 are only 12 kb apart) may reflect a lack of crossing over between the loci or, more likely, selection for particular combinations of alleles. In principle, population admixture may also create linkage disequilibrium patterns but this is unlikely to account for the extensive disequilibrium found in virtually all human populations. The presence of linkage disequilibrium in human populations can, in any given population, make it difficult to identify which gene on a disease-associated haplotype is responsible for the observed association. Thus, a disease could show a strong association with a given DRB1 allele (e.g. DRB1*0301), but alleles at nearby loci (e.g. DQA1, DQB1, HLA-B or other non-HLA loci) that are in linkage disequilibrium with DRB1*0301 could, in principle, be responsible for the observed disease association. Some HLA haplotypes reveal patterns of linkage disequilibrium that extend toward the centromere to DPB1 and toward the telomere to HLA-B and HLA-A. These so-called 'extended haplotypes' (e.g. Al, B8, DRB1*301, DQB1 *0201, DPB1 *0101) have been taken as evidence for strong selection for particular haplotypic combinations. Because the patterns of linkage disequilibrium for alleles at the HLA loci can vary in different populations, studies of the same disease in different populations can be very instructive in helping to identify which gene or combination of genes on a given haplotype may be responsible for the observed disease association.

In addition to association studies, the role of genes in the HLA region in the pathogenesis of certain diseases has been demonstrated by linkage analysis. Linkage analysis follows the cosegregation of alleles with disease in large multiplex pedigrees. Many disease genes have 'incomplete penetrance' and, similarly, for alleles conferring disease predisposition, many unaffected individuals in a pedigree may carry the susceptibility alleles. Given the confounding effect of incomplete penetrance for conventional cosegregation studies, a highly informative approach has been to focus on the analysis of the genetic markers only among affected sib pairs. The null hypothesis of no linkage would predict a random distribution among affected sib pairs for chromosomes or haplotypes detected with a given genetic marker (i.e. an HLA locus or a variable number tandem repeat locus). The expected random distribution for affected sib pairs is 25% with two identical-by-descent (IBD) haplotypes, 50% for those containing one IBD haplotype and 25% for those containing zero IBD haplotypes. Excess haplotype sharing among affected sib pairs relative to the distribution predicted by the null hypothesis is evidence of linkage. This approach (termed nonparametric) has the virtue of not requiring assumptions about parameters such as genetic dominance or recessivity, or estimates of penetrance, as do conventional (parametric) linkage analyses.

In general, linkage studies have properties distinct from association studies. In case-control studies, a positive association for a given marker and a specific disease will be obtained only if the marker allele is in linkage disequilibrium with the true disease gene, that is only if the marker locus is physically close to the disease locus, usually significantly less than 1 cM (1% recombination). In linkage studies, however, the marker need not be in linkage disequilibrium with the disease locus, only close enough so that recombination is uncommon. Linkage methods are expected to have reduced power when the disease allele is frequent in the general population. In a genome-wide scan for disease genes, when a genetic region has been identified by linkage methods, association (or linkage disequilibrium) methods are useful for homing in on a much smaller region. In terms of sample acquisition, a large number of family samples, however, is usually harder to obtain than samples for case-control studies.

Studies of multiplex families or of affected sib pairs also allow one to estimate the proportion of the total genetic risk attributable to a given genetic-region defined by a specific marker; this approach involves calculating a value (\J from the ratio of expected to observed affected sib pairs that share zero haplotypes. For IDDM, for example, the observed proportion of affected sib pairs sharing zero HLA haplotypes is about 0.06; the expected proportion is 0.25, yielding a V, for HLA of about 4.1. A proportion of about 50% for the total genetic risk for IDDM attributable to the HLA region can be calculated, making certain assumptions, from these values.

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