Genetic Variations and Diabetes

There is ample evidence showing that type 1 diabetes (DM1) and type 2 diabetes (DM2) are complex genetic diseases (3, 4). For both DM1 and DM2, the concordance rate of monozygotic twins is much higher than that of dizygotic twins. In DM1, the concordance rate for monozygotic twins is reported to range between 21 and 70% and that for dizygotic twins to range between 0 and 13% (5). In DM2, the concordance rate for monozygotic twins is 63%, and for dizygotic twins it is 43% (6). In addition, for both DM1 and DM2, the sibling of a patient has much higher risk than the general population. The risk to siblings of type 1 diabetic individuals is about 6%, compared to about 0.4% in the general European population (4). Siblings of individuals with DM2 have about fourfold to sixfold higher risk than a random individual (3). However, although the genetic nature of the common types of diabetes is obvious, the pathogenesis is complicated, involving multiple genes, environment

Fig. 1. SNP classification.

factors, and the interaction of genes and environment. At the same time, rare types of diabetes, with Mendelian inheritance from rare mutations, are also known.

There are two general methods used to locate diabetes genes, that is, linkage study and association study. A linkage study examines the genome regions shared by affected relatives, based on the coseg-regation of genes found together in close proximity on a chromosome. An association study examines the coexistence of genetic markers with the disease. There are two types of association study, that is, the population-based study using a case-control format and the family-based study using the transmission disequilibrium test (TDT). Compared with the family-based study, the population-based study has relatively higher statistical power, that is, less demanding on the sample size. However, the population-based study can suffer from bias from population stratification. Population stratification occurs when there are multiple subgroups with different allele frequencies within a population. The different underlying allele frequencies in sampled subgroups might be independent of the disease and can lead to erroneous conclusions of disease relevance (7). The advantage of a family-based study is that it is immune to the bias from population stratification. But in many cases, it is hard to collect complete family samples, especially for, late onset genetic diseases, such as DM2.

Association studies are more powerful, but each marker covers a very small part of the genome and must be well targeted. Marker targeting has been done in three ways: (1) Association studies can follow a linkage study. The genetic regions identified by linkage typically extend over several megabases and include many genes inside the region. Therefore, following the linkage study, an association study is needed to pinpoint the disease causative gene. (2) Association studies can use a candidate gene approach. For a candidate gene implicated in a disease, an association study can address its disease causative effect, no matter whether the gene is located in an interesting region from linkage study. Successful examples of this approach are the DM1 genes INS(8), PTPN22(9), and IL2RA(10). (3) Most recently there are genome-wide association (GWA) studies. Taking advantage of the recent availability of high-throughput genotyping platforms, for example, the Illumina Beadarray and the Affymetrix GeneChips, researchers are able to screen the whole genome for disease associations with high-density coverage. This has rapidly accelerated diabetes gene discovery in the past year or two. In what follows, we will discuss the genetic basis of different types of diabetes in detail, based largely on recent progress.

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