Home / Resources / Clinical Gems / International Textbook of Diabetes Mellitus, 4th Ed., Excerpt #169: Molecular Genetics of Type 1 Diabetes Part 6

International Textbook of Diabetes Mellitus, 4th Ed., Excerpt #169: Molecular Genetics of Type 1 Diabetes Part 6

Mar 19, 2019
 

Other genetic markers—the “missing heritability”

Collectively the confirmed T1DM risk loci account for approximately 70% of disease heritability, with around 40–50% being attributed to the HLA genes. These figures are well in excess of the 10–20% of heritability of other complex diseases that can be explained by genetic factors. Experience from GWAS suggests that overall disease risk is likely to be influenced by many genes, most having a weak biologic effect. This may be due to the subtle effects of risk alleles on gene function or the modest contribution of individual gene products to the biologic pathways involved in disease pathogenesis. None of the confirmed T1DM risk variants have complete penetrance and are therefore neither necessary nor sufficient for disease to develop. This makes it difficult to use genetic profiling to predict disease risk as T1DM can develop in the absence of susceptibility variants and does not always occur in subjects with known risk markers. Furthermore the combination of susceptibility variants underlying T1DM may differ between populations or between individuals according to their exposure to different environmental triggers. Further GWAS efforts with ever-increasing sample sizes may discover additional common risk SNPs, but their effect sizes are likely to be similar to, or smaller than, those already identified and they are unlikely to explain the missing 30% of heritability.

Recently, interest has grown in the contribution to T1DM of highly penetrant, low-frequency variants, as these may be expected to cause severe immune dysregulation in the small percentage of individuals who carry them and may therefore account for the missing genetic risk. It is possible that the end-point of autoimmune β-cell destruction could result from a multitude of different immune dysregulation mechanisms, each related to the effects of different rare genetic variants. These loci could therefore be of crucial importance in a substantial proportion of T1DM cases. Such variants are too infrequent to be identified by GWAS, but can be picked up by extensive resequencing of candidate genes. This approach has identified four rare variants in the IFIH1 gene that independently lower the risk of T1DM and are more strongly associated with disease than the common polymorphisms identified by GWAS [56]. All four  variants were predicted to alter the expression and structure of the encoded protein and two (a nonsense mutation in exon 10 (E627X) and a nonsynonymous mutation in exon 13 (Ile923Val)) were subsequently shown to influence the production of inflammatory cytokines in peripheral blood cells [57]. Whole-exome and whole-genome sequencing strategies are now being used to identify other rare variants that influence disease risk.

The inability of existing genetic approaches to directly identify causal variants, combined with the genetic and phenotypic heterogeneity of T1DM, makes it unlikely that the whole spectrum of disease susceptibility variants can be identified by examining statistical associations with sequence variants. Functional genomics and mechanistic studies are required to elucidate important pathogenic pathways, identify disease loci relevant to these pathways and determine genotype-phenotype correlations. Transcriptomic analysis of lymphoid tissue and pancreatic islets can be used to identify genes that are differentially expressed in different states of immune activation, allowing pathogenically relevant gene networks to be determined. These can then be screened for genetic variants that influence specific molecular subphenotypes. Further work is also needed to understand the mechanisms underlying the regulation of susceptibility gene function.The impact of epigenetic modification should also be explored further as this will integrate the influence of environmental factors on disease risk.

Click here to view all Chapter 30 references.