The lifetime risk of type 1 diabetes for a member of the general population is often quoted as 0.4%. This increases to >1% if the mother has diabetes and intriguingly to >3% if the father also has type 1 diabetes. The sibling risk is 6% (15 times greater than in a member of the general population). Second degree relatives are also at increased risk, although this is less easy to quantify. Before rational therapies to delay or prevent the onset of type 1 diabetes can be offered in a clinical setting, accurate identification of those at risk is essential. Autoimmunity is initiated in infancy, and primary prevention trials require those at high genetic risk to be identified at birth or before islet autoantibodies are detectable. This relies on calculation of genetic risk.
Calculating genetic risk for a complex disease is challenging. Over the last three decades, the study of type 1 diabetes has led the field in the identification of genes underlying complex multifactorial diseases. Unlike single gene disorders, which are inherited in distinct predictable Mendelian patterns, in multifactorial diseases such as type 1 diabetes, identification of the combination of underlying causative genes is still a work in progress.
It has been estimated that about half of the genetic risk of type 1 diabetes can be accounted for by human leucocyte antigen (HLA)-mediated susceptibility and while recent genome-wide association studies have resulted in an explosion of information regarding genetic susceptibility to type 1 diabetes, HLA remains the most important genetic determinant.
90–95% of the young children with type 1 diabetes carry either or both of the susceptibility haplotypes, DRB103-DQA10501-DQB1*0201/DRB10401-DQA10301-DQB1*0302, whereas the protective DR2-DQB1*0602 is present in <0.1%. HLA class II haplotypes have been ranked in a risk hierarchy, and those in the general population with the highest risk genotype DRB103-DQA10501-DQB1*0201/DRB10401-DQA10301-DQB1*0302 have a 5% absolute risk of getting diabetes by the age of 15 years.
A Belgian study suggests that genetic strategies can be used to identify the 10% of the general population that contains most future cases of type 1 diabetes, but the majority of this genetically at-risk population will never develop islet autoimmunity.
It is possible that screening the general population for high-risk HLA genes with islet autoantibody follow-up could represent a strategy to identify most future cases of type 1 diabetes. This strategy has been used by the DIPP (Diabetes Prediction and Prevention Trial) study in Finland and by the Diabetes Autoimmunity Study in the Young (DAISY) study in the USA.
In DIPP, all newborn infants in a defined region carrying HLA DQB1 genotypes conferring susceptibility to type 1 diabetes were observed from birth for the appearance of diabetes-associated autoantibodies: 116,720 consecutively born infants were screened for high-risk HLA DQB1 genes; 17,397 (6.7%) infants had increased genetic risk and 11,225 consented to follow-up for islet autoantibody screening. Two different islet autoantibodies were detected in at least two consecutive samples in 328 (2.9% of those consented).
In the prospective DAISY cohort study, 27,000 newborn infants were screened for high-risk HLA genotypes and 1135 (4.2%) were identified for follow-up.
Extreme risk for type 1 diabetes
A study of 48 families with siblings matched for high risk DR3/4 genotype participating in the DAISY study recently reported that siblings who shared both extended high risk haplotypes identical by descent (IBD) with the proband had a 55% risk for type 1 diabetes by the age of 12 years and that 63% of these were positive for islet autoantibodies at age 7 years. This compares with a 7% risk of diabetes by age 12 years in HLA DR/DQ identical siblings who were not identical by descent.
This 'extreme risk' IBD haplotype is now used to identify individuals at risk of T1D for therapeutic intervention in Pre-POINT – a clinical trial using oral insulin very early in life in at risk siblings to prevent appearance of islet autoantibodies.
HLA susceptibility (and therefore genetic risk) is dynamic
Intriguingly, as the incidence of type 1 diabetes has been increasing, the frequency of HLA class II susceptibility genotypes in affected individuals has decreased. The frequency of individuals with the highest risk genotype DRB103-DQB10201/DRB10401-DQB10302 has been decreasing over the last half century, while the frequency of those with the intermediate genotypes (carrying only one of the haplotypes DRB103-DQB10201 or DRB10401-DQB10302) has increased. As the gene pool cannot change over this time frame, it appears that increasing environmental pressure is precipitating disease in individuals with less genetic susceptibility thus contributing to the ongoing increasing numbers of children developing type 1 diabetes. This dynamic in assessment of genetic risk for type 1 diabetes will potentially create difficulties for therapeutic trials where accurate assessment of risk is crucial.
Recent genome-wide association (GWA) studies have resulted in the identification of more than 40 non-HLA susceptibility loci for type 1 diabetes. The success of GWA studies comes not only from increased power due to increased number of patients and controls available for analysis, but is also attributable to the availability of high-throughput genotyping arrays and the HapMap project that defined areas of linkage disequilibrium throughout the genome to allow maximum genetic information to be obtained from analysing a minimum number of genetic polymorphisms.
The non-HLA genes associated with type 1 diabetes have only had a limited impact on genetic risk indicating that other mechanisms must influence the genetic contribution to disease. GWAS detect common variants associated with disease, but some yet to be identified rare variants may have greater effects on risk.
Sequencing analysis has shown that some loci are deleted or present in multiple copies. If such a region contains transcription factor binding sites or enhancers, then there could be a functional or phenotypic effects. These copy number variants (CNV) are not easily detected by current high-throughput genotyping methods and emerging techniques will clarify their role in susceptibility to type 1 diabetes.
The other unknown factor is potentially the role of imprinting and epigenetics. Genomic imprinting is the phenomenon by which some genes are preferentially expressed if they are maternally inherited, whereas others are expressed if they are paternally inherited. Several studies have suggested differences in paternal and maternal inheritance patterns in type 1 diabetes, making imprinting an important possible mechanism.
Genomic imprinting is not the only means by which transcription is altered. In particular, microRNAs (miRNAs) that have been identified in viruses, plants and animals have the capacity to regulate gene expression in a sequence-specific manner. A greater understanding of miRNAs in type 1 diabetes could provide unique insights into how environmental agents can alter the risk of disease.
If the ability to predict an outcome reflects scientific understanding, there is still some way to go in type 1 diabetes. A first degree family history is, empirically, about as predictive of diabetes as a range of sophisticated genetic investigations performed in members of the general population. Within family members, genetic testing can however stratify risk, for example by identifying those at extreme risk or with protective alleles. Second generation genetic investigation does however promise to provide greater insight into the interaction between genes and environment in the causation of type 1 diabetes.
^ Lambert AP, Gillespie KM, Thomson G, et al. Absolute risk of childhood-onset type 1 diabetes defined by human leukocyte antigen class II a population-based study in the United Kingdom. J Clin Endocrinol Metabol 2004;89:4037–43
^ Van der Auwera BJ, Schuit FC, et al. Relative and absolute HLA-DQA1-DQB1 linked risk for developing type I diabetes before 40 years of age in the Belgian implications for future prevention studies. Human Immunol 2012;63:40–50
^ Kukko M, Virtanen SM, Toivonen A, et al. Geographical variation in risk HLA-DQB1 genotypes for type 1 diabetes and signs of beta-cell autoimmunity in a high-incidence country. Diabetes Care 2004;27:676–81
^ Barker JM, Barriga KJ, Yu L, et al. Prediction of autoantibody positivity and progression to type 1 Diabetes Autoimmunity Study in the Young (DAISY). J Clin Endocrinol Metab 2004;89:3896–902.
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^ Bonifacio E, Achenbach P, Pan L, et al. Mucosal insulin vaccination for type 1 diabetes prevention. Exp Clin Endocrinol Diabetes 2008;116 Suppl 1:S26–S29
^ Gillespie KM, Bain SC, Barnett AH, et al. The rising incidence of childhood type 1 diabetes and reduced contribution of high-risk HLA haplotypes. Lancet 2004;364:1699–1700
^ Todd JA, Walker NM, Cooper JD, et al. Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes, Nat Genet 2007;39:857–64