**3.2 Genome-wide association analysis (GWAS) and genetic risk scores**

The polygenic risk score method summarizes multiple genetic risk elements into a single score. There are benefits to establishing successful genetic risk scores. Over the past 20 years, the advancement in technology has allowed for publicly available genetic data. Combine this with the decreased costs in genotyping processes, the T1D genetic risk score (T1D GRS) has the opportunity to demonstrate its applicability for "disease prediction, discrimination, investigation of unusual cohorts, and investigation of biology in large datasets where genetic data are available" [41]. In 2018, a group following a cohort from The Environmental Determinants of Diabetes in the Young (TEDDY)

study created a genetic score based on 3 SNPs for HLA class II genotyping and 41 SNPs in other genes. The score identified newborn children, with no family history of T1D, who had a >10% risk for developing pre-symptomatic T1D, a nearly 2-fold higher risk than children identified by high-risk HLA genotypes alone [42].

GWAS previously associated the 3p21.31 locus with T1D [43]. The 3p21.31 locus encodes for many chemokine receptors including the C-C motif chemokine receptor 2 [44]. C-C motif chemokine ligand 2 (CCL2) is a pro-inflammatory chemokine that binds to CCR2 to promote T cell recruitment and macrophage activation. Tran et al analyzed CCL2 levels in the DAISY cohort and found paradoxically decreased CCL2 in T1D patients compared to controls. The proposed mechanism was that variants in the 3p21.31 genetic locus promote the development of T1D by increasing CCR2 expression, causing subsequent pancreatic islet cell destruction while simultaneously depleting the CCL2 pool [44].

The major limitation of genetic risk score development is the genetic heterogeneity among different ethnic groups and populations. This especially proves to be a challenge in identifying T1D susceptibility genes [1]. Most genetic risk score validation utilizes populations of European ancestry. Studies of genetic risk scores in African ancestry populations suggest that an ancestry-specific genetic risk score may improve the prediction of T1D [45].
