# Recent Advances of Integrative Bio-Omics Technologies to Improve Type 1 Diabetes (T1D) Care
## 3 Pathogenesis and Biomarkers  
Modern technologies and advancements in medicine have progressed past the \"one size fits all\" approach in therapeutic options. One important tool in this context is the molecular analysis of gene variants to identify genes involved in the pathogenesis of T1D [7; 21; 22; 23]. The products of these genes often referred to as biomarkers, may provide information related to better disease treatment and management. Especially studies that included micro-RNA expression analysis have aided in the understanding of the pathogenesis of T1D. New-onset T1D has been associated with the overexpression of the gene _Forkhead Box O3_ (FOXO3) and a low expression of a pancreas-specific microRNA, called miR-375 [24; 25]. FOXO3 is a transcription factor involved in the development and differentiation of regulatory T-cells. High expression levels of FOXO3, along with the ongoing islet autoimmune destruction, in new-onset T1D individuals may explain the exhaustion and dysfunction seen in their regulatory T-cell populations [26; 27; 28]. miR-375 has been shown to target _insulin-induced gene 2_ (_INSIG2), which regulates insulin secretion and beta-cellmass [25]. The gene expression levels of miR375 and _FOXO3_ could serve as biomarkers for T1D and should be further explored to possibly prevent the progression of new-onset diagnosis of the disease. Additionally, other genes and microRNAs have been identified as showing signs of differential expression in the development of T1D. [PERSON] et al. identified two chromosomal regions associated with T1D diagnosis age, which are found in the chromosomal location Chr17q12 and near the gene _P.H.D. finger protein 20 like 1 (ph/2011)_ on chromosome 8 [12]. In individuals with T1D miR-148a and miR-181a are found to be elevated in the blood, and miR-21 and miR-155 are elevated in urine [29]. These genes and microRNAs may prove to be useful biomarkers for the prediction of T1D development and warrant further investigation. Metabolomic data offers new insights into T1D-related autoimmunity by assessing the role of gene regulation and dietary exposure in the development of T1D. Gene expression-associated dysregulation of vitamins in circulation were assessed in the TEDDY study, yielding results indicative of lower plasma Vitamin C and D levels at infancy in HLA-DR3/DR4 children [9]. In a study by [PERSON] et al., in vitro treatment with 1,25(O.H. )\({}_{2}\)D\({}_{3}\) reduced proinflammatory cytokines, including interleukin 6 (IL-6), chemokine 2 (CCL-2), interleukin 23 A (IL-23A), and interleukin 15 (IL-15). Furthermore, the treatment also increased levels of anti-inflammatory cytokines (such as interleukin 10 (IL-10)) and affected the programmed death-ligand 1 gene (PD-L1) in individuals with T1D [30; 31]. Animal studies demonstrated that upregulation of PD-L1 expression can be preventive against T1D progression as it leads to the persistence of neo-islet supporting insulin production [32]. By assessing gene regulation as well as nutrient intake, metabolomic data provide the most practical information in creating risk profiles for the development of autoimmune diseases, such as T1D. In fact, researchers have successfully used metabolomic data to identify biomarkers predicting the genetic susceptibility to diet-induced beta-cell failure [31]. Specifically, in individuals with the rare genetic syndrome called Mutant INS-gene-induced Diabetes of Youth (MIDY), a mutation in the _proinsulin-R(B22)E_ and \(Q\) causes misfolding of the proinsulin protein in the endoplasmic reticulum. This triggers rapid insulin deficiencies and results in glucose intolerance upon exposure to a high-fat diet [33; 34; 35]. Interestingly, molecular studies in animal models propose that evolution is maintaining islet cell heterogeneity and that mutations affecting protein-folding might serve as important predictors for diabetes outcomes, especially hypoglycemia [33].