# Recent Advances of Integrative Bio-Omics Technologies to Improve Type 1 Diabetes (T1D) Care
## 5 Treatment of Diabetes  
Novel biomarkers and metabolic profiles can be leveraged to identify drug targets for the development of therapeutics, both for the treatment of T1D or more generally, the prevention of autoimmune disorders. In [PERSON] et al., investigators identified a gene mutation that causes individuals to be misdiagnosed as having T1D [49]. These individuals carry a mutated allele of the gene _hepatocyte nuclear factor-1 alpha_ (_HNF1a_), resulting in a monogenic form of diabetes, MODY3, which does not cause insulin dependency as found in most individuals with T1D. Differently than in regular T1D, sulphonylueas are more efficacious for MODY3 individuals when compared to insulin therapy and are the potentially better treatment option with a broader therapeutic window for this subpopulation [50]. This shows that accruing genomic information can alter the therapeutic outlook, even in diseases with a similar presentation, and can be used to create unique therapeutic approaches that will ultimately result in better outcomes for individuals [23]. Furthermore, as mentioned above, metagenomic studies and the technological advances in computational sciences, provide modern medicine with the opportunity to identify new drugs for the treatment of T1D and the repurposing of FDA-cleared compounds. In the [PERSON] et al. study, 992 proteins from previous proteomic and metabolomic studies were identified as potential drug targets [48]. These targets were cross-referenced with drug libraries to identify nine drugs with the potential to treat T1D [29; 51]. In repurposing existing medications, the investigators also explored how these targets were similar to others found in diseases such as Alzheimer's Disease, further emphasizing the value of large-scale \"-omics\" data [37, 52]. The ability to find associations between seemingly independent factors provides a more comprehensive understanding of disease states and allows for innovative approaches to therapeutics. Recent evidence points to shared etiological features between T1D and type 2 diabetes (T2D). Although, the two diseases have a very different clinical presentation and pathophysiology, Genome-Wide Association Studies (GWAS) have uncovered common loci, including the _transcription factor 7-like 2_ loci (_TCF7L2_). T1D and T2D disproportionally affect adults and youth, respectively, with T2D being more common in adults. However, it has been identified that \(\sim\)15% of common genes between T1D and T2D encode for proteins targeted by FDA-approved drugs [53, 54]. Some of those drugs cause diabetes or diabetes-like symptoms themselves, including hypoglycemia (i.e., streptozotocinocin, pembrolizumab, nivolumab, and doxorubicin). However, numerous compounds have been successfully used for the treatment of either form of diabetes and could be repurposed for the treatment of the other form. For example, disulfram, pirfenidone, and tretinoin have recently been successfully used to normalize glycemic dysregulation and treat complications in individuals with T1D and T2D. Another large-scale study performed on 61,427 participants with T1D, used fine-mapping, trans-ancestral and genomic analysis to identify novel potential drug targets. [PERSON] and coworkers, highlighted at least 50 candidate target genes, however only 12 are currently investigated in clinical trials for autoimmune diseases (including _IL-6R_) [55]. To prioritize the most promising therapeutics, researchers use a combination of methods to predict the interaction between drugs and their targets in the context of biological and disease system-level networks. Molecular docking analysis highlighted another group of FDA-approved compounds for their potential use as T1D therapeutics, including melatonin, resveratrol, eugenol, lapatinib, geldanamycin, and azathioprine.