ROLE OF GENOMICS AND PROTEOMICS IN DISEASE DIAGNOSIS

Genomics and proteomics are quickly transforming the practice of clinical medicine with regard to disease diagnosis through early, precise and personalized detection of complex disorders. In this study, we explore how whole-exome sequencing and mass spectrometry-based proteomic profiling can be combined to produce greater diagnostic utility in three key clinical areas: breast cancer, Alzheimer disease, and type 2 diabetes mellitus. A group of 120 participants (patients and healthy controls) were enrolled to undergo comprehensive genomic and proteomic analysis. Important disease specific genetic mutations, e.g. BRCA1/2/HER2 in breast cancer, APOE 4 in Alzheimer disease, TCF7L2 in diabetes and their relationship with respective protein biomarkers, e.g. HER2 protein, tau, and amyloid- 82, inflammatory cytokines were identified. The diagnostic accuracy of statistical and machine learning models were high (up to 94.2%), and gene variants were strongly correlated with protein expression levels (r > 0.7). These results affirm that multi-omics in tandem increases the classification of disease and biomarker identification in a grand magnitude compared to traditional methods. The article underlines the potential of genomics and proteomics in enabling earlier accurate diagnosis and informing customized medicine, but also points to the issue of validation upon greater scale and the application of apparatus to clinical practice.