Genomics of the Orang Asli and Malays: functional modelling of the pathogenic SNPS for cancers and risk prediction for eating behaviours, nutrient deficiencies and metabolic disorders / Nurul Ain Khoruddin

Single-nucleotide polymorphisms (SNPs) are the most common genetic variations associated with various human diseases, including cancers and nutritional disorders. Genome-wide association studies (GWAS) had discovered numerous SNPs related to increased risk of cancers such as breast cancer, colorectal cancer, and leukaemia as well as nutritional disorders. However, GWAS are frequently carried out in certain populations, for which the Orang Asli and Malays were excluded. By mining the whole-genome sequence of the 98 Orang Asli and 96 Malays, genome variations were identified and two bioinformatic pipelines were established to identify and evaluate the impact of pathogenic SNPs that may increase the risk of cancers, eating behaviours, nutrient deficiency, and metabolic disorders among them. A database of genotype-predicted phenotypes was built in this study. For the cancer risk prediction pipeline, five different in silico tools, SIFT, PROVEAN, PolyPhen-2, Condel, and PANTHER, were utilised to predict and analyse the functional effect of the SNPs. Out of the 80 cancer-related nsSNPs from the GWAS dataset, 52 nsSNPs were found among the Orang Asli and Malays. Three nsSNPs, rs1126809 (TYR), rs10936600 (LRRC34), and rs757978 (FARP2) were identified as the most damaging pathogenic variants associated with basal cell carcinoma or squamous cell carcinoma, multiple myeloma and chronic lymphocytic leukaemia, respectively. These mutations modify the protein interface and change the allosteric sites of the respective proteins. As the TYR, LRRC34, and FARP2 genes are involved in so many biological processes, including cell proliferation, differentiation, growth, and survival, any loss of protein function might lead to cancer formation. Thus, rs1126809, rs10936600, and rs757978 are the significant pathogenic variants that are likely to increase the risks of cancers among the Orang Asli and Malays. For the nutrient-related variant prediction pipeline, three bioinformatics tools (VCFtools, ANNOVAR and VEP) were used to identify and annotate the SNPs. The genetic risks of the eating behaviours, nutrient deficiencies, and metabolic disorders of both cohorts, Orang Asli and Malays, were profiled. The Orang Asli and the Malays genomes have an average of 70 SNPs associated with eating behaviours, 81 SNPs associated with nutrient deficiencies and 80 SNPs associated with metabolic disorders. The genetic markers identified in this study provided the basis for phenotype-genotype studies to be conducted within the Malaysian populations so that an association between genetic markers with cancers, eating behaviours, nutrient deficiency, and metabolic disorders can be established. It is believed that this bioinformatics approach would complement the healthcare providers to offer appropriate preventive or corrective measures for individuals at risk. Thus, the developed pipeline and the database generated from this study are fundamental in implementing precision medicine for cancers and nutrient disorders. The data may be used to strategise educational programmes or interventions to increase awareness and promote a healthy lifestyle among the OA and Malays. However, the functions and effects of the identified variants still require wet lab experiments for further investigations.