SAT-191 WHOLE GENOME ANALYSIS OF ABORIGINAL AUSTRALIANS REVEALS VARIANTS ASSOCIATED WITH KIDNEY DISEASE

Abstract

Indigenous Australians in remote areas are up to 20 times more likely to develop end stage renal disease than non-Indigenous Australians. Remote communities in Western Australia and Northern Territory are experiencing an escalating renal disease epidemic, such as the Tiwi people who are at a high risk of kidney disease, significantly reducing their life expectancy. Genetic factors are though to affect 36-75% of kidney function and chronic kidney disease (CKD) progression. Population-scale genomic studies have established that the frequencies of specific disease-associated alleles vary substantially between populations, and identifying these alleles can offer insights useful for preventing, diagnosing, and treating these diseases in a population-specific manner. The Tiwi people have participated in a 25 year longitudinal study of chronic disease incidence, progression, treatments, and outcomes, offering a wealth of biochemical and physical phenotyping data. We have previously shown that there is a strong genetic component to kidney disease among the Tiwi people, but the exact alleles involved remained uncertain. In the present study, we conducted a whole genome sequencing (WGS) analysis of 120 individuals from the Tiwi islands and identified several genetic loci associated with traits linked to kidney disease, including serum creatinine, EGFR, and uric acid levels. Study participants were categorized as cases (n=60) or controls (n=60) for kidney disease, based on albumin creatinine ratio and estimated glomerular filtration rate. We sequenced the whole genomes of 120 participants at 30x coverage using HiSeq X Series, aligned reads to the reference human genome using the BWA tool, and then employed the GATK pipeline to identify genetic variants. Six computational approaches were used to assess the functional impact of genetic variants (SIFT, Polyphen2, MutationTaster2, LRT, FATHMM, and PROVEAN), and we probed the association of identified variants with kidney disease using the ClinVar, GAD, and GWAS databases. MAF (Minor Allele Frequency) analysis was carried out using VCFtools and in-house scripts. Notably, we utilized a customized database of genes associated with kidney disease curated from literature sources and currently available diagnostic gene panels. We identified 12,507,010 variants, of which 19,899 were predicted to be deleterious. We observed an at least 2-fold allelic difference between cases and controls for 569 polymorphic variants, of which 16% were present in the 1000 Genome data (<=1 MAF), and 73% were not present in the 1000G dataset. Further focused kidney disease gene analysis showed that 8 variants were associated with kidney disease. We observed a remarkably high frequency (3-fold) in alleles associated with Alport syndrome in cases relative to controls. Our results suggest population-specific CKD risk alleles exist in the Tiwi people that were not detected by previous lower coverage population genomics studies, and we are collecting samples to validate these findings. These novel variants offer a potential means of screening individuals in this population to identify those at risk of kidney disease. The combination of these genomic data with the available 25 years of compiled longitudinal clinical data represents an invaluable resource that can be harnessed to improve health among all Indigenous Australian populations.