Detecting genetic factors associated with chronic kidney disease using multiple measures and two novel kidney function biomarkers.

摘要

Chronic kidney disease (CKD) affects approximately 11.5% of U.S adults, and there is no sign of decline [1]. A key measure in the diagnosis of CKD is glomerular filtration rate (GFR), which is often estimated using equations based on endogenous biomarker levels. Although family studies showed that genetic factors explain about one-third of the variation in estimated GFR (eGFR), eGFR loci identified by genome-wide association studies to date explain less than 2% of the variation of eGFR on a population level. Genetic heterogeneity and the lack of precision in GFR estimates, amongst other factors, contribute the difficulties in identifying genes underlying renal function.;To partially remediate the preceding problems, Aim 1 of this thesis work used a measurement error model of GFR to examine how inclusion of multiple measures of eGFR impacts sample size and power in genetic association studies. Aims 2 and 3 were genome-wide association studies of two novel renal biomarkers, beta trace protein (BTP) and beta-2 microglobulin (B2M), conducted to understand the renal and non-renal genetic loci associated with these markers.;Results from Aim 1 showed that the use of multiple measures could lead to gain in precision, thus power; however, the gain depended greatly on the correlation structure of the errors associated with the multiple outcome measures. The work from Aim 2 followed up a novel locus of B2M in the human leukocyte antigen (HLA) region and identified classical HLA alleles that explained the GWAS signals using imputation. The work from Aim 3 identified a novel locus of BTP upstream of PTGDS, the gene that encode BTP, in European Americans and replicated this locus in African Americans. Top signals of each biomarker were not associated with creatinine-based eGFR, and, conversely, each marker was associated with a few of the GFR loci identified by previous GWASs of creatinine-based eGFR.;This thesis work improves genetic research of GFR determinants by identify ways to minimize the effect of systematic errors in detecting genetic association.