Understanding genetic architecture of kidney function through analysis of genome-wide arrays

chronic kidney disease;genome-wide association study;exome;copy number variation;Epidemiology

Li, ManArking, Dan ;

Johns Hopkins University

关键词: chronic kidney disease;    genome-wide association study;    exome;    copy number variation;    Epidemiology;   

Others  :  https://jscholarship.library.jhu.edu/bitstream/handle/1774.2/60511/LI-DISSERTATION-2015.pdf?sequence=1&isAllowed=y

瑞士|英语

来源: JOHNS HOPKINS DSpace Repository

【 摘 要 】

Chronic kidney disease (CKD) is a worldwide public health problem. In the United States, both incidence and prevalence of CKD are rising, leading to increasing morbidity, mortality, and medical costs. Kidney function, such as estimated glomerular filtration rate (eGFR), is heritable. Previous genome-wide association studies (GWAS) have identified 29 genetic loci for eGFR. However, most of the published variants are non-coding and explain a small proportion of eGFR heritability. Moreover, the vast majority of these studies were conducted in European ancestry populations, thus leaving even more unexplained heritability in African Americans. Our objective is to identify additional loci for eGFR in both the European ancestry and African American populations.We conducted a meta-analysis of genome-wide association studies for eGFR with data from up to 133,413 European ancestry individuals from 48 studies. We identified 24 novel genomic loci for kidney function and confirmed association at 29 previously identified ones. In addition, I combined the data from 133,413 European ancestry participants and 16,840 African American participants with trans-ethnic meta-analysis. All previously published loci and more than half of the newly identified loci in European ancestry participants were genome-wide significant in the trans-ethnic meta-analysis. The results from trans-ethnic meta-analysis suggest that some of the genetic loci of eGFR can be generalized across different ancestry groups and we were able to fine-map several of them by leveraging the linkage disequilibrium (LD) structure in African Americans. These observations highlight the importance of large-scale genomic studies in different ancestry groups for identifying kidney function susceptibility loci.Exonic genetic variants with minor allele frequency (MAF) < 5% had not been represented well in existing GWAS. We meta-analyzed the association result from 24 European ancestry studies and 5 African American studies between eGFR and the genetic variants genotyped on the Illumina HumanExome Beadchip (;;Exome Array”). In European ancestry, we identified 8 novel loci associated with eGFR that achieved exome array wide significance. The lowest frequency variant that achieved exome array wide significance is at EDEM3 (MAF=2%, p=5.25*10-8), which is involved in endoplasmic reticulum-associated degradation. We also identified a novel gene-based association with eGFR in SOS2 gene using gene-based statistical tests. In African American, we identified 4 novel loci with eGFR and 1 novel gene enriched with rare variants. Our findings suggest there are additional associations to be discovered by leveraging data from coding regions and low frequency variants.Copy number variants (CNVs) have not been explicitly examined in the current GWAS pipeline. To increase our understanding of the role of CNVs in influencing eGFR, we identified 226 and 256 copy number polymorphisms (CNPs) in the European ancestry and African American cohorts in the ARIC study from high-throughput Affymetix arrays using a hidden Markov model and performed genome-wide association analysis of the CNPs and eGFR in each ancestry group separately. We identified a CNP in the European ancestry population on chromosome 5 located in a gene desert approaching Bonferroni statistical significance. The region appears to have transcription factor binding sites as measured from chip-seq experiments in human kidney cell lines. Lastly, this work showed that common CNVs detectable with these methods do not contribute substantially to the heritability of eGFR and further investigations in low-frequency CNVs and other types of CNVs are needed.With these new genotyping technologies and new statistical tools, we were able to look at the association of kidney function with various genetic data. We were able to confirm the known eGFR loci and discovered new loci associated with eGFR that may shed light on new biological pathway related to kidney function and potentially influence targets for treatment of CKD. These results indicate that the genetic architecture of kidney function is more complicated and require further investigation.