Kidney Week

Abstract: FR-OR068

Genome-Wide Polygenic Score and Urinary Tract Stone Diagnosis in a Multiethnic Cohort

Session Information

• Genetic Diseases and the Kidneys
  November 08, 2019 | Location: 144, Walter E. Washington Convention Center
  Abstract Time: 05:54 PM - 06:06 PM

Category: Genetic Diseases of the Kidneys

• 1002 Genetic Diseases of the Kidneys: Non-Cystic

Authors

• Paranjpe, Ishan, Icahn School of Medicine at Mount Sinai, New York, New York, United States

Ishan Paranjpe



Ishan is a second year medical student at Mount Sinai in New York City. He has an interest in applying statistical methods and bioinformatics approaches to precision medicine.

• Paranjpe, Manish, Harvard Medical School, Boston, Massachusetts, United States

Manish Paranjpe,

• Chan, Lili, Icahn School of Medicine at Mount Sinai, New York, New York, United States

Lili Chan,

• He, John Cijiang, Mount Sinai School of Medicine, New York, New York, United States

John Cijiang He,

• Coca, Steven G., Icahn School of Medicine at Mount Sinai, New York, New York, United States

Steven G. Coca,

• Do, Ron, Icahn School of Medicine at Mount Sinai, New York, New York, United States

Ron Do,

• Gupta, Mantu, Mount Sinai, New York, New York, United States

Mantu Gupta,

• Nadkarni, Girish N., Icahn School of Medicine at Mount Sinai, New York, New York, United States

Girish N. Nadkarni,

Background

Urinary tract stones are highly heritable and clinical risk factors only explain a portion of stone occurrence. Additionally, urinary tract stones may occur in the absence of risk factors. We aimed to develop a polygenic score for association with urinary tract stones.

Methods

We used genome-wide association studies (GWAS) summary statistics for urinary tract stones from the UK Biobank (n=361,141), to generate polygenic scores with increasing number of single nucleotide variants (SNVs). We then determined the association of the best performing polygenic score with urinary tract stone diagnosis in individuals with and without clinical risk factors (diabetes, hypertension, gout and obesity) in a biobanked cohort using imputed genotyping data (BioMe Biobank, 1208 cases, 30,233 controls) and calculated adjusted odds ratios (aOR) with 95% confidence intervals (CI) adjusting for age, sex and genetic ancestry.

Results

A genome wide polygenic score (GPS_stone) utilizing the most SNVs (~7 million) explained the highest variance and was chosen for further analysis. In individuals with at least one risk factor, every standard deviation (SD) increase in GPS_stone was associated with a 14% increase in odds of diagnosis (aOR 1.14; 1.08 – 1.22; p = 4.3 x 10^-5). In individuals without clinical risk factors, every SD increase in GPS_stone was associated with a 30% increase in odds of diagnosis (aOR 1.3; 1.1 – 1.5; p = 4.7 x 10^-3, Figure 1). In these individuals, the top 10% had four-fold increased odds of diagnosis relative to the lowest 10% (aOR 3.7; 95% CI 1.7 – 9.3; p = 0.003).

Conclusion

We developed a genomic wide risk score, GPS_stone, that is associated with urinary tract stones overall and even in the absence of known clinical risk factors identifies a subgroup with genetic risk comparable to a monogenic mutation.

Funding

• NIDDK Support