Abdominal obesity and Diabetic Kidney Disease: A Mendelian Randomization Study
Aim: Diabetic kidney disease (DKD) develops in approximately 40% of patients who are diabetic and is the leading cause of end stage renal disease worldwide. Our previous study indicated that abdominal obesity is an important risk factor of DKD, consistent with several observational studies. However, the causal correlation between the abdominal obesity and DKD remains unclear.
Scientific rational: To identify the causal correlation between the abdominal obesity and DKD, we intend to use the approach of Mendelian randomization, which has traditionally been used to determine whether a candidate risk factor is causally related to a clinical outcome using the genotype as an instrument. In a Mendelian randomization study, genetic variants is used as to divide a population into genotypic subgroups, in an analogous way as how participants are divided into arms in a randomized controlled trial. By dividing participants into subgroups with different genetically exposures to the risk factor, we can evaluate the causal effect of the risk factor on disease risk. A recent large-scale Genome wide association study (GWAS) identified 48 SNPs associated with abdominal obesity, and combining these 48 SNPs into a weighted polygenic risk score, we can determine whether a genetic predisposition to abdominal obesity is associated with DKD.
Project duration: The duration of this project will be three years, from 2020 to 2023.
Public health impact: We expected to identify the causal association between abdominal obesity and the development of DKD. If further research validates our findings, two recommendations on the risk assessment and intervention of DKD might be considered by clinical practice: (1) Clinical screening of abdominal obesity by simple anthropometric measures to identify diabetic patients who might be more susceptible to diabetic nephropathy; (2) Interventions aiming to reduce abdominal adipose tissue may become an important adjunct to glycemic and blood pressure control for reducing the risk of DKD.
Diabetic kidney disease (DKD) is a devastating complication of type 2 diabetes(T2DM) and the leading cause of end-stage renal disease (ESRD), accounting for approximately 50% of cases in developed countries worldwide. Although optimizing glucose and blood pressure control were achieved in T2DM, the progressive renal failure in DKD cannot be completely prevented.
Approximately half of the patients with diabetes are overweight or obese. Abdominal obesity, representative of accumulation of visceral adipose tissue, has been shown to be closely correlated to the incidence and progression of DKD. Our previous study indicated that abdominal obesity is more closely associated with DKD than general obesity. However, whether this association is causal remains unclear.
Mendelian randomization has emerged as a novel and powerful approach to assess causality, free from the limitations of traditional observational studies and the operational constraints of randomized controlled trials. Based on the principle of random assortment of gene variants during meiosis, Mendelian randomization is considered analogous to a randomized controlled trial, where exposure groups are defined by genotype. In this study, using the approach of Mendelian randomization, we aimed to test whether abdominal obesity is causally related to DKD .
To allow unbiased estimation of the causal effect of the exposure on the outcome, a valid genetic instrumental variable fulfills three core assumptions:
(1)the variants must be strongly associated with the exposure
(2)the variants must not be associated with confounders (factors confound the relationship between exposure and outcome)
(3)the variants should be independent of the outcome given the exposure
Therefore, it involves the analysis of genes, environment and other factors related to exposure and outcome. Several steps were needed and we have extended several other sub goals as follows:
(1)Analyze the key genetic variants (including gain or loss of function variants) associated with abdominal obesity
(2)Analyze the environmental factors and its interaction with genes on abdominal obesity and related diabetes, DKD, cardiovascular disease and mortality
(3)Analyze the factors, including environmental factors and biomarkers like aldosterone and mineralocorticoid receptor activity, associated with DKD and progressed CKD (e.g., ESRD, cardiovascular disease and death), by means like machine learning
(4)Analyze the genetic variants associated with DKD (mainly eGFR) and progressed CKD(e.g., ESRD, cardiovascular disease and death), and its overlaps with variants of abdominal obesity
(5)Verify whether various GFR formulas for general population is applicable for diabetes