清晨好,您是今天最早来到科研通的研友!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您科研之路漫漫前行!

The causal effects of lipid traits on kidney function in Africans: bidirectional and multivariable Mendelian-randomization study

孟德尔随机化 混淆 医学 肾功能 脂蛋白 生物 遗传学 胆固醇 内科学 内分泌学 基因 遗传变异 基因型
作者
Christopher Kintu,Opeyemi Soremekun,Abram Bunya Kamiza,Allan Kalungi,Richard Mayanja,Robert Kalyesubula,Bernard Bagaya S,Daudi Jjingo,June Fabian,Dipender Gill,Moffat Nyirenda,Dorothea Nitsch,Tinashe Chikowore,Segun Fatumo
出处
期刊:EBioMedicine [Elsevier BV]
卷期号:90: 104537-104537 被引量:20
标识
DOI:10.1016/j.ebiom.2023.104537
摘要

Summary

Background

Observational studies have investigated the effect of serum lipids on kidney function, but these findings are limited by confounding, reverse causation and have reported conflicting results. Mendelian randomization (MR) studies address this confounding problem. However, they have been conducted mostly in European ancestry individuals. We, therefore, set out to investigate the effect of lipid traits on the estimated glomerular filtration rate (eGFR) based on serum creatinine in individuals of African ancestry.

Methods

We used the two-sample and multivariable Mendelian randomization (MVMR) approaches; in which instrument variables (IV's) for the predictor (lipid traits) were derived from summary-level data of a meta-analyzed African lipid GWAS (MALG, n = 24,215) from the African Partnership for Chronic Disease Research (APCDR) (n = 13,612) & the Africa Wits-IN-DEPTH partnership for Genomics studies (AWI-Gen) dataset (n = 10,603). The outcome IV's were computed from the eGFR summary-level data of African-ancestry individuals within the Million Veteran Program (n = 57,336). A random-effects inverse variance method was used in our primary analysis, and pleiotropy was adjusted for using robust and penalized sensitivity testing. The lipid predictors for the MVMR were high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides (TG).

Findings

We found a significant causal association between genetically predicted low-density lipoprotein (LDL) cholesterol and eGFR in African ancestry individuals β = 1.1 (95% CI [0.411–1.788]; p = 0.002). Similarly, total cholesterol (TC) showed a significant causal effect on eGFR β = 1.619 (95% CI [0.412–2.826]; p = 0.009). However, the IVW estimate showed that genetically predicted HDL-C β = −0.164, (95% CI = [−1.329 to 1.00]; p = 0.782), and TG β = −0.934 (CI = [−2.815 to 0.947]; p = 0.33) were not significantly causally associated with the risk of eGFR. In the multivariable analysis inverse-variance weighted (MVIVW) method, there was evidence for a causal association between LDL and eGFR β = 1.228 (CI = [0.477–1.979]; p = 0.001). A significant causal effect of Triglycerides (TG) on eGFR in the MVIVW analysis β = −1.3 ([−2.533 to −0.067]; p = 0.039) was observed as well. All the causal estimates reported reflect a unit change in the outcome per a 1 SD increase in the exposure. HDL showed no evidence of a significant causal association with eGFR in the MVIVW method (β = −0.117 (95% CI [−1.252 to 0.018]; p = 0.840)). We found no evidence of a reverse causal impact of eGFR on serum lipids. All our sensitivity analyses indicated no strong evidence of pleiotropy or heterogeneity between our instrumental variables for both the forward and reverse MR analysis.

Interpretation

In this African ancestry population, genetically predicted higher LDL-C and TC are causally associated with higher eGFR levels, which may suggest that the relationship between LDL, TC and kidney function may be U-shaped. And as such, lowering LDL_C does not necessarily improve risk of kidney disease. This may also imply the reason why LDL_C is seen to be a poorer predictor of kidney function compared to HDL. In addition, this further supports that more work is warranted to confirm the potential association between lipid traits and risk of kidney disease in individuals of African Ancestry.

Funding

Wellcome (220740/Z/20/Z).

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
冰雪痕完成签到 ,获得积分10
11秒前
小小完成签到 ,获得积分10
28秒前
sheg完成签到,获得积分10
34秒前
沫沫完成签到 ,获得积分20
48秒前
科科通通完成签到,获得积分10
58秒前
1分钟前
秋迎夏完成签到,获得积分0
1分钟前
高海龙完成签到 ,获得积分10
1分钟前
炳灿完成签到 ,获得积分10
2分钟前
科研狗完成签到 ,获得积分10
2分钟前
雪白小丸子完成签到,获得积分10
2分钟前
紫婧完成签到,获得积分10
2分钟前
郭磊完成签到 ,获得积分10
2分钟前
qianci2009完成签到,获得积分0
2分钟前
minnie完成签到 ,获得积分10
2分钟前
Karl完成签到,获得积分10
3分钟前
负责秋烟完成签到 ,获得积分10
3分钟前
研友_LN25rL完成签到,获得积分10
3分钟前
worldlet完成签到 ,获得积分10
3分钟前
jiaaniu完成签到 ,获得积分10
3分钟前
Jcc完成签到 ,获得积分10
4分钟前
高山流水完成签到 ,获得积分10
4分钟前
予三千笔墨完成签到 ,获得积分10
4分钟前
奋斗的小笼包完成签到 ,获得积分10
4分钟前
rockyshi完成签到 ,获得积分10
4分钟前
姜勇完成签到,获得积分10
4分钟前
ChandlerZB完成签到,获得积分10
4分钟前
愤怒的鲨鱼完成签到 ,获得积分10
4分钟前
积极的白羊完成签到 ,获得积分10
4分钟前
Lauren完成签到 ,获得积分10
4分钟前
我很厉害的1q完成签到,获得积分10
5分钟前
小女子常戚戚完成签到,获得积分10
5分钟前
游泳池完成签到,获得积分10
5分钟前
qianzhihe2完成签到,获得积分10
5分钟前
无悔完成签到 ,获得积分0
5分钟前
cwanglh完成签到 ,获得积分10
5分钟前
5分钟前
哈哈哈完成签到 ,获得积分10
5分钟前
Charles发布了新的文献求助10
5分钟前
Cell完成签到 ,获得积分10
5分钟前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Photodetectors: From Ultraviolet to Infrared 500
On the Dragon Seas, a sailor's adventures in the far east 500
Yangtze Reminiscences. Some Notes And Recollections Of Service With The China Navigation Company Ltd., 1925-1939 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6353128
求助须知:如何正确求助?哪些是违规求助? 8167967
关于积分的说明 17191352
捐赠科研通 5409134
什么是DOI,文献DOI怎么找? 2863594
邀请新用户注册赠送积分活动 1840960
关于科研通互助平台的介绍 1689819