Sun Yan V, Liu Chang, Hui Qin, Zhou Jin J, Gaziano J Michael, Wilson Peter Wf, Joseph Jacob, Phillips Lawrence S
medRxiv. 2023 Sep 25:2023.09.22.23295915. doi: 10.1101/2023.09.22.23295915.
Type 2 diabetes (T2D) is a major risk factor for heart failure (HF) across demographic groups. On the other hand, metabolic impairment, including elevated T2D incidence is a hallmark of HF pathophysiology. We investigated the bidirectional relationship between T2D and HF, and identified genetic associations with diabetes-related HF after correction for potential collider bias.
We performed a genome-wide association study (GWAS) of HF to identify genetic instrumental variables (GIVs) for HF, and to enable bidirectional Mendelian Randomization (MR) analysis between T2D and HF. Since genetics and HF can independently influence T2D, collider bias may occur when T2D (i.e., collider) is controlled for by design or analysis. Thus, we conducted GWAS of diabetes-related HF with correction for collider bias.
We first identified 61 genomic loci, including 24 novel loci, significantly associated with all-cause HF in 114,275 HF cases and over 1.5 million controls of European ancestry. Combined with the summary statistics of a T2D GWAS, we obtained 59 and 82 GIVs for HF and T2D, respectively. Using a two-sample bidirectional MR approach, we estimated that T2D increased HF risk (OR 1.07, 95% CI 1.04-1.10), while HF also increased T2D risk (OR 1.60, 95% CI 1.36-1.88). Then we performed a GWAS of diabetes-related HF corrected for collider bias due to prevalent HF affecting incidence of T2D. After removing the spurious association of locus due to collider bias, we identified two genome-wide significant loci close to (chromosome 4) and (chromosome 9) associated with diabetes-related HF in the Million Veteran Program, and replicated the associations in the UK Biobank study.
We identified novel HF-associated loci to enable bidirectional MR study of T2D and HF. Our MR findings support T2D as a HF risk factor and provide strong evidence that HF increases T2D risk. As a result, collider bias leads to spurious genetic associations of diabetes-related HF, which can be effectively corrected to identify true positive loci. Evaluation of collider bias should be a critical component when conducting GWAS of complex disease phenotypes such as diabetes-related cardiovascular complications.
2型糖尿病（T2D）是各人群中心力衰竭（HF）的主要危险因素。另一方面，包括T2D发病率升高在内的代谢障碍是HF病理生理学的一个标志。我们研究了T2D与HF之间的双向关系，并在校正潜在的碰撞偏倚后确定了与糖尿病相关HF的基因关联。
我们进行了一项HF的全基因组关联研究（GWAS），以识别HF的基因工具变量（GIV），并实现T2D与HF之间的双向孟德尔随机化（MR）分析。由于遗传学和HF可独立影响T2D，因此当在设计或分析中控制T2D（即碰撞变量）时，可能会出现碰撞偏倚。因此，我们对糖尿病相关HF进行了GWAS，并校正了碰撞偏倚。
我们首先在114,275例HF病例和超过150万欧洲血统对照中，鉴定出61个基因组位点，包括24个新位点，与全因HF显著相关。结合T2D GWAS的汇总统计数据，我们分别获得了59个和82个HF和T2D的GIV。使用双样本双向MR方法，我们估计T2D增加HF风险（OR 1.07，95%CI 1.04 - 1.10），而HF也增加T2D风险（OR 1.60，95%CI 1.36 - 1.88）。然后，我们对糖尿病相关HF进行了GWAS，校正了由于普遍存在的HF影响T2D发病率而导致的碰撞偏倚。在去除由于碰撞偏倚导致的位点的虚假关联后，我们在百万退伍军人计划中鉴定出两个全基因组显著位点，靠近（4号染色体）和（9号染色体），与糖尿病相关HF相关，并在英国生物银行研究中重复了这些关联。
我们鉴定出了与HF相关的新位点，以实现T2D与HF的双向MR研究。我们的MR研究结果支持T2D作为HF的危险因素，并提供了强有力的证据表明HF增加T2D风险。结果，碰撞偏倚导致了糖尿病相关HF的虚假基因关联，可有效校正以识别真正的阳性位点。在进行糖尿病相关心血管并发症等复杂疾病表型的GWAS时，评估碰撞偏倚应是一个关键组成部分。
