Lu Jiawen, Liu Yang, Wang Zhenqian, Zhou Kaixin, Pan Ying, Zhong Shao, Jiang Guozhi
School of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China.
School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, Guangdong, China.
JACC Asia. 2024 Sep 10;4(11):825-838. doi: 10.1016/j.jacasi.2024.07.011. eCollection 2024 Nov.
Dyslipidemia is a recognized risk factor for type 2 diabetes (T2D), yet the genetic basis and causal nature remain unclear, particularly in Chinese populations.
The authors investigated the causal effects of genetically predicted lipid levels on T2D risk and explored the potential effects of lipid-modifying drugs.
Leveraging data from the Kunshan Community cohort in China, we analyzed the associations between low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, and triglycerides (TGs) with T2D risk using genetic risk scores, 1-sample univariable, multivariable, and nonlinear Mendelian randomization (MR) analyses. Two-sample MR using summary-level data from Global Lipid Genetics Consortium and Biobank Japan was used for validation. Drug-target MR was used to examine the impact of lipid-modifying drug targets on T2D.
Lower genetic risk scores of LDL-C (OR per SD: 0.97 [95% CI: 0.95-0.99]; = 0.010) and TGs (0.96 [95%CI: 0.94-0.98]; = 0.002) were associated with increased T2D risk. Univariable MR revealed that genetically predicted lower LDL-C (0.78 [95% CI: 0.65-0.93]; = 0.006) and TG levels (0.76 [95% CI: 0.66-0.89]; < 0.001) were linked to a higher T2D risk, validated by 2-sample MR. Multivariable MR demonstrated a direct inverse association between LDL-C (0.80 [95% CI: 0.66-0.97]; = 0.020) and TG (0.80 [95% CI: 0.66-0.97]; = 0.022) with T2D. No evidence was found for nonlinearity. Among lipid-modifying drugs, genetic mimicry of apolipoprotein C3 (APOC3) inhibition increased T2D risk (OR per 1 mmol/L reduction in TG: 1.38 [95% CI: 1.10-1.75]; = 0.007).
Our findings suggested potential adverse effects of lower LDL-C, TG levels, as well as long-term use of APOC3 inhibitors on T2D risk in Chinese populations. These findings highlight the need for cautious lipid management strategies in T2D prevention.
血脂异常是2型糖尿病(T2D)公认的危险因素,但其遗传基础和因果性质仍不清楚,尤其是在中国人群中。
作者研究了基因预测的血脂水平对T2D风险的因果影响,并探讨了调脂药物的潜在作用。
利用中国昆山社区队列的数据,我们使用遗传风险评分、单样本单变量、多变量和非线性孟德尔随机化(MR)分析,分析了低密度脂蛋白胆固醇(LDL-C)、高密度脂蛋白胆固醇和甘油三酯(TGs)与T2D风险之间的关联。使用来自全球脂质遗传学联盟和日本生物银行的汇总水平数据进行两样本MR验证。药物靶点MR用于研究调脂药物靶点对T2D的影响。
LDL-C(每标准差的OR:0.97 [95%CI:0.95-0.99];P = 0.010)和TGs(0.96 [95%CI:0.94-0.98];P = 0.002)的较低遗传风险评分与T2D风险增加相关。单变量MR显示,基因预测的较低LDL-C(0.78 [95%CI:0.65-0.93];P = 0.006)和TG水平(0.76 [95%CI:0.66-0.89];P < 0.001)与较高的T2D风险相关,两样本MR验证了这一点。多变量MR表明LDL-C(0.80 [95%CI:0.66-0.97];P = 0.020)和TG(0.80 [95%CI:0.66-0.97];P = 0.022)与T2D之间存在直接的负相关。未发现非线性证据。在调脂药物中,载脂蛋白C3(APOC3)抑制的基因模拟增加了T2D风险(每降低1 mmol/L TG的OR:1.38 [95%CI:1.10-1.75];P = 0.007)。
我们的研究结果提示,较低的LDL-C、TG水平以及长期使用APOC3抑制剂对中国人群的T2D风险可能存在不良影响。这些发现凸显了在T2D预防中谨慎制定血脂管理策略的必要性。