Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD.
Diabetes Care. 2023 Apr 1;46(4):733-741. doi: 10.2337/dc22-1830.
The plasma proteome preceding diabetes can improve our understanding of diabetes pathogenesis.
In 8,923 Atherosclerosis Risk in Communities (ARIC) Study participants (aged 47-70 years, 57% women, 19% Black), we conducted discovery and internal validation for associations of 4,955 plasma proteins with incident diabetes. We externally validated results in the Singapore Multi-Ethnic Cohort (MEC) nested case-control (624 case subjects, 1,214 control subjects). We used Cox regression to discover and validate protein associations and risk-prediction models (elastic net regression with cardiometabolic risk factors and proteins) for incident diabetes. We conducted a pathway analysis and examined causality using genetic instruments.
There were 2,147 new diabetes cases over a median of 19 years. In the discovery sample (n = 6,010), 140 proteins were associated with incident diabetes after adjustment for 11 risk factors (P < 10-5). Internal validation (n = 2,913) showed 64 of the 140 proteins remained significant (P < 0.05/140). Of the 63 available proteins, 47 (75%) were validated in MEC. Novel associations with diabetes were found for 22 the 47 proteins. Prediction models (27 proteins selected by elastic net) developed in discovery had a C statistic of 0.731 in internal validation, with ΔC statistic of 0.011 (P = 0.04) beyond 13 risk factors, including fasting glucose and HbA1c. Inflammation and lipid metabolism pathways were overrepresented among the diabetes-associated proteins. Genetic instrument analyses suggested plasma SHBG, ATP1B2, and GSTA1 play causal roles in diabetes risk.
We identified 47 plasma proteins predictive of incident diabetes, established causal effects for 3 proteins, and identified diabetes-associated inflammation and lipid pathways with potential implications for diagnosis and therapy.
研究糖尿病前期的血浆蛋白质组可以帮助我们深入了解糖尿病的发病机制。
在 8923 名动脉粥样硬化风险社区（ARIC）研究参与者（年龄 47-70 岁，57%为女性，19%为黑人）中，我们发现并验证了 4955 种血浆蛋白与糖尿病发病的相关性。我们在新加坡多民族队列（MEC）巢式病例对照研究中（624 例病例，1214 例对照）进行了结果外部验证。我们使用 Cox 回归发现和验证与糖尿病发病相关的蛋白质，并构建风险预测模型（使用心血管代谢危险因素和蛋白质的弹性网络回归）。我们进行了途径分析并使用遗传工具检查因果关系。
中位随访时间为 19 年期间，共发生了 2147 例新发糖尿病。在发现样本（n=6010）中，经过 11 种危险因素校正后，有 140 种蛋白与糖尿病发病相关（P<10-5）。内部验证（n=2913）显示，140 种蛋白中有 64 种仍具有显著意义（P<0.05/140）。在 63 种可用蛋白中，47 种（75%）在 MEC 中得到验证。在这 47 种蛋白中，有 22 种与糖尿病发生有关。在发现阶段建立的预测模型（通过弹性网络选择的 27 种蛋白）在内部验证中的 C 统计量为 0.731，与包括空腹血糖和糖化血红蛋白在内的 13 种危险因素相比，增加了 0.011（P=0.04）。糖尿病相关蛋白中存在过度表达的炎症和脂质代谢途径。遗传工具分析表明，血浆 SHBG、ATP1B2 和 GSTA1 在糖尿病风险中起因果作用。
我们鉴定出 47 种预测糖尿病发病的血浆蛋白，确定了 3 种蛋白的因果作用，并发现了与糖尿病相关的炎症和脂质代谢途径，这可能对诊断和治疗具有重要意义。
