Department of Epidemiology, Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-sen University, Guangzhou, China.
School of Life Sciences, Westlake University, Hangzhou, China.
Aging Cell. 2024 Feb;23(2):e14035. doi: 10.1111/acel.14035. Epub 2023 Nov 16.
The role of circulatory proteomics in osteoporosis is unclear. Proteome-wide profiling holds the potential to offer mechanistic insights into osteoporosis. Serum proteome with 413 proteins was profiled by liquid chromatography-tandem mass spectrometry (LC-MS/MS) at baseline, and the 2nd, and 3rd follow-ups (7704 person-tests) in the prospective Chinese cohorts with 9.8 follow-up years: discovery cohort (n = 1785) and internal validation cohort (n = 1630). Bone mineral density (BMD) was measured using dual-energy X-ray absorptiometry (DXA) at follow-ups 1 through 3 at lumbar spine (LS) and femoral neck (FN). We used the Light Gradient Boosting Machine (LightGBM) to identify the osteoporosis (OP)-related proteomic features. The relationships between serum proteins and BMD in the two cohorts were estimated by linear mixed-effects model (LMM). Meta-analysis was then performed to explore the combined associations. We identified 53 proteins associated with osteoporosis using LightGBM, and a meta-analysis showed that 22 of these proteins illuminated a significant correlation with BMD (p < 0.05). The most common proteins among them were PHLD, SAMP, PEDF, HPTR, APOA1, SHBG, CO6, A2MG, CBPN, RAIN APOD, and THBG. The identified proteins were used to generate the biological age (BA) of bone. Each 1 SD-year increase in KDM-Proage was associated with higher risk of LS-OP (hazard ratio [HR], 1.25; 95% CI, 1.14-1.36, p = 4.96 × 10 ), and FN-OP (HR, 1.13; 95% CI, 1.02-1.23, p = 9.71 × 10 ). The findings uncovered that the apolipoproteins, zymoproteins, complements, and binding proteins presented new mechanistic insights into osteoporosis. Serum proteomics could be a crucial indicator for evaluating bone aging.
循环蛋白质组学在骨质疏松症中的作用尚不清楚。蛋白质组学的全谱分析有可能为骨质疏松症提供机制上的见解。通过液相色谱-串联质谱 (LC-MS/MS) 在基线、第 2 次和第 3 次随访（9.8 年的前瞻性中国队列中的 7704 人次测试）中对血清蛋白质组（413 种蛋白质）进行了分析：发现队列（n=1785）和内部验证队列（n=1630）。在第 1 次到第 3 次随访中使用双能 X 线吸收法 (DXA) 测量腰椎 (LS) 和股骨颈 (FN) 的骨密度 (BMD)。我们使用 Light Gradient Boosting Machine (LightGBM) 来识别与骨质疏松症相关的蛋白质组学特征。通过线性混合效应模型 (LMM) 估计两个队列中血清蛋白与 BMD 的关系。然后进行荟萃分析以探讨联合关联。我们使用 LightGBM 鉴定出 53 种与骨质疏松症相关的蛋白质，荟萃分析显示其中 22 种蛋白质与 BMD 有显著相关性（p<0.05）。其中最常见的蛋白质是 PHLD、SAMP、PEDF、HPTR、APOA1、SHBG、CO6、A2MG、CBPN、RAIN APOD 和 THBG。鉴定出的蛋白质用于生成骨骼的生物年龄 (BA)。KDM-Proage 每增加 1 个标准差年，LS-OP（风险比 [HR]，1.25；95%置信区间，1.14-1.36，p=4.96×10-4）和 FN-OP（HR，1.13；95%置信区间，1.02-1.23，p=9.71×10-3）的风险更高。研究结果揭示了载脂蛋白、酶蛋白、补体和结合蛋白为骨质疏松症提供了新的机制见解。血清蛋白质组学可能是评估骨骼老化的重要指标。
