DataSheet1_Genetic insight into the putative causal proteins and druggable targets of osteoporosis: a large-scale proteome-wide mendelian randomization study.xlsx

Background: Osteoporosis is a major causative factor of the global burden of disease and disability, characterized by low bone mineral density (BMD) and high risks of fracture. We aimed to identify putative causal proteins and druggable targets of osteoporosis.Methods: This study utilized the largest GWAS summary statistics on plasma proteins and estimated heel BMD (eBMD) to identify causal proteins of osteoporosis by mendelian randomization (MR) analysis. Different GWAS datasets were used to validate the results. Multiple sensitivity analyses were conducted to evaluate the robustness of primary MR findings. We have also performed an enrichment analysis for the identified causal proteins and evaluated their druggability.Results: After Bonferroni correction, 67 proteins were identified to be causally associated with estimated BMD (eBMD) (p < 4 × 10−5). We further replicated 38 of the 67 proteins to be associated with total body BMD, lumbar spine BMD, femoral neck BMD as well as fractures, such as RSPO3, IDUA, SMOC2, and LRP4. The findings were supported by sensitivity analyses. Enrichment analysis identified multiple Gene Ontology items, including collagen-containing extracellular matrix (GO:0062023, p = 1.6 × 10−10), collagen binding (GO:0005518, p = 8.6 × 10−5), and extracellular matrix structural constituent (GO:0005201, p = 2.7 × 10−5).Conclusion: The study identified novel putative causal proteins for osteoporosis which may serve as potential early screening biomarkers and druggable targets. Furthermore, the role of plasma proteins involved in collagen binding and extracellular matrix in the development of osteoporosis was highlighted. Further studies are warranted to validate our findings and investigate the underlying mechanism.

背景：骨质疏松症是全球疾病负担和残疾的主要原因之一，其特征为骨矿物质密度（BMD）降低和高骨折风险。本研究旨在识别骨质疏松症的潜在致病蛋白和可药物靶点。方法：本研究利用了最大的血浆蛋白GWAS汇总统计数据和跟骨骨密度（eBMD）估计值，通过孟德尔随机化（MR）分析来识别骨质疏松症的因果蛋白。使用不同的GWAS数据集来验证结果。进行了多次敏感性分析，以评估主要MR发现的稳健性。我们还对识别到的因果蛋白进行了富集分析，并评估了它们的可药物性。结果：经过Bonferroni校正后，共识别出67种蛋白质与估计的骨密度（eBMD）存在因果关系（p < 4 × 10−5）。我们进一步验证了其中的38种蛋白质与全身骨密度、腰椎骨密度、股骨颈骨密度以及骨折相关，如RSPO3、IDUA、SMOC2和LRP4。这些发现得到了敏感性分析的支持。富集分析识别出多个基因本体条目，包括含胶原蛋白的细胞外基质（GO:0062023，p = 1.6 × 10−10）、胶原蛋白结合（GO:0005518，p = 8.6 × 10−5）和细胞外基质结构成分（GO:0005201，p = 2.7 × 10−5）。结论：本研究识别了新的潜在致病蛋白，这些蛋白可能作为潜在的早期筛查生物标志物和可药物靶点。此外，强调了参与胶原蛋白结合和细胞外基质的血浆蛋白在骨质疏松症发展中的作用。需要进一步的研究来验证我们的发现并探究其潜在机制。