Deciphering proteins in Alzheimer’s disease: A new Mendelian randomization method integrated with AlphaFold3 for 3D structure prediction

• Published in: Cell genomics Vol. 4; no. 12; p. 100700
• Main Authors: Yao, Minhao, Miller, Gary W., Vardarajan, Badri N., Baccarelli, Andrea A., Guo, Zijian, Liu, Zhonghua
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 11.12.2024; Elsevier
• Subjects: 3D structure; AlphaFold3; Alzheimer Disease - genetics; Alzheimer's disease; Biomarkers; causal inference; Genetics; Genome-Wide Association Study; Humans; instrumental variable; Membrane Glycoproteins - genetics; Mendelian randomization; Mendelian Randomization Analysis; missense variants; pQTL; proteomics; Proteomics - methods; Quantitative Trait Loci; Receptor, EphA1 - genetics; Receptor, EphA1 - metabolism; Receptors, Immunologic - genetics; AlphaFold3; instrumental variable; proteomics; genome-wide association study; 3D structure; Mendelian randomization; causal inference; Alzheimer's disease; pQTL; missense variants
• ISSN: 2666-979X; 2666-979X
• DOI: 10.1016/j.xgen.2024.100700

Hidden confounding biases hinder identifying causal protein biomarkers for Alzheimer’s disease in non-randomized studies. While Mendelian randomization (MR) can mitigate these biases using protein quantitative trait loci (pQTLs) as instrumental variables, some pQTLs violate core assumptions, leading to biased conclusions. To address this, we propose MR-SPI, a novel MR method that selects valid pQTL instruments using Leo Tolstoy’s Anna Karenina principle and performs robust post-selection inference. Integrating MR-SPI with AlphaFold3, we developed a computational pipeline to identify causal protein biomarkers and predict 3D structural changes. Applied to genome-wide proteomics data from 54,306 UK Biobank participants and 455,258 subjects (71,880 cases and 383,378 controls) for a genome-wide association study of Alzheimer’s disease, we identified seven proteins (TREM2, PILRB, PILRA, EPHA1, CD33, RET, and CD55) with structural alterations due to missense mutations. These findings offer insights into the etiology and potential drug targets for Alzheimer’s disease. [Display omitted] •MR-SPI is a new instrumental variable method for causal inference in proteomics data•Seven plasma proteins have been identified as linked to Alzheimer’s disease•AlphaFold3 predicts protein 3D structural changes caused by missense mutations•Genetic-variant-induced structural changes may help identify future drug targets Yao et al. develop a computational pipeline integrating a robust Mendelian randomization method with AlphaFold3 to select valid pQTL instruments, identify causal protein biomarkers, and predict 3D structural alterations. Seven plasma proteins have been identified as linked to Alzheimer’s disease and may aid future drug development.