Multivariate proteome-wide association study to identify causal proteins for Alzheimer’s disease

Music City Center 

Alzheimer's disease (AD) is a complex and progressive neurodegenerative disorder that accounts for the majority of individuals with dementia. Here we aim to identify causal plasma proteins for AD, shedding light on the etiology of AD. We utilized the latest large-scale plasma proteomic data from UK Biobank Pharma Proteomics Project and AD GWAS summary data from the International Genomics of Alzheimer's Project. Via a univariate instrumental variable (IV) regression method, we identified causal proteins through cis-pQTLs and through (both cis- and trans-) pQTLs. To further reduce potential false positives due to high linkage disequilibrium of some pQTLs and high correlations among some proteins, we developed a multivariate IV regression method, called 2-Stage Constrained Maximum Likelihood (MV-2ScML), to distinguish direct and confounding effects of proteins; key features of the method include its robustness to invalid IVs and applicability to GWAS summary data. Our work highlights some differences between using cis-pQTL and trans-pQTL, and critical values of multivariate analysis to detect causal proteins with direct effects, providing insights into plasma protein pathways to AD.

2ScML

2SLS

constrained maximum likelihood

instrumental variable (IV)

pleiotropy 

Section on Statistics in Genomics and Genetics