Detecting potential causal relationship between multiple risk factors and Alzheimer’s disease using multivariable Mendelian randomization
Year: 2020
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Alzheimer's disease (AD) is a progressive brain disorder characterized by cognitive skills deterioration that affects many elderly individuals. The identified genetic loci for AD failed to explain the large variability in AD and very few causal factors have been identified so far. RESULTS: =3.564E-05) were associated with increasing AD risk. Genetically predicted FG was suggestively associated with increased AD risk. Furthermore, MR-BMA analysis also confirmed FG and years of schooling as two of the top five causal risk factors for AD. CONCLUSIONS: Our findings might provide us novel insights for treatment and intervention into the causal risk factors for AD or AD-related complex diseases. METHODS: By using extension methods of Mendelian randomization (MR)--multivariable MR (mvMR) and MR based on Bayesian model averaging (MR-BMA), we intend to estimate the potential causal relationship between nine risk factors and AD outcome and try to prioritize the most causal risk factors for AD.
Source: Aging
Authors: Qiang Zhang, Fei Xu, Lianke Wang, Wei-Dong Zhang, Chang-Qing Sun, Hong-Wen Deng
Institutions: Zhengzhou University, Tulane University
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: green
Awards: Integration of brain imaging with genomic and epigenomic data, Epigenomewide DNA Methylation Study for Osteoporosis Risk, Decoding Methylation Mediated Epigenomic Contributions to Male Osteoporosis, Tulane COBRE for Clinical and Translational Research in Cardiometabolic Diseases, Trans-omics Integration of Multi-omics Studies for Osteoporosis
OpenAlex ID: W3103915724