Bayesian network analysis of BIN1 risk allele and other risk factors and biomarkers of Alzheimer’s disease

Abstract

AbstractBackgroundThe Bridging Integrator I (BIN1) is a significant genetic risk gene, second only to the established risk gene apolipoprotein E (APOE4), for late‐onset Alzheimer’s disease (LOAD, AD) (Carrasquillo, 2011). BIN1 rs744733 risk allele was shown to affect tau pathology and cognitive decline (Franzmeier, 2021).In this study, we compared BIN1 risk allele rs6733839 with APOE4 on interdependency among AD risk factors and biomarkers by applying Bayesian Network (BN) modeling (Scutari, 2017) to data from Lilly AD clinical trials.MethodData from A05C (n = 142, NCT01565382), A05E (n = 217, NCT02016560), and untreated arms of AZES (n = 206, NCT02245737), LLCF (n = 229, NCT02791191), and LZAX (n = 194, NCT01900665) trial participants were used for the analysis (table 1). We constructed graphs representing the dependencies among the variables, including demographics, genetic risk genes, brain amyloid and tau measured by 18F‐Florbetapir or 18F‐Flortaucipir positron emission tomography (PET) imaging quantified globally and regionally as a standardized uptake value ratio. Longitudinal tau changes from baseline were computed for a sub cohort (n = 234). Conditional Gaussian Bayesian Network (CGBN) was used to model discrete (gender, genotype) and continuous (age, PET quantifications) variables. Directed Acyclic Graphs (DAG) structure was learned using constraint‐based Incremental Association (iamb) algorithm and score‐based Hill‐Climbing (hc) algorithm with one‐sided type I error rate at 10%. The connection strength was estimated by bootstrap resampling and computing the probability of any variable influencing another variable. Model parameters were estimated using the maximum likelihood estimation method.ResultThe result shows that age influences baseline amyloid (Strength s = 1.0) and parietal tau (s = 0.83). APOE4 influences baseline amyloid (s = 0.75) and tau at four lopes with strength ranging from 0.84 to 0.31 in the order of frontal, parietal, occipital, and temporal lobes. BIN1 influences baseline tau at the parietal lobe (s = 0.42) and other lobes with strength below 0.3. We have not observed consistent dependency between variables and change in tau, likely due to the small sample size (n = 234).ConclusionOur study result is consistent with current knowledge of APOE4 influencing amyloid and tau. The finding that BIN1 influences tau supports the observation of BIN1 rs744373, in linkage disequilibrium with rs6733839, in ADNI and BioFINDER studies (Franzmeier, 2021).