An Integrated Bioinformatics Approach for Identifying Genetic Markers that Predict Cerebrospinal Fluid Biomarker p-tau181/Aβ1-42 Ratio in ApoE4-Negative Mild Cognitive Impairment Patients
Abstract
Alzheimer's disease (AD) is the most common form of dementia, with no disease-modifying treatment yet available. Early detection of patients at risk of developing AD is of central importance. Blood-based genetic signatures can serve as early detection and as population-based screening tools. In this study, we aimed to identify genetic markers and gene signatures associated with cerebrospinal fluid (CSF) biomarkers levels of t-tau, p-tau181, and with the two ratios t-tau/Aβ1-42 and p-tau181/Aβ1-42 in the context of progression from mild cognitive impairment (MCI) to AD, and to identify a panel of genetic markers that can predict CSF biomarker p-tau181/Aβ1-42 ratio with consideration of APOE ε4 stratification. We analyzed genome-wide the Alzheimer's Disease Neuroimaging Initiative dataset with up to 48 months follow-up. In the first part of the analysis, the main effect of single nucleotide polymorphisms (SNPs) under an additive genetic model was assessed for each of the four CSF biomarkers. In the second part of the analysis, we performed an integrated analysis of genome-wide association study results with pathway enrichment analysis, predictive modeling and network analysis in the subgroup of ApoE4-negative subjects. We identified a panel of five SNPs, rs6766238, rs1143960, rs1249963, rs11975968, and rs4836493, that are predictive for p-tau181/Aβ1-42 ratio (high/low) with a sensitivity of 66% and a specificity of 70% (AUC 0.74). These results suggest that a panel of SNPs is a potential prognostic biomarker in ApoE4-negative MCI patients.
