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• W2099682931 abstract "Early detection of Alzheimer's disease (AD) before or during prodromal stages is critically important for development of effective treatment or prevention. Recent efforts seeking novel measures for early detection identified a set of cerebrospinal fluid (CSF) biomarkers [1,2]. Data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) provides 159 CSF analytes using a Rules Based Medicine (RBM) panel. We investigated the functional role of single nucleotide polymorphisms (SNPs) within each protein-coding gene on CSF protein levels. Quality-controlled genotype data and CSF analytes from 292 non-Hispanic Caucasian participants were analyzed. After preprocessing steps, 869 SNPs within 79 protein-coding genes were assessed for associations with 76 analytes. Corresponding SNPs and analytes were analyzed using additive and dominant genetic model s in four statistical models (M) with combinations of APOE e 4 status (E4) and baseline diagnosis (DX) as covariates (M1-without E4 and DX). Sex, age, education, and handedness were included in the model when significant. SNPs with uncorrected P <1.0*10 -4, generated by paired SNP-protein analyses, were considered significant. Analyses using M1 identified 31 significant associations between 9 analytes and 31 SNPs, belonging to 9 genes, shown in Figure 1. For each association, a genetic model with smallest p -value was chosen as a proper model. Other statistical models didn't change the set of significant associations but had slightly different p -values. For each of these associations, the fraction of R2 (ΔR2), accounted for by each SNP in M1, was computed using all participants (3 to 40 percent), and separately for 83 HC, 140 patients with mild cognitive impairment, and 69 AD (Table 1). Heatmap of significant associations at P <1.0×10−4 (upper) in the result of model 1 (M1) and linkage disequlibrium among significant SNPs within each gene. The heatmap shows the significant associations, not representing their p-values. The genetic model with smallest p-value for each association is represented by color and SNPs in a blue rectangle were also significantly associated with the same plasma analyte in ADNI-1 cohort. Variation in 31 SNPs within protein-coding genes significantly influenced the level of corresponding CSF proteins. 16 of the SNPs were also identified in our previous study of plasma proteomics [3]. The role of these 31 SNPs differs by diagnostic group for some analytes, warranting further investigation. Potential synergy between CSF proteomic assays and those for plasma [3] also deserves further study with regard to AD pathophysiology and early detection. References: [1] Hu et al. Acta Neuropath (2010). [2] Craig-Schapiro et al. PLoS One (2011). [3] Kim et al. AAIC 2011(2011)." @default.
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• W2099682931 date "2012-07-01" @default.
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• W2099682931 title "IC-P-069: Pairwise gene-protein association analysis on CSF proteomics in the ADNI-1 cohort" @default.
• W2099682931 doi "https://doi.org/10.1016/j.jalz.2012.05.102" @default.
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