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P4‐139: Rare finding in early‐onset dementia: Description of a patient with a novel PSEN2 mutation harbouring pathogenic huntingtin allele
Author(s) -
Kovacs Tibor,
Remenyi Viktoria,
Molnar Maria Judit,
Tegze Narcisz,
MiltenbergerMiltenyi Gabriel
Publication year - 2012
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2012.05.1842
Subject(s) - psen1 , presenilin , genetics , dementia , missense mutation , penetrance , mutation , family history , frontotemporal dementia , biology , allele , medicine , alzheimer's disease , gene , disease , pathology , phenotype
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. Methods: 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 a dditive 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<1.010 -4, generated by paired SNP-protein analyses, were considered significant. Results: 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 R 2 (DR 2), 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). Conclusions: 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(201 1).