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P2‐084: Effect of Chronic Lithium Treatment on Telomeric Length in Triple‐Transgenic Alzheimer's Disease MICE
Author(s) -
de Mattos Cardillo Giancarlo,
de Jesus de Paula Vanessa,
Ikenaga Eliza Hiromi,
Costa Luciana Rodrigues,
Catanozi Sergio,
Schaeffer Evelin Lisete,
Gattaz Wagner Farid,
Forlenza Orestes Vicente,
Kerr Daniel S.
Publication year - 2016
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.2016.06.1289
Subject(s) - hippocampus , telomere , lithium (medication) , neuroinflammation , neuroprotection , transgene , olfactory epithelium , genetically modified mouse , medicine , endocrinology , biology , neuroscience , disease , olfactory system , genetics , dna , gene
genetic variants in linkage disequilibrium (LD) and may not be actually functional. Moreover, all 21 of the significant SNPs identified in phase 1 of the International Genomics of Alzheimer’s Project (IGAP) meta-analysis (Lambert et al. 2013) are in nonprotein-coding regions, implicating gene regulatory mechanisms as underlying the association signal. This suggests a need for functional annotation of expanded sets of SNPs spanning the LD regions tagged by the IGAP SNPs in order to identify the truly causal variants, their regulatory mechanisms, and their target genes.Methods:We developed a reproducible bioinformatics pipeline for the proposed analysis. First, we built an expanded set of variants by finding SNPs near the tagging SNP that meet a ‘locus-wide’ significance threshold and identifying all SNPs in LD with any locus-wide significant SNP or the tag SNP. Next, we overlapped the expanded SNP set with enhancers from FANTOM5 and eQTLs from GTEx and identified their respective target genes, characterized the distribution of SNPs across genomic elements like exons and introns, and incorporated other functional information including epigenomics data from NIH Roadmap Epigenomics and transcription factor binding sites. Results: The expanded SNP set from the 21 top IGAP phase 1 hits included 2,126 unique SNPs. We prioritized SNPs that both overlapped enhancers and were eQTLs and identified several putatively functional SNPs: 4 near CASS4, 28 near CELF1, 2 near EPHA1, 4 near SLC24A4, 128 near HLA-DRB5/HLA-DRB1, and 4 near MS4A6A. Each region except SLC24A4, which harbored fibroblast eQTLs and monocyte enhancers, contained at least one SNP overlapping both monocyte enhancers and whole blood eQTLs, supporting the hypothesis of innate immune response involvement in LOAD etiology. Conclusions:Computational analysis of functional genomic data across hundreds of tissues and cell types identified a small number of putatively causal SNPs for LOAD with strong functional evidence. This set of variants is being further refined and characterized, and we will report more functional results during the AAIC 2016 meeting.