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P4‐032: Novel Combination Treatment for Alzheimer’s Disease Promotes Hippocampal Neurogenesis in Tgcrnd8 Mice
Author(s) -
Morrone Christopher D.,
Thomason Lynsie A.M.,
Brown Mary E.,
Aubert Isabelle,
McLaurin JoAnne
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.2016.06.2121
Subject(s) - neurogenesis , bromodeoxyuridine , genetically modified mouse , hippocampal formation , dentate gyrus , inositol , neuroscience , pharmacology , alzheimer's disease , neurotrophic factors , chemistry , biology , transgene , medicine , biochemistry , receptor , disease , immunohistochemistry , gene
(ROSMAP), temporal cortex and cerebellum (Mayo Clinic), and frontal pole (FP), superior temporal gyrus (STG), and parahippocampal gyrus (PHG) (Mount Sinai). In total, 1596 (592, 448, 556) samples derived from 1103 (592, 233, 314) patients were analyzed (ROSMAP, Mount Sinai, and Mayo Clinic respectively). We employ multiple network algorithms to infer gene coexpression and regulatory networks among samples within each study by brain region, and these were combined to identify consensus gene modules. Results:A core set of biologically coherent gene modules were identified in a consistent manner across methods, brain region, and study cohort. These included gene modules that were enriched for mitochondrial function, synaptic transmission, immune response, and myelination. Additionally, we replicate previously published findings from AD transcriptome coexpression analyses, including the importance of microglia and innate immunity pathways. Conclusions: Transcriptional network inference holds great promise for elucidating molecular pathways that cause or modulate Alzheimer’s disease pathophysiology. The results demonstrate the ability to identify transcriptional networks that are consistent across studies and may represent potential AD pathophysiologic pathways. These computational models of Alzheimer’s disease have the potential to provide new hypotheses concerning drivers of AD development and progression for target discovery.