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Transcriptional signatures of brain aging and Alzheimer's disease: What are our rodent models telling us?

ABSTRACT: Aging is the biggest risk factor for idiopathic Alzheimer's disease (AD). Recently, the National Institutes of Health released AD research recommendations that include: appreciating normal brain aging, expanding data-driven research, using open-access resources, and evaluating experimental reproducibility. Transcriptome data sets for aging and AD in humans and animal models are available in NIH-curated, publically accessible databases. However, little work has been done to test for concordance among those molecular signatures. Here, we test the hypothesis that brain transcriptional profiles from animal models recapitulate those observed in the human condition. Raw transcriptional profile data from twenty-nine studies were analyzed to produce p-values and fold changes for young vs. aged or control vs. AD conditions. Concordance across profiles was assessed at three levels: (1) # of significant genes observed vs. # expected by chance; (2) proportion of significant genes showing directional agreement; (3) correlation among studies for magnitude of effect among significant genes. The highest concordance was found within subjects across brain regions. Normal brain aging was concordant across studies, brain regions, and species, despite profound differences in chronological aging among humans, rats and mice. Human studies of idiopathic AD were concordant across brain structures and studies, but were not concordant with the transcriptional profiles of transgenic AD mouse models. Further, the five transgenic AD mouse models that were assessed were not concordant with one another. These results suggest that normal brain aging is similar in humans and research animals, and that different transgenic AD model mice may reflect selected aspects of AD pathology.

SUBMITTER: Hargis KE

PROVIDER: S-EPMC5533609 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature

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Transcriptional signatures of brain aging and Alzheimer's disease: What are our rodent models telling us?

Hargis Kendra E KE Blalock Eric M EM

Behavioural brain research 20160504 Pt B

Aging is the biggest risk factor for idiopathic Alzheimer's disease (AD). Recently, the National Institutes of Health released AD research recommendations that include: appreciating normal brain aging, expanding data-driven research, using open-access resources, and evaluating experimental reproducibility. Transcriptome data sets for aging and AD in humans and animal models are available in NIH-curated, publically accessible databases. However, little work has been done to test for concordance a ...[more]

PMID: 27155503

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Project description:Telomere length (TL) attrition, epigenetic age acceleration, and mitochondrial DNA copy number (mtDNAcn) decline are established hallmarks of aging. Each has been individually associated with Alzheimer's dementia, cognitive function, and pathologic Alzheimer's disease (AD). Epigenetic age and mtDNAcn have been studied in brain tissue directly but prior work on TL in brain is limited to small sample sizes and most studies have examined leukocyte TL. Importantly, TL, epigenetic age clocks, and mtDNAcn have not been studied jointly in brain tissue from an AD cohort. We examined dorsolateral prefrontal cortex (DLPFC) tissue from N = 367 participants of the Religious Orders Study (ROS) or the Rush Memory and Aging Project (MAP). TL and mtDNAcn were estimated from whole genome sequencing (WGS) data and cortical clock age was computed on 347 CpG sites. We examined dementia, MCI, and level of and change in cognition, pathologic AD, and three quantitative AD traits, as well as measures of other neurodegenerative diseases and cerebrovascular diseases (CVD). We previously showed that mtDNAcn from DLPFC brain tissue was associated with clinical and pathologic features of AD. Here, we show that those associations are independent of TL. We found TL to be associated with β-amyloid levels (beta = - 0.15, p = 0.023), hippocampal sclerosis (OR = 0.56, p = 0.0015) and cerebral atherosclerosis (OR = 1.44, p = 0.0007). We found strong associations between mtDNAcn and clinical measures of AD. The strongest associations with pathologic measures of AD were with cortical clock and there were associations of mtDNAcn with global AD pathology and tau tangles. Of the other pathologic traits, mtDNAcn was associated with hippocampal sclerosis, macroscopic infarctions and CAA and cortical clock was associated with Lewy bodies. Multi-modal age acceleration, accelerated aging on both mtDNAcn and cortical clock, had greater effect size than a single measure alone. These findings highlight for the first time that age acceleration determined on multiple genomic measures, mtDNAcn and cortical clock may have a larger effect on AD/AD related disorders (ADRD) pathogenesis than single measures.

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Transcriptional signatures of brain aging and Alzheimer's disease: What are our rodent models telling us?

Publications

Transcriptional signatures of brain aging and Alzheimer's disease: What are our rodent models telling us?

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