4.5 Article

Integrated multi-omics analysis of brain aging in female nonhuman primates reveals altered signaling pathways relevant to age-related disorders

Journal

NEUROBIOLOGY OF AGING
Volume 132, Issue -, Pages 109-119

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.neurobiolaging.2023.08.009

Keywords

Integrated omics; Nonhuman primate; Brain prefrontal cortex; Normal aging

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This study used an integrated omics approach to investigate the changes in the prefrontal cortex (PFC) of healthy female baboons during aging. The results revealed known and novel pathways associated with PFC aging, with Gamma-aminobutyric acid (GABA) tissue content potentially serving as a biomarker for assessing PFC changes with age. These pathway changes may represent early steps in the decline of PFC functions and could provide biomarkers for assessing cognitive status in humans.
The prefrontal cortex (PFC) has been implicated as a key brain region responsible for age-related cognitive decline. Little is known about aging-related molecular changes in PFC that may mediate these effects. To date, no studies have used untargeted discovery methods with integrated analyses to determine PFC mo-lecular changes in healthy female primates. We quantified PFC changes associated with healthy aging in female baboons by integrating multiple omics data types (transcriptomics, proteomics, metabolomics) from samples across the adult age span. Our integrated omics approach using unbiased weighted gene co -ex-pression network analysis to integrate data and treat age as a continuous variable, revealed highly inter-connected known and novel pathways associated with PFC aging. We found Gamma-aminobutyric acid (GABA) tissue content associated with these signaling pathways, providing 1 potential biomarker to assess PFC changes with age. These highly coordinated pathway changes during aging may represent early steps for aging-related decline in PFC functions, such as learning and memory, and provide potential biomarkers to assess cognitive status in humans.(c) 2023 Elsevier Inc. All rights reserved.

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