TY - JOUR
T1 - Brain microRNAs are associated with variation in cognitive trajectory in advanced age
AU - Wingo, Aliza P.
AU - Wang, Mengli
AU - Liu, Jiaqi
AU - Breen, Michael S.
AU - Yang, Hyun Sik
AU - Tang, Beisha
AU - Schneider, Julie A.
AU - Seyfried, Nicholas T.
AU - Lah, James J.
AU - Levey, Allan I.
AU - Bennett, David A.
AU - Jin, Peng
AU - De Jager, Philip L.
AU - Wingo, Thomas S.
N1 - Funding Information:
We would like to thank the participants of the ROS, MAP, Banner, and BLSA studies for their participation in these studies. A.P.W. was also supported by a grant from the US Veterans Administration (BX003853) and US Institute of Health U01 MH115484. T. S.W. was also supported by a grant from the US Veterans Administration (IK2 BX001820) and US Institute of Health P50 AG025688. N.T.S. was also supported by the following grants from US Institute of Health: R01 AG061800, R01 AG053960, R01A G057911, R01 AG053960. We thank Thanneer Perumal, PhD for performing quality control of the RNA-seq data and creating the estimated cell-type proportions from RNA-seq data, Benjamin Logsdon, PhD for contributing to the quality control and annotation of the RNA-sequencing data, and Wen Fan, MS for assistance with creating the VariancePartition plots. Support for this research was provided by the following grants from the US National Institutes of Health: R01 AG056533 (A.P.W. and T.S.W.), R01 AG036042 (D.A.B and P.L.D), R01 AG017917 (D.A.B.), RF1 AG015819 (D.A. B.), RC2 AG036547 (D.A.B.), P30 AG10161 (D.A.B.), U01 AG46152 (P.L.D.), U01 AG046161 (A.I.L.), P50 AG025688 (A.I.L.), P30 NS055077 (A.I.L.), and VA 1IK4 BX005219 (A.P.W). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - In advancing age, some individuals maintain a stable cognitive performance over time, while others experience a rapid decline. Such variation in cognitive trajectory is only partially explained by common neurodegenerative pathologies. Hence, we aimed to identify new molecular processes underlying variation in cognitive trajectory using brain microRNA profile followed by an integrative analysis with brain transcriptome and proteome. Individual cognitive trajectories were derived from longitudinally assessed cognitive-test scores of older-adult brain donors from four longitudinal cohorts. Postmortem brain microRNA profiles, transcriptomes, and proteomes were derived from the dorsolateral prefrontal cortex. The global microRNA association study of cognitive trajectory was performed in a discovery (n = 454) and replication cohort (n = 134), followed by a meta-analysis that identified 6 microRNAs. Among these, miR-132-3p and miR-29a-3p were most significantly associated with cognitive trajectory. They explain 18.2% and 2.0% of the variance of cognitive trajectory, respectively, and act independently of the eight measured neurodegenerative pathologies. Furthermore, integrative transcriptomic and proteomic analyses revealed that miR-132-3p was significantly associated with 24 of the 47 modules of co-expressed genes of the transcriptome, miR-29a-3p with 3 modules, and identified 84 and 214 downstream targets of miR-132-3p and miR-29a-3p, respectively, in cognitive trajectory. This is the first global microRNA study of cognitive trajectory to our knowledge. We identified miR-29a-3p and miR-132-3p as novel and robust contributors to cognitive trajectory independently of the eight known cerebral pathologies. Our findings lay a foundation for future studies investigating mechanisms and developing interventions to enhance cognitive stability in advanced age.
AB - In advancing age, some individuals maintain a stable cognitive performance over time, while others experience a rapid decline. Such variation in cognitive trajectory is only partially explained by common neurodegenerative pathologies. Hence, we aimed to identify new molecular processes underlying variation in cognitive trajectory using brain microRNA profile followed by an integrative analysis with brain transcriptome and proteome. Individual cognitive trajectories were derived from longitudinally assessed cognitive-test scores of older-adult brain donors from four longitudinal cohorts. Postmortem brain microRNA profiles, transcriptomes, and proteomes were derived from the dorsolateral prefrontal cortex. The global microRNA association study of cognitive trajectory was performed in a discovery (n = 454) and replication cohort (n = 134), followed by a meta-analysis that identified 6 microRNAs. Among these, miR-132-3p and miR-29a-3p were most significantly associated with cognitive trajectory. They explain 18.2% and 2.0% of the variance of cognitive trajectory, respectively, and act independently of the eight measured neurodegenerative pathologies. Furthermore, integrative transcriptomic and proteomic analyses revealed that miR-132-3p was significantly associated with 24 of the 47 modules of co-expressed genes of the transcriptome, miR-29a-3p with 3 modules, and identified 84 and 214 downstream targets of miR-132-3p and miR-29a-3p, respectively, in cognitive trajectory. This is the first global microRNA study of cognitive trajectory to our knowledge. We identified miR-29a-3p and miR-132-3p as novel and robust contributors to cognitive trajectory independently of the eight known cerebral pathologies. Our findings lay a foundation for future studies investigating mechanisms and developing interventions to enhance cognitive stability in advanced age.
UR - http://www.scopus.com/inward/record.url?scp=85123972632&partnerID=8YFLogxK
U2 - 10.1038/s41398-022-01806-3
DO - 10.1038/s41398-022-01806-3
M3 - Article
C2 - 35105862
AN - SCOPUS:85123972632
VL - 12
JO - Translational Psychiatry
JF - Translational Psychiatry
SN - 2158-3188
IS - 1
M1 - 47
ER -