Format

Send to

Choose Destination
PLoS Med. 2017 Apr 25;14(4):e1002287. doi: 10.1371/journal.pmed.1002287. eCollection 2017 Apr.

Identification of genes associated with dissociation of cognitive performance and neuropathological burden: Multistep analysis of genetic, epigenetic, and transcriptional data.

Author information

1
Program in Translational NeuroPsychiatric Genomics, Institute for the Neurosciences, Departments of Neurology and Psychiatry, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
2
Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, United States of America.
3
Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Boston, Massachusetts, United States of America.
4
Harvard Medical School, Boston, Massachusetts, United States of America.
5
Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, United States of America.
6
Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, United States of America.
7
Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America.
8
Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Chicago, Illinois, United States of America.
9
Department of Psychiatry, University of British Columbia, Vancouver, British Columbia, Canada.
10
Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, Illinois, United States of America.
11
Center for Translational & Systems Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, New York, United States of America.

Abstract

INTRODUCTION:

The molecular underpinnings of the dissociation of cognitive performance and neuropathological burden are poorly understood, and there are currently no known genetic or epigenetic determinants of the dissociation.

METHODS AND FINDINGS:

"Residual cognition" was quantified by regressing out the effects of cerebral pathologies and demographic characteristics on global cognitive performance proximate to death. To identify genes influencing residual cognition, we leveraged neuropathological, genetic, epigenetic, and transcriptional data available for deceased participants of the Religious Orders Study (n = 492) and the Rush Memory and Aging Project (n = 487). Given that our sample size was underpowered to detect genome-wide significance, we applied a multistep approach to identify genes influencing residual cognition, based on our prior observation that independent genetic and epigenetic risk factors can converge on the same locus. In the first step (n = 979), we performed a genome-wide association study with a predefined suggestive p < 10-5, and nine independent loci met this threshold in eight distinct chromosomal regions. Three of the six genes within 100 kb of the lead SNP are expressed in the dorsolateral prefrontal cortex (DLPFC): UNC5C, ENC1, and TMEM106B. In the second step, in the subset of participants with DLPFC DNA methylation data (n = 648), we found that residual cognition was related to differential DNA methylation of UNC5C and ENC1 (false discovery rate < 0.05). In the third step, in the subset of participants with DLPFC RNA sequencing data (n = 469), brain transcription levels of UNC5C and ENC1 were evaluated for their association with residual cognition: RNA levels of both UNC5C (estimated effect = -0.40, 95% CI -0.69 to -0.10, p = 0.0089) and ENC1 (estimated effect = 0.0064, 95% CI 0.0033 to 0.0096, p = 5.7 × 10-5) were associated with residual cognition. In secondary analyses, we explored the mechanism of these associations and found that ENC1 may be related to the previously documented effect of depression on cognitive decline, while UNC5C may alter the composition of presynaptic terminals. Of note, the TMEM106B allele identified in the first step as being associated with better residual cognition is in strong linkage disequilibrium with rs1990622A (r2 = 0.66), a previously identified protective allele for TDP-43 proteinopathy. Limitations include the small sample size for the genetic analysis, which was underpowered to detect genome-wide significance, the evaluation being limited to a single cortical region for epigenetic and transcriptomic data, and the use of categorical measures for certain non-amyloid-plaque, non-neurofibrillary-tangle neuropathologies.

CONCLUSIONS:

Through a multistep analysis of cognitive, neuropathological, genomic, epigenomic, and transcriptomic data, we identified ENC1 and UNC5C as genes with convergent genetic, epigenetic, and transcriptomic evidence supporting a potential role in the dissociation of cognition and neuropathology in an aging population, and we expanded our understanding of the TMEM106B haplotype that is protective against TDP-43 proteinopathy.

PMID:
28441426
PMCID:
PMC5404753
DOI:
10.1371/journal.pmed.1002287
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Public Library of Science Icon for PubMed Central
Loading ...
Support Center