Cited by 217Dementia and Cognitive Impairment ResearchAlzheimer's disease research and treatmentsAdvanced Proteomics Techniques and Applications

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Large-scale proteomic analysis of human brain identifies proteins associated with cognitive trajectory in advanced age

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Published version of a preprint

Abstract

In advanced age, some individuals maintain a stable cognitive trajectory while others experience a rapid decline. Such variation in cognitive trajectory is only partially explained by traditional neurodegenerative pathologies. Hence, to identify new processes underlying variation in cognitive trajectory, we perform an unbiased proteome-wide association study of cognitive trajectory in a discovery ( n = 104) and replication cohort ( n = 39) of initially cognitively unimpaired, longitudinally assessed older-adult brain donors. We find 579 proteins associated with cognitive trajectory after meta-analysis. Notably, we present evidence for increased neuronal mitochondrial activities in cognitive stability regardless of the burden of traditional neuropathologies. Furthermore, we provide additional evidence for increased synaptic abundance and decreased inflammation and apoptosis in cognitive stability. Importantly, we nominate proteins associated with cognitive trajectory, particularly the 38 proteins that act independently of neuropathologies and are also hub proteins of protein co-expression networks, as promising targets for future mechanistic studies of cognitive trajectory.

Overview

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TL;DR

This study performed an unbiased proteome-wide association study of cognitive trajectory in discovery (n = 104) and replication (n = 39) cohorts of initially cognitively unimpaired older-adult brain donors. Meta-analysis identified 579 proteins associated with cognitive trajectory, with cognitive stability linked to increased neuronal mitochondrial and synaptic proteins and decreased inflammation/apoptosis proteins.

Key findings

  • Meta-analysis found 579 proteins associated with cognitive trajectory at FDR < 0.05 among 2,752 protein isoforms detected in both cohorts; 350 had increased abundance and 229 had decreased abundance in cognitive stability.
  • Higher-abundance proteins in cognitive stability were enriched for mitochondrial function and synaptic transmission, and for neurons; lower-abundance proteins were enriched for inflammatory response, apoptosis, endothelial function, and RNA processing, and for oligodendrocyte, astrocyte, and microglia.
  • After adjusting for β-amyloid plaques and neurofibrillary tangles, 232 proteins remained associated with cognitive trajectory; higher-abundance proteins were still enriched for mitochondrial activities and synaptic transmission, while lower-abundance proteins changed to processes including glycolysis and neurofilament bundle assembly.
  • 38 proteins were associated with cognitive trajectory independently of β-amyloid plaques and neurofibrillary tangles and were hub proteins in both cohorts; the top protein was DLG4/PSD95, and the first principal component of the PSD95 interactome was associated with cognitive trajectory (β = 0.016; p = 0.0001; N = 104).

Methods

  • Discovery cohort: Banner Sun Health Research Institute participants (n = 104), non-demented at baseline, followed up to 14 years; replication cohort: Baltimore Longitudinal Study of Aging participants (n = 39), followed up to 20 years. Dorsolateral prefrontal cortex was analyzed by label-free proteomics; 3,710 proteins in Banner and 3,933 in BLSA were detected with 10% or fewer missing values, with 2,752 isoforms common to both.
  • Person-specific cognitive trajectory was estimated using a linear mixed model of annual MMSE score with random intercept and random slope per subject. Proteome-wide association used linear regression per cohort followed by METAL meta-analysis, adjusting for sex, age at enrollment, education, age at death, PMI, and batch; a secondary analysis additionally adjusted for β-amyloid plaques and neurofibrillary tangles.
  • Protein co-expression networks were constructed with WGCNA in Banner, and published BLSA networks were used; hub proteins were defined as those with intramodular kME in the top 90th percentile. GO and brain cell-type enrichment used Fisher’s exact test with FDR correction.

Limitations

  • The paper states that this is an association study and precludes causal inference; label-free proteomics yielded approximately 3,900 proteins, which is not as comprehensive as ideal; MMSE is a coarse screening tool; and sample sizes were relatively small (n = 104 and n = 39) and exclusively Caucasian, limiting generalizability and power.
  • The paper notes that BLSA protein co-expression modules were previously built using dorsolateral prefrontal cortex and precuneus, so module memberships might differ from those based on dorsolateral prefrontal cortex alone.
  • The paper notes that in BLSA only one module remained significantly associated with cognitive trajectory after multiple testing adjustment, likely due to small sample size and lower power.

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Integrity signals

Registry

Crossref · 10.1038/s41467-019-09613-z

Cites

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Statistics

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Figures

Fig. 1 Overview of the study design and results. The samples used in this study were from participants in two large prospective studies of aging in the United States who donated their brains upon death. Each subject in the present study were initially cognitively normal and had antecedent cognitive data used to estimate personal cognitive trajectories. Whole brain proteomic analysis of dorsolateral prefrontal cortex was used to estimate protein abundance for each participant. Proteome-wide association study of cognitive trajectory and protein co-expression network analysis revealed that individuals with cognitive stability (i.e., relatively little decline in cognition over time) have decreased abundance of the proteins involved in inflammation and apoptosis but increased abundance of the proteins involved in mitochondrial activities and synaptic function. Promising protein targets for further study are presented
Fig. 1 Overview of the study design and results. The samples used in this study were from participants in two large prospective studies of aging in the United States who donated their brains upon death. Each subject in the present study were initially cognitively normal and had antecedent cognitive data used to estimate personal cognitive trajectories. Whole brain proteomic analysis of dorsolateral prefrontal cortex was used to estimate protein abundance for each participant. Proteome-wide association study of cognitive trajectory and protein co-expression network analysis revealed that individuals with cognitive stability (i.e., relatively little decline in cognition over time) have decreased abundance of the proteins involved in inflammation and apoptosis but increased abundance of the proteins involved in mitochondrial activities and synaptic function. Promising protein targets for further study are presentedCC BY · PubMed Central
Fig. 2 Person-specific cognitive trajectory. This figure summarizes cognitive trajectory for each individual with colors indicating clinical diagnosis and Braak stage. Individual cognitive trajectory in the Banner cohort by a last clinical diagnosis (AD or control) prior to death and b Braak stage. Individual cognitive trajectory in the BLSA cohort by c clinical diagnosis; d Braak stage. A positive slope or small negative slope reflects cognitive stability. A larger negative slope reflects faster cognitive decline. The underlying data are available through the Synapse platform (protein abundance, https://www.synapse.org/#!Synapse:syn7170616 and https://www.synapse.org/#!Synapse:syn3606086) and Supplementary Data 1
Fig. 2 Person-specific cognitive trajectory. This figure summarizes cognitive trajectory for each individual with colors indicating clinical diagnosis and Braak stage. Individual cognitive trajectory in the Banner cohort by a last clinical diagnosis (AD or control) prior to death and b Braak stage. Individual cognitive trajectory in the BLSA cohort by c clinical diagnosis; d Braak stage. A positive slope or small negative slope reflects cognitive stability. A larger negative slope reflects faster cognitive decline. The underlying data are available through the Synapse platform (protein abundance, https://www.synapse.org/#!Synapse:syn7170616 and https://www.synapse.org/#!Synapse:syn3606086) and Supplementary Data 1CC BY · PubMed Central
Fig. 3 Differential protein expression in cognitive trajectory. This figure summarizes the meta-analysis of the proteome-wide association study of cognitive trajectory in the discovery (Banner) and replication (BLSA) cohort. a Volcano plot for the meta-analysis of the proteome-wide association studies of cognitive trajectory in the discovery and replication cohorts. A total of 579 proteins were associated with cognitive trajectory at FDR < 0.05. Among these, 350 proteins had increased abundance and 229 had decreased abundance in cognitive stability. The underlying data are available as Supplementary Data 2. In b, c, protein abundance vs. slope of cognitive trajectory is plotted with the best-fit regression line drawn in blue and the 95% confidence interval for the regression line shaded in gray. b Higher VGF protein level was associated with cognitive stability. Of note, for cognitive trajectory, a small negative slope reflects slow decline and a large negative slope reflects fast decline. Cognitive stability is reflected by a positive slope or very small negative slope of the cognitive trajectory. c Lower MAPT protein level was associated with cognitive stability. The data underlying b, c are available through the Synapse platform (protein abundance, https://www.synapse.org/#!Synapse:syn7170616 and https://www.synapse.org/#!Synapse:syn3606086) and Supplementary Data 1 (cognitive trajectories)
Fig. 3 Differential protein expression in cognitive trajectory. This figure summarizes the meta-analysis of the proteome-wide association study of cognitive trajectory in the discovery (Banner) and replication (BLSA) cohort. a Volcano plot for the meta-analysis of the proteome-wide association studies of cognitive trajectory in the discovery and replication cohorts. A total of 579 proteins were associated with cognitive trajectory at FDR < 0.05. Among these, 350 proteins had increased abundance and 229 had decreased abundance in cognitive stability. The underlying data are available as Supplementary Data 2. In b, c, protein abundance vs. slope of cognitive trajectory is plotted with the best-fit regression line drawn in blue and the 95% confidence interval for the regression line shaded in gray. b Higher VGF protein level was associated with cognitive stability. Of note, for cognitive trajectory, a small negative slope reflects slow decline and a large negative slope reflects fast decline. Cognitive stability is reflected by a positive slope or very small negative slope of the cognitive trajectory. c Lower MAPT protein level was associated with cognitive stability. The data underlying b, c are available through the Synapse platform (protein abundance, https://www.synapse.org/#!Synapse:syn7170616 and https://www.synapse.org/#!Synapse:syn3606086) and Supplementary Data 1 (cognitive trajectories)CC BY · PubMed Central
Fig. 4 Protein co-expression network. This figure shows the WGCNA cluster dendogram and 20 distinct protein co-expressed modules defined by dendogram branch cutting in the Banner cohort. Each module is given in a box with the module number and a functional summary of the proteins in the module derived by gene ontology enrichment. The underlying data are provided as a Supplementary Data 7
Fig. 4 Protein co-expression network. This figure shows the WGCNA cluster dendogram and 20 distinct protein co-expressed modules defined by dendogram branch cutting in the Banner cohort. Each module is given in a box with the module number and a functional summary of the proteins in the module derived by gene ontology enrichment. The underlying data are provided as a Supplementary Data 7CC BY · PubMed Central
Fig. 5 Modules enriched for cognitive trajectory-associated proteins. This figure summarizes the protein co-expression modules that are enriched for cognitive trajectory-associated proteins for each cohort with and without adjustment for neuropathologies. Enrichment was determined by Fisher’s exact test and reported p-values are adjusted for FDR. There are 579 cognitive trajectory-associated proteins in Banner and BLSA cohorts, which were divided into lower-abundance proteins in cognitive stability (229 proteins, colored in salmon) and higher-abundance proteins in cognitive stability (350 proteins, colored in turquoise), respectively. a Banner protein module enrichment; b BLSA protein module enrichment. After adjusting for β-amyloid plaques and neurofibrillary tangles, there were 232 cognitive trajectory-associated proteins, and enrichment was performed separately for lower-abundance proteins in cognitive stability (81 proteins, colored in salmon) and higher-abundance proteins in cognitive stability (151 proteins, colored in turquoise), respectively. c Banner protein module enrichment; d BLSA protein module enrichment. Source data are provided as a Source Data file
Fig. 5 Modules enriched for cognitive trajectory-associated proteins. This figure summarizes the protein co-expression modules that are enriched for cognitive trajectory-associated proteins for each cohort with and without adjustment for neuropathologies. Enrichment was determined by Fisher’s exact test and reported p-values are adjusted for FDR. There are 579 cognitive trajectory-associated proteins in Banner and BLSA cohorts, which were divided into lower-abundance proteins in cognitive stability (229 proteins, colored in salmon) and higher-abundance proteins in cognitive stability (350 proteins, colored in turquoise), respectively. a Banner protein module enrichment; b BLSA protein module enrichment. After adjusting for β-amyloid plaques and neurofibrillary tangles, there were 232 cognitive trajectory-associated proteins, and enrichment was performed separately for lower-abundance proteins in cognitive stability (81 proteins, colored in salmon) and higher-abundance proteins in cognitive stability (151 proteins, colored in turquoise), respectively. c Banner protein module enrichment; d BLSA protein module enrichment. Source data are provided as a Source Data fileCC BY · PubMed Central

Verification

Claims the paper makes

71 Own result · 49 Not checked yet · 19 Own interpretation · 12 Own method · 1 Partly supported · 1 Couldn’t confirm · 1 No basis given · accuracy not yet measured

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Show all 77 claims

  • Probably not a substantial claim. 51
  • It may state two separate claims as one. 51
77 of 77
  • The paper relies on this without support.

    No proteome-wide study of cognitive trajectory has been performed to date.

    “Yet, no proteome-wide study of cognitive trajectory has been performed to date.”
  • The paper relies on this without support.

    Removing batch, sex, age at death, and PMI effects from the proteomic profiles does not remove variance related to cognitive trajectory.

    “We removed these technical (batch and PMI) and biological effects (sex and age at death) because they may confound our association analyses between cognitive trajectory and protein levels.”
  • The paper relies on this without support.

    The BLSA protein co-expression networks from Seyfried et al. are applicable to the current BLSA proteomic data despite being built from different brain regions (precuneus and prefrontal cortex).

    “For BLSA, we used the BLSA networks from Seyfried et al.23, which were previously built using proteins measured from the precuneus and prefrontal cortex in the same individual.”
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Metadata

Authors
Wingo, A. P., Dammer, E. B., Breen, M. S., Logsdon, B. A., Duong, D. M., Troncosco, J. C., Thambisetty, M., Beach, T. G., Serrano, G. E., Reiman, E. M., Caselli, R. J., Lah, J. J., Seyfried, N. T., Levey, A. I., & Wingo, T. S.
Affiliations
  • Emory University (US)
  • Icahn School of Medicine at Mount Sinai (US)
  • Sage Bionetworks (US)
  • Johns Hopkins University (US)
  • National Institutes of Health (US)
  • Banner Sun Health Research Institute (US)
  • University of Arizona (US)
  • Mayo Clinic (US)
Corresponding author
Seyfried, Nicholas T.
Venue
Nature Communications
Published
2019-04-08
Volume
10
Issue
1
Pages
1619-1619
ISSN
2041-1723 (ISSN-L)
OpenAlex
W2937979781
Cited by
211
References
78
Citations by year
2026: 19 · 2025: 19 · 2024: 38 · 2023: 37 · 2022: 29 · 2021: 33 · 2020: 28 · 2019: 8
FWCI
4.12
Type
journal article
Language
en
Open access
Locations
  • Nature Communications (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • UA Campus Repository (The University of Arizona) (acceptedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
  • eScholarship (California Digital Library) (submittedVersion, cc-by)
Funders
  • U.S. Department of Veterans Affairs (I01BX003853, IK2 BX001820)
  • Michael J. Fox Foundation for Parkinson's Research (U24 NS072026, 05-901, 211002, 11060, P30 AG19610)
  • Alzheimer's Association (P50 AG025688, 11060)
  • Emory University (P50AG025688, AG025688)
  • Arizona Department of Health Services (P30 AG19610, P50 AG025688, U24 NS072026, 05-901, 211002, Contract 211002)
  • Weston Brain Institute (11060)
  • Arizona Biomedical Research Commission (P30 AG19610, 05–901, Contracts 4001, 0011, 05‐901 and 1001, U24 NS072026, 4001, 0011, 05-901, and 1001, 211002)
  • Alzheimer's Disease Research Center, Emory University (P50 AG025688, AG025688)
  • National Institute on Aging (211002, P30-AG-19610, R01AG056533, AG 025688, AG-19610, R01AG057911, AG057911, U01AG061357, I01 BX003853, P30AG019610, U01AG046161, 05-901, AG056533, AG061800, P50AG025688, R01AG053960, R01AG061800)
  • National Institute of Mental Health (U01MH115484)
  • National Institute of Neurological Disorders and Stroke (NS055077, NS072026, 211002, P30NS055077, U24NS072026, 05-901, U24 NS072026 National Brain, P30 AG19610)
Topics
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
  • Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
Keywords
cognitive trajectories, aging, human brain proteome, proteome-wide association study, cognitive stability, cognitive decline, mitochondrial activity, synaptic proteins, neuroinflammation, apoptosis, neuropathology, protein co-expression networks, hub proteins, older adults
MeSH terms
Biological Variation, Population, Aged, Aged, 80 and over, Aging, Alzheimer Disease, Brain, Cognition, Humans, Middle Aged, Parkinson Disease, Proteome, Proteomics, Healthy Volunteers

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