Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study
- Washington University in St. Louis, United States
- Institute for Neurological Research (FLENI), Argentina
- Mayo Clinic Florida, United States
- Indiana University, United States
- Osaka Metropolitan University, Japan
- Ludwig-Maximilians-Universität München, Germany
Abstract
Background: Estimates of 'brain-predicted age' quantify apparent brain age compared to normative trajectories of neuroimaging features. The brain age gap (BAG) between predicted and chronological age is elevated in symptomatic Alzheimer disease (AD), but has not been well explored in presymptomatic AD. Prior studies have typically modeled BAG with structural magnetic resonance imaging (MRI), but more recently other modalities, including functional connectivity (FC) and multimodal MRI, have been explored.
Methods: We trained three models to predict age from FC, structural (S), or multimodal MRI (S+FC) in 390 amyloid-negative cognitively normal (CN/A-) participants (18-89 years old). In independent samples of 144 CN/A-, 154 CN/A+, and 154 cognitively impaired (CI; CDR > 0) participants, we tested relationships between BAG and AD biomarkers of amyloid and tau, as well as a global cognitive composite.
Results: All models predicted age in the control training set, with the multimodal model outperforming the unimodal models. All three BAG estimates were significantly elevated in CI compared to controls. FC-BAG was significantly reduced in CN/A+ participants compared to CN/A-. In CI participants only, elevated S-BAG and S+FC-BAG were associated with more advanced AD pathology and lower cognitive performance.
Conclusions: Both FC-BAG and S-BAG are elevated in CI participants. However, FC and structural MRI also capture complementary signals. Specifically, FC-BAG may capture a unique biphasic response to presymptomatic AD pathology, while S-BAG may capture pathological progression and cognitive decline in the symptomatic stage. A multimodal age-prediction model improves sensitivity to healthy age differences.
Funding: This work was supported by the National Institutes of Health (P01-AG026276, P01-AG03991, P30-AG066444, 5-R01-AG052550, 5-R01-AG057680, 1-R01-AG067505, 1S10RR022984-01A1, U19-AG032438), the BrightFocus Foundation (A2022014F), and the Alzheimer’s Association (SG-20-690363-DIAN).
Data availability
This project utilized datasets obtained from the Knight ADRC and DIAN. The Knight ADRC and DIAN encourage and facilitate research by current and new investigators, and thus, the data and code are available to all qualified researchers after appropriate review. Requests for access to the data used in this study may be placed to the Knight ADRC Leadership Committee (https://knightadrc.wustl.edu/professionals-clinicians/request-center-resources/) and the DIAN Steering Committee (https://dian.wustl.edu/our-research/for-investigators/dian-observational-study-investigator-resources/data-request-form/). Requests for access to the Ances lab data may be placed to the corresponding author. Code used in this study is available at https://github.com/peterrmillar/MultimodalBrainAge.
Article and author information
Author details
Funding
National Institutes of Health (P01-AG026276)
- John C Morris
National Institutes of Health (P01-AG03991)
- John C Morris
National Institutes of Health (P30-AG066444)
- John C Morris
National Institutes of Health (5-R01-AG052550)
- Beau M Ances
National Institutes of Health (5-R01-AG057680)
- Beau M Ances
National Institutes of Health (U19-AG032438)
- Randall J Bateman
BrightFocus Foundation (A2022014F)
- Peter R Millar
Alzheimer's Association (SG-20-690363-DIAN)
- Randall J Bateman
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Ethics
Human subjects: All participants provided written informed consent in accordance with the Declaration of Helsinki and their local institutional review board. All procedures were approved by the Human Research Protection Office at WUSTL (IRB ID # 201204041).
Reviewing Editor
- Karla L Miller, University of Oxford, United Kingdom
Publication history
- Received: July 14, 2022
- Accepted: December 30, 2022
- Accepted Manuscript published: January 6, 2023 (version 1)
Copyright
© 2023, Millar et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
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Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study
eLife 12:e81869.
https://doi.org/10.7554/eLife.81869
Further reading
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- Medicine
Background:
We have previously shown that the long non-coding (lnc)RNA prostate cancer associated 3 (PCA3; formerly prostate cancer antigen 3) functions as a trans-dominant negative oncogene by targeting the previously unrecognized prostate cancer suppressor gene PRUNE2 (a homolog of the Drosophila prune gene), thereby forming a functional unit within a unique allelic locus in human cells. Here, we investigated the PCA3/PRUNE2 regulatory axis from early (tumorigenic) to late (biochemical recurrence) genetic events during human prostate cancer progression.
Methods:
The reciprocal PCA3 and PRUNE2 gene expression relationship in paired prostate cancer and adjacent normal prostate was analyzed in two independent retrospective cohorts of clinically annotated cases post-radical prostatectomy: a single-institutional discovery cohort (n=107) and a multi-institutional validation cohort (n=497). We compared the tumor gene expression of PCA3 and PRUNE2 to their corresponding expression in the normal prostate. We also serially examined clinical/pathological variables including time to disease recurrence.
Results:
We consistently observed increased expression of PCA3 and decreased expression of PRUNE2 in prostate cancer compared with the adjacent normal prostate across all tumor grades and stages. However, there was no association between the relative gene expression levels of PCA3 or PRUNE2 and time to disease recurrence, independent of tumor grades and stages.
Conclusions:
We concluded that upregulation of the lncRNA PCA3 and targeted downregulation of the protein-coding PRUNE2 gene in prostate cancer could be early (rather than late) molecular events in the progression of human prostate tumorigenesis but are not associated with biochemical recurrence. Further studies of PCA3/PRUNE2 dysregulation are warranted.
Funding:
We received support from the Human Tissue Repository and Tissue Analysis Shared Resource from the Department of Pathology of the University of New Mexico School of Medicine and a pilot award from the University of New Mexico Comprehensive Cancer Center. RP and WA were supported by awards from the Levy-Longenbaugh Donor-Advised Fund and the Prostate Cancer Foundation. EDN reports research fellowship support from the Brazilian National Council for Scientific and Technological Development (CNPq), Brazil, and the Associação Beneficente Alzira Denise Hertzog Silva (ABADHS), Brazil. This work has been funded in part by the NCI Cancer Center Support Grants (CCSG; P30) to the University of New Mexico Comprehensive Cancer Center (CA118100) and the Rutgers Cancer Institute of New Jersey (CA072720).
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- Cancer Biology
- Medicine
Background: In this international multicenter study we aimed to determine the independent risk factors associated with increased 30-day mortality and the impact of cancer and novel treatment modalities in a large group of patients with and without cancer with COVID-19 from multiple countries.
Methods: We retrospectively collected de-identified data on a cohort of patients with and without cancer diagnosed with COVID-19 between January and November 2020, from 16 international centers.
Results: We analyzed 3966 COVID-19 confirmed patients, 1115 with cancer and 2851 nwithout cancer patients. Patients with cancer were more likely to be pancytopenic, and have a smoking history, pulmonary disorders, hypertension, diabetes mellitus, and corticosteroid use in the preceding two weeks (p≤0.01). In addition, they were more likely to present with higher inflammatory biomarkers (D-dimer, ferritin and procalcitonin), but were less likely to present with clinical symptoms (p≤0.01). By country-adjusted multivariable logistic regression analyses, cancer was not found to be an independent risk factor for 30-day mortality (p=0.18) whereas lymphopenia was independently associated with increased mortality in all patients, and in patients with cancer. Older age (≥65 years) was the strongest predictor of 30-day mortality in all patients(OR=4.47, p<0.0001). Remdesivir was the only therapeutic agent independently associated with decreased 30-day mortality ()(OR=0.64, p=0.036). Among patients on low-flow oxygen at admission, patients who received remdesivir had a lower 30-day mortality rate than those who did not (5.9% vs 17.6%; p=0.03).
Conclusions: Increased 30-day all-cause mortality from COVID-19 was not independently associated with cancer but was independently associated with lymphopenia often observed in hematolgic malignancy. Remdesivir, particularly in patients with cancer receiving low-flow oxygen, can reduce 30-day all-cause mortality.
Funding: National Cancer Institute, National Institutes of Health.
