Association of Midlife Depressive Symptoms with Regional Amyloid-β and Tau in the Framingham Heart Study

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Abstract

Background: Depressive symptoms predict increased risk for dementia decades before the emergence of cognitive symptoms. Studies in older adults provide preliminary evidence for an association between depressive symptoms and amyloid-β (Aβ) and tau accumulation. It is unknown if similar alterations are observed in midlife when preventive strategies may be most effective. Objective: The study aim was to evaluate the association between depressive symptoms and cerebral Aβ and tau in a predominately middle-aged cohort with examination of the apolipoprotein (APOE) ɛ4 allele as a moderator. Methods: Participants included 201 adults (mean age 53±8 years) who underwent 11C-Pittsburgh Compound B amyloid and 18F-Flortaucipir tau positron emission tomography (PET) imaging. Depressive symptoms were evaluated with the Center for Epidemiological Studies Depression Scale (CES-D) at the time of PET imaging, as well as eight years prior. Associations between depressive symptoms at both timepoints, as well as depression (CES-D≥16), with regional Aβ and tau PET retention were evaluated with linear regression adjusting for age and sex. Interactions with the APOE ɛ4 allele were explored. Results: Depressive symptoms and depression were not associated with PET outcomes in the overall sample. However, among APOE ɛ4 allele carriers, there was a significant cross-sectional association between depressive symptoms and increased tau PET uptake in the entorhinal cortex (β= 0.446, SE = 0.155, p = 0.006) and amygdala (β= 0.350, SE = 0.133, p = 0.012). Conclusion: Although longitudinal studies are necessary, the results suggest that APOE ɛ4 carriers with depressive symptoms may present with higher susceptibility to early tau accumulation in regions integral to affective regulation and memory consolidation.

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The CES-D Scale: A Self-Report Depression Scale for Research in the General Population

L Radloff (1977)

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NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease

Clifford R. Jack, David Bennett, Kaj Blennow … (2018)

In 2011, the National Institute on Aging and Alzheimer’s Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer’s disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer’s Association to update and unify the 2011 guidelines. This unifying update is labeled a “research framework” because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer’s Association Research Framework, Alzheimer’s disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.

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An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

Rahul Desikan, Florent Ségonne, Bruce Fischl … (2006)

In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.

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Author and article information

Journal

Title: Journal of Alzheimer's Disease

Abbreviated Title: JAD

Publisher: IOS Press

ISSN (Print): 13872877

ISSN (Electronic): 18758908

Publication date Created: May 15 2021

Publication date (Print): May 15 2021

Pages: 1-12

Affiliations

[1 ]Glenn Biggs Institute for Alzheimer’s & Neurodegenerative Diseases, University of Texas Health Science Center, San Antonio, TX, USA

[2 ]Department of Neurology, University of Texas Health Science Center, San Antonio, TX, USA

[3 ]The Framingham Heart Study, Framingham, MA, USA

[4 ]Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA

[5 ]Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA

[6 ]Center for Imaging of Neurodegenerative Disease, Veteran Affairs Administration, San Francisco, CA, USA

[7 ]Department of Neurology, New York University Grossman School of Medicine, New York, NY, USA

[8 ]Department of Population Health Sciences, University of Texas Health Science Center, San Antonio, TX, USA

[9 ]Department of Neurology, Boston University School of Medicine, Boston, MA, USA

[10 ]Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA

[11 ]Department of Anatomy and Neurobiology, Boston University School of Medicine, Boston, MA, USA

[12 ]Department of Neurology, University of California Davis, Davis, CA, USA

[13 ]Center for Neuroscience, University of California Davis, Davis, CA, USA

[14 ]Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA

[15 ]Department of Neurology, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA

Article

DOI: 10.3233/JAD-210232

PubMed ID: 34024836

SO-VID: c080bfdd-665c-4129-a33c-5d27cd277b6c

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Association of Midlife Depressive Symptoms with Regional Amyloid-β and Tau in the Framingham Heart Study

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Abstract

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Functional role of amyloid

Most cited references 69

The CES-D Scale: A Self-Report Depression Scale for Research in the General Population

NIA-AA Research Framework: Toward a biological definition of Alzheimer’s disease

An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest.

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Cited by 10

Most referenced authors 1,395