Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2017 Feb 1.
Published in final edited form as: Neuropsychology. 2016 Feb;30(2):135–142. doi: 10.1037/neu0000223

Late-Life Depression is Not Associated with Dementia Related Pathology

Robert S Wilson 1, Patricia A Boyle 1, Ana W Capuano 1, Raj C Shah 1, George M Hoganson 1, Sukriti Nag 1, David A Bennett 1
PMCID: PMC4740262  NIHMSID: NIHMS697605  PMID: 26237627

Abstract

Objective

To test the hypothesis that late-life depression is associated with dementia related pathology.

Method

Older participants (n=1,965) in 3 longitudinal clinical-pathologic cohort studies who had no cognitive impairment at baseline underwent annual clinical evaluations for a mean of 8.0 years (SD = 5.0). We defined depression diagnostically, as major depression during the study period, and psychometrically, as elevated depressive symptoms during the study period, and established their relation to cognitive outcomes (incident dementia, rate of cognitive decline). A total of 657 participants died and underwent a uniform neuropathologic examination. We estimated the association of depression with 6 dementia related markers (tau tangles, beta-amyloid plaques, Lewy bodies, hippocampal sclerosis, gross and microscopic infarcts) in logistic regression models.

Results

In the full cohort, 9.4% were diagnosed with major depression and 8.6% had chronically elevated depressive symptoms, both of which were related to adverse cognitive outcomes. In the 657 persons who died and had a neuropathologic examination, higher beta-amyloid plaque burden was associated with higher likelihood of major depression (present in 11.0%; odds ratio = 1.392, 95% confidence interval = 1.088, 1.780) but not with elevated depressive symptoms (present in 11.3%; odds ratio = 0.919, 95% confidence interval = 0.726, 1.165). None of the other pathologic markers was related to either of the depression measures. Neither dementia nor antidepressant medication modified the relation of pathology to depression.

Conclusion

The results do not support the hypothesis that major depression is associated with dementia related pathology.

Keywords: depression, longitudinal study, clinical-pathologic study, dementia, antidepressant medication

INTRODUCTION

Depression is associated with an increased risk of developing of dementia (Jorm, 2001; Ownby, Crocco, Acevedo, John, & Lowenstein, 2006; Byers & Yaffe, 2011) for reasons that are not clear. The most parsimonious explanation is that they share common pathologic mechanisms, with depression a prodromal manifestation of the same pathologies that eventually cause dementia (Bromelhoff et al., 2009; Panza et al., 2010; Li et al., 2011; Lenoir et al., 2011; Barnes et al., 2012; Heser et al., 2013). Clinical-pathologic research has generally not suggested an association between depressive symptoms and dementia related pathologies (Wilson et al., 2003; Royall & Palmer, 2013; Wilson, Capuano, et al., 2014). However, there is evidence that major depression is associated with neuritic plaques and neurofibrillary tangles (Rapp et al., 2006), suggesting that depression may need to reach some threshold of severity before its association with dementia related pathology is detectable. Support for this idea has been mixed in subsequent studies (Rapp et al., 2008; Tsopelas et al., 2011), possibly due to differences in depression criteria or the confounding influence of other factors such as dementia or antidepressant medication use.

In the present study, we test the hypothesis that depression is associated with common pathologic conditions linked to late-life dementia. Analyses are based on data from three longitudinal clinical-pathologic cohort studies that included annual clinical evaluations and brain autopsy at death. A total of 1,963 persons had no cognitive impairment at enrollment and valid data on depression which was defined in 2 ways: major depression diagnosed during the study and persistently elevated depressive symptoms during the study. During follow-up, 657 individuals died and underwent a brain autopsy, and measures of 6 dementia related neurodegenerative and cerebrovascular conditions were derived from a uniform neuropathologic examination. In a series of logistic regression models, we estimated the association of each neuropathologic marker with depression and tested whether these associations were modified by the presence of dementia or use of antidepressant medications.

METHODS

Participants

Analyses are based on individuals from three ongoing longitudinal clinical-pathologic cohort studies. The Religious Orders Study began in 1994. It involves older Catholic priests, nuns, and monks from more than 40 groups across the United States (Wilson, Bienias, Evans, & Bennett, 2004; Bennett, Schneider, Arvanitakis, & Wilson, 2012). The Rush Memory and Aging Project began in 1997 and includes older lay persons from the Chicago area (Bennett et al., 2005; Bennett, Schneider, Buchman, et al., 2012). The Minority Aging Research Study began in 2004. Participants are older black persons in the Chicago area recruited from the community and the clinical core of the Rush Alzheimer’s Disease Core Center (Arvanitakis, Bennett, Wilson, & Barnes, 2010; Barnes, Shah, Aggarwal, Bennett, & Schneider, 2012). At baseline, persons in each study were at least 50 years old, had not previously been diagnosed with dementia, and agreed to annual clinical evaluations. All persons in the Religious Orders study and Rush Memory and Aging Project and a subset of those in the Minority Aging Research Study also agreed to brain autopsy at death. All participants provided written informed consent after a thorough discussion with study personnel. The institutional review board of Rush University Medical Center approved each study.

At the time of these analyses, 2,444 individuals had completed the baseline clinical evaluation and been found to have no cognitive impairment. There were 44 deaths before the first annual follow-up evaluation and 97 persons had been in the study less than one year. Of the remaining 2,303 individuals who were eligible for follow-up, 1,965 (85.3%) had follow-up data and were included in analyses. They had a mean age at baseline of 76.3 years (SD=7.5) and a mean of 16.1 years of education (SD=3.7); 73.8% were women. During a mean of 8.0 years of annual follow-up (SD=5.0), 764 persons died. Of these, 683 (89.4 %) had a brain autopsy, and a uniform neuropathologic examination had been completed on the first consecutive 657 individuals who died at a mean age of 87.9 (SD=6.7). Compared to the 1,310 participants without neuropathologic data, the 657 neuropathologically examined individuals were older at baseline (79.1 vs 74.9, t[1,428.9] = 12.5, p <0.001), had more years of education (16.5 vs 15.9, t[1,965] = 3.5, p < 0.001), and were more apt to be men (33.3% vs 22.6%, χ2 [1] = 26.1, p<0.001) and have elevated depressive symptoms on the Center for Epidemiological Studies Depression scale (11.3% vs 7.3%, χ2 [1]=8.9, p = 0.003) but the subgroups did not differ in rate of major depression (11.0% vs 8.6%, χ2[1] = 2.8, p=0.095).

Clinical Evaluation

Each year participants had a uniform clinical evaluation that included a structured medical history, detailed cognitive testing, and a neurologic examination. Following the evaluation, an experienced clinician diagnosed dementia according to the criteria of the joint working group of the National Institute of Neurological and Communicative Disorders and Stroke and the Alzheimer’s Disease and Related Disorders Association (McKhann et al., 1984). These require a history of cognitive decline and impairment in at least two cognitive domains.

Assessment of Depression

We defined depression in two ways. The first was major depression according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders, 3rd ed, Revised (American Psychiatric Association, 1987) implemented with a subset of questions from the Diagnostic Interview Schedule (Robins, Helzer, & Croughan, 1981) at each annual evaluation. All participants were asked “In the past month, has there been a period of 2 weeks or more during which you felt sad, blue, or depressed, or when you lost interest and pleasure in things you usually cared about?” A yes response elicited questions about the presence of 8 other symptoms of depression during this period (e.g., appetite, sleep, energy, concentration, guilt), and the presence of 4 or more of these additional depressive symptoms led to a diagnosis of major depression (American Psychiatric Association, 1987). Persons were classified as depressed if they met these criteria at any point during the study. To complement this diagnostic definition of depression, we used a psychometric definition that required persistent symptoms. At each evaluation, participants completed a 10-item version (Kohout, Berkman, Evans, & Cornoni-Huntley, 1993) of the Center for Epidemiological Studies Depression scale (Radloff, 1977). Individuals were asked if they had experienced each of 10 depressive symptoms in the past week (e.g., “I felt like like everything I did was an effort”). Because the accepted depression cutoff score of 16 on the original Center for Epidemiological Studies Depression scale represents approximately 27% of the total possible score (i.e., 16/60 = 0.267), we chose a depression cutoff score of 3 on the 10-item Center for Epidemiological Studies Depression scale which represents 30% of the total possible score and required a mean score of 3 or more symptoms across all evaluations as a psychometric indicator of depression. Medications were coded each year using the Medi-Span Master Drug Database (Medi-Span, Inc., 1995).

Assessment of Cognitive Function

As part of each annual clinical evaluation, a battery of 19 cognitive performance tests was administered by a research assistant in an approximately one hour session. The cognitive assessment was designed to support clinical classification of dementia and allow measurement of change in cognitive function over time. Two tests were used exclusively for clinical classification: the Mini-Mental State Examination (Folstein, Folstein, & McHugh, 1975), a measure of global cognitive function, and Complex Ideational Material (Kaplan & Goodglass, 1983), a measure of auditory verbal comprehension. The other 17 tests were used diagnostically and in longitudinal analyses. Episodic memory was assessed with 7 measures: immediate and delayed recall of Story A from Logical Memory of the Wechsler Memory Scale-Revised (Wechsler, 1987) and the East Boston story (Albert et al., 1991; Wilson, Beckett, et al., 2002) and Word List Memory, Word List Recall, and Word List Recognition from the test battery developed by the Consortium to Establish a Registry for Alzheimer’s Disease (Welsh et al., 1994). Semantic memory was assessed with a 15-item short form (Welsh et al., 1994) of the Boston Naming Test, a measure of verbal fluency that involved naming examples of two categories (animals, vegetables) in separate 1-minute trials (Welsh et al., 1994; Wilson, Beckett, et al., 2002), and a 15-item word recognition task that required pronunciation of words with atypical spelling sound correspondence (Wilson, Beckett, et al., 2002). Working memory was measured with Digit Span Forward and Digit Span Backward from the Wechsler Memory Scale-Revised (Wechsler, 1987) and Digit Ordering which required listening to strings of digits and saying them back in ascending order (Wilson, Beckett, et a., 2002). Number Comparision (Ekstrom, French, Harman, & Kermen, 1976; Wilson, Beckett, et al., 2002) and the oral version of the Symbol Digit Modalities Test (Smith, 1982) were used to measure perceptual speed. A 15-item form of Judgment of Line Orientation (Benton, Sivan, Hamsher, Varney, & Spreen, 1994) and a 16-item form of Standard Progressive Matrices (Raven, Court, & Raven, 1992) assessed visuospatial ability.

The presence or absence of impairment in 5 cognitive domains (orientation, attention, memory, language, perception) was determined by a neuropsychologist after review of all cognitive data and ratings of each domain generated by an algorithm (Bennett, Schneider, et al., 2006; Wilson, Boyle, Yang, James, & Bennett, 2014). Those with impairment in any cognitive domain at baseline were excluded from analyses.

To accommodate a wide range of cognitive ability and thereby minimize floor and ceiling artifacts, we analyzed change in cognitive function over time with a composite measure of global cognition based on all 17 tests. Raw scores on the individual tests of cognitive function were converted to z scores, using the baseline means and standard deviations of all persons in the parent studies. The z scores were then averaged to create a composite measure of global cognition, as previously described (Wilson, Beckett, et al., 2002; Wilson, Boyle, et al., 2014).

Neuropathologic Examination

Persons died a mean of 0.8 year after the last clinical assessment (SD = 1.0) and the brain was removed a mean of 8.6 hours following death (SD=7.0). As previously detailed (Bennett, Schneider, Wilson, Bienias, & Arnold, 2004; Bennett et al., 2006), tissue preservation and sectioning and quantification of pathologic data followed a standard protocol that was implemented by individuals who were unaware of all clinical information. One cm slabs were cut from the cerebral hemispheres (coronally) and cerebellar hemispheres (sagitally) and the brainstem was removed at the level of the mamillary bodies and bisected mid-pons.

All slabs were inspected for gross infarcts. We fixed slabs from one cerebral and cerebellar hemisphere and slabs from the other hemisphere with suspected infarcts in 4% paraformaldehyde. We histologically confirmed suspected infarcts and classified them as acute, subacute, or chronic. In 9 regions (6 cortical, 2 subcortical, 1 brainstem) of one hemisphere, we used 6-um paraffin-embedded hematoxylin and eosin stained sections to identify microscopic infarcts. Chronic gross and microscopic infarcts were each treated as binary variables in analyses.

We used immunohistochemistry and computer-assisted sampling to assess beta-amyloid plaques and tau-tangles in 8 brain regions: anterior cingulate cortex, entorhinal cortex, CA1/subiculum, dorsal lateral prefrontal cortex, superior frontal cortex, inferior parietal cortex, inferior temporal cortex, and primary visual cortex (Bennet et al., 2004). Beta-amyloid was labeled with an N-terminus-directed monoclonal antibody (1:1,000, 10D5; Elan Pharmaceuticals, Dublin, Ireland), and tau-immunoreactive tangles were quantified with an anti-paired helical filament-tau antibody clone AT8 (1:2,000; Thermo Scientific, Rockford, IL). The regional values were averaged to form continuous composite measures of beta-amyloid burden (with a square root transformation) and tau-tangle density, as previously described (Bennett et al., 2004).

A monoclonal antibody to phosphorylated alpha-synuclein (1:20,000; Wako Chemical USA Inc., Richmond, VA) was used to identify Lewy bodies in 6 regions: substantia nigra, entorhinal cortex, anterior cingulate cortex, inferior parietal cortex, midfrontal cortex, and superior or middle temporal cortex (Wilson et al., 2011). Hippocampal sclerosis was defined as severe neuronal loss in the pyramidal cell layer of the subiculum or any hippocampal subfield (Wilson, Yu, et al., 2013).

Statistical Analysis

In the full cohort, we assessed the relation of each depression measure to likelihood of developing incident dementia in logistic regression models and to rate of global cognitive decline in mixed-effects models. These and all subsequent analyses were adjusted for age, gender, and education. We assessed the relation of the postmortem pathologic measures to the depression measures in logistic regression models. Logistic regression models were also used to test whether dementia or antidepressant medication use modified the association between the pathologic markers and depression measures.

RESULTS

Depression

In the full cohort (n=1,965), there were 184 (9.4%) persons who were diagnosed with major depression at some point during the study and 169 (8.6%) persons who had a mean of 3 or more depressive symptoms on the Center for Epidemiological Studies Depression scale during the study. The two measures were correlated, with 76 individuals meeting both definitions, 1,686 meeting neither definition, 108 with major depression but not chronically elevated depressive symptoms, 93 with elevated depressive symptoms but not major depression, and 2 missing data on depressive symptoms (χ2 [1] = 275.8, p< 0.001). As shown in Table 1, those with depression by either definition had less education and a lower baseline level of global cognition than those without depression and were more likely to be women. In support of their validity, both measures were associated with antidepressant medication use (Table 1).

Table 1.

Characteristics of persons in the full cohort with and without depression by diagnostic and psychometric definitions

Major Depression Elevated Depressive Symptoms
Characteristic Yes (n=184) No (n=1,781) p Yes (n=169) No (n=1,794) p
Age, baseline 75.8 (7.3) 76.4 (7.5) 0.293 77.8 (7.1) 76.2 (7.5) 0.006
Education 14.9 (4.4) 16.3 (3.6) <0.001 14.5 (4.1) 16.3 (3.7) <0.001
Women, % 81.1 73.1 0.018 82.8 73.0 0.005
Antidepressant use, % 53.5 25.5 <0.001 56.2 25.5 <0.001
Global cognition, baseline 0.085 (0.455) 0.282 (0.427) <0.001 0.068(0.494) 0.282 (0.423) <0.001
Open in a new tab

Note. Data are presented as mean (SD) unless otherwise indicated. Two participants were missing data on depressive symptoms.

Depression and Dementia

Because binary indicators of depression have been related to cognitive outcomes in previous research (Jorm, 2001; Ownby et al., 2006; Byers & Yaffe, 2011), the first analytic aim was to assess whether the depression measures were related to cognitive outcomes as further test of their validity. During a mean of 8.0 years of follow-up (SD= 5.0), 346 individuals developed incident dementia, and we constructed separate logistic regression models to test whether the depression measures were related to likelihood of incident dementia. These and all subsequent analyses were adjusted for the potentially confounding effects of age, gender, and educational attainment. Both major depression and elevated depressive symptoms during the study were associated with higher likelihood of developing dementia (Table 2).

Table 2.

Association of depression with incident dementia and cognitive decline in the full cohort

Depression measure Cognitive Outcome Odds Ratio 95% CI Estimate SE P
Major depression Dementia 2.358 1.641, 3.388
Cognitive intercept −0.134 0.030 <0.001
Cognitive slope −0.026 0.007 <0.001
Elevated depressive symptoms Dementia 1.975 1.356, 2.874
Cognitive intercept −0.141 0.033 <0.001
Cognitive slope −0.039 0.009 <0.001
Open in a new tab

Note. Estimated from logistic and mixed-effects models adjusted for age at baseline, gender, and education. CI, confidence interval; SE, standard error.

At baseline, the composite measure of global cognition ranged from −1.49 to 1.49 (mean= 0.26, SD=0.43 skewness=−0.30), with higher scores indicating better cognitive functioning. We constructed mixed-effects models (Laird & Ware, 1982) to test whether the depression measures were related to trajectories of global cognitive decline. As shown in Table 2, both depression measures were associated with lower level of cognitive function at baseline and faster rate of cognitive decline during follow-up.

Dementia Related Pathology

A total of 657 individuals died and underwent a brain autopsy and uniform neuropathologic examination. The composite measure of tau tangle density ranged from 0.0 to 32.2 (mean = 4.6, SD = 5.3) with at least some level of tau present in 656 persons (99.9%. Due to its skewed distribution, we used the square root of the composite measure of beta-amyloid burden. At least some amyloid was detected in 565 persons (86.0%) (mean = 1.5, SD = 1.2, range = 0.0–4.7). There were Lewy bodies in 22.1%, hippocampal sclerosis in 6.2%, one or more chronic gross infarcts in 31.4%, and one or more chronic microscopic infarcts in 28.3%. There was some postmortem evidence of dementia related pathology in all individuals: 41 persons (6.2%) had 1 postmortem marker, 259 (39.4%) had 2 markers, 219 (33.3%) had 3 markers, 109 (10.6%) had 4 markers, 27 (4.1%) had 5 markers, and 2 (0.3%) had all 6 markers.

Depression and Pathology

In the neuropathologically examined group, 72 individuals (11.0%) met criteria for major depression at some point during the study and 74 (11.3%) had chronically elevated depressive symptoms on the Center for Epidemiological Studies Depression scale. There were 33 individuals who met both definitions of depression, 544 who met neither, 39 with major depression but not persistently elevated depressive symptoms, and 41 with elevated depressive symptom but not major depression (χ2 [1] = 96.7, p<0.001).

To test whether dementia related pathology was associated with depression, we regressed each depression measure on the 6 pathologic markers in separate logistic models adjusted for age at death, gender, and education (table 3). Higher beta-amyloid plaque burden was associated with higher odds of major depression but not with elevated depressive symptoms. The other pathologic markers were not related to either depression measure.

Table 3.

Association of dementia related pathologies with depression

Major Depression Elevated Depressive Symptoms
Pathologic Marker Odds Ratio 95% CI Odds Ratio 95% CI
Tangle density 0.994 0.942, 1.047 0.987 0.933, 1.043
Amyloid plaques 1.392 1.088, 1.780 0.919 0.726, 1.165
Lewy bodies 1.344 0.735, 2.455 1.350 0.767, 2.377
Hippcampal sclerosis 0.758 0.220, 2.609 0.482 0.112, 2.081
Gross Infarcts 1.218 0.686, 2.164 1.228 0.721. 2.092
Microinfarcts 1.108 0.614, 2.002 1.183 0.687, 2.039
Open in a new tab

Note. Estimated from 2 logistic regression models adjusted for age at death, gender, and education. CI, confidence interval.

Modifying Factors

Because previous research has suggested that the association of neuropathologic markers to depression might depend on the presence or absence of dementia (Rapp et al., 2006; Rapp et al., 2008; Tsopelas et al., 2011), we tested whether dementia modified the association of each pathological measure with each depression measure (table 4). There was no evidence that the relation of pathology to depression differed in those with versus without dementia.

Table 4.

Assessment of whether dementia modified the association of pathology with depression

Major depression Elevated depressive symptoms
Interaction term Estimate SE p Estimate SE p
Tangle density x dementia −0.001 0.049 0.981 −0.081 0.055 0.139
Amyloid plaques x dementia −0.006 0.251 0.980 −0.088 0.242 0.716
Lewy bodies x dementia 0.478 0.593 0.420 −0.693 0.574 0.227
Hippocampal sclerosis x dementia −0.659 1.307 0.614 −1.184 1.485 0.425
Gross infarcts x dementia 0.338 0.561 0.547 1.068 0.563 0.058
Microinfarcts x dementia −1.158 0.622 0.063 −0.084 0.560 0.881
Open in a new tab

Note. Estimated from 12 logistic regression models adjusted for age at death, gender, and education. SE, standard error.

There is evidence in animal research that the deleterious effects of chronic stress on the brain are modified by antidepressant medication (Czéh et al., 2001; Shakesby, Anwyl, & Rowan, 2002). Therefore, we tested whether the associations of the pathologic measures with depression were modified by use of antidepressant medications during the study. There was no evidence that antidepressant medication use affected results.

DISCUSSION

In a longitudinal clinical-pathologic study of more than 650 older persons without cognitive impairment at enrollment, we defined depression as major depression or elevated depressive symptoms during the study. Following brain autopsy, there was a uniform neuropathologic examination to quantify common dementia related pathologies. None of the postmortem pathologic markers was related to depression except for an association of beta-amyloid burden with major depression but not elevated depressive symptoms. Overall, the results do not support the hypothesis that major depression is related to the neurodegenerative or cerebrovascular conditions underlying late-life dementia.

Evidence of an association between depression and dementia related pathology comes mainly from 2 studies of prevalent dementia. In one of these, a history of major depression was associated with higher levels of hippocampal plaques and tangles (Rapp et al., 2006). In the other study, a diagnosis of depression was associated with higher burden of tangles but not plaques (Rapp et al., 2008). In both of these studies, however, the presence of dementia greatly complicates the diagnosis of depression because self report is less accurate due to impaired memory (Gilley & Wilson, 1997) and informant report is potentially biased due to comorbid dementia. As a result, depressive symptoms are more difficult to disentangle from the dementia syndrome, and because of this criterion contamination, depressive symptoms may be more likely to show a spurious correlation with dementia related pathology, particularly when other factors may be contributing to error in clinical classification of depression such as reliance on retrospective report (Rapp et al., 2006) or use of depression diagnostic criteria that are insufficiently specified (Rapp et al., 2008). To avoid this potential source of bias, one clinical-pathologic study of late-life depression and AD pathology excluded individuals with dementia (Tsopelas et al., 2011). There was no association of semiquantitative ratings of plaques and tangles with late-life depression, but it is possible that excluding those with dementia affected results by restricting the range of AD pathology observed on postmortem examination. The present study confronted this issue in two ways. First, participants had no cognitive impairment at baseline and all dementia was incident, so that most of depression data collection was from individuals without dementia. Second, we explicitly tested whether incident dementia modified the association between depression and the pathologic markers, and we found no evidence that it did. We suggest, therefore, that the lack of an association between major depression and dementia related pathology in the present study, and the previous study that excluded dementia (Tsopelas et al., 2011), is probably substantially correct.

A challenge in clinical-pathologic research on late-life depression is the potentially confounding influence of antidepressant medications. That is, antidepressant medication use might alter the impact of chronic depression on the brain (Czéh et al., 2001; Shakesby et al., 2002) or by reducing depressive symptoms, antidepressant medication use might obscure an association between depression and pathologic markers. In the present analyses, however, we found no evidence that antidepressant medication use modified the association between depression and the neuropathologic markers.

Major depression (Jorm, 2001; Ownby et al., 2006; Byers & Yaffe, 2011) and higher level of depressive symptoms (Wilson, Barnes, et al., 2002; Saczynski et al., 2010; Barnes et al., 2012) are each associated with higher risk of dementia, but neither major depression in the present analyses nor level of depressive symptoms in previous analyses (Wilson et al., 2014) were related to postmortem markers of AD and other late-life dementias. This suggests that depression, whether defined diagnostically or psychometrically, somehow reduces cognitive reserve and that effective treatment of depression may bolster cognitive reserve. Previous clinical-pathologic (Soetanto et al., 2010; Wilson, Nag, et al., 2013) and clinical-radiologic (Koolschijn et al., 2009; Dotson, Davatzikos, Kraut, & Resnick, 2009; Sexton, Mackay, & Ebmeier, 2009; Sexton et al., 2012) research has associated depression with fronto-subcortical and limbic circuits that support regulation of emotional states. In addition, resting state functional connectivity studies have identified abnormalities in major depressin involving in particular the default mode network, affective network, and cerebellum (Wang, Hermens, Hickie, & Lagopoulos, 2012; Zeng et al., 2012; Ma, Zeng, Shen, Liu & Hu, 2013), and these functional abnormalities have been associated with cognitive decline (Wang et al., 2015). Better understanding of the neurobiological bases of the relationship between late-life depression and cognition might suggest novel approaches to enhancing late-life cognitive health.

These data have important strengths and limitations. Results were mostly consistent with diagnostic and psychometric measures of depression, suggesting that they are reliable. There were high rates of participation in clinical follow-up and brain autopsy, minimizing bias due to selective attrition. Dementia classification was based on a uniform clinical assessment and accepted criteria applied by an experienced clinician and neuropathologic assessment was based on a uniform examination of multiple brain regions, reducing measurement error. A limitation is that results are based on a selected group of participants and may not generalize to other groups of older persons. In addition, it is possible that pathological changes in brainstem aminergic nuclei could be contributing to late-life depression, but previous clinical-pathologic research in these (Wilson, Nag, et al., 2013) and other (Hendricksen, Thomas, Ferrier, Ince, & O’Brien, 2004; Syed et al., 2005) cohorts does not support this idea. Finally, treating depression as a binary variable allowed us to focus on moderately severe depression, but it limited statistical power which may have affected results, particularly for less common pathologic conditions such as hippocampal sclerosis.

Acknowledgments

This research was supported by NIH grants R01AG17917, P30AG10161, R01AG15819, R01AG33678, and R01AG34374, and by the Illinois Department of Public Health. The funding organizations had no role in the design or conduct of the study; collection, management, analysis, or interpretation of the data; or preparation, review, or approval of the manuscript. The authors thank the many Illinois residents for participating in the Rush Memory and Aging Project and the many Catholic nuns, priests, and monks for participating in the Religious Orders Study; Traci Colvin, MPH, and Karen Skish, MS, for study coordination; John Gibbons, MS, and Greg Klein, MS, for data management; and Alysha Kett, MS, for statistical programming.

References

  1. Albert M, Scherr P, Taylor J, Evans D, Funkensten H. Use of brief cognitive tests to identify individuals in the community with clinically diagnosed Alzheimer’s disease. International Journal of Neuroscience. 1991;57:167–178. doi: 10.3109/00207459109150691. [DOI] [PubMed] [Google Scholar]
  2. American Psychiatric Association. Diagnostic and statistical manual of mental disorders. 3. Washington, DC: American Psychiatric Association; 1987. revised. [Google Scholar]
  3. Barnes LL, Wilson RS, Everson-Rose SA, Hayward MD, Evans DA, Mendes de Leon CF. Effects of early-life adversity on cognitive decline in older African Americans and whites. Neurology. 2012;79:2321–2327. doi: 10.1212/WNL.0b013e318278b607. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Barnes DE, Yaffe K, Byers AL, McCormick M, Schaefer C, Whitmer RA. Midlife vs late-life depressive symptoms and risk of dementia. Archives of General Psychiatry. 2012;69:493–498. doi: 10.1001/archgenpsychiatry.2011.1481. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Bennett DA, Schneider JA, Aggarwal NT, Arvanitakis Z, Shah RC, Kelly JF, Wilson RS. Decision rules guiding the clinical diagnosis of Alzheimer’s disease in two community-based cohort studies compared to standard practice in a clinic-based cohort study. Neuroepidemiology. 2006;27:169–176. doi: 10.1159/000096129. [DOI] [PubMed] [Google Scholar]
  6. Bennett DA, Schneider JA, Arvanitakis Z, Kelly JF, Aggarwal NT, Shah RC, Wilson RS. Neuropathology of older persons without cognitive impairment from two community-based studies. Neurology. 2006;66:1837–1844. doi: 10.1212/01.wnl.0000219668.47116.e6. [DOI] [PubMed] [Google Scholar]
  7. Bennett DA, Schneider JA, Arvanitakis Z, Wilson RS. Overview and findings from the Religious Orders Study. Current Alzheimer Research. 2012;9:628–645. doi: 10.2174/156720512801322573. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Bennett DA, Schneider JA, Buchman AS, Barnes LL, Boyle PA, Wilson RS. Overview and findings from the Rush Memory and Aging Project. Current Alzheimer Research. 2012;9:646–663. doi: 10.2174/156720512801322663. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Bennett DA, Schneider JA, Buchman AS, Mendes de Leon CF, Wilson RS. The Rush Memory and Aging Project: study design and baseline characteristics of the study cohort. Neuroepidemiology. 2005;25:163–175. doi: 10.1159/000087446. [DOI] [PubMed] [Google Scholar]
  10. Bennett DA, Schneider JA, Wilson RS, Bienias JL, Arnold SE. Neurofibrillary tangles mediate the association of amyloid with clinical AD and level of cognitive function. Archives of Neurology. 2004;61:348–384. doi: 10.1001/archneur.61.3.378. [DOI] [PubMed] [Google Scholar]
  11. Benton AL, Sivan AB, de Hamsher KS, Varney NR, Spreen O. Contributions to neuropsychological assessment. 2. New York: Oxford University Press; 1994. [Google Scholar]
  12. Brommelhoff JA, Gatz M, Johansson B, McArdle JJ, Fratiglioni L, Pedersen NL. Depression as a risk factor or prodomal feature for dementia? Findings in a population-based sample of Swedish twins. Psychology and Aging. 2009;24:373–384. doi: 10.1037/a0015713. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Byers AL, Yaffe K. Depression and risk of developing dementia. Nature Reviews Neurology. 2011;7:323–331. doi: 10.1038/nrneurol.2011.60. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Czéh B, Michaelis T, Watanabe T, Frahm J, de Biurrun G, van Kampen M, Fuchs E. Stress-induced changes in cerebral metabolities, hippocampal volume, and cell proliferation are prevented by antidepressant treatment with tianeptine. Proceedings of the National Academy of Sciences. 2001;98:12796–12801. doi: 10.1073/pnas.211427898. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Dotson VM, Davatzikos C, Kraut MA, Resnick SM. Depressive symptoms and brain volumes in older adults: a longitudinal magnetic resonance imaging study. Journal of Psychiatry and Neuroscience. 2009;34:367–375. [PMC free article] [PubMed] [Google Scholar]
  16. Ekstrom RB, French JW, Harman HH, Kermen D. Manual for kit of factor-referenced cognitive tests. Princeton, NJ: Educational Testing Service; 1976. [Google Scholar]
  17. Folstein M, Folstein S, McHugh P. Mini-Mental State: a practical method for grading the mental state of patients for the clinician. Journal of Psychiatric Research. 1975;12:189–198. doi: 10.1016/0022-3956(75)90026-6. [DOI] [PubMed] [Google Scholar]
  18. Gilley DW, Wilson RS. Criterion-related validity of the Geriatric Depression Scale in Alzheimer’s disease. Journal of Clinical Experimental Neuropsychology. 1997;19:489–499. doi: 10.1080/01688639708403739. [DOI] [PubMed] [Google Scholar]
  19. Hendricksen M, Thomas AJ, Ferrier IN, Ince P, O’Brien JT. Neuropathological study of the dorsal raphe nuclei in late-life depression and Alzheimer’s disease with and without depression. American Journal of Psychiatry. 2004;161:1092–1102. doi: 10.1176/appi.ajp.161.6.1096. [DOI] [PubMed] [Google Scholar]
  20. Heser K, Tebarth F, Wiese B, Eisele M, Bickel H, Kohler M, Wagner M. Age of major depression onset, depressive symptoms, and risk for subsequent dementia: results of the German Study on Ageing, Cognition, and Dementia in Primary Care Patients (AgeCoDe) Psychological Medicine. 2013;43:1597–1610. doi: 10.1017/S0033291712002449. [DOI] [PubMed] [Google Scholar]
  21. Jorm AF. History of depression as a risk factor for dementia: an updated review. Australian and New Zealand Journal of Psychiatry. 2001;35:776–781. doi: 10.1046/j.1440-1614.2001.00967.x. [DOI] [PubMed] [Google Scholar]
  22. Kaplan EF, Goodglass H, Weintraub S. The Boston Naming Test. 2. Philadelphia, Pa: Lea & Febiger; 1983. [Google Scholar]
  23. Kohout FJ, Berkman LF, Evans DA, Cornoni-Huntley J. Two shorter forms of the CES-D depression symptoms index. Journal of Aging and Health. 1993;5:79–193. doi: 10.1177/089826439300500202. [DOI] [PubMed] [Google Scholar]
  24. Koolschijn PCMP, van Haren N, EM, Lensvelt-Mulders GJLM, Hulshoff Pol HE, Kahn RS. Brain volume abnormalities in major depressive disorder: a meta-analysis of magnetic resonance imaging studies. Human Brain Mapping. 2009;30:3719–3735. doi: 10.1002/hbm.20801. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Laird N, Ware J. Random effects models for longitudinal data. Biometrics. 1982;38:963–974. [PubMed] [Google Scholar]
  26. Lenoir H, Dufouil C, Auriacombe S, Lacombe JM, Dartigues JF, Ritchie K, Tzourio C. Depression history, depressive symptoms, and incident dementia: the 3C Study. Journal of Alzheimer’s Disease. 2011;26:27–38. doi: 10.3233/JAD-2011-101614. [DOI] [PubMed] [Google Scholar]
  27. Li G, Wang LY, Shofer JB, Thompson ML, Peskind ER, McCormick W, Larson EB. Temporal relationship between depression and dementia: findings from a large community-based 15 year follow-up study. Archives of General Psychiatry. 2011;68:970–977. doi: 10.1001/archgenpsychiatry.2011.86. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan E. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS/ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s disease. Neurology. 1984;34:939–944. doi: 10.1212/wnl.34.7.939. [DOI] [PubMed] [Google Scholar]
  29. Medi-Span, Inc. Master drug database documentation manual. Indianapolis, IN: Medi-Span, Inc; 1995. [Google Scholar]
  30. Ownby RL, Crocco E, Acevedo A, John V, Loewenstein D. Depression and risk for Alzheimer disease: systematic review, meta-analysis, and meta-regression analysis. Archives of General Psychiatry. 2006;63:530–538. doi: 10.1001/archpsyc.63.5.530. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Panza F, Frisardi V, Capurso C, D’Introno A, Colacicco AM, Imbimbo BP, Solfrizzi Y. Late-life depression, mild cognitive impairment, and dementia: possible continuum? American Journal of Geriatric Psychiatry. 2010;18:98–116. doi: 10.1097/JGP.0b013e3181b0fa13. [DOI] [PubMed] [Google Scholar]
  32. Radloff LS. The CES-D scale: a self-report depression scale for research in the general population. Applied Psychological Measurement. 1977;1:385–401. [Google Scholar]
  33. Rapp MA, Schnaider-Beeri M, Grossman HT, Sano M, Perl DP, Purohit DP, Haroutunian V. Increased hippocampal plaques and tangles in patients with Alzheimer disease with a lifetime history of major depression. Archives of General Psychiatry. 2006;63:161–167. doi: 10.1001/archpsyc.63.2.161. [DOI] [PubMed] [Google Scholar]
  34. Rapp MA, Schnaider-Beeri M, Purohit DP, Perl DP, Haroutunian V, Sano M. Increased neurofibrillary tangles in patients with Alzheimer disease and comorbid depression. American Journal of Geriatric Psychiatry. 2008;16:168–174. doi: 10.1097/JGP.0b013e31816029ec. [DOI] [PubMed] [Google Scholar]
  35. Raven JC, Court JH, Raven J. Manual for Raven’s progressive matrices and vocabulary: Standard Progressive Matrices. Oxford, England: Oxford Psychologists Press; 1992. [Google Scholar]
  36. Robins LN, Helzer JE, Croughan J. National Institute of Mental Health Diagnostic Interview Schedule: history, characteristics, validity. Archives of General Psychiatry. 1981;38:381–389. doi: 10.1001/archpsyc.1981.01780290015001. [DOI] [PubMed] [Google Scholar]
  37. Royall DR, Palmer R. Alzheimer’s disease pathology does not mediate the association between depressive symptoms and subsequent cognitive decline. Alzheimer’s & Dementia. 2013;9:318–325. doi: 10.1016/j.jalz.2011.11.009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Saczynski JS, Beiser A, Seshadri S, Auerbach S, Wolf PA, Au R. Depressive symptoms and risk of dementia: the Framingham Heart Study. Neurology. 2010;75:35–41. doi: 10.1212/WNL.0b013e3181e62138. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Schneider JA, Li JL, Li Y, Wilson RS, Kordower JH, Bennett DA. Neurofibrillary tangles in the substantia nigra are related to gait impairment in older persons. Annals of Neurology. 2006;59:166–173. doi: 10.1002/ana.20723. [DOI] [PubMed] [Google Scholar]
  40. Sexton CE, Allan CL, Masurier ML, McDermott LM, Kalu UG, Hermann LL, Ebmeier KP. Magnetic resonance imaging in late-life depression: multimodal examination of network disruption. Archives of General Psychiatry. 2012;69:680–689. doi: 10.1001/archgenpsychiatry.2011.1862. [DOI] [PubMed] [Google Scholar]
  41. Sexton CE, Mackay CE, Ebmeier KP. A systematic review of diffusion tensor imaging studies in affective disorders. Biological Psychiatry. 2009;66:814–823. doi: 10.1016/j.biopsych.2009.05.024. [DOI] [PubMed] [Google Scholar]
  42. Shakesby AC, Anwyl R, Rowan MJ. Overcoming the effects of stress on synaptic plasticity in the intact hippocampus: rapid actions of serotonergic and antidepressant agents. Journal of Neuroscience. 2002;22:3638–3644. doi: 10.1523/JNEUROSCI.22-09-03638.2002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Smith A. Symbol Digit Modalities Test manual-revised. Los Angeles: Western Psychological Services; 1982. [Google Scholar]
  44. Soetanto A, Wilson RS, Talbot K, Un A, Schneider JA, Sobiesk M, Arnold SE. Anxiety and depression are associated with MAP2 and synaptopodin immunolabeled dendrite and spine densities in hippocampal CA3 of older humans. Archives of General Psychiatry. 2010;67:448–457. doi: 10.1001/archgenpsychiatry.2010.48. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Syed A, Chatfield M, Matthews F, Harrison P, Brayne C, Esiri MM. Depression in the elderly: pathological study of raphe and locus ceruleus. Neuropathology and Applied Neurobiology. 2005;31:405–413. doi: 10.1111/j.1365-2990.2005.00662.x. [DOI] [PubMed] [Google Scholar]
  46. Tsopelas C, Stewart R, Savva GM, Brayne C, Ince P, Thomas A, Matthews FE Medical Research Council Cognitive Function and Ageing Study. Neuropathological correlates of late-life depression in older people. British Journal Psychiatry. 2011;198:109–114. doi: 10.1192/bjp.bp.110.078816. [DOI] [PubMed] [Google Scholar]
  47. Wechsler D. Wechsler Memory Scale-Revised manual. San Antonio, TX: Psychological Corporation; 1987. [Google Scholar]
  48. Welsh KA, Butters N, Mohs RC, Beekly D, Edland S, Fillenbaum G, Heyman A. The Consortium to Establish a Registry for Alzheimer’s Disease (CERAD), part V: a normative study of the neuropsychological battery. Neurology. 1994;44:609–614. doi: 10.1212/wnl.44.4.609. [DOI] [PubMed] [Google Scholar]
  49. Wilson RS, Barnes LL, Mendes de Leon CF, Aggarwal NT, Schneider JA, Bach J, Bennett DA. Depressive symptoms, cognitive decline, and risk of AD in older persons. Neurology. 2002;59:364–370. doi: 10.1212/wnl.59.3.364. [DOI] [PubMed] [Google Scholar]
  50. Wilson RS, Beckett LA, Barnes LL, Schneider JA, Bach J, Evans DA, Bennett DA. Individual differences in rates of change in cognitive abilities of older persons. Psychology and Aging. 2002;17:179–193. [PubMed] [Google Scholar]
  51. Wilson RS, Bienias JL, Evans DA, Bennett DA. Religious Orders Study: Overview and change in cognitive and motor speed. Aging Neuropsychology Cognition. 2004;11:280–303. [Google Scholar]
  52. Wilson RS, Boyle PA, Yang J, James BD, Bennett DA. Early life instruction in foreign language and music and incidence of mild cognitive impairment. Neuropsychology. 2014 Aug 11; doi: 10.1037/neu0000129. Epub ahead of print NIHMS616583. [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Wilson RS, Capuano AW, Boyle PA, Hoganson G, Hizel LP, Shah RC, Bennett DA. Clinical-pathologic study of depressive symptoms and cognitive decline in old age. Neurology. 2014;83:702–709. doi: 10.1212/WNL.0000000000000715. [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Wilson RS, Nag S, Boyle PA, Hizel LP, Yu L, Buchman AS, Bennett DA. Brainstem aminergic nuclei and late life depressive symptoms. Journal of the American Medical Association Psychiatry. 2013;70:1320–1328. doi: 10.1001/jamapsychiatry.2013.2224. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Wilson RS, Schneider JA, Bienias JL, Arnold SE, Evans DA, Bennett DA. Depressive symptoms, clinical AD, and cortical plaques and tangles in older persons. Neurology. 2003;61:1102–1107. doi: 10.1212/01.wnl.0000092914.04345.97. [DOI] [PubMed] [Google Scholar]
  56. Wilson RS, Yu L, Schneider JA, Arnold SE, Buchman AS, Bennett DA. Lewy bodies and olfactory dysfunction in old age. Chemical Senses. 2011;36:367–373. doi: 10.1093/chemse/bjq139. [DOI] [PMC free article] [PubMed] [Google Scholar]
  57. Wilson RS, Yu L, Trojanowski JQ, Chen EY, Boyle PA, Bennett DA, Schneider JA. TDP-43 pathology, cognitive decline, and dementia in old age. Journal of the American Medical Association Neurology. 2013;70:1418–1424. doi: 10.1001/jamaneurol.2013.3961. [DOI] [PMC free article] [PubMed] [Google Scholar]

RESOURCES