Caregiving-Related Depression Increases Neuroinflammation in Spousal Caregivers to Individuals With Cognitive Impairment: A Longitudinal Study (original) (raw)

So Yeon Jeon, MD, PhD ,

Department of Psychiatry, Chungnam National University Hospital

, Daejeon,

Republic of Korea

Department of Psychiatry, College of Medicine, Chungnam National University

, Daejeon,

Republic of Korea

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Hee Won Yang, MD ,

Department of Psychiatry, Chungnam National University Hospital

, Daejeon,

Republic of Korea

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Bo Ran Son, BA ,

Brain Research Institute, College of Medicine, Chungnam National University

, Daejeon,

Republic of Korea

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Jimin Baek, BA ,

Department of Psychiatry, Chungnam National University Hospital

, Daejeon,

Republic of Korea

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Jeong Lan Kim, MD, PhD

Department of Psychiatry, Chungnam National University Hospital

, Daejeon,

Republic of Korea

Department of Psychiatry, College of Medicine, Chungnam National University

, Daejeon,

Republic of Korea

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Editorial decision:

11 September 2024

Published:

19 September 2024

Corrected and typeset:

03 December 2024

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So Yeon Jeon, Hee Won Yang, Bo Ran Son, Jimin Baek, Jeong Lan Kim, Caregiving-Related Depression Increases Neuroinflammation in Spousal Caregivers to Individuals With Cognitive Impairment: A Longitudinal Study, The Journals of Gerontology: Series A, Volume 79, Issue 11, November 2024, glae235, https://doi.org/10.1093/gerona/glae235
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Abstract

Background

The caregiving burden of the spousal caregivers (SCGs) to individuals with cognitive impairment poses public health challenges with adverse psychosocial and physiological effects. However, few studies have investigated the neurobiological impact of caregiving, particularly through the investigation of neuroinflammation and neurodegeneration.

Methods

Using data from a longitudinal cohort at Chungnam National University Hospital, the relationship between caregiving burden, neuroinflammation, and neurodegeneration was examined in 38 older adult couples over a 16-month period. Caregiving burden was assessed through a multifaceted approach. For factors related to the care recipient, we assessed cognitive function and neuropsychiatric symptoms. Factors regarding the SCGs included the measurement of perceived depression. Glial fibrillary acidic protein (GFAP) was used as a plasma biomarker for neuroinflammation and neurofilament light chain (NfL) for neurodegeneration. Regression analyses were adjusted for age, sex, apolipoprotein E status, follow-up interval, vascular risk factors, and physical activity.

Results

Changes in depression among SCGs were significantly correlated with increased GFAP levels (p = .003), indicating that greater depressive symptoms during caregiving are associated with increased neuroinflammation. In contrast, no significant correlations were found between changes in cognitive function or neuropsychiatric symptoms in care recipients and the plasma biomarker levels of SCGs. Additionally, there was no significant association between changes in depression and NfL levels in SCGs.

Conclusions

The psychological stress experienced by SCGs while caring for partners with cognitive impairment actively contributes to neuroinflammation, a well-known risk factor for various diseases. This study emphasizes the need to address psychological stress experienced by older adult caregivers.

Caregiving for older adults with cognitive decline, which has been identified as a prototypic chronic stressor (1), constitutes a significant public health challenge with well-documented adverse psychosocial and physiological ramifications (2–5). The clinical manifestations experienced by caregivers include depressive symptoms (6–8), social isolation (9), and decreased physical activity (10). These manifestations not only compromise the caregiver’s quality of life but also correlate with increased risks of cognitive impairment (7,11–14) and cardiovascular diseases (11,12,15) in caregivers. These adverse impacts are especially harmful to spousal caregivers (SCGs), as they are typically older adults simultaneously undergoing a natural decline in their immune system (16). Longitudinal analyses have demonstrated that compared with their non-caregiving counterparts, SCGs face a 63% increased relative risk of all-cause mortality (17), implying profound health implications associated with caregiving for SCGs.

The link between caregiving burden and adverse health outcomes is partly attributed to the inflammatory process, as evidenced by elevated levels of C-reactive protein (CRP) and cytokines such as interleukin-6, and tumor necrosis factor-alpha, along with reduced antibody levels (3,18–20). The overproduction of these cytokines and inflammatory markers is associated with age-related health problems, including cardiovascular disease (21) and all-cause dementia (22,23). In a 2-year longitudinal study, an increased CRP levels were linked to the functional decline of caregivers to individuals with dementia but not to non-caregivers (20). Existing evidence further supports the connection between chronic psychological stress and neuroinflammatory and neurodegenerative processes (24). Moreover, a longitudinal study with a 14-year follow-up demonstrated that SCGs have an increased risk of all-cause dementia, specifically with a 1.6-fold increase (13). Another longitudinal study reported that, even after the death of the care recipient, SCGs to individuals with dementia showed consistently accelerated cognitive decline compared with SCGs to individuals without dementia (14). Despite these findings, the direct impact of caregiving burden on neuronal damage, specifically neuroinflammation and neurodegeneration, remains underexplored. Recent evidence strongly suggests that the glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are indicators of ongoing neuroinflammation and neurodegeneration (25,26). GFAP, which is indicative of astrocytic activation (27), and NfL (28), which is a marker of axonal damage, both provide valuable insights into the pathological processes underlying neurological disorders. Notably, recent large-scale longitudinal studies have reported that elevated plasma GFAP and NfL levels are strongly correlated with an increased risk of all-cause dementia (25,29–32). This suggests that caregiving-related stress could be linked to neuroinflammation and neurodegeneration. However, the relationship between caregiving burden and these plasma biomarkers in SCGs to individuals with cognitive impairment is yet to be determined.

Therefore, this study investigated the relationship between the caregiving burden in caregivers to individuals with cognitive impairment and plasma levels of GFAP and NfL in SCGs. The caregiving burden was evaluated using a multifaceted approach to investigate the factors influencing the neurobiological impact among SCGs. We assessed perceived depression among SCGs for factors relating to the SCGs. Additionally, given the significant correlation between the severity of cognitive impairment and neuropsychiatric problems in care recipients and the caregiving burden (33,34), we assessed cognitive function and neuropsychiatric symptoms for factors related to the care recipient.

Method

Study Design and Participants

This study was part of a longitudinal cohort study focusing on older adult couples engaged in spousal caregiving at the Chungnam National University Geriatric Psychiatry Clinic. Enrollment in the cohort began in May 2020, and annual assessments were conducted. The analysis included older adult couples registered up to May 2023 and selected those who had completed 2 rounds of evaluation. The detailed methods are described in our previous study (35). At every assessment, the measurement of cognitive function and neuropsychiatric symptoms of the care recipients was performed along with clinical evaluations of the SCGs, which included assessments of depression and cognitive function and blood tests. To measure the cognitive functions of both care recipients and SCGs, we utilized the Korean version of the Mini-Mental State Examination (MMSE) (36). This study analyzed the data from 38 couples who completed all baseline and follow-up evaluations. Of the SCGs, 23 cared for individuals with dementia and 15 cared for those without dementia. The inclusion criteria for the SCGs were as follows: (1) age between 55 and 90 years, (2) serving as the primary caregiver for a spouse, (3) ability to live independently, (4) not diagnosed with dementia, and (5) not diagnosed with major depressive disorder at enrollment. Dementia was diagnosed based on the DSM-IV criteria established by the American Psychiatric Association in 1994. This study was approved by the Ethical Review Committee of Chungnam National University Hospital (approval number 2020-05-002). Informed consent was obtained from all participants prior to their involvement.

Clinical Assessments for Caregiving Burden

During the study, the SCGs underwent detailed clinical evaluations conducted annually by a skilled neuropsychological technician and a research nurse. The caregiving burden was evaluated based not only on the perceived depression of the SCGs but also on the cognition and neuropsychiatric symptoms of the care recipient.

Depressive symptoms in the SCGs were measured using the Korean version of the Geriatric Depression Scale (GDS) (37). GDS scores of 16 or above are considered to be an indication for major depression screening (37). We evaluated the severity of cognitive impairment in care recipients assessed by the MMSE and neuropsychiatric symptoms, which are established factors associated with caregiving burden in SCGs (4,33).

To assess neuropsychiatric symptoms in care recipients, we used the 12-item neuropsychiatric inventory (NPI) (38). This inventory spans a range of neuropsychiatric symptoms across 12 domains: delusions, hallucinations, agitation (or aggression), depression/dysphoria, anxiety, elation (or euphoria), apathy (or indifference), disinhibition, irritability (or lability), aberrant motor behavior, nighttime disturbances, and changes in appetite. Upon endorsement of any symptoms, SCGs were prompted to evaluate both the frequency and intensity of the symptoms within each domain. These evaluations were used to calculate a score for each domain (with a maximum of 12 points). Any domain not endorsed by a caregiver was assigned a score of 0. The sum of the domain scores yielded the total NPI score for each care recipient, with a maximum score of 144 points.

Assessment for Covariates

Comorbid vascular risk factors in SCGs, including diabetes mellitus, hyperlipidemia, hypertension, coronary artery disease, transient ischemic attack, and stroke were assessed based on ongoing pharmacological treatments or medical histories. This assessment was conducted through comprehensive interviews and corroborated by a trained nurse, forming the basis for the Vascular Risk Score (VRS), which represents the cumulative presence of vascular risk factors as a percentage (39). Body mass index (BMI) was calculated by dividing the participants’ weight in kilograms by the square of their height in meters, with measurements taken and calculated by research nurses. The Korean version of the International Physical Activity Questionnaire (IPAQ) was used to assess physical activity levels in participants (40). This questionnaire comprises 7 items that record the total time (in minutes) spent on moderate to vigorous physical activities, including walking and periods of inactivity, over the past 7 days. Responses were converted into metabolic equivalent task (MET) minutes per week (MET-min/week) following the IPAQ scoring guidelines (41). An average MET score was calculated for each type of activity using the following MET values: walking = 3.3 METs, moderate physical activity = 4.0 METs, and vigorous physical activity = 8.0 METs. The overall physical activity level was determined by summing the MET-min/week values from walking, moderate activity, and vigorous activity.

Blood Sampling and Laboratory Assessments

Genomic DNA was isolated from whole-blood samples, and apolipoprotein E (APOE) genotyping was conducted as previously described (42). Presence of the APOE ε4 allele (APOE4) was confirmed if at least one ε4 allele was identified. Levels of plasma GFAP and NfL were measured through the Single Molecule Array (SIMOA) method using the Simoa Neurology 2-Plex A assay kit (Quanterix, Billerica, MA) and DNA Link (DNA Link Inc., Seoul, Republic of Korea) to carry out the immunoassay procedures. In a standard experimental setup, both samples and controls were allocated to 96-well Quanterix plates for duplicate analysis, including a 4× dilution performed by the device, following the manufacturer’s instructions. The assay employed a SIMOA HD-X machine (Quanterix) for a 2-step immunoassay where target antibodies on paramagnetic beads were mixed with the sample and a biotinylated detection antibody in a single step. This allows the target molecules in the sample to be simultaneously captured by the bead-coated antibodies and detected using the biotinylated antibody. The minimum detectable limit was 0.241 pg/mL for NfL and 0.467 pg/mL for GFAP, as determined analytically. Data acquisition was performed using a SIMOA HD-X analyzer operated with SIMOA HD-X software (Quanterix), version 3.1.2011.30002.

Statistical Analysis

We compared SCGs to individuals with and without dementia to assess potential differences in caregiving burden and its impact on plasma biomarkers. This comparison aimed to explore whether clinically relevant differences exist in SCG variables based on the diagnostic status of the care recipient.

And, we conducted linear regression analyses to explore the association between the caregiving burden and the levels of GFAP and NfL among SCGs at baseline. In Model 1, the age and sex of the SCGs were adjusted as covariates. Model 2 expanded upon Model 1 by including APOE4 status, VRS and IPAQ scores as additional covariates, along with BMI, for GFAP analysis. In the longitudinal analysis, changes between baseline and follow-up assessments were quantified by calculating the differences in variables, followed by linear regression analyses to further examine these relationships. This involved analyzing the connection between alterations in the GDS scores of SCGs and the MMSE (or NPI) scores of care recipients and the corresponding changes in GFAP and NfL levels. Moreover, the longitudinal analyses were adjusted for the interval between assessments and the baseline values of the GDS scores of SCGs and MMSE (or NPI) scores of care recipients. Bonferroni correction was applied for multiple comparisons using p < .05/2 (=number for each dependent variable [GFAP and NfL]).

To explore the moderating effects of sex, APOE4 status, and clinical diagnosis on caregiving burden and plasma biomarkers, variables that showed associations with plasma biomarkers with a statistical significance of p < .025 were selected for further analyses. Multiple linear regression analyses were conducted after controlling for the age of the SCGs, MMSE scores of the care recipients, APOE4 status, VRS, IPAQ scores and other selected factors. These analyses included interaction terms (eg, the MMSE score of the care recipient multiplied by sex) as independent variables, with the chosen factor serving as the dependent variable.

In an exploratory manner, we analyzed the relationship between plasma biomarkers and MMSE scores in SCGs, both cross-sectionally and longitudinally. Initially, comparisons were made between baseline plasma biomarker levels and MMSE scores of the SCGs. We explored whether baseline plasma biomarker levels and changes in these biomarkers were associated with changes in the MMSE scores of the SCGs. Given the exploratory nature of this analysis, adjustments were made solely for age, sex, and APOE4 status, including the interval between assessments in the longitudinal analyses. All analyses were performed using SPSS 21 software (SPSS Inc., Chicago, IL), and p values < 0.05 (2-sided) were considered to indicate statistical significance.

Results

Characteristics of the Study Population

Table 1 shows the demographic and clinical characteristics of the study population at baseline. In the whole sample, the mean baseline age was 72.9 years (standard deviation, 6.1 years). Age was significantly associated with NfL (r = 0.448, p = .005), but showed trend level association with GFAP (r = 0.297, p = .074). Among care recipients, 23 (60.5%) were diagnosed with dementia. The SCGs to individuals with dementia were slightly older than those to individuals without dementia, although this difference was not significant. The BMI of SCGs to individuals with dementia was lower than that of SCGs to individuals without dementia. However, no significant differences were observed between the 2 groups in terms of sex, educational level, or type of care provided (Table 1).

Table 1.

Characteristics of Study Population

Notes: Data are presented as mean ± SD or n (%). APOE = apolipoprotein E; CAD = coronary artery disease; CDR = Clinical Dementia Rating; GDS = Geriatric Depression Scale; GFAP = glial fibrillary acidic protein; IPAQ = International Physical Activity Questionnaire; MET = metabolic equivalent task; MMSE = Mini-Mental State Examination; NfL = neurofilament light chain; NPI = Neuropsychiatric Inventory; SCG = spousal caregiver; SD = standard deviation; TIA = transient ischemic attack; VRS = vascular risk factor score.

Table 1.

Characteristics of Study Population

Notes: Data are presented as mean ± SD or n (%). APOE = apolipoprotein E; CAD = coronary artery disease; CDR = Clinical Dementia Rating; GDS = Geriatric Depression Scale; GFAP = glial fibrillary acidic protein; IPAQ = International Physical Activity Questionnaire; MET = metabolic equivalent task; MMSE = Mini-Mental State Examination; NfL = neurofilament light chain; NPI = Neuropsychiatric Inventory; SCG = spousal caregiver; SD = standard deviation; TIA = transient ischemic attack; VRS = vascular risk factor score.

Baseline Association of Caregiving Burden With GFAP and NfL Levels Among SCGs

At baseline, no significant correlation was found between the GDS scores and levels of GFAP (β = 0.076, p = .687) and NfL (β = −0.025, p = .612) among SCGs. Similarly, the MMSE or NPI scores of care recipients showed no association with GFAP (β = 0.261, p = .170 for MMSE scores; β = −0.073, p = .696 for NPI scores) and NfL levels (β = 0.006, p = .973 for MMSE scores; β = −.059, p = .727 for NPI scores) in SCGs (Table 2). Further, no significant associations were found between the NPI subdomains and GFAP and NfL levels (Supplementary Table 1).

Table 2.

Baseline Association of Caregiving Burden With GFAP and NfL Levels Among SCGs

Notes: APOE = apolipoprotein E; BMI = body mass index; GDS; Geriatric Depression Scale; GFAP; glial fibrillary acidic protein; IPAQ = International Physical Activity Questionnaire; MMSE = Mini-Mental State Examination; NfL; neurofilament light chain; NPI = neuropsychiatric inventory; SCG = spousal caregiver; VRS = vascular risk factor score.

*Model 1: Adjusted for age and sex of SCGs.

†Model 2: Adjusted for age, sex, APOE4 postivity, VRS, IPAQ scores of SCGs (and BMI for GFAP analyses).

Table 2.

Baseline Association of Caregiving Burden With GFAP and NfL Levels Among SCGs

Notes: APOE = apolipoprotein E; BMI = body mass index; GDS; Geriatric Depression Scale; GFAP; glial fibrillary acidic protein; IPAQ = International Physical Activity Questionnaire; MMSE = Mini-Mental State Examination; NfL; neurofilament light chain; NPI = neuropsychiatric inventory; SCG = spousal caregiver; VRS = vascular risk factor score.

*Model 1: Adjusted for age and sex of SCGs.

†Model 2: Adjusted for age, sex, APOE4 postivity, VRS, IPAQ scores of SCGs (and BMI for GFAP analyses).

Longitudinal Association of Caregiving Burden With GFAP and NfL Levels Among SCGs

Changes in GDS among SCGs were significantly correlated with changes in GFAP levels, a relationship that persisted even after adjusting for VRS, BMI, IPAQ scores, APOE4 status, and baseline GDS (β = 0.763, p = .003; Table 3 and Figure 1). This indicates that an increase in depressive symptoms among the SCGs during the evaluation period was associated with a corresponding increase in GFAP levels. No significant correlation was observed between changes in GDS and NfL levels (β = 0.392, p = .130). Changes in MMSE or NPI scores for care recipients did not show a significant relationship with changes in GFAP (β = 0.087, p = .705 for MMSE scores; β = −0.188, p = .225 for NPI score) or NfL (β = 0.094, p = .659 for MMSE scores; β = −0.104, p = .242 for NPI score) levels in SCGs (Table 3). An exploratory analysis of the NPI subdomains revealed that greater changes in hallucination scores of care recipients were associated with an increase in NfL levels among SCGs (β = 0.431, p = .032). However, after applying the Bonferroni correction, the result was not significant (Supplementary Table 2).

Table 3.

Longitudinal Association of Caregiving Burden With GFAP and NfL Levels Among SCGs

Notes: GDS = Geriatric Depression Scale; GFAP = glial fibrillary acidic protein; MMSE = Mini-Mental State Examination; NfL = neurofilament light chain; NPI = neuropsychiatric inventory; SCG = spousal caregiver.

*Model 1: Adjusted for age and sex of SCGs.

†Model 2: Adjusted for age, sex, APOE4 positivity, VRS, interval, IPAQ scores, and baseline MMSE of care recipients or baseline GDS of SCGs (and BMI for GFAP analyses).

Table 3.

Longitudinal Association of Caregiving Burden With GFAP and NfL Levels Among SCGs

Notes: GDS = Geriatric Depression Scale; GFAP = glial fibrillary acidic protein; MMSE = Mini-Mental State Examination; NfL = neurofilament light chain; NPI = neuropsychiatric inventory; SCG = spousal caregiver.

*Model 1: Adjusted for age and sex of SCGs.

†Model 2: Adjusted for age, sex, APOE4 positivity, VRS, interval, IPAQ scores, and baseline MMSE of care recipients or baseline GDS of SCGs (and BMI for GFAP analyses).

Figure 1.

Longitudinal association of changes in depression and changes in (A) GFAP and (B) NfL among SCGs. Multiple linear regression analyses were performed after controlling for age, sex, APOE4 status, VRS, IPAQ scores, follow-up interval, and baseline GDS of the SCGs (and BMI for GFAP analyses). APOE = apolipoprotein E; BMI = body mass index; GDS = Geriatric Depression Scale; GFAP = glial fibrillary acidic protein; IPAQ = International Physical Activity Questionnaire; MMSE = Mini-Mental State Examination; NfL, neurofilament light chain; SCG = spousal caregiver; VRS = vascular risk factor score.

Interaction Effect of Sex, APOE4 Status, and Clinical Diagnosis of Care Recipients

We also tested whether the influence of changes in depression on the changes in GFAP levels differed according to sex, APOE4 status, or clinical diagnosis of the care recipient. However, none of the variables showed significant interaction effects (Table 4).

Table 4.

Moderating Effects of Sex, APOE4 Positivity of SCGs, and Clinical Diagnosis of Care Recipients on Associations Between Changes in GDS and GFAP Among SCGs

Notes: The multiple logistic regression model included Δ GDS, sex (or APOE4 or clinical diagnosis), and the interaction between Δ GDS and sex (or APOE4 or clinical diagnosis), all treated as independent variables. Age, sex, APOE4 positivity, VRS, IPAQ scores, follow-up intervals, BMI, and baseline GDS were treated as covariates when appropriate, and annualized △ GFAP was treated as the dependent variable. APOE = apolipoprotein E; BMI = body mass index; GDS = Geriatric Depression Scale; GFAP = glial fibrillary acidic protein; IPAQ = International Physical Activity Questionnaire; SCG = spousal caregiver.

*Cognitively normal versus mild cognitive impairment.

Table 4.

Moderating Effects of Sex, APOE4 Positivity of SCGs, and Clinical Diagnosis of Care Recipients on Associations Between Changes in GDS and GFAP Among SCGs

Notes: The multiple logistic regression model included Δ GDS, sex (or APOE4 or clinical diagnosis), and the interaction between Δ GDS and sex (or APOE4 or clinical diagnosis), all treated as independent variables. Age, sex, APOE4 positivity, VRS, IPAQ scores, follow-up intervals, BMI, and baseline GDS were treated as covariates when appropriate, and annualized △ GFAP was treated as the dependent variable. APOE = apolipoprotein E; BMI = body mass index; GDS = Geriatric Depression Scale; GFAP = glial fibrillary acidic protein; IPAQ = International Physical Activity Questionnaire; SCG = spousal caregiver.

*Cognitively normal versus mild cognitive impairment.

Association of Plasma GFAP and NfL Levels With Cognition in SCGs

The association between plasma biomarkers and the cognitive function was also examined among SCGs. No significant relationship was found between baseline levels of GFAP (β = 0.305, p = .070) and NfL (β = −0.254, p = .167) and MMSE scores in SCGs. Similarly, there was no significant with changes in MMSE scores (β = −0.136, p = .455 for GFAP and β = 0.204, p = .310 for NfL). Furthermore, longitudinal analyses revealed that changes in GFAP levels (β = 0.110, p = .546) and NfL levels (β = −0.138, p = .418) were not significantly related to changes in MMSE scores (Supplementary Table 3).

Discussion

In this longitudinal study, we aimed to explore the impact of caregiving burden on neuroinflammation and neurodegeneration among SCGs to individuals with cognitive decline. The results showed a significant correlation between increased depressive symptoms in SCGs and elevated levels of GFAP, a biomarker of neuroinflammation. These results provide novel insights into the influence of caregiving to patients with cognitive decline on the neurobiological alterations of the SCGs, specifically regarding GFAP and NfL levels. Our fingdings highlight potential neurobiological mechanisms underlying the health risks faced by SCGs of older adults with cognitive impairment.

Previous studies have primarily focused on the psychological and social consequences of caregiving to patients with cognitive impairment (1,3,6) and documented increased risks of dementia (13) and cardiovascular disease (11,12,15) among caregivers. Our study adds a neurobiological evidence by demonstrating a correlation between increased depressive symptoms and GFAP levels, even after adjusting for VRS, BMI, IPAQ scores, and APOE4 status, which could affect GFAP levels. This supports the hypothesis that neuroinflammation mediates the relationship between caregiving-related stress and its health consequences, aligning with prior evidence linking depressive symptoms to neuroinflammatory responses (43–46).

Research has shown increased GFAP levels in the cerebrospinal fluid (46) and blood (44) of patients with depression, indicating astrocytic activation (27), which is a feature of depression (47). Astroglial proteins, such as GFAP, have already been shown to be candidate markers for neurodegenerative diseases (25,48). Recent large-scale longitudinal studies have shown that elevated GFAP levels are robust prognostic markers for all-cause dementia (25,29–31). Supporting our findings, the study by Vitaliano et al. (20) demonstrated that increased CRP levels over a 2-year period were associated with functional decline in caregivers to individuals with dementia, compared to demographically matched non-caregivers even after adjusting for baseline functional impairment and psychological distress. These findings suggest that caregiving and associated inflammation play key roles in the accelerated functional decline observed in caregivers. While Vitaliano et al.’s work focuses on systemic inflammation (20), our study extends this to neuroinflammation, as reflected in elevated GFAP levels. Additionally, previous research has demonstrated that compared with controls, the SCGs to individuals with dementia have a 1.6-fold increased risk of dementia incidence over a 14-year longitudinal follow-up period (13). Integrating these previous findings with the results of our study suggests that neuroinflammation, potentially induced by depression, plays a significant role in mediating adverse functional and neurocognitive outcomes in SCGs.

Specific normative data for GFAP and NfL levels in the Korean population have yet to be established. However, the baseline levels in our participants (188.2 ± 76.0 pg/mL for GFAP and 21.6 ± 12.3 pg/mL for NfL) were within the normative ranges reported for a similarly aged Canadian cohort (40.7–228 pg/mL for GFAP and 8.1–47.1 pg/mL for NfL in individuals aged 60–80) (49). Given the emerging evidence linking GFAP and NfL levels to dementia prediction in healthy older adults (25,26), the increasing depressive symptoms reported by SCGs to spouses without dementia need close attention. This observation suggests the potential for early detection and intervention for dementia, emphasizing the critical role of monitoring depressive symptoms in SCGs as indicators of underlying neuroinflammation and an increased risk of neurodegeneration.

The finding that NfL levels were not correlated with GDS scores at baseline, as well as the lack of an association between their longitudinal changes, aligns with previous findings (44,50) that indicated no significant differences in NfL levels between patients with depression and healthy controls. This suggests a more direct involvement of caregiving-related stress in neuroinflammatory processes than in neurodegenerative changes, as indicated by NfL levels. In our study, changes in GDS scores were not associated with changes in NfL levels; however, a positive correlation was observed with follow-up NfL levels (data not shown). Therefore, further longitudinal studies are needed to determine whether the neuroinflammation caused by stress affects neurodegeneration in caregivers.

There was no significant association between the baseline and longitudinal changes in the MMSE scores of SCGs and plasma biomarkers. One possible explanation for this finding is that the SCGs in our cohort, who were capable of accompanying their spouses with cognitive decline to a university hospital for treatment, may already possess resilience. Additionally, the follow-up period of 16 months may have been too short to observe significant relationships with longitudinal MMSE changes. Previous studies that have identified GFAP and NfL levels as prognostic factors for dementia typically involved much longer follow-up durations, ranging from 4 to 14 years (25,26,29).

The results of our study indicated no relationship between the degree of cognitive impairment or neuropsychiatric symptoms in care recipients and plasma biomarkers, either cross-sectionally or longitudinally. This suggests that depression experienced by SCGs may have a more significant impact on neuroinflammation than the severity of the care recipient’s cognitive impairment or neuropsychiatric symptoms. Moreover, our analysis did not reveal significant interaction effects between changes in depressive symptoms and GFAP or NfL levels across sex, APOE4 status, or clinical diagnosis of care recipients. This finding indicates that caregiving-induced psychological distress is a pervasive risk factor for neuroinflammation, independent of sex, APOE4 status, or the severity of cognitive impairment in care recipients.

These findings have significant clinical implications. SCGs are often referred to as the “invisible second patient,” as they are known to have a higher risk of not only dementia but also all-cause mortality (17). GFAP is a strong prognostic blood-based biomarker of the incidence of dementia in older adults (25,29,32). The significant association between depressive symptoms and increased GFAP levels emphasizes the need for clinicians to actively monitor SCGs for signs of depression. Early identification and intervention can mitigate the risk of cognitive impairment, emphasizing the importance of supporting mental health and well-being in SCGs.

Despite the strengths of our study, it has several limitations. First, the recruitment of participants from a tertiary university hospital, all of whom were healthy enough to provide care to spouses with cognitive decline, introduced a potential selection bias. This bias may skew the results toward the null hypothesis, suggesting that the impact of depression on neuroinflammation may be underestimated in SCGs. Second, the recruitment period coincided with the COVID-19 pandemic, which necessitates caution when interpreting these results. In Korea, strict isolation measures were implemented early on for patients with confirmed COVID-19 and their contacts. During the recruitment period, individuals with respiratory symptoms or a temperature above 37.5°C were restricted from entering hospitals. Therefore, the impact of infection on participant evaluation is believed to have been minimal. Third, our study did not use the zarit burden interview, a commonly used measure of caregiving burden. Instead, we assessed cognitive decline and neuropsychiatric symptoms of dementia in care recipients and perceived stress levels in caregivers. This approach provided a more comprehensive view of the factors influencing neuroinflammation and neurodegeneration in SCGs. By considering multiple aspects of caregiving and using measures routinely assessed in clinical settings, our method may have advantages in terms of applicability and feasibility in real-world clinical use. Lastly, although this study employed a longitudinal design, it had a relatively small sample size. Nevertheless, we identified significant associations between depressive symptoms in SCGs and markers of neuroinflammation, even after adjusting for various factors known to influence neuroinflammatory processes, including VRS, physical activity levels and BMI. Further research involving larger cohorts and extended follow-up periods is warranted to validate and expand our observations.

In conclusion, this study contributes to the understanding of neuroinflammatory responses to caregiving-related stress, providing a crucial link between the psychological burden of caregiving and its neurobiological consequences. Future studies should focus on delineating the specific molecular pathways involved and investigating targeted interventions to alleviate neuroinflammatory responses in SCGs. Addressing these challenges is crucial for developing comprehensive strategies to support the health and well-being of SCGs, who are themselves older adults and at risk of neurodegenerative disorders.

Funding

This work was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education (grant number RS-2023-00210380); and Chungnam National University Hospital.

Conflict of Interest

None.

Data Availability

The data sets generated and analyzed during the present study are not publicly available due to ethical considerations and privacy restrictions. However, the data can be made available by the corresponding author upon request, subject to approval by the Institutional Review Board of the Chungnam National University Hospital, South Korea.

Acknowledgments

We would like to thank all the participants of this study.

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© The Author(s) 2024. Published by Oxford University Press on behalf of The Gerontological Society of America.

This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

Topic:

• physical activity
• psychological stress
• dementia
• apolipoprotein e
• biological markers
• caregivers
• depressive disorders
• follow-up
• glial fibrillary acidic protein
• hospitals, university
• nerve degeneration
• plasma
• cognitive impairment
• older adult
• neuroinflammatory diseases
• neurofilament protein l

Supplementary data