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. Author manuscript; available in PMC: 2025 Apr 1.
Published in final edited form as: Stress Health. 2023 Sep 7;40(2):e3313. doi: 10.1002/smi.3313

Depressed, Stressed, and Inflamed: C-Reactive Protein Linked with Depression Symptoms in Midlife Women with Both Childhood and Current Life Stress

Christina A Metcalf 1, Rachel L Johnson 2, Korrina A Duffy 1, Ellen W Freeman 3, Mary D Sammel 1,2, C Neill Epperson 1,4
PMCID: PMC10918037  NIHMSID: NIHMS1929851  PMID: 37679965

Abstract

Purpose:

To determine whether the relationship between inflammatory factors and clinically significant depression symptoms is moderated by high exposure to adverse childhood experiences and current life stressors in a longitudinal community cohort of mid-life women.

Methods:

Participants from the Penn Ovarian Aging Study (POAS) community cohort (age at baseline: M=45.3 [SD=3.8]) were included in analyses if they had a blood sample measuring basal inflammatory markers during at least one visit where depression symptom severity and current stressful life events were also assessed (N=142, average number of visits per participant=1.75 [SD=0.92]). Approximately annually over the course of 16 years, participants self-reported depression symptom severity using the Center for Epidemiologic Studies Depression (CESD) Scale, provided menstrual diaries to determine menopause stage and contributed blood samples. Residual blood samples were assayed for interleukin (IL)-6, IL 1-beta (IL-1β), tumor necrosis factor alpha (TNF-α), and high sensitivity C-reactive protein (hsCRP). Early life stress was quantified using the Adverse Childhood Experiences questionnaire (low [0–1 experience(s)] vs. high [≥ 2 experiences]). Current stressful life events were assessed using a structured interview (low [0–1 events] vs. high [≥ 2 events]). Generalized estimating equation models were used to model associations with the outcome of interest—clinically significant depression symptoms (CESD ≥16)—and risk factors: inflammatory marker levels (log transformed), adverse childhood experiences group, and current life stressors group. Covariates included menopause stage, age at study baseline, BMI, race, and smoking status.

Results:

We found a significant three-way interaction between log hsCRP levels, adverse childhood experiences group, and current life stressors group on likelihood of experiencing clinically significant depression symptoms (OR: 4.33; 95% CI: 1.22, 15.46; p = 0.024) after adjusting for covariates. Solely for women with high adverse childhood experiences and with high current life stressors, higher hsCRP was associated with higher odds of having clinically significant depression symptoms (OR: 1.46; 95% CI 1.07, 1.98; p = 0.016). This three-way interaction was not significant for IL-6, IL-1β, and TNF-α.

Conclusions:

For women in midlife with exposure to high adverse childhood experiences and multiple current life stressors, elevated levels of CRP were uniquely associated with clinically significant depression symptoms. Early life adversity and current life stressors represent identifiable individual risk factors whose negative impact may be curtailed with inventions to target inflammation in midlife women.

Keywords: mood, adverse childhood experiences, stressors, inflammatory markers, menopause

Introduction

Inflammatory markers associated with depression may be elevated only in a subset of patients (longitudinal studies: Gimeno et al., 2009; Khandaker et al., 2014; Wium-Andersen et al., 2013; Zalli et al., 2016; cross-sectional studies: Dowlati et al., 2014; Goldsmith et al., 2016; Haapakoski et al., 2015; Howren et al., 2009; but see also Osimo et al., 2020). For example, a meta-analysis of 30 studies found that only half of patients with depression had elevated C-reactive protein (CRP) levels (Osimo et al., 2019). Furthermore, the relationship between inflammatory markers and major depressive disorder (MDD) has stronger support for some inflammatory markers, such as CRP and interleukin-6 (IL-6), but more inconsistent evidence for other inflammatory markers, such as tumor-necrosis factor alpha (TNF-α) and IL-1 beta (IL-1β) (Haapakoski et al., 2015). A meta-analysis of 18 studies demonstrated that cytokine levels in the blood were generally higher in acutely depressed patients compared to healthy controls but with effect sizes ranging from small to large (see Table 3, Goldsmith et al., 2016). These variable effect sizes could indicate that certain inflammatory markers are elevated in only a subset of individuals with depression. Consideration of factors that serve as additional “hits” – such as adverse childhood experiences and current life stressors – may help explain the conditions under which elevated inflammatory markers and depression are linked.

Table 3.

Odds ratios of the likelihood of experiencing clinically significant depression symptoms by adverse childhood experiences group and current life stressor group based on a one-unit change in log C-reactive protein (CRP; presented as CRP z-scores for interpretability).

High adverse childhood experience exposure Low adverse childhood experience exposure
Clinically significant depression symptoms hsCRP z-score Odds Ratio (95% CI) P value hsCRP z-score Odds Ratio (95% CI) P value P value for high vs. low adverse childhood experiences
Current life stressors
 0–1 0.81 (0.34, 1.91) 0.623 1.62 (0.84, 3.16) 0.149 0.209
 ≥2 1.78 (1.11, 2.86) 0.016* 0.83 (0.49, 1.41) 0.494 0.029*
P value for high vs. low current life stressors 0.092 0.098
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hsCRP: high sensitivity C-reactive protein

P values for each of the four groups (high adverse childhood experiences, 0–1 life stressors; high adverse childhood experiences, ≥ 2 life stressors; low adverse childhood experiences, 0–1 life stressors; low adverse childhood experiences, ≥ 2 life stressors) test whether the odds ratio for the effect of CRP significantly differs from 1. Then, p values for high (≥ 2) vs. low (0–1) current life stressors test whether the effect of CRP in high vs. low life stressors differs within each adverse childhood experiences group. Likewise, p values for high (≥ 2) vs. low (0–1) adverse childhood experiences test whether the effect of CRP in high (≥ 2) vs. low (0–1) adverse childhood experiences differs within each current life stressor group.

*

p < 0.05

More recently, research has begun to consider whether exposure to adverse childhood experiences moderates the inflammation-depression relationship, with three studies finding that MDD patients with a history of childhood adversity had elevated inflammation, suggesting a subtype with “inflammatory depression” (Danese, 2008: hsCRP and a composite measure of hsCRP, fibrinogen, and white blood cells; de Punder et al., 2018: composite measure of CRP, IL-6, and white blood cell count; Pace et al., 2006: IL-6 and nuclear factor kappa β DNA binding). Another study found that CRP and IL-6 were associated with depression in those with childhood adversity but not in those without this exposure (Miller & Cole, 2012). Yet, to date, only one study has tested whether early life stress moderates the association between inflammation and depression symptoms by testing for an interaction (Kuhlman et al., 2020) – a statistically more rigorous approach than stratifying analyses by stress exposure subgroup. Importantly, this study found that higher exposure to early life stress strengthened the relationship between acute increases in IL-6 24 hours following vaccine administration and heightened depressive symptoms. These findings suggest that early life stress may sensitize individuals to the psychological consequences of inflammation.

Emerging evidence suggests that current and recent life stress also moderate the inflammation-depression relationship. Among healthy adults, perceived stress moderated the effect of endotoxin administration on depression, such that those with higher perceived stress experienced greater increases in depressed mood in the endotoxin condition relative to the control condition (Irwin & Piber, 2018). In another study, high stress following a recent early-stage breast cancer diagnosis moderated the relationship between CRP and depressive symptoms (Manigault et al., 2021). Elevated CRP was associated with increased odds of endorsing clinically significant depression symptoms only in patients with high cancer-related stress. In a longitudinal study following a diverse sample of urban adolescents, recent stressful life events combined with larger increases in inflammatory markers over time were associated with more severe depression symptoms (Kautz et al., 2020).

Animal studies have considered how these two “hits” – early life stress and current life stress – interact to impact outcomes (Calcia et al., 2016; Cao et al., 2021). The combination of early and current life stress may sensitize the central nervous system (CNS) to increases in peripheral inflammation by increasing the permeability of the blood-brain-barrier (BBB), allowing peripheral proinflammatory cytokines to infiltrate the CNS (Kuvacheva et al., 2016; Menard et al., 2017), triggering cytokine production within the brain (Bilbo & Schwarz, 2012). Cytokines in the brain have been linked to depression-like behaviors in animal models, both when cytokines have been administered directly into the brain (Anforth et al., 1998; Dantzer & Kelley, 2007) and when they have infiltrated the brain via a compromised BBB (Menard et al., 2017).

While research in humans has examined the contributions of childhood stress (Danese et al., 2008; de Punder et al., 2018; Kuhlman et al., 2020; Pace et al., 2006) and current life stress (Irwin et al., 2019; Kautz et al., 2020; Manigault et al., 2021) independently on the inflammation-depression relationship, to our knowledge, the interactive effects of these two hits have not been studied in clinical samples. One study tested the interaction effect of adverse childhood experiences and current stressors on inflammation but did not consider whether inflammation was related to depression (Hostinar, 2015).

Paralleling the broader clinical literature, the inflammation-depression relationship has garnered mixed empirical support during the menopause transition. Inflammatory markers have been shown to be associated with depressive symptoms among pre- or early perimenopausal women in adjusted models (Matthews et al., 2007: fibrinogen, but not CRP, factor VIIc, fibrinogen, plasminogen activator inhibitor Type 1, or tissue-type plasminogen activator antigen), peri- and post-menopausal women not on hormone therapy (Liukkonen et al., 2010: CRP), and post-menopausal women on hormone therapy (Ma et al., 2013: CRP). To our knowledge, neither adverse childhood experiences nor current life stressors have been examined as potential independent or interactive moderators of the inflammation-depression relationship during the menopause transition; however, both have been identified as relevant risk factors for depression during the menopause transition in studies that did not examine inflammatory markers (Bromberger et al., 2007, 2011; Shanmugan et al., 2017). The dynamic hormonal milieu of the menopause transition and its impact on inflammatory, neurocognitive, and stress processes provides a relevant context in which to study the inflammation-depression relationship and its potential moderators (Lombardo et al., 2021; Mattina et al., 2019).

In the present work, we sought to determine whether adverse childhood experiences (low vs. high) and current life stressors (low vs. high) moderated the relationship between inflammatory marker levels (IL-6, IL-1β, TNF-α, and high sensitivity CRP [hsCRP]) and clinically significant depressive symptoms in a longitudinal community cohort of midlife women, where half of the participants contributed data from two or more assessments over the longitudinal study. We predicted that the relationship between inflammatory markers and clinically significant depression symptoms would be strongest for those with two additional hits – those with high adverse childhood experiences and high current life stressors.

Methods

Cohort description

One hundred forty-two participants from the PENN Ovarian Aging Study (POAS) cohort (Freeman & Sammel, 2016) completed the Adverse Childhood Experiences Questionnaire (Felitti et al., 1998), the Center for Epidemiologic Studies Depression (CESD) Scale (Radloff, 1977), and a structured interview that assessed current stressful life events. Residual blood samples were assayed for inflammatory markers if, at the time of collection, participants were not physically ill (e.g., had a cold) and were not using medications that could have impacted inflammatory marker levels (e.g., antibiotics, corticosteroids, psychotropics, or cold or allergy medications). Recruitment and selection of the POAS cohort sample have been described previously (Freeman & Sammel, 2016).

At study start, all POAS cohort participants were premenopausal, between 35–47 years old, and had a uterus and at least one ovary. Exclusion criteria included recent substance abuse, use of psychotropics or hormonal contraception, and health problems affecting hormone function (e.g., breast cancer). The study was designed to include equal numbers of African American and Caucasian participants, contacted through random number dialing to Philadelphia County residences in 1996 and 1997. The University of Pennsylvania institutional review board approved all study procedures; all participants provided written informed consent.

Procedures

Data were collected approximately annually over the course of 16 years. Assessments included demographics, menstrual cycle information, health status, health behaviors, height, weight, and blood collection. Stressful life events that occurred in the past six months were assessed using a structured interview that was added to the protocol at approximately year five. Adverse childhood experiences history was obtained at the end of the study.

Measures

Clinically significant depression symptoms

Depression symptom severity was assessed using the 20-item CESD self-report scale (Radloff, 1977). Participants indicated the frequency that they experienced each item from 0 (rarely or none of the time) to 3 (most or all of the time); total scores ranged from 0–60. A score of ≥ 16 is commonly used to indicate clinically significant depression symptoms (Smarr & Keefer, 2011). For analyses, we considered a score of ≥ 16 as indicating clinically significant depression symptoms, whereas a score of < 16 was not considered indicative of clinically significant depression symptoms. The CESD has demonstrated high reliability (Radloff, 1977), and in a sample of women in midlife, has good reliability and construct validity (Knight et al., 1997). Internal consistency of the CESD at POAS baseline was good (Cronbach’s alpha 0.78 (95% CI (bootstrapped from 1000 samples) 0.75, 0.82; N=436), as was CESD internal consistency for those POAS participants included in the present manuscript (Cronbach’s alpha 0.80 (95% CI (bootstrapped from 1000 samples) 0.71, 0.86, N=142).

Adverse childhood experiences

Early life stress was assessed using the 10-item Adverse Childhood Experiences Questionnaire (Felitti et al., 1998). The Adverse Childhood Experiences Questionnaire asks participants to indicate which of 10 types of adversity occurred before the age of 18. The Adverse Childhood Experiences Questionnaire includes items on abuse (emotional, physical, and sexual), neglect (emotional and physical), and household/family dysfunction (parental separation or divorce, household domestic violence, household substance abuse, parental mental illness, and member of household imprisoned). Each of the 10 adverse childhood experiences count for one point, which are added together to create a composite score that can range from 0–10. For analyses, we considered adverse childhood experiences as low (0–1) or high (≥ 2), based on previous studies showing that exposure to two or more adverse childhood experiences is linked with negative cognitive and mood outcomes in midlife (Epperson et al., 2017; Shanmugan et al., 2020). To our knowledge, psychometric properties of this instrument have not been published (McLellan & MacMillan, 2020).

Current life stressors

Current life stressors were assessed via a semi-structured interview based on the Detroit Couples Study Life Events Method (Kessler & Wethington, 1991). Participants endorsed whether they or someone important to them had experienced various stressful life events in the past six months (e.g., being fired, laid off, or quit work without another job; losing a house or something else important; death of a husband, wife, or partner; moving). Because the distribution of this variable was skewed, with few high values, we dichotomized exposure into balanced groups representing “low” current life stressors (less than two events in the past six months) and “high” current life stressors (two or more of these events in the past six months). Importantly, a previous study using this categorization found that midlife women reporting high current life stressors were over four times more likely to experience clinically significant depressive symptoms over the course of a five-year span of the menopause transition relative to those with no current life stressors (Bromberger et al., 2007). This interview demonstrated adequate reliability over a twelve-month recall period (Kessler & Wethington, 1991).

Inflammatory marker assessments

Participants provided non-fasting blood samples (2.5 oz) from the non-dominant arm at each in-home visit into vacutainer serum separator tubes with separator gel and clot activator. In-home visits were scheduled throughout the day and trained research interviewers collected the blood samples. Menstruating participants collected one sample between days 2–6 of the menstrual cycle (follicular stage) for two consecutive menstrual cycles. Non-menstruating participants collected one sample followed by another sample one month later. Samples were placed on ice, centrifuged for 20 minutes, aliquoted into polypropylene tubes, and stored at −80°C. Blood samples were originally used for hormone assays. Samples that had enough remaining blood and met the previously listed criteria were assayed for hsCRP (in singlicate on BNII using Immunonephelometry [Siemens, BNII Malvern PA]), as well as IL-6, IL-1β, and TNF-α (in duplicate using Human High Sensitivity IL-6, IL-1β, and TNF-α Cytokine Premixed Magnetic Luminex Performance Assay [R&D Systems]). Multiple samples for individual participants were quantified in the same batch. Intra-assay coefficients of variation were 5.2% (IL-6), 5.3% (IL-1β), and 5.2% (TNF-α). Inter-assay coefficients of variation were 9.6% (IL-6), 12.8% (IL-1β), and 9.6% (TNF-α). Intra-assay and inter-assay coefficients of variation were not available for hsCRP. The sensitivity threshold was 0.16 mg/mL for hsCRP, 0.14 pg/mL for IL-6, 0.08 pg/mL for IL-1β, and 0.29 pg/mL for TNF-α. Inflammatory marker levels were natural log transformed to reduce skew and meet assumptions for linear models. If two blood samples from the same assessment year were collected and met the previously listed criteria, inflammatory marker values were averaged.

Menopausal status

Menopause stage groupings included premenopause (regular menstrual cycles or ≤ 7-day cycle length change from typical), early transition (≥ 7-day cycle length change for ≥ 2 consecutive cycles or 60 days amenorrhea), late transition (60 days to 11 months amenorrhea), and postmenopause (≥ 12 months amenorrhea), adapted from the initial staging system for reproductive aging in women (Soules et al., 2001).

Statistical Analyses

When comparing demographics across the four subgroups based on adverse childhood experiences (low vs. high) and current life stressors (low vs. high), one-way ANOVAs and Fisher’s exact tests were used. Generalized estimating equation models with an exchangeable correlation structure to account for repeated measures were used to model associations with the binary outcome of interest—clinically significant depression symptoms (CESD ≥ 16) or not (CESD < 16)—and risk factors: adverse childhood experiences (low: 0–1 vs. high: ≥ 2), current life stressors (low: 0–1 vs. high: ≥ 2), and inflammatory marker levels (continuous, log transformed). These models were selected so that all available visit data for participants could be included in the models. Power calculations for this analysis assumed 2-sided type I error of 5%, an overall prevalence of clinically significant depressive symptoms ranging from 30–45%, and 80% power. With these assumptions, the sample size of 142 participants has 80% power to detect an odds ratio of 1.70 per SD increase in log-inflammatory marker levels or greater. For our primary analyses, we controlled for relevant covariates associated with our outcome and risk factors of interest identified a priori based on previous literature (Freeman 2014; Epperson 2017): menopause phase (pre-menopause, early transition, late transition, and post-menopause), study baseline age (continuous), BMI (continuous), race (white or African American), and smoking status (smoker or non-smoker). Unadjusted models examining the associations of inflammatory markers with clinically significant depression symptoms are also presented to compare the primary results to a model without the examination of a three-way interaction. Two-sided p-values of < 0.05 were considered statistically significant. Analyses were conducted using R (version 4.2.0).

Results

Participants and assessments

Among the 142 participants, there were 249 total observations with all data available for depression symptom severity, current life stressors, inflammatory markers, and covariates. Table 1 provides baseline demographic information, log inflammatory marker levels, current life stressors, and depression symptom severity by adverse childhood experiences and current life stressor exposure subgroups. We observed significant demographic differences in race between subgroups (low adverse childhood experiences/low current life stressor group: 19.4% African American while the three other subgroups ranged from 50.0 to 58.6% African American). CESD scores at baseline and clinically significant depression symptoms at baseline (CESD ≥ 16) also differed significantly across subgroups, as expected. Participants contributed data from an average of 1.75 (SD 0.92) visits. Adverse childhood experiences scores ranged from 0–9 (median 2, 1st and 3rd quartiles of 1 and 3 adverse childhood experiences), and our current life stressors ranged from 0–9 (median 2, 1st and 3rd quartiles of 1 and 4 current life stressors). Frequencies of item-level adverse childhood experiences in overall sample and within each adverse childhood experiences/current life stressors subgroup are represented in Supplemental Table 1.

Table 1.

Baseline demographic characteristics, cytokine levels, current life stress, and depression symptom severity by adverse childhood experience exposure and current life stress exposure groups

Baseline characteristic Overall (N = 142) Low adverse childhood experiences, 0–1 life events (N = 36) Low adverse childhood experiences, 2+ life events (N = 34) High adverse childhood experiences, 0–1 life events (N = 26) High ACE, 2+ life events (N = 46) p value
Race 0.002
 White 76 (53.9%) 29 (80.6%) 14 (41.2%) 13 (50.0%) 20 (44.4%)
 African American 65 (46.1%) 7 (19.4%) 20 (58.8%) 13 (50.0%) 25 (55.6%)
Education 0.112
 High school or less 56 (39.7%) 12 (33.3%) 16 (47.1%) 6 (23.1%) 22 (48.9%)
 At least some college 85 (60.3%) 24 (66.7%) 18 (52.9%) 20 (76.9%) 23 (51.1%)
BMI 30.0 (7.8) 28.4 (8.4) 29.9 (8.0) 29.1 (6.0) 31.8 (7.9) 0.250
Age 45.3 (3.8) 44.4 (4.0) 46.0 (3.7) 45.0 (3.6) 45.5 (3.9) 0.317
Ever smoker 44 (31.2%) 9 (25.0%) 8 (23.5%) 9 (34.6%) 18 (40.0%) 0.356
hsCRP
 Geometric mean (95% CI) 1.5 (1.2, 1.9) 1.5 (0.9, 2.5) 1.4 (0.7, 2.7) 1.4 (0.8, 2.5) 1.6 (1, 2.5)
 Log hsCRP 0.4 (1.6) 0.4 (1.5) 0.3 (1.8) 0.4 (1.4) 0.5 (1.5) 0.988
IL-6
 Geometric mean (95% CI) 9.9 (6.6, 14.9) 6.9 (3.4, 14.2) 13.2 (5.5, 31.6) 10.6 (3.8, 29.4) 10.2 (4.7, 22.1)
 Log IL-6 2.3 (2.4) 1.9 (2.1) 2.6 (2.5) 2.4 (2.5) 2.3 (2.6) 0.745
IL-1β
 Geometric mean (95% CI) 2.0 (1.2, 3.3) 1.9 (0.8, 4.4) 2.3 (0.7, 6.8) 1.5 (0.4, 5.7) 2.3 (0.9, 5.6)
 Log IL-1β 0.7 (3.0) 0.6 (2.4) 0.8 (3.2) 0.4 (3.3) 0.8 (3.0) 0.937
TNF-α
 Geometric mean (95% CI) 21.9 (16.7, 28.6) 20 (12.5, 32.0) 29.7 (18.1, 48.8) 21.8 (11.2, 42.6) 18.8 (10.7, 32.8)
 Log TNF-α 3.1 (1.6) 3.0 (1.4) 3.4 (1.4) 3.1 (1.7) 2.9 (1.9) 0.629
Current life events 2.3 (2.1) 0.4 (0.5) 3.4 (1.5) 0.6 (0.5) 3.9 (1.8) <0.001
Current life events >= 2 80 (56.3%) 0 (0.0%) 34 (100.0%) 0 (0.0%) 46 (100.0%) <0.001
CESD 13.4 (9.4) 9.6 (7.7) 13.0 (9.2) 10.5 (6.6) 18.3 (10.3) <0.001
CESD ≥ 16 52 (36.6%) 8 (22.2%) 13 (38.2%) 4 (15.4%) 27 (58.7%) <0.001
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BMI: body mass index; hsCRP: high sensitivity C-reactive protein; IL-6: interleukin 6; IL-1β: interleukin 1-beta; TNF-α: tumor necrosis factor alpha; CESD: Center for Epidemiologic Studies Depression Scale.

Association between inflammatory markers and likelihood of experiencing clinically significant depression symptoms is moderated by adverse childhood experiences and current life stressors

We found a significant three-way interaction among log hsCRP levels, adverse childhood experiences group (low vs. high), and current life stressor group (low vs. high) on clinically significant depression (CESD ≥ 16) adjusting for covariates (OR: 4.33; 95% CI: 1.22, 15.46; p = 0.024, Table 2). Table 3 illustrates this statistically significant three-way interaction by estimating the association between CRP and depression within all four strata defined by adverse childhood experiences and current life stress. All estimates are from the three-way interaction model and not an evaluation of subgroups. Among those with high adverse childhood experiences and a high numbers of current life stressors, higher levels of hsCRP were associated with higher odds of experiencing clinically significant depression symptoms (OR: 1.46; 95% CI: 1.07, 1.98; p = 0.016), such that for every one-unit increase in log-transformed CRP, the odds of having clinically significant depression symptoms increased by approximately 46%. No significant relationship emerged between hsCRP and clinically significant depression symptoms in women with low adverse childhood experiences regardless of current life stressors or in high adverse childhood experiences women with a low number of current life stressors (ps > 0.05; Table 3). Supplemental Table 2 displays odds ratios for all predictors in this model. The three-way interaction models involving other inflammatory markers (i.e., IL-6, IL-1β, TNF-α) were not associated with odds of experiencing clinically significant depression symptoms (ps > 0.05; Table 2). No inflammatory markers were not significantly related to odds of experiencing clinically significant depression symptoms in models examining this relationship only as a main effect (Supplemental Table 3).

Table 2.

Three-way interactions between adverse childhood experiences exposure group, current life stressors, and inflammatory markers to predict depression outcome (CESD ≥ 16)

Unadjusted interaction p value Adjusteda interaction p value
log hsCRP * current life stressor group * adverse childhood experience group 0.019* 0.024*
log IL-1β * current life stressor group * adverse childhood experience group 0.999 0.692
log IL-6 * current life stressor group * adverse childhood experience group 0.244 0.417
log TNF-α * current life stressor group * adverse childhood experience group 0.743 0.854
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hsCRP: high sensitivity C-reactive protein; IL-6: interleukin 6; IL-1β: interleukin 1-beta; TNF-α: tumor necrosis factor alpha; CESD: Center for Epidemiologic Studies Depression Scale. Current life stressor groups: (low [0–1 events] vs. high [≥ 2 events]); Adverse childhood experience groups: (low [0–1 experience(s)] vs. high [≥ 2 experiences]).

a

Adjusted models included BMI, race, education, baseline age, and baseline cognitive performance as covariates.

*

p < 0.05

Discussion

Our study showed that for a subgroup of midlife women—specifically those with two or more adverse childhood experiences and current life stressors—higher hsCRP was associated with higher odds of experiencing clinically significant depression symptoms, even after controlling for relevant covariates. For women with high adverse childhood experiences and a high number of current life stressors, elevated levels of CRP may be uniquely related to clinically significant depression symptoms. The three-way interaction between adverse childhood experiences, current life stressors, and inflammatory markers on clinically significant depression symptoms that we observed for CRP was not significant for any of the other inflammatory markers that we examined (IL-6, IL-1β, or TNF-α)—although IL-6 did show a similar pattern in the high ACE/high current life stressor subgroup. To our knowledge, this work is the first to test the moderating role of the two “hits” of early life and current life stressors on the inflammation-depression relationship in humans.

Our work emphasizes the potential role of current life stressors alongside exposure to adverse childhood experiences in moderating the relationship between inflammation and depression (Danese et al., 2008; Miller & Cole, 2012). In contrast to other work finding that CRP is higher in high adverse childhood experiences groups compared to low adverse childhood experiences groups (e.g., Baumeister et al., 2016), CRP was not significantly different between our adverse childhood experiences groups although we did find a trend in this direction (i.e., there was not a main effect of adverse childhood experiences group on CRP). CRP was also not significantly higher in the high adverse childhood experiences/high current life stressor subgroup compared to the other three subgroups (i.e., there was not a two-way interaction between adverse childhood experiences and current life stressor groups on CRP alone). Rather, our study demonstrated that the link between CRP and clinically significant depression symptoms was dependent on the presence of both childhood and current stress. Given that the high adverse childhood experiences/high current life stressor subgroup was the only one to show a significant association between CRP and depression risk, the causal role of CRP in influencing depressive symptoms in this subgroup should be tested in future research as well as whether interventions targeting inflammation have antidepressant effects in the high adverse childhood experiences/high current life stressor subgroup.

Our findings further highlight CRP as a relevant inflammatory marker for midlife women with high adverse childhood experiences, high current life stressor exposure, and clinically significant depression symptoms as no significant effects were observed with any of the other inflammatory markers: IL-6, IL-1β, and TNF-α. Among the inflammatory markers that we measured, previous meta-analyses have most robustly linked plasma CRP and IL-6 with depression (Haapakoski et al., 2015; Osimo et al., 2020). Plasma CRP may reflect inflammatory activity in the CNS given that plasma CRP significantly correlates with CRP, IL-6, and TNF-α in cerebral spinal fluid among individuals with MDD, whereas other plasma inflammatory markers do not show such associations (Felger et al., 2020). Another reason we may have observed effects with CRP, but not with IL-6, IL-1β, and TNF-α, is that CRP is more stable over time relative to these other cytokines, given that it has a half-life of about 20 hours versus minutes for many cytokines (Pepys & Hirschfield, 2003; Vigushin et al., 1993; Whiteside, 1994). Furthermore, in our data, IL-6 and IL-1β had larger standard deviations than CRP and we thus had more power to detect relationships with CRP than these other inflammatory markers.

The present findings in midlife women parallel findings during other stages of the lifespan that have demonstrated associations between inflammation and depression specifically among individuals exposed to adverse childhood experiences (Danese et al., 2008; Kuhlman et al., 2020; Miller & Cole, 2012). Our study also complements previous work showing that adverse childhood experiences and current life stressors can modify the relationship between inflammatory markers and negative brain outcomes in midlife women. Recently, it was found that during perimenopause, adverse childhood experiences history modified the relationship between TNF-α and verbal memory, such that higher levels of TNF-α were associated with poorer verbal memory in women with high but not low adverse childhood experiences (Metcalf et al., 2022). Our present findings and previous work support the notion that ACE history and current life stressors can modify the relationship between inflammatory markers and brain health in midlife women.

Emerging research indicates that the CNS becomes sensitized to peripheral inflammatory markers after early life stress exposure (Bilbo & Schwarz, 2012). CNS sensitization following early life stress may occur via increased permeability of the blood brain barrier (BBB), through which peripheral inflammatory markers can enter the brain (Bilbo & Schwarz, 2012). Infiltration of peripheral immune cells into the brain contributes to neuroinflammation—or the presence of cytokines, chemokines, or secondary messengers within the CNS (DiSabato et al., 2016). Neuroinflammation has been linked to depression (Troubat et al., 2021). For instance, neuroinflammation—including in the form of elevated pro-inflammatory cytokines—has been discovered in the brains of depressed suicide victims (Janelidze et al., 2011). This mechanism as well as the “two-hit hypothesis” —with early life stress providing a first “hit” resulting in long-standing alterations in the CNS that interact with a second “hit” of subsequent stress (Calcia et al., 2016; Cao et al., 2021) —may explain why we found that inflammation was only associated with depression in the subgroup of our sample with exposure to high adverse childhood experiences and multiple current life stressors.

Depression symptoms among the women with high adverse childhood experiences exposure and high current life stressors in our sample may be more sensitive to higher levels of CRP in part due to the impact of the menopause transition. Although we controlled for menopause stage, a substantial amount of the data provided were from visits that took place in the early (26.9%) or late menopause transition (16.9%)—periods during which estradiol fluctuates substantially. In experimental work, estradiol variability increases sensitivity to social stress in a manner that interacts with stressful life events and the menopause transition to predict depressive symptoms (Gordon et al., 2016, 2019). Women with high adverse childhood experiences are at an increased risk for depression during the menopause transition more broadly (Epperson et al., 2017) as are women experiencing recent life stressors in midlife (Bromberger et al., 2007, 2011). Our findings suggest that, among midlife women, the combination of high adverse childhood experiences exposure and current life stressors sensitize women to the harmful effects of inflammation, such that inflammation may be more likely to cause depression, perhaps also due to estradiol variability characteristic of the menopause transition. As such, these data may not be generalizable to men or women in other age groups.

Strengths of the present work include that 24% (34/142) of the participants changed with respect to their current life stressor levels at different visits, providing data about how current life stressor level interacts with childhood stress and CRP to predict depression within the same people under different current life stressor circumstances. In other words, having the same participant with the same adverse childhood event history providing information from blood samples and depression symptom severity from different visits where she was and was not experiencing multiple current life stressors, respectively, increases our confidence about the importance of the role multiple current life stressors play as a second “hit” necessary to see an increased risk for clinically significant depression when CRP is elevated. Our study had limitations as well. We conducted secondary data analyses and were limited to measuring inflammatory markers in remaining blood samples during visits where life events were also measured. We were powered only for relatively large effects, i.e. odds ratio of 1.70 per SD increase in log-inflammatory marker levels or greater. Our study was correlational in nature; therefore, we cannot ascertain whether elevated CRP caused depression symptoms or whether the depression symptoms caused CRP to be elevated, but prior research suggests both pathways may be possible (Beurel et al., 2020). We only had access to the summary scores for current life stressors and CESD at a given study visit rather than item-level data, precluding additional analyses regarding the potential relevance of certain stressors or particular depression symptoms in these interactive relationships. The Adverse Childhood Experiences Questionnaire has received criticism as an instrument, including its lack of psychometric assessment, and alternative methods for measuring childhood adversity may be useful in future work (McLennan, MacMillan, Afifi, 2020). CRP was assayed in singlicate, prohibiting us from being able to estimate coefficients of variation to assess the precision of its measurement. This limitation warrants that the principal findings of this paper be interpreted with caution.

Conclusion

Life stressors are salient and common challenges for midlife women that can negatively impact health—warranting attention from researchers and clinicians alike. Our findings suggest that multiple current life stressors and high exposure to adversity in childhood may serve as a “double hit,” making women in midlife more susceptible to negative outcomes, such as depression, when CRP is elevated. In clinical settings, midlife women should be screened for both childhood adversity and current life stressors, particularly as previous research has shown that the menopause transition is associated with increased depression risk for women with high adverse childhood experiences and women with life stressors. In addition, findings from this research emphasize the importance of encouraging healthy behaviors known to reduce markers of inflammation. Future research should determine whether high CRP could be used as a biomarker of depression risk and a target for intervention in midlife women with high childhood adversity and high current life stressors.

Supplementary Material

Supinfo

Acknowledgements:

Grants from the National Institute of Mental Health (T32 MH015442, CAM), the Office of Research on Women’s Health (P50 MH099910, CNE, MDS), the National Institute on Drug Abuse (K24 DA030301, CNE; R01 DA37289, CNE), the National Institute on Aging (R01 AG048839, CNE, MDS; R01 AG012745-15, EWF, MDS), and the Ludeman Center for Women’s Health Research (CAM) supported this research.

Footnotes

Conflicts of interest:

CAM, RLJ, KAD, MDS, and EWF have nothing to disclose. CNE serves on the Advisory Board for Sage Therapeutics and Asarina Pharma, from which she receives consulting fees. She receives research grant support from Sage Therapeutics.

Data accessibility:

The datasets analyzed during the current study are available from the corresponding author upon reasonable request.

References

  1. Anforth H, Bluthe R, Bristow A, Hopkins S, Lenczowski M, Luheshi G, Lundkvist J, Michaud B, Mistry Y, Van Dam A, Zhen C, Dantzer R, Poole S, Rothwell N, Tilders F, & Wollman E (1998). Biological activity and brain actions of recombinant rat interleukin-1alpha and interleukin-1beta. European Cytokine Network, 9(3), 279–288. [PubMed] [Google Scholar]
  2. Baumeister D, Akhtar R, Ciufolini S, Pariante CM, & Mondelli V (2016). Childhood trauma and adulthood inflammation: a meta-analysis of peripheral C-reactive protein, interleukin-6 and tumour necrosis factor-α. Molecular Psychiatry, 21, 642–649. 10.1038/mp.2015.67 [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Beurel E, Toups M, & Nemeroff CB (2020). The bidirectional relationship of depression and inflammation: Double trouble. Neuron, 107(2), 234–256. 10.1016/j.neuron.2020.06.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Bilbo SD, & Schwarz JM (2012). The immune system and developmental programming of brain and behavior. Frontiers in Neuroendocrinology, 33(3), 267–286. 10.1016/j.yfrne.2012.08.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Bromberger JT, Kravitz HM, Chang YF, Cyranowski JM, Brown C, & Matthews KA (2011). Major depression during and after the menopausal transition: Study of Women’s Health Across the Nation (SWAN). Psychological Medicine, 41(9), 1879–1888. 10.1017/S003329171100016X [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Bromberger JT, Matthews KA, Schott LL, Brockwell S, Avis NE, Kravitz HM, Everson-Rose SA, Gold EB, Sowers M, & Randolph JF (2007). Depressive symptoms during the menopausal transition: The Study of Women’s Health Across the Nation (SWAN). Journal of Affective Disorders, 103, 267–272. 10.1016/j.jad.2007.01.034 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Calcia MA, Bonsall DR, Bloomfield PS, Selvaraj S, Barichello T, & Howes OD (2016). Stress and neuroinflammation: A systematic review of the effects of stress on microglia and the implications for mental illness. Psychopharmacology, 233(9), 1637–1650. 10.1007/s00213-016-4218-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Cao P, Chen C, Liu A, Shan Q, Zhu X, Jia C, Peng X, Zhang M, Farzinpour Z, Zhou W, Wang H, Zhou J-N, Song X, Wang L, Tao W, Zheng C, Zhang Y, Ding Y-Q, Jin Y, … Zhang Z (2021). Early-life inflammation promotes depressive symptoms in adolescence via microglial engulfment of dendritic spines. Neuron, 109(16), 2573–2589.e9. 10.1016/j.neuron.2021.06.012 [DOI] [PubMed] [Google Scholar]
  9. Danese A, Moffitt TE, Pariante CM, Ambler A, Poulton R, & Caspi A (2008). Elevated inflammation levels in depressed adults with a history of childhood maltreatment. Archives of General Psychiatry, 65(4), 409–415. 10.1001/archpsyc.65.6.725 [DOI] [PMC free article] [PubMed] [Google Scholar]
  10. Dantzer R, & Kelley KW (2007). Twenty years of research on cytokine-induced sickness behavior. Brain Behavior and Immunity, 21(2), 153–160. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. de Punder K. De, Entringer S, Heim C, Deuter CE, Otte C, Wingenfeld K, & Kuehl LK (2018). Inflammatory measures in depressed patients with and without a history of adverse childhood experiences. Frontiers in Psychiatry, 9, 610. 10.3389/fpsyt.2018.00610 [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. DiSabato DJ, Quan N, & Godbout JP (2016). Neuroinflammation: the devil is in the details. Journal of Neurochemistry, 139, 136–153. 10.1111/jnc.13607 [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Dowlati Y, Segal ZV, Ravindran AV, Steiner M, Stewart DE, & Meyer JH (2014). Effect of dysfunctional attitudes and postpartum state on vulnerability to depressed mood. Journal of Affective Disorders, 161, 16–20. 10.1016/j.jad.2014.02.047 [DOI] [PubMed] [Google Scholar]
  14. Epperson CN, Sammel MD, Bale TL, Kim DR, Conlin S, Scalice S, Freeman K, & Freeman EW (2017). Adverse childhood experiences and risk for first-episode major depression during the menopause transition. Journal of Clinical Psychiatry, 78(3), e298–e307. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Felger JC, Haroon E, Patel TA, Goldsmith DR, Wommack EC, Woolwine BJ, Le NA, Feinberg R, Tansey MG, & Miller AH (2020). What does plasma CRP tell us about peripheral and central inflammation in depression? Molecular Psychiatry, 25(6), 1301–1311. 10.1038/s41380-018-0096-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Felitti VJ, Anda RF, Nordenberg D, Williamson DF, Spitz AM, Edwards V, Koss MP, Marks JS, & Marks JS (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The Adverse Childhood Experiences (ACE) study. American Journal of Preventive Medicine, 56(6), 774–786. [DOI] [PubMed] [Google Scholar]
  17. Freeman EW, & Sammel MD (2016). Methods in a longitudinal cohort study of late reproductive age women: the Penn Ovarian Aging Study (POAS). Women’s Midlife Health, 2(1), 1–11. 10.1186/s40695-016-0014-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Gimeno D, Kivimäki M, Brunner EJ, Elovainio M, De Vogli R, Steptoe A, Kumari M, Lowe GDO, Rumley A, Marmot MG, & Ferrie JE (2009). Associations of C-reactive protein and interleukin-6 with cognitive symptoms of depression: 12-Year follow-up of the Whitehall II study. Psychological Medicine, 39(3), 413–423. 10.1017/S0033291708003723 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Goldsmith DR, Rapaport MH, & Miller BJ (2016). A meta-analysis of blood cytokine network alterations in psychiatric patients: comparisons between schizophrenia, bipolar disorder and depression. Molecular Psychiatry, April 2015, 1–14. 10.1038/mp.2016.3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Gordon JL, Peltier A, Grummisch JA, & Sykes Tottenham L (2019). Estradiol fluctuation, sensitivity to stress, and depressive symptoms in the menopause transition: A pilot study. Frontiers in Psychology, 10, 1319. 10.3389/fpsyg.2019.01319 [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Gordon JL, Rubinow DR, Eisenlohr-Moul TA, Leserman J, & Girdler SS (2016). Estradiol Variability, Stressful Life Events and the Emergence of Depressive Symptomatology during the Menopause Transition. Menopause, 23(3), 257–266. 10.1097/GME.0000000000000528 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Haapakoski R, Mathieu J, Ebmeier KP, Alenius H, & Kivimäki M (2015). Cumulative meta-analysis of interleukins 6 and 1β, tumour necrosis factor α and C-reactive protein in patients with major depressive disorder. Brain, Behavior, and Immunity, 49, 206–215. 10.1016/j.bbi.2015.06.001 [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Hostinar CE (2015). Additive contributions of childhood adversity and recent stressors to inflammation at midlife: Findings from the MIDUS study. Physiology & Behavior, 176(5), 139–148. 10.1016/j.physbeh.2017.03.040 [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Howren MB, Suls J, & Martin R (2009). Depressive symptomatology, rather than neuroticism, predicts inflated physical symptom reports in community-residing women. Psychosomatic Medicine, 71(9), 951–957. 10.1097/PSY.0b013e3181b9b2d7 [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Irwin MR, Cole S, Olmstead R, Breen EC, Cho JJ, Moieni M, & Eisenberger NI (2019). Moderators for depressed mood and systemic and transcriptional inflammatory responses: a randomized controlled trial of endotoxin. Neuropsychopharmacology, 44(3), 635–641. 10.1038/s41386-018-0259-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Irwin MR, & Piber D (2018). Insomnia and inflammation: a two hit model of depression risk and prevention. World Psychiatry, 17(3), 359–361. 10.1002/wps.20556 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Janelidze S, Mattei D, Westrin Å, Träskman Bendz L, & Brundin L (2011). Cytokine levels in the blood may distinguish suicide attempters from depressed patients Shorena. Brain, Behavior, and Immunity, 25(2), 335–339. 10.1016/j.bbi.2010.10.010 [DOI] [PubMed] [Google Scholar]
  28. Kautz MM, Coe CL, McArthur BA, Mac Giollabhui N, Ellman LM, Abramson LY, & Alloy LB (2020). Longitudinal changes of inflammatory biomarkers moderate the relationship between recent stressful life events and prospective symptoms of depression in a diverse sample of urban adolescents. Brain, Behavior, and Immunity, 86(February 2019), 43–52. 10.1016/j.bbi.2019.02.029 [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Kessler RC, & Wethington E (1991). The reliability of life event reports in a community survey. Psychological Medicine, 21(3), 723–738. 10.1017/S0033291700022364 [DOI] [PubMed] [Google Scholar]
  30. Khandaker GM, Pearson RM, Zammit S, Lewis G, & Jones PB (2014). Association of serum interleukin 6 and C-reactive protein in childhood with depression and psychosis in young adult life a population-based longitudinal study. JAMA Psychiatry, 71(10), 1121–1128. 10.1001/jamapsychiatry.2014.1332 [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Kuhlman KR, Robles TF, Haydon MD, Dooley L, Boyle CC, & Bower JE (2020). Early life stress sensitizes individuals to the psychological correlates of mild fluctuations in inflammation. Developmental Psychobiology, 62(3), 400–408. 10.1002/dev.21908 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Kuvacheva NV, Morgun AV, Malinovskaya NA, Gorina YV, Khilazheva ED, Pozhilenkova EA, Panina YA, Boytsova EB, Ruzaeva VA, Trufanova LV, & Salmina AB (2016). Tight junction proteins of cerebral endothelial cells in early postnatal development. Cell and Tissue Biology, 10(5), 372–377. 10.1134/S1990519X16050084 [DOI] [PubMed] [Google Scholar]
  33. Liukkonen T, Vanhala M, Jokelainen J, Keinänen-Kiukaanniemi S, Koponen H, & Timonen M (2010). Effect of menopause and use of contraceptives/hormone therapy on association of C-reactive protein and depression: A population-based study. Journal of Psychosomatic Research, 68(6), 573–579. 10.1016/j.jpsychores.2009.11.003 [DOI] [PubMed] [Google Scholar]
  34. Lombardo G, Mondelli V, Dazzan P, & Pariante CM (2021). Sex hormones and immune system: A possible interplay in affective disorders? A systematic review. Journal of Affective Disorders, 290(March), 1–14. 10.1016/j.jad.2021.04.035 [DOI] [PubMed] [Google Scholar]
  35. Ma Y, Balasubramanian R, Pagoto SL, Schneider KL, Hébert JR, Phillips LS, Goveas JS, Culver AL, Olendzki BC, Beck J, Smoller JW, Sepavich DM, Ockene JK, Uebelacker L, Zorn M, & Liu S (2013). Relations of depressive symptoms and antidepressant use to body mass index and selected biomarkers for diabetes and cardiovascular disease. American Journal of Public Health, 103(8). 10.2105/AJPH.2013.301394 [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Manigault AW, Kuhlman KR, Irwin MR, Cole SW, Ganz PA, Crespi CM, & Bower JE (2021). Vulnerability to inflammation-related depressive symptoms: Moderation by stress in women with breast cancer. Brain, Behavior, and Immunity, 94(February), 71–78. 10.1016/j.bbi.2021.03.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. Matthews KA, Schott LL, Bromberger JT, Cyranowski J, Everson-Rose SA, & Sowers MF (2007). Associations between depressive symptoms and inflammatory/hemostatic markers in women during the menopausal transition. Psychosomatic Medicine, 69(2), 124–130. 10.1097/01.psy.0000256574.30389.1b [DOI] [PubMed] [Google Scholar]
  38. Mattina GF, Van Lieshout RJ, & Steiner M (2019). Inflammation, depression and cardiovascular disease in women: The role of the immune system across critical reproductive events. Therapeutic Advances in Cardiovascular Disease, 13, 1–26. 10.1177/1753944719851950 [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Menard C, Pfau ML, Hodes GE, Kana V, Wang VX, Bouchard S, Takahashi A, Flanigan ME, Aleyasin H, Leclair KB, Janssen WG, Labonté B, Parise EM, Lorsch ZS, Golden SA, Heshmati M, Tamminga C, Turecki G, Campbell M, … Russo SJ (2017). Social stress induces neurovascular pathology promoting depression. Nature Neuroscience, 20(12), 1752–1760. 10.1038/s41593-017-0010-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Metcalf CA, Johnson RL, Novick AM, Freeman EW, Sammel MD, Anthony LG, & Epperson CN (2022). Adverse childhood experiences interact with inflammation and menopause transition stage to predict verbal memory in women. Brain, Behavior, & Immunity - Health, 20(January), 100411. 10.1016/j.bbih.2022.100411 [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Miller GE, & Cole SW (2012). Clustering of depression and inflammation in adolescents previously exposed to childhood adversity. Biological Psychiatry, 72(1), 34–40. 10.1016/j.biopsych.2012.02.034 [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Osimo EF, Baxter LJ, Lewis G, Jones PB, & Khandaker GM (2019). Prevalence of low-grade inflammation in depression: A systematic review and meta-Analysis of CRP levels. Psychological Medicine, 49(12), 1958–1970. 10.1017/S0033291719001454 [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Osimo EF, Pillinger T, Rodriguez IM, Khandaker GM, Pariante CM, & Howes OD (2020). Inflammatory markers in depression: A meta-analysis of mean differences and variability in 5,166 patients and 5,083 controls. Brain, Behavior, and Immunity, 87(February), 901–909. 10.1016/j.bbi.2020.02.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Pace TWW, Ph D, Mletzko TC, Alagbe O, Musselman DL, Nemeroff CB, Miller AH, & Heim CM (2006). Increased stress-induced inflammatory responses in male patients with major depression and increased early life stress. American Journal of Psychiatr, 163(9), 1630–1633. [DOI] [PubMed] [Google Scholar]
  45. Pepys MB, & Hirschfield GM (2003). C-reactive protein: a critical update. Journal of Clinical Investigation, 112(2), 299–299. 10.1172/jci18921c1 [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Radloff LS (1977). The CES-D scale: A self-report depression scale for research in the general population. Applied Psychological Measurement, 1(3), 385–401. 10.1177/014662167700100306 [DOI] [Google Scholar]
  47. Shanmugan S, Loughead J, Nanga RPR, Elliott M, Hariharan H, Appleby D, Kim D, Ruparel K, Reddy R, Brown TE, & Epperson CN (2017). Lisdexamfetamine effects on executive activation and neurochemistry in menopausal women with executive function difficulties. Neuropsychopharmacology, 42(2), 437–445. 10.1038/npp.2016.162 [DOI] [PMC free article] [PubMed] [Google Scholar]
  48. Shanmugan S, Sammel MD, Loughead J, Ruparel K, Gur RC, Brown TE, Faust J, Domchek S, & Epperson CN (2020). Executive function after risk-reducing salpingo-oophorectomy in BRCA1 and BRCA2 mutation carriers: does current mood and early life adversity matter? Menopause, 27(7), 746–755. 10.1097/GME.0000000000001535 [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Smarr KL, & Keefer AL (2011). Measures of depression and depressive symptoms: Beck depression Inventory-II (BDI-II), center for epidemiologic studies depression scale (CES-D), geriatric depression scale (GDS), hospital anxiety and depression scale (HADS), and patient health Questionna. Arthritis Care & Research, 63(S11), S454 –S466. 10.1002/acr.20556 [DOI] [PubMed] [Google Scholar]
  50. Soules MR, Sherman S, Parrott E, Rebar R, Santoro NF, Utian W, & Woods NF (2001). Executive summary: Stages of Reproductive Aging Workshop (STRAW). Climacteric, 4(4), 267–272. 10.1080/cmt.4.4.267.272 [DOI] [PubMed] [Google Scholar]
  51. Troubat R, Barone P, Leman S, Desmidt T, Cressant A, Atanasova B, Brizard B, El Hage W, Surget A, Belzung C, & Camus V (2021). Neuroinflammation and depression: A review. European Journal of Neuroscience, 53(1), 151–171. 10.1111/ejn.14720 [DOI] [PubMed] [Google Scholar]
  52. Vigushin DM, Pepys MB, & Hawkins PN (1993). Metabolic and scintigraphic studies of radioiodinated human C-reactive protein in health and disease. Journal of Clinical Investigation, 91(4), 1351–1357. 10.1172/JCI116336 [DOI] [PMC free article] [PubMed] [Google Scholar]
  53. Whiteside TL (1994). Cytokines and cytokine measurements in a clinical laboratory. Clinical and Diagnostic Laboratory Immunology, 1(3), 257–260. 10.1128/cdli.1.3.257-260.1994 [DOI] [PMC free article] [PubMed] [Google Scholar]
  54. Wium-Andersen MK, Ørsted DD, Nielsen SF, & Nordestgaard BG (2013). Elevated C-reactive protein levels, psychological distress, and depression in 73131 individuals. JAMA Psychiatry, 70(2), 176–184. 10.1001/2013.jamapsychiatry.102 [DOI] [PubMed] [Google Scholar]
  55. Zalli A, Jovanova O, Hoogendijk WJG, Tiemeier H, & Carvalho LA (2016). Low-grade inflammation predicts persistence of depressive symptoms. Psychopharmacology, 233(9), 1669–1678. 10.1007/s00213-015-3919-9 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supinfo
NIHMS1929851-supplement-Supinfo.docx (24.3KB, docx)

Data Availability Statement

The datasets analyzed during the current study are available from the corresponding author upon reasonable request.

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