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# Role of early life adversities in inflammation-related neuropsychiatric comorbidity in obesity

Juliette Montet, Sandra Dexpert, Muriel Darnaudéry, Cédric Beau, Damien Forestier, Patrick Ledaguenel, Eric Magne, Bruno Aouizerate, Lucile Capuron

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## To cite this version:

Juliette Montet, Sandra Dexpert, Muriel Darnaudéry, Cédric Beau, Damien Forestier, et al., Role of early life adversities in inflammation-related neuropsychiatric comorbidity in obesity. Brain, Behavior, and Immunity, 2025, 128, pp.612 - 619. 10.1016/j.bbi.2025.04.039. hal-05215796

HAL Id: hal-05215796

https://hal.inrae.fr/hal-05215796v1

Submitted on 20 Aug 2025

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# Role of early life adversities in inflammation-related neuropsychiatric comorbidity in obesity

Juliette Montet<sup>a</sup>, Sandra Dexpert<sup>a</sup>, Muriel Darnaudéry<sup>a</sup>, Cédric Beau<sup>b</sup>, Damien Forestier<sup>b</sup>, Patrick Ledaguenel<sup>b</sup>, Eric Magne<sup>b</sup>, Bruno Aouizerate<sup>a,c</sup>, Lucile Capuron<sup>a,*</sup>

## ARTICLE INFO

### Keywords:

- Obesity

- Inflammation

- Early Life Adversities

- Trauma

- Stress

- Neuropsychiatric Symptoms

## ABSTRACT

A growing body of data highlights the key role of adiposity-related inflammation in the development of neuropsychiatric comorbidity in obesity. Nevertheless, despite similar levels of inflammation, only a subgroup of obese subjects is afflicted with neuropsychiatric symptoms, suggesting the contribution of additional vulnerability factors. In light of previous work suggesting the involvement of early life adversity (ELA), this study aims to determine whether ELA promotes the emergence of inflammation-related neuropsychiatric symptoms in a sample of obese subjects.

Eighty-two adults afflicted with obesity (BMI > 30 kg/m²) and twenty-one lean individuals (BMI < 25 kg/m²) were recruited. Depressive symptoms, fatigue and neurobehavioral symptoms were assessed through semi-structured interviews and validated self-reports. ELA was measured using the Childhood Trauma Questionnaire (CTQ). Systemic inflammation was determined through serum concentrations of high-sensitivity C-reactive protein (hsCRP).

In the whole population under study, hsCRP concentrations were significantly associated with neuropsychiatric symptoms, consistent with the increased prevalence of neuropsychiatric comorbidity in obese subjects. Significant associations were also found between ELA severity and neuropsychiatric symptoms. Although they did not influence hsCRP levels, ELA antecedents in obese subjects were associated with more marked mood, fatigue and cognitive symptoms. Among ELA, sexual abuse was the only significant predictor of the association between hsCRP levels and neuropsychiatric comorbidity in obesity. These findings support the hypothesis that ELA represents a potent vulnerability factor for the development of neuropsychiatric comorbidity in obese subjects with chronic inflammation.

## 1. Introduction

Despite active awareness campaigns, the prevalence of obesity is continuing to rise worldwide, with a 2-fold increase in the rate of adults concerned since 1990 (WHO, 2024a). This progression is of particular concern as it is associated with the emergence of a large number of non-communicable diseases, representing the leading causes of death worldwide (WHO, 2024b). This picture is even worsened by the burden of neuropsychiatric comorbidities that are frequent in obesity, encompassing symptoms of depression, anxiety, fatigue, neurocognitive and sleep alterations (Amiri & Behnezhad, 2019; Dawes et al., 2016;

Farruggia & Small, 2019; Huet et al., 2021; Lim et al., 2005; Luppino et al., 2010; Pereira-Miranda et al., 2017). In addition to significantly impair the quality of life and social/occupational function of affected individuals (Chae et al., 2022; Donini et al., 2020; Nigatu et al., 2016), the development of these comorbidities also compromises adherence to treatment and weight loss management programs (Burgess et al., 2017; Mazzeschi et al., 2012; Mendes et al., 2019; Somerset et al., 2011). Accordingly, there is an urgent need to identify the mechanisms and factors contributing to the development of neuropsychiatric comorbidities in obesity in order to propose relevant preventive and therapeutic strategies.

<footnote><sup>a</sup> Univ. Bordeaux, INRAE, Bordeaux INP, NutriNeurO, UMR 1286, Bordeaux, France</footnote>

<footnote><sup>b</sup> Service de Chirurgie Digestive et Pariétale, Clinique Tivoli, 33000 Bordeaux, and clinique Jean Villar, 33520 Bruges, France</footnote>

<footnote><sup>c</sup> CH Charles Perrens, Pôle de Psychiatrie Générale et Universitaire, Centre de référence régional des pathologies anxieuses et dépressives, Centre Expert Dépression Résistante FondaMental, Bordeaux, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>E-mail address: lucile.capuron@inrae.fr (L. Capuron).</footnote>
Research in recent years has contributed to show that inflammation plays a major role in the pathophysiology of neuropsychiatric symptoms (Capuron & Castanon, 2017; Milaneschi et al., 2021; Miller & Raison, 2016; Raison et al., 2006), notably in obesity, a fundamental inflammatory condition (Capuron et al., 2011; Capuron et al., 2017; Castanon et al., 2014; Delgado et al., 2018; Lasselin et al., 2016; Milaneschi et al., 2019). While circulating levels of inflammatory markers, including hsCRP and IL-6, were found to significantly predict the development of obesity-related neuropsychiatric comorbidities, the observation that only a subgroup of obese subjects is afflicted with these alterations suggests the involvement of additional contributing factors (Dawes et al., 2016; Duarte-Guerra et al., 2017; Galland-Decker et al., 2019; Huet et al., 2021; Prickett et al., 2015; Yang et al., 2018). Whether these factors pave the way to inflammation or act synergistically with it to cause neuropsychiatric symptoms remains to be determined.

Previous studies have shown that the sensitization of the stress response system significantly contributes to the depressogenic effects of chronic inflammation in medically ill patients (Capuron et al., 2003). In particular, the hyper-responsivity of the Hypothalamic-Pituitary-Adrenal (HPA) axis was identified as a predictive marker of vulnerability to cytokine-induced depression (Capuron et al., 2003). Consistent with this finding, comorbid depression in obesity was found to be associated with the overactivation of NFκB and Glucocorticoid Receptor (GR) signaling pathways, suggesting the interplay between the immune and stress response systems in the onset of obesity-related depressive symptoms (Moisan et al., 2021). Preclinical and clinical studies have extensively documented the involvement of early life adversities (ELA) in the development of durable HPA axis disruptions at adulthood (Danese & McEwen, 2012; Murphy et al., 2022; Tyrka et al., 2016). ELA refer to negative environmental situations experienced during childhood that deprive children of appropriate care or expose them to fear- or anxiety-provoking conditions (Herzberg & Gunnar, 2020). These events, found to sensitize the stress response system, as evidenced by increased adrenocorticotropic hormone (ACTH) and cortisol response to dexamethasone/corticotropin-releasing factor (CRF) test in subjects exposed to childhood abuse or neglect (Christine Heim et al., 2008), are associated with a greater propensity to develop depression (Heim et al., 2000). Interestingly, ELA were also shown to be associated with profound alterations of the immune system, reflected in increased expression of proinflammatory genes and enhanced levels of circulating inflammatory markers (Brown et al., 2021), correlating with neuropsychiatric symptoms (Jiang et al., 2025; Maayan & Maayan, 2024).

Altogether, these data suggest that ELA may represent one of these factors significantly contributing to the neuropsychiatric effects of inflammation in obese individuals. To assess this possibility, the present study investigated the association between ELA, chronic low-grade inflammation, and neuropsychiatric symptoms in a sample of obese subjects relatively to a group of lean/non-inflamed participants. We hypothesized i) that neuropsychiatric comorbidity correlate with systemic inflammation and thus will be overall more prevalent in obese subjects, and ii) that obese subjects with ELA will be more prone to develop such comorbidity than obese subjects free of ELA, despite similar levels of inflammation.

# 2. Methods

## 2.1. Participants

Eighty-two adult subjects with obesity (BMI > 30 kg/m²) meeting eligibility criteria for bariatric surgery were recruited in the digestive and parietal surgery departments of two private clinics (Tivoli and Jean-Villar) in Bordeaux area, France. An additional group of twenty-one lean healthy subjects (BMI between 18.5 and 25 kg/m²) was recruited through public advertisements. For all study participants, exclusion criteria were: age > 65 years old; acute or chronic inflammatory conditions (other than obesity or obesity-related comorbidities for the group

of obese subjects); current treatment with antidepressants or any other psychotropic drug; current treatment with anti-inflammatory or immunosuppressive drugs; current diagnosis of psychiatric disease (except for major depressive disorder (MDD)); and/or severe medical illness. The study was approved by the Institutional Ethics Committee for the Protection of Persons (CPP Bordeaux, France). All participants provided written informed consent after reading a complete description of the study.

## 2.2. Measurements

### 2.2.1. Clinical and neuropsychiatric assessments

Socio-demographic and clinical characteristics were collected in all participants by trained professionals through a semi-structured interview. Psychiatric antecedents, current treatments and obesity-related comorbidities, including type-2 diabetes, hypertension (HTA), dysthyroidism, obstructive sleep apnea (OSA), were reported by the patients or collected from their medical records.

Depressive symptoms were evaluated using the Montgomery-Asberg Depression Rating Scale (MADRS), a clinician administered scale of 10 items rated from 0 to 6 (Montgomery & Asberg, 1979). The MINI-International Neuropsychiatric Interview (MINI) was used for the diagnosis of current and past MDD, according to DSM-IV criteria (Sheehan et al., 1998).

The Multidimensional Fatigue Inventory (MFI) was used to assess fatigue symptoms. This 20-item self-report questionnaire evaluates five dimensions of fatigue, including general fatigue, physical fatigue, mental fatigue, reduced activity and reduced motivation. Each dimension contains four items scored from 1 to 5 (Smets et al., 1995).

General behavioral symptoms were assessed with the Neurotoxicity Rating Scale (NRS), a 39-item self-report questionnaire (Valentine et al., 1995) with items scored 0 “not present” to 4 “extremely severe”. As previously described (Huet et al., 2021), NRS items were grouped into four specific symptom dimensions for data analysis, including the dimensions of sickness (tiredness, fever, sick feeling, body aches, joint/muscle pain, headaches), cognitive symptoms (indecisiveness, distractibility, episodes of confusion, word-finding problems, memory impairment), anxiety symptoms (anxiety, tension, irritability, agitation, worries about health) and sleep problems (difficulty getting to sleep or staying asleep, sleeping too much).

### 2.2.2. Early life adversity

ELA was assessed through the short form of the Childhood Trauma Questionnaire (CTQ) (Bernstein et al., 2003), a retrospective 28-item self-report questionnaire. Each item is rated on a Likert scale ranging from 1 to 5 (1 for “never true” and 5 for “very often true”) to assess the frequency of certain events during childhood or adolescence. The questionnaire evaluates 5 subtypes of ELA: 1) emotional abuse (EA), 2) physical abuse (PA), 3) sexual abuse (SA), 4) emotional neglect (EN), and 5) physical neglect (PN). A severity score can be calculated for each subtype. The cumulative ELA severity total score is calculated by adding the scores obtained for the 5 subtypes of ELA. Subjects were classified according to the presence (ELA +) or absence (ELA-) of at least one moderate exposure in one of the subscales by creating a dichotomous variable based on the cut-off scores defined in the CTQ manual (EA ≥ 13, PA ≥ 10, SA ≥ 8, EN ≥ 15, and PN ≥ 10) (Bernstein & Fink, 1998). The CTQ also includes a minimization/denial (MD) subscale based on items 10, 16 and 21. A score of 1 is attributed when the response ‘very often true’ has been answered to these items, otherwise the score is 0. The sum of the 3 dichotomized items gives a score varying from 0 to 3. A score of 0 indicates no minimization, while a score of 1 corresponds to low minimization, 2 to intermediate minimization and 3 to high minimization (Bernstein & Fink, 1998).

### 2.2.3. Systemic inflammation

Fasting blood samples were collected in all study participants for the
measurement of serum concentrations of high-sensitivity C-reactive protein (hsCRP), a reliable marker of systemic inflammation (Felger et al., 2020). After 30–45 min at room temperature, samples were centrifuged (3200 rpm, 10 min at 4 °C), and sera were stored at –80 °C, until the assays. Serum concentrations of hsCRP were determined at the Automated Medical Biology Platform (PABiM) from Bordeaux University Hospital by quantitative immunoturbidimetry using the MULTI-GENT CRP Vario assay on ARCHITECT cSystems analyzers (C8200 and C16000) according to manufacturer's instructions.

## 2.3. Statistical analysis

For all analyses, raw values of serum hsCRP concentrations were log transformed due to non-normality of the distribution as assessed by Shapiro-Wilk test. Extreme values for hsCRP (>3SD above the mean) were obtained in two participants, and were therefore considered outliers and excluded from analyses on this variable. Of note, data regarding past MDD were missing in four participants. Sociodemographic, medical, neuropsychiatric and ELA-related variables were compared between groups using Student's t-tests, ANOVAs or ANCOVAs controlling for age, sex and obesity-related comorbidities for continuous variables, followed by post-hoc Tukey's comparisons when appropriate. Categorical variables were compared by chi-squared test (χ²) or Fisher's exact test when adequate.

A principal component analysis was performed in the whole population under study to extract a general neuropsychiatric comorbidity factor score, which encapsulates the total MADRS score, the five MFI dimensions, and the four NRS dimensions. Subjects were stratified on the basis of this score, with positive scores corresponding to the presence of neuropsychiatric comorbidity (Huet et al., 2021). Linear regression models were used to assess the relationship between BMI, hsCRP, CTQ scores and the neuropsychiatric comorbidity factor score in the population as a whole and in the obese subject subgroups. The moderating effects of ELA (CTQ total score and dimensions) on the relationship between hsCRP and the neuropsychiatric comorbidity factor score were examined using the moderation regression model available in Hayes' PROCESS macro v4.2 in SPSS v29 (Rockwood & Hayes, 2020). Regressions models included age, sex and obesity-related comorbidities as covariates. Statistical analyses were performed with SPSS statistics, version 29. All probabilities were two-tailed, with the level of significance set at p < 0.05.

# 3. Results

## 3.1. Characteristics of study participants

Characteristics of study participants are described in Table 1. There were no age or sex differences between the groups of lean and obese subjects (p = 0.849 and p > 0.99, respectively). In the whole population, 85.44 % were women, with a mean age of 38 years. The prevalence of obesity-related comorbidities, notably hypertension and OSA, was higher in obese subjects (p = 0.037 and p < 0.001, respectively). Antecedents of depression were similar in both groups (p = 0.853). Overall, obese subjects exhibited more severe neuropsychiatric symptoms than lean subjects, as indicated by greater MADRS, MFI and NRS total scores (all p < 0.001). The detailed comparison of neuropsychiatric symptoms between groups is shown in Supplementary Table S1. Overall, obese subjects exhibited higher scores of lassitude, pessimistic thoughts, and suicidal thoughts on the MADRS scale (p = 0.028; p < 0.001; p = 0.007, respectively). These subjects also showed greater symptoms of general fatigue, physical fatigue and reduced activity on the MFI scale (p = 0.006; p < 0.001; p = 0.018, respectively), together with symptoms of altered sleep, sickness and anxiety on the NRS scale (p = 0.003; p < 0.001; p < 0.001, respectively). Among obese subjects, 7.32 % met criteria for MDD at the time of the study. As expected, levels of systemic inflammation, reflected in hsCRP serum concentrations, were higher in

<table><caption>**Table 1**

Characteristics of study participants.</caption><thead><tr><th></th><th>Lean subjects</th><th>Obese subjects</th><th>p</th></tr></thead><tbody><tr><td>Sample size, n</td><td>21</td><td>82</td><td></td></tr><tr><td>Age, years (SD)</td><td>38.67<br>(8.28)</td><td>38.18<br>(10.79)</td><td>0.849</td></tr><tr><td>Females, n (%)</td><td>18 (85.7)</td><td>70 (85.4)</td><td>&gt;0.99</td></tr><tr><td>BMI, kg/m<sup>2</sup> (SD)</td><td>21.75<br>(1.47)</td><td>40.44 (5.10)</td><td>&lt;0.001</td></tr><tr><td>Weight, kg (SD)</td><td>59.75<br>(7.90)</td><td>110.66<br>(18.45)</td><td>&lt;0.001</td></tr><tr><td><strong>Inflammation</strong></td><td></td><td></td><td></td></tr><tr><td>hsCRP, mg/L (SD)</td><td>0.57 (0.35)</td><td>7.18 (4.72)</td><td>&lt;0.001</td></tr><tr><td><strong>Obesity-related comorbidities</strong></td><td></td><td></td><td></td></tr><tr><td>Hypertension, n (%)</td><td>0</td><td>15 (18.3)</td><td>0.037</td></tr><tr><td>Type-2 diabetes, n (%)</td><td>0</td><td>5 (6.1)</td><td>0.580</td></tr><tr><td>Dysthyroidism, n (%)</td><td>0</td><td>5 (6.1)</td><td>0.580</td></tr><tr><td>Obstructive sleep apnea, n (%)</td><td>0</td><td>45 (54.9)</td><td>&lt;0.001</td></tr><tr><td><strong>Neuropsychiatric profile</strong></td><td></td><td></td><td></td></tr><tr><td>Depressive symptoms (MADRS total score (SD))</td><td>2.10 (2.53)</td><td>6.93 (5.79)</td><td>&lt;0.001</td></tr><tr><td>Fatigue (MFI total score (SD))</td><td>34.76<br>(10.56)</td><td>50.30<br>(14.30)</td><td>&lt;0.001</td></tr><tr><td>General behavioral symptoms (NRS total score (SD))</td><td>12.86<br>(10.05)</td><td>36.04<br>(20.36)</td><td>&lt;0.001</td></tr><tr><td>Current MDD, n (%)</td><td>0 (0)</td><td>6 (7.32)</td><td>0.342</td></tr><tr><td>History of MDD, n (%)</td><td>8 (38.1)</td><td>28 (35.9)</td><td>0.853</td></tr><tr><td><strong>Childhood adversity</strong></td><td></td><td></td><td></td></tr><tr><td>Childhood adversity exposure, n (%)</td><td>7 (33.33)</td><td>38 (46.30)</td><td>0.284</td></tr><tr><td>CTQ scores</td><td></td><td></td><td></td></tr><tr><td>Emotional abuse</td><td>10.14<br>(6.00)</td><td>9.37 (4.52)</td><td>0.514</td></tr><tr><td>Physical abuse</td><td>6.24 (2.21)</td><td>6.96 (3.90)</td><td>0.416</td></tr><tr><td>Sexual abuse</td><td>6.05 (2.82)</td><td>6.85 (4.32)</td><td>0.423</td></tr><tr><td>Emotional neglect</td><td>10.90<br>(4.38)</td><td>12.53 (5.23)</td><td>0.192</td></tr><tr><td>Physical neglect</td><td>6.43 (1.75)</td><td>7.76 (3.19)</td><td>0.068</td></tr><tr><td>CTQ total score</td><td>39.76<br>(14.66)</td><td>43.47<br>(16.88)</td><td>0.359</td></tr><tr><td>Minimization/denial subscale</td><td></td><td></td><td></td></tr><tr><td>No, n (%)</td><td>15 (71.43)</td><td>55 (67.07)</td><td>0.703</td></tr><tr><td>Low, n (%)</td><td>3 (14.29)</td><td>13 (15.85)</td><td>&gt;0.99</td></tr><tr><td>Intermediate, n (%)</td><td>2 (9.52)</td><td>6 (7.32)</td><td>0.664</td></tr><tr><td>High, n (%)</td><td>1 (4.76)</td><td>8 (9.76)</td><td>0.682</td></tr><tr><td colspan="4">Continuous variables are presented as mean and standard deviation and compared using Student's t-test, whereas categorical variables are presented as n (%) and compared by chi-squared test or Fisher's exact test when 25 % or more of the observations had an expected frequency of five or less. Abbreviations: BMI, body mass index; CTQ, Childhood Trauma Questionnaire; hsCRP, high-sensitivity C-reactive Protein; MADRS, Montgomery Asberg Depression Rating Scale; MFI, Multidimensional Fatigue Inventory; MDD, Major Depressive Disorder; NRS, Neurotoxicity Rating Scale; SD, standard deviation.</td></tr></tbody></table>

obese subjects compared to lean participants (p < 0.001). Of note, all lean participants exhibited levels of hsCRP below 1.50 mg/L (hsCRP < 1 mg/L: 80.95 % and 1 < hsCRP > 1.5 mg/L: 19.05 %), confirming the absence of low-grade inflammation in this group (Osimo et al., 2019). No significant difference was found between obese and lean subjects with respect to ELA antecedents, either on the CTQ total score (p = 0.359) or on CTQ dimensions (EA, p = 0.514; PA, p = 0.416; SA; p = 0.423; EN, p = 0.192; PN, p = 0.068). Based on the classification described above, 33.33 % of lean subjects were considered as having being exposed to ELA, against 46.31 % in obese subjects (χ²(1) = 1.150, p = 0.284). Among lean participants, 28.57 % (n = 6) of the subjects displayed minimization compared with 32.93 % (n = 27) of the obese subjects (χ²(1) = 0.146, p = 0.703).

## 3.2. Neuropsychiatric comorbidity is more prevalent in obese subjects and relate to systemic inflammation and ELA in the whole population

In the whole population under study, a PCA was performed on neuropsychiatric scores to extract a computed score of neuropsychiatric
comorbidity. Consistent with earlier findings showing strong inter-relationships between individual neuropsychiatric symptoms (Huet et al., 2021), the analysis extracted one single factor explaining 57.22 % of the variance. As expected, the prevalence of neuropsychiatric comorbidity, reflected in a positive score on the identified factor, was significantly higher in obese subjects, with 54.87 % of individuals concerned compared to 19.05 % in the group of lean participants ($\chi^2(1) = 8.606, p = 0.003$) (Fig. 1A). Congruent with this, BMI predicted significantly the neuropsychiatric comorbidity factor score, when the model was adjusted for age, sex and obesity-related comorbidities ($\beta = 0.237, p = 0.022$) (Table 2). In line with the inflammatory characteristic of obesity, scores on the neuropsychiatric comorbidity factor were also highly correlated to hsCRP levels in the whole population under study ($\beta = 0.446, p < 0.001$) (Fig. 1B). This association remained highly significant after adjustment for age, sex and obesity-related comorbidities ($\beta = 0.367, p < 0.001$) (Table 2). While the relationship between hsCRP and neuropsychiatric comorbidity also remained when the analysis controlled for BMI ($\beta = 0.350, p = 0.019$), the association of BMI and the neuropsychiatric comorbidity factor score did not significantly persist after adjustment for hsCRP ($\beta = 0.023, p = 0.868$), suggesting that this relationship was mediated by hsCRP levels (Table 2). In the whole population under study, the CTQ total score also predicted the neuropsychiatric comorbidity factor score ($\beta = 0.290, p = 0.003$) before (Fig. 1C) and after adjustment for age, sex and obesity-related comorbidities ($\beta = 0.250, p = 0.008$) (Table 2). Hierarchical linear regression indicated that the inclusion of the CTQ total score variable in addition to hsCRP significantly improved the ability of the model to predict neuropsychiatric comorbidity ($R^2$ variation = 0.081, $p = 0.001$). In this model, both hsCRP ($\beta = 0.407, p < 0.001$) and CTQ total score ($\beta = 0.291, p = 0.001$) were significantly associated with the neuropsychiatric comorbidity factor score (Table 2).

### 3.3. ELA enhance the risk of neuropsychiatric comorbidity in obese individuals, independently of systemic inflammation levels

Although no difference in hsCRP concentrations were found between obese subjects with or without ELA ($p = 0.520$) (Fig. 2A), obese subjects with ELA (ELA+) exhibited greater neuropsychiatric comorbidity scores compared to obese subjects with no history of ELA (ELA-) ($p = 0.034$) (Fig. 2B). Accordingly, the prevalence of neuropsychiatric comorbidity was higher in ELA+ obese subjects compared to ELA- obese subjects,

<caption>**Table 2**</caption>

Respective contribution of BMI, hsCRP and CTQ total score to the neuropsychiatric comorbidity factor score in the whole population under study.

<table><thead><tr><th rowspan="2">Model</th><th rowspan="2">Predictors</th><th colspan="2">Neuropsychiatric comorbidity factor score</th></tr><tr><th>Coefficients<br>β</th><th>Sig.</th></tr></thead><tbody><tr><td>1</td><td>BMI</td><td>0.237</td><td>0.022</td></tr><tr><td>2</td><td>hsCRP</td><td>0.367</td><td>&lt;0.001</td></tr><tr><td rowspan="2">3</td><td>BMI</td><td>0.023</td><td>0.868</td></tr><tr><td>hsCRP</td><td>0.350</td><td>0.019</td></tr><tr><td>4</td><td>CTQ total score</td><td>0.250</td><td>0.008</td></tr><tr><td rowspan="2">5</td><td>hsCRP</td><td>0.407</td><td>&lt;0.001</td></tr><tr><td>CTQ total score</td><td>0.291</td><td>0.001</td></tr></tbody><tfoot><tr><td colspan="4">Analyses were performed using multiple regression analyses adjusted for age, sex and obesity-related comorbidities. Analyses were performed using log-transformed hsCRP values. Abbreviations: BMI: body mass index; CTQ: Childhood Trauma Questionnaire; hsCRP: high-sensitivity C-reactive protein.</td></tr></tfoot></table>

albeit only reaching statistical trend (65.8 % vs. 45.5 %, $\chi^2(1) = 3.405, p = 0.065$) (Fig. 2C). In line with these findings, the CTQ total score was significantly associated with the comorbidity neuropsychiatric factor score in obese subjects ($\beta = 0.289, p = 0.008$), regardless of hsCRP levels ($\beta = 0.319, p = 0.006$) (Supplementary Table 2). To assess the possibility of specificities according to symptom dimensions, MFI, NRS and MADRS scores were compared between obese subjects with or without ELA. Results indicated greater total MADRS scores ($t(80) = 2.606, p = 0.011$), and in the specific MADRS items of reported sadness ($t(80) = 2.900, p = 0.005$), reduced sleep ($t(80) = 2.636, p = 0.010$), concentration difficulties ($t(80) = 2.696, p = 0.009$) and lassitude ($t(80) = 2.154, p = 0.034$), in ELA+ obese. These differences remained significant after adjustment for age, sex and obesity-related comorbidities. Similarly, MFI fatigue scores, particularly in the dimensions of mental fatigue ($t(80) = 3.084, p = 0.003$) and reduced activity ($t(80) = 2.294, p = 0.024$), and NRS scores, notably related to cognitive alterations ($t(80) = 3.063, p = 0.003$), were increased in ELA+ obese subjects. These differences survived statistical adjustment for age, sex and obesity-related comorbidities (Table 3).

### 3.4. ELA modulate the relationship between systemic inflammation and neuropsychiatric comorbidity in obesity

Moderation analyses were conducted to examine whether ELA

<figure><img src="image_5.png" /><figcaption>**Fig. 1.** Neuropsychiatric comorbidity and its relationship with hsCRP levels and CTQ total scores in the whole population. Panel A: Prevalence of neuropsychiatric comorbidity in obese subjects (N = 82; blue bar) versus lean controls (N = 21; grey bar). Data are shown as percentage, and compared by $\chi^2$ test. **$p < 0.01$**. Panel B: Relationship between hsCRP levels and the neuropsychiatric comorbidity factor score in the whole population (grey dot: lean controls; blue dot: obese subjects), assessed by linear regression model. Panel C: Relationship between the CTQ total score and the neuropsychiatric comorbidity factor score in the whole population (grey dot: lean controls; blue dot: obese subjects), assessed by linear regression model. Abbreviations: hsCRP; high-sensitivity C-reactive Protein; CTQ: Childhood Trauma Questionnaire.</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>**Fig. 2.** High-sensitivity CRP levels, neuropsychiatric comorbidity score and prevalence in lean controls and obese subjects with and without early life adversity. Panel A: Serum levels of hsCRP levels in lean controls (N = 21, grey bar), obese subjects without antecedents of early life adversity (ELA-; N = 44; light blue bar), and obese subjects with antecedents of early life adversity (ELA+, N = 38; dark blue bar). Data are shown as mean (±SEM), and individual data, and compared by ANOVA, followed by Tukey's multiple comparisons as post-hoc tests. \*\*\*\*p < 0.0001; ns: non-significant. Panel B: Neuropsychiatric comorbidity factor scores in lean controls (N = 21, grey bar), obese subjects without antecedents of early life adversity (ELA-; N = 44; light blue bar), and obese subjects with antecedents of early life adversity (ELA+, N = 38; dark blue bar). Data are shown as mean (±SEM), and individual data, and compared by ANOVA, followed by Tukey's multiple comparisons as post-hoc tests. \*p < 0.05, \*\*\*\*p < 0.001, \*\*\*\*\*p < 0.0001. Panel C: Prevalence of neuropsychiatric comorbidity in lean controls (grey bar; 19.05 %);, obese subjects without antecedents of early life adversity (ELA-, light blue bar; 45.5 %), and obese subjects with antecedents of early life adversity (ELA+, dark blue bar; (65.8 %). Data are shown as percentage, and compared by $\chi^2$ test. \*p < 0.05, \*\*\*\*p < 0.001.</figcaption></figure>

<caption>**Table 3**</caption>

Comparison of neuropsychiatric symptom scores in obese subjects with (ELA+) or without (ELA-) antecedents of early life adversity.

<table><thead><tr><th></th><th>ELA-</th><th>ELA+</th><th>p1</th><th>p2</th></tr></thead><tbody><tr><td>Sample size, n</td><td>44</td><td>38</td><td></td><td></td></tr><tr><td><strong>MADRS</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>MADRS total score (SD)</td><td>5.43 (4.64)</td><td>8.66 (6.52)</td><td>0.011</td><td>0.016</td></tr><tr><td>1. Apparent sadness</td><td>0.34 (0.64)</td><td>0.58 (0.86)</td><td>0.156</td><td>0.197</td></tr><tr><td>2. Reported sadness</td><td>0.36 (0.75)</td><td>0.95 (1.06)</td><td>0.005</td><td>0.011</td></tr><tr><td>3. Inner tension</td><td>0.89 (1.04)</td><td>0.89 (1.01)</td><td>0.971</td><td>0.940</td></tr><tr><td>4. Reduced sleep</td><td>0.52 (1.09)</td><td>1.18 (1.18)</td><td>0.010</td><td>0.009</td></tr><tr><td>5. Reduced appetite</td><td>0.14 (0.51)</td><td>0.16 (0.68)</td><td>0.870</td><td>0.962</td></tr><tr><td>6. Concentration difficulties</td><td>0.25 (0.69)</td><td>0.76 (1.02)</td><td>0.009</td><td>0.011</td></tr><tr><td>7. Lassitude</td><td>0.48 (0.88)</td><td>1.03 (1.40)</td><td>0.034</td><td>0.049</td></tr><tr><td>8. Inability to feel</td><td>0.36 (0.78)</td><td>0.66 (1.15)</td><td>0.173</td><td>0.255</td></tr><tr><td>9. Pessimistic thoughts</td><td>1.73 (1.04)</td><td>1.89 (1.18)</td><td>0.497</td><td>0.524</td></tr><tr><td>10. Suicidal thoughts</td><td>0.36 (0.57)</td><td>0.55 (0.69)</td><td>0.178</td><td>0.207</td></tr><tr><td><strong>MFI</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>MFI total score (SD)</td><td>47.14 (13.36)</td><td>53.96 (14.64)</td><td>0.030</td><td>0.064</td></tr><tr><td>General fatigue</td><td>12.00 (4.26)</td><td>13.36 (3.54)</td><td>0.124</td><td>0.230</td></tr><tr><td>Physical fatigue</td><td>12.82 (4.09)</td><td>13.53 (3.43)</td><td>0.402</td><td>0.578</td></tr><tr><td>Mental fatigue</td><td>6.66 (3.05)</td><td>8.95 (3.67)</td><td>0.003</td><td>0.006</td></tr><tr><td>Reduced activity</td><td>8.32 (2.94)</td><td>10.03 (3.80)</td><td>0.024</td><td>0.046</td></tr><tr><td>Reduced motivation</td><td>7.34 (2.96)</td><td>8.11 (3.33)</td><td>0.275</td><td>0.345</td></tr><tr><td><strong>NRS</strong></td><td></td><td></td><td></td><td></td></tr><tr><td>NRS total score (SD)</td><td>32.11 (18.29)</td><td>40.59 (21.89)</td><td>0.060</td><td>0.077</td></tr><tr><td>Cognitive alterations</td><td>2.19 (2.43)</td><td>4.54 (4.37)</td><td>0.003</td><td>0.006</td></tr><tr><td>Altered Sleep</td><td>3.58 (2.53)</td><td>3.96 (2.53)</td><td>0.499</td><td>0.602</td></tr><tr><td>Sickness symptoms</td><td>9.61 (5.02)</td><td>10.05 (3.98)</td><td>0.666</td><td>0.661</td></tr><tr><td>Anxiety</td><td>5.42 (2.88)</td><td>6.64 (3.47)</td><td>0.085</td><td>0.127</td></tr></tbody><tfoot><tr><td colspan="5">Data are presented as mean and standard deviation and compared using Student's t-test (p1) or ANCOVA controlling for age, sex and obesity-related comorbidities (p2). Abbreviations: ELA, Early life adversity; MADRS, Montgomery Asberg Depression Rating Scale; MFI, Multidimensional Fatigue Inventory; NRS, Neurotoxicity Rating Scale; SD, standard deviation.</td></tr></tfoot></table>

influenced the relationship between systemic inflammation and neuropsychiatric comorbidity in obese subjects. As shown in **supplementary Table 3**, the CTQ total score did not moderate the association between serum hsCRP levels and the neuropsychiatric comorbidity factor score

($\Delta R^2$ = 0.0156, F(1,73) = 1.370, p = 0.245). However, when specific CTQ dimensions were assessed as potential moderators, sexual abuse was found to significantly moderate the association of hsCRP with the neuropsychiatric factor score ($\Delta R^2$ = 0.069, F(1,73) = 5.920, p = 0.017). This effect was not measured with other CTQ dimensions. In line with this, a significant relationship between hsCRP and the neuropsychiatric comorbidity factor score was found in obese subjects with a history of sexual abuse (Sexual abuse history: $\beta$ = 0.562, p = 0.029) but not in those without (No sexual abuse history: $\beta$ = 0.012, p = 0.922) (Fig. 3).

## 4. Discussion

Although inflammation has repeatedly been shown to promote the

<figure><img src="image_7.png" /><figcaption>**Fig. 3.** Relationship between serum levels of hsCRP and the neuropsychiatric comorbidity factor score in obese subjects with (SA+; green dots) or without (SA-; grey dots) sexual abuse history. Simple linear regressions were performed on log-transformed hsCRP values. Abbreviations: hsCRP: high-sensitivity C-reactive protein; SA: Sexual Abuse.</figcaption></figure>
development of neuropsychiatric symptoms, the observation that only a
subset of patients exhibits these symptoms in the presence of inflam-
mation suggests the contribution of facilitating or predisposing factors.
In the present study, we assessed the potential role of ELA in paving the
way to inflammation-related neuropsychiatric comorbidity in subjects
afflicted with obesity.

In line with previous reports, neuropsychiatric symptoms, including
depressive, fatigue and cognitive symptoms, correlated with levels of
systemic inflammation in the whole population under study, and were
thus highly prevalent in obese subjects (54.87 % against 19.05 % in lean
controls) (Callaghan et al., 2020; Delgado et al., 2018; Evangelou et al.,
2019; Huet et al., 2021). Moreover, and as expected, both hsCRP levels
and ELA independently predicted neuropsychiatric comorbidity in the
population as a whole, supporting further the complex interplay be-
tween biological and environmental factors in mental health outcomes.

In the obese population, levels of systemic inflammation were com-
parable across subjects with or without ELA. Nevertheless, antecedents
of ELA in this population were associated with greater neuropsychiatric
symptoms, supporting the mediating and contributory role of early life
stress on inflammation-related neuropsychiatric comorbidity in obesity.
To our knowledge, our study is the first to identify ELA as a potent
vulnerabilizing factor for the depressogenic effects of inflammation in
obesity. This finding is consistent with previous reports in clinical set-
tings showing that the sensitization of the stress response system, likely
related to early life or chronic stress, represents a reliable vulnerability
marker of inflammation-related neuropsychiatric symptoms, including
depression (Capuron et al., 2003; Kuhlman et al., 2020; Miller et al.,
2024; Miller & Cole, 2012). Interestingly, while hsCRP levels did not
gradually influence neuropsychiatric symptoms in the overall inflamed
obese population, a significant association between hCRP and neuro-
psychiatric comorbidity was found only in obese subjects with a history
of sexual abuse. This result suggests a potential modulation of systemic
inflammation by sexual abuse, in line with previous reports document-
ing significant relationship between this type of ELA and circulating
levels of pro-inflammatory markers in patients with mood and anxiety
disorders (Grosse et al., 2016; Quagliato & Nardi, 2023). Larger in-
vestigations are needed to further address this association.

Noteworthy, 46.3 % of obese subjects presented at least one
dimension of ELA of moderate severity, a finding consistent with pre-
vious research on obese samples awaiting bariatric surgery (Konrad
et al., 2023). This high prevalence of ELA antecedents in obese subjects
stretches the possibility that ELA represents a potent risk factor for the
development of obesity. This notion is in line with recent *meta*-analyses
showing that individuals with ELA are at higher risk of lifetime over-
weight or obesity (Doom et al., 2023; Wimmelmann et al., 2024; Wiss &
Brewerton, 2020). Additionally, our results indicate that ELA may also
contribute to obesity-related neuropsychiatric complications. The two
phenomena are not exclusive, as ELA could facilitate systemic inflam-
mation by promoting overweight/obesity, which in turn could
contribute to the emergence of neuropsychiatric symptoms (Zagaria
et al., 2024). This possibility is consistent with recent findings showing
indirect associations between ELA and circulating inflammatory
markers through changes in BMI over time (Hall et al., 2024). In the
present study, no significant relationship was found between ELA and
hsCRP levels, possibly due to the limited BMI/inflammation range
among obese subjects. However, comparable levels of hsCRP in ELA+
vs. ELA- obese subjects do not rule out the possibility that ELA activates
different inflammatory signal cascades that are not reflected in periph-
eral inflammatory markers, such as hsCRP. This scenario is supported by
a recent study showing increased NF-κB gene expression, in the absence
of difference in hsCRP levels, in pregnant women with ELA compared to
women free of ELA (Méndez Leal et al., 2023). Similarly, increased
expression of genes related to NFkB and GR signaling pathways were
reported in obese subjects with comorbid MDD compared to obese
subjects free of depression, despite equivalent serum levels of hsCRP in
the two groups (Moisan et al., 2021). This result highlights the

possibility that adiposity-driven inflammation triggers the HPA axis,
which upregulates inflammatory signaling pathways in ELA subjects,
due to impaired negative feedback, contributing thus to the develop-
ment of neuropsychiatric symptoms. Further research is needed to test
this hypothesis.

A better knowledge of the profile of patients at risk for neuropsychiatric symptoms in the obese population is crucial to improve treatment options, since overweight or obesity was found to be associated with antidepressant non-response in 75 % of studies (Puzhko et al., 2020). Accordingly, our results suggest that ELA may represent critical factors for the risk of obesity-related neuropsychiatric comorbidity, and should be considered in clinical practice for the development of targeted preventive strategies. Moreover, and relevant to the treatment of obesity, taking into account antecedents of ELA in obese subjects appears further justified, especially in light of recent reports studies documenting associations with bariatric surgery outcomes. Specifically, obese individuals with a history of ELA were found to exhibit higher depressive symptoms following surgery (Konrad et al., 2023) and an increased risk of psychiatric hospitalization 2 years after, notably in those with antecedents of sexual abuse (Clark et al., 2007).

Our study includes several limitations that should be considered in
future investigations. Since the obese population included in the study
was enrolled in a bariatric surgery program, and thus was not supposed
to present current severe MDD before surgery (HAS & FFN, 2024), the
actual sample might not be representative of the general obese popu-
lation, which was found to be more largely afflicted with MDD in pre-
vious reports (Blasco et al., 2020). Furthermore, because of these
recruitment characteristics, the present study primarily focused on cases
of severe obesity and future research is needed to extend these findings
to lower grades of obesity, including overweight. In addition, the
different proportion of obese cases and lean controls may represent one
statistical limitation of the study that should be addressed in further
studies by including groups with similar sample sizes. Finally, despite
hsCRP represents currently the most widely used biomarker to charac-
terize systemic inflammation in relation to mental health outcomes
(Felger et al., 2020), further investigations are needed to investigate the
role of other inflammatory factors and precisely determine how ELA
might influence inflammatory pathways to promote or exacerbate
neuropsychiatric comorbidities in obesity. More mechanistic studies are
also warranted to further determine the causality and sequence of
events.

In conclusion, our results comfort the role of inflammatory processes
in the development of neuropsychiatric symptoms in obese individuals,
and identify ELA, notably sexual abuse, as potent mediatory risk factors
for these alterations. These findings highlight the strong interplay be-
tween chronic systemic inflammation and ELA in obesity-related
neuropsychiatric comorbidity.

CRediT authorship contribution statement

**Juliette Montet:** Writing – original draft, Visualization, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation.
**Sandra Dexpert:** Resources, Project administration, Investigation, Data curation. **Muriel Darnaudéry:** Writing – review & editing, Methodology, Conceptualization. **Cédric Beau:** Writing – review & editing, Resources, Investigation. **Damien Forestier:** Writing – review & editing, Resources, Investigation. **Patrick Ledaguene:** Writing – review & editing, Resources, Investigation. **Eric Magne:** Writing – review & editing, Resources, Investigation. **Bruno Aouizerate:** Writing – review & editing, Supervision, Methodology, Conceptualization. **Lucile Capuron:** Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Resources, Project administration, Methodology, Funding acquisition, Formal analysis, Data curation, Conceptualization.
## Funding

This work was supported by funds from the Fondation pour la Recherche Médicale (FRM) (ENV202003011543, Dr Capuron; and FDT202404018149, J Montet), the French National Research Agency, ANR (ANR-11-JSV1-0006, Dr Capuron), the National Research Institute for Agriculture, Food and Environment (INRAE), and the University of Bordeaux.

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgments

The authors thank Dr M. Salzmann-Lovato, Dr C. Duvivier, and medical assistants for their continued help with patients' recruitment.

## Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.bbi.2025.04.039.

## Data availability

Data will be made available on request.

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