Increased plasma levels of neuro-related proteins in patients with stress-related exhaustion: A longitudinal study

Exhaustion disorder (ED) is a stress-related disorder characterized by physical and mental symptoms of exhaustion. Recent data suggest that pathophysiological processes in the central nervous system are involved in the biological mechanisms underlying ED. The aims of this study were to investigate if plasma levels of neuro-related proteins differ between patients with ED and healthy controls, and, if so, to investigate if these differences persist over time. Using the Olink Neuro Exploratory panel, we quantified the plasma levels of 92 neuro-related proteins in 163 ED patients at the time of diagnosis (baseline), 149 patients at long-term follow-up (7 – 12 years later, median follow-up time 9 years and 5 months), and 100 healthy controls. We found that the plasma levels of 40 proteins were significantly higher in the ED group at baseline compared with the control group. Out of these, the plasma levels of 36 proteins were significantly lower in the ED group at follow-up compared with the same group at baseline and the plasma levels of four proteins did not significantly differ between the groups. At follow-up, the plasma levels of two proteins were significantly lower in the ED group compared with the control group. These data support the hypothesis that pathophysiological processes in the central nervous system are involved in the biological mechanisms underlying ED.


Introduction
Stress-related exhaustion is an increasing problem in many countries and is now one of the main causes of long-term sick leave in Sweden (Försäkringskassan The Swedish Social Insurance Agency, 2020;Grossi et al., 2015).However, different terms to describe the stress-related exhaustion are used in different countries.A commonly used term is burnout, defined by Maslach and co-workers as a psychological syndrome with exhaustion, cynicism, and inefficacy as the core dimensions (Maslach et al., 2001).As burnout is not a clinical diagnosis, the term clinical burnout has been proposed to describe clinically significant burnout (Grossi et al., 2015).In 2003, the term exhaustion disorder (ED) was introduced in Sweden.ED is a stress-induced disorder characterized by physical and mental symptoms of exhaustion, markedly reduced mental energy, memory impairment, sleep disturbance, emotional instability, and intolerance to stress (National Board of Health and Welfare, 2003).The diagnostic criteria were established by the Swedish National Board of Health and Welfare in 2003 and ED was assigned the code F43.8A in the Swedish version of ICD-10.The symptoms of ED and burnout are overlapping and most patients with ED also have high burnout scores (Jonsdottir et al., 2009).In addition, comorbidity with anxiety and depression is high (Glise et al., 2012).One of the cardinal symptoms of ED is impaired cognitive function and studies have shown that ED is associated with cognitive impairment across multiple cognitive domains (Gavelin et al., 2022).In addition, patients with ED report high levels of mental fatigue during cognitive tasks (Gavelin et al., 2023).Studies investigating the course of illness have found that the symptoms of ED can be long-lasting.Almost half of the former ED patients report problems with memory and extreme fatigue 7 years after receiving the diagnose, 73 % report reduced stress tolerance (Glise et al., 2020), 68 % report difficulties related to learning and memory, and 59 % report difficulties related to general/executive cognitive function (Ellbin et al., 2021).Yet, the biological mechanisms underlying these symptoms remains to be elucidated.
Due to the important role of the hypothalamus-pituitary-adrenal (HPA) axis in acute stress reactions, most studies investigating biological mechanisms underlying ED and burnout have focused on dysregulation of the HPA axis, but no firm conclusion regarding the role of the HPA axis can be drawn (Jonsdottir and Sjors Dahlman, 2019).Instead, we have found neurofilament light (NfL), a marker of axonal injury, and glial fibrillary acidic protein (GFAP), a marker of astrocytic activation, to be increased in patients with ED compared with controls (Hansson et al., 2022).Moreover, the neurotrophic factor brain-derived neurotrophic factor (BDNF) has been found to be decreased in patients with ED compared with controls (Sjors Dahlman et al., 2019).Supported by the cognitive symptomatology, these findings suggest that pathophysiological processes in the central nervous system are involved in the biological mechanisms underlying ED.Therefore, in the present study, we have expanded our previous investigations by using a panel of neuro-related proteins, involved in e.g., cell communication, regulation of cellular processes, cell differentiation and neurogenesis.
The aims of this study were firstly to investigate if plasma levels of neuro-related proteins differ between patients with ED and healthy controls, secondly to investigate if these differences persist over time, and thirdly to investigate if plasma levels of neuro-related proteins change over time among patients with ED.

Study population
This study is part of a longitudinal study conducted at the Institute of Stress Medicine (ISM), which is a specialist outpatient clinic for patients with ED, located in Gothenburg, Sweden.The patients were referred to ISM from primary care units or occupational health care centers.All patients included in the study were judged by a senior physician at the clinic to fulfil the criteria for ED (Table 1), and hence diagnosed with ED at their first visit to the clinic (baseline).According to the diagnostic criteria, patients with other medical conditions that could explain the fatigue were excluded.So were also patients with alcohol or drug abuse and patients with psychiatric illness other than depression and anxiety.Depression and anxiety were assessed using the Primary Care Evaluation of Mental Disorders (PRIME-MD) instrument (Spitzer et al., 1994).Before consulting the physician, the patient completed a one-page PRIME-MD patient questionnaire that covers questions on somatic as well as mental symptoms.Affirmative responses were followed-up by the physician in a structured interview conforming to the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fourth Revision, for diagnostic assessment of depression and anxiety disorder.The diagnostic procedure has been described in detail previously (Glise et al., 2012).To be included in the study, patients should not have been on sick leave for more than 6 months.The treatment at ISM lasted for approximately 18 months and has been described in detail previously (Glise et al., 2012).In brief, the patients were offered a stress-reduction program, physical exercise, and monthly visits with the physician.Cognitive behavioral group therapy for insomnia, individual psychotherapy, and/or antidepressant medication was offered when needed.Also, communication with the Social Insurance Office and the employer was facilitated.Following treatment at the clinic, all patients that had passed seven years or more since their first visit to the clinic (n=353) were invited to participate in a follow-up clinical assessment, including assessment of residual stress-related exhaustion.Out of these, 163 patients accepted to participate in the follow-up clinical assessment.These constitute the patient group at baseline.The patients that agreed to participate (n=163) were significantly older at baseline (mean age 44 years, SD 9.6) than the patients that were eligible, but did not agree to participate or did not answer the invitation (drop-out group, n=190) (mean age 41 years, SD 9.0, p=0.003).There were also significantly more women in the participating group (77 %) than in the drop-out group (67 %, p=0.041).The groups did not differ at baseline regarding self-reported symptoms of burnout, anxiety, or depression.At the follow-up clinical assessment of the 163 former patients, 51 patients still fulfilled the diagnostic criteria for ED, whereas 99 patients no longer fulfilled the criteria for ED and were thus considered recovered (Glise et al., 2020).These 150 patients, which were either fulfilling or not fulfilling the diagnostic criteria for ED at follow-up, constitute the patient group at follow-up.Out of the 163 former patients, 13 patients had developed other conditions that could explain the fatigue and as they had other diseases that could affect the results of the study, they were excluded from the follow-up group.The healthy controls were recruited from advertisement in newspapers, in social media, and at the region's intranet.The inclusion criteria for the healthy control group were 1) healthy, and 2) 20-50 years of age.The exclusion criteria were 1) self-rated exhaustion disorder; 2) somatic or psychiatric disease; 3) pregnancy or lactation; 4) overconsumption of alcohol.Hence, the study population consisted of 100 healthy controls, 163 patients with ED at baseline and 150 patients at follow-up, 7-12 years later.Blood sampling was not possible in one patient at follow-up, hence the follow-up group consisted of 149 former patients at the clinic.The patients donated blood at baseline and at follow-up, i.e., 7-12 years later.Median time between baseline and follow-up were 9 years and 5 months, and mean time between baseline and follow-up were 9 years and 4 months.The healthy controls only donated blood at one timepoint (baseline).Blood was drawn in 4 ml K2EDTA tubes (VACUETTE®) and centrifuged at 3500 rpm at +4 • C for 15 min.The blood plasma was separated in 1 ml aliquots and stored at − 80 • C.

Burnout and symptoms of depression and anxiety
The Shirom-Melamed Burnout Questionnaire (SMBQ) was used to

Table 1
Diagnostic criteria for Exhaustion Disorder according to the National Board of Health and Welfare (2003).
A. Physical and mental symptoms of exhaustion with minimum two weeks duration.The symptoms have developed in response to one or more identifiable stressors which have been present for at least 6 months.B. Markedly reduced mental energy, which is manifested by reduced initiative, lack of endurance, or increase of time needed for recovery after mental efforts.C. At least four of the following symptoms have been present most of the day, nearly every day, during the same 2-week period: 1. Persistent complaints of impaired memory.2. Markedly reduced capacity to tolerate demands or to work under time pressure.3. Emotional instability or irritability.4. Insomnia or hypersomnia.5. Persistent complaints of physical weakness or fatigue.6. Physical symptoms such as muscular pain, chest pain, palpitations, gastrointestinal problems, vertigo, or increased sensitivity to sounds.D. The symptoms cause clinically significant distress or impairment in social, occupational, or other important areas of functioning.E. The symptoms are not due to the direct physiological effects of a substance (e.g. a drug of abuse, a medication) or a general medical condition (e.g.hypothyroidism, diabetes, infectious disease).F. If criteria for major depressive disorder, dysthymic disorder or generalized anxiety disorder are met, exhaustion disorder is set a comorbid condition.
C. Hansson et al. assess self-reported symptoms of burnout at baseline and at follow-up.A revised 18 item version of the SMBQ was used in this study (Lundgren-Nilsson et al., 2012).Each item is rated on a seven-point scale ranging from 1 ("almost never") to 7 ("almost always"), and hence the mean score can range from 1 to 7. A mean score of ≥4.4 has been suggested as a clinically relevant cut-off to identify potential cases of clinical burnout (Lundgren-Nilsson et al., 2012).
The Hospital Anxiety and Depression scale (HAD) was used to assess self-reported symptoms of depression and anxiety at baseline and at follow-up (Zigmond and Snaith, 1983).The HAD scale consists of 14 statements concerning feelings during the past week, seven for each of the two subscales.Four response alternatives (scored 0-3) indicating degree or frequency are available for each statement.A sum score above 10 for each subscale is considered to indicate clinically significant depression and anxiety, respectively (Zigmond and Snaith, 1983).

Protein analysis
Protein concentrations in plasma were quantified using the Olink® Neuro Exploratory panel provided by Olink Bioscience (Olink Bioscience, Uppsala, Sweden), as described earlier (Assarsson et al., 2014).This multiplex panel gives a relative quantification of 92 proteins in one sample.Each protein is detected by a matched pair of antibodies, coupled to unique oligonucleotides, and measured by quantitative real-time polymerase chain reaction (PCR).The analyses were performed by Olink Bioscience.Data received from Olink Bioscience are presented as normalized protein expression (NPX), which is a relative quantification unit on a log2 scale with data being normalized to minimize both intra-assay and inter-assay variation.For one of the samples all analyses failed and four of the samples did not pass the quality control.Hence, 407 samples passed the quality control, whereof 99 samples from the healthy control group, 159 samples from the ED group at baseline, and 149 samples from the ED group at follow-up.For 45 of the 92 proteins, one or more of the analyzed samples fell below the limit of detection (LOD).The proportion of samples below LOD varied between 0.2 % and 93.6 %.For 25 of the 92 proteins, more than 20 % of the analyzed samples fell below LOD.Those proteins were considered to have too many unreliable observations and were omitted from further analyses.Hence, the final dataset consisted of 67 proteins analyzed in 407 samples.Supplementary table 1 lists all 67 included proteins with full protein names.

Ethics
All participants gave their written informed consent before entering the study.This study was performed in accordance with the Declaration of Helsinki and was approved by the Regional Ethical Review Board in Gothenburg, Sweden, which is a part of the Swedish national committee for ethical approval (Dnr 439-05 and 242-15).

Statistical analyses
Differences in demographic variables between the patients and controls were analyzed using independent samples t-test for continuous variables, Pearson chi-square for dichotomous variables and independent samples Mann-Whitney U test for categorical variables.Differences in demographic variables between two timepoints within the same group were analyzed using paired samples t-test for continuous variables and related-samples Wilcoxon signed rank test for categorical variables.Associations between protein levels and age were explored using Pearson correlation.Differences in protein levels between women and men were analyzed using independent samples t-test.To avoid confounding the results by disease status, only the control group was included in these analyses.
Principal component analysis (PCA) was conducted to exploratively examine protein expression in patients and controls at baseline and follow-up.With the PCA, the total number of correlated variables (67 proteins) is reduced to a smaller number of uncorrelated principal components (PC) that account for much of the information contained in the observed variables.The PCA is conducted in such a way that the first PC accounts for as much of the variance in the data as possible.The second PC is uncorrelated to the first PC and accounts for the second largest amount of variance in the data and so on.The total amount of variance explained is calculated cumulatively from the PCs with eigenvalues above 1.Loadings (values ranging from -1 to 1) are correlation coefficients between the variable and the PC and provide information about which variables give the largest contribution to the PCs.
Differences in protein concentration between the ED group at baseline and the control group, and between the ED group at follow-up and the control group, were analyzed using general linear model, adjusting for age and sex.Differences in protein concentrations between the ED group at baseline and the same group at follow-up were analyzed using mixed models, adjusting for age and sex.Bonferroni correction was used to adjust for multiple comparisons.Hence, the α-value was adjusted to 0.05/67 = 0.00075 and a p-value <0.00075 was considered statistically significant.Partial eta squared (pes) indicates the effect size.Pes = 0.14 indicates a large effect, pes = 0.06 indicates a medium effect, and pes = 0.01 indicates a small effect (Richardson, 2011).The statistical analyses were performed using the IBM SPSS Statistics version 25.

Expression analyses
The tissue distribution of mRNA expression of the 67 proteins in the final dataset was assessed using the GTEx database.Data was downloaded from https://www.gtexportal.org/home/datasetsFebruary 23rd 2018.The dataset contains RNASeq expression profiles from 53 tissues (5-564 samples per tissue) and data is presented as median Transcripts Per Kilobase Million for each tissue.The mRNA tissue distribution was illustrated by a heatmap using Heatmapper (http://heatmapper.ca/expression/).

Characteristics of the study population
The characteristics of the study population are shown in Table 2.There were significantly more women in the ED group than in the BMI = body mass index 1 Self-reported symptoms measured using the Shirom-Melamed Burnout Questionnaire (SMBQ).
2 Self-reported symptoms measured using the Hospital Anxiety and Depression scale (HAD).
3 Higher education is defined as at least 1 year of university/college education.
C. Hansson et al. control group (p<0.001) and the ED group was significantly older (p<0.001).Body mass index (BMI) did not differ between the control group and the ED group at baseline, but the ED group had significantly higher BMI at follow-up than at baseline (p<0.001).Marital status did not differ between the groups.The control group had a larger proportion of participants with at least 1 year of university education than the ED group (p<0.001).Self-reported symptoms of burnout, anxiety and depression, measured by SMBQ and HAD, were significantly higher in the ED group at baseline than in the control group (p<0.001),significantly lower in the ED group at follow-up than in the ED group at baseline (p<0.001), and significantly higher in the ED group at followup than in the control group (p<0.001).There was a significantly higher proportion of patients than controls with a diagnosis of anxiety (p<0.001) and the proportion of patients with a diagnosis of anxiety was significantly lower at follow-up than at baseline (p<0.001).Likewise, there was a significantly higher proportion of patients than controls with a diagnosis of depression (p<0.001) and the proportion of patients with a diagnosis of depression was significantly lower at follow-up than at baseline (p<0.001).Antidepressant medication was significantly more common in the ED groups than in the control group (p<0.001) and did not significantly differ between the ED group at baseline and follow-up (Table 2).

The principal component analysis (PCA) showed a clear separation between the ED group at baseline and controls
Principal component analysis (PCA) of the 67 analyzed proteins showed a clear separation in the protein expression patterns between the ED group at baseline and the control group, as well as between the ED group at baseline and the same group at follow-up.However, no clear separation in protein expression was seen between the patient group at follow-up and the control group (Fig. 1).The principal component analysis gave a total of 11 principal components, explaining 71.7 % of the total variation.Principal component 1 (PC1) explained 35.3 % of the variation and principal component 2 (PC2) explained 15.3 % of the variation.Thus, PC1 and PC2 together explained 50.6 % of the total variation.The loadings of each protein to PC1 and PC2 are shown in Supplementary table 2.

Decreased plasma levels of neuro-related proteins over time in patients with ED
One protein (PHOSPHO1) had significantly higher plasma concentration in the ED group at follow-up compared with the same group at baseline and 40 proteins had significantly lower plasma concentration in the ED group at follow-up compared with the same group at baseline (Table 3 and Supplementary table 5).Out of the 40 proteins that had significantly higher plasma concentration in the ED group at baseline compared with controls, 36 proteins had significantly lower plasma concentration in the ED group at follow-up compared with the same group at baseline, and the plasma concentration of four proteins (Calsyntenin-1 (CLSTN1), Latent-transforming growth factor beta-binding protein 3 (LTBP3), Immunoglobulin alpha Fc receptor (FCAR), and Fibroblast growth factor receptor 2 (FGFR2)) were not significantly different between the two timepoints (Table 3 and Supplementary table  5).
Additional analyses, comparing the protein levels at follow-up between the patients that still fulfilled the diagnostic criteria at follow-up and the patients that were considered recovered at follow-up, showed no significant differences between the groups (Supplementary table 6).

The tissue distribution analysis showed large variability in expression sites of the investigated proteins
To get an overview of the expression sites of the investigated proteins, RNAseq data from a public database was analyzed and visualized by a heatmap (Fig. 2).No clear patterns of tissues contributing to the expression of the altered proteins were observed and the main site of expression for each of the analyzed proteins showed large variability (Fig. 2).

Protein levels were affected by age and sex
Investigating the associations between plasma protein levels and age in the healthy controls showed that 22.4 % of the proteins were significantly correlated with age, whereof 3.0 % were positively correlated and 19.4 % were negatively correlated with age.Exploring sex differences in plasma protein levels in the healthy controls showed that 23.9 % of the proteins were significantly different between women and men, whereof 22.4 % of the proteins had higher levels in women and 1.5 % of the proteins had higher levels in men.

Discussion
The PCA analysis indicated a clear separation in the protein expression patterns between the ED group at baseline and the healthy control group that was no longer apparent at follow-up.These findings were confirmed by the univariate analyses, which showed higher plasma levels of a large number of neuro-related proteins in patients with ED compared with healthy controls.The univariate analyses also confirmed C. Hansson et al. that the plasma levels of most of these proteins did not significantly differ between patients and controls at follow-up.These findings indicate that long-term stress exposure influences neuro-related biological processes and that most of these processes normalizes over time.
The proteins that differed the most between patients with ED and healthy controls were CRADD, PMVK, TBCB, PRTFDC1, NAA10, KIF1BP, and FKBP5.Several of these proteins are involved in axonal and dendritic growth, synaptic vesicle transport and plasticity, and neuronal growth and degradation, suggesting that these processes may be involved in the pathophysiology of ED.TBCB is a regulator of axonal growth; while excess TBCB leads to axonal damage and neuronal degradation, inhibition of TBCB enhances axonal growth (Lopez-Fanarraga et al., 2007).KIF1BP is required for organization of the axonal cytoskeleton, and for axonal outgrowth and maintenance (Lyons et al., 2008).Moreover, KIF1BP is involved in the regulation of synaptic vesicle transport (Kevenaar et al., 2016).As seen in the tissue distribution analysis, both TBCB and KIF1BP are highly expressed in the brain.NAA10, the catalytic subunit of the N-acetyltransferase A complex, is an  important regulator involved in many biological processes, including cell growth and differentiation (Lee et al., 2018a).NAA10 is important for dendritic development and has also been suggested to play a role in synaptic plasticity (Ohkawa et al., 2008).CRADD associates with caspase-2 to initiate stress induced apoptosis (Tinel and Tschopp, 2004).Caspase-dependent apoptosis is involved in a number of diseases including neurodegenerative diseases (Favaloro et al., 2012).Moreover, CRADD/caspase-2 signaling has been suggested to be required for normal cognitive function (Di Donato et al., 2016), which is interesting as cognitive impairment is one of the cardinal symptoms of ED.Other proteins are involved in the regulation and synthesis of cortisol.PMVK is an enzyme in the cholesterol synthesis pathway (Ershov et al., 2021).Cholesterol is the precursor of steroid hormones (Luo et al., 2020), including cortisol.FKBP5 is an important regulator of glucocorticoid receptor (GR) sensitivity.When FKBP5 is bound to the GR complex, cortisol binds with lower affinity to the GR.Activation of the GR induces transcription of FKBP5, providing an ultra-short negative feedback loop (Binder, 2009).FKBP5 has been shown to be a biomarker for long-term cortisol exposure (Lee et al., 2018b).In our study, FKBP5 was significantly increased in the ED group at baseline compared with controls, indicating an increased cortisol load in the ED group during the previous months.This is interesting given the conflicting results regarding cortisol in patients with ED, where the cortisol levels of patients with ED have been shown to be both higher, lower, or not different from controls, possibly reflecting methodological inconsistencies, the diurnal pattern of cortisol secretion (Jonsdottir and Sjors Dahlman, 2019), or cortisol being measured at different timepoints in the course of illness.PRTFDC1 has been identified as the only gene to reach genome-wide significance in a large GWAS studying combat stress vulnerability for PTSD (Nievergelt et al., 2015), suggesting that this gene is involved in stress-related disorders.The tissue distribution analysis indicates that PRTFDC1 is highly expressed in the brain, but also in the pituitary, the adrenal glands, and in the female reproductive organs, like the ovary, cervix, and uterus.Most of the proteins that were significantly increased in the ED group at baseline compared with controls had normalized at follow-up, suggesting that these proteins are increased in response to long-term stress, but normalizes when stress levels are reduced.However, four of the proteins (CLSTN1, LTBP3, FCAR, and FGFR2) may be regarded as only partially normalized at follow-up, as their plasma levels were not significantly different from neither the ED group at baseline's nor from the controls'.CLSTN1 is a synaptic protein that has been found to be involved in preclinical Alzheimer's disease (Lleo et al., 2019).The increased expression of CLSTN1 in patients with ED is interesting as long-term stress in midlife has been associated with an increased risk of dementia, especially Alzheimer's disease, later in life (Johansson et al., 2010).This is supported by animal studies showing that increased expression of CLSTN1 is associated with stress-induced damaged cortical dendritic morphology and decreased cognitive function (Xu et al., 2015).The tissue distribution analysis shows that CLSTN1 is highly expressed in the brain, especially in the cerebellum and the frontal cortex.LTBP3 is an extracellular matrix protein that bind latent TGF-β.Mice lacking LTBP-3 has abnormally high corticosterone levels, up to 5-18-fold higher levels than wild type littermate controls (Chen et al., 2003), but the mechanism is still unknown.FCAR has been identified as a key gene for epilepsy (Zhu et al., 2021) as well as for multiple sclerosis (Achiron et al., 2004), suggesting that FCAR may be involved in inflammatory responses in the CNS.FGFR2 is part of the fibroblast growth factor (FGF) family that is involved in neurogenesis and gliogenesis, axon outgrowth, myelinogenesis, and tissue repair (Terwisscha van Scheltinga et al., 2013).The FGF system is also involved in anxiety, depression, fear conditioning, and the response to stress and has been proposed to be a key link between stress, neuroplasticity and affective behavior (Turner et al., 2012).FGFR2 is also involved in cognitive impairments (Terwisscha van Scheltinga et al., 2013), which is interesting as patients with ED often suffer from long-term cognitive impairments (Ellbin et al., 2021).Possibly, FGFR2 may be involved in the long-term cognitive impairments seen in patients with ED.
Previous research regarding biological mechanisms in ED and clinical burnout has mainly focused on dysregulation of the hypothalamuspituitary-adrenal (HPA) axis, and to a lesser extent on dysregulation of the autonomic nervous system, immune system, growth factors, and other hormones, but no conclusive biomarker has yet been found (Danhof-Pont et al., 2011;Grossi et al., 2015;Jonsdottir and Sjors Dahlman, 2019).However, several studies have raised the question if chronic stress may lead to cerebral changes or damage that could be long-lasting.For example, functional alterations as well as structural changes have been found in the brains of patients with ED compared with healthy controls (Blix et al., 2013;Golkar et al., 2014;Jovanovic et al., 2011;Savic et al., 2018;Skau et al., 2021).Some of these changes, e.g.thinning of the prefrontal cortex and reduction of the caudate volume, have been found to be reversible, while other changes, e.g.amygdala enlargement, remained after 1-2 years (Savic et al., 2018).In addition, we recently found increased levels of NfL, a marker of axonal injury, in patients with ED compared with controls.At long-term follow-up, the NfL levels were no longer increased compared with controls, and may thus be considered to be normalized (Hansson et al., 2022).We also found increased levels of GFAP, a marker of astrocytic activation, in patients with ED compared with controls (Hansson et al., 2022).Likewise, a recent study found that patients with ED had significantly higher plasma concentrations of aquaporin 4-and GFAP-positive extracellular vesicles than healthy controls, indicating that patients with ED have increased leakage of astrocyte-derived extracellular vesicles through the blood-brain barrier (Wallensten et al., 2021).Moreover, lower levels of the neurotrophic factor BDNF have been found in patients with ED compared with healthy controls (Sjors Dahlman et al., 2019).Lower levels of BDNF have also been found in burnout compared with healthy controls in several studies (He et al., 2017;Onen Sertoz et al., 2008).BDNF is a neurotrophic factor that promotes hippocampal adult neurogenesis (Lee et al., 2002).Stress has been shown to reduce the expression of BDNF in the hippocampus (Smith et al., 1995) and to inhibit hippocampal adult neurogenesis (Gould et al., 1997).Stress-induced reduction of hippocampal adult neurogenesis has been proposed to be the biological and cellular basis of altered brain plasticity resulting in stress-related syndromes like burnout (Eriksson and Wallin, 2004).This supports the hypothesis that neuro-related alterations may be involved in the pathophysiology of ED/burnout.
Studies investigating stress-induced changes in neuronal architecture have shown that chronic stress results in shrinkage of dendrites in the hippocampus and the medial prefrontal cortex, and expansion of dendrites in the amygdala and orbitofrontal cortex (McEwen et al., 2016).This is in line with imaging studies of patients with ED, which show increased amygdala volumes and decreased thickness of the PFC (Savic et al., 2018).The altered expression of proteins involved in axonal and dendritic growth, synaptic vesicle transport and plasticity, and neuronal growth and degradation, found in patients with ED in the present study supports previous studies showing structural changes in the brain after chronic stress.The prefrontal cortex is particularly sensitive to the detrimental effects of stress (Arnsten, 2009).The prefrontal cortex is important for self-regulatory behaviors, working memory, and executive function (McEwen et al., 2016), functions that are impaired in patients with ED (Gavelin et al., 2022).In our study, several of the proteins that were significantly increased in the ED group at baseline are highly expressed in the frontal cortex, e.g., PPP3R1, HMOX2, CLSTN1, KIF1BP, and TBCB.Moreover, CLSTN1 was not significantly decreased at follow-up compared with baseline and has been implicated in stress-induced dendritic cortical morphology and decreased cognitive function (Xu et al., 2015).Most of the proteins in our study had returned to normal levels at follow-up.However, many of the patients still experienced problems with executive cognitive function, learning and memory, fatigue, and stress intolerance (Ellbin et al., 2021;Glise et al., 2020).Notably, recovery from stress does not necessarily mean a return  to the stress-naïve state.For example, prefrontal dendrites that regrow after recovery from stress are more proximal to the cell body than the dendrites that retracted (McEwen et al., 2015).This kind of changes is not captured by our study.Hence, to fully understand the consequences of chronic stress and the biological mechanisms of ED, future studies should integrate mechanistic studies, genetic, epigenetic, and proteomic studies with imaging studies, to try to elucidate this complex phenomenon.

Methodological considerations
One important methodological consideration is that we have not controlled for the potential influence of medication on plasma protein levels.The main reason is that the healthy control group were not on any medication.However, within the patient group at baseline, the plasma levels of the studied proteins did not differ between users and nonusers of SSRIs, SNRIs, or other antidepressants.In our study, 22 % of the proteins were significantly associated with age and 24 % of the proteins differed significantly between women and men.This is in line with previous studies showing that many plasma proteins change significantly with age and sex (Lehallier et al., 2019).The distribution of age and sex differed between the patients and controls in our study.Therefore, the comparisons of plasma protein levels were adjusted for age and sex.Blood samples from the control group were collected in 2017-2018, from the ED group at baseline in 2004-2010, and from the ED group at follow-up in 2016-2017.Hence, the blood samples from the ED group at baseline were stored several years longer than the blood samples from the other groups.The stability over time has been investigated by (Enroth et al., 2016).They analyzed plasma levels of 108 proteins, to investigate the influence of long-term freezer storage, chronological age at sampling, and season and month of the year at sampling on protein abundance levels.They found that 18 of the 108 proteins were influenced by storage time, out of which one protein remained statistically significant after correction for multiple testing.Moreover, they found that 70 of the of the 108 proteins were influenced by age, out of which 45 proteins remained statistically significant after correction for multiple testing.Seasonal changes affected 15 of the 108 proteins, but none of these differences remained statistically significant when adjusting for multiple comparisons.In our study, we have adjusted for age, which has been shown in several studies to influence plasma protein levels, but we have not adjusted for storage time or seasonal changes.However, in our study, the blood samples were stored at − 80 • C and had never been thawed before the protein analysis, reducing the risk of protein degradation.Finally, the patients in this study have been referred to a specialist clinic for ED.Hence it is possible that they represent more severe cases of ED compared with patients with ED in primary care.Thus, the results of this study should be validated in a more heterogenous cohort of patients preferably in a primary care setting.

Conclusion
The plasma levels of a large number of neuro-related proteins were increased in patients with ED in the acute phase of the disease but had normalized at long-term follow-up.These data support the hypothesis that pathophysiological processes in the central nervous system are involved in the biological mechanisms underlying ED.The findings of our study add to the knowledge from previous studies showing that neuro-related mechanisms seem to be affected in patients with stressrelated exhaustion.Thus, the results may pave the way for further exploration of the biological mechanisms behind ED.

Ctrl
= control group (n=99), ED T1 = ED group at baseline (n=159), ED T2 = ED group at 7-12 years follow-up (n=149).Bold font indicates p<0.00075.* Orange color indicates higher expression in the ED group compared with controls.Blue color indicates lower expression in the ED group compared with controls.# Orange color indicates higher expression at follow-up compared with baseline.Blue color indicates lower expression at follow-up compared with baseline.

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.Hansson et al.

Fig. 2 .
Fig. 2. Heatmap of mRNA tissue distribution of the investigated proteins.Orange color indicate tissue with high mRNA expression.Blue color indicate tissue with low mRNA expression.

Table 2
Characteristics of the study population.

Table 3
Differences in plasma levels of neuro-related proteins between patients with exhaustion disorder (ED) and controls.