The burden of mental disorders has been increasing worldwide (Vigo et al., 2016; World Health Organization(Who), 2017). Major depressive disorder (MDD) is one of the most prevalent mood syndrome, affecting 350 million people globally (World Health Organization(Who), 2017; Liu et al., 2020). Currently, there is a thought in the research field that the comprehension of MDD pathophysiology is essential to the strengthening of precision psychiatry, by supporting prognosis, diagnosis, treatments, and follow-up of patients, and thus would help in the reduction of MDD burden (Schmidt et al., 2011; Dean and Keshavan, 2017; Menke, 2018). These are the main goals of the large European and American studies such as the Roadmap for Mental Health Research and Research Domain Criteria, respectively (Insel et al., 2010; Elfeddali et al., 2014).

Many studies have tried to associate neurobiological markers with a set of MDD symptoms as shown in 5th Diagnostic and Statistical Manual of Mental Disorders (DSM-5) (American Psychiatric Association, 2013; Hashimoto, 2015; Fried et al., 2019; Koo et al., 2019). However, the physiological dysfunctions observed in patients with major depression are inconsistent: they are not present in all patients with the same intensity, and with similar relationship with symptoms (Bremmer et al., 2017; Zou et al., 2018; Almeida et al., 2019). Therefore, at present, none biomarker validated in scientific studies is widely used clinically (Menke, 2018). It is suggested that the progression of clinical disease, such as the severity of depressive symptoms and the sleep changes, and some sociodemographic characteristics, like gender, age, income, and education, can be related to the large variance observed in the pathophysiology of patients with depression (Mello et al., 2007; Verduijn et al., 2015; Menke, 2018; Kim, 2020; Perna et al., 2020; Santiago et al., 2020).

Some patients with MDD often show dysregulation of hypothalamus-pituitary-adrenal (HPA) axis, which is the main endocrine stress system. However, the studies have conflicting views about up- and downregulation of HPA axis in these patients (Bremmer et al., 2017; Dean and Keshavan, 2017; Ferrari and Villa, 2017). Some show systemic hypercortisolemia (Gold et al., 1986, 1988), while other studies show hypocortisolemia (Tu et al., 2013; Kunugi et al., 2015). Furthermore, disruptions in the cortisol awakening response (CAR) and the circadian cortisol pattern are also found, which can be measured from saliva samples (Chida and Steptoe, 2009; Marques et al., 2010; Vreeburg et al., 2013; Moreira et al., 2016; Galvão et al., 2018).

Increased systemic inflammation is another physiological alteration observed in some patients with depression (Krishnadas and Cavanagh, 2012; Lopresti et al., 2014; Zou et al., 2018). It is proposed that cortisol changes disrupt homeostasis of the immune system, stimulating proinflammatory cytokines, such as interleukin 6 (IL-6), and tumor necrosis factor-α (Zunszain et al., 2011; Sousa et al., 2015). Furthermore, an increase in the C-reactive protein (CRP) levels, a non-specific inflammatory biomarker released by hepatocytes, is also observed in patients with MDD (Haapakoski et al., 2015; Köhler-Forsberg et al., 2016; Galvão-Coelho et al., 2020).

In addition, neuroimaging studies have revealed a reduced hippocampal volume in some patients with depression, which is speculated to be related to a decrease in the levels of neurotrophins, such as brain-derived neurotrophic factor (BDNF) (Lima-Ojeda et al., 2018; Roddy et al., 2019; Sheline et al., 2019). Although some studies have shown lower levels of blood BDNF in patients with major depression (MD) in comparison with those of healthy subjects, the results are inconsistent (Karege et al., 2002; Groves, 2007; Lee and Kim, 2009; Vu and Student, 2009; Cubala and Landowski, 2014; Almeida et al., 2019).

Interestingly, all these changes, including HPA axis, immune system, and the levels of BDNF, have physiological pathways that are often integrated with sleep disturbances in a disrupted positive-feedback system (Cubala and Landowski, 2014; Giese et al., 2014; Kunugi et al., 2015; Chrousos et al., 2016; Ferrari and Villa, 2017; van Dalfsen and Markus, 2018). The decrease in sleep quality is usually observed before the onset of MDD (Breslau et al., 1996; Perlis et al., 1997; Ohayon and Roth, 2003), while persistent sleep impairments are associated with the severity of MDD, worse treatment outcomes, and consequently, the recurrence of illness (Moos and Cronkite, 1999; Santiago et al., 2020).

Despite the knowledge about the relationship across these important biological systems, a minor number of studies have evaluated these changes simultaneously and over the clinical progression of MDD (Verduijn et al., 2015). Therefore, the purpose of this study was to evaluate patients with depression in distinct MDD stages (de novo patients and patients with treatment-resistant depression), by the serum mature BDNF (mBDNF), plasma CRP, serum cortisol (SC), and the salivary CAR, aiming to compare them with those of a control group of healthy volunteers. These physiological parameters were analyzed by taking into account the severity of the depression symptom, sleep quality, and sociodemographic characteristics of the participants. We hypothesized that patients with depression have distinct physiological profiles from healthy volunteers, which will be influenced by the stage of disease, that is, worse physiological parameters would be related to stronger depressive symptoms and worse sleep quality.

From the initial inquiries of 640 participants, 120 participants who potentially met the inclusion criteria were selected for the screening phase: 62 healthy participants and 58 patients with MD, with 30 being grouped as patients with first episode of MD (14 men and 16 women) and 28 participants with TRD (7 men and 21 women). The healthy participants were divided into two groups, namely, a control group (CG1, n = 32; 15 men and 17 women) for the de novo MD group and a control group for TRD (CG2, n = 30; 7 men and 23 women). The consolidated standards for clinical trial reports (CONSORT) are shown in Supplementary Figure 1.

As per our hypothesis, the results of our present study reveal that patients with MDD present with differing cortisol, mBDNF, and CRP profiles than that observed in healthy volunteers. Furthermore, these molecular changes were highly dependent on the stages of MDD, i.e., the severity of depressive symptoms and the sleep quality.

The levels of both serum and saliva (i.e., CAR) cortisol were higher in the patients with de novo MDD, whereas it was presented in lower levels in the TRD group compared with the respective healthy controls. Moreover, moderate correlations were found between the lower levels of both cortisol measures and stronger depressive symptoms. In the literature, some studies have revealed that hypercortisolemia and higher CAR are usually observed in patients with the short-term depression (Foreman and Goodyer, 1988; Lopez-Duran et al., 2009; Dedovic and Ngiam, 2015), whereas other specify that patients with TRD and with a long-term disease have hypocortisolemia and a blunted CAR (Stetler and Miller, 2005; Vreeburg et al., 2013; Moreira et al., 2016; Bremmer et al., 2017; Galvão et al., 2018). In contrast, studies that analyze changes in cortisol over clinical progression of MDD are sporadic, but like our findings, they support the notion of reduction in cortisol levels over disease severity (Verduijn et al., 2015).

One of the main risk factors for MDD is chronic stress (Mazure, 1998; Dohrenwend, 2006); although the reactivity of the HPA axis to a stressor is an adaptive function, the absence of its recovery induces many dysfunctions (Sen et al., 2008; Sousa et al., 2015). The sustained overstimulation of the HPA axis, caused by an impaired negative feedback from the HPA axis, results in hypercortisolemia (Dean and Keshavan, 2017), as it is found in patients with mild and moderate MDD (Gold et al., 1988; Juruena and Cleare, 2007; Dean and Keshavan, 2017; Ferrari and Villa, 2017), as well as in patients with Cushing’s syndrome (Gold et al., 1986), which share some similar symptoms such as metabolic syndrome (Pivonello et al., 2015). However, if the HPA axis function has been hyperactivated for a long time, this can later result in adrenal failure (Yehuda et al., 2005) or an increase in the sensitivity of cortisol negative feedback in the hypothalamus (Sriram et al., 2012), thus switching such profile from hypercortisolemia to hypocortisolemia, as it is seen in patients with TRD (Herbert, 2013) and in individuals with Addison’s syndrome who show chronic fatigue syndrome (Maripuu et al., 2014). Therefore, our findings importantly reveal the contrast in cortisol changes between de novo and TRD depression, suggesting a switch from hypercortisolemia to hypocortisolemia as the MDD gets worse and longer, thus helping for better understanding about HPA changes in MDD (Vreeburg et al., 2013; Bremmer et al., 2017; Galvão et al., 2018). This further supports the theory that these changes are related to the severity of depressive symptoms (Stetler and Miller, 2005; Karlović et al., 2012; Herbert, 2013).

We also found that the earlier use of antidepressants predicted lower levels of both cortisol measures (i.e., SC and CAR). Distinct classes of antidepressants may have opposite effects in the modulation of cortisol, which also depends on the treatment duration. Therefore, since patients with TRD in our study used many different classes of antidepressants and had distinct treatment schemes (dose and duration), it is difficult to assure wheter the low levels of cortisol found here are an etiology of the disorder or a result of earlier antidepressant treatments. In the case of de novo patients (who were naïve these medications), it may be speculated that their high levels of cortisol are associated with etiologic changes of MDD.

Therefore, these distinct cortisol changes in TRD and de novo patients should be taken into account in the choice of the antidepressant treatment, since cortisol is a pleiotropic hormone (Schüle, 2007; Galvão-Coelho et al., 2012). Mainly because, patients in remission who have ongoing HPA-axis dysfunction have higher relapse risk (Slavich and Irwin, 2014).

Furthermore, we found that patients with TRD had higher levels of mBDNF than healthy volunteers, while patients with first episode showed similar levels of mBDNF as compared to its control group. Indeed, a positive correlation between mBDNF levels and MDD severity was found. The increased mBDNF of patients with TRD are in opposition to our hypothesis. The neurodegenerative hypothesis of MDD and some studies in this field show low blood levels of BDNF in patients with MDD (Mannari et al., 2008; Monteleone et al., 2008; Lima-Ojeda et al., 2018), although this finding is not unanimous (Almeida et al., 2019; Verduijn et al., 2015; Vu and Student, 2009). Here, we found that earlier antidepressant treatment predicts high levels of mBDNF. Therefore, supported by earlier evidences (Pilar-Cuéllar et al., 2012; Zhou et al., 2017) and by observation that patients with first episode MDD, who were naïve for antidepressant medication, presented similar levels of mBDNF of the control group, we might speculate that the increased levels of mBDNF are potentially due to the long-term use of antidepressants by patients with TRD (Perito and Fortunato, 2012; Yoshida et al., 2012; Lima-Ojeda et al., 2018).

In addition, BDNF isoforms should be taken into account. Most studies in patients with MDD analyzed the levels of total blood BDNF (Vu and Student, 2009; Shirayama et al., 2015; Almeida et al., 2019); however, we measured its active isoform, i.e., the mBDNF. The few studies that examined mBDNF in patients with MDD have showed both low and high levels of this isoform when compared with controls (Foltran and Diaz, 2016; Angoa-Perez et al., 2017). Importantly, it is proposed that the pro-BDNF/mature BDNF (mBDNF) ratio should be more relevant for shaping physiological or pathological conditions (Raison et al., 2013; Zhao et al., 2017; Mora et al., 2018; Osimo et al., 2019).

The concentration of CRP was not measured for patients with first MDD episode since 96.6% did not show measurable levels of CRP and, thereby, a absence of inflammation. Earlier, other studies in drug-naïve patients with MDD or in patients with initial stages of this disorder also did not detect increases in CRP or IL-6 compared with controls (Cubala and Landowski, 2014; Verduijn et al., 2015; Zou et al., 2018).

However, patients with TRD had higher levels of CRP than healthy volunteers, which was characterized as a low-grade inflammatory profile (CRP level >3 mg/L; healthy adult population <1 mg/L) (Angoa-Perez et al., 2017; Zhao et al., 2017). Some studies have identified CRP as an etiological factor for MDD (Harris et al., 1999; Vreeburg et al., 2013; Köhler-Forsberg et al., 2016) and pointed its increase regardless of IL-6 (Ivashchenko et al., 2005; Saito et al., 2016). Since the measurement of CRP shows some advantages, such as high stability and low-cost dosage, it is proposed that CRP could be used alone as an inflammatory biomarker in MDD, independently of IL-6 (Carboni, 2013; Galvão-Coelho et al., 2020). A significant correlation between CRP and MDD severity is seen in some studies (Carboni, 2013; Köhler-Forsberg et al., 2016), although it is not unanimous (Verduijn et al., 2015). Here, we did not find this correlation possibly due to our small sample size for CRP quantitative data. Although we have found between-group differences among these physiological parameters, it is important to note that these inflammatory changes are not exclusive of depression and may occur in other diseases. Therefore, the changes in these physiological parameters cannot be exclusive biomarkers of MDD (Mondelli et al., 2010; Martinotti et al., 2016; Orsolini et al., 2018).

Moreover, we must highlight that the physiological changes observed in our patients remained significant even after controlling for relevant individual and social characteristics. For the patients with first episode and their control, a weak inverse correlation was found between the levels of SC and age, although the age dispersion is small in this sample. Some studies have showed age-related changes of the HPA axis in healthy and clinical populations (Yiallouris et al., 2019). For patients with TRD and their control, we found a positive correlation between BMI and the levels of cortisol and CRP. High levels of proinflammatory biomarkers can be observed in individuals with overweight due to an overactive metabolism of cortisone into cortisol in the adipose tissue and also due to a local immune activity (Milaneschi et al., 2019). Moreover, the lower-income volunteers had higher levels of mBDNF, probably a consequence of earlier antidepressant treatment, since low-income is expected to be a strong stressor, what would lower mBDNF levels (Fung et al., 2015). Therefore, these results show the importance of controlling potential sociodemographic modulators of physiological parameters, avoiding erroneous interpretations.

We observed that worse sleep quality is related to lower levels of both cortisol parameters. A blunted CAR has been observed in patients with MDD and sleep disorders (Santiago et al., 2020). Patients with MDD have presented changes in slow wave sleep as a result of reduction in HPA axis activity (Balbo et al., 2010). Currently, there is no clear conclusion about the relationship between cortisol and sleep changes, whether this hormonal change is a cause or a consequence of sleep disturbances (Steiger, 2003).

Finally, worse sleep quality was weakly correlated with higher levels of mBDNF. Despite some studies showing that high levels of BDNF are related to a good sleep profile (Giese et al., 2014), MDD patients with sleep disorders did not show low levels of serum BDNF (Santiago et al., 2020). Interestingly, therapies using acute sleep deprivation for MDD increased mBDNF levels (Schmitt et al., 2016). Moreover it can be noted that, although sleep changes are potentially in part related to inflammation (Patel et al., 2009; Chrousos et al., 2016), we did not find correlations between these elements, which can be in part due to the reduced sample size of patients who had their quantitative value of CRP measured.

Recently, some studies have explored whether various biomarkers are related to the specific symptoms of the psychopathologies, rather than to the global condition (Yoshida et al., 2012; Caldieraro et al., 2017). For instance, the HAM-D sub-domains have been used to assess the response to antidepressants (Silverstone et al., 2002). In our study, the HAM-D sub-score, which was the sum of HAM-D sub-domains selected by the Boruta algorithm, had a weak contribution to the improvement of the correlation strength between depression severity and physiological parameters. Similar founds were observed for PSQI sub-scores.

It is essential to point out some limitations of this study, such as the modest number of volunteers, the cross-sectional design with a single sample of blood and saliva per subject, and the lack of pro-BDNF measurement, which is relevant to evaluate the relationship between m-BDNF and pro-BDNF. It is also important to highlight that some psychometric instruments were filled out by the clinician in contrast to others of self-report. Therefore, studies with larger populations of patients with MDD and designed with sequential biological measurements throughout the day and on different days are encouraged. Moreover, it is of important to evidence that only around 30% of depressive patients show a progression to TRD (Demyttenaere and Van Duppen, 2019), although it is believed that understanding the physiological changes in this group is important to give pavement to studies of MDD biomarkers and new treatments.

In conclusion, these results show that changes in some physiological parameters are distinct according to the clinical stage of depression. This understanding would be important to support the precision psychiatry, to stimulate further studies on biological assessments for depression, and to investigate how it may be underlying the lack of clinical response to usual pharmacotherapies.

The datasets presented in this article are not readily available because the sharing of this data set was not previously authorized by the local ethics committee. Requests to access the datasets should be directed to NG-C, nicolelgalvaocoelho@gmail.com.

The studies involving human participants were reviewed and approved by the Onofre Lopes University Hospital (HUOL) Medical Research Ethics Committee (# 579,479) and Federal University of Rio Grande do Norte (UFRN) Human Research Ethics Committee (# 2.628.202). The patients/participants provided their written informed consent to participate in this study.

NG-C, DA, FP-F, BL-S, JM-d-O, EN, and ML-M planned the clinical trial. FP-F and DA screened volunteers. AM and RA measured the hormonal data. AM and GS carried out statistical analysis and illustrated the figures and tables. All authors contributed to the manuscript.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.