The Unique Nature of Depression and Anxiety among College Students with Adverse Childhood Experiences

Abstract

It is well established that adverse childhood experiences (ACEs) contribute to the development of mental disorders in adulthood. However, less is known about how childhood trauma impacts the mind and the body, whether the resulting mental disorders have different characteristics than those occurring without these antecedent conditions, and if treatment modalities need to reflect the unique nature of mental disorders rooted in trauma. Survey and biomarker data were gathered from a sample of college students (n = 93) to explore the relationship between childhood trauma and mental health. We examine how neuroimmune systems (inflammation and neuroplasticity) relate to depression and anxiety and whether these associations vary for those with and without a history of childhood trauma. Findings reveal that students with 4 or more ACEs are more likely to have depression and anxiety than students without these experiences. In addition, we find that inflammation (CRP) and neuronal health (BDNF) are associated with mental health disorders among students with four or more ACEs, but not for students without this history. These findings suggest that mental disorders associated with four or more ACEs may be uniquely tied to physiological processes, and consequently, warrant tailored treatments. The implications for mental health intervention include, 1) screening for childhood trauma, inflammation, and neuronal health and 2) referral to treatments which are theoretically and empirically tied to the root causes of mental disorders rather than those designed merely to suppress their symptoms.

Introduction

Researchers have moved beyond simplistic explanations for mental disorders (e.g. a chemical imbalance in the brain) to a lengthy and complex list of indicated correlates. Many of these factors are physiological such as, genetic predispositions, dysregulation of neurons/ neurotransmitters, nutritional deficiencies or food sensitivities, inflammation, insulin uptake, and/or inadequate gut bacteria (Boris and Mandel 1994; Dash et al. 2015; Gatt et al. 2015; Grace 2016; Heckbert et al. 2010; Miller and Raison 2016). These biological explanations are thought to represent approximately 40% of the explanatory variance in mental illness, while environmental risks are estimated to account for another 40% of the variance (Cockerham 2017; Nestler et al. 2016). Environmental risks include a wide array of acute and chronic stressors (e.g. death of a spouse, divorce, persistent poverty), environmental toxins, the physical environment, and social isolation (Banerjee et al. 2007; Cockerham 2017; Evans 2003; Schmitt et al. 2014; Williams and Ross 2007).

Within this category of environmental strain, the Adverse Childhood Experiences Study (ACES) has focused a great deal of attention on adversity experienced during childhood. The ACE investigation revealed that the seeds of adult disease are planted in stressful childhood events such as abuse/neglect, domestic violence, and parental substance abuse (Hughes et al. 2017; Shonkoff et al. 2012). Specifically, researchers found a dose-response relationship between ACEs and heart disease, cancer, stroke, depression, substance abuse, suicidality, and a host of other disorders (Shonkoff et al. 2012). For example, respondents who experienced four or more adverse events in childhood were 4.5 times (450%) more likely to have clinical depression and anxiety disorder in adulthood, compared to those without any trauma (Felitti et al. 1998; Steven Stephens 2015).

The ACE study spurred a number of studies designed to uncover how traumatic experiences in childhood might “get under the skin” to ultimately undermine health and well-being. Specifically, a cumulating body of literature suggests that childhood trauma can create a level of “toxic stress” in the body, which alters the ability to regenerate and maintain neurons, called neuroplasticity (Heim et al. 2008). Brain derived neurotropic factor (BDNF) is a reliable and valid measure of neuroplasticity or neuronal health (Daskalakis et al. 2015). Adequate levels of BDNF are crucial for the neuroplasticity involved with learning and memory (Lu and Gottschalk 2000). In addition, low BDNF levels have been linked with susceptibility to a range of neuropsychiatric disorders including Alzheimer’s disease, autism, depression, eating disorders and schizophrenia (Notaras et al. 2015a; b).

In addition to the effect on neuronal health, complex trauma is believed to create an overactive stress response where the body’s fight or flight mechanism gets turned on but never turned off. These bodily processes affect the individual’s capacity to cope with environmental challenges and pathogens, called inflammatory response (Baumeister et al. 2016; Danese et al. 2007; Slopen et al. 2014). Research has specifically linked adverse childhood experiences to higher levels of inflammatory markers (such as Interleukin-6 or C-Reactive Protein) in adulthood (Danese et al. 2011; Pietras and Goodman 2013; Slopen et al. 2013). Also, inflammation has been a contributing factor to an increased risk of mental health disorders such as anxiety and depression (McNally et al. 2008; Vogelzangs et al. 2013). Finally, Nusslock and Miller (2016) hypothesize that significant early life stressors (i.e., childhood trauma) affect both the brain and the immune system in such a way that promotes not only one but multiple disease processes, including chronic illness, depression, and anxiety. In this instance, early life stressors affect the feedback loop between the neural and immune systems, in which inflammation undermines neural circuitries and vice versa (Nusslock and Miller 2016). However, no studies have investigated markers of neuroplasticity and inflammation simultaneously in predicting depression or anxiety. This may explain the inconsistent findings in the literature where some studies find a link between inflammation, neuroplasticity, and mental disorders in the context of childhood trauma while some do not show such evidence (Ceballos and Sharma 2016; Danese et al. 2007; Pace et al. 2006). Thus, we have preliminary evidence and plausible theories for how childhood adversity contributes to mental health disorders in adulthood, but the picture is not yet complete.

The ACE study and subsequent investigations have expanded our understanding of how complex trauma impacts mental health. Consequently, there have been calls to make systems, particularly the mental health system, trauma-informed (Elliott et al. 2005; Ko et al. 2008; SAMSHA 2014). Advocates for trauma-informed care urge the field to adopt trauma screening, trauma training, and trauma treatments (e.g. cognitive behavioral therapy for trauma, play therapy) (Ko et al. 2008). Likewise, the SAMSHA funded National Child Traumatic Stress Network has made significant progress in developing and disseminating trauma-informed approaches and treatments. While the ACEs literature has been widely disseminated and the field of inquiry and practice development surrounding trauma-informed care has momentum, there is much work to be done. First, the diagnostic tools and treatment protocols for common mental health disorders such as depression and anxiety, have not adequately incorporated this new information. The Diagnostic and Statistical Manual of Mental Disorders (DSM-5), along with common screening tools for depression and anxiety (e.g. PHQ-9, GAD, Beck), focus on self-reported psycho-social symptoms (Frances 2013; Pickersgill 2014). These diagnostic tools do not acknowledge causes and make few distinctions regarding these mental health disorders, other than to denote symptom severity. While there have been calls for universal ACEs screening, it is not yet common practice (Dube 2018; Watt 2017). In addition, the scientific findings regarding the impact of trauma on physiological processes have not led to a restructuring of the mental health treatment protocol or tailored treatment programs. For example, individuals screening positive for depression and/or anxiety are typically not given biological tests for neuronal health or inflammation. Consequently, regardless of whether an individual seeking treatment has experienced trauma, the dominant treatment protocol remains cognitive behavioral therapy, psychotropic medication, or a combination of the two. For example, in a study of mental health treatment of children in kinship and foster care, who by definition have experienced abuse/neglect and family disruption, Watt (2017) found that mental health providers understood the complex array of causal factors, but operated as if the children’s trauma histories were irrelevant to the diagnosis and treatment of the presenting mental disorder(s).

There are several possible explanations for the persistence of the narrow mental health treatment protocol. First, it could reflect a lag in the translational science. It may simply take more time for policy makers and practitioners to receive the necessary training in trauma-informed care and to adapt systems to accommodate this new perspective. For example, a large percentage of individuals with mental health disorders receive treatment from their primary care providers (DeGruy 1996; Oyama et al. 2012). However, there is ongoing discussion over whether ACEs screening should occur in primary care and these debates have not yet been resolved (Dube 2018; Finkelhor 2017). Less optimistically, there could be overt resistance on the part of pharmaceutical industries, which would prefer to retain the standard protocol of psychotropic medication for most mental disorders, regardless of their origins (Whitaker 2017; Whitaker and Cosgrove 2015). While both of these barriers may be at play, it is also possible that researchers have not elucidated the relationship between childhood trauma and mental health in sufficient detail, or packaged what we do know in a way that convinces practitioners of the need for change. This research would need to demonstrate, not only that trauma affects the mind and body, but also that the mental disorders that emerge from it are qualitatively different, requiring their own unique approach to diagnosis and treatment.

A small body of research has addressed the question of whether mental disorders differ for those with and without childhood trauma. Danese et al. (2008) found that child maltreatment is associated with comorbid conditions of depression and inflammation (CRP) in adulthood. They found no association between depression and inflammation when controlling for these childhood experiences. Danese and her colleagues note that their study cannot tease out causal order and that additional research is needed. However, their findings help to explain inconsistencies in previous research on depression and inflammation and point to the heterogeneity of the population of individuals experiencing clinical depression. In addition, Heim and colleagues (Heim et al. 2008), in an investigation of individuals with depression, found more heightened stress responses to challenge and a stronger correlation between stress responses and depressive symptoms for those with childhood trauma relative to those with no trauma history. In addition, they found that individuals with both depression and a history of childhood trauma are less responsive to treatments that include psychotropic medication than those with depression but no trauma history. Heim and colleagues (Heim et al. 2008) conclude that trauma histories either contribute to a different subtype of depression or that heightened physiological stress responses merely mimic depressive symptomology. While the Heim et al. (2008) study was small (n < 50), their hypotheses hold significant implications for mental health diagnosis and treatment, and thus warrant additional investigation.

We seek to explore the line of inquiry posed by Danese et al. (2008) and Heim et al. (2008). In the present study, we use data collected from a sample of college students attending a large diverse university in the Southwest. We gathered survey and blood sample data in order to explore the impact of trauma on the mind and body. Using these data, we examine whether childhood trauma is merely a correlate of mental illness, or if it also serves as a moderator, contributing to unique forms of depression and anxiety. More specifically we explore the following research questions, 1) is childhood trauma (4 or more ACEs) associated with depression and/or anxiety among college students, 2) does the neuroimmune system (inflammation and neuroplasticity) mediate the relationship between childhood trauma and mental health and 3) is the relationship between the neuroimmune system and mental health different for those with and without a history of childhood trauma (a moderating effect)?

The initial ACE study was of an older adult population (average age of 56) (Felitti et al. 1998). However, research also reveals that the majority of college students have had adverse childhood experiences (Karatekin 2017; Khrapatina and Berman 2017) and that childhood trauma is associated with physical and mental health problems among college students (Karatekin 2017; Velikis et al. 2009). In addition, studies using college student samples have demonstrated associations between ACEs and heightened stress responses (Dale et al. 2018; Kalamakis et al. 2015). Thus, a college student sample can be used to replicate and extend our understanding of the impact of childhood trauma on mental health.

Methods

Procedure

Survey and biomarker data were obtained from a volunteer sample of University students. Students were recruited through courses and on-campus advertisements. Participants were offered either a $30 gift card or course credit as an incentive. Because the study involved blood sampling, exclusionary criteria included fear of needles. Participants were not excluded for medical conditions, medications, or drug or alcohol use; however, data pertaining to these issues were collected for use in statistical analyses (Rudolph et al. 2011). The sample (n = 93) included students age 18 to 27. IRB approval was obtained for the study and appropriate procedures were followed (e.g. consent forms, data security).

During the testing session, students completed a 15–20 min self-administered online survey (Qualtrics) to capture information on adverse childhood experiences, mental health, and demographics. Participants also provided one blood sample. Blood from the antecubital vein was collected in sterile serum separator tubes (BD Vacutainer Venous Blood Collection Tubes, Becton, Dickinson and Company, Franklin Lakes, New Jersey, USA). The blood samples were kept at room temperature for 15 min to allow for clotting, after which the samples were centrifuged at 1100 rpm for 15 min. Serum was then harvested, aliquoted, and stored at −20 °C until analysis. All assays were performed in duplicate, and the intra-assay and inter-assay coefficients of variance were below 10%.

Serum BDNF was quantified using commercially available enzyme-linked immunosorbent essay (ELISA) kits (Human BDNF Quantikine Immunoassay, DBD00, R&D systems). The serum samples were diluted 1:80 in the supplied sample diluent in the kit and analyzed according to the manufacturer’s instructions. The plate was read at 450 nm using a spectrophotometric plate reader (Dynex MRXe plate reader with Revelation software, Dynex Technologies, Chantilly, Virginia, USA). Concentrations of CRP in serum samples were measured by commercially available ELISA kits (Quantikine ELISA Human C-Reactive Protein kit by R&D systems). All assays were performed according to the manufacturer’s detailed instructions and the plate was read at 450 nm using the aformentioned spectrophotometric plate reader.

Measures

Depression and anxiety were the key dependent variables in the study. The Patient Health Questionnaire (PHQ-9) is a reliable and valid instrument used to assess depression (Spitzer et al. 2000; Kroenke et al. 2001). The questions ask about how often in the last two weeks the respondent felt depressed mood, loss of appetite, sleep problems, etc. These questions could be answered from 0 to 3 (not at all to nearly every day). PHQ-9 scores ranged from 0 to 27. The 9-items showed good internal reliability (Cronbach’s alpha = 0.88). Anxiety was assessed using the GAD (General Anxiety Disorder scale). The GAD is a 7-item scale that asks respondents how often in the last two weeks (not at all to nearly every day) they felt nervous, could not stop worrying, felt that something terrible was going to happen, etc. The responses for each item range from 0 to 3 and the range for the total score is 0–21. The GAD scale has established reliability and validity (Spitzer et al. 2006) and it demonstrated reliability within our sample (Cronbach’s alpha = .89).

Our key independent variables used to capture the neuroimmune system were Brain-Derived Neurotropic Factor (BDNF) and C-Reactive Protein (CRP). Our blood sample data provided an assessment of neuroplasticity/neuronal health using Brain Derived Neurotropic Factor (BDNF), a measure with established reliability and validity (Ceballos and Sharma 2016; Daskalakis et al. 2015). We measured inflammation through C-Reactive Protein (CRP). CRP is a reliable and valid measure of inflammation (Pearson et al. 2003). BDNF ranged from 44.58 to 766.73 pg/ml. CRP ranged from 1.25 to 338.65 ng/ml. Given the skewed distribution for CRP, values were natural log-transformed for the analysis. Additional covariates included the respondent’s age (years), gender (male or female), the parents’ highest level of education (coded 1 if the mother or father had a college degree, 0 if otherwise), race/ethnicity (dummy coded for non-Hispanic white and non-white), whether they were taking any prescription medication (1 for yes and 0 for no), and whether they were taking psychotropic medication specifically (1 for yes and 0 for no).

Adverse childhood experiences were captured using the ten questions from the original ACE study conducted by the Centers for Disease Control and Kaiser Permanente (Felitti et al. 1998). Respondents were asked, while they were growing up, during their first 18 years of life, did they experience physical, sexual or emotional abuse, neglect, parents’ divorce, substance use, mental illness, and/or incarceration, or domestic violence. Research has examined these ACE measures in a number of different ways (e.g. individual items, total score). However, one of the most common techniques for operationalizing adverse childhood experiences is to identify those having an ACE score of 4 or higher (Hughes et al. 2017). This level of trauma has consistently been associated with significant and substantive increases in the risk of adverse physical and mental health outcomes. Thus, we also define childhood trauma as having an ACE score of 4 or higher. We compare this to those with lower ACE scores (3 or less). It is clear that an ACE score of 3 could also represent a significant level of trauma and thus we also ran our analyses comparing those with ACE scores of 4 or higher to those with an ACE score of 0 or 1. These two approaches produced similar findings and no substantive differences. Thus, to maximize our sample size we present the results using the full sample, with a dummy coded variable capturing those with 4 or more ACEs (coded as 1) relative to those with less than four ACEs (coded as 0). This variable was used as an independent predictor and as a moderating variable in our models of depression and anxiety.

Results

Table 1 provides descriptive data on the study variables.

Table 1.

Characteristics of key variables

Variables	Mean (SD)/%
Predictors
Childhood Trauma
ACE score ≥ 4	32%
ACE score ≤ 3	68%
CRP Scores (log) a	2.00 (1.64)
BDNF Scores b	391.45 (147.71)
Outcomes
Depression Scores c	7.22 (5.70)
Anxiety Scores d	7.14 (5.38)
Covariates
Age (years) e	21.04 (2.05)
Gender
Male	23%
Female	73%
Parent’s highest level of education
College degree and above	63%
Some college or less	37%
Race/Ethnicity
Non-Hispanic White	40%
Non-White	60%
Taking any prescribed medication
Yes	46%
No	54%
Taking any psychotropic medication
Yes	3%
No	97%
Total Observations	93

^a The score range for log CRP is 0.23–7.29

^b The score range for BDNF is 44.58–766.73

^c Depression severity is measured by PHQ-9. The score range is 0–27. Higher scores indicate higher levels of depression

^d Anxiety is measured by GAD. The score range is 0–21. Higher scores indicate higher levels of anxiety

^e Age range is 18–27 years old

Table 1 reveals that childhood trauma was common among our sample. Approximately 32% of the sample report an ACE score of four or higher. As expected for a college student sample, the average age was 21 and the majority of respondents report a parent with a college degree (63%). Our sample is racially/ethnicity diverse, with approximately 40% describing themselves as non-Hispanic White and the other 60% identifying as non-White (primarily Hispanic and African-American). The majority of the sample identify as female (73%). A sizable percentage report taking prescription medication of some sort (46%). Only three respondents report taking psychotropic medication specifically (3%). Because of the low level of reported psychotropic medication use, our analyses will control for medication use generally, rather than psychotropic medication specifically. Mean depression and anxiety scores are 7.22 and 7.14, respectively. A score of ten is the threshold for identifying a clinical level of depression and/or anxiety.

Tables 2 and 3 provide our analysis of the bivariate relationships between study variables. Table 2 reveals our first line of inquiry, which was to examine how trauma (4 or more ACEs) relates to all of the study variables. Table 3 reveals how all of the study variables relate to our dependent variables of anxiety and depression.

Table 2.

Relationship between key variables and complex trauma (t-tests)

Variables (mean scores)	ACEs > =4 (n = 30)	ACEs < =3 (n = 63)	t
Age	20.90	21.12	−.471
Female	.73	.73	.000
Parent College Education	.57	.67	−.922
White	.40	.39	.029
Medication	.67	.35	2.951**
CRP Scores (log)	1.84	2.08	−.630
BDNF Scores	421.08	377.34	1.341
Depression Scores	9.27	6.24	2.462*
Anxiety Scores	9.70	5.92	3.336**

^*p < 0.05, ^**p < 0.01, ^***p < 0.001

Table 3.

Correlations between study variables and mental health (n = 93)

	Depression (PHQ-9 score)	Anxiety (GAD score)
Trauma (ACE score > =4)	.258**	.330**
BDNF	.075	−.033
Log CRP	.040	.069
Age	.084	−.038
Female	.067	.138
White	−.039	−.017
Parent College Educated	−.189	−.168
Medication	.045	.125

^*p < 0.05,^**p < 0.01,^***p < 0.001

Our bivariate analyses allow us to explore the nature of several relationships. Most importantly, it reveals that respondents with 4 or more ACEs have significantly higher scores on the depression (PHQ-9) and anxiety (GAD) scales than those with an ACE score less than 4. They are also more likely to be taking prescription medication. However, Table 2 reveals that there is not a statistically significant relationship between trauma and physiological dysregulation (CRP and BNDF). In addition, Table 3 indicates that CRP and BDNF are not significantly associated with depression and/or anxiety. A hypothesis commonly offered in the literature is that trauma creates high levels of neuroimmune dysregulation which then contributes to mental health disorders (a mediation model). These preliminary bivariate findings do not support this hypothesis. However, to explore these relationships in more depth we ran a series of regression analyses.

Table 4 provides three regression models of depression scores. Model 1 examines the effects of 4 or more ACEs when controlling for demographic characteristics. Model 2 adds biomarker data for neuroplasticity (BDNF) and inflammation (CRP) in order to determine if the higher rates of depression found for those with childhood trauma might be mediated by neuroimmune dysregulation (even though there were no bivariate associations between trauma and the neuroimmune measures). Finally, we explored the possibility of a moderating effect of trauma. First, we ran two separate models for those with and without 4 or more ACEs (results not shown). These analyses revealed process differences in the effects of the neuroimmune variables on mental health. In order to test for the significance of the process differences, we developed Model 3, which includes two interaction terms for the combined effect of childhood trauma and neuroimmune system functioning.

Table 4.

OLS regressions predicting depression (PHQ-9 scores)

Independent variables	Model 1		Model 2		Model 3
	β	t	β	t	β	t
Trauma (ref. ACE scores ≤3)	0.24	2.12*	0.28	2.38*	0.13	0.37
CRP scores (log)			0.17	1.46	−0.004	−0.03
BDNF scores			0.05	0.44	0.04	0.29
Interactions
ACE x CRP					0.50	2.50*
ACE x BDNF					−0.23	−0.63
Covariates
Age	0.14	0.21	0.13	1.17	0.10	0.87
Female (ref. male)	0.11	0.93	0.11	0.89	0.04	0.32
Parent’s Education (ref. some college or less)	−0.16	−1.40	−0.18	−1.58	−0.17	−1.49
White (ref. non-white)	−0.02	−0.16	0.02	0.15	−0.06	−0.48
Taking prescribed medication	−0.05	−0.44	−1.14	−1.11	−0.11	−0.87
R squared	.101		.136		.204
n	89		84		84

^*p < 0.05, ^**p < 0.01, ^***p < 0.001

Model 1 reveals that having 4 or more ACEs is associated with an increase in depression scores, net of the effects of covariates such as age, gender, parent’s education, race/ethnicity, and prescription medication use. As revealed in the bivariate analyses, Model 2 also indicates that this effect is not mediated by neuroimmune functioning. While it is commonly suggested, we do not find that 4 or more ACEs simply increases physiological dysregulation which in turn increases depression. However, Model 3 reveals a more complicated relationship, one where an ACE score of 4 or higher serves as a moderator. In Model 3, inflammation (CRP) interacts with trauma (4 or more ACEs) to increase depression scores. However, there is no impact of CRP for those without this level of childhood trauma. These findings suggest that inflammation may contribute to, or accompany, depression for those with 4 or more ACEs, but is unlikely to characterize depression among those without these childhood experiences. Interestingly, the CRP/Trauma effect is the only significant predictor in the model. It eliminates the effect of 4 or more ACEs alone and results in a model which explains approximately 20% of the variance in depression (R^2 = ..204).

Table 5 provides a similar analysis for the dependent variable of anxiety (GAD scores).

Table 5.

OLS regressions predicting anxiety (GAD scores)

Independent variables	Model 1		Model 2		Model 3
	β	t	β	t	β	t
Trauma (ref. ACE scores ≤3)	0.30	2.74**	0.41	3.64**	0.82	2.51*
CRP scores (log)			0.21	1.94	0.11	0.86
BDNF scores			−0.08	−0.71	0.02	0.14
Interactions
ACE x CRP					0.41	2.13*
ACE x BDNF					−0.77	−2.17*
Covariates
Age	0.03	0.23	0.03	0.24	−0.003	−0.02
Female (ref. male)	0.13	1.16	0.14	1.18	0.09	0.79
Parent’s Education (ref. some college or less)	−0.13	−1.16	−0.14	−1.22	−0.11	−1.00
White (ref. non-white)	−0.01	−0.05	0.02	0.13	−0.04	−0.48
Taking prescribed medication	0.001	0.01	−0.15	−1.18	−0.14	−1.12
R squared	.133		.203		.271
n	89		84		84

^*p < 0.05, ^**p < 0.01, ^***p < 0.001

Similar to the results for depression, Table 5 reveals that 4 or more ACEs is associated with an increase in anxiety scores, net of demographic controls (Model 1). It also shows that this effect is not mediated by BDNF and/or CRP (Model 2). Model 3, reveals again, that trauma serves to moderate the effect of the neuroimmune system variables on mental health. In this model, the interaction terms for 4 or more ACEs and BDNF and CRP are statistically significant. As expected, BDNF (neuroplasticity) reduces anxiety for those with a history of 4 or more ACEs and CRP (inflammation) increases it. These effects were not found for those without this history of trauma. This model also has a relatively high level of explained variance as well (R² = .271). However, unlike the model for depression, 4 or more ACEs remains a significant predictor of anxiety when all relevant controls and interaction terms are included.

Discussion

Researchers have identified biological and environmental risk factors for mental illness, and the most progressive lines of inquiry explore the interaction between the two categories (Nestler et al. 2016). In particular, we now understand that childhood trauma can create a level of toxic stress in the body that can impact physical and mental health across the life course (Hanson et al. 2015; Shonkoff et al. 2012). In light of these new insights, there is growing pressure to make the mental health system more trauma-informed (Ko et al. 2008; SAMSHA 2014). However, mental health treatment protocols have been slow to respond to this more sophisticated portrait of mental health. Trauma screeners and biological tests for physiological dysregulation are not standard practice. Rather, mental health diagnoses are typically based upon self-reported symptoms classified as mental illnesses in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) (Frances 2013; Pickersgill 2014). The current system is also predicated upon the biomedical model of mental health (e.g. chemical imbalances in the brain) which typically does not acknowledge environmental causes (Frances 2013; Whitaker 2010). Consequently, the most common treatments are those that focus on brain chemistry (psychotropic medication) and/or therapies to affect thought processes (cognitive behavioral therapy) (Whitaker 2010; Whooley 2014).

The trauma perspective has not yet fully transformed the mental health field, in part, because of gaps in the research on childhood trauma and adult mental health. Advocates for the trauma perspective have long argued that those with trauma histories should be treated in a fundamentally different way than those presenting with mental disorders but without these adverse experiences (Elliott et al. 2005). However, the research has not provided those advocating for the trauma perspective with sufficient supporting evidence for their position. Providers may accept that trauma affects the mind and the body and increases the risk of mental health problems, but practice as if this knowledge doesn’t require a change in the way they treat the mental health disorders that emerge from traumatic experiences (Watt 2017).

The present study contributes to the small but growing body of evidence which suggests that the mental health disorders of those with childhood trauma histories are unique and should be treated as such. Specifically, we find that neuronal health and inflammation are associated with mental health disorders for those with 4 or more ACEs, but not for those without these childhood experiences. These findings are compatible with theories of how adverse childhood experiences might relate to the neuroimmune system (Nusslock and Miller 2016). They also support research by Danese et al. (2008) and Heim et al. (2008). Danese and colleagues (Danese et al. 2008) found a co-occurrence of inflammation and depression among those with a history of child maltreatment but not among those without these experiences. Heim et al. (2008) found more heightened stress responses and a stronger correlation between stress responses and depressive symptoms among depressed individuals with a history of childhood trauma compared to those with depression but without these experiences. They also found that those with childhood trauma and depression were less responsive to psychotropic medication. These studies, as does ours, reveal moderating relationships, indicating that developmental pathways to and/or characteristics of mental illness are different for those with trauma histories.

As the body of empirical evidence for a moderating effect of trauma grows, it becomes more important to clarify the resulting implications. This emergent research reveals that the nature of depression and anxiety experienced by those with childhood trauma is more likely to be characterized by physiological dysregulation than disorders experienced by individuals who do not share these histories. It could be that these physiological factors are a cause of their mental health symptoms, a consequence, or both. This is not yet known and needs to be explored. If the problems in the neuroimmune system are causal factors, then interventions are needed to address these underlying physiological processes. If these physiological factors are also, or instead, a consequence, then they also need to be addressed as they can exacerbate mental health disorders and contribute to additional physical health problems (e.g. heart disease). Thus, providers who encounter individuals exhibiting symptoms of depression and/or anxiety should screen for childhood trauma and physiological dysregulation before they develop their treatment plans. If these additional risks are present, treatments which aim to improve inflammation and neuroplasticity may be the most appropriate first step. For example, exercise, meditation, and aromatherapy massage have been shown to increase BDNF levels/neuroplasticity (Erickson et al. 2011; Tolahunase et al. 2018; Wu et al. 2014). Likewise, inflammation is responsive to lifestyle interventions such as diet (Giugliano et al. 2006), physical activity (Kasapis and Thompson 2005), and meditation (Pace et al. 2009). In addition, yoga is particularly effective at addressing irregularities in the “fight or flight” mechanism and states of hypervigilance as it reduces heart rate, blood pressure, stress responses and inflammation, and the effects are in many cases, greater than those associated with regular exercise (Ross and Thomas 2010). Finally, there is also a need to increase access to therapies that are designed specifically to address the underlying trauma (e.g. trauma-focused cognitive behavioral therapy) (Mannarino et al. 2014).

There are a number of limitations of the present study. Our data are cross-sectional, thus we cannot establish the causal pathways through which physiological processes and mental health disorders come to be associated with one another for those with adverse childhood experiences. In addition, from our investigation we can only speculate that this association should lead to tailored treatments. That hypothesis will require more rigorous evaluation of the differential effects of various treatments. Finally, our investigation is a small study of college students, and thus requires replication with larger, more representative samples. All of these limitations identify potential avenues for future investigation.

While more research is needed, our findings contribute to an emergent body of work which indicates a need to view and treat mental disorders rooted in trauma differently from those without these antecedent causes. In order to do this, mental health providers need to be equipped with a broader array of diagnostic tools and treatment modalities so that they can understand and address the heterogeneity in the population of those suffering from mental health disorders. These changes can help to create an interdisciplinary research-based mental health system, one that promotes recovery by addressing the complex array of root causes, rather than relying on treatment protocols designed only to suppress symptoms.

Compliance with Ethical Standards

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed Consent

Informed consent was obtained from all individual participants included in the study.

Conflict of Interest

The authors declare that they have no conflict of interest.