Significance The primary finding in this study was the dramatic primary association of brain resting-state network (RSN) connectivity abnormalities with a history of childhood trauma in major depressive disorder (MDD). Even though participants in this study were not selected for a history of trauma and the brain imaging took place decades after trauma occurrence, the scar of prior trauma was evident in functional dysconnectivity. In addition to childhood trauma, dimensions of MDD symptoms were related to abnormal network connectivity. Further, we found that a network model of MDD described within- and between-network connectivity differences from controls in multiple RSNs, including the default mode network, frontoparietal network, and attention and sensory systems.

Abstract Patients with major depressive disorder (MDD) present with heterogeneous symptom profiles, while neurobiological mechanisms are still largely unknown. Brain network studies consistently report disruptions of resting-state networks (RSNs) in patients with MDD, including hypoconnectivity in the frontoparietal network (FPN), hyperconnectivity in the default mode network (DMN), and increased connection between the DMN and FPN. Using a large, multisite fMRI dataset (n = 189 patients with MDD, n = 39 controls), we investigated network connectivity differences within and between RSNs in patients with MDD and healthy controls. We found that MDD could be characterized by a network model with the following abnormalities relative to controls: (i) lower within-network connectivity in three task-positive RSNs [FPN, dorsal attention network (DAN), and cingulo-opercular network (CON)], (ii) higher within-network connectivity in two intrinsic networks [DMN and salience network (SAN)], and (iii) higher within-network connectivity in two sensory networks [sensorimotor network (SMN) and visual network (VIS)]. Furthermore, we found significant alterations in connectivity between a number of these networks. Among patients with MDD, a history of childhood trauma and current symptoms quantified by clinical assessments were associated with a multivariate pattern of seven different within- and between-network connectivities involving the DAN, FPN, CON, subcortical regions, ventral attention network (VAN), auditory network (AUD), VIS, and SMN. Overall, our study showed that traumatic childhood experiences and dimensional symptoms are linked to abnormal network architecture in MDD. Our results suggest that RSN connectivity may explain underlying neurobiological mechanisms of MDD symptoms and has the potential to serve as an effective diagnostic biomarker.

Major depressive disorder (MDD) is a common mental disorder characterized by heterogeneous symptoms: persistently depressed mood, loss of interest, low self-esteem and energy level, weight change, insomnia or hypersomnia, and disturbance in cognitive functions such as attention and memory (1). These symptoms impair daily life function and increase the risk of suicide (2). According to the WHO, depression is the fourth leading cause of disability worldwide and is projected to be second by 2020 (3). In addition, experiences of childhood trauma, including physical, sexual, or emotional abuse, as well as physical or emotional neglect, have been found to be associated with the emergence and persistence of depressive and anxiety disorders (4). However, neurobiological mechanisms underlying the dimensional symptoms of MDD remain unclear (5, 6).

The human brain contains an estimated 100–1,000 trillion synapses. This complex neural system is amenable to scientific investigation from a network perspective by using modern network theory (7) to reveal resting-state networks (RSNs) (8, 9) that play important roles in brain function and disease, including major depression. MDD has been found to be associated with specific abnormalities in multiple RSNs compared with healthy controls (10). In particular, fMRI studies have consistently reported reduced functional connectivity (hypoconnectivity) within the frontoparietal network (FPN) (11, 12), increased connectivity (hyperconnectivity) within the default mode network (DMN) (13, 14), and hyperconnectivity between the DMN and FPN in patients with MDD. The FPN is involved in executive control of attention and emotion, while the DMN is involved in internally oriented attention and self-referential processing (15, 16). Dysfunction of these networks is integrally associated with MDD (5). A few studies also found salience network (SAN) (17) and dorsal attention network (DAN) (18) dysfunction in MDD, but these findings are less frequently reported than those for the DMN and FPN. A recent large (556 patients with MDD and 518 healthy controls) meta-analysis of seed-based RSN studies confirmed alterations in functional connectivity in the DMN, FPN, SAN, and DAN among patients with MDD (19). Moreover, the abnormalities in network connectivity in MDD have been shown to be associated with depression severity (20), illness duration (18, 21), the number and length of episodes (13, 21), and treatment outcomes (22, 23). However, none of these studies used multivariate methods to simultaneously examine relationships among brain networks and item-level data from clinical assessments.

In this study, we first compared differences in brain networks between patients with MDD and controls. Then, among the patients with MDD, we used multivariate methods to examine correlations between network measures and a large number of clinical variables that had first been grouped into clusters. In particular, we used a multisite fMRI dataset consisting of 189 patients with MDD and 39 healthy controls to investigate abnormalities in the system-level brain network architecture in patients with MDD relative to controls. Among the patients with MDD, we also studied relationships between brain networks and clinical symptoms, including depression (general and anhedonic depression), anxiety, personality (neuroticism, extraversion, openness, agreeableness, and conscientiousness), suicidality, and experiences of childhood trauma (physical abuse/neglect, emotional abuse/neglect, and sexual abuse), which were measured by 213 item-level survey questions. We hypothesized that (i) patients with MDD would present with abnormal connectivity patterns of RSNs, including the DMN and FPN, compared with controls, using a system-level connectivity analysis, and (ii) multivariate patterns of network connectivity within and between RSNs in patients with MDD would be associated with clinical symptoms, quantified by data-driven clustering of item-level survey data. To test our second hypothesis, we used canonical correlation analysis (CCA) to identify multivariate relationships between RSN connectivity measures and item-level clinical data in patients with MDD. Recent studies (20, 24) have shown that CCA, a powerful multivariate approach that seeks to identify clusters of maximal correlation between two groups of variables, can detect associations between structural or functional connectivity and behavioral measures. To our knowledge, our work is the first to apply CCA to study multivariate relationships between network connectivity and item-level clinical data in patients with MDD.

Discussion Symptom-Specific Changes of Within- and Between-Network Connectivity in MDD. This data-driven study shows symptom-specific, system-level alterations of brain network connectivity in major depression. Our main findings are reflected in both network measures correlated with symptom clusters and connectivity abnormalities relative to controls. Previous studies that used the same subjects have found that several symptoms of major depression, such as anhedonia (27) (using task-fMRI data), anxiety (using clinical data) (28), and neuroticism (using EEG data) (29), were related to neural function and behavioral phenotyping in patients with MDD. However, these studies did not examine resting-state fMRI data and did not examine a full spectrum of data-driven behavioral brain network architectures. Several previous studies that examined brain network attributes have shown associations with depression and anxiety symptoms measured by various summary clinical scores (11, 13, 21, 30). Our study, however, investigates multivariate network-related associations with item-level data that characterize a broad range of dimensional symptoms: experiences of childhood trauma, depression, anxiety, anhedonia, neuroticism, suicidal tendency, and personality traits. Notably, we found that experiences of childhood trauma [not reported previously in association with brain networks in depression (5, 19)] had by far the strongest association among these patient symptom–brain network correlations. Traumatic experiences were correlated with within-network connectivity of the DAN and subcortical regions (SUB) and with between-network connectivity involving task-positive networks (DAN, FPN, and CON) and sensory systems (SMN, VIS, and AUD). With estimates of ∼10% of all children in the United States having been subjected to child abuse, the significance of child maltreatment on brain morphology and function is an important consideration (31). The population attributable risk of adverse childhood experiences (ACEs) accounts for 67% of suicide attempts (32), and exposure to six or more ACEs was found to account for a 20-y reduction in lifespan (33). SMN connectivity with the DAN and VIS connectivity with the CON were especially indicative of emotional abuse/neglect and physical abuse/neglect, respectively. These systems have been related to treatment outcomes in affective disorders, risk, and family history of depression (34), and to functional domains, including error monitoring and top-down attentional control (35). We speculate that physical abuse/neglect and emotional abuse/neglect may have induced abnormal activation of sensory systems, such as the sensorimotor and visual cortex, and to have dysregulated connectivity with ventral and dorsal attention systems. Specifically, the increased DAN-SMN correlation with emotional abuse/neglect and increased CON-VIS and DAN-VAN correlations with physical abuse and neglect identified in our study can be interpreted in light of the role of the DAN in regulation of perceptual attention (36). How this alteration in connections occurs is not clear, but one hypothesis is that it might involve early developmental changes that are then impacted by experience. For example, the interhemispheric coherence within the DMN is already strong by the age of 6 y, but anterior-posterior coherence between the medial prefrontal cortex and parietal regions is relatively weak at this stage compared with future stages (37), suggesting an important experiential aspect in sculpting the DMN. Analogously, interhemispheric connectivity within the dorsal attention system may develop early, but anterior-posterior coherence may receive important experiential influences (e.g., ACEs), disrupting connectivity. This network sculpting may be affected by early-life stressors and trauma, which have been shown to predispose individuals to the development of depression (38), potentially through factors acting on neuroplasticity and connectivity (39). Another study (40) also found that childhood emotional maltreatment was associated with abnormal SUB and SAN connectivity. Our findings regarding childhood trauma-related functional network abnormalities in MDD could also be interpreted alternatively. Both experimental (41, 42) and modeling (43) studies have demonstrated that functional networks are shaped by the underlying structural networks. Of note, previous studies have shown that patients who experienced repeated episodes of trauma had alterations in gray matter volumes and structural integrity of sensory systems (44⇓–46). Thus, it is plausible that resting-state functional connectivity with sensory systems could be disrupted as sequelae of childhood maltreatment, as found in our study. A comprehensive review of the structural and functional consequences of childhood maltreatment (47) identified over 180 studies with findings of associated brain abnormalities, frequently manifested as structural abnormalities in subcortical regions. In the current study, we found that childhood trauma-related network connectivity abnormalities were preserved and detected even well into adulthood. Therefore, our current study not only confirmed the important relationship between childhood trauma and major depression but also linked patients’ experiences of childhood trauma with specific functional brain network abnormalities that suggest a possible environmental contributor to neurobiological clinical symptom profiles. In addition, we found that depressive symptoms, personality traits, and sexual abuse were associated with subcortical and between-network connectivity involving the three task-positive networks (DAN, FPN, and CON) (48) and three sensory systems (SMN, VIS, and AUD), which is consistent with previous studies (5, 10, 49) and supports the idea that many brain network features contribute to broad clinical pathology. Several items of sexual abuse, as with physical and emotional abuse, were especially related to increased within-network DAN connectivity and network connectivity between the DAN and FPN. This system may be particularly related to regulation of perceptual attention (36, 50) with related consequences for depressed patients (51, 52), increasing negative attention bias. Neuroticism (negative correlation) and positive mood symptoms (positive correlation) were especially linked to within-SUB connectivity, which has a consistent precedent in the prior literature (53⇓–55). As might be expected, opposite behavioral characteristics (suicidality and openness, anxiety and agreeableness) had opposite signs in their network correlations with DAN-VAN and CON-VIS, respectively. Moreover, the association between network connectivity involving the task-positive networks and sensory systems with dimensional depression symptoms and personality, such as FPN-DAN (negative correlation with depression), DAN-SMN (positive correlation with anhedonia), and CON-AUD (negative correlation with conscientiousness), further confirmed that disturbance of executive control (FPN/CON), external attention processing (DAN/VAN), and personality in patients with MDD could be characterized by abnormal information transfer between corresponding networks (10, 19, 56). Although the specific symptom and brain network domains were linked in a broad way across these measures in this cohort, the specific links between clinically relevant features and resting fMRI detailed here may guide research into additional patient populations that may share symptom and brain pathology profiles with MDD (57, 58). Difference in Within- and Between-Network Connectivity in Patients with MDD Compared with Controls. We identified a network model of patients with MDD relative to controls that corroborates the abnormal within-network connectivity of DMN and FPN that has consistently been reported by previous experimental studies (11, 13, 14) and by a recent large meta-analysis (19). However, our study also identified less frequently reported abnormal within-network connectivity in the DAN (18), SAN (17), and CON (59). Of note, increased DMN connectivity and decreased FPN, CON, and DAN connectivity have been found in other studies to be related to higher levels of maladaptive rumination (11) and goal-oriented attention deficits in MDD (19), respectively. Overall, the interpretation of the current findings can be placed in a broader context supporting network imbalance between the task-positive (FPN, CON, and DAN) and intrinsic (DMN and SAN) networks that results in the cognitive and executive dysfunction, as well as emotional dysregulation, that characterize MDD (60). In addition to different within-network connectivity from controls, we identified abnormal between-network connectivity. These network abnormalities occur in both task-positive and task-negative systems. Task-positive networks (i.e., the FPN, CON, DAN) are primarily involved in executive control and external attention. Our results suggest that the abnormal connectivity patterns of these networks are related to dysfunction of executive control (as reflected by decreased FPN and CON connectivity) (61, 62) and external attention (as related to decreased DAN connectivity) (63). In contrast, the DMN plays an important role in internal attention and self-referential thinking when external demands for attention are minimal (8, 16). The increased connectivity of the DMN, with its focus on internal states, could exacerbate the tendency for patients to dwell or ruminate on negative feelings and events (11, 14, 64). Moreover, the prominent role of the SAN in emotion regulation for salient events and sensory experiences might explain how the abnormal increased within-network connectivity (segregation) in the SAN could contribute to ruminative responses to negative mood states and life events in patients with MDD (65). Thus, our results provide further evidence for the integrative role of DMN and FPN in cognitive processing and for further understanding the neurocircuitry basis of major depression. In summary, we provide evidence for brain network abnormalities in patients with MDD compared with controls and for multivariate patient symptom–brain network associations that are most notably driven by experiences of childhood trauma. Future Directions. In this study, our primary focus was on the multivariate correlation patterns between symptom profiles in major depression and brain networks. In future work, these multivariate patient symptom–brain network associations can be extended to other patient samples with depressive symptoms and other samples with a history of childhood trauma to determine whether these associations generalize. Further, CCA can be employed more generally to investigate multivariate correlation profiles in other psychiatric disorders.

Acknowledgments We thank Dr. Danielle Bassett, Dr. Richard Betzel, and Dr. Theodore Satterthwaite for their helpful suggestions about the estimation of functional connectivity and motion correction. We thank Jared Zimmerman for many helpful discussions and suggestions about presentation of the results. We also thank Rastko Ciric and Irem Aselcioglu for helping with data processing and providing valuable support and discussion. We thank Maria Prociuk for her assistance with the preparation and submission of the manuscript. We also thank all participants for their participation. We acknowledge the following support: Grant U01 MH109991 (to Y.I.S.), Grants R01 NS085211 and RG-1707-28586 (to R.T.S.), Grant R01-MH111886 (to D.J.O.), Grant U01 MH092221 (to M.H.T.), and Grant U01 MH092250 (to P.M., R.P., and M.M.W.). The content is solely the responsibility of the authors and does not necessarily represent the official views of any of the funding agencies.

Footnotes Author contributions: M.Y. and Y.I.S. designed research; M.Y., K.A.L., R.T.S., and Y.I.S. performed research; M.A.O., M.L.P., M.M., M.F., M.H.T., P.M., R.P., and M.M.W. collected data; M.Y., P.A.C., and T.M.M. analyzed data; and M.Y., K.A.L., R.T.S., D.J.O., R.D., and Y.I.S. wrote the paper.

Conflict of interest statement: A comprehensive list of lifetime disclosures of M.F. is available at https://mghcme.org/faculty/faculty-detail/maurizio_fava. M.A.O. receives royalties for the use of the Columbia Suicide Severity Rating Scale and has received financial compensation from Pfizer for the safety evaluation of a clinical facility, unrelated to the current study; she was the recipient of a grant from Eli Lilly to support a year’s salary for the Lilly Suicide Scholar, Enrique Baca-Garcia; she has received unrestricted educational grants and/or lecture fees from AstraZeneca, Bristol-Myers Squibb, Eli Lilly, Janssen, Otsuka, Pfizer, Sanofi-Aventis, and Shire; and her family owns stock in Bristol-Myers Squibb. P.M. has received research grant support from Forest, Naurex, and Sunovion. M.M.W. has received funding from the Interstitial Cystitis Association, National Alliance for the Research of Schizophrenia and Depression (NARSAD), the National Institute on Drug Abuse, the National Institute of Mental Health (NIMH), the Sackler Foundation, and the Templeton Foundation, and she receives royalties from American Psychiatric Publishing, MultiHealth Systems, Oxford University Press, and Perseus Press. M.H.T. is or has served as an advisor/consultant and has received fees from Abbott Laboratories, Abdi Ibrahim, Akzo (Organon Pharmaceuticals), Alkermes, AstraZeneca, Axon Advisors, Bristol-Myers Squibb, Cephalon, Cerecor, the CME Institute of Physicians, Concert Pharmaceuticals, Eli Lilly, Evotec, Fabre Kramer Pharmaceuticals, Forest Pharmaceuticals, GlaxoSmithKline, Janssen Global Services LLC, Janssen Pharmaceutica Products LP, Johnson and Johnson Pharmaceutical Research and Development, Libby, Lundbeck, Meade Johnson, MedAvante, Medtronic, Merck, Mitsubishi Tanabe Pharma Development America, Naurex, Neuronetics, Otsuka Pharmaceuticals, Pamlab, Parke-Davis Pharmaceuticals, Pfizer, PgxHealth, Phoenix Marketing Solutions, Rexahn Pharmaceuticals, Ridge Diagnostics, Roche Products Ltd., Sepracor, Shire Development, Sierra, SK Life Science, Sunovion, Takeda, Tal Medical/Puretech Venture, Targacept, Transcept, VantagePoint, Vivus, and Wyeth-Ayerst Laboratories, and he has received grant/research support from the Agency for Healthcare Research and Quality, Corcept Therapeutics, Cyberonics, Merck, NARSAD, the NIMH, and the National Institute on Drug Abuse. All other authors report no financial relationships with commercial interests.

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