Delineation of early and later adult onset depression by diffusion tensor imaging

Integrating brain imaging features and genomic profiles for the subtyping of major depression

BACKGROUND

Precise stratification of patients into homogeneous disease subgroups could address the heterogeneity of phenotypes and enhance understanding of the pathophysiology underlying specific subtypes. Existing literature on subtyping patients with major depressive disorder (MDD) mainly utilized clinical features only. Genomic and imaging data may improve subtyping, but advanced methods are required due to the high dimensionality of features.

METHODS

We propose a novel disease subtyping framework for MDD by integrating brain structural features, genotype-predicted expression levels in brain tissues, and clinical features. Using a multi-view biclustering approach, we classify patients into clinically and biologically homogeneous subgroups. Additionally, we propose approaches to identify causally relevant genes for clustering.

RESULTS

We verified the reliability of the subtyping model by internal and external validation. High prediction strengths (PS) (average PS: 0.896, minimum: 0.854), a measure of generalizability of the derived clusters in independent datasets, support the validity of our approach. External validation using patient outcome variables (treatment response and hospitalization risks) confirmed the clinical relevance of the identified subgroups. Furthermore, subtype-defining genes overlapped with known susceptibility genes for MDD and were involved in relevant biological pathways. In addition, drug repositioning analysis based on these genes prioritized promising candidates for subtype-specific treatments.

CONCLUSIONS

Our approach successfully stratified MDD patients into subgroups with distinct clinical prognoses. The identification of biologically and clinically meaningful subtypes may enable more personalized treatment strategies. This study also provides a framework for disease subtyping that can be extended to other complex disorders.

Unveiling diverse clinical symptom patterns and neural activity profiles in major depressive disorder subtypes

BACKGROUND

The heterogeneity of major depressive disorder (MDD) significantly hinders its effective and optimal clinical outcomes. This study aimed to identify MDD subtypes by adopting a data-driven approach and assessing validity based on symptomatology and neuroimaging.

METHODS

A total of 259 patients with MDD and 92 healthy controls were enrolled in this cross-sectional study. Latent profile analysis (LPA) was used to identify MDD subtypes based on validated clinical symptoms. To examine whether there were differences between these identified MDD subtypes, network analysis was used to test any differences in symptom patterns between these subtypes. We also compared neural activity between these identified MDD subtypes and tested whether certain neural activities were related to individual subtypes. This MDD subtyping was further tested in an independent dataset that contains 86 patients with MDD.

FINDINGS

Five MDD subtypes with distinct depressive symptom patterns were identified using the LPA model, with the 5-class model selected as the optimal classification solution based on its superior fit indices (AIC = 6656.296, aBIC = 6681.030, entropy = 0.917, LMR p = 0.3267, BLRT p < 0.001). The identified subtypes include atypical-like depression, two melancholic depression (moderate and severe) subtypes with distinct patterns on feeling anxious, and two anhedonic depression subtypes (moderate and severe) with different manifestations on weight/appetite loss. The reproducibility of the classification was also confirmed. Significant differences in symptom structures between melancholic and two anhedonic subtypes, and between anhedonic and atypical subtypes were observed (all p < 0.05). Furthermore, these identified subtypes had differential neural activities in both regional spontaneous neural activity (pFWE < 0.005) and functional connectivity between different brain regions (pFDR < 0.005), linked to different clinical symptoms (FDR q < 0.05).

INTERPRETATION

The network analysis and neuroimaging tests support the existence and validity of the identified MDD subtypes, each exhibiting unique clinical manifestations and neural activity patterns. The categorisation of these subtypes sheds light on the heterogeneity of depression and suggest that personalised treatment and management strategies tailored to specific subtypes may enhance intervention strategies in clinical settings.

FUNDING

National Natural Science Foundation of China (NSFC) and China Scholarship Council (CSC).

Lateralized white matter integrity changes across the lifespan in major depression: AES-SDM meta-analysis

This meta-analysis examined white matter fractional anisotropy (FA) differences across the lifespan to better understand underlying neurobiological mechanisms of major depressive disorder (MDD). Using anisotropic effect size-based-signed differential mapping (AES-SDM), the study meta-analyzed 67 whole-brain FA voxel-based analysis (VBA) and tract-based spatial statistics (TBSS) studies. The sample included 3620 individuals with MDD and 3764 age-matched healthy controls, ranging from adolescence to older adulthood. AES-SDM uses anisotropic kernels combined with random-effects models and permutation tests to perform robust neuroimaging meta-analysis. Between-group analyses uncovered a lateralization effect: Adolescent and adult MDD were associated with left-hemisphere abnormalities, while older adult MDD was associated with right-hemisphere abnormalities. Specifically, MDD was associated with lower left anterior thalamic projection, left pons, left corticospinal projection, and left cingulum FA in adolescents; lower left optic radiation, left striatum, left cingulum, and left inferior longitudinal fasciculus FA in adults; and lower right anterior thalamic projection, right fronto-occipital fasciculus, right striatum, right superior longitudinal fasciculus, and left inferior longitudinal fasciculus FA in older adults. The laterality seen in the current data and previous research could potentially serve as biomarkers to improve diagnostic accuracy. It is recommended that future white matter MDD primary studies include more adolescents and older adults.

Subtyping drug-free first-episode major depressive disorder based on cortical surface area alterations

BACKGROUND

Major depressive disorder (MDD) is recognized as a complex and heterogeneous metal illness, characterized by diverse clinical symptoms and variable treatment outcomes. Previous studies have repeatedly reported alterations in brain morphology in MDD, but findings vary across sample characteristics. Whether this neurobiological substrate could stratify MDD into more homogeneous clinical subgroups thus improving personalized medicine remains unknown.

METHODS

We included 65 drug-free patients with first-episode MDD and 66 healthy controls (HCs) and collected their structural MRI data. We performed the surface reconstruction and calculated cortical surface area using Freesurfer. The surface area of 34 Gy matter regions in each hemisphere based on the Desikan-Killiany atlas were extracted for each participant and subtyping results were obtained with the Louvain community detection algorithm. The demographic and clinical characteristics were then compared between MDD subgroups.

RESULTS

Two subgroups defined by distinct patterns of cortical surface area were identified in first-episode MDD. Subgroup 1 exhibited a significant reduction in surface area across nearly the entire cortex compared to subgroup 2 and HCs, whereas subgroup 2 demonstrated increased surface area than HCs. Further, subgroup 1 exhibited a higher proportion of females, and higher severity of anxiety symptoms compared to subgroup 2.

LIMITATIONS

The relatively small sample size.

CONCLUSIONS

This study identified two neurobiologically subgroups with distinct alterations in cortical surface area among drug-free patients with first-episode MDD. Our results highlight the promise of in delineating morphological heterogeneity within MDD, particularly in relation to the severity of anxiety symptoms.

Demyelination in Patients with POST-COVID Depression

Background: Depression is one of the most severe sequelae of COVID-19, with major depressive disorder often characterized by disruption in white matter (WM) connectivity stemming from changes in brain myelination. This study aimed to quantitatively assess brain myelination in clinically diagnosed post-COVID depression (PCD) using the recently proposed MRI method, macromolecular proton fraction (MPF) mapping. Methods: The study involved 63 recovered COVID-19 patients (52 mild, 11 moderate, and 2 severe) at 13.5 ± 10.0 months post-recovery, with matched controls without prior COVID-19 history (n = 19). A post-COVID depression group (PCD, n = 25) was identified based on psychiatric diagnosis, while a comparison group (noPCD, n = 38) included participants with neurological COVID-19 complications, excluding clinical depression. Results: Fast MPF mapping revealed extensive demyelination in PCD patients, particularly in juxtacortical WM (predominantly occipital lobe and medial surface), WM tracts (inferior fronto-occipital fasciculus (IFOF), posterior thalamic radiation, external capsule, sagittal stratum, tapetum), and grey matter (GM) structures (hippocampus, putamen, globus pallidus, and amygdala). The noPCD group also displayed notable demyelination, but with less magnitude and propagation. Multiple regression analysis highlighted IFOF demyelination as the primary predictor of Hamilton scores, PCD presence, and severity. The number of post-COVID symptoms was a significant predictor of PCD presence, while the number of acute symptoms was a significant predictor of PCD severity. Conclusions: This study, for the first time, reveals extensive demyelination in numerous WM and GM structures in PCD, outlining IFOF demyelination as a key biomarker.

Challenges in Identifying Individualized Brain Biomarkers of Late Life Depression

Research into neuroimaging biomarkers for Late Life Depression (LLD) has identified neural correlates of LLD including increased white matter hyperintensities and reduced hippocampal volume. However, studies into neuroimaging biomarkers for LLD largely fail to converge. This lack of replicability is potentially due to challenges linked to construct variability, etiological heterogeneity, and experimental rigor. We discuss suggestions to help address these challenges, including improved construct standardization, increased sample sizes, multimodal approaches to parse heterogeneity, and the use of individualized analytical models.

A neuroimaging-based precision medicine framework for depression

BACKGROUND

Symptom-based diagnostic criteria of depression leads to notorious heterogeneity and subjectivity.

METHODS

The study was conducted in two stages at two sites: development of a neuroimaging-based subtyping and precise repetitive transcranial magnetic stimulation (rTMS) strategy for depression at Center 1 and its clinical application at Center 2. Center 1 identified depression subtypes and subtype-specific rTMS targets based on amplitude of low frequency fluctuation (ALFF) in a cohort of 238 major depressive disorder patients and 66 healthy controls (HC). Subtypes were identified using a Gaussian Mixture Model, and subtype-specific rTMS targets were selected based on dominant brain regions prominently differentiating depression subtypes from HC. Subsequently, one classifier was employed and 72 hospitalized, depressed youths at Center 2 received two-week precise rTMS. MRI and clinical assessments were obtained at baseline, midpoint, and treatment completion for evaluation.

RESULTS

Two neuroimaging subtypes of depression, archetypal and atypical depression, were identified based on distinct frontal-posterior functional imbalance patterns as measured by ALFF. The dorsomedial prefrontal cortex was identified as the rTMS target for archetypal depression, and the occipital cortex for atypical depression. Following precise rTMS, ALFF alterations were normalized in both archetypal and atypical depressed youths, corresponding with symptom response of 90.00% in archetypal depression and 70.73% in atypical depression.

CONCLUSIONS

A precision medicine framework for depression was developed based on objective neurobiomarkers and implemented with promising results, actualizing a subtyping-treatment-evaluation closed loop in depression. Future randomized controlled trials are warranted.

Normative modeling analysis reveals corpus callosum volume changes in early and mid-to-late first episode major depression

BACKGROUND

It has been widely accepted that major depressive disorder (MDD) impacts brain structures including the Corpus Callosum (CC). However, this assumption is based on scarce literature data involving small sample sizes. Furthermore, it is still unclear whether such CC volume changes may already be present at a first depressive episode.

METHODS

To further investigate this question, we compared 369 first-episode MDD patients (mean age = 35 years (sd = 12), 249 females; 283 early onset, 86 mid-to-late onset) from the open-source REST meta-MDD database closely matched for age and gender to 490 never-depressed individuals (mean age = 37 years (sd = 14); 309 females) using Z-scores obtained from normative neuroanatomical modeling to assess individual variability in CC (sub)volumes.

RESULTS

Relative to the norms established by the healthy controls, first-episode MDD patients displayed CC volume (z-score) reductions in the entire CC (including the body), as did mid-to-late-onset first-episode MDD patients (age ≥ 45 y). In early-onset first-episode MDD patients (age ≤ 44 y), depression severity symptoms were related to volume increases in the entire CC, as well as the body and splenium.

LIMITATIONS

No data on depressive episode duration. Relatively small sample size for mid-to-late first-episode MDD patients.

CONCLUSIONS

Our data revealed CC (sub)volume differences in early versus mid-to-late onset first episode MDD. Especially at early onset, depression severity may result in neural white matter activity as potential reaction to stress influences. Our results underline the importance of prompt clinical interventions at early onset MDD.

Depression severity partially mediates the association between thyroid function and psychotic symptoms in first-episode, drug-naive major depressive disorder patients with comorbid anxiety at different ages of onset

BACKGROUND

Anxiety and psychotic symptoms are common in patients with major depressive disorder (MDD), with a strong association with thyroid function. Age of onset contributes to the heterogeneity of MDD patients. This study aimed to assess the prevalence of psychotic symptoms in MDD patients with comorbid anxiety and to explore the relationship between thyroid function and psychotic symptoms by ages of onset.

METHODS

A total of 894 first-episode, drug-naïve Chinese Han MDD patients with comorbid anxiety were recruited. Thyroid function and psychometric measures including Hamilton Anxiety Scale, Hamilton Depression Scale, and Positive and Negative Syndrome Scale were evaluated. Patients were divided into early adulthood onset (EAO, < 45 years old) and mid-adulthood onset (MAO, ≥ 45 years old) groups.

RESULTS

The MAO subgroup had a higher prevalence of psychotic symptoms compared to EAO subgroup. TSH and TPOAb levels were positively correlated with psychotic symptoms severity, with a more pronounced effect in MAO subgroup. Furthermore, MDD severity partially mediated the effects of TPOAb and TSH levels on psychotic symptoms in both subgroups.

LIMITATIONS

A causal relationship could not be demonstrated with this cross-sectional study, and the results should be limited to first-episode, drug-naïve MDD patients without considering more potential confounders. Moreover, the male-to-female ratio imbalance is present.

CONCLUSIONS

Our results indicated that age of onset moderated the association between thyroid function and psychotic symptom, and depression severity partially mediated the effects of thyroid function on psychotic symptoms, suggesting thyroid function may serve as a biomarker of psychotic symptoms in MDD patients with anxiety.

Brain-based Sex Differences in Depression: A Systematic Review of Neuroimaging Studies

Major depressive disorder (MDD) is a common psychiatric illness with a wide range of symptoms such as mood decline, loss of interest, and feelings of guilt and worthlessness. Women develop depression more often than men, and the diagnostic criteria for depression mainly rely on female patients' symptoms. By contrast, male depression usually manifests as anger attacks, aggression, substance use, and risk-taking behaviors. Various studies have focused on the neuroimaging findings in psychiatric disorders for a better understanding of their underlying mechanisms. With this review, we aimed to summarize the existing literature on the neuroimaging findings in depression, separated by male and female subjects. A search was conducted on PubMed and Scopus for magnetic resonance imaging (MRI), functional MRI (fMRI), and diffusion tensor imaging (DTI) studies of depression. After screening the search results, 15 MRI, 12 fMRI, and 4 DTI studies were included. Sex differences were mainly reflected in the following regions: 1) total brain, hippocampus, amygdala, habenula, anterior cingulate cortex, and corpus callosum volumes, 2) frontal and temporal gyri functions, along with functions of the caudate nucleus and prefrontal cortex, and 3) frontal fasciculi and frontal projections of corpus callosum microstructural alterations. Our review faces limitations such as small sample sizes and heterogeneity in populations and modalities. But in conclusion, it reflects the possible roles of sex-based hormonal and social factors in the depression pathophysiology.

Resolving heterogeneity in depression using individualized structural covariance network analysis

BACKGROUND

Elucidating individual aberrance is a critical first step toward precision medicine for heterogeneous disorders such as depression. The neuropathology of depression is related to abnormal inter-regional structural covariance indicating a brain maturational disruption. However, most studies focus on group-level structural covariance aberrance and ignore the interindividual heterogeneity. For that reason, we aimed to identify individualized structural covariance aberrance with the help of individualized differential structural covariance network (IDSCN) analysis.

METHODS

T1-weighted anatomical images of 195 first-episode untreated patients with depression and matched healthy controls (n = 78) were acquired. We obtained IDSCN for each patient and identified subtypes of depression based on shared differential edges.

RESULTS

As a result, patients with depression demonstrated tremendous heterogeneity in the distribution of differential structural covariance edges. Despite this heterogeneity, altered edges within subcortical-cerebellum network were often shared by most of the patients. Two robust neuroanatomical subtypes were identified. Specifically, patients in subtype 1 often shared decreased motor network-related edges. Patients in subtype 2 often shared decreased subcortical-cerebellum network-related edges. Functional annotation further revealed that differential edges in subtype 2 were mainly implicated in reward/motivation-related functional terms.

CONCLUSIONS

In conclusion, we investigated individualized differential structural covariance and identified that decreased edges within subcortical-cerebellum network are often shared by patients with depression. The identified two subtypes provide new insights into taxonomy and facilitate potential clues to precision diagnosis and treatment of depression.

Unraveling the mystery of white matter in depression: A translational perspective on recent advances

BACKGROUND

Numerous cortical and subcortical structures have been studied extensively concerning alterations of their integrity as well as their neurotransmitters in depression. However, connections between these structures have received considerably less attention.

OBJECTIVE

This systematic review presents results from recent neuroimaging as well as neuropathologic studies conducted on humans and other mammals. It aims to provide evidence for impaired white matter integrity in individuals expressing a depressive phenotype.

METHODS

A systematic database search in accordance with the PRISMA guidelines was conducted to identify imaging and postmortem studies conducted on humans with a diagnosis of major depressive disorder, as well as on rodents and primates subjected to an animal model of depression.

RESULTS

Alterations are especially apparent in frontal gyri, as well as in structures establishing interhemispheric connectivity between frontal regions. Translational neuropathological findings point to alterations in oligodendrocyte density and morphology, as well as to alterations in the expression of genes related to myelin synthesis. An important role of early life adversities in the development of depressive symptoms and white matter alterations across species is thereby revealed. Data indicating that stress can interfere with physiological myelination patterns is presented. Altered myelination is most notably present in regions that are subject to maturation during the developmental stage of exposure to adversities.

CONCLUSION

Translational studies point to replicable alterations in white matter integrity in subjects suffering from depression across multiple species. Impaired white matter integrity is apparent in imaging as well as neuropathological studies. Future studies should focus on determining to what extent influencing white matter integrity is able to improve symptoms of depression in animals as well as humans.

Age-related heterogeneity revealed by disruption of white matter structural networks in patients with first-episode untreated major depressive disorder: WM Network In OA-MDD

The clinical treatment and prognosis of major depressive disorder (MDD) are limited by the high degree of disease heterogeneity. It is unclear whether there is a potential network mechanism for age-related heterogeneity. We aimed to uncover the heterogeneity of the white matter (WM) network at different ages of onset and its correlation with different symptom characteristics. 85 first-episode MDD patients and 84 corresponding healthy controls (HCs) were recruited and underwent diffusion tensor imaging scans. Structural network characteristics were analyzed using graph theory methods. We observed an accelerated age-related decline of the WM network in MDD patients compared with HCs. Distinct symptom-related networks were identified in three MDD groups with different onset-age. For early-onset MDD (18-29 years; EOD), higher guilt and loss of interest were correlated with the insula, and inferior parietal lobe which in default mode network and salience network. For mid-term-onset MDD (30-44 years; MOD), higher somatic symptoms were correlated with thalamus which in cortico-striatal-thalamic-cortical circuit. For later-onset MDD (45-60 years; LOD), poor sleep symptoms were correlated with the caudate in the basal ganglia, which suggests the cingulate operculum network in the control of sleep. These results supported a circuit-based heterogeneity associated with the age of onset in MDD. Understanding this circuit-based heterogeneity might help to develop a new target for clinical treatment strategies.

Reduced myelin density in unmedicated major depressive disorder: An inhomogeneous magnetization transfer MRI study

OBJECTIVES

To detect the whole-brain reduced myelin density in unmedicated patients with major depressive disorder (MDD) using the inhomogeneous magnetization transfer (ihMT) imaging technology. Compared to other technologies, the ihMT provides high specificity and sensitivity to detect myelin.

METHOD

In this prospective study, fifty unmedicated patients (mean age 25.36 years, 40% men) with MDD and 57 age- and sex-matched healthy controls (HCs) (mean age 25.02 years, 53% men) were recruited between January 2019 and December 2019. All participants underwent ihMT imaging, and pseudo-quantitative ihMT (qihMT) and ihMT ratio (ihMTR) were obtained. The mean values of qihMT and ihMTR extracted from the 50 WM masks (extracted from the International Consortium for Brain Mapping, ICBM-152) in each participant were compared between participants in the MDD and HCs groups. The symptoms of patients were evaluated using the 24-item Hamilton Depression Rating scale (HDRS).

RESULTS

Compared with the HC group, the MDD group showed significantly decreased qihMT and ihMTR values in the left inferior fronto-occipital fasciculus (IFOF) (t = -4.057, p < 0.001; t = -3.662, p < 0.001) and the left uncinate fasciculus (UF) (t = -4.776, p < 0.001; t = -3.800, p < 0.001) after Bonferroni correction. The correlation analysis displayed a significant negative correlation between qihMT values of the left IFOF and HDRS total scores in patients with MDD (r = -0.390, p = 0.012).

LIMITATIONS

This was a cross-sectional study with a relative small sample.

CONCLUSIONS

These findings suggest the reduced myelin density in the IFOF and UF in patients with MDD, which might be associated with the pathophysiology of MDD.

Predicting treatment selections for individuals with major depressive disorder according to functional connectivity subgroups

BACKGROUND

Major depressive disorder (MDD) is a highly prevalent and disabling disease. Currently, patients' treatment choices depend on their clinical symptoms observed by clinicians, which are subjective. Rich evidence suggests that different functional networks' dysfunctions correspond to different intervention preferences. Here, we aimed to develop a prediction model based on data-driven subgroups to provide treatment recommendations.

METHODS

All 630 participants enrolled from four sites underwent functional magnetic resonances imaging at baseline. In the discovery dataset (n=228), we firstly identified MDD subgroups by the hierarchical clustering method using the canonical variates of resting-state functional connectivity (FC) through canonical correlation analyses. The demographic, symptom improvement and FC were compared among subgroups. The preference intervention for each subgroup was also determined. Next, we predicted the individual treatment strategy. Specifically, a patient was assigned into predefined subgroups based on FC similarities and then his/her treatment strategy was determined by the subgroups' preferred interventions.

RESULTS

Three subgroups with specific treatment recommendations were emerged including: (1) a selective serotonin reuptake inhibitors-oriented subgroup with early improvements in working and activities. (2) a stimulation-oriented subgroup with more alleviation in suicide. (3) a selective serotonin noradrenaline reuptake inhibitors-oriented subgroup with more alleviation in hypochondriasis. Through cross-dataset testing respectively conducted on three testing datasets, results showed an overall accuracy of 72.83%.

CONCLUSIONS

Our works revealed the correspondences between subgroups and their treatment preferences and predicted individual treatment strategy based on such correspondences. Our model has the potential to support psychiatrists in early clinical decision making for better treatment outcomes.

Depressive and anxiety symptoms are related to decreased lateral prefrontal cortex functioning during cognitive control in older people

Some studies have found a relationship between negative emotional symptoms and decreased lateral PFC functioning during a cognitive control task in healthy younger adults. Here, we asked whether this relationship is also present in the general older population and across different functional domains of the lateral PFC. Thirty-six older people (13 males) self-reported their recent depressive and anxiety symptoms. They also took two cognitive control tasks known to differentially engage the lateral frontoparietal network (digit n-back task) and the lateral frontotemporal network (Category Fluency Test) while hemodynamic changes in the PFC were monitored by functional near-infrared spectroscopy (fNIRS). Both depressive and anxiety symptoms were associated with decreased activation in the bilateral lateral PFC during cognitive control performance. Interestingly, these relationships were driven by the n-back task. Our findings suggest that depressive and anxiety symptoms are related to decreased lateral PFC functioning in particular domains of cognitive control among older people.

Identification of transdiagnostic psychiatric disorder subtypes using unsupervised learning

Psychiatric disorders show heterogeneous symptoms and trajectories, with current nosology not accurately reflecting their molecular etiology and the variability and symptomatic overlap within and between diagnostic classes. This heterogeneity impedes timely and targeted treatment. Our study aimed to identify psychiatric patient clusters that share clinical and genetic features and may profit from similar therapies. We used high-dimensional data clustering on deep clinical data to identify transdiagnostic groups in a discovery sample (N = 1250) of healthy controls and patients diagnosed with depression, bipolar disorder, schizophrenia, schizoaffective disorder, and other psychiatric disorders. We observed five diagnostically mixed clusters and ordered them based on severity. The least impaired cluster 0, containing most healthy controls, showed general well-being. Clusters 1-3 differed predominantly regarding levels of maltreatment, depression, daily functioning, and parental bonding. Cluster 4 contained most patients diagnosed with psychotic disorders and exhibited the highest severity in many dimensions, including medication load. Depressed patients were present in all clusters, indicating that we captured different disease stages or subtypes. We replicated all but the smallest cluster 1 in an independent sample (N = 622). Next, we analyzed genetic differences between clusters using polygenic scores (PGS) and the psychiatric family history. These genetic variables differed mainly between clusters 0 and 4 (prediction area under the receiver operating characteristic curve (AUC) = 81%; significant PGS: cross-disorder psychiatric risk, schizophrenia, and educational attainment). Our results confirm that psychiatric disorders consist of heterogeneous subtypes sharing molecular factors and symptoms. The identification of transdiagnostic clusters advances our understanding of the heterogeneity of psychiatric disorders and may support the development of personalized treatments.

Prospective study on microstructure in medication-naïve adolescents with first-episode major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is one of the most prevalent mental disorders during adolescence, and early diagnosis and treatment are important. We aimed to characterize the microstructure of the brain in medication-naïve adolescents with first-episode MDD.

METHODS

Patients with MDD (N = 31) and healthy controls (N = 27) participated in this study and severity of depressive symptoms, duration of untreated depressive episode, demographic data, and diffuse tensor imaging data were collected. A comparative analysis of patients and healthy controls was performed, and the effect of medication on the brain`s integrity was investigated through comparison before and after 3 months of treatment in the patient group. Tract-based spatial statistics was used for diffusion tensor image analysis.

RESULTS

In the patient group, functional anisotropy (FA) values were significantly higher at the genu of the corpus callosum, body of the corpus callosum, and right anterior corona radiata than in healthy controls. After 3 months of treatment, FA values were significantly decreased in the left anterior limb of the internal capsule, left posterior limb of the internal capsule, and left superior longitudinal fasciculus.

LIMITATIONS

The sample size is relatively small and 3-month treatment period was relatively short.

CONCLUSION

FA values of patients with MDD were increased compared to healthy controls and decreased after treatment. These results suggested that pharmacological treatments in the early stages of MDD might restore the brain`s integrity.

Assessment of Disrupted Brain Structural Connectome in Depressive Patients With Suicidal Ideation Using Generalized Q-Sampling MRI

Suicide is one of the leading causes of mortality worldwide. Various factors could lead to suicidal ideation (SI), while depression is the predominant cause among all mental disorders. Studies have shown that alterations in brain structures and networks may be highly associated with suicidality. This study investigated both neurological structural variations and network alterations in depressed patients with suicidal ideation by using generalized q-sampling imaging (GQI) and Graph Theoretical Analysis (GTA). This study recruited 155 participants and divided them into three groups: 44 depressed patients with suicidal ideation (SI+; 20 males and 24 females with mean age = 42, SD = 12), 56 depressed patients without suicidal ideation (Depressed; 24 males and 32 females with mean age = 45, SD = 11) and 55 healthy controls (HC; nine males and 46 females with mean age = 39, SD = 11). Both the generalized fractional anisotropy (GFA) and normalized quantitative anisotropy (NQA) values were evaluated in a voxel-based statistical analysis by GQI. We analyzed different topological parameters in the graph theoretical analysis and the subnetwork interconnections in the Network-based Statistical (NBS) analysis. In the voxel-based statistical analysis, both the GFA and NQA values in the SI+ group were generally lower than those in the Depressed and HC groups in the corpus callosum and cingulate gyrus. Furthermore, we found that the SI+ group demonstrated higher global integration and lower local segregation among the three groups of participants. In the network-based statistical analysis, we discovered that the SI+ group had stronger connections of subnetworks in the frontal lobe than the HC group. We found significant structural differences in depressed patients with suicidal ideation compared to depressed patients without suicidal ideation and healthy controls and we also found several network alterations among these groups of participants, which indicated that white matter integrity and network alterations are associated with patients with depression as well as suicidal ideation.

Early onset of depression and treatment outcome in patients with major depressive disorder

Major depressive disorder (MDD) is a highly heterogeneous disorder, which may partly explain why treatment outcome using antidepressants is unsatisfactory. We investigated the onset of depression as a possible clinical marker for therapy response prediction in the context of somatic biomarkers blood pressure and plasma electrolyte concentration. 889 MDD patients were divided into early (EO, n = 226), intermediate (IO, n = 493), and late onset (LO, n = 169) patients and were analyzed for differences in socio-demographic and clinical parameters, comorbidities and treatment outcome as well as systolic blood pressure and electrolytes. EO patients more often suffered from a recurrent depression, had more previous depressive episodes, a higher rate of comorbid axis I and II disorders, and more often reported of suicidality (p < 0.001) compared to IO and LO patients. Treatment outcome was not different from IO and LO patients, although LO patients responded faster. EO patients who showed an early non-improvement of depression after 2 weeks of therapy (<20% improvement) had a 4.3-fold higher likelihood to become non-remitter as compared to LO patients with an early improvement. EO patients had significantly lower systolic blood pressure than patients with IO or LO and electrolytes in EO patients were significantly correlated with depression severity. Our results confirm other studies showing an association of an early onset of depression with a slower treatment response. The worse treatment outcome in patients with an additional early non-improvement to antidepressant therapy opens perspectives to develop and test individualized treatment approaches for EO and LO patients in the future, which may be based on differences in autonomic regulation.

Replicable association between human cytomegalovirus infection and reduced white matter fractional anisotropy in major depressive disorder

Major depressive disorder (MDD) is associated with reductions in white matter microstructural integrity as measured by fractional anisotropy (FA), an index derived from diffusion tensor imaging (DTI). The neurotropic herpesvirus, human cytomegalovirus (HCMV), is a major cause of white matter pathology in immunosuppressed populations but its relationship with FA has never been tested in MDD despite the presence of inflammation and weakened antiviral immunity in a subset of depressed patients. We tested the relationship between FA and HCMV infection in two independent samples consisting of 176 individuals with MDD and 44 healthy controls (HC) (Discovery sample) and 88 participants with MDD and 48 HCs (Replication sample). Equal numbers of HCMV positive (HCMV+) and HCMV negative (HCMV-) groups within each sample were balanced on ten different clinical/demographic variables using propensity score matching. Anti-HCMV IgG antibodies were measured using a solid-phase ELISA. In the Discovery sample, significantly lower FA was observed in the right inferior fronto-occipital fasciculus (IFOF) in HCMV+ participants with MDD compared to HCMV- participants with MDD (cluster size 1316 mm3; pFWE < 0.05, d = -0.58). This association was confirmed in the replication sample by extracting the mean FA from this exact cluster and applying the identical statistical model (p < 0.05, d = -0.45). There was no significant effect of diagnosis or interaction between diagnosis and HCMV in either sample. The effect of chronic HCMV infection on white matter integrity may-in at-risk individuals-contribute to the psychopathology of depression. These findings may provide a novel target of intervention for a subgroup of patients with MDD.

Diffusion Tensor Imaging Group Analysis Using Tract Profiling and Directional Statistics

Group analysis in diffusion tensor imaging is challenging. Comparisons of tensor morphology across groups have typically been performed on scalar measures of diffusivity, such as fractional anisotropy (FA), disregarding the complex three-dimensional morphologies of diffusion tensors. Scalar measures consider only the magnitude of the diffusion but not directions. In the present study, we have introduced a new approach based on directional statistics to use directional information of diffusion tensors in statistical group analysis based on Bingham distribution. We have investigated different directional statistical models to find the best fit. During the experiments, we confirmed that carrying out directional statistical analysis along the tract is much more effective than voxel- or skeleton-guided directional statistics. Hence, we propose a new method called tract profiling and directional statistics (TPDS) applicable to fiber bundles. As a case study, the method has been applied to identify connectivity differences of patients with major depressive disorder. The results obtained with the directional statistic-based analysis are consistent with those of NBS, but additionally, we found significant changes in the right hemisphere striatum, ACC, and prefrontal, parietal, temporal, and occipital connections as well as left hemispheric differences in the limbic areas such as the thalamus, amygdala, and hippocampus. The results are also evaluated with respect to fiber lengths. Comparison with the output of the network-based statistical toolbox indicated that the benefit of the proposed method becomes much more distinctive as the tract length increases. The likelihood of finding clusters of voxels that differ in long tracts is higher in TPDS, while that relationship is not clearly established in NBS.

White matter microstructure relates to lassitude but not diagnosis in adolescents with depression

The neurobiology of adolescent depression remains poorly understood. Initial studies suggested impaired white matter microstructure in adults and adolescents, but findings have not been consistent. Challenges in this literature have included small samples, medication confounds and inconsistent correction for type I error. This study addressed these issues in a new examination of fractional anisotropy (FA) in adolescents with major depressive disorder (MDD) using diffusion tensor imaging. We examined FA in 81 adolescents aged 12-19 (44 MDD [all unmedicated], 37 controls). We conducted logistic regression analyses to examine the odds of MDD versus control based on FA within standard white matter tracts that were delineated by probabilistic tractography. We also examined relationships between FA and disease severity (overall depression and dimensions of illness). Finally, we conducted a voxel-wise group comparison of FA. All analyses covaried for age, sex and socioeconomic status, and applied rigorous corrections for multiple testing. Logistic regression did not reveal significant associations between diagnosis and FA within white matter tracts defined by probabilistic tractography. Dimensional analyses revealed that greater lassitude was associated with higher FA in right cingulum bundle and bilateral corticospinal tracts, but with lower FA in right anterior thalamic radiation. Voxel-wise group comparisons of FA did not reveal significant group differences. The current findings do not support low FA as a neurobiological marker of adolescent depression. Dimensional results suggest that FA relates to lassitude but not overall depression. Given the clinical and neurobiological heterogeneity of depression, future work utilizing dimensional approaches may help elucidate the role of white matter microstructure in adolescent depression neurobiology.

Targeted sequencing of the BDNF gene in young Chinese Han people with major depressive disorder

BACKGROUND

Adolescence and young adulthood are considered the peak age for the emergence of many psychiatric disorders, in particular major depressive disorder (MDD). Previous research has shown substantial heritability for MDD. In addition, the brain-derived neurotrophic factor (BDNF) gene is known to be associated with MDD. However, there has been no study conducting targeted sequencing of the BDNF gene in young MDD patients so far.

METHOD

To examine whether the BDNF gene is associated with the occurrence of MDD in young patients, we used targeted sequencing to detect the BDNF gene variants in 259 young Chinese Han people (105 MDD patients and 154 healthy subjects).

RESULTS

The BDNF variant rs4030470 was associated with MDD in young Chinese Han people (uncorrected p = 0.046), but this was no longer significant after applying FDR correction (p = 0.552, after FDR correction). We did not find any significant differences in genotype or haplotype frequencies between the case and control groups, and furthermore discovered no rare mutation variants any of the 259 subjects.

CONCLUSION

Our results do not support an association of the BDNF gene variants with MDD in young people in the Chinese Han population.

Association of cortical thickness with age of onset in first-episode, drug-naïve major depression

OBJECTIVE

We previously showed differences in brain grey matter volume changes between patients with early-onset adult depression (EOD) and late-onset adult depression (LOD). Here, we aim to identify whether cortical thickness (CT) is affected by the age of onset in patients with depression.

METHODS

High-resolution MRI images were obtained for 54 major depressive disorder (MDD) patients with EOD, 58 patients with LOD, 57 young healthy controls (HCs), and 58 aged HCs. Depression severity was assessed using the Hamilton Depression Rating Scale 17-item (HDRS17). Associations between CT of patients and clinical scores were analyzed.

RESULTS

There was a significant main effect of diagnosis for the left rostal anterior cingulate (rACC), right inferior temporal, right lateral orbitofrontal cortex (lOFC), and bilateral pericalcarine. A remarkable onset age-group effect on CT was observed in the rACC and bilateral caudal anterior cingulate (cACC). The diagnosis-by-onset age interaction effect was found in bilateral rACC and right lOFC. Thinning CT in bilateral rACC was observed in EOD patients compared to young HCs. Compared to older HCs, thicker CT in lOFC was seen in the LOD patient group. Compared with the LOD group, the EOD group showed cortical thinning of the right cACC and posterior cingulate cortex (PCC). There were no significant associations between CT in right cACC or PCC with symptom severity or illness duration.

CONCLUSIONS

MDD patients with different age at onset show distinct CT alterations, suggesting potentially divergent pathological mechanisms of EOD and LOD.

Causes and Consequences of Diagnostic Heterogeneity in Depression: Paths to Discovering Novel Biological Depression Subtypes

Depression is a highly heterogeneous syndrome that bears only modest correlations with its biological substrates, motivating a renewed interest in rethinking our approach to diagnosing depression for research purposes and new efforts to discover subtypes of depression anchored in biology. Here, we review the major causes of diagnostic heterogeneity in depression, with consideration of both clinical symptoms and behaviors (symptomatology and trajectory of depressive episodes) and biology (genetics and sexually dimorphic factors). Next, we discuss the promise of using data-driven strategies to discover novel subtypes of depression based on functional neuroimaging measures, including dimensional, categorical, and hybrid approaches to parsing diagnostic heterogeneity and understanding its biological basis. The merits of using resting-state functional magnetic resonance imaging functional connectivity techniques for subtyping are considered along with a set of technical challenges and potential solutions. We conclude by identifying promising future directions for defining neurobiologically informed depression subtypes and leveraging them in the future for predicting treatment outcomes and informing clinical decision making.

White matter disturbances in major depressive disorder: a coordinated analysis across 20 international cohorts in the ENIGMA MDD working group

Alterations in white matter (WM) microstructure have been implicated in the pathophysiology of major depressive disorder (MDD). However, previous findings have been inconsistent, partially due to low statistical power and the heterogeneity of depression. In the largest multi-site study to date, we examined WM anisotropy and diffusivity in 1305 MDD patients and 1602 healthy controls (age range 12-88 years) from 20 samples worldwide, which included both adults and adolescents, within the MDD Working Group of the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) consortium. Processing of diffusion tensor imaging (DTI) data and statistical analyses were harmonized across sites and effects were meta-analyzed across studies. We observed subtle, but widespread, lower fractional anisotropy (FA) in adult MDD patients compared with controls in 16 out of 25 WM tracts of interest (Cohen's d between 0.12 and 0.26). The largest differences were observed in the corpus callosum and corona radiata. Widespread higher radial diffusivity (RD) was also observed (all Cohen's d between 0.12 and 0.18). Findings appeared to be driven by patients with recurrent MDD and an adult age of onset of depression. White matter microstructural differences in a smaller sample of adolescent MDD patients and controls did not survive correction for multiple testing. In this coordinated and harmonized multisite DTI study, we showed subtle, but widespread differences in WM microstructure in adult MDD, which may suggest structural disconnectivity in MDD.

Multimodal fusion of structural and functional brain imaging in depression using linked independent component analysis

Previous structural and functional neuroimaging studies have implicated distributed brain regions and networks in depression. However, there are no robust imaging biomarkers that are specific to depression, which may be due to clinical heterogeneity and neurobiological complexity. A dimensional approach and fusion of imaging modalities may yield a more coherent view of the neuronal correlates of depression. We used linked independent component analysis to fuse cortical macrostructure (thickness, area, gray matter density), white matter diffusion properties and resting-state functional magnetic resonance imaging default mode network amplitude in patients with a history of depression (n = 170) and controls (n = 71). We used univariate and machine learning approaches to assess the relationship between age, sex, case-control status, and symptom loads for depression and anxiety with the resulting brain components. Univariate analyses revealed strong associations between age and sex with mainly global but also regional specific brain components, with varying degrees of multimodal involvement. In contrast, there were no significant associations with case-control status, nor symptom loads for depression and anxiety with the brain components, nor any interaction effects with age and sex. Machine learning revealed low model performance for classifying patients from controls and predicting symptom loads for depression and anxiety, but high age prediction accuracy. Multimodal fusion of brain imaging data alone may not be sufficient for dissecting the clinical and neurobiological heterogeneity of depression. Precise clinical stratification and methods for brain phenotyping at the individual level based on large training samples may be needed to parse the neuroanatomy of depression.

Time heals all wounds? A 2-year longitudinal diffusion tensor imaging study in major depressive disorder

BACKGROUND

Cross-sectional studies have repeatedly shown impaired white matter integrity in patients with major depressive disorder. Longitudinal analyses are missing from the current research and are crucial to elucidating the impact of disease trajectories on white matter impairment in major depressive disorder.

METHODS

Fifty-nine patients with major depressive disorder receiving inpatient treatment, as well as 49 healthy controls, took part in a prospective study. Participants were scanned twice (baseline and follow-up), approximately 2.25 years apart, using diffusion tensor imaging. We analyzed diffusion metrics using tract-based spatial statistics.

RESULTS

At baseline, patients had higher mean diffusivity in a large bilateral frontal cluster comprising the body and genu of the corpus callosum, the anterior and superior corona radiata, and the superior longitudinal fasciculus. A significant group × time interaction revealed a decrease of mean diffusivity in patients with major depressive disorder over time, abolishing group differences at follow-up. This effect was observed irrespective of disease course in the follow-up period.

LIMITATIONS

Analyzing the course of illness is challenging because of recollection biases in patients with major depressive disorder.

CONCLUSION

This study reports follow-up diffusion tensor imaging data in patients with major depressive disorder after an acute depressive episode. We demonstrated impaired prefrontal white matter microstructure (higher mean diffusivity) at baseline in patients with major depressive disorder, which normalized at follow-up after 2 years, irrespective of disease course. This might have been due to a general treatment effect and might have reflected recovery of white matter integrity.

Data-driven biological subtypes of depression: systematic review of biological approaches to depression subtyping

Research into major depressive disorder (MDD) is complicated by population heterogeneity, which has motivated the search for more homogeneous subtypes through data-driven computational methods to identify patterns in data. In addition, data on biological differences could play an important role in identifying clinically useful subtypes. This systematic review aimed to summarize evidence for biological subtypes of MDD from data-driven studies. We undertook a systematic literature search of PubMed, PsycINFO, and Embase (December 2018). We included studies that identified (1) data-driven subtypes of MDD based on biological variables, or (2) data-driven subtypes based on clinical features (e.g., symptom patterns) and validated these with biological variables post-hoc. Twenty-nine publications including 24 separate analyses in 20 unique samples were identified, including a total of ~ 4000 subjects. Five out of six biochemical studies indicated that there might be depression subtypes with and without disturbed neurotransmitter levels, and one indicated there might be an inflammatory subtype. Seven symptom-based studies identified subtypes, which were mainly determined by severity and by weight gain vs. loss. Two studies compared subtypes based on medication response. These symptom-based subtypes were associated with differences in biomarker profiles and functional connectivity, but results have not sufficiently been replicated. Four out of five neuroimaging studies found evidence for groups with structural and connectivity differences, but results were inconsistent. The single genetic study found a subtype with a distinct pattern of SNPs, but this subtype has not been replicated in an independent test sample. One study combining all aforementioned types of data discovered a subtypes with different levels of functional connectivity, childhood abuse, and treatment response, but the sample size was small. Although the reviewed work provides many leads for future research, the methodological differences across studies and lack of replication preclude definitive conclusions about the existence of clinically useful and generalizable biological subtypes.

The neural markers of MRI to differentiate depression and panic disorder

Depression and panic disorder (PD) share the common pathophysiology from the perspectives of neurotransmitters. The relatively high comorbidity between depression and PD contributes to the substantial obstacles to differentiate from depression and PD, especially for the brain pathophysiology. There are significant differences in the diagnostic criteria between depression and PD. However, the paradox of similar pathophysiology and different diagnostic criteria in these two disorders were still the issues needing to be addressed. Therefore the clarification of potential difference in the field of neuroscience and pathophysiology between depression and PD can help the clinicians and scientists to understand more comprehensively about significant differences between depression and PD. The researchers should be curious about the underlying difference of pathophysiology beneath the significant distinction of clinical symptoms. In this review article, I tried to find some evidences for the differences between depression and PD, especially for neural markers revealed by magnetic resonance imaging (MRI). The distinctions of structural and functional alterations in depression and PD are reviewed. From the structural perspectives, PD seems to have less severe gray matter alterations in frontal and temporal lobes than depression. The study of white matter microintegrity reveals more widespread alterations in fronto-limbic circuit of depression patients than PD patients, such as the uncinate fasciculus and anterior thalamic radiation. PD might have a more restrictive pattern of structural alterations when compared to depression. For the functional perspectives, the core site of depression pathophysiology is the anterior subnetwork of resting-state network, such as anterior cingulate cortex, which is not significantly altered in PD. A possibly emerging pattern of fronto-limbic distinction between depression and PD has been revealed by these explorative reports. The future trend for machine learning and pattern recognition might confirm the differentiation pattern between depression and PD based on the explorative results.

Altered white matter volumes in first-episode depression: Evidence from cross-sectional and longitudinal voxel-based analyses

BACKGROUND

Major depressive disorder (MDD) is accompanied by atypical brain structure affecting grey and white matter from the early stages. Neuroimaging studies of first-episode depression (FED) have provided evidence on this regard, but most of the studies are cross-sectional. The aim of this longitudinal study was to test potential changes in grey matter (GM) and white matter (WM) volumes in FED.

METHODS

Thirty-three untreated FED patients (DSM-IV criteria) and 33 healthy controls (HC) underwent a 3T structural magnetic resonance imaging (sMRI) at baseline and after 2 years. Depressive symptoms were assessed at baseline and throughout the study with the 17-item Hamilton Depressive Rating Scale (HDRS-17). Recurrences of FED patients were also collected along the follow-up. To analyze GM and WM differences, whole-brain voxel-based morphometry (VBM, SPM12) was employed (FWE corrected).

RESULTS

FED patients showed significant reductions compared to HC in WM volumes of prefrontal cortex (left anterior corona radiata). No differences were found in GM volumes. Full factorial longitudinal analysis of the whole sample revealed no significant effect in GM nor in WM, while the full factorial longitudinal analysis comparing recurrent and non-recurrent patients showed increments in WM volumes of left posterior corona radiata and right posterior thalamic radiation in the recurrent group.

LIMITATIONS

Limited sample size, especially in the follow-up.

CONCLUSIONS

The present findings provided some new evidence of the role of white matter alterations in the early stages of MDD and in the progression of the illness.

Resilience to Risk for Psychopathology: The Role of White Matter Microstructural Development in Adolescence

BACKGROUND

One major risk factor for the development of psychopathology is a family history of psychopathology (FHP). Cross-sectional studies have shown that FHP is associated with alterations in white matter microstructure in adolescents without current psychopathology; however, whether these associations persist throughout adolescence, particularly in those who remain resilient to developing psychopathology, is unclear.

METHODS

Sixty-six adolescents underwent diffusion-weighted imaging at baseline (12-16 years of age) and at one or two follow-up visits (142 total scans). Adolescents' parents completed a modified Family History Assessment Module to calculate FHP density (FHPD) based on familial alcohol use, substance use, and major depressive, generalized anxiety, substance-induced mood, and antisocial personality disorders. The relationship between FHPD and white matter microstructural development was examined using multilevel modeling.

RESULTS

FHPD was associated with significant alterations in white matter microstructure at baseline; in the bilateral superior corona radiata and left superior longitudinal fasciculus, these effects were transient (FHPD was associated with altered white matter microstructure only in early adolescence), while effects in the posterior limb of the internal capsule were persistent. Associations between FHPD and white matter microstructure in the body of the corpus callosum emerged later in adolescence.

CONCLUSIONS

This prospective, longitudinal study provides novel information indicating that the association between FHP and white matter microstructure previously observed in adolescents is transient in most regions but may persist into late adolescence in other regions, despite current resilience to developing psychopathology. Future studies are necessary to determine if these persistent alterations are associated with onset of psychopathology later in life.

Effects of Uric Acid on the Alterations of White Matter Connectivity in Patients with Major Depression

OBJECTIVE

Uric acid is a non-enzymatic antioxidant associated with depression. Despite its known protective role in other brain disorders, little is known about its influence on the structural characteristics of brains of patients with major depressive disorder (MDD). This study explored the association between uric acid and characteristics of white matter (WM) in patients with MDD.

METHODS

A total of 32 patients with MDD and 23 healthy controls (HCs) were examined. All participants were scored based on the Beck Depression Inventory and Beck Anxiety Inventory at baseline. All patients were also rated with the Hamilton Depression Rating Scale. We collected blood samples from all participants immediately after their enrollment and before the initiation of antidepressants in case of patients. Tract-based spatial statistics were used for all imaging analyses.

RESULTS

Lower fractional anisotropy (FA) and higher radial diffusivity (RD) values were found in the MDD group than in the HC group. Voxelwise correlation analysis revealed that the serum uric acid levels positively correlated with the FA and negatively with the RD in WM regions that previously showed significant group differences in the MDD group. The correlated areas were located in the left anterior corona radiata, left frontal lobe WM, and left anterior cingulate cortex WM.

CONCLUSION

The present study suggests a significant association between altered WM connectivity and serum uric acid levels in patients with MDD, possibly through demyelination.

Association between abnormal serum myelin-specific protein levels and white matter integrity in first-episode and drug-naïve patients with major depressive disorder

BACKGROUND

Although the structural abnormalities of white matter (WM) have been described in patients with major depressive disorder (MDD), the neuropathological changes remain unclear. The current study aimed to investigate the myelin oligodendrocyte glycoprotein (MOG) and myelin-associated glycoprotein (MAG) levels and their correlations with WM integrity in first-episode, drug-naïve MDD patients.

METHODS

We obtained diffusion tensor images of 102 first-episode, drug-naïve MDD patients and 81 age- and sex-matched controls. Serum MOG and MAG levels of all participants were measured and compared between the two groups. The correlations between WM integrity and MOG and MAG levels were examined.

RESULTS

MOG and MAG serum levels were significantly higher in MDD patients than in controls. Patients with MDD also showed decreased fractional anisotropy (FA) and axial diffusivity in the WM of the bilateral thalamus, right hippocampus, right temporal lobe, and left pulvinar. At the whole-brain level, no regions showed any correlations of diffusivity parameters with MOG or MAG levels in healthy subjects. However, we observed two-way correlations between the MOG and MAG levels and the FA and mean diffusivity values in the WM of the left middle frontal lobe, right inferior parietal lobe, and right supplementary motor area in MDD patients.

LIMITATIONS

Further investigation with a larger sample size and longitudinal studies are required to better understand the neuropathology of WM integrity in MDD.

CONCLUSIONS

Our findings represent the first evidence of a relationship between abnormal serum myelin-specific protein levels and impaired WM integrity, which may help to better understand the neurobiological mechanisms of MDD.

White matter integrity correlates with depressive symptomatology in temporal lobe epilepsy

RATIONALE

White matter abnormalities occur in both temporal lobe epilepsy (TLE) and depression, but there is limited research examining the depression-white matter association in depressed individuals with TLE. This study examined the relationship between white matter integrity (WMI) and depression including the influence of age at seizure onset, in adults with TLE, TLE and depression, and depression only.

METHODS

Thirty-one adults were in one of three groups: TLE without depression (TLE; n=11), TLE with depression (TLE+DEP; n=9), and depression without TLE (DEP; n=11). Participants completed structured interviews for depression diagnosis and severity. White matter integrity was estimated based on fractional anisotropy (FA) calculated in frontotemporolimbic (FTL) and non-FTL regions in the JHU DTI atlas.

RESULTS

In adults with TLE (n=20), depressive symptomology was significantly correlated with FA in non-FTL regions and trended toward significance in FTL regions. These associations were found in FTL (statistically significant) and non-FTL (trended toward significance) regions in participants with childhood seizure onset but not in those with adolescent/adult seizure onset.

CONCLUSIONS

Current results suggest that WMI, within FTL and non-FTL regions, are associated with depressive symptomology in adults with TLE. This association may be most notable in those with childhood-onset epilepsy. These findings could have important implications for the conceptualization and clinical care of neuropsychiatric comorbidities in TLE.

State-dependent microstructural white matter changes in drug-naïve patients with first-episode psychosis

BACKGROUND

Diffusion tensor imaging (DTI) studies have consistently shown white matter (WM) microstructural abnormalities in schizophrenia. Whether or not such alterations could vary depending on clinical status (i.e. acute psychosis v. remission) remains to be investigated.

METHODS

Twenty-five treatment-naïve first-episode psychosis (FEP) patients and 51 healthy-controls (HC) underwent MRI scanning at baseline. Twenty-one patients were re-scanned as soon as they achieved sustained remission of symptoms; 36 HC were also scanned twice. Rate-of-change maps of longitudinal DTI changes were calculated for in order to examine WM alterations associated with changes in clinical status. We conducted voxelwise analyses of fractional anisotropy (FA) and trace (TR) maps.

RESULTS

At baseline, FEP presented reductions of FA in comparison with HC [p < 0.05, false-discovery rate (FDR)-corrected] affecting fronto-limbic WM and associative, projective and commissural fasciculi. After symptom remission, patients showed FA increase over time (p < 0.001, uncorrected) in some of the above WM tracts, namely the right anterior thalamic radiation, right uncinate fasciculus/inferior fronto-occipital fasciculus, and left inferior fronto-occipital fasciculus/inferior longitudinal fasciculus. We also found significant correlations between reductions in PANSS scores and FA increases over time (p < 0.05, FDR-corrected).

CONCLUSIONS

WM changes affecting brain tracts critical to the integration of perceptual information, cognition and emotions are detectable soon after the onset of FEP and may partially reverse in direct relation to the remission of acute psychotic symptoms. Our findings reinforce the view that WM abnormalities in brain tracts are a key neurobiological feature of acute psychotic disorders, and recovery from such WM pathology can lead to amelioration of symptoms.

Identify changes of brain regional homogeneity in early and later adult onset patients with first-episode depression using resting-state fMRI

Objective

Previous work exhibited different brain grey matter volume (GMV) changes between patients with early adult onset depression (EOD, age 18–29) and later adult onset depression (LOD, age 30–44) by using 30-year-old as the cut-off age. To identify whether regional homogeneity (ReHo) changes are also different between EOD and LOD by using same cut-off age, we used resting-state functional magnetic resonance imaging (fMRI) to detect the abnormal ReHo between patients with EOD and LOD in the present study.

Methods

Resting-state fMRI scans of 58 patients with EOD, 62 patients with LOD, 60 young healthy controls (HC), and 52 old HC were obtained. The ReHo approach was used to analyze the images.

Results

The ANOVA analysis revealed that the ReHo values in the frontoparietal, occipital, and cerebellar regions were significantly different among the four groups. Relative to patients with LOD, patients with EOD displayed significantly increased ReHo in the left precuneus, and decreased ReHo in the right fusiform. The ReHo values in the left precuneus and the right fusiform had no significant correlation with the score of the depression rating scale or illness duration in both patient subgroups. Compared to young HC, patients with EOD showed significantly increased ReHo in the right frontoparietal regions and the right calcarine. Furthermore, the increased ReHo in the right frontoparietal regions, right insula and left hippocampus, and decreased ReHo in the left inferior occipital gyrus, right middle occipital gyrus, left calcarine, and left supplementary motor area were observed in patients with LOD when compared to old HC.

Conclusions

The ReHo of brain areas that were related to mood regulation was changed in the first-episode, drug-naive adult patients with MDD. Adult patients with EOD and LOD exhibited different ReHo abnormalities relative to each age-matched comparison group, suggesting that depressed adult patients with different age-onset might have different pathological mechanism.

Intrinsic disruption of white matter microarchitecture in first-episode, drug-naive major depressive disorder: A voxel-based meta-analysis of diffusion tensor imaging

Previous studies have demonstrated the influences of episodes and antidepressant drugs on white matter (WM) in patients with major depressive disorder (MDD). However, most diffusion tensor imaging (DTI) studies included highly heterogeneous individuals with different numbers of depressive episodes or medication status. To exclude the confounding effects of multiple episodes or medication, we conducted a quantitative voxel-based meta-analysis of fractional anisotropy (FA) in patients with first-episode, drug-naive MDD to identify the intrinsic WM alterations involved in the pathogenesis of MDD. The pooled meta-analysis revealed significant FA reductions in the body of the corpus callosum (CC), bilateral anterior limb of the internal capsule (ALIC), right inferior temporal gyrus (ITG) and right superior frontal gyrus (SFG) in MDD patients relative to healthy controls. Meta-regression analyses revealed that FA reduction in the right ALIC and right SFG was negatively correlated with symptom severity and duration of depression, respectively. Our findings provide robust evidence that the WM impairments in the interhemispheric connections and frontal-subcortical neuronal circuits may play an important role in MDD pathogenesis.

Gender differences in the structural connectome of the teenage brain revealed by generalized q-sampling MRI

The question of whether there are biological differences between male and female brains is a fraught one, and political positions and prior expectations seem to have a strong influence on the interpretation of scientific data in this field. This question is relevant to issues of gender differences in the prevalence of psychiatric conditions, including autism, attention deficit hyperactivity disorder (ADHD), Tourette's syndrome, schizophrenia, dyslexia, depression, and eating disorders. Understanding how gender influences vulnerability to these conditions is significant. Diffusion magnetic resonance imaging (dMRI) provides a non-invasive method to investigate brain microstructure and the integrity of anatomical connectivity. Generalized q-sampling imaging (GQI) has been proposed to characterize complicated fiber patterns and distinguish fiber orientations, providing an opportunity for more accurate, higher-order descriptions through the water diffusion process. Therefore, we aimed to investigate differences in the brain's structural network between teenage males and females using GQI. This study included 59 (i.e., 33 males and 26 females) age- and education-matched subjects (age range: 13 to 14 years). The structural connectome was obtained by graph theoretical and network-based statistical (NBS) analyses. Our findings show that teenage male brains exhibit better intrahemispheric communication, and teenage female brains exhibit better interhemispheric communication. Our results also suggest that the network organization of teenage male brains is more local, more segregated, and more similar to small-world networks than teenage female brains. We conclude that the use of an MRI study with a GQI-based structural connectomic approach like ours presents novel insights into network-based systems of the brain and provides a new piece of the puzzle regarding gender differences.

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The GQI-based structural connectomic study provides a new piece of the puzzle regarding gender differences.

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Male brains exhibit better intrahemispheric communication, and female exhibit better interhemispheric communication.

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The network organization of teenage male brains is more local and more segregated than teenage female brains.

Microstructural brain abnormalities in medication-free patients with major depressive disorder: a systematic review and meta-analysis of diffusion tensor imaging

BACKGROUND

Multiple meta-analyses of diffusion tensor imaging (DTI) studies have reported impaired white matter integrity in patients with major depressive disorder (MDD). However, owing to inclusion of medicated patients in these studies, it is difficult to conclude whether these reported alterations are associated with MDD or confounded by medication effects. A meta-analysis of DTI studies on medication-free (medication-naive and medication washout) patients with MDD would therefore be necessary to disentangle MDD-specific effects.

METHODS

We analyzed white matter alterations between medication-free patients with MDD and healthy controls using anisotropic effect size-signed differential mapping (AES-SDM). We used DTI query software for fibre tracking.

RESULTS

Both pooled and subgroup meta-analyses in medication washout patients showed robust fractional anisotropy (FA) reductions in white matter of the right cerebellum hemispheric lobule, body of the corpus callosum (CC) and bilateral superior longitudinal fasciculus III (SLF III), whereas FA reductions in the genu of the CC and right anterior thalamic projections were seen in only medication-naive patients. Fibre tracking showed that the main tracts with observed FA reductions included the right cerebellar tracts, body of the CC, bilateral SLF III and arcuate fascicle.

LIMITATIONS

The analytic techniques, patient characteristics and clinical variables of the included studies were heterogeneous; we could not exclude the effects of nondrug therapies owing to a lack of data.

CONCLUSION

By excluding the confounding influences of current medication status, findings from the present study may provide a better understanding of the underlying neuropathology of MDD.

Anatomical brain difference of subthreshold depression in young and middle-aged individuals

BACKGROUND

Subthreshold depression (StD) is associated with substantial functional impairments due to depressive symptoms that do not fully meet the diagnosis of major depressive disorder (MDD). Its high incidence in the general population and debilitating symptoms has recently put it at the forefront of mood disorder research.

AIM

In this study we investigated common volumetric brain changes in both young and middle-aged StD patients.

METHODS

Two cohorts of StD patients, young and middle-aged, (n = 57) and matched controls (n = 76) underwent voxel-based morphometry (VBM).

RESULTS

VBM analysis found that: 1) compared with healthy controls, StD patients showed decreased gray matter volume (GMV) in the bilateral globus pallidus and precentral gyrus, as well as increased GMV in the left thalamus and right rostral anterior cingulate cortex/medial prefrontal cortex; 2) there is a significant association between Center for Epidemiological Studies Depression Scale scores and the bilateral globus pallidus (negative) and left thalamus (positive); 3) there is no interaction between age (young vs. middle-age) and group (StD vs. controls).

CONCLUSIONS

Our findings indicate significant VBM brain changes in both young and middle-aged individuals with StD. Individuals with StD, regardless of age, may share common neural characteristics.

Assessment of abnormal brain structures and networks in major depressive disorder using morphometric and connectome analyses

BACKGROUND

It is hypothesized that the phenomenology of major depressive disorder (MDD) is subserved by disturbances in the structure and function of brain circuits; however, findings of structural abnormalities using MRI have been inconsistent. Generalized q-sampling imaging (GQI) methodology provides an opportunity to assess the functional integrity of white matter tracts in implicated circuits.

METHODS

The study population was comprised of 16 outpatients with MDD (mean age 44.81±2.2 years) and 30 age- and gender-matched healthy controls (mean age 45.03±1.88 years). We excluded participants with any other primary mental disorder, substance use disorder, or any neurological illnesses. We used T1-weighted 3D MRI with voxel-based morphometry (VBM) and vertex-wise shape analysis, and GQI with voxel-based statistical analysis (VBA), graph theoretical analysis (GTA) and network-based statistical (NBS) analysis to evaluate brain structure and connectivity abnormalities in MDD compared to healthy controls correlates with clinical measures of depressive symptom severity, Hamilton Depression Rating Scale 17-item (HAMD) and Hospital Anxiety and Depression Scale (HADS).

RESULTS

Using VBM and vertex-wise shape analyses, we found significant volumetric decreases in the hippocampus and amygdala among subjects with MDD (p<0.001). Using GQI, we found decreases in diffusion anisotropy in the superior longitudinal fasciculus and increases in diffusion probability distribution in the frontal lobe among subjects with MDD (p<0.01). In GTA and NBS analyses, we found several disruptions in connectivity among subjects with MDD, particularly in the frontal lobes (p<0.05). In addition, structural alterations were correlated with depressive symptom severity (p<0.01).

LIMITATIONS

Small sample size; the cross-sectional design did not allow us to observe treatment effects in the MDD participants.

CONCLUSIONS

Our results provide further evidence indicating that MDD may be conceptualized as a brain disorder with abnormal circuit structure and connectivity.

Changes of grey matter volume in first-episode drug-naive adult major depressive disorder patients with different age-onset

Objective

Little is known about the pathological mechanism of early adult onset depression (EOD) and later adult onset depression (LOD). We seek to determine whether grey matter volume (GMV) change in EOD and LOD are different, which could also delineate EOD and LOD.

Methods

In present study, 147 first-episode, drug-naive patients with major depressive disorder (MDD), age between 18 and 45, were divided into two groups on the basis of age of MDD onset: the early adult onset group (age 18–29) and the later adult onset group (age 30–44), and a total of 130 gender-, and age-, matched healthy controls (HC) were also divided into two groups which fit for each patient group. Magnetic resonance imaging was conducted on all subjects. The voxel-based morphometry (VBM) approach was employed to analyze the images.

Results

Widespread abnormalities of GMV throughout parietal, temporal, limbic regions, occipital cortex and cerebellum were observed in MDD patients. Compare to young HC, reduced GMV in right fusiform gyrus, right middle temporal gyrus, vermis III and increased GMV in right middle occipital gyrus were seen in the EOD group. In contrast, relative to old HC, decreased GMV in the right hippocampus and increased GMV in the left middle temporal gyrus were observed in the LOD group. Compared to the LOD group, the EOD group had smaller GMV in right posterior cingulate cortex. There was no significant correlation between GMV of the right posterior cingulate cortex and the score of the depression rating scale in patients group.

Conclusions

The GMV of the brain areas that were related to mood regulation was decreased in the first-episode, drug-naive adult patients with MDD. Adult patients with EOD and LOD exhibited different GMV changes relative to each age-matched comparison group, suggesting depressed adult patients with different age-onset might have different pathological mechanism.

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Grey matter volume widely decreased in the drug-naive adult patients with MDD.

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Depressed patients with different age-onset have different grey matter change.

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30 years old is an appropriate cutoff age for different age-onset depression.

Epigenetic Modifications of Major Depressive Disorder

Major depressive disorder (MDD) is a chronic disease whose neurological basis and pathophysiology remain poorly understood. Initially, it was proposed that genetic variations were responsible for the development of this disease. Nevertheless, several studies within the last decade have provided evidence suggesting that environmental factors play an important role in MDD pathophysiology. Alterations in epigenetics mechanism, such as DNA methylation, histone modification and microRNA expression could favor MDD advance in response to stressful experiences and environmental factors. The aim of this review is to describe genetic alterations, and particularly altered epigenetic mechanisms, that could be determinants for MDD progress, and how these alterations may arise as useful screening, diagnosis and treatment monitoring biomarkers of depressive disorders.

The White Matter Microintegrity Alterations of Neocortical and Limbic Association Fibers in Major Depressive Disorder and Panic Disorder: The Comparison

The studies regarding to the comparisons between major depressive disorder (MDD) and panic disorder (PD) in the microintegrity of white matter (WM) are uncommon. Therefore, we tried to a way to classify the MDD and PD. Fifty-three patients with 1st-episode medication-naive PD, 54 healthy controls, and 53 patients with 1st-episode medication-naive MDD were enrolled in this study. The controls and patients were matched for age, gender, education, and handedness. The diffusion tensor imaging scanning was also performed. The WM microintegrity was analyzed and compared between 3 groups of participants (ANOVA analysis) with age and gender as covariates. The MDD group had lower WM microintegrity than the PD group in the left anterior thalamic radiation, left uncinate fasciculus, left inferior fronto-occipital fasciculus, and bilateral corpus callosum. The MDD group had reductions in the microintegrity when compared to controls in the bilateral superior longitudinal fasciculi, inferior longitudinal fasciculi, inferior fronto-occipital fasciculi, and corpus callosum. The PD group had lower microintegrity in bilateral superior longitudinal fasciculi and left inferior fronto-occipital fasciculus when compared to controls. The widespread pattern of microintegrity alterations in fronto-limbic WM circuit for MDD was different from restrictive pattern of alterations for PD.