First-episode Drug-naive Patients Research Articles

Serum IL-6 as a Potential Biomarker of Metabolic Status in Schizophrenia Patients and Its Correlation with Psychotic Symptoms

Objectives: This study aimed to investigate the serum IL-6 level in schizophrenia patients, considering disease chronicity and metabolic status, and to examine its correlation with psychotic symptom scores. The present study also evaluated the diagnostic value of serum IL-6 as a peripheral biomarker for assessing the metabolic health of schizophrenia patients. Methods: Serum IL-6 levels were measured using enzyme-linked immunosorbent assay (ELISA) in 92 schizophrenia patients [44 First Episode Drug Naive (FEDN), 48 chronic schizophrenia (CSZ) patients] and 32 healthy controls. Patients were also stratified into high-risk and no-risk cohorts based on their metabolic status. Psychotic symptoms were assessed with the Positive and Negative Syndrome Scale (PANSS). Findings: Serum IL-6 levels were significantly higher in schizophrenia patients compared to healthy controls (p<0.001), with no difference between FEDN and CSZ patients (p=0.475). Elevated IL-6 levels were observed in patients in high-risk group compared to those in no-risk group (p<0.001). There was a positive correlation between serum IL-6 levels and BMI (r=0.557, p<0.001), G score (r=0.244, p=0.01), and total PANSS score (r=0.228, p=0.02). Similar associations were found in CSZ patients. The ROC curve analysis showed that serum IL-6 has strong diagnostic potential for distinguishing schizophrenia patients in the high-risk group from those in the no-risk group (AUC=0.875, 95% CI: 0.781-0.969, p<0.001), suggesting its value as a biomarker. Novelty: This study highlights the stable role of serum IL-6 in schizophrenia patients regardless of disease chronicity. The findings suggest that serum IL-6 levels were significantly associated with disease severity as measured by PANSS and metabolic health of schizophrenia patients, providing new insights into its prognostic and diagnostic utility. Early identification and targeted management of high-risk groups can improve patient outcomes and quality of life. Keywords: Schizophrenia, IL-6, FEDN, Chronic, PANSS, Metabolic status, Biomarker

Gray matter volume differences based on sex in first-episode drug-naive patients with major depressive disorder and its molecular analysis.

This study analyzed whether gray matter volume (GMV) differences exist between the sexes in patients with major depressive disorder (MDD) and explored the relationships between these differences and neurotransmitter systems. This study enrolled 190 first-episode drug-naive patients with MDD and 293 healthy controls. All participants underwent T1-weighted high-resolution MRI. The interaction between the diagnosis (healthy controls vs. MDD) and sex (male vs. female) regarding GMV alterations was analyzed. The JuSpace toolbox, which covers a wide range of neurotransmitter systems, was used to identify the relationship between MDD-induced and sex-induced GMV alterations and specific receptor/transporter proteins in the brain. Sex-specific GMV differences were observed in the healthy controls but not in MDD patients. Male healthy controls had a larger GMV in the bilateral parahippocampal, lingual, inferior occipital, fusiform, cerebellar subregions, and left inferior temporal than female healthy controls, but several subregions of the thalamus had a larger GMV in female healthy controls than in male healthy controls. Sex-induced GMV alterations were associated with 5-hydroxytryptamine receptor subtype 1a, cannabinoid receptor, and dopamine receptor (P < 0.01, false discovery rate corrected). GMV differences were not detected in the main effect of diagnosis and the interaction of diagnosis and sex. Sex-specific GMV differences are associated with the spatial distribution of serotonin, dopamine, and cannabinoid neurotransmitter receptor systems. Sex-based physiological differences in the GMV may account for male and female susceptibility to and differences in the clinical symptoms of MDD.

Peak width of skeletonized mean diffusivity as a neuroimaging biomarker in first-episode schizophrenia.

Peak width of skeletonized mean diffusivity (PSMD), a fully automated diffusion tensor imaging (DTI) biomarker of white matter (WM) microstructure damage, has been shown to be associated with cognition in various WM pathologies. However, its application in schizophrenic disease remains unexplored. This study aims to investigate PSMD along with other DTI markers in first-episode schizophrenia patients compared to healthy controls (HCs), and explore the correlations between these metrics and clinical characteristics. A total of 56 first-episode drug-naive schizophrenia patients and 64 HCs were recruited for this study. Participants underwent structural imaging and DTI, followed by comprehensive clinical assessments, including the Positive and Negative Syndrome Scale (PANSS) for patients and cognitive function tests for all participants. We calculated PSMD, peak width of skeletonized fractional anisotropy (PSFA), axial diffusivity (PSAD), radial diffusivity (PSRD) values, skeletonized average mean diffusivity (MD), average fractional anisotropy (FA), average axial diffusivity (AD), and average radial diffusivity (RD) values as well as structural network global topological parameters, and examined between-group differences in these WM metrics. Furthermore, we investigated associations between abnormal metrics and clinical characteristics. Compared to HCs, patients exhibited significantly increased PSMD values (t = 2.467, p = 0.015), decreased global efficiency (Z = -2.188, p = 0.029), and increased normalized characteristic path length (lambda) (t = 2.270, p = 0.025). No significant differences were observed between the groups in the remaining metrics, including PSFA, PSAD, PSRD, average MD, FA, AD, RD, local efficiency, normalized cluster coefficient, small-worldness, assortativity, modularity, or hierarchy (p > 0.05). After adjusting for relevant variables, both PSMD and lambda values exhibited a significant negative correlation with reasoning and problem-solving scores (PSMD: r = -0.409, p = 0.038; lambda: r = -0.520, p = 0.006). No statistically significant correlations were observed between each PANSS score and the aforementioned metrics in the patient group (p > 0.05). Multivariate linear regression analysis revealed that increased PSMD (β = -0.426, t = -2.260, p = 0.034) and increased lambda (β = -0.490, t = -2.994, p = 0.007) were independently associated with decreased reasoning and problem-solving scores respectively ( = 0.295, F = 2.951, p = 0.029). But these significant correlations did not withstand FDR correction (p_FDR > 0.05). PSMD can be considered as a valuable neuroimaging biomarker that complements conventional diffusion measurements for investigating abnormalities in WM microstructural integrity and cognitive functions in schizophrenia.

Changed ventral striatum structural covariance and grey matter volume in depression during a one-year follow-up

Empirical findings suggest reduced cortico-striatal structural connectivity in patients with major depressive disorder (MDD). However, the relationship between the abnormal structural covariance and one-year outcome of first-episode drug-naive patients has not been evaluated. This longitudinal study aimed to identify specific changes of ventral striatum-related brain structural covariance and grey matter volume in forty-two first-episode patients with major depression disorder compared with thirty-seven healthy controls at the baseline and the one-year follow-up conditions. At the baseline, patients showed decreased structural covariance between the left ventral striatum and the bilateral superior frontal gyrus (SFG), bilateral middle frontal gyrus (MFG), right supplementary motor area (SMA) and left precentral gyrus and increased grey matter volume at the left fusiform and left parahippocampus. At the one-year follow-up, patients showed decreased structural covariance between the left ventral striatum and the right SFG, right MFG, left precentral gyrus and left postcentral gyrus, and increased structural covariance between the right ventral striatum and the right amygdala, right hippocampus, right parahippocampus, right superior temporal pole, right insula and right olfactory bulb and decreased volume at the left SMA compared with controls. These findings suggest that specific ventral striatum connectivity changes contribute to the early brain development of the MDD.

White matter microstructure alterations of the posterior limb of internal capsule in first-episode drug naive schizophrenia patients

ObjectivesPrevious studies have shown that microstructural alterations in white matter (WM) could contribute to the symptom manifestation and support the dysconnectivity hypothesis in schizophrenia patients. These alterations were pervasive, non-specific, and reported inconsistently across the literature. This study aimed to specifically investigate the microstructure alterations of the posterior limb of the internal capsule (PLIC) in first-episode, drug-naive schizophrenia patients. Utilizing a multicompartmental biophysical model, we further explored the correlation between these alterations and syndrome scale scores. MethodsThirty-two individuals with first-episode, drug-naive schizophrenia (FES) and thirty demographically matched healthy controls were enrolled. High-resolution multi-shell diffusion MRI data were collected, followed by the application of a three-compartment Neurite Orientation Dispersion and Density Imaging (NODDI) model to scrutinize the alterations in white matter microstructure. Changes in sensory and motor fibers within the PLIC were specifically focused on. Additionally, the correlation between these pathological changes and scores on the Positive and Negative Syndrome Scale (PANSS) was investigated. ResultsThe Neurite density index (NDI) in the left PLIC was significantly lower in FES patients compared to healthy individuals, and positively correlated with PANSS positive syndrome scores (r = 0.0379, p = 0.046). In the sensory component (left superior thalamic radiation within PLIC, STR_P), the NDI was significantly elevated (p < 0.0001). Conversely, the NDI in the motor component (left corticospinal tract within PLIC, CST_P) was reduced (p = 0.007) in FES patients compared to healthy individuals, and strongly correlated with PANSS positive syndrome scores (p < 0.020) and PANSS total scores (p < 0.045). Moreover, the NDI deviation of STR from total PLIC (fSTR_P) and NDI deviation in STR_P and CST_P compared to PLIC region (fPLIC) were significantly higher in FES patients than in healthy controls (p < 0.00001), with an area under the curve (AUC) of fPLIC reaching 0.872. ConclusionThe study’s findings provided new insights into the discrepancy of white matter microstructure changes associated with the sensory and motor fibers in the PLIC region in FES patients. These results contribute to the growing body of evidence suggesting that WM microstructural alterations play a critical role in schizophrenia pathophysiology.

Impaired topology and connectivity of grey matter structural networks in major depressive disorder: evidence from a multi-site neuroimaging data-set.

Major depressive disorder (MDD) has been increasingly understood as a disruption of brain connectome. Investigating grey matter structural networks with a large sample size can provide valuable insights into the structural basis of network-level neuropathological underpinnings of MDD. Using a multisite MRI data-set including nearly 2000 individuals, this study aimed to identify robust topology and connectivity abnormalities of grey matter structural network linked to MDD and relevant clinical phenotypes. A total of 955 MDD patients and 1009 healthy controls were included from 23 sites. Individualised structural covariance networks (SCN) were established based on grey matter volume maps. Following data harmonisation, network topological metrics and focal connectivity were examined for group-level comparisons, individual-level classification performance and association with clinical ratings. Various validation strategies were applied to confirm the reliability of findings. Compared with healthy controls, MDD individuals exhibited increased global efficiency, abnormal regional centralities (i.e. thalamus, precentral gyrus, middle cingulate cortex and default mode network) and altered circuit connectivity (i.e. ventral attention network and frontoparietal network). First-episode drug-naive and recurrent patients exhibited different patterns of deficits in network topology and connectivity. In addition, the individual-level classification of topological metrics outperforms that of structural connectivity. The thalamus-insula connectivity was positively associated with the severity of depressive symptoms. Based on this high-powered data-set, we identified reliable patterns of impaired topology and connectivity of individualised SCN in MDD and relevant subtypes, which adds to the current understanding of neuropathology of MDD and might guide future development of diagnostic and therapeutic markers.

Prevalence and associated factors of obesity in patients with major depressive disorder at different ages of onset.

Major depressive disorder (MDD) and obesity are two serious public health problems. Although there have been some research on both, there have few studies on differences in obesity among MDD patients at different ages of onset. The study aims to evaluate the prevalence and factors associated with obesity in MDD patients at different ages of onset. This study totally recruited 1718 first-episode drug-naive MDD patients aged from 18 to 60years. All subjects were divided into two subgroups: early adulthood onset (EAO, 18-45years) and mid-adulthood onset (MAO, 45-60years). Clinical symptoms of patients were evaluated using the 17-item Hamilton Depression Rating Scale (HAMD-17), Hamilton Anxiety Scale (HAMA), and Positive and Negative Syndrome Scale (PANSS) positive subscale. Baseline parameters including body mass index (BMI), blood pressure, and hematological biochemical parameters were assessed to investigate the association between these parameters and weight gain risk. The percentages of overweight and obesity patients with MDD in EAO group were 54.4% and 4.1%, respectively, and the percentages of overweight and obesity patients with MDD in MAO group were 60.4% and 2.8%, respectively. MDD patients in the MAO group had a longer duration of illness and higher scores in HAMD, HAMA, and PANSS positive subscale. They also had higher levels of thyroid stimulating hormone (TSH), anti-thyroglobulin (TgAb), fasting blood glucose (FBG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), systolic and diastolic blood pressures (SBP and DBP) levels. BMI did not differ significantly between the two groups. In the EAO group, statistically significant differences were found among normal weight, overweight and obese group in duration of illness, age of onset, TSH, TgAb, thyroid peroxidase antibody (TPOAb), free thyroxine (FT4), TC, triglycerides (TG), SBP and DBP. The TSH, TgTb and SBP were identified as risk factors for weight gain. In the MAO group, statistically significant differences were found among normal weight, overweight and obese group in TSH and FBG. The two indicators were identified as risk factors for weight gain. There were no significant differences in the weight of MDD patients at different ages of onset, while the factors that could potentially lead to obesity did show some differences.

Ghrelin and depressive symptoms in patients with first-episode drug-naïve major depressive disorder: The mediating role of hypothalamic-pituitary-adrenal axis.

Major depressive disorder (MDD) is one of the global burdens of disease, and its pathogenesis remains unclear. An increasing amount of research indicates that ghrelin regulates mood in patients with MDD. Still, current results are inconsistent, and the mechanisms underlying how ghrelin modulates depressive symptoms are inconclusive, especially in first-episode drug-naïve MDD patients. Therefore, this study aims to investigate the relationship and potential mechanism between ghrelin and first-episode drug-naïve MDD. Ninety first-episode drug-naïve MDD patients and 65 healthy controls (HCs) were included. Hamilton Depression Scale (HAMD-17) as a measure of depressive symptoms. Plasma levels of ghrelin and hypothalamic-pituitary-adrenal axis (HPA-axis) hormones were measured in all participants. Compared to HCs, the ghrelin levels were higher in the MDD (p < .001) and still showed significance after covarying for sex, age, and Body Mass Index (BMI). Ghrelin was positively related to corticotropin-releasing-hormone (CRH) levels (r = .867, p < .001), adrenocorticotropic hormone (ACTH) levels (r = .830, p < .001), and cortisol levels (r = .902, p < .001) in partial correlation analysis. In addition, there was a positive correlation between HAMD total score and ghrelin levels (r = .240, p = .026). Other than that, the HAMD total score also had a positive correlation with the CRH (r = .333, p = .002) and cortisol (r = .307, p = .004) levels. Further mediation analysis demonstrated that the relationship between ghrelin and HAMD total score was mediated by CRH (ab-path; β = .4457, 95% CI = 0.0780-1.0253, c-path; β = .2447, p = .0260, c'-path; β = -.2009, p = .3427). These findings revealed that plasma ghrelin provides a pivotal link to depressive symptoms in first-episode drug-naive MDD patients. CRH mediated the relationship between ghrelin and HAMD total score. It might provide new insights into understanding the pathogenesis of MDD, contributing to intervention and treatment from this approach.

The potential predictors for treatment-resistance depression after selective serotonin reuptake inhibitors therapy in Han Chinese: A resting-state functional magnetic resonance imaging study.

Selective serotonin reuptake inhibitors (SSRIs) are among the most important antidepressants. However, there is limited research on predicting the occurrence of treatment-resistant depression (TRD) after 5 years. Examining the predictive effect of TRD occurrence using resting-state fMRI in patients initiating SSRIs treatment at the onset of major depressive disorder (MDD) could potentially enhance TRD management. A total of 60 first-episode drug-naive MDD patients who met the criteria, along with 41 healthy controls of Han Chinese ethnicity, were recruited. All MDD patients received SSRIs as the initial treatment for relieving depressive symptoms. Resting-state fMRI scans were conducted for all subjects. Follow-up assessments were conducted over a period of five years, during which MDD patients were categorized into treatment-resistant depression (TRD) and non-treatment-resistant depression (NRD) groups based on disease progression. Amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), and Regional Homogeneity (ReHo) values were calculated and compared among the three groups. Additionally, receiver operating characteristic (ROC) curves were employed to identify potential predictors. After 5 years of follow-up, it was found that 43 MDD patients were classified as NRD, while 17 were classified as TRD. In comparison to TRD, NRD exhibited decreased ALFF in the left middle cingulum gyrus (MCG.L) and in the right middle frontal gyrus (MFG.R), as well as decreased ReHo in MCG.L. Furthermore, NRD showed increased fALFF in the left precuneus (PCUN.L). The area under the curve (AUC) values were as follows: 0.724 (MCG.L by ALFF), 0.732 (MFG.R), 0.767 (PCUN.L), 0.774 (MCG.L by ReHo), 0.878 (combined), 0.547 (HAMD), and 0.408 (HAMA) respectively. The findings suggest that PCUN.L, MFG.R, MCG.L, and the combined measures may indicate the possibility of developing TRD after 5 years when SSRIs are used as the initial therapy for relieving depressive symptoms in MDD patients.

Does Baseline Cognitive Function Predict the Reduction Rate in HDRS-17 Total Scores in First-Episode, Drug-Naïve Patients with Major Depressive Disorder?

Major depressive disorder (MDD) is associated with worse cognitive functioning. We aim to examine the association between baseline cognitive functioning and the reduction rate in HDRS-17 total scores and to highlight the predictors of the reduction rate in HDRS-17 total scores in MDD with first-episode, drug-naïve (FED) patients. Ninety FED patients were recruited consecutively and evaluated using the 17-item Hamilton Depression Rating Scale (HDRS-17), the 14-item Hamilton Anxiety Scale (HAMA-14), the Functioning Assessment Short Test (FAST) and the MATRICS Consensus Cognitive Battery (MCCB) at baseline and again at week 8. Eighty-four FED patients completed the study. Comparison showed that response group had significantly higher T scores in TMT-A, BACS-SC, WMS-III, BVMT-R, MSCEI and CPT-IP, but showed significantly lower scores in FAST total scores including autonomy, occupational functioning, cognitive functioning, interpersonal relationship than non- response group (all p's< 0.05). Partial correlation analysis also found that the reduction rate in HDRS-17 total scores could be negatively associated with autonomy, cognitive functioning and interpersonal relationship domains as well as total FAST scores, also was further positively associated with T-scores of BACS-SC, CPT-IP and MSCEI in MCCB, even when accounting for potential confounders. Furthermore, the levels of cognitive function domain, autonomy domain in FAST, and BACS-SC, CPT-IP in MCCB may predict the reduction rate in HDRS-17 total scores in FED patients (all p's< 0.05). Our findings underscore significant correlations between baseline functioning and the reduction rate in HDRS-17 total scores in FED patients. Moreover, better baseline cognitive function, autonomy, speed of processing and attention/vigilance are more likely to predict patients' response to antidepressant treatment, indicating pre-treatment better cognitive functioning may be predictors to treatment response in FED.

Exploring specific associations of childhood maltreatment with social cognition in drug-naive first-episode major depressive disorder: a sex-centric approach.

Childhood maltreatment (CM) has been linked to social cognition deficits in major depressive disorder (MDD), but little is known about sex-specific effects. This study aimed to investigate the sex-specific associations of CM with social cognition in first-episode drug-naive patients with MDD. A total of 117 first-episode drug-naive patients with MDD and 134 healthy controls (HCs) were recruited and assessed for demographic and clinical characteristics. All participants completed the Childhood Trauma Questionnaire (CTQ), Toronto Alexithymia Scale (TAS-20), Interpersonal Reactivity Index-C (IRI), and Facial Emotion Recognition Test. Partial correlation analysis was used to explore the sex-specific association of CM with social cognition. Our findings revealed significant differences in the associations of CM with social cognition between males and females in MDD patients. In comparison to HCs, the associations of CM with social cognition displayed distinct and even contrasting sex-specific patterns in MDD patients. Specifically, male MDD patients exhibited unique imbalanced associations between emotional neglect and alexithymia, while both female and male MDD patients shared imbalanced associations of childhood abuse with empathy. These results emphasize the importance of considering the sex-specific associations of CM with social cognition in MDD and highlight the need for personalized interventions and treatments based on sex for MDD patients with a history of CM.

Changes of cortical thickness in the first episode, drug-naive depression patients with and without melancholic features

Melancholic depression (MD) is a more severe type of major depressive disorder (MDD) with a core feature of anhedonia. However, its pathophysiology remains unclear. The current study aims to investigate whether there is a significant difference in cortical thickness (CT) that can be used to differentiate MD patients from non-melancholic depression (NMD) patients. We recruited 137 first-episode drug-naive MDD patients and 75 healthy controls (HCs) for structural magnetic resonance imaging, analyzed using the Surface-based morphometry approach. Meanwhile, the MDD patients were divided into the MD and NMD subgroups according to their scores on the Montgomery-Asberg Depression Rating Scale and Hamilton Depression Rating Scale. No significant CT differences among the three groups were found. We also did not find significant CT changes between the NMD and the HCs groups or between the MD and NMD groups. However, the CT of the left postcentral gyrus and right precuneus among MD patients were larger than HCs. Moreover, the CT of the left postcentral gyrus and right precuneus were not correlated with the severity of the disease and illness duration. The findings suggest that the CT alterations of the left postcentral gyrus and the right precuneus are distinct pathological mechanisms for MD.

Correlation of Obesity and Clinical Characteristics in Drug-Naive First-Episode Patients With Schizophrenia.

This study was aimed at investigating the prevalence of obesity in drug-naive first-episode (DNFE) patients with schizophrenia and its association with metabolic parameters, psychopathological symptoms, and cognitive function. We collected general information on 411 DNFE schizophrenia patients and divided them into obese and nonobese groups according to body mass index (BMI). Glucolipid metabolic parameters of patients were collected. Positive and Negative Syndrome Scale was performed for assessing patients' psychopathological symptoms. Cognitive function was observed and evaluated in both groups. Pearson correlation analysis was applied to assess factors related to BMI, while we conducted multiple stepwise regression analysis for determining risk factors for obesity. Obesity occurred in 60.34% of DNFE patients with schizophrenia, whereas the obese group had notably higher BMI value and waist-to-hip ratio than the nonobese group (P < 0.05). Obese patients had markedly higher levels of blood glucose, insulin, apolipoprotein B, total triglycerides, low-density lipoprotein cholesterol, and total cholesterol versus nonobese patients (P < 0.05). Besides, the disease severity and cognitive function were dramatically lower in the obese group. Results of multiple stepwise regression analysis demonstrated negative symptoms, low-density lipoprotein cholesterol, triglycerides, and blood glucose levels as the risk factors for comorbid obesity in DNFE patients with schizophrenia. The detection rate of obesity was high in DNFE patients with schizophrenia, and there was an intrinsic association between obesity and glucolipid metabolism, clinical symptoms, and cognitive function among them. Our study will provide a theoretical foundation for the diagnosis of obesity in DNFE patients with schizophrenia and the development of effective early interventions.

Thyroid dysfunction in young, first-episode and drug-naïve patients with major depressive disorder: prevalence and associated clinical factors.

The incidence of thyroid dysfunction (TD) and major depressive disorder (MDD) is increasing year by year in the general population. However, the prevalence and correlates of TD in first-episode drug-naive (FEDN) MDD patients have not been explored. This study sought to fill this gap and examine the association between TD and MDD. We recruited 1,289 FEDN MDD patients aged 18 ~ 45 years. A total of 1,289 FEDN MDD outpatients were recruited. Demographical and suicide data were collected for each patient, and lipid profiles, thyroid function, and fasting blood glucose (FBG) levels were measured. The Hamilton Depression Scale 17 (HAMD-17) was assessed for depression. The prevalence of TD in young FEDN MDD patients was 64.86%. Compared with those without TD, patients with TD had longer duration of illness, greater HAMD score, higher BMI, TG, TC, and LDL-C levels, and higher suicide attempt rates, but lower HDL-C and FBG levels. Further logistic regression indicated that duration of illness, HAMD score, TC, HDL-C, BMI, and FBG levels were significantly associated with TD. No causal relationship can be drawn due to the cross-sectional design. TD is common in young FEDN MDD patients. So clinicians should monitor thyroid function in patients with MDD.

Heterogeneous brain dynamic functional connectivity patterns in first‐episode drug‐naive patients with major depressive disorder

It remains challenging to identify depression accurately due to its biological heterogeneity. As people suffering from depression are associated with functional brain network alterations, we investigated subtypes of patients with first-episode drug-naive (FEDN) depression based on brain network characteristics. This study included data from 91 FEDN patients and 91 matched healthy individuals obtained from the International Big-Data Center for Depression Research. Twenty large-scale functional connectivity networks were computed using group information guided independent component analysis. A multivariate unsupervised normative modeling method was used to identify subtypes of FEDN and their associated networks, focusing on individual-level variability among the patients for quantifying deviations of their brain networks from the normative range. Two patient subtypes were identified with distinctive abnormal functional network patterns, consisting of 10 informative connectivity networks, including the default mode network and frontoparietal network. 16% of patients belonged to subtype I with larger extreme deviations from the normal range and shorter illness duration, while 84% belonged to subtype II with weaker extreme deviations and longer illness duration. Moreover, the structural changes in subtype II patients were more complex than the subtype I patients. Compared with healthy controls, both increased and decreased gray matter (GM) abnormalities were identified in widely distributed brain regions in subtype II patients. In contrast, most abnormalities were decreased GM in subtype I. The informative functional network connectivity patterns gleaned from the imaging data can facilitate the accurate identification of FEDN-MDD subtypes and their associated neurobiological heterogeneity.

Prevalence, risk factors and clinical correlates of glucose disturbances in a large sample of Han Chinese patients with first-episode drug-naïve major depressive disorder.

Glucose disturbances are a common comorbidity of major depressive disorder (MDD) patients and have been extensively studied in the past. However, few studies have explored glucose disturbances in first-episode drug-naïve (FEDN) MDD patients. The purpose of this study was to examine the prevalence and risk factors of glucose disturbances in FEDN MDD patients to understand the relationship between MDD and glucose disturbances in the acute early phase and provide important implications for therapeutic interventions. Using a cross-sectional design, we recruited a total of 1718 MDD patients. We collected their socio-demographic information, clinical data, and blood glucose indicators.17-item Hamilton Depression Rating Scale (HAMD), 14-item Hamilton Anxiety Rating Scale (HAMA), and the positive symptom subscale of the Positive and Negative Syndrome Scale (PANSS) were used to assess their depression, anxiety, psychotic symptoms, respectively. The prevalence of glucose disturbances in FEDN MDD patients was 13.6%. Depression, anxiety and psychotic symptoms, body mass index (BMI) levels and suicide attempts rates were higher in the group with glucose disorders than in the group without glucose disorders among patients with first-episode drug-naive MDD. Correlation analysis showed that glucose disturbances were associated with HAMD score, HAMA score, BMI, psychotic symptoms and suicide attempts. Furthermore, binary logistic regression showed that HAMD score and suicide attempts were independently associated with glucose disturbances in MDD patients. Our findings suggest that the prevalence of comorbid glucose disturbances is very high in FEDN MDD patients. Moreover, more severe depressive symptoms and higher suicide attempts are correlated with glucose disturbances in MDD FEDN patients in the early stage.

Transcriptional substrates of brain structural and functional impairments in drug-naive first-episode patients with major depressive disorder

BackgroundDespite remarkable success in identifying genetic risk factors for depression, there are still open questions about the exact genetic mechanisms underlying certain disease phenotypes, such as brain structural and functional impairments. MethodsComprehensive multi-modal neuroimaging meta-analyses were conducted to examine changes in brain structure and function in drug-naive first-episode patients with major depressive disorder (DF-MDD). Combined with the Allen Human Brain Atlas, transcriptome-neuroimaging spatial association analyses were performed to identify genes whose expression related to these brain structural and functional changes, followed by a range of gene functional signature analyses. ResultsMeta-analyses revealed gray matter atrophy in the insula, temporal pole, cerebellum and postcentral gyrus, and a complex pattern of hyper-function in the temporal pole and hypo-function in the cuneus/precuneus, angular gyrus and lingual gyrus in DF-MDD. Moreover, these brain structural and functional changes were spatially associated with the expression of 1194 and 1733 genes, respectively. Importantly, there were commonalities and differences in the two gene sets and their functional signatures including functional enrichment, specific expression, behavioral relevance, and constructed protein-protein interaction networks. LimitationsThe results merit further verification using a large sample of DF-MDD. ConclusionsOur findings not only corroborate the polygenic nature of depression, but also suggest common and distinct genetic modulations of brain structural and functional impairments in this disorder.

Disrupted intrinsic functional brain network in patients with late-life depression: Evidence from a multi-site dataset

BackgroundLate-life depression (LLD) is a common and serious mental disorder, whose neural mechanisms are not yet fully understood. In this study, we aimed to characterize LLD-related changes in intrinsic functional brain networks using a large, multi-site sample. MethodsUsing resting-state functional magnetic resonance imaging, the edge-based functional connectivity (FC) as well as multiple topological brain network metrics at both global and nodal levels were compared between 206 LLD patients and 210 normal controls (NCs). ResultsCompared with NCs, the LLD patients had extensive alterations in the intrinsic brain FCs, especially significant decreases in FCs within the default mode network (DMN) and within the somatomotor network (SMN). The LLD patients also showed alterations in several global brain network metrics compared with NCs, including significant decreases in global efficiency, local efficiency, clustering coefficient, and small-worldness, as well as a significantly increased characteristic path length. Moreover, significant alterations in nodal network metrics (increased nodal betweenness and decreased nodal efficiency) were found in patients with LLD, which mainly involved the DMN and SMN. Post-hoc subgroup analyses indicated that the above changes in FC strengths were present in both first-episode, drug-naïve (FEDN) and non-FEDN patients, and were correlated with depression severity in the FEDN patients. Moreover, changes in FC strengths were found in both the early/late-onset (depression starts before/after the age of 50) patients, while altered topological metrics were found in only the late-onset patients. ConclusionsThese results may help to strengthen our understanding of the underlying neural mechanisms and biological heterogeneity in LLD.

Gender differences in major depressive disorders: A resting state fMRI study.

Major depressive disorder (MDD) has a high disability rate and brings a large disease burden to patients and the country. Significant sex differences exist in both the epidemiological and clinical features in MDD. The effect of sex on brain function in MDD is not clear now. Regional homogeneity (ReHo) and ALFF are widely used research method in the study of brain function. This research aimed to use ReHo and ALFF to explore gender differences in brain function images in MDD. Eighty first-episode drug-naive patients (47 women and 30 men) with MDD and 85 age, education matched healthy volunteers (47 women and 31 men) were recruited in our study and participated in resting-state functional magnetic resonance imaging scans. ReHo and ALFF were used to assess brain activity, two-way ANOVA and post hoc analysis was conducted to explore the sex difference in MDD. Correlation analysis was used to explore the relationship between abnormal brain functioning and clinical symptoms. We observed sex-specific patterns and diagnostic differences in MDD Patients, further post hoc comparisons indicated that women with MDD showed decreased ALFF value in the right superior occipital gyrus and decreased ReHo value in the left calcarine and left dorsolateral superior frontal gyrus compared with HC females and men with MDD. Men with MDD showed decreased ReHo value in the right median cingulate gyrus compared with HC males and increased ReHo value in the left dorsolateral superior frontal gyrus compared with HC males, we also found that HC males showed higher ReHo value in the right median cingulate gyrus than HC females. Men and women do have sex differences in brain function, the occipital lobe, calcarine, DLPFC, and DCG were the main different brain regions found between male and female in MDD, which may be the biomarker brain regions that can help diagnose and treat MDD in men and women.

Altered spatio-temporal state patterns for functional dynamics estimation in first-episode drug-naive major depression.

Patients with major depressive disorder (MDD) display affective and cognitive impairments. Although MDD-associated abnormalities of brain function and structure have been explored in depth, the relationships between MDD and spatio-temporal large-scale functional networks have not been evaluated in large-sample datasets. We employed data from International Big-Data Center for Depression Research (IBCDR), and comparable 543 healthy controls (HC) and 314 first-episode drug-naive (FEDN) MDD patients were included. We used a multivariate pattern classification method to learn informative spatio-temporal functional states. Brain states of each participant were extracted for functional dynamic estimation using an independent component analysis. Then, a multi-kernel pattern classification method was developed to identify discriminative spatio-temporal states associated with FEDN MDD. Finally, statistical analysis was applied to intrinsic and clinical brain characteristics. Compared with HC, FEDN MDD patients exhibited altered spatio-temporal functional states of the default mode network (DMN), the salience network, a hub network (centered on the dorsolateral prefrontal cortex), and a relatively complex coupling network (visual, DMN, motor-somatosensory and subcortical networks). Multi-kernel classification models to distinguish patients from HC obtained areas under the receiver operating characteristic curves up to 0.80. Classification scores correlated with Hamilton Depression Rating Scale scores and age at MDD onset. FEDN MDD patients had multiple abnormal spatio-temporal functional states. Classification scores derived from these states were related to symptom severity. The assessment of spatio-temporal states may represent a powerful clinical and research tool to distinguish between neuropsychiatric patients and controls.