Background GW117(N-(2-(6-chloro-7-deuteromethoxynaphthalen-1-yl)ethyl)acetamide)is a dual-acting agent(MT1/MT2 agonist,5-HT_(2C)antagonist)with prior evidence of antidepressant efficacy and favourable safety.Aims To p...Background GW117(N-(2-(6-chloro-7-deuteromethoxynaphthalen-1-yl)ethyl)acetamide)is a dual-acting agent(MT1/MT2 agonist,5-HT_(2C)antagonist)with prior evidence of antidepressant efficacy and favourable safety.Aims To preliminarily evaluate the efficacy and safety of GW117 in major depressive disorder(MDD)and to explore the optimal dosing.Methods A total of 280 eligible patients aged 18-65years with MDD were randomly assigned(1:1:1:1)to8 weeks of double-blind treatment with fixed doses of GW117 tablets(20,40,60 mg/day)or placebo.The primary endpoint was the change from baseline to Week 8 in the total score of the Hamilton Rating Scale for Depression-17item(HAMD-17).Key secondary endpoints included changes in the Montgomery-?sberg Depression Rating Scale(MADRS)total score over the same period.Results In the full analysis set(n=276),GW117 showed numerically greater reductions versus placebo in the HAMD-17 and MADRS total scores,as well as higher response rates at Week 8.However,these differences did not reach statistical significance,potentially due to a high placebo response and other contributing factors.In a post hoc analysis of an optimal subgroup(baseline HAMD-17>24 or insomnia factor>4),GW117 showed efficacy in improving multidimensional symptoms,including insomnia.The 20 mg dose demonstrated a significant3.66-point greater reduction in MADRS(p=0.026)and a23.16%higher response rate(p=0.013)compared with placebo.GW117 was well-tolerated,with no cases of alanine aminotransferase or aspartate aminotransferase exceeding 3×the upper limit of normal and no concerning safety signals reported.Conclusions This exploratory study found that GW117demonstrated encouraging antidepressant efficacy and a favourable safety profile in patients with MDD.Although differences versus placebo did not reach statistical significance in the overall population,GW11720 mg monotherapy showed significant improvements in multidimensional depressive symptoms,including insomnia,in the optimal response subgroup.No hepatotoxicity was reported,supporting its promising therapeutic potential for further clinical development.展开更多
Background Biomarkers for predicting suicide risk in hospitalised patients with mental disorders have been understudied.Currently,suicide risk assessment tools based on objective indicators are limited in China.Aims T...Background Biomarkers for predicting suicide risk in hospitalised patients with mental disorders have been understudied.Currently,suicide risk assessment tools based on objective indicators are limited in China.Aims To examine the value of various biomarkers in suicide risk prediction and develop a risk assessment model with clinical utility using machine learning.Methods This cohort study analysed patients with major depressive disorder(MDD) who were hospitalised for the first time between January 2016 and March 2023 from four specialised mental health institutions.A total of 139 features,including biomarker measurements,medical orders and psychological scales,were assessed for analysis.Their suicide risk was evaluated by qualified nurses using Nurse s Global Assessment of Suicide Risk within 1 week after admission.Five machine learning models were trained with 10-fold cross-validation across three hospitals and were externally validated in an independent cohort.The primary performance was assessed using the area under the receiver operating characteristic curve(AUROC).The model was interpreted using the SHapley Additive exPlanations(SHAP) analysis.Biomarker importance was evaluated by comparing model performance with and without these biomarkers.Results Of 3143 patients with MDD included in this study,the incidence of high suicide risk within 1 week after first admission was 660(21.0%).Among all models,the Extreme Gradient Boosting can more effectively predict future risks,with an AUROC higher than 0.8(p<0.001).The SHAP values identified the 10 most important features,including five biomarkers.After clustering analysis,electroconvulsive therapy,physical restraint,β2-microglobulin and triiodothyronine were found to have heterogeneous effects on suicide risk.Combining biomarkers with other data from electronic health records significantly improved the performance and clinical utility of machine learning models based on demographics,diagnosis,laboratory tests,medical orders and psychological scales.Conclusions This study demonstrates the potential for a biomarker-based suicide risk assessment for patients with MDD,emphasising the interaction between biomarkers and therapeutic interventions.展开更多
To the editor:A wide range of affective disorders affects people of all ages globally and contributes significantly to the global disease burden.1 In China,a nationwide survey found a 3.21% prevalence of affective dis...To the editor:A wide range of affective disorders affects people of all ages globally and contributes significantly to the global disease burden.1 In China,a nationwide survey found a 3.21% prevalence of affective disorders in children and adolescents,with major depressive disorder(MDD)at 2.00%and bipolar disorder at 0.86%.展开更多
The majority of individuals maintain normal physiological and behavioral function despite experiencing severe traumatic stress,demonstrating psychological resilience.Yet a clinically significant proportion develops in...The majority of individuals maintain normal physiological and behavioral function despite experiencing severe traumatic stress,demonstrating psychological resilience.Yet a clinically significant proportion develops increased vulnerability,often presenting as stress-related psychiatric conditions such as major depressive disorder(MDD)[1].The global prevalence of MDD is surging unprecedentedly,contributing substantially to the global burden of disease and disability.展开更多
Background Yueju Pill,a classic traditional Chinese medicine,shows antidepressant effects rapidly.However,biomarkers that can predict its treatment outcomes in major depressive disorder(MDD)are still lacking.Multimoda...Background Yueju Pill,a classic traditional Chinese medicine,shows antidepressant effects rapidly.However,biomarkers that can predict its treatment outcomes in major depressive disorder(MDD)are still lacking.Multimodal magnetic resonance imaging(MRI)offers a promising avenue to identify such biomarkers.Aims This pilot study aimed to explore whether therapeutic responses to Yueju Pill could be predicted by MRI-derived brain networks and to identify drug-specific biomarkers in comparison to escitalopram,a mainstream antidepressant.Methods We collected multimodal MRI data and blood samples from 28 outpatients with MDD from the Fourth People's Hospital of Taizhou,who were randomly divided into two groups to receive either Yueju Pill(23 g/time/day)or escitalopram(10 mg,two times a day)for 4 days.Morphological and functional brain networks were constructed and used to predict individual changes in symptoms quantified by the 24-item Hamilton Depression Scale(HAMD-24)scores and serum brain-derived neurotrophic factor(BDNF)levels.Results After the treatment,both groups exhibited significant reductions in the HAMD-24 scores,while only the Yueju Pill group showed significant increases in the BDNF levels.Gyrification Index-based morphological networks predicted change rates of the HAMD-24 scores in both groups,but sulcus depth-based and cortical thickness-based morphological networks predicted change rates of the HAMD-24 scores and BDNF levels,respectively,only in the Yueju Pill group.Subnetwork analyses revealed that the visual network independently predicted the changes in both the HAMD-24 scores(sulcus depth-based networks)and BDNF levels(cortical thickness-based networks)following Yueju Pill treatment.Conclusions Morphological but not functional brain networks can predict symptom improvement and BDNF changes of patients with MDD after Yueju Pill treatment.Sulcus depth-based and cortical thickness-based morphological brain networks,particularly their visual subnetworks,might serve as Yueju Pill-specific biomarkers for predicting the therapeutic responses.These findings have the potential to guide personalised therapy for patients with MDD early in the therapeutic process.展开更多
Background Major depressive disorder(MDD),characterised by persistent anhedonia and elevated suicide risk,represents a global mental health challenge.Recent studies suggest a link between gut-brain axis dysfunction an...Background Major depressive disorder(MDD),characterised by persistent anhedonia and elevated suicide risk,represents a global mental health challenge.Recent studies suggest a link between gut-brain axis dysfunction and depression.The natural compound paeoniflorin demonstrates clinically relevant antidepressant effects,yet its underlying neurobiological mechanisms remain elusive.Aims This study aims to examine how paeoniflorin alleviates depression-like behaviours in rats subjected to chronic unpredictable mild stress(CUMS)by modulating the function of gut-brain axis,and explore the connections between gut microbiota,metabolites and MDD.Methods Depression-like behaviours in rats were induced by CUMS,and the antidepressant effect of paeoniflorin was assessed using behavioural tests.The composition and function of the intestinal microbiota were analysed using 16S rRNA sequencing,and metabolomic analysis was performed on serum,hippocampus,jejunum and faecal samples.Enzyme-linked immunosorbent assay and hematoxylin and eosin staining were used to detect the levels of inflammatory factors and cortisol,as well as the infiltration of inflammatory cells in the jejunum of rats after cohousing.Long-term potentiation assays and Golgi staining were used to detect dendritic spine density and synaptic plasticity,respectively.Results Paeoniflorin significantly alleviated depression-like behaviours and cognitive deficits in CUMS rats.16S rRNA sequencing revealed that paeoniflorin improved the abundance and diversity of the gut microbiota in CUMS rats.Enrichment of differential metabolites in the brain,intestine,faeces and serum revealed a primary accumulation in the amino acid metabolism pathway.We further observed a correlation between the relative abundance of microbial communities and metabolites.Cohousing experiments verified that microbial metabolites of paeoniflorin can reduce neuroinflammation and improve synaptic plasticity.Conclusions Disruptions in gut microbiota and its metabolites impair gut-brain interactions.Paeoniflorin’s neuroprotective and antidepressant effects are mediated through the modulation of the function of the gut-brain axis.展开更多
White-matter tracts play a pivotal role in transmitting sensory and motor information,facilitating interhemispheric communication and integrating different brain regions.Meanwhile,sensorimotor disturbance is a common ...White-matter tracts play a pivotal role in transmitting sensory and motor information,facilitating interhemispheric communication and integrating different brain regions.Meanwhile,sensorimotor disturbance is a common symptom in patients with major depressive disorder(MDD).However,the role of aberrant sensorimotor white-matter system in MDD remains largely unknown.Herein,we investigated the topological structure alterations of white-matter morphological brain networks in 233 MDD patients versus 257 matched healthy controls(HCs)from the DIRECT consortium.White-matter networks were derived from magnetic resonance imaging(MRI)data by combining voxel-based morphometry(VBM)and three-dimensional discrete wavelet transform(3D-DWT)approaches.Support vector machine(SVM)analysis was performed to discriminate MDD patients from HCs.The results indicated that the network topological changes in node degree,node efficiency,and node betweenness were mainly located in the sensorimotor superficial white-matter system in MDD.Using network nodal topological properties as classification features,the SVM model could effectively distinguish MDD patients from HCs.These findings provide new evidence to highlight the importance of the sensorimotor system in brain mechanisms underlying MDD from a new perspective of white-matter morphological network.展开更多
Background Metabolic dysregulation has been implicated in major depressive disorder(MDD).Aims We aimed to explore the potential role of plasma metabolites in MDD.Methods We conducted Mendelian randomisation(MR)analysi...Background Metabolic dysregulation has been implicated in major depressive disorder(MDD).Aims We aimed to explore the potential role of plasma metabolites in MDD.Methods We conducted Mendelian randomisation(MR)analysis to evaluate the causal effects of 871 circulating metabolites on MDD,using the Genome-Wide Association Studies datasets of MDD(N=1035760)and metabolites(N=8299).Bayesian colocalisation and druggability analyses were employed to identify genetic variants contributing to both MDD and levels of metabolites in plasma and to pinpoint metabolites with therapeutic potential,respectively.Results MR analysis identified 11 metabolites associated with MDD(false discovery rate<0.05).Eight metabolites,including arachidonate(20:4n6)(odds ratio(OR):0.97),1-arachidonoyl-GPC(20:4n6)(OR:0.98),1-(1-enylpalmitoyl)-2-palmitoleoyl-GPC(P-16:0/16:1)(OR:0.97),succinoyltaurine(OR:0.98),3-methoxycatechol sulphate(1)(OR:0.98)and 11β-hydroxyandrosterone glucuronide(OR:0.97),showed protective effects against MDD.Three metabolites were associated with increased risk,namely,butyrylglycine(OR:1.03),3-carboxy-4-methyl-5-propyl-2-furanpropanoate(OR:1.02)and 1-(1-enyl-stearoyl)-2-oleoyl-GPE(P-18:0/18:1)(OR:1.02).Colocalisation analysis supported shared genetic signals between five lipid metabolites and MDD,particularly at loci harbouring FADS and ATP9A.Notably,a majority of metabolites associated with MDD are being explored as therapeutic targets for various psychiatric disorders.Conclusions Genetically predicted levels of certain circulating metabolites make a causal contribution to MDD.Further investigation of their roles may provide novel pathophysiological insights and give clues for targeted therapies.展开更多
Background The patient-reported Dimensional Anhedonia Rating Scale(DARS)has been adapted into Chinese,so there is a need to evaluate its measurement properties in a Chinese population.Aims To evaluate the reliability ...Background The patient-reported Dimensional Anhedonia Rating Scale(DARS)has been adapted into Chinese,so there is a need to evaluate its measurement properties in a Chinese population.Aims To evaluate the reliability and validity of the DARS among Chinese individuals with major depressive disorder(MDD)and its treatment sensitivity in a prospective clinical study.Methods Data were from a multicentre,prospective clinical study(NCT03294525),which recruited both patients with MDD,who were followed for 8 weeks,and healthy controls(HCs),assessed at baseline only.The analysis included confirmatory factor analysis,validity and sensitivity to change.Results Patients’mean(standard deviation(SD))age was 34.8(11.0)years,with 68.7%being female.75.2%of patients with MDD had melancholic features,followed by 63.8%with anxious distress.Patients had experienced MDD for a mean(SD)of 9.2(18)months.DARS scores covered the full range of severity with no major floor or ceiling effects.Confirmatory factor analysis showed adequate fit statistics(comparative fit index 0.976,goodness-of-fit index 0.935 and root mean square error of approximation 0.055).Convergent validity with anhedonia-related measures was confirmed.While the correlation between the DARS and the Hamilton Depression Rating Scale was not strong(r=0.31,baseline),the DARS was found to differentiate between levels of depression.Greater improvements in DARS scores were seen with the Hamilton Rating Scale for Depression responder group(effect size 1.16)compared with the non-responder group(effect size 0.46).Conclusions This study comprehensively evaluated the measurement properties of the DARS using a Chinese population with MDD.Overall,the Chinese version of DARS demonstrates good psychometric properties and has been found to be responsive to change during antidepressant treatment.The DARS is a suitable scale for assessing patient-reported anhedonia in future clinical trials.展开更多
文摘Background GW117(N-(2-(6-chloro-7-deuteromethoxynaphthalen-1-yl)ethyl)acetamide)is a dual-acting agent(MT1/MT2 agonist,5-HT_(2C)antagonist)with prior evidence of antidepressant efficacy and favourable safety.Aims To preliminarily evaluate the efficacy and safety of GW117 in major depressive disorder(MDD)and to explore the optimal dosing.Methods A total of 280 eligible patients aged 18-65years with MDD were randomly assigned(1:1:1:1)to8 weeks of double-blind treatment with fixed doses of GW117 tablets(20,40,60 mg/day)or placebo.The primary endpoint was the change from baseline to Week 8 in the total score of the Hamilton Rating Scale for Depression-17item(HAMD-17).Key secondary endpoints included changes in the Montgomery-?sberg Depression Rating Scale(MADRS)total score over the same period.Results In the full analysis set(n=276),GW117 showed numerically greater reductions versus placebo in the HAMD-17 and MADRS total scores,as well as higher response rates at Week 8.However,these differences did not reach statistical significance,potentially due to a high placebo response and other contributing factors.In a post hoc analysis of an optimal subgroup(baseline HAMD-17>24 or insomnia factor>4),GW117 showed efficacy in improving multidimensional symptoms,including insomnia.The 20 mg dose demonstrated a significant3.66-point greater reduction in MADRS(p=0.026)and a23.16%higher response rate(p=0.013)compared with placebo.GW117 was well-tolerated,with no cases of alanine aminotransferase or aspartate aminotransferase exceeding 3×the upper limit of normal and no concerning safety signals reported.Conclusions This exploratory study found that GW117demonstrated encouraging antidepressant efficacy and a favourable safety profile in patients with MDD.Although differences versus placebo did not reach statistical significance in the overall population,GW11720 mg monotherapy showed significant improvements in multidimensional depressive symptoms,including insomnia,in the optimal response subgroup.No hepatotoxicity was reported,supporting its promising therapeutic potential for further clinical development.
基金supported by projects from Shanghai Putuo District Municipal Health Committee(ptkwws202413)Shanghai Municipal Health Commission(202340018)+2 种基金Shanghai Hospital Development Center(Data Sharing and Emulation of Clinical Trials,CCS-DASET:SHDC2024CRI008)Shanghai Changning District Municipal Commission of Health(CNWJXY026)School of Innovation and Entrepreneurship,Tongji University(S202310247388,X2024085 and X2024048).
文摘Background Biomarkers for predicting suicide risk in hospitalised patients with mental disorders have been understudied.Currently,suicide risk assessment tools based on objective indicators are limited in China.Aims To examine the value of various biomarkers in suicide risk prediction and develop a risk assessment model with clinical utility using machine learning.Methods This cohort study analysed patients with major depressive disorder(MDD) who were hospitalised for the first time between January 2016 and March 2023 from four specialised mental health institutions.A total of 139 features,including biomarker measurements,medical orders and psychological scales,were assessed for analysis.Their suicide risk was evaluated by qualified nurses using Nurse s Global Assessment of Suicide Risk within 1 week after admission.Five machine learning models were trained with 10-fold cross-validation across three hospitals and were externally validated in an independent cohort.The primary performance was assessed using the area under the receiver operating characteristic curve(AUROC).The model was interpreted using the SHapley Additive exPlanations(SHAP) analysis.Biomarker importance was evaluated by comparing model performance with and without these biomarkers.Results Of 3143 patients with MDD included in this study,the incidence of high suicide risk within 1 week after first admission was 660(21.0%).Among all models,the Extreme Gradient Boosting can more effectively predict future risks,with an AUROC higher than 0.8(p<0.001).The SHAP values identified the 10 most important features,including five biomarkers.After clustering analysis,electroconvulsive therapy,physical restraint,β2-microglobulin and triiodothyronine were found to have heterogeneous effects on suicide risk.Combining biomarkers with other data from electronic health records significantly improved the performance and clinical utility of machine learning models based on demographics,diagnosis,laboratory tests,medical orders and psychological scales.Conclusions This study demonstrates the potential for a biomarker-based suicide risk assessment for patients with MDD,emphasising the interaction between biomarkers and therapeutic interventions.
基金the Tianjin Health Research Project(Grant No.TJWJ2023MS038)Tianjin Education Commission Research Project(Grant No.2023KJ044)S&T Program of Hebei(SG2021189)。
文摘To the editor:A wide range of affective disorders affects people of all ages globally and contributes significantly to the global disease burden.1 In China,a nationwide survey found a 3.21% prevalence of affective disorders in children and adolescents,with major depressive disorder(MDD)at 2.00%and bipolar disorder at 0.86%.
基金supported by the National Natural Science Foundation of China(32300851)Zhejiang Provincial Natural Science Foundation(LQ24h310008).
文摘The majority of individuals maintain normal physiological and behavioral function despite experiencing severe traumatic stress,demonstrating psychological resilience.Yet a clinically significant proportion develops increased vulnerability,often presenting as stress-related psychiatric conditions such as major depressive disorder(MDD)[1].The global prevalence of MDD is surging unprecedentedly,contributing substantially to the global burden of disease and disability.
基金supported by the National Key Research and Development Program of China(No.2022YFE0201000)National Natural Science Foundation of China(Nos.82472092,82174002,81874374 and 81673625)+2 种基金a grant from the Research Center for Brain Cognition and Human Development,Guangdong,China(No.2024B0303390003)Key Realm R&D Program of Guangzhou(No.202206010109)Taizhou Science and Technology Support Program(Social Development)project(No.TS2016-12).
文摘Background Yueju Pill,a classic traditional Chinese medicine,shows antidepressant effects rapidly.However,biomarkers that can predict its treatment outcomes in major depressive disorder(MDD)are still lacking.Multimodal magnetic resonance imaging(MRI)offers a promising avenue to identify such biomarkers.Aims This pilot study aimed to explore whether therapeutic responses to Yueju Pill could be predicted by MRI-derived brain networks and to identify drug-specific biomarkers in comparison to escitalopram,a mainstream antidepressant.Methods We collected multimodal MRI data and blood samples from 28 outpatients with MDD from the Fourth People's Hospital of Taizhou,who were randomly divided into two groups to receive either Yueju Pill(23 g/time/day)or escitalopram(10 mg,two times a day)for 4 days.Morphological and functional brain networks were constructed and used to predict individual changes in symptoms quantified by the 24-item Hamilton Depression Scale(HAMD-24)scores and serum brain-derived neurotrophic factor(BDNF)levels.Results After the treatment,both groups exhibited significant reductions in the HAMD-24 scores,while only the Yueju Pill group showed significant increases in the BDNF levels.Gyrification Index-based morphological networks predicted change rates of the HAMD-24 scores in both groups,but sulcus depth-based and cortical thickness-based morphological networks predicted change rates of the HAMD-24 scores and BDNF levels,respectively,only in the Yueju Pill group.Subnetwork analyses revealed that the visual network independently predicted the changes in both the HAMD-24 scores(sulcus depth-based networks)and BDNF levels(cortical thickness-based networks)following Yueju Pill treatment.Conclusions Morphological but not functional brain networks can predict symptom improvement and BDNF changes of patients with MDD after Yueju Pill treatment.Sulcus depth-based and cortical thickness-based morphological brain networks,particularly their visual subnetworks,might serve as Yueju Pill-specific biomarkers for predicting the therapeutic responses.These findings have the potential to guide personalised therapy for patients with MDD early in the therapeutic process.
基金supported by the National Natural Science Foundation of China(No 82305144)the Jiangsu Provincial Natural Science Foundation Project for Universities(No 23KJB360004)the National Natural Science Foundation Supporting Project of Nanjing University of Chinese Medicine(No XPT82305144).
文摘Background Major depressive disorder(MDD),characterised by persistent anhedonia and elevated suicide risk,represents a global mental health challenge.Recent studies suggest a link between gut-brain axis dysfunction and depression.The natural compound paeoniflorin demonstrates clinically relevant antidepressant effects,yet its underlying neurobiological mechanisms remain elusive.Aims This study aims to examine how paeoniflorin alleviates depression-like behaviours in rats subjected to chronic unpredictable mild stress(CUMS)by modulating the function of gut-brain axis,and explore the connections between gut microbiota,metabolites and MDD.Methods Depression-like behaviours in rats were induced by CUMS,and the antidepressant effect of paeoniflorin was assessed using behavioural tests.The composition and function of the intestinal microbiota were analysed using 16S rRNA sequencing,and metabolomic analysis was performed on serum,hippocampus,jejunum and faecal samples.Enzyme-linked immunosorbent assay and hematoxylin and eosin staining were used to detect the levels of inflammatory factors and cortisol,as well as the infiltration of inflammatory cells in the jejunum of rats after cohousing.Long-term potentiation assays and Golgi staining were used to detect dendritic spine density and synaptic plasticity,respectively.Results Paeoniflorin significantly alleviated depression-like behaviours and cognitive deficits in CUMS rats.16S rRNA sequencing revealed that paeoniflorin improved the abundance and diversity of the gut microbiota in CUMS rats.Enrichment of differential metabolites in the brain,intestine,faeces and serum revealed a primary accumulation in the amino acid metabolism pathway.We further observed a correlation between the relative abundance of microbial communities and metabolites.Cohousing experiments verified that microbial metabolites of paeoniflorin can reduce neuroinflammation and improve synaptic plasticity.Conclusions Disruptions in gut microbiota and its metabolites impair gut-brain interactions.Paeoniflorin’s neuroprotective and antidepressant effects are mediated through the modulation of the function of the gut-brain axis.
基金supported by the Zhejiang Medical and Health Science and Technology Project(No.2022KY1055)the Zhejiang Provincial Natural Science Foundation of China(No.LY17H180007)+1 种基金the Key Clinical Specialty Construction Project of Zhejiang Provincethe Key Medical Disciplines of Hangzhou,China.
文摘White-matter tracts play a pivotal role in transmitting sensory and motor information,facilitating interhemispheric communication and integrating different brain regions.Meanwhile,sensorimotor disturbance is a common symptom in patients with major depressive disorder(MDD).However,the role of aberrant sensorimotor white-matter system in MDD remains largely unknown.Herein,we investigated the topological structure alterations of white-matter morphological brain networks in 233 MDD patients versus 257 matched healthy controls(HCs)from the DIRECT consortium.White-matter networks were derived from magnetic resonance imaging(MRI)data by combining voxel-based morphometry(VBM)and three-dimensional discrete wavelet transform(3D-DWT)approaches.Support vector machine(SVM)analysis was performed to discriminate MDD patients from HCs.The results indicated that the network topological changes in node degree,node efficiency,and node betweenness were mainly located in the sensorimotor superficial white-matter system in MDD.Using network nodal topological properties as classification features,the SVM model could effectively distinguish MDD patients from HCs.These findings provide new evidence to highlight the importance of the sensorimotor system in brain mechanisms underlying MDD from a new perspective of white-matter morphological network.
文摘Background Metabolic dysregulation has been implicated in major depressive disorder(MDD).Aims We aimed to explore the potential role of plasma metabolites in MDD.Methods We conducted Mendelian randomisation(MR)analysis to evaluate the causal effects of 871 circulating metabolites on MDD,using the Genome-Wide Association Studies datasets of MDD(N=1035760)and metabolites(N=8299).Bayesian colocalisation and druggability analyses were employed to identify genetic variants contributing to both MDD and levels of metabolites in plasma and to pinpoint metabolites with therapeutic potential,respectively.Results MR analysis identified 11 metabolites associated with MDD(false discovery rate<0.05).Eight metabolites,including arachidonate(20:4n6)(odds ratio(OR):0.97),1-arachidonoyl-GPC(20:4n6)(OR:0.98),1-(1-enylpalmitoyl)-2-palmitoleoyl-GPC(P-16:0/16:1)(OR:0.97),succinoyltaurine(OR:0.98),3-methoxycatechol sulphate(1)(OR:0.98)and 11β-hydroxyandrosterone glucuronide(OR:0.97),showed protective effects against MDD.Three metabolites were associated with increased risk,namely,butyrylglycine(OR:1.03),3-carboxy-4-methyl-5-propyl-2-furanpropanoate(OR:1.02)and 1-(1-enyl-stearoyl)-2-oleoyl-GPE(P-18:0/18:1)(OR:1.02).Colocalisation analysis supported shared genetic signals between five lipid metabolites and MDD,particularly at loci harbouring FADS and ATP9A.Notably,a majority of metabolites associated with MDD are being explored as therapeutic targets for various psychiatric disorders.Conclusions Genetically predicted levels of certain circulating metabolites make a causal contribution to MDD.Further investigation of their roles may provide novel pathophysiological insights and give clues for targeted therapies.
基金supported by the National Natural Science Foundation of China(No.82371530,82171529)the Capital Health Development Special Research Project(2022-1-4111)the National Key Technology R and D Program(No.2015BAI13B01).
文摘Background The patient-reported Dimensional Anhedonia Rating Scale(DARS)has been adapted into Chinese,so there is a need to evaluate its measurement properties in a Chinese population.Aims To evaluate the reliability and validity of the DARS among Chinese individuals with major depressive disorder(MDD)and its treatment sensitivity in a prospective clinical study.Methods Data were from a multicentre,prospective clinical study(NCT03294525),which recruited both patients with MDD,who were followed for 8 weeks,and healthy controls(HCs),assessed at baseline only.The analysis included confirmatory factor analysis,validity and sensitivity to change.Results Patients’mean(standard deviation(SD))age was 34.8(11.0)years,with 68.7%being female.75.2%of patients with MDD had melancholic features,followed by 63.8%with anxious distress.Patients had experienced MDD for a mean(SD)of 9.2(18)months.DARS scores covered the full range of severity with no major floor or ceiling effects.Confirmatory factor analysis showed adequate fit statistics(comparative fit index 0.976,goodness-of-fit index 0.935 and root mean square error of approximation 0.055).Convergent validity with anhedonia-related measures was confirmed.While the correlation between the DARS and the Hamilton Depression Rating Scale was not strong(r=0.31,baseline),the DARS was found to differentiate between levels of depression.Greater improvements in DARS scores were seen with the Hamilton Rating Scale for Depression responder group(effect size 1.16)compared with the non-responder group(effect size 0.46).Conclusions This study comprehensively evaluated the measurement properties of the DARS using a Chinese population with MDD.Overall,the Chinese version of DARS demonstrates good psychometric properties and has been found to be responsive to change during antidepressant treatment.The DARS is a suitable scale for assessing patient-reported anhedonia in future clinical trials.
