Pub Date : 2024-08-01DOI: 10.1101/2024.07.31.24311268
Metin Çınaroğlu, Eda Yılmazer, Zeynep Alpugan, Gökben Hızlı Sayar
The 2023 Kahramanmaraş earthquakes, with magnitudes of 7.7 and 7.6, caused extensive destruction and psychological distress across southeastern Turkey. This study explores the psychological impact on non-victims, particularly Istanbul residents, focusing on mental health outcomes and coping mechanisms. A cross-sectional survey was conducted from March to May 2024 with 721 participants from various Turkish cities, including a significant portion from Istanbul. Validated psychological scales such as the Beck Depression Inventory-II (BDI-II), Beck Anxiety Inventory (BAI), Warwick-Edinburgh Mental Well-being Scale (WEMWBS), and PTSD Checklist for DSM-5 (PCL-5) measured depression, anxiety, well-being, and PTSD symptoms. Sociodemographic factors like age, gender, occupation, income, education level, and previous earthquake experience were also analyzed. Results showed significant psychological distress among non-victims: 51.9% reported high levels of distress, with 24% meeting PTSD criteria, 30% exhibiting moderate to severe depression, and 28% experiencing significant anxiety. Higher income and education levels correlated with better mental health outcomes. Higher education levels were linked to lower PTSD risk (β = -0.20, p < 0.01) and fewer depression symptoms (β = -0.15, p < 0.05). Higher income was associated with lower depression scores (β = -0.20, p < 0.01) and fewer PTSD symptoms (β = -0.15, p < 0.05). Age positively correlated with well-being (r = 0.68, p < 0.001) and negatively with PTSD symptoms (r = -0.15, p < 0.05). Comparisons with victim studies of major earthquakes, such as the 1995 Great Hanshin-Awaji earthquake, the 1999 Marmara earthquake, the 2008 Wenchuan earthquake, and the 2000 Iceland earthquakes, revealed similar profound psychological impacts. This highlights the need for comprehensive mental health interventions for both direct and indirect exposures. This study underscores the necessity for inclusive mental health strategies to enhance resilience and well-being, ensuring robust recovery after catastrophic events.
{"title":"Psychological Impact of the 2023 Kahramanmaraş Earthquakes on Non-Victims","authors":"Metin Çınaroğlu, Eda Yılmazer, Zeynep Alpugan, Gökben Hızlı Sayar","doi":"10.1101/2024.07.31.24311268","DOIUrl":"https://doi.org/10.1101/2024.07.31.24311268","url":null,"abstract":"The 2023 Kahramanmaraş earthquakes, with magnitudes of 7.7 and 7.6, caused extensive destruction and psychological distress across southeastern Turkey. This study explores the psychological impact on non-victims, particularly Istanbul residents, focusing on mental health outcomes and coping mechanisms. A cross-sectional survey was conducted from March to May 2024 with 721 participants from various Turkish cities, including a significant portion from Istanbul. Validated psychological scales such as the Beck Depression Inventory-II (BDI-II), Beck Anxiety Inventory (BAI), Warwick-Edinburgh Mental Well-being Scale (WEMWBS), and PTSD Checklist for DSM-5 (PCL-5) measured depression, anxiety, well-being, and PTSD symptoms. Sociodemographic factors like age, gender, occupation, income, education level, and previous earthquake experience were also analyzed.\u0000Results showed significant psychological distress among non-victims: 51.9% reported high levels of distress, with 24% meeting PTSD criteria, 30% exhibiting moderate to severe depression, and 28% experiencing significant anxiety. Higher income and education levels correlated with better mental health outcomes. Higher education levels were linked to lower PTSD risk (β = -0.20, p < 0.01) and fewer depression symptoms (β = -0.15, p < 0.05). Higher income was associated with lower depression scores (β = -0.20, p < 0.01) and fewer PTSD symptoms (β = -0.15, p < 0.05). Age positively correlated with well-being (r = 0.68, p < 0.001) and negatively with PTSD symptoms (r = -0.15, p < 0.05).\u0000Comparisons with victim studies of major earthquakes, such as the 1995 Great Hanshin-Awaji earthquake, the 1999 Marmara earthquake, the 2008 Wenchuan earthquake, and the 2000 Iceland earthquakes, revealed similar profound psychological impacts. This highlights the need for comprehensive mental health interventions for both direct and indirect exposures. This study underscores the necessity for inclusive mental health strategies to enhance resilience and well-being, ensuring robust recovery after catastrophic events.","PeriodicalId":501388,"journal":{"name":"medRxiv - Psychiatry and Clinical Psychology","volume":"127 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141863979","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.1101/2024.07.30.24311203
Matthew JY Kang, Dhamidhu Eratne, Olivia Dean, Michael Berk, Adam J Walker, Cassandra Wannan, Charles B Malpas, Claudia Cicognola, Shorena Janelidze, Oskar Hansson, Jasleen Grewal, Philip B Mitchell, Malcolm Hopwood, Christos Pantelis, Alexander F Santillo, Dennis Velakoulis
ABSTRACT Importance: Recent methodological developments allow us to measure small amounts of brain-specific proteins in the blood, including neurofilament light chain (NfL), a marker of axonal pathology, and glial fibrillary acidic protein (GFAP), a marker of astrocytic activation. Given the evidence of potential astroglial pathology and neuronal dysfunction in bipolar disorder, these markers may provide further insight into its pathophysiology. Objective: We investigated plasma NfL and GFAP levels in people with bipolar depression and compared them with unaffected individuals. Design, Setting, and Participants: This cross-sectional study included 216 individuals, of which 120 participants had bipolar depression and 96 healthy controls. The blood samples were analysed between November 2023 and April 2024. Main outcomes and measures: We used bootstrapped general linear models (GLM) to compare plasma NfL and GFAP levels between people with bipolar depression and healthy controls, adjusted adjusting for age, sex, and weight. We examined associations between these biomarkers and clinical variables, including mood symptom severity, past psychiatric history, and functioning, adjusting for multiple comparisons. For additional sensitivity analyses, predictors were evaluated using Bayesian model averaging (BMA). Results: GFAP and NfL levels in plasma were elevated in people with bipolar depression (n = 120) compared to healthy controls (n = 96) after adjusting for age, sex and weight. The duration of illness was positively associated with NfL. The BMA analysis also identified duration of illness as a strong predictor of NfL (Posterior Inclusion Probability, PIP = 0.85). Age of onset was positively associated with GFAP. The BMA analysis similarly found age of onset to be a moderately strong predictor (PIP = 0.67). Conclusions and Relevance: This study found elevated levels of plasma NfL and GFAP in bipolar depression compared to unaffected individuals, with significant associations with the duration of illness and age at onset, suggesting a degree of neuronal injury and astrocytic dysfunction in bipolar depression. These biomarkers may reflect specific illness stages, including neuroprogression and the later onset of bipolar disorder.
{"title":"Plasma Glial Fibrillary Acidic Protein and Neurofilament Light are Elevated in Bipolar Disorder: Evidence for Neuroprogression and Astrocytic Activation","authors":"Matthew JY Kang, Dhamidhu Eratne, Olivia Dean, Michael Berk, Adam J Walker, Cassandra Wannan, Charles B Malpas, Claudia Cicognola, Shorena Janelidze, Oskar Hansson, Jasleen Grewal, Philip B Mitchell, Malcolm Hopwood, Christos Pantelis, Alexander F Santillo, Dennis Velakoulis","doi":"10.1101/2024.07.30.24311203","DOIUrl":"https://doi.org/10.1101/2024.07.30.24311203","url":null,"abstract":"ABSTRACT Importance: Recent methodological developments allow us to measure small amounts of brain-specific proteins in the blood, including neurofilament light chain (NfL), a marker of axonal pathology, and glial fibrillary acidic protein (GFAP), a marker of astrocytic activation. Given the evidence of potential astroglial pathology and neuronal dysfunction in bipolar disorder, these markers may provide further insight into its pathophysiology. Objective: We investigated plasma NfL and GFAP levels in people with bipolar depression and compared them with unaffected individuals.\u0000Design, Setting, and Participants: This cross-sectional study included 216 individuals, of which 120 participants had bipolar depression and 96 healthy controls. The blood samples were analysed between November 2023 and April 2024.\u0000Main outcomes and measures: We used bootstrapped general linear models (GLM) to compare plasma NfL and GFAP levels between people with bipolar depression and healthy controls, adjusted adjusting for age, sex, and weight. We examined associations between these biomarkers and clinical variables, including mood symptom severity, past psychiatric history, and functioning, adjusting for multiple comparisons. For additional sensitivity analyses, predictors were evaluated using Bayesian model averaging (BMA).\u0000Results: GFAP and NfL levels in plasma were elevated in people with bipolar depression (n = 120) compared to healthy controls (n = 96) after adjusting for age, sex and weight. The duration of illness was positively associated with NfL. The BMA analysis also identified duration of illness as a strong predictor of NfL (Posterior Inclusion Probability, PIP = 0.85). Age of onset was positively associated with GFAP. The BMA analysis similarly found age of onset to be a moderately strong predictor (PIP = 0.67).\u0000Conclusions and Relevance: This study found elevated levels of plasma NfL and GFAP in bipolar depression compared to unaffected individuals, with significant associations with the duration of illness and age at onset, suggesting a degree of neuronal injury and astrocytic dysfunction in bipolar depression. These biomarkers may reflect specific illness stages, including neuroprogression and the later onset of bipolar disorder.","PeriodicalId":501388,"journal":{"name":"medRxiv - Psychiatry and Clinical Psychology","volume":"74 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141863982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.1101/2024.07.29.24311191
Desmond J Oathes, Almaris Figueroa Gonzalez, Julie Grier, Camille Blaine, Sarai D Garcia, Kristin J Linn
Background: Image-guided brain stimulation is hypothesized to enhance clinical outcomes but head-to-head comparisons favoring image-guidance are so far lacking. Methods: PTSD/MDD patients were randomized (N=51) to a two-condition sequence in a two period cross-over design. For the first condition, patients were randomized to 10-session rTMS treatment to either a subgenual cingulate (sgACC) functional connectivity cortical target (fMRI-guided) or standard scalp-based target. Additionally, patients were randomized to either watch a nature video or perform a demanding cognitive task with rTMS administration. Patients crossed over to the two conditions not received in period one. rTMS was delivered in an intermittent theta burst (iTBS) pattern with 2400 pulses per session. Among N=49 patients analyzed, 60% identified as female and average age was 34. Results: Compared with the scalp-based target, fMRI-guided rTMS was superior in improving depression symptoms (F(1,43.92)=5.933, p=0.019) as well as PTSD hyperarousal (F(1,40.78)=5.076, p=0.030). The median level of symptom change for fMRI-guided targets exceeded 60% improvement across both scales. Symptom improvements at 6-mo follow-up were durable and both favored fMRI-guidance. For patients reporting symptoms at this timepoint, depression improved by 70% (N13); the PCL improved by 69% with Hyperarousal (N14) and Avoidance (N12) subscales improving by 78% and 79%, respectively, for the fMRI-guided target. Conclusions: We demonstrated preliminary evidence for the clinical superiority of a new fMRI-guided target which should be followed up with larger comparative effectiveness studies that include imaging and clinical outcomes.
{"title":"Clinical Response to fMRI-guided Compared to Non-Image Guided rTMS in Depression and PTSD: A Randomized Trial","authors":"Desmond J Oathes, Almaris Figueroa Gonzalez, Julie Grier, Camille Blaine, Sarai D Garcia, Kristin J Linn","doi":"10.1101/2024.07.29.24311191","DOIUrl":"https://doi.org/10.1101/2024.07.29.24311191","url":null,"abstract":"Background: Image-guided brain stimulation is hypothesized to enhance clinical outcomes but head-to-head comparisons favoring image-guidance are so far lacking. Methods: PTSD/MDD patients were randomized (N=51) to a two-condition sequence in a two period cross-over design. For the first condition, patients were randomized to 10-session rTMS treatment to either a subgenual cingulate (sgACC) functional connectivity cortical target (fMRI-guided) or standard scalp-based target. Additionally, patients were randomized to either watch a nature video or perform a demanding cognitive task with rTMS administration. Patients crossed over to the two conditions not received in period one. rTMS was delivered in an intermittent theta burst (iTBS) pattern with 2400 pulses per session. Among N=49 patients analyzed, 60% identified as female and average age was 34. Results: Compared with the scalp-based target, fMRI-guided rTMS was superior in improving depression symptoms (F(1,43.92)=5.933, p=0.019) as well as PTSD hyperarousal (F(1,40.78)=5.076, p=0.030). The median level of symptom change for fMRI-guided targets exceeded 60% improvement across both scales. Symptom improvements at 6-mo follow-up were durable and both favored fMRI-guidance. For patients reporting symptoms at this timepoint, depression improved by 70% (N13); the PCL improved by 69% with Hyperarousal (N14) and Avoidance (N12) subscales improving by 78% and 79%, respectively, for the fMRI-guided target. Conclusions: We demonstrated preliminary evidence for the clinical superiority of a new fMRI-guided target which should be followed up with larger comparative effectiveness studies that include imaging and clinical outcomes.","PeriodicalId":501388,"journal":{"name":"medRxiv - Psychiatry and Clinical Psychology","volume":"28 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141863981","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-31DOI: 10.1101/2024.07.29.24310966
Shi Liu, Yu Qi, Shaohua Hu, Ning Wei, Jianmin Zhang, Junming Zhu, Hemmings Wu, Hailan Hu, Yuxiao Yang, Yueming Wang
Deep brain stimulation (DBS) targeting the lateral habenula (LHb) is a promising therapy for treatment-resistant depression (TRD) but its clinical effect has been variable, which can be improved by adaptive DBS (aDBS) guided by a neural biomarker of depression symptoms. A clinically-viable neural biomarker is desired to classify depression symptom states, track both slow and fast symptom variations during the treatment, and respond to DBS parameter alterations, which is currently lacking. Here, we conducted a study on one TRD patient who achieved remission following a 41-week LHb DBS treatment, during which we assessed slow symptom variations using weekly clinical ratings and fast variations using daily self-reports. We recorded daily LHb local field potentials (LFP) concurrently with the reports during the entire treatment process. We then used machine learning methods to identify a personalized depression neural biomarker from spectral and temporal LFP features. The identified neural biomarker classified high and low depression symptom severity states with a cross-validated accuracy of 0.97. It further simultaneously tracked both weekly (slow) and daily (fast) depression symptom variation dynamics, achieving test data explained variance of 0.74 and 0.63, respectively. It finally responded to DBS frequency alterations. Our results hold promise to identify clinically-viable neural biomarkers to facilitate future aDBS for treating TRD.
{"title":"A Habenula Neural Biomarker Simultaneously Tracks Weekly and Daily Symptom Variations during Deep Brain Stimulation Therapy for Depression","authors":"Shi Liu, Yu Qi, Shaohua Hu, Ning Wei, Jianmin Zhang, Junming Zhu, Hemmings Wu, Hailan Hu, Yuxiao Yang, Yueming Wang","doi":"10.1101/2024.07.29.24310966","DOIUrl":"https://doi.org/10.1101/2024.07.29.24310966","url":null,"abstract":"Deep brain stimulation (DBS) targeting the lateral habenula (LHb) is a promising therapy for treatment-resistant depression (TRD) but its clinical effect has been variable, which can be improved by adaptive DBS (aDBS) guided by a neural biomarker of depression symptoms. A clinically-viable neural biomarker is desired to classify depression symptom states, track both slow and fast symptom variations during the treatment, and respond to DBS parameter alterations, which is currently lacking. Here, we conducted a study on one TRD patient who achieved remission following a 41-week LHb DBS treatment, during which we assessed slow symptom variations using weekly clinical ratings and fast variations using daily self-reports. We recorded daily LHb local field potentials (LFP) concurrently with the reports during the entire treatment process. We then used machine learning methods to identify a personalized depression neural biomarker from spectral and temporal LFP features. The identified neural biomarker classified high and low depression symptom severity states with a cross-validated accuracy of 0.97. It further simultaneously tracked both weekly (slow) and daily (fast) depression symptom variation dynamics, achieving test data explained variance of 0.74 and 0.63, respectively. It finally responded to DBS frequency alterations. Our results hold promise to identify clinically-viable neural biomarkers to facilitate future aDBS for treating TRD.","PeriodicalId":501388,"journal":{"name":"medRxiv - Psychiatry and Clinical Psychology","volume":"49 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141863980","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Background: Traditional neuromodulation strategies for enhancing cognitive abilities in bipolar disorder (BD) patients have shown promise, yet there remains a need for novel intervention modalities to improve therapeutic outcomes. Methods: This study introduces a novel multi-modal neuro-stimulaton (MNS) protocol using individualized DTI data to identify fiber tracts between the DLPFC and dACC. The highest structural connectivity point is selected as the individualized stimulation target, which is targeted using a combination of optimized tACS and robot-assisted navigated rTMS. A double-blind randomized controlled trial (Trial registration number: NCT05964777) was conducted to investigate the clinical efficacy of this innovative neuromodulation approach on cognitive abilities in BD patients. One hundred BD patients were randomly assigned to four groups: Group A (Active tACS-Active rTMS (MNS Protocol)), Group B (Sham tACS-Active rTMS), Group C (Active tACS-Sham rTMS ), and Group D (Sham tACS-Sham rTMS). Participants underwent 15 sessions over three weeks. Cognitive assessments (THINC integrated tool) were conducted at baseline (Week 0), post-treatment (Week 3), and follow-up (Week 8). Results: Sixty-six participants completed all 15 sessions. Group A (MNS Protocol) showed superior improvements in Spotter CRT, TMT, and DSST scores compared to other groups at Week 3, with sustained cognitive enhancement in Spotter CRT at Week 8 (P < 0.01). Only Group A exhibited significant activation in the left frontal region post-MNS intervention. The novel MNS protocol was well tolerated, with no significant side effects observed. Conclusions: DTI-guided multimodal neuro-stimulation mode significantly improves cognitive impairments and is safe for BD patients.
{"title":"Cognitive Enhancement in Bipolar Disorder: A Double-Blind, Randomized Controlled Trial Utilizing a Novel DTI-Guided Multimodal Neuro-stimulation Protocol","authors":"Minmin Wang, Xiaomei Zhang, Hetong Zhou, Qianfeng Chen, Qiqi Tong, Qiai Han, Xudong Zhao, Dandan Wang, Jianbo Lai, Hongjian He, Shaomin Zhang, Shaohua Hu","doi":"10.1101/2024.07.25.24311037","DOIUrl":"https://doi.org/10.1101/2024.07.25.24311037","url":null,"abstract":"Background: Traditional neuromodulation strategies for enhancing cognitive abilities in bipolar disorder (BD) patients have shown promise, yet there remains a need for novel intervention modalities to improve therapeutic outcomes.\u0000Methods: This study introduces a novel multi-modal neuro-stimulaton (MNS) protocol using individualized DTI data to identify fiber tracts between the DLPFC and dACC. The highest structural connectivity point is selected as the individualized stimulation target, which is targeted using a combination of optimized tACS and robot-assisted navigated rTMS. A double-blind randomized controlled trial (Trial registration number: NCT05964777) was conducted to investigate the clinical efficacy of this innovative neuromodulation approach on cognitive abilities in BD patients. One hundred BD patients were randomly assigned to four groups: Group A (Active tACS-Active rTMS (MNS Protocol)), Group B (Sham tACS-Active rTMS), Group C (Active tACS-Sham rTMS ), and Group D (Sham tACS-Sham rTMS). Participants underwent 15 sessions over three weeks. Cognitive assessments (THINC integrated tool) were conducted at baseline (Week 0), post-treatment (Week 3), and follow-up (Week 8).\u0000Results: Sixty-six participants completed all 15 sessions. Group A (MNS Protocol) showed superior improvements in Spotter CRT, TMT, and DSST scores compared to other groups at Week 3, with sustained cognitive enhancement in Spotter CRT at Week 8 (P < 0.01). Only Group A exhibited significant activation in the left frontal region post-MNS intervention. The novel MNS protocol was well tolerated, with no significant side effects observed.\u0000Conclusions: DTI-guided multimodal neuro-stimulation mode significantly improves cognitive impairments and is safe for BD patients.","PeriodicalId":501388,"journal":{"name":"medRxiv - Psychiatry and Clinical Psychology","volume":"51 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141778344","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-27DOI: 10.1101/2024.07.26.24311078
Benney MR Argue, Lucas G Casten, Shaylah McCool, Aysheh Alrfooh, Jenny Gringer Richards, John A Wemmie, Vincent A Magnotta, Aislinn J Williams, Jake J Michaelson, Jess G Fiedorowicz, Sabrina M Scroggins, Marie Elizabeth Gaine
Background: Bipolar disorder is a debilitating mood disorder associated with a high risk of suicide and characterized by immune dysregulation. In this study, we used a multi-faceted approach to better distinguish the pattern of dysregulation of immune profiles in individuals with BD. Methods: We analyzed peripheral blood mononuclear cells (bipolar disorder N=39, control N=30), serum cytokines (bipolar disorder N=86, control N=58), whole blood RNA (bipolar disorder N=25, control N=25), and whole blood DNA (bipolar disorder N=104, control N=66) to identify immune-related differences in participants diagnosed with bipolar disorder compared to controls. Results: Flow cytometry revealed a higher proportion of monocytes in participants with bipolar disorder together with a lower proportion of T helper cells. Additionally, the levels of 18 cytokines were significantly elevated, while two were reduced in participants with bipolar disorder. Most of the cytokines altered in individuals with bipolar disorder were proinflammatory. Forty-nine genes were differentially expressed in our bipolar disorder cohort and further analyses uncovered several immune-related pathways altered in these individuals. Genetic analysis indicated variants associated with inflammatory bowel disease also influences bipolar disorder risk. Discussion: Our findings indicate a significant immune component to bipolar disorder pathophysiology and genetic overlap with inflammatory bowel disease. This comprehensive study supports existing literature, whilst also highlighting novel immune targets altered in individuals with bipolar disorder. Specifically, multiple lines of evidence indicate differences in the peripheral representation of monocytes and T cells are hallmarks of bipolar disorder.
{"title":"Patterns of Immune Dysregulation in Bipolar Disorder","authors":"Benney MR Argue, Lucas G Casten, Shaylah McCool, Aysheh Alrfooh, Jenny Gringer Richards, John A Wemmie, Vincent A Magnotta, Aislinn J Williams, Jake J Michaelson, Jess G Fiedorowicz, Sabrina M Scroggins, Marie Elizabeth Gaine","doi":"10.1101/2024.07.26.24311078","DOIUrl":"https://doi.org/10.1101/2024.07.26.24311078","url":null,"abstract":"Background: Bipolar disorder is a debilitating mood disorder associated with a high risk of suicide and characterized by immune dysregulation. In this study, we used a multi-faceted approach to better distinguish the pattern of dysregulation of immune profiles in individuals with BD. Methods: We analyzed peripheral blood mononuclear cells (bipolar disorder N=39, control N=30), serum cytokines (bipolar disorder N=86, control N=58), whole blood RNA (bipolar disorder N=25, control N=25), and whole blood DNA (bipolar disorder N=104, control N=66) to identify immune-related differences in participants diagnosed with bipolar disorder compared to controls. Results: Flow cytometry revealed a higher proportion of monocytes in participants with bipolar disorder together with a lower proportion of T helper cells. Additionally, the levels of 18 cytokines were significantly elevated, while two were reduced in participants with bipolar disorder. Most of the cytokines altered in individuals with bipolar disorder were proinflammatory. Forty-nine genes were differentially expressed in our bipolar disorder cohort and further analyses uncovered several immune-related pathways altered in these individuals. Genetic analysis indicated variants associated with inflammatory bowel disease also influences bipolar disorder risk.\u0000Discussion: Our findings indicate a significant immune component to bipolar disorder pathophysiology and genetic overlap with inflammatory bowel disease. This comprehensive study supports existing literature, whilst also highlighting novel immune targets altered in individuals with bipolar disorder. Specifically, multiple lines of evidence indicate differences in the peripheral representation of monocytes and T cells are hallmarks of bipolar disorder.","PeriodicalId":501388,"journal":{"name":"medRxiv - Psychiatry and Clinical Psychology","volume":"102 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141778343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-27DOI: 10.1101/2024.07.25.24311024
Michelle Frances Kennedy, Paul Schwenn, Amanda Boyes, Lia Mills, Taliah Prince, Marcella Parker, Daniel F Hermens
Background: Adolescence represents a sensitive developmental period characterised by an increased incidence of emerging mental health symptoms and formal diagnostic onset. These conditions can remain a significant burden throughout life. The Longitudinal Adolescent Brain Study (LABS) commenced in 2018 to track the onset and trajectory of mental health symptoms among general population participants. This research aims to identify polysymptomatic clusters of emerging mental health symptoms in adolescents and examine how these clusters vary by age and change over time, providing insights into the pluripotentiality of disorder development. Methods: LABS participants aged 12-17 years (n=166) completed the Mini International Neuropsychiatric Interview (MINI Kid) approximately every 4 months, with up to 15 timepoints. Due to this high dimensional dataset, the data was first processed using a dimensionality reduction step (uniform manifold approximation and projection; UMAP). Following this, the data was clustered using Bayesian model averaging of k-means, gaussian mixture model and hierarchical clustering to identify distinct symptom clusters. Symptom clusters were described in terms of the original neuropsychiatric interview responses using separate XGBoost classifier models. Symptom cluster dynamics were analysed using Markov chain transition probability matrices and longitudinal analysis. To explore the relationship between symptom clusters and psychological distress and wellbeing, correlational analyses were conducted using scores from the Kessler Psychological Distress Scale (K10) and the COMPAS-W Wellbeing Scale. Outcomes: Six symptom-based clusters (states) were identified: attention, anxiety, depression, manic episode - heritability, anhedonia, and well. Depression and anxiety clusters had the greatest pluripotentiality. Analysis of psychological distress and wellbeing demonstrated an inverse relationship between the states: those with greater psychological distress had more symptoms, conversely those with greater wellbeing had fewer symptoms. Interpretations: Mapping polysymptomatic clusters of mental health symptoms and their pluripotential and transitory trajectories in adolescents enables more effective targeting of preventive interventions. This approach moves beyond categorical classifications to mitigate the progression of early symptoms into enduring psychiatric disorders.
{"title":"Longitudinal Dynamics and Pluripotentiality of Polysymptomatic Clustering in Adolescent Mental Health.","authors":"Michelle Frances Kennedy, Paul Schwenn, Amanda Boyes, Lia Mills, Taliah Prince, Marcella Parker, Daniel F Hermens","doi":"10.1101/2024.07.25.24311024","DOIUrl":"https://doi.org/10.1101/2024.07.25.24311024","url":null,"abstract":"Background: Adolescence represents a sensitive developmental period characterised by an increased incidence of emerging mental health symptoms and formal diagnostic onset. These conditions can remain a significant burden throughout life. The Longitudinal Adolescent Brain Study (LABS) commenced in 2018 to track the onset and trajectory of mental health symptoms among general population participants. This research aims to identify polysymptomatic clusters of emerging mental health symptoms in adolescents and examine how these clusters vary by age and change over time, providing insights into the pluripotentiality of disorder development.\u0000Methods: LABS participants aged 12-17 years (n=166) completed the Mini International Neuropsychiatric Interview (MINI Kid) approximately every 4 months, with up to 15 timepoints. Due to this high dimensional dataset, the data was first processed using a dimensionality reduction step (uniform manifold approximation and projection; UMAP). Following this, the data was clustered using Bayesian model averaging of k-means, gaussian mixture model and hierarchical clustering to identify distinct symptom clusters. Symptom clusters were described in terms of the original neuropsychiatric interview responses using separate XGBoost classifier models. Symptom cluster dynamics were analysed using Markov chain transition probability matrices and longitudinal analysis. To explore the relationship between symptom clusters and psychological distress and wellbeing, correlational analyses were conducted using scores from the Kessler Psychological Distress Scale (K10) and the COMPAS-W Wellbeing Scale.\u0000Outcomes: Six symptom-based clusters (states) were identified: attention, anxiety, depression, manic episode - heritability, anhedonia, and well. Depression and anxiety clusters had the greatest pluripotentiality. Analysis of psychological distress and wellbeing demonstrated an inverse relationship between the states: those with greater psychological distress had more symptoms, conversely those with greater wellbeing had fewer symptoms.\u0000Interpretations: Mapping polysymptomatic clusters of mental health symptoms and their pluripotential and transitory trajectories in adolescents enables more effective targeting of preventive interventions. This approach moves beyond categorical classifications to mitigate the progression of early symptoms into enduring psychiatric disorders.","PeriodicalId":501388,"journal":{"name":"medRxiv - Psychiatry and Clinical Psychology","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141778205","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-26DOI: 10.1101/2024.07.25.24310985
Claudio Crema, Alberto Boccali, Alessandra Martinelli, Silvia De Francesco, Serena Meloni, Cesare Michele Baronio, laura Pedrini, Mariangela Lanfredi, Damiano Archetti, Alberto Redolfi, Roberta Rossi
Borderline Personality Disorder (BPD) is a complex mental condition. Individuals with BPD have an average of three lifetime suicide attempts, and 10% of them die by suicide. Understanding risk factors linked to suicidal behaviors is crucial for effective intervention strategies. In recent years, machine learning (ML) approaches for predicting suicide risk in persons with mental disorders have been developed, but a reliable, BPD-specific tool is lacking. In this work, we developed DRAMA-BPD (Detecting Risk factors for suicide Attempts with Machine learning Approaches in Borderline Personality Disorder), a second-opinion tool to assess suicide risk in individuals with BPD. DRAMA-BPD, built upon a Support Vector Machine (SVM) classifier, is trained on the CLIMAMITHE (CLM) dataset, which encompasses sociodemographic, clinical, emotional assessments, and MRI data. Feature selection revealed that 6 out of the 7 most important features are MRI-derived, and a comprehensive review was conducted to ensure consistency with existing scientific literature. The classifier achieved an overall Area Under the Curve (AUC) of 0.73, Precision (P) of 0.75, Recall (R) of 0.70, and F1-score of 0.72. Tests were conducted on the independent SUDMEX_CONN dataset, yielding an AUC of 0.59, P of 0.46, R of 0.92, and F1 of 0.62. While there is a significant imbalance between Precision and Recall, these results demonstrate the potential utility of the proposed model.
{"title":"Suicide Risk in Borderline Personality Disorder: a Machine Learning Tool based on Clinical and MRI Data","authors":"Claudio Crema, Alberto Boccali, Alessandra Martinelli, Silvia De Francesco, Serena Meloni, Cesare Michele Baronio, laura Pedrini, Mariangela Lanfredi, Damiano Archetti, Alberto Redolfi, Roberta Rossi","doi":"10.1101/2024.07.25.24310985","DOIUrl":"https://doi.org/10.1101/2024.07.25.24310985","url":null,"abstract":"Borderline Personality Disorder (BPD) is a complex mental condition. Individuals with BPD have an average of three lifetime suicide attempts, and 10% of them die by suicide. Understanding risk factors linked to suicidal behaviors is crucial for effective intervention strategies. In recent years, machine learning (ML) approaches for predicting suicide risk in persons with mental disorders have been developed, but a reliable, BPD-specific tool is lacking. In this work, we developed DRAMA-BPD (Detecting Risk factors for suicide Attempts with Machine learning Approaches in Borderline Personality Disorder), a second-opinion tool to assess suicide risk in individuals with BPD. DRAMA-BPD, built upon a Support Vector Machine (SVM) classifier, is trained on the CLIMAMITHE (CLM) dataset, which encompasses sociodemographic, clinical, emotional assessments, and MRI data. Feature selection revealed that 6 out of the 7 most important features are MRI-derived, and a comprehensive review was conducted to ensure consistency with existing scientific literature. The classifier achieved an overall Area Under the Curve (AUC) of 0.73, Precision (P) of 0.75, Recall (R) of 0.70, and F1-score of 0.72. Tests were conducted on the independent SUDMEX_CONN dataset, yielding an AUC of 0.59, P of 0.46, R of 0.92, and F1 of 0.62. While there is a significant imbalance between Precision and Recall, these results demonstrate the potential utility of the proposed model.","PeriodicalId":501388,"journal":{"name":"medRxiv - Psychiatry and Clinical Psychology","volume":"23 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141778345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-25DOI: 10.1101/2024.07.25.24310972
Kelly Fleetwood, Raied Alotaibi, Stine H Scheuer, Daniel J Smith, Sarah H Wild, Caroline A Jackson
Objective To determine time-trends in life expectancy (LE) of people with a severe mental illness (SMI) compared with the general population. Design Observational population-based study. Setting Scotland, 2000-2019. Linked psychiatric hospital admission and death records. Participants Adults with a psychiatric hospital admission record for schizophrenia (28,797), bipolar disorder (16,657) or major depression (72,504) compared with the Scottish population (4.3 million adults in 2011). Main outcome measures Trends over time in life years lost for people with schizophrenia, bipolar disorder or major depression compared with the Scottish population, for all deaths, and natural and unnatural deaths, stratified by sex. Results Among people with SMI, one third died during the study period. Between 2000 and 2019, LE increased in the general Scottish population and the LE gap widened for people with schizophrenia. For 2000-2002, men and women with schizophrenia lost an excess 9.4 (95% CI 8.5 to 10.3) and 8.2 (7.4 to 9.0) life years, respectively, compared to the general population. In 2017-2019, this excess life years lost increased to 11.8 (10.9 to 12.7) and 11.1 (10.0 to 12.1) for men and women, respectively. There was no evidence of a change over time in the LE gap of 5 to 8 years for people with bipolar disorder or major depression. Changes in LE for natural and unnatural causes of death varied by individual SMI and sex. Conclusions The LE gap in people with an SMI persisted or widened in Scotland from 2000-2019. These entrenched disparities reflect intersecting inequalities requiring coordinated solutions at multiple levels to improve LE in this and other marginalised and socially excluded groups.
{"title":"Time-trends in life expectancy of people with severe mental illness in Scotland, 2000-2019: a population-based study","authors":"Kelly Fleetwood, Raied Alotaibi, Stine H Scheuer, Daniel J Smith, Sarah H Wild, Caroline A Jackson","doi":"10.1101/2024.07.25.24310972","DOIUrl":"https://doi.org/10.1101/2024.07.25.24310972","url":null,"abstract":"Objective To determine time-trends in life expectancy (LE) of people with a severe mental illness (SMI) compared with the general population. Design Observational population-based study. Setting Scotland, 2000-2019. Linked psychiatric hospital admission and death records. Participants Adults with a psychiatric hospital admission record for schizophrenia (28,797), bipolar disorder (16,657) or major depression (72,504) compared with the Scottish population (4.3 million adults in 2011). Main outcome measures Trends over time in life years lost for people with schizophrenia, bipolar disorder or major depression compared with the Scottish population, for all deaths, and natural and unnatural deaths, stratified by sex. Results Among people with SMI, one third died during the study period. Between 2000 and 2019, LE increased in the general Scottish population and the LE gap widened for people with schizophrenia. For 2000-2002, men and women with schizophrenia lost an excess 9.4 (95% CI 8.5 to 10.3) and 8.2 (7.4 to 9.0) life years, respectively, compared to the general population. In 2017-2019, this excess life years lost increased to 11.8 (10.9 to 12.7) and 11.1 (10.0 to 12.1) for men and women, respectively. There was no evidence of a change over time in the LE gap of 5 to 8 years for people with bipolar disorder or major depression. Changes in LE for natural and unnatural causes of death varied by individual SMI and sex. Conclusions The LE gap in people with an SMI persisted or widened in Scotland from 2000-2019. These entrenched disparities reflect intersecting inequalities requiring coordinated solutions at multiple levels to improve LE in this and other marginalised and socially excluded groups.","PeriodicalId":501388,"journal":{"name":"medRxiv - Psychiatry and Clinical Psychology","volume":"62 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141778346","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-25DOI: 10.1101/2024.07.25.24310979
Maura MacPhee, Jo Howe, Hafsah Habib, Emilia Piwowarczyk, Geoff Wong, Amy Ahern, Gurkiran Birdi, Suzanne Higgs, Sheri Oduola, Alex Kenny, Annabel Walsh, Rachel Upthegrove, Katherine Allen, Max Carlish, Justine Lovell, Ian Maidment
Abstract Introduction Antipsychotic medications are used to treat individuals with severe mental illness. These medications are associated with rapid weight gain and several physical and mental risk factors. Early, proactive weight management is necessary to pre-empt these risk factors. Methods A realist review was conducted to identify contextual factors and underlying mechanisms associated with effective, non-pharmacological weight management interventions for this population. A stakeholder group of practitioners and a stakeholder group of individuals with lived experience and their family carers were integral to the review process. Results The realist review consisted of 58 documents where 41 papers were intervention studies of non-pharmacological weight management interventions for individuals with severe mental illness. Weight management interventions typically included nutrition counseling, physical activity and behaviour therapies offered over different time ranges by combinations of facilitators. Follow-up was rarely reported, and these intervention studies yielded mixed outcomes for weight loss/weight gain prevention, decreased clinical risk indicators and improved physical and mental health. Review documents and stakeholder discussions were used to construct a programme theory and 12 testable context-mechanism-outcome configurations. Review findings emphasise the significant effect of stigma/double stigma on individuals with severe mental illness and weight gain. Therapeutic practitioner relationships, family and peer support contribute to individuals' engagement with healthy behaviours. Conclusions Multi-country non-pharmacological interventions for weight management have had mixed results. This realist review identified characteristics and potential mechanisms that may make a significant, positive difference to individuals with severe mental illness. A realist evaluation with primary data is currently underway.
{"title":"REalist Synthesis Of non-pharmacologicaL interVEntions for antipsychotic-induced weight gain (RESOLVE) in people living with severe mental illness","authors":"Maura MacPhee, Jo Howe, Hafsah Habib, Emilia Piwowarczyk, Geoff Wong, Amy Ahern, Gurkiran Birdi, Suzanne Higgs, Sheri Oduola, Alex Kenny, Annabel Walsh, Rachel Upthegrove, Katherine Allen, Max Carlish, Justine Lovell, Ian Maidment","doi":"10.1101/2024.07.25.24310979","DOIUrl":"https://doi.org/10.1101/2024.07.25.24310979","url":null,"abstract":"Abstract Introduction Antipsychotic medications are used to treat individuals with severe mental illness. These medications are associated with rapid weight gain and several physical and mental risk factors. Early, proactive weight management is necessary to pre-empt these risk factors. Methods A realist review was conducted to identify contextual factors and underlying mechanisms associated with effective, non-pharmacological weight management interventions for this population. A stakeholder group of practitioners and a stakeholder group of individuals with lived experience and their family carers were integral to the review process. Results The realist review consisted of 58 documents where 41 papers were intervention studies of non-pharmacological weight management interventions for individuals with severe mental illness. Weight management interventions typically included nutrition counseling, physical activity and behaviour therapies offered over different time ranges by combinations of facilitators. Follow-up was rarely reported, and these intervention studies yielded mixed outcomes for weight loss/weight gain prevention, decreased clinical risk indicators and improved physical and mental health. Review documents and stakeholder discussions were used to construct a programme theory and 12 testable context-mechanism-outcome configurations. Review findings emphasise the significant effect of stigma/double stigma on individuals with severe mental illness and weight gain. Therapeutic practitioner relationships, family and peer support contribute to individuals' engagement with healthy behaviours. Conclusions Multi-country non-pharmacological interventions for weight management have had mixed results. This realist review identified characteristics and potential mechanisms that may make a significant, positive difference to individuals with severe mental illness. A realist evaluation with primary data is currently underway.","PeriodicalId":501388,"journal":{"name":"medRxiv - Psychiatry and Clinical Psychology","volume":"25 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141778347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：