Browsing by Subject "Major depressive disorder"
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Item Characterizing Heterogeneity in Neuroimaging, Cognition, Clinical Symptoms, and Genetics Among Patients With Late-Life Depression(American Medical Association, 2022) Wen, Junhao; Fu, Cynthia H. Y.; Tosun, Duygu; Veturi, Yogasudha; Yang, Zhijian; Abdulkadir, Ahmed; Mamourian, Elizabeth; Srinivasan, Dhivya; Skampardoni, Ioanna; Singh, Ashish; Nawani, Hema; Bao, Jingxuan; Erus, Guray; Shou, Haochang; Habes, Mohamad; Doshi, Jimit; Varol, Erdem; Mackin, R. Scott; Sotiras, Aristeidis; Fan, Yong; Saykin, Andrew J.; Sheline, Yvette I.; Shen, Li; Ritchie, Marylyn D.; Wolk, David A.; Albert, Marilyn; Resnick, Susan M.; Davatzikos, Christos; iSTAGING consortium; ADNI; BIOCARD; BLSA; Radiology and Imaging Sciences, School of MedicineImportance: Late-life depression (LLD) is characterized by considerable heterogeneity in clinical manifestation. Unraveling such heterogeneity might aid in elucidating etiological mechanisms and support precision and individualized medicine. Objective: To cross-sectionally and longitudinally delineate disease-related heterogeneity in LLD associated with neuroanatomy, cognitive functioning, clinical symptoms, and genetic profiles. Design, setting, and participants: The Imaging-Based Coordinate System for Aging and Neurodegenerative Diseases (iSTAGING) study is an international multicenter consortium investigating brain aging in pooled and harmonized data from 13 studies with more than 35 000 participants, including a subset of individuals with major depressive disorder. Multimodal data from a multicenter sample (N = 996), including neuroimaging, neurocognitive assessments, and genetics, were analyzed in this study. A semisupervised clustering method (heterogeneity through discriminative analysis) was applied to regional gray matter (GM) brain volumes to derive dimensional representations. Data were collected from July 2017 to July 2020 and analyzed from July 2020 to December 2021. Main outcomes and measures: Two dimensions were identified to delineate LLD-associated heterogeneity in voxelwise GM maps, white matter (WM) fractional anisotropy, neurocognitive functioning, clinical phenotype, and genetics. Results: A total of 501 participants with LLD (mean [SD] age, 67.39 [5.56] years; 332 women) and 495 healthy control individuals (mean [SD] age, 66.53 [5.16] years; 333 women) were included. Patients in dimension 1 demonstrated relatively preserved brain anatomy without WM disruptions relative to healthy control individuals. In contrast, patients in dimension 2 showed widespread brain atrophy and WM integrity disruptions, along with cognitive impairment and higher depression severity. Moreover, 1 de novo independent genetic variant (rs13120336; chromosome: 4, 186387714; minor allele, G) was significantly associated with dimension 1 (odds ratio, 2.35; SE, 0.15; P = 3.14 ×108) but not with dimension 2. The 2 dimensions demonstrated significant single-nucleotide variant-based heritability of 18% to 27% within the general population (N = 12 518 in UK Biobank). In a subset of individuals having longitudinal measurements, those in dimension 2 experienced a more rapid longitudinal change in GM and brain age (Cohen f2 = 0.03; P = .02) and were more likely to progress to Alzheimer disease (Cohen f2 = 0.03; P = .03) compared with those in dimension 1 (N = 1431 participants and 7224 scans from the Alzheimer's Disease Neuroimaging Initiative [ADNI], Baltimore Longitudinal Study of Aging [BLSA], and Biomarkers for Older Controls at Risk for Dementia [BIOCARD] data sets). Conclusions and relevance: This study characterized heterogeneity in LLD into 2 dimensions with distinct neuroanatomical, cognitive, clinical, and genetic profiles. This dimensional approach provides a potential mechanism for investigating the heterogeneity of LLD and the relevance of the latent dimensions to possible disease mechanisms, clinical outcomes, and responses to interventions.Item Collaborative meta-analysis finds no evidence of a strong interaction between stress and 5-HTTLPR genotype contributing to the development of depression(Nature Publishing Group, 2018-01) Culverhouse, Robert C.; Saccone, Nancy L.; Horton, Amy C.; Ma, Yinjiao; Anstey, Kaarin J.; Banaschewski, Tobias; Burmeister, Margit; Cohen-Woods, Sarah; Etain, Bruno; Fisher, Helen L.; Goldman, Noreen; Guillaume, Sébastien; Horwood, John; Juhasz, Gabriella; Lester, Kathryn J.; Mandelli, Laura; Middeldorp, Christel M.; Olié, Emilie; Villafuerte, Sandra; Air, Tracy M.; Araya, Ricardo; Bowes, Lucy; Burns, Richard; Byrne, Enda M.; Coffey, Carolyn; Coventry, William L.; Gawronski, Katerina; Glei, Dana; Hatzimanolis, Alex; Hottenga, Jouke-Jan; Jaussent, Isabelle; Jawahar, Catharine; Jennen-Steinmetz, Christine; Kramer, John R.; Lajnef, Mohamed; Little, Keriann; zu Schwabedissen, Henriette Meyer; Nauck, Matthias; Nederhof, Esther; Petschner, Peter; Peyrot, Wouter J.; Schwahn, Christian; Sinnamon, Grant; Stacey, David; Tian, Yan; Toben, Catherine; Auwera, Sandra Van der; Wainwright, Nick; Wang, Jen-Chyong; Willemsen, Gonneke; Anderson, Ian M.; Arolt, Volker; Åslund, Cecilia; Bagdy, Gyorgy; Baune, Bernhard T.; Bellivier, Frank; Boomsma, Dorret I.; Courtet, Philippe; Dannlowski, Udo; de Geus, Eco J.C.; Deakin, John F. W.; Easteal, Simon; Eley, Thalia; Fergusson, David M.; Goate, Alison M.; Gonda, Xenia; Grabe, Hans J.; Holzman, Claudia; Johnson, Eric O.; Kennedy, Martin; Laucht, Manfred; Martin, Nicholas G.; Munafò, Marcus; Nilsson, Kent W.; Oldehinkel, Albertine J.; Olsson, Craig; Ormel, Johan; Otte, Christian; Patton, George C.; Penninx, Brenda W.J.H.; Ritchie, Karen; Sarchiapone, Marco; Scheid, JM; Serretti, Alessandro; Smit, Johannes H.; Stefanis, Nicholas C.; Surtees, Paul G.; Völzke, Henry; Weinstein, Maxine; Whooley, Mary; Nurnberger, John I., Jr.; Breslau, Naomi; Bierut, Laura J.; Psychiatry, School of MedicineThe hypothesis that the S allele of the 5-HTTLPR serotonin transporter promoter region is associated with increased risk of depression, but only in individuals exposed to stressful situations, has generated much interest, research, and controversy since first proposed in 2003. Multiple meta-analyses combining results from heterogeneous analyses have not settled the issue. To determine the magnitude of the interaction and the conditions under which it might be observed, we performed new analyses on 31 datasets containing 38 802 European-ancestry subjects genotyped for 5-HTTLPR and assessed for depression and childhood maltreatment or other stressful life events, and meta-analyzed the results. Analyses targeted two stressors (narrow, broad) and two depression outcomes (current, lifetime). All groups that published on this topic prior to the initiation of our study and met the assessment and sample size criteria were invited to participate. Additional groups, identified by consortium members or self-identified in response to our protocol (published prior to the start of analysis1) with qualifying unpublished data were also invited to participate. A uniform data analysis script implementing the protocol was executed by each of the consortium members. Our findings do not support the interaction hypothesis. We found no subgroups or variable definitions for which an interaction between stress and 5-HTTLPR genotype was statistically significant. In contrast, our findings for the main effects of life stressors (strong risk factor) and 5-HTTLPR genotype (no impact on risk) are strikingly consistent across our contributing studies, the original study reporting the interaction, and subsequent meta-analyses. Our conclusion is that if an interaction exists in which the S allele of 5-HTTLPR increases risk of depression only in stressed individuals, then it is not broadly generalizable, but must be of modest effect size and only observable in limited situations.Item Development and Validation of a Model to Predict Posttraumatic Stress Disorder and Major Depression After a Motor Vehicle Collision(American Medical Association, 2021) Ziobrowski, Hannah N.; Kennedy, Chris J.; Ustun, Berk; House, Stacey L.; Beaudoin, Francesca L.; An, Xinming; Zeng, Donglin; Bollen, Kenneth A.; Petukhova, Maria; Sampson, Nancy A.; Puac-Polanco, Victor; Lee, Sue; Koenen, Karestan C.; Ressler, Kerry J.; McLean, Samuel A.; Kessler, Ronald C.; AURORA Consortium; Stevens, Jennifer S.; Neylan, Thomas C.; Clifford, Gari D.; Jovanovic, Tanja; Linnstaedt, Sarah D.; Germine, Laura T.; Rauch, Scott L.; Haran, John P.; Storrow, Alan B.; Lewandowski, Christopher; Musey, Paul I., Jr.; Hendry, Phyllis L.; Sheikh, Sophia; Jones, Christopher W.; Punches, Brittany E.; Lyons, Michael S.; Murty, Vishnu P.; McGrath, Meghan E.; Pascual, Jose L.; Seamon, Mark J.; Datner, Elizabeth M.; Chang, Anna M.; Pearson, Claire; Peak, David A.; Jambaulikar, Guruprasad; Merchant, Roland C.; Domeier, Robert M.; Rathlev, Niels K.; O'Neil, Brian J.; Sergot, Paulina; Sanchez, Leon D.; Bruce, Steven E.; Pietrzak, Robert H.; Joormann, Jutta; Barch, Deanna M.; Pizzagalli, Diego A.; Sheridan, John F.; Harte, Steven E.; Elliott, James M.; van Rooij, Sanne J.H.; Emergency Medicine, School of MedicineImportance: A substantial proportion of the 40 million people in the US who present to emergency departments (EDs) each year after traumatic events develop posttraumatic stress disorder (PTSD) or major depressive episode (MDE). Accurately identifying patients at high risk in the ED would facilitate the targeting of preventive interventions. Objectives: To develop and validate a prediction tool based on ED reports after a motor vehicle collision to predict PTSD or MDE 3 months later. Design, setting, and participants: The Advancing Understanding of Recovery After Trauma (AURORA) study is a longitudinal study that examined adverse posttraumatic neuropsychiatric sequalae among patients who presented to 28 US urban EDs in the immediate aftermath of a traumatic experience. Enrollment began on September 25, 2017. The 1003 patients considered in this diagnostic/prognostic report completed 3-month assessments by January 31, 2020. Each patient received a baseline ED assessment along with follow-up self-report surveys 2 weeks, 8 weeks, and 3 months later. An ensemble machine learning method was used to predict 3-month PTSD or MDE from baseline information. Data analysis was performed from November 1, 2020, to May 31, 2021. Main outcomes and measures: The PTSD Checklist for DSM-5 was used to assess PTSD and the Patient Reported Outcomes Measurement Information System Depression Short-Form 8b to assess MDE. Results: A total of 1003 patients (median [interquartile range] age, 34.5 [24-43] years; 715 [weighted 67.9%] female; 100 [weighted 10.7%] Hispanic, 537 [weighted 52.7%] non-Hispanic Black, 324 [weighted 32.2%] non-Hispanic White, and 42 [weighted 4.4%] of non-Hispanic other race or ethnicity were included in this study. A total of 274 patients (weighted 26.6%) met criteria for 3-month PTSD or MDE. An ensemble machine learning model restricted to 30 predictors estimated in a training sample (patients from the Northeast or Midwest) had good prediction accuracy (mean [SE] area under the curve [AUC], 0.815 [0.031]) and calibration (mean [SE] integrated calibration index, 0.040 [0.002]; mean [SE] expected calibration error, 0.039 [0.002]) in an independent test sample (patients from the South). Patients in the top 30% of predicted risk accounted for 65% of all 3-month PTSD or MDE, with a mean (SE) positive predictive value of 58.2% (6.4%) among these patients at high risk. The model had good consistency across regions of the country in terms of both AUC (mean [SE], 0.789 [0.025] using the Northeast as the test sample and 0.809 [0.023] using the Midwest as the test sample) and calibration (mean [SE] integrated calibration index, 0.048 [0.003] using the Northeast as the test sample and 0.024 [0.001] using the Midwest as the test sample; mean [SE] expected calibration error, 0.034 [0.003] using the Northeast as the test sample and 0.025 [0.001] using the Midwest as the test sample). The most important predictors in terms of Shapley Additive Explanations values were symptoms of anxiety sensitivity and depressive disposition, psychological distress in the 30 days before motor vehicle collision, and peritraumatic psychosomatic symptoms. Conclusions and relevance: The results of this study suggest that a short set of questions feasible to administer in an ED can predict 3-month PTSD or MDE with good AUC, calibration, and geographic consistency. Patients at high risk can be identified in the ED for targeting if cost-effective preventive interventions are developed.Item Genetic and environment effects on structural neuroimaging endophenotype for bipolar disorder: a novel molecular approach(Springer Nature, 2022-04-04) Hu, Bo; Cha, Jungwon; Fullerton, Janice M.; Hesam-Shariati, Sonia; Nakamura, Kunio; Nurnberger, John I.; Anand, Amit; Psychiatry, School of MedicineWe investigated gene-environment effects on structural brain endophenotype in bipolar disorder (BD) using a novel method of combining polygenic risk scores with epigenetic signatures since traditional methods of examining the family history and trauma effects have significant limitations. The study enrolled 119 subjects, including 55 BD spectrum (BDS) subjects diagnosed with BD or major depressive disorder (MDD) with subthreshold BD symptoms and 64 non-BDS subjects comprising 32 MDD subjects without BD symptoms and 32 healthy subjects. The blood samples underwent genome-wide genotyping and methylation quantification. We derived polygenic risk score (PRS) and methylation profile score (MPS) as weighted summations of risk single nucleotide polymorphisms and methylation probes, respectively, which were considered as molecular measures of genetic and environmental risks for BD. Linear regression was used to relate PRS, MPS, and their interaction to 44 brain structure measures quantified from magnetic resonance imaging (MRI) on 47 BDS subjects, and the results were compared with those based on family history and childhood trauma. After multiplicity corrections using false discovery rate (FDR), MPS was found to be negatively associated with the volume of the medial geniculate thalamus (FDR = 0.059, partial R2 = 0.208). Family history, trauma scale, and PRS were not associated with any brain measures. PRS and MPS show significant interactions on whole putamen (FDR = 0.09, partial R2 = 0.337). No significant gene-environment interactions were identified for the family history and trauma scale. PRS and MPS generally explained greater proportions of variances of the brain measures (range of partial R2 = [0.008, 0.337]) than the clinical risk factors (range = [0.004, 0.228]).Item Interplay of Metabolome and Gut Microbiome in Individuals With Major Depressive Disorder vs Control Individuals(American Medical Association, 2023) Amin, Najaf; Liu, Jun; Bonnechere, Bruno; MahmoudianDehkordi, Siamak; Arnold, Matthias; Batra, Richa; Chiou, Yu-Jie; Fernandes, Marco; Ikram, M. Arfan; Kraaij, Robert; Krumsiek, Jan; Newby, Danielle; Nho, Kwangsik; Radjabzadeh, Djawad; Saykin, Andrew J.; Shi, Liu; Sproviero, William; Winchester, Laura; Yang, Yang; Nevado-Holgado, Alejo J.; Kastenmüller, Gabi; Kaddurah-Daouk, Rima; van Duijn, Cornelia M.; Radiology and Imaging Sciences, School of MedicineImportance: Metabolomics reflect the net effect of genetic and environmental influences and thus provide a comprehensive approach to evaluating the pathogenesis of complex diseases, such as depression. Objective: To identify the metabolic signatures of major depressive disorder (MDD), elucidate the direction of associations using mendelian randomization, and evaluate the interplay of the human gut microbiome and metabolome in the development of MDD. Design, setting and participants: This cohort study used data from participants in the UK Biobank cohort (n = 500 000; aged 37 to 73 years; recruited from 2006 to 2010) whose blood was profiled for metabolomics. Replication was sought in the PREDICT and BBMRI-NL studies. Publicly available summary statistics from a 2019 genome-wide association study of depression were used for the mendelian randomization (individuals with MDD = 59 851; control individuals = 113 154). Summary statistics for the metabolites were obtained from OpenGWAS in MRbase (n = 118 000). To evaluate the interplay of the metabolome and the gut microbiome in the pathogenesis of depression, metabolic signatures of the gut microbiome were obtained from a 2019 study performed in Dutch cohorts. Data were analyzed from March to December 2021. Main outcomes and measures: Outcomes were lifetime and recurrent MDD, with 249 metabolites profiled with nuclear magnetic resonance spectroscopy with the Nightingale platform. Results: The study included 6811 individuals with lifetime MDD compared with 51 446 control individuals and 4370 individuals with recurrent MDD compared with 62 508 control individuals. Individuals with lifetime MDD were younger (median [IQR] age, 56 [49-62] years vs 58 [51-64] years) and more often female (4447 [65%] vs 2364 [35%]) than control individuals. Metabolic signatures of MDD consisted of 124 metabolites spanning the energy and lipid metabolism pathways. Novel findings included 49 metabolites, including those involved in the tricarboxylic acid cycle (ie, citrate and pyruvate). Citrate was significantly decreased (β [SE], -0.07 [0.02]; FDR = 4 × 10-04) and pyruvate was significantly increased (β [SE], 0.04 [0.02]; FDR = 0.02) in individuals with MDD. Changes observed in these metabolites, particularly lipoproteins, were consistent with the differential composition of gut microbiota belonging to the order Clostridiales and the phyla Proteobacteria/Pseudomonadota and Bacteroidetes/Bacteroidota. Mendelian randomization suggested that fatty acids and intermediate and very large density lipoproteins changed in association with the disease process but high-density lipoproteins and the metabolites in the tricarboxylic acid cycle did not. Conclusions and relevance: The study findings showed that energy metabolism was disturbed in individuals with MDD and that the interplay of the gut microbiome and blood metabolome may play a role in lipid metabolism in individuals with MDD.Item Moderators of the association between depressive, manic, and mixed mood symptoms and suicidal ideation and behavior: An analysis of the National Network of Depression Centers Mood Outcomes Program(Elsevier, 2021) Fiedorowicz, Jess G.; Persons, Jane E.; Assari, Shervin; Ostacher, Michael J.; Goes, Fernando S.; Nurnberger, John I.; Coryell, William H.; Psychiatry, School of MedicineBackground: It has not been established that suicide risk with mixed symptoms is any greater than the depressive component or if there is synergy between depressive and manic symptoms in conveying suicide risk. Methods: The National Network of Depression Centers Mood Outcomes Program collected data from measurement-based care for 17,179 visits from 6,105 unique individuals with clinically diagnosed mood disorders (998 bipolar disorder, 5,117 major depression). The Patient Health Questionaire-8 (PHQ-8) captured depressive symptoms and the Altman Self-Rating Mania scale (ASRM) measured hypomanic/manic symptoms. Generalized linear mixed models assessed associations between depressive symptoms, manic symptoms, and their interaction (to test for synergistic effects of mixed symptoms) on the primary outcome of suicidal ideation or behavior (secondarily suicidal behavior only) from the Columbia-Suicide Severity Rating Scale (C-SSRS). Moderation was assessed. Results: PHQ-8 scores were strongly associated with suicide-related outcomes across diagnoses. ASRM scores showed no association with suicidal ideation/behavior in bipolar disorder and an inverse association in major depression. There was no evidence of synergy between depressive and manic symptoms. There was no moderation by sex, race, or mood disorder polarity. Those over 55 years of age showed a protective effect of manic symptoms, which was lost when depressive symptoms were also present (mixed symptoms). Discussion: Mixed depressive and manic symptoms convey no excess risk of suicidal ideation or behavior beyond the risk conveyed by the depressive symptoms alone. Depressive symptoms are strongly linked to suicidal ideation and suicidal behavior and represent an important and potentially modifiable risk factor for suicide.Item Narrative Analyses: Cognitive Behavior Group Therapy for Women with Menopause and Bipolar or Major Depressive Disorders(Mary Ann Liebert, 2021-09-22) Conklin, Danette; Carpenter, Janet S.; Sorenson Whitney, Meredith; DeLozier, Sarah; Ogede, Daisy Okwa; Bazella, Corinne; McVoy, Molly; Sajatovic, Martha; School of NursingBackground: Bipolar and depressive disorders (bipolar disorder [BD], major depressive disorder [MDD]), as well as menopause affect millions of women. Although there are three known cognitive behavioral group treatment (CBGT) protocols to help women with problematic menopause symptoms, they do not target women on the BD or MDD spectrum. The purpose of this qualitative study was to learn more about the treatment needs and group experiences of women with problematic menopause symptoms and diagnosed on the BD and MDD spectrum, who participated in a CBGT intervention for menopausal symptoms. Methods: Narrative data recorded by clinicians (Interventionists' notes) and participants (Evaluation of Groups Survey) were analyzed using content analyses. Results: Several themes emerged from (n = 11 BD; n = 48 MDD) what women wanted help with (specific symptoms and general aspects of menopause), what women liked about CBGT (specific and general aspects of the program), and changes needed in the CBGT intervention (things wished for and barriers that interfered with the program). The two diagnostic groups differed in their responses, although both groups identified content and delivery gaps they wished would be addressed. Specifically related to their diagnosis, women most commonly talked about problems with worsening mood and mood instability and multiple stressors interfering with their ability to follow through with the intervention. Conclusions: These findings can help refine existing CBGT protocols for women diagnosed on the BD and MDD spectrum seeking help for menopause symptoms.Item (R)-(-)-Ketamine: The Promise of a Novel Treatment for Psychiatric and Neurological Disorders(MDPI, 2024-06-20) Shafique, Hana; Demers, Julie C.; Biesiada, Julia; Golani, Lalit K.; Cerne, Rok; Smith, Jodi L.; Szostak, Marta; Witkin, Jeffrey M.; Psychology, School of ScienceNMDA receptor antagonists have potential for therapeutics in neurological and psychiatric diseases, including neurodegenerative diseases, epilepsy, traumatic brain injury, substance abuse disorder (SUD), and major depressive disorder (MDD). (S)-ketamine was the first of a novel class of antidepressants, rapid-acting antidepressants, to be approved for medical use. The stereoisomer, (R)-ketamine (arketamine), is currently under development for treatment-resistant depression (TRD). The compound has demonstrated efficacy in multiple animal models. Two clinical studies disclosed efficacy in TRD and bipolar depression. A study by the drug sponsor recently failed to reach a priori clinical endpoints but post hoc analysis revealed efficacy. The clinical value of (R)-ketamine is supported by experimental data in humans and rodents, showing that it is less sedating, does not produce marked psychotomimetic or dissociative effects, has less abuse potential than (S)-ketamine, and produces efficacy in animal models of a range of neurological and psychiatric disorders. The mechanisms of action of the antidepressant effects of (R)-ketamine are hypothesized to be due to NMDA receptor antagonism and/or non-NMDA receptor mechanisms. We suggest that further clinical experimentation with (R)-ketamine will create novel and improved medicines for some of the neurological and psychiatric disorders that are underserved by current medications.Item Relationship of Hoarding and Depression Symptoms in Older Adults(Elsevier, 2024) Nutley, Sara; Nguyen, Binh K.; Mackin, R. Scott; Insel, Philip S.; Tosun, Duygu; Butters, Meryl; Aisen, Paul; Raman, Rema; Saykin, Andrew J.; Toga, Arthur W.; Jack, Clifford; Weiner, Michael W.; Nelson, Craig; Kassel, Michelle; Kryza-Lacombe, Maria; Eichenbaum, Joseph; Nosheny, Rachel L.; Mathews, Carol A.; Radiology and Imaging Sciences, School of MedicineHoarding disorder (HD) is a debilitating neuropsychiatric condition that affects 2%-6% of the population and increases in incidence with age. Major depressive disorder (MDD) co-occurs with HD in approximately 50% of cases and leads to increased functional impairment and disability. However, only one study to date has examined the rate and trajectory of hoarding symptoms in older individuals with a lifetime history of MDD, including those with current active depression (late-life depression; LLD). We therefore sought to characterize this potentially distinct phenotype. We determined the incidence of HD in two separate cohorts of participants with LLD (n = 73) or lifetime history of MDD (n = 580) and examined the reliability and stability of hoarding symptoms using the Saving Inventory-Revised (SI-R) and Hoarding Rating Scale-Self Report (HRS), as well as the co-variance of hoarding and depression scores over time. HD was present in 12% to 33% of participants with MDD, with higher rates found in those with active depressive symptoms. Hoarding severity was stable across timepoints in both samples (all correlations >0.75), and fewer than 30% of participants in each sample experienced significant changes in severity between any two timepoints. Change in depression symptoms over time did not co-vary with change in hoarding symptoms. These findings indicate that hoarding is a more common comorbidity in LLD than previously suggested, and should be considered in screening and management of LLD. Future studies should further characterize the interaction of these conditions and their impact on outcomes, particularly functional impairment in this vulnerable population.Item Role of Glial Cells in Neuronal Function, Mood Disorders, and Drug Addiction(MDPI, 2024-05-30) Tizabi, Yousef; Getachew, Bruk; Hauser, Sheketha R.; Tsytsarev, Vassiliy; Manhães, Alex C.; da Silva, Victor Diogenes Amaral; Psychiatry, School of MedicineMood disorders and substance use disorder (SUD) are of immense medical and social concern. Although significant progress on neuronal involvement in mood and reward circuitries has been achieved, it is only relatively recently that the role of glia in these disorders has attracted attention. Detailed understanding of the glial functions in these devastating diseases could offer novel interventions. Here, following a brief review of circuitries involved in mood regulation and reward perception, the specific contributions of neurotrophic factors, neuroinflammation, and gut microbiota to these diseases are highlighted. In this context, the role of specific glial cells (e.g., microglia, astroglia, oligodendrocytes, and synantocytes) on phenotypic manifestation of mood disorders or SUD are emphasized. In addition, use of this knowledge in the potential development of novel therapeutics is touched upon.