- Browse by Subject
Browsing by Subject "Major depressive disorder"
Now showing 1 - 7 of 7
Results Per Page
Sort Options
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 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 Treatment-Resistant Depression in Adolescents: Clinical Features and Measurement of Treatment Resistance(Mary Ann Liebert, Inc., 2020-05) Strawn, Jeffrey R.; Aaronson, Scott T.; Elmaadawi, Ahmed Z.; Schrodt, G. Randolph; Holbert, Richard C.; Verdoliva, Sarah; Heart, Karen; Demitrack, Mark A.; Croarkin, Paul E.; Psychiatry, School of MedicineObjective: To describe the clinical characteristics of adolescents with antidepressant treatment-resistant major depressive disorder (MDD) and to examine the utility of the Antidepressant Treatment Record (ATR) in categorizing treatment resistance in this population. Methods: Adolescents with treatment-resistant MDD enrolled in an interventional study underwent a baseline evaluation with the ATR, Children's Depression Rating Scale-Revised (CDRS-R), and Clinical Global Impressions-Severity (CGI-S) scales. Demographic and clinical characteristics were examined with regard to ATR-defined level of resistance (level 1 to ≥3) using analysis of variance and χ2 tests. Results: In adolescents with treatment-resistant MDD (N = 97), aged 12-21 years, most were female (65%), white (89%), and had recurrent illness (78%). Patients were severely ill (median CGI-S score of 5), had a mean CDRS-R score of 63 ± 10, and 17.5% had been hospitalized for depression-related symptoms. Fifty-two patients were classified as ATR 1, whereas 32 were classified as ATR level 2 and 13 patients as ≥3, respectively. For increasing ATR-defined levels, illness duration increased from 12.0 (range: 1.5-31.9) to 14.8 (range: 1.8-31.7) to 19.5 (range: 2.5-36.2) months and the likelihood of treatment with serotonin norepinephrine reuptake inhibitors (SNRIs) and dopamine norepinephrine reuptake inhibitors (DNRIs) similarly increased (p = 0.006 for both SNRIs and DNRIs) as did the likelihood of treatment with mixed dopamine serotonin receptor antagonists (χ2 = 17, p < 0.001). Conclusions: This study underscores the morbidity and chronicity of treatment-resistant MDD in adolescents. The present characterization of related clinical features describes the use of nonselective serotonin reuptake inhibitors in adolescents with treatment-resistant depression and raises the possibility that those with the greatest medication treatment resistance are less likely to have had recurrent episodes. The study also demonstrates the utility of the ATR in categorizing treatment resistance in adolescents with MDD.