Pub Date : 2016-11-01DOI: 10.1001/jamapsychiatry.2016.2092
Thomas V Fernandez, James F Leckman
{"title":"Prenatal and Perinatal Risk Factors and the Promise of Birth Cohort Studies: Origins of Obsessive-Compulsive Disorder.","authors":"Thomas V Fernandez, James F Leckman","doi":"10.1001/jamapsychiatry.2016.2092","DOIUrl":"10.1001/jamapsychiatry.2016.2092","url":null,"abstract":"","PeriodicalId":58,"journal":{"name":"The Journal of Physical Chemistry ","volume":"67 12","pages":"1117-1118"},"PeriodicalIF":25.8,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5180419/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50623988","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-10-01DOI: 10.1001/jamapsychiatry.2016.1736
Megan C Lytle, Vincent M B Silenzio, Eric D Caine
{"title":"Are There Still Too Few Suicides to Generate Public Outrage?","authors":"Megan C Lytle, Vincent M B Silenzio, Eric D Caine","doi":"10.1001/jamapsychiatry.2016.1736","DOIUrl":"10.1001/jamapsychiatry.2016.1736","url":null,"abstract":"","PeriodicalId":58,"journal":{"name":"The Journal of Physical Chemistry ","volume":"70 6","pages":"1003-1004"},"PeriodicalIF":25.8,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5082695/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50623912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-05-01DOI: 10.1001/jamapsychiatry.2016.0129
Divya Mehta, Felix C Tropf, Jacob Gratten, Andrew Bakshi, Zhihong Zhu, Silviu-Alin Bacanu, Gibran Hemani, Patrik K E Magnusson, Nicola Barban, Tõnu Esko, Andres Metspalu, Harold Snieder, Bryan J Mowry, Kenneth S Kendler, Jian Yang, Peter M Visscher, John J McGrath, Melinda C Mills, Naomi R Wray, S Hong Lee, Ole A Andreassen, Elvira Bramon, Richard Bruggeman, Joseph D Buxbaum, Murray J Cairns, Rita M Cantor, C Robert Cloninger, David Cohen, Benedicto Crespo-Facorro, Ariel Darvasi, Lynn E DeLisi, Timothy Dinan, Srdjan Djurovic, Gary Donohoe, Elodie Drapeau, Valentina Escott-Price, Nelson B Freimer, Lyudmila Georgieva, Lieuwe de Haan, Frans A Henskens, Inge Joa, Antonio Julià, Andrey Khrunin, Bernard Lerer, Svetlana Limborska, Carmel M Loughland, Milan Macek, Patrik K E Magnusson, Sara Marsal, Robert W McCarley, Andrew M McIntosh, Andrew McQuillin, Bela Melegh, Patricia T Michie, Derek W Morris, Kieran C Murphy, Inez Myin-Germeys, Ann Olincy, Jim Van Os, Christos Pantelis, Danielle Posthuma, Digby Quested, Ulrich Schall, Rodney J Scott, Larry J Seidman, Draga Toncheva, Paul A Tooney, John Waddington, Daniel R Weinberger, Mark Weiser, Jing Qin Wu
Importance: A recently published study of national data by McGrath et al in 2014 showed increased risk of schizophrenia (SCZ) in offspring associated with both early and delayed parental age, consistent with a U-shaped relationship. However, it remains unclear if the risk to the child is due to psychosocial factors associated with parental age or if those at higher risk for SCZ tend to have children at an earlier or later age.
Objective: To determine if there is a genetic association between SCZ and age at first birth (AFB) using genetically informative but independently ascertained data sets.
Design, setting, and participants: This investigation used multiple independent genome-wide association study data sets. The SCZ sample comprised 18 957 SCZ cases and 22 673 controls in a genome-wide association study from the second phase of the Psychiatric Genomics Consortium, and the AFB sample comprised 12 247 genotyped women measured for AFB from the following 4 community cohorts: Estonia (Estonian Genome Center Biobank, University of Tartu), the Netherlands (LifeLines Cohort Study), Sweden (Swedish Twin Registry), and the United Kingdom (TwinsUK). Schizophrenia genetic risk for each woman in the AFB community sample was estimated using genetic effects inferred from the SCZ genome-wide association study.
Main outcomes and measures: We tested if SCZ genetic risk was a significant predictor of response variables based on published polynomial functions that described the relationship between maternal age and SCZ risk in offspring in Denmark. We substituted AFB for maternal age in these functions, one of which was corrected for the age of the father, and found that the fit was superior for the model without adjustment for the father's age.
Results: We observed a U-shaped relationship between SCZ risk and AFB in the community cohorts, consistent with the previously reported relationship between SCZ risk in offspring and maternal age when not adjusted for the age of the father. We confirmed that SCZ risk profile scores significantly predicted the response variables (coefficient of determination R2 = 1.1E-03, P = 4.1E-04), reflecting the published relationship between maternal age and SCZ risk in offspring by McGrath et al in 2014.
Conclusions and relevance: This study provides evidence for a significant overlap between genetic factors associated with risk of SCZ and genetic factors associated with AFB. It has been reported that SCZ risk associated with increased maternal age is explained by the age of the father and that de novo mutations that occur more frequently in the germline of older men are the underlying causal mechanism. This explanation may need to be revised if, as suggested herein and if replicated in future studies, there is also increased genetic risk of SCZ in older mothers.
{"title":"Evidence for Genetic Overlap Between Schizophrenia and Age at First Birth in Women.","authors":"Divya Mehta, Felix C Tropf, Jacob Gratten, Andrew Bakshi, Zhihong Zhu, Silviu-Alin Bacanu, Gibran Hemani, Patrik K E Magnusson, Nicola Barban, Tõnu Esko, Andres Metspalu, Harold Snieder, Bryan J Mowry, Kenneth S Kendler, Jian Yang, Peter M Visscher, John J McGrath, Melinda C Mills, Naomi R Wray, S Hong Lee, Ole A Andreassen, Elvira Bramon, Richard Bruggeman, Joseph D Buxbaum, Murray J Cairns, Rita M Cantor, C Robert Cloninger, David Cohen, Benedicto Crespo-Facorro, Ariel Darvasi, Lynn E DeLisi, Timothy Dinan, Srdjan Djurovic, Gary Donohoe, Elodie Drapeau, Valentina Escott-Price, Nelson B Freimer, Lyudmila Georgieva, Lieuwe de Haan, Frans A Henskens, Inge Joa, Antonio Julià, Andrey Khrunin, Bernard Lerer, Svetlana Limborska, Carmel M Loughland, Milan Macek, Patrik K E Magnusson, Sara Marsal, Robert W McCarley, Andrew M McIntosh, Andrew McQuillin, Bela Melegh, Patricia T Michie, Derek W Morris, Kieran C Murphy, Inez Myin-Germeys, Ann Olincy, Jim Van Os, Christos Pantelis, Danielle Posthuma, Digby Quested, Ulrich Schall, Rodney J Scott, Larry J Seidman, Draga Toncheva, Paul A Tooney, John Waddington, Daniel R Weinberger, Mark Weiser, Jing Qin Wu","doi":"10.1001/jamapsychiatry.2016.0129","DOIUrl":"10.1001/jamapsychiatry.2016.0129","url":null,"abstract":"<p><strong>Importance: </strong>A recently published study of national data by McGrath et al in 2014 showed increased risk of schizophrenia (SCZ) in offspring associated with both early and delayed parental age, consistent with a U-shaped relationship. However, it remains unclear if the risk to the child is due to psychosocial factors associated with parental age or if those at higher risk for SCZ tend to have children at an earlier or later age.</p><p><strong>Objective: </strong>To determine if there is a genetic association between SCZ and age at first birth (AFB) using genetically informative but independently ascertained data sets.</p><p><strong>Design, setting, and participants: </strong>This investigation used multiple independent genome-wide association study data sets. The SCZ sample comprised 18 957 SCZ cases and 22 673 controls in a genome-wide association study from the second phase of the Psychiatric Genomics Consortium, and the AFB sample comprised 12 247 genotyped women measured for AFB from the following 4 community cohorts: Estonia (Estonian Genome Center Biobank, University of Tartu), the Netherlands (LifeLines Cohort Study), Sweden (Swedish Twin Registry), and the United Kingdom (TwinsUK). Schizophrenia genetic risk for each woman in the AFB community sample was estimated using genetic effects inferred from the SCZ genome-wide association study.</p><p><strong>Main outcomes and measures: </strong>We tested if SCZ genetic risk was a significant predictor of response variables based on published polynomial functions that described the relationship between maternal age and SCZ risk in offspring in Denmark. We substituted AFB for maternal age in these functions, one of which was corrected for the age of the father, and found that the fit was superior for the model without adjustment for the father's age.</p><p><strong>Results: </strong>We observed a U-shaped relationship between SCZ risk and AFB in the community cohorts, consistent with the previously reported relationship between SCZ risk in offspring and maternal age when not adjusted for the age of the father. We confirmed that SCZ risk profile scores significantly predicted the response variables (coefficient of determination R2 = 1.1E-03, P = 4.1E-04), reflecting the published relationship between maternal age and SCZ risk in offspring by McGrath et al in 2014.</p><p><strong>Conclusions and relevance: </strong>This study provides evidence for a significant overlap between genetic factors associated with risk of SCZ and genetic factors associated with AFB. It has been reported that SCZ risk associated with increased maternal age is explained by the age of the father and that de novo mutations that occur more frequently in the germline of older men are the underlying causal mechanism. This explanation may need to be revised if, as suggested herein and if replicated in future studies, there is also increased genetic risk of SCZ in older mothers.</p>","PeriodicalId":58,"journal":{"name":"The Journal of Physical Chemistry ","volume":"76 21","pages":"497-505"},"PeriodicalIF":25.8,"publicationDate":"2016-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5785705/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50623443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-05-01DOI: 10.1001/jamapsychiatry.2015.3463
Theodore D Satterthwaite, Daniel H Wolf, Monica E Calkins, Simon N Vandekar, Guray Erus, Kosha Ruparel, David R Roalf, Kristin A Linn, Mark A Elliott, Tyler M Moore, Hakon Hakonarson, Russell T Shinohara, Christos Davatzikos, Ruben C Gur, Raquel E Gur
Importance: Structural brain abnormalities are prominent in psychotic disorders, including schizophrenia. However, it is unclear when aberrations emerge in the disease process and if such deficits are present in association with less severe psychosis spectrum (PS) symptoms in youth.
Objective: To investigate the presence of structural brain abnormalities in youth with PS symptoms.
Design, setting, and participants: The Philadelphia Neurodevelopmental Cohort is a prospectively accrued, community-based sample of 9498 youth who received a structured psychiatric evaluation. A subsample of 1601 individuals underwent neuroimaging, including structural magnetic resonance imaging, at an academic and children's hospital health care network between November 1, 2009, and November 30, 2011.
Main outcomes and measures: Measures of brain volume derived from T1-weighted structural neuroimaging at 3 T. Analyses were conducted at global, regional, and voxelwise levels. Regional volumes were estimated with an advanced multiatlas regional segmentation procedure, and voxelwise volumetric analyses were conducted as well. Nonlinear developmental patterns were examined using penalized splines within a general additive model. Psychosis spectrum (PS) symptom severity was summarized using factor analysis and evaluated dimensionally.
Results: Following exclusions due to comorbidity and image quality assurance, the final sample included 791 participants aged youth 8 to 22 years. Fifty percent (n = 393) were female. After structured interviews, 391 participants were identified as having PS features (PS group) and 400 participants were identified as typically developing comparison individuals without significant psychopathology (TD group). Compared with the TD group, the PS group had diminished whole-brain gray matter volume (P = 1.8 × 10-10) and expanded white matter volume (P = 2.8 × 10-11). Voxelwise analyses revealed significantly lower gray matter volume in the medial temporal lobe (maximum z score = 5.2 and cluster size of 1225 for the right and maximum z score = 4.5 and cluster size of 310 for the left) as well as in frontal, temporal, and parietal cortex. Volumetric reduction in the medial temporal lobe was correlated with PS symptom severity.
Conclusions and relevance: Structural brain abnormalities that have been commonly reported in adults with psychosis are present early in life in youth with PS symptoms and are not due to medication effects. Future longitudinal studies could use the presence of such abnormalities in conjunction with clinical presentation, cognitive profile, and genomics to predict risk and aid in stratification to guide early interventions.
{"title":"Structural Brain Abnormalities in Youth With Psychosis Spectrum Symptoms.","authors":"Theodore D Satterthwaite, Daniel H Wolf, Monica E Calkins, Simon N Vandekar, Guray Erus, Kosha Ruparel, David R Roalf, Kristin A Linn, Mark A Elliott, Tyler M Moore, Hakon Hakonarson, Russell T Shinohara, Christos Davatzikos, Ruben C Gur, Raquel E Gur","doi":"10.1001/jamapsychiatry.2015.3463","DOIUrl":"10.1001/jamapsychiatry.2015.3463","url":null,"abstract":"<p><strong>Importance: </strong>Structural brain abnormalities are prominent in psychotic disorders, including schizophrenia. However, it is unclear when aberrations emerge in the disease process and if such deficits are present in association with less severe psychosis spectrum (PS) symptoms in youth.</p><p><strong>Objective: </strong>To investigate the presence of structural brain abnormalities in youth with PS symptoms.</p><p><strong>Design, setting, and participants: </strong>The Philadelphia Neurodevelopmental Cohort is a prospectively accrued, community-based sample of 9498 youth who received a structured psychiatric evaluation. A subsample of 1601 individuals underwent neuroimaging, including structural magnetic resonance imaging, at an academic and children's hospital health care network between November 1, 2009, and November 30, 2011.</p><p><strong>Main outcomes and measures: </strong>Measures of brain volume derived from T1-weighted structural neuroimaging at 3 T. Analyses were conducted at global, regional, and voxelwise levels. Regional volumes were estimated with an advanced multiatlas regional segmentation procedure, and voxelwise volumetric analyses were conducted as well. Nonlinear developmental patterns were examined using penalized splines within a general additive model. Psychosis spectrum (PS) symptom severity was summarized using factor analysis and evaluated dimensionally.</p><p><strong>Results: </strong>Following exclusions due to comorbidity and image quality assurance, the final sample included 791 participants aged youth 8 to 22 years. Fifty percent (n = 393) were female. After structured interviews, 391 participants were identified as having PS features (PS group) and 400 participants were identified as typically developing comparison individuals without significant psychopathology (TD group). Compared with the TD group, the PS group had diminished whole-brain gray matter volume (P = 1.8 × 10-10) and expanded white matter volume (P = 2.8 × 10-11). Voxelwise analyses revealed significantly lower gray matter volume in the medial temporal lobe (maximum z score = 5.2 and cluster size of 1225 for the right and maximum z score = 4.5 and cluster size of 310 for the left) as well as in frontal, temporal, and parietal cortex. Volumetric reduction in the medial temporal lobe was correlated with PS symptom severity.</p><p><strong>Conclusions and relevance: </strong>Structural brain abnormalities that have been commonly reported in adults with psychosis are present early in life in youth with PS symptoms and are not due to medication effects. Future longitudinal studies could use the presence of such abnormalities in conjunction with clinical presentation, cognitive profile, and genomics to predict risk and aid in stratification to guide early interventions.</p>","PeriodicalId":58,"journal":{"name":"The Journal of Physical Chemistry ","volume":"79 10","pages":"515-24"},"PeriodicalIF":22.5,"publicationDate":"2016-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5048443/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50623801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-05-01DOI: 10.1001/jamapsychiatry.2016.0036
Richard Sherva, Qian Wang, Henry Kranzler, Hongyu Zhao, Ryan Koesterer, Aryeh Herman, Lindsay A Farrer, Joel Gelernter
Importance: Cannabis dependence (CAD) is a serious problem worldwide and is of growing importance in the United States because cannabis is increasingly available legally. Although genetic factors contribute substantially to CAD risk, at present no well-established specific genetic risk factors for CAD have been elucidated.
Objective: To report findings for DSM-IV CAD criteria from association analyses performed in large cohorts of African American and European American participants from 3 studies of substance use disorder genetics.
Design, setting, and participants: This genome-wide association study for DSM-IV CAD criterion count was performed in 3 independent substance dependence cohorts (the Yale-Penn Study, Study of Addiction: Genetics and Environment [SAGE], and International Consortium on the Genetics of Heroin Dependence [ICGHD]). A referral sample and volunteers recruited in the community and from substance abuse treatment centers included 6000 African American and 8754 European American participants, including some from small families. Participants from the Yale-Penn Study were recruited from 2000 to 2013. Data were collected for the SAGE trial from 1990 to 2007 and for the ICGHD from 2004 to 2009. Data were analyzed from January 2, 2013, to November 9, 2015.
Main outcomes and measures: Criterion count for DSM-IV CAD.
Results: Among the 14 754 participants, 7879 were male, 6875 were female, and the mean (SD) age was 39.2 (10.2) years. Three independent regions with genome-wide significant single-nucleotide polymorphism associations were identified, considering the largest possible sample. These included rs143244591 (β = 0.54, P = 4.32 × 10-10 for the meta-analysis) in novel antisense transcript RP11-206M11.7;rs146091982 (β = 0.54, P = 1.33 × 10-9 for the meta-analysis) in the solute carrier family 35 member G1 gene (SLC35G1); and rs77378271 (β = 0.29, P = 2.13 × 10-8 for the meta-analysis) in the CUB and Sushi multiple domains 1 gene (CSMD1). Also noted was evidence of genome-level pleiotropy between CAD and major depressive disorder and for an association with single-nucleotide polymorphisms in genes associated with schizophrenia risk. Several of the genes identified have functions related to neuronal calcium homeostasis or central nervous system development.
Conclusions and relevance: These results are the first, to our knowledge, to identify specific CAD risk alleles and potential genetic factors contributing to the comorbidity of CAD with major depression and schizophrenia.
重要性:大麻依赖症(CAD)是全球范围内的一个严重问题,在美国也日益重要,因为大麻越来越多地合法供应。虽然遗传因素在很大程度上导致了 CAD 风险,但目前还没有明确的特定 CAD 遗传风险因素:报告从 3 项药物使用障碍遗传学研究中对大量非裔美国人和欧洲裔美国人参与者进行的关联分析中得出的符合 DSM-IV CAD 标准的结果:这项针对 DSM-IV CAD 标准计数的全基因组关联研究在 3 个独立的药物依赖队列(耶鲁-宾夕法尼亚研究、成瘾研究、遗传与环境研究 [SAGE])中进行:遗传与环境研究》(Study Addiction: Genetics and Environment [SAGE])和《海洛因依赖性遗传学国际联合会》(International Consortium on the Genetics of Heroin Dependence [ICGHD]))。转介样本以及在社区和药物滥用治疗中心招募的志愿者包括 6000 名非洲裔美国人和 8754 名欧洲裔美国人,其中一些人来自小家庭。耶鲁-宾夕法尼亚研究的参与者是在 2000 年至 2013 年期间招募的。SAGE试验的数据收集时间为1990年至2007年,ICGHD试验的数据收集时间为2004年至2009年。数据分析时间为2013年1月2日至2015年11月9日:DSM-IV CAD的标准计数:在14 754名参与者中,男性7879人,女性6875人,平均(标清)年龄为39.2(10.2)岁。考虑到可能的最大样本,发现了三个具有全基因组显著单核苷酸多态性关联的独立区域。其中包括新型反义转录本 RP11-206M11.7 中的 rs143244591(β = 0.54,荟萃分析 P = 4.32 × 10-10);rs146091982(β = 0.54,荟萃分析 P = 1.33×10-9);溶质运载家族 35 成员 G1 基因(SLC35G1)中的 rs77378271(β = 0.29,荟萃分析 P = 2.13×10-8);以及 CUB 和 Sushi 多域 1 基因(CSMD1)中的 rs77378271(β = 0.29,荟萃分析 P = 2.13×10-8)。此外,还有证据表明,CAD 与重度抑郁障碍之间存在基因组水平的多效性,并且与精神分裂症风险相关基因中的单核苷酸多态性有关。所发现的几个基因具有与神经元钙稳态或中枢神经系统发育有关的功能:据我们所知,这些研究结果是首次鉴定出导致心血管疾病与重度抑郁症和精神分裂症并发的特异性心血管疾病风险等位基因和潜在遗传因素。
{"title":"Genome-wide Association Study of Cannabis Dependence Severity, Novel Risk Variants, and Shared Genetic Risks.","authors":"Richard Sherva, Qian Wang, Henry Kranzler, Hongyu Zhao, Ryan Koesterer, Aryeh Herman, Lindsay A Farrer, Joel Gelernter","doi":"10.1001/jamapsychiatry.2016.0036","DOIUrl":"10.1001/jamapsychiatry.2016.0036","url":null,"abstract":"<p><strong>Importance: </strong>Cannabis dependence (CAD) is a serious problem worldwide and is of growing importance in the United States because cannabis is increasingly available legally. Although genetic factors contribute substantially to CAD risk, at present no well-established specific genetic risk factors for CAD have been elucidated.</p><p><strong>Objective: </strong>To report findings for DSM-IV CAD criteria from association analyses performed in large cohorts of African American and European American participants from 3 studies of substance use disorder genetics.</p><p><strong>Design, setting, and participants: </strong>This genome-wide association study for DSM-IV CAD criterion count was performed in 3 independent substance dependence cohorts (the Yale-Penn Study, Study of Addiction: Genetics and Environment [SAGE], and International Consortium on the Genetics of Heroin Dependence [ICGHD]). A referral sample and volunteers recruited in the community and from substance abuse treatment centers included 6000 African American and 8754 European American participants, including some from small families. Participants from the Yale-Penn Study were recruited from 2000 to 2013. Data were collected for the SAGE trial from 1990 to 2007 and for the ICGHD from 2004 to 2009. Data were analyzed from January 2, 2013, to November 9, 2015.</p><p><strong>Main outcomes and measures: </strong>Criterion count for DSM-IV CAD.</p><p><strong>Results: </strong>Among the 14 754 participants, 7879 were male, 6875 were female, and the mean (SD) age was 39.2 (10.2) years. Three independent regions with genome-wide significant single-nucleotide polymorphism associations were identified, considering the largest possible sample. These included rs143244591 (β = 0.54, P = 4.32 × 10-10 for the meta-analysis) in novel antisense transcript RP11-206M11.7;rs146091982 (β = 0.54, P = 1.33 × 10-9 for the meta-analysis) in the solute carrier family 35 member G1 gene (SLC35G1); and rs77378271 (β = 0.29, P = 2.13 × 10-8 for the meta-analysis) in the CUB and Sushi multiple domains 1 gene (CSMD1). Also noted was evidence of genome-level pleiotropy between CAD and major depressive disorder and for an association with single-nucleotide polymorphisms in genes associated with schizophrenia risk. Several of the genes identified have functions related to neuronal calcium homeostasis or central nervous system development.</p><p><strong>Conclusions and relevance: </strong>These results are the first, to our knowledge, to identify specific CAD risk alleles and potential genetic factors contributing to the comorbidity of CAD with major depression and schizophrenia.</p>","PeriodicalId":58,"journal":{"name":"The Journal of Physical Chemistry ","volume":"78 18","pages":"472-80"},"PeriodicalIF":25.8,"publicationDate":"2016-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4974817/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50623834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-04-01DOI: 10.1001/jamapsychiatry.2015.3018
Mads Engel Hauberg, Panos Roussos, Jakob Grove, Anders Dupont Børglum, Manuel Mattheisen
Importance: The recent implication of 108 genomic loci in schizophrenia marked a great advancement in our understanding of the disease. Against the background of its polygenic nature there is a necessity to identify how schizophrenia risk genes interplay. As regulators of gene expression, microRNAs (miRNAs) have repeatedly been implicated in schizophrenia etiology. It is therefore of interest to establish their role in the regulation of schizophrenia risk genes in disease-relevant biological processes.
Objective: To examine the role of miRNAs in schizophrenia in the context of disease-associated genetic variation.
Design, setting, and participants: The basis of this study was summary statistics from the largest schizophrenia genome-wide association study meta-analysis to date (83 550 individuals in a meta-analysis of 52 genome-wide association studies) completed in 2014 along with publicly available data for predicted miRNA targets. We examined whether schizophrenia risk genes were more likely to be regulated by miRNA. Further, we used gene set analyses to identify miRNAs that are regulators of schizophrenia risk genes.
Main outcomes and measures: Results from association tests for miRNA targetomes and related analyses.
Results: In line with previous studies, we found that similar to other complex traits, schizophrenia risk genes were more likely to be regulated by miRNAs (P < 2 × 10-16). Further, the gene set analyses revealed several miRNAs regulating schizophrenia risk genes, with the strongest enrichment for targets of miR-9-5p (P = .0056 for enrichment among the top 1% most-associated single-nucleotide polymorphisms, corrected for multiple testing). It is further of note that MIR9-2 is located in a genomic region showing strong evidence for association with schizophrenia (P = 7.1 × 10-8). The second and third strongest gene set signals were seen for the targets of miR-485-5p and miR-137, respectively.
Conclusions and relevance: This study provides evidence for a role of miR-9-5p in the etiology of schizophrenia. Its implication is of particular interest as the functions of this neurodevelopmental miRNA tie in with established disease biology: it has a regulatory loop with the fragile X mental retardation homologue FXR1 and regulates dopamine D2 receptor density.
{"title":"Analyzing the Role of MicroRNAs in Schizophrenia in the Context of Common Genetic Risk Variants.","authors":"Mads Engel Hauberg, Panos Roussos, Jakob Grove, Anders Dupont Børglum, Manuel Mattheisen","doi":"10.1001/jamapsychiatry.2015.3018","DOIUrl":"10.1001/jamapsychiatry.2015.3018","url":null,"abstract":"<p><strong>Importance: </strong>The recent implication of 108 genomic loci in schizophrenia marked a great advancement in our understanding of the disease. Against the background of its polygenic nature there is a necessity to identify how schizophrenia risk genes interplay. As regulators of gene expression, microRNAs (miRNAs) have repeatedly been implicated in schizophrenia etiology. It is therefore of interest to establish their role in the regulation of schizophrenia risk genes in disease-relevant biological processes.</p><p><strong>Objective: </strong>To examine the role of miRNAs in schizophrenia in the context of disease-associated genetic variation.</p><p><strong>Design, setting, and participants: </strong>The basis of this study was summary statistics from the largest schizophrenia genome-wide association study meta-analysis to date (83 550 individuals in a meta-analysis of 52 genome-wide association studies) completed in 2014 along with publicly available data for predicted miRNA targets. We examined whether schizophrenia risk genes were more likely to be regulated by miRNA. Further, we used gene set analyses to identify miRNAs that are regulators of schizophrenia risk genes.</p><p><strong>Main outcomes and measures: </strong>Results from association tests for miRNA targetomes and related analyses.</p><p><strong>Results: </strong>In line with previous studies, we found that similar to other complex traits, schizophrenia risk genes were more likely to be regulated by miRNAs (P < 2 × 10-16). Further, the gene set analyses revealed several miRNAs regulating schizophrenia risk genes, with the strongest enrichment for targets of miR-9-5p (P = .0056 for enrichment among the top 1% most-associated single-nucleotide polymorphisms, corrected for multiple testing). It is further of note that MIR9-2 is located in a genomic region showing strong evidence for association with schizophrenia (P = 7.1 × 10-8). The second and third strongest gene set signals were seen for the targets of miR-485-5p and miR-137, respectively.</p><p><strong>Conclusions and relevance: </strong>This study provides evidence for a role of miR-9-5p in the etiology of schizophrenia. Its implication is of particular interest as the functions of this neurodevelopmental miRNA tie in with established disease biology: it has a regulatory loop with the fragile X mental retardation homologue FXR1 and regulates dopamine D2 receptor density.</p>","PeriodicalId":58,"journal":{"name":"The Journal of Physical Chemistry ","volume":"85 19","pages":"369-77"},"PeriodicalIF":25.8,"publicationDate":"2016-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1001/jamapsychiatry.2015.3018","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50623410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-03-01DOI: 10.1001/jamapsychiatry.2015.2692
Andrea J Gonzalez-Mantilla, Andres Moreno-De-Luca, David H Ledbetter, Christa Lese Martin
<p><strong>Importance: </strong>Developmental brain disorders are a group of clinically and genetically heterogeneous disorders characterized by high heritability. Specific highly penetrant genetic causes can often be shared by a subset of individuals with different phenotypic features, and recent advances in genome sequencing have allowed the rapid and cost-effective identification of many of these pathogenic variants.</p><p><strong>Objectives: </strong>To identify novel candidate genes for developmental brain disorders and provide additional evidence of previously implicated genes.</p><p><strong>Data sources: </strong>The PubMed database was searched for studies published from March 28, 2003, through May 7, 2015, with large cohorts of individuals with developmental brain disorders.</p><p><strong>Data extraction and synthesis: </strong>A tiered, multilevel data-integration approach was used, which intersects (1) whole-genome data from structural and sequence pathogenic loss-of-function (pLOF) variants, (2) phenotype data from 6 apparently distinct disorders (intellectual disability, autism, attention-deficit/hyperactivity disorder, schizophrenia, bipolar disorder, and epilepsy), and (3) additional data from large-scale studies, smaller cohorts, and case reports focusing on specific candidate genes. All candidate genes were ranked into 4 tiers based on the strength of evidence as follows: tier 1, genes with 3 or more de novo pathogenic loss-of-function variants; tier 2, genes with 2 de novo pathogenic loss-of-function variants; tier 3, genes with 1 de novo pathogenic loss-of-function variant; and tier 4, genes with only inherited (or unknown inheritance) pathogenic loss-of-function variants.</p><p><strong>Main outcomes and measures: </strong>Development of a comprehensive knowledge base of candidate genes related to developmental brain disorders. Genes were prioritized based on the inheritance pattern and total number of pathogenic loss-of-function variants identified amongst unrelated individuals with any one of six developmental brain disorders.</p><p><strong>Study selection: </strong>A combination of phenotype-based and genotype-based literature review yielded 384 studies that used whole-genome or exome sequencing, chromosomal microarray analysis, and/or targeted sequencing to evaluate 1960 individuals with developmental brain disorders.</p><p><strong>Results: </strong>Our initial phenotype-based literature review yielded 1911 individuals with pLOF variants involving 1034 genes from 118 studies. Filtering our results to genes with 2 or more pLOF variants identified in at least 2 unrelated individuals resulted in 241 genes from 1110 individuals. Of the 241 genes involved in brain disorders, 7 were novel high-confidence genes and 10 were novel putative candidate genes. Fifty-nine genes were ranked in tier 1, 44 in tier 2, 68 in tier 3, and 70 in tier 4. By transcending clinical diagnostic boundaries, the evidence level for 18 additional genes th
{"title":"A Cross-Disorder Method to Identify Novel Candidate Genes for Developmental Brain Disorders.","authors":"Andrea J Gonzalez-Mantilla, Andres Moreno-De-Luca, David H Ledbetter, Christa Lese Martin","doi":"10.1001/jamapsychiatry.2015.2692","DOIUrl":"10.1001/jamapsychiatry.2015.2692","url":null,"abstract":"<p><strong>Importance: </strong>Developmental brain disorders are a group of clinically and genetically heterogeneous disorders characterized by high heritability. Specific highly penetrant genetic causes can often be shared by a subset of individuals with different phenotypic features, and recent advances in genome sequencing have allowed the rapid and cost-effective identification of many of these pathogenic variants.</p><p><strong>Objectives: </strong>To identify novel candidate genes for developmental brain disorders and provide additional evidence of previously implicated genes.</p><p><strong>Data sources: </strong>The PubMed database was searched for studies published from March 28, 2003, through May 7, 2015, with large cohorts of individuals with developmental brain disorders.</p><p><strong>Data extraction and synthesis: </strong>A tiered, multilevel data-integration approach was used, which intersects (1) whole-genome data from structural and sequence pathogenic loss-of-function (pLOF) variants, (2) phenotype data from 6 apparently distinct disorders (intellectual disability, autism, attention-deficit/hyperactivity disorder, schizophrenia, bipolar disorder, and epilepsy), and (3) additional data from large-scale studies, smaller cohorts, and case reports focusing on specific candidate genes. All candidate genes were ranked into 4 tiers based on the strength of evidence as follows: tier 1, genes with 3 or more de novo pathogenic loss-of-function variants; tier 2, genes with 2 de novo pathogenic loss-of-function variants; tier 3, genes with 1 de novo pathogenic loss-of-function variant; and tier 4, genes with only inherited (or unknown inheritance) pathogenic loss-of-function variants.</p><p><strong>Main outcomes and measures: </strong>Development of a comprehensive knowledge base of candidate genes related to developmental brain disorders. Genes were prioritized based on the inheritance pattern and total number of pathogenic loss-of-function variants identified amongst unrelated individuals with any one of six developmental brain disorders.</p><p><strong>Study selection: </strong>A combination of phenotype-based and genotype-based literature review yielded 384 studies that used whole-genome or exome sequencing, chromosomal microarray analysis, and/or targeted sequencing to evaluate 1960 individuals with developmental brain disorders.</p><p><strong>Results: </strong>Our initial phenotype-based literature review yielded 1911 individuals with pLOF variants involving 1034 genes from 118 studies. Filtering our results to genes with 2 or more pLOF variants identified in at least 2 unrelated individuals resulted in 241 genes from 1110 individuals. Of the 241 genes involved in brain disorders, 7 were novel high-confidence genes and 10 were novel putative candidate genes. Fifty-nine genes were ranked in tier 1, 44 in tier 2, 68 in tier 3, and 70 in tier 4. By transcending clinical diagnostic boundaries, the evidence level for 18 additional genes th","PeriodicalId":58,"journal":{"name":"The Journal of Physical Chemistry ","volume":"92 7","pages":"275-83"},"PeriodicalIF":25.8,"publicationDate":"2016-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5333489/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50623541","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-02-01DOI: 10.1001/jamapsychiatry.2015.2821
Vinod H Srihari, Anant Jani, Muir Gray
{"title":"Early Intervention for Psychotic Disorders: Building Population Health Systems.","authors":"Vinod H Srihari, Anant Jani, Muir Gray","doi":"10.1001/jamapsychiatry.2015.2821","DOIUrl":"10.1001/jamapsychiatry.2015.2821","url":null,"abstract":"","PeriodicalId":58,"journal":{"name":"The Journal of Physical Chemistry ","volume":"89 23","pages":"101-2"},"PeriodicalIF":25.8,"publicationDate":"2016-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50623717","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 : 2016-01-01DOI: 10.1001/jamapsychiatry.2015.2453
Ian H Gotlib, Sarah J Ordaz
{"title":"The Importance of Assessing Neural Trajectories in Pediatric Depression.","authors":"Ian H Gotlib, Sarah J Ordaz","doi":"10.1001/jamapsychiatry.2015.2453","DOIUrl":"10.1001/jamapsychiatry.2015.2453","url":null,"abstract":"","PeriodicalId":58,"journal":{"name":"The Journal of Physical Chemistry ","volume":"95 15","pages":"9-10"},"PeriodicalIF":25.8,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5522740/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50623208","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2016-01-01DOI: 10.1001/jamapsychiatry.2015.2132
Bridget F Grant, Tulshi D Saha, W June Ruan, Risë B Goldstein, S Patricia Chou, Jeesun Jung, Haitao Zhang, Sharon M Smith, Roger P Pickering, Boji Huang, Deborah S Hasin
<p><strong>Importance: </strong>Current information on the prevalence and sociodemographic and clinical profiles of individuals in the general population with DSM-5 drug use disorder (DUD) is limited. Given the present societal and economic context in the United States and the new diagnostic system, up-to-date national information is needed from a single uniform data source.</p><p><strong>Objective: </strong>To present nationally representative findings on the prevalence, correlates, psychiatric comorbidity, disability, and treatment of DSM-5 DUD diagnoses overall and by severity level.</p><p><strong>Design, setting, and participants: </strong>In-person interviews were conducted with 36,309 adults in the 2012-2013 National Epidemiologic Survey on Alcohol and Related Conditions-III, a cross-sectional representative survey of the United States. The household response rate was 72%; person-level response rate, 84%; and overall response rate, 60.1%. Data were collected April 2012 through June 2013 and analyzed from February through March 2015.</p><p><strong>Main outcomes and measures: </strong>Twelve-month and lifetime DUD, based on amphetamine, cannabis, club drug, cocaine, hallucinogen, heroin, nonheroin opioid, sedative/tranquilizer, and/or solvent/inhalant use disorders.</p><p><strong>Results: </strong>Prevalences of 12-month and lifetime DUD were 3.9% and 9.9%, respectively. Drug use disorder was generally greater among men, white and Native American individuals, younger and previously or never married adults, those with lower education and income, and those residing in the West. Significant associations were found between 12-month and lifetime DUD and other substance use disorders. Significant associations were also found between any 12-month DUD and major depressive disorder (odds ratio [OR], 1.3; 95% CI, 1.09-1.64), dysthymia (OR, 1.5; 95% CI, 1.09-2.02), bipolar I (OR, 1.5; 95% CI, 1.06-2.05), posttraumatic stress disorder (OR, 1.6; 95% CI, 1.27-2.10), and antisocial (OR, 1.4; 95% CI, 1.11-1.75), borderline (OR, 1.8; 95% CI, 1.41-2.24), and schizotypal (OR, 1.5; 95% CI, 1.18-1.87) personality disorders. Similar associations were found for any lifetime DUD with the exception that lifetime DUD was also associated with generalized anxiety disorder (OR, 1.3; 95% CI, 1.06-1.49), panic disorder (OR, 1.3; 95% CI, 1.06-1.59), and social phobia (OR, 1.3; 95% CI, 1.09-1.64). Twelve-month DUD was associated with significant disability, increasing with DUD severity. Among respondents with 12-month and lifetime DUD, only 13.5% and 24.6% received treatment, respectively.</p><p><strong>Conclusions and relevance: </strong>DSM-5 DUD is a common, highly comorbid, and disabling disorder that largely goes untreated in the United States. These findings indicate the need for additional studies to understand the broad relationships in more detail; estimate present-day economic costs of DUDs; investigate hypotheses regarding etiology, chronicity, and treatment use;
重要性:目前有关 DSM-5 药物滥用障碍(DUD)患者在普通人群中的流行率、社会人口学和临床概况的信息十分有限。考虑到美国当前的社会和经济背景以及新的诊断系统,需要从单一的统一数据源获得最新的全国性信息:目的:就 DSM-5 DUD 诊断的总体患病率、相关性、精神病合并症、残疾和治疗情况以及严重程度,提供具有全国代表性的研究结果:2012-2013年美国全国酒精及相关疾病流行病学调查-III是一项具有代表性的横断面调查,对36309名成年人进行了面对面访谈。家庭响应率为 72%;个人响应率为 84%;总体响应率为 60.1%。数据收集时间为 2012 年 4 月至 2013 年 6 月,分析时间为 2015 年 2 月至 3 月:根据苯丙胺、大麻、俱乐部用药、可卡因、致幻剂、海洛因、非海洛因类阿片、镇静剂/镇定剂和/或溶剂/吸入剂使用障碍,得出 12 个月和终生的 DUD:12 个月和终生 DUD 患病率分别为 3.9% 和 9.9%。男性、白人和美国原住民、年龄较轻、曾结过婚或从未结过婚的成年人、教育程度和收入较低的人以及居住在西部地区的人中,吸毒障碍的发生率普遍较高。研究发现,12 个月和终生 DUD 与其他药物使用失调之间存在显著关联。任何 12 个月的 DUD 与重度抑郁障碍(几率比 [OR],1.3;95% CI,1.09-1.64)、癔症(OR,1.5;95% CI,1.09-2.02)、躁郁症 I(OR,1.5;95% CI,1.06-2.05)、创伤后应激障碍(OR,1.5;95% CI,1.06-2.05)和其他药物使用障碍之间也存在显著关联。05)、创伤后应激障碍(OR,1.6;95% CI,1.27-2.10)、反社会人格障碍(OR,1.4;95% CI,1.11-1.75)、边缘型人格障碍(OR,1.8;95% CI,1.41-2.24)和分裂型人格障碍(OR,1.5;95% CI,1.18-1.87)。除了终生 DUD 与广泛性焦虑症(OR,1.3;95% CI,1.06-1.49)、恐慌症(OR,1.3;95% CI,1.06-1.59)和社交恐惧症(OR,1.3;95% CI,1.09-1.64)相关之外,其他任何终生 DUD 也存在类似的关联。12 个月的 DUD 与严重残疾有关,残疾程度随 DUD 严重程度的增加而增加。在患有 12 个月和终生 DUD 的受访者中,分别只有 13.5% 和 24.6% 接受了治疗:DSM-5中的DUD是一种常见的、高度并发的致残性障碍,在美国大多未得到治疗。这些发现表明,有必要开展更多的研究,以更详细地了解广泛的关系;估算 DUD 现今的经济成本;调查有关病因、慢性病和治疗使用的假设;并为政策制定者提供有关服务提供和研究资源分配的信息。研究结果还表明,迫切需要消除 DUD 的污名化,并对公众、临床医生和政策制定者进行治疗教育,以鼓励患者寻求帮助。
{"title":"Epidemiology of DSM-5 Drug Use Disorder: Results From the National Epidemiologic Survey on Alcohol and Related Conditions-III.","authors":"Bridget F Grant, Tulshi D Saha, W June Ruan, Risë B Goldstein, S Patricia Chou, Jeesun Jung, Haitao Zhang, Sharon M Smith, Roger P Pickering, Boji Huang, Deborah S Hasin","doi":"10.1001/jamapsychiatry.2015.2132","DOIUrl":"10.1001/jamapsychiatry.2015.2132","url":null,"abstract":"<p><strong>Importance: </strong>Current information on the prevalence and sociodemographic and clinical profiles of individuals in the general population with DSM-5 drug use disorder (DUD) is limited. Given the present societal and economic context in the United States and the new diagnostic system, up-to-date national information is needed from a single uniform data source.</p><p><strong>Objective: </strong>To present nationally representative findings on the prevalence, correlates, psychiatric comorbidity, disability, and treatment of DSM-5 DUD diagnoses overall and by severity level.</p><p><strong>Design, setting, and participants: </strong>In-person interviews were conducted with 36,309 adults in the 2012-2013 National Epidemiologic Survey on Alcohol and Related Conditions-III, a cross-sectional representative survey of the United States. The household response rate was 72%; person-level response rate, 84%; and overall response rate, 60.1%. Data were collected April 2012 through June 2013 and analyzed from February through March 2015.</p><p><strong>Main outcomes and measures: </strong>Twelve-month and lifetime DUD, based on amphetamine, cannabis, club drug, cocaine, hallucinogen, heroin, nonheroin opioid, sedative/tranquilizer, and/or solvent/inhalant use disorders.</p><p><strong>Results: </strong>Prevalences of 12-month and lifetime DUD were 3.9% and 9.9%, respectively. Drug use disorder was generally greater among men, white and Native American individuals, younger and previously or never married adults, those with lower education and income, and those residing in the West. Significant associations were found between 12-month and lifetime DUD and other substance use disorders. Significant associations were also found between any 12-month DUD and major depressive disorder (odds ratio [OR], 1.3; 95% CI, 1.09-1.64), dysthymia (OR, 1.5; 95% CI, 1.09-2.02), bipolar I (OR, 1.5; 95% CI, 1.06-2.05), posttraumatic stress disorder (OR, 1.6; 95% CI, 1.27-2.10), and antisocial (OR, 1.4; 95% CI, 1.11-1.75), borderline (OR, 1.8; 95% CI, 1.41-2.24), and schizotypal (OR, 1.5; 95% CI, 1.18-1.87) personality disorders. Similar associations were found for any lifetime DUD with the exception that lifetime DUD was also associated with generalized anxiety disorder (OR, 1.3; 95% CI, 1.06-1.49), panic disorder (OR, 1.3; 95% CI, 1.06-1.59), and social phobia (OR, 1.3; 95% CI, 1.09-1.64). Twelve-month DUD was associated with significant disability, increasing with DUD severity. Among respondents with 12-month and lifetime DUD, only 13.5% and 24.6% received treatment, respectively.</p><p><strong>Conclusions and relevance: </strong>DSM-5 DUD is a common, highly comorbid, and disabling disorder that largely goes untreated in the United States. These findings indicate the need for additional studies to understand the broad relationships in more detail; estimate present-day economic costs of DUDs; investigate hypotheses regarding etiology, chronicity, and treatment use; ","PeriodicalId":58,"journal":{"name":"The Journal of Physical Chemistry ","volume":"98 24","pages":"39-47"},"PeriodicalIF":25.8,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5062605/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50622920","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}