Pub Date : 2021-12-01Epub Date: 2021-07-09DOI: 10.1159/000518098
Lívia Ramos-da-Silva, Pamela T Carlson, Licia C Silva-Costa, Daniel Martins-de-Souza, Valéria de Almeida
Major depressive disorder (MDD) is a complex and multifactorial psychiatric disorder that causes serious health, social, and economic concerns worldwide. The main treatment of the symptoms is through antidepressant (AD) drugs. However, not all patients respond properly to these drugs. Omic sciences are widely used to analyze not only biomarkers for the AD response but also their molecular mechanism. In this review, we aimed to focus on omics data to better understand the molecular mechanisms involving AD effects on MDD. We consistently found, from preclinical to clinical data, that glutamatergic transmission, immune/inflammatory processes, energy metabolism, oxidative stress, and lipid metabolism were associated with traditional and potential new ADs. Despite efforts of studies investigating biomarkers of response to ADs, which could contribute to personalized treatment, there is no biomarker panel available for clinical application. From clinical genomic studies, we found that the main findings contribute to the development of pharmacogenomic tests for AD efficacy for each patient. Several studies pointed at DRD2, PXDNL, CACNA1E, and CACNA2D1 genes as potential targets for MDD treatment and the efficacy and rapid-antidepressant effect of ketamine. Finally, more in-depth studies of the molecular targets pointed here are needed to determine the clinical relevance and provide further evidence for precision MDD treatment.
{"title":"Molecular Mechanisms Associated with Antidepressant Treatment on Major Depression.","authors":"Lívia Ramos-da-Silva, Pamela T Carlson, Licia C Silva-Costa, Daniel Martins-de-Souza, Valéria de Almeida","doi":"10.1159/000518098","DOIUrl":"https://doi.org/10.1159/000518098","url":null,"abstract":"<p><p>Major depressive disorder (MDD) is a complex and multifactorial psychiatric disorder that causes serious health, social, and economic concerns worldwide. The main treatment of the symptoms is through antidepressant (AD) drugs. However, not all patients respond properly to these drugs. Omic sciences are widely used to analyze not only biomarkers for the AD response but also their molecular mechanism. In this review, we aimed to focus on omics data to better understand the molecular mechanisms involving AD effects on MDD. We consistently found, from preclinical to clinical data, that glutamatergic transmission, immune/inflammatory processes, energy metabolism, oxidative stress, and lipid metabolism were associated with traditional and potential new ADs. Despite efforts of studies investigating biomarkers of response to ADs, which could contribute to personalized treatment, there is no biomarker panel available for clinical application. From clinical genomic studies, we found that the main findings contribute to the development of pharmacogenomic tests for AD efficacy for each patient. Several studies pointed at <i>DRD2</i>, <i>PXDNL</i>, <i>CACNA1E</i>, and <i>CACNA2D1</i> genes as potential targets for MDD treatment and the efficacy and rapid-antidepressant effect of ketamine. Finally, more in-depth studies of the molecular targets pointed here are needed to determine the clinical relevance and provide further evidence for precision MDD treatment.</p>","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":" ","pages":"49-59"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1159/000518098","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40490485","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 : 2021-12-01Epub Date: 2021-08-24DOI: 10.1159/000518926
Beatriz Camarena, Elizabeth G Atkinson, Mark Baker, Claudia Becerra-Palars, Lori B Chibnik, Raúl Escamilla-Orozco, Joanna Jiménez-Pavón, Zan Koenig, Carla Márquez-Luna, Alicia R Martin, Ingrid Pamela Morales-Cedillo, Ana Maria Olivares, Hiram Ortega-Ortiz, Alejandra Monserrat Rodriguez-Ramírez, Ricardo Saracco-Alvarez, Rebecca E Basaldua, Brena F Sena, Karestan C Koenen
No large-scale genome-wide association studies (GWASs) of psychosis have been conducted in Mexico or Latin America to date. Schizophrenia and bipolar disorder in particular have been found to be highly heritable and genetically influenced. However, understanding of the biological basis of psychosis in Latin American populations is limited as previous genomic studies have almost exclusively relied on participants of Northern European ancestry. With the goal of expanding knowledge on the genomic basis of psychotic disorders within the Mexican population, the National Institute of Psychiatry Ramón de la Fuente Muñiz (INPRFM), the Harvard T.H. Chan School of Public Health, and the Broad Institute's Stanley Center for Psychiatric Research launched the Neuropsychiatric Genetics Research of Psychosis in Mexican Populations (NeuroMex) project to collect and analyze case-control psychosis samples from 5 states across Mexico. This article describes the planned sample collection and GWAS protocol for the NeuroMex study. The 4-year study will span from April 2018 to 2022 and aims to recruit 9,208 participants: 4,604 cases and 4,604 controls. Study sites across Mexico were selected to ensure collected samples capture the genomic diversity within the Mexican population. Blood samples and phenotypic data will be collected during the participant interview process and will contribute to the development of a local biobank in Mexico. DNA extraction will be done locally and genetic analysis will take place at the Broad Institute in Cambridge, MA. We will collect extensive phenotypic information using several clinical scales. All study materials including phenotypic instruments utilized are openly available in Spanish and English. The described study represents a long-term collaboration of a number of institutions from across Mexico and the Boston area, including clinical psychiatrists, clinical researchers, computational biologists, and managers at the 3 collaborating institutions. The development of relevant data management, quality assurance, and analysis plans are the primary considerations in this protocol article. Extensive management and analysis processes were developed for both the phenotypic and genetic data collected. Capacity building, partnerships, and training between and among the collaborating institutions are intrinsic components to this study and its long-term success.
{"title":"Neuropsychiatric Genetics of Psychosis in the Mexican Population: A Genome-Wide Association Study Protocol for Schizophrenia, Schizoaffective, and Bipolar Disorder Patients and Controls.","authors":"Beatriz Camarena, Elizabeth G Atkinson, Mark Baker, Claudia Becerra-Palars, Lori B Chibnik, Raúl Escamilla-Orozco, Joanna Jiménez-Pavón, Zan Koenig, Carla Márquez-Luna, Alicia R Martin, Ingrid Pamela Morales-Cedillo, Ana Maria Olivares, Hiram Ortega-Ortiz, Alejandra Monserrat Rodriguez-Ramírez, Ricardo Saracco-Alvarez, Rebecca E Basaldua, Brena F Sena, Karestan C Koenen","doi":"10.1159/000518926","DOIUrl":"10.1159/000518926","url":null,"abstract":"<p><p>No large-scale genome-wide association studies (GWASs) of psychosis have been conducted in Mexico or Latin America to date. Schizophrenia and bipolar disorder in particular have been found to be highly heritable and genetically influenced. However, understanding of the biological basis of psychosis in Latin American populations is limited as previous genomic studies have almost exclusively relied on participants of Northern European ancestry. With the goal of expanding knowledge on the genomic basis of psychotic disorders within the Mexican population, the National Institute of Psychiatry Ramón de la Fuente Muñiz (INPRFM), the Harvard T.H. Chan School of Public Health, and the Broad Institute's Stanley Center for Psychiatric Research launched the Neuropsychiatric Genetics Research of Psychosis in Mexican Populations (NeuroMex) project to collect and analyze case-control psychosis samples from 5 states across Mexico. This article describes the planned sample collection and GWAS protocol for the NeuroMex study. The 4-year study will span from April 2018 to 2022 and aims to recruit 9,208 participants: 4,604 cases and 4,604 controls. Study sites across Mexico were selected to ensure collected samples capture the genomic diversity within the Mexican population. Blood samples and phenotypic data will be collected during the participant interview process and will contribute to the development of a local biobank in Mexico. DNA extraction will be done locally and genetic analysis will take place at the Broad Institute in Cambridge, MA. We will collect extensive phenotypic information using several clinical scales. All study materials including phenotypic instruments utilized are openly available in Spanish and English. The described study represents a long-term collaboration of a number of institutions from across Mexico and the Boston area, including clinical psychiatrists, clinical researchers, computational biologists, and managers at the 3 collaborating institutions. The development of relevant data management, quality assurance, and analysis plans are the primary considerations in this protocol article. Extensive management and analysis processes were developed for both the phenotypic and genetic data collected. Capacity building, partnerships, and training between and among the collaborating institutions are intrinsic components to this study and its long-term success.</p>","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":"7 3-4","pages":"60-70"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740081/pdf/cxp-0007-0060.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"33438095","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 : 2021-12-01Epub Date: 2021-08-05DOI: 10.1159/000518863
Travis T Mallard, Sandra Sanchez-Roige
{"title":"Dimensional Phenotypes in Psychiatric Genetics: Lessons from Genome-Wide Association Studies of Alcohol Use Phenotypes.","authors":"Travis T Mallard, Sandra Sanchez-Roige","doi":"10.1159/000518863","DOIUrl":"10.1159/000518863","url":null,"abstract":"","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":"7 3-4","pages":"45-48"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8739983/pdf/cxp-0007-0045.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39739651","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 : 2021-12-01Epub Date: 2021-11-18DOI: 10.1159/000519707
Brandon J Coombes, Vincent Millischer, Anthony Batzler, Beth Larrabee, Liping Hou, Sergi Papiol, Urs Heilbronner, Mazda Adli, Kazufumi Akiyama, Nirmala Akula, Azmeraw T Amare, Raffaella Ardau, Barbara Arias, Jean-Michel Aubry, Lena Backlund, Michael Bauer, Bernhard T Baune, Frank Bellivier, Antoni Benabarre, Susanne Bengesser, Abesh Kumar Bhattacharjee, Pablo Cervantes, Hsi-Chung Chen, Caterina Chillotti, Sven Cichon, Scott R Clark, Francesc Colom, Cristiana Cruceanu, Piotr M Czerski, Nina Dalkner, Franziska Degenhardt, Maria Del Zompo, J Raymond DePaulo, Bruno Étain, Peter Falkai, Ewa Ferensztajn-Rochowiak, Andreas J Forstner, Louise Frisen, Sébastien Gard, Julie S Garnham, Fernando S Goes, Maria Grigoroiu-Serbanescu, Paul Grof, Ryota Hashimoto, Joanna Hauser, Stefan Herms, Per Hoffmann, Stephane Jamain, Esther Jiménez, Jean-Pierre Kahn, Layla Kassem, Tadafumi Kato, John R Kelsoe, Sarah Kittel-Schneider, Barbara König, Po-Hsiu Kuo, Ichiro Kusumi, Gonzalo Laje, Mikael Landén, Catharina Lavebratt, Marion Leboyer, Susan G Leckband, Mario Maj, Mirko Manchia, Lina Martinsson, Michael J McCarthy, Susan L McElroy, Philip B Mitchell, Marina Mitjans, Francis M Mondimore, Palmiero Monteleone, Caroline M Nievergelt, Markus M Nöthen, Tomas Novák, Claire O'Donovan, Urban Osby, Norio Ozaki, Andrea Pfennig, Claudia Pisanu, James B Potash, Andreas Reif, Eva Reininghaus, Marcella Rietschel, Guy A Rouleau, Janusz K Rybakowski, Martin Schalling, Peter R Schofield, Klaus Oliver Schubert, Barbara W Schweizer, Giovanni Severino, Tatyana Shekhtman, Paul D Shilling, Katzutaka Shimoda, Christian Simhandl, Claire M Slaney, Alessio Squassina, Thomas Stamm, Pavla Stopkova, Alfonso Tortorella, Gustavo Turecki, Eduard Vieta, Stephanie H Witt, Peter P Zandi, Janice M Fullerton, Martin Alda, Mark A Frye, Thomas G Schulze, Francis J McMahon, Joanna M Biernacka
Response to lithium varies widely between individuals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients (N = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), and schizophrenia (SCZ) were computed using lassosum and in a model including all three PRSs and other covariates, and the PRS of ADHD (β = -0.14; 95% confidence interval [CI]: -0.24 to -0.03; p value = 0.010) and MDD (β = -0.16; 95% CI: -0.27 to -0.04; p value = 0.005) predicted worse quantitative lithium response. A higher SCZ PRS was associated with higher rates of medication nonadherence (OR = 1.61; 95% CI: 1.34-1.93; p value = 2e-7). This study indicates that genetic risk for ADHD and depression may influence lithium treatment response. Interestingly, a higher SCZ PRS was associated with poor adherence, which can negatively impact treatment response. Incorporating genetic risk of ADHD, depression, and SCZ in combination with clinical risk may lead to better clinical care for patients with BD.
{"title":"Association of Attention-Deficit/Hyperactivity Disorder and Depression Polygenic Scores with Lithium Response: A Consortium for Lithium Genetics Study.","authors":"Brandon J Coombes, Vincent Millischer, Anthony Batzler, Beth Larrabee, Liping Hou, Sergi Papiol, Urs Heilbronner, Mazda Adli, Kazufumi Akiyama, Nirmala Akula, Azmeraw T Amare, Raffaella Ardau, Barbara Arias, Jean-Michel Aubry, Lena Backlund, Michael Bauer, Bernhard T Baune, Frank Bellivier, Antoni Benabarre, Susanne Bengesser, Abesh Kumar Bhattacharjee, Pablo Cervantes, Hsi-Chung Chen, Caterina Chillotti, Sven Cichon, Scott R Clark, Francesc Colom, Cristiana Cruceanu, Piotr M Czerski, Nina Dalkner, Franziska Degenhardt, Maria Del Zompo, J Raymond DePaulo, Bruno Étain, Peter Falkai, Ewa Ferensztajn-Rochowiak, Andreas J Forstner, Louise Frisen, Sébastien Gard, Julie S Garnham, Fernando S Goes, Maria Grigoroiu-Serbanescu, Paul Grof, Ryota Hashimoto, Joanna Hauser, Stefan Herms, Per Hoffmann, Stephane Jamain, Esther Jiménez, Jean-Pierre Kahn, Layla Kassem, Tadafumi Kato, John R Kelsoe, Sarah Kittel-Schneider, Barbara König, Po-Hsiu Kuo, Ichiro Kusumi, Gonzalo Laje, Mikael Landén, Catharina Lavebratt, Marion Leboyer, Susan G Leckband, Mario Maj, Mirko Manchia, Lina Martinsson, Michael J McCarthy, Susan L McElroy, Philip B Mitchell, Marina Mitjans, Francis M Mondimore, Palmiero Monteleone, Caroline M Nievergelt, Markus M Nöthen, Tomas Novák, Claire O'Donovan, Urban Osby, Norio Ozaki, Andrea Pfennig, Claudia Pisanu, James B Potash, Andreas Reif, Eva Reininghaus, Marcella Rietschel, Guy A Rouleau, Janusz K Rybakowski, Martin Schalling, Peter R Schofield, Klaus Oliver Schubert, Barbara W Schweizer, Giovanni Severino, Tatyana Shekhtman, Paul D Shilling, Katzutaka Shimoda, Christian Simhandl, Claire M Slaney, Alessio Squassina, Thomas Stamm, Pavla Stopkova, Alfonso Tortorella, Gustavo Turecki, Eduard Vieta, Stephanie H Witt, Peter P Zandi, Janice M Fullerton, Martin Alda, Mark A Frye, Thomas G Schulze, Francis J McMahon, Joanna M Biernacka","doi":"10.1159/000519707","DOIUrl":"https://doi.org/10.1159/000519707","url":null,"abstract":"<p><p>Response to lithium varies widely between individuals with bipolar disorder (BD). Polygenic risk scores (PRSs) can uncover pharmacogenomics effects and may help predict drug response. Patients (<i>N</i> = 2,510) with BD were assessed for long-term lithium response in the Consortium on Lithium Genetics using the Retrospective Criteria of Long-Term Treatment Response in Research Subjects with Bipolar Disorder score. PRSs for attention-deficit/hyperactivity disorder (ADHD), major depressive disorder (MDD), and schizophrenia (SCZ) were computed using <i>lassosum</i> and in a model including all three PRSs and other covariates, and the PRS of ADHD (β = -0.14; 95% confidence interval [CI]: -0.24 to -0.03; <i>p</i> value = 0.010) and MDD (β = -0.16; 95% CI: -0.27 to -0.04; <i>p</i> value = 0.005) predicted worse quantitative lithium response. A higher SCZ PRS was associated with higher rates of medication nonadherence (OR = 1.61; 95% CI: 1.34-1.93; <i>p</i> value = 2e-7). This study indicates that genetic risk for ADHD and depression may influence lithium treatment response. Interestingly, a higher SCZ PRS was associated with poor adherence, which can negatively impact treatment response. Incorporating genetic risk of ADHD, depression, and SCZ in combination with clinical risk may lead to better clinical care for patients with BD.</p>","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":" ","pages":"80-89"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740189/pdf/cxp-0007-0080.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40699284","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}
Elizabeth G. Atkinson – Broad Institute of MIT and Harvard, Boston, MA, USA Dimitrios Avramopoulos – Johns Hopkins University, Baltimore, MD, USA Mounira Banasr – University of Toronto, Toronto, ON, Canada Cathy L. Barr – Toronto Western Research Institute, Toronto, ON, Canada Kristen Brennand – Icahn School of Medicine at Mount Sinai, New York, NY, USA William Byerley – University of California, San Francisco, CA, USA Karmel W. Choi – Massachusetts General Hospital, Boston, MA, USA Jonathan R.I. Coleman – King’s College London, London, United Kingdom Kelly Cosgrove – Yale University, New Haven, CT, USA Shareefa Dalvie – University of Cape Town, Cape Town, South Africa Lea K. Davis – Vanderbilt University, Nashville, Nashville, TN, USA Jubao Duan – University of Chicago, Chicago, IL, USA Howard J. Edenberg – Indiana University, Indianapolis, IN, USA Joshua Gordon – National Institute of Mental Health, Bethesda, MD, USA Jeremy Hall – Cardiff University, Cardiff, United Kingdom Steven E. Hyman – Harvard University, Cambridge, MA, USA Emma C. Johnson – Washington University, St. Louis, MO, USA James L. Kennedy – Centre for Addiction and Mental Health, Toronto, ON, Canada John Krystal – Yale School of Medicine, New Haven, CT, USA Ming Li – Kunming Institute of Zoology, Kunming, China Brady Maher – Lieber Institute, Baltimore, MD, USA Anil K. Malhotra – The Zucker Hillside Hospital, Glen Oaks, NY, USA Daniel Martins-de-Souza – University of Campinas, Campinas, Brazil Janitza L. Montalvo-Ortiz – Yale University, West Haven, CT, USA Daniel J. Mueller – Centre for Addiction and Mental Health, Toronto, ON, Canada Roseann E. Peterson – Virginia Commonwealth University, Richmond, VA, USA Konasale M. Prasad – University of Pittsburgh, Pittsburgh, PA, USA Sandra Roige-Sanchez – University of California San Diego, La Jolla, CA, USA Christopher A. Ross – John Hopkins University, Baltimore, MD, USA Takeshi Sakurai – Kyoto University, Kyoto, Japan Dorothy Sit – Northwestern University, Chicago, IL, USA Hang Zhou – Yale University, West Haven, CT, USA Complex Psychiatry
Elizabeth G. Atkinson -麻省理工学院和哈佛大学Broad研究所,马萨诸塞州波士顿Dimitrios Avramopoulos -约翰霍普金斯大学,马里兰州巴尔的摩,美国Mounira Banasr -多伦多大学,安大略省多伦多,加拿大Cathy L. Barr -多伦多西部研究所,安大略省多伦多,加拿大纽约,纽约州,美国,克里斯顿·布伦南-伊坎医学院,西奈山,美国,纽约,加利福尼亚大学,旧金山,美国,卡梅尔·W. Choi -马萨诸塞州总医院,马萨诸塞州波士顿美国Jonathan R.I. Coleman -英国伦敦国王学院Kelly Cosgrove -美国康涅狄格州纽黑文耶鲁大学shaefa Dalvie -南非开普敦开普敦大学Lea K. Davis -田纳西州纳什维尔纳什维尔范德比尔特大学美国伊利诺伊芝加哥大学Howard J. Edenberg -美国印第安纳州印第安纳波利斯州印第安纳大学Joshua Gordon -美国马里兰州贝塞斯达国家心理健康研究所Jeremy Hall -卡迪夫大学卡迪夫英国史蒂文·e·海曼——哈佛大学,剑桥,妈,美国艾玛·c·约翰逊——华盛顿大学,圣路易斯,密苏里州,美国詹姆斯·l·肯尼迪——成瘾与精神健康中心,多伦多,加拿大约翰。克里斯托-耶鲁大学医学院,纽黑文,CT,美国李明——中国科学院昆明动物研究所、昆明,中国布雷迪马赫-利研究所,巴尔的摩,医学博士,美国Anil Malhotra - k Zucker山坡上医院,格伦橡树,纽约,美国丹尼尔Martins-de-Souza -坎皮纳斯大学Janitza L. montalvoo - ortiz -耶鲁大学,西黑文,康涅狄格州,美国Daniel J. Mueller -成瘾和心理健康中心,多伦多,安大略省,加拿大Roseann E. Peterson -弗吉尼亚联邦大学,里士满,弗吉尼亚州,美国,Konasale M. Prasad -匹兹堡大学,宾夕法尼亚州,匹兹堡,美国,Sandra Roige-Sanchez -加州大学圣地亚哥,拉霍亚,加利福尼亚州,美国,克里斯托弗A.罗斯-约翰霍普金斯大学,马里兰州,巴尔的摩,美国,Sakurai Takeshi -京都大学,京都日本Dorothy Sit - Northwestern University, Chicago, IL, USA杭州- Yale University, West Haven, CT, USA复杂精神病学
{"title":"Contents Vol. 7, 2021","authors":"","doi":"10.1159/000521008","DOIUrl":"https://doi.org/10.1159/000521008","url":null,"abstract":"Elizabeth G. Atkinson – Broad Institute of MIT and Harvard, Boston, MA, USA Dimitrios Avramopoulos – Johns Hopkins University, Baltimore, MD, USA Mounira Banasr – University of Toronto, Toronto, ON, Canada Cathy L. Barr – Toronto Western Research Institute, Toronto, ON, Canada Kristen Brennand – Icahn School of Medicine at Mount Sinai, New York, NY, USA William Byerley – University of California, San Francisco, CA, USA Karmel W. Choi – Massachusetts General Hospital, Boston, MA, USA Jonathan R.I. Coleman – King’s College London, London, United Kingdom Kelly Cosgrove – Yale University, New Haven, CT, USA Shareefa Dalvie – University of Cape Town, Cape Town, South Africa Lea K. Davis – Vanderbilt University, Nashville, Nashville, TN, USA Jubao Duan – University of Chicago, Chicago, IL, USA Howard J. Edenberg – Indiana University, Indianapolis, IN, USA Joshua Gordon – National Institute of Mental Health, Bethesda, MD, USA Jeremy Hall – Cardiff University, Cardiff, United Kingdom Steven E. Hyman – Harvard University, Cambridge, MA, USA Emma C. Johnson – Washington University, St. Louis, MO, USA James L. Kennedy – Centre for Addiction and Mental Health, Toronto, ON, Canada John Krystal – Yale School of Medicine, New Haven, CT, USA Ming Li – Kunming Institute of Zoology, Kunming, China Brady Maher – Lieber Institute, Baltimore, MD, USA Anil K. Malhotra – The Zucker Hillside Hospital, Glen Oaks, NY, USA Daniel Martins-de-Souza – University of Campinas, Campinas, Brazil Janitza L. Montalvo-Ortiz – Yale University, West Haven, CT, USA Daniel J. Mueller – Centre for Addiction and Mental Health, Toronto, ON, Canada Roseann E. Peterson – Virginia Commonwealth University, Richmond, VA, USA Konasale M. Prasad – University of Pittsburgh, Pittsburgh, PA, USA Sandra Roige-Sanchez – University of California San Diego, La Jolla, CA, USA Christopher A. Ross – John Hopkins University, Baltimore, MD, USA Takeshi Sakurai – Kyoto University, Kyoto, Japan Dorothy Sit – Northwestern University, Chicago, IL, USA Hang Zhou – Yale University, West Haven, CT, USA Complex Psychiatry","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":"27 1","pages":"I - IV"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74117766","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 : 2021-12-01Epub Date: 2021-08-03DOI: 10.1159/000518819
Zachary A Cordner, Seva G Khambadkone, Shanshan Zhu, Justin Bai, R Rasadokht Forti, Ethan Goodman, Kellie L K Tamashiro, Christopher A Ross
The ANK3 locus has been repeatedly found to confer an increased risk for bipolar disorder. ANK3 codes for Ankyrin-G (Ank-G), a scaffold protein concentrated at axon initial segments, nodes of Ranvier, and dendritic spines, where it organizes voltage-gated sodium and potassium channels and cytoskeletal proteins. Mice with homozygous conditional knockout of Ank-G in the adult forebrain display hyperactivity and reduced anxiety-like behaviors, responsive to mood stabilizers. Their behavior switches to a depression-like phenotype when exposed to chronic social defeat stress (SDS), and then spontaneously reverts to baseline hyperactivity. Ank-G heterozygous conditional knockouts (Ank-G Het cKO) have not previously been characterized. Here, we describe the behavior of Ank-G Het cKO mice compared to littermate controls in the open field, elevated plus maze, and forced swim test, under both unstressed and stressed conditions. We found that Ank-G Het cKO is not significantly different from controls at baseline or after chronic SDS. The chronic stress-induced "depression-like" behavioral phenotype is persistent for at least 28 days and is responsive to fluoxetine. Strikingly, Ank-G Het cKO mice display increased sensitivity to a short duration SDS, which does not affect controls. The heterozygous Ank-G genetic model may provide novel insights into the role of Ank-G in the pathophysiology of stress sensitivity and "depression-like" phenotypes and could be useful for studying Ank-G-related gene-environment interactions.
ANK3 基因座多次被发现会增加躁郁症的患病风险。ANK3编码Ankyrin-G(Ank-G),这是一种支架蛋白,主要集中在轴突起始节段、Ranvier节和树突棘,它在这些地方组织电压门控钠和钾通道以及细胞骨架蛋白。在成年前脑中同源条件性敲除 Ank-G 的小鼠表现出多动和焦虑样行为减少,对情绪稳定剂有反应。当暴露于慢性社会挫败应激(SDS)时,它们的行为会转为抑郁样表型,然后自发地恢复到基线多动状态。Ank-G 杂合子条件性基因敲除(Ank-G Het cKO)之前还没有被描述过。在这里,我们描述了 Ank-G Het cKO 小鼠与同卵对照组相比,在非应激和应激条件下,在空地、高架加迷宫和强迫游泳试验中的行为。我们发现,Ank-G Het cKO 在基线和慢性 SDS 后与对照组没有显著差异。慢性应激诱导的 "抑郁样 "行为表型可持续至少 28 天,并且对氟西汀有反应。令人吃惊的是,Ank-G Het cKO 小鼠对短时间 SDS 的敏感性增加,而对照组不受影响。杂合子Ank-G基因模型可能会对Ank-G在应激敏感性和 "抑郁样 "表型的病理生理学中的作用提供新的见解,并有助于研究Ank-G相关基因与环境的相互作用。
{"title":"Ankyrin-G Heterozygous Knockout Mice Display Increased Sensitivity to Social Defeat Stress.","authors":"Zachary A Cordner, Seva G Khambadkone, Shanshan Zhu, Justin Bai, R Rasadokht Forti, Ethan Goodman, Kellie L K Tamashiro, Christopher A Ross","doi":"10.1159/000518819","DOIUrl":"10.1159/000518819","url":null,"abstract":"<p><p>The <i>ANK3</i> locus has been repeatedly found to confer an increased risk for bipolar disorder. <i>ANK3</i> codes for Ankyrin-G (Ank-G), a scaffold protein concentrated at axon initial segments, nodes of Ranvier, and dendritic spines, where it organizes voltage-gated sodium and potassium channels and cytoskeletal proteins. Mice with homozygous conditional knockout of Ank-G in the adult forebrain display hyperactivity and reduced anxiety-like behaviors, responsive to mood stabilizers. Their behavior switches to a depression-like phenotype when exposed to chronic social defeat stress (SDS), and then spontaneously reverts to baseline hyperactivity. Ank-G heterozygous conditional knockouts (Ank-G Het cKO) have not previously been characterized. Here, we describe the behavior of Ank-G Het cKO mice compared to littermate controls in the open field, elevated plus maze, and forced swim test, under both unstressed and stressed conditions. We found that Ank-G Het cKO is not significantly different from controls at baseline or after chronic SDS. The chronic stress-induced \"depression-like\" behavioral phenotype is persistent for at least 28 days and is responsive to fluoxetine. Strikingly, Ank-G Het cKO mice display increased sensitivity to a short duration SDS, which does not affect controls. The heterozygous Ank-G genetic model may provide novel insights into the role of Ank-G in the pathophysiology of stress sensitivity and \"depression-like\" phenotypes and could be useful for studying Ank-G-related gene-environment interactions.</p>","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":" ","pages":"71-79"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740233/pdf/cxp-0007-0071.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40670821","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}
A. Shahzad, Nazri M. Nawi, M. Z. Rehman, Abdullah Khan
In this modern era, people utilise the web to share information and to deliver services and products. The information seekers use different search engines (SEs) such as Google, Bing, and Yahoo as tools to search for products, services, and information. However, web spamming is one of the most significant issues encountered by SEs because it dramatically affects the quality of SE results. Web spamming’s economic impact is enormous because web spammers index massive free advertising data on SEs to increase the volume of web traffic on a targeted website. Spammers trick an SE into ranking irrelevant web pages higher than relevant web pages in the search engine results pages (SERPs) using different web-spamming techniques. Consequently, these high-ranked unrelated web pages contain insufficient or inappropriate information for the user. To detect the spam web pages, several researchers from industry and academia are working. No efficient technique that is capable of catching all spam web pages on the World Wide Web (WWW) has been presented yet. This research is an attempt to propose an improved framework for content- and link-based web-spam identification. The framework uses stopwords, keywords’ frequency, part of speech (POS) ratio, spam keywords database, and copied-content algorithms for content-based web-spam detection. For link-based web-spam detection, we initially exposed the relationship network behind the link-based web spamming and then used the paid-link database, neighbour pages, spam signals, and link-farm algorithms. Finally, we combined all the content- and link-based spam identification algorithms to identify both types of spam. To conduct experiments and to obtain threshold values, WEBSPAM-UK2006 and WEBSPAM-UK2007 datasets were used. A promising F-measure of 79.6% with 81.2% precision shows the applicability and effectiveness of the proposed approach.
{"title":"An Improved Framework for Content- and Link-Based Web-Spam Detection: A Combined Approach","authors":"A. Shahzad, Nazri M. Nawi, M. Z. Rehman, Abdullah Khan","doi":"10.1155/2021/6625739","DOIUrl":"https://doi.org/10.1155/2021/6625739","url":null,"abstract":"In this modern era, people utilise the web to share information and to deliver services and products. The information seekers use different search engines (SEs) such as Google, Bing, and Yahoo as tools to search for products, services, and information. However, web spamming is one of the most significant issues encountered by SEs because it dramatically affects the quality of SE results. Web spamming’s economic impact is enormous because web spammers index massive free advertising data on SEs to increase the volume of web traffic on a targeted website. Spammers trick an SE into ranking irrelevant web pages higher than relevant web pages in the search engine results pages (SERPs) using different web-spamming techniques. Consequently, these high-ranked unrelated web pages contain insufficient or inappropriate information for the user. To detect the spam web pages, several researchers from industry and academia are working. No efficient technique that is capable of catching all spam web pages on the World Wide Web (WWW) has been presented yet. This research is an attempt to propose an improved framework for content- and link-based web-spam identification. The framework uses stopwords, keywords’ frequency, part of speech (POS) ratio, spam keywords database, and copied-content algorithms for content-based web-spam detection. For link-based web-spam detection, we initially exposed the relationship network behind the link-based web spamming and then used the paid-link database, neighbour pages, spam signals, and link-farm algorithms. Finally, we combined all the content- and link-based spam identification algorithms to identify both types of spam. To conduct experiments and to obtain threshold values, WEBSPAM-UK2006 and WEBSPAM-UK2007 datasets were used. A promising F-measure of 79.6% with 81.2% precision shows the applicability and effectiveness of the proposed approach.","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":"48 1","pages":"6625739:1-6625739:18"},"PeriodicalIF":0.0,"publicationDate":"2021-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77676861","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}
Green innovation investments have rapidly grown since 2000. Green innovation indexes play important roles and are typically constructed by screening and indexing. However, Nobel Laureate Markowitz emphasizes portfolio selection instead of security selection and accentuates that “A good portfolio is more than a long list of good stocks.” Moreover, the screening-indexing strategies ignore that investors can take green innovation as an additional objective and thus gain additional utility. We consequently construct 3-objective portfolio selection for green innovation in addition to variance and expected return. An efficient frontier of portfolio selection then extends to an efficient surface which is a panorama of the optimal variance, expected return, and expected green innovation. Investors thus fully envisage the trade-offs and enjoy the freedom of choosing preferred portfolios on the surface. In contrast, the screening-indexing strategies inflexibly leave investors with only one point (i.e., the green innovation index). As the originality, we prove in a theorem that there typically exists a curve on the efficient surface so all portfolios on the curve dominate the green innovation index. We test the dominance by component stocks of China Securities Index 300 and obtain affirmative results out of sample. The results still hold in robustness tests. At last, we classify green innovation into categories, further model the categories by general k -objective portfolio selection, and still illustrate the dominance. Consequently, investors can consider and control each category.
{"title":"Constructing Multiple-Objective Portfolio Selection for Green Innovation and Dominating Green Innovation Indexes","authors":"Meng Li, Kezhi Liao, Y. Qi, Tong Liu","doi":"10.17632/4YKNHCK825.1","DOIUrl":"https://doi.org/10.17632/4YKNHCK825.1","url":null,"abstract":"Green innovation investments have rapidly grown since 2000. Green innovation indexes play important roles and are typically constructed by screening and indexing. However, Nobel Laureate Markowitz emphasizes portfolio selection instead of security selection and accentuates that “A good portfolio is more than a long list of good stocks.” Moreover, the screening-indexing strategies ignore that investors can take green innovation as an additional objective and thus gain additional utility. We consequently construct 3-objective portfolio selection for green innovation in addition to variance and expected return. An efficient frontier of portfolio selection then extends to an efficient surface which is a panorama of the optimal variance, expected return, and expected green innovation. Investors thus fully envisage the trade-offs and enjoy the freedom of choosing preferred portfolios on the surface. In contrast, the screening-indexing strategies inflexibly leave investors with only one point (i.e., the green innovation index). As the originality, we prove in a theorem that there typically exists a curve on the efficient surface so all portfolios on the curve dominate the green innovation index. We test the dominance by component stocks of China Securities Index 300 and obtain affirmative results out of sample. The results still hold in robustness tests. At last, we classify green innovation into categories, further model the categories by general \u0000 \u0000 k\u0000 \u0000 -objective portfolio selection, and still illustrate the dominance. Consequently, investors can consider and control each category.","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":"74 1","pages":"8263720:1-8263720:19"},"PeriodicalIF":0.0,"publicationDate":"2021-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79605456","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 : 2021-08-01Epub Date: 2021-02-08DOI: 10.1159/000515066
Michael Y Bai, David B Lovejoy, Gilles J Guillemin, Rouba Kozak, Trevor W Stone, Maju Mathew Koola
The kynurenine pathway (KP) is a major route for L-tryptophan (L-TRP) metabolism, yielding a variety of bioactive compounds including kynurenic acid (KYNA), 3-hydroxykynurenine (3-HK), quinolinic acid (QUIN), and picolinic acid (PIC). These tryptophan catabolites are involved in the pathogenesis of many neuropsychiatric disorders, particularly when the KP becomes dysregulated. Accordingly, the enzymes that regulate the KP such as indoleamine 2,3-dioxygenase (IDO)/tryptophan 2,3-dioxygenase, kynurenine aminotransferases (KATs), and kynurenine 3-monooxygenase (KMO) represent potential drug targets as enzymatic inhibition can favorably rebalance KP metabolite concentrations. In addition, the galantamine-memantine combination, through its modulatory effects at the alpha7 nicotinic acetylcholine receptors and N-methyl-D-aspartate receptors, may counteract the effects of KYNA. The aim of this review is to highlight the effectiveness of IDO-1, KAT II, and KMO inhibitors, as well as the galantamine-memantine combination in the modulation of different KP metabolites. KAT II inhibitors are capable of decreasing the KYNA levels in the rat brain by a maximum of 80%. KMO inhibitors effectively reduce the central nervous system (CNS) levels of 3-HK, while markedly boosting the brain concentration of KYNA. Emerging data suggest that the galantamine-memantine combination also lowers L-TRP, kynurenine, KYNA, and PIC levels in humans. Presently, there are only 2 pathophysiological mechanisms (cholinergic and glutamatergic) that are FDA approved for the treatment of cognitive dysfunction for which purpose the galantamine-memantine combination has been designed for clinical use against Alzheimer's disease. The alpha7 nicotinic-NMDA hypothesis targeted by the galantamine-memantine combination has been implicated in the pathophysiology of various CNS diseases. Similarly, KYNA is well capable of modulating the neuropathophysiology of these disorders. This is known as the KYNA-centric hypothesis, which may be implicated in the management of certain neuropsychiatric conditions. In line with this hypothesis, KYNA may be considered as the "conductor of the orchestra" for the major pathophysiological mechanisms underlying CNS disorders. Therefore, there is great opportunity to further explore and compare the biological effects of these therapeutic modalities in animal models with a special focus on their effects on KP metabolites in the CNS and with the ultimate goal of progressing to clinical trials for many neuropsychiatric diseases.
{"title":"Galantamine-Memantine Combination and Kynurenine Pathway Enzyme Inhibitors in the Treatment of Neuropsychiatric Disorders.","authors":"Michael Y Bai, David B Lovejoy, Gilles J Guillemin, Rouba Kozak, Trevor W Stone, Maju Mathew Koola","doi":"10.1159/000515066","DOIUrl":"10.1159/000515066","url":null,"abstract":"<p><p>The kynurenine pathway (KP) is a major route for L-tryptophan (L-TRP) metabolism, yielding a variety of bioactive compounds including kynurenic acid (KYNA), 3-hydroxykynurenine (3-HK), quinolinic acid (QUIN), and picolinic acid (PIC). These tryptophan catabolites are involved in the pathogenesis of many neuropsychiatric disorders, particularly when the KP becomes dysregulated. Accordingly, the enzymes that regulate the KP such as indoleamine 2,3-dioxygenase (IDO)/tryptophan 2,3-dioxygenase, kynurenine aminotransferases (KATs), and kynurenine 3-monooxygenase (KMO) represent potential drug targets as enzymatic inhibition can favorably rebalance KP metabolite concentrations. In addition, the galantamine-memantine combination, through its modulatory effects at the alpha7 nicotinic acetylcholine receptors and N-methyl-D-aspartate receptors, may counteract the effects of KYNA. The aim of this review is to highlight the effectiveness of IDO-1, KAT II, and KMO inhibitors, as well as the galantamine-memantine combination in the modulation of different KP metabolites. KAT II inhibitors are capable of decreasing the KYNA levels in the rat brain by a maximum of 80%. KMO inhibitors effectively reduce the central nervous system (CNS) levels of 3-HK, while markedly boosting the brain concentration of KYNA. Emerging data suggest that the galantamine-memantine combination also lowers L-TRP, kynurenine, KYNA, and PIC levels in humans. Presently, there are only 2 pathophysiological mechanisms (cholinergic and glutamatergic) that are FDA approved for the treatment of cognitive dysfunction for which purpose the galantamine-memantine combination has been designed for clinical use against Alzheimer's disease. The alpha7 nicotinic-NMDA hypothesis targeted by the galantamine-memantine combination has been implicated in the pathophysiology of various CNS diseases. Similarly, KYNA is well capable of modulating the neuropathophysiology of these disorders. This is known as the KYNA-centric hypothesis, which may be implicated in the management of certain neuropsychiatric conditions. In line with this hypothesis, KYNA may be considered as the \"conductor of the orchestra\" for the major pathophysiological mechanisms underlying CNS disorders. Therefore, there is great opportunity to further explore and compare the biological effects of these therapeutic modalities in animal models with a special focus on their effects on KP metabolites in the CNS and with the ultimate goal of progressing to clinical trials for many neuropsychiatric diseases.</p>","PeriodicalId":72654,"journal":{"name":"Complex psychiatry","volume":"7 1-2","pages":"19-33"},"PeriodicalIF":0.0,"publicationDate":"2021-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1159/000515066","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"39905714","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}