1
|
Faraji M, Viera-Resto OA, Berrios BJ, Bizon JL, Setlow B. Effects of systemic oxytocin receptor activation and blockade on risky decision making in female and male rats. Behav Neurosci 2025; 139:137-152. [PMID: 40193422 PMCID: PMC12052479 DOI: 10.1037/bne0000621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/09/2025]
Abstract
The neuropeptide oxytocin is traditionally known for its roles in parturition, lactation, and social behavior. Other data, however, show that oxytocin can modulate behaviors outside of these contexts, including drug self-administration and some aspects of cost-benefit decision making. Here we used a pharmacological approach to investigate the contributions of oxytocin signaling to decision making under risk of explicit punishment. Female and male Long-Evans rats were trained on a risky decision-making task in which they chose between a small, "safe" food reward and a large, "risky" food reward that was accompanied by varying probabilities of mild footshock. Once stable choice behavior emerged, rats were tested in the task following acute intraperitoneal injections of oxytocin or the oxytocin receptor antagonist L-368,899. Oxytocin dose-dependently reduced preference for the large, risky reward only in females, whereas L-368,899 dose-dependently reduced preference for the large, risky reward in both sexes. Control experiments showed that these effects could not be accounted for by drug-induced alterations in preference for the large reward or shock sensitivity. Together, these results reveal partially sex-dependent effects of oxytocin signaling on risky decision making in rats. (PsycInfo Database Record (c) 2025 APA, all rights reserved).
Collapse
Affiliation(s)
- Mojdeh Faraji
- Department of Psychiatry, University of Florida
- Center for Addiction Research and Education, University of Florida
| | | | | | - Jennifer L. Bizon
- Center for Addiction Research and Education, University of Florida
- Department of Neuroscience, University of Florida
- McKnight Brain Institute, University of Florida
| | - Barry Setlow
- Department of Psychiatry, University of Florida
- Center for Addiction Research and Education, University of Florida
- McKnight Brain Institute, University of Florida
| |
Collapse
|
2
|
Koyuncu Z, Aslantürk Halil K, Selçukoğlu Kilimci Ö, Arslan B, Tanrıöver Aydın E, Yücel E, Arvas YU, Aksu NE, Aksoy Poyraz C, Demirel ÖF, Küçük L, Doğangün B, Weiss MD, Tarakçıoğlu MC. The moderating role of gender on the relationship between childhood attention deficit and hyperactivity symptoms and functional impairment. PLoS One 2025; 20:e0321767. [PMID: 40238745 PMCID: PMC12002437 DOI: 10.1371/journal.pone.0321767] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Accepted: 03/11/2025] [Indexed: 04/18/2025] Open
Abstract
This study aimed to examine the link between childhood attention deficit and hyperactivity symptoms (CAS) and functional impairment in university students, while also investigating whether gender moderates this relationship. Six hundred and eighty university students participated in this cross-sectional study. The assessment was conducted using the Wender-Utah Rating Scale-25 (WURS), the Brief Symptom Inventory (BSI), and the Weiss Functional Impairment Rating Scale - Self Report (WFIRS-S). The relationship between CAS and general and domain-based functional impairment was evaluated using eight moderation models. Control variables, including age and concomitant psychiatric symptoms (five BSI scores), were added to the models. We observed positive associations between WURS and all WFIRS-S scores. In addition, WURS significantly interacted with gender in explaining WFIRS-S total (t = -2.26, p =.024). Gender also moderated the link between WURS and impairments in social (t = -2.00, p =.046) and risk domains (t = -2.86, p =.004). Accordingly, the associations between CAS and overall functional impairment, as well as impairments in social and risk domains, were stronger in men than in women. These findings highlight the significant role of CAS in functional impairments among university students, with gender emerging as a key moderating factor, particularly in social and risk-related domains.
Collapse
Affiliation(s)
- Zehra Koyuncu
- Department of Child and Adolescent Psychiatry, Cerrahpasa Faculty of Medicine, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Kübra Aslantürk Halil
- Florence Nightingale Faculty of Nursing, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Özge Selçukoğlu Kilimci
- Department of Psychiatry, Cerrahpasa Faculty of Medicine, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Büşra Arslan
- Department of Child and Adolescent Psychiatry, Cerrahpasa Faculty of Medicine, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Ezgi Tanrıöver Aydın
- Department of Psychiatry, Cerrahpasa Faculty of Medicine, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Emine Yücel
- Department of Psychology, Selçuk University, Konya, Turkey
| | - Yekta Uğur Arvas
- Cerrahpasa Faculty of Medicine, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Nazan Ebru Aksu
- Cerrahpasa Faculty of Medicine, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Cana Aksoy Poyraz
- Department of Psychiatry, Cerrahpasa Faculty of Medicine, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Ömer Faruk Demirel
- Department of Psychiatry, Cerrahpasa Faculty of Medicine, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Leyla Küçük
- Florence Nightingale Faculty of Nursing, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Burak Doğangün
- Department of Child and Adolescent Psychiatry, Cerrahpasa Faculty of Medicine, Istanbul University-Cerrahpasa, Istanbul, Turkey
| | - Margaret Danielle Weiss
- Cambridge Health Alliance, Harvard Medical School, Cambridge, Massachusetts, United States of America
| | - Mahmut Cem Tarakçıoğlu
- Department of Child and Adolescent Psychiatry, Cerrahpasa Faculty of Medicine, Istanbul University-Cerrahpasa, Istanbul, Turkey
| |
Collapse
|
3
|
Konzok J, Gorski M, Winkler TW, Baumeister SE, Warrier V, Leitzmann MF, Baurecht H. Child maltreatment as a transdiagnostic risk factor for the externalizing dimension: a Mendelian randomization study. Mol Psychiatry 2025; 30:567-573. [PMID: 39174650 PMCID: PMC11746131 DOI: 10.1038/s41380-024-02700-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 08/14/2024] [Accepted: 08/15/2024] [Indexed: 08/24/2024]
Abstract
Observational studies suggest that child maltreatment increases the risk of externalizing spectrum disorders such as attention deficit hyperactivity disorder (ADHD), conduct disorder (CD), antisocial personality disorder (ASPD), and substance use disorder (SUD). Yet, only few of such associations have been investigated by approaches that provide strong evidence for causation, such as Mendelian Randomization (MR). Establishing causal inference is essential given the growing recognition of gene-environment correlations, which can confound observational research in the context of childhood maltreatment. Evaluating causality between child maltreatment and the externalizing phenotypes, we used genome-wide association study (GWAS) summary data for child maltreatment (143,473 participants), ADHD (20,183 cases; 35,191 controls), CD (451 cases; 256,859 controls), ASPD (381 cases; 252,877 controls), alcohol use disorder (AUD; 13,422 cases; 244,533 controls), opioid use disorder (OUD; 775 cases; 255,921 controls), and cannabinoid use disorder (CUD; 14,080 cases; 343,726 controls). We also generated a latent variable 'common externalizing factor' (EXT) using genomic structural equation modeling. Genetically predicted childhood maltreatment was consistently associated with ADHD (odds ratio [OR], 10.09; 95%-CI, 4.76-21.40; P = 1.63 × 10-09), AUD (OR, 3.72; 95%-CI, 1.85-7.52; P = 2.42 × 10-04), and the EXT (OR, 2.64; 95%-CI, 1.52-4.60; P = 5.80 × 10-04) across the different analyses and pleiotropy-robust methods. A subsequent GWAS on childhood maltreatment and the externalizing dimension from Externalizing Consortium (EXT-CON) confirmed these results. Two of the top five genes with the strongest associations in EXT GWAS, CADM2 and SEMA6D, are also ranked among the top 10 in the EXT-CON. The present results confirm the existence of a common externalizing factor and an increasing vulnerability caused by child maltreatment, with crucial implications for prevention. However, the partly diverging results also indicate that specific influences impact individual phenotypes separately.
Collapse
Affiliation(s)
- Julian Konzok
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany.
| | - Mathias Gorski
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Sebastian E Baumeister
- Institute of Health Services Research in Dentistry, University of Münster, Münster, Germany
| | - Varun Warrier
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - Michael F Leitzmann
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| | - Hansjörg Baurecht
- Department of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany
| |
Collapse
|
4
|
Humińska-Lisowska K. Dopamine in Sports: A Narrative Review on the Genetic and Epigenetic Factors Shaping Personality and Athletic Performance. Int J Mol Sci 2024; 25:11602. [PMID: 39519153 PMCID: PMC11546834 DOI: 10.3390/ijms252111602] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2024] [Revised: 10/22/2024] [Accepted: 10/27/2024] [Indexed: 11/16/2024] Open
Abstract
This narrative review examines the relationship between dopamine-related genetic polymorphisms, personality traits, and athletic success. Advances in sports genetics have identified specific single nucleotide polymorphisms (SNPs) in dopamine-related genes linked to personality traits crucial for athletic performance, such as motivation, cognitive function, and emotional resilience. This review clarifies how genetic variations can influence athletic predisposition through dopaminergic pathways and environmental interactions. Key findings reveal associations between specific SNPs and enhanced performance in various sports. For example, polymorphisms such as COMT Val158Met rs4680 and BDNF Val66Met rs6265 are associated with traits that could benefit performance, such as increased focus, stress resilience and conscientiousness, especially in martial arts. DRD3 rs167771 is associated with higher agreeableness, benefiting teamwork in sports like football. This synthesis underscores the multidimensional role of genetics in shaping athletic ability and advocates for integrating genetic profiling into personalized training to optimize performance and well-being. However, research gaps remain, including the need for standardized training protocols and exploring gene-environment interactions in diverse populations. Future studies should focus on how genetic and epigenetic factors can inform tailored interventions to enhance both physical and psychological aspects of athletic performance. By bridging genetics, personality psychology, and exercise science, this review paves the way for innovative training and performance optimization strategies.
Collapse
Affiliation(s)
- Kinga Humińska-Lisowska
- Faculty of Physical Education, Gdansk University of Physical Education and Sport, 80-336 Gdańsk, Poland
| |
Collapse
|
5
|
Thorpe HHA, Fontanillas P, Meredith JJ, Jennings MV, Cupertino RB, Pakala S, 23andMe Research Team, Elson SL, Khokhar JY, Davis LK, Johnson EC, Palmer AA, Sanchez-Roige S. Genome-wide association studies of lifetime and frequency cannabis use in 131,895 individuals. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.14.24308946. [PMID: 38947071 PMCID: PMC11213095 DOI: 10.1101/2024.06.14.24308946] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Cannabis is one of the most widely used drugs globally. Decriminalization of cannabis is further increasing cannabis consumption. We performed genome-wide association studies (GWASs) of lifetime (N=131,895) and frequency (N=73,374) of cannabis use. Lifetime cannabis use GWAS identified two loci, one near CADM2 (rs11922956, p=2.40E-11) and another near GRM3 (rs12673181, p=6.90E-09). Frequency of use GWAS identified one locus near CADM2 (rs4856591, p=8.10E-09; r2 =0.76 with rs11922956). Both traits were heritable and genetically correlated with previous GWASs of lifetime use and cannabis use disorder (CUD), as well as other substance use and cognitive traits. Polygenic scores (PGSs) for lifetime and frequency of cannabis use associated cannabis use phenotypes in AllofUs participants. Phenome-wide association study of lifetime cannabis use PGS in a hospital cohort replicated associations with substance use and mood disorders, and uncovered associations with celiac and infectious diseases. This work demonstrates the value of GWASs of CUD transition risk factors.
Collapse
Affiliation(s)
- Hayley H A Thorpe
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | | | - John J Meredith
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Mariela V Jennings
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Renata B Cupertino
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Shreya Pakala
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | | | | | - Jibran Y Khokhar
- Department of Anatomy and Cell Biology, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Lea K Davis
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Psychiatry and Behavioral Sciences, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| |
Collapse
|
6
|
Faraji M, Viera-Resto OA, Berrios BJ, Bizon JL, Setlow B. Effects of systemic oxytocin receptor activation and blockade on risky decision making in female and male rats. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.13.593981. [PMID: 38798601 PMCID: PMC11118492 DOI: 10.1101/2024.05.13.593981] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
The neuropeptide oxytocin is traditionally known for its roles in parturition, lactation, and social behavior. Other data, however, show that oxytocin can modulate behaviors outside of these contexts, including drug self-administration and some aspects of cost-benefit decision making. Here we used a pharmacological approach to investigate the contributions of oxytocin signaling to decision making under risk of explicit punishment. Female and male Long-Evans rats were trained on a risky decision-making task in which they chose between a small, "safe" food reward and a large, "risky" food reward that was accompanied by varying probabilities of mild footshock. Once stable choice behavior emerged, rats were tested in the task following acute intraperitoneal injections of oxytocin or the oxytocin receptor antagonist L-368,899. Neither drug affected task performance in males. In females, however, both oxytocin and L-368,899 caused a dose-dependent reduction in preference for large risky reward. Control experiments showed that these effects could not be accounted for by alterations in food motivation or shock sensitivity. Together, these results reveal a sex-dependent effect of oxytocin signaling on risky decision making in rats.
Collapse
Affiliation(s)
- Mojdeh Faraji
- Department of Psychiatry, University of Florida
- Center for Addiction Research and Education, University of Florida
| | | | | | - Jennifer L Bizon
- Center for Addiction Research and Education, University of Florida
- Department of Neuroscience, University of Florida
- McKnight Brain Institute, University of Florida
| | - Barry Setlow
- Department of Psychiatry, University of Florida
- Center for Addiction Research and Education, University of Florida
- McKnight Brain Institute, University of Florida
| |
Collapse
|
7
|
Arellano Spano M, Morris TT, Davies NM, Hughes A. Genetic associations of risk behaviours and educational achievement. Commun Biol 2024; 7:435. [PMID: 38600303 PMCID: PMC11006670 DOI: 10.1038/s42003-024-06091-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 03/22/2024] [Indexed: 04/12/2024] Open
Abstract
Risk behaviours are common in adolescent and persist into adulthood, people who engage in more risk behaviours are more likely to have lower educational attainment. We applied genetic causal inference methods to explore the causal relationship between adolescent risk behaviours and educational achievement. Risk behaviours were phenotypically associated with educational achievement at age 16 after adjusting for confounders (-0.11, 95%CI: -0.11, -0.09). Genomic-based restricted maximum likelihood (GREML) results indicated that both traits were heritable and have a shared genetic architecture (Riskh 2 = 0.18, 95% CI: -0.11,0.47; educationh 2 = 0.60, 95%CI: 0.50,0.70). Consistent with the phenotypic results, genetic variation associated with risk behaviour was negatively associated with education (r g = -0.51, 95%CI: -1.04,0.02). Lastly, the bidirectional MR results indicate that educational achievement or a closely related trait is likely to affect risk behaviours PGI (β=-1.04, 95% CI: -1.41, -0.67), but we found little evidence that the genetic variation associated with risk behaviours affected educational achievement (β=0.00, 95% CI: -0.24,0.24). The results suggest engagement in risk behaviour may be partly driven by educational achievement or a closely related trait.
Collapse
Affiliation(s)
- Michelle Arellano Spano
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, BS8 2BN, United Kingdom.
- Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, United Kingdom.
| | - Tim T Morris
- Centre for Longitudinal Studies, Social Research Institute, University College London, London, United Kingdom
| | - Neil M Davies
- Division of Psychiatry, University College London, Maple House, 149 Tottenham Court Rd, London, W1T 7NF, United Kingdom
- Department of Statistical Sciences, University College London, London, WC1E 6BT, United Kingdom
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, 7491, Trondheim, Norway
| | - Amanda Hughes
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, Bristol, BS8 2BN, United Kingdom
- Population Health Sciences, Bristol Medical School, University of Bristol, Barley House, Oakfield Grove, Bristol, BS8 2BN, United Kingdom
| |
Collapse
|
8
|
Wu X, Luo G, Dong Z, Zheng W, Jia G. Integrated Pleiotropic Gene Set Unveils Comorbidity Insights across Digestive Cancers and Other Diseases. Genes (Basel) 2024; 15:478. [PMID: 38674412 PMCID: PMC11049963 DOI: 10.3390/genes15040478] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Revised: 03/31/2024] [Accepted: 04/04/2024] [Indexed: 04/28/2024] Open
Abstract
Comorbidities are prevalent in digestive cancers, intensifying patient discomfort and complicating prognosis. Identifying potential comorbidities and investigating their genetic connections in a systemic manner prove to be instrumental in averting additional health challenges during digestive cancer management. Here, we investigated 150 diseases across 18 categories by collecting and integrating various factors related to disease comorbidity, such as disease-associated SNPs or genes from sources like MalaCards, GWAS Catalog and UK Biobank. Through this extensive analysis, we have established an integrated pleiotropic gene set comprising 548 genes in total. Particularly, there enclosed the genes encoding major histocompatibility complex or related to antigen presentation. Additionally, we have unveiled patterns in protein-protein interactions and key hub genes/proteins including TP53, KRAS, CTNNB1 and PIK3CA, which may elucidate the co-occurrence of digestive cancers with certain diseases. These findings provide valuable insights into the molecular origins of comorbidity, offering potential avenues for patient stratification and the development of targeted therapies in clinical trials.
Collapse
Affiliation(s)
- Xinnan Wu
- Institute of Public-Safety and Big Data, College of Data Science, Taiyuan University of Technology, University Street, Yuci District, Jinzhong 030600, China;
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; (G.L.); (Z.D.)
| | - Guangwen Luo
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; (G.L.); (Z.D.)
| | - Zhaonian Dong
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; (G.L.); (Z.D.)
| | - Wen Zheng
- Institute of Public-Safety and Big Data, College of Data Science, Taiyuan University of Technology, University Street, Yuci District, Jinzhong 030600, China;
| | - Gengjie Jia
- Shenzhen Branch, Guangdong Laboratory of Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture and Rural Affairs, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen 518120, China; (G.L.); (Z.D.)
| |
Collapse
|
9
|
Koller D, Mitjans M, Kouakou M, Friligkou E, Cabrera-Mendoza B, Deak JD, Llonga N, Pathak GA, Stiltner B, Løkhammer S, Levey DF, Zhou H, Hatoum AS, Kember RL, Kranzler HR, Stein MB, Corominas R, Demontis D, Artigas MS, Ramos-Quiroga JA, Gelernter J, Ribasés M, Cormand B, Polimanti R. Genetic contribution to the comorbidity between attention-deficit/hyperactivity disorder and substance use disorders. Psychiatry Res 2024; 333:115758. [PMID: 38335780 PMCID: PMC11157987 DOI: 10.1016/j.psychres.2024.115758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 01/17/2024] [Accepted: 01/23/2024] [Indexed: 02/12/2024]
Abstract
We characterized the genetic architecture of the attention-deficit hyperactivity disorder-substance use disorder (ADHD-SUD) relationship by investigating genetic correlation, causality, pleiotropy, and common polygenic risk. Summary statistics from genome-wide association studies (GWAS) were used to investigate ADHD (Neff = 51,568), cannabis use disorder (CanUD, Neff = 161,053), opioid use disorder (OUD, Neff = 57,120), problematic alcohol use (PAU, Neff = 502,272), and problematic tobacco use (PTU, Neff = 97,836). ADHD, CanUD, and OUD GWAS meta-analyses included cohorts with case definitions based on different diagnostic criteria. PAU GWAS combined information related to alcohol use disorder, alcohol dependence, and the items related to alcohol problematic consequences assessed by the alcohol use disorders identification test. PTU GWAS was generated a multi-trait analysis including information regarding Fagerström Test for Nicotine Dependence and cigarettes per day. Linkage disequilibrium score regression analyses indicated positive genetic correlation with CanUD, OUD, PAU, and PTU. Genomic structural equation modeling showed that these genetic correlations were related to two latent factors: one including ADHD, CanUD, and PTU and the other with OUD and PAU. The evidence of a causal effect of PAU and PTU on ADHD was stronger than the reverse in the two-sample Mendelian randomization analysis. Conversely, similar strength of evidence was found between ADHD and CanUD. CADM2 rs62250713 was a pleiotropic SNP between ADHD and all SUDs. We found seven, one, and twenty-eight pleiotropic variants between ADHD and CanUD, PAU, and PTU, respectively. Finally, OUD, CanUD, and PAU PRS were associated with increased odds of ADHD. Our findings demonstrated the contribution of multiple pleiotropic mechanisms to the comorbidity between ADHD and SUDs.
Collapse
Affiliation(s)
- Dora Koller
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA; Department of Genetics, Microbiology, and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain.
| | - Marina Mitjans
- Department of Genetics, Microbiology, and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Institute of Biomedicine of the University of Barcelona (IBUB), Barcelona, Catalonia Spain; Sant Joan de Déu Research Institute (IR-SJD), Esplugues de Llobregat, Catalonia, Spain
| | - Manuela Kouakou
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA
| | - Eleni Friligkou
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA
| | - Brenda Cabrera-Mendoza
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA
| | - Joseph D Deak
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA
| | - Natalia Llonga
- Psychiatric Genetics Unit, Group of Psychiatry Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Gita A Pathak
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA
| | - Brendan Stiltner
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA
| | - Solveig Løkhammer
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway; Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Daniel F Levey
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA
| | - Hang Zhou
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA
| | - Alexander S Hatoum
- Department of Psychological and Brain Sciences, Washington University in Saint Louis, St. Louis, MO, USA
| | - Rachel L Kember
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; Mental Illness Research, Education and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, USA
| | - Henry R Kranzler
- Department of Psychiatry, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA; Mental Illness Research, Education and Clinical Center, Veterans Integrated Service Network 4, Crescenz Veterans Affairs Medical Center, Philadelphia, Pennsylvania, USA
| | - Murray B Stein
- Department of Psychiatry, University of California, San Diego, La Jolla, USA; Herbert Wertheim School of Public Health, University of California, San Diego, La Jolla, USA; VA San Diego Healthcare System, San Diego, CA, La Jolla, USA
| | - Roser Corominas
- Department of Genetics, Microbiology, and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain; Institute of Biomedicine of the University of Barcelona (IBUB), Barcelona, Catalonia Spain; Sant Joan de Déu Research Institute (IR-SJD), Esplugues de Llobregat, Catalonia, Spain; Biomedical Network Research Centre on Rare Disorders (CIBERER), Instituto de Salud Carlos III, Madrid, Spain
| | - Ditte Demontis
- Department of Biomedicine - Human Genetics, Aarhus University, Aarhus, Denmark; The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark; Center for Genomics and Personalized Medicine, Aarhus, Denmark; The Novo Nordisk Foundation Center for Genomic Mechanisms of Disease, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - María Soler Artigas
- Department of Genetics, Microbiology, and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Psychiatric Genetics Unit, Group of Psychiatry Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain; Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Josep Antoni Ramos-Quiroga
- Department of Genetics, Microbiology, and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Psychiatric Genetics Unit, Group of Psychiatry Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain; Department of Psychiatry and Forensic Medicine, Universitat Autonoma de Barcelona, Barcelona, Spain
| | - Joel Gelernter
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA; Department of Genetics, Yale School of Medicine, New Haven, CT, USA; Department of Neuroscience, Yale School of Medicine, New Haven, CT, USA
| | - Marta Ribasés
- Department of Genetics, Microbiology, and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain; Biomedical Network Research Centre on Mental Health (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain; Psychiatric Genetics Unit, Group of Psychiatry Mental Health and Addiction, Vall d'Hebron Research Institute (VHIR), Universitat Autònoma de Barcelona, Barcelona, Spain; Department of Mental Health, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | - Bru Cormand
- Department of Genetics, Microbiology, and Statistics, Faculty of Biology, University of Barcelona, Catalonia, Spain; Institute of Biomedicine of the University of Barcelona (IBUB), Barcelona, Catalonia Spain; Sant Joan de Déu Research Institute (IR-SJD), Esplugues de Llobregat, Catalonia, Spain; Biomedical Network Research Centre on Rare Disorders (CIBERER), Instituto de Salud Carlos III, Madrid, Spain
| | - Renato Polimanti
- Department of Psychiatry, Yale School of Medicine, New Haven, CA, USA; Veterans Affairs Connecticut Healthcare Center, West Haven, CA, USA; Wu Tsai Institute, Yale University, New Haven, CT, USA
| |
Collapse
|
10
|
Kullberg MJ, Van Schie CC, Allegrini AG, Ahmadzadeh Y, Wechsler DL, Elzinga BM, McAdams TA. Comparing findings from the random-intercept cross-lagged panel model and the monozygotic twin difference cross-lagged panel model: Maladaptive parenting and offspring emotional and behavioural problems. JCPP ADVANCES 2024; 4:e12203. [PMID: 38486957 PMCID: PMC10933702 DOI: 10.1002/jcv2.12203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 10/02/2023] [Indexed: 03/17/2024] Open
Abstract
Background In this study we compare results obtained when applying the monozygotic twin difference cross-lagged panel model (MZD-CLPM) and a random intercept cross-lagged panel model (RI-CLPM) to the same data. Each of these models is designed to strengthen researchers' ability to draw causal inference from cross-lagged associations. We explore differences and similarities in how each model does this, and in the results each model produces. Specifically, we examine associations between maladaptive parenting and child emotional and behavioural problems in identical twins aged 9, 12 and 16. Method Child reports of 5698 identical twins from the Twins Early Development Study (TEDS) were analysed. We ran a regular CLPM to anchor our findings within the current literature, then applied the MZD-CLPM and the RI-CLPM. Results The RI-CLPM and MZD-CLPM each enable researchers to evaluate the direction of effects between correlated variables, after accounting for unmeasured sources of potential confounding. Our interpretation of these models therefore focusses primarily on the magnitude and significance of cross-lagged associations. In both the MZD-CLPM and the RI-CLPM behavioural problems at age 9 resulted in higher levels of maladaptive parenting at age 12. Other effects were not consistently significant across the two models, although the majority of estimates pointed in the same direction. Conclusion In light of the triangulated methods, differences in the results obtained using the MZD-CLPM and the RI-CLPM underline the importance of careful consideration of what sources of unmeasured confounding different models control for and that nuance is required when interpreting findings using such models. We provide an overview of what the CLPM, RI-CLPM and MZD-CLPM can and cannot control for in this respect and the conclusions that can be drawn from each model.
Collapse
Affiliation(s)
| | - Charlotte C. Van Schie
- Institute of Clinical PsychologyLeiden UniversityLeidenThe Netherlands
- Leiden Institute for Brain and Cognition (LIBC)Leiden University Medical CentreLeidenThe Netherlands
- School of Psychology and Illawarra Health and Medical Research InstituteUniversity of WollongongWollongongAustralia
| | - Andrea G. Allegrini
- Psychology and Language SciencesUniversity College LondonLondonUK
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology & NeuroscienceKing's College LondonLondonUK
| | - Yasmin Ahmadzadeh
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology & NeuroscienceKing's College LondonLondonUK
| | - Daniel L. Wechsler
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology & NeuroscienceKing's College LondonLondonUK
| | - Bernet M. Elzinga
- Institute of Clinical PsychologyLeiden UniversityLeidenThe Netherlands
- Leiden Institute for Brain and Cognition (LIBC)Leiden University Medical CentreLeidenThe Netherlands
| | - Tom A. McAdams
- Social, Genetic and Developmental Psychiatry CentreInstitute of Psychiatry, Psychology & NeuroscienceKing's College LondonLondonUK
- Promenta Research CentreUniversity of OsloOsloNorway
| |
Collapse
|
11
|
Waszczuk MA, Jonas KG, Bornovalova M, Breen G, Bulik CM, Docherty AR, Eley TC, Hettema JM, Kotov R, Krueger RF, Lencz T, Li JJ, Vassos E, Waldman ID. Dimensional and transdiagnostic phenotypes in psychiatric genome-wide association studies. Mol Psychiatry 2023; 28:4943-4953. [PMID: 37402851 PMCID: PMC10764644 DOI: 10.1038/s41380-023-02142-8] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/17/2023] [Accepted: 06/16/2023] [Indexed: 07/06/2023]
Abstract
Genome-wide association studies (GWAS) provide biological insights into disease onset and progression and have potential to produce clinically useful biomarkers. A growing body of GWAS focuses on quantitative and transdiagnostic phenotypic targets, such as symptom severity or biological markers, to enhance gene discovery and the translational utility of genetic findings. The current review discusses such phenotypic approaches in GWAS across major psychiatric disorders. We identify themes and recommendations that emerge from the literature to date, including issues of sample size, reliability, convergent validity, sources of phenotypic information, phenotypes based on biological and behavioral markers such as neuroimaging and chronotype, and longitudinal phenotypes. We also discuss insights from multi-trait methods such as genomic structural equation modelling. These provide insight into how hierarchical 'splitting' and 'lumping' approaches can be applied to both diagnostic and dimensional phenotypes to model clinical heterogeneity and comorbidity. Overall, dimensional and transdiagnostic phenotypes have enhanced gene discovery in many psychiatric conditions and promises to yield fruitful GWAS targets in the years to come.
Collapse
Affiliation(s)
- Monika A Waszczuk
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, USA.
| | - Katherine G Jonas
- Department of Psychiatry, Stony Brook University School of Medicine, Stony Brook, NY, USA
| | | | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Cynthia M Bulik
- Department of Psychiatry, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anna R Docherty
- Huntsman Mental Health Institute, Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT, USA
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
| | - Thalia C Eley
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - John M Hettema
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
- Department of Psychiatry, Texas A&M Health Sciences Center, Bryan, TX, USA
| | - Roman Kotov
- Department of Psychiatry, Stony Brook University School of Medicine, Stony Brook, NY, USA
| | - Robert F Krueger
- Psychology Department, University of Minnesota, Minneapolis, MN, USA
| | - Todd Lencz
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, USA
| | - James J Li
- Department of Psychology, University of Wisconsin, Madison, WI, USA
- Waisman Center, University of Wisconsin, Madison, WI, USA
| | - Evangelos Vassos
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Irwin D Waldman
- Department of Psychology, Emory University, Atlanta, GA, USA
- Center for Computational and Quantitative Genetics, Emory University, Atlanta, GA, USA
| |
Collapse
|
12
|
Hicks TA, Bountress KE, Adkins AE, Svikis DS, Gillespie NA, Dick DM, Spit for Science Working Group, Amstadter AB. A longitudinal mediational investigation of risk pathways among cannabis use, interpersonal trauma exposure, and trauma-related distress. PSYCHOLOGICAL TRAUMA : THEORY, RESEARCH, PRACTICE AND POLICY 2023; 15:969-978. [PMID: 35099217 PMCID: PMC9339011 DOI: 10.1037/tra0001207] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
OBJECTIVE College students are at high risk for cannabis use, interpersonal trauma (IPT) exposure, and trauma-related distress (TRD). Two phenotypic etiologic models posited to explain associations between cannabis use and trauma-related phenotypes are the self-medication (trauma/TRD → cannabis use) and high-risk (cannabis use → trauma/TRD) hypotheses. The primary objective of the present study was to investigate direct and indirect associations among cannabis use, IPT exposure, and TRD above and beyond established covariates. METHOD The current study used data from the first assessment (i.e., baseline survey at Year 1 Fall) and two follow-up assessments (i.e., Year 1 Spring and Year 2 Spring) from an ongoing longitudinal study on college behavioral health. Participants were 4 cohorts of college students (n = 9,889) who completed measures of demographics, substance use, IPT, and TRD. Indirect effects of IPT on cannabis through TRD (i.e., self-medication) and cannabis on TRD through IPT (i.e., high-risk), including tests of covariate effects (e.g., gender, age, race, cohort, alcohol, nicotine), were simultaneously estimated using a longitudinal mediation modeling framework. RESULTS Results suggest that more IPT exposure increases risk for TRD and subsequent nonexperimental (use 6+ times) cannabis use, and that experimental (use 1-5 times) and nonexperimental cannabis use increases risk for IPT exposure and subsequent TRD. CONCLUSIONS Both the self-medication and high-risk hypotheses were supported. Findings support a bidirectional causal relationship between cannabis use and trauma-related phenotypes. Additionally, results highlight areas for colleges to intervene among students to help reduce cannabis use and create a safer environment. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
Collapse
Affiliation(s)
- Terrell A. Hicks
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia
- Department of Psychology, Virginia Commonwealth University, Richmond, Virginia
| | - Kaitlin E. Bountress
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia
| | - Amy E. Adkins
- Department of Psychology, Virginia Commonwealth University, Richmond, Virginia
| | - Dace S. Svikis
- Department of Psychology, Virginia Commonwealth University, Richmond, Virginia
| | - Nathan A. Gillespie
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, Virginia
| | - Danielle M. Dick
- Department of Psychology, Virginia Commonwealth University, Richmond, Virginia
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, Virginia
| | | | - Ananda B. Amstadter
- Virginia Institute for Psychiatric and Behavioral Genetics, Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia
- Department of Psychology, Virginia Commonwealth University, Richmond, Virginia
- Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, Virginia
| |
Collapse
|
13
|
Howarth ERI, Szott ID, Witham CL, Wilding CS, Bethell EJ. Genetic polymorphisms in the serotonin, dopamine and opioid pathways influence social attention in rhesus macaques (Macaca mulatta). PLoS One 2023; 18:e0288108. [PMID: 37531334 PMCID: PMC10395878 DOI: 10.1371/journal.pone.0288108] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 06/20/2023] [Indexed: 08/04/2023] Open
Abstract
Behaviour has a significant heritable component; however, unpicking the variants of interest in the neural circuits and molecular pathways that underpin these has proven difficult. Here, we present a comprehensive analysis of the relationship between known and new candidate genes from identified pathways and key behaviours for survival in 109 adult rhesus macaques (Macaca mulatta). Eight genes involved in emotion were analysed for variation at a total of nine loci. Genetic data were then correlated with cognitive and observational measures of behaviour associated with wellbeing and survival using MCMC-based Bayesian GLMM in R, to account for relatedness within the macaque population. For four loci the variants genotyped were length polymorphisms (SLC6A4 5-hydroxytryptamine transporter length-polymorphic repeat (5-HTTLPR), SLC6A4 STin polymorphism, Tryptophan 5-hydroxylase 2 (TPH2) and Monoamine oxidase A (MAOA)) whilst for the other five (5-hydroxytryptamine receptor 2A (HTR2A), Dopamine Receptor D4 (DRD4), Oxytocin receptor (OXTR), Arginine vasopressin receptor 1A (AVPR1a), Opioid receptor mu(μ) 1 (OPRM1)) SNPs were analysed. STin genotype, DRD4 haplotype and OXTR haplotype were significantly associated with the cognitive and observational measures of behaviour associated with wellbeing and survival. Genotype for 5-HTTLPR, STin and AVPR1a, and haplotype for HTR2A, DRD4 and OXTR were significantly associated with the duration of behaviours including fear and anxiety. Understanding the biological underpinnings of individual variation in negative emotion (e.g., fear and anxiety), together with their impact on social behaviour (e.g., social attention including vigilance for threat) has application for managing primate populations in the wild and captivity, as well as potential translational application for understanding of the genetic basis of emotions in humans.
Collapse
Affiliation(s)
- Emmeline R. I. Howarth
- Research Centre in Brain and Behaviour, School of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool, United Kingdom
- Department of Biological Sciences, University of Chester, Chester, United Kingdom
| | - Isabelle D. Szott
- Research Centre in Brain and Behaviour, School of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool, United Kingdom
| | - Claire L. Witham
- Centre for Macaques, Harwell Institute, Medical Research Council, Salisbury, United Kingdom
| | - Craig S. Wilding
- Biodiversity and Conservation Group, School of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool, United Kingdom
| | - Emily J. Bethell
- Research Centre in Brain and Behaviour, School of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool, United Kingdom
| |
Collapse
|
14
|
Nurmi EL, Laughlin CP, de Wit H, Palmer AA, MacKillop J, Cannon TD, Bilder RM, Congdon E, Sabb FW, Seaman LC, McElroy JJ, Libowitz MR, Weafer J, Gray J, Dean AC, Hellemann GS, London ED. Polygenic contributions to performance on the Balloon Analogue Risk Task. Mol Psychiatry 2023; 28:3524-3530. [PMID: 37582857 PMCID: PMC10618088 DOI: 10.1038/s41380-023-02123-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 05/03/2023] [Accepted: 06/07/2023] [Indexed: 08/17/2023]
Abstract
Risky decision-making is a common, heritable endophenotype seen across many psychiatric disorders. Its underlying genetic architecture is incompletely explored. We examined behavior in the Balloon Analogue Risk Task (BART), which tests risky decision-making, in two independent samples of European ancestry. One sample (n = 1138) comprised healthy participants and some psychiatric patients (53 schizophrenia, 42 bipolar disorder, 47 ADHD); the other (n = 911) excluded for recent treatment of various psychiatric disorders but not ADHD. Participants provided DNA and performed the BART, indexed by mean adjusted pumps. We constructed a polygenic risk score (PRS) for discovery in each dataset and tested it in the other as replication. Subsequently, a genome-wide MEGA-analysis, combining both samples, tested genetic correlation with risk-taking self-report in the UK Biobank sample and psychiatric phenotypes characterized by risk-taking (ADHD, Bipolar Disorder, Alcohol Use Disorder, prior cannabis use) in the Psychiatric Genomics Consortium. The PRS for BART performance in one dataset predicted task performance in the replication sample (r = 0.13, p = 0.000012, pFDR = 0.000052), as did the reciprocal analysis (r = 0.09, p = 0.0083, pFDR=0.04). Excluding participants with psychiatric diagnoses produced similar results. The MEGA-GWAS identified a single SNP (rs12023073; p = 3.24 × 10-8) near IGSF21, a protein involved in inhibitory brain synapses; replication samples are needed to validate this result. A PRS for self-reported cannabis use (p = 0.00047, pFDR = 0.0053), but not self-reported risk-taking or psychiatric disorder status, predicted behavior on the BART in our MEGA-GWAS sample. The findings reveal polygenic architecture of risky decision-making as measured by the BART and highlight its overlap with cannabis use.
Collapse
Affiliation(s)
- E L Nurmi
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, 90024, USA.
| | - C P Laughlin
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, 90024, USA
| | - H de Wit
- Department of Psychiatry, University of Chicago, Chicago, IL, 60637, USA
| | - A A Palmer
- Department of Psychiatry, University of California at San Diego, La Jolla, CA, 92093, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, 92093, USA
| | - J MacKillop
- Peter Boris Centre for Addictions Research, McMaster University and St. Joseph's Healthcare Hamilton, Hamilton, ON, L8S4L8, Canada
| | - T D Cannon
- Departments of Psychology and Psychiatry, Yale University, New Haven, CT, 06520, USA
| | - R M Bilder
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, 90024, USA
| | - E Congdon
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, 90024, USA
| | - F W Sabb
- Prevention Science Institute, University of Utah, Salt Lake City, UT, 84112, USA
| | - L C Seaman
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, 90024, USA
| | - J J McElroy
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, 90024, USA
| | - M R Libowitz
- Department of Neurobiology, University of Kentucky, Lexington, KY, 40506, USA
| | - J Weafer
- Department of Psychology, University of Kentucky, Lexington, KY, 40506, USA
| | - J Gray
- Department of Psychology, University of Georgia, Athens, GA, 30602, USA
| | - A C Dean
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, 90024, USA
| | - G S Hellemann
- Department of Public Health, University of Alabama at Birmingham, Birmingham, AL, 35294, USA
| | - E D London
- Department of Psychiatry and Biobehavioral Sciences, University of California at Los Angeles, Los Angeles, CA, 90024, USA
- Department of Molecular and Medical Pharmacology, University of California at Los Angeles, Los Angeles, CA, 90024, USA
| |
Collapse
|
15
|
Domaradzki J, Czekajewska J, Walkowiak D. To donate or not to donate? Future healthcare professionals' opinions on biobanking of human biological material for research purposes. BMC Med Ethics 2023; 24:53. [PMID: 37481540 PMCID: PMC10363302 DOI: 10.1186/s12910-023-00930-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Accepted: 07/11/2023] [Indexed: 07/24/2023] Open
Abstract
BACKGROUND Over the last few decades biobanks have been recognised as institutions that may revolutionise biomedical research and the development of personalised medicine. Poland, however, still lacks clear regulations regarding the running of biobanks and the conducting of biomedical research. While the awareness of the general public regarding biobanks is low, healthcare professions and medical students also lack basic knowledge regarding biobanks, and such ignorance may affect their support for biobanks. METHODS This study is aimed at assessing the knowledge and attitudes of future healthcare professionals towards the donation of human biological material for research purposes and is based on a sample of 865 Polish medical students at Poznań University of Medical Sciences. RESULTS This research has shown that the awareness of medical students' regarding biobanks is low. It has also shown that while the majority of future healthcare professionals enrolled in this study supported the idea of biobank research and declared themselves willing to donate, still many students felt ambivalent about the biobanking of human biological material for research purposes and expressed concerns over biobanking research. While the primarily motivation to participate in biobank research was the desire to help advance science and to develop innovative therapies, the most common reason for a refusal was the fear that the government, insurance companies or employers, might have access to the samples. Concerns over unethical use of samples and data safety were also prevalent. More than half of students opted for a study-specific model of consent and only a few opted for broad consent. CONCLUSIONS This research suggests that a lack of knowledge about biobanks, their role and activities may affect medical students' support for biobanks and their active participation in the collection and management of biospecimens for research purposes. Since in the future medical, nursing and pharmacy students will be involved in the collection, storage, testing and analysis of biospecimens from their patients, medical students in all professional fields should be trained regarding the concept, purposes and operational procedures of biobanks, as well as the ethical, legal and social implications of biobank research.
Collapse
Affiliation(s)
- Jan Domaradzki
- Department of Social Sciences and Humanities, Poznan University of Medical Sciences, Rokietnicka 7, St., Poznań, 60-806, Poland.
| | - Justyna Czekajewska
- Department of Social Sciences and Humanities, Poznan University of Medical Sciences, Rokietnicka 7, St., Poznań, 60-806, Poland
| | - Dariusz Walkowiak
- Department of Organization and Management in Health Care, Poznan University of Medical Sciences, Poznań, Poland
| |
Collapse
|
16
|
Jung K, Yoon J, Ahn Y, Kim S, Shim I, Ko H, Jung SH, Kim J, Kim H, Lee DJ, Cha S, Lee H, Kim B, Cho MY, Cho H, Kim DS, Kim J, Park WY, Park TH, O Connell KS, Andreassen OA, Myung W, Won HH. Leveraging genetic overlap between irritability and psychiatric disorders to identify genetic variants of major psychiatric disorders. Exp Mol Med 2023; 55:1193-1202. [PMID: 37258574 PMCID: PMC10317967 DOI: 10.1038/s12276-023-01005-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Revised: 02/07/2023] [Accepted: 03/13/2023] [Indexed: 06/02/2023] Open
Abstract
Irritability is a heritable core mental trait associated with several psychiatric illnesses. However, the genomic basis of irritability is unclear. Therefore, this study aimed to 1) identify the genetic variants associated with irritability and investigate the associated biological pathways, genes, and tissues as well as single-nucleotide polymorphism (SNP)-based heritability; 2) explore the relationships between irritability and various traits, including psychiatric disorders; and 3) identify additional and shared genetic variants for irritability and psychiatric disorders. We conducted a genome-wide association study (GWAS) using 379,506 European samples (105,975 cases and 273,531 controls) from the UK Biobank. We utilized various post-GWAS analyses, including linkage disequilibrium score regression, the bivariate causal mixture model (MiXeR), and conditional and conjunctional false discovery rate approaches. This GWAS identified 15 independent loci associated with irritability; the total SNP heritability estimate was 4.19%. Genetic correlations with psychiatric disorders were most pronounced for major depressive disorder (MDD) and bipolar II disorder (BD II). MiXeR analysis revealed polygenic overlap with schizophrenia (SCZ), bipolar I disorder (BD I), and MDD. Conditional false discovery rate analyses identified additional loci associated with SCZ (number [n] of additional SNPs = 105), BD I (n = 54), MDD (n = 107), and irritability (n = 157). Conjunctional false discovery rate analyses identified 85, 41, and 198 shared loci between irritability and SCZ, BD I, and MDD, respectively. Multiple genetic loci were associated with irritability and three main psychiatric disorders. Given that irritability is a cross-disorder trait, these findings may help to elucidate the genomics of psychiatric disorders.
Collapse
Affiliation(s)
- Kyeongmin Jung
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, 13620, South Korea
| | - Joohyun Yoon
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, 13620, South Korea
| | - Yeeun Ahn
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Soyeon Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Injeong Shim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Hyunwoong Ko
- Interdisciplinary Program in Cognitive Science, Seoul National University, Seoul, 08826, South Korea
- Department of Psychiatry, SMG-SNU Boramae Medical Center, Seoul National University College of Medicine, Seoul, 03080, South Korea
- Dental Research Institute, Seoul National University School of Dentistry, Seoul, 03080, South Korea
| | - Sang-Hyuk Jung
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Jaeyoung Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, 13620, South Korea
| | - Hyejin Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Dong June Lee
- Department of Health Sciences and Technology, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Soojin Cha
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Hyewon Lee
- Department of Health Administration and Management, College of Medical Sciences, Soonchunhyang University, Asan, 31538, South Korea
| | - Beomsu Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Min Young Cho
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Hyunbin Cho
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Dan Say Kim
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea
| | - Jinho Kim
- Precision Medicine Center, Future Innovation Research Division, Seoul National University Bundang Hospital, Seongnam, 13620, South Korea
| | - Woong-Yang Park
- Samsung Genome Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, South Korea
| | - Tae Hwan Park
- Department of Plastic and Reconstructive Surgery, Hallym University Dongtan Sacred Heart Hospital, Dongtan Sacred Heart Hospital, Hallym University College of Medicine, Hwaseong, 18450, South Korea
| | - Kevin S O Connell
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, NO-316, Norway
| | - Ole A Andreassen
- Norwegian Center for Mental Disorders Research (NORMENT), Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, NO-316, Norway
| | - Woojae Myung
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, 13620, South Korea.
- Department of Psychiatry, Seoul National University, College of Medicine, Seoul, 03080, South Korea.
| | - Hong-Hee Won
- Department of Digital Health, Samsung Advanced Institute for Health Sciences and Technology (SAIHST), Sungkyunkwan University, Samsung Medical Center, Seoul, 06355, South Korea.
- Samsung Genome Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, South Korea.
| |
Collapse
|
17
|
Sanchez-Roige S, Jennings MV, Thorpe HHA, Mallari JE, van der Werf LC, Bianchi SB, Huang Y, Lee C, Mallard TT, Barnes SA, Wu JY, Barkley-Levenson AM, Boussaty EC, Snethlage CE, Schafer D, Babic Z, Winters BD, Watters KE, Biederer T, Mackillop J, Stephens DN, Elson SL, Fontanillas P, Khokhar JY, Young JW, Palmer AA. CADM2 is implicated in impulsive personality and numerous other traits by genome- and phenome-wide association studies in humans and mice. Transl Psychiatry 2023; 13:167. [PMID: 37173343 PMCID: PMC10182097 DOI: 10.1038/s41398-023-02453-y] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 04/17/2023] [Accepted: 04/25/2023] [Indexed: 05/15/2023] Open
Abstract
Impulsivity is a multidimensional heritable phenotype that broadly refers to the tendency to act prematurely and is associated with multiple forms of psychopathology, including substance use disorders. We performed genome-wide association studies (GWAS) of eight impulsive personality traits from the Barratt Impulsiveness Scale and the short UPPS-P Impulsive Personality Scale (N = 123,509-133,517 23andMe research participants of European ancestry), and a measure of Drug Experimentation (N = 130,684). Because these GWAS implicated the gene CADM2, we next performed single-SNP phenome-wide studies (PheWAS) of several of the implicated variants in CADM2 in a multi-ancestral 23andMe cohort (N = 3,229,317, European; N = 579,623, Latin American; N = 199,663, African American). Finally, we produced Cadm2 mutant mice and used them to perform a Mouse-PheWAS ("MouseWAS") by testing them with a battery of relevant behavioral tasks. In humans, impulsive personality traits showed modest chip-heritability (~6-11%), and moderate genetic correlations (rg = 0.20-0.50) with other personality traits, and various psychiatric and medical traits. We identified significant associations proximal to genes such as TCF4 and PTPRF, and also identified nominal associations proximal to DRD2 and CRHR1. PheWAS for CADM2 variants identified associations with 378 traits in European participants, and 47 traits in Latin American participants, replicating associations with risky behaviors, cognition and BMI, and revealing novel associations including allergies, anxiety, irritable bowel syndrome, and migraine. Our MouseWAS recapitulated some of the associations found in humans, including impulsivity, cognition, and BMI. Our results further delineate the role of CADM2 in impulsivity and numerous other psychiatric and somatic traits across ancestries and species.
Collapse
Affiliation(s)
- Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA.
| | - Mariela V Jennings
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Hayley H A Thorpe
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
| | - Jazlene E Mallari
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | | | - Sevim B Bianchi
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Yuye Huang
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Calvin Lee
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Travis T Mallard
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Samuel A Barnes
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Jin Yi Wu
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | | | - Ely C Boussaty
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Cedric E Snethlage
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Danielle Schafer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Zeljana Babic
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Boyer D Winters
- Department of Psychology, University of Guelph, Guelph, ON, Canada
| | - Katherine E Watters
- Department of Neuroscience, Tufts University School of Medicine, Boston, MA, USA
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Thomas Biederer
- Department of Neuroscience, Tufts University School of Medicine, Boston, MA, USA
| | - James Mackillop
- Peter Boris Centre for Addictions Research, McMaster University and St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada and Homewood Research Institute, Guelph, ON, Canada
| | - David N Stephens
- Laboratory of Behavioural and Clinical Neuroscience, School of Psychology, University of Sussex, Brighton, UK
| | | | | | - Jibran Y Khokhar
- Department of Biomedical Sciences, Ontario Veterinary College, University of Guelph, Guelph, ON, Canada
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Jared W Young
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA.
| |
Collapse
|
18
|
Diemer EW, Havdahl A, Andreassen OA, Munafò M, Njolstad PR, Tiemeier H, Zuccolo L, Swanson SA. Bounding the average causal effect in Mendelian randomisation studies with multiple proposed instruments: An application to prenatal alcohol exposure and attention deficit hyperactivity disorder. Paediatr Perinat Epidemiol 2023; 37:326-337. [PMID: 36722651 PMCID: PMC10946905 DOI: 10.1111/ppe.12951] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 10/11/2022] [Accepted: 12/17/2022] [Indexed: 02/02/2023]
Abstract
BACKGROUND As large-scale observational data become more available, caution regarding causal assumptions remains critically important. This may be especially true for Mendelian randomisation (MR), an increasingly popular approach. Point estimation in MR usually requires strong, often implausible homogeneity assumptions beyond the core instrumental conditions. Bounding, which does not require homogeneity assumptions, is infrequently applied in MR. OBJECTIVES We aimed to demonstrate computing nonparametric bounds for the causal risk difference derived from multiple proposed instruments in an MR study where effect heterogeneity is expected. METHODS Using data from the Norwegian Mother, Father and Child Cohort Study (n = 2056) and Avon Longitudinal Study of Parents and Children (n = 6216) to study the average causal effect of maternal pregnancy alcohol use on offspring attention deficit hyperactivity disorder symptoms, we proposed 11 maternal SNPs as instruments. We computed bounds assuming subsets of SNPs were jointly valid instruments, for all combinations of SNPs where the MR model was not falsified. RESULTS The MR assumptions were violated for all sets with more than 4 SNPs in one cohort and for all sets with more than 2 SNPs in the other. Bounds assuming one SNP was an individually valid instrument barely improved on assumption-free bounds. Bounds tightened as more SNPs were assumed to be jointly valid instruments, and occasionally identified directions of effect, though bounds from different sets varied. CONCLUSIONS Our results suggest that, when proposing multiple instruments, bounds can contextualise plausible magnitudes and directions of effects. Computing bounds over multiple assumption sets, particularly in large, high-dimensional data, offers a means of triangulating results across different potential sources of bias within a study and may help researchers to better evaluate and emphasise which estimates are compatible with the most plausible assumptions for their specific setting.
Collapse
Affiliation(s)
- Elizabeth W. Diemer
- Department of Child and Adolescent PsychiatryErasmus MCRotterdamthe Netherlands
- CAUSALabHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
- Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
| | - Alexandra Havdahl
- MRC Integrative Epidemiology Unit at the University of BristolBristolUK
- Nic Waals InstituteLovisenberg Diaconal HospitalOsloNorway
- Department of Mental DisordersNorwegian Institute of Public Health
| | - Ole A. Andreassen
- NORMENT, KG Jebsen Centre for Psychosis Research, Department of Clinical ScienceUniversity of BergenBergenNorway
| | - Marcus R. Munafò
- MRC Integrative Epidemiology Unit at the University of BristolBristolUK
- School of Psychological ScienceUniversity of BristolBristolUK
- NIHR Biomedical Research CentreUniversity Hospitals Bristol NHS Foundation Trust and University of BristolBristolUK
| | - Pal R. Njolstad
- Department of Paediatric and Adolescent MedicineHaukeland University HospitalBergenNorway
- KG Jebsen Center for Diabetes Research, Department of Clinical ScienceUniversity of BergenBergenNorway
| | - Henning Tiemeier
- Department of Child and Adolescent PsychiatryErasmus MCRotterdamthe Netherlands
- Department of Social and Behavioral ScienceHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
| | - Luisa Zuccolo
- MRC Integrative Epidemiology Unit at the University of BristolBristolUK
- Department of Population Health Sciences, Bristol Medical SchoolUniversity of BristolBristolUK
- Centre for Health Data ScienceHuman Technopole FoundationMilanItaly
| | - Sonja A. Swanson
- CAUSALabHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
- Department of EpidemiologyHarvard T.H. Chan School of Public HealthBostonMassachusettsUSA
- Department of EpidemiologyErasmus MCRotterdamthe Netherlands
- Department of EpidemiologyUniversity of PittsburghPittsburghPennsylvaniaUSA
| |
Collapse
|
19
|
Pishva E, van den Hove DLA, Laroche V, Lvovs A, Roy A, Ortega G, Burrage J, Veidebaum T, Kanarik M, Mill J, Lesch KP, Harro J. Genome-wide DNA methylation analysis of aggressive behaviour: a longitudinal population-based study. J Child Psychol Psychiatry 2023. [PMID: 36929374 DOI: 10.1111/jcpp.13782] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/25/2023] [Indexed: 03/18/2023]
Abstract
BACKGROUND Human aggression is influenced by an interplay between genetic predisposition and experience across the life span. This interaction is thought to occur through epigenetic mechanisms, inducing differential gene expression, thereby moderating neuronal cell and circuit function, and thus shaping aggressive behaviour. METHODS Genome-wide DNA methylation (DNAm) levels were measured in peripheral blood obtained from 95 individuals participating in the Estonian Children Personality Behaviours and Health Study (ECPBHS) at 15 and 25 years of age. We examined the association between aggressive behaviour, as measured by Life History of Aggression (LHA) total score and DNAm levels both assessed at age 25. We further examined the pleiotropic effect of genetic variants regulating LHA-associated differentially methylated positions (DMPs) and multiple traits related to aggressive behaviours. Lastly, we tested whether the DNA methylomic loci identified in association with LHA at age 25 were also present at age 15. RESULTS We found one differentially methylated position (DMP) (cg17815886; p = 1.12 × 10-8 ) and five differentially methylated regions (DMRs) associated with LHA after multiple testing adjustments. The DMP annotated to the PDLIM5 gene, and DMRs resided in the vicinity of four protein-encoding genes (TRIM10, GTF2H4, SLC45A4, B3GALT4) and a long intergenic non-coding RNA (LINC02068). We observed evidence for the colocalization of genetic variants associated with top DMPs and general cognitive function, educational attainment and cholesterol levels. Notably, a subset of the DMPs associated with LHA at age 25 also displayed altered DNAm patterns at age 15 with high accuracy in predicting aggression. CONCLUSIONS Our findings highlight the potential role of DNAm in the development of aggressive behaviours. We observed pleiotropic genetic variants associated with identified DMPs, and various traits previously established to be relevant in shaping aggression in humans. The concordance of DNAm signatures in adolescents and young adults may have predictive value for inappropriate and maladaptive aggression later in life.
Collapse
Affiliation(s)
- Ehsan Pishva
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands.,College of Medicine and Health, University of Exeter Medical School, Exeter, UK
| | - Daniel L A van den Hove
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands.,Division of Molecular Psychiatry, Center of Mental Health, University of Würzburg, Würzburg, Germany
| | - Valentin Laroche
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands
| | - Aneth Lvovs
- School of Natural Sciences and Health, Tallinn University, Tallinn, Estonia.,Chair of Neuropsychopharmacology, Institute of Chemistry, University of Tartu, Tartu, Estonia
| | - Arunima Roy
- Division of Molecular Psychiatry, Center of Mental Health, University of Würzburg, Würzburg, Germany
| | - Gabriela Ortega
- Division of Molecular Psychiatry, Center of Mental Health, University of Würzburg, Würzburg, Germany
| | - Joe Burrage
- College of Medicine and Health, University of Exeter Medical School, Exeter, UK
| | | | - Margus Kanarik
- Chair of Neuropsychopharmacology, Institute of Chemistry, University of Tartu, Tartu, Estonia
| | - Jonathan Mill
- College of Medicine and Health, University of Exeter Medical School, Exeter, UK
| | - Klaus-Peter Lesch
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands.,Division of Molecular Psychiatry, Center of Mental Health, University of Würzburg, Würzburg, Germany
| | - Jaanus Harro
- Chair of Neuropsychopharmacology, Institute of Chemistry, University of Tartu, Tartu, Estonia
| |
Collapse
|
20
|
Carreras-Torres R, Kim AE, Lin Y, Diez-Obrero V, Bien SA, Qu C, Wang J, Dimou N, Aglago EK, Albanes D, Arndt V, Baurley JW, Berndt SI, Bézieau S, Bishop DT, Bouras E, Brenner H, Budiarto A, Campbell PT, Casey G, Chan AT, Chang-Claude J, Chen X, Conti DV, Dampier CH, Devall MAM, Drew DA, Figueiredo JC, Gallinger S, Giles GG, Gruber SB, Gsur A, Gunter MJ, Harrison TA, Hidaka A, Hoffmeister M, Huyghe JR, Jenkins MA, Jordahl KM, Kawaguchi E, Keku TO, Kundaje A, Le Marchand L, Lewinger JP, Li L, Mahesworo B, Morrison JL, Murphy N, Nan H, Nassir R, Newcomb PA, Obón-Santacana M, Ogino S, Ose J, Pai RK, Palmer JR, Papadimitriou N, Pardamean B, Peoples AR, Pharoah PDP, Platz EA, Rennert G, Ruiz-Narvaez E, Sakoda LC, Scacheri PC, Schmit SL, Schoen RE, Shcherbina A, Slattery ML, Stern MC, Su YR, Tangen CM, Thomas DC, Tian Y, Tsilidis KK, Ulrich CM, van Duijnhoven FJB, Van Guelpen B, Visvanathan K, Vodicka P, Cenggoro TW, Weinstein SJ, White E, Wolk A, Woods MO, Hsu L, Peters U, Moreno V, Gauderman WJ. Genome-wide Interaction Study with Smoking for Colorectal Cancer Risk Identifies Novel Genetic Loci Related to Tumor Suppression, Inflammation, and Immune Response. Cancer Epidemiol Biomarkers Prev 2023; 32:315-328. [PMID: 36576985 PMCID: PMC9992283 DOI: 10.1158/1055-9965.epi-22-0763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 09/19/2022] [Accepted: 12/19/2022] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Tobacco smoking is an established risk factor for colorectal cancer. However, genetically defined population subgroups may have increased susceptibility to smoking-related effects on colorectal cancer. METHODS A genome-wide interaction scan was performed including 33,756 colorectal cancer cases and 44,346 controls from three genetic consortia. RESULTS Evidence of an interaction was observed between smoking status (ever vs. never smokers) and a locus on 3p12.1 (rs9880919, P = 4.58 × 10-8), with higher associated risk in subjects carrying the GG genotype [OR, 1.25; 95% confidence interval (CI), 1.20-1.30] compared with the other genotypes (OR <1.17 for GA and AA). Among ever smokers, we observed interactions between smoking intensity (increase in 10 cigarettes smoked per day) and two loci on 6p21.33 (rs4151657, P = 1.72 × 10-8) and 8q24.23 (rs7005722, P = 2.88 × 10-8). Subjects carrying the rs4151657 TT genotype showed higher risk (OR, 1.12; 95% CI, 1.09-1.16) compared with the other genotypes (OR <1.06 for TC and CC). Similarly, higher risk was observed among subjects carrying the rs7005722 AA genotype (OR, 1.17; 95% CI, 1.07-1.28) compared with the other genotypes (OR <1.13 for AC and CC). Functional annotation revealed that SNPs in 3p12.1 and 6p21.33 loci were located in regulatory regions, and were associated with expression levels of nearby genes. Genetic models predicting gene expression revealed that smoking parameters were associated with lower colorectal cancer risk with higher expression levels of CADM2 (3p12.1) and ATF6B (6p21.33). CONCLUSIONS Our study identified novel genetic loci that may modulate the risk for colorectal cancer of smoking status and intensity, linked to tumor suppression and immune response. IMPACT These findings can guide potential prevention treatments.
Collapse
Affiliation(s)
- Robert Carreras-Torres
- Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
- Oncology Data Analytics Program, Catalan Institute of Oncology, L'Hospitalet de Llobregat, Barcelona, Spain
- Digestive Diseases and Microbiota Group, Girona Biomedical Research Institute (IDIBGI), Salt, 17190, Girona, Spain
| | - Andre E Kim
- Division of Biostatistics, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Yi Lin
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Virginia Diez-Obrero
- Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
- Oncology Data Analytics Program, Catalan Institute of Oncology, L'Hospitalet de Llobregat, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Stephanie A Bien
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Conghui Qu
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Jun Wang
- Division of Biostatistics, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Niki Dimou
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France
| | - Elom K Aglago
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - James W Baurley
- Bioinformatics and Data Science Research Center, Bina Nusantara University, Jakarta, Indonesia
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Stéphane Bézieau
- Service de Génétique Médicale, Centre Hospitalier Universitaire (CHU) Nantes, Nantes, France
| | - D Timothy Bishop
- Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Emmanouil Bouras
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Arif Budiarto
- Bioinformatics and Data Science Research Center, Bina Nusantara University, Jakarta, Indonesia
| | - Peter T Campbell
- Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, Georgia, USA
| | - Graham Casey
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, USA
| | - Andrew T Chan
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Xuechen Chen
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - David V Conti
- Division of Biostatistics, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Christopher H Dampier
- Department of General Surgery, University of Virginia School of Medicine, Charlottesville, Virginia, USA
| | - Matthew AM Devall
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, Virginia, USA
| | - David A Drew
- Clinical & Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Jane C Figueiredo
- Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Steven Gallinger
- Lunenfeld Tanenbaum Research Institute, Mount Sinai Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Graham G Giles
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Stephen B Gruber
- Department of Medical Oncology & Therapeutics Research, City of Hope National Medical Center, Duarte, CA, USA
| | - Andrea Gsur
- Institute of Cancer Research, Department of Medicine I, Medical University Vienna, Vienna, Austria
| | - Marc J Gunter
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France
| | - Tabitha A Harrison
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Akihisa Hidaka
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Jeroen R Huyghe
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Mark A Jenkins
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Kristina M Jordahl
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Eric Kawaguchi
- Division of Biostatistics, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Temitope O Keku
- Center for Gastrointestinal Biology and Disease, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Anshul Kundaje
- Department of Genetics, Department of Computer Science, Stanford University, Stanford, California, USA
| | | | - Juan Pablo Lewinger
- Division of Biostatistics, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Li Li
- Department of Family Medicine, University of Virginia, Charlottesville, Virginia, USA
| | - Bharuno Mahesworo
- Bioinformatics and Data Science Research Center, Bina Nusantara University, Jakarta, Indonesia
| | - John L Morrison
- Division of Biostatistics, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Neil Murphy
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France
| | - Hongmei Nan
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Indianapolis, Indiana, USA
| | - Rami Nassir
- Department of Pathology, School of Medicine, Umm Al-Qura’a University, Saudi Arabia
| | - Polly A Newcomb
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Mireia Obón-Santacana
- Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
- Oncology Data Analytics Program, Catalan Institute of Oncology, L'Hospitalet de Llobregat, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Shuji Ogino
- Program in MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA; Department of Oncologic Pathology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, USA; Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
| | - Jennifer Ose
- Huntsman Cancer Institute, Salt Lake City, Utah, USA
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Rish K Pai
- Department of Laboratory Medicine and Pathology, Mayo Clinic Arizona, Scottsdale, Arizona, USA
| | - Julie R Palmer
- Slone Epidemiology Center at Boston University, Boston, MA, USA
| | - Nikos Papadimitriou
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, Lyon, France
| | - Bens Pardamean
- Bioinformatics and Data Science Research Center, Bina Nusantara University, Jakarta, Indonesia
| | | | - Paul D P Pharoah
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Elizabeth A Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Gad Rennert
- Department of Community Medicine and Epidemiology, Lady Davis Carmel Medical Center, Haifa, Israel
| | - Edward Ruiz-Narvaez
- Department of Nutritional Sciences, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Lori C Sakoda
- Division of Research, Kaiser Permanente Northern California, Oakland, California, USA
| | - Peter C Scacheri
- Department of Genetics and Genome Sciences, Case Western Reserve University, Cleveland, Ohio, USA
| | - Stephanie L Schmit
- Genomic Medicine Institute, Cleveland Clinic, Cleveland, Ohio, USA
- Population and Cancer Prevention Program, Case Comprehensive Cancer Center, Cleveland, Ohio, USA
| | - Robert E Schoen
- Department of Medicine and Epidemiology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
| | - Anna Shcherbina
- Biomedical Informatics Program, Dept. of Biomedical Data Sciences, Stanford University
| | - Martha L Slattery
- Department of Internal Medicine, University of Utah, Salt Lake City, Utah, USA
| | - Mariana C Stern
- Division of Biostatistics, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Yu-Ru Su
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Catherine M Tangen
- SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Duncan C Thomas
- Division of Biostatistics, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Yu Tian
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- School of Public Health, Capital Medical University, Beijing, China
| | - Konstantinos K Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Cornelia M Ulrich
- Huntsman Cancer Institute, Salt Lake City, Utah, USA
- Department of Population Health Sciences, University of Utah, Salt Lake City, Utah, USA
| | - Franzel JB van Duijnhoven
- Division of Human Nutrition and Health, Wageningen University & Research, Wageningen, The Netherlands
| | - Bethany Van Guelpen
- Department of Radiation Sciences, Oncology Unit, Umeå University, Umeå, Sweden
- Wallenberg Centre for Molecular Medicine, Umeå University, Umeå, Sweden
| | - Kala Visvanathan
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Pavel Vodicka
- Department of Molecular Biology of Cancer, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, and Biomedical Center, Medical Faculty, Pilsen, Czech Republic
| | - Tjeng Wawan Cenggoro
- Bioinformatics and Data Science Research Center, Bina Nusantara University, Jakarta, Indonesia
| | - Stephanie J Weinstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Emily White
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Alicja Wolk
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Michael O Woods
- Memorial University of Newfoundland, Discipline of Genetics, St. John's, Canada
| | - Li Hsu
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
- School of Public Health, University of Washington, Seattle, Washington, USA
| | - Victor Moreno
- Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
- Oncology Data Analytics Program, Catalan Institute of Oncology, L'Hospitalet de Llobregat, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, Spain
| | - W James Gauderman
- Division of Biostatistics, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| |
Collapse
|
21
|
Wormington B, Thorp JG, Scott JG, Derks EM. Influences on the Genetic Relationship Between Cannabis Use and Schizophrenia: The Role of the Externalizing Spectrum. Schizophr Bull 2022; 48:1318-1326. [PMID: 35925031 PMCID: PMC9673266 DOI: 10.1093/schbul/sbac095] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND AND HYPOTHESIS The nature of the robust association between cannabis use and schizophrenia remains undetermined. Plausible hypotheses explaining this relationship include the premise that cannabis use causes schizophrenia, increased liability for schizophrenia increases the risk of cannabis use initiation (eg, self-medication), or the bidirectional causal hypothesis where both factors play a role in the development of the other. Alternatively, factors that confound the relationship between schizophrenia and cannabis use may explain their association. Externalizing behaviors are related to both schizophrenia and cannabis use and may influence their relationship. STUDY DESIGN This study aimed to evaluate whether externalizing behaviors influence the genetic relationship between cannabis use and schizophrenia. We conducted a multivariate genome-wide association analysis of 6 externalizing behaviors in order to construct a genetic latent factor of the externalizing spectrum. Genomic structural equation modeling was used to evaluate the influence of externalizing behaviors on the genetic relationship between cannabis use and schizophrenia. RESULTS We found that externalizing behaviors partially explained the association between cannabis use and schizophrenia by up to 42%. CONCLUSIONS This partial explanation of the association by externalizing behaviors suggests that there may be other unidentified confounding factors, alongside a possible direct association between schizophrenia and cannabis use. Future studies should aim to identify further confounding factors to accurately explain the relationship between cannabis use and schizophrenia.
Collapse
Affiliation(s)
- Briar Wormington
- To whom correspondence should be addressed; Briar Wormington, QIMR Berghofer, 300 Herston Road, Herston, QLD 4006, e-mail:
| | - Jackson G Thorp
- QIMR Berghofer, Translational Neurogenomics Group, Herston, QLD, Australia,Faculty of Medicine, University of Queensland, Herston, QLD, Australia
| | - James G Scott
- Faculty of Medicine, University of Queensland, Herston, QLD, Australia,QIMR Berghofer, Child and Youth Mental Health, Herston, QLD, Australia,Metro North Mental Health Service, Brisbane, QLD, Australia
| | - Eske M Derks
- QIMR Berghofer, Translational Neurogenomics Group, Herston, QLD, Australia,Faculty of Medicine, University of Queensland, Herston, QLD, Australia
| |
Collapse
|
22
|
Harrison PJ, Mould A, Tunbridge EM. New drug targets in psychiatry: Neurobiological considerations in the genomics era. Neurosci Biobehav Rev 2022; 139:104763. [PMID: 35787892 DOI: 10.1016/j.neubiorev.2022.104763] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Revised: 05/15/2022] [Accepted: 06/14/2022] [Indexed: 01/11/2023]
Abstract
After a period of withdrawal, pharmaceutical companies have begun to reinvest in neuropsychiatric disorders, due to improvements in our understanding of these disorders, stimulated in part by genomic studies. However, translating this information into disease insights and ultimately into tractable therapeutic targets is a major challenge. Here we consider how different sources of information might be integrated to guide this process. We review how an understanding of neurobiology has been used to advance therapeutic candidates identified in the pre-genomic era, using catechol-O-methyltransferase (COMT) as an exemplar. We then contrast with ZNF804A, the first genome-wide significant schizophrenia gene, and draw on some of the lessons that these and other examples provide. We highlight that, at least in the short term, the translation of potential targets for which there is orthogonal neurobiological support is likely to be more straightforward and productive than that those relying solely on genomic information. Although we focus here on information from genomic studies of schizophrenia, the points are broadly applicable across major psychiatric disorders and their symptoms.
Collapse
Affiliation(s)
- Paul J Harrison
- Department of Psychiatry, University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Oxford, UK
| | - Arne Mould
- Department of Psychiatry, University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Oxford, UK
| | - Elizabeth M Tunbridge
- Department of Psychiatry, University of Oxford, Oxford, UK; Oxford Health NHS Foundation Trust, Oxford, UK.
| |
Collapse
|
23
|
Klimentidis YC, Newell M, van der Zee MD, Bland VL, May-Wilson S, Arani G, Menni C, Mangino M, Arora A, Raichlen DA, Alexander GE, Wilson JF, Boomsma DI, Hottenga JJ, de Geus EJ, Pirastu N. Genome-wide Association Study of Liking for Several Types of Physical Activity in the UK Biobank and Two Replication Cohorts. Med Sci Sports Exerc 2022; 54:1252-1260. [PMID: 35320144 PMCID: PMC9288543 DOI: 10.1249/mss.0000000000002907] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
INTRODUCTION A lack of physical activity (PA) is one of the most pressing health issues today. Our individual propensity for PA is influenced by genetic factors. Stated liking of different PA types may help capture additional and informative dimensions of PA behavior genetics. METHODS In over 157,000 individuals from the UK Biobank, we performed genome-wide association studies of five items assessing the liking of different PA types, plus an additional derived trait of overall PA-liking. We attempted to replicate significant associations in the Netherlands Twin Register (NTR) and TwinsUK. Additionally, polygenic scores (PGS) were trained in the UK Biobank for each PA-liking item and for self-reported PA behavior, and tested for association with PA in the NTR. RESULTS We identified a total of 19 unique significant loci across all five PA-liking items and the overall PA-liking trait, and these showed strong directional consistency in the replication cohorts. Four of these loci were previously identified for PA behavior, including CADM2 , which was associated with three PA-liking items. The PA-liking items were genetically correlated with self-reported ( rg = 0.38-0.80) and accelerometer ( rg = 0.26-0.49) PA measures, and with a wide range of health-related traits. Each PA-liking PGS significantly predicted the same PA-liking item in NTR. The PGS of liking for going to the gym predicted PA behavior in the NTR ( r2 = 0.40%) nearly as well as a PGS based on self-reported PA behavior ( r2 = 0.42%). Combining the two PGS into a single model increased the r2 to 0.59%, suggesting that PA-liking captures distinct and relevant dimensions of PA behavior. CONCLUSIONS We have identified the first loci associated with PA-liking and extended our understanding of the genetic basis of PA behavior.
Collapse
Affiliation(s)
- Yann C. Klimentidis
- Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ
| | - Michelle Newell
- Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ
| | - Matthijs D. van der Zee
- Department of Biological Psychology, Vrije Universiteit Amsterdam, THE NETHERLANDS
- Amsterdam Public Health Institute, Amsterdam UMC, THE NETHERLANDS
| | - Victoria L. Bland
- Division of Geriatric Medicine, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Sebastian May-Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UNITED KINGDOM
| | - Gayatri Arani
- Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ
| | - Cristina Menni
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, UNITED KINGDOM
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, UNITED KINGDOM
- NIHR Biomedical Research Centre at Guy’s and St Thomas’ Foundation Trust, London, UNITED KINGDOM
| | - Amit Arora
- Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ
| | - David A. Raichlen
- Human and Evolutionary Biology Section, Department of Biological Sciences, University of Southern California, CA
| | - Gene E. Alexander
- Department of Psychology and Psychiatry, University of Arizona, Tucson, AZ
- Neuroscience and Physiological Sciences Graduate Inter-Disciplinary Programs, University of Arizona, Tucson, AZ
- Evelyn F. McKnight Brain Institute, University of Arizona, Tucson, AZ
- Arizona Alzheimer’s Consortium, AZ
| | - James F. Wilson
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UNITED KINGDOM
- MRC Human Genetics Unit, Institute of Genetic and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UNITED KINGDOM
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, THE NETHERLANDS
- Amsterdam Public Health Institute, Amsterdam UMC, THE NETHERLANDS
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, THE NETHERLANDS
- Amsterdam Public Health Institute, Amsterdam UMC, THE NETHERLANDS
| | - Eco J.C. de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, THE NETHERLANDS
- Amsterdam Public Health Institute, Amsterdam UMC, THE NETHERLANDS
| | - Nicola Pirastu
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UNITED KINGDOM
| |
Collapse
|
24
|
Younger adults tolerate more relational risks in everyday life as revealed by the general risk-taking questionnaire. Sci Rep 2022; 12:12184. [PMID: 35842465 PMCID: PMC9288464 DOI: 10.1038/s41598-022-16438-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2021] [Accepted: 07/11/2022] [Indexed: 12/02/2022] Open
Abstract
A range of self-report questionnaires were developed to quantify one’s risk-taking (RT) tendency. Exploring people’s perceived risk level associated with negative risk behaviors is essential to develop a better understanding and intervention policies for RT. In the present study, we proposed a 2 × 10-item scale, namely, the general risk-taking questionnaire (GRTQ), to evaluate RT tendency and risk attitude among the general population by measuring people’s engagement in and perceptions toward 10 commonly known risky behaviors. A total of 2984 adults residing in 10 prefectures in Japan (age range = 20–59, 53.12% female) provided valid responses to an online survey. Apart from the factor analysis procedures, multivariate negative binomial regression models have been applied to investigate the relationship between RT engagement and perception. We obtained two identical factors, namely, personal risk and relational risk, for both scales of the GRTQ. Increased levels of RT engagement were found in younger, male, nonmarried, nonparent and urban respondents. Despite an overall negative correlation between RT engagement and perception, our model revealed a weaker linkage in the younger population for relational risk behaviors. Overall, we showed evidence that the GRTQ is an easy-to-administer, valid and reliable measure of RT for future clinical research.
Collapse
|
25
|
Kandaswamy R, Allegrini A, Nancarrow AF, Cave SN, Plomin R, von Stumm S. Predicting Alcohol Use From Genome-Wide Polygenic Scores, Environmental Factors, and Their Interactions in Young Adulthood. Psychosom Med 2022; 84:244-250. [PMID: 34469941 DOI: 10.1097/psy.0000000000001005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
OBJECTIVE Alcohol use during emerging adulthood is associated with adverse life outcomes, but its risk factors are not well known. Here, we predicted alcohol use in 3153 young adults aged 22 years from a) genome-wide polygenic scores (GPS) based on genome-wide association studies for the target phenotypes number of drinks per week and Alcohol Use Disorders Identification Test scores, b) 30 environmental factors, and c) their interactions (i.e., G × E effects). METHODS Data were collected from 1994 to 2018 as a part of the UK Twins Early Development Study. RESULTS GPS accounted for up to 1.9% of the variance in alcohol use (i.e., Alcohol Use Disorders Identification Test score), whereas the 30 measures of environmental factors together accounted for 21.1%. The 30 GPS by environment interactions did not explain any additional variance, and none of the interaction terms exceeded the significance threshold after correcting for multiple testing. CONCLUSIONS GPS and some environmental factors significantly predicted alcohol use in young adulthood, but we observed no GPS by environment interactions in our study.
Collapse
Affiliation(s)
- Radhika Kandaswamy
- From the Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience (Kandaswamy, Allegrini, Plomin), King's College London, London; Department of Education (Nancarrow, von Stumm), University of York, Heslington, York, United Kingdom; and School of Psychology (Cave), University of Nottingham, Nottingham, United Kingdom
| | | | | | | | | | | |
Collapse
|
26
|
Wang H, Alda M, Trappenberg T, Nunes A. A scoping review and comparison of approaches for measuring genetic heterogeneity in psychiatric disorders. Psychiatr Genet 2022; 32:1-8. [PMID: 34694248 DOI: 10.1097/ypg.0000000000000304] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
An improved understanding of genetic etiological heterogeneity in a psychiatric condition may help us (a) isolate a neurophysiological 'final common pathway' by identifying its upstream genetic origins and (b) facilitate characterization of the condition's phenotypic variation. This review aims to identify existing genetic heterogeneity measurements in the psychiatric literature and provides a conceptual review of their mechanisms, limitations, and assumptions. The Scopus database was searched for studies that quantified genetic heterogeneity or correlation of psychiatric phenotypes with human genetic data. Ninety studies were included. Eighty-seven reports quantified genetic correlation, five applied genomic structural equation modelling, three evaluated departure from the Hardy-Weinberg equilibrium at one or more loci, and two applied a novel approach known as MiXeR. We found no study that rigorously measured genetic etiological heterogeneity across a large number of markers. Developing such approaches may help better characterize the biological diversity of psychopathology.
Collapse
Affiliation(s)
| | - Martin Alda
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
| | | | - Abraham Nunes
- Faculty of Computer Science
- Department of Psychiatry, Dalhousie University, Halifax, Nova Scotia, Canada
| |
Collapse
|
27
|
Rolls ET, Wan Z, Cheng W, Feng J. Risk-taking in humans and the medial orbitofrontal cortex reward system. Neuroimage 2022; 249:118893. [PMID: 35007715 DOI: 10.1016/j.neuroimage.2022.118893] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 12/28/2021] [Accepted: 01/06/2022] [Indexed: 11/29/2022] Open
Abstract
Risk-taking differs between humans, and is associated with the personality measures of impulsivity and sensation-seeking. To analyse the brain systems involved, self-report risk-taking, resting state functional connectivity, and related behavioral measures were analyzed in 18,740 participants of both sexes from the UK Biobank. Functional connectivities of the medial orbitofrontal cortex, ventromedial prefrontal cortex (VMPFC), and the parahippocampal areas were significantly higher in the risk-taking group (p < 0.001, FDR corrected). The risk-taking measure was validated in that it was significantly associated with alcohol drinking amount (r = 0.08, p = 5.1×10-28), cannabis use (r = 0.12, p = 6.0×10-66), and anxious feelings (r = -0.12, p = 7.6×-98). The functional connectivity findings were cross-validated in two independent datasets. The higher functional connectivity of the medial orbitofrontal cortex and VMPFC included higher connectivity with the anterior cingulate cortex, which provides a route for these reward-related regions to have a greater influence on action in risk-taking individuals. In conclusion, the medial orbitofrontal cortex, which is involved in reward value and pleasure, was found to be related to risk-taking, which is associated with impulsivity. An implication is that risk-taking is driven by specific orbitofrontal cortex reward systems, and is different for different rewards which are represented differently in the brains of different individuals. This is an advance in understanding the bases and mechanisms of risk-taking in humans, given that the orbitofrontal cortex, VMPFC and anterior cingulate cortex are highly developed in humans, and that risk-taking can be reported in humans.
Collapse
Affiliation(s)
- Edmund T Rolls
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK; Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, 200433, China; Oxford Centre for Computational Neuroscience, Oxford, UK.
| | - Zhuo Wan
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK
| | - Wei Cheng
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, 200433, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, 200433, China; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China
| | - Jianfeng Feng
- Department of Computer Science, University of Warwick, Coventry CV4 7AL, UK; Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, 200433, China; Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence, Fudan University, Ministry of Education, Shanghai, 200433, China; Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China
| |
Collapse
|
28
|
Bondy E, Bogdan R. Understanding Anhedonia from a Genomic Perspective. Curr Top Behav Neurosci 2022; 58:61-79. [PMID: 35152374 PMCID: PMC9375777 DOI: 10.1007/7854_2021_293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Anhedonia, or the decreased ability to experience pleasure, is a cardinal symptom of major depression that commonly occurs within other forms of psychopathology. Supportive of long-held theory that anhedonia represents a genetically influenced vulnerability marker for depression, evidence from twin studies suggests that it is moderately-largely heritable. However, the genomic sources of this heritability are just beginning to be understood. In this review, we survey what is known about the genomic architecture underlying anhedonia and related constructs. We briefly review twin and initial candidate gene studies before focusing on genome-wide association study (GWAS) and polygenic efforts. As large samples are needed to reliably detect the small effects that typically characterize common genetic variants, the study of anhedonia and related phenotypes conflicts with current genomic research requirements and frameworks that prioritize sample size over precise phenotyping. This has resulted in few and underpowered studies of anhedonia-related constructs that have largely failed to reliably identify individual variants. Nonetheless, the polygenic architecture of anhedonia-related constructs identified in these studies has genetic overlap with depression and schizophrenia as well as related brain structure (e.g., striatal volume), providing important clues to etiology that may usefully guide refinement in nosology. As we await the accumulation of larger samples for more well-powered GWAS of reward-related constructs, novel analytic techniques that leverage GWAS summary statistics (e.g., genomic structural equation modeling) may currently be used to help characterize how the genomic architecture of anhedonia is shared and distinct from that underlying other constructs (e.g., depression, neuroticism, anxiety).
Collapse
Affiliation(s)
- Erin Bondy
- Department of Psychological and Brain Sciences, Washington University in Saint Louis, St. Louis, MO, USA
| | - Ryan Bogdan
- Department of Psychological and Brain Sciences, Washington University in Saint Louis, St. Louis, MO, USA.
| |
Collapse
|
29
|
Brick LA, Benca-Bachman CE, Bertin L, Martin KP, Risner V, Palmer RHC. The intermediary role of adolescent temperamental and behavioral traits on the prospective associations between polygenic risk and cannabis use among young adults of European Ancestry. Addiction 2021; 116:2779-2789. [PMID: 33686717 PMCID: PMC8426427 DOI: 10.1111/add.15476] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 10/14/2020] [Accepted: 02/24/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND AND AIMS Cannabis use (CU) is an etiologically complex behavior with several social, temperamental, neurocognitive, and behavioral precursors. Biometrical and molecular studies suggest an interplay of environmental and pleiotropic influences. However, it remains unclear whether identified genetic effects related to behavioral and temperamental characteristics have developmentally direct or indirect mechanisms on CU behavior. The Transmissible Liability Index (TLI) is a measure of continuous liability based on developmental precursors of substance use disorders. This study aimed to examine if the TLI plays a role in understanding genetic risk for CU behaviors. DESIGN Genome-wide association studies (n > 10 000; European Ancestry [EA]) of CU, risk tolerance, neuroticism, anxiety, and depression were used to construct polygenic scores (PGSs). Analyses assessed whether PGSs indirectly impacted risk for repeated use via TLI. SETTING United States of America. PARTICIPANTS From Add Health study, 4077 individuals of EA age 11 to 21 during baseline interview collection. MEASUREMENTS Outcomes were initiation and repeated cannabis use (>5× in lifetime). The TLI was parameterized using a latent factor from 21 questions assessing for precursors of disordered use. FINDINGS The marker-based heritability of TLI, initiation, and repeated use were significant, but modest (14%, P = 0.033; 15%, P = 0.025; and 17%, P = 0.008, respectively). TLI and repeated use were genetically correlated (rg = 0.76, P = 0.033). The PGS for CU was associated with increased risk for repeated use and PGS for risk tolerance and depression were associated with TLI. Mediation analyses indicated significant, but very weak, indirect effects of PGS for risk tolerance and depression on repeated CU via the TLI. CONCLUSIONS Adolescent behavioral and temperamental characteristics (i.e. the Transmissible Liability Index) appear to be early indicators of repeated cannabis use in adulthood. Although polygenic scores for cannabis use directly increased risk for repeated cannabis use, weak evidence was found for the role of polygenic scores of other internalizing/externalizing traits acting through adolescent derived Transmissible Liability Index on cannabis use behavior.
Collapse
Affiliation(s)
- Leslie A Brick
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, Georgia, USA,Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Chelsie E Benca-Bachman
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, Georgia, USA
| | - Lauren Bertin
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, Georgia, USA
| | - Kathleen P Martin
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, Georgia, USA
| | - Victoria Risner
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, Georgia, USA
| | - Rohan HC Palmer
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, Georgia, USA
| |
Collapse
|
30
|
Hindley G, Bahrami S, Steen NE, O'Connell KS, Frei O, Shadrin A, Bettella F, Rødevand L, Fan CC, Dale AM, Djurovic S, Smeland OB, Andreassen OA. Characterising the shared genetic determinants of bipolar disorder, schizophrenia and risk-taking. Transl Psychiatry 2021; 11:466. [PMID: 34497263 PMCID: PMC8426401 DOI: 10.1038/s41398-021-01576-4] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/19/2021] [Revised: 07/19/2021] [Accepted: 08/18/2021] [Indexed: 02/08/2023] Open
Abstract
Increased risk-taking is a central component of bipolar disorder (BIP) and is implicated in schizophrenia (SCZ). Risky behaviours, including smoking and alcohol use, are overrepresented in both disorders and associated with poor health outcomes. Positive genetic correlations are reported but an improved understanding of the shared genetic architecture between risk phenotypes and psychiatric disorders may provide insights into underlying neurobiological mechanisms. We aimed to characterise the genetic overlap between risk phenotypes and SCZ, and BIP by estimating the total number of shared variants using the bivariate causal mixture model and identifying shared genomic loci using the conjunctional false discovery rate method. Summary statistics from genome wide association studies of SCZ, BIP, risk-taking and risky behaviours were acquired (n = 82,315-466,751). Genomic loci were functionally annotated using FUMA. Of 8.6-8.7 K variants predicted to influence BIP, 6.6 K and 7.4 K were predicted to influence risk-taking and risky behaviours, respectively. Similarly, of 10.2-10.3 K variants influencing SCZ, 9.6 and 8.8 K were predicted to influence risk-taking and risky behaviours, respectively. We identified 192 loci jointly associated with SCZ and risk phenotypes and 206 associated with BIP and risk phenotypes, of which 68 were common to both risk-taking and risky behaviours and 124 were novel to SCZ or BIP. Functional annotation implicated differential expression in multiple cortical and sub-cortical regions. In conclusion, we report extensive polygenic overlap between risk phenotypes and BIP and SCZ, identify specific loci contributing to this shared risk and highlight biologically plausible mechanisms that may underlie risk-taking in severe psychiatric disorders.
Collapse
Affiliation(s)
- Guy Hindley
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway.
- Psychosis Studies, Institute of Psychiatry, Psychology and Neurosciences, King's College London, London, UK.
| | - Shahram Bahrami
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Nils Eiel Steen
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Kevin S O'Connell
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Oleksandr Frei
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
- Center for Bioinformatics, Department of Informatics, University of Oslo, Blindern, 0316, Oslo, Norway
| | - Alexey Shadrin
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Francesco Bettella
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Linn Rødevand
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Chun C Fan
- Department of Neurology, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- Multimodal Imaging Laboratory, University of California San Diego, La Jolla, CA, 92093, USA
| | - Anders M Dale
- Department of Neurology, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
- Department of Radiology, University of California, San Diego, La Jolla, CA, 92093, USA
- Department of Cognitive Science, University of California, San Diego, La Jolla, CA, USA
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway
- NORMENT, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Olav B Smeland
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway
| | - Ole A Andreassen
- NORMENT, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, 0407, Oslo, Norway.
| |
Collapse
|
31
|
Nectins and Nectin-like molecules in synapse formation and involvement in neurological diseases. Mol Cell Neurosci 2021; 115:103653. [PMID: 34242750 DOI: 10.1016/j.mcn.2021.103653] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 05/11/2021] [Accepted: 06/25/2021] [Indexed: 12/12/2022] Open
Abstract
Synapses are interneuronal junctions which form neuronal networks and play roles in a variety of functions, including learning and memory. Two types of junctions, synaptic junctions (SJs) and puncta adherentia junctions (PAJs), have been identified. SJs are found at all excitatory and inhibitory synapses whereas PAJs are found at excitatory synapses, but not inhibitory synapses, and particularly well developed at hippocampal mossy fiber giant excitatory synapses. Both SJs and PAJs are mediated by cell adhesion molecules (CAMs). Major CAMs at SJs are neuroligins-neurexins and Nectin-like molecules (Necls)/CADMs/SynCAMs whereas those at PAJs are nectins and cadherins. In addition to synaptic PAJs, extrasynaptic PAJs have been identified at contact sites between neighboring dendrites near synapses and regulate synapse formation. In addition to SJs and PAJs, a new type of cell adhesion apparatus different from these junctional apparatuses has been identified and named nectin/Necl spots. One nectin spot at contact sites between neighboring dendrites at extrasynaptic regions near synapses regulates synapse formation. Several members of nectins and Necls had been identified as viral receptors before finding their physiological functions as CAMs and evidence is accumulating that many nectins and Necls are related to onset and progression of neurological diseases. We review here nectin and Necls in synapse formation and involvement in neurological diseases.
Collapse
|
32
|
Ausmees L, Talts M, Allik J, Vainik U, Sikka TT, Nikopensius T, Esko T, Realo A. Taking risks to feel excitement: Detailed personality profile and genetic associations. EUROPEAN JOURNAL OF PERSONALITY 2021. [DOI: 10.1177/08902070211019242] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
This study mapped the personality and genetics of risky excitement-seekers focusing on skydiving behavior. We compared 298 skydivers to 298 demographically matched controls across the NEO Personality Inventory-3 domains, facets, and 240 items. The most significant item-level effects were aggregated into a poly-item score of skydiving-associated personality markers (Study 1), where higher scores describe individuals who enjoy risky situations but have no self-control issues. The skydiving-associated personality marker score was associated with greater physical activity, higher rate of traumatic injuries, and better mental health in a sample of 3558 adults (Study 2). From genetic perspective, we associated skydiving behavior with 19 candidate variants that have previously been linked to excitement-seeking (Study 1). Polymorphisms in the SERT gene were the strongest predictors of skydiving, but the false discovery rate-adjusted (FDR-adjusted) p-values were non-significant. In Study 2, we predicted the skydiving-associated personality marker score and E5: Excitement-seeking from multiple risk-taking polygenic scores, using publicly available summary data from genome-wide association studies. While E5: Excitement-seeking was most strongly predicted by general risk tolerance and risky behaviors’ polygenic scores, the skydiving-associated personality marker score was most strongly associated with the adventurousness polygenic scores. Phenotypic and polygenic scores associations suggest that skydiving is a specific—perhaps more functional—form of excitement-seeking, which may nevertheless lead to physical injuries.
Collapse
Affiliation(s)
- Liisi Ausmees
- Institute of Psychology, University of Tartu, Estonia
| | - Maie Talts
- Institute of Psychology, University of Tartu, Estonia
| | - Jüri Allik
- Institute of Psychology, University of Tartu, Estonia
- Estonian Academy of Sciences, Estonia
| | - Uku Vainik
- Institute of Psychology, University of Tartu, Estonia
- Montreal Neurological Institute, McGill University, Canada
| | | | | | - Tõnu Esko
- Institute of Genomics, University of Tartu, Estonia
| | - Anu Realo
- Institute of Psychology, University of Tartu, Estonia
- Department of Psychology, University of Warwick, UK
| |
Collapse
|
33
|
Genome-wide association study of early-onset bipolar I disorder in the Han Taiwanese population. Transl Psychiatry 2021; 11:301. [PMID: 34016946 PMCID: PMC8137921 DOI: 10.1038/s41398-021-01407-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2020] [Revised: 04/05/2021] [Accepted: 04/21/2021] [Indexed: 02/04/2023] Open
Abstract
The search for susceptibility genes underlying the heterogeneous bipolar disorder has been inconclusive, often with irreproducible results. There is a hope that narrowing the phenotypes will increase the power of genetic analysis. Early-onset bipolar disorder is thought to be a genetically homogeneous subtype with greater symptom severity. We conducted a genome-wide association study (GWAS) for this subtype in bipolar I (BPI) disorder. Study participants included 1779 patients of Han Chinese descent with BPI disorder recruited by the Taiwan Bipolar Consortium. We conducted phenotype assessment using the Chinese version of the Schedules for Clinical Assessment in Neuropsychiatry and prepared a life chart with graphic depiction of lifetime clinical course for each of the BPI patient recruited. The assessment of onset age was based on this life chart with early onset defined as ≤20 years of age. We performed GWAS in a discovery group of 516 early-onset and 790 non-early-onset BPI patients, followed by a replication study in an independent group of 153 early-onset and 320 non-early-onset BPI patients and a meta-analysis with these two groups. The SNP rs11127876, located in the intron of CADM2, showed association with early-onset BPI in the discovery cohort (P = 7.04 × 10-8) and in the test of replication (P = 0.0354). After meta-analysis, this SNP was demonstrated to be a new genetic locus in CADM2 gene associated with early-onset BPI disorder (P = 5.19 × 10-8).
Collapse
|
34
|
Better the devil you know than the devil you don't: Neural processing of risk and ambiguity. Neuroimage 2021; 236:118109. [PMID: 33940147 DOI: 10.1016/j.neuroimage.2021.118109] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 04/14/2021] [Accepted: 04/18/2021] [Indexed: 11/23/2022] Open
Abstract
Risk and ambiguity are inherent in virtually all human decision-making. Risk refers to a situation in which we know the precise probability of potential outcomes of each option, whereas ambiguity refers to a situation in which outcome probabilities are not known. A large body of research has shown that individuals prefer known risks to ambiguity, a phenomenon known as ambiguity aversion. One heated debate concerns whether risky and ambiguous decisions rely on the same or distinct neural circuits. In the current meta-analyses, we integrated the results of neuroimaging research on decision-making under risk (n = 69) and ambiguity (n = 31). Our results showed that both processing of risk and ambiguity showed convergence in anterior insula, indicating a key role of anterior insula in encoding uncertainty. Risk additionally engaged dorsomedial prefrontal cortex (dmPFC) and ventral striatum, whereas ambiguity specifically recruited the dorsolateral prefrontal cortex (dlPFC), inferior parietal lobe (IPL) and right anterior insula. Our findings demonstrate overlapping and distinct neural substrates underlying different types of uncertainty, guiding future neuroimaging research on risk-taking and ambiguity aversion.
Collapse
|
35
|
Hamer D, Mustanski B, Sell R, Sanders SA, Garcia JR. Comment on “Large-scale GWAS reveals insights into the genetic architecture of same-sex sexual behavior”. Science 2021; 371:371/6536/eaba2941. [DOI: 10.1126/science.aba2941] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2019] [Accepted: 03/09/2021] [Indexed: 12/15/2022]
Affiliation(s)
- Dean Hamer
- National Cancer Institute, Bethesda, MD 20892, USA
- Qwaves Media, Haleiwa, HI 96712, USA
| | - Brian Mustanski
- Institute for Sexual and Gender Minority Health and Wellbeing, Northwestern University, Chicago, IL 60611, USA
- Department of Medical Social Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL 60601, USA
| | - Randall Sell
- Department of Community Health and Prevention, Drexel University School of Public Health, Philadelphia, PA 19104, USA
| | - Stephanie A. Sanders
- Kinsey Institute, Indiana University, Bloomington, IN 47405, USA
- Department of Gender Studies, Indiana University, Bloomington, IN 47405, USA
| | - Justin R. Garcia
- Kinsey Institute, Indiana University, Bloomington, IN 47405, USA
- Department of Gender Studies, Indiana University, Bloomington, IN 47405, USA
| |
Collapse
|
36
|
Thorpe HHA, Talhat MA, Khokhar JY. High genes: Genetic underpinnings of cannabis use phenotypes. Prog Neuropsychopharmacol Biol Psychiatry 2021; 106:110164. [PMID: 33152387 DOI: 10.1016/j.pnpbp.2020.110164] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Revised: 09/25/2020] [Accepted: 10/29/2020] [Indexed: 12/19/2022]
Abstract
Cannabis is one of the most widely used substances across the globe and its use has a substantial heritable component. However, the heritability of cannabis use varies according to substance use phenotype, suggesting that a unique profile of gene variants may contribute to the different stages of use, such as age of use onset, lifetime use, cannabis use disorder, and withdrawal and craving during abstinence. Herein, we review a subset of genes identified by candidate gene, family-based linkage, and genome-wide association studies related to these cannabis use phenotypes. We also describe their relationships with other substances, and their functions at the neurobiological, cognitive, and behavioral levels to hypothesize the role of these genes in cannabis use risk. Delineating genetic risk factors in the various stages of cannabis use will provide insight into the biological mechanisms related to cannabis use and highlight points of intervention prior to and following the development of dependence, as well as identify targets to aid drug development for treating problematic cannabis use.
Collapse
Affiliation(s)
- Hayley H A Thorpe
- Department of Biomedical Sciences, University of Guelph, Guelph, ON, Canada
| | | | - Jibran Y Khokhar
- Department of Biomedical Sciences, University of Guelph, Guelph, ON, Canada.
| |
Collapse
|
37
|
Carrier M, Guilbert J, Lévesque JP, Tremblay MÈ, Desjardins M. Structural and Functional Features of Developing Brain Capillaries, and Their Alteration in Schizophrenia. Front Cell Neurosci 2021; 14:595002. [PMID: 33519380 PMCID: PMC7843388 DOI: 10.3389/fncel.2020.595002] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2020] [Accepted: 12/04/2020] [Indexed: 12/19/2022] Open
Abstract
Schizophrenia affects more than 1% of the world's population and shows very high heterogeneity in the positive, negative, and cognitive symptoms experienced by patients. The pathogenic mechanisms underlying this neurodevelopmental disorder are largely unknown, although it is proposed to emerge from multiple genetic and environmental risk factors. In this work, we explore the potential alterations in the developing blood vessel network which could contribute to the development of schizophrenia. Specifically, we discuss how the vascular network evolves during early postnatal life and how genetic and environmental risk factors can lead to detrimental changes. Blood vessels, capillaries in particular, constitute a dynamic and complex infrastructure distributing oxygen and nutrients to the brain. During postnatal development, capillaries undergo many structural and anatomical changes in order to form a fully functional, mature vascular network. Advanced technologies like magnetic resonance imaging and near infrared spectroscopy are now enabling to study how the brain vasculature and its supporting features are established in humans from birth until adulthood. Furthermore, the contribution of the different neurovascular unit elements, including pericytes, endothelial cells, astrocytes and microglia, to proper brain function and behavior, can be dissected. This investigation conducted among different brain regions altered in schizophrenia, such as the prefrontal cortex, may provide further evidence that schizophrenia can be considered a neurovascular disorder.
Collapse
Affiliation(s)
- Micaël Carrier
- Axe Neurosciences, Centre de recherche du CHU de Québec - Université Laval, Québec, QC, Canada.,Department of Molecular Medicine, Université Laval, Québec, QC, Canada
| | - Jérémie Guilbert
- Axe Oncologie, Centre de recherche du CHU de Québec, Université Laval, Québec, QC, Canada.,Department of Physics, Physical Engineering and Optics, Université Laval, Québec, QC, Canada
| | - Jean-Philippe Lévesque
- Axe Oncologie, Centre de recherche du CHU de Québec, Université Laval, Québec, QC, Canada.,Department of Physics, Physical Engineering and Optics, Université Laval, Québec, QC, Canada
| | - Marie-Ève Tremblay
- Axe Neurosciences, Centre de recherche du CHU de Québec - Université Laval, Québec, QC, Canada.,Department of Molecular Medicine, Université Laval, Québec, QC, Canada.,Division of Medical Sciences, University of Victoria, Victoria, BC, Canada.,Department of Biochemistry and Molecular Biology, The University of British Columbia, Vancouver, BC, Canada.,Neurology and Neurosurgery Department, McGill University, Montréal, QC, Canada
| | - Michèle Desjardins
- Axe Oncologie, Centre de recherche du CHU de Québec, Université Laval, Québec, QC, Canada.,Department of Physics, Physical Engineering and Optics, Université Laval, Québec, QC, Canada
| |
Collapse
|
38
|
Morris J, Leung SSY, Bailey ME, Cullen B, Ferguson A, Graham N, Johnston KJA, Lyall DM, Lyall LM, Ward J, Smith DJ, Strawbridge RJ. Exploring the Role of Contactins across Psychological, Psychiatric and Cardiometabolic Traits within UK Biobank. Genes (Basel) 2020; 11:E1326. [PMID: 33182605 PMCID: PMC7697406 DOI: 10.3390/genes11111326] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Revised: 11/05/2020] [Accepted: 11/07/2020] [Indexed: 12/17/2022] Open
Abstract
Individuals with severe mental illness have an increased risk of cardiometabolic diseases compared to the general population. Shared risk factors and medication effects explain part of this excess risk; however, there is growing evidence to suggest that shared biology (including genetic variation) is likely to contribute to comorbidity between mental and physical illness. Contactins are a family of genes involved in development of the nervous system and implicated, though genome-wide association studies, in a wide range of psychological, psychiatric and cardiometabolic conditions. Contactins are plausible candidates for shared pathology between mental and physical health. We used data from UK Biobank to systematically assess how genetic variation in contactin genes was associated with a wide range of psychological, psychiatric and cardiometabolic conditions. We also investigated whether associations for cardiometabolic and psychological traits represented the same or distinct signals and how the genetic variation might influence the measured traits. We identified: A novel genetic association between variation in CNTN1 and current smoking; two independent signals in CNTN4 for BMI; and demonstrated that associations between CNTN5 and neuroticism were distinct from those between CNTN5 and blood pressure/HbA1c. There was no evidence that the contactin genes contributed to shared aetiology between physical and mental illness.
Collapse
Affiliation(s)
- Julia Morris
- Institute of Health and Wellbeing, University of Glasgow, Glasgow G12 8RZ, UK; (J.M.); (S.S.Y.L.); (B.C.); (A.F.); (N.G.); (K.J.A.J.); (D.M.L.); (L.M.L.); (J.W.); (D.J.S.)
| | - Soddy Sau Yu Leung
- Institute of Health and Wellbeing, University of Glasgow, Glasgow G12 8RZ, UK; (J.M.); (S.S.Y.L.); (B.C.); (A.F.); (N.G.); (K.J.A.J.); (D.M.L.); (L.M.L.); (J.W.); (D.J.S.)
| | - Mark E.S. Bailey
- School of Life Sciences, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK;
| | - Breda Cullen
- Institute of Health and Wellbeing, University of Glasgow, Glasgow G12 8RZ, UK; (J.M.); (S.S.Y.L.); (B.C.); (A.F.); (N.G.); (K.J.A.J.); (D.M.L.); (L.M.L.); (J.W.); (D.J.S.)
| | - Amy Ferguson
- Institute of Health and Wellbeing, University of Glasgow, Glasgow G12 8RZ, UK; (J.M.); (S.S.Y.L.); (B.C.); (A.F.); (N.G.); (K.J.A.J.); (D.M.L.); (L.M.L.); (J.W.); (D.J.S.)
| | - Nicholas Graham
- Institute of Health and Wellbeing, University of Glasgow, Glasgow G12 8RZ, UK; (J.M.); (S.S.Y.L.); (B.C.); (A.F.); (N.G.); (K.J.A.J.); (D.M.L.); (L.M.L.); (J.W.); (D.J.S.)
| | - Keira J. A. Johnston
- Institute of Health and Wellbeing, University of Glasgow, Glasgow G12 8RZ, UK; (J.M.); (S.S.Y.L.); (B.C.); (A.F.); (N.G.); (K.J.A.J.); (D.M.L.); (L.M.L.); (J.W.); (D.J.S.)
- School of Life Sciences, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow G12 8QQ, UK;
- Deanery of Molecular, Genetic and Population Health Sciences, College of Medicine and Veterinary Medicine, University of Edinburgh, Edinburgh EH8 9AG, UK
| | - Donald M. Lyall
- Institute of Health and Wellbeing, University of Glasgow, Glasgow G12 8RZ, UK; (J.M.); (S.S.Y.L.); (B.C.); (A.F.); (N.G.); (K.J.A.J.); (D.M.L.); (L.M.L.); (J.W.); (D.J.S.)
| | - Laura M. Lyall
- Institute of Health and Wellbeing, University of Glasgow, Glasgow G12 8RZ, UK; (J.M.); (S.S.Y.L.); (B.C.); (A.F.); (N.G.); (K.J.A.J.); (D.M.L.); (L.M.L.); (J.W.); (D.J.S.)
| | - Joey Ward
- Institute of Health and Wellbeing, University of Glasgow, Glasgow G12 8RZ, UK; (J.M.); (S.S.Y.L.); (B.C.); (A.F.); (N.G.); (K.J.A.J.); (D.M.L.); (L.M.L.); (J.W.); (D.J.S.)
| | - Daniel J. Smith
- Institute of Health and Wellbeing, University of Glasgow, Glasgow G12 8RZ, UK; (J.M.); (S.S.Y.L.); (B.C.); (A.F.); (N.G.); (K.J.A.J.); (D.M.L.); (L.M.L.); (J.W.); (D.J.S.)
| | - Rona J. Strawbridge
- Institute of Health and Wellbeing, University of Glasgow, Glasgow G12 8RZ, UK; (J.M.); (S.S.Y.L.); (B.C.); (A.F.); (N.G.); (K.J.A.J.); (D.M.L.); (L.M.L.); (J.W.); (D.J.S.)
- Health Data Research UK, Glasgow G12 8RZ, UK
- Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, 171 77 Stockholm, Sweden
| |
Collapse
|
39
|
Identification of candidate genetic variants and altered protein expression in neural stem and mature neural cells support altered microtubule function to be an essential component in bipolar disorder. Transl Psychiatry 2020; 10:390. [PMID: 33168801 PMCID: PMC7652854 DOI: 10.1038/s41398-020-01056-1] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Revised: 09/07/2020] [Accepted: 09/29/2020] [Indexed: 01/31/2023] Open
Abstract
Identification of causative genetic variants leading to the development of bipolar disorder (BD) could result in genetic tests that would facilitate diagnosis. A better understanding of affected genes and pathways is also necessary for targeting of genes that may improve treatment strategies. To date several susceptibility genes have been reported from genome-wide association studies (GWAS), but little is known about specific variants that affect disease development. Here, we performed quantitative proteomics and whole-genome sequencing (WGS). Quantitative proteomics revealed NLRP2 as the most significantly up-regulated protein in neural stem cells and mature neural cells obtained from BD-patient cell samples. These results are in concordance with our previously published transcriptome analysis. Furthermore, the levels of FEZ2 and CADM2 proteins were also significantly differentially expressed in BD compared to control derived cells. The levels of FEZ2 were significantly downregulated in neural stem cells (NSC) while CADM2 was significantly up-regulated in mature neuronal cell culture. Promising novel candidate mutations were identified in the ANK3, NEK3, NEK7, TUBB, ANKRD1, and BRD2 genes. A literature search of candidate variants and deregulated proteins revealed that there are several connections to microtubule function for the molecules putatively involved. Microtubule function in neurons is critical for axon structure and axonal transport. A functional dynamic microtubule is also needed for an advocate response to cellular and environmental stress. If microtubule dynamics is compromised by mutations, it could be followed by deregulated expression forming a possible explanation for the inherited vulnerability to stressful life events that have been proposed to trigger mood episodes in BD patients.
Collapse
|
40
|
Getz LJ, Dellaire G. Back to Basics: Application of the Principles of Bioethics to Heritable Genome Interventions. SCIENCE AND ENGINEERING ETHICS 2020; 26:2735-2748. [PMID: 32524426 DOI: 10.1007/s11948-020-00226-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Accepted: 05/21/2020] [Indexed: 06/11/2023]
Abstract
Prior to their announcement of the birth of gene-edited twins in China, Dr. He Jiankui and colleagues published a set of draft ethical principles for discussing the legal, social, and ethical aspects of heritable genome interventions. Within this document, He and colleagues made it clear that their goal with these principles was to "clarify for the public the clinical future of early-in-life genetic surgeries" or heritable genome editing. In light of He's widely criticized gene editing experiments it is of interest to place these draft principles in the larger ethical debate surrounding heritable genome editing. Here we examine the principles proposed by He and colleagues through the lens of Beauchamp and Childress' Principles of Biomedical Ethics. We also analyze the stated goal that the "clinical future" of heritable genome editing was clarified by He and colleagues' proposed principles. Finally, we highlight what might be done to help prevent individual actors from pushing forward ahead of broad societal consensus on heritable genome editing.
Collapse
Affiliation(s)
- Landon J Getz
- Department of Microbiology and Immunology, Faculty of Medicine, Dalhousie University, PO Box 15000, Halifax, NS, B3H 4R2, Canada
| | - Graham Dellaire
- Department of Pathology, Faculty of Medicine, Dalhousie University, PO BOX 15000, Halifax, NS, B3H 4R2, Canada.
- Department of Biochemistry and Molecular Biology, Faculty of Medicine, Dalhousie University, Halifax, NS, Canada.
| |
Collapse
|
41
|
Dissecting clinical heterogeneity of bipolar disorder using multiple polygenic risk scores. Transl Psychiatry 2020; 10:314. [PMID: 32948743 PMCID: PMC7501305 DOI: 10.1038/s41398-020-00996-y] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Revised: 08/10/2020] [Accepted: 09/03/2020] [Indexed: 12/17/2022] Open
Abstract
Bipolar disorder (BD) has high clinical heterogeneity, frequent psychiatric comorbidities, and elevated suicide risk. To determine genetic differences between common clinical sub-phenotypes of BD, we performed a systematic polygenic risk score (PRS) analysis using multiple PRSs from a range of psychiatric, personality, and lifestyle traits to dissect differences in BD sub-phenotypes in two BD cohorts: the Mayo Clinic BD Biobank (N = 968) and Genetic Association Information Network (N = 1001). Participants were assessed for history of psychosis, early-onset BD, rapid cycling (defined as four or more episodes in a year), and suicide attempts using questionnaires and the Structured Clinical Interview for DSM-IV. In a combined sample of 1969 bipolar cases (45.5% male), those with psychosis had higher PRS for SCZ (OR = 1.3 per S.D.; p = 3e-5) but lower PRSs for anhedonia (OR = 0.87; p = 0.003) and BMI (OR = 0.87; p = 0.003). Rapid cycling cases had higher PRS for ADHD (OR = 1.23; p = 7e-5) and MDD (OR = 1.23; p = 4e-5) and lower BD PRS (OR = 0.8; p = 0.004). Cases with a suicide attempt had higher PRS for MDD (OR = 1.26; p = 1e-6) and anhedonia (OR = 1.22; p = 2e-5) as well as lower PRS for educational attainment (OR = 0.87; p = 0.003). The observed novel PRS associations with sub-phenotypes align with clinical observations such as rapid cycling BD patients having a greater lifetime prevalence of ADHD. Our findings confirm that genetic heterogeneity contributes to clinical heterogeneity of BD and consideration of genetic contribution to psychopathologic components of psychiatric disorders may improve genetic prediction of complex psychiatric disorders.
Collapse
|
42
|
Allegrini AG, Verweij KJH, Abdellaoui A, Treur JL, Hottenga JJ, Willemsen G, Boomsma DI, Vink JM. Genetic Vulnerability for Smoking and Cannabis Use: Associations With E-Cigarette and Water Pipe Use. Nicotine Tob Res 2020; 21:723-730. [PMID: 30053134 DOI: 10.1093/ntr/nty150] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2017] [Accepted: 07/17/2018] [Indexed: 02/03/2023]
Abstract
INTRODUCTION Cigarette smoking and cannabis use are heritable traits and share, at least in part, a common genetic substrate. In recent years, the prevalence of alternative methods of nicotine intakes, such as electronic cigarette (e-cigarette) and water pipe use, has risen substantially. We tested whether the genetic vulnerability underlying cigarettes smoking and cannabis use explained variability in e-cigarette and water pipe use phenotypes, as these vaping methods are alternatives for smoking tobacco cigarettes and joints. METHODS On the basis of the summary statistics of the International Cannabis Consortium and the Tobacco and Genetics Consortium, we generated polygenic risk scores (PRSs) for smoking and cannabis use traits, and used these to predict e-cigarette and water pipe use phenotypes in a sample of 5025 individuals from the Netherlands Twin Register. RESULTS PRSs for cigarettes per day were positively associated with lifetime e-cigarette use and early initiation of water pipe use, but only in ex-smokers (odds ratio = 1.43, R2 = 1.56%, p = .011) and never cigarette smokers (odds ratio = 1.35, R2 = 1.60%, p = .013) respectively. CONCLUSIONS Most associations of PRSs for cigarette smoking and cannabis use with e-cigarette and water pipe use were not significant, potentially due to a lack of power. The significant associations between genetic liability to smoking heaviness with e-cigarette and water pipe phenotypes are in line with studies indicating a common genetic background for substance-use phenotypes. These associations emerged only in nonsmokers, and future studies should investigate the nature of this observation. IMPLICATIONS Our study showed that genetic vulnerability to smoking heaviness is associated with lifetime e-cigarette use and age at initiation of water pipe use. This finding has implications for the current debate on whether alternative smoking methods, such as usage of vaping devices, predispose to smoking initiation and related behaviors.
Collapse
Affiliation(s)
- Andrea G Allegrini
- Department of Developmental Psychopathology, Behavioural Science Institute, Faculty of Social Sciences, Radboud University, Nijmegen, The Netherlands
| | - Karin J H Verweij
- Department of Developmental Psychopathology, Behavioural Science Institute, Faculty of Social Sciences, Radboud University, Nijmegen, The Netherlands.,Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Abdel Abdellaoui
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.,Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Jorien L Treur
- Department of Developmental Psychopathology, Behavioural Science Institute, Faculty of Social Sciences, Radboud University, Nijmegen, The Netherlands
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | - Jacqueline M Vink
- Department of Developmental Psychopathology, Behavioural Science Institute, Faculty of Social Sciences, Radboud University, Nijmegen, The Netherlands
| |
Collapse
|
43
|
Dahlén A, Wagle M, Zarei M, Guo S. Heritable natural variation of light/dark preference in an outbred zebrafish population. J Neurogenet 2019; 33:199-208. [PMID: 31544554 DOI: 10.1080/01677063.2019.1663846] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Anxiety is a fear-like response to stimuli perceived to be threatening. Excessive or uncontrollable anxiety is a debilitating psychiatric disorder which affects many people throughout their lifetime. In unravelling the complex genetic and environmental regulations of anxiety-like phenotypes, models measuring the natural dark avoidance of larval zebrafish have shed light on the individual variation and heritability of this anxiety-related trait. Using the light/dark choice paradigm and selective breeding, this study aims to validate previous findings of the variable (VDA) and strong dark aversion (SDA) heritability in AB-WT larval zebrafish using the outbred zebrafish strain EK, which offers more genetic diversity to aid in future molecular mapping efforts. 190 larvae (6 days post fertilization [dpf] and 7 dpf) were tested across four trials and divided into variable (VDA), medium (MDA) and strong (SDA) dark aversion for further in-crosses. VDA and MDA larvae became more explorative with time, whereas SDA larvae rarely left the preferred light zone. The SDA and VDA in-crosses significantly increased the respective phenotypes in the second generation of larvae, whereas VDA × MDA inter-crosses did not. For the second-generation SDA cohort, dark aversion correlated with increased thigmotaxis, which reinforces SDA as an anxiety-like phenotype. Our finding that the dark aversion trait and SDA and VDA phenotypes are heritable in an outbred zebrafish population lays an important foundation for future studies of genetic underpinnings using whole-genome mapping methods. This conserved fear/anxiety-like response in a highly accessible model organism also allows for further pharmacological and behavioral studies to elucidate the etiology of anxiety and the search for novel therapeutics for anxiety disorders.
Collapse
Affiliation(s)
- Amelia Dahlén
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA.,School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, UK
| | - Mahendra Wagle
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA
| | - Mahdi Zarei
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA
| | - Su Guo
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, USA
| |
Collapse
|
44
|
Davis CN, Slutske WS, Martin NG, Agrawal A, Lynskey MT. Genetic and environmental influences on gambling disorder liability: a replication and combined analysis of two twin studies. Psychol Med 2019; 49:1705-1712. [PMID: 30160223 PMCID: PMC6395556 DOI: 10.1017/s0033291718002325] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND Gambling disorder (GD), recognized in Diagnostic and Statistical Manual of Mental Disorders, Version 5 (DSM-5) as a behavioral addiction, is associated with a range of adverse outcomes. However, there has been little research on the genetic and environmental influences on the development of this disorder. This study reports results from the largest twin study of GD conducted to date. METHODS Replication and combined analyses were based on samples of 3292 (mean age 31.8, born 1972-79) and 4764 (mean age 37.7, born 1964-71) male, female, and unlike-sex twin pairs from the Australian Twin Registry. Univariate biometric twin models estimated the proportion of variation in the latent GD liability that could be attributed to genetic, shared environmental, and unique environmental factors, and whether these differed quantitatively or qualitatively for men and women. RESULTS In the replication study, when using a lower GD threshold, there was evidence for significant genetic (60%; 95% confidence interval (CI) 45-76%) and unique environmental (40%; 95% CI 24-56%), but not shared environmental contributions (0%; 95% CI 0-0%) to GD liability; this did not significantly differ from the original study. In the combined analysis, higher GD thresholds (such as one consistent with DSM-5 GD) and a multiple threshold definitions of GD yielded similar results. There was no evidence for quantitative or qualitative sex differences in the liability for GD. CONCLUSIONS Twin studies of GD are few in number but they tell a remarkably similar story: substantial genetic and unique environmental influences, with no evidence for shared environmental contributions or sex differences in GD liability.
Collapse
Affiliation(s)
| | | | | | - Arpana Agrawal
- Washington University School of Medicine, St. Louis, MO, USA
| | - Michael T. Lynskey
- King’s College London Institute of Psychiatry, Psychology & Neuroscience, London, UK
| |
Collapse
|
45
|
Morris J, Bailey MES, Baldassarre D, Cullen B, de Faire U, Ferguson A, Gigante B, Giral P, Goel A, Graham N, Hamsten A, Humphries SE, Johnston KJA, Lyall DM, Lyall LM, Sennblad B, Silveira A, Smit AJ, Tremoli E, Veglia F, Ward J, Watkins H, Smith DJ, Strawbridge RJ. Genetic variation in CADM2 as a link between psychological traits and obesity. Sci Rep 2019; 9:7339. [PMID: 31089183 PMCID: PMC6517397 DOI: 10.1038/s41598-019-43861-9] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Accepted: 05/02/2019] [Indexed: 12/12/2022] Open
Abstract
CADM2 has been associated with a range of behavioural and metabolic traits, including physical activity, risk-taking, educational attainment, alcohol and cannabis use and obesity. Here, we set out to determine whether CADM2 contributes to mechanisms shared between mental and physical health disorders. We assessed genetic variants in the CADM2 locus for association with phenotypes in the UK Biobank, IMPROVE, PROCARDIS and SCARFSHEEP studies, before performing meta-analyses. A wide range of metabolic phenotypes were meta-analysed. Psychological phenotypes analysed in UK Biobank only were major depressive disorder, generalised anxiety disorder, bipolar disorder, neuroticism, mood instability and risk-taking behaviour. In UK Biobank, four, 88 and 172 genetic variants were significantly (p < 1 × 10-5) associated with neuroticism, mood instability and risk-taking respectively. In meta-analyses of 4 cohorts, we identified 362, 63 and 11 genetic variants significantly (p < 1 × 10-5) associated with BMI, SBP and CRP respectively. Genetic effects on BMI, CRP and risk-taking were all positively correlated, and were consistently inversely correlated with genetic effects on SBP, mood instability and neuroticism. Conditional analyses suggested an overlap in the signals for physical and psychological traits. Many significant variants had genotype-specific effects on CADM2 expression levels in adult brain and adipose tissues. CADM2 variants influence a wide range of both psychological and metabolic traits, suggesting common biological mechanisms across phenotypes via regulation of CADM2 expression levels in adipose tissue. Functional studies of CADM2 are required to fully understand mechanisms connecting mental and physical health conditions.
Collapse
Affiliation(s)
- Julia Morris
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Mark E S Bailey
- School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Damiano Baldassarre
- Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milan, Italy
- Centro Cardiologico Monzino, IRCCS, Milan, Italy
| | - Breda Cullen
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Ulf de Faire
- Unit of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Amy Ferguson
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Bruna Gigante
- Unit of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Division of Cardiovascular Medicine, Department of Clinical Sciences, Danderyd University Hospital, Stockholm, Sweden
| | - Philippe Giral
- Assistance Publique-Hopitaux de Paris, Service Endocrinologie-Metabolisme, Groupe Hôpitalier Pitie-Salpetriere, Unités de Prévention Cardiovasculaire, Paris, France
| | - Anuj Goel
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Nicholas Graham
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Anders Hamsten
- Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Steve E Humphries
- Centre for Cardiovascular Genetics, Institute Cardiovascular Science, University College London, London, UK
| | - Keira J A Johnston
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
- School of Life Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
- Division of Psychiatry, College of Medicine, University of Edinburgh, Edinburgh, UK
| | - Donald M Lyall
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Laura M Lyall
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Bengt Sennblad
- Department of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Angela Silveira
- Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Andries J Smit
- Department of Medicine, University Medical Center Groningen and University of Groningen, Groningen, The Netherlands
| | - Elena Tremoli
- Centro Cardiologico Monzino, IRCCS, Milan, Italy
- Dipartimento di Scienze Farmacologiche e Biomolecolari, Università di Milano, Milan, Italy
| | | | - Joey Ward
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Hugh Watkins
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Daniel J Smith
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
| | - Rona J Strawbridge
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK.
- Cardiovascular Medicine Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden.
| |
Collapse
|
46
|
Chen J, Liu J, Calhoun VD. The Translational Potential of Neuroimaging Genomic Analyses To Diagnosis And Treatment In The Mental Disorders. PROCEEDINGS OF THE IEEE. INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS 2019; 107:912-927. [PMID: 32051642 PMCID: PMC7015534 DOI: 10.1109/jproc.2019.2913145] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Imaging genomics focuses on characterizing genomic influence on the variation of neurobiological traits, holding promise for illuminating the pathogenesis, reforming the diagnostic system, and precision medicine of mental disorders. This paper aims to provide an overall picture of the current status of neuroimaging-genomic analyses in mental disorders, and how we can increase their translational potential into clinical practice. The review is organized around three perspectives. (a) Towards reliability, generalizability and interpretability, where we summarize the multivariate models and discuss the considerations and trade-offs of using these methods and how reliable findings may be reached, to serve as ground for further delineation. (b) Towards improved diagnosis, where we outline the advantages and challenges of constructing a dimensional transdiagnostic model and how imaging genomic analyses map into this framework to aid in deconstructing heterogeneity and achieving an optimal stratification of patients that better inform treatment planning. (c) Towards improved treatment. Here we highlight recent efforts and progress in elucidating the functional annotations that bridge between genomic risk and neurobiological abnormalities, in detecting genomic predisposition and prodromal neurodevelopmental changes, as well as in identifying imaging genomic biomarkers for predicting treatment response. Providing an overview of the challenges and promises, this review hopefully motivates imaging genomic studies with multivariate, dimensional and transdiagnostic designs for generalizable and interpretable findings that facilitate development of personalized treatment.
Collapse
Affiliation(s)
- Jiayu Chen
- The Mind Research Network, Albuquerque, NM 87106 USA
| | - Jingyu Liu
- The Mind Research Network, Albuquerque, NM 87106 USA, and also with the Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131 USA
| | - Vince D Calhoun
- The Mind Research Network, Albuquerque, NM 87106 USA, and also with the Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM 87131 USA
| |
Collapse
|
47
|
Cetty L, Shahwan S, Satghare P, Devi F, Chua BY, Verma S, Lee H, Chong SA, Subramaniam M. Hazardous alcohol use in a sample of first episode psychosis patients in Singapore. BMC Psychiatry 2019; 19:91. [PMID: 30876474 PMCID: PMC6419799 DOI: 10.1186/s12888-019-2073-z] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2018] [Accepted: 03/07/2019] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Hazardous alcohol use has often been found to be more prevalent amongst psychiatric outpatients than the general population. Additionally, it has also been associated with poorer outcomes. The study aimed to investigate (1) the prevalence and (2) socio-demographic and clinical correlates of hazardous alcohol use, as well as (3) the relationship between hazardous alcohol use and quality of life in an outpatient sample with First Episode Psychosis (FEP) in Singapore. METHODS Baseline data (N = 280) was extracted from a longitudinal study investigating smoking and alcohol use amongst outpatients with FEP in a psychiatric hospital. Information on socio-demographics, hazardous alcohol use, and quality of life was collected through a self-report survey. Hazardous alcohol use was ascertained by total scores of 8 or higher on the Alcohol Use Disorders Identification Test (AUDIT). Data was analysed using logistic regression and linear regression analyses. RESULTS The prevalence of hazardous alcohol use over the past 12-month period was 12.9%. Those who had never smoked in their lifetime (vs current smokers) and those with a diagnosis of brief psychotic disorder (vs schizophrenia spectrum disorders) were found to have significantly lower odds of hazardous alcohol use. Hazardous alcohol use was also associated with lower negative symptom scores. Lastly, hazardous alcohol use was found to significantly predict lower scores on the physical health, social relationship and environment domains of quality of life. CONCLUSIONS The association between hazardous alcohol use and lower negative symptom scores is a surprising finding that needs to be further explored. The significant impact of hazardous alcohol use in reductions in quality of life suggests that early screening and interventions could benefit patients with hazardous alcohol use and comorbid psychosis.
Collapse
Affiliation(s)
- Laxman Cetty
- Research Division, Institute of Mental Health, Buangkok Green Medical Park, 10 Buangkok View, Singapore, 539747, Singapore.
| | - Shazana Shahwan
- 0000 0004 0469 9592grid.414752.1Research Division, Institute of Mental Health, Buangkok Green Medical Park, 10 Buangkok View, Singapore, 539747 Singapore
| | - Pratika Satghare
- 0000 0004 0469 9592grid.414752.1Research Division, Institute of Mental Health, Buangkok Green Medical Park, 10 Buangkok View, Singapore, 539747 Singapore
| | - Fiona Devi
- 0000 0004 0469 9592grid.414752.1Research Division, Institute of Mental Health, Buangkok Green Medical Park, 10 Buangkok View, Singapore, 539747 Singapore
| | - Boon Yiang Chua
- 0000 0004 0469 9592grid.414752.1Research Division, Institute of Mental Health, Buangkok Green Medical Park, 10 Buangkok View, Singapore, 539747 Singapore
| | - Swapna Verma
- 0000 0004 0469 9592grid.414752.1Department of Early Psychosis Intervention, Institute of Mental Health, Buangkok Green Medical Park, 10 Buangkok View, Singapore, 539747 Singapore
| | - Helen Lee
- 0000 0004 0469 9592grid.414752.1Department of Early Psychosis Intervention, Institute of Mental Health, Buangkok Green Medical Park, 10 Buangkok View, Singapore, 539747 Singapore
| | - Siow Ann Chong
- 0000 0004 0469 9592grid.414752.1Research Division, Institute of Mental Health, Buangkok Green Medical Park, 10 Buangkok View, Singapore, 539747 Singapore
| | - Mythily Subramaniam
- 0000 0004 0469 9592grid.414752.1Research Division, Institute of Mental Health, Buangkok Green Medical Park, 10 Buangkok View, Singapore, 539747 Singapore ,0000 0001 2224 0361grid.59025.3bLee Kong Chian School of Medicine, Novena Campus, 11 Mandalay Road, Singapore, 308232 Singapore
| |
Collapse
|
48
|
Karlsson Linnér R, Biroli P, Kong E, Meddens SFW, Wedow R, Fontana MA, Lebreton M, Tino SP, Abdellaoui A, Hammerschlag AR, Nivard MG, Okbay A, Rietveld CA, Timshel PN, Trzaskowski M, Vlaming RD, Zünd CL, Bao Y, Buzdugan L, Caplin AH, Chen CY, Eibich P, Fontanillas P, Gonzalez JR, Joshi PK, Karhunen V, Kleinman A, Levin RZ, Lill CM, Meddens GA, Muntané G, Sanchez-Roige S, Rooij FJV, Taskesen E, Wu Y, Zhang F, Auton A, Boardman JD, Clark DW, Conlin A, Dolan CC, Fischbacher U, Groenen PJF, Harris KM, Hasler G, Hofman A, Ikram MA, Jain S, Karlsson R, Kessler RC, Kooyman M, MacKillop J, Männikkö M, Morcillo-Suarez C, McQueen MB, Schmidt KM, Smart MC, Sutter M, Thurik AR, Uitterlinden AG, White J, Wit HD, Yang J, Bertram L, Boomsma DI, Esko T, Fehr E, Hinds DA, Johannesson M, Kumari M, Laibson D, Magnusson PKE, Meyer MN, Navarro A, Palmer AA, Pers TH, Posthuma D, Schunk D, Stein MB, Svento R, Tiemeier H, Timmers PRHJ, Turley P, Ursano RJ, Wagner GG, Wilson JF, Gratten J, Lee JJ, Cesarini D, Benjamin DJ, Koellinger PD, Beauchamp JP. Genome-wide association analyses of risk tolerance and risky behaviors in over 1 million individuals identify hundreds of loci and shared genetic influences. Nat Genet 2019; 51:245-257. [PMID: 30643258 PMCID: PMC6713272 DOI: 10.1038/s41588-018-0309-3] [Citation(s) in RCA: 412] [Impact Index Per Article: 68.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2018] [Accepted: 11/07/2018] [Indexed: 02/02/2023]
Abstract
Humans vary substantially in their willingness to take risks. In a combined sample of over 1 million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. Across all GWAS, we identified hundreds of associated loci, including 99 loci associated with general risk tolerance. We report evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is genetically correlated ([Formula: see text] ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near SNPs associated with general risk tolerance are highly expressed in brain tissues and point to a role for glutamatergic and GABAergic neurotransmission. We found no evidence of enrichment for genes previously hypothesized to relate to risk tolerance.
Collapse
Affiliation(s)
- Richard Karlsson Linnér
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, the Netherlands.
- Erasmus University Rotterdam Institute for Behavior and Biology, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands.
- Department of Economics, VU University Amsterdam, Amsterdam, the Netherlands.
| | - Pietro Biroli
- Department of Economics, University of Zurich, Zurich, Switzerland
| | - Edward Kong
- Department of Economics, Harvard University, Cambridge, MA, USA
| | - S Fleur W Meddens
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, the Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Department of Economics, VU University Amsterdam, Amsterdam, the Netherlands
| | - Robbee Wedow
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Analytic Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Department of Sociology, Harvard University, Cambridge, MA, USA
| | - Mark Alan Fontana
- Center for the Advancement of Value in Musculoskeletal Care, Hospital for Special Surgery, New York, NY, USA
- Department of Healthcare Policy and Research, Weill Cornell Medical College, Cornell University, New York, NY, USA
| | - Maël Lebreton
- Amsterdam School of Economics, University of Amsterdam, Amsterdam, the Netherlands
- Amsterdam Brain and Cognition, University of Amsterdam, Amsterdam, the Netherlands
| | - Stephen P Tino
- Department of Economics, University of Toronto, Toronto, Ontario, Canada
| | - Abdel Abdellaoui
- Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Anke R Hammerschlag
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, the Netherlands
| | - Michel G Nivard
- Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Aysu Okbay
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, the Netherlands
- Department of Economics, VU University Amsterdam, Amsterdam, the Netherlands
| | - Cornelius A Rietveld
- Erasmus University Rotterdam Institute for Behavior and Biology, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Department of Applied Economics, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Pascal N Timshel
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Maciej Trzaskowski
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Ronald de Vlaming
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, the Netherlands
- Erasmus University Rotterdam Institute for Behavior and Biology, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Department of Economics, VU University Amsterdam, Amsterdam, the Netherlands
| | - Christian L Zünd
- Department of Economics, University of Zurich, Zurich, Switzerland
| | - Yanchun Bao
- Institute for Social and Economic Research, University of Essex, Colchester, UK
| | - Laura Buzdugan
- Seminar for Statistics, Department of Mathematics, ETH Zurich, Zurich, Switzerland
- Department of Economics, University of Zurich, Zurich, Switzerland
| | | | - Chia-Yen Chen
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Psychiatric & Neurodevelopmental Genetics Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Peter Eibich
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
- Socio-Economic Panel Study, DIW Berlin, Berlin, Germany
- Max Planck Institute for Demographic Research, Rostock, Germany
| | | | - Juan R Gonzalez
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Peter K Joshi
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, Scotland
| | - Ville Karhunen
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | | | - Remy Z Levin
- Department of Economics, University of California San Diego, La Jolla, CA, USA
| | - Christina M Lill
- Genetic and Molecular Epidemiology Group, Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics & Cardiogenetics, University of Lübeck, Lübeck, Germany
| | | | - Gerard Muntané
- Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Barcelona, Spain
- Research Department, Hospital Universitari Institut Pere Mata, Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- Centro de Investigación Biomédica en Red en Salud Mental (CIBERSAM), Reus, Spain
| | | | - Frank J van Rooij
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Erdogan Taskesen
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, the Netherlands
| | - Yang Wu
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Futao Zhang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
| | - Adam Auton
- Research, 23andMe, Inc., Mountain View, CA, USA
| | - Jason D Boardman
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, CO, USA
- Institute of Behavioral Science, University of Colorado Boulder, Boulder, CO, USA
- Department of Sociology, University of Colorado Boulder, Boulder, CO, USA
| | - David W Clark
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, Scotland
| | - Andrew Conlin
- Department of Economics and Finance, Oulu Business School, University of Oulu, Oulu, Finland
| | - Conor C Dolan
- Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Urs Fischbacher
- Department of Economics, University of Konstanz, Konstanz, Germany
- Thurgau Institute of Economics, Kreuzlingen, Switzerland
| | - Patrick J F Groenen
- Erasmus University Rotterdam Institute for Behavior and Biology, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Department of Econometrics, Erasmus University Rotterdam, Rotterdam, Rotterdam, the Netherlands
| | - Kathleen Mullan Harris
- Department of Sociology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Gregor Hasler
- Unit of Psychiatry Research, University of Fribourg, Fribourg, Switzerland
| | - Albert Hofman
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Mohammad A Ikram
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Sonia Jain
- Family Medicine and Public Health, University of California San Diego, La Jolla, CA, USA
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ronald C Kessler
- Department of Health Care Policy, Harvard Medical School, Boston, MA, USA
| | | | - James MacKillop
- Peter Boris Centre for Addictions Research, McMaster University/St. Joseph's Healthcare Hamilton, Hamilton, Ontario, Canada
- Homewood Research Institute, Guelph, Ontario, Canada
| | - Minna Männikkö
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Carlos Morcillo-Suarez
- Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Barcelona, Spain
| | - Matthew B McQueen
- Department of Integrative Physiology, University of Colorado Boulder, Boulder, CO, USA
| | - Klaus M Schmidt
- Department of Economics, University of Munich, Munich, Germany
| | - Melissa C Smart
- Institute for Social and Economic Research, University of Essex, Colchester, UK
| | - Matthias Sutter
- Department of Economics, University of Cologne, Cologne, Germany
- Experimental Economics Group, Max Planck Institute for Research into Collective Goods, Bonn, Germany
- Department of Public Finance, University of Innsbruck, Innsbruck, Austria
| | - A Roy Thurik
- Erasmus University Rotterdam Institute for Behavior and Biology, Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
- Montpellier Business School, Montpellier, France
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus Medical Centre, Rotterdam, the Netherlands
| | - Jon White
- UCL Genetics Institute, Department of Genetics, Evolution and Environment, University College London, London, UK
| | - Harriet de Wit
- Psychiatry and Behavioral Neuroscience, University of Chicago, Chicago, IL, USA
| | - Jian Yang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, Australia
| | - Lars Bertram
- Genetic and Molecular Epidemiology Group, Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics & Cardiogenetics, University of Lübeck, Lübeck, Germany
- Dept of Psychology, University of Olso, Oslo, Norway
- School of Public Health, Imperial College London, London, UK
| | - Dorret I Boomsma
- Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Tõnu Esko
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Ernst Fehr
- Department of Economics, University of Zurich, Zurich, Switzerland
| | | | - Magnus Johannesson
- Department of Economics, Stockholm School of Economics, Stockholm, Sweden
| | - Meena Kumari
- Institute for Social and Economic Research, University of Essex, Colchester, UK
| | - David Laibson
- Department of Economics, Harvard University, Cambridge, MA, USA
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Michelle N Meyer
- Center for Translational Bioethics and Health Care Policy, Geisinger Health System, Danville, PA, USA
| | - Arcadi Navarro
- Departament de Ciències Experimentals i de la Salut, Universitat Pompeu Fabra, Barcelona, Spain
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain
- Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Catalonia, Spain
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
| | - Tune H Pers
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Danielle Posthuma
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, the Netherlands
- Department of Clinical Genetics, VU Medical Centre, Amsterdam, the Netherlands
| | - Daniel Schunk
- Department of Economics, Johannes Gutenberg University, Mainz, Germany
| | - Murray B Stein
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Family Medicine and Public Health, University of California San Diego, La Jolla, CA, USA
| | - Rauli Svento
- Department of Economics and Finance, Oulu Business School, University of Oulu, Oulu, Finland
| | - Henning Tiemeier
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Paul R H J Timmers
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, Scotland
| | - Patrick Turley
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Analytic Translational Genetics Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Behavioral and Health Genomics Center, Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
| | - Robert J Ursano
- Department of Psychiatry, Center for the Study of Traumatic Stress, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Gert G Wagner
- Socio-Economic Panel Study, DIW Berlin, Berlin, Germany
- Max Planck Institute for Human Development, Berlin, Germany
| | - James F Wilson
- Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, Scotland
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, Scotland
| | - Jacob Gratten
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Australia
- Mater Medical Research Institute, Translational Research Institute, Brisbane, Australia
| | - James J Lee
- Department of Psychology, University of Minnesota Twin Cities, Minneapolis, MN, USA
| | - David Cesarini
- Department of Economics, New York University, New York, NY, USA
| | - Daniel J Benjamin
- Behavioral and Health Genomics Center, Center for Economic and Social Research, University of Southern California, Los Angeles, CA, USA
- Department of Economics, University of Southern California, Los Angeles, CA, USA
- National Bureau of Economic Research, Cambridge, MA, USA
| | - Philipp D Koellinger
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University Amsterdam, Amsterdam, the Netherlands
- Department of Economics, VU University Amsterdam, Amsterdam, the Netherlands
- German Institute for Economic Research, DIW Berlin, Berlin, Germany
| | | |
Collapse
|
49
|
Abstract
Tourette syndrome (TS) is a complex disorder characterized by repetitive, sudden, and involuntary movements or vocalizations, called tics. Tics usually appear in childhood, and their severity varies over time. In addition to frequent tics, people with TS are at risk for associated problems including attention deficit hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), anxiety, depression, and problems with sleep. TS occurs in most populations and ethnic groups worldwide, and it is more common in males than in females. Previous family and twin studies have shown that the majority of cases of TS are inherited. TS was previously thought to have an autosomal dominant pattern of inheritance. However, several decades of research have shown that this is unlikely the case. Instead, TS most likely results from a variety of genetic and environmental factors, not changes in a single gene. In the past decade, there has been a rapid development of innovative genetic technologies and methodologies, as well as significant progress in genetic studies of psychiatric disorders. In this review, we will briefly summarize previous genetic epidemiological studies of TS and related disorders. We will also review previous genetic studies based on genome-wide linkage analyses and candidate gene association studies to comment on problems of previous methodological and strategic issues. Our main purpose for this review will be to summarize the new genetic discoveries of TS based on novel genetic methods and strategies, such as genome-wide association studies (GWASs), whole exome sequencing (WES), and whole genome sequencing (WGS). We will also compare the new genetic discoveries of TS with other major psychiatric disorders in order to understand the current status of TS genetics and its relationship with other psychiatric disorders.
Collapse
|
50
|
Drange OK, Vaaler AE, Morken G, Andreassen OA, Malt UF, Finseth PI. Clinical characteristics of patients with bipolar disorder and premorbid traumatic brain injury: a cross-sectional study. Int J Bipolar Disord 2018; 6:19. [PMID: 30198055 PMCID: PMC6162005 DOI: 10.1186/s40345-018-0128-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Accepted: 08/04/2018] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND About one in ten diagnosed with bipolar disorder (BD) has experienced a premorbid traumatic brain injury (TBI), while not fulfilling the criteria of bipolar and related disorder due to another medical condition (BD due to TBI). We investigated whether these patients have similar clinical characteristics as previously described in BD due to TBI (i.e. more aggression and irritability and an increased hypomania/mania:depression ratio) and other distinct clinical characteristics. METHODS Five hundred five patients diagnosed with BD type I, type II, or not otherwise specified, or cyclothymia were interviewed about family, medical, and psychiatric history, and assessed with the Young Mania Rating Scale (YMRS) and the Inventory of Depressive Symptoms Clinician Rated 30 (IDS-C30). Principal component analyses of YMRS and IDS-C30 were conducted. Bivariate analyses and logistic regression analyses were used to compare clinical characteristics between patients with (n = 37) and without (n = 468) premorbid TBI. RESULTS Premorbid TBI was associated with a higher YMRS disruptive component score (OR 1.7, 95% CI 1.1-2.4, p = 0.0077) and more comorbid migraine (OR 4.6, 95% CI 1.9-11, p = 0.00090) independently of several possible confounders. Items on disruptive/aggressive behaviour and irritability had the highest loadings on the YMRS disruptive component. Premorbid TBI was not associated with an increased hypomania/mania:depression ratio. CONCLUSIONS Disruptive symptoms and comorbid migraine characterize BD with premorbid TBI. Further studies should examine whether the partial phenomenological overlap with BD due to TBI could be explained by a continuum of pathophysiological effects of TBI across the diagnostic dichotomy. Trial registration ClinicalTrials.gov: NCT00201526. Registered September 2005 (retrospectively registered).
Collapse
Affiliation(s)
- Ole Kristian Drange
- Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway. .,Department of Østmarka, Division of Mental Health Care, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.
| | - Arne Einar Vaaler
- Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway.,Department of Østmarka, Division of Mental Health Care, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Gunnar Morken
- Department of Mental Health, Norwegian University of Science and Technology, Trondheim, Norway.,Department of Østmarka, Division of Mental Health Care, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Ole Andreas Andreassen
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,NORMENT, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Ulrik Fredrik Malt
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway.,Department of Research and Education, Division of Clinical Neuroscience, Oslo University Hospital, Oslo, Norway
| | - Per Ivar Finseth
- Department of Brøset, Division of Mental Health Care, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| |
Collapse
|