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Deng WQ, Belisario K, Munafò MR, MacKillop J. Longitudinal characterization of impulsivity phenotypes boosts signal for genomic correlates and heritability. Mol Psychiatry 2024:10.1038/s41380-024-02704-4. [PMID: 39181994 DOI: 10.1038/s41380-024-02704-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Revised: 08/14/2024] [Accepted: 08/16/2024] [Indexed: 08/27/2024]
Abstract
Genomic correlates of impulsivity have been identified in several genome-wide association studies (GWAS) using cross-sectional designs, but no studies have investigated the molecular genetic correlates of impulsivity phenotypes using longitudinally constructed traits. In 3860 unrelated European participants in the Avon Longitudinal Study of Parents and Children (ALSPAC), we constructed longitudinal phenotypes for delay discounting and impulsive personality traits (as measured by the UPPS-P impulsive behavior scales) via assessment at ages 24, 26, and 28. We conducted GWASs of impulsivity using both cross-sectional and longitudinal phenotypes, estimated heritability and their phenotypic and genetic correlations, and evaluated their association with recently-developed polygenic risk scores (PRSs) for the impulsivity indicators themselves and also related psychiatric conditions. Latent growth curve modeling revealed a stable intercept over time for all impulsivity phenotypes. High genetic correlation of cross-sectional measures over time suggested a stable genetic component for delay discounting (rg = 0.53-0.99) and sensation seeking (rg = 0.99). Heritability estimates of the stable longitudinal phenotypes substantively improved as compared to their cross-sectional counterparts, revealing a significant SNP-heritability for delay discounting (0.22; p = 0.03) and sensation seeking (0.35; p = 0.0007). Consistent with previous reports, GWAS and gene-based analyses revealed associations between specific longitudinal impulsivity indicators and CADM2 and NCAM1 genes. The PRSs for the impulsivity indicators and disorders related to self-regulation were also significantly associated with longitudinal impulsivity traits. Finally, we validated the associations between longitudinal impulsivity phenotypes and their PRSs in an independent 13-wave longitudinal study (n = 1019) and the benefit of longitudinal phenotypes in simulation studies. In this first longitudinal genetic study of impulsivity traits, the results revealed stable genomic correlates of delay discounting and sensation seeking over time and further validated the utility of recently-developed PRSs, both in relation to the observed traits and in connecting them to psychiatric disorders. More generally, these findings support using latent intercepts as novel longitudinal phenotypes to boost signal for heritability and genomic correlates of mechanisms contributing to psychiatric disease liability.
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Affiliation(s)
- Wei Q Deng
- Peter Boris Centre for Addictions Research, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada.
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.
| | - Kyla Belisario
- Peter Boris Centre for Addictions Research, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
| | - Marcus R Munafò
- School of Psychological Science, University of Bristol, Bristol, UK
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - James MacKillop
- Peter Boris Centre for Addictions Research, St. Joseph's Healthcare Hamilton, Hamilton, ON, Canada.
- Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada.
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Malone SG, Davis CN, Piserchia Z, Setzer MR, Toikumo S, Zhou H, Winterlind EL, Gelernter J, Justice A, Leggio L, Rentsch CT, Kranzler HR, Gray JC. Alcohol use disorder and body mass index show genetic pleiotropy and shared neural associations. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.03.24306773. [PMID: 38746260 PMCID: PMC11092735 DOI: 10.1101/2024.05.03.24306773] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Background The prevalence of co-occurring heavy alcohol consumption and obesity is increasing in the United States. Despite neurobiological overlap in the regulation of alcohol consumption and eating behavior, alcohol- and body mass index (BMI)-related phenotypes show no or minimal genetic correlation. We hypothesized that the lack of genetic correlation is due to mixed effect directions of variants shared by AUD and BMI. Methods We applied MiXeR, to investigate shared genetic architecture between AUD and BMI in individuals of European ancestry. We used conjunctional false discovery rate (conjFDR) analysis to detect loci associated with both phenotypes and their directional effect, Functional Mapping and Annotation (FUMA) to identify lead single nucleotide polymorphisms (SNPs), Genotype-Tissue Expression (GTEx) samples to examine gene expression enrichment across tissue types, and BrainXcan to evaluate the shared associations of AUD and BMI with brain image-derived phenotypes. Results MiXeR analysis indicated polygenic overlap of 80.9% between AUD and BMI, despite a genetic correlation (r g ) of -.03. ConjFDR analysis yielded 56 lead SNPs with the same effect direction and 76 with the opposite direction. Of the 132 shared lead SNPs, 53 were novel for both AUD and BMI. GTEx analyses identified significant overexpression in the frontal cortex (BA9), hypothalamus, cortex, anterior cingulate cortex (BA24), hippocampus, and amygdala. Amygdala and caudate nucleus gray matter volumes were significantly associated with both AUD and BMI in BrainXcan analyses. Conclusions More than half of variants significantly associated with AUD and BMI had opposite directions of effect for the traits, supporting our hypothesis that this is the basis for their lack of genetic correlation. Follow-up analyses identified brain regions implicated in executive functioning, reward, homeostasis, and food intake regulation. Together, these findings clarify the extensive polygenic overlap between AUD and BMI and elucidate several overlapping neurobiological mechanisms.
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3
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Chen Y, Feng S, Li Y, Zhang C, Chao G, Zhang S. Gut microbiota and intestinal immunity-A crosstalk in irritable bowel syndrome. Immunology 2024; 172:1-20. [PMID: 38174581 DOI: 10.1111/imm.13749] [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: 08/21/2023] [Accepted: 12/20/2023] [Indexed: 01/05/2024] Open
Abstract
Irritable bowel syndrome (IBS), one of the most prevalent functional gastrointestinal disorders, is characterized by recurrent abdominal pain and abnormal defecation habits, resulting in a severe healthcare burden worldwide. The pathophysiological mechanisms of IBS are multi-factorially involved, including food antigens, visceral hypersensitivity reactions, and the brain-gut axis. Numerous studies have found that gut microbiota and intestinal mucosal immunity play an important role in the development of IBS in crosstalk with multiple mechanisms. Therefore, based on existing evidence, this paper elaborates that the damage and activation of intestinal mucosal immunity and the disturbance of gut microbiota are closely related to the progression of IBS. Combined with the application prospect, it also provides references for further in-depth exploration and clinical practice.
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Affiliation(s)
- Yuxuan Chen
- The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China
| | - Shuyan Feng
- The First Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China
| | - Ying Li
- The First Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China
| | - Chi Zhang
- Sir Run Run Shaw Hospital of Zhejiang University, Hangzhou, China
| | - Guanqun Chao
- Department of General Practice, Sir Run Run Shaw Hospital of Zhejiang University, Hangzhou, China
| | - Shuo Zhang
- The Second Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China
- Department of Gastroenterology, The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, China
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4
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Venkatesh SS, Wittemans LBL, Palmer DS, Baya NA, Ferreira T, Hill B, Lassen FH, Parker MJ, Reibe S, Elhakeem A, Banasik K, Bruun MT, Erikstrup C, Jensen BA, Juul A, Mikkelsen C, Nielsen HS, Ostrowski SR, Pedersen OB, Rohde PD, Sorensen E, Ullum H, Westergaard D, Haraldsson A, Holm H, Jonsdottir I, Olafsson I, Steingrimsdottir T, Steinthorsdottir V, Thorleifsson G, Figueredo J, Karjalainen MK, Pasanen A, Jacobs BM, Hubers N, Lippincott M, Fraser A, Lawlor DA, Timpson NJ, Nyegaard M, Stefansson K, Magi R, Laivuori H, van Heel DA, Boomsma DI, Balasubramanian R, Seminara SB, Chan YM, Laisk T, Lindgren CM. Genome-wide analyses identify 21 infertility loci and over 400 reproductive hormone loci across the allele frequency spectrum. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.19.24304530. [PMID: 38562841 PMCID: PMC10984039 DOI: 10.1101/2024.03.19.24304530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Genome-wide association studies (GWASs) may help inform treatments for infertility, whose causes remain unknown in many cases. Here we present GWAS meta-analyses across six cohorts for male and female infertility in up to 41,200 cases and 687,005 controls. We identified 21 genetic risk loci for infertility (P≤5E-08), of which 12 have not been reported for any reproductive condition. We found positive genetic correlations between endometriosis and all-cause female infertility (rg=0.585, P=8.98E-14), and between polycystic ovary syndrome and anovulatory infertility (rg=0.403, P=2.16E-03). The evolutionary persistence of female infertility-risk alleles in EBAG9 may be explained by recent directional selection. We additionally identified up to 269 genetic loci associated with follicle-stimulating hormone (FSH), luteinising hormone, oestradiol, and testosterone through sex-specific GWAS meta-analyses (N=6,095-246,862). While hormone-associated variants near FSHB and ARL14EP colocalised with signals for anovulatory infertility, we found no rg between female infertility and reproductive hormones (P>0.05). Exome sequencing analyses in the UK Biobank (N=197,340) revealed that women carrying testosterone-lowering rare variants in GPC2 were at higher risk of infertility (OR=2.63, P=1.25E-03). Taken together, our results suggest that while individual genes associated with hormone regulation may be relevant for fertility, there is limited genetic evidence for correlation between reproductive hormones and infertility at the population level. We provide the first comprehensive view of the genetic architecture of infertility across multiple diagnostic criteria in men and women, and characterise its relationship to other health conditions.
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Affiliation(s)
- Samvida S Venkatesh
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, United Kingdom
| | - Laura B L Wittemans
- Novo Nordisk Research Centre Oxford, Oxford, United Kingdom
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, United Kingdom
| | - Duncan S Palmer
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Nikolas A Baya
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, United Kingdom
| | - Teresa Ferreira
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
| | - Barney Hill
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Frederik Heymann Lassen
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, United Kingdom
| | - Melody J Parker
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Nuffield Department of Clinical Medicine, University of Oxford, John Radcliffe Hospital, Oxford, United Kingdom
| | - Saskia Reibe
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Nuffield Department of Population Health, Medical Sciences Division, University of Oxford, Oxford, United Kingdom
| | - Ahmed Elhakeem
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Karina Banasik
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Department of Obstetrics and Gynecology, Copenhagen University Hospital, Hvidovre, Copenhagen, Denmark
| | - Mie T Bruun
- Department of Clinical Immunology, Odense University Hospital, Odense, Denmark
| | - Christian Erikstrup
- Department of Clinical Immunology, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Health, Aarhus University, Aarhus, Denmark
| | - Bitten A Jensen
- Department of Clinical Immunology, Aalborg University Hospital, Aalborg, Denmark
| | - Anders Juul
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen; Copenhagen, Denmark
- Department of Growth and Reproduction, Copenhagen University Hospital-Rigshospitalet, Copenhagen, Denmark
| | - Christina Mikkelsen
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Science, Copenhagen University, Copenhagen, Denmark
| | - Henriette S Nielsen
- Department of Obstetrics and Gynecology, The Fertility Clinic, Hvidovre University Hospital, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Sisse R Ostrowski
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Ole B Pedersen
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Immunology, Zealand University Hospital, Kge, Denmark
| | - Palle D Rohde
- Genomic Medicine, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Erik Sorensen
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | | | - David Westergaard
- Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark
- Department of Obstetrics and Gynecology, Copenhagen University Hospital, Hvidovre, Copenhagen, Denmark
| | - Asgeir Haraldsson
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Children's Hospital Iceland, Landspitali University Hospital, Reykjavik, Iceland
| | - Hilma Holm
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
| | - Ingileif Jonsdottir
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
| | - Isleifur Olafsson
- Department of Clinical Biochemistry, Landspitali University Hospital, Reykjavik, Iceland
| | - Thora Steingrimsdottir
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Department of Obstetrics and Gynecology, Landspitali University Hospital, Reykjavik, Iceland
| | | | | | - Jessica Figueredo
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Minna K Karjalainen
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Finland
- Northern Finland Birth Cohorts, Arctic Biobank, Infrastructure for Population Studies, Faculty of Medicine, University of Oulu, Oulu, Finland
| | - Anu Pasanen
- Research Unit of Clinical Medicine, Medical Research Center Oulu, University of Oulu, and Department of Children and Adolescents, Oulu University Hospital, Oulu, Finland
| | - Benjamin M Jacobs
- Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University London, London, EC1M 6BQ, United Kingdom
| | - Nikki Hubers
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Institute, Amsterdam, The Netherlands
| | - Margaret Lippincott
- Harvard Reproductive Sciences Center and Reproductive Endocrine Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Abigail Fraser
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Nicholas J Timpson
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, United Kingdom
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Mette Nyegaard
- Genomic Medicine, Department of Health Science and Technology, Aalborg University, Aalborg, Denmark
| | - Kari Stefansson
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- deCODE genetics/Amgen, Inc., Reykjavik, Iceland
| | - Reedik Magi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Hannele Laivuori
- Institute for Molecular Medicine Finland, Helsinki Institute of Life Science, University of Helsinki, Helsinki, Finland
- Medical and Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Department of Obstetrics and Gynecology, Tampere University Hospital, Finland
- Center for Child, Adolescent, and Maternal Health Research, Faculty of Medicine and Health Technology, Tampere University, Finland
| | - David A van Heel
- Blizard Institute, Queen Mary University London, London, E1 2AT, United Kingdom
| | - Dorret I Boomsma
- Department of Biological Psychology, Netherlands Twin Register, Vrije Universiteit, Amsterdam, The Netherlands
- Amsterdam Reproduction and Development Institute, Amsterdam, The Netherlands
| | - Ravikumar Balasubramanian
- Harvard Reproductive Sciences Center and Reproductive Endocrine Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Stephanie B Seminara
- Harvard Reproductive Sciences Center and Reproductive Endocrine Unit, Massachusetts General Hospital, Boston, Massachusetts, United States of America
- Harvard Medical School, Boston, Massachusetts, United States of America
| | - Yee-Ming Chan
- Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Endocrinology, Department of Pediatrics, Boston Children's Hospital, Boston, Massachusetts, United States of America
| | - Triin Laisk
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Cecilia M Lindgren
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford OX3 7LF, United Kingdom
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7BN, United Kingdom
- Nuffield Department of Women's and Reproductive Health, Medical Sciences Division, University of Oxford, United Kingdom
- Broad Institute of Harvard and MIT, Cambridge, Massachusetts, United States of America
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Kiewa J, Meltzer-Brody S, Milgrom J, Guintivano J, Hickie IB, Whiteman DC, Olsen CM, Medland SE, Martin NG, Wray NR, Byrne EM. Comprehensive Sex-Stratified Genetic Analysis of 28 Blood Biomarkers and Depression Reveals a Significant Association between Depression and Low Levels of Total Protein in Females. Complex Psychiatry 2024; 10:19-34. [PMID: 38584764 PMCID: PMC10997320 DOI: 10.1159/000538058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 02/14/2024] [Indexed: 04/09/2024] Open
Abstract
Introduction Major depression (MD) is more common amongst women than men, and MD episodes have been associated with fluctuations in reproductive hormones amongst women. To investigate biological underpinnings of heterogeneity in MD, the associations between depression, stratified by sex and including perinatal depression (PND), and blood biomarkers, using UK Biobank (UKB) data, were evaluated, and extended to include the association of depression with biomarker polygenic scores (PGS), generated as proxy for each biomarker. Method Using female (N = 39,761) and male (N = 38,821) UKB participants, lifetime MD and PND were tested for association with 28 blood biomarkers. A GWAS was conducted for each biomarker and genetic correlations with depression subgroups were estimated. Using independent data from the Australian Genetics of Depression Study, PGS were constructed for each biomarker, and tested for association with depression status (n [female cases/controls] = 9,006/6,442; n [male cases/controls] = 3,106/6,222). Regions of significant local genetic correlation between depression subgroups and biomarkers highlighted by the PGS analysis were identified. Results Depression in females was significantly associated with levels of twelve biomarkers, including total protein (OR = 0.90, CI = [0.86, 0.94], p = 3.9 × 10-6) and vitamin D (OR = 0.94, CI = [0.90, 0.97], p = 2.6 × 10-4), and PND with five biomarker levels, also including total protein (OR = 0.88, CI = [0.81, 0.96], p = 4.7 × 10-3). Depression in males was significantly associated with levels of eleven biomarkers. In the independent Australian Genetics of Depression Study, PGS analysis found significant associations for female depression and PND with total protein (female depression: OR = 0.93, CI = [0.88, 0.98], p = 3.6 × 10-3; PND: OR = 0.91, CI = [0.86, 0.96], p = 1.1 × 10-3), as well as with vitamin D (female depression: OR = 0.93, CI = [0.89, 0.97], p = 2.0 × 10-3; PND: OR = 0.92, CI = [0.87, 0.97], p = 1.4 × 10-3). The male depression sample did not report any significant results, and the point estimate of total protein (OR = 0.98, CI = [0.92-1.04], p = 4.7 × 10-1) did not indicate any association. Local genetic correlation analysis highlighted significant genetic correlation between PND and total protein, located in 5q13.3 (rG = 0.68, CI = [0.33, 1.0], p = 3.6 × 10-4). Discussion and Conclusion Multiple lines of evidence from genetic analysis highlight an association between total serum protein levels and depression in females. Further research involving prospective measurement of total protein and depressive symptoms is warranted.
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Affiliation(s)
- Jacqueline Kiewa
- Child Health Research Centre, University of Queensland, Brisbane, QLD, Australia
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | | | - Jeannette Milgrom
- Parent-Infant Research Institute, Austin Health, Melbourne, VIC, Australia
- Melbourne School of Psychological Sciences, The University of Melbourne, Melbourne, VIC, Australia
| | - Jerry Guintivano
- Department of Psychiatry, University of North Carolina, Chapel Hill, NC, USA
| | - Ian B. Hickie
- Brain and Mind Centre, University of Sydney, Sydney, NSW, Australia
| | | | | | - Sarah E. Medland
- QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | | | - Naomi R. Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Enda M. Byrne
- Child Health Research Centre, University of Queensland, Brisbane, QLD, Australia
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Yue X, Lan F, Liu W. CircDDX17 inhibits invasive progression of pituitary adenomas by sponging miR-1279 and regulating CADM2 expression. Front Oncol 2023; 13:1268644. [PMID: 38023219 PMCID: PMC10646483 DOI: 10.3389/fonc.2023.1268644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 10/09/2023] [Indexed: 12/01/2023] Open
Abstract
Purpose Increasing evidence has revealed that circDDX17 plays significant regulatory roles in tumor progression. In the present study, we investigated the role of circDDX17 in pituitary adenomas (PAs). Methods Reverse transcription-quantitative PCR was performed to detect the expression of Circular RNA DDX17 (circDDX17), microRNA-1279 (miR-1279), and cell adhesion molecule 2 (CADM2) in PA tissues. Cell abilities of migration and invasion were examined by wound healing and transwell assays. Dual-luciferase reporter, RNA immunoprecipitation, and RNA pull-down assays were applied to confirm the associations among circDDX17, miR-1279, and CADM2. Xenograft tumor experiments were performed to investigate the roles of circDDX17 in vivo. Results In the present study, we found that circDDX17 was downregulated in PA tissues correlated with invasion, tumor size, and progression-free survival of patients with PA. Enforced expression of circDDX17 significantly inhibited migration and invasion through miR-1279. Notably, CADM2 was verified as the direct binding target of miR-1279, and silencing the expression of CADM2 reverses the tumor suppressing effects induced by circDDX17 overexpression. We demonstrated that circDDX17 upregulated the expression of CADM2 by sponging miR-1279, which suppressed the invasive biological behaviors of PA. Conclusion CircDDX17 may serve as a tumor suppressor and potential promising biomarker and effectively therapeutic target for the management of PA.
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Affiliation(s)
- Xiao Yue
- Department of Neurosurgery, Xijing Hospital, Air Force Medical University, Xi’an, Shaanxi, China
| | - Fengming Lan
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | - Weiping Liu
- Department of Neurosurgery, Xijing Hospital, Air Force Medical University, Xi’an, Shaanxi, China
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Liu X, Li Y. Genetic correlation for alcohol consumption between Europeans and East Asians. BMC Genomics 2023; 24:652. [PMID: 37904118 PMCID: PMC10614326 DOI: 10.1186/s12864-023-09766-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Accepted: 10/25/2023] [Indexed: 11/01/2023] Open
Abstract
Genome-wide association studies (GWAS) have identified many genetic variants associated with alcohol consumption in Europeans and East Asians, as well as other populations. However, the genetic homogeneity and heterogeneity between these populations have not been thoroughly investigated, despite evidence of varying effect sizes of variants between ethnicities and the presence of population-specific strong signals of selection on loci associated with alcohol consumption. In order to better understand the relationship between Europeans and East Asians in the genetic architecture of alcohol consumption, we compared their heritability and evaluated their genetic correlation using GWAS results from UK Biobank (UKB) and Biobank Japan (BBJ). We found that these two populations have low genetic correlation due to the large difference on chromosome 12. After excluding this chromosome, the genetic correlation was moderately high ([Formula: see text] = 0.544, p = 1.12e-4) and 44.31% of the genome-wide causal variants were inferred to be shared between Europeans and East Asians. Given those observations, we conducted a meta-analysis on UKB and BBJ and identified new signals, including the CADM2 gene on chromosome 3, which has been associated with various behavioral and metabolic traits. Overall, our findings suggest that the genetic architecture of alcohol consumption is largely shared between Europeans and East Asians, but there are exceptions such as the enrichment of heritability on chromosome 12 in East Asians.
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Affiliation(s)
- Xuan Liu
- Department of Neurology, The First People's Hospital of Wenling, Taizhou, China
| | - Yongang Li
- Department of Neurology, The First People's Hospital of Wenling, Taizhou, China.
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8
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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: 18] [Impact Index Per Article: 18.0] [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.
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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.
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9
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Brick LA, Benca-Bachman CE, Johnson EC, Gustavson DE, Carper M, Palmer RHC. Genetic associations among internalizing and externalizing traits with polysubstance use among young adults. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.04.23287779. [PMID: 37066212 PMCID: PMC10104191 DOI: 10.1101/2023.04.04.23287779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Though most genetic studies of substance use focus on specific substances in isolation or generalized vulnerability across multiple substances, few studies to date focus on the concurrent use of two or more substances within a specified time frame (i.e., polysubstance use; PSU). We evaluated whether distinct genetic factors underlying internalizing and externalizing traits were associated with past 30-day PSU above variance shared across general psychopathology and substance use (SU). Using Genomic Structural Equation Modeling, we constructed theory-driven, multivariate genetic factors of 16 internalizing, externalizing, and SU traits using genome-wide association studies (GWAS) summary statistics. Next, we fit a model with a higher order SU-related psychopathology factor as well as genetic variance specific to externalizing and internalizing (i.e., residual genetic variance not explained by SU or general psychopathology). GWAS-by-subtraction was used to obtain single nucleotide polymorphism effects on each of these factors. Polygenic scores (PGS) were then created in an independent target sample with data on PSU, the National Longitudinal Study of Adolescent to Adult Health. To evaluate the effect of genetic variance due to internalizing and externalizing traits independent of variance related to SU, we regressed PSU on the PGSs, controlling for sex, age, and genetic principal components. PGSs for SU-related psychopathology and non-SU externalizing traits were associated with higher PSU factor scores, while the non-SU internalizing PGS was not significantly associated with PSU. In total, the three PGSs accounted for an additional 4% of the variance in PSU above and beyond a null model with only age, sex, and genetic principal components as predictors. These findings suggest that there may be unique genetic variance in externalizing traits contributing to liability for PSU that is independent of the genetic variance shared with SU.
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Affiliation(s)
- Leslie A Brick
- Department of Psychiatry and Human Behavior, Alpert Medical School of Brown University, Providence, Rhode Island, USA
- Providence VA Medical Center, Providence, Rhode Island, USA
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, Georgia, USA
| | - Chelsie E Benca-Bachman
- Providence VA Medical Center, Providence, Rhode Island, USA
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, Georgia, USA
| | - Emma C Johnson
- Department of Psychiatry, Washington University School of Medicine, Saint Louis, Missouri, USA
| | - Daniel E. Gustavson
- Institute for Behavioral Genetics, University of Colorado Boulder, Boulder, Colorado, USA
| | - Matthew Carper
- Department of Clinical Psychology, William James College, Newton, Massachusetts, USA
| | - Rohan HC Palmer
- Providence VA Medical Center, Providence, Rhode Island, USA
- Behavioral Genetics of Addiction Laboratory, Department of Psychology at Emory University, Atlanta, Georgia, USA
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10
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Boeckx C. What made us "hunter-gatherers of words". Front Neurosci 2023; 17:1080861. [PMID: 36845441 PMCID: PMC9947416 DOI: 10.3389/fnins.2023.1080861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 01/19/2023] [Indexed: 02/11/2023] Open
Abstract
This paper makes three interconnected claims: (i) the "human condition" cannot be captured by evolutionary narratives that reduce it to a recent 'cognitive modernity', nor by narratives that eliminates all cognitive differences between us and out closest extinct relatives, (ii) signals from paleogenomics, especially coming from deserts of introgression but also from signatures of positive selection, point to the importance of mutations that impact neurodevelopment, plausibly leading to temperamental differences, which may impact cultural evolutionary trajectories in specific ways, and (iii) these trajectories are expected to affect the language phenotypes, modifying what is being learned and how it is put to use. In particular, I hypothesize that these different trajectories influence the development of symbolic systems, the flexible ways in which symbols combine, and the size and configurations of the communities in which these systems are put to use.
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Affiliation(s)
- Cedric Boeckx
- Section of General Linguistics, Universitat de Barcelona, Barcelona, Spain
- Institute of Complex Systems, Universitat de Barcelona, Barcelona, Spain
- Catalan Institute for Research and Advanced Studies (ICREA), Barcelona, Spain
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11
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The neurobiology of irritable bowel syndrome. Mol Psychiatry 2023; 28:1451-1465. [PMID: 36732586 DOI: 10.1038/s41380-023-01972-w] [Citation(s) in RCA: 43] [Impact Index Per Article: 43.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/06/2023] [Accepted: 01/17/2023] [Indexed: 02/04/2023]
Abstract
Irritable bowel syndrome (IBS) is the most prevalent disorder of brain-gut interactions that affects between 5 and 10% of the general population worldwide. The current symptom criteria restrict the diagnosis to recurrent abdominal pain associated with altered bowel habits, but the majority of patients also report non-painful abdominal discomfort, associated psychiatric conditions (anxiety and depression), as well as other visceral and somatic pain-related symptoms. For decades, IBS was considered an intestinal motility disorder, and more recently a gut disorder. However, based on an extensive body of reported information about central, peripheral mechanisms and genetic factors involved in the pathophysiology of IBS symptoms, a comprehensive disease model of brain-gut-microbiome interactions has emerged, which can explain altered bowel habits, chronic abdominal pain, and psychiatric comorbidities. In this review, we will first describe novel insights into several key components of brain-gut microbiome interactions, starting with reported alterations in the gut connectome and enteric nervous system, and a list of distinct functional and structural brain signatures, and comparing them to the proposed brain alterations in anxiety disorders. We will then point out the emerging correlations between the brain networks with the genomic, gastrointestinal, immune, and gut microbiome-related parameters. We will incorporate this new information into a systems-based disease model of IBS. Finally, we will discuss the implications of such a model for the improved understanding of the disorder and the development of more effective treatment approaches in the future.
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12
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Verweij KJH, Vink JM, Abdellaoui A, Gillespie NA, Derks EM, Treur JL. The genetic aetiology of cannabis use: from twin models to genome-wide association studies and beyond. Transl Psychiatry 2022; 12:489. [PMID: 36411281 PMCID: PMC9678872 DOI: 10.1038/s41398-022-02215-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 09/26/2022] [Accepted: 10/03/2022] [Indexed: 11/22/2022] Open
Abstract
Cannabis is among the most widely consumed psychoactive substances worldwide. Individual differences in cannabis use phenotypes can partly be explained by genetic differences. Technical and methodological advances have increased our understanding of the genetic aetiology of cannabis use. This narrative review discusses the genetic literature on cannabis use, covering twin, linkage, and candidate-gene studies, and the more recent genome-wide association studies (GWASs), as well as the interplay between genetic and environmental factors. Not only do we focus on the insights that these methods have provided on the genetic aetiology of cannabis use, but also on how they have helped to clarify the relationship between cannabis use and co-occurring traits, such as the use of other substances and mental health disorders. Twin studies have shown that cannabis use is moderately heritable, with higher heritability estimates for more severe phases of use. Linkage and candidate-gene studies have been largely unsuccessful, while GWASs so far only explain a small portion of the heritability. Dozens of genetic variants predictive of cannabis use have been identified, located in genes such as CADM2, FOXP2, and CHRNA2. Studies that applied multivariate methods (twin models, genetic correlation analysis, polygenic score analysis, genomic structural equation modelling, Mendelian randomisation) indicate that there is considerable genetic overlap between cannabis use and other traits (especially other substances and externalising disorders) and some evidence for causal relationships (most convincingly for schizophrenia). We end our review by discussing implications of these findings and suggestions for future work.
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Affiliation(s)
- Karin J. H. Verweij
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, The Netherlands
| | - Jacqueline M. Vink
- grid.5590.90000000122931605Behavioural Science Institute, Radboud University Nijmegen, Thomas van Aquinostraat 4, 6525 GD Nijmegen, The Netherlands
| | - Abdel Abdellaoui
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, The Netherlands
| | - Nathan A. Gillespie
- grid.224260.00000 0004 0458 8737Virginia Institute for Psychiatric and Behavior Genetics, Virginia Commonwealth University, 800 East Leigh St, Suite 100, Richmond, VA 23219 USA
| | - Eske M. Derks
- grid.1049.c0000 0001 2294 1395Translational Neurogenomics, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston, QLD 4006 Australia
| | - Jorien L. Treur
- grid.7177.60000000084992262Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Meibergdreef 5, 1105 AZ Amsterdam, The Netherlands
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