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Ouyang D, Liu Y, Xie W. Exploring the Causal Relationship Between Migraine and Insomnia Through Bidirectional Two-Sample Mendelian Randomization: A Bidirectional Causal Relationship. J Pain Res 2024; 17:2407-2415. [PMID: 39050680 PMCID: PMC11268570 DOI: 10.2147/jpr.s460566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2024] [Accepted: 07/08/2024] [Indexed: 07/27/2024] Open
Abstract
Introduction The intricate relationship between migraine and insomnia has been a subject of great interest due to its complex mechanisms. Despite extensive research, understanding the causal link between these conditions remains a challenge. Material and Methods This study employs a bidirectional Mendelian randomization approach to investigate the causal relationship between migraine and insomnia. Risk loci for both conditions were derived from large-scale Genome-Wide Association Studies (GWAS). The primary method of Mendelian Randomization utilized in this study is the Inverse Variance Weighted (IVW) method. Results Our findings indicate a bidirectional causal relationship between migraine and insomnia. In the discovery set, migraine had a significant effect on insomnia (OR=1.02, 95% CI=1.02 (1.01-1.03), PIVW=5.30E-04). However, this effect was not confirmed in the validation set (OR=1.03, 95% CI=1.03 (0.87-1.21), PIVW=0.77). Insomnia also had a significant effect on migraine (OR=1.02, 95% CI=1.02 (0.01-1.03), PIVW=2.67E-08), and this effect was validated in the validation set (OR=2.30, 95% CI=2.30 (1.60-3.30), PIVW=5.78E-06). Conclusion This study provides meaningful insights into the bidirectional causality between migraine and insomnia, highlighting a complex interplay between these conditions. While our findings advance the understanding of the relationship between migraine and insomnia, they also open up new avenues for further research. The results underscore the need for considering both conditions in clinical and therapeutic strategies.
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Affiliation(s)
- Di Ouyang
- Department of Neurology, Traditional Chinese Medicine Hospital of YuLin, Yulin, Guangxi, People’s Republic of China
| | - Yuhe Liu
- Department of Orthopedics, Traditional Chinese Medicine Hospital of YuLin, Yulin, Guangxi, People’s Republic of China
| | - Weiming Xie
- Department of Basic Medicine, Guangxi Medical University, Nanning, Guangxi, People’s Republic of China
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2
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Xiao X, Wu X, Yi L, You F, Li X, Xiao C. Causal linkage between type 2 diabetes mellitus and inflammatory bowel disease: an integrated Mendelian randomization study and bioinformatics analysis. Front Endocrinol (Lausanne) 2024; 15:1275699. [PMID: 38313367 PMCID: PMC10836595 DOI: 10.3389/fendo.2024.1275699] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Accepted: 01/05/2024] [Indexed: 02/06/2024] Open
Abstract
Background Observational studies have indicated associations between type 2 diabetes mellitus (T2DM) and both colorectal cancer (CRC) and inflammatory bowel disease (IBD). However, the underlying causality and biological mechanisms between these associations remains unclear. Methods We conducted a bidirectional Mendelian randomization (MR) analysis employing summary statistics from genome-wide association studies involving European individuals. The inverse variance weighting (IVW) method was the primary method used to assess causality. Additionally, we applied MR Egger, Weighted median, Simple mode, and Weighted mode to evaluate the robustness of the results. Outliers were identified and eliminated using the MR-PRESSO, while the MR-Egger intercept was used to assess the horizontal pleiotropic effects of single nucleotide polymorphisms (SNPs). The heterogeneity was evaluated using the Cochrane Q test, and sensitivity analysis was performed using leave-one-out method. The F statistic was calculated to evaluate weak instrumental variable bias. Finally, a pilot bioinformatics analysis was conducted to explore the underlying biological mechanisms between T2DM and IBD/UC. Results The IVW results demonstrated that T2DM significantly reduced risks of IBD (OR=0.885, 95% CI: 0.818-0.958, P=0.002) and ulcerative colitis (UC) (OR=0.887, 95% CI: 0.812-0.968, P=0.007). Although the 95% CIs of MR Egger, Weighted median, Simple mode, and Weighted mode were broad, the majority of their estimates were consistent with the direction of IVW. Despite significant heterogeneity among SNPs, no horizontal pleiotropy was observed. The leave-one-out analysis showed that the causality remained consistent after each SNP was removed, underscoring the reliability of the results. Reverse MR analysis indicated that genetic susceptibility to both CRC and IBD had no significant effect on the relative risk of T2DM. Ten hub genes were identified, which mainly enriched in pathways including maturity onset diabetes of the young, thyroid cancer, gastric acid secretion, longevity regulating pathway, melanogenesis, and pancreatic secretion. Conclusion The presence of T2DM does not increase the risk of CRC or IBD. Moreover, T2DM might reduce risk of IBD, including UC. Conversely, the occurrence of CRC or IBD does not influence the risk of T2DM. The association between T2DM and IBD/UC may be related to the changes in multiple metabolic pathways and CTLA-4-mediated immune response.
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Affiliation(s)
- Xiang Xiao
- TCM Regulating Metabolic Diseases Key Laboratory of Sichuan Province, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Xuanyu Wu
- TCM Regulating Metabolic Diseases Key Laboratory of Sichuan Province, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Lu Yi
- TCM Regulating Metabolic Diseases Key Laboratory of Sichuan Province, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Fengming You
- TCM Regulating Metabolic Diseases Key Laboratory of Sichuan Province, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Cancer Institute, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Xueke Li
- TCM Regulating Metabolic Diseases Key Laboratory of Sichuan Province, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Chong Xiao
- TCM Regulating Metabolic Diseases Key Laboratory of Sichuan Province, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China
- Cancer Institute, Chengdu University of Traditional Chinese Medicine, Chengdu, China
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3
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Reyes-Pérez P, García-Marín LM, Aman AM, Antar T, Flores-Ocampo V, Mitchell BL, Medina-Rivera A, Rentería ME. Investigating the Shared Genetic Etiology Between Parkinson's Disease and Depression. JOURNAL OF PARKINSON'S DISEASE 2024; 14:483-493. [PMID: 38457145 DOI: 10.3233/jpd-230176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/09/2024]
Abstract
Background Depression is a common symptom in Parkinson's disease (PD), resulting from underlying neuropathological processes and psychological factors. However, the extent to which shared genetic risk factors contribute to the relationship between depression and PD is poorly understood. Objective To examine the effects of common genetic variants influencing the etiology of PD and depression risk at the genome-wide and local genomic regional level. Methods We comprehensively investigated the genetic relationship between PD and depression using genome-wide association studies data. First, we estimated the genetic correlation at the genome-wide level using linkage-disequilibrium score regression, followed by local genetic correlation analysis using the GWAS-pairwise method and functional annotation to identify genes that may jointly influence the risk for both traits. Also, we performed Latent Causal Variable, Latent Heritable Confounder Mendelian Randomization, and traditional Mendelian Randomization analyses to investigate the potential causal relationship. Results Although the genetic correlation between PD and depression was not statistically significant at the genome-wide level, GWAS-pairwise analyses identified 16 genomic segments associated with PD and depression, implicating nine genes. Further analyses revealed distinct patterns within individual genes, suggesting an intricate pattern. These genes involve various biological processes, including neurotransmitter regulation, senescence, and nucleo-cytoplasmic transport mechanisms. We did not observe genetic evidence of causality between PD and depression. Conclusions Our findings did not support a genome-wide genetic correlation or a causal association between both conditions. However, we identified genomic segments but identified genomic segments linked to distinct biological pathways influencing their etiology.Further research is needed to understand their functional consequences.
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Affiliation(s)
- Paula Reyes-Pérez
- Laboratorio Internacional de Investigación Sobre el Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
| | - Luis M García-Marín
- Laboratorio Internacional de Investigación Sobre el Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Asma M Aman
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
| | - Tarek Antar
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Victor Flores-Ocampo
- Laboratorio Internacional de Investigación Sobre el Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
- Licenciatura en Ciencias Genómicas, Escuela Nacional de Estudios Superiores Unidad Juriquilla, Universidad Nacional Autónoma de México, Querétaro, México
| | - Brittany L Mitchell
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Alejandra Medina-Rivera
- Laboratorio Internacional de Investigación Sobre el Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
| | - Miguel E Rentería
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, University of Queensland, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Health, Queensland University of Technology, Brisbane, QLD,Australia
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García-Marín LM, Reyes-Pérez P, Diaz-Torres S, Medina-Rivera A, Martin NG, Mitchell BL, Rentería ME. Shared molecular genetic factors influence subcortical brain morphometry and Parkinson's disease risk. NPJ Parkinsons Dis 2023; 9:73. [PMID: 37164954 PMCID: PMC10172359 DOI: 10.1038/s41531-023-00515-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Accepted: 04/28/2023] [Indexed: 05/12/2023] Open
Abstract
Parkinson's disease (PD) is a late-onset and genetically complex neurodegenerative disorder. Here we sought to identify genes and molecular pathways underlying the associations between PD and the volume of ten brain structures measured through magnetic resonance imaging (MRI) scans. We leveraged genome-wide genetic data from several cohorts, including the International Parkinson's Disease Genomics Consortium (IPDG), the UK Biobank, the Adolescent Brain Cognitive Development (ABCD) study, the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE), the Enhancing Neuroimaging Genetics through Meta-Analyses (ENIGMA), and 23andMe. We observed significant positive genetic correlations between PD and intracranial and subcortical brain volumes. Genome-wide association studies (GWAS) - pairwise analyses identified 210 genomic segments with shared aetiology between PD and at least one of these brain structures. Pathway enrichment results highlight potential links with chronic inflammation, the hypothalamic-pituitary-adrenal pathway, mitophagy, disrupted vesicle-trafficking, calcium-dependent, and autophagic pathways. Investigations for putative causal genetic effects suggest that a larger putamen volume could influence PD risk, independently of the potential causal genetic effects of intracranial volume (ICV) on PD. Our findings suggest that genetic variants influencing larger intracranial and subcortical brain volumes, possibly during earlier stages of life, influence the risk of developing PD later in life.
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Affiliation(s)
- Luis M García-Marín
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.
- Laboratorio Internacional de Investigación del Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México.
| | - Paula Reyes-Pérez
- Laboratorio Internacional de Investigación del Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
| | - Santiago Diaz-Torres
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Alejandra Medina-Rivera
- Laboratorio Internacional de Investigación del Genoma Humano, Universidad Nacional Autónoma de México, Juriquilla, Querétaro, México
| | - Nicholas G Martin
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Brittany L Mitchell
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Miguel E Rentería
- Mental Health and Neuroscience Program, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
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5
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Farrell SF, Kho PF, Lundberg M, Campos AI, Rentería ME, de Zoete RMJ, Sterling M, Ngo TT, Cuéllar-Partida G. A Shared Genetic Signature for Common Chronic Pain Conditions and its Impact on Biopsychosocial Traits. THE JOURNAL OF PAIN 2023; 24:369-386. [PMID: 36252619 DOI: 10.1016/j.jpain.2022.10.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Revised: 09/28/2022] [Accepted: 10/06/2022] [Indexed: 11/11/2022]
Abstract
The multiple comorbidities & dimensions of chronic pain present a formidable challenge in disentangling its aetiology. Here, we performed genome-wide association studies of 8 chronic pain types using UK Biobank data (N =4,037-79,089 cases; N = 239,125 controls), followed by bivariate linkage disequilibrium-score regression and latent causal variable analyses to determine (respectively) their genetic correlations and genetic causal proportion (GCP) parameters with 1,492 other complex traits. We report evidence of a shared genetic signature across chronic pain types as their genetic correlations and GCP directions were broadly consistent across an array of biopsychosocial traits. Across 5,942 significant genetic correlations, 570 trait pairs could be explained by a causal association (|GCP| >0.6; 5% false discovery rate), including 82 traits affected by pain while 410 contributed to an increased risk of chronic pain (cf. 78 with a decreased risk) such as certain somatic pathologies (eg, musculoskeletal), psychiatric traits (eg, depression), socioeconomic factors (eg, occupation) and medical comorbidities (eg, cardiovascular disease). This data-driven phenome-wide association analysis has demonstrated a novel and efficient strategy for identifying genetically supported risk & protective traits to enhance the design of interventional trials targeting underlying causal factors and accelerate the development of more effective treatments with broader clinical utility. PERSPECTIVE: Through large-scale phenome-wide association analyses of >1,400 biopsychosocial traits, this article provides evidence for a shared genetic signature across 8 common chronic pain types. It lays the foundation for further translational studies focused on identifying causal genetic variants and pathophysiological pathways to develop novel diagnostic & therapeutic technologies and strategies.
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Affiliation(s)
- Scott F Farrell
- RECOVER Injury Research Centre, The University of Queensland, Herston, Queensland, Australia; NHMRC Centre of Research Excellence: Better Health Outcomes for Compensable Injury, The University of Queensland, Herston, Queensland, Australia; Tess Cramond Pain & Research Centre, Royal Brisbane & Women's Hospital, Herston, Queensland, Australia.
| | - Pik-Fang Kho
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, California; Molecular Cancer Epidemiology Laboratory, Population Health Program, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia; School of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Mischa Lundberg
- UQ Diamantina Institute, The University of Queensland & Translational Research Institute, Woolloongabba, Queensland, Australia; Transformational Bioinformatics, CSIRO Health & Biosecurity, North Ryde, New South Wales, Australia
| | - Adrián I Campos
- Institute for Molecular Bioscience, The University of Queensland, St Lucia, Queensland, Australia; Genetic Epidemiology Laboratory, Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Miguel E Rentería
- Genetic Epidemiology Laboratory, Mental Health & Neuroscience Program, QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia
| | - Rutger M J de Zoete
- School of Allied Health Science and Practice, The University of Adelaide, Adelaide, South Australia, Australia
| | - Michele Sterling
- RECOVER Injury Research Centre, The University of Queensland, Herston, Queensland, Australia; NHMRC Centre of Research Excellence: Better Health Outcomes for Compensable Injury, The University of Queensland, Herston, Queensland, Australia
| | - Trung Thanh Ngo
- RECOVER Injury Research Centre, The University of Queensland, Herston, Queensland, Australia
| | - Gabriel Cuéllar-Partida
- UQ Diamantina Institute, The University of Queensland & Translational Research Institute, Woolloongabba, Queensland, Australia
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6
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Harder AV, Terwindt GM, Nyholt DR, van den Maagdenberg AM. Migraine genetics: Status and road forward. Cephalalgia 2023; 43:3331024221145962. [PMID: 36759319 DOI: 10.1177/03331024221145962] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/11/2023]
Abstract
BACKGROUND Migraine is considered a multifactorial genetic disorder. Different platforms and methods are used to unravel the genetic basis of migraine. Initially, linkage analysis in multigenerational families followed by Sanger sequencing of protein-coding parts (exons) of genes in the genomic region shared by affected family members identified high-effect risk DNA mutations for rare Mendelian forms of migraine, foremost hemiplegic migraine. More recently, genome-wide association studies testing millions of DNA variants in large groups of patients and controls have proven successful in identifying many dozens of low-effect risk DNA variants for the more common forms of migraine with the number of associated DNA variants increasing steadily with larger sample sizes. Currently, next-generation sequencing, utilising whole exome and whole genome sequence data, and other omics data are being used to facilitate their functional interpretation and the discovery of additional risk factors. Various methods and analysis tools, such as genetic correlation and causality analysis, are used to further characterise genetic risk factors. FINDINGS We describe recent findings in genome-wide association studies and next-generation sequencing analysis in migraine. We show that the combined results of the two most recent and most powerful migraine genome-wide association studies have identified a total of 178 LD-independent (r2 < 0.1) genome-wide significant single nucleotide polymorphisms (SNPs), of which 99 were unique to Hautakangas et al., 11 were unique to Choquet et al., and 68 were identified by both studies. When considering that Choquet et al. also identified three SNPs in a female-specific genome-wide association studies then these two recent studies identified 181 independent SNPs robustly associated with migraine. Cross-trait and causal analyses are beginning to identify and characterise specific biological factors that contribute to migraine risk and its comorbid conditions. CONCLUSION This review provides a timely update and overview of recent genetic findings in migraine.
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Affiliation(s)
- Aster Ve Harder
- Department of Neurology, Leiden University Medical Centre, Leiden, The Netherlands.,Department of Human Genetics, Leiden University Medical Centre, Leiden, The Netherlands
| | - Gisela M Terwindt
- Department of Human Genetics, Leiden University Medical Centre, Leiden, The Netherlands
| | - Dale R Nyholt
- School of Biomedical Sciences, Faculty of Health, and Centre for Genomics and Personalised Health, Queensland University of Technology, Brisbane, Australia
| | - Arn Mjm van den Maagdenberg
- Department of Neurology, Leiden University Medical Centre, Leiden, The Netherlands.,Department of Human Genetics, Leiden University Medical Centre, Leiden, The Netherlands
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7
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Aman AM, García-Marín LM, Thorp JG, Campos AI, Cuellar-Partida G, Martin NG, Rentería ME. Phenome-wide screening of the putative causal determinants of depression using genetic data. Hum Mol Genet 2022; 31:2887-2898. [PMID: 35394011 DOI: 10.1093/hmg/ddac081] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 03/30/2022] [Accepted: 03/31/2022] [Indexed: 11/13/2022] Open
Abstract
Depression is one of the most common mental health disorders and one of the top causes of disability throughout the world. The present study sought to identify putative causal associations between depression and hundreds of complex human traits through a genome-wide screening of genetic data and a hypothesis-free approach. We leveraged genome-wide association studies (GWAS) summary statistics for depression and 1504 complex traits and investigated potential causal relationships using the latent causal variable method. We identified 559 traits genetically correlated with depression risk at FDR < 5%. Of these, 46 were putative causal genetic determinants of depression, including lifestyle factors, diseases of the nervous system, respiratory disorders, diseases of the musculoskeletal system, traits related to the health of the gastrointestinal system, obesity, vitamin D levels, and the use of prescription medications, among others. No phenotypes were identified as potential outcomes of depression. Our results suggest that genetic liability to multiple complex traits may contribute to a higher risk for depression. In particular, we show a putative causal genetic effect of pain, obesity, and inflammation on depression. These findings provide novel insights into the potential causal determinants of depression and should be interpreted as testable hypotheses for future studies to confirm, which may facilitate the design of new prevention strategies to reduce depression's burden.
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Affiliation(s)
- Asma M Aman
- Institut für Medizinische Informationsverarbeitung, Biometrie und Epidemiologie (IBE), Ludwig-Maximilians-Universität München, Munich, Germany
| | - Luis M García-Marín
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane QLD Australia.,School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane QLD Australia
| | - Jackson G Thorp
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane QLD Australia.,Translational Neurogenomics, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Adrian I Campos
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD Australia
| | - Gabriel Cuellar-Partida
- The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, QLD, Australia
| | - Nicholas G Martin
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane QLD Australia
| | - Miguel E Rentería
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane QLD Australia.,School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane QLD Australia
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8
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Farrell SF, Campos AI, Kho PF, de Zoete RMJ, Sterling M, Rentería ME, Ngo TT, Cuéllar-Partida G. Genetic basis to structural grey matter associations with chronic pain. Brain 2021; 144:3611-3622. [PMID: 34907416 DOI: 10.1093/brain/awab334] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 08/06/2021] [Accepted: 08/12/2021] [Indexed: 01/26/2023] Open
Abstract
Structural neuroimaging studies of individuals with chronic pain conditions have often observed decreased regional grey matter at a phenotypic level. However, it is not known if this association can be attributed to genetic factors. Here we employed a novel integrative data-driven and hypothesis-testing approach to determine whether there is a genetic basis to grey matter morphology differences in chronic pain. Using publicly available genome-wide association study summary statistics for regional chronic pain conditions (n = 196 963) and structural neuroimaging measures (n = 19 629-34 000), we applied bivariate linkage disequilibrium-score regression and latent causal variable analyses to determine the genetic correlations (rG) and genetic causal proportion (GCP) between these complex traits, respectively. Five a priori brain regions (i.e. prefrontal cortex, cingulate cortex, insula, thalamus and superior temporal gyrus) were selected based on systematic reviews of grey matter morphology studies in chronic pain. Across this evidence-based selection of five brain regions, 10 significant negative genetic correlations (out of 369) were found (false discovery rate < 5%), suggesting a shared genetic basis to both reduced regional grey matter morphology and the presence of chronic pain. Specifically, negative genetic correlations were observed between reduced insula grey matter morphology and chronic pain in the abdomen (mean insula cortical thickness), hips (left insula volume) and neck/shoulders (left and right insula volume). Similarly, a shared genetic basis was found for reduced posterior cingulate cortex volume in chronic pain of the hip (left and right posterior cingulate), neck/shoulder (left posterior cingulate) and chronic pain at any site (left posterior cingulate); and for reduced pars triangularis volume in chronic neck/shoulder (left pars triangularis) and widespread pain (right pars triangularis). Across these negative genetic correlations, a significant genetic causal proportion was only found between mean insula thickness and chronic abdominal pain [rG (standard error, SE) = -0.25 (0.08), P = 1.06 × 10-3; GCP (SE) = -0.69 (0.20), P = 4.96 × 10-4]. This finding suggests that the genes underlying reduced cortical thickness of the insula causally contribute to an increased risk of chronic abdominal pain. Altogether, these results provide independent corroborating evidence for observational reports of decreased grey matter of particular brain regions in chronic pain. Further, we show for the first time that this association is mediated (in part) by genetic factors. These novel findings warrant further investigation into the neurogenetic pathways that underlie the development and prolongation of chronic pain conditions.
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Affiliation(s)
- Scott F Farrell
- RECOVER Injury Research Centre, The University of Queensland, Herston, QLD, Australia.,NHMRC Centre for Research Excellence in Road Traffic Injury Recovery, The University of Queensland, Herston, QLD, Australia.,Menzies Health Institute Queensland, Griffith University, Gold Coast, QLD, Australia
| | - Adrián I Campos
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, St Lucia, QLD, Australia.,Genetic Epidemiology Laboratory, Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Pik-Fang Kho
- Molecular Cancer Epidemiology Laboratory, Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia.,School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD, Australia
| | - Rutger M J de Zoete
- School of Allied Health Science and Practice, The University of Adelaide, Adelaide, SA, Australia
| | - Michele Sterling
- RECOVER Injury Research Centre, The University of Queensland, Herston, QLD, Australia.,NHMRC Centre for Research Excellence in Road Traffic Injury Recovery, The University of Queensland, Herston, QLD, Australia
| | - Miguel E Rentería
- School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, St Lucia, QLD, Australia.,Genetic Epidemiology Laboratory, Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia
| | - Trung Thanh Ngo
- Diamantina Institute, The University of Queensland and Translational Research Institute, Woolloongabba, QLD, Australia
| | - Gabriel Cuéllar-Partida
- Diamantina Institute, The University of Queensland and Translational Research Institute, Woolloongabba, QLD, Australia
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9
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García-Marín LM, Campos AI, Cuéllar-Partida G, Medland SE, Kollins SH, Rentería ME. Large-scale genetic investigation reveals genetic liability to multiple complex traits influencing a higher risk of ADHD. Sci Rep 2021; 11:22628. [PMID: 34799595 PMCID: PMC8604995 DOI: 10.1038/s41598-021-01517-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Accepted: 10/11/2021] [Indexed: 11/25/2022] Open
Abstract
Attention Deficit-Hyperactivity Disorder (ADHD) is a complex psychiatric and neurodevelopmental disorder that develops during childhood and spans into adulthood. ADHD’s aetiology is complex, and evidence about its cause and risk factors is limited. We leveraged genetic data from genome-wide association studies (GWAS) and performed latent causal variable analyses using a hypothesis-free approach to infer causal associations between 1387 complex traits and ADHD. We identified 37 inferred potential causal associations with ADHD risk. Our results reveal that genetic variants associated with iron deficiency anemia (ICD10), obesity, type 2 diabetes, synovitis and tenosynovitis (ICD10), polyarthritis (ICD10), neck or shoulder pain, and substance use in adults display partial genetic causality on ADHD risk in children. Genetic variants associated with ADHD have a partial genetic causality increasing the risk for chronic obstructive pulmonary disease and carpal tunnel syndrome. Protective factors for ADHD risk included genetic variants associated with the likelihood of participating in socially supportive and interactive activities. Our results show that genetic liability to multiple complex traits influences a higher risk for ADHD, highlighting the potential role of cardiometabolic phenotypes and physical pain in ADHD’s aetiology. These findings have the potential to inform future clinical studies and development of interventions.
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Affiliation(s)
- Luis M García-Marín
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia. .,School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.
| | - Adrián I Campos
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia.,School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia
| | - Gabriel Cuéllar-Partida
- The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, QLD, Australia.,23andMe, Inc, Sunnyvale, CA, USA
| | - Sarah E Medland
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
| | - Scott H Kollins
- Department of Psychiatry & Behavioral Sciences, School of Medicine, Duke University, Durham, NC, USA.,Holmusk Technologies, Inc., New York, NY, USA
| | - Miguel E Rentería
- Department of Genetics and Computational Biology, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia. .,School of Biomedical Sciences, Faculty of Medicine, The University of Queensland, Brisbane, QLD, Australia.
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10
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Understanding genetic risk factors for common side effects of antidepressant medications. COMMUNICATIONS MEDICINE 2021; 1:45. [PMID: 35602235 PMCID: PMC9053224 DOI: 10.1038/s43856-021-00046-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Accepted: 10/21/2021] [Indexed: 01/03/2023] Open
Abstract
Background Major depression is one of the most disabling health conditions internationally. In recent years, new generation antidepressant medicines have become very widely prescribed. While these medicines are efficacious, side effects are common and frequently result in discontinuation of treatment. Compared with specific pharmacological properties of the different medications, the relevance of individual vulnerability is understudied. Methods We used data from the Australian Genetics of Depression Study to gain insights into the aetiology and genetic risk factors to antidepressant side effects. To this end, we employed structural equation modelling, polygenic risk scoring and regressions. Results Here we show that participants reporting a specific side effect for one antidepressant are more likely to report the same side effect for other antidepressants, suggesting the presence of shared individual or pharmacological factors. Polygenic risk scores (PRS) for depression associated with side effects that overlapped with depressive symptoms, including suicidality and anxiety. Body Mass Index PRS are strongly associated with weight gain from all medications. PRS for headaches are associated with headaches from sertraline. Insomnia PRS show some evidence of predicting insomnia from amitriptyline and escitalopram. Conclusions Our results suggest a set of common factors underlying the risk for antidepressant side effects. These factors seem to be partly explained by genetic liability related to depression severity and the nature of the side effect. Future studies on the genetic aetiology of side effects will enable insights into their underlying mechanisms and the possibility of risk stratification and prophylaxis strategies. Antidepressants are commonly prescribed medications, but adverse side effects are cause for treatment discontinuation. We analysed data from a large group of adults who have taken antidepressants to understand why some people experience specific side effects. Our results suggest that a person’s genetic characteristics play a role. For example, participants genetically predisposed to a higher body mass index were more likely to report weight gain from antidepressants. These results open up the possibility of predicting adverse side effects as we increase our knowledge on the genetics of related complex traits. Future studies can focus on performing large-scale genetic studies of antidepressant side effects to gain further insights into the mechanisms underlying antidepressant side effects and to identify genetic markers of side effects that could be used in the clinic. Campos et al. study the genetic aetiology of antidepressant side effects. Using data from the Australian Genetics of Depression study, the authors show that polygenic risk scores for traits such as BMI, insomnia and headaches have a shared genetic basis with side effects to commonly used antidepressant drugs.
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11
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Bentivegna E, Luciani M, Scarso F, Bruscia C, Chiappino D, Amore E, Nalli G, Martelletti P. Hormonal therapies in migraine management: current perspectives on patient selection and risk management. Expert Rev Neurother 2021; 21:1347-1355. [PMID: 34739361 DOI: 10.1080/14737175.2021.2003706] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
INTRODUCTION The link between sex hormones and migraines has long been investigated but the mechanisms underlying this altered interaction are not yet fully understood. Herein, we retrace the knowledge on this association in relationship with risk of stroke. AREAS COVERED Estrogens fluctuations could trigger migraine attacks and exogenous estrogens intake could be a risk factor for venous thromboembolism (VTE) and stroke. At the same time, ischemic heart diseases and stroke share a common substrate with migraine and other mood disorders, depression, and anxiety. EXPERT OPINION The use of hormonal therapies in the context of contraception or replacement therapy must be closely evaluated in a careful risk assessment. We highlight the complex interaction of hormone/neuroinflammation pathways underlying the pathophysiology of migraine glimpsing in mood disorders a possible common denominator of link between hormonal and neuronal systems.
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Affiliation(s)
- Enrico Bentivegna
- Department of Clinical and Molecular Medicine, Sapienza University, Rome, Italy.,Regional Referral Headache Centre, Sant'Andrea Hospital, Rome, Italy
| | - Michelangelo Luciani
- Department of Clinical and Molecular Medicine, Sapienza University, Rome, Italy.,Regional Referral Headache Centre, Sant'Andrea Hospital, Rome, Italy
| | - Francesco Scarso
- Department of Clinical and Molecular Medicine, Sapienza University, Rome, Italy.,Regional Referral Headache Centre, Sant'Andrea Hospital, Rome, Italy
| | - Clara Bruscia
- Department of Clinical and Molecular Medicine, Sapienza University, Rome, Italy.,Regional Referral Headache Centre, Sant'Andrea Hospital, Rome, Italy
| | - Dario Chiappino
- Department of Clinical and Molecular Medicine, Sapienza University, Rome, Italy.,Regional Referral Headache Centre, Sant'Andrea Hospital, Rome, Italy
| | - Emanuele Amore
- Department of Clinical and Molecular Medicine, Sapienza University, Rome, Italy.,Regional Referral Headache Centre, Sant'Andrea Hospital, Rome, Italy
| | - Gabriele Nalli
- Department of Clinical and Molecular Medicine, Sapienza University, Rome, Italy.,Regional Referral Headache Centre, Sant'Andrea Hospital, Rome, Italy
| | - Paolo Martelletti
- Department of Clinical and Molecular Medicine, Sapienza University, Rome, Italy.,Regional Referral Headache Centre, Sant'Andrea Hospital, Rome, Italy
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Özaltun MF, Geyik S, Yılmaz ŞG. Screening for Copy Number Variations of the 15q13.3 Hotspot in CHRNA7 Gene and Expression in Patients with Migraines. Curr Issues Mol Biol 2021; 43:1090-1113. [PMID: 34563047 PMCID: PMC8929100 DOI: 10.3390/cimb43020078] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 08/24/2021] [Accepted: 09/02/2021] [Indexed: 12/02/2022] Open
Abstract
Background: a migraine is a neurological disease. Copy number variation (CNV) is a phenomenon in which parts of the genome are repeated. We investigated the effects of the CNV and gene expression at the location 15q13.3 in the Cholinergic Receptor Nicotinic Alpha 7 Subunit (CHRNA7) gene, which we believe to be effective in the migraine clinic. Methods: we evaluated changes in CHRNA7 gene expression levels and CNV of 15q13.3 in patients with migraine (n = 102, with aura, n = 43; without aura, n = 59) according to healthy controls (n = 120) by q-PCR. The data obtained were analyzed against the reference telomerase reverse transcriptase (TERT) gene with the double copy number by standard curve analysis. Copy numbers were graded as a normal copy (2), gain (2>), and loss (<2). Results: we analyzed using the 2−ΔΔCT calculation method. The CHRNA7 gene was significantly downregulated in patients (p < 0.05). The analysis of CNV in the CHRNA7 gene was statistically significant in the patient group, according to healthy controls (p < 0.05). A decreased copy number indicates a dosage loss. However, no significant difference was observed among gain, normal, and loss copy numbers and expression values in patients (p > 0.05). The change in CNV was not associated with the downregulation of the CHRNA7 gene. Conclusion: Downregulation of the CHRNA7 gene may contribute to the formation of migraine by inactivation of the alpha-7 nicotinic receptor (α7nAChR). The association of CNV gains and losses with migraines will lead to better understanding of the molecular mechanisms and pathogenesis, to better define the disease, to be used as a treatment target.
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Affiliation(s)
- Mehmet Fatih Özaltun
- Department of Neurology, Gaziantep University, Gaziantep 27310, Turkey; (M.F.Ö.); (S.G.)
| | - Sırma Geyik
- Department of Neurology, Gaziantep University, Gaziantep 27310, Turkey; (M.F.Ö.); (S.G.)
| | - Şenay Görücü Yılmaz
- Department of Nutrition and Dietetics, Gaziantep University, Gaziantep 27310, Turkey
- Correspondence: or ; Tel.: +90-(342)-360-1200; Fax: +90-(342)-360-8795
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