1
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Zhang SX, Li LZ. War Anxiety: A Review. Curr Psychiatry Rep 2024:10.1007/s11920-024-01583-4. [PMID: 39738916 DOI: 10.1007/s11920-024-01583-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 12/16/2024] [Indexed: 01/02/2025]
Abstract
PURPOSE OF REVIEW This review critically evaluates literature on war-induced anxiety, highlighting findings from 2021 to 2024, especially during the Russia-Ukraine war. RECENT FINDINGS Measures and prevalence estimates of anxiety and fear are updated. Populations affected by armed conflicts include residents of conflict zones and neighboring countries, internally displaced persons, refugees, combatants, and healthcare and humanitarian aid workers. Socioeconomic factors predict anxiety incidence and individuals differ in coping strategies. Anxiety could have long-term adverse effects over the life-course and across generations. Community and online interventions may reduce anxiety. The review underscores research directions in war-related anxiety's definition and assessment, risk and protective factors, health and societal consequences, and prevention and treatment approaches. The review provides an update for mental health researchers and practitioners working with the victims of war and other crises, often compounded by additional layers of stress of social inequalities, political divisions, and ethnic and racial tensions.
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Affiliation(s)
- Stephen X Zhang
- University of Adelaide, 9-30 Nexus10 Tower, 10 Pulteney St, Adelaide, SA, 5000, Australia.
- Baylor University, 1621 S 3rd St, Waco, TX, 76706, USA.
| | - Lambert Zixin Li
- Stanford University, 152B East Faculty Building, 655 Knight Way, Stanford, CA, 94305-7298, USA
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2
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Sun Z, Liu M, Zhao G, Zhang Z, Xu J, Song L, Zhang W, Wang S, Jia L, Wu Q, Wu Y, Wang H, Liu N, Su Q, Liu F. Causal relationships between cortical brain structural alterations and migraine subtypes: a bidirectional Mendelian randomization study of 2,347 neuroimaging phenotypes. J Headache Pain 2024; 25:186. [PMID: 39468451 PMCID: PMC11514853 DOI: 10.1186/s10194-024-01896-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2024] [Accepted: 10/23/2024] [Indexed: 10/30/2024] Open
Abstract
BACKGROUND Previous studies have shown that migraines are associated with brain structural changes. However, the causal relationships between these changes and migraine, as well as its subtypes, migraine with aura (MA) and migraine without aura (MO), remain largely unclear. METHODS We utilized genome-wide association study (GWAS) summary statistics from European cohorts for 2,347 cortical structural magnetic resonance imaging (MRI) phenotypes, derived from both T1-weighted and diffusion tensor imaging scans (n = 36,663), with migraine and its subtypes (n = 147,970-375,752). Cortical phenotypes included both macrostructural (e.g., cortical thickness, surface area) and microstructural (e.g., fractional anisotropy, mean diffusivity) features. Genetic correlations were first assessed to identify significant associations, followed by bidirectional Mendelian randomization (MR) analyses to determine causal relationships between these brain phenotypes and migraine, as well as its subtypes (MA and MO). Sensitivity analyses were applied to ensure the robustness of the results. RESULTS Genetic correlation analysis identified 510 significant associations between cortical structural phenotypes and migraine across 401 distinct traits. Forward MR analysis revealed nine significant causal effects of cortical structural changes on migraine risk. Specifically, increased cortical thickness and local gyrification index in specific cortical regions were associated with a decreased risk of overall migraine, MA, and MO, while intracellular volume fraction and orientation diffusion index in specific regions increased the risk of MA and MO. Reverse MR analysis demonstrated that MA causally increased mean diffusivity in the insular and frontal opercular cortex. Sensitivity analyses confirmed the robustness of these findings, with no evidence of horizontal pleiotropy or heterogeneity. CONCLUSION This study identifies causal relationships between cortical neuroimaging phenotypes and migraine, highlighting potential biomarkers for migraine diagnosis, treatment, and prevention.
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Affiliation(s)
- Zuhao Sun
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Mengge Liu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Guoshu Zhao
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Zhihui Zhang
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Jinglei Xu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Linlin Song
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Wanwan Zhang
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Shaoying Wang
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Linlin Jia
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Qian Wu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Yue Wu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Haolin Wang
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China
| | - Nannan Liu
- Institute of Mental Health, Tianjin Anding Hospital, Mental Health Center of Tianjin Medical University, Tianjin, 300222, China.
- Brain Assessment & Intervention Laboratory, Tianjin Anding Hospital, Institute of Mental Health, Mental Health Center of Tianjin Medical University, Tianjin, 300222, China.
| | - Qian Su
- Department of Molecular Imaging and Nuclear Medicine, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for China, Tianjin, 300060, China.
| | - Feng Liu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, No. 154, Anshan Road, Heping District, Tianjin, 300052, China.
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Wang W, Jia W, Wang S, Wang Y, Zhang Z, Lei M, Zhai Y, Xu J, Sun J, Zhang W, Wang Y, Jiang Y, Jiang Y, Liu M, Sun Z, Liu F. Unraveling the causal relationships between depression and brain structural imaging phenotypes: A bidirectional Mendelian Randomization study. Brain Res 2024; 1840:149049. [PMID: 38825161 DOI: 10.1016/j.brainres.2024.149049] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2024] [Revised: 05/11/2024] [Accepted: 05/30/2024] [Indexed: 06/04/2024]
Abstract
BACKGROUND Previous studies have revealed structural brain abnormalities in individuals with depression, but the causal relationship between depression and brain structure remains unclear. METHODS A genetic correlation analysis was conducted using summary statistics from the largest genome-wide association studies for depression (N = 674,452) and 1,265 brain structural imaging-derived phenotypes (IDPs, N = 33,224). Subsequently, a bidirectional two-sample Mendelian Randomization (MR) approach was employed to explore the causal relationships between depression and the IDPs that showed genetic correlations with depression. The main MR results were obtained using the inverse variance weighted (IVW) method, and other MR methods were further employed to ensure the reliability of the findings. RESULTS Ninety structural IDPs were identified as being genetically correlated with depression and were included in the MR analyses. The IVW MR results indicated that reductions in the volume of several brain regions, including the bilateral subcallosal cortex, right medial orbitofrontal cortex, and right middle-posterior part of the cingulate cortex, were causally linked to an increased risk of depression. Additionally, decreases in surface area of the right middle temporal visual area, right middle temporal cortex, right inferior temporal cortex, and right middle-posterior part of the cingulate cortex were causally associated with a heightened risk of depression. Validation and sensitivity analyses supported the robustness of these findings. However, no evidence was found for a causal effect of depression on structural IDPs. CONCLUSIONS Our findings reveal the causal influence of specific brain structures on depression, providing evidence to consider brain structural changes in the etiology and treatment of depression.
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Affiliation(s)
- Wenqin Wang
- School of Mathematical Sciences, Tiangong University, Tianjin 300387, China.
| | - Wenhui Jia
- School of Mathematical Sciences, Tiangong University, Tianjin 300387, China
| | - Shaoying Wang
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Ying Wang
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Zhihui Zhang
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Minghuan Lei
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Ying Zhai
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jinglei Xu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jinghan Sun
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Wanwan Zhang
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yao Wang
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yurong Jiang
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yifan Jiang
- School of Nursing, Tianjin Medical University, Tianjin 300070, China
| | - Mengge Liu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China.
| | - Zuhao Sun
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China.
| | - Feng Liu
- Department of Radiology, Tianjin Key Laboratory of Functional Imaging & Tianjin Institute of Radiology, Tianjin Medical University General Hospital, Tianjin 300052, China.
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Friligkou E, Løkhammer S, Cabrera-Mendoza B, Shen J, He J, Deiana G, Zanoaga MD, Asgel Z, Pilcher A, Di Lascio L, Makharashvili A, Koller D, Tylee DS, Pathak GA, Polimanti R. Gene discovery and biological insights into anxiety disorders from a large-scale multi-ancestry genome-wide association study. Nat Genet 2024; 56:2036-2045. [PMID: 39294497 DOI: 10.1038/s41588-024-01908-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Accepted: 08/13/2024] [Indexed: 09/20/2024]
Abstract
We leveraged information from more than 1.2 million participants, including 97,383 cases, to investigate the genetics of anxiety disorders across five continental groups. Through ancestry-specific and cross-ancestry genome-wide association studies, we identified 51 anxiety-associated loci, 39 of which were novel. In addition, polygenic risk scores derived from individuals of European descent were associated with anxiety in African, admixed American and East Asian groups. The heritability of anxiety was enriched for genes expressed in the limbic system, cerebral cortex, cerebellum, metencephalon, entorhinal cortex and brain stem. Transcriptome-wide and proteome-wide analyses highlighted 115 genes associated with anxiety through brain-specific and cross-tissue regulation. Anxiety also showed global and local genetic correlations with depression, schizophrenia and bipolar disorder and widespread pleiotropy with several physical health domains. Overall, this study expands our knowledge regarding the genetic risk and pathogenesis of anxiety disorders, highlighting the importance of investigating diverse populations and integrating multi-omics information.
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Affiliation(s)
- Eleni Friligkou
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT, USA
| | - Solveig Løkhammer
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr. Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Brenda Cabrera-Mendoza
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT, USA
| | - Jie Shen
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Cardiology, Children's Hospital of Soochow University, Suzhou, China
| | - Jun He
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT, USA
| | - Giovanni Deiana
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Center for Neuroscience, Pharmacology Unit, School of Pharmacy, University of Camerino, Camerino, Italy
| | - Mihaela Diana Zanoaga
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
| | - Zeynep Asgel
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Child and Adolescent Psychiatry, NYU Langone Health, New York Metropolitan Area, New York, NY, USA
| | - Abigail Pilcher
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Luciana Di Lascio
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- IRCCS Istituto Clinico Humanitas, Rozzano, Milan, Italy; Humanitas University, Pieve Emanuele, Milan, Italy
| | - Ana Makharashvili
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT, USA
| | - Dora Koller
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Genetics, Microbiology and Statistics, Faculty of Biology, University of Barcelona, Barcelona, Spain
| | - Daniel S Tylee
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
| | - Gita A Pathak
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT, USA
| | - Renato Polimanti
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA.
- Cooperative Studies Program Clinical Epidemiology Research Center (CSP-CERC), VA Connecticut Healthcare System, West Haven, CT, USA.
- Wu Tsai Institute, Yale University, New Haven, CT, USA.
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT, USA.
- Department of Biomedical Informatics and Data Science, Yale School of Medicine, New Haven, CT, USA.
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5
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Huang D, Wu Y, Yue J, Wang X. Causal relationship between resting-state networks and depression: a bidirectional two-sample mendelian randomization study. BMC Psychiatry 2024; 24:402. [PMID: 38811927 PMCID: PMC11138044 DOI: 10.1186/s12888-024-05857-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2023] [Accepted: 05/20/2024] [Indexed: 05/31/2024] Open
Abstract
BACKGROUND Cerebral resting-state networks were suggested to be strongly associated with depressive disorders. However, the causal relationship between cerebral networks and depressive disorders remains controversial. In this study, we aimed to investigate the effect of resting-state networks on depressive disorders using a bidirectional Mendelian randomization (MR) design. METHODS Updated summary-level genome-wide association study (GWAS) data correlated with resting-state networks were obtained from a meta-analysis of European-descent GWAS from the Complex Trait Genetics Lab. Depression-related GWAS data were obtained from the FinnGen study involving participants with European ancestry. Resting-state functional magnetic resonance imaging and multiband diffusion imaging of the brain were performed to measure functional and structural connectivity in seven well-known networks. Inverse-variance weighting was used as the primary estimate, whereas the MR-Pleiotropy RESidual Sum and Outliers (PRESSO), MR-Egger, and weighted median were used to detect heterogeneity, sensitivity, and pleiotropy. RESULTS In total, 20,928 functional and 20,573 structural connectivity data as well as depression-related GWAS data from 48,847 patients and 225,483 controls were analyzed. Evidence for a causal effect of the structural limbic network on depressive disorders was found in the inverse variance-weighted limbic network (odds ratio, [Formula: see text]; 95% confidence interval, [Formula: see text]; [Formula: see text]), whereas the causal effect of depressive disorders on SC LN was not found(OR=1.0025; CI,1.0005-1.0046; P=0.012). No significant associations between functional connectivity of the resting-state networks and depressive disorders were found in this MR study. CONCLUSIONS These results suggest that genetically determined structural connectivity of the limbic network has a causal effect on depressive disorders and may play a critical role in its neuropathology.
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Affiliation(s)
- Dongmiao Huang
- Department of Psychiatry, the Fifth Affiliated Hospital of Sun Yat-sen University, No. 52, East Meihua Road, Zhuhai City, Guangdong Province, 519000, China
| | - Yuelin Wu
- Department of Psychiatry, the Fifth Affiliated Hospital of Sun Yat-sen University, No. 52, East Meihua Road, Zhuhai City, Guangdong Province, 519000, China
| | - Jihui Yue
- Department of Psychiatry, the Fifth Affiliated Hospital of Sun Yat-sen University, No. 52, East Meihua Road, Zhuhai City, Guangdong Province, 519000, China.
| | - Xianglan Wang
- Department of Psychiatry, the Fifth Affiliated Hospital of Sun Yat-sen University, No. 52, East Meihua Road, Zhuhai City, Guangdong Province, 519000, China.
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Liu W, Yan H, Jia W, Huang J, Fu Z, Xu W, Yu H, Yang W, Pan W, Zheng B, Liu Y, Chen X, Gao Y, Tian D. Association between gut microbiota and Hirschsprung disease: a bidirectional two-sample Mendelian randomization study. Front Microbiol 2024; 15:1366181. [PMID: 38516012 PMCID: PMC10956417 DOI: 10.3389/fmicb.2024.1366181] [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: 01/05/2024] [Accepted: 02/20/2024] [Indexed: 03/23/2024] Open
Abstract
Background Several studies have pointed to the critical role of gut microbiota (GM) and their metabolites in Hirschsprung disease (HSCR) pathogenesis. However, the detailed causal relationship between GM and HSCR remains unknown. Methods In this study, we used two-sample Mendelian randomization (MR) analysis to investigate the causal relationship between GM and HSCR, based on the MiBioGen Consortium's genome-wide association study (GWAS) and the GWAS Catalog's HSCR data. Reverse MR analysis was performed subsequently, and the sensitivity analysis, Cochran's Q-test, MR pleiotropy residual sum, outlier (MR-PRESSO), and the MR-Egger intercept were used to analyze heterogeneity or horizontal pleiotropy. 16S rDNA sequencing and targeted mass spectrometry were developed for initial validation. Results In the forward MR analysis, inverse-variance weighted (IVW) estimates suggested that Eggerthella (OR: 2.66, 95%CI: 1.23-5.74, p = 0.01) was a risk factor for HSCR, while Peptococcus (OR: 0.37, 95%CI: 0.18-0.73, p = 0.004), Ruminococcus2 (OR: 0.32, 95%CI: 0.11-0.91, p = 0.03), Clostridiaceae1 (OR: 0.22, 95%CI: 0.06-0.78, p = 0.02), Mollicutes RF9 (OR: 0.27, 95%CI: 0.09-0.8, p = 0.02), Ruminococcaceae (OR: 0.16, 95%CI: 0.04-0.66, p = 0.01), and Paraprevotella (OR: 0.45, 95%CI: 0.21-0.98, p = 0.04) were protective factors for HSCR, which had no heterogeneity or horizontal pleiotropy. However, reverse MR analysis showed that HSCR (OR: 1.02, 95%CI: 1-1.03, p = 0.049) is the risk factor for Eggerthella. Furthermore, some of the above microbiota and short-chain fatty acids (SCFAs) were altered in HSCR, showing a correlation. Conclusion Our analysis established the relationship between specific GM and HSCR, identifying specific bacteria as protective or risk factors. Significant microbiota and SCFAs were altered in HSCR, underlining the importance of further study and providing new insights into the pathogenesis and treatment.
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Affiliation(s)
- Wei Liu
- Department of Pediatric Surgery, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
- Institute of Neurobiology, Environment and Genes Related to Diseases Key Laboratory of Chinese Ministry of Education, Xi'an Jiaotong University, Xi'an, China
| | - Hanlei Yan
- Department of Pediatric Surgery, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
- Institute of Neurobiology, Environment and Genes Related to Diseases Key Laboratory of Chinese Ministry of Education, Xi'an Jiaotong University, Xi'an, China
| | - Wanying Jia
- Department of Pediatric Surgery, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
- Institute of Neurobiology, Environment and Genes Related to Diseases Key Laboratory of Chinese Ministry of Education, Xi'an Jiaotong University, Xi'an, China
| | - Jingjing Huang
- Department of Pediatric Surgery, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
- Institute of Neurobiology, Environment and Genes Related to Diseases Key Laboratory of Chinese Ministry of Education, Xi'an Jiaotong University, Xi'an, China
| | - Zihao Fu
- Department of Pediatric Surgery, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
- Institute of Neurobiology, Environment and Genes Related to Diseases Key Laboratory of Chinese Ministry of Education, Xi'an Jiaotong University, Xi'an, China
| | - Wenyao Xu
- Department of Pediatric Surgery, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
- Institute of Neurobiology, Environment and Genes Related to Diseases Key Laboratory of Chinese Ministry of Education, Xi'an Jiaotong University, Xi'an, China
| | - Hui Yu
- Department of Pediatric Surgery, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
- Institute of Neurobiology, Environment and Genes Related to Diseases Key Laboratory of Chinese Ministry of Education, Xi'an Jiaotong University, Xi'an, China
| | - Weili Yang
- Department of Pediatric Surgery, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Weikang Pan
- Department of Pediatric Surgery, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Baijun Zheng
- Department of Pediatric Surgery, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Yong Liu
- Institute of Neurobiology, Environment and Genes Related to Diseases Key Laboratory of Chinese Ministry of Education, Xi'an Jiaotong University, Xi'an, China
| | - Xinlin Chen
- Institute of Neurobiology, Environment and Genes Related to Diseases Key Laboratory of Chinese Ministry of Education, Xi'an Jiaotong University, Xi'an, China
| | - Ya Gao
- Department of Pediatric Surgery, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
| | - Donghao Tian
- Department of Pediatric Surgery, The Second Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China
- Institute of Neurobiology, Environment and Genes Related to Diseases Key Laboratory of Chinese Ministry of Education, Xi'an Jiaotong University, Xi'an, China
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7
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Friligkou E, Løkhammer S, Cabrera-Mendoza B, Shen J, He J, Deiana G, Zanoaga MD, Asgel Z, Pilcher A, Di Lascio L, Makharashvili A, Koller D, Tylee DS, Pathak GA, Polimanti R. Gene Discovery and Biological Insights into Anxiety Disorders from a Multi-Ancestry Genome-wide Association Study of >1.2 Million Participants. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.14.24302836. [PMID: 38405718 PMCID: PMC10889004 DOI: 10.1101/2024.02.14.24302836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
We leveraged information from more than 1.2 million participants to investigate the genetics of anxiety disorders across five continental ancestral groups. Ancestry-specific and cross-ancestry genome-wide association studies identified 51 anxiety-associated loci, 39 of which are novel. Additionally, polygenic risk scores derived from individuals of European descent were associated with anxiety in African, Admixed-American, and East Asian groups. The heritability of anxiety was enriched for genes expressed in the limbic system, the cerebral cortex, the cerebellum, the metencephalon, the entorhinal cortex, and the brain stem. Transcriptome- and proteome-wide analyses highlighted 115 genes associated with anxiety through brain-specific and cross-tissue regulation. We also observed global and local genetic correlations with depression, schizophrenia, and bipolar disorder and putative causal relationships with several physical health conditions. Overall, this study expands the knowledge regarding the genetic risk and pathogenesis of anxiety disorders, highlighting the importance of investigating diverse populations and integrating multi-omics information.
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