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Jiang MZ, Gaynor SM, Li X, Van Buren E, Stilp A, Buth E, Wang FF, Manansala R, Gogarten SM, Li Z, Polfus LM, Salimi S, Bis JC, Pankratz N, Yanek LR, Durda P, Tracy RP, Rich SS, Rotter JI, Mitchell BD, Lewis JP, Psaty BM, Pratte KA, Silverman EK, Kaplan RC, Avery C, North KE, Mathias RA, Faraday N, Lin H, Wang B, Carson AP, Norwood AF, Gibbs RA, Kooperberg C, Lundin J, Peters U, Dupuis J, Hou L, Fornage M, Benjamin EJ, Reiner AP, Bowler RP, Lin X, Auer PL, Raffield LM. Whole genome sequencing based analysis of inflammation biomarkers in the Trans-Omics for Precision Medicine (TOPMed) consortium. Hum Mol Genet 2024; 33:1429-1441. [PMID: 38747556 PMCID: PMC11305684 DOI: 10.1093/hmg/ddae050] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 01/31/2024] [Accepted: 03/11/2024] [Indexed: 05/28/2024] Open
Abstract
Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38 465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program (with varying sample size by trait, where the minimum sample size was n = 737 for MMP-1). We identified 22 distinct single-variant associations across 6 traits-E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin-that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.
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Affiliation(s)
- Min-Zhi Jiang
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599, United States
| | - Sheila M Gaynor
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA 02115, United States
- Regeneron Genetics Center, 777 Old Saw Mill River Road, Tarrytown, NY 10591, United States
| | - Xihao Li
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599, United States
- Department of Biostatistics, 135 Dauer Drive, 4115D McGavran-Greenberg Hall, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, United States
| | - Eric Van Buren
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA 02115, United States
| | - Adrienne Stilp
- Department of Biostatistics, 4333 Brooklyn Ave NE, University of Washington, Seattle, WA 98105, United States
| | - Erin Buth
- Department of Biostatistics, 4333 Brooklyn Ave NE, University of Washington, Seattle, WA 98105, United States
| | - Fei Fei Wang
- Department of Biostatistics, 4333 Brooklyn Ave NE, University of Washington, Seattle, WA 98105, United States
| | - Regina Manansala
- Centre for Health Economics Research & Modelling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO) WHO Collaborating Centre, University of Antwerp, Campus Drie Eiken - Building S; Universiteitsplein 1 2610 Antwerpen, Belgium
| | - Stephanie M Gogarten
- Department of Biostatistics, 4333 Brooklyn Ave NE, University of Washington, Seattle, WA 98105, United States
| | - Zilin Li
- School of Mathematics and Statistics, Northeast Normal University, 5268 Renmin Street, Changchun, JL 130024, China
| | - Linda M Polfus
- Advanced Analytics, Ambry Genetics, 1 Enterprise, Aliso Viejo, CA 92656, United States
| | - Shabnam Salimi
- Department of Epidemiology and Public Health, Division of Gerontology, University of Maryland School of Medicine, 655 W. Baltimore Street, Baltimore, MD 21201, United States
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 4333 Brooklyn Ave NE, Box 359458, Seattle, WA 98195, United States
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, 420 Delaware Street SE, Minneapolis, MN 55455, United States
| | - Lisa R Yanek
- Department of Medicine, General Internal Medicine, Johns Hopkins University School of Medicine, 1830 E Monument St Rm 8024, Baltimore, MD 21287, United States
| | - Peter Durda
- Department of Pathology & Laboratory Medicine, University of Vermont Larner College of Medicine, 360 South Park Drive, Colchester, VT 05446, United States
| | - Russell P Tracy
- Department of Pathology & Laboratory Medicine, University of Vermont Larner College of Medicine, 360 South Park Drive, Colchester, VT 05446, United States
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, 200 Jeanette Lancaster Way, Charlottesville, VA 22903, United States
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, 1124 W. Carson Street, Torrance, CA 90502, United States
| | - Braxton D Mitchell
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, 670 W. Baltimore St., Baltimore, MD 21201, United States
| | - Joshua P Lewis
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, 670 W. Baltimore St., Baltimore, MD 21201, United States
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 4333 Brooklyn Ave NE, Box 359458, Seattle, WA 98195, United States
- Departments of Epidemiology and Health Systems and Population Health, University of Washington, 4333 Brooklyn Ave NE, Seattle, WA 98101, United States
| | - Katherine A Pratte
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, 1400 Jackson Street, Denver, CO 80206, United States
| | - Edwin K Silverman
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital, 181 Longwood Avenue, Boston, MA 02115, United States
| | - Robert C Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, 1300 Morris Park Avenue, Bronx, NY 10461, United States
| | - Christy Avery
- Department of Epidemiology, University of North Carolina at Chapel Hill, 137 East Franklin Street, Chapel Hill, NC 27599, United States
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, 137 East Franklin Street, Chapel Hill, NC 27599, United States
| | - Rasika A Mathias
- Department of Medicine, Allergy and Clinical Immunology, Johns Hopkins University School of Medicine, 5501 Hopkins Bayview Cir JHAAC Room 3B53, Baltimore, MD 21287, United States
| | - Nauder Faraday
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD 21287, United States
| | - Honghuang Lin
- Department of Medicine, University of Massachusetts Chan Medical School, 55 Lake Ave North, Worcester, MA 01655, United States
| | - Biqi Wang
- Department of Medicine, University of Massachusetts Chan Medical School, 55 Lake Ave North, Worcester, MA 01655, United States
| | - April P Carson
- Department of Medicine, University of Mississippi Medical Center, 350 W. Woodrow Wilson Avenue, Suite 701, Jackson, MS 39213, United States
| | - Arnita F Norwood
- Department of Medicine, University of Mississippi Medical Center, 350 W. Woodrow Wilson Avenue, Suite 701, Jackson, MS 39213, United States
| | - Richard A Gibbs
- Department of Molecular and Human Genetics, Human Genome Sequencing Center, Baylor College of Medicine, One Baylor Plaza, Houston, TX 77030, United States
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, 1100 Fairview Avenue N, Seattle, WA 98109, United States
| | - Jessica Lundin
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, 1100 Fairview Avenue N, Seattle, WA 98109, United States
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, 1100 Fairview Avenue N, Seattle, WA 98109, United States
| | - Josée Dupuis
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, 2001 McGill College Avenue, Montreal, QC H3A 1G1, Canada
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA 02118, United States
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, 680 N Lake Shore Drive, Chicago, IL 60611, United States
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, 1825 Pressler Street, Houston, TX 77030, United States
| | - Emelia J Benjamin
- Department of Medicine, Cardiovascular Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, 72 East Newton Street, Boston, MA 02118, United States
- Department of Epidemiology, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA 02118, United States
- Boston University and National Heart, Lung, and Blood Institute’s Framingham Heart Study, 73 Mount Wayte Ave #2, Framingham, MA 01702, United States
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, 4333 Brooklyn Ave NE, Seattle, WA 98105, United States
| | - Russell P Bowler
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, 1400 Jackson Street, Denver, CO 80206, United States
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA 02115, United States
| | - Paul L Auer
- Division of Biostatistics, Institute for Health and Equity, and Cancer Center, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, United States
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC 27599, United States
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Kamali Z, Esmaeil N, Thio CHL, Vaez A, Snieder H. Pathway-Based Mendelian Randomization for Pre-Infection IL-6 Levels Highlights Its Role in Coronavirus Disease. Genes (Basel) 2024; 15:889. [PMID: 39062668 PMCID: PMC11275426 DOI: 10.3390/genes15070889] [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: 06/04/2024] [Revised: 06/29/2024] [Accepted: 07/01/2024] [Indexed: 07/28/2024] Open
Abstract
OBJECTIVES Interleukin 6 (IL-6) levels at hospital admission have been suggested for disease prognosis, and IL-6 antagonists have been suggested for the treatment of patients with severe COVID-19. However, less is known about the relationship between pre-COVID-19 IL-6 levels and the risk of severe COVID-19. To fill in this gap, here we extensively investigated the association of genetically instrumented IL-6 pathway components with the risk of severe COVID-19. METHODS We used a two-sample Mendelian randomization study design and retrieved genetic instruments for blood biomarkers of IL-6 activation, including IL-6, soluble IL-6 receptor, IL-6 signal transducer, and CRP, from respective large available GWASs. To establish associations of these instruments with COVID-19 outcomes, we used data from the Host Genetics Initiative and GenOMICC studies. RESULTS Our analyses revealed inverse associations of genetically instrumented levels of IL-6 and its soluble receptor with the risk of developing severe disease (OR = 0.60 and 0.94, respectively). They also demonstrated a positive association of severe disease with the soluble signal transducer level (OR = 1.13). Only IL-6 associations with severe COVID-19 outcomes reached the significance threshold corrected for multiple testing (p < 0.003; with COVID-19 hospitalization and critical illness). CONCLUSIONS These potential causal relationships for pre-COVID-19 IL-6 levels with the risk of developing severe symptoms provide opportunities for further evaluation of these factors as prognostic/preventive markers of severe COVID-19. Further studies will need to clarify whether the higher risk for a severe disease course with lower baseline IL-6 levels may also extend to other infectious diseases.
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Affiliation(s)
- Zoha Kamali
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan 81746-73441, Iran
- Department of Epidemiology, University of Groningen, University Medical Centre Groningen, Hanzeplein 1 (9713 GZ), P.O. Box 30.001, 9700 RB Groningen, The Netherlands (H.S.)
| | - Nafiseh Esmaeil
- Department of Immunology, School of Medicine, Isfahan University of Medical Sciences, Isfahan 81746-73441, Iran;
- Research Institute for Primordial Prevention of Non-Communicable Disease, Isfahan University of Medical Sciences, Isfahan 81746-73441, Iran
| | - Chris H. L. Thio
- Department of Epidemiology, University of Groningen, University Medical Centre Groningen, Hanzeplein 1 (9713 GZ), P.O. Box 30.001, 9700 RB Groningen, The Netherlands (H.S.)
| | - Ahmad Vaez
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan 81746-73441, Iran
- Department of Epidemiology, University of Groningen, University Medical Centre Groningen, Hanzeplein 1 (9713 GZ), P.O. Box 30.001, 9700 RB Groningen, The Netherlands (H.S.)
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Centre Groningen, Hanzeplein 1 (9713 GZ), P.O. Box 30.001, 9700 RB Groningen, The Netherlands (H.S.)
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3
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Zheng S, Tsao PS, Pan C. Abdominal aortic aneurysm and cardiometabolic traits share strong genetic susceptibility to lipid metabolism and inflammation. Nat Commun 2024; 15:5652. [PMID: 38969659 PMCID: PMC11226445 DOI: 10.1038/s41467-024-49921-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Accepted: 06/25/2024] [Indexed: 07/07/2024] Open
Abstract
Abdominal aortic aneurysm has a high heritability and often co-occurs with other cardiometabolic disorders, suggesting shared genetic susceptibility. We investigate this commonality leveraging recent GWAS studies of abdominal aortic aneurysm and 32 cardiometabolic traits. We find significant genetic correlations between abdominal aortic aneurysm and 21 of the cardiometabolic traits investigated, including causal relationships with coronary artery disease, hypertension, lipid traits, and blood pressure. For each trait pair, we identify shared causal variants, genes, and pathways, revealing that cholesterol metabolism and inflammation are shared most prominently. Additionally, we show the tissue and cell type specificity in the shared signals, with strong enrichment across traits in the liver, arteries, adipose tissues, macrophages, adipocytes, and fibroblasts. Finally, we leverage drug-gene databases to identify several lipid-lowering drugs and antioxidants with high potential to treat abdominal aortic aneurysm with comorbidities. Our study provides insight into the shared genetic mechanism between abdominal aortic aneurysm and cardiometabolic traits, and identifies potential targets for pharmacological intervention.
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Affiliation(s)
- Shufen Zheng
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Guangzhou, China
- Center for Evolutionary Biology, Intelligent Medicine Institute, School of Life Sciences, Fudan University, Shanghai, China
| | - Philip S Tsao
- Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, USA.
- Stanford Cardiovascular Institute, Stanford University, California, USA.
- VA Palo Alto Health Care System, Palo Alto, California, USA.
| | - Cuiping Pan
- Center for Intelligent Medicine Research, Greater Bay Area Institute of Precision Medicine (Guangzhou), Guangzhou, China.
- Center for Evolutionary Biology, Intelligent Medicine Institute, School of Life Sciences, Fudan University, Shanghai, China.
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4
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Bergstedt J, Pasman JA, Ma Z, Harder A, Yao S, Parker N, Treur JL, Smit DJA, Frei O, Shadrin AA, Meijsen JJ, Shen Q, Hägg S, Tornvall P, Buil A, Werge T, Hjerling-Leffler J, Als TD, Børglum AD, Lewis CM, McIntosh AM, Valdimarsdóttir UA, Andreassen OA, Sullivan PF, Lu Y, Fang F. Distinct biological signature and modifiable risk factors underlie the comorbidity between major depressive disorder and cardiovascular disease. NATURE CARDIOVASCULAR RESEARCH 2024; 3:754-769. [PMID: 38898929 PMCID: PMC11182748 DOI: 10.1038/s44161-024-00488-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/31/2023] [Accepted: 05/08/2024] [Indexed: 06/21/2024]
Abstract
Major depressive disorder (MDD) and cardiovascular disease (CVD) are often comorbid, resulting in excess morbidity and mortality. Here we show that CVDs share most of their genetic risk factors with MDD. Multivariate genome-wide association analysis of shared genetic liability between MDD and atherosclerotic CVD revealed seven loci and distinct patterns of tissue and brain cell-type enrichments, suggesting the involvement of the thalamus. Part of the genetic overlap was explained by shared inflammatory, metabolic and psychosocial or lifestyle risk factors. Our data indicated causal effects of genetic liability to MDD on CVD risk, but not from most CVDs to MDD, and showed that the causal effects were partly explained by metabolic and psychosocial or lifestyle factors. The distinct signature of MDD-atherosclerotic CVD comorbidity suggests an immunometabolic subtype of MDD that is more strongly associated with CVD than overall MDD. In summary, we identified biological mechanisms underlying MDD-CVD comorbidity and modifiable risk factors for prevention of CVD in individuals with MDD.
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Affiliation(s)
- Jacob Bergstedt
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Joëlle A. Pasman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ziyan Ma
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Arvid Harder
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Shuyang Yao
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Nadine Parker
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Jorien L. Treur
- Genetic Epidemiology, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Dirk J. A. Smit
- Genetic Epidemiology, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Oleksandr Frei
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- Centre for Bioinformatics, Department of Informatics, University of Oslo, Oslo, Norway
| | - Alexey A. Shadrin
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Joeri J. Meijsen
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
| | - Qing Shen
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Clinical Research Center for Mental Disorders, Shanghai Pudong New Area Mental Health Center, Tongji University School of Medicine, Shanghai, China
- Institute for Advanced Study, Tongji University, Shanghai, China
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Per Tornvall
- Department of Clinical Science and Education Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
| | - Alfonso Buil
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jens Hjerling-Leffler
- Department Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Thomas D. Als
- Department of Molecular Medicine (MOMA), Molecular Diagnostic Laboratory, Aarhus University Hospital, Aarhus, Denmark
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Anders D. Børglum
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Cathryn M. Lewis
- Social, Genetic and Developmental Psychiatry Centre, King’s College London, London, UK
- Department of Medical and Molecular Genetics, King’s College London, London, UK
| | - Andrew M. McIntosh
- Centre for Clinical Brain Sciences, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Centre for Genomics and Experimental Medicine, University of Edinburgh, Edinburgh, UK
| | - Unnur A. Valdimarsdóttir
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Department of Epidemiology, Harvard TH Chan School of Public Health, Harvard University, Boston, MA USA
| | - Ole A. Andreassen
- Centre for Precision Psychiatry, Division of Mental Health and Addiction, University of Oslo and Oslo University Hospital, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental Disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Patrick F. Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Yi Lu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Fang Fang
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
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Kasher M, Freidin MB, Williams FMK, Cherny SS, Ashkenazi S, Livshits G. Glycoprotein Acetyls Is a Novel Biomarker Predicting Cardiovascular Complications in Rheumatoid Arthritis. Int J Mol Sci 2024; 25:5981. [PMID: 38892172 PMCID: PMC11173129 DOI: 10.3390/ijms25115981] [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: 04/30/2024] [Revised: 05/25/2024] [Accepted: 05/28/2024] [Indexed: 06/21/2024] Open
Abstract
The relationship between rheumatoid arthritis (RA) and early onset atherosclerosis is well depicted, each with an important inflammatory component. Glycoprotein acetyls (GlycA), a novel biomarker of inflammation, may play a role in the manifestation of these two inflammatory conditions. The present study examined a potential mediating role of GlycA within the RA-atherosclerosis relationship to determine whether it accounts for the excess risk of cardiovascular disease over that posed by lipid risk factors. The UK Biobank dataset was acquired to establish associations among RA, atherosclerosis, GlycA, and major lipid factors: total cholesterol (TC), high- and low-density lipoprotein (HDL, LDL) cholesterol, and triglycerides (TGs). Genome-wide association study summary statistics were collected from various resources to perform genetic analyses. Causality among variables was tested using Mendelian Randomization (MR) analysis. Genes of interest were identified using colocalization analysis and gene enrichment analysis. MR results appeared to indicate that the genetic relationship between GlycA and RA and also between RA and atherosclerosis was explained by horizontal pleiotropy (p-value = 0.001 and <0.001, respectively), while GlycA may causally predict atherosclerosis (p-value = 0.017). Colocalization analysis revealed several functionally relevant genes shared between GlycA and all the variables assessed. Two loci were apparent in all relationships tested and included the HLA region as well as SLC22A1. GlycA appears to mediate the RA-atherosclerosis relationship through several possible pathways. GlycA, although pleiotropically related to RA, appears to causally predict atherosclerosis. Thus, GlycA is suggested as a significant factor in the etiology of atherosclerosis development in RA.
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Affiliation(s)
- Melody Kasher
- Department of Morphological Sciences, Adelson School of Medicine, Ariel University, Ariel 4070000, Israel; (M.K.); (S.A.)
| | - Maxim B. Freidin
- Department of Biology, School of Biological and Behavioural Sciences, Queen Mary University of London, London E1 4NS, UK;
| | - Frances M. K. Williams
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King’s College London, London WC2R 2LS, UK;
| | - Stacey S. Cherny
- Human Population Biology Research Unit, Department of Anatomy and Anthropology, School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel;
- Department of Epidemiology and Preventive Medicine, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel
| | - Shai Ashkenazi
- Department of Morphological Sciences, Adelson School of Medicine, Ariel University, Ariel 4070000, Israel; (M.K.); (S.A.)
| | - Gregory Livshits
- Department of Morphological Sciences, Adelson School of Medicine, Ariel University, Ariel 4070000, Israel; (M.K.); (S.A.)
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King’s College London, London WC2R 2LS, UK;
- Human Population Biology Research Unit, Department of Anatomy and Anthropology, School of Medicine, Tel Aviv University, Tel Aviv 69978, Israel;
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Johnston KJ, Signer R, Huckins LM. Chronic Overlapping Pain Conditions and Nociplastic Pain. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.06.27.23291959. [PMID: 38766033 PMCID: PMC11100847 DOI: 10.1101/2023.06.27.23291959] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Chronic Overlapping Pain Conditions (COPCs) are a subset of chronic pain conditions commonly comorbid with one another and more prevalent in women and assigned female at birth (AFAB) individuals. Pain experience in these conditions may better fit with a new mechanistic pain descriptor, nociplastic pain, and nociplastic type pain may represent a shared underlying factor among COPCs. We applied GenomicSEM common-factor genome wide association study (GWAS) and multivariate transcriptome-wide association (TWAS) analyses to existing GWAS output for six COPCs in order to find genetic variation associated with nociplastic type pain, followed by genetic correlation (linkage-disequilibrium score regression), gene-set and tissue enrichment analyses. We found 24 independent single nucleotide polymorphisms (SNPs), and 127 unique genes significantly associated with nociplastic type pain, and showed nociplastic type pain to be a polygenic trait with significant SNP-heritability. We found significant genetic overlap between multisite chronic pain and nociplastic type pain, and to a smaller extent with rheumatoid arthritis and a neuropathic pain phenotype. Tissue enrichment analyses highlighted cardiac and thyroid tissue, and gene set enrichment analyses emphasized potential shared mechanisms in cognitive, personality, and metabolic traits and nociplastic type pain along with distinct pathology in migraine and headache. We use a well-powered network approach to investigate nociplastic type pain using existing COPC GWAS output, and show nociplastic type pain to be a complex, heritable trait, in addition to contributing to understanding of potential mechanisms in development of nociplastic pain.
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Affiliation(s)
- Keira J.A. Johnston
- Department of Psychiatry, Yale School of Medicine, Yale University, New Haven, CT 06511, USA
| | - Rebecca Signer
- Department of Genetic and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York City, NY 10029, USA
| | - Laura M. Huckins
- Department of Psychiatry, Yale School of Medicine, Yale University, New Haven, CT 06511, USA
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7
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Maihofer AX, Ratanatharathorn A, Hemmings SMJ, Costenbader KH, Michopoulos V, Polimanti R, Rothbaum AO, Seedat S, Mikita EA, Smith AK, Salem RM, Shaffer RA, Wu T, Sebat J, Ressler KJ, Stein MB, Koenen KC, Wolf EJ, Sumner JA, Nievergelt CM. Effects of genetically predicted posttraumatic stress disorder on autoimmune phenotypes. Transl Psychiatry 2024; 14:172. [PMID: 38561342 PMCID: PMC10984931 DOI: 10.1038/s41398-024-02869-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 02/21/2024] [Accepted: 03/11/2024] [Indexed: 04/04/2024] Open
Abstract
Observational studies suggest that posttraumatic stress disorder (PTSD) increases risk for various autoimmune diseases. Insights into shared biology and causal relationships between these diseases may inform intervention approaches to PTSD and co-morbid autoimmune conditions. We investigated the shared genetic contributions and causal relationships between PTSD, 18 autoimmune diseases, and 3 immune/inflammatory biomarkers. Univariate MiXeR was used to contrast the genetic architectures of phenotypes. Genetic correlations were estimated using linkage disequilibrium score regression. Bi-directional, two-sample Mendelian randomization (MR) was performed using independent, genome-wide significant single nucleotide polymorphisms; inverse variance weighted and weighted median MR estimates were evaluated. Sensitivity analyses for uncorrelated (MR PRESSO) and correlated horizontal pleiotropy (CAUSE) were also performed. PTSD was considerably more polygenic (10,863 influential variants) than autoimmune diseases (median 255 influential variants). However, PTSD evidenced significant genetic correlation with nine autoimmune diseases and three inflammatory biomarkers. PTSD had putative causal effects on autoimmune thyroid disease (p = 0.00009) and C-reactive protein (CRP) (p = 4.3 × 10-7). Inferences were not substantially altered by sensitivity analyses. Additionally, the PTSD-autoimmune thyroid disease association remained significant in multivariable MR analysis adjusted for genetically predicted inflammatory biomarkers as potential mechanistic pathway variables. No autoimmune disease had a significant causal effect on PTSD (all p values > 0.05). Although causal effect models were supported for associations of PTSD with CRP, shared pleiotropy was adequate to explain a putative causal effect of CRP on PTSD (p = 0.18). In summary, our results suggest a significant genetic overlap between PTSD, autoimmune diseases, and biomarkers of inflammation. PTSD has a putative causal effect on autoimmune thyroid disease, consistent with existing epidemiologic evidence. A previously reported causal effect of CRP on PTSD is potentially confounded by shared genetics. Together, results highlight the nuanced links between PTSD, autoimmune disorders, and associated inflammatory signatures, and suggest the importance of targeting related pathways to protect against disease and disability.
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Affiliation(s)
- Adam X Maihofer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.
- Veterans Affairs San Diego Healthcare System, Center of Excellence for Stress and Mental Health, San Diego, CA, USA.
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA.
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA.
| | - Andrew Ratanatharathorn
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Sian M J Hemmings
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, Western Cape, South Africa
- South African Medical Research Council/Genomics of Brain Disorders Research Unit, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Karen H Costenbader
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Vasiliki Michopoulos
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA
| | - Renato Polimanti
- VA Connecticut Healthcare Center, West Haven, CT, USA
- Department of Psychiatry, Yale University School of Medicine, New Haven, CT, USA
| | - Alex O Rothbaum
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA
- Department of Research and Outcomes, Skyland Trail, Atlanta, GA, USA
| | - Soraya Seedat
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, Western Cape, South Africa
- South African Medical Research Council/Genomics of Brain Disorders Research Unit, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Elizabeth A Mikita
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Veterans Affairs San Diego Healthcare System, Center of Excellence for Stress and Mental Health, San Diego, CA, USA
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
| | - Alicia K Smith
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA
- Department of Gynecology and Obstetrics, Emory University, Atlanta, GA, USA
| | - Rany M Salem
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Richard A Shaffer
- Department of Epidemiology and Health Sciences, Naval Health Research Center, San Diego, CA, USA
| | - Tianying Wu
- Division of Epidemiology and Biostatistics, School of Public Health, San Diego State University, San Diego, CA, USA
- Moores Cancer Center, University of California, San Diego, San Diego, CA, USA
| | - Jonathan Sebat
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
- Department of Cellular and Molecular Medicine, University of California San Diego, La Jolla, CA, USA
| | - Kerry J Ressler
- Department of Psychiatry and Behavioral Sciences, Emory University, Atlanta, GA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- McLean Hospital, Belmont, MA, USA
| | - Murray B Stein
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla, CA, USA
| | - Karestan C Koenen
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - Erika J Wolf
- VA Boston Healthcare System, National Center for PTSD, Boston, MA, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Jennifer A Sumner
- Department of Psychology, University of California Los Angeles, Los Angeles, CA, USA
| | - Caroline M Nievergelt
- Department of Psychiatry, University of California San Diego, La Jolla, CA, USA
- Veterans Affairs San Diego Healthcare System, Center of Excellence for Stress and Mental Health, San Diego, CA, USA
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
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8
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Wu O, Wu Y, Zhang X, Liu W, Zhang H, Khederzadeh S, Lu X, Zhu XW. Causal effect of interleukin (IL)-6 on blood pressure and hypertension: A mendelian randomization study. Immunogenetics 2024; 76:123-135. [PMID: 38427105 DOI: 10.1007/s00251-024-01332-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 01/11/2024] [Indexed: 03/02/2024]
Abstract
To examine whether circulating interleukin-6 (IL-6) levels (CirIL6) have a causal effect on blood pressure using Mendelian randomization (MR) methods. We used data from genome-wide association studies (GWAS) of European ancestry to obtain genetic instruments for circulating IL-6 levels and blood pressure measurements. We applied several robust MR methods to estimate the causal effects and to test for heterogeneity and pleiotropy. We found that circulating IL-6 had a significant positive causal effect on systolic blood pressure (SBP) and pulmonary arterial hypertension (PAH), but not on diastolic blood pressure (DBP) or hypertension. We found that as CirIL6 genetically increased, SBP increased using Inverse Variance Weighted (IVW) method (for ukb-b-20175, β = 0.082 with SE = 0.032, P = 0.011; for ukb-a-360, β = 0.075 with SE = 0.031, P = 0.014) and weighted median (WM) method (for ukb-b-20175, β = 0.061 with SE = 0.022, P = 0.006; for ukb-a-360, β = 0.065 with SE = 0.027, P = 0.014). Moreover, CirIL6 may be associated with an increased risk of PAH using WM method (odds ratio (OR) = 15.503, 95% CI, 1.025-234.525, P = 0.048), but not with IVW method. Our study provides novel evidence that circulating IL-6 has a causal role in the development of SBP and PAH, but not DBP or hypertension. These findings suggest that IL-6 may be a potential therapeutic target for preventing or treating cardiovascular diseases and metabolic disorders. However, more studies are needed to confirm the causal effects of IL-6 on blood pressure and to elucidate the underlying mechanisms and pathways.
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Affiliation(s)
- Ou Wu
- Shulan International Medical College, Zhejiang Shuren University, Hangzhou, Zhejiang, People's Republic of China.
- Zhejiang Chinese Medical University, Hangzhou, Zhejiang, People's Republic of China.
| | - Ya Wu
- Anhui Medical University, Hefei, Anhui, People's Republic of China
| | - Xingyu Zhang
- Thomas E. Starzl Transplantation Institute, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Wei Liu
- JFIntelligent Healthcare Technology Co., Ltd Building No.5-7, No.699 Tianxiang Avenue, Hi-Tech Zone, Nanchang, Jiangxi Province, People's Republic of China
| | - Hu Zhang
- Department of Thoracic Surgery, Sir Run Run Shaw Hospital Affiliated with Medical College of Zhejiang University, Hangzhou, Zhejiang, People's Republic of China
| | - Saber Khederzadeh
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, People's Republic of China
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, Zhejiang, People's Republic of China
| | - Xi Lu
- Hangzhou Vocational and Technical College, Hangzhou, Zhejiang, People's Republic of China.
| | - Xiao-Wei Zhu
- School of Medicine, Shaoxing University, Shaoxing, Zhejiang, People's Republic of China.
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9
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Lukas E, Veeneman RR, Smit DJA, Vermeulen JM, Pathak GA, Polimanti R, Verweij KJH, Treur JL. A genetic exploration of the relationship between Posttraumatic Stress Disorder and cardiovascular diseases. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.20.24304533. [PMID: 38562880 PMCID: PMC10984043 DOI: 10.1101/2024.03.20.24304533] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Background and Aims Experiencing a traumatic event may lead to Posttraumatic Stress Disorder (PTSD), including symptoms such as flashbacks and hyperarousal. Individuals suffering from PTSD are at increased risk of cardiovascular disease (CVD), but it is unclear why. This study assesses shared genetic liability and potential causal pathways between PTSD and CVD. Methods We leveraged summary-level data of genome-wide association studies (PTSD: N= 1,222,882; atrial fibrillation (AF): N=482,409; coronary artery disease (CAD): N=1,165,690; hypertension: N=458,554; heart failure (HF): N=977,323). First, we estimated genetic correlations and utilized genomic structural equation modeling to identify a common genetic factor for PTSD and CVD. Next, we assessed biological, behavioural, and psychosocial factors as potential mediators. Finally, we employed multivariable Mendelian randomization to examine causal pathways between PTSD and CVD, incorporating the same potential mediators. Results Significant genetic correlations were found between PTSD and CAD, HT, and HF (rg =0.21-0.32, p≤ 3.08 · 10-16), but not between PTSD and AF. Insomnia, smoking, alcohol dependence, waist-to-hip ratio, and inflammation (IL6, C-reactive protein) partly mediated these associations. Mendelian randomization indicated that PTSD causally increases CAD (IVW OR=1.53, 95% CIs=1.19-1.96, p=0.001), HF (OR=1.44, CIs=1.08-1.92, p=0.012), and to a lesser degree hypertension (OR=1.25, CIs=1.05-1.49, p=0.012). While insomnia, smoking, alcohol, and inflammation were important mediators, independent causal effects also remained. Conclusions In addition to shared genetic liability between PTSD and CVD, we present strong evidence for causal effects of PTSD on CVD. Crucially, we implicate specific lifestyle and biological mediators (insomnia, substance use, inflammation) which has important implications for interventions to prevent CVD in PTSD patients.
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Affiliation(s)
- Eva Lukas
- Genetic Epidemiology Group, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Rada R Veeneman
- Genetic Epidemiology Group, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Dirk JA Smit
- Genetic Epidemiology Group, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | | | - Jentien M Vermeulen
- Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Gita A Pathak
- Department of Psychiatry, Yale University School of Medicine, 60 Temple, Suite 7A, New Haven, CT, USA
- Veteran Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Renato Polimanti
- Department of Psychiatry, Yale University School of Medicine, 60 Temple, Suite 7A, New Haven, CT, USA
- Veteran Affairs Connecticut Healthcare System, West Haven, CT, USA
| | - Karin JH Verweij
- Genetic Epidemiology Group, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Jorien L Treur
- Genetic Epidemiology Group, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
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10
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Zhang T, Chen Y, Li X, Zhang J, Duan L. Genetic associations and potential mediators between psychiatric disorders and irritable bowel syndrome: a Mendelian randomization study with mediation analysis. Front Psychiatry 2024; 15:1279266. [PMID: 38352653 PMCID: PMC10861787 DOI: 10.3389/fpsyt.2024.1279266] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 01/15/2024] [Indexed: 02/16/2024] Open
Abstract
Objective Potential causal associations between psychiatric disorders and irritable bowel syndrome have been demonstrated in observational studies; however, these studies are susceptible to underlying confounding and reverse causation biases. We aimed to assess the causal effects of psychiatric disorders on irritable bowel syndrome (IBS) and the potential mediators from a genetic perspective by conducting a Mendelian randomization (MR) study with mediation analysis. Method Genetic instruments associated with psychiatric disorders, potential mediators, and IBS were obtained from large-scale genome-wide association studies (GWAS). Three MR methods - the inverse-variance weighted (IVW) method, MR-Egger method, and weighted median method, were used to investigate causal association estimates. Heterogeneity among different genetic instrumental variables (IVs) was assessed using Q tests. Additionally, the MR-PRESSO and MR-Pleiotropy methods were used to verify horizontal pleiotropy and detect outliers that might bias the results, which were removed from further analysis. Consequently, we used MR mediation analysis to investigate potential mediators in the causal associations between psychiatric disorders and IBS. Results MR provided evidence of the causal effects of genetically predicted broad depression, major depressive disorder (MDD), anxiety disorder, post-traumatic stress disorder (PTSD), and schizophrenia on IBS. The results of MR mediation analysis demonstrated that the reduction in acetate levels mediated 12.6% of the effects of broad depression on IBS; insomnia mediated 16.00%, 16.20%, and 27.14% of the effects of broad depression, MDD, and PTSD on IBS, respectively; and the increase in blood β-hydroxybutyrate levels mediated 50.76% of the effects of schizophrenia on IBS. Conclusion Our study confirmed the brain-gut axis involvement and potential modulators in the pathophysiology of psychiatric disorder-induced IBS from a genetic perspective, and suggests potential therapeutic targets for the disrupted brain-gut axis.
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Affiliation(s)
| | | | | | | | - Liping Duan
- Department of Gastroenterology, Peking University Third Hospital, Beijing, China
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11
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Bergstedt J, Pasman JA, Ma Z, Harder A, Yao S, Parker N, Treur JL, Smit DJA, Frei O, Shadrin A, Meijsen JJ, Shen Q, Hägg S, Tornvall P, Buil A, Werge T, Hjerling-Leffler J, Als TD, Børglum AD, Lewis CM, McIntosh AM, Valdimarsdóttir UA, Andreassen OA, Sullivan PF, Lu Y, Fang F. Distinct genomic signatures and modifiable risk factors underly the comorbidity between major depressive disorder and cardiovascular disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.09.01.23294931. [PMID: 37693619 PMCID: PMC10491387 DOI: 10.1101/2023.09.01.23294931] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/12/2023]
Abstract
Major depressive disorder (MDD) and cardiovascular disease (CVD) are often comorbid, resulting in excess morbidity and mortality. Using genomic data, this study elucidates biological mechanisms, key risk factors, and causal pathways underlying their comorbidity. We show that CVDs share a large proportion of their genetic risk factors with MDD. Multivariate genome-wide association analysis of the shared genetic liability between MDD and atherosclerotic CVD (ASCVD) revealed seven novel loci and distinct patterns of tissue and brain cell-type enrichments, suggesting a role for the thalamus. Part of the genetic overlap was explained by shared inflammatory, metabolic, and psychosocial/lifestyle risk factors. Finally, we found support for causal effects of genetic liability to MDD on CVD risk, but not from most CVDs to MDD, and demonstrated that the causal effects were partly explained by metabolic and psychosocial/lifestyle factors. The distinct signature of MDD-ASCVD comorbidity aligns with the idea of an immunometabolic sub-type of MDD more strongly associated with CVD than overall MDD. In summary, we identify plausible biological mechanisms underlying MDD-CVD comorbidity, as well as key modifiable risk factors for prevention of CVD in individuals with MDD.
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Affiliation(s)
- Jacob Bergstedt
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Joëlle A Pasman
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ziyan Ma
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Arvid Harder
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Shuyang Yao
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department Medical Biochemistry and Biophysics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Nadine Parker
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Jorien L Treur
- Genetic Epidemiology, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Dirk J A Smit
- Genetic Epidemiology, Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | - Oleksandr Frei
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Alexey Shadrin
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Joeri J Meijsen
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
| | - Qing Shen
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Clinical Research Center for Mental Disorders, Shanghai Pudong New Area Mental Health Center, Tongji University School of Medicine, Shanghai, China
- Institute for Advanced Study, Tongji University, Shanghai, China
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Per Tornvall
- Department of Clinical Science and Education Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
| | - Alfonso Buil
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
| | - Thomas Werge
- Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Copenhagen, Roskilde, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Copenhagen, Denmark
- Lundbeck Foundation GeoGenetics Centre, GLOBE Institute, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jens Hjerling-Leffler
- Department Medical Biochemistry and Biophysics, Karolinska Institutet, 171 77 Stockholm, Sweden
| | - Thomas D Als
- Department of Molecular Medicine (MOMA), Molecular Diagnostic Laboratory, Aarhus University Hospital, Aarhus, Denmark
| | - Anders D Børglum
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, Aarhus, Denmark
- Center for Genomics and Personalized Medicine, Aarhus, Denmark
| | - Cathryn M Lewis
- Social, Genetic and Developmental Psychiatry Centre, King's College London, London, UK
- Department of Medical and Molecular Genetics, King's College London, London, UK
| | - Andrew M McIntosh
- Centre for Clinical Brain Sciences, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Centre for Genomics and Experimental Medicine, University of Edinburgh, Edinburgh, UK
| | - Unnur A Valdimarsdóttir
- Centre of Public Health Sciences, Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Epidemiology, Harvard TH Chan School of Public Health, Harvard University, Boston, Massachusetts, USA
| | - Ole A Andreassen
- NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
- K.G. Jebsen Centre for Neurodevelopmental disorders, University of Oslo and Oslo University Hospital, Oslo, Norway
| | - Patrick F Sullivan
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Departments of Genetics and Psychiatry, University of North Carolina at Chapel Hill, NC, USA
| | - Yi Lu
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Fang Fang
- Unit of Integrative Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
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12
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So HC, Xue X, Ma Z, Sham PC. SumVg: Total Heritability Explained by All Variants in Genome-Wide Association Studies Based on Summary Statistics with Standard Error Estimates. Int J Mol Sci 2024; 25:1347. [PMID: 38279346 PMCID: PMC10816209 DOI: 10.3390/ijms25021347] [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: 10/13/2023] [Revised: 01/15/2024] [Accepted: 01/16/2024] [Indexed: 01/28/2024] Open
Abstract
Genome-wide association studies (GWAS) are commonly employed to study the genetic basis of complex traits/diseases, and a key question is how much heritability could be explained by all single nucleotide polymorphisms (SNPs) in GWAS. One widely used approach that relies on summary statistics only is linkage disequilibrium score regression (LDSC); however, this approach requires certain assumptions about the effects of SNPs (e.g., all SNPs contribute to heritability and each SNP contributes equal variance). More flexible modeling methods may be useful. We previously developed an approach recovering the "true" effect sizes from a set of observed z-statistics with an empirical Bayes approach, using only summary statistics. However, methods for standard error (SE) estimation are not available yet, limiting the interpretation of our results and the applicability of the approach. In this study, we developed several resampling-based approaches to estimate the SE of SNP-based heritability, including two jackknife and three parametric bootstrap methods. The resampling procedures are performed at the SNP level as it is most common to estimate heritability from GWAS summary statistics alone. Simulations showed that the delete-d-jackknife and parametric bootstrap approaches provide good estimates of the SE. In particular, the parametric bootstrap approaches yield the lowest root-mean-squared-error (RMSE) of the true SE. We also explored various methods for constructing confidence intervals (CIs). In addition, we applied our method to estimate the SNP-based heritability of 12 immune-related traits (levels of cytokines and growth factors) to shed light on their genetic architecture. We also implemented the methods to compute the sum of heritability explained and the corresponding SE in an R package SumVg. In conclusion, SumVg may provide a useful alternative tool for calculating SNP heritability and estimating SE/CI, which does not rely on distributional assumptions of SNP effects.
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Affiliation(s)
- Hon-Cheong So
- School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong, China; (X.X.); (Z.M.)
- KIZ-CUHK Joint Laboratory of Bioresources and Molecular Research of Common Diseases, Kunming Institute of Zoology and The Chinese University of Hong Kong, Shatin, Hong Kong, China
- Department of Psychiatry, The Chinese University of Hong Kong, Shatin, Hong Kong, China
- CUHK Shenzhen Research Institute, Shenzhen 518057, China
- Margaret K. L. Cheung Research Centre for Management of Parkinsonism, The Chinese University of Hong Kong, Shatin, Hong Kong, China
- Hong Kong Branch of the Chinese Academy of Sciences Center for Excellence in Animal Evolution and Genetics, The Chinese University of Hong Kong, Shatin, Hong Kong, China
- Brain and Mind Institute, The Chinese University of Hong Kong, Shatin, Hong Kong, China
| | - Xiao Xue
- School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong, China; (X.X.); (Z.M.)
| | - Zhijie Ma
- School of Biomedical Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong, China; (X.X.); (Z.M.)
| | - Pak-Chung Sham
- Department of Psychiatry, The University of Hong Kong, Pokfulam, Hong Kong, China;
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13
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Jiang MZ, Gaynor SM, Li X, Van Buren E, Stilp A, Buth E, Wang FF, Manansala R, Gogarten SM, Li Z, Polfus LM, Salimi S, Bis JC, Pankratz N, Yanek LR, Durda P, Tracy RP, Rich SS, Rotter JI, Mitchell BD, Lewis JP, Psaty BM, Pratte KA, Silverman EK, Kaplan RC, Avery C, North K, Mathias RA, Faraday N, Lin H, Wang B, Carson AP, Norwood AF, Gibbs RA, Kooperberg C, Lundin J, Peters U, Dupuis J, Hou L, Fornage M, Benjamin EJ, Reiner AP, Bowler RP, Lin X, Auer PL, Raffield LM. Whole Genome Sequencing Based Analysis of Inflammation Biomarkers in the Trans-Omics for Precision Medicine (TOPMed) Consortium. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.09.10.555215. [PMID: 37745480 PMCID: PMC10515765 DOI: 10.1101/2023.09.10.555215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/26/2023]
Abstract
Inflammation biomarkers can provide valuable insight into the role of inflammatory processes in many diseases and conditions. Sequencing based analyses of such biomarkers can also serve as an exemplar of the genetic architecture of quantitative traits. To evaluate the biological insight, which can be provided by a multi-ancestry, whole-genome based association study, we performed a comprehensive analysis of 21 inflammation biomarkers from up to 38,465 individuals with whole-genome sequencing from the Trans-Omics for Precision Medicine (TOPMed) program. We identified 22 distinct single-variant associations across 6 traits - E-selectin, intercellular adhesion molecule 1, interleukin-6, lipoprotein-associated phospholipase A2 activity and mass, and P-selectin - that remained significant after conditioning on previously identified associations for these inflammatory biomarkers. We further expanded upon known biomarker associations by pairing the single-variant analysis with a rare variant set-based analysis that further identified 19 significant rare variant set-based associations with 5 traits. These signals were distinct from both significant single variant association signals within TOPMed and genetic signals observed in prior studies, demonstrating the complementary value of performing both single and rare variant analyses when analyzing quantitative traits. We also confirm several previously reported signals from semi-quantitative proteomics platforms. Many of these signals demonstrate the extensive allelic heterogeneity and ancestry-differentiated variant-trait associations common for inflammation biomarkers, a characteristic we hypothesize will be increasingly observed with well-powered, large-scale analyses of complex traits.
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Affiliation(s)
- Min-Zhi Jiang
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA
| | - Sheila M. Gaynor
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA
- Regeneron Genetics Center, Tarrytown, NY, 10591, USA
| | - Xihao Li
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Eric Van Buren
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA
| | - Adrienne Stilp
- Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA
| | - Erin Buth
- Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA
| | - Fei Fei Wang
- Department of Biostatistics, University of Washington, Seattle, WA, 98105, USA
| | - Regina Manansala
- Centre for Health Economics Research & Modelling Infectious Diseases (CHERMID), Vaccine & Infectious Disease Institute (VAXINFECTIO) WHO Collaborating Centre, University of Antwerp, Antwerp, BE
| | | | - Zilin Li
- School of Mathematics and Statistics, Northeast Normal University, Changchun, Jilin, 130024, China
| | - Linda M. Polfus
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, 90033, USA
| | - Shabnam Salimi
- Department of Epidemiology and Public Health, Division of Gerontology, University of Maryland School of Medicine, Baltimore, MD, 21201, USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 4333 Brooklyn Ave NE, Box 359458, Seattle, WA, 98195, USA
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, 55455, USA
| | - Lisa R. Yanek
- Department of Medicine, General Internal Medicine, Johns Hopkins University School of Medicine, 1830 E Monument St Rm 8024, Baltimore, MD, 21287, USA
| | - Peter Durda
- Department of Pathology & Laboratory Medicine, University of Vermont Larner College of Medicine, 360 South Park Drive, Colchester, VT, 05446, USA
| | - Russell P. Tracy
- Department of Pathology & Laboratory Medicine, University of Vermont Larner College of Medicine, 360 South Park Drive, Colchester, VT, 05446, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, 200 Jeanette Lancaster Way, Charlottesville, VA, 22903, USA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, 1124 W. Carson Street, Torrance, CA, 90502, USA
| | - Braxton D. Mitchell
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, 670 W. Baltimore St., Baltimore, MD, 21201, USA
| | - Joshua P. Lewis
- Department of Medicine, Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, 670 W. Baltimore St., Baltimore, MD, 21201, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, 4333 Brooklyn Ave NE, Box 359458, Seattle, WA, 98195, USA
- Departments of Epidemiology and Health Systems and Population Health, University of Washington, 4333 Brooklyn Ave NE, Seattle, WA, 98101, USA
| | - Katherine A. Pratte
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, Denver, CO, 80206, USA
| | - Edwin K. Silverman
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women’s Hospital, 181 Longwood Avenue, Boston, MA, 02115, USA
| | - Robert C. Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Christy Avery
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Kari North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Rasika A. Mathias
- Department of Medicine, Allergy and Clinical Immunology, Johns Hopkins University School of Medicine, 5501 Hopkins Bayview Cir JHAAC Room 3B53, Baltimore, MD, 21287, USA
| | - Nauder Faraday
- Department of Anesthesiology and Critical Care Medicine, Johns Hopkins University School of Medicine, 600 N Wolfe St, Baltimore, MD, 21287, USA
| | - Honghuang Lin
- Department of Medicine, University of Massachusetts Chan Medical School, 55 Lake Ave North, Worcester, MA, 01655, USA
| | - Biqi Wang
- Department of Medicine, University of Massachusetts Chan Medical School, 55 Lake Ave North, Worcester, MA, 01655, USA
| | - April P. Carson
- Department of Medicine, University of Mississippi Medical Center, 350 W. Woodrow Wilson Avenue, Suite 701, Jackson, MS, 39213, USA
| | - Arnita F. Norwood
- Department of Medicine, University of Mississippi Medical Center, 350 W. Woodrow Wilson Avenue, Suite 701, Jackson, MS, 39213, USA
| | - Richard A. Gibbs
- Department of Molecular and Human Genetics, Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Jessica Lundin
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Josée Dupuis
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, Québec, H3A 1G1, Canada
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Emelia J. Benjamin
- Department of Medicine, Cardiovascular Medicine, Boston Medical Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, 02118, USA
- Boston University and National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, 01702, USA
| | - Alexander P. Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, 98105, USA
| | - Russell P. Bowler
- Department of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, National Jewish Health, Denver, CO, 80206, USA
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, 655 Huntington Avenue, Boston, MA, 02115, USA
| | - Paul L. Auer
- Division of Biostatistics, Institute for Health and Equity, and Cancer Center, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Laura M. Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA
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Crick DCP, Sanderson E, Jones H, Goulding N, Borges MC, Clayton G, Carter AR, Halligan S, Lawlor DA, Khandaker GM, Fraser A. Glycoprotein acetyls and depression: Testing for directionality and potential causality using longitudinal data and Mendelian randomization analyses. J Affect Disord 2023; 335:431-439. [PMID: 37196932 PMCID: PMC7615476 DOI: 10.1016/j.jad.2023.05.033] [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: 02/01/2023] [Revised: 05/05/2023] [Accepted: 05/11/2023] [Indexed: 05/19/2023]
Abstract
BACKGROUND Inflammation is associated with depression, but causality remains unclear. We investigated potential causality and direction of effect between inflammation and depression. METHODS Using data from the ALSPAC birth cohort (n = 4021; 42.18 % male), we used multivariable regression to investigate bidirectional longitudinal associations of GlycA and depression and depression symptoms, assessed at ages 18y and 24y. We used two-sample Mendelian randomization (MR) to investigate potential causality and directionality. Genetic variants for GlycA were obtained from UK Biobank (UKB) (N = 115,078); for depression from the Psychiatric Genomics Consortium and UKB (N = 500,199); and for depressive symptoms (N = 161,460) from the Social Science Genetic Association Consortium. In addition to the Inverse Variance Weighted method, we used sensitivity analyses to strengthen causal inference. We conducted multivariable MR adjusting for body mass index (BMI) due to known genetic correlation between inflammation, depression and BMI. RESULTS In the cohort analysis, after adjusting for potential confounders we found no evidence of associations between GlycA and depression symptoms score or vice versa. We observed an association between GlycA and depression (OR = 1∙18, 95 % CI: 1∙03-1∙36). MR suggested no causal effect of GlycA on depression, but there was a causal effect of depression on GlycA (mean difference in GlycA = 0∙09; 95 % CI: 0∙03-0∙16), which was maintained in some, but not all, sensitivity analyses. LIMITATIONS The GWAS sample overlap could incur bias. CONCLUSION We found no consistent evidence for an effect of GlycA on depression. There was evidence that depression increases GlycA in the MR analysis, but this may be confounded/mediated by BMI.
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Affiliation(s)
- Daisy C P Crick
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
| | - Eleanor Sanderson
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Hannah Jones
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Neil Goulding
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Maria Carolina Borges
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Gemma Clayton
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Alice R Carter
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Sarah Halligan
- Department of Psychology, University of Bath, Bath, UK; Department of Psychiatry and Mental Health, University of Cape Town, South Africa
| | - Deborah A Lawlor
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Golam M Khandaker
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK; NIHR Bristol Biomedical Research Centre, Bristol, UK; Avon and Wiltshire Mental Health Partnership NHS Trust, Bristol, UK
| | - Abigail Fraser
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
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15
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Casu A, Nunez Lopez YO, Yu G, Clifford C, Bilal A, Petrilli AM, Cornnell H, Carnero EA, Bhatheja A, Corbin KD, Iliuk A, Maahs DM, Pratley RE. The proteome and phosphoproteome of circulating extracellular vesicle-enriched preparations are associated with characteristic clinical features in type 1 diabetes. Front Endocrinol (Lausanne) 2023; 14:1219293. [PMID: 37576973 PMCID: PMC10417723 DOI: 10.3389/fendo.2023.1219293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/08/2023] [Accepted: 07/06/2023] [Indexed: 08/15/2023] Open
Abstract
Introduction There are no validated clinical or laboratory biomarkers to identify and differentiate endotypes of type 1 diabetes (T1D) or the risk of progression to chronic complications. Extracellular vesicles (EVs) have been studied as biomarkers in several different disease states but have not been well studied in T1D. Methods As the initial step towards circulating biomarker identification in T1D, this pilot study aimed to provide an initial characterization of the proteomic and phosphoproteomic landscape of circulating EV-enriched preparations in participants with established T1D (N=10) and healthy normal volunteers (Controls) (N=7) (NCT03379792) carefully matched by age, race/ethnicity, sex, and BMI. EV-enriched preparations were obtained using EVtrap® technology. Proteins were identified and quantified by LC-MS analysis. Differential abundance and coexpression network (WGCNA), and pathway enrichment analyses were implemented. Results The detected proteins and phosphoproteins were enriched (75%) in exosomal proteins cataloged in the ExoCarta database. A total of 181 proteins and 8 phosphoproteins were differentially abundant in participants with T1D compared to controls, including some well-known EVproteins (i.e., CD63, RAB14, BSG, LAMP2, and EZR). Enrichment analyses of differentially abundant proteins and phosphoproteins of EV-enriched preparations identified associations with neutrophil, platelet, and immune response functions, as well as prion protein aggregation. Downregulated proteins were involved in MHC class II signaling and the regulation of monocyte differentiation. Potential key roles in T1D for C1q, plasminogen, IL6ST, CD40, HLA-DQB1, HLA-DRB1, CD74, NUCB1, and SAP, are highlighted. Remarkably, WGCNA uncovered two protein modules significantly associated with pancreas size, which may be implicated in the pathogenesis of T1D. Similarly, these modules showed significant enrichment for membrane compartments, processes associated with inflammation and the immune response, and regulation of viral processes, among others. Discussion This study demonstrates the potential of proteomic and phosphoproteomic signatures of EV-enriched preparations to provide insight into the pathobiology of T1D. The WGCNA analysis could be a powerful tool to discriminate signatures associated with different pathobiological components of the disease.
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Affiliation(s)
- Anna Casu
- AdventHealth, Translational Research Institute (TRI), Orlando, FL, United States
| | - Yury O. Nunez Lopez
- AdventHealth, Translational Research Institute (TRI), Orlando, FL, United States
| | - Gongxin Yu
- AdventHealth, Translational Research Institute (TRI), Orlando, FL, United States
| | - Christopher Clifford
- AdventHealth, Translational Research Institute (TRI), Orlando, FL, United States
| | - Anika Bilal
- AdventHealth, Translational Research Institute (TRI), Orlando, FL, United States
| | | | - Heather Cornnell
- AdventHealth, Translational Research Institute (TRI), Orlando, FL, United States
| | | | - Ananya Bhatheja
- AdventHealth, Translational Research Institute (TRI), Orlando, FL, United States
| | - Karen D. Corbin
- AdventHealth, Translational Research Institute (TRI), Orlando, FL, United States
| | - Anton Iliuk
- Biomarker Discovery Department, Tymora Analytical Operations, West Lafayette, IN, United States
| | - David M. Maahs
- Department of Pediatrics, Stanford University School of Medicine, Stanford, CA, United States
| | - Richard E. Pratley
- AdventHealth, Translational Research Institute (TRI), Orlando, FL, United States
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16
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Li W, Lu Q, Qian J, Feng Y, Luo J, Luo C, He W, Dong B, Liu H, Liu Z, Su C. Assessing the causal relationship between genetically determined inflammatory biomarkers and low back pain risk: a bidirectional two-sample Mendelian randomization study. Front Immunol 2023; 14:1174656. [PMID: 37520547 PMCID: PMC10372790 DOI: 10.3389/fimmu.2023.1174656] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 06/27/2023] [Indexed: 08/01/2023] Open
Abstract
Background Observational studies have suggested an association between inflammatory markers and low back pain (LBP), but the causal relationship between these factors remains uncertain. Methods We conducted a bidirectional two-sample Mendelian randomization analysis (MR) study to investigate whether there is a causal relationship between inflammatory markers and low back pain. We obtained genetic data for CRP, along with its upstream inflammatory markers IL-6, IL-8, and IL-10, as well as low back pain from publicly available genome-wide association studies (GWAS). We applied several MR methods, including inverse variance weighting, weighted median, MR-Egger, Wald Ratio, and MR-PRESSO, to test for causal relationships. Sensitivity analyses were also conducted to assess the robustness of the results. Results Our analyses utilizing the Inverse Variance Weighted (IVW) method, the MR-Egger method, and the weighted median method indicated that IL-6 may be associated with an increased risk of LBP (Effect Size: -0.009, 95% Confidence Interval: -0.013-0.006, p = 9.16e-08); however, in the reverse direction, there was no significant causal effect of LBP on inflammatory markers. Conclusion Our study used a Mendelian randomization approach and found that elevated IL-6 levels may reduce the risk of LBP.
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Affiliation(s)
- Wenhan Li
- Tui-Na Department, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Qunwen Lu
- Tui-Na Department, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Junhui Qian
- Tui-Na Department, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
- Department of Acupuncture, Moxibustion, Tui-Na and Rehabilitation, Guang'an City Hospital of Traditional Chinese Medicine, Guangan, Sichuan, China
| | - Yue Feng
- Tui-Na Teaching and Research Department, College of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
- Tui-Na Department, Meishan City Hospital of Traditional Chinese Medicine, Meishan, Sichuan, China
| | - Jian Luo
- Tui-Na Department, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Caigui Luo
- Tui-Na Department, Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
| | - Wenshan He
- Rehabilitation Department, School of Clinic Medicine & The First Affiliated Hospital of Chengdu Medical College, Chengdu, Sichuan, China
| | - Bing Dong
- Chinese Medicine Rehabilitation Department, Jiahekang Hospital, Luzhou, Sichuan, China
| | - Huahui Liu
- Department of Acupuncture, Moxibustion, Tui-Na and Rehabilitation, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, Sichuan, China
| | - Zhongxing Liu
- Center for Traditional Chinese Medicine Prevention and Health Care, Chengdu Integrated TCM & Western Medicine Hospital, Chengdu, Sichuan, China
| | - Chengguo Su
- Tui-Na Teaching and Research Department, College of Acupuncture and Tuina, Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan, China
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Zhong Q, Yao C, Zhong W. Causal Relationship Between Inflammation and Preeclampsia: Genetic Evidence from a Mendelian Randomization Study. Twin Res Hum Genet 2023; 26:231-235. [PMID: 37458219 DOI: 10.1017/thg.2023.27] [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] [Indexed: 09/14/2023]
Abstract
Preeclampsia (PE) is a hypertensive disorder of pregnancy. PE patients were reported to have higher serum levels of C-reactive protein (CRP), interleukin-6 (IL-6) and tumor necrosis factor α (TNF-α) than those in healthy controls. However, whether the expressions of these inflammation biomarkers have a causal relationship with PE is unspecified. We applied the Mendelian randomization method to infer the causal relationship between inflammation biomarkers (e.g., CRP, IL-6, interleukin 1 receptor antagonist [IL-1ra] and TNF-α) and PE. Single nucleotide polymorphisms (SNPs) strongly related to inflammation biomarkers were used as instrumental variables. CRP, IL-1ra and IL-6 levels showed no significant effect on PE progression, while the genetic predicted higher level of TNF-α significantly increased the risk of PE (OR per 1-SD increase in TNF-α: 4.33; 95% CI [1.99, 9.39]; p = .00021). The findings suggest that pro-inflammatory activity of TNF-α could be a determinant for PE progression. More antenatal care should be given to those pregnant women with higher level of inflammation biomarkers, especially TNF-α.
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Affiliation(s)
- Qiongxiang Zhong
- No.2 Obstetrics and Gynecology Department, Hunan Provincial People's Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, China
| | - Chanjiao Yao
- No.2 Obstetrics and Gynecology Department, Hunan Provincial People's Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, China
| | - Wei Zhong
- No.2 Obstetrics and Gynecology Department, Hunan Provincial People's Hospital (The First Affiliated Hospital of Hunan Normal University), Changsha, China
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18
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Slaney C, Sallis HM, Jones HJ, Dardani C, Tilling K, Munafò MR, Davey Smith G, Mahedy L, Khandaker GM. Association between inflammation and cognition: Triangulation of evidence using a population-based cohort and Mendelian randomization analyses. Brain Behav Immun 2023; 110:30-42. [PMID: 36791891 PMCID: PMC10728829 DOI: 10.1016/j.bbi.2023.02.010] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 01/23/2023] [Accepted: 02/10/2023] [Indexed: 02/15/2023] Open
Abstract
BACKGROUND Inflammation is associated with cognitive functioning and dementia in older adults, but whether inflammation is related to cognitive functioning in youth and whether these associations are causal remains unclear. METHODS In a population-based cohort (Avon Longitudinal Study of Parents and Children; ALSPAC), we investigated cross-sectional associations of inflammatory markers (C-reactive protein [CRP], Interleukin-6 [IL-6] and Glycoprotein acetyls [GlycA]) with measures of cold (working memory, response inhibition) and hot (emotion recognition) cognition at age 24 (N = 3,305 in multiple imputation models). Furthermore, we conducted one-sample and two-sample bidirectional Mendelian randomization (MR) analyses to examine potential causal effects of genetically-proxied inflammatory markers (CRP, GlycA, IL-6, IL-6 receptor, soluble IL-6 receptor) on cognitive measures (above) and on general cognitive ability. RESULTS In the ALSPAC cohort, there was limited evidence of an association between standardised inflammatory markers and standardised cognitive measures at age 24 after adjusting for potential confounders (N = 3,305; beta range, -0.02 [95 % confidence interval (CI) -0.06 to 0.02, p = 0.27] to 0.02 [95 % CI -0.02 to 0.05, p = 0.33]). Similarly, we found limited evidence of potential effects of 1-unit increase in genetically-proxied inflammatory markers on standardised working memory, emotion recognition or response inhibition in one-sample MR using ALSPAC data (beta range, -0.73 [95 % CI -2.47 to 1.01, p = 0.41] to 0.21 [95 % CI -1.42 to 1.84, p = 0.80]; or on standardised general cognitive ability in two-sample MR using the latest Genome-Wide Association Study (GWAS) datasets (inverse-variance weighted beta range, -0.02 [95 % CI -0.05 to 0.01, p = 0.12] to 0.03 [95 % CI -0.01 to 0.07, p = 0.19]). CONCLUSIONS Our MR findings do not provide strong evidence of a potential causal effect of inflammatory markers (CRP, IL-6, IL-6 receptor, GlycA) on the cognitive functions examined here. Given the large confidence intervals in the one-sample MR, larger GWAS of specific cognitive measures are needed to enable well-powered MR analyses to investigate whether inflammation causally influences specific cognitive domains.
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Affiliation(s)
- Chloe Slaney
- MRC Integrative Epidemiology Unit at the University of Bristol, UK; School of Psychological Science, University of Bristol, 12a Priory Road, Bristol, UK; Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, UK.
| | - Hannah M Sallis
- MRC Integrative Epidemiology Unit at the University of Bristol, UK; School of Psychological Science, University of Bristol, 12a Priory Road, Bristol, UK; Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Hannah J Jones
- MRC Integrative Epidemiology Unit at the University of Bristol, UK; Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, UK; National Institute for Health Research Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, UK
| | - Christina Dardani
- Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Kate Tilling
- MRC Integrative Epidemiology Unit at the University of Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Marcus R Munafò
- MRC Integrative Epidemiology Unit at the University of Bristol, UK; School of Psychological Science, University of Bristol, 12a Priory Road, Bristol, UK; National Institute for Health Research Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; National Institute for Health Research Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, UK
| | - Liam Mahedy
- MRC Integrative Epidemiology Unit at the University of Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; National Institute for Health Research Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, UK
| | - Golam M Khandaker
- MRC Integrative Epidemiology Unit at the University of Bristol, UK; Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; National Institute for Health Research Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, UK
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19
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Zuo C, Zhuang Z, Yang P, Zhang H, Li X, Huang T, Ahluwalia TS. Dissecting the causal association between inflammation and post-traumatic stress disorder: A bidirectional Mendelian randomization study. J Affect Disord 2023; 333:436-445. [PMID: 37086801 DOI: 10.1016/j.jad.2023.04.080] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 04/14/2023] [Accepted: 04/17/2023] [Indexed: 04/24/2023]
Abstract
BACKGROUND Accumulating evidence showed a bidirectional association between post-traumatic stress disorder and inflammation. However, whether the association is causal remains unclear. We aimed to evaluate the causal relationships between inflammatory cytokines and post-traumatic stress disorder using two-sample bi-directional Mendelian randomization analysis. METHODS Single nucleotide polymorphism from genome-wide association studies of inflammatory cytokines, C-reactive protein, and post-traumatic stress disorder (23,212 patients and 151,447 controls) was selected as instrumental variables. The causal associations were estimated by inverse variance weighting with sensitivity analyses using weighted median, MR-Egger, and MR-PRESSO methods. RESULTS We observed suggestive associations of genetically predicted interleukin-17 (IL-17) and RANTES with post-traumatic stress disorder. One standard deviation (SD) increase in genetically predicted level of IL-17 lowered the risk of post-traumatic stress disorder with an odds ratio (OR) of 0.902 (95 % CI = 0.828, 0.984, P = 0.02). One SD higher genetically predicted RANTES (CCL5) concentration increased post-traumatic stress disorder risk (OR = 1.067, 95 % CI = 1.005, 1.133, P = 0.032). However, we found no evidence of causal associations of post-traumatic stress disorder with the selected inflammatory cytokines and biomarkers. We observed no evidence supporting the presence of pleiotropy. The results of sensitivity analyses demonstrated the same directions and similar effect sizes as the primary findings. LIMITATIONS Potential pleiotropy, possible weak instruments, and low statistical power limited our findings. CONCLUSION Inflammation was suggestively causally associated with the risk of post-traumatic stress disorder, and inflammatory cytokines had no downstream effect on post-traumatic stress disorder. Further studies are needed to explain the mechanisms of systemic inflammation and neuroinflammation in post-traumatic stress disorder.
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Affiliation(s)
- Chuanlong Zuo
- School of Nursing, Peking University, Beijing 100191, China.
| | - Zhenhuang Zhuang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 100191 Beijing, China.
| | - Ping Yang
- School of Nursing, Peking University, Beijing 100191, China.
| | - Hua Zhang
- Research Center of Clinical Epidemiology, Peking University Third Hospital, 100191 Beijing, China
| | - Xiangping Li
- School of Nursing, Peking University, Beijing 100191, China.
| | - Tao Huang
- Department of Epidemiology & Biostatistics, School of Public Health, Peking University, 100191 Beijing, China; Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, 100191 Beijing, China; Center for Intelligent Public Health, Academy for Artificial Intelligence, Peking University, 100191 Beijing, China.
| | - Tarunveer S Ahluwalia
- Steno Diabetes Center Copenhagen, Gentofte DK2820, Denmark; Department of Biology, The Bioinformatics Center, University of Copenhagen, Copenhagen DK2200, Denmark.
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20
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Scaramuzzo G, Nucera F, Asmundo A, Messina R, Mari M, Montanaro F, Johansen MD, Monaco F, Fadda G, Tuccari G, Hansbro NG, Hansbro PM, Hansel TT, Adcock IM, David A, Kirkham P, Caramori G, Volta CA, Spadaro S. Cellular and molecular features of COVID-19 associated ARDS: therapeutic relevance. J Inflamm (Lond) 2023; 20:11. [PMID: 36941580 PMCID: PMC10027286 DOI: 10.1186/s12950-023-00333-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Accepted: 02/08/2023] [Indexed: 03/23/2023] Open
Abstract
The severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection can be asymptomatic or cause a disease (COVID-19) characterized by different levels of severity. The main cause of severe COVID-19 and death is represented by acute (or acute on chronic) respiratory failure and acute respiratory distress syndrome (ARDS), often requiring hospital admission and ventilator support.The molecular pathogenesis of COVID-19-related ARDS (by now termed c-ARDS) is still poorly understood. In this review we will discuss the genetic susceptibility to COVID-19, the pathogenesis and the local and systemic biomarkers correlated with c-ARDS and the therapeutic options that target the cell signalling pathways of c-ARDS.
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Affiliation(s)
- Gaetano Scaramuzzo
- Department of Translational Medicine, University of Ferrara, Ferrara, Italy
- Department of Emergency, Section of Intensive Care and Anesthesia, Azienda Ospedaliera-Universitaria Sant'Anna, Ferrara, Italy
| | - Francesco Nucera
- Pneumologia, Dipartimento di Scienze Biomediche, Odontoiatriche e delle Immagini Morfologiche e Funzionali (BIOMORF), Università di Messina, Messina, Italy
| | - Alessio Asmundo
- Medicina Legale, Dipartimento di Scienze Biomediche, Odontoiatriche e delle Immagini Morfologiche e Funzionali (BIOMORF), Università di Messina, Messina, Italy
| | - Roberto Messina
- Intensive Care Unit, Dipartimento di Patologia Umana e dell'Età Evolutiva Gaetano Barresi, Università di Messina, Messina, Italy
| | - Matilde Mari
- Department of Translational Medicine, University of Ferrara, Ferrara, Italy
- Department of Emergency, Section of Intensive Care and Anesthesia, Azienda Ospedaliera-Universitaria Sant'Anna, Ferrara, Italy
| | - Federica Montanaro
- Department of Translational Medicine, University of Ferrara, Ferrara, Italy
- Department of Emergency, Section of Intensive Care and Anesthesia, Azienda Ospedaliera-Universitaria Sant'Anna, Ferrara, Italy
| | - Matt D Johansen
- Centre for Inflammation, School of Life Sciences, Faculty of Science, Centenary Institute and University of Technology Sydney, Sydney, NSW, Australia
| | - Francesco Monaco
- Chirurgia Toracica, Dipartimento di Scienze Biomediche, Odontoiatriche e delle Immagini Morfologiche e Funzionali (BIOMORF), Università di Messina, Messina, Italy
| | - Guido Fadda
- Section of Pathological Anatomy, Department of Human Pathology of Adult and Developmental Age "Gaetano Barresi", University of Messina, Messina, Italy
| | - Giovanni Tuccari
- Section of Pathological Anatomy, Department of Human Pathology of Adult and Developmental Age "Gaetano Barresi", University of Messina, Messina, Italy
| | - Nicole G Hansbro
- Centre for Inflammation, School of Life Sciences, Faculty of Science, Centenary Institute and University of Technology Sydney, Sydney, NSW, Australia
| | - Philip M Hansbro
- Centre for Inflammation, School of Life Sciences, Faculty of Science, Centenary Institute and University of Technology Sydney, Sydney, NSW, Australia
| | - Trevor T Hansel
- Medical Research Council and Asthma, UK Centre in Allergic Mechanisms of Asthma, London, UK
| | - Ian M Adcock
- Airway Disease Section, National Heart and Lung Institute, Imperial College London, London, UK
| | - Antonio David
- Intensive Care Unit, Dipartimento di Patologia Umana e dell'Età Evolutiva Gaetano Barresi, Università di Messina, Messina, Italy
| | - Paul Kirkham
- Department of Biomedical Sciences, Faculty of Sciences and Engineering, University of Wolverhampton, West Midlands, Wolverhampton, UK
| | - Gaetano Caramori
- Pneumologia, Dipartimento di Scienze Biomediche, Odontoiatriche e delle Immagini Morfologiche e Funzionali (BIOMORF), Università di Messina, Messina, Italy.
| | - Carlo Alberto Volta
- Department of Translational Medicine, University of Ferrara, Ferrara, Italy
- Department of Emergency, Section of Intensive Care and Anesthesia, Azienda Ospedaliera-Universitaria Sant'Anna, Ferrara, Italy
| | - Savino Spadaro
- Department of Translational Medicine, University of Ferrara, Ferrara, Italy
- Department of Emergency, Section of Intensive Care and Anesthesia, Azienda Ospedaliera-Universitaria Sant'Anna, Ferrara, Italy
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21
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Kruk D, Yeung ACY, Faiz A, ten Hacken NHT, Timens W, van Kuppevelt TH, Daamen W, Hof D, Harmsen MC, Rojas M, Heijink IH. Gene expression profiles in mesenchymal stromal cells from bone marrow, adipose tissue and lung tissue of COPD patients and controls. Respir Res 2023; 24:22. [PMID: 36681830 PMCID: PMC9863276 DOI: 10.1186/s12931-023-02314-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Accepted: 01/03/2023] [Indexed: 01/23/2023] Open
Abstract
BACKGROUND Chronic obstructive pulmonary disease (COPD) is characterized by irreversible lung tissue damage. Novel regenerative strategies are urgently awaited. Cultured mesenchymal stem/stromal cells (MSCs) have shown promising results in experimental models of COPD, but differences between sources may impact on their potential use in therapeutic strategies in patients. AIM To assess the transcriptome of lung-derived MSCs (LMSCs), bone marrow-derived MSCs (BM-MSC) and adipose-derived MSCs (AD-MSCs) from COPD patients and non-COPD controls. METHODS We studied differences in gene expression profiles between the MSC-subtypes, as well as between COPD and control using RNA sequencing (RNA-seq). RESULTS We show that besides heterogeneity between donors, MSCs from different sources have strongly divergent gene signatures. The growth factors FGF10 and HGF were predominantly expressed in LMSCs. MSCs from all sources displayed altered expression profiles in COPD, with most pronounced significantly up- and downregulated genes in MSCs from adipose tissue. Pathway analysis revealed that the most differentially expressed genes in COPD-derived AD-MSCs are involved in extracellular matrix (ECM) binding and expression. In LMSCs, the gene that differed most strongly between COPD and control was CSGALNACT1, an ECM modulating gene. CONCLUSION Autologous MSCs from COPD patients display abnormalities with respect to their transcriptome, which were surprisingly most profound in MSCs from extrapulmonary sources. LMSCs may be optimally equipped for lung tissue repair because of the expression of specific growth factor genes.
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Affiliation(s)
- Dennis Kruk
- grid.4494.d0000 0000 9558 4598Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, Groningen The Netherlands ,grid.4494.d0000 0000 9558 4598Groningen Research Institute for Asthma and COPD, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Anna C. Y. Yeung
- grid.117476.20000 0004 1936 7611Respiratory Bioinformatics and Molecular Biology (RBMB) Group, The University of Technology Sydney, Ultimo, NSW Australia ,grid.1013.30000 0004 1936 834XWoolcock Institute of Medical Research, The University of Sydney, Glebe, NSW Australia
| | - Alen Faiz
- grid.117476.20000 0004 1936 7611Respiratory Bioinformatics and Molecular Biology (RBMB) Group, The University of Technology Sydney, Ultimo, NSW Australia
| | - Nick H. T. ten Hacken
- grid.4494.d0000 0000 9558 4598Groningen Research Institute for Asthma and COPD, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands ,grid.4494.d0000 0000 9558 4598Department of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Wim Timens
- grid.4494.d0000 0000 9558 4598Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, Groningen The Netherlands ,grid.4494.d0000 0000 9558 4598Groningen Research Institute for Asthma and COPD, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Toin H. van Kuppevelt
- grid.5590.90000000122931605Department of Biochemistry, University of Nijmegen, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Willeke Daamen
- grid.5590.90000000122931605Department of Biochemistry, University of Nijmegen, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Danique Hof
- grid.5590.90000000122931605Department of Biochemistry, University of Nijmegen, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Martin C. Harmsen
- grid.4494.d0000 0000 9558 4598Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, Groningen The Netherlands
| | - Mauricio Rojas
- grid.261331.40000 0001 2285 7943Division of Pulmonary, Critical Care and Sleep Medicine, The Ohio State University, Columbus, OH USA
| | - Irene H. Heijink
- grid.4494.d0000 0000 9558 4598Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9713 GZ Groningen, Groningen The Netherlands ,grid.4494.d0000 0000 9558 4598Groningen Research Institute for Asthma and COPD, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands ,grid.4494.d0000 0000 9558 4598Department of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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22
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Cheng Q, Zhang X, Chen LS, Liu J. Mendelian randomization accounting for complex correlated horizontal pleiotropy while elucidating shared genetic etiology. Nat Commun 2022; 13:6490. [PMID: 36310177 PMCID: PMC9618026 DOI: 10.1038/s41467-022-34164-1] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 10/17/2022] [Indexed: 12/25/2022] Open
Abstract
Mendelian randomization (MR) harnesses genetic variants as instrumental variables (IVs) to study the causal effect of exposure on outcome using summary statistics from genome-wide association studies. Classic MR assumptions are violated when IVs are associated with unmeasured confounders, i.e., when correlated horizontal pleiotropy (CHP) arises. Such confounders could be a shared gene or inter-connected pathways underlying exposure and outcome. We propose MR-CUE (MR with Correlated horizontal pleiotropy Unraveling shared Etiology and confounding), for estimating causal effect while identifying IVs with CHP and accounting for estimation uncertainty. For those IVs, we map their cis-associated genes and enriched pathways to inform shared genetic etiology underlying exposure and outcome. We apply MR-CUE to study the effects of interleukin 6 on multiple traits/diseases and identify several S100 genes involved in shared genetic etiology. We assess the effects of multiple exposures on type 2 diabetes across European and East Asian populations.
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Affiliation(s)
- Qing Cheng
- grid.443347.30000 0004 1761 2353Center of Statistical Research, School of Statistics, Southwestern University of Finance and Economics, Chengdu, Sichuan China ,grid.428397.30000 0004 0385 0924Centre for Quantitative Medicine, Health Services & Systems Research, Duke-NUS Medical School, Singapore, Singapore
| | - Xiao Zhang
- grid.428397.30000 0004 0385 0924Centre for Quantitative Medicine, Health Services & Systems Research, Duke-NUS Medical School, Singapore, Singapore
| | - Lin S. Chen
- grid.170205.10000 0004 1936 7822Department of Public Health Sciences, The University of Chicago, Chicago, IL USA
| | - Jin Liu
- Centre for Quantitative Medicine, Health Services & Systems Research, Duke-NUS Medical School, Singapore, Singapore.
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23
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Junco-Vicente A, Solache-Berrocal G, del Río-García Á, Rolle-Sóñora V, Areces S, Morís C, Martín M, Rodríguez I. IL6 gene polymorphism association with calcific aortic valve stenosis and influence on serum levels of interleukin-6. Front Cardiovasc Med 2022; 9:989539. [PMID: 36337884 PMCID: PMC9630837 DOI: 10.3389/fcvm.2022.989539] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 10/03/2022] [Indexed: 07/30/2023] Open
Abstract
Aortic valve stenosis is the most frequent valve disease in developed countries and its prevalence will increase with population aging. There is still no pharmaceutical treatment nor biomarker to determine the susceptibility to develop aortic stenosis. Therefore, we analyzed the association of polymorphisms in risk loci with calcific aortic stenosis. Patients with aortic valve disease were genotyped for PALMD rs6702619, LPA rs10455872, and IL6 rs1800795 polymorphisms and circulating levels of interleukin-6 (IL-6) were measured. Calcium content of leaflets obtained in valve replacement surgeries was determined by micro-computed tomography. In the genotyping of 578 individuals, we found significant association between PALMD and IL6 polymorphisms and aortic stenosis in patients with tricuspid aortic valve, independently of other potentially confounding variables such as age and dyslipidemia. There was no association of these polymorphisms with valve calcium content, but this value correlated with the mean aortic pressure gradient (r = 0.44; P < 0.001). The CC genotype of IL6 polymorphism was associated with higher levels of serum IL-6 compared to other genotypes (23.5 vs. 10.5 pg/ml, respectively; P = 0.029). Therefore, patients carrying the CC genotype of IL6 rs1800795 polymorphism present higher levels of circulating IL-6 and this could contribute to the severity of the aortic valve stenosis. Our results agree with the identification of IL6 as a locus risk for stenosis and also with the intervention of this cytokine in aortic valve calcification. A more exhaustive follow-up of those patients carrying risk genotypes is therefore recommended.
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Affiliation(s)
- Alejandro Junco-Vicente
- Department of Cardiology, Área del Corazón, Hospital Universitario Central de Asturias (HUCA), Oviedo, Spain
| | - Guillermo Solache-Berrocal
- Cardiac Pathology Research Group, Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
| | - Álvaro del Río-García
- Cardiac Pathology Research Group, Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
| | - Valeria Rolle-Sóñora
- Biostatistics and Epidemiology Platform, Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
| | - Sheila Areces
- Department of Cardiology, Área del Corazón, Hospital Universitario Central de Asturias (HUCA), Oviedo, Spain
| | - César Morís
- Department of Cardiology, Área del Corazón, Hospital Universitario Central de Asturias (HUCA), Oviedo, Spain
- Cardiac Pathology Research Group, Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
- Department of Medicine, Faculty of Medicine, University of Oviedo, Oviedo, Spain
| | - María Martín
- Department of Cardiology, Área del Corazón, Hospital Universitario Central de Asturias (HUCA), Oviedo, Spain
- Cardiac Pathology Research Group, Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
| | - Isabel Rodríguez
- Cardiac Pathology Research Group, Instituto de Investigación Sanitaria del Principado de Asturias (ISPA), Oviedo, Spain
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24
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Bottigliengo D, Foco L, Seibler P, Klein C, König IR, Del Greco M F. A Mendelian randomization study investigating the causal role of inflammation on Parkinson’s disease. Brain 2022; 145:3444-3453. [PMID: 35656776 PMCID: PMC9586538 DOI: 10.1093/brain/awac193] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 04/10/2022] [Accepted: 05/10/2022] [Indexed: 11/13/2022] Open
Abstract
There is increasing evidence for inflammation as a determinant in the pathogenesis of Parkinson’s disease, but its role in parkinsonian neurodegeneration remains elusive. It is not clear whether inflammatory cascades are causes or consequences of dopamine neuron death. In the present study, we aim to perform an in-depth statistical investigation of the causal relationship between inflammation and Parkinson’s disease using a two-sample Mendelian randomization design. Genetic instruments were selected using summary-level data from the largest genome-wide association studies to date (sample size ranging from 13 955 to 204 402 individuals) conducted on a European population for the following inflammation biomarkers: C-reactive protein, interleukin-6, interleukin 1 receptor antagonist and tumour necrosis factor α. Genetic association data on Parkinson’s disease (56 306 cases and 1 417 791 controls) and age at onset of Parkinson’s disease (28 568 cases) were obtained from the International Parkinson’s Disease Genomics Consortium. On primary analysis, causal associations were estimated on sets of strong (P-value < 5 × 10−8; F-statistic > 10) and independent (linkage disequilibrium r2 < 0.001) genetic instruments using the inverse-variance weighted method. In sensitivity analysis, we estimated causal effects using robust Mendelian randomization methods and after removing pleiotropic genetic variants. Reverse causation was also explored. We repeated the analysis on different data sources for inflammatory biomarkers to check the consistency of the findings. In all the three data sources selected for interleukin-6, we found statistical evidence for an earlier age at onset of Parkinson’s disease associated with increased interleukin-6 concentration [years difference per 1 log-unit increase = −2.364, 95% confidence interval (CI) = −4.789–0.060; years difference per 1 log-unit increase = −2.011, 95% CI = −3.706 to −0.317; years difference per 1 log-unit increase = −1.569, 95% CI = −2.891 to −0.247]. We did not observe any statistical evidence for causal effects of C-reactive protein, interleukin 1 receptor antagonist and tumour necrosis factor α on both Parkinson’s disease and its age at onset. Results after excluding possible pleiotropic genetic variants were consistent with findings from primary analyses. When investigating reverse causation, we did not find evidence for a causal effect of Parkinson’s disease or age at onset on any biomarkers of inflammation. We found evidence for a causal association between the onset of Parkinson’s disease and interleukin-6. The findings of this study suggest that the pro-inflammatory activity of the interleukin-6 cytokine could be a determinant of prodromal Parkinson’s disease.
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Affiliation(s)
| | - Luisa Foco
- Institute for Biomedicine, Eurac Research , Bolzano (39100), Italy
| | - Philip Seibler
- Institute of Neurogenetics, University of Lübeck and University Hospital of Schleswig-Holstein , Lübeck, Germany
| | - Christine Klein
- Institute of Neurogenetics, University of Lübeck and University Hospital of Schleswig-Holstein , Lübeck, Germany
- Department of Psychiatry and Psychotherapy, University of Lübeck , Germany
| | - Inke R. König
- Institute of Medical Biometry and Statistics, University of Lübeck and University Hospital of Schleswig-Holstein , Lübeck, Germany
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25
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Vandebergh M, Becelaere S, Dubois B, Goris A. Body Mass Index, Interleukin-6 Signaling and Multiple Sclerosis: A Mendelian Randomization Study. Front Immunol 2022; 13:834644. [PMID: 35386698 PMCID: PMC8978959 DOI: 10.3389/fimmu.2022.834644] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2021] [Accepted: 02/25/2022] [Indexed: 12/14/2022] Open
Abstract
Objectives We explored whether genetically predicted increased body mass index (BMI) modulates multiple sclerosis (MS) risk through interleukin-6 (IL-6) signaling. Methods We performed a two-sample Mendelian randomization (MR) study using multiple genome-wide association studies (GWAS) datasets for BMI, IL-6 signaling, IL-6 levels and c-reactive protein (CRP) levels as exposures and estimated their effects on risk of MS from GWAS data from the International Multiple Sclerosis Genetics Consortium (IMSGC) in 14,802 MS cases and 26,703 controls. Results In univariable MR analyses, genetically predicted increased BMI and IL-6 signaling were associated with higher risk of MS (BMI: odds ratio (OR) = 1.30, 95% confidence interval (CI) = 1.15-1.47, p = 3.76 × 10-5; IL-6 signaling: OR = 1.51, 95% CI = 1.11-2.04, p = 0.01). Furthermore, higher BMI was associated with increased IL-6 signaling (β = 0.37, 95% CI = 0.32,0.41, p = 1.58 × 10-65). In multivariable MR analyses, the effect of IL-6 signaling on MS risk remained after adjusting for BMI (OR = 1.36, 95% CI = 1.11-1.68, p = 0.003) and higher BMI remained associated with an increased risk for MS after adjustment for IL-6 signaling (OR = 1.16, 95% CI =1.00-1.34, p = 0.046). The proportion of the effect of BMI on MS mediated by IL-6 signaling corresponded to 43% (95% CI = 25%-54%). In contrast to IL-6 signaling, there was little evidence for an effect of serum IL-6 levels or CRP levels on risk of MS. Conclusion In this study, we identified IL-6 signaling as a major mediator of the association between BMI and risk of MS. Further explorations of pathways underlying the association between BMI and MS are required and will, together with our findings, improve the understanding of MS biology and potentially lead to improved opportunities for targeted prevention strategies.
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Affiliation(s)
- Marijne Vandebergh
- Laboratory for Neuroimmunology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium
| | - Sara Becelaere
- Laboratory for Neuroimmunology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Laboratory for Human Evolutionary Genetics, Department of Human Genetics, KU Leuven, Leuven, Belgium
| | | | - Bénédicte Dubois
- Laboratory for Neuroimmunology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Department of Neurology, University Hospitals Leuven, Leuven, Belgium
| | - An Goris
- Laboratory for Neuroimmunology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium
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26
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Diaz-Barreiro A, Huard A, Palmer G. Multifaceted roles of IL-38 in inflammation and cancer. Cytokine 2022; 151:155808. [DOI: 10.1016/j.cyto.2022.155808] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Revised: 01/08/2022] [Accepted: 01/11/2022] [Indexed: 12/11/2022]
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27
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Kreiner FF, Kraaijenhof JM, von Herrath M, Hovingh GKK, von Scholten BJ. Interleukin 6 in diabetes, chronic kidney disease and cardiovascular disease: mechanisms and therapeutic perspectives. Expert Rev Clin Immunol 2022; 18:377-389. [PMID: 35212585 DOI: 10.1080/1744666x.2022.2045952] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
INTRODUCTION Diabetes, chronic kidney disease (CKD) and cardiovascular disease (CVD) are cardiometabolic diseases that remain amongst the leading causes of morbidity and premature mortality. Here, we review the current understanding of how anti-inflammatory intervention via inhibition of the pro-inflammatory but pleiotropic cytokine interleukin (IL) 6 may benefit patients with these or related diseases or complications. AREAS COVERED Based on a PubMed literature search, this review integrates and contextualizes evidence regarding the clinical utility of anti-IL-6 intervention in the treatment of cardiometabolic diseases, as well as of the associated condition non-alcoholic hepatosteatosis. EXPERT OPINION Evidence implicates the pro-inflammatory effects of IL-6 in the pathophysiology of diabetes, CKD and CVD. Thus, targeting the IL-6 pathway holds a therapeutic potential in these cardiometabolic disorders. However, because IL-6 has multiple homeostatic roles, antagonizing this cytokine may be associated with side effects such as increased risk of infection as seen with other anti-inflammatory drugs. Additional studies are required to establish the benefit-risk profile of anti-IL-6 intervention in the cardiometabolic diseases, whilst also considering alternative interventions such as lifestyle changes. IL-6 is also elevated in NASH, but the clinical usefulness of targeting IL-6 in this hepatic disorder remains largely unexplored.
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Affiliation(s)
| | - Jordan M Kraaijenhof
- Global Chief Medical Office, Novo Nordisk A/S, Søborg, Denmark.,Department of Vascular Medicine, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Matthias von Herrath
- Global Chief Medical Office, Novo Nordisk A/S, Søborg, Denmark.,La Jolla Institute for Immunology, La Jolla, California, United States
| | - G Kees Kornelis Hovingh
- Global Chief Medical Office, Novo Nordisk A/S, Søborg, Denmark.,Department of Vascular Medicine, Amsterdam University Medical Center, Amsterdam, The Netherlands
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28
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Williams PT. Quantile-Dependent Expressivity of Serum Interleukin-6 Concentrations as a Possible Explanation of Gene-Disease Interactions, Gene-Environment Interactions, and Pharmacogenetic Effects. Inflammation 2022; 45:1059-1075. [PMID: 34993731 DOI: 10.1007/s10753-021-01601-0] [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: 07/26/2021] [Accepted: 11/15/2021] [Indexed: 12/01/2022]
Abstract
Interleukin 6 (IL-6) is a moderately heritable pleiotropic cytokine whose elevated concentrations in coronary artery disease, peripheral arterial disease, pulmonary arterial hypertension, Eales' disease, Sjògren's syndrome, osteoarthritis, adenocarcinoma, neuroblastoma, polymyalgia rheumatica, pulmonary tuberculosis, and enterovirus 71 infection, and following coronary artery bypass graft show larger genetic effects than in unaffected low IL-6 controls. We hypothesize that genetic effects may depend upon whether average IL-6 concentrations are high or low, i.e., quantile-dependent expressivity. Quantile-specific offspring-parent (βOP) and full-sib regression slopes (βFS) were estimated by applying quantile regression to the age- and sex-adjusted serum IL-6 concentrations in families surveyed in the Framingham Heart Study. Quantile-specific heritabilities were calculated as h2 = 2βOP / (1 + rspouse) and h2 = {(1 + 8rspouseβFS)0.5 -1} / (2rspouse)). Heritability (h2 ± SE) of IL-6 concentrations increased from 0.01 ± 0.01 at the 10th percentile (NS), 0.02 ± 0.01 at the 25th (P = 0.009), 0.03 ± 0.01 at the 50th (P = 0.007), 0.04 ± 0.02 at the 75th (P = 0.004), and 0.13 ± 0.05 at the 90th percentile (P = 0.03), or 0.0005 ± 0.0002 for each 1% increase in the offspring's phenotype distribution (Plinear trend = 0.02) when estimated from βOP and from 0.02 ± 0.02 at the 10th (NS), 0.02 ± 0.02 at the 25th (NS), 0.06 ± 0.02 at the 50th (P = 0.01), 0.12 ± 0.04 at the 75th (P = 0.001), and 0.30 ± 0.03 at the 90th percentile (P < 10-16), or 0.0015 ± 0.0007 for each 1% increase in the sibling phenotype distribution (Plinear trend = 0.02) when estimated from βFS. Thus the heritability of serum IL-6 concentrations is quantile dependent, which may contribute in part to the larger genetic effect size reported for diseases and environmental conditions that elevate IL-6 concentrations vis-à-vis unaffected controls.
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Affiliation(s)
- Paul T Williams
- Lawrence Berkeley National Laboratory, Molecular Biophysics & Integrated Bioimaging Division, 1 Cyclotron Road, Berkeley, CA, 94720, USA.
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29
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Cupido AJ, Asselbergs FW, Natarajan P, Ridker PM, Hovingh GK, Schmidt AF. Dissecting the IL-6 pathway in cardiometabolic disease: a Mendelian randomization study on both IL6 and IL6R. Br J Clin Pharmacol 2021; 88:2875-2884. [PMID: 34931349 PMCID: PMC9303316 DOI: 10.1111/bcp.15191] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 10/07/2021] [Accepted: 10/28/2021] [Indexed: 11/26/2022] Open
Abstract
BACKGROUND Chronic inflammation is a risk factor for cardiovascular disease. IL-6 signaling perturbation through IL-6 or IL-6R blockade may have potential benefit on cardiovascular risk. It is unknown whether targeting either IL-6 or IL-6 receptor may result in similar effects on CVD and adverse events. We compared the anticipated effects of targeting IL-6 and IL-6 receptor on cardiometabolic risk and potential side effects. METHODS We constructed four instruments: two main instruments with genetic variants in the IL6 and IL6R loci weighted for their association with CRP, and two after firstly filtering variants for their association with IL-6 or IL-6R expression. Analyses were performed for coronary artery disease (CAD), ischemic stroke, atrial fibrillation (AF), heart failure, type 2 diabetes (T2D), rheumatoid arthritis (RA), infection endpoints, and quantitative hematological, metabolic, and anthropometric parameters. RESULTS A 1 mg/L lower CRP by the IL6 instrument was associated with lower CAD (OR 0.86, 95% CI 0.77;0.96), AF, and T2D risk. A 1mg/L lower CRP by the IL6R instrument was associated with lower CAD (OR 0.90, 95% CI 0.86;0.95), any stroke and ischemic stroke, AF, RA risk and higher pneumonia risk. The eQTL filtered results were in concordance with the main results, but with wider confidence intervals. CONCLUSIONS IL-6 signalling perturbation by either IL6 or IL6R genetic instruments is associated with a similar risk reduction for multiple cardiometabolic diseases, suggesting that both IL-6 and IL-6R are potential therapeutic targets to lower CVD. Moreover, IL-6 rather than IL-6R inhibition might have a more favorable pneumonia risk.
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Affiliation(s)
- Arjen J Cupido
- Department of Vascular Medicine, Amsterdam University Medical Centers, location AMC, University of Amsterdam, Amsterdam, Netherlands.,Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Folkert W Asselbergs
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.,Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom.,Health Data Research UK and Institute of Health Informatics, University College London, London, United Kingdom
| | - Pradeep Natarajan
- Cardiovascular Research Center, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, US.,Program in Medical and Population Genetics and Cardiovascular Disease Initiative, Broad Institute of Harvard and MIT, Cambridge, Massachusetts, US
| | | | - Paul M Ridker
- Divisions of Preventive Medicine and Cardiovascular Medicine, Department of Medicine, Center for Cardiovascular Disease Prevention, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States
| | - G Kees Hovingh
- Department of Vascular Medicine, Amsterdam University Medical Centers, location AMC, University of Amsterdam, Amsterdam, Netherlands
| | - A Floriaan Schmidt
- Department of Cardiology, Division Heart & Lungs, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands.,Institute of Cardiovascular Science, Faculty of Population Health Sciences, University College London, London, United Kingdom
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30
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Yu X, Ho K, Shen Z, Fu X, Huang H, Wu D, Lin Y, Lin Y, Chen W, Su M, Qiu C, Zhuang X, Su Z. The Association of Human Leukocyte Antigen and COVID-19 in Southern China. Open Forum Infect Dis 2021; 8:ofab410. [PMID: 34552996 PMCID: PMC8436377 DOI: 10.1093/ofid/ofab410] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 08/06/2021] [Indexed: 12/24/2022] Open
Abstract
Human leukocyte antigen (HLA) polymorphism is hypothesized to be associated with diverse immune responses toward infectious diseases. Herein, by comparing against multiple subpopulation groups as control, we confirmed that HLA-B*15:27 and HLA-DRB1*04:06 were associated with coronavirus disease 2019 susceptibility in China. Both alleles were predicted to have weak binding affinities toward viral proteins.
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Affiliation(s)
- Xueping Yu
- Department of Infectious Disease, The First Hospital of Quanzhou, affiliated to Fujian Medical University, Quanzhou, Fujian, China
| | - Kuoting Ho
- HI. Q Biomedical Laboratory, Quanzhou, Fujian, China.,School of Biomedical Science, Huaqiao University, Quanzhou, Fujian, China
| | - Zhongliang Shen
- Department of Infectious Disease, Huashan Hospital, Fudan University, Shanghai, China
| | - Xiaoying Fu
- HI. Q Biomedical Laboratory, Quanzhou, Fujian, China
| | - Hongbo Huang
- Department of Respiratory Disease, The First Hospital of Quanzhou, affiliated to Fujian Medical University, Quanzhou, Fujian, China
| | - Delun Wu
- HI. Q Biomedical Laboratory, Quanzhou, Fujian, China
| | - Yancheng Lin
- HI. Q Biomedical Laboratory, Quanzhou, Fujian, China
| | - Yijian Lin
- Department of Respiratory Disease, The First Hospital of Quanzhou, affiliated to Fujian Medical University, Quanzhou, Fujian, China
| | - Wenhuang Chen
- Department of Infectious Disease, The First Hospital of Quanzhou, affiliated to Fujian Medical University, Quanzhou, Fujian, China
| | - Milong Su
- Department of Clinical Laboratory, The First Hospital of Quanzhou, affiliated to Fujian Medical University, Quanzhou, Fujian, China
| | - Chao Qiu
- Department of Infectious Disease, Huashan Hospital, Fudan University, Shanghai, China
| | - Xibin Zhuang
- Department of Respiratory Disease, The First Hospital of Quanzhou, affiliated to Fujian Medical University, Quanzhou, Fujian, China
| | - Zhijun Su
- Department of Infectious Disease, The First Hospital of Quanzhou, affiliated to Fujian Medical University, Quanzhou, Fujian, China
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