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Li Q, Patrick MT, Sreeskandarajan S, Kang J, Kahlenberg JM, Gudjonsson JE, He Z, Tsoi LC. Large-scale epidemiological analysis of common skin diseases to identify shared and unique comorbidities and demographic factors. Front Immunol 2024; 14:1309549. [PMID: 38259463 PMCID: PMC10800546 DOI: 10.3389/fimmu.2023.1309549] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2023] [Accepted: 12/12/2023] [Indexed: 01/24/2024] Open
Abstract
Introduction The utilization of large-scale claims databases has greatly improved the management, accessibility, and integration of extensive medical data. However, its potential for systematically identifying comorbidities in the context of skin diseases remains unexplored. Methods This study aims to assess the capability of a comprehensive claims database in identifying comorbidities linked to 14 specific skin and skin-related conditions and examining temporal changes in their association patterns. This study employed a retrospective case-control cohort design utilizing 13 million skin/skin-related patients and 2 million randomly sampled controls from Optum's de-identified Clinformatics® Data Mart Database spanning the period from 2001 to 2018. A broad spectrum of comorbidities encompassing cancer, diabetes, respiratory, mental, immunity, gastrointestinal, and cardiovascular conditions were examined for each of the 14 skin and skin-related disorders in the study. Results Using the established type-2 diabetes (T2D) and psoriasis comorbidity as example, we demonstrated the association is significant (P-values<1x10-15) and stable across years (OR=1.15-1.31). Analysis of the 2014-2018 data reveals that celiac disease, Crohn's disease, and ulcerative colitis exhibit the strongest associations with the 14 skin/skin-related conditions. Systemic lupus erythematosus (SLE), leprosy, and hidradenitis suppurativa show the strongest associations with 30 different comorbidities. Particularly notable associations include Crohn's disease with leprosy (odds ratio [OR]=6.60, 95% confidence interval [CI]: 3.09-14.08), primary biliary cirrhosis with SLE (OR=6.07, 95% CI: 4.93-7.46), and celiac disease with SLE (OR=6.06, 95% CI: 5.49-6.69). In addition, changes in associations were observed over time. For instance, the association between atopic dermatitis and lung cancer demonstrates a marked decrease over the past decade, with the odds ratio decreasing from 1.75 (95% CI: 1.47-2.07) to 1.02 (95% CI: 0.97-1.07). The identification of skin-associated comorbidities contributes to individualized healthcare and improved clinical management, while also enhancing our understanding of shared pathophysiology. Moreover, tracking these associations over time aids in evaluating the progression of clinical diagnosis and treatment. Discussion The findings highlight the potential of utilizing comprehensive claims databases in advancing research and improving patient care in dermatology.
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Affiliation(s)
- Qinmengge Li
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, United States
| | - Matthew T Patrick
- Department of Dermatology, University of Michigan, Ann Arbor, MI, United States
| | - Sutharzan Sreeskandarajan
- The Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, Cincinnati, OH, United States
| | - Jian Kang
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, United States
| | - J Michelle Kahlenberg
- Department of Dermatology, University of Michigan, Ann Arbor, MI, United States
- Rheumatology, Internal Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Johann E Gudjonsson
- Department of Dermatology, University of Michigan, Ann Arbor, MI, United States
| | - Zhi He
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, United States
| | - Lam C Tsoi
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, United States
- Department of Dermatology, University of Michigan, Ann Arbor, MI, United States
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, United States
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Ma F, Gharaee-Kermani M, Tsoi LC, Plazyo O, Chaskar P, Harms P, Patrick MT, Xing X, Hile G, Piketty C, Lazzari A, Van Delm W, Maverakis E, Nakamura M, Modlin RL, Kahlenberg JM, Billi AC, Julia V, Krishnaswamy JK, Gudjonsson JE. Single-cell profiling of prurigo nodularis demonstrates immune-stromal crosstalk driving profibrotic responses and reversal with nemolizumab. J Allergy Clin Immunol 2024; 153:146-160. [PMID: 37506977 DOI: 10.1016/j.jaci.2023.07.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 06/14/2023] [Accepted: 07/19/2023] [Indexed: 07/30/2023]
Abstract
BACKGROUND Prurigo nodularis (PN) is a chronic neuroimmune skin disease characterized by bilaterally distributed pruritic hyperkeratotic nodules on extremities and trunk. Neuroimmune dysregulation and chronic scratching are believed to both induce and maintain the characteristic lesions. OBJECTIVES This study sought to provide a comprehensive view of the molecular pathogenesis of PN at the single-cell level to identify and outline key pathologic processes and the cell types involved. Features that distinguish PN skin from the skin of patients with atopic dermatitis were of particular interest. We further aimed to determine the impact of the IL31RA antagonist, nemolizumab, and its specificity at the single-cell level. METHODS Single-cell RNA-sequencing of skin from 15 healthy donors and nonlesional and lesional skin from 6 patients each with PN and atopic dermatitis, combined with spatial-sequencing using the 10x Visium platform. Integration with bulk RNA-sequencing data from patients treated with nemolizumab. RESULTS This study demonstrates that PN is an inflammatory skin disease characterized by both keratinocyte proliferation and activation of profibrotic responses. This study also demonstrates that the COL11A1+ fibroblast subset is a major contributor to fibrosis and is predominantly found in the papillary dermis of PN skin. Activation of fibrotic responses is the main distinguishing feature between PN and atopic dermatitis skin. This study further shows the broad effect of nemolizumab on PN cell types, with a prominent effect driving COL11A1+ fibroblast and keratinocyte responses toward normal. CONCLUSIONS This study provides a high-resolution characterization of the cell types and cellular processes activated in PN skin, establishing PN as a chronic fibrotic inflammatory skin disease. It further demonstrates the broad effect of nemolizumab on pathological processes in PN skin.
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Affiliation(s)
- Feiyang Ma
- Department of Dermatology, University of Michigan, Ann Arbor, Mich
| | | | - Lam C Tsoi
- Department of Dermatology, University of Michigan, Ann Arbor, Mich; Department of Biostatistics, University of Michigan, Ann Arbor, Mich; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Mich
| | - Olesya Plazyo
- Department of Dermatology, University of Michigan, Ann Arbor, Mich
| | | | - Paul Harms
- Department of Dermatology, University of Michigan, Ann Arbor, Mich; Department of Pathology, University of Michigan, Ann Arbor, Mich
| | | | - Xianying Xing
- Department of Dermatology, University of Michigan, Ann Arbor, Mich
| | - Grace Hile
- Department of Dermatology, University of Michigan, Ann Arbor, Mich
| | | | | | | | - Emanual Maverakis
- Department of Dermatology, University of California-Davis, Sacramento, Calif
| | - Mio Nakamura
- Department of Dermatology, University of Michigan, Ann Arbor, Mich
| | - Robert L Modlin
- Department of Dermatology, University of California-Los Angeles, Calif
| | - J Michelle Kahlenberg
- Department of Internal Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, Mich; Taubman Medical Research Institute, University of Michigan, Ann Arbor, Mich
| | - Allison C Billi
- Department of Dermatology, University of Michigan, Ann Arbor, Mich
| | | | | | - Johann E Gudjonsson
- Department of Dermatology, University of Michigan, Ann Arbor, Mich; Department of Internal Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, Mich; Taubman Medical Research Institute, University of Michigan, Ann Arbor, Mich.
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Patrick MT, Sreeskandarajan S, Shefler A, Wasikowski R, Sarkar MK, Chen J, Qin T, Billi AC, Kahlenberg JM, Prens E, Hovnanian A, Weidinger S, Elder JT, Kuo CC, Gudjonsson JE, Tsoi LC. Large-scale functional inference for skin-expressing lncRNAs using expression and sequence information. JCI Insight 2023; 8:e172956. [PMID: 38131377 PMCID: PMC10807743 DOI: 10.1172/jci.insight.172956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Accepted: 11/08/2023] [Indexed: 12/23/2023] Open
Abstract
Long noncoding RNAs (lncRNAs) regulate the expression of protein-coding genes and have been shown to play important roles in inflammatory skin diseases. However, we still have limited understanding of the functional impact of lncRNAs in skin, partly due to their tissue specificity and lower expression levels compared with protein-coding genes. We compiled a comprehensive list of 18,517 lncRNAs from different sources and studied their expression profiles in 834 RNA-Seq samples from multiple inflammatory skin conditions and cytokine-stimulated keratinocytes. Applying a balanced random forest to predict involvement in biological functions, we achieved a median AUROC of 0.79 in 10-fold cross-validation, identifying significant DNA binding domains (DBDs) for 39 lncRNAs. G18244, a skin-expressing lncRNA predicted for IL-4/IL-13 signaling in keratinocytes, was highly correlated in expression with F13A1, a protein-coding gene involved in macrophage regulation, and we further identified a significant DBD in F13A1 for G18244. Reflecting clinical implications, AC090198.1 (predicted for IL-17 pathway) and AC005332.6 (predicted for IFN-γ pathway) had significant negative correlation with the SCORAD metric for atopic dermatitis. We also utilized single-cell RNA and spatial sequencing data to validate cell type specificity. Our research demonstrates lncRNAs have important immunological roles and can help prioritize their impact on inflammatory skin diseases.
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Affiliation(s)
- Matthew T. Patrick
- Department of Dermatology, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Sutharzan Sreeskandarajan
- Department of Dermatology, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA
- Center for Autoimmune Genomics and Etiology (CAGE), Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, USA
| | - Alanna Shefler
- Department of Dermatology, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Rachael Wasikowski
- Department of Dermatology, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Mrinal K. Sarkar
- Department of Dermatology, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Jiahan Chen
- Department of Dermatology, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA
- College of Sciences, North Carolina State University, Raleigh, North Carolina, USA
| | - Tingting Qin
- Department of Computational Medicine & Bioinformatics and
| | - Allison C. Billi
- Department of Dermatology, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - J. Michelle Kahlenberg
- Department of Dermatology, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA
- Division of Rheumatology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Errol Prens
- Department of Dermatology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Alain Hovnanian
- Laboratory of Genetic Skin Diseases, Imagine Institute, Paris, France
| | - Stephan Weidinger
- Department of Dermatology and Allergy, University Medical Center Schleswig-Holstein, Kiel, Germany
| | - James T. Elder
- Department of Dermatology, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA
- Ann Arbor Veterans Affairs Hospital, Ann Arbor, Michigan, USA
| | - Chao-Chung Kuo
- Institute for Computational Genomics, Joint Research Center for Computational Biomedicine, RWTH Aachen University, Aachen, Germany
| | - Johann E. Gudjonsson
- Department of Dermatology, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Lam C. Tsoi
- Department of Dermatology, Michigan Medicine, University of Michigan, Ann Arbor, Michigan, USA
- Department of Computational Medicine & Bioinformatics and
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
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Zhang H, Patrick MT, Tejasvi T, Sarkar MK, Wasikowski R, Stuart PE, Li Q, Xing X, Voorhees JJ, Ward NL, He K, Zhou X, Gudjonsson JE, Nair RP, Elder JT, Tsoi LC. Retrospective pharmacogenetic study of psoriasis highlights the role of KLK7 in tumour necrosis factor signalling. Br J Dermatol 2023; 190:70-79. [PMID: 37672660 PMCID: PMC10733628 DOI: 10.1093/bjd/ljad332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 08/29/2023] [Accepted: 09/01/2023] [Indexed: 09/08/2023]
Abstract
BACKGROUND Multiple treatment options are available for the management of psoriasis, but clinical response varies among individual patients and no biomarkers are available to facilitate treatment selection for improved patient outcomes. OBJECTIVES To utilize retrospective data to conduct a pharmacogenetic study to explore the potential genetic pathways associated with drug response in the treatment of psoriasis. METHODS We conducted a retrospective pharmacogenetic study using self-evaluated treatment response from 1942 genotyped patients with psoriasis. We examined 6 502 658 genetic markers to model their associations with response to six treatment options using linear regression, adjusting for cohort variables and demographic features. We further utilized an integrative approach incorporating epigenomics, transcriptomics and a longitudinal clinical cohort to provide biological implications for the topmost signals associated with drug response. RESULTS Two novel markers were revealed to be associated with treatment response: rs1991820 (P = 1.30 × 10-6) for anti-tumour necrosis factor (TNF) biologics; and rs62264137 (P = 2.94 × 10-6) for methotrexate, which was also associated with cutaneous mRNA expression levels of two known psoriasis-related genes KLK7 (P = 1.0 × 10-12) and CD200 (P = 5.4 × 10-6). We demonstrated that KLK7 expression was increased in the psoriatic epidermis, as shown by immunohistochemistry, as well as single-cell RNA sequencing, and its responsiveness to anti-TNF treatment was highlighted. By inhibiting the expression of KLK7, we further illustrated that keratinocytes have decreased proinflammatory responses to TNF. CONCLUSIONS Our study implicates the genetic regulation of cytokine responses in predicting clinical drug response and supports the association between pharmacogenetic loci and anti-TNF response, as shown here for KLK7.
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Affiliation(s)
| | | | - Trilokraj Tejasvi
- Department of Dermatology
- Ann Arbor Veterans Affairs Hospital, Ann Arbor, MI, USA
| | | | | | | | | | | | | | - Nicole L Ward
- Department of Dermatology, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | | | - Johann E Gudjonsson
- Department of Dermatology
- Taubman Medical Research Institute, University of Michigan Medical School, Ann Arbor, MI, USA
| | | | - James T Elder
- Department of Dermatology
- Ann Arbor Veterans Affairs Hospital, Ann Arbor, MI, USA
| | - Lam C Tsoi
- Departments of Biostatistics
- Department of Dermatology
- Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
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5
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Dand N, Stuart PE, Bowes J, Ellinghaus D, Nititham J, Saklatvala JR, Teder-Laving M, Thomas LF, Traks T, Uebe S, Assmann G, Baudry D, Behrens F, Billi AC, Brown MA, Burkhardt H, Capon F, Chung R, Curtis CJ, Duckworth M, Ellinghaus E, FitzGerald O, Gerdes S, Griffiths CEM, Gulliver S, Helliwell P, Ho P, Hoffmann P, Holmen OL, Huang ZM, Hveem K, Jadon D, Köhm M, Kraus C, Lamacchia C, Lee SH, Ma F, Mahil SK, McHugh N, McManus R, Modalsli EH, Nissen MJ, Nöthen M, Oji V, Oksenberg JR, Patrick MT, Perez-White BE, Ramming A, Rech J, Rosen C, Sarkar MK, Schett G, Schmidt B, Tejasvi T, Traupe H, Voorhees JJ, Wacker EM, Warren RB, Wasikowski R, Weidinger S, Wen X, Zhang Z, Barton A, Chandran V, Esko T, Foerster J, Franke A, Gladman DD, Gudjonsson JE, Gulliver W, Hüffmeier U, Kingo K, Kõks S, Liao W, Løset M, Mägi R, Nair RP, Rahman P, Reis A, Smith CH, Di Meglio P, Barker JN, Tsoi LC, Simpson MA, Elder JT. GWAS meta-analysis of psoriasis identifies new susceptibility alleles impacting disease mechanisms and therapeutic targets. medRxiv 2023:2023.10.04.23296543. [PMID: 37873414 PMCID: PMC10593001 DOI: 10.1101/2023.10.04.23296543] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
Psoriasis is a common, debilitating immune-mediated skin disease. Genetic studies have identified biological mechanisms of psoriasis risk, including those targeted by effective therapies. However, the genetic liability to psoriasis is not fully explained by variation at robustly identified risk loci. To move towards a saturation map of psoriasis susceptibility we meta-analysed 18 GWAS comprising 36,466 cases and 458,078 controls and identified 109 distinct psoriasis susceptibility loci, including 45 that have not been previously reported. These include susceptibility variants at loci in which the therapeutic targets IL17RA and AHR are encoded, and deleterious coding variants supporting potential new drug targets (including in STAP2, CPVL and POU2F3). We conducted a transcriptome-wide association study to identify regulatory effects of psoriasis susceptibility variants and cross-referenced these against single cell expression profiles in psoriasis-affected skin, highlighting roles for the transcriptional regulation of haematopoietic cell development and epigenetic modulation of interferon signalling in psoriasis pathobiology.
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Affiliation(s)
- Nick Dand
- Department of Medical & Molecular Genetics, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK
- Health Data Research UK, London, UK
| | - Philip E Stuart
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - John Bowes
- Centre for Genetics and Genomics Versus Arthritis, The University of Manchester, Manchester, UK
- National Institute for Health and Care Research (NIHR) Manchester Biomedical Research Centre, The University of Manchester, Manchester, UK
| | - David Ellinghaus
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Joanne Nititham
- Deparment of Dermatology, University of California San Francisco, San Francisco, CA, USA
| | - Jake R Saklatvala
- Department of Medical & Molecular Genetics, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | | | - Laurent F Thomas
- Department of Clinical and Molecular Medicine, NTNU - Norwegian University of Science and Technology, Trondheim, Norway
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU - Norwegian University of Science and Technology, Trondheim, Norway
- BioCore - Bioinformatics Core Facility, NTNU - Norwegian University of Science and Technology, Trondheim, Norway
- Clinic of Laboratory Medicine, St.Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Tanel Traks
- Department of Dermatology and Venereology, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
| | - Steffen Uebe
- Institute of Human Genetics, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Gunter Assmann
- RUB University Hospital JWK Minden, Department of Rheumatology, Minden, Germany
- Jose-Carreras Centrum for Immuno- and Gene Therapy, University of Saarland Medical School, Homburg, Germany
| | - David Baudry
- St John's Institute of Dermatology, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - Frank Behrens
- Division of Translational Rheumatology, Immunology - Inflammation Medicine, University Hospital, Goethe University, Frankfurt am Main, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Frankfurt am Main, Germany
- Fraunhofer Cluster of Excellence Immune-mediated Diseases CIMD, Frankfurt am Main, Germany
- Division of Rheumatology, University Hospital, Goethe University, Frankfurt am Main, Germany
| | - Allison C Billi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Matthew A Brown
- Department of Medical & Molecular Genetics, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK
- Genomics England, Canary Wharf, London, UK
| | - Harald Burkhardt
- Division of Rheumatology, University Hospital, Goethe University, Frankfurt am Main, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Frankfurt am Main, Germany
- Fraunhofer Cluster of Excellence Immune-mediated Diseases CIMD, Frankfurt am Main, Germany
| | - Francesca Capon
- Department of Medical & Molecular Genetics, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - Raymond Chung
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, Denmark Hill, Camberwell, London, UK
- National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley Hospital, London, UK
| | - Charles J Curtis
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, Denmark Hill, Camberwell, London, UK
- National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley Hospital, London, UK
| | - Michael Duckworth
- St John's Institute of Dermatology, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - Eva Ellinghaus
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Oliver FitzGerald
- UCD School of Medicine and Medical Sciences and Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Ireland
| | - Sascha Gerdes
- Department of Dermatology, Venereology and Allergy, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Christopher E M Griffiths
- Centre for Dermatology Research, University of Manchester, NIHR Manchester Biomedical Research Centre, Manchester, UK
- St John's Institute of Dermatology, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK
- Department of Dermatology, King's College Hospital NHS Foundation Trust, London, UK
| | | | - Philip Helliwell
- National Institute for Health and Care Research (NIHR) Leeds Biomedical Research Centre, Leeds Teaching Hospitals Trust, UK
- Leeds Institute of Rheumatic and Musculoskeletal Disease, University of Leeds, UK
| | - Pauline Ho
- Centre for Genetics and Genomics Versus Arthritis, The University of Manchester, Manchester, UK
- National Institute for Health and Care Research (NIHR) Manchester Biomedical Research Centre, The University of Manchester, Manchester, UK
- The Kellgren Centre for Rheumatology, Manchester University NHS Foundation Trust, Manchester, UK
| | - Per Hoffmann
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Oddgeir L Holmen
- HUNT Research Centre, Department of Public Health and Nursing, NTNU - Norwegian University of Science and Technology, Levanger, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Zhi-Ming Huang
- Deparment of Dermatology, University of California San Francisco, San Francisco, CA, USA
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU - Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, NTNU - Norwegian University of Science and Technology, Levanger, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Deepak Jadon
- Department of Medicine, University of Cambridge, Cambridge, UK
| | - Michaela Köhm
- Division of Translational Rheumatology, Immunology - Inflammation Medicine, University Hospital, Goethe University, Frankfurt am Main, Germany
- Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Frankfurt am Main, Germany
- Fraunhofer Cluster of Excellence Immune-mediated Diseases CIMD, Frankfurt am Main, Germany
- Division of Rheumatology, University Hospital, Goethe University, Frankfurt am Main, Germany
| | - Cornelia Kraus
- Institute of Human Genetics, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Céline Lamacchia
- Division of Rheumatology, Geneva University Hospital, Geneva, Switzerland
| | - Sang Hyuck Lee
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, Denmark Hill, Camberwell, London, UK
- National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley Hospital, London, UK
| | - Feiyang Ma
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Satveer K Mahil
- St John's Institute of Dermatology, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK
- St John's Institute of Dermatology, Guy's and St Thomas' National Health Service (NHS) Foundation Trust, London, UK
| | - Neil McHugh
- Royal National Hospital for Rheumatic Diseases and Dept Pharmacy and Pharmacology, University of Bath, UK
| | - Ross McManus
- Department of Clinical Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Ireland
| | - Ellen H Modalsli
- Department of Clinical and Molecular Medicine, NTNU - Norwegian University of Science and Technology, Trondheim, Norway
- Department of Dermatology, Clinic of Orthopedy, Rheumatology and Dermatology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Michael J Nissen
- Division of Rheumatology, Geneva University Hospital, Geneva, Switzerland
| | - Markus Nöthen
- Institute of Human Genetics, University of Bonn, School of Medicine & University Hospital Bonn, Bonn, Germany
| | - Vinzenz Oji
- Department of Dermatology, University of Münster, Münster, Germany
| | - Jorge R Oksenberg
- Weill Institute for Neurosciences, Department of Neurology, University of California, San Francisco, CA, USA
| | - Matthew T Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | | | - Andreas Ramming
- Department of Internal Medicine 3, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Ulmenweg 18, 91054, Erlangen, Germany
- Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander-University Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany
| | - Jürgen Rech
- Department of Internal Medicine 3, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Ulmenweg 18, 91054, Erlangen, Germany
- Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander-University Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany
| | - Cheryl Rosen
- Division of Dermatology, Toronto Western Hospital, University of Toronto, Toronto, Ontario, Canada
| | - Mrinal K Sarkar
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Georg Schett
- Department of Internal Medicine 3, Friedrich-Alexander-University Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Ulmenweg 18, 91054, Erlangen, Germany
- Deutsches Zentrum Immuntherapie (DZI), Friedrich-Alexander-University Erlangen-Nürnberg and Universitätsklinikum Erlangen, Erlangen, Germany
| | - Börge Schmidt
- Institute of Medical Informatics, Biometry and Epidemiology, University Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Trilokraj Tejasvi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
- Ann Arbor Veterans Affairs Hospital, Ann Arbor, MI, USA
| | - Heiko Traupe
- Department of Dermatology, University of Münster, Münster, Germany
| | - John J Voorhees
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Eike Matthias Wacker
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Richard B Warren
- Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, UK
- Centre for Dermatology Research, Salford Royal Hospital, Northern Care Alliance NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, M6 8HD, UK
| | - Rachael Wasikowski
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Stephan Weidinger
- Department of Dermatology, Venereology and Allergy, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Xiaoquan Wen
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Zhaolin Zhang
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Anne Barton
- Centre for Genetics and Genomics Versus Arthritis, The University of Manchester, Manchester, UK
- National Institute for Health and Care Research (NIHR) Manchester Biomedical Research Centre, The University of Manchester, Manchester, UK
- The Kellgren Centre for Rheumatology, Manchester University NHS Foundation Trust, Manchester, UK
| | - Vinod Chandran
- Schroeder Arthritis Institute, Krembil Research Institute, and Toronto Western Hospital, University Health Network and University of Toronto, Toronto, Ontario, Canada
| | - Tõnu Esko
- Institute of Genomics, University of Tartu, Tartu, Estonia
| | - John Foerster
- College of Medicine, Dentistry, and Nursing, University of Dundee, Dundee, UK
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Dafna D Gladman
- Schroeder Arthritis Institute, Krembil Research Institute, and Toronto Western Hospital, University Health Network and University of Toronto, Toronto, Ontario, Canada
| | - Johann E Gudjonsson
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Wayne Gulliver
- Newlab Clinical Research Inc, St. John's, NL, Canada
- Department of Dermatology, Discipline of Medicine, Faculty of Medicine, Memorial University of Newfoundland, St. John's, NL, Canada
| | - Ulrike Hüffmeier
- Institute of Human Genetics, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Külli Kingo
- Department of Dermatology and Venereology, Institute of Clinical Medicine, University of Tartu, Tartu, Estonia
- Dermatology Clinic, Tartu University Hospital, Tartu, Estonia
| | - Sulev Kõks
- Perron Institute for Neurological and Translational Science, Nedlands, WA 6009, Australia
- Centre for Molecular Medicine and Innovative Therapeutics, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia
| | - Wilson Liao
- Deparment of Dermatology, University of California San Francisco, San Francisco, CA, USA
| | - Mari Løset
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU - Norwegian University of Science and Technology, Trondheim, Norway
- Department of Dermatology, Clinic of Orthopedy, Rheumatology and Dermatology, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Reedik Mägi
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Rajan P Nair
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Proton Rahman
- Memorial University of Newfoundland, St. John's, NL, Canada
| | - André Reis
- Institute of Human Genetics, Universitätsklinikum Erlangen, FAU Erlangen-Nürnberg, Erlangen, Germany
| | - Catherine H Smith
- St John's Institute of Dermatology, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK
- St John's Institute of Dermatology, Guy's and St Thomas' National Health Service (NHS) Foundation Trust, London, UK
| | - Paola Di Meglio
- St John's Institute of Dermatology, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - Jonathan N Barker
- St John's Institute of Dermatology, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK
- St John's Institute of Dermatology, Guy's and St Thomas' National Health Service (NHS) Foundation Trust, London, UK
| | - Lam C Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Michael A Simpson
- Department of Medical & Molecular Genetics, School of Basic & Medical Biosciences, Faculty of Life Sciences & Medicine, King's College London, London, UK
| | - James T Elder
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
- Ann Arbor Veterans Affairs Hospital, Ann Arbor, MI, USA
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6
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Wang YN, Gan T, Qu S, Xu LL, Hu Y, Liu LJ, Shi SF, Lv JC, Tsoi LC, Patrick MT, He K, Berthier CC, Xu HJ, Zhou XJ, Zhang H. MTMR3 risk alleles enhance Toll Like Receptor 9-induced IgA immunity in IgA nephropathy. Kidney Int 2023; 104:562-576. [PMID: 37414396 DOI: 10.1016/j.kint.2023.06.018] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 05/29/2023] [Accepted: 06/15/2023] [Indexed: 07/08/2023]
Abstract
Multiple genome-wide association studies (GWASs) have reproducibly identified the MTMR3/HORMAD2/LIF/OSM locus to be associated with IgA nephropathy (IgAN). However, the causal variant(s), implicated gene(s), and altered mechanisms remain poorly understood. Here, we performed fine-mapping analyses based on GWAS datasets encompassing 2762 IgAN cases and 5803 control individuals, and identified rs4823074 as the candidate causal variant that intersects the MTMR3 promoter in B-lymphoblastoid cells. Mendelian randomization studies suggested the risk allele may modulate disease susceptibility by affecting serum IgA levels through increased MTMR3 expression. Consistently, elevated MTMR3 expression in peripheral blood mononuclear cells was observed in patients with IgAN. Further mechanistic studies in vitro demonstrated that MTMR3 increased IgA production dependent upon its phosphatidylinositol 3-phosphate binding domain. Moreover, our study provided the in vivo functional evidence that Mtmr3-/- mice exhibited defective Toll Like Receptor 9-induced IgA production, glomerular IgA deposition, as well as mesangial cell proliferation. RNA-seq and pathway analyses showed that MTMR3 deficiency resulted in an impaired intestinal immune network for IgA production. Thus, our results support the role of MTMR3 in IgAN pathogenesis by enhancing Toll Like Receptor 9-induced IgA immunity.
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Affiliation(s)
- Yan-Na Wang
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China
| | - Ting Gan
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China
| | - Shu Qu
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China
| | - Lin-Lin Xu
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China
| | - Yong Hu
- Beijing Institute of Biotechnology, Beijing, People's Republic of China
| | - Li-Jun Liu
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China
| | - Su-Fang Shi
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China
| | - Ji-Cheng Lv
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China
| | - Lam C Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA; Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
| | - Matthew T Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA; Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
| | - Kevin He
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA; Kidney Epidemiology and Cost Center, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Celine C Berthier
- Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Hu-Ji Xu
- Department of Rheumatology and Immunology, Shanghai Changzheng Hospital, The Second Military Medical University, Shanghai, People's Republic of China
| | - Xu-Jie Zhou
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China.
| | - Hong Zhang
- Renal Division, Department of Medicine, Peking University First Hospital, Beijing, People's Republic of China; Peking University Institute of Nephrology, Peking University, Beijing, People's Republic of China; Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People's Republic of China; Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People's Republic of China; State Key Laboratory of Vascular Homeostasis and Remodeling, Peking University, Beijing, People's Republic of China.
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7
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Billi AC, Wasikowski R, Ma F, Yalavarthi S, Hoy CK, Zuo Y, Patrick MT, Shah N, Parker C, Aaronson C, Harbaugh A, Lucido MF, Shedden K, Rao K, IglayReger HB, Burant CF, Kahlenberg JM, Tsoi LC, Gudjonsson JE, Knight JS, Kanthi Y. Key patient demographics shape innate immune topography in noncritical hypoxic COVID-19 pneumonia. JCI Insight 2023; 8:e166110. [PMID: 37606044 PMCID: PMC10543737 DOI: 10.1172/jci.insight.166110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 07/11/2023] [Indexed: 08/23/2023] Open
Abstract
Risk of severe disease and death due to COVID-19 is increased in certain patient demographic groups, including those of advanced age, male sex, and obese body mass index. Investigations of the biological variations that contribute to this risk have been hampered by heterogeneous severity, with immunologic features of critical disease potentially obscuring differences between risk groups. To examine immune heterogeneity related to demographic risk factors, we enrolled 38 patients hospitalized with clinically homogeneous COVID-19 pneumonia - defined as oxygen saturation less than 94% on room air without respiratory failure, septic shock, or multiple organ dysfunction - and performed single-cell RNA-Seq of leukocytes collected at admission. Examination of individual risk factors identified strong shifts within neutrophil and monocyte/dendritic cell (Mo/DC) compartments, revealing altered immune cell type-specific responses in higher risk COVID-19 patient subgroups. Specifically, we found transcriptional evidence of altered neutrophil maturation in aged versus young patients and enhanced cytokine responses in Mo/DCs of male versus female patients. Such innate immune cell alterations may contribute to outcome differences linked to these risk factors. They also highlight the importance of diverse patient cohorts in studies of therapies targeting the immune response in COVID-19.
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Affiliation(s)
| | | | - Feiyang Ma
- Division of Rheumatology, Department of Internal Medicine
| | | | - Claire K. Hoy
- Division of Rheumatology, Department of Internal Medicine
| | - Yu Zuo
- Division of Rheumatology, Department of Internal Medicine
| | | | - Neha Shah
- Division of Cardiovascular Medicine, Department of Internal Medicine
| | | | - Chad Aaronson
- Division of Rheumatology, Department of Internal Medicine
| | | | | | - Kerby Shedden
- Division of Rheumatology, Department of Internal Medicine
| | - Krishna Rao
- Division of Infectious Disease, Department of Internal Medicine
| | | | - Charles F. Burant
- A. Alfred Taubman Medical Research Institute
- Department of Internal Medicine
- Department of Nutritional Sciences
| | | | - Lam C. Tsoi
- Department of Dermatology
- Department of Computational Medicine and Bioinformatics, and
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | | | | | - Yogendra Kanthi
- Division of Cardiovascular Medicine, Department of Internal Medicine
- Laboratory of Vascular Thrombosis and Inflammation, National Heart, Lung, and Blood Institute, NIH, Bethesda, Maryland, USA
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8
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Patrick MT, Nair RP, He K, Stuart PE, Billi AC, Zhou X, Gudjonsson JE, Oksenberg JR, Elder JT, Tsoi LC. Shared Genetic Risk Factors for Multiple Sclerosis/Psoriasis Suggest Involvement of Interleukin-17 and Janus Kinase-Signal Transducers and Activators of Transcription Signaling. Ann Neurol 2023; 94:384-397. [PMID: 37127916 PMCID: PMC10524664 DOI: 10.1002/ana.26672] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 04/24/2023] [Accepted: 04/27/2023] [Indexed: 05/03/2023]
Abstract
OBJECTIVE Psoriasis and multiple sclerosis (MS) are complex immune diseases that are mediated by T cells and share multiple comorbidities. Previous studies have suggested psoriatic patients are at higher risk of MS; however, causal relationships between the two conditions remain unclear. Through epidemiology and genetics, we provide a comprehensive understanding of the relationship, and share molecular factors between psoriasis and MS. METHODS We used logistic regression, trans-disease meta-analysis and Mendelian randomization. Medical claims data were included from 30 million patients, including 141,544 with MS and 742,919 with psoriasis. We used genome-wide association study summary statistics from 11,024 psoriatic, 14,802 MS cases, and 43,039 controls for trans-disease meta-analysis, with additional summary statistics from 5 million individuals for Mendelian randomization. RESULTS Psoriatic patients have a significantly higher risk of MS (4,637 patients with both diseases; odds ratio [OR] 1.07, p = 1.2 × 10-5 ) after controlling for potential confounders. Using inverse variance and equally weighted trans-disease meta-analysis, we revealed >20 shared and opposing (direction of effect) genetic loci outside the major histocompatibility complex that showed significant genetic colocalization (in COLOC and COLOC-SuSiE v5.1.0). Co-expression analysis of genes from these loci further identified distinct clusters that were enriched among pathways for interleukin-17/tumor necrosis factor-α (OR >39, p < 1.6 × 10-3 ) and Janus kinase-signal transducers and activators of transcription (OR 35, p = 1.1 × 10-5 ), including genes, such as TNFAIP3, TYK2, and TNFRSF1A. Mendelian randomization found psoriasis as an exposure has a significant causal effect on MS (OR 1.04, p = 5.8 × 10-3 ), independent of type 1 diabetes (OR 1.05, p = 4.3 × 10-7 ), type 2 diabetes (OR 1.08, p = 2.3 × 10-3 ), inflammatory bowel disease (OR 1.11, p = 1.6 × 10-11 ), and vitamin D level (OR 0.75, p = 9.4 × 10-3 ). INTERPRETATION By investigating the shared genetics of psoriasis and MS, along with their modifiable risk factors, our findings will advance innovations in treatment for patients suffering from comorbidities. ANN NEUROL 2023;94:384-397.
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Affiliation(s)
- Matthew T. Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Rajan P. Nair
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Kevin He
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Philip E. Stuart
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Allison C. Billi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Xiang Zhou
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Johann E. Gudjonsson
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Jorge R. Oksenberg
- Department of Neurology, University of California, San Francisco, California, United States of America
| | - James T. Elder
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
| | - Lam C. Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, United States of America
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, Michigan, United States of America
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9
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Zhou XJ, Su T, Xie J, Xie QH, Wang LZ, Hu Y, Chen G, Jia Y, Huang JW, Li G, Liu Y, Yu XJ, Nath SK, Tsoi LC, Patrick MT, Berthier CC, Liu G, Wang SX, Xu H, Chen N, Hao CM, Zhang H, Yang L. Genome-Wide Association Study in Acute Tubulointerstitial Nephritis. J Am Soc Nephrol 2023; 34:895-908. [PMID: 36749126 PMCID: PMC10125656 DOI: 10.1681/asn.0000000000000091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 12/28/2022] [Indexed: 02/08/2023] Open
Abstract
SIGNIFICANCE STATEMENT Polymorphisms of HLA genes may confer susceptibility to acute tubulointerstitial nephritis (ATIN), but small sample sizes and candidate gene design have hindered their investigation. The first genome-wide association study of ATIN identified two significant loci, risk haplotype DRB1*14-DQA1*0101-DQB1*0503 (DR14 serotype) and protective haplotype DRB1*1501-DQA1*0102-DQB1*0602 (DR15 serotype), with amino acid position 60 in the peptide-binding groove P10 of HLA-DR β 1 key. Risk alleles were shared among different causes of ATIN and HLA genotypes associated with kidney injury and immune therapy response. HLA alleles showed the strongest association. The findings suggest that a genetically conferred risk of immune dysregulation is part of the pathogenesis of ATIN. BACKGROUND Acute tubulointerstitial nephritis (ATIN) is a rare immune-related disease, accounting for approximately 10% of patients with unexplained AKI. Previous elucidation of the relationship between genetic factors that contribute to its pathogenesis was hampered because of small sample sizes and candidate gene design. METHODS We undertook the first two-stage genome-wide association study and meta-analysis involving 544 kidney biopsy-defined patients with ATIN and 2346 controls of Chinese ancestry. We conducted statistical fine-mapping analysis, provided functional annotations of significant variants, estimated single nucleotide polymorphism (SNP)-based heritability, and checked genotype and subphenotype correlations. RESULTS Two genome-wide significant loci, rs35087390 of HLA-DQA1 ( P =3.01×10 -39 ) on 6p21.32 and rs2417771 of PLEKHA5 on 12p12.3 ( P =2.14×10 -8 ), emerged from the analysis. HLA imputation using two reference panels suggested that HLA-DRB1*14 mainly drives the HLA risk association . HLA-DRB1 residue 60 belonging to pocket P10 was the key amino acid position. The SNP-based heritability estimates with and without the HLA locus were 20.43% and 10.35%, respectively. Different clinical subphenotypes (drug-related or tubulointerstitial nephritis and uveitis syndrome) seemed to share the same risk alleles. However, the HLA risk genotype was associated with disease severity and response rate to immunosuppressive therapy. CONCLUSIONS We identified two candidate genome regions associated with susceptibility to ATIN. The findings suggest that a genetically conferred risk of immune dysregulation is involved in the pathogenesis of ATIN.
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Affiliation(s)
- Xu-Jie Zhou
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Tao Su
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Jingyuan Xie
- Department of Nephrology, Institute of Nephrology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qiong-Hong Xie
- Division of Nephrology, Huashan Hospital, Fudan University, Shanghai, China
| | - Li-Zhong Wang
- WeGene, Shenzhen Zaozhidao Technology Co., Ltd., Shenzhen, China
- Human Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, China
- Shenzhen WeGene Clinical Laboratory, Shenzhen, China
| | - Yong Hu
- Beijing Institute of Biotechnology, Beijing, China
| | - Gang Chen
- WeGene, Shenzhen Zaozhidao Technology Co., Ltd., Shenzhen, China
- Human Provincial Key Lab on Bioinformatics, School of Computer Science and Engineering, Central South University, Changsha, China
- Shenzhen WeGene Clinical Laboratory, Shenzhen, China
| | - Yan Jia
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Jun-Wen Huang
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Gui Li
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Yang Liu
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Xiao-Juan Yu
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Swapan K. Nath
- Arthritis and Clinical Immunology Program, Oklahoma Medical Research Foundation, Oklahoma City, Oklahoma
| | - Lam C. Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan
| | - Matthew T. Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan
| | - Celine C. Berthier
- Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Gang Liu
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Su-Xia Wang
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Huji Xu
- Department of Rheumatology and Immunology, Shanghai Changzheng Hospital, Second Military Medical University, Shanghai, China
- Peking-Tsinghua Center for Life Sciences, Tsinghua University, Beijing, China
- School of Clinical Medicine, Tsinghua University, Beijing, China
| | - Nan Chen
- Department of Nephrology, Institute of Nephrology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Chuan-Ming Hao
- Division of Nephrology, Huashan Hospital, Fudan University, Shanghai, China
| | - Hong Zhang
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
| | - Li Yang
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, China
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10
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Khunsriraksakul C, Li Q, Markus H, Patrick MT, Sauteraud R, McGuire D, Wang X, Wang C, Wang L, Chen S, Shenoy G, Li B, Zhong X, Olsen NJ, Carrel L, Tsoi LC, Jiang B, Liu DJ. Multi-ancestry and multi-trait genome-wide association meta-analyses inform clinical risk prediction for systemic lupus erythematosus. Nat Commun 2023; 14:668. [PMID: 36750564 PMCID: PMC9905560 DOI: 10.1038/s41467-023-36306-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 01/25/2023] [Indexed: 02/09/2023] Open
Abstract
Systemic lupus erythematosus is a heritable autoimmune disease that predominantly affects young women. To improve our understanding of genetic etiology, we conduct multi-ancestry and multi-trait meta-analysis of genome-wide association studies, encompassing 12 systemic lupus erythematosus cohorts from 3 different ancestries and 10 genetically correlated autoimmune diseases, and identify 16 novel loci. We also perform transcriptome-wide association studies, computational drug repurposing analysis, and cell type enrichment analysis. We discover putative drug classes, including a histone deacetylase inhibitor that could be repurposed to treat lupus. We also identify multiple cell types enriched with putative target genes, such as non-classical monocytes and B cells, which may be targeted for future therapeutics. Using this newly assembled result, we further construct polygenic risk score models and demonstrate that integrating polygenic risk score with clinical lab biomarkers improves the diagnostic accuracy of systemic lupus erythematosus using the Vanderbilt BioVU and Michigan Genomics Initiative biobanks.
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Affiliation(s)
- Chachrit Khunsriraksakul
- Program in Bioinformatics and Genomics, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA.,Institute for Personalized Medicine, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Qinmengge Li
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
| | - Havell Markus
- Program in Bioinformatics and Genomics, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA.,Institute for Personalized Medicine, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Matthew T Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
| | - Renan Sauteraud
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Daniel McGuire
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Xingyan Wang
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Chen Wang
- Program in Bioinformatics and Genomics, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Lida Wang
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Siyuan Chen
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Ganesh Shenoy
- Department of Neurosurgery, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Bingshan Li
- Department of Molecular Physiology & Biophysics, Vanderbilt University, Nashville, TN, 37235, USA
| | - Xue Zhong
- Department of Medicine, Division of Genetic Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Nancy J Olsen
- Department of Medicine, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Laura Carrel
- Department of Biochemistry and Molecular Biology, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Lam C Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, 48109, USA
| | - Bibo Jiang
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA
| | - Dajiang J Liu
- Program in Bioinformatics and Genomics, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA. .,Institute for Personalized Medicine, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA. .,Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, 17033, USA.
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11
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Patrick MT, Li Q, Wasikowski R, Mehta N, Gudjonsson JE, Elder JT, Zhou X, Tsoi LC. Shared genetic risk factors and causal association between psoriasis and coronary artery disease. Nat Commun 2022; 13:6565. [PMID: 36323703 PMCID: PMC9630428 DOI: 10.1038/s41467-022-34323-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 10/20/2022] [Indexed: 11/06/2022] Open
Abstract
Psoriasis and coronary artery disease (CAD) are related comorbidities that are well established, but whether a genetic basis underlies this is not well studied. We apply trans-disease meta-analysis to 11,024 psoriasis and 60,801 CAD cases, along with their associated controls, identifying one opposing and three shared genetic loci, which are confirmed through colocalization analysis. Combining results from Bayesian credible interval analysis with independent information from genomic, epigenomic, and spatial chromatin organization, we prioritize genes (including IFIH1 and IL23A) that have implications for common molecular mechanisms involved in psoriasis and CAD inflammatory signaling. Chronic systemic inflammation has been associated with CAD and myocardial infarction, and Mendelian randomization analysis finds that CAD as an exposure can have a significant causal effect on psoriasis (OR = 1.11; p = 3×10-6) following adjustment for BMI and waist-hip ratio. Together, these findings suggest that systemic inflammation which causes CAD can increase the risk of psoriasis.
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Affiliation(s)
- Matthew T Patrick
- Department of Dermatology, Michigan Medicine, University of Michigan, Michigan, MI, USA
| | - Qinmengge Li
- Department of Biostatistics, School of Public Health, University of Michigan, Michigan, MI, USA
| | - Rachael Wasikowski
- Department of Dermatology, Michigan Medicine, University of Michigan, Michigan, MI, USA
| | - Nehal Mehta
- Section of Inflammation and Cardiometabolic Disease, National Heart, Lung, and Blood Institute, National Institutes of Health, Michigan, MD, USA
| | - Johann E Gudjonsson
- Department of Dermatology, Michigan Medicine, University of Michigan, Michigan, MI, USA
| | - James T Elder
- Department of Dermatology, Michigan Medicine, University of Michigan, Michigan, MI, USA
| | - Xiang Zhou
- Department of Biostatistics, School of Public Health, University of Michigan, Michigan, MI, USA
| | - Lam C Tsoi
- Department of Dermatology, Michigan Medicine, University of Michigan, Michigan, MI, USA.
- Department of Biostatistics, School of Public Health, University of Michigan, Michigan, MI, USA.
- Department of Computational Medicine and Bioinformatics, Michigan Medicine, University of Michigan, Michigan, MI, USA.
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12
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Wei J, Zhu J, Xu H, Zhou D, Elder JT, Tsoi LC, Patrick MT, Li Y. Alcohol consumption and smoking in relation to psoriasis: a Mendelian randomization study. Br J Dermatol 2022; 187:684-691. [PMID: 35764530 DOI: 10.1111/bjd.21718] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 06/14/2022] [Accepted: 06/26/2022] [Indexed: 11/30/2022]
Abstract
BACKGROUND Alcohol consumption and smoking have been reported to be associated with psoriasis risk. However, a conclusion with high-quality evidence of causality could not be easily drawn from regular observational studies. OBJECTIVES This study aims to assess the causal associations of alcohol consumption and smoking with psoriasis. METHODS Genome-wide association study (GWAS) summary-level data for alcohol consumption (N = 941 280), smoking initiation (N = 1 232 091), cigarettes per day (N = 337 334) and smoking cessation (N = 547 219) was obtained from the GSCAN consortium (Sequencing Consortium of Alcohol and Nicotine use). The GWAS results for lifetime smoking (N = 462 690) were obtained from the UK Biobank samples. Summary statistics for psoriasis were obtained from a recent GWAS meta-analysis of eight cohorts comprising 19 032 cases and 286 769 controls and the FinnGen consortium, comprising 4510 cases and 212 242 controls. Linkage disequilibrium score regression was applied to compute the genetic correlation. Bidirectional Mendelian randomization (MR) analyses were conducted to determine casual direction using independent genetic variants that reached genome-wide significance (P < 5 × 10-8 ). RESULTS There were genetic correlations between smoking and psoriasis. MR revealed a causal effect of smoking initiation [odds ratio (OR) 1·46, 95% confidence interval (CI) 1·32-1·60, P = 6·24E-14], cigarettes per day (OR 1·38, 95% CI 1·13-1·67, P = 0·001) and lifetime smoking (OR 1·96, 95% CI 1·41-2·73, P = 7·32E-05) on psoriasis. Additionally, a suggestive causal effect of smoking cessation on psoriasis was observed (OR 1·39, 95% CI 1·07-1·79, P = 0·012). We found no causal relationship between alcohol consumption and psoriasis (P = 0·379). The reverse associations were not statistically significant. CONCLUSIONS Our findings provide causal evidence for the effects of smoking on psoriasis risk. What is already known about this topic? Alcohol consumption and smoking have been reported to be associated with psoriasis risk. Whether alcohol consumption and smoking have a causal effect on psoriasis risk remains unclear. What does this study add? This Mendelian randomization study shows a causal association between smoking, but not alcohol consumption, and the risk of developing psoriasis. Restricting smoking could be helpful in reducing the burden of psoriasis.
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Affiliation(s)
- Jiahe Wei
- Department of Epidemiology and Health Statistics, School of Public Health, Hangzhou Medical College, Hangzhou, China
| | - Jiahao Zhu
- Department of Epidemiology and Health Statistics, School of Public Health, Hangzhou Medical College, Hangzhou, China
| | - Huiqing Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Hangzhou Medical College, Hangzhou, China
| | - Dan Zhou
- School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.,Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - James T Elder
- Department of Dermatology, University of Michigan, Ann Arbor, MI, USA.,Ann Arbor Veterans Affairs Hospital, Ann Arbor, Michigan, USA
| | - Lam C Tsoi
- Department of Dermatology, University of Michigan, Ann Arbor, MI, USA.,Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA
| | - Matthew T Patrick
- Department of Dermatology, University of Michigan, Ann Arbor, MI, USA
| | - Yingjun Li
- Department of Epidemiology and Health Statistics, School of Public Health, Hangzhou Medical College, Hangzhou, China
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13
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Patrick MT, Bardhi R, Zhou W, Elder JT, Gudjonsson JE, Tsoi LC. Enhanced rare disease mapping for phenome-wide genetic association in the UK Biobank. Genome Med 2022; 14:85. [PMID: 35945607 PMCID: PMC9364550 DOI: 10.1186/s13073-022-01094-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 07/21/2022] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Rare diseases collectively affect up to 10% of the population, but often lack effective treatment, and typically little is known about their pathophysiology. Major challenges include suboptimal phenotype mapping and limited statistical power. Population biobanks, such as the UK Biobank, recruit many individuals who can be affected by rare diseases; however, investigation into their utility for rare disease research remains limited. We hypothesized the UK Biobank can be used as a unique population assay for rare diseases in the general population. METHODS We constructed a consensus mapping between ICD-10 codes and ORPHA codes for rare diseases, then identified individuals with each rare condition in the UK Biobank, and investigated their age at recruitment, sex bias, and comorbidity distributions. Using exome sequencing data from 167,246 individuals of European ancestry, we performed genetic association controlling for case/control imbalance (SAIGE) to identify potential rare pathogenic variants for each disease. RESULTS Using our mapping approach, we identified and characterized 420 rare diseases affecting 23,575 individuals in the UK Biobank. Significant genetic associations included JAK2 V617F for immune thrombocytopenic purpura (p = 1.24 × 10-13) and a novel CALR loss of function variant for essential thrombocythemia (p = 1.59 × 10-13). We constructed an interactive resource highlighting demographic information ( http://www-personal.umich.edu/~mattpat/rareDiseases.html ) and demonstrate transferability by applying our mapping to a medical claims database. CONCLUSIONS Enhanced disease mapping and increased power from population biobanks can elucidate the demographics and genetic associations for rare diseases.
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Affiliation(s)
- Matthew T Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA.
| | - Redina Bardhi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA.,School of Medicine, Wayne State University, Detroit, MI, USA
| | - Wei Zhou
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA.,Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA.,Stanley Center for Psychiatric Research, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - James T Elder
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Johann E Gudjonsson
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Lam C Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA. .,Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA. .,Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
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14
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Jamerson TA, Li Q, Sreeskandarajan S, Budunova IV, He Z, Kang J, Gudjonsson JE, Patrick MT, Tsoi LC. Roles Played by Stress-Induced Pathways in Driving Ethnic Heterogeneity for Inflammatory Skin Diseases. Front Immunol 2022; 13:845655. [PMID: 35572606 PMCID: PMC9095822 DOI: 10.3389/fimmu.2022.845655] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 03/23/2022] [Indexed: 12/25/2022] Open
Abstract
Immune-mediated skin conditions (IMSCs) are a diverse group of autoimmune diseases associated with significant disease burden. Atopic dermatitis and psoriasis are among the most common IMSCs in the United States and have disproportionate impact on racial and ethnic minorities. African American patients are more likely to develop atopic dermatitis compared to their European American counterparts; and despite lower prevalence of psoriasis among this group, African American patients can suffer from more extensive disease involvement, significant post-inflammatory changes, and a decreased quality of life. While recent studies have been focused on understanding the heterogeneity underlying disease mechanisms and genetic factors at play, little emphasis has been put on the effect of psychosocial or psychological stress on immune pathways, and how these factors contribute to differences in clinical severity, prevalence, and treatment response across ethnic groups. In this review, we explore the heterogeneity of atopic dermatitis and psoriasis between African American and European American patients by summarizing epidemiological studies, addressing potential molecular and environmental factors, with a focus on the intersection between stress and inflammatory pathways.
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Affiliation(s)
- Taylor A. Jamerson
- Department of Dermatology, Michigan Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Qinmengge Li
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | | | - Irina V. Budunova
- Department of Dermatology, Northwestern Medicine, Northwestern University, Chicago, IL, United States,Department of Urology, Northwestern Medicine, Northwestern University, Chicago, IL, United States
| | - Zhi He
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Jian Kang
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Johann E. Gudjonsson
- Department of Dermatology, Michigan Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Matthew T. Patrick
- Department of Dermatology, Michigan Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Lam C. Tsoi
- Department of Dermatology, Michigan Medicine, University of Michigan, Ann Arbor, MI, United States,Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States,Department of Computational Medicine and Bioinformatics, Michigan Medicine, University of Michigan, Ann Arbor, MI, United States,*Correspondence: Lam C. Tsoi,
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15
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Verhaegen ME, Harms PW, Van Goor JJ, Arche J, Patrick MT, Wilbert D, Zabawa H, Grachtchouk M, Liu CJ, Hu K, Kelly MC, Chen P, Saunders TL, Weidinger S, Syu LJ, Runge JS, Gudjonsson JE, Wong SY, Brownell I, Cieslik M, Udager AM, Chinnaiyan AM, Tsoi LC, Dlugosz AA. Direct cellular reprogramming enables development of viral T antigen-driven Merkel cell carcinoma in mice. J Clin Invest 2022; 132:152069. [PMID: 35143422 PMCID: PMC8970662 DOI: 10.1172/jci152069] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2021] [Accepted: 02/08/2022] [Indexed: 11/17/2022] Open
Abstract
Merkel cell carcinoma (MCC) is an aggressive neuroendocrine skin cancer that frequently carries an integrated Merkel cell polyomavirus (MCPyV) genome and expresses viral transforming antigens (TAgs). MCC tumor cells also express signature genes detected in skin-resident, postmitotic Merkel cells, including atonal bHLH transcription factor 1 (ATOH1), which is required for Merkel cell development from epidermal progenitors. We now report the use of in vivo cellular reprogramming, using ATOH1, to drive MCC development from murine epidermis. We generated mice that conditionally expressed MCPyV TAgs and ATOH1 in epidermal cells, yielding microscopic collections of proliferating MCC-like cells arising from hair follicles. Immunostaining of these nascent tumors revealed p53 accumulation and apoptosis, and targeted deletion of transformation related protein 53 (Trp53) led to development of gross skin tumors with classic MCC histology and marker expression. Global transcriptome analysis confirmed the close similarity of mouse and human MCCs, and hierarchical clustering showed conserved upregulation of signature genes. Our data establish that expression of MCPyV TAgs in ATOH1-reprogrammed epidermal cells and their neuroendocrine progeny initiates hair follicle–derived MCC tumorigenesis in adult mice. Moreover, progression to full-blown MCC in this model requires loss of p53, mimicking the functional inhibition of p53 reported in human MCPyV-positive MCCs.
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Affiliation(s)
- Monique E Verhaegen
- Department of Dermatology, University of Michigan, Ann Arbor, United States of America
| | - Paul W Harms
- Department of Dermatology, University of Michigan, Ann Arbor, United States of America
| | - Julia J Van Goor
- Department of Dermatology, University of Michigan, Ann Arbor, United States of America
| | - Jacob Arche
- Department of Dermatology, University of Michigan, Ann Arbor, United States of America
| | - Matthew T Patrick
- Department of Dermatology, University of Michigan, Ann Arbor, United States of America
| | - Dawn Wilbert
- Department of Dermatology, University of Michigan, Ann Arbor, United States of America
| | - Haley Zabawa
- Department of Dermatology, University of Michigan, Ann Arbor, United States of America
| | - Marina Grachtchouk
- Department of Dermatology, University of Michigan, Ann Arbor, United States of America
| | - Chia-Jen Liu
- Department of Pathology, University of Michigan, Ann Arbor, United States of America
| | - Kevin Hu
- Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, United States of America
| | - Michael C Kelly
- Department of Cell Biology, Emory University School of Medicine, Atlanta, United States of America
| | - Ping Chen
- Department of Cell Biology, Emory University School of Medicine, Atlanta, United States of America
| | - Thomas L Saunders
- Department of Internal Medicine, University of Michigan, Ann Arbor, United States of America
| | - Stephan Weidinger
- Department of Dermatology and Allergy, University Hospital Schleswig-Holstein, Kiel, Germany
| | - Li-Jyun Syu
- Department of Dermatology, University of Michigan, Ann Arbor, United States of America
| | - John S Runge
- Department of Dermatology, University of Michigan, Ann Arbor, United States of America
| | - Johann E Gudjonsson
- Department of Dermatology, University of Michigan, Ann Arbor, United States of America
| | - Sunny Y Wong
- Department of Cell & Developmental Biology, University of Michigan, Ann Arbor, United States of America
| | - Isaac Brownell
- Dermatology Branch, National Cancer Institute, Bethesda, United States of America
| | - Marcin Cieslik
- Department of Pathology, University of Michigan, Ann Arbor, United States of America
| | - Aaron M Udager
- Department of Pathology, University of Michigan, Ann Arbor, United States of America
| | - Arul M Chinnaiyan
- Department of Pathology, University of Michigan, Ann Arbor, United States of America
| | - Lam C Tsoi
- Department of Biostatistics, University of Michigan, Ann Arbor, United States of America
| | - Andrzej A Dlugosz
- Department of Cell & Developmental Biology, University of Michigan, Ann Arbor, United States of America
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16
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Tsoi LC, Patrick MT, Shuai S, Sarkar MK, Chi S, Ruffino B, Billi AC, Xing X, Uppala R, Zang C, Fullmer J, He Z, Maverakis E, Mehta NN, White BEP, Getsios S, Helfrich Y, Voorhees JJ, Kahlenberg JM, Weidinger S, Gudjonsson JE. Cytokine responses in nonlesional psoriatic skin as clinical predictor to anti-TNF agents. J Allergy Clin Immunol 2022; 149:640-649.e5. [PMID: 34343561 PMCID: PMC9451046 DOI: 10.1016/j.jaci.2021.07.024] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 06/14/2021] [Accepted: 07/20/2021] [Indexed: 02/03/2023]
Abstract
BACKGROUND A major issue with the current management of psoriasis is our inability to predict treatment response. OBJECTIVE Our aim was to evaluate the ability to use baseline molecular expression profiling to assess treatment outcome for patients with psoriasis. METHODS We conducted a longitudinal study of 46 patients with chronic plaque psoriasis treated with anti-TNF agent etanercept, and molecular profiles were assessed in more than 200 RNA-seq samples. RESULTS We demonstrated correlation between clinical response and molecular changes during the course of the treatment, particularly for genes responding to IL-17A/TNF in keratinocytes. Intriguingly, baseline gene expressions in nonlesional, but not lesional, skin were the best marker of treatment response at week 12. We identified USP18, a known regulator of IFN responses, as positively correlated with Psoriasis Area and Severity Index (PASI) improvement (P = 9.8 × 10-4) and demonstrate its role in regulating IFN/TNF responses in keratinocytes. Consistently, cytokine gene signatures enriched in baseline nonlesional skin expression profiles had strong correlations with PASI improvement. Using this information, we developed a statistical model for predicting PASI75 (ie, 75% of PASI improvement) at week 12, achieving area under the receiver-operating characteristic curve value of 0.75 and up to 80% accurate PASI75 prediction among the top predicted responders. CONCLUSIONS Our results illustrate feasibility of assessing drug response in psoriasis using nonlesional skin and implicate involvement of IFN regulators in anti-TNF responses.
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Affiliation(s)
- Lam C. Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA,Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor MI, USA,Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA,Correspondence should be addressed to: Lam C Tsoi () and Johann E Gudjonsson (), Med Sci I, 1301 E Catherine St, Ann Ann, MI, 48109, USA, Phone number: 734-764-7069
| | - Matthew T. Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Shao Shuai
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA,Department of Dermatology, Xijing hospital, Fourth Military Medical University, Xi’an, Shannxi, China
| | - Mrinal K. Sarkar
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Sunyi Chi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA,Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Bethany Ruffino
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Allison C. Billi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Xianying Xing
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Ranjitha Uppala
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Cheng Zang
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Joseph Fullmer
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Zhi He
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Emanual Maverakis
- Department of Dermatology, School of Medicine, UC-Davis Medical Center, 2315 Stockton Blvd, Sacramento, CA, 95817, USA
| | - Nehal N. Mehta
- Section of Inflammation and Cardiometabolic Diseases, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, MD
| | | | - Spiro Getsios
- Department of Dermatology, Northwestern University, Chicago, IL 60611, USA
| | - Yolanda Helfrich
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - John J. Voorhees
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - J. Michelle Kahlenberg
- Divison of Rheumatology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Stephan Weidinger
- Department of Dermatology and Allergy, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Johann E Gudjonsson
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA,Correspondence should be addressed to: Lam C Tsoi () and Johann E Gudjonsson (), Med Sci I, 1301 E Catherine St, Ann Ann, MI, 48109, USA, Phone number: 734-764-7069
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17
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Stuart PE, Tsoi LC, Nair RP, Ghosh M, Kabra M, Shaiq PA, Raja GK, Qamar R, Thelma B, Patrick MT, Parihar A, Singh S, Khandpur S, Kumar U, Wittig M, Degenhardt F, Tejasvi T, Voorhees JJ, Weidinger S, Franke A, Abecasis GR, Sharma VK, Elder JT. Transethnic analysis of psoriasis susceptibility in South Asians and Europeans enhances fine-mapping in the MHC and genomewide. HGG Adv 2022; 3:100069. [PMID: 34927100 PMCID: PMC8682265 DOI: 10.1016/j.xhgg.2021.100069] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 10/24/2021] [Indexed: 02/06/2023] Open
Abstract
Because transethnic analysis may facilitate prioritization of causal genetic variants, we performed a genomewide association study (GWAS) of psoriasis in South Asians (SAS), consisting of 2,590 cases and 1,720 controls. Comparison with our existing European-origin (EUR) GWAS showed that effect sizes of known psoriasis signals were highly correlated in SAS and EUR (Spearman ρ = 0.78; p < 2 × 10-14). Transethnic meta-analysis identified two non-MHC psoriasis loci (1p36.22 and 1q24.2) not previously identified in EUR, which may have regulatory roles. For these two loci, the transethnic GWAS provided higher genetic resolution and reduced the number of potential causal variants compared to using the EUR sample alone. We then explored multiple strategies to develop reference panels for accurately imputing MHC genotypes in both SAS and EUR populations and conducted a fine-mapping of MHC psoriasis associations in SAS and the largest such effort for EUR. HLA-C*06 was the top-ranking MHC locus in both populations but was even more prominent in SAS based on odds ratio, disease liability, model fit and predictive power. Transethnic modeling also substantially boosted the probability that the HLA-C*06 protein variant is causal. Secondary MHC signals included coding variants of HLA-C and HLA-B, but also potential regulatory variants of these two genes as well as HLA-A and several HLA class II genes, with effects on both chromatin accessibility and gene expression. This study highlights the shared genetic basis of psoriasis in SAS and EUR populations and the value of transethnic meta-analysis for discovery and fine-mapping of susceptibility loci.
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Affiliation(s)
- Philip E. Stuart
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Lam C. Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor MI, USA
| | - Rajan P. Nair
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Manju Ghosh
- Department of Pediatrics Genetics, All India Institute of Medical Sciences, New Delhi, India
| | - Madhulika Kabra
- Department of Pediatrics Genetics, All India Institute of Medical Sciences, New Delhi, India
| | - Pakeeza A. Shaiq
- Department of Biochemistry, PMASAA University, Rawalpindi, Pakistan
| | - Ghazala K. Raja
- Department of Biochemistry, PMASAA University, Rawalpindi, Pakistan
| | - Raheel Qamar
- COMSATS Institute of Information Technology, Islamabad, Pakistan
| | - B.K. Thelma
- Department of Genetics, University of Delhi South Campus, 110021 New Delhi, India
| | - Matthew T. Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Anita Parihar
- Department of Dermatology, All India Institute of Medical Sciences, New Delhi, India
| | - Sonam Singh
- Department of Dermatology, All India Institute of Medical Sciences, New Delhi, India
| | - Sujay Khandpur
- Department of Dermatology, All India Institute of Medical Sciences, New Delhi, India
| | - Uma Kumar
- Department of Rheumatology, All India Institute of Medical Sciences, New Delhi, India
| | - Michael Wittig
- Institute of Clinical Molecular Biology, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel 24105, Germany
| | - Frauke Degenhardt
- Institute of Clinical Molecular Biology, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel 24105, Germany
| | - Trilokraj Tejasvi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
- Ann Arbor Veterans Affairs Hospital, Ann Arbor, MI, USA
| | - John J. Voorhees
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
| | - Stephan Weidinger
- Department of Dermatology, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel 24105, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel 24105, Germany
| | - Goncalo R. Abecasis
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Vinod K. Sharma
- Department of Dermatology, All India Institute of Medical Sciences, New Delhi, India
| | - James T. Elder
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, USA
- Ann Arbor Veterans Affairs Hospital, Ann Arbor, MI, USA
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18
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Shefler A, Patrick MT, Wasikowski R, Chen J, Sarkar MK, Gudjonsson JE, Tsoi LC. Skin-Expressing lncRNAs in Inflammatory Responses. Front Genet 2022; 13:835740. [PMID: 35559048 PMCID: PMC9086234 DOI: 10.3389/fgene.2022.835740] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 03/08/2022] [Indexed: 12/25/2022] Open
Abstract
Long non-coding RNAs (lncRNAs) have attracted attention for their potential roles in modulating keratinocyte differentiation and inflammatory response; however, for many identified skin-expressing lncRNAs, there is no comprehensive characterization regarding their biological roles. In addition, the reported expression profiles for lncRNAs can be ambiguous due to their low-expressing nature. The objective of this review is to utilize large scale genomic data to characterize the prominent skin-expressing lncRNAs, aiming to provide additional insights for their potential roles in the pathology of inflammatory skin of psoriasis and atopic dermatitis by integrating in vitro and in vivo data. We highlighted the different skin-expressing lncRNAs, including H19, which is significantly down-regulated in lesional skin of AD/psoriasis and upon cytokine stimulation in keratinocytes; it is also negatively correlated with CYP1A1 (r = -0.75, p = 8 × 10-73), a gene involved in drug metabolism and skin barrier homeostasis, in keratinocytes. In addition, SPRR2C, a potential regulator that modulates IL-22 stimulation, was upregulated in both atopic dermatitis and psoriasis lesional skin and was also downstream of the IL-17A and IL-17 + TNF signaling in keratinocytes. Using scRNAseq, we further revealed the cell type specificity of lncRNAs, including basal-expressing nature of H19 in the epidermis. Interestingly, instead of having cell type specific expression profile, we found few lncRNAs that are express across different cell types in skin, including MALAT1, NEAT1, and GAS5. While lncRNAs in general have lower expression, our results combining in vitro and in vivo experimental data demonstrate how some of these lncRNAs can play mediator roles in the cytokine-stimulated pathway.
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Affiliation(s)
- Alanna Shefler
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Matthew T. Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Rachael Wasikowski
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Jiahan Chen
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, United States
| | - Mrinal K. Sarkar
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Johann E. Gudjonsson
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Lam C. Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, United States
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, United States
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, United States
- *Correspondence: Lam C. Tsoi,
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19
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Tsoi LC, Hacini-Rachinel F, Fogel P, Rousseau F, Xing X, Patrick MT, Billi AC, Berthier CC, Kahlenberg JM, Lazzari A, Wiegmann H, Ständer S, Piketty C, Julia V, Krishnaswamy JK, Gudjonsson JE. Transcriptomic characterization of prurigo nodularis and the therapeutic response to nemolizumab. J Allergy Clin Immunol 2021; 149:1329-1339. [PMID: 34857395 DOI: 10.1016/j.jaci.2021.10.004] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2021] [Revised: 10/01/2021] [Accepted: 10/07/2021] [Indexed: 10/19/2022]
Abstract
BACKGROUND Prurigo nodularis (PN) is a debilitating, difficult-to-treat, intensely pruritic, chronic inflammatory skin disease characterized by hyperkeratotic skin nodules. The pathogenesis of PN is not well understood but is believed to involve cross talk between sensory nerve fibers, immune cells, and the epidermis. It is centered around the neuroimmune cytokine IL-31, driving an intractable itch-scratch cycle. OBJECTIVE We sought to provide a comprehensive view of the transcriptomic changes in PN skin and characterize the mechanism of action of the anti-IL-31 receptor inhibitor nemolizumab. METHOD RNA sequencing of biopsy samples obtained from a cohort of patients treated with the anti-IL-31 receptor inhibitor nemolizumab and taken at baseline and week 12. Generation and integration of patient data with RNA-Seq data generated from reconstructed human epidermis stimulated with IL-31 and other proinflammatory cytokines. RESULTS Our results demonstrate that nemolizumab effectively decreases IL-31 responses in PN skin, leading to effective suppression of downstream inflammatory responses including TH2/IL-13 and TH17/IL-17 responses. This is accompanied by decreased keratinocyte proliferation and normalization of epidermal differentiation and function. Furthermore, our results demonstrate how transcriptomic changes associated with nemolizumab treatment correlate with improvement in lesions, pruritus, stabilization of extracellular matrix remodeling, and processes associated with cutaneous nerve function. CONCLUSION These data demonstrate a broad response to IL-31 receptor inhibition with nemolizumab and confirm the critical upstream role of IL-31 in PN pathogenesis.
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Affiliation(s)
- Lam C Tsoi
- Department of Dermatology, University of Michigan, Ann Arbor, Mich; Department of Biostatistics, University of Michigan, Ann Arbor, Mich; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Mich
| | | | | | | | - Xianying Xing
- Department of Dermatology, University of Michigan, Ann Arbor, Mich
| | | | - Allison C Billi
- Department of Dermatology, University of Michigan, Ann Arbor, Mich
| | - Celine C Berthier
- Department of Internal Medicine, Division of Nephrology, University of Michigan, Ann Arbor, Mich
| | - J Michelle Kahlenberg
- Department of Internal Medicine, Division of Rheumatology, University of Michigan, Ann Arbor, Mich; Taubman Medical Research Institute, University of Michigan Medical School, Ann Arbor, Mich
| | | | - Henning Wiegmann
- Department of Dermatology and Center for Chronic Pruritus, University Hospital Münster, Münster, Germany
| | - Sonja Ständer
- Department of Dermatology and Center for Chronic Pruritus, University Hospital Münster, Münster, Germany
| | | | | | | | - Johann E Gudjonsson
- Department of Dermatology, University of Michigan, Ann Arbor, Mich; Taubman Medical Research Institute, University of Michigan Medical School, Ann Arbor, Mich.
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20
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Patrick MT, Bardhi R, Raja K, He K, Tsoi LC. Advancement in predicting interactions between drugs used to treat psoriasis and its comorbidities by integrating molecular and clinical resources. J Am Med Inform Assoc 2021; 28:1159-1167. [PMID: 33544847 DOI: 10.1093/jamia/ocaa335] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Accepted: 12/14/2020] [Indexed: 12/18/2022] Open
Abstract
OBJECTIVE Drug-drug interactions (DDIs) can result in adverse and potentially life-threatening health consequences; however, it is challenging to predict potential DDIs in advance. We introduce a new computational approach to comprehensively assess the drug pairs which may be involved in specific DDI types by combining information from large-scale gene expression (984 transcriptomic datasets), molecular structure (2159 drugs), and medical claims (150 million patients). MATERIALS AND METHODS Features were integrated using ensemble machine learning techniques, and we evaluated the DDIs predicted with a large hospital-based medical records dataset. Our pipeline integrates information from >30 different resources, including >10 000 drugs and >1.7 million drug-gene pairs. We applied our technique to predict interactions between 37 611 drug pairs used to treat psoriasis and its comorbidities. RESULTS Our approach achieves >0.9 area under the receiver operator curve (AUROC) for differentiating 11 861 known DDIs from 25 750 non-DDI drug pairs. Significantly, we demonstrate that the novel DDIs we predict can be confirmed through independent data sources and supported using clinical medical records. CONCLUSIONS By applying machine learning and taking advantage of molecular, genomic, and health record data, we are able to accurately predict potential new DDIs that can have an impact on public health.
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Affiliation(s)
- Matthew T Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Redina Bardhi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA.,School of Medicine, Wayne State University, Detroit, Michigan, USA
| | - Kalpana Raja
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA.,Morgridge Institute for Research, Madison, Wisconsin, USA
| | - Kevin He
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA
| | - Lam C Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA.,Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA.,Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
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21
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Zhou XJ, Tsoi LC, Hu Y, Patrick MT, He K, Berthier CC, Li Y, Wang YN, Qi YY, Zhang YM, Gan T, Li Y, Hou P, Liu LJ, Shi SF, Lv JC, Xu HJ, Zhang H. Exome Chip Analyses and Genetic Risk for IgA Nephropathy among Han Chinese. Clin J Am Soc Nephrol 2021; 16:213-224. [PMID: 33462083 PMCID: PMC7863642 DOI: 10.2215/cjn.06910520] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 12/11/2020] [Indexed: 02/04/2023]
Abstract
BACKGROUND AND OBJECTIVES IgA nephropathy is the most common form of primary GN worldwide. The evidence of geographic and ethnic differences, as well as familial aggregation of the disease, supports a strong genetic contribution to IgA nephropathy. Evidence for genetic factors in IgA nephropathy comes also from genome-wide association patient-control studies. However, few studies have systematically evaluated the contribution of coding variation in IgA nephropathy. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS We performed a two-stage exome chip-based association study in 13,242 samples, including 3363 patients with IgA nephropathy and 9879 healthy controls of Han Chinese ancestry. Common variant functional annotation, gene-based low-frequency variants analysis, differential mRNA expression, and gene network integration were also explored. RESULTS We identified three non-HLA gene regions (FBXL21, CCR6, and STAT3) and one HLA gene region (GABBR1) with suggestive significance (Pmeta <5×10-5) in single-variant associations. These novel non-HLA variants were annotated as expression-associated single-nucleotide polymorphisms and were located in enhancer regions enriched in histone marks H3K4me1 in primary B cells. Gene-based low-frequency variants analysis suggests CFB as another potential susceptibility gene. Further combined expression and network integration suggested that the five novel susceptibility genes, TGFBI, CCR6, STAT3, GABBR1, and CFB, were involved in IgA nephropathy. CONCLUSIONS Five novel gene regions with suggestive significance for IgA nephropathy were identified and shed new light for further mechanism investigation.
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Affiliation(s)
- Xu-jie Zhou
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, People’s Republic of China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People’s Republic of China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People’s Republic of China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Lam C. Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan
| | - Yong Hu
- Beijing Institute of Biotechnology, Beijing, People’s Republic of China
| | - Matthew T. Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Kevin He
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
- Kidney Epidemiology and Cost Center, School of Public Health, University of Michigan, Ann Arbor, Michigan
| | - Celine C. Berthier
- Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Yanming Li
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, Kansas
| | - Yan-na Wang
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, People’s Republic of China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People’s Republic of China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People’s Republic of China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Yuan-yuan Qi
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, People’s Republic of China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People’s Republic of China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People’s Republic of China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Yue-miao Zhang
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, People’s Republic of China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People’s Republic of China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People’s Republic of China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Ting Gan
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, People’s Republic of China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People’s Republic of China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People’s Republic of China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Yang Li
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, People’s Republic of China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People’s Republic of China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People’s Republic of China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Ping Hou
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, People’s Republic of China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People’s Republic of China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People’s Republic of China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Li-jun Liu
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, People’s Republic of China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People’s Republic of China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People’s Republic of China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Su-fang Shi
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, People’s Republic of China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People’s Republic of China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People’s Republic of China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Ji-cheng Lv
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, People’s Republic of China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People’s Republic of China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People’s Republic of China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
| | - Hu-ji Xu
- Department of Biostatistics and Data Science, University of Kansas Medical Center, Kansas City, Kansas
- Department of Rheumatology and Immunology, Shanghai Changzheng Hospital, The Second Military Medical University, Shanghai, People’s Republic of China
| | - Hong Zhang
- Renal Division, Peking University First Hospital, Peking University Institute of Nephrology, Beijing, People’s Republic of China
- Key Laboratory of Renal Disease, Ministry of Health of China, Beijing, People’s Republic of China
- Key Laboratory of Chronic Kidney Disease Prevention and Treatment (Peking University), Ministry of Education, Beijing, People’s Republic of China
- Research Units of Diagnosis and Treatment of Immune-Mediated Kidney Diseases, Chinese Academy of Medical Sciences, Beijing, People’s Republic of China
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22
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Patrick MT, Zhang H, Wasikowski R, Prens EP, Weidinger S, Gudjonsson JE, Elder JT, He K, Tsoi LC. Associations between COVID-19 and skin conditions identified through epidemiology and genomic studies. J Allergy Clin Immunol 2021; 147:857-869.e7. [PMID: 33485957 PMCID: PMC7825803 DOI: 10.1016/j.jaci.2021.01.006] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 01/08/2021] [Accepted: 01/12/2021] [Indexed: 12/13/2022]
Abstract
Background Coronavirus disease 2019 (COVID-19) is commonly associated with skin manifestations, and may also exacerbate existing skin diseases, yet the relationship between COVID-19 and skin diseases remains unclear. Objective By investigating this relationship through a multiomics approach, we sought to ascertain whether patients with skin conditions are more susceptible to COVID-19. Methods We conducted an epidemiological study and then compared gene expression across 9 different inflammatory skin conditions and severe acute respiratory syndrome coronavirus 2–infected bronchial epithelial cell lines, and then performed a genome-wide association study transdisease meta-analysis between COVID-19 susceptibility and 2 skin diseases (psoriasis and atopic dermatitis). Results Skin conditions, including psoriasis and atopic dermatitis, increase the risk of COVID-19 (odds ratio, 1.55; P = 1.4 × 10−9) but decrease the risk of mechanical ventilation (odds ratio, 0.22; P = 8.5 × 10−5). We observed significant overlap in gene expression between the infected normal bronchial epithelial cells and inflammatory skin diseases, such as psoriasis and atopic dermatitis. For genes that are commonly induced in both the severe acute respiratory syndrome coronavirus 2 infection and skin diseases, there are 4 S100 family members located in the epidermal differentiation complex, and we also identified the “IL-17 signaling pathway” (P = 4.9 × 10−77) as one of the most significantly enriched pathways. Furthermore, a shared genome-wide significant locus in the epidermal differentiation complex was identified between psoriasis and severe acute respiratory syndrome coronavirus 2 infection, with the lead marker being a significant expression quantitative trait locus for S100A12 (P = 3.3 × 10−7). Conclusions Together our findings suggest association between inflammatory skin conditions and higher risk of COVID-19, but with less severe course, and highlight shared components involved in anti–COVID-19 immune response.
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Affiliation(s)
- Matthew T Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Mich.
| | - Haihan Zhang
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Mich
| | - Rachael Wasikowski
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Mich
| | - Errol P Prens
- Department of Dermatology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Stephan Weidinger
- Department of Dermatology and Allergy, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Johann E Gudjonsson
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Mich
| | - James T Elder
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Mich; Ann Arbor Veterans Affairs Hospital, Ann Arbor, Mich
| | - Kevin He
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Mich
| | - Lam C Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Mich; Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Mich; Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, Mich.
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23
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Patrick MT, Stuart PE, Zhang H, Zhao Q, Yin X, He K, Zhou XJ, Mehta NN, Voorhees JJ, Boehnke M, Gudjonsson JE, Nair RP, Handelman SK, Elder JT, Liu DJ, Tsoi LC. Causal Relationship and Shared Genetic Loci between Psoriasis and Type 2 Diabetes through Trans-Disease Meta-Analysis. J Invest Dermatol 2020; 141:1493-1502. [PMID: 33385400 DOI: 10.1016/j.jid.2020.11.025] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 11/09/2020] [Accepted: 11/23/2020] [Indexed: 01/04/2023]
Abstract
Psoriasis and type 2 diabetes (T2D) are complex conditions with significant impacts on health. Patients with psoriasis have a higher risk of T2D (∼1.5 OR) and vice versa, controlling for body mass index; yet, there has been a limited study comparing their genetic architecture. We hypothesized that there are shared genetic components between psoriasis and T2D. Trans-disease meta-analysis was applied to 8,016,731 well-imputed genetic markers from large-scale meta-analyses of psoriasis (11,024 cases and 16,336 controls) and T2D (74,124 cases and 824,006 controls), adjusted for body mass index. We confirmed our findings in a hospital-based study (42,112 patients) and tested for causal relationships with multivariable Mendelian randomization. Mendelian randomization identified a causal relationship between psoriasis and T2D (P = 1.6 × 10‒4, OR = 1.01) and highlighted the impact of body mass index. Trans-disease meta-analysis further revealed four genome-wide significant loci (P < 5 × 10‒8) with evidence of colocalization and shared directions of effect between psoriasis and T2D not present in body mass index. The proteins coded by genes in these loci (ACTR2, ERLIN1, TRMT112, and BECN1) are connected through NF-κB signaling. Our results provide insight into the immunological components that connect immune-mediated skin conditions and metabolic diseases, independent of confounding factors.
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Affiliation(s)
- Matthew T Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Philip E Stuart
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Haihan Zhang
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA; Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Qingyuan Zhao
- Statistical Laboratory, Centre for Mathematical Sciences, University of Cambridge, Cambridge, United Kingdom
| | - Xianyong Yin
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Kevin He
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Xu-Jie Zhou
- Renal Division, Peking University First Hospital, Beijing, China
| | - Nehal N Mehta
- National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - John J Voorhees
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Michael Boehnke
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Johann E Gudjonsson
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Rajan P Nair
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Samuel K Handelman
- Division of Gastroenterology, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - James T Elder
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA; Ann Arbor Veterans Affairs Hospital, Ann Arbor, Michigan, USA
| | - Dajiang J Liu
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Pennsylvania, USA
| | - Lam C Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA; Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor Michigan, USA.
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24
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Gudjonsson JE, Tsoi LC, Ma F, Billi AC, van Straalen KR, Vossen ARJV, van der Zee HH, Harms PW, Wasikowski R, Yee CM, Rizvi SM, Xing X, Xing E, Plazyo O, Zeng C, Patrick MT, Lowe MM, Burney RE, Kozlow JH, Cherry-Bukowiec JR, Jiang Y, Kirma J, Weidinger S, Cushing KC, Rosenblum MD, Berthier C, MacLeod AS, Voorhees JJ, Wen F, Kahlenberg JM, Maverakis E, Modlin RL, Prens EP. Contribution of plasma cells and B cells to hidradenitis suppurativa pathogenesis. JCI Insight 2020; 5:139930. [PMID: 32853177 PMCID: PMC7566715 DOI: 10.1172/jci.insight.139930] [Citation(s) in RCA: 91] [Impact Index Per Article: 22.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 08/20/2020] [Indexed: 12/27/2022] Open
Abstract
Hidradenitis suppurativa (HS) is a debilitating chronic inflammatory skin disease characterized by chronic abscess formation and development of multiple draining sinus tracts in the groin, axillae, and perineum. Using proteomic and transcriptomic approaches, we characterized the inflammatory responses in HS in depth, revealing immune responses centered on IFN-γ, IL-36, and TNF, with lesser contribution from IL-17A. We further identified B cells and plasma cells, with associated increases in immunoglobulin production and complement activation, as pivotal players in HS pathogenesis, with Bruton’s tyrosine kinase (BTK) and spleen tyrosine kinase (SYK) pathway activation as a central signal transduction network in HS. These data provide preclinical evidence to accelerate the path toward clinical trials targeting BTK and SYK signaling in moderate-to-severe HS. B-cells and plasma cells are critical pathogenic cell populations in chronic Hidradenitis Suppurativa and are potential therapeutic targets.
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Affiliation(s)
| | - Lam C Tsoi
- Department of Dermatology and.,Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan, USA.,Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Feiyang Ma
- Department of Molecular, Cell and Developmental Biology, David Geffen School of Medicine at University of California (UCLA), Los Angeles, California, USA
| | | | - K R van Straalen
- Department of Dermatology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - A R J V Vossen
- Department of Dermatology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - H H van der Zee
- Department of Dermatology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Paul W Harms
- Department of Dermatology and.,Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | | | - Christine M Yee
- Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | - Syed M Rizvi
- Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | | | | | | | | | | | - Margaret M Lowe
- Department of Dermatology, UCSF, San Francisco, California, USA
| | | | | | | | | | | | - Stephan Weidinger
- Department of Dermatology, Venereology and Allergy, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | | | | | - Celine Berthier
- Division of Nephrology, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Amanda S MacLeod
- Department of Dermatology, Duke University School of Medicine, Durham, North Carolina, USA
| | | | - Fei Wen
- Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | - J Michelle Kahlenberg
- Division of Rheumatology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Emanual Maverakis
- Department of Dermatology, University of California Davis School of Medicine, Sacramento, California, USA
| | - Robert L Modlin
- Division of Dermatology, Department of Medicine, Immunology and Molecular Genetics, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
| | - Errol P Prens
- Department of Dermatology, Erasmus University Medical Center, Rotterdam, Netherlands
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25
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Tsoi LC, Gharaee-Kermani M, Berthier CC, Nault T, Hile GA, Estadt SN, Patrick MT, Wasikowski R, Billi AC, Lowe L, Reed TJ, Gudjonsson JE, Kahlenberg JM. IL18-containing 5-gene signature distinguishes histologically identical dermatomyositis and lupus erythematosus skin lesions. JCI Insight 2020; 5:139558. [PMID: 32644977 PMCID: PMC7455118 DOI: 10.1172/jci.insight.139558] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 07/02/2020] [Indexed: 12/26/2022] Open
Abstract
Skin lesions in dermatomyositis (DM) are common, are frequently refractory, and have prognostic significance. Histologically, DM lesions appear similar to cutaneous lupus erythematosus (CLE) lesions and frequently cannot be differentiated. We thus compared the transcriptional profile of DM biopsies with CLE lesions to identify unique features. Type I IFN signaling, including IFN-κ upregulation, was a common pathway in both DM and CLE; however, CLE also exhibited other inflammatory pathways. Notably, DM lesions could be distinguished from CLE by a 5-gene biomarker panel that included IL18 upregulation. Using single-cell RNA-sequencing, we further identified keratinocytes as the main source of increased IL-18 in DM skin. This study identifies a potentially novel molecular signature, with significant clinical implications for differentiating DM from CLE lesions, and highlights the potential role for IL-18 in the pathophysiology of DM skin disease. IL-18 distinguishes dermatomyositis skin inflammation from cutaneous lupus erythematosus lesions.
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Affiliation(s)
- Lam C Tsoi
- Department of Dermatology and.,Department of Computational Medicine & Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan, USA.,Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | | | | | - Tori Nault
- Division of General Medicine, Department of Internal Medicine
| | | | - Shannon N Estadt
- Division of Rheumatology, Department of Internal Medicine.,Program in Immunology, and
| | | | | | | | - Lori Lowe
- Department of Dermatology and.,Department of Pathology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Tamra J Reed
- Division of Rheumatology, Department of Internal Medicine
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26
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Patrick MT, Stuart PE, Raja K, Chi S, He Z, Voorhees JJ, Tejasvi T, Gudjonsson JE, Kahlenberg JM, Chandran V, Rahman P, Gladman DD, Nair RP, Elder JT, Tsoi LC. Integrative Approach to Reveal Cell Type Specificity and Gene Candidates for Psoriatic Arthritis Outside the MHC. Front Genet 2019; 10:304. [PMID: 31031798 PMCID: PMC6470186 DOI: 10.3389/fgene.2019.00304] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Accepted: 03/19/2019] [Indexed: 12/13/2022] Open
Abstract
We recently conducted a large association analysis to compare the genetic profiles between patients with psoriatic arthritis (PsA) and cutaneous-only psoriasis (PsC). Despite including over 7,000 genotyped patients, only the MHC achieved genome-wide significance. In this study, we hypothesized that appropriate epigenomic elements (H3K27ac marks for active enhancers) can guide us to reveal valuable information about the loci with suggestive evidence of association. Our aim is to investigate these loci and explore how they may lead to the development of PsA. We evaluated this potential by investigating the genes connected with these loci from the perspective of pharmacogenomics and gene expression. We illustrated that markers with suggestive evidence of association outside the MHC region are enriched in H3K27ac marks for osteoblast and chondrogenic differentiated cells; using pharmacogenomics resources, we showed that genes near these markers are targeted by existing drugs used to treat psoriatic arthritis. Significantly, six of the ten suggestive significant loci overlapping the regulatory elements encompass genes differentially expressed (FDR < 5%) in differentiated osteoblasts, including genes participating in the Wnt signaling such as RUNX1, FUT8, and CTNNAL1. Our approach shows that epigenomic information can be used as cost-effective approach to enhance the inferences for GWAS results, especially in situations when few genome-wide significant loci are available. Our results also point the way to more directed investigations comparing the genetics of PsA and PsC.
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Affiliation(s)
- Matthew T. Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Philip E. Stuart
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Kalpana Raja
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, United States
- Morgridge Institute for Research, Madison, WI, United States
| | - Sunyi Chi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, United States
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, United States
| | - Zhi He
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, United States
| | - John J. Voorhees
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, United States
| | - Trilokraj Tejasvi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, United States
- Ann Arbor Veterans Affairs Hospital, Ann Arbor, MI, United States
| | - Johann E. Gudjonsson
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, United States
| | - J. Michelle Kahlenberg
- Division of Rheumatology, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, United States
| | - Vinod Chandran
- Division of Rheumatology, Department of Medicine, University of Toronto, Toronto, ON, Canada
- Centre for Prognosis Studies in the Rheumatic Diseases, Krembil Research Institute, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, Canada
- Faculty of Medicine, Memorial University of Newfoundland, St. John’s, NL, Canada
| | - Proton Rahman
- Faculty of Medicine, Memorial University of Newfoundland, St. John’s, NL, Canada
| | - Dafna D. Gladman
- Division of Rheumatology, Department of Medicine, University of Toronto, Toronto, ON, Canada
- Centre for Prognosis Studies in the Rheumatic Diseases, Krembil Research Institute, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Rajan P. Nair
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, United States
| | - James T. Elder
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, United States
- Ann Arbor Veterans Affairs Hospital, Ann Arbor, MI, United States
| | - Lam C. Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, MI, United States
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, United States
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, United States
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27
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Patrick MT, Tsoi LC, Gudjonsson JE. Making New Connections-Chromosome Conformation Capture for Identification of Disease-Associated Target Genes. J Invest Dermatol 2019; 139:514-517. [PMID: 30797317 DOI: 10.1016/j.jid.2018.11.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Revised: 11/28/2018] [Accepted: 11/28/2018] [Indexed: 11/29/2022]
Abstract
Most susceptibility loci for complex dermatologic diseases fall within non-coding regions, making assignment of function difficult. Chromosome conformation capture addresses this problem by using the spatial organization of chromatin to identify the genes these loci interact with, often across long distances. Furthermore, as gene regulation is tissue-/cell-dependent, studying relevant cell populations is critical to reveal the molecular mechanisms involved.
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Affiliation(s)
- Matthew T Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - Lam C Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA; Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA
| | - Johann E Gudjonsson
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA.
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28
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Sarkar MK, Hile GA, Tsoi LC, Xing X, Liu J, Liang Y, Berthier CC, Swindell WR, Patrick MT, Shao S, Tsou PS, Uppala R, Beamer MA, Srivastava A, Bielas SL, Harms PW, Getsios S, Elder JT, Voorhees JJ, Gudjonsson JE, Kahlenberg JM. Photosensitivity and type I IFN responses in cutaneous lupus are driven by epidermal-derived interferon kappa. Ann Rheum Dis 2018; 77:1653-1664. [PMID: 30021804 DOI: 10.1136/annrheumdis-2018-213197] [Citation(s) in RCA: 135] [Impact Index Per Article: 22.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2018] [Revised: 06/01/2018] [Accepted: 07/03/2018] [Indexed: 01/11/2023]
Abstract
OBJECTIVE Skin inflammation and photosensitivity are common in patients with cutaneous lupus erythematosus (CLE) and systemic lupus erythematosus (SLE), yet little is known about the mechanisms that regulate these traits. Here we investigate the role of interferon kappa (IFN-κ) in regulation of type I interferon (IFN) and photosensitive responses and examine its dysregulation in lupus skin. METHODS mRNA expression of type I IFN genes was analysed from microarray data of CLE lesions and healthy control skin. Similar expression in cultured primary keratinocytes, fibroblasts and endothelial cells was analysed via RNA-seq. IFNK knock-out (KO) keratinocytes were generated using CRISPR/Cas9. Keratinocytes stably overexpressing IFN-κ were created via G418 selection of transfected cells. IFN responses were assessed via phosphorylation of STAT1 and STAT2 and qRT-PCR for IFN-regulated genes. Ultraviolet B-mediated apoptosis was analysed via TUNEL staining. In vivo protein expression was assessed via immunofluorescent staining of normal and CLE lesional skin. RESULTS IFNK is one of two type I IFNs significantly increased (1.5-fold change, false discovery rate (FDR) q<0.001) in lesional CLE skin. Gene ontology (GO) analysis showed that type I IFN responses were enriched (FDR=6.8×10-04) in keratinocytes not in fibroblast and endothelial cells, and this epithelial-derived IFN-κ is responsible for maintaining baseline type I IFN responses in healthy skin. Increased levels of IFN-κ, such as seen in SLE, amplify and accelerate responsiveness of epithelia to IFN-α and increase keratinocyte sensitivity to UV irradiation. Notably, KO of IFN-κ or inhibition of IFN signalling with baricitinib abrogates UVB-induced apoptosis. CONCLUSION Collectively, our data identify IFN-κ as a critical IFN in CLE pathology via promotion of enhanced IFN responses and photosensitivity. IFN-κ is a potential novel target for UVB prophylaxis and CLE-directed therapy.
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Affiliation(s)
- Mrinal K Sarkar
- Department of Dermatology, University of Michigan, Ann Arbor, Michigan, USA
| | - Grace A Hile
- Division of Rheumatology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Lam C Tsoi
- Department of Dermatology, University of Michigan, Ann Arbor, Michigan, USA.,Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, Michigan, USA.,Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, USA
| | - Xianying Xing
- Department of Dermatology, University of Michigan, Ann Arbor, Michigan, USA
| | - Jianhua Liu
- Division of Rheumatology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Yun Liang
- Department of Dermatology, University of Michigan, Ann Arbor, Michigan, USA
| | - Celine C Berthier
- Division of Nephrology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - William R Swindell
- Department of Dermatology, University of Michigan, Ann Arbor, Michigan, USA
| | - Matthew T Patrick
- Department of Dermatology, University of Michigan, Ann Arbor, Michigan, USA
| | - Shuai Shao
- Department of Dermatology, University of Michigan, Ann Arbor, Michigan, USA
| | - Pei-Suen Tsou
- Division of Rheumatology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
| | - Ranjitha Uppala
- Department of Dermatology, University of Michigan, Ann Arbor, Michigan, USA
| | - Maria A Beamer
- Department of Dermatology, University of Michigan, Ann Arbor, Michigan, USA
| | - Anshika Srivastava
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan, USA
| | - Stephanie L Bielas
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan, USA
| | - Paul W Harms
- Department of Dermatology, University of Michigan, Ann Arbor, Michigan, USA.,Department of Pathology, University of Michigan, Ann Arbor, Michigan, USA
| | - Spiro Getsios
- Department of Dermatology, Northwestern University, Chicago, Illinois, USA
| | - James T Elder
- Department of Dermatology, University of Michigan, Ann Arbor, Michigan, USA
| | - John J Voorhees
- Department of Dermatology, University of Michigan, Ann Arbor, Michigan, USA
| | | | - J Michelle Kahlenberg
- Division of Rheumatology, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
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29
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Abstract
Complex cutaneous disorders result from the combined effect of many different genes and environmental factors, with individual genetic variants often having only a modest effect on disease risk. The ability to examine large numbers of samples is required for correlating genetic variants with diseases/traits. Technological advances in high-throughput genotyping, along with mapping of the human genome and its associated inter-individual variation, have allowed genetic variants to be analyzed at high density in large case-control cohorts for many diseases, including several major skin diseases. These genome-wide association studies focus on showing differences in the frequencies of variants between case and control groups, rather than co-transmission of a variant and disease through a family, as is done in linkage studies. In this review, we provide overall guidance for genome-wide association study analysis and interpreting the results. Additionally, we discuss challenges and future directions for genome-wide association studies, focusing on translation of findings to provide biological and clinical implications for dermatology.
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Affiliation(s)
- Lam C Tsoi
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA; Department of Computational Medicine and Bioinformatics, University of Michigan Medical School, Ann Arbor, Michigan, USA; Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan, USA.
| | - Matthew T Patrick
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA
| | - James T Elder
- Department of Dermatology, University of Michigan Medical School, Ann Arbor, Michigan, USA; Ann Arbor Veterans Affairs Hospital, Ann Arbor, Michigan, USA.
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