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Wang F, Jia K, Li Y. Integrative deep learning with prior assisted feature selection. Stat Med 2024; 43:3792-3814. [PMID: 38923006 DOI: 10.1002/sim.10148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 04/23/2024] [Accepted: 06/07/2024] [Indexed: 06/28/2024]
Abstract
Integrative analysis has emerged as a prominent tool in biomedical research, offering a solution to the "smalln $$ n $$ and largep $$ p $$ " challenge. Leveraging the powerful capabilities of deep learning in extracting complex relationship between genes and diseases, our objective in this study is to incorporate deep learning into the framework of integrative analysis. Recognizing the redundancy within candidate features, we introduce a dedicated feature selection layer in the proposed integrative deep learning method. To further improve the performance of feature selection, the rich previous researches are utilized by an ensemble learning method to identify "prior information". This leads to the proposed prior assisted integrative deep learning (PANDA) method. We demonstrate the superiority of the PANDA method through a series of simulation studies, showing its clear advantages over competing approaches in both feature selection and outcome prediction. Finally, a skin cutaneous melanoma (SKCM) dataset is extensively analyzed by the PANDA method to show its practical application.
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Affiliation(s)
- Feifei Wang
- Center for Applied Statistics, Renmin University of China, Beijing, China
- School of Statistics, Renmin University of China, Beijing, China
| | - Ke Jia
- School of Statistics, Renmin University of China, Beijing, China
| | - Yang Li
- Center for Applied Statistics, Renmin University of China, Beijing, China
- School of Statistics, Renmin University of China, Beijing, China
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2
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Lincoln MR, Connally N, Axisa PP, Gasperi C, Mitrovic M, van Heel D, Wijmenga C, Withoff S, Jonkers IH, Padyukov L, Rich SS, Graham RR, Gaffney PM, Langefeld CD, Vyse TJ, Hafler DA, Chun S, Sunyaev SR, Cotsapas C. Genetic mapping across autoimmune diseases reveals shared associations and mechanisms. Nat Genet 2024; 56:838-845. [PMID: 38741015 DOI: 10.1038/s41588-024-01732-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 03/21/2024] [Indexed: 05/16/2024]
Abstract
Autoimmune and inflammatory diseases are polygenic disorders of the immune system. Many genomic loci harbor risk alleles for several diseases, but the limited resolution of genetic mapping prevents determining whether the same allele is responsible, indicating a shared underlying mechanism. Here, using a collection of 129,058 cases and controls across 6 diseases, we show that ~40% of overlapping associations are due to the same allele. We improve fine-mapping resolution for shared alleles twofold by combining cases and controls across diseases, allowing us to identify more expression quantitative trait loci driven by the shared alleles. The patterns indicate widespread sharing of pathogenic mechanisms but not a single global autoimmune mechanism. Our approach can be applied to any set of traits and is particularly valuable as sample collections become depleted.
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Affiliation(s)
- Matthew R Lincoln
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
- Division of Neurology at the Department of Medicine, University of Toronto, Toronto, Ontario, Canada
- Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, Ontario, Canada
| | - Noah Connally
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Pierre-Paul Axisa
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | | | - Mitja Mitrovic
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
- Faculty of Chemistry and Chemical Engineering, University of Maribor, Maribor, Slovenia
| | - David van Heel
- Blizard Institute, Queen Mary University of London, London, UK
| | - Cisca Wijmenga
- Department of Genetics at the University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Sebo Withoff
- Department of Genetics at the University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Iris H Jonkers
- Department of Genetics at the University Medical Center Groningen, University of Groningen, Groningen, the Netherlands
| | - Leonid Padyukov
- Division of Rheumatology at the Department of Medicine, Karolinska Institutet and Karolinska University Hospital, Stockholm, Sweden
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
- Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Robert R Graham
- Maze Therapeutics, South San Francisco, CA, USA
- Genentech, South San Francisco, CA, USA
| | - Patrick M Gaffney
- Genes and Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA
| | - Carl D Langefeld
- Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Precision Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Timothy J Vyse
- Department of Medical and Molecular Genetics, Kings College London, London, UK
| | - David A Hafler
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Sung Chun
- Division of Genetics, Brigham and Women's Hospital, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Shamil R Sunyaev
- Division of Genetics, Brigham and Women's Hospital, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Chris Cotsapas
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA.
- Department of Genetics, Yale School of Medicine, New Haven, CT, USA.
- Vesalius Therapeutics, Cambridge, MA, USA.
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Ortiz GG, Torres-Mendoza BMG, Ramírez-Jirano J, Marquez-Pedroza J, Hernández-Cruz JJ, Mireles-Ramirez MA, Torres-Sánchez ED. Genetic Basis of Inflammatory Demyelinating Diseases of the Central Nervous System: Multiple Sclerosis and Neuromyelitis Optica Spectrum. Genes (Basel) 2023; 14:1319. [PMID: 37510224 PMCID: PMC10379341 DOI: 10.3390/genes14071319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2023] [Revised: 06/15/2023] [Accepted: 06/20/2023] [Indexed: 07/30/2023] Open
Abstract
Demyelinating diseases alter myelin or the coating surrounding most nerve fibers in the central and peripheral nervous systems. The grouping of human central nervous system demyelinating disorders today includes multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) as distinct disease categories. Each disease is caused by a complex combination of genetic and environmental variables, many involving an autoimmune response. Even though these conditions are fundamentally similar, research into genetic factors, their unique clinical manifestations, and lesion pathology has helped with differential diagnosis and disease pathogenesis knowledge. This review aims to synthesize the genetic approaches that explain the differential susceptibility between these diseases, explore the overlapping clinical features, and pathological findings, discuss existing and emerging hypotheses on the etiology of demyelination, and assess recent pathogenicity studies and their implications for human demyelination. This review presents critical information from previous studies on the disease, which asks several questions to understand the gaps in research in this field.
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Affiliation(s)
- Genaro Gabriel Ortiz
- Department of Philosophical and Methodological Disciplines and Service of Molecular Biology in Medicine Hospital, Civil University Health Sciences Center, University of Guadalajara, Guadalajara 44340, Jalisco, Mexico
- Department of Neurology, High Specialty Medical Unit, Western National Medical Center of the Mexican Institute of Social Security, Guadalajara 44329, Jalisco, Mexico
| | - Blanca M G Torres-Mendoza
- Department of Philosophical and Methodological Disciplines and Service of Molecular Biology in Medicine Hospital, Civil University Health Sciences Center, University of Guadalajara, Guadalajara 44340, Jalisco, Mexico
- Neurosciences Division, Western Biomedical Research Center, Mexican Social Security Institute (Instituto Mexicano del Seguro Social, IMSS), Guadalajara 44340, Jalisco, Mexico
| | - Javier Ramírez-Jirano
- Neurosciences Division, Western Biomedical Research Center, Mexican Social Security Institute (Instituto Mexicano del Seguro Social, IMSS), Guadalajara 44340, Jalisco, Mexico
| | - Jazmin Marquez-Pedroza
- Neurosciences Division, Western Biomedical Research Center, Mexican Social Security Institute (Instituto Mexicano del Seguro Social, IMSS), Guadalajara 44340, Jalisco, Mexico
- Coordination of Academic Activities, Western Biomedical Research Center, Mexican Social Security Institute (Instituto Mexicano del Seguro Social, IMSS), Guadalajara 44340, Jalisco, Mexico
| | - José J Hernández-Cruz
- Department of Neurology, High Specialty Medical Unit, Western National Medical Center of the Mexican Institute of Social Security, Guadalajara 44329, Jalisco, Mexico
| | - Mario A Mireles-Ramirez
- Department of Neurology, High Specialty Medical Unit, Western National Medical Center of the Mexican Institute of Social Security, Guadalajara 44329, Jalisco, Mexico
| | - Erandis D Torres-Sánchez
- Department of Medical and Life Sciences, University Center of la Cienega, University of Guadalajara, Ocotlan 47820, Jalisco, Mexico
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Jun YK, Yu DA, Han YM, Lee SR, Koh SJ, Park H. The Relationship Between Rosacea and Inflammatory Bowel Disease: A Systematic Review and Meta-analysis. Dermatol Ther (Heidelb) 2023:10.1007/s13555-023-00964-6. [PMID: 37338720 DOI: 10.1007/s13555-023-00964-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Accepted: 06/07/2023] [Indexed: 06/21/2023] Open
Abstract
INTRODUCTION Rosacea and inflammatory bowel disease (IBD) are chronic inflammatory disorders of the skin and the gut, which are interfaces between the environment and the human body. Although growing evidence has implicated a possible link between rosacea and IBD, it remains unclear whether IBD increases the risk of rosacea and vice versa. Therefore, we investigated the association between rosacea and IBD in this study. METHODS We performed a systematic review and meta-analysis according to the Preferred Reporting Items for Systematic Review and Meta-analysis (PRISMA) guidelines. RESULTS Eight eligible studies were included in this meta-analysis. Overall, the prevalence of rosacea was higher in the IBD group than in the control group, with a pooled odds ratio (OR) of 1.86 (95% confidence interval [CI](1), 1.52-2.26). Both the Crohn's disease and the ulcerative colitis groups had higher prevalences of rosacea than the control group, with ORs of 1.74 (95% CI 1.34-2.28) and 2.00 (95% CI 1.63-2.45), respectively. Compared with those in the control group, the risks of IBD, Crohn's disease, and ulcerative colitis were significantly higher in the rosacea group, with incidence rate ratios of 1.37 (95% CI 1.22-1.53), 1.60 (95% CI 1.33-1.92), and 1.26 (95% CI 1.09-1.45), respectively. CONCLUSION Our meta-analysis suggests that IBD is bidirectionally associated with rosacea. Future interdisciplinary studies are needed to better understand the mechanism of interaction between rosacea and IBD .
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Affiliation(s)
- Yu Kyung Jun
- Division of Gastroenterology, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, Korea
- Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, 101 Daehak-ro Jongno-gu, Seoul, 03080, Korea
- Laboratory of Intestinal Mucosa and Skin Immunology, Seoul National University College of Medicine, Seoul, Korea
| | - Da-Ae Yu
- Department of Dermatology, Konkuk University School of Medicine, Seoul, Korea
| | - Yoo Min Han
- Department of Internal Medicine and Healthcare Research Institute, Seoul National University Hospital Healthcare System Gangnam Center, Seoul, Korea
- Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, 101 Daehak-ro Jongno-gu, Seoul, 03080, Korea
| | - Soo Ran Lee
- Department of Dermatology, SMG-SNU Boramae Medical Center, 20 Boramaero-5-gil, Dongjak-gu, Seoul, 07061, Korea
| | - Seong-Joon Koh
- Department of Internal Medicine and Liver Research Institute, Seoul National University College of Medicine, 101 Daehak-ro Jongno-gu, Seoul, 03080, Korea.
- Laboratory of Intestinal Mucosa and Skin Immunology, Seoul National University College of Medicine, Seoul, Korea.
| | - Hyunsun Park
- Department of Dermatology, SMG-SNU Boramae Medical Center, 20 Boramaero-5-gil, Dongjak-gu, Seoul, 07061, Korea.
- Laboratory of Intestinal Mucosa and Skin Immunology, Seoul National University College of Medicine, Seoul, Korea.
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Zhang HG, McDermott G, Seyok T, Huang S, Dahal K, L'Yi S, Lea-Bonzel C, Stratton J, Weisenfeld D, Monach P, Raychaudhuri S, Yu KH, Cai T, Cui J, Hong C, Cai T, Liao KP. Identifying shared genetic architecture between rheumatoid arthritis and other conditions: a phenome-wide association study with genetic risk scores. EBioMedicine 2023; 92:104581. [PMID: 37121095 PMCID: PMC10173154 DOI: 10.1016/j.ebiom.2023.104581] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2022] [Revised: 03/19/2023] [Accepted: 04/05/2023] [Indexed: 05/02/2023] Open
Abstract
BACKGROUND Rheumatoid arthritis (RA) shares genetic variants with other autoimmune conditions, but existing studies test the association between RA variants with a pre-defined set of phenotypes. The objective of this study was to perform a large-scale, systemic screen to determine phenotypes that share genetic architecture with RA to inform our understanding of shared pathways. METHODS In the UK Biobank (UKB), we constructed RA genetic risk scores (GRS) incorporating human leukocyte antigen (HLA) and non-HLA risk alleles. Phenotypes were defined using groupings of International Classification of Diseases (ICD) codes. Patients with an RA code were excluded to mitigate the possibility of associations being driven by the diagnosis or management of RA. We performed a phenome-wide association study, testing the association between the RA GRS with phenotypes using multivariate generalized estimating equations that adjusted for age, sex, and first five principal components. Statistical significance was defined using Bonferroni correction. Results were replicated in an independent cohort and replicated phenotypes were validated using medical record review of patients. FINDINGS We studied n = 316,166 subjects from UKB without evidence of RA and screened for association between the RA GRS and n = 1317 phenotypes. In the UKB, 20 phenotypes were significantly associated with the RA GRS, of which 13 (65%) were immune mediated conditions including polymyalgia rheumatica, granulomatosis with polyangiitis (GPA), type 1 diabetes, and multiple sclerosis. We further identified a novel association in Celiac disease where the HLA and non-HLA alleles had strong associations in opposite directions. Strikingly, we observed that the non-HLA GRS was exclusively associated with greater risk of the validated conditions, suggesting shared underlying pathways outside the HLA region. INTERPRETATION This study replicated and identified novel autoimmune phenotypes verified by medical record review that share immune pathways with RA and may inform opportunities for shared treatment targets, as well as risk assessment for conditions with a paucity of genomic data, such as GPA. FUNDING This research was funded by the US National Institutes of Health (P30AR072577, R21AR078339, R35GM142879, T32AR007530) and the Harold and DuVal Bowen Fund.
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Affiliation(s)
- Harrison G Zhang
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Greg McDermott
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Thany Seyok
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Sicong Huang
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Kumar Dahal
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Sehi L'Yi
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Clara Lea-Bonzel
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Jacklyn Stratton
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Dana Weisenfeld
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Paul Monach
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; VA Boston Healthcare System, Boston, MA, USA
| | - Soumya Raychaudhuri
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; Center for Data Science, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Kun-Hsing Yu
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Tianrun Cai
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Jing Cui
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Chuan Hong
- Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA
| | - Tianxi Cai
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; VA Boston Healthcare System, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Katherine P Liao
- Division of Rheumatology, Inflammation, and Immunity, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA; VA Boston Healthcare System, Boston, MA, USA.
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Germline genetic variation and predicting immune checkpoint inhibitor induced toxicity. NPJ Genom Med 2022; 7:73. [PMID: 36564402 PMCID: PMC9789157 DOI: 10.1038/s41525-022-00345-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 12/07/2022] [Indexed: 12/25/2022] Open
Abstract
Immune checkpoint inhibitor (ICI) therapy has revolutionised the treatment of various cancer types. ICIs reinstate T-cell function to elicit an anti-cancer immune response. The resulting immune response can however have off-target effects which manifest as autoimmune type serious immune-related adverse events (irAE) in ~10-55% of patients treated. It is currently challenging to predict both who will experience irAEs and to what severity. Identification of patients at high risk of serious irAE would revolutionise patient care. While the pathogenesis driving irAE development is still unclear, host genetic factors are proposed to be key determinants of these events. This review presents current evidence supporting the role of the host genome in determining risk of irAE. We summarise the spectrum and timing of irAEs following treatment with ICIs and describe currently reported germline genetic variation associated with expression of immuno-modulatory factors within the cancer immunity cycle, development of autoimmune disease and irAE occurrence. We propose that germline genetic determinants of host immune function and autoimmune diseases could also explain risk of irAE development. We also endorse genome-wide association studies of patients being treated with ICIs to identify genetic variants that can be used in polygenic risk scores to predict risk of irAE.
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Van Horebeek L, Dedoncker N, Dubois B, Goris A. Frequent somatic mosaicism in T lymphocyte subsets in individuals with and without multiple sclerosis. Front Immunol 2022; 13:993178. [PMID: 36618380 PMCID: PMC9817019 DOI: 10.3389/fimmu.2022.993178] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Accepted: 12/09/2022] [Indexed: 12/25/2022] Open
Abstract
Background Somatic variants are variations in an individual's genome acquired after the zygotic stadium and result from mitotic errors or not (fully) repaired DNA damage. Objectives To investigate whether somatic mosaicism in T lymphocyte subsets is enriched early in multiple sclerosis (MS). Methods We identified somatic variants with variant allele fractions ≥1% across the whole exome in CD4+ and CD8+ T lymphocytes of 21 treatment-naive MS patients with <5 years of disease duration and 16 partially age-matched healthy controls. We investigated the known somatic STAT3 variant p.Y640F in peripheral blood in a larger cohort of 446 MS patients and 259 controls. Results All subjects carried 1-142 variants in CD4+ or CD8+ T lymphocytes. Variants were more common, more abundant, and increased with age in CD8+ T lymphocytes. Somatic variants were common in the genes DNMT3A and especially STAT3. Overall, the presence or abundance of somatic variants, including the STAT3 p.Y640F variant, did not differ between MS patients and controls. Conclusions Somatic variation in T lymphocyte subsets is widespread in both control individuals and MS patients. Somatic mosaicism in T lymphocyte subsets is not enriched in early MS and thus unlikely to contribute to MS risk, but future research needs to address whether a subset of variants influences disease susceptibility.
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Affiliation(s)
- Lies Van Horebeek
- Laboratory for Neuroimmunology, Department of Neurosciences, Leuven Brain Institute, Katholieke Universiteit (KU) Leuven, Leuven, Belgium
| | - Nina Dedoncker
- Laboratory for Neuroimmunology, Department of Neurosciences, Leuven Brain Institute, Katholieke Universiteit (KU) Leuven, Leuven, Belgium
| | - Bénédicte Dubois
- Laboratory for Neuroimmunology, Department of Neurosciences, Leuven Brain Institute, Katholieke Universiteit (KU) Leuven, Leuven, Belgium,Department of Neurology, University Hospitals Leuven, Leuven, Belgium
| | - An Goris
- Laboratory for Neuroimmunology, Department of Neurosciences, Leuven Brain Institute, Katholieke Universiteit (KU) Leuven, Leuven, Belgium,*Correspondence: An Goris,
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Zhao C, Jia X, Wang Y, Luo Z, Fan J, Shi X, Yang Y. Overlapping genetic susceptibility of seven autoimmune diseases:SPU tests based on genome-wide association summary statistics. Gene 2022; 851:147036. [DOI: 10.1016/j.gene.2022.147036] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 10/26/2022] [Accepted: 11/04/2022] [Indexed: 11/11/2022]
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Samuels H, Malov M, Saha Detroja T, Ben Zaken K, Bloch N, Gal-Tanamy M, Avni O, Polis B, Samson AO. Autoimmune Disease Classification Based on PubMed Text Mining. J Clin Med 2022; 11:jcm11154345. [PMID: 35893435 PMCID: PMC9369164 DOI: 10.3390/jcm11154345] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 06/15/2022] [Accepted: 07/08/2022] [Indexed: 11/30/2022] Open
Abstract
Autoimmune diseases (AIDs) are often co-associated, and about 25% of patients with one AID tend to develop other comorbid AIDs. Here, we employ the power of datamining to predict the comorbidity of AIDs based on their normalized co-citation in PubMed. First, we validate our technique in a test dataset using earlier-reported comorbidities of seven knowns AIDs. Notably, the prediction correlates well with comorbidity (R = 0.91) and validates our methodology. Then, we predict the association of 100 AIDs and classify them using principal component analysis. Our results are helpful in classifying AIDs into one of the following systems: (1) gastrointestinal, (2) neuronal, (3) eye, (4) cutaneous, (5) musculoskeletal, (6) kidneys and lungs, (7) cardiovascular, (8) hematopoietic, (9) endocrine, and (10) multiple. Our classification agrees with experimentally based taxonomy and ranks AID according to affected systems and gender. Some AIDs are unclassified and do not associate well with other AIDs. Interestingly, Alzheimer’s disease correlates well with other AIDs such as multiple sclerosis. Finally, our results generate a network classification of autoimmune diseases based on PubMed text mining and help map this medical universe. Our results are expected to assist healthcare workers in diagnosing comorbidity in patients with an autoimmune disease, and to help researchers in identifying common genetic, environmental, and autoimmune mechanisms.
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Affiliation(s)
- Hadas Samuels
- Azrieli Faculty of Medicine, Bar Ilan University, Safed 1311502, Israel; (H.S.); (M.M.); (T.S.D.); (K.B.Z.); (N.B.); (M.G.-T.); (O.A.)
| | - Malki Malov
- Azrieli Faculty of Medicine, Bar Ilan University, Safed 1311502, Israel; (H.S.); (M.M.); (T.S.D.); (K.B.Z.); (N.B.); (M.G.-T.); (O.A.)
| | - Trishna Saha Detroja
- Azrieli Faculty of Medicine, Bar Ilan University, Safed 1311502, Israel; (H.S.); (M.M.); (T.S.D.); (K.B.Z.); (N.B.); (M.G.-T.); (O.A.)
| | - Karin Ben Zaken
- Azrieli Faculty of Medicine, Bar Ilan University, Safed 1311502, Israel; (H.S.); (M.M.); (T.S.D.); (K.B.Z.); (N.B.); (M.G.-T.); (O.A.)
| | - Naamah Bloch
- Azrieli Faculty of Medicine, Bar Ilan University, Safed 1311502, Israel; (H.S.); (M.M.); (T.S.D.); (K.B.Z.); (N.B.); (M.G.-T.); (O.A.)
| | - Meital Gal-Tanamy
- Azrieli Faculty of Medicine, Bar Ilan University, Safed 1311502, Israel; (H.S.); (M.M.); (T.S.D.); (K.B.Z.); (N.B.); (M.G.-T.); (O.A.)
| | - Orly Avni
- Azrieli Faculty of Medicine, Bar Ilan University, Safed 1311502, Israel; (H.S.); (M.M.); (T.S.D.); (K.B.Z.); (N.B.); (M.G.-T.); (O.A.)
| | - Baruh Polis
- School of Medicine, Yale University, New Haven, CT 06520, USA;
| | - Abraham O. Samson
- Azrieli Faculty of Medicine, Bar Ilan University, Safed 1311502, Israel; (H.S.); (M.M.); (T.S.D.); (K.B.Z.); (N.B.); (M.G.-T.); (O.A.)
- Correspondence:
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10
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Ramírez-Bello J, Jiménez-Morales S, Barbosa-Cobos RE, Sánchez-Zauco N, Hernández-Molina G, Luria-Pérez R, Fragoso JM, Cabello-Gutiérrez C, Montúfar-Robles I. TNFSF4 is a risk factor for rheumatoid arthritis but not for primary Sjögren's syndrome in the Mexican population. Immunobiology 2022; 227:152244. [PMID: 35835012 DOI: 10.1016/j.imbio.2022.152244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 06/04/2022] [Accepted: 07/06/2022] [Indexed: 11/29/2022]
Abstract
PURPOSE Rheumatoid arthritis (RA) and primary Sjögren's syndrome (pSS) are autoimmune diseases (ADs) characterized by joint damage and involvement of the salivary glands, respectively. ADs share some susceptibility loci, such as TNFSF4, which is a classical susceptibility gene associated with systemic lupus erythematosus, but its role in RA and pSS is not yet clear. Thus, the aim of this study was to determine whether three TNFSFS4 polymorphisms are associated with RA and pSS. METHODS Our case-control study included 500 controls, 459 patients with RA, and 210 patients with pSS from Mexico. TNFSF4 single nucleotide polymorphisms (SNPs) rs1234315C/T, rs2205960G/T, and rs704840T/G were genotyped using TaqMan probes and discrimination allelic assay. RESULTS The three TNFSF4 SNPs were associated with susceptibility to RA (rs1234315C/T: odds ratio [OR] 1.4, p = 0.01; rs2205960G/T: OR 1.23, p = 0.03; rs704840T/G: OR 1.24, p = 0.02). An association between TNFSF4 rs1234315C/T and pSS was also observed (OR 1.28, p = 0.04), however, after Bonferroni correction, this association was lost. CONCLUSION Our data suggest that TNFSF4 could be a risk factor in RA but not pSS in a Mexican population.
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Affiliation(s)
- Julian Ramírez-Bello
- Departamento de Endocrinología, Instituto Nacional de Cardiología Ignacio Chávez, 14080 Mexico City, Mexico.
| | - Silvia Jiménez-Morales
- Laboratorio de Genómica del Cáncer, Instituto Nacional de Medicina Genómica, 14610 Mexico City, Mexico.
| | | | - Norma Sánchez-Zauco
- División de Auxiliares de Diagnóstico y Tratamiento, UMAE Hospital de Especialidades, Centro Médico Nacional Siglo XXI, 06720 IMSS, Mexico.
| | - Gabriela Hernández-Molina
- Departamento de Inmunología y Reumatología, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, 14080 Mexico City, Mexico.
| | - Rosendo Luria-Pérez
- Unidad de Investigación en Enfermedades Hemato-Oncológicas, Hospital Infantil de México Federico Gómez, 06720, Mexico.
| | - José M Fragoso
- Departamento de Biología Molecular, Instituto Nacional de Cardiología Ignacio Chávez, 14080 Mexico City, Mexico.
| | - Carlos Cabello-Gutiérrez
- Departamento de Investigación en Virología y Micología, Instituto Nacional de Enfermedades Respiratorias, 14080 Mexico City, Mexico.
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11
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Julienne H, Laville V, McCaw ZR, He Z, Guillemot V, Lasry C, Ziyatdinov A, Nerin C, Vaysse A, Lechat P, Ménager H, Le Goff W, Dube MP, Kraft P, Ionita-Laza I, Vilhjálmsson BJ, Aschard H. Multitrait GWAS to connect disease variants and biological mechanisms. PLoS Genet 2021; 17:e1009713. [PMID: 34460823 PMCID: PMC8437297 DOI: 10.1371/journal.pgen.1009713] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 09/13/2021] [Accepted: 07/12/2021] [Indexed: 12/30/2022] Open
Abstract
Genome-wide association studies (GWASs) have uncovered a wealth of associations between common variants and human phenotypes. Here, we present an integrative analysis of GWAS summary statistics from 36 phenotypes to decipher multitrait genetic architecture and its link with biological mechanisms. Our framework incorporates multitrait association mapping along with an investigation of the breakdown of genetic associations into clusters of variants harboring similar multitrait association profiles. Focusing on two subsets of immunity and metabolism phenotypes, we then demonstrate how genetic variants within clusters can be mapped to biological pathways and disease mechanisms. Finally, for the metabolism set, we investigate the link between gene cluster assignment and the success of drug targets in randomized controlled trials.
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Affiliation(s)
- Hanna Julienne
- Department of Computational Biology, Institut Pasteur, Paris, France
| | - Vincent Laville
- Department of Computational Biology, Institut Pasteur, Paris, France
| | - Zachary R. McCaw
- Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Zihuai He
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, California, United States of America
| | - Vincent Guillemot
- Department of Computational Biology, Institut Pasteur, Paris, France
| | - Carla Lasry
- Department of Computational Biology, Institut Pasteur, Paris, France
| | - Andrey Ziyatdinov
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Cyril Nerin
- Department of Computational Biology, Institut Pasteur, Paris, France
| | - Amaury Vaysse
- Department of Computational Biology, Institut Pasteur, Paris, France
| | - Pierre Lechat
- Department of Computational Biology, Institut Pasteur, Paris, France
| | - Hervé Ménager
- Department of Computational Biology, Institut Pasteur, Paris, France
| | - Wilfried Le Goff
- Sorbonne Université, INSERM, Institute of Cardiometabolism and Nutrition (ICAN), UMR_S 1166, Paris, France
| | - Marie-Pierre Dube
- Université de Montréal Beaulieu-Saucier Pharmacogenomics Centre, Montreal Heart Institute, Montreal, Canada
- Université de Montréal, Faculty of Medicine, Department of medicine, Université de Montréal, Montreal, Canada
| | - Peter Kraft
- Department of Biostatistics, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America
| | - Iuliana Ionita-Laza
- Department of Biostatistics, Columbia University, New York, New York, United States of America
| | - Bjarni J. Vilhjálmsson
- National Centre for Register-based Research, Department of Economics and Business Economics, Aarhus University, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Hugues Aschard
- Department of Computational Biology, Institut Pasteur, Paris, France
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, Massachusetts, United States of America
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12
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Shen Y, Tang K, Chen D, Hong M, Sun F, Wang S, Ke Y, Wu T, Sun R, Qian J, Du Y. Riok3 inhibits the antiviral immune response by facilitating TRIM40-mediated RIG-I and MDA5 degradation. Cell Rep 2021; 35:109272. [PMID: 34161773 PMCID: PMC8363743 DOI: 10.1016/j.celrep.2021.109272] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 01/07/2021] [Accepted: 05/27/2021] [Indexed: 02/07/2023] Open
Abstract
The type I interferon (IFN) pathway is a key component of innate immune response upon invasion of foreign pathogens. It is also under precise control to prevent excessive upregulation and undesired inflammation cascade. In the present study, we report that Riok3, an atypical kinase, negatively regulates retinoic acid-inducible gene-I (RIG-I)-like receptors (RLRs) sensing-induced type I IFN signaling. Riok3 deficiency selectively inhibits RNA viral replication in vitro, resulting from an upregulated type I IFN pathway. Mice with myeloid-specific Riok3 knockout also show a more robust induction of type I IFN upon RNA virus infection and are more resistant to RNA virus-induced pathogenesis. Mechanistically, Riok3 recruits and interacts with the E3 ubiquitin ligase TRIM40, leading to the degradation of RIG-I and melanoma differentiation-associated gene-5 (MDA5) via K48- and K27-linked ubiquitination. Collectively, our data reveal the mechanism that Riok3 employs to be a negative regulator of antiviral innate immunity.
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Affiliation(s)
- Yong Shen
- Cancer Institute, ZJU-UCLA Joint Center for Medical Education and Research, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, P.R. China; Department of Breast Surgery, The First Affiliated Hospital, Zhejiang Chinese Medical University, Hangzhou, P.R. China
| | - Kejun Tang
- Cancer Institute, ZJU-UCLA Joint Center for Medical Education and Research, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, P.R. China; Department of Surgery, Women's Hospital, School of Medicine, Zhejiang University, Hangzhou, P.R. China
| | - Dongdong Chen
- Cancer Institute, ZJU-UCLA Joint Center for Medical Education and Research, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, P.R. China
| | - Mengying Hong
- Cancer Institute, ZJU-UCLA Joint Center for Medical Education and Research, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, P.R. China
| | - Fangfang Sun
- Cancer Institute, ZJU-UCLA Joint Center for Medical Education and Research, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, P.R. China
| | - SaiSai Wang
- Department of Colorectal Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, P.R. China
| | - Yuehai Ke
- Department of Pathology and Pathophysiology, Program in Molecular Cell Biology, Zhejiang University School of Medicine, Hangzhou, China
| | - Tingting Wu
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Ren Sun
- Cancer Institute, ZJU-UCLA Joint Center for Medical Education and Research, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, P.R. China; Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; School of Biomedical Sciences, LKS Faculty of Medicine, The Hongkong University, Hongkong, China.
| | - Jing Qian
- Pharmaceutical Informatics Institute, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, P.R. China.
| | - Yushen Du
- Cancer Institute, ZJU-UCLA Joint Center for Medical Education and Research, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, P.R. China; Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
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13
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Sticht J, Álvaro-Benito M, Konigorski S. Type 1 Diabetes and the HLA Region: Genetic Association Besides Classical HLA Class II Genes. Front Genet 2021; 12:683946. [PMID: 34220961 PMCID: PMC8248358 DOI: 10.3389/fgene.2021.683946] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Accepted: 05/25/2021] [Indexed: 01/07/2023] Open
Abstract
Type 1 diabetes is an autoimmune disease with rising incidence in high-income countries. Genetic and environmental predisposing factors contribute to the etiology of the disease, although their interaction is not sufficiently understood to allow for preventive action. Strongest known associations with genetic variation map to classical HLA class II genes. Because of its genetic complexity, the HLA region has been under-represented in genome-wide association studies, having potentially hindered the identification of relevant associations underlying the etiology of the disease. Here, we performed a comprehensive HLA-wide genetic association analysis of type 1 diabetes including multi-allelic and rare variants. We used high-density whole-exome sequencing data of the HLA region in the large UK Biobank dataset to apply gene-based association tests with a carefully defined type 1 diabetes phenotype (97 cases and 48,700 controls). Exon-based and single-variant association tests were used to complement the analysis. We replicated the known association of type 1 diabetes with the classical HLA-DQ gene. Tailoring the analysis toward rare variants, we additionally identified the lysine methyl transferase EHMT2 as associated. Deeper insight into genetic variation associated with disease as presented and discussed in detail here can help unraveling mechanistic details of the etiology of type 1 diabetes. More specifically, we hypothesize that genetic variation in EHMT2 could impact autoimmunity in type 1 diabetes development.
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Affiliation(s)
- Jana Sticht
- Digital Health and Machine Learning Research Group, Hasso Plattner Institute for Digital Engineering, Potsdam, Germany.,Laboratory of Protein Biochemistry, Department of Biology, Chemistry and Pharmacy, Freie Universität Berlin, Berlin, Germany
| | - Miguel Álvaro-Benito
- Laboratory of Protein Biochemistry, Department of Biology, Chemistry and Pharmacy, Freie Universität Berlin, Berlin, Germany
| | - Stefan Konigorski
- Digital Health and Machine Learning Research Group, Hasso Plattner Institute for Digital Engineering, Potsdam, Germany
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14
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Jia X, Zhao C, Zhao W. Emerging Roles of MHC Class I Region-Encoded E3 Ubiquitin Ligases in Innate Immunity. Front Immunol 2021; 12:687102. [PMID: 34177938 PMCID: PMC8222901 DOI: 10.3389/fimmu.2021.687102] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Accepted: 05/27/2021] [Indexed: 12/15/2022] Open
Abstract
The major histocompatibility complex (MHC) class I (MHC-I) region contains a multitude of genes relevant to immune response. Multiple E3 ubiquitin ligase genes, including tripartite motif 10 (TRIM10), TRIM15, TRIM26, TRIM27, TRIM31, TRIM38, TRIM39, TRIM40, and RING finger protein 39 (RNF39), are organized in a tight cluster, and an additional two TRIM genes (namely TRIM38 and TRIM27) telomeric of the cluster within the MHC-I region. The E3 ubiquitin ligases encoded by these genes possess important roles in controlling the intensity of innate immune responses. In this review, we discuss the E3 ubiquitin ligases encoded within the MHC-I region, highlight their regulatory roles in innate immunity, and outline their potential functions in infection, inflammatory and autoimmune diseases.
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Affiliation(s)
- Xiuzhi Jia
- Department of Pathogenic Biology, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Chunyuan Zhao
- Department of Pathogenic Biology, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Wei Zhao
- Department of Pathogenic Biology, School of Basic Medical Science, Cheeloo College of Medicine, Shandong University, Jinan, China
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15
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Prins BP, Leitsalu L, Pärna K, Fischer K, Metspalu A, Haller T, Snieder H. Advances in Genomic Discovery and Implications for Personalized Prevention and Medicine: Estonia as Example. J Pers Med 2021; 11:jpm11050358. [PMID: 33946982 PMCID: PMC8145318 DOI: 10.3390/jpm11050358] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 04/19/2021] [Accepted: 04/25/2021] [Indexed: 02/07/2023] Open
Abstract
The current paradigm of personalized medicine envisages the use of genomic data to provide predictive information on the health course of an individual with the aim of prevention and individualized care. However, substantial efforts are required to realize the concept: enhanced genetic discoveries, translation into intervention strategies, and a systematic implementation in healthcare. Here we review how further genetic discoveries are improving personalized prediction and advance functional insights into the link between genetics and disease. In the second part we give our perspective on the way these advances in genomic research will transform the future of personalized prevention and medicine using Estonia as a primer.
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Affiliation(s)
- Bram Peter Prins
- MRC/BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK
- Correspondence: (B.P.P.); (H.S.)
| | - Liis Leitsalu
- Institute of Genomics, University of Tartu, 51010 Tartu, Estonia; (L.L.); (K.P.); (K.F.); (A.M.); (T.H.)
| | - Katri Pärna
- Institute of Genomics, University of Tartu, 51010 Tartu, Estonia; (L.L.); (K.P.); (K.F.); (A.M.); (T.H.)
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands
- Institute of Molecular and Cell Biology, University of Tartu, 51010 Tartu, Estonia
| | - Krista Fischer
- Institute of Genomics, University of Tartu, 51010 Tartu, Estonia; (L.L.); (K.P.); (K.F.); (A.M.); (T.H.)
- Institute of Mathematics and Statistics, University of Tartu, 50409 Tartu, Estonia
| | - Andres Metspalu
- Institute of Genomics, University of Tartu, 51010 Tartu, Estonia; (L.L.); (K.P.); (K.F.); (A.M.); (T.H.)
| | - Toomas Haller
- Institute of Genomics, University of Tartu, 51010 Tartu, Estonia; (L.L.); (K.P.); (K.F.); (A.M.); (T.H.)
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands
- Correspondence: (B.P.P.); (H.S.)
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16
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Díaz-Santiago E, Claros MG, Yahyaoui R, de Diego-Otero Y, Calvo R, Hoenicka J, Palau F, Ranea JAG, Perkins JR. Decoding Neuromuscular Disorders Using Phenotypic Clusters Obtained From Co-Occurrence Networks. Front Mol Biosci 2021; 8:635074. [PMID: 34046427 PMCID: PMC8147726 DOI: 10.3389/fmolb.2021.635074] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Accepted: 02/15/2021] [Indexed: 12/19/2022] Open
Abstract
Neuromuscular disorders (NMDs) represent an important subset of rare diseases associated with elevated morbidity and mortality whose diagnosis can take years. Here we present a novel approach using systems biology to produce functionally-coherent phenotype clusters that provide insight into the cellular functions and phenotypic patterns underlying NMDs, using the Human Phenotype Ontology as a common framework. Gene and phenotype information was obtained for 424 NMDs in OMIM and 126 NMDs in Orphanet, and 335 and 216 phenotypes were identified as typical for NMDs, respectively. ‘Elevated serum creatine kinase’ was the most specific to NMDs, in agreement with the clinical test of elevated serum creatinine kinase that is conducted on NMD patients. The approach to obtain co-occurring NMD phenotypes was validated based on co-mention in PubMed abstracts. A total of 231 (OMIM) and 150 (Orphanet) clusters of highly connected co-occurrent NMD phenotypes were obtained. In parallel, a tripartite network based on phenotypes, diseases and genes was used to associate NMD phenotypes with functions, an approach also validated by literature co-mention, with KEGG pathways showing proportionally higher overlap than Gene Ontology and Reactome. Phenotype-function pairs were crossed with the co-occurrent NMD phenotype clusters to obtain 40 (OMIM) and 72 (Orphanet) functionally coherent phenotype clusters. As expected, many of these overlapped with known diseases and confirmed existing knowledge. Other clusters revealed interesting new findings, indicating informative phenotypes for differential diagnosis, providing deeper knowledge of NMDs, and pointing towards specific cell dysfunction caused by pleiotropic genes. This work is an example of reproducible research that i) can help better understand NMDs and support their diagnosis by providing a new tool that exploits existing information to obtain novel clusters of functionally-related phenotypes, and ii) takes us another step towards personalised medicine for NMDs.
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Affiliation(s)
- Elena Díaz-Santiago
- Department of Molecular Biology and Biochemistry, Universidad de Málaga, Málaga, Spain
| | - M Gonzalo Claros
- Department of Molecular Biology and Biochemistry, Universidad de Málaga, Málaga, Spain.,CIBER de Enfermedades Raras (CIBERER), Madrid, Spain.,Institute of Biomedical Research in Malaga (IBIMA), IBIMA-RARE, Málaga, Spain.,Institute for Mediterranean and Subtropical Horticulture "La Mayora" (IHSM-UMA-CSIC), Málaga, Spain
| | - Raquel Yahyaoui
- Institute of Biomedical Research in Malaga (IBIMA), IBIMA-RARE, Málaga, Spain.,Laboratory of Metabolopathies and Neonatal Screening, Málaga Regional University Hospital, Málaga, Spain
| | | | - Rocío Calvo
- Institute of Biomedical Research in Malaga (IBIMA), IBIMA-RARE, Málaga, Spain.,Laboratory of Metabolopathies and Neonatal Screening, Málaga Regional University Hospital, Málaga, Spain
| | - Janet Hoenicka
- CIBER de Enfermedades Raras (CIBERER), Madrid, Spain.,Sant Joan de Déu Hospital and Research Institute, Barcelona, Spain
| | - Francesc Palau
- CIBER de Enfermedades Raras (CIBERER), Madrid, Spain.,Sant Joan de Déu Hospital and Research Institute, Barcelona, Spain.,Hospital Clínic and University of Barcelona School of Medicine and Health Sciences, Barcelona, Spain
| | - Juan A G Ranea
- Department of Molecular Biology and Biochemistry, Universidad de Málaga, Málaga, Spain.,CIBER de Enfermedades Raras (CIBERER), Madrid, Spain.,Institute of Biomedical Research in Malaga (IBIMA), IBIMA-RARE, Málaga, Spain
| | - James R Perkins
- Department of Molecular Biology and Biochemistry, Universidad de Málaga, Málaga, Spain.,CIBER de Enfermedades Raras (CIBERER), Madrid, Spain.,Institute of Biomedical Research in Malaga (IBIMA), IBIMA-RARE, Málaga, Spain
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17
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Higuchi T, Oka S, Furukawa H, Tohma S, Yatsuhashi H, Migita K. Genetic risk factors for autoimmune hepatitis: implications for phenotypic heterogeneity and biomarkers for drug response. Hum Genomics 2021; 15:6. [PMID: 33509297 PMCID: PMC7841991 DOI: 10.1186/s40246-020-00301-4] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2020] [Accepted: 12/15/2020] [Indexed: 01/10/2023] Open
Abstract
Autoimmune hepatitis (AIH) is a rare chronic progressive liver disease with autoimmune features. It mainly affects middle-aged women. AIH is occasionally complicated with liver cirrhosis that worsens the prognosis. Genetic and environmental factors are involved in the pathogenesis of AIH. Genetic studies of other diseases have been revealing of pathogenesis and drug efficacy. In this review, we summarize the genetic risk factors for AIH, including human leukocyte antigen (HLA) and non-HLA genes. A genome-wide association study (GWAS) on European AIH revealed the strongest associations to be with single nucleotide variants (SNVs) in HLA. Predisposing alleles for AIH were DRB1*03:01 and DRB1*04:01 in Europeans; DRB1*04:04, DRB1*04:05, and DRB1*13:01 in Latin Americans; and DRB1*04:01 and DRB1*04:05 in Japanese. Other risk SNVs in non-HLA genes for AIH were found by a candidate gene approach, but several SNVs were confirmed in replication studies. Some genetic factors of AIH overlapped with those of other autoimmune diseases. Larger-scale GWASs of other ethnic groups are required. The results of genetic studies might provide an explanation for the phenotypic heterogeneity of AIH and biomarkers for drug responses.
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Affiliation(s)
- Takashi Higuchi
- Molecular and Genetic Epidemiology Laboratory, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, 305-8575, Japan.,Department of Nephrology, Ushiku Aiwa General Hospital, 896 Shishiko-cho, Ushiku, 300-1296, Japan.,Department of Rheumatology, National Hospital Organization Tokyo National Hospital, 3-1-1 Takeoka, Kiyose, 204-8585, Japan
| | - Shomi Oka
- Molecular and Genetic Epidemiology Laboratory, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, 305-8575, Japan.,Department of Rheumatology, National Hospital Organization Tokyo National Hospital, 3-1-1 Takeoka, Kiyose, 204-8585, Japan.,Clinical Research Center for Allergy and Rheumatology, National Hospital Organization Sagamihara National Hospital, 18-1 Sakuradai, Minami-ku, Sagamihara, 252-0392, Japan
| | - Hiroshi Furukawa
- Molecular and Genetic Epidemiology Laboratory, Faculty of Medicine, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, 305-8575, Japan. .,Department of Rheumatology, National Hospital Organization Tokyo National Hospital, 3-1-1 Takeoka, Kiyose, 204-8585, Japan. .,Clinical Research Center for Allergy and Rheumatology, National Hospital Organization Sagamihara National Hospital, 18-1 Sakuradai, Minami-ku, Sagamihara, 252-0392, Japan.
| | - Shigeto Tohma
- Department of Rheumatology, National Hospital Organization Tokyo National Hospital, 3-1-1 Takeoka, Kiyose, 204-8585, Japan.,Clinical Research Center for Allergy and Rheumatology, National Hospital Organization Sagamihara National Hospital, 18-1 Sakuradai, Minami-ku, Sagamihara, 252-0392, Japan
| | - Hiroshi Yatsuhashi
- Clinical Research Center, National Hospital Organization Nagasaki Medical Center, 2-1001-1 Kubara, Omura, 856-8562, Japan
| | - Kiyoshi Migita
- Clinical Research Center, National Hospital Organization Nagasaki Medical Center, 2-1001-1 Kubara, Omura, 856-8562, Japan.,Department of Rheumatology, Fukushima Medical University School of Medicine, 1 Hikarigaoka, Fukushima, 960-1295, Japan
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18
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Ruiz-Ballesteros AI, Meza-Meza MR, Vizmanos-Lamotte B, Parra-Rojas I, de la Cruz-Mosso U. Association of Vitamin D Metabolism Gene Polymorphisms with Autoimmunity: Evidence in Population Genetic Studies. Int J Mol Sci 2020; 21:ijms21249626. [PMID: 33348854 PMCID: PMC7766382 DOI: 10.3390/ijms21249626] [Citation(s) in RCA: 50] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2020] [Revised: 12/08/2020] [Accepted: 12/15/2020] [Indexed: 02/07/2023] Open
Abstract
A high prevalence of vitamin D (calcidiol) serum deficiency has been described in several autoimmune diseases, including multiple sclerosis (MS), rheumatoid arthritis (AR), and systemic lupus erythematosus (SLE). Vitamin D is a potent immunonutrient that through its main metabolite calcitriol, regulates the immunomodulation of macrophages, dendritic cells, T and B lymphocytes, which express the vitamin D receptor (VDR), and they produce and respond to calcitriol. Genetic association studies have shown that up to 65% of vitamin D serum variance may be explained due to genetic background. The 90% of genetic variability takes place in the form of single nucleotide polymorphisms (SNPs), and SNPs in genes related to vitamin D metabolism have been linked to influence the calcidiol serum levels, such as in the vitamin D binding protein (VDBP; rs2282679 GC), 25-hydroxylase (rs10751657 CYP2R1), 1α-hydroxylase (rs10877012, CYP27B1) and the vitamin D receptor (FokI (rs2228570), BsmI (rs1544410), ApaI (rs7975232), and TaqI (rs731236) VDR). Therefore, the aim of this comprehensive literature review was to discuss the current findings of functional SNPs in GC, CYP2R1, CYP27B1, and VDR associated to genetic risk, and the most common clinical features of MS, RA, and SLE.
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Affiliation(s)
- Adolfo I. Ruiz-Ballesteros
- Grupo de Inmunonutrición y Genómica Nutricional en las Enfermedades Autoinmunes, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara Jalisco 44160, Mexico; (A.I.R.-B.); (M.R.M.-M.)
- Instituto de Investigación en Ciencias Biomédicas, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara Jalisco 44340, Mexico
- Programa de Doctorado en Ciencias de la Nutrición Traslacional, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara Jalisco 44340, Mexico;
| | - Mónica R. Meza-Meza
- Grupo de Inmunonutrición y Genómica Nutricional en las Enfermedades Autoinmunes, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara Jalisco 44160, Mexico; (A.I.R.-B.); (M.R.M.-M.)
- Instituto de Investigación en Ciencias Biomédicas, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara Jalisco 44340, Mexico
- Programa de Doctorado en Ciencias Biomédicas Inmunología, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara Jalisco 44340, Mexico
| | - Barbara Vizmanos-Lamotte
- Programa de Doctorado en Ciencias de la Nutrición Traslacional, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara Jalisco 44340, Mexico;
- Instituto de Nutrigenética y Nutrigenómica Traslacional, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara Jalisco 44340, Mexico
| | - Isela Parra-Rojas
- Laboratorio de Investigación en Obesidad y Diabetes, Facultad de Ciencias Químico-Biológicas, Universidad Autónoma de Guerrero, Chilpancingo de los Bravo Guerrero 39087, Mexico;
| | - Ulises de la Cruz-Mosso
- Grupo de Inmunonutrición y Genómica Nutricional en las Enfermedades Autoinmunes, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara Jalisco 44160, Mexico; (A.I.R.-B.); (M.R.M.-M.)
- Instituto de Investigación en Ciencias Biomédicas, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara Jalisco 44340, Mexico
- Programa de Doctorado en Ciencias de la Nutrición Traslacional, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara Jalisco 44340, Mexico;
- Programa de Doctorado en Ciencias Biomédicas Inmunología, Centro Universitario de Ciencias de la Salud, Universidad de Guadalajara, Guadalajara Jalisco 44340, Mexico
- Correspondence: ; Tel.: +52-1-331-744-15-75
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Singh R, Chandel S, Dey D, Ghosh A, Roy S, Ravichandiran V, Ghosh D. Epigenetic modification and therapeutic targets of diabetes mellitus. Biosci Rep 2020; 40:BSR20202160. [PMID: 32815547 PMCID: PMC7494983 DOI: 10.1042/bsr20202160] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Revised: 08/07/2020] [Accepted: 08/17/2020] [Indexed: 12/11/2022] Open
Abstract
The prevalence of diabetes and its related complications are increasing significantly globally. Collected evidence suggested that several genetic and environmental factors contribute to diabetes mellitus. Associated complications such as retinopathy, neuropathy, nephropathy and other cardiovascular complications are a direct result of diabetes. Epigenetic factors include deoxyribonucleic acid (DNA) methylation and histone post-translational modifications. These factors are directly related with pathological factors such as oxidative stress, generation of inflammatory mediators and hyperglycemia. These result in altered gene expression and targets cells in the pathology of diabetes mellitus without specific changes in a DNA sequence. Environmental factors and malnutrition are equally responsible for epigenetic states. Accumulated evidence suggested that environmental stimuli alter the gene expression that result in epigenetic changes in chromatin. Recent studies proposed that epigenetics may include the occurrence of 'metabolic memory' found in animal studies. Further study into epigenetic mechanism might give us new vision into the pathogenesis of diabetes mellitus and related complication thus leading to the discovery of new therapeutic targets. In this review, we discuss the possible epigenetic changes and mechanism that happen in diabetes mellitus type 1 and type 2 separately. We highlight the important epigenetic and non-epigenetic therapeutic targets involved in the management of diabetes and associated complications.
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Affiliation(s)
- Rajveer Singh
- National Institute of Pharmaceutical Education and Research, Kolkata 164, Manicktala Main Road, Kolkata 700054, India
| | - Shivani Chandel
- National Institute of Pharmaceutical Education and Research, Kolkata 164, Manicktala Main Road, Kolkata 700054, India
| | - Dhritiman Dey
- National Institute of Pharmaceutical Education and Research, Kolkata 164, Manicktala Main Road, Kolkata 700054, India
| | - Arijit Ghosh
- Department of Chemistry, University of Calcutta, Kolkata 700009, India
| | - Syamal Roy
- National Institute of Pharmaceutical Education and Research, Kolkata 164, Manicktala Main Road, Kolkata 700054, India
| | - Velayutham Ravichandiran
- National Institute of Pharmaceutical Education and Research, Kolkata 164, Manicktala Main Road, Kolkata 700054, India
| | - Dipanjan Ghosh
- National Institute of Pharmaceutical Education and Research, Kolkata 164, Manicktala Main Road, Kolkata 700054, India
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Álvaro-Benito M, Freund C. Revisiting nonclassical HLA II functions in antigen presentation: Peptide editing and its modulation. HLA 2020; 96:415-429. [PMID: 32767512 DOI: 10.1111/tan.14007] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Accepted: 08/04/2020] [Indexed: 01/08/2023]
Abstract
The nonclassical major histocompatibility complex of class II molecules (ncMHCII) HLA-DM (DM) and HLA-DO (DO) feature essential functions for the selection of the peptides that are displayed by classical MHCII proteins (MHCII) for CD4+ Th cell surveillance. Thus, although the binding groove of classical MHCII dictates the main features of the peptides displayed, ncMHCII function defines the preferential loading of peptides from specific cellular compartments and the extent to which they are presented. DM acts as a chaperone for classical MHCII molecules facilitating peptide exchange and thereby favoring the binding of peptide-MHCII complexes of high kinetic stability mostly in late endosomal compartments. DO on the other hand binds to DM blocking its peptide-editing function in B cells and thymic epithelial cells, limiting DM activity in these cellular subsets. DM and DO distinct expression patterns therefore define specific antigen presentation profiles that select unique peptide pools for each set of antigen presenting cell. We have come a long way understanding the mechanistic underpinnings of such distinct editing profiles and start to grasp the implications for ncMHCII biological function. DM acts as filter for the selection of immunodominant, pathogen-derived epitopes while DO blocks DM activity under certain physiological conditions to promote tolerance to self. Interestingly, recent findings have shown that the unexplored and neglected ncMHCII genetic diversity modulates retroviral infection in mouse, and affects human ncMHCII function. This review aims at highlighting the importance of ncMHCII function for CD4+ Th cell responses while integrating and evaluating what could be the impact of distinct editing profiles because of natural genetic variations.
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Affiliation(s)
- Miguel Álvaro-Benito
- Laboratory of Protein Biochemistry, Institute für Chemie und Biochemie, Department of Biology, Chemistry, Pharmacy, Freie Universität Berlin, Berlin, Germany
| | - Christian Freund
- Laboratory of Protein Biochemistry, Institute für Chemie und Biochemie, Department of Biology, Chemistry, Pharmacy, Freie Universität Berlin, Berlin, Germany
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21
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Kawai VK, Shi M, Feng Q, Chung CP, Liu G, Cox NJ, Jarvik GP, Lee MTM, Hebbring SJ, Harley JB, Kaufman KM, Namjou B, Larson E, Gordon AS, Roden DM, Stein CM, Mosley JD. Pleiotropy in the Genetic Predisposition to Rheumatoid Arthritis: A Phenome-Wide Association Study and Inverse Variance-Weighted Meta-Analysis. Arthritis Rheumatol 2020; 72:1483-1492. [PMID: 32307929 DOI: 10.1002/art.41291] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Accepted: 04/14/2020] [Indexed: 12/17/2022]
Abstract
OBJECTIVE This study was undertaken to investigate the hypothesis that a genetic predisposition toward rheumatoid arthritis (RA) increases the risk of 10 cardiometabolic and autoimmune disorders previously associated with RA in epidemiologic studies, and to define new genetic pleiotropy present in RA. METHODS Two approaches were used to test our hypothesis. First, we constructed a weighted genetic risk score (wGRS) and then examined its association with 10 prespecified disorders. Additionally, a phenome-wide association study (PheWAS) was carried out to identify potential new associations. Second, inverse variance-weighted regression (IVWR) meta-analysis was used to characterize the association between genetic susceptibility to RA and the prespecified disorders, with the results expressed as odds ratios (ORs) and 95% confidence intervals (95% CIs). RESULTS The wGRS for RA was significantly associated with type 1 diabetes mellitus (DM) (OR 1.10 [95% CI 1.04-1.16]; P = 9.82 × 10-4 ) and multiple sclerosis (OR 0.82 [95% CI 0.77-0.88]; P = 1.73 × 10-8 ), but not with other cardiometabolic phenotypes. In the PheWAS, wGRS was also associated with an increased risk of several autoimmune phenotypes including RA, thyroiditis, and systemic sclerosis, and with a decreased risk of demyelinating disorders. In the IVWR meta-analyses, RA was significantly associated with an increased risk of type 1 DM (P = 1.15 × 10-14 ), with evidence of horizontal pleiotropy (Mendelian Randomization-Egger intercept estimate P = 0.001) likely driven by rs2476601, a PTPN22 variant. The association between type 1 DM and RA remained significant (P = 9.53 × 10-9 ) after excluding rs2476601, with no evidence of horizontal pleiotropy (intercept estimate P = 0.939). RA was also significantly associated with type 2 DM and C-reactive protein levels. These associations were driven by variation in the major histocompatibility complex region. CONCLUSION This study presents evidence of pleiotropy between the genetic predisposition to RA and associated phenotypes found in other autoimmune and cardiometabolic disorders, including type 1 DM.
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Affiliation(s)
- Vivian K Kawai
- Vanderbilt University Medical Center, Nashville, Tennessee
| | - Mingjian Shi
- Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Qiping Feng
- Vanderbilt University Medical Center, Nashville, Tennessee
| | - Cecilia P Chung
- Vanderbilt University Medical Center, Tennessee Valley Healthcare System Nashville Campus, and Vanderbilt University School of Medicine, Nashville, Tennessee
| | - Ge Liu
- Vanderbilt University Medical Center, Nashville, Tennessee
| | - Nancy J Cox
- Vanderbilt University Medical Center and Vanderbilt University School of Medicine, Nashville, Tennessee
| | | | | | | | - John B Harley
- Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, and Cincinnati VA Medical Center, Cincinnati, Ohio
| | - Kenneth M Kaufman
- Cincinnati Children's Hospital Medical Center, University of Cincinnati College of Medicine, and Cincinnati VA Medical Center, Cincinnati, Ohio
| | - Bahram Namjou
- Cincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine, Cincinnati, Ohio
| | - Eric Larson
- Kaiser Permanente Washington Health Research Institute, Seattle
| | - Adam S Gordon
- Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Dan M Roden
- Vanderbilt University Medical Center and Vanderbilt University School of Medicine, Nashville, Tennessee
| | | | - Jonathan D Mosley
- Vanderbilt University Medical Center and Vanderbilt University School of Medicine, Nashville, Tennessee
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Abstract
Over the last several years, next-generation sequencing and its recent push toward single-cell resolution have transformed the landscape of immunology research by revealing novel complexities about all components of the immune system. With the vast amounts of diverse data currently being generated, and with the methods of analyzing and combining diverse data improving as well, integrative systems approaches are becoming more powerful. Previous integrative approaches have combined multiple data types and revealed ways that the immune system, both as a whole and as individual parts, is affected by genetics, the microbiome, and other factors. In this review, we explore the data types that are available for studying immunology with an integrative systems approach, as well as the current strategies and challenges for conducting such analyses.
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Affiliation(s)
- Silvia Pineda
- Bakar Computational Health Sciences Institute, University of California, San Francisco, California 94158, USA
- Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Centre, 28029 Madrid, Spain
| | - Daniel G. Bunis
- Bakar Computational Health Sciences Institute, University of California, San Francisco, California 94158, USA
| | - Idit Kosti
- Bakar Computational Health Sciences Institute, University of California, San Francisco, California 94158, USA
- Department of Pediatrics, University of California, San Francisco, California 94143, USA
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California, San Francisco, California 94158, USA
- Department of Pediatrics, University of California, San Francisco, California 94143, USA
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23
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Yan CY, Ma YR, Sun F, Zhang RJ, Fang Y, Zhang QY, Wu FY, Zhao SX, Song HD. Candidate gene associations reveal sex-specific Graves' disease risk alleles among Chinese Han populations. Mol Genet Genomic Med 2020; 8:e1249. [PMID: 32342657 PMCID: PMC7336758 DOI: 10.1002/mgg3.1249] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 03/18/2020] [Accepted: 03/24/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND With several susceptibility single nucleotide polymorphisms identified by case-control association studies, Graves' disease is one of the most common forms of autoimmune thyroid disease. In this study, we aimed to determine whether any observed differences in genetic associations are influenced by sex in Chinese Han populations. METHODS A total of 8,835 patients with Graves' disease and 9,936 sex-matched healthy controls were enrolled in the study. Confirmed by a two-staged association analysis, sex-specific analyses among 20 Graves' disease susceptibility loci were conducted. RESULTS A significant sex-gene interaction was detected primarily at rs5912838 on Xq21.1 between the GPR174 and ITM2A genes, whereby male Graves' disease patients possessed a significantly higher frequency of risk alleles than their female counterparts. Interestingly, compared to women, male patients with Graves' disease had a higher cumulative genetic risk and higher persistent thyroid stimulating hormone receptor antibody-positive rate after receiving antithyroid drug therapy for at least 1 year. CONCLUSION The findings of this study suggest the existence of one potential sex-specific Graves' disease variant on Xq21.1. This could increase our understanding of the pivotal mechanism behind Graves' disease and ultimately aid in identifying possible therapeutic targets.
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Affiliation(s)
- Chen-Yan Yan
- Department of Molecular Diagnostics, The Core Laboratory in Medical Center of Clinical Research, Department of Endocrinology, Shanghai Ninth People's Hospital, State Key Laboratory of Medical Genomics, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu-Ru Ma
- Department of Molecular Diagnostics, The Core Laboratory in Medical Center of Clinical Research, Department of Endocrinology, Shanghai Ninth People's Hospital, State Key Laboratory of Medical Genomics, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Feng Sun
- Department of Molecular Diagnostics, The Core Laboratory in Medical Center of Clinical Research, Department of Endocrinology, Shanghai Ninth People's Hospital, State Key Laboratory of Medical Genomics, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Rui-Jia Zhang
- Department of Molecular Diagnostics, The Core Laboratory in Medical Center of Clinical Research, Department of Endocrinology, Shanghai Ninth People's Hospital, State Key Laboratory of Medical Genomics, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Ya Fang
- Department of Molecular Diagnostics, The Core Laboratory in Medical Center of Clinical Research, Department of Endocrinology, Shanghai Ninth People's Hospital, State Key Laboratory of Medical Genomics, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qian-Yue Zhang
- Department of Molecular Diagnostics, The Core Laboratory in Medical Center of Clinical Research, Department of Endocrinology, Shanghai Ninth People's Hospital, State Key Laboratory of Medical Genomics, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Feng-Yao Wu
- Department of Molecular Diagnostics, The Core Laboratory in Medical Center of Clinical Research, Department of Endocrinology, Shanghai Ninth People's Hospital, State Key Laboratory of Medical Genomics, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shuang-Xia Zhao
- Department of Molecular Diagnostics, The Core Laboratory in Medical Center of Clinical Research, Department of Endocrinology, Shanghai Ninth People's Hospital, State Key Laboratory of Medical Genomics, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Huai-Dong Song
- Department of Molecular Diagnostics, The Core Laboratory in Medical Center of Clinical Research, Department of Endocrinology, Shanghai Ninth People's Hospital, State Key Laboratory of Medical Genomics, Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Kopp TI, Delcoigne B, Arkema EV, Jacobsen RK, Magyari M, Ibfelt EH, Locht H, Sellebjerg F, Cordtz RL, Jensen DV, Askling J, Dreyer L. Risk of neuroinflammatory events in arthritis patients treated with tumour necrosis factor alpha inhibitors: a collaborative population-based cohort study from Denmark and Sweden. Ann Rheum Dis 2020; 79:566-572. [DOI: 10.1136/annrheumdis-2019-216693] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Revised: 02/20/2020] [Accepted: 02/20/2020] [Indexed: 11/04/2022]
Abstract
ObjectivesTo investigate whether tumour necrosis factor alpha inhibitors (TNFis) are associated with an increased risk of neuroinflammatory diseases among patients with arthritic diseases.MethodsCohorts of patients with rheumatoid arthritis (RA, n=25 796), psoriatic arthritis (PsA, n=8586) and ankylosing spondylitis (AS, n=9527) who initiated a TNFi treatment year 2000–2017 were identified from nationwide clinical rheumatology registers in Sweden and Denmark. Information on demyelinating disease and inflammatory neuropathy diagnoses was retrieved from prospective linkage to National Patients Register. A Cox proportional hazard model was used to estimate HRs and 95% CI comparing TNFi exposed and non-exposed, by disease and country.ResultsAmong 111 455 patients with RA, we identified 270 (Sweden) and 51 (Denmark) events (all types of neuroinflammatory diseases combined), corresponding to crude incidence rates (per 1000 person-years) of 0.37 (Sweden) and 0.39 (Denmark) in TNFi-treated patients vs 0.39 (Sweden) and 0.28 (Denmark) in unexposed patients, and an age-sex-calendar-period-adjusted HR (95% CI) of 0.97 (0.72 to 1.33) (Sweden) and 1.45 (0.74 to 2.81) (Denmark) in TNFi exposed compared with non-exposed patients. For a total of 64 065 AS/PsA patients, the corresponding numbers were: 196 and 32 events, crude incidence rates of 0.59 and 0.87 in TNFi-treated patients vs 0.40 and 0.19 in unexposed patients, and HRs of 1.50 (1.07 to 2.11) and 3.41 (1.30 to 8.96), for Sweden and Denmark, respectively. For multiple sclerosis, the patterns of HRs were similar.ConclusionsUse of TNFi in AS/PsA, but not in RA, was associated with increased risk of incident neuroinflammatory disease, though the absolute risk was below one in 1000 patients/year.
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25
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Jia X, Shi N, Feng Y, Li Y, Tan J, Xu F, Wang W, Sun C, Deng H, Yang Y, Shi X. Identification of 67 Pleiotropic Genes Associated With Seven Autoimmune/Autoinflammatory Diseases Using Multivariate Statistical Analysis. Front Immunol 2020; 11:30. [PMID: 32117227 PMCID: PMC7008725 DOI: 10.3389/fimmu.2020.00030] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Accepted: 01/08/2020] [Indexed: 12/19/2022] Open
Abstract
Although genome-wide association studies (GWAS) have a dramatic impact on susceptibility locus discovery, this univariate approach has limitations in detecting complex genotype-phenotype correlations. Multivariate analysis is essential to identify shared genetic risk factors acting through common biological mechanisms of autoimmune/autoinflammatory diseases. In this study, GWAS summary statistics, including 41,274 single nucleotide polymorphisms (SNPs) located in 11,516 gene regions, were analyzed to identify shared variants of seven autoimmune/autoinflammatory diseases using the metaCCA method. Gene-based association analysis was used to refine the pleiotropic genes. In addition, GO term enrichment analysis and protein-protein interaction network analysis were applied to explore the potential biological functions of the identified genes. A total of 4,962 SNPs (P < 1.21 × 10-6) and 1,044 pleotropic genes (P < 4.34 × 10-6) were identified by metaCCA analysis. By screening the results of gene-based P-values, we identified the existence of 27 confirmed pleiotropic genes and highlighted 40 novel pleiotropic genes that achieved statistical significance in the metaCCA analysis and were also associated with at least one autoimmune/autoinflammatory in the VEGAS2 analysis. Using the metaCCA method, we identified novel variants associated with complex diseases incorporating different GWAS datasets. Our analysis may provide insights for the development of common therapeutic approaches for autoimmune/autoinflammatory diseases based on the pleiotropic genes and common mechanisms identified.
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Affiliation(s)
- Xiaocan Jia
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Nian Shi
- Department of Physical Diagnosis, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yu Feng
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Yifan Li
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Jiebing Tan
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Fei Xu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Wei Wang
- Department of Occupational and Environmental Health, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Changqing Sun
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Hongwen Deng
- Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States
| | - Yongli Yang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xuezhong Shi
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
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26
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Horizontal and vertical integrative analysis methods for mental disorders omics data. Sci Rep 2019; 9:13430. [PMID: 31530853 PMCID: PMC6748966 DOI: 10.1038/s41598-019-49718-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Accepted: 08/30/2019] [Indexed: 12/18/2022] Open
Abstract
In recent biomedical studies, omics profiling has been extensively conducted on various types of mental disorders. In most of the existing analyses, a single type of mental disorder and a single type of omics measurement are analyzed. In the study of other complex diseases, integrative analysis, both vertical and horizontal integration, has been conducted and shown to bring significantly new insights into disease etiology, progression, biomarkers, and treatment. In this article, we showcase the applicability of integrative analysis to mental disorders. In particular, the horizontal integration of bipolar disorder and schizophrenia and the vertical integration of gene expression and copy number variation data are conducted. The analysis is based on the sparse principal component analysis, penalization, and other advanced statistical techniques. In data analysis, integration leads to biologically sensible findings, including the disease-related gene expressions, copy number variations, and their associations, which differ from the “benchmark” analysis. Overall, this study suggests the potential of integrative analysis in mental disorder research.
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Aslam MM, John P, Fan KH, Bhatti A, Jahangir S, Feingold E, Demirci FY, Kamboh MI. Exploration of shared genetic susceptibility loci between type 1 diabetes and rheumatoid arthritis in the Pakistani population. BMC Res Notes 2019; 12:544. [PMID: 31455420 PMCID: PMC6712654 DOI: 10.1186/s13104-019-4590-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2019] [Accepted: 08/21/2019] [Indexed: 12/11/2022] Open
Abstract
OBJECTIVE Type 1 diabetes (T1D) and rheumatoid arthritis (RA) are autoimmune diseases. It is known that certain genetic loci and factors that increase the overall autoimmunity risk can be shared among different autoimmune diseases. We sought to replicate seven T1D-related SNPs (single nucleotide polymorphisms) that have been previously reported to be associated with RA susceptibility in a small set of mixed family-based and case-control Pakistani sample in a relatively large and independent RA case-control sample from the same population. Seven T1D-associated SNPs (GLIS3/rs7020673, BACH2/rs11755527, SKAP2/rs7804356, GDSMB/rs2290400, C6orf173/rs9388489, LOC399716/rs947474 and DLK1-MEG2/rs941576) were genotyped in a large Pakistani RA case-control sample (n = 1959) using TaqMan® SNP genotyping assays. RESULTS None of the tested SNPs showed statistically significant association with RA susceptibility; however, one SNP (GLIS3/rs7020673) showed a trend for association (OR = 0.88, p = 7.99E-02). Our study has failed to replicate the previously reported association of seven T1D-associated SNPs with RA risk in a large sample from the same population. Thus, our results do not support a major role of these T1D SNPs in affecting RA susceptibility in the Pakistani population.
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Affiliation(s)
- Muhammad Muaaz Aslam
- Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, Pakistan.,Department of Human Genetics, Graduate School of Public Health (GSPH), University of Pittsburgh, Pittsburgh, PA, 15216, USA
| | - Peter John
- Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, Pakistan
| | - Kang-Hsien Fan
- Department of Human Genetics, Graduate School of Public Health (GSPH), University of Pittsburgh, Pittsburgh, PA, 15216, USA
| | - Attya Bhatti
- Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, Pakistan
| | - Sidrah Jahangir
- Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, Pakistan
| | - Eleanor Feingold
- Department of Human Genetics, Graduate School of Public Health (GSPH), University of Pittsburgh, Pittsburgh, PA, 15216, USA
| | - F Yesim Demirci
- Department of Human Genetics, Graduate School of Public Health (GSPH), University of Pittsburgh, Pittsburgh, PA, 15216, USA
| | - M Ilyas Kamboh
- Department of Human Genetics, Graduate School of Public Health (GSPH), University of Pittsburgh, Pittsburgh, PA, 15216, USA.
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Qian L, Shi H, Ding M. Comparative analysis of gene expression profiles in children with type 1 diabetes mellitus. Mol Med Rep 2019; 19:3989-4000. [PMID: 30942443 PMCID: PMC6472094 DOI: 10.3892/mmr.2019.10099] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Accepted: 06/22/2018] [Indexed: 01/07/2023] Open
Abstract
Type 1 diabetes (T1D) is an autoimmune disease that is typically diagnosed in children. The aim of the present study was to identify potential genes involved in the pathogenesis of childhood T1D. Two datasets of mRNA expression in children with T1D were obtained from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) in children with T1D were identified. Functional analysis was performed and a protein‑protein interaction (PPI) network was constructed, as was a transcription factor (TF)‑target network. The expression of selected DEGs was further assessed using reverse transcription‑quantitative polymerase chain reaction (RT‑qPCR) analysis. Electronic validation and diagnostic value analysis of the identified DEGs [cytokine inducible SH2 containing protein (CISH), SR‑related CTD associated factor 11 (SCAF11), estrogen receptor 1 (ESR1), Rho GTPase activating protein 25 (ARHGAP25), major histocompatibility complex, class II, DR β4 (HLA‑DRB4) and interleukin 23 subunit α (IL23A)] was performed in the GEO dataset. Compared with the normal control group, a total of 1,467 DEGs with P<0.05 were identified in children with T1D. CISH and SCAF11 were determined to be the most up‑ and downregulated genes, respectively. Heterogeneous nuclear ribonucleoprotein D (HNRNPD; degree=33), protein kinase AMP‑activated catalytic subunit α1 (PRKAA1; degree=11), integrin subunit α4 (ITGA4; degree=8) and ESR1 (degree=8) were identified in the PPI network as high‑degree genes. ARHGAP25 (degree=12), HNRNPD (degree=10), HLA‑DRB4 (degree=10) and IL23A (degree=9) were high‑degree genes identified in the TF‑target network. RT‑qPCR revealed that the expression of HNRNPD, PRKAA1, ITGA4 and transporter 2, ATP binding cassette subfamily B member was consistent with the results of the integrated analysis. Furthermore, the results of the electronic validation were consistent with the bioinformatics analysis. SCAF11, CISH and ARHGAP25 were identified to possess value as potential diagnostic markers for children with T1D. In conclusion, identifying DEGs in children with T1D may contribute to our understanding of its pathogenesis, and such DEGs may be used as diagnostic biomarkers for children with T1D.
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Affiliation(s)
- Liwei Qian
- Department of Pediatrics, The Second People's Hospital of Liaocheng, Liaocheng, Shandong 252000, P.R. China
| | - Honglei Shi
- Department of Pediatrics, The Second People's Hospital of Liaocheng, Liaocheng, Shandong 252000, P.R. China
| | - Meili Ding
- Department of Pediatrics, Shandong Jining No. 1 People's Hospital, Jining, Shandong 272011, P.R. China
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Sirota M, Thomas CG, Liu R, Zuhl M, Banerjee P, Wong RJ, Quaintance CC, Leite R, Chubiz J, Anderson R, Chappell J, Kim M, Grobman W, Zhang G, Rokas A, England SK, Parry S, Shaw GM, Simpson JL, Thomson E, Butte AJ. Enabling precision medicine in neonatology, an integrated repository for preterm birth research. Sci Data 2018; 5:180219. [PMID: 30398470 PMCID: PMC6219406 DOI: 10.1038/sdata.2018.219] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Accepted: 07/19/2018] [Indexed: 12/14/2022] Open
Abstract
Preterm birth, or the delivery of an infant prior to 37 weeks of gestation, is a significant cause of infant morbidity and mortality. In the last decade, the advent and continued development of molecular profiling technologies has enabled researchers to generate vast amount of 'omics' data, which together with integrative computational approaches, can help refine the current knowledge about disease mechanisms, diagnostics, and therapeutics. Here we describe the March of Dimes' Database for Preterm Birth Research (http://www.immport.org/resources/mod), a unique resource that contains a variety of 'omics' datasets related to preterm birth. The database is open publicly, and as of January 2018, links 13 molecular studies with data across tens of thousands of patients from 6 measurement modalities. The data in the repository are highly diverse and include genomic, transcriptomic, immunological, and microbiome data. Relevant datasets are augmented with additional molecular characterizations of almost 25,000 biological samples from public databases. We believe our data-sharing efforts will lead to enhanced research collaborations and coordination accelerating the overall pace of discovery in preterm birth research.
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Affiliation(s)
- Marina Sirota
- Institute for Computational Health Sciences, University of California, San Francisco, CA 94158, USA.,Department of Pediatrics, University of California, San Francisco, CA 94158, USA
| | | | - Rebecca Liu
- Enterprise Science And Computing, Inc., Rockville, MD 20850, USA
| | - Maya Zuhl
- March of Dimes, White Plains, NY 10605, USA
| | | | - Ronald J Wong
- March of Dimes Prematurity Research Center at Stanford, Department of Pediatrics, Stanford University School of Medicine Stanford, CA 94305, USA
| | - Cecele C Quaintance
- March of Dimes Prematurity Research Center at Stanford, Department of Pediatrics, Stanford University School of Medicine Stanford, CA 94305, USA
| | - Rita Leite
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jessica Chubiz
- Department of Obstetrics and Gynecology, Washington University in St Louis, St. Louis, MO 63110, USA
| | - Rebecca Anderson
- Department of Human Genetics, University of Chicago, Chicago, IL 60637, USA
| | - Joanne Chappell
- Cincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Mara Kim
- Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA.,Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - William Grobman
- Department of Obstetrics and Gynecology, Feinberg School of Medicine, Northwestern University, Chicago, IL 60637, USA
| | - Ge Zhang
- Cincinnati Children's Hospital Medical Center and University of Cincinnati College of Medicine, Cincinnati, OH 45267, USA
| | - Antonis Rokas
- Department of Biological Sciences, Vanderbilt University, Nashville, TN 37235, USA.,Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37212, USA
| | - Sarah K England
- Department of Obstetrics and Gynecology, Washington University in St Louis, St. Louis, MO 63110, USA
| | - Samuel Parry
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Gary M Shaw
- March of Dimes Prematurity Research Center at Stanford, Department of Pediatrics, Stanford University School of Medicine Stanford, CA 94305, USA
| | | | | | - Atul J Butte
- Institute for Computational Health Sciences, University of California, San Francisco, CA 94158, USA.,Department of Pediatrics, University of California, San Francisco, CA 94158, USA
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Zhao C, Jia M, Song H, Yu Z, Wang W, Li Q, Zhang L, Zhao W, Cao X. The E3 Ubiquitin Ligase TRIM40 Attenuates Antiviral Immune Responses by Targeting MDA5 and RIG-I. Cell Rep 2018; 21:1613-1623. [PMID: 29117565 DOI: 10.1016/j.celrep.2017.10.020] [Citation(s) in RCA: 88] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2017] [Revised: 08/20/2017] [Accepted: 10/04/2017] [Indexed: 12/24/2022] Open
Abstract
Retinoic acid-inducible gene-I (RIG-I)-like receptors (RLRs), including melanoma differentiation-associated gene 5 (MDA5) and RIG-I, are crucial for host recognition of non-self RNAs, especially viral RNA. Thus, the expression and activation of RLRs play fundamental roles in eliminating the invading RNA viruses and maintaining immune homeostasis. However, how RLR expression is tightly regulated remains to be further investigated. In this study, we identified a major histocompatibility complex (MHC)-encoded gene, tripartite interaction motif 40 (TRIM40), as a suppressor of RLR signaling by directly targeting MDA5 and RIG-I. TRIM40 binds to MDA5 and RIG-I and promotes their K27- and K48-linked polyubiquitination via its E3 ligase activity, leading to their proteasomal degradation. TRIM40 deficiency enhances RLR-triggered signaling. Consequently, TRIM40 deficiency greatly enhances antiviral immune responses and decreases viral replication in vivo. Thus, we demonstrate that TRIM40 limits RLR-triggered innate activation, suggesting TRIM40 as a potential therapeutic target for the control of viral infection.
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Affiliation(s)
- Chunyuan Zhao
- Department of Immunology & Center for Immunotherapy, Institute of Basic Medical Sciences, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100005, China
| | - Mutian Jia
- Department of Immunology, School of Basic Medical Science, Shandong University, Jinan, Shandong 250012, China; State Key Laboratory of Microbial Technology, Shandong University, Jinan, Shandong 250012, China
| | - Hui Song
- Department of Immunology, School of Basic Medical Science, Shandong University, Jinan, Shandong 250012, China; State Key Laboratory of Microbial Technology, Shandong University, Jinan, Shandong 250012, China
| | - Zhongxia Yu
- Department of Immunology, School of Basic Medical Science, Shandong University, Jinan, Shandong 250012, China; State Key Laboratory of Microbial Technology, Shandong University, Jinan, Shandong 250012, China
| | - Wenwen Wang
- Department of Immunology, School of Basic Medical Science, Shandong University, Jinan, Shandong 250012, China; State Key Laboratory of Microbial Technology, Shandong University, Jinan, Shandong 250012, China
| | - Qi Li
- Department of Immunology, School of Basic Medical Science, Shandong University, Jinan, Shandong 250012, China; State Key Laboratory of Microbial Technology, Shandong University, Jinan, Shandong 250012, China
| | - Lining Zhang
- Department of Immunology, School of Basic Medical Science, Shandong University, Jinan, Shandong 250012, China
| | - Wei Zhao
- Department of Immunology, School of Basic Medical Science, Shandong University, Jinan, Shandong 250012, China; State Key Laboratory of Microbial Technology, Shandong University, Jinan, Shandong 250012, China.
| | - Xuetao Cao
- Department of Immunology & Center for Immunotherapy, Institute of Basic Medical Sciences, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100005, China; National Key Laboratory of Medical Immunology & Institute of Immunology, Second Military Medical University, Shanghai, China.
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Mescheriakova JY, Hintzen RQ. No excess of autoimmune diseases in multiple sclerosis families from the Netherlands. Acta Neurol Scand 2018; 137:531-537. [PMID: 29315461 DOI: 10.1111/ane.12896] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/14/2017] [Indexed: 01/20/2023]
Abstract
OBJECTIVES Autoimmune diseases (AIDs) cluster in families; however, to what extent AIDs co-occur in MS multiplex families with two or more affected individuals is still controversial. The study aimed to evaluate coexisting AIDs in this type of families from the Netherlands. MATERIALS AND METHODS A total of 155 MS multiplex families (155 MS probands, 959 first-degree relatives and 212 spouses) were characterized for a history of 11 AIDs by means of a self-administered questionnaire. RESULTS In 43.2% of MS multiplex families, at least one AID was present in the first-degree relatives. Overall, the frequency of AIDs was not significantly different between patients with MS (11%), their first-degree family members (11%) and controls (5.2%). After correction for age at inclusion and gender, the odds ratios (OR) for AIDs were not significant for patients with MS (OR = 1.8 [0.77-4.34], P = .17) and first-degree family members (OR = 2.0 [0.98-4.10], P = .06) when both compared to spouses. The frequency of AIDs in mothers did not differ from that in fathers after correction for sex bias (19% vs 8%, P = .51). A presence of AID was more often reported in maternal than paternal second-degree relatives (23% vs 10%, P = .0020). CONCLUSION Although nearly half of the Dutch MS multiplex families reported an AID, no excess of AIDs was present in patients with MS from multiplex families or their first-degree family members compared to the spouses.
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Affiliation(s)
- J. Y. Mescheriakova
- Department of Neurology; MS Centre ErasMS; Erasmus Medical Centre; Rotterdam The Netherlands
| | - R. Q. Hintzen
- Department of Neurology; MS Centre ErasMS; Erasmus Medical Centre; Rotterdam The Netherlands
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Haljas K, Amare AT, Alizadeh BZ, Hsu YH, Mosley T, Newman A, Murabito J, Tiemeier H, Tanaka T, van Duijn C, Ding J, Llewellyn DJ, Bennett DA, Terracciano A, Launer L, Ladwig KH, Cornelis MC, Teumer A, Grabe H, Kardia SLR, Ware EB, Smith JA, Snieder H, Eriksson JG, Groop L, Räikkönen K, Lahti J. Bivariate Genome-Wide Association Study of Depressive Symptoms With Type 2 Diabetes and Quantitative Glycemic Traits. Psychosom Med 2018; 80:242-251. [PMID: 29280852 PMCID: PMC6051528 DOI: 10.1097/psy.0000000000000555] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
OBJECTIVE Shared genetic background may explain phenotypic associations between depression and Type 2 diabetes (T2D). We aimed to study, on a genome-wide level, if genetic correlation and pleiotropic loci exist between depressive symptoms and T2D or glycemic traits. METHODS We estimated single-nucleotide polymorphism (SNP)-based heritability and analyzed genetic correlation between depressive symptoms and T2D and glycemic traits with the linkage disequilibrium score regression by combining summary statistics of previously conducted meta-analyses for depressive symptoms by CHARGE consortium (N = 51,258), T2D by DIAGRAM consortium (N = 34,840 patients and 114,981 controls), fasting glucose, fasting insulin, and homeostatic model assessment of β-cell function and insulin resistance by MAGIC consortium (N = 58,074). Finally, we investigated pleiotropic loci using a bivariate genome-wide association study approach with summary statistics from genome-wide association study meta-analyses and reported loci with genome-wide significant bivariate association p value (p < 5 × 10). Biological annotation and function of significant pleiotropic SNPs were assessed in several databases. RESULTS The SNP-based heritability ranged from 0.04 to 0.10 in each individual trait. In the linkage disequilibrium score regression analyses, depressive symptoms showed no significant genetic correlation with T2D or glycemic traits (p > 0.37). However, we identified pleiotropic genetic variations for depressive symptoms and T2D (in the IGF2BP2, CDKAL1, CDKN2B-AS, and PLEKHA1 genes), and fasting glucose (in the MADD, CDKN2B-AS, PEX16, and MTNR1B genes). CONCLUSIONS We found no significant overall genetic correlations between depressive symptoms, T2D, or glycemic traits suggesting major differences in underlying biology of these traits. However, several potential pleiotropic loci were identified between depressive symptoms, T2D, and fasting glucose, suggesting that previously established phenotypic associations may be partly explained by genetic variation in these specific loci.
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Affiliation(s)
- Kadri Haljas
- From the Departments of Psychology and Logopedics (Haljas, Räikkönen) and Psychology and Logopedics, Faculty of Medicine (Lahti), and Helsinki Collegium for Advanced Studies (Lahti), University of Helsinki, Helsinki, Finland; Department of Epidemiology (Amare, Alizadeh, Snieder), University of Groningen, University Medical Center Groningen, Groningen, the Netherlands; Harvard Medical School (Hsu), Boston, Massachusetts; Institute for Molecular Medicine Finland (FIMM) (Groop), Helsinki, Finland; Lund University Diabetes Centre (Groop), Lund University, Lund, Sweden; Department of General Practice and Primary Health Care (Eriksson), University of Helsinki and Helsinki University Hospital; Folkhälsan Research Center (Eriksson), Helsinki, Finland; Department of Medicine (Mosley), University of Mississippi Medical Center, Jackson, Mississippi; Department of Epidemiology, School of Public Health (Newman), University of Pittsburgh, Pittsburgh, Pennsylvania; Department of Medicine, Section of General Internal Medicine (Murabito), Boston University School of Medicine, Boston; Boston University and National Heart, Lung, and Blood Institute's Framingham Heart Study, Framingham, Massachusetts (Murabito); Departments of Epidemiology and Psychiatry (Tiemeier), Erasmus University Medical Center, Rotterdam, the Netherlands; Translational Gerontology Branch (Tanaka), National Institute on Aging, Baltimore, Maryland; Genetic Epidemiology Unit, Department of Epidemiology (van Duijn), Erasmus University Medical Center, Rotterdam; Centre for Medical Systems Biology (van Duijn), Leiden, the Netherlands; Department of Internal Medicine, Division of Geriatrics (Ding), Wake Forest University, Winston-Salem, North Carolina; University of Exeter Medical School (Llewellyn), Exeter, UK; Rush Alzheimer's Disease Center (Bennett), Chicago, Illinois; Florida State University, College of Medicine (Terracciano), Tallahassee, Florida; Laboratory of Epidemiology and Population Sciences (Launer), National Institute on Aging, Bethesda, Maryland; Department of Psychiatry and Psychotherapy (Grabe), Helios Hospital Stralsund; Department of Psychiatry and Psychotherapy (Grabe) and Institute for Community Medicine (Teumer), University Medicine Greifswald; German Center for Neurodegenerative Diseases (Grabe), Site Rostock/Greifswald, Greifswald, Germany; Institute of Epidemiology II, Mental Health Research Unit, Helmholtz Zentrum München (Ladwig), German Research Center for Environmental Health, Neuherberg, Germany; Psychosomatic Medicine and Psychotherapy (Ladwig), Universitäts-Klinikum Rechts der Isar, Technische Universität München, Munich, Germany & German Center for Diabetes Research (DZD), München-Neuherberg, Germany; Department of Preventive Medicine (Cornelis), Northwestern University Feinberg School of Medicine, Chicago, Illinois; and Department of Epidemiology, School of Public Health (Kardia, Ware, Smith), and Survey Research Center, Institute for Social Research (Ware, Smith), University of Michigan, Ann Arbor, Michigan
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Lu C, Liu X, Wang L, Jiang N, Yu J, Zhao X, Hu H, Zheng S, Li X, Wang G. Integrated analyses for genetic markers of polycystic ovary syndrome with 9 case-control studies of gene expression profiles. Oncotarget 2018; 8:3170-3180. [PMID: 27965459 PMCID: PMC5356873 DOI: 10.18632/oncotarget.13881] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Accepted: 12/01/2016] [Indexed: 12/25/2022] Open
Abstract
Due to genetic heterogeneity and variable diagnostic criteria, genetic studies of polycystic ovary syndrome are particularly challenging. Furthermore, lack of sufficiently large cohorts limits the identification of susceptibility genes contributing to polycystic ovary syndrome. Here, we carried out a systematic search of studies deposited in the Gene Expression Omnibus database through August 31, 2016. The present analyses included studies with: 1) patients with polycystic ovary syndrome and normal controls, 2) gene expression profiling of messenger RNA, and 3) sufficient data for our analysis. Ultimately, a total of 9 studies with 13 datasets met the inclusion criteria and were performed for the subsequent integrated analyses. Through comprehensive analyses, there were 13 genetic factors overlapped in all datasets and identified as significant specific genes for polycystic ovary syndrome. After quality control assessment, there were six datasets remained. Further gene ontology enrichment and pathway analyses suggested that differentially expressed genes mainly enriched in oocyte pathways. These findings provide potential molecular markers for diagnosis and prognosis of polycystic ovary syndrome, and need in-depth studies on the exact function and mechanism in polycystic ovary syndrome.
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Affiliation(s)
- Chenqi Lu
- Department of Biostatistics and Computational Biology, State Key Laboratory of Genetic Engineering, Department of Gynecology, Obstetrics and Gynecology Hospital, School of Life Sciences, Fudan University, Shanghai, China
| | - Xiaoqin Liu
- Clinical and Translational Research Center of Shanghai First Maternity and Infant Health Hospital, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Science and Technology, Tongji University, Shanghai, China
| | - Lin Wang
- Department of Endocrinology, East Hospital, Tongji University School of Medicine, Tongji University, Shanghai, China
| | - Ning Jiang
- Department of Biostatistics and Computational Biology, State Key Laboratory of Genetic Engineering, Department of Gynecology, Obstetrics and Gynecology Hospital, School of Life Sciences, Fudan University, Shanghai, China
| | - Jun Yu
- Clinical and Translational Research Center of Shanghai First Maternity and Infant Health Hospital, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Science and Technology, Tongji University, Shanghai, China
| | - Xiaobo Zhao
- Clinical and Translational Research Center of Shanghai First Maternity and Infant Health Hospital, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Science and Technology, Tongji University, Shanghai, China
| | - Hairong Hu
- Department of Biostatistics and Computational Biology, State Key Laboratory of Genetic Engineering, Department of Gynecology, Obstetrics and Gynecology Hospital, School of Life Sciences, Fudan University, Shanghai, China
| | - Saihua Zheng
- Department of Biostatistics and Computational Biology, State Key Laboratory of Genetic Engineering, Department of Gynecology, Obstetrics and Gynecology Hospital, School of Life Sciences, Fudan University, Shanghai, China
| | - Xuelian Li
- Department of Biostatistics and Computational Biology, State Key Laboratory of Genetic Engineering, Department of Gynecology, Obstetrics and Gynecology Hospital, School of Life Sciences, Fudan University, Shanghai, China
| | - Guiying Wang
- Clinical and Translational Research Center of Shanghai First Maternity and Infant Health Hospital, Shanghai Key Laboratory of Signaling and Disease Research, School of Life Science and Technology, Tongji University, Shanghai, China
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Parkkola A, Laine AP, Karhunen M, Härkönen T, Ryhänen SJ, Ilonen J, Knip M. HLA and non-HLA genes and familial predisposition to autoimmune diseases in families with a child affected by type 1 diabetes. PLoS One 2017; 12:e0188402. [PMID: 29182645 PMCID: PMC5705143 DOI: 10.1371/journal.pone.0188402] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2017] [Accepted: 11/06/2017] [Indexed: 12/12/2022] Open
Abstract
Genetic predisposition could be assumed to be causing clustering of autoimmunity in individuals and families. We tested whether HLA and non-HLA loci associate with such clustering of autoimmunity. We included 1,745 children with type 1 diabetes from the Finnish Pediatric Diabetes Register. Data on personal or family history of autoimmune diseases were collected with a structured questionnaire and, for a subset, with a detailed search for celiac disease and autoimmune thyroid disease. Children with multiple autoimmune diseases or with multiple affected first- or second-degree relatives were identified. We analysed type 1 diabetes related HLA class II haplotypes and genotyped 41 single nucleotide polymorphisms (SNPs) outside the HLA region. The HLA-DR4-DQ8 haplotype was associated with having type 1 diabetes only whereas the HLA-DR3-DQ2 haplotype was more common in children with multiple autoimmune diseases. Children with multiple autoimmune diseases showed nominal association with RGS1 (rs2816316), and children coming from an autoimmune family with rs11711054 (CCR3-CCR5). In multivariate analyses, the overall effect of non-HLA SNPs on both phenotypes was evident, associations with RGS1 and CCR3-CCR5 region were confirmed and additional associations were implicated: NRP1, FUT2, and CD69 for children with multiple autoimmune diseases. In conclusion, HLA-DR3-DQ2 haplotype and some non-HLA SNPs contribute to the clustering of autoimmune diseases in children with type 1 diabetes and in their families.
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Affiliation(s)
- Anna Parkkola
- Scientific Laboratory, Children’s Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
- Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | - Antti-Pekka Laine
- Immunogenetics Laboratory, University of Turku, and Turku University Hospital, Turku, Finland
| | - Markku Karhunen
- Department of Political and Economic Studies, University of Helsinki, Helsinki, Finland
| | - Taina Härkönen
- Scientific Laboratory, Children’s Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | - Samppa J. Ryhänen
- Scientific Laboratory, Children’s Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | - Jorma Ilonen
- Immunogenetics Laboratory, University of Turku, and Turku University Hospital, Turku, Finland
| | - Mikael Knip
- Scientific Laboratory, Children’s Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
- Folkhälsan Research Center, Helsinki, Finland
- Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
- Department of Pediatrics, Tampere University Hospital, Tampere, Finland
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Alvaro-Benito M, Morrison E, Wieczorek M, Sticht J, Freund C. Human leukocyte Antigen-DM polymorphisms in autoimmune diseases. Open Biol 2017; 6:rsob.160165. [PMID: 27534821 PMCID: PMC5008016 DOI: 10.1098/rsob.160165] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2016] [Accepted: 07/19/2016] [Indexed: 12/20/2022] Open
Abstract
Classical MHC class II (MHCII) proteins present peptides for CD4+ T-cell surveillance and are by far the most prominent risk factor for a number of autoimmune disorders. To date, many studies have shown that this link between particular MHCII alleles and disease depends on the MHCII's particular ability to bind and present certain peptides in specific physiological contexts. However, less attention has been paid to the non-classical MHCII molecule human leucocyte antigen-DM, which catalyses peptide exchange on classical MHCII proteins acting as a peptide editor. DM function impacts the presentation of both antigenic peptides in the periphery and key self-peptides during T-cell development in the thymus. In this way, DM activity directly influences the response to pathogens, as well as mechanisms of self-tolerance acquisition. While decreased DM editing of particular MHCII proteins has been proposed to be related to autoimmune disorders, no experimental evidence for different DM catalytic properties had been reported until recently. Biochemical and structural investigations, together with new animal models of loss of DM activity, have provided an attractive foundation for identifying different catalytic efficiencies for DM allotypes. Here, we revisit the current knowledge of DM function and discuss how DM function may impart autoimmunity at the organism level.
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Affiliation(s)
- Miguel Alvaro-Benito
- Protein Biochemistry Group, Institute for Chemistry and Biochemistry, Department of Biology, Chemistry and Pharmacy, Freie Universität Berlin, Berlin, Germany
| | - Eliot Morrison
- Protein Biochemistry Group, Institute for Chemistry and Biochemistry, Department of Biology, Chemistry and Pharmacy, Freie Universität Berlin, Berlin, Germany
| | - Marek Wieczorek
- Protein Biochemistry Group, Institute for Chemistry and Biochemistry, Department of Biology, Chemistry and Pharmacy, Freie Universität Berlin, Berlin, Germany
| | - Jana Sticht
- Protein Biochemistry Group, Institute for Chemistry and Biochemistry, Department of Biology, Chemistry and Pharmacy, Freie Universität Berlin, Berlin, Germany
| | - Christian Freund
- Protein Biochemistry Group, Institute for Chemistry and Biochemistry, Department of Biology, Chemistry and Pharmacy, Freie Universität Berlin, Berlin, Germany
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Wang J, Song D, Liu Y, Lu G, Yang S, Liu L, Gao Z, Ma L, Guo Z, Zhang C, Wang H, Yang B. HLA-DMB restricts human T-cell leukemia virus type-1 (HTLV-1) protein expression via regulation of ATG7 acetylation. Sci Rep 2017; 7:14416. [PMID: 29089548 PMCID: PMC5663917 DOI: 10.1038/s41598-017-14882-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2017] [Accepted: 10/19/2017] [Indexed: 12/21/2022] Open
Abstract
The roles of autophagy in viral infection are complicated. While autophagy has been shown to function in host antiviral defense by eliminating intracellular viruses and regulating adaptive immunity, several viruses have evolved molecular mechanisms to get benefits from it. The deltaretrovirus human T-cell leukemia virus type-1 (HTLV-1) has been reported to profit its replication from enhancing autophagosome accumulation. Here, we reported that HLA-DMB (generally referred to here as DMB), the beta chain of the non-classical MHC-II protein HLA-DM, had strong expression in HTLV-1-transformed T-cell lines and could be induced in Hela, PMA-differentiated THP1 (PMA-THP1) or primary human monocytes by HTLV-1 infection. Immunoblot and real-time PCR assays demonstrated that overexpression of DMB decreased HTLV-1 protein expression while the knockdown of DMB increased HTLV-1 protein expression. Immunoblot and confocal microscopy assays indicated that overexpression of DMB decreased HTLV-1 induced autophagosome accumulation while the knockdown of DMB yielded the opposite effects. Coimmunoprecipitation and immunoprecipitation experiments suggested DMB interacted with autophagy-related gene (ATG) 7 and increased the acetylation of ATG7. Taken together, these results suggested DMB modulated HTLV-1 protein expression through regulation of autophagosome accumulation and our findings suggested a new mechanism by which the host cells defended against HTLV-1 infection.
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Affiliation(s)
- Jie Wang
- Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
- Henan Key Laboratory of immunology and targeted drugs, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
- Xinxiang assegai medical laboratory institute, Xinxiang, 453003, China
| | - Di Song
- Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
- Henan Key Laboratory of immunology and targeted drugs, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
- Xinxiang assegai medical laboratory institute, Xinxiang, 453003, China
| | - Yanzi Liu
- Department of Laboratory Medicine, the Third Affiliated Hospital of Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Guangjian Lu
- Clinical Laboratory, the First Affiliated Hospital of Xinxiang Medical University, Weihui, 453100, Henan Province, China
| | - Shuai Yang
- Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Lu Liu
- Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Zhitao Gao
- Department of Immunology/Department of Bio-therapeutic, Institute of Basic Medicine, School of Life Sciences, PLA Medical School, Chinese PLA General Hospital, 28 Fuxing Road, Beijing, 100853, China
| | - Lingling Ma
- Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Zhixiang Guo
- Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Chenguang Zhang
- Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China
| | - Hui Wang
- Henan Key Laboratory of immunology and targeted drugs, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China.
| | - Bo Yang
- Henan Collaborative Innovation Center of Molecular Diagnosis and Laboratory Medicine, School of Laboratory Medicine, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China.
- Henan Key Laboratory of immunology and targeted drugs, Xinxiang Medical University, Xinxiang, 453003, Henan Province, China.
- Xinxiang assegai medical laboratory institute, Xinxiang, 453003, China.
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A functional genomics predictive network model identifies regulators of inflammatory bowel disease. Nat Genet 2017; 49:1437-1449. [PMID: 28892060 PMCID: PMC5660607 DOI: 10.1038/ng.3947] [Citation(s) in RCA: 154] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2016] [Accepted: 08/11/2017] [Indexed: 02/07/2023]
Abstract
A major challenge in inflammatory bowel disease (IBD) is the integration of diverse IBD data sets to construct predictive models of IBD. We present a predictive model of the immune component of IBD that informs causal relationships among loci previously linked to IBD through genome-wide association studies (GWAS) using functional and regulatory annotations that relate to the cells, tissues, and pathophysiology of IBD. Our model consists of individual networks constructed using molecular data generated from intestinal samples isolated from three populations of patients with IBD at different stages of disease. We performed key driver analysis to identify genes predicted to modulate network regulatory states associated with IBD, prioritizing and prospectively validating 12 of the top key drivers experimentally. This validated key driver set not only introduces new regulators of processes central to IBD but also provides the integrated circuits of genetic, molecular, and clinical traits that can be directly queried to interrogate and refine the regulatory framework defining IBD.
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Kreiner E, Waage J, Standl M, Brix S, Pers TH, Couto Alves A, Warrington NM, Tiesler CMT, Fuertes E, Franke L, Hirschhorn JN, James A, Simpson A, Tung JY, Koppelman GH, Postma DS, Pennell CE, Jarvelin MR, Custovic A, Timpson N, Ferreira MA, Strachan DP, Henderson J, Hinds D, Bisgaard H, Bønnelykke K. Shared genetic variants suggest common pathways in allergy and autoimmune diseases. J Allergy Clin Immunol 2017; 140:771-781. [PMID: 28188724 DOI: 10.1016/j.jaci.2016.10.055] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2016] [Revised: 09/12/2016] [Accepted: 10/11/2016] [Indexed: 01/06/2023]
Abstract
BACKGROUND The relationship between allergy and autoimmune disorders is complex and poorly understood. OBJECTIVE We sought to investigate commonalities in genetic loci and pathways between allergy and autoimmune diseases to elucidate shared disease mechanisms. METHODS We meta-analyzed 2 genome-wide association studies on self-reported allergy and sensitization comprising a total of 62,330 subjects. These results were used to calculate enrichment for single nucleotide polymorphisms (SNPs) previously associated with autoimmune diseases. Furthermore, we probed for enrichment within genetic pathways and of transcription factor binding sites and characterized commonalities in variant burden on tissue-specific regulatory sites by calculating the enrichment of allergy SNPs falling in gene regulatory regions in various cells using Encode Roadmap DNase-hypersensitive site data. Finally, we compared the allergy data with those of all known diseases. RESULTS Among 290 loci previously associated with 16 autoimmune diseases, we found a significant enrichment of loci also associated with allergy (P = 1.4e-17) encompassing 29 loci at a false discovery rate of less than 0.05. Such enrichment seemed to be a general characteristic for autoimmune diseases. Among the common loci, 48% had the same direction of effect for allergy and autoimmune diseases. Additionally, we observed an enrichment of allergy SNPs falling within immune pathways and regions of chromatin accessible in immune cells that was also represented in patients with autoimmune diseases but not those with other diseases. CONCLUSION We identified shared susceptibility loci and commonalities in pathways between allergy and autoimmune diseases, suggesting shared disease mechanisms. Further studies of these shared genetic mechanisms might help in understanding the complex relationship between these diseases, including the parallel increase in disease prevalence.
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Affiliation(s)
- Eskil Kreiner
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Johannes Waage
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
| | - Marie Standl
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Susanne Brix
- The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - Tune H Pers
- The Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark; Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, Mass; Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, Mass; Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark
| | - Alexessander Couto Alves
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Nicole M Warrington
- University of Queensland Diamantina Institute, University of Queensland, Translational Research Institute, Brisbane, Australia; School of Women's and Infants' Health, University of Western Australia, Perth, Australia
| | - Carla M T Tiesler
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany; Ludwig-Maximilians-Universität of Munich, Dr. von Hauner Children's Hospital, Munich, Germany
| | - Elaine Fuertes
- Institute of Epidemiology I, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Lude Franke
- Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Joel N Hirschhorn
- Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, Mass; Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, Mass; Department of Genetics, Harvard Medical School, Boston, Mass
| | - Alan James
- Busselton Population Medical Research Foundation, Sir Charles Gairdner Hospital, Perth, Australia; School of Medicine and Pharmacology, University of West Australia, Nedlands, Australia; Department of Pulmonary Physiology, West Australian Sleep Disorders Research Institute, Nedlands, Australia
| | - Angela Simpson
- University of Manchester, Manchester Academic Health Science Centre, University Hospital of South Manchester NHS Foundation Trust, Manchester, United Kingdom
| | | | - Gerard H Koppelman
- University of Groningen, University Medical Center Groningen, Department of Pediatric Pulmonology and Pediatric Allergology, Beatrix Children's Hospital, GRIAC Research Institute, Groningen, The Netherlands
| | - Dirkje S Postma
- University of Groningen, University Medical Center Groningen, Department Pulmonary Medicine and Tuberculosis, GRIAC Research Institute, Groningen, The Netherlands
| | - Craig E Pennell
- School of Women's and Infants' Health, University of Western Australia, Perth, Australia
| | - Marjo-Riitta Jarvelin
- Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom; Center for Life Course Epidemiology, Faculty of Medicine, University of Oulu, Oulu, Finland; Biocenter Oulu, University of Oulu, Oulu, Finland; Unit of Primary Care, Oulu University Hospital, Oulu, Finland; Department of Children and Young People and Families, National Institute for Health and Welfare, Oulu, Finland
| | - Adnan Custovic
- University of Manchester, Manchester Academic Health Science Centre, University Hospital of South Manchester NHS Foundation Trust, Manchester, United Kingdom
| | - Nicholas Timpson
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | | | - David P Strachan
- Population Health Research Institute, St George's, University of London, London, United Kingdom
| | - John Henderson
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | | | - Hans Bisgaard
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark.
| | - Klaus Bønnelykke
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Copenhagen, Denmark
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40
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Chen WC, Wang WC, Okada Y, Chang WP, Chou YH, Chang HH, Huang JD, Chen DY, Chang WC. rs2841277 ( PLD4) is associated with susceptibility and rs4672495 is associated with disease activity in rheumatoid arthritis. Oncotarget 2017; 8:64180-64190. [PMID: 28969061 PMCID: PMC5609993 DOI: 10.18632/oncotarget.19419] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2017] [Accepted: 06/05/2017] [Indexed: 12/16/2022] Open
Abstract
Rheumatoid arthritis (RA) is one of the most common autoimmune diseases, can lead to long-term joint damage, chronic pain, and loss of motor function in the hands, and may share some common genetic factors with other autoimmune disorders, such as ankylosing spondylitis (AS). Many single-nucleotide polymorphisms (SNPs) were reported by genome-wide association studies (GWASs) of RA, but some of them have not been examined in the Taiwanese population. In this study, for 15 SNPs reported in previous RA and AS GWASs, we investigated their association with RA in a Taiwanese population. Based on 334 RA patients recruited from the Taichung Veterans General Hospital and 16,036 healthy subjects from the Taiwan Biobank (TWB) project, we observed that subjects having minor allele C at rs2841277 (phospholipase D family, member 4 (PLD4)) have lower susceptibility of RA, compare to those having genotype TT (Odds ratio (OR) = 0.6, p = 3.0 × 10−6). Among the RA patients, we observed that subjects having GG at rs4672495 have a lower proportion of severe RA, compare to other subjects (OR = 0.09, p = 5.6 × 10−3). Results of a bioinformatics approach showed that rs2841277 is able to influence expression of LINC00638 and AHNAK2 and rs4672495 is able to influence the expression of B3GNT2. In summary, this study replicated an association of rs2841277 with RA susceptibility and showed an AS-associated SNP, rs4672495, is associated with RA activity in the Taiwanese population.
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Affiliation(s)
- Wei-Chiao Chen
- Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Wen-Chang Wang
- The Ph.D. Program for Translational Medicine, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan
| | - Yukinori Okada
- Department of Statistical Genetics, Graduate School of Medicine, Osaka University, Osaka, Japan
| | - Wei-Pin Chang
- School of Health Care Administration, College of Management, Taipei Medical University, Taipei, Taiwan
| | - Yii-Her Chou
- Department of Urology, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan.,Department of Urology, School of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Hui-Hua Chang
- Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan.,School of Pharmacy, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Jin-Ding Huang
- Institute of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Der-Yuan Chen
- Department of Internal Medicine and Medical Education, Taichung Veterans General Hospital, Taichung, Taiwan.,Faculty of Medicine, National Yang Ming University, Taipei, Taiwan.,Ph.D. Program in Translational Medicine, National Chung Hsing University, Taichung, Taiwan.,Institute of Biomedical Science and Rong Hsing Research Center for Translational Medicine, National Chung Hsing University, Taichung, Taiwan
| | - Wei-Chiao Chang
- The Ph.D. Program for Translational Medicine, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan.,Master Program for Clinical Pharmacogenomics and Pharmacoproteomics, School of Pharmacy, Taipei Medical University, Taipei, Taiwan.,Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei, Taiwan.,Center for Biomarkers and Biotech Drugs, Kaohsiung Medical University, Kaohsiung, Taiwan.,Department of Pharmacy, Taipei Medical University-Wanfang Hospital, Taipei, Taiwan
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Gragnani L, Fognani E, De Re V, Libra M, Garozzo A, Caini P, Cerretelli G, Giovannelli A, Lorini S, Monti M, Bagnoli S, Piaceri I, Zignego AL. Notch4 and mhc class II polymorphisms are associated with hcv-related benign and malignant lymphoproliferative diseases. Oncotarget 2017; 8:71528-71535. [PMID: 29069725 PMCID: PMC5641068 DOI: 10.18632/oncotarget.17655] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2017] [Accepted: 03/29/2017] [Indexed: 12/24/2022] Open
Abstract
Mixed cryoglobulinemia (MC), is a HCV-related, clinically benign, lymphoproliferative disorder (LPD) that may evolve into a non Hodgkin's lymphoma (NHL). Significant associations were found between two single nucleotide polymorphisms near NOTCH4 (rs2071286) and the HLA class II (rs9461776) genes and HCV-related MC syndrome (MCS). We analyzed NOTCH4 rs2071286 and HLA-II rs9461776 in 3 HCV-related LPD groups (asymptomatic MC, MCS, NHL) with HCV infection without lymphoproliferative disorders. We found a positive relationship between NOTCH4 rs207186 T minor allele frequency (MAF) and patients with HCV-related LPDs at risk of NHL (Chi-square test for trend = 14.84 p = 0.0001), in accordance with an over-dominant model in the NHL group (CT vs CC + TT, OR=1.88, 95% CI 1.24–2.83, p = 0.0026). Regarding HLA II rs9461776, G MAF increased in patients with HCV-related LPDs at risk of NHL (Chi-square test for trend = 8.40 p = 0.0038), in accordance with a recessive genotypic model in the NHL group (G/G vs A/A + A/G, OR = 11.07, 95% CI 2.37–51.64, p = 0.0022). Both NOTCH4 rs2071286 and HLA-II rs9461776 were present on chromosome 6 and showed D’ and r values of linkage disequilibrium (LD) of about 0.5 values, thereby suggesting there is no extensive LD in the HCV+ population. This data shows that the previously demonstrated association between NOTCH4 rs2071286 and HLA-II rs9461776 polymorphisms and HCV-related MCS could be extended to overall patients with HCV-related LPDs. The significant relationship between rs2071286 and rs9461776 MAF and the increased risk for NHL, suggests their use as non-invasive markers to categorize patients at risk of lymphoma.
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Affiliation(s)
- Laura Gragnani
- Center for Systemic Manifestations of Hepatitis Viruses (MaSVE), Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Elisa Fognani
- Center for Systemic Manifestations of Hepatitis Viruses (MaSVE), Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Valli De Re
- Centro di Riferimento oncologico, National Cancer Institute, Aviano, Italy
| | - Massimo Libra
- Department of Biomedical and Biotechnological Sciences, Section of Microbiology, University of Catania, Italy
| | - Adriana Garozzo
- Department of Biomedical and Biotechnological Sciences, Section of Microbiology, University of Catania, Italy
| | - Patrizio Caini
- Center for Systemic Manifestations of Hepatitis Viruses (MaSVE), Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Guia Cerretelli
- Center for Systemic Manifestations of Hepatitis Viruses (MaSVE), Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Andrea Giovannelli
- Center for Systemic Manifestations of Hepatitis Viruses (MaSVE), Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Serena Lorini
- Center for Systemic Manifestations of Hepatitis Viruses (MaSVE), Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Monica Monti
- Center for Systemic Manifestations of Hepatitis Viruses (MaSVE), Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
| | - Silvia Bagnoli
- Department of Neuroscience, Psychology, Drug Research and Children's Health, University of Florence, Florence, Italy
| | - Irene Piaceri
- Department of Neuroscience, Psychology, Drug Research and Children's Health, University of Florence, Florence, Italy
| | - Anna Linda Zignego
- Center for Systemic Manifestations of Hepatitis Viruses (MaSVE), Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy
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Malavia TA, Chaparala S, Wood J, Chowdari K, Prasad KM, McClain L, Jegga AG, Ganapathiraju MK, Nimgaonkar VL. Generating testable hypotheses for schizophrenia and rheumatoid arthritis pathogenesis by integrating epidemiological, genomic, and protein interaction data. NPJ SCHIZOPHRENIA 2017; 3:11. [PMID: 28560257 PMCID: PMC5441529 DOI: 10.1038/s41537-017-0010-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2016] [Revised: 01/13/2017] [Accepted: 01/13/2017] [Indexed: 02/04/2023]
Abstract
Patients with schizophrenia and their relatives have reduced prevalence of rheumatoid arthritis. Schizophrenia and rheumatoid arthritis genome-wide association studies also indicate negative genetic correlations, suggesting that there may be shared pathogenesis at the DNA level or downstream. A portion of the inverse prevalence could be attributed to pleiotropy, i.e., variants of a single nucleotide polymorphism that could confer differential risk for these disorders. To study the basis for such an interrelationship, we initially compared lists of single nucleotide polymorphisms with significant genetic associations (p < 1e-8) for schizophrenia or rheumatoid arthritis, evaluating patterns of linkage disequilibrium and apparent pleiotropic risk profiles. Single nucleotide polymorphisms that conferred risk for both schizophrenia and rheumatoid arthritis were localized solely to the extended HLA region. Among single nucleotide polymorphisms that conferred differential risk for schizophrenia and rheumatoid arthritis, the majority were localized to HLA-B, TNXB, NOTCH4, HLA-C, HCP5, MICB, PSORS1C1, and C6orf10; published functional data indicate that HLA-B and HLA-C have the most plausible pathogenic roles in both disorders. Interactomes of these eight genes were constructed from protein-protein interaction information using publicly available databases and novel computational predictions. The genes harboring apparently pleiotropic single nucleotide polymorphisms are closely connected to rheumatoid arthritis and schizophrenia associated genes through common interacting partners. A separate and independent analysis of the interactomes of rheumatoid arthritis and schizophrenia genes showed a significant overlap between the two interactomes and that they share several common pathways, motivating functional studies suggesting a relationship in the pathogenesis of schizophrenia/rheumatoid arthritis.
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Affiliation(s)
- Tulsi A. Malavia
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, USA
| | - Srilakshmi Chaparala
- Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA USA
| | - Joel Wood
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, USA
| | | | | | - Lora McClain
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, USA
| | - Anil G. Jegga
- Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH USA
| | - Madhavi K. Ganapathiraju
- Department of Biomedical Informatics, School of Medicine, University of Pittsburgh, Pittsburgh, PA USA
| | - Vishwajit L. Nimgaonkar
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, USA
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, USA
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43
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Goncharova ZA, Sizyakina LP, Belovolova RA, Megeryan VA. [Comorbid autoimmune pathology in patients treated with disease modifying drugs]. Zh Nevrol Psikhiatr Im S S Korsakova 2017; 116:53-60. [PMID: 28139612 DOI: 10.17116/jnevro201611610253-60] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Because of intensive growth of the prevalence of multiple sclerosis (MS) and other autoimmune diseases (AID) during the last years, the comorbidity of MS and AID is not a rarity. In this literature review, the development of comorbid AID in patients with MS is considered to be the probable complication of disease modifying therapy with drugs of different groups. The authors present the own data on the prevalence of comorbid autoimmune pathology in patients with MS treated with disease modifying drugs.
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Affiliation(s)
| | - L P Sizyakina
- The Research Institute of Clinical Immunology of Rostov State Medical University, Rostov-on-Don, Russia
| | - R A Belovolova
- The Research Institute of Clinical Immunology of Rostov State Medical University, Rostov-on-Don, Russia
| | - V A Megeryan
- Rostov State Medical University, Rostov-on-Don, Russia
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44
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Chen WC, Wei JCC, Lu HF, Wong HSC, Woon PY, Hsu YW, Huang JD, Chang WC. rs657075 (CSF2) Is Associated with the Disease Phenotype (BAS-G) of Ankylosing Spondylitis. Int J Mol Sci 2017; 18:ijms18010083. [PMID: 28054948 PMCID: PMC5297717 DOI: 10.3390/ijms18010083] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2016] [Revised: 12/14/2016] [Accepted: 12/23/2016] [Indexed: 11/16/2022] Open
Abstract
Ankylosing spondylitis (AS) is a systemic autoimmune disease mainly affecting the lumbar spine and sacroiliac joints, and exhibits peripheral inflammatory arthropathy. More than 25 loci have been identified as associated with AS. Because both AS and rheumatoid arthritis (RA) are autoimmune diseases that may share some common genetic factors, we therefore examined if the newly identified RA genetic polymorphisms were associated with AS in a Taiwanese population. In this study, we enrolled 475 AS patients and 11,301 healthy subjects from a Taiwanese biobank as controls. Although none of single-nucleotide polymorphisms (SNPs) were associated with the susceptibility to AS, the AS disease index Bath AS Global (BAS-G) clinical phenotype was observed as significantly correlated to the AA genotype of rs657075 (CSF2). The significance remains after gender/age/disease duration adjustment and after group categorization by human leukocyte antigen-B 27 (HLA-B27) genotype. We further investigated the possible functions of rs657075 through bioinformatics approaches. Results revealed that polymorphism of rs657075 is able to influence the expression of acyl-CoA synthetase long-chain family member 6 (ACSL6). In conclusion, our study indicated that rs657075 (CSF2) is strongly associated with the AS disease index Bath AS Global (BAS-G) clinical phenotype.
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Affiliation(s)
- Wei-Chiao Chen
- Institude of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan.
| | - James Cheng-Chung Wei
- Division of Allergy, Immunology and Rheumatology, Chung Shan Medical University Hospital, Taichung 40201, Taiwan.
- Institute of Medicine, Chung Shan Medical University, Taichung 40201, Taiwan.
- Institute of Integrative Medicine, China Medical University, Taichung 40201, Taiwan.
| | - Hsing-Fang Lu
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei 11014, Taiwan.
| | - Henry Sung-Ching Wong
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei 11014, Taiwan.
- Master Program for Clinical Pharmacogenomics and Pharmacoproteomics, School of Pharmacy, Taipei Medical University, Taipei 11014, Taiwan.
| | - Peng Yeong Woon
- Department of Molecular Biology and Human Genetics, Tzu Chi University, Hualien 97004, Taiwan.
| | - Yu-Wen Hsu
- The Ph.D. Program for Translational Medicine, College of Medical Science and Technology, Taipei Medical University and Academia Sinica, Taipei 11031, Taiwan.
| | - Jin-Ding Huang
- Institude of Clinical Pharmacy and Pharmaceutical Sciences, College of Medicine, National Cheng Kung University, Tainan 70101, Taiwan.
| | - Wei-Chiao Chang
- Department of Clinical Pharmacy, School of Pharmacy, Taipei Medical University, Taipei 11014, Taiwan.
- Master Program for Clinical Pharmacogenomics and Pharmacoproteomics, School of Pharmacy, Taipei Medical University, Taipei 11014, Taiwan.
- The Ph.D. Program for Translational Medicine, College of Medical Science and Technology, Taipei Medical University and Academia Sinica, Taipei 11031, Taiwan.
- Center for Biomarkers and Biotech Drugs, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.
- Department of Pharmacy, Taipei Medical University-Wanfang Hospital, Taipei 116, Taiwan.
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Pouladi N, Achour I, Li H, Berghout J, Kenost C, Gonzalez-Garay ML, Lussier YA. Biomechanisms of Comorbidity: Reviewing Integrative Analyses of Multi-omics Datasets and Electronic Health Records. Yearb Med Inform 2016; 25:194-206. [PMID: 27830251 PMCID: PMC5171562 DOI: 10.15265/iy-2016-040] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
OBJECTIVES Disease comorbidity is a pervasive phenomenon impacting patients' health outcomes, disease management, and clinical decisions. This review presents past, current and future research directions leveraging both phenotypic and molecular information to uncover disease similarity underpinning the biology and etiology of disease comorbidity. METHODS We retrieved ~130 publications and retained 59, ranging from 2006 to 2015, that comprise a minimum number of five diseases and at least one type of biomolecule. We surveyed their methods, disease similarity metrics, and calculation of comorbidities in the electronic health records, if present. RESULTS Among the surveyed studies, 44% generated or validated disease similarity metrics in context of comorbidity, with 60% being published in the last two years. As inputs, 87% of studies utilized intragenic loci and proteins while 13% employed RNA (mRNA, LncRNA or miRNA). Network modeling was predominantly used (35%) followed by statistics (28%) to impute similarity between these biomolecules and diseases. Studies with large numbers of biomolecules and diseases used network models or naïve overlap of disease-molecule associations, while machine learning, statistics, and information retrieval were utilized in smaller and moderate sized studies. Multiscale computations comprising shared function, network topology, and phenotypes were performed exclusively on proteins. CONCLUSION This review highlighted the growing methods for identifying the molecular mechanisms underpinning comorbidities that leverage multiscale molecular information and patterns from electronic health records. The survey unveiled that intergenic polymorphisms have been overlooked for similarity imputation compared to their intragenic counterparts, offering new opportunities to bridge the mechanistic and similarity gaps of comorbidity.
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Affiliation(s)
| | | | | | | | | | | | - Y A Lussier
- Dr. Yves A. Lussier, The University of Arizona, Bio5 Building, 1657 East Helen Street, Tucson, AZ 85721, USA, Fax: +1 520 626 4824, E-Mail:
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46
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Xia W, Wu J, Deng FY, Wu LF, Zhang YH, Guo YF, Lei SF. Integrative analysis for identification of shared markers from various functional cells/tissues for rheumatoid arthritis. Immunogenetics 2016; 69:77-86. [PMID: 27812736 DOI: 10.1007/s00251-016-0956-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2016] [Accepted: 10/19/2016] [Indexed: 01/18/2023]
Abstract
Rheumatoid arthritis (RA) is a systemic autoimmune disease. So far, it is unclear whether there exist common RA-related genes shared in different tissues/cells. In this study, we conducted an integrative analysis on multiple datasets to identify potential shared genes that are significant in multiple tissues/cells for RA. Seven microarray gene expression datasets representing various RA-related tissues/cells were downloaded from the Gene Expression Omnibus (GEO). Statistical analyses, testing both marginal and joint effects, were conducted to identify significant genes shared in various samples. Followed-up analyses were conducted on functional annotation clustering analysis, protein-protein interaction (PPI) analysis, gene-based association analysis, and ELISA validation analysis in in-house samples. We identified 18 shared significant genes, which were mainly involved in the immune response and chemokine signaling pathway. Among the 18 genes, eight genes (PPBP, PF4, HLA-F, S100A8, RNASEH2A, P2RY6, JAG2, and PCBP1) interact with known RA genes. Two genes (HLA-F and PCBP1) are significant in gene-based association analysis (P = 1.03E-31, P = 1.30E-2, respectively). Additionally, PCBP1 also showed differential protein expression levels in in-house case-control plasma samples (P = 2.60E-2). This study represented the first effort to identify shared RA markers from different functional cells or tissues. The results suggested that one of the shared genes, i.e., PCBP1, is a promising biomarker for RA.
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Affiliation(s)
- Wei Xia
- Center for Genetic Epidemiology and Genomics, School of Public Health, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China.,Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China
| | - Jian Wu
- Department of Rheumatology, the First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215000, People's Republic of China
| | - Fei-Yan Deng
- Center for Genetic Epidemiology and Genomics, School of Public Health, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China.,Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China
| | - Long-Fei Wu
- Center for Genetic Epidemiology and Genomics, School of Public Health, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China.,Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China
| | - Yong-Hong Zhang
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China
| | - Yu-Fan Guo
- Department of Rheumatology, the First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215000, People's Republic of China.
| | - Shu-Feng Lei
- Center for Genetic Epidemiology and Genomics, School of Public Health, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China. .,Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Soochow University, Suzhou, Jiangsu, 215123, People's Republic of China.
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47
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Alonso A, Julià A, Vinaixa M, Domènech E, Fernández-Nebro A, Cañete JD, Ferrándiz C, Tornero J, Gisbert JP, Nos P, Casbas AG, Puig L, González-Álvaro I, Pinto-Tasende JA, Blanco R, Rodríguez MA, Beltran A, Correig X, Marsal S. Urine metabolome profiling of immune-mediated inflammatory diseases. BMC Med 2016; 14:133. [PMID: 27609333 PMCID: PMC5016926 DOI: 10.1186/s12916-016-0681-8] [Citation(s) in RCA: 82] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2016] [Accepted: 08/25/2016] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Immune-mediated inflammatory diseases (IMIDs) are a group of complex and prevalent diseases where disease diagnostic and activity monitoring is highly challenging. The determination of the metabolite profiles of biological samples is becoming a powerful approach to identify new biomarkers of clinical utility. In order to identify new metabolite biomarkers of diagnosis and disease activity, we have performed the first large-scale profiling of the urine metabolome of the six most prevalent IMIDs: rheumatoid arthritis, psoriatic arthritis, psoriasis, systemic lupus erythematosus, Crohn's disease, and ulcerative colitis. METHODS Using nuclear magnetic resonance, we analyzed the urine metabolome in a discovery cohort of 1210 patients and 100 controls. Within each IMID, two patient subgroups were recruited representing extreme disease activity (very high vs. very low). Metabolite association analysis with disease diagnosis and disease activity was performed using multivariate linear regression in order to control for the effects of clinical, epidemiological, or technical variability. After multiple test correction, the most significant metabolite biomarkers were validated in an independent cohort of 1200 patients and 200 controls. RESULTS In the discovery cohort, we identified 28 significant associations between urine metabolite levels and disease diagnosis and three significant metabolite associations with disease activity (P FDR < 0.05). Using the validation cohort, we validated 26 of the diagnostic associations and all three metabolite associations with disease activity (P FDR < 0.05). Combining all diagnostic biomarkers using multivariate classifiers we obtained a good disease prediction accuracy in all IMIDs and particularly high in inflammatory bowel diseases. Several of the associated metabolites were found to be commonly altered in multiple IMIDs, some of which can be considered as hub biomarkers. The analysis of the metabolic reactions connecting the IMID-associated metabolites showed an over-representation of citric acid cycle, phenylalanine, and glycine-serine metabolism pathways. CONCLUSIONS This study shows that urine is a source of biomarkers of clinical utility in IMIDs. We have found that IMIDs show similar metabolic changes, particularly between clinically similar diseases and we have found, for the first time, the presence of hub metabolites. These findings represent an important step in the development of more efficient and less invasive diagnostic and disease monitoring methods in IMIDs.
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Affiliation(s)
- Arnald Alonso
- Rheumatology Research Group, Vall d'Hebron Hospital Research Institute, Barcelona, Spain
| | - Antonio Julià
- Rheumatology Research Group, Vall d'Hebron Hospital Research Institute, Barcelona, Spain.
| | - Maria Vinaixa
- Centre for Omic Sciences, COS-DEEEA-URV-IISPV, Reus, Spain.,Metabolomics Platform, CIBERDEM, Reus, Spain
| | - Eugeni Domènech
- Hospital Universitari Germans Trias i Pujol, Badalona, Spain.,CIBERehd, Madrid, Spain
| | - Antonio Fernández-Nebro
- UGC Reumatología, Instituto de Investigación Biomédica (IBIMA), Hospital Regional Universitario de Málaga, Universidad de Málaga, Málaga, Spain
| | - Juan D Cañete
- Hospital Clínic de Barcelona and IDIBAPS, Barcelona, Spain
| | | | - Jesús Tornero
- Hospital Universitario Guadalajara, Guadalajara, Spain
| | - Javier P Gisbert
- CIBERehd, Madrid, Spain.,Hospital Universitario de la Princesa and IIS-IP, Madrid, Spain
| | - Pilar Nos
- CIBERehd, Madrid, Spain.,Hospital la Fe, Valencia, Spain
| | | | - Lluís Puig
- Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | | | | | - Ricardo Blanco
- Hospital Universitario Marqués de Valdecilla, Santander, Spain
| | - Miguel A Rodríguez
- Centre for Omic Sciences, COS-DEEEA-URV-IISPV, Reus, Spain.,Metabolomics Platform, CIBERDEM, Reus, Spain
| | - Antoni Beltran
- Centre for Omic Sciences, COS-DEEEA-URV-IISPV, Reus, Spain.,Metabolomics Platform, CIBERDEM, Reus, Spain
| | - Xavier Correig
- Centre for Omic Sciences, COS-DEEEA-URV-IISPV, Reus, Spain.,Metabolomics Platform, CIBERDEM, Reus, Spain
| | - Sara Marsal
- Rheumatology Research Group, Vall d'Hebron Hospital Research Institute, Barcelona, Spain.
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48
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Gall BJ, Schroer AB, Gross JD, Setola V, Siderovski DP. Reduction of GPSM3 expression akin to the arthritis-protective SNP rs204989 differentially affects migration in a neutrophil model. Genes Immun 2016; 17:321-7. [PMID: 27307211 PMCID: PMC5009006 DOI: 10.1038/gene.2016.26] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2016] [Revised: 05/03/2016] [Accepted: 05/09/2016] [Indexed: 12/11/2022]
Abstract
G Protein Signaling Modulator-3 (GPSM3) is a leukocyte-specific regulator of G protein-coupled receptors (GPCRs), which binds inactivated Gαi·GDP subunits and precludes their reassociation with Gβγ subunits. GPSM3 deficiency protects mice from inflammatory arthritis and, in humans, GPSM3 single nucleotide polymorphisms (SNPs) are inversely associated with the risk of rheumatoid arthritis development; recently, these polymorphisms were linked to one particular SNP (rs204989) that decreases GPSM3 transcript abundance. However, the precise role of GPSM3 in leukocyte biology is unknown. Here we show that GPSM3 is induced in the human promyelocytic leukemia NB4 cell line following retinoic acid treatment, which differentiates this cell line into a model of neutrophil physiology (NB4*). Reducing GPSM3 expression in NB4* cells, akin to the effect ascribed to the rs204989 C>T transition, disrupts cellular migration toward leukotriene B4 (LTB4) and (to a lesser extent) interleukin-8 (a.k.a. IL-8 or CXCL8), but not migration toward formylated peptides (fMLP). As the chemoattractants LTB4 and CXCL8 are involved in recruitment of neutrophils to the arthritic joint, our results suggest that the arthritis-protective GPSM3 SNP rs204989 may act to decrease neutrophil chemoattractant responsiveness.
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Affiliation(s)
- B J Gall
- Department of Physiology and Pharmacology, West Virginia University School of Medicine, Morgantown, WV, USA
| | - A B Schroer
- Department of Physiology and Pharmacology, West Virginia University School of Medicine, Morgantown, WV, USA
| | - J D Gross
- Department of Physiology and Pharmacology, West Virginia University School of Medicine, Morgantown, WV, USA
| | - V Setola
- Department of Physiology and Pharmacology, West Virginia University School of Medicine, Morgantown, WV, USA.,Department of Behavioral Medicine and Psychiatry, West Virginia University School of Medicine, Morgantown, WV, USA
| | - D P Siderovski
- Department of Physiology and Pharmacology, West Virginia University School of Medicine, Morgantown, WV, USA
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49
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Blanco-Gómez A, Castillo-Lluva S, Del Mar Sáez-Freire M, Hontecillas-Prieto L, Mao JH, Castellanos-Martín A, Pérez-Losada J. Missing heritability of complex diseases: Enlightenment by genetic variants from intermediate phenotypes. Bioessays 2016; 38:664-73. [PMID: 27241833 DOI: 10.1002/bies.201600084] [Citation(s) in RCA: 44] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
Abstract
Diseases of complex origin have a component of quantitative genetics that contributes to their susceptibility and phenotypic variability. However, after several studies, a major part of the genetic component of complex phenotypes has still not been found, a situation known as "missing heritability." Although there have been many hypotheses put forward to explain the reasons for the missing heritability, its definitive causes remain unknown. Complex diseases are caused by multiple intermediate phenotypes involved in their pathogenesis and, very often, each one of these intermediate phenotypes also has a component of quantitative inheritance. Here we propose that at least part of the missing heritability can be explained by the genetic component of intermediate phenotypes that is not detectable at the level of the main complex trait. At the same time, the identification of the genetic component of intermediate phenotypes provides an opportunity to identify part of the missing heritability of complex diseases.
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Affiliation(s)
- Adrián Blanco-Gómez
- Instituto de Biología Molecular y Celular del Cáncer (CIC-IBMCC), Universidad de Salamanca/CSIC, Salamanca, Spain.,Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca, Spain
| | - Sonia Castillo-Lluva
- Instituto de Biología Molecular y Celular del Cáncer (CIC-IBMCC), Universidad de Salamanca/CSIC, Salamanca, Spain.,Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca, Spain
| | - María Del Mar Sáez-Freire
- Instituto de Biología Molecular y Celular del Cáncer (CIC-IBMCC), Universidad de Salamanca/CSIC, Salamanca, Spain.,Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca, Spain
| | - Lourdes Hontecillas-Prieto
- Instituto de Biología Molecular y Celular del Cáncer (CIC-IBMCC), Universidad de Salamanca/CSIC, Salamanca, Spain.,Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca, Spain
| | - Jian Hua Mao
- Life Sciences Division, Lawrence Berkeley National Laboratory (LBNL), University of California, Berkeley, CA, USA
| | - Andrés Castellanos-Martín
- Instituto de Biología Molecular y Celular del Cáncer (CIC-IBMCC), Universidad de Salamanca/CSIC, Salamanca, Spain.,Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca, Spain
| | - Jesus Pérez-Losada
- Instituto de Biología Molecular y Celular del Cáncer (CIC-IBMCC), Universidad de Salamanca/CSIC, Salamanca, Spain.,Instituto de Investigación Biomédica de Salamanca (IBSAL), Salamanca, Spain
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50
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Bagley SC, Sirota M, Chen R, Butte AJ, Altman RB. Constraints on Biological Mechanism from Disease Comorbidity Using Electronic Medical Records and Database of Genetic Variants. PLoS Comput Biol 2016; 12:e1004885. [PMID: 27115429 PMCID: PMC4846031 DOI: 10.1371/journal.pcbi.1004885] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2015] [Accepted: 03/29/2016] [Indexed: 12/24/2022] Open
Abstract
Patterns of disease co-occurrence that deviate from statistical independence may represent important constraints on biological mechanism, which sometimes can be explained by shared genetics. In this work we study the relationship between disease co-occurrence and commonly shared genetic architecture of disease. Records of pairs of diseases were combined from two different electronic medical systems (Columbia, Stanford), and compared to a large database of published disease-associated genetic variants (VARIMED); data on 35 disorders were available across all three sources, which include medical records for over 1.2 million patients and variants from over 17,000 publications. Based on the sources in which they appeared, disease pairs were categorized as having predominant clinical, genetic, or both kinds of manifestations. Confounding effects of age on disease incidence were controlled for by only comparing diseases when they fall in the same cluster of similarly shaped incidence patterns. We find that disease pairs that are overrepresented in both electronic medical record systems and in VARIMED come from two main disease classes, autoimmune and neuropsychiatric. We furthermore identify specific genes that are shared within these disease groups.
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Affiliation(s)
- Steven C. Bagley
- Department of Genetics, Stanford University, Stanford, California, United States of America
- * E-mail:
| | - Marina Sirota
- UCSF Institute for Computational Health Sciences, San Francisco, California, United States of America
| | - Richard Chen
- Personalis, Inc., Menlo Park, California, United States of America
| | - Atul J. Butte
- UCSF Institute for Computational Health Sciences, San Francisco, California, United States of America
| | - Russ B. Altman
- Department of Genetics, Stanford University, Stanford, California, United States of America
- Department of Bioengineering, Stanford University, Stanford, California, United States of America
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