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Villagra UMM, da Cunha BR, Polachini GM, Henrique T, Stefanini ACB, de Castro TB, da Silva CHTP, Feitosa OA, Fukuyama EE, López RVM, Dias-Neto E, Nunes FD, Severino P, Tajara EH. Expression of Truncated Products at the 5'-Terminal Region of RIPK2 and Evolutive Aspects that Support Their Biological Importance. Genome Biol Evol 2024; 16:evae106. [PMID: 38752399 PMCID: PMC11221433 DOI: 10.1093/gbe/evae106] [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] [Accepted: 05/10/2024] [Indexed: 07/04/2024] Open
Abstract
Alternative splicing is the process of generating different mRNAs from the same primary transcript, which contributes to increase the transcriptome and proteome diversity. Abnormal splicing has been associated with the development of several diseases including cancer. Given that mutations and abnormal levels of the RIPK2 transcript and RIP-2 protein are frequent in tumors, and that RIP-2 modulates immune and inflammatory responses, we investigated alternative splicing events that result in partial deletions of the kinase domain at the N-terminus of RIP-2. We also investigated the structure and expression of the RIPK2 truncated variants and isoforms in different environments. In addition, we searched data throughout Supraprimates evolution that could support the biological importance of RIPK2 alternatively spliced products. We observed that human variants and isoforms were differentially regulated following temperature stress, and that the truncated transcript was more expressed than the long transcript in tumor samples. The inverse was found for the longer protein isoform. The truncated variant was also detected in chimpanzee, gorilla, hare, pika, mouse, rat, and tree shrew. The fact that the same variant has been preserved in mammals with divergence times up to 70 million years raises the hypothesis that it may have a functional significance.
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Affiliation(s)
- Ulises M M Villagra
- Faculty of Exact Sciences, Biotechnology and Molecular Biology Institute (IBBM), National University of La Plata-CCT, CONICET, La Plata, Argentina
| | - Bianca R da Cunha
- Department of Molecular Biology, School of Medicine of São José do Rio Preto/FAMERP, São José do Rio Preto, SP, Brazil
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo/USP, São Paulo, SP, Brazil
| | - Giovana M Polachini
- Department of Molecular Biology, School of Medicine of São José do Rio Preto/FAMERP, São José do Rio Preto, SP, Brazil
| | - Tiago Henrique
- Department of Molecular Biology, School of Medicine of São José do Rio Preto/FAMERP, São José do Rio Preto, SP, Brazil
| | - Ana Carolina Buzzo Stefanini
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo/USP, São Paulo, SP, Brazil
| | - Tialfi Bergamin de Castro
- Department of Molecular Biology, School of Medicine of São José do Rio Preto/FAMERP, São José do Rio Preto, SP, Brazil
- Microbial Pathogenesis Department, University of Maryland Baltimore, School of Dentistry, Baltimore, MD, USA
| | - Carlos H T P da Silva
- Computational Laboratory of Pharmaceutical Chemistry, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo/USP, Ribeirão Preto, SP, Brazil
| | - Olavo A Feitosa
- Computational Laboratory of Pharmaceutical Chemistry, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo/USP, Ribeirão Preto, SP, Brazil
| | - Erica E Fukuyama
- Head and Neck Surgery Department, Arnaldo Vieira de Carvalho Cancer Institute, São Paulo, SP, Brazil
| | - Rossana V M López
- Comprehensive Center for Precision Oncology, Center for Translational Research in Oncology, State of São Paulo Cancer Institute—ICESP, Clinics Hospital, Sao Paulo University Medical School, São Paulo, SP, Brazil
| | - Emmanuel Dias-Neto
- Laboratory of Medical Genomics, A.C. Camargo Cancer Center, São Paulo, SP, Brazil
| | - Fabio D Nunes
- Department of Stomatology, School of Dentistry, University of São Paulo/USP, São Paulo, SP, Brazil
| | - Patricia Severino
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo/USP, São Paulo, SP, Brazil
- Albert Einstein Research and Education Institute, Hospital Israelita Albert Einstein, São Paulo, SP, Brazil
| | - Eloiza H Tajara
- Department of Molecular Biology, School of Medicine of São José do Rio Preto/FAMERP, São José do Rio Preto, SP, Brazil
- Department of Genetics and Evolutionary Biology, Institute of Biosciences, University of São Paulo/USP, São Paulo, SP, Brazil
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Nieto-Caballero VE, Reijneveld JF, Ruvalcaba A, Innocenzi G, Abeydeera N, Asgari S, Lopez K, Iwany SK, Luo Y, Nathan A, Fernandez-Salinas D, Chiñas M, Huang CC, Zhang Z, León SR, Calderon RI, Lecca L, Budzik JM, Murray M, Van Rhijn I, Raychaudhuri S, Moody DB, Suliman S, Gutierrez-Arcelus M. History of tuberculosis disease is associated with genetic regulatory variation in Peruvians. PLoS Genet 2024; 20:e1011313. [PMID: 38870230 PMCID: PMC11208071 DOI: 10.1371/journal.pgen.1011313] [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: 09/13/2023] [Revised: 06/26/2024] [Accepted: 05/21/2024] [Indexed: 06/15/2024] Open
Abstract
A quarter of humanity is estimated to have been exposed to Mycobacterium tuberculosis (Mtb) with a 5-10% risk of developing tuberculosis (TB) disease. Variability in responses to Mtb infection could be due to host or pathogen heterogeneity. Here, we focused on host genetic variation in a Peruvian population and its associations with gene regulation in monocyte-derived macrophages and dendritic cells (DCs). We recruited former household contacts of TB patients who previously progressed to TB (cases, n = 63) or did not progress to TB (controls, n = 63). Transcriptomic profiling of monocyte-derived DCs and macrophages measured the impact of genetic variants on gene expression by identifying expression quantitative trait loci (eQTL). We identified 330 and 257 eQTL genes in DCs and macrophages (False Discovery Rate (FDR) < 0.05), respectively. Four genes in DCs showed interaction between eQTL variants and TB progression status. The top eQTL interaction for a protein-coding gene was with FAH, the gene encoding fumarylacetoacetate hydrolase, which mediates the last step in mammalian tyrosine catabolism. FAH expression was associated with genetic regulatory variation in cases but not controls. Using public transcriptomic and epigenomic data of Mtb-infected monocyte-derived dendritic cells, we found that Mtb infection results in FAH downregulation and DNA methylation changes in the locus. Overall, this study demonstrates effects of genetic variation on gene expression levels that are dependent on history of infectious disease and highlights a candidate pathogenic mechanism through pathogen-response genes. Furthermore, our results point to tyrosine metabolism and related candidate TB progression pathways for further investigation.
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Affiliation(s)
- Victor E. Nieto-Caballero
- Division of Immunology, Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Undergraduate Program in Genomic Sciences, Center for Genomic Sciences, Universidad Nacional Autónoma de México (UNAM), Morelos, Mexico
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Josephine F. Reijneveld
- Zuckerberg San Francisco General Hospital, Division of Experimental Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Angel Ruvalcaba
- Zuckerberg San Francisco General Hospital, Division of Experimental Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Gabriel Innocenzi
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Nalin Abeydeera
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Samira Asgari
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
- Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America
| | - Kattya Lopez
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Socios En Salud Sucursal Peru, Lima, Peru
| | - Sarah K. Iwany
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Yang Luo
- Division of Immunology, Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
- Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Kennedy Institute of Rheumatology, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, United Kingdom
| | - Aparna Nathan
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
- Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Daniela Fernandez-Salinas
- Division of Immunology, Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Marcos Chiñas
- Division of Immunology, Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
| | - Chuan-Chin Huang
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Zibiao Zhang
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Segundo R. León
- Socios En Salud Sucursal Peru, Lima, Peru
- Medical Technology School and Global Health Research Institute, San Juan Bautista Private University, Lima, Perú
| | | | | | - Jonathan M. Budzik
- Division of Pulmonary, Critical Care, Allergy and Sleep Medicine, Department of Medicine, University of California San Francisco, San Francisco, California, United States of America
| | - Megan Murray
- Department of Global Health and Social Medicine, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Ildiko Van Rhijn
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Soumya Raychaudhuri
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
- Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - D. Branch Moody
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Sara Suliman
- Zuckerberg San Francisco General Hospital, Division of Experimental Medicine, University of California San Francisco, San Francisco, California, United States of America
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Gladstone-UCSF Institute of Genomic Immunology, University of California San Francisco, San Francisco, California, United States of America
- Chan Zuckerberg Initiative Biohub, San Francisco, California, United States of America
| | - Maria Gutierrez-Arcelus
- Division of Immunology, Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Department of Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, United States of America
- Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
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Gonzalez-Latapi P, Bustos B, Dong S, Lubbe S, Simuni T, Krainc D. Alterations in Blood Methylome as Potential Epigenetic Biomarker in Sporadic Parkinson's Disease. Ann Neurol 2024; 95:1162-1172. [PMID: 38563317 DOI: 10.1002/ana.26923] [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: 09/29/2023] [Revised: 02/03/2024] [Accepted: 02/19/2024] [Indexed: 04/04/2024]
Abstract
OBJECTIVE To characterize DNA methylation (DNAm) differences between sporadic Parkinson's disease (PD) and healthy control (HC) individuals enrolled in the Parkinson's Progression Markers Initiative (PPMI). METHODS Using whole blood, we characterized longitudinal differences in DNAm between sporadic PD patients (n = 196) and HCs (n = 86) enrolled in PPMI. RNA sequencing (RNAseq) was used to conduct gene expression analyses for genes mapped to differentially methylated cytosine-guanine sites (CpGs). RESULTS At the time of patient enrollment, 5,178 CpGs were differentially methylated (2,683 hypermethylated and 2,495 hypomethylated) in PD compared to HC. Of these, 579 CpGs underwent significant methylation changes over 3 years. Several differentially methylated CpGs were found near the cytochrome P450 family 2 subfamily E member 1 (CYP2E1) gene. Additionally, multiple hypermethylated CpGs were associated with the N-myc downregulated gene family member 4 (NDRG4) gene. RNA-Seq analyses showed 75 differentially expressed genes in PD patients compared to controls. An integrative analysis of both differentially methylated sites and differentially expressed genes revealed 20 genes that exhibited hypomethylation concomitant with overexpression. Additionally, 1 gene, cathepsin H (CTSH), displayed hypermethylation that was associated with its decreased expression. INTERPRETATION We provide initial evidence of alterations in DNAm in blood of PD patients that may serve as potential epigenetic biomarker of disease. To evaluate the significance of these changes throughout the progression of PD, additional profiling at longer intervals and during the prodromal stages of disease will be necessary. ANN NEUROL 2024;95:1162-1172.
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Affiliation(s)
- Paulina Gonzalez-Latapi
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Bernabe Bustos
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Siyuan Dong
- Biostatistics Collaboration Center, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Steven Lubbe
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Tanya Simuni
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Dimitri Krainc
- Department of Neurology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
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Chiñas M, Fernandez-Salinas D, Aguiar VRC, Nieto-Caballero VE, Lefton M, Nigrovic PA, Ermann J, Gutierrez-Arcelus M. Functional genomics implicates natural killer cells in the pathogenesis of ankylosing spondylitis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.09.21.23295912. [PMID: 37808698 PMCID: PMC10557806 DOI: 10.1101/2023.09.21.23295912] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/10/2023]
Abstract
Objective Multiple lines of evidence indicate that ankylosing spondylitis (AS) is a lymphocyte-driven disease. However, which lymphocyte populations are critical in AS pathogenesis is not known. In this study, we aimed to identify the key cell types mediating the genetic risk in AS using an unbiased functional genomics approach. Methods We integrated genome-wide association study (GWAS) data with epigenomic and transcriptomic datasets of human immune cells. To quantify enrichment of cell type-specific open chromatin or gene expression in AS risk loci, we used three published methods that have successfully identified relevant cell types in other diseases. We performed co-localization analyses between GWAS risk loci and genetic variants associated with gene expression (eQTL) to find putative target genes. Results Natural killer (NK) cell-specific open chromatin regions are significantly enriched in heritability for AS, compared to other immune cell types such as T cells, B cells, and monocytes. This finding was consistent between two AS GWAS. Using RNA-seq data, we validated that genes in AS risk loci are enriched in NK cell-specific gene expression. Using the human Space-Time Gut Cell Atlas, we also found significant upregulation of AS-associated genes predominantly in NK cells. Co-localization analysis revealed four AS risk loci affecting regulation of candidate target genes in NK cells: two known loci, ERAP1 and TNFRSF1A, and two under-studied loci, ENTR1 (aka SDCCAG3) and B3GNT2. Conclusion Our findings suggest that NK cells may play a crucial role in AS development and highlight four putative target genes for functional follow-up in NK cells.
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Affiliation(s)
- Marcos Chiñas
- Division of Immunology, Boston Children’s Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Daniela Fernandez-Salinas
- Division of Immunology, Boston Children’s Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Licenciatura en Ciencias Genomicas, Centro de Ciencias Genomicas, Universidad Nacional Autónoma de México (UNAM), Morelos 62210, Mexico
| | - Vitor R. C. Aguiar
- Division of Immunology, Boston Children’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
| | - Victor E. Nieto-Caballero
- Division of Immunology, Boston Children’s Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Licenciatura en Ciencias Genomicas, Centro de Ciencias Genomicas, Universidad Nacional Autónoma de México (UNAM), Morelos 62210, Mexico
| | - Micah Lefton
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Peter A. Nigrovic
- Division of Immunology, Boston Children’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Joerg Ermann
- Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Maria Gutierrez-Arcelus
- Division of Immunology, Boston Children’s Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA, USA
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Tang Z, Gaskins AJ, Hood RB, Ford JB, Hauser R, Smith AK, Everson TM. Former smoking associated with epigenetic modifications in human granulosa cells among women undergoing assisted reproduction. Sci Rep 2024; 14:5009. [PMID: 38424222 PMCID: PMC10904848 DOI: 10.1038/s41598-024-54957-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Accepted: 02/19/2024] [Indexed: 03/02/2024] Open
Abstract
Smoking exposure during adulthood can disrupt oocyte development in women, contributing to infertility and possibly adverse birth outcomes. Some of these effects may be reflected in epigenome profiles in granulosa cells (GCs) in human follicular fluid. We compared the epigenetic modifications throughout the genome in GCs from women who were former (N = 15) versus never smokers (N = 44) undergoing assisted reproductive technologies (ART). This study included 59 women undergoing ART. Smoking history including time since quitting was determined by questionnaire. GCs were collected during oocyte retrieval and DNA methylation (DNAm) levels were profiled using the Infinium MethylationEPIC BeadChip. We performed an epigenome-wide association study with robust linear models, regressing DNAm level at individual loci on smoking status, adjusting for age, ovarian stimulation protocol, and three surrogate variables. We performed differentially methylated regions (DMRs) analysis and over-representation analysis of the identified CpGs and corresponding gene set. 81 CpGs were differentially methylated among former smokers compared to never smokers (FDR < 0.05). We identified 2 significant DMRs (KCNQ1 and RHBDD2). The former smoking-associated genes were enriched in oxytocin signaling, adrenergic signaling in cardiomyocytes, platelet activation, axon guidance, and chemokine signaling pathway. These epigenetic variations have been associated with inflammatory responses, reproductive outcomes, cancer development, neurodevelopmental disorder, and cardiometabolic health. Secondarily, we examined the relationships between time since quitting and DNAm at significant CpGs. We observed three CpGs in negative associations with the length of quitting smoking (p < 0.05), which were cg04254052 (KCNIP1), cg22875371 (OGDHL), and cg27289628 (LOC148145), while one in positive association, which was cg13487862 (PLXNB1). As a pilot study, we demonstrated epigenetic modifications associated with former smoking in GCs. The study is informative to potential biological pathways underlying the documented association between smoking and female infertility and biomarker discovery for smoking-associated reproductive outcomes.
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Affiliation(s)
- Ziyin Tang
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Audrey J Gaskins
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Robert B Hood
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Jennifer B Ford
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Russ Hauser
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Alicia K Smith
- Department of Obstetrics and Gynecology, School of Medicine, Emory University, Atlanta, GA, USA
| | - Todd M Everson
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
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Shimada M, Omae Y, Kakita A, Gabdulkhaev R, Hitomi Y, Miyagawa T, Honda M, Fujimoto A, Tokunaga K. Identification of region-specific gene isoforms in the human brain using long-read transcriptome sequencing. SCIENCE ADVANCES 2024; 10:eadj5279. [PMID: 38266094 PMCID: PMC10807796 DOI: 10.1126/sciadv.adj5279] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/04/2023] [Accepted: 12/21/2023] [Indexed: 01/26/2024]
Abstract
In neurological and neuropsychiatric diseases, different brain regions are affected, and differences in gene expression patterns could potentially explain this mechanism. However, limited studies have precisely explored gene expression in different regions of the human brain. In this study, we performed long-read RNA sequencing on three different brain regions of the same individuals: the cerebellum, hypothalamus, and temporal cortex. Despite stringent filtering criteria excluding isoforms predicted to be artifacts, over half of the isoforms expressed in multiple samples across multiple regions were found to be unregistered in the GENCODE reference. We then especially focused on genes with different major isoforms in each brain region, even with similar overall expression levels, and identified that many of such genes including GAS7 might have distinct roles in dendritic spine and neuronal formation in each region. We also found that DNA methylation might, in part, drive different isoform expressions in different regions. These findings highlight the significance of analyzing isoforms expressed in disease-relevant sites.
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Affiliation(s)
- Mihoko Shimada
- Genome Medical Science Project (Toyama), National Center for Global Health and Medicine (NCGM), Tokyo, Japan
- Center for Clinical Sciences, National Center for Global Health and Medicine (NCGM), Tokyo, Japan
- Sleep Disorders Project, Department of Psychiatry and Behavioral Sciences, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Yosuke Omae
- Genome Medical Science Project (Toyama), National Center for Global Health and Medicine (NCGM), Tokyo, Japan
| | - Akiyoshi Kakita
- Department of Pathology, Brain Research Institute, Niigata University, Niigata, Japan
| | - Ramil Gabdulkhaev
- Department of Pathology, Brain Research Institute, Niigata University, Niigata, Japan
| | - Yuki Hitomi
- Department of Human Genetics, Research Institute, National Center for Global Health and Medicine (NCGM), Tokyo, Japan
| | - Taku Miyagawa
- Sleep Disorders Project, Department of Psychiatry and Behavioral Sciences, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
| | - Makoto Honda
- Sleep Disorders Project, Department of Psychiatry and Behavioral Sciences, Tokyo Metropolitan Institute of Medical Science, Tokyo, Japan
- Japan Somnology Center and Seiwa Hospital, Institute of Neuropsychiatry, Tokyo, Japan
| | - Akihiro Fujimoto
- Department of Human Genetics, Graduate School of Medicine, the University of Tokyo, Tokyo, Japan
| | - Katsushi Tokunaga
- Genome Medical Science Project (Toyama), National Center for Global Health and Medicine (NCGM), Tokyo, Japan
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Kumar S, Seem K, Kumar S, Singh A, Krishnan SG, Mohapatra T. DNA methylome analysis provides insights into gene regulatory mechanism for better performance of rice under fluctuating environmental conditions: epigenomics of adaptive plasticity. PLANTA 2023; 259:4. [PMID: 37993704 DOI: 10.1007/s00425-023-04272-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/02/2023] [Accepted: 10/20/2023] [Indexed: 11/24/2023]
Abstract
MAIN CONCLUSION Roots play an important role in adaptive plasticity of rice under dry/direct-sown conditions. However, hypomethylation of genes in leaves (resulting in up-regulated expression) complements the adaptive plasticity of Nagina-22 under DSR conditions. Rice is generally cultivated by transplanting which requires plenty of water for irrigation. Such a practice makes rice cultivation a challenging task under global climate change and reducing water availability. However, dry-seeded/direct-sown rice (DSR) has emerged as a resource-saving alternative to transplanted rice (TPR). Though some of the well-adapted local cultivars are used for DSR, only limited success has been achieved in developing DSR varieties mainly because of a limited knowledge of adaptability of rice under fluctuating environmental conditions. Based on better morpho-physiological and agronomic performance of Nagina-22 (N-22) under DSR conditions, N-22 and IR-64 were grown by transplanting and direct-sowing and used for whole genome methylome analysis to unravel the epigenetic basis of adaptive plasticity of rice. Comparative methylome and transcriptome analyses indicated a large number (4078) of genes regulated through DNA methylation/demethylation in N-22 under DSR conditions. Gene × environment interactions play important roles in adaptive plasticity of rice under direct-sown conditions. While genes for pectinesterase, LRK10, C2H2 zinc-finger protein, splicing factor, transposable elements, and some of the unannotated proteins were hypermethylated, the genes for regulation of transcription, protein phosphorylation, etc. were hypomethylated in CG context in the root of N-22, which played important roles in providing adaptive plasticity to N-22 under DSR conditions. Hypomethylation leading to up-regulation of gene expression in the leaf complements the adaptive plasticity of N-22 under DSR conditions. Moreover, differential post-translational modification of proteins and chromatin assembly/disassembly through DNA methylation in CHG context modulate adaptive plasticity of N-22. These findings would help developing DSR cultivars for increased water-productivity and ecological efficiency.
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Affiliation(s)
- Suresh Kumar
- Division of Biochemistry, ICAR-Indian Agricultural Research Institute, New Delhi, India.
| | - Karishma Seem
- Division of Biochemistry, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | | | - Archana Singh
- Division of Biochemistry, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | - S Gopala Krishnan
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
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Berl A, Shir-az O, Genish I, Biran H, Mann D, Singh A, Wise J, Kravtsov V, Kidron D, Golberg A, Vitkin E, Yakhini Z, Shalom A. Exploring multisite heterogeneity of human basal cell carcinoma proteome and transcriptome. PLoS One 2023; 18:e0293744. [PMID: 37948379 PMCID: PMC10637653 DOI: 10.1371/journal.pone.0293744] [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: 02/02/2023] [Accepted: 10/18/2023] [Indexed: 11/12/2023] Open
Abstract
Basal cell carcinoma (BCC) is the most common type of skin cancer. Due to multiple, potential underlying molecular tumor aberrations, clinical treatment protocols are not well-defined. This study presents multisite molecular heterogeneity profiles of human BCC based on RNA and proteome profiling. Three areas from lesions excised from 9 patients were analyzed. The focus was gene expression profiles based on proteome and RNA measurements of intra-tumor heterogeneity from the same patient and inter-tumor heterogeneity in nodular, infiltrative, and superficial BCC tumor subtypes from different patients. We observed significant overlap in intra- and inter-tumor variability of proteome and RNA expression profiles, showing significant multisite heterogeneity of protein expression in the BCC tumors. Inter-subtype analysis has also identified unique proteins for each BCC subtype. This profiling leads to a deeper understanding of BCC molecular heterogeneity and potentially contributes to developing new sampling tools for personalized diagnostics therapeutic approaches to BCC.
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Affiliation(s)
- Ariel Berl
- Department of Plastic Surgery, Meir Medical Center, Kfar Sava, Israel, Affiliated with the Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Ofir Shir-az
- Department of Plastic Surgery, Meir Medical Center, Kfar Sava, Israel, Affiliated with the Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Ilai Genish
- Efi Arazi School of Computer Science, Reichman University, Herzliya, Israel
| | - Hadas Biran
- Department of Computer Science, Technion - Israel Institute of Technology, Haifa, Israel
| | - Din Mann
- Department of Plastic Surgery, Meir Medical Center, Kfar Sava, Israel, Affiliated with the Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Amrita Singh
- Department of Environmental Studies, Porter School of Environment and Earth Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Julia Wise
- Department of Environmental Studies, Porter School of Environment and Earth Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Vladimir Kravtsov
- Department of Pathology, Meir Medical Center, Kfar Sava, Israel, Affiliated with the Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Debora Kidron
- Department of Pathology, Meir Medical Center, Kfar Sava, Israel, Affiliated with the Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
| | - Alexander Golberg
- Department of Environmental Studies, Porter School of Environment and Earth Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Edward Vitkin
- Efi Arazi School of Computer Science, Reichman University, Herzliya, Israel
| | - Zohar Yakhini
- Efi Arazi School of Computer Science, Reichman University, Herzliya, Israel
- Department of Computer Science, Technion - Israel Institute of Technology, Haifa, Israel
| | - Avshalom Shalom
- Department of Plastic Surgery, Meir Medical Center, Kfar Sava, Israel, Affiliated with the Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
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9
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Wang Q, Martínez-Bonet M, Kim T, Sparks JA, Ishigaki K, Chen X, Sudman M, Aguiar V, Sim S, Hernandez MC, Chiu DJ, Wactor A, Wauford B, Marion MC, Gutierrez-Arcelus M, Bowes J, Eyre S, Nordal E, Prahalad S, Rygg M, Videm V, Raychaudhuri S, Weirauch MT, Langefeld CD, Thompson SD, Nigrovic PA. Identification of a regulatory pathway governing TRAF1 via an arthritis-associated non-coding variant. CELL GENOMICS 2023; 3:100420. [PMID: 38020975 PMCID: PMC10667332 DOI: 10.1016/j.xgen.2023.100420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 06/16/2023] [Accepted: 09/11/2023] [Indexed: 12/01/2023]
Abstract
TRAF1/C5 was among the first loci shown to confer risk for inflammatory arthritis in the absence of an associated coding variant, but its genetic mechanism remains undefined. Using Immunochip data from 3,939 patients with juvenile idiopathic arthritis (JIA) and 14,412 control individuals, we identified 132 plausible common non-coding variants, reduced serially by single-nucleotide polymorphism sequencing (SNP-seq), electrophoretic mobility shift, and luciferase studies to the single variant rs7034653 in the third intron of TRAF1. Genetically manipulated experimental cells and primary monocytes from genotyped donors establish that the risk G allele reduces binding of Fos-related antigen 2 (FRA2), encoded by FOSL2, resulting in reduced TRAF1 expression and enhanced tumor necrosis factor (TNF) production. Conditioning on this JIA variant eliminated attributable risk for rheumatoid arthritis, implicating a mechanism shared across the arthritis spectrum. These findings reveal that rs7034653, FRA2, and TRAF1 mediate a pathway through which a non-coding functional variant drives risk of inflammatory arthritis in children and adults.
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Affiliation(s)
- Qiang Wang
- Division of Immunology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Marta Martínez-Bonet
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Laboratory of Immune-regulation, Instituto de Investigación Sanitaria Gregorio Marañón, Madrid, Spain
| | - Taehyeung Kim
- Division of Immunology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Jeffrey A. Sparks
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Kazuyoshi Ishigaki
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Xiaoting Chen
- Center of Autoimmune Genomics and Etiology, Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
| | - Marc Sudman
- Center of Autoimmune Genomics and Etiology, Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
| | - Vitor Aguiar
- Division of Immunology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Sangwan Sim
- Division of Immunology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Darren J. Chiu
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Alexandra Wactor
- Division of Immunology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Brian Wauford
- Division of Immunology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Miranda C. Marion
- Department of Biostatistics and Data Science, and Center for Precision Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Maria Gutierrez-Arcelus
- Division of Immunology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
- Center of Autoimmune Genomics and Etiology, Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
| | - John Bowes
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Oxford Road, Manchester, UK
- NIHR Manchester Musculoskeletal Biomedical Research Unit, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Stephen Eyre
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Oxford Road, Manchester, UK
- NIHR Manchester Musculoskeletal Biomedical Research Unit, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, UK
| | - Ellen Nordal
- University Hospital of North Norway and UIT The Arctic University of Norway, Tromsø, Norway
| | - Sampath Prahalad
- Emory University Department of Pediatrics and Children’s Healthcare of Atlanta, Atlanta, GA, USA
| | - Marite Rygg
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
- Department of Pediatrics, St. Olav’s University Hospital, Trondheim, Norway
| | - Vibeke Videm
- Department of Clinical and Molecular Medicine, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Soumya Raychaudhuri
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Oxford Road, Manchester, UK
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Center for Data Science, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Matthew T. Weirauch
- Center of Autoimmune Genomics and Etiology, Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
- Divisions of Human Genetics, Biomedical Informatics, and Developmental Biology, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Carl D. Langefeld
- Department of Biostatistics and Data Science, and Center for Precision Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Susan D. Thompson
- Center of Autoimmune Genomics and Etiology, Division of Human Genetics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Peter A. Nigrovic
- Division of Immunology, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
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10
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Buckhaults K, Swack BD, Sachs BD. Estrogen administration and withdrawal in a model of hormone-simulated pregnancy lead to alterations in behavior and gene expression but do not induce depression-like phenotypes in mice. Physiol Behav 2023; 269:114288. [PMID: 37414236 DOI: 10.1016/j.physbeh.2023.114288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 06/19/2023] [Accepted: 07/03/2023] [Indexed: 07/08/2023]
Abstract
Pregnancy and the post-partum period are associated with substantial fluctuations in hormone levels and are frequently associated with significant stress. Many individuals also experience affective disturbances during the peri‑partum period, including anxiety, the 'baby blues,' and post-partum depression. However, the extent to which these affective changes result from rapidly altering hormone levels, increased stress, or the combination of both remains largely unknown. The current study sought to evaluate the consequences of pregnancy-like hormonal changes on behavior and gene expression in c57BL/6 mice in the absence of stress using a hormone-simulated pregnancy model. Our results reveal that animals receiving hormone injections to simulate the high levels of estrogen observed in late pregnancy and animals withdrawn from estrogen to mimic the rapid decline in this hormone following parturition both exhibit increased anxiety-like behavior compared to ovariectomized controls in the novel open field test. However, no other significant anxiety- or depression-like alterations were observed in either hormone-treated group compared to ovariectomized controls. Both hormone administration and estrogen withdrawal were shown to induce several significant alterations in gene expression in the bed nucleus of the stria terminalis and the paraventricular nucleus of the hypothalamus. In contrast to the estrogen withdrawal hypothesis of post-partum depression, our results suggest that this method estrogen withdrawal following hormone-simulated pregnancy in the absence of stress does not induce phenotypes consistent with post-partum depression in c57BL/6 mice. However, given that estrogen withdrawal does lead to significant gene expression changes in two stress-sensitive brain regions, it remains possible that estrogen withdrawal could still contribute to affective dysregulation in the peri-partum period by influencing susceptibility to stress. Future research is required to evaluate this possibility.
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Affiliation(s)
- Kerry Buckhaults
- Department of Psychological and Brain Sciences, Villanova University, Villanova, PA, 19085, USA
| | - Benjamin D Swack
- Department of Psychological and Brain Sciences, Villanova University, Villanova, PA, 19085, USA
| | - Benjamin D Sachs
- Department of Psychological and Brain Sciences, Villanova University, Villanova, PA, 19085, USA.
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11
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Suliman S, Nieto-Caballero VE, Asgari S, Lopez K, Iwany SK, Luo Y, Nathan A, Fernandez-Salinas D, Chiñas M, Huang CC, Zhang Z, León SR, Calderon RI, Lecca L, Murray M, Van Rhijn I, Raychaudhuri S, Moody DB, Gutierrez-Arcelus M. History of tuberculosis disease is associated with genetic regulatory variation in Peruvians. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.20.23291558. [PMID: 37425785 PMCID: PMC10327177 DOI: 10.1101/2023.06.20.23291558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
A quarter of humanity is estimated to be latently infected with Mycobacterium tuberculosis (Mtb) with a 5-10% risk of developing tuberculosis (TB) disease. Variability in responses to Mtb infection could be due to host or pathogen heterogeneity. Here, we focused on host genetic variation in a Peruvian population and its associations with gene regulation in monocyte-derived macrophages and dendritic cells (DCs). We recruited former household contacts of TB patients who previously progressed to TB (cases, n=63) or did not progress to TB (controls, n=63). Transcriptomic profiling of monocyte-derived dendritic cells (DCs) and macrophages measured the impact of genetic variants on gene expression by identifying expression quantitative trait loci (eQTL). We identified 330 and 257 eQTL genes in DCs and macrophages (False Discovery Rate (FDR) < 0.05), respectively. Five genes in DCs showed interaction between eQTL variants and TB progression status. The top eQTL interaction for a protein-coding gene was with FAH, the gene encoding fumarylacetoacetate hydrolase, which mediates the last step in mammalian tyrosine catabolism. FAH expression was associated with genetic regulatory variation in cases but not controls. Using public transcriptomic and epigenomic data of Mtb-infected monocyte-derived dendritic cells, we found that Mtb infection results in FAH downregulation and DNA methylation changes in the locus. Overall, this study demonstrates effects of genetic variation on gene expression levels that are dependent on history of infectious disease and highlights a candidate pathogenic mechanism through pathogen-response genes. Furthermore, our results point to tyrosine metabolism and related candidate TB progression pathways for further investigation.
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Affiliation(s)
- Sara Suliman
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Zuckerberg San Francisco General Hospital, Division of Experimental Medicine, University of California San Francisco, San Francisco, CA, USA
- Gladstone-UCSF Institute of Genomic Immunology, University of California San Francisco, San Francisco, CA, USA
- Chan Zuckerberg Initiative Biohub, San Francisco, CA, USA
| | - Victor E. Nieto-Caballero
- Division of Immunology, Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
- Undergraduate Program in Genomic Sciences, Center for Genomic Sciences, Universidad Nacional Autónoma de México (UNAM), Morelos 62210, Mexico
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Samira Asgari
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Institute for Genomic Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Kattya Lopez
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Socios En Salud Sucursal Peru, Lima, Peru
| | - Sarah K. Iwany
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Yang Luo
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Kennedy Institute of Rheumatology, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK
| | - Aparna Nathan
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Daniela Fernandez-Salinas
- Division of Immunology, Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Marcos Chiñas
- Division of Immunology, Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Chuan-Chin Huang
- Department of Global Health and Social Medicine, and Division of Global Health Equity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Zibiao Zhang
- Department of Global Health and Social Medicine, and Division of Global Health Equity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Segundo R León
- Socios En Salud Sucursal Peru, Lima, Peru
- Medical Technology School and Global Health Research Institute, San Juan Bautista Private University, Lima, Perú
| | | | | | - Megan Murray
- Department of Global Health and Social Medicine, and Division of Global Health Equity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Ildiko Van Rhijn
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Infectious Diseases and Immunology, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - Soumya Raychaudhuri
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - D. Branch Moody
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Maria Gutierrez-Arcelus
- Division of Rheumatology, Inflammation and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Division of Immunology, Department of Pediatrics, Boston Children’s Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Genetics, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
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12
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Subramani P, Nagarajan N, Mariaraj S, Vilwanathan R. Knockdown of sirtuin6 positively regulates acetylation of DNMT1 to inhibit NOTCH signaling pathway in non-small cell lung cancer cell lines. Cell Signal 2023; 105:110629. [PMID: 36813148 DOI: 10.1016/j.cellsig.2023.110629] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2022] [Revised: 02/10/2023] [Accepted: 02/13/2023] [Indexed: 02/22/2023]
Abstract
BACKGROUND AND AIM Sirtuin proteins (1-7) are nicotinamide adenine dinucleotide (NAD)-dependent deacetylases and ADP-ribosyl transferases (class III histone deacetylase enzymes (HDAC)) mainly involved in the removal of the acetyl group from histone proteins. SIRT6, one of the sirtuins, plays a major role in cancer progression in many types of cancer conditions. We recently reported that SIRT6 acts as an oncogene in NSCLC; thus, silencing of SIRT6 inhibits cell proliferation and induces apoptosis in NSCLC cell lines. NOTCH signaling has been reported to be involved in cell survival and regulates cell proliferation and differentiation. However, recent studies from different groups have converged on the notion that NOTCH1 may be an important oncogene in NSCLC. The abnormal expression of NOTCH signaling pathway members is a relatively frequent event in patients with NSCLC. SIRT6 and the NOTCH signaling pathway might play a critical role in tumorigenesis since they are highly expressed in NSCLC. This study has been performed to explore the exact mechanism by which SIRT6 inhibits cell proliferation and induces the apoptosis of NSCLC cell lines and its correlation with NOTCH signaling. MAIN METHODS In vitro experiments with human NSCLC cells have been performed. Immunocytochemistry study was used to analyze the expression of NOTCH1 and DNMT1 in A549 and NCI-H460 cell lines. RT-qPCR, Western Blot, Methylated DNA specific PCR, and Co-Immunoprecipitation were performed to explore the key events in the regulation of NOTCH signaling by silencing SIRT6 in NSCLC cell lines. KEY FINDINGS The findings of this study suggest that silencing of SIRT6 significantly promotes the acetylation status of DNMT1 and stabilizes it. Consequently, acetylated DNMT1 translocates into the nucleus and methylates the NOTCH1 promoter region, resulting in the hindering of NOTCH1-mediated NOTCH signaling.
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Affiliation(s)
- Prabhu Subramani
- Cancer Biology Laboratory, Department of Biochemistry, School of Life Sciences, Bharathidasan University, Tiruchirappalli 620 024, Tamil Nadu, India
| | - Nanthakumar Nagarajan
- Cancer Biology Laboratory, Department of Biochemistry, School of Life Sciences, Bharathidasan University, Tiruchirappalli 620 024, Tamil Nadu, India
| | - Sagayamercy Mariaraj
- Cancer Biology Laboratory, Department of Biochemistry, School of Life Sciences, Bharathidasan University, Tiruchirappalli 620 024, Tamil Nadu, India
| | - Ravikumar Vilwanathan
- Cancer Biology Laboratory, Department of Biochemistry, School of Life Sciences, Bharathidasan University, Tiruchirappalli 620 024, Tamil Nadu, India.
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13
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Allen PC, Smith S, Wilson RC, Wirth JR, Wilson NH, Baker Frost D, Flume J, Gilkeson GS, Cunningham MA, Langefeld CD, Absher DM, Ramos PS. Distinct genome-wide DNA methylation and gene expression signatures in classical monocytes from African American patients with systemic sclerosis. Clin Epigenetics 2023; 15:25. [PMID: 36803404 PMCID: PMC9938585 DOI: 10.1186/s13148-023-01445-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Accepted: 02/08/2023] [Indexed: 02/19/2023] Open
Abstract
BACKGROUND Systemic sclerosis (SSc) is a multisystem autoimmune disorder that has an unclear etiology and disproportionately affects women and African Americans. Despite this, African Americans are dramatically underrepresented in SSc research. Additionally, monocytes show heightened activation in SSc and in African Americans relative to European Americans. In this study, we sought to investigate DNA methylation and gene expression patterns in classical monocytes in a health disparity population. METHODS Classical monocytes (CD14+ + CD16-) were FACS-isolated from 34 self-reported African American women. Samples from 12 SSc patients and 12 healthy controls were hybridized on MethylationEPIC BeadChip array, while RNA-seq was performed on 16 SSc patients and 18 healthy controls. Analyses were computed to identify differentially methylated CpGs (DMCs), differentially expressed genes (DEGs), and CpGs associated with changes in gene expression (eQTM analysis). RESULTS We observed modest DNA methylation and gene expression differences between cases and controls. The genes harboring the top DMCs, the top DEGs, as well as the top eQTM loci were enriched for metabolic processes. Genes involved in immune processes and pathways showed a weak upregulation in the transcriptomic analysis. While many genes were newly identified, several other have been previously reported as differentially methylated or expressed in different blood cells from patients with SSc, supporting for their potential dysregulation in SSc. CONCLUSIONS While contrasting with results found in other blood cell types in largely European-descent groups, the results of this study support that variation in DNA methylation and gene expression exists among different cell types and individuals of different genetic, clinical, social, and environmental backgrounds. This finding supports the importance of including diverse, well-characterized patients to understand the different roles of DNA methylation and gene expression variability in the dysregulation of classical monocytes in diverse populations, which might help explaining the health disparities.
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Affiliation(s)
- Peter C Allen
- Department of Genetics, University of Alabama at Birmingham, Birmingham, AL, USA
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Sarah Smith
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Robert C Wilson
- Department of Pathology and Laboratory Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Jena R Wirth
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Nathan H Wilson
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - DeAnna Baker Frost
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Jonathan Flume
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Gary S Gilkeson
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Melissa A Cunningham
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA
| | - Carl D Langefeld
- Department of Biostatistics and Data Science, Wake Forest University School of Medicine, Winston-Salem, NC, USA
- Center for Precision Medicine, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Devin M Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Paula S Ramos
- Department of Medicine, Medical University of South Carolina, Charleston, SC, USA.
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA.
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14
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Lees-Murdock D, Ward M. Can Nutritional Epigenomics Explain Persistent Effects of Periconceptional Folic Acid in the Methylome? J Nutr 2023; 152:2636-2637. [PMID: 36288239 DOI: 10.1093/jn/nxac224] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 09/25/2022] [Accepted: 09/26/2022] [Indexed: 02/02/2023] Open
Affiliation(s)
- Diane Lees-Murdock
- Genomic Medicine, School of Biomedical Sciences, Ulster University, Coleraine, N Ireland, United Kingdom
| | - Mary Ward
- Nutrition Innovation Centre for Food and Health (NICHE), School of Biomedical Sciences, Ulster University, Coleraine, N Ireland, United Kingdom
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15
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Oliva M, Demanelis K, Lu Y, Chernoff M, Jasmine F, Ahsan H, Kibriya MG, Chen LS, Pierce BL. DNA methylation QTL mapping across diverse human tissues provides molecular links between genetic variation and complex traits. Nat Genet 2023; 55:112-122. [PMID: 36510025 PMCID: PMC10249665 DOI: 10.1038/s41588-022-01248-z] [Citation(s) in RCA: 53] [Impact Index Per Article: 53.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2021] [Accepted: 10/26/2022] [Indexed: 12/14/2022]
Abstract
Studies of DNA methylation (DNAm) in solid human tissues are relatively scarce; tissue-specific characterization of DNAm is needed to understand its role in gene regulation and its relevance to complex traits. We generated array-based DNAm profiles for 987 human samples from the Genotype-Tissue Expression (GTEx) project, representing 9 tissue types and 424 subjects. We characterized methylome and transcriptome correlations (eQTMs), genetic regulation in cis (mQTLs and eQTLs) across tissues and e/mQTLs links to complex traits. We identified mQTLs for 286,152 CpG sites, many of which (>5%) show tissue specificity, and mQTL colocalizations with 2,254 distinct GWAS hits across 83 traits. For 91% of these loci, a candidate gene link was identified by integration of functional maps, including eQTMs, and/or eQTL colocalization, but only 33% of loci involved an eQTL and mQTL present in the same tissue type. With this DNAm-focused integrative analysis, we contribute to the understanding of molecular regulatory mechanisms in human tissues and their impact on complex traits.
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Affiliation(s)
- Meritxell Oliva
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA.
| | - Kathryn Demanelis
- Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Yihao Lu
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Meytal Chernoff
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Farzana Jasmine
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Habibul Ahsan
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
- Comprehensive Cancer Center, University of Chicago, Chicago, IL, USA
- Department of Medicine, University of Chicago, Chicago, IL, USA
- Institute for Population and Precision Health, University of Chicago, Chicago, IL, USA
| | - Muhammad G Kibriya
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA
- Institute for Population and Precision Health, University of Chicago, Chicago, IL, USA
| | - Lin S Chen
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA.
| | - Brandon L Pierce
- Department of Public Health Sciences, University of Chicago, Chicago, IL, USA.
- Department of Human Genetics, University of Chicago, Chicago, IL, USA.
- Comprehensive Cancer Center, University of Chicago, Chicago, IL, USA.
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16
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Xu P, Dong S, Wu L, Bai Y, Bi X, Li Y, Shu C. Maternal and Placental DNA Methylation Changes Associated with the Pathogenesis of Gestational Diabetes Mellitus. Nutrients 2022; 15:nu15010070. [PMID: 36615730 PMCID: PMC9823627 DOI: 10.3390/nu15010070] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Revised: 12/11/2022] [Accepted: 12/15/2022] [Indexed: 12/28/2022] Open
Abstract
Gestational diabetes mellitus (GDM) is an important metabolic complication of pregnancy, which affects the future health of both the mother and the newborn. The pathogenesis of GDM is not completely clear, but what is clear is that with the development and growth of the placenta, GDM onset and blood glucose is difficult to control, while gestational diabetes patients' blood glucose drops and reaches normal after placenta delivery. This may be associated with placental secretion of insulin-like growth factor, adipokines, tumor necrosis factor-α, cytokines and insulin resistance. Therefore, endocrine secretion of placenta plays a key role in the pathogenesis of GDM. The influence of DNA methylation of these molecules and pathway-related genes on gene expression is also closely related to the pathogenesis of GDM. Here, this review attempts to clarify the pathogenesis of GDM and the related maternal and placental DNA methylation changes and how they affect metabolic pathways.
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Wang K, Dai R, Xia Y, Tian J, Jiao C, Mikhailova T, Zhang C, Chen C, Liu C. Spatiotemporal specificity of correlated DNA methylation and gene expression pairs across different human tissues and stages of brain development. Epigenetics 2022; 17:1110-1127. [PMID: 34652256 PMCID: PMC9543113 DOI: 10.1080/15592294.2021.1993607] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
DNA methylation (DNAm) that occurs on promoter regions is primarily considered to repress gene expression. Previous studies indicated that DNAm could also show positive correlations with gene expression. Both DNAm and gene expression profiles are known to be tissue- and development-specific. This study aims to investigate how DNAm and gene expression are coordinated across different human tissues and developmental stages, as well as the biological significance of such correlations. By analyzing 2,239 samples with both DNAm and gene expression data in the same human subjects obtained from six published datasets, we evaluated the correlations between gene and CpG pairs (GCPs) at cis-regions and compared significantly correlated GCPs (cGCPs) across different tissues and brains at different age groups. A total of 37,363 cGCPs was identified in the six datasets; approximately 38% of the cGCPs were positively correlated. The majority (>90%) of cGCPs was tissue- or development-specific. We also observed that the correlation direction can be opposite in different tissues and ages. Further analysis highlights the importance of cGCPs for their cellular functions and potential roles in complex traits and human diseases. For instance, the early developmental brain possessed a highly unique set of cGCPs that were associated with neurogenesis and psychiatric disorders. By assessing the epigenetic factors involved in cGCPs, we discovered novel regulatory mechanisms of positive cGCPs distinct from negative cGCPs, which were related to multiple factors, such as H3K27me3, CTCF, and JARD2. The catalogue of cGCPs compiled can be used to guide functional interpretation of genetic and epigenetic studies.
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Affiliation(s)
- Kangli Wang
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Rujia Dai
- Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, NY, USA
| | - Yan Xia
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China,Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, NY, USA
| | - Jianghua Tian
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Chuan Jiao
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China,Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, NY, USA
| | - Tatiana Mikhailova
- Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, NY, USA
| | - Chunling Zhang
- Department of Neuroscience and Physiology, State University of New York Upstate Medical University, Syracuse, Ny, USA
| | - Chao Chen
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China,National Clinical Research Center on Mental Disorders, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China,National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Chunyu Liu
- Center for Medical Genetics & Hunan Key Laboratory of Medical Genetics, School of Life Sciences, and Department of Psychiatry, The Second Xiangya Hospital, Central South University, Changsha, Hunan, China,Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, NY, USA,Department of Neuroscience and Physiology, State University of New York Upstate Medical University, Syracuse, Ny, USA,CONTACT Chunyu Liu Department of Psychiatry, State University of New York Upstate Medical University, Syracuse, NY13210, USA; Chao Chen Center for Medical Genetics, Central South University, Changsha, Hunan 410005, China
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18
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Epigenetic signatures relating to disease-associated genotypic burden in familial risk of bipolar disorder. Transl Psychiatry 2022; 12:310. [PMID: 35922419 PMCID: PMC9349272 DOI: 10.1038/s41398-022-02079-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Revised: 07/18/2022] [Accepted: 07/20/2022] [Indexed: 11/08/2022] Open
Abstract
Environmental factors contribute to risk of bipolar disorder (BD), but how environmental factors impact the development of psychopathology within the context of elevated genetic risk is unknown. We herein sought to identify epigenetic signatures operating in the context of polygenic risk for BD in young people at high familial risk (HR) of BD. Peripheral blood-derived DNA was assayed using Illumina PsychArray, and Methylation-450K or -EPIC BeadChips. Polygenic risk scores (PRS) were calculated using summary statistics from recent genome-wide association studies for BD, major depressive disorder (MDD) and cross-disorder (meta-analysis of eight psychiatric disorders). Unrelated HR participants of European ancestry (n = 103) were stratified based on their BD-PRS score within the HR-population distribution, and the top two quintiles (High-BD-PRS; n = 41) compared against the bottom two quintiles (Low-BD-PRS; n = 41). The High-BD-PRS stratum also had higher mean cross-disorder-PRS and MDD-PRS (ANCOVA p = 0.035 and p = 0.024, respectively). We evaluated DNA methylation differences between High-BD-PRS and Low-BD-PRS strata using linear models. One differentially methylated probe (DMP) (cg00933603; p = 3.54 × 10-7) in VARS2, a mitochondrial aminoacyl-tRNA synthetase, remained significantly hypomethylated after multiple-testing correction. Overall, BD-PRS appeared to broadly impact epigenetic processes, with 1,183 genes mapped to nominal DMPs (p < 0.05); these displayed convergence with genes previously associated with BD, schizophrenia, chronotype, and risk taking. We tested poly-methylomic epigenetic profiles derived from nominal DMPs in two independent samples (n = 54 and n = 82, respectively), and conducted an exploratory evaluation of the effects of family environment, indexing cohesion and flexibility. This study highlights an important interplay between heritable risk and epigenetic factors, which warrant further exploration.
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Manu DM, Mwinyi J, Schiöth HB. Challenges in Analyzing Functional Epigenetic Data in Perspective of Adolescent Psychiatric Health. Int J Mol Sci 2022; 23:ijms23105856. [PMID: 35628666 PMCID: PMC9147258 DOI: 10.3390/ijms23105856] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 05/11/2022] [Accepted: 05/18/2022] [Indexed: 12/10/2022] Open
Abstract
The formative period of adolescence plays a crucial role in the development of skills and abilities for adulthood. Adolescents who are affected by mental health conditions are at risk of suicide and social and academic impairments. Gene–environment complementary contributions to the molecular mechanisms involved in psychiatric disorders have emphasized the need to analyze epigenetic marks such as DNA methylation (DNAm) and non-coding RNAs. However, the large and diverse bioinformatic and statistical methods, referring to the confounders of the statistical models, application of multiple-testing adjustment methods, questions regarding the correlation of DNAm across tissues, and sex-dependent differences in results, have raised challenges regarding the interpretation of the results. Based on the example of generalized anxiety disorder (GAD) and depressive disorder (MDD), we shed light on the current knowledge and usage of methodological tools in analyzing epigenetics. Statistical robustness is an essential prerequisite for a better understanding and interpretation of epigenetic modifications and helps to find novel targets for personalized therapeutics in psychiatric diseases.
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20
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Flynn E, Lappalainen T. Functional Characterization of Genetic Variant Effects on Expression. Annu Rev Biomed Data Sci 2022; 5:119-139. [PMID: 35483347 DOI: 10.1146/annurev-biodatasci-122120-010010] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Thousands of common genetic variants in the human population have been associated with disease risk and phenotypic variation by genome-wide association studies (GWAS). However, the majority of GWAS variants fall into noncoding regions of the genome, complicating our understanding of their regulatory functions, and few molecular mechanisms of GWAS variant effects have been clearly elucidated. Here, we set out to review genetic variant effects, focusing on expression quantitative trait loci (eQTLs), including their utility in interpreting GWAS variant mechanisms. We discuss the interrelated challenges and opportunities for eQTL analysis, covering determining causal variants, elucidating molecular mechanisms of action, and understanding context variability. Addressing these questions can enable better functional characterization of disease-associated loci and provide insights into fundamental biological questions of the noncoding genetic regulatory code and its control of gene expression. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Elise Flynn
- New York Genome Center, New York, NY, USA; , .,Department of Systems Biology, Columbia University, New York, NY, USA
| | - Tuuli Lappalainen
- New York Genome Center, New York, NY, USA; , .,Department of Systems Biology, Columbia University, New York, NY, USA.,Science for Life Laboratory, Department of Gene Technology, KTH Royal Institute of Technology, Stockholm, Sweden
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21
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Lamka GF, Harder AM, Sundaram M, Schwartz TS, Christie MR, DeWoody JA, Willoughby JR. Epigenetics in Ecology, Evolution, and Conservation. Front Ecol Evol 2022. [DOI: 10.3389/fevo.2022.871791] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Epigenetic variation is often characterized by modifications to DNA that do not alter the underlying nucleotide sequence, but can influence behavior, morphology, and physiological phenotypes by affecting gene expression and protein synthesis. In this review, we consider how the emerging field of ecological epigenetics (eco-epi) aims to use epigenetic variation to explain ecologically relevant phenotypic variation and predict evolutionary trajectories that are important in conservation. Here, we focus on how epigenetic data have contributed to our understanding of wild populations, including plants, animals, and fungi. First, we identified published eco-epi literature and found that there was limited taxonomic and ecosystem coverage and that, by necessity of available technology, these studies have most often focused on the summarized epigenome rather than locus- or nucleotide-level epigenome characteristics. We also found that while many studies focused on adaptation and heritability of the epigenome, the field has thematically expanded into topics such as disease ecology and epigenome-based ageing of individuals. In the second part of our synthesis, we discuss key insights that have emerged from the epigenetic field broadly and use these to preview the path toward integration of epigenetics into ecology. Specifically, we suggest moving focus to nucleotide-level differences in the epigenome rather than whole-epigenome data and that we incorporate several facets of epigenome characterization (e.g., methylation, chromatin structure). Finally, we also suggest that incorporation of behavior and stress data will be critical to the process of fully integrating eco-epi data into ecology, conservation, and evolutionary biology.
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22
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Ruiz-Arenas C, Hernandez-Ferrer C, Vives-Usano M, Marí S, Quintela I, Mason D, Cadiou S, Casas M, Andrusaityte S, Gutzkow KB, Vafeiadi M, Wright J, Lepeule J, Grazuleviciene R, Chatzi L, Carracedo Á, Estivill X, Marti E, Escaramís G, Vrijheid M, González JR, Bustamante M. Identification of autosomal cis expression quantitative trait methylation (cis eQTMs) in children's blood. eLife 2022; 11:65310. [PMID: 35302492 PMCID: PMC8933004 DOI: 10.7554/elife.65310] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 02/11/2022] [Indexed: 12/12/2022] Open
Abstract
Background The identification of expression quantitative trait methylation (eQTMs), defined as associations between DNA methylation levels and gene expression, might help the biological interpretation of epigenome-wide association studies (EWAS). We aimed to identify autosomal cis eQTMs in children's blood, using data from 832 children of the Human Early Life Exposome (HELIX) project. Methods Blood DNA methylation and gene expression were measured with the Illumina 450K and the Affymetrix HTA v2 arrays, respectively. The relationship between methylation levels and expression of nearby genes (1 Mb window centered at the transcription start site, TSS) was assessed by fitting 13.6 M linear regressions adjusting for sex, age, cohort, and blood cell composition. Results We identified 39,749 blood autosomal cis eQTMs, representing 21,966 unique CpGs (eCpGs, 5.7% of total CpGs) and 8,886 unique transcript clusters (eGenes, 15.3% of total transcript clusters, equivalent to genes). In 87.9% of these cis eQTMs, the eCpG was located at <250 kb from eGene's TSS; and 58.8% of all eQTMs showed an inverse relationship between the methylation and expression levels. Only around half of the autosomal cis-eQTMs eGenes could be captured through annotation of the eCpG to the closest gene. eCpGs had less measurement error and were enriched for active blood regulatory regions and for CpGs reported to be associated with environmental exposures or phenotypic traits. In 40.4% of the eQTMs, the CpG and the eGene were both associated with at least one genetic variant. The overlap of autosomal cis eQTMs in children's blood with those described in adults was small (13.8%), and age-shared cis eQTMs tended to be proximal to the TSS and enriched for genetic variants. Conclusions This catalogue of autosomal cis eQTMs in children's blood can help the biological interpretation of EWAS findings and is publicly available at https://helixomics.isglobal.org/ and at Dryad (doi:10.5061/dryad.fxpnvx0t0). Funding The study has received funding from the European Community's Seventh Framework Programme (FP7/2007-206) under grant agreement no 308333 (HELIX project); the H2020-EU.3.1.2. - Preventing Disease Programme under grant agreement no 874583 (ATHLETE project); from the European Union's Horizon 2020 research and innovation programme under grant agreement no 733206 (LIFECYCLE project), and from the European Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL and Instituto de Salud Carlos III) under the grant agreement no AC18/00006 (NutriPROGRAM project). The genotyping was supported by the projects PI17/01225 and PI17/01935, funded by the Instituto de Salud Carlos III and co-funded by European Union (ERDF, "A way to make Europe") and the Centro Nacional de Genotipado-CEGEN (PRB2-ISCIII). BiB received core infrastructure funding from the Wellcome Trust (WT101597MA) and a joint grant from the UK Medical Research Council (MRC) and Economic and Social Science Research Council (ESRC) (MR/N024397/1). INMA data collections were supported by grants from the Instituto de Salud Carlos III, CIBERESP, and the Generalitat de Catalunya-CIRIT. KANC was funded by the grant of the Lithuanian Agency for Science Innovation and Technology (6-04-2014_31V-66). The Norwegian Mother, Father and Child Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research. The Rhea project was financially supported by European projects (EU FP6-2003-Food-3-NewGeneris, EU FP6. STREP Hiwate, EU FP7 ENV.2007.1.2.2.2. Project No 211250 Escape, EU FP7-2008-ENV-1.2.1.4 Envirogenomarkers, EU FP7-HEALTH-2009- single stage CHICOS, EU FP7 ENV.2008.1.2.1.6. Proposal No 226285 ENRIECO, EU- FP7- HEALTH-2012 Proposal No 308333 HELIX), and the Greek Ministry of Health (Program of Prevention of obesity and neurodevelopmental disorders in preschool children, in Heraklion district, Crete, Greece: 2011-2014; "Rhea Plus": Primary Prevention Program of Environmental Risk Factors for Reproductive Health, and Child Health: 2012-15). We acknowledge support from the Spanish Ministry of Science and Innovation through the "Centro de Excelencia Severo Ochoa 2019-2023" Program (CEX2018-000806-S), and support from the Generalitat de Catalunya through the CERCA Program. MV-U and CR-A were supported by a FI fellowship from the Catalan Government (FI-DGR 2015 and #016FI_B 00272). MC received funding from Instituto Carlos III (Ministry of Economy and Competitiveness) (CD12/00563 and MS16/00128).
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Affiliation(s)
- Carlos Ruiz-Arenas
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Barcelona, Spain.,Universitat Pompeu Fabra (UPF), Barcelona, Spain
| | - Carles Hernandez-Ferrer
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.,Centro Nacional de Análisis Genómico (CNAG-CRG), Center for Genomic Regulation, Barcelona Institute of Science and Technology (BIST), Barcelona, Spain.,ISGlobal, Barcelona, Spain
| | - Marta Vives-Usano
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.,ISGlobal, Barcelona, Spain.,Center for Genomic Regulation (CRG), Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Sergi Marí
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.,ISGlobal, Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Ines Quintela
- Medicine Genomics Group, University of Santiago de Compostela, Santiago de Compostela, Spain
| | - Dan Mason
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, United Kingdom
| | - Solène Cadiou
- University Grenoble Alpes, Inserm, CNRS, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, Grenoble, France
| | - Maribel Casas
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.,ISGlobal, Barcelona, Spain
| | - Sandra Andrusaityte
- Department of Environmental Science, Vytautas Magnus University, Kaunas, Lithuania
| | | | - Marina Vafeiadi
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.,ISGlobal, Barcelona, Spain.,Department of Social Medicine, University of Crete, Crete, Greece
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, United Kingdom
| | - Johanna Lepeule
- University Grenoble Alpes, Inserm, CNRS, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, Grenoble, France
| | | | - Leda Chatzi
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, Los Angeles, United States
| | - Ángel Carracedo
- Medicine Genomics Group, CIBERER, University of Santiago de Compostela, Santiago de Compostela, Spain.,Galician Foundation of Genomic Medicine, Santiago de Compostela, Spain
| | - Xavier Estivill
- Quantitative Genomics Medicine Laboratories (qGenomics), Esplugues del Llobrega, Barcelona, Spain
| | - Eulàlia Marti
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.,Departament de Biomedicina, Institut de Neurociències, Universitat de Barcelona, Barcelona, Spain
| | - Geòrgia Escaramís
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.,Departament de Biomedicina, Institut de Neurociències, Universitat de Barcelona, Barcelona, Spain
| | - Martine Vrijheid
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.,ISGlobal, Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Juan R González
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.,ISGlobal, Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Mariona Bustamante
- Universitat Pompeu Fabra (UPF), Barcelona, Spain.,ISGlobal, Barcelona, Spain.,CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
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23
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Yang Z, He Y, Wang Y, Huang L, Tang Y, He Y, Chen Y, Han Z. Genome-Wide Analysis for the Regulation of Gene Alternative Splicing by DNA Methylation Level in Glioma and its Prognostic Implications. Front Genet 2022; 13:799913. [PMID: 35309147 PMCID: PMC8931337 DOI: 10.3389/fgene.2022.799913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 01/20/2022] [Indexed: 11/13/2022] Open
Abstract
Glioma is a primary high malignant intracranial tumor with poorly understood molecular mechanisms. Previous studies found that both DNA methylation modification and gene alternative splicing (AS) play a key role in tumorigenesis of glioma, and there is an obvious regulatory relationship between them. However, to date, no comprehensive study has been performed to analyze the influence of DNA methylation level on gene AS in glioma on a genome-wide scale. Here, we performed this study by integrating DNA methylation, gene expression, AS, disease risk methylation at position, and clinical data from 537 low-grade glioma (LGG) and glioblastoma (GBM) individuals. We first conducted a differential analysis of AS events and DNA methylation positions between LGG and GBM subjects, respectively. Then, we evaluated the influence of differential methylation positions on differential AS events. Further, Fisher’s exact test was used to verify our findings and identify potential key genes in glioma. Finally, we performed a series of analyses to investigate influence of these genes on the clinical prognosis of glioma. In total, we identified 130 glioma-related genes whose AS significantly affected by DNA methylation level. Eleven of them play an important role in glioma prognosis. In short, these results will help to better understand the pathogenesis of glioma.
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Affiliation(s)
- Zeyuan Yang
- Department of Bioinformatics, School of Basic Medicine, Chongqing Medical University, Chongqing, China
| | - Yijie He
- Department of Bioinformatics, School of Basic Medicine, Chongqing Medical University, Chongqing, China
| | - Yongheng Wang
- Department of Bioinformatics, School of Basic Medicine, Chongqing Medical University, Chongqing, China
- International Research Laboratory of Reproduction and Development, Chongqing Medical University, Chongqing, China
| | - Lin Huang
- Department of Bioinformatics, School of Basic Medicine, Chongqing Medical University, Chongqing, China
| | - Yaqin Tang
- Department of Bioinformatics, School of Basic Medicine, Chongqing Medical University, Chongqing, China
| | - Yue He
- Group of Mathematics Education Teaching and Research, Chongqing Fudan Secondary School, Chongqing, China
| | - Yihan Chen
- Department of Bioinformatics, School of Basic Medicine, Chongqing Medical University, Chongqing, China
| | - Zhijie Han
- Department of Bioinformatics, School of Basic Medicine, Chongqing Medical University, Chongqing, China
- *Correspondence: Zhijie Han,
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Kumar S, Seem K, Kumar S, Vinod KK, Chinnusamy V, Mohapatra T. Pup1 QTL Regulates Gene Expression Through Epigenetic Modification of DNA Under Phosphate Starvation Stress in Rice. FRONTIERS IN PLANT SCIENCE 2022; 13:871890. [PMID: 35712593 PMCID: PMC9195100 DOI: 10.3389/fpls.2022.871890] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Accepted: 04/29/2022] [Indexed: 05/03/2023]
Abstract
Cytosine methylation, epigenetic DNA modification, is well known to regulate gene expression. Among the epigenetic modifications, 5-methylcytosine (5-mC) has been one of the extensively studied epigenetic changes responsible for regulating gene expression in animals and plants. Though a dramatic change in 5-mC content is observed at the genome level, the variation in gene expression is generally less than that it is expected. Only less is understood about the significance of 5-mC in gene regulation under P-starvation stress in plants. Using whole-genome bisulfite sequencing of a pair of rice [Pusa-44 and its near-isogenic line (NIL)-23 harboring Pup1 QTL] genotypes, we could decipher the role of Pup1 on DNA (de)methylation-mediated regulation of gene expression under P-starvation stress. We observed 13-15% of total cytosines to be methylated in the rice genome, which increased significantly under the stress. The number of differentially methylated regions (DMRs) for hypomethylation (6,068) was higher than those (5,279) for hypermethylated DMRs under the stress, particularly in root of NIL-23. Hypomethylation in CHH context caused upregulated expression of 489 genes in shoot and 382 genes in root of NIL-23 under the stress, wherein 387 genes in shoot and 240 genes in root were upregulated exclusively in NIL-23. Many of the genes for DNA methylation, a few for DNA demethylation, and RNA-directed DNA methylation were upregulated in root of NIL-23 under the stress. Methylation or demethylation of DNA in genic regions differentially affected gene expression. Correlation analysis for the distribution of DMRs and gene expression indicated the regulation of gene mainly through (de)methylation of promoter. Many of the P-responsive genes were hypomethylated or upregulated in roots of NIL-23 under the stress. Hypermethylation of gene body in CG, CHG, and CHH contexts caused up- or downregulated expression of transcription factors (TFs), P transporters, phosphoesterases, retrotransposon proteins, and other proteins. Our integrated transcriptome and methylome analyses revealed an important role of the Pup1 QTL in epigenetic regulation of the genes for transporters, TFs, phosphatases, carbohydrate metabolism, hormone-signaling, and chromatin architecture or epigenetic modifications in P-starvation tolerance. This provides insights into the molecular function of Pup1 in modulating gene expression through DNA (de)methylation, which might be useful in improving P-use efficiency or productivity of rice in P-deficient soil.
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Affiliation(s)
- Suresh Kumar
- Division of Biochemistry, ICAR-Indian Agricultural Research Institute, New Delhi, India
- *Correspondence: Suresh Kumar ; ; orcid.org/0000-0002-7127-3079
| | - Karishma Seem
- Division of Biochemistry, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | | | - K. K. Vinod
- Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi, India
| | - Viswanathan Chinnusamy
- Division of Plant Physiology, ICAR-Indian Agricultural Research Institute, New Delhi, India
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25
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Campagna MP, Xavier A, Lechner-Scott J, Maltby V, Scott RJ, Butzkueven H, Jokubaitis VG, Lea RA. Epigenome-wide association studies: current knowledge, strategies and recommendations. Clin Epigenetics 2021; 13:214. [PMID: 34863305 PMCID: PMC8645110 DOI: 10.1186/s13148-021-01200-8] [Citation(s) in RCA: 56] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 11/19/2021] [Indexed: 02/06/2023] Open
Abstract
The aetiology and pathophysiology of complex diseases are driven by the interaction between genetic and environmental factors. The variability in risk and outcomes in these diseases are incompletely explained by genetics or environmental risk factors individually. Therefore, researchers are now exploring the epigenome, a biological interface at which genetics and the environment can interact. There is a growing body of evidence supporting the role of epigenetic mechanisms in complex disease pathophysiology. Epigenome-wide association studies (EWASes) investigate the association between a phenotype and epigenetic variants, most commonly DNA methylation. The decreasing cost of measuring epigenome-wide methylation and the increasing accessibility of bioinformatic pipelines have contributed to the rise in EWASes published in recent years. Here, we review the current literature on these EWASes and provide further recommendations and strategies for successfully conducting them. We have constrained our review to studies using methylation data as this is the most studied epigenetic mechanism; microarray-based data as whole-genome bisulphite sequencing remains prohibitively expensive for most laboratories; and blood-based studies due to the non-invasiveness of peripheral blood collection and availability of archived DNA, as well as the accessibility of publicly available blood-cell-based methylation data. Further, we address multiple novel areas of EWAS analysis that have not been covered in previous reviews: (1) longitudinal study designs, (2) the chip analysis methylation pipeline (ChAMP), (3) differentially methylated region (DMR) identification paradigms, (4) methylation quantitative trait loci (methQTL) analysis, (5) methylation age analysis and (6) identifying cell-specific differential methylation from mixed cell data using statistical deconvolution.
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Affiliation(s)
- Maria Pia Campagna
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
| | - Alexandre Xavier
- Centre for Information Based Medicine, Hunter Medical Research Institute, Newcastle, Australia
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia
| | - Jeannette Lechner-Scott
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia
- Department of Neurology, Division of Medicine, John Hunter Hospital, Newcastle, Australia
| | - Vicky Maltby
- Centre for Information Based Medicine, Hunter Medical Research Institute, Newcastle, Australia
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia
| | - Rodney J Scott
- Centre for Information Based Medicine, Hunter Medical Research Institute, Newcastle, Australia
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia
- Division of Molecular Medicine, New South Wales Health Pathology North, Newcastle, Australia
| | - Helmut Butzkueven
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
- Department of Neurology, Alfred Health, Melbourne, Australia
| | - Vilija G Jokubaitis
- Department of Neuroscience, Central Clinical School, Monash University, Melbourne, Australia
- Department of Neurology, Alfred Health, Melbourne, Australia
| | - Rodney A Lea
- School of Biomedical Sciences and Pharmacy, University of Newcastle, Newcastle, Australia.
- Centre for Genomics and Personalised Health, School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia.
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26
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Claussnitzer M, Susztak K. Gaining insight into metabolic diseases from human genetic discoveries. Trends Genet 2021; 37:1081-1094. [PMID: 34315631 PMCID: PMC8578350 DOI: 10.1016/j.tig.2021.07.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Revised: 06/29/2021] [Accepted: 07/05/2021] [Indexed: 12/30/2022]
Abstract
Human large-scale genetic association studies have identified sequence variations at thousands of genetic risk loci that are more common in patients with diverse metabolic disease compared with healthy controls. While these genetic associations have been replicated in multiple large cohorts and sometimes can explain up to 50% of heritability, the molecular and cellular mechanisms affected by common genetic variation associated with metabolic disease remains mostly unknown. A variety of new genome-wide data types, in conjunction with novel biostatistical and computational analytical methodologies and foundational experimental technologies, are paving the way for a principled approach to systematic variant-to-function (V2F) studies for metabolic diseases, turning associated regions into causal variants, cell types and states of action, effector genes, and cellular and physiological mechanisms. Identification of new target genes and cellular programs for metabolic risk loci will improve mechanistic understanding of disease biology and identification of novel therapeutic strategies.
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Affiliation(s)
- Melina Claussnitzer
- Beth Israel Deaconess Medical Center, The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Katalin Susztak
- Department of Medicine and Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA.
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27
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Casares-Marfil D, Kerick M, Andrés-León E, Bosch-Nicolau P, Molina I, Martin J, Acosta-Herrera M. GWAS loci associated with Chagas cardiomyopathy influences DNA methylation levels. PLoS Negl Trop Dis 2021; 15:e0009874. [PMID: 34714828 PMCID: PMC8580254 DOI: 10.1371/journal.pntd.0009874] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 11/10/2021] [Accepted: 10/05/2021] [Indexed: 02/07/2023] Open
Abstract
A recent genome-wide association study (GWAS) identified a locus in chromosome 11 associated with the chronic cardiac form of Chagas disease. Here we aimed to elucidate the potential functional mechanism underlying this genetic association by analyzing the correlation among single nucleotide polymorphisms (SNPs) and DNA methylation (DNAm) levels as cis methylation quantitative trait loci (cis-mQTL) within this region. A total of 2,611 SNPs were tested against 2,647 DNAm sites, in a subset of 37 chronic Chagas cardiomyopathy patients and 20 asymptomatic individuals from the GWAS. We identified 6,958 significant cis-mQTLs (False Discovery Rate [FDR]<0.05) at 1 Mb each side of the GWAS leading variant, where six of them potentially modulate the expression of the SAC3D1 gene, the reported gene in the previous GWAS. In addition, a total of 268 cis-mQTLs showed differential methylation between chronic Chagas cardiomyopathy patients and asymptomatic individuals. The most significant cis-mQTLs mapped in the gene bodies of POLA2 (FDR = 1.04x10-11), PLAAT3 (FDR = 7.22x10-03), and CCDC88B (FDR = 1.89x10-02) that have been associated with cardiovascular and hematological traits in previous studies. One of the most relevant interactions correlated with hypermethylation of CCDC88B. This gene is involved in the inflammatory response, and its methylation and expression levels have been previously reported in Chagas cardiomyopathy. Our findings support the functional relevance of the previously associated genomic region, highlighting the regulation of novel genes that could play a role in the chronic cardiac form of the disease. Genome-wide association studies (GWAS) have provided extensive information regarding the genetic component of complex traits, including parasitic diseases such as Chagas disease. However, these associations mapped in regulatory regions of the genome and assigning them a functional consequence have been cumbersome. In this study we aimed to evaluate the functional mechanism underlying the previously reported genomic association with chronic Chagas cardiomyopathy, by assessing the correlation between methylation changes and the underlying genetic variations within the region. These methylation quantitative trait loci (mQTLs) may be involved in gene expression regulation. We identified mQTLs in three genes that have been associated with cardiovascular diseases in previous studies. Interestingly, one of these genes was previously identified as differentially methylated and expressed in heart biopsies of chronic Chagas cardiomyopathy patients. Our results suggest novel genes that could play a role in the chronic Chagas cardiomyopathy, evidencing the functional relevance of the previously associated loci.
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Affiliation(s)
| | - Martin Kerick
- Institute of Parasitology and Biomedicine López-Neyra, CSIC, Granada, Spain
| | | | - Pau Bosch-Nicolau
- Unidad de Medicina Tropical y Salud Internacional Hospital Universitari Vall d’Hebron, PROSICS, Barcelona, Spain
| | - Israel Molina
- Unidad de Medicina Tropical y Salud Internacional Hospital Universitari Vall d’Hebron, PROSICS, Barcelona, Spain
| | | | - Javier Martin
- Institute of Parasitology and Biomedicine López-Neyra, CSIC, Granada, Spain
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28
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Farrow E, Chiocchetti AG, Rogers JC, Pauli R, Raschle NM, Gonzalez-Madruga K, Smaragdi A, Martinelli A, Kohls G, Stadler C, Konrad K, Fairchild G, Freitag CM, Chechlacz M, De Brito SA. SLC25A24 gene methylation and gray matter volume in females with and without conduct disorder: an exploratory epigenetic neuroimaging study. Transl Psychiatry 2021; 11:492. [PMID: 34561420 PMCID: PMC8463588 DOI: 10.1038/s41398-021-01609-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 06/29/2021] [Accepted: 09/02/2021] [Indexed: 11/09/2022] Open
Abstract
Conduct disorder (CD), a psychiatric disorder characterized by a repetitive pattern of antisocial behaviors, results from a complex interplay between genetic and environmental factors. The clinical presentation of CD varies both according to the individual's sex and level of callous-unemotional (CU) traits, but it remains unclear how genetic and environmental factors interact at the molecular level to produce these differences. Emerging evidence in males implicates methylation of genes associated with socio-affective processes. Here, we combined an epigenome-wide association study with structural neuroimaging in 51 females with CD and 59 typically developing (TD) females to examine DNA methylation in relation to CD, CU traits, and gray matter volume (GMV). We demonstrate an inverse pattern of correlation between CU traits and methylation of a chromosome 1 region in CD females (positive) as compared to TD females (negative). The identified region spans exon 1 of the SLC25A24 gene, central to energy metabolism due to its role in mitochondrial function. Increased SLC25A24 methylation was also related to lower GMV in multiple brain regions in the overall cohort. These included the superior frontal gyrus, prefrontal cortex, and supramarginal gyrus, secondary visual cortex and ventral posterior cingulate cortex, which are regions that have previously been implicated in CD and CU traits. While our findings are preliminary and need to be replicated in larger samples, they provide novel evidence that CU traits in females are associated with methylation levels in a fundamentally different way in CD and TD, which in turn may relate to observable variations in GMV across the brain.
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Affiliation(s)
- Elizabeth Farrow
- School of Psychology and Centre for Human Brain Health, University of Birmingham, Birmingham, UK.
| | - Andreas G. Chiocchetti
- grid.7839.50000 0004 1936 9721Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Jack C. Rogers
- grid.6572.60000 0004 1936 7486School of Psychology and Institute for Mental Health, University of Birmingham, Birmingham, UK
| | - Ruth Pauli
- grid.6572.60000 0004 1936 7486School of Psychology and Centre for Human Brain Health, University of Birmingham, Birmingham, UK
| | - Nora M. Raschle
- grid.7400.30000 0004 1937 0650Jacobs Center for Productive Youth Development, University of Zurich, Zurich, Switzerland
| | | | | | - Anne Martinelli
- grid.7839.50000 0004 1936 9721Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Gregor Kohls
- grid.1957.a0000 0001 0728 696XRWTH Aachen University, Aachen, Germany
| | | | - Kerstin Konrad
- grid.1957.a0000 0001 0728 696XRWTH Aachen University, Aachen, Germany
| | - Graeme Fairchild
- grid.7340.00000 0001 2162 1699Department of Psychology, University of Bath, Bath, UK
| | - Christine M. Freitag
- grid.7839.50000 0004 1936 9721Department of Child and Adolescent Psychiatry, Psychosomatics, and Psychotherapy, University Hospital Frankfurt, Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Magdalena Chechlacz
- grid.6572.60000 0004 1936 7486School of Psychology and Centre for Human Brain Health, University of Birmingham, Birmingham, UK
| | - Stephane A. De Brito
- grid.6572.60000 0004 1936 7486School of Psychology and Centre for Human Brain Health, University of Birmingham, Birmingham, UK
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29
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Ding P, Ouyang W, Luo J, Kwoh CK. Heterogeneous information network and its application to human health and disease. Brief Bioinform 2021; 21:1327-1346. [PMID: 31566212 DOI: 10.1093/bib/bbz091] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 06/29/2019] [Accepted: 06/30/2019] [Indexed: 12/11/2022] Open
Abstract
The molecular components with the functional interdependencies in human cell form complicated biological network. Diseases are mostly caused by the perturbations of the composite of the interaction multi-biomolecules, rather than an abnormality of a single biomolecule. Furthermore, new biological functions and processes could be revealed by discovering novel biological entity relationships. Hence, more and more biologists focus on studying the complex biological system instead of the individual biological components. The emergence of heterogeneous information network (HIN) offers a promising way to systematically explore complicated and heterogeneous relationships between various molecules for apparently distinct phenotypes. In this review, we first present the basic definition of HIN and the biological system considered as a complex HIN. Then, we discuss the topological properties of HIN and how these can be applied to detect network motif and functional module. Afterwards, methodologies of discovering relationships between disease and biomolecule are presented. Useful insights on how HIN aids in drug development and explores human interactome are provided. Finally, we analyze the challenges and opportunities for uncovering combinatorial patterns among pharmacogenomics and cell-type detection based on single-cell genomic data.
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Affiliation(s)
- Pingjian Ding
- School of Computer Science, University of South China, Hengyang, China
| | - Wenjue Ouyang
- College of Computer Science and Electronic Engineering, Hunan University, Changsha, China
| | - Jiawei Luo
- College of Computer Science and Electronic Engineering, Hunan University, Changsha, China
| | - Chee-Keong Kwoh
- School of Computer Science and Engineering, Nanyang Technological University, Singapore, Singapore
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30
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Scherer M, Gasparoni G, Rahmouni S, Shashkova T, Arnoux M, Louis E, Nostaeva A, Avalos D, Dermitzakis ET, Aulchenko YS, Lengauer T, Lyons PA, Georges M, Walter J. Identification of tissue-specific and common methylation quantitative trait loci in healthy individuals using MAGAR. Epigenetics Chromatin 2021; 14:44. [PMID: 34530905 PMCID: PMC8444396 DOI: 10.1186/s13072-021-00415-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Accepted: 08/02/2021] [Indexed: 12/18/2022] Open
Abstract
Background Understanding the influence of genetic variants on DNA methylation is fundamental for the interpretation of epigenomic data in the context of disease. There is a need for systematic approaches not only for determining methylation quantitative trait loci (methQTL), but also for discriminating general from cell type-specific effects. Results Here, we present a two-step computational framework MAGAR (https://bioconductor.org/packages/MAGAR), which fully supports the identification of methQTLs from matched genotyping and DNA methylation data, and additionally allows for illuminating cell type-specific methQTL effects. In a pilot analysis, we apply MAGAR on data in four tissues (ileum, rectum, T cells, B cells) from healthy individuals and demonstrate the discrimination of common from cell type-specific methQTLs. We experimentally validate both types of methQTLs in an independent data set comprising additional cell types and tissues. Finally, we validate selected methQTLs located in the PON1, ZNF155, and NRG2 genes by ultra-deep local sequencing. In line with previous reports, we find cell type-specific methQTLs to be preferentially located in enhancer elements. Conclusions Our analysis demonstrates that a systematic analysis of methQTLs provides important new insights on the influences of genetic variants to cell type-specific epigenomic variation. Supplementary Information The online version contains supplementary material available at 10.1186/s13072-021-00415-6.
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Affiliation(s)
- Michael Scherer
- Department of Genetics/Epigenetics, Saarland University, Saarbrücken, Germany.,Computational Biology, Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbrücken, Germany.,Graduate School of Computer Science, Saarland Informatics Campus, Saarbrücken, Germany.,Department of Bioinformatics and Genomics, Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain
| | - Gilles Gasparoni
- Department of Genetics/Epigenetics, Saarland University, Saarbrücken, Germany
| | - Souad Rahmouni
- Unit of Animal Genomics, GIGA-Institute & Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Tatiana Shashkova
- Kurchatov Genomics Center of the Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia.,Research and Training Center on Bioinformatics, A.A. Kharkevich Institute for Information Transmission Problems, Moscow, Russia
| | - Marion Arnoux
- Department of Genetics/Epigenetics, Saarland University, Saarbrücken, Germany
| | - Edouard Louis
- Department of Gastroenterology, Liège University Hospital, CHU Liège, Liège, Belgium
| | | | - Diana Avalos
- Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland.,Swiss Institute of Bioinformatics (SIB), University of Geneva, Geneva, Switzerland.,Institute of Genetics and Genomics in Geneva, University of Geneva, Geneva, Switzerland
| | - Emmanouil T Dermitzakis
- Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland.,Swiss Institute of Bioinformatics (SIB), University of Geneva, Geneva, Switzerland.,Institute of Genetics and Genomics in Geneva, University of Geneva, Geneva, Switzerland
| | - Yurii S Aulchenko
- Kurchatov Genomics Center of the Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia.,Novosibirsk State University, Novosibirsk, Russia.,Moscow Institute of Physics and Technology (State University), Moscow, Russia.,PolyKnomics BV, 's-Hertogenbosch, The Netherlands
| | - Thomas Lengauer
- Computational Biology, Max Planck Institute for Informatics, Saarland Informatics Campus, Saarbrücken, Germany
| | - Paul A Lyons
- Department of Medicine, University of Cambridge School of Clinical Medicine, University of Cambridge, Cambridge Biomedical Campus, Cambridge, CB2 0QQ, UK.,Cambridge Institute for Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, CB2 0AW, UK
| | - Michel Georges
- Unit of Animal Genomics, GIGA-Institute & Faculty of Veterinary Medicine, University of Liège, Liège, Belgium
| | - Jörn Walter
- Department of Genetics/Epigenetics, Saarland University, Saarbrücken, Germany.
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Genome-wide sequencing-based identification of methylation quantitative trait loci and their role in schizophrenia risk. Nat Commun 2021; 12:5251. [PMID: 34475392 PMCID: PMC8413445 DOI: 10.1038/s41467-021-25517-3] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Accepted: 08/12/2021] [Indexed: 11/28/2022] Open
Abstract
DNA methylation (DNAm) is an epigenetic regulator of gene expression and a hallmark of gene-environment interaction. Using whole-genome bisulfite sequencing, we have surveyed DNAm in 344 samples of human postmortem brain tissue from neurotypical subjects and individuals with schizophrenia. We identify genetic influence on local methylation levels throughout the genome, both at CpG sites and CpH sites, with 86% of SNPs and 55% of CpGs being part of methylation quantitative trait loci (meQTLs). These associations can further be clustered into regions that are differentially methylated by a given SNP, highlighting the genes and regions with which these loci are epigenetically associated. These findings can be used to better characterize schizophrenia GWAS-identified variants as epigenetic risk variants. Regions differentially methylated by schizophrenia risk-SNPs explain much of the heritability associated with risk loci, despite covering only a fraction of the genomic space. We provide a comprehensive, single base resolution view of association between genetic variation and genomic methylation, and implicate schizophrenia GWAS-associated variants as influencing the epigenetic plasticity of the brain. The authors provide a comprehensive, single base resolution view of association between genetic variation and DNA methylation in human brain. They also show that heritability attributed to schizophrenia GWAS-associated variants reflects the epigenetic plasticity of the brain.
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32
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Valencia-Ortega J, Saucedo R, Sánchez-Rodríguez MA, Cruz-Durán JG, Martínez EGR. Epigenetic Alterations Related to Gestational Diabetes Mellitus. Int J Mol Sci 2021; 22:ijms22179462. [PMID: 34502370 PMCID: PMC8430976 DOI: 10.3390/ijms22179462] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 08/27/2021] [Accepted: 08/28/2021] [Indexed: 02/06/2023] Open
Abstract
Gestational diabetes mellitus (GDM) is the most common metabolic complication in pregnancy, which affects the future health of both the mother and the newborn. Its pathophysiology involves nutritional, hormonal, immunological, genetic and epigenetic factors. Among the latter, it has been observed that alterations in DNA (deoxyribonucleic acid) methylation patterns and in the levels of certain micro RNAs, whether in placenta or adipose tissue, are related to well-known characteristics of the disease, such as hyperglycemia, insulin resistance, inflammation and excessive placental growth. Furthermore, epigenetic alterations of gestational diabetes mellitus are observable in maternal blood, although their pathophysiological roles are completely unknown. Despite this, it has not been possible to determine the causes of the epigenetic characteristics of GDM, highlighting the need for integral and longitudinal studies. Based on this, this article summarizes the most relevant and recent studies on epigenetic alterations in placenta, adipose tissue and maternal blood associated with GDM in order to provide the reader with a general overview of the subject and indicate future research topics.
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Affiliation(s)
- Jorge Valencia-Ortega
- Unidad de Investigación Médica en Enfermedades Endocrinas, UMAE Hospital de Especialidades, Instituto Mexicano del Seguro Social, Mexico City 06600, Mexico;
| | - Renata Saucedo
- Unidad de Investigación Médica en Enfermedades Endocrinas, UMAE Hospital de Especialidades, Instituto Mexicano del Seguro Social, Mexico City 06600, Mexico;
- Correspondence: ; Tel.: +55-55887521
| | - Martha A. Sánchez-Rodríguez
- Unidad de Investigación en Gerontología, Facultad de Estudios Superiores Zaragoza, Universidad Autónoma de México, Mexico City 04510, Mexico;
| | - José G. Cruz-Durán
- UMAE Hospital de Gineco-Obstetricia No. 3, Instituto Mexicano del Seguro Social, Mexico City 06600, Mexico;
| | - Edgar G. Ramos Martínez
- Universidad Autónoma Benito Juárez de Oaxaca and Instituto de Cómputo Aplicado en Ciencias, Oaxaca 68120, Mexico;
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33
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Bhattacharya A, Li Y, Love MI. MOSTWAS: Multi-Omic Strategies for Transcriptome-Wide Association Studies. PLoS Genet 2021; 17:e1009398. [PMID: 33684137 PMCID: PMC7971899 DOI: 10.1371/journal.pgen.1009398] [Citation(s) in RCA: 37] [Impact Index Per Article: 12.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Revised: 03/18/2021] [Accepted: 02/04/2021] [Indexed: 02/06/2023] Open
Abstract
Traditional predictive models for transcriptome-wide association studies (TWAS) consider only single nucleotide polymorphisms (SNPs) local to genes of interest and perform parameter shrinkage with a regularization process. These approaches ignore the effect of distal-SNPs or other molecular effects underlying the SNP-gene association. Here, we outline multi-omics strategies for transcriptome imputation from germline genetics to allow more powerful testing of gene-trait associations by prioritizing distal-SNPs to the gene of interest. In one extension, we identify mediating biomarkers (CpG sites, microRNAs, and transcription factors) highly associated with gene expression and train predictive models for these mediators using their local SNPs. Imputed values for mediators are then incorporated into the final predictive model of gene expression, along with local SNPs. In the second extension, we assess distal-eQTLs (SNPs associated with genes not in a local window around it) for their mediation effect through mediating biomarkers local to these distal-eSNPs. Distal-eSNPs with large indirect mediation effects are then included in the transcriptomic prediction model with the local SNPs around the gene of interest. Using simulations and real data from ROS/MAP brain tissue and TCGA breast tumors, we show considerable gains of percent variance explained (1-2% additive increase) of gene expression and TWAS power to detect gene-trait associations. This integrative approach to transcriptome-wide imputation and association studies aids in identifying the complex interactions underlying genetic regulation within a tissue and important risk genes for various traits and disorders.
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Affiliation(s)
- Arjun Bhattacharya
- Department of Pathology and Laboratory Medicine, University of California-Los Angeles, Los Angeles, California, United States of America
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Michael I. Love
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
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34
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Wu C, Bradley J, Li Y, Wu L, Deng HW. A gene-level methylome-wide association analysis identifies novel Alzheimer's disease genes. Bioinformatics 2021; 37:btab045. [PMID: 33523132 PMCID: PMC8337007 DOI: 10.1093/bioinformatics/btab045] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Revised: 12/31/2020] [Accepted: 01/20/2021] [Indexed: 12/12/2022] Open
Abstract
MOTIVATION Transcriptome-wide association studies (TWAS) have successfully facilitated the discovery of novel genetic risk loci for many complex traits, including late-onset Alzheimer's disease (AD). However, most existing TWAS methods rely only on gene expression and ignore epigenetic modification (i.e., DNA methylation) and functional regulatory information (i.e., enhancer-promoter interactions), both of which contribute significantly to the genetic basis of AD. RESULTS We develop a novel gene-level association testing method that integrates genetically regulated DNA methylation and enhancer-target gene pairs with genome-wide association study (GWAS) summary results. Through simulations, we show that our approach, referred to as the CMO (cross methylome omnibus) test, yielded well controlled type I error rates and achieved much higher statistical power than competing methods under a wide range of scenarios. Furthermore, compared with TWAS, CMO identified an average of 124% more associations when analyzing several brain imaging-related GWAS results. By analyzing to date the largest AD GWAS of 71,880 cases and 383,378 controls, CMO identified six novel loci for AD, which have been ignored by competing methods. AVAILABILITY Software: https://github.com/ChongWuLab/CMO. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Chong Wu
- Department of Statistics, Florida State University, Tallahassee, FL 32306, USA
| | - Jonathan Bradley
- Department of Statistics, Florida State University, Tallahassee, FL 32306, USA
| | - Yanming Li
- Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, KS 66160, USA
| | - Lang Wu
- Population Sciences in the Pacific Program, University of Hawaii Cancer Center, Honolulu, HI 96813, USA
| | - Hong-Wen Deng
- Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University School of Medicine, New Orleans, LA 70112, USA
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35
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Baker Frost D, da Silveira W, Hazard ES, Atanelishvili I, Wilson RC, Flume J, Day KL, Oates JC, Bogatkevich GS, Feghali-Bostwick C, Hardiman G, Ramos PS. Differential DNA Methylation Landscape in Skin Fibroblasts from African Americans with Systemic Sclerosis. Genes (Basel) 2021; 12:129. [PMID: 33498390 PMCID: PMC7909410 DOI: 10.3390/genes12020129] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 01/15/2021] [Accepted: 01/18/2021] [Indexed: 01/20/2023] Open
Abstract
The etiology and reasons underlying the ethnic disparities in systemic sclerosis (SSc) remain unknown. African Americans are disproportionally affected by SSc and yet are underrepresented in research. The aim of this study was to comprehensively investigate the association of DNA methylation levels with SSc in dermal fibroblasts from patients of African ancestry. Reduced representation bisulfite sequencing (RRBS) was performed on primary dermal fibroblasts from 15 SSc patients and 15 controls of African ancestry, and over 3.8 million CpG sites were tested for differential methylation patterns between cases and controls. The dermal fibroblasts from African American patients exhibited widespread reduced DNA methylation. Differentially methylated CpG sites were most enriched in introns and intergenic regions while depleted in 5' UTR, promoters, and CpG islands. Seventeen genes and eleven promoters showed significant differential methylation, mostly in non-coding RNA genes and pseudogenes. Gene set enrichment analysis (GSEA) and gene ontology (GO) analyses revealed an enrichment of pathways related to interferon signaling and mesenchymal differentiation. The hypomethylation of DLX5 and TMEM140 was accompanied by these genes' overexpression in patients but underexpression for lncRNA MGC12916. These data show that differential methylation occurs in dermal fibroblasts from African American patients with SSc and identifies novel coding and non-coding genes.
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Affiliation(s)
- DeAnna Baker Frost
- Department of Medicine, Division of Rheumatology and Immunology, Medical University of South Carolina, Charleston, SC 29425, USA; (D.B.F.); (I.A.); (J.F.); (J.C.O.); (G.S.B.); (C.F.-B.)
| | - Willian da Silveira
- Institute for Global Food Security, School of Biological Sciences, Queens University Belfast, Belfast BT9 5DL, UK; (W.d.S.); (G.H.)
| | - E. Starr Hazard
- Computational Biology Resource Center, Medical University of South Carolina, Charleston, SC 29425, USA;
| | - Ilia Atanelishvili
- Department of Medicine, Division of Rheumatology and Immunology, Medical University of South Carolina, Charleston, SC 29425, USA; (D.B.F.); (I.A.); (J.F.); (J.C.O.); (G.S.B.); (C.F.-B.)
| | - Robert C. Wilson
- Department of Pathology and Laboratory Medicine, Medical University of South Carolina, Charleston, SC 29425, USA;
| | - Jonathan Flume
- Department of Medicine, Division of Rheumatology and Immunology, Medical University of South Carolina, Charleston, SC 29425, USA; (D.B.F.); (I.A.); (J.F.); (J.C.O.); (G.S.B.); (C.F.-B.)
| | | | - James C. Oates
- Department of Medicine, Division of Rheumatology and Immunology, Medical University of South Carolina, Charleston, SC 29425, USA; (D.B.F.); (I.A.); (J.F.); (J.C.O.); (G.S.B.); (C.F.-B.)
- Rheumatology Section, Ralph H. Johnson VA Medical Center, Charleston, SC 29425, USA
| | - Galina S. Bogatkevich
- Department of Medicine, Division of Rheumatology and Immunology, Medical University of South Carolina, Charleston, SC 29425, USA; (D.B.F.); (I.A.); (J.F.); (J.C.O.); (G.S.B.); (C.F.-B.)
| | - Carol Feghali-Bostwick
- Department of Medicine, Division of Rheumatology and Immunology, Medical University of South Carolina, Charleston, SC 29425, USA; (D.B.F.); (I.A.); (J.F.); (J.C.O.); (G.S.B.); (C.F.-B.)
| | - Gary Hardiman
- Institute for Global Food Security, School of Biological Sciences, Queens University Belfast, Belfast BT9 5DL, UK; (W.d.S.); (G.H.)
| | - Paula S. Ramos
- Department of Medicine, Division of Rheumatology and Immunology, Medical University of South Carolina, Charleston, SC 29425, USA; (D.B.F.); (I.A.); (J.F.); (J.C.O.); (G.S.B.); (C.F.-B.)
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC 29425, USA
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Robles-Espinoza CD, Mohammadi P, Bonilla X, Gutierrez-Arcelus M. Allele-specific expression: applications in cancer and technical considerations. Curr Opin Genet Dev 2021; 66:10-19. [PMID: 33383480 PMCID: PMC7985293 DOI: 10.1016/j.gde.2020.10.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2020] [Revised: 10/26/2020] [Accepted: 10/31/2020] [Indexed: 11/18/2022]
Abstract
Allele-specific gene expression can influence disease traits. Non-coding germline genetic variants that alter regulatory elements can cause allele-specific gene expression and contribute to cancer susceptibility. In tumors, both somatic copy number alterations and somatic single nucleotide variants have been shown to lead to allele-specific expression of genes, many of which are considered drivers of tumor growth. Here, we review recent studies revealing the pervasive presence of this phenomenon in cancer susceptibility and progression. Furthermore, we underscore the importance of careful experimental design and computational analysis for accurate allelic expression quantification and avoidance of false positives. Finally, we discuss additional methodological challenges encountered in cancer studies and in the burgeoning field of single-cell transcriptomics.
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Affiliation(s)
- Carla Daniela Robles-Espinoza
- Laboratorio Internacional de Investigación sobre el Genoma Humano, Universidad Nacional Autónoma de México, Campus Juriquilla, Boulevard Juriquilla 3001, Santiago de Querétaro 76230, Mexico; Wellcome Sanger Institute, Hinxton, Cambridgeshire CB10 1SA, UK
| | - Pejman Mohammadi
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA; Scripps Translational Science Institute, The Scripps Research Institute, La Jolla, CA, USA
| | - Ximena Bonilla
- Department of Computer Science, ETH Zurich, Universitätsstr. 6, 8092 Zürich, Switzerland; Swiss Institute of Bioinformatics, Quartier Sorge - Bâtiment Amphipôle, Lausanne 1015, Switzerland; University Hospital Zurich, Rämistrasse 100, 8091 Zürich, Switzerland
| | - Maria Gutierrez-Arcelus
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA; Division of Immunology, Department of Pediatrics, Boston Children's Hospital, Harvard Medical School, Boston, Massachusetts, USA.
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Hou P, Bao S, Fan D, Yan C, Su J, Qu J, Zhou M. Machine learning-based integrative analysis of methylome and transcriptome identifies novel prognostic DNA methylation signature in uveal melanoma. Brief Bioinform 2020; 22:6048939. [PMID: 33367533 DOI: 10.1093/bib/bbaa371] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 11/09/2020] [Accepted: 11/22/2020] [Indexed: 12/11/2022] Open
Abstract
Uveal melanoma (UVM) is the most common primary intraocular human malignancy with a high mortality rate. Aberrant DNA methylation has rapidly emerged as a diagnostic and prognostic signature in many cancers. However, such DNA methylation signature available in UVM remains limited. In this study, we performed a genome-wide integrative analysis of methylome and transcriptome and identified 40 methylation-driven prognostic genes (MDPGs) associated with the tumorigenesis and progression of UVM. Then, we proposed a machine-learning-based discovery and validation strategy to identify a DNA methylation-driven signature (10MeSig) composing of 10 MDPGs (AZGP1, BAI1, CCDC74A, FUT3, PLCD1, S100A4, SCN8A, SEMA3B, SLC25A38 and SLC44A3), which stratified 80 patients of the discovery cohort into two risk subtypes with significantly different overall survival (HR = 29, 95% CI: 6.7-126, P < 0.001). The 10MeSig was validated subsequently in an independent cohort with 57 patients and yielded a similar prognostic value (HR = 2.1, 95% CI: 1.2-3.7, P = 0.006). Multivariable Cox regression analysis showed that the 10MeSig is an independent predictive factor for the survival of patients with UVM. With a prospective validation study, this 10MeSig will improve clinical decisions and provide new insights into the pathogenesis of UVM.
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Affiliation(s)
- Ping Hou
- School of Biomedical Engineering, Wenzhou Medical University
| | - Siqi Bao
- School of Biomedical Engineering, Wenzhou Medical University
| | - Dandan Fan
- School of Biomedical Engineering, Wenzhou Medical University
| | - Congcong Yan
- School of Biomedical Engineering, Wenzhou Medical University
| | - Jianzhong Su
- School of Biomedical Engineering, Wenzhou Medical University
| | - Jia Qu
- School of Optometry and Ophthalmology and Eye Hospital, Wenzhou Medical University
| | - Meng Zhou
- School of Biomedical Engineering, Wenzhou Medical University
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Feng W, Zhao P, Zheng X, Hu Z, Liu J. Profiling Novel Alternative Splicing within Multiple Tissues Provides Useful Insights into Porcine Genome Annotation. Genes (Basel) 2020; 11:genes11121405. [PMID: 33255998 PMCID: PMC7760890 DOI: 10.3390/genes11121405] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 11/24/2020] [Accepted: 11/24/2020] [Indexed: 12/22/2022] Open
Abstract
Alternative splicing (AS) is a process during gene expression that results in a single gene coding for different protein variants. AS contributes to transcriptome and proteome diversity. In order to characterize AS in pigs, genome-wide transcripts and AS events were detected using RNA sequencing of 34 different tissues in Duroc pigs. In total, 138,403 AS events and 29,270 expressed genes were identified. An alternative donor site was the most common AS form and accounted for 44% of the total AS events. The percentage of the other three AS forms (exon skipping, alternative acceptor site, and intron retention) was approximately 19%. The results showed that the most common AS events involving alternative donor sites could produce different transcripts or proteins that affect the biological processes. The expression of genes with tissue-specific AS events showed that gene functions were consistent with tissue functions. AS increased proteome diversity and resulted in novel proteins that gained or lost important functional domains. In summary, these findings extend porcine genome annotation and highlight roles that AS could play in determining tissue identity.
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Involvement of lncRNAs in celiac disease pathogenesis. INTERNATIONAL REVIEW OF CELL AND MOLECULAR BIOLOGY 2020. [PMID: 33707056 DOI: 10.1016/bs.ircmb.2020.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/15/2023]
Abstract
Celiac disease (CD) is an immune-mediated disease that develops in genetically susceptible individuals upon gluten exposure. Human Leukocyte Antigen (HLA) genes in the Major Histocompatibility Complex (MHC) have been described to represent the 40% of the genetic risk to develop CD. Aiming to gain understanding of the genetic involvement in CD, high throughput studies have been performed, revealing that many CD-associated variants are located in non-coding regions, hindering the study of the functional implications of these single nucleotide polymorphisms (SNPs). In the last decade, long non-coding RNAs (lncRNAs) have been described to be influenced by disease-associated SNPs and to drive many important mechanisms involved in the development of inflammatory diseases. Here we describe the lncRNAs identified and characterized in the context of celiac disease and highlight the importance of the study of these molecules in inflammatory and autoimmune disorders.
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Shi X, Radhakrishnan S, Wen J, Chen JY, Chen J, Lam BA, Mills RE, Stranger BE, Lee C, Setlur SR. Association of CNVs with methylation variation. NPJ Genom Med 2020; 5:41. [PMID: 33062306 PMCID: PMC7519119 DOI: 10.1038/s41525-020-00145-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2019] [Accepted: 08/04/2020] [Indexed: 12/03/2022] Open
Abstract
Germline copy number variants (CNVs) and single-nucleotide polymorphisms (SNPs) form the basis of inter-individual genetic variation. Although the phenotypic effects of SNPs have been extensively investigated, the effects of CNVs is relatively less understood. To better characterize mechanisms by which CNVs affect cellular phenotype, we tested their association with variable CpG methylation in a genome-wide manner. Using paired CNV and methylation data from the 1000 genomes and HapMap projects, we identified genome-wide associations by methylation quantitative trait locus (mQTL) analysis. We found individual CNVs being associated with methylation of multiple CpGs and vice versa. CNV-associated methylation changes were correlated with gene expression. CNV-mQTLs were enriched for regulatory regions, transcription factor-binding sites (TFBSs), and were involved in long-range physical interactions with associated CpGs. Some CNV-mQTLs were associated with methylation of imprinted genes. Several CNV-mQTLs and/or associated genes were among those previously reported by genome-wide association studies (GWASs). We demonstrate that germline CNVs in the genome are associated with CpG methylation. Our findings suggest that structural variation together with methylation may affect cellular phenotype.
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Affiliation(s)
- Xinghua Shi
- Department of Bioinformatics and Genomics, College of Computing and Informatics, University of North Carolina, Charlotte, North Carolina 28223 USA.,Present Address: Department of Computer and Information Sciences, College of Science and Technology, Temple University, Philadelphia, Pennsylvania 19122 USA
| | - Saranya Radhakrishnan
- Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115 USA
| | - Jia Wen
- Department of Bioinformatics and Genomics, College of Computing and Informatics, University of North Carolina, Charlotte, North Carolina 28223 USA
| | - Jin Yun Chen
- Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115 USA
| | - Junjie Chen
- Department of Bioinformatics and Genomics, College of Computing and Informatics, University of North Carolina, Charlotte, North Carolina 28223 USA.,Present Address: Department of Computer and Information Sciences, College of Science and Technology, Temple University, Philadelphia, Pennsylvania 19122 USA
| | - Brianna Ashlyn Lam
- Department of Bioinformatics and Genomics, College of Computing and Informatics, University of North Carolina, Charlotte, North Carolina 28223 USA
| | - Ryan E Mills
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109 USA
| | - Barbara E Stranger
- Department of Pharmacology, Northwestern University, Chicago, Illinois 60611 USA
| | - Charles Lee
- The Jackson Laboratory for Genomic Medicine, Farmington, Connecticut 06032 USA.,Department of Life Sciences, Ewha Womans University, Seoul, 03760 South Korea.,Precision Medicine Center, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710061 Shaanxi China
| | - Sunita R Setlur
- Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115 USA
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Alternative splicing of MR1 regulates antigen presentation to MAIT cells. Sci Rep 2020; 10:15429. [PMID: 32963314 PMCID: PMC7508857 DOI: 10.1038/s41598-020-72394-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Accepted: 08/24/2020] [Indexed: 01/09/2023] Open
Abstract
Mucosal Associated Invariant T (MAIT) cells can sense intracellular infection by a broad array of pathogens. These cells are activated upon encountering microbial antigen(s) displayed by MR1 on the surface of an infected cell. Human MR1 undergoes alternative splicing. The full-length isoform, MR1A, can activate MAIT cells, while the function of the isoforms, MR1B and MR1C, are incompletely understood. In this report, we sought to characterize the expression and function of these splice variants. Using a transcriptomic analysis in conjunction with qPCR, we find that that MR1A and MR1B transcripts are widely expressed. However only MR1A can present mycobacterial antigen to MAIT cells. Coexpression of MR1B with MR1A decreases MAIT cell activation following bacterial infection. Additionally, expression of MR1B prior to MR1A lowers total MR1A abundance, suggesting competition between MR1A and MR1B for either ligands or chaperones required for folding and/or trafficking. Finally, we evaluated CD4/CD8 double positive thymocytes expressing surface MR1. Here, we find that relative expression of MR1A/MR1B transcript is associated with the prevalence of MR1 + CD4/CD8 cells in the thymus. Our results suggest alternative splicing of MR1 represents a means of regulating MAIT activation in response to microbial ligand(s).
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Jalilvand A, Yari K, Aznab M, Rahimi Z, Salahshouri Far I, Mohammadi P. A case-control study on the SNP309T → G and 40-bp Del1518 of the MDM2 gene and a systematic review for MDM2 polymorphisms in the patients with breast cancer. J Clin Lab Anal 2020; 34:e23529. [PMID: 32951271 PMCID: PMC7755803 DOI: 10.1002/jcla.23529] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2020] [Revised: 07/13/2020] [Accepted: 07/15/2020] [Indexed: 02/05/2023] Open
Abstract
Objective The current research was conducted to study the association between the SNP309 and del1518 polymorphisms with the breast cancer in the patients with the Kurdish ethnic background from western Iran. Also, a systematic review of the relevant case‐control studies on the MDM2 polymorphisms in the patients with breast cancer was performed. Methodology Two mL of peripheral blood was taken from 100 patients with breast cancer and 100 healthy individuals. The frequencies of MDM2 SNP309 and del1518 genotypes and alleles were determined using the PCR‐RFLP and PCR methods, respectively. Results The frequency of the TT, TG, and GG of MDM2‐SNP309 genotypes in the patients was obtained as 23%, 52%, and 25%, and they were equal to 22%, 40%, and 38% in the control group, respectively. Also, considering the MDM2‐del1518 polymorphism, the frequencies of ins/ins, ins/del, and del/del genotypes were equal to 52%, 41%, and 7% in the breast cancer group and they were equal to 62, 30, and 8% in the control group, respectively. Analysis of the results indicated that the GG genotype plays a protective role for the breast cancer in the recessive model (GG vs TT + TG) of SNP309 (χ2 = 3.916, P = .048, and OR = 0.54). Conclusion Our findings revealed that the GG genotype of MDM2‐SNP309 can play a protective role in the breast cancer disease. Also, our systematic review indicated that the SNP309, SNP285, and del1518 of MDM2 gene in different populations mostly did not have a significant association with the risk of breast cancer.
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Affiliation(s)
- Amin Jalilvand
- Medical Biology Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Kheirollah Yari
- Medical Biology Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran.,Zagros Bioidea Co, Razi University Incubator, Kermanshah, Iran
| | - Mozaffar Aznab
- Department of Internal Medicine, Medical Oncologist-Hematologist, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Zohreh Rahimi
- Medical Biology Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran
| | - Iman Salahshouri Far
- Department of Biology, Science and Research Branch, Islamic Azad University, Tehran, Iran
| | - Pantea Mohammadi
- Medical Biology Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Kermanshah, Iran
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He Y, Chhetri SB, Arvanitis M, Srinivasan K, Aguet F, Ardlie KG, Barbeira AN, Bonazzola R, Im HK, Brown CD, Battle A. sn-spMF: matrix factorization informs tissue-specific genetic regulation of gene expression. Genome Biol 2020; 21:235. [PMID: 32912314 PMCID: PMC7488540 DOI: 10.1186/s13059-020-02129-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Accepted: 08/04/2020] [Indexed: 01/09/2023] Open
Abstract
Genetic regulation of gene expression, revealed by expression quantitative trait loci (eQTLs), exhibits complex patterns of tissue-specific effects. Characterization of these patterns may allow us to better understand mechanisms of gene regulation and disease etiology. We develop a constrained matrix factorization model, sn-spMF, to learn patterns of tissue-sharing and apply it to 49 human tissues from the Genotype-Tissue Expression (GTEx) project. The learned factors reflect tissues with known biological similarity and identify transcription factors that may mediate tissue-specific effects. sn-spMF, available at https://github.com/heyuan7676/ts_eQTLs , can be applied to learn biologically interpretable patterns of eQTL tissue-specificity and generate testable mechanistic hypotheses.
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Affiliation(s)
- Yuan He
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, 21218, MD, USA
| | - Surya B Chhetri
- HudsonAlpha Institute for Biotechnology, Huntsville, 35806, AL, USA
- Current Address: Department of Biomedical Engineering, Johns Hopkins University, Baltimore, 21218, MD, USA
| | - Marios Arvanitis
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, 21218, MD, USA
- Department of Medicine, Division of Cardiology, Johns Hopkins University, Baltimore, 21287, MD, USA
| | - Kaushik Srinivasan
- Department of Computer Science, Johns Hopkins University, Baltimore, 21218, MD, USA
| | - François Aguet
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Alvaro N Barbeira
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA
| | - Rodrigo Bonazzola
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA
| | - Hae Kyung Im
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL, USA
| | - Christopher D Brown
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, 19104, PA, USA.
| | - Alexis Battle
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, 21218, MD, USA.
- Department of Computer Science, Johns Hopkins University, Baltimore, 21218, MD, USA.
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Polli A, Godderis L, Ghosh M, Ickmans K, Nijs J. Epigenetic and miRNA Expression Changes in People with Pain: A Systematic Review. THE JOURNAL OF PAIN 2020; 21:763-780. [DOI: 10.1016/j.jpain.2019.12.002] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/08/2019] [Revised: 09/30/2019] [Accepted: 12/02/2019] [Indexed: 01/13/2023]
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Kim S, Forno E, Zhang R, Park HJ, Xu Z, Yan Q, Boutaoui N, Acosta-Pérez E, Canino G, Chen W, Celedón JC. Expression Quantitative Trait Methylation Analysis Reveals Methylomic Associations With Gene Expression in Childhood Asthma. Chest 2020; 158:1841-1856. [PMID: 32569636 DOI: 10.1016/j.chest.2020.05.601] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2020] [Revised: 04/10/2020] [Accepted: 05/23/2020] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Nasal (airway) epithelial methylation profiles have been associated with asthma, but the effects of such profiles on expression of distant cis-genes are largely unknown. RESEARCH QUESTION To identify genes whose expression is associated with proximal and distal CpG probes (within 1 Mb), and to assess whether and how such genes are differentially expressed in atopic asthma. STUDY DESIGN AND METHODS Genome-wide expression quantitative trait methylation (eQTM) analysis in nasal epithelium from Puerto Rican subjects (aged 9-20 years) with (n = 219) and without (n = 236) asthma. After the eQTM analysis, a Gene Ontology Enrichment analysis was conducted for the top 500 eQTM genes, and mediation analyses were performed to identify paths from DNA methylation to atopic asthma through gene expression. Asthma was defined as physician-diagnosed asthma and wheeze in the previous year, and atopy was defined as at least one positive IgE to allergens. Atopic asthma was defined as the presence of both atopy and asthma. RESULTS We identified 16,867 significant methylation-gene expression pairs (false-discovery rate-adjusted P < .01) in nasal epithelium from study participants. Most eQTM methylation probes were distant (average distance, ∼378 kb) from their target genes, and also more likely to be located in enhancer regions of their target genes in lung tissue than control probes. The top 500 eQTM genes were enriched in pathways for immune processes and epithelial integrity and were more likely to have been previously identified as differentially expressed in atopic asthma. In a mediation analysis, we identified 5,934 paths through which methylation markers could affect atopic asthma through gene expression in nasal epithelium. INTERPRETATION Previous epigenome-wide association studies of asthma have estimated the effects of DNA methylation markers on expression of nearby genes in airway epithelium. Our findings suggest that distant epigenetic regulation of gene expression in airway epithelium plays a role in atopic asthma.
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Affiliation(s)
- Soyeon Kim
- Division of Pulmonary Medicine, Department of Pediatrics, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA
| | - Erick Forno
- Division of Pulmonary Medicine, Department of Pediatrics, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA
| | - Rong Zhang
- Department of Statistics, University of Pittsburgh, Pittsburgh, PA
| | - Hyun Jung Park
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, PA
| | - Zhongli Xu
- Division of Pulmonary Medicine, Department of Pediatrics, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA; School of Medicine, Tsinghua University, Beijing, China
| | - Qi Yan
- Division of Pulmonary Medicine, Department of Pediatrics, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA
| | - Nadia Boutaoui
- Division of Pulmonary Medicine, Department of Pediatrics, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA
| | - Edna Acosta-Pérez
- Behavioral Sciences Research Institute, University of Puerto Rico, San Juan, PR
| | - Glorisa Canino
- Behavioral Sciences Research Institute, University of Puerto Rico, San Juan, PR
| | - Wei Chen
- Division of Pulmonary Medicine, Department of Pediatrics, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA
| | - Juan C Celedón
- Division of Pulmonary Medicine, Department of Pediatrics, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA.
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46
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Wu C, Pan W. Integration of methylation QTL and enhancer-target gene maps with schizophrenia GWAS summary results identifies novel genes. Bioinformatics 2020; 35:3576-3583. [PMID: 30850848 DOI: 10.1093/bioinformatics/btz161] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2018] [Revised: 02/04/2019] [Accepted: 03/05/2019] [Indexed: 01/06/2023] Open
Abstract
MOTIVATION Most trait-associated genetic variants identified in genome-wide association studies (GWASs) are located in non-coding regions of the genome and thought to act through their regulatory roles. RESULTS To account for enriched association signals in DNA regulatory elements, we propose a novel and general gene-based association testing strategy that integrates enhancer-target gene pairs and methylation quantitative trait locus data with GWAS summary results; it aims to both boost statistical power for new discoveries and enhance mechanistic interpretability of any new discovery. By reanalyzing two large-scale schizophrenia GWAS summary datasets, we demonstrate that the proposed method could identify some significant and novel genes (containing no genome-wide significant SNPs nearby) that would have been missed by other competing approaches, including the standard and some integrative gene-based association methods, such as one incorporating enhancer-target gene pairs and one integrating expression quantitative trait loci. AVAILABILITY AND IMPLEMENTATION Software: wuchong.org/egmethyl.html. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Chong Wu
- Department of Statistics, Florida State University, Tallahassee, FL, USA
| | - Wei Pan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN, USA
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Swenson S, Blum K, McLaughlin T, Gold MS, Thanos PK. The therapeutic potential of exercise for neuropsychiatric diseases: A review. J Neurol Sci 2020; 412:116763. [PMID: 32305746 DOI: 10.1016/j.jns.2020.116763] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Revised: 02/14/2020] [Accepted: 02/28/2020] [Indexed: 02/06/2023]
Abstract
Exercise is known to have a myriad of health benefits. There is much to be learned from the effects of exercise and its potential for prevention, attenuation and treatment of multiple neuropsychiatric diseases and behavioral disorders. Furthermore, recent data and research on exercise benefits with respect to major health crises, such as, that of opioid and general substance use disorders, make it very important to better understand and review the mechanisms of exercise and how it could be utilized for effective treatments or adjunct treatments for these diseases. In addition, mechanisms, epigenetics and sex differences are examined and discussed in terms of future research implications.
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Affiliation(s)
- Sabrina Swenson
- Behavioral Neuropharmacology and Neuroimaging Laboratory on Addictions, Clinical Research Institute on Addictions, Department of Pharmacology and Toxicology, Jacobs School of Medicine and Biosciences, State University of New York at Buffalo, Buffalo, NY, USA
| | - Kenneth Blum
- Western Univesity Health Sciences, Graduate College, Pomona, CA, USA
| | | | - Mark S Gold
- Washington University in St. Louis, School of Medicine, St. Louis, MO, USA
| | - Panayotis K Thanos
- Behavioral Neuropharmacology and Neuroimaging Laboratory on Addictions, Clinical Research Institute on Addictions, Department of Pharmacology and Toxicology, Jacobs School of Medicine and Biosciences, State University of New York at Buffalo, Buffalo, NY, USA; Department of Psychology, State University of New York at Buffalo, Buffalo, NY, USA.
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48
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Kim S, Park HJ, Cui X, Zhi D. Collective effects of long-range DNA methylations predict gene expressions and estimate phenotypes in cancer. Sci Rep 2020; 10:3920. [PMID: 32127627 PMCID: PMC7054398 DOI: 10.1038/s41598-020-60845-2] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2019] [Accepted: 02/07/2020] [Indexed: 01/12/2023] Open
Abstract
DNA methylation of various genomic regions has been found to be associated with gene expression in diverse biological contexts. However, most genome-wide studies have focused on the effect of (1) methylation in cis, not in trans and (2) a single CpG, not the collective effects of multiple CpGs, on gene expression. In this study, we developed a statistical machine learning model, geneEXPLORE (gene expression prediction by long-range epigenetics), that quantifies the collective effects of both cis- and trans- methylations on gene expression. By applying geneEXPLORE to The Cancer Genome Atlas (TCGA) breast and 10 other types of cancer data, we found that most genes are associated with methylations of as much as 10 Mb from the promoters or more, and the long-range methylation explains 50% of the variation in gene expression on average, far greater than cis-methylation. geneEXPLORE outperforms competing methods such as BioMethyl and MethylXcan. Further, the predicted gene expressions could predict clinical phenotypes such as breast tumor status and estrogen receptor status (AUC = 0.999, 0.94 respectively) as accurately as the measured gene expression levels. These results suggest that geneEXPLORE provides a means for accurate imputation of gene expression, which can be further used to predict clinical phenotypes.
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Affiliation(s)
- Soyeon Kim
- Department of Pediatrics, School of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, United States.,Division of Pediatric Pulmonary Medicine, UPMC Children's hospital of Pittsburgh, Pittsburgh, Pennsylvania, United States
| | - Hyun Jung Park
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pennsylvania, United States
| | - Xiangqin Cui
- Department of Biostatistics and Bioinformatics, Emory University, Atlanta, Georgia, United States
| | - Degui Zhi
- Center for Precision Health, School of Biomedical Informatics, School of Public Health, University of Texas Health Center at Houston, Houston, Texas, United States.
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49
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Cai M, Chen LS, Liu J, Yang C. IGREX for quantifying the impact of genetically regulated expression on phenotypes. NAR Genom Bioinform 2020; 2:lqaa010. [PMID: 32118202 PMCID: PMC7034630 DOI: 10.1093/nargab/lqaa010] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2019] [Revised: 01/08/2020] [Accepted: 02/05/2020] [Indexed: 12/20/2022] Open
Abstract
By leveraging existing GWAS and eQTL resources, transcriptome-wide association studies (TWAS) have achieved many successes in identifying trait-associations of genetically regulated expression (GREX) levels. TWAS analysis relies on the shared GREX variation across GWAS and the reference eQTL data, which depends on the cellular conditions of the eQTL data. Considering the increasing availability of eQTL data from different conditions and the often unknown trait-relevant cell/tissue-types, we propose a method and tool, IGREX, for precisely quantifying the proportion of phenotypic variation attributed to the GREX component. IGREX takes as input a reference eQTL panel and individual-level or summary-level GWAS data. Using eQTL data of 48 tissue types from the GTEx project as a reference panel, we evaluated the tissue-specific IGREX impact on a wide spectrum of phenotypes. We observed strong GREX effects on immune-related protein biomarkers. By incorporating trans-eQTLs and analyzing genetically regulated alternative splicing events, we evaluated new potential directions for TWAS analysis.
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Affiliation(s)
- Mingxuan Cai
- Department of Mathematics, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
| | - Lin S Chen
- Department of Public Health Sciences, The University of Chicago, IL 60637, USA
| | - Jin Liu
- Center for Quantitative Medicine, Duke-NUS Medical School, 169856, Singapore
| | - Can Yang
- Department of Mathematics, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong
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50
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Mooney MA, Ryabinin P, Wilmot B, Bhatt P, Mill J, Nigg JT. Large epigenome-wide association study of childhood ADHD identifies peripheral DNA methylation associated with disease and polygenic risk burden. Transl Psychiatry 2020; 10:8. [PMID: 32066674 PMCID: PMC7026179 DOI: 10.1038/s41398-020-0710-4] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 12/09/2019] [Accepted: 12/20/2019] [Indexed: 12/17/2022] Open
Abstract
Epigenetic variation in peripheral tissues is being widely studied as a molecular biomarker of complex disease and disease-related exposures. To date, few studies have examined differences in DNA methylation associated with attention-deficit hyperactivity disorder (ADHD). In this study, we profiled genetic and methylomic variation across the genome in saliva samples from children (age 7-12 years) with clinically established ADHD (N = 391) and nonpsychiatric controls (N = 213). We tested for differentially methylated positions (DMPs) associated with both ADHD diagnosis and ADHD polygenic risk score, by using linear regression models including smoking, medication effects, and other potential confounders in our statistical models. Our results support previously reported associations between ADHD and DNA methylation levels at sites annotated to VIPR2, and identify several novel disease-associated DMPs (p < 1e-5), although none of them were genome-wide significant. The two top-ranked, ADHD-associated DMPs (cg17478313 annotated to SLC7A8 and cg21609804 annotated to MARK2) are also significantly associated with nearby SNPs (p = 1.2e-46 and p = 2.07e-59), providing evidence that disease-associated DMPs are under genetic control. We also report a genome-wide significant association between ADHD polygenic risk and variable DNA methylation at a site annotated to the promoter of GART and SON (p = 6.71E-8). Finally, we show that ADHD-associated SNPs colocalize with SNPs associated with methylation levels in saliva. This is the first large-scale study of DNA methylation in children with ADHD. Our results represent novel epigenetic biomarkers for ADHD that may be useful for patient stratification, reinforce the importance of genetic effects on DNA methylation, and provide plausible molecular mechanisms for ADHD risk variants.
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Affiliation(s)
- Michael A. Mooney
- grid.5288.70000 0000 9758 5690Division of Bioinformatics & Computational Biology, Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, OR USA ,grid.5288.70000 0000 9758 5690OHSU Knight Cancer Institute, Portland, OR USA
| | - Peter Ryabinin
- grid.5288.70000 0000 9758 5690Oregon Clinical and Translational Research Institute, Portland, OR USA
| | - Beth Wilmot
- grid.5288.70000 0000 9758 5690Division of Bioinformatics & Computational Biology, Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, OR USA ,grid.5288.70000 0000 9758 5690Oregon Clinical and Translational Research Institute, Portland, OR USA
| | - Priya Bhatt
- grid.5288.70000 0000 9758 5690Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, OR USA
| | - Jonathan Mill
- grid.8391.30000 0004 1936 8024University of Exeter Medical School, Exeter University, Exeter, UK
| | - Joel T. Nigg
- grid.5288.70000 0000 9758 5690Division of Psychology, Department of Psychiatry, Oregon Health & Science University, Portland, OR USA ,grid.5288.70000 0000 9758 5690Department of Behavioral Neuroscience, Oregon Health & Science University, Portland, OR USA
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