1
|
Hood RB, Everson TM, Ford JB, Hauser R, Knight A, Smith AK, Gaskins AJ. Epigenetic age acceleration in follicular fluid and markers of ovarian response among women undergoing IVF. Hum Reprod 2024; 39:2003-2009. [PMID: 38890131 PMCID: PMC11373381 DOI: 10.1093/humrep/deae136] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 05/07/2024] [Indexed: 06/20/2024] Open
Abstract
STUDY QUESTION Are markers of epigenetic age acceleration in follicular fluid associated with outcomes of ovarian stimulation? SUMMARY ANSWER Increased epigenetic age acceleration of follicular fluid using the Horvath clock, but not other epigenetic clocks (GrimAge and Granulosa Cell), was associated with lower peak estradiol levels and decreased number of total and mature oocytes. WHAT IS KNOWN ALREADY In granulosa cells, there are inconsistent findings between epigenetic age acceleration and ovarian response outcomes. STUDY DESIGN, SIZE, DURATION Our study included 61 women undergoing IVF at an academic fertility clinic in the New England area who were part of the Environment and Reproductive Health Study (2006-2016). PARTICIPANTS/MATERIALS, SETTING, METHODS Participants provided a follicular fluid sample during oocyte retrieval. DNA methylation of follicular fluid was assessed using a genome-wide methylation screening tool. Three established epigenetic clocks (Horvath, GrimAge, and Granulosa Cell) were used to predict DNA-methylation-based epigenetic age. To calculate the age acceleration, we regressed epigenetic age on chronological age and extracted the residuals. The association between epigenetic age acceleration and ovarian response outcomes (peak estradiol levels, follicle stimulation hormone, number of total, and mature oocytes) was assessed using linear and Poisson regression adjusted for chronological age, three surrogate variables (to account for cellular heterogeneity), race, smoking status, initial infertility diagnosis, and stimulation protocol. MAIN RESULTS AND ROLE OF CHANCE Compared to the median chronological age of our participants (34 years), the Horvath clock predicted, on an average, a younger epigenetic age (median: 24.2 years) while the GrimAge (median: 38.6 years) and Granulosa Cell (median: 39.0 years) clocks predicted, on an average, an older epigenetic age. Age acceleration based on the Horvath clock was associated with lower peak estradiol levels (-819.4 unit decrease in peak estradiol levels per standard deviation increase; 95% CI: -1265.7, -373.1) and fewer total (% change in total oocytes retrieved per standard deviation increase: -21.8%; 95% CI: -37.1%, -2.8%) and mature oocytes retrieved (% change in mature oocytes retrieved per standard deviation increase: -23.8%; 95% CI: -39.9%, -3.4%). The age acceleration based on the two other epigenetic clocks was not associated with markers of ovarian response. LIMITATIONS, REASONS FOR CAUTION Our sample size was small and we did not specifically isolate granulosa cells from follicular fluid samples so our samples could have included mixed cell types. WIDER IMPLICATIONS OF THE FINDINGS Our results highlight that certain epigenetic clocks may be predictive of ovarian stimulation outcomes when applied to follicular fluid; however, the inconsistent findings for specific clocks across studies indicate a need for further research to better understand the clinical utility of epigenetic clocks to improve IVF treatment. STUDY FUNDING/COMPETING INTEREST(S) The study was supported by grants ES009718, ES022955, ES000002, and ES026648 from the National Institute of Environmental Health Sciences (NIEHS) and a pilot grant from the NIEHS-funded HERCULES Center at Emory University (P30 ES019776). RBH was supported by the Emory University NIH Training Grant (T32-ES012870). TRIAL REGISTRATION NUMBER N/A.
Collapse
Affiliation(s)
- Robert B Hood
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Todd M Everson
- Gangarosa Department of Environmental Health, 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, Boston, MA, USA
| | - Russ Hauser
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Anna Knight
- Department of Gynecology and Obstetrics, School of Medicine, Emory University, Atlanta, GA, USA
| | - Alicia K Smith
- Department of Gynecology and Obstetrics, School of Medicine, Emory University, Atlanta, GA, USA
| | - Audrey J Gaskins
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| |
Collapse
|
2
|
Wu Y, He B, Hua J, Hu W, Han Y, Zhang J. Deciphering the molecular regulatory of RAB32/GPRC5A axis in chronic obstructive pulmonary disease. Respir Res 2024; 25:116. [PMID: 38448858 PMCID: PMC10919015 DOI: 10.1186/s12931-024-02724-2] [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: 11/05/2023] [Accepted: 02/11/2024] [Indexed: 03/08/2024] Open
Abstract
BACKGROUND Chronic obstructive pulmonary disease (COPD) is a significant public health problem characterized by persistent airflow limitation. Despite previous research into the pathogenesis of COPD, a comprehensive understanding of the cell-type-specific mechanisms in COPD remains lacking. Recent studies have implicated Rab GTPases in regulating chronic immune response and inflammation via multiple pathways. In this study, the molecular regulating mechanism of RAB32 in COPD was investigated by multiple bioinformatics mining and experimental verification. METHODS We collected lung tissue surgical specimens from Zhongshan Hospital, Fudan University, and RT-qPCR and western blotting were used to detect the expression of Rabs in COPD lung tissues. Four COPD microarray datasets from the Gene Expression Omnibus (GEO) were analyzed. COPD-related epithelial cell scRNA-seq data was obtained from the GSE173896 dataset. Weighted gene co-expression network analysis (WGCNA), mfuzz cluster, and Spearman correlation analysis were combined to obtain the regulatory network of RAB32 in COPD. The slingshot algorithm was used to identify the regulatory molecule, and the co-localization of RAB32 and GPRC5A was observed with immunofluorescence. RESULTS WGCNA identified 771 key module genes significantly associated with the occurrence of COPD, including five Rab genes. RAB32 was up-regulated in lung tissues from subjects with COPD as contrast to those without COPD on both mRNA and protein levels. Integrating the results of WGCNA, Mfuzz clusters, and Spearman analysis, nine potential interacting genes with RAB32 were identified. Among these genes, GPRC5A exhibited a similar molecular expression pattern to RAB32. Co-expression density analysis at the cell level demonstrated that the co-expression density of RAB32 and GPRC5A was higher in type I alveolar epithelial cells (AT1s) than in type II alveolar epithelial cells (AT2s). The immunofluorescence also confirmed the co-localization of RAB32 and GPRC5A, and the Pearson correlation analysis found the relationship between RAB32 and GPRC5A was significantly stronger in the COPD lungs (r = 0.65) compared to the non-COPD lungs (r = 0.33). CONCLUSIONS Our study marked endeavor to delineate the molecular regulatory axis of RAB32 in COPD by employing diverse methods and identifying GPRC5A as a potential interacting molecule with RAB32. These findings offered novel perspectives on the mechanism of COPD.
Collapse
Affiliation(s)
- Yixing Wu
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Binfeng He
- Department of General Practice, Xinqiao Hospital, Third Military Medical University, Chongqing, China
| | - Jianlan Hua
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Weiping Hu
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Yaopin Han
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Jing Zhang
- Department of Pulmonary and Critical Care Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
| |
Collapse
|
3
|
Garmire LX, Li Y, Huang Q, Xu C, Teichmann SA, Kaminski N, Pellegrini M, Nguyen Q, Teschendorff AE. Challenges and perspectives in computational deconvolution of genomics data. Nat Methods 2024; 21:391-400. [PMID: 38374264 DOI: 10.1038/s41592-023-02166-6] [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: 11/04/2022] [Accepted: 12/26/2023] [Indexed: 02/21/2024]
Abstract
Deciphering cell-type heterogeneity is crucial for systematically understanding tissue homeostasis and its dysregulation in diseases. Computational deconvolution is an efficient approach for estimating cell-type abundances from a variety of omics data. Despite substantial methodological progress in computational deconvolution in recent years, challenges are still outstanding. Here we enlist four important challenges related to computational deconvolution: the quality of the reference data, generation of ground truth data, limitations of computational methodologies, and benchmarking design and implementation. Finally, we make recommendations on reference data generation, new directions of computational methodologies, and strategies to promote rigorous benchmarking.
Collapse
Affiliation(s)
- Lana X Garmire
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA.
| | - Yijun Li
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
| | - Qianhui Huang
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Chuan Xu
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | | | - Naftali Kaminski
- Pulmonary, Critical Care & Sleep Medicine, Yale University School of Medicine, New Haven, CT, USA
| | - Matteo Pellegrini
- Molecular, Cell and Developmental Biology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Quan Nguyen
- Institute for Molecular Bioscience, The University of Queensland and QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Andrew E Teschendorff
- CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China
- UCL Cancer Institute, University College London, London, UK
| |
Collapse
|
4
|
Tamarelle J, Creze MM, Savathdy V, Phonekeo S, Wallenborn J, Siengsounthone L, Fink G, Odermatt P, Kounnavong S, Sayasone S, Vonaesch P. Dynamics and consequences of nutrition-related microbial dysbiosis in early life: study protocol of the VITERBI GUT project. Front Nutr 2023; 10:1111478. [PMID: 37275646 PMCID: PMC10232750 DOI: 10.3389/fnut.2023.1111478] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 05/02/2023] [Indexed: 06/07/2023] Open
Abstract
Introduction Early life under- and overnutrition (jointly termed malnutrition) is increasingly recognized as an important risk factor for adult obesity and metabolic syndrome, a diet-related cluster of conditions including high blood sugar, fat and cholesterol. Nevertheless, the exact factors linking early life malnutrition with metabolic syndrome remain poorly characterized. We hypothesize that the microbiota plays a crucial role in this trajectory and that the pathophysiological mechanisms underlying under- and overnutrition are, to some extent, shared. We further hypothesize that a "dysbiotic seed microbiota" is transmitted to children during the birth process, altering the children's microbiota composition and metabolic health. The overall objective of this project is to understand the precise causes and biological mechanisms linking prenatal or early life under- or overnutrition with the predisposition to develop overnutrition and/or metabolic disease in later life, as well as to investigate the possibility of a dysbiotic seed microbiota inheritance in the context of maternal malnutrition. Methods/design VITERBI GUT is a prospective birth cohort allowing to study the link between early life malnutrition, the microbiota and metabolic health. VITERBI GUT will include 100 undernourished, 100 normally nourished and 100 overnourished pregnant women living in Vientiane, Lao People's Democratic Republic (PDR). Women will be recruited during their third trimester of pregnancy and followed with their child until its second birthday. Anthropometric, clinical, metabolic and nutritional data are collected from both the mother and the child. The microbiota composition of maternal and child's fecal and oral samples as well as maternal vaginal and breast milk samples will be determined using amplicon and shotgun metagenomic sequencing. Epigenetic modifications and lipid profiles will be assessed in the child's blood at 2 years of age. We will investigate for possible associations between metabolic health, epigenetics, and microbial changes. Discussion We expect the VITERBI GUT project to contribute to the emerging literature linking the early life microbiota, epigenetic changes and growth/metabolic health. We also expect this project to give new (molecular) insights into the mechanisms linking malnutrition-induced early life dysbiosis and metabolic health in later life, opening new avenues for microbiota-engineering using microbiota-targeted interventions.
Collapse
Affiliation(s)
- Jeanne Tamarelle
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | - Margaux M. Creze
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| | - Vanthanom Savathdy
- Lao Tropical and Public Health Institute, Ministry of Health, Vientiane, Lao People’s Democratic Republic (PDR)
| | - Sengrloun Phonekeo
- Lao Tropical and Public Health Institute, Ministry of Health, Vientiane, Lao People’s Democratic Republic (PDR)
| | - Jordyn Wallenborn
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Latsamy Siengsounthone
- Lao Tropical and Public Health Institute, Ministry of Health, Vientiane, Lao People’s Democratic Republic (PDR)
| | - Günther Fink
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Peter Odermatt
- Department of Epidemiology and Public Health, Swiss Tropical and Public Health Institute, Allschwil, Switzerland
- University of Basel, Basel, Switzerland
| | - Sengchanh Kounnavong
- Lao Tropical and Public Health Institute, Ministry of Health, Vientiane, Lao People’s Democratic Republic (PDR)
| | - Somphou Sayasone
- Lao Tropical and Public Health Institute, Ministry of Health, Vientiane, Lao People’s Democratic Republic (PDR)
| | - Pascale Vonaesch
- Department of Fundamental Microbiology, University of Lausanne, Lausanne, Switzerland
| |
Collapse
|
5
|
McAllan L, Baranasic D, Villicaña S, Brown S, Zhang W, Lehne B, Adamo M, Jenkinson A, Elkalaawy M, Mohammadi B, Hashemi M, Fernandes N, Lambie N, Williams R, Christiansen C, Yang Y, Zudina L, Lagou V, Tan S, Castillo-Fernandez J, King JWD, Soong R, Elliott P, Scott J, Prokopenko I, Cebola I, Loh M, Lenhard B, Batterham RL, Bell JT, Chambers JC, Kooner JS, Scott WR. Integrative genomic analyses in adipocytes implicate DNA methylation in human obesity and diabetes. Nat Commun 2023; 14:2784. [PMID: 37188674 PMCID: PMC10185556 DOI: 10.1038/s41467-023-38439-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 05/03/2023] [Indexed: 05/17/2023] Open
Abstract
DNA methylation variations are prevalent in human obesity but evidence of a causative role in disease pathogenesis is limited. Here, we combine epigenome-wide association and integrative genomics to investigate the impact of adipocyte DNA methylation variations in human obesity. We discover extensive DNA methylation changes that are robustly associated with obesity (N = 190 samples, 691 loci in subcutaneous and 173 loci in visceral adipocytes, P < 1 × 10-7). We connect obesity-associated methylation variations to transcriptomic changes at >500 target genes, and identify putative methylation-transcription factor interactions. Through Mendelian Randomisation, we infer causal effects of methylation on obesity and obesity-induced metabolic disturbances at 59 independent loci. Targeted methylation sequencing, CRISPR-activation and gene silencing in adipocytes, further identifies regional methylation variations, underlying regulatory elements and novel cellular metabolic effects. Our results indicate DNA methylation is an important determinant of human obesity and its metabolic complications, and reveal mechanisms through which altered methylation may impact adipocyte functions.
Collapse
Affiliation(s)
- Liam McAllan
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
- MRC London Institute of Medical Sciences, London, W12 0NN, UK
| | - Damir Baranasic
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
- MRC London Institute of Medical Sciences, London, W12 0NN, UK
| | - Sergio Villicaña
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Scarlett Brown
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
- MRC London Institute of Medical Sciences, London, W12 0NN, UK
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
| | - Benjamin Lehne
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
| | - Marco Adamo
- UCLH Bariatric Centre for Weight Loss, Weight Management and Metabolic and Endocrine Surgery, University College London Hospitals, Ground Floor West Wing, 250 Euston Road, London, NW1 2PG, UK
| | - Andrew Jenkinson
- UCLH Bariatric Centre for Weight Loss, Weight Management and Metabolic and Endocrine Surgery, University College London Hospitals, Ground Floor West Wing, 250 Euston Road, London, NW1 2PG, UK
| | - Mohamed Elkalaawy
- UCLH Bariatric Centre for Weight Loss, Weight Management and Metabolic and Endocrine Surgery, University College London Hospitals, Ground Floor West Wing, 250 Euston Road, London, NW1 2PG, UK
| | - Borzoueh Mohammadi
- UCLH Bariatric Centre for Weight Loss, Weight Management and Metabolic and Endocrine Surgery, University College London Hospitals, Ground Floor West Wing, 250 Euston Road, London, NW1 2PG, UK
| | - Majid Hashemi
- UCLH Bariatric Centre for Weight Loss, Weight Management and Metabolic and Endocrine Surgery, University College London Hospitals, Ground Floor West Wing, 250 Euston Road, London, NW1 2PG, UK
| | - Nadia Fernandes
- Imperial BRC Genomics Facility, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
| | - Nathalie Lambie
- Imperial BRC Genomics Facility, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
| | - Richard Williams
- Imperial BRC Genomics Facility, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
| | - Colette Christiansen
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- School of Mathematics and Statistics, Faculty of Science, Technology, Engineering and Mathematics, The Open University, Milton Keynes, UK
| | - Youwen Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
- School of Cardiovascular and Metabolic Medicine and Sciences, James Black Centre, King's College London British Heart Foundation Centre of Excellence, 125 Coldharbour Lane, London, SE5 9NU, UK
| | - Liudmila Zudina
- Department of Clinical & Experimental Medicine, University of Surrey, Guildford, UK
| | - Vasiliki Lagou
- Department of Microbiology and Immunology, Laboratory of Adaptive Immunity, KU Leuven, Leuven, Belgium
- VIB-KU Leuven Center for Brain and Disease Research, Leuven, Belgium
| | - Sili Tan
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
| | | | - James W D King
- MRC London Institute of Medical Sciences, London, W12 0NN, UK
| | - Richie Soong
- Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore
- Department of Pathology, National University Hospital, Singapore, Singapore
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- National Institute for Health Research Biomedical Research Centre, Imperial College London, London, UK
| | - James Scott
- National Heart and Lung Institute, Imperial College London, London, W12 0NN, UK
- Imperial College Healthcare NHS Trust, London, W12 0HS, UK
| | - Inga Prokopenko
- Department of Clinical & Experimental Medicine, University of Surrey, Guildford, UK
- People-Centred Artificial Intelligence Institute, University of Surrey, Guildford, UK
- Institute of Biochemistry and Genetics, Ufa Federal Research Centre Russian Academy of Sciences, Ufa, Russian Federation
| | - Inês Cebola
- Section of Genetics and Genomics, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Marie Loh
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
- Translational Laboratory in Genetic Medicine (TLGM), Agency for Science, Technology and Research (A*STAR), 8A Biomedical Grove, Immunos, Level 5, Singapore, 138648, Singapore
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Boris Lenhard
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK
- MRC London Institute of Medical Sciences, London, W12 0NN, UK
| | - Rachel L Batterham
- UCLH Bariatric Centre for Weight Loss, Weight Management and Metabolic and Endocrine Surgery, University College London Hospitals, Ground Floor West Wing, 250 Euston Road, London, NW1 2PG, UK
- Centre for Obesity Research, Rayne Institute, Department of Medicine, University College, London, WC1E 6JJ, UK
- National Institute of Health Research University College London Hospitals Biomedical Research Centre, London, W1T 7DN, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - John C Chambers
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Imperial College Healthcare NHS Trust, London, W12 0HS, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London North West University Healthcare NHS Trust, Middlesex, UB1 3HW, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, W12 0NN, UK
- Imperial College Healthcare NHS Trust, London, W12 0HS, UK
| | - William R Scott
- Institute of Clinical Sciences, Faculty of Medicine, Imperial College London, London, W12 0NN, UK.
- MRC London Institute of Medical Sciences, London, W12 0NN, UK.
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK.
- Imperial College Healthcare NHS Trust, London, W12 0HS, UK.
| |
Collapse
|
6
|
Romanowska J, Nustad HE, Page CM, Denault WRP, Lee Y, Magnus MC, Haftorn KL, Gjerdevik M, Novakovic B, Saffery R, Gjessing HK, Lyle R, Magnus P, Håberg SE, Jugessur A. The X-factor in ART: does the use of assisted reproductive technologies influence DNA methylation on the X chromosome? Hum Genomics 2023; 17:35. [PMID: 37085889 PMCID: PMC10122315 DOI: 10.1186/s40246-023-00484-6] [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: 01/09/2023] [Accepted: 04/10/2023] [Indexed: 04/23/2023] Open
Abstract
BACKGROUND Assisted reproductive technologies (ART) may perturb DNA methylation (DNAm) in early embryonic development. Although a handful of epigenome-wide association studies of ART have been published, none have investigated CpGs on the X chromosome. To bridge this knowledge gap, we leveraged one of the largest collections of mother-father-newborn trios of ART and non-ART (natural) conceptions to date to investigate sex-specific DNAm differences on the X chromosome. The discovery cohort consisted of 982 ART and 963 non-ART trios from the Norwegian Mother, Father, and Child Cohort Study (MoBa). To verify our results from the MoBa cohort, we used an external cohort of 149 ART and 58 non-ART neonates from the Australian 'Clinical review of the Health of adults conceived following Assisted Reproductive Technologies' (CHART) study. The Illumina EPIC array was used to measure DNAm in both datasets. In the MoBa cohort, we performed a set of X-chromosome-wide association studies ('XWASs' hereafter) to search for sex-specific DNAm differences between ART and non-ART newborns. We tested several models to investigate the influence of various confounders, including parental DNAm. We also searched for differentially methylated regions (DMRs) and regions of co-methylation flanking the most significant CpGs. Additionally, we ran an analogous model to our main model on the external CHART dataset. RESULTS In the MoBa cohort, we found more differentially methylated CpGs and DMRs in girls than boys. Most of the associations persisted after controlling for parental DNAm and other confounders. Many of the significant CpGs and DMRs were in gene-promoter regions, and several of the genes linked to these CpGs are expressed in tissues relevant for both ART and sex (testis, placenta, and fallopian tube). We found no support for parental DNAm-dependent features as an explanation for the observed associations in the newborns. The most significant CpG in the boys-only analysis was in UBE2DNL, which is expressed in testes but with unknown function. The most significant CpGs in the girls-only analysis were in EIF2S3 and AMOT. These three loci also displayed differential DNAm in the CHART cohort. CONCLUSIONS Genes that co-localized with the significant CpGs and DMRs associated with ART are implicated in several key biological processes (e.g., neurodevelopment) and disorders (e.g., intellectual disability and autism). These connections are particularly compelling in light of previous findings indicating that neurodevelopmental outcomes differ in ART-conceived children compared to those naturally conceived.
Collapse
Affiliation(s)
- Julia Romanowska
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway.
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.
| | - Haakon E Nustad
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- DeepInsight, 0154, Oslo, Norway
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Mathematics, Faculty of Mathematics and Natural Sciences, University of Oslo, Oslo, Norway
| | - William R P Denault
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Human Genetics, University of Chicago, Chicago, IL, USA
| | - Yunsung Lee
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Maria C Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Kristine L Haftorn
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Miriam Gjerdevik
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Computer Science, Electrical Engineering and Mathematical Sciences, Western Norway University of Applied Sciences, Bergen, Norway
| | - Boris Novakovic
- Murdoch Children's Research Institute, Melbourne, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, Australia
| | - Richard Saffery
- Murdoch Children's Research Institute, Melbourne, Australia
- Department of Paediatrics, University of Melbourne, Melbourne, Australia
| | - Håkon K Gjessing
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| | - Robert Lyle
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Medical Genetics, Oslo University Hospital and University of Oslo, Oslo, Norway
| | - Per Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Astanand Jugessur
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
| |
Collapse
|
7
|
Liu W, Liu C, Chen C, Huang X, Yi Q, Tian Y, Peng B, Yuan Y. Construction and Verification of a Glycolysis-Associated Gene Signature for the Prediction of Overall Survival in Low Grade Glioma. Front Genet 2022; 13:843711. [PMID: 35401698 PMCID: PMC8983898 DOI: 10.3389/fgene.2022.843711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2021] [Accepted: 03/07/2022] [Indexed: 11/24/2022] Open
Abstract
The overall survival of patients with lower grade glioma (LGG) that might develop into high-grade malignant glioma shows marked heterogeneity. The currently used clinical evaluation index is not sufficient to predict precise prognostic outcomes accurately. To optimize survival risk stratification and the personalized management of patients with LGG, there is an urgent need to develop an accurate risk prediction model. The TCGA-LGG dataset, downloaded from The Cancer Genome Atlas (TCGA) portal, was used as a training cohort, and the Chinese Glioma Genome Atlas (CGGA) dataset and Rembrandt dataset were used as validation cohorts. The levels of various cancer hallmarks were quantified, which identified glycolysis as the primary overall survival-related risk factor in LGGs. Furthermore, using various bioinformatic and statistical methods, we developed a strong glycolysis-related gene signature to predict prognosis. Gene set enrichment analysis showed that in our model, high-risk glioma correlated with the chemoradiotherapy resistance and poor survival. Moreover, based on established risk model and other clinical features, a decision tree and a nomogram were built, which could serve as useful tools in the diagnosis and treatment of LGGs. This study indicates that the glycolysis-related gene signature could distinguish high-risk and low‐risk patients precisely, and thus can be used as an independent clinical feature.
Collapse
Affiliation(s)
- Wei Liu
- Department of Radiation Oncology, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Chunshan Liu
- Department of Radiation Oncology, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Chengcong Chen
- Department of Radiation Oncology, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Xiaoting Huang
- Department of Radiation Oncology, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Qi Yi
- Department of Radiation Oncology, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Yunhong Tian
- Department of Radiation Oncology, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Biao Peng
- Department of Neurosurgery, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| | - Yawei Yuan
- Department of Radiation Oncology, Affiliated Cancer Hospital and Institute of Guangzhou Medical University, Guangzhou, China
| |
Collapse
|
8
|
Ferreté-Bonastre AG, Cortés-Hernández J, Ballestar E. What can we learn from DNA methylation studies in lupus? Clin Immunol 2022; 234:108920. [PMID: 34973429 DOI: 10.1016/j.clim.2021.108920] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Revised: 12/23/2021] [Accepted: 12/26/2021] [Indexed: 11/17/2022]
Abstract
During the past twenty years, a wide range of studies have established the existence of epigenetic alterations, particularly DNA methylation changes, in lupus. Epigenetic changes might have different contributions in children-onset versus adult-onset lupus. DNA methylation alterations have been identified and characterized in relation to disease activity and damage, different lupus subtypes and responses to drugs. However, to date there has been no practical application of these findings in the clinical milieu. In this article, we provide a review of key studies showing the relationship between DNA methylation and the many clinical aspects related to lupus. We also propose several options, in relation to the range of methodological developments and experimental design, that could optimize these findings and make them amenable for use in clinical practice.
Collapse
Affiliation(s)
| | | | - Esteban Ballestar
- Epigenetics and Immune Disease Group, Josep Carreras Research Institute (IJC), 08916 Badalona, Barcelona, Spain; Epigenetics in Inflammatory and Metabolic Diseases Laboratory, Health Science Center (HSC), East China Normal University (ECNU), Shanghai, 200241, China.
| |
Collapse
|
9
|
Salas LA, Peres LC, Thayer ZM, Smith RWA, Guo Y, Chung W, Si J, Liang L. A transdisciplinary approach to understand the epigenetic basis of race/ethnicity health disparities. Epigenomics 2021; 13:1761-1770. [PMID: 33719520 PMCID: PMC8579937 DOI: 10.2217/epi-2020-0080] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 04/07/2020] [Indexed: 11/21/2022] Open
Abstract
Health disparities correspond to differences in disease burden and mortality among socially defined population groups. Such disparities may emerge according to race/ethnicity, socioeconomic status and a variety of other social contexts, and are documented for a wide range of diseases. Here, we provide a transdisciplinary perspective on the contribution of epigenetics to the understanding of health disparities, with a special emphasis on disparities across socially defined racial/ethnic groups. Scientists in the fields of biological anthropology, bioinformatics and molecular epidemiology provide a summary of theoretical, statistical and practical considerations for conducting epigenetic health disparities research, and provide examples of successful applications from cancer research using this approach.
Collapse
Affiliation(s)
- Lucas A Salas
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Lebanon, NH 03756, USA
| | - Lauren C Peres
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL 33612, USA
| | - Zaneta M Thayer
- Department of Anthropology, Dartmouth College, Hanover, NH 03755, USA
| | - Rick WA Smith
- Department of Anthropology, Dartmouth College, Hanover, NH 03755, USA
- The William H. Neukom Institute for Computational Science, Dartmouth College, Hanover, NH 03755, USA
| | | | - Wonil Chung
- Department of Statistics & Actuarial Science, Soongsil University, Seoul, 06478, Korea
- Program in Genetic Epidemiology & Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Jiahui Si
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Biostatistics & Epidemiology, Peking University School of Public Health, Beijing, 100191, China
| | - Liming Liang
- Program in Genetic Epidemiology & Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| |
Collapse
|
10
|
Si J, Yang S, Sun D, Yu C, Guo Y, Lin Y, Millwood IY, Walters RG, Yang L, Chen Y, Du H, Hua Y, Liu J, Chen J, Chen Z, Chen W, Lv J, Liang L, Li L. Epigenome-wide analysis of DNA methylation and coronary heart disease: a nested case-control study. eLife 2021; 10:e68671. [PMID: 34515027 PMCID: PMC8585480 DOI: 10.7554/elife.68671] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 09/12/2021] [Indexed: 02/05/2023] Open
Abstract
Background Identifying environmentally responsive genetic loci where DNA methylation is associated with coronary heart disease (CHD) may reveal novel pathways or therapeutic targets for CHD. We conducted the first prospective epigenome-wide analysis of DNA methylation in relation to incident CHD in the Asian population. Methods We did a nested case-control study comprising incident CHD cases and 1:1 matched controls who were identified from the 10 year follow-up of the China Kadoorie Biobank. Methylation level of baseline blood leukocyte DNA was measured by Infinium Methylation EPIC BeadChip. We performed the single cytosine-phosphate-guanine (CpG) site association analysis and network approach to identify CHD-associated CpG sites and co-methylation gene module. Results After quality control, 982 participants (mean age 50.1 years) were retained. Methylation level at 25 CpG sites across the genome was associated with incident CHD (genome-wide false discovery rate [FDR] < 0.05 or module-specific FDR < 0.01). One SD increase in methylation level of identified CpGs was associated with differences in CHD risk, ranging from a 47 % decrease to a 118 % increase. Mediation analyses revealed 28.5 % of the excessed CHD risk associated with smoking was mediated by methylation level at the promoter region of ANKS1A gene (P for mediation effect = 0.036). Methylation level at the promoter region of SNX30 was associated with blood pressure and subsequent risk of CHD, with the mediating proportion to be 7.7 % (P = 0.003) via systolic blood pressure and 6.4 % (P = 0.006) via diastolic blood pressure. Network analysis revealed a co-methylation module associated with CHD. Conclusions We identified novel blood methylation alterations associated with incident CHD in the Asian population and provided evidence of the possible role of epigenetic regulations in the smoking- and blood pressure-related pathways to CHD risk. Funding This work was supported by National Natural Science Foundation of China (81390544 and 91846303). The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation in Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust (202922/Z/16/Z, 088158/Z/09/Z, 104085/Z/14/Z), grant (2016YFC0900500, 2016YFC0900501, 2016YFC0900504, 2016YFC1303904) from the National Key R&D Program of China, and Chinese Ministry of Science and Technology (2011BAI09B01).
Collapse
Affiliation(s)
- Jiahui Si
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science CenterBeijingChina
- Departments of Epidemiology and Biostatistics, Harvard T.H. Chan School of Public HealthBostonUnited States
| | - Songchun Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science CenterBeijingChina
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science CenterBeijingChina
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science CenterBeijingChina
| | - Yu Guo
- Chinese Academy of Medical SciencesBeijingChina
| | - Yifei Lin
- Department of Urology, West China Hospital, Sichuan UniversityChengduChina
| | - Iona Y Millwood
- Medical Research Council Population Health Research Unit at the University of OxfordOxfordUnited Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Robin G Walters
- Medical Research Council Population Health Research Unit at the University of OxfordOxfordUnited Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Ling Yang
- Medical Research Council Population Health Research Unit at the University of OxfordOxfordUnited Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Yiping Chen
- Medical Research Council Population Health Research Unit at the University of OxfordOxfordUnited Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Huaidong Du
- Medical Research Council Population Health Research Unit at the University of OxfordOxfordUnited Kingdom
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Yujie Hua
- NCDs Prevention and Control Department, Suzhou CDCJiangsuChina
| | - Jingchao Liu
- NCDs Prevention and Control Department, Wuzhong CDCJiangsuChina
| | - Junshi Chen
- China National Center for Food Safety Risk AssessmentBeijingChina
| | - Zhengming Chen
- Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of OxfordOxfordUnited Kingdom
| | - Wei Chen
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane UniversityNew OrleansUnited States
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science CenterBeijingChina
- Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of EducationBeijingChina
- Peking University Institute of Environmental MedicineBeijingChina
| | - Liming Liang
- Departments of Epidemiology and Biostatistics, Harvard T.H. Chan School of Public HealthBostonUnited States
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science CenterBeijingChina
| | | |
Collapse
|
11
|
Silva R, Moran B, Baird AM, O'Rourke CJ, Finn SP, McDermott R, Watson W, Gallagher WM, Brennan DJ, Perry AS. Longitudinal analysis of individual cfDNA methylome patterns in metastatic prostate cancer. Clin Epigenetics 2021; 13:168. [PMID: 34454584 PMCID: PMC8403420 DOI: 10.1186/s13148-021-01155-w] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 08/17/2021] [Indexed: 01/27/2023] Open
Abstract
Background Disease progression and therapeutic resistance are hallmarks of advanced stage prostate cancer (PCa), which remains a major cause of cancer-related mortality around the world. Longitudinal studies, coupled with the use of liquid biopsies, offer a potentially new and minimally invasive platform to study the dynamics of tumour progression. Our aim was to investigate the dynamics of personal DNA methylomic profiles of metastatic PCa (mPCa) patients, during disease progression and therapy administration. Results Forty-eight plasma samples from 9 mPCa patients were collected, longitudinally, over 13–21 months. After circulating cell-free DNA (cfDNA) isolation, DNA methylation was profiled using the Infinium MethylationEPIC BeadChip. The top 5% most variable probes across time, within each individual, were utilised to study dynamic methylation patterns during disease progression and therapeutic response. Statistical testing was carried out to identify differentially methylated genes (DMGs) in cfDNA, which were subsequently validated in two independent mPCa (cfDNA and FFPE tissue) cohorts. Individual cfDNA global methylation patterns were temporally stable throughout the disease course. However, a proportion of CpG sites presented a dynamic temporal pattern that was consistent with clinical events, including different therapies, and were prominently associated with genes linked to immune response pathways. Additionally, study of the tumour fraction of cfDNA identified > 2000 DMGs with dynamic methylation patterns. Conclusions Longitudinal assessment of cfDNA methylation in mPCa patients unveiled dynamic patterns associated with disease progression and therapy administration, thus highlighting the potential of using liquid biopsies to study PCa evolution at a methylomic level. ![]()
Supplementary Information The online version contains supplementary material available at 10.1186/s13148-021-01155-w.
Collapse
Affiliation(s)
- Romina Silva
- Cancer Biology and Therapeutics Laboratory, UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland.,School of Medicine, University College Dublin, Dublin, Ireland.,School of Biology and Environmental Science, Science West, O'Brien Science Centre, University College Dublin, Dublin, Ireland
| | - Bruce Moran
- Department of Pathology, St. Vincent's University Hospital, Dublin, Ireland
| | - Anne-Marie Baird
- Department of Clinical Medicine, Trinity College, Dublin, Ireland
| | - Colm J O'Rourke
- Biotech Research and Innovation Centre, Department of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Stephen P Finn
- Department of Clinical Medicine, Trinity College, Dublin, Ireland.,Department of Histopathology, St James's Hospital, Dublin, Ireland
| | - Ray McDermott
- Cancer Trials Ireland, Dublin, Ireland.,Department of Medical Oncology, St. Vincent's University Hospital, Dublin, Ireland
| | - William Watson
- School of Medicine, University College Dublin, Dublin, Ireland
| | - William M Gallagher
- Cancer Biology and Therapeutics Laboratory, UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland.,School of Biomolecular and Biomedical Science, University College Dublin, Dublin, Ireland
| | - Donal J Brennan
- Cancer Biology and Therapeutics Laboratory, UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland.,School of Medicine, University College Dublin, Dublin, Ireland
| | - Antoinette S Perry
- Cancer Biology and Therapeutics Laboratory, UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland. .,School of Biology and Environmental Science, Science West, O'Brien Science Centre, University College Dublin, Dublin, Ireland.
| |
Collapse
|
12
|
Gordevicius J, Li P, Marshall LL, Killinger BA, Lang S, Ensink E, Kuhn NC, Cui W, Maroof N, Lauria R, Rueb C, Siebourg-Polster J, Maliver P, Lamp J, Vega I, Manfredsson FP, Britschgi M, Labrie V. Epigenetic inactivation of the autophagy-lysosomal system in appendix in Parkinson's disease. Nat Commun 2021; 12:5134. [PMID: 34446734 PMCID: PMC8390554 DOI: 10.1038/s41467-021-25474-x] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 08/04/2021] [Indexed: 12/13/2022] Open
Abstract
The gastrointestinal tract may be a site of origin for α-synuclein pathology in idiopathic Parkinson's disease (PD). Disruption of the autophagy-lysosome pathway (ALP) may contribute to α-synuclein aggregation. Here we examined epigenetic alterations in the ALP in the appendix by deep sequencing DNA methylation at 521 ALP genes. We identified aberrant methylation at 928 cytosines affecting 326 ALP genes in the appendix of individuals with PD and widespread hypermethylation that is also seen in the brain of individuals with PD. In mice, we find that DNA methylation changes at ALP genes induced by chronic gut inflammation are greatly exacerbated by α-synuclein pathology. DNA methylation changes at ALP genes induced by synucleinopathy are associated with the ALP abnormalities observed in the appendix of individuals with PD specifically involving lysosomal genes. Our work identifies epigenetic dysregulation of the ALP which may suggest a potential mechanism for accumulation of α-synuclein pathology in idiopathic PD.
Collapse
Affiliation(s)
- Juozas Gordevicius
- Center for Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA.
- Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania.
| | - Peipei Li
- Center for Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA
| | - Lee L Marshall
- Center for Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA
| | - Bryan A Killinger
- Center for Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA
- Graduate College, Rush University Medical Center, Chicago, IL, USA
| | - Sean Lang
- Center for Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA
| | - Elizabeth Ensink
- Center for Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA
| | - Nathan C Kuhn
- Department of Translational Neuroscience, College of Human Medicine, Michigan State University, Grand Rapids, MI, USA
| | - Wei Cui
- Center for Epigenetics, Van Andel Institute, Grand Rapids, MI, USA
| | - Nazia Maroof
- Roche Pharma Research and Early Development, Neuroscience Discovery, Roche Innovation Center, Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Roberta Lauria
- Roche Pharma Research and Early Development, Neuroscience Discovery, Roche Innovation Center, Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Christina Rueb
- Roche Pharma Research and Early Development, Neuroscience Discovery, Roche Innovation Center, Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Juliane Siebourg-Polster
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Pierre Maliver
- Roche Pharma Research and Early Development, Pharmaceutical Sciences, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Jared Lamp
- Department of Translational Neuroscience, College of Human Medicine, Michigan State University, Grand Rapids, MI, USA
- Integrated Mass Spectrometry Unit, College of Human Medicine, Michigan State University, Grand Rapids, MI, USA
| | - Irving Vega
- Department of Translational Neuroscience, College of Human Medicine, Michigan State University, Grand Rapids, MI, USA
- Integrated Mass Spectrometry Unit, College of Human Medicine, Michigan State University, Grand Rapids, MI, USA
| | - Fredric P Manfredsson
- Department of Translational Neuroscience, College of Human Medicine, Michigan State University, Grand Rapids, MI, USA
- Parkinson's Disease Research Unit, Department of Neurobiology, Barrow Neurological Institute, Phoenix, AZ, USA
| | - Markus Britschgi
- Roche Pharma Research and Early Development, Neuroscience Discovery, Roche Innovation Center, Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Viviane Labrie
- Center for Neurodegenerative Science, Van Andel Institute, Grand Rapids, MI, USA
- Division of Psychiatry and Behavioral Medicine, College of Human Medicine, Michigan State University, Grand Rapids, MI, USA
| |
Collapse
|
13
|
Ghildayal N, Fore R, Lutz SM, Cardenas A, Perron P, Bouchard L, Hivert MF. Early-pregnancy maternal body mass index is associated with common DNA methylation markers in cord blood and placenta: a paired-tissue epigenome-wide association study. Epigenetics 2021; 17:808-818. [PMID: 34384032 DOI: 10.1080/15592294.2021.1959975] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
Women entering pregnancy with elevated body mass index (BMI) face greater risk of adverse outcomes during pregnancy, delivery, and for their offspring later in life, potentially via epigenetics. If epigenetic programming occurs early during in utero development, the differential marks should be detectable in multiple tissues despite the known unique epigenetic profile in each.We used early-pregnancy BMI as reflection of maternal metabolic milieu exposure in peri-conception and early-pregnancy period. We analysed DNA methylation in paired cord blood and placenta samples among 437 newborns from Gen3G, a pre-birth prospective cohort of primarily European descent. We measured DNA methylation in both tissues across the genome in >720,000 CpG sites using the Illumina MethylationEPIC array. At each site, we used linear mixed models (LMMs) with an unstructured variance-covariance matrix to test for an association between maternal early-pregnancy BMI and DNA methylation in both tissues (modelled as M-values). We adjusted for tissue-specific covariates, offspring sex, gestational age at delivery, and maternal smoking and age.Women had a mean (SD) BMI of 25.4 (5.7) kg/m2 measured at first trimester visit (mean=9.9 weeks). Early-pregnancy BMI was associated with differential DNA methylation levels in paired-tissue analyses at two sites: cg10593758 (β=0.0126, SE=0.0025; P=4.07e-7), annotated to CRHBP, and cg0762168 (β=-0.0094, SE=0.0018; P=2.78e-7), annotated to CCDC97.Application of LMMs in DNA methylation data from distinct fetal-origin tissues allowed us to identify CpG sites at which early-pregnancy BMI may have an epigenetic 'programming' effect on overall fetus development. One site (CRHBP) may play a role in hypothalamic-pituitary-adrenal axis regulation.
Collapse
Affiliation(s)
- Nidhi Ghildayal
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, United States of America
| | - Ruby Fore
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, United States of America
| | - Sharon M Lutz
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, United States of America.,Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States of America
| | - Andres Cardenas
- Division of Environmental Health Sciences, School of Public Health & Center for Computational Biology, University of California, Berkeley, CA, United States of America
| | - Patrice Perron
- Department of Medicine, Faculté De Médecine Et Des Sciences De La Santé, Université De Sherbrooke, Sherbrooke, Canada.,Centre De Recherche Du Centre Hospitalier Universitaire De Sherbrooke, Sherbrooke, Canada
| | - Luigi Bouchard
- Centre De Recherche Du Centre Hospitalier Universitaire De Sherbrooke, Sherbrooke, Canada.,Department of Biochemistry and Functional Genomics, Faculté De Médecine Et Des Sciences De La Santé, University De Sherbrooke, Sherbrooke, Canada.,Department of Medical Biology, CIUSSS Du Saguenay-Lac-Saint-Jean, Hôpital De Chicoutimi, Saguenay, Canada
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, United States of America.,Department of Medicine, Faculté De Médecine Et Des Sciences De La Santé, Université De Sherbrooke, Sherbrooke, Canada.,Diabetes Unit, Massachusetts General Hospital, and Harvard Medical School, Boston, MA, United States of America
| |
Collapse
|
14
|
Jones AR, Iacoangeli A, Adey BN, Bowles H, Shatunov A, Troakes C, Garson JA, McCormick AL, Al-Chalabi A. A HML6 endogenous retrovirus on chromosome 3 is upregulated in amyotrophic lateral sclerosis motor cortex. Sci Rep 2021; 11:14283. [PMID: 34253796 PMCID: PMC8275748 DOI: 10.1038/s41598-021-93742-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2021] [Accepted: 05/21/2021] [Indexed: 02/06/2023] Open
Abstract
There is increasing evidence that endogenous retroviruses (ERVs) play a significant role in central nervous system diseases, including amyotrophic lateral sclerosis (ALS). Studies of ALS have consistently identified retroviral enzyme reverse transcriptase activity in patients. Evidence indicates that ERVs are the cause of reverse transcriptase activity in ALS, but it is currently unclear whether this is due to a specific ERV locus or a family of ERVs. We employed a combination of bioinformatic methods to identify whether specific ERVs or ERV families are associated with ALS. Using the largest post-mortem RNA-sequence datasets available we selectively identified ERVs that closely resembled full-length proviruses. In the discovery dataset there was one ERV locus (HML6_3p21.31c) that showed significant increased expression in post-mortem motor cortex tissue after multiple-testing correction. Using six replication post-mortem datasets we found HML6_3p21.31c was consistently upregulated in ALS in motor cortex and cerebellum tissue. In addition, HML6_3p21.31c showed significant co-expression with cytokine binding and genes involved in EBV, HTLV-1 and HIV type-1 infections. There were no significant differences in ERV family expression between ALS and controls. Our results support the hypothesis that specific ERV loci are involved in ALS pathology.
Collapse
Affiliation(s)
- Ashley R. Jones
- grid.13097.3c0000 0001 2322 6764Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, SE5 9NU UK
| | - Alfredo Iacoangeli
- grid.13097.3c0000 0001 2322 6764Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, SE5 9NU UK ,grid.13097.3c0000 0001 2322 6764Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK ,grid.451056.30000 0001 2116 3923National Institute for Health Research Biomedical Research Centre and Dementia Unit at South London and Maudsley NHS Foundation Trust and King’s College London, London, UK
| | - Brett N. Adey
- grid.13097.3c0000 0001 2322 6764Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK ,grid.13097.3c0000 0001 2322 6764Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK ,grid.13097.3c0000 0001 2322 6764NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Trust, King’s College London, London, UK
| | - Harry Bowles
- grid.13097.3c0000 0001 2322 6764Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, SE5 9NU UK ,grid.13097.3c0000 0001 2322 6764Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK ,grid.451056.30000 0001 2116 3923National Institute for Health Research Biomedical Research Centre and Dementia Unit at South London and Maudsley NHS Foundation Trust and King’s College London, London, UK ,grid.451056.30000 0001 2116 3923National Institute for Health Research Biomedical Research Centre at Guy’s and St Thomas’ NHS Foundation Trust and King’s College London, London, UK
| | - Aleksey Shatunov
- grid.13097.3c0000 0001 2322 6764Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, SE5 9NU UK
| | - Claire Troakes
- grid.13097.3c0000 0001 2322 6764MRC London Neurodegenerative Diseases Brain Bank, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Jeremy A. Garson
- grid.83440.3b0000000121901201Division of Infection and Immunity, University College London, London, UK
| | - Adele L. McCormick
- grid.12896.340000 0000 9046 8598School of Life Sciences, University of Westminster, London, UK
| | - Ammar Al-Chalabi
- grid.13097.3c0000 0001 2322 6764Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, SE5 9NU UK
| |
Collapse
|
15
|
Bermejo JL, Huang G, Manoochehri M, Mesa KG, Schick M, Silos RG, Ko YD, Brüning T, Brauch H, Lo WY, Hoheisel JD, Hamann U. Long intergenic noncoding RNA 299 methylation in peripheral blood is a biomarker for triple-negative breast cancer. Epigenomics 2019; 11:81-93. [DOI: 10.2217/epi-2018-0121] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Aim: To identify DNA methylation biomarkers in peripheral blood samples from triple-negative breast cancer (TNBC) patients. Materials & methods: We conducted an epigenome-wide association study (EWAS): the most promising markers were identified in 233 TNBC case–control pairs (discovery set) and subsequently validated in an independent validation set (57 TNBC patients and 124 controls). Results: cg06588802 (LINC00299/ID2) showed a higher methylation in TNBC patients compared with controls (discovery set: 3% increase, p-value = 0.0009; validation set: 2% increase, p-value = 0.01). Consistent results at four neighboring methylation probes and the strong negative correlation (rho = -0.93) with LINC00299 expression add plausibility to this result. Conclusion: Hypermethylation of LINC00299 in peripheral blood may constitute a useful circulating biomarker for TNBC.
Collapse
Affiliation(s)
- Justo L Bermejo
- Statistical Genetics Group, Institute of Medical Biometry & Informatics, University of Heidelberg, Heidelberg, 69120, Germany
| | - Guanmengqian Huang
- Department of Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany
| | - Mehdi Manoochehri
- Department of Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany
| | - Karen G Mesa
- Statistical Genetics Group, Institute of Medical Biometry & Informatics, University of Heidelberg, Heidelberg, 69120, Germany
- Department of Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany
| | - Matthias Schick
- Genomics & Proteomics Core Facility, Microarray Unit, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany
| | - Rosa G Silos
- Statistical Genetics Group, Institute of Medical Biometry & Informatics, University of Heidelberg, Heidelberg, 69120, Germany
| | - Yon-Dschun Ko
- Department of Internal Medicine, Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus, Bonn, 53113, Germany
| | - Thomas Brüning
- Institute for Prevention & Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bochum, 44789, Germany
| | - Hiltrud Brauch
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, 70376, Germany
- Department of Clinical Pharmacology, University of Tübingen, Tübingen, 70376, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany
| | - Wing-Yee Lo
- Dr. Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, 70376, Germany
- Department of Clinical Pharmacology, University of Tübingen, Tübingen, 70376, Germany
| | - Jörg D Hoheisel
- Division of Functional Genome Analysis, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany
| | - Ute Hamann
- Department of Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, 69120, Germany
| |
Collapse
|