Permutation-based significance analysis reduces the type 1 error rate in bisulfite sequencing data analysis of human umbilical cord blood samplesResearch Centre for Integrative Physiology and Pharmacology, Institute of Biomedicine, University of Turku, Turku, Finland.
Research Centre for Integrative Physiology and Pharmacology, Institute of Biomedicine, University of Turku, Turku, Finland.
Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland.
Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland.
Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland; Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland.
Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland; InFLAMES Research Flagship Center, University of Turku, Turku Finland.
Research Centre for Integrative Physiology and Pharmacology, Institute of Biomedicine, University of Turku, Turku, Finland; Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland; Department of Pediatrics, Turku University Hospital, Turku, Finland .
Pediatric Research Center, Children's Hospital, University of Helsinki and Helsinki University Hospital, Helsinki, Finland; Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland; Center for Child Health Research, Tampere University Hospital, Tampere, Finland.
Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland.
Turku Bioscience Centre, University of Turku and Åbo Akademi University, Turku, Finland; InFLAMES Research Flagship Center, University of Turku, Turku Finland; Institute of Biomedicine, University of Turku, Turku, Finland.
Department of Computer Science, Aalto University, Espoo, Finland.
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2022 (English)In: Epigenetics, ISSN 1559-2294, E-ISSN 1559-2308, Vol. 17, no 12, p. 1608-1627Article in journal (Refereed) Published
Abstract [en]
DNA methylation patterns are largely established in-utero and might mediate the impacts of in-utero conditions on later health outcomes. Associations between perinatal DNA methylation marks and pregnancy-related variables, such as maternal age and gestational weight gain, have been earlier studied with methylation microarrays, which typically cover less than 2% of human CpG sites. To detect such associations outside these regions, we chose the bisulphite sequencing approach. We collected and curated clinical data on 200 newborn infants; whose umbilical cord blood samples were analysed with the reduced representation bisulphite sequencing (RRBS) method. A generalized linear mixed-effects model was fit for each high coverage CpG site, followed by spatial and multiple testing adjustment of P values to identify differentially methylated cytosines (DMCs) and regions (DMRs) associated with clinical variables, such as maternal age, mode of delivery, and birth weight. Type 1 error rate was then evaluated with a permutation analysis. We discovered a strong inflation of spatially adjusted P values through the permutation analysis, which we then applied for empirical type 1 error control. The inflation of P values was caused by a common method for spatial adjustment and DMR detection, implemented in tools comb-p and RADMeth. Based on empirically estimated significance thresholds, very little differential methylation was associated with any of the studied clinical variables, other than sex. With this analysis workflow, the sex-associated differentially methylated regions were highly reproducible across studies, technologies, and statistical models.
Place, publisher, year, edition, pages
Taylor & Francis, 2022. Vol. 17, no 12, p. 1608-1627
Keywords [en]
DNA methylation, RRBS, analysis workflow, bisulphite sequencing, differential methylation, pregnancy, sex, spatial correlation, type 1 error, umbilical cord blood
National Category
Medical Genetics
Identifiers
URN: urn:nbn:se:oru:diva-97835DOI: 10.1080/15592294.2022.2044127ISI: 000764920200001PubMedID: 35246015Scopus ID: 2-s2.0-85126064394OAI: oai:DiVA.org:oru-97835DiVA, id: diva2:1642598
Funder
Academy of Finland, 340231 292335 294337 319280 31444 329277 331790 292660 311584 335436 250114 292482Novo Nordisk
Note
Funding agencies:
InFLAMES Flagship Programme of the Academy of Finland 337530
Business Finland
Juvenile Diabetes Research Foundation
Sigrid Juselius Foundation
Jane and Aatos Erkko Foundation
Finnish Diabetes Foundation
Finnish Cancer Foundation
EFSD
Pediatric Research Foundation
Turku University Hospital Special Governmental Grants
Turku Doctoral Programme of Molecular Medicine (TuDMM)
Finnish Cultural Foundation
Finnish IT center for science
Kyllikki and Uolevi Lehikoinen Foundation
2022-03-072022-03-072023-12-08Bibliographically approved