Search

Search Results

Zenodo Logo
Zenodo
Taschereau, Amélie; Bouchard, Luigi 2023-06-29 Taschereau, A., Thibeault, K., Allard, C., Juvinao-Quintero, D., Perron, P., Lutz, S. M., Bouchard, L., & Hivert, M. F. (2023). Maternal glycemia in pregnancy is longitudinally associated with blood DNAm variation at the FSD1L gene from birth to 5 years of age. Clinical epigenetics, 15(1), 107. https://doi.org/10.1186/s13148-023-01524-7 BackgroundIn utero exposure to maternal hyperglycemia has been associated with an increased risk for the development of chronic diseases in later life. These predispositions may be programmed by fetal DNA methylation (DNAm) changes that persist postnatally. However, although some studies have associated fetal exposure to gestational hyperglycemia with DNAm variations at birth, and metabolic phenotypes in childhood, no study has yet examined how maternal hyperglycemia during pregnancy may be associated with offspring DNAm from birth to five years of age. HypothesisMaternal hyperglycemia is associated with variation in offspring DNAm from birth to 5 years of age. MethodsWe estimated maternal hyperglycemia using the area under the curve for glucose (AUCglu) following an oral glucose tolerance test conducted at 24–30 weeks of pregnancy. We quantified DNAm levels in cord blood (n = 440) and peripheral blood at five years of age (n = 293) using the Infinium MethylationEPIC BeadChip (Illumina). Our total sample included 539 unique dyads (mother–child) with 194 dyads having DNAm at both time-points. We first regressed DNAm M-values against the cell types and child age for each time-point separately to account for the difference by time of measurement for these variables. We then used a random intercept model from the linear mixed model (LMM) framework to assess the longitudinal association between maternal AUCglu and the repeated measures of residuals of DNAm. We adjusted for the following covariates as fixed effects in the random intercept model: maternal age, gravidity, smoking status, child sex, maternal body mass index (BMI) (measured at first trimester of pregnancy), and a binary variable for time-point. ResultsIn utero exposure to higher maternal AUCglu was associated with lower offspring blood DNAm levels at cg00967989 located in FSD1L gene (β = − 0.0267, P = 2.13 × 10–8) in adjusted linear regression mixed models. Our study also reports other CpG sites for which DNAm levels were suggestively associated (P < 1.0 × 10–5) with in utero exposure to gestational hyperglycemia. Two of these (cg12140144 and cg07946633) were found in the promotor region of PRDM16 gene (β: − 0.0251, P = 4.37 × 10–07 and β: − 0.0206, P = 2.24 × 10–06, respectively). ConclusionMaternal hyperglycemia is associated with offspring DNAm longitudinally assessed from birth to 5 years of age. https://creativecommons.org/licenses/by/4.0/legalcode
Figshare Logo
Taylor & Francis
Ma, Baoshan; Allard, Catherine; Bouchard, Luigi; Perron, Patrice; Mittleman, Murray A.; Hivert, Marie-France; Liang, Liming 2023 DNA methylation is known to be responsive to prenatal exposures, which may be a part of the mechanism linking early developmental exposures to future chronic diseases. Many studies use blood to measure DNA methylation, yet we know that DNA methylation is tissue specific. Placenta is central to fetal growth and development, but it is rarely feasible to collect this tissue in large epidemiological studies; on the other hand, cord blood samples are more accessible. In this study, based on paired samples of both placenta and cord blood tissues from 169 individuals, we investigated the methylation concordance between placenta and cord blood. We then employed a machine-learning-based model to predict locus-specific DNA methylation levels in placenta using DNA methylation levels in cord blood. We found that methylation correlation between placenta and cord blood is lower than other tissue pairs, consistent with existing observations that placenta methylation has a distinct pattern. Nonetheless, there are still a number of CpG sites showing robust association between the two tissues. We built prediction models for placenta methylation based on cord blood data and documented a subset of 1,012 CpG sites with high correlation between measured and predicted placenta methylation levels. The resulting list of CpG sites and prediction models could help to reveal the loci where internal or external influences may affect DNA methylation in both placenta and cord blood, and provide a reference data to predict the effects on placenta in future study even when the tissue is not available in an epidemiological study. https://creativecommons.org/licenses/by/4.0/legalcode
Figshare Logo
Taylor & Francis
Clément, Andrée-Anne; Lamarche, Daphnée; Masse, Marie-Hélène; Légaré, Cécilia; Tai, Lee-Hwa; Deland, Laurence Fleury; Battista, Marie-Claude; Bouchard, Luigi; D’Aragon, Frédérick 2022 Neurologically deceased organ donors (NDDs) generally display an immune response involving an intense production of pro-inflammatory cytokines referred to as the cytokine storm. The sudden surge of inflammatory mediators in circulation promotes tissue and organ damages and ultimately leads to poor transplant outcome. As microRNAs (miRNAs) are frequently proposed as key regulators of inflammation and are relatively stable in circulation, changes in their profiles could play a role in the onset of the cytokine storm in NDDs. In this proof-of-concept study, we sought to investigate differentially abundant circulating miRNAs in a temporal manner between neurological death and organ recovery and to assess the association between specific miRNAs and levels of inflammatory cytokines in blood. Plasma samples from five NDDs were obtained at multiple time points between organ donation consent and organ recovery. Using a time-course analysis and miRNA sequencing, we identified 32 plasma miRNAs fluctuating between consent and organ recovery (false discovery rate; q-value &lt; 0.1). Eleven miRNAs relatively abundant (&gt;100 reads) and detected in all samples were selected for further biological pathway analysis (miR-486-3p, miR-103a-3p, miR-106b-3p, miR-182-5p, miR-101-3p, miR-10a-5p, miR-125a-5p, miR-146b-5p, miR-26a-5p, miR-423-5p, miR-92b-3p). These miRNAs targeted genes such as <i>c-JUN</i> (TNF signalling pathway) and <i>eEF2</i> (AMPK pathway), suggesting a potential role in regulation of inflammation. Our results contribute to a better understanding of the miRNAs dynamic after neurological death in organ donors and could potentially be used to predict the related early cytokine storm.<b>Trial registration</b>: ClinicalTrials.gov ID NCT03786991. Registered December 2018 https://creativecommons.org/licenses/by/4.0/legalcode
Figshare Logo
figshare
Kadalayil, Latha; Alam, Md. Zahangir; White, Cory Haley; Ghantous, Akram; Walton, Esther; Gruzieva, Olena; Merid, Simon Kebede; Kumar, Ashish; Roy, Ritu P.; Solomon, Olivia; Huen, Karen; Eskenazi, Brenda; Rzehak, Peter; Grote, Veit; Langhendries, Jean-Paul; Verduci, Elvira; Ferre, Natalia; Gruszfeld, Darek; Gao, Lu; Guan, Weihua; Zeng, Xuehuo; Schisterman, Enrique F.; Dou, John F.; Bakulski, Kelly M.; Feinberg, Jason I.; Soomro, Munawar Hussain; Pesce, Giancarlo; Baiz, Nour; Isaevska, Elena; Plusquin, Michelle; Vafeiadi, Marina; Roumeliotaki, Theano; Langie, Sabine A. S.; Standaert, Arnout; Allard, Catherine; Perron, Patrice; Bouchard, Luigi; van Meel, Evelien R.; Felix, Janine F.; Jaddoe, Vincent W. V.; Yousefi, Paul D.; Ramlau-Hansen, Cecilia H.; Relton, Caroline L.; Tobi, Elmar W.; Starling, Anne P.; Yang, Ivana V.; Llambrich, Maria; Santorelli, Gillian; Lepeule, Johanna; Salas, Lucas A.; Bustamante, Mariona; Ewart, Susan L.; Zhang, Hongmei; Karmaus, Wilfried; Röder, Stefan; Zenclussen, Ana Claudia; Jin, Jianping; Nystad, Wenche; Page, Christian M.; Magnus, Maria; Jima, Dereje D.; Hoyo, Cathrine; Maguire, Rachel L.; Kvist, Tuomas; Czamara, Darina; Räikkönen, Katri; Gong, Tong; Ullemar, Vilhelmina; Rifas-Shiman, Sheryl L.; Oken, Emily; Almqvist, Catarina; Karlsson, Robert; Lahti, Jari; Murphy, Susan K.; Håberg, Siri E.; London, Stephanie; Herberth, Gunda; Arshad, Hasan; Sunyer, Jordi; Grazuleviciene, Regina; Dabelea, Dana; Steegers-Theunissen, Régine P. M.; Nohr, Ellen A.; Sørensen, Thorkild I. A.; Duijts, Liesbeth; Hivert, Marie-France; Nelen, Vera; Popovic, Maja; Kogevinas, Manolis; Nawrot, Tim S.; Herceg, Zdenko; Annesi-Maesano, Isabella; Fallin, M. Daniele; Yeung, Edwina; Breton, Carrie V.; Koletzko, Berthold; Holland, Nina; Wiemels, Joseph L.; Melén, Erik; Sharp, Gemma C.; Silver, Matt J.; Rezwan, Faisal I.; Holloway, John W. 2023 Additional file 1. Table S1: “Summary of the studies in the meta-analysis for the association between Season of Birth and DNA methylation at birth and in children (age: 1 to 11 years)”. Baseline summary of participants from each of the individual cohorts. https://creativecommons.org/licenses/by/4.0/legalcode
Figshare Logo
figshare
Kadalayil, Latha; Alam, Md. Zahangir; White, Cory Haley; Ghantous, Akram; Walton, Esther; Gruzieva, Olena; Merid, Simon Kebede; Kumar, Ashish; Roy, Ritu P.; Solomon, Olivia; Huen, Karen; Eskenazi, Brenda; Rzehak, Peter; Grote, Veit; Langhendries, Jean-Paul; Verduci, Elvira; Ferre, Natalia; Gruszfeld, Darek; Gao, Lu; Guan, Weihua; Zeng, Xuehuo; Schisterman, Enrique F.; Dou, John F.; Bakulski, Kelly M.; Feinberg, Jason I.; Soomro, Munawar Hussain; Pesce, Giancarlo; Baiz, Nour; Isaevska, Elena; Plusquin, Michelle; Vafeiadi, Marina; Roumeliotaki, Theano; Langie, Sabine A. S.; Standaert, Arnout; Allard, Catherine; Perron, Patrice; Bouchard, Luigi; van Meel, Evelien R.; Felix, Janine F.; Jaddoe, Vincent W. V.; Yousefi, Paul D.; Ramlau-Hansen, Cecilia H.; Relton, Caroline L.; Tobi, Elmar W.; Starling, Anne P.; Yang, Ivana V.; Llambrich, Maria; Santorelli, Gillian; Lepeule, Johanna; Salas, Lucas A.; Bustamante, Mariona; Ewart, Susan L.; Zhang, Hongmei; Karmaus, Wilfried; Röder, Stefan; Zenclussen, Ana Claudia; Jin, Jianping; Nystad, Wenche; Page, Christian M.; Magnus, Maria; Jima, Dereje D.; Hoyo, Cathrine; Maguire, Rachel L.; Kvist, Tuomas; Czamara, Darina; Räikkönen, Katri; Gong, Tong; Ullemar, Vilhelmina; Rifas-Shiman, Sheryl L.; Oken, Emily; Almqvist, Catarina; Karlsson, Robert; Lahti, Jari; Murphy, Susan K.; Håberg, Siri E.; London, Stephanie; Herberth, Gunda; Arshad, Hasan; Sunyer, Jordi; Grazuleviciene, Regina; Dabelea, Dana; Steegers-Theunissen, Régine P. M.; Nohr, Ellen A.; Sørensen, Thorkild I. A.; Duijts, Liesbeth; Hivert, Marie-France; Nelen, Vera; Popovic, Maja; Kogevinas, Manolis; Nawrot, Tim S.; Herceg, Zdenko; Annesi-Maesano, Isabella; Fallin, M. Daniele; Yeung, Edwina; Breton, Carrie V.; Koletzko, Berthold; Holland, Nina; Wiemels, Joseph L.; Melén, Erik; Sharp, Gemma C.; Silver, Matt J.; Rezwan, Faisal I.; Holloway, John W. 2023 Additional file 5. Table S4: “Direction of differential methylation of CpGs in DMRs of the at-birth and childhood analyses (preliminary analysis”). https://creativecommons.org/licenses/by/4.0/legalcode
Figshare Logo
figshare
Kadalayil, Latha; Alam, Md. Zahangir; White, Cory Haley; Ghantous, Akram; Walton, Esther; Gruzieva, Olena; Merid, Simon Kebede; Kumar, Ashish; Roy, Ritu P.; Solomon, Olivia; Huen, Karen; Eskenazi, Brenda; Rzehak, Peter; Grote, Veit; Langhendries, Jean-Paul; Verduci, Elvira; Ferre, Natalia; Gruszfeld, Darek; Gao, Lu; Guan, Weihua; Zeng, Xuehuo; Schisterman, Enrique F.; Dou, John F.; Bakulski, Kelly M.; Feinberg, Jason I.; Soomro, Munawar Hussain; Pesce, Giancarlo; Baiz, Nour; Isaevska, Elena; Plusquin, Michelle; Vafeiadi, Marina; Roumeliotaki, Theano; Langie, Sabine A. S.; Standaert, Arnout; Allard, Catherine; Perron, Patrice; Bouchard, Luigi; van Meel, Evelien R.; Felix, Janine F.; Jaddoe, Vincent W. V.; Yousefi, Paul D.; Ramlau-Hansen, Cecilia H.; Relton, Caroline L.; Tobi, Elmar W.; Starling, Anne P.; Yang, Ivana V.; Llambrich, Maria; Santorelli, Gillian; Lepeule, Johanna; Salas, Lucas A.; Bustamante, Mariona; Ewart, Susan L.; Zhang, Hongmei; Karmaus, Wilfried; Röder, Stefan; Zenclussen, Ana Claudia; Jin, Jianping; Nystad, Wenche; Page, Christian M.; Magnus, Maria; Jima, Dereje D.; Hoyo, Cathrine; Maguire, Rachel L.; Kvist, Tuomas; Czamara, Darina; Räikkönen, Katri; Gong, Tong; Ullemar, Vilhelmina; Rifas-Shiman, Sheryl L.; Oken, Emily; Almqvist, Catarina; Karlsson, Robert; Lahti, Jari; Murphy, Susan K.; Håberg, Siri E.; London, Stephanie; Herberth, Gunda; Arshad, Hasan; Sunyer, Jordi; Grazuleviciene, Regina; Dabelea, Dana; Steegers-Theunissen, Régine P. M.; Nohr, Ellen A.; Sørensen, Thorkild I. A.; Duijts, Liesbeth; Hivert, Marie-France; Nelen, Vera; Popovic, Maja; Kogevinas, Manolis; Nawrot, Tim S.; Herceg, Zdenko; Annesi-Maesano, Isabella; Fallin, M. Daniele; Yeung, Edwina; Breton, Carrie V.; Koletzko, Berthold; Holland, Nina; Wiemels, Joseph L.; Melén, Erik; Sharp, Gemma C.; Silver, Matt J.; Rezwan, Faisal I.; Holloway, John W. 2023 Additional file 6. Table S5: “Genes mapped to DMP/DMR identified in at-birth samples of babies born in the latitude ≥ 50°N and some examples of their associations with biological functions”. Provides examples of known functional associations of genes mapped to significant CpG sites or differentially methylated regions identified in this study. https://creativecommons.org/licenses/by/4.0/legalcode
Figshare Logo
figshare
Kadalayil, Latha; Alam, Md. Zahangir; White, Cory Haley; Ghantous, Akram; Walton, Esther; Gruzieva, Olena; Merid, Simon Kebede; Kumar, Ashish; Roy, Ritu P.; Solomon, Olivia; Huen, Karen; Eskenazi, Brenda; Rzehak, Peter; Grote, Veit; Langhendries, Jean-Paul; Verduci, Elvira; Ferre, Natalia; Gruszfeld, Darek; Gao, Lu; Guan, Weihua; Zeng, Xuehuo; Schisterman, Enrique F.; Dou, John F.; Bakulski, Kelly M.; Feinberg, Jason I.; Soomro, Munawar Hussain; Pesce, Giancarlo; Baiz, Nour; Isaevska, Elena; Plusquin, Michelle; Vafeiadi, Marina; Roumeliotaki, Theano; Langie, Sabine A. S.; Standaert, Arnout; Allard, Catherine; Perron, Patrice; Bouchard, Luigi; van Meel, Evelien R.; Felix, Janine F.; Jaddoe, Vincent W. V.; Yousefi, Paul D.; Ramlau-Hansen, Cecilia H.; Relton, Caroline L.; Tobi, Elmar W.; Starling, Anne P.; Yang, Ivana V.; Llambrich, Maria; Santorelli, Gillian; Lepeule, Johanna; Salas, Lucas A.; Bustamante, Mariona; Ewart, Susan L.; Zhang, Hongmei; Karmaus, Wilfried; Röder, Stefan; Zenclussen, Ana Claudia; Jin, Jianping; Nystad, Wenche; Page, Christian M.; Magnus, Maria; Jima, Dereje D.; Hoyo, Cathrine; Maguire, Rachel L.; Kvist, Tuomas; Czamara, Darina; Räikkönen, Katri; Gong, Tong; Ullemar, Vilhelmina; Rifas-Shiman, Sheryl L.; Oken, Emily; Almqvist, Catarina; Karlsson, Robert; Lahti, Jari; Murphy, Susan K.; Håberg, Siri E.; London, Stephanie; Herberth, Gunda; Arshad, Hasan; Sunyer, Jordi; Grazuleviciene, Regina; Dabelea, Dana; Steegers-Theunissen, Régine P. M.; Nohr, Ellen A.; Sørensen, Thorkild I. A.; Duijts, Liesbeth; Hivert, Marie-France; Nelen, Vera; Popovic, Maja; Kogevinas, Manolis; Nawrot, Tim S.; Herceg, Zdenko; Annesi-Maesano, Isabella; Fallin, M. Daniele; Yeung, Edwina; Breton, Carrie V.; Koletzko, Berthold; Holland, Nina; Wiemels, Joseph L.; Melén, Erik; Sharp, Gemma C.; Silver, Matt J.; Rezwan, Faisal I.; Holloway, John W. 2023 Additional file 8. Table S8: “Genes mapped to DMR identified in the childhood samples of children born in the latitude ≥ 50°N and some examples of their associations with biological functions”. Provides examples of known functional associations of genes mapped to significant differentially methylated regions identified in this study. https://creativecommons.org/licenses/by/4.0/legalcode
Figshare Logo
figshare
Borges, Maria Carolina; Clayton, Gemma L.; Freathy, Rachel M.; Felix, Janine F.; Fernández-Sanlés, Alba; Soares, Ana Gonçalves; Kilpi, Fanny; Yang, Qian; McEachan, Rosemary R. C.; Richmond, Rebecca C.; Liu, Xueping; Skotte, Line; Irizar, Amaia; Hattersley, Andrew T.; Bodinier, Barbara; Scholtens, Denise M.; Nohr, Ellen A.; Bond, Tom A.; Hayes, M. Geoffrey; West, Jane; Tyrrell, Jessica; Wright, John; Bouchard, Luigi; Murcia, Mario; Bustamante, Mariona; Chadeau-Hyam, Marc; Jarvelin, Marjo-Riitta; Vrijheid, Martine; Perron, Patrice; Magnus, Per; Gaillard, Romy; Jaddoe, Vincent W. V.; Lowe, William L.; Feenstra, Bjarke; Hivert, Marie-France; Sørensen, Thorkild I. A.; Håberg, Siri E.; Serbert, Sylvain; Magnus, Maria; Lawlor, Deborah A. 2024 Additional file 2. Supplementary tables. https://creativecommons.org/licenses/by/4.0/legalcode