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      Maternal Glycaemic and Insulinemic Status and Newborn DNA Methylation: Findings in Women With Overweight and Obesity

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          Abstract

          Context

          Maternal dysglycaemia and prepregnancy obesity are associated with adverse offspring outcomes. Epigenetic mechanisms such as DNA methylation (DNAm) could contribute.

          Objective

          To examine relationships between maternal glycaemia, insulinemic status, and dietary glycemic indices during pregnancy and an antenatal behavioral-lifestyle intervention with newborn DNAm.

          Methods

          We investigated 172 women from a randomized controlled trial of a lifestyle intervention in pregnant women who were overweight or obese. Fasting glucose and insulin concentrations and derived indices of insulin resistance (HOMA-IR), β-cell function (HOMA-%B), and insulin sensitivity were determined at baseline (15) and 28 weeks’ gestation. Dietary glycemic load (GL) and index (GI) were calculated from 3-day food diaries. Newborn cord blood DNAm levels of 850K CpG sites were measured using the Illumina Infinium HumanMethylationEPIC array. Associations of each biomarker, dietary index and intervention with DNAm were examined.

          Results

          Early pregnancy HOMA-IR and HOMA-%B were associated with lower DNAm at CpG sites cg03158092 and cg05985988, respectively. Early pregnancy insulin sensitivity was associated with higher DNAm at cg04976151. Higher late pregnancy insulin concentrations and GL scores were positively associated with DNAm at CpGs cg12082129 and cg11955198 and changes in maternal GI with lower DNAm at CpG cg03403995 (Bonferroni corrected P < 5.99 × 10 −8). These later associations were located at genes previously implicated in growth or regulation of insulin processes. No effects of the intervention on cord blood DNAm were observed. None of our findings were replicated in previous studies.

          Conclusion

          Among women who were overweight or obese, maternal pregnancy dietary glycemic indices, glucose, and insulin homeostasis were associated with modest changes in their newborn methylome.

          Trial registration

          ISRCTN29316280

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          Most cited references63

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          The Human Genome Browser at UCSC

          As vertebrate genome sequences near completion and research refocuses to their analysis, the issue of effective genome annotation display becomes critical. A mature web tool for rapid and reliable display of any requested portion of the genome at any scale, together with several dozen aligned annotation tracks, is provided at http://genome.ucsc.edu. This browser displays assembly contigs and gaps, mRNA and expressed sequence tag alignments, multiple gene predictions, cross-species homologies, single nucleotide polymorphisms, sequence-tagged sites, radiation hybrid data, transposon repeats, and more as a stack of coregistered tracks. Text and sequence-based searches provide quick and precise access to any region of specific interest. Secondary links from individual features lead to sequence details and supplementary off-site databases. One-half of the annotation tracks are computed at the University of California, Santa Cruz from publicly available sequence data; collaborators worldwide provide the rest. Users can stably add their own custom tracks to the browser for educational or research purposes. The conceptual and technical framework of the browser, its underlying MYSQL database, and overall use are described. The web site currently serves over 50,000 pages per day to over 3000 different users.
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            The GeneCards Suite: From Gene Data Mining to Disease Genome Sequence Analyses.

            GeneCards, the human gene compendium, enables researchers to effectively navigate and inter-relate the wide universe of human genes, diseases, variants, proteins, cells, and biological pathways. Our recently launched Version 4 has a revamped infrastructure facilitating faster data updates, better-targeted data queries, and friendlier user experience. It also provides a stronger foundation for the GeneCards suite of companion databases and analysis tools. Improved data unification includes gene-disease links via MalaCards and merged biological pathways via PathCards, as well as drug information and proteome expression. VarElect, another suite member, is a phenotype prioritizer for next-generation sequencing, leveraging the GeneCards and MalaCards knowledgebase. It automatically infers direct and indirect scored associations between hundreds or even thousands of variant-containing genes and disease phenotype terms. VarElect's capabilities, either independently or within TGex, our comprehensive variant analysis pipeline, help prepare for the challenge of clinical projects that involve thousands of exome/genome NGS analyses. © 2016 by John Wiley & Sons, Inc.
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              Quantitative insulin sensitivity check index: a simple, accurate method for assessing insulin sensitivity in humans.

              Insulin resistance plays an important role in the pathophysiology of diabetes and is associated with obesity and other cardiovascular risk factors. The "gold standard" glucose clamp and minimal model analysis are two established methods for determining insulin sensitivity in vivo, but neither is easily implemented in large studies. Thus, it is of interest to develop a simple, accurate method for assessing insulin sensitivity that is useful for clinical investigations. We performed both hyperinsulinemic isoglycemic glucose clamp and insulin-modified frequently sampled iv glucose tolerance tests on 28 nonobese, 13 obese, and 15 type 2 diabetic subjects. We obtained correlations between indexes of insulin sensitivity from glucose clamp studies (SI(Clamp)) and minimal model analysis (SI(MM)) that were comparable to previous reports (r = 0.57). We performed a sensitivity analysis on our data and discovered that physiological steady state values [i.e. fasting insulin (I(0)) and glucose (G(0))] contain critical information about insulin sensitivity. We defined a quantitative insulin sensitivity check index (QUICKI = 1/[log(I(0)) + log(G(0))]) that has substantially better correlation with SI(Clamp) (r = 0.78) than the correlation we observed between SI(MM) and SI(Clamp). Moreover, we observed a comparable overall correlation between QUICKI and SI(Clamp) in a totally independent group of 21 obese and 14 nonobese subjects from another institution. We conclude that QUICKI is an index of insulin sensitivity obtained from a fasting blood sample that may be useful for clinical research.
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                Author and article information

                Contributors
                Journal
                J Clin Endocrinol Metab
                J Clin Endocrinol Metab
                jcem
                The Journal of Clinical Endocrinology and Metabolism
                Oxford University Press (US )
                0021-972X
                1945-7197
                January 2023
                22 September 2022
                22 September 2022
                : 108
                : 1
                : 85-98
                Affiliations
                School of Public Health, Physiotherapy and Sports Science, University College Dublin , Dublin 4, Republic of Ireland
                UCD Perinatal Research Centre, School of Medicine, National Maternity Hospital, University College Dublin , Dublin, Ireland
                School of Medicine, University College Dublin , Dublin, Republic of Ireland
                School of Public Health, Physiotherapy and Sports Science, University College Dublin , Dublin 4, Republic of Ireland
                School of Public Health, Physiotherapy and Sports Science, University College Dublin , Dublin 4, Republic of Ireland
                School of Public Health, Physiotherapy and Sports Science, University College Dublin , Dublin 4, Republic of Ireland
                MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol , Bristol, UK
                School of Public Health, Physiotherapy and Sports Science, University College Dublin , Dublin 4, Republic of Ireland
                Author notes
                Correspondence: Marion Lecorguillé, PhD, School of Public Health, Physiotherapy and Sports Science, Woodview House, University College Dublin, Belfield, Dublin 4, Ireland. Email: marion.lecorguille@ 123456ucd.ie .

                Matthew Suderman and Catherine M. Phillips are joint senior authors on this work.

                Conflict of Interest The authors have nothing to disclose.

                Author information
                https://orcid.org/0000-0002-6915-533X
                https://orcid.org/0000-0002-3477-6494
                https://orcid.org/0000-0002-4229-3599
                https://orcid.org/0000-0001-9548-4914
                https://orcid.org/0000-0002-2715-9930
                https://orcid.org/0000-0003-4916-4463
                Article
                dgac553
                10.1210/clinem/dgac553
                9759168
                36137169
                ea894119-9575-4c24-93b9-776cefd6f235
                © The Author(s) 2022. Published by Oxford University Press on behalf of the Endocrine Society.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 28 April 2022
                : 16 September 2022
                : 17 October 2022
                Page count
                Pages: 14
                Funding
                Funded by: Science Foundation Ireland, doi 10.13039/501100001602;
                Award ID: SFI/16/ERA-HDHL/3360
                Funded by: National Maternity Hospital Medical Fund;
                Funded by: University College Dublin, doi 10.13039/501100001631;
                Funded by: Irish Health Research Board;
                Award ID: HRC/2007/13
                Categories
                Clinical Research Article
                AcademicSubjects/MED00250

                Endocrinology & Diabetes
                lifestyle intervention,overweight and obese pregnancy,maternal dietary glycemic indices,maternal glycaemia,insulin concentrations,dna methylation

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