253-OR: Maternal Hyperglycemia Is Associated with Offspring Adiposity through Altered Lipid Metabolism in Type 1 Diabetes Pregnancy
Bibliographic record
Abstract
Objective: Type 1 diabetes in pregnancy is associated with increased birthweight and adiposity in offspring, which may contribute to increased future cardiometabolic risk. We assessed if the effects of maternal hyperglycemia on adiposity were mediated by altered lipid metabolism in pregnancy. Methods and Outcomes: 200 women in the Continuous Glucose Monitoring (CGM) in Pregnant women with Type 1 diabetes Trial (CONCEPTT) had a livebirth. Liquid chromatography-mass spectrometry of maternal serum (12, 24, 34 wks; n=174) and cord blood (n=93) measured 21metabolites. Anthropometry was performed at birth by trained staff. Statistical Analysis: Linear regression of CGM time above range 12, 24, 34 wks (>140 mg/dl; >7.8 mmol/l) with adjustment for maternal age, BMI, parity, ethnicity, education and intervention (birth gestation for offspring) . Significance limit was p=0.0for unselected analysis of all metabolites, p=0.for subset analysis with skinfolds. Results: Maternal hyperglycemia at 24 and 34 weeks was associated with increased triglycerides containing FA (16:0) , (16:1) , (18:0) and (18:1) in maternal serum, considered biomarkers of de novo lipogenesis. Maternal hyperglycemia was associated with abundant carnitines in cord blood, suggesting increased fetal beta oxidation. Lipogenesis-associated species (maternal serum) and carnitines (cord blood) were associated with offspring skinfold sum, independently of maternal hyperglycemia. However, maternal hyperglycemia retained a strong independent association with skinfold sum despite adjustment for potential lipid mediators. Conclusions: Maternal hyperglycemia is associated with features of de novo lipogenesis in the maternal metabolism and beta oxidation in the offspring. Altered lipid metabolism significantly contributes to offspring adiposity but does not appear to solely mediate the relationship between hyperglycemia and body composition in type 1 diabetes pregnancy. Disclosure C.L.Meek: Research Support; Dexcom, Inc. Z.A.Stewart: None. D.Feig: Advisory Panel; Novo Nordisk, Research Support; Apotex. A.Koulman: None. H.R.Murphy: Advisory Panel; Medtronic. Funding This project was funded by Diabetes UK (PG 2017/2278) . The CONCEPTT trial was funded by Juvenile Diabetes Research Foundation (JDRF) grants #17-2011-533, and grants under the JDRF Canadian Clinical Trial Network, a public-private partnership including JDRF and FedDev Ontario and supported by JDRF #80-2010-585. Medtronic supplied the CGM sensors and CGM systems at reduced cost. The study sponsor/funders were not involved in the design of the study; the collection, analysis, and interpretation of data; writing the report; and did not impose any restrictions regarding the publication of the report.CLM is supported by the Diabetes UK Harry Keen Intermediate Clinical Fellowship (DUK-HKF 17/0005712) and the European Foundation for the Study of Diabetes – Novo Nordisk Foundation Future Leaders’ Award (NNF19SA058974) . HRM conducts independent research supported by the National Institute for Health Research (Career Development Fellowship, CDF-2013-06-035) , and is supported by Tommy’s charity. SF and AK acknowledge funding from the BBSRC (BB/M027252/1) . DSF conducts independent research supported by the Canadian Institute for Health Research.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".