Characterizing Gestational Weight Gain According to Institute of Medicine Guidelines in Women with Type 1 Diabetes Mellitus: Association with Maternal and Perinatal Outcome

2016 ◽  
Vol 33 (13) ◽  
pp. 1266-1272 ◽  
Author(s):  
Katherine Bowers ◽  
Ketrell McWhorter ◽  
Barak Rosen ◽  
Michelle Adams ◽  
Menachem Miodovnik ◽  
...  
2018 ◽  
Vol 47 (2) ◽  
pp. 417-426 ◽  
Author(s):  
Maria C Magnus ◽  
Sjurdur F Olsen ◽  
Charlotta Granstrom ◽  
Nicolai A Lund-Blix ◽  
Jannet Svensson ◽  
...  

2015 ◽  
Vol 35 (2) ◽  
pp. 86-87
Author(s):  
C.M. Scifres ◽  
M.N. Feghali ◽  
A.D. Althouse ◽  
S.N. Caritis ◽  
J.M. Catov

Diabetes Care ◽  
2014 ◽  
Vol 37 (10) ◽  
pp. 2677-2684 ◽  
Author(s):  
Anna L. Secher ◽  
Clara B. Parellada ◽  
Lene Ringholm ◽  
Björg Ásbjörnsdóttir ◽  
Peter Damm ◽  
...  

Insulin ◽  
2008 ◽  
Vol 3 (2) ◽  
pp. 59-66 ◽  
Author(s):  
Lisa H. Fish ◽  
Harry P. Wetzler ◽  
Janet L. Davidson ◽  
Cori L. Ofstead ◽  
Mary L. Johnson

2014 ◽  
Vol 210 (1) ◽  
pp. S138
Author(s):  
Christina Scifres ◽  
Maisa Feghali ◽  
Steve Caritis ◽  
Janet Catov

2020 ◽  
Author(s):  
Agnieszka H. Ludwig-Słomczyńska ◽  
Michał T. Seweryn ◽  
Przemysław Kapusta ◽  
Ewelina Pitera ◽  
Urszula Mantaj ◽  
...  

ABSTRACTBackgroundClinical data suggest that BMI and gestational weight gain (GWG) are strongly interconnected phenotypes, however the genetic basis of the latter is rather unclear. Here we aim to find genes and genetic variants which influence BMI and/or GWG.MethodsWe have genotyped 316 type 1 diabetics using Illumina Infinium Omni Express Exome-8 v1.4 arrays. The GIANT, ARIC and T2D-GENES summary statistics were used for TWAS (performed with PrediXcan) in adipose tissue. Next, the analysis of association of imputed expression with BMI in the general and diabetic cohorts (Analysis 1 and 2) or GWG (Analysis 3 and 4) was performed, followed by variant association analysis (1Mb around identified loci) with the mentioned phenotypes.ResultsIn Analysis 1 we have found 175 BMI associated genes and 19 variants (p<10−4) which influenced GWG, with the strongest association for rs11465293 in CCL24 (p=3.18E-06). Analysis 2, with diabetes included in the model, led to discovery of 1812 BMI associated loci and 207 variants (p<10−4) influencing GWG, with the strongest association for rs9690213 in PODXL (p=9.86E-07). In Analysis 3, among 648 GWG associated loci, 2091 variants were associated with BMI (FDR<0.05). In Analysis 4, 7 variants in GWG associated loci influenced BMI in the ARIC cohort.ConclusionsHere, we have shown that loci influencing BMI might have an impact on GWG and GWG associated loci might influence BMI, both in the general and T1DM cohorts. The results suggest that both phenotypes are related to insulin signaling, glucose homeostasis, mitochondrial metabolism, ubiquitinoylation and inflammatory responses.


2019 ◽  
Vol 25 (11) ◽  
pp. 1137-1150 ◽  
Author(s):  
Qianyue Xu ◽  
Zhijuan Ge ◽  
Jun Hu ◽  
Shanmei Shen ◽  
Yan Bi ◽  
...  

Objective: To explore the association of excessive gestational weight gain (GWG) defined by the Institute of Medicine (IOM) targets and adverse perinatal outcomes in gestational diabetes mellitus (GDM) pregnancies, and whether a modified target might be related to a lower rate of adverse perinatal outcomes for GDM. Methods: This retrospective cohort study involved 1,138 women of normal glucose tolerance (NGT) and 1,200 women with GDM. Based on the IOM target, pregnancies were classified to appropriate GWG (aGWG), inadequate GWG, and excessive GWG (eGWG). Modified GWG targets included: upper limit of IOM target minus 1 kg (IOM-1) or 2 kg (IOM-2), both upper and lower targets minus 1 kg (IOM-1-1) or 2 kg (IOM-2-2). Results: The proportions of women achieving eGWG were 26.3% in NGT and 31.2% in GDM ( P = .036); in comparison, for aGWG NGT, the risks of large for gestational age (LGA) were significantly higher in eGWG NGT (adjusted odds ratio [OR] 1.47; 95% confidence interval [CI] 1.02 to 2.13), aGWG GDM (adjusted OR 1.42; 95% CI 1.03 to 1.95), and eGWG GDM (adjusted OR 2.70; 95% CI 1.92 to 3.70). GDM pregnancies gaining aGWG based on the modified GWG targets (IOM-2, IOM-1-1, and IOM-2-2) had a lower prevalence of LGA and macrosomia delivery than that for similar pregnancies using the original IOM target (all P<.05). Conclusion: For aGWG GDM according to the IOM target, adhering to a more stringent weight control was associated with decreased adverse outcomes. A tighter IOM target might help to reduce the prevalence of adverse pregnancy outcomes. Abbreviations: aGWG = appropriate gestational weight gain; BG = blood glucose; BMI = body mass index; CI = confidence interval; eGWG = excessive gestational weight gain; GDM = gestational diabetes mellitus; GW = gestational weeks; GWG = gestational weight gain; HbA1c = hemoglobin A1c; iGWG = inadequate gestational weight gain; IOM = Institute of Medicine; LGA = large for gestational age; NGT = normal glucose tolerance; NICU = neonatal intensive care unit; OGTT = oral glucose tolerance test; OR = odds ratio; PARp = partial population attributable risks; SGA = small for gestational age


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