Browsing by Author "Zhu, Yeyi"

Now showing 1 - 5 of 5
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    Age at Menarche and Risk of Gestational Diabetes Mellitus: A Prospective Cohort Study Among 27,482 Women
    (American Diabetes Association, 2016-03) Chen, Liwei; Li, Shanshan; He, Chunyan; Zhu, Yeyi; Buck Louis, Germaine M.; Yeung, Edwina; Hu, Frank B.; Zhang, Cuilin; Department of Epidemiology, Richard M. Fairbanks School of Public Health
    OBJECTIVE: To examine the association between age at menarche and risk of gestational diabetes mellitus (GDM). RESEARCH DESIGN AND METHODS: A prospective cohort study of 42,109 eligible pregnancies from 27,482 women in the Nurses' Health Study II. RESULTS: The adjusted risk ratios for GDM across the age at menarche categories (≤11, 12, 13, and ≥14 years) were 1.34 (95% CI 1.14-1.58), 1.13 (0.97-1.31), 1.11 (0.95-1.29), and 1.00 (referent; P for trend = 0.0005), respectively. Analysis of the mediating effect indicated that 42.1% (P = 0.0007) of the association was mediated through prepregnancy BMI. CONCLUSIONS: These findings suggested that earlier menarche was significantly associated with an increased risk of GDM. This association was largely mediated through prepregnancy excessive body adiposity.
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    Longitudinal Plasma Metabolomics Profile in Pregnancy—A Study in an Ethnically Diverse U.S. Pregnancy Cohort
    (MDPI, 2021-09-01) Mitro, Susanna D.; Wu, Jing; Rahman, Mohammad L.; Cao, Yaqi; Zhu, Yeyi; Chen, Zhen; Chen, Liwei; Li, Mengying; Hinkle, Stefanie N.; Bremer, Andrew A.; Weir, Natalie L.; Tsai, Michael Y.; Song, Yiqing; Grantz, Katherine L.; Gelaye, Bizu; Zhang, Cuilin; Epidemiology, School of Public Health
    Amino acids, fatty acids, and acylcarnitine metabolites play a pivotal role in maternal and fetal health, but profiles of these metabolites over pregnancy are not completely established. We described longitudinal trajectories of targeted amino acids, fatty acids, and acylcarnitines in pregnancy. We quantified 102 metabolites and combinations (37 fatty acids, 37 amino acids, and 28 acylcarnitines) in plasma samples from pregnant women in the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies-Singletons cohort (n = 214 women at 10-14 and 15-26 weeks, 107 at 26-31 weeks, and 103 at 33-39 weeks). We used linear mixed models to estimate metabolite trajectories and examined variation by body mass index (BMI), race/ethnicity, and fetal sex. After excluding largely undetected metabolites, we analyzed 77 metabolites and combinations. Levels of 13 of 15 acylcarnitines, 7 of 25 amino acids, and 18 of 37 fatty acids significantly declined over gestation, while 8 of 25 amino acids and 10 of 37 fatty acids significantly increased. Several trajectories appeared to differ by BMI, race/ethnicity, and fetal sex although no tests for interactions remained significant after multiple testing correction. Future studies merit longitudinal measurements to capture metabolite changes in pregnancy, and larger samples to examine modifying effects of maternal and fetal characteristics.
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    Metabolic Biomarkers of Mediterranean Diet in Pregnant Women
    (Elsevier, 2021) Dai, Jin; Chen, Liwei; Fei, Zhe; Liu, Xinyue; Zhu, Yeyi; Hinkle, Stefanie N.; Wu, Jing; Lu, Ruijin; Rahman, Mohammad L.; Chen, Zhen; Song, Yiqing; Zhang, Cuilin; Epidemiology, Richard M. Fairbanks School of Public Health
    Objectives: Using an untargeted approach to identify plasma metabolomics signature of the Mediterranean diet, a healthful dietary pattern related to both maternal and fetal outcomes, in pregnancy. Methods: This study included 193 pregnant women from the NICHD Fetal Growth Studies-Singletons (FGS) cohort who had habitual dietary intake in the past three months measured at 8–13 gestational weeks (GW) by the semi-quantified food frequency questionnaire. Fasting plasma metabolomics profiles at 15–26 GW were measured by the high-throughput liquid chromatography quadrupole time of-flight mass spectrometry (LC-QTOF MS/MS). Metabolites were re-scaled to a median of 1 for each batch and log transformed. Alternate Mediterranean Diet (aMED) score was calculated by eight food and nutrient components (i.e., fruits, vegetables, whole grains, nuts, fish, legumes, red and processed meats, and monounsaturated-to-saturated fat ratio), with a higher score indicating a better adherence. Prospective associations of aMED score in peri-conception and early pregnancy with individual metabolites at 15–26 GW were estimated using the linear regression adjusting for potential confounders and multiple testing. LASSO (Least Absolute Shrinkage and Selection Operator) regression with 10-fold cross-validation was performed to select metabolites that were jointly associated with high aMED score (defined as the top tertile). All statistical analyses were weighted to represent the entire FGS cohort. Results: A total of 460 known metabolites were profiled and annotated. Six metabolites were selected as the biomarkers of high aMED score by the LASSO regression (i.e., with no-zero coefficients). Among them, glutamic acid and 3-hydroxybutyric acid were negatively whereas PC (40:7), CE (20:5), TG (49:1), and TG (58:4) were positively associated with aMED score. The six biomarkers were also confirmed by the linear regression with false discovery rates < 0.1. Conclusions: Our study is the first one conducted in pregnant women using the untargeted metabolomics approach and we newly identified several biomarkers of Mediterranean diet in pregnant women. Results from this study warrant the replication by future studies.
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    Plasma Acylcarnitines during Pregnancy and Neonatal Anthropometry: A Longitudinal Study in a Multiracial Cohort
    (MDPI, 2021-12-17) Song, Yiqing; Lyu, Chen; Li, Ming; Rahman, Mohammad L.; Chen, Zhen; Zhu, Yeyi; Hinkle, Stefanie N.; Chen, Liwei; Mitro, Susanna D.; Li, Ling-Jun; Weir, Natalie L.; Tsai, Michael Y.; Zhang, Cuilin; Epidemiology, School of Public Health
    As surrogate readouts reflecting mitochondrial dysfunction, elevated levels of plasma acylcarnitines have been associated with cardiometabolic disorders, such as obesity, gestational diabetes, and type 2 diabetes. This study aimed to examine prospective associations of acylcarnitine profiles across gestation with neonatal anthropometry, including birthweight, birthweight z score, body length, sum of skinfolds, and sum of body circumferences. We quantified 28 acylcarnitines using electrospray ionization tandem mass spectrometry in plasma collected at gestational weeks 10-14, 15-26, 23-31, and 33-39 among 321 pregnant women from the National Institute of Child Health and Human Development (NICHD) Fetal Growth Studies-Singletons. A latent-class trajectory approach was applied to identify trajectories of acylcarnitines across gestation. We examined the associations of individual acylcarnitines and distinct trajectory groups with neonatal anthropometry using weighted generalized linear models adjusting for maternal age, race/ethnicity, education, parity, gestational age at blood collection, and pre-pregnancy body mass index (BMI). We identified three distinct trajectory groups in C2, C3, and C4 and two trajectory groups in C5, C10, C5-DC, C8:1, C10:1, and C12, respectively. Women with nonlinear decreasing C12 levels across gestation (5.7%) had offspring with significantly lower birthweight (-475 g; 95% CI, -942, -6.79), birthweight z score (-0.39, -0.71, -0.06), and birth length (-1.38 cm, -2.49, -0.27) than those with persistently stable C12 levels (94.3%) (all nominal p value < 0.05). Women with consistently higher levels of C10 (6.1%) had offspring with thicker sum of skinfolds (4.91 mm, 0.85, 8.98) than did women with lower levels (93.9%) during pregnancy, whereas women with lower C10:1 levels (12.6%) had offspring with thicker sum of skinfolds (3.23 mm, 0.19, 6.27) than did women with abruptly increasing levels (87.4%) (p < 0.05). In conclusion, this study suggests that distinctive trajectories of C10, C10:1, and C12 acylcarnitine levels throughout pregnancy were significantly associated with neonatal anthropometry.
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    Second international consensus report on gaps and opportunities for the clinical translation of precision diabetes medicine
    (Springer Nature, 2023) Tobias, Deirdre K.; Merino, Jordi; Ahmad, Abrar; Aiken, Catherine; Benham, Jamie L.; Bodhini, Dhanasekaran; Clark, Amy L.; Colclough, Kevin; Corcoy, Rosa; Cromer, Sara J.; Duan, Daisy; Felton, Jamie L.; Francis, Ellen C.; Gillard, Pieter; Gingras, Véronique; Gaillard, Romy; Haider, Eram; Hughes, Alice; Ikle, Jennifer M.; Jacobsen, Laura M.; Kahkoska, Anna R.; Kettunen, Jarno L. T.; Kreienkamp, Raymond J.; Lim, Lee-Ling; Männistö, Jonna M. E.; Massey, Robert; Mclennan, Niamh-Maire; Miller, Rachel G.; Morieri, Mario Luca; Most, Jasper; Naylor, Rochelle N.; Ozkan, Bige; Patel, Kashyap Amratlal; Pilla, Scott J.; Prystupa, Katsiaryna; Raghavan, Sridharan; Rooney, Mary R.; Schön, Martin; Semnani-Azad, Zhila; Sevilla-Gonzalez, Magdalena; Svalastoga, Pernille; Takele, Wubet Worku; Tam, Claudia Ha-Ting; Thuesen, Anne Cathrine B.; Tosur, Mustafa; Wallace, Amelia S.; Wang, Caroline C.; Wong, Jessie J.; Yamamoto, Jennifer M.; Young, Katherine; Amouyal, Chloé; Andersen, Mette K.; Bonham, Maxine P.; Chen, Mingling; Cheng, Feifei; Chikowore, Tinashe; Chivers, Sian C.; Clemmensen, Christoffer; Dabelea, Dana; Dawed, Adem Y.; Deutsch, Aaron J.; Dickens, Laura T.; DiMeglio, Linda A.; Dudenhöffer-Pfeifer, Monika; Evans-Molina, Carmella; Fernández-Balsells, María Mercè; Fitipaldi, Hugo; Fitzpatrick, Stephanie L.; Gitelman, Stephen E.; Goodarzi, Mark O.; Grieger, Jessica A.; Guasch-Ferré, Marta; Habibi, Nahal; Hansen, Torben; Huang, Chuiguo; Harris-Kawano, Arianna; Ismail, Heba M.; Hoag, Benjamin; Johnson, Randi K.; Jones, Angus G.; Koivula, Robert W.; Leong, Aaron; Leung, Gloria K. W.; Libman, Ingrid M.; Liu, Kai; Long, S. Alice; Lowe, William L., Jr.; Morton, Robert W.; Motala, Ayesha A.; Onengut-Gumuscu, Suna; Pankow, James S.; Pathirana, Maleesa; Pazmino, Sofia; Perez, Dianna; Petrie, John R.; Powe, Camille E.; Quinteros, Alejandra; Jain, Rashmi; Ray, Debashree; Ried-Larsen, Mathias; Saeed, Zeb; Santhakumar, Vanessa; Kanbour, Sarah; Sarkar, Sudipa; Monaco, Gabriela S. F.; Scholtens, Denise M.; Selvin, Elizabeth; Sheu, Wayne Huey-Herng; Speake, Cate; Stanislawski, Maggie A.; Steenackers, Nele; Steck, Andrea K.; Stefan, Norbert; Støy, Julie; Taylor, Rachael; Tye, Sok Cin; Ukke, Gebresilasea Gendisha; Urazbayeva, Marzhan; Van der Schueren, Bart; Vatier, Camille; Wentworth, John M.; Hannah, Wesley; White, Sara L.; Yu, Gechang; Zhang, Yingchai; Zhou, Shao J.; Beltrand, Jacques; Polak, Michel; Aukrust, Ingvild; de Franco, Elisa; Flanagan, Sarah E.; Maloney, Kristin A.; McGovern, Andrew; Molnes, Janne; Nakabuye, Mariam; Njølstad, Pål Rasmus; Pomares-Millan, Hugo; Provenzano, Michele; Saint-Martin, Cécile; Zhang, Cuilin; Zhu, Yeyi; Auh, Sungyoung; de Souza, Russell; Fawcett, Andrea J.; Gruber, Chandra; Mekonnen, Eskedar Getie; Mixter, Emily; Sherifali, Diana; Eckel, Robert H.; Nolan, John J.; Philipson, Louis H.; Brown, Rebecca J.; Billings, Liana K.; Boyle, Kristen; Costacou, Tina; Dennis, John M.; Florez, Jose C.; Gloyn, Anna L.; Gomez, Maria F.; Gottlieb, Peter A.; Greeley, Siri Atma W.; Griffin, Kurt; Hattersley, Andrew T.; Hirsch, Irl B.; Hivert, Marie-France; Hood, Korey K.; Josefson, Jami L.; Kwak, Soo Heon; Laffel, Lori M.; Lim, Siew S.; Loos, Ruth J. F.; Ma, Ronald C. W.; Mathieu, Chantal; Mathioudakis, Nestoras; Meigs, James B.; Misra, Shivani; Mohan, Viswanathan; Murphy, Rinki; Oram, Richard; Owen, Katharine R.; Ozanne, Susan E.; Pearson, Ewan R.; Perng, Wei; Pollin, Toni I.; Pop-Busui, Rodica; Pratley, Richard E.; Redman, Leanne M.; Redondo, Maria J.; Reynolds, Rebecca M.; Semple, Robert K.; Sherr, Jennifer L.; Sims, Emily K.; Sweeting, Arianne; Tuomi, Tiinamaija; Udler, Miriam S.; Vesco, Kimberly K.; Vilsbøll, Tina; Wagner, Robert; Rich, Stephen S.; Franks, Paul W.; Pediatrics, School of Medicine
    Precision medicine is part of the logical evolution of contemporary evidence-based medicine that seeks to reduce errors and optimize outcomes when making medical decisions and health recommendations. Diabetes affects hundreds of millions of people worldwide, many of whom will develop life-threatening complications and die prematurely. Precision medicine can potentially address this enormous problem by accounting for heterogeneity in the etiology, clinical presentation and pathogenesis of common forms of diabetes and risks of complications. This second international consensus report on precision diabetes medicine summarizes the findings from a systematic evidence review across the key pillars of precision medicine (prevention, diagnosis, treatment, prognosis) in four recognized forms of diabetes (monogenic, gestational, type 1, type 2). These reviews address key questions about the translation of precision medicine research into practice. Although not complete, owing to the vast literature on this topic, they revealed opportunities for the immediate or near-term clinical implementation of precision diabetes medicine; furthermore, we expose important gaps in knowledge, focusing on the need to obtain new clinically relevant evidence. Gaps include the need for common standards for clinical readiness, including consideration of cost-effectiveness, health equity, predictive accuracy, liability and accessibility. Key milestones are outlined for the broad clinical implementation of precision diabetes medicine.