Education & Certifications
Bachelor of Arts, Harvard University, Biology (2012)
Metabolomic profiling in the prediction of gestational diabetes mellitus.
2015; 58 (6): 1329–32
Metabolomic profiling in populations with impaired glucose tolerance has revealed that branched chain and aromatic amino acids (BCAAs) are predictive of type 2 diabetes. Because gestational diabetes mellitus (GDM) shares pathophysiological similarities with type 2 diabetes, the metabolite profile predictive of type 2 diabetes could potentially identify women who will develop GDM.We conducted a nested case-control study of 18- to 40-year-old women who participated in the Massachusetts General Hospital Obstetrical Maternal Study between 1998 and 2007. Participants were enrolled during their first trimester of a singleton pregnancy and fasting serum samples were collected. The women were followed throughout pregnancy and identified as having GDM or normal glucose tolerance (NGT) in the third trimester. Women with GDM (n = 96) were matched to women with NGT (n = 96) by age, BMI, gravidity and parity. Liquid chromatography-mass spectrometry was used to measure the levels of 91 metabolites.Data analyses revealed the following characteristics (mean ± SD): age 32.8 ± 4.4 years, BMI 28.3 ± 5.6 kg/m(2), gravidity 2 ± 1 and parity 1 ± 1. Six metabolites (anthranilic acid, alanine, glutamate, creatinine, allantoin and serine) were identified as having significantly different levels between the two groups in conditional logistic regression analyses (p < 0.05). The levels of the BCAAs did not differ significantly between GDM and NGT.Metabolic markers identified as being predictive of type 2 diabetes may not have the same predictive power for GDM. However, further study in a racially/ethnically diverse population-based cohort is necessary.
View details for DOI 10.1007/s00125-015-3553-4
View details for PubMedID 25748329
View details for PubMedCentralID PMC4428592
Center of mass motion in swimming fish: effects of speed and locomotor mode during undulatory propulsion
2014; 117 (4): 269-281
Studies of center of mass (COM) motion are fundamental to understanding the dynamics of animal movement, and have been carried out extensively for terrestrial and aerial locomotion. But despite a large amount of literature describing different body movement patterns in fishes, analyses of how the center of mass moves during undulatory propulsion are not available. These data would be valuable for understanding the dynamics of different body movement patterns and the effect of differing body shapes on locomotor force production. In the present study, we analyzed the magnitude and frequency components of COM motion in three dimensions (x: surge, y: sway, z: heave) in three fish species (eel, bluegill sunfish, and clown knifefish) swimming with four locomotor modes at three speeds using high-speed video, and used an image cross-correlation technique to estimate COM motion, thus enabling untethered and unrestrained locomotion. Anguilliform swimming by eels shows reduced COM surge oscillation magnitude relative to carangiform swimming, but not compared to knifefish using a gymnotiform locomotor style. Labriform swimming (bluegill at 0.5 body lengths/s) displays reduced COM sway oscillation relative to swimming in a carangiform style at higher speeds. Oscillation frequency of the COM in the surge direction occurs at twice the tail beat frequency for carangiform and anguilliform swimming, but at the same frequency as the tail beat for gymnotiform locomotion in clown knifefish. Scaling analysis of COM heave oscillation for terrestrial locomotion suggests that COM heave motion scales with positive allometry, and that fish have relatively low COM oscillations for their body size.
View details for DOI 10.1016/j.zoo1.2014.03.002
View details for Web of Science ID 000340977600007
View details for PubMedID 24925455
A systematic review of metabolite profiling in gestational diabetes mellitus.
2014; 57 (12): 2453–64
Gestational diabetes mellitus is associated with adverse maternal and fetal outcomes during, as well as subsequent to, pregnancy, including increased risk of type 2 diabetes and cardiovascular disease. Because of the importance of early risk stratification in preventing these complications, improved first-trimester biomarker determination for diagnosing gestational diabetes would enhance our ability to optimise both maternal and fetal health. Metabolomic profiling, the systematic study of small molecule products of biochemical pathways, has shown promise in the identification of key metabolites associated with the pathogenesis of several metabolic diseases, including gestational diabetes. This article provides a systematic review of the current state of research on biomarkers and gestational diabetes and discusses the clinical relevance of metabolomics in the prediction, diagnosis and management of gestational diabetes.We conducted a systematic search of MEDLINE (PubMed) up to the end of February 2014 using the key term combinations of 'metabolomics,' 'metabonomics,' 'nuclear magnetic spectroscopy,' 'mass spectrometry,' 'metabolic profiling' and 'amino acid profile' combined (AND) with 'gestational diabetes'. Additional articles were identified through searching the reference lists from included studies. Quality assessment of included articles was conducted through the use of QUADOMICS.This systematic review included 17 articles. The biomarkers most consistently associated with gestational diabetes were asymmetric dimethylarginine and NEFAs. After QUADOMICS analysis, 13 of the 17 included studies were classified as 'high quality'.Existing metabolomic studies of gestational diabetes present inconsistent findings regarding metabolite profile characteristics. Further studies are needed in larger, more racially/ethnically diverse populations.
View details for DOI 10.1007/s00125-014-3371-0
View details for PubMedID 25193282
View details for PubMedCentralID PMC4221524
Metabolomic Analysis Reveals Amino Acid Responses to an Oral Glucose Tolerance Test in Women with Prior History of Gestational Diabetes Mellitus.
Journal of clinical & translational endocrinology
2014; 1 (2): 38–43
Although gestational diabetes mellitus (GDM) is associated with an increased risk of type 2 diabetes mellitus (T2DM) compared to normoglycemic pregnancies, the biochemical pathways underlying the progression of GDM to T2DM are not fully elucidated. The purpose of this exploratory study was to utilize metabolomics with an oral glucose tolerance test (OGTT) to examine the amino acid response in women with prior GDM to determine if a relationship between these metabolites and established risk factors for T2DM exists.Thirty-eight non-pregnant women without diabetes but with prior GDM within the previous 3 years were recruited from a community-based population. A 75 g-OGTT was administered; fasting and 2-hr plasma samples were obtained. Metabolite profiles of 23 amino acids or amino acid derivatives were measured with gas chromatography-mass spectrometry. Measures of insulin resistance were derived from the OGTT and risk factors for T2DM were obtained by self-report.Twenty-two metabolite levels decreased significantly in response to the OGTT (p<0.05). The clinical covariates most powerfully associated with metabolite level changes included race, body mass index (BMI), and duration of prior breastfeeding, (mean ± SD of standardized β-coefficients, β = -0.38 ± 0.05, 0.25 ± 0.08, and 0.44 ± 0.03, respectively, all p<0.05). Notably, a prior history of breastfeeding was associated with the greatest number of metabolite changes.Greater change in metabolite levels after a glucose challenge was significantly associated with a longer duration of breastfeeding and higher BMI. Further exploration of these preliminary observations and closer examination of the specific pathways implicated are warranted.
View details for DOI 10.1016/j.jcte.2014.03.003
View details for PubMedID 24932438
View details for PubMedCentralID PMC4052833