Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Eugene P. Rhee is active.

Publication


Featured researches published by Eugene P. Rhee.


Nature Medicine | 2011

Metabolite profiles and the risk of developing diabetes

Thomas J. Wang; Martin G. Larson; Susan Cheng; Eugene P. Rhee; Elizabeth L. McCabe; Gregory D. Lewis; Caroline S. Fox; Paul F. Jacques; Céline Fernandez; Christopher J. O'Donnell; Stephen A Carr; Vamsi K. Mootha; Jose C. Florez; Amanda Souza; Olle Melander; Clary B. Clish; Robert E. Gerszten

Emerging technologies allow the high-throughput profiling of metabolic status from a blood specimen (metabolomics). We investigated whether metabolite profiles could predict the development of diabetes. Among 2,422 normoglycemic individuals followed for 12 years, 201 developed diabetes. Amino acids, amines and other polar metabolites were profiled in baseline specimens by liquid chromatography–tandem mass spectrometry (LC-MS). Cases and controls were matched for age, body mass index and fasting glucose. Five branched-chain and aromatic amino acids had highly significant associations with future diabetes: isoleucine, leucine, valine, tyrosine and phenylalanine. A combination of three amino acids predicted future diabetes (with a more than fivefold higher risk for individuals in top quartile). The results were replicated in an independent, prospective cohort. These findings underscore the potential key role of amino acid metabolism early in the pathogenesis of diabetes and suggest that amino acid profiles could aid in diabetes risk assessment.


Journal of The American Society of Nephrology | 2005

Fibroblast Growth Factor-23 Mitigates Hyperphosphatemia but Accentuates Calcitriol Deficiency in Chronic Kidney Disease

Orlando M. Gutiérrez; Tamara Isakova; Eugene P. Rhee; Anand Shah; Julie Holmes; Gina Collerone; Harald Jüppner; Myles Wolf

Hyperphosphatemia, calcitriol deficiency, and secondary hyperparathyroidism (SHPT) are common complications of chronic kidney disease (CKD). Fibroblast growth factor-23 (FGF-23) is a novel phosphaturic hormone that also inhibits renal 1alpha-hydroxylase activity and thus may be involved in the pathogenesis of SHPT. Several hypotheses were tested: that FGF-23 increases as renal function declines; is linearly associated with serum phosphate levels; is associated with increased phosphaturia independent of parathyroid hormone (PTH); and is associated with decreased calcitriol levels independent of renal function, hyperphosphatemia, and vitamin D stores. FGF-23, PTH, 25(OH)D3, calcitriol, calcium, phosphate, and urinary fractional excretion of phosphate (Fe(PO4)) were measured in 80 CKD patients. Multiple linear regression was used to test the hypotheses. FGF-23 and PTH were inversely associated with estimated GFR (eGFR), whereas calcitriol levels were linearly associated with eGFR. Hyperphosphatemia and hypocalcemia were present in only 12 and 6% of patients, respectively, all of whose eGFR was <30. Increased Fe(PO4) was associated with decreased eGFR, and both increased FGF-23 and PTH were independently associated with increased Fe(PO4). Increased FGF-23 and decreased 25(OH)D3 were independent predictors of decreased calcitriol, but the effects on calcitriol levels of renal function itself and hyperphosphatemia were completely extinguished by adjusting for FGF-23. It is concluded that FGF-23 levels increase early in CKD before the development of serum mineral abnormalities and are independently associated with serum phosphate, Fe(PO4), and calcitriol deficiency. Increased FGF-23 may contribute to maintaining normal serum phosphate levels in the face of advancing CKD but may worsen calcitriol deficiency and thus may be a central factor in the early pathogenesis of SHPT.


Journal of Clinical Investigation | 2011

Lipid profiling identifies a triacylglycerol signature of insulin resistance and improves diabetes prediction in humans

Eugene P. Rhee; Susan Cheng; Martin G. Larson; Geoffrey A. Walford; Gregory D. Lewis; Elizabeth L. McCabe; Elaine Yang; Laurie A. Farrell; Caroline S. Fox; Christopher J. O’Donnell; Steven A. Carr; Jose C. Florez; Clary B. Clish; Thomas J. Wang; Robert E. Gerszten

Dyslipidemia is an independent risk factor for type 2 diabetes, although exactly which of the many plasma lipids contribute to this remains unclear. We therefore investigated whether lipid profiling can inform diabetes prediction by performing liquid chromatography/mass spectrometry-based lipid profiling in 189 individuals who developed type 2 diabetes and 189 matched disease-free individuals, with over 12 years of follow up in the Framingham Heart Study. We found that lipids of lower carbon number and double bond content were associated with an increased risk of diabetes, whereas lipids of higher carbon number and double bond content were associated with decreased risk. This pattern was strongest for triacylglycerols (TAGs) and persisted after multivariable adjustment for age, sex, BMI, fasting glucose, fasting insulin, total triglycerides, and HDL cholesterol. A combination of 2 TAGs further improved diabetes prediction. To explore potential mechanisms that modulate the distribution of plasma lipids, we performed lipid profiling during oral glucose tolerance testing, pharmacologic interventions, and acute exercise testing. Levels of TAGs associated with increased risk for diabetes decreased in response to insulin action and were elevated in the setting of insulin resistance. Conversely, levels of TAGs associated with decreased diabetes risk rose in response to insulin and were poorly correlated with insulin resistance. These studies identify a relationship between lipid acyl chain content and diabetes risk and demonstrate how lipid profiling could aid in clinical risk assessment.


Circulation | 2012

Metabolite Profiling Identifies Pathways Associated With Metabolic Risk in Humans

Susan Cheng; Eugene P. Rhee; Martin G. Larson; Gregory D. Lewis; Elizabeth L. McCabe; Dongxiao Shen; Melinda J. Palma; Lee D. Roberts; Andre Dejam; Amanda Souza; Amy Deik; Martin Magnusson; Caroline S. Fox; Christopher J. O'Donnell; Olle Melander; Clary B. Clish; Robert E. Gerszten; Thomas J. Wang

Background— Although metabolic risk factors are known to cluster in individuals who are prone to developing diabetes mellitus and cardiovascular disease, the underlying biological mechanisms remain poorly understood. Methods and Results— To identify pathways associated with cardiometabolic risk, we used liquid chromatography/mass spectrometry to determine the plasma concentrations of 45 distinct metabolites and to examine their relation to cardiometabolic risk in the Framingham Heart Study (FHS; n=1015) and the Malmö Diet and Cancer Study (MDC; n=746). We then interrogated significant findings in experimental models of cardiovascular and metabolic disease. We observed that metabolic risk factors (obesity, insulin resistance, high blood pressure, and dyslipidemia) were associated with multiple metabolites, including branched-chain amino acids, other hydrophobic amino acids, tryptophan breakdown products, and nucleotide metabolites. We observed strong associations of insulin resistance traits with glutamine (standardized regression coefficients, −0.04 to −0.22 per 1-SD change in log-glutamine; P<0.001), glutamate (0.05 to 0.14; P<0.001), and the glutamine-to-glutamate ratio (−0.05 to −0.20; P<0.001) in the discovery sample (FHS); similar associations were observed in the replication sample (MDC). High glutamine-to-glutamate ratio was associated with lower risk of incident diabetes mellitus in FHS (odds ratio, 0.79; adjusted P=0.03) but not in MDC. In experimental models, administration of glutamine in mice led to both increased glucose tolerance (P=0.01) and decreased blood pressure (P<0.05). Conclusions— Biochemical profiling identified circulating metabolites not previously associated with metabolic traits. Experimentally interrogating one of these pathways demonstrated that excess glutamine relative to glutamate, resulting from exogenous administration, is associated with reduced metabolic risk in mice.


Science Translational Medicine | 2010

Metabolic Signatures of Exercise in Human Plasma

Gregory D. Lewis; Laurie A. Farrell; Malissa J. Wood; Maryann Martinovic; Zoltan Arany; Glenn C. Rowe; Amanda Souza; Susan Cheng; Elizabeth L. McCabe; Elaine Yang; Xu Shi; Rahul C. Deo; Frederick P. Roth; Aarti Asnani; Eugene P. Rhee; David M. Systrom; Marc J. Semigran; Steven A. Carr; Thomas J. Wang; Marc S. Sabatine; Clary B. Clish; Robert E. Gerszten

Measurement by mass spectrometry of 200 blood metabolites reveals that individuals who are more fit respond more effectively to exercise, as shown by larger exercise-induced increase in glycerol. What Happens When You Run the Boston Marathon? We used to call it toil; now, we call it exercise. The human body has evolved to perform physical labor, and modern sedentary lifestyles are at odds with this evolutionary mandate. This disconnect makes it all the more imperative that we understand the physiology of how the body converts fuel to work. Lewis and colleagues have moved us toward that goal by comprehensively surveying blood metabolites in people of varying fitness levels before and during exercise. Through the use of a high-sensitivity mass spectrometry method, they have characterized these exercise-induced metabolic changes in unprecedented detail. The authors measured 200 blood metabolites in groups of people before, during, and after exercise on a treadmill. They found that the elevated glycolysis, lipolysis, and amino acid catabolism that occur in skeletal muscle cells during use are reflected in a rise in marker metabolites of these processes in blood. Also appearing in the blood after exercise were niacinamide, which enhances insulin release and improves glycemic control, and allantoin, an indicator of oxidative stress. Even when other variables were controlled for, the people who were more fit—as measured by their maximum oxygen use—exhibited more lipolysis during exercise (98% increase) than did the less fit (48% increase) participants or those who developed heart ischemia upon exertion (18% increase). Even more striking was the increase in lipolysis (1128%) in runners after they finished the Boston Marathon, a 26.2-mile run through the winding roads of Boston and its environs. From these data, the authors could not tell whether the more well-conditioned individuals were fitter because their metabolism used fat more effectively or whether, once attaining fitness, these able-bodied metabolic systems were better at burning fat. A mechanistic clue is provided by a final experiment in which the authors show that a combination of six of the metabolites elevated by exercise reflects an increase in glucose utilization and lipid metabolism in skeletal muscle cells, whereas none of the individual elevated molecules signal this effect. Thus, a cost of our sedentary lives may be to deoptimize the operation of the complicated system that is human metabolism. Sorting out how this backsliding occurs and how to restore the vigor of our metabolism will be facilitated by the findings and tools reported here. Exercise provides numerous salutary effects, but our understanding of how these occur is limited. To gain a clearer picture of exercise-induced metabolic responses, we have developed comprehensive plasma metabolite signatures by using mass spectrometry to measure >200 metabolites before and after exercise. We identified plasma indicators of glycogenolysis (glucose-6-phosphate), tricarboxylic acid cycle span 2 expansion (succinate, malate, and fumarate), and lipolysis (glycerol), as well as modulators of insulin sensitivity (niacinamide) and fatty acid oxidation (pantothenic acid). Metabolites that were highly correlated with fitness parameters were found in subjects undergoing acute exercise testing and marathon running and in 302 subjects from a longitudinal cohort study. Exercise-induced increases in glycerol were strongly related to fitness levels in normal individuals and were attenuated in subjects with myocardial ischemia. A combination of metabolites that increased in plasma in response to exercise (glycerol, niacinamide, glucose-6-phosphate, pantothenate, and succinate) up-regulated the expression of nur77, a transcriptional regulator of glucose utilization and lipid metabolism genes in skeletal muscle in vitro. Plasma metabolic profiles obtained during exercise provide signatures of exercise performance and cardiovascular disease susceptibility, in addition to highlighting molecular pathways that may modulate the salutary effects of exercise.


Journal of Clinical Investigation | 2013

2-Aminoadipic acid is a biomarker for diabetes risk

Thomas J. Wang; Debby Ngo; Nikolaos Psychogios; Andre Dejam; Martin G. Larson; Anahita Ghorbani; John O’Sullivan; Susan Cheng; Eugene P. Rhee; Sumita Sinha; Elizabeth L. McCabe; Caroline S. Fox; Christopher J. O’Donnell; Jennifer E. Ho; Jose C. Florez; Martin Magnusson; Kerry A. Pierce; Amanda Souza; Yi Yu; Christian C. Carter; Peter E. Light; Olle Melander; Clary B. Clish; Robert E. Gerszten

Improvements in metabolite-profiling techniques are providing increased breadth of coverage of the human metabolome and may highlight biomarkers and pathways in common diseases such as diabetes. Using a metabolomics platform that analyzes intermediary organic acids, purines, pyrimidines, and other compounds, we performed a nested case-control study of 188 individuals who developed diabetes and 188 propensity-matched controls from 2,422 normoglycemic participants followed for 12 years in the Framingham Heart Study. The metabolite 2-aminoadipic acid (2-AAA) was most strongly associated with the risk of developing diabetes. Individuals with 2-AAA concentrations in the top quartile had greater than a 4-fold risk of developing diabetes. Levels of 2-AAA were not well correlated with other metabolite biomarkers of diabetes, such as branched chain amino acids and aromatic amino acids, suggesting they report on a distinct pathophysiological pathway. In experimental studies, administration of 2-AAA lowered fasting plasma glucose levels in mice fed both standard chow and high-fat diets. Further, 2-AAA treatment enhanced insulin secretion from a pancreatic β cell line as well as murine and human islets. These data highlight a metabolite not previously associated with diabetes risk that is increased up to 12 years before the onset of overt disease. Our findings suggest that 2-AAA is a marker of diabetes risk and a potential modulator of glucose homeostasis in humans.


Nature Cell Biology | 2012

Programming human pluripotent stem cells into white and brown adipocytes

Tim Ahfeldt; Robert T. Schinzel; Youn-Kyoung Lee; David G. Hendrickson; Adam Kaplan; David H. Lum; Raymond Camahort; Fang Xia; Jennifer Shay; Eugene P. Rhee; Clary B. Clish; Rahul C. Deo; Tony Shen; Frank H. Lau; Alicia Cowley; Greg Mowrer; Heba Al-Siddiqi; Matthias Nahrendorf; Kiran Musunuru; Robert E. Gerszten; John L. Rinn; Chad A. Cowan

The utility of human pluripotent stem cells is dependent on efficient differentiation protocols that convert these cells into relevant adult cell types. Here we report the robust and efficient differentiation of human pluripotent stem cells into white or brown adipocytes. We found that inducible expression of PPARG2 alone or combined with CEBPB and/or PRDM16 in mesenchymal progenitor cells derived from pluripotent stem cells programmed their development towards a white or brown adipocyte cell fate with efficiencies of 85%–90%. These adipocytes retained their identity independent of transgene expression, could be maintained in culture for several weeks, expressed mature markers and had mature functional properties such as lipid catabolism and insulin-responsiveness. When transplanted into mice, the programmed cells gave rise to ectopic fat pads with the morphological and functional characteristics of white or brown adipose tissue. These results indicate that the cells could be used to faithfully model human disease.


Clinical Chemistry | 2012

Metabolomics and Cardiovascular Biomarker Discovery

Eugene P. Rhee; Robert E. Gerszten

BACKGROUND Metabolomics, the systematic analysis of low molecular weight biochemical compounds in a biological specimen, has been increasingly applied to biomarker discovery. CONTENT Because no single analytical method can accommodate the chemical diversity of the entire metabolome, various methods such as nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) have been employed, with the latter coupled to an array of separation techniques including gas and liquid chromatography. Whereas NMR can provide structural information and absolute quantification for select metabolites without the use of exogenous standards, MS tends to have much higher analytical sensitivity, enabling broader surveys of the metabolome. Both NMR and MS can be used to characterize metabolite data either in a targeted manner or in a nontargeted, pattern-recognition manner. In addition to technical considerations, careful sample selection and study design are important to minimize potential confounding influences on the metabolome, including diet, medications, and comorbitidies. To this end, metabolite profiling has been applied to human biomarker discovery in small-scale interventions, in which individuals are extremely well phenotyped and able to serve as their own biological controls, as well as in larger epidemiological cohorts. Understanding how metabolites relate to each other and to established risk markers for diseases such as diabetes and renal failure will be important in evaluating the potential value of these metabolites as clinically useful biomarkers. SUMMARY Applied to both experimental and epidemiological study designs, metabolite profiling has begun to highlight the breadth metabolic disturbances that accompany human disease. Experimental work in model systems and integration with other functional genomic approaches will be required to establish a causal link between select biomarkers and disease pathogenesis.


Journal of The American Society of Nephrology | 2010

Metabolite Profiling Identifies Markers of Uremia

Eugene P. Rhee; Amanda Souza; Laurie A. Farrell; Martin R. Pollak; Gregory D. Lewis; David Steele; Ravi Thadhani; Clary B. Clish; Anna Greka; Robert E. Gerszten

ESRD is a state of small-molecule disarray. We applied liquid chromatography/tandem mass spectrometry-based metabolite profiling to survey>350 small molecules in 44 fasting subjects with ESRD, before and after hemodialysis, and in 10 age-matched, at-risk fasting control subjects. At baseline, increased levels of polar analytes and decreased levels of lipid analytes characterized uremic plasma. In addition to confirming the elevation of numerous previously identified uremic toxins, we identified several additional markers of ESRD, including dicarboxylic acids (adipate, malonate, methylmalonate, and maleate), biogenic amines, nucleotide derivatives, phenols, and sphingomyelins. The pattern of lipids was notable for a universal decrease in lower-molecular-weight triacylglycerols, and an increase in several intermediate-molecular-weight triacylglycerols in ESRD compared with controls; standard measurement of total triglycerides obscured this heterogeneity. These observations suggest disturbed triglyceride catabolism and/or beta-oxidation in ESRD. As expected, the hemodialysis procedure was associated with significant decreases in most polar analytes. Unexpected increases in several metabolites, however, indicated activation of a broad catabolic program, including glycolysis, lipolysis, ketosis, and nucleotide breakdown. In summary, this study demonstrates the application of metabolite profiling to identify markers of ESRD, provide perspective on uremic dyslipidemia, and broaden our understanding of the biochemical effects of hemodialysis.


Cell Metabolism | 2013

A Genome-wide Association Study of the Human Metabolome in a Community-Based Cohort

Eugene P. Rhee; Jennifer E. Ho; Ming-Huei Chen; Dongxiao Shen; Susan Cheng; Martin G. Larson; Anahita Ghorbani; Xu Shi; Iiro Taneli Helenius; Christopher J. O’Donnell; Amanda Souza; Amy Deik; Kerry A. Pierce; Kevin Bullock; Geoffrey A. Walford; Jose C. Florez; Clary B. Clish; Jing-Ruey J. Yeh; Thomas J. Wang; Robert E. Gerszten

Because metabolites are hypothesized to play key roles as markers and effectors of cardiometabolic diseases, recent studies have sought to annotate the genetic determinants of circulating metabolite levels. We report a genome-wide association study (GWAS) of 217 plasma metabolites, including >100 not measured in prior GWAS, in 2076 participants of the Framingham Heart Study (FHS). For the majority of analytes, we find that estimated heritability explains >20% of interindividual variation, and that variation attributable to heritable factors is greater than that attributable to clinical factors. Further, we identify 31 genetic loci associated with plasma metabolites, including 23 that have not previously been reported. Importantly, we include GWAS results for all surveyed metabolites and demonstrate how this information highlights a role for AGXT2 in cholesterol ester and triacylglycerol metabolism. Thus, our study outlines the relative contributions of inherited and clinical factors on the plasma metabolome and provides a resource for metabolism research.

Collaboration


Dive into the Eugene P. Rhee's collaboration.

Top Co-Authors

Avatar

Robert E. Gerszten

Beth Israel Deaconess Medical Center

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Brian Christine

University of Alabama at Birmingham

View shared research outputs
Top Co-Authors

Avatar

Gerard D. Henry

University of Arkansas for Medical Sciences

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

L. Jones

University of Texas at Austin

View shared research outputs
Top Co-Authors

Avatar

Thomas J. Wang

Vanderbilt University Medical Center

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Susan Cheng

Brigham and Women's Hospital

View shared research outputs
Researchain Logo
Decentralizing Knowledge