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Breuer R.,Northwestern University | Young J.B.,Metabolism and Molecular Medicine
Journal of Hypertension | Year: 2012

Objective: Several studies have confirmed the remarkable observation that cumulative urinary potassium (K) excretion is less in African-Americans than White Americans even when identical amounts of potassium are provided in the diet. This study was designed to examine whether this decrease in urinary potassium could be compensatory to an increase in gastrointestinal excretion of potassium in African-Americans. Methods: Twenty-three young, healthy, normotensive participants of both sexes and races were placed on a fixed diet of 100 mEq per day of K and 180 mEq per day of sodium (Na) for 9 days. All urine and stool were collected daily and analyzed for electrolytes. Blood was obtained for determination of electrolytes, blood urea nitrogen (BUN), creatinine, glucose, insulin, renin, and aldosterone at the beginning and at the end of the study period. Results: Cumulative urinary excretion of K was significantly less in African-Americans (609 ± 31 mEq) compared with White Americans (713 ± 22 mEq, P = 0.015). There was no significant racial difference, however, in the cumulative gastrointestinal excretion of K (105 ± 11 versus 95 ± 9 mEq, P = 0.28) in African-Americans versus White Americans, respectively. Conclusion: The racial difference in urinary K handling manifested by decreased excretion of K in African-Americans cannot be attributed to an increase in net gastrointestinal excretion of this cation. © 2012 Wolters Kluwer Health | Lippincott Williams & Wilkins. Source


Rajavashisth T.B.,Metabolism and Molecular Medicine | Rajavashisth T.B.,Omics Biotechnology Inc. | Shaheen M.,Charles R. Drew University of Medicine and Science | Norris K.C.,Charles R. Drew University of Medicine and Science | And 4 more authors.
BMJ Open | Year: 2012

Objective: To determine the association between diabetes mellitus (DM) and marijuana use. Design: Cross-sectional study. Setting: Data from the National Health and Nutrition Examination Survey (NHANES III, 1988-1994) conducted by the National Center for Health Statistics of the Centers for Disease Control and Prevention. Participants: The study included participants of the NHANES III, a nationally representative sample of the US population. The total analytic sample was 10 896 adults. The study included four groups (n=10 896): non-marijuana users (61.0%), past marijuana users (30.7%), light (one to four times/month) (5.0%) and heavy (more than five times/month) current marijuana users (3.3%). DM was defined based on self-report or abnormal glycaemic parameters. We analysed data related to demographics, body mass index, smoking status, alcohol use, total serum cholesterol, highdensity lipoprotein, triglyceride, serum 25-hydroxy vitamin D, plasma haemoglobin A1c, fasting plasma glucose level and the serum levels of C reactive protein and four additional inflammatory markers as related to marijuana use. Main outcome measures: OR for DM associated with marijuana use adjusted for potential confounding variables (ie, odds of DM in marijuana users compared with non-marijuana users). Results: Marijuana users had a lower age-adjusted prevalence of DM compared to non-marijuana users (OR 0.42, 95% CI 0.33 to 0.55; p<0.0001). The prevalence of elevated C reactive protein (>0.5 mg/dl) was significantly higher (p<0.0001) among nonmarijuana users (18.9%) than among past (12.7%) or current light (15.8%) or heavy (9.2%) users. In a robust multivariate model controlling for sociodemographic factors, laboratory values and comorbidity, the lower odds of DM among marijuana users was significant (adjusted OR 0.36, 95% CI 0.24 to 0.55; p<0.0001). Conclusions: Marijuana use was independently associated with a lower prevalence of DM. Further studies are needed to show a direct effect of marijuana on DM. Source


Urbanek M.,Metabolism and Molecular Medicine | Hayes M.G.,Metabolism and Molecular Medicine | Armstrong L.L.,Metabolism and Molecular Medicine | Morrison J.,University of Chicago | And 15 more authors.
Human Molecular Genetics | Year: 2013

Newborns characterized as large and small for gestational age are at risk for increased mortality and morbidity during the first year of life as well as for obesity and dysglycemia as children and adults. The intrauterine environment and fetal genes contribute to the fetal size at birth. To define the genetic architecture underlying the newborn size, we performed a genome-wide association study (GWAS) in 4281 newborns in four ethnic groups from the Hyperglycemia and Adverse Pregnancy Outcome Study. We tested for association with newborn anthropometric traits (birth length, headcircumference, birth weight, percent fatmassandsumof skinfolds)andnewborn metabolic traits (cord glucose and C-peptide) under three models. Model 1 adjusted for field center, ancestry, neonatal gender, gestational age at delivery, parity, maternal age at oral glucose tolerance test (OGTT); Model 2 adjusted for Model 1 covariates, maternal body mass index (BMI) at OGTT, maternal height at OGTT, maternal mean arterial pressure at OGTT, maternal smoking and drinking; Model 3 adjusted for Model 2 covariates, maternal glucose and C-peptide atOGTT. Strong evidence for associationwasobserved with measures of newborn adiposity (sum of skinfolds model 3 Z-score 7.356, P = 1.90 × 10-13, and to a lesser degree fat mass and birth weight) and a region on Chr3q25.31 mapping between CCNL and LEKR1. These findings were replicated in an independent cohort of 2296 newborns. This region has previously been shown to be associated with birth weight in Europeans. The current study suggests that association of this locus with birth weight is secondary to an effect on fat as opposed to lean body mass. © The Author 2013. Published by Oxford University Press. All rights reserved. Source


Tsuda A.,Metabolism and Molecular Medicine | Ishimura E.,Osaka City University | Ohno Y.,Metabolism and Molecular Medicine | Ichii M.,Metabolism and Molecular Medicine | And 5 more authors.
Diabetes Research and Clinical Practice | Year: 2014

Aims: To examine whether glomerular hemodynamic parameters in humans are associated with glycemic control indices, by simultaneously measuring clearance of inulin (Cin) and para-aminohippuric acid (CPHA). Methods: Thirty-one subjects (age 55.4±14.7 years; 15 men and 16 women; 21 diabetics and 10 non-diabetics) were enrolled. Cin and CPAH were measured simultaneously. Afferent arteriolar resistance (Ra), efferent arteriolar resistance (Re), glomerular hydrostatic pressure (Pglo) and glomerular filtration fraction (FF) were calculated according to Gomez' formula. Results: FF correlated significantly and positively with fasting plasma glucose (FPG), hemoglobin A1c (HbA1c) and glycated albumin (GA) (r=0.396, p=0.0303; r=0.587, p=0.0007; r=0.525, p=0.0070, respectively). Pglo correlated significantly and positively with FPG, HbA1c and GA (r=0.572, p=0.0008; r=0.535, p=0.0019; r=0.540, p=0.0053, respectively). Although there was no significant correlation between Ra and glycemic control indices, Re correlated significantly and positively with HbA1c and GA (r=0.499, p=0.0043; r=0.592, p=0.0018, respectively). FF, Pglo and Re were associated significantly with HbA1c and GA after adjustment for age. Conclusions: These results demonstrate, in humans, that poor glycemic control is associated with increased Re, but not Ra. It is suggested that increased Re causes increased Pglo, leading to increased FF. Thus, hemodynamic abnormalities with poor glycemic control may be related to glomerular hypertension in humans. © 2014 Elsevier Ireland Ltd. Source


Peek C.B.,Metabolism and Molecular Medicine | Peek C.B.,Northwestern University | Ramsey K.M.,Metabolism and Molecular Medicine | Ramsey K.M.,Northwestern University | And 4 more authors.
Trends in Endocrinology and Metabolism | Year: 2012

The circadian system synchronizes behavioral and physiologic processes with daily changes in the external light-dark cycle, optimizing energetic cycles with the rising and setting of the sun. Molecular clocks are organized hierarchically, with neural clocks orchestrating the daily switch between periods of feeding and fasting, and peripheral clocks generating 24. h oscillations of energy storage and utilization. Recent studies indicate that clocks respond to nutrient signals and that a high-fat diet influences the period of locomotor activity under free-running conditions, a core property of the clock. A major goal is to identify the molecular basis for the reciprocal relation between metabolic and circadian pathways. Here the role of peptidergic hormones and macromolecules as nutrient signals integrating circadian and metabolic systems is highlighted. © 2012 Elsevier Ltd. Source

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