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Articles by R Roberts
Total Records ( 5 ) for R Roberts
  C Glicksman , D. J Pournaras , M Wright , R Roberts , D Mahon , R Welbourn , R Sherwood , J Alaghband Zadeh and C. W. le Roux
  Background

Bile acids can act as signalling molecules via various receptors including the nuclear farnesoid X receptor (FXR) and pregnane X receptor (PXR), and the cell surface G-protein-coupled receptor TGR5. The signalling has been implicated in the release of peptide YY (PYY) and glucagon-like peptide 1 (GLP-1), which improves glycaemic control and energy expenditure. We investigated whether morbidly obese subjects have altered postprandial bile acid responses in comparison to normal weight subjects.

Method

Blood samples were taken every 30 min from 0 to 180 min following a 400 kcal test meal. Samples were taken from 12 normal weight subjects with a body mass index (BMI) of 23.2 (2.8) kg/m2 (median [interquartile range (IQR)]) and seven obese patients with a BMI of 47.2 (7.2) kg/m2. Fractionated bile acids were measured on these samples using high-performance liquid chromatography tandem mass spectrometry.

Results

The obese subjects showed a lower postprandial response in total bile acids compared with the normal weight subjects. An increase of 6.4 (5.0) and 2.6 (3.3) µmol/L (median [IQR]) in normal weight and obese subjects was observed, respectively (P = 0.02). The difference was predominantly due to the glycine-conjugated fraction (P = 0.03). There was no difference in the increase of the unconjugated or taurine-conjugated fractions.

Conclusions

The decreased postprandial bile acid response in obese subjects compared with normal weight subjects may partly explain the suboptimal GLP-1 and PYY responses and could affect appetite, glycaemic control and energy expenditure.

  J Stone , A Carson , R Duncan , R Coleman , R Roberts , C Warlow , C Hibberd , G Murray , R Cull , A Pelosi , J Cavanagh , K Matthews , R Goldbeck , R Smyth , J Walker , A.D MacMahon and M. Sharpe
 

It has been previously reported that a substantial proportion of newly referred neurology out-patients have symptoms that are considered by the assessing neurologist as unexplained by ‘organic disease’. There has however been much controversy about how often such patients subsequently develop a disease diagnosis that, with hindsight, would have explained the symptoms. We aimed to determine in a large sample of new neurology out-patients: (i) what proportion are assessed as having symptoms unexplained by disease and the diagnoses given to them; and (ii) how often a neurological disorder emerged which, with hindsight, explained the original symptoms. We carried out a prospective cohort study of patients referred from primary care to National Health Service neurology clinics in Scotland, UK. Measures were: (i) the proportion of patients with symptoms rated by the assessing neurologist as ‘not at all’ or only ‘somewhat explained’ by ‘organic disease’ and the neurological diagnoses recorded at initial assessment; and (ii) the frequency of unexpected new diagnoses made over the following 18 months (according to the primary-care physician). One thousand four hundred and forty-four patients (30% of all new patients) were rated as having symptoms ‘not at all’ or only ‘somewhat explained’ by ‘organic disease’. The most common categories of diagnosis were: (i) organic neurological disease but with symptoms unexplained by it (26%); (ii) headache disorders (26%); and (iii) conversion symptoms (motor, sensory or non-epileptic attacks) (18%). At follow-up only 4 out of 1030 patients (0.4%) had acquired an organic disease diagnosis that was unexpected at initial assessment and plausibly the cause of the patients’ original symptoms. Eight patients had died at follow-up; five of whom had initial diagnoses of non-epileptic attacks. Seven other types of diagnostic change with very different implications to a ‘missed diagnosis’ were found and a new classification of diagnostic revision is presented. One-third of new neurology out-patients are assessed as having symptoms ‘unexplained by organic disease’. A new diagnosis, which with hindsight explained the original symptoms, rarely became apparent to the patient's primary care doctor in the 18 months following the initial hospital consultation.

  K. D Folmes , A. Y.M Chan , D. P.Y Koonen , T. C Pulinilkunnil , I Baczko , B. E Hunter , S Thorn , M. F Allard , R Roberts , M. H Gollob , P. E Light and J. R.B. Dyck
 

Background— Humans with an R302Q mutation in AMPK2 (the PRKAG2 gene) develop a glycogen storage cardiomyopathy characterized by a familial form of Wolff-Parkinson-White syndrome and cardiac hypertrophy. This phenotype is recapitulated in transgenic mice with cardiomyocyte-restricted expression of AMPK2R302Q. Although considerable information is known regarding the consequences of harboring the 2R302Q mutation, little is known about the early signaling events that contribute to the development of this cardiomyopathy.

Methods and Results— To distinguish the direct effects of 2R302Q expression from later compensatory alterations in signaling, we used transgenic mice expressing either the wild-type AMPK2 subunit (TG2WT) or the mutated form (TG2R302Q), in combination with acute expression of these proteins in neonatal rat cardiomyocytes. Although acute expression of 2R302Q induces AMPK activation and upregulation of glycogen synthase and AS160, with an associated increase in glycogen content, AMPK activity, glycogen synthase activity, and AS160 expression are reduced in hearts from TG2R302Q mice, likely in response to the existing 37-fold increase in glycogen. Interestingly, 2WT expression has similar, yet less marked effects than 2R302Q expression in both cardiomyocytes and hearts.

Conclusions— Using acute and chronic models of 2R302Q expression, we have differentiated the direct effects of the 2R302Q mutation from eventual compensatory modifications. Our data suggest that expression of 2R302Q induces AMPK activation and the eventual increase in glycogen content, a finding that is masked in hearts from transgenic adult mice. These findings are the first to highlight temporal differences in the effects of the PRKAG2 R302Q mutation on cardiac metabolic signaling events.

  R. W Davies , S Dandona , A. F. R Stewart , L Chen , S. G Ellis , W. H Wilson Tang , S. L Hazen , R Roberts , R McPherson and G. A. Wells
  Background—

Genome-wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) at multiple loci that are significantly associated with coronary artery disease (CAD) risk. In this study, we sought to determine and compare the predictive capabilities of 9p21.3 alone and a panel of SNPs identified and replicated through GWAS for CAD.

Methods and Results—

We used the Ottawa Heart Genomics Study (OHGS) (3323 cases, 2319 control subjects) and the Wellcome Trust Case Control Consortium (WTCCC) (1926 cases, 2938 control subjects) data sets. We compared the ability of allele counting, logistic regression, and support vector machines. Two sets of SNPs, 9p21.3 alone and a set of 12 SNPs identified by GWAS and through a model-fitting procedure, were considered. Performance was assessed by measuring area under the curve (AUC) for OHGS using 10-fold cross-validation and WTCCC as a replication set. AUC for logistic regression using OHGS increased significantly from 0.555 to 0.608 (P=3.59x10–14) for 9p21.3 versus the 12 SNPs, respectively. This difference remained when traditional risk factors were considered in a subgroup of OHGS (1388 cases, 2038 control subjects), with AUC increasing from 0.804 to 0.809 (P=0.037). The added predictive value over and above the traditional risk factors was not significant for 9p21.3 (AUC 0.801 versus 0.804, P=0.097) but was for the 12 SNPs (AUC 0.801 versus 0.809, P=0.0073). Performance was similar between OHGS and WTCCC. Logistic regression outperformed both support vector machines and allele counting.

Conclusions—

Using the collective of 12 SNPs confers significantly greater predictive capabilities for CAD than 9p21.3, whether traditional risks are or are not considered. More accurate models probably will evolve as additional CAD-associated SNPs are identified.

  M Preuss , I. R Konig , J. R Thompson , J Erdmann , D Absher , T. L Assimes , S Blankenberg , E Boerwinkle , L Chen , L. A Cupples , A. S Hall , E Halperin , C Hengstenberg , H Holm , R Laaksonen , M Li , W Marz , R McPherson , K Musunuru , C. P Nelson , M Susan Burnett , S. E Epstein , C. J O'Donnell , T Quertermous , D. J Rader , R Roberts , A Schillert , K Stefansson , A. F. R Stewart , G Thorleifsson , B. F Voight , G. A Wells , A Ziegler , S Kathiresan , M. P Reilly , N. J Samani , H Schunkert and on behalf of the CARDIoGRAM Consortium
  Background—

Recent genome-wide association studies (GWAS) of myocardial infarction (MI) and other forms of coronary artery disease (CAD) have led to the discovery of at least 13 genetic loci. In addition to the effect size, power to detect associations is largely driven by sample size. Therefore, to maximize the chance of finding novel susceptibility loci for CAD and MI, the Coronary ARtery DIsease Genome-wide Replication And Meta-analysis (CARDIoGRAM) consortium was formed.

Methods and Results—

CARDIoGRAM combines data from all published and several unpublished GWAS in individuals with European ancestry; includes >22 000 cases with CAD, MI, or both and >60 000 controls; and unifies samples from the Atherosclerotic Disease VAscular functioN and genetiC Epidemiology study, CADomics, Cohorts for Heart and Aging Research in Genomic Epidemiology, deCODE, the German Myocardial Infarction Family Studies I, II, and III, Ludwigshafen Risk and Cardiovascular Heath Study/AtheroRemo, MedStar, Myocardial Infarction Genetics Consortium, Ottawa Heart Genomics Study, PennCath, and the Wellcome Trust Case Control Consortium. Genotyping was carried out on Affymetrix or Illumina platforms followed by imputation of genotypes in most studies. On average, 2.2 million single nucleotide polymorphisms were generated per study. The results from each study are combined using meta-analysis. As proof of principle, we meta-analyzed risk variants at 9p21 and found that rs1333049 confers a 29% increase in risk for MI per copy (P=2x10–20).

Conclusion—

CARDIoGRAM is poised to contribute to our understanding of the role of common genetic variation on risk for CAD and MI.

 
 
 
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