scholarly article | Q13442814 |
P50 | author | Michael Marmot | Q1928530 |
Stephen E Humphries | Q51751590 | ||
Mika Kivimäki | Q37386335 | ||
Meena Kumari | Q37390225 | ||
Philippa Talmud | Q37390347 | ||
Aroon Hingorani | Q47156734 | ||
P2093 | author name string | Eric J Brunner | |
Jackie A Cooper | |||
P2860 | cites work | Post genome-wide association studies of novel genes associated with type 2 diabetes show gene-gene interaction and high predictive value | Q21092217 |
Projections of global mortality and burden of disease from 2002 to 2030 | Q21144688 | ||
Prediction of Coronary Heart Disease Using Risk Factor Categories | Q22241923 | ||
Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls | Q24550675 | ||
Mortality in relation to smoking: 50 years' observations on male British doctors | Q24563394 | ||
A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity | Q24650037 | ||
Homeostasis model assessment: insulin resistance and ?-cell function from fasting plasma glucose and insulin concentrations in man | Q26776977 | ||
Health inequalities among British civil servants: the Whitehall II study | Q28243710 | ||
A genome-wide association study identifies novel risk loci for type 2 diabetes | Q28287727 | ||
Myocardial infarction and coronary deaths in the World Health Organization MONICA Project. Registration procedures, event rates, and case-fatality rates in 38 populations from 21 countries in four continents. | Q50119393 | ||
Prediction of incident diabetes mellitus in middle-aged adults: the Framingham Offspring Study. | Q51470643 | ||
Cohort Profile: The Whitehall II study | Q57241528 | ||
Association of Transcription Factor 7-Like 2 (TCF7L2) Variants With Type 2 Diabetes in a Finnish Sample | Q57317723 | ||
Combined analysis of 19 common validated type 2 diabetes susceptibility gene variants shows moderate discriminative value and no evidence of gene–gene interaction | Q57364039 | ||
A Large-Scale Association Analysis of Common Variation of the HNF1 Gene With Type 2 Diabetes in the U.K. Caucasian Population | Q63352764 | ||
Confidence interval estimation of interaction | Q67550286 | ||
Application of high-performance liquid chromatography in establishing an accurate index of blood glucose control | Q68670464 | ||
Measurement of free insulin concentrations: the influence of the timing of extraction of insulin antibodies | Q69925445 | ||
Replication of genome-wide association signals in UK samples reveals risk loci for type 2 diabetes | Q28680760 | ||
Genetic variation in the gene encoding calpain-10 is associated with type 2 diabetes mellitus | Q28771769 | ||
Meta-analysis of genome-wide association data and large-scale replication identifies additional susceptibility loci for type 2 diabetes | Q29417138 | ||
A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants | Q29547210 | ||
Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels | Q29547214 | ||
Efficacy and safety of cholesterol-lowering treatment: prospective meta-analysis of data from 90,056 participants in 14 randomised trials of statins | Q29547856 | ||
Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond | Q29614697 | ||
Pharmacological and lifestyle interventions to prevent or delay type 2 diabetes in people with impaired glucose tolerance: systematic review and meta-analysis | Q30829257 | ||
Combining information from common type 2 diabetes risk polymorphisms improves disease prediction | Q33259329 | ||
Concept, design and implementation of a cardiovascular gene-centric 50 k SNP array for large-scale genomic association studies | Q33381588 | ||
Are variants in the CAPN10 gene related to risk of type 2 diabetes? A quantitative assessment of population and family-based association studies | Q33909587 | ||
Genotype score in addition to common risk factors for prediction of type 2 diabetes | Q34884376 | ||
Clinical risk factors, DNA variants, and the development of type 2 diabetes | Q34884389 | ||
Systematic review and meta-analysis of the association between complement factor H Y402H polymorphisms and age-related macular degeneration | Q36564570 | ||
Predicting cardiovascular risk in England and Wales: prospective derivation and validation of QRISK2. | Q36738148 | ||
Assessing the combined impact of 18 common genetic variants of modest effect sizes on type 2 diabetes risk | Q36943793 | ||
Predicting risk of type 2 diabetes in England and Wales: prospective derivation and validation of QDScore | Q37138275 | ||
New gene variants alter type 2 diabetes risk predominantly through reduced beta-cell function | Q37187240 | ||
Genome-wide association study for type 2 diabetes: clinical applications | Q37412138 | ||
Methods for Determining the Amount of Glucose in Blood | Q39931660 | ||
Predicting type 2 diabetes based on polymorphisms from genome-wide association studies: a population-based study | Q40060574 | ||
Chromosome 9p21.3 coronary heart disease locus genotype and prospective risk of CHD in healthy middle-aged men. | Q40126925 | ||
Simple scoring scheme for calculating the risk of acute coronary events based on the 10-year follow-up of the prospective cardiovascular Münster (PROCAM) study | Q40664994 | ||
Risk prediction of prevalent diabetes in a Swiss population using a weighted genetic score--the CoLaus Study | Q43952022 | ||
Population-based incidence rates and risk factors for type 2 diabetes in white individuals: the Bruneck study | Q44953922 | ||
A simple risk score identifies individuals at high risk of developing Type 2 diabetes: a prospective cohort study | Q46564797 | ||
Impact of common type 2 diabetes risk polymorphisms in the DESIR prospective study | Q46918373 | ||
P407 | language of work or name | English | Q1860 |
P921 | main subject | type 2 diabetes | Q3025883 |
P304 | page(s) | b4838 | |
P577 | publication date | 2010-01-14 | |
P1433 | published in | The BMJ | Q546003 |
P1476 | title | Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study | |
P478 | volume | 340 |
Q36210172 | A genotype risk score predicts type 2 diabetes from young adulthood: the CARDIA study |
Q35512242 | A methodological perspective on genetic risk prediction studies in type 2 diabetes: recommendations for future research |
Q33734310 | A new explained-variance based genetic risk score for predictive modeling of disease risk |
Q35532280 | Advances in risk prediction of type 2 diabetes: integrating genetic scores with Framingham risk models |
Q35059477 | Age trajectories of glycaemic traits in non-diabetic South Asian and white individuals: the Whitehall II cohort study. |
Q35014452 | Air pollution as a risk factor for type 2 diabetes |
Q36845050 | Animal models of GWAS-identified type 2 diabetes genes |
Q26999723 | Annotating individual human genomes |
Q49464137 | Application of Single-Nucleotide Polymorphism-Related Risk Estimates in Identification of Increased Genetic Susceptibility to Cardiovascular Diseases: A Literature Review. |
Q39329097 | Association between periodontitis needing surgical treatment and subsequent diabetes risk: a population-based cohort study. |
Q84931424 | Association of ACACB polymorphisms with obesity and diabetes |
Q37087883 | Association of environmental and genetic factors and gene-environment interactions with risk of developing rheumatoid arthritis |
Q34476646 | Association of the vitamin D binding protein polymorphisms with the risk of type 2 diabetes mellitus: a meta-analysis |
Q38171656 | Behavior genetics: past, present, future |
Q57805973 | Benzene exposure induces insulin resistance in mice |
Q57659515 | Biomarker und Risikoprädiktion des Typ-2-Diabetes |
Q37886659 | Biomarkers for the prediction of type 2 diabetes and cardiovascular disease |
Q56336997 | Candidate Genes and Political Behavior |
Q91655346 | Cardiovascular precision medicine: Bad news from the front? |
Q38216627 | Chasing Mendel: five questions for personalized medicine |
Q37504084 | Co-occurrence of risk alleles in or near genes modulating insulin secretion predisposes obese youth to prediabetes |
Q54387343 | Combining 33 genetic variants with prostate-specific antigen for prediction of prostate cancer: longitudinal study. |
Q34399372 | Common genetic variants are significant risk factors for early menopause: results from the Breakthrough Generations Study |
Q37214131 | Common variants in the ATP2B1 gene are associated with susceptibility to hypertension: the Japanese Millennium Genome Project |
Q46047123 | Current directions in behavioral medicine research on genetic testing for disease susceptibility: introduction to the special section |
Q34606541 | Developing genetic epidemiological models to predict risk for nasopharyngeal carcinoma in high-risk population of China |
Q36898879 | Development and evaluation of a genetic risk score for obesity |
Q30419790 | Development of GMDR-GPU for gene-gene interaction analysis and its application to WTCCC GWAS data for type 2 diabetes |
Q51351800 | Development of a new scoring system for predicting the 5 year incidence of type 2 diabetes in Japan: the Toranomon Hospital Health Management Center Study 6 (TOPICS 6). |
Q57659474 | Diabetesrisikoscores |
Q38974295 | Distribution Characteristics and Combined Effect of Polymorphisms Affecting Alcohol Consumption Behaviour in the Hungarian General and Roma Populations |
Q61814477 | Driving Type 2 Diabetes Risk Scores into Clinical Practice: Performance Analysis in Hospital Settings |
Q34307658 | Effect of communicating genetic and phenotypic risk for type 2 diabetes in combination with lifestyle advice on objectively measured physical activity: protocol of a randomised controlled trial |
Q36099476 | Effect of five genetic variants associated with lung function on the risk of chronic obstructive lung disease, and their joint effects on lung function |
Q47097715 | Enrichment of minor allele of SNPs and genetic prediction of type 2 diabetes risk in British population. |
Q34411784 | Epidemiological studies of CHD and the evolution of preventive cardiology |
Q30834328 | Estimating the predictive ability of genetic risk models in simulated data based on published results from genome-wide association studies |
Q37034684 | Evaluation of genetic risk score models in the presence of interaction and linkage disequilibrium |
Q36065519 | Evaluation of genetic risk scores for prediction of dichotomous outcomes. |
Q37717813 | Evidences of +896 A/G TLR4 polymorphism as an indicative of prevalence of complications in T2DM patients |
Q38052761 | From genotype to human β cell phenotype and beyond |
Q33638105 | Gene-lifestyle interaction and type 2 diabetes: the EPIC interact case-cohort study |
Q38974166 | Genetic Association and Risk Scores in a Chronic Obstructive Pulmonary Disease Meta-analysis of 16,707 Subjects. |
Q58763341 | Genetic Determinants of Telomere Length in African American Youth |
Q35761568 | Genetic Testing and Type 2 Diabetes Risk Awareness |
Q40396533 | Genetic Variants Influencing Joint Damage in Mexican Americans and European Americans With Rheumatoid Arthritis |
Q38025234 | Genetic advances of type 2 diabetes in Chinese populations |
Q34153165 | Genetic associations in diabetic nephropathy: a meta-analysis |
Q37193385 | Genetic modifiers of cystic fibrosis-related diabetes |
Q26822607 | Genetic prediction of common diseases. Still no help for the clinical diabetologist! |
Q42399357 | Genetic risk prediction for CKD: a journey of a thousand miles |
Q33807014 | Genetic risk profiling for prediction of type 2 diabetes |
Q39295277 | Genetic risk scores and number of autoantibodies in patients with rheumatoid arthritis |
Q50606693 | Genetic risk scores in the prediction of plasma glucose, impaired insulin secretion, insulin resistance and incident type 2 diabetes in the METSIM study. |
Q36111952 | Genetic risk sum score comprised of common polygenic variation is associated with body mass index |
Q26829897 | Genetic screening for the risk of type 2 diabetes: worthless or valuable? |
Q53910369 | Genetics in population health science: strategies and opportunities. |
Q35808509 | Genetics of Type 2 Diabetes and Clinical Utility. |
Q51372835 | Genetics of type 2 diabetes. |
Q33593963 | Genetics of type 2 diabetes: insights into the pathogenesis and its clinical application |
Q28302158 | Genetics of type 2 diabetes: pathophysiologic and clinical relevance |
Q33947336 | Genome Wide Association Study to predict severe asthma exacerbations in children using random forests classifiers |
Q30427183 | Genome-wide association and large-scale follow up identifies 16 new loci influencing lung function. |
Q26825851 | Genome-wide association studies of chronic kidney disease: what have we learned? |
Q85246836 | Genomic risk prediction |
Q35113219 | Genomic risk profiling: attitudes and use in personal and clinical care of primary care physicians who offer risk profiling. |
Q38327711 | Genomic-based tools for the risk assessment, management, and prevention of type 2 diabetes |
Q38103168 | Genomics of elite sporting performance: what little we know and necessary advances. |
Q36355974 | Genotype prediction of adult type 2 diabetes from adolescence in a multiracial population |
Q33351391 | Giant sucking sound: can physiology fill the intellectual void left by the reductionists? |
Q39003864 | High Prevalence of Smoking in the Roma Population Seems to Have No Genetic Background |
Q98568523 | High genetic burden of type 2 diabetes can promote the high prevalence of disease: a longitudinal cohort study in Iran |
Q34349950 | How accurate can genetic predictions be? |
Q36166473 | How genes influence life span: the biodemography of human survival |
Q45976084 | Hyperuricemia in young adults and risk of insulin resistance, prediabetes, and diabetes: a 15-year follow-up study. |
Q36852845 | IRS1 gene variants, dysglycaemic metabolic changes and type-2 diabetes risk. |
Q26770167 | Improved prediction of complex diseases by common genetic markers: state of the art and further perspectives |
Q36017113 | Inclusion of gene-gene and gene-environment interactions unlikely to dramatically improve risk prediction for complex diseases |
Q36547686 | Innate biology versus lifestyle behaviour in the aetiology of obesity and type 2 diabetes: the GLACIER Study |
Q38262599 | Insights into the genetic susceptibility to type 2 diabetes from genome-wide association studies of glycaemic traits. |
Q47570610 | Integration of Distributed Services and Hybrid Models Based on Process Choreography to Predict and Detect Type 2 Diabetes. |
Q26859442 | Is genetic testing useful to predict type 2 diabetes? |
Q36572172 | Lack of association of the HMGA1 IVS5-13insC variant with type 2 diabetes in an ethnically diverse hypertensive case control cohort |
Q34430295 | Meta-analysis of the relationship between common type 2 diabetes risk gene variants with gestational diabetes mellitus |
Q41491446 | Meta-analytic research on the relationship between cumulative risk alleles and risk of type 2 diabetes mellitus. |
Q41505838 | Neuronal cell adhesion genes: Key players in risk for schizophrenia, bipolar disorder and other neurodevelopmental brain disorders? |
Q34382115 | New onset of diabetes after transplantation - an overview of epidemiology, mechanism of development and diagnosis |
Q35620221 | New-onset diabetes after renal transplantation: risk assessment and management |
Q36477823 | Novel risk factors and the prediction of type 2 diabetes in the Atherosclerosis Risk in Communities (ARIC) study |
Q38187946 | Nutrigenetics: bridging two worlds to understand type 2 diabetes. |
Q35624242 | Performance of a genetic risk score for CKD stage 3 in the general population |
Q24289193 | Personalized medicine: hope or hype? |
Q34150453 | Phenomics: the next challenge |
Q33646775 | Polygenic type 2 diabetes prediction at the limit of common variant detection |
Q37220830 | Predicting risk of type 2 diabetes mellitus with genetic risk models on the basis of established genome-wide association markers: a systematic review |
Q34998359 | Predicting the risk of rheumatoid arthritis and its age of onset through modelling genetic risk variants with smoking |
Q92760833 | Prediction model for the efficacy of folic acid therapy on hyperhomocysteinaemia based on genetic risk score methods |
Q39346397 | Prediction of type 2 diabetes in women with a history of gestational diabetes using a genetic risk score |
Q35565720 | Predictive genetic testing for the identification of high-risk groups: a simulation study on the impact of predictive ability |
Q38067242 | Prognostic models in the clinical arena |
Q40040989 | Risk assessment models for genetic risk predictors of lung cancer using two-stage replication for Asian and European populations |
Q46918161 | Risk categorization for complex disorders according to genotype relative risk and precision in parameter estimates. |
Q37859373 | Risk modeling strategies for pharmacogenetic studies |
Q35575823 | Risk models and scores for type 2 diabetes: systematic review |
Q39674639 | Risk prediction models: a framework for assessment |
Q34248203 | Rs7206790 and rs11644943 in FTO gene are associated with risk of obesity in Chinese school-age population |
Q24307634 | SNPs in axon guidance pathway genes and susceptibility for Parkinson's disease in the Korean population |
Q43136206 | San Antonio heart study diabetes prediction model applicable to a Middle Eastern population? Tehran glucose and lipid study |
Q37882225 | Screening for type 2 diabetes and dysglycemia |
Q36168758 | Sex-Specific Parental Effects on Offspring Lipid Levels |
Q35532317 | Sixty-five common genetic variants and prediction of type 2 diabetes |
Q35631474 | Sodium butyrate epigenetically modulates high-fat diet-induced skeletal muscle mitochondrial adaptation, obesity and insulin resistance through nucleosome positioning |
Q47136255 | Statistical methods to detect pleiotropy in human complex traits |
Q24289354 | Strengthening the reporting of genetic risk prediction studies (GRIPS): explanation and elaboration. |
Q24289476 | Strengthening the reporting of genetic risk prediction studies (GRIPS): explanation and elaboration |
Q56632047 | Strengthening the reporting of genetic risk prediction studies (GRIPS): explanation and elaboration |
Q37827645 | Ten questions about systems biology |
Q36742590 | The benefits of using genetic information to design prevention trials |
Q30249029 | The effect of communicating the genetic risk of cardiometabolic disorders on motivation and actual engagement in preventative lifestyle modification and clinical outcome: a systematic review and meta-analysis of randomised controlled trials. |
Q34353579 | The effect of renin angiotensin system genetic variants in acute pancreatitis |
Q37895457 | The genetics of common kidney disease: a pathway toward clinical relevance. |
Q38061186 | The genetics of type 2 diabetes and its clinical relevance |
Q41420032 | The impact of PNPLA3 and JAZF1 on hepatocellular carcinoma in non-viral hepatitis patients with type 2 diabetes mellitus. |
Q38265561 | The impact of cytomegalovirus infection on new-onset diabetes mellitus after kidney transplantation: a review on current findings. |
Q37483686 | The known genetic loci for telomere length may be involved in the modification of telomeres length after birth |
Q33687505 | The link between family history and risk of type 2 diabetes is not explained by anthropometric, lifestyle or genetic risk factors: the EPIC-InterAct study |
Q38146916 | The potential of novel biomarkers to improve risk prediction of type 2 diabetes |
Q34735432 | The value of genetic information for diabetes risk prediction - differences according to sex, age, family history and obesity |
Q37953791 | The worldwide epidemiology of type 2 diabetes mellitus--present and future perspectives |
Q37642781 | Translating genomics into improved healthcare |
Q38162828 | Type 2 diabetes mellitus in pediatrics: a new challenge |
Q45048753 | Type 2 diabetes-related genetic risk scores associated with variations in fasting plasma glucose and development of impaired glucose homeostasis in the prospective DESIR study |
Q36384522 | Use of genomic panels to determine risk of developing type 2 diabetes in the general population: a targeted evidence-based review |
Q46938393 | Use of reclassification for assessment of improved prediction: an empirical evaluation |
Q36876237 | Using genetic information from candidate gene and genome-wide association studies in risk prediction for alcohol dependence |
Q57416703 | Using genetics to predict the natural history of asthma? |
Q30248720 | Utility of nonblood-based risk assessment for predicting type 2 diabetes mellitus: A meta-analysis |
Q35905115 | Utilizing Genetic Predisposition Score in Predicting Risk of Type 2 Diabetes Mellitus Incidence: A Community-based Cohort Study on Middle-aged Koreans. |
Q38026994 | What can genetics tell us about the cause of fixed airflow obstruction? |
Q36374101 | What will diabetes genomes tell us? |
Search more.