scholarly journals Mitochondrial DNA Coding and Control Region Variants as Genetic Risk Factors for Type 2 Diabetes

Diabetes ◽  
2012 ◽  
Vol 61 (10) ◽  
pp. 2642-2651 ◽  
Author(s):  
C.-W. Liou ◽  
J.-B. Chen ◽  
M.-M. Tiao ◽  
S.-W. Weng ◽  
T.-L. Huang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Mitochondrial Dna ◽  
Control Region ◽  
Genetic Risk ◽  
Genetic Risk Factors ◽  
Dna Coding ◽  
And Control

1655-P: Genetic Risk Factors for Incident Cardiovascular Disease in Type 2 Diabetes Patients

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1655-P
Author(s):  
SOO HEON KWAK ◽  
JOSEP M. MERCADER ◽  
AARON LEONG ◽  
BIANCA PORNEALA ◽  
PEITAO WU ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Cardiovascular Disease ◽  
Genetic Risk ◽  
Genetic Risk Factors ◽  
Incident Cardiovascular Disease ◽  
Diabetes Patients

Admixture in Mexico City: implications for admixture mapping of Type 2 diabetes genetic risk factors

2006 ◽  
Vol 120 (6) ◽  
pp. 807-819 ◽  
Author(s):  
Veronica L. Martinez-Marignac ◽  
Adan Valladares ◽  
Emily Cameron ◽  
Andrea Chan ◽  
Arjuna Perera ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Mexico City ◽  
Genetic Risk ◽  
Genetic Risk Factors ◽  
Admixture Mapping

scholarly journals Utility of genetic and non-genetic risk factors in prediction of type 2 diabetes: Whitehall II prospective cohort study

BMJ ◽  
2010 ◽  
Vol 340 (jan14 1) ◽  
pp. b4838-b4838 ◽  
Author(s):  
P. J Talmud ◽  
A. D Hingorani ◽  
J. A Cooper ◽  
M. G Marmot ◽  
E. J Brunner ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Cohort Study ◽  
Prospective Cohort Study ◽  
Genetic Risk ◽  
Prospective Cohort ◽  
Genetic Risk Factors

scholarly journals 184Are genetic risk factors clinically useful in prognostic models for type 2 diabetes mellitus?

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Vera Helen Buss ◽  
Margo Barr ◽  
Marlien Varnfield ◽  
Mark Harris
Keyword(s):  
Diabetes Mellitus ◽  
Risk Factors ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Genetic Risk ◽  
Prediction Models ◽  
Genetic Risk Factors ◽  
Genetic Models ◽  
Prognostic Models

Abstract Background Many prognostic models exist for the prediction of type 2 diabetes mellitus. Some of these include genetic risk factors. The objective of this review was to investigate whether including genetic variables in prediction models for type 2 diabetes mellitus is clinically useful. Methods Studies were included if they reported on prognostic prediction models for type 2 diabetes mellitus. Seven medical and bioengineering databases were searched using terms regarding risk prediction and diabetes combined via Boolean operators. In studies including genetic variables, the c-statistics of genetic and non-genetic models were compared. Results Seventy-six studies published between 2002 and 2019 were included in the review. Twenty of these (published 2008 to 2019) included genetic variables, namely deleterious alleles and specific small nuclear polymorphisms. Study samples represented the general population. When comparing genetic to non-genetic models, one study reported a statistically significantly greater c-statistic for the genetic and four for the non-genetic models. Adding genetic risk factors to a clinical model did not substantially increase the predictive accuracy of any study. Conclusions The use of genetic data did not show any meaningful improvements in the predictive performance for the general population compared to clinical models. Studies using genetic data were often based on small sample sizes and not externally validated, raising concerns regarding potential overfitting and lack of generalisability. Key messages Currently, the clinical usefulness of genetic risk scores for type 2 diabetes mellitus seems quite limited.

scholarly journals Type 2 diabetes genes – Present status and data from Norwegian studies

2013 ◽  
Vol 23 (1) ◽  
Author(s):  
Jens K. Hertel Hertel ◽  
Stefan Johansson ◽  
Kristian Midthjell ◽  
Ottar Nygård ◽  
Pål R. Njølstad ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Genetic Risk ◽  
Association Studies ◽  
Pancreatic Beta Cell ◽  
Genetic Risk Factors ◽  
Candidate Gene Approach ◽  
Genome Wide Association Studies ◽  
Complex Disorders

The worldwide rise in prevalence of type 2 diabetes has led to an intense search for the genetic risk factors of this disease. In type 2 diabetes and other complex disorders, multiple genetic and environmental factors, as well as the interaction between these factors, determine the phenotype. In this review, we summarize present knowledge, generated by more than two decades of efforts to dissect the genetic architecture of type 2 diabetes. Initial studies were either based on a candidate gene approach or attempted to fine-map signals generated from linkage analysis. Despite the detection of multiple genomic regions proposed to be linked to type 2 diabetes, subsequent positional fine-mapping of candidates were mostly inconclusive. However, the introduction of genome-wide association studies (GWAS), applied on thousands of patients and controls, completely changed the field. To date, more than 50 susceptibility loci for type 2 diabetes have been detected through the establishment of large research consortia, the application of GWAS on intermediary diabetes phenotypes and the use of study samples of different ethnicities. Still, the common variants identified in the GWAS era only explain some of the heritability seen for type 2 diabetes. Thus, focus is now shifting towards searching also for rare variants using new high-throughput sequencing technologies. For genes involved in the genetic predisposition to type 2 diabetes the emerging picture is that there are hundreds of different gene variants working in a complex interplay influencing pancreatic beta cell function/mass and, only to a lesser extent, insulin action. Several Norwegian studies have contributed to the field, extending our understanding of genetic risk factors in type 2 diabetes and in diabetes-related phenotypes like obesity and cardiovascular disease.

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