scholarly journals Harnessing the power of polygenic risk scores to predict type 2 diabetes and its subtypes in a high-risk population of British Pakistanis and Bangladeshis in a routine healthcare setting

2021 ◽  
Author(s):  
Sam Hodgson ◽  
Qin Qin Huang ◽  
Neneh Sallah ◽  
Chris J Griffiths ◽  
William Newman ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
High Risk ◽  
European Ancestry ◽  
Risk Scores ◽  
P Value ◽  
High Risk Population ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
British Pakistanis

Background: Type 2 diabetes is a heterogeneous condition highly prevalent in British Pakistanis and Bangladeshis (BPB). The Genes & Health (G&H) cohort offers means to explore genetic determinants of disease in BPBs, combining genetic and lifelong health record data. Methods: We assessed whether common genetic loci associated with type 2 diabetes in European-ancestry individuals (EUR) replicate in G&H. We constructed a type 2 diabetes polygenic risk score (PRS) and combined it with a clinical risk instrument (QDiabetes) to build a novel, integrated risk tool (IRT). We compared IRT performance using net reclassification index (NRI) versus QDiabetes alone. We assessed the ability of the PRS to predict type 2 diabetes following gestational diabetes (GDM). We compared PRS distribution between type 2 diabetes subgroups identified by clinical features at diagnosis. Findings: Accounting for power, we replicated fewer loci associated with type 2 diabetes in G&H (n = 76/338, 22%) than would be expected if all EUR-ascertained loci were transferable (n = 95, 28%) (binomial p value = 0.01). In 13,648 patients free from type 2 diabetes followed up for 10 years, NRI was 3.2% for IRT versus QDiabetes (95% confidence interval 2.0 - 4.4%). IRT performance was best in reclassification of young adults deemed low risk by QDiabetes as high risk. PRS was independently associated with progression to type 2 diabetes after GDM (p = 0.028). Mean type 2 diabetes PRS differed between phenotypically-defined type 2 diabetes subgroups (p = 0.002). Interpretation: The type 2 diabetes PRS has broad potential clinical application in BPB, improving identification of type 2 diabetes risk (especially in the young), and characterisation of type 2 diabetes subgroups at diagnosis. Funding: Wellcome Trust, MRC, NIHR, and others. Full funding disclosed within.

scholarly journals Systematic Review of Polygenic Risk Scores for Type 1 and Type 2 Diabetes

2020 ◽  
Vol 21 (5) ◽  
pp. 1703 ◽  
Author(s):  
Felipe Padilla-Martínez ◽  
Francois Collin ◽  
Miroslaw Kwasniewski ◽  
Adam Kretowski
Keyword(s):  
Systematic Review ◽  
Type 2 Diabetes ◽  
Area Under The Curve ◽  
Healthy People ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Polygenic Risk ◽  
Diabetes Patients

Recent studies have led to considerable advances in the identification of genetic variants associated with type 1 and type 2 diabetes. An approach for converting genetic data into a predictive measure of disease susceptibility is to add the risk effects of loci into a polygenic risk score. In order to summarize the recent findings, we conducted a systematic review of studies comparing the accuracy of polygenic risk scores developed during the last two decades. We selected 15 risk scores from three databases (Scopus, Web of Science and PubMed) enrolled in this systematic review. We identified three polygenic risk scores that discriminate between type 1 diabetes patients and healthy people, one that discriminate between type 1 and type 2 diabetes, two that discriminate between type 1 and monogenic diabetes and nine polygenic risk scores that discriminate between type 2 diabetes patients and healthy people. Prediction accuracy of polygenic risk scores was assessed by comparing the area under the curve. The actual benefits, potential obstacles and possible solutions for the implementation of polygenic risk scores in clinical practice were also discussed. Develop strategies to establish the clinical validity of polygenic risk scores by creating a framework for the interpretation of findings and their translation into actual evidence, are the way to demonstrate their utility in medical practice.

scholarly journals Validation of a Trans-Ancestry Polygenic Risk Score for Type 2 Diabetes in Diverse Populations

2021 ◽  
Author(s):  
Tian Ge ◽  
Amit Patki ◽  
Vinodh Srinivasasainagendra ◽  
Yen-Feng Lin ◽  
Marguerite Ryan Irvin ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
African American ◽  
Large Scale ◽  
Association Studies ◽  
Risk Scores ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk

ABSTRACTType 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for an equitable deployment of PRS to clinical practice that benefits global populations. Here we integrate T2D GWAS in European, African American and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and evaluate the PRS in the multi-ethnic eMERGE study, four African American cohorts, and the Taiwan Biobank. The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined, and the top 2% of the PRS distribution can identify individuals with an approximately 2.5-4.5 fold of increase in T2D risk, suggesting the potential of using the trans-ancestry PRS as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare.

Genome-wide polygenic risk score for retinopathy of type 2 diabetes

2021 ◽  
Author(s):  
Iain S Forrest ◽  
Kumardeep Chaudhary ◽  
Ishan Paranjpe ◽  
Ha My T Vy ◽  
Carla Marquez-Luna ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Risk Score ◽  
Large Scale ◽  
European Ancestry ◽  
Polygenic Risk Score ◽  
Standard Deviation Increase ◽  
Polygenic Risk ◽  
Genome Wide ◽  
A Genome

Abstract Diabetic retinopathy (DR) is a common consequence in type 2 diabetes (T2D) and a leading cause of blindness in working-age adults. Yet, its genetic predisposition is largely unknown. Here, we examined the polygenic architecture underlying DR by deriving and assessing a genome-wide polygenic risk score (PRS) for DR. We evaluated the PRS in 6079 individuals with T2D of European, Hispanic, African and other ancestries from a large-scale multi-ethnic biobank. Main outcomes were PRS association with DR diagnosis, symptoms and complications, and time to diagnosis, and transferability to non-European ancestries. We observed that PRS was significantly associated with DR. A standard deviation increase in PRS was accompanied by an adjusted odds ratio (OR) of 1.12 [95% confidence interval (CI) 1.04–1.20; P = 0.001] for DR diagnosis. When stratified by ancestry, PRS was associated with the highest OR in European ancestry (OR = 1.22, 95% CI 1.02–1.41; P = 0.049), followed by African (OR = 1.15, 95% CI 1.03–1.28; P = 0.028) and Hispanic ancestries (OR = 1.10, 95% CI 1.00–1.10; P = 0.050). Individuals in the top PRS decile had a 1.8-fold elevated risk for DR versus the bottom decile (P = 0.002). Among individuals without DR diagnosis, the top PRS decile had more DR symptoms than the bottom decile (P = 0.008). The PRS was associated with retinal hemorrhage (OR = 1.44, 95% CI 1.03–2.02; P = 0.03) and earlier DR presentation (10% probability of DR by 4 years in the top PRS decile versus 8 years in the bottom decile). These results establish the significant polygenic underpinnings of DR and indicate the need for more diverse ancestries in biobanks to develop multi-ancestral PRS.

1645-P: Polygenic Risk Score for Prediction of Complications in Men and Women with Type 2 Diabetes

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1645-P
Author(s):  
JOHANNE TREMBLAY ◽  
REDHA ATTAOUA ◽  
MOUNSIF HALOUI ◽  
RAMZAN TAHIR ◽  
CAROLE LONG ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Risk Score ◽  
Polygenic Risk Score ◽  
Men And Women ◽  
Polygenic Risk ◽  
Prediction Of Complications

304-OR: Polygenic Risk Score Predicts Type 2 Diabetes Susceptibility in a Diverse Consumer Genetic Database

Diabetes ◽  
2019 ◽  
Vol 68 (Supplement 1) ◽  
pp. 304-OR
Author(s):  
MICHAEL L. MULTHAUP ◽  
RYOSUKE KITA ◽  
NICHOLAS ERIKSSON ◽  
STELLA ASLIBEKYAN ◽  
JANIE SHELTON ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Risk Score ◽  
Polygenic Risk Score ◽  
Diabetes Susceptibility ◽  
Genetic Database ◽  
Polygenic Risk

scholarly journals Polygenic risk scores predict diabetes complications and their response to intensive blood pressure and glucose control

Diabetologia ◽  
2021 ◽  
Author(s):  
Johanne Tremblay ◽  
Mounsif Haloui ◽  
Redha Attaoua ◽  
Ramzan Tahir ◽  
Camil Hishmih ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Type 2 Diabetes ◽  
High Risk ◽  
Glucose Control ◽  
Risk Group ◽  
Cardiovascular Death ◽  
Polygenic Risk ◽  
Renal Complications ◽  
Intensive Blood Pressure

Abstract Aims/hypothesis Type 2 diabetes increases the risk of cardiovascular and renal complications, but early risk prediction could lead to timely intervention and better outcomes. Genetic information can be used to enable early detection of risk. Methods We developed a multi-polygenic risk score (multiPRS) that combines ten weighted PRSs (10 wPRS) composed of 598 SNPs associated with main risk factors and outcomes of type 2 diabetes, derived from summary statistics data of genome-wide association studies. The 10 wPRS, first principal component of ethnicity, sex, age at onset and diabetes duration were included into one logistic regression model to predict micro- and macrovascular outcomes in 4098 participants in the ADVANCE study and 17,604 individuals with type 2 diabetes in the UK Biobank study. Results The model showed a similar predictive performance for cardiovascular and renal complications in different cohorts. It identified the top 30% of ADVANCE participants with a mean of 3.1-fold increased risk of major micro- and macrovascular events (p = 6.3 × 10−21 and p = 9.6 × 10−31, respectively) and a 4.4-fold (p = 6.8 × 10−33) higher risk of cardiovascular death. While in ADVANCE overall, combined intensive blood pressure and glucose control decreased cardiovascular death by 24%, the model identified a high-risk group in whom it decreased the mortality rate by 47%, and a low-risk group in whom it had no discernible effect. High-risk individuals had the greatest absolute risk reduction with a number needed to treat of 12 to prevent one cardiovascular death over 5 years. Conclusions/interpretation This novel multiPRS model stratified individuals with type 2 diabetes according to risk of complications and helped to target earlier those who would receive greater benefit from intensive therapy. Graphical abstract

1134-P: Polygenic Risk Score of Type 2 Diabetes as a Predictive Factor for Macrovascular Complications: A Prospective Population-Based UK Biobank Study

Diabetes ◽  
2021 ◽  
Vol 70 (Supplement 1) ◽  
pp. 1134-P
Author(s):  
SANGHYUK JUNG ◽  
DOKYOON KIM ◽  
MANU SHIVAKUMAR ◽  
HONG-HEE WON ◽  
JAE-SEUNG YUN
Keyword(s):  
Type 2 Diabetes ◽  
Risk Score ◽  
Predictive Factor ◽  
Population Based ◽  
Macrovascular Complications ◽  
Polygenic Risk Score ◽  
Uk Biobank ◽  
Polygenic Risk

03 TOWARDS DISEASE INTERCEPTION: CONTRIBUTION OF POLYGENIC RISK SCORES TOWARDS AGE-DEPENDENT RISK OF IBD IN A HIGH-RISK POPULATION

2019 ◽  
Vol 156 (3) ◽  
pp. S73-S74
Author(s):  
Elizabeth A. Spencer ◽  
Kyle Gettler ◽  
Drew Helmus ◽  
Shannon Telesco ◽  
Amy Hart ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Scores ◽  
High Risk Population ◽  
Risk Population ◽  
Polygenic Risk ◽  
Age Dependent

Glucose intolerance and diabetes

2015 ◽  
Author(s):  
Christina Jarnert ◽  
Linda Mellbin ◽  
Lars Rydén ◽  
Jaakko Tuomilehto
Keyword(s):  
Type 2 Diabetes ◽  
High Risk ◽  
Glucose Metabolism ◽  
Blood Circulation ◽  
High Risk Population ◽  
Primary And Secondary Prevention ◽  
Cvd Risk ◽  
The People ◽  
Elevated Glucose

Diabetes dramatically increases the risk of cardiovascular diseases (CVD). Diabetes is defined by elevated glucose in blood circulation. The level of glycaemia has a graded relation with CVD risk and diabetes is very frequent in people with CVD. In the general population half of the people with type 2 diabetes are undiagnosed, yet efficient methods for population screening exist. Despite considerable improvements in the management of CVD, patients with disturbed glucose metabolism have not benefited to the same extent as those without diabetes. Primary and secondary prevention of CVD in people with diabetes and other disturbances in glucose metabolism must be multifactorial and treatment targets stricter than for patients without glucose aberrations. Increased collaboration between different therapeutic disciplines including diabetologists, cardiologists, general practitioners, and dieticians is key to improved management for this large and high-risk population. Some important aspects of these issues are presented in this chapter.

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