A Pilot Study- Identify Genetic Variants for Diabetic Cataract Using GoDARTS Dataset

  • Kaida Zhang

    Student thesis: Master's ThesisMaster of Science

    Abstract

    Background: Diabetic cataract is one of the major eye complications of diabetes. It was reported that cataract occurs two to five times more frequently in patients with diabetes compared with those with no diabetes. The purpose of this study was to identify genetic contributors of diabetic cataract based on a genome-wide association approach using a well-defined Scottish diabetic cohort.

    Methods: A diabetic cataract case in this study was defined as a type 2 diabetic patient who has ever been recorded in the linked e-health records to have cataracts in one or both eyes and who had previous cataract extraction surgeries in at least one eye. A control in this study was defined as a type 2 diabetic individual who has never been diagnosed as cataract in the linked e-health records and had no history of cataract surgeries. A standard genome-wide association approach was applied. Besides, the logistic regression was used to analyze the potential risk factors including Age, Gender, Body Mass Index(BMI), Alcohol intake, Total serum cholesterol, High-density lipoprotein(HDL)-cholesterol, Low-density lipoprotein(LDL)-cholesterol, Blood pressure, HbA1c and Serum triglycerides chosen from the literature review.

    Results: Overall, we have 1986 diabetic cataract cases and 3429 controls in the genetics of diabetes audit and research in Tayside Scotland (GoDARTS) dataset. We set the significant P value of Single Nucleotide Polymorphisms (SNP) in the project as 10−6, there are 7 associated Single Nucleotide Polymorphisms in the range of genome-wide significance we set, including rs10197646 (P 4.12x10-7), chr13:48026216:D (P 4.15x10-7), rs7582173 (P 4.30x10-7), rs62168795 (P 5.59x10-7), rs1381015 (P 7.12x10-7), rs2269547 (P 7.25x10-7), rs523355 (P 8.63x10-7). The age-adjusted prevalence of diabetic cataract was 24.9% in the Tayside. We also identified age (odd ratio [OR] 0.955, 95%confidence interval [CI] 0.948-0.962), female (OR 1.191, 95%CI 1.055-1.345), systolic blood pressure (OR 0.997, 95% CI 0.994-0.999) diastolic blood pressure (OR 1.004, 95% 1.001-1.008), current smoker (OR 1.313, 95% CI 1.034-1.667), BMI in 2nd Quartile 27.71-31.32 (OR 0.838, 95% CI 0.703-0.998), total serum cholesterol in 2nd Quartile 3.92-4.37 (OR 0.798, 95% CI 0.642-0.992), serum HDL cholesterol in 3rd Quartile 1.36-1.48 (OR 0.737, 95% CI 0.596-0.910), and serum triglycerides in 3rd Quartile 2.24-2.40 (OR 0.393, 95% CI 0.316-0.490) as associated significant factors with diabetic cataract in Scottish population.

    Conclusions: We identified the 7 significant SNPs related with the potential genes in Tayside population and found supporting evidence that MAP3K19, R3HDM1, GGA1, CCT7 genes are associated with diabetic cataract. The role of genes in the cataractogenesis needs to be reevaluated in future studies. The risk and protective factors were identified with GoDARTS dataset.

    Date of Award2016
    LanguageEnglish
    Awarding Institution
    • University of Dundee
    SupervisorWeihua Meng (Supervisor), Helen Looker (Supervisor) & Fiona Williams (Supervisor)

    Keywords

    • Diabetic cataract
    • GWAS
    • GoDARTS

    Cite this

    A Pilot Study- Identify Genetic Variants for Diabetic Cataract Using GoDARTS Dataset
    Zhang, K. (Author). 2016

    Student thesis: Master's ThesisMaster of Science