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Title: Genetic overlap between type 2 diabetes and depression
Author: Kan, Carol
ISNI:       0000 0004 7656 2907
Awarding Body: King's College London
Current Institution: King's College London (University of London)
Date of Award: 2017
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Background: An association between type 2 diabetes (T2DM) and depression has been reported in epidemiological studies. The mechanisms underlying the T2DM-depression link remain unclear. One possible question is whether the co-occurrence of T2DM and depression is due to common genetic and/or common environmental vulnerabilities. A genetic overlap between T2DM and depression will provide evidence supporting a common biological pathway to both disorders. Method: This thesis applied three methodological approaches: i) structural equation modelling of twin data, ii) polygenic score analysis and iii) linkage disequilibrium score regression using genome-wide association studies (GWAS) data. For the first approach, the primary dataset was the Swedish Twin Registry with replication in the Danish Twin Registry and Colombo Twin and Singleton Study (COTASS-2). For the second and third approach, the population cohorts deCODE and UK Biobank, and the Psychiatric Genomics Consortium Major Depressive Disorder (PGC-MDD-29) dataset were used. Result: In the twin studies, a genetic overlap between T2DM and depression was observed in the Swedish Twin Registry and the finding was replicated in the Danish Twin Registry and COTASS-2. In the GWAS datasets, T2DM-polygenic scores were not a major contribution to depression nor depression-polygenic scores for T2DM in both deCODE and UK Biobank. A small, negative but statistically significant association was observed between feelings of guilt/worthlessness and T2DM-polygenic scores in the PGC-MDD-29 dataset. Conclusion: Twin studies have suggested a genetic overlap between T2DM and depression. There are many reasons to explain the discrepancies in findings between twin studies and GWAS. Clarifying the shared heritability between these two complex traits is an important next step while gene-environment interaction is an area that needs to be explored, given genotypes can affect an individual’s responses to the environment and environment can differentially affect genotypes expression.
Supervisor: Ismail, Khalida ; Lewis, Cathryn Mair ; Rijsdijk, Fruhling Vesta Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available