Ferguson, Amy Christina (2019) Understanding genetic relationships between circadian function and mood disorders. PhD thesis, University of Glasgow.
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Abstract
Mood disorders are amongst the most prevalent and disabling conditions worldwide. There is increasing evidence for the involvement of disrupted circadian rhythms in mood disorders. The mechanism of associations between circadian dysfunction and mood disorders are complex and not fully understood. This thesis explores the influence of genetic variation of circadian function on mood disorder-related phenotypes within two relatively large cohorts, ALSPAC (N=8,100) and UK Biobank (N=500,000). I investigated genetic variants associated with different features of circadian function and how genetic loading for these common variants was associated with risk of mood disorders and related traits. To my knowledge, this is the first application of circadian polygenic risk scores to investigate mood disorder risk. Both a priori candidate gene profile risk scores (CACNA1C) and polygenic risk scores (PRS) were used to investigate the relationship between the genetics of circadian function and mood disorder-related phenotypes. A genome-wide association study (GWAS) was carried out to identify common variants associated with circadian rest/activity rhythmicity and to assess genetic correlation with mood disorders. Mendelian randomisation was used to assess the direction of the relationship between circadian dysfunction and mood disorders. Chronotype polygenic risk scores (specifically ‘eveningness’ PRS) were associated with increased risk of bipolar disorder in UK Biobank and with hypomanic features in ALSPAC. The GWAS of low relative amplitude (a measure of circadian rest/activity rhythmicity) identified several associated variants and these variants were used to create a PRS for low relative amplitude. Increased PRS for low relative amplitude was associated with mood instability in UK Biobank. There are limitations to the population cohorts used in these analyses. They may be under-representative of individuals with clinically-diagnosed mood disorders. Also, the mood phenotypes tested were based on self-report which could be vulnerable to response biases. The polygenic risk scores had small but significant effects on the mood disorder phenotypes investigated. This work identified associations between genetic variation of circadian function and mood disorder-related phenotypes in both ALSPAC and UK Biobank. With expansion, development and replication, PRS of circadian function could
inform treatment stratification approaches for mood disorders. This thesis also suggests a need for further investigation of the underlying biology of circadian function and how this relates to the pathophysiology of mood disorders. Strengths to this thesis include the large sample sizes of the cohorts. The actigraph data obtained from UK Biobank allowed for the largest GWAS of rest/activity rhythmicity to date. The extensive self-report and interview-based data available in UK Biobank also provide a breadth of mood disorder-related phenotypes to investigate. As this is one of the first examples of using circadian polygenic risk scores to investigate the underlying pathophysiology of mood disorders this work requires replication in other population cohorts. It would also be of interest to test these risk scores within clinical populations and assess the extent to which they may support clinical management decisions.
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