Patterns of symptoms in major depressive disorder and genetics of the disorder using low-pass sequencing data
My thesis aims at identifying both genetic and environmental causes of major depressive disorder (MDD), using a large case-control study: 6,000 Chinese women with recurrent MDD and 6,000 controls. One of the major challenges for conducting genetic research on MDD is disease heterogeneity. The first...
| Main Authors: | , |
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| Format: | Thesis |
| Language: | English |
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2013
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| _version_ | 1826315662642905088 |
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| author | Li, Y Yihan Li |
| author2 | Flint, J |
| author_facet | Flint, J Li, Y Yihan Li |
| author_sort | Li, Y |
| collection | OXFORD |
| description | My thesis aims at identifying both genetic and environmental causes of major depressive disorder (MDD), using a large case-control study: 6,000 Chinese women with recurrent MDD and 6,000 controls. One of the major challenges for conducting genetic research on MDD is disease heterogeneity. The first question addressed is how different MDD is from highly comorbid anxiety disorders. I examine how anxiety disorders predict clinical features of depression and the degree of heterogeneity in their predictive pattern. The second question addressed is whether clinically defined MDD is a single disorder, or whether it consists of multiple subtypes. Results are then compared with and interpreted in the context of Western studies. Furthermore, latent class analysis and factor analysis results are also used in association analysis to explore more genetically homogeneous subtypes. Genetic data were derived using a novel strategy, low pass whole genome sequence analysis. Using genotypes imputed from the sequence data, I show that a cluster of single nucleotide polymorphisms (SNPs) is significantly associated with a binary disease phenotype including only cases with ≥ 4 episodes of MDD, suggesting that recurrence might be an indication of genetic predisposition. The third issue examined is the contribution of rare variants to disease susceptibility. Again using sparse sequence data, I identified exonic sequence variants and performed gene-based analysis by comparing the number of variants between cases and controls in every gene. Furthermore I performed gene enrichment test by combining P values of SNP association tests at different minor allele frequency ranges. Overall, I did not find convincing evidence that rare variants aggregately contribute to disease susceptibility. However, the gene-based analysis resulted in an unexpected finding: cases have an excess of variants in all thirteen-protein coding mitochondrial genes, which was due to copy number differences in the mitochondrial genome. Both human phenotypic data as well as mice experimental data show that the increase in the mitochondrial copy number in cases is due to chronic stress. |
| first_indexed | 2024-03-06T18:53:28Z |
| format | Thesis |
| id | oxford-uuid:110887ce-fa6a-4a86-8063-d3de0d85d0d6 |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-12-09T03:30:12Z |
| publishDate | 2013 |
| record_format | dspace |
| spelling | oxford-uuid:110887ce-fa6a-4a86-8063-d3de0d85d0d62024-12-01T13:33:41ZPatterns of symptoms in major depressive disorder and genetics of the disorder using low-pass sequencing dataThesishttp://purl.org/coar/resource_type/c_db06uuid:110887ce-fa6a-4a86-8063-d3de0d85d0d6Genetics (medical sciences)Anxiety disordersPsychiatryBioinformatics (life sciences)Suicide researchMathematical genetics and bioinformatics (statistics)Medical SciencesClinical geneticsEvidence based mental healthStressEnglishOxford University Research Archive - Valet2013Li, YYihan LiFlint, JMy thesis aims at identifying both genetic and environmental causes of major depressive disorder (MDD), using a large case-control study: 6,000 Chinese women with recurrent MDD and 6,000 controls. One of the major challenges for conducting genetic research on MDD is disease heterogeneity. The first question addressed is how different MDD is from highly comorbid anxiety disorders. I examine how anxiety disorders predict clinical features of depression and the degree of heterogeneity in their predictive pattern. The second question addressed is whether clinically defined MDD is a single disorder, or whether it consists of multiple subtypes. Results are then compared with and interpreted in the context of Western studies. Furthermore, latent class analysis and factor analysis results are also used in association analysis to explore more genetically homogeneous subtypes. Genetic data were derived using a novel strategy, low pass whole genome sequence analysis. Using genotypes imputed from the sequence data, I show that a cluster of single nucleotide polymorphisms (SNPs) is significantly associated with a binary disease phenotype including only cases with ≥ 4 episodes of MDD, suggesting that recurrence might be an indication of genetic predisposition. The third issue examined is the contribution of rare variants to disease susceptibility. Again using sparse sequence data, I identified exonic sequence variants and performed gene-based analysis by comparing the number of variants between cases and controls in every gene. Furthermore I performed gene enrichment test by combining P values of SNP association tests at different minor allele frequency ranges. Overall, I did not find convincing evidence that rare variants aggregately contribute to disease susceptibility. However, the gene-based analysis resulted in an unexpected finding: cases have an excess of variants in all thirteen-protein coding mitochondrial genes, which was due to copy number differences in the mitochondrial genome. Both human phenotypic data as well as mice experimental data show that the increase in the mitochondrial copy number in cases is due to chronic stress. |
| spellingShingle | Genetics (medical sciences) Anxiety disorders Psychiatry Bioinformatics (life sciences) Suicide research Mathematical genetics and bioinformatics (statistics) Medical Sciences Clinical genetics Evidence based mental health Stress Li, Y Yihan Li Patterns of symptoms in major depressive disorder and genetics of the disorder using low-pass sequencing data |
| title | Patterns of symptoms in major depressive disorder and genetics of the disorder using low-pass sequencing data |
| title_full | Patterns of symptoms in major depressive disorder and genetics of the disorder using low-pass sequencing data |
| title_fullStr | Patterns of symptoms in major depressive disorder and genetics of the disorder using low-pass sequencing data |
| title_full_unstemmed | Patterns of symptoms in major depressive disorder and genetics of the disorder using low-pass sequencing data |
| title_short | Patterns of symptoms in major depressive disorder and genetics of the disorder using low-pass sequencing data |
| title_sort | patterns of symptoms in major depressive disorder and genetics of the disorder using low pass sequencing data |
| topic | Genetics (medical sciences) Anxiety disorders Psychiatry Bioinformatics (life sciences) Suicide research Mathematical genetics and bioinformatics (statistics) Medical Sciences Clinical genetics Evidence based mental health Stress |
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