Differential Methylation Analysis of Monozygotic Twin Pairs Discordant for Body Mass Index

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dc.contributor Helsingin yliopisto, Matemaattis-luonnontieteellinen tiedekunta, Matematiikan ja tilastotieteen laitos fi
dc.contributor.author Ismail, Khadeeja fi
dc.date.accessioned 2012-09-06T12:00:13Z
dc.date.available 2012-09-06T12:00:13Z
dc.date.issued 2012-09-06
dc.identifier.uri http://hdl.handle.net/10138/36531
dc.description Vain tiivistelmä. Opinnäytteiden arkistokappaleet ovat luettavissa Helsingin yliopiston kirjastossa. Hae HELKA-tietokannasta (http://www.helsinki.fi/helka/index.htm). fi
dc.description Abstract only. The paper copy of the whole thesis is available for reading room use at the Helsinki University Library. Search HELKA online catalog (http://www.helsinki.fi/helka/index.htm). en
dc.description Endast avhandlingens sammandrag. Pappersexemplaret av hela avhandlingen finns för läsesalsbruk i Helsingfors universitets bibliotek. Sök i HELKA-databasen (http://www.helsinki.fi/helka/index.htm). sv
dc.description.abstract Obesity is associated with life styles involving overconsumption of high-energy food and having low amount of physical activity but the heritability of obesity has also been shown to be high. Results from genome wide association studies (GWAS), however, could explain only 5% of this heritability. This evidence points towards epigenetics acting as a mediator that allows the environment to affect the phenotype without changing the genotype, and epigenetics as a factor that may explain the missing heritability. DNA methylation, which plays an important role in cell differentiation and which has already been associated with diseases such as cancer and diabetes, is the most studied epigenetic factor. DNA methylation is the addition of a methyl group to a cytosine occurring next to a guanine connected by the phosphate backbone, the positions known as CpG sites. This thesis is based on the study of DNA methylation in obesity, using monozygotic twins discordant for obesity where obesity discordance is defined as having a difference in body mass index (BMI) greater than 3m2/kg. MZ twin pairs share the same genome and are matched for age, sex, cohort effects, intrauterine environment and the environment in which they grow up after birth. This helps to cancel out many confounding factors that may affect the results otherwise. The samples for this analysis was obtained from 22 obesity-discordant pairs and 8 obesity-concordant pairs. DNA from whole-blood was bisulfite-converted and hybridized to the Infinium HumanMethylation450 BeadChip. The data was then preprocessed and analyzed for within-pair differences in twins discordant for BMI, and this showed no CpG sites as differentially methylated within pairs. The analysis was then repeated on twins discordant for both BMI and liver-fat and this showed 180 CpG sites as significantly differentially methylated within pairs. However, it was not possible to use these results for pathway analysis using the methods used in gene expression analysis, as too few of these CpG sites mapped to genes on pathways. Gene-set analysis (GSA) was then applied to the methylation data to identify interesting pathways, using predefined groups of CpG sites (probe-sets), each group representing a pathway in the KEGG database. The significant pathways were further analyzed to identify the CpG sites that were most discordant within twin pairs. The results from GSA and the initial paired analysis provided an interesting list of genes and pathways most of which had previously been associated with obesity. However, the analyses can be improved by using a normalization method that is more specific to the Infinium 450K array and also by increasing the sample size. This is listed as future work, together with the analysis of DNA from adipose tissue. The pipeline developed from this analysis will be used in the future analyses, but with modifications wherever necessary. fi
dc.language.iso en fi
dc.title Differential Methylation Analysis of Monozygotic Twin Pairs Discordant for Body Mass Index fi
dc.type Thesis fi
dc.type.ontasot Pro gradu -työ fi
dc.type.dcmitype text fi
dc.subject.discipline Bioinformatics fi

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