Palumbo, Domenico (2018) Inter-individual methylation variation and its relationship with evolution and cancer. [Tesi di dottorato]


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Item Type: Tesi di dottorato
Lingua: English
Title: Inter-individual methylation variation and its relationship with evolution and cancer
Date: 6 December 2018
Number of Pages: 47
Institution: Università degli Studi di Napoli Federico II
Department: Medicina Molecolare e Biotecnologie Mediche
Dottorato: Medicina molecolare e biotecnologie mediche
Ciclo di dottorato: 31
Coordinatore del Corso di dottorato:
Avvedimento, Vittorio
Cocozza, SergioUNSPECIFIED
Date: 6 December 2018
Number of Pages: 47
Uncontrolled Keywords: methylation, cancer, evolution
Settori scientifico-disciplinari del MIUR: Area 06 - Scienze mediche > MED/03 - Genetica medica
Date Deposited: 09 Jan 2019 12:51
Last Modified: 30 Jun 2020 08:26


Background: In recent years, epigenetics has gained interest among scientists involved in different research areas (e.g. cancer, molecular medicine, behavior, development). It is now clear that the environment influences the methylome by promoting methylation variation with possible effects on both healthy and disease-related phenotypes. I studied inter-individual DNA methylation variation in healthy individuals and in cancer tissues to identify possible factors influencing this variation. Results: Using the EPIC-Italy dataset (1 tissue, 83 males and 83 age-matched healthy females), I analyzed methylation variation values in relation to CpG cluster density and I found a strong association between them (p-value < 2.2*10-16). Furthermore, I found that genes related to CpGs with high methylation variation values were enriched for immunological pathways; instead, those associated with low variation were enriched for pathways related to basic cellular functions. Finally, I found an association between methylation variation values and signals of both ancient (p-value < 2.2*10-16) and recent selective pressure (p-value < 1*10-4). Furthermore, using TCGA datasets (4 healthy and cancer tissues), I analyzed methylation variation correlation in several tissues and in different conditions. I found that cancer tissues show higher methylation variation than healthy tissues (p-value < 2.2*10-16). Finally, I used a linear regression model to calculate Differentially Methylated CpGs (DM-CpGs) and I found that DM-CpGs always display higher inter-individual methylation variation especially in cancer (p-value < 2.2*10-16). Conclusion: These results indicate the presence in healthy subjects of an intricate interplay between genetics, epigenetics and evolutionary constraints that influence the inter-individual methylation variation. Furthermore, my results show an increase of inter-individual variation in cancer.


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