Cargando…

A Genome-Wide Integrative Association Study of DNA Methylation and Gene Expression Data and Later Life Cognitive Functioning in Monozygotic Twins

Monozygotic twins are genetically identical but rarely phenotypically identical. Epigenetic and transcriptional variation could influence this phenotypic discordance. Investigation of intra-pair differences in molecular markers and a given phenotype in monozygotic twins controls most of the genetic...

Descripción completa

Detalles Bibliográficos
Autores principales: Soerensen, Mette, Hozakowska-Roszkowska, Dominika Marzena, Nygaard, Marianne, Larsen, Martin J., Schwämmle, Veit, Christensen, Kaare, Christiansen, Lene, Tan, Qihua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7160301/
https://www.ncbi.nlm.nih.gov/pubmed/32327964
http://dx.doi.org/10.3389/fnins.2020.00233
Descripción
Sumario:Monozygotic twins are genetically identical but rarely phenotypically identical. Epigenetic and transcriptional variation could influence this phenotypic discordance. Investigation of intra-pair differences in molecular markers and a given phenotype in monozygotic twins controls most of the genetic contribution, enabling studies of the molecular features of the phenotype. This study aimed to identify genes associated with cognition in later life using integrated enrichment analyses of the results of blood-derived intra-pair epigenome-wide and transcriptome-wide association analyses of cognition in 452 middle-aged and old-aged monozygotic twins (56–80 years). Integrated analyses were performed with an unsupervised approach using KeyPathwayMiner, and a supervised approach using the KEGG and Reactome databases. The supervised approach identified several enriched gene sets, including “neuroactive ligand receptor interaction” (p-value = 1.62(∗)10-2), “Neurotrophin signaling” (p-value = 2.52(∗)10-3), “Alzheimer’s disease” (p-value = 1.20(∗)10-2), and “long-term depression” (p-value = 1.62(∗)10-2). The unsupervised approach resulted in a 238 gene network, including the Alzheimer’s disease gene APP (Amyloid Beta Precursor Protein) as an exception node, and several novel candidate genes. The strength of the unsupervised method is that it can reveal previously uncharacterized sub-pathways and detect interplay between biological processes, which remain undetected by the current supervised methods. In conclusion, this study identified several previously reported cognition genes and pathways and, additionally, puts forward novel candidates for further verification and validation.