Analyzing DNA methylation patterns in subjects diagnosed with schizophrenia using machine learning methods
PBN-AR
Instytucja
Instytut Podstaw Informatyki Polskiej Akademii Nauk
Informacje podstawowe
Główny język publikacji
angielski
Czasopismo
Journal of Psychiatric Research
ISSN
0022-3956
EISSN
Wydawca
DOI
URL
Rok publikacji
2019
Numer zeszytu
Strony od-do
41-47
Numer tomu
114
Liczba arkuszy
Słowa kluczowe
en
DNA methylation
Schizophrenia
Machine learning
Classification
Clustering
Streszczenia
Język
en
Treść
Schizophrenia is a common mental disorder with high heritability. It is genetically complex and to date more than a hundred risk loci have been identified. Association of environmental factors and schizophrenia has also been reported, while epigenetic analyses have yielded ambiguous and sometimes conflicting results. Here, we analyzed fresh frozen post-mortem brain tissue from a cohort of 73 subjects diagnosed with schizophrenia and 52 control samples, using the Illumina Infinium HumanMethylation450 Bead Chip, to investigate genome-wide DNA methylation patterns in the two groups. Analysis of differential methylation was performed with the Bioconductor Minfi package and modern machine-learning and visualization techniques, which were shown previously to be successful in detecting and highlighting differentially methylated patterns in case-control studies. In this dataset, however, these methods did not uncover any significant signals discerning the patient group and healthy controls, suggesting that if there are methylation changes associated with schizophrenia, they are heterogeneous and complex with small effect.
Inne
System-identifier
IPIPAN-A-5628
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