Combinatorial identification of DNA methylation patterns over age in the human brain.
BACKGROUND
DNA methylation plays a key role in developmental processes, which is reflected in changing methylation patterns at specific CpG sites over the lifetime of an individual. The underlying mechanisms are complex and possibly affect multiple genes or entire pathways.


RESULTS
We applied a multivariate approach to identify combinations of CpG sites that undergo modifications when transitioning between developmental stages. Monte Carlo feature selection produced a list of ranked and statistically significant CpG sites, while rule-based models allowed for identifying particular methylation changes in these sites. Our rule-based classifier reports combinations of CpG sites, together with changes in their methylation status in the form of easy-to-read IF-THEN rules, which allows for identification of the genes associated with the underlying sites.


CONCLUSIONS
We utilized machine learning and statistical methods to discretize decision class (age) values to get a general pattern of methylation changes over the lifespan. The CpG sites present in the significant rules were annotated to genes involved in brain formation, general development, as well as genes linked to cancer and Alzheimer's disease.
Department of Cell and Molecular Biology, Computational and Systems Biology, Uppsala University, Uppsala, Sweden.
Behrooz
B
Torabi Moghadam
Laboratory of Bioinformatics, Neurobiology Center, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland.
Michal
M
Dabrowski
Laboratory of Molecular Neurobiology, Neurobiology Center, Nencki Institute of Experimental Biology of Polish Academy of Sciences, Warsaw, Poland.
Bozena
B
Kaminska
Department of Medical Biochemistry and Microbiology/BILS, Genomics, Uppsala University, Uppsala, Sweden.
Manfred G
MG
Grabherr
Department of Cell and Molecular Biology, Computational and Systems Biology, Uppsala University, Uppsala, Sweden. jan.komorowski@icm.uu.se.|Institute of Computer Science, Polish Academy of Sciences, 01-248, Warszawa, Poland. jan.komorowski@icm.uu.se.
Jan
J
Komorowski
Aging; DNA methylation; Feature selection; Rule-based classification
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