Based on data from more than 400 twins, researchers used multi-omics data integration to develop a model for predicting blood pressure values. Their research is described in the peer-reviewed OMICS: A Journal of Integrative Biology. Click here to read the article now.
The investigators utilized a multi-omics regression-based method called sparse multi-block partial least square to predict systolic and diastolic blood pressure values. The study of high blood pressure has high public health importance, as it is known to increase the risk of cardiovascular, cerebrovascular and renal disease, amongst other common chronic human diseases. The authors, Gabin Drouard, Miina Ollikainen, and Jaakko Kaprio from the Institute for Molecular Medicine Finland, University of Helsinki, and coauthors in Finland and Augusta, Georgia, integrated blocks of omics - including transcriptomic, methylation, and metabolomic data - as well as polygenic risk scores into the modeling.
"In addition to revealing interesting inter-omics associations, we found that each block of omics heterogeneously improved the predictions of blood pressure values once the multi-omics data were integrated," stated the investigators.
"Hypertension is a high-prevalence multi-factorial disease. The new study by Drouard and colleagues is important for two reasons. First, it presents a multi-omics approach to integrate single omics analyses. Second, it illustrates the exploratory and predictive gains achieved by multi-omics study of a complex phenotype such as blood pressure. I believe this study is significant in the current era of systems medicine and planetary health," says Vural Özdemir, MD, PhD, DABCP, Editor-in-Chief of OMICS.
About the Journal
OMICS: A Journal of Integrative Biology is an authoritative and highly innovative peer-reviewed interdisciplinary journal published monthly online, addressing the latest advances at the intersection of postgenomics medicine, biotechnology and global society, including the integration of multi-omics knowledge, data analyses and modeling, and applications of high-throughput approaches to study complex biological and societal problems. Public policy, governance and societal aspects of the large-scale biology and 21st century data-enabled sciences are also peer-reviewed. Complete tables of content and a sample issue may be viewed on the OMICS: A Journal of Integrative Biology website.
About the Publisher
Mary Ann Liebert, Inc., publishers is known for establishing authoritative peer-reviewed journals in many areas of science and biomedical research. Its biotechnology trade magazine, Genetic Engineering & Biotechnology News (GEN), was the first in its field and is today the industry's most widely read publication worldwide. A complete list of the firm's more than 100 journals, books, and newsmagazines is available on the Mary Ann Liebert, Inc., publishers website.
