Alzheimer's Disease Research: A COIN Study Using Co-authorship Network Analytics

Using bibliometric data from 269 Alzheimer investigators and the 167,142 researchers contained in their two-step collaboration network (i.e., co-authors and co-authors of co-authors), an eigen decomposition of the 13,254 unique Medical Subject Heading (MeSH) terms associated with the 43,736 papers authored by the Alzheimer researchers was performed. A correspondence-analysis-based transformation of the data produced a bench-to-bedside translational spectrum along which each of the original 269 Alzheimer investigators were placed. The spectrum was found to naturally divide into two partitions one of which housed basic scientists while the other grouped together clinical researchers. In addition to the semantic partitions, two main coauthor subgroups were isolated, and the authors who were most central to those co-author subgroups were analyzed for their ability to bridge the “translational divide” which separated researchers grouped in the “bench” (i.e. basic science) partition from those in the “bedside” (i.e., clinical investigation) partition. If a given research community can be partitioned into bench and bedside components, then the possibility exists to use such a dataset to identify people who might be best suited to attempt to bridge the “translational divide” which often exists between those researchers who make scientific breakthroughs in the lab and those clinical investigators capable of bringing the bench discoveries to the patients in the form of clinical trials.