Due to the large amount of new papers regularly entering the MEDLINE database, there is an ongoing effort to design tools that help indexing this new material. Here we investigate the hypothesis that past indexing information coming from referencing and authoring links can be used for this purpose. Using a JAMA-based subset of MEDLINE, we designed ranking scores which rely on this information; given a new article, the aim of these scores is to build an ordered list of MeSH terms that should be used to index this article. Evaluation measures on an independent, 1000-document data set are given. Comparison with equivalent works shows benefits in recall, F-measure and mean average precision. Moreover, cited articles and authors' past articles contribute to seven of the top ten ranking features, supporting our hypothesis. Further improvements and extensions to this work are exposed in the conclusion.