(chemicals associated with AD through literature mining). Thus, the filtering method utilizing cooccurrence scores to generate the SC20 list was more effective than the reverse neighboring relations approach for generating the TOP1 list. In stark contrast to the previous work with PD , the AD-CTD list did not reveal any confident annotations, and only two in total. Interestingly, a considerably higher number of unique features was observed in the HMDB-CSF suspect list using HILIC (45 features, Figure ), compared to RPLC (15 features, Figure ), suggesting that HILIC is a more effective chromatographic approach for CSF analysis, likely due to the matrix's polarity.