Hourican, C., Peeters, G., Melis, R.J.F., Kok, A., van Schoor, N.M., Wezeman, S., Lees, M., Olde Rikkert, M.G.M., Quax, R.
In older adults, some symptoms, signs and behaviours only reveal their effect on health when they occur together rather than one at a time. This work introduces an open, bias-aware workflow — partial information decomposition plus a "BUST" map — that detects and interprets these "together-only" synergistic combinations across a large ageing cohort, flagging feature pairs that conventional association measures overlook.
Peeters, G., Hourican, C., Lees, M., Quax, R., Melis, R., Kok, A., van Schoor, N.M., Olde Rikkert, M.
In older adults living with several chronic conditions, the symptoms people actually experience carry information about their day-to-day functioning that formal disease diagnoses miss — and adding symptoms sharply improves prediction of functional limitations. This supports a more symptom-oriented view of multimorbidity.
Li, J., Bosch, J.A., Rydin, A.O., Hourican, C., Koloi, A., Tassi, S.C., Mishra, P.P., Mishra, B.H., Kähönen, M., Lehtimäki, T., Raitakari, O.T., Laaksonen, R., Keltikangas-Järvinen, L., Juonala, M., Quax, R.
Heart disease and depression often occur together, but the biology connecting them is poorly understood. Using a network approach on ~1,700 people (validated in the UK Biobank), the study pinpoints specific metabolites and lipids that biologically link particular depressive symptoms to cardiovascular measures — suggesting shared pathways that could inform prevention and treatment.
Hourican, C., Peeters, G., Melis, R.J.F., Wezeman, S.L., Gill, T.M., Olde Rikkert, M.G.M., Quax, R.
Multimorbidity research usually counts diseases or looks at them in pairs, which hides how signs, symptoms and diseases actually combine. This perspective argues for networks that link signs, symptoms and diseases together and capture higher-order (synergistic) interactions as hypergraphs — showing, via a synthetic model, that pairwise thinking can miss the best intervention or produce unexpected "side-effects" a hypergraph reveals.