The emergence of large datasets containing multimodal data from longitudinally followed cohorts such as the Michael J Fox Foundation Parkinson’s Progression Markers Initiative has facilitated novel machine learning approaches to develop predication models of PD progression.39,40 In the current study, we have employed machine learning algorithms to further explore the association between peripheral inflammatory cytokines and clinical PD symptomology using longitudinally collected serum samples from PD patients with and without the LRRK2 G2019S mutation. The gene discussed is LRRK2; the disease is Parkinson disease.