Joint modeling of zero-inflated longitudinal proportions and time-to-event data with application to a gut microbiome study

• Published in: bioRxiv
• Main Authors: Hu, Jiyuan, Chan, Wang, Blaser, Martin J, Li, Huilin
• Format: Paper
• Language: English
• Published: Cold Spring Harbor Cold Spring Harbor Laboratory Press 11.12.2020; Cold Spring Harbor Laboratory
• Edition: 1.1
• Subjects: Bioinformatics; Intestinal microflora; Microbiomes; Joint model; Longitudinal microbiome study; Survival outcome; Zero inflation; Skewness
• ISSN: 2692-8205; 2692-8205
• DOI: 10.1101/2020.12.10.419945

, which is comprised of two sub-models: a longitudinal sub-model called zero-inflated scaled-Beta generalized linear mixed-effects regression to depict the temporal structure of microbial proportions among subjects; and a survival sub-model to characterize the occurrence of an event and its relationship with the longitudinal microbiome proportions. JointMM is specifically designed to handle the zero-inflated and highly skewed longitudinal microbial proportion data and examine whether the temporal pattern of microbial presence and/or the non-zero microbial proportions are associated with differences in the time to an event. The longitudinal sub-model of JointMM also provides the capacity to investigate how the (time-varying) covariates are related to the temporal microbial presence/absence patterns and/or the changing trend in non-zero proportions. Comprehensive simulations and real data analyses are used to assess the statistical efficiency and interpretability of JointMM. Competing Interest Statement The authors have declared no competing interest.