A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä
Hypothesis-driven mediation analysis for compositional data: an application to gut microbiome
Tekijät: Kartiosuo, Noora; Nevalainen Jaakko; Raitakari, Olli; Pahkala, Katja; Auranen, Kari
Kustantaja: Taylor and Francis Ltd.
Julkaisuvuosi: 2024
Journal: Biostatistics & Epidemiology
Tietokannassa oleva lehden nimi: Biostatistics and Epidemiology
Artikkelin numero: e2360375
Vuosikerta: 8
Numero: 1
DOI: https://doi.org/10.1080/24709360.2024.2360375
Verkko-osoite: https://doi.org/10.1080/24709360.2024.2360375
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/457415677
Sequencing read-count data often exhibit sparsity (zero-count inflation) and overdispersion. As most sequencing techniques provide an arbitrary total count, taxon-specific counts should be treated under the compositional data-analytic framework. There is increasing interest in the role of gut microbiome composition in mediating the effects of exposures on health. Previous compositional mediation approaches have focused on identifying mediating taxa among a number of candidates. We here consider compositional causal mediation when a priori knowledge is available about the hierarchy for a restricted number of taxa, building on a single hypothesis structured as contrasts between appropriate sub-compositions. Based on the assumed causal graph and the theory of multiple contemporaneous mediators, we define non-parametric estimands for overall and coordinate-wise mediation effects and show how they are estimated based on parametric linear models. The mediators have straightforward and coherent interpretations, related to causal questions about interrelationships between the sub-compositions. We perform a simulation study focusing on the impact of sparsity on estimation. While unbiased, the estimators' precision depends on sparsity and the relative magnitudes of exposure-to-mediator and mediator-to-outcome effects in a complex manner. In the empirical application we find an inverse association of fibre intake on insulin level, mainly attributable to the direct effects.
Julkaisussa olevat rahoitustiedot:
NK has been financially supported by Emil Aaltonen Foundation and the MATTI programme in The University of Turku Graduate School (UTUGS). The STRIP study has been financially supported by the Academy of Finland (grants 206374, 294834, 251360, 275595, 307996, and 322112), the Juho Vainio Foundation, the Finnish Foundation for Cardiovascular Research, the Finnish Ministry of Education and Culture, the Finnish Cultural Foundation, the Sigrid Jusélius Foundation, Special Governmental grants for Health Sciences Research (Turku University Hospital), the the Yrjö Jahnsson Foundation, the Finnish Medical Foundation, and the Turku University Foundation.
