Inferring causal pathways between metabolic processes and liver fat accumulation: an IMI DIRECT study

Author:

Atabaki-Pasdar Naeimeh,Pomares-Millan Hugo,Koivula Robert W,Tura Andrea,Brown Andrew,Viñuela Ana,Agudelo Leandro,Coral Daniel,van Oort Sabine,Allin Kristine,Chabanova Elizaveta,Cederberg Henna,De Masi Federico,Elders Petra,Tajes Juan Fernandez,Forgie Ian M,Hansen Tue H,Heggie Alison,Jones Angus,Kokkola Tarja,Mahajan Anubha,McDonald Timothy J,McEvoy Donna,Tsirigos Konstantinos,Teare Harriet,Vangipurapu Jagadish,Vestergaard Henrik,Adamski Jerzy,Beulens Joline WJ,Brunak Søren,Dermitzakis Emmanouil,Hansen Torben,Hattersley Andrew T,Laakso Markku,Pedersen Oluf,Ridderstråle Martin,Ruetten Hartmut,Rutters Femke,Schwenk Jochen M,Walker Mark,Giordano Giuseppe N,Ohlsson Mattias,Gupta Ramneek,Mari Andrea,McCarthy Mark I,Thomas E Louise,Bell Jimmy D,Pavo Imre,Pearson Ewan R,Franks Paul W

Abstract

ABSTRACTType 2 diabetes (T2D) and non-alcoholic fatty liver disease (NAFLD) often co-occur. Defining causal pathways underlying this relationship may help optimize the prevention and treatment of both diseases. Thus, we assessed the strength and magnitude of the putative causal pathways linking dysglycemia and fatty liver, using a combination of causal inference methods.Measures of glycemia, insulin dynamics, magnetic resonance imaging (MRI)-derived abdominal and liver fat content, serological biomarkers, lifestyle, and anthropometry were obtained in participants from the IMI DIRECT cohorts (n=795 with new onset T2D and 2234 individuals free from diabetes). UK Biobank (n=3641) was used for modelling and replication purposes. Bayesian networks were employed to infer causal pathways, with causal validation using two-sample Mendelian randomization.Bayesian networks fitted to IMI DIRECT data identified higher basal insulin secretion rate (BasalISR) and MRI-derived excess visceral fat (VAT) accumulation as the features of dysmetabolism most likely to cause liver fat accumulation; the unconditional probability of fatty liver (>5%) increased significantly when conditioning on high levels of BasalISR and VAT (by 23%, 32% respectively; 40% for both). Analyses in UK Biobank yielded comparable results. MR confirmed most causal pathways predicted by the Bayesian networks.Here, BasalISR had the highest causal effect on fatty liver predisposition, providing mechanistic evidence underpinning the established association of NAFLD and T2D. BasalISR may represent a pragmatic biomarker for NAFLD prediction in clinical practice.

Publisher

Cold Spring Harbor Laboratory

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