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Hugo Pomares-Millan

Doctoral student

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

Author

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

Summary, in English

Type 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.Competing Interest StatementHR is an employee and shareholder of Sanofi. MIM: The views expressed in this article are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health. MIM has served on advisory panels for Pfizer, NovoNordisk and Zoe Global, has received honoraria from Merck, Pfizer, Novo Nordisk and Eli Lilly, and research funding from Abbvie, Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck, NovoNordisk, Pfizer, Roche, Sanofi Aventis, Servier, and Takeda. As of June 2019, MIM is an employee of Genentech, and a holder of Roche stock. AM is a consultant for Lilly and has received research grants from several diabetes drug companies. PWF has received research grants from numerous diabetes drug companies and fess as consultant from Novo Nordisk, Lilly, and Zoe Global Ltd. He is currently the Scientific Director in Patient Care at the Novo Nordisk Foundation. Other authors declare non competing interests.Funding StatementThe work leading to this publication has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreement 115317 (DIRECT) resources of which are composed of financial contribution from the European Union Seventh Framework Programme (FP7/2007-2013) and EFPIA companies in kind contribution. NAP is supported in part by Henning och Johan Throne-Holsts Foundation, Hans Werthen Foundation, an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. HPM is supported by an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. AGJ is supported by an NIHR Clinician Scientist award (17/0005624). RK is funded by the Novo Nordisk Foundation (NNF18OC0031650) as part of a postdoctoral fellowship, an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. AK, PM, HF, JF and GNG are supported by an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. TJM is funded by an NIHR clinical senior lecturer fellowship. S.Bru acknowledges support from the Novo Nordisk Foundation (grants NNF17OC0027594 and NNF14CC0001). ATH is a Wellcome Trust Senior Investigator and is also supported by the NIHR Exeter Clinical Research Facility. JMS acknowledges support from Science for Life Laboratory (Plasma Profiling Facility), Knut and Alice Wallenberg Foundation (Human Protein Atlas) and Erling-Persson Foundation (KTH Centre for Precision Medicine). MIM is supported by the following grants; Wellcome (090532, 098381, 106130, 203141, 212259); NIH (U01-DK105535). PWF is supported by an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Approval for the study protocol was obtained from each of the regional research ethics review boards separately (Lund, Sweden: 20130312105459927, Copenhagen, Denmark: H-1-2012-166 and H-1-2012-100, Amsterdam, Netherlands: NL40099.029.12, Newcastle, Dundee and Exeter, UK: 12/NE/0132), and all participants provided written informed consent at enrolment. The research conformed to the ethical principles for medical research involving human participants outlined in the Declaration of Helsinki.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAuthors agree to make data and materials supporting the results or analyses presented in their paper available upon reasonable request

Department/s

  • Genetic and Molecular Epidemiology
  • EXODIAB: Excellence of Diabetes Research in Sweden
  • Diabetes - Clinical Obesity
  • EpiHealth: Epidemiology for Health
  • eSSENCE: The e-Science Collaboration
  • Artificial Intelligence in CardioThoracic Sciences (AICTS)

Publishing year

2021

Language

English

Publication/Series

medRxiv

Document type

Preprint

Publisher

medRxiv

Topic

  • Endocrinology and Diabetes

Status

Published

Research group

  • Genetic and Molecular Epidemiology
  • Diabetes - Clinical Obesity
  • Artificial Intelligence in CardioThoracic Sciences (AICTS)