Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Alberto Romagnoni; Inga Prokopenko; Simon Jegou; Kristel Van Steen; Gilles Wainrib; Jean-Pierre Hugot; Laurent Peyrin-Biroulet; Mathias Chamaillard; Jean-Frederick Colombel; Mario Cottone; Mauro D'Amato; Renata D'Inca; Jonas Halfvarson; Paul Henderson; Amir Karban; Nicholas A Kennedy; Mohammed Azam Khan; Marc Lemann; Arie Levine; Dunecan Massey; Monica Milla; Sok Meng Evelyn Ng; Ioannis Oikonomou; Harald Peeters; Deborah D Proctor; Jean-Francois Rahier; Paul Rutgeerts; Frank Seibold; Laura Stronati; Kirstin M Taylor; Leif Torkvist; Kullak Ublick; Johan Van Limbergen; Andre Van Gossum; Morten H Vatn; Hu Zhang; Wei Zhang; Jane M Andrews; Peter A Bampton; Murray Barclay; Timothy H Florin; Richard Gearry; Krupa Krishnaprasad; Ian C Lawrance; Gillian Mahy; Grant W Montgomery; Graham Radford-Smith; Rebecca L Roberts; Lisa A Simms; Katherine Hanigan; Anthony Croft; Leila Amininijad; Isabelle Cleynen; Olivier Dewit; Denis Franchimont; Michel Georges; Debby Laukens; Emilie Theatre; Severine Vermeire; Guy Aumais; Leonard Baidoo; Arthur M Barrie; Karen Beck; Edmond-Jean Bernard; David G Binion; Alain Bitton; Steve R Brant; Judy H Cho; Albert Cohen; Kenneth Croitoru; Mark J Daly; Lisa W Datta; Colette Deslandres; Richard H Duerr; Debra Dutridge; John Ferguson; Joann Fultz; Philippe Goyette; Gordon R Greenberg; Talin Haritunians; Gilles Jobin; Seymour Katz; Raymond G Lahaie; Dermot P McGovern; Linda Nelson; Sok Meng Ng; Kaida Ning; Pierre Pare; Miguel D Regueiro; John D Rioux; Elizabeth Ruggiero; L Philip Schumm; Marc Schwartz; Regan Scott; Yashoda Sharma; Mark S Silverberg; Denise Spears; A Hillary Steinhart; Joanne M Stempak; Jason M Swoger; Constantina Tsagarelis; Clarence Zhang; Hongyu Zhao; Jan Aerts; Tariq Ahmad; Hazel Arbury; Anthony Attwood; Adam Auton; Stephen G Ball; Anthony J Balmforth; Chris Barnes; Jeffrey C Barrett; Ines Barroso; Anne Barton; Amanda J Bennett; Sanjeev Bhaskar; Katarzyna Blaszczyk; John Bowes; Oliver J Brand; Peter S Braund; Francesca Bredin; Gerome Breen; Morris J Brown; Ian N Bruce; Jaswinder Bull; Oliver S Burren; John Burton; Jake Byrnes; Sian Caesar; Niall Cardin; Chris M Clee; Alison J Coffey; John Mc Connell; Donald F Conrad; Jason D Cooper; Anna F Dominiczak; Kate Downes; Hazel E Drummond; Darshna Dudakia; Andrew Dunham; Bernadette Ebbs; Diana Eccles; Sarah Edkins; Cathryn Edwards; Anna Elliot; Paul Emery; David M Evans; Gareth Evans; Steve Eyre; Anne Farmer; I Nicol Ferrier; Edward Flynn; Alistair Forbes; Liz Forty; Jayne A Franklyn; Timothy M Frayling; Rachel M Freathy; Eleni Giannoulatou; Polly Gibbs; Paul Gilbert; Katherine Gordon-Smith; Emma Gray; Elaine Green; Chris J Groves; Detelina Grozeva; Rhian Gwilliam; Anita Hall; Naomi Hammond; Matt Hardy; Pile Harrison; Neelam Hassanali; Husam Hebaishi; Sarah Hines; Anne Hinks; Graham A Hitman; Lynne Hocking; Chris Holmes; Eleanor Howard; Philip Howard; Joanna MM Howson; Debbie Hughes; Sarah Hunt; John D Isaacs; Mahim Jain; Derek P Jewell; Toby Johnson; Jennifer D Jolley; Ian R Jones; Lisa A Jones; George Kirov; Cordelia F Langford; Hana Lango-Allen; G Mark Lathrop; James Lee; Kate L Lee; Charlie Lees; Kevin Lewis; Cecilia M Lindgren; Meeta Maisuria-Armer; Julian Maller; John Mansfield; Jonathan L Marchini; Paul Martin; Dunecan CO Massey; Wendy L McArdle; Peter McGuffin; Kirsten E McLay; Gil McVean; Alex Mentzer; Michael L Mimmack; Ann E Morgan; Andrew P Morris; Craig Mowat; Patricia B Munroe; Simon Myers; William Newman; Elaine R Nimmo; Michael C O'Donovan; Abiodun Onipinla; Nigel R Ovington; Michael J Owen; Kimmo Palin; Aarno Palotie; Kirstie Parnell; Richard Pearson; David Pernet; John RB Perry; Anne Phillips; Vincent Plagnol; Natalie J Prescott; Michael A Quail; Suzanne Rafelt; Nigel W Rayner; David M Reid; Anthony Renwick; Susan M Ring; Neil Robertson; Samuel Robson; Ellie Russell; David St Clair; Jennifer G Sambrook; Jeremy D Sanderson; Stephen J Sawcer; Helen Schuilenburg; Carol E Scott; Richard Scott; Sheila Seal; Sue Shaw-Hawkins; Beverley M Shields; Matthew J Simmonds; Debbie J Smyth; Elilan Somaskantharajah; Katarina Spanova; Sophia Steer; Jonathan Stephens; Helen E Stevens; Kathy Stirrups; Millicent A Stone; David P Strachan; Zhan Su; Deborah PM Symmons; John R Thompson; Wendy Thomson; Martin D Tobin; Mary E Travers; Clare Turnbull; Damjan Vukcevic; Louise Wain; Mark Walker; Neil M Walker; Chris Wallace; Margaret Warren-Perry; Nicholas A Watkins; John Webster; Michael N Weedon; Anthony G Wilson; Matthew Woodburn; B Paul Wordsworth; Chris Yau; Allan H Young; Eleftheria Zeggini; Matthew A Brown; Paul R Burton; Mark J Caulfield; Alastair Compston; Martin Farrall; Stephen CL Gough; Alistair S Hall; Andrew T Hattersley; Adrian VS Hill; Christopher G Mathew; Marcus Pembrey; Jack Satsangi; Michael R Stratton; Jane Worthington; Matthew E Hurles; Audrey Duncanson; Willem H Ouwehand; Miles Parkes; Nazneen Rahman; John A Todd; Nilesh J Samani; Dominic P Kwiatkowski; Mark McCarthy; Nick Craddock; Panos Deloukas; Peter Donnelly; Jenefer M Blackwell; Elvira Bramon; Juan P Casas; Aiden Corvin; Janusz Jankowski; Hugh S Markus; Colin NA Palmer; Robert Plomin; Anna Rautanen; Richard C Trembath; Ananth C Viswanathan; Nicholas W Wood; Chris CA Spencer; Gavin Band; Celine Bellenguez; Colin Freeman; Garrett Hellenthal; Matti Pirinen; Amy Strange; Hannah Blackburn; Suzannah J Bumpstead; Serge Dronov; Matthew Gillman; Alagurevathi Jayakumar; Owen T McCann; Jennifer Liddle; Simon C Potter; Radhi Ravindrarajah; Michelle Ricketts; Matthew Waller; Paul Weston; Sara Widaa; Pamela Whittaker

doi:10.1038/s41598-019-46649-z

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Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Journal article

Peer reviewed

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

Alberto Romagnoni, Inga Prokopenko, Simon Jegou, Kristel Van Steen, Gilles Wainrib, Jean-Pierre Hugot, Laurent Peyrin-Biroulet, Mathias Chamaillard, Jean-Frederick Colombel, Mario Cottone, …

Scientific Reports, Vol.9, 10351

17/07/2019

DOI: https://doi.org/10.1038/s41598-019-46649-z

Abstract

ASSOCIATION

INFLAMMATORY-BOWEL-DISEASE

LOCI

Multidisciplinary Sciences

RISK PREDICTION

Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers. status: published

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Title: Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data
Creators: Alberto Romagnoni - Université Paris Sciences et Lettres
Inga Prokopenko
Simon Jegou
Kristel Van Steen - University of Liège
Gilles Wainrib - Université Paris Sciences et Lettres
Jean-Pierre Hugot - Center for Research on Inflammation
Laurent Peyrin-Biroulet
Mathias Chamaillard
Jean-Frederick Colombel
Mario Cottone
Mauro D'Amato
Renata D'Inca
Jonas Halfvarson
Paul Henderson
Amir Karban
Nicholas A Kennedy
Mohammed Azam Khan
Marc Lemann
Arie Levine
Dunecan Massey
Monica Milla
Sok Meng Evelyn Ng
Ioannis Oikonomou
Harald Peeters
Deborah D Proctor
Jean-Francois Rahier
Paul Rutgeerts
Frank Seibold
Laura Stronati
Kirstin M Taylor
Leif Torkvist
Kullak Ublick
Johan Van Limbergen
Andre Van Gossum
Morten H Vatn
Hu Zhang - Center for Research on Inflammation
Wei Zhang
Jane M Andrews
Peter A Bampton
Murray Barclay
Timothy H Florin
Richard Gearry
Krupa Krishnaprasad
Ian C Lawrance
Gillian Mahy
Grant W Montgomery
Graham Radford-Smith
Rebecca L Roberts
Lisa A Simms
Katherine Hanigan
Anthony Croft
Leila Amininijad
Isabelle Cleynen
Olivier Dewit
Denis Franchimont
Michel Georges
Debby Laukens
Emilie Theatre
Severine Vermeire
Guy Aumais
Leonard Baidoo
Arthur M Barrie
Karen Beck
Edmond-Jean Bernard
David G Binion
Alain Bitton
Steve R Brant
Judy H Cho
Albert Cohen - Center for Research on Inflammation
Kenneth Croitoru
Mark J Daly
Lisa W Datta
Colette Deslandres
Richard H Duerr
Debra Dutridge
John Ferguson
Joann Fultz
Philippe Goyette
Gordon R Greenberg
Talin Haritunians
Gilles Jobin - Université Paris Sciences et Lettres
Seymour Katz
Raymond G Lahaie
Dermot P McGovern
Linda Nelson
Sok Meng Ng
Kaida Ning
Pierre Pare - Center for Research on Inflammation
Miguel D Regueiro
John D Rioux
Elizabeth Ruggiero
L Philip Schumm
Marc Schwartz
Regan Scott
Yashoda Sharma
Mark S Silverberg
Denise Spears
A Hillary Steinhart
Joanne M Stempak
Jason M Swoger
Constantina Tsagarelis
Clarence Zhang
Hongyu Zhao
Jan Aerts
Tariq Ahmad
Hazel Arbury
Anthony Attwood
Adam Auton
Stephen G Ball
Anthony J Balmforth
Chris Barnes
Jeffrey C Barrett
Ines Barroso
Anne Barton
Amanda J Bennett
Sanjeev Bhaskar
Katarzyna Blaszczyk
John Bowes
Oliver J Brand
Peter S Braund
Francesca Bredin
Gerome Breen
Morris J Brown
Ian N Bruce
Jaswinder Bull
Oliver S Burren
John Burton
Jake Byrnes
Sian Caesar
Niall Cardin
Chris M Clee
Alison J Coffey
John Mc Connell
Donald F Conrad
Jason D Cooper
Anna F Dominiczak
Kate Downes
Hazel E Drummond
Darshna Dudakia
Andrew Dunham
Bernadette Ebbs
Diana Eccles
Sarah Edkins
Cathryn Edwards
Anna Elliot
Paul Emery
David M Evans
Gareth Evans
Steve Eyre
Anne Farmer
I Nicol Ferrier
Edward Flynn
Alistair Forbes
Liz Forty
Jayne A Franklyn
Timothy M Frayling
Rachel M Freathy
Eleni Giannoulatou
Polly Gibbs
Paul Gilbert
Katherine Gordon-Smith
Emma Gray
Elaine Green
Chris J Groves
Detelina Grozeva
Rhian Gwilliam
Anita Hall
Naomi Hammond
Matt Hardy
Pile Harrison
Neelam Hassanali
Husam Hebaishi
Sarah Hines
Anne Hinks
Graham A Hitman
Lynne Hocking
Chris Holmes
Eleanor Howard
Philip Howard
Joanna MM Howson
Debbie Hughes
Sarah Hunt
John D Isaacs
Mahim Jain
Derek P Jewell
Toby Johnson
Jennifer D Jolley
Ian R Jones
Lisa A Jones
George Kirov
Cordelia F Langford
Hana Lango-Allen
G Mark Lathrop
James Lee
Kate L Lee
Charlie Lees
Kevin Lewis
Cecilia M Lindgren
Meeta Maisuria-Armer
Julian Maller
John Mansfield
Jonathan L Marchini
Paul Martin
Dunecan CO Massey
Wendy L McArdle
Peter McGuffin
Kirsten E McLay
Gil McVean - Université Paris Sciences et Lettres
Alex Mentzer
Michael L Mimmack
Ann E Morgan
Andrew P Morris
Craig Mowat
Patricia B Munroe
Simon Myers
William Newman
Elaine R Nimmo
Michael C O'Donovan
Abiodun Onipinla
Nigel R Ovington
Michael J Owen
Kimmo Palin
Aarno Palotie
Kirstie Parnell
Richard Pearson
David Pernet
John RB Perry
Anne Phillips
Vincent Plagnol
Natalie J Prescott
Michael A Quail
Suzanne Rafelt
Nigel W Rayner
David M Reid
Anthony Renwick
Susan M Ring
Neil Robertson
Samuel Robson
Ellie Russell
David St Clair
Jennifer G Sambrook
Jeremy D Sanderson
Stephen J Sawcer
Helen Schuilenburg
Carol E Scott
Richard Scott
Sheila Seal
Sue Shaw-Hawkins
Beverley M Shields
Matthew J Simmonds
Debbie J Smyth
Elilan Somaskantharajah
Katarina Spanova
Sophia Steer
Jonathan Stephens
Helen E Stevens
Kathy Stirrups
Millicent A Stone
David P Strachan
Zhan Su
Deborah PM Symmons
John R Thompson
Wendy Thomson
Martin D Tobin
Mary E Travers
Clare Turnbull
Damjan Vukcevic
Louise Wain - Université Paris Sciences et Lettres
Mark Walker
Neil M Walker
Chris Wallace
Margaret Warren-Perry
Nicholas A Watkins
John Webster
Michael N Weedon
Anthony G Wilson
Matthew Woodburn
B Paul Wordsworth
Chris Yau
Allan H Young
Eleftheria Zeggini
Matthew A Brown
Paul R Burton
Mark J Caulfield
Alastair Compston
Martin Farrall
Stephen CL Gough
Alistair S Hall
Andrew T Hattersley
Adrian VS Hill
Christopher G Mathew
Marcus Pembrey
Jack Satsangi
Michael R Stratton
Jane Worthington
Matthew E Hurles
Audrey Duncanson
Willem H Ouwehand
Miles Parkes
Nazneen Rahman
John A Todd
Nilesh J Samani
Dominic P Kwiatkowski
Mark McCarthy
Nick Craddock
Panos Deloukas
Peter Donnelly
Jenefer M Blackwell
Elvira Bramon
Juan P Casas
Aiden Corvin
Janusz Jankowski
Hugh S Markus
Colin NA Palmer
Robert Plomin
Anna Rautanen
Richard C Trembath
Ananth C Viswanathan
Nicholas W Wood
Chris CA Spencer
Gavin Band
Celine Bellenguez
Colin Freeman
Garrett Hellenthal
Matti Pirinen
Amy Strange
Hannah Blackburn
Suzannah J Bumpstead
Serge Dronov
Matthew Gillman
Alagurevathi Jayakumar
Owen T McCann
Jennifer Liddle
Simon C Potter
Radhi Ravindrarajah
Michelle Ricketts
Matthew Waller
Paul Weston
Sara Widaa
Pamela Whittaker
Publication Details: Scientific Reports, Vol.9, 10351
Publisher: Nature Research
Date published: 17/07/2019
Grant note: This work was supported by Fondation pour la Recherche Médical (ref DEI20151234405) and Investissements d’Avenir programme ANR-11-IDEX-0005-02, Sorbonne Paris Cite, Laboratoire d’excellence INFLAMEX. The authors thank the students that participated to the wisdom of the crowd exercise.
Identifiers: 99817432002346
Copyright: © The Author(s) 2019. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Academic Unit: School of Biosciences
Language: English
Resource Type: Journal article

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

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