IGES Conference

Watch the Videos: Scroll down to access the prerecorded “Lightning Talks for Topped-ranked Poster”and invited “Speakers Talks”. These are posted in the order they appear in the IGES 2020 Program (Click here for PDF).  Live talks will be posted at a later date.

IGES 2020 Program: Live video presentations from keynote speakers and Neel and Williams award finalists will take place on July 2nd and 3rd, with questions and discussions after each talk.  Check out the IGES website for the full set of conference activities, and register to obtain the link for the zoom broadcasts; registration is free! Check the website regularly, for additional opportunities to interact with conference attendees–via zoom breakout rooms and chat sessions. 

 Poster SessionPosters can be viewed, commented on, and discussed with the author on the IGES website. IGES Abstracts: The 2020 meeting abstracts have been published in Genetic Epidemiology; click to  download or view 

Don’t forget !! Share comments about your favourite talk on social media – use URL http://ludmercentre.ca/iges-conference

Don’t forget to use the IGES 2020 hashtag!  —  #iges20stay@home

IGES Program Videos

Invited videoconference presentations, July 2, 2020

EDT: 8:00 am – 10:30 am, July 2, 2020

BST: 13h00-15h30, July 2, 2020

KST: 21h00-23h30, July 2, 2020

EDT: 8:00-8:15 am

BST: 13h00-13h15

KST: 21h00-21h15

Opening & Introduction

Chairs: Corinne Engelman and Celia Greenwood

EDT: 8:15 – 8:45 am

BST: 13h15-13h45

KST: 21h15-21h45

Peter Kraft, Ph.D.

IGES President 2020

Presidential Address

Peter Kraft is a Professor of Epidemiology and Biostatistics at the Harvard T.H. Chan School of Public Health. Dr. Kraft’s research focuses on statistical issues in the design and analysis of genetic association studies, with an emphasis on applications in cancer epidemiology. He has published over 300 articles and was recognized by Thompson Reuters as a highly cited researcher in 2014. Dr. Kraft has also developed and taught courses on introductory genetic epidemiology and “big data” for epidemiologists. Dr. Kraft is the Director of the Harvard Chan Program in Genetic Epidemiology and Statistical Genetics, and Faculty Director of the Harvard Chan Bioinformatics Core.

Q&A with Prof. Kraft

EDT: 8:45 – 9:15 am

BST: 13h45-14h15

KST: 21h45-22h15

Hongbing Shen, M.D., Ph.D.

 President, Nanjing Medical University

Polygenic Risk Scores for Lung Cancer in Chinese and Caucasian Populations

Professor Shen is the Academician of the Chinese Academy of Engineering and President of Nanjing Medical University. He also served as Director of the Cancer Center and Professor of Epidemiology for Nanjing Medical University. Prof. Shen’s research is primarily focused on genetic and environmental influences on cancer development and prognosis. Prof. Shen has led a large study exploring the genetic basis of lung cancer in the Chinese population which identified novel susceptibility genes. In addition, he developed a polygenic risk score (PRS) for lung cancer which has been successfully evaluated in a large-scale prospective cohort study in Chinese population.

Note: There was no live Q&A due to technical issues. 

ETD: 9:15 – 9:45 am

BST: 14h15-14h45

KST: 22h15-22h45

Zhengming Chen, Ph.D.

Professor of Epidemiology,  University of Oxford

Realizing the power of big biobanks in diverse populations for stroke medicine

Professor Chen’s primary research domains lie in the environmental and genetic causes of chronic disease, evidence-based medicine and evaluation of widely practicable treatments for chronic diseases (such as IHD, stroke and cancer) as well as efficient strategies for chronic disease control in developing countries. Over the past 20 years, he has led several large randomised trials and cohort studies involving >750,000 individuals. He has been the lead principal investigator in the UK for the China Kadoorie Biobank (CKB) prospective study of 0.5 million adults, leading a research team in Oxford for the study design, development, data management and analysis for the CKB.

Q&A with Prof. Chen (short due to delayed start)

EDT: 9:45 – 10:00 am

BST: 14h45-15h00

KST: 22h45-23h00

Neel Finalist

Divya Sharma, Ph.D.

Dalla Lana School of Public Health, University of Toronto

Combining human and artificial intelligence: Ensemble of convolutional neural networks for disease prediction from microbiome data

Research supports the potential use of microbiome as a predictor of some diseases. Motivated by the findings that microbiome data is complex in nature and there is an inherent correlation due to the hierarchical taxonomy of microbial Operational Taxonomic Units (OTUs), we proposed a novel machine learning method incorporating a stratified approach to group OTUs into clusters based on their phylum. Convolutional Neural Networks (CNNs) were used to train within each of the clusters individually. Further, through ensemble learning approach, features obtained from each cluster were concatenated to improve prediction accuracy.

EDT: 10:00 – 10:15 am

BST: 15h00-15h15

KST: 23h00-23h15

Neel Finalist

Stefan Konigorski, Ph.D.

Digital Health & Machine Learning Group, Hasso Plattner Institute for Digital Engineering, Potsdam, Germany

Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, USA

Fast Kernel-based Rare-Variant Association Tests Integrating Variant Annotations from Deep Learning

In recent years, deep learning has enabled the accurate prediction of the function of DNA‐ and RNA‐sequences based on their nucleotide sequences alone. In another line of research, kernel‐based tests have been established as powerful association tests of rare genetic variants. Here, we combine these two streams of research and present seak (se quence a nnotations in k ernel‐based tests): a fast implementation of flexible set‐based genetic association tests that include variant effects on intermediate molecular traits, correcting for family and population structure. This can be interpreted as testing for genetic effects that are mediated or moderated by intermediate molecular traits.

ETD: 10:15 – 10:30 am

BST: 15h15-15h30

KST: 23h15-23h30

Neel Finalist

Myriam Brossard, Ph.D.

Lunenfeld‐Tanenbaum Research Institute, Sinai Health System, Toronto, Canada 

Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Canada

Characterization of direct and/or indirect genetic associations for multiple traits in longitudinal studies of disease progression

Associations of SNPs and longitudinal factors with time‐to‐event outcomes are often investigated with a Cox survival model (CM) that includes longitudinal risk factors as time dependent covariates. When longitudinal traits are endogenous and/or are measured with random error, joint modelling of risk factors and outcomes can determine direct and/or indirect association of SNPs with time‐to‐event traits while accounting for dependences with risk factors. Here, we present a joint model (JM) that consists of: a mixed model for multiple longitudinal traits describing the trajectory of each trait as a function of SNP effects and subject random effects; and a frailty CM for multiple time‐to‐event outcomes that depends on SNPs and longitudinal trajectories

General Q&A with all the Speakers

1st Lightning Talks, Top Ranked Posters, July 2, 2020

EDT: 2:00-3:00 pm, July 2, 2020

BST: 19h00-20h00, July 2, 2020

KST: 03h00-04h00, July 2, 2020

EDT: 2:00-3:00 pm

BST: 19h00-20h00 

KST: 03h00-04h00


France Gagnon

Wei Xu

Group 1 of 4 --- 8 Talks

Presenters 1.1 to 1.4

1.1  Jocelyn Quistrebert, Paris Descartes University
1.2  Yafang Li, Baylor College of Medicine
1.3  Wes Spiller, University of Bristol
1.4  Quan Long, University of Calgary

Q&A with Presenters 1.1 to 1.4

Presenters 1.5 to 1.8

1.5  Jonathan Sulc, University of Lausanne
1.6  Peng Wei, University of Texas, MD Anderson Center
1.7  Diana Kormilez, University of Lübeck
1.8  Yanyu Liang, University of Chicago

Q&A with Presenters 1.5 to 1.8

2cd Lightning Talks, Top Ranked Posters, July 2 (3*), 2020

EDT: 8:00-9:00 pm, July 2, 2020

BST: 01h00-02h00, July 3*, 2020

KST: 9h00-10h00, July 2, 2020

EDT: 8:00-9:00 pm

*BST: 01h00-02h00*

KST: 9h00-10h00


Saonli Basu

Zuoheng Wang


* July 3 (not 2)

Group 2 of 4 -- 8 Talks

Presenters 2.1 to 2.2

2.1  Douglas Shaw, Vanderbilt University
2.2  Xuexia Wang, University of North Texas
2.3  Xinyuan Zhang, University of Pennsylvania
2.4  Subrata Paul, University of Colorado – Denver

Q&A with Presenters 2.1 to 2.4

Presenters 2.5 to 2.8

2.5  Kangjin Kim, Seoul National University
2.6  Yunlong Liu, Indiana University School of Medicine
2.7  Dongjing Liu, University of Pittsburg
2.8  Shelley Bull, Lunenfeld Research Institute

Q&A with Presenters 2.5 to 2.8

Invited videoconference presentations, July 3, 2020

EDT: 8:00-10:30 am, July 3, 2020

BST: 13h00-15h30, July 3, 2020

KST: 21h00-23h30, July 3, 2020

EDT: 8:00-8:10 am


Chairs: Heike Bickeboller and Sanjay Shete

EDT: 8:10-8:40 am

BST: 13h10-13h40

KST: 21h10-21h40

Xihong Lin, Ph.D.


T.H. Chan School of Public Health4

Analysis of Large-Scale Biobanks and Whole Genome Sequencing Studies: Challenges and Opportunities

Xihong Lin is Professor of Biostatistics, Professor of Statistics, and Coordinating Director of the HCSPH Program in Quantitative Genomics at Harvard University. Dr. Lin’s research interests lie in development and application of scalable statistical and computational methods for analysis of massive data from genome, exposome and phenome, such as Whole Genome Sequencing studies, integrative analysis of different types of data, and biobanks. She received the 2006 Presidents’ Award and the 2017 FN David Award from the Committee of Presidents of Statistical Societies (COPSS), and is an elected member of the US National Academy of Medicine. She is the PI of the Outstanding Investigator Award (R35) from the National Cancer Institute, and the contact PI of the Harvard Analysis Center of the Genome Sequencing Program of the National Human Genome Research Institute.

EDT: 8:40-8:55 am

BST: 13h40-13h55

KST: 21h40-21h55

Moderated discussion of Dr. Lin’s presentation

Dr. Philip Awadalla, Ontario Institute for Cancer Research

Williams Finalist  —


Heike Bickeboller

Sanjay Shete

Williams Award

EDT: 8:55-9:10 am

BST: 13h55-14h10

KST: 21h55-22h10

Williams Finalist  —

Dongyang Yang, Ph.D.

Division of Biostatistics, Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada

Clustering of Human Microbiome Sequencing Data: A Distance-based Unsupervised Learning Model

Analysis of the human microbiome allows the assessment of the microbial community and its impacts on human health. Microbiome composition can be quantified using 16 S rRNA technology into sequencing data which are usually skewed and heavy‐tailed with excess zeros. Clustering approaches are useful in personalized medicine by identifying subgroups for patients stratification. However, there is currently a lack of standardized clustering method for such complex microbiome sequencing data. We propose a clustering algorithm with a specific beta diversity measure that can address the presence‐absence bias encountered for sparse count data and effectively measure the sample distances for stratification.

Q&A with Dongyang Yang

EDT: 9:10-9:25 am

BST: 14h10-14h25

KST: 22h10-22h25

Williams Finalist

Grace Png, Ph.D.

Institute of Translational Genomics, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany

Exploring the Genetic Architecture of the Human Neurological Proteome using Whole Genome Sequencing

The human proteome has a stronger genetic component compared to many complex diseases, making it a valuable resource of potential disease biomarkers and drug targets. This is especially so for highly polygenic neurological disorders whose mechanisms remain elusive. Here, we present the first sequence‐based protein quantitative trait loci (pQTL) analysis of 92 neurological proteins.

Q&A with Grace Png

EDT: 9:25-9:40 am

BST: 14h25-14h40

KST: 22h25-22h40

Williams Finalist

Roxanna Korologou-Linden, MSc.

Medical Research Council Integrative Epidemiology Unit, and   Population Health Sciences, Bristol Medical School, University of Bristol, UK

Investigating causal effects of genetic variants for Alzheimer's disease in the UK BIOBANK

Observational studies for Alzheimer’s disease (AD) have reported conflicting evidence for potential modifiable risk factors, possibly due to bias from confounding, selection bias and reverse causation. Genetic studies have identified SNPs associated with late‐onset Alzheimer’s disease, all exerting low to modest effects (except for those in the apolipoprotein E gene). We perform a phenome‐wide association study (pheWAS) to investigate the effects of a polygenic risk score (PRS) for AD on a wide range of phenotypes, minimizing the bias of a prior hypothesis and confounding present in most observational studies.

Note; due to technical difficulties there was no live Q&A.

Award sponsored by Wiley

Best 2019 paper in Genetic Epidemiology

Best Paper Awardee

Paper: Lai Jiang, Constrained Instruments and Their Application to Mendelian Randomization with Pleiotropy, Genet Epidemiol. 2019 Jun;43(4):373-401

IGES Discussant, Andre Scherag, Jena University Hospital, Germany

IGES Discussant, Frank Dudbridge, University of Leicester, Leicester, UK

Discussion and Q&A

3rd Lightning Talks, Top Ranked Posters, July 3 (4*), 2020

EDT: 2:00-3:00 pm, July 3, 2020

BST: 19h00-20h00, July 3, 2020

KST: 03h00-04h00, July 4*, 2004

EDT: 2:00-3:00 pm

BST: 19h00-20h00

*KST: 03h00-04h00*


Iris Heid

Janet Sinsheimer

* July 4 (not 3)

Group 3 of 4 -- 8 Talks

Presenters 3.1 to 3.4

3.1  Mathias Gorski, University of Regensburg
3.2  Katharina Stahl, University of Göttingen
3.3  Tianyuan Lu, McGill University
3.4  Michael Epstein, Emory University

Q&A with Presenters 3.1 to 3.4

Presenters 3.5 to 3.8

3.5  Rima Mustafa, Imperial College London
3.6  Michael Hauser, Duke University
3.7  Lucy Goudswaard, University of Bristol
3.8  Jeanine Houwing-Duistermaat, University of Leeds

Q&A with Presenters 3.5 to 3.8

4th Lightning Talks, Top Ranked Posters, July 3 (4*), 2020

EDT: 8:00-9:00 pm, July 3, 2020

BST: 19h00-20h00, July 4*, 2020

KST: 9h00-10h00, July 4*, 2004

EDT: 8:00-9:00 pm

*BST: 01h00-02h00*

*KST: 9h00-10h00*


Maggie Wang

Hsin-Chou Yang

* July 4 (not 3)

Group 4 of 4 -- 8 Talks

Presenters 4.1 to 4.4

4.1  Soyoung Jeon, University of Southern California
4.2  Pimphen Charoen, Mahidol University
4.3  Xiaoxuan Xia, Chinese University of Hong Kong
4.4  Ian Arriaga MacKenzie, University of Colorado-Denver

Q&A with Presenters 4.1 to 4.4

Presenters 4.5 to 4.8

4.5  Lai Jiang, McGill University
4.6  Eun Kyung Choe, University of Pennsylvania
4.7  Genevieve Wojcik, Johns Hopkins, Bloomberg School of Public Health
4.8  Hongyan Xu, University of Augusta 

Q&A with Presenters 4.5 to 4.8

Special Session, Genetic Epidemiology of COVID-19 and SARS-COV-2, July 4, 2020

EDT: 8:00-9:00 pm, July 4, 2020

BST: 19h00-20h00, July 4, 2020

KST: 9h00-10h00, July 4, 2004


Chairs: Stella Aslibekyan and Saurabh Ghosh

EDT: 9:00-9:30am

BST: 14h00-14h30

KST: 22h00-22h30

Priya Duggal, Ph.D. 

Associate Professor of Epidemiology and International Health, and the Director, Genetic Epidemiology program, Johns Hopkins Bloomberg School of Public Health

Co-Director, Burroughs-Wellcome funded training program, Maryland: Genetics, Epidemiology and Medicine 


Host Genetics and COVID-19: What do we know about infectious diseases?

Priya Duggal received her MPH in International Health and PhD in Epidemiology at the Johns Hopkins Bloomberg School of Public Health with Dr. Terri H. Beaty. She then completed her post-doctoral fellowship in Statistical Genetics at the National Human Genome Research Institute with Dr. Joan Bailey-Wilson. Her research is on the host genetic susceptibility to infectious disease with a focus on the role of host genetics in susceptibility and progression of disease and immune response. She has worked with both adult and pediatric populations within the US and Internationally to identify host genes associated with parasitic (E. histolytica, Cryptosporidium), viral (hepatitis C, HIV, hepatitis B, enterovirus) and bacterial (campylobacter) infections. She also leads efforts to understand Acute Flaccid Myelitis , a paralysis that occurs in children following a viral infection. And she is directing the genetics arm of the Environmental Influences on Child Health Outcomes (ECHO) study of 50,000 children and mothers. Dr. Duggal has served on the education (2007-2010), local planning (2014-2015) and communications committees (2015-present) for IGES.

Recording includes Q&A at the end. 

EDT: 9:30-9:45am

BST: 14h30-14h45

KST: 22h30-22h45

Mulong Du, Ph.D.

Harvard T.H. Chan School of Public Health

A Multiple Omics Analysis of COVID-19-Associated ARDS Identified Pathways Associated with Risk and Potential Intervention

Visiting Scientist, Harvard T.H. Chan School of Public Health.
Instructor, School of Public Health, Nanjing Medical University.
Genetic Epi and Biostatistics.

Recording includes Q&A at the end. 

EDT: 9:30-9:45 am

BST: 14h30-14h45

KST: 22h30-22h45

Matthew PatrickMEng, Ph.D.

University of Michigan, Ann Arbor

Psoriasis and Covid-19 Shared Genetic Signal in LCE Gene cluster

Matthew Patrick, MEng, PhD joined the U-M Department of Dermatology faculty as a Research Investigator in 2020. He is a member of the Cutaneous Bioinformatics Research Program. Dr. Patrick is pursuing research focused upon translational bioinformatics, particularly on providing biological inference from high dimensional data for dermatological research.

Recording includes Q&A at the end. 

EDT: 10:00-10:15 am

BST: 15h00-15h15

KST: 23h00-23h15

Georg Hahn, Ph.D.

Harvard T.H. Chan School of Public Health

Unsupervised Cluster Analysis of SARS-CoV-2 Genomes Identifies Distinct Genetic Subgroups of the SARS-CoV-2 Virus

Georg Hahn is a research associate at Harvard University working on large-scale estimation and multiple testing problems in the Biostatistics Department of the Harvard T.H. Chan School of Public Health.

Q&A with G Hahn

EDT: 10:15-10:30 am

BST: 15h15-15h30

KST: 23h15-23h30

Maik Pietzner, Ph.D. 

MRC Epidemiology Group, University of Cambridge

Genetic Architecture of Host Proteins Interacting with SARS-CoV-2

Maik Pietzner is a Senior Research Associate, Aetiology and Mechanisms of Diabetes and Related Metabolic Disorders of Later Life. A biomathematician by training Maik Pietzner is working on the computational and knowledge-based integration of large-scale OMICs data sets, e.g. genomics, proteomics or metabolomics, from population-based studies to identify mechanisms causing metabolic diseases, in particular type 2 diabetes.

Recording includes Q&A at the end. 

EDT: 10:30-11:00 am

BST: 15h30-16h00

KST: 23h30-24h00

Caroline Colijn, Ph.D.

Canada 150 Research Chair in Mathematics for Evolution, Infection and Public Health

Simon Fraser University

Serial intervals and virus genomes: estimating SARS-CoV-2 epidemic parameters with genomic data

Dr Colijn’s work is at the interface of mathematics and the epidemiology and evolution of pathogens. She hold a Canada 150 Research Chair in Mathematics for Evolution, Infection and Public Health. Her group developd mathematical tools connecting sequence data to the ecology and evolution of infections. She also has a long-standing interest in the dynamics of diverse interacting pathogens; e.g., how the interplay between co-infection, competition and selection drive the development of antimicrobial resistance. To answer these questions, her group is building new approaches to analyzing and comparing phylogenetic trees derived from sequence data, studying tree space and branching processes, and developing ecological and epidemiological models with diversity in mind.

Q&A with Dr. Caroline Colijn

EDT: 11:00-11:15 am

BST: 16h00-16h15

KST: 24h00-24h15


Announcements: Award winners

Neel Award and Williams Award winners, sponsored by Wiley

Poster competition, sponsored by CANSSI STAGE

The IGES Program Committee and the Board of Directors would like to warmly thank all keynote speakers, conference participants, and IGES members for their willingness to participate in this altered format for our annual conference. 

In particular, we would like to thank this year’s sponsors (Wiley, Ludmer Centre for Neuroinformatics & Mental Health) and the sponsors who have agreed to defer their sponsorship until the 2021 meeting (Dalla Lana School of Public Health, Canadian Institute of Health Research). Mark the dates for IGES 2021:  August 16-18, 2021, Esterel Resort, Estérel, (Province of) Quebec, Canada .

On behalf of the Ludmer Centre’s Scientific co-Director Celia Greenwood, the Centre and McGill University are please to assist with this online event and the hosting of these conference videos.

For more information, visit the IGES website (here) or contact:

Program Committee Chair for 2020 IGES meeting: Dr. Ching-Ti Liu
IGES Past President: Dr. Celia Greenwood
IGES 2020 President: Dr. Peter Kraft