Jue Sheng Ong

Dr. Jue Sheng Ong

Statistical Genetics, Population Health Department, QIMR Berghofer Medical Research Institute, Herston, QLD, Australia

Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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27 August 2018 in Nature Neuroscience
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JPJoëlle A. Pasman
Joëlle A. Pasman
KVKarin J. H. Verweij
Karin J. H. Verweij
ZGZachary Gerring
Zachary Gerring
SSSven Stringer
Sven Stringer
SSSandra Sanchez-Roige
Sandra Sanchez-Roige
JVJacqueline Vink
Jacqueline Vink

24 February 2021 in Nature Communications
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Journal Article
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PGPuya Gharahkhani
Puya Gharahkhani
EJEric Jorgenson
Eric Jorgenson
PHPirro Hysi
Pirro Hysi
AKAnthony P. Khawaja
Anthony P. Khawaja
SPSarah Pendergrass
Sarah Pendergrass
JWJaney L. Wiggs
Janey L. Wiggs
Primary open-angle glaucoma (POAG), is a heritable common cause of blindness world-wide. To identify risk loci, we conduct a large multi-ethnic meta-analysis of genome-wide association studies on a total of 34,179 cases and 349,321 controls, identifying 44 previously unreported risk loci and confirming 83 loci that were previously known. The majority of loci have broadly consistent effects across European, Asian and African ancestries. Cross-ancestry data improve fine-mapping of causal variants for several loci. Integration of multiple lines of genetic evidence support the functional relevance of the identified POAG risk loci and highlight potential contributions of several genes to POAG pathogenesis, including SVEP1, RERE, VCAM1, ZNF638, CLIC5, SLC2A12, YAP1, MXRA5, and SMAD6. Several drug compounds targeting POAG risk genes may be potential glaucoma therapeutic candidates.

2 May 2019 in Genetic Epidemiology
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JOJue Sheng Ong
Jue Sheng Ong
Stuart MacGregorStuart MacGregor
Stuart MacGregor
With the advent of very large scale genome‐wide association studies (GWASs), the promise of Mendelian randomization (MR) has begun to be fulfilled. However, whilst GWASs have provided essential information on the single nucleotide polymorphisms (SNPs) associated with modifiable risk factors needed for MR, the availability of large numbers of SNP instruments raises issues of how best to use this information and how to deal with potential problems such as pleiotropy. Here we provide commentary on some of the recent advances in the MR analysis, including an overview of the different genetic architectures that are being uncovered for a variety of modifiable risk factors and how users ought to take that into consideration when designing MR studies.

20 January 2020 in Nature Genetics
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NCNEIGHBORHOOD consortium
NEIGHBORHOOD consortium
JCJamie E. Craig
Jamie E. Craig
UCUK Biobank Eye and Vision Consortium
UK Biobank Eye and Vision Consortium
XHXikun Han
Xikun Han
AQAyub Qassim
Ayub Qassim
Stuart MacGregorStuart MacGregor
Stuart MacGregor

27 July 2018 in Nature Genetics
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Stuart MacGregorStuart MacGregor
Stuart MacGregor
JOJue Sheng Ong
Jue Sheng Ong
JAJiyuan An
Jiyuan An
XHXikun Han
Xikun Han
TZTiger Zhou
Tiger Zhou
AHAlex Hewitt
Alex Hewitt

29 June 2021 in Gut
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JOJue Sheng Ong
Jue Sheng Ong
JAJiyuan An
Jiyuan An
XHXikun Han
Xikun Han
MLMatthew H Law
Matthew H Law
PNPriyanka Nandakumar
Priyanka Nandakumar
Stuart MacGregorStuart MacGregor
Stuart MacGregor
Objective Gastro-oesophageal reflux disease (GERD) has heterogeneous aetiology primarily attributable to its symptom-based definitions. GERD genome-wide association studies (GWASs) have shown strong genetic overlaps with established risk factors such as obesity and depression. We hypothesised that the shared genetic architecture between GERD and these risk factors can be leveraged to (1) identify new GERD and Barrett’s oesophagus (BE) risk loci and (2) explore potentially heterogeneous pathways leading to GERD and oesophageal complications. Design We applied multitrait GWAS models combining GERD (78 707 cases; 288 734 controls) and genetically correlated traits including education attainment, depression and body mass index. We also used multitrait analysis to identify BE risk loci. Top hits were replicated in 23andMe (462 753 GERD cases, 24 099 BE cases, 1 484 025 controls). We additionally dissected the GERD loci into obesity-driven and depression-driven subgroups. These subgroups were investigated to determine how they relate to tissue-specific gene expression and to risk of serious oesophageal disease (BE and/or oesophageal adenocarcinoma, EA). Results We identified 88 loci associated with GERD, with 59 replicating in 23andMe after multiple testing corrections. Our BE analysis identified seven novel loci. Additionally we showed that only the obesity-driven GERD loci (but not the depression-driven loci) were associated with genes enriched in oesophageal tissues and successfully predicted BE/EA. Conclusion Our multitrait model identified many novel risk loci for GERD and BE. We present strong evidence for a genetic underpinning of disease heterogeneity in GERD and show that GERD loci associated with depressive symptoms are not strong predictors of BE/EA relative to obesity-driven GERD loci.