Singapore, 15 December 2025—As global health systems brace for the next wave of infectious and chronic diseases, scientists are looking to human genetics, population differences, medical imaging and health informatics for answers. As an example, researchers have proposed that understanding how genetic variants shape disease susceptibility across populations could transform how the world prepares for future threats.
To investigate this possibility, one of the five projects awarded under this year’s Duke–Duke-NUS Research Collaboration Pilot Project Grants focuses on studies comparing cohorts in Singapore and the United States to determine genetic features controlling infection susceptibility. Co-led by Associate Professor Dennis Ko from Duke University School of Medicine and Assistant Professor Mart Matthias Lamers from Duke-NUS Medical School, this flagship project is titled "An Organoid Single-Cell GWAS Platform for Comparing Infectious Disease Susceptibility in USA vs. Singapore”.
To investigate how genetic differences influence vulnerability to respiratory pathogens, the scientists will grow nasal organoids—miniature models of the human nose—using cells from hundreds of donors from both countries. By exposing these cells to viruses, they will analyse how infection unfolds at the cellular level and build an atlas of human genetics susceptibility that could accelerate new drug discovery.
The other four projects will tackle high-impact healthcare challenges in liver transplantation, diabetes, lung cancer and eye disease:
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Project title: MIA-Lung: Multiplex IHC Atlas for Lung Cancer |
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Project title: Uncovering Ancestry-Specific and Shared Genetic Risk Factors for Fuchs Endothelial Corneal Dystrophy (FECD) in Asian and European Populations through Integrative Genomics |
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Project title: Comparative Outcomes in Liver Transplantation: A Two-Center Analysis of U.S. and Singapore Cohorts |
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Project title: Comparative Imaging-Based Analysis of Adiposity Distribution and Diabetes Risk in Asian and Non-Asian Populations |
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Diseases can often differ in how they appear, progress and respond to treatment across Asian and non-Asian populations—differences shaped by genetics as well as environmental and lifestyle factors. Studying diverse populations helps researchers identify the drivers of these variations and translate them into more accurate diagnoses and targeted treatments.
“Studying different populations helps reveal what drives disease variations and how care can be tailored to serve people more effectively,” said Professor Patrick Tan, Dean-designate and Senior Vice-Dean for Research at Duke-NUS.
“Thanks to advances in genomics and data science, large-scale analyses are now possible at an unprecedented level. Through its long-standing partnerships with Duke University and SingHealth, Duke-NUS is uniquely positioned to support scientifically compelling studies tapping on both the US and Singapore.”
More than 40 proposals were submitted this year and following a competitive review, five outstanding projects were selected. Each is jointly led by a Duke Principal Investigator (PI) and a Duke-NUS PI. The Duke PI will receive US$100,000 and the Duke-NUS PI will receive S$100,000 over two years.
Since 2009, the Duke-Duke-NUS partnership has supported over 70 projects[1] with more than S$8.5 million in funding—underscoring a long-standing commitment to advancing innovative research addressing urgent global health challenges.
For detailed descriptions of this year’s projects and their expected impacts, please refer to Annex A.
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[1] Excludes the five newly-awarded projects.
Annex A: About the Projects
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TITLE: MIA-Lung: Multiplex IHC Atlas for Lung Cancer PIs: Laura Alder (Duke PI), Aaron Tan Chia-Ken (Duke-NUS PI) SUMMARY: The MIA-Lung (Multiplex IHC Atlas for Lung Cancer) study seeks to profile ADC-relevant biomarkers using multiplex immunohistochemistry (IHC) on tissue microarrays (TMAs) from both Asian (Duke-NUS) and Western (Duke) cohorts. |
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TITLE: An Organoid Single-Cell GWAS Platform for Comparing Infectious Disease Susceptibility in USA vs. Singapore PIs: Dennis Ko (Duke PI), Mart Matthias Lamers (Duke-NUS PI) SUMMARY: As the world recovers from COVID-19, it faces growing health challenges from drug-resistant bacteria and viruses that can jump from animals to people. To stay safe, we need new and smarter ways to fight infections. One promising approach is studying how our genes affect how we respond to viruses, but such studies currently require data from thousands of patients. This project takes another approach by using nasal cell cultures from hundreds of volunteers (from the USA and Singapore). These cells are exposed to viruses to see how easily each person’s cells become infected. This information can then be used to figure out which bits of DNA make some people more or less susceptible to viruses. This will enable us to test whether people in the USA and Singapore show different genetic patterns of virus susceptibility. |
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TITLE: Uncovering Ancestry-Specific and Shared Genetic Risk Factors for Fuchs Endothelial Corneal Dystrophy (FECD) in Asian and European Populations through Integrative Genomics PIs: Li Yi-Ju (Duke PI), Jodhbir Mehta (Duke-NUS PI) SUMMARY: Fuchs Endothelial Corneal Dystrophy (FECD) is a progressive corneal disorder affecting 7–12% of the population, with symptoms typically manifesting after age 50 and occurring 2-4 times more in women. FECD is the leading cause of corneal transplantation worldwide, leading to high healthcare burden. Genetic predisposition plays a significant role in FECD, strongly supported by high heritability estimates and genetic findings. Several genetic risk variants have been identified for FECD, but primarily in European populations. Among them, the trinucleotide repeat expansion (CTG18.1) in TCF4 was well-confirmed by multiple studies from different populations. Our group led a large genome-wide association study for FECD and identified three additional novel loci, including KANK4, LAMC1, and LINC00970/ATP1B1. However, these findings still do not fully explain FECD heritability. There is still a large knowledge gap for the genetics of FECD in non-European populations. This proposal aims to bridge the genetic understanding of FECD between European and Asian cohorts through three objectives: (1) Identifying common and rare variants associated with FECD risk through the analysis of whole genome sequence data; (2) investigating mitochondrial variants and haplogroups for their association with FECD risk; and (3) developing predictive polygenic risk scores incorporating nuclear and mitochondrial variants and correlating them with clinical and demographic features. This integrative approach is expected to advance genetic discovery and risk prediction for FECD across European and Asian ancestries. |
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TITLE: Comparative Outcomes in Liver Transplantation: A Two-Center Analysis of U.S. and Singapore Cohorts PIs: Debra Lynn Sudan (Duke PI), Prema Raj Jeyaraj (Duke-NUS PI) SUMMARY: Liver transplantation (LT) represents the definitive treatment for end-stage liver disease, yet significant international variation exists in access, donor practices, and outcomes. In Singapore, living donor liver transplantation (LDLT) predominates due to limited deceased donor availability, while in the US, deceased donor liver transplantation (DDLT) remains the standard, including the use of extended criteria donors and machine perfusion technologies. These differing strategies may influence post-transplant recovery, complication profiles, and health system burden, but comparative evidence remains limited. This pilot project aims to compare post-transplant outcomes between two major transplant centers in Singapore and the US and identify predictors of failure to achieve “textbook outcomes” (TO) – a validated composite measure of optimal recovery. TO encompasses 90-day survival without graft failure, surgical intervention, ICU readmission, or transfusion. Only one in three LT recipients achieve TO, with TO failure incurring significant clinical and economic consequences. We propose to develop a harmonised data analytic framework incorporating electronic medical record (EMR)-derived data from Duke University Hospital (DUH) and SingHealth Duke-NUS Transplant Centre (SDTC). Further, we will adopt and refine automated tools, such as Duke’s automated post-operative outcome detection algorithm and Singapore’s Patient Condition Adaptive Pathway System (PCAPS) to extract high-fidelity clinical data. We aim to identify key demographic, clinical, and procedural factors driving TO failure and mortality. By establishing a scalable, harmonised framework for transplant outcomes benchmarking, this project will lay the foundation for international quality improvement tools and real-time decision support system in LT. |
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TITLE: Comparative Imaging-Based Analysis of Adiposity Distribution and Diabetes Risk in Asian and Non-Asian Populations PIs: Jiuk James Jung (Duke PI), Liu Nan (Duke-NUS PI) SUMMARY: Asian individuals develop type 2 diabetes mellitus (T2DM) at markedly lower body mass index (BMI) than non-Asian peers, yet the biologic drivers of this disparity remain unclear. Mounting evidence indicates that where fat is stored, especially visceral adipose tissue (VAT) and ectopic infiltration in skeletal muscle, rather than total mass determines metabolic risk. Leveraging recent advances in deep learning segmentation of routine CT scans, the study will undertake a transnational, harmonised analysis of imaging-derived adiposity characteristics and diabetic complications in Asian versus non-Asian cohorts. We will integrate two data sources: SingHealth Diabetes Registry linked with EHR (>200,000 Singaporeans, 95% Asian) and the Duke University Health System EHR (>3 million Americans, 96.5% non-Asian). A validated nnU-Net pipeline (Dice > 0.90 for VAT, subcutaneous adipose tissue (SAT), and skeletal muscle identification) will generate high-throughput measures of VAT/SAT and muscle density from abdominal CTs performed between 2015 – 2024. Aim 1 will compare VAT/SAT ratio and skeletal muscle fat infiltration across four BMI strata, testing the hypothesis that Asian adults with T2DM exhibit higher pathogenic fat depots than BMI-matched non-Asian counterparts. Aim 2 will evaluate whether these adiposity metrics differentially associate with micro- and macrovascular diabetes complications, using multivariable logistic regression with ethnicity-by-adiposity interaction terms. Immediate deliverables include open-source imaging segmentation platform, cross-ethnic effect-size estimates of imaging-derived characteristics predicting diabetic complications, and a secure analytic framework across two health systems. This pilot will catalyse future longitudinal studies of adiposity dynamics, inform precision risk-stratification tools beyond BMI, and advance equitable metabolic care for ethnically diverse populations. |