| 1 |
Advancing Precision Medicine for Cardiovascular Disease and Diabetes in Asian Populations |
Lead PI:
Prof John Chambers, Lee Kong Chian School of Medicine
Co-Lead PI:
A/Prof Sim Xueling, National University of Singapore
Co-Lead PI:
Prof Cheng Ching-Yu, Duke-NUS Medical School
Co-Lead PI:
Prof Yeo Khung Keong, National Heart Centre Singapore |
1. Determine the behavioural (including nutrition and physical activity), environmental, genetic, and other molecular factors that underpin CVD and diabetes in the multi-ethnic Asian population in Singapore.
2. Develop and validate algorithms for accurate identification of Asian individuals who are at increased risk of CVD and diabetes. |
| 2 |
The SG100K Cognitive Health Programme |
Lead PI:
Adj Asst Prof Max Lam, Lee Kong Chian School of Medicine
Co-Lead PI:
A/Prof Jimmy Lee, Institute of Mental Health
Co-Lead PI:
Prof Liu Jianjun, A*STAR Genome Institute of Singapore |
1. Establish the biological underpinnings for cognitive function in diverse Asian and global populations.
2. Establish the biological convergence between cognitive function and disease traits.
3. Establish epidemiological and genomic risk predictors of cognitive health. |
| 3 |
The SG100K_Med Alliance - Clinical Genetics Researchers United for the Analysis of Mendelian Disease Variation in SG100K |
Lead PI:
Asst Prof Lim Weng Khong, Duke-NUS Medical School
Co-Lead PI:
A/Prof Joanne Ngeow, Lee Kong Chian School of Medicine
Co-Lead PI:
A/Prof Saumya Jamuar, Duke-NUS Medical School |
1. Seek a deeper understanding of genetic disease burden in major Asian populations through a comprehensive analysis of structural variation and short tandem repeat expansions.
2. Demonstrate how SG100K data can resolve variants of uncertain significance.
3. Explore impact of polygenic backgrounds on penetrance in autosomal dominant conditions for under-represented Asian populations. |
| 4 |
Identification of Asian-specific Genetic Association with Fat and Lean Muscle Mass Distribution |
Lead PI:
Asst Prof Liu Boxiang, National University of Singapore
Co-Lead PI:
A/Prof Sim Xueling, National University of Singapore
Co-Lead PI:
Prof Tai E Shyong, National University of Singapore |
1. Perform multi-ethnic meta-analysis of fat and lean muscle mass using SG100K and UKBB datasets.
2. Mendelian randomisation analysis to identify the contribution of fat and lean muscle mass to cardiometabolic diseases.
3. Colocalisation analysis to identify risk genes affecting fat and lean muscle mass.
4. Conduct functional validation studies of identified genetic loci. |
| 5 |
HLA alleles and its Association with Auto-immune Diseases and Pharmacogenomics in Multi-Ancestral Asian Populations |
Lead PI:
A/Prof Sim Xueling, National University of Singapore
Co-Lead PI:
Adj A/Prof Leong Khai Pang, Tan Tock Seng Hospital
Co-Lead PI:
Dr Wharton Chan, Duke-NUS Medical School |
1. Generate a high-resolution human leukocyte antigen (HLA) reference panel in Asian populations.
2. Generate frequencies of HLA alleles and haplotypes in Asian populations for local reference and for global population comparisons.
3. Conduct association analyses of HLA alleles in outcomes including auto-immune diseases and pharmacogenomic responses. |
| 6 |
Unraveling the Determinants of Kidney Health in a Multi-Ethnic Asian Population |
Lead PI:
A/Prof Yeo See Cheng, Tan Tock Seng Hospital
Co-Lead PI:
Prof John Chambers, Lee Kong Chian School of Medicine |
1. Determine prevalence of chronic kidney disease (CKD) among adults.
2. Examine association of CKD with genetic, clinical, and socio-behavioural predictors.
3. Examine relative contribution of key predictors driving differences in CKD risks across different sub-population.
4. Develop and validate an integrated risk score for the development of CKD in a representative multi-ethnic Asian population-based cohort in Singapore. |
| 7 |
The High Variability of Tandem Repeats Offers Insights into Population Diversity and may Explain the Missing Heritability of Complex Neurological and Neurocognitive Disorders in Asian Populations |
Lead PI:
Prof Liu Jianjun A*STAR Genome Institute of Singapore
Co-Lead PI:
Dr Nicolas Bertin, A*STAR Genome Institute of Singapore
Co-Lead PI:
Asst Prof Lim Weng Khong, Duke-NUS Medical School |
1. Generate SG100K genome wide tandem repeats (TR) variation catalogue and characterise their respective prevalence in Asian populations.
2. Characterise contributions of TR variations to the aetiology of complex neurological and neurocognitive disorders. |
| 8 |
An Integrated Pharmacoeconomic-Pharmacokinetic Framework for Prioritising and Testing Clinically Important Drug-Gene Interactions |
Lead PI:
Dr Janice Goh, A*STAR Bioinformatics Institute
Co-Lead PI:
A/Prof Wee Hwee Lin, National University of Singapore
Co-Lead PI:
Dr Nicolas Bertin, A*STAR Genome Institute of Singapore |
1. Evaluate the occurrence of known drug-gene interactions based on HER data and its impact on efficacy and toxicity.
2. Explore genotype-drug response associations using SG100K and linked HER datasets augmented by a dedicated pipeline for haplotyping highly polymorphic drug metabolising enzyme CYP2D6.
3. Develop a pharmacokinetics-informed framework for evaluating and ranking both known and novel drug-gene sets for clinical action to make dose recommendations. |
| 9 |
Genetic Variants Contributing to Clonal Haematopoiesis across Diverse Asian Genomes |
Lead PI:
Prof Ong Sin Tiong, Duke-NUS Medical School
Co-Lead PI:
Prof Ashok Vekitaraman, National University of Singapore
Co-Lead PI:
Prof Chng Wee Joo, National University of Singapore
Co-Lead PI:
Prof John Chambers, Lee Kong Chian School of Medicine
Co-lead PI:
Dr Nicolas Bertin, A*STAR Genome Institute of Singapore |
1. Determine age-related incidence of clonal haematopoiesis (CH) among our three major ancestry groups.
2. Correlate CH status with clinical metadata, measures of ageing and disease-incidence, and disease-related variables including biomarkers.
3. Discover novel genetic associations with CH.
4. Integrate functional genomics for novel Asian CH driver mutation discovery and validation.
5. Correlate CH status with cell clusters and gene expression signatures in the AIDA scRNA-seq dataset. |
| 10 |
Computation of Genome-Wide LD Scores and Matrices from the SG100K resource |
Lead PI:
Li Jingmei, A*STAR Genome Institute of Singapore
Co-Lead PI:
Rajkumar s/o Dorajoo, A*STAR Genome Institute of Singapore
Co-Lead PI:
Khor Chiea Chuen, A*STAR Genome Institute of Singapore |
1. Compute in-sample dosage-based LD matrices and scores for each of the three major ancestry groups in SG100K, taking reference from similar work performed by the Pan-UK Biobank.
2. Use LD score regression analysis to estimate heritabilities.
3. Use fine-mapping analysis to identify causal variants of well-powered complex traits.
|
| 11 |
Chronic Liver Disease is a Significant Risk Factor for Adverse Cardiometabolic Outcomes |
Lead PI:
Mark Chan, National University Hospital, Cardiology
Co-Lead PI:
Dr Nicholas Chew, National University Hospital, Cardiology |
1. Investigate associations between established non-invasive chronic liver disease (CLD) biomarkers and cardiometabolic outcomes.
2. Evaluate how these associations relate to major adverse cardiac events.
3. Examine whether these associations with CLD are independent from associated metabolic disease. |
| 12 |
Nonlinear Methods for Genomic Association Analysis of Eye Diseases |
Lead PI:
Liu Dianbo, National University of Singapore, Ophthalmology
Co-Lead PI:
A/P Wee Hwee Lin, National University of Singapore
Co-Lead PI:
Dr Nicolas Bertin, A*STAR Genome Institute of Singapore |
1. Identify non-linear genetic associations contributing to the susceptibility and manifestation of diverse eye diseases.
2. Explore epistatic interactions and allelic heterogeneity within the genomic data to unravel the complex relationships between multiple genetic variants.
3. Investigate how non-linear responses to environmental variables contribute to the phenotypic variation, with a focus on refining our understanding of gene-environment interactions in the context of ocular health.
4. Investigate and interpret the biological relevance of non-linear genetic associations. Aim to gain insights into the underlying mechanisms linking identified genetic variants to specific eye diseases and contribute to a more comprehensive understanding of the biology involved.
5. Evaluate the public health implications of the identified non-linear genetic associations, considering their potential impact on disease prevention, intervention, and personalised treatment strategies. Assess the translational potential of the research findings to inform clinical practice, public health policies, and contribute to advancements in precision medicine for ocular health. |
| 13 |
Advancing the Understanding of Biological Mechanisms Influencing Chronic Inflammatory Skin Diseases |
Lead PI:
Yew Yik Weng, National Skin Centre
Co-Lead PI:
Steven Thng Tien Guan, National Skin Centre
Co-Lead PI:
Marie Loh, Lee Kong Chian School of Medicine |
1. Identify host genetic factors associated with chronic inflammatory skin diseases, specifically AD, psoriasis and chronic urticaria using genome wide association and rare variant analyses among SG100K study participants, taking advantage of whole genome sequence data and linkage to disease information from national electronic health records (NEHR).
2. Examine the relationship between genetic variants and polygenic risk scores (PRS) associated with skin phenotypes and real-world health data for skin diseases (including diagnosis, onset, severity and treatment outcomes) to identify genetic predictors of disease trajectories, complications and co-morbidities and treatment outcomes using the TRUST dataset. |
| 14 |
Mood and Diet in Patients with Irritable Bowel Syndrome (IBS) in Singapore |
Lead PI:
Theresia Mina, Lee Kong Chian School of Medicine
Co-Lead PI:
John Chambers, Lee Kong Chian School of Medicine
Co-Lead PI:
Sim Xueling, National University of Singapore |
1. Evaluate the dietary pattern and characteristics of patients with IBS in Singapore.
2. Identify patterns of mood disorders in patients with IBS in Singapore.
3. Identify genetic variants associated with IBS in the multi-ethnic Singaporean Population. Explore and characterise common genetic polymorphisms IBS within the diverse Singaporean population. This comprehensive genetic investigation aims to unravel the unique genetic landscape of IBS, considering the multi-ethnic composition of the population.
4. Investigate the effects of lifestyle factors on IBS Risk and progression. Systematically examine the impact of lifestyle factors, including diet, physical activity, sleep, stress, and mental health, on the risk and progression of IBS. This multifaceted investigation seeks to discern the intricate relationships between lifestyle choices and IBS, contributing valuable insights for developing targeted interventions and improving patient outcomes.
5. Elucidate potential interactions between genetic and environmental influences on IBS. Uncover and elucidate potential interactions between genetic factors and environmental influences in the development and progression of IBS. This integrated approach aims to provide a nuanced understanding of how genetic predispositions and environmental exposures collaboratively contribute to the manifestation of IBS, offering a foundation for personalised and precision medicine strategies. |
| 15 |
The Contribution of Genetics to Dietary Habit and Its Relation to Adiposity and Cardiometabolic Diseases in Multiethnic Asian Population |
Lead PI:
Theresia Mina, Lee Kong Chian School of Medicine
Co-Lead PI:
John Chambers, Lee Kong Chian School of Medicine
Co-Lead PI:
Sim Xueling, National University of Singapore |
1. Conduct phenotypic associations of macronutrients with visceral adiposity as primary outcome, and the visceral fat linked cardiometabolic traits and diseases as secondary outcomes in multiethnic Asian population.
2. Perform GWAS of macronutrients in multiethnic Asian population using the SG100K dataset and a GWAS meta-analysis using the UK Biobank macronutrient intake data.
3. Perform functional annotation of significant loci and estimate the genetic correlations of macronutrient intake with visceral fat linked cardiometabolic traits and diseases as secondary outcomes.
4. Conduct one-sample and two-sample Mendelian Randomisation (MR) with macronutrient intake as exposure variables and visceral adiposity as outcome variables, with relevant sensitivity analyses. |
| 16 |
A Structural Variation Catalogue Across Three Ancestrally Diverse Singapore Populations |
Lead PI:
Joanna Tan Hui Juan, A*STAR Genome Institute of Singapore
Co-Lead PI:
Shyam Prabhakar, A*STAR Genome Institute of Singapore
Co-Lead PI:
Patrick Tan Boon Ooi, A*STAR Genome Institute of Singapore |
1. Build a catalogue of SVs (deletions, insertions, duplications, inversions, translocations, and tandem repeats) from the PRECISE-SG100K dataset.
2. Investigate the identified SVs to uncover population-specific trends.
3. Examine the functional consequences of SVs in different genomic regions as well as predict the impact of SVs in medically relevant genes.
4. Identify SVs that are associated with phenotypic traits within the PRECISE-SG100K dataset.
5. Elucidate the impact of SVs on variation in cell type-specific gene expression (SV-eQTLs) and validate SVs through copy number variation inferences from scRNA-seq data. |
| 17 |
Genome-wide Association Study and Population-based Evaluation of Patients with Diabetic Foot Ulcers |
Lead PI:
Joseph Lo, Woodlands Health
Co-Lead PI:
Kavita Venkataraman, National University of Singapore
Co-Lead PI:
Yusuf Ali, Lee Kong Chian School of Medicine |
1. Identify genetic loci associated with diabetic foot ulcers in Asian patients with diabetes mellitus.
2. Identify differences in genetic loci within Malay/Indian ethnicities.
3. Identify genetic loci associated with diabetic peripheral neuropathy.
4. Identify potential gene-environment interactions (for example, tobacco smoking) associated with the risk of diabetic foot ulcers.
5. Identify socioeconomic and other risk factors associated with diabetic foot ulcers.
6. Identify correlations between macro-angiopathy, micro-vascular reactivity nephropathy and retinopathy and diabetic foot ulcers.
7. Develop multi-polygenic risk score for developing diabetic foot ulcers. |
| 18 |
The SG100K Cancer and Aging Workgroup: Developing Risk Models for Cancer Associations |
Lead PI:
Joanne Ngeow, Lee Kong Chian School of Medicine
Co-Lead PI:
Rajkumar s/o Dorajoo, A*STAR Genome Institute of Singapore
Co-Lead PI: Neerja Karnani, A*STAR Genome Institute of Singapore |
1. Generate common variant polygenic risk scores for common cancers (breast, colorectal, liver, lung, and prostate cancers) and identify potential functional rare coding genetic mutations in strong cancer related genes in the SG100K dataset.
2. Generate additional age-related biomarkers (i.e as telomere length estimates) related to cancer risk from the SG100K WGS data and identify genetic predispositions associated with these biomarkers.
3. Linkage of genetic datasets with TRUST to derive clinical data and determine common cancer status (breast, colorectal, liver, lung, and prostate cancers). |
| 19 |
Genetic Susceptibility of Age-related Hearing Loss |
Lead PI:
Liu Jianjun, A*STAR Genome Institute of Singapore
Co-Lead PI:
Nicolas Bertin, A*STAR Genome Institute of Singapore
Co-Lead PI:
Lim Weng Khong, Duke-NUS Medical School |
1. Generate a SG100K genome wide TR variation catalogue and characterisation their respective prevalence in Asian populations.
2. Characterise the contributions of TR variations to the aetiology of complex neurological and neurocognitive disorders. |
| 20 |
Evaluating the Promise and Perils of Glucagon-like Peptide-1 (GLP-1) Receptor Agonist: A Deep Dive into Therapeutic Potentials and Adverse Effects |
Lead PI:
Huang Jian, A*STAR Singapore Institute for Clinical Sciences and Bioinformatics Institute
Co-Lead PI:
Dennis Wan, A*STAR Singapore Institute for Clinical Sciences and Bioinformatics Institute |
1. Investigate the effects of GLP-1 receptor agonist on various domains of health outcomes using an observational study design.
2. Identify the non-synonymous single nucleotide polymorphisms (SNPs) of GLP-1 receptor agonist prescription and predict nsSNPs responsible for the differential response to GLP-1 receptor agonist.
3. Provide genetic evidence for the therapeutic potentials and adverse effects of GLP-1 receptor agonists by adopting a drug target Mendelian randomisation design. |
| 21 |
Unravelling the Pathogenesis of Inflammatory Bowel Disease and Associated Immune-mediated Disorders in the Singaporean Population |
Lead PI:
Sunny Wong, Lee Kong Chian School of Medicine
Co-Lead PI:
Anselm Mak, National University of Singapore
Co-Lead PI:
Bernett Lee, Lee Kong Chian School of Medicine |
1. Identify Genetic Variants Associated with IBD and Related Immune-Mediated Disorders in the Multi-Ethnic Singaporean Population. Explore and characterise both common and rare genetic variants linked to IBD, and spondyloarthropathies, uveitis, Behcet's disease, psoriasis, and other related immune-mediated conditions within the diverse Singaporean population. This comprehensive genetic investigation aims to unravel the unique genetic landscape of this disease cluster, considering the multi-ethnic composition of the population.
2. Investigate the Effects of Lifestyle Factors on IBD and Associated Diseases Risk and Progression. Systematically examine the impact of lifestyle factors, including diet, physical activity, sleep, stress, and mental health, on the risk and progression of IBD and associated immune-mediated diseases. This multifaceted investigation seeks to discern the intricate relationships between lifestyle choices and disease outcomes, contributing valuable insights for developing targeted interventions and improving patient wellbeing.
3. Delineate shared and distinct mechanisms underlying IBD, spondyloarthropathy, uveitis, psoriasis, Behcet's and other related conditions. Elucidate the shared and unique genetic and biological pathways driving IBD, spondyloarthropathy, uveitis, psoriasis, Behcet's disease, and other related conditions. This will provide critical insights into disease mechanisms to guide targeted prevention and treatment strategies for this nexus of related diseases.
4. Elucidate Potential Interactions Between Genetic and Environmental Influences on This Disease Cluster. Uncover and elucidate potential interactions between genetic factors and environmental influences in the development and progression of IBD and related conditions. This integrated approach aims to provide a nuanced understanding of how genetic predispositions and environmental exposures collaboratively contribute to the manifestation of this disease cluster, offering a foundation for personalised and precision medicine strategies. |
| 22 |
Genetics of Allergic Diseases and Acne Vulgaris in the Singapore Population: Validation and Functional Characterisation of Candidates |
Lead PI:
Chew Fook Tim, National University of Singapore |
1. Validate disease-associated genetic polymorphisms and environmental factors that were previously identified and functionally characterised in the SMCGES cohort, using the PRECISE-SG100K dataset.
2. Investigate the associations of previously identified asthma/AR/AD/acne candidate genes with the other clinical parameters relevant to the disease of interest. For instance, whether the allelic/genotypic differences of genetic variants would affect the treatment response, lung function (spirometry), skin condition (sites of flexural dermatitis and psoriasis, etc.) in complex disease.
3. Reproduce and validate the observed associations between specific dietary habits and allergic diseases, using a more extensive and culturally relevant FFQ.
4. Explore causal relationship between dietary habits and allergic diseases by understanding how changes in dietary patterns influence the development and progression of allergic diseases. |
| 23 |
Modulation of Cholesterol 7α-hydroxylase (CYP7A1) Activity as an Orthogonal Approach to the Management of Hypercholesterolemia |
Lead PI:
Ho Han Kiat, National University of Singapore |
1. Determine the prevalence of CYP7A1 single nucleotide polymorphisms (SNP) locally, on extrapolation, to the region that presents similar ethnicities.
2. Ascertain the relationship between CYP7A1 SNPs and hypercholesterolemia in our local population.
3. Identify the target population most likely to benefit from targeting CYP7A1 as an orthogonal approach to cholesterol control.
4. Study the impact of non-genetic extrinsic factors, such as comorbidities and comedications, on the genotypes to discern the possibility of phenoconversion. |
| 25 |
Asian-specific Parkinson's Disease-linked Genetic Risk Variants and Systemic Clinical Outcomes |
Lead PI:
Tan Eng King, National Neuroscience Institute
Co-Lead PI:
Thomas Welton, Duke-NUS Medical School
Co-Lead PI:
Chan Ling Ling, Duke-NUS Medical School |
Analyse the genetic information and clinical records to determine if those at risk or with prodromal Parkinson's Disease can be further stratified for intervention or monitoring of subclinical disease, and also to better understand the impact of Parkinson's Disease risk gene variants on the different systems and organs |
| 26 |
Physiological, Environmental and Genetic Determinants of Heterogeneity in Singaporeans’ Health Span |
Lead PI:
Neerja Karnani, A*STAR Bioinformatics Institute
Co-Lead PI:
Joanne Ngeow, Lee Kong Chian School of Medicine
Co-Lead PI:
Brian Kennedy, National University of Singapore
Co-Lead PI:
Rajkumar s/o Dorajoo, A*STAR Genome Institute of Singapore |
1. Investigate the stressors associated with aging and identify the factors contributing to resilience.
2. Investigate gender-specific variations in aging stressors and assess the influence of reproductive aging.
3. Examine the effects of Asian ethnicity on the aging process and healthspan.
4. Evaluate the pharmacogenomic effects of medications on lifespan and overall health during aging. |