National Precision Medicine (NPM) programme

Building a National Precision Medicine (NPM) programme – SG10K_Health

Background
The SG10K_Health project is a multi-institutional initiative developing an ‘all-of-Singapore' coordinated approach to precision medicine (PM). PM is a fast emerging field that seeks to improve treatment and prevent disease by considering individual and population genetic variation in genes, environment and lifestyle patterns. Through PM, patients may receive more accurate diagnosis, customised treatments achieving maximal benefit while minimising side effects, and reduced health care costs by avoiding ineffective treatments. At present, the Asian population is severely under-represented in the public genotypic databases. The current lack of large-scale control databases of Asian-specific genetic variation linked to clinical phenotypes is a significant barrier to the conduct of PM in Asia, to avoid mis-diagnosis and overtreatment due to the mistaken identification of pathogenic variants. The Singaporean population consists of three major ethnic groups, Chinese, Malay, and Indian, which together represent over 80% of the genetic variation in Asia. The presence of these three major ethnic groups in a single country thus offers a unique opportunity for Singapore, despite its small size, to contribute to global efforts in PM, complementing other large-scale efforts such as All of US and Genomics England.

Objectives
The SG10K_Health project aims to empower biomedical and genetic studies of Singapore and Asian-centric diseases by: 1) building local infrastructure and deep capabilities to generate, analyse and store human genetic data at population scale, in a safe, secure and rapid manner, 2) generating a diverse and rich control dataset of Asian populations for genetic association study of diseases, and 3) developing advanced analytical tools for genetic variants interpretation to derive disease risk predictions and identify clinically actionable variants. Notably, statistical estimates indicate that a genomic data set of 10,000 individuals will be sufficient to capture essentially all common alleles (ie more than 1% allele frequency) in our Singapore population. Currently, the SG10K_Health data is linked to research traits (e.g., height, weight, blood pressure) and in the future will be linked to clinical records, subject to participant consent.

Genomic Web Services
We have established various web services to enable users to query the SG10K_Health dataset, including allele frequencies, protein-drug interactions, imputation and polygenic risk scores.

  • CHORUS Variant Browser
  • CHORUS Beacon
  • SNPdrug3D
  • Imputation
  • Polygenic Risk Score

The web services can be access through our SG10K_Health web portal at https://npm.a-star.edu.sg

Data Access
The National Precision Medicine Data Access Committee (NPM DAC) has been established to oversee access to the SG10K_Health datasets to ensure:

  • Data is used appropriately according to NPM terms and conditions, including adherence to informed consent forms and ethical approvals for the data in question.
  • Data users are qualified investigators embedded within a recognised research-intensive organisation.
Interested applicatnts can visit https://npm.a-star.edu.sg/help to read through the data access policies and data access forms.

For more information on the list of approved studies, please visit https://npm.a-star.edu.sg/help

 

Publications & Press Release
Cell Magazine

Early research on the first 5000 (“SG10K_Pilot”) subjects analyzed by whole genome sequencing (WGS) in the Singaporean population was published in the prestigious scientific journal Cell (2019). Our work was recognized by being awarded the cover art design for the October 17th issue of the journal https://doi.org/10.1016/j.cell.2019.09.019).

    Key highlights:
  • Discovery of 52 million novel variants by 13.7× WGS of 4,810 Singaporeans.
  • Insights into population structure and evolutionary history of Asians.
  • Identification of 20 loci under selection that are enriched for GWAS (Genome-wide Association Studies) signals.
  • Substantial improvement of imputation in diverse Asian and Oceanian populations).

Programme investigators
Lead investigators: Prof Patrick Tan (GIS) and Prof Tai E Shyong (NUHs)
Co-investigators: Prof John Chambers (LKCMedicine), Dr Neerja Karnani (SICS), Prof Liu Jian Jun (GIS), Dr Shyam Prabhakar (GIS), Dr Birgit Eisenhaber (BII), Dr Chandra Verma (BII), Dr Sebastian Maurer-Stroh (BII), Dr Rick Goh (IHPC), Dr Sonia Davila (Duke-NUS), Dr Pavitra Krishnaswamy (I2R), Dr Sim Xueling (NUS), Dr Marie Loh (LKCMedicine), Prof Cheng Ching-Yu (SERI) and Dr Leong Khai Pang (TTSH).

Contact Us
For more information on the SG10K_Health program and web services, please reach out to us at contact_npco@gis.a-star.edu.sg

Infographics