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Increasing the Productivity of Discovery Research

The volume and complexity of data arising from the genomics revolution are driving increasing demand for statisticians to work with scientists and doctors to unravel the mysteries of complex multifactorial diseases. SAS/Genetics software is designed specifically for genetics research. It enables researchers to examine the relationship between multiple markers and find associations between markers and traits using case-control or family data.

Engaging in both basic and clinical research of innovation and high-impact, the Department of Pediatrics and Adolescent Medicine at the University of Hong Kong has used statistical genetics software to analyze genetic marker data and their association with diseases.

Identifying genetic causes for disease
SAS/Genetics software was used for conducting haplotype analyses. The researchers ran the haplotype procedure, which uses the expectation-maximization algorithm to generate maximum-likelihood estimates of haplotype frequencies. This haplotype procedure was performed for the patients, for the control subjects and for the patients and control subjects combined, in order to test the overall difference in haplotype frequency among these target groups.

The department is currently investigating the genetic factors contributing to the development of infectious diseases and autoimmune diseases that are prevalent in the Hong Kong Chinese population. These diseases are caused by many risk factors interacting together. The risk factors can be infectious agents, environmental and genetic factors. The focus of the department’s research is on studying the genetic susceptibility of the Hong Kong Chinese to these prevalent diseases.

One of the most recent published studies in The Journal of Infectious Diseases is about finding the associations between host genetic factors and tuberculosis (TB). The research is a population-based control study which involved 516 Hong Kong Chinese patients with TB and 514 healthy control subjects. Another research paper is about identifying genetic factors causing systemic lupus erythematosus (SLE), a complex multifactorial autoimmune disease that can have severe disease impact on the patients.

The future of public health and disease prevention
“The Department of Pediatrics and Adolescent Medicine at the University of Hong Kong has been using the SAS platform for statistical analyses. We trust that SAS/Genetics software can provide the statisticians and researchers with greater flexibility and give output from numerous procedures interpreted simultaneously,” said Dawn Kung, Regional Director, SAS Greater China.

Dr Alan K. S. Chiang, Assistant Professor, Department of Pediatrics and Adolescent Medicine, Faculty of Medicine, The University of Hong Kong has commented that they can use some existing genetics software that were developed by individual scientists but those software were mostly in DOS platform and had limitations in the sample size number. “We are looking for a flexible statistical platform to analyze the genetic data of a large number of individuals.” said Dr Chiang. He estimated that analysis of the genetic data by a familiar and efficient statistical software can effect time saving by two to three fold.

“These types of basic genomic data of infectious diseases and autoimmune diseases will accumulate and form our database. At this moment, the findings cannot be applied directly to the patients, but will build the foundation to foster further research and testing. As the methodologies and analyses are getting more mature and accurate, these data may be important for the development of novel public health preventive and treatment measures in the future,” concluded Dr Chiang.

Copyright © SAS Institute Inc. All Rights Reserved.

Dr. Alan K. S. Chiang 
Assistant Professor Department of Pediatrics and Adolescent Medicine, Faculty of Medicine

University of Hong Kong

Challenge:
Investigate the genetic factors contributing to the development of infectious and autoimmune diseases prevalent in the Hong Kong Chinese population.
Solution:
Doctors and scientists analyze genetic data in half the time with familiar and efficient statistical processes.

These data may be important for the development of novel public health prevention and treatment measures in the future.

Dr. Alan K. S. Chiang

Assistant Professor, Department of Pediatrics and Adolescent Medicine, University of Hong Kong

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