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
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
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.
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Dr. Alan K. S. Chiang
Assistant Professor Department of Pediatrics and Adolescent Medicine, Faculty of Medicine
University of Hong Kong
Investigate the genetic factors contributing to the development of infectious and autoimmune diseases prevalent in the Hong Kong Chinese population.
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