Ming-Wei Lin

Biomarker and Health with Academic and Enterprise Viewpoint

Shin-Hua Lin ¹, Wendy Yi-Ying Wu¹, Li-Shang Chen², Amy Ming-Feng Yen², Tzeng-Ying Liu³, Hsu-Hsi Chen⁴, and Ming-Wei Lin^1,5

¹Institute of Public Health, National Yang-Ming University, Taipei, Taiwan

²School of Oral Hygiene, College of Oral Medicine, Taipei Medical University, Taipei, Taiwan

³Lienchiang County Government, Matsu, Taiwan

⁴Institute of Epidemiology and Preventative Medicine, National Taiwan University, Taipei, Taiwan

⁵Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan

With the availability of multi-omics data and information, offers health professionals a great opportunity to develop precision medicine by taking an integrated approach to consider the genetic makeup of an individual as well as the impact of environmental exposures and lifestyle. In this presentation, we tried to demonstrate how we applied biomarker to predict health outcomes in the Matsu cohort from both academic and enterprise points of view.

Since 2002, we have established a population-based cohort by recruiting subjects participating in the Matsu Community-Based Integrated Screening (MA-CIS) project. This Matsu cohort included more than 4000 Chinese subjects with the age over 30. Among them, more than 3000 subjects have DNA and/or plasma samples available. With this cohort, we conducted several studies focused on biomarkers and health outcomes. Here we briefly described two studies as examples to demonstrate how we could apply biomarker data to predict the health outcomes in the era of precision medicine. The first one we used the KLOTHO gene polymorphisms to find out if these genetic markers can be of use as biomarkers to predict their association with hypertension and the variations on blood pressure in Matsu. The second study we applied a Mendelian randomization design to assess whether adiposity causally affects known cardiovascular risk factors and bone mineral density by using three FTO genetic variants as instrumental variables.