Webinar on risk disease management of preterm infants

Multi-omics for risk stratification and disease management of preterm infants Webinar wiith Wen Zhong.

Preterm birth is the leading cause of neonatal mortality and morbidity worldwide. Although recent improvements in neonatal intensive care have increased the survival rates of premature infants, increasing attention is being paid to risks of short and long-term morbidities, including development delays, respiratory problems, hearing and vision impairments, neurodevelopmental disorders. The aetiology behind preterm morbidities is multifactorial and poorly understood. It is not known which infants are at risk of developing which disease. Thus, there is an urgent need to develop individualized prediction tool to accurately estimate morbidity risks of the preterm infants. In our research,  we develop a molecular developmental map for preterm infants with different gestational age to monitor the health and disease of the vulnerable babies. 

Wen Zhong, DDLS fellow at SciLifeLab and Linköping University with a research focus on integrative multi-omics in precision medicine and diagnostics. The rise of high throughput molecular technologies has shed light on the development of next-generation molecular diagnostics and biomarkers for patient stratifications in the precision medicine era. There is an urgent need to develop new systematic tools to combine multi-omics data and link genotype to phenotype to expand our knowledge of complex traits of human diseases. Our research group mainly focuses on the integration of multi-omics, the interplay between genetics and phenotypes, and the development of data-driven strategies/tools for precision medicine. The aim is to investigate the molecular biomarkers for the estimation of disease risks, early diagnosis of disease, stratification of drug treatment response, disease progression monitoring and the stratification of patients. To enable these projects, we develop and optimize trustworthy AI tools to facilitate the utilization of data-driven systems medicine and inform precision medicine-based decision support. 

Participate on Zoom https://umu.zoom.us/j/65664475052