Aging is a complex biological process characterized by a gradual decline in physiological functions, which increases susceptibility to diseases and death. This process is influenced by a myriad of genetic, environmental, and lifestyle factors. Our research on aging and aging-related diseases like AD and PD is utilizing multi-omics and wearable technology to gain a comprehensive understanding of the aging process. The ultimate goal of our research is to develop predictive models for aging and aging-related diseases. These models aim to integrate multi-omics data with information from wearable devices, along with clinical and demographic information. Machine learning and artificial intelligence algorithms are employed to analyze this vast and complex dataset, with the objective of identifying patterns and predictive biomarkers. In summary, our lab’s research represents a cutting-edge, interdisciplinary approach to studying aging, leveraging the power of multi-omics and wearable technology to build comprehensive predictive models for aging and its related diseases. This research not only deepens our understanding of the biological processes of aging but also holds promise for improving health outcomes in the aging population.

Maternal and Child Health (MCH) is a critical public health domain focused on the health and well-being of mothers and children. Our lab’s research in Maternal and Child Health, particularly concerning preterm birth, is employing multi-omics and wearable technology to deepen understanding and improve outcomes. Our lab is likely integrating data from these multi-omics analyses with information collected from wearable devices to create a comprehensive picture of maternal and fetal health. This integrated approach can identify patterns and risk factors associated with preterm birth and other pregnancy-related complications. Advanced data analysis techniques, including machine learning and AI, are used to analyze these complex datasets, aiming to develop predictive models for adverse pregnancy outcomes.

Our lab’s research focuses on integrating multi-omics and wearable data to advance the field of precision medicine, with a special emphasis on understanding the intricate interplay between the microbiome and metabolome. Our research likely involves analyzing how the microbiome affects the metabolome and vice versa. For instance, certain metabolites produced by the microbiome can impact human metabolic pathways, while changes in the host’s metabolism can alter the microbiome composition. Understanding this bidirectional relationship is crucial for developing targeted therapeutic strategies. The ultimate goal of our lab’s research is to use the integrated data from multi-omics and wearables for precision medicine. By understanding the complex interactions between the microbiome and metabolome, and how they relate to individual physiological states, our aim to develop personalized healthcare strategies. This could involve tailored dietary recommendations, customized probiotic or prebiotic therapies, or specific drug treatments based on an individual’s unique microbiome-metabolome profile.