Background: Modern medicine is rapidly moving towards a data-driven paradigm based on comprehensive multimodal health assessments. Integrated analysis of data from different modalities has the potential of uncovering novel biomarkers and disease signatures.
Methods: We collected 1385 data features from diverse modalities, including metabolome, microbiome, genetics, and advanced imaging, from 1253 individuals and from a longitudinal validation cohort of 1083 individuals.
Obesity is a heterogeneous phenotype that is crudely measured by body mass index (BMI). There is a need for a more precise yet portable method of phenotyping and categorizing risk in large numbers of people with obesity to advance clinical care and drug development. Here, we used non-targeted metabolomics and whole-genome sequencing to identify metabolic and genetic signatures of obesity.
View Article and Find Full Text PDFPurpose: To characterize and compare the prevalence of soft contact lens-related (SCL) dryness symptoms in large populations of SCL wearers in North America (NAm) and the United Kingdom (UK).
Methods: SCL wearers from NAm (n = 1443) and UK (n = 932) sites completed self-administered questionnaires on SCL symptoms and wearing experiences. A categorization for contact lens-related dry eye (CL-DE) was applied that combined Contact Lens Dry Eye Questionnaire (CLDEQ) items on dryness frequency and intensity at the end of the day (CL-DE+ = constantly/frequently/sometimes plus intensity = 3-5, and CL-DE- = never/rarely plus intensity = 0-1, Marginal = all other ratings).