PROJECT SUMMARY In this project we aim to validate tools that researchers (including other All of Us researchers) can utilize to assess and follow the severity of metabolic syndrome (MetS) among study participants, and we will also evaluate characteristics of MetS among minoritized groups for use in personalized medicine in clinical practice. MetS is a cluster of cardiovascular disease (CVD) risk factors that occur together more frequently than would be expected by chance, as though they are driven by a common underlying process that is related to risk for future Type 2 diabetes (T2D) and CVD. We previously formulated MetS severity z-scores (MetS-Z) specific to sex and to three different race/ethnicities (individuals who are non-Hispanic white, non-Hispanic black or Hispanic), but we did not previously have statistical power to assess for—and if necessary derive— unique MetS-Z scores for other racial/ethnic and sexual/gender groups. In particular Asian American individuals have been noted to manifest insulin resistance at a lower BMI (suggesting unique manifestation of MetS), and many sexual/gender sub-groups have been noted to have high levels of chronic stress from discrimination, which could also affect MetS severity. We propose to use confirmatory factor analysis to assess MetS severity among multiple minoritized race/ethnicity and sexual/gender groups in All of Us. If the loading factors for the individual MetS components differ for a specific population sub-group, we will derive a unique MetS severity z-score for that group (e.g. among individuals who are Asian American); if the MetS loading factors are similar to other groups, we will utilize the corresponding MetS-Z score for that group’s set of loading factors. We will then assess how these MetS-Z scores relate to social determinants of health (SDOH), including perceived discrimination and depressive symptoms— the physiological stress from which can exacerbate MetS. This may help in highlighting the importance of assessing and considering SDOH in clinical care. Finally, we will evaluate how baseline MetS-Z is related to longitudinal risk for T2D and CVD, including assessing for whether this differs by racial/ethnic and sexual gender sub-groups. Our overall goal is to provide support for personalized medicine considerations for all individuals, including minoritized groups. These data will help validate specific MetS-Z scores that can be used to assess relationships with metabolic health for other topics of interest to multiple investigator teams in All of Us.