Implementation of a Scalable Online Weight Management Programme in Clinical Settings: Protocol for the PROPS 2.0 Programme (Partnerships for Reducing Overweight and Obesity with Patient-Centered Strategies 2.0).

INTRODUCTION: There is an urgent need for scalable strategies for treating overweight and obesity in clinical settings. PROPS 2.0 (Partnerships for Reducing Overweight and Obesity with Patient-Centered Strategies 2.0) aims to adapt and implement the combined intervention from the PROPS Study at scale, in a diverse cross-section of patients and providers. METHODS AND ANALYSIS: We are implementing PROPS 2.0 across a variety of clinics at Brigham and Women's Hospital, targeting enrolment of 5000 patients. Providers can refer patients or patients can self-refer. Eligible patients must be ≥20 years old and have a body mass index (BMI) of ≥30 kg/m2 or a BMI of 25-29.9 kg/m2 plus another cardiovascular risk factor or obesity-related condition. After enrolment, patients register for the RestoreHealth online programme/app (HealthFleet Inc.) and participate for 12 months. Patients can engage with the programme and receive personalized feedback from a coach. Patient navigators help to enrol patients, enter updates in the electronic health record, and refer patients to additional resources. The RE-AIM (Reach, Effectiveness, Adoption, Implementation, and Maintenance) framework is guiding the evaluation. ETHICS AND DISSEMINATION: The Mass General Brigham Human Research Committee approved this protocol. An implementation guide will be created and disseminated, to help other sites adopt the intervention in the future. TRIAL REGISTRATION NUMBER: NCT0555925.

Associations between neighborhood socioeconomic deprivation, IFNγ, and high-density lipoprotein particle size: Data from the Washington, D.C. cardiovascular health and needs assessment.

INTRODUCTION: Neighborhood socioeconomic deprivation is associated with increased cardiovascular risk factors, including inflammation. Inflammation plays an important role in modifying the cardioprotective function of high-density lipoprotein (HDL). Moreover, recent studies suggest that very high HDL is associated with adverse cardiovascular disease (CVD) outcomes. Thus, we sought to explore the relationships between neighborhood socioeconomic deprivation as a marker of chronic stress, inflammation, proprotein convertase subtilisin/kexin type 9 (PCSK9) (a core component of the HDL proteome), HDL characterisitcs, and biological aging as a predictor of CVD and all-cause mortality. METHODS: Sixty African American subjects were recruited to the NIH Clinical Center as part of a community-based participatory research-designed observational study. Neighborhood deprivation index (NDI), a marker of neighborhood socioeconomic deprivation, was measured using US Census data. HDL characteristics (cholesterol, particle number, size, subspecies) were determined from NMR lipoprotein profiling, and plasma cytokines (IL-1ß, IL-6, IL-8, TNFα, IFNγ) were measured using an ELISA-based multiplex technique. Epigenetic clock biomarkers of aging were measured using DNA methylation data obtained from participants' buffy coat samples. We used linear regression modeling adjusted for atherosclerotic cardiovascular disease (ASCVD) risk score, body mass index (BMI), and lipid-lowering medication use to investigate relationships of interest. RESULTS: NDI directly associated with large HDL particle count (H7P) and IFNγ and trended toward significance with HDL-C and PCSK9. IFNγ and PCSK9 then directly associated with H7P. H7P also directly associated with higher DNA methylation phenotypic age (PhenoAge). CONCLUSION: We highlight associations between neighborhood socioeconomic deprivation, IFNγ, PCSK9, HDL subspecies, and epigenetic biomarkers of aging. Taken together, our findings suggest indirect pathways linking neighborhood deprivation-related stress and inflammation to HDL and immune epigenetic changes. Moreover, these results add to recent work showing the pathogenicity of high HDL levels and underscore the need to understand how chronic stress-related inflammation and lipoprotein subspecies relate to CVD risk across diverse populations.