Faculty Bibliography

AIMS/OBJECTIVE:To characterize changes in continuous glucose monitoring (CGM)-derived time in tight range (TIR) measures in individuals with prediabetes or non-insulin-treated type 2 diabetes undergoing dietary weight loss intervention and to quantify the association between weight loss and TIR improvement. METHODS:) were analysed. The association between weight change and TIR change adjusted for demographic and clinical covariates was computed using linear regression. RESULTS:. There were no associations between weight loss and change in any overnight TIR measure. CONCLUSION/CONCLUSIONS:in individuals with prediabetes and non-insulin-treated type 2 diabetes undergoing dietary intervention. The daytime time in tight range measures can complement traditional markers like HbA1c, offering a more comprehensive view of glycaemic variations during dietary weight loss programmes for individuals with prediabetes and type 2 diabetes not on insulin.

PURPOSE/OBJECTIVE:We developed a comprehensive sleeve gastrectomy (SG) weight loss study cohort and biorepository to uncover mechanisms, biomarkers and predictive factors of weight loss, weight maintenance and amelioration of obesity-related comorbidities. For this purpose, we collected psychosocial, anthropometric, clinical data and a variety of samples pre-surgery, intraoperatively and 1.5, 3, 12 and 24 months post-surgery. For longer-term assessment, the collection of psychosocial and anthropometric data was extended to 10 years. Here, we present in-depth characterisation of the cohort and detailed overview of study procedures as a foundation for future analyses. PARTICIPANTS/METHODS:We consented 647 participants between June 2017 and March 2020 from two bariatric surgery clinics in New York City-one major urban hospital and one private hospital. Of 355 participants who provided baseline data, 300 underwent SG. Of these, 79% are females with an average age of 38 years, 68% are Hispanic, 20% are non-Hispanic Black and 11% are non-Hispanic White. FINDINGS TO DATE/RESULTS:We collected intraoperative adipose and stomach tissues from 282 patients and biosamples (blood, urine, saliva, stool) from 245 patients at 1.5 months, 238 at 3 month, 218 at 12 months and 180 at 24 months post-surgery. We are currently collecting anthropometric and psychosocial data annually until 10 years post-surgery. Data analysis is currently underway. FUTURE PLANS/UNASSIGNED:Our future research will explore the variability in weight loss outcomes observed in our cohort, particularly among Black and Hispanic patients in comparison to their White counterparts. We will identify social determinants of health, metabolic factors and other variables that may predict weight loss success, weight maintenance and remission of obesity-related comorbidities. Additionally, we plan to leverage our biorepository for collaborative research studies. We will complete long-term follow-up data by December 2031. We plan to apply for funding to expand biosample collection through year 10 to provide insights into the mechanisms of long-term weight maintenance.

OBJECTIVES:This study evaluated whether a range of demographic, social and geographic factors had an influence on glycaemic control longitudinally after an initial diagnosis of diabetes. DESIGN, SETTING AND PARTICIPANTS:We used the US Veterans Administration Diabetes Risk national cohort to track glycaemic control among patients 20-79-year old with a new diagnosis of type 2 diabetes. PRIMARY OUTCOME AND METHODS:We modelled associations between glycaemic control at follow-up clinical assessments and geographic factors including neighbourhood race/ethnicity, socioeconomic, land use and food environment measures. We also adjusted for individual demographics, comorbidities, haemoglobin A1c (HbA1c) at diagnosis and duration of follow-up. These factors were analysed within strata of community type: high-density urban, low-density urban, suburban/small town and rural areas. RESULTS:We analysed 246 079 Veterans who developed a new type 2 diabetes diagnosis in 2008-2018 and had at least 2 years of follow-up data available. Across all community types, we found that lower baseline HbA1c and female sex were strongly associated with a higher likelihood of within-range HbA1c at follow-up. Surprisingly, patients who were older or had more documented comorbidities were more likely to have within-range follow-up HbA1c results. While there was variation by community type, none of the geographic measures analysed consistently demonstrated significant associations with glycaemic control across all community types.

Cardiovascular disease risk is known to be influenced by both the severity of a risk factor and the duration of exposure (eg, LDL [low-density lipoprotein] cholesterol, tobacco smoke). However, this concept has been largely neglected within the obesity literature. While obesity severity has been closely linked with cardiometabolic diseases, the risk of developing these conditions among those with obesity may be augmented by greater obesity duration over the life span. Few longitudinal or contemporary studies have investigated the influence of both factors in combination-cumulative obesity exposure-instead generally focusing on obesity severity, often at a single time point, given ease of use and lack of established methods to encapsulate duration. Our review focuses on what is known about the influence of the duration of exposure to excess adiposity within the obesity-associated cardiometabolic disease risk equation by means of summarizing the hypothesized mechanisms for and evidence surrounding the relationships of obesity duration with diverse cardiovascular and metabolic disease. Through the synthesis of the currently available data, we aim to highlight the importance of a better understanding of the influence of obesity duration in cardiovascular and metabolic disease pathogenesis. We underscore the clinical importance of aggressive early attention to obesity identification and intervention to prevent the development of chronic diseases that arise from exposure to excess body weight.

As the worldwide prevalence of overweight and obesity continues to rise, so too does the urgency to fully understand mediating mechanisms, to discover new targets for safe and effective therapeutic intervention, and to identify biomarkers to track obesity and the success of weight loss interventions. In 2016, the American Heart Association sought applications for a Strategically Focused Research Network (SFRN) on Obesity. In 2017, 4 centers were named, including Johns Hopkins University School of Medicine, New York University Grossman School of Medicine, University of Alabama at Birmingham, and Vanderbilt University Medical Center. These 4 centers were convened to study mechanisms and therapeutic targets in obesity, to train a talented cadre of American Heart Association SFRN-designated fellows, and to initiate and sustain effective and enduring collaborations within the individual centers and throughout the SFRN networks. This review summarizes the central themes, major findings, successful training of highly motivated and productive fellows, and the innovative collaborations and studies forged through this SFRN on Obesity. Leveraging expertise in in vitro and cellular model assays, animal models, and humans, the work of these 4 centers has made a significant impact in the field of obesity, opening doors to important discoveries, and the identification of a future generation of obesity-focused investigators and next-step clinical trials. The creation of the SFRN on Obesity for these 4 centers is but the beginning of innovative science and, importantly, the birth of new collaborations and research partnerships to propel the field forward.

Recent studies implicate macrophages in regulation of thermogenic, sympathetic neuron-mediated norepinephrine (NE) signaling in adipose tissues, but understanding of such non-classical macrophage activities is incomplete. Here we show that male mice lacking the allograft inflammatory factor-1 (AIF1) protein resist high fat diet (HFD)-induced obesity and hyperglycemia. We link this phenotype to higher adipose NE levels that stem from decreased monoamine oxidase A (MAOA) expression and NE clearance by AIF1-deficient macrophages, and find through reciprocal bone marrow transplantation that donor Aif1^-/- vs WT genotype confers the obesity phenotype in mice. Interestingly, human sequence variants near the AIF1 locus associate with obesity and diabetes; in adipose samples from participants with obesity, we observe direct correlation of AIF1 and MAOA transcript levels. These findings identify AIF1 as a regulator of MAOA expression in macrophages and catecholamine activity in adipose tissues - limiting energy expenditure and promoting energy storage - and suggest how it might contribute to human obesity.

Obesity has reached epidemic proportions in the United States, but little is known about the mechanisms of weight gain and weight loss. Integration of omics data is becoming a popular tool to increase understanding in such complex phenotypes. Biomarkers come in abundance, but small sample size remains a serious limitation in clinical trials. In the present study, we developed a strategy to screen predictors from a multiomics, high-dimensional, and longitudinal dataset from a small cohort of 10 women with obesity who were provided an identical very-low calorie diet. Our proposal explores the combinatorial space of potential predictors from transcriptomics, microbiome, metabolome, fecal bile acids, and clinical data with the application of the first-order Spearman partial correlation coefficient. Two statistics are proposed for screening predictors, the partial association score, and the persistent significance. We applied our strategy to predict rates of weight loss in our sample of participants in a hospital metabolic facility. Our method reduced an initial set of 42,000 biomarker candidates to 61 robust predictors. The results show baseline fecal bile acids and regulation in RT-polymerase chain reaction as the most predictive data sources in forecasting the rate of weight-loss. In summary, the present study proposes a strategy based on nonparametric statistics for ranking and screening predictors of weight loss from a multiomics study. The proposed biomarker screening strategy warrants further translational clinical investigation in obesity and other complex clinical phenotypes.

Although tissue uptake of fatty acids from chylomicrons is primarily via lipoprotein lipase (LpL) hydrolysis of triglycerides (TGs), studies of patients with genetic LpL deficiency suggest additional pathways deliver dietary lipids to tissues. Despite an intact endothelial cell (EC) barrier, hyperchylomicronemic patients accumulate chylomicron-derived lipids within skin macrophages, leading to the clinical finding eruptive xanthomas. We explored whether an LpL-independent pathway exists for transfer of circulating lipids across the EC barrier. We found that LpL-deficient mice had a marked increase in aortic EC lipid droplets before and after a fat gavage. Cultured ECs internalized chylomicrons, which were hydrolyzed within lysosomes. The products of this hydrolysis fueled lipid droplet biogenesis in ECs and triggered lipid accumulation in cocultured macrophages. EC chylomicron uptake was inhibited by competition with HDL and knockdown of the scavenger receptor-BI (SR-BI). In vivo, SR-BI knockdown reduced TG accumulation in aortic ECs and skin macrophages of LpL-deficient mice. Thus, ECs internalize chylomicrons, metabolize them in lysosomes, and either store or release their lipids. This latter process may allow accumulation of TGs within skin macrophages and illustrates a pathway that might be responsible for creation of eruptive xanthomas.