Faculty Bibliography

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.

Aging leads to a number of disorders caused by cellular senescence, tissue damage, and organ dysfunction. It has been reported that anti-inflammatory and insulin-sensitizing compounds delay, or reverse, the aging process and prevent metabolic disorders, neurodegenerative disease, and muscle atrophy, improving healthspan and extending lifespan. Here we investigated the effects of PPARγ agonists in preventing aging and increasing longevity, given their known properties in lowering inflammation and decreasing glycemia. Our molecular and physiological studies show that long-term treatment of mice at 14 months of age with low doses of the PPARγ ligand rosiglitazone (Rosi) improved glucose metabolism and mitochondrial functionality. These effects were associated with decreased inflammation and reduced tissue atrophy, improved cognitive function, and diminished anxiety- and depression-like conditions, without any adverse effects on cardiac and skeletal functionality. Furthermore, Rosi treatment of mice started when they were 14 months old was associated with lifespan extension. A retrospective analysis of the effects of the PPARγ agonist pioglitazone (Pio) on longevity showed decreased mortality in patients receiving Pio compared to those receiving a PPARγ-independent insulin secretagogue glimepiride. Taken together, these data suggest the possibility of using PPARγ agonists to promote healthy aging and extend lifespan.