Citations

Introduction: Metabolically obese normal weight (MONW) refers to metabolic abnormalities despite normal body mass index (BMI). Hypothesis: Because obesity is generally defined by BMI, it is assumed that people with MONW do not have excessive adiposity but still have the metabolic dysregulation associated with adiposity. Methods: We included participants aged 20-65 of the National Health and Nutrition Examination Surveys from 1999-2006 and 2011-2018 with normal BMI (18.5-25 kg/m 2 ), fasting blood samples, and DEXA data. According to the AHA criteria, MONW was defined having ≥3 of the following criteria, besides a normal BMI: Hypertriglyceridemia (≥ 150 mg/dL) or treatment for elevated triglycerides; HDL cholesterol level < 40 mg/dL in men or <50 mg/dL in women or treatment for reduced HDL-C; elevated blood pressure (systolic ≥ 130 mmHg and/or diastolic ≥ 85 mmHg) or antihypertensive treatment or history of hypertension; elevated fasting plasma glucose ≥ 100 mg/dL or insulin/oral hypoglycemic treatment and central obesity by waist circumference (≥ 94 cm in men and ≥ 80 cm in women). High fat percentage was defined as ≥25% in men, ≥35% in women. Weighted logistic regression was performed to test the relation between MONW and high fat%, central obesity. Results: Of the 7,887 participants (53.6% men; mean age±SE was 39.23±0.24 years), 2433 (33.4%) had normal BMI included in the analysis. Among these, 148 had MONW (5%). Mean Fat% was 26.08±0.36% in those with MONW versus 21.90±0.17% in those without MONW for men, and 37.02±0.35% versus 33.31±0.21% for women. MONW subjects were 2.21 times more likely to have either central obesity or high fat % (OR 12.09, 95%CI: 6.18-23.67, p<0.01) and 2.18 times more likely to have high fat % (OR=2.84, 95%CI: 1.72-4.67, p<0.01) (see Figure). Conclusions: Most individuals with MONW have either increased fat content, central deposition of fat, or both. That highlights people with normal BMI may still have metabolic complications of adiposity.

Background: The role of body adiposity on metabolic dysregulation in subjects with normal body mass index (BMI) is still under debate with limited population-based evidence. Hypothesis: Body adiposity measured by dual x-ray absorptiometry (DEXA) is associated with metabolic disorders in normal-weight individuals. Methods: We evaluated a sample of adults aged 20-65 who underwent DEXA in the US National Health and Nutrition Examination Surveys from 1999-2006 and 2011-2018. We excluded those with history of cardiovascular disease, cancer, and chronic obstructive pulmonary disease. Weighted logistic regression was performed to test the association between body fat percentage (BF%) and metabolic disorders [e.g., insulin resistance (IR), metabolic syndrome (MS), dyslipidemia, type 2 diabetes mellitus (DM), hypertension]. Models were adjusted for potential confounders while considering complex survey design and were further stratified by sex and BF% as tertiles in normal-weight individuals. IR was tested as a secondary analysis to evaluate the effect on the predicted risk. Results: We included 20,613 individuals (51.5% men, 65.4% non-Hispanic whites), mean age ± SE was 39.42±0.22 years, and 6,424 were normal weight by BMI and represented our study sample. The overall BF% in these subjects measured by DEXA was 28.41±0.19%. In our cohort, metabolic disorders were prevalent in 2.1% to 40.4% of patients (Table 1). Every 10-unit % increase in total BF% was associated with a higher risk for IR, MS, dyslipidemia in the normal weight BMI group (Table 1). Metabolic disorders were associated with BF% tertiles (Figure 1). IR was significantly associated with body fat across all BF% tertiles for men and highest tertiles for women (Figure 2). Conclusion(s): Less than 1/3 of subjects in a representative national sample had a normal BMI. Even in these “normal weight” subjects, increases in body adiposity are significantly associated with increased cardiometabolic disease burden.

Abstract Aims The objective of this study was to assess the effect of HER2-directed therapy (HER2-Tx) on peripheral vasoreactivity and its correlation with cardiac function changes and the additive effects of anthracycline/cyclophosphamide (AC) therapy and baseline cardiovascular risk. Methods and results Single-centre, prospective cohort study of women with newly diagnosed stage 1–3 HER2-positive breast cancer undergoing HER2-Tx +/− AC. All participants underwent baseline and 3-monthly evaluations with Endo-Peripheral Arterial Tonometry (Endo-PAT), vascular biomarkers [C-type natriuretic peptide (CNP) and neuregulin-1 beta (NRG-1β)], and echocardiography. Cardiotoxicity was defined as a decrease in the left ventricular ejection fraction (LVEF) of &gt;10% to a value &lt;53%. Of the 47 patients enrolled, 20 (43%) received AC in addition to HER2-Tx. Deterioration of reactive hyperaemia index (RHI) on Endo-PAT by ≥20% was more common in patients receiving HER-Tx plus AC than HER2-Tx alone (65% vs. 22%; P = 0.003). A decrease in CNP and log NRG-1β levels by 1 standard deviation did not differ significantly between the AC and non-AC groups (CNP: 20.0% vs. 7.4%; P = 0.20 and NRG-1β: 15% vs. 11%; P = 0.69) nor did GLS (35% vs. 37%; P = 0.89). Patients treated with AC had a significantly lower 3D LVEF than non-AC recipients as early as 3 months after exposure (mean 59.3% (SD 3) vs. 63.8% (SD 4); P = 0.02). Reactive hyperaemia index and GLS were the only parameters correlating with LVEF change. Conclusion Combination therapy with AC, but not HER2-Tx alone, leads to a decline in peripheral vascular and cardiac function. Larger studies will need to define more precisely the causal correlation between vascular and cardiac function changes in cancer patients.

The single-cell platform mass cytometry (CyTOF) enables detection of significant changes in one million of renal cells, especially in subsets of immune cells in ischemic human kidneys distal to renal artery stenosis (RAS). We found that pro-repair cell types such as scattered tubular-progenitor-like cells, aged neutrophils, and regulatory B cells show a compensatory increase in RAS. Immune cell phenotype changes may reflect ongoing inflammation and impaired immune defense capability in the kidneys.

Background Superimposition of the metabolic syndrome (MetS) on renovascular disease (RVD) amplifies intrarenal microvascular loss. Extracellular vesicles (EVs) released from adipose tissue‐derived mesenchymal stem/stromal cells (MSCs) may mediate their paracrine effect, but their efficacy to protect the renal microcirculation in RVD complicated by MetS remains unclear. Using a novel swine model, we tested the hypothesis that EVs would attenuate microvascular loss in MetS+RVD. Methods Four groups of pigs (n=7 each) were studied after 16 weeks of diet‐induced MetS and unilateral RVD (MetS+RVD), MetS+RVD treated 4 weeks earlier with a single intra‐renal delivery of pre‐labeled EVs harvested from autologous MSCs, and Lean and MetS Sham controls. Stenotic‐kidney renal blood flow (RBF) and glomerular filtration rate (GFR) were measured in‐vivo (fast CT), whereas EV characteristics, renal microvascular architecture (micro‐CT), and injury pathways ex‐vivo. Results mRNA sequencing of EVs and their parent MSCs revealed that EVs were enriched with pro‐angiogenic genes, including vascular endothelial growth factor (VEGF)‐A, VEGF–C, and Von Willebrand Factor (vWF)‐A Domain Containing‐1 (VWA)‐1 (). In addition, protein expression of VEGF and vWF was higher in EVs compared to MSCs (). EVs were detected in the stenotic‐kidney ex‐vivo internalized by tubular and endothelial cells. EVs restored renal expression of the pro‐angiogenic factors VEGF, Notch‐1, and Notch ligand delta‐like‐4 (DLL4) and improved cortical microvascular density (). Tubulointerstitial fibrosis increased and RBF and GFR decreased in MetS+RVD vs. MetS, but were restored in MetS+RVD+EV (). Conclusions Intra‐renal delivery of MSC‐derived EVs bearing pro‐angiogenic properties in swine MetS+RVD restored stenotic‐kidney microcirculation, and in turn its hemodynamics and function. Our study suggests a novel therapeutic potential for MSC‐derived EVs in restoring renal function in chronic experimental MetS+RVD. Support or Funding Information This study was partly supported by NIH grant numbers DK73608, DK104273, HL123160, and DK102325, DK106427, the Mayo Clinic Center for Regenerative Medicine, and the Mayo Clinic Mary Kathryn and Michael B. Panitch Career Development Award.

Abstract Background Atherosclerotic cardiovascular disease (ASCVD), of which coronary artery disease (CAD) is the primary manifestation, is the leading cause of death worldwide. The AHA/ACC Pooled Cohort Equation (PCE) facilitates risk stratification and initiation of primary prevention of ASCVD, however their performance is suboptimal. Purpose We develop an artificial intelligence-based electrocardiogram (ECG) analysis (AI-ECG) algorithm to detect different stages of CAD and assessed the value of AI-ECG over PCE to predict incident myocardial infarction (MI) and survival over 3-years. Methods Using electronic health record data from approximately 7 million patients seen at over 70 hospitals and clinics across 5 states in the USA, we created independent AI-ECG models to identify elevated coronary artery calcium (CAC) by computer tomography, the presence of obstructive CAD by stress test or angiography, and left ventricular regional akinesis by echocardiogram, presumed to represent prior MI. Deep structured data, AI-enabled natural language processing of unstructured data were used to ensure cohort, and physician review of labeling were used to ensure cohort accuracy. These models were ensembled into a single model that was used to assess the utility of AI-ECG for predicting new occurrence MI in PCE- and age-stratified cohorts of patient with no prior history of ASCVD, over a 3-year timeframe using Cox’s proportional hazards analysis. Results A total of 6,080 patients (15,192 ECGs) were labeled positive for CAC ≥ 300, 12,561 patients (18,915 ECGs) positive for obstructive CAD, and 10,767 patients (23,870 ECGs) positive for regional akinesis. AI-ECG for identifying elevated CACS, obstructive CAD, and regional akinesis achieved AUROCs of 0.86, 0.80, and 0.93, respectively. All AI-ECG models identified increased 3-year risk for MI and death in AI-ECG positive versus AI-ECG negative patients and subgroups with 2 or 3 positive results had stepwise increased risk (Figure A). In a 3-year survival analysis of all-comer patients, the hazard ratio for those that tested positive on 1, 2, or 3 versus 0 positive disease-specific models were 1.61 (1.53-1.69). 2.40 (2.27-2.55), 3.42 (3.21-3.65), respectively. Risk stratification was also observed in cohorts without prior ASCVD stratified by low and high PCE-derived 10-year ASCVD risk (Figure B) and in cohorts stratified by age, including under the age of 40. Conclusions AI-ECG has potential to address unmet need for accessible risk stratification in patients in whom PCE under, over, or insufficiently estimate ASCVD risk, and in whom risk assessment over periods of time shorter than 10 years is desired.

Introduction: The carotid artery rim sign on CTA is characterized by soft-plaque components surrounded by a rind of thin, adventitial calcification and its role in plaque instability is not established yet. Intraplaque hemorrhage (IPH) and the inflammatory microenvironment in carotid atheroma are considered features of atherosclerotic plaque vulnerability leading to cerebrovascular events. Hypothesis: The association between rim sign on CTA and carotid IPH and inflammation remains scantly investigated. In this study, we aimed to determine whether rim sign is associated with IPH on MRA and with the extent of IPH and inflammation on histology. We hypothesized that rim sign may be a radiological predictor of carotid IPH and inflammation. Methods: We retrospectively enrolled 100 consecutive patients who underwent carotid endarterectomy (CEA) and neck CTA before CEA. On CTA, the ipsilateral rim sign was defined as the presence of adventitial calcifications with internal soft-tissue plaque of ≥2 mm in maximum thickness. Of the included patients, 25 had MRA with 3D magnetization-prepared rapid acquisition with gradient echo (MPRAGE) sequence. Carotid plaque specimens were collected and stained with H&E to quantify IPH (%). Histologically, we defined IPH as an area of carotid plaque with blood elements, and inflammatory microenvironment as the presence of lymphocytes and plasma cells (chronic inflammation) and foam cells. Results: The rim sign on CTA was present in 56 (56%) of patients. IPH on MRA was present in 11 (44%) patients. The rim sign was significantly associated with the presence of IPH on MRA [9 (81.8%) vs 2 (14.3%); p=0.003]. On histology, the rim sign was associated with a higher extent of IPH [5.0 % (IQR 2.0-25.0) vs 5.0% (IQR 0.0-10.0); p=0.017], with chronic inflammation [44 (78.6%) vs 12 (21.4%); p=0.003], and foam cells [51 (91.1%) vs 5 (8.9%); p<0.001]. Conclusions: These findings suggest that rim sign on CTA may be proposed as a potential imaging marker of IPH as well as a histologic predictor of IPH extent and carotid plaque inflammatory microenvironment.

Background: The gap between electrocardiogram (ECG) artificial intelligence-derived age (ECG-Age) and chronological age (Age-Gap) predicts cardiovascular (CV) comorbidities and mortality reflecting physiologic age. Adverse childhood experiences (ACEs) are traumatic and harmful events that impact adulthood CV outcomes. We hypothesized that ACEs would be associated with physiologic age as determined by the Age-Gap. Methods: We applied a previously validated ECG-Age algorithm to the ECGs of 1,988 consecutive individuals aged ≥18, that within 2 years completed an ACEs questionnaire as part of psychological evaluations for weight management. The ACE questionnaire assesses 3 psychosocial domains (i) childhood abuse (psychological, physical or sexual), (ii) household dysfunction (substance abuse, mental illness, female figure treated violently, criminal behavior and parental separation/divorce) and (iii) neglect (emotional or physical) before age 18; results ranged 0 to 10 and were categorized as burden (0, 1-3, and ≥4) and presence (abuse, household dysfunction, neglect). Age-Gap was operationalized as (≤mean or > mean) positive values reflect physiological aging. Logistic regression analyses tested the association between ACE and Age-Gap. Results: Mean ± SD chronological age was 49±13 yr, ECG-Age 54±12 yr, Age-Gap 4.26±8.95 yr,75% women, average ACE 2±2, 32% experienced 0, 44% 1-3, and 24% ≥4 ACEs. Age-Gap was 1.4 years higher in those who experienced at least 1 ACE. Compared to those who didn’t experience ACE those who faced 1-3 ACE were more likely to have an Age-Gap >mean (OR 1.28 95%CI 1.57-1.04) independent of sex and the age-adjusted Charlson comorbidity index Fig A. Also, they were more prone to experiencing neglect and household dysfunction Fig B. Conclusions: Age-gap was associated with ACEs burden and domains, underscoring the need to identify ACEs during clinical evaluations to prevent ACEs at the individual, family, and community levels.