166 research outputs found
PROLONGED QRS DURATION PREDICTS INCREASED INDEXED LEFT VENTRICULAR VOLUME AND MASS BY CMR: THE FRAMINGHAM HEART STUDY
Reference values for left atrial size by cardiovascular magnetic resonance in the Framingham Heart Study Offspring cohort
Burden of Adverse Metabolic Factors Is Associated With Increased Left Ventricular Concentricity in Adults With Normal-Range Body Mass Index: The Framingham Heart Study
Introduction: Persons with normal-range body mass index (BMI) but adverse metabolic characteristics associated with obesity have been described as metabolically-obese normal weight (MONW). We sought to determine whether adverse metabolic profile is associated with alterations in left ventricular (LV) structure or function among adults with normal BMI. Methods: From the 1794 Framingham Heart Study Offspring cohort adults who underwent cardiac magnetic resonance imaging (CMRI) , we identified 446 free of non-skin cancer and prevalent clinical cardiovascular disease (CVD) who had 18.5â€BMI\u3c25.0 kg/m2 and complete covariates. We calculated a metabolic score (MS) where 1 point was assigned for each of: a) fasting glucoseâ„100 mg/dL or diabetes; b) SBPâ„140 or DBPâ„90 mmHg or antihypertensive treatment; c) TGâ„150 or HDL_C \u3c40(M)/\u3c50(W) mg/dL or lipid treatment; d) HOMA-IRâ„2.5; e) waist circumference â„102/88cm for M/W. Participants were classified as MS0 (no points), MS1 (exactly 1 point), or MS2+ (â„2 points). LV mass (LVM), end-diastolic volume (EDV), ejection fraction (EF), and concentricity (LVM/EDV) were measured from breathhold cine SSFP CMR scans; we calculated LVM/BSA. Analysis of covariance (ANCOVA) was used to compare MS1 and MS2+ groups to the MS0 group. CMRI variables were adjusted for sex, age, heart rate (HR) and body size (BSA); LVM/BSA was adjusted for sex, age, HR only. We also tested for linear trend across metabolic groups. Results: LV concentricity increased with worsening metabolic status. This was driven by lower LV EDV, not increased LVM. LVM did not differ across (trend) or between MS-groups. LVEDV decreased across groups but only MS2 differed significantly from MS0. LVEF increased slightly but significantly across MS-groups. Conclusions: In a community-dwelling cohort, among participants who were free of cancer and clinical CVD and had normal BMI, worsening metabolic profile was associated with adverse remodeling of the left ventricle, reflected by greater LV concentricity
Normal reference values for thoracic and abdominal aorta and main pulmonary artery dimensions by cardiovascular magnetic resonance: the Framingham heart study
The Natural History of Left Ventricular Geometry in the Community Clinical Correlates and Prognostic Significance of Change in LVÂ Geometric Pattern
AbstractObjectivesThis study sought to evaluate pattern and clinical correlates of change in left ventricular (LV) geometry over a 4-year period in the community; it also assessed whether the pattern of change in LV geometry over 4 years predicts incident cardiovascular disease (CVD), including myocardial infarction, heart failure, and cardiovascular death, during an additional subsequent follow-up period.BackgroundIt is unclear how LV geometric patterns change over time and whether changes in LV geometry have prognostic significance.MethodsThis study evaluated 4,492 observations (2,604 unique Framingham Heart Study participants attending consecutive examinations) to categorize LV geometry at baseline and after 4 years. Four groups were defined on the basis of the sex-specific distributions of left ventricular mass (LVM) and relative wall thickness (RWT) (normal: LVM and RWTÂ <80th percentile; concentric remodeling: LVMÂ <80th percentile but RWTÂ â„80th percentile; eccentric hypertrophy: LVMÂ â„80th percentile but RWTÂ <80th percentile; and concentric hypertrophy: LVM and RWTÂ â„80th percentile).ResultsAt baseline, 2,874 of 4,492 observations (64%) had normal LVM and RWT. Participants with normal geometry or concentric remodeling progressed infrequently (4% to 8%) to eccentric or concentric hypertrophy. Change from eccentric to concentric hypertrophy was uncommon (8%). Among participants with concentric hypertrophy, 19% developed eccentric hypertrophy within the 4-year period. Among participants with abnormal LV geometry at baseline, a significant proportion (29% to 53%) reverted to normal geometry within 4 years. Higher blood pressure, greater body mass index (BMI), advancing age, and male sex were key correlates of developing an abnormal geometry. Development of an abnormal LV geometric pattern over 4 years was associated with increased CVD risk (140 events) during a subsequent median follow-up of 12 years (adjusted-hazards ratio: 1.59; 95% confidence interval: 1.04 to 2.43).ConclusionsThe longitudinal observations in the community suggest that dynamic changes in LV geometric pattern over time are common. Higher blood pressure and greater BMI are modifiable factors associated with the development of abnormal LV geometry, and such progression portends an adverse prognosis
Pericardial Fat Thickness Increases with Greater Burden of Adverse Metabolic Factors Among Adults with Normal-Range Body Mass Index: The Framingham Heart Study
Introduction: Greater burden of pericardial fat is associated with increased body mass index (BMI). Obesity is associated with unfavorable metabolic characteristics such as hypertension, dyslipidemia, and glucose intolerance. We sought to determine whether unfavorable metabolic profile alone, in the absence of excess BMI, was itself associated with increased pericardial fat thickness (PFT).
Methods:From the 1,794 Framingham Offspring cohort adults who underwent cardiac magnetic resonance (CMR), we identified 446 free of non-skin cancer and prevalent clinical cardiovascular disease (CVD) who had 18.5â€BMI2and complete covariates. We calculated a metabolic score (MS) based on ATPIII criteria where 1 point was assigned for each of: a) fasting glucoseâ„100 mg/dL or diabetes; b) SBPâ„130 or DBPâ„85 mmHg or antihypertensive treatment; c) triglyceridesâ„150 mg/dL; d) HDL cholesterol \u3c40(M)/
Results: PFT increased with worsening metabolic score at the fixed locations of the apical and mid-level RV, as well as at maximal PFT. On pairwise comparisons, only the MS3+ group had PFT that was consistently significantly greater than that of MS0.
Conclusions: In a community-dwelling cohort, among participants who were free of cancer and clinical CVD and had normal-range or BMI, worsening metabolic profile was associated with increased pericardial fat thickness
Comparison of methods for ranking and stratification of community-dwelling adults by pericardial fat thickness measured using cardiovascular magnetic resonance imaging
Impact of left ventricular trabeculations and papillary muscles on measures of cavity volume and ejection fraction
Distinct Adaptations of Mitochondrial Dynamics to Electrical Pulse Stimulation in Lean and Severely Obese Primary Myotubes
BACKGROUND: Skeletal muscle from lean and obese subjects elicit differential adaptations in response to exercise/muscle contractions. In order to determine whether obesity alters the adaptations in mitochondrial dynamics in response to exercise/muscle contractions and whether any of these distinct adaptations are linked to alterations in insulin sensitivity, we compared the effects of electrical pulse stimulation (EPS) on mitochondrial network structure and regulatory proteins in mitochondrial dynamics in myotubes from lean humans and humans with severe obesity and evaluated the correlations between these regulatory proteins and insulin signaling. METHODS: Myotubes from human skeletal muscle cells obtained from lean humans (BMI 23.8 ± 1.67 kg/m(2)) and humans with severer obesity (45.5 ± 2.26 kg/m(2)) (n=8/group) were electrically stimulated for 24 hours. Four-hours after EPS, mitochondrial network structure, protein markers of insulin signaling and mitochondrial dynamics were assessed. RESULTS: EPS enhanced insulin-stimulated Akt(Ser473) phosphorylation, reduced the number of non-networked individual mitochondria and increased the mitochondrial network size in both groups (P<0.05). Mitochondrial fusion marker mitofusin 2 was significantly increased in myotubes from the lean subjects (P<0.05), but reduced in subjects with severe obesity (P<0.05). In contrast, fission marker dynamin-related protein 1 (Drp1(Ser616)) was reduced in myotubes from subjects with severe obesity (P<0.05), but remained unchanged in lean subjects. Reductions in Drp(Ser616) phosphorylation were correlated with improvements in insulin-stimulated Akt(Ser473) phosphorylation following EPS (r = â0.679, P = 0.004). CONCLUSION: Our data demonstrated that EPS induces more fused mitochondrial networks, which are associated with differential adaptations in mitochondrial dynamic processes in myotubes from lean humans and human with severe obesity. It also suggests that improved insulin signaling following muscle contractions may be linked to the reduction in Drp1 activity
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Atherosclerotic Biomarkers and Aortic Atherosclerosis by Cardiovascular Magnetic Resonance Imaging in the Framingham Heart Study
Background: The relations between subclinical atherosclerosis and inflammatory biomarkers have generated intense interest but their significance remains unclear. We sought to determine the association between a panel of biomarkers and subclinical aortic atherosclerosis in a communityâbased cohort. Methods and Results: We evaluated 1547 participants of the Framingham Heart Study Offspring cohort who attended the 7th examination cycle and underwent both cardiovascular magnetic resonance imaging (CMR) and assays for 10 biomarkers associated with atherosclerosis: highâsensitivity Câreactive protein, fibrinogen, intercellular adhesion moleculeâ1, interleukinâ6, interleukinâ18, lipoproteinâassociated phospholipaseâA2 activity and mass, monocyte chemoattractant proteinâ1, Pâselectin, and tumor necrosis factor receptorâ2. In logistic regression analysis, we found no significant association between the biomarker panel and the presence of aortic plaque (global P=0.53). Using Tobit regression with aortic plaque as a continuous variable, we noted a modest association between biomarker panel and aortic plaque volume in ageâ and sexâadjusted analyses (P=0.003). However, this association was attenuated after further adjustment for clinical covariates (P=0.09). Conclusions: In our communityâbased cohort, we found no significant association between our multibiomarker panel and aortic plaque. Our results underscore the strengths and limitations of the use of biomarkers for the identification of subclinical atherosclerosis and the importance of traditional risk factors
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