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Atrial fibrillation contributes to substantial increases in morbidity and mortality. We aimed to develop a risk score to predict individuals' absolute risk of developing the condition, and to provide a framework for researchers to assess new risk markers. We assessed 4764 participants in the Framingham Heart Study from 8044 examinations (55% women, 45–95 years of age) undertaken between June, 1968, and September, 1987. Thereafter, participants were monitored for the first event of atrial fibrillation for a maximum of 10 years. Multivariable Cox regression identified clinical risk factors associated with development of atrial fibrillation in 10 years. Secondary analyses incorporated routine echocardiographic measurements (5152 participants, 7156 examinations) to reclassify the risk of atrial fibrillation and to assess whether these measurements improved risk prediction. 457 (10%) of the 4764 participants developed atrial fibrillation. Age, sex, body-mass index, systolic blood pressure, treatment for hypertension, PR interval, clinically significant cardiac murmur, and heart failure were associated with atrial fibrillation and incorporated in a risk score (p<0·05, except body-mass index p=0·08), clinical model C statistic 0·78 (95% CI 0·76–0·80). Risk of atrial fibrillation in 10 years varied with age: more than 15% risk was recorded in 53 (1%) participants younger than 65 years, compared with 783 (27%) older than 65 years. Additional incorporation of echocardiographic measurements to enhance the risk prediction model only slightly improved the C statistic from 0·78 (95% CI 0·75–0·80) to 0·79 (0·77–0·82), p=0·005. Echocardiographic measurements did not improve risk reclassification (p=0·18). From clinical factors readily accessible in primary care, our risk score could help to identify risk of atrial fibrillation for individuals in the community, assess technologies or markers for improvement of risk prediction, and target high-risk individuals for preventive measures. US National Institutes of Health.

The authors of this study genotyped single-nucleotide polymorphisms (SNPs) at 18 diabetes-associated loci in participants of the Framingham Offspring Study. A genotype score based on these risk alleles predicted new cases of diabetes but resulted in only a slightly better prediction of risk than knowledge of common risk factors alone. In this study, a genotype score based on 18 diabetes-associated loci predicted new cases of diabetes but resulted in only a slightly better prediction of risk than knowledge of common risk factors alone. Type 2 diabetes mellitus is a major health problem worldwide. 1 Fortunately, its development can be prevented in many instances, 2 and persons at risk can be readily identified with the measurement of a few common risk factors. 3 – 5 Type 2 diabetes is heritable, with a risk for people with familial diabetes as compared with those without familial diabetes that is increased by a factor of 2 to 6. 6 , 7 Recent genetic association studies have provided convincing evidence that several novel loci are associated with the risk of diabetes, 8 – 13 each with a 5 to 37% increase in the relative odds of . . .

Pediatric glioblastomas (GBM) are highly aggressive and lethal tumors. Recent sequencing studies have shown that ~30 % of pediatric GBM and ~80 % of diffuse intrinsic pontine gliomas show K27M mutations in the H3F3A gene, a variant encoding histone H3.3. H3F3A K27M mutations lead to global reduction in H3K27me3. Our goal was to develop biomarkers for the histopathologic detection of these tumors. Therefore, we evaluated the utility of measuring H3K27me3 global reduction as a histopathologic and prognostic biomarker and tested an antibody directed specifically against the H3.3 K27M mutation in 290 samples. The study cohort included 203 pediatric (including 38 pediatric high-grade astrocytomas) and 38 adult brain tumors of various subtypes and grades and 49 non-neoplastic reactive brain tissues. Detection of H3.3 K27M by immunohistochemistry showed 100 % sensitivity and specificity and was superior to global reduction in H3K27me3 as a biomarker in diagnosing H3F3A K27M mutations. Moreover, cases that stained positive for H3.3 K27M showed a significantly poor prognosis compared to corresponding negative tumors. These results suggest that immunohistochemical detection of H3.3 K27M is a sensitive and specific surrogate for the H3F3A K27M mutation and defines a prognostically poor subset of pediatric GBM.

Heart failure, a strong risk factor for atrial fibrillation (AF), is often accompanied by elevated liver transaminases. The aim of this study was to test the hypothesis that elevated transaminases are associated with the risk for incident AF in the community. A total of 3,744 participants (mean age 65 ± 10 years, 56.8% women) from the Framingham Heart Study Original and Offspring cohorts, free of clinical heart failure, were studied. Cox proportional-hazards models adjusted for standard AF risk factors (age, gender, body mass index, systolic blood pressure, electrocardiographic PR interval, antihypertensive treatment, smoking, diabetes, valvular heart disease, and alcohol consumption) were examined to investigate associations between baseline serum transaminase levels (alanine transaminase and aspartate transaminase) and the incidence of AF over up to 10 years (29,099 person-years) of follow-up. During follow-up, 383 subjects developed AF. The 2 transaminases were significantly associated with greater risk for incident AF (hazard ratio expressed per SD of natural logarithmically transformed biomarker: alanine transaminase hazard ratio 1.19, 95% confidence interval 1.07 to 1.32, p = 0.002; aspartate transaminase hazard ratio 1.12, 95% confidence interval 1.01 to 1.24, p = 0.03). The associations between transaminases and AF remained consistent after the exclusion of participants with moderate to severe alcohol consumption. However, when added to known risk factors for AF, alanine transaminase and aspartate transaminase only subtly improved the prediction of AF. In conclusion, elevated transaminase concentrations are associated with increased AF incidence. The mechanisms by which higher mean transaminase concentrations are associated with incident AF remain to be determined.

OBJECTIVE:--Metabolic syndrome increases the risk for type 2 diabetes and cardiovascular disease (CVD) and may be associated with insulin resistance. RESEARCH DESIGN AND METHODS--We tested the hypothesis that the metabolic syndrome confers risk with or without concomitant insulin resistance among 2,803 Framingham Offspring Study subjects followed up to 11 years for new diabetes (135 cases) or CVD (240 cases). We classified subjects by presence of metabolic syndrome (using the National Cholesterol Education Program's [NCEPs] Third Adult Treatment Panel [ATP III], International Diabetes Federation [IDF], or European Group for the Study of Insulin Resistance [EGIR] criteria) and insulin resistance (homeostasis model assessment of insulin resistance >=75th percentile) and used separate risk factor-adjusted proportional hazards models to estimate relative risks (RRs) for diabetes or CVD using as referents those without insulin resistance, metabolic syndrome, or without both. RESULTS:--Fifty-six percent of individuals with ATP III, 52% with IDF, and 100% with EGIR definitions of metabolic syndrome had insulin resistance. Insulin resistance increased risk for diabetes (RR 2.6 [95% CI 1.7-4.0]) and CVD (1.8 [1.4-2.3]) as did metabolic syndrome for diabetes (ATP III, 3.5 [2.2-5.6]; IDF, 4.6 [2.7-7.7]; and EGIR, 3.3 [2.1-5.1]) and CVD (ATP III, 1.8 [1.4-2.3]; IDF, 1.7 [1.3-2.3]; and EGIR, 2.1 [1.6-2.7]). Relative to those without either metabolic syndrome or insulin resistance, metabolic syndrome and insulin resistance increased risk for diabetes (ATP III, 6.0 [3.3-10.8] and IDF, 6.9 [3.7-13.0]) and CVD (ATP III, 2.3 [1.7-3.1] and IDF, 2.2 [1.6-3.0]). Any instance of metabolic syndrome without insulin resistance increased risk for diabetes approximately threefold (P < 0.001); IDF metabolic syndrome without insulin resistance (RR 1.6, P = 0.01), but not ATP III metabolic syndrome without insulin resistance (RR 1.3, P = 0.2), increased risk for CVD. CONCLUSIONS:--Metabolic syndrome increased risk for diabetes regardless of insulin resistance. Metabolic syndrome by ATP III criteria may require insulin resistance to increase risk for CVD. The simultaneous presence of metabolic syndrome and insulin resistance identifies an especially high-risk individual.

We sought to investigate whether higher concentrations of resistin and lower concentrations of adiponectin relate to incident atrial fibrillation (AF) and whether this association is mediated by AF risk factors and inflammation. Resistin and adiponectin are adipokines that have been associated with multiple known risk factors for AF including diabetes, obesity, inflammation, and heart failure. We studied the relations between circulating concentrations of both adipokines and incident AF in participants of the Framingham Offspring Study. Participants (n = 2,487) had a mean age of 61 ± 10 years, and 54% were women. During a mean follow-up of 7.6 ± 2.0 years, 206 (8.3%) individuals (96 women) developed incident AF. Plasma resistin concentration was significantly associated with incident AF (multivariable-adjusted hazard ratio [HR] 1.17 per SD [0.41 ng/mL] of natural logarithmically transformed resistin, 95% CI 1.02-1.34, P = .028). The resistin-AF association was attenuated after further adjustment for C-reactive protein (HR per SD increase resistin 1.14, 95% CI 0.99-1.31, P = .073). Adiponectin concentrations were not significantly associated with incident AF (multivariable-adjusted HR of 0.95 per SD [0.62 μg/mL] of logarithmically transformed adiponectin, 95% CI 0.81-1.10, P = .478). In our community-based longitudinal study, higher mean concentrations of resistin were associated with incident AF, but the relation was attenuated by adjustment for C-reactive protein. We did not detect a statistically significant association between adiponectin and incident AF. Additional studies are needed to clarify the potential role of adipokines in AF and mechanisms linking adiposity to AF.

Insulin Resistance, the Metabolic Syndrome, and Incident Cardiovascular Events in the Framingham Offspring Study Martin K. Rutter 1 2 , James B. Meigs 3 4 , Lisa M. Sullivan 5 , Ralph B. D’Agostino, Sr 5 and Peter W. Wilson 6 7 1 Department of Medicine, Countess of Chester Hospital NHS Trust, Chester, U.K 2 Department of Medicine, University of Manchester, Manchester, U.K 3 Harvard Medical School, Boston, Massachusetts 4 General Internal Medicine Unit, Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts 5 Boston University School of Public Health, Boston, Massachusetts 6 Medical University of South Carolina, Charleston, South Carolina 7 National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts Address correspondence and reprint requests to Martin K. Rutter, MD, Directorate of Medicine, Countess of Chester Hospital NHS Trust, Liverpool Road, Chester, CH2 1UL, U.K. E-mail: martin.rutter{at}coch.nhs.uk Abstract The metabolic syndrome and insulin resistance have been related to incident cardiovascular disease (CVD), but it is uncertain if metabolic syndrome predicts CVD independent of insulin resistance. Our study sample included 2,898 people without diabetes or CVD at baseline. Metabolic syndrome was defined by the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) criteria. Insulin resistance was defined by the homeostasis model assessment (HOMA-IR) and by Gutt et al.’s insulin sensitivity index (ISI 0,120 ). Age- and sex-adjusted proportional hazards regression models assessed the association of baseline metabolic syndrome and insulin resistance to 7-year CVD risk (186 events). Metabolic syndrome and both measures of insulin resistance were individually related to incident CVD (age- and sex-adjusted hazard ratio [HR] for metabolic syndrome [present versus absent]: 2.0 [95% CI 1.5–2.6], P = 0.0001; for HOMA-IR: 1.9 [1.2–2.9], P = 0.003; and for ISI 0,120 [both highest versus lowest quartile]: 0.5 [0.3–0.7], P = 0.001). In models adjusted for age, sex, LDL cholesterol, and smoking status and including metabolic syndrome, ISI 0,120 levels were independently related to incident CVD (0.5 [0.3–0.8], P = 0.004), whereas HOMA-IR levels were not (1.3 [0.8–2.1], P = 0.24); metabolic syndrome was associated with increased CVD risk in both models (HR 1.6, P ≤ 0.007 in both). In conclusion, metabolic syndrome and ISI 0,120 but not HOMA-IR independently predicted incident CVD. Metabolic syndrome may not capture all the CVD risk associated with insulin resistance. Footnotes M.K.R. has received honoraria, consulting fees, and grant/research support from GlaxoSmithKline. P.W.W. has received honoraria from Merck and Pfizer; consulting fees from Eli Lilly, GlaxoSmithKline, and Sanofi; and grant/research support from GlaxoSmithKline and Wyeth. CVD, cardiovascular disease; HOMA-IR, homeostasis model assessment of insulin resistance; ISI, insulin sensitivity index; NCEP, National Cholesterol Education Program. Accepted August 1, 2005. Received December 5, 2004. DIABETES

OBJECTIVE: Obesity predisposes individuals to congestive heart failure (CHF) and cardiovascular disease (CVD). Leptin regulates energy homeostasis, is elevated in obesity, and influences ventricular and vascular remodeling. We tested the hypothesis that leptin levels are associated with greater risk of CHF, CVD, and mortality in elderly individuals. RESEARCH DESIGN AND METHODS: We evaluated 818 elderly (mean age 79 years, 62% women) Framingham Study participants attending a routine examination at which plasma leptin was assayed. RESULTS: Leptin levels were higher in women and strongly correlated with BMI (P < 0.0001). On follow-up (mean 8.0 years), 129 (of 775 free of CHF) participants developed CHF, 187 (of 532 free of CVD) experienced a first CVD event, and 391 individuals died. In multivariable Cox regression models adjusting for established risk factors, log-leptin was positively associated with incidence of CHF and CVD (hazard ratio [HR] per SD increment 1.26 [95% CI 1.03-1.55] and 1.28 [1.09-1.50], respectively). Additional adjustment for BMI nullified the association with CHF (0.97 [0.75-1.24]) but only modestly attenuated the relation to CVD incidence (1.23 [1.00-1.51], P = 0.052). We observed a nonlinear, U-shaped relation between log-leptin and mortality (P = 0.005 for quadratic term) with greater risk of death evident at both low and high leptin levels. CONCLUSIONS: In our moderate-sized community-based elderly sample, higher circulating leptin levels were associated with a greater risk of CHF and CVD, but leptin did not provide incremental prognostic information beyond BMI. Additional investigations are warranted to elucidate the U-shaped relation of leptin to mortality.

An adeno-associated viral vector was used to introduce a FIX gene with enhanced biologic activity in 10 participants with hemophilia B. The annualized bleeding rate was 11.1 events per year before therapy versus 0.4 afterward. Steady-state factor IX levels were 33.7% of normal.

Early menopausal age is associated with risk of cardiovascular events including myocardial infraction, stroke, and increased mortality. Relations between menopausal age and atrial fibrillation (AF) have not been investigated. We examined the association between menopausal age and AF. Framingham Heart Study women ≥60 years old without prevalent AF and natural menopause were followed up for 10 years or until incident AF. Menopausal age was modeled as a continuous variable and by categories (<45, 45-53, and >53 years). We used Cox proportional hazards regression to determine associations between menopausal age and AF risk. In 1,809 Framingham women (2,662 person-examinations, mean baseline age 71.4 ± 7.6 years, menopausal age 49.8 ± 3.6 years), there were 273 unique participants with incident AF. We did not identify a significant association between the SD of menopausal age (3.6 years) and AF (hazard ratio [HR] per SD 0.94, 95% CI 0.83-1.06; P = .29). In a multivariable model with established risk factors for AF, menopausal age was not associated with incident AF (HR per SD 0.97, 95% CI 0.86-1.09; P = .60). Examining categorical menopausal age, earlier menopausal age (<45 years) was not significantly associated with increased AF risk compared with older menopausal age >53 years (HR 1.20, 95% CI 0.74-1.94; P = .52) or menopausal age 45 to 53 years (HR 1.38, 95% CI 0.93-2.04; P = .11). In our moderate-sized, community-based sample, we did not identify menopausal age as significantly increasing AF risk. However, future larger studies will need to examine whether there is a small effect of menopausal age on AF risk.