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2.  Renal Artery Calcium, Cardiovascular Risk Factors and Indices of Renal Function 
The American journal of cardiology  2013;113(1):10.1016/j.amjcard.2013.09.036.
Vascular calcium is well studied in the coronary and peripheral arteries although there is limited data focusing on calcium deposits specific to renal arteries. The associations between renal artery calcium (RAC), cardiovascular disease (CVD) risk factors, and indices of renal function are unknown. We examined 2699 Framingham Heart Study participants who were part of a multidetector computed tomography substudy from 2008–2011. RAC was measured as a calcified plaque of >130 Hounsfield units and an area of >3 contiguous pixels. Detectable RAC was defined as an Agatston score >0. Chronic kidney disease (CKD) was defined as an eGFR <60 mL/min/1.73m2. Microalbuminuria was defined as ACR ≥17 mg/g for men and ≥25 mg/g for women. Multivariable adjusted logistic regression models were used to evaluate the associations between RAC, CVD risk factors, and renal function. The associations were secondarily adjusted for coronary artery calcium (CAC) that was used as a marker of non-renal systemic vascular calcium. The prevalence of RAC was 28.2%; this was similar in women (28.8%) and men (27.5%). Individuals with RAC had a higher odds of microalbuminuria (OR 1.79, 95% CI 1.22–2.61, p=0.003), hypertension (OR 2.11, 95% CI 1.69–2.64, p<0.001) and diabetes (OR 1.60, 95% CI 1.14–2.24, p=0.01) but not CKD (OR 0.87, 95% CI 0.58–1.32). After adjustment for CAC, the association with microalbuminuria and hypertension persisted but the association with diabetes became non-significant. In conclusion, RAC is common and independently associated with microalbuminuria and hypertension after adjustment for non-renal vascular calcium. RAC may be uniquely associated with these markers of renal end-organ damage.
PMCID: PMC3882167  PMID: 24210678
cardiovascular risk factors; microalbuminuria; renal artery calcium
3.  Relation of Hypothyroidism and Incident Atrial Fibrillation (from the Framingham Heart Study) 
American heart journal  2013;167(1):10.1016/j.ahj.2013.10.012.
Hyperthyroidism has a well-described association with atrial fibrillation (AF). However, the relation of hypothyroidism to AF has had limited investigation. Hypothyroidism is associated with cardiovascular risk factors, subclinical cardiovascular disease and overt cardiovascular disease, all of which predispose to AF. We investigated 10-year incidence of AF in a community-dwelling cohort.
Among 6,653 Framingham heart Study participants, 5,069 participants, 52% woman, mean age 57±12, were eligible after excluding those with missing thyroid stimulating hormone (TSH), TSH <0.45 μU/L (hyperthyroid), TSH >19.9 μU/L or prevalent AF. TSH was categorized by range (≥0.45 to <4.5, 4.5 to <10.0, 10.0 to ≤19.9 μU/L) and by quartiles. We examined the associations between TSH and 10-year risk of AF using multivariable-adjusted Cox proportional hazards analysis.
Over 10-year follow-up, we observed 277 cases of incident AF. A 1-standard deviation (SD) increase in TSH was not associated with increased risk of AF (hazard ratio 1.01, 95% confidence interval 0.90 to 1.14, p=0.83). In categorical analysis, employing TSH ≥0.45 to <4.5 μU/L as the referent (equivalent to euthyroid state), we found no significant association between hypothyroidism and 10-year AF risk. Comparing the highest (2.6
In conclusion, we did not identify a significant association between hypothyroidism and 10-year risk of incident AF in a community-based study.
PMCID: PMC3868014  PMID: 24332151
Atrial fibrillation; hypothyroidism; risk factors; cohort study
Carriers of the T allele of the single-nucleotide polymorphism rs13038305 tend to have lower cystatin C levels and higher cystatin C-based estimated glomerular filtration rate (eGFRcys). Adjusting for this genetic effect on cystatin C concentrations may improve GFR estimation, reclassify cases of CKD, and strengthen risk estimates for cardiovascular disease (CVD) and mortality.
Study Design
Setting & Population
Four population-based cohorts: Atherosclerosis Risk in Communities (ARIC), Cardiovascular Health (CHS), Framingham Heart (FHS), and Health, Aging, and Body Compostion (Health ABC) studies.
We estimated the association of rs13038305 with eGFRcys and eGFRcr, and performed longitudinal analyses of the associations of eGFRcys with mortality and cardiovascular events following adjustment for rs13038305.
We assessed reclassification by genotype-adjusted eGFRcys across CKD categories: <45, 45–59, 60–89, and ≥90 mL/min/1.73 m2. We compared mortality and CVD outcomes in those reclassified to a worse eGFRcys category with those unaffected. Results were combined using fixed-effect inverse-variance meta-analysis.
In 14,645 participants, each copy of the T allele of rs13038305 (frequency, 21%), was associated with 6.4% lower cystatin C concentration, 5.5 mL/min/1.73 m2 higher eGFRcys, and 36% [95% CI, 29%–41%] lower odds of CKD. Associations with CVD (HR, 1.17; 95% CI, 1.14–1.20) and mortality (HR, 1.22; 95% CI, 1.19–1.24) per 10- ml/min/1.73 m2 lower eGFRcys were similar with or without rs13038305 adjustment. In total, 1134 participants (7.7%) were reclassified to a worse CKD category following rs13038305 adjustment, and rates of CVD and mortality were higher in individuals who were reclassified. However, the overall net reclassification index was not significant for either outcome, at 0.009 (95% CI, −0.003 to 0.022) for mortality and 0.014 (95% CI, 0.0 to 0.028) for CVD.
rs13038305 only explains a small proportion of cystatin C variation.
Statistical adjustment can correct a genetic bias in GFR estimates based on cystatin C in carriers of the T allele of rs13038305 and result in changes in disease classification. However, on a population level, the effects on overall reclassification of CKD status are modest.
PMCID: PMC3872167  PMID: 23932088
Cystatin C; chronic kidney disease; genetics; single nucleotide polymorphism; net reclassification improvement
PLoS ONE  2014;9(11):e113118.
Protecting and promoting recovery of species at risk of extinction is a critical component of biodiversity conservation. In Canada, the Committee on the Status of Endangered Wildlife in Canada (COSEWIC) determines whether species are at risk of extinction or extirpation, and has conducted these assessments since 1977. We examined trends in COSEWIC assessments to identify whether at-risk species that have been assessed more than once tended to improve, remain constant, or deteriorate in status, as a way of assessing the effectiveness of biodiversity conservation in Canada. Of 369 species that met our criteria for examination, 115 deteriorated, 202 remained unchanged, and 52 improved in status. Only 20 species (5.4%) improved to the point where they were ‘not at risk’, and five of those were due to increased sampling efforts rather than an increase in population size. Species outcomes were also dependent on the severity of their initial assessment; for example, 47% of species that were initially listed as special concern deteriorated between assessments. After receiving an at-risk assessment by COSEWIC, a species is considered for listing under the federal Species at Risk Act (SARA), which is the primary national tool that mandates protection for at-risk species. We examined whether SARA-listing was associated with improved COSEWIC assessment outcomes relative to unlisted species. Of 305 species that had multiple assessments and were SARA-listed, 221 were listed at a level that required identification and protection of critical habitat; however, critical habitat was fully identified for only 56 of these species. We suggest that the Canadian government should formally identify and protect critical habitat, as is required by existing legislation. In addition, our finding that at-risk species in Canada rarely recover leads us to recommend that every effort be made to actively prevent species from becoming at-risk in the first place.
PMCID: PMC4234741  PMID: 25401772
Academic radiology  2013;20(11):10.1016/j.acra.2013.08.008.
Rationale and Objectives
Abdominal aortic calcification (AAC) can be quantified using computed tomography (CT), but imaging planes are prescribed based on bony landmarks, so that individual variation between the landmark and the aortoiliac junction can result in variable aortic coverage. In the Framingham CT substudy, we scanned a 15-cm (Z-direction) abdominal segment cranial to the S1 vertebral body. We sought to determine the range and distribution of length of aorta scanned, the distribution of AAC within the abdominal aorta, and to compare burden of AAC measured from fixed-length segments versus AAC from all slices cranial to the aortoiliac bifurcation.
Materials and Methods
AAC was quantified by modified Agatston score (AS) in 100 Framingham Heart Study participants (60±13 years, 51 men). We compared AS measured from 5-cm and 8-cm segments to ASALL (total visualized aorta).
73/100 participants had AAC > 0. The total length of aorta imaged was ≥ 8 cm in 84% of participants. Qualitatively, 5-cm and 8-cm segments correctly identified 96% and 99%, respectively, of participants as having or not having AAC. Quantitatively, AS8cm was within 20% of ASALL in four-fifths and within 30% of ASALL in nine-tenths of participants. AS5cm more severely underestimated ASALL.
Using S1 as the caudal imaging landmark in a 15-cm slab yields ≥ 8 cm aortic coverage in most adults. Both 5-cm and 8-cm analysis strategies are comparable to analyzing the total visualized abdominal aorta for prevalent AAC, but only 8-cm segment analysis yields quantitatively similar measures of AAC.
PMCID: PMC3842029  PMID: 24119355
abdominal aorta; calcium; population study; segment length; computed tomography
Incorporation of novel plasma protein biomarkers may improve current models for prediction of atherosclerotic cardiovascular disease (ASCVD) risk.
Approach and Results
We utilized discovery mass spectrometry (MS) to determine plasma concentrations of 861 proteins in 135 myocardial infarction (MI) cases and 135 matched controls. We then measured 59markers by targeted MS in 336 ASCVD case-control pairs. Associations with MI or ASCVD were tested in single marker and multimarker analyses adjusted for established ASCVD risk factors.
Twelve single markers from discovery MS were associated with MI incidence (at p<0.01) adjusting for clinical risk factors. Seven proteins in aggregate (cyclophilin A, CD5 antigen-like, cell surface glycoprotein MUC18, collagen-alpha 1 [XVIII] chain, salivary alpha-amylase 1, C-reactive protein, and multimerin-2) were highly associated with MI (p<0.0001) and significantly improved its prediction compared to a model with clinical risk factors alone (C-statistic of 0.71 vs. 0.84). Through targeted MS, twelve single proteins were predictors of ASCVD (at p<0.05) after adjusting for established risk factors. In multimarker analyses, four proteins in combination (alpha-1-acid glycoprotein 1, paraoxonase 1, tetranectin, and CD5 antigen-like, predicted incident ASCVD (p<0.0001) and moderately improved the C-statistic from the model with clinical covariates alone (C-statistic of 0.69 vs. 0.73).
Proteomics profiling identified single and multimarker protein panels that are associated with new onset ASCVD and may lead to a better understanding of underlying disease mechanisms. Our findings include many novel protein biomarkers that, if externally validated, may improve risk assessment for MI and ASCVD.
PMCID: PMC4061732  PMID: 24526693
Biomarker; cardiovascular disease; epidemiology; myocardial infarction; proteomics
To determine whether ectopic fat depots are prospectively associated with cardiovascular disease, cancer and all-cause mortality.
The morbidity associated with excess body weight varies among individuals of similar body mass index. Ectopic fat depots may underlie this risk differential. However, prospective studies of directly measured fat are limited.
Participants from the Framingham Heart Study (n=3086, 49% women, mean age 50.2 years) underwent assessment of fat depots (visceral adipose tissue, pericardial adipose tissue, and periaortic adipose tissue) using multidetector computed tomography, and were followed longitudinally for a median of 5.0 years. Cox proportional hazards regression models were used to examine the association of each fat depot (per 1 standard deviation increment) with the risk of incident cardiovascular disease, cancer, and all-cause mortality after adjustment for standard risk factors, including body mass index.
Overall, there were 90 cardiovascular events, 141 cancer events, and 71 deaths. After multivariable adjustment, visceral adipose tissue was associated with cardiovascular disease (HR 1.44, 95% CI 1.08–1.92, p=0.01) and cancer (HR 1.43, 95% CI 1.12–1.84, p=0.005). Addition of visceral adipose tissue to a multivariable model that included body mass index modestly improved cardiovascular risk prediction (net reclassification improvement of 16.3%). None of the fat depots were associated with all-cause mortality.
Visceral adiposity is associated with incident cardiovascular disease and cancer after adjustment for clinical risk factors and generalized adiposity. These findings support the growing appreciation of a pathogenic role of ectopic fat.
PMCID: PMC4142485  PMID: 23850922
obesity; visceral fat; body fat distribution; cardiovascular disease; cancer
Human Molecular Genetics  2013;22(17):3597-3607.
Genetic loci for body mass index (BMI) in adolescence and young adulthood, a period of high risk for weight gain, are understudied, yet may yield important insight into the etiology of obesity and early intervention. To identify novel genetic loci and examine the influence of known loci on BMI during this critical time period in late adolescence and early adulthood, we performed a two-stage meta-analysis using 14 genome-wide association studies in populations of European ancestry with data on BMI between ages 16 and 25 in up to 29 880 individuals. We identified seven independent loci (P < 5.0 × 10−8) near FTO (P = 3.72 × 10−23), TMEM18 (P = 3.24 × 10−17), MC4R (P = 4.41 × 10−17), TNNI3K (P = 4.32 × 10−11), SEC16B (P = 6.24 × 10−9), GNPDA2 (P = 1.11 × 10−8) and POMC (P = 4.94 × 10−8) as well as a potential secondary signal at the POMC locus (rs2118404, P = 2.4 × 10−5 after conditioning on the established single-nucleotide polymorphism at this locus) in adolescents and young adults. To evaluate the impact of the established genetic loci on BMI at these young ages, we examined differences between the effect sizes of 32 published BMI loci in European adult populations (aged 18–90) and those observed in our adolescent and young adult meta-analysis. Four loci (near PRKD1, TNNI3K, SEC16B and CADM2) had larger effects and one locus (near SH2B1) had a smaller effect on BMI during adolescence and young adulthood compared with older adults (P < 0.05). These results suggest that genetic loci for BMI can vary in their effects across the life course, underlying the importance of evaluating BMI at different ages.
PMCID: PMC3736869  PMID: 23669352
Obesity (Silver Spring, Md.)  2014;22(3):919-924.
The association of familial as compared to genetic factors in the current obesogenic environment, compared to earlier, leaner time periods, is uncertain.
Design and Methods
Participants from the Framingham Heart Study were classified according to parental obesity status in the Original, Offspring, and Third Generation cohorts; mean BMI levels were estimated and we compared the association of parental history across generations. Finally, a genetic risk score comprised of 32 well-replicated single nucleotide polymorphisms for BMI was examined in association with BMI levels in 1948, 1971, and 2002.
BMI was 1.49 kg/m2 higher per each affected parent among the Offspring, and increased to 2.09 kg/m2 higher among the Third Generation participants (p-value for the cohort comparison=0.007). Parental history of obesity was associated with increased weight gain (p<0.0001) and incident obesity (p=0.009). Despite a stronger association of parental obesity with offspring BMI in more contemporary time periods, we observed no change in the effect size of a BMI genetic risk score from 1948 to 2002 (p=0.11 for test of trend across the time periods).
The association of parental obesity has become stronger in more contemporary time period, whereas the association of a BMI genetic risk score has not changed.
PMCID: PMC3887126  PMID: 23836774
obesity; epidemiology; weight change; family history; Framingham Heart Study
Diabetes Care  2013;36(8):2139-2141.
PMCID: PMC3714497  PMID: 23881964
Dairy foods are nutrient-dense and may be protective against long-term weight gain.
We aimed to examine the longitudinal association between dairy consumption and annualized changes in weight and waist circumference (WC) in adults.
Members of the Framingham Heart Study Offspring Cohort who participated in the 5th through 8th study examinations (1991–2008) were included in these analyses (3,440 participants with 11,683 observations). At each exam, dietary intake was assessed by a validated food frequency questionnaire, and weight and WC were assessed following standardized procedures. Repeated measures models were used for the longitudinal analyses by adjusting for time-varying or invariant covariates.
On average, participants gained weight and WC during follow-up. Dairy intake increased across exams. After adjusting for demographic and lifestyle factors (including diet quality), participants who consumed ≥3 servings/d of total dairy had 0.10 [±0.04] kg smaller annualized increment of weight (Ptrend=0.04) than those consuming <1 serving/d. Higher total dairy intake was also marginally associated with less WC gain (Ptrend=0.05). Similarly, participants who consumed ≥3 servings/wk of yogurt had a 0.10 [±0.04] kg and 0.13 [±0.05] cm smaller annualized increment of weight (Ptrend=0.03) and WC (Ptrend=0.008) than those consuming <1 serving/wk, respectively. Skim/low-fat milk, cheese, total high-fat or total low-fat dairy intake was not associated with long-term change of weight or WC.
Further longitudinal and interventional studies are warranted to confirm the beneficial role of increasing total dairy and yogurt intake, as part of a healthy and calorie-balanced dietary pattern, in the long-term prevention of gain in weight and WC.
PMCID: PMC3809320  PMID: 23736371
Dairy; Weight; Waist circumference; Longitudinal; Milk; Yogurt
Ectopic fat density is associated with cardiovascular disease (CVD) risk factors above and beyond fat volume. Volumetric measures of ectopic fat have been associated with CVD risk factors and subclinical atherosclerosis. The aim of this study was to investigate the association between fat density and subclinical atherosclerosis.
Methods and Results
Participants were drawn from the Multi‐Detector Computed Tomography (MDCT) substudy of the Framingham Heart Study (n=3079; mean age, 50.1 years; 49.2% women). Fat density was indirectly estimated by computed tomography attenuation (Hounsfield Units [HU]) on abdominal scan slices. Visceral fat (VAT), subcutaneous fat (SAT), and pericardial fat HU and volumes were quantified using standard protocols; coronary and abdominal aortic calcium (CAC and AAC, respectively) were measured radiographically. Multivariable‐adjusted logistic regression models were used to evaluate the association between adipose tissue HU and the presence of CAC and AAC. Overall, 17.1% of the participants had elevated CAC (Agatston score [AS]>100), and 23.3% had elevated AAC (AS>age‐/sex‐specific cutoffs). Per 5‐unit decrement in VAT HU, the odds ratio (OR) for elevated CAC was 0.76 (95% confidence interval [CI], 0.65 to 0.89; P=0.0005), even after adjustment for body mass index or VAT volume. Results were similar for SAT HU. With decreasing VAT HU, we also observed an OR of 0.79 (95% CI, 0.67 to 0.92; P=0.004) for elevated AAC after multivariable adjustment. We found no significant associations between SAT HU and AAC. There was no significant association between pericardial fat HU and either CAC or AAC.
Lower VAT and SAT HU, indirect estimates of fat quality, are associated with a lower risk of subclinical atherosclerosis.
PMCID: PMC4310364  PMID: 25169793
atherosclerosis; epidemiology; fat density; obesity
BMC Genetics  2014;15:81.
Hyperuricemia is associated with multiple diseases, including gout, cardiovascular disease, and renal disease. Serum urate is highly heritable, yet association studies of single nucleotide polymorphisms (SNPs) and serum uric acid explain a small fraction of the heritability. Whether copy number polymorphisms (CNPs) contribute to uric acid levels is unknown.
We assessed copy number on a genome-wide scale among 8,411 individuals of European ancestry (EA) who participated in the Atherosclerosis Risk in Communities (ARIC) study. CNPs upstream of the urate transporter SLC2A9 on chromosome 4p16.1 are associated with uric acid (χ2df2=3545, p=3.19×10-23). Effect sizes, expressed as the percentage change in uric acid per deleted copy, are most pronounced among women (3.974.935.87 [ 2.55097.5 denoting percentiles], p=4.57×10-23) and independent of previously reported SNPs in SLC2A9 as assessed by SNP and CNP regression models and the phasing SNP and CNP haplotypes (χ2df2=3190,p=7.23×10-08). Our finding is replicated in the Framingham Heart Study (FHS), where the effect size estimated from 4,089 women is comparable to ARIC in direction and magnitude (1.414.707.88, p=5.46×10-03).
This is the first study to characterize CNPs in ARIC and the first genome-wide analysis of CNPs and uric acid. Our findings suggests a novel, non-coding regulatory mechanism for SLC2A9-mediated modulation of serum uric acid, and detail a bioinformatic approach for assessing the contribution of CNPs to heritable traits in large population-based studies where technical sources of variation are substantial.
PMCID: PMC4118309  PMID: 25007794
Copy number polymorphism; Hyperuricemia; Genomewide association study
JACC. Cardiovascular imaging  2013;6(7):762-771.
The aim of this study was to evaluate whether computed tomography (CT) attenuation, as a measure of fat quality, is associated with cardiometabolic risk factors above and beyond fat quantity.
Visceral (VAT) and subcutaneous adipose tissue (SAT) are pathogenic fat depots associated with cardiometabolic risk. Adipose tissue attenuation in CT images is variable, similar to adipose tissue volume. However, whether the quality of abdominal fat attenuation is associated to cardiometabolic risk independent of the quantity is uncertain.
Participants were drawn from the Framingham Heart Study CT sub-study. VAT and SAT volumes were acquired by semi-quantitative assessment. Fat quality was measured by CT attenuation and recorded as mean Hounsfield Units (HU) within each fat depot. Sex-specific linear and logistic multivariable regression models were used to assess the association between standard deviation (SD) decrease in HU and each risk factor.
Lower CT attenuation of VAT and SAT was correlated with higher BMI levels in both sexes. Risk factors were generally more adverse with decreasing HU values. For example, in women, per 1-SD decrease in VAT HU, the odds ratio (OR) was increased for hypertension (OR 1.80), impaired fasting glucose (OR 2.10), metabolic syndrome (OR 3.65) and insulin resistance (OR 3.36) (all p<0.0001). In models that further adjusted for VAT volume, impaired fasting glucose, metabolic syndrome and insulin resistance remained significant. Trends were similar but less pronounced in SAT and in men. There was evidence of an interaction between HU and fat volume among both women and men.
Lower CT attenuation of VAT and SAT is associated with adverse cardiometabolic risk above and beyond total adipose tissue volume. Qualitative indices of abdominal fat depots may provide insight regarding cardiometabolic risk independent of fat quantity.
PMCID: PMC3745280  PMID: 23664720
Obesity; Epidemiology; CT Imaging; Risk Factors
Chronic kidney disease is associated with cardiovascular disease. We tested for evidence of a shared genetic basis to these traits.
Study Design
We conducted two targeted analyses. First, we examined whether known single nucleotide polymorphisms (SNPs) underpinning kidney traits were associated with a series of vascular phenotypes. Additionally, we tested whether vascular SNPs were associated with markers of kidney damage. Significance was set to 1.5 × 10-4 (0.05/325 tests).
Setting & Participants
Vascular outcomes were analyzed in participants from the AortaGen (20,634), CARDIoGRAM (86,995), CHARGE Eye (15,358), CHARGE IMT (31,181), ICBP (69,395) and NeuroCHARGE (12,385) consortia. Tests for kidney outcomes were conducted in up to 67,093 participants from the CKDGen consortium.
We used 19 kidney SNPs and 64 vascular SNPs.
Outcomes & Measurements
Vascular outcomes tested were blood pressure, coronary artery disease, carotid intima-media thickness, pulse wave velocity, retinal venular caliber and brain white matter lesions. Kidney outcomes were estimated glomerular filtration rate and albuminuria.
In general, we found that kidney disease variants were not associated with vascular phenotypes (127 of 133 tests were non-significant). The one exception was rs653178 near SH2B3 (SH2B adaptor protein 3), which showed direction-consistent association with systolic (p=9.3E-10) and diastolic (p=1.6E-14) blood pressure and coronary artery disease (p=2.2E-6), all previously reported. Similarly, the 64 SNPs associated with vascular phenotypes were not associated with kidney phenotypes (187 of 192 tests were non-significant), with the exception of 2 high-correlated SNPs at the SH2B3 locus (p=1.06E-07 and p=7.05E-08).
Combined effect size of the SNPs for kidney and vascular outcomes may be too low to detect shared genetic associations.
Overall, although we confirmed one locus (SH2B3) as associated with both kidney and cardiovascular disease, our primary findings suggest that there is little overlap between kidney and cardiovascular disease risk variants in the overall population. The reciprocal risks of kidney and cardiovascular disease may not be genetically mediated, but rather a function of the disease milieu itself.
PMCID: PMC3660426  PMID: 23474010
Diabetes Care  2013;36(6):1590-1596.
Many studies of diabetes have examined risk factors at the time of diabetes diagnosis instead of considering the lifetime burden of adverse risk factor levels. We examined the 30-year cardiovascular disease (CVD) risk factor burden that participants have up to the time of diabetes diagnosis.
Among participants free of CVD, incident diabetes cases (fasting plasma glucose ≥126 mg/dL or treatment) occurring at examinations 2 through 8 (1979–2008) of the Framingham Heart Study Offspring cohort were age- and sex-matched 1:2 to controls. CVD risk factors (hypertension, high LDL cholesterol, low HDL cholesterol, high triglycerides, obesity) were measured at the time of diabetes diagnosis and at time points 10, 20, and 30 years prior. Conditional logistic regression was used to compare risk factor levels at each time point between diabetes cases and controls.
We identified 525 participants with new-onset diabetes who were matched to 1,049 controls (mean age, 60 years; 40% women). Compared with those without diabetes, individuals who eventually developed diabetes had higher levels of hypertension (odds ratio [OR], 2.2; P = 0.003), high LDL (OR, 1.5; P = 0.04), low HDL (OR, 2.1; P = 0.0001), high triglycerides (OR, 1.7; P = 0.04), and obesity (OR, 3.3; P < 0.0001) at time points 30 years before diabetes diagnosis. After further adjustment for BMI, the ORs for hypertension (OR, 1.9; P = 0.02) and low HDL (OR, 1.7; P = 0.01) remained statistically significant.
CVD risk factors are increased up to 30 years before diagnosis of diabetes. These findings highlight the importance of a life course approach to CVD risk factor identification among individuals at risk for diabetes.
PMCID: PMC3661800  PMID: 23340887
Human Molecular Genetics  2013;22(10):2119-2127.
With white blood cell count emerging as an important risk factor for chronic inflammatory diseases, genetic associations of differential leukocyte types, specifically monocyte count, are providing novel candidate genes and pathways to further investigate. Circulating monocytes play a critical role in vascular diseases such as in the formation of atherosclerotic plaque. We performed a joint and ancestry-stratified genome-wide association analyses to identify variants specifically associated with monocyte count in 11 014 subjects in the electronic Medical Records and Genomics Network. In the joint and European ancestry samples, we identified novel associations in the chromosome 16 interferon regulatory factor 8 (IRF8) gene (P-value = 2.78×10(−16), β = −0.22). Other monocyte associations include novel missense variants in the chemokine-binding protein 2 (CCBP2) gene (P-value = 1.88×10(−7), β = 0.30) and a region of replication found in ribophorin I (RPN1) (P-value = 2.63×10(−16), β = −0.23) on chromosome 3. The CCBP2 and RPN1 region is located near GATA binding protein2 gene that has been previously shown to be associated with coronary heart disease. On chromosome 9, we found a novel association in the prostaglandin reductase 1 gene (P-value = 2.29×10(−7), β = 0.16), which is downstream from lysophosphatidic acid receptor 1. This region has previously been shown to be associated with monocyte count. We also replicated monocyte associations of genome-wide significance (P-value = 5.68×10(−17), β = −0.23) at the integrin, alpha 4 gene on chromosome 2. The novel IRF8 results and further replications provide supporting evidence of genetic regions associated with monocyte count.
PMCID: PMC3633369  PMID: 23314186
The American journal of cardiology  2013;111(10):1510-1516.
Current screening and detection of asymptomatic aortic aneurysms is largely based on uniform cut-point diameters. Our objective was to define normal aortic diameters in asymptomatic men and women in a community-based cohort and to determine the association between aortic diameters and traditional risk factors for cardiovascular disease (CVD).Measurements of the diameter of the ascending aorta(AA), descending thoracic aorta (DTA), infrarenal abdominal (IRA) and lower abdominal aorta (LAA) were acquired from 3,431 Framingham Heart Study participants. Mean diameters were stratified by sex, age, and body surface area (BSA). Univariate associations with risk factor levels were examined and multivariable linear regression analysis was used to assess the significance of covariate-adjusted relations with aortic diameters. For men, the average diameter was 34.1 mm for AA, 25.8 mm for DTA, 19.3 mm for IRA and 18.7 mm for LAA.For women, the average diameter was 31.9 mm for AA, 23.1 mm for DTA, 16.7 mm for IRA, and 16.0 mm for LAA. The mean aorticdiameters were strongly correlated (p<0.0001) with age and BSA in age-adjusted analyses, and these relations remained significant in multivariable regression analyses. Positive associations of diastolic BP with AA and DTA in both sexes and pack years of cigarette smoking with DTA in women and with IRA in men and women were observed. In conclusion, average diameters of the thoracic and abdominal aorta by CT are larger in men compared with women, vary significantly with age and BSA, and are associated with modifiable CVD risk factors including diastolic blood pressure and cigarette smoking.
PMCID: PMC3644324  PMID: 23497775
Aortic diameter; computed tomography; sex; age; body surface area
Mid-life obesity is associated with T2D risk. However, less is known about the cumulative effect of obesity during adulthood.
Framingham Offspring Study participants who had an examination at 35±2 years and were initially free of T2D were included in this study (N=1026). A cumulative excess weight (CEW) score (year*kg/m2) was calculated until T2D diagnostic or the end of follow-up.
Eighty-four individuals (8.2%) developed T2D over 20±6 years. Mean CEW scores were 118.0± 114.6 year*kg/m2 in individuals who developed T2D and 30.2±91.4 year*kg/m2 in those who did not develop T2D (P<0.01). T2D risk was doubled for each standard deviation increase in the CEW score (OR= 1.99 [1.64–2.40]; P<0.001). However, CEW score was only significantly associated with T2D incidence for participants with a baseline BMI <25 kg/m2 (OR =2.13 [1.36–3.36]; P <0.001).
Accumulating weight between the mid-thirties to the mid-fifties increases the risk of developing T2D. However, BMI in mid-thirties remains a stronger predictor of T2D risk.
PMCID: PMC3670768  PMID: 23312789
Adults; Aging; BMI; Diagnosis; Epidemiology
Berndt, Sonja I. | Gustafsson, Stefan | Mägi, Reedik | Ganna, Andrea | Wheeler, Eleanor | Feitosa, Mary F. | Justice, Anne E. | Monda, Keri L. | Croteau-Chonka, Damien C. | Day, Felix R. | Esko, Tõnu | Fall, Tove | Ferreira, Teresa | Gentilini, Davide | Jackson, Anne U. | Luan, Jian’an | Randall, Joshua C. | Vedantam, Sailaja | Willer, Cristen J. | Winkler, Thomas W. | Wood, Andrew R. | Workalemahu, Tsegaselassie | Hu, Yi-Juan | Lee, Sang Hong | Liang, Liming | Lin, Dan-Yu | Min, Josine L. | Neale, Benjamin M. | Thorleifsson, Gudmar | Yang, Jian | Albrecht, Eva | Amin, Najaf | Bragg-Gresham, Jennifer L. | Cadby, Gemma | den Heijer, Martin | Eklund, Niina | Fischer, Krista | Goel, Anuj | Hottenga, Jouke-Jan | Huffman, Jennifer E. | Jarick, Ivonne | Johansson, Åsa | Johnson, Toby | Kanoni, Stavroula | Kleber, Marcus E. | König, Inke R. | Kristiansson, Kati | Kutalik, Zoltán | Lamina, Claudia | Lecoeur, Cecile | Li, Guo | Mangino, Massimo | McArdle, Wendy L. | Medina-Gomez, Carolina | Müller-Nurasyid, Martina | Ngwa, Julius S. | Nolte, Ilja M. | Paternoster, Lavinia | Pechlivanis, Sonali | Perola, Markus | Peters, Marjolein J. | Preuss, Michael | Rose, Lynda M. | Shi, Jianxin | Shungin, Dmitry | Smith, Albert Vernon | Strawbridge, Rona J. | Surakka, Ida | Teumer, Alexander | Trip, Mieke D. | Tyrer, Jonathan | Van Vliet-Ostaptchouk, Jana V. | Vandenput, Liesbeth | Waite, Lindsay L. | Zhao, Jing Hua | Absher, Devin | Asselbergs, Folkert W. | Atalay, Mustafa | Attwood, Antony P. | Balmforth, Anthony J. | Basart, Hanneke | Beilby, John | Bonnycastle, Lori L. | Brambilla, Paolo | Bruinenberg, Marcel | Campbell, Harry | Chasman, Daniel I. | Chines, Peter S. | Collins, Francis S. | Connell, John M. | Cookson, William | de Faire, Ulf | de Vegt, Femmie | Dei, Mariano | Dimitriou, Maria | Edkins, Sarah | Estrada, Karol | Evans, David M. | Farrall, Martin | Ferrario, Marco M. | Ferrières, Jean | Franke, Lude | Frau, Francesca | Gejman, Pablo V. | Grallert, Harald | Grönberg, Henrik | Gudnason, Vilmundur | Hall, Alistair S. | Hall, Per | Hartikainen, Anna-Liisa | Hayward, Caroline | Heard-Costa, Nancy L. | Heath, Andrew C. | Hebebrand, Johannes | Homuth, Georg | Hu, Frank B. | Hunt, Sarah E. | Hyppönen, Elina | Iribarren, Carlos | Jacobs, Kevin B. | Jansson, John-Olov | Jula, Antti | Kähönen, Mika | Kathiresan, Sekar | Kee, Frank | Khaw, Kay-Tee | Kivimaki, Mika | Koenig, Wolfgang | Kraja, Aldi T. | Kumari, Meena | Kuulasmaa, Kari | Kuusisto, Johanna | Laitinen, Jaana H. | Lakka, Timo A. | Langenberg, Claudia | Launer, Lenore J. | Lind, Lars | Lindström, Jaana | Liu, Jianjun | Liuzzi, Antonio | Lokki, Marja-Liisa | Lorentzon, Mattias | Madden, Pamela A. | Magnusson, Patrik K. | Manunta, Paolo | Marek, Diana | März, Winfried | Mateo Leach, Irene | McKnight, Barbara | Medland, Sarah E. | Mihailov, Evelin | Milani, Lili | Montgomery, Grant W. | Mooser, Vincent | Mühleisen, Thomas W. | Munroe, Patricia B. | Musk, Arthur W. | Narisu, Narisu | Navis, Gerjan | Nicholson, George | Nohr, Ellen A. | Ong, Ken K. | Oostra, Ben A. | Palmer, Colin N.A. | Palotie, Aarno | Peden, John F. | Pedersen, Nancy | Peters, Annette | Polasek, Ozren | Pouta, Anneli | Pramstaller, Peter P. | Prokopenko, Inga | Pütter, Carolin | Radhakrishnan, Aparna | Raitakari, Olli | Rendon, Augusto | Rivadeneira, Fernando | Rudan, Igor | Saaristo, Timo E. | Sambrook, Jennifer G. | Sanders, Alan R. | Sanna, Serena | Saramies, Jouko | Schipf, Sabine | Schreiber, Stefan | Schunkert, Heribert | Shin, So-Youn | Signorini, Stefano | Sinisalo, Juha | Skrobek, Boris | Soranzo, Nicole | Stančáková, Alena | Stark, Klaus | Stephens, Jonathan C. | Stirrups, Kathleen | Stolk, Ronald P. | Stumvoll, Michael | Swift, Amy J. | Theodoraki, Eirini V. | Thorand, Barbara | Tregouet, David-Alexandre | Tremoli, Elena | Van der Klauw, Melanie M. | van Meurs, Joyce B.J. | Vermeulen, Sita H. | Viikari, Jorma | Virtamo, Jarmo | Vitart, Veronique | Waeber, Gérard | Wang, Zhaoming | Widén, Elisabeth | Wild, Sarah H. | Willemsen, Gonneke | Winkelmann, Bernhard R. | Witteman, Jacqueline C.M. | Wolffenbuttel, Bruce H.R. | Wong, Andrew | Wright, Alan F. | Zillikens, M. Carola | Amouyel, Philippe | Boehm, Bernhard O. | Boerwinkle, Eric | Boomsma, Dorret I. | Caulfield, Mark J. | Chanock, Stephen J. | Cupples, L. Adrienne | Cusi, Daniele | Dedoussis, George V. | Erdmann, Jeanette | Eriksson, Johan G. | Franks, Paul W. | Froguel, Philippe | Gieger, Christian | Gyllensten, Ulf | Hamsten, Anders | Harris, Tamara B. | Hengstenberg, Christian | Hicks, Andrew A. | Hingorani, Aroon | Hinney, Anke | Hofman, Albert | Hovingh, Kees G. | Hveem, Kristian | Illig, Thomas | Jarvelin, Marjo-Riitta | Jöckel, Karl-Heinz | Keinanen-Kiukaanniemi, Sirkka M. | Kiemeney, Lambertus A. | Kuh, Diana | Laakso, Markku | Lehtimäki, Terho | Levinson, Douglas F. | Martin, Nicholas G. | Metspalu, Andres | Morris, Andrew D. | Nieminen, Markku S. | Njølstad, Inger | Ohlsson, Claes | Oldehinkel, Albertine J. | Ouwehand, Willem H. | Palmer, Lyle J. | Penninx, Brenda | Power, Chris | Province, Michael A. | Psaty, Bruce M. | Qi, Lu | Rauramaa, Rainer | Ridker, Paul M. | Ripatti, Samuli | Salomaa, Veikko | Samani, Nilesh J. | Snieder, Harold | Sørensen, Thorkild I.A. | Spector, Timothy D. | Stefansson, Kari | Tönjes, Anke | Tuomilehto, Jaakko | Uitterlinden, André G. | Uusitupa, Matti | van der Harst, Pim | Vollenweider, Peter | Wallaschofski, Henri | Wareham, Nicholas J. | Watkins, Hugh | Wichmann, H.-Erich | Wilson, James F. | Abecasis, Goncalo R. | Assimes, Themistocles L. | Barroso, Inês | Boehnke, Michael | Borecki, Ingrid B. | Deloukas, Panos | Fox, Caroline S. | Frayling, Timothy | Groop, Leif C. | Haritunian, Talin | Heid, Iris M. | Hunter, David | Kaplan, Robert C. | Karpe, Fredrik | Moffatt, Miriam | Mohlke, Karen L. | O’Connell, Jeffrey R. | Pawitan, Yudi | Schadt, Eric E. | Schlessinger, David | Steinthorsdottir, Valgerdur | Strachan, David P. | Thorsteinsdottir, Unnur | van Duijn, Cornelia M. | Visscher, Peter M. | Di Blasio, Anna Maria | Hirschhorn, Joel N. | Lindgren, Cecilia M. | Morris, Andrew P. | Meyre, David | Scherag, André | McCarthy, Mark I. | Speliotes, Elizabeth K. | North, Kari E. | Loos, Ruth J.F. | Ingelsson, Erik
Nature genetics  2013;45(5):501-512.
Approaches exploiting extremes of the trait distribution may reveal novel loci for common traits, but it is unknown whether such loci are generalizable to the general population. In a genome-wide search for loci associated with upper vs. lower 5th percentiles of body mass index, height and waist-hip ratio, as well as clinical classes of obesity including up to 263,407 European individuals, we identified four new loci (IGFBP4, H6PD, RSRC1, PPP2R2A) influencing height detected in the tails and seven new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3, ZZZ3) for clinical classes of obesity. Further, we show that there is large overlap in terms of genetic structure and distribution of variants between traits based on extremes and the general population and little etiologic heterogeneity between obesity subgroups.
PMCID: PMC3973018  PMID: 23563607
Intramuscular fat accumulates between muscle fibers or within muscle cells. We investigated the association of intramuscular fat with other ectopic fat deposits and metabolic risk factors.
Approach and Results
Participants (n = 2945; 50.2% women; mean age 50.8 years) from the Framingham Heart Study underwent multidetector computed tomography scanning of the abdomen. Regions of interest were placed on the left and right paraspinous muscle and the muscle attenuation (MA) in Hounsfield units were averaged. We examined the association between MA and metabolic risk factors in multivariable models and additionally adjusted for BMI and visceral fat (VAT) in separate models. MA was associated with dysglycemia, dyslipidemia, and hypertension in both sexes. In women, per standard deviation decrease in MA, there was a 1.34 (95% CI 1.10–1.64) increase in the odds of diabetes, a 1.40 (95% CI 1.22 – 1.61) increase in the odds of high triglycerides, and a 1.29 (95% CI 1.12 – 1.48) increase in the odds of hypertension. However, none of these associations persisted after adjustment for BMI or VAT. In men, we observed similar patterns for most risk factors. The exception was metabolic syndrome, which retained association in women even after adjustment for BMI and VAT, and low HDL and high triglycerides in men, whose associations also persisted after adjustment for BMI and VAT.
MA was associated with metabolic risk factors, but most of these associations were lost after adjustment for BMI or VAT. However, a unique association remained for metabolic syndrome in women and lipids in men.
PMCID: PMC3696991  PMID: 23349188
Metabolism; obesity; intramuscular fat; epidemiology
Clinical chemistry  2013;59(11):1613-1620.
Growth differentiation factor-15 (GDF-15), soluble ST2 (sST2), and high-sensitivity troponin I (hsTnI) are emerging predictors of adverse clinical outcomes. We sought to examine whether circulating concentrations are related to the development of kidney disease in the community.
Plasma GDF-15, sST2, and hsTnI concentrations were measured in 2,614 Framingham Offspring cohort participants (mean age 57 years, 54% women) at the sixth examination cycle (1995–1998). Associations of biomarkers with incident chronic kidney disease (CKD, eGFR<60 ml/min/1.73m2, n=276), microalbuminuria (urinary albumin to creatinine ratio ≥ 25 mg/g in women and 17 mg/g in men, n=191), and rapid decline in renal function (decline in eGFR ≥ 3 ml/min/1.73m2 per year, n=237), were evaluated using multivariable logistic regression; P<0.006 was considered statistically significant in primary analyses.
Participants were followed over a mean of 9.5 years. Higher plasma GDF-15 was associated with incident CKD (multivariable-adjusted OR 1.9 per 1-unit increase in log-GDF-15, 95% CI 1.6–2.3, P<0.0001) and rapid decline in renal function (OR 1.6, 95% CI 1.3–1.8, P<0.0001). GDF-15, sST2, and hsTnI had suggestive associations with incident microalbuminuria but did not meet the pre-specified P-value threshold after multivariable adjustment. Adding plasma GDF-15 to clinical covariates improved risk prediction of incident CKD: the c-statistic increased from 0.826 to 0.845 (P=0.0007), and categorical net reclassification was 6.3% (95% CI 2.7–9.9%).
Higher circulating GDF-15 is associated with incident renal outcomes, and improves risk prediction of incident CKD. These findings may provide insights into mechanisms of renal injury.
PMCID: PMC3972213  PMID: 23873716
Kidney; Risk Factors; Epidemiology
Obesity is associated with altered atrial electrophysiology and a prominent risk factor for atrial fibrillation. Body mass index, the most widely used adiposity measure, has been related to atrial electrical remodeling. We tested the hypothesis that pericardial fat is independently associated with electrocardiographic measures of atrial conduction.
Methods and Results
We performed a cross‐sectional analysis of 1946 Framingham Heart Study participants (45% women) to determine the relation between pericardial fat and atrial conduction as measured by P wave indices (PWI): PR interval, P wave duration (P‐duration), P wave amplitude (P‐amplitude), P wave area (P‐area), and P wave terminal force (P‐terminal). We performed sex‐stratified linear regression analyses adjusted for relevant clinical variables and ectopic fat depots. Each 1‐SD increase in pericardial fat was significantly associated with PR interval (β=1.7 ms, P=0.049), P‐duration (β=2.3 ms, P<0.001), and P‐terminal (β=297 μV·ms, P<0.001) among women; and P‐duration (β=1.2 ms, P=0.002), P‐amplitude (β=−2.5 μV, P<0. 001), and P‐terminal (β=160 μV·ms, P=0.002) among men. Among both sexes, pericardial fat was significantly associated with P‐duration in analyses additionally adjusting for visceral fat or intrathoracic fat; a similar but non‐significant trend existed with P‐terminal. Among women, pericardial fat was significantly associated with P wave area after adjustment for visceral and intrathoracic fat.
Pericardial fat is associated with atrial conduction as quantified by PWI, even with adjustment for extracardiac fat depots. Further studies are warranted to identify the mechanisms through which pericardial fat may modify atrial electrophysiology and promote subsequent risk for arrhythmogenesis.
PMCID: PMC4187474  PMID: 24595189
atrium; conduction; electrocardiography; epidemiology; obesity

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