Scott, Christopher G.

Background Hyper‐ and hypokalemia are clinically silent, common in patients with renal or cardiac disease, and are life threatening. A noninvasive, unobtrusive, blood‐free method for tracking potassium would be an important clinical advance. Methods and Results Two groups of hemodialysis patients (development group, n=26; validation group, n=19) underwent high‐resolution digital ECG recordings and had 2 to 3 blood tests during dialysis. Using advanced signal processing, we developed a personalized regression model for each patient to noninvasively calculate potassium values during the second and third dialysis sessions using only the processed single‐channel ECG . In addition, by analyzing the entire development group's first‐visit data, we created a global model for all patients that was validated against subsequent sessions in the development group and in a separate validation group. This global model sought to predict potassium, based on the T wave characteristics, with no blood tests required. For the personalized model, we successfully calculated potassium values with an absolute error of 0.36±0.34 mmol/L (or 10% of the measured blood potassium). For the global model, potassium prediction was also accurate, with an absolute error of 0.44±0.47 mmol/L for the training group (or 11% of the measured blood potassium) and 0.5±0.42 for the validation set (or 12% of the measured blood potassium). Conclusions The signal‐processed ECG derived from a single lead can be used to calculate potassium values with clinically meaningful resolution using a strategy that requires no blood tests. This enables a cost‐effective, noninvasive, unobtrusive strategy for potassium assessment that can be used during remote monitoring.

Dysrhythmias and Death in BiMVPIntroductionBileaflet mitral valve prolapse (BiMVP) is common among survivors of otherwise unexplained sudden cardiac death, but prognostic implications of BiMVP are unknown. This study evaluated whether patients with BiMVP are at higher risk for ventricular dysrhythmias, ICD placement, or death compared to controls with either single‐leaflet mitral valve prolapse (SiMVP) or no mitral valve prolapse (MVP).Methods and ResultsThis retrospective, matched cohort study included 18,786 patients who underwent echocardiography at Mayo Clinic between June 1990 and September 2014. The study included three cohorts: BiMVP, SiMVP, and controls without MVP. We assessed rates of ventricular dysrhythmias, ICD placement, and all‐cause mortality between groups. BiMVP was associated with higher rates of ventricular tachycardia compared to SiMVP and controls (adjusted HR 1.48 [1.14–1.92], P = 0.003 and 1.40 [1.04–1.88], P = 0.026, respectively); however, there were no statistically significant differences in rates of ventricular fibrillation/cardiac arrest or ICD placement between groups. BiMVP was associated with a lower rate of all‐cause mortality compared to SiMVP and controls (adjusted HR 0.86 [0.79–0.94], P = 0.0008, and 0.55 [0.50–0.60], P < 0.0001, respectively).ConclusionAlthough BiMVP is associated with ventricular tachycardia, it is not associated with an increased risk of cardiac arrest/ventricular fibrillation or ICD implantation and is, paradoxically, associated with a better survival compared to SiMVP or matched controls. The findings suggest that, despite its association with ventricular tachycardia, BiMVP in the absence of other risk factors does not seem to portend a poor prognosis at the population level.

Background We recently reported that normal aldosterone levels are associated with cardiovascular, renal, and metabolic disease in a sample of the US general community (Visit 1). For the current analyses we used the same cohort in a new 4‐year follow‐up study (Visit 2). Methods and Results We measured aldosterone at Visit 1 and analyzed its predictive role for new diseases at Visit 2 (n=1140). We measured aldosterone at Visit 2 and investigated its associations with disease at Visit 2 (n=1368). We analyzed aldosterone continuously and we also dichotomized the variable as whether subjects were in the third tertile versus second and first tertiles. As continuous variable at Visit 1, aldosterone predicted new onset hypertension ( HTN ) ( OR =1.36, CI =1.13–1.63, P =0.001), central obesity ( OR =1.36, CI =1.07–1.73, P =0.011), and use of lipid‐lowering drugs ( OR =1.25, CI =1.05–1.48, P =0.012) at Visit 2, after adjustment for age, sex, and body mass index. When in the third tertile (8.5–88.6 ng/dL), aldosterone predicted type 2 diabetes (T2 DM , OR =1.96, CI =1.03–3.70, P =0.039). At Visit 2, aldosterone remained associated with HTN , obesity, and chronic kidney disease ( CKD ), as reported for Visit 1. However, aldosterone was not associated with heart failure ( HF ) at Visit 1 and 2, nor was aldosterone a predictor of HF between visits. Conclusions Aldosterone predicts new HTN , central obesity, T2 DM , and use of lipid‐lowering drugs in the general community and remains associated with HTN , obesity, and CKD over 4 years. Aldosterone is not associated nor predicts HF . Further studies are warranted to evaluate aldosterone as therapeutic target in the general community.

Abstract Purpose: Mammographic breast density is an established and strong risk factor for breast cancer. Recently, a number of common genetic susceptibility loci have been identified as risk factors for breast cancer. We present the first report on the relative contribution of 76 validated breast cancer susceptibility loci, in the context of a polygenic risk score (PRS), to the breast density and breast cancer association. We also examine whether the PRS improves prediction of the Breast Cancer Surveillance Consortium (BCSC) 5-year risk model above and beyond breast density and clinical factors included in the model. Methods: The study population included 1643 cases and 2397 controls from three independent epidemiologic studies: the Mayo Mammography Health Study (MMHS), the Mayo Clinic Breast Cancer Study (MCBCS), and the Bavarian Breast Cancer Cases and Control Study (BBCC). Data collected on patients in each of the studies included clinical risk factor, BI-RADS breast density [a) almost entirely fat; b) scattered fibroglandular densities; c) heterogeneously dense; and d) extremely dense] and genotypes for the 76 breast cancer susceptibility loci known at the time of the study. We formed a PRS from the reported per-SNP odds ratios (OR) for 76 known breast cancer susceptibility loci, and evaluated whether BI-RADS density and the PRS were independent risk factors for breast cancer, when adjusted for age, 1/BMI and study. We also incorporated the PRS (OR) into the BCSC 5-year risk model and estimated 5-year risk for the MMHS nested case-control study of 339 invasive cases, 765 controls. Results: BI-RADS density (p&lt;0.0001) and PRS (p&lt;0.0001) were independent risk factors for breast cancer that together showed greater discrimination of risk (AUC=0.69) than density (AUC=0.66; ΔAUC=0.029) or PRS score alone (AUC=0.68; ΔAUC=0.013; p&lt;0.001). Relative to those with scattered fibroglandular densities and average (2nd quartile) PRS, women with extremely dense breasts and in the highest PRS quartile, had a 2.7 fold (95%CI: 1.7-4.1) increased risk of breast cancer, while those with fatty breasts and in the lowest PRS quartile had a reduced risk (OR=0.30, 95%CI: 0.18-0.51). Incorporation of the PRS into the BCSC risk model improved discrimination (ΔAUC=0.031, p=0.001), for a net reclassification improvement of 20% (95%CI: 11%-28%), split equally among cases (9%) and controls (11%). Conclusion: BI-RADS density and the PRS are both important risk factors for breast cancer that can be included in breast cancer risk models to improve prediction of this disease. Using these models to identify high and low-risk risk groups will facilitate improved tailored screening and primary prevention interventions. Citation Format: Celine M. Vachon, V. Shane Pankratz, Christopher G. Scott, Lothar Haeberle, Elad Ziv, Matthew R. Jensen, Kathleen R. Brandt, Dana H. Whaley, Janet E. Olson, Katharina Heusinger, Carolin C. Hack, Sebastian M. Jud, Matthias W. Beckmann, Jeffrey A. Tice, Kristen S. Purrington, Thomas A. Sellers, Karla Kerlikowske, Peter A. Fasching, Fergus J. Couch. The contribution of common breast cancer susceptibility loci to the breast density and breast cancer association and the Breast Cancer Surveillance Consortium (BCSC) risk model. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 940. doi:10.1158/1538-7445.AM2014-940

Abstract Background: Mammographic breast density (MBD) reflects the proportion of fibroglandular tissue in the breast, and is an established risk factor for breast cancer. Benign breast disease (BBD) is also a known risk factor for breast cancer. We previously showed an association between lobular involution (physiologic atrophy) and MBD in a large cohort study of women with BBD. We performed a comprehensive evaluation of the association of histologic features of BBD with MBD. Methods: The Mayo BBD cohort includes women, 18 to 85 years, who were diagnosed with BBD at Mayo Clinic in Rochester, MN between 01/01/1967 and 12/31/1991. For this study, we included women who had a mammogram within 6 months of BBD diagnosis, and diagnosed with BBD between 1985 and 1991 when parenchymal pattern of breast density was clinically recorded. Risk factor information such as age, and body mass index (BMI) was collected from medical records. Parenchymal pattern, assessed clinically and previously used in multiple studies of MBD and risk, classified breast density based on extent and type of density, into four categories: N1 (non-dense, no ducts visible); P1 (ductal prominence occupying &lt;25% breast); P2 (prominent ductal pattern occupying &gt;25% of the breast; DY (homogenous plaque-like areas of density). All assessments of benign breast tissue were performed by expert breast pathologists blinded to both MBD and BBD reports. Histologic characteristics included overall impression (non-proliferative disease (NPD), proliferative disease without atypia (PDWA), and atypical hyperplasia (AH)), proportion of normal lobules that were involuted (no (0%), partial (1 to 74%), or complete (≥75%)), type of AH (ADH or ALH), ductal and lobular hyperplasia, calcifications, sclerosing adenosis, columnar alteration, cyst, fibroadenoma, marked fibrosis, intra-ductal papilloma, radial scar (number and size), duct ectasia, and mucocele like tumors. Associations of parenchymal pattern with BBD characteristics were examined using multicategorical nominal logistic regression models. We first examined associations after adjustment for age and BMI. All variables statistically significant (p&lt;0.05) in these models were then simultaneously included in a fully-adjusted model. Results: Of 2,257 women in the study, 14% were &lt;40 years old, 52.7% between 40- 59 years, and 32.9% were ≥60 years. In this sample, 55.2% of women had NPD, 36% had PDWA, and AH in 8.8%. MBD was classified as N1 in 21.8%, P1 in 12.6%, P2 in 23.7% and DY in 41.9%. Age- and BMI-adjusted analyses showed that there was an association of parenchymal pattern with overall impression, lobular involution, ductal hyperplasia, sclerosing adenosis, columnar alteration, cyst, duct ectasia and fibrosis. Multivariate analyses found that women of younger age (p&lt;0.001) and with lower BMI (p&lt;0.001), presence of fibrosis (p&lt;0.001) and no involution (p=0.016) were more likely to have P2 or DY parenchymal pattern than women without those characteristics. Conclusion: Among women with benign breast disease, higher MBD is associated with younger age, lower BMI, fibrosis, and lack of lobular involution. These findings, concordant with other studies of MBD, provide insight into underlying mechanisms by which MBD and BBD contribute to breast cancer risk. Citation Format: Karthik Ghosh, Robert A Vierkant, Ryan D Frank, Daniel W Visscher, Vernon S Pankratz, Christopher G Scott, Derek C Radisky, Marlene H Frost, Lynn C Hartmann, Amy C Degnim, Celine M Vachon. Association between mammographic breast density and histologic features of benign breast disease [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P6-10-14.

Abstract Introduction: We recently reported the percentage of mammographic density (MD) to be a breast cancer risk factor across tumor characteristics and age groups. Yet, we noted stronger associations for tumors of large size and positive lymph nodes across all ages, and ER-negative status among women ages &lt;55 years, suggesting high MD may play an important role in tumor aggressiveness, especially in younger women. We extend this initial study to investigate whether these associations with aggressive disease are due to the underlying associations of absolute dense or non-dense area, or both, with breast cancer risk. Methods: Data were pooled from six studies including 3517 women with invasive breast cancer and 8558 without. Dense area and non-dense area were assessed from digitized film-screen mammograms using a computer-assisted threshold technique. We standardized dense and non-dense area measurements made within each study and categorized into quartiles based on the control distribution for pooled analyses. We used polytomous logistic regression to calculate breast cancer odds according to tumor type, histopathological characteristics, and receptor (ER, PR) status by age (&lt;55, 55-64, and ≥65 years), adjusting for continuous age, body mass index, and study site. Results: Absolute dense area was associated with increased breast cancer risk [odds ratios (ORs) Q1 vs Q2: 0.67, Q3 vs Q2: 1.25, Q4 vs Q2: 1.62] and non-dense area was associated with decreased breast cancer risk (ORs: Q1 vs Q2: 1.44, Q3 vs Q2: 0.89, Q4 vs Q2: 0.71) overall and across all age groups. Positive associations for absolute dense area were observed across all invasive tumor characteristics. Stronger associations were noted for larger tumors across all ages (p-trend &lt;0.01). Among women &lt;55 years, stronger associations were observed for ER+ vs ER- [p-heterogeneity (het) = 0.02] and PR+ vs PR- tumors (p-het = 0.02). Non-dense area was inversely associated with all tumor characteristics evaluated except for tumors &lt;1.1 cm, for which no association was present. The inverse association was stronger for larger tumors, particularly for women &lt;55 years (p-trend &lt;0.01). Also among women &lt;55 years, a stronger inverse association with non-dense area was observed for ER- vs. ER+ tumors (p-het = 0.02). Conclusion: These results suggest the strong association we previously observed of high percent MD and ER-negative disease in women &lt;55 years could be explained by the low amount of non-dense area in these women. Further research is warranted to clarify the possible differential associations of absolute dense and non-dense area on breast cancer risk according to tumor characteristics. Citation Format: Kimberly A. Bertrand, Christopher G. Scott, Rulla M. Tamimi, Matthew R. Jensen, V. Shane Pankratz, Aaron Norman, John Shepherd, Yunn-Yi Chen, Karla Kerlikowske, Celine M. Vachon. Dense and non-dense mammographic area and risk of breast cancer by age and tumor characteristics. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 3279. doi:10.1158/1538-7445.AM2014-3279

C-type natriuretic peptide (CNP) is an endothelium-derived peptide that is released as a protective mechanism in response cardiovascular injury or disease. However, no studies have investigated circulating CNP, identifying clinical factors that may influence CNP and its relationship to cardiovascular disease in the general population. We studied 1841 randomly selected subjects from Olmsted County, MN (mean age, 63±11 years; 48% men). Plasma CNP was measured by a well-established radioimmunoassay and echocardiography, clinical characterization, and detailed medical record review were performed. We report that CNP circulates at various concentrations (median, 13 pg/mL), was unaffected by sex, was weakly associated by age, and that highest quartile of CNP identified a high-risk phenotype. Subjects with CNP in the highest quartile were associated with increased risk of myocardial infarction (multivariable-adjusted hazard ratio, 1.51; 95% confidence interval, 1.09–2.09; P =0.01) but not heart failure, cerebrovascular accidents, or death during a follow-up of 12 years. Addition of the highest quartile of CNP to clinical variables led to a modest increase in the integrated discrimination improvement for risk of myocardial infarction. In a large community-based cohort, elevated circulating CNP identified a high-risk phenotype that included cardiovascular comorbidities and left ventricular dysfunction, and provided evidence that highest concentrations of CNP potentially has prognostic value in predicting future risk of myocardial infarction. Together, these data from the general population highlight the potential value of CNP and support the need for additional studies to evaluate whether mechanisms regulating CNP could improve outcomes.

Abstract Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P &lt; 10−5). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk. Cancer Res; 75(12); 2457–67. ©2015 AACR.

Background— In asymptomatic patients with severe aortic stenosis, guidelines recommend left ventricular ejection fraction (LVEF) of <50% as the threshold for referral for aortic valve replacement. We investigated the importance of LVEF on long-term outcome after aortic valve replacement in symptomatic and asymptomatic patients with severe aortic stenosis. Methods and Results— We retrospectively identified 2017 patients with severe aortic stenosis (aortic valve area<1 cm 2 , mean gradient≥40 mm Hg, or indexed aortic valve area<0.6 cm 2 /m 2 ) who underwent surgical aortic valve replacement from January 1995 to June 2009. Patients were divided into 4 groups depending on preoperative LVEF (<50% in 300 [15%] patients, 50%–59% in 331 [17%], 60%–69% in 908 [45%], and ≥70% in 478 [24%]). During follow-up of 5.3±4.4 years, 1056 (52%) patients died. A decrease in mortality was observed with increasing LVEF, P <0.0001; 5-year mortality estimates (95% confidence interval) were 0.41 (0.35–0.47), LVEF<50%; 0.35 (0.29–0.41), LVEF 50% to 59%; 0.26 (0.23–0.29), LVEF 60% to 69%; and 0.22 (0.18–0.26), LVEF≥70%. Compared with patients with LVEF≥60%, patients with LVEF 50% to 59% had increased mortality (hazard ratio [HR], 1.58; P <0.001), with similar risk increase in both symptomatic (HR, 1.56; P <0.001) and asymptomatic patients (HR, 1.58; P =0.006). Correcting for risk factors, LV mass index, aortic valve area, and stroke volume index, LVEF was independently predictive of mortality (HR, 0.88 per 10%; P <0.001). When this analysis was repeated in the subset of 1333 patients without history of coronary artery disease, LVEF remained associated with mortality (HR, 0.90 per 10%; P =0.009). Conclusions— LVEF is a powerful predictor of outcome in patients with severe aortic stenosis undergoing aortic valve replacement, independent of the presence of valve-related symptoms.

Background: A women-based formula for calculation of age-predicted maximum heart rate [age-predicted maximum heart rate=206−(0.88×age)] was established in asymptomatic volunteer women undergoing treadmill exercise tolerance testing (ETT). We sought to perform a comparison of the performance of this women-based formula for prediction of peak heart rate to the traditional formula [220−age] and our own database-generated prediction formula in a large database of women undergoing ETT. Methods: We performed a retrospective analysis of all consecutive women who underwent symptom-limited Bruce protocol ETT at the Mayo Clinic from 1994 to 2010. Women with known cardiovascular disease or those using beta blockers, calcium channel blockers, or digitalis were excluded. Separate analyses were performed according to symptomatic status. Results: The study included 11,029 women (89.4% Caucasian) with a mean age 52±12 years; 3,632 (33%) were referred specifically for evaluation of symptoms. Age-predicted maximum heart rate calculated by the traditional formula was achieved by 49.7% of women versus 69.9% by the women-based formula with most of the underestimation observed in older women. Average absolute deviation between achieved and predicted peak heart rate (HR) was 10.85±9.18 bpm for traditional versus 11.98±9.00 for women-based formulas (dependent t =−16.64, p <0.0001). The linear regression line calculated from our population [HR=201−(0.67×age)] was closer to the women-based formula, both in terms of intercept and slope than the traditional formula. Peak HR was shown to be slightly affected (−2.5 bpm) by symptom status at referral, whereas smoking and diabetes more significantly reduced achieved peak HR. Conclusions: The women-based formula underestimated peak HR, especially in older women, but was observed to be closer in both intercept and slope to the regression line determined from our study in this large population of female patients. These sex-unique observations should be taken into account when determining adequacy and targets for ETT in women.