Genetic and environmental determinants of blood pressure:the role of obesity and the autonomic nervous system

Cardiac autonomic dysfunction and obesity may play a role in the development of higher blood pressure, however the underlying physiological mechanisms are not yet fully understood. This thesis aimed to unravel the factors that influence the cardiac autonomic nervous system (ANS) and to determine the genetic and environmental overlap of blood pressure with cardiac ANS and obesity measures in three large population-based databases. First, I found that age and sex were the most important determinants of the cardiac ANS measures, explaining about 16% of the inter-individual differences. We also established reference values across difference age groups and showed that the function of the cardiac ANS declined substantially with age and that women had a better cardiac ANS function than men. Second, I confirmed that all cardiac ANS and obesity indices were heritable and showed that they significantly correlated with blood pressure. Third, we found significant genetic correlations of the cardiac ANS and obesity indices with blood pressure. In conclusion, our work provides robust evidence that blood pressure is genetically correlated with cardiac ANS and obesity which will drive the scientific efforts to identify genes responsible for these shared genetic influences

Heritability and the Genetic Correlation of Heart Rate Variability and Blood Pressure in >29 000 Families The Lifelines Cohort Study:The Lifelines Cohort Study

Dysregulation of the cardiac autonomic nervous system, as indexed by reduced heart rate variability (HRV), has been associated with the development of high blood pressure (BP). However, the underlying pathological mechanisms are not yet fully understood. This study aimed to estimate heritability of HRV and BP and to determine their genetic overlap. We used baseline data of the 3-generation Lifelines population-based cohort study (n=149 067; mean age, 44.5). In-house software was used to calculate root mean square of successive differences and SD of normal-to-normal intervals as indices of HRV based on 10-second resting ECGs. BP was recorded with an automatic BP monitor. We estimated heritabilities and genetic correlations with variance components methods in ASReml software. We additionally estimated genetic correlations with bivariate linkage disequilibrium score regression using publicly available genome-wide association study data. The heritability (SE) estimates were 15.6% (0.90%) for SD of normal-to-normal intervals and 17.9% (0.90%) for root mean square of successive differences. For BP measures, they ranged from 24.4% (0.90%) for pulse pressure to 30.3% (0.90%) for diastolic BP. Significant negative genetic correlations (all P<0.0001) of root mean square of successive differences/SD of normal-to-normal intervals with systolic BP (-0.20/-0.16) and with diastolic BP (-0.15/-0.13) were observed. LD score regression showed largely consistent genetic correlation estimates of root mean square of successive differences/SD of normal-to-normal intervals with systolic BP (range, -0.08 to -0.23) and diastolic BP (range, -0.20 to -0.27). Our study shows a substantial contribution of genetic factors in explaining the variance of HRV and BP measures in the general population. The significant negative genetic correlations between HRV and BP indicate that genetic pathways for HRV and BP partially overlap

Spontaneous baroreflex sensitivity and its association with age, sex, obesity indices and hypertension:a population study

BACKGROUND: Low baroreflex sensitivity (BRS) is an established risk factor for cardiovascular disorders. We investigated determinants of BRS in a large sample from general population. METHODS: In a population-based study (n=901) data were collected on BRS, arm cuff blood pressure (BP) and obesity indices including body mass index (BMI), waist-to-hip ratio (WHR), waist circumference and percentage body fat (%BF). BRS was calculated by spectral analysis software based on continuously recorded spontaneous fluctuations in beat-to-beat finger BP for 10 to 15 minutes. Correlations and multivariable regression analyses were used to test associations of age, sex, obesity indices and hypertension with BRS while considering effects of lifestyle factors (smoking, alcohol consumption and physical activity). RESULTS: In multivariable analysis, age, sex, %BF, and hypertension were independently associated with BRS. BRS decreased with -0.10 (95% confidence interval [CI]: -0.15 to -0.06) ms/mmHg with each year of increase in age. Women had -1.55 (95% CI: -2.28 to -0.73) ms/mmHg lower mean BRS than men. The effects of %BF (per 10% increase) and hypertension on BRS were -0.55 (95% CI: -0.97 to -0.13) ms/mmHg and -1.23 (95% CI: -1.92 to -0.46) ms/mmHg, respectively. There was no evidence of associations between BRS and lifestyle factors. Age, age 2, sex, and their interactions plus %BF and hypertension contributed 16.9% of total variance of BRS. CONCLUSIONS: In this large general population study, we confirm prior findings that age and sex are important factors associated with BRS and find %BF is more strongly related to less favorable BRS levels than BMI

Dynamics Analysis and Fractional-Order Approximate Entropy of Nonlinear Inventory Management Systems

Inventory management is complex nonlinear systems that are affected by various external factors, including course human action and policy. We study the inventory management model under special circumstances and analyse the equilibrium point of the system. The dynamics of the system is analysed by means of the eigenvalue trajectory, bifurcations, chaotic attractor, and largest Lyapunov exponent diagram. At the same time, according to the definition of fractional calculus, the fractional approximate entropy is used to analyse the system, and the results are consistent with those of the largest Lyapunov exponent diagram, which shows the effectiveness of this method

B-Bi2O3 and Er3+ doped B-Bi2O3 single crystalline nanosheets with exposed reactive {001} facets and enhanced photocatalytic performance

Upconverter Er3+ doped B-Bi2O3 nanosheets with selectively exposed reactive {001} facets as the main external surfaces were fabricated by a novel and simple approach for the first time. The products were characterized by X-ray powder diffraction, transmission electron microscopy, high-resolution transmission electron microscopy and UV-vis diffuse reflectance spectroscopy. The introduction of 0.8wt per cent Er3+ significantly improved the photocatalytic activities of the B-Bi2O3. The enhanced photocatalytic activity of B-Bi2O3 nanosheets can be attributed to the exposed reactive {001} facets and the dopant Er3+ which can transform visible light into ultraviolet light. Both the acetic acid and alcohol contributed to the formation of nanosheets. This synthetic approach exhibited good versatility in fabricating other porous materials. 2013 Elsevier B.V

Model-based clustering of high-dimensional data: Variable selection versus facet determination

Variable selection is an important problem for cluster analysis of high-dimensional data. It is also a difficult one. The difficulty originates not only from the lack of class information but also the fact that high-dimensional data are often multifaceted and can be meaningfully clustered in multiple ways. In such a case the effort to find one subset of attributes that presumably gives the "best" clustering may be misguided. It makes more sense to identify various facets of a data set (each being based on a subset of attributes), cluster the data along each one, and present the results to the domain experts for appraisal and selection. In this paper, we propose a generalization of the Gaussian mixture models and demonstrate its ability to automatically identify natural facets of data and cluster data along each of those facets simultaneously. We present empirical results to show that facet determination usually leads to better clustering results than variable selection. (C) 2012 Elsevier Inc. All rights reserved