Association of common variants in NPPA and NPPB with circulating natriuretic peptides and blood pressure

We examined the association of common variants at the NPPA-NPPB locus with circulating concentrations of the natriuretic peptides, which have blood pressure-lowering properties. We genotyped SNPs at the NPPA-NPPB locus in 14,743 individuals of European ancestry, and identified associations of plasma atrial natriuretic peptide with rs5068 (P = 8 × 10 -70), rs198358 (P = 8 × 10 -30) and rs632793 (P = 2 × 10 -10), and of plasma B-type natriuretic peptide with rs5068 (P = 3 × 10 -12), rs198358 (P = 1 × 10 -25) and rs632793 (P = 2 × 10 -68). In 29,717 individuals, the alleles of rs5068 and rs198358 that showed association with increased circulating natriuretic peptide concentrations were also found to be associated with lower systolic (P = 2 × 10 -6 and 6 × 10 -5, respectively) and diastolic blood pressure (P = 1 × 10 -6 and 5 × 10 -5), as well as reduced odds of hypertension (OR = 0.85, 95% CI = 0.79-0.92, P = 4 × 10 -5; OR = 0.90, 95% CI = 0.85-0.95, P = 2 × 10 -4, respectively). Common genetic variants at the NPPA-NPPB locus found to be associated with circulating natriuretic peptide concentrations contribute to interindividual variation in blood pressure and hypertension.

Value-oriented impact assessment: the economics of a new approach to impact assessment

Environmental Impact Assessment has gained a prominent position as a tool to evaluate the environmental effects of economic activities. However, all approaches proposed so far use a burden-oriented logic. They concentrate on the different environmental impacts in order to ascertain the overall environmental damage caused by economic activity. This paper argues that such a burden-oriented view is (a) hampered by a series of methodological shortcomings which hinders its widespread use in practice; and (b) is analytically incomplete. The paper proposes a value-oriented approach to impact assessment. For this purpose an economic analysis of the optimal use of environmental and social resources is conducted from both a burden-oriented and a value-oriented standpoint. The basic logic of a value-oriented impact assessment is explained, as well as the resulting economic conditions for an optimal use of resources. In addition, it is shown that value- and burden-oriented approaches are complementary to achieve optimality. Finally, the paper discusses the conditions under which the use of burden- or value-oriented impact assessments is appropriate, respectively.

Contribution of 30 Biomarkers to 10-year cardiovascular risk estimation in 2 population cohorts: The MONICA, risk, genetics, archiving and monograph (MORGAM) biomarker project

Background— Cardiovascular risk estimation by novel biomarkers needs assessment in disease-free population cohorts, followed up for incident cardiovascular events, assaying the serum and plasma archived at baseline. We report results from 2 cohorts in such a continuing study.<br/>Methods and Results— Thirty novel biomarkers from different pathophysiological pathways were evaluated in 7915 men and women of the FINRISK97 population cohort with 538 incident cardiovascular events at 10 years (fatal or nonfatal coronary or stroke events), from which a biomarker score was developed and then validated in the 2551 men of the Belfast Prospective Epidemiological Study of Myocardial Infarction (PRIME) cohort (260 events). No single biomarker consistently improved risk estimation in FINRISK97 men and FINRISK97 women and the Belfast PRIME Men cohort after allowing for confounding factors; however, the strongest associations (with hazard ratio per SD in FINRISK97 men) were found for N-terminal pro-brain natriuretic peptide (1.23), C-reactive protein (1.23), B-type natriuretic peptide (1.19), and sensitive troponin I (1.18). A biomarker score was developed from the FINRISK97 cohort with the use of regression coefficients and lasso methods, with selection of troponin I, C-reactive protein, and N-terminal pro-brain natriuretic peptide. Adding this score to a conventional risk factor model in the Belfast PRIME Men cohort validated it by improved c-statistics (P=0.004) and integrated discrimination (P<0.0001) and led to significant reclassification of individuals into risk categories (P=0.0008).<br/>Conclusions— The addition of a biomarker score including N-terminal pro-brain natriuretic peptide, C-reactive protein, and sensitive troponin I to a conventional risk model improved 10-year risk estimation for cardiovascular events in 2 middle-aged European populations. Further validation is needed in other populations and age groups.

Revealing differences in gene network inference algorithms on the network level by ensemble methods

Motivation: The inference of regulatory networks from large-scale expression data holds great promise because of the potentially causal interpretation of these networks. However, due to the difficulty to establish reliable methods based on observational data there is so far only incomplete knowledge about possibilities and limitations of such inference methods in this context.<br/><br/>Results: In this article, we conduct a statistical analysis investigating differences and similarities of four network inference algorithms, ARACNE, CLR, MRNET and RN, with respect to local network-based measures. We employ ensemble methods allowing to assess the inferability down to the level of individual edges. Our analysis reveals the bias of these inference methods with respect to the inference of various network components and, hence, provides guidance in the interpretation of inferred regulatory networks from expression data. Further, as application we predict the total number of regulatory interactions in human B cells and hypothesize about the role of Myc and its targets regarding molecular information processing.