Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease

We performed a meta-analysis of 14 genome-wide association studies of coronary artery disease (CAD) comprising 22,233 individuals with CAD (cases) and 64,762 controls of European descent followed by genotyping of top association signals in 56,682 additional individuals. This analysis identified 13 loci newly associated with CAD at P < 5 × 10?? and confirmed the association of 10 of 12 previously reported CAD loci. The 13 new loci showed risk allele frequencies ranging from 0.13 to 0.91 and were associated with a 6% to 17% increase in the risk of CAD per allele. Notably, only three of the new loci showed significant association with traditional CAD risk factors and the majority lie in gene regions not previously implicated in the pathogenesis of CAD. Finally, five of the new CAD risk loci appear to have pleiotropic effects, showing strong association with various other human diseases or traits.     

Common variants in ZNF365 are associated with both mammographic density and breast cancer risk

High-percent mammographic density adjusted for age and body mass index is one of the strongest risk factors for breast cancer. We conducted a meta analysis of five genome-wide association studies of percent mammographic density and report an association with rs10995190 in ZNF365 (combined P = 9.6 × 10(-10)). Common variants in ZNF365 have also recently been associated with susceptibility to breast cancer.     

Genome-wide association study identifies a locus at 7p15.2 associated with endometriosis

Endometriosis is a common gynecological disease associated with pelvic pain and subfertility. We conducted a genome-wide association study (GWAS) in 3,194 individuals with surgically confirmed endometriosis (cases) and 7,060 controls from Australia and the UK. Polygenic predictive modeling showed significantly increased genetic loading among 1,364 cases with moderate to severe endometriosis. The strongest association signal was on 7p15.2 (rs12700667) for 'all' endometriosis (P = 2.6 × 10??, odds ratio (OR) = 1.22, 95% CI 1.13-1.32) and for moderate to severe disease (P = 1.5 × 10??, OR = 1.38, 95% CI 1.24-1.53). We replicated rs12700667 in an independent cohort from the United States of 2,392 self-reported, surgically confirmed endometriosis cases and 2,271 controls (P = 1.2 × 10?3, OR = 1.17, 95% CI 1.06-1.28), resulting in a genome-wide significant P value of 1.4 × 10?? (OR = 1.20, 95% CI 1.13-1.27) for 'all' endometriosis in our combined datasets of 5,586 cases and 9,331 controls. rs12700667 is located in an intergenic region upstream of the plausible candidate genes NFE2L3 and HOXA10.     

Meta-analysis of genome-wide association studies identifies common variants associated with blood pressure variation in east Asians

We conducted a meta-analysis of genome-wide association studies of systolic (SBP) and diastolic (DBP) blood pressure in 19,608 subjects of east Asian ancestry from the AGEN-BP consortium followed up with de novo genotyping (n = 10,518) and further replication (n = 20,247) in east Asian samples. We identified genome-wide significant (P < 5 × 10(-8)) associations with SBP or DBP, which included variants at four new loci (ST7L-CAPZA1, FIGN-GRB14, ENPEP and NPR3) and a newly discovered variant near TBX3. Among the five newly discovered variants, we obtained significant replication in the independent samples for all of these loci except NPR3. We also confirmed seven loci previously identified in populations of European descent. Moreover, at 12q24.13 near ALDH2, we observed strong association signals (P = 7.9 × 10(-31) and P = 1.3 × 10(-35) for SBP and DBP, respectively) with ethnic specificity. These findings provide new insights into blood pressure regulation and potential targets for intervention.     

Germline mutations in RAD51D confer susceptibility to ovarian cancer

Recently, RAD51C mutations were identified in families with breast and ovarian cancer. This observation prompted us to investigate the role of RAD51D in cancer susceptibility. We identified eight inactivating RAD51D mutations in unrelated individuals from 911 breast-ovarian cancer families compared with one inactivating mutation identified in 1,060 controls (P = 0.01). The association found here was principally with ovarian cancer, with three mutations identified in the 59 pedigrees with three or more individuals with ovarian cancer (P = 0.0005). The relative risk of ovarian cancer for RAD51D mutation carriers was estimated to be 6.30 (95% CI 2.86-13.85, P = 4.8 × 10(-6)). By contrast, we estimated the relative risk of breast cancer to be 1.32 (95% CI 0.59-2.96, P = 0.50). These data indicate that RAD51D mutation testing may have clinical utility in individuals with ovarian cancer and their families. Moreover, we show that cells deficient in RAD51D are sensitive to treatment with a PARP inhibitor, suggesting a possible therapeutic approach for cancers arising in RAD51D mutation carriers.     

Dynamic harmonic regression

This paper describes in detail a flexible approach to nonstationary time series analysis based on a Dynamic Harmonic Regression (DHR) model of the Unobserved Components (UC) type, formulated within a stochastic state space setting. The model is particularly useful for adaptive seasonal adjustment, signal extraction and interpolation over gaps, as well as forecasting or backcasting. The Kalman Filter and Fixed Interval Smoothing algorithms are exploited for estimating the various components, with the Noise Variance Ratio and other hyperparameters in the stochastic state space model estimated by a novel optimization method in the frequency domain. Unlike other approaches of this general type, which normally exploit Maximum Likelihood methods, this optimization procedure is based on a cost function defined in terms of the difference between the logarithmic pseudo‐spectrum of the DHR model and the logarithmic autoregressive spectrum of the time series. The cost function not only seems to yield improved convergence characteristics when compared with the alternative ML cost function, but it also has much reduced numerical requirements. Copyright © 1999 John Wiley & Sons, Ltd.     

eIF2A,an initiator tRNA carrier refractory to eIF2α kinases,functions synergistically with eIF5B

The initiator tRNA (Met-tRNA _i ^Met ) at the P site of the small ribosomal subunit plays an important role in the recognition of an mRNA start codon. In bacteria, the initiator tRNA carrier, IF2, facilitates the positioning of Met-tRNA _i ^Met on the small ribosomal subunit. Eukarya contain the Met-tRNA _i ^Met carrier, eIF2 (unrelated to IF2), whose carrier activity is inhibited under stress conditions by the phosphorylation of its α-subunit by stress-activated eIF2α kinases. The stress-resistant initiator tRNA carrier, eIF2A, was recently uncovered and shown to load Met-tRNA _i ^Met on the 40S ribosomal subunit associated with a stress-resistant mRNA under stress conditions. Here, we report that eIF2A interacts and functionally cooperates with eIF5B (a homolog of IF2), and we describe the functional domains of eIF2A that are required for its binding of Met-tRNA _i ^Met , eIF5B, and a stress-resistant mRNA. The results indicate that the eukaryotic eIF5B–eIF2A complex functionally mimics the bacterial IF2 containing ribosome-, GTP-, and initiator tRNA-binding domains in a single polypeptide.     

Molecular cloning of cDNA for murine interleukin-3

The cDNA sequence for murine interleukin-3, one of the colony stimulating factors that regulate haematopoiesis, codes for a polypeptide of 166 amino acids including a putative signal peptide. The predicted amino acid sequence indicates that formation of mature interleukin-3 involves proteolytic removal of not only the signal peptide but additional amino-terminal amino acids.     

Robust seasonal adjustment by Bayesian modelling

Akaike's BAYSEA approach to seasonal decomposition is designed to capture the respective merits of several pre-existing adjustment techniques. BAYSEA is computationally efficient, requires only weak assumptions about the data-generating process, and is based on solid inferential (namely, Bayesian) foundations. We present a model similar to that used in BAYSEA, but based on a double exponential rather than a Gaussian error model. The resulting procedure has the advantages of Akaike's method, but in addition is resistant to outliers. The optimal decomposition is obtained rapidly using a sparse linear programming code. Confidence bands and predictive intervals can be obtained using Gibbs sampling.