The Incidence and Cost of New Onset Hyperlipidemia Claims Among US Wait-Listed and Transplanted Renal Allograft Recipients

Background: Hyperlipidemia increases mortality and is common with kidney-disease. New-onset hyperlipidemia (NOHL) among patients wait-listed and after transplantation may impact costs and graft-survival of patients with kidney disease. Methods: Using the United States Renal Data System, we compared the costs to Medicare associated with or without NOHL in wait-listed patients in the second and first year pre-transplant and transplanted patients in the first and second year post-transplant. We also examined the impact on graft-survival of NOHL. Results: New onset hyperlipidemia was especially expensive when it occurred well before transplantation. When compared with individuals with no hyperlipidemia, patients with early onset hyperlipidemia cost an extra $15,228 in the two years before transplantation and an extra$14,673 in the two years following transplantation. As has been found in prior studies, patients without any NOHL had the worst graft survival rates. Conclusions: Although NOHL was associated with increased pre- and post-transplant costs, patients diagnosed with NOHL between the second year before and second year after transplantation experienced higher graft-survival rates than those without NOHL by 2-years post-transplantation. Prior studies attribute this relationship to inflammation and malnutrition, which result in lower cholesterol levels and worse outcomes

An emerging Panton–Valentine leukocidin-positive CC5-meticillin-resistant Staphylococcus aureus-IVc clone recovered from hospital and community settings over a 17-year period from 12 countries investigated by whole-genome sequencing

Background: A novel Panton–Valentine leukocidin (PVL)-positive meticillin-resistant Staphylococcus aureus (MRSA) clonal complex (CC)5-MRSA-IVc (‘Sri Lankan’ clone) was recently described from Sri Lanka. Similar isolates caused a recent Irish hospital outbreak. Aim: To investigate the international dissemination and diversity of PVL-positive CC5-MRSA-IVc isolates from hospital and community settings using whole-genome sequencing (WGS). Methods: Core-genome single nucleotide polymorphism (cgSNP) analysis, core-genome multi-locus sequence typing (cgMLST) and microarray-based detection of antimicrobial-resistance and virulence genes were used to investigate PVL-positive CC5-MRSA-IVc (N = 214 including 46 ‘Sri Lankan’ clone) from hospital and community settings in 12 countries over 17 years. Comparators included 29 PVL-positive and 23 PVL-negative CC5/ST5-MRSA-I/II/IVa/IVc/IVg/V. Results: Maximum-likelihood cgSNP analysis grouped 209/214 (97.7%) CC5-MRSA-IVc into Clade I; average of 110 cgSNPs between isolates. Clade III contained the five remaining CC5-MRSA-IVc; average of 92 cgSNPs between isolates. Clade II contained seven PVL-positive CC5-MRSA-IVa comparators, whereas the remaining 45 comparators formed an outlier group. Minimum-spanning cgMLST analysis revealed a comparably low average of 57 allelic differences between all CC5/ST5-MRSA-IVc. All 214 CC5/ST5-MRSA-IVc were identified as ‘Sri Lankan’ clone, predominantly spa type t002 (186/214) with low population diversity and harboured a similar range of virulence genes and variable antimicrobial-resistance genes. All 214 Sri Lankan clone isolates and Clade II comparators harboured a 9616-bp chromosomal PVL-encoding phage remnant, suggesting both arose from a PVL-positive meticillin-susceptible ancestor. Over half of Sri Lankan clone isolates were from infections (142/214), and where detailed metadata were available (168/214), most were community associated (85/168). Conclusions: Stable chromosomal retention of pvl may facilitate Sri-Lankan clone dissemination

Genome‐wide association study of INDELs identified four novel susceptibility loci associated with lung cancer risk

Genome‐wide association studies (GWAS) have identified 45 susceptibility loci associated with lung cancer. Only less than SNPs, small insertions and deletions (INDELs) are the second most abundant genetic polymorphisms in the human genome. INDELs are highly associated with multiple human diseases, including lung cancer. However, limited studies with large‐scale samples have been available to systematically evaluate the effects of INDELs on lung cancer risk. Here, we performed a large‐scale meta‐analysis to evaluate INDELs and their risk for lung cancer in 23,202 cases and 19,048 controls. Functional annotations were performed to further explore the potential function of lung cancer risk INDELs. Conditional analysis was used to clarify the relationship between INDELs and SNPs. Four new risk loci were identified in genome‐wide INDEL analysis (1p13.2: rs5777156, Insertion, OR = 0.92, P = 9.10 × 10−8; 4q28.2: rs58404727, Deletion, OR = 1.19, P = 5.25 × 10−7; 12p13.31: rs71450133, Deletion, OR = 1.09, P = 8.83 × 10−7; and 14q22.3: rs34057993, Deletion, OR = 0.90, P = 7.64 × 10−8). The eQTL analysis and functional annotation suggested that INDELs might affect lung cancer susceptibility by regulating the expression of target genes. After conducting conditional analysis on potential causal SNPs, the INDELs in the new loci were still nominally significant. Our findings indicate that INDELs could be potentially functional genetic variants for lung cancer risk. Further functional experiments are needed to better understand INDEL mechanisms in carcinogenesis

Irbesartan in Marfan syndrome (AIMS): a double-blind, placebo-controlled randomised trial

BACKGROUND: Irbesartan, a long acting selective angiotensin-1 receptor inhibitor, in Marfan syndrome might reduce aortic dilatation, which is associated with dissection and rupture. We aimed to determine the effects of irbesartan on the rate of aortic dilatation in children and adults with Marfan syndrome. METHODS: We did a placebo-controlled, double-blind randomised trial at 22 centres in the UK. Individuals aged 6-40 years with clinically confirmed Marfan syndrome were eligible for inclusion. Study participants were all given 75 mg open label irbesartan once daily, then randomly assigned to 150 mg of irbesartan (increased to 300 mg as tolerated) or matching placebo. Aortic diameter was measured by echocardiography at baseline and then annually. All images were analysed by a core laboratory blinded to treatment allocation. The primary endpoint was the rate of aortic root dilatation. This trial is registered with ISRCTN, number ISRCTN90011794. FINDINGS: Between March 14, 2012, and May 1, 2015, 192 participants were recruited and randomly assigned to irbesartan (n=104) or placebo (n=88), and all were followed for up to 5 years. Median age at recruitment was 18 years (IQR 12-28), 99 (52%) were female, mean blood pressure was 110/65 mm Hg (SDs 16 and 12), and 108 (56%) were taking β blockers. Mean baseline aortic root diameter was 34·4 mm in the irbesartan group (SD 5·8) and placebo group (5·5). The mean rate of aortic root dilatation was 0·53 mm per year (95% CI 0·39 to 0·67) in the irbesartan group compared with 0·74 mm per year (0·60 to 0·89) in the placebo group, with a difference in means of -0·22 mm per year (-0·41 to -0·02, p=0·030). The rate of change in aortic Z score was also reduced by irbesartan (difference in means -0·10 per year, 95% CI -0·19 to -0·01, p=0·035). Irbesartan was well tolerated with no observed differences in rates of serious adverse events. INTERPRETATION: Irbesartan is associated with a reduction in the rate of aortic dilatation in children and young adults with Marfan syndrome and could reduce the incidence of aortic complications

Fine-Scale Mapping of the 5q11.2 Breast Cancer Locus Reveals at Least Three Independent Risk Variants Regulating MAP3K1

Peer reviewe

Identification of independent association signals and putative functional variants for breast cancer risk through fine-scale mapping of the 12p11 locus.

BACKGROUND: Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk. METHOD: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/ ), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation. RESULTS: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 × 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 × 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 × 10(-4)) identified in the general populations, and rs113824616 (P = 7 × 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P < 0.05 in East Asians, but none of the associations were statistically significant in African descendants. Multiple candidate functional variants are located in putative enhancer sequences. Chromatin interaction data suggested that PTHLH was the likely target gene of these enhancers. Of the six variants with the strongest evidence of potential functionality, rs11049453 was statistically significantly associated with the expression of PTHLH and its nearby gene CCDC91 at P < 0.05. CONCLUSION: This study identified four independent association signals at 12p11 and revealed potentially functional variants, providing additional insights into the underlying biological mechanism(s) for the association observed between variants at 12p11 and breast cancer risk.UK funding includes Cancer Research UK and NIH.This is the final version of the article. It first appeared from BioMed Central via http://dx.doi.org/10.1186/s13058-016-0718-

Impact of individual level uncertainty of lung cancer polygenic risk score (PRS) on risk stratification

Background Although polygenic risk score (PRS) has emerged as a promising tool for predicting cancer risk from genome-wide association studies (GWAS), the individual-level accuracy of lung cancer PRS and the extent to which its impact on subsequent clinical applications remains largely unexplored. Methods Lung cancer PRSs and confidence/credible interval (CI) were constructed using two statistical approaches for each individual: (1) the weighted sum of 16 GWAS-derived significant SNP loci and the CI through the bootstrapping method (PRS-16-CV) and (2) LDpred2 and the CI through posteriors sampling (PRS-Bayes), among 17,166 lung cancer cases and 12,894 controls with European ancestry from the International Lung Cancer Consortium. Individuals were classified into different genetic risk subgroups based on the relationship between their own PRS mean/PRS CI and the population level threshold. Results Considerable variances in PRS point estimates at the individual level were observed for both methods, with an average standard deviation (s.d.) of 0.12 for PRS-16-CV and a much larger s.d. of 0.88 for PRS-Bayes. Using PRS-16-CV, only 25.0% of individuals with PRS point estimates in the lowest decile of PRS and 16.8% in the highest decile have their entire 95% CI fully contained in the lowest and highest decile, respectively, while PRS-Bayes was unable to find any eligible individuals. Only 19% of the individuals were concordantly identified as having high genetic risk (> 90th percentile) using the two PRS estimators. An increased relative risk of lung cancer comparing the highest PRS percentile to the lowest was observed when taking the CI into account (OR = 2.73, 95% CI: 2.12–3.50, P-value = 4.13 × 10−15) compared to using PRS-16-CV mean (OR = 2.23, 95% CI: 1.99–2.49, P-value = 5.70 × 10−46). Improved risk prediction performance with higher AUC was consistently observed in individuals identified by PRS-16-CV CI, and the best performance was achieved by incorporating age, gender, and detailed smoking pack-years (AUC: 0.73, 95% CI = 0.72–0.74). Conclusions Lung cancer PRS estimates using different methods have modest correlations at the individual level, highlighting the importance of considering individual-level uncertainty when evaluating the practical utility of PRS

Iam hiQ—a novel pair of accuracy indices for imputed genotypes

Background Imputation of untyped markers is a standard tool in genome-wide association studies to close the gap between directly genotyped and other known DNA variants. However, high accuracy with which genotypes are imputed is fundamental. Several accuracy measures have been proposed and some are implemented in imputation software, unfortunately diversely across platforms. In the present paper, we introduce Iam hiQ, an independent pair of accuracy measures that can be applied to dosage files, the output of all imputation software. Iam (imputation accuracy measure) quantifies the average amount of individual-specific versus population-specific genotype information in a linear manner. hiQ (heterogeneity in quantities of dosages) addresses the inter-individual heterogeneity between dosages of a marker across the sample at hand. Results Applying both measures to a large case–control sample of the International Lung Cancer Consortium (ILCCO), comprising 27,065 individuals, we found meaningful thresholds for Iam and hiQ suitable to classify markers of poor accuracy. We demonstrate how Manhattan-like plots and moving averages of Iam and hiQ can be useful to identify regions enriched with less accurate imputed markers, whereas these regions would by missed when applying the accuracy measure info (implemented in IMPUTE2). Conclusion We recommend using Iam hiQ additional to other accuracy scores for variant filtering before stepping into the analysis of imputed GWAS data