Assessing the sensitivity of regression results to unmeasured confounders in observational studies

This paper presents a general approach for assessing the sensitivity of the point and interval estimates of the primary exposure effect in an observational study to the residual confounding effects of unmeasured variables after adjusting for measured covariates. The proposed method assumes that the true exposure effect can be represented in a regression model that includes the exposure indicator as well as the measured and unmeasured confounders. One can use the corresponding reduced model that omits the unmeasured confounder to make statistical inferences about the true exposure effect by specifying the distributions of the unmeasured confounder in the exposed and unexposed groups along with the effects of the unmeasured confounder on the outcome variable. Under certain conditions, there exists a simple algebraic relationship between the true exposure effect in the full model and the apparent exposure effect in the reduced model. One can then estimate the true exposure effect by making a simple adjustment to the point and interval estimates of the apparent exposure effect obtained from standard software or published reports. The proposed method handles both binary response and censored survival time data, accommodates any study design, and allows the unmeasured confounder to be discrete or normally distributed. We describe applications to two major medical studies

Digital Drugs: an anatomy of new medicines

Medicines are digitalized as aspects of their regulation and use are embodied in or draw from interlinked computerized systems and databases. This paper considers how this development changes the delivery of health care, the pharma industry, and regulatory and professional structures, as it reconfigures the material character of drugs themselves. It draws on the concept of assemblage in presenting a theory-based analysis that explores digital drugs’ ontological status including how they embody benefit and value. The paper addresses three interconnected domains – that of use of drugs (practice), of research (epistemology) and of regulation (structures)

Large-scale pharmacogenomic study of sulfonylureas and the QT, JT and QRS intervals: CHARGE Pharmacogenomics Working Group

Sulfonylureas, a commonly used class of medication used to treat type 2 diabetes, have been associated with an increased risk of cardiovascular disease. Their effects on QT interval duration and related electrocardiographic phenotypes are potential mechanisms for this adverse effect. In 11 ethnically diverse cohorts that included 71 857 European, African-American and Hispanic/Latino ancestry individuals with repeated measures of medication use and electrocardiogram (ECG) measurements, we conducted a pharmacogenomic genome-wide association study of sulfonylurea use and three ECG phenotypes: QT, JT and QRS intervals. In ancestry-specific meta-analyses, eight novel pharmacogenomic loci met the threshold for genome-wide significance (P<5 × 10−8), and a pharmacokinetic variant in CYP2C9 (rs1057910) that has been associated with sulfonylurea-related treatment effects and other adverse drug reactions in previous studies was replicated. Additional research is needed to replicate the novel findings and to understand their biological basis

Novel gene variants predict serum levels of the cytokines IL-18 and IL-1ra in older adults

Activation of inflammatory pathways measured by serum inflammatory markers such as interleukin-18 (IL-18) and interleukin-1 receptor antagonist (IL-1ra) is strongly associated with the progression of chronic disease states in older adults. Given that these serum cytokine levels are in part a heritable trait, genetic variation may predict increased serum levels. Using the Cardiovascular Health Study and InCHIANTI cohorts, a genome-wide association study was performed to identify genetic variants that influence IL18 and IL-1ra serum levels among older adults. Multiple linear regression models characterized the association between each SNP and log-transformed cytokine values. Tests for multiple independent signals within statistically significant loci were performed using haplotype analysis and regression models conditional on lead SNP in each region. Multiple SNPs were associated with these cytokines with genome-wide significance, including SNPs in the IL18-BCO gene region of chromosome 2 for IL-18 (top SNP rs2250417, P = 1.9×10−32) and in the IL1 gene family region of chromosome 2 for IL-1ra (rs6743376, P = 2.3×10−26). Haplotype tests and conditional linear regression models showed evidence of multiple independent signals in these regions. Serum IL-18 levels were also associated with a region on chromosome 2 containing the NLRC4 gene (rs12989936, P = 2.7×10−19). These data characterize multiple robust genetic signals that influence IL-18 and IL-1ra cytokine production. In particular, the signal for serum IL-18 located on chromosome two is novel and potentially important in inflammasome triggered chronic activation of inflammation in older adults. Replication in independent cohorts is an important next step, as well as molecular studies to better understand the role of NLRC4

Orthostatic hypotension and novel blood pressure-associated gene variants: Genetics of Postural Hemodynamics (GPH) Consortium

Aims Orthostatic hypotension (OH), an independent predictor of mortality and cardiovascular events, strongly correlates with hypertension. Recent genome-wide studies have identified new loci influencing blood pressure (BP) in populations, but their impact on OH remains unknown. Methods and resultsA total of 38 970 men and women of European ancestry from five population-based cohorts were included, of whom 2656 (6.8) met the diagnostic criteria for OH (systolic/diastolic BP drop <20/10 mmHg within 3 min of standing). Thirty-one recently discovered BP-associated single nucleotide polymorphisms (SNPs) were examined using an additive genetic model and the major allele as referent. Relations between OH, orthostatic systolic BP response, and genetic variants were assessed by inverse variance-weighted meta-analysis. We found Bonferroni adjusted (P < 0.0016) significant evidence for association between OH and the EBF1 locus (rs11953630, per-minor-allele odds ratio, 95 confidence interval: 0.90, 0.850.96; P=0.001), and nominal evidence (P < 0.05) for CYP17A1 (rs11191548: 0.85, 0.750.95; P=0.005), and NPR3-C5orf23 (rs1173771: 0.92, 0.870.98; P=0.009) loci. Among subjects not taking BP-lowering drugs, three SNPs within the NPPA/NPPB locus were nominally associated with increased risk of OH (rs17367504: 1.13, 1.021.24; P=0.02, rs198358: 1.10, 1.011.20; P=0.04, and rs5068: 1.22, 1.041.43; P=0.01). Moreover, an ADM variant was nominally associated with continuous orthostatic systolic BP response in the adjusted model (P=0.04). ConclusionThe overall association between common gene variants in BP loci and OH was generally weak and the direction of effect inconsistent with resting BP findings. These results suggest that OH and resting BP share few genetic components