Citations

Abstract BackgroundCopy number variants (CNVs) are pervasive in the human genome but potential disease associations with rare CNVs have not been comprehensively assessed in large datasets. We analysed rare CNVs in genes and non-coding regions for 86,788 breast cancer cases and 76,122 controls of European ancestry with genome-wide array data.ResultsGene burden tests detected the strongest association for deletions in BRCA1 (P= 3.7E-18). Nine other genes were associated with a p-value < 0.01 including known susceptibility genes CHEK2 (P= 0.0008), ATM (P= 0.002) and BRCA2 (P= 0.008). Outside the known genes we detected associations with p-values < 0.001 for either overall or subtype-specific breast cancer at nine deletion regions and four duplication regions. Three of the deletion regions were in established common susceptibility loci.ConclusionsThis is the first genome-wide analysis of rare CNVs in a large breast cancer case-control dataset. We detected associations with exonic deletions in established breast cancer susceptibility genes. We also detected suggestive associations with non-coding CNVs in known and novel loci with large effects sizes. Larger sample sizes will be required to reach robust levels of statistical significance.

Background: Cardiovascular disease (CVD) remains the leading cause of death for African-American (AA) adults. There is a low prevalence of ideal cardiovascular health (CVH) (as defined by the American Heart Association’s Life’s Simple 7 TM (LS7)), especially diet, physical activity and obesity among AAs placing them at a disproportionately high risk for CVD. The identification of psychosocial stress that may influence ideal CVH could assist in the development of more effective behavior change interventions among AAs. Objectives: The aim of this study is to examine the associations of multidimensional stressors (chronic stress, minor stressors, and major life events - MLEs) with the LS7 components (classified as poor, intermediate and ideal) in AAs. We hypothesize that stress is negatively associated with the likelihood of achievement of intermediate/ideal levels of the LS7 components and LS7 composite score after adjusting for traditional socio-demographic factors. Methods: Using the Jackson Heart Study (JHS), a cohort of AAs based in Jackson, Mississippi (n=4383), we conducted a cross-sectional analysis of the association of stress measures with LS7 components (smoking, diet, physical activity, body mass index, blood pressure, total cholesterol and glucose). This association was measured using logistic regression which assessed the odds ratios (OR, 95% confidence interval (CI)) of the achievement of intermediate/ideal levels of CVH with progressive adjustment for demographic, socioeconomic, behavioral and biomedical factors. A composite LS7 score was calculated [range 0-14; categorized as 0 to 6 (poor), 7 to 8 (intermediate) and 9 to 14 (ideal)]. We also constructed a cumulative stress score as a summation of tertiles of each stress measure (range 3-9). Results: Fewer participants achieved intermediate or ideal CVH for the LS7 components including diet (39%), physical activity (51%) and BMI (47%). Higher chronic stress and minor stressors scores were associated a decreased likelihood of achievement of ideal/intermediate levels for smoking [OR 0.80; 95% CI 0.73-0.88 and OR 0.84; 95% CI 0.75-0.94, respectively). Higher MLE scores were associated decreased likelihood of achievement of ideal/intermediate levels for smoking (OR 0.84; 95% CI 0.76-0.92) and glucose (OR 0.90; 95% CI 0.82-0.98). Those with higher minor stressors and MLE scores were less likely to achieve intermediate or ideal LS7 composite score categories (OR 0.89; 95% CI 0.81-0.97 and OR 0.91; 95% CI 0.84-0.98, respectively). There was no statistically significant association between LS7 composite scores and cumulative stress scores. Conclusions: Our results suggest that key stress measures may contribute adversely to CVH among AAs. These findings provide support for future lifestyle interventions which integrate a focus on alleviating stressors in this high risk population to improve CVH.

AimsThe diagnosis of focal nodular hyperplasia (FNH) and the interpretation of glutamine synthetase (GS) staining can be challenging on biopsies. We aimed to evaluate the reproducibility of needle biopsy diagnosis of FNH, the effect of GS immunohistochemistry on FNH diagnosis, and which histological features are most useful for the diagnosis of FNH.Methods and resultsThe study included virtual needle biopsies generated from 75 resection specimens (30 FNHs, 15 hepatocellular adenomas, 15 hepatocellular carcinomas, and 15 non‐lesional liver specimens). Pathologists were reasonably accurate (83.1%) in the diagnosis of FNH with haematoxylin and eosin alone. Ductular reaction and nodularity had the highest sensitivity for a diagnosis of FNH (88.1% and 82.2%, respectively), whereas central scar was the most specific feature (90.6%). The presence of two or more of the classic histological features had 89.6% sensitivity and 86.2% specificity for a diagnosis of FNH. Diagnostic accuracy was significantly higher with the addition of a GS stain. A map‐like GS staining pattern was highly specific (99.3%) for FNH. However, GS staining was interpreted as non‐map‐like in 14.4% of reviews of true FNH cases, and overall interobserver agreement for interpretation of the GS staining pattern was only moderate (kappa = 0.42).ConclusionsPathologists are reasonably accurate in the diagnosis of FNH on virtual biopsies, and GS staining improves accuracy. However, a subset of FNH cases remain challenging. Steatosis and a pseudo‐map‐like GS staining pattern were associated with increased difficulty. Therefore, although a map‐like GS staining pattern is useful for confirmation of a diagnosis, the lack of a map‐like GS staining pattern on needle biopsy does not necessarily exclude a diagnosis of FNH.

Statistical analyses are a crucial component of the biomedical research process and are necessary to draw inferences from biomedical research data. The application of sound statistical methodology is a prerequisite for publication in the American Heart Association (AHA) journal portfolio. The objective of this document is to summarize key aspects of statistical reporting that might be most relevant to the authors, reviewers, and readership of AHA journals. The AHA Scientific Publication Committee convened a task force to inventory existing statistical standards for publication in biomedical journals and to identify approaches suitable for the AHA journal portfolio. The experts on the task force were selected by the AHA Scientific Publication Committee, who identified 12 key topics that serve as the section headers for this document. For each topic, the members of the writing group identified relevant references and evaluated them as a resource to make the standards summarized herein. Each section was independently reviewed by an expert reviewer who was not part of the task force. Expert reviewers were also permitted to comment on other sections if they chose. Differences of opinion were adjudicated by consensus. The standards presented in this report are intended to serve as a guide for high-quality reporting of statistical analyses methods and results.

Abstract Background: Use of menopausal hormone therapy (MHT) is associated with increased risk for breast cancer. However, the relevant mechanisms and its interaction with genetic variants are not fully understood. Methods: We conducted a genome-wide interaction analysis between MHT use and genetic variants for breast cancer risk in 27,585 cases and 34,785 controls from 26 observational studies. All women were post-menopausal and of European ancestry. Multivariable logistic regression models were used to test for multiplicative interactions between genetic variants and current MHT use. We considered interaction p-values<5x10-8 as genome-wide significant, and p-values<1x10-5 as suggestive. Linkage disequilibrium (LD)-based clumping was performed to identify independent candidate variants.Results: None of the 9.7 million genetic variants tested for interactions with MHT use reached genome-wide significance. Only 213 variants, representing 18 independent loci, had p-values<1x105. The strongest evidence was found for rs4674019 (p-value=2.27x10-7), which showed genome-wide significant interaction (p-value=3.8x10-8) with current MHT use when analysis was restricted to population-based studies only. Limiting the analyses to combined estrogen-progesterone MHT use only or to estrogen receptor (ER) positive cases did not identify any genome-wide significant evidence of interactions. Conclusions: In this large genome-wide SNP-MHT interaction study of breast cancer, we found no strong support for common genetic variants modifying the effect of MHT on breast cancer risk. These results suggest that common genetic variation has limited impact on the observed MHT–breast cancer risk association.

Abstract Objectives To describe the methodology and implications of the patient‐identified most bothersome symptom (PI‐MBS) measure used in the phase 3, multicenter, randomized, double‐blind, placebo‐controlled, and parallel‐group PROMISE‐2 trial and to evaluate the contribution of this measure to the assessment of the preventive migraine benefits of treatment. Background Although freedom from MBS is a coprimary endpoint in acute migraine treatment trials, its evaluation in preventive migraine trials is limited. The PROMISE‐2 study assessed a unique PI‐MBS measure as a secondary endpoint. Methods This was a secondary analysis of data from the PROMISE‐2 study. Adults with chronic migraine (CM) were randomized to receive intravenous (IV) eptinezumab 100 mg, eptinezumab 300 mg, or placebo, administered on day 0 and every 12 weeks. At the screening visit, patients were asked to verbally describe the MBS associated with their CM; the question format was open ended. At subsequent visits, patients were asked to rate the overall change in severity of their MBS from study inception to that time point, using a 7‐point ordinal scale ranging from “very much worse” (−3) to “very much improved” (+3). Patients completed the Patient Global Impression of Change (PGIC) assessment during the same visits, using an identical rating scale and recall period. Endpoints were summarized descriptively; post hoc correlations using the methodologies of Pearson and Spearman were calculated to evaluate relationships between PGIC and PI‐MBS and between PGIC and mean monthly migraine days (MMDs; primary efficacy endpoint in PROMISE‐2). Results Altogether, 1072 patients received treatment (eptinezumab 100 mg, n = 356; eptinezumab 300 mg, n = 350; placebo, n = 366) and were included in the analysis. There were 23 unique MBS identified; those reported by ≥10 patients included light sensitivity (18.7%), nausea/vomiting (15.1%), pain with activity (13.7%), pain (12.4%), headache (11.2%), sound sensitivity (7.3%), throbbing/pulsating pain (4.7%), cognitive disruption (4.1%), fatigue (2.4%), mood changes (1.5%), and sensitivity to smell (0.9%). Four weeks after the first dose (week 4), the rates of much or very much improvement in PI‐MBS were higher with eptinezumab 100 mg (45%) and 300 mg (57%) than with placebo (29%). Four weeks after the second dose (week 16), the proportions with much or very much improvement in PI‐MBS had increased to 58%, 65%, and 36%, respectively. At each time point, the percentages of patients with PGIC ratings of much or very much improved were similar to those for patient‐reported improvement in PI‐MBS. Patient ratings of changes in PI‐MBS and PGIC correlated strongly across time points (Pearson, r range, 0.83–0.88; Spearman, r range, 0.83–0.89); the absolute value of the correlations was greater than the correlation among changes in MMDs and PGIC (Pearson, r range, −0.49 to −0.52; Spearman, r range, −0.49 to −0.52). Conclusions Among patients with CM in the PROMISE‐2 study, a broad range of PI‐MBS was reported at baseline. Throughout the study, patients treated with eptinezumab reported greater improvement in their PI‐MBS severity compared with placebo recipients, and this improvement correlated strongly with PGIC findings. Collectively, these results indicate that PI‐MBS is a promising and novel outcome measure for preventive trials of CM and thus may provide a unique patient‐centered approach for identifying and measuring the burden of migraine symptoms that matter most to each patient, as well as the benefits of treatment.

AbstractBackgroundNon‐statin lipid lowering therapies (LLTs) provide additional treatment options for patients. Use patterns and patient perceptions of non‐statin LLT remain incompletely described.HypothesisThe guideline‐recommended statin intensity remains underutilized in patients treated with and without non‐statin LLT.MethodsThe PALM Registry collected LLT information on patients with or at risk of ASCVD treated at 125 US clinics in 2015. We compared patient perceptions, lipid levels and statin use among patients treated with and without non‐statin LLT.ResultsAmong 7720 patients, 1930 (25.0%) were treated with a non‐statin LLT (1249 fish oil, 417 fibrates, 329 ezetimibe, 196 niacin). Concurrent statin treatment occurred in 73.7%, of which 45.4% were dosed under the guideline‐recommended intensity. Compared with patients on statin alone, patients receiving both a statin and non‐statin LLT (n = 1423) were more likely to be male, white race and to perceive themselves as higher risk of ASCVD compared with their peers (38.5% vs. 34.9%, p = .047). Only 27.4% of patients treated with non‐statin LLT alone perceived themselves at higher risk. Most (75.7%) patients treated with a non‐statin LLT alone reported never being treated with a statin, despite ASCVD in 30.8% of these patients. Among those previously treated with a statin, 59.3% reported being willing to try a statin again.ConclusionsNon‐statin LLT is used in one in four patients with or at risk for ASCVD; its use is frequently in place of statin therapy or in the absence of guideline‐recommended statin intensity. More work is needed to establish statins as first line therapy.

Background: Prevention strategies for Alzheimer’s disease and Alzheimer’s disease related dementias (AD/ADRDs) are urgently needed for reducing incidence. Intra-patient variability in lipid levels is a potentially modifiable risk factor for incident AD/ADRD. Although regular lipid measurements are a part of common clinical practice and longitudinal data routinely available in electronic health records (EHR), research examining this association between AD/ADRD and lipid variability across multiple lipid types remains scarce. Methods: All residents living in Olmsted County, MN on 1/1/2006 age ≥60 years without an AD/ADRD diagnosis were identified using Centers for Medicare & Medicaid Services diagnostic codes. Persons with ≥3 lipid measurements (total cholesterol or triglycerides) in the 5 years prior to index date were retained. Lipid variability was quantified using variability independent of the mean (VIM). Models were adjusted for traditional risk factors. Associations between lipid variability quintiles and incident AD/ADRD were assessed using Cox proportional hazards regression. Multiple imputation was used for missing covariates. Participants were followed through 2018 for incident AD/ADRD. Results: The final analysis included data on 11,551 participants with total cholesterol and 11,502 participants with triglycerides. Participants had a mean age of 71 (range 60-99) years, and were primarily white (96%). Females (54%) were also slightly more frequent than males. Median follow up was 12.9 years (range: 0-13). Participants in the highest quintile of variability for total cholesterol and triglycerides had a 20% increased risk of incident AD/ADRD. Similar results were found in the subset with complete covariate data. Conclusion: In a large EHR derived cohort, persons in the highest quintile of lipid variation had an increased risk of incident AD/ADRD. Further studies to identify the mechanisms behind this risk factor and replication of these results across a more diverse population are needed.

Background: Larger within-patient variability of lipid levels has been associated with an increased risk of cardiovascular disease (CVD). However, measures of lipid variability are not currently used clinically. We investigated the feasibility of calculating lipid variability within a large electronic health record (EHR)-based population cohort and assessed associations with incident CVD. Methods: We identified all individuals ≥40 years of age who resided in Olmsted County, MN on 1/1/2006 (index date) without prior CVD. CVD was defined as myocardial infarction, coronary artery bypass graft surgery, percutaneous coronary intervention or stroke. Patients with ≥3 measurements of total cholesterol, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and/or triglycerides during the 5 years before the index date were retained in the analyses. Lipid variability was calculated using variability independent of the mean (VIM). Patients were followed through 9/30/2017 for incident CVD (including CVD death). Cox regression was used to investigate the association between quintiles of lipid VIMs and incident CVD. Results: We identified 18,642 individuals (mean age 60; 55% female) who were free of CVD at baseline and VIM calculated for at least one lipid measurement. After adjustment, those in the highest VIM quintiles of total cholesterol had a 25% increased risk of CVD (Q5 vs. Q1 HR: 1.25, 95% CI: 1.08-1.45; Table). We observed similar results for LDL-C (Q5 vs. Q1 HR: 1.20, 95% CI: 1.04-1.39) and HDL-C (Q5 vs. Q1 HR: 1.25, 95% CI: 1.09-1.43). There was no association between triglyceride variability quintiles and CVD risk. Conclusion: In a large EHR-based population cohort, high variability in total cholesterol, HDL-C and LDL-C was associated with an increased risk of CVD, independently of traditional risk factors, suggesting it may be a target for intervention. Lipid variability can be calculated in the EHR environment but more research is needed to determine its clinical utility.