Citations

Background Although VCAM‐1 (vascular cell adhesion molecule‐1) and ICAM‐1 (intercellular adhesion molecule‐1) have been associated with incident heart failure with preserved ejection fraction (HFpEF) and atrial fibrillation (AF), the associations of VCAM‐1 and ICAM‐1 with sensitive measures of cardiac structure/function are unclear. The objective of this study is to evaluate associations between VCAM‐1, ICAM‐1, and measures of cardiac structure and function as potential pathways through which cellular adhesion molecules promote HFpEF and AF risk. Methods and Results In MESA (Multi‐Ethnic Study of Atherosclerosis), we evaluated the associations of circulating VCAM‐1 and ICAM‐1 at examination 2 (2002–2004) with measures of cardiac structure/function on cardiac magnetic resonance imaging at examination 5 (2010–2011) after multivariable adjustment. Mediation analysis of left atrial (LA) strain on the association between VCAM‐1 or ICAM‐1 and AF or HFpEF was also performed. Overall, 2304 individuals (63±10 years; 47% men) with VCAM‐1 or ICAM‐1, cardiac magnetic resonance imaging, and covariate data were included in analysis. Higher VCAM‐1 and ICAM‐1 were associated with lower LA peak longitudinal strain and worse global circumferential left ventricular strain but were not associated with left ventricular myocardial scar or interstitial fibrosis. Lower LA peak longitudinal strain mediated 8% (95% CI, 2–30) of the relationship between VCAM‐1 and HFpEF and 9% (95% CI, 2–21) of the relationship between VCAM‐1 and AF. Conclusions Higher VCAM‐1 and ICAM‐1 were associated with lower LA function and left ventricular systolic function but were not associated with myocardial scar or interstitial fibrosis. VCAM‐1 and ICAM‐1 may promote HFpEF and AF risk through impaired LA reservoir function.

Abstract Background Accurate assessment of axillary lymph nodes (ALNs) is a critical step for timely diagnosis of metastasis and proper subsequent intervention in breast cancer patients. Herein, we compare the diagnostic utility of quantitative high-definition microvasculature imaging (qHDMI), shear wave elastography (SWE) and their combination for differentiation of metastatic ALNs from reactive. Methods A total of 85 female patients with suspicious ALNs recommended for fine needle aspiration biopsy (FNAB) were included in the study, and the pathology results were used as the gold standard for labeling the status of each ALN. Three SWE metrics and ten qHDMI-derived biomarkers were used in our analyses. Additionally, age, as well as clinical ultrasound features such as nodal size and cortical thickness were included as clinical factors. The Wilcoxon rank-sum test was utilized to analyze distributional differences in biomarkers between metastatic and reactive ALNs. Multiple elastic-net logistic regression models were developed based on varying combinations of clinical, qHDMI, and SWE feature sets. A 70%/30% train/test split was adopted, and ROC curve analyses were performed to evaluate and compare classification performance. Moreover, distributional differences in qHDMI and SWE biomarkers between ALNs corresponding to breast cancer immunohistochemical subtypes luminal A and B were investigated. Results Of the total of 85 ALNs included in the analysis, 42 were metastatic. Statistically significant (p-value < 0.05) differences were observed in all but one of the qHDMI biomarkers, as well as all the SWE metrics. Test-set discrimination defined by area under ROC curve (AUC) was low for the model using only clinical features (0.62; 95% CI = [0.39,0.84]), with higher performance observed for models using SWE only (0.93; [0.82,1.00]), qHDMI only (0.97; [0.91,1.00]), qHDMI-SWE (0.97; [0.92,1.00]), and qHDMI-SWE plus clinical biomarkers (0.98; [0.94,1.00]). No statistically significant improvements were seen in the combined SWE-qHDMI and SWE-qHDMI-C classification models relative to the qHDMI-only model, although power for comparison was limited. Four qHDMI biomarkers and two SWE measures exhibited statistically significant distributions among breast cancer luminal A and B subtypes. Conclusions qHDMI classification model was able to separate metastatic from reactive ALNs with high accuracy. qHDMI, SWE, and the combined models had improved classification performance over the baseline Clinical model. qHDMI biomarkers can be valuable in determining the malignancy status of suspicious ALNs, providing helpful information regarding breast cancer prognosis.

Angiogenesis has an essential role in the de novo evolution of choroidal melanoma as well as choroidal nevus transformation into melanoma. Differentiating early-stage melanoma from nevus is of high clinical importance; thus, imaging techniques that provide objective information regarding tumor microvasculature structures could aid accurate early detection. Herein, we investigated the feasibility of quantitative high-definition microvessel imaging (qHDMI) for differentiation of choroidal tumors in humans. This new ultrasound-based technique encompasses a series of morphological filtering and vessel enhancement techniques, enabling the visualization of tumor microvessels as small as 150 microns and extracting vessel morphological features as new tumor biomarkers. Distributional differences between the malignant melanomas and benign nevi were tested on 37 patients with choroidal tumors using a non-parametric Wilcoxon rank-sum test, and statistical significance was declared for biomarkers with p-values < 0.05. The ocular oncology diagnosis was choroidal melanoma (malignant) in 21 and choroidal nevus (benign) in 15 patients. The mean thickness of benign and malignant masses was 1.70 ± 0.40 mm and 3.81 ± 2.63 mm, respectively. Six HDMI biomarkers, including number of vessel segments (p = 0.003), number of branch points (p = 0.003), vessel density (p = 0.03), maximum tortuosity (p = 0.001), microvessel fractal dimension (p = 0.002), and maximum diameter (p = 0.003) exhibited significant distributional differences between the two groups. Contrast-free HDMI provided noninvasive imaging and quantification of microvessels of choroidal tumors. The results of this pilot study indicate the potential use of qHDMI as a complementary tool for characterization of small ocular tumors and early detection of choroidal melanoma.

Objective CYP2C9 and CYP2C19 are highly polymorphic pharmacogenes that encodes enzymes that metabolize a large number of clinically relevant drugs. While the majority of variability in drug metabolism can be explained by a few common alleles, identification of gene sequence variation that alters enzyme activity and incorporation of that information into pharmacogenomic rules for clinical decision support might lead to improved therapy. Using sequence data derived from the Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment (RIGHT Protocol), we sought to identify variants of unknown significance (VUSs) for CYP2C9 and CYP2C19, and to characterize the function of the encoded enzymes. Methods Targeted next‐generation sequencing for 84 pharmacogenes using the PGRN‐Seq v1.0 capture reagent was performed with DNA samples from 1013 RIGHT Protocol participants. Plasmids containing VUSs were created using site directed mutagenesis and were transiently expressed in COS‐1 cells. Initial determination of enzyme activity was performed using fluorogenic substrates. Enzyme kinetic parameters (Km and Vmax) for each of the variant allozymes were determined using liquid chromatography mass spectrometry with tolbutamide (CYP2C9) and mephenytoin (CYP2C19) as prototypic substrates. We also compared our results with in silico functional predictions by SIFT and Polyphen. Results Seven VUSs were identified for each gene, none of which had been functionally characterized. There were significant positive correlations between protein content and fluorometric enzyme activity for all variants for both CYP2C9 (P<0.05) and CYP2C19 (P<0.005). Notably, CYP2C9 V237L and CYP2C19 A173V activity was much lower than predicted based on protein content. The substrate intrinsic clearance of CYP2C9 variants P73L , S115R , V237L [6.23E‐05±1.08E‐05; 2.55E‐05±4.1E‐06; 7.28E‐05±2.4E‐05 (uL/mg protein/min)], and CYP2C19 variants V113I , A173V , R186C and R186H [2.49E‐04±2.78E‐05; 1.80E‐05±2.19E‐06; 2.33E‐05±9.2E‐06;1.45E‐04±1.2E‐05 (uL/mg protein/min)] were less than 25% of their respective WT enzyme . Conclusion Sequencing of CYP2C9 and CYP2C19 from 1013 subjects identified low frequency variants that had not been functionally characterized. In silico predictions which showed variable results, can be helpful but are not always accurate, hence functional validation is necessary for VUSs requiring protein expression and determination of kinetic parameters. Efforts to identify variation in diverse populations is resulting in a very large number of VUSs, so there is a need for the application of high throughput mutagenesis approaches and functional characterization methods to help pharmacogenomics contribute to precision medicine. Support or Funding Information NIH RO1 GM28157 and the Mayo Center for Individualized Medicine Pharmacogenomics Program.

Mendelian randomization has become a popular tool to assess causal relationships using existing observational data. While randomized controlled trials are considered the gold standard for establishing causality between exposures and outcomes, it is not always feasible to conduct a trial. Mendelian randomization is a causal inference method that uses observational data to infer causal relationships by using genetic variation as a surrogate for the exposure of interest. Publications using the approach have increased dramatically in recent years, including in the field of hepatology. In this concise review, we describe the concepts, assumptions, and interpretation of Mendelian randomization as related to studies in hepatology. We focus on the strengths and weaknesses of the approach for a non-statistical audience, using an illustrative example to assess the causal relationship between body mass index and NAFLD.

Background: Antidepressants are among the most prescribed medications in the United States. The aim of this study was to explore the prevalence of antidepressant prescriptions and investigate sex differences and age-sex interactions in adults enrolled in the Right Drug, Right Dose, Right Time: Using Genomic Data to Individualize Treatment (RIGHT) study. Materials and Methods: We conducted a retrospective analysis of the RIGHT study. Using electronic prescriptions, we assessed 12-month prevalence of antidepressant treatment. Sex differences and age-sex interactions were evaluated using multivariable logistic regression and flexible recursive smoothing splines. Results: The sample consisted of 11,087 participants (60% women). Antidepressant prescription prevalence was 22.24% (27.96% women, 13.58% men). After adjusting for age and enrollment year, women had significantly greater odds of antidepressant prescription (odds ratio = 2.29; 95% confidence interval = 2.07, 2.54). Furthermore, selective serotonin reuptake inhibitors (SSRIs) had a significant age-sex interaction. While SSRI prescriptions in men showed a sustained decrease with age, there was no such decline for women until after reaching ∼50 years of age. There are important limitations to consider in this study. Electronic prescription data were cross-sectional; information on treatment duration or adherence was not collected; this cohort is not nationally representative; and enrollment occurred over a broad period, introducing confounding by changes in temporal prescribing practices. Conclusions: Underscored by the significant interaction between age and sex on odds of SSRI prescription, our results warrant age to be incorporated as a mediator when investigating sex differences in mental illness, especially mood disorders and their treatment.

Background The relationship between mitochondrial DNA copy number (mtDNA CN) and cardiovascular disease remains elusive. Methods and Results We performed cross‐sectional and prospective association analyses of blood‐derived mtDNA CN and cardiovascular disease outcomes in 27 316 participants in 8 cohorts of multiple racial and ethnic groups with whole‐genome sequencing. We also performed Mendelian randomization to explore causal relationships of mtDNA CN with coronary heart disease (CHD) and cardiometabolic risk factors (obesity, diabetes, hypertension, and hyperlipidemia). P <0.01 was used for significance. We validated most of the previously reported associations between mtDNA CN and cardiovascular disease outcomes. For example, 1‐SD unit lower level of mtDNA CN was associated with 1.08 (95% CI, 1.04–1.12; P <0.001) times the hazard for developing incident CHD, adjusting for covariates. Mendelian randomization analyses showed no causal effect from a lower level of mtDNA CN to a higher CHD risk (β=0.091; P =0.11) or in the reverse direction (β=−0.012; P =0.076). Additional bidirectional Mendelian randomization analyses revealed that low‐density lipoprotein cholesterol had a causal effect on mtDNA CN (β=−0.084; P <0.001), but the reverse direction was not significant ( P =0.059). No causal associations were observed between mtDNA CN and obesity, diabetes, and hypertension, in either direction. Multivariable Mendelian randomization analyses showed no causal effect of CHD on mtDNA CN, controlling for low‐density lipoprotein cholesterol level ( P =0.52), whereas there was a strong direct causal effect of higher low‐density lipoprotein cholesterol on lower mtDNA CN, adjusting for CHD status (β=−0.092; P <0.001). Conclusions Our findings indicate that high low‐density lipoprotein cholesterol may underlie the complex relationships between mtDNA CN and vascular atherosclerosis.