Citations

Introduction: Fibromuscular dysplasia (FMD) is a non-atherosclerotic arteriopathy of unknown etiology, afflicting mostly middle-aged women. It is characterized by stenotic lesions of the vascular wall in middle-size arteries, sometimes associated with dissection, aneurysm or tortuosity. Renovascular hypertension is a major presentation of FMD and 50–85% of FMD patients are hypertensive. Methods & Results: We report results from the first genome-wide association meta-analysis of six studies including 1556 FMD cases and 7100 controls. We identified four robustly associated loci (PHACTR1, LRP1, ATP2B1, and LIMA1). Using colocalization and transcriptome-wide association analysis with arterial expression datasets, we found PHACTR1, LRP1 and ATP2B1 as target genes at FMD loci and identified one additional locus (SLC24A3). We analysed chromatin accessibility in artery-derived primary cells and found that FMD associated variants were located in arterial specific regulatory elements active in smooth muscle cells. Target genes were broadly involved in mechanisms related to actin cytoskeleton and intracellular calcium homeostasis, central to vascular contraction. All FMD loci were also associated to at least one blood pressure trait. Colocalization analysis supported the same genetic variants to cause association to FMD and systolic blood pressure at PHACTR1, ATP2B1 and LIMA1 loci, and for FMD and pulse pressure at PHACTR1, LRP1 and ATP2B1 loci. Using genome-wide genetic correlation, we found a significant association between FMD and blood pressure. Mendelian Randomization analysis supported genetically determined systolic blood pressure to significantly increase the risk of FMD. However, we confirmed using adjusted and stratified analyses that hypertension status alone was not driving the association with FMD at top loci. We also report an important genetic overlap of FMD with migraine, intracranial aneurysm, coronary artery disease and myocardial infarction. Conclusion: Our study confirms FMD as a polygenic disease following a complex genetic mode of inheritance. We find that FMD shares an important part of its genetic basis with blood pressure regulation, involving in particular several genes related to intracellular calcium homeostasis and vascular smooth muscle contraction. These results are consistent with previous studies showing systemic alterations in vascular contraction in FMD patients, even outside of affected arterial beds. While the mechanisms through which FMD may cause renovascular hypertension are well known, further studies will be required to determine how alterations in vascular contraction may lead to the arterial remodeling observed in FMD.

Abstract Introduction: Despite the decline in overall mortality and incidence of cancer in the US population, disparities in cancer care still largely exist within certain groups. The proportion of racial and ethnic minorities recruited to participate in cancer research is persistently lower than the US population. The rapid adoption of electronic health records (EHRs) systems has enabled computational cohort identification and eligibility screening for facilitating cancer research. However, EHR data is known to suffer from data quality issues due to numerous factors, such as care access. Patients with limited care access due to low socioeconomic status would naturally be sparsely represented in EHR data relative to those of higher status. Prospective enrollees may be disqualified due to biased or incomplete EHR data at the screening stage. Methods: To systematically identify data quality variabilities in EHRs, we implemented an information score (i-score) to reflect the density, variability, and irregularity of patients’ data. The pattern can be measured by estimating the variability of the time gaps between observations. For a patient observed n times, the encountered observation times are represented as x(1)…x(n). The relative time interval g for each observed encounter can be defined as g1 = [x(i+1)-x(i)]/[x(n)-x(1)], for I = 1…n - 1. The average amount of information of each observation is then defined as I, between 0 and 1, calculated as: I = 2/n+(n-2)/n[1-sqrt((n-1)Var{gi;i=1…n-1})]. An equality-spaced observation would receive a high i-score. The lower the i-score, the higher the data irregularity. We conducted a case study in a cohort of de novo stage IV breast cancer (DNIV) assembled by a previously validated phenotyping algorithm (Wang AACR 2020). The cohort contains 1,918 DNIV cases between 2004 and 2018 at Mayo Clinic Rochester. We used the i-score to assess patient visits, breast cancer diagnosis codes, and narrative documentation, achieved by the extraction of stage, surgery, de novo, and metastasis information based on the phenotyping definitions. The summary statistics of the i-scores were compared among four racial groups: African American (3%), Asian (1%), Caucasian (87%), and Other (9%). ANOVA F test was used to compare the group differences. Results and Conclusion: The mean i-scores for visit, diagnosis and narrative documentation were 0.712, 0.200, and 0.056 for African American, 0.412, 0.301, and 0.073 for Asian, 0.438, 0.278, and 0.056 for Caucasian, and 0.519, 0.343, and 0.043 for the other category, respectively. The F test indicated significant differences between visit (p<0.001) and diagnosis (p=0.0267) data. No difference was found in narrative documentation (p=0. 8591). In conclusion, there was a substantial i-score variation discovered, especially within the African American group, suggesting a strong need to address EHR quality disparity for cancer research. Citation Format: Sunyang Fu, Liwei Wang, Folakemi T. Odedina, Hongfang Liu. Assessment of EHR data quality variabilities among different racial groups in the cohort of de novo stage IV breast cancer [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr A020.

Abstract Context Metformin is the first-line drug for treating diabetes but has a high failure rate. Objective To identify demographic and clinical factors available in the electronic health record (EHR) that predict metformin failure. Methods A cohort of patients with at least 1 abnormal diabetes screening test that initiated metformin was identified at 3 sites (Arizona, Mississippi, and Minnesota). We identified 22 047 metformin initiators (48% female, mean age of 57 ± 14 years) including 2141 African Americans, 440 Asians, 962 Other/Multiracial, 1539 Hispanics, and 16 764 non-Hispanic White people. We defined metformin failure as either the lack of a target glycated hemoglobin (HbA1c) (<7%) within 18 months of index or the start of dual therapy. We used tree-based extreme gradient boosting (XGBoost) models to assess overall risk prediction performance and relative contribution of individual factors when using EHR data for risk of metformin failure. Results In this large diverse population, we observed a high rate of metformin failure (43%). The XGBoost model that included baseline HbA1c, age, sex, and race/ethnicity corresponded to high discrimination performance (C-index of 0.731; 95% CI 0.722, 0.740) for risk of metformin failure. Baseline HbA1c corresponded to the largest feature performance with higher levels associated with metformin failure. The addition of other clinical factors improved model performance (0.745; 95% CI 0.737, 0.754, P < .0001). Conclusion Baseline HbA1c was the strongest predictor of metformin failure and additional factors substantially improved performance suggesting that routinely available clinical data could be used to identify patients at high risk of metformin failure who might benefit from closer monitoring and earlier treatment intensification.

Abstract Primary sclerosing cholangitis (PSC) is a complex bile duct disorder. Its etiology is incompletely understood, but environmental chemicals likely contribute to risk. Patients with PSC have an altered bile metabolome, which may be influenced by environmental chemicals. This novel study utilized state-of-the-art high-resolution mass spectrometry (HRMS) with bile samples to provide the first characterization of environmental chemicals and metabolomics (collectively, the exposome) in PSC patients located in the United States of America (USA) (n = 24) and Norway (n = 30). First, environmental chemical- and metabolome-wide association studies were conducted to assess geographic-based similarities and differences in the bile of PSC patients. Nine environmental chemicals (false discovery rate, FDR < 0.20) and 3143 metabolic features (FDR < 0.05) differed by site. Next, pathway analysis was performed to identify metabolomic pathways that were similarly and differentially enriched by the site. Fifteen pathways were differentially enriched (P < .05) in the categories of amino acid, glycan, carbohydrate, energy, and vitamin/cofactor metabolism. Finally, chemicals and pathways were integrated to derive exposure–effect correlation networks by site. These networks demonstrate the shared and differential chemical–metabolome associations by site and highlight important pathways that are likely relevant to PSC. The USA patients demonstrated higher environmental chemical bile content and increased associations between chemicals and metabolic pathways than those in Norway. Polychlorinated biphenyl (PCB)-118 and PCB-101 were identified as chemicals of interest for additional investigation in PSC given broad associations with metabolomic pathways in both the USA and Norway patients. Associated pathways include glycan degradation pathways, which play a key role in microbiome regulation and thus may be implicated in PSC pathophysiology.

Background Delayed neurological improvement (DNI) is a phenomenon that involves patient improvement in the absence of early neurological change following treatment for acute ischemic stroke. The patient characteristics associated with this condition are largely unexplored. Methods Following the PRISMA guidelines, a systematic review of the English language literature was conducted using PubMed, Embase, Web of science, and Scopus. We calculated pooled odds ratios (ORs), mean differences (MDs), and their corresponding 95% confidence intervals (CIs) to test the association between patient characteristics and achievement of DNI. Results Seven studies, with 3266 patients, were included in our analysis. All studies reported a different definition of DNI, with five studies focusing on rates of good functional outcome at 90 days post-treatment in the absence of early neurological improvement. Use of intravenous thrombolytics was associated with increased rates of DNI (OR 1.96, 95% CI 1.28 to 3.00; p = 0.002). Atrial fibrillation was associated with decreased rates of DNI (OR 0.69, 95% CI 0.57 to 0.82; p < 0.001), as was hypertension (OR 0.66, 95% CI 0.53 to 0.83, p < 0.001), and diabetes mellitus (OR 0.71, 95% CI 0.56 to 0.90; p = 0.005). On average, patients who achieved DNI were 6.30 years younger than their non-DNI counterparts ( MD −6.30, 95% CI −9.19 to −3.41; p < 0.001). There were modest associations between male sex and DNI (OR 1.36, 95% CI 1.01 to 1.74, p = 0.042), and smoking and DNI (OR 1.28, 95% CI 1.03 to 1.59, p = 0.027). Conclusions DNI is a phenomenon that is not presently well understood. Lack of uniformity among definitions of DNI hinders efforts to explore DNI and the factors associated with its occurrence. Future studies should work to establish a consensus definition of DNI to determine its causes and significance more accurately.