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This retrospective study aims to assess the diagnostic utility of peripheral blood eosinophil counts in distinguishing between benign and malignant pulmonary nodules (PNs) prior to surgical intervention. We involved patients presenting with PNs measuring ≤30 mm as the primary CT imaging finding prior to surgical procedures at the General Hospital of Northern Theater Command in Shenyang, China, during the period spanning 2021 to 2022. Multivariable logistic regression analysis and receiver operator characteristic curve analysis, along with area under the curve (AUC) calculations, were used to determine the diagnostic value of eosinophil. A total of 361 patients with PN were included, consisting of 135 with benign PN and 226 with malignant PN. Multivariable logistic regression analysis showed that eosinophil percentage (OR = 1.909, 95% CI: 1.323-2.844, P < .001), absolute eosinophil value (OR = 0.001, 95% CI: 0.000-0.452, P = .033), tumor diameter (OR = 0.918, 95% CI: 0.877-0.959, P < .001), nodule type (OR = 0.227, 95% CI: 0.125-0.400, P < .001), sex (OR = 2.577, 95% CI: 1.554-4.329, P < .001), and age (OR = 0.967, 95% CI: 0.945-0.989, P = .004) were independently associated with malignant PN. The diagnostic value of regression model (AUC [95% CI]: 0.775 [0.725-0.825]; sensitivity: 74.3%; specificity: 71.1%) was superior to eosinophil percentage (AUC [95% CI]: 0.616 [0.556-0.677]; specificity: 66.8%; specificity: 51.1%) (Delong test: P < .001). Peripheral blood eosinophil percentage might be useful for early malignant PN diagnosis, and combining that with other characteristics might improve the diagnostic performance., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc.)

Background: Defining the RNA transcriptome in Alzheimer Disease (AD) will help understand the disease mechanisms and provide biomarkers. Though the AD blood transcriptome has been studied, effects of white matter hyperintensities (WMH) were not considered. This study investigated the AD blood transcriptome and accounted for WMH., Methods: RNA from whole blood was processed on whole-genome microarrays., Results: A total of 293 probe sets were differentially expressed in AD versus controls, 5 of which were significant for WMH status. The 288 AD-specific probe sets classified subjects with 87.5% sensitivity and 90.5% specificity. They represented 188 genes of which 29 have been reported in prior AD blood and 89 in AD brain studies. Regulated blood genes included MMP9, MME (Neprilysin), TGFβ1, CA4, OCLN, ATM, TGM3, IGFR2, NOV, RNF213, BMX, LRRN1, CAMK2G, INSR, CTSD, SORCS1, SORL1, and TANC2., Conclusions: RNA expression is altered in AD blood irrespective of WMH status. Some genes are shared with AD brain.

Background and Purpose: The cause of ischemic stroke remains unclear, or cryptogenic, in as many as 35% of patients with stroke. Not knowing the cause of stroke restricts optimal implementation of prevention therapy and limits stroke research. We demonstrate how gene expression profiles in blood can be used in conjunction with a measure of infarct location on neuroimaging to predict a probable cause in cryptogenic stroke., Methods: The cause of cryptogenic stroke was predicted using previously described profiles of differentially expressed genes characteristic of patients with cardioembolic, arterial, and lacunar stroke. RNA was isolated from peripheral blood of 131 cryptogenic strokes and compared with profiles derived from 149 strokes of known cause. Each sample was run on Affymetrix U133 Plus 2.0 microarrays. Cause of cryptogenic stroke was predicted using gene expression in blood and infarct location., Results: Cryptogenic strokes were predicted to be 58% cardioembolic, 18% arterial, 12% lacunar, and 12% unclear etiology. Cryptogenic stroke of predicted cardioembolic etiology had more prior myocardial infarction and higher CHA(2)DS(2)-VASc scores compared with stroke of predicted arterial etiology. Predicted lacunar strokes had higher systolic and diastolic blood pressures and lower National Institutes of Health Stroke Scale compared with predicted arterial and cardioembolic strokes. Cryptogenic strokes of unclear predicted etiology were less likely to have a prior transient ischemic attack or ischemic stroke., Conclusions: Gene expression in conjunction with a measure of infarct location can predict a probable cause in cryptogenic strokes. Predicted groups require further evaluation to determine whether relevant clinical, imaging, or therapeutic differences exist for each group.

Background and Purpose: Deciphering whether a transient neurological event (TNE) is of ischemic or nonischemic etiology can be challenging. Ischemia of cerebral tissue elicits an immune response in stroke and transient ischemic attack (TIA). This response, as detected by RNA expressed in immune cells, could potentially distinguish ischemic from nonischemic TNE., Methods: Analysis of 208 TIAs, ischemic strokes, controls, and TNE was performed. RNA from blood was processed on microarrays. TIAs (n=26) and ischemic strokes (n=94) were compared with controls (n=44) to identify differentially expressed genes (false discovery rate <0.05, fold change ≥1.2). Genes common to TIA and stroke were used predict ischemia in TIA diffusion-weighted imaging-positive/minor stroke (n=17), nonischemic TNE (n=13), and TNE of unclear etiology (n=14)., Results: Seventy-four genes expressed in TIA were common to those in ischemic stroke. Functional pathways common to TIA and stroke related to activation of innate and adaptive immune systems, involving granulocytes and B cells. A prediction model using 26 of the 74 ischemia genes distinguished TIA and stroke subjects from control subjects with 89% sensitivity and specificity. In the validation cohort, 17 of 17 TIA diffusion-weighted imaging-positive/minor strokes were predicted to be ischemic, and 10 of 13 nonischemic TNE were predicted to be nonischemic. In TNE of unclear etiology, 71% were predicted to be ischemic. These subjects had higher ABCD(2) scores., Conclusions: A common molecular response to ischemia in TIA and stroke was identified, relating to activation of innate and adaptive immune systems. TNE of ischemic etiology was identified based on gene profiles that may be of clinical use once validated.

Background and Purpose: Differences in ischemic stroke between men and women have been mainly attributed to hormonal effects. However, sex differences in immune response to ischemia may exist. We hypothesized that differential expression of X-chromosome genes in blood immune cells contribute to differences between men and women with ischemic stroke., Methods: RNA levels of 683 X-chromosome genes were measured on Affymetrix U133 Plus2.0 microarrays. Blood samples from patients with ischemic stroke were obtained at ≤ 3 hours, 5 hours, and 24 hours (n=61; 183 samples) after onset and compared with control subjects without symptomatic vascular diseases (n=109). Sex difference in X-chromosome gene expression was determined using analysis of covariance (false discovery rate ≤ 0.05, fold change ≥ 1.2)., Results: At ≤ 3, 5, and 24 hours after stroke, there were 37, 140, and 61 X-chromosome genes, respectively, that changed in women; and 23, 18, and 31 X-chromosome genes that changed in men. Female-specific genes were associated with post-translational modification, small-molecule biochemistry, and cell-cell signaling. Male-specific genes were associated with cellular movement, development, cell-trafficking, and cell death. Altered sex specific X-chromosome gene expression occurred in 2 genes known to be associated with human stroke, including galactosidase A and IDS, mutations of which result in Fabry disease and Hunter syndrome, respectively., Conclusions: There are differences in X-chromosome gene expression between men and women with ischemic stroke. Future studies are needed to decipher whether these differences are associated with sexually dimorphic immune response, repair or other mechanisms after stroke, or whether some of them represent risk determinants.

Background and Purpose: White matter hyperintensities (WMH) are areas of high signal detected by T2 and fluid-attenuated inversion recovery sequences on brain MRI. Although associated with aging, cerebrovascular risk factors, and cognitive impairment, the pathogenesis of WMH remains unclear. Thus, RNA expression was assessed in the blood of individuals with and without extensive WMH to search for evidence of oxidative stress, inflammation, and other abnormalities described in WMH lesions in brain., Methods: Subjects included 20 with extensive WMH (WMH+), 45% of whom had Alzheimer disease, and 18 with minimal WMH (WMH-), 44% of whom had Alzheimer disease. All subjects were clinically evaluated and underwent quantitative MRI. Total RNA from whole blood was processed on human whole genome Affymetrix HU133 Plus 2.0 microarrays. RNA expression was analyzed using an analysis of covariance., Results: Two hundred forty-one genes were differentially regulated at ± 1.2-fold difference (P < 0.005) in subjects with WMH+ as compared to WMH-, regardless of cognitive status and 50 genes were differentially regulated with ± 1.5-fold difference (P < 0.005). Cluster and principal components analyses showed that the expression profiles for these genes distinguished WMH+ from WMH- subjects. Function analyses suggested that WMH-specific genes were associated with oxidative stress, inflammation, detoxification, and hormone signaling, and included genes associated with oligodendrocyte proliferation, axon repair, long-term potentiation, and neurotransmission., Conclusions: The unique RNA expression profile in blood associated with WMH is consistent with roles of systemic oxidative stress and inflammation, as well as other potential processes in the pathogenesis or consequences of WMH.

Background and Purpose: A blood-based biomarker of acute ischemic stroke would be of significant value in clinical practice. This study aimed to (1) replicate in a larger cohort our previous study using gene expression profiling to predict ischemic stroke; and (2) refine prediction of ischemic stroke by including control groups relevant to ischemic stroke., Methods: Patients with ischemic stroke (n=70, 199 samples) were compared with control subjects who were healthy (n=38), had vascular risk factors (n=52), and who had myocardial infarction (n=17). Whole blood was drawn ≤3 hours, 5 hours, and 24 hours after stroke onset and from control subjects. RNA was processed on whole genome microarrays. Genes differentially expressed in ischemic stroke were identified and analyzed for predictive ability to discriminate stroke from control subjects., Results: The 29 probe sets previously reported predicted a new set of ischemic strokes with 93.5% sensitivity and 89.5% specificity. Sixty- and 46-probe sets differentiated control groups from 3-hour and 24-hour ischemic stroke samples, respectively. A 97-probe set correctly classified 86% of ischemic strokes (3 hour+24 hour), 84% of healthy subjects, 96% of vascular risk factor subjects, and 75% with myocardial infarction., Conclusions: This study replicated our previously reported gene expression profile in a larger cohort and identified additional genes that discriminate ischemic stroke from relevant control groups. This multigene approach shows potential for a point-of-care test in acute ischemic stroke.