CCL23 is a chemokine implicated in inflammation and host defense responses. It has been recently associated with acquired brain damage and stroke outcomes. In this study, we reported the role of CCL23 in Alzheimer’s disease (AD). We evaluated the levels of CCL23 in 659 individuals: cognitively normal, mild cognitive impaired (MCI), and AD patients. Two cross-sectional (study 1, n = 53; study 2, n = 200) and two longitudinal (study 3, n = 74; study 4, n = 332) studies were analyzed separately. CCL23 levels in the blood and/or cerebrospinal fluid (CSF) of each study were measured by immunoassays. Globally, our results suggest a predictive role of CCL23 protein levels both in the plasma in study 3 (hazard ratio (HR) = 2.5 (confidence interval (CI) 95% : 1.2–5.3), p = 0.02) and in the CSF in study 4 (HR = 3.05 (CI 95% : 1.02–5), p = 0.04) in cases of MCI that progress to AD. Moreover, we observed that the APOE ɛ 4 allele was associated with higher levels of CCL23 in study 2 (470.33 pg/mL (interquartile range (IQR): 303.33–597.76) versus 377.94 pg/mL (IQR: 267.16–529.19), p = 0.01) ( APOE genotypes were available in studies 2 and 4). Together, these findings support the role of CCL23 in neuroinflammation in the early stages of AD, suggesting that CCL23 might be a candidate blood biomarker for MCI to AD progression.

Background and Purpose: The aim of this study was to evaluate and independently validate SAA (serum amyloid A)—a recently discovered blood biomarker—to predict poststroke infections. Methods: The derivation cohort (A) was composed of 283 acute ischemic stroke patients and the independent validation cohort (B), of 367 patients. The primary outcome measure was any stroke-associated infection, defined by the criteria of the US Centers for Disease Control and Prevention, occurring during hospitalization. To determine the association of SAA levels on admission with the development of infections, logistic regression models were calculated. The discriminatory ability of SAA was assessed, by calculating the area under the receiver operating characteristic curve. Results: After adjusting for all predictors that were significantly associated with any infection in the univariate analysis, SAA remained an independent predictor in study A (adjusted odds ratio, 1.44 [95% CI, 1.16–1.79]; P =0.001) and in study B (adjusted odds ratio, 1.52 [1.05–2.22]; P =0.028). Adding SAA to the best regression model without the biomarker, the discriminatory accuracy improved from 0.76 (0.69–0.83) to 0.79 (0.72–0.86; P <0.001; likelihood ratio test) in study A. These results were externally validated in study B with an improvement in the area under the receiver operating characteristic curve, from 0.75 (0.70–0.81) to 0.76 (0.71–0.82; P <0.038). Conclusions: Among patients with ischemic stroke, blood SAA measured on admission is a novel independent predictor of infection after stroke. SAA improved the discrimination between patients who developed an infection compared with those who did not in both derivation and validation cohorts. Registration: URL: https://www.clinicaltrials.gov . Unique identifier: NCT00390962.

Background: Acute decompensated heart failure (ADHF) and respiratory tract infections (RTIs) are potentially life‐threatening complications in patients experiencing stroke during hospitalization. We aimed to test whether blood biomarker panels might predict these complications early after admission. Methods and Results: Nine hundred thirty‐eight patients experiencing ischemic stroke were prospectively recruited in the Stroke‐Chip study. Post‐stroke complications during hospitalization were retrospectively evaluated. Blood samples were drawn within 6 hours after stroke onset, and 14 biomarkers were analyzed by immunoassays. Biomarker values were normalized using log‐transformation and Z score. PanelomiX algorithm was used to select panels with the best accuracy for predicting ADHF and RTI. Logistic regression models were constructed with the clinical variables and the biomarker panels. The additional predictive value of the panels compared with the clinical model alone was evaluated by receiver operating characteristic curves. An internal validation through a 10‐fold cross‐validation with 3 repeats was performed. ADHF and RTI occurred in 19 (2%) and 86 (9.1%) cases, respectively. Three‐biomarker panels were developed as predictors: vascular adhesion protein‐1 >5.67, NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide) >4.98 and d ‐dimer >5.38 (sensitivity, 89.5%; specificity, 71.7%) for ADHF; and interleukin‐6 >3.97, von Willebrand factor >3.67, and d ‐dimer >4.58 (sensitivity, 82.6%; specificity, 59.8%) for RTI. Both panels independently predicted stroke complications (panel for ADHF: odds ratio [OR] [95% CI], 10.1 [3–52.2]; panel for RTI: OR, 3.73 [1.95–7.14]) after adjustment by clinical confounders. The addition of the panel to clinical predictors significantly improved areas under the curve of the receiver operating characteristic curves in both cases. Conclusions: Blood biomarkers could be useful for the early prediction of ADHF and RTI. Future studies should assess the usefulness of these panels in front of patients experiencing stroke with respiratory symptoms such as dyspnea.

To confirm the diagnostic accuracy of candidate biomarkers in stroke‐associated pneumonia (SAP), we prospectively enrolled ischemic stroke patients with NIHSS ≥ 10 on admission from March‐2016 to August‐2017. Blood samples were collected at baseline, 24 and 48 h after stroke onset. Biomarkers (MR‐proADM, suPAR, SAA) were determined by immunoassays. Regarding biomarkers, MR‐proADM at 24 h (P = 0.04) and both suPAR and SAA at 48 h (P = 0.036 and P = 0.057) were associated with pneumonia. The combination of SAA > 25.15 mg/dL and suPAR> 3.14 ng/mL at 48 h had 80% sensitivity and 95.8% specificity when both biomarkers were above the cut‐off. The evaluated biomarkers represent promising tools to be evaluated in future large, prospective studies on SAP. An accurate SAP diagnosis by thorax CT might help to reduce variability in such studies.

After stroke and other brain injuries, there is a high incidence of respiratory complications such as pneumonia or acute lung injury. The molecular mechanisms that drive the brain-lung interaction post-stroke have not yet been elucidated. We performed transient middle cerebral artery occlusion (MCAO) and sham surgery on C57BL/6J mice and collected bronchoalveolar lavage fluid (BALF), serum, brain, and lung homogenate samples 24 h after surgery. A 92 proteins-panel developed by Olink Proteomics^® was used to analyze the content in BALF and lung homogenates. MCAO animals had higher protein concentration levels in BALF than sham-controls, but these levels did not correlate with the infarct volume. No alteration in alveolar-capillary barrier permeability was observed. A total of 12 and 14 proteins were differentially expressed between the groups (FDR < 0.1) in BALF and lung tissue homogenates, respectively. Of those, HGF, TGF-α, and CCL2 were identified as the most relevant to this study. Their protein expression patterns were verified by ELISA. This study confirmed that post-stroke lung damage was not associated with increased lung permeability or cerebral ischemia severity. Furthermore, the dysregulation of HGF, TGF-α, and CCL2 in BALF and lung tissue after ischemia could play an important role in the molecular mechanisms underlying stroke-induced lung damage.