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A universal predictive and mechanistic urinary peptide signature in acute kidney injury

International audienceBackground The delayed diagnosis of acute kidney injury (AKI) episodes and the lack of specificity of current single AKI biomarkers hamper its management. Urinary peptidome analysis may help to identify early molecular changes in AKI and grasp its complexity to identify potential targetable molecular pathways.Methods In derivation and validation cohorts totalizing 1170 major cardiac bypass surgery patients and in an external cohort of 1569 intensive care unit (ICU) patients, a peptide-based score predictive of AKI (7-day KDIGO classification) was developed, validated, and compared to the reference biomarker urinary NGAL and NephroCheck and clinical scores. Results A set of 204 urinary peptides derived from 48 proteins related to hemolysis, inflammation, immune cells trafficking, innate immunity, and cell growth and survival was identified and validated for the early discrimination (< 4 h) of patients according to their risk to develop AKI (OR 6.13 [3.96–9.59], p < 0.001) outperforming reference biomarkers (urinary NGAL and [IGFBP7].[TIMP2] product) and clinical scores. In an external cohort of 1569 ICU patients, performances of the signature were similar (OR 5.92 [4.73–7.45], p < 0.001), and it was also associated with the in-hospital mortality (OR 2.62 [2.05–3.38], p < 0.001). Conclusions An overarching AKI physiopathology-driven urinary peptide signature shows significant promise for identifying, at an early stage, patients who will progress to AKI and thus to develop tailored treatments for this frequent and life-threatening condition. Performance of the urine peptide signature is as high as or higher than that of single biomarkers but adds mechanistic information that may help to discriminate sub-phenotypes of AKI offering new therapeutic avenues

Additional file 1 of A universal predictive and mechanistic urinary peptide signature in acute kidney injury

Additional file 1: Supplementary Figure S1: S100A9 expression after epithelial injury. A. Urinary calprotectin (S100A8/A9) abundance 4 hours after cardiac bypass-surgery. B–F. Blood urea nitrogen (B), mRNA S100a9 (C), S100A9 immunostaining (D-E) and mRNA Kim1 (F) in sham mice and after bilateral renal ischemia/reperfusion (hours 6, 24 and 48). G–J. mRNA expression of S100a9 and Kim1 in MCT cells submitted to interleukin-1b (IL1β, 10 ng/mL) or tumor necrosis factor-1a (TNFa, 10 ng/mL) (G-H) or hypoxia (I-J). AKI, acute kidney injury; BUN, blood urea nitrogen; Norm, normoxia; Hyp, hypoxia. Supplementary Figure S2: Performances of the peptide-based signature to identify AKI that developed within the first 2 days following cardiac surgery. ROC curves with corresponding AUROC and 95% confidence intervals of the local clinical score (blue, pointed), the full 204 peptides-based score (red), the urinary NGAL level (yellow, pointed) and the nephrocheck ([IGFBP7].[TIMP2] product) in the validation cohort. Supplementary Figure S3: Reduction and combination of the peptide-based signature. A. ROC curves with corresponding AUROC and 95% confidence intervals of the local clinical score (blue, pointed), the full 204 peptides-based score (red), the reduced 17 peptides-based score (black, dashed) and the combination of local clinical and full peptide-based score in the validation cohort. B. List of peptides included in the reduced 17-peptides signature according to their parental protein. LMAN2, Lectin mannose binding 2 ; MGP, Matrix gla protein. Supplementary Figure S4: Performances of the 204 peptides-based signature and the reference urinary biomarker NGAL for AKI prediction in the external ICU validation cohort. A. ROC curves with corresponding AUROC and 95% confidence intervals of the 204 peptides-based score and the reference urinary biomarker NGAL to predict AKI after ICU admission. B. ROC curves with corresponding AUROC and 95% confidence intervals of the 204 peptides-based score and reference urinary biomarker NGAL to predict the development of AKI within seven days after admission. Supplementary Figure S5: Performances of the 204 peptides-based score for in-hospital mortality prediction. Odds-ratio (OR) of in-hospital mortality were calculated with unadjusted, Euroscore-II-adjusted or propensity score-adjusted logistic regression. Supplementary Table S1: Correlations between clinical characteristics and the 204-peptides-based score. BMI, body mass index; PAOD, peripheral artery obliterans disease; COPD, chronic obstructive pulmonary disease; LVEF, left ventricular ejection fraction; eGFR, estimated glomerular filtration rate; CBP, cardiac bypass; RBC, red blood cells. Supplementary Table S2: Performance of the peptide-based score to predict acute kidney injury in the external ICU validation cohort, according to the cause of admission to the intensive care unit. ICU, intensive care unit; AUROC, area under the receiver operating characteristics curve. Supplementary file S1: Methodology. Urinary peptidomics and statistical analyses

Proximity to parental symptom onset and amyloid-β burden in sporadic Alzheimer disease

IMPORTANCE Alzheimer disease (AD) develops during several decades. Presymptomatic individuals might be the best candidates for clinical trials, but their identification is challenging because they have no symptoms. OBJECTIVE To assess whether a sporadic parental estimated years to symptom onset calculation could be used to identify information about amyloid-β (Aβ) levels in asymptomatic individuals with a parental history of AD dementia. DESIGN, SETTING, AND PARTICIPANTS This cohort study analyzed Aβ1-42 in cerebrospinal fluid (CSF) specimens from 101 cognitively normal individuals who had a lumbar puncture as part of the Presymptomatic Evaluation of Novel or Experimental Treatments for Alzheimer Disease (PREVENT-AD) cohort from September 1, 2011, through November 30, 2016 (374 participants were enrolled in the cohort during this period). The study estimated each participant's proximity to his/her parent's symptom onset by subtracting the index relative's onset age from his/her current age. The association between proximity to parental symptom onset and Aβ levels was then assessed using apolipoprotein E ϵ4 (APOE4) status and sex as interactive terms. These analyses were performed again in 2 independent cohorts using CSF and Pittsburgh compound B carbon 11-labeled positron emission tomography (PIB-PET) Aβ biomarkers: the Adult Children Study (ACS) and the Wisconsin Registry for Alzheimer Prevention (WRAP) cohorts. MAIN OUTCOMES AND MEASURES The association between proximity to parental symptom onset and Aβ burden in asymptomatic individuals with a parental history of sporadic AD. RESULTS The present analysis included a subset of 101 PREVENT-AD individuals (mean [SD] age, 61.8 [5.1] years; 30 [29.7%] male), 128 ACS participants (112 participants underwent CSF measurement: mean [SD] age, 63.4 [5.1] years; 31 [27.7%] male; and 107 underwent PIB-PET: mean [SD] age, 64.6 [5.3] years; 27 [25.2%] male), and 135 WRAP participants (85 participants underwent CSF measurement: mean [SD] age, 59.9 [6.0] years; 27 [31.8%] male; and 135 underwent PIB-PET: mean [SD] age, 59.6 [6.1] years; 43 [31.9%] male). In the PREVENT-AD cohort, individuals approaching their parent's onset age had lower CSF Aβ1-42 levels (range, 402-1597; B = -9.09, P = .04). This association was stronger in APOE4 carriers (B = -17.9, P = .03) and women (B = -19.8, P = .02). In the ACS cohort, the main association was replicated using PIB-PET data, and the sex interaction was replicated using CSF and PIB-PET data. In the WRAP cohort, the results were not replicated using cross-sectional data, but the main association and the APOE interaction were replicated using PIB-PET longitudinal data. CONCLUSIONS AND RELEVANCE These results suggest that proximity to parental symptom onsetmay help estimate Aβ biomarker changes in women or APOE4 carrier asymptomatic individuals with a parental history of sporadic AD

Outcomes After Endovascular Therapy With Procedural Sedation vs General Anesthesia in Patients With Acute Ischemic Stroke The AMETIS Randomized Clinical Trial

International audienceImportance General anesthesia and procedural sedation are common practice for mechanical thrombectomy in acute ischemic stroke. However, risks and benefits of each strategy are unclear. Objective To determine whether general anesthesia or procedural sedation for anterior circulation large-vessel occlusion acute ischemic stroke thrombectomy are associated with a difference in periprocedural complications and 3-month functional outcome. Design, Setting, and Participants This open-label, blinded end point randomized clinical trial was conducted between August 2017 and February 2020, with final follow-up in May 2020, at 10 centers in France. Adults with occlusion of the intracranial internal carotid artery and/or the proximal middle cerebral artery treated with thrombectomy were enrolled. Interventions Patients were assigned to receive general anesthesia with tracheal intubation (n = 135) or procedural sedation (n = 138). Main Outcomes and Measures The prespecified primary composite outcome was functional independence (a score of 0 to 2 on the modified Rankin Scale, which ranges from 0 [no neurologic disability] to 6 [death]) at 90 days and absence of major periprocedural complications (procedure-related serious adverse events, pneumonia, myocardial infarction, cardiogenic acute pulmonary edema, or malignant stroke) at 7 days. Results Among 273 patients evaluable for the primary outcome in the modified intention-to-treat population, 142 (52.0%) were women, and the mean (SD) age was 71.6 (13.8) years. The primary outcome occurred in 38 of 135 patients (28.2%) assigned to general anesthesia and in 50 of 138 patients (36.2%) assigned to procedural sedation (absolute difference, 8.1 percentage points; 95% CI, −2.3 to 19.1; P = .15). At 90 days, the rate of patients achieving functional independence was 33.3% (45 of 135) with general anesthesia and 39.1% (54 of 138) with procedural sedation (relative risk, 1.18; 95% CI, 0.86-1.61; P = .32). The rate of patients without major periprocedural complications at 7 days was 65.9% (89 of 135) with general anesthesia and 67.4% (93 of 138) with procedural sedation (relative risk, 1.02; 95% CI, 0.86-1.21; P = .80). Conclusions and Relevance In patients treated with mechanical thrombectomy for anterior circulation acute ischemic stroke, general anesthesia and procedural sedation were associated with similar rates of functional independence and major periprocedural complications. Trial Registration ClinicalTrials.gov Identifier: NCT0322914

The neurophysiological brain-fingerprint of Parkinson’s diseaseResearch in context

Summary: Background: Research in healthy young adults shows that characteristic patterns of brain activity define individual “brain-fingerprints” that are unique to each person. However, variability in these brain-fingerprints increases in individuals with neurological conditions, challenging the clinical relevance and potential impact of the approach. Our study shows that brain-fingerprints derived from neurophysiological brain activity are associated with pathophysiological and clinical traits of individual patients with Parkinson’s disease (PD). Methods: We created brain-fingerprints from task-free brain activity recorded through magnetoencephalography in 79 PD patients and compared them with those from two independent samples of age-matched healthy controls (N = 424 total). We decomposed brain activity into arrhythmic and rhythmic components, defining distinct brain-fingerprints for each type from recording durations of up to 4 min and as short as 30 s. Findings: The arrhythmic spectral components of cortical activity in patients with Parkinson’s disease are more variable over short periods, challenging the definition of a reliable brain-fingerprint. However, by isolating the rhythmic components of cortical activity, we derived brain-fingerprints that distinguished between patients and healthy controls with about 90% accuracy. The most prominent cortical features of the resulting Parkinson’s brain-fingerprint are mapped to polyrhythmic activity in unimodal sensorimotor regions. Leveraging these features, we also demonstrate that Parkinson’s symptom laterality can be decoded directly from cortical neurophysiological activity. Furthermore, our study reveals that the cortical topography of the Parkinson’s brain-fingerprint aligns with that of neurotransmitter systems affected by the disease’s pathophysiology. Interpretation: The increased moment-to-moment variability of arrhythmic brain-fingerprints challenges patient differentiation and explains previously published results. We outline patient-specific rhythmic brain signaling features that provide insights into both the neurophysiological signature and symptom laterality of Parkinson’s disease. Thus, the proposed definition of a rhythmic brain-fingerprint of Parkinson’s disease may contribute to novel, refined approaches to patient stratification. Symmetrically, we discuss how rhythmic brain-fingerprints may contribute to the improved identification and testing of therapeutic neurostimulation targets. Funding: Data collection and sharing for this project was provided by the Quebec Parkinson Network (QPN), the Pre-symptomatic Evaluation of Novel or Experimental Treatments for Alzheimer’s Disease (PREVENT-AD; release 6.0) program, the Cambridge Centre for Aging Neuroscience (Cam-CAN), and the Open MEG Archives (OMEGA). The QPN is funded by a grant from Fonds de Recherche du Québec - Santé (FRQS). PREVENT-AD was launched in 2011 as a $13.5 million, 7-year public-private partnership using funds provided by McGill University, the FRQS, an unrestricted research grant from Pfizer Canada, the Levesque Foundation, the Douglas Hospital Research Centre and Foundation, the Government of Canada, and the Canada Fund for Innovation. The Brainstorm project is supported by funding to SB from the NIH (R01-EB026299-05). Further funding to SB for this study included a Discovery grant from the Natural Sciences and Engineering Research Council of Canada of Canada (436355-13), and the CIHR Canada research Chair in Neural Dynamics of Brain Systems (CRC-2017-00311)