Effects of storage conditions on the stability of blood-based markers for the diagnosis of Alzheimer's disease.

OBJECTIVES: Alzheimer's disease (AD) is considered the most common cause of dementia in older people. Recently, blood-based markers (BBM) Aß1-42, Aß1-40, and phospho Tau181 (p-Tau181) have demonstrated the potential to transform the diagnosis and prognostic assessment of AD. Our aim was to investigate the effect of different storage conditions on the quantification of these BBM and to evaluate the interchangeability of plasma and serum samples. METHODS: Forty-two individuals with some degree of cognitive impairment were studied. Thirty further patients were retrospectively selected. Aß1-42, Aß1-40, and p-Tau181 were quantified using the LUMIPULSE-G600II automated platform. To assess interchangeability between conditions, correction factors for magnitudes that showed strong correlations were calculated, followed by classification consistency studies. RESULTS: Storing samples at 4 °C for 8-9 days was associated with a decrease in Aß fractions but not when stored for 1-2 days. Using the ratio partially attenuated the pre-analytical effects. For p-Tau181, samples stored at 4 °C presented lower concentrations, whereas frozen samples presented higher ones. Concerning classification consistency in comparisons that revealed strong correlations (p-Tau181), the percentage of total agreement was greater than 90 % in a large number of the tested cut-offs values. CONCLUSIONS: Our findings provide relevant information for the standardization of sample collection and storage in the analysis of AD BBM in an automated platform. This knowledge is crucial to ensure their introduction into clinical settings.

Importance of cerebrospinal fluid storage conditions for the Alzheimer's disease diagnostics on an automated platform.

OBJECTIVES: Alzheimer's disease (AD) is considered the most common cause of dementia in older people. Cerebrospinal fluid (CSF) Aß1-42, Aß1-40, total Tau (t-Tau), and phospho Tau (p-Tau) are important biomarkers for the diagnosis, however, they are highly dependent on the pre-analytical conditions. Our aim was to investigate the potential influence of different storage conditions on the simultaneous quantification of these biomarkers in a fully-automated platform to accommodate easier pre-analytical conditions for laboratories. METHODS: CSF samples were obtained from 11 consecutive patients. Aß1-42, Aß1-40, p-Tau, and t-Tau were quantified using the LUMIPULSE G600II automated platform. RESULTS: Temperature and storage days significantly influenced Aß1-42 and Aß1-40 with concentrations decreasing with days spent at 4 °C. The use of the Aß1-42/Aß1-40 ratio could partly compensate it. P-Tau and t-Tau were not affected by any of the tested storage conditions. For conditions involving storage at 4 °C, a correction factor of 1.081 can be applied. Diagnostic agreement was almost perfect in all conditions. CONCLUSIONS: Cutoffs calculated in samples stored at -80 °C can be safely used in samples stored at -20 °C for 15-16 days or up to two days at RT and subsequent freezing at -80 °C. For samples stored at 4 °C, cutoffs would require applying a correction factor, allowing to work with the certainty of reaching the same clinical diagnosis.

Use of plasma biomarkers for AT(N) classification of neurodegenerative dementias.

OBJECTIVES: All categories included in the AT(N) classification can now be measured in plasma. However, their agreement with cerebrospinal fluid (CSF) markers is not fully established. A blood signature to generate the AT(N) classification would facilitate early diagnosis of patients with Alzheimer's disease (AD) through an easy and minimally invasive approach. METHODS: We measured Aß, pTau181 and neurofilament light (NfL) in 150 plasma samples of the Sant Pau Initiative on Neurodegeneration cohort including patients with mild cognitive impairment, AD dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal participants. We classified participants in the AT(N) categories according to CSF biomarkers and studied the diagnostic value of plasma biomarkers within each category individually and in combination. RESULTS: The plasma Aß composite, pTau181 and NfL yielded areas under the curve (AUC) of 0.75, 0.78 and 0.88 to discriminate positive and negative participants in their respective A, T and N categories. The combination of all three markers did not outperform pTau181 alone (AUC=0.81) to discriminate A+T+ from A-T- participants. There was a moderate correlation between plasma Aß composite and CSF Aß1-42/Aß1-40 (Rho=-0.5, p<0.001) and between plasma pTau181 and CSF pTau181 in the entire cohort (Rho=0.51, p<0.001). NfL levels in plasma showed high correlation with those in CSF (Rho=0.78, p<0.001). CONCLUSIONS: Plasma biomarkers are useful to detect the AT(N) categories, and their use can differentiate patients with pathophysiological evidence of AD. A blood AT(N) signature may facilitate early diagnosis and follow-up of patients with AD through an easy and minimally invasive approach.

Diagnostic performance of plasma pTau217, pTau181, Aß1-42 and Aß1-40 in the LUMIPULSE automated platform for the detection of Alzheimer disease.

BACKGROUND: Recently developed blood markers for Alzheimer's disease (AD) detection have high accuracy but usually require ultra-sensitive analytic tools not commonly available in clinical laboratories, and their performance in clinical practice is unknown. METHODS: We analyzed plasma samples from 290 consecutive participants that underwent lumbar puncture in routine clinical practice in a specialized memory clinic (66 cognitively unimpaired, 130 participants with mild cognitive impairment, and 94 with dementia). Participants were classified as amyloid positive (A +) or negative (A-) according to CSF Aß1-42/Aß1-40 ratio. Plasma pTau217, pTau181, Aß1-42 and Aß1-40 were measured in the fully-automated LUMIPULSE platform. We used linear regression to compare plasma biomarkers concentrations between A + and A- groups, evaluated Spearman's correlation between plasma and CSF and performed ROC analyses to assess their diagnostic accuracy to detect brain amyloidosis as determined by CSF Aß1-42/Aß1-40 ratio. We analyzed the concordance of pTau217 with CSF amyloidosis. RESULTS: Plasma pTau217 and pTau181 concentration were higher in A + than A- while the plasma Aß1-42/Aß1-40 ratio was lower in A + compared to A-. pTau181 and the Aß1-42/Aß1-40 ratio showed moderate correlation between plasma and CSF (Rho = 0.66 and 0.69, respectively). The areas under the ROC curve to discriminate A + from A- participants were 0.94 (95% CI 0.92-0.97) for pTau217, and 0.88 (95% CI 0.84-0.92) for both pTau181 and Aß1-42/Aß1-40. Chronic kidney disease (CKD) was related to increased plasma biomarker concentrations, but ratios were less affected. Plasma pTau217 had the highest fold change (× 3.2) and showed high predictive capability in discriminating A + from A-, having 4-7% misclassification rate. The global accuracy of plasma pTau217 using a two-threshold approach was robust in symptomatic groups, exceeding 90%. CONCLUSION: The evaluation of blood biomarkers on an automated platform exhibited high diagnostic accuracy for AD pathophysiology, and pTau217 showed excellent diagnostic accuracy to identify participants with AD in a consecutive sample representing the routine clinical practice in a specialized memory unit.

Diagnostic performance of plasma pTau 217, pTau 181, Aß 1-42 and Aß 1-40 in the LUMIPULSE automated platform for the detection of Alzheimer disease.

BACKGROUND: Recently developed blood markers for Alzheimer's disease (AD) detection have high accuracy but usually require ultra-sensitive analytic tools not commonly available in clinical laboratories, and their performance in clinical practice is unknown. METHODS: We analyzed plasma samples from 290 consecutive participants that underwent lumbar puncture in routine clinical practice in a specialized memory clinic (66 cognitively unimpaired, 130 participants with mild cognitive impairment, and 94 with dementia). Participants were classified as amyloid positive (A+) or negative (A-) according to CSF Aß1-42/Aß1-40 ratio. Plasma pTau217, pTau181, Aß1-42 and Aß1-40 were measured in the fully-automated LUMIPULSE platform. We used linear regression to compare plasma biomarkers concentrations between A + and A- groups, evaluated Spearman's correlation between plasma and CSF and performed ROC analyses to assess their diagnostic accuracy to detect brain amyloidosis as determined by CSF Aß1-42/Aß1-40 ratio. We analyzed the potential of pTau217 to predict amyloidosis in CSF. RESULTS: Plasma pTau217 and pTau181 concentration were higher in A + than A- while the plasma Aß1-42/Aß1-40 ratio was lower in A + compared to A-. pTau181 and the Aß1-42/Aß1-40 ratio showed moderate correlation between plasma and CSF (Rho = 0.66 and 0.69, respectively). The areas under the ROC curve to discriminate A + from A- participants were 0.94 (95% CI 0.92-0.97) for pTau217, and 0.88 (95% CI 0.84-0.92) for both pTau181 and Aß1-42/Aß1-40. Chronic kidney disease (CKD) was related to increased plasma biomarker concentrations, but ratios were less affected. Plasma pTau217 had the highest fold change (x4.2) and showed high predictive capability in discriminating A + from A-, having 4-7% misclassification rate. The global accuracy of plasma pTau217 using a two-threshold approach was robust in symptomatic groups, exceeding 90%. CONCLUSION: The evaluation of blood biomarkers on an automated platform exhibited high diagnostic accuracy for AD pathophysiology, and pTau217 showed excellent diagnostic accuracy to identify participants with AD in a consecutive sample representing the routine clinical practice in a specialized memory unit.

The Aß1-42/Aß1-40 ratio in CSF is more strongly associated to tau markers and clinical progression than Aß1-42 alone.

BACKGROUND: Cerebrospinal fluid (CSF) Aß1-42 levels and the Aß1-42/Aß1-40 ratio are markers of amyloid pathology, but previous studies suggest that their levels might be influenced by additional pathophysiological processes. AIMS: To compare Aß1-42 and the Aß1-42/Aß1-40 ratio in CSF in different neurodegenerative disorders and study their association with other biomarkers (tTau, pTau181, and NfL) and with cognitive and functional progression. METHODS: We included all participants from the Sant Pau Initiative on Neurodegeneration (SPIN) with CSF Aß1-42 and Aß1-42/Aß1-40. Participants had diagnoses of Alzheimer's disease (AD), dementia with Lewy bodies, frontotemporal lobar degeneration-related syndromes, non-neurodegenerative conditions, or were cognitively normal. We classified participants as "positive" or "negative" according to each marker. We compared CSF levels of tTau, pTau181, and NfL between concordant and discordant groups through ANCOVA and assessed differences in cognitive (MMSE, FCSRT) and functional (GDS, CDR-SOB) progression using Cox regression and linear-mixed models. RESULTS: In the 1791 participants, the agreement between Aß1-42 and Aß1-42/Aß1-40 was 78.3%. The Aß1-42/Aß1-40 ratio showed a stronger correlation with tTau and pTau181 than Aß1-42 and an agreement with tTau and pTau181 of 73.1% and 77.1%, respectively. Participants with a low Aß1-42/Aß1-40 ratio showed higher tTau and pTau181 and worse cognitive and functional prognosis, regardless of whether they were positive or negative for Aß1-42. The results were consistent across stages, diagnostic categories, and use of different cutoffs. CONCLUSION: Although Aß1-42 and Aß1-42/Aß1-40 are considered markers of the same pathophysiological pathway, our findings provide evidence favoring the use of the Aß1-42/Aß1-40 ratio in clinical laboratories in the context of AD.

Plasma glial fibrillary acidic protein and neurofilament light chain for the diagnostic and prognostic evaluation of frontotemporal dementia.

BACKGROUND: Astrocytes play an essential role in neuroinflammation and are involved in the pathogenesis of neurodenegerative diseases. Studies of glial fibrillary acidic protein (GFAP), an astrocytic damage marker, may help advance our understanding of different neurodegenerative diseases. In this study, we investigated the diagnostic performance of plasma GFAP (pGFAP), plasma neurofilament light chain (pNfL) and their combination for frontotemporal dementia (FTD) and Alzheimer's disease (AD) and their clinical utility in predicting disease progression. METHODS: pGFAP and pNfL concentrations were measured in 72 FTD, 56 AD and 83 cognitively normal (CN) participants using the Single Molecule Array technology. Of the 211 participants, 199 underwent cerebrospinal (CSF) analysis and 122 had magnetic resonance imaging. We compared cross-sectional biomarker levels between groups, studied their diagnostic performance and assessed correlation between CSF biomarkers, cognitive performance and cortical thickness. The prognostic performance was investigated, analyzing cognitive decline  through group comparisons by tertile. RESULTS: Unlike pNfL, which was increased similarly in both clinical groups, pGFAP was increased in FTD but lower than in AD (all P < 0.01). Combination of both plasma markers improved the diagnostic performance to discriminate FTD from AD (area under the curve [AUC]: combination 0.78; pGFAP 0.7; pNfL 0.61, all P < 0.05). In FTD, pGFAP correlated with cognition, CSF and plasma NfL, and cortical thickness (all P < 0.05). The higher tertile of pGFAP was associated with greater change in MMSE score and poor cognitive outcome during follow-up both in FTD (1.40 points annually, hazard ratio [HR] 3.82, P < 0.005) and in AD (1.20 points annually, HR 2.26, P < 0.005). CONCLUSIONS: pGFAP and pNfL levels differ in FTD and AD, and their combination is useful for distinguishing between the two diseases. pGFAP could also be used to track disease severity and predict greater cognitive decline during follow-up in patients with FTD.

Características clínicas de los pacientes con activación de código ictus no identificados por el servicio de emergencias médicas / Clinical characteristics of patients with stroke code activation not identified by the emergency medical service

OBJETIVOS: Determinar la sensibilidad de detección de ictus por parte de los servicios de emergencias médicas (SEM) y analizar las características clínicas de los pacientes con sospecha de ictus no identificados. PACIENTES Y MÉTODOS: Registro prospectivo de pacientes con sospecha de ictus de nuestra área (850.000 habitantes) desde 2011 hasta 2017. Se seleccionó a la población que avisó al SEM. De ésta, se compararon los pacientes con y sin activación de código ictus por parte del SEM (SEM+ frente a SEM-). Se registraron los datos demográficos, el tiempo de evolución, las características clínicas del episodio y el tratamiento de reperfusión administrado. RESULTADOS: De un total de 5.497 pacientes con sospecha de ictus, 2.087 alertaron al SEM: 1.611 (77%) SEM+ y 476 (33%) SEM-. Los pacientes SEM- presentaron menor puntuación en la National Institute of Health Stroke Scale (8 frente a 11) y mayor frecuencia de clínica de territorio vertebrobasilar (14,1% frente a 8,7%) y de clínica hemisférica parcial (23,5% frente a 18,4%), especialmente del hemisferio izquierdo (78,1% frente a 48,4%). Se administró tratamiento de reperfusión en el 29% de los SEM+ y en el 23% de los SEM-. El tiempo desde el inicio de los síntomas hasta el tratamiento fue 42 minutos más largo en el grupo de pacientes SEM- (175 frente a 133 minutos). CONCLUSIONES: La sensibilidad del SEM para detectar pacientes con ictus en nuestra serie es del 77%. Hemos identificado características clínicas asociadas a la falta de sensibilidad, como los síntomas de territorio vertebrobasilar o el trastorno de lenguaje aislado

AIMS: To determine the sensitivity of stroke detection by emergency medical services (EMS) and to analyse the clinical characteristics of unidentified patients with suspected stroke. PATIENTS AND METHODS: Prospective register of patients with suspected stroke in our area (850,000 inhabitants) from 2011 to 2017. The population that notified the EMS was selected. Of this population, patients with and without stroke code activation by the EMS were compared (EMS+ versus EMS-). Demographics, time to progression, clinical characteristics of the episode and reperfusion therapy administered were recorded. RESULTS: Of a total of 5,497 patients with suspected stroke, 2,087 alerted the EMS: 1,611 (77%) EMS+ and 476 (33%) EMS-. The EMS- patients presented lower scores on the National Institute of Health Stroke Scale (8 vs. 11) and a greater frequency of clinical features of the vertebrobasilar territory (14.1% vs. 8.7%) and partial hemispheric clinical features (23.5% vs. 18.4%), especially in the left hemisphere (78.1% vs. 48.4%). Reperfusion treatment was administered in 29% of EMS+ and 23% of EMS-. The time from symptom onset to treatment was 42 minutes longer in the EMS group (175 versus 133 minutes). CONCLUSIONS: The sensitivity of EMS to detect stroke patients in our series is 77%. We have identified clinical features associated with lack of sensitivity, such as vertebrobasilar territory symptoms or isolated language disorder