Clinical value of plasma ALZpath pTau217 immunoassay for assessing mild cognitive impairment.

ALZHEIMER'S DISEASE

Journal

Journal of neurology, neurosurgery, and psychiatry
ISSN: 1468-330X
Titre abrégé: J Neurol Neurosurg Psychiatry
Pays: England
ID NLM: 2985191R

Informations de publication

Date de publication:
24 Apr 2024
Historique:
received: 25 01 2024
accepted: 04 04 2024
medline: 25 4 2024
pubmed: 25 4 2024
entrez: 24 4 2024
Statut: aheadofprint

Résumé

Among plasma biomarkers for Alzheimer's disease (AD), pTau181 and pTau217 are the most promising. However, transition from research to routine clinical use will require confirmation of clinical performance in prospective cohorts and evaluation of cofounding factors. pTau181 and pTau217 were quantified using, Quanterix and ALZpath, SIMOA assays in the well-characterised prospective multicentre BALTAZAR (Biomarker of AmyLoid pepTide and AlZheimer's diseAse Risk) cohort of participants with mild cognitive impairment (MCI). Among participants with MCI, 55% were Aβ+ and 29% developed dementia due to AD. pTau181 and pTau217 were higher in the Aβ+ population with fold change of 1.5 and 2.7, respectively. MCI that converted to AD also had higher levels than non-converters, with HRs of 1.38 (1.26 to 1.51) for pTau181 compared with 8.22 (5.45 to 12.39) for pTau217. The area under the curve for predicting Aβ+ was 0.783 (95% CI 0.721 to 0.836; cut-point 2.75 pg/mL) for pTau181 and 0.914 (95% CI 0.868 to 0.948; cut-point 0.44 pg/mL) for pTau217. The high predictive power of pTau217 was not improved by adding age, sex and apolipoprotein E ε4 (APOEε4) status, in a logistic model. Age, APOEε4 and renal dysfunction were associated with pTau levels, but the clinical performance of pTau217 was only marginally altered by these factors. Using a two cut-point approach, a 95% positive predictive value for Aβ+ corresponded to pTau217 >0.8 pg/mL and a 95% negative predictive value at <0.23 pg/mL. At these two cut-points, the percentages of MCI conversion were 56.8% and 9.7%, respectively, while the annual rates of decline in Mini-Mental State Examination were -2.32 versus -0.65. Plasma pTau217 and pTau181 both correlate with AD, but the fold change in pTau217 makes it better to diagnose cerebral amyloidosis, and predict cognitive decline and conversion to AD dementia.

Sections du résumé

BACKGROUND BACKGROUND
Among plasma biomarkers for Alzheimer's disease (AD), pTau181 and pTau217 are the most promising. However, transition from research to routine clinical use will require confirmation of clinical performance in prospective cohorts and evaluation of cofounding factors.
METHOD METHODS
pTau181 and pTau217 were quantified using, Quanterix and ALZpath, SIMOA assays in the well-characterised prospective multicentre BALTAZAR (Biomarker of AmyLoid pepTide and AlZheimer's diseAse Risk) cohort of participants with mild cognitive impairment (MCI).
RESULTS RESULTS
Among participants with MCI, 55% were Aβ+ and 29% developed dementia due to AD. pTau181 and pTau217 were higher in the Aβ+ population with fold change of 1.5 and 2.7, respectively. MCI that converted to AD also had higher levels than non-converters, with HRs of 1.38 (1.26 to 1.51) for pTau181 compared with 8.22 (5.45 to 12.39) for pTau217. The area under the curve for predicting Aβ+ was 0.783 (95% CI 0.721 to 0.836; cut-point 2.75 pg/mL) for pTau181 and 0.914 (95% CI 0.868 to 0.948; cut-point 0.44 pg/mL) for pTau217. The high predictive power of pTau217 was not improved by adding age, sex and apolipoprotein E ε4 (APOEε4) status, in a logistic model. Age, APOEε4 and renal dysfunction were associated with pTau levels, but the clinical performance of pTau217 was only marginally altered by these factors. Using a two cut-point approach, a 95% positive predictive value for Aβ+ corresponded to pTau217 >0.8 pg/mL and a 95% negative predictive value at <0.23 pg/mL. At these two cut-points, the percentages of MCI conversion were 56.8% and 9.7%, respectively, while the annual rates of decline in Mini-Mental State Examination were -2.32 versus -0.65.
CONCLUSIONS CONCLUSIONS
Plasma pTau217 and pTau181 both correlate with AD, but the fold change in pTau217 makes it better to diagnose cerebral amyloidosis, and predict cognitive decline and conversion to AD dementia.

Identifiants

pubmed: 38658136
pii: jnnp-2024-333467
doi: 10.1136/jnnp-2024-333467
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Investigateurs

Yasmina Boudali (Y)
Jacques Touchon (J)
Marie-Laure Seux (ML)
Hermine Lenoir (H)
Catherine Bayle (C)
Christine Delmaire (C)
Xavier Delbeuck (X)
Florence Moulin (F)
Emmanuelle Duron (E)
Florence Latour (F)
Matthieu Plichart (M)
Sophie Pichierri (S)
Galdric Orvoën (G)
Evelyne Galbrun (E)
Giovanni Castelnovo (G)
Lisette Volpe-Gillot (L)
Florien Labourée (F)
Pascaline Cassagnaud (P)
Françoise Lala (F)
Bruno Vellas (B)
Julien Dumurgier (J)
Anne-Sophie Rigaud (AS)
Christine Perret-Guillaume (C)
Eliana Alonso (E)
Foucaud du Boisgueheneuc (FD)
Laurence Hugonot-Diener (L)
Adeline Rollin-Sillaire (A)
Olivier Martinaud (O)
Clémence Boully (C)
Yann Spivac (Y)
Agnès Devendeville (A)
Joël Belmin (J)
Philippe Robert (P)
Thierry Dantoine (T)
Laure Caillard (L)
David Wallon (D)
Didier Hannequin (D)
Nathalie Sastre (N)
Sophie Haffen (S)
Anna Kearney-Schwartz (A)
Jean-Luc Novella (JL)
Vincent Deramecourt (V)
Valérie Chauvire (V)
Gabiel Abitbol (G)
Nathalie Schwald (N)
Caroline Hommet (C)
François Sellal (F)
Marie-Ange Cariot (MA)
Mohamed Abdellaoui (M)
Sarah Benisty (S)
Salim Gherabli (S)
Pierre Anthony (P)
Frédéric Bloch (F)
Nathalie Charasz (N)
Sophie Chauvelier (S)
Jean-Yves Gaubert (JY)
Guillaume Sacco (G)
Olivier Guerin (O)
Jacques Boddaert (J)
Marc Paccalin (M)
Marie-Anne Mackowiak (MA)
Marie-Thérèse Rabus (MT)
Valérie Gissot (V)
Athanase Benetos (A)
Candice Picard (C)
Céline Guillemaud (C)
Gilles Berrut (G)
Claire Gervais (C)
Jacques Hugon (J)
Jean-Marc Michel (JM)
Jean-Philippe David (JP)
Marion Paulin (M)
Pierre Vandel Pierre-JeanOusset (PV)
Sylvie Pariel (S)
Vincent Camus (V)
Anne Chawakilian (A)
Léna Kermanac'h (L)
Anne-Cécile Troussiere (AC)
Cécile Adam (C)
Diane Dupuy (D)
Elena Paillaud (E)
Hélène Briault (H)
Isabelle Saulnier (I)
Karl Mondon (K)
Marie-Agnès Picat (MA)
Marie Laurent (M)
Olivier Godefroy (O)
Stéphanie Libercier RezkiDaheb (SL)
Djamila Krabchi (D)
Marie Chupin (M)
Edouard Chaussade (E)
Christiane Baret-Rose (C)

Informations de copyright

© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

Déclaration de conflit d'intérêts

Competing interests: None declared.

Auteurs

Sylvain Lehmann (S)

LBPC-PPC, Université de Montpellier, INM INSERM, IRMB CHU de Montpellier, Montpellier, France sylvain.lehmann@umontpellier.fr.

Susanna Schraen-Maschke (S)

Université Lille, Inserm, CHU Lille, UMR-S-U1172, LiCEND, Lille Neuroscience & Cognition, LabEx DISTALZ, F-59000, Lille, France.

Jean-Sébastien Vidal (JS)

Université Paris Cité, EA 4468, APHP, Hospital Broca, Memory Resource and Research Centre of de Paris-Broca-Ile de France, F-75013, Paris, Île-de-France, France.

Constance Delaby (C)

LBPC-PPC, Université de Montpellier, INM INSERM, IRMB CHU de Montpellier, Montpellier, France.
Sant Pau Memory Unit, Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau - Universitat Autònoma de Barcelona, Barcelona, Spain.

Luc Buee (L)

Université Lille, Inserm, CHU Lille, UMR-S-U1172, LiCEND, Lille Neuroscience & Cognition, LabEx DISTALZ, F-59000, Lille, France.

Frédéric Blanc (F)

Université de Strasbourg, Hôpitaux Universitaires de Strasbourg, Memory Resource and Research Centre of Strasbourg/Colmar, French National Centre for Scientific Research (CNRS), ICube Laboratory and Fédération de Médecine Translationnelle de Strasbourg (FMTS), Team Imagerie Multimodale Intégrative en Santé (IMIS)/Neurocrypto, F-67000, Strasbourg, France.

Claire Paquet (C)

Université Paris Cité, GHU APHP Nord Lariboisière Fernand Widal, Centre de Neurologie Cognitive, F-75010, Paris, France.

Bernadette Allinquant (B)

UMR-S1266, Université Paris Cité, Institute of Psychiatry and Neuroscience, Inserm, Paris, France.

Stéphanie Bombois (S)

Université Lille, Inserm, CHU Lille, UMR-S-U1172, LiCEND, Lille Neuroscience & Cognition, LabEx DISTALZ, F-59000, Lille, France.
Assistance Publique-Hôpitaux de Paris (AP-HP), Département de Neurologie, Centre des Maladies Cognitives et Comportementales, GH Pitié-Salpêtrière, Paris, France.

Audrey Gabelle (A)

Université de Montpellier, Memory Research and Resources center, department of Neurology, Inserm INM NeuroPEPs team, F-34000, Montpellier, France.

Olivier Hanon (O)

Université Paris Cité, EA 4468, APHP, Hospital Broca, Memory Resource and Research Centre of de Paris-Broca-Ile de France, F-75013, Paris, Île-de-France, France.

Classifications MeSH