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Clinical Manifestations.

Yuthachai Sarutikriangkri1,2, Thanakit Pongpitakmetha1,3,4,5, Akarin Hiransuthikul1,6

  • 1Memory Clinic, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 26, 2025
PubMed
Summary
This summary is machine-generated.

Plasma p-tau217 shows promise for Alzheimer's disease (AD) diagnosis. New cut-off scores for the Montreal Cognitive Assessment - Thai Version (MoCA-Thai) and MoCA-Memory Index Score (MoCA-MIS) aid in detecting AD pathology in Thailand.

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Area of Science:

  • Neurology
  • Biomarkers
  • Cognitive Assessment

Background:

  • Plasma p-tau217 is an emerging Alzheimer's disease (AD) biomarker, offering a more accessible diagnostic alternative.
  • Cognitive screening tools like MoCA-Thai and MMSE-Thai are vital in clinical settings, but their optimal cut-off scores for identifying AD pathology, especially with plasma biomarkers, are unclear in LMICs.
  • This study investigates the utility of MoCA-Thai, MoCA-MIS, and MMSE-Thai in conjunction with plasma p-tau217 for AD diagnosis.

Purpose of the Study:

  • To evaluate the diagnostic performance of MoCA-Thai, MoCA-MIS, and MMSE-Thai for Alzheimer's disease (AD) using plasma p-tau217.
  • To determine optimal cut-off scores for these cognitive tests to identify AD pathology.
  • To assess the feasibility of integrating cognitive screening with plasma biomarkers for early AD detection in Thailand.

Main Methods:

  • Recruitment of early-stage dementia patients (CDR ≤ 1) from the INDE cohort in Thailand.
  • Determination of AD pathology using a validated plasma p-tau217 cut-off (>7.46 pg/mL).
  • Application of Receiver Operating Characteristic (ROC) analysis and Youden's index to identify optimal cut-off scores for cognitive assessments.

Main Results:

  • AD patients exhibited significantly lower scores on MoCA-Thai, MoCA-MIS, and MMSE-Thai compared to non-AD individuals.
  • MoCA-MIS demonstrated the highest discriminative ability (AUROC = 0.762), followed by MoCA-Thai (AUROC = 0.738) and MMSE-Thai (AUROC = 0.725).
  • Optimal cut-off scores were identified as ≤21 for MoCA-Thai (Sensitivity = 75%, Specificity = 69%) and ≤6 for MoCA-MIS (Sensitivity = 67%, Specificity = 77%).

Conclusions:

  • A MoCA-Thai cut-off of ≤21 and a MoCA-MIS cut-off of ≤6 effectively identify AD pathology in the studied cohort.
  • These findings support the integration of cognitive screening tests with plasma biomarkers for enhanced early AD detection.
  • The study highlights the potential of these combined approaches in clinical settings in Thailand, particularly where advanced diagnostic access is limited.