Supplementary Material for: The Utility of CSF Biomarkers in Diagnosing Alzheimer's Disease: A Thai Cohort Study

INTRODUCTION: Cutoff values for cerebrospinal fluid biomarkers vary by analytic technique and population, which complicates the differentiation of Alzheimer’s disease (AD) from non-AD dementias. We aimed to establish local cerebrospinal fluid biomarker cutoffs within a Thai cohort.
MATERIALS AND METHODS: We recruited 68 patients with various forms of dementia from the Memory Clinic at Siriraj Hospital, Thailand. Each patient underwent clinical subtyping for dementia, and their cerebrospinal fluid levels of Aβ42, p-tau181, and t-tau were quantified using the Fujirebio INNOTEST ELISA. We then employed a data-driven approach, specifically a Z-score-based Gaussian Mixture Model, to define intersection cutoffs for Aβ42, p-tau181, t-tau, and the p-tau181/Aβ42 ratio. These established biomarker cutoffs were subsequently incorporated with clinical manifestations to refine the clinicobiological diagnoses.
RESULTS: Our study included 67 patients (mean age 65.5 ± 7.4 years, 61.2% female). Using a data-driven approach, we established the following CSF biomarker cutoffs for identifying AD in this Thai cohort: Aβ42 at 492.67 pg/mL, p-tau181 at 44.00 pg/mL, t-tau at 545.97 pg/mL, and the p-tau181/Aβ42 ratio at 0.057. After incorporating these CSF biomarker results with clinical profiles, the diagnoses changed in 17.9% of the patients.
CONCLUSIONS: In this study, CSF cutoffs for differentiating AD from non-AD dementia were established through a data-driven approach, which has been demonstrated as a valid alternative methodology. The integration of clinical and biological profiles is paramount in achieving accurate dementia diagnoses.

引言：脑脊液生物标志物（cerebrospinal fluid biomarkers）的截断值会因检测技术和人群不同而存在差异，这使得阿尔茨海默病（Alzheimer’s disease, AD）与非AD痴呆的鉴别诊断复杂化。本研究旨在建立泰国人群队列中的本地化脑脊液生物标志物截断值。材料与方法：本研究从泰国诗里拉吉医院（Siriraj Hospital）记忆门诊招募了68例各类痴呆患者。对所有患者进行痴呆临床分型，并采用富士瑞必欧（Fujirebio）INNOTEST酶联免疫吸附试验（ELISA）定量检测其脑脊液中β淀粉样蛋白42（Aβ42）、磷酸化tau蛋白181位（p-tau181）及总tau蛋白（t-tau）水平。随后采用数据驱动方法，具体为基于Z得分的高斯混合模型（Gaussian Mixture Model），确定Aβ42、p-tau181、t-tau及p-tau181/Aβ42比值的交叉截断值。将上述确立的生物标志物截断值与临床表现相结合，以优化临床生物学诊断。结果：本研究最终纳入67例患者（平均年龄65.5±7.4岁，女性占比61.2%）。通过数据驱动方法，本研究为该泰国队列确立了用于鉴别AD的脑脊液生物标志物截断值：Aβ42为492.67 pg/mL，p-tau181为44.00 pg/mL，t-tau为545.97 pg/mL，p-tau181/Aβ42比值为0.057。将脑脊液生物标志物检测结果与临床特征相结合后，17.9%的患者诊断结果发生了调整。结论：本研究通过数据驱动方法确立了用于区分AD与非AD痴呆的脑脊液截断值，该方法已被证实为一种可靠的替代方案。将临床特征与生物学特征相结合，对于实现精准的痴呆诊断至关重要。