Ibanez Laura, Liu Menghan, Beric Aleksandra, Timsina Jigyasha, Kholfeld Pat, Bergmann Kristy, Lowery Joey, Sykora Nick, Sanchez-Montejo Brenda, Brock Will, Budde John P, Bateman Randall J, Barthelemy Nicolas, Schindler Suzanne E, Holtzman David M, Benzinger Tammie L S, Xiong Chengjie, Tarawneh Rawan, Moulder Krista, Morris John C, Sung Yun Ju, Cruchaga Carlos
Department of Psychiatry, Washington University School of Medicine.
Department of Neurology, Washington University School of Medicine.
medRxiv. 2024 Jun 14:2024.06.13.24308895. doi: 10.1101/2024.06.13.24308895.
Alzheimer's Disease (AD) biomarker measurement is key to aid in the diagnosis and prognosis of the disease. In the research setting, participant recruitment and retention and optimization of sample use, is one of the main challenges that observational studies face. Thus, obtaining accurate established biomarker measurements for stratification and maximizing use of the precious samples is key. Accurate technologies are currently available for established biomarkers, mainly immunoassays and immunoprecipitation liquid chromatography-mass spectrometry (IP-MS), and some of them are already being used in clinical settings. Although some immunoassays- and IP-MS based platforms provide multiplexing for several different coding proteins there is not a current platform that can measure all the stablished and emerging biomarkers in one run. The NUcleic acid Linked Immuno-Sandwich Assay (NULISA) is a mid-throughput platform with antibody-based measurements with a sequencing output that requires 15μL of sample volume to measure more than 100 analytes, including those typically assayed for AD. Here we benchmarked and compared the AD-relevant biomarkers including in the NULISA against validated assays, in both CSF and plasma. Overall, we have found that CSF measures of Aß42/40, NfL, GFAP, and p-tau217 are highly correlated and have similar predictive performance when measured by immunoassay, mass-spectrometry or NULISA. In plasma, p-tau217 shows a performance similar to that reported with other technologies when predicting amyloidosis. Other established and exploratory biomarkers (total tau, p-tau181, NRGN, YKL40, sTREM2, VILIP1 among other) show a wide range of correlation values depending on the fluid and the platform. Our results indicate that the multiplexed immunoassay platform produces reliable results for established biomarkers in CSF that are useful in research settings, with the advantage of measuring additional novel biomarkers using minimal sample volume.
阿尔茨海默病（AD）生物标志物的检测对于辅助该疾病的诊断和预后评估至关重要。在研究环境中，参与者的招募与留存以及样本使用的优化是观察性研究面临的主要挑战之一。因此，获取用于分层的准确且已确立的生物标志物测量值并最大限度地利用珍贵样本是关键。目前已有准确的技术可用于已确立的生物标志物检测，主要是免疫测定和免疫沉淀液相色谱 - 质谱联用（IP-MS），其中一些已在临床环境中使用。尽管一些基于免疫测定和IP-MS的平台可对几种不同的编码蛋白进行多重检测，但目前尚无一个平台能够一次性检测所有已确立的和新出现的生物标志物。核酸连接免疫夹心测定法（NULISA）是一种中等通量的平台，基于抗体进行检测并具有测序输出，测量超过100种分析物仅需15μL样本体积，包括那些常用于AD检测的分析物。在此，我们在脑脊液和血浆中，将NULISA检测的与AD相关的生物标志物与经过验证的检测方法进行了基准测试和比较。总体而言，我们发现通过免疫测定、质谱或NULISA检测时，脑脊液中Aβ42/40、NfL、GFAP和p-tau217的测量值高度相关且具有相似的预测性能。在血浆中，p-tau217在预测淀粉样变性时表现出与其他技术报道的相似性能。其他已确立的和探索性生物标志物（总tau、p-tau181、NRGN、YKL40、sTREM2、VILIP1等）根据检测的液体和平台不同，显示出广泛的相关值范围。我们的结果表明，这种多重免疫测定平台可为脑脊液中已确立的生物标志物产生可靠的结果，这在研究环境中很有用，其优势在于使用最少的样本体积就能检测额外的新型生物标志物。
