请用中文对下列段落的主要内容进行翻译：This study presents results of analysis on the largest existing cohort of participants with data available on multiple plasma biomarkers and neuropathologic evaluation. However, there are some limitations. Namely, our top predictive performance was that of ADNC with plasma biomarkers, demographics, and Mayo-PACC with AUC of 0.821 when comparing intermediate/high versus low/none ADNC. This is lower compared to other studies, which have shown AUC of 0.93 when comparing a high ADNC group versus a mixed intermediate/low/none group [5]. Smirnov et al. achieved similar performance to our work using p-tau181in a large cohort to predict high ADNC, but the added value of combining plasma biomarkers was not explored [37]. This performance may be due to the sample composition in these studies, which is reflective of an unselected population in comparison to clinic sample of AD dementia participants and controls seen in other studies. Though the AUC is lower, it is likely reflective of variability seen in the population. The intermediate ADNC category encompasses more variability in the amyloid and tau spectrum, while still showing evidence of neuropathologic change. This group may benefit most from early diagnosis for prognostication and treatment strategies. However, it is important to note that all plasma samples in this work were collected on average 1.5 years prior to death. Although the findings illustrate the biological relationships of the plasma biomarkers and neuropathology, the terminal nature of the participants probably overstates the associations for those persons with longer survivals.

The subgroup analysis of participants without CKD showed an overall trend towards lower prediction performance of neuropathologic change and loss of significance in the variable pool that includes plasma biomarkers. The lower prediction performance seen here are likely due to multiple medical comorbidities that are present in heterogenous participants from a population-based study. CKD and other associated metabolic comorbidities such as cardiovascular disease likely introduce variability in plasma biomarker level measurements and associated with neurodegeneration, making it more difficult to reliably predict underlying neuropathologic changes due to amyloid or tau [10, 28].

Another limitation is the assay used for plasma biomarkers and its scope. Prior head-to-head comparisons have shown that Quanterix p-tau181 and Aβ42/40 ratio may be on the lower end diagnostic performance [15, 17]. Additionally, evidence has shown utility of biomarkers such as p-tau217 and p-tau231, which may further improve prediction of underlying neuropathologic changes [3, 24, 42]. Other platforms such as mass spectrometry may provide more sensitive measures than immunoassays. However, the assay we used is a clinically available assay which increases the clinical relevance of our work. A limitation of this study is that no separate cohort with neuropathology and plasma biomarkers acquired under a different platform assay was included in this study. Such a cohort could confirm the findings described in this work and enhance generalizability. Lastly, collecting demographic, cognitive, and plasma biomarker data from a large population-based study presents several challenges and limitations. For instance, not all participants had complete data across all data pools, particularly when it came to Mayo-PACC scores. Consequently, the sample size decreased as the variable pool increased, which may explain why different variables were selected for the prediction of Braak staging and ADNC from the biomarker only pool (N = 348) compared to the biomarker plus demographics plus cognitive scores pool (N = 262) or why performance decreased in larger variable pools when the same variables were selected.