Bornhorst, Joshua

Abstract INTRODUCTION When cerebrospinal fluid (CSF) and positron emission tomography (PET) measurements for amyloid‐beta‐peptide (Aβ) related pathology are discordant, therapeutic decision‐making becomes uncertain. METHODS Using data from patients with mild cognitive impairment ( n = 541) from the Alzheimer's Disease Neuroimaging Initiative, we examined baseline characteristics and longitudinal clinical outcomes in persons grouped according to normal/abnormal Aβ via concurrent CSF and PET determinations using standard cutpoints. RESULTS Discordant groups for brain Aβ status (CSF+/PET− and CSF−/PET+) each represented about 5% of the mild cognitive impairment (MCI) population. Longitudinally, neither discordant group declined more than the CSF−/PET− group on either a memory measure or the Clinical Dementia Rating Sum of Boxes scores over a median 4 years of observation, while the CSF+/PET+ group exhibited worsening on both measures. DISCUSSION In contrast to the clinical decline observed in the CSF+/PET+ group, persons with MCI and CSF+/PET− or CSF−/PET+ brain amyloid patterns did not exhibit incipient decline. Highlights Discrepant abnormal cerebrospinal fluid (CSF) and positron emission tomography (PET) brain amyloid indicators are uncommon in mild cognitive impairment (MCI). CSF‐PET discrepant persons with MCI tend to have less abnormal values initially. CSF‐PET discrepant persons with MCI have a benign prognosis at 4 years.

Abstract INTRODUCTION Plasma biomarkers of Alzheimer's disease (AD) represent accessible alternatives to positron emission tomography (PET) and cerebrospinal fluid (CSF)‐based biomarkers in well‐characterized cohorts. It remains to be determined whether performance is maintained in outpatient clinics comprised of patients with multiple causes of cognitive impairment. METHODS Plasma phosphorylated tau217 (p‐tau217) and amyloid beta (Aβ) 42/40 were measured in 509 patients evaluated in a tertiary‐care memory clinic. Biomarker performance was compared across diagnoses, referencing established cutpoints for positive and negative biomarkers. RESULTS Plasma p‐tau217 distinguished patients with diagnoses of symptomatic AD with 95% sensitivity and 82% specificity. Integration of Aβ42 measurements (p‐tau217/Aβ42) incrementally improved specificity (86%). Plasma p‐tau217 and p‐tau217/Aβ42 concentrations closely associated with established CSF biomarkers of AD (area under the curve [AUC]: 0.94 and 0.96, respectively). Reduced kidney function associated with elevated plasma p‐tau217 and p‐tau217/Aβ42 concentrations in patients without AD (referencing CSF biomarkers). DISCUSSION Plasma p‐tau217 and p‐tau217/Aβ42 concentrations demonstrated robust diagnostic performance in a heterogeneous clinical cohort; interpretation requires consideration of kidney function. Highlights Plasma phosphorylated tau217 (p‐tau217) reliably identified clinic patients with Alzheimer's disease. A two‐cutpoint strategy yielded definitive results in 86% of patients. Integration of plasma amyloid beta (Aβ; p‐tau217/Aβ42) minimally improved diagnostic performance. Plasma p‐tau217 levels were increased in patients with kidney dysfunction.

AbstractINTRODUCTIONWe compare the stability of phosphorylated tau (p‐tau)217, amyloid beta (Aβ)42, Aβ40, Aβ42/40, and p‐tau217/Aβ42 at different storage temperatures.METHODSTen ethylenediaminetetraacetic acid–plasma sample aliquots stored at frozen, refrigerated, and ambient temperatures were tested at various timepoints up to 30 days. The mean percent change from baseline was calculated.RESULTSAβ42 and Aβ40 concentrations decreased by >15% after 6 hours at ambient temperature and after 24 hours refrigerated, while p‐tau217 remained stable over 72 hours with < 10% deviation from baseline at either storage temperature. The Aβ42/40 ratio remained relatively constant as each analyte concentration decreased concurrently, while the p‐tau217/Aβ42 ratio deviated from baseline over time. All biomarkers were stable up to 30 days frozen.DISCUSSIONDifferences in the stability of Aβ42 and p‐tau217 may lead to altered p‐tau217/Aβ42 ratio results if samples are not handled properly during the pre‐analytical testing phase. Ideally, samples should be frozen promptly and sent to the laboratory frozen.Highlights Plasma phosphorylated tau (p‐tau)217, amyloid beta (Aβ)42, Aβ40, Aβ42/40, and p‐tau217/Aβ42 stability was assessed. P‐tau217 was stable, but Aβ42 and Aβ40 started decreasing by 6 hours at ambient temperature. The analyte stability differences led to falsely increased p‐tau217/Aβ42 ratios. Increases > 15% were seen in p‐tau217/Aβ42 after 6 hours at ambient temperature or 24 hours at 4°C.

AbstractBackgroundEvidence for abnormal amyloid‐β (Aβ) plaque accumulation is necessary prior to initiating anti‐amyloid therapy in early symptomatic Alzheimer’s disease (AD). While the clinical trials for lecanemab and related drugs utilized positron emission tomography (PET) to demonstrate brain amyloidosis, current appropriate use recommendations for clinical practice consider PET or cerebrospinal fluid (CSF) biomarkers as satisfactory for this purpose. Here, we present four clinical cases where CSF biomarker results were discordant from amyloid PET, with the potential to result in erroneous treatment targeting.MethodPatients were seen at a tertiary care subspecialty clinic in consideration for lecanemab therapy. All patients had office examination, neuropsychological assessment, structural magnetic resonance imaging (MRI), amyloid PET (with either 11C‐Pittsburgh compound B or 18F‐florbetapir), CSF AD biomarkers (Roche Elecsys p‐tau181/Aβ42 and Fujirebio Lumipulse Aβ42/Aβ40 ratios), and apolipoprotein E (APOE) allele testing. Amyloid PET interpretations were made by consensus visual review from experienced readers.ResultAll four patients had clinical diagnoses of mild cognitive impairment or mild dementia (Table 1). Two patients had positive CSF p‐tau181/Aβ42 and Aβ42/40 ratios with negative amyloid PET (indicating sparse to no neuritic plaques). Case 1 displayed aphasia (characterized by anomia and deep dysgraphia) and imaging findings possibly compatible with semantic dementia. Case 2 displayed a gait abnormality and imaging signs of abnormal CSF dynamics. Two other patients had negative CSF p‐tau181/Aβ42 measures with positive amyloid PET (indicating moderate to frequent neuritic plaques). In those instances, the clinical syndrome and imaging studies were strongly supportive of AD and the CSF Aβ42/40 ratio was “likely positive” (Table 1). For one patient (Case 4), tau PET and Lumipulse plasma p‐tau217 concentration were both positive.ConclusionClinicians prescribing anti‐amyloid therapies should be aware of the possibility for CSF biomarkers to be discordant from amyloid PET status in select scenarios. These cases highlight the value of considering PET imaging in the presence of clinically atypical features, concern for mixed etiology, or strong clinical suspicion for AD despite negative CSF biomarkers. Larger series are needed to identify broader patterns contributing to biomarker discordance by assay, modality (PET versus CSF/plasma measures), and medical/neurologic comorbidities.

AbstractBackgroundNeurofilament Light Chain (NfL) is a blood biomarker of axonal injury and neurodegeneration that can be used in a variety of neurological disorders. Despite the potential clinical use of plasma NfL across multiple neurological disorders, there is increasing evidence that underlying comorbidities such as renal impairment associated with chronic kidney disease (CKD) and cardiovascular diseases can increase NfL concentrations. The objective of this study was to determine the relationship between plasma NfL concentrations and renal function (CKD staging) in individuals without known neurological conditions.MethodsIndividuals (n=62) seen in an outpatient setting at Mayo Clinic who had various stages of renal impairment (stages 1‐5 by CKD‐EPI 2021 estimated glomerular filtration rate (eGFR) equation) and did not have co‐existing conditions that are known to elevate plasma NfL were retrospectively identified through electronic medical record review. EDTA plasma from these patients collected within +/‐ 30 days of the eGFR determination was identified and stored frozen (‐80°C) until the time of testing. Samples were tested using the Simoa® NF‐light™ V2 Advantage Kit (Quanterix). NfL concentrations in pg/mL were used to calculate age‐adjusted Z‐scores (https://shiny.dkfbasel.ch/baselnflreference/) using an online calculator. Correlation analysis was performed to assess associations of continuous eGFR (mL/min/ 1.73 m2) with plasma NfL age‐adjusted Z‐scores.ResultsA strong negative correlation between NfL Z‐score and eGFR was observed (Spearman’s ρ= ‐0.806). Mean NfL Z‐scores (ranges) in each CKD stage were ‐0.4(‐2.3‐1.4) for stage 1 (N=9), 0.9(‐0.8‐1.9) for stage 2 (N=10), 1.9(‐1.2‐3.4) for stage 3 (N=29), 2.9(2.7‐3.5) for stage 4 (N=6), and 3.2(1.6‐3.7) for stage 5 (N=8); with all groups showing significant differences (P>0.05) except between groups 4 and 5 (P=0.09).ConclusionsPlasma NfL concentrations were increased in individuals with a decreased eGFR. Kidney impairment is an important potential confounding factor to consider when utilizing NfL as a biomarker of neurodegeneration in the clinical setting.

AbstractBackgroundTau phosphorylated at threonine 217 (pTau217) is one of the most promising blood‐based biomarkers of Alzheimer’s disease (AD). This study compares the performance of two plasma pTau217 immunoassays on the Simoa platform for detection of abnormal amyloid‐PET.MethodPlasma samples from 112 individuals without cognitive impairment and 114 with mild cognitive impairment (MCI) or AD related dementia were evaluated. Testing was performed on the Quanterix Simoa® HD‐X Analyzer using the ALZpath Simoa® pTau217 and the Simoa® ACC pTau217 (Janssen antibodies) commercial assays. Amyloid‐PET imaging was performed using 11C‐Pittsburgh Compound B and a standard uptake value ratio (SUVR) cutoff of ≥1.52 (≥25 Centiloid) was used for abnormal (n= 147) vs. normal (n= 79) classification. Passing‐Bablok regression analysis and Spearman’s correlation coefficient (rho) were used to estimate bias and correlation between the assays, respectively. Correlation of each assay with Amyloid‐PET SUVR was evaluated. Amyloid‐PET status as the outcome and plasma pTau217 as predictor was used to estimate the area under the receiver operating characteristic (ROC) curve (AUC).ResultThe pTau217 concentrations between the two assays showed an excellent correlation (Spearman’s rho= 0.94 [95% CI= 0.93 to 0.96, p<0.0001]). However, the Passing‐Bablok regression analysis equation for ALZpath (x‐axis) and ACC (y‐axis) was y= 0.1324x ‐ 0.0019, showing that measured pTau217 concentrations with the ALZpath assay were higher (∼87%) than with the ACC assay (concentrations ranged 0.057 to 3.5 pg/mL and 0.003 to 0.5 pg/mL, respectively). Correlations between amyloid‐PET SUVR and the two pTau217 immunoassays were almost identical with Spearman’s rho= 0.70 (95% CI= 0.62 to 0.76, p<0.0001) for ALZpath and 0.69 (95% CI= 0.61 to 0.75, p<0.0001) for ACC. The AUC for detection of an abnormal amyloid‐PET among the MCI/AD group was 0.88 (95% CI= 0.81 to 0.95) for ALZpath, and 0.89 (95% CI= 0.83 to 0.96) for ACC.ConclusionAnalytically, the two Simoa® pTau217 assays correlate well with each other, but results are not interchangeable due to a significant proportional bias. Clinically, the performance of the assays was largely equivalent for the detection of abnormal amyloid‐PET by AUC analysis based on their almost identical correlations with amyloid‐PET SUVR.

Abstract Background We sought to evaluate key performance indicators related to an internally developed and deployed artificial intelligence (AI)-augmented kidney stone composition test system for potential improvements in test quality, efficiency, cost-effectiveness, and staff satisfaction. Methods We compared quality, efficiency, staff satisfaction, and financial data from the 6 months after the AI-augmented laboratory test system was deployed (test period) with data from the same 6-month period in the previous year (control period) to determine if AI-augmentation improved key performance indicators of this laboratory test. Results In the 6 months following the deployment (test period) of the AI-augmented kidney stone composition test system, 44 830 kidney stones were analyzed. Of these, 92% of kidney stones were eligible for AI-assisted interpretation. Out of these AI-eligible stones, 45% were able to be auto-released by the AI-augmented test system without human secondary review. Furthermore, the new AI-augmented kidney stone test system resulted in an apparent 40% reduction in incorrect laboratory results. Additionally, the new AI-augmented test system improved laboratory efficiency by 20%, improved staff satisfaction, and reduced the average analysis cost per kidney stone by $0.23. Conclusions The AI-augmented test system improved test quality, efficiency, cost-effectiveness and staff satisfaction related to this kidney stone composition test.

Abstract Background Multianalyte assays with algorithmic analysis (MAAAs), such as the Prostate Health Index (phi), are increasingly utilized for generating disease risk scores. Currently, imprecision and bias in phi are not directly monitored by quality control (QC) assessment of the index but rather by QC assessment of individual components. This may not be adequately controlling for imprecision and bias in the calculated multicomponent phi value itself. Methods Inter- and intra-assay phi precision was compared to precision of the individual component assays. QC measurements from total prostate-specific antigen (PSA), free PSA, and p2PSA were used to calculate a single calculated phi QC metric (PHIc). The frequency of QC failure of PHIc, relative to individual components QC by Westgard rules (13S and 22S), was determined. The effects of varying analyte component assay bias on the resulting PHIc metric were also examined. Results Average measured phi imprecision (6.7% CV) was higher than individual phi analyte component imprecision (3.9–4.5% CV) across 2 Beckman Coulter Unicel DxI 800 instruments. A retrospective examination of PHIc QC over 84 quality control determinations was concurrently carried out for both PHIc and component assay failure patterns, which were dependent on SDs utilized for Westgard evaluation. Finally, reinforcing nonlinear changes in PHIc were observed in select cases of introduced simulated bias of individual component measurements. Conclusions An additional calculated phi QC measure can be introduced to monitor MAAA precision/bias, and in principle calculated index controls may represent a complementary supplemental QC method that could be applied to other MAAA indices.