A Comprehensive Head-to-Head Comparison of Key Plasma Phosphorylated Tau 217 Biomarker Tests.

Plasma phosphorylated-tau 217 (p-tau217) is currently the most promising biomarkers for reliable detection of Alzheimer's disease (AD) pathology. Various p-tau217 assays have been developed, but their relative performance is unclear. We compared key plasma p-tau217 tests using cross-sectional and longitudinal measures of amyloid-ß (Aß)-PET, tau-PET, and cognition as outcomes, and benchmarked them against cerebrospinal fluid (CSF) biomarker tests. Samples from 998 individuals (mean[range] age 68.5[20.0-92.5], 53% female) from the Swedish BioFINDER-2 cohort were analyzed. Plasma p-tau217 was measured with mass spectrometry (MS) assays (the ratio between phosphorylated and non-phosphorylated [%p-tau217WashU]and ptau217WashU) as well as with immunoassays (p-tau217Lilly, p-tau217Janssen, p-tau217ALZpath). CSF biomarkers included p-tau217Lilly, and the FDA-approved p-tau181/Aß42Elecsys and p-tau181Elecsys. All plasma p-tau217 tests exhibited high ability to detect abnormal Aß-PET (AUC range: 0.91-0.96) and tau-PET (AUC range: 0.94-0.97). Plasma %p-tau217WashU had the highest performance, with significantly higher AUCs than all the immunoassays (P diff<0.007). For detecting Aß-PET status, %p-tau217WashU had an accuracy of 0.93 (immunoassays: 0.83-0.88), sensitivity of 91% (immunoassays: 84-87%), and a specificity of 94% (immunoassays: 85-89%). Among immunoassays, p-tau217Lilly and plasma p-tau217ALZpath had higher AUCs than plasma p-tau217Janssen for Aß-PET status (P diff<0.006), and p-tau217Lilly outperformed plasma p-tau217ALZpath for tau-PET status (P diff=0.025). Plasma %p-tau217WashU exhibited higher associations with all PET load outcomes compared to immunoassays; baseline Aß-PET load (R2: 0.72; immunoassays: 0.47-0.58; Pdiff<0.001), baseline tau-PET load (R2: 0.51; immunoassays: 0.38-0.45; Pdiff<0.001), longitudinal Aß-PET load (R2: 0.53; immunoassays: 0.31-0.38; Pdiff<0.001) and longitudinal tau-PET load (R2: 0.50; immunoassays: 0.35-0.43; Pdiff<0.014). Among immunoassays, plasma p-tau217Lilly was more strongly associated with Aß-PET load than plasma p-tau217Janssen (P diff<0.020) and with tau-PET load than both plasma p-tau217Janssen and plasma p-tau217ALZpath (all P diff<0.010). Plasma %p-tau217 also correlated more strongly with baseline cognition (Mini-Mental State Examination[MMSE]) than all immunoassays (R2 %p-tau217WashU: 0.33; immunoassays: 0.27-0.30; P diff<0.024). The main results were replicated in an external cohort from Washington University in St Louis (n =219). Finally, p-tau217Nulisa showed similar performance to other immunoassays in subsets of both cohorts. In summary, both MS- and immunoassay-based p-tau217 tests generally perform well in identifying Aß-PET, tau-PET, and cognitive abnormalities, but %p-tau217WashU performed significantly better than all the examined immunoassays. Plasma %p-tau217 may be considered as a stand-alone confirmatory test for AD pathology, while some immunoassays might be better suited as triage tests where positive results are confirmed with a second test.

Clinical application of plasma P-tau217 to assess eligibility for amyloid-lowering immunotherapy in memory clinic patients with early Alzheimer's disease.

BACKGROUND: With the approval of disease-modifying treatments (DMTs) for early Alzheimer's disease (AD), there is an increased need for efficient and non-invasive detection methods for cerebral amyloid-ß (Aß) pathology. Current methods, including positron emission tomography (PET) and cerebrospinal fluid (CSF) analysis, are costly and invasive methods that may limit access to new treatments. Plasma tau phosphorylated at threonine-217 (P-tau217) presents a promising alternative, yet optimal cutoffs for treatment eligibility with DMTs like aducanumab require further investigation. This study evaluates the efficacy of one- and two-cutoff strategies for determining DMT eligibility at the Butler Hospital Memory & Aging Program (MAP). METHODS: In this retrospective, cross-sectional diagnostic cohort study, we first developed P-tau217 cutoffs using site-specific and BioFINDER-2 training data, which were then tested in potential DMT candidates from Butler MAP (total n = 150). ROC analysis was used to calculate the area under the curve (AUC) and accuracy of P-tau217 interpretation strategies, using Aß-PET/CSF testing as the standard of truth. RESULTS: Potential DMT candidates at Butler MAP (n = 50), primarily diagnosed with mild cognitive impairment (n = 29 [58%]) or mild dementia (21 [42%]), were predominantly Aß-positive (38 [76%]), and half (25 [50%]) were subsequently treated with aducanumab. Elevated P-tau217 predicted cerebral Aß positivity in potential DMT candidates (AUC = 0.97 [0.92-1]), with diagnostic accuracy ranging from 0.88 (0.76-0.95, p = 0.028) to 0.96 (0.86-1, p < .001). When using site-specific cutoffs, a subset of DMT candidates (10%) exhibited borderline P-tau217 (between 0.273 and 0.399 pg/mL) that would have potentially required confirmatory testing. CONCLUSIONS: This study, which included participants treated with aducanumab, confirms the utility of one- and two-cutoff strategies for interpreting plasma P-tau217 in assessing DMT eligibility. Using P-tau217 could potentially replace more invasive diagnostic methods, and all aducanumab-treated participants would have been deemed eligible based on P-tau217. However, false positives remain a concern, particularly when applying externally derived cutoffs that exhibited lower specificity which could have led to inappropriate treatment of Aß-negative participants. Future research should focus on prospective validation of P-tau217 cutoffs to enhance their generalizability and inform standardized treatment decision-making across diverse populations.

Prediction of future cognitive decline among cognitively unimpaired individuals using measures of soluble phosphorylated tau or tau tangle pathology.

Plasma p-tau217 and Tau-PET are strong prognostic biomarkers in Alzheimer's disease (AD), but their relative performance in predicting future cognitive decline among cognitively unimpaired (CU) individuals is unclear. In this head-to-head comparison study including 9 cohorts and 1534 individuals, we found that plasma p-tau217 and medial temporal lobe Tau-PET signal showed similar associations with cognitive decline on a global cognitive composite test (R2 PET=0.32 vs R2 PLASMA=0.32, pdifference=0.812) and with progression to mild cognitive impairment (Hazard ratio[HR]PET=1.56[1.43-1.70] vs HRPLASMA=1.63[1.50-1.77], pdifference=0.627). Combined plasma and PET models were superior to the single biomarker models (R2=0.36, p<0.01). Furthermore, sequential selection using plasma p-tau217 and then Tau-PET reduced the number of participants required for a clinical trial by 94%, compared to a 75% reduction when using plasma p-tau217 alone. We conclude that plasma p-tau217 and Tau-PET showed similar performance for predicting future cognitive decline in CU individuals, and their sequential use (i.e., plasma p-tau217 followed by Tau-PET in a subset with high plasma p-tau217) is useful for screening in clinical trials in preclinical AD.

Identification of distinct and shared biomarker panels in different manifestations of cerebral small vessel disease through proteomic profiling.

The pathophysiology underlying various manifestations of cerebral small vessel disease (cSVD) remains obscure. Using cerebrospinal fluid proximity extension assays and co-expression network analysis of 2,943 proteins, we found common and distinct proteomic signatures between white matter lesions (WML), microbleeds and infarcts measured in 856 living patients, and validated WML-associated proteins in three additional datasets. Proteins indicative of extracellular matrix dysregulation and vascular remodeling, including ELN, POSTN, CCN2 and MMP12 were elevated across all cSVD manifestations, with MMP12 emerging as an early cSVD indicator. cSVD-associated proteins formed a co-abundance network linked to metabolism and enriched in endothelial and arterial smooth muscle cells, showing elevated levels at early disease manifestations. Later disease stages involved changes in microglial proteins, associated with longitudinal WML progression, and changes in neuronal proteins mediating WML-associated cognitive decline. These findings provide an atlas of novel cSVD biomarkers and a promising roadmap for the next generation of cSVD therapeutics.

Remote and unsupervised digital memory assessments can reliably detect cognitive impairment in Alzheimer's disease.

INTRODUCTION: Remote unsupervised cognitive assessments have the potential to complement and facilitate cognitive assessment in clinical and research settings. METHODS: Here, we evaluate the usability, validity, and reliability of unsupervised remote memory assessments via mobile devices in individuals without dementia from the Swedish BioFINDER-2 study and explore their prognostic utility regarding future cognitive decline. RESULTS: Usability was rated positively; remote memory assessments showed good construct validity with traditional neuropsychological assessments and were significantly associated with tau-positron emission tomography and downstream magnetic resonance imaging measures. Memory performance at baseline was associated with future cognitive decline and prediction of future cognitive decline was further improved by combining remote digital memory assessments with plasma p-tau217. Finally, retest reliability was moderate for a single assessment and good for an aggregate of two sessions. DISCUSSION: Our results demonstrate that unsupervised digital memory assessments might be used for diagnosis and prognosis in Alzheimer's disease, potentially in combination with plasma biomarkers. HIGHLIGHTS: Remote and unsupervised digital memory assessments are feasible in older adults and individuals in early stages of Alzheimer's disease. Digital memory assessments are associated with neuropsychological in-clinic assessments, tau-positron emission tomography and magnetic resonance imaging measures. Combination of digital memory assessments with plasma p-tau217 holds promise for prognosis of future cognitive decline. Future validation in further independent, larger, and more diverse cohorts is needed to inform clinical implementation.

Effects of time of the day at sampling on CSF and plasma levels of Alzheimer' disease biomarkers.

BACKGROUND: Studies suggest that cerebrospinal fluid (CSF) levels of amyloid-ß (Aß)42 and Aß40 present a circadian rhythm. However sustained sampling of large volumes of CSF with indwelling intrathecal catheters used in most of these studies might have affected CSF dynamics and thereby confounded the observed fluctuations in the biomarker levels. METHODS: We included 38 individuals with either normal (N = 20) or abnormal (N = 18) CSF Aß42/Aß40 levels at baseline. CSF and plasma were collected at two visits separated by an average of 53 days with lumbar punctures and venipunctures performed either in the morning or evening. At the first visit, sample collection was performed in the morning for 17 participants and the order was reversed for the remaining 21 participants. CSF and plasma samples were analyzed for Alzheimer' disease (AD) biomarkers, including Aß42, Aß40, GFAP, NfL p-tau181, p-tau217, p-tau231 and t-tau. CSF samples were also tested using mass spectrometry for 22 synaptic and endo-lysosomal proteins. RESULTS: CSF Aß42 (mean difference [MD], 0.21 ng/mL; p = 0.038), CSF Aß40 (MD, 1.85 ng/mL; p < 0.001), plasma Aß42 (MD, 1.65 pg/mL; p = 0.002) and plasma Aß40 (MD, 0.01 ng/mL, p = 0.002) were increased by 4.2-17.0% in evening compared with morning samples. Further, CSF levels of 14 synaptic and endo-lysosomal proteins, including neurogranin and neuronal pentraxin-1, were increased by 4.5-13.3% in the evening samples (MDrange, 0.02-0.56 fmol/µl; p < 0.042). However, no significant differences were found between morning and evening levels for the Aß42/Aß40 ratio, different p-tau variants, GFAP and NfL. There were no significant interaction between sampling time and Aß status for any of the biomarkers, except that CSF t-tau was increased (by 5.74%) in the evening samples compared to the morning samples in Aß-positive (MD, 16.46 ng/ml; p = 0.009) but not Aß-negative participants (MD, 1.89 ng/ml; p = 0.47). There were no significant interactions between sampling time and order in which samples were obtained. DISCUSSION: Our findings provide evidence for diurnal fluctuations in Aß peptide levels, both in CSF and plasma, while CSF and plasma p-tau, GFAP and NfL were unaffected. Importantly, Aß42/Aß40 ratio remained unaltered, suggesting that it is more suitable for implementation in clinical workup than individual Aß peptides. Additionally, we show that CSF levels of many synaptic and endo-lysosomal proteins presented a diurnal rhythm, implying a build-up of neuronal activity markers during the day. These results will guide the development of unified sample collection procedures to avoid effects of diurnal variation for future implementation of AD biomarkers in clinical practice and drug trials.

A machine learning-based prediction of tau load and distribution in Alzheimer's disease using plasma, MRI and clinical variables.

Tau positron emission tomography (PET) is a reliable neuroimaging technique for assessing regional load of tau pathology in the brain, commonly used in Alzheimer's disease (AD) research and clinical trials. However, its routine clinical use is limited by cost and accessibility barriers. Here we explore using machine learning (ML) models to predict clinically useful tau-PET outcomes from low-cost and non-invasive features, e.g., basic clinical variables, plasma biomarkers, and structural magnetic resonance imaging (MRI). Results demonstrated that models including plasma biomarkers yielded highly accurate predictions of tau-PET burden (best model: R-squared=0.66-0.68), with especially high contribution from plasma P-tau217. In contrast, MRI variables stood out as best predictors (best model: R-squared=0.28-0.42) of asymmetric tau load between the two hemispheres (an example of clinically relevant spatial information). The models showed high generalizability to external test cohorts with data collected at multiple sites. Based on these results, we also propose a proof-of-concept two-step classification workflow, demonstrating how the ML models can be translated to a clinical setting. This study reveals current potential in predicting tau-PET information from scalable cost-effective variables, which could improve diagnosis and prognosis of AD.

Clinical application of plasma P-tau217 to assess eligibility for amyloid-lowering immunotherapy in memory clinic patients with early Alzheimer's disease.

Background: With the approval of disease-modifying treatments (DMTs) for early Alzheimer's disease (AD), there is an increased need for efficient and non-invasive detection methods for cerebral amyloid-ß (Aß) pathology. Current methods, including positron emission tomography (PET) and cerebrospinal fluid (CSF) analysis, are costly and invasive methods that may limit access to new treatments. Plasma tau phosphorylated at threonine-217 (P-tau217) presents a promising alternative, yet optimal cutoffs for treatment eligibility with DMTs like aducanumab require further investigation. This study evaluates the efficacy of one- and two-cutoff strategies for determining DMT eligibility at the Butler Hospital Memory & Aging Program (MAP). Methods: In this retrospective, cross-sectional diagnostic cohort study, we first developed P-tau217 cutoffs using site-specific training data and BioFINDER-2, which were then tested in potential DMT candidates from Butler MAP (total n = 150). ROC analysis was used to calculate the area under the curve (AUC) and accuracy of P-tau217 interpretation strategies, using Aß-PET/CSF testing as the standard of truth. Results: Potential DMT candidates at Butler MAP (n = 50), primarily diagnosed with mild cognitive impairment (n = 29 [58%]) or mild dementia (21 [42%]), were predominantly Aß-positive (38 [76%]), and half (25 [50%]) were subsequently treated with aducanumab. Elevated P-tau217 predicted cerebral Aß positivity in potential DMT candidates (AUC = 0.97 [0.92-1]), with diagnostic accuracy ranging from 0.88 (0.76-0.95, p = 0.028) to 0.96 (0.86-1, p < .001). When using site-specific cutoffs, a subset of DMT candidates (10%) exhibited borderline P-tau217 (between 0.273 and 0.399 pg/mL) that would have potentially required from confirmatory testing. Conclusions: This study, which included participants treated with aducanumab, confirms the utility of one- and two-cutoff strategies for interpreting plasma P-tau217 in assessing DMT eligibility. Using P-tau217 could potentially replace more invasive diagnostic methods, and all aducanumab-treated participants would have been deemed eligible based on P-tau217. However, false positives remain a concern, particularly when applying externally derived cutoffs that exhibited lower specificity which could have led to inappropriate treatment of Aß-negative participants. Future research should focus on prospective validation of P-tau217 cutoffs to enhance their generalizability and inform standardized treatment decision-making across diverse populations.

Head-to-Head Comparison of Tau and Amyloid Positron Emission Tomography Visual Reads for Differential Diagnosis of Neurodegenerative Disorders: An International, Multicenter Study.

OBJECTIVE: We compared the accuracy of amyloid and [18F]Flortaucipir (FTP) tau positron emission tomography (PET) visual reads for distinguishing patients with mild cognitive impairment (MCI) or dementia with fluid biomarker support of Alzheimer's disease (AD). METHODS: Participants with FTP-PET, amyloid-PET, and diagnosis of dementia-AD (n = 102), MCI-AD (n = 41), non-AD diseases (n = 76), and controls (n = 20) were included. AD status was determined independent of PET by cerebrospinal fluid or plasma biomarkers. The mean age was 66.9 years, and 44.8% were women. Three readers interpreted scans blindly and independently. Amyloid-PET was classified as positive/negative using tracer-specific criteria. FTP-PET was classified as positive with medial temporal lobe (MTL) binding as the minimum uptake indicating AD tau (tau-MTL+), positive with posterolateral temporal or extratemporal cortical binding in an AD-like pattern (tau-CTX+), or negative. The majority of scan interpretations were used to calculate diagnostic accuracy of visual reads in detecting MCI/dementia with fluid biomarker support for AD (MCI/dementia-AD). RESULTS: Sensitivity of amyloid-PET for MCI/dementia-AD was 95.8% (95% confidence interval 91.1-98.4%), which was comparable to tau-CTX+ 92.3% (86.7-96.1%, p = 0.67) and tau-MTL+ 97.2% (93.0-99.2%, p = 0.27). Specificity of amyloid-PET for biomarker-negative healthy and disease controls was 84.4% (75.5-91.0%), which was like tau-CTX+ 88.5% (80.4-94.1%, p = 0.34), and trended toward being higher than tau-MTL+ 75.0% (65.1-83.3%, p = 0.08). Tau-CTX+ had higher specificity than tau-MTL+ (p = 0.0002), but sensitivity was lower (p = 0.02), driven by decreased sensitivity for MCI-AD (80.5% [65.1-91.2] vs. 95.1% [83.5-99.4], p = 0.03). INTERPRETATION: Amyloid- and tau-PET visual reads have similar sensitivity/specificity for detecting AD in cognitively impaired patients. Visual tau-PET interpretations requiring cortical binding outside MTL increase specificity, but lower sensitivity for MCI-AD. ANN NEUROL 2024.

Medial temporal lobe atrophy patterns in early- versus late-onset amnestic Alzheimer's disease.

Background: The medial temporal lobe (MTL) is hypothesized to be relatively spared in early-onset Alzheimer's disease (EOAD). Yet, detailed examination of MTL subfield volumes and drivers of atrophy in amnestic EOAD is lacking. Methods: BioFINDER-2 participants with memory impairment, abnormal amyloid-ß status and tau-PET were included. Forty-one EOAD individuals aged ≤65 years and, as comparison, late-onset AD (LOAD, ≥70 years, n=154) and Aß-negative cognitively unimpaired controls were included. MTL subregions and biomarkers of (co-)pathologies were measured. Results: AD groups showed smaller MTL subregions compared to controls. Atrophy patterns were similar across AD groups, although LOAD showed thinner entorhinal cortices compared to EOAD. EOAD showed lower WMH compared to LOAD. No differences in MTL tau-PET or transactive response DNA binding protein 43-proxy positivity was found. Conclusions: We found in vivo evidence for MTL atrophy in amnestic EOAD and overall similar levels to LOAD of MTL tau pathology and co-pathologies.

Combining plasma Aß and p-tau217 improves detection of brain amyloid in non-demented elderly.

BACKGROUND: Maximizing the efficiency to screen amyloid-positive individuals in asymptomatic and non-demented aged population using blood-based biomarkers is essential for future success of clinical trials in the early stage of Alzheimer's disease (AD). In this study, we elucidate the utility of combination of plasma amyloid-ß (Aß)-related biomarkers and tau phosphorylated at threonine 217 (p-tau217) to predict abnormal Aß-positron emission tomography (PET) in the preclinical and prodromal AD. METHODS: We designed the cross-sectional study including two ethnically distinct cohorts, the Japanese trial-ready cohort for preclinica and prodromal AD (J-TRC) and the Swedish BioFINDER study. J-TRC included 474 non-demented individuals (CDR 0: 331, CDR 0.5: 143). Participants underwent plasma Aß and p-tau217 assessments, and Aß-PET imaging. Findings in J-TRC were replicated in the BioFINDER cohort including 177 participants (cognitively unimpaired: 114, mild cognitive impairment: 63). In both cohorts, plasma Aß(1-42) (Aß42) and Aß(1-40) (Aß40) were measured using immunoprecipitation-MALDI TOF mass spectrometry (Shimadzu), and p-tau217 was measured with an immunoassay on the Meso Scale Discovery platform (Eli Lilly). RESULTS: Aß-PET was abnormal in 81 participants from J-TRC and 71 participants from BioFINDER. Plasma Aß42/Aß40 ratio and p-tau217 individually showed moderate to high accuracies when detecting abnormal Aß-PET scans, which were improved by combining plasma biomarkers and by including age, sex and APOE genotype in the models. In J-TRC, the highest AUCs were observed for the models combining p-tau217/Aß42 ratio, APOE, age, sex in the whole cohort (AUC = 0.936), combining p-tau217, Aß42/Aß40 ratio, APOE, age, sex in the CDR 0 group (AUC = 0.948), and combining p-tau217/Aß42 ratio, APOE, age, sex in the CDR 0.5 group (AUC = 0.955), respectively. Each subgroup results were replicated in BioFINDER, where the highest AUCs were seen for models combining p-tau217, Aß42/40 ratio, APOE, age, sex in cognitively unimpaired (AUC = 0.938), and p-tau217/Aß42 ratio, APOE, age, sex in mild cognitive impairment (AUC = 0.914). CONCLUSIONS: Combination of plasma Aß-related biomarkers and p-tau217 exhibits high performance when predicting Aß-PET positivity. Adding basic clinical information (i.e., age, sex, APOE Îµ genotype) improved the prediction in preclinical AD, but not in prodromal AD. Combination of Aß-related biomarkers and p-tau217 could be highly useful for pre-screening of participants in clinical trials of preclinical and prodromal AD.

MRI-Derived AD Signature of Cortical Thinning and Plasma P-Tau217 for Predicting Alzheimer Dementia Among Community-Dwelling Older Adults.

Background and Objectives: Structural brain MRI and blood-based phosphorylated tau (p-tau) measures are among the least invasive and least expensive Alzheimer's disease (AD) biomarkers to date. The extent to which these biomarkers may outperform one another in predicting future Alzheimer dementia diagnosis is poorly understood, however. This study investigated 2 specific AD biomarkers, i.e., a cortical thickness signature of AD (AD-CT) and plasma p-tau217, for predicting Alzheimer dementia. Methods: Data came from community-dwelling older participants of the Religious Orders Study or the Rush Memory and Aging Project. AD-CT was obtained from 3T MRI scans using a magnetization-prepared rapid acquisition gradient echo sequence and by averaging thickness from previously identified cortical regions implicated in AD. Plasma p-tau217 was quantified using an immunoassay developed by Lilly Research Laboratories on the MSD platform. Both MRI scans and blood specimens were collected at the same visits, and subsequent diagnoses of Alzheimer dementia were determined through annual detailed clinical evaluations. Cox proportional hazards models examined the associations of the 2 biomarkers with incident Alzheimer dementia, and prediction accuracy was assessed using c-statistics. Results: A total of 198 older adults, on average 84 years of age, were included. Over a mean follow-up of 4 years, 60 (30%) individuals developed Alzheimer dementia. AD-CT (hazard ratio: 1.71, 95% CI 1.26-2.31) and separately plasma p-tau217 (hazard ratio: 2.57, 95% CI 1.83-3.61) were associated with incident Alzheimer dementia. The c-statistic for prediction accuracy was consistently higher for plasma p-tau217 (between 0.74 and 0.81) than AD-CT (between 0.70 and 0.75) across a range of time horizons. Furthermore, with both biomarkers included in the same model, there was only modest improvement in the c-statistic due to AD-CT. Discussion: Plasma p-tau217 outperforms an imaging-based cortical thickness signature of AD in predicting future Alzheimer dementia diagnosis. Furthermore, the AD cortical thickness signature adds little to the prediction accuracy above and beyond plasma p-tau217.

Cerebrospinal fluid reference proteins increase accuracy and interpretability of biomarkers for brain diseases.

Cerebrospinal fluid (CSF) biomarkers reflect brain pathophysiology and are used extensively in translational research as well as in clinical practice for diagnosis of neurological diseases, e.g., Alzheimer's disease (AD). However, CSF biomarker concentrations may be influenced by non-disease related inter-individual variability. Here we use a data-driven approach to demonstrate the existence of inter-individual variability in mean standardized CSF protein levels. We show that these non-disease related differences cause many commonly reported CSF biomarkers to be highly correlated, thereby producing misleading results if not accounted for. To adjust for this inter-individual variability, we identified and evaluated high-performing reference proteins which improved the diagnostic accuracy of key CSF AD biomarkers. Our reference protein method attenuates the risk for false positive findings, and improves the sensitivity and specificity of CSF biomarkers, with broad implications for both research and clinical practice.

A generalizable data-driven model of atrophy heterogeneity and progression in memory clinic settings.

Memory clinic patients are a heterogeneous population representing various aetiologies of pathological ageing. It is not known whether divergent spatiotemporal progression patterns of brain atrophy, as previously described in Alzheimer's disease patients, are prevalent and clinically meaningful in this group of older adults. To uncover distinct atrophy subtypes, we applied the Subtype and Stage Inference (SuStaIn) algorithm to baseline structural MRI data from 813 participants enrolled in the DELCODE cohort (mean ± standard deviation, age = 70.67 ± 6.07 years, 52% females). Participants were cognitively unimpaired (n = 285) or fulfilled diagnostic criteria for subjective cognitive decline (n = 342), mild cognitive impairment (n = 118) or dementia of the Alzheimer's type (n = 68). Atrophy subtypes were compared in baseline demographics, fluid Alzheimer's disease biomarker levels, the Preclinical Alzheimer Cognitive Composite (PACC-5) as well as episodic memory and executive functioning. PACC-5 trajectories over up to 240 weeks were examined. To test whether baseline atrophy subtype and stage predicted clinical trajectories before manifest cognitive impairment, we analysed PACC-5 trajectories and mild cognitive impairment conversion rates of cognitively unimpaired participants and those with subjective cognitive decline. Limbic-predominant and hippocampal-sparing atrophy subtypes were identified. Limbic-predominant atrophy initially affected the medial temporal lobes, followed by further temporal regions and, finally, the remaining cortical regions. At baseline, this subtype was related to older age, more pathological Alzheimer's disease biomarker levels, APOE ε4 carriership and an amnestic cognitive impairment. Hippocampal-sparing atrophy initially occurred outside the temporal lobe, with the medial temporal lobe spared up to advanced atrophy stages. This atrophy pattern also affected individuals with positive Alzheimer's disease biomarkers and was associated with more generalized cognitive impairment. Limbic-predominant atrophy, in all participants and in only unimpaired participants, was linked to more negative longitudinal PACC-5 slopes than observed in participants without or with hippocampal-sparing atrophy and increased the risk of mild cognitive impairment conversion. SuStaIn modelling was repeated in a sample from the Swedish BioFINDER-2 cohort. Highly similar atrophy progression patterns and associated cognitive profiles were identified. Cross-cohort model generalizability, at both the subject and the group level, was excellent, indicating reliable performance in previously unseen data. The proposed model is a promising tool for capturing heterogeneity among older adults at early at-risk states for Alzheimer's disease in applied settings. The implementation of atrophy subtype- and stage-specific end points might increase the statistical power of pharmacological trials targeting early Alzheimer's disease.

Associations between structural brain changes and blood neurofilament light chain protein in treatment-resistant schizophrenia.

Background and Hypothesis: Around 30% of people with schizophrenia are refractory to antipsychotic treatment (treatment-resistant schizophrenia; TRS). While abnormal structural neuroimaging findings, in particular volume and thickness reductions, are often observed in schizophrenia, it is anticipated that biomarkers of neuronal injury like neurofilament light chain protein (NfL) can improve our understanding of the pathological basis underlying schizophrenia. The current study aimed to determine whether people with TRS demonstrate different associations between plasma NfL levels and regional cortical thickness reductions compared with controls. Study Design: Measurements of plasma NfL and cortical thickness were obtained from 39 individuals with TRS, and 43 healthy controls. T1-weighted magnetic resonance imaging sequences were obtained and processed via FreeSurfer. General linear mixed models adjusting for age and weight were estimated to determine whether the interaction between diagnostic group and plasma NfL level predicted lower cortical thickness across frontotemporal structures and the insula. Study Results: Significant (false discovery rate corrected) cortical thinning of the left (p = 0.001, η2p = 0.104) and right (p < 0.001, η2p = 0.167) insula was associated with higher levels of plasma NfL in TRS, but not in healthy controls. Conclusions: The association between regional thickness reduction of the insula bilaterally and plasma NfL may reflect a neurodegenerative process during the course of TRS. The findings of the present study suggest that some level of cortical degeneration localised to the bilateral insula may exist in people with TRS, which is not observed in the normal population.

Disease staging of Alzheimer's disease using a CSF-based biomarker model.

Biological staging of individuals with Alzheimer's disease (AD) may improve diagnostic and prognostic workup of dementia in clinical practice and the design of clinical trials. In this study, we used the Subtype and Stage Inference (SuStaIn) algorithm to establish a robust biological staging model for AD using cerebrospinal fluid (CSF) biomarkers. Our analysis involved 426 participants from BioFINDER-2 and was validated in 222 participants from the Knight Alzheimer Disease Research Center cohort. SuStaIn identified a singular biomarker sequence and revealed that five CSF biomarkers effectively constituted a reliable staging model (ordered: Aß42/40, pT217/T217, pT205/T205, MTBR-tau243 and non-phosphorylated mid-region tau). The CSF stages (0-5) demonstrated a correlation with increased abnormalities in other AD-related biomarkers, such as Aß-PET and tau-PET, and aligned with longitudinal biomarker changes reflective of AD progression. Higher CSF stages at baseline were associated with an elevated hazard ratio of clinical decline. This study highlights a common molecular pathway underlying AD pathophysiology across all patients, suggesting that a single CSF collection can accurately indicate the presence of AD pathologies and characterize the stage of disease progression. The proposed staging model has implications for enhancing diagnostic and prognostic assessments in both clinical practice and the design of clinical trials.

Comparing a pre-defined versus deep learning approach for extracting brain atrophy patterns to predict cognitive decline due to Alzheimer's disease in patients with mild cognitive symptoms.

BACKGROUND: Predicting future Alzheimer's disease (AD)-related cognitive decline among individuals with subjective cognitive decline (SCD) or mild cognitive impairment (MCI) is an important task for healthcare. Structural brain imaging as measured by magnetic resonance imaging (MRI) could potentially contribute when making such predictions. It is unclear if the predictive performance of MRI can be improved using entire brain images in deep learning (DL) models compared to using pre-defined brain regions. METHODS: A cohort of 332 individuals with SCD/MCI were included from the Swedish BioFINDER-1 study. The goal was to predict longitudinal SCD/MCI-to-AD dementia progression and change in Mini-Mental State Examination (MMSE) over four years. Four models were evaluated using different predictors: (1) clinical data only, including demographics, cognitive tests and APOE ε4 status, (2) clinical data plus hippocampal volume, (3) clinical data plus all regional MRI gray matter volumes (N = 68) extracted using FreeSurfer software, (4) a DL model trained using multi-task learning with MRI images, Jacobian determinant images and baseline cognition as input. A double cross-validation scheme, with five test folds and for each of those ten validation folds, was used. External evaluation was performed on part of the ADNI dataset, including 108 patients. Mann-Whitney U-test was used to determine statistically significant differences in performance, with p-values less than 0.05 considered significant. RESULTS: In the BioFINDER cohort, 109 patients (33%) progressed to AD dementia. The performance of the clinical data model for prediction of progression to AD dementia was area under the curve (AUC) = 0.85 and four-year cognitive decline was R2 = 0.14. The performance was improved for both outcomes when adding hippocampal volume (AUC = 0.86, R2 = 0.16). Adding FreeSurfer brain regions improved prediction of four-year cognitive decline but not progression to AD (AUC = 0.83, R2 = 0.17), while the DL model worsened the performance for both outcomes (AUC = 0.84, R2 = 0.08). A sensitivity analysis showed that the Jacobian determinant image was more informative than the MRI image, but that performance was maximized when both were included. In the external evaluation cohort from ADNI, 23 patients (21%) progressed to AD dementia. The results for predicted progression to AD dementia were similar to the results for the BioFINDER test data, while the performance for the cognitive decline was deteriorated. CONCLUSIONS: The DL model did not significantly improve the prediction of clinical disease progression in AD, compared to regression models with a single pre-defined brain region.

A blood-based biomarker workflow for optimal tau-PET referral in memory clinic settings.

Blood-based biomarkers for screening may guide tau positrion emissition tomography (PET) scan referrals to optimize prognostic evaluation in Alzheimer's disease. Plasma Aß42/Aß40, pTau181, pTau217, pTau231, NfL, and GFAP were measured along with tau-PET in memory clinic patients with subjective cognitive decline, mild cognitive impairment or dementia, in the Swedish BioFINDER-2 study (n = 548) and in the TRIAD study (n = 179). For each plasma biomarker, cutoffs were determined for 90%, 95%, or 97.5% sensitivity to detect tau-PET-positivity. We calculated the percentage of patients below the cutoffs (who would not undergo tau-PET; "saved scans") and the tau-PET-positivity rate among participants above the cutoffs (who would undergo tau-PET; "positive predictive value"). Generally, plasma pTau217 performed best. At the 95% sensitivity cutoff in both cohorts, pTau217 resulted in avoiding nearly half tau-PET scans, with a tau-PET-positivity rate among those who would be referred for a scan around 70%. And although tau-PET was strongly associated with subsequent cognitive decline, in BioFINDER-2 it predicted cognitive decline only among individuals above the referral cutoff on plasma pTau217, supporting that this workflow could reduce prognostically uninformative tau-PET scans. In conclusion, plasma pTau217 may guide selection of patients for tau-PET, when accurate prognostic information is of clinical value.

Cerebrospinal fluid biomarker panel for synaptic dysfunction in a broad spectrum of neurodegenerative diseases.

Synaptic dysfunction and degeneration is likely the key pathophysiology for the progression of cognitive decline in various dementia disorders. Synaptic status can be monitored by measuring synaptic proteins in CSF. In this study, both known and new synaptic proteins were investigated and compared as potential biomarkers of synaptic dysfunction, particularly in the context of Alzheimer's disease (AD). Seventeen synaptic proteins were quantified in CSF using two different targeted mass spectrometry assays in the prospective Swedish BioFINDER-2 study. The study included 958 individuals, characterized as having mild cognitive impairment (MCI, n = 205), AD dementia (n = 149) and a spectrum of other neurodegenerative diseases (n = 171), in addition to cognitively unimpaired individuals (CU, n = 443). Synaptic protein levels were compared between diagnostic groups and their associations with cognitive decline and key neuroimaging measures (amyloid-ß-PET, tau-PET and cortical thickness) were assessed. Among the 17 synaptic proteins examined, 14 were specifically elevated in the AD continuum. SNAP-25, 14-3-3 zeta/delta, ß-synuclein, and neurogranin exhibited the highest discriminatory accuracy in differentiating AD dementia from controls (areas under the curve = 0.81-0.93). SNAP-25 and 14-3-3 zeta/delta also had the strongest associations with tau-PET, amyloid-ß-PET and cortical thickness at baseline and were associated with longitudinal changes in these imaging biomarkers [ß(standard error, SE) = -0.056(0.0006) to 0.058(0.005), P < 0.0001]. SNAP-25 was the strongest predictor of progression to AD dementia in non-demented individuals (hazard ratio = 2.11). In contrast, neuronal pentraxins were decreased in all neurodegenerative diseases (except for Parkinson's disease), and NPTX2 showed the strongest associations with subsequent cognitive decline [longitudinal Mini-Mental State Examination: ß(SE) = 0.57(0.1), P ≤ 0.0001; and mPACC: ß(SE) = 0.095(0.024), P ≤ 0.001] across the AD continuum. Interestingly, utilizing a ratio of the proteins that displayed higher levels in AD, such as SNAP-25 or 14-3-3 zeta/delta, over NPTX2 improved the biomarkers' associations with cognitive decline and brain atrophy. We found 14-3-3 zeta/delta and SNAP-25 to be especially promising as synaptic biomarkers of pathophysiological changes in AD. Neuronal pentraxins were identified as general indicators of neurodegeneration and associated with cognitive decline across various neurodegenerative dementias. Cognitive decline and brain atrophy were best predicted by ratios of SNAP-25/NPTX2 and 14-3-3 zeta/delta/NPTX2.

Highly accurate blood test for Alzheimer's disease is similar or superior to clinical cerebrospinal fluid tests.

With the emergence of Alzheimer's disease (AD) disease-modifying therapies, identifying patients who could benefit from these treatments becomes critical. In this study, we evaluated whether a precise blood test could perform as well as established cerebrospinal fluid (CSF) tests in detecting amyloid-ß (Aß) plaques and tau tangles. Plasma %p-tau217 (ratio of phosporylated-tau217 to non-phosphorylated tau) was analyzed by mass spectrometry in the Swedish BioFINDER-2 cohort (n = 1,422) and the US Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) cohort (n = 337). Matched CSF samples were analyzed with clinically used and FDA-approved automated immunoassays for Aß42/40 and p-tau181/Aß42. The primary and secondary outcomes were detection of brain Aß or tau pathology, respectively, using positron emission tomography (PET) imaging as the reference standard. Main analyses were focused on individuals with cognitive impairment (mild cognitive impairment and mild dementia), which is the target population for available disease-modifying treatments. Plasma %p-tau217 was clinically equivalent to FDA-approved CSF tests in classifying Aß PET status, with an area under the curve (AUC) for both between 0.95 and 0.97. Plasma %p-tau217 was generally superior to CSF tests in classification of tau-PET with AUCs of 0.95-0.98. In cognitively impaired subcohorts (BioFINDER-2: n = 720; Knight ADRC: n = 50), plasma %p-tau217 had an accuracy, a positive predictive value and a negative predictive value of 89-90% for Aß PET and 87-88% for tau PET status, which was clinically equivalent to CSF tests, further improving to 95% using a two-cutoffs approach. Blood plasma %p-tau217 demonstrated performance that was clinically equivalent or superior to clinically used FDA-approved CSF tests in the detection of AD pathology. Use of high-performance blood tests in clinical practice can improve access to accurate AD diagnosis and AD-specific treatments.