Jones, David T.

Abstract INTRODUCTION Early‐onset and late‐onset Alzheimer's disease (EOAD and LOAD, respectively) have distinct clinical manifestations, with prior work based on small samples suggesting unique patterns of neurodegeneration. The current study performed a head‐to‐head comparison of cortical atrophy in EOAD and LOAD, using two large and well‐characterized cohorts (LEADS and ADNI). METHODS We analyzed brain structural magnetic resonance imaging (MRI) data acquired from 377 sporadic EOAD patients and 317 sporadicLOAD patients who were amyloid positive and had mild cognitive impairment (MCI) or mild dementia (i.e., early‐stage AD), along with cognitively unimpaired participants. RESULTS After controlling for the level of cognitive impairment, we found a double dissociation between AD clinical phenotype and localization/magnitude of atrophy, characterized by predominant neocortical involvement in EOAD and more focal anterior medial temporal involvement in LOAD. DISCUSSION Our findings point to the clinical utility of MRI‐based biomarkers of atrophy in differentiating between EOAD and LOAD, which may be useful for diagnosis, prognostication, and treatment. Highlights Early‐onset Alzheimer's disease (EOAD) and late‐onset AD (LOAD) patients showed distinct and overlapping cortical atrophy patterns. EOAD patients showed prominent atrophy in widespread neocortical regions. LOAD patients showed prominent atrophy in the anterior medial temporal lobe. Regional atrophy was correlated with the severity of global cognitive impairment. Results were comparable when the sample was stratified for mild cognitive impairment (MCI) and dementia.

Abstract Nerve conduction F-wave studies contain crucial information about subclinical motor dysfunction that can be used to diagnose patients with amyotrophic lateral sclerosis (ALS). However, F-wave responses are highly variable in morphology, making waveform interpretation challenging. Artificial intelligence techniques can extract time–frequency features to provide new insights into ALS diagnosis and prognosis. A retrospective analysis was performed on F-wave responses from 46 802 patients. Discrete wavelet transforms were applied to time-series waveform responses after stimulating ulnar, median, fibular and tibial nerves. Wavelet coefficient statistics, onset age, sex and body mass index were features for training a Gradient Boosting Machine model on 40 095 patients (5329 diagnosed with motor neuron disease). Model performance was tested on responses from 689 ALS patients meeting Gold Coast criteria and 689 age- and sex-matched controls. An exploratory analysis examined model performance on cohorts of patients with inclusion body myositis, cervical radiculopathy, lumbar radiculopathy or peripheral neuropathy, which can mimic ALS symptoms. Factors affecting survival were estimated through Cox proportional hazards regression. The model trained using wavelet features on the full waveform had 90% recall, 87% precision and 88% accuracy. Similar model performance was measured using features from only the M-wave or F-wave. Classification probabilities for ALS patients were statistically different from the diagnoses mimicking ALS symptoms (P < 0.001, ANOVA, Tukey’s post hoc test). Higher model classification probabilities of ALS, older age at onset, and family history of ALS alone or with frontotemporal dementia were factors decreasing survival. Longer diagnostic delay and upper limb onset site were factors increasing survival. Model scores two standard deviations below the mean had 4 months increased survival (two standard deviations below had 3 months decreased survival). Artificial intelligence techniques extracted important information from F-wave responses to estimate a patient’s likelihood of ALS and their survival risks. Although the model can make predictions at a specific decision threshold as presented here, the true strength of such a model lies in its ability to provide probabilities about whether a patient is likely to have ALS in comparison to other mimicking diagnoses, such as inclusion body myositis, cervical or lumbar radiculopathy or peripheral neuropathy. These probabilities provide clinicians with additional information that they can use to make the final diagnosis with greater confidence and precision. Integrating such a model into the clinical workflow could help clinicians to diagnose ALS sooner and manage treatment based on estimated survival, which might improve outcomes and the quality of life of patients.

Abstract Limbic predominant age‐related TDP‐43 encephalopathy neuropathologic change (LATE‐NC) is highly prevalent in late life and a common co‐pathology with Alzheimer's disease neuropathologic change (ADNC). LATE‐NC is a slowly progressive, amnestic clinical syndrome. Alternatively, when present with ADNC, LATE‐NC is associated with a more rapid course. With the emergence of anti‐amyloid therapeutics, discrimination of LATE‐NC from ADNC is critical and will lead to greater clinical recognition of amnestic patients without ADNC. Furthermore, co‐pathology with LATE‐NC may influence outcomes of these therapeutics. Thus there is a need to identify patients during life with likely LATE‐NC. We propose criteria for clinical diagnosis of LATE as an initial framework for further validation. In the context of progressive memory loss and substantial hippocampal atrophy, criteria are laid out for probable (amyloid negative) or possible LATE (amyloid biomarkers are unavailable or when amyloid is present, but hippocampal neurodegeneration is out of proportion to expected pure ADNC). Highlights Limbic‐predominant age‐related TDP‐43 encephalopathy (LATE) is a highly prevalent driver of neuropathologic memory loss in late life. LATE neuropathologic change (LATE‐NC) is a common co‐pathology with Alzheimer's disease neuropathologic change (ADNC) and may influence outcomes with emerging disease‐modifying medicines. We provide initial clinical criteria for diagnosing LATE during life either when LATE‐NC is the likely primary driver of symptoms or when observed in conjunction with AD. Definitions of possible and probable LATE are provided.

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.

AbstractBackgroundAs new anti‐amyloid immunotherapies emerge for Alzheimer’s disease (AD), it is clear that early diagnosis of AD pathology is crucial for treatment success. This can be challenging in atypical presentations of AD and, together with our reliance on CSF or PET scans, can, at times, lead to delayed diagnosis. Here, we further explore the possible role of plasma tau phosphorylated at threonine 217 (P‐tau217) for the detection of primary AD or AD co‐pathology when frontotemporal dementia spectrum disorders are the main clinical presentation.MethodParticipants were recruited through ALLFTD, a North American multisite research consortium for the longitudinal assessment of frontotemporal lobar degeneration. After excluding cases with known FTD‐causing mutations, 573 participants with sporadic disease, mild cognitive/behavioral impairment, or healthy familial controls evaluated between 2014 and 2023 were included in this analysis (45.8% female, median age 66 years). 39 of those cases underwent neuropathological evaluation. Plasma P‐tau217 was measured with the Eli Lilly electrochemiluminescence‐based assay. P‐tau217 concentrations were compared by phenotype, disease severity, genotype, and, when available, neuropathological diagnosis with non‐parametric tests. Its diagnostic performance was tested with ROC curves. Associations between plasma P‐tau217 concentrations and clinical scales of global cognition, memory, executive function, motor function, and social cognition with linear regressions and non‐parametric tests.ResultPlasma P‐tau217 concentrations were higher in logopenic variant primary progressive aphasia (lvPPA) and amnestic dementia (AmDem), compared to participants with normal cognition or other FTD phenotypes. P‐tau217 concentrations were higher in APOE e4 carriers, compared to non‐carriers, regardless of phenotype, but were not affected by disease severity. P‐tau217 concentrations showed associations with clinical measures of global cognition, memory, and executive function, but had no associations with measures of motor function or social cognition. Plasma P‐tau217 concentrations were elevated in high and intermediate ADNC scoring, or more advanced Braak stages, even when AD was not the primary pathology.ConclusionEven when FTD is suspected, high plasma p‐tau 217 concentrations are strongly associated with underlying AD as primary pathology or contributing co‐pathology. Plasma P‐tau217 could be a tool to support the development of disease‐modifying therapies for atypical Alzheimer’s disease presentations or for FTD cases with Alzheimer’s disease co‐pathology.

AbstractBackgroundParkinson’s disease and dementia with Lewy bodies are characterized by abnormal iron deposition in the substantia nigra, which can be measured with quantitative susceptibility mapping (QSM) on MRI. However, neuropathologic validation of the increased QSM in the substantia nigra associated with Lewy body disease (LBD) is lacking. We compared substantia nigra QSM on antemortem MRI between patients with and without Lewy‐related pathology which was confirmed by autopsy in all cases.MethodWe studied cases with antemortem QSM who underwent autopsy from the Mayo Clinic Alzheimer’s Disease Research Center and Mayo Clinic Study of Aging (n=54). Immunohistochemistry was performed with rabbit NACP antibody against the amino acids 98‐115 of the α‐synuclein protein to detect Lewy‐related pathology. After neuropathologic evaluation, cases were classified as LBD‐present (n=13) if they had Lewy‐related pathology and LBD‐absent (n=42) if they did not have Lewy‐related pathology. Alzheimer’s disease co‐pathology was present in 9 of the LBD‐present cohort (70%). QSM was calculated for the whole substantia nigra and the two sub‐regions: pars compacta and pars reticulata. Non‐parametric Wilcoxon rank‐sum test was used to compare substantia nigra QSM values between LBD‐present and LBD‐absent cases. Area under the curve (AUC) analyses tested the accuracy of QSM to distinguish the two groups.ResultsLBD‐present group had higher QSM values in the substantia nigra than LBD‐absent group. Furthermore, sub‐regional analyses showed that the LBD‐present group had higher QSM in the substantia nigra pars compacta (p=0.008) but not in the pars reticulata than the LBD‐absent group (Figure 1). QSM of the substantia nigra pars compacta distinguished LBD‐present and LBD‐absent cases with good accuracy (AUC=0.74; p=0.006; Figure 2).ConclusionThis study provides neuropathologic insight into the relevance of QSM of substantia nigra pars compacta as an in‐vivo biomarker of autopsy‐confirmed LBD. These findings indicate that imaging evidence of abnormal iron deposition in the substantia nigra may serve as a biomarker of Lewy‐related pathology in patients with primary LBD (i.e., Parkinson disease, dementia with Lewy bodies) and patients with potential LBD co‐pathology (e.g., patients with Alzheimer disease).

AbstractBackgroundDementia with Lewy bodies (DLB) frequently co‐occurs with Alzheimer’s disease (AD) pathologies, exacerbating disease progression. Biophysical models of diffusion imaging data, such as Neurite Orientation Dispersion and Density Imaging (NODDI), may reveal novel insights into the neurobiological substrates of AD on cortical and white matter microstructural injury.MethodA cohort of 57 DLB patients on the DLB spectrum (33 clinically probable DLB and 14 prodromal DLB) and 57 cognitively unimpaired (CU) controls underwent NODDI and PET imaging with [18F]‐Flortaucipir and [11C]‐PiB (Table 1). NODDI parameters were derived from white matter tracts and grey matter regions using the JHU “Eve” and Mayo Clinic Adult Lifespan Template atlases, respectively. Conditional logistic models were used to compare these parameters between the two groups, accounting for the 1:1 matching on age and sex. The associations of tau and amyloid‐β with NODDI parameters across the white matter tracts were examined with linear regressions. A region‐by‐region approach was adopted to evaluate the relationships of tau and amyloid‐β with grey matter NODDI, adjusting for age, APOE, and local grey matter volumes.ResultDLB spectrum patients exhibited extensive white matter abnormalities relative to CU, including lower fractional anisotropy, higher mean diffusivity (MD), and lower tissue‐weighted neurite density (tNDI). In grey matter, these deficits were paralleled with higher MD and lower tNDI and ODI, primarily in the temporoparietal and posterior cortices. Regression models revealed significant associations of elevated [18F]‐Flortaucipir uptake with deficits in temporal and limbic white matter tracts and a temporal‐lobe pattern of higher MD and lower tNDI in the cortex (Figure 1). No associations were observed with [11C]‐PiB in the DLB spectrum.ConclusionThese findings demonstrated an in vivo relationship between tau deposition and neurite deficits that spatially aligned with the canonical AD “cortical signature” of neurodegeneration in both white matter tracts and grey matter regions in DLB. Our study underscores the detrimental impact of AD pathology in DLB and provides a rationale for further investigations into the underlying mechanisms of AD in DLB. Future longitudinal studies tracking the progression of these changes could inform therapeutic strategies for DLB in the presence of AD pathologies

AbstractBackgroundUnderstanding the relationship between AβPET and AβCSF biomarkers will define their potential utility in Aβ treatment. Few longitudinal or neuropathological comparisons have been reported. We assessed the relationship of AβPET and AβCSF biomarkers in a large community cohort.MethodParticipants 50+ years with coincident AβPET and AβCSF biomarkers (pTau181/Aβ42, n=505, and Aβ42/40, n=54) were included. Of these participants, a subgroup was identified that had neuropathology data (n=47) of which many had longitudinal AβPET and CSF testing. The relationships of AβPET and CSF biomarkers were assessed cross‐sectionally in all participants and longitudinally in those with autopsy data. Analyses were performed using AβPET Meta‐ROI and AβPET early‐Aβ‐deposition ROIs (ROIs with early Aβ deposition: fusiform, angular, inferior temporal, middle temporal, middle occipital, and calcarine).ResultIn biomarker tests performed at the same time, more participants were AβPET+ and CSF‐ than AβPET‐ and CSF+ using Meta‐ROI AβPET. This discordance occurred more frequently when using early‐Aβ‐deposition regions (Figure 1). Of 47 participants with autopsy data, 35 had Thal stage ≥1. The sensitivity for earliest detection of cortical Aβ neuropathology by AβPET was 89% (31/35) and by CSF was 66%, (23/35). Eight of these 35 had positive AβPET findings and negative coincident CSF tests at the first time tested. Of these, 5/8 were Meta‐ROI and early AβPET ROI positive. The other 3/8 were only positive on early‐Aβ AβPET ROIs. Four of the 8 with negative CSF and positive AβPET had subsequent testing and 2/4 became positive on CSF tests after 1.5 years while 2/4 continued to be negative on subsequent testing.ConclusionAβPET is more sensitive for detection of early cortical Aβ deposition than CSF biomarkers in cross‐sectional or autopsy data. While the assessment of AβPET by standard Meta‐ROI AβPET methods showed cortical Aβ deposition occurring when not indicated by CSF biomarkers, AβPET ROIs for early Aβ deposition detected additional participants that were AβPET positive and AβCSF negative. These findings have implications for detecting early Aβ neuropathology among CU participants in Aβ prevention trials when robust detection is needed. Further work is needed to compare Aβ plasma biomarkers and AβPET using these methods.

AbstractBackgroundLimbic‐predominant age‐related TDP‐43 encephalopathy (LATE) is a neuropathologically‐defined disease, and it is frequently comorbid with Alzheimer’s disease neuropathological change (ADNC). However, the neurological syndrome associated with LATE neuropathological change (LATE‐NC) is not defined. We propose a set of clinical criteria for a limbic‐predominant amnestic neurodegenerative syndrome (LANS) that is highly associated with LATE‐NC. These criteria assess degree of certainty (highest, high, moderate, low) based on features that are measurable in vivo, including older age at evaluation, a mild clinical syndrome, impaired semantic knowledge, disproportionate hippocampal atrophy, limbic hypometabolism, absence of neocortical degeneration patterns and low likelihood of neocortical tau. We operationalized these criteria using two large datasets with clinical and pathologic outcomes.MethodWe screened autopsied patients from Mayo Clinic and ADNI cohorts and applied the LANS criteria to those with an antemortem predominant amnestic syndrome (Mayo, n = 165; ADNI, n = 53). We compared frequencies of neuropathological diagnoses across LANS likelihoods, compared longitudinal CDR‐SB trajectories across LANS likelihoods, and stratified ADNC/LATE‐NC patients according to their LANS likelihood and compared their longitudinal CDR‐SB trajectories to those with ADNC or LATE‐NC.ResultADNC, ADNC/LATE‐NC and LATE‐NC accounted for 35%, 37% and 4% of cases in the Mayo cohort, respectively, and 30%, 22%, and 9% of cases in the ADNI cohort, respectively (Fig. 1). ADNC cases had the lowest LANS likelihoods, LATE‐NC patients had the highest likelihoods, and ADNC/LATE‐NC patients had intermediate likelihoods. Patients with high LANS likelihoods had a milder and slower clinical course and more severe temporo‐limbic degeneration compared to those with low likelihoods (Fig. 2). ADNC/LATE‐NC patients with higher likelihoods had more temporo‐limbic degeneration and a slower rate of cognitive decline, and those with lower likelihoods had more lateral temporo‐parietal degeneration and a faster rate of cognitive decline (Fig. 3).ConclusionThe implementation of LANS criteria has implications for disambiguating the different driving etiologies of progressive amnestic presentations in older age to guide prognosis, treatment, and clinical trial design and enrollment. The development of in vivo biomarkers specific to TDP‐43 pathology are needed to further refine molecular associations between LANS and LATE‐NC and precise antemortem diagnoses of LATE.

ABSTRACT Background and Purpose In idiopathic normal pressure hydrocephalus (iNPH) patients, cerebrospinal fluid (CSF) flow is typically evaluated with a cardiac‐gated two‐dimensional (2D) phase‐contrast (PC) MRI through the cerebral aqueduct. This approach is limited by the evaluation of a single location and does not account for respiration effects on flow. In this study, we quantified the cardiac and respiratory contributions to CSF movement at multiple intracranial locations using a real‐time 2D PC‐MRI and evaluated the diagnostic value of CSF dynamics biomarkers in classifying iNPH patients. Methods This study included 37 participants: 16 iNPH, 10 Alzheimer's disease (AD), and 11 cognitively unimpaired (CU) controls. Anatomical and real‐time (non‐gated) PC images were acquired in a 3T Philips scanner. CSF flow was assessed at the foramen magnum, fourth ventricle, Sylvian fissure, lateral ventricle, and cerebral aqueduct. We calculated three CSF dynamics biomarkers: mean velocity amplitude, cardiac signal power, and respiratory signal power. Biomarkers from each location were evaluated for classifying iNPH versus AD and CU using support vector machine (SVM). A p ‐value of 0.05 or less was considered statistically significant. Results The velocity amplitude and cardiac signal power were significantly reduced in iNPH compared to CU ( p < 0.005) and AD ( p < 0.05) at the lateral ventricle. The SVM model using biomarkers from the lateral ventricle performed significantly better at classifying iNPH than the other locations in terms of accuracy ( p < 0.005) and diagnostic odds ratio ( p < 0.05). Conclusion Evaluation of CSF movement beyond the cerebral aqueduct may aid in identifying patients with and understanding the pathophysiology of iNPH.