Typical and atypical pathology in primary progressive aphasia variants.
ABSTRACT: To characterize in vivo signatures of pathological diagnosis in a large cohort of patients with primary progressive aphasia (PPA) variants defined by current diagnostic classification.Extensive clinical, cognitive, neuroimaging, and neuropathological data were collected from 69 patients with sporadic PPA, divided into 29 semantic (svPPA), 25 nonfluent (nfvPPA), 11 logopenic (lvPPA), and 4 mixed PPA. Patterns of gray matter (GM) and white matter (WM) atrophy at presentation were assessed and tested as predictors of pathological diagnosis using support vector machine (SVM) algorithms.A clinical diagnosis of PPA was associated with frontotemporal lobar degeneration (FTLD) with transactive response DNA-binding protein (TDP) inclusions in 40.5%, FTLD-tau in 40.5%, and Alzheimer disease (AD) pathology in 19% of cases. Each variant was associated with 1 typical pathology; 24 of 29 (83%) svPPA showed FTLD-TDP type C, 22 of 25 (88%) nfvPPA showed FTLD-tau, and all 11 lvPPA had AD. Within FTLD-tau, 4R-tau pathology was commonly associated with nfvPPA, whereas Pick disease was observed in a minority of subjects across all variants except for lvPPA. Compared with pathologically typical cases, svPPA-tau showed significant extrapyramidal signs, greater executive impairment, and severe striatal and frontal GM and WM atrophy. nfvPPA-TDP patients lacked general motor symptoms or significant WM atrophy. Combining GM and WM volumes, SVM analysis showed 92.7% accuracy to distinguish FTLD-tau and FTLD-TDP pathologies across variants.Each PPA clinical variant is associated with a typical and most frequent cognitive, neuroimaging, and neuropathological profile. Specific clinical and early anatomical features may suggest rare and atypical pathological diagnosis in vivo. Ann Neurol 2017;81:430-443.
Project description:<h4>Objective</h4>To identify early cognitive and neuroimaging features of sporadic nonfluent/agrammatic variant of primary progressive aphasia (nfvPPA) caused by frontotemporal lobar degeneration (FTLD) subtypes.<h4>Methods</h4>We prospectively collected clinical, neuroimaging, and neuropathologic data in 11 patients with sporadic nfvPPA with FTLD-tau (nfvPPA-tau, n = 9) or FTLD-transactive response DNA binding protein pathology of 43 kD type A (nfvPPA-TDP, n = 2). We analyzed patterns of cognitive and gray matter (GM) and white matter (WM) atrophy at presentation in the whole group and in each pathologic subtype separately. We also considered longitudinal clinical data.<h4>Results</h4>At first evaluation, regardless of pathologic FTLD subtype, apraxia of speech (AOS) was the most common cognitive feature and atrophy involved the left posterior frontal lobe. Each pathologic subtype showed few distinctive features. At presentation, patients with nfvPPA-tau presented with mild to moderate AOS, mixed dysarthria with prominent hypokinetic features, clear agrammatism, and atrophy in the GM of the left posterior frontal regions and in left frontal WM. While speech and language deficits were prominent early, within 3 years of symptom onset, all patients with nfvPPA-tau developed significant extrapyramidal motor signs. At presentation, patients with nfvPPA-TDP had severe AOS, dysarthria with spastic features, mild agrammatism, and atrophy in left posterior frontal GM only. Selective mutism occurred early, when general neurologic examination only showed mild decrease in finger dexterity in the right hand.<h4>Conclusions</h4>Clinical features in sporadic nfvPPA caused by FTLD subtypes relate to neurodegeneration of GM and WM in frontal motor speech and language networks. We propose that early WM atrophy in nfvPPA is suggestive of FTLD-tau pathology while early selective GM loss might be indicative of FTLD-TDP.
Project description:<h4>Background</h4>The primary progressive aphasias (PPA) represent a group of usually sporadic neurodegenerative disorders with three main variants: the nonfluent or agrammatic variant (nfvPPA), the semantic variant (svPPA), and the logopenic variant (lvPPA). They are usually associated with a specific underlying pathology: nfvPPA with a primary tauopathy, svPPA with a TDP-43 proteinopathy, and lvPPA with underlying Alzheimer's disease (AD). Little is known about their cause or pathophysiology, but prior studies in both AD and svPPA have suggested a role for neuroinflammation. In this study, we set out to investigate the role of chemokines across the PPA spectrum, with a primary focus on central changes in cerebrospinal fluid (CSF) METHODS: Thirty-six participants with sporadic PPA (11 svPPA, 13 nfvPPA, and 12 lvPPA) as well as 19 healthy controls were recruited to the study and donated CSF and plasma samples. All patients with lvPPA had a tau/Aβ42 biomarker profile consistent with AD, whilst this was normal in the other PPA groups and controls. We assessed twenty chemokines in CSF and plasma using Proximity Extension Assay technology: CCL2 (MCP-1), CCL3 (MIP-1a), CCL4 (MIP-1β), CCL7 (MCP-3), CCL8 (MCP-2), CCL11 (eotaxin), CCL13 (MCP-4), CCL19, CCL20, CCL23, CCL25, CCL28, CX3CL1 (fractalkine), CXCL1, CXCL5, CXCL6, CXCL8 (IL-8), CXCL9, CXCL10, and CXCL11.<h4>Results</h4>In CSF, CCL19 and CXCL6 were decreased in both svPPA and nfvPPA compared with controls whilst CXCL5 was decreased in the nfvPPA group with a borderline significant decrease in the svPPA group. In contrast, CCL2, CCL3 and CX3CL1 were increased in lvPPA compared with controls and nfvPPA (and greater than svPPA for CX3CL1). CXCL1 was also increased in lvPPA compared with nfvPPA but not the other groups. CX3CL1 was significantly correlated with CSF total tau concentrations in the controls and each of the PPA groups. Fewer significant differences were seen between groups in plasma, although in general, results were in the opposite direction to CSF, i.e. decreased in lvPPA compared with controls (CCL3 and CCL19), and increased in svPPA (CCL8) and nfvPPA (CCL13).<h4>Conclusion</h4>Differential alteration of chemokines across the PPA variants is seen in both CSF and plasma. Importantly, these results suggest a role for neuroinflammation in these poorly understood sporadic disorders, and therefore also a potential future therapeutic target.
Project description:OBJECTIVE:To estimate the prevalence of amyloid positivity, defined by positron emission tomography (PET)/cerebrospinal fluid (CSF) biomarkers and/or neuropathological examination, in primary progressive aphasia (PPA) variants. METHODS:We conducted a meta-analysis with individual participant data from 1,251 patients diagnosed with PPA (including logopenic [lvPPA, n?=?443], nonfluent [nfvPPA, n?=?333], semantic [svPPA, n?=?401], and mixed/unclassifiable [n?=?74] variants of PPA) from 36 centers, with a measure of amyloid-? pathology (CSF [n?=?600], PET [n?=?366], and/or autopsy [n?=?378]) available. The estimated prevalence of amyloid positivity according to PPA variant, age, and apolipoprotein E (ApoE) ?4 status was determined using generalized estimating equation models. RESULTS:Amyloid-? positivity was more prevalent in lvPPA (86%) than in nfvPPA (20%) or svPPA (16%; p?<?0.001). Prevalence of amyloid-? positivity increased with age in nfvPPA (from 10% at age 50 years to 27% at age 80 years, p?<?0.01) and svPPA (from 6% at age 50 years to 32% at age 80 years, p?<?0.001), but not in lvPPA (p?=?0.94). Across PPA variants, ApoE ?4 carriers were more often amyloid-? positive (58.0%) than noncarriers (35.0%, p?<?0.001). Autopsy data revealed Alzheimer disease pathology as the most common pathologic diagnosis in lvPPA (76%), frontotemporal lobar degeneration-TDP-43 in svPPA (80%), and frontotemporal lobar degeneration-TDP-43/tau in nfvPPA (64%). INTERPRETATION:This study shows that the current PPA classification system helps to predict underlying pathology across different cohorts and clinical settings, and suggests that age and ApoE genotype should be considered when interpreting amyloid-? biomarkers in PPA patients. Ann Neurol 2018;84:737-748.
Project description:Frontotemporal lobar degeneration proteinopathies with tau inclusions (FTLD-Tau) or TDP-43 inclusions (FTLD-TDP) are associated with clinically similar phenotypes. However, these disparate proteinopathies likely differ in cellular severity and regional distribution of inclusions in white matter (WM) and adjacent grey matter (GM), which have been understudied. We performed a neuropathological study of subcortical WM and adjacent GM in a large autopsy cohort (n?=?92; FTLD-Tau?=?37, FTLD-TDP?=?55) using a validated digital image approach. The antemortem clinical phenotype was behavioral-variant frontotemporal dementia (bvFTD) in 23 patients with FTLD-Tau and 42 with FTLD-TDP, and primary progressive aphasia (PPA) in 14 patients with FTLD-Tau and 13 with FTLD-TDP. We used linear mixed-effects models to: (1) compare WM pathology burden between proteinopathies; (2) investigate the relationship between WM pathology burden and WM degeneration using luxol fast blue (LFB) myelin staining; (3) study regional patterns of pathology burden in clinico-pathological groups. WM pathology burden was greater in FTLD-Tau compared to FTLD-TDP across regions (beta?=?4.21, SE?=?0.34, p?<?0.001), and correlated with the degree of WM degeneration in both FTLD-Tau (beta?=?0.32, SE?=?0.10, p?=?0.002) and FTLD-TDP (beta?=?0.40, SE?=?0.08, p?<?0.001). WM degeneration was greater in FTLD-Tau than FTLD-TDP particularly in middle-frontal and anterior cingulate regions (p?<?0.05). Distinct regional patterns of WM and GM inclusions characterized FTLD-Tau and FTLD-TDP proteinopathies, and associated in part with clinical phenotype. In FTLD-Tau, WM pathology was particularly severe in the dorsolateral frontal cortex in nonfluent-variant PPA, and GM pathology in dorsolateral and paralimbic frontal regions with some variation across tauopathies. Differently, FTLD-TDP had little WM regional variability, but showed severe GM pathology burden in ventromedial prefrontal regions in both bvFTD and PPA. To conclude, FTLD-Tau and FTLD-TDP proteinopathies have distinct severity and regional distribution of WM and GM pathology, which may impact their clinical presentation, with overall greater severity of WM pathology as a distinguishing feature of tauopathies.
Project description:<h4>Introduction</h4>The Frontotemporal Lobar Degeneration Module (FTLD-MOD) includes a neuropsychological battery designed to assess the clinical features of FTLD, although much is unknown about its utility. We investigated FTLD-MOD and Uniform Data Set 3.0 (UDS) language tests for differential diagnosis and disease monitoring.<h4>Methods</h4>Linear regressions compared baseline performances in 1655 National Alzheimer's Coordinating Center participants (behavioral variant frontotemporal dementia (bvFTD, n = 612), semantic variant primary progressive aphasia (svPPA, n = 168), non-fluent/agrammatic variant PPA (nfvPPA, n = 168), logopenic variant PPA (lvPPA, n = 109), and controls (n = 581)). Sample sizes to detect treatment effects were estimated using longitudinal data.<h4>Results</h4>Among PPAs, the FTLD-MOD language tasks and UDS Multilingual Naming Test accurately discriminated svPPA. Number Span Forward best discriminated lvPPA; Phonemic:Semantic Fluency ratio was excellent for nfvPPA classification. UDS fluency and naming measures required the smallest sample size to detect meaningful change.<h4>Discussion</h4>The FTLD-MOD and UDS differentiated among PPA subtypes. UDS 3.0 measures performed best for longitudinal monitoring.
Project description:Digital pathology is increasingly prominent in neurodegenerative disease research, but variability in immunohistochemical staining intensity between staining batches prevents large-scale comparative studies. Here we provide a statistically rigorous method to account for staining batch effects in a large sample of brain tissue with frontotemporal lobar degeneration with tau inclusions (FTLD-Tau, N = 39) or TDP-43 inclusions (FTLD-TDP, N = 53). We analyzed the relationship between duplicate measurements of digital pathology, i.e., percent area occupied by pathology (%AO) for grey matter (GM) and white matter (WM), from two distinct staining batches. We found a significant difference in duplicate measurements from distinct staining batches in FTLD-Tau (mean difference: GM = 1.13 ± 0.44, WM = 1.28 ± 0.56; p < 0.001) and FTLD-TDP (GM = 0.95 ± 0.66, WM = 0.90 ± 0.77; p < 0.001), and these measurements were linearly related (R-squared [Rsq]: FTLD-Tau GM = 0.92, WM = 0.92; FTLD-TDP GM = 0.75, WM = 0.78; p < 0.001 all). We therefore used linear regression to transform %AO from distinct staining batches into equivalent values. Using a train-test set design, we examined transformation prerequisites (i.e., Rsq) from linear-modeling in training sets, and we applied equivalence factors (i.e., beta, intercept) to independent testing sets to determine transformation outcomes (i.e., intraclass correlation coefficient [ICC]). First, random iterations (×100) of linear regression showed that smaller training sets (N = 12-24), feasible for prospective use, have acceptable transformation prerequisites (mean Rsq: FTLD-Tau ?0.9; FTLD-TDP ?0.7). When cross-validated on independent complementary testing sets, in FTLD-Tau, N = 12 training sets resulted in 100% of GM and WM transformations with optimal transformation outcomes (ICC ? 0.8), while in FTLD-TDP N = 24 training sets resulted in optimal ICC in testing sets (GM = 72%, WM = 98%). We therefore propose training sets of N = 12 in FTLD-Tau and N = 24 in FTLD-TDP for prospective transformations. Finally, the transformation enabled us to significantly reduce batch-related difference in duplicate measurements in FTLD-Tau (GM/WM: p < 0.001 both) and FTLD-TDP (GM/WM: p < 0.001 both), and to decrease the necessary sample size estimated in a power analysis in FTLD-Tau (GM:-40%; WM: -34%) and FTLD-TDP (GM: -20%; WM: -30%). Finally, we tested generalizability of our approach using a second, open-source, image analysis platform and found similar results. We concluded that a small sample of tissue stained in duplicate can be used to account for pre-analytical variability such as staining batch effects, thereby improving methods for future studies.
Project description:Frontotemporal lobar degeneration (FTLD) is most commonly associated with TAR-DNA binding protein (TDP-43) or tau pathology at autopsy, but there are no in vivo biomarkers reliably discriminating between sporadic cases. As disease-modifying treatments emerge, it is critical to accurately identify underlying pathology in living patients so that they can be entered into appropriate etiology-directed clinical trials. Patients with tau inclusions (FTLD-TAU) appear to have relatively greater white matter (WM) disease at autopsy than those patients with TDP-43 (FTLD-TDP). In this paper, we investigate the ability of white matter (WM) imaging to help discriminate between FTLD-TAU and FTLD-TDP during life using diffusion tensor imaging (DTI).Patients with autopsy-confirmed disease or a genetic mutation consistent with FTLD-TDP or FTLD-TAU underwent multimodal T1 volumetric MRI and diffusion weighted imaging scans. We quantified cortical thickness in GM and fractional anisotropy (FA) in WM. We performed Eigenanatomy, a statistically robust dimensionality reduction algorithm, and used leave-one-out cross-validation to predict underlying pathology. Neuropathological assessment of GM and WM disease burden was performed in the autopsy-cases to confirm our findings of an ante-mortem GM and WM dissociation in the neuroimaging cohort.ROC curve analyses evaluated classification accuracy in individual patients and revealed 96% sensitivity and 100% specificity for WM analyses. FTLD-TAU had significantly more WM degeneration and inclusion severity at autopsy relative to FTLD-TDP.These neuroimaging and neuropathological investigations provide converging evidence for greater WM burden associated with FTLD-TAU, and emphasise the role of WM neuroimaging for in vivo discrimination between FTLD-TAU and FTLD-TDP.
Project description:Objective: Behavioral variant frontotemporal dementia (bvFTD), is commonly considered the cognitive presentation of the frontotemporal dementia-motor neuron disease (FTD-MND) spectrum disorder. We evaluated the prevalence of primary progressive aphasia in a series of pathologically confirmed cases of FTD-MND spectrum. Methods: Pathologically confirmed cases of frontotemporal lobar degeneration-motor neuron disease (FTLD-MND) were obtained from the UCSF brain bank. Cases were analyzed for presence of language impairment via retrospective chart review of research visits that include neurologic exam, in-depth cognitive testing and magnetic resonance imaging (MRI) imaging. Forty one cases were included. Thirty two were diagnosed with FTD-MND, while nine cases were diagnosed as MND-only from clinical evaluation. Results: Ten FTLD-MND cases (31%) presented with prominent or isolated language involvement consistent with a diagnosis of primary progressive aphasia (PPA), which we called progressive aphasia with motor neuron disease (PA-MND). Of these, three cases that mirrored the non-fluent variant of PPA (nfvPPA) were named nfvPA-MND. The imaging pattern of these nfvPA-MND showed atrophy strictly confined to the frontal and anterior temporal language cortical areas. Another group of seven cases that resembled patients with the semantic variant PPA (svPPA) were named svPA-MND. The group of svPPA-MND on imaging analysis showed selective atrophy of the temporal lobe and orbitofrontal cortex. Conclusions: Language impairment was a frequent phenotype of FTD-MND associated with focal atrophy patterns within the language networks. This data suggest patients with FTD-MND can present quite often with language phenotype of nfvPPA and svPPA, as opposed to exclusive bvFTD symptoms.
Project description:<h4>Background and purpose</h4>There are three distinct subtypes of primary progressive aphasia (PPA): the nonfluent/agrammatic variant (nfvPPA), the semantic variant (svPPA), and the logopenic variant (lvPPA). We sought to characterize the pattern of [¹?F]-THK5351 retention across all three subtypes and determine the topography of [¹?F]-THK5351 retention correlated with each neurolinguistic score.<h4>Methods</h4>We enrolled 50 participants, comprising 13 PPA patients (3 nfvPPA, 5 svPPA, and 5 lvPPA) and 37 subjects with normal cognition (NC) who underwent 3.0-tesla magnetic resonance imaging, [¹?F]-THK5351 positron-emission tomography scans, and detailed neuropsychological tests. The PPA patients additionally participated in extensive neurolinguistic tests. Voxel-wise and region-of-interest-based analyses were performed to analyze [¹?F]-THK5351 retention.<h4>Results</h4>The nfvPPA patients exhibited higher [¹?F]-THK5351 retention in the the left inferior frontal and precentral gyri. In svPPA patients, [¹?F]-THK5351 retention was elevated in the anteroinferior and lateral temporal cortices compared to the NC group (left>right). The lvPPA patients exhibited predominant [¹?F]-THK5351 retention in the inferior parietal, lateral temporal, and dorsolateral prefrontal cortices, and the precuneus (left>right). [¹?F]-THK5351 retention in the left inferior frontal area was associated with lower fluency scores. Comprehension was correlated with [¹?F]-THK5351 retention in the left temporal cortices. Repetition was associated with [¹?F]-THK5351 retention in the left inferior parietal and posterior temporal areas, while naming difficulty was correlated with retention in the left fusiform and temporal cortices.<h4>Conclusions</h4>The pattern of [¹?F]-THK5351 retention was well matched with clinical and radiological findings for each PPA subtype, in agreement with the anatomical and functional location of each language domain.
Project description:Currently, variant subtyping in primary progressive aphasia (PPA) requires an expert neurologist and extensive language and cognitive testing. Spelling impairments appear early in the development of the disorder, and the three PPA variants (non-fluent - nfvPPA; semantic - svPPA; logopenic - lvPPA) reportedly show fairly distinct spelling profiles. Given the theoretical and empirical evidence indicating that spelling may serve as a proxy for spoken language, the current study aimed to determine whether spelling performance alone, when evaluated with advanced statistical analyses, allows for accurate PPA variant classification. A spelling to dictation task (with real words and pseudowords) was administered to 33 PPA individuals: 17 lvPPA, 10 nfvPPA, 6 svPPA. Using machine learning classification algorithms, we obtained pairwise variant classification accuracies that ranged between 67 and 100%. In additional analyses that assumed no prior knowledge of each case's variant, classification accuracies ranged between 59 and 70%. To our knowledge, this is the first time that all the PPA variants, including the most challenging logopenic variant, have been classified with such high accuracy when using information from a single language task. These results underscore the rich structure of the spelling process and support the use of a spelling task in PPA variant classification.