Recent studies suggest that hippocampus has different cortical connectivity and functionality along its longitudinal axis. We sought to elucidate the possible different pattern of atrophy in ...longitudinal axis of hippocampus between Amyloid/Tau pathology and TDP-43-pathies. Seventy-three presenile subjects were included: Amyloid/Tau group (33 Alzheimer's disease with confirmed cerebrospinal fluid CSF biomarkers), probable TDP-43 group (7 semantic variant progressive primary aphasia, 5 GRN and 2 C9orf72 mutation carriers) and 26 healthy controls. We conducted a region-of-interest voxel-based morphometry analysis on the hippocampal longitudinal axis, by contrasting the groups, covarying with CSF biomarkers (Aβ42, total tau, p-tau) and covarying with episodic memory scores. Amyloid/Tau pathology affected mainly posterior hippocampus while anterior left hippocampus was more atrophied in probable TDP-43-pathies. We also observed a significant correlation of posterior hippocampal atrophy with Alzheimer's disease CSF biomarkers and visual memory scores. Taken together, these data suggest that there is a potential differentiation along the hippocampal longitudinal axis based on the underlying pathology, which could be used as a potential biomarker to identify the underlying pathology in different neurodegenerative diseases.
Abstract Alzheimer's disease (AD) is the most common neurodegenerative dementia. Approximately 10% of cases present at an age of onset before 65 years old, which in turn can be monogenic familial AD ...(FAD) or sporadic early-onset AD (sEOAD). Mutations in PSEN1, PSEN2 , and APP genes have been linked with FAD. The aim of our study is to describe the brain whole-genome RNA expression profile of the posterior cingulate area in sEOAD and FAD caused by PSEN1 mutations (FAD-PSEN1). Fourteen patients (7 sEOAD and 7 FAD-PSEN1) and 7 neurologically healthy control subjects were selected and whole-genome expression was measured using Affymetrix Human Gene 1.1 microarrays. We identified statistically significant expression changes in sEOAD and FAD-PSEN1 brains with respect to control subjects (3183 and 3350 differentially expressed genes DEG respectively, false discovery rate-corrected p < 0.05). Of them, 1916 DEG were common between the 2 comparisons. We did not identify DEG between sEOAD and FAD-PSEN1. Microarray data were validated through real-time quantitative polymerase chain reaction. In silico analysis of DEG revealed an alteration in biological pathways related to intracellular signaling pathways (particularly calcium signaling), neuroactive ligand-receptor interactions, axon guidance, and long-term potentiation in both groups of patients. In conclusion, the altered biological final pathways in sEOAD and FAD-PSEN1 are mainly related with cell signaling cascades, synaptic plasticity, and learning and memory processes. We hypothesize that these 2 groups of early-onset AD with distinct etiologies and likely different could present a neurodegenerative process with potential different pathways that might converge in a common and similar final stage of the disease.
Plasma biomarkers have emerged as promising tools for identifying amyloid beta (Aβ) pathology. Before implementation in routine clinical practice, confounding factors modifying their concentration ...beyond neurodegenerative diseases should be identified. We studied the association of a comprehensive list of demographics, comorbidities, medication and laboratory parameters with plasma p-tau181, glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) on a prospective memory clinic cohort and studied their impact on diagnostic accuracy for discriminating CSF/amyloid PET-defined Aβ status. Three hundred sixty patients (mean age 66.5 years, 55% females, 53% Aβ positive) were included. Sex, age and Aβ status-adjusted models showed that only estimated glomerular filtration rate (eGFR, standardized β −0.115 −0.192 to −0.035,
p
= 0.005) was associated with p-tau181 levels, although with a much smaller effect than Aβ status (0.685 0.607–0.763,
p
< 0.001). Age, sex, body mass index (BMI), Charlson comorbidity index (CCI) and eGFR significantly modified GFAP concentration. Age, blood volume (BV) and eGFR were associated with NfL levels. p-tau181 predicted Aβ status with 87% sensitivity and specificity with no relevant increase in diagnostic performance by adding any of the confounding factors. Using two cut-offs, plasma p-tau181 could have spared 62% of amyloid-PET/CSF testing. Excluding patients with chronic kidney disease did not change the proposed cut-offs nor the diagnostic performance. In conclusion, in a memory clinic cohort, age, sex, eGFR, BMI, BV and CCI slightly modified plasma p-tau181, GFAP and NfL concentrations but their impact on the diagnostic accuracy of plasma biomarkers for Aβ status discrimination was minimal.
Sporadic early-onset Alzheimer’s disease (EOAD) and autosomal dominant Alzheimer’s disease (ADAD) provide the opportunity to investigate the physiopathological mechanisms in the absence of aging, ...present in late-onset forms. Frontotemporal dementia (FTD) causes early-onset dementia associated to tau or TDP43 protein deposits. A 15% of FTD cases are caused by mutations in
C9orf72
,
GRN
, or
MAPT
genes. Lymphoblastoid cell lines (LCLs) have been proposed as an alternative to brain tissue for studying earlier phases of neurodegenerative diseases. The aim of this study is to investigate the expression profile in EOAD, ADAD, and sporadic and genetic FTD (sFTD and gFTD, respectively), using brain tissue and LCLs. Sixty subjects of the following groups were included: EOAD, ADAD, sFTD, gFTD, and controls. Gene expression was analyzed with Clariom D microarray (Affymetrix). Brain tissue pairwise comparisons revealed six common differentially expressed genes (DEG) for all the patients’ groups compared with controls:
RGS20
,
WIF1
,
HSPB1
,
EMP3
,
S100A11
and
GFAP.
Common up-regulated biological pathways were identified both in brain and LCLs (including inflammation and glial cell differentiation), while down-regulated pathways were detected mainly in brain tissue (including synaptic signaling, metabolism and mitochondrial dysfunction).
CD163, ADAMTS9
and
LIN7A
gene expression disruption was validated by qPCR in brain tissue and
NrCAM
in LCLs in their respective group comparisons. In conclusion, our study highlights neuroinflammation, metabolism and synaptic signaling disturbances as common altered pathways in different AD and FTD forms. The use of LCLs might be appropriate for studying early immune system and inflammation, and some neural features in neurodegenerative dementias.
Abstract Cerebrospinal fluid (CSF) concentrations of YKL-40 that serve as biomarker of neuroinflammation are known to be altered along the clinico-biological continuum of Alzheimer's disease (AD). ...The specific structural cerebral correlates of CSF YKL-40 were evaluated across the early stages of AD from normal to preclinical to mild dementia. Nonlinear gray matter (GM) volume associations with CSF YKL-40 levels were assessed in a total of 116 subjects, including normal controls and those with preclinical AD as defined by CSF Aβ < 500 pg/mL, mild cognitive impairment (MCI) due to AD, or mild AD dementia. Age-corrected YKL-40 levels were increased in MCIs versus the rest of groups and showed an inverse u-shaped association with p-tau values. A similar nonlinear relationship was found between GM volume and YKL-40 in inferior and lateral temporal regions spreading to the supramarginal gyrus, insula, inferior frontal cortex, and cerebellum in MCI and AD. These findings for YKL-40 remained unchanged after adjusting for p-tau, which was found to be associated with GM volumes in distinct anatomic areas. CSF YKL-40, a biomarker of glial inflammation, is associated with a cerebral structural signature distinct from that related to p-tau neurodegeneration at the earliest stages of cognitive decline due to AD.
Early-onset Alzheimer’s disease (EOAD) and frontotemporal dementia (FTD) have a high proportion of genetically determined cases. Next-generation sequencing technologies have triggered the discovery ...of new mutations and genetic variants in dementia-causal genes. We performed whole-exome sequencing and selective analysis of known genes causative of EOAD and FTD in a well-characterized Spanish cohort of 103 patients (60 EOAD, 43 FTD) to find genetic variants associated to patients’ phenotype. In EOAD patients, a new likely pathogenic variant in PSEN1 gene (p.G378R) was found. In FTD patients, 2 likely pathogenic variants were found, one in MAPT gene (p.P397S) and one in VCP gene (p.R159H). In our series, 2% of early-onset dementia without criteria for clinical genetic testing according to current guidelines presented a likely pathogenic mutation. We have also detected 13 additional variants of uncertain significance in causal genes, as well as rare variants in risk genes for dementia (ABCA7, SORL1, SQSTM1, and TREM2). Next-generation technologies in neurodegenerative diseases constitute a powerful tool that significantly contributes to patients’ diagnosis.
•Whole-exome sequencing analysis of 103 patients with early-onset dementia.•A novel likely pathogenic variant is described in PSEN1 gene (p.G378R) in AD.•Novel likely pathogenic variants are found in MAPT (p.P397S) and VCP (p.R159H) in FTD.•We have found likely pathogenic variants in 2% of patients without early-onset family history of disease.•Clinical criteria for genetic testing may disappear as WES becomes more available.
Frontotemporal Dementia (FTD) is preceded by a long period of subtle brain changes, occurring in the absence of overt cognitive symptoms, that need to be still fully characterized. Dynamic network ...analysis based on resting-state magnetic resonance imaging (rs-fMRI) is a potentially powerful tool for the study of preclinical FTD.
In the present study, we employed a "chronnectome" approach (recurring, time-varying patterns of connectivity) to evaluate measures of dynamic connectivity in 472 at-risk FTD subjects from the Genetic Frontotemporal dementia research Initiative (GENFI) cohort.
We considered 249 subjects with FTD-related pathogenetic mutations and 223 mutation non-carriers (HC). Dynamic connectivity was evaluated using independent component analysis and sliding-time window correlation to rs-fMRI data, and meta-state measures of global brain flexibility were extracted.
Results show that presymptomatic FTD exhibits diminished dynamic fluidity, visiting less meta-states, shifting less often across them, and travelling through a narrowed meta-state distance, as compared to HC. Dynamic connectivity changes characterize preclinical FTD, arguing for the desynchronization of the inner fluctuations of the brain. These changes antedate clinical symptoms, and might represent an early signature of FTD to be used as a biomarker in clinical trials.
•Frontotemporal Dementia is preceded by a long period of subtle brain changes.•Time-varying dynamic connectivity can unveiled underappreciated brain details.•Presymptomatic Frontotemporal Dementia exhibits a reduced dynamic fluidity.•Frontotemporal Dementia showed a selective vulnerability of specific brain regions.•At the very early stage Frontotemporal Dementia is affecting brain as global system.
Background
The diagnosis of early‐onset neurodegenerative dementias (<65 years) can represent a challenge due to their lower frequency respect to late‐onset dementias and atypical forms of ...presentation. Cognitive impairment has emerged as a frequent complaint after COVID‐19 infection.
Method
We retrospectively reviewed (2016‐2021) the demographic and clinical data of the new referrals at our early onset dementia clinic (Hospital Clínic Barcelona). We used Fisher’s Exact test and ANOVA in Stata/IC 16.1 to analyze differences between patients visited in 2021, 2020 and the period 2016‐2019.
Result
We evaluated 296 patients in 2021, 104 in 2020 and 98 patients/year in 2016‐2019. In 2021, patients had an age at onset (AAO) of 50.1 years, lower than 2020 (53.4) and the period 2016‐2019 (53.0) (p<0.05). The percentage of women in 2021 (69.6%) was higher than 2020 (57.7) and 2016‐2019 (56.0) (p<0.05). Diagnostic delay was lower in 2021 (2.1 years) than 2020 (3.3) and 2016‐2019 (3.0) (p<0.05). No differences were found in Minimental (MMSE) scores (Table 1).
In the period 2016‐2021, the number of neurodegenerative diseases (ND) remained steady, the number of subjective cognitive decline (SCD) decreased and the number of non neurodegenerative causes (NNC) experienced a large increase (Table 1), representing 77.7% of visits in 2021.
We did not find differences in the type of ND diagnosis in each period (Figure 1A). ND subgroups did not show differences in AAO, sex or MMSE. In 2021, NND presented lower AAO, higher percentage of women, lower diagnostic delay (Figure 1B) and higher MMSE scores than previous years. No differences were found in the SCD group.
Cognitive impairment after Covid‐19 accounted for 16.7% of NND in 2020 (n = 8, AAO 50.6 (11.8), 62.5% female, MMSE 26.8(2.3)) and 66.6% of NND in 2021 (n = 153, AAO 49,0 (10.0), 80.1% female, MMSE 27.8 (2.6)).
Conclusion
In 2021 we visited approximately three times more patients than in 2016‐2020, among which we observed an increase in NND, mainly patients with cognitive impairment after Covid‐19. On contrast, we found a similar number of ND diagnosis and reduction in SCD.
Background
Little is known about the influence of age at onset (AAO) on plasma biomarkers and their use as prognostic biomarkers in Alzheimer’s disease (AD).
Method
We selected patients with AD ...diagnosis with available neuropsychological testing (NPS) at time of diagnosis and two years later, and plasma biomarkers at baseline.
NPS battery included Free and Cued Selective Reminding Test (FCSRT), Landscape test (visual memory), Boston Naming Test, Semantic Fluency, BDAE auditory comprehension, Constructional and Ideomotor Praxis, Visual Object and Space Perception (VOSP) Incomplete Letters and Number Location subtests, Trail Making Test (TMT) A and B, Phonemic Fluency, and Digit Span Forward and Backward. NPS scores were compared by AAO: early‐onset AD (EOAD; <65 years) vs. late onset AD (LOAD; >65y).
We analyzed plasma biomarkers phosphorilated‐tau181 (p‐tau181), total tau (t‐tau), neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP) and ubiquitin C‐terminal hydrolase L1 (UCHL‐1) using the Quanterix Simoa p‐tau181 Advantage V2 and Neurology 4‐Plex A assays. Group comparisons and linear regressions adjusted by years of education (YOE) were performed in Stata/IC 16.1.
Result
Forty‐two participants were included, 23 LOAD and 19 EOAD. Plasma p‐tau181 and GFAP levels were higher in LOAD (Table 1). We did not find differences between LOAD and EOAD in NPS tests at baseline or +2 years (Table 2).
Plasma ptau‐181 was associated with progression in MMSE globally, VOSP‐Incomplete letters globally and in EOAD. Plasma NfL were associated to Boston Naming test globally and in EOAD, Semantic fluency test globally, VOSP‐incomplete letters in EOAD, and Free and Total Learning of FCSRT in LOAD. Plasma GFAP was associated to MMSE globally and in EOAD, Free learning of FCSRT in LOAD and VOSP‐Incomplete letters and number location globally. Plasma UCHL‐1 was associated to Semantic fluency test in LOAD (Table 3). Praxis and attention and executive function tests loss were not associated to plasma biomarkers.
Conclusion
Plasma p‐tau18, NfL, GFAP and UCHL‐1 were associated to pogression in memory, language and visual tests. They were predominantly associated to memory loss in LOAD and language and visual function loss in EOAD. Results need to be interpreted cautiously due to small sample size.
Background
Blood‐based biomarkers have recently emerged as minimally‐invasive, accessible and relatively inexpensive diagnostic and prognostic tools for people with cognitive impairment. Before being ...routinely implemented in clinical practice, the diagnostic performance of distinct commercially available assays should be studied in real‐world cohorts. We aimed to study and compare the diagnostic accuracy of different plasma biomarkers measured using two different assay platforms in a memory clinic cohort.
Method
Participants were selected from a prospective memory clinic cohort; all had Alzheimer’s disease (AD) CSF biomarkers performed. Plasma p‐tau181, GFAP and NfL were measured using Simoa (Quanterix), while plasma p‐tau181, Aβ1‐40 and Aβ1‐42 were quantified using Lumipulse G (Fujirebio). Clinical diagnoses were made according to published criteria, blinded to plasma biomarkers. Aβ status (‐/+) was defined by CSF Aβ concentration using local cutoffs.
Result
One hundred and ten participants were included (mean age standard deviation 66 7.8 years, 56% women). Diagnostic categories included 10 cognitively unimpaired controls, 24 with suspected non‐neurodegenerative cause of cognitive impairment (SND), 53 AD, 9 Lewy body disease (LBD, 4 Aβ+) and 14 frontotemporal dementia (FTD, 1 Aβ+).
Plasma p‐tau181Quanterix and Aβ1‐42/Aβ1‐40 had the highest diagnostic accuracy (Figure 1) to discriminate between SND and AD (AUC CI 0.94 0.89‐0.99 and 0.94 0.85‐1), followed by GFAP (0.93 0.87‐0.99), p‐tau181Fujirebio (0.90 0.82‐0.98) and Aβ1‐42 (0.71 0.58‐0.85). Plasma NfL performed the best to differentiate FTD from SND and AD (AUC 0.95 0.88‐1 and 0.85 0.71‐0.99, respectively).
For Aβ status discrimination (Figure 2), p‐tau181Quanterix had an AUC CI of 0.91 0.85‐0.96, followed by p‐tau181Fujirebio (0.86 0.79‐0.93), Aβ1‐42/Aβ1‐40 (0.85 0.76‐0.93) and GFAP (0.84 0.77‐0.92) with no statistically significant differences in AUCs. Balanced (Youden index) cut‐offs were calculated to study diagnostic performance, resulting in sensitivities of 79‐83%, specificities of 74‐83% and accuracies of 76‐83%. No combination of plasma biomarkers resulted in a significantly increased discriminative accuracy for Aβ status. All plasma biomarkers were moderately correlated with p‐tau181Quanterix (ρ = 0.40‐0.75, Figure 3).
Conclusion
In our cohort, p‐tau181Quanterix, p‐tau181Fujirebio, Aβ1‐42/Aβ1‐40 and GFAP had a high diagnostic performance to discriminate CSF‐defined Aβ status. Plasma NfL identified individuals with FTD. Further studies comparing different plasma biomarkers are needed before implementation in clinical practice.
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