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Voxel‐wise maps of correlation between fraction anisotropy and cerebrospinal fluid‐biomarkers, studied separately for each group
Source publication
Prior studies have described distinct patterns of brain gray matter and white matter alterations in Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD), as well as differences in their cerebrospinal fluid (CSF) biomarkers profiles. We aim to investigate the relationship between early‐onset AD (EOAD) and FTLD structural alterations...
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Patients with Frontotemporal Dementia (FTD) have impaired cognitive abilities, executive and behavioral traits, loss of language ability, and decreased memory capabilities. Based on the distinct patterns of cortical atrophy and symptoms, the FTD spectrum primarily includes three variants: behavioral variant FTD (bvFTD), non-fluent variant primary p...
Citations
... In fact, CSF Ng levels were observably (but non-significantly) higher even in aMCI due to AD compared to FTLD dementia. Our data of higher CSF Ng concentrations in patients with AD are in agreement with previous reports [8,9,[50][51][52][53][54], as well as with a meta-analysis comparing CSF Ng levels in patients with AD and other neurodegenerative diseases including FTLD [55], highlighting the connection with AD-specific pathophysiological processes that appear to be markedly different from those driving FTLD in the context of markers of postsynaptic dysfunction. We found that CSF Ng levels were significantly higher in patients with FTLD dementia than in patients with MCI due to FTLD. ...
Background
There is initial evidence suggesting that biomarker neurogranin (Ng) may distinguish Alzheimer’s disease (AD) from other neurodegenerative diseases. Therefore, we assessed (a) the discriminant ability of cerebrospinal fluid (CSF) Ng levels to distinguish between AD and frontotemporal lobar degeneration (FTLD) pathology and between different stages within the same disease, (b) the relationship between Ng levels and cognitive performance in both AD and FTLD pathology, and (c) whether CSF Ng levels vary by apolipoprotein E (APOE) polymorphism in the AD continuum.
Methods
Participants with subjective cognitive decline (SCD) (n = 33), amnestic mild cognitive impairment (aMCI) due to AD (n = 109), AD dementia (n = 67), MCI due to FTLD (n = 25), and FTLD dementia (n = 29) were recruited from the Czech Brain Aging Study. One-way analysis of covariance (ANCOVA) assessed Ng levels in diagnostic subgroups. Linear regressions evaluated the relationship between CSF Ng levels, memory scores, and APOE polymorphism.
Results
Ng levels were higher in aMCI-AD patients compared to MCI-FTLD (F[1, 134] = 15.16, p < .001), and in AD-dementia compared to FTLD-dementia (F[1, 96] = 4.60, p = .029). Additionally, Ng levels were higher in FTLD-dementia patients compared to MCI-FTLD (F[1, 54]= 4.35, p = .034), lower in SCD participants compared to aMCI-AD (F[1, 142] = 10.72, p = .001) and AD-dementia (F[1, 100] = 20.90, p < .001), and did not differ between SCD participants and MCI-FTLD (F[1, 58]= 1.02, p = .491) or FTLD-dementia (F[1, 62]= 2.27, p = .051). The main effect of diagnosis across the diagnostic subgroups on Aβ1−42/Ng ratio was significant too (F[4, 263]=, p < .001). We found a non-significant association between Ng levels and memory scores overall (β=-0.25, p = .154) or in AD diagnostic subgroups, and non-significant differences in this association between overall AD APOE ε4 carriers and non-carriers (β=-0.32, p = .358).
Conclusions
In this first study to-date to assess MCI and dementia due to AD or FTLD within one study, elevated CSF Ng appears to be an early biomarker of AD-related impairment, but its role as a biomarker appears to diminish after dementia diagnosis, whereby dementia-related underlying processes in AD and FTLD may begin to merge. The Aβ1−42/Ng ratio discriminated AD from FTLD patients better than Ng alone. CSF Ng levels were not related to memory in AD or FTLD, suggesting that Ng may be a marker of the biological signs of disease state rather than cognitive deficits.
... The association of CSF biomarkers and distinct brain atrophies is not yet sufficiently understood. However, cortical atrophies can be partially explained by levels of Aβ and 14-3-3 in AD, and neurofilament light chain and 14-3-3 in FTD (Falgàs et al., 2020). ...
Background: Dementia can be caused by numerous different diseases that present variable clinical courses and reveal multiple patterns of brain atrophy, making its accurate early diagnosis by conventional examinative means challenging. Although highly accurate and powerful, magnetic resonance imaging (MRI) currently plays only a supportive role in dementia diagnosis, largely due to the enormous volume and diversity of data it generates. AI-based software solutions/algorithms that can perform automated segmentation and volumetry analyses of MRI data are being increasingly used to address this issue. Numerous commercial and non-commercial software solutions for automated brain segmentation and volumetry exist, with FreeSurfer being the most frequently used. Objectives: This Review is an account of the current situation regarding the application of automated brain segmentation and volumetry to dementia diagnosis. Methods: We performed a PubMed search for "FreeSurfer AND Dementia" and obtained 493 results. Based on these search results, we conducted an in-depth source analysis to identify additional publications, software tools, and methods. Studies were analyzed for design, patient collective, and for statistical evaluation (mathematical methods, correlations). Results: In the studies identified, the main diseases and cohorts represented were Alzheimer's disease (n = 276), mild cognitive impairment (n = 157), frontotemporal dementia (n = 34), Parkinson's disease (n = 29), dementia with Lewy bodies (n = 20), and healthy controls (n = 356). The findings and methods of a selection of the studies identified were summarized and discussed. Conclusion: Our evaluation showed that, while a large number of studies and software solutions are available, many diseases are underrepresented in terms of their incidence. There is therefore plenty of scope for targeted research.
... Neurofilament light chain (NfL) plays an important role in axon transmission and function maintenance, and is the most abundant intermediate filament protein in myelinated subcortical axons 28 . Previous studies pointed that NFL is an ideal marker of large-caliber axonal degeneration, and increased NfL levels incerebrospinal fluid(CSF) are like to reflect neurodegeneration-related axonal injury 29 , such as Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD), multiple sclerosis and amyotrophic lateral sclerosis 30,31 . In addition, CSF NfL levels have also been proved to be an effective way to distinguish FTLD from AD 32,33 . ...
Convenient and effective biomarkers are essential for the early diagnosis and treatment of Alzheimer’s disease (AD). In the cross-sectional study, 103 patients with AD, 82 patients with aMCI and 508 normal controls (NC) were enrolled. The single‐molecule array (Simoa) technique was used to assess the levels of plasma proteins, including NfL, T-tau, P-tau-181, Aβ40, Aβ42. Montreal Cognitive Assessment (MoCA) was used to assess the overall cognitive function of all subjects. Moreover, Amyloid PET and structural head MRI were also performed in a subset of the population. In the follow-up, the previous 508 normal older adults were followed up for two years, then COX regression analysis was used to investigate the association between baseline plasma proteins and future cognitive outcomes. NfL, T-tau, P-tau-181, Aβ40, Aβ42 and Aβ42/40 were altered in AD dementia, and NfL, Aβ42 and Aβ42/40 significantly outperformed all plasma proteins in differentiating AD dementia from NC, while NfL and Aβ42/40 could effectively distinguish between aMCI and NC. However, only plasma NfL was associated with future cognitive decline, and it was negatively correlated with MoCA (r = − 0.298, p < 0.001) and the volume of the left globus pallidus (r = − 0.278, p = 0.033). Plasma NfL can help distinguish between cognitively normal and cognitively impaired individuals (MCI/dementia) at the syndrome level. However, since we have not introduced other biomarkers for AD, such as PET CT or cerebrospinal fluid, and have not verified in other neurodegenerative diseases, whether plasma NFL can be used as a biomarker for AD needs to be further studied and explored.
... Alzheimer's disease (AD), the most frequent type of neurodegenerative dementia [1], can be classified into early-onset and late-onset forms. In early-onset AD (EOAD) (5% of AD cases), symptoms appear, according to consensus, before 65 years old [2]. According to the etiology, the vast majority of EOAD cases have a sporadic origin (sEOAD) [3], but there is also a small percentage of cases (<1%) that show an autosomal dominant pattern of inheritance (ADAD), which is caused by mutations in three genes involved in the β-amyloid cascade: APP, PSEN1, and PSEN2 [4]. ...
Epigenetics, a potential underlying pathogenic mechanism of neurodegenerative diseases, has been in the scope of several studies performed so far. However, there is a gap in regard to analyzing different forms of early-onset dementia and the use of Lymphoblastoid cell lines (LCLs). We performed a genome-wide DNA methylation analysis on sixty-four samples (from the prefrontal cortex and LCLs) including those taken from patients with early-onset forms of Alzheimer’s disease (AD) and frontotemporal dementia (FTD) and healthy controls. A beta regression model and adjusted p-values were used to obtain differentially methylated positions (DMPs) via pairwise comparisons. A correlation analysis of DMP levels with Clariom D array gene expression data from the same cohort was also performed. The results showed hypermethylation as the most frequent finding in both tissues studied in the patient groups. Biological significance analysis revealed common pathways altered in AD and FTD patients, affecting neuron development, metabolism, signal transduction, and immune system pathways. These alterations were also found in LCL samples, suggesting the epigenetic changes might not be limited to the central nervous system. In the brain, CpG methylation presented an inverse correlation with gene expression, while in LCLs, we observed mainly a positive correlation. This study enhances our understanding of the biological pathways that are associated with neurodegeneration, describes differential methylation patterns, and suggests LCLs are a potential cell model for studying neurodegenerative diseases in earlier clinical phases than brain tissue.
... Only a few studies have focused on microstructural changes in WM or metabolic imaging. Falgàs et al. [56] showed, in 64 early-onset AD patients, a negative correlation between CSF NfLs and fractional anisotropy (FA) in the corticospinal tract and uncinate, inferiorlongitudinal, and inferior fronto-occipital fasciculi. Across all subjects and cognitively unimpaired controls, a significant association between plasma NfLs and hippocampal microstructures (cornus ammonis 4 and dentate gyrus) was found, whereas no association emerged in AD or MCI patients alone [48]. ...
... The first one included 132 FTD patients, including extrapyramidal phenotypes, and found an inverse correlation between serum NfL levels and cortical thickness of the prefrontal, temporal, and parietal regions, mainly in the dorso-lateral prefrontal cortex and on the left side [59]. Similar results have been shown with CSF NfLs, in areas of the bilateral frontal lobe such as the left pars opercularis, pars triangularis, middle and superior frontal, and precentral gyri, and the right prefrontal and orbitofrontal cortices [56,71], and in the temporal and parietal lobes [55]. Conversely, Illán-Gala and colleagues [61] investigated the same association in FTD and ALS patients and did not report significant results. ...
... As for WM microstructural integrity, Spotorno et al. [71] showed a negative correlation between plasma NfLs and FA in the uncinate and inferior fronto-occipital fasciculi, the anterior thalamic radiation, the corpus callosum, the left corticospinal tract, and the cerebral peduncle in bvFTD patients, while Falgàs and colleagues [56] reported an association between CSF NfLs and FA in the forceps minor, anterior thalamic radiation, cingulum, and left superior longitudinal fasciculus in all FTD patients. Longitudinally, it has been shown that higher baseline CSF NfLs predict a faster rate of decline in FA in frontotemporal areas in bvFTD and nfvPPA, and show a trend toward significance in the right uncinated fasciculus and the genu of corpus callosum in svPPA [63]. ...
Neurofilaments light chain (NfLs) are currently recognized as a marker of axonal injury and degeneration. Their measurement in biological fluids has a promising role in the diagnosis, prognosis, and monitoring of the therapeutic response in neurological diseases, including neurodegenerative dementias. In recent years, their relationship with clinical phenotypes and measures of disease severity has been extensively studied. Here, we reviewed studies investigating the association between NfLs and imaging measures of grey matter (GM) and white matter (WM) damage in neurodegenerative dementias. We identified a large number of studies investigating this association in Alzheimer’s disease (AD) and disorders of the frontotemporal dementia (FTD) spectrum. Results were heterogeneous, possibly due to different methodological approaches—both in NfL measurements and imaging analyses—and inclusion criteria. However, a positive association between NfL levels and GM atrophy, WM microstructural disruption, glucose hypometabolism, and protein accumulation emerged invariably, confirming the role of NfLs as a reliable biomarker for neurodegenerative dementias, albeit not specific.
... Cerebrospinal fluid (CSF) biomarkers, such as the amyloid-beta protein 42 (Aβ42), the total tau (t-tau), and phosphorylated tau (p-tau), have been included in the current criteria for AD diagnosis [7,8]. Other CSF biomarkers, such as neurofilament light chain (NfL) levels, a marker of neuroaxonal damage, and 14-3-3 protein levels, a marker of synaptic-neuronal loss, have been both proposed as nonspecific neurodegeneration markers [9][10][11][12]. ...
... On the other hand, the temporal and frontal lobes were the ones with the highest deviations for the FTD patients compared to the HC trend. In addition, temporal regions presented higher deviation than the AD group, depicting higher structural alterations in FTD [11,32,34,35]. ...
Background and objective
Alzheimer’s disease (AD) and frontotemporal dementia (FTD) show different patterns of cortical thickness (CTh) loss compared with healthy controls (HC), even though there is relevant heterogeneity between individuals suffering from each of these diseases. Thus, we developed CTh models to study individual variability in AD, FTD, and HC.
Methods
We used the baseline CTh measures of 379 participants obtained from the structural MRI processed with FreeSurfer. A total of 169 AD patients (63 ± 9 years, 65 men), 88 FTD patients (64 ± 9 years, 43 men), and 122 HC (62 ± 10 years, 47 men) were studied. We fitted region-wise temporal models of CTh using Support Vector Regression. Then, we studied associations of individual deviations from the model with cerebrospinal fluid levels of neurofilament light chain (NfL) and 14–3-3 protein and Mini-Mental State Examination (MMSE). Furthermore, we used real longitudinal data from 144 participants to test model predictivity.
Results
We defined CTh spatiotemporal models for each group with a reliable fit. Individual deviation correlated with MMSE for AD and with NfL for FTD. AD patients with higher deviations from the trend presented higher MMSE values. In FTD, lower NfL levels were associated with higher deviations from the CTh prediction. For AD and HC, we could predict longitudinal visits with the presented model trained with baseline data. For FTD, the longitudinal visits had more variability.
Conclusion
We highlight the value of CTh models for studying AD and FTD longitudinal changes and variability and their relationships with cognitive features and biomarkers.
... Although prior neuroimaging studies have advanced our understanding of anatomic abnormalities in EOAD, these studies have included small samples, composed mainly of patients with amnestic EOAD dementia. 5,7,10,11 No studies have focused on developing an MRI biomarker specific to EOAD. Such a disease-signature MRI biomarker has been established and validated in LOAD dementia 12 and has proven to be powerful in predicting progressive decline in people with mild cognitive impairment (MCI) 13,14 or who were cognitively unimpaired, [15][16][17] and in predicting molecular biomarker status. ...
INTRODUCTION
Magnetic resonance imaging (MRI) research has advanced our understanding of neurodegeneration in sporadic early‐onset Alzheimer's disease (EOAD) but studies include small samples, mostly amnestic EOAD, and have not focused on developing an MRI biomarker.
METHODS
We analyzed MRI scans to define the sporadic EOAD‐signature atrophy in a small sample (n = 25) of Massachusetts General Hospital (MGH) EOAD patients, investigated its reproducibility in the large longitudinal early‐onset Alzheimer's disease study (LEADS) sample (n = 211), and investigated the relationship of the magnitude of atrophy with cognitive impairment.
RESULTS
The EOAD‐signature atrophy was replicated across the two cohorts, with prominent atrophy in the caudal lateral temporal cortex, inferior parietal lobule, and posterior cingulate and precuneus cortices, and with relative sparing of the medial temporal lobe. The magnitude of EOAD‐signature atrophy was associated with the severity of cognitive impairment.
DISCUSSION
The EOAD‐signature atrophy is a reliable and clinically valid biomarker of AD‐related neurodegeneration that could be used in clinical trials for EOAD.
Highlights
We developed an early‐onset Alzheimer's disease (EOAD)–signature of atrophy based on magnetic resonance imaging (MRI) scans.
EOAD signature was robustly reproducible across two independent patient cohorts.
EOAD signature included prominent atrophy in parietal and posterior temporal cortex.
The EOAD‐signature atrophy was associated with the severity of cognitive impairment.
EOAD signature is a reliable and clinically valid biomarker of neurodegeneration.
... In Alzheimer's Disease, for instance, correlations between NF-L levels and CT have been found in the left and right lateral temporal lobes and in right inferior parietal and left superior frontal regions (Alcolea et al., 2017;Illán-Gala et al., 2021). In frontotemporal lobar degeneration related syndromes, local associations of NF-L levels with CT have been found in frontal, temporal, and parietal areas of both hemispheres (Alcolea et al., 2017;Falgàs et al., 2020;Illán-Gala et al., 2021;Spotorno et al., 2020). Therefore, while structural alterations in acAN seem more spatially homogeneous compared to neurodegenerative diseases [e.g. in Alzheimer's Disease the most pronounced reductions are located in the hippocampus and the temporal pole (Karow et al., 2010)], the neural mechanisms underlying these alterations might be similar, and seem in both cases related to axonal damage. ...
Background:
Anorexia nervosa (AN) is characterized by severe emaciation and drastic reductions of brain mass, but the underlying mechanisms remain unclear. The present study investigated the putative association between the serum-based protein markers of brain damage neurofilament light (NF-L), tau protein, and glial fibrillary acidic protein (GFAP) and cortical thinning in acute AN.
Methods:
Blood samples and magnetic resonance imaging scans were obtained from 52 predominantly adolescent, female patients with AN before and after partial weight restoration (increase in body mass index >14%). The effect of marker levels before weight gain and change in marker levels on cortical thickness (CT) was modeled at each vertex of the cortical surface using linear mixed-effect models. To test whether the observed effects were specific to AN, follow-up analyses exploring a potential general association of marker levels with CT were conducted in a female healthy control (HC) sample (n = 147).
Results:
In AN, higher baseline levels of NF-L, an established marker of axonal damage, were associated with lower CT in several regions, with the most prominent clusters located in bilateral temporal lobes. Tau protein and GFAP were not associated with CT. In HC, no associations between damage marker levels and CT were detected.
Conclusions:
A speculative interpretation would be that cortical thinning in acute AN might be at least partially a result of axonal damage processes. Further studies should thus test the potential of serum NF-L to become a reliable, low-cost and minimally invasive marker of structural brain alterations in AN.
... Similar results have been reported in a previous cohort consisting of AD and FTD patients [30]. The plausible reasons for the lack of differential CSF profiles of synaptic proteins in the two disease groups could be the heterogeneity of FTD as a disease, its co-pathologies with AD and other dementias, or the sheer underrepresentation of FTD in clinical cohorts due to misclassification [10,[31][32][33]. Furthermore, it has been suggested that the implied AD specificity of Ng could be a result of selection bias in cohorts. ...
... NPTX2 reportedly has predictive value for patients with genetic FTD [33,34]. In this cohort, the NPTX2 levels were significantly lower in FTD patients compared to SCD. ...
Background
Loss of synaptic functionality has been recently identified as an early-stage indicator of neurological diseases. Consequently, monitoring changes in synaptic protein levels may be relevant for observing disease evolution or treatment responses in patients. Here, we have studied the relationship between fluid biomarkers of neurodegeneration and synaptic dysfunction in patients with Alzheimer’s disease (AD), frontotemporal dementia (FTD), and subjective cognitive decline (SCD).
Methods
The exploratory cohort consisted of cerebrospinal fluid (CSF) samples (n = 60) from patients diagnosed with AD (n = 20), FTD (n = 20), and SCD (n = 20) from the Amsterdam Dementia Cohort. We developed two novel immunoassays for the synaptic proteins synaptosomal-associated protein-25 (SNAP25) and vesicle-associated membrane protein-2 (VAMP2). We measured the levels of these biomarkers in CSF, in addition to neuronal pentraxin-2 (NPTX2), glutamate ionotropic receptor-4 (GluR4), and neurogranin (Ng) for this cohort. All in-house immunoassays were validated and analytically qualified prior to clinical application. CSF neurogranin (Ng) was measured using a commercially available ELISA.
Results
This pilot study indicated that SNAP25, VAMP2, and Ng may not be specific biomarkers for AD as their levels were significantly elevated in patients with both AD and FTD compared to SCD. Moreover, the strength of the correlations between synaptic proteins was lower in the AD and FTD clinical groups compared to SCD. SNAP25, VAMP2, and Ng correlated strongly with each other as well as with total Tau (Tau) and phosphorylated Tau (PTau) in all three clinical groups. However, this correlation was weakened or absent with NPTX2 and GluR4. None of the synaptic proteins correlated to neurofilament light (NfL) in any clinical group.
Conclusion
The correlation of the synaptic biomarkers with CSF Tau and PTau but the lack thereof with NfL implies that distinct pathological pathways may be involved in synaptic versus axonal degeneration. Our results reflect the diversity of synaptic pathology in neurodegenerative dementias.
... Concretely, using structural MRI, studies have described patterns of cortical thickness (CTh) and gray matter (GM) volume loss both in AD and FTD when compared separately with healthy populations (Bocchetta et al., 2021;Canu et al., 2017;Contador et al., 2021;Möller et al., 2013). In addition, in a previous study including both diseases, we showed that distinct brain atrophy patterns could potentially help in differentiating AD and FTD (Falgàs et al., 2020). More recently, measures derived from MRI have been used within ML algorithms to differentiate these diseases (Bron et al., 2017;Li et al., 2021;Möller et al., 2016;Penny et al., 2007). ...
... ML techniques search for robust interactions between features (in our case the brain regions), so it is plausible that AD and FTD patterns present both differential and overlapping regions. Previous works (Davatzikos et al., 2008;Falgàs et al., 2020;Laakso et al., 2000) have also found some overlapping patterns of degeneration across disorders. Overall, we believe that the joint analysis of overlapping patterns (i.e., indicating common neurodegeneration) and specific regional alterations will be crucial in future works investigating differential diagnosis. ...
Alzheimer's disease (AD) and frontotemporal dementia (FTD) are common causes of dementia with partly overlapping, symptoms and brain signatures. There is a need to establish an accurate diagnosis and to obtain markers for disease tracking. We combined unsupervised and supervised machine learning to discriminate between AD and FTD using brain magnetic resonance imaging (MRI). We included baseline 3T-T1 MRI data from 339 subjects: 99 healthy controls (CTR), 153 AD and 87 FTD patients; and 2-year follow-up data from 114 subjects. We obtained subcortical gray matter volumes and cortical thickness measures using FreeSurfer. We used dimensionality reduction to obtain a single feature that was later used in a support vector machine for classification. Discrimination patterns were obtained with the contribution of each region to the single feature. Our algorithm differentiated CTR versus AD and CTR versus FTD at the cross-sectional level with 83.3% and 82.1% of accuracy. These increased up to 90.0% and 88.0% with longitudinal data. When we studied the classification between AD versus FTD we obtained an accuracy of 63.3% at the cross-sectional level and 75.0% for longitudinal data. The AD versus FTD versus CTR classification has reached an accuracy of 60.7%, and 71.3% for cross-sectional and longitudinal data respectively. Disease discrimination brain maps are in concordance with previous results obtained with classical approaches. By using a single feature, we were capable to classify CTR, AD, and FTD with good accuracy, considering the inherent overlap between diseases. Importantly, the algorithm can be used with cross-sectional and longitudinal data.
