Stepwise Functional Brain Architecture Correlates with Atrophy in Progressive Supranuclear Palsy.

BACKGROUND: Stepwise functional connectivity (SFC) detects whole-brain functional couplings of a selected region of interest at increasing link-step topological distances. OBJECTIVE: This study applied SFC to test the hypothesis that stepwise architecture propagating from the disease epicenter would shape patterns of brain atrophy in patients with progressive supranuclear palsy-Richardson's syndrome (PSP-RS). METHODS: Thirty-six patients with PSP-RS and 44 age-matched healthy control subjects underwent brain magnetic resonance imaging on a 3-T scanner. The disease epicenter was defined as the peak of atrophy observed in an independent cohort of 13 cases with postmortem confirmation of PSP pathology and used as seed region for SFC analysis. First, we explored SFC rearrangements in patients with PSP-RS, as compared with age-matched control subjects. Subsequently, we tested SFC architecture propagating from the disease epicenter as a determinant of brain atrophy distribution. RESULTS: The disease epicenter was identified in the left midbrain tegmental region. Compared with age-matched control subjects, patients with PSP-RS showed progressively widespread decreased SFC of the midbrain with striatal and cerebellar regions through direct connections and sensorimotor cortical regions through indirect connections. A correlation was found between average link-step distance from the left midbrain in healthy subjects and brain volumes in patients with PSP-RS (r = 0.38, P < 0.001). CONCLUSIONS: This study provides comprehensive insights into the topology of functional network rearrangements in PSP-RS and demonstrates that the brain architectural topology, as described by SFC propagating from the disease epicenter, shapes the pattern of atrophic changes in PSP-RS. Our findings support the view of a network-based pathology propagation in this primary tauopathy. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Analysis of individual alpha frequency in a large cohort from a tertiary memory center.

BACKGROUND AND PURPOSE: Precise and timely diagnosis is crucial for the optimal use of emerging disease-modifying treatments for Alzheimer disease (AD). Electroencephalography (EEG), which is noninvasive and cost-effective, can capture neural abnormalities linked to various dementias. This study explores the use of individual alpha frequency (IAF) derived from EEG as a diagnostic and prognostic tool in cognitively impaired patients. METHODS: This retrospective study included 375 patients from the tertiary Memory Clinic of IRCCS San Raffaele Hospital, Milan, Italy. Participants underwent clinical and neuropsychological assessments, brain imaging, cerebrospinal fluid biomarker analysis, and resting-state EEG. Patients were categorized by amyloid status, the AT(N) classification system, clinical diagnosis, and mild cognitive impairment (MCI) progression to AD dementia. IAF was calculated and compared among study groups. Receiver operating characteristic (ROC) analysis was used to calculate its discriminative performance. RESULTS: IAF was higher in amyloid-negative subjects and varied significantly across AT(N) groups. ROC analysis confirmed IAF's ability to distinguish A-T-N- from the A+T+N+ and A+T-N+ groups. IAF was lower in AD and Lewy body dementia patients compared to MCI and other dementia types, with moderate discriminatory capability. Among A+ MCI patients, IAF was significantly lower in those who converted to AD within 2 years compared to stable MCI patients and predicted time to conversion (p < 0.001, R = 0.38). CONCLUSIONS: IAF is a valuable tool for dementia diagnosis and prognosis, correlating with amyloid status and neurodegeneration. It effectively predicts MCI progression to AD, supporting its use in early, targeted interventions in the context of disease-modifying treatments.

Resting state functional brain networks associated with emotion processing in frontotemporal lobar degeneration.

This study investigated the relationship between emotion processing and resting-state functional connectivity (rs-FC) of the brain networks in frontotemporal lobar degeneration (FTLD). Eighty FTLD patients (including cases with behavioral variant of frontotemporal dementia, primary progressive aphasia, progressive supranuclear palsy syndrome, motor neuron disease) and 65 healthy controls underwent rs-functional MRI. Emotion processing was tested using the Comprehensive Affect Testing System (CATS). In patients and controls, correlations were investigated between each emotion construct and rs-FC changes within critical networks. Mean rs-FC of the clusters significantly associated with CATS scoring were compared among FTLD groups. FTLD patients had pathological CATS scores compared with controls. In controls, increased rs-FC of the cerebellar and visuo-associative networks correlated with better scores in emotion-matching and discrimination tasks, respectively; while decreased rs-FC of the visuo-spatial network was related with better performance in the affect-matching and naming. In FTLD, the associations between rs-FC and CATS scores involved more brain regions, such as orbitofrontal and middle frontal gyri within anterior networks (i.e., salience and default-mode), parietal and somatosensory regions within visuo-spatial and sensorimotor networks, caudate and thalamus within basal-ganglia network. Rs-FC changes associated with CATS were similar among all FTLD groups. In FTLD compared to controls, the pattern of rs-FC associated with emotional processing involves a larger number of brain regions, likely due to functional specificity loss and compensatory attempts. These associations were similar across all FTLD groups, suggesting a common physiopathological mechanism of emotion processing breakdown, regardless the clinical presentation and pattern of atrophy.

Combining semi-quantitative rating and automated brain volumetry in MRI evaluation of patients with probable behavioural variant of fronto-temporal dementia: an added value for clinical practise?

PURPOSE: To evaluate the diagnostic value of combined semiquantitative and quantitative assessment of brain atrophy in the diagnostic workup of the behavioural-variant of frontotemporal dementia (bvFTD). METHODS: Three neuroradiologists defined brain atrophy grading and identified atrophy pattern suggestive of bvFTD on 3D-T1 brain MRI of 112 subjects using a semiquantitative rating scale (Kipps'). A quantitative atrophy assessment was performed using two different automated software (Quantib® ND and Icometrix®). A combined semiquantitative and quantitative assessment of brain atrophy was made to evaluate the improvement in brain atrophy grading to identify probable bvFTD patients. RESULTS: Observers' performances in the diagnosis of bvFTD were very good for Observer 1 (k value = 0.881) and 2 (k value = 0.867), substantial for Observer 3 (k value = 0.741). Semiquantitative atrophy grading of all the observers showed a moderate and a poor correlation with the volume values calculated by Icometrix® and by Quantib® ND, respectively. For the definition of neuroradiological signs presumptive of bvFTD, the use of Icometrix® software improved the diagnostic accuracy for Observer 1 resulting in an AUC of 0.974, and for Observer 3 resulting in a AUC of 0.971 (p-value < 0.001). The use of Quantib® ND software improved the diagnostic accuracy for Observer 1 resulting in an AUC of 0.974, and for Observer 3 resulting in a AUC of 0.977 (p-value < 0.001). No improvement was observed for Observer 2. CONCLUSION: Combining semiquantitative and quantitative brain imaging evaluation allows to reduce discrepancies in the neuroradiological diagnostic workup of bvFTD by different readers.

CSF-based liquid biopsy pointing to a diagnosis of diffuse glioma in a patient with supposed neurodegenerative disorder.

INTRODUCTION: The differential diagnosis of brain diseases becomes challenging in cases where imaging is not sufficiently informative, and surgical biopsy is impossible or unacceptable to the patient. METHODS: An elderly patient with progressive short-term memory loss and cognitive impairment presented with a normal brain CT scan, a brain FDG-PET that indicated symmetrical deterioration of the white matter in the frontal lobes, and inconclusive results of a molecular marker analysis of suspected dementia in cerebrospinal fluid (CSF). Brain MRI suggested the diagnosis of lower grade glioma. The patient refused surgical biopsy. In order to investigate whether somatic mutations associated with gliomas existed, we performed a "liquid biopsy" by the targeted sequencing of cell-free DNA (cfDNA) from his CSF. RESULTS: Deep sequencing of the cfDNA from CSF revealed somatic mutations characteristically found in gliomas, including mutations of the TP53 (Arg282Trp), BRAF (Val600Glu), and IDH1 (Arg132His) genes. The patient is currently treated with temozolomide, and his clinical and MRI findings suggest the stabilization of his disease. CONCLUSION: Neurological patients may benefit from liquid biopsy diagnostic work-up as it can reveal therapeutically targetable mutations.

Lifelong bilingualism and mechanisms of neuroprotection in Alzheimer dementia.

Lifelong bilingualism is associated with delayed dementia onset, suggesting a protective effect on the brain. Here, we aim to study the effects of lifelong bilingualism as a dichotomous and continuous phenomenon, on brain metabolism and connectivity in individuals with Alzheimer's dementia. Ninety-eight patients with Alzheimer's dementia (56 monolinguals; 42 bilinguals) from three centers entered the study. All underwent an [18F]-fluorodeoxyglucose positron emission tomography (PET) imaging session. A language background questionnaire measured the level of language use for conversation and reading. Severity of brain hypometabolism and strength of connectivity of the major neurocognitive networks was compared across monolingual and bilingual individuals, and tested against the frequency of second language life-long usage. Age, years of education, and MMSE score were included in all above mentioned analyses as nuisance covariates. Cerebral hypometabolism was more severe in bilingual compared to monolingual patients; severity of hypometabolism positively correlated with the degree of second language use. The metabolic connectivity analyses showed increased connectivity in the executive, language, and anterior default mode networks in bilingual compared to monolingual patients. The change in neuronal connectivity was stronger in subjects with higher second language use. All effects were most pronounced in the left cerebral hemisphere. The neuroprotective effects of lifelong bilingualism act both against neurodegenerative processes and through the modulation of brain networks connectivity. These findings highlight the relevance of lifelong bilingualism in brain reserve and compensation, supporting bilingual education and social interventions aimed at usage, and maintenance of two or more languages, including dialects, especially crucial in the elderly people.

Integrated evaluation of a panel of neurochemical biomarkers to optimize diagnosis and prognosis in amyotrophic lateral sclerosis.

BACKGROUND AND PURPOSE: This study was undertaken to determine the diagnostic and prognostic value of a panel of serum biomarkers and to correlate their concentrations with several clinical parameters in a large cohort of patients with amyotrophic lateral sclerosis (ALS). METHODS: One hundred forty-three consecutive patients with ALS and a control cohort consisting of 70 patients with other neurodegenerative disorders (DEG), 70 patients with ALS mimic disorders (ALSmd), and 45 healthy controls (HC) were included. Serum neurofilament light chain (NfL), ubiquitin carboxyl-terminal hydrolase isozyme L1 (UCHL1), glial fibrillary acidic protein (GFAP), and total tau protein levels were measured using ultrasensitive single molecule array. RESULTS: NfL correlated with disease progression rate (p < 0.001) and with the measures of upper motor neuron burden (p < 0.001). NfL was higher in the ALS patients with classic and pyramidal phenotype. GFAP was raised in ALS with cognitive-behavioral impairment compared with ALS with normal cognition. NfL displayed the best diagnostic performance in discriminating ALS from HC (area under the curve [AUC] = 0.990), DEG (AUC = 0.946), and ALSmd (AUC = 0.850). UCHL1 performed well in distinguishing ALS from HC (AUC = 0.761), whereas it was not helpful in differentiating ALS from DEG and ALSmd. In multivariate analysis, NfL (p < 0.001) and UCHL1 (p = 0.038) were independent prognostic factors. Survival analysis combining NfL and UCHL1 effectively stratified patients with lower NfL levels (p < 0.001). CONCLUSIONS: NfL is a useful biomarker for the diagnosis of ALS and the strongest predictor of survival. UCHL1 is an independent prognostic factor helpful in stratifying survival in patients with low NfL levels, likely to have slowly progressive disease. GFAP reflects extramotor involvement, namely cognitive impairment or frontotemporal dementia.

Changes in functional and structural brain connectome along the Alzheimer's disease continuum.

The aim of this study was two-fold: (i) to investigate structural and functional brain network architecture in patients with Alzheimer's disease (AD) and amnestic mild cognitive impairment (aMCI), stratified in converters (c-aMCI) and non-converters (nc-aMCI) to AD; and to assess the relationship between healthy brain network functional connectivity and the topography of brain atrophy in patients along the AD continuum. Ninety-four AD patients, 47 aMCI patients (25 c-aMCI within 36 months) and 53 age- and sex-matched healthy controls were studied. Graph analysis and connectomics assessed global and local, structural and functional topological network properties and regional connectivity. Healthy topological features of brain regions were assessed based on their connectivity with the point of maximal atrophy (epicenter) in AD and aMCI patients. Brain network graph analysis properties were severely altered in AD patients. Structural brain network was already altered in c-aMCI patients relative to healthy controls in particular in the temporal and parietal brain regions, while functional connectivity did not change. Structural connectivity alterations distinguished c-aMCI from nc-aMCI cases. In both AD and c-aMCI, the point of maximal atrophy was located in left hippocampus (disease-epicenter). Brain regions most strongly connected with the disease-epicenter in the healthy functional connectome were also the most atrophic in both AD and c-aMCI patients. Progressive degeneration in the AD continuum is associated with an early breakdown of anatomical brain connections and follows the strongest connections with the disease-epicenter. These findings support the hypothesis that the topography of brain connectional architecture can modulate the spread of AD through the brain.

Biomarker-based stability in limbic-predominant amnestic mild cognitive impairment.

BACKGROUND: The amnestic presentation of mild cognitive impairment (aMCI) represents the most common prodromal stage of Alzheimer's disease (AD) dementia. There is, however, some evidence of aMCI with typical amnestic syndrome but showing long-term clinical stability. The ability to predict stability or progression to dementia in the aMCI condition is important, particularly for the selection of candidates in clinical trials. We aimed to establish the role of in vivo biomarkers, as assessed by cerebrospinal fluid (CSF) measures and [18 F]fluorodeoxyglucose (FDG)-positron emission tomography (PET) imaging, in predicting prognosis in a large aMCI cohort. METHODS: We conducted a retrospective study, including 142 aMCI subjects who had a long follow-up (4-19 years), baseline CSF data and [18 F]FDG-PET scans individually assessed by validated voxel-based procedures, classifying subjects into either limbic-predominant or AD-like hypometabolism patterns. RESULTS: The two aMCI cohorts were clinically comparable at baseline. At follow-up, the aMCI group with a limbic-predominant [18 F]FDG-PET pattern showed clinical stability over a very long follow-up (8.20 ± 3.30 years), no decline in Mini-Mental State Examination score, and only 7% conversion to dementia. Conversely, the aMCI group with an AD-like [18 F]FDG-PET pattern had a high rate of dementia progression (86%) over a shorter follow-up (6.47 ± 2.07 years). Individual [18 F]FDG-PET hypometabolism patterns predicted stability or conversion with high accuracy (area under the curve = 0.89), sensitivity (0.90) and specificity (0.89). In the limbic-predominant aMCI cohort, CSF biomarkers showed large variability and no prognostic value. CONCLUSIONS: In a large series of clinically comparable subjects with aMCI at baseline, the specific [18 F]FDG-PET limbic-predominant hypometabolism pattern was associated with clinical stability, making progression to AD very unlikely. The identification of a biomarker-based benign course in aMCI subjects has important implications for prognosis and in planning clinical trials.

Plasma neurofilament light chain levels and cognitive testing as predictors of fast progression in Alzheimer's disease.

BACKGROUND: Alzheimer's disease (AD) is characterized by a heterogeneous course. Predicting a fast rather than a slow decline over time is crucial to both provide a reliable prognosis and elaborate stricter enrolment criteria in clinical trials. Here we searched for independent predictors of cognitive decline rate to assess the risk of fast disease progression already at baseline. METHODS: Fifty-three subjects with an "in-vivo biomarker confirmed" diagnosis of AD were included. Neuropsychological assessment, plasma neurofilaments (NfL) concentrations and, in a subsample of 23 patients, brain magnetic resonance imaging were available. Patients were labelled FAST or SLOW depending on the Mini-Mental State Examination (MMSE) points lost per year (FAST if more than 3 points). We adopted single logistic regression models to search for independent predictors of FAST progression. RESULTS: At baseline no differences were found between FAST and SLOW subgroups in demographics, MMSE scores, vascular burden and medial temporal lobe atrophy measurements. Higher plasma NfL concentrations and worse scores at semantic verbal fluency (SVF) and clock drawing test (CDT) were independent predictors of FAST decline, after controlling for age, education, sex and baseline disease severity stage. The regression model combining all the predictors correctly classified 80% of patients overall. The risk of FAST decline was 81.2% if all the three predictors were abnormal (i.e., SVF ≤21.5, CDT ≤5.5, NfL ≥22.19). CONCLUSIONS: An easily applicable algorithm, including plasma NfL measurement and two neuropsychological tests worldwide adopted in clinical practice (SVF and CDT), may allow clinicians to reliably stratify AD patients in relation to the risk of fast cognitive decline.

Brain metabolic signatures across the Alzheimer's disease spectrum.

PURPOSE: Given the challenges posed by the clinical diagnosis of atypical Alzheimer's disease (AD) variants and the limited imaging evidence available in the prodromal phases of atypical AD, we assessed brain hypometabolism patterns at the single-subject level in the AD variants spectrum. Specifically, we tested the accuracy of [18F]FDG-PET brain hypometabolism, as a biomarker of neurodegeneration, in supporting the differential diagnosis of atypical AD variants in individuals with dementia and mild cognitive impairment (MCI). METHODS: We retrospectively collected N = 67 patients with a diagnosis of typical AD and AD variants according to the IWG-2 criteria (22 typical-AD, 15 frontal variant-AD, 14 logopenic variant-AD and 16 posterior variant-AD). Further, we included N = 11 MCI subjects, who subsequently received a clinical diagnosis of atypical AD dementia at follow-up (21 ± 11 months). We assessed brain hypometabolism patterns at group- and single-subject level, using W-score maps, measuring their accuracy in supporting differential diagnosis. In addition, the regional prevalence of cerebral hypometabolism was computed to identify the most vulnerable core regions. RESULTS: W-score maps pointed at distinct, specific patterns of hypometabolism in typical and atypical AD variants, confirmed by the assessment of core hypometabolism regions, showing that each variant was characterized by specific regional vulnerabilities, namely in occipital, left-sided, or frontal brain regions. ROC curves allowed discrimination among AD variants and also non-AD dementia (i.e., dementia with Lewy bodies and behavioral variant of frontotemporal dementia), with high sensitivity and specificity. Notably, we provide preliminary evidence that, even in AD prodromal phases, these specific [18F]FDG-PET patterns are already detectable and predictive of clinical progression to atypical AD variants at follow-up. CONCLUSIONS: The AD variant-specific patterns of brain hypometabolism, highly consistent at single-subject level and already evident in the prodromal stages, represent relevant markers of disease neurodegeneration, with highly supportive diagnostic and prognostic role.

CSF p-tau/Aß42 ratio and brain FDG-PET may reliably detect MCI "imminent" converters to AD.

PURPOSE: To know whether mild cognitive impairment (MCI) patients will develop Alzheimer's disease (AD) dementia in very short time or remain stable is of crucial importance, also considering new experimental drugs usually tested within very short time frames. Here we combined cerebrospinal fluid (CSF) AD biomarkers and a neurodegeneration marker such as brain FDG-PET to define an objective algorithm, suitable not only to reliably detect MCI converters to AD dementia but also to predict timing of conversion. METHODS: We included 77 consecutive MCI patients with neurological/neuropsychological assessment, brain 18F-FDG-PET and CSF analysis available at diagnosis and a neuropsychological/neurological evaluation every 6 months for a medium- to a long-term follow-up (at least 2 and up to 8 years). Binomial logistic regression models and Kaplan-Meier survival analyses were performed to determine the best biomarker (or combination of biomarkers) in detecting MCI converters to AD dementia and then, among the converters, those who converted in short time frames. RESULTS: Thirty-five out of 77 MCI patients (45%) converted to AD dementia, with an average conversion time since MCI diagnosis of 26.07 months. CSF p-tau/Aß42 was the most accurate predictor of conversion from MCI to AD dementia (82.9% sensitivity; 90% specificity). CSF p-tau/Aß42 and FDG-PET-positive MCIs converted to AD dementia significantly earlier than the CSF-positive-only MCIs (median conversion time, 17.1 vs 31.3 months). CONCLUSIONS: CSF p-tau/Aß42 ratio and brain FDG-PET may predict both occurrence and timing of MCI conversion to full-blown AD dementia. MCI patients with both biomarkers suggestive for AD will likely develop an AD dementia shortly, thus representing the ideal target for any new experimental drug requiring short periods to be tested for.

The impact of bilingualism on brain reserve and metabolic connectivity in Alzheimer's dementia.

Cognitive reserve (CR) prevents cognitive decline and delays neurodegeneration. Recent epidemiological evidence suggests that lifelong bilingualism may act as CR delaying the onset of dementia by ∼4.5 y. Much controversy surrounds the issue of bilingualism and its putative neuroprotective effects. We studied brain metabolism, a direct index of synaptic function and density, and neural connectivity to shed light on the effects of bilingualism in vivo in Alzheimer's dementia (AD). Eighty-five patients with probable AD and matched for disease duration (45 German-Italian bilingual speakers and 40 monolingual speakers) were included. Notably, bilingual individuals were on average 5 y older than their monolingual peers. In agreement with our predictions and with models of CR, cerebral hypometabolism was more severe in the group of bilingual individuals with AD. The metabolic connectivity analyses crucially supported the neuroprotective effect of bilingualism by showing an increased connectivity in the executive control and the default mode networks in the bilingual, compared with the monolingual, AD patients. Furthermore, the degree of lifelong bilingualism (i.e., high, moderate, or low use) was significantly correlated to functional modulations in crucial neural networks, suggesting both neural reserve and compensatory mechanisms. These findings indicate that lifelong bilingualism acts as a powerful CR proxy in dementia and exerts neuroprotective effects against neurodegeneration. Delaying the onset of dementia is a top priority of modern societies, and the present in vivo neurobiological evidence should stimulate social programs and interventions to support bilingual or multilingual education and the maintenance of the second language among senior citizens.

Vulnerability of multiple large-scale brain networks in dementia with Lewy bodies.

Aberrations of large-scale brain networks are found in the majority of neurodegenerative disorders. The brain connectivity alterations underlying dementia with Lewy bodies (DLB) remain, however, still elusive, with contrasting results possibly due to the pathological and clinical heterogeneity characterizing this disorder. Here, we provide a molecular assessment of brain network alterations, based on cerebral metabolic measurements as proxies of synaptic activity and density, in a large cohort of DLB patients (N = 72). We applied a seed-based interregional correlation analysis approach (p < .01, false discovery rate corrected) to evaluate large-scale resting-state networks' integrity and their interactions. We found both local and long-distance metabolic connectivity alterations, affecting the posterior cortical networks, that is, primary visual and the posterior default mode network, as well as the limbic and attention networks, suggesting a widespread derangement of the brain connectome. Notably, patients with the lowest visual and attention cognitive scores showed the most severe connectivity derangement in regions of the primary visual network. In addition, network-level alterations were differentially associated with the core clinical manifestations, namely, hallucinations with more severe metabolic dysfunction of the attention and visual networks, and rapid eye movement sleep behavior disorder with alterations of connectivity of attention and subcortical networks. These multiple network-level vulnerabilities may modulate the core clinical and cognitive features of DLB and suggest that DLB should be considered as a complex multinetwork disorder.

Prevalence of amyloid-ß pathology in distinct variants of primary progressive aphasia.

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-ß 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) ε4 status was determined using generalized estimating equation models. RESULTS: Amyloid-ß positivity was more prevalent in lvPPA (86%) than in nfvPPA (20%) or svPPA (16%; p < 0.001). Prevalence of amyloid-ß 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 ε4 carriers were more often amyloid-ß 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-ß biomarkers in PPA patients. Ann Neurol 2018;84:737-748.

Heterogeneous brain FDG-PET metabolic patterns in patients with C9orf72 mutation.

OBJECTIVE: The hexanucleotide repeat expansion in C9orf72 is an associated genetic cause in amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). In the "ALS/FTD" spectrum prevails clinical heterogeneity and an in vivo knowledge of the underling brain dysfunction in patients carrying C9orf72 mutation remain limited and only described at group level. The study aimed to assess the brain metabolic alterations characterizing patients with C9orf72 mutation using FDG-PET in single individuals. METHODS: We applied a validated statistical parametric mapping (SPM) voxel-based procedure for FDG-PET data to obtain maps of brain relative hypometabolism and hypermetabolism at single-subject level in six FTD/ALS patients carrying the C9orf72 mutation. RESULTS: Clinical diagnoses classified the patients as right semantic variant of frontotemporal dementia (one case, C9svFTD), behavioral variant of frontotemporal dementia (two cases, C9bvFTD), and bulbar amyotrophic lateral sclerosis (three cases, C9bALS). The FDG-PET SPM revealed a prevalent frontal hypometabolism in C9bvFTD cases, and right temporal polar and lateral involvement in C9svFTD, consistent with the clinical diagnosis. There was a quite comparable occipital and cerebellar hypermetabolism in these cases. The three C9bALS patients showed variable patterns of hypo- and hypermetabolism. CONCLUSIONS: The present work is the first in vivo FDG-PET study showing the heterogeneous patterns of brain regional hypo- and hypermetabolism in single patients sharing C9orf72 mutation. Brain hypometabolism was consistent with the clinical phenotypes, supporting the diagnostic importance of neuroimaging functional biomarkers to capture at single-subject level specific brain dysfunction.

Primary progressive multiple sclerosis presenting with severe predominant cognitive impairment and psychiatric symptoms: A challenging case.

Severe cognitive dysfunction is a frequent feature of multiple sclerosis (MS), normally associated with later stages of the disease in adult population. Nevertheless, progressive cognitive and neuropsychiatric disturbances might rarely be the presenting and predominant symptom. In order to better characterize this peculiar phenotype of MS, we report on the case of a 38-year-old man who referred to our hospital with the suspect of hereditary leukodystrophy after 5 years of behavioral and mood abnormalities, global cognitive dysfunction, clumsiness, and very mild pyramidal and cerebellar signs. Brain and spinal magnetic resonance imaging (MRI) combined with cerebrospinal fluid (CSF) analysis prompted the diagnosis of MS.

Neuropsychiatric subsyndromes and brain metabolic network dysfunctions in early onset Alzheimer's disease.

Neuropsychiatric symptoms (NPSs) often occur in early-age-of-onset Alzheimer's disease (EOAD) and cluster into sub-syndromes (SSy). The aim of this study was to investigate the association between 18 F-FDG-PET regional and connectivity-based brain metabolic dysfunctions and neuropsychiatric SSy. NPSs were assessed in 27 EOAD using the Neuropsychiatric Inventory and further clustered into four SSy (apathetic, hyperactivity, affective, and psychotic SSy). Eighty-five percent of EOAD showed at least one NPS. Voxel-wise correlations between SSy scores and brain glucose metabolism (assessed with 18 F-FDG positron emission tomography) were studied. Interregional correlation analysis was used to explore metabolic connectivity in the salience (aSN) and default mode networks (DMN) in a larger sample of EOAD (N = 51) and Healthy Controls (N = 57). The apathetic, hyperactivity, and affective SSy were highly prevalent (>60%) as compared to the psychotic SSy (33%). The hyperactivity SSy scores were associated with increase of glucose metabolism in frontal and limbic structures, implicated in behavioral control. A comparable positive correlation with part of the same network was found for the affective SSy scores. On the other hand, the apathetic SSy scores were negatively correlated with metabolism in the bilateral orbitofrontal and dorsolateral frontal cortex known to be involved in motivation and decision-making processes. Consistent with these SSy regional correlations with brain metabolic dysfunction, the connectivity analysis showed increases in the aSN and decreases in the DMN. Behavioral abnormalities in EOAD are associated with specific dysfunctional changes in brain metabolic activity, in particular in the aSN that seems to play a crucial role in NPSs in EOAD. Hum Brain Mapp 37:4234-4247, 2016. © 2016 Wiley Periodicals, Inc.

Cross-validation of biomarkers for the early differential diagnosis and prognosis of dementia in a clinical setting.

PURPOSE: The aim of this study was to evaluate the supportive role of molecular and structural biomarkers (CSF protein levels, FDG PET and MRI) in the early differential diagnosis of dementia in a large sample of patients with neurodegenerative dementia, and in determining the risk of disease progression in subjects with mild cognitive impairment (MCI). METHODS: We evaluated the supportive role of CSF Aß42, t-Tau, p-Tau levels, conventional brain MRI and visual assessment of FDG PET SPM t-maps in the early diagnosis of dementia and the evaluation of MCI progression. RESULTS: Diagnosis based on molecular biomarkers showed the best fit with the final diagnosis at a long follow-up. FDG PET SPM t-maps had the highest diagnostic accuracy in Alzheimer's disease and in the differential diagnosis of non-Alzheimer's disease dementias. The p-tau/Aß42 ratio was the only CSF biomarker providing a significant classification rate for Alzheimer's disease. An Alzheimer's disease-positive metabolic pattern as shown by FDG PET SPM in MCI was the best predictor of conversion to Alzheimer's disease. CONCLUSION: In this clinical setting, FDG PET SPM t-maps and the p-tau/Aß42 ratio improved clinical diagnostic accuracy, supporting the importance of these biomarkers in the emerging diagnostic criteria for Alzheimer's disease dementia. FDG PET using SPM t-maps had the highest predictive value by identifying hypometabolic patterns in different neurodegenerative dementias and normal brain metabolism in MCI, confirming its additional crucial exclusionary role.