Frontotemporal dementia is a highly heritable neurodegenerative disorder. In about a third of patients, the disease is caused by autosomal dominant genetic mutations usually in one of three genes: progranulin (GRN), microtubule-associated protein tau (MAPT), or chromosome 9 open reading frame 72 (C9orf72). Findings from studies of other genetic dementias have shown neuroimaging and cognitive changes before symptoms onset, and we aimed to identify whether such changes could be shown in frontotemporal dementia. We recruited participants to this multicentre study who either were known carriers of a pathogenic mutation in GRN, MAPT, or C9orf72, or were at risk of carrying a mutation because a first-degree relative was a known symptomatic carrier. We calculated time to expected onset as the difference between age at assessment and mean age at onset within the family. Participants underwent a standardised clinical assessment and neuropsychological battery. We did MRI and generated cortical and subcortical volumes using a parcellation of the volumetric T1-weighted scan. We used linear mixed-effects models to examine whether the association of neuropsychology and imaging measures with time to expected onset of symptoms differed between mutation carriers and non-carriers. Between Jan 30, 2012, and Sept 15, 2013, we recruited participants from 11 research sites in the UK, Italy, the Netherlands, Sweden, and Canada. We analysed data from 220 participants: 118 mutation carriers (40 symptomatic and 78 asymptomatic) and 102 non-carriers. For neuropsychology measures, we noted the earliest significant differences between mutation carriers and non-carriers 5 years before expected onset, when differences were significant for all measures except for tests of immediate recall and verbal fluency. We noted the largest Z score differences between carriers and non-carriers 5 years before expected onset in tests of naming (Boston Naming Test -0·7; SE 0·3) and executive function (Trail Making Test Part B, Digit Span backwards, and Digit Symbol Task, all -0·5, SE 0·2). For imaging measures, we noted differences earliest for the insula (at 10 years before expected symptom onset, mean volume as a percentage of total intracranial volume was 0·80% in mutation carriers and 0·84% in non-carriers; difference -0·04, SE 0·02) followed by the temporal lobe (at 10 years before expected symptom onset, mean volume as a percentage of total intracranial volume 8·1% in mutation carriers and 8·3% in non-carriers; difference -0·2, SE 0·1). Structural imaging and cognitive changes can be identified 5-10 years before expected onset of symptoms in asymptomatic adults at risk of genetic frontotemporal dementia. These findings could help to define biomarkers that can stage presymptomatic disease and track disease progression, which will be important for future therapeutic trials. Centres of Excellence in Neurodegeneration.

Frontotemporal dementia is a heterogenous neurodegenerative disorder, with about a third of cases being genetic. Most of this genetic component is accounted for by mutations in GRN, MAPT, and C9orf72. In this study, we aimed to complement previous phenotypic studies by doing an international study of age at symptom onset, age at death, and disease duration in individuals with mutations in GRN, MAPT, and C9orf72. In this international, retrospective cohort study, we collected data on age at symptom onset, age at death, and disease duration for patients with pathogenic mutations in the GRN and MAPT genes and pathological expansions in the C9orf72 gene through the Frontotemporal Dementia Prevention Initiative and from published papers. We used mixed effects models to explore differences in age at onset, age at death, and disease duration between genetic groups and individual mutations. We also assessed correlations between the age at onset and at death of each individual and the age at onset and at death of their parents and the mean age at onset and at death of their family members. Lastly, we used mixed effects models to investigate the extent to which variability in age at onset and at death could be accounted for by family membership and the specific mutation carried. Data were available from 3403 individuals from 1492 families: 1433 with C9orf72 expansions (755 families), 1179 with GRN mutations (483 families, 130 different mutations), and 791 with MAPT mutations (254 families, 67 different mutations). Mean age at symptom onset and at death was 49·5 years (SD 10·0; onset) and 58·5 years (11·3; death) in the MAPT group, 58·2 years (9·8; onset) and 65·3 years (10·9; death) in the C9orf72 group, and 61·3 years (8·8; onset) and 68·8 years (9·7; death) in the GRN group. Mean disease duration was 6·4 years (SD 4·9) in the C9orf72 group, 7·1 years (3·9) in the GRN group, and 9·3 years (6·4) in the MAPT group. Individual age at onset and at death was significantly correlated with both parental age at onset and at death and with mean family age at onset and at death in all three groups, with a stronger correlation observed in the MAPT group (r=0·45 between individual and parental age at onset, r=0·63 between individual and mean family age at onset, r=0·58 between individual and parental age at death, and r=0·69 between individual and mean family age at death) than in either the C9orf72 group (r=0·32 individual and parental age at onset, r=0·36 individual and mean family age at onset, r=0·38 individual and parental age at death, and r=0·40 individual and mean family age at death) or the GRN group (r=0·22 individual and parental age at onset, r=0·18 individual and mean family age at onset, r=0·22 individual and parental age at death, and r=0·32 individual and mean family age at death). Modelling showed that the variability in age at onset and at death in the MAPT group was explained partly by the specific mutation (48%, 95% CI 35-62, for age at onset; 61%, 47-73, for age at death), and even more by family membership (66%, 56-75, for age at onset; 74%, 65-82, for age at death). In the GRN group, only 2% (0-10) of the variability of age at onset and 9% (3-21) of that of age of death was explained by the specific mutation, whereas 14% (9-22) of the variability of age at onset and 20% (12-30) of that of age at death was explained by family membership. In the C9orf72 group, family membership explained 17% (11-26) of the variability of age at onset and 19% (12-29) of that of age at death. Our study showed that age at symptom onset and at death of people with genetic frontotemporal dementia is influenced by genetic group and, particularly for MAPT mutations, by the specific mutation carried and by family membership. Although estimation of age at onset will be an important factor in future pre-symptomatic therapeutic trials for all three genetic groups, our study suggests that data from other members of the family will be particularly helpful only for individuals with MAPT mutations. Further work in identifying both genetic and environmental factors that modify phenotype in all groups will be important to improve such estimates. UK Medical Research Council, National Institute for Health Research, and Alzheimer's Society.

Several micro(mi)RNA are deregulated in brain, cerebrospinal fluid (CSF), and serum/plasma from patients with Alzheimer's disease (AD). The aim of the study was to profile circulating miRNAs in serum as non-invasive biomarkers for AD, correlating them with those identified in CSF, the biological fluid which better reflects biochemical changes occurring during pathological processes in the brain and may provide a robust indicator of AD-related disease pathogenesis thanks to the evidence of low amyloid and high levels of tau and hyperphosphorylated tau. Using a two-step analysis (array and validation through real-time PCR), a down-regulation (mean fold change ± SEM) of miR-125b (0.415 ± 0.11 versus 1.381 ± 0.36, p = 0.009), miR-23a (0.111 ± 0.03 versus 0.732 ± 0.14, p < 0.001), and miR-26b (0.414 ± 0.11 versus 1.353 ± 0.39, p < 0.01), out of 84 tested, was shown in serum from 22 AD patients compared with 18 non-inflammatory and 8 inflammatory neurological controls (NINDCs and INDCs) and 10 patients with frontotemporal dementia. Significant down-regulation of miR-125b and miR-26b was also confirmed in CSF from AD patients versus NINDCs (miR-125b: 0.089 ± 0.03 versus 0.230 ± 0.08, p < 0.001; miR-26b: 0.217 ± 0.06 versus 1.255 ± 0.29, p < 0.001, mean fold change ± SEM, respectively), whereas data were not replicated for miR-23a. In serum, miR-125b had an AUC of 0.82 to distinguish AD from NINDCs (95% CI: 0.65–0.98, p = 0.005). In conclusion, we demonstrated that cell-free miR-125b serum levels are decreased in serum from patients with AD as compared with NINDC and distinguish between AD and NINDCs with an accuracy of 82%.

Alzheimer’s disease (AD) is the most common cause of neurodegenerative dementia, whilst Parkinson’s disease (PD) is a neurodegenerative movement disorder. These two neurodegenerative disorders share the accumulation of toxic proteins as a pathological hallmark. The lack of definitive disease-modifying treatments for these neurogenerative diseases has led to the hypothesis of new pathogenic mechanisms to target and design new potential therapeutic approaches. The recent observation that the glymphatic system is supposed to be responsible for the movement of cerebrospinal fluid into the brain and clearance of metabolic waste has led to study its involvement in the pathogenesis of these classic proteinopathies. Aquaporin-4 (AQP4), a water channel located in the endfeet of astrocyte membrane, is considered a primary driver of the glymphatic clearance system, and defective AQP4-mediated glymphatic drainage has been linked to proteinopathies. The objective of the present review is to present the recent body of knowledge that links the glymphatic system to the pathogenesis of AD and PD disease and other lifestyle factors such as sleep deprivation and exercise that may influence glymphatic system function. We will also focus on the potential neuroimaging approaches that could identify a neuroimaging marker to detect glymphatic system changes.

Background and Objectives The goal of this work was to investigate the natural history and outcomes after treatment for spontaneous amyloid-related imaging abnormalities (ARIA)-like in cerebral amyloid angiopathy–related inflammation (CAA-ri). Methods This was a multicenter, hospital-based, longitudinal, prospective observational study of inpatients meeting CAA-ri diagnostic criteria recruited through the Inflammatory Cerebral Amyloid Angiopathy and Alzheimer9s Disease βiomarkers International Network from January 2013 to March 2017. A protocol for systematic data collection at first-ever presentation and at subsequent in-person visits, including T1-weighted, gradient recalled echo–T2*, fluid-suppressed T2-weighted (fluid-attenuated inversion recovery), and T1 postgadolinium contrast-enhanced images acquired on 1.5T MRI, was used at the 3-, 6-, 12-, and 24-month follow-up. Centralized reads of MRIs were performed by investigators blinded to clinical, therapeutic, and time-point information. Main outcomes were survival, clinical and radiologic recovery, intracerebral hemorrhage (ICH), and recurrence of CAA-ri. Results The study enrolled 113 participants (10.6% definite, 71.7% probable, and 17.7% possible CAA-ri). Their mean age was 72.9 years; 43.4% were female; 37.1% were APOEε4 carriers; 36.3% had a history of Alzheimer disease; and 33.6% had a history of ICH. A history of ICH and the occurrence of new ICH at follow-up were more common in patients with cortical superficial siderosis at baseline (52.6% vs 14.3%, p < 0.0001 and 19.3% vs 3.6%, p < 0.009, respectively). After the first-ever presentation of CAA-ri, 70.3% (95% confidence interval [CI] 61.6%–78.5%) and 84.1% (95% CI 76.2%–90.6%) clinically recovered within 3 and 12 months, followed by radiologic recovery in 45.1% (95% CI 36.4%–54.8%) and 77.4% (95% CI 67.7%–85.9%), respectively. After clinicoradiologic resolution of the first-ever episode, 38.3% (95% CI 22.9%–59.2%) had at least 1 recurrence within the following 24 months. Recurrence was more likely if IV high-dose corticosteroid pulse therapy was suddenly stopped compared to slow oral tapering off (hazard ratio 4.68, 95% CI 1.57–13.93; p = 0.006). Discussion These results from the largest longitudinal cohort registry of patients with CAA-ri support the transient and potentially relapsing inflammatory nature of the clinical-radiologic acute manifestations of the disease and the effectiveness of slow oral tapering off after IV corticosteroid pulse therapy in preventing recurrences. Our results highlight the importance of differential diagnosis for spontaneous ARIA-like events in β-amyloid–driven diseases, including treatment-related ARIA in patients with Alzheimer disease exposed to immunotherapy drugs.

Small extracellular vesicles (EVs) are able to pass from the central nervous system (CNS) into peripheral blood and contain molecule markers of their parental origin. The aim of our study was to isolate and characterize total and neural-derived small EVs (NDEVs) and their micro RNA (miRNA) cargo in Alzheimer’s disease (AD) patients. Small NDEVs were isolated from plasma in a population consisting of 40 AD patients and 40 healthy subjects (CTRLs) using high throughput Advanced TaqMan miRNA OpenArrays^®, which enables the simultaneous determination of 754 miRNAs. MiR-23a-3p, miR-223-3p, miR-100-3p and miR-190-5p showed a significant dysregulation in small NDEVs from AD patients as compared with controls (1.16 ± 0.49 versus 7.54 ± 2.5, p = 0.026; 9.32 ± 2.27 versus 0.66 ± 0.18, p <0.0001; 0.069 ± 0.01 versus 0.5 ± 0.1, p < 0.0001 and 2.9 ± 1.2 versus 1.93 ± 0.9, p < 0.05, respectively). A further validation analysis confirmed that miR-23a-3p, miR-223-3p and miR-190a-5p levels in small NDEVs from AD patients were significantly upregulated as compared with controls (p = 0.008; p = 0.016; p = 0.003, respectively) whereas miR-100-3p levels were significantly downregulated (p = 0.008). This is the first study that carries out the comparison between total plasma small EV population and NDEVs, demonstrating the presence of a specific AD NDEV miRNA signature.