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We report the generation of a gene-edited human induced pluripotent stem cell (iPSC) line from an Alzheimer’s disease patient-derived iPSC line harbouring the PSEN1 H163R mutation. This line demonstrates pluripotent stem cell morphology, expression of pluripotency markers, and maintains a normal karyotype.

Abstract Triggering receptor expressed on myeloid cells 2 (TREM2) plays a critical role in microglial activation, survival, and apoptosis, as well as in Alzheimer’s disease (AD) pathogenesis. We previously reported the MS4A locus as a key modulator for soluble TREM2 (sTREM2) in cerebrospinal fluid (CSF). To identify additional novel genetic modifiers of sTREM2, we performed the largest genome-wide association study (GWAS) and identified four loci for CSF sTREM2 in 3,350 individuals of European ancestry. Through multi-ethnic fine mapping, we identified two independent missense variants (p.M178V in MS4A4A and p.A112T in MS4A6A) that drive the association in MS4A locus and showed an epistatic effect for sTREM2 levels and AD risk. The novel TREM2 locus on chr 6 contains two rare missense variants (rs75932628 p.R47H, P=7.16×10-19; rs142232675 p.D87N, P=2.71×10-10) associated with sTREM2 and AD risk. The third novel locus in the TGFBR2 and RBMS3 gene region (rs73823326, P=3.86×10-9) included a regulatory variant with a microglia-specific chromatin loop for the promoter of TGFBR2. Using cell-based assays we demonstrate that overexpression and knock-down of TGFBR2, but not RBMS3, leads to significant changes of sTREM2. The last novel locus is located on the APOE region (rs11666329, P=2.52×10-8), but we demonstrated that this signal was independent of APOE genotype. This signal colocalized with cis-eQTL of NECTIN2 in the brain cortex and cis-pQTL of NECTIN2 in CSF. Overexpression of NECTIN2 led to an increase of sTREM2 supporting the genetic findings. To our knowledge, this is the largest study to date aimed at identifying genetic modifiers of CSF sTREM2. This study provided novel insights into the MS4A and TREM2 loci, two well-known AD risk genes, and identified TGFBR2 and NECTIN2 as additional modulators involved in TREM2 biology.

BackgroundFrontotemporal lobar degeneration (FTLD) is a leading cause of dementia in individuals aged

Abstract Introduction Remote smartphone assessments of cognition, speech/language, and motor functioning in frontotemporal dementia (FTD) could enable decentralized clinical trials and improve access to research. We studied the feasibility and acceptability of remote smartphone data collection in FTD research using the ALLFTD Mobile App (ALLFTD‐mApp). Methods A diagnostically mixed sample of 214 participants with FTD or from familial FTD kindreds (asymptomatic: CDR®+NACC‐FTLD = 0 [N = 101]; prodromal: 0.5 [N = 49]; symptomatic ≥1 [N = 51]; not measured [N = 13]) were asked to complete ALLFTD‐mApp tests on their smartphone three times within 12 days. They completed smartphone familiarity and participation experience surveys. Results It was feasible for participants to complete the ALLFTD‐mApp on their own smartphones. Participants reported high smartphone familiarity, completed ∼ 70% of tasks, and considered the time commitment acceptable (98% of respondents). Greater disease severity was associated with poorer performance across several tests. Discussion These findings suggest that the ALLFTD‐mApp study protocol is feasible and acceptable for remote FTD research. HIGHLIGHTS The ALLFTD Mobile App is a smartphone‐based platform for remote, self‐administered data collection. The ALLFTD Mobile App consists of a comprehensive battery of surveys and tests of executive functioning, memory, speech and language, and motor abilities. Remote digital data collection using the ALLFTD Mobile App was feasible in a multicenter research consortium that studies FTD. Data was collected in healthy controls and participants with a range of diagnoses, particularly FTD spectrum disorders. Remote digital data collection was well accepted by participants with a variety of diagnoses.

“Brain-predicted age” quantifies apparent brain age compared to normative neuroimaging trajectories. Advanced brain-predicted age has been well established in symptomatic Alzheimer disease (AD), but is underexplored in preclinical AD. Prior brain-predicted age studies have typically used structural MRI, but resting-state functional connectivity (FC) remains underexplored. Our model predicted age from FC in 391 cognitively normal, amyloid-negative controls (ages 18–89). We applied the trained model to 145 amyloid-negative, 151 preclinical AD, and 156 symptomatic AD participants to test group differences. The model accurately predicted age in the training set. FC-predicted brain age gaps (FC-BAG) were significantly older in symptomatic AD and significantly younger in preclinical AD compared to controls. There was minimal correspondence between networks predictive of age and AD. Elevated FC-BAG may reflect network disruption during symptomatic AD. Reduced FC-BAG in preclinical AD was opposite to the expected direction, and may reflect a biphasic response to preclinical AD pathology or may be driven by inconsistency between age-related vs. AD-related networks. Overall, FC-predicted brain age may be a sensitive AD biomarker.

Abstract Dementia with Lewy bodies (DLB) is a clinically heterogeneous disorder with a substantial burden on healthcare. Despite this, the genetic basis of the disorder is not well defined and its boundaries with other neurodegenerative diseases are unclear. Here, we performed whole exome sequencing of a cohort of 1118 Caucasian DLB patients, and focused on genes causative of monogenic neurodegenerative diseases. We analyzed variants in 60 genes implicated in DLB, Alzheimer’s disease, Parkinson’s disease, frontotemporal dementia, and atypical parkinsonian or dementia disorders, in order to determine their frequency in DLB. We focused on variants that have previously been reported as pathogenic, and also describe variants reported as pathogenic which remain of unknown clinical significance, as well as variants associated with strong risk. Rare missense variants of unknown significance were found in APP, CHCHD2, DCTN1, GRN, MAPT, NOTCH3, SQSTM1, TBK1 and TIA1. Additionally, we identified a pathogenic GRN p.Arg493* mutation, potentially adding to the diversity of phenotypes associated with this mutation. The rarity of previously reported pathogenic mutations in this cohort suggests that the genetic overlap of other neurodegenerative diseases with DLB is not substantial. Since it is now clear that genetics plays a role in DLB, these data suggest that other genetic loci play a role in this disease.

Abstract Introduction Conventional Z‐scores are generated by subtracting the mean and dividing by the standard deviation. More recent methods linearly correct for age, sex, and education, so that these “adjusted” Z‐scores better represent whether an individual's cognitive performance is abnormal. Extreme negative Z‐scores for individuals relative to this normative distribution are considered indicative of cognitive deficiency. Methods In this article, we consider nonlinear shape constrained additive models accounting for age, sex, and education (correcting for nonlinearity). Additional shape constrained additive models account for varying standard deviation of the cognitive scores with age (correcting for heterogeneity of variance). Results Corrected Z‐scores based on nonlinear shape constrained additive models provide improved adjustment for age, sex, and education, as indicated by higher adjusted‐R2. Discussion Nonlinearly corrected Z‐scores with respect to age, sex, and education with age‐varying residual standard deviation allow for improved detection of non‐normative extreme cognitive scores.

Recent large-scale genetic studies have allowed for the first glimpse of the effects of common genetic variability in dementia with Lewy bodies (DLB), identifying risk variants with appreciable effect sizes. However, it is currently well established that a substantial portion of the genetic heritable component of complex traits is not captured by genome-wide significant SNPs. To overcome this issue, we have estimated the proportion of phenotypic variance explained by genetic variability (SNP heritability) in DLB using a method that is unbiased by allele frequency or linkage disequilibrium properties of the underlying variants. This shows that the heritability of DLB is nearly twice as high as previous estimates based on common variants only (31% vs 59.9%). We also determine the amount of phenotypic variance in DLB that can be explained by recent polygenic risk scores from either Parkinson's disease (PD) or Alzheimer's disease (AD), and show that, despite being highly significant, they explain a low amount of variance. Additionally, to identify pleiotropic events that might improve our understanding of the disease, we performed genetic correlation analyses of DLB with over 200 diseases and biomedically relevant traits. Our data shows that DLB has a positive correlation with education phenotypes, which is opposite to what occurs in AD. Overall, our data suggests that novel genetic risk factors for DLB should be identified by larger GWAS and these are likely to be independent from known AD and PD risk variants.

Abstract The first Lewy Body Dementia Association (LBDA) Research Centers of Excellence (RCOE) Investigator’s meeting was held on December 14, 2017, in New Orleans. The program was established to increase patient access to clinical experts on Lewy body dementia (LBD), which includes dementia with Lewy bodies (DLB) and Parkinson’s disease dementia (PDD), and to create a clinical trials-ready network. Four working groups (WG) were created to pursue the LBDA RCOE aims: (1) increase access to high-quality clinical care, (2) increase access to support for people living with LBD and their caregivers, (3) increase knowledge of LBD among medical and allied (or other) professionals, and (4) create infrastructure for a clinical trials-ready network as well as resources to advance the study of new therapeutics.

Background and Purpose: Patients with dementia with Lewy bodies (DLB) are characterized by hypometabolism in the parieto–occipital cortex and the cingulate island sign (CIS) on 18F-fluorodeoxyglucose (FDG) PET. Whether this pattern of hypometabolism is present as early as the prodromal stage of DLB is unknown. We investigated the pattern of hypometabolism in patients with mild cognitive impairment (MCI) who progressed to probable DLB compared to MCI patients who progressed to Alzheimer’s disease (AD) dementia and clinically unimpaired (CU) controls. Methods: Patients with MCI from the Mayo Clinic Alzheimer’s Disease Research Center who underwent FDG PET at baseline and progressed to either probable DLB (MCI-DLB; n = 17) or AD dementia (MCI-AD; n = 41) during follow-up, and a comparison cohort of CU controls (n = 100) were included. Results: Patients with MCI-DLB had hypometabolism in the parieto-occipital cortex extending into temporal lobes, substantia nigra and thalamus. When compared to MCI-AD, medial temporal and posterior cingulate metabolism were preserved in patients with MCI-DLB, accompanied by greater hypometabolism in the substantia nigra in MCI-DLB compared to MCI-AD. In distinguishing MCI-DLB from MCI-AD at the maximum value of Youden’s index, CIS ratio was highly specific (90%) but not sensitive (59%), but a higher medial temporal to substantia nigra ratio was both sensitive (94%) and specific (83%). Conclusion: FDG PET is a potential biomarker for the prodromal stage of DLB. A higher medial temporal metabolism and CIS ratio, and lower substantia nigra metabolism have additive value in distinguishing prodromal DLB and AD.

Abstract Introduction Changes in personality characteristics are associated with the onset of symptoms in Alzheimer's disease (AD) and may even precede clinical diagnosis. However, personality changes caused by disease progression can be difficult to separate from changes that occur with normal aging. The Dominantly Inherited Alzheimer Network (DIAN) provides a unique cohort in which to relate measures of personality traits to in vivo markers of disease in a much younger sample than in typical late onset AD. Methods Personality traits measured with the International Personality Item Pool at baseline from DIAN participants were analyzed as a function of estimated years to onset of clinical symptoms and well‐established AD biomarkers. Results Both neuroticism and conscientiousness were correlated with years to symptom onset and markers of tau pathology in the cerebrospinal fluid. Self‐reported conscientiousness and both neuroticism and conscientiousness ratings from a collateral source were correlated with longitudinal rates of cognitive decline such that participants who were rated as higher on neuroticism and lower on conscientiousness exhibited accelerated rates of cognitive decline. Discussion Personality traits are correlated with the accumulation of AD pathology and time to symptom onset, suggesting that AD progression can influence an individual's personality characteristics. Together these findings suggest that measuring neuroticism and conscientiousness may hold utility in tracking disease progression in AD.

Abstract Background Progressive supranuclear palsy (PSP) is a parkinsonian neurodegenerative tauopathy affecting brain regions involved in motor function, including the basal ganglia, diencephalon and brainstem. While PSP is largely considered to be a sporadic disorder, cases with suspected familial inheritance have been identified and the common MAPT H1haplotype is a major genetic risk factor. Due to the relatively low prevalence of PSP, large sample sizes can be difficult to achieve, and this has limited the ability to detect true genetic risk factors at the genome-wide statistical threshold for significance in GWAS data. With this in mind, in this study we genotyped the genetic variants that displayed the strongest degree of association with PSP (P

Increasing progranulin (PGRN) levels is a promising approach for treating frontotemporal dementia and other neurodegenerative diseases. Here Nicholson et al.show that the prosaposin (PSAP) locus is associated with plasma PGRN levels and demonstrate that PSAP can alter PGRN levels and its oligomerization.

Abstract Introduction This study investigated the comparability of potential Alzheimer's disease (AD) biomarkers across blood fractions and assay platforms. Methods Nonfasting serum and plasma samples from 300 participants (150 AD patients and 150 controls) were analyzed. Proteomic markers were obtained via electrochemiluminescence or Luminex technology. Comparisons were conducted via Pearson correlations. The relative importance of proteins within an AD diagnostic profile was examined using random forest importance plots. Results On the Meso Scale Discovery multiplex platform, 10 of the 21 markers shared >50% of the variance across blood fractions (serum amyloid A R2 = 0.99, interleukin (IL)10 R2 = 0.95, fatty acid‐binding protein (FABP) R2 = 0.94, I309 R2 = 0.94, IL‐5 R2 = 0.94, IL‐6 R2 = 0.94, eotaxin3 R2 = 0.91, IL‐18 R2 = 0.87, soluble tumor necrosis factor receptor 1 R2 = 0.85, and pancreatic polypeptide R2 = 0.81). When examining protein concentrations across platforms, only five markers shared >50% of the variance (beta 2 microglobulin R2 = 0.92, IL‐18 R2 = 0.80, factor VII R2 = 0.78, CRP R2 = 0.74, and FABP R2 = 0.70). Discussion The current findings highlight the importance of considering blood fractions and assay platforms when searching for AD relevant biomarkers.

ContextThere is no rapid and cost effective tool that can be implemented as a front-line screening tool for Alzheimer's disease (AD) at the population level.ObjectiveTo generate and cross-validate a blood-based screener for AD that yields acceptable accuracy across both serum and plasma.Design, setting, participantsAnalysis of serum biomarker proteins were conducted on 197 Alzheimer's disease (AD) participants and 199 control participants from the Texas Alzheimer's Research Consortium (TARC) with further analysis conducted on plasma proteins from 112 AD and 52 control participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). The full algorithm was derived from a biomarker risk score, clinical lab (glucose, triglycerides, total cholesterol, homocysteine), and demographic (age, gender, education, APOE*E4 status) data.Major outcome measuresAlzheimer's disease.Results11 proteins met our criteria and were utilized for the biomarker risk score. The random forest (RF) biomarker risk score from the TARC serum samples (training set) yielded adequate accuracy in the ADNI plasma sample (training set) (AUC = 0.70, sensitivity (SN) = 0.54 and specificity (SP) = 0.78), which was below that obtained from ADNI cerebral spinal fluid (CSF) analyses (t-tau/Aβ ratio AUC = 0.92). However, the full algorithm yielded excellent accuracy (AUC = 0.88, SN = 0.75, and SP = 0.91). The likelihood ratio of having AD based on a positive test finding (LR+) = 7.03 (SE = 1.17; 95% CI = 4.49-14.47), the likelihood ratio of not having AD based on the algorithm (LR-) = 3.55 (SE = 1.15; 2.22-5.71), and the odds ratio of AD were calculated in the ADNI cohort (OR) = 28.70 (1.55; 95% CI = 11.86-69.47).ConclusionsIt is possible to create a blood-based screening algorithm that works across both serum and plasma that provides a comparable screening accuracy to that obtained from CSF analyses.

Frontotemporal dementia (FTD) is an uncommon but important form of degenerative disease. It may make up 50% of dementia cases presenting before age 60. The symptoms are related to the anatomic areas affected. Neary divided the clinical syndromes into "frontotemporal dementia," "progressive nonfluent aphasia," and "semantic dementia." However, the pathology may extend beyond the frontal and temporal lobes and additional symptoms may be found. Although most cases are sporadic, some cases are genetic. The best-known genetic mutation causing FTD is frontotemporal dementia with parkinsonism, linked to the microtubule-associated protein tau on chromosome 17. There are other known genes and chromosome loci related to FTD. The most common pathology found is frontotemporal degeneration with ubiquitin inclusions. In contrast, FTD with Pick bodies is rare. Although there are strategies to help patients and their families, there is no known treatment for the disease. [ABSTRACT FROM AUTHOR]