Perivascular spaces, plasma GFAP, and speeded executive function in neurodegenerative diseases.

INTRODUCTION: We investigated the effect of perivascular spaces (PVS) volume on speeded executive function (sEF), as mediated by white matter hyperintensities (WMH) volume and plasma glial fibrillary acidic protein (GFAP) in neurodegenerative diseases. METHODS: A mediation analysis was performed to assess the relationship between neuroimaging markers and plasma biomarkers on sEF in 333 participants clinically diagnosed with Alzheimer's disease/mild cognitive impairment, frontotemporal dementia, or cerebrovascular disease from the Ontario Neurodegenerative Disease Research Initiative. RESULTS: PVS was significantly associated with sEF (c = -0.125 ± 0.054, 95% bootstrap confidence interval [CI] [-0.2309, -0.0189], p = 0.021). This effect was mediated by both GFAP and WMH. DISCUSSION: In this unique clinical cohort of neurodegenerative diseases, we demonstrated that the effect of PVS on sEF was mediated by the presence of elevated plasma GFAP and white matter disease. These findings highlight the potential utility of imaging and plasma biomarkers in the current landscape of therapeutics targeting dementia. HIGHLIGHTS: Perivascular spaces (PVS) and white matter hyperintensities (WMH) are imaging markers of small vessel disease. Plasma glial fibrillary protein acidic protein (GFAP) is a biomarker of astroglial injury. PVS, WMH, and GFAP are relevant in executive dysfunction from neurodegeneration. PVS's effect on executive function was mediated by GFAP and white matter disease.

Evaluating the Effect of Alzheimer's Disease-Related Biomarker Change in Corticobasal Syndrome and Progressive Supranuclear Palsy.

OBJECTIVES: To evaluate the effect of Alzheimer's disease (AD) -related biomarker change on clinical features, brain atrophy and functional connectivity of patients with corticobasal syndrome (CBS) and progressive supranuclear palsy (PSP). METHODS: Data from patients with a clinical diagnosis of CBS, PSP, and AD and healthy controls were obtained from the 4-R-Tauopathy Neuroimaging Initiative 1 and 2, the Alzheimer's Disease Neuroimaging Initiative, and a local cohort from the Toronto Western Hospital. Patients with CBS and PSP were divided into AD-positive (CBS/PSP-AD) and AD-negative (CBS/PSP-noAD) groups based on fluid biomarkers and amyloid PET scans. Cognitive, motor, and depression scores; AD fluid biomarkers (cerebrospinal p-tau, t-tau, and amyloid-beta, and plasma ptau-217); and neuroimaging data (amyloid PET, MRI and fMRI) were collected. Clinical features, whole-brain gray matter volume and functional networks connectivity were compared across groups. RESULTS: Data were analyzed from 87 CBS/PSP-noAD and 23 CBS/PSP-AD, 18 AD, and 30 healthy controls. CBS/PSP-noAD showed worse performance in comparison to CBS/PSP-AD in the PSPRS [mean(SD): 34.8(15.8) vs 23.3(11.6)] and the UPDRS scores [mean(SD): 34.2(17.0) vs 21.8(13.3)]. CBS/PSP-AD demonstrated atrophy in AD signature areas and brainstem, while CBS/PSP-noAD patients displayed atrophy in frontal and temporal areas, globus pallidus, and brainstem compared to healthy controls. The default mode network showed greatest disconnection in CBS/PSP-AD compared with CBS/PSP-no AD and controls. The thalamic network connectivity was most affected in CBS/PSP-noAD. INTERPRETATION: AD biomarker positivity may modulate the clinical presentation of CBS/PSP, with evidence of distinctive structural and functional brain changes associated with the AD pathology/co-pathology. ANN NEUROL 2024;96:99-109.

Gene specific effects on brain volume and cognition of TMEM106B in frontotemporal lobar degeneration.

Background and Objectives: TMEM106B has been proposed as a modifier of disease risk in FTLD-TDP, particularly in GRN mutation carriers. Furthermore, TMEM106B has been investigated as a disease modifier in the context of healthy aging and across multiple neurodegenerative diseases. The objective of this study is to evaluate and compare the effect of TMEM106B on gray matter volume and cognition in each of the common genetic FTD groups and in sporadic FTD patients. Methods: Participants were enrolled through the ARTFL/LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) study, which includes symptomatic and presymptomatic individuals with a pathogenic mutation in C9orf72, GRN, MAPT, VCP, TBK1, TARDBP, symptomatic non-mutation carriers, and non-carrier family controls. All participants were genotyped for the TMEM106B rs1990622 SNP. Cross-sectionally, linear mixed-effects models were fitted to assess an association between TMEM106B and genetic group interaction with each outcome measure (gray matter volume and UDS3-EF for cognition), adjusting for education, age, sex and CDR®+NACC-FTLD sum of boxes. Subsequently, associations between TMEM106B and each outcome measure were investigated within the genetic group. For longitudinal modeling, linear mixed-effects models with time by TMEM106B predictor interactions were fitted. Results: The minor allele of TMEM106B rs1990622, linked to a decreased risk of FTD, associated with greater gray matter volume in GRN mutation carriers under the recessive dosage model. This was most pronounced in the thalamus in the left hemisphere, with a retained association when considering presymptomatic GRN mutation carriers only. The minor allele of TMEM106B rs1990622 also associated with greater cognitive scores among all C9orf72 mutation carriers and in presymptomatic C9orf72 mutation carriers, under the recessive dosage model. Discussion: We identified associations of TMEM106B with gray matter volume and cognition in the presence of GRN and C9orf72 mutations. This further supports TMEM106B as modifier of TDP-43 pathology. The association of TMEM106B with outcomes of interest in presymptomatic GRN and C9orf72 mutation carriers could additionally reflect TMEM106B's impact on divergent pathophysiological changes before the appearance of clinical symptoms.

Reliability and Validity of Smartphone Cognitive Testing for Frontotemporal Lobar Degeneration.

Importance: Frontotemporal lobar degeneration (FTLD) is relatively rare, behavioral and motor symptoms increase travel burden, and standard neuropsychological tests are not sensitive to early-stage disease. Remote smartphone-based cognitive assessments could mitigate these barriers to trial recruitment and success, but no such tools are validated for FTLD. Objective: To evaluate the reliability and validity of smartphone-based cognitive measures for remote FTLD evaluations. Design, Setting, and Participants: In this cohort study conducted from January 10, 2019, to July 31, 2023, controls and participants with FTLD performed smartphone application (app)-based executive functioning tasks and an associative memory task 3 times over 2 weeks. Observational research participants were enrolled through 18 centers of a North American FTLD research consortium (ALLFTD) and were asked to complete the tests remotely using their own smartphones. Of 1163 eligible individuals (enrolled in parent studies), 360 were enrolled in the present study; 364 refused and 439 were excluded. Participants were divided into discovery (n = 258) and validation (n = 102) cohorts. Among 329 participants with data available on disease stage, 195 were asymptomatic or had preclinical FTLD (59.3%), 66 had prodromal FTLD (20.1%), and 68 had symptomatic FTLD (20.7%) with a range of clinical syndromes. Exposure: Participants completed standard in-clinic measures and remotely administered ALLFTD mobile app (app) smartphone tests. Main Outcomes and Measures: Internal consistency, test-retest reliability, association of smartphone tests with criterion standard clinical measures, and diagnostic accuracy. Results: In the 360 participants (mean [SD] age, 54.0 [15.4] years; 209 [58.1%] women), smartphone tests showed moderate-to-excellent reliability (intraclass correlation coefficients, 0.77-0.95). Validity was supported by association of smartphones tests with disease severity (r range, 0.38-0.59), criterion-standard neuropsychological tests (r range, 0.40-0.66), and brain volume (standardized ß range, 0.34-0.50). Smartphone tests accurately differentiated individuals with dementia from controls (area under the curve [AUC], 0.93 [95% CI, 0.90-0.96]) and were more sensitive to early symptoms (AUC, 0.82 [95% CI, 0.76-0.88]) than the Montreal Cognitive Assessment (AUC, 0.68 [95% CI, 0.59-0.78]) (z of comparison, -2.49 [95% CI, -0.19 to -0.02]; P = .01). Reliability and validity findings were highly similar in the discovery and validation cohorts. Preclinical participants who carried pathogenic variants performed significantly worse than noncarrier family controls on 3 app tasks (eg, 2-back ß = -0.49 [95% CI, -0.72 to -0.25]; P < .001) but not a composite of traditional neuropsychological measures (ß = -0.14 [95% CI, -0.42 to 0.14]; P = .32). Conclusions and Relevance: The findings of this cohort study suggest that smartphones could offer a feasible, reliable, valid, and scalable solution for remote evaluations of FTLD and may improve early detection. Smartphone assessments should be considered as a complementary approach to traditional in-person trial designs. Future research should validate these results in diverse populations and evaluate the utility of these tests for longitudinal monitoring.

Unusual combinations of neurodegenerative pathologies with chronic traumatic encephalopathy (CTE) complicates clinical prediction of CTE.

BACKGROUND AND PURPOSE: Chronic traumatic encephalopathy (CTE) has gained widespread attention due to its association with multiple concussions and contact sports. However, CTE remains a postmortem diagnosis, and the link between clinical symptoms and CTE pathology is poorly understood. This study aimed to investigate the presence of copathologies and their impact on symptoms in former contact sports athletes. METHODS: This was a retrospective case series design of 12 consecutive cases of former contact sports athletes referred for autopsy. Analyses are descriptive and include clinical history as well as the pathological findings of the autopsied brains. RESULTS: All participants had a history of multiple concussions, and all but one had documented progressive cognitive, psychiatric, and/or motor symptoms. The results showed that 11 of the 12 participants had evidence of CTE in the brain, but also other copathologies, including different combinations of tauopathies, and other rare entities. CONCLUSIONS: The heterogeneity of symptoms after repetitive head injuries and the diverse pathological combinations accompanying CTE complicate the prediction of CTE in clinical practice. It is prudent to consider the possibility of multiple copathologies when clinically assessing patients with repetitive head injuries, especially as they age, and attributing neurological or cognitive symptoms solely to presumptive CTE in elderly patients should be discouraged.

Investigating the association between a history of depression and biomarkers of Alzheimer's disease, cerebrovascular disease, and neurodegeneration in patients with dementia.

The association between depression and dementia, particularly Alzheimer's disease (AD) and cerebrovascular disease (CVD), remains an active area of research. This study aimed to investigate the relationship between a history of depression and biomarkers of AD and CVD in patients with dementia in a clinical setting. A total of 126 patients from the University Health Network (UHN) Memory Clinic with comprehensive clinical evaluations, including neuropsychological testing and medical examinations, were included. Lumbar puncture was performed to collect cerebrospinal fluid (CSF) for biomarker analysis, and brain magnetic resonance imaging (MRI) scans were obtained to assess white matter hyperintensity (WMH) burden. The presence of depression was determined through medical records. The study findings did not reveal significant differences between participants with and without a history of depression in terms of AD biomarkers, WMH burden, neurofilament light chain levels, cognitive scores, age of symptom onset, disease duration, or vascular risk scores. Logistic regression analysis did not indicate a meaningful predictive value of these variables for depression status. This clinical study contributes to our understanding regarding the association between depression and AD/CVD biomarkers in patients with cognitive impairment. Further research is needed to elucidate the complex relationship between depression and dementia and to explore the potential mechanisms linking depression, AD, and CVD.

Assessing the Role of Past Depression in Patients with Mild Cognitive Impairment, with and without Biomarkers for Alzheimer's Disease.

Major depressive disorder (MDD) is a risk factor for Alzheimer's disease (AD). Cerebrovascular disease (CVD) is implicated in MDD and AD. Our study compared participants with AD positive and negative cerebrospinal fluid (CSF) biomarkers on neuropsychological performance, remitted MDD status, and CVD burden. Next, we compared AD-CSF biomarkers and white matter hyperintensities (WMH) burden among three groups: mild cognitive impairment (MCI) (n = 12), MCI with remitted MDD (MDD+MCI) (n = 12), and remitted MDD alone (MDD) (n = 7). Few participants (18%) with MCI+MDD exhibited AD(+) biomarkers. Nearly all participants had moderate-severe WMH. WMH may contribute to cognitive impairment or depression in MCI patients with AD(-) biomarkers.

Development of a sensitive trial-ready poly(GP) CSF biomarker assay for C9orf72-associated frontotemporal dementia and amyotrophic lateral sclerosis.

OBJECTIVE: A GGGGCC repeat expansion in the C9orf72 gene is the most common cause of genetic frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS). As potential therapies targeting the repeat expansion are now entering clinical trials, sensitive biomarker assays of target engagement are urgently required. Our objective was to develop such an assay. METHODS: We used the single molecule array (Simoa) platform to develop an immunoassay for measuring poly(GP) dipeptide repeat proteins (DPRs) generated by the C9orf72 repeat expansion in cerebrospinal fluid (CSF) of people with C9orf72-associated FTD/ALS. RESULTS AND CONCLUSIONS: We show the assay to be highly sensitive and robust, passing extensive qualification criteria including low intraplate and interplate variability, a high precision and accuracy in measuring both calibrators and samples, dilutional parallelism, tolerance to sample and standard freeze-thaw and no haemoglobin interference. We used this assay to measure poly(GP) in CSF samples collected through the Genetic FTD Initiative (N=40 C9orf72 and 15 controls). We found it had 100% specificity and 100% sensitivity and a large window for detecting target engagement, as the C9orf72 CSF sample with the lowest poly(GP) signal had eightfold higher signal than controls and on average values from C9orf72 samples were 38-fold higher than controls, which all fell below the lower limit of quantification of the assay. These data indicate that a Simoa-based poly(GP) DPR assay is suitable for use in clinical trials to determine target engagement of therapeutics aimed at reducing C9orf72 repeat-containing transcripts.

The Longitudinal Assessment of Neuropsychiatric Symptoms in Mild Cognitive Impairment and Alzheimer's Disease and Their Association With White Matter Hyperintensities in the National Alzheimer's Coordinating Center's Uniform Data Set.

BACKGROUND: Neuropsychiatric symptoms (NPSs) are common in Alzheimer's disease (AD). NPSs contribute to patients' distress, caregiver burden, and institutionalization. White matter hyperintensities (WMHs) appear on magnetic resonance imaging, usually indicative of cerebrovascular disease. WMHs have been associated with certain NPSs. We aimed to assess the relationship between WMH and NPS severity in mild cognitive impairment (MCI) due to AD (MCI-AD) and in AD and to assess the ability of WMHs to predict NPS progression. Data were obtained from the National Alzheimer's Coordinating Center. METHODS: A total of 252 participants (114 with MCI-AD and 138 with AD) were used in this study. Baseline WMHs were quantified using an automated segmentation technique. NPSs were measured using the Neuropsychiatric Inventory. Mixed-effect models and correlations were used to determine the relationship between WMHs and NPSs. RESULTS: Longitudinal mixed-effect models revealed a significant relationship between increase in Neuropsychiatric Inventory total scores and baseline WMHs (p = .014). There was a significant relationship between baseline WMHs and an increase in delusions (p = .023), hallucinations (p = .040), agitation (p = .093), depression (p = .017), and irritability (p = .002). Correlation plot analysis showed that baseline whole-brain WMHs predicted change in future Neuropsychiatric Inventory total scores (r = .169, p = .008) and predicted change in future agitation severity scores (r = .165, p = .009). WMHs in the temporal lobes (r = .169, p = .008) and frontal lobes (r = .153, p = .016) contributed most to this change. CONCLUSIONS: Depression, irritability, and agitation are common NPSs and very distressful to patients and caregivers. Our findings of increased NPS severity over time in MCI-AD and AD with increased WMHs have important implications for treatment, arguing for aggressive treatment of vascular risk factors in patients with MCI-AD or AD.

Rates of Brain Atrophy Across Disease Stages in Familial Frontotemporal Dementia Associated With MAPT, GRN, and C9orf72 Pathogenic Variants.

Importance: Several clinical trials are planned for familial forms of frontotemporal lobar degeneration (f-FTLD). Precise modeling of brain atrophy in f-FTLD could improve the power to detect a treatment effect. Objective: To characterize regions and rates of atrophy in the 3 primary f-FTLD genetic groups (MAPT, GRN, and C9orf72) across all disease stages from asymptomatic to dementia. Design, Setting, and Participants: This investigation was a case-control study of participants enrolled in the Advancing Research and Treatment for Frontotemporal Lobar Degeneration or Longitudinal Evaluation of Familial Frontotemporal Dementia studies. The study took place at 18 North American academic medical centers between January 2009 and September 2018. Participants with f-FTLD (n = 100) with a known pathogenic variant (MAPT [n = 28], GRN [n = 33], or C9orf72 [n = 39]) were grouped according to disease stage (ie, Clinical Dementia Rating [CDR] plus National Alzheimer's Coordinating Center [NACC] FTLD module). Included were participants with at least 2 structural magnetic resonance images at presymptomatic (CDR + NACC FTLD = 0 [n = 57]), mild or questionable (CDR + NACC FTLD = 0.5 [n = 15]), or symptomatic (CDR + NACC FTLD = ≥1 [n = 28]) disease stages. The control group included family members of known pathogenic variant carriers who did not carry the pathogenic variant (n = 60). Main Outcomes and Measures: This study fitted bayesian linear mixed-effects models in each voxel of the brain to quantify the rate of atrophy in each of the 3 genes, at each of the 3 disease stages, compared with controls. The study also analyzed rates of clinical decline in each of these groups, as measured by the CDR + NACC FTLD box score. Results: The sample included 100 participants with f-FTLD with a known pathogenic variant (mean [SD] age, 50.48 [13.78] years; 53 [53%] female) and 60 family members of known pathogenic variant carriers who did not carry the pathogenic variant (mean [SD] age, 47.51 [12.43] years; 36 [60%] female). MAPT and GRN pathogenic variants were associated with increased rates of volume loss compared with controls at all stages of disease. In MAPT pathogenic variant carriers, statistically significant regions of accelerated volume loss compared with controls were identified in temporal regions bilaterally in the presymptomatic stage, with global spread in the symptomatic stage. For example, mean [SD] rates of atrophy in the left temporal were -231 [47] mm3 per year during the presymptomatic stage, -381 [208] mm3 per year during the mild stage, and -1485 [1025] mm3 per year during the symptomatic stage (P < .05). GRN pathogenic variant carriers generally had minimal increases in atrophy rates between the presymptomatic and mild stages, with rapid increases in atrophy rates in the symptomatic stages. For example, in the right frontal lobes, annualized volume loss was -267 [81] mm3 per year in the presymptomatic stage and -182 [90] mm3 per year in the mild stage, but -1169 [555] mm3 per year in the symptomatic stage. Compared with the other groups, C9orf72 expansion carriers showed minimal increases in rate of volume loss with disease progression. For example, the mean (SD) annualized rates of atrophy in the right frontal lobe in C9orf72 expansion carriers was -272 (118) mm3 per year in presymptomatic stages, -310 (189) mm3 per year in mildly symptomatic stages, and -251 (145) mm3 per year in symptomatic stages. Conclusions and Relevance: These findings are relevant to clinical trial planning and suggest that the mechanism by which C9orf72 pathogenic variants lead to symptoms may be fundamentally different from the mechanisms associated with other pathogenic variants.

Performance comparison of 10 different classification techniques in segmenting white matter hyperintensities in aging.

INTRODUCTION: White matter hyperintensities (WMHs) are areas of abnormal signal on magnetic resonance images (MRIs) that characterize various types of histopathological lesions. The load and location of WMHs are important clinical measures that may indicate the presence of small vessel disease in aging and Alzheimer's disease (AD) patients. Manually segmenting WMHs is time consuming and prone to inter-rater and intra-rater variabilities. Automated tools that can accurately and robustly detect these lesions can be used to measure the vascular burden in individuals with AD or the elderly population in general. Many WMH segmentation techniques use a classifier in combination with a set of intensity and location features to segment WMHs, however, the optimal choice of classifier is unknown. METHODS: We compare 10 different linear and nonlinear classification techniques to identify WMHs from MRI data. Each classifier is trained and optimized based on a set of features obtained from co-registered MR images containing spatial location and intensity information. We further assess the performance of the classifiers using different combinations of MRI contrast information. The performances of the different classifiers were compared on three heterogeneous multi-site datasets, including images acquired with different scanners and different scan-parameters. These included data from the ADC study from University of California Davis, the NACC database and the ADNI study. The classifiers (naïve Bayes, logistic regression, decision trees, random forests, support vector machines, k-nearest neighbors, bagging, and boosting) were evaluated using a variety of voxel-wise and volumetric similarity measures such as Dice Kappa similarity index (SI), Intra-Class Correlation (ICC), and sensitivity as well as computational burden and processing times. These investigations enable meaningful comparisons between the performances of different classifiers to determine the most suitable classifiers for segmentation of WMHs. In the spirit of open-source science, we also make available a fully automated tool for segmentation of WMHs with pre-trained classifiers for all these techniques. RESULTS: Random Forests yielded the best performance among all classifiers with mean Dice Kappa (SI) of 0.66±0.17 and ICC=0.99 for the ADC dataset (using T1w, T2w, PD, and FLAIR scans), SI=0.72±0.10, ICC=0.93 for the NACC dataset (using T1w and FLAIR scans), SI=0.66±0.23, ICC=0.94 for ADNI1 dataset (using T1w, T2w, and PD scans) and SI=0.72±0.19, ICC=0.96 for ADNI2/GO dataset (using T1w and FLAIR scans). Not using the T2w/PD information did not change the performance of the Random Forest classifier (SI=0.66±0.17, ICC=0.99). However, not using FLAIR information in the ADC dataset significantly decreased the Dice Kappa, but the volumetric correlation did not drastically change (SI=0.47±0.21, ICC=0.95). CONCLUSION: Our investigations showed that with appropriate features, most off-the-shelf classifiers are able to accurately detect WMHs in presence of FLAIR scan information, while Random Forests had the best performance across all datasets. However, we observed that the performances of most linear classifiers and some nonlinear classifiers drastically decline in absence of FLAIR information, with Random Forest still retaining the best performance.

Validation of a Regression Technique for Segmentation of White Matter Hyperintensities in Alzheimer's Disease.

Segmentation and volumetric quantification of white matter hyperintensities (WMHs) is essential in assessment and monitoring of the vascular burden in aging and Alzheimer's disease (AD), especially when considering their effect on cognition. Manually segmenting WMHs in large cohorts is technically unfeasible due to time and accuracy concerns. Automated tools that can detect WMHs robustly and with high accuracy are needed. Here, we present and validate a fully automatic technique for segmentation and volumetric quantification of WMHs in aging and AD. The proposed technique combines intensity and location features frommultiplemagnetic resonance imaging contrasts and manually labeled training data with a linear classifier to perform fast and robust segmentations. It provides both a continuous subject specific WMH map reflecting different levels of tissue damage and binary segmentations. Themethodwas used to detectWMHs in 80 elderly/AD brains (ADC data set) as well as 40 healthy subjects at risk of AD (PREVENT-AD data set). Robustness across different scanners was validated using ten subjects from ADNI2/GO study. Voxel-wise and volumetric agreements were evaluated using Dice similarity index (SI) and intra-class correlation (ICC), yielding ICC=0.96 , SI = 0.62±0.16 for ADC data set and ICC=0.78 , SI=0.51±0.15 for PREVENT-AD data set. The proposed method was robust in the independent sample yielding SI=0.64±0.17 with ICC=0.93 for ADNI2/GO subjects. The proposed method provides fast, accurate, and robust segmentations on previously unseen data from different models of scanners, making it ideal to study WMHs in large scale multi-site studies.

Metabolic disorders with clinical and radiologic features of sporadic Creutzfeldt-Jakob disease.

Two patients with metabolic disorders presented with clinical and radiologic features suggestive of sporadic Creutzfeldt-Jakob disease (sCJD). Case 1 was a 50-year-old man with rapid decline in cognitive, behavioral, and motor function following new-onset seizures. MRI was read as consistent with CJD, and he was referred for a treatment trial, but it was determined that he recently experienced rapid correction of hyponatremia resulting in extrapontine myelinolysis. Case 2 was a 66-year-old woman with poorly controlled diabetes mellitus who was found unconscious after a suspected insulin overdose. Examination showed altered mental status and neuroimaging was remarkable for cortical/striatal hyperintensities suggestive of sCJD. On autopsy, she had hypoglycemic/hypoxic nerve cell loss. Although characteristic MRI findings have high sensitivity and specificity for sCJD, potentially reversible metabolic disorders sometimes present rapidly and can resemble sCJD both clinically and radiologically. These cases highlight the importance of establishing a broad differential diagnosis when evaluating a patient with suspected sCJD.

Induced pluripotent stem cell models of progranulin-deficient frontotemporal dementia uncover specific reversible neuronal defects.

The pathogenic mechanisms of frontotemporal dementia (FTD) remain poorly understood. Here we generated multiple induced pluripotent stem cell lines from a control subject, a patient with sporadic FTD, and an FTD patient with a novel heterozygous GRN mutation (progranulin [PGRN] S116X). In neurons and microglia differentiated from PGRN S116X induced pluripotent stem cells, the levels of intracellular and secreted PGRN were reduced, establishing patient-specific cellular models of PGRN haploinsufficiency. Through a systematic screen of inducers of cellular stress, we found that PGRN S116X neurons, but not sporadic FTD neurons, exhibited increased sensitivity to staurosporine and other kinase inhibitors. Moreover, the serine/threonine kinase S6K2, a component of the phosphatidylinositol 3-kinase and mitogen-activated protein kinase pathways, was specifically downregulated in PGRN S116X neurons. Both increased sensitivity to kinase inhibitors and reduced S6K2 were rescued by PGRN expression. Our findings identify cell-autonomous, reversible defects in patient neurons with PGRN deficiency, and provide a compelling model for studying PGRN-dependent pathogenic mechanisms and testing potential therapies.

Diffuse axonal and tissue injury in patients with multiple sclerosis with low cerebral lesion load and no disability.

BACKGROUND: Although in situ pathological studies and in vivo magnetic resonance (MR) investigations have shown that axonal injury can be significant in the early stages of multiple sclerosis (MS), diffuse axonal injury is generally considered a secondary event. Cerebral axonal damage can be specifically assessed in vivo by measuring levels of brain N-acetylaspartate (NAA, a specific index of axonal integrity detected by MR spectroscopy). Other new MR measurements such as magnetization transfer ratio (MTr) or computed estimation of brain volume can provide less specific indexes of tissue damage. OBJECTIVE: To determine whether diffuse axonal and tissue injury is present in patients with definite MS who do not show clinically significant disability. METHODS: We measured brain NAA levels (normalized to creatine [Cr]), MTr values, and cerebral volumes in patients with definite MS who had low T2-weighted MR imaging lesion volumes and no clinical disability, and also in age-matched healthy control subjects. RESULTS: Values of central brain NAA/Cr and MTr in normal-appearing white matter were significantly lower in the MS patients than in controls (P<.001). In contrast, total brain volumes were not significantly different between these groups. Similar results were found for MS patients with early disease (duration, <3 years) and with a particularly low cerebral T2-weighted MR imaging lesion load (< or = 2 cm(3)). CONCLUSIONS: Cerebral NAA/Cr and MTr values are diffusely decreased in MS patients with early disease, low demyelinating lesion load, and no significant disability. This suggests that axonal and/or tissue injury begins very early in the course of MS and might be at least partially independent of cerebral demyelination.

Magnetization transfer can predict clinical evolution in patients with multiple sclerosis.

The clinical course of multiple sclerosis (MS) is highly variable ranging from benign to aggressive, and is difficult to predict. Since magnetization transfer (MT) imaging can detect focal abnormalities in normal-appearing white matter (NAWM) before the appearance of lesions on conventional MRI, we hypothesized that changes in MT might be able to predict the clinical evolution of MS. We assessed MR data from MS patients who were subsequently followed clinically for 5 years. We computed the mean MT ratio (MTr) in gray matter, in lesions identified on T2-weighted MRI, and in NAWM, as well as in a thick central brain slice for each patient. Patients were divided into stable and worsening groups according to their change in Expanded Disability Status Scale (EDSS) scores over 5 years. We calculated the sensitivity, specificity, predictive value, and odds ratio of the baseline MTr measures in order to assess their prognostic utility. We found significant differences in baseline MTr values in NAWM (p = 0.005) and brain slice (p = 0.03) between clinically stable and worsening MS patients. When these MTr values were compared with changes in EDSS over 5 years, a strong correlation was found between the EDSS changes and MTr values in both NAWM (SRCC = -0.76, p < 0.001) and in the brain slice (SRCC = 0.59, p = 0.01). Baseline NAWM MTr correctly predicted clinical evolution in 15/18 patients (1 false positive and 2 false negatives), yielding a positive predictive value of 77.78 %, a negative predictive value of 88.89 %, and an odds ratio of 28. The relationship between 5-year changes in EDSS and MTr values in T2 weighted MRI lesions was weaker (SRCC = -0.43, p = 0.07). Our data support the notion that the quantification of MTr in the NAWM can predict the clinical evolution of MS. Lower MTr values predict poorer long-term clinical outcome. Abnormalities of MTr values in the NAWM are more relevant to the development of future patient disability than those in the T2-weighted MRI lesions.