Knopman, David S.

Abstract Predominant limbic degeneration has been associated with various underlying aetiologies and an older age, predominant impairment of episodic memory and slow clinical progression. However, the neurological syndrome associated with predominant limbic degeneration is not defined. This endeavour is critical to distinguish such a syndrome from those originating from neocortical degeneration, which may differ in underlying aetiology, disease course and therapeutic needs. We propose a set of clinical criteria for a limbic-predominant amnestic neurodegenerative syndrome that is highly associated with limbic-predominant age-related TDP-43 encephalopathy but also other pathologic entities. The criteria incorporate core, standard and advanced features, including older age at evaluation, mild clinical syndrome, disproportionate hippocampal atrophy, impaired semantic memory, limbic hypometabolism, absence of neocortical degeneration and low likelihood of neocortical tau, with degrees of certainty (highest, high, moderate and low). We operationalized this set of criteria using clinical, imaging and biomarker data to validate its associations with clinical and pathologic outcomes. We screened autopsied patients from Mayo Clinic and Alzheimer’s Disease Neuroimaging Initiative cohorts and applied the criteria to those with an antemortem predominant amnestic syndrome (Mayo, n = 165; Alzheimer’s Disease Neuroimaging Initiative, n = 53) and who had Alzheimer’s disease neuropathological change, limbic-predominant age-related TDP-43 encephalopathy or both pathologies at autopsy. These neuropathology-defined groups accounted for 35, 37 and 4% of cases in the Mayo cohort, respectively, and 30, 22 and 9% of cases in the Alzheimer’s Disease Neuroimaging Initiative cohort, respectively. The criteria effectively categorized these cases, with Alzheimer’s disease having the lowest likelihoods, limbic-predominant age-related TDP-43 encephalopathy patients having the highest likelihoods and patients with both pathologies having intermediate likelihoods. A logistic regression using the criteria features as predictors of TDP-43 achieved a balanced accuracy of 74.6% in the Mayo cohort, and out-of-sample predictions in an external cohort achieved a balanced accuracy of 73.3%. Patients with high likelihoods had a milder and slower clinical course and more severe temporo-limbic degeneration compared to those with low likelihoods. Stratifying patients with both Alzheimer’s disease neuropathological change and limbic-predominant age-related TDP-43 encephalopathy from the Mayo cohort according to their likelihoods revealed that those with higher likelihoods had more temporo-limbic degeneration and a slower rate of decline and those with lower likelihoods had more lateral temporo-parietal degeneration and a faster rate of decline. The implementation of criteria for a limbic-predominant amnestic neurodegenerative syndrome has implications to disambiguate the different aetiologies of progressive amnestic presentations in older age and guide diagnosis, prognosis, treatment and clinical trials.

Genetic variation at the transmembrane protein 106B gene ( TMEM106B) has been linked to risk of frontotemporal lobar degeneration with TDP-43 inclusions (FTLD-TDP) through an unknown mechanism. We found that presence of the TMEM106B rs3173615 protective genotype was associated with longer survival after symptom onset in a postmortem FTLD-TDP cohort, suggesting a slower disease course. The seminal discovery that filaments derived from TMEM106B is a common feature in aging and, across a range of neurodegenerative disorders, suggests that genetic variants in TMEM106B could modulate disease risk and progression through modulating TMEM106B aggregation. To explore this possibility and assess the pathological relevance of TMEM106B accumulation, we generated a new antibody targeting the TMEM106B filament core sequence. Analysis of postmortem samples revealed that the TMEM106B rs3173615 risk allele was associated with higher TMEM106B core accumulation in patients with FTLD-TDP. In contrast, minimal TMEM106B core deposition was detected in carriers of the protective allele. Although the abundance of monomeric full-length TMEM106B was unchanged, carriers of the protective genotype exhibited an increase in dimeric full-length TMEM106B. Increased TMEM106B core deposition was also associated with enhanced TDP-43 dysfunction, and interactome data suggested a role for TMEM106B core filaments in impaired RNA transport, local translation, and endolysosomal function in FTLD-TDP. Overall, these findings suggest that prevention of TMEM106B core accumulation is central to the mechanism by which the TMEM106B protective haplotype reduces disease risk and slows progression.

AbstractBackgroundThe ALLFTD Consortium aims to characterize preclinical and prodromal stage of familial Frontotemporal Lobar Degeneration (f‐FTLD) to prepare for clinical trials in FTLD.MethodWe prospectively followed 320 asymptomatic participants of the ALLFTD Consortium who are family members of f‐FTLD with a mutation in MAPT (n = 106), GRN (n = 74), or C9orf72 (n = 140), and describe the ratings on the eight domains of CDR® plus NACC FTLD (FTLD‐CDR) in those who phenoconverted to Mild Behavioral and/or Cognitive Impairment (MBCI). MBCI was diagnosed by the proposed research criteria for MBCI‐FTD (Barker MS, et al. Brain 2022). Participants who were diagnosed as MBCI but returned to asymptomatic at the following visit were excluded from the FTLD‐CDR assessment. ANOVA was used to compare continuous variables, and chi‐square test was used to compare categorical variables across the groups.ResultThirty‐six participants (15 MAPT, 9 GRN, 12 C9orf72) developed MBCI during follow‐up visits, 13 participants (5 MAPT, 3 GRN, 5 C9orf72) were diagnosed as MBCI but were characterized as asymptomatic at the following visit, and 271 participants stayed asymptomatic. Percentage of male in MBCI participants was 50% (MAPT 60%, GRN 33%, C9orf72 50%, p = 0.45). Age at phenoconversion to MBCI was 53.6±13.0 years old, the youngest in MAPT and the oldest in GRN participants (MAPT 44.3±8.3, GRN 63.1±11.3, C9orf72 56.4±10.8, p<0.001). Abnormal rating on each of the eight CDR® plus NACC FTLD domains at the initial visit of MBCI phenoconversion were observed in: “Memory” 36% (MAPT 33%, GRN 33%, C9orf72 44%, p = 0.95); “Orientation” 8% (MAPT 7%, GRN 8%, C9orf72 11%, p = 0.93); “Judgment/Problem Solving” 44% (MAPT 47%, GRN 50%, C9orf72 33%, p = 0.73); “Community Affairs” 22% (MAPT 27%, GRN 17%, C9orf72 22%, p = 0.82); “Home/Hobbies” 25% (MAPT 40%, GRN 8%, C9orf72 22%, p = 0.16); “Personal Care” 0%; “Behavior/Comportment/Personality” 44% (MAPT 60%, GRN 42%, C9orf72 22%, p = 0.19); “Language” 31% (MAPT 13%, GRN 50%, C9orf72 33%, p = 0.12).ConclusionThe three most common FTLD‐CDR domains initially disturbed in the prodromal stage of fFTLD were “Behavior/Comportment/Personality”, “Judgment/Problem Solving”, and “Memory”, while “Orientation” was intact in the majority of the individuals. Memory impairment without disorientation was seen in one‐third of the prodromal fFTLD participants.

AbstractBackgroundGenetic mutations causative of familial fronto‐temporal lobar degeneration (f‐FTLD) are highly predictive of a specific proteinopathy, but there exists substantial inter‐individual variability in their system‐level pathophysiology, which can be assessed with 18Fluorodeoxyglucose‐positron emission tomography (FDG‐PET). Determining data‐driven patterns of network degeneration suggestive of underlying specific FTLD‐related genetic mutations is paramount to guide complex clinical decision making supported by the quantification of FDG‐PET.MethodWe collected clinical and FDG‐PET data from 39 patients with f‐FTLD, including 11 carrying the C9orf72 hexanucleotide expansion (1 asymptomatic, 9 with a predominant behavioral phenotype, 1 with a predominant language phenotype), 12 carrying a GRN mutation (1 asymptomatic, 7 behavioral, 4 language), and 16 carrying a MAPT mutation (6 asymptomatic, 10 behavioral). We performed a spectral covariance decomposition analysis between FDG‐PET images to yield latent patterns reflective of a distribution of metabolism opposing poles of relative hyper‐ and hypo‐metabolism across the entire brain (“eigenbrains” or EBs). We then conducted linear discriminant analyses (LDAs) to perform EB‐based multiclass predictions of genetic mutation and clinical phenotype.ResultThe spectral decomposition analysis yielded five eigenbrains, which explained 58.79% of the covariance between FDG‐PET images (Fig. 1). Gradients indicative of relative hypometabolism in left fronto‐temporo‐parietal areas distinguished GRN mutation carriers from other genetic mutations (EB1, EB2, EB4) and were associated with clinical phenotypes predominantly involving language (EB1, EB2, EB3). Conversely, those indicative of relative hypometabolism in prefrontal areas (EB3) and temporopolar areas (EB2) with a right hemispheric predominance were mostly associated with clinical phenotypes predominantly involving behavior/personality, and EB2 distinguished MAPT mutation carriers from other genetic mutations. The LDAs yielded accuracies of 80% and 75% in predicting genetic status and predominant clinical phenotype, respectively (Fig. 2).ConclusionFive EBs explained a high proportion of covariance in patterns of network degeneration across FTLD‐related genetic mutations. These EBs contained information relevant to the system‐level physiology associated with FTLD‐related pathogenic mechanisms and that allowed the prediction of clinical phenotype with relatively high accuracy. This supports the utility of FDG‐PET to guide the development of tools supporting clinical decision making and ongoing efforts to develop network‐based biomarkers to track disease progression and risk of phenoconversion in f‐FTLD.

AbstractBackgroundQuantitative rapid eye movement (REM) sleep without atonia (RSWA) recorded during polysomnography (PSG) represents loss of normal REM sleep atonia. RSWA is the neurophysiologic signature of REM sleep behavior disorder (RBD). Visually scored RSWA is a candidate biomarker for synucleinopathies. However, visual RSWA scoring requires expert scoring, limiting widespread application. We comparatively analyzed RSWA in DLB and iRBD using the automated Ferri REM Atonia Index (RAI).MethodWe quantitatively analyzed the RAI in 12 DLB and 20 iRBD patients, compared to 20 controls using Hypnolab Software for Sleep Analysis (SWS Soft, Inc, Colognola ai Colli, Italy). PSG data were converted to European Data Format (.EDF), and the submentalis surface electromyogram (EMG) signal was notch‐filtered at 60 Hertz and rectified. Automatically calculated RAI scores were comparatively analyzed across groups (DLB, iRBD, controls) using Kruskal Wallis H tests for group comparisons, and regression analyses determined relationships between diagnosis, age, and sex. Logistic regression ROC determined optimal RAI for distinguishing iRBD from DLB. When interpreting RAI, lower values represent greater amounts of RSWA, and higher values represent more normal REM atonia.ResultMean age was older in DLB than in iRBD or controls (72.6 vs. 68.7 vs. 66.5 years). All 12 DLB participants were men, the iRBD group had 18 men and 2 women, and controls were comprised of 16 men and 4 women. Mean RAI was lowest in DLB (0.46), intermediate in iRBD (0.71) and highest in controls (0.96), indicating a gradient in RSWA amounts from DLB patients (highest) to controls (lowest) (Figure). Regression demonstrated diagnosis independently predicted RAI, controlling for age and sex (adjusted R2 = 0.49, p = 0.0001). The RAI that optimally distinguished iRBD from DLB was 0.46 (specificity 85%, sensitivity 58%, AUC = 0.75).ConclusionThe RAI demonstrated a clear gradient throughout the Lewy body spectrum; highest (indicating lowest RSWA amounts) in controls, intermediate in iRBD, and lowest (indicating greatest RSWA) in DLB. The RAI is a promising, time efficient and broadly applicable candidate biomarker for DLB and iRBD. Automated quantitative RSWA could be a valuable tool for deep phenotyping throughout the Lewy body disease spectrum.