Forsberg, Leah K.

Objective Age of symptom onset is highly variable in familial frontotemporal lobar degeneration (f‐FTLD). Accurate prediction of onset would inform clinical management and trial enrollment. Prior studies indicate that individualized maps of brain atrophy can predict conversion to dementia in f‐FTLD. We used a Bayesian linear mixed‐effect (BLME) prediction method for identifying accelerated brain volume loss to predict conversion to dementia. Methods Participants included 234 asymptomatic or prodromal carriers of C9orf72 , GRN , or MAPT mutations (including 21 dementia converters) with ≥3 longitudinal magnetic resonance imaging (MRI) T1‐weighted scans. The BLME models established individual voxel‐wise gray matter trajectories using the first 2 scans. Person‐specific clusters of accelerated volume loss were estimated in subsequent scans and tested as predictors of dementia conversion compared with other approaches in time‐varying Cox proportional hazard models covarying for age. Receiver‐operating characteristic (ROC) curves estimated utility of cluster volume in discriminating which participants converted to dementia within 24 months. Results The BLME cluster volume predicted conversion to dementia in f‐FTLD mutation carriers overall and separately in C9orf72 , GRN , and MAPT , with comparable hazard ratios observed for atrophy W‐maps and regional volumes. Within a 24‐month timeframe, BLME cluster volume discriminated dementia converters from non‐converters with larger areas under the curve (AUCs) than other approaches. Interpretation Bayesian‐modeled individualized atrophy scores predict dementia progression among asymptomatic f‐FTLD mutation carriers and may have increased utility compared with other structural imaging methods when studying individuals over shorter timeframes that align with clinical trial design. ANN NEUROL 20269999:n/a–n/a

Abstract Background Previous studies demonstrate that certain asymptomatic MAPT variant carriers (Asymp‐ MAPT ) exhibit altered baseline gray matter volume (GMV) and functional connectivity (FC) profiles. It remains unclear whether these imaging measures may herald risk for earlier conversion to the symptomatic phase. To address this, we stratified Asymp‐ MAPT based on baseline GMV and longitudinal FC changes to assess whether any Asymp‐ MAPT subgroups showed signs of longitudinal neurodegeneration or cognitive decline. Method We studied 25 Asymp‐ MAPT recruited from the UCSF Memory and Aging Center and ALLFTD Consortia. Using a median split, we divided Asymp‐ MAPT into groups with smaller (LowGMV; n = 12) and larger baseline GMV (HighGMV; n = 13) within regions atrophied in symptomatic MAPT carriers ( n = 20). Next, we stratified Asymp‐ MAPT based on longitudinal FC changes using k‐means clustering on rates of change in FC for four intrinsic connectivity networks associated with common MAPT ‐related syndromes: salience (SN), corticobasal syndrome (CBS), progressive supranuclear palsy (PSP), and default mode (DMN) networks. We compared Asymp‐ MAPT subgroups from each stratification on baseline and longitudinal changes in demographics, plasma neurofilament light (NfL) concentration, GMV within 246 Brainnetome regions, and neuropsychological test scores. Result Stratification of Asymp‐ MAPT based on baseline GMV showed that LowGMV had higher education levels compared to HighGMV, with no other demographic differences. Though LowGMV and HighGMV did not differ in baseline NfL, LowGMV showed greater longitudinal NfL increases. These groups did not differ in baseline or longitudinal GMV changes. LowGMV had lower baseline attention and working memory scores, and greater longitudinal decline in set‐shifting and visuospatial performance. Stratification based on FC changes yielded one group (DecFC; n = 17) exhibiting longitudinal decreases in the SN, PSP, and DMN and another (IncFC; n = 8) showing increases in each network. DecFC and IncFC did not differ in demographics, baseline or longitudinal NfL, or baseline GMV. Longitudinally, DecFC showed greater decline in posterior superior temporal and inferior parietal cortices. DecFC showed lower baseline attention and semantic fluency scores, and greater longitudinal decline in set‐shifting and visuospatial memory performance. Conclusion Lower baseline GMV within regions atrophied during the symptomatic phase and longitudinal FC declines within MAPT ‐relevant networks may signal earlier symptomatic conversion in Asymp‐ MAPT .

Abstract Background Isolated REM sleep behavior disorder (iRBD) is a parasomnia that reflects an evolving α‐synucleinopathy disorder, providing an opportunity to study early pathological changes. While diffusion tensor imaging (DTI) studies have shown white matter changes in iRBD, Neurite Orientation Dispersion and Density Imaging (NODDI) may offer better biological specificity in characterizing microstructural alterations through measures of Neurite Density Index (NDI), Orientation Dispersion Index (ODI), and Free Water Fraction (FWF). Method We included 77 participants with polysomnography‐confirmed iRBD from the North American Prodromal Synucleinopathy (NAPS) Consortium and 154 age‐ and sex‐matched cognitively unimpaired controls from the Mayo Clinic Study of Aging. White matter microstructure was evaluated using standardized multi‐shell diffusion on 3T MRI, quantifying DTI metrics (fractional anisotropy, FA; and mean diffusivity, MD) and NODDI parameters across bilateral white matter tracts defined by the JHU “Eve” WM atlas. Group differences were assessed using conditional logistic regression, with correlations to motor performance evaluated using the Purdue Pegboard and Alternating Finger Tapping tests. Result Compared to controls, iRBD participants demonstrated widespread and bidirectional white matter changes across major white matter pathways (see Figure 1 for glass brain visualizations). While predominantly showing decreases, FA exhibited some increases, particularly in the corticospinal tract. MD showed a largely opposite pattern with predominantly increased values across tracts. NODDI metrics revealed complex bidirectional patterns: ODI was broadly increased across multiple tracts with focal decreases, while NDI showed a pattern of predominantly decreased values alongside localized increases. FWF demonstrated a mixed pattern with predominant decreases across most tracts. In addition, both DTI and NODDI metrics showed extensive, moderate correlations with the Purdue Pegboard Test and Alternating Finger Tapping performance ( T = 2.0, p < 0.05, Figure 2). Conclusion Our study highlighted widespread and complex bidirectional white matter microstructural alterations in individuals with iRBD, demonstrating significant correlations with dexterity and motor performance even during the prodromal stage. These results suggest that extensive white matter abnormalities occur early in prodromal α‐synucleinopathies and highlight the value of advanced diffusion imaging techniques in characterizing iRBD and its potential prediction of phenoconversion to overt neurodegenerative disorders.

Abstract Background Dementia with Lewy Bodies (DLB) has been overlooked or misdiagnosed as Alzheimer's disease (AD) dementia due to its frequent concomitant AD pathology with Lewy Body Disease (LBD) pathology. Although autopsy confirmation has been the gold standard for the precise diagnosis of DLB, time‐course 123 I‐FP‐CIT SPECT (DaT‐SPECT) findings in autopsy‐confirmed DLB are not well characterized. We previously reported that the DaTQUANT z‐score of the more affected side of the putamen has the best discriminatory power in detecting LBD pathology and nigrostriatal degeneration in dementia patients and demonstrated z‐score of −1 as the cutoff value. We sought to examine how DaT‐SPECT findings change over time in autopsy confirmed LBD patients in preparation for its use in LBD targeted clinical trials. Method Eight autopsy confirmed neocortical or limbic LBD patients who underwent two or more DaT‐SPECT were included. Nigrostriatal dopamine transporter (DaT) binding and age‐adjusted z‐scores were analyzed using the DaTQUANT 2.0 software (GE Healthcare). Result Six patients (75%) were male. The patients had 2.5±0.7 longitudinal DaT‐SPECT scans. Clinical diagnosis at initial scan was: DLB (75%), mild cognitive impairment (MCI) with REM sleep behavior disorder (RBD) (13%), and isolated RBD (iRBD) (13%). Clinical diagnosis at last scan was: DLB (88%) and iRBD (12%). All patients developed dementia during life. Mean age at initial scan/last scan/autopsy were 71.1±7.0/73.4±6.9/75.1±7.3 years old. Time from initial and last scan to autopsy were 4.0±1.9 and 1.8±1.9 years respectively. Seven patients (88%) had neocortical LBD and one (12%) had limbic LBD. Concomitant AD pathology was observed in four patients (two males (33%), two females (100%)). All patients had DaTQUANT putamen z‐score <‐1.0 at their initial scan including in MCI+RBD (‐1.76) and iRBD (‐1.53) patients. In the DLB patients at their initial scans, five (83%) had DaTQUANT putamen z‐score <‐2.0 and one (17%) had z‐score of ‐1.55. All patients (100%) showed DaTQUANT putamen z‐score <‐2.0 at their last scans. Conclusion DaTQUANT using cut‐off putamen z‐score of ‐1 was associated with underlying LBD pathology including at their iRBD and MCI stages. Nigrostriatal DaT binding tends to decline over time with DaTQUANT z‐score <‐2 at their last scans.

Abstract Background A hexanucleotide repeat expansion in C9orf72 is the leading genetic cause of frontotemporal lobar degeneration and amyotrophic lateral sclerosis. There remains a critical need for biomarkers that track disease progression across clinical stages. Cross‐sectionally, intrinsic connectivity networks (ICNs) derived from task‐free fMRI (tf‐fMRI) detects abnormalities in C9orf72 expansion carriers ( C9orf72+ ), even when brain structural differences are subtle (Lee et al. , 2017). Few studies have examined longitudinal connectivity changes in C9orf72+ , however. Methods We analyzed longitudinal structural and tf‐fMRI data and plasma neurofilament light chain (NfL) concentrations of C9orf72+ recruited from UCSF and the ALLFTD Consortia. Mean time from first to last scan was 2.4±1.3 years. Participants included 36 asymptomatic (aSx‐ C9 ), 17 prodromal (prodromal‐ C9 ), 29 symptomatic (Sx‐ C9 ) carriers, and 107 healthy controls (HC). For structural MRI analyses, smoothed gray matter maps were parcellated into 246 regions‐of‐interest based on the Brainnetome atlas. We conducted voxelwise seed‐based tf‐fMRI analyses to examine ICNs showing alterations C9orf72+ based on previous literature: salience network (SN), sensorimotor network (SMN), default mode network (DMN), and a medial pulvinar thalamus network (pulvinar). General linear models and linear mixed models (LMM) compared C9orf72+ groups to HC in baseline and longitudinal gray matter and functional connectivity, as well as examined associations between longitudinal functional connectivity changes and baseline NfL concentrations. Results Despite a lack of longitudinal gray matter decline, aSx‐ and Sx‐ C9orf72+ showed functional connectivity changes. Compared to HC, aSx‐ C9 had baseline hypoconnectivity in the SN, SMN, and pulvinar network. Longitudinally, this group showed declines in the SN and pulvinar network, alongside DMN increases. Prodromal‐ C9 exhibited baseline SMN hypoconnectivity and hyperconnectivity in the DMN and pulvinar network, but no significant longitudinal changes. Sx‐ C9 showed baseline hypoconnectivity in SN, SMN, and DMN, with additional regions of DMN hyperconnectivity, while longitudinally, SN and SMN connectivity increased. In aSx‐ C9 , higher baseline NfL concentrations correlated with regions of SMN decreases over time and both increases and decreases in the pulvinar network. In prodromal‐ C9 and Sx‐ C9 combined, higher NfL was associated with DMN increases longitudinally. Conclusions Though gray matter declines were undetectable over a span of several years, functional connectivity networks changed dynamically in C9orf72+ .