Roberson, Erik D.

Abstract Objective The Financial Capacity Instrument-Short Form (FCI-SF) is a performance-based measure of everyday financial skills that takes 15 min to administer. Although the FCI-SF has demonstrated excellent psychometric properties, advanced psychometric methods such as item response theory (IRT) can provide important information on the performance of individual test items in measuring financial capacity and in distinguishing between healthy and cognitively impaired individuals. Method Participants were 272 older adults diagnosed with mild cognitive impairment (MCI) and 1,344 cognitively healthy controls recruited from the Mayo Clinic Study of Aging at the Mayo Clinic in Rochester, Minnesota and also from the Cognitive Observations in Seniors study at the University of Alabama at Birmingham. Participants in each study were administered the FCI-SF, which evaluates coin/currency calculation, financial conceptual knowledge, use of a checkbook/register, and use of a bank statement. Results A unidimensional two-parameter logistic model best fit the 37 FCI-SF Test items, and most FCI-SF items fit the unidimensional two-parameter model well. The results indicated that all FCI-SF items robustly distinguished cognitively healthy controls from persons with MCI. Conclusions The study results showed that the FCI-SF performed well under IRT analysis, further highlighted the psychometric properties of the FCI-SF as a valid and reliable measure of financial capacity, and demonstrated the clinical utility of the FCI-SF in distinguishing between cognitively normal and cognitively impaired individuals.

AbstractBackgroundDyadic (self and study partner) subjective reports of an individual’s recent cognitive and functional decline are an efficient approach to facilitate identification of older adults with, and at risk for, Mild Cognitive Impairment (MCI). Such methods can be easily adapted for remote administration, but few studies have investigated the ability of remotely‐collected, unsupervised dyadic subjective reports to accurately detect MCI and cognitive decline.MethodsIn 289 older adults enrolled in the Brain health Registry (BHR), with clinically‐confirmed diagnoses of Cognitively‐unimpaired (CU) or MCI, we identified the optimal combination of remote measures to accurately distinguish CU from MCI. We then externally validated our predictive model in 217 participants enrolled in a separate cohort, Validation of Online Methods to Predict Cognitive Decline (eVAL). Predictors included Cogstate Brief Battery One Card Learning (OCL) accuracy; self‐ and study partner‐reported memory concern (SMCs); performance on online adaptations of Everyday Cognition Scale (ECog, self‐ and study partner‐report versions), Geriatric Depression Scale Short Form (GDS); family history of AD, age, gender, and education. We calculated 10‐fold cross validated area under the ROC curves (cvAUC), 95% confidence intervals (CI), and the percentage of participants correctly classified (accuracy) for all models. Likelihood ratio (LR) tests were used to compare model fits.ResultsIn the BHR cohort, models including dyad‐report ECog, family history of AD, GDS, and Cogstate OCL scores distinguished CU from MCI with the highest accuracy (cvAUC = 0.90; 95% CI = 0.83, 0.92; accuracy = 85.5%). Models excluding study partner‐report ECog distinguished diagnostic groups with moderate accuracy (cvAUC = 0.83; 95% CI = 0.78, 0.85; accuracy = 75.9%) When applied to the validation cohort, the optimal training model including dyadic report performed with moderate accuracy ( Table 2 ). In the validation cohort, inclusion of study partner (but not self) report SMC, in addition to dyadic‐report ECog, improved model fit (LR test p<0.01).ConclusionsRemotely‐collected dyadic subjective measures, along with other remote measures, accurately distinguish CU from MCI. Subjective cognitive and functional decline and concerns about memory problems independently contribute to diagnostic discrimination. Results support future utilization of remote dyadic subjective measures to efficiently identify older adults with MCI for prodromal AD clinical trials, and in clinical care settings.

AbstractIntroductionTo address the need for remote assessments of cognitive decline and dementia, we developed and administered electronic versions of the Clinical Dementia Rating (CDR®) and the Financial Capacity Instrument‐Short Form (FCI‐SF) (F‐CAP®), called the eCDR and eFCI, respectively.MethodsThe CDR and FCI‐SF were adapted for remote, unsupervised, online use based on item response analysis of the standard instruments. Participants completed the eCDR and eFCI first in clinic, and then at home within 2 weeks.ResultsOf the 243 enrolled participants, 179 (73%) cognitively unimpaired (CU), 50 (21%) with mild cognitive impairment (MCI) or dementia, and 14 (6%) with an unknown diagnosis, 84% and 85% of them successfully completed the eCDR and eFCI, respectively, at home.DiscussionThese results show initial feasibility in developing and administering online instruments to remotely assess and monitor cognitive decline along the CU to MCI/very mild dementia continuum. Validation is an important next step.

AbstractBackgroundFrontotemporal dementia spectrum disorders (FTD) display complex neuropathological substrates and poor clinicopathological correlations, which hinders therapy development. Plasma P‐tau217 is an emerging tool to screen for Alzheimer’s disease (AD) pathology and may have diagnostic value in FTD.MethodPlasma P‐tau217 was measured cross‐sectionally by electrochemiluminescence in FTD patients referred to ALLFTD from ARTFL (n = 628, 45.7% female, median age 66 ± 12 years). P‐tau217 differences by baseline phenotype, disease severity and genotype were determined with non‐parametric tests and general linear models. Associations between P‐tau217 and measures of disease severity and neuropsychological performance were determined with linear regressions corrected for age, sex, phenotype and APOE.ResultThe sample included 33% behavioral variant FTD, 23.6% primary progressive aphasia (PPA), 28.5% atypical parkinsonism, 1.6% amnestic dementia (AmDem), 2.8% FTD/motoneuron disease, 3% mild cognitive/behavioral impairment and 7.5% healthy controls. Only 1.6% carried FTD‐causing mutations. P‐tau217 was not related to age (r = 0.034, 95%CI ‐0.03 – 0.12, p = 0.4). Compared to controls (0.18 ± 0.07 pg/mL), P‐tau217 was elevated only in AmDem (0.58 ± 0.9 pg/mL, p = 0.001) and logopenic PPA (lvPPA, 0.71 ± 0.62 pg/mL p < 0.001). P‐tau217 ≥ 0.42 pg/mL effectively discriminated AmDem and lvPPA from all other phenotypes (AUC 0.87, 95%CI 0.77 – 0.96, p = 0.001, 77% sensitivity, 92% specificity). AmDem (60%) and lvPPA (91.7%) had the highest prevalence of high (≥ 0.42 pg/mL) P‐tau217, and the highest prevalence of APOE4 (AmDem 40%, lvPPA 63.6%). APOE4 carriers (0.23 ± 0.22 pg/mL) had higher P‐tau217, than non‐carriers (0.19 ± 0.09 pg/mL), regardless of phenotype (APOE effect p = .002, APOE x phenotype, p = 0.44). P‐tau217 was associated with worse clinical severity, mood, memory and executive function, but not with worse motor symptoms or social cognition.ConclusionWhen FTD is suspected, high plasma P‐tau217 is strongly associated with amnestic dementia and logopenic PPA phenotypes. Pending completion of ongoing neuropathological, CSF and molecular neuroimaging analyses, the data support the use of plasma P‐tau217 to identify atypical AD as a cause or AD as a co‐pathology contributing to FTD clinical presentation.

AbstractBackgroundClinical trials for tauopathies require novel biomarkers for disease detection and monitoring. One previous study found functional connectivity (FC) alterations in presymptomatic (preSx) MAPT mutation carriers (Whitwell et al., 2011), yet studies have not examined FC networks along the MAPT disease continuum. We hypothesized that both symptomatic (Sx) and preSx MAPT mutation carriers would show FC alterations compared to healthy controls (HC).MethodLeveraging task‐free fMRI data from the UCSF Memory and Aging Center and the ARTFL/LEFFTDS Consortia (Boeve et al., 2019), we compared 14 Sx and 33 preSx to 80 HC to characterize their FC profiles. Using a seed‐based approach, we studied FC within networks associated with different MAPT clinical syndromes (i.e., salience network [SN] for behavioral variant frontotemporal dementia, default mode network [DMN] for Alzheimer’s‐like amnestic syndrome, corticobasal syndrome [CBS] and progressive supranuclear palsy [PSP] networks). Complementing the seed‐based approach, we next calculated whole‐brain intra‐/inter‐network FC matrices for 14 networks (Brown et al., 2019), and applied K‐means clustering to assess whether preSx displayed heterogeneous connectivity profiles. ComBat was applied to harmonize multi‐site imaging data (Fortin et al., 2017, 2018). Thresholding was set at a joint height and extent threshold of p<0.05 (uncorrected) with age, sex, education and handedness as nuisance covariates.ResultCompared to HC, Sx featured disrupted FC within key hubs of all four networks, and regions of cerebellar and pontine hyperconnectivity within CBS and PSP networks. As seen in Sx vs. HC, preSx had similar anatomical patterns of SN/CBS network hypoconnectivity and CBS/PSP network hyperconnectivity vs. HC. In contrast to Sx, who had DMN disruption, preSx showed DMN hyperconnectivity vs. HC.Whole‐brain analyses revealed that Sx had disrupted intra‐/inter‐network FC in networks involving the insula/anterior temporal lobe. Clustering analysis identified two preSx subgroups. Compared to HC, preSx1 principally had disrupted FC across networks including those disrupted in Sx, whereas preSx2 mainly demonstrated hyperconnectivity.ConclusionSx and preSx both demonstrated robust FC alterations. Future studies will investigate whether the preSx subgroup whose whole‐brain FC was similar to Sx in that it showed principally FC disruption may be at greater risk for imminent symptom conversion and/or neurodegeneration.

AbstractBackgroundProgranulin (GRN) mutations cause autosomal dominant frontotemporal lobar degeneration. Clinical trials for GRN‐targeted therapies are underway, yet reliable biomarkers to predict onset and track disease progression remain elusive. Task‐free functional MRI (tf‐fMRI) connectivity may be more sensitive than structural measures for detecting presymptomatic changes (Dopper, 2014; Premi, 2016). Presymptomatic GRN feature tf‐fMRI hyperconnectivity that is more pronounced in older carriers presumably closer to symptom onset, suggesting hyperconnectivity may be a harbinger of disease (Lee, 2019). To aid the interpretation of hyperconnectivity, we explored relationships of structural and tf‐fMRI measures with candidate fluid biomarkers for GRN: CSF complement proteins C3b and C1q, which drive neurodegeneration in GRN ‐/‐ mice (Lui, 2016) and plasma neurofilament light chain (NfL), a marker of axonal injury.MethodWe studied 20 symptomatic GRN (Sx), 39 presymptomatic GRN (preSx), and 67 healthy‐controls (HC). Cross‐sectional CSF C3b, C1q, and plasma NfL concentrations were compared between groups. Correlations controlling for age assessed relationships between fluid biomarkers and symptom severity (CDR®+NACC‐FTLD box score). Voxelwise multiple regression models examined interactions between fluid biomarkers and gene status on grey matter probability maps (GM) and voxelwise tf‐fMRI whole‐brain weighted degree (WBD) maps.ResultComplement concentrations were similar between Sx, preSx, and HC. Across all GRN, C3b concentrations increased with symptom severity (r=0.34, p=0.04). In Sx, but not preSx, higher C3b was associated with increased WBD in medial‐frontal regions, left insula, and thalamus compared to HC. Sx had higher NfL concentrations compared to preSx and HC. Across all GRN and in Sx, higher NfL was associated with greater symptom severity (r=0.60, p<0.001; r=0.72, p<0.001). In Sx, higher NfL was associated with lower GM in precuneus and bilateral frontoinsular cortices, but not WBD, compared to HC. In preSx, higher NfL was associated with increased WBD in thalamus and right temporal regions, but not GM, compared to HC.ConclusionC3b and NfL concentrations correlated with symptom severity. C3b concentrations were associated with tf‐fMRI connectivity alterations in Sx while NfL concentrations were associated with connectivity alterations in preSx. Longitudinal studies are needed to determine temporal relationships between altered connectivity, atrophy, complement, NfL rise, and symptom onset.

AbstractBackgroundBlood neurofilament light chain (NfL) is a robust predictor of phenoconversion in familial frontotemporal lobar degeneration (fFTLD). The comparative value of CSF NfL and other CSF markers of degeneration in fFTLD remains unexplored.MethodFLTD‐causing mutation carriers were recruited through ALLFTD (n = 113, 56.6% female, mean age 48.1 ± 13 years; 29 C9orf72, 16 GRN, 34 MAPT, 34 mutation non‐carriers) and prospectively evaluated for 3 years. Baseline CSF was analyzed for NfL, phosphorylated neurofilament heavy chain (p‐NfH), tau, phosphorylated tau181 (p‐tau) and neurogranin using fit‐for‐purpose immunoassays. Mixed effect linear models, with random slopes, corrected for age, sex, genotype and total intracranial volume related CSF biomarkers to longitudinal clinical variables.ResultNfL (β = 0.64, p < 0.001), p‐NfH (β = 0.68, p < 0.001) and tau (β = 0.46, p < 0.001) correlated with age. There were no differences in biomarker concentrations by phenotype or severity, except for higher NfL and p‐NfH in full phenotype, compared to prodromal disease and asymptomatic carriers. Low neurogranin (β = ‐0.39, p < 0.001), low p‐tau (β = ‐0.33, p < 0.001) and high NfL (β = 0.42, p < 0.001) correlated with worse baseline disease severity measured by the CDR® Dementia Staging Instrument plus behavior and language domains from the National Alzheimer’s Disease Coordinating Center FTLD module sum of boxes (CDR®+NACC‐FTLDsb), and with other measures of global cognition, instrumental and daily function, and frontal and temporal brain volumes. Regardless of genotype, the predicted annualized rate of CDR®+NACC‐FTLDsb score worsenings per higher baseline CSF biomarker Log pg/mL were tau: 3.0 ± 0.2, NfL: 2.8 ± 0.2 and p‐NfH: 2.8 ± 0.2. High tau, NfL and p‐NfH also predicted worsening in other measures of global cognition and instrumental and daily function. Neurogranin and p‐tau did not predict clinical decline.ConclusionCSF tau, p‐tau, neurogranin, NfL and p‐NfH reflect important aspects of disease severity in fFTLD. In contrast to Alzheimer’s disease, low p‐tau and neurogranin are inversely related to clinical severity, which suggests a distinctive pathophysiological process and has implications for therapeutic development. CSF NfL, p‐NfH and tau have strong prognostic value in fFTLD.

AbstractBackgroundUp to 30% of frontotemporal dementia (FTD) cases are due to known pathogenic mutations (f‐FTD). Little is known about the factors that predict who will choose to learn their results. Upcoming clinical trials in f‐FTD may require disclosure prior to enrollment, even before symptom onset, and thus characterizing this sample is important. Furthermore, understanding the mood impacts of genetic disclosure may guide genetic counseling practice.MethodF‐FTD participants (n=568) from families with a known pathogenic mutation (MAPT, C9orf72, GRN) were enrolled through the ARTFL/LEFFTDS Longitudinal FTD Study (ALLFTD) and provided the opportunity for disclosure. Independent‐sample t‐tests compared demographic and psychosocial factors between participants who did and did not receive their results. In participants who were asymptomatic at baseline and follow up (n=199,177 with follow‐up), linear mixed effects modeling was used to investigate pre‐ to post‐disclosure changes in the 15‐item Geriatric Depression Scale (GDS).ResultOf participants from families with a known pathogenic genetic mutation, 47% received genetic disclosure. Of the asymptomatic subset (n=386), 36% know their mutation status. Of these asymptomatic learners, 46% received disclosure through the study, and the remainder learned their genetic status prior to study enrollment. None of the analyzed demographic or psychosocial factors (i.e., sex, age, education, having children) differed between learners and non‐learners (p’s > 0.05). In the longitudinal analysis of asymptomatic participants, learners showed a pre‐ to post‐increase of 0.31 GDS points/year (95%CI: ‐0.08, 0.69, p = 0.12), whereas non‐learners showed a slight decline (‐0.15 points/year, 95%CI: ‐0.36, 0.06, p = 0.16). This difference between slopes was statistically significant (0.46, 95%CI: 0.02, 0.89, p=0.04) but represents a small clinical effect. In asymptomatic learners, slopes did not differ based on mutation status (0.28, 95%CI: ‐0.66, 1.20, p=0.55). Conclusions were based on the estimates and full range of confidence intervals.ConclusionThe majority of asymptomatic research participants do not know their genetic status, which will be a consideration for clinical trials that require disclosure. No considered demographic factors were strongly associated with the decision to receive disclosure. The findings suggest that disclosure in asymptomatic participants has minimal impact on depressive symptoms regardless of genetic results.