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AbstractBackgroundMost studies on the relationship between neuropsychiatric symptoms (NPS) and cognitive decline focus on NPS data collected over a short period of time. To better understand the association between NPS and cognitive decline, including their temporal relationship, it is important to know NPS status across a person’s life.MethodWe utilized the unique Rochester Epidemiology Project medical record linkage system that has captured medical records as far back as 1907, to abstract the psychiatric history of 1810 cognitively unimpaired participants in the population‐based Mayo Clinic Study of Aging (MCSA). Trained nurse abstractors ascertained the presence of exposure to three common NPS (anxiety, depression, and unspecified emotional distress [UED]), both before and after entry into the MCSA. We conducted Cox Proportional Hazards (PH) models using age as the time scale and adjusting for sex, education, and APOE E4 allele for each NPS in predicting mild cognitive impairment (MCI), or dementia. Additional analyses considering medication use (yes/no) and timing of NPS were also run.ResultAnxiety (Hazard Ratio [HR] = 1.47, p<0.001), depression (HR = 1.36, p = 0.001), and UED (HR = 1.22, p = 0.039) were associated with a higher risk of MCI. These associations were present regardless of medication use for anxiety (With medication: HR = 1.51, p<0.001; without medication: HR = 1.41, p = 0.015), and for those taking medications for depression (With medication: HR = 1.47, p<0.001; without medication: 1.09, p = 0.597). Anxiety was associated with MCI regardless of timing of onset with the strongest relationship being for those with onset of anxiety before 65 that persisted into later life (HR = 1.88, p = 0.004). Depression was associated regardless of timing of onset if the depression was present in late life too. The results were similar for the outcome of dementia (Anxiety: HR = 1.62, p<0.001; depression: HR = 1.31, p = 0.040; UED: HR = 1.37, p = 0.014). The associations accounting for medication use and timing of NPS were similar for the outcome of dementia too.ConclusionNPS is associated with progression to MCI and dementia. Both medication use and timing of NPS might play a role in these associations.

AbstractBackgroundRapidly progressive dementia (RPD) includes patients with less than two years from the onset of cognitive impairment to incapacitation due to dementia. Although RPD is often associated with fatal neurodegenerative diseases, including early‐onset Alzheimer disease or Creutzfeldt‐Jakob disease, treatable forms of RPD are increasingly recognized. Early recognition of patients with potentially treatable causes of RPD is key to the timely provision of therapies required to achieve the best possible long‐term outcomes.Method155 patients with RPD were prospectively enrolled from February 2016 to August 2022 via two tertiary care centers. Etiologic diagnoses were independently assigned by two neurologists with good agreement (>90%). Causes of RPD were further classified as treatment‐responsive or nonresponsive, referencing the extant literature. Demographic, clinical, and paraclinical features associated with treatable causes of RPD were identified using stepwise multivariate logistic regression and validated with 5‐fold cross validation.Result87/155 patients (56.1%) had a potentially treatable cause of RPD, including autoimmune/inflammatory disease (n = 52, 59.8%), vasculitis (n = 13, 14.9%), primary psychiatric disease (n = 4, 4.6%), or nutritional deficiency (n = 4, 4.6%). Multivariable analyses identified seven features that were independently associated with treatment‐responsiveness: age‐at‐symptom onset (OR: 0.62 per decade, 95%CI: 0.42‐0.93), seizures (OR: 9.81, 95%CI: 2.84‐33.89), MRI suggestive of autoimmune encephalitis (OR: 23.08, 95%CI: 2.28‐233.40), CSF white blood cell count ≥10 cells/mm3 (OR: 32.24, 95%CI:5.80‐179.21), movement abnormalities (OR: 4.99, 95%CI: 1.76‐14.10), presence of disease‐associated tumor (OR: 13.82, 95%CI: 2.25‐85.11), and mania (OR: 18.47, 95%CI: 1.76‐193.61). Model performance was excellent (c‐statistic = 0.88, 95%CI: 0.82‐0.94; p<0.001): 71 patients (81.6%) with potentially treatable causes of RPD and 56 patients (82.4%) with non‐treatable causes of RPD were correctly classified (PPV = 85.5%; NPV = 77.8%).ConclusionTreatment‐responsive causes of RPD were common in our series. Younger age, seizures, movement abnormalities, or mania at presentation, and paraclinical tests suggesting inflammation (MRI or CSF) or tumor in patients with RPD should prompt consideration of treatable causes of RPD and initiation of treatment when indicated.

AbstractBackgroundThe Alzheimer’s Disease Neuroimaging Initiative (ADNI) is a longitudinal observational study of individuals across the dementia spectrum that validates biomarkers for clinical trials. The newest phase of the study, ADNI4, aims to substantially increase the inclusion of underrepresented populations to improve generalizability of ADNI results. Novel biomarkers, including a speech‐based cognitive assessment and blood‐based plasma biomarkers, are integrated into the study design as key participant screening measures.MethodTo help achieve recruitment goals, ADNI4 uses a new, multi‐phase approach to remotely enroll and screen participants. A large study cohort (aiming for 20,000+ participants) provide initial screening data via an online study platform including demographics, medical history related to study exclusionary criteria, and results from a speech‐based cognitive memory assessment (Novoic Ltd. Storyteller test) and a measure of subjective cognitive/functional decline (Everyday Cognition (ECog) 12‐item). Based on screening results, a subset of online study participants is referred to a Quest Diagnostics location to provide a blood sample for plasma biomarker analysis (aiming for 4,000+ participants). Finally, select participants are referred to ADNI clinical sites for in‐depth characterization (goal of up to 1,500 in‐clinic participants).ResultWe report ADNI’s initial approach for selecting participants from the online screening cohort to undergo plasma biomarker phenotyping, and subsequent selection to a clinical site. Participants from diverse demographic backgrounds (especially for race, ethnicity, and/or education) and those with a higher estimated likelihood of cognitive impairment are given priority in the referral selection process. Likelihood of cognitive impairment is assessed using results from subjective memory complaint questions, responses to the ECog 12‐item questionnaire, and the Novoic Storyteller results. Individuals with results showing high concordance across these measures are prioritized, as well as those who have subsequent plasma results indicating biomarker positivity.ConclusionWeighing the various study requirements and inclusivity goals increases the complexity of participant selection decision making, and is a time‐intensive process. As the ADNI study progresses we aim to automate the participant selection/referral process by developing algorithms that account and encode for changing study prioritizations and dynamics across numerous dimensions. Learnings from ADNI4’s new remote processes will help inform future clinical trial design.

AbstractBackgroundPatients with a yes‐no reversal verbally and non‐verbally respond “yes” when they mean “no” and vice versa. They are typically aware of the error and able to correct it given additional time. This symptom commonly, but not exclusively, occurs in patients with primary progressive apraxia of speech (PPAOS). PPAOS is a form of frontotemporal dementia associated with hypometabolism in the supplementary motor area (SMA; e.g., Utianski et al., 2018); as the disease progresses, a wider network of frontal and subcortical regions become implicated. Behaviorally, this symptom seems to reflect poor response inhibition, but the specific anatomical underpinning is not yet understood. Given the brain regions known to be involved in PPAOS, we hypothesized that yes‐no reversals emerge due to degeneration of regions near the SMA and/or frontostriatal regions.MethodWe conducted an exploratory retrospective study of 28 patients who presented with PPAOS and had an FDG‐PET scan; 14 (50%) endorsed yes‐no reversals (see Table 1 for group characteristics). Clinically, AOS severity was measured using clinician ratings (0 = absent, 4 = severe) and frontal dysfunction was captured by the Frontal Assessment Battery (FAB) and the Frontal Behavioral Inventory (FBI). We also measured median standardized uptake value ratios (SUVRs) in the SMA and pre‐SMA, as well as the head and body of the caudate with automated, in‐house software. The caudate ROI was selected based on visual comparison of the FDG‐PET scans between groups and the association between this region and inhibition during response interference (e.g., Schmidt et al., 2020).ResultNeither AOS severity nor hypometabolism in the pre‐SMA/SMA regions differed significantly between groups. In contrast, patients with a yes‐no reversal demonstrated significantly lower scores on the FAB and greater hypometabolism in the caudate body relative to patients without (see Figure 1).ConclusionResults suggest that yes‐no reversals relate to frontostriatal dysfunction rather than AOS severity or SMA activity in these patients. Further research is needed to address why a disproportionate number of patients with PPAOS develop this symptom.

AbstractBackgroundBrief self‐administered cognitive assessments deployed remotely and combined with plasma biomarkers of Alzheimer’s disease (AD) are well suited to assess clinical symptoms and underlying biology in large‐scale decentralized studies. We investigated whether associations of self‐administered cognitive measures and plasma biomarkers were comparable to associations of in‐person cognitive measures and plasma biomarkers.MethodParticipants included 327 adults from the Mayo Clinic Study of Aging (mean age = 70.8; 48% female; mean education = 16.0 years; 96.9% white). Most (94.5%) were cognitively unimpaired; 5.5% had consensus diagnosis of mild cognitive impairment. Participants completed Mayo Test Drive (MTD; Stricker et al., 2022), a remote, self‐administered, multi‐device compatible web‐based cognitive assessment comprised of the Stricker Learning Span (SLS) and Symbols test that are combined into a MTD composite. Participants also completed in‐person neuropsychological assessment (global‐z; Mayo Preclinical Alzheimer’s disease Cognitive Composite [Mayo‐PACC]) and fasting venipuncture. Plasma was assayed via HD‐X simoa platform for amyloid‐beta (Aβ)‐42 and Aβ‐40 to create an Aβ42/40 ratio, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) using the N4PE Quanterix kit as well as phosphorylated‐tau protein 181 (p‐tau181). P‐tau181, GFAP, and NfL were log10‐transformed. Multiple regression analyses adjusting for age, sex, and education examined associations between plasma biomarkers and composite and subtest scores from remote and in‐person measures. Davidson‐Mackinnon J‐test compared R‐squared values of models with remote versus in‐person composites.ResultLower performances on MTD, global‐z, and Mayo‐PACC (Table 1) were associated with higher GFAP (p’s≤.02), NfL (p’s≤.003), and p‐tau181 (p’s = .04). For memory, worse SLS and AVLT sum of trials were associated with higher GFAP (p’s≤.01) and NfL (p’s≤.03). For processing speed/executive function, worse Symbols and Trails B were associated with higher p‐tau181 (p’s≤.02). Worse Trails B and Digit Symbol Coding were associated with higher NfL (p’s≤.02), and worse Digit Symbol Coding was associated with lower Aβ42/40 (p = 0.03; Table 2). A multivariable model with MTD explained significantly more variance (p = .04) for NfL (adjusted R‐squared = 0.461) than a multivariable model with Mayo‐PACC (adjusted R‐squared = 0.447); remote and in‐person composite measures were comparable for other associations (p’s>.05).ConclusionRemote and in‐person composite measures showed comparable associations with AD‐related plasma biomarkers, supporting MTD’s criterion validity.

AbstractBackgroundThe DEMQOL (Dementia Quality of Life) scale is a patient reported questionnaire and proxy form that captures subjective life quality. Participants in ALLFTD and their Study Partners (SP) complete these questionnaires at each study visit.MethodWe analyzed the DEMQOL in participants and their SPs when the SP was reported to be a spouse or equivalent. Analyses focused on the final overall quality of life (QoL) rating for the participant (poor, fair, good, or very good).ResultDEMQOL responses from 907 dyads (participant: mean age 58.3±13.4 years, 44% female, and mean education 15.9±2.5 years) were analyzed. Participants rated their overall QoL as very good (45.8%), good (36.5%), fair (14%), and poor (3.5%). SPs rated their participant’s overall QoL as very good (33.6%), good (41%), fair (19.4%), and poor (6%). There was a discordance in ratings between participants and SPs (p<0.0001); in almost 50% of cases, participants rated their QoL better (33.2%) or worse (15.2%) than their SP rated their QoL. When considering disease severity (CDR®+NACC‐FTLD global score), participants rated their QoL better than their SP rated their QoL (CDR®+NACC‐FTLD = 0: 19.4%, CDR®+NACC‐FTLD = 0.5: 42%, and CDR®+NACC‐FTLD = 1+: 33.2%), worse than (CDR®+NACC‐FTLD = 0: 15.1%, CDR®+NACC‐FTLD = 0.5: 13.3%, and CDR®+NACC‐FTLD = 1+: 15.2%), or the same (CDR®+NACC‐FTLD = 0: 65.6%, CDR®+NACC‐FTLD = 0.5: 44.8%, and CDR®+NACC‐FTLD = 1+: 51.6%).ConclusionAmong participants and SPs, similarities and differences in QoL ratings are fairly consistent regardless of global CDR®+NACC‐FTLD rating. Generally, participants are equally or more optimistic about QoL than their SPs. Longitudinal analyses are forthcoming.

AbstractBackgroundSmartphone‐based cognitive and motor tests enable frequent remote assessments in observational research studies and clinical trials, limiting travel burden and increasing access to research for underrepresented groups. One such smartphone tool is the ALLFTD Mobile App, which was designed to capture the clinical features of neurodegenerative diseases via a battery of cognitive, speech, and motor tasks. In this study, we focus on recruiting a demographically diverse normative sample. We have partnered with the UCSF Brain Health Registry (BHR) to recruit 1,000 cognitively healthy participants across the lifespan. Here we describe the study design and initial feasibility results.MethodsWe designed an automated workflow in which participants never interact with the study team except for troubleshooting. BHR participants without reported cognitive impairment were contacted by email to participate in this study (n = 668). Interested participants downloaded the app onto their smartphone and completed in‐app electronic consent. They were asked to complete three ∼30‐minute sessions of cognitive, motor and speech measures over two weeks. Adherence was determined by evaluating the completion rate of app tasks. In a subset who completed a user experience questionnaire (n = 116), responses were quantified using descriptive statistics.ResultsThe current enrollment rate is 23.20% (155/668) of contacted participants. Average age is 62 (SD = 8.2, range = 25‐84). Average adherence is 76%. Participants reported a range of perceived task difficulty: 38% indicated tasks were “very easy” or “somewhat easy”, 26% indicated they were “neutral,” 36% found the tasks “somewhat difficult,” and none reported them to be “very difficult.” The time commitment was reported to be acceptable by 97% of participants, and 20% were willing to complete additional tasks. Over half (59%) of participants indicated that they preferred using a smartphone to complete cognitive assessments over traditional pen‐and‐paper measures.ConclusionsOur preliminary results demonstrate the feasibility and acceptability of recruiting participants, including older adults, through a registry and conducting remote smartphone testing via a fully automated workflow that is highly scalable. Future analysis will study the effects of demographic factors on feasibility and investigate the reliability and validity of the app measures in this sample.

AbstractBackgroundThe cardiac and respiratory cycles have been suggested as major drivers of cerebrospinal fluid(CSF) flow. The glymphatic system, one of the mechanisms for the clearance of amyloid‐beta and tau proteins, relies heavily on the movement(flow) of the CSF, and thus, investigating the forces that modulate the CSF flow is essential for understanding the glymphatic flux. Because breathing is trainable through exercise and self‐directed methods, various breathing methods may enhance the CSF flow.MethodReal‐time phase‐contrast MRI(pc‐MRI) was used to measure the CSF flow at the foramen magnum on a 3T. Fast resting‐state fMRI(rsfMRI;TR400ms) was conducted on a compact 3T. Under an IRB‐approved protocol, participants were instructed to breathe slowly and deeply, and subsequently switch to their spontaneous breathing. For rsfMRI data preprocessing, we performed motion correction, skull stripping, spatial smoothing(4mm), temporal filtering(0.01 to 0.1Hz), and linear and quadratic temporal trends removal. fMRI time courses were then normalized to Z‐score at each voxel before being averaged. On the pcMRI, the phase was summed in a CSF region‐of‐interest and plotted vs time. Additionally, we confirmed for possible confounding effects such as head motion or motion‐induced susceptibility changes.ResultrsfMRI findings showed that deep breathing promoted large oscillations in the CSF flow in the ventricles, while spontaneous breathing did not(Figure 1). Additionally, deep breathing resulted in large oscillations in lobar cortical regions. Similar results were observed in the pcMRI, with larger CSF velocity through the foramen magnum during the deep breathing compared to the spontaneous breathing(Figure 2A‐B). The cumulative summation result showed that the volume of CSF flow was increased during deep breathing(Figure 2C).ConclusionThis study provides new evidence that slow and deep breathing promotes CSF flow and global brain BOLD signal, which may be useful in promoting circulation in the brain. The study’s findings also open new avenues for research in the field of neurovascular coupling and mechanisms associated with glymphatic clearance. As hampered CSF flow and/or worsen glymphatic clearance have been shown to associate with pathological aging and dementia, including Alzheimer’s disease and Parkinson’s disease, future research is needed explore the potential of breathing training methods as a non‐pharmacological intervention to support brain health.

AbstractBackgroundEarly diagnosis of Alzheimer’s disease (AD) is crucial for ensuring patients have timely access to essential care. Given the symptoms of early AD are often subtle, it is important that both primary care physicians (PCPs) and neurologists are able to diagnose their patients. Several sources of evidence have indicated that most PCPs and neurologists lack knowledge, competence, and confidence regarding recognition of early forms of AD. To address the clinical practice gaps, a series of CME‐certified programs covering the symptoms, assessment, and diagnosis of early forms of AD were developed.MethodThe data presented here are based on outcomes from four online CME‐certified multimedia programs housed on a single destination page. Each CME‐certified program utilized expert physicians to educate learners on recognizing early forms of AD. Each CME program asked a series of pre‐post questions designed to assess immediate changes in knowledge, competence, or confidence. The questions were grouped into clinically relevant themes. The educational effect for all of the programs was determined by using a paired‐samples t‐test to identify significant differences between pre‐ and post‐assessment responses for each question. Data across all four programs were collected from February 2022 through December 2022. All four programs were promoted to an audience of US‐ and ex‐US physicians.ResultParticipation across the four programs ranged from 543 to 2,510 PCPs and 256 to 1,025 neurologists. PCPs and neurologists demonstrated significant (P<0.05) pre‐vs post education improvements on the following themes: biomarkers in AD, clinical trial outcomes, cognitive assessment scales, diagnosis of AD, diagnosis of mild cognitive impairment (MCI), and symptoms differentiating AD from MCI. Participation in the education also significantly (P<0.001) improved confidence in the identification of early forms of AD among PCPs and neurologists. No substantial differences in knowledge, competence, or confidence were seen for either clinician group based on geographic location of the learner.ConclusionThe results indicated that clinicians who participated in CME‐certified curriculum‐based education in multiple formats were better prepared to recognize early forms of AD. Future education should continue to discuss the use of clinical strategies to recognize early forms of AD.

AbstractBackgroundTriplication of the APP allele in Down syndrome (DS) leads to excess amyloid production and Alzheimer’s disease (AD) related cognitive decline. Key biomarkers (amyloid, tau, neurodegeneration) can identify pathological processes that occur before clinical symptoms and more precisely stage adults with DS along the AD continuum. Previous research has used changes in cortical thickness (CT) as an indicator of neurodegeneration in autosomal‐dominant AD1, but not DS‐related AD. It is unclear when and where cortical thinning occurs along the AD continuum in DS and if these differences are associated with increasing AD pathology.MethodCross‐sectional analysis compared DS participants from the Alzheimer Biomarkers Consortium‐Down Syndrome (106 amyloid‐/cognitively unimpaired, nonclinical, 20% reserved for receiver‐operating characteristic, ROC, analyses; 45 amyloid+/cognitively unimpaired, preclinical; 27 amyloid+/cognitively impaired, clinical) who had amyloid positron emission tomography and magnetic resonance imaging (MRI). Amyloid positivity was defined using standardized uptake value ratio (partial volume corrected) cortical mean values (1.42/1.19 for PIB/AV452) and impairment was based on consensus diagnosis. CT differences between nonclinical and clinical groups were calculated in FreeSurfer v5.3 for multiple thresholds (p<.05/.01/.005/.001/.0005/.0001) using a cluster‐wise false discovery rate of .001, corrected across hemispheres, after controlling for age and sex. CT values were extracted for each threshold and used in ROC analyses (nonclinical reserved participants compared against preclinical and preclinical compared against clinical) to identify key cortical regions that best discriminated amyloid positivity and between unimpaired and impaired.ResultSignificant decreases in parietal and inferior temporal CT were observed between nonclinical and clinical (Figures 1 and 2). ROC analyses identified regions in the left (threshold .05) and right (threshold .005) hemispheres that best differentiated nonclinical from preclinical. Observed area under the curves (AUCs) of .772 and .830 exceeded those previously reported for autosomal‐dominant AD (.547/.540)1. Analyses differentiating preclinical from clinical observed AUCs of .786 for left (threshold .0005) and .770 for right (threshold .0005) hemispheres.ConclusionCT differences primarily within posterior cortical regions differentiated adults with DS by amyloid status and cognitive impairment. CT differences were more diffuse for amyloid positivity but more focal for impairment.1. Dincer (2020). NeuroImage: Clinical, 28, 102491.2. Su (2019). Alzheimer’s Dement, 11, 180‐190.