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AbstractINTRODUCTIONWe evaluated preliminary feasibility of a digital, culturally‐informed approach to recruit and screen participants for the Alzheimer's Disease Neuroimaging Initiative (ADNI4).METHODSParticipants were recruited using digital advertising and completed digital surveys (e.g., demographics, medical exclusion criteria, 12‐item Everyday Cognition Scale [ECog‐12]), Novoic Storyteller speech‐based cognitive test). Completion rates and assessment performance were compared between underrepresented populations (URPs: individuals from ethnoculturally minoritized or low education backgrounds) and non‐URPs.RESULTSOf 3099 participants who provided contact information, 654 enrolled in the cohort, and 595 completed at least one assessment. Two hundred forty‐seven participants were from URPs. Of those enrolled, 465 met ADNI4 inclusion criteria and 237 evidenced possible cognitive impairment from ECog‐12 or Storyteller performance. URPs had lower ECog and Storyteller completion rates. Scores varied by ethnocultural group and educational level.DISCUSSIONPreliminary results demonstrate digital recruitment and screening assessment of an older diverse cohort, including those with possible cognitive impairment, are feasible. Improving engagement and achieving educational diversity are key challenges.Highlights A total of 654 participants enrolled in a digital cohort to facilitate ADNI4 recruitment. Culturally‐informed digital ads aided enrollment of underrepresented populations. From those enrolled, 42% were from underrepresented ethnocultural and educational groups. Digital screening tools indicate > 50% of participants likely cognitively impaired. Completion rates and assessment performance vary by ethnocultural group and education.

AbstractINTRODUCTIONWell‐chosen biomarkers have the potential to increase the efficiency of clinical trials and drug discovery and should show good precision as well as clinical validity.METHODSWe suggest measures that operationalize these criteria and describe a general approach that can be used for inference‐based comparisons of biomarker performance. The methods are applied to measures obtained from structural magnetic resonance imaging (MRI) from individuals with mild dementia (n = 70) or mild cognitive impairment (MCI; n = 303) enrolled in the Alzheimer's Disease Neuroimaging Initiative.RESULTSVentricular volume and hippocampal volume showed the best precision in detecting change over time in both individuals with MCI and with dementia. Differences in clinical validity varied by group.DISCUSSIONThe methodology presented provides a standardized framework for comparison of biomarkers across modalities and across different methods used to generate similar measures and will help in the search for the most promising biomarkers.Highlights A framework for comparison of biomarkers on pre‐defined criteria is presented. Criteria for comparison include precision in capturing change and clinical validity. Ventricular volume has high precision in change for both dementia and mild cognitive impairment (MCI) trials. Imaging measures’ performance in clinical validity varies more for dementia than for MCI.

AbstractBackgroundWe examined neuropsychiatric symptoms (NPS) and psychotropic medication use at the midway point of data collection of the Longitudinal Early‐onset Alzheimer’s Disease Study (LEADS). We compared amyloid‐positive early‐onset Alzheimer’s disease (EOAD) participants and amyloid‐negative early‐onset non‐Alzheimer’s disease [EOnonAD]) participants across NPS domains and psychotropic medication categories.Method282 participants enrolled in LEADS were compared across diagnostic groups – amyloid‐positive EOAD (n = 212) and amyloid‐negative EOnonAD (n = 70). All participants were between ages 40 and 64 at baseline. NPS were measured with the Neuropsychiatric Inventory – Questionnaire (NPI‐Q) and Geriatric Depression Scale – Short Form (GDS‐SF). Medications were categorized into psychotropic category (e.g., antidepressants, antipsychotics, benzodiazepines). Groups were compared on NPI‐Q using binary logistic regression adjusting for sex and disease severity, on GDS‐SF using linear regression adjusting for sex and disease severity, and on psychotropic medication use using Chi square or Fisher’s exact test.ResultDemographic data are presented in Table 1. Average total NPI‐Q score was higher in EOnonAD than EOAD (p = .002, ŋp 2 = .03). Regardless of diagnostic group, informants endorsed Affective behaviors most frequently (76.2%). EOAD informants endorsed fewer Distress‐Tension behaviors (p = .02, OR = .498) and Impulse Control behaviors (p = .01, OR = .438). EOAD informants also endorsed apathy (p < .001, OR = .316), irritability (p = .02, OR = .498), and disinhibition (p = .04, OR = .476) at lower frequency than EOnonAD. GDS‐SF showed that the EOnonAD participants self‐reported more symptoms of depression than the EOAD group (p = .002, ŋp 2 = .03). (Table 2A). A minority of participants, regardless of diagnostic group, reported psychotropic medication use (35%). There was higher use in EOnonAD (38%) than EOAD (24%) (p = .03, Cohen W = .14) (Table 2B).ConclusionNPS burden and psychotropic medication use were higher in EOnonAD than EOAD participants, despite EOnonAD being less severely impaired. LEADS continues to collect data. Future studies will examine etiologies that may be larger drivers of NPS than AD neuropathology, mediators (e.g., race, ethnicity) in the association between NPS and diagnostic group classication, compare NPS in EOAD vs. LOAD, and examine longitudinal changes in neuropsychiatric profiles.

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.

Abstract INTRODUCTION Magnetic resonance imaging (MRI) research has advanced our understanding of neurodegeneration in sporadic early‐onset Alzheimer's disease (EOAD) but studies include small samples, mostly amnestic EOAD, and have not focused on developing an MRI biomarker. METHODS We analyzed MRI scans to define the sporadic EOAD‐signature atrophy in a small sample (n = 25) of Massachusetts General Hospital (MGH) EOAD patients, investigated its reproducibility in the large longitudinal early‐onset Alzheimer's disease study (LEADS) sample (n = 211), and investigated the relationship of the magnitude of atrophy with cognitive impairment. RESULTS The EOAD‐signature atrophy was replicated across the two cohorts, with prominent atrophy in the caudal lateral temporal cortex, inferior parietal lobule, and posterior cingulate and precuneus cortices, and with relative sparing of the medial temporal lobe. The magnitude of EOAD‐signature atrophy was associated with the severity of cognitive impairment. DISCUSSION The EOAD‐signature atrophy is a reliable and clinically valid biomarker of AD‐related neurodegeneration that could be used in clinical trials for EOAD. Highlights We developed an early‐onset Alzheimer's disease (EOAD)–signature of atrophy based on magnetic resonance imaging (MRI) scans. EOAD signature was robustly reproducible across two independent patient cohorts. EOAD signature included prominent atrophy in parietal and posterior temporal cortex. The EOAD‐signature atrophy was associated with the severity of cognitive impairment. EOAD signature is a reliable and clinically valid biomarker of neurodegeneration.

ImportanceIncreased white matter hyperintensity (WMH) volume is a common magnetic resonance imaging (MRI) finding in both autosomal dominant Alzheimer disease (ADAD) and late-onset Alzheimer disease (LOAD), but it remains unclear whether increased WMH along the AD continuum is reflective of AD-intrinsic processes or secondary to elevated systemic vascular risk factors.ObjectiveTo estimate the associations of neurodegeneration and parenchymal and vessel amyloidosis with WMH accumulation and investigate whether systemic vascular risk is associated with WMH beyond these AD-intrinsic processes.Design, Setting, and ParticipantsThis cohort study used data from 3 longitudinal cohort studies conducted in tertiary and community-based medical centers—the Dominantly Inherited Alzheimer Network (DIAN; February 2010 to March 2020), the Alzheimer’s Disease Neuroimaging Initiative (ADNI; July 2007 to September 2021), and the Harvard Aging Brain Study (HABS; September 2010 to December 2019).Main Outcome and MeasuresThe main outcomes were the independent associations of neurodegeneration (decreases in gray matter volume), parenchymal amyloidosis (assessed by amyloid positron emission tomography), and vessel amyloidosis (evidenced by cerebral microbleeds [CMBs]) with cross-sectional and longitudinal WMH.ResultsData from 3960 MRI sessions among 1141 participants were included: 252 pathogenic variant carriers from DIAN (mean [SD] age, 38.4 [11.2] years; 137 [54%] female), 571 older adults from ADNI (mean [SD] age, 72.8 [7.3] years; 274 [48%] female), and 318 older adults from HABS (mean [SD] age, 72.4 [7.6] years; 194 [61%] female). Longitudinal increases in WMH volume were greater in individuals with CMBs compared with those without (DIAN: t = 3.2 [P = .001]; ADNI: t = 2.7 [P = .008]), associated with longitudinal decreases in gray matter volume (DIAN: t = −3.1 [P = .002]; ADNI: t = −5.6 [P &amp;lt; .001]; HABS: t = −2.2 [P = .03]), greater in older individuals (DIAN: t = 6.8 [P &amp;lt; .001]; ADNI: t = 9.1 [P &amp;lt; .001]; HABS: t = 5.4 [P &amp;lt; .001]), and not associated with systemic vascular risk (DIAN: t = 0.7 [P = .40]; ADNI: t = 0.6 [P = .50]; HABS: t = 1.8 [P = .06]) in individuals with ADAD and LOAD after accounting for age, gray matter volume, CMB presence, and amyloid burden. In older adults without CMBs at baseline, greater WMH volume was associated with CMB development during longitudinal follow-up (Cox proportional hazards regression model hazard ratio, 2.63; 95% CI, 1.72-4.03; P &amp;lt; .001).Conclusions and RelevanceThe findings suggest that increased WMH volume in AD is associated with neurodegeneration and parenchymal and vessel amyloidosis but not with elevated systemic vascular risk. Additionally, increased WMH volume may represent an early sign of vessel amyloidosis preceding the emergence of CMBs.

AbstractIntroductionOne goal of the Longitudinal Early‐onset Alzheimer's Disease Study (LEADS) is to investigate the genetic etiology of early onset (40–64 years) cognitive impairment. Toward this goal, LEADS participants are screened for known pathogenic variants.MethodsLEADS amyloid‐positive early‐onset Alzheimer's disease (EOAD) or negative early‐onset non‐AD (EOnonAD) cases were whole exome sequenced (N = 299). Pathogenic variant frequency in APP, PSEN1, PSEN2, GRN, MAPT, and C9ORF72 was assessed for EOAD and EOnonAD. Gene burden testing was performed in cases compared to similar‐age cognitively normal controls in the Parkinson's Progression Markers Initiative (PPMI) study.ResultsPreviously reported pathogenic variants in the six genes were identified in 1.35% of EOAD (3/223) and 6.58% of EOnonAD (5/76). No genes showed enrichment for carriers of rare functional variants in LEADS cases.DiscussionResults suggest that LEADS is enriched for novel genetic causative variants, as previously reported variants are not observed in most cases.Highlights Sequencing identified eight cognitively impaired pathogenic variant carriers. Pathogenic variants were identified in PSEN1, GRN, MAPT, and C9ORF72. Rare variants were not enriched in APP, PSEN1/2, GRN, and MAPT. The Longitudinal Early‐onset Alzheimer's Disease Study (LEADS) is a key resource for early‐onset Alzheimer's genetic research

AbstractThe Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to improve Alzheimer's disease (AD) clinical trials. Since 2006, ADNI has shared clinical, neuroimaging, and cognitive data, and biofluid samples. We used conventional search methods to identify 1459 publications from 2021 to 2022 using ADNI data/samples and reviewed 291 impactful studies. This review details how ADNI studies improved disease progression understanding and clinical trial efficiency. Advances in subject selection, detection of treatment effects, harmonization, and modeling improved clinical trials and plasma biomarkers like phosphorylated tau showed promise for clinical use. Biomarkers of amyloid beta, tau, neurodegeneration, inflammation, and others were prognostic with individualized prediction algorithms available online. Studies supported the amyloid cascade, emphasized the importance of neuroinflammation, and detailed widespread heterogeneity in disease, linked to genetic and vascular risk, co‐pathologies, sex, and resilience. Biological subtypes were consistently observed. Generalizability of ADNI results is limited by lack of cohort diversity, an issue ADNI‐4 aims to address by enrolling a diverse cohort.

Abstract INTRODUCTION We compared white matter hyperintensities (WMHs) in early‐onset Alzheimer's disease (EOAD) with cognitively normal (CN) and early‐onset amyloid‐negative cognitively impaired (EOnonAD) groups in the Longitudinal Early‐Onset Alzheimer's Disease Study. METHODS We investigated the role of increased WMH in cognition and amyloid and tau burden. We compared WMH burden of 205 EOAD, 68 EOnonAD, and 89 CN participants in lobar regions using t ‐tests and analyses of covariance. Linear regression analyses were used to investigate the association between WMH and cognitive impairment and that between amyloid and tau burden. RESULTS EOAD showed greater WMHs compared with CN and EOnonAD participants across all regions with no significant differences between CN and EOnonAD groups. Greater WMHs were associated with worse cognition. Tau burden was positively associated with WMH burden in the EOAD group. DISCUSSION EOAD consistently showed higher WMH volumes. Overall, greater WMHs were associated with worse cognition and higher tau burden in EOAD. Highlights This study represents a comprehensive characterization of WMHs in sporadic EOAD. WMH volumes are associated with tau burden from positron emission tomography (PET) in EOAD, suggesting WMHs are correlated with increasing burden of AD. Greater WMH volumes are associated with worse performance on global cognitive tests. EOAD participants have higher WMH volumes compared with CN and early‐onset amyloid‐negative cognitively impaired (EOnonAD) groups across all brain regions.

AbstractIntroductionOne goal of the Longitudinal Early Onset Alzheimer's Disease Study (LEADS) is to define the fluid biomarker characteristics of early‐onset Alzheimer's disease (EOAD).MethodsCerebrospinal fluid (CSF) concentrations of Aβ1‐40, Aβ1‐42, total tau (tTau), pTau181, VILIP‐1, SNAP‐25, neurogranin (Ng), neurofilament light chain (NfL), and YKL‐40 were measured by immunoassay in 165 LEADS participants. The associations of biomarker concentrations with diagnostic group and standard cognitive tests were evaluated.ResultsBiomarkers were correlated with one another. Levels of CSF Aβ42/40, pTau181, tTau, SNAP‐25, and Ng in EOAD differed significantly from cognitively normal and early‐onset non‐AD dementia; NfL, YKL‐40, and VILIP‐1 did not. Across groups, all biomarkers except SNAP‐25 were correlated with cognition. Within the EOAD group, Aβ42/40, NfL, Ng, and SNAP‐25 were correlated with at least one cognitive measure.DiscussionThis study provides a comprehensive analysis of CSF biomarkers in sporadic EOAD that can inform EOAD clinical trial design.