Citations

AbstractBackgroundA key focus of the U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) is recruitment of unimpaired older individuals at risk for cognitive decline with heterogeneous characteristics (under‐represented racial and ethnicity groups (URG), family history of cognitive decline, hypertension, geographic diversity), and a subset of individuals undergo PET and MRI.MethodTo examine effects of heterogeneity on relationships between risk factors, AD biomarkers (Aß and entorhinal tau PET, hippocampal volume (HV)) and cognition (global, executive function, and memory) were examined from U.S. POINTER neuroimaging participants (N = 602, about 65% of the anticipated total sample) and a subset of Alzheimer’s Disease Neuroimaging Initiative participants (N = 503). Neuroimaging data were processed and analyzed using harmonized methods across studies. Some cohort‐specific measurements were standardized using a within‐cohort reference group (Aß‐negative individuals <70yrs and with global CDR = 0).ResultU.S. POINTER imaging participants are younger than those in ADNI (68.6+/‐5.0yrs vs 70.7+/‐4.4yrs), more likely to be female (65% vs 58%) and from URG (27% vs 15%), and had lower education (14.7+/‐3.3yrs vs 16.7+/‐2.3yrs) and higher Framingham Cardiovascular Risk scores (9.9+/‐8.3 vs 7.7+/‐5.3). The groups differed on several AD biomarkers and cognitive measures (Table). In regression models, AD biomarkers were stronger predictors of cognitive performance in ADNI compared to POINTER. Specifically, Aß+ individuals with elevated tau had disproportionately poorer cognitive performance in ADNI, and this relationship remained consistent across cognitive measures (Figure). Conversely, demographic/risk variables were stronger predictors in POINTER. Demographic/risk predictors (age, sex, education, race, and FRS) together explained twice as much variance in global cognition in POINTER compared to ADNI (Adjusted R2 = 29% vs 14%). The addition of AD biomarkers to the model further increased the amount of variance in global cognition explained from 14% to 34% in ADNI, but addition of AD biomarkers did not increase variance explained in the POINTER model.ConclusionHeterogeneity among study participants appears to influence baseline biomarker‐cognition relationships such that AD biomarkers explain more variability in cognitive performance in ADNI than POINTER. These findings further suggest that cohort characteristics may affect the potential influence of amyloid‐ and tau‐modifying treatments on cognition.

AbstractBackgroundThe Standardized Centralized Alzheimer’s & related dementias Neuroimaging (SCAN) project harmonizes processing of prospectively acquired PET and MRI scans from Alzheimer’s disease research centers (ADRCs) across the USA. SCAN data will be integrated with other ADRC data streams within the National Alzheimer’s Coordinating Center (NACC), including the Uniform Data Set which includes rich longitudinal demographic, cognitive, and neuropathological data, resulting in a large, potentially representative cohort. The project has sought to accommodate site‐to‐site variation in image acquisition while permitting harmonization of imaging data, necessitating new analytic approaches for different PET tracers and PET scans without MRIs.MethodPET scans underwent preprocessing for quality control and smoothing to a uniform resolution. MRI‐free processing pipelines and positivity thresholds were developed for each beta‐amyloid (Aß)‐PET tracer: [11C]PiB, [18F]florbetaben (FBB), [18F]florbetapir (FBP) and [18F]flutafuranol (NAV). A generic Aß‐PET template was used for spatial normalization and cortical summary SUVRs were calculated in template space. Aß‐positivity thresholds were determined by examining both MRI‐dependent thresholds transformed into MRI‐free units and a young control mean+2SD. Centiloid (CL) conversions were completed for each Aß‐PET tracer. Tau‐PET tracers ([18F]flortaucipir (FTP) and [18F]MK‐6240) required tracer‐specific warping templates for best performance relative to gold‐standard MRI‐dependent processing. Demographic and clinical data were obtained from NACC.Result15 ADRCs have contributed data to SCAN as of January 2023. 477 participants had preprocessed, SCAN‐compliant (https://scan.naccdata.org/) Aß‐PET scans and NACC data; 219 of these participants (46%) also had tau‐PET scans (Table 1). This cohort included 18% of individuals from underrepresented groups. Clinical diagnostic groups ranged from cognitively unimpaired to MCI and dementia (74% of whom had AD dementia). Using pooled Aß‐PET data across 4 tracers in CLs, there were expected differences in Aß burden by diagnosis group (Fig. 1) and positive associations with tau (Fig. 2).ConclusionSCAN has successfully harmonized PET data from more than a dozen US ADRCs yielding a large, clinically heterogeneous cohort of deeply phenotyped research participants. SCAN data will be compatible with ADNI data allowing for further pooling of data and greater statistical power to drive critical questions in AD and related dementias research.

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.

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.

AbstractIntroductionThe Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to validate biomarkers for Alzheimer's disease (AD) clinical trials. To improve generalizability, ADNI4 aims to enroll 50‐60% of its new participants from underrepresented populations (URPs) using new biofluid and digital technologies. ADNI4 has received funding from the National Institute on Aging beginning September 2022.MethodsADNI4 will recruit URPs using community‐engaged approaches. An online portal will screen 20,000 participants, 4000 of whom (50‐60% URPs) will be tested for plasma biomarkers and APOE. From this, 500 new participants will undergo in‐clinic assessment joining 500 ADNI3 rollover participants. Remaining participants (∼3500) will undergo longitudinal plasma and digital cognitive testing. ADNI4 will add MRI sequences and new PET tracers. Project 1 will optimize biomarkers in AD clinical trials.Results and DiscussionADNI4 will improve generalizability of results, use remote digital and blood screening, and continue providing longitudinal clinical, biomarker, and autopsy data to investigators.

AbstractThe extent to which the pathophysiology of autosomal dominant Alzheimer's disease corresponds to the pathophysiology of ‘sporadic’ late onset Alzheimer's disease is unknown, thus limiting the extrapolation of study findings and clinical trial results in autosomal dominant Alzheimer's disease to late onset Alzheimer's disease.We compared brain MRI and amyloid PET data, as well as CSF concentrations of amyloid-β42, amyloid-β40, tau and tau phosphorylated at position 181, in 292 carriers of pathogenic variants for Alzheimer's disease from the Dominantly Inherited Alzheimer Network, with corresponding data from 559 participants from the Alzheimer’s Disease Neuroimaging Initiative. Imaging data and CSF samples were reprocessed as appropriate to guarantee uniform pipelines and assays. Data analyses yielded rates of change before and after symptomatic onset of Alzheimer's disease, allowing the alignment of the ∼30-year age difference between the cohorts on a clinically meaningful anchor point, namely the participant age at symptomatic onset.Biomarker profiles were similar for both autosomal dominant Alzheimer's disease and late onset Alzheimer's disease. Both groups demonstrated accelerated rates of decline in cognitive performance and in regional brain volume loss after symptomatic onset. Although amyloid burden accumulation as determined by PET was greater after symptomatic onset in autosomal dominant Alzheimer's disease than in late onset Alzheimer's disease participants, CSF assays of amyloid-β42, amyloid-β40, tau and p-tau181 were largely overlapping in both groups. Rates of change in cognitive performance and hippocampal volume loss after symptomatic onset were more aggressive for autosomal dominant Alzheimer's disease participants.These findings suggest a similar pathophysiology of autosomal dominant Alzheimer's disease and late onset Alzheimer's disease, supporting a shared pathobiological construct.

AbstractBackgroundThe U.S. Study to Protect Brain Health Through Lifestyle Intervention to Reduce Risk (U.S. POINTER) is a 2‐year randomized controlled trial to evaluate the effect of lifestyle interventions in older adults (60‐79 years) who are cognitively unimpaired but at increased risk for cognitive decline/dementia due to factors such as cardiovascular disease and family history. The POINTER Imaging ancillary study is collecting PET and MRI data to evaluate neuroimaging biomarkers of AD and cerebrovascular pathophysiology in this at‐risk sample.MethodPOINTER Imaging is actively enrolling 1250 participants, 23% from under‐represented racial/ethnic groups (URG), recruited from five U.S. POINTER clinical sites. Participants have undergone PET imaging with [18F]Florbetaben (FBB) to measure Aβ and [18F]MK‐6240 to measure tau burden, as well as MRI to measure brain morphometry, white matter hyperintensities and cerebral blood flow. FBB and MK‐6240 data were quality checked, pre‐processed, and quantified using previously validated methods. PET images were coregistered to a structural MRI, which was also used to create FreeSurfer‐defined reference regions and regions of interest. We examined PET imaging measures (global Aβ, regional tau) and basic demographic (age, sex, race/ethnicity) characteristics of the sample.Result96 participants (mean age 69.3±5.0) have been enrolled in POINTER Imaging. Of these, 59 (61%) are women and 22 (23%) are URG, which is similar to rates of women (75%) and URG (22%) in the main trial. This dataset is <10% of targeted enrollment, was predominantly recruited from 2/5 clinical sites and may not represent the final imaging cohort. FBB quantification (N=20) revealed a mean cortical summary SUVR of 1.09±0.12 (19.6±18.4 centiloids) (whole cerebellum normalization; previously validated positivity threshold=1.08), and 8/20 (40%) of these participants were Aβ+ (Fig. 1A). MK‐6240 quantification (N=23) showed predominantly no/minimal binding with a few exceptions in medial and lateral temporal lobes (Fig. 1B&C).ConclusionThe POINTER imaging study is meeting the target URG enrollment and representative of the main U.S. POINTER trial. Higher frequency of Aβ positivity than published in population cohorts coupled with greater cardiovascular risk factors among POINTER participants highlights our success in recruiting individuals at increased risk of cognitive decline.

Abstract The Worldwide Alzheimer's Disease Neuroimaging Initiative (WW‐ADNI) is a collaborative effort to investigate imaging and biofluid markers that can inform Alzheimer's disease treatment trials. It is a public‐private partnership that spans North America, Argentina, Australia, Canada, China, Japan, Korea, Mexico, and Taiwan. In 2004, ADNI researchers began a naturalistic, longitudinal study that continues today around the globe. Through several successive phases (ADNI‐1, ADNI‐GO, ADNI‐2, and ADNI‐3), the study has fueled amyloid and tau phenotyping and refined neuroimaging methodologies. WW‐ADNI researchers have successfully standardized analyses and openly share data without embargo, providing a rich data set for other investigators. On August 26, 2020, the Alzheimer's Association convened WW‐ADNI researchers who shared updates from ADNI‐3 and their vision for ADNI‐4.

Abstract Introduction Amyloid beta (Aβ), tau, and neurodegeneration jointly with the Alzheimer's disease (AD) risk factors affect the severity of clinical symptoms and disease progression. Methods Within 248 Aβ‐positive elderly with and without cognitive impairment and dementia, partial least squares structural equation pathway modeling was used to assess the direct and indirect effects of imaging biomarkers (global Aβ‐positron emission tomography [PET] uptake, regional tau‐PET uptake, and regional magnetic resonance imaging–based atrophy) and risk‐factors (age, sex, education, apolipoprotein E [ APOE ], and white‐matter lesions) on cross‐sectional cognitive impairment and longitudinal cognitive decline. Results Sixteen percent of variance in cross‐sectional cognitive impairment was accounted for by Aβ, 46% to 47% by tau, and 25% to 29% by atrophy, although 53% to 58% of total variance in cognitive impairment was explained by incorporating mediated and direct effects of AD risk factors. The Aβ–tau–atrophy pathway accounted for 50% to 56% of variance in longitudinal cognitive decline while Aβ, tau, and atrophy independently explained 16%, 46% to 47%, and 25% to 29% of the variance, respectively. Discussion These findings emphasize that treatments that remove Aβ and completely stop downstream effects on tau and neurodegeneration would only be partially effective in slowing of cognitive decline or reversing cognitive impairment.