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A Protocol for the Inclusion of Minoritized Persons in Alzheimer Disease Research From the ADNI3 Diversity Taskforce
Okonkwo, Ozioma C. , Ashford, Miriam T. , Conti, Catherine , Strong, Joe, Raman, Rema , Nosheny, Rachel L. , Flenniken, Derek , Miller, Melanie J. , Diaz, Adam , Soto, Annabelle M., Ances, Beau M. , Beigi, Maryam , Doraiswamy, P. Murali , Duara, Ranjan , Farlow, Martin R. , Grossman, Hillel, Mintzer, Jacobo , Reist, Christopher , Rogalskı, Emily , Sabbagh, Marwan N. , Salloway, Stephen, Schneider, Lon S. , Petersen, Ronald C. , Aisen, Paul , Weiner, Michael W., Initiative, Alzheimer’s Disease Neuroimaging, Ances, Beau M , Mindt, Mónica Rivera , Donohue, Michael , Duara, Ranjan , Shah, Raj C. , Initiative, Alzheimer’s Disease Neuroimaging

JAMA Network Open | August 9, 2024 | Volume: 7 | Issue: 8 | Pages: e2427073

10.1001/jamanetworkopen.2024.27073 | PMID 39120898 Get It

ImportanceBlack or African American (hereinafter, Black) and Hispanic or Latino/a/x (hereinafter, Latinx) adults are disproportionally affected by Alzheimer disease, but most research studies do not enroll adequate numbers of both of these populations. The Alzheimer’s Disease Neuroimaging Initiative-3 (ADNI3) launched a diversity taskforce to pilot a multipronged effort to increase the study inclusion of Black and Latinx older adults.ObjectiveTo describe and evaluate the culturally informed and community-engaged inclusion efforts to increase the screening and enrollment of Black and Latinx older adults in ADNI3.Design, Setting, and ParticipantsThis cross-sectional study used baseline data from a longitudinal, multisite, observational study conducted from January 15, 2021, to July 12, 2022, with no follow-up. The study was conducted at 13 ADNI3 sites in the US. Participants included individuals aged 55 to 90 years without cognitive impairment and those with mild cognitive impairment or Alzheimer disease.ExposuresEfforts included (1) launch of an external advisory board, (2) changes to the study protocol, (3) updates to the digital prescreener, (4) selection and deployment of 13 community-engaged research study sites, (5) development and deployment of local and centralized outreach efforts, and (6) development of a community-science partnership board.Main Outcomes and MeasuresScreening and enrollment numbers from centralized and local outreach efforts, digital advertisement metrics, and digital prescreener completion.ResultsA total of 91 participants enrolled in the trial via centralized and local outreach efforts, of which 22 (24.2%) identified as Latinx and 55 (60.4%) identified as Black (median [IQR] age, 65.6 [IQR, 61.5-72.5] years; 62 women [68.1%]). This represented a 267.6% increase in the monthly rate of enrollment (before: 1.11 per month; during: 4.08 per month) of underrepresented populations. For the centralized effort, social media advertisements were run between June 1, 2021, and July 31, 2022, which resulted in 2079 completed digital prescreeners, of which 1289 met criteria for subsequent site-level screening. Local efforts were run between June 1, 2021, to July 31, 2022. A total of 151 participants underwent site-level screening (100 from local efforts, 41 from centralized efforts, 10 from other sources).Conclusions and RelevanceIn this cross-sectional study of pilot inclusion efforts, a culturally informed, community-engaged approach increased the inclusion of Black and Latinx participants in an Alzheimer disease cohort study.
Clinicopathologic Heterogeneity and Glial Activation Patterns in Alzheimer Disease
Frankenhauser, Isabelle , Peng, Zhongwei , Labuzan, Sydney A. , Boon, Baayla D.C. , Moloney, Christina M. , Pottier, Cyril , Wickland, Daniel P. , Tranovich, Jessica F., Wood, Ashley , Hinkle, Kelly M., Lincoln, Sarah, Spychalla, Anthony J., Przybelski, Scott A. , Kwan, Rain S., Lesser, Elizabeth R. , Carter, Rickey E. , Ross, Owen A. , Lachner, Christian , Ertekin‐Taner, Nilüfer , Ferman, Tanis J. , Fields, Julie A. , Nguyen, Aivi T. , Reichard, R. Ross , Graff‐Radford, Jonathan , Petersen, Ronald C. , Jack, Clifford R. , Kantarci, Kejal , Day, Gregory S. , Duara, Ranjan , Graff‐Radford, Neill R. , Lowe, Val J. , Murray, Melissa E. , Kouri, Naomi , Caetano-Anolles, Kelsey, Corriveau-Lecavalier, Nick , Wood, Ashley C., Lincoln, Sarah J, Engelberg-Cook, Erica , Crook, Julia E. , Jack, Clifford R , Ross, Owen A , Carter, Rickey E , Kantarci, Kejal , Day, Gregory S , Murray, Melissa E , Ferman, Tanis J , Nguyen, Aivi T , Pottier, Cyril , Caetano-Anollés, Kelsey , Corriveau‐Lecavalier, Nick , Wood, Ashley C., Senjem, Matthew L. , Schwarz, Christopher G. , Machulda, Mary M. , Ramanan, Vijay K. , Jones, David T. , Boeve, Bradley F. , Knopman, David S. , Duara, Ranjan , Dickson, Dennis W. , Vemuri, Prashanthi

JAMA Neurology | April 15, 2024 | Volume: 81 | Issue: 6 | Pages: 619

10.1001/jamaneurol.2024.0784 | PMID 38619853 Get It

Importance Factors associated with clinical heterogeneity in Alzheimer disease (AD) lay along a continuum hypothesized to associate with tangle distribution and are relevant for understanding glial activation considerations in therapeutic advancement. Objectives To examine clinicopathologic and neuroimaging characteristics of disease heterogeneity in AD along a quantitative continuum using the corticolimbic index (CLix) to account for individuality of spatially distributed tangles found at autopsy. Design, Setting, and Participants This cross-sectional study was a retrospective medical record review performed on the Florida Autopsied Multiethnic (FLAME) cohort accessioned from 1991 to 2020. Data were analyzed from December 2022 to December 2023. Structural magnetic resonance imaging (MRI) and tau positron emission tomography (PET) were evaluated in an independent neuroimaging group. The FLAME cohort includes 2809 autopsied individuals; included in this study were neuropathologically diagnosed AD cases (FLAME-AD). A digital pathology subgroup of FLAME-AD cases was derived for glial activation analyses. Main Outcomes and Measures Clinicopathologic factors of heterogeneity that inform patient history and neuropathologic evaluation of AD; CLix score (lower, relative cortical predominance/hippocampal sparing vs higher, relative cortical sparing/limbic predominant cases); neuroimaging measures (ie, structural MRI and tau-PET). Results Of the 2809 autopsied individuals in the FLAME cohort, 1361 neuropathologically diagnosed AD cases were evaluated. A digital pathology subgroup included 60 FLAME-AD cases. The independent neuroimaging group included 93 cases. Among the 1361 FLAME-AD cases, 633 were male (47%; median [range] age at death, 81 [54-96] years) and 728 were female (53%; median [range] age at death, 81 [53-102] years). A younger symptomatic onset (Spearman ρ = 0.39, P < .001) and faster decline on the Mini-Mental State Examination (Spearman ρ = 0.27; P < .001) correlated with a lower CLix score in FLAME-AD series. Cases with a nonamnestic syndrome had lower CLix scores (median [IQR], 13 [9-18]) vs not (median [IQR], 21 [15-27]; P < .001). Hippocampal MRI volume (Spearman ρ = −0.45; P < .001) and flortaucipir tau-PET uptake in posterior cingulate and precuneus cortex (Spearman ρ = −0.74; P < .001) inversely correlated with CLix score. Although AD cases with a CLix score less than 10 had higher cortical tangle count, we found lower percentage of CD68-activated microglia/macrophage burden (median [IQR], 0.46% [0.32%-0.75%]) compared with cases with a CLix score of 10 to 30 (median [IQR], 0.75% [0.51%-0.98%]) and on par with a CLix score of 30 or greater (median [IQR], 0.40% [0.32%-0.57%]; P = .02). Conclusions and Relevance Findings show that AD heterogeneity exists along a continuum of corticolimbic tangle distribution. Reduced CD68 burden may signify an underappreciated association between tau accumulation and microglia/macrophages activation that should be considered in personalized therapy for immune dysregulation.
Baseline neuropsychiatric symptoms and psychotropic medication use midway through data collection of the Longitudinal Early‐ Onset Alzheimer’s Disease Study (LEADS) Cohort
Wonderlin, Ryan J., Hammers, Dustin B. , Garcia, Alex Pena, Eloyan, Ani , Taurone, Alexander, Thangarajah, Maryanne, Gao, Sujuan , Kirby, Kala, Aisen, Paul , Griffin, Percy , Iaccarino, Leo, Kramer, Joel H. , Soleimani‐Meigooni, David N. , Rumbaugh, Malia, Touroutoglou, Alexandra , Duara, Ranjan , Graff‐Radford, Neill R. , Masdeu, Joseph C. , Mendez, Mario F. , Onyike, Chiadi U. , Riddle, Meghan C., Rogalskı, Emily , Salloway, Stephen , Sha, Sharon, Dickerson, Brad C., Apostolova, Liana G. , Polsinelli, Angelina J. , Hammers, Dustin B , Beckett, Laurel , Wang, Sophia , Logan, Paige E. , Dage, Jeffrey L. , Foroud, Tatiana , Koeppe, Robert A. , Kukull, Walter A. , Joie, Renaud La , Mundada, Nidhi S. , Murray, Melissa E. , Nudelman, Kelly , Toga, Arthur W. , Vemuri, Prashanthi , Atri, Alireza , Day, Gregory S. , Duara, Ranjan , Honig, Lawrence S. , Jones, David T. , Masdeu, Joseph C , Musiek, Erik , Sha, Sharon J. , Turner, Raymond Scott , Wingo, Thomas S , Wolk, David A. , Womack, Kyle , Carrillo, María C. , Rabinovici, Gil D.

Alzheimer's & Dementia | December 25, 2023 | Volume: 19 | Issue: S24 | Pages: No page available

10.1002/alz.083140 Get It

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.
Cognitive Clusters of Early‐onset non‐Alzheimer’s disease
Kim, Hee Jin , Lane, Kathleen A. , Gao, Sujuan , Hammers, Dustin B. , Aisen, Paul , Eloyan, Ani , Iaccarino, Leo, Kramer, Joel H. , Rumbaugh, Malia, Soleimani‐Meigooni, David N. , Taurone, Alexander, Duara, Ranjan , Graff‐Radford, Neill R. , Masdeu, Joseph C. , Mendez, Mario F. , Onyike, Chiadi U. , Riddle, Meghan C., Rogalskı, Emily , Salloway, Stephen , Sha, Sharon, Dickerson, Brad C., Apostolova, Liana G. , Hammers, Dustin B , Logan, Paige E. , Dage, Jeffrey L. , Foroud, Tatiana , Grinberg, Lea T. , Jack, Clifford R. , Koeppe, Robert A. , Kukull, Walter A. , Joie, Renaud La , Mundada, Nidhi S. , Murray, Melissa E. , Nudelman, Kelly , Toga, Arthur W. , Vemuri, Prashanthi , Atri, Alireza , Day, Gregory S. , Duara, Ranjan , Honig, Lawrence S. , Jones, David T. , Masdeu, Joseph C , Musiek, Erik , Sha, Sharon J. , Turner, Raymond Scott , Wingo, Thomas S , Wolk, David A. , Carrillo, María C. , Rabinovici, Gil D.

Alzheimer's & Dementia | December 25, 2023 | Volume: 19 | Issue: S24 | Pages: No page available

10.1002/alz.083061 Get It

AbstractBackgroundApproximately 10‐25% of amnestic early‐onset dementia are negative for amyloid (Early‐onset non‐Alzheimer’s Disease, EOnonAD). EOnonAD is a heterogenous group with various etiologies. In order to better understand the traits of EOnonAD, we clustered amnestic EOnonAD individuals according to cognitive patterns.MethodCognitive data of 62 EOnonAD individuals from the Longitudinal Early‐onset AD study (LEADS) were Z‐normalized to 91 intact individuals after adjusting for age, sex, and education. This led to domain‐averaged composite Z‐scores for memory, language, speed/attention, visuospatial, and executive function. Cluster analysis using the Ward method on the residuals for the five composites was performed. We used Scree plot using the pseudo T‐squared to determine the optimal number of clusters. We compared demographics, imaging biomarkers (amyloid and tau PET SUVR, hippocampal volume), plasma (pTau231, Aß40, Aß42, glial fibrillary acidic protein, and neurofilament light chain (NfL)), and cerebrospinal fluid (CSF) biomarkers (Aß42/40, NfL, Neurogranin, Visinin‐like protein, YKL‐40, and Synaptosome Associated Protein 25) across the clusters after adjusting for age, sex, and education. We compared gray matter density of each EOnonAD cluster to controls (n = 84) using voxel‐wise multiple linear regressions in SPM12, adjusting for age, sex, education, and intracranial volume.ResultScree plot using the pseudo‐T‐squared suggested three clusters. Cluster 1 (38/62, 61.3%) was characterized by having the mildest cognitive impairment in all domains. Cluster 2 (19/62, 30.6%) was characterized by more severe memory and language impairment. Cluster 3 (5/62, 8.1%) was characterized by more severe impairment in speed/attention, visuospatial, and executive function (Table 1). Cluster 3 showed significantly higher NfL for both plasma (Cluster 1 vs 3, p<0.001; Cluster 2 vs 3, p < 0.004) and CSF (Cluster 1 vs 3, p = 0.001). Other biomarkers did not show significant difference (Table 1). Only Cluster 3 showed significant atrophy in the bilateral fronto‐parietal areas at p<0.01, uncorrected (Figure 1).ConclusionWe identified heterogeneity in cognitive patterns among amnestic EOnonAD individuals. Cluster 1 had mildest cognitive impairment; Cluster 2 had predominant impairment in memory and language; and Cluster 3 had predominant impairment in speed/attention, visuospatial, and executive function, with significant fronto‐parietal atrophy and high NfL indicating active neurodegeneration.
Digital pathology analysis reveals TDP‐43 pathology as a strong predictor of glial activation in Alzheimer’s disease
Frankenhauser, Isabelle , Peng, Zhongwei , Tranovich, Jessica F., Lesser, Elizabeth R. , Lachner, Christian , Ertekin‐Taner, Nilüfer , Duara, Ranjan , Graff‐Radford, Neill R. , Kouri, Naomi , Boon, Baayla D.C. , Labuzan, Sydney A. , Crook, Julia E. , Duara, Ranjan , Dickson, Dennis W. , Carter, Rickey E. , Murray, Melissa E.

Alzheimer's & Dementia | December 25, 2023 | Volume: 19 | Issue: S12 | Pages: No page available

10.1002/alz.080535 Get It

AbstractBackgroundGlial activation plays a critical role in Alzheimer’s disease (AD) pathogenesis and is associated with amyloid‐β plaques and neurofibrillary tangles composed of phosphorylated tau (phospho‐tau). With approximately 40%‐60% of AD cases having limbic‐predominant age‐related TDP‐43 encephalopathy neuropathologic change (LATE‐NC), TDP‐43 pathology has become more the rule than the exception in AD brains. However, the effect of LATE‐NC in AD‐related glial activation is unknown.MethodWe analyzed the effect of TDP‐43 pathology on glial activation in three AD subtypes: hippocampal sparing (HpSp) AD, typical AD, and limbic predominant AD. Twenty cases of each subtype (n = 60 total) were selected from the FLorida Autopsied Multi‐Ethnic (FLAME) cohort. Cases were immunohistochemically evaluated on serial sections of the hippocampus in the CA1 and subiculum subsectors, and superior temporal, inferior parietal, and mid‐frontal cortices with antibodies to CD68 (phagocytosis), GFAP (astrogliosis), GT‐38 (conformation‐specific AD‐type tau), 6F/3D (amyloid‐β), and phospho‐Serine 409/410 of TDP‐43 (pTDP‐43). Digital pathology was employed to quantify immunohistochemical staining. Multivariable regression modeling was utilized to understand the relationship between glial activation and AD pathologies.ResultThe level of glial activation, defined as % of immunoreactive surface area for CD68 and GFAP, was lowest in HpSp AD (0.54%, 13%), whereas typical AD (1.3%, 33%) and limbic predominant AD (1.3%, 30%) had similar levels suggesting a ceiling effect, or plateau, of gliosis levels (both p<0.001). HpSp AD was more often male (p<0.001) and younger at disease onset (p<0.001) compared to both typical AD and limbic predominant AD. Multivariable regression modeling of CD68 (subiculum R2 = 0.60) identified advanced tau to be a significant predictor of CD68 in all brain regions. LATE‐NC stage predicted increased CD68 levels in limbic brain regions. Multivariable regression modeling of GFAP (CA1 R2 = 0.60) showed that Aβ was the strongest predictor of astrogliosis in CA1 and subiculum (p<0.001). Advanced tau in CA1 and parietal cortex, LATE‐NC in subiculum and temporal cortex, and APOE4 genotype in CA1 predicted a significant increase in GFAP.ConclusionThese findings highlight the significant role TDP‐43 pathology plays in affecting the microenvironment and interplay between neuroinflammation and neurodegeneration and have important implications for therapeutic strategies in AD with co‐morbid LATE‐NC.
Distinct amyloid‐β deposits inversely correlate with glial activation and tangles in Alzheimer’s disease subtypes
Peng, Zhongwei , Tranovich, Jessica F., Frankenhauser, Isabelle , Lincoln, Sarah, Lachner, Christian , Ertekin‐Taner, Nilüfer , Duara, Ranjan , Graff‐Radford, Neill R. , Boon, Baayla D.C. , Kouri, Naomi , Labuzan, Sydney A. , Duara, Ranjan , Dickson, Dennis W. , Murray, Melissa E.

Alzheimer's & Dementia | December 25, 2023 | Volume: 19 | Issue: S12 | Pages: No page available

10.1002/alz.073357 Get It

AbstractBackgroundThe coarse‐grained plaque is a biochemically and morphologically distinct amyloid‐β (Aβ) deposit that was discovered in clinically‐defined atypical Alzheimer’s disease (AD). Unlike other Aβ deposits, this plaque is not observed in cognitively normal people. This study investigates the hypothesis that the coarse‐grained plaque is distinctly associated with AD neuropathologic change and glial activation within the context of AD subtypes.MethodSixty AD cases from the FLorida Autopsied Multi‐Ethnic (FLAME) cohort were assessed. We included 20 hippocampal sparing (HpSp) AD, 20 typical AD, and 20 limbic predominant AD. Immunohistochemistry was performed on the middle frontal, inferior temporal, and inferior parietal cortex for AD neuropathology (Aβ [6F/3D], phospho‐tau [AT8], tau [GT38]) and glial activation (CD68 [KP1] and GFAP). Digital pathology was used to quantify burden. Thioflavin‐S tangle counts were performed at time of neuropathologic diagnosis. Distinct deposit types, including classic cored plaques, coarse‐grained plaques, cerebral amyloid angiopathy (CAA)‐Type 1, and CAA‐Type 2, were semi‐quantitatively scored on Aβ (Fig. 1). Correlations between demographic, clinical, and neuropathologic characteristics were assessed using Spearman rho analysis and reported if p<0.05. An independent cohort of ∼100 HpSp AD cases will be assessed to validate initial findings.ResultIn the frontal cortex of HpSp AD, higher scores of classic cored plaques correlated with older age at onset and death, non‐APOE ε4 carriership, and less CAA‐Type 1 and Type 2 (Fig. 2). On the contrary, the severity of coarse‐grained plaques correlated with a younger age at onset and death, APOE ε4 carriership, higher scores for CAA‐Type 1, CAA‐Type 2, and increased burden of Aβ, GFAP, and CD68. Classic cored plaques correlated negatively with phospho‐tau and tau, whereas coarse‐grained plaques correlated positively with phospho‐tau, tau, and tangles. The two deposit types were negatively correlated with each other. Correlations were weaker but showed similar trends in other AD subtypes (Fig. 2) and regions.ConclusionWithin HpSp AD, classic cored and coarse‐grained plaques show distinct correlations with glial activation, (phospho‐)tau, and tangles. These results suggest opposite directions of association for these deposits on AD neuropathologic change that may impact clinical symptoms. These findings are relevant to therapies targeting overall Aβ pathology.
Focal Cortical Patterns in Hippocampal Sparing AD Reveal Significant Clinical Differences (S48.001)
Duara, Ranjan , Liesinger, Amanda M., Petersen, Ronald, Graff‐Radford, Neill R. , Murray, Melissa E. , Duara, Ranjan , Cannon, Ashley , Ross, Owen A. , Petersen, Ronald, Boeve, Bradley F. , Dickson, Dennis W.

Neurology | December 7, 2023 | Volume: 82 | Issue: 10_supplement | Pages: No page available

10.1212/wnl.82.10_supplement.s48.001 Get It

The Sporadic Early‐onset Alzheimer's Disease Signature Of Atrophy: Preliminary Findings From The Longitudinal Early‐onset Alzheimer's Disease Study (LEADS) Cohort
Touroutoglou, Alexandra , Katsumi, Yuta , Brickhouse, Michael , Zaitsev, Alexander, Eckbo, Ryan, Aisen, Paul, Dage, Jeffrey L. , Eloyan, Ani , Ghetti, Bernardino , Griffin, Percy , Hammers, Dustin B. , Jack, Clifford R. , Kramer, Joel H. , Joie, Renaud La , Mundada, Nidhi S. , Kukull, Walter A. , Polsinelli, Angelina J. , Rumbaugh, Malia, Soleimani‐Meigooni, David N. , Toga, Arthur W. , Vemuri, Prashanthi , Day, Gregory S. , Duara, Ranjan , Graff‐Radford, Neill R. , Masdeu, Joseph C. , Mendez, Mario F. , Onyike, Chiadi U. , Riddle, Meghan , Rogalskı, Emily , Salloway, Stephen , Sha, Sharon, Turner, Raymond Scott , Wingo, Thomas S. , Carrillo, María C. , Rabinovici, Gil D. , Apostolova, Liana G. , Jack, Clifford R , Vemuri, Prashanthi , Day, Gregory S , La Joie, Renaud , Rabinovici, Gil D , Ghetti, Bernardino F , Wingo, Thomas S , Dage, Jeffrey L , Beckett, Laurel , Foroud, Tatiana , Hammers, Dustin B , Iaccarino, Leonardo , Koeppe, Robert A. , Murray, Melissa E. , Nudelman, Kelly , Atri, Alireza , Duara, Ranjan , Honig, Lawrence S. , Jones, David T. , Masdeu, Joseph C , Musiek, Erik , Sha, Sharon J. , Wolk, David A. , Womack, Kyle , Dickerson, Bradford Clark

Alzheimer's & Dementia | October 18, 2023 | Volume: 19 | Issue: S9 | Pages: No page available

10.1002/alz.13466 | PMID 37850549 Get It

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.
Etiology of White Matter Hyperintensities in Autosomal Dominant and Sporadic Alzheimer Disease
Shirzadi, Zahra , Schultz, Stephanie A. , Yau, Wai‐Ying Wendy , Fitzpatrick, Colleen , Levin, Raina, Kantarci, Kejal , Preboske, Gregory M., Jack, Clifford R. , Farlow, Martin R. , Hassenstab, Jason , Morris, John C. , Xiong, Chengjie , Levey, Allan I. , Gordon, Brian A. , Salloway, Stephen , Perrin, Richard J. , Xiong, Chengjie , Fox, Nick C. , Goate, Alison , Day, Gregory S. , Chui, Helena C., Berman, Sarah , Mori, Hiroshi , Ruthirakuhan, Myuri , Wu, Che‐Yuan , Sohrabi, Hamid R. , Martins, Ralph N. , Johnson, Keith A. , Greenberg, Steven M. , Chhatwal, Jasmeer P. , Initiative, Dominantly Inherited Alzheimer Network and the Alzheimer’s Disease Neuroimaging, Weiner, Michael W. , Aisen, Paul, Petersen, Ronald , Jack, Clifford R., Jagust, William J. , Trojanowki, John Q., Morris, John C., Shaw, Leslie M. , Khachaturian, Zaven S., Carrillo, Maria, Potter, William Z., Bernard, Marie , Jackson, Jonathan , Masliah, Eliezer , Masterman, Donna, Okonkwo, Ozioma C. , Ryan, Laurie, Silverberg, Nina, Fleisher, Adam , Sacrey, Diana Truran, Fockler, Juliet , Conti, Cat, Jin, Chengshi , Nosheny, Rachel L. , Ashford, Miriam T. , Flenniken, Derek , Kormos, Adrienne, Montine, Tom, Raman, Rema , Jiménez, Gustavo , Gessert, Devon, Salazar, Jennifer, Zimmerman, Caileigh, Cabrera, Yuliana, Walter, Sarah , Miller, Garrett, Coker, Godfrey, Clanton, Taylor, Hergesheimer, Lindsey, Adegoke, Olusegun, Mahboubi, Payam, Moore, Shelley, Pizzola, Jeremy, Shaffer, Elizabeth , Sloan, Brittany, Forghanian-Arani, Arvin, Borowski, Bret, Ward, Chad, Gunter, Jeff, Jahanshad, Neda , DeCarli, Charles, Knaack, Alexander , Chen, Stephanie Rossi, Choe, Mark, Crawford, Karen , Reiman, Eric M. , Mathis, Chet, Landau, Susan, Cairns, Nigel J., Householder, Erin, Franklin, Erin , Bernhardt, Haley, Taylor‐Reinwald, Lisa, Korecka, Magdalena , Figurski, Michael, Neu, Scott, Apostolova, Liana G. , Foroud, Tatiana M., Faber, Kelley, Wilmes, Kristi, Thal, Leon J., Lind, Betty, Crissey, Rachel, Carter, Raina, Dolen, Sara, Schneider, Lon S. , Pawluczyk, Sonia, Becerra, Mauricio, Teodoro, Liberty, Dagerman, Karen, Spann, Bryan M., Brewer, James B., Vanderswag, Helen, Ziolkowski, Jaimie, Heidebrink, Judith L. , Zbizek-Nulph, Lisa, Mason, Sara S., Albers, Colleen S., Johnson, Kris , Villaneuva-Meyer, Javier, Pavlik, Valory , Pacini, Nathaniel, Lamb, Ashley, Kass, Joseph S. , Doody, Rachelle S., Shibley, Victoria, Chowdhury, Munir , Rountree, Susan, Dang, Mimi, Mintz, Akiva , Winkfield, David, Carroll, Maria , Stobbs-Cucchi, Georgia , Oliver, Angela , Creech, Mary L., Mintun, Mark A., Schneider, Stacy, Geldmacher, David , Love, Marissa Natelson , Griffith, Randall, Clark, David, Brockington, John, Marson, Daniel , Grossman, Hillel, Goldstein, Martin , Mitsis, Effie, Samuels, Patricia, Duara, Ranjan , Greig‐Custo, Maria T., Rodriguez, Rosemarie, Albert, Marilyn, Onyike, Chiadi, Farrington, Leonie, Rudow, Scott, Brichko, Rottislav, Kielb, Stephanie , Smith, Amanda , Raj, Balebail Ashok, Fargher, Kristin, Shulman, Melanie , Faustin, Arline , Rao, Julia, Castro, Karen M. , Ulysse, Anaztasia, Chen, Shannon, Sheikh, Mohammed O., Singleton-Garvin, Jamika, Doraiswamy, P. Murali , Petrella, Jeffrey R. , James, Olga, Borges‐Neto, Salvador , Karlawish, Jason , Vaishnavi, Sanjeev , Clark, Christopher M. , Arnold, Steven E. , Smith, Charles D. , Khouli, Riham El , Raslau, Flavius D., Oakley, MaryAnn, Simpson, Donna M., Martin, Kim, Kowalski, Nancy, Keltz, Melanie, Goldstein, Bonnie S., Makino, Kelly M., Ismail, M. Saleem , Brand, Connie, Thai, Gaby , Pierce, Aimee, Witbracht, Megan , Mathews, Dana, Quiceno, Mary , Hajjar, Ihab , Cellar, Janet S., Swerdlow, Russell H. , Kremen, Sarah , Tingus, Kathleen, Lu, Po H. , Bartzokis, George, Woo, Ellen, Graff‐Radford, Neill R. , Parfitt, Francine, Poki-Walker, Kim, Hake, Ann Marie , Matthews, Brandy R., Herring, Scott, Dyck, Christopher H. van , Mecca, Adam P. , Good, Susan P., MacAvoy, Martha G., Carson, Richard E. , Varma, Pradeep, Chertkow, Howard , Vaitekunis, Susan, Hosein, Chris, Mudge, Benita, Assaly, Michele, Rachinsky, Irina, Kertesz, Andrew, Drost, Dick, Rogers, John, Grant, Ian , Muse, Brittanie, Rogalskı, Emily , Robson, Jordan, Mesulam, M.‐Marsel, Kerwin, Diana , Wu, Chuang‐Kuo, Johnson, Nancy E., Lipowski, Kristine, Weıntraub, Sandra , Bonakdarpour, Borna , Hernando, Raymundo, Sarrael, Antero, Rosen, Howard J., Johnson, Kathleen, Reynolds, Brigid, Poe, Jessica, Sperling, Reisa A., Marshall, Gad A. , Yesavage, Jerome A. , Taylor, Joy L. , Chao, Steven, Coleman, Jaila, White, Jessica D. , Lane, Barton , Rosen, Allyson , Tinklenberg, Jared, Belden, Christine M. , Clark, Kelly, Zamrini, Edward , Sabbagh, Marwan, Kowall, Neil W. , Budson, Andrew E. , Ntekim, Oyonumo, Wolday, Saba, Khan, Javed , Nwulia, Evaristus , Nadarajah, Sheeba , Lerner, Alan J. , Ogrocki, Paula, Tatsuoka, Curtis , Fatica, Parianne, Olichney, John , Bates, Vernice, Capote, Horacio, Rainka, Michelle, Borrie, Michael, Lee, T‐Y, Asthana, Sanjay , Carlsson, Cynthia M., Perrin, Allison, Burke, Anna , Kataki, Maria , Hart, David , Zimmerman, Earl A. , Celmins, Dzintra, Smith, Karen Ekstam, Shim, Hyungsub , Nam, Ki Won , Schtulz, Susan K., Williamson, Jeff D. , Craft, Suzanne , Cleveland, Jo, Ott, Brian R. , Drake, Jonathan, Tremont, Geoffrey , Daiello, Lori A. , Ritter, Aaron, Bernick, Charles , Munic, Donna, O’Connell, Abigail, Mintzer, Jacobo , Wiliams, Arthur, Masdeu, Joseph C. , Shi, Jiong , Garcia, Angelica, Newhouse, Paul , Salloway, Steven, Malloy, Paul, Correia, Stephen , Kittur, Smita, Blank, Karen, Anderson, Karen, Flashman, Laura A. , Seltzer, Marc, Hynes, Mary L. , Santulli, Robert B. , Relkin, Norman , Chiang, Gloria, Lee, Athena, Lin, Michael, Ravdin, Lisa , Sood, Ajay, Blanchard, Kimberly S., Fleischman, Debra , Varon, Daniel, Greig, Maria T., Martin, Kimberly S., Reist, Christopher , Sadowsky, Carl, Villena, Teresa, Rosen, Howard, Peskind, Elaine R. , Li, Gail, Vöglein, Jonathan , Méndez, Patricio Chrem, Ikonomović, Snežana, Nadkarni, Neelesh K. , Ramírez, Laura, Leon, Yudy Milena, Ramos, Cláudia , Alzate, Diana, Baena, Ana , Londono, Natalia, Laske, Christoph , Kuder-Buletta, Elke, Gräber‐Sultan, Susanne, Preische, Oliver, Hofmann, Anna, Ishii, Kenji , Senda, Michio , Riddle, Meghan C., Menard, William, Bodge, Courtney, Surti, Mustafa, Sanchez-Gonzalez, VJ, Orozco-Barajas, Maribel, Esposito, Bianca, Fernanadez, Victoria, Jerome, Gina, Herries, Elizabeth, Seyfried, Nicholas T. , Bechara, Jacob , Chen, Allison , Hantler, Nancy, Hornbeck, Russ C. , Jarman, Steve, Keefe, Sarah , Koudelis, Deborah, Massoumzadeh, Parinaz , Nicklaus, Joyce , Pulizos, Christine, Mishall, Sheetal, Sabaredzovic, Edita, Deng, Emily , Candela, Madison, Smith, Hunter , Scott, Jalen , Gremminger, Emily, Ma, Yinjiao , Bui, Ryan , Lu, Ruijin , Daniels, Alisha , Courtney, Laura, Supnet, Charlene , Xu, Jinbin , Ringman, John M. , Barthélemy, Nicolas R. , Jack, Clifford R , Gordon, Brian A , Kantarci, Kejal , Day, Gregory S , Vöglein, Jonathan , Xiong, Chengjie , Fox, Nick C , Hassenstab, Jason , Morris, John C , Goate, Alison M , Supnet-Bell, Charlene , Berman, Sarah , Levey, Allan I , Kremen, Sarah , Joseph‐Mathurin, Nelly , Jucker, Mathias , Xiong, Chengjie , Karch, Celeste M. , Schofield, Peter R. , McDade, Eric , Cruchaga, Carlos , Allegri, Ricardo , Koeppe, Robert A. , Chui, Helena C. , Sánchez‐Valle, Raquel , Lee, Jae‐Hong , Rosa-Neto, Pedro , Swardfager, Walter , Benzinger, Tammie L.S. , Bateman, Randall J. , Sperling, Reisa Anne , Schultz, Aaron P. , Initiative, Dominantly Inherited Alzheimer Network and the Alzheimer’s Disease Neuroimaging, Jack, Clifford R., Toga, Arthur W. , Beckett, Laurel , Green, Robert C. , Saykin, Andrew J. , Morris, John C., Barnes, Lisa L. , González, Hector, Ho, Carole , Hsiao, John , Veitch, Dallas P. , Neuhaus, John M , Rafii, Michael S. , Donohue, Michael , Smith, Stephanie R. , Harvey, Danielle , Arani, Arvin , Schwarz, Christopher G. , Jones, David T. , Senjem, Matthew L. , Vemuri, Prashanthi , Reid, Robert I. , Malone, Ian B. , Thompson, Paul M. , Thomopoulos, Sophia I. , Nir, Talia M. , Fletcher, Evan M. , Tosun, Duygu , Yushkevich, Paul A. , Das, Sandhitsu R. , Chen, Kewei , Mathis, Chet, Nho, Kwangsik T. , Risacher, Shannon L. , Shen, Li , Nudelman, Kelly , Silbert, Lisa C. , Kaye, Jeffrey , Carter, Raina, Quinn, Joseph F. , Lord, Joanne L. , Knopman, David S. , Stern, Yaakov , Honig, Lawrence S. , Ances, Beau M. , Goldstein, Martin A., Greenberg, Jonathan, Shah, Raj C. , Lamar, Melissa , Duara, Ranjan , Sadowski, Martin , Wısnıewskı, Thomas , Wong, Terence Z. , Wolk, David A. , Jicha, Gregory A. , López, Oscar L. , Porsteinsson, Anton P. , Yanez, Beatriz, Sosa, Elizabeth M. , Kelley, Brendan , Nguyen, Trung Dung , Womack, Kyle , Lah, James J. , Burns, Jeffrey M. , Brooks, William Miles , Silverman, Daniel H.S. , Teng, Edmond , Brosch, Jared R. , Black, Sandra E. , Stefanovic, Bojana , Heyn, Chris , Hsiung, Ging‐Yuek Robin , Kim, Ellen , Sossi, Vesna , Feldman, Howard , Finger, Elizabeth C. , Pasternak, Stephen , Miller, Bruce L. , Perry, David C. , Turner, Raymond Scott , MCCann, Kelly, Sperling, Reisa A., Atri, Alireza , Killiany, Ronald , Stern, Robert A. , Mez, Jesse , Obisesan, Thomas O. , Maillard, Pauline , Carmichael, Owen , Bartha, Robert , Johnson, Sterling C. , Carlsson, Cynthia M. , Scharre, Douglas W. , Tarawneh, Rawan M. , Miller, Del D. , Ponto, Laura L. Boles , Koleva, Hristina , Yang, Mia , Sink, Kaycee M. , Masdeu, Joseph C , Potkin, Steven G. , Salloway, Steve , Pearlson, Godfrey D. , Sood, Ajay, Arfanakis, Konstantinos , Varón, Daniel , Martínez, Walter Fabián , Petrie, Eric C. , Noble, James M. , Surace, Ezequiel , Lopera, Francisco Javier , Aguillon, David , Londono, Natalia, Moreno, Sonia, Ikeuchi, Takeshi , Kasuga, Kensaku , Niimi, Yoshiki , Cash, David M. , Roh, Jee Hoon , Takada, Leonel Tadao , Renton, Alan , Marsh, Jacob A. , Llibre‐Guerra, Jorge J. , Johnson, Erik C. B. , Brooks, William S. , Chen, Charles , Flores, Shaney , McCullough, Austin , McKay, Nicole S. , Wáng, Qīng , Candela, Madison, Hobbs, Diana A. , Wang, Peter , Xu, Xiong, Li, Yan , Sosa, Ana Luisa , Smith, Jennifer A.

JAMA Neurology | October 16, 2023 | Volume: 80 | Issue: 12 | Pages: 1353

10.1001/jamaneurol.2023.3618 | PMID 37843849 Get It

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.
Pathogenic variants in the Longitudinal Early‐onset Alzheimer's Disease Study cohort
Jackson, Trever, Rumbaugh, Malia, Eloyan, Ani , Abreu, Marco , Dage, Jeffrey L. , Snoddy, Casey, Faber, Kelley , Hammers, Dustin B. , Taurone, Alexander, Thangarajah, Maryanne, Aisen, Paul, Kramer, Joel H. , Kukull, Walter A. , Vemuri, Prashanthi , Day, Gregory S. , Duara, Ranjan , Graff‐Radford, Neill R. , Masdeu, Joseph C. , Mendez, Mario F. , Onyike, Chiadi U. , Riddle, Meghan , Rogalskı, Emily , Salloway, Stephen , Sha, Sharon J. , Turner, Raymond Scott , Wingo, Thomas S. , Carrillo, María C. , Rabinovici, Gil D. , Apostolova, Liana G. , Vemuri, Prashanthi , Day, Gregory S , Rabinovici, Gil D , Wingo, Thomas S , Dage, Jeffrey L , Nudelman, Kelly , Foroud, Tatiana , Hammers, Dustin B , Beckett, Laurel , Koeppe, Robert A. , Murray, Melissa E. , Toga, Arthur W. , Atri, Alireza , Duara, Ranjan , Honig, Lawrence S. , Jones, David T. , Masdeu, Joseph C , Musiek, Erik , Wolk, David A. , Dickerson, Bradford Clark

Alzheimer's & Dementia | October 7, 2023 | Volume: 19 | Issue: S9 | Pages: No page available

10.1002/alz.13482 | PMID 37801072 Get It

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