Browsing by Author "Ances, Beau M."
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Item Comparing cortical signatures of atrophy between late-onset and autosomal dominant Alzheimer disease(Elsevier, 2020) Dincer, Aylin; Gordon, Brian A.; Hari-Raj, Amrita; Keefe, Sarah J.; Flores, Shaney; McKay, Nicole S.; Paulick, Angela M.; Shady Lewis, Kristine E.; Feldman, Rebecca L.; Hornbeck, Russ C.; Allegri, Ricardo; Ances, Beau M.; Berman, Sarah B.; Brickman, Adam M.; Brooks, William S.; Cash, David M.; Chhatwal, Jasmeer P.; Farlow, Martin R.; la Fougère, Christian; Fox, Nick C.; Fulham, Michael J.; Jack, Clifford R., Jr.; Joseph-Mathurin, Nelly; Karch, Celeste M.; Lee, Athene; Levin, Johannes; Masters, Colin L.; McDade, Eric M.; Oh, Hwamee; Perrin, Richard J.; Raji, Cyrus; Salloway, Stephen P.; Schofield, Peter R.; Su, Yi; Villemagne, Victor L.; Wang, Qing; Weiner, Michael W.; Xiong, Chengjie; Yakushev, Igor; Morris, John C.; Bateman, Randall J.; Benzinger, Tammie L.S.; Neurology, School of MedicineDefining a signature of cortical regions of interest preferentially affected by Alzheimer disease (AD) pathology may offer improved sensitivity to early AD compared to hippocampal volume or mesial temporal lobe alone. Since late-onset Alzheimer disease (LOAD) participants tend to have age-related comorbidities, the younger-onset age in autosomal dominant AD (ADAD) may provide a more idealized model of cortical thinning in AD. To test this, the goals of this study were to compare the degree of overlap between the ADAD and LOAD cortical thinning maps and to evaluate the ability of the ADAD cortical signature regions to predict early pathological changes in cognitively normal individuals. We defined and analyzed the LOAD cortical maps of cortical thickness in 588 participants from the Knight Alzheimer Disease Research Center (Knight ADRC) and the ADAD cortical maps in 269 participants from the Dominantly Inherited Alzheimer Network (DIAN) observational study. Both cohorts were divided into three groups: cognitively normal controls (nADRC = 381; nDIAN = 145), preclinical (nADRC = 153; nDIAN = 76), and cognitively impaired (nADRC = 54; nDIAN = 48). Both cohorts underwent clinical assessments, 3T MRI, and amyloid PET imaging with either 11C-Pittsburgh compound B or 18F-florbetapir. To generate cortical signature maps of cortical thickness, we performed a vertex-wise analysis between the cognitively normal controls and impaired groups within each cohort using six increasingly conservative statistical thresholds to determine significance. The optimal cortical map among the six statistical thresholds was determined from a receiver operating characteristic analysis testing the performance of each map in discriminating between the cognitively normal controls and preclinical groups. We then performed within-cohort and cross-cohort (e.g. ADAD maps evaluated in the Knight ADRC cohort) analyses to examine the sensitivity of the optimal cortical signature maps to the amyloid levels using only the cognitively normal individuals (cognitively normal controls and preclinical groups) in comparison to hippocampal volume. We found the optimal cortical signature maps were sensitive to early increases in amyloid for the asymptomatic individuals within their respective cohorts and were significant beyond the inclusion of hippocampus volume, but the cortical signature maps performed poorly when analyzing across cohorts. These results suggest the cortical signature maps are a useful MRI biomarker of early AD-related neurodegeneration in preclinical individuals and the pattern of decline differs between LOAD and ADAD.Item Comparison of amyloid accumulation between Down syndrome and autosomal-dominant Alzheimer disease(Wiley, 2022) Boerwinkle, Anna H.; Gordon, Brian A.; Wisch, Julie K.; Flores, Shaney; Henson, Rachel L.; Butt, Omar Hameed; Chen, Charles D.; Benzinger, Tammie L. S.; Fagan, Anne M.; Handen, Benjamin L.; Christian, Bradley T.; Head, Elizabeth; Mapstone, Mark; Klunk, William E.; Rafii, Michael S.; O’Bryant, Sid E.; Price, Julie C.; Schupf, Nicole; Laymon, Charles M.; Krinsky-McHale, Sharon J.; Lai, Florence; Rosas, H. Diana; Hartley, Sigan L.; Zaman, Shahid; Lott, Ira T.; Silverman, Wayne; Brickman, Adam M.; Lee, Joseph H.; Allegri, Ricardo Francisco; Berman, Sarah; Chhatwal, Jasmeer P.; Chui, Helena C.; Cruchaga, Carlos; Farlow, Martin R.; Fox, Nick C.; Goate, Alison; Day, Gregory S.; Graff-Radford, Neill R.; Jucker, Mathias; Lee, Jae-Hong; Levin, Johannes; Martins, Ralph N.; Mori, Hiroshi; Perrin, Richard J.; Salloway, Stephen P.; Sanchez-Valle, Raquel; Schofield, Peter R.; Xiong, Chengjie; Karch, Celeste M.; Hassenstab, Jason J.; McDade, Eric; Bateman, Randall J.; Ances, Beau M.; Neurology, School of MedicineBackground: Given the triplication of chromosome 21 and the location of the amyloid precursor protein gene on chromosome 21, almost all adults with Down syndrome (DS) develop Alzheimer disease (AD)-like pathology and dementia during their lifetime. Comparing amyloid accumulation in DS to autosomal dominant AD (ADAD), another genetic form of AD, may improve our understanding of early AD pathology development. Method: We assessed amyloid positron emission tomography (PET) imaging in 192 participants with DS and 33 sibling controls from the Alzheimer’s Biomarker Consortium-Down Syndrome (ABC-DS) and 265 mutation-carriers (MC) and 169 familial controls from the Dominantly Inherited Alzheimer Network (DIAN) (Table 1). We calculated regional standard uptake value ratios (SUVR) using a cerebellar cortex reference region and converted global amyloid burden SUVR to centiloids. We compared amyloid PET by cognitive status and estimated-years-to-symptom-onset (EYO). EYO was calculated for DIAN participants by subtracting their age from parental age of symptom onset and for ABC-DS participants by subtracting their age from 50.2 years, a published average age of symptom onset in a large sample of individuals with DS (Fortea et al., 2020). In a subset of participants, we assessed the relationship between amyloid PET and CSF Aβ42/40. Result: The relationship between CSF Aβ42/40 and amyloid PET was similar in DS and MC participants (Figure 1). We did not observe significant differences between MC and DS grouped by cognitive status (Figure 2). However, when assessed over EYO, global amyloid burden was significantly elevated in MC at EYO ≥ -23 but was not elevated in DS until EYO ≥ -15 (Figure 3). We observed early cortical and subcortical amyloid PET increases in both groups, but we also measured some regional differences in amyloid PET changes between MC and DS, specifically in the medial occipital region (Figure 4 and 5). Conclusion: These results demonstrate similarities in the relationship between amyloid biomarkers and the levels of amyloid accumulation in ADAD and DS. However, we also observed a 5-10 year delay and some regional differences in amyloid accumulation in DS. This is important for future clinical trials to consider when recruiting participants and determining treatment efficacy.Item Connectivity‐informed adaptive regularization for generalized outcomes(Wiley, 2021-02) Brzyski, Damian; Karas, Marta; Ances, Beau M.; Dzemidzic, Mario; Goñi, Joaquín; Randolph, Timothy W.; Harezlak, Jaroslaw; Neurology, School of MedicineOne of the challenging problems in neuroimaging is the principled incorporation of information from different imaging modalities. Data from each modality are frequently analyzed separately using, for instance, dimensionality reduction techniques, which result in a loss of mutual information. We propose a novel regularization method, generalized ridgified Partially Empirical Eigenvectors for Regression (griPEER), to estimate associations between the brain structure features and a scalar outcome within the generalized linear regression framework. griPEER improves the regression coefficient estimation by providing a principled approach to use external information from the structural brain connectivity. Specifically, we incorporate a penalty term, derived from the structural connectivity Laplacian matrix, in the penalized generalized linear regression. In this work, we address both theoretical and computational issues and demonstrate the robustness of our method despite incomplete information about the structural brain connectivity. In addition, we also provide a significance testing procedure for performing inference on the estimated coefficients. Finally, griPEER is evaluated both in extensive simulation studies and using clinical data to classify HIV+ and HIV− individuals.Item Longitudinal Accumulation of Cerebral Microhemorrhages in Dominantly Inherited Alzheimer Disease(American Academy of Neurology, 2021-03-23) Joseph-Mathurin, Nelly; Wang, Guoqiao; Kantarci, Kejal; Jack, Clifford R., Jr.; McDade, Eric; Hassenstab, Jason; Blazey, Tyler M.; Gordon, Brian A.; Su, Yi; Chen, Gengsheng; Massoumzadeh, Parinaz; Hornbeck, Russ C.; Allegri, Ricardo F.; Ances, Beau M.; Berman, Sarah B.; Brickman, Adam M.; Brooks, William S.; Cash, David M.; Chhatwal, Jasmeer P.; Chui, Helena C.; Correia, Stephen; Cruchaga, Carlos; Farlow, Martin R.; Fox, Nick C.; Fulham, Michael; Ghetti, Bernardino; Graff-Radford, Neill R.; Johnson, Keith A.; Karch, Celeste M.; Laske, Christoph; Lee, Athene K.W.; Levin, Johannes; Masters, Colin L.; Noble, James M.; O’Connor, Antoinette; Perrin, Richard J.; Preboske, Gregory M.; Ringman, John M.; Rowe, Christopher C.; Salloway, Stephen; Saykin, Andrew J.; Schofield, Peter R.; Shimada, Hiroyuki; Shoji, Mikio; Suzuki, Kazushi; Villemagne, Victor L.; Xiong, Chengjie; Yakushev, Igor; Morris, John C.; Bateman, Randall J.; Benzinger, Tammie L.S.; Pathology and Laboratory Medicine, School of MedicineObjective: To investigate the inherent clinical risks associated with the presence of cerebral microhemorrhages (CMHs) or cerebral microbleeds and characterize individuals at high risk for developing hemorrhagic amyloid-related imaging abnormality (ARIA-H), we longitudinally evaluated families with dominantly inherited Alzheimer disease (DIAD). Methods: Mutation carriers (n = 310) and noncarriers (n = 201) underwent neuroimaging, including gradient echo MRI sequences to detect CMHs, and neuropsychological and clinical assessments. Cross-sectional and longitudinal analyses evaluated relationships between CMHs and neuroimaging and clinical markers of disease. Results: Three percent of noncarriers and 8% of carriers developed CMHs primarily located in lobar areas. Carriers with CMHs were older, had higher diastolic blood pressure and Hachinski ischemic scores, and more clinical, cognitive, and motor impairments than those without CMHs. APOE ε4 status was not associated with the prevalence or incidence of CMHs. Prevalent or incident CMHs predicted faster change in Clinical Dementia Rating although not composite cognitive measure, cortical thickness, hippocampal volume, or white matter lesions. Critically, the presence of 2 or more CMHs was associated with a significant risk for development of additional CMHs over time (8.95 ± 10.04 per year). Conclusion: Our study highlights factors associated with the development of CMHs in individuals with DIAD. CMHs are a part of the underlying disease process in DIAD and are significantly associated with dementia. This highlights that in participants in treatment trials exposed to drugs, which carry the risk of ARIA-H as a complication, it may be challenging to separate natural incidence of CMHs from drug-related CMHs.Item Multimodal brain age estimates relate to Alzheimer disease biomarkers and cognition in early stages: a cross-sectional observational study(eLife Sciences, 2023-01-06) Millar, Peter R.; Gordon, Brian A.; Luckett, Patrick H.; Benzinger, Tammie L. S.; Cruchaga, Carlos; Fagan, Anne M.; Hassenstab, Jason J.; Perrin, Richard J.; Schindler, Suzanne E.; Allegri, Ricardo F.; Day, Gregory S.; Farlow, Martin R.; Mori, Hiroshi; Nübling, Georg; The Dominantly Inherited Alzheimer Network; Bateman, Randall J.; Morris, John C.; Ances, Beau M.; Neurology, School of MedicineBackground: Estimates of 'brain-predicted age' quantify apparent brain age compared to normative trajectories of neuroimaging features. The brain age gap (BAG) between predicted and chronological age is elevated in symptomatic Alzheimer disease (AD) but has not been well explored in presymptomatic AD. Prior studies have typically modeled BAG with structural MRI, but more recently other modalities, including functional connectivity (FC) and multimodal MRI, have been explored. Methods: We trained three models to predict age from FC, structural (S), or multimodal MRI (S+FC) in 390 amyloid-negative cognitively normal (CN/A-) participants (18-89 years old). In independent samples of 144 CN/A-, 154 CN/A+, and 154 cognitively impaired (CI; CDR > 0) participants, we tested relationships between BAG and AD biomarkers of amyloid and tau, as well as a global cognitive composite. Results: All models predicted age in the control training set, with the multimodal model outperforming the unimodal models. All three BAG estimates were significantly elevated in CI compared to controls. FC-BAG was significantly reduced in CN/A+ participants compared to CN/A-. In CI participants only, elevated S-BAG and S+FC BAG were associated with more advanced AD pathology and lower cognitive performance. Conclusions: Both FC-BAG and S-BAG are elevated in CI participants. However, FC and structural MRI also capture complementary signals. Specifically, FC-BAG may capture a unique biphasic response to presymptomatic AD pathology, while S-BAG may capture pathological progression and cognitive decline in the symptomatic stage. A multimodal age-prediction model improves sensitivity to healthy age differences.Item Partial Volume Correction in Quantitative Amyloid Imaging.(Elsevier, 2015-02-15) Su, Yi; Blazey, Tyler M.; Snyder, Abraham Z.; Raichle, Marcus E.; Marcus, Daniel S.; Ances, Beau M.; Bateman, Randall J.; Cairns, Nigel J.; Aldea, Patricia; Cash, Lisa; Christensen, Jon J.; Friedrichsen, Karl; Hornbeck, Russ C.; Farrar, Angela M.; Owen, Christopher J.; Mayeux, Richard; Brickman, Adam M.; Klunk, William; Price, Julie C.; Thompson, Paul M.; Ghetti, Bernardino; Saykin, Andrew J.; Sperling, Reisa A.; Johnson, Keith A.; Schofield, Peter R.; Buckles, Virginia; Morris, John C.; Benzinger, Tammie LS; Department of Pathology & Laboratory Medicine, IU School of MedicineAmyloid imaging is a valuable tool for research and diagnosis in dementing disorders. As positron emission tomography (PET) scanners have limited spatial resolution, measured signals are distorted by partial volume effects. Various techniques have been proposed for correcting partial volume effects, but there is no consensus as to whether these techniques are necessary in amyloid imaging, and, if so, how they should be implemented. We evaluated a two-component partial volume correction technique and a regional spread function technique using both simulated and human Pittsburgh compound B (PiB) PET imaging data. Both correction techniques compensated for partial volume effects and yielded improved detection of subtle changes in PiB retention. However, the regional spread function technique was more accurate in application to simulated data. Because PiB retention estimates depend on the correction technique, standardization is necessary to compare results across groups. Partial volume correction has sometimes been avoided because it increases the sensitivity to inaccuracy in image registration and segmentation. However, our results indicate that appropriate PVC may enhance our ability to detect changes in amyloid deposition.Item Pattern and degree of individual brain atrophy predicts dementia onset in dominantly inherited Alzheimer's disease(Wiley, 2021-07-05) Keret, Ophir; Staffaroni, Adam M.; Ringman, John M.; Cobigo, Yann; Goh, Sheng-Yang M.; Wolf, Amy; Allen, Isabel Elaine; Salloway, Stephen; Chhatwal, Jasmeer; Brickman, Adam M.; Reyes-Dumeyer, Dolly; Bateman, Randal J.; Benzinger, Tammie L.S.; Morris, John C.; Ances, Beau M.; Joseph-Mathurin, Nelly; Perrin, Richard J.; Gordon, Brian A.; Levin, Johannes; Vöglein, Jonathan; Jucker, Mathias; la Fougère, Christian; Martins, Ralph N.; Sohrabi, Hamid R.; Taddei, Kevin; Villemagne, Victor L.; Schofield, Peter R.; Brooks, William S.; Fulham, Michael; Masters, Colin L.; Ghetti, Bernardino; Saykin, Andrew J.; Jack, Clifford R.; Graff-Radford, Neill R.; Weiner, Michael; Cash, David M.; Allegri, Ricardo F.; Chrem, Patricio; Yi, Su; Miller, Bruce L.; Rabinovici, Gil D.; Rosen, Howard J.; Pathology and Laboratory Medicine, School of MedicineIntroduction: Asymptomatic and mildly symptomatic dominantly inherited Alzheimer's disease mutation carriers (DIAD-MC) are ideal candidates for preventative treatment trials aimed at delaying or preventing dementia onset. Brain atrophy is an early feature of DIAD-MC and could help predict risk for dementia during trial enrollment. Methods: We created a dementia risk score by entering standardized gray-matter volumes from 231 DIAD-MC into a logistic regression to classify participants with and without dementia. The score's predictive utility was assessed using Cox models and receiver operating curves on a separate group of 65 DIAD-MC followed longitudinally. Results: Our risk score separated asymptomatic versus demented DIAD-MC with 96.4% (standard error = 0.02) and predicted conversion to dementia at next visit (hazard ratio = 1.32, 95% confidence interval [CI: 1.15, 1.49]) and within 2 years (area under the curve = 90.3%, 95% CI [82.3%-98.2%]) and improved prediction beyond established methods based on familial age of onset. Discussion: Individualized risk scores based on brain atrophy could be useful for establishing enrollment criteria and stratifying DIAD-MC participants for prevention trials.Item Plasma Total-Tau and Neurofilament Light Chain as Diagnostic Biomarkers of Alzheimer's Disease Dementia and Mild Cognitive Impairment in Adults with Down Syndrome(IOS Press, 2021) Petersen, Melissa E.; Rafii, Michael S.; Zhang, Fan; Hall, James; Julovich, David; Ances, Beau M.; Schupf, Nicole; Krinsky-McHale, Sharon J.; Mapstone, Mark; Silverman, Wayne; Lott, Ira; Klunk, William; Head, Elizabeth; Christian, Brad; Foroud, Tatiana; Lai, Florence; Rosas, H. Diana; Zaman, Shahid; Wang, Mei-Cheng; Tycko, Benjamin; Lee, Joseph H.; Handen, Benjamin; Hartley, Sigan; Fortea, Juan; O’Bryant, Sid; Alzheimer’s Biomarker Consortium – Down Syndrome (ABC-DS); Medical and Molecular Genetics, School of MedicineBackground: The need for diagnostic biomarkers of cognitive decline is particularly important among aging adults with Down syndrome (DS). Growing empirical support has identified the utility of plasma derived biomarkers among neurotypical adults with mild cognitive impairment (MCI) and Alzheimer's disease (AD); however, the application of such biomarkers has been limited among the DS population. Objective: This study aimed to investigate the cross-sectional diagnostic performance of plasma neurofilament light chain (Nf-L) and total-tau, individually and in combination among a cohort of DS adults. Methods: Plasma samples were analyzed from n = 305 (n = 225 cognitively stable (CS); n = 44 MCI-DS; n = 36 DS-AD) participants enrolled in the Alzheimer's Biomarker Consortium -Down Syndrome. Results: In distinguishing DS-AD participants from CS, Nf-L alone produced an AUC of 90%, total-tau alone reached 74%, and combined reached an AUC of 86%. When age and gender were included, AUC increased to 93%. Higher values of Nf-L, total-tau, and age were all shown to be associated with increased risk for DS-AD. When distinguishing MCI-DS participants from CS, Nf-L alone produced an AUC of 65%, while total-tau alone reached 56%. A combined model with Nf-L, total-tau, age, and gender produced an AUC of 87%. Both higher values in age and total-tau were found to increase risk for MCI-DS; Nf-L levels were not associated with increased risk for MCI-DS. Conclusion: Advanced assay techniques make total-tau and particularly Nf-L useful biomarkers of both AD pathology and clinical status in DS and have the potential to serve as outcome measures in clinical trials for future disease-modifying drugs.Item Preferential degradation of cognitive networks differentiates Alzheimer's disease from ageing(Oxford University Press, 2018-05-01) Chhatwal, Jasmeer P.; Schultz, Aaron P.; Johnson, Keith A.; Hedden, Trey; Jaimes, Sehily; Benzinger, Tammie L S.; Jack, Clifford; Ances, Beau M.; Ringman, John M.; Marcus, Daniel S.; Ghetti, Bernardino; Farlow, Martin R.; Danek, Adrian; Levin, Johannes; Yakushev, Igor; Laske, Christoph; Koeppe, Robert A.; Galasko, Douglas R.; Xiong, Chengjie; Masters, Colin L.; Schofield, Peter R.; Kinnunen, Kirsi M.; Salloway, Stephen; Martins, Ralph N.; McDade, Eric; Cairns, Nigel J.; Buckles, Virginia D.; Morris, John C.; Bateman, Randall; Sperling, Reisa A.; Pathology and Laboratory Medicine, School of MedicineConverging evidence from structural, metabolic and functional connectivity MRI suggests that neurodegenerative diseases, such as Alzheimer's disease, target specific neural networks. However, age-related network changes commonly co-occur with neuropathological cascades, limiting efforts to disentangle disease-specific alterations in network function from those associated with normal ageing. Here we elucidate the differential effects of ageing and Alzheimer's disease pathology through simultaneous analyses of two functional connectivity MRI datasets: (i) young participants harbouring highly-penetrant mutations leading to autosomal-dominant Alzheimer's disease from the Dominantly Inherited Alzheimer's Network (DIAN), an Alzheimer's disease cohort in which age-related comorbidities are minimal and likelihood of progression along an Alzheimer's disease trajectory is extremely high; and (ii) young and elderly participants from the Harvard Aging Brain Study, a cohort in which imaging biomarkers of amyloid burden and neurodegeneration can be used to disambiguate ageing alone from preclinical Alzheimer's disease. Consonant with prior reports, we observed the preferential degradation of cognitive (especially the default and dorsal attention networks) over motor and sensory networks in early autosomal-dominant Alzheimer's disease, and found that this distinctive degradation pattern was magnified in more advanced stages of disease. Importantly, a nascent form of the pattern observed across the autosomal-dominant Alzheimer's disease spectrum was also detectable in clinically normal elderly with clear biomarker evidence of Alzheimer's disease pathology (preclinical Alzheimer's disease). At the more granular level of individual connections between node pairs, we observed that connections within cognitive networks were preferentially targeted in Alzheimer's disease (with between network connections relatively spared), and that connections between positively coupled nodes (correlations) were preferentially degraded as compared to connections between negatively coupled nodes (anti-correlations). In contrast, ageing in the absence of Alzheimer's disease biomarkers was characterized by a far less network-specific degradation across cognitive and sensory networks, of between- and within-network connections, and of connections between positively and negatively coupled nodes. We go on to demonstrate that formalizing the differential patterns of network degradation in ageing and Alzheimer's disease may have the practical benefit of yielding connectivity measurements that highlight early Alzheimer's disease-related connectivity changes over those due to age-related processes. Together, the contrasting patterns of connectivity in Alzheimer's disease and ageing add to prior work arguing against Alzheimer's disease as a form of accelerated ageing, and suggest multi-network composite functional connectivity MRI metrics may be useful in the detection of early Alzheimer's disease-specific alterations co-occurring with age-related connectivity changes. More broadly, our findings are consistent with a specific pattern of network degradation associated with the spreading of Alzheimer's disease pathology within targeted neural networks.Item Presenilin-1 mutation position influences amyloidosis, small vessel disease, and dementia with disease stage(Wiley, 2024) Joseph-Mathurin, Nelly; Feldman, Rebecca L.; Lu, Ruijin; Shirzadi, Zahra; Toomer, Carmen; Saint Clair, Junie R.; Ma, Yinjiao; McKay, Nicole S.; Strain, Jeremy F.; Kilgore, Collin; Friedrichsen, Karl A.; Chen, Charles D.; Gordon, Brian A.; Chen, Gengsheng; Hornbeck, Russ C.; Massoumzadeh, Parinaz; McCullough, Austin A.; Wang, Qing; Li, Yan; Wang, Guoqiao; Keefe, Sarah J.; Schultz, Stephanie A.; Cruchaga, Carlos; Preboske, Gregory M.; Jack, Clifford R., Jr.; Llibre-Guerra, Jorge J.; Allegri, Ricardo F.; Ances, Beau M.; Berman, Sarah B.; Brooks, William S.; Cash, David M.; Day, Gregory S.; Fox, Nick C.; Fulham, Michael; Ghetti, Bernardino; Johnson, Keith A.; Jucker, Mathias; Klunk, William E.; la Fougère, Christian; Levin, Johannes; Niimi, Yoshiki; Oh, Hwamee; Perrin, Richard J.; Reischl, Gerald; Ringman, John M.; Saykin, Andrew J.; Schofield, Peter R.; Su, Yi; Supnet-Bell, Charlene; Vöglein, Jonathan; Yakushev, Igor; Brickman, Adam M.; Morris, John C.; McDade, Eric; Xiong, Chengjie; Bateman, Randall J.; Chhatwal, Jasmeer P.; Benzinger, Tammie L. S.; Dominantly Inherited Alzheimer Network; Pathology and Laboratory Medicine, School of MedicineIntroduction: Amyloidosis, including cerebral amyloid angiopathy, and markers of small vessel disease (SVD) vary across dominantly inherited Alzheimer's disease (DIAD) presenilin-1 (PSEN1) mutation carriers. We investigated how mutation position relative to codon 200 (pre-/postcodon 200) influences these pathologic features and dementia at different stages. Methods: Individuals from families with known PSEN1 mutations (n = 393) underwent neuroimaging and clinical assessments. We cross-sectionally evaluated regional Pittsburgh compound B-positron emission tomography uptake, magnetic resonance imaging markers of SVD (diffusion tensor imaging-based white matter injury, white matter hyperintensity volumes, and microhemorrhages), and cognition. Results: Postcodon 200 carriers had lower amyloid burden in all regions but worse markers of SVD and worse Clinical Dementia Rating® scores compared to precodon 200 carriers as a function of estimated years to symptom onset. Markers of SVD partially mediated the mutation position effects on clinical measures. Discussion: We demonstrated the genotypic variability behind spatiotemporal amyloidosis, SVD, and clinical presentation in DIAD, which may inform patient prognosis and clinical trials. Highlights: Mutation position influences Aβ burden, SVD, and dementia. PSEN1 pre-200 group had stronger associations between Aβ burden and disease stage. PSEN1 post-200 group had stronger associations between SVD markers and disease stage. PSEN1 post-200 group had worse dementia score than pre-200 in late disease stage. Diffusion tensor imaging-based SVD markers mediated mutation position effects on dementia in the late stage.