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Browsing by Author "Alzheimer's Disease Neuroimaging Initiative"
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Item The Alzheimer's Disease Neuroimaging Initiative 2 Biomarker Core: A review of progress and plans(Elsevier, 2015-07) Kang, Ju-Hee; Korecka, Magdalena; Figurski, Michal J.; Toledo, Jon B.; Blennow, Kaj; Zetterberg, Henrik; Waligorska, Teresa; Brylska, Magdalena; Fields, Leona; Shah, Nirali; Soares, Holly; Dean, Robert A.; Vanderstichele, Hugo; Petersen, Ronald C.; Aisen, Paul S.; Saykin, Andrew J.; Weiner, Michael W.; Trojanowski, John Q.; Shaw, Leslie M.; Alzheimer's Disease Neuroimaging Initiative; Department of Radiology and Imaging Sciences, School of MedicineINTRODUCTION: We describe Alzheimer's Disease Neuroimaging Initiative (ADNI) Biomarker Core progress including: the Biobank; cerebrospinal fluid (CSF) amyloid beta (Aβ1-42), t-tau, and p-tau181 analytical performance, definition of Alzheimer's disease (AD) profile for plaque, and tangle burden detection and increased risk for progression to AD; AD disease heterogeneity; progress in standardization; and new studies using ADNI biofluids. METHODS: Review publications authored or coauthored by ADNI Biomarker core faculty and selected non-ADNI studies to deepen the understanding and interpretation of CSF Aβ1-42, t-tau, and p-tau181 data. RESULTS: CSF AD biomarker measurements with the qualified AlzBio3 immunoassay detects neuropathologic AD hallmarks in preclinical and prodromal disease stages, based on CSF studies in non-ADNI living subjects followed by the autopsy confirmation of AD. Collaboration across ADNI cores generated the temporal ordering model of AD biomarkers varying across individuals because of genetic/environmental factors that increase/decrease resilience to AD pathologies. DISCUSSION: Further studies will refine this model and enable the use of biomarkers studied in ADNI clinically and in disease-modifying therapeutic trials.Item Building a Surface Atlas of Hippocampal Subfields from MRI Scans using FreeSurfer, FIRST and SPHARM(Institute of Electrical and Electronics Engineers, 2014-08) Cong, Shan; Rizkalla, Maher; Du, Eliza Y.; West, John; Risacher, Shannon; Saykin, Andrew J.; Shen, Li; Alzheimer's Disease Neuroimaging Initiative; Department of Medicine, IU School of MedicineThe hippocampus is widely studied with neuroimaging techniques given its importance in learning and memory and its potential as a biomarker for brain disorders such as Alzheimer's disease and epilepsy. However, its complex folding anatomy often presents analytical challenges. In particular, the critical hippocampal subfield information is usually ignored by hippocampal registration in detailed morphometric studies. Such an approach is thus inadequate to accurately characterize hippocampal morphometry and effectively identify hippocampal structural changes related to different conditions. To bridge this gap, we present our initial effort towards building a computational framework for subfield-guided hippocampal morphometry. This initial effort is focused on surface-based morphometry and aims to build a surface atlas of hippocampal subfields. Using the FreeSurfer software package, we obtain valuable hippocampal subfield information. Using the FIRST software package, we extract reliable hippocampal surface information. Using SPHARM, we develop an approach to create an atlas by mapping interpolated subfield information onto an average surface. The empirical result using ADNI data demonstrates the promise and good reproducibility of the proposed method.Item Examining the role of repeated test exposure over 12 months across ADNI protocols(Wiley, 2022) Hammers, Dustin B.; Duff, Kevin; Apostolova, Liana G.; Alzheimer's Disease Neuroimaging Initiative; Neurology, School of MedicineObjective: Changes to study protocols during longitudinal research may alter cognitive testing schedules over time. Unlike in prior Alzheimer's Disease Neuroimaging Initiative (ADNI) protocols, where testing occurred twice annually, participants enrolled in the ADNI-3 are no longer exposed to cognitive materials at 6 months. This may affect their 12-month performance relative to earlier ADNI cohorts, and potentially confounds data harmonization attempts between earlier and later ADNI protocols. Method: Using data from participants enrolled across multiple ADNI protocols, this study investigated whether test exposure during 6-month cognitive evaluation influenced scores on subsequent 12-month evaluation. Results: No interaction effects were observed between test exposure group and time at 12 months on cognitive performance. No improvements, and limited declines, were seen between baseline and 12-month follow-up scores on most measures. Conclusions: The 6-month testing session had minimal impact on 12-month performance in ADNI. Collapsing longitudinal data across ADNI protocols in future research appears appropriate.Item Genetic studies of quantitative MCI and AD phenotypes in ADNI: Progress, opportunities, and plans(Elsevier, 2015-07) Saykin, Andrew J.; Shen, Li; Yao, Xiaohui; Kim, Sungeun; Nho, Kwangsik; Risacher, Shannon L.; Ramanan, Vijay K.; Foroud, Tatiana M.; Faber, Kelly M.; Sarwar, Nadeem; Munsie, Leanne M.; Hu, Xiaolan; Soares, Holly D.; Potkin, Steven G.; Thompson, Paul M.; Kauwe, John S. K.; Kaddurah-Daouk, Rima; Green, Robert C.; Toga, Arthur W.; Weiner, Michael W.; Alzheimer's Disease Neuroimaging Initiative; Department of Radiology and Imaging Sciences, IU School of MedicineINTRODUCTION: Genetic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) have been crucial in advancing the understanding of Alzheimer's disease (AD) pathophysiology. Here, we provide an update on sample collection, scientific progress and opportunities, conceptual issues, and future plans. METHODS: Lymphoblastoid cell lines and DNA and RNA samples from blood have been collected and banked, and data and biosamples have been widely disseminated. To date, APOE genotyping, genome-wide association study (GWAS), and whole exome and whole genome sequencing data have been obtained and disseminated. RESULTS: ADNI genetic data have been downloaded thousands of times, and >300 publications have resulted, including reports of large-scale GWAS by consortia to which ADNI contributed. Many of the first applications of quantitative endophenotype association studies used ADNI data, including some of the earliest GWAS and pathway-based studies of biospecimen and imaging biomarkers, as well as memory and other clinical/cognitive variables. Other contributions include some of the first whole exome and whole genome sequencing data sets and reports in healthy controls, mild cognitive impairment, and AD. DISCUSSION: Numerous genetic susceptibility and protective markers for AD and disease biomarkers have been identified and replicated using ADNI data and have heavily implicated immune, mitochondrial, cell cycle/fate, and other biological processes. Early sequencing studies suggest that rare and structural variants are likely to account for significant additional phenotypic variation. Longitudinal analyses of transcriptomic, proteomic, metabolomic, and epigenomic changes will also further elucidate dynamic processes underlying preclinical and prodromal stages of disease. Integration of this unique collection of multiomics data within a systems biology framework will help to separate truly informative markers of early disease mechanisms and potential novel therapeutic targets from the vast background of less relevant biological processes. Fortunately, a broad swath of the scientific community has accepted this grand challenge.Item Genome-wide association study identifies susceptibility loci of brain atrophy to NFIA and ST18 in Alzheimer's disease(Elsevier, 2021-06) Kim, Bo-Hyun; Nho, Kwangsik; Lee, Jong-Min; Alzheimer's Disease Neuroimaging Initiative; Radiology & Imaging Sciences, School of MedicineTo identify genetic variants influencing cortical atrophy in Alzheimer's disease (AD), we performed genome-wide association studies (GWAS) of mean cortical thicknesses in 17 AD-related brain. In this study, we used neuroimaging and genetic data of 919 participants from the Alzheimer's Disease Neuroimaging Initiative cohort, which include 268 cognitively normal controls, 488 mild cognitive impairment, 163 AD individuals. We performed GWAS with 3,041,429 single nucleotide polymorphisms (SNPs) for cortical thickness. The results of GWAS indicated that rs10109716 in ST18 (ST18 C2H2C-type zinc finger transcription factor) and rs661526 in NFIA (nuclear factor I A) genes are significantly associated with mean cortical thicknesses of the left inferior frontal gyrus and left parahippocampal gyrus, respectively. The rs661526 regulates the expression levels of NFIA in the substantia nigra and frontal cortex and rs10109716 regulates the expression levels of ST18 in the thalamus. These results suggest a crucial role of identified genes for cortical atrophy and could provide further insights into the genetic basis of AD.Item Immunity gene IFITM3 variant: Relation to cognition and Alzheimer's disease pathology(Alzheimer’s Association, 2022-06-21) Pyun, Jung-Min; Park, Young Ho; Hodges, Angela; Jang, Jae-Won; Bice, Paula J.; Kim, SangYun; Saykin, Andrew J.; Nho, Kwangsik; AddNeuroMed Consortium; Alzheimer's Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineIntroduction: We investigated single-nucleotide polymorphisms (SNPs) in IFITM3, an innate immunity gene and modulator of amyloid beta in Alzheimer's disease (AD), for association with cognition and AD biomarkers. Methods: We used data from the Alzheimer's Disease Neuroimaging Initiative (ADNI; N = 1565) and AddNeuroMed (N = 633) as discovery and replication samples, respectively. We performed gene-based association analysis of SNPs in IFITM3 with cognitive performance and SNP-based association analysis with cognitive decline and amyloid, tau, and neurodegeneration biomarkers for AD. Results: Gene-based association analysis showed that IFITM3 was significantly associated with cognitive performance. Particularly, rs10751647 in IFITM3 was associated with less cognitive decline, less amyloid and tau burden, and less brain atrophy in ADNI. The association of rs10751647 with cognitive decline and brain atrophy was replicated in AddNeuroMed. Discussion: This suggests that rs10751647 in IFITM3 is associated with less vulnerability for cognitive decline and AD biomarkers, providing mechanistic insight regarding involvement of immunity and infection in AD. Highlights: IFITM3 is significantly associated with cognitive performance.rs10751647 in IFITM3 is associated with cognitive decline rates with replication.rs10751647 is associated with amyloid beta load, cerebrospinal fluid phosphorylated tau levels, and brain atrophy.rs10751647 is associated with IFITM3 expression levels in blood and brain.rs10751647 in IFITM3 is related to less vulnerability to Alzheimer's disease pathogenesis.Item Impact of the Alzheimer's Disease Neuroimaging Initiative, 2004 to 2014(Elsevier, 2015-07) Weiner, Michael W.; Veitch, Dallas P.; Aisen, Paul S.; Beckett, Laurel A.; Cairns, Nigel J.; Cedarbaum, Jesse; Donohue, Michael C.; Green, Robert C.; Harvey, Danielle; Jack, Clifford R.; Jagust, William; Morris, John C.; Petersen, Ronald C.; Saykin, Andrew J.; Shaw, Leslie; Thompson, Paul M.; Toga, Arthur W.; Trojanowski, John Q.; Alzheimer's Disease Neuroimaging Initiative; Department of Radiology and Imaging Sciences, IU School of MedicineINTRODUCTION: The Alzheimer's Disease Neuroimaging Initiative (ADNI) was established in 2004 to facilitate the development of effective treatments for Alzheimer's disease (AD) by validating biomarkers for AD clinical trials. METHODS: We searched for ADNI publications using established methods. RESULTS: ADNI has (1) developed standardized biomarkers for use in clinical trial subject selection and as surrogate outcome measures; (2) standardized protocols for use across multiple centers; (3) initiated worldwide ADNI; (4) inspired initiatives investigating traumatic brain injury and post-traumatic stress disorder in military populations, and depression, respectively, as an AD risk factor; (5) acted as a data-sharing model; (6) generated data used in over 600 publications, leading to the identification of novel AD risk alleles, and an understanding of the relationship between biomarkers and AD progression; and (7) inspired other public-private partnerships developing biomarkers for Parkinson's disease and multiple sclerosis. DISCUSSION: ADNI has made myriad impacts in its first decade. A competitive renewal of the project in 2015 would see the use of newly developed tau imaging ligands, and the continued development of recruitment strategies and outcome measures for clinical trials.Item Increasing participant diversity in AD research: Plans for digital screening, blood testing, and a community-engaged approach in the Alzheimer's Disease Neuroimaging Initiative 4(Wiley, 2023) Weiner, Michael W.; Veitch, Dallas P.; Miller, Melanie J.; Aisen, Paul S.; Albala, Bruce; Beckett, Laurel A.; Green, Robert C.; Harvey, Danielle; Jack, Clifford R., Jr.; Jagust, William; Landau, Susan M.; Morris, John C.; Nosheny, Rachel; Okonkwo, Ozioma C.; Perrin, Richard J.; Petersen, Ronald C.; Rivera-Mindt, Monica; Saykin, Andrew J.; Shaw, Leslie M.; Toga, Arthur W.; Tosun, Duygu; Trojanowski, John Q.; Alzheimer's Disease Neuroimaging Initiative; Radiology and Imaging Sciences, School of MedicineIntroduction: The 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. Methods: ADNI4 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 discussion: ADNI4 will improve generalizability of results, use remote digital and blood screening, and continue providing longitudinal clinical, biomarker, and autopsy data to investigators.Item Metabolomic and lipidomic signatures in autosomal dominant and late-onset Alzheimer's disease brains(Wiley, 2023) Novotny, Brenna C.; Fernandez, Maria Victoria; Wang, Ciyang; Budde, John P.; Bergmann, Kristy; Eteleeb, Abdallah M.; Bradley, Joseph; Webster, Carol; Ebl, Curtis; Norton, Joanne; Gentsch, Jen; Dube, Umber; Wang, Fengxian; Morris, John C.; Bateman, Randall J.; Perrin, Richard J.; McDade, Eric; Xiong, Chengjie; Chhatwal, Jasmeer; Dominantly Inherited Alzheimer Network (DIAN) Study Group; Alzheimer's Disease Neuroimaging Initiative; Alzheimer's Disease Metabolomics Consortium (ADMC); Goate, Alison; Farlow, Martin; Schofield, Peter; Chui, Helena; Karch, Celeste M.; Cruchaga, Carlos; Benitez, Bruno A.; Harari, Oscar; Neurology, School of MedicineIntroduction: The identification of multiple genetic risk factors for Alzheimer's disease (AD) suggests that many pathways contribute to AD onset and progression. However, the metabolomic and lipidomic profiles in carriers of distinct genetic risk factors are not fully understood. The metabolome can provide a direct image of dysregulated pathways in the brain. Methods: We interrogated metabolomic signatures in the AD brain, including carriers of pathogenic variants in APP, PSEN1, and PSEN2 (autosomal dominant AD; ADAD), APOE ɛ4, and TREM2 risk variant carriers, and sporadic AD (sAD). Results: We identified 133 unique and shared metabolites associated with ADAD, TREM2, and sAD. We identified a signature of 16 metabolites significantly altered between groups and associated with AD duration. Discussion: AD genetic variants show distinct metabolic perturbations. Investigation of these metabolites may provide greater insight into the etiology of AD and its impact on clinical presentation. Highlights: APP/PSEN1/PSEN2 and TREM2 variant carriers show distinct metabolic changes. A total of 133 metabolites were differentially abundant in AD genetic groups. β-citrylglutamate is differentially abundant in autosomal dominant, TREM2, and sporadic AD. A 16-metabolite profile shows differences between Alzheimer's disease (AD) genetic groups. The identified metabolic profile is associated with duration of disease.Item Multimodal data integration via mediation analysis with high-dimensional exposures and mediators(Wiley, 2022) Zhao, Yi; Li, Lexin; Alzheimer's Disease Neuroimaging Initiative; Biostatistics and Health Data Science, School of MedicineMotivated by an imaging proteomics study for Alzheimer's disease (AD), in this article, we propose a mediation analysis approach with high-dimensional exposures and high-dimensional mediators to integrate data collected from multiple platforms. The proposed method combines principal component analysis with penalized least squares estimation for a set of linear structural equation models. The former reduces the dimensionality and produces uncorrelated linear combinations of the exposure variables, whereas the latter achieves simultaneous path selection and effect estimation while allowing the mediators to be correlated. Applying the method to the AD data identifies numerous interesting protein peptides, brain regions, and protein-structure-memory paths, which are in accordance with and also supplement existing findings of AD research. Additional simulations further demonstrate the effective empirical performance of the method.