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Jagust, William J.

https://orcid.org/0000-0002-4458-113X

A5061269385 | I95457486

Mayo Clinic

University of California, Berkeley

Citations 125

IC‐P‐098: The role of APOE‐ɛ4 genotype in early mild cognitive impairment (EMCI): Preliminary results from ADNI‐2

Alzheimer's & Dementia | July 19, 2012 | Volume: 8 | Issue: 4S_Part_2 | Pages: No page available

10.1016/j.jalz.2012.05.131

Brain atrophy as a surrogate marker in MS

Neurology | May 13, 2012 | Volume: 54 | Issue: 4 | Pages: 782-783

10.1212/wnl.54.4.782 | PMID 10690960

Predicting missing biomarker data in a longitudinal study of Alzheimer disease

Neurology | April 5, 2012 | Volume: 78 | Issue: 18 | Pages: 1376-1382

10.1212/wnl.0b013e318253d5b3 | PMID 22491869

The Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

Alzheimer's & Dementia | November 3, 2011 | Volume: 8 | Issue: 1S | Pages: No page available

10.1016/j.jalz.2011.09.172 | PMID 22047634

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β‐amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151–3) and tau‐mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [ 18 F]‐fluorodeoxyglucose‐PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β‐amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates for the detection of AD in its preclinical stages; (5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities, whereas MRI measures of change were shown to be the most efficient outcome measures; (6) the confirmation of the AD risk loci CLU , CR1 , and PICALM and the identification of novel candidate risk loci; (7) worldwide impact through the establishment of ADNI‐like programs in Europe, Asia, and Australia; (8) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease‐modifying drugs for AD; and (9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2‐year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI‐2) in October 2010 through to 2016, with enrollment of an additional 550 participants.
Impact of apolipoprotein ɛ4–cerebrospinal fluid beta‐amyloid interaction on hippocampal volume loss over 1 year in mild cognitive impairment

Alzheimer's & Dementia | September 1, 2011 | Volume: 7 | Issue: 5 | Pages: 514-520

10.1016/j.jalz.2010.12.010 | PMID 21889115

BackgroundThe majority of studies relating amyloid pathology with brain volumes have been cross‐sectional. Apolipoprotein ɛ4 (APOE ɛ4), a genetic risk factor for Alzheimer's disease, is also known to be associated with hippocampal volume loss. No studies have considered the effects of amyloid pathology and APOE ɛ4 together on longitudinal volume loss.MethodsWe evaluated whether an abnormal level of cerebrospinal fluid beta‐amyloid (CSF Aβ) and APOE ɛ4 carrier status were independently associated with greater hippocampal volume loss over 1 year. We then assessed whether APOE ɛ4 status and CSF Aβ acted synergistically, testing the significance of an interaction term in the regression analysis. We included 297 participants: 77 cognitively normal, 144 with mild cognitive impairment (MCI), and 76 with Alzheimer's disease.ResultsAn abnormal CSF Aβ level was found to be associated with greater hippocampal volume loss over 1 year in each group. APOE ɛ4 was associated with hippocampal volume loss only in the cognitively normal and MCI groups. APOE ɛ4 carriers with abnormal CSF Aβ in the MCI group acted synergistically to produce disproportionately greater volume loss than noncarriers.ConclusionBaseline CSF Aβ predicts progression of hippocampal volume loss. APOE ɛ4 carrier status amplifies the degree of neurodegeneration in MCI. Understanding the effect of interactions between genetic risk and amyloid pathology will be important in clinical trials and our understanding of the disease process.
IC‐P‐049: Change in amyloid deposition is related to concurrent cognitive change in MCI

Alzheimer's & Dementia | August 1, 2011 | Volume: 7 | Issue: 4S_Part_1 | Pages: No page available

10.1016/j.jalz.2011.05.118

IC‐02‐03: CSF biomarker and PIB‐PET–derived beta‐amyloid signature predicts metabolic, grey matter and cognitive changes in nondemented subjects

Alzheimer's & Dementia | August 1, 2011 | Volume: 7 | Issue: 4S_Part_1 | Pages: No page available

10.1016/j.jalz.2011.05.010

O1‐04‐05: CSF biomarker and PIB‐PET—derived beta‐amyloid signature predicts Brain metabolism, grey matter and cognitive changes in non‐demented subjects

Alzheimer's & Dementia | August 1, 2011 | Volume: 7 | Issue: 4S_Part_3 | Pages: No page available

10.1016/j.jalz.2011.05.252

The diagnosis of mild cognitive impairment due to Alzheimer's disease: Recommendations from the National Institute on Aging‐Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease

Alzheimer's & Dementia | April 22, 2011 | Volume: 7 | Issue: 3 | Pages: 270-279

10.1016/j.jalz.2011.03.008 | PMID 21514249

The National Institute on Aging and the Alzheimer's Association charged a workgroup with the task of developing criteria for the symptomatic predementia phase of Alzheimer's disease (AD), referred to in this article as mild cognitive impairment due to AD. The workgroup developed the following two sets of criteria: (1) core clinical criteria that could be used by healthcare providers without access to advanced imaging techniques or cerebrospinal fluid analysis, and (2) research criteria that could be used in clinical research settings, including clinical trials. The second set of criteria incorporate the use of biomarkers based on imaging and cerebrospinal fluid measures. The final set of criteria for mild cognitive impairment due to AD has four levels of certainty, depending on the presence and nature of the biomarker findings. Considerable work is needed to validate the criteria that use biomarkers and to standardize biomarker analysis for use in community settings.
O3‐03‐08: Biomarker predictors of cognitive decline in healthy older participants in the Alzheimer's Disease Neuroimaging Initiative

Alzheimer's & Dementia | July 11, 2010 | Volume: 6 | Issue: 4S_Part_4 | Pages: No page available

10.1016/j.jalz.2010.05.411