Affiliation: Mayo Clinic
Country: USA


  1. Li D, Misialek J, Jack C, Mielke M, Knopman D, Gottesman R, et al. Plasma Metabolites Associated with Brain MRI Measures of Neurodegeneration in Older Adults in the Atherosclerosis Risk in Communities⁻Neurocognitive Study (ARIC-NCS). Int J Mol Sci. 2019;20: pubmed publisher
    ..This study identified associations between certain plasma metabolites and brain MRI measures of SVD and neurodegeneration in older adults, particularly higher SM (OH) concentrations with higher total brain volume. ..
  2. Jack C, Vemuri P, Wiste H, Weigand S, Aisen P, Trojanowski J, et al. Evidence for ordering of Alzheimer disease biomarkers. Arch Neurol. 2011;68:1526-35 pubmed publisher
  3. Jack C, Bernstein M, Borowski B, Gunter J, Fox N, Thompson P, et al. Update on the magnetic resonance imaging core of the Alzheimer's disease neuroimaging initiative. Alzheimers Dement. 2010;6:212-20 pubmed publisher
    ..These experimental sub-studies are designed to demonstrate the feasibility of acquiring useful data in a multicenter (but single vendor) setting for these three emerging MRI applications. ..
  4. Daianu M, Jahanshad N, Nir T, Leonardo C, Jack C, Weiner M, et al. Algebraic connectivity of brain networks shows patterns of segregation leading to reduced network robustness in Alzheimer's disease. Comput Diffus MRI (2014). 2014;2014:55-64 pubmed
    ..Network components became more disconnected and segregated, and their modularity increased. These measures are sensitive to diagnostic group differences, and may help understand the complex changes in AD. ..
  5. Jack C, Knopman D, Weigand S, Wiste H, Vemuri P, Lowe V, et al. An operational approach to National Institute on Aging-Alzheimer's Association criteria for preclinical Alzheimer disease. Ann Neurol. 2012;71:765-75 pubmed publisher
    ..Future longitudinal validation of the criteria will be important. ..
  6. Jack C, Bennett D, Blennow K, Carrillo M, Dunn B, Haeberlein S, et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimers Dement. 2018;14:535-562 pubmed publisher
    ..This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people. ..
  7. Jack C, Therneau T, Wiste H, Weigand S, Knopman D, Lowe V, et al. Transition rates between amyloid and neurodegeneration biomarker states and to dementia: a population-based, longitudinal cohort study. Lancet Neurol. 2016;15:56-64 pubmed publisher
    ..National Institute on Aging, Alexander Family Professorship of Alzheimer's Disease Research, the GHR Foundation. ..
  8. Jack C, Vemuri P, Wiste H, Weigand S, Lesnick T, Lowe V, et al. Shapes of the trajectories of 5 major biomarkers of Alzheimer disease. Arch Neurol. 2012;69:856-67 pubmed
    ..Creating reliable models that describe the full trajectories of Alzheimer disease biomarkers will require significant additional longitudinal data in individual participants. ..
  9. Jack C, Barnes J, Bernstein M, Borowski B, Brewer J, Clegg S, et al. Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2. Alzheimers Dement. 2015;11:740-56 pubmed publisher
    ..Over the past decade the MRI core of ADNI has fulfilled its mandate of improving methods for clinical trials in AD and will continue to do so in the future. ..

More Information


  1. Jack C, Lowe V, Weigand S, Wiste H, Senjem M, Knopman D, et al. Serial PIB and MRI in normal, mild cognitive impairment and Alzheimer's disease: implications for sequence of pathological events in Alzheimer's disease. Brain. 2009;132:1355-65 pubmed publisher
    ..This model implies a complimentary role for MRI and PIB imaging in Alzheimer's disease, with each reflecting one of the major pathologies, amyloid dysmetabolism and neurodegeneration. ..
  2. Jack C, Wiste H, Weigand S, Therneau T, Knopman D, Lowe V, et al. Age-specific and sex-specific prevalence of cerebral β-amyloidosis, tauopathy, and neurodegeneration in cognitively unimpaired individuals aged 50-95 years: a cross-sectional study. Lancet Neurol. 2017;16:435-444 pubmed publisher
    ..National Institute on Aging (part of the US National Institutes of Health), the Alexander Family Professorship of Alzheimer's Disease Research, the Mayo Clinic, and the GHR Foundation. ..
  3. Jack C, Bennett D, Blennow K, Carrillo M, Feldman H, Frisoni G, et al. A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers. Neurology. 2016;87:539-47 pubmed publisher
  4. Jack C, Wiste H, Vemuri P, Weigand S, Senjem M, Zeng G, et al. Brain beta-amyloid measures and magnetic resonance imaging atrophy both predict time-to-progression from mild cognitive impairment to Alzheimer's disease. Brain. 2010;133:3336-48 pubmed publisher
  5. Jack C, Wiste H, Weigand S, Knopman D, Mielke M, Vemuri P, et al. Different definitions of neurodegeneration produce similar amyloid/neurodegeneration biomarker group findings. Brain. 2015;138:3747-59 pubmed publisher
  6. Jack C. PART and SNAP. Acta Neuropathol. 2014;128:773-6 pubmed publisher
  7. Jack C, Wiste H, Weigand S, Rocca W, Knopman D, Mielke M, et al. Age-specific population frequencies of cerebral β-amyloidosis and neurodegeneration among people with normal cognitive function aged 50-89 years: a cross-sectional study. Lancet Neurol. 2014;13:997-1005 pubmed publisher
    ..US National Institute on Aging and Alexander Family Professorship of Alzheimer's Disease Research. ..
  8. Jack C, Holtzman D. Biomarker modeling of Alzheimer's disease. Neuron. 2013;80:1347-58 pubmed publisher
    ..In this Review, we discuss several time-dependent models of AD that take into consideration varying age of onset (early versus late) and the influence of aging and co-occurring brain pathologies that commonly arise in the elderly. ..
  9. Jack C, Wiste H, Lesnick T, Weigand S, Knopman D, Vemuri P, et al. Brain ?-amyloid load approaches a plateau. Neurology. 2013;80:890-6 pubmed publisher
    ..5-2.5 is approximately 15 years. This roughly 15-year interval where the slope of the amyloid SUVR vs time curve is greatest and roughly linear represents a large therapeutic window for secondary preventive interventions. ..
  10. Jack C, Knopman D, Jagust W, Petersen R, Weiner M, Aisen P, et al. Tracking pathophysiological processes in Alzheimer's disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 2013;12:207-16 pubmed publisher
  11. Jack C, Barrio J, Kepe V. Cerebral amyloid PET imaging in Alzheimer's disease. Acta Neuropathol. 2013;126:643-57 pubmed publisher
  12. Jack C, Wiste H, Weigand S, Therneau T, Lowe V, Knopman D, et al. Defining imaging biomarker cut points for brain aging and Alzheimer's disease. Alzheimers Dement. 2017;13:205-216 pubmed publisher
  13. Jack C, Albert M, Knopman D, McKhann G, Sperling R, Carrillo M, et al. Introduction to the recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011;7:257-62 pubmed publisher
    ..However, the recommendations of the preclinical AD workgroup are intended purely for research purposes. ..
  14. Aisen P, Cummings J, Jack C, Morris J, Sperling R, Frölich L, et al. On the path to 2025: understanding the Alzheimer's disease continuum. Alzheimers Res Ther. 2017;9:60 pubmed publisher
    ..While the pathophysiology of AD has still not been elucidated completely, there is ample evidence to support researchers and clinicians embracing the view of a disease continuum in their study, diagnosis, and management of the disease. ..
  15. Marks M, Alexander A, Matsumoto J, Matsumoto J, Morris J, Petersen R, et al. Creating three dimensional models of Alzheimer's disease. 3D Print Med. 2017;3:13 pubmed publisher
    ..Our explicated workflow can create effective models of Alzheimer's brains that can be used in patient education, medical education, and policy forums. ..