Skip to main content
Springer logoLink to Springer
letter
. 2014 Nov 8;128(6):773–776. doi: 10.1007/s00401-014-1362-3

PART and SNAP

Clifford R Jack Jr 1,
PMCID: PMC4231211  PMID: 25380757

The condition described by Crary et al. [5] of predominantly medial temporal lobe tauopathy in the absence of β-amyloidosis has a clear parallel in the recent imaging/biomarker literature. Individuals with imaging/biomarker evidence of Alzheimer’s disease (AD)-like neurodegeneration without β-amyloidosis have been labeled “suspected non-Alzheimer’s pathophysiology (SNAP)” [8, 13, 18, 22, 27, 30, 31, 34, 37, 39, 41, 44].

Biomarkers of β-amyloidosis are amyloid PET and low CSF Aβ42. Biomarkers of AD-related neurodegeneration are high CSF tau (total or phosphorylated); atrophy on structural MRI in an AD-like topographic pattern (particularly medial temporal structures); and decreased metabolism on FDG-PET in an AD-like topographic pattern [14]. Positive or negative cut points for each biomarker modality have typically been established in relation to AD dementia subjects [8, 13, 18, 22, 27, 30, 31, 34, 37, 39, 41, 44]. By designating subjects as either β-amyloid positive or negative, and neurodegeneration positive or negative, every individual can be classified into one of four groups: neither amyloidosis nor neurodegeneration; amyloidosis without neurodegeneration; amyloidosis plus neurodegeneration; or, neurodegeneration without amyloidosis (i.e., SNAP). We [18] originally labeled this last group SNAP because we felt that neurodegeneration in this group represented non-AD etiologies; however, as discussed later in this commentary, the designation “non-AD” has been controversial. While the SNAP construct was initially described in cognitively normal elderly [18] it has also been applied to categorize mildly impaired individuals.

Linking neurodegeneration in SNAP to PART pathology

The link between atrophy of medial temporal structures on MRI and the pathology of PART is straightforward, as is the link between abnormally elevated CSF tau and the pathology of PART. The link between decreased metabolism in AD-like areas on FDG-PET and the pathology of PART may, however, not be intuitively obvious. Medial parietal and lateral temporal/parietal cortical hypometabolism in PART could be explained by direct involvement of these areas by tauopathy which has extended beyond the medial temporal lobe as described in Crary et al. [5]. It could also be explained, however, by the fact that the medial temporal lobe (always involved in PART) is highly connected functionally to the posterior default mode network which is located anatomically in medial parietal and lateral temporal/parietal cortex and therefore overlaps extensively with the AD-like hypometabolism pattern [1, 2, 36].

Parallels between PART and SNAP

At least 12 different studies in seven different cohorts have been published to date describing characteristics of SNAP in cognitively normal elderly subjects [13, 18, 2023, 27, 34, 37, 39, 41, 44]. And at least three studies in four different cohorts have been published describing SNAP in MCI subjects [8, 30, 31]. Clear parallels exist between SNAP and PART in several areas.

First, while population frequencies of PART are not estimated in Crary et al. [5], PART is judged to be common in middle-aged and elderly subjects. SNAP is likewise common in subjects over age 65. Of 1,425 cognitively normal subjects reported from seven different centers, 315 (22 %) were categorized as SNAP [18, 22, 27, 37, 39, 41]. Of 277 MCI subjects reported from 4 different studies, 68 (25 %) were categorized as SNAP [8, 30, 31]. Given the large numbers of subjects included in these studies (esp. cognitively normal) the population frequency estimates of SNAP are likely reliable.

Second, APOE4 is underrepresented in both PART and SNAP. The frequency of APOE4 carriership among subjects with definite PART ranges from 9.1 to 20 % for different Braak stages (Table 1, in Crary et al. [5]). Among cognitively normal SNAP subjects, reported frequencies of APOE4 carriership ranged from 12 to 30 % [18, 22, 27, 41]. In all these studies, the frequency of APOE4 in SNAP was dramatically lower than in subjects with preclinical AD.

Third, the cognitive/clinical profile of both SNAP and PART is one of no impairment to mild cognitive impairment. Frank dementia appears to be rare in SNAP [24]. Mean MMSE scores among subjects with definite PART grouped by Braak stage (with average age in the 80 s) ranged from 28 to 24 Table 1 in Crary et al. [5]). SNAP in turn has been described in subjects who are either cognitively normal or MCI. Furthermore, longitudinal clinical follow-up of cognitively normal SNAP subjects reveals a somewhat benign trajectory where the risk of clinical/cognitive decline for SNAP is significantly less than subjects classified as both amyloidosis and neurodegeneration positive [22, 27, 34, 39, 41].

Caveats concerning parallels between PART and SNAP

Drawing parallels between SNAP and PART comes with an important caveat—neurodegenerative imaging/biomarker non-specificity. The imaging findings used to define neurodegeneration in SNAP are not specific for temporal lobe tauopathy (i.e., PART). While hippocampal/medial temporal atrophy on MRI correlates well with tau burden and Braak stage [15, 43], other pathologies also produce hippocampal atrophy. These are well known to pathologists and include hippocampal sclerosis [15, 29, 33, 45], frontotemporal lobar degeneration (especially with TDP43 pathology [42]), argyrophilic grain disease, and ischemia/anoxia [7]. Temporal/parietal FDG-PET hypometabolism also occurs in conditions other than temporal lobe tauopathy, for example, cerebrovascular disease [44]. The same caveat applies to elevated CSF tau, which is seen in conditions other than PART including ischemic cerebrovascular disease, traumatic brain injury, and Creutzfeldt–Jakob disease [38].

These caveats notwithstanding, to date, autopsy results have been reported in 4 SNAP subjects [41]. Three of the four had low probability AD and the fourth was not AD by NIA–AA pathological criteria [12, 26]. Two of the four autopsy reports [41] described medial temporal tauopathy without amyloidosis—i.e., they met the definition of PART.

A solution for imaging/biomarker non-specificity may soon be at hand. Tau PET ligands have recently been developed [4, 25, 40] and the hope (or expectation) is that tau PET will reveal the contribution of tau to the neurodegenerative profile seen in subjects labeled SNAP on the basis of MRI, FDG-PET and CSF tau.

The chief controversy: is PART a non-AD process or part of the AD spectrum?

As asserted in the accompanying commentary, the major controversy with PART is whether it should be considered an age-related non-AD entity or part of the AD pathological spectrum. Precisely, the same controversy exists in the imaging/biomarker literature on SNAP. Some in the imaging/biomarker community argue that evidence of β-amyloid deposition is required to label an individual as being in the “AD pathophysiological pathway” on the basis of biomarkers and hence SNAP is correctly labeled a non-AD condition. Others argue that because the neurodegenerative biomarkers in SNAP are AD-like, SNAP represents a “pre fibrillar amyloid” part of the AD spectrum [3]. Elegant arguments have appeared on both sides of this debate.

There may be a way, however, to reconcile these opposing viewpoints on both PART and SNAP. A series of recent publications in the imaging/biomarker literature have proposed the following step-wise scenario as a common pathological and biomarker sequence in late-onset AD [16, 17, 19, 28]. This proposed pathological sequence is in fact based on earlier autopsy literature [6, 9, 32].

  1. Essentially everyone in the population develops PART at some point in life. Typically this occurs prior to significant fibrillar amyloid deposition. By itself, however, PART produces none to mild clinical symptomatology.

  2. Independently from PART, β-amyloidosis develops in neocortical areas [10, 35].

  3. At some point in time, which varies considerably from person to person and through as yet undetermined signaling mechanisms, β-amyloidosis begins to induce the spread of tauopathy from medial temporal to widespread neocortical association areas.

  4. Severe clinical symptoms are due to direct involvement of neocortical areas by the accelerated and expanding tauopathy, not due to direct involvement by β-amyloid deposition.

In this model of late-onset AD [6, 9, 16, 17, 19, 28, 32], the role of β-amyloid is to induce the propagation of tauopathy, rather than to initiate the first tau deposition in the brain (as is likely the case in genetically determined AD [11]).

In summary, the paper by Crary et al. [5] formalizes a key concept that links autopsy findings to imaging/biomarker findings and fills a void that the imaging/biomarker community has struggled with for several years. By introducing the term PART and characterizing this entity Crary et al. [5] have provided the clinical, imaging/biomarker community with an important foundation on which to rest future studies.

Acknowledgements

This study was funded by National Institute on Aging (RO1-AG011378, RO1-AG041851); the Alexander Family Professorship of Alzheimer’s Disease Research.

Conflict of interest

Dr. Jack has provided consulting services for Janssen Research and Development, LLC. He received research funding from the NIH [R01-AG011378, U01-HL096917, U01-AG024904, RO1 AG041851, R01 AG37551, R01AG043392, U01-AG06786], and the Alexander Family Alzheimer’s Disease Research Professorship of the Mayo Foundation.

References

  • 1.Buckner RL, Sepulcre J, Talukdar T, Krienen FM, Liu H, Hedden T, Andrews-Hanna JR, Sperling RA, Johnson KA. Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer’s disease. J Neurosci. 2009;29(6):1860–1873. doi: 10.1523/JNEUROSCI.5062-08.2009. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Buckner RL, Snyder AZ, Shannon BJ, LaRossa G, Sachs R, Fotenos AF, Sheline YI, Klunk WE, Mathis CA, Morris JC, Mintun MA. Molecular, structural, and functional characterization of Alzheimer’s disease: evidence for a relationship between default activity, amyloid, and memory. J Neurosci. 2005;25(34):7709–7717. doi: 10.1523/JNEUROSCI.2177-05.2005. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Chetelat G. Alzheimer disease: abeta-independent processes-rethinking preclinical AD. Nat Rev Neurol. 2013;9(3):123–124. doi: 10.1038/nrneurol.2013.21. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Chien DT, Bahri S, Szardenings AK, Walsh JC, Mu F, Su MY, Shankle WR, Elizarov A, Kolb HC. Early clinical PET imaging results with the novel PHF-tau radioligand [F-18]-T807. J Alzheimers Dis. 2013;34(2):457–468. doi: 10.3233/JAD-122059. [DOI] [PubMed] [Google Scholar]
  • 5.Crary JF, Trojanowski JQ, Schneider JA, Abisambra JF, Abner EL, Alafuzoff I, Arnold SE, Attems J, Beach TG, Bigio EH, Cairns NJ, Dickson DW, Gearing M, Grinberg LT, Hof PR, Hyman BT, Jicha GA, Jellinger KA, Kovacs GG, Knopman D, Kofler J, Kukull WA, Mackenzie IR, Masliah E, McKee AC, Montine TJ, Murray ME, Neltner JH, Santa-Maria I, Seeley WW, Serrano-Pozo A, Shelanski ML, Stein TD, Takao M, Thal DR, Toledo JB, Troncoso JC, Vonsattel JP, White CL, 3rd, Wisniewski T, Woltjer RL, Yamada M, Nelson PT (2014) Primary age-related tauopathy (PART): a common pathology associated with human aging. Acta Neuropathol. doi:10.1007/s00401-014-1349-0 [DOI] [PMC free article] [PubMed]
  • 6.Delacourte A, Sergeant N, Wattez A, Maurage CA, Lebert F, Pasquier F, David JP. Tau aggregation in the hippocampal formation: an ageing or a pathological process? Exp Gerontol. 2002;37(10–11):1291–1296. doi: 10.1016/S0531-5565(02)00141-9. [DOI] [PubMed] [Google Scholar]
  • 7.Di Paola M, Caltagirone C, Fadda L, Sabatini U, Serra L, Carlesimo GA. Hippocampal atrophy is the critical brain change in patients with hypoxic amnesia. Hippocampus. 2008;18(7):719–728. doi: 10.1002/hipo.20432. [DOI] [PubMed] [Google Scholar]
  • 8.Duara R, Loewenstein DA, Shen Q, Barker W, Potter E, Varon D, Heurlin K, Vandenberghe R, Buckley C. Amyloid positron emission tomography with (18)F-flutemetamol and structural magnetic resonance imaging in the classification of mild cognitive impairment and Alzheimer’s disease. Alzheimers Dement. 2013;9(3):295–301. doi: 10.1016/j.jalz.2012.01.006. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Duyckaerts C, Hauw JJ. Prevalence, incidence and duration of Braak’s stages in the general population: can we know? Neurobiol Aging. 1997;18(4):362–369. doi: 10.1016/S0197-4580(97)00047-X. [DOI] [PubMed] [Google Scholar]
  • 10.Duyckaerts C, Uchihara T, Seilhean D, He Y, Hauw JJ. Dissociation of Alzheimer type pathology in a disconnected piece of cortex. Acta Neuropathol. 1997;93(5):501–507. doi: 10.1007/s004010050645. [DOI] [PubMed] [Google Scholar]
  • 11.Hardy J, Selkoe DJ. The amyloid hypothesis of Alzheimer’s disease: progress and problems on the road to therapeutics. Science. 2002;297(5580):353–356. doi: 10.1126/science.1072994. [DOI] [PubMed] [Google Scholar]
  • 12.Hyman BT, Phelps CH, Beach TG, Bigio EH, Cairns NJ, Carrillo MC, Dickson DW, Duyckaerts C, Frosch MP, Masliah E, Mirra SS, Nelson PT, Schneider JA, Thal DR, Thies B, Trojanowski JQ, Vinters HV, Montine TJ. National Institute on aging-Alzheimer’s Association guidelines for the neuropathologic assessment of Alzheimer’s disease. Alzheimers Dement. 2012;8(1):1–13. doi: 10.1016/j.jalz.2011.10.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Ivanoiu A, Dricot L, Gilis N, Grandin C, Lhommel R, Quenon L, Hanseeuw B (2014) Classification of non-demented patients attending a memory clinic using the new diagnostic criteria for Alzheimer’s disease with disease-related biomarkers. J Alzheimers Dis. doi:10.3233/JAD-140651 [DOI] [PubMed]
  • 14.Jack CR, Jr, Albert MS, Knopman DS, McKhann GM, Sperling RA, Carillo M, Thies W, Phelps CH. 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(3):257–262. doi: 10.1016/j.jalz.2011.03.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Jack CR, Jr, Dickson DW, Parisi JE, Xu YC, Cha RH, O’Brien PC, Edland SD, Smith GE, Boeve BF, Tangalos EG, Kokmen E, Petersen RC. Antemortem MRI findings correlate with hippocampal neuropathology in typical aging and dementia. Neurology. 2002;58(5):750–757. doi: 10.1212/WNL.58.5.750. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Jack CR, Jr, Holtzman DM. Biomarker modeling of Alzheimer’s Disease. Neuron. 2013;80(6):1347–1358. doi: 10.1016/j.neuron.2013.12.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Jack CR, Jr, Knopman DS, Jagust WJ, Petersen RC, Weiner MW, Aisen PS, Shaw LM, Vemuri P, Wiste HJ, Weigand SD, Lesnick T, Pankratz VS, Donohue M, Trojanowski JQ. Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurol. 2013;12(2):207–216. doi: 10.1016/S1474-4422(12)70291-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Jack CR, Jr, Knopman DS, Weigand SD, Wiste HJ, Vemuri P, Lowe V, Kantarci K, Gunter JL, Senjem ML, Ivnik RJ, Roberts R, Rocca WA, Boeve BF, Petersen RC. An operational approach to NIA–AA criteria for preclinical Alzheimer’s disease. Ann Neurol. 2012;71(6):765–775. doi: 10.1002/ana.22628. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Jack CR, Jr, Wiste HJ, Knopman DS, Vemuri P, Mielke MM, Weigand SD, Senjem ML, Gunter JL, Lowe V, Gregg BE, Pankratz VS, Petersen RC. Rates of beta-amyloid accumulation are independent of hippocampal neurodegeneration. Neurology. 2014;82(18):1605–1612. doi: 10.1212/WNL.0000000000000386. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Jack CR, Jr, Wiste HJ, Weigand SD, Knopman DS, Lowe V, Vemuri P, Mielke MM, Jones DT, Senjem ML, Gunter JL, Gregg BE, Pankratz VS, Petersen RC. Amyloid-first and neurodegeneration-first profiles characterize incident amyloid PET positivity. Neurology. 2013;81(20):1732–1740. doi: 10.1212/01.wnl.0000435556.21319.e4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Jack CR, Jr, Wiste HJ, Weigand SD, Rocca WA, Knopman DS, Mielke MM, Lowe VJ, Senjem ML, Gunter JL, Preboske GM, Pankratz VS, Vemuri P, Petersen RC. Age-specific population frequencies of cerebral beta-amyloidosis and neurodegeneration among people with normal cognitive function aged 50–89 years: a cross-sectional study. Lancet Neurol. 2014;13(10):997–1005. doi: 10.1016/S1474-4422(14)70194-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Knopman DS, Jack CR, Jr, Wiste HJ, Weigand SD, Vemuri P, Lowe V, Kantarci K, Gunter JL, Senjem ML, Ivnik RJ, Roberts RO, Boeve BF, Petersen RC. Short-term clinical outcomes for stages of NIA–AA preclinical Alzheimer disease. Neurology. 2012;78(20):1576–1582. doi: 10.1212/WNL.0b013e3182563bbe. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Knopman DS, Jack CR, Jr, Wiste HJ, Weigand SD, Vemuri P, Lowe VJ, Kantarci K, Gunter JL, Senjem ML, Mielke MM, Roberts RO, Boeve BF, Petersen RC. Brain injury biomarkers are not dependent on beta-amyloid in normal elderly. Ann Neurol. 2013;73(4):472–480. doi: 10.1002/ana.23816. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Lowe VJ, Peller PJ, Weigand SD, Montoya Quintero C, Tosakulwong N, Vemuri P, Senjem ML, Jordan L, Jack CR, Jr, Knopman D, Petersen RC. Application of the National Institute on Aging-Alzheimer’s Association AD criteria to ADNI. Neurology. 2013;80(23):2130–2137. doi: 10.1212/WNL.0b013e318295d6cf. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Maruyama M, Shimada H, Suhara T, Shinotoh H, Ji B, Maeda J, Zhang MR, Trojanowski JQ, Lee VM, Ono M, Masamoto K, Takano H, Sahara N, Iwata N, Okamura N, Furumoto S, Kudo Y, Chang Q, Saido TC, Takashima A, Lewis J, Jang MK, Aoki I, Ito H, Higuchi M. Imaging of tau pathology in a tauopathy mouse model and in Alzheimer patients compared to normal controls. Neuron. 2013;79(6):1094–1108. doi: 10.1016/j.neuron.2013.07.037. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Montine TJ, Phelps CH, Beach TG, Bigio EH, Cairns NJ, Dickson DW, Duyckaerts C, Frosch MP, Masliah E, Mirra SS, Nelson PT, Schneider JA, Thal DR, Trojanowski JQ, Vinters HV, Hyman BT. National Institute on Aging-Alzheimer’s Association guidelines for the neuropathologic assessment of Alzheimer’s disease: a practical approach. Acta Neuropathol. 2012;123(1):1–11. doi: 10.1007/s00401-011-0910-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Mormino EC, Betensky RA, Hedden T, Schultz AP, Amariglio RE, Rentz DM, Johnson KA, Sperling RA (2014) Synergistic effect of beta-amyloid and neurodegeneration on cognitive decline in clinically normal individuals. JAMA Neurol. doi:10.1001/jamaneurol.2014.2031 [DOI] [PMC free article] [PubMed]
  • 28.Musiek ES, Holtzman DM. Origins of Alzheimer’s disease: reconciling cerebrospinal fluid biomarker and neuropathology data regarding the temporal sequence of amyloid-beta and tau involvement. Curr Opin Neurol. 2012;25(6):715–720. doi: 10.1097/WCO.0b013e32835a30f4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Nelson PT, Smith CD, Abner EL, Wilfred BJ, Wang WX, Neltner JH, Baker M, Fardo DW, Kryscio RJ, Scheff SW, Jicha GA, Jellinger KA, Van Eldik LJ, Schmitt FA. Hippocampal sclerosis of aging, a prevalent and high-morbidity brain disease. Acta Neuropathol. 2013;126(2):161–177. doi: 10.1007/s00401-013-1154-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30.Petersen RC, Aisen P, Boeve BF, Geda YE, Ivnik RJ, Knopman DS, Mielke M, Pankratz VS, Roberts R, Rocca WA, Weigand S, Weiner M, Wiste H, Jack CR., Jr Criteria for mild cognitive impairment due to Alzheimer’s disease in the community. Ann Neurol. 2013 doi: 10.1002/ana.23931. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Prestia A, Caroli A, van der Flier WM, Ossenkoppele R, Van Berckel B, Barkhof F, Teunissen CE, Wall AE, Carter SF, Scholl M, Choo IH, Nordberg A, Scheltens P, Frisoni GB. Prediction of dementia in MCI patients based on core diagnostic markers for Alzheimer disease. Neurology. 2013;80(11):1048–1056. doi: 10.1212/WNL.0b013e3182872830. [DOI] [PubMed] [Google Scholar]
  • 32.Price JL, Morris JC. Tangles and plaques in nondemented aging and “preclinical” Alzheimer’s disease. Ann Neurol. 1999;45(3):358–368. doi: 10.1002/1531-8249(199903)45:3<358::AID-ANA12>3.0.CO;2-X. [DOI] [PubMed] [Google Scholar]
  • 33.Probst A, Taylor KI, Tolnay M. Hippocampal sclerosis dementia: a reappraisal. Acta Neuropathol. 2007;114(4):335–345. doi: 10.1007/s00401-007-0262-1. [DOI] [PubMed] [Google Scholar]
  • 34.Roe CM, Fagan AM, Grant EA, Hassenstab J, Moulder KL, Maue Dreyfus D, Sutphen CL, Benzinger TL, Mintun MA, Holtzman DM, Morris JC. Amyloid imaging and CSF biomarkers in predicting cognitive impairment up to 7.5 years later. Neurology. 2013;80(19):1784–1791. doi: 10.1212/WNL.0b013e3182918ca6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Small SA, Duff K. Linking Abeta and tau in late-onset Alzheimer’s disease: a dual pathway hypothesis. Neuron. 2008;60(4):534–542. doi: 10.1016/j.neuron.2008.11.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Sperling RA, Laviolette PS, O’Keefe K, O’Brien J, Rentz DM, Pihlajamaki M, Marshall G, Hyman BT, Selkoe DJ, Hedden T, Buckner RL, Becker JA, Johnson KA. Amyloid deposition is associated with impaired default network function in older persons without dementia. Neuron. 2009;63(2):178–188. doi: 10.1016/j.neuron.2009.07.003. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Toledo JB, Weiner MW, Wolk DA, Da X, Chen K, Arnold SE, Jagust W, Jack C, Reiman EM, Davatzikos C, Shaw LM, Trojanowski JQ. Neuronal injury biomarkers and prognosis in ADNI subjects with normal cognition. Acta Neuropathol Commun. 2014;2(1):26. doi: 10.1186/2051-5960-2-26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Tsitsopoulos PP, Marklund N. Amyloid-beta peptides and tau protein as biomarkers in cerebrospinal and interstitial fluid following traumatic brain injury: a review of experimental and clinical studies. Front Neurol. 2013;4:79. doi: 10.3389/fneur.2013.00079. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.van Harten AC, Smits LL, Teunissen CE, Visser PJ, Koene T, Blankenstein MA, Scheltens P, van der Flier WM. Preclinical AD predicts decline in memory and executive functions in subjective complaints. Neurology. 2013;81(16):1409–1416. doi: 10.1212/WNL.0b013e3182a8418b. [DOI] [PubMed] [Google Scholar]
  • 40.Villemagne VL, Furumoto S, Fodero-Tavoletti MT, Mulligan RS, Hodges J, Harada R, Yates P, Piguet O, Pejoska S, Dore V, Yanai K, Masters CL, Kudo Y, Rowe CC, Okamura N. In vivo evaluation of a novel tau imaging tracer for Alzheimer’s disease. Eur J Nucl Med Mol Imaging. 2014;41(5):816–826. doi: 10.1007/s00259-013-2681-7. [DOI] [PubMed] [Google Scholar]
  • 41.Vos SJ, Xiong C, Visser PJ, Jasielec MS, Hassenstab J, Grant EA, Cairns NJ, Morris JC, Holtzman DM, Fagan AM. Preclinical Alzheimer’s disease and its outcome: a longitudinal cohort study. Lancet Neurol. 2013;12(10):957–965. doi: 10.1016/S1474-4422(13)70194-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Whitwell JL, Jack CR, Jr, Parisi JE, Senjem ML, Knopman DS, Boeve BF, Rademakers R, Baker M, Petersen RC, Dickson DW, Josephs KA. Does TDP-43 type confer a distinct pattern of atrophy in frontotemporal lobar degeneration? Neurology. 2010;75(24):2212–2220. doi: 10.1212/WNL.0b013e31820203c2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Whitwell JL, Josephs KA, Murray ME, Kantarci K, Przybelski SA, Weigand SD, Vemuri P, Senjem ML, Parisi JE, Knopman DS, Boeve BF, Petersen RC, Dickson DW, Jack CR., Jr MRI correlates of neurofibrillary tangle pathology at autopsy: a voxel-based morphometry study. Neurology. 2008;71(10):743–749. doi: 10.1212/01.wnl.0000324924.91351.7d. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Wirth M, Villeneuve S, Haase CM, Madison CM, Oh H, Landau SM, Rabinovici GD, Jagust WJ (2013) Associations between Alzheimer disease biomarkers, neurodegeneration, and cognition in cognitively normal older people. JAMA Neurol. doi:10.1001/jamaneurol.2013.4013 [DOI] [PMC free article] [PubMed]
  • 45.Zarow C, Vinters HV, Ellis WG, Weiner MW, Mungas D, White L, Chui HC. Correlates of hippocampal neuron number in Alzheimer’s disease and ischemic vascular dementia. Ann Neurol. 2005;57(6):896–903. doi: 10.1002/ana.20503. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Acta Neuropathologica are provided here courtesy of Springer

RESOURCES