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Association between FDG uptake, CSF biomarkers and cognitive performance in patients with probable Alzheimer’s disease

Abstract

Purpose

Brain imaging of FDG uptake and cerebrospinal fluid (CSF) concentration of amyloid-beta 1–42 (Aβ1-42) or tau proteins are promising biomarkers in the diagnosis of Alzheimer’s disease (AD). There is still uncertainty regarding any association between decreased FDG uptake and alterations in CSF markers.

Methods

The relationship between FDG uptake, CSF Aβ1-42 and total tau (T-tau), as well as the Mini-Mental State Examination (MMSE) score was investigated in 34 subjects with probable AD using step-wise linear regression. FDG uptake was scaled to the pons.

Results

Scaled FDG uptake was significantly reduced in the probable AD subjects compared to 17 controls bilaterally in the precuneus/posterior cingulate area, angular gyrus/inferior parietal cortex, inferior temporal/midtemporal cortex, midfrontal cortex, and left caudate. Voxel-based single-subject analysis of the probable AD subjects at p < 0.001 (uncorrected) revealed a total volume of significant hypometabolism ranging from 0 to 452 ml (median 70 ml). The total hypometabolic volume was negatively correlated with the MMSE score, but it was not correlated with the CSF measures. VOI-based step-wise linear regression revealed that scaled FDG uptake in the precuneus/posterior cingulate was negatively correlated with CSF Aβ1-42. Scaled FDG uptake in the caudate was positively correlated with CSF T-tau.

Conclusion

The extent and local severity of the reduction in FDG uptake in probable AD subjects are associated with cognitive impairment. In addition, there appears to be a relationship between local FDG uptake and CSF biomarkers which differs between different brain regions.

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References

  1. 1.

    Silverman DHS. Brain 18F-FDG PET in the diagnosis of neurodegenerative dementias: comparison with perfusion SPECT and with clinical evaluations lacking nuclear imaging. J Nucl Med 2004;45:594–607.

    PubMed  Google Scholar 

  2. 2.

    Sunderland T, Linker G, Mirza N, Putnam KT, Friedman DL, Kimmel LH, et al. Decreased beta-amyloid1-42 and increased tau levels in cerebrospinal fluid of patients with Alzheimer disease. JAMA 2003;289:2094–103.

    PubMed  Article  Google Scholar 

  3. 3.

    Blennow K, Hampel H. CSF markers for incipient Alzheimer’s disease. Lancet Neurol 2003;2:605–13.

    PubMed  Article  CAS  Google Scholar 

  4. 4.

    Engelborghs S, De Vreese K, Van de Casteele T, Vanderstichele H, Van Everbroeck B, Cras P, et al. Diagnostic performance of a CSF-biomarker panel in autopsy-confirmed dementia. Neurobiol Aging 2008;29:1143–59.

    PubMed  Article  Google Scholar 

  5. 5.

    Strozyk D, Blennow K, White LR, Launer LJ. CSF Abeta 42 levels correlate with amyloid-neuropathology in a population-based autopsy study. Neurology 2003;60:652–6.

    PubMed  CAS  Google Scholar 

  6. 6.

    Clark CM, Xie S, Chittams J, Ewbank D, Peskind E, Galasko D, et al. Cerebrospinal fluid tau and beta-amyloid: how well do these biomarkers reflect autopsy-confirmed dementia diagnoses? Arch Neurol 2003;60:1696–702.

    PubMed  Article  Google Scholar 

  7. 7.

    Fagan AM, Mintun MA, Mach RH, Lee SY, Dence CS, Shah AR, et al. Inverse relation between in vivo amyloid imaging load and cerebrospinal fluid Abeta42 in humans. Ann Neurol 2006;59:512–9.

    PubMed  Article  CAS  Google Scholar 

  8. 8.

    Kadekaro M, Crane AM, Sokoloff L. Differential effects of electrical stimulation of sciatic nerve on metabolic activity in spinal cord and dorsal root ganglion in the rat. Proc Natl Acad Sci U S A 1985;82:6010–3.

    PubMed  Article  CAS  Google Scholar 

  9. 9.

    Mielke R, Schroder R, Fink GR, Kessler J, Herholz K, Heiss WD. Regional cerebral glucose metabolism and postmortem pathology in Alzheimer’s disease. Acta Neuropathol 1996;91:174–9.

    PubMed  Article  CAS  Google Scholar 

  10. 10.

    Buerger K, Zinkowski R, Teipel SJ, Tapiola T, Arai H, Blennow K, et al. Differential diagnosis of Alzheimer disease with cerebrospinal fluid levels of tau protein phosphorylated at threonine 231. Arch Neurol 2002;59:1267–72.

    PubMed  Article  Google Scholar 

  11. 11.

    Silverman DH, Small GW, Chang CY, Lu CS, Kung De Aburto MA, Chen W, et al. Positron emission tomography in evaluation of dementia: regional brain metabolism and long-term outcome. JAMA 2001;286:2120–7.

    PubMed  Article  CAS  Google Scholar 

  12. 12.

    Okamura N, Arai H, Higuchi M, Tashiro M, Matsui T, Itoh M, et al. Cerebrospinal fluid levels of amyloid beta-peptide1-42, but not tau have positive correlation with brain glucose metabolism in humans. Neurosci Lett 1999;273:203–7.

    PubMed  Article  CAS  Google Scholar 

  13. 13.

    Fellgiebel A, Siessmeier T, Scheurich A, Winterer G, Bartenstein P, Schmidt LG, et al. Association of elevated phospho-tau levels with Alzheimer-typical 18F-fluoro-2-deoxy-D-glucose positron emission tomography findings in patients with mild cognitive impairment. Biol Psychiatry 2004;56:279–83.

    PubMed  Article  CAS  Google Scholar 

  14. 14.

    Mosconi L, De Santi S, Brys M, Tsui WH, Pirraglia E, Glodzik-Sobanska L, et al. Hypometabolism and altered cerebrospinal fluid markers in normal apolipoprotein E E4 carriers with subjective memory complaints. Biol Psychiatry 2008;63:609–18.

    PubMed  Article  CAS  Google Scholar 

  15. 15.

    Ceravolo R, Borghetti D, Kiferle L, Tognoni G, Giorgetti A, Neglia D, et al. CSF phosphorylated TAU protein levels correlate with cerebral glucose metabolism assessed with PET in Alzheimer’s disease. Brain Res Bull 2008;76:80–4.

    PubMed  Article  CAS  Google Scholar 

  16. 16.

    Friston KJ, Holmes AP, Worsley KJ, Poline JP, Frith CD, Frackowiak RSJ. Statistical parametric maps in functional Imaging: a general linear approach. Hum Brain Mapp 1995;2:189–210.

    Article  Google Scholar 

  17. 17.

    McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer’s disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer’s Disease. Neurology 1984;34:939–44.

    PubMed  CAS  Google Scholar 

  18. 18.

    Hoffman JM, Welsh-Bohmer KA, Hanson M, Crain B, Hulette C, Earl N, et al. FDG PET imaging in patients with pathologically verified dementia. J Nucl Med 2000;41:1920–8.

    PubMed  CAS  Google Scholar 

  19. 19.

    Hixson JE, Vernier DT. Restriction isotyping of human apolipoprotein E by gene amplification and cleavage with HhaI. J Lipid Res 1990;31:545–8.

    PubMed  CAS  Google Scholar 

  20. 20.

    Wienhard K, Eriksson L, Grootoonk S, Casey M, Pietrzyk U, Heiss WD. Performance evaluation of the positron scanner ECAT EXACT. J Comput Assist Tomogr 1992;16:804–13.

    PubMed  Article  CAS  Google Scholar 

  21. 21.

    Minoshima S, Frey KA, Foster NL, Kuhl DE. Preserved pontine glucose metabolism in Alzheimer disease: a reference region for functional brain image (PET) analysis. J Comput Assist Tomogr 1995;19:541–7.

    PubMed  Article  CAS  Google Scholar 

  22. 22.

    Tzourio-Mazoyer N, Landeau B, Papathanassiou D, Crivello F, Etard O, Delcroix N, et al. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 2002;15:273–89.

    PubMed  Article  CAS  Google Scholar 

  23. 23.

    Perneger TV. What’s wrong with Bonferroni adjustments. BMJ 1998;316:1236–8.

    PubMed  CAS  Google Scholar 

  24. 24.

    Herholz K, Salmon E, Perani D, Baron JC, Holthoff V, Frolich L, et al. Discrimination between Alzheimer dementia and controls by automated analysis of multicenter FDG PET. Neuroimage 2002;17:302–16.

    PubMed  Article  CAS  Google Scholar 

  25. 25.

    Minoshima S, Frey KA, Koeppe RA, Foster NL, Kuhl DE. A diagnostic approach in Alzheimer’s disease using three-dimensional stereotactic surface projections of fluorine-18-FDG PET. J Nucl Med 1995;36:1238–48.

    PubMed  CAS  Google Scholar 

  26. 26.

    Mielke R, Herholz K, Grond M, Kessler J, Heiss WD. Clinical deterioration in probable Alzheimer’s disease correlates with progressive metabolic impairment of association areas. Dementia 1994;5:36–41.

    PubMed  CAS  Google Scholar 

  27. 27.

    Bouwman FH, van der Flier WM, Schoonenboom NS, van Elk EJ, Kok A, Rijmen F, et al. Longitudinal changes of CSF biomarkers in memory clinic patients. Neurology 2007;69:1006–11.

    PubMed  Article  CAS  Google Scholar 

  28. 28.

    Piert M, Koeppe RA, Giordani B, Berent S, Kuhl DE. Diminished glucose transport and phosphorylation in Alzheimer’s disease determined by dynamic FDG-PET. J Nucl Med 1996;37:201–8.

    PubMed  CAS  Google Scholar 

  29. 29.

    Cummings JL. Toward a molecular neuropsychiatry of neurodegenerative diseases. Ann Neurol 2003;54:147–54.

    PubMed  Article  CAS  Google Scholar 

  30. 30.

    Mendez MF, Perryman KM, Miller BL, Swartz JR, Cummings JL. Compulsive behaviors as presenting symptoms of frontotemporal dementia. J Geriatr Psychiatry Neurol 1997;10:154–7.

    PubMed  CAS  Google Scholar 

  31. 31.

    Baxter LR Jr, Phelps ME, Mazziotta JC, Guze BH, Schwartz JM, Selin CE. Local cerebral glucose metabolic rates in obsessive-compulsive disorder. A comparison with rates in unipolar depression and in normal controls. Arch Gen Psychiatry 1987;44:211–8.

    PubMed  Google Scholar 

  32. 32.

    Poldrack RA, Packard MG. Competition among multiple memory systems: converging evidence from animal and human brain studies. Neuropsychologia 2003;41:245–51.

    PubMed  Article  Google Scholar 

  33. 33.

    Poldrack RA, Clark J, Pare-Blagoev EJ, Shohamy D, Creso Moyano J, Myers C, et al. Interactive memory systems in the human brain. Nature 2001;414:546–50.

    PubMed  Article  CAS  Google Scholar 

  34. 34.

    Klimkowicz-Mrowiec A, Slowik A, Krzywoszanski L, Herzog-Krzywoszanska R, Szczudlik A. Severity of explicit memory impairment due to Alzheimer’s disease improves effectiveness of implicit learning. J Neurol 2008;255:502–9.

    PubMed  Article  Google Scholar 

  35. 35.

    Andersson J. Re: PET scan reconstructions (item 009521 in SPM mail archive). 2002. https://www.jiscmail.ac.uk/cgi-bin/wa.exe?A2=ind02&L=SPM&P=R174130. Accessed 4 Feb 2009.

  36. 36.

    Hoffman EJ, Cutler PD, Guerrero TM, Digby WM, Mazziotta JC. Assessment of accuracy of PET utilizing a 3-D phantom to simulate the activity distribution of [18F]fluorodeoxyglucose uptake in the human brain. J Cereb Blood Flow Metab 1991;11:A17–25.

    PubMed  CAS  Google Scholar 

  37. 37.

    Ishii K, Willoch F, Minoshima S, Drzezga A, Ficaro EP, Cross DJ, et al. Statistical brain mapping of 18F-FDG PET in Alzheimer’s disease: validation of anatomic standardization for atrophied brains. J Nucl Med 2001;42:548–57.

    PubMed  CAS  Google Scholar 

  38. 38.

    Sokoloff L, Reivich M, Kennedy C, Des Rosiers MH, Patlak CS, Pettigrew KD, et al. The [14C]deoxyglucose method for the measurement of local cerebral glucose utilization: theory, procedure, and normal values in the conscious and anesthetized albino rat. J Neurochem 1977;28:897–916.

    PubMed  Article  CAS  Google Scholar 

  39. 39.

    Okada J, Yoshikawa K, Imazeki K, Uno K, Minoshima S, Itami J, et al. Change of cerebral glucose metabolism by antineoplastic drug. Am J Physiol Imaging 1991;6:162–6.

    PubMed  CAS  Google Scholar 

  40. 40.

    Phillips PC, Dhawan V, Strother SC, Sidtis JJ, Evans AC, Allen JC, et al. Reduced cerebral glucose metabolism and increased brain capillary permeability following high-dose methotrexate chemotherapy: a positron emission tomographic study. Ann Neurol 1987;21:59–63.

    PubMed  Article  CAS  Google Scholar 

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Correspondence to Ralph Buchert.

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Arlt, S., Brassen, S., Jahn, H. et al. Association between FDG uptake, CSF biomarkers and cognitive performance in patients with probable Alzheimer’s disease. Eur J Nucl Med Mol Imaging 36, 1090–1100 (2009). https://doi.org/10.1007/s00259-009-1063-7

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Keywords

  • Alzheimer’s disease
  • Cerebrospinal fluid
  • Positron emission tomography
  • 18F-Fluorodeoxyglucose
  • Statistical parametric mapping