- Research article
- Open Access
Distinct cerebrospinal fluid amyloid β peptide signatures in sporadic and PSEN1A431E-associated familial Alzheimer's disease
© Portelius et al; licensee BioMed Central Ltd. 2010
- Received: 22 August 2009
- Accepted: 14 January 2010
- Published: 14 January 2010
Alzheimer's disease (AD) is associated with deposition of amyloid β (Aβ) in the brain, which is reflected by low concentration of the Aβ1-42 peptide in the cerebrospinal fluid (CSF). There are at least 15 additional Aβ peptides in human CSF and their relative abundance pattern is thought to reflect the production and degradation of Aβ. Here, we test the hypothesis that AD is characterized by a specific CSF Aβ isoform pattern that is distinct when comparing sporadic AD (SAD) and familial AD (FAD) due to different mechanisms underlying brain amyloid pathology in the two disease groups.
We measured Aβ isoform concentrations in CSF from 18 patients with SAD, 7 carriers of the FAD-associated presenilin 1 (PSEN1) A431E mutation, 17 healthy controls and 6 patients with depression using immunoprecipitation-mass spectrometry. Low CSF levels of Aβ1-42 and high levels of Aβ1-16 distinguished SAD patients and FAD mutation carriers from healthy controls and depressed patients. SAD and FAD were characterized by similar changes in Aβ1-42 and Aβ1-16, but FAD mutation carriers exhibited very low levels of Aβ1-37, Aβ1-38 and Aβ1-39.
SAD patients and PSEN1 A431E mutation carriers are characterized by aberrant CSF Aβ isoform patterns that hold clinically relevant diagnostic information. PSEN1 A431E mutation carriers exhibit low levels of Aβ1-37, Aβ1-38 and Aβ1-39; fragments that are normally produced by γ-secretase, suggesting that the PSEN1 A431E mutation modulates γ-secretase cleavage site preference in a disease-promoting manner.
- Amyloid Precursor Protein
- A431E Mutation
- PSEN1 Mutation
- Relative Abundance Pattern
- Cotton Wool Plaque
Pathological hallmarks of Alzheimer's disease (AD) include synaptic and neuronal degeneration along with extracellular deposits of amyloid β protein (Aβ) in senile plaques in the cerebral cortex . These changes are reflected in vivo by elevated tau protein concentrations and reduced levels of the aggregation prone 42 amino acid isoform of Aβ (Aβ1-42) in the cerebrospinal fluid (CSF) [2, 3]. The mechanism underlying CSF Aβ1-42 reduction in AD is thought to be sequestration of the peptide in senile plaques. Accordingly, studies have found a strong correlation between low Aβ1-42 in CSF and high numbers of plaques in the neocortex and hippocampus , as well as high retention of Pittsburgh Compound-B (PIB) in positron emission tomography (PET) scans that directly reflect plaque pathology in the brain [5, 6]. Aβ peptides are generated through proteolytic processing of the transmembrane amyloid precursor protein (APP). In the amyloidogenic pathway, APP is cleaved by two aspartyl proteases, first by β-secretase within its ectodomain and subsequently by γ-secretase within its transmembrane domain . Certain forms of Aβ1-42 may act early in the disease process by disrupting synaptic plasticity mechanisms that are believed to underlie memory in the hippocampal network [8, 9].
γ-Secretase is a multiprotein complex with the presenilin (PS) proteins at its enzymatic core . Because of imprecise cleavage specificity, γ-secretase generates Aβ peptides of variable length at the carboxyl terminus. Mutations in the PS-encoding PSEN1 and PSEN2 genes that accelerate brain amyloid plaque pathology and cause early onset familial AD (FAD) increase the Aβ1-42/Aβ1-40 ratio in primary fibroblasts and plasma of affected individuals, in transfected cells, and in transgenic animals, but this effect is modest and not always reproducible [11, 12]. To date, more than 160 distinct AD-promoting missense mutations have been identified in PSEN1 and three in PSEN2.
In addition to Aβ1-42 and Aβ1-40, there are several shorter isoforms of Aβ . We recently identified a set of 18 N- and C-terminally truncated Aβ peptides in CSF using immunoprecipitation-mass spectrometry (IP-MS) [14, 15]. Their relative abundance pattern distinguished AD from controls with an accuracy of 86% . Here, we test the hypotheses that (i) sporadic AD patients are different from controls and patients with depression with regards to their CSF Aβ isoform pattern, (ii) SAD patients and FAD mutation carriers differ in their Aβ isoform pattern as a reflection of different mechanisms underlying brain amyloid deposition in the two disease groups, and (iii) the AD-associated Aβ1-16 fragment affects hippocampal synaptic plasticity.
Demographic characteristics of patients and controlsa
SAD patients (n = 18)
PSEN1A431E mutation carriers (n = 7)
(n = 17)
Patients with depression (n = 6)
Summary of the 7 subjects with the PSEN1 A431E mutation
CSF Aβ isoform patterns are distinct across groups
Recent cell culture experiments using different secretase inhibitors suggest that Aβ1-16 is derived from concerted cleavages of APP by β - and α-secretase, thus reflecting a third metabolic pathway for APP . Curiously, depressed patients in this study also had higher Aβ1-16 levels than the healthy controls (Figure 2). Pending confirmation in independent and larger patient materials, this result may provide clues regarding altered APP metabolism in depression. There were no other Aβ-related changes in common in depression and SAD vs. controls.
FAD mutation carriers express low levels of Aβ1-37, Aβ1-38 and Aβ1-39 in CSF
AD-associated Aβ1-16 does not inhibit long-term potentiation
Although the findings of this study are intriguing, there are some limitations that should be mentioned.
First, the study is small and the important findings, i.e., the increased levels of Aβ1-16 in AD and depression and the reduced levels of Aβ1-37, Aβ1-38 and Aβ1-39 in PSEN1 A431E-caused FAD, are in need of replication.
Second, CSF samples were obtained at different centers. However, no center effects on Aβ isoform levels were detected. Further, when levels of the various Aβ peptides were compared between the 7 FAD mutation carriers and their 3 similarly aged non-mutation carrying kin from whom CSF was obtained at the same center, levels of Aβ1-37, Aβ1-38 and Aβ1-39 but not of other Aβ peptides were significantly lower (P ≤ 0.003) and non-overlapping. In fact, differences in these levels were greater than that of Aβ1-42, which was non-significant in this small subpopulation. The finding of decreased levels of Aβ1-37, Aβ1-38 and Aβ1-39 in the CSF of persons with the A431E PSEN1 mutation therefore appears to be a robust finding. How this might be related to the cotton wool plaque pathology that has been demonstrated to consist of increased amounts of N-terminally truncated forms of Aβ42 in persons with other PSEN1 mutations  is unclear.
Third, the age distribution differed between the different groups. Of all the Aβ isoforms, in all study groups, only Aβ1-34 in the controls correlated with age (rs = -0.61, P = 0.01). However, Aβ1-34 is higher in the AD group compared with the controls, which is opposite to what would have been expected if the difference were due to an age effect. This makes age an unlikely confounder.
The findings presented here show that (i) SAD patients differ from cognitively normal individuals and depressed patients with regards to their CSF Aβ isoform pattern and (ii) carriers of the FAD-associated PSEN1 A431E mutation have low CSF levels of C-terminally truncated Aβ peptides shorter than Aβ1-40, suggesting a loss of function effect that leads to a relative abundance of aggregation-prone Aβ1-42. The influence of Aβ1-37, Aβ1-38 and Aβ1-39 reductions on Aβ1-42 oligomerization and toxicity needs to be examined in experimental studies. CSF Aβ1-16 may be a positive biomarker for AD but its specificity against depression must be tested further.
Patients with SAD and major depression were diagnosed according to DSM-IIIR criteria . SAD patients fulfilled the criteria of probable AD defined by NINCDS-ADRDA (National Institute of Neurological and Communicative Disorders - Stroke/Alzheimer's Disease and Related Disorders Association) . The seven persons carrying the A431E mutation in PSEN1  were participants in a study of symptomatic persons affected by (n = 2), and asymptomatic persons at-risk for (n = 5) FAD being conducted at UCLA. Subjects seen at UCLA underwent a comprehensive clinical evaluation by investigators blind to their genetic status that included the Clinical Dementia Rating scale . Three of the 17 controls were non-mutation carrying family members also enrolled in this study. The healthy controls were mainly recruited from senior citizen organizations and through information meetings on dementia. A few controls were spouses of subjects in the study. Inclusion criteria for controls were that they should be physically and mentally healthy and not experiencing or exhibiting any cognitive impairment. All controls were thoroughly interviewed about their somatic and mental health by researchers before inclusion in the study. Mini-mental state examination (MMSE) was used as a global measure of cognitive functioning . The study was approved by the ethics committees of Ludwig-Maximilian University, Germany, and UCLA and UCSD, USA.
CSF sampling and biochemical analyses
CSF samples were collected in the morning by lumbar puncture (LP) through the L3/L4 or L4/L5 interspace. CSF was collected in polypropylene tubes in 500 μL aliquots that were centrifuged, frozen and stored at -80°C pending biochemical analyses, without being thawed and re-frozen. The immunoprecipitation and mass spectrometric analysis were conducted as described before . Briefly, 8 μg of the monoclonal antibody 6E10 (epitope 4-9, Signet Laboratories Inc., Dedham, USA) was used together with magnetic Dynabeads (Sheep anti-mouse IgG) for immunoprecipitating C-terminally truncated Aβ peptides from 1 mL CSF. The samples were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOFMS, Autoflex, Bruker Daltonics, Bremen, Germany) operating in reflector mode. An in house MATLAB® program (Mathworks Inc. Natick, MA, USA) was used for integration of the peaks for each spectrum and the integration limits were from-2 to +5 m/z relative to the monoisotopic peak. Prior to the statistical analysis the peak areas were normalized to the sum of the integrated peaks.
Electrophysiological experiments were performed on hippocampal slices from 35-60 day-old male Wistar rats. The rats were anesthetized with isoflurane (Abbott) prior to decapitation. The brain was removed and placed in an ice-cold solution containing (in mM): 140 cholineCl, 2.5 KCl, 0.5 CaCl2, 7 MgCl2, 25 NaHCO3, 1.25 NaH2PO4, 1.3 ascorbic acid and 7 dextrose. Transverse hippocampal slices (400 μm thick) were cut with a vibratome (HM 650 V Microm, Germany) in the same ice-cold solution and were subsequently stored in artificial cerebrospinal fluid (ACSF) containing (in mM): 124 NaCl, 3 KCl, 2 CaCl2, 4 MgCl2, 26 NaHCO3, 1.25 NaH2PO4, 0.5 ascorbic acid, 3 myo-inositol, 4 D, L-lactic acid, and 10 D-glucose. After at least one hour of storage at 25°C, a single slice was transferred to a recording chamber where it was kept submerged in a constant flow (~2 ml min-1) at 30-32°C. The perfusion fluid contained (in mM) 124 NaCl, 3 KCl, 4 CaCl2, 4 MgCl2, 26 NaHCO3, 1.25 NaH2PO4, and 10 D-glucose. Picrotoxin (100 μM, Sigma-Aldrich Stockholm, Sweden) was always present in the perfusion fluid to block GABAA receptor-mediated activity. All solutions were continuously bubbled with 95% O2 and 5% CO2 (pH ~7.4). The higher than normal Ca2+ and Mg2+ concentrations were used to inhibit spontaneous network activity. ACSF was spiked with synthetic Aβ1-16 (Bachem, Weil am Rhein, Germany) in water solution to a final concentration of 1 μg/L. Aβ1-42 oligomers were prepared according to a standard protocol . Briefly, 1 μM Aβ1-42 was dissolved in 1,1,1,3,3,3-hexofluoro-2-propanol (HFIP) on ice and incubated for 90 minutes in room temperature. HFIP was removed using speedvac and the remaining Aβ1-42 peptide film was stored at -80°C. The film was dissolved in DMSO to 5 mM, sonicated, further diluted in PBS containing 0.2% SDS to 400 μM and incubated for six hours at 37°C. Water was added to a concentration of 100 μM and this solution was incubated for 18 hours at 37°C. Finally, the solution was centrifuged at 3000 g for 20 minutes and stored for no more than three days at 4°C.
Electrical stimulation of Schaffer collateral/commissural axons and recordings of synaptic responses were carried out in the stratum radiatum of the CA1 region. Stimuli consisted of biphasic constant current pulses (15-80 μA, 200 μS, STG 1002 Multi Channel Systems MCS Gmbh, Reutlingen, Germany) delivered through tungsten wires (resistance ~0.1 MΩ). The synaptic input was activated every 5 s. Field excitatory postsynaptic potentials (EPSPs) were recorded with a glass micropipette (1 M NaCl, resistance ~4 MΩ). Field EPSPs were sampled at 10 kHz with an EPC-9 amplifier (HEKA Elektronik, Lambrecht, Germany) and filtered at 1 kHz. Evoked responses were analyzed off-line using custom-made IGOR Pro (WaveMetrics, Lake Oswego, OR) software. Field EPSP magnitude was estimated by linear regression over the first 0.8 ms of the initial slope. The presynaptic volley was measured as the slope of the initial positive-negative deflection, and it was not allowed to change by more than 15% during the experiment.
Multivariate discriminant analysis (DA) was performed using the orthogonal projection to latent structure (OPLS) algorithm  implemented in the software SIMCA P+ v. 12 (Umetrics, Umeå, Sweden). In general, OPLS-DA finds the direction (score vector) in the multidimensional orthogonal space created by the different measured variables that best separate the predefined classes. To visualize the result from an OPLS-DA, the observations are projected onto a plane spanned by the score vectors. The contribution of the different variables to the score vectors is presented in a loading plot. A vector from the origin to a variable in the loading plot points in the direction that an observation in the score plot will be displaced if the value of the variable is increased. Also, the extent of the displacement is proportional to the magnitude of the vector . Comparisons between groups with regards to individual, normalized Aβ isoform intensities were performed using nonparametric Kruskal-Wallis test, followed by the Mann-Whitney test. P-values for the Mann-Whitney test were reported given that (i) the p-value for the Kruskal-Wallis was below 0.05 after Bonferroni correction (15 tests) and (ii) the difference was significant at p < 0.05 using Dunn's post hoc test for multiple comparisons. Electrophysiological data were evaluated using Student's t-test.
This work was supported by grants from the Swedish Research Council (projects 2006-6227, 2006-2740 and 2006-3505), the Alzheimer's Association (NIRG-08-90356), cNEUPRO, the Royal Swedish Academy of Sciences, the Sahlgrenska University Hospital, the Inga-Britt and Arne Lundberg Research Foundation, the Göteborg Medical Society, the Swedish Medical Society, Swedish Brain Power, Stiftelsen Gamla Tjänarinnor, Gun och Bertil Stohnes stiftelse, Åhlén-stiftelsen, Alzheimer Foundation, Sweden, U.S. PHS K08 AG-22228, AG-O5131 and AG-023185, California DHS #04-35522, Alzheimer's Disease Research Center Grant P50 AG-16570, General Clinical Research Centers Program M01-RR00865, the Sidell Kagan Foundation, the Shirley and Jack Goldberg Trust, and the Easton Consortium for Biomarker and Drug Discovery.
- Blennow K, de Leon MJ, Zetterberg H: Alzheimer's disease. Lancet. 2006, 368: 387-403. 10.1016/S0140-6736(06)69113-7.PubMedView ArticleGoogle Scholar
- Hampel H, Burger K, Teipel SJ, Bokde AL, Zetterberg H, Blennow K: Core candidate neurochemical and imaging biomarkers of Alzheimer's disease. Alzheimers Dement. 2008, 4: 38-48. 10.1016/j.jalz.2007.08.006.PubMedView ArticleGoogle Scholar
- Blennow K, Hampel H: CSF markers for incipient Alzheimer's disease. Lancet Neurol. 2003, 2: 605-613. 10.1016/S1474-4422(03)00530-1.PubMedView ArticleGoogle Scholar
- 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: 652-656.PubMedView ArticleGoogle Scholar
- Fagan AM, Mintun MA, Mach RH, Lee SY, Dence CS, Shah AR, LaRossa GN, Spinner ML, Klunk WE, Mathis CA, DeKosky ST, Morris JC, Holtzman DM: Inverse relation between in vivo amyloid imaging load and cerebrospinal fluid Abeta42 in humans. Ann Neurol. 2006, 59: 512-519. 10.1002/ana.20730.PubMedView ArticleGoogle Scholar
- Forsberg A, Engler H, Almkvist O, Blomquist G, Hagman G, Wall A, Ringheim A, Långström B, Nordberg A: PET imaging of amyloid deposition in patients with mild cognitive impairment. Neurobiol Aging. 2008, 29: 1456-1465. 10.1016/j.neurobiolaging.2007.03.029.PubMedView ArticleGoogle Scholar
- Andreasson U, Portelius E, Andersson ME, Blennow K, Zetterberg H: Aspects of beta-amyloid as a biomarker for Alzheimer's disease. Biomarkers Med. 2007, 1: 59-78. 10.2217/175203184.108.40.206.View ArticleGoogle Scholar
- Klyubin I, Betts V, Welzel AT, Blennow K, Zetterberg H, Wallin A, Lemere CA, Cullen WK, Peng Y, Wisniewski T, Selkoe DJ, Anwyl R, Walsh DM, Rowan MJ: Amyloid beta protein dimer-containing human CSF disrupts synaptic plasticity: prevention by systemic passive immunization. J Neurosci. 2008, 28: 4231-4237. 10.1523/JNEUROSCI.5161-07.2008.PubMedPubMed CentralView ArticleGoogle Scholar
- Shankar GM, Bloodgood BL, Townsend M, Walsh DM, Selkoe DJ, Sabatini BL: Natural oligomers of the Alzheimer amyloid-beta protein induce reversible synapse loss by modulating an NMDA-type glutamate receptor-dependent signaling pathway. J Neurosci. 2007, 27: 2866-2875. 10.1523/JNEUROSCI.4970-06.2007.PubMedView ArticleGoogle Scholar
- Selkoe DJ: Alzheimer's disease: genes, proteins, and therapy. Physiol Rev. 2001, 81: 741-766.PubMedGoogle Scholar
- Bentahir M, Nyabi O, Verhamme J, Tolia A, Horré K, Wiltfang J, Esselmann H, De Strooper B: Presenilin clinical mutations can affect gamma-secretase activity by different mechanisms. J Neurochem. 2006, 96: 732-742. 10.1111/j.1471-4159.2005.03578.x.PubMedView ArticleGoogle Scholar
- Kumar-Singh S, Theuns J, Van Broeck B, Pirici D, Vennekens K, Corsmit E, Cruts M, Dermaut B, Wang R, Van Broeckhoven C: Mean age-of-onset of familial alzheimer disease caused by presenilin mutations correlates with both increased Abeta42 and decreased Abeta40. Hum Mutat. 2006, 27: 686-695. 10.1002/humu.20336.PubMedView ArticleGoogle Scholar
- Portelius E, Zetterberg H, Gobom J, Andreasson U, Blennow K: Targeted proteomics in Alzheimer's disease: focus on amyloid-beta. Expert Rev Proteomics. 2008, 5: 225-237. 10.1586/147894220.127.116.11.PubMedView ArticleGoogle Scholar
- Portelius E, Westman-Brinkmalm A, Zetterberg H, Blennow K: Determination of beta-amyloid peptide signatures in cerebrospinal fluid using immunoprecipitation-mass spectrometry. J Proteome Res. 2006, 5: 1010-1016. 10.1021/pr050475v.PubMedView ArticleGoogle Scholar
- Portelius E, Tran AJ, Andreasson U, Persson R, Brinkmalm G, Zetterberg H, Blennow K, Westman-Brinkmalm A: Characterization of amyloid beta peptides in cerebrospinal fluid by an automated immunoprecipitation procedure followed by mass spectrometry. J Proteome Res. 2007, 6: 4433-4439. 10.1021/pr0703627.PubMedView ArticleGoogle Scholar
- Portelius E, Zetterberg H, Andreasson U, Brinkmalm G, Andreasen N, Wallin A, Westman-Brinkmalm A, Blennow K: An Alzheimer's disease-specific beta-amyloid fragment signature in cerebrospinal fluid. Neurosci Lett. 2006, 409: 215-219. 10.1016/j.neulet.2006.09.044.PubMedView ArticleGoogle Scholar
- Yescas P, Huertas-Vazquez A, Villarreal-Molina MT, Rasmussen A, Tusié-Luna MT, López M, Canizales-Quinteros S, Alonso ME: Founder effect for the Ala431Glu mutation of the presenilin 1 gene causing early-onset Alzheimer's disease in Mexican families. Neurogenetics. 2006, 7: 195-200. 10.1007/s10048-006-0043-3.PubMedView ArticleGoogle Scholar
- Murrell J, Ghetti B, Cochran E, Macias-Islas MA, Medina L, Varpetian A, Cummings JL, Mendez MF, Kawas C, Chui H, Ringman JM: The A431E mutation in PSEN1 causing familial Alzheimer's disease originating in Jalisco State, Mexico: an additional fifteen families. Neurogenetics. 2006, 7: 277-279. 10.1007/s10048-006-0053-1.PubMedPubMed CentralView ArticleGoogle Scholar
- Cochran EJ, Murrell JR, Fox J, Ringman J, Ghetti B: A novel mutation in the Presenilin-1 gene (A431E) associated with early-onset Alzheimer's disease. J Exp Neuropathol Exp Neurol. 2001, 60: 544-Google Scholar
- Ringman JM, Younkin SG, Pratico D, Seltzer W, Cole GM, Geschwind DH, Rodriguez-Agudelo Y, Schaffer B, Fein J, Sokolow S, Rosario ER, Gylys KH, Varpetian A, Medina LD, Cummings JL: Biochemical markers in persons with preclinical familial Alzheimer disease. Neurology. 2008, 71: 85-92. 10.1212/01.wnl.0000303973.71803.81.PubMedView ArticleGoogle Scholar
- Andreasen N, Zetterberg H: Amyloid-related biomarkers for Alzheimer's disease. Curr Med Chem. 2008, 15: 766-771. 10.2174/092986708783955572.PubMedView ArticleGoogle Scholar
- Portelius E, Price E, Brinkmalm G, Stiteler M, Olsson M, Persson R, Westman-Brinkmalm A, Zetterberg H, Simon AJ, Blennow K: A novel pathway for amyloid precursor protein processing. Neurobiol Aging. 2009, doi:10.1016/j.neurobiolaging.2009.06.002; PMID: 19604603,Google Scholar
- Jan A, Gokce O, Luthi-Carter R, Lashuel HA: The ratio of monomeric to aggregated forms of Abeta40 and Abeta42 is an important determinant of amyloid-beta aggregation, fibrillogenesis, and toxicity. J Biol Chem. 2008, 283: 28176-28189. 10.1074/jbc.M803159200.PubMedPubMed CentralView ArticleGoogle Scholar
- Murray MM, Bernstein SL, Nyugen V, Condron MM, Teplow DB, Bowers MT: Amyloid beta protein: Abeta40 inhibits Abeta42 oligomerization. J Am Chem Soc. 2009, 131: 6316-6317. 10.1021/ja8092604.PubMedPubMed CentralView ArticleGoogle Scholar
- Wasling P, Daborg J, Riebe I, Andersson M, Portelius E, Blennow K, Hanse E, Zetterberg H: Synaptic retrogenesis and amyloid-beta in Alzheimer's disease. J Alzheimers Dis. 2009, 16: 1-14.PubMedGoogle Scholar
- Karlstrom H, Brooks WS, Kwok JB, Broe GA, Kril JJ, McCann H, Halliday GM, Schofield PR: Variable phenotype of Alzheimer's disease with spastic paraparesis. J Neurochem. 2008, 104: 573-583.PubMedGoogle Scholar
- American Psychiatric Association: Diagnostic and statistical manual of mental disorders, third edition, revised. 1987, Arlington, VA, USA: American Psychiatric AssociationGoogle Scholar
- 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: 939-944.PubMedView ArticleGoogle Scholar
- Morris JC: Clinical dementia rating: a reliable and valid diagnostic and staging measure for dementia of the Alzheimer type. Int Psychogeriatr. 1997, 9 (Suppl 1): 173-176. 10.1017/S1041610297004870. discussion 177-178PubMedView ArticleGoogle Scholar
- Folstein MF, Folstein SE, McHugh PR: "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975, 12: 189-198. 10.1016/0022-3956(75)90026-6.PubMedView ArticleGoogle Scholar
- Barghorn S, Nimmrich V, Striebinger A, Krantz C, Keller P, Janson B, Bahr M, Schmidt M, Bitner RS, Harlan J, Barlow E, Ebert U, Hillen H: Globular amyloid beta-peptide oligomer - a homogenous and stable neuropathological protein in Alzheimer's disease. J Neurochem. 2005, 95: 834-847. 10.1111/j.1471-4159.2005.03407.x.PubMedView ArticleGoogle Scholar
- Bylesjö M, Rantalainen M, Cloarec O, Nicholson J, Holmes E, Trygg J: OPLS discriminant analysis: combining the strengths of PLS-DA and SIMCA classification. J Chemometrics. 2007, 20: 341-351. 10.1002/cem.1006.View ArticleGoogle Scholar
- Eriksson L, Johansson E, Kettaneh-Wold N, Trygg J, Wikström C, Wold S: Multi- and Megavariate Data Analysis Part I: Basic Principles and Applications, Second revised and enlarged edition. 2006, Umeå: Umetrics ABGoogle Scholar
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