Stratification by Genetic and Demographic Characteristics Improves Diagnostic Accuracy of Cerebrospinal Fluid Biomarkers in Rapidly Progressive Dementia

Abstract

Background: Cerebrospinal fluid (CSF) biomarkers are routinely used for the differential diagnosis of rapidly progressive dementia, but are also affected by patients’ characteristics.

Objective: To assess if stratification by age, sex, and genetic risk factors improves the accuracy of cerebrospinal fluid (CSF) biomarkers in patients with rapidly progressive dementia.

Methods: 1,538 individuals with sporadic Creutzfeldt-Jakob disease (CJD), 173 with classic Alzheimer’s disease (cAD), 37 with rapidly progressive Alzheimer’s disease (rpAD), and 589 without signs of dementia were included in this retrospective diagnostic study. The effect of age, sex, PRNP codon 129, and APOE genotype on CSF levels of tau, p-tau, Aβ_1–42, and Aβ_1–40 values measured at time of diagnostic work-up was assessed.

Results: Tau was a better marker for the differentiation of CJD and rpAD in older (AUC:0.97; 95% CI:0.96–1.00) than in younger (AUC:0.91; 95% CI:0.87–0.94) patients as tau levels increased with age in CJD patients, but not in rpAD patients. PRNP codon 129 and APOE genotype had complex effects on biomarkers in all diseases, making stratification by genotype a powerful tool. In females (AUC:0.78; 95% CI:0.65–0.91) and patients older than 70 (AUC:0.78; 95% CI:0.62–0.93), tau was able to differentiate with moderate accuracy between cAD and rpAD patients.

Conclusion: Implementation of stratum-specific reference ranges improves the diagnostic accuracy of CSF biomarkers for the differential diagnosis of rapidly progressive dementia. Diagnostic criteria developed for this setting have to take this into account.

Keywords

Alzheimer’s disease amyloid-beta biomarker cerebrospinal fluid Creutzfeldt-Jakob disease dementia tau

INTRODUCTION

Cerebrospinal fluid (CSF) biomarkers have become an essential part of the routine diagnostic work-up for dementia as well as of diagnostic criteria for neurodegenerative diseases [1, 2]. While some of these biomarkers represent disease-specific pathophysiological patterns [e.g., amyloid-β (Aβ)_1–42 and Aβ_1–40 in Alzheimer’s disease (AD)], others are related to unspecific signs of neurodegeneration (e.g., tau protein) making them a potential marker for more than one form of dementia [1, 3]. As differentiation of distinct forms of dementia becomes increasingly more important due to the prospect of disease-specific treatment options, direct comparisons of how biomarkers can differentiate between these dementia forms have been addressed by several studies for many of the currently available CSF biomarkers [4 –6]. However, these studies did not take into account that CSF biomarkers depend not only on underlying disease, but are also affected by demographic and genetic characteristics. APOE genotypes, for instance, have been shown to modulate Aβ_1–42 values in AD and Creutzfeldt-Jakob disease (CJD) [7, 8]; tau levels differed considerably between PRNP codon 129 genotypes in CJD with some CJD subtypes showing tau levels not clearly distinguishable from AD [9].

These findings indicate that stratification by genetic and demographic factors might be a powerful tool for increasing the diagnostic performance of CSF biomarkers.

It was the aim of this study to investigate comprehensively if knowledge on demographic factors and genetic markers is helpful or even necessary for correctly differentiating different forms of rapidly progressive dementia based on established CSF biomarkers.

MATERIALS AND METHODS

Study population

This diagnostic study is based on data from two ongoing cohort studies at the Clinical Dementia Center Göttingen [10, 11]. Patients diagnosed with probable or definite sporadic CJD (sCJD) as well as patients diagnosed with AD according to the Dubois criteria were considered for inclusion in the study [1, 2]. AD patients were further sub-classified in classic AD (cAD) and rapidly progressive AD [12 –14]. Rapidly progressive AD (rpAD) was defined by a velocity of cognitive decline of >6 points/year on the Mini-Mental Status Examination scale (MMSE) as proposed by Schmidt et al. [14]. As a control group, individuals in the same age range with no signs of dementia but defined other clinical indication for a lumbar puncture were included. The presence of neurodegenerative diseases was ruled out in all control patients during follow-up using routine clinical diagnostics. Only patients with an either clinically or pathologically defined alternative diagnosis (psychosis, bipolar disorder, schizophrenia, inflammatory and autoimmune diseases, meningitis, headache, vertigo, pain syndromes) were included. In all patients, lumbar punctures were performed at time of first routine diagnostic work up for their underlying symptoms.

CSF tests

CSF tau protein, phosphorylated tau-181 (p-tau) as well as Aβ_1–42 (Innogenetics, Ghent, Belgium) and Aβ_1–40 (The Genetics Company, Schlieren, Switzerland) levels were analyzed quantitatively using commercially available ELISA kits according to the manufacturer’s instructions.

Genetic testing

Genetic testing was performed on genomic DNA isolated from blood or brain tissue. Patients were investigated for their PRNP codon 129 genotype (MM, MV, VV) and APOE genotype (E2/E3, E3/E3, E2/E4, E3/E4, E4/E4) using routine genetic testing [15, 16]. For CJD patients, PRNP codon 129 genotypes were further stratified by PrP type into MM1, MM2, VV1, VV2, MV1, and MV2 if available. Due to sparse data in some genotypes and for mechanistic considerations, APOE genotypes were regrouped in “No E4 allele”, “One E4 allele”, and “E4/E4”.

Statistical analyses

Biomarker levels were logarithmized due to their skewed distributions and were then compared between groups using two-sided t-tests or ANOVAs with Tukey Post-hoc tests. Logarithmized means and confidence intervals were then back-transformed and displayed as such in tables. Receiver operating characteristics (ROC) analyses (stratified by genetic and demographic characteristics) were performed for the differential diagnosis of CJD and rpAD, CJD and AD (cAD and rpAD) as well as for a differentiation of AD in rpAD and cAD cases. For each comparison, the best cut-off was determined using the Youden index; sensitivity and specificity were reported for this cut-off value. In addition, cut-off values and specificities were calculated for a fixed sensitivity of 95% (Supplementary Table 4); this represents a situation in which the considered biomarkers are used as a screening test which might then be confirmed by a highly specific second test (e.g., RT-QuIC). All data analyses were performed using Stata 12 (StataCorp, USA).

Ethics

Informed consent for this study as well as for routine genetic testing was given by all study participants or their legal next of kin. Ethics approval was obtained from the local Ethics Committee of the University of Göttingen (Number 11/11/93 (+ Amendments) and Number 9/6/08).

RESULTS

A total of 1,538 CJD patients, 210 AD patients, and 589 non-demented individuals were included in this study; 37 AD patients fulfilled rpAD criteria (Table 1). There were no differences in sex (p = 0.967) and age (p = 0.517) between CJD and rpAD patients. PRNP codon 129 VV alleles were more frequent in CJD (35.6%) than in rpAD (18.2%, p = 0.124) or cAD patients (17.9%, p = 0.006), while APOE E4/E4 alleles were found more often in cAD and rpAD than in CJD patients (12.7% and 6.5% versus 2.2%, p < 0.001, Table 1).

Overall diagnostic accuracy

While Aβ_1–42, Aβ_1–40, and p-tau showed no to modest abilities to differentiate CJD and rpAD patients, tau could be identified as an almost perfect marker for differentiating between these two diseases (AUC:0.91; 95% CI:0.88–0.94, Tables 2 and 3); patients with rpAD, however, could not be differentiated reliably from cAD patients by any of the tested biomarkers (Table 4). All investigated biomarkers were able to differentiate patients with rapidly progressive dementia and cAD from control patients without dementia. Diagnostic accuracy, however, varied dependent on underlying disease (Supplementary Table 3).

Effect of sex on biomarkers and their diagnostic accuracy

In the group of rpAD patients, tau (p = 0.003) and p-tau (p = 0.147) levels were considerably higher in females than in males; there was no effect of sex on tau or p-tau levels in CJD or cAD patients (Table 2). This led to a clearly improved diagnostic accuracy of tau and p-tau for the differentiation of CJD and rpAD when ROC analyses were stratified by sex (tau specificity increased from 86% overall (AUC:0.91; 95% CI:0.88–0.94; cut-off: 1100 pg/ml) to 94% (AUC:0.95; 95% CI:0.91–0.98; cut-off: 750 pg/ml) in the female subgroup, Table 3). Moreover, rpAD patients could also be differentiated with good diagnostic accuracy from cAD patients based on tau values in the female subgroup (AUC:0.78; 95% CI:0.65–0.91), which was not the case in the overall analysis (AUC:0.64; 95% CI:0.53–0.75). For all other markers, stratification by sex did not affect AUC values.

Effect of age on biomarkers and their diagnostic accuracy

While tau and p-tau levels were increasing with age in CJD patients (and in non-demented control patients, Table 2, Supplementary Table 1), there was no (or an even decreasing) trend for tau levels in rpAD and cAD patients (Table 2). When stratifying tau values by age, it could be shown that with increasing age tau’s diagnostic accuracy for a differentiation of CJD and rpAD patients increased as well (Table 3). By applying age-specific cut-off values for the differentiation of both diseases, specificity could be increased from 86% overall to at least 94% in all strata. P-tau on the other hand could be used as a diagnostic marker for CJD versus rpAD in younger patients (AUC:0.85; 95% CI:0.65–1.00), but did not perform well in patients older than 70 years (AUC:0.62; 95% CI:0.43–0.80). As age did not influence biomarker values in rpAD and cAD cases, these observations were also true for the differentiation of CJD and cAD cases (Table 4). There were no apparent age trends for Aβ_1–42 or Aβ_1–40 in any of the disease entities (Table 2).

Effect of PRNP codon 129 genotype

PRNP codon 129 genotype affected tau, p-tau and Aβ_1–40 values in CJD patients as well as p-tau levels in rpAD patients (Table 2). In CJD patients, tau levels were significantly lower in MV than in MM and VV genotypes (p < 0.001), while Aβ_1–40 values were lowest in VV patients (p < 0.001). Stratification by PRNP codon 129 genotype increased the diagnostic accuracy of tau for CJD versus rpAD considerably from an overall AUC of 0.91 to an AUC of at least 0.96 in all strata (Table 3). The same was true for Aβ_1–40; in this case an original low overall AUC (0.57; 95% CI:0.45–0.68) could be increased to clinical useful accuracy levels in all strata, reaching the highest level in VV patients (AUC:0.87; 95% CI:0.73–0.99). For p-tau, levels increased in CJD patients with increasing numbers of V alleles. rpAD patients showed the same pattern as CJD patients; in cAD patients, MM alleles were associated with the highest p-tau levels (Table 2). The differing patterns (which were associated with disease progression rates) allowed p-tau to differentiate well between cAD and rpAD when stratifying by codon 129 genotype and applying genotype-specific cut-off values (Table 4). The poor overall diagnostic accuracy (AUC:0.53; 95% CI:0.42–0.65) could be increased considerably in the MM (AUC:0.75; 95% CI:0.43–0.85) and VV genotype stratum (AUC:0.74; 95% CI:0.46–1.00). Further stratification of codon 129 genotype by PrP type in CJD patients showed that PrP type had a huge effect on tau levels (with MM1, MV1, and VV2 subtypes showing the highest values, Table 2), but did not influence the other markers. As PrP type is only available postmortem, this is of primary interest for mechanical considerations, but not for diagnostic purposes.

Effect of APOE genotype

In CJD patients, Aβ_1–42 levels were decreasing with an increasing number of E4 alleles (p < 0.001, Table 2) allowing a better differentiation of rpAD versus CJD patients when one (AUC:0.77; 95% CI:0.66–0.88) or two E4 levels (AUC:0.81; 95% CI:0.40–1.00) were present than when no stratification was performed (AUC:0.53; 95% CI:0.44–0.61) (Table 3). Although there was no genotype effect on Aβ_1–40 levels in the different diseases, stratum-specific cut-off values led still to an increase of the diagnostic accuracy of Aβ_1–40 in the differentiation of rpAD and CJD to an AUC above 0.75 in all strata. Moreover, stratification by APOE genotype and application of strata-specific cut-off values increased the diagnostic accuracy of tau and p-tau in the differential diagnosis of CJD and rpAD in all strata (Table 3).

DISCUSSION

In our study we analyzed for the first time comprehensively how demographic characteristics and genetic markers influence CSF biomarkers and their diagnostic accuracy in the differential diagnosis of rapidly progressive dementia. We showed that stratification by sex led to a better differentiation of rpAD cases from CJD (and cAD) cases in females based on tau and p-tau levels, while it had no effect on other markers. A similar situation was found for patient’s age and PRNP codon 129 genotype. Biomarkers like tau and p-tau had been shown to increase with age in healthy individuals in previous studies which could be confirmed by our work [17 –20]. This age pattern was found in our study for CJD patients as well, while tau levels were not affected by age in rpAD patients and decreased even slightly with increasing age in cAD cases. These disease-specific effects might be due to different pathways of tau degradation in the respective diseases. Independently of their molecular correlates, observed differences imply that information on age needs to be incorporated when developing reference values and thresholds for tau and p-tau as disease-specific biomarkers in rapidly progressive dementia. This is supported by the observation that best cut-off values for a differentiation of rpAD and CJD based on total tau decreased with age (1,700 in the youngest, 1,100 in the oldest age group, Table 3). Furthermore, it has been shown before, that tau levels are highly dependent on PRNP codon 129 genotype in CJD patients [9, 21], and that stratification by genotype might be a valuable tool [22]. This was confirmed by our study. Interestingly, rpAD biomarker levels were affected in a similar way by PRNP genotype as they were in CJD patients, while cAD biomarker levels showed a different pattern. This might suggest that disease progression is not only genotype-specific in CJD, but also in AD patients (however, in a more complex way). Information on PRNP codon 129 genotype was especially helpful when trying to differentiate CJD and rpAD patients based on tau and Aβ_1–40 levels. Although PRNP codon 129 alleles alone are not enough to fully describe biomarker levels in CJD patients, stratifying by genotype and applying genotype-specific cut-off values already improved the diagnostic accuracy of tau for a differentiation of CJD and AD patients considerably (sensitivity increased from 84% overall to more than 86% in all strata, specificity from 86% to more than 92%, Table 3). This is of clinical importance as information on PrP type (which would be necessary for a full understanding of tau levels in CJD patients) is usually only available post-mortem. Although APOE genotypes did not have a relevant overall effect on biomarker values except for Aβ_1–42, the diagnostic accuracy of tau and the amyloids was much higher after stratification for APOE genotype. In general, tau offered good to excellent discriminatory ability in all subgroups, while Aβ_1–40 and Aβ_1–42 were only helpful when stratified by genetic characteristics. This was especially the case when stratifying tau levels by age; this led to an increase of specificity from 40% overall to more than 86% in all strata when fixing sensitivity at 95%. Age-stratified tau levels could thus be used as a first highly sensitive screening test for differentiating CJD from rpAD that could then be complemented in a second step by a highly specific test like RT-QuIC.

The genotype- and age-dependent differences in levels of biomarkers presented in our study might impact the future diagnostic work up of rapidly progressive dementia. In addition, the current data may shed a light on the codon 129 genotype-dependent role of tau and p-tau in the pathophysiological mechanisms of CJD and AD. Genotype-dependent biomarker patterns in CJD might represent genotype-dependent clinical manifestations and neuropathological features which have been described extensively in the literature [9 , 23]. Thus, understanding and analyzing the genotype-dependent biomarker profiles can help us in understanding genotype-dependent pathophysiological mechanisms in the brain.

A major strength of this study is the comprehensive analysis of biomarkers and modifying factors (including genetic markers) in a unique and large sample of patients with rapidly progressive dementia and cAD. However, despite the total sample size of 2,292, our study was still not large enough for, e.g., analyzing the effect of all six APOE genotype alleles at the same time. Moreover, the number of rpAD patients was relatively small, limiting the conclusions that can be drawn for this subgroup. A major limitation of our study is the fact that genetic characteristics were only available for a subset of the study population; this might have introduced selection bias in our analyses. However, data were mainly missing as patients or their next of kin did not give informed consent to genetic analyses. As these decisions are unlikely to depend on biomarker levels measured in this study, the potential for selection bias is rather small. Comparisons to the control group might have overestimated true diagnostic accuracy in a clinical setting as control patients represented a wide spectrum of neurological diseases, and were not restricted to patients with similar symptom complexes (as, for example, inflammatory or auto-immune diseases). The observed trend to a decrease of tau levels with increasing age is in contrast to previous studies [24]; this could indicate the presence of selection bias for our study population, e.g., in the way that older patients with AD symptoms were less likely to be referred to our tertiary-care center if their tau values were supportive of an AD diagnosis. However, most of the patients enrolled in our study received their first lumbar puncture in our center, so that this is unlikely to have happened. In our study, we focused mainly on biomarkers already established for the diagnosis of AD and did not consider 14-3-3, which is a good diagnostic test for CJD but has been shown to be unaltered in AD patients. In addition, we did not consider combination of biomarkers; although they might increase the overall diagnostic accuracy in the differential diagnosis of rapidly progressive dementia [6], stratification of these combined biomarkers by demographic and genetic factors would represent a mixture of the stratification effects of the single biomarkers.

In conclusion, we propose that CSF biomarker-based diagnosis of rapid progressive dementia should take into account demographic and genetic characteristics by applying stratum-specific reference ranges; this can be easily translated into clinical practice, as, for example, different cut-off values based on the age of the respective patient can be applied without additional effort. By doing so, the diagnostic accuracy of CSF biomarkers can be improved considerably. Moreover, our results should enforce future molecular research on the differential effect of age and codon 129 genotype on CSF tau and p-tau levels.

Footnotes

ACKNOWLEDGMENTS

This study was supported by the Robert Koch-Institute through funds of the Federal Ministry of Health (grant no. 1369-341), by a grant from the European Commission: PRIORITY FP7 (grant no. 222887), by the EU joint programme -Neurodegenerative Disease Research (JPND - DEMTEST: Biomarker based diagnosis of rapidly progressive dementias-optimization of diagnostic protocols, 01ED1201A) as well as by the Alzheimer-Forschungs-Initiative e.V. (AFI 12851).

Authors’ disclosures available online ().

Appendix

References

Dubois

, Feldman

, Jacova

, Dekosky

, Barberger-Gateau

, Cummings

, Delacourte

, Galasko

, Gauthier

, Jicha

, Meguro

, O’Brien

, Pasquier

, Robert

, Rossor

, Salloway

, Stern

, Visser

, Scheltens

(2007) Research criteria for the diagnosis of Alzheimer’s disease: Revising the NINCDS-ADRDA criteria. Lancet Neurol 6, 734–746.

Zerr

, Kallenberg

, Summers

, Romero

, Taratuto

, Heinemann

, Breithaupt

, Varges

, Meissner

, Ladogana

, Schuur

, Haik

, Collins

, Jansen

, Stokin

, Pimentel

, Hewer

, Collie

, Smith

, Roberts

, Brandel

, van Duijn

, Pocchiari

, Begue

, Cras

, Will

, Sanchez-Juan

(2009) Updated clinical diagnostic criteria for sporadic Creutzfeldt-Jakob disease. Brain 132, 2659–2668.

Otto

, Wiltfang

, Cepek

, Neumann

, Mollenhauer

, Steinacker

, Ciesielczyk

, Schulz-Schaeffer

, Kretzschmar

, Poser

(2002) Tau protein and 14-3-3 protein in the differential diagnosis of Creutzfeldt-Jakob disease. Neurology 58, 192–197.

Engelborghs

, De Vreese

, Van de Casteele

, Vanderstichele

, Van Everbroeck

, Cras

, Martin

, Vanmechelen

, De Deyn

(2008) Diagnostic performance of a CSF-biomarker panel in autopsy-confirmed dementia. Neurobiol Aging 29, 1143–1159.

Schoonenboom

, Reesink

, Verwey

, Kester

, Teunissen

, van de Ven

, Pijnenburg

, Blankenstein

, Rozemuller

, Scheltens

, van der Flier

(2012) Cerebrospinal fluid markers for differential dementia diagnosis in a large memory clinic cohort. Neurology 78, 47–54.

Llorens

, Schmitz

, Karch

, Cramm

, Lange

, Gherib

, Varges

, Schmidt

, Zerr

, Stoeck

(2016) Comparative analysis of cerebrospinal fluid biomarkers in the differential diagnosis of neurodegenerative dementia. Alzheimers Dement 12, 577–589.

Varges

, Jung

, Gawinecka

, Heinemann

, Schmitz

, von Ahsen

, Krasnianski

, Armstrong

, Zerr

(2011) Amyloid-beta 1–42 levels are modified by apolipoprotein E epsilon4 in Creutzfeldt-Jakob disease in a similar manner as in Alzheimer’s disease. J Alzheimers Dis 23, 717–726.

Galasko

, Chang

, Motter

, Clark

, Kaye

, Knopman

, Thomas

, Kholodenko

, Schenk

, Lieberburg

, Miller

, Green

, Basherad

, Kertiles

, Boss

, Seubert

(1998) High cerebrospinal fluid tau and low amyloid beta42 levels in the clinical diagnosis of Alzheimer disease and relation to apolipoprotein E genotype. Arch Neurol 55, 937–945.

Karch

, Hermann

, Ponto

, Schmitz

, Arora

, Zafar

, Llorens

, Muller-Heine

, Zerr

(2015) Cerebrospinal fluid tau levels are a marker for molecular subtype in sporadic Creutzfeldt-Jakob disease. Neurobiol Aging 36, 1964–1968.

10.

Heinemann

, Krasnianski

, Meissner

, Varges

, Kallenberg

, Schulz-Schaeffer

, Steinhoff

, Grasbon-Frodl

, Kretzschmar

, Zerr

(2007) Creutzfeldt-Jakob disease in Germany: A prospective 12-year surveillance. Brain 130, 1350–1359.

11.

Schmidt

, Karch

, Artjomova

, Hoeschel

, Zerr

(2013) Pre-progression rates in Alzheimer’s disease revisited. J Alzheimers Dis 35, 451–454.

12.

Schmidt

, Haik

, Satoh

, Rabano

, Martinez-Martin

, Roeber

, Brandel

, Calero-Lara

, de Pedro-Cuesta

, Laplanche

, Hauw

, Kretzschmar

, Zerr

(2012) Rapidly progressive Alzheimer’s disease: A multicenter update. J Alzheimers Dis 30, 751–756.

13.

Schmidt

, Redyk

, Meissner

, Krack

, von Ahsen

, Roeber

, Kretzschmar

, Zerr

(2010) Clinical features of rapidly progressive Alzheimer’s disease. Dement Geriatr Cogn Disord 29, 371–378.

14.

Schmidt

, Wolff

, Weitz

, Bartlau

, Korth

, Zerr

(2011) Rapidly progressive Alzheimer disease. Arch Neurol 68, 1124–1130.

15.

Mollenhauer

, Bibl

, Wiltfang

, Steinacker

, Ciesielczyk

, Neubert

, Trenkwalder

, Otto

(2006) Total tau protein, phosphorylated tau (181p) protein, beta-amyloid(1–42), and beta-amyloid(1–40) in cerebrospinal fluid of patients with dementia with Lewy bodies. Clin Chem Lab Med 44, 192–195.

16.

Windl

, Giese

, Schulz-Schaeffer

, Zerr

, Skworc

, Arendt

, Oberdieck

, Bodemer

, Poser

, Kretzschmar

(1999) Molecular genetics of human prion diseases in Germany. Hum Genet 105, 244–252.

17.

Burger nee Buch

, Padberg

, Nolde

, Teipel

, Stubner

, Haslinger

, Schwarz

, Sunderland

, Arai

, Rapoport

, Moller

, Hampel

(1999) Cerebrospinal fluid tau protein shows a better discrimination in young old (<70 years) than in old old patients with Alzheimer’s disease compared with controls. Neurosci Lett 277, 21–24.

18.

Humpel

(2011) Identifying and validating biomarkers for Alzheimer’s disease. Trends Biotechnol 29, 26–32.

19.

Sjogren

, Davidsson

, Tullberg

, Minthon

, Wallin

, Wikkelso

, Granerus

, Vanderstichele

, Vanmechelen

, Blennow

(2001) Both total and phosphorylated tau are increased in Alzheimer’s disease. J Neurol Neurosurg Psychiatry 70, 624–630.

20.

Sjogren

, Vanderstichele

, Agren

, Zachrisson

, Edsbagge

, Wikkelso

, Skoog

, Wallin

, Wahlund

, Marcusson

, Nagga

, Andreasen

, Davidsson

, Vanmechelen

, Blennow

(2001) Tau and Abeta42 in cerebrospinal fluid from healthy adults 21–93 years of age: Establishment of reference values. Clin Chem 47, 1776–1781.

21.

Parchi

, Castellani

, Capellari

, Ghetti

, Young

, Chen

, Farlow

, Dickson

, Sima

, Trojanowski

, Petersen

, Gambetti

(1996) Molecular basis of phenotypic variability in sporadic Creutzfeldt-Jakob disease. Ann Neurol 39, 767–778.

22.

Sanchez-Juan

, Green

, Ladogana

, Cuadrado-Corrales

, Saanchez-Valle

, Mitrovaa

, Stoeck

, Sklaviadis

, Kulczycki

, Hess

, Bodemer

, Slivarichova

, Saiz

, Calero

, Ingrosso

, Knight

, Janssens

, van

Duijn CM

, Zerr

(2006) CSF tests in the differential diagnosis of Creutzfeldt-Jakob disease. Neurology 67, 637–643.

23.

Puoti

, Giaccone

, Rossi

, Canciani

, Bugiani

, Tagliavini

(1999) Sporadic Creutzfeldt-Jakob disease: Co-occurrence of different types of PrP(Sc) in the same brain. Neurology 53, 2173–2176.

24.

Mattsson

, Rosen

, Hansson

, Andreasen

, Parnetti

, Jonsson

, Herukka

, van der Flier

, Blankenstein

, Ewers

, Rich

, Kaiser

, Verbeek

, Olde Rikkert

, Tsolaki

, Mulugeta

, Aarsland

, Visser

, Schroder

, Marcusson

, de Leon

, Hampel

, Scheltens

, Wallin

, Eriksdotter-Jonhagen

, Minthon

, Winblad

, Blennow

, Zetterberg

(2012) Age and diagnostic performance of Alzheimer disease CSF biomarkers. Neurology 78, 468–476.