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Acta Neurologica Belgica

, Volume 118, Issue 3, pp 395–403 | Cite as

A systematic review comparing the diagnostic value of 14-3-3 protein in the cerebrospinal fluid, RT-QuIC and RT-QuIC on nasal brushing in sporadic Creutzfeldt–Jakob disease

  • Olivia Behaeghe
  • Elias Mangelschots
  • Bart De Vil
  • Patrick Cras
Review

Abstract

Background

Sporadic Creutzfeldt–Jakob disease (sCJD) is a human prion disease that is a relatively common differential diagnosis in dementia patients. Therefore it needs a good diagnostic tool. Brain autopsy is the golden standard for the diagnosis of CJD; however, a less invasive technique is 14-3-3 protein measurement in the cerebrospinal fluid (CSF). In this systematic review, we compared the diagnostic value of the 14-3-3 protein measurement to the newer RT-QuIC test and a variant of RT-QuIC where nasal brushing is used to collect the samples.

Methods

The search via MeSH terms and quality assessment was carried out by two individual researchers.

Results

In 14-3-3 and RT-QuIC the sensitivity was comparable, respectively, 88% and 86%. Specificity however was higher in RT-QuIC 99.5% compared to 80% in 14-3-3. Nasal brushing showed the best results with a sensitivity of 97% and a specificity of 100%.

Conclusion

Nasal brushing, despite being the best diagnostic tool according to the data, needs more study since there has only been a few studies regarding the technique. It is safe to say that due to the high specificity, RT-QuIC is superior to 14-3-3 testing.

Keywords

CJD Prion Nasal brushing RT-QuIC 14-3-3 

Introduction

The most common prion disease in human patients is Creutzfeldt–Jakob disease (CJD). CJD is a neurodegenerative disease that affects the central nervous system. Because of the destruction, the brain atrophies, acquires a spongiform-like structure and an accumulation of the prions in the central nervous system occurs. A prion is a misfolded protein. The incidence of CJD is one in every million persons. CJD is characterized by a rapid progression. The first symptoms include myoclonus, visual or cerebellar disturbance, pyramidal, extra-pyramidal dysfunction and akinetic mutism. Usually death will occur within 2 years after the diagnosis. The survival depends strongly on the type of CJD. There are some very promising trials searching for a therapy that will delay the progression of the disease.

There are four known types of CJD. Variant CJD (vCJD) is most probably caused by the consumption of prion-infected beef meat and causes bovine spongiform encephalopathy (BSE), more commonly known as ‘mad cow disease’. A second type is caused by iatrogenic contamination due to instruments used in surgery on infected brains or meninges. Routine sterilization with heat, proteases or ionizing radiation is not thorough enough to disinfect the instruments from prions. Prions can also be transmitted through blood transfusions and human pituitary-derived hormone therapy when talking about vCJD. Familial CJD (fCJD) is the second most prevalent form of CJD which accounts for 15% of the known cases of CJD. fCJD is autosomal dominant and caused by a range of mutations in the prion protein gene (PRNP) that is located on chromosome 20. The last and most commonly prevalent form of CJD is sporadic CJD (sCJD), which accounts for 85% of all cases. The etiology of sCJD remains unknown up to this day. There are six molecular subtypes of sCJD, which can be traced back to the genotype of codon 129 of the PRNP. This heterogeneity of the subtypes is caused by the influence of methionine (M) and/or valine (V) polymorphism at codon 129 of the PRNP and the glycoform type 1 or 2 of the prion protein in CJD (PrPCJD) [1].

sCJD is a common differential diagnosis of rapidly progressive dementia and a wide array of neurodegenerative diseases. This is why it is important to find the most effective way to diagnose CJD. When the clinical diagnosis of CJD is suspected based on the typical symptoms, further investigation is needed to exclude or confirm the suspicion. At present clinical practice, most used methods include electroencephalography (EEG), MRI of the brain and the analysis of cerebrospinal fluid (CSF) for specific biomarkers, for which the standard for CJD is 14-3-3 protein. In 80% of the patients, the EEG shows generalized periodic sharp wave pattern, which consists of triphasic periodic complexes at one per second [2]. Diffusion-weighted MRI images show high signal intensity in the basal ganglia, specifically in the cingulate cortex, the striatum, nucleus caudatus and the putamen [3]. Furthermore, we can look at the different biomarkers in the cerebrospinal fluid, of which 14-3-3 is most commonly used at the present and the only one approved by the WHO [2, 4]. Sensitivity and specificity of these diagnostic tools are not high enough to confirm CJD in patients with certainty and to date the only way to obtain certainty of the diagnosis is brain biopsy. More sensitive and specific diagnostic tests are needed to confirm CJD with certainty in living patients. Thus we looked into the techniques RT-QuIC on CSF and on nasal brushing, which are able to show the existence of prion protein in the brain tissue. They are very promising and need further investigation to prove their effectiveness.

Quaking induced conversion (QuIC) is a detection method that exploits the conversion of PrPc to PrPsc in vivo and replicates it in an accelerated in vitro format. Recently an adaptation of the technique has incorporated thioflavin T (ThT) and recombinant PrP in the mixture, which in now known as real-time QuIC (RT-QuIC) [5, 6]. The recombinant PrP (recPrp) is used as a substrate to multiply the smaller amounts of PrP seeds that are extracted from the CSF to a detectable level. The next step is to add ThT as a fluorescent dye. Because of the addition of ThT we are able to see the aggregation of PrP in real time through the analysis by a fluorescent reader.

With the nasal brushing technique we collect olfactory epithelium from the nasal cavity. The olfactory epithelium obtained during the procedure is then further investigated using the RT-QuIC method to determine if there are prions present in the neurons from the olfactory epithelium [7]. RT-QuIC can also be used on the CSF of a patient.

The aim of this study was to further investigate the sensitivity and specificity of RT-QuIC on CSF and olfactory epithelium in sCJD and to compare this to the sensitivity and specificity of the currently used biomarkers to diagnose sCJD.

Methods

Eligibility criteria

The objective of the study was to compare the sensitivity and specificity of the currently used diagnostic marker 14-3-3 to RT-QuIC on CSF and on olfactory epithelium in sCJD patients. Herefore, we performed a literature review. We included studies comparing RT-QuIC to other diagnostic tests and other forms of prion diseases, not studies that solely focused on RT-QuIC or solely on the diagnosis of sCJD. The primary goal was to obtain studies with reliable information about the sensitivity and specificity concerning the diagnosis of sCJD. We also considered that diagnosis with 14-3-3 biomarker is more familiar and studied than RT-QuIC. Thus the 14-3-3 studies had to have tighter inclusion criteria than the RT-QuIC studies. We only included studies that have an element based on sCJD. Studies only performed on animal testing were excluded since we were specifically searching for human studies. These groups of patients had to be sufficiently large to be included and these patients had to be previously diagnosed or suspected with sCJD. Further, we only included studies that researched the sensitivity and/or specificity of the diagnostic techniques in question. Due to the nature of the review, studies other than case–control studies were not eligible for the review.

Search strategy

Medical Subject Headings (MeSH terms) included: Creutzfeldt - Jakob disease, Sporadic Creutzfeldt - Jakob disease, RT-QuIC, 14-3-3 proteins, biomarkers and cerebrospinal fluid. Electronic databases included: TRIP database (https://www.tripdatabase.com/), PubMed (http://www.ncbi.nlm.nih.gov/pubmed/), PMC: PubMed Central (http://www.ncbi.nlm.nih.gov/pmc/), Cochrane Library (http://www.cochranelibrary.com/), Medline Plus (https://www.nlm.nih.gov/medlineplus/), Google Scholar (http://scholar.google.be/). In addition we reviewed articles listed in the reference lists. We searched these electronic databases from inception to February 2017.

First we studied the existing guidelines and existing protocols for the diagnosis of CJD. The WHO diagnostic criteria were considered most useful. After this step, we researched synthesis using the TRIP database and found one article (4). Later we used CEBAM to search for systematic reviews, but none seemed to exist that were useful for our study. The last step was to look for primary studies in databases like PubMed and Google scholar.

The search was based on the PICO used in this systematic review. PICO stands for population, intervention, comparison and outcome.

Population: Suspected of sCJD or histologically diagnosed through biopsy.

Intervention: RT-QuIC of CSF and nasal brushing.

Comparison: 14-3-3 protein test in CSF.

Outcome: The sensitivity and specificity toward each of the extracted techniques.

Data management was performed with Endnote X7 in order to manage records and data throughout our review.

Selection process

We entered all articles in our reference manager and duplicates were manually removed. The references were screened for relevance in two stages. First we selected articles based on title and abstract, while the second phase consisted of reading the full text article. This selection process was executed independently by EM and OB. One article was not available in a free full text online. Therefore we wrote the authors to obtain a copy. The other full texts were accessed by the electronic library of the University of Antwerp.

If there were any disagreements between the two team members concerning the inclusion or exclusion of an article, discussion resulted in a consensus.

Two investigators independently collected and extracted data from each article using a data extraction form. The extracted data were based on PICOS format, including population, intervention, comparison, outcome and study type. Population characteristics included sporadic Creutzfeldt–Jakob disease, intervention and comparison (14-3-3 protein and RT-QuIC on CSF or on nasal brushing) and study type (case–control study). We also included trial information (year of publication, short summary, duration and country) and number of participants per group.

If the data were not available in numbers, we read the data off the graphs. If multiple results were reported, we chose the one with the best p value.

Two authors independently assessed the quality of the individual articles using QUADAS 2 guidelines and checklists to assess potential bias in the studies and to evaluate its generalizability. If one of the domains of the QUADAS 2 guidelines or the checklist were high or unclear, we classified the article as having an overall risk of bias.

Data analysis

Results were presented in a schematic and clear way. If possible the gravity of the patients’ disease and symptoms, which had a positive test for sCJD were presented and these were compared to patients with a negative test. To analyze the data we used a 2 × 2-table of the patients’ data using the false positives (FP), false negatives (FN), true positives (TP) and true negatives (TN). Using this table we found the sensitivity, specificity, positive and negative predictive values and likelihood ratios. If these values were already given in the study in question, we still calculated the searched values using our own 2 × 2-table. Further, we have used Excel to show our results in a well-ordered manner to summarize the outcomes. If the values were not given, we used the given sensitivity and specificity.

Results

The original search yielded 121 articles; through additional search we found another 3. Thus we had 124 articles to start with. After removal of duplicates, 110 records were left, so 14 articles were removed. After abstract review we assessed 41 full-articles for eligibility, so 69 records were excluded based on the abstract. These articles were then subjected to the QUADAS 2 quality assessment. 21 articles were then included in the systematic review of which 2 were only used in the introduction. Eventually 19 were part of the qualitative synthesis; see Fig. 1 for more details.

Fig. 1

Flowchart of article selection. This figure was made with Microsoft Word 2007

In this section, we will describe the results we found in the 19 articles included in the quantitative systematic review. When false and true negatives/positives were not given, we used the sensitivity and specificity that were given in the article. When this happened, we did not have enough data to calculate these values ourselves. We also could not incorporate the positive and negative likelihood ratio, positive and negative predictive value and diagnostic odds ratio. When true and false positives/negatives were given, we calculated the sensitivity, specificity, positive and negative predictive value, the positive and negative likelihood ratio and the diagnostic odds ratio to see if they matched the given values. All true positives were confirmed by pathology.

Atarashi et al.

The first study was a diagnostic test accuracy review concerning RT-QuIC on CSF that included over 200 participants with neurodegenerative disease. Sensitivity was measured to be 80% and specificity 100%. No true/false positives/negatives were given, so these were the only values we could use [8].

Atarashi et al.

In this diagnostic study accuracy review 65 patients were included who had sCJD or another neurodegenerative disease. 30 patients were determined to have sCJD, 35 were set in the control group. The study researched RT-QuIC on CSF and 14-3-3 in CSF. The results we calculated matched the given values. Sensitivity for 14-3-3 was 72%, in RT-QuIC on CSF it was 83%. Specificity was 86% in 14-3-3 and 100% in RT-QuIC on CSF. Positive predictive value was 72% for 14-3-3 and 100% for RT-QuIC on CSF. Negative predictive value was 86% for 14-3-3 and 92% for RT-QuIC on CSF. Positive likelihood ratio was 5 for 14-3-3 and could not be calculated for RT-QuIC on CSF, because we had 0 false positives. Negative likelihood ratio was 0.3 for 14-3-3 and 0.1 for RT-QuIC on CSF. Diagnostic odd ratio was 15.6 for 14-3-3 and could not be calculated for RT-QuIC on CSF, because there were no false positives [9].

Bahl et al.

This is a diagnostic test accuracy review testing 14-3-3 in CSF in 234 participants. 21 of those were patients with definite or probable sCJD and eventually 2 of those were excluded, leaving 19 patients. Sensitivity was found to be 95%, whereas specificity was 78%. We calculated the positive predictive value to be 35% and negative predictive value to be 99%. Positive and negative likelihood ratios were, respectively, 4.30 and 0.06. Lastly, we calculated the diagnostic odds ratio that was 63.8 [10].

Baldeiras et al.

In this diagnostic study accuracy review there were 71 patients. 30 of them had sCJD and 41 were non sCJD. The diagnostic test that was researched in this study was 14-3-3 in CSF. The calculated results matched the given values. The sensitivity was 97%, the specificity was 78%, positive predictive value was 76% and negative predictive value 97%. Positive and negative likelihood ratios were, respectively, 4.4 and 0.0. The diagnostic odds ratio was 103.1 [11].

Collins et al.

A diagnostic test, accuracy review testing 14-3-3 in CSF in 124 participants, of which there were 38 with sCJD and 73 without. Sensitivity in this study was 89% and specificity 93%. Positive predictive value was 87% and negative predictive value was 94%. Positive likelihood ratio was 13.1 and negative likelihood ratio was 0.1. Further, the diagnostic odds ratio was calculated to be 115.6 [12].

Coulthart et al.

This study tested the accuracy of the diagnostic test 14-3-3 in CSF. The total number of participants was 1000. The subdivision of the patients was 127 sCJD and 873 probable non-CJD. No true or false positives/negatives were given, so we could not calculate the values ourselves. The sensitivity was 88%, specificity was 72%. Positive and negative predictive values were, respectively 31% and < 10%. Positive and negative likelihood ratios were, respectively, 3.1 and 0.2. Diagnostic odds ratio could not be calculated due to no true or false positives/negatives [13].

Cramm et al.

The next article is a diagnostic test accuracy review that researched the sensitivity and specificity of RT-QuIC on CSF of 64 sCJD and 39 gCJD patients, with a control group consisting of 400 participants, giving the study a total of 510 participants. Sensitivity turned out to be 80 (for the sCJD patients) and specificity was 99%. No false/true positives/negatives were given [14].

Forner et al.

This is a diagnostic test accuracy review that included 98 participants with 57 pathologic confirmed sCJD; the rest was a control group consisting of 41 patients with nonprion rapidly progressive dementia. The biomarker researched here was 14-3-3 in CSF. Sensitivity was the only value given and was 70% [15].

Green et al.

This diagnostic accuracy review had 126 cases of suspected CJD. 35 had confirmed sCJD, 20 probable sCJD, 26 suspected vCJD and 45 no CJD. This study researched the diagnostic test of 14-3-3 in the CSF. The sensitivity and specificity were 82 and 94%, respectively. Positive and negative predictive values were 96 and 76%, respectively. The positive and negative likelihood ratios were 13.9 and 0.2, respectively. Diagnostic odds ratio was 72. True and false positives/negatives were given, so we calculated the values. The values we calculated, matched the given results [16].

Matsui et al.

14-3-3 in the CSF is the diagnostic test that was studied in this study. In total there were 233 patients included of which 124 CJD (114 sCJD, 7 gCJD and 3 iCJD) and a control group of 99 patients. There were no true or false positives/negatives given, so we could not calculate the values ourselves. Sensitivity and specificity were 95 and 73%, respectively. Positive and negative likelihood ratios were 3.5 and 0.1, respectively. Positive and negative predictive value and diagnostic odds ratio could not be calculated, because no true or false positives were given [17].

McGuire et al.

This diagnostic test accuracy review reviews the accuracy of RT-QuIC on CSF and 14-3-3. 108 patients that were suspected of sCJD were included of which 56 actually had sCJD and 52 were classified in the control group. True and false positives/negatives were given, so we could calculate the values ourselves. They matched the given values in the article. The sensitivity and specificity were 91 and 98%, respectively. Positive and negative predictive values were 98 and 91%, respectively. The positive and negative likelihood ratios were 47.4 and 0.1, respectively. The diagnostic odds ratio was 520.2. These results accounted for the RT-QuIC test on CSF. The 14-3-3 values were the following. Sensitivity and specificity were 92 and 56%, respectively. Positive and negative predictive values were 69 and 88%, respectively. Positive and negative likelihood ratios were 2.1 and 0.1, respectively. Diagnostic odds ratio was 16,4 [18].

Orrú et al.

This study is a diagnostic test accuracy review that tested the possibility to use RT-QuIC on nasal brushing instead of RT-QuIC on CSF. 74 patients were tested, 31 with CJD, of which 15 had definite sCJD, 14 probable sCJD and 2 had gCJD. The control group consisted of 43 patients with other neurodegenerative disorders. We only used the data for the sCJD patients in our systematic review. The use of RT-QuIC on nasal brushing had a sensitivity of 97% and a specificity of 100%. Positive predictive value was 100% and negative predictive value was 98%. Negative likelihood ratio was calculated to be 0.03. Positive likelihood ratio and diagnostic odds ratio could not be calculated due to the lack of false positives [4].

Orrú et al.

RT-QuIC on CSF was the diagnostic test reviewed in this diagnostic test accuracy review. In total, 87 patients were included of which 47 with sCJD and 39 in the control group (neurodegenerative diseases). True and false positives/negatives were given, so we could calculate the results. After a comparison we saw that the values matched the ones in the article. The sensitivity and specificity were 96 and 100%, respectively. Positive and negative predictive values were 100 and 95%, respectively. Positive likelihood ratio and diagnostic odds ratio could not be calculated, because the false positives were 0. Negative likelihood ratio was 0.04 [19].

Pennington et al.

This article is a diagnostic test accuracy review and tested the 14-3-3 biomarker. The study consisted of 68 patients of which 47 were neuropathologically confirmed sCJD patients and 21 other made up the control group. The results given were a sensitivity of 96%, a specificity of 67%, a positive predictive value of 87% and a negative predictive value of 88%. Further, we could calculate the positive and negative likelihood ratios of 2.90 and 0.05, respectively [20].

Sanchez-Juan et al.

This diagnostic study reviewed the accuracy of 14-3-3 in the CSF. 2976 patients were included in total. 1859 patients had CJD and 1117 were used in the control group. No true or false positives/negatives were given, so we could not calculate the values ourselves. The sensitivity and specificity were 85 and 95%, respectively. Positive and negative likelihood ratios were 17 and 0.2, respectively. Positive and negative predictive values and diagnostic odds ratios could not be calculated [21].

Van Everbroeck et al.

In this diagnostic test accuracy review they tested 14-3-3 on a total of 239 participants of which 75 with sCJD, 34 with Alzheimer and 33 with other dementias. 97 other participants formed a control group. In our study, we only used the data for sCJD patients. Sensitivity was 96% and specificity 92%. Positive predictive value was 92% and negative predictive value was 98%. Positive likelihood ratio was 26.4 and negative likelihood ratio 0.04. Lastly the diagnostic odds ratio of this study was 632 [22].

Koscova et al.

This study tested the diagnostic value of 14-3-3 protein over a period of 10 years. Since the technique has improved over this period, we will work with the latest values. The sensitivity was measured to be 90% and the specificity 52%. True/false positives/negatives were given so we measured the values independently. Positive likelihood ratio was found to be 0.95 and negative likelihood ratio was 0.19. Positive predictive value was 0.81 and negative predictive value was 0.68. This gives us a diagnostic odds ratio of 5 [23].

Bongianni et al.

In this diagnostic accuracy study they studied the accuracy of RT-QuIC on CSF compared to the accuracy of the same technique on nasal brushing samples. The results for the RT-QuIC on CSF were the following: a sensitivity and specificity of 95 and 100%, respectively, compared to RT-QuIC on nasal brushing which had both a sensitivity and specificity of 100% [24].

Groveman et al.

In the last study, they researched the accuracy of RT-QuIC on CSF in a total of 113 patients. Eventually they measured a sensitivity of 94% and a specificity of 100% [25].

Table 1 shows the values found and calculated for the articles concerning the articles about 14-3-3. Table 2 shows them for RT-QuIC on CSF and Table 3 for RT-QuIC on nasal brushing studies. We calculated the mean values of the sensitivity and specificity of both diagnostic tests and compared these to the values found in the study concerning nasal brushing. The mean specificity and sensitivity of 14-3-3 were, respectively, 78% and 88.3%. For RT-QuIC on CSF these were 99.6 and 87% for specificity and sensitivity, respectively. For RT-QuIC on nasal brushing this was 100% and 98.5%, respectively. This is shown in Table 4.

Table 1

Values of 14-3-3 studies

14-3-3

True positives

False positives

False negatives

True negatives

Sensitivity (%)

Specificity (%)

Study

Atarashi et al. [1]

13

5

5

30

72

86

Bahl [10]

18

33

1

117

95

78

Baldeiras [11]

29

9

1

32

97

78

Collins [12]

34

5

4

68

89

93

Coulthart [13]

/

/

/

/

88

72

Forner [15]

42

/

15

/

70

/

Green [16]

45

2

10

32

82

94

Matsui [17]

/

/

/

/

95

73

McGuire [18]

52

23

4

29

93

56

Pennington [20]

/

/

/

/

96

67

Sanchez-Juan [21]

/

/

/

/

85

95

Van Everbroeck [22]

72

6

3

158

96

92

Koscova [23]

54

12

6

13

90

52

Table 2

Values of RT-QuIC on CSF studies

RT-QuIC on CSF

True positives

False positives

False negatives

True negatives

Sensitivity (%)

Specificity (%)

Study

Atarashi et al. [1]

200

0

/

/

80

100

Atarashi et al. [1]

15

0

3

35

83

100

Cramm [14]

/

/

/

/

80

99

McGuire [18]

51

1

5

51

91

98

Orru [4]

23

0

7

46

77

100

Orru (2015)

46

0

2

39

96

100

Bongianni (2016)

54

0

3

71

95

100

Groveman (2016)

106

/

7

/

94

100

Table 3

Values of RT-QuIC on nasal brushing studies

RT-QuIC on nasal brushing

True positives

False positives

False negatives

True negatives

Sensitivity (%)

Specificity (%)

Study

Orru [7]

30

0

1

43

97

100

Bongianni (2016)

30

0

0

17

100

100

Table 4

Mean results of researched diagnostic tests

 

Sensitivity (mean) (%)

Specificity (mean) (%)

14-3-3

88.3

78.0

RT-QuIC on CSF

87.0

99.6

RT-QuIC on nasal brushing

98.5

100

Discussion

The research for articles and guidelines was performed in a very detailed way as described above. We only included the studies that seemed the most relevant, which we see as a strength of this study. As these studies did not compare 14-3-3, RT-QuIC on CSF and on nasal brushing to each other, it was always tested on different patients. There was no study comparing all three methods on the same patients. This is a limit to our systematic review. As RT-QuIC on nasal brushing is still a very new technique in the diagnosis of CJD, there were not as many studies to be found as about 14-3-3 or RT-QuIC on CSF. Thus there was not much data to be found.

To compare both tests in sensitivity and/or specificity, we calculated the mean values for these in both tests. The results showed a similar sensitivity. However, the specificity was significantly higher in RT-QuIC on CSF. RT-QuIC on nasal brushing showed the highest specificity. This result however was only the conclusion of two studies and RT-QuIC on nasal brushing needs further investigation to be able to estimate its value in the diagnosis of sCJD.

Notes

Funding

No financial support was offered nor accepted for this systematic review.

Compliance with ethical standards

Conflict of interest

A possible conflict of interest is that one of the authors is now editor-in-chief of this journal (Patrick Cras, PhD, MD).

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

An informed consent was not needed here, as this is a systematic review.

References

  1. 1.
    Poggiolini I, Saverioni D, Parchi P (2013) Prion protein misfolding, strains, and neurotoxicity: an update from studies on mammalian prions. Int J Cell Biol 2013:1–24.  https://doi.org/10.1155/2013/910314 CrossRefGoogle Scholar
  2. 2.
    Creutzfeldt–Jakob disease (CJD) and variant CJD (vCJD)Google Scholar
  3. 3.
    Robinson R (2011) MRI can distinguish CJD from other rapid dementias. Neurol Today 11(9)Google Scholar
  4. 4.
    Orrú CD, Bongianni M, Tonoli G, Ferrari S, Hughson AG, Groveman BR et al (2014) A Test for Creutzfeldt–Jakob Disease Using Nasal Brushings. N Engl J Med 371(6):519–529CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    McGuire LI, Peden AH, Orru CD, Wilham JM, Appleford NE, Mallinson G et al (2012) Real time quaking-induced conversion analysis of cerebrospinal fluid in sporadic Creutzfeldt–Jakob disease. Ann Neurol 72(2):278–285CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Iacono D, Ferrari S, Gelati M, Zanusso G, Mariotto S, Monaco S (2015) Sporadic Creutzfeldt–Jakob disease: prion pathology in medulla oblongata-possible routes of infection and host susceptibility. Biomed Res Int 2015:396791CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Orru CD, Bongianni M, Tonoli G, Ferrari S, Hughson AG, Groveman BR et al (2014) A test for Creutzfeldt–Jakob disease using nasal brushings. N Engl J Med 371(6):519–529CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Atarashi R, Sano K, Satoh K, Nishida N (2011) Real-time quaking-induced conversion: a highly sensitive assay for prion detection. Prion 5(3):150–153CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Atarashi R, Satoh K, Sano K, Fuse T, Yamaguchi N, Ishibashi D et al (2011) Ultrasensitive human prion detection in cerebrospinal fluid by real-time quaking-induced conversion. Nat Med 17(2):175–178CrossRefPubMedGoogle Scholar
  10. 10.
    Bahl JM, Heegaard NH, Falkenhorst G, Laursen H, Hogenhaven H, Molbak K et al (2009) The diagnostic efficiency of biomarkers in sporadic Creutzfeldt–Jakob disease compared to Alzheimer’s disease. Neurobiol Aging 30(11):1834–1841CrossRefPubMedGoogle Scholar
  11. 11.
    Baldeiras IE, Ribeiro MH, Pacheco P, Machado A, Santana I, Cunha L et al (2009) Diagnostic value of CSF protein profile in a Portuguese population of sCJD patients. J Neurol 256(9):1540–1550CrossRefPubMedGoogle Scholar
  12. 12.
    Collins S, Boyd A, Fletcher A, Gonzales M, McLean CA, Byron K et al (2000) Creutzfeldt–Jakob disease: diagnostic utility of 14-3-3 protein immunodetection in cerebrospinal fluid. J Clin Neurosci 7(3):203–208CrossRefPubMedGoogle Scholar
  13. 13.
    Coulthart MB, Jansen GH, Olsen E, Godal DL, Connolly T, Choi BC et al (2011) Diagnostic accuracy of cerebrospinal fluid protein markers for sporadic Creutzfeldt–Jakob disease in Canada: a 6-year prospective study. BMC Neurol 11:133CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Cramm M, Schmitz M, Karch A, Mitrova E, Kuhn F, Schroeder B et al (2015) Stability and reproducibility underscore utility of RT-QuIC for diagnosis of Creutzfeldt–Jakob disease. Mol NeurobiolGoogle Scholar
  15. 15.
    Forner SA, Takada LT, Bettcher BM, Lobach IV, Tartaglia MC, Torres-Chae C et al (2015) Comparing CSF biomarkers and brain MRI in the diagnosis of sporadic Creutzfeldt–Jakob disease. Neurol Clin Pract 5(2):116–125CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Green AJ, Ramljak S, Muller WE, Knight RS, Schroder HC (2002) 14-3-3 in the cerebrospinal fluid of patients with variant and sporadic Creutzfeldt–Jakob disease measured using capture assay able to detect low levels of 14-3-3 protein. Neurosci Lett 324(1):57–60CrossRefPubMedGoogle Scholar
  17. 17.
    Matsui Y, Satoh K, Miyazaki T, Shirabe S, Atarashi R, Mutsukura K et al (2011) High sensitivity of an ELISA kit for detection of the gamma-isoform of 14-3-3 proteins: usefulness in laboratory diagnosis of human prion disease. BMC Neurol 11:120-CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    McGuire LI, Peden AH, Orrú CD, Wilham JM, Appleford NE, Mallinson G et al (2012) RT-QuIC analysis of cerebrospinal fluid in sporadic Creutzfeldt–Jakob disease. Ann Neurol 72(2):278–285CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Orrú CD, Groveman BR, Hughson AG, Zanusso G, Coulthart MB, Caughey B (2015) Rapid and sensitive RT-QuIC detection of human Creutzfeldt–Jakob disease using cerebrospinal fluid. mBio 6(1):e02451–e02414CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Pennington C, Chohan G, Mackenzie J, Andrews M, Will R, Knight R et al (2009) The role of cerebrospinal fluid proteins as early diagnostic markers for sporadic Creutzfeldt–Jakob disease. Neurosci Lett 455(1):56–59CrossRefPubMedGoogle Scholar
  21. 21.
    Sanchez-Juan P, Green A, Ladogana A, Cuadrado-Corrales N, Saanchez-Valle R, Mitrovaa E et al (2006) CSF tests in the differential diagnosis of Creutzfeldt–Jakob disease. Neurology 67(4):637–643CrossRefPubMedGoogle Scholar
  22. 22.
    Van Everbroeck B, Green AJ, Vanmechelen E, Vanderstichele H, Pals P, Sanchez-Valle R et al (2002) Phosphorylated tau in cerebrospinal fluid as a marker for Creutzfeldt–Jakob disease. J Neurol Neurosurg Psychiatry 73(1):79–81CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Koscova S, Zakova Slivarichova D, Tomeckova I, Melicherova K, Stelzer M, Janakova A et al (2016) Cerebrospinal Fluid Biomarkers in the Diagnosis of Creutzfeldt–Jakob Disease in Slovak Patients: over 10-Year Period Review. Molecular neurobiologyGoogle Scholar
  24. 24.
    Bongianni M, Orru C, Groveman BR, Sacchetto L, Fiorini M, Tonoli G et al (2017) Diagnosis of human prion disease using real-time quaking-induced conversion testing of olfactory mucosa and cerebrospinal fluid samples. JAMA neurology 74(2):155–162CrossRefPubMedGoogle Scholar
  25. 25.
    Groveman BR, Orrú CD, Hughson AG, Bongianni M, Fiorini M, Imperiale D et al (2017) Extended and direct evaluation of RT-QuIC assays for Creutzfeldt–Jakob disease diagnosis. Ann Clin Transl Neurol 4(2):139–144CrossRefPubMedGoogle Scholar

Copyright information

© Belgian Neurological Society 2018

Authors and Affiliations

  1. 1.Faculty of Medicine and Health SciencesUniversity of AntwerpWilrijkBelgium
  2. 2.Laboratory of Neurology, Translational NeurosciencesUniversity of AntwerpWilrijkBelgium
  3. 3.Institute Born-BungeUniversity of AntwerpWilrijkBelgium
  4. 4.Department of NeurologyAntwerp University HospitalEdegemBelgium

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