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  • Review
  • Open Access

Advantages and disadvantages of the use of the CSF Amyloid β (Aβ) 42/40 ratio in the diagnosis of Alzheimer’s Disease

Alzheimer's Research & Therapy201911:34

https://doi.org/10.1186/s13195-019-0485-0

  • Published:

Abstract

The cerebrospinal fluid (CSF) biochemical markers (biomarkers) Amyloidβ 42 (Aβ42), total Tau (T-tau) and Tau phosphorylated at threonine 181 (P-tau181) have proven diagnostic accuracy for mild cognitive impairment and dementia due to Alzheimer’s Disease (AD). In an effort to improve the accuracy of an AD diagnosis, it is important to be able to distinguish between AD and other types of dementia (non-AD). The concentration ratio of Aβ42 to Aβ40 (Aβ42/40 Ratio) has been suggested to be superior to the concentration of Aβ42 alone when identifying patients with AD. This article reviews the available evidence on the use of the CSF Aβ42/40 ratio in the diagnosis of AD. Based on the body of evidence presented herein, it is the conclusion of the current working group that the CSF Aβ42/40 ratio, rather than the absolute value of CSF Aβ42, should be used when analysing CSF AD biomarkers to improve the percentage of appropriately diagnosed patients.

Keywords

  • Alzheimer’s Disease
  • Amyloidβ Peptides
  • 42/40 ratio
  • Biomarkers
  • Cerebrospinal Fluid

Introduction

Alzheimer’s Disease (AD) is the most prevalent form of age-related dementia. The clinical manifestation of AD is generally preceded by a relatively symptom-free preclinical phase [1]. After the first clinical symptoms appear in the prodromal phase, patients transition clinically into mild cognitive impairment (MCI) [2], which eventually results in AD dementia (ADD) [3]. These phases are accompanied by biochemical changes in the brain that are reflected in cerebrospinal fluid (CSF) [4, 5]. Decreases in CSF concentrations of amyloid-beta 42 (Aβ42) (a marker of amyloidosis) and elevations in tau species (markers of axonal damage and neurofibrillary tangles) are well-established as biomarkers useful for AD diagnosis [6, 7]. Importantly, analysis of these CSF biochemical markers (biomarkers) for AD has been shown to predict conversion from MCI to ADD with accuracies of > 80% [810].

Depending on their age, approximately 30–50% of patients with MCI will develop ADD within 5 years [11]. Therefore, early diagnosis is essential to enable appropriate counselling to take place, as well as for planning treatment and care. In addition, the possibility of making an early diagnosis, prior to the appearance of symptoms, is essential for the clinical evaluation of novel, potentially disease-modifying drugs for the treatment of AD.

In an effort to improve the accuracy of an AD diagnosis, it is important to be able to distinguish between AD and other types of dementia (non-AD) that are not characterized by amyloid pathology. Although the concentration of another amyloid peptide species, Aβ40, has been reported to be unaltered in AD, the concentration ratio of Aβ42 to Aβ40 (Aβ42/40 ratio) has been suggested to be superior to the concentration of Aβ42 alone in discriminating patients with AD [12, 13]. To date, there has been a lack of comprehensive reviews on the applicability of the CSF Aβ42/40 ratio in AD diagnosis.

Thus, the aim of the current article was to review the available evidence on the use of the CSF Aβ42/40 ratio in the (i) differential diagnosis of AD dementia vs non-AD dementias and (ii) prediction of subsequent development of AD dementia in cases with MCI, and to discuss its value in comparison to other CSF biomarkers and compared to other diagnostic modalities, such as Aβ positron emission tomography (Aβ-PET). In addition, the effects of non-AD pathologies and pre-analytical handling on the various CSF biomarkers were also discussed. In order to achieve these goals, a working group was brought together to critically evaluate the evidence for use of the CSF Aβ42/40 ratio in the diagnosis of AD and a consensus paper was drafted reviewing the advantages and disadvantages surrounding the use of the CSF Aβ42/40 ratio.

This review addresses the advantages and disadvantages of the Aβ42/40 ratio to detect Aβ pathology, which is an approach to normalize the Aβ42 CSF concentration for the total Aβ CSF concentration (represented by the most abundant isoform, i.e. Aβ40). In contrast, this paper does not address approaches to interpret the overall pattern of the AD CSF biomarkers that combine results derived from the two distinct AD pathologies (amyloidosis and neurodegeneration) to form any kind of ‘ratios’.

Methods

A group of experts in the field of AD biomarkers were brought together, and several meetings of this working group were conducted. During the meetings, discussions took place based both on evidence gathered from scientific publications and the experience of the group members, as experts in the field. Studies were selected to be included in this paper based on an independent review by at least two (in most cases by all) co-authors of the report, with MEDLINE database as the primary source of the studies. Searches were conducted using keywords, such as ‘Aβ42/40’ and ‘Aβ40’ and excluding those, whose primary scope was not the role of the Aβ42/40 ratio in AD diagnostics. The results of the discussions and the evidence gathered during the meetings are presented in this paper.

Results

42 versus the Aβ42/40 ratio

Comparison of the diagnostic accuracy in the context of use of differential diagnostics when discriminating AD from other neurodegenerative disorders

Due to similar clinical manifestations and overlapping brain pathologies, differentiation of AD from other neurodegenerative disorders may prove difficult even with the aid of biomarkers. For example, the symptoms and biomarker patterns observed in patients with dementia with Lewy bodies (DLB) or subcortical vascular dementia (VaD) sometimes closely resemble those of AD, which makes differential diagnosis difficult and decreases the diagnostic accuracy of the core CSF AD biomarkers, especially in the early stages of the disease. Therefore, evidence was gathered on whether adding the CSF Aβ42/40 ratio to the existing panel of biomarkers could improve the accuracy of the differential diagnosis of AD from other dementia disorders. Here we provide details of 16 studies that have compared the diagnostic accuracy of CSF biomarkers to diagnose ADD versus non-ADDs. These studies demonstrate the usefulness of the CSF Aβ42/40 ratio for the diagnosis of AD in patients with dementia. Studies with relevant data are also summarized in Table 1.
Table 1

CSF biomarkers to distinguish cases with ADD from cases with non-ADD

Study

Number of AD patients

Number of non-AD patients

Number of control patients

CSF biomarkers

Optimal cut-off*

Sensitivity % (95% CI)**

Specificity % (95% CI)**

AUC (95% CI)

SL (p value)#

Shoji et al. [12]

55

68

34

42

158.6 fmol/mL

42/40 ratio##

0.078##

51

82

NP

Lewczuk et al. [13]

22

11

35

42

550 pg/mL

100

80

0.923

42/40 ratio

9.75

95.2

88.4

0.944

NP

Spies et al. [22]

69

69

47

AD vs controls

 

16 DLB

 

42

93

87

0.949

 

27 FTD

 

42/40 ratio

93

87

0.947

NP

 

26 VaD

 

AD vs non-AD

   

42

83

74

0.811

NP

42/40 ratio

85

85

0.903

 

Hertze et al. [32]

94

166 (MCI)

29 (DD)

38

AD vs controls

 

42 MSD

< 523

73

89

0.88 (0.82–0.93)

42 MSD/40 ratio

< 0.069

93

86

0.91 (0.86–0.95)

NP

42 MSD/38 ratio

< 0.37

87

82

0.89 (0.83–0.93)

NP

MCI-AD vs MCI

42 MSD

< 523

67

71

0.73 (0.66–0.80)

42 MSD/40 ratio

< 0.069

85

71

0.86 (0.79–0.91)

NP

42 MSD/38 ratio

< 0.37

88

71

0.85 (0.79–0.91)

NP

Gabelle et al. [14]

52

34

42

AD vs FTD

42

> 464

79

62

0.75

42/40 ratio

≤11.1

79

76

0.85

n.s.

42/38 ratio

≤2.00

88

86

0.87

n.s.

Slaets et al. [16]

80

69 (NP)

11 (AD+CVD)

75

24 DLB (15 NP)

29 FTD (12 NP)

22 VaD (11 NP)

30

42

517 pg/mL

81

59

0.747 (0.670–0.827)

42/40 ratio

0.057

81

60

0.749 (0.673–0.826)

NP

Nutu et al. [17]

48

127

43 PD

33 PDD

       

51 DLB

107

AD vs control

42

444 ng/L

94

72

0.871 (0.811–0.930)

-NP

42/40 ratio

0.125

92

79

0.871 (0.801–0.933)

 

AD vs PDD

42

449 ng/L

94

61

0.805 (0.704–0.905)

42/40 ratio

0.150

90

81

0.910 (0.844–0.976)

NP

AD vs DLB

42

387 ng/L

88

41

0.675 (0.570–0.780)

42/40 ratio

0.115

90

57

0.759 (0.664–0.853)

NP

Baldeiras et al. [18]

   

AD vs controls

42

534 pg/mL

82

74

0.818

40/42 ratio

8.3

59

81

0.719

NP

AD vs FTD

     

42

538 pg/mL

70

82

0.791

40/42 ratio

5.4

59

87

0.778

NP

Dumurgier et al. [19]

367 (AD+ non-AD)

0

AD vs non-AD

42

737–836 pg/mL

78

79

0.81

42/40 ratio

0.050–0.082

73

78

0.81

NP

Struyfs et al. [23]

100

50

50

AD vs controls

50 (AD)

17 (DLB)

 

42

< 722 pg/mL

98.0

74.0

0.874

50 (MCI-AD)

17 (FTD)

 

42/40 ratio

< 0.1099

85.7

78.0

0.881

NP

 

16 (VaD)

 

42/38 ratio

< 0.269

81.6

82.0

0.858

NP

   

AD vs non-AD

42

< 694 pg/mL

95.9

40.0

0.686

42/40 ratio

< 0.1215

93.9

50.0

0.782

NP

42/38 ratio

< 0.2730

81.6

68.0

0.804

NP

Bousiges et al. [25]

70

55

15

Pro-AD vs pro-DLB

31 (AD-d)

20 (DLB-d)

 

42

≤ 730 ng/L

84.6

71.4

0.84 (0.74–0.92)

39 (pro-AD)

35 (pro-DLB)

 

42/40 ratio

≤ 0.0529

88.9

100

0.95 (0.83–0.99)

NP

   

AD-d vs DLB-d

42

≤ 504 ng/L

67.7

80

0.77 (0.63–0.88)

42/40 ratio

≤ 0.0799

92.3

88.9

0.86 (0.64–0.97)

NP

Janelidze et al. [24]

Cohort 2

Cohort 2

Cohort 2

AD vs MCI

75 (AD)

62 (MCI)

53

42

0.817 (0.743–0.890)

35 (MCI-AD)

34 (VaD)

Cohort 3

42/40 ratio

0.879 (0.823–0.936)

< 0.028

Cohort 3

47 (DLB/PDD)

328

42/38 ratio

0.856 (0.790–0.923)

< 0.222

137

33 (FTD)

 

AD vs DLB/PDD

 

Cohort 3

 

42

0.583 (0.476–0.690)

 

35 (DLB/PDD)

 

42/40 ratio

0.792 (0.707–0.877)

< 0.001

 

128 (PD)

 

42/38 ratio

0.796 (0.710–0.883)

< 0.001

   

AD vs VaD

42

0.698 (0.580–0.816)

42/40 ratio

0.880 (0.814–0.946)

< 0.001

42/38 ratio

0.860 (0.786–0.935)

< 0.001

AD vs non-AD

 

42

0.720 (0.651–0.788)

42/40 ratio

0.863 (0.813–0.912)

< 0.001

42/38 ratio

0.863 (0.813–0.913)

< 0.001

Lehmann et al. [26]

342

562

0

AD vs non-AD

Cohort 1

Cohort 1

 

Cohort 1

 

124

276

 

42

500 pg/mL

0.78 (0.734–0.818)

Cohort 2

Cohort 2

 

42/40 ratio

0.1

0.90 (0.865–0.926)

< 0.0001

218

286

 

Cohort 2

 

42

700 pg/mL

0.60 (0.553–0.641)

42/40 ratio

0.05

0.77 (0.728–0.803)

< 0.0001

*Optimal cut-offs were created using different statistical approaches—please see original articles for details. **Sensitivity and specificity are a function of the cut-off, and the cut-offs were calculated in different ways; therefore, they are not clearly comparable across different articles. #Significance levels (p values) of the AUC values are comparisons of the Aβ isoform ratios vs Aβ42 alone. ##Note that the ratio in the original article is inversed, but for consistency, the Aβ42/40 ratio has been calculated for this table. Amyloid beta, AD Alzheimer’s Disease, ADD AD dementia, Ad-d demented AD patients, AUC area under curve, CJD Creutzfeldt-Jakob Disease, CSF cerebrospinal fluid, DLB dementia with Lewy bodies, DLB-d demented DLB patients, FTD frontotemporal dementia, MCI mild cognitive impairment, MCI-AD MCI that subsequently developed ADD or MCI due to AD, NP neuropathologically confirmed, NP not provided, NPH normal pressure hydrocephalus, n.s not significant, PD Parkinson’s Disease, PDD Parkinson’s Disease dementia, pro-AD prodromal-AD patients, pro-DLB prodromal-DLB patients, PsD psychiatric disorders, SL significance level, VaD vascular dementia

In a study of patients with ADD, normal controls, patients with non-ADD and patients with other neurological diseases, Shoji et al. [12] found that the ADD group had a significantly higher level of tau than the normal control group (p <  0.001), but Aβ40 levels did not show any significant differences between the groups. The reduction of Aβ42 levels in AD also resulted in a significant increase in the Aβ40/42 ratio (note that the ratio reported in this study has Aβ40 in the numerator, in contrast to most of the other studies summarized in the current paper) as an improved marker. The authors therefore concluded that the Aβ ratio is another important marker for AD.

Lewczuk et al. [13] measured concentrations of Aβ42, Aβ40 and total tau (T-tau) in order to compare their accuracy in discriminating patients with ADD, non-ADD and control subjects. The results showed that concentrations of Aβ42 were decreased (p <  0.001) and of T-tau were increased (p <  0.001) in ADD patients, while Aβ40 concentrations did not differ significantly among the groups. For all groups when the Aβ42/40 ratio was used, more patients were classified correctly, compared to when the Aβ42 concentration alone was used (94 vs 86.7% when comparing ADD to controls, 90 vs 85% when comparing ADD to non-ADD and 90.8 vs 87% when comparing ADD to non-ADD plus controls). The improvement of the diagnostic accuracy reported in this study was not significant, probably due to the small numbers of subjects and a clear ceiling effect (a relatively high number of patients were already correctly classified using Aβ42 alone).

Gabelle et al. [14] evaluated the value of individual and combined measurements of CSF biomarkers. They found that both Aβ40/42 and Aβ38/42 ratios were significantly altered in AD. They also found that the Aβ40/38 ratio was the only one that differentiated clearly control subjects from FTD subjects, while not being significant between AD and FTD. In the ROC curves, they found that for FTD versus AD diagnosis, the best AUCs for amyloid biomarkers were the Aβ38/42 ratio and the Innogenetics Aβ/Tau index (IATI) (AUCs = 0.87). However, the Aβ40/42 ratio or Aβ42 alone had very close and statistically undifferentiated AUC values. The authors concluded that the Aβ38/42, Aβ40/42 and the IATI ratios were also better than individual biomarkers to identify AD therefore justifying their clinical relevance.

In another study carried out by Wiltfang et al. [15], the authors found that alterations of Aβ42 concentrations might not only result from AD pathology but may also be related to total Aβ peptide concentrations. In such cases, healthy individuals with relatively low total Aβ might be misdiagnosed as having ‘pathologically low’ Aβ42 concentrations, and vice versa, AD subjects with high total Aβ might be misinterpreted as normal Aβ42 carriers. It was therefore concluded that the analysis of CSF Aβ42 alone (i.e. without Aβ40) might lead to misinterpretation of the neurochemical dementia diagnostics outcome in subjects with constitutively high or low concentrations of total Aβ peptides. Consequently, the authors conclude that the CSF Aβ42/40 ratio can possibly improve the reliability of the neurochemical dementia diagnosis.

A study by Slaets et al. [16] compared the use of different biomarkers for the diagnosis of AD. Addition of the CSF Aβ42/40 ratio to the existing panel of biomarkers, Aβ42, Aβ40 and tau phosphorylated at threonine 181 (P-tau181) was compared to the panel without the addition of the ratio. The results showed that the CSF Aβ42/40 ratio was significantly decreased in AD patients (0.043 ± 0.021) compared to non-AD patients (0.064 ± 0.027; p <  0.001) and controls (0.053 ± 0.023; p < 0.001). Following receiver operating characteristic (ROC) analysis, the optimal cut-offs discriminating the groups were defined as the values maximising the sum of the sensitivity and the specificity. Although the difference between the areas under the ROC curves (AUC) for Aβ42 and Aβ42/40 turned out to be insignificant, the diagnostic accuracy of the decision tree that contained Aβ42, Aβ40, P-tau181 and the Aβ42/40 ratio was significantly better than the diagnostic accuracy of the decision tree without Aβ40 and the Aβ42/40 ratio (80% vs 74%; p < 0.001). The authors concluded that there was no difference in CSF Aβ40 levels found between AD and non-AD patients, but that adding CSF Aβ40 and the CSF Aβ42/40 ratio to a biomarker-based decision tree, might have an added value for discriminating AD from non-AD patients in cases with intermediate CSF P-tau181 values.

Nutu et al. [17] evaluated whether the CSF Aβ42/40 ratio could be used for differentiating AD from DLB and Parkinson’s Disease Dementia (PDD). The primary finding of this study was that the CSF Aβ42/40 ratio increased discrimination of AD from PDD and DLB compared with either of the two Aβ biomarkers individually. Of note, in this study, Aβ40 was significantly higher in AD. Furthermore, the authors concluded that use of the Aβ42/40 ratio could improve the differentiation of AD from PDD and DLB.

In a study by Baldeiras et al. [18], the added value of another CSF Aβ-peptide (Aβ40), along with the core CSF markers T-tau, P-tau181 and Aβ42, in the discrimination between two large dementia groups of FTD (n = 107), AD (n = 107) and non-demented subjects (n = 33) was evaluated. The authors found that their data ‘taken together’ indicated that ‘although CSF Aβ40 has no added value in the distinction between AD and FTD patients, it might be useful in the discrimination between AD and FTD patients from non-demented controls, and therefore could be considered in patients diagnostic work-up’.

In a prospective study of subjects with cognitive disorders at three French memory centres (Paris-North, Lille and Montpellier; the PLM study), Dumurgier et al. [19] assessed whether the use of the Aβ42/40 ratio would reduce the frequency of indeterminate CSF profiles. They found that, on the basis of local optimum cut-offs for Aβ42 and P-tau181, 22% of patients had indeterminate CSF profiles. The systematic use of the Aβ42/40 ratio instead of Aβ42 levels alone decreased the number of indeterminate profiles (17%; p = 0.03), but it failed to improve the classification of subjects (NRI = − 2.1%; p = 0.64). In contrast, use of the Aβ42/40 ratio instead of Aβ42 levels alone in patients with a discrepancy between P-tau181 and Aβ42 led to a reduction by half of the number of indeterminate profiles (10%; p < 0.001) and was also in agreement with clinician diagnosis (NRI = 10.5%; p = 0.003). The authors therefore concluded that in patients with a discrepancy between CSF P-tau181 and CSF Aβ42, the assessment of the Aβ42/40 ratio led to a reliable biological conclusion in over 50% of cases that agreed with a clinician’s diagnosis.

Sauvee et al. [20] investigated whether the CSF Aβ42/40 ratio could be used to improve the accuracy of diagnostically relevant conclusions in patients with ambiguous CSF Aβ42 or tau results. They found that one third of the biomarker profiles of patients with atypical dementia were ambiguous. The addition of the CSF Aβ42/40 ratio increased the proportion of interpretable profiles from 69 to 87%, without changing the conclusion when the usual biomarkers (Aβ42 and P-tau181) were concordant. The authors therefore concluded that their results support the use of the Aβ42/40 ratio in addition to the usual CSF AD biomarkers for patients with ambiguous profiles. They added that this method could be specifically directed to this population (i.e. patients with ambiguous results) in order to improve the level of certainty for clinical routine practice.

Lewczuk et al. [21] also compared the diagnostic accuracies of the CSF Aβ42/40 ratio and CSF Aβ42 alone. Analysis of Aβ42 gave a sensitivity and specificity of 69.3% and 88.9%, respectively, whereas the Aβ42/40 ratio showed significantly improved performance with sensitivity and specificity of 93.3% and 100%, respectively. Thus, the authors concluded that the CSF Aβ42/40 ratio concentration shows significantly better diagnostic performance compared to the CSF Aβ42 concentration alone. It should be noted, however, that this study must not be interpreted as providing absolute values of the diagnostic accuracies, but their relative comparison.

In another study including various CSF biomarkers, Spies et al. [22] investigated the CSF Aβ42/40 ratio under the assumption that Aβ40 closely represents the total cerebral Aβ load. They found that the Aβ42/40 ratio improves differentiation of AD patients from VaD, DLB and non-ADD patients when compared to Aβ42 alone. Furthermore, they found that the Aβ42/40 ratio is a more easily interpretable alternative to the combination of Aβ42, P-tau181 and T-tau when differentiating AD from either frontotemporal dementia (FTD) or other non-ADDs. Since they found different Aβ40 concentrations in the various dementia groups, the authors also added that it can be debated if the Aβ42/40 ratio is a good representation of the Aβ42 fraction of the total Aβ load and thus eliminates inter-individual differences in total Aβ concentrations.

A study of patients with AAD, non-ADDs (DLB, FTD, VaD), MCI due to AD and non-demented controls found that the CSF Aβ42/40 ratio improved the diagnostic performance of Aβ42 in most differential diagnostic situations. Struyfs et al. [23] also found that the Aβ42/40 ratio was the best biomarker to distinguish between AD-MCI and FTD.

Similarly, Janelidze et al. [24] also found that the CSF Aβ42/40 ratio, as well as the CSF Aβ42/38 ratio, was ‘superior biomarkers of AD pathology compared with Aβ42 alone’. Using three commercially available CSF biomarker immunoassays, this study found that the CSF Aβ42/40 and Aβ42/38 ratios improved differentiation of AD from non-ADs, especially when separating AD from DLB/PDD and VaD.

The authors point to several potential explanations for the improved accuracy when using the CSF Aβ42/40 and Aβ42/38 ratios instead of Aβ42. They suggest that it might be that subcortical pathologies not specific to AD, such as WMLs and alpha-synuclein pathology, cause reduced levels of all CSF Aβ species, including Aβ42. A second explanation for the improved diagnostic accuracy of the Aβ42/40 and Aβ42/38 ratios could be that differences in the overall production and clearance of Aβ probably contribute to inter-individual variability in total CSF Aβ levels. This is supported by the present finding that in CSF Aβ42 correlates with Aβ38 and Aβ40 even in healthy controls. Consequently, when detecting Aβ42 brain pathology with CSF Aβ42, using ratios to Aβ40 or Aβ38 might correct for inter-individual differences in total Aβ levels.

In another study, which evaluated the differential diagnosis of DLB and AD, once again, the CSF Aβ42/40 ratio was found to aid diagnosis. The study by Bousiges et al. [25] found that the Aβ42/40 ratio remained unchanged in DLB patients between the prodromal and demented stages, contrary to what was observed in AD. The Aβ42/40 ratio therefore makes it possible to distinguish between the two pathologies ‘at a time when the differential diagnosis is difficult’.

Finally, in a study by Lehmann et al. [26], the Aβ42/40 ratio was added to a previously described PLM scale (Paris-Lille-Montpellier study), which combines Aβ42, T-tau and P-tau181 biomarkers, in order to evaluate an optimized PLMR scale (PLM ratio scale). Nine hundred and four participants (342 AD and 562 non-AD) were studied, in two chronologically different cohorts (400 Mtp-1 and 504 Mtp-2). For AD patients, the mean CSF Aβ42 and CSF Aβ42/40 ratio was 553 ± 216 pg/mL and 0.069 ± 0.022 pg/mL in Mtp-1 and 702 ± 335 pg/mL and 0.045 ± 0.020 pg/mL in Mtp-2. The distribution of AD and non-AD differed between the PLM and the PLMR scales (p < 0.0001). The percentage AD well-classified (class 3) increased with PLMR from 38 to 83% in Mpt-1 and from 33 to 53% in Mpt-2. A sharp reduction of the discordant profiles going from 34 to 16.3% and from 37.5 to 19.8%, for Mtp-1 and Mtp-2 respectively, was also observed. The authors concluded that the integration of the Aβ42/40 ratio in the PLMR scale resulted in an easy-to-use tool which reduced the discrepancies in biologically doubtful cases and increased the confidence in the diagnosis.

In order to try to assess what is the overall impact on diagnosis, an estimation was made of what the actual percentage of patients that are misdiagnosed by Aβ42 alone and that become correctly classified with the Aβ42/40 ratio. Assuming normal distribution of Aβ40 across the population of interest [15], a very conservative estimation is that neglecting Aβ40 (which is equivalent to applying Aβ42 as the sole CSF biomarker of amyloidosis) leads to misdiagnoses of ca. 5–10% of cases. This is further confirmed by Baldeiras et al. [27], who found an increase in the proportion of interpretable CSF profiles from 61 to 75% (i.e. ca. 20% of the baseline value) of the MCI patients. Also, Dorey et al. [28] report that determining CSF Aβ40 concentrations corrected diagnosis in AD patients with non-pathological CSF Aβ42 levels in 76.2% of cases using the CSF Aβ42/40 ratio.

In summary, the accumulation of evidence clearly points to the usefulness of the CSF Aβ42/40 ratio for the diagnosis of AD in patients with dementia. The CSF Aβ42/40 ratio is also better than CSF Aβ42 alone at distinguishing AD dementia from non-AD dementias, not only from controls. The evidence therefore strongly suggests that the CSF Aβ42/40 ratio, rather than CSF Aβ42 alone, should be used in the clinical work-up of AD, as a way to improve the diagnostic accuracy for distinguishing ADD from other dementia disorders.

Comparison of the diagnostic accuracy for predicting the development of ADD in patients with MCI

With disease-modifying therapies on the horizon, there is a need to be able to predict the risk of developing ADD before the onset of dementia, i.e. during the MCI and subjective cognitive decline (SCD) stages. The increased percentage of MCI subjects with pathologic CSF who convert to ADD, compared to those having normal CSF, is considered a very strong argument in favour of the use of CSF biomarkers as predictors of MCI to ADD conversion. Here we provide details of six studies that have compared the diagnostic accuracy of CSF biomarkers when predicting the development of ADD in patients with MCI. All of the studies show the added value of the CSF Aβ42/40 ratio in accurately predicting progression to ADD. Studies with relevant data are also summarized in Table 2.
Table 2

CSF biomarkers for predicting the development of AD in patients with MCI

Study

Number of AD patients

Number of MCI/ non-AD patients

Number of control patients

CSF biomarkers

Optimal cut-off*

Sensitivity % (95% CI)**

Specificity % (95% CI)**

AUC (95% CI)

SL (p value)#

Hansson et al. [31]

0

137 (MCI)

0

42

0.64 ng/mL

93 (82–98)

53 (41–64)

0.77 (0.69–0.84)

42/40 ratio

0.95

87 (76–95)

78 (67–86)

0.87 (0.80–0.92)

< 0.05

Hertze et al. [32]

94

166 (MCI) 29

38

MCI-AD vs MCI

 

(DD)

 

42 MSD

< 523

67

71

0.73 (0.66–0.80)

   

42 MSD/40 ratio

< 0.069

85

71

0.86 (0.79–0.91)

NP

42 MSD/38 ratio

< 0.37

88

71

0.85 (0.79–0.91)

NP

Parnetti et al. [33]

28 (AD) 32

58 (MCI-MCI)

0

MCI-AD vs MCI-MCI

(MCI-AD)

28 (OND)

 

42

420.5 pg/mL

56 (38–74)

96 (88–99)

0.85

42/40 ratio

5.3

71 (48–89)

92 (79–98)

0.82

NP

AD vs non-AD (OND)

42

500.0 pg/mL

63 (42–81)

79 (59–92)

0.70

42/40 ratio

5.0

74 (54–89)

79 (59–92)

0.78

NP

Lewczuk et al. [21]

75 (AD-MCI)

0

45

42

691 pg/mL

69.3

88.9

0.895 (0.819–0.946)

42/40 ratio

0.06

93.3

100

0.970 (0.916–0.993)

< 0.0001

Baldeiras et al. [27]

168

197 (MCI)

66

42

585 pg/mL

82

83

0.882 (0.837–0.927)

42/40 ratio

0.068

79

86

0.874 (0.827–0.921)

n.s.

Frölich et al. [34]

0

115 (MCI)

0

42

< 600 pg/mL

74

64

0.68

42/40 ratio

59

75

0.66

NP

*Optimal cut-offs were created using different statistical approaches—please see original articles for details.**Sensitivity and specificity are a function of the cut-off, and the cut-offs were calculated in different ways, therefore they are not clearly comparable across different articles. #Significance levels (p values) of the AUC values are comparisons of the Aβ isoform ratios vs Aβ42 alone. Amyloid beta, AD Alzheimer’s Disease, AD-MCI early AD and MCI, AUC area under curve, DD depressive disorder, MCI mild cognitive impairment, MCI-AD mild cognitive impairment patients progressing to AD, MCI-MCI stable MCI patients, MSD Meso Scale Discovery assay, NP not provided, n.s not significant, OND other neurological diseases, SL significance level

In a study validating the previously introduced Erlangen Score interpretation algorithm [29], Lewczuk et al. compared three- and four-biomarker-based approaches in the German Competence Network Dementias cohort. They found that the score based on four biomarkers (i.e. including the Aβ42/40 ratio in addition to Aβ42) correlated better with the ratio of pre-dementia subjects having progressed to ADD than the score based on three biomarkers [30].

In a study by Hansson et al. [31], baseline levels of Aβ40 and Aβ42 in CSF were measured in a cohort of patients with MCI (n = 137) in relation to the final diagnosis after 4–6 years of follow-up. The Aβ42 concentration at baseline and the Aβ42/40 ratio were significantly decreased in MCI patients who developed ADD compared to cognitively stable MCI patients and MCI patients who developed other forms of dementia (p < 0.001). The baseline levels of Aβ40 were similar in all MCI groups but correlated with change in Mini-Mental State Examination scores in converters to ADD. The Aβ42/40 ratio was superior to Aβ42 concentration with regard to identifying incipient AD in MCI (p < 0.05). The authors concluded that the data provides support for the view that amyloid precursor protein metabolism is disturbed in early sporadic AD and points to the usefulness of the Aβ42/40 ratio as a predictive biomarker for AD.

A study by Hertze et al. [32] investigated the diagnostic accuracy of CSF biomarkers to predict the development of ADD within 5 years in patients with MCI. The results showed that the predictive values of the Aβ42/40 and Aβ42/38 ratios were higher compared to that of Aβ42 alone (p < 0.01) when using the electrochemiluminescence technology of the Meso Scale Discovery (MSD) platform to quantify amyloid in MCI patients. However, Aβ42 quantified with a bead-based multiplexing (xMAP) technology performed as well as the MSD Aβ42/40 ratio.

A 4-year follow-up study carried out by Parnetti et al. [33] measured CSF Aβ40, Aβ42, T-tau and P-tau181 in patients with AD, stable MCI (MCI-MCI) and MCI evolving into ADD (MCI-AD) in order to evaluate the power of each biomarker and/or their combination in predicting AD progression. Although they found that inclusion of the Aβ42/40 ratio instead of Aβ42 alone did not improve the prediction power of the model in the multivariate analysis, when univariate statistics were employed, they found that the Aβ42/40 ratio had an increased sensitivity with respect to Aβ42.

In a recently published paper, Baldeiras et al. [27] showed that replacing Aβ42 by the Aβ42/40 ratio resulted in a significant increase in the proportion of interpretable biological profiles (from 61 to 75%, p = 0.001) of MCI patients, due to a reduction by half in the number of suspected non-Alzheimer pathophysiology cases and an increase in the proportion of the high-AD-likelihood subgroup. In their study, the risk of progression to ADD was highest in the ‘high-likelihood’ group and increased when the Aβ42/40 ratio, instead of Aβ42, combined with T-tau and P-tau181 was used for biomarker-based categorization.

Frölich et al. [34] investigated whether the progression of MCI to AD dementia can be predicted by cognitive, neuroimaging and CSF markers. They studied 115 complete datasets from MCI patients of the ‘Dementia Competence Network’, a German multi-centre cohort study with annual follow-up up to 3 years. They hypothesized that since most biomarkers reveal complementary information, a combination of biomarkers may increase the predictive power. Their results showed that two- to four-parameter combinations of the eight predictor/biomarker indices (MMSE, CDR-sb, CERAD-DR, HCV, Aβ42, Aβ42/40, T-tau and P-tau181) were numerically superior over the performance of a single biomarker index in predicting MCI subjects who progressed to AD. In this dataset, however, the Aβ42/Aβ40 ratio was not consistently superior to Aβ42 alone for predicting AD dementia in MCI patients.

Together these reports provide evidence that clearly demonstrates the added value of the CSF Aβ42/40 ratio in accurately predicting progression to ADD.

In the last years, studies have also been published applying the CSF Aβ38 concentration as the reference isomer for normalization of the Aβ42 concentration (in the form of Aβ42/38 ratio). However, it needs to be stressed that neither the results of these studies, nor the physiological rationale behind using Aβ38 instead of Aβ40 is convincing enough to replace Aβ40.

Comparison of the diagnostic accuracy of the CSF biomarkers and Aβ-PET

CSF Aβ42 and Aβ-PET have both been found to correlate highly with brain biopsy findings [35, 36]. Decreased concentrations of CSF Aβ42 and increased retention of amyloid tracers in the brain on PET are considered the earliest biomarkers of AD, although some evidence suggests that the alterations measurable in the CSF occur earlier [43]. A potential advantage of Aβ-PET over CSF Aβ42 as an early diagnostic marker is the possibility to detect regional Aβ depositions that might occur before the global neocortical signal becomes pathologic. On the other hand, analysis of CSF offers a quantitative result of the net effect of the biomarkers. Running costs of CSF analysis are 10- to 15-fold lower than those for Aβ-PET (total costs for lumbar puncture and analysis of four CSF biomarkers in Germany do not exceed €200). CSF analysis is also more accessible to patients, it does not require the patient and caregiver to travel to a distant centre equipped with PET facilities and it enables simultaneous analysis of dozens of biomarkers in one sample volume, including biomarkers of neurodegeneration, neuroinflammation and others [3739]. In contrast to neuroimaging modalities, a CSF-based approach enables aliquoting and storage of a sample’s volume for further analyses in the future, also in other laboratories.

Finally, although lumbar puncture is frequently regarded as an invasive procedure, serious complications are extremely rare, with the most common, headache, only being observed in 2% of the elderly population and being easily treated with simple analgesia [40]. On the other hand, it is questionable to consider injection of radioactive tracers, designed to target brain tissue, as a ‘non-invasive’ procedure. Here we provide details of five studies that have compared the diagnostic accuracy of CSF biomarkers and Aβ-PET, all showing that both methods can identify early AD with high accuracy. Studies with relevant data are also summarized in Table 3.
Table 3

Studies comparing CSF biomarkers and Aβ-PET

Study

Number of AD patients

Number of MCI/ non-AD patients

Number of control patients

CSF biomarkers/ PET

Optimal cut-off*

Sensitivity% (95% CI)**

Specificity% (95% CI)**

AUC (95% CI)

SL (p value)#

Mattsson et al. [42]

121

68 (SCD)

161

42

< 192 ng/L

419 (MCI)

 

42/40 ratio

 

 

NP

  

Florbetapir PET

> 1.11 SUV

NP

Janelidze et al. [24]

Cohort 1

Cohort 1

Cohort 1

Euroimmun

0

215 (MCI)

0

42

< 507.5 pg/mL

83.2

83.3

0.894 (0.850–0.937)

   

42/40 ratio

< 0.10

97.2

88.0

0.954 (0.923–0.986)

0.008

42/38 ratio

< 0.29

92.5

88.9

0.943 (0.911–0.975)

0.007

MSD

42

< 495.9 pg/mL

85.0

88.9

0.916 (0.876–0.956)

42/40 ratio

< 0.09

95.3

95.4

0.975 (0.952–0.998)

< 0.001

42/38 ratio

< 0.17

97.2

91.7

0.964 (0.935–0.992)

0.007

Quanterix

42

< 1742 pg/mL

73.3

77.5

0.810 (0.707–0.913)

42/40 ratio

< 0.16

90.0

90.0

0.912 (0.834–0.991)

0.002

Lewczuk et al. [41]

0

199 CN &

0

42

735 pg/mL

81.6 (68.0–91.2)

72.7 (64.8–79.6)

0.814 (0.752–0.865)

 

abnormal (150 PET−/ 49 PET+)

 

42/40 ratio

0.05

95.9 (86.0–99.5)

88.0 (81.7–92.7)

0.936 (0.892–0.966)

< 0.001

Janelidze et al. [44]

0

262 (MCI/SCD)

0

Innotest

42

≤ 548 pg/mL

96

82

0.92 (0.89–0.95)

42/40 ratio

≤ 0.06

91

82

0.92 (0.88–0.95)

NP

Modified Innotest

42

≤ 1091 pg/mL

92

74

0.87 (0.83–0.91)

42/40 ratio

≤ 0.12

92

87

0.93 (0.90–0.96)

≤ 0.01

Euroimmun

 

42

≤ 449 pg/

82

80

0.88

42/40 ratio

mL

≤ 0.10

93

88

(0.84–0.92)

0.93 (0.90–0.96)

≤ 0.01

MSD

42

≤ 506 pg/mL

94

76

0.89 (0.85–0.93)

42/40 ratio

≤ 0.08

96

89

0.95 (0.93–0.98)

≤ 0.001

Schindler et al. [46]

0

22 (MCI)

176 (CN)

42

< 1.098 pg/mL

0.85 (0.80–0.90)

 

(~ 25% PiB+)

(~ 25% PiB+)

42/40 ratio

< 0.075

0.93 (0.89–0.96)

NP

*Optimal cut-offs were created using different statistical approaches—please see original articles for details. **Sensitivity and specificity are a function of the cut-off, and the cut-offs were calculated in different ways, therefore they are not clearly comparable across different articles. #Significance levels (p values) of the AUC values are comparisons of the Aβ isoform ratios vs Aβ42 alone. amyloid beta, AD Alzheimer’s Disease, ADAS-cog Alzheimer’s Disease Assessment Scale-cognitive subscale, AUC area under curve, cen centiloid, CN cognitively normal, CU centiloid units, DLB dementia with Lewy bodies, FTD frontotemporal dementia, MCI mild cognitive impairment, MCI-AD MCI that subsequently developed AD dementia, MSD Meso Scale Discovery, NP not provided, n.s not significant, PD Parkinson’s Disease, PDD Parkinson’s Disease with dementia, PET, positron emission tomography, MS-RMP mass spectrometry-based candidate reference measurement procedure, PiB carbon-11 labelled thioflavin-T derivative, Pittsburgh compound B, SCD subjective cognitive decline, SL significance level, SUV standardized uptake value, VaD subcortical vascular dementia, vis visual

In Cohort 1 of a study carried out by Janelidze et al. [24], which included 215 MCI patients, a discrepancy between CSF Aβ42 and Aβ-PET status was observed. In fact, they found that 10–20% of healthy individuals and MCI patients showed a mismatch in CSF Aβ42 and Aβ-PET status. In their study, they found that the CSF Aβ42/40 and Aβ42/38 ratios better predict abnormal cortical amyloid deposition (visualized with PET) compared with Aβ42. The ratios increased the classification performance both for patients who were falsely classified as positive (by low CSF Aβ42) and for patients who were falsely classified as negative (by high CSF Aβ42).

One possible explanation proposed by the authors for the improved concordance between Aβ-PET and CSF Aβ, when using the Aβ42/40 and Aβ42/38 ratios instead of Aβ42, was that subcortical pathologies not specific to AD could cause reduced levels of all CSF Aβ species, including Aβ42, but not the ratios. For example, in patients with MCI, low CSF Aβ42, Aβ40 and Aβ38 were all linked to subcortical injury, including increased white matter lesions (WML) and enlarged lateral ventricles. The mechanisms underlying these associations are likely related to dysregulation in β amyloid precursor protein pathways with a general decline in the production of Aβ.

A study by Lewczuk et al. [41] reported an association between amyloid alterations reflected in the CSF with those in Aβ-PET in a cohort of 199 patients. The results showed that the CSF Aβ42/40 ratio corresponded better than Aβ42 with PET results, with a larger proportion of concordant cases (89.4% vs 74.9%, respectively, p < 0.001) and a larger area under the ROC curve (AUC 0.936 vs 0.814, respectively, p < 0.001) associated with the ratio. For both CSF biomarkers, the percentage of CSF-abnormal/PET-normal cases was larger than that of CSF-normal/PET abnormal cases. The authors concluded that the CSF Aβ42/40 ratio is superior to Aβ42 alone as a marker of amyloid-positivity by PET, which may be explained by the fact that the ratio compensates for general between-individual variations in CSF total Aβ concentrations. Furthermore, they speculated, that the fact that there was a higher proportion of subjects with pathologic CSF (as reflected by Aβ42 or Aβ42/40) and normal PET compared to those with pathologic PET and normal CSF might suggest that CSF reflects amyloidosis earlier than PET does. Similar conclusions based on earlier findings in CSF compared to PET were also made by Mattsson et al. and Palmqvist et al. [42, 43].

Janelidze et al. [44] studied the concordance between CSF Aβ42 levels measured using five different immunoassays [Innotest, Modified Innotest (increased antibody concentration and incubation time, and lower CSF volume), fully automated Lumipulse, Euroimmun and MSD assays) and visual read of Aβ-PET images in 262 patients with MCI or SCD. They found that although the accuracy to correlate with visual 18F-flutemetamol PET was decreased when using newer Aβ42 assays, this limitation is overcome by using the CSF Aβ42/40 ratio. They also found that the CSF Aβ42/40 ratio from the newer assays showed improved accuracy for detection of cortical Aβ fibrils as measured by PET. Moreover, the sensitivities and specificities of these newer assays were less influenced by moderate changes in the cut-offs when the CSF Aβ42/40 ratio was used, a finding that is important when samples will be analysed consecutively over time.

In another study analysing the agreement between data on cerebral amyloidosis, derived using Pittsburgh compound B (PiB) PET and immunosorbent assay of CSF Aβ42, Leuzy et al. [45] examined 243 subjects with normal cognition and patients with MCI. They found that agreement between PiB classification and MSD immunosorbent assay/mass spectrometry reference measurement procedure findings was further improved when using the CSF Aβ42/40 ratio.

A study by Schindler et al. [46] studied the relationship between CSF biomarkers, as measured by a novel automated immunoassay platform and Aβ-PET. They found that CSF biomarker ratios (T-tau/Aβ42, P-tau181/Aβ42 and Aβ42/40) best discriminated PiB-positive from PiB-negative individuals.

These reports show that both Aβ-PET and CSF biomarkers can identify early AD with high accuracy. However, several studies strongly suggest that Aβ alterations in the CSF occur earlier [42, 43]. Similarly, there is no convincing evidence that the spatial distribution of Aβ deposits in the brain tissue observed in PET deliver clinically relevant information [47]. In addition, the CSF Aβ42/40 ratio can better predict abnormal cortical amyloid deposition (visualized with PET) compared with Aβ42. This then leads to fewer patients being diagnosed as false positive (low CSF Aβ42) or false negative (high CSF Aβ42).

Effects of non-AD pathologies on Aβ42, Aβ40 and the Aβ42/40 ratio, such as WMLs, PDD and DLB

In clinical practice, CSF biomarker analyses are often carried out in patients with atypical or mixed presentation of dementia. This makes the diagnosis complex and highlights the importance of being able to discriminate AD from other neurodegenerative processes such as FTD, WMLs, VaD, DLB, PDD and cerebral amyloid angiopathy [5].

Selnes et al. [48] studied the effects of cerebrovascular disease on amyloid precursor protein metabolites in CSF in 37 patients with SCD or MCI without stroke, and 26 after acute stroke. They found that CSF levels of Aβ38, Aβ40 and Aβ42 were inversely correlated with chronic WML volume (p ≤ 0.01; p ≤ 0.05; p ≤ 0.05, respectively), but not with acute WML or infarct volumes.

Similarly, van Westen et al. [49] studied the association of cerebral WML with Aβ isoforms and Aβ-PET in 831 subjects with cognitive performance ranging from normal to ADD. The results showed that all Aβ isoforms were consistently inversely correlated with WML, but the CSF Aβ42/40 ratio and Aβ-PET were not. These results indicate that the presence of WMLs affects the levels of CSF Aβ38, Aβ40 and Aβ42, but not the CSF Aβ42/40 ratio or Aβ-PET.

Finally, Gabelle et al. [14] observed that Aβ40 levels were decreased in FTD suggesting that it could represent a diagnostic biomarker in this pathology.

It can therefore be concluded that Aβ42, as well as Aβ38 and Aβ40, might be reduced in CSF due to non-AD related pathologies, but usually, the Aβ42/40 ratio, as well as other Aβ ratios, including Aβ42, are not affected. These studies therefore point to the usefulness of the CSF Aβ42/40 ratio in improving the accuracy of the differential diagnosis in patients with ambiguous biological profiles or with other conditions that might affect the concentrations of the Aβ peptides.

Effects of pre-analytical handling on Aβ42 and the Aβ42/40 ratio

Various papers have pointed out pre-analytical and analytical variability between laboratories for the concentration of the Aβ42 peptide in CSF [5054]. Tubes for collection, sample handling and sample storage conditions, in particular, have been noted as critical factors [55, 56]. These factors have also been highlighted as a possible reason for problems linked to inter-centre variability when it comes to analysing CSF biomarkers [57].

The type of sampling and storage tubes used is an important source of variability because of the tendency of Aβ peptides to adsorb on plastic surfaces [21, 54, 56]. It has been proposed that there is parallel adsorption of CSF Aβ42 and Aβ40 onto the sampling tube surface, regardless of the type of plastic, however with significant differences across different type of plastics [58]. They also suggest that systematic use of the CSF Aβ42/40 ratio would provide a complete interpretation of CSF amyloid biomarker results, integrating the impact of plastic tube type.

Lewczuk et al. [58] measured biomarkers of AD (T-tau, P-tau181, Aβ42, Aβ40) in CSF samples in collection tubes made of different materials. The results suggest that the CSF Aβ42/40 ratio and CSF P-tau181 are much less prone to methodologic error introduced by interactions of the biomarkers’ molecules with the test tube surfaces compared with Aβ40 and Aβ42 concentrations, similarly to the concentrations of T-tau. The authors concluded that the CSF Aβ42/40 ratio is a more reliable biomarker than pure Aβ concentrations, as the Aβ42/40 ratio is less altered by interaction with the surface of the collection tubes.

In a similar study by Gervaise-Henry et al. [59], the impact of collection tubes and repetitive freeze/thaw cycles on CSF Aβ42 and Aβ40 concentrations was investigated. CSF from 35 patients was collected in different polypropylene (PP) tubes and stored at − 80 °C. Samples were also subjected to three successive freeze-thaw cycles. The results showed that CSF Aβ42 and Aβ40 values were significantly different depending on the type of collection tube and the number of freeze/thaw cycles. Although the calculation of the CSF Aβ42/40 ratio eliminated the effect of PP tube-dependent variation, this was not the case for freeze-thaw cycle-associated variation. The authors concluded that the use of Aβ42/40 ratio rather than Aβ42 alone could contribute toward pre-analytical standardization, thus allowing for the general use of CSF AD biomarkers in routine practice.

Willemse et al. [60] tested several variables as potential confounders influencing adsorption of Aβ peptides on the surfaces of test tubes, including different polypropylene tube brands, volumes, CSF Aβ42 concentrations, incubation times, pipettes, vortex intensities and other CSF proteins. They found that every sample transfer from one tube to another resulted in 5% loss of Aβ42 concentration, which reached as high as 10% when small volumes were used. This decrease in concentration was, however, similar for Aβ40, resulting in stable Aβ42/40 ratios over multiple tube transfers. Correspondingly, they conclude that use of the Aβ42/40 ratio overcomes the effect of adsorption-derived Aβ concentration loss and can therefore contribute to increased diagnostic accuracy.

Furthermore, Vanderstichele et al. [61] determined that using the CSF Aβ42/40 ratio mitigates many of the effects of additional freeze/thaw cycles, tube type and CSF volumes for PP storage tubes. In fact, they concluded that the CSF Aβ42/40 ratio is clearly a more robust biomarker than Aβ42 toward (pre-) analytical interfering factors. They also observed that the rate of adsorption to PP recipients is higher for Aβ42 than for the other amyloid isoforms, such as Aβ40, and therefore using the Aβ42/40 ratio does not completely eliminate the effects of binding of Aβ to the tube walls of PP tubes. However, they found that ‘low binding recipients’ are able to reduce the binding of Aβ species to the tube walls. They concluded that integration of the Aβ42/40 ratio and ‘low-binding tubes’ into guidance criteria may speed up worldwide standardization of CSF biomarker analysis.

In summary, evidence from studies on the effect of pre-analytical handling on biomarkers of AD suggest that use of the CSF Aβ42/40 ratio would improve the interpretation of CSF amyloid biomarker results, by reducing the impact of these factors on the final outcome. The use of the CSF Aβ42/40 ratio could therefore contribute toward pre-analytical standardization, allowing for the use of CSF AD biomarkers in routine clinical practice.

Disadvantages of the use of the CSF Aβ42/40 ratio

The main disadvantage of the use of the CSF Aβ42/40 ratio is economical and not interpretational in nature. Considering the laboratory costs of the AD biomarkers, the inclusion of Aβ40 increases the costs by ca. €40–50, which is negligible when considering the total costs of the diagnostic work-up and treatment of patients with suspected AD assessed at specialized memory clinics. Furthermore, the amount of CSF sample needed to perform this additional test is also negligible (5–10 μL, depending on the method). In addition, interpretation of the results when four biomarkers (instead of three) are used is not more complex, when a solid interpretational algorithm is validated and consequently used.

Conclusion

There is a growing body of evidence that suggests the better diagnostic performance of the CSF Aβ42/40 ratio compared to CSF Aβ42 alone. In addition, it also appears to be clear that including the CSF Aβ42/40 ratio in the clinical workup of MCI patients improves the accuracy of predicting progression to AD.

It has also been shown that both Aβ-PET and CSF biomarkers can identify early amyloid pathology with high accuracy. The CSF Aβ42/40 ratio can also better predict abnormal cortical amyloid deposition (visualized with PET) compared with CSF Aβ42. This then leads to fewer patients being diagnosed as false positive (low CSF Aβ42) or false negative (high CSF Aβ42). In addition, there is evidence to suggest that Aβ alterations in CSF occur earlier than they are detectable in Aβ-PET.

Addition of the CSF Aβ42/40 ratio to the usual panel of CSF AD biomarkers for patients with ambiguous biological profiles also increases the number of interpretable results.

It has also been found that the use of the CSF Aβ42/40 ratio rather than CSF Aβ42 alone contributes toward pre-analytical standardization, removing the effects of (pre-)analytical interfering factors, such as tube type, freeze/thaw cycles and CSF volumes.

The working group therefore makes the following recommendations:
  1. 1.

    The Aβ42/40 ratio should always be analysed, irrespective of the results of other AD biomarkers, and without paying attention to whether Aβ42 is normal or pathologic. This is driven by the fact that the Aβ42/40 ratio can equally change the CSF interpretation from ‘normal to pathologic’ as from ‘pathologic to normal’. Analysing the Aβ42/40 ratio only in cases with abnormal Aβ42 (leaving cases with normal Aβ42 without further consideration, i.e. as truly not having amyloidosis) would neglect the former scenario. On the other hand, performing Aβ42/40 ratio analysis only in cases with normal Aβ42 (with subjects with abnormal Aβ42 considered as truly having amyloidosis) would neglect the latter case.

     
  2. 2.

    It should be mandatory for every laboratory to establish their own specific reference values (cut-offs) for the Aβ42/40 ratio and to participate in an internal quality control programme to ensure longitudinal stability in the measurements of Aβ42 and Aβ40, just as it is mandatory to establish reference values and control quality of all other biomarkers.

     
  3. 3.

    Following on from (2), it is possible to combine laboratory results obtained on different platforms and from different vendors. The point is only that the reference value for the Aβ42/40 ratio must be carefully validated. It is beyond the scope of this paper to make suggestions on statistical methods to calculate reference values and/or their transfer from other laboratories or analytical platforms.

     

Based on the body of evidence collected here it is the conclusion of the current working group that the CSF Aβ42/40 ratio, rather than the absolute value of CSF Aβ42, should be used when analysing CSF AD biomarkers to improve the percentage of appropriately diagnosed patients. It is also suggested that the CSF Aβ42/40 ratio could therefore be used as a proxy for amyloid status in AD clinical trials and eventually in clinical care settings.

Abbreviations

AD: 

Alzheimer’s Disease

ADD: 

AD dementia

AUC: 

Area under the ROC curve

42

Amyloid β 42

42/40 Ratio: 

Concentration ratio of Aβ42 to Aβ40

Aβ-PET: 

Aβ positron emission tomography

CSF: 

Cerebrospinal Fluid

DLB: 

Dementia with Lewy Bodies

FTD: 

Frontotemporal Dementia

MCI: 

Mild cognitive impairment

MCI-AD: 

MCI evolving into ADD

MCI-MCI: 

Stable MCI

non-AD: 

Other types of dementia

PDD: 

Parkinson’s Disease Dementia

PiB: 

Pittsburgh compound B

PLMR-scale: 

PLM ratio scale

PLM-scale: 

Paris-Lille-Montpellier scale

P-tau181

Tau phosphorylated at threonine 181

ROC: 

Receiver Operating Characteristic

SCD: 

Subjective cognitive decline

T-tau: 

Total Tau

VaD: 

Subcortical vascular dementia

WML: 

White matter lesions

Declarations

Acknowledgements

We would like to thank Dr. Michelle Derbyshire for her excellent support as a medical writer. We are grateful to Dr. Sandra Langer for outstanding organization of the meetings and conferences leading to this paper and her exceptional comments. We highly appreciate critical reading by Dr. Nathalie Le Bastard, Dr. Christopher Traynham and Dr. Laura Vernoux.

Funding

Fujirebio Europe sponsored this paper, however, it had no influence on its factual content. PL was supported by the Innovative Medicines Initiative Joint Undertaking under EMIF grant agreement n° 115372, resources of which are composed of financial contribution from the European Union’s Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution. OH has acquired research support (for the institution) from Roche, GE Healthcare, Biogen, AVID Radiopharmaceuticals, Fujirebio and Euroimmun. HZ’s research is supported by the Swedish Research Council, the European Research Council, the Knut and Alice Wallenberg Foundation, the Olav Thon Foundation, the UK Dementia Research Institute at UCL and Swedish State Support for Clinical Research (ALFGBG).

Availability of data and materials

This review does not contain any analyzable data. All sources cited in this paper are publicly available.

Authors’ contributions

OH and PL prepared the initial draft of the paper. All authors read and approved the final paper.

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

All authors have received consultation honoraria from Fujirebio Europe. PL has received honoraria for consultations and/or lectures from Fujirebio, IBL International, AJ Roboscreen and Roche. In the past 2 years, OH has received consultancy/speaker fees (paid to the institution) from Lilly and Roche. HZ has served on scientific advisory boards for Eli Lilly, Roche Diagnostics, Samumed, CogRx and Wave.

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Authors’ Affiliations

(1)
Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
(2)
Memory Clinic, Skåne University Hospital, Malmö, Sweden
(3)
Center of Excellence for Neurodegenerative disorders (COEN) of Montpellier, Montpellier University, CHU Montpellier, INSERM, Montpellier, France
(4)
Department of Neurology, University of Ulm, Ulm, Germany
(5)
Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
(6)
Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
(7)
UK Dementia Research Institute, London, UK
(8)
Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen and Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
(9)
Department of Neurodegeneration Diagnostics, Medical University of Bialystok, Bialystok, Poland
(10)
Lab for Clinical Neurochemistry and Neurochemical Dementia Diagnostics, Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, Schwabachanlage 6, 91054 Erlangen, Germany

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