Alzheimer’s Disease CSF Biomarker Profiles in Idiopathic Normal Pressure Hydrocephalus
by
, , and
Salvatore Mazzeo
1,2
,
Filippo Emiliani
1,
Silvia Bagnoli
1,
Sonia Padiglioni
3,4,
Lorenzo Maria Del Re
5,
Giulia Giacomucci
1,
Juri Balestrini
1,
Assunta Ingannato
1,
Valentina Moschini
6,
Carmen Morinelli
6,
Giulia Galdo
1,
Cristina Polito
2,
Camilla Ferrari
1,
Gastone Pansini
7,
Alessandro Della Puppa
1,
Sandro Sorbi
1,2,
Benedetta Nacmias
1,2 and
Valentina Bessi
1,4,* 1
Department of Neuroscience, Psychology, Drug Research and Child Health, Careggi University Hospital, University of Florence, Largo Brambilla, 3, 50134 Florence, Italy
2
IRCCS Fondazione Don Carlo Gnocchi, 50143 Florence, Italy
3
Regional Referral Centre for Relational Criticalities, 50139 Florence, Italy
4
Research and Innovation Centre for Dementia-CRIDEM, Careggi University Hospital, 50134 Florence, Italy
5
Research Unit of Medicine Ageing, Department of Experimental and Clinical Medicine, University of Florence, 50121 Florence, Italy
6
Dipartimento Neuromosucolo-Scheletrico e Degli Organi di Senso, Careggi University Hospital, 50134 Florence, Italy
7
Neurosurgery Unit, Careggi University Hospital, Largo Giovanni Alessandro Brambilla 3, 50134 Florence, Italy
*
Author to whom correspondence should be addressed.
J. Pers. Med. 2022, 12(6), 935; https://doi.org/10.3390/jpm12060935
Submission received: 21 April 2022
/
Revised: 25 May 2022
/
Accepted: 31 May 2022
/
Published: 6 June 2022
(This article belongs to the Special Issue Molecular Biomarkers and Precision Medicine for Alzheimer)
Abstract
:Patients with idiopathic normal pressure hydrocephalus (iNPH) frequently show pathologic CSF Aβ42 levels, comparable with Alzheimer’s Disease (AD). Nevertheless, the clinical meaning of these findings has not been fully explained. We aimed to assess the role of AD CSF biomarkers (Aβ42, Aβ42/Aβ40, p-tau, t-tau) in iNPH. To this purpose, we enrolled 44 patients diagnosed with iNPH and 101 with AD. All the patients underwent CSF sampling. We compared CSF biomarker levels in iNPH and AD: Aβ42 levels were not different between iNPH and AD, while Aβ42/Aβ40, p-tau, and t-tau were significantly different and showed excellent accuracy in distinguishing iNPH and AD. A multiple logistic regression analysis showed that Aβ42/Aβ40 was the variable that most contributed to differentiating the two groups. Furthermore, iNPH patients with positive Aβ42/Aβ40 had higher p-tau and t-tau than iNPH patients with negative Aβ42/Aβ40. Those iNPH patients who showed cognitive impairment had lower Aβ42/Aβ40 and higher p-tau than patients without cognitive impairment. We concluded that positive CSF Aβ42 with negative Aβ42/Aβ40, p-tau, and t-tau is a typical CSF profile of iNPH. On the contrary, positive Aβ42/Aβ40 in iNPH patients, especially when associated with positive p-tau, may lead to suspicion of a coexistent AD pathology.
1. Introduction
Idiopathic normal pressure hydrocephalus (iNPH) is the most common form of hydrocephalus in adults with an estimated prevalence of 5.9% in patients over 80 years [1]. It is characterized by a classical triad of symptoms (cognitive disturbances, balance/gait impairment, and urinary incontinence), in the presence of a communicating hydrocephalus and a normal opening pressure upon lumbar puncture [2]. It is crucial to diagnose this condition early because 70–80% of patients show clinical improvement following ventricular–peritoneal shunt insertion [3]. Nevertheless, iNPH diagnosis could be challenging because the typical clinical triad is neither sensitive (it is present in <60% of patients [4,5]), nor specific, as clinical features of iNPH are shared with other cognitive and movement disorders, such as Alzheimer’s Disease (AD), vascular dementia, Parkinson’s disease, and atypical parkinsonian syndromes [6,7,8,9]. Moreover, cerebrospinal fluid (CSF) concentration of Aβ42 (one of the AD core biomarkers, whose reduction reflects Aβ amyloid plaques deposition in the brain [10]) was widely shown to be reduced also in iNPH [11]. In iNPH, the reduction of Aβ42 seems not to be related to Aβ amyloid plaques deposition, but to downregulation of Aβ production due to periventricular hypometabolism [12] and to the impairment of glymphatic clearance mechanisms and CSF turnover [13,14].
However, concomitant AD neuropathologic changes have been frequently seen in brain biopsies or in postmortem neuropathological examinations of patients with clinical diagnoses of iNPH [15,16,17]. Furthermore, the presence of AD pathology in iNPH was found to be associated with neuropsychiatric symptoms and behavior changes [18,19,20,21], as well as response to ventricular-peritoneal shunt [22,23,24,25,26]. Due to this evidence, a CSF AD biomarker analysis may have diagnostic and prognostic value, influencing the management of iNPH patients.
Nevertheless, CSF Aβ42 measurement is influenced by interindividual physiological differences in amyloid processing [27] and false negatives are common also in patients with AD, as well as false positives in patients with other neurogenerative diseases and healthy individuals [28]. Measurement of the Aβ40 and Aβ42/Aβ40 ratio have been proposed to overcome this limit [28]. Aβ40 is the most abundant Aβ peptide and is less likely to aggregate than Aβ42. In AD, the reduced levels of Aβ42 are associated with slightly increased or steady levels of Aβ40 [29]. Therefore, the Aβ42/Aβ40 ratio is lower in AD than in healthy controls and showed higher accuracy as compared to Aβ42 in distinguishing AD from other neurodegenerative diseases [28]. In contrast, in iNPH patients, the CSF levels of all the amyloid precursor protein (APP) fragments (Aβ38, Aβ40, Aβ42, sAPPα, and sAPPβ) are decreased compared to controls [11,12,30]. Hence, we speculated that while Aβ42 levels are reduced in the CSF of iNPH patients, Aβ42/Aβ40 may be normal and could be the key factor in interpreting results of CSF biomarkers in iNPH. In this study, we aimed to test our hypothesis by assessing the accuracy of each CSF biomarker in distinguishing iNPH and AD patients to define a typical biomarker profile of iNPH.
2. Materials and Methods
2.1. Participants and Clinical Assessment
We included 44 patients diagnosed with iNPH according to international guidelines [7] and 101 patients diagnosed with AD according to NIA-AA criteria [31]. All of the patients were consecutively referred to the Centre for Alzheimer’s Disease and Adult Cognitive Disorders and Neurology Uniti of Careggi Hospital in Florence for CSF collection between December 2018 and March 2022.
All patients in the iNPH group had ventricular enlargement associated with a patent Sylvian aqueduct and the absence of a macroscopic obstruction of CSF flow, lack of cortical atrophy, presence of periventricular water content, and an increased callosal angle in the coronal plane [32]. Patients in this group were not suffering from any other neurological, psychiatric, or medical conditions that could potentially explain their presenting symptoms.
We excluded AD patients with a history of head injury, other neurological and/or systemic diseases, major depression, and alcoholism or other substance abuse.
All of the patients underwent a comprehensive familial and clinical history, general and neurological examination, extensive neuropsychological investigation, brain magnetic resonance imaging (MRI) or brain Computed Tomography (TC), and lumbar puncture for CSF collection. Patients diagnosed with iNPH underwent a CSF tap test, a procedure that improves the diagnostic accuracy of iNPH and could predict a favorable response to CSF shunt surgery [33].
The local ethics committee approved the protocol of the study. All participants gave written informed consent to participate in the study.
2.2. CSF Tap Test
The iNPH patients underwent baseline evaluation of gait/balance and cognitive function within 24 h before the lumbar puncture. The baseline evaluation included: Short Physical Performance Battery [34], Mini-Mental State Examination [MMSE] [35], Frontal Assessment Battery [36], Phonemic Fluency Test, and Trail-making Test [37]. The lumbar puncture was performed at 9.00 a.m. with removal of 30–50 mL of CSF. The gait/balance assessment (Short Physical Performance Battery) was repeated 6, 24, and 48 h after the CSF subtraction. The neuropsychological examination (Phonemic Fluency test and Trail Making Test) was repeated 6, 24, and 48 h after the CSF subtraction.
2.3. CSF Biomarkers Analysis
The CSF samples collected by the lumbar puncture were immediately centrifuged and stored at −80 °C until performing the analysis. Aβ42, Aβ42/Aβ40 ratio, t-tau, and p-tau have been measured using a chemiluminescent enzyme immunoassay (CLEIA) analyzer LUMIPULSE G600 (Fujirebio, Tokyo, Japan). Cut-off values for CSF were determined by following Fujirebio guidelines (Diagnostic sensitivity and specificity using clinical diagnosis and follow-up golden standard, 19 November 2018 [38]): Aβ42 > 670 pg/mL, Aβ42/Aβ40 ratio > 0.062, t-tau < 400 pg/mL and p-tau < 60 pg/mL. Patients were rated as Aβ42+ or Aβ42− and Aβ42/Aβ40+ and Aβ42/Aβ40− if the Aβ42 and Aβ42/Aβ40 were lower or higher than the cut-off values, respectively. Patients were rated as T+ or T− and N+ or N− if the CSF p-tau and t-tau concentrations were higher or lower than cut-off values, respectively [39].
2.4. Statistical Analysis
Patient groups were characterized using means and standard deviations (SD). We tested for normality in the distribution of the data using the Kolmogorov–Smirnov test. Depending on the distribution of the data, we used t-tests or non-parametric Mann–Whitney U tests for between-groups comparisons and Pearson’s r or Spearman’s ρ for correlations. We used chi-square tests to compare categorical data. We calculated the size effect with Cohen’s d for normally distributed numeric measures, η2 for Mann–Whitney U Test, and Cramer’s V for categorical data. Receiver operating characteristic (ROC) analyses were performed to evaluate the ability of CSF biomarkers to distinguish between iNPH and AD. Youden’s method was used to detect the best cut-off value and accuracy, sensitivity, and specificity. We used binomial logistic regression to ascertain the contribution of each biomarker in distinguishing iNPH and AD. Bonferroni correction was applied to correct for multiple comparisons. All statistical analyses were performed with SPSS software v.25 (SPSS Inc., Chicago, IL, USA) and the computing environment R 4.0.2 (R Foundation for Statistical Computing, Vienna, Austria, 2013).
3. Results
3.1. Description of the Sample
At onset, all the patients in the iNPH group had balance/gait impairment, 33 (75.00%) had cognitive impairment, and 31 (70.45%) had urinary incontinence. Twenty-three patients (52.27%) had the complete triad, while three patients (6.82%) only had balance/gait impairment. Thirteen out of 44 iNPH patients (29.55%) experienced an improvement in their gait after the CSF tap test, while 31 patients (70.45%) did not. Figure 1 shows correlations among the demographic features and CSF biomarkers in the iNPH and AD groups (Figure 1). Both in AD and iNPH, Aβ42/Aβ40 correlated with Aβ42 and p-tau correlated with t-tau. In the iNPH group Aβ42/Aβ40 also correlated with p-tau. In AD patients, MMSE was significantly correlated with age.
3.2. Comparison between iNPH and AD Groups
The iNPH patients were older than the AD (p = 0.044, Cohen’s d = −0.001) and had a lower frequency of APOE ε4+ (χ2 = 5.74, p = 0.017), but these differences where not statistically significant when adjusted for multiple comparisons (accepted at p < 0.003). There were no differences in years of education (p = 0.519, Cohen’s d = −0.135). AD patients had lower mean MMSE scores than iNPH patients (24.25 [SD = 4.02] vs. 19.57 [SD = 4.85], p < 0.001, Cohen’s d = 1.05). There were no differences in Aβ42 concentration between iNPH and AD (624.89 [316.30.82] pg/mL vs. 563.49 [236.941] pg/mL, p = 0.119, d = 0.22), while the Aβ42/Aβ40 ratios were significantly higher in iNPH than in AD (0.09 [0.02] vs. 0.04 [0.02], p < 0.001, d = 2.21). Patients in the iNPH group also had lower p-tau (32.13 [17.85] pg/mL vs. 125.52 [63.09] pg/mL, p < 0.001, d = 2.01) and t-tau (242.66 [205.59] pg/mL vs. 768.79 [374.22] pg/mL, p < 0.001, d = 1.74) concentrations than patients in the AD group (Table 1, Figure 2).
Thirty-one out of 44 iNPH patients and 79 out of 101 AD patients had positive Aβ42 (CSF Aβ42 concentrations below the cut-off value), with no difference in distribution between groups (70.45% [95% C.I = 56.97:83.94] vs. 78.22% [95% C.I. 70.17:86.27], χ2 = 1.01, p = 0.315, V = 0.083). On the opposite, proportions of a positive Aβ42/Aβ40 ratio, (13.64% [95% C.I. = 3.50:23.78] vs. 93.07% [95% C.I. = 88.12:98.02], χ2 = 90.35, p < 0.001, V = 0.79), p-tau (6.82% [95% C.I. = 0:14.27] vs. 88.12% [95% C.I. 81.81:94.43%], χ2 = 87.35, p < 0.001, V = 0.78) and t-tau (11.36 [95% C.I. = 1.99:20.74] vs. 84.16% [95% C.I. = 77.04:91.28], χ2 = 68.98, p < 0.001, V = 0.69) concentrations were significantly lower in the iNPH patients compared to the AD group (Table 1, Figure 3).
3.3. CSF Biomarkers Accuracy in Distinguishing between iNPH and AD
Table 2 summarizes the area under the curve (AUC), accuracy, sensitivity, and specificity of each CSF biomarker in distinguishing iNPH and AD patients. We identified the cut-off values by Youden’s method. The Aβ42/Aβ40 ratio, p-tau, and t-tau showed very high accuracy without differences between the three biomarkers, as showed by the intersection of the 95% confidence intervals. Aβ42 was not able to distinguish between iNPH and AD (Figure 4).
3.4. Logistic Regression Models
To ascertain the effect of each biomarker in discriminating between iNPH and AD adjusting for age, we performed a multivariate logistic regression model including age and CSF biomarker concentrations as independent variables. The regression model was statistically significant (χ2 = 137.19, p < 0.001). The model explained 86.53% (Nagelkerke R2) of the variance in progression. The accuracy of the model in distinguishing between AD and iNPH was 93.79% (95% C.I. = 89.86:97.72) (sensitivity = 96.04% [95% C.I. = 92.87:99.21], specificity = 88.64% [95% C.I. = 83.47:93.81]). The Aβ42/Aβ40 ratio was shown as the only variable which significantly contributed to the model, independent of confounding factors (B = −128.38, S.E. = 47.83, p = 0.007) (Table 3).
We performed the same analysis considering CSF biomarkers after dichotomization according to cut-off values (Table 3). The regression model was statistically significant (χ2 = 128.67, p < 0.001). The model explained 83.21% (Nagelkerke R2) of the variance in progression. Age (B = −0.15, S.E. = 0.06, p = 0.013), Aβ42/Aβ40 (B = 4.37, S.E. = 1.06, p < 0.001) and p-tau (B = 5.05, S.E. = 1.58, p = 0.001) significantly contributed to the model (Table 3).
3.5. Comparison between iNPH and AD with Positive Aβ42
To explore the meaning of positive Aβ42 in iNPH patients, we compared the AD and iNPH groups and considered only patients who had positive Aβ42 (31 iNPH/Aβ42+ vs. 79 AD/Aβ42+, Table 4). The iNPH/Aβ42+ had higher MMSE than AD/Aβ42+ (24.68 [3.43] vs. 19.53 [3.42], p < 0.001, d = 1.50). There was no difference in age. The lower frequency of APOE ε4 in iNPH than in AD/Aβ42+ patients was not statistically significant when adjusted for multiple comparison (23.81 [95% C.I. = 5.59:42.03], χ2 = 4.52, p = 0.033, V = 0.22). The CSF biomarker concentrations (Aβ42/Aβ40, p-tau, and t-tau) were different between iNPH/Aβ42+ and AD/Aβ42+ (Figure 5). In particular among 31 iNPH/Aβ42+, only six patients (19.35% [95% C.I. = 5.45:33.26]) had positive Aβ42/Aβ40, two patients (6.45% [95% C.I. = 0:15.10]) had positive p-tau, and four patients (12.90% [95% C.I. = 1.10:24.70]) had positive t-tau. In contrast, 76 out of 79 AD/Aβ42+ patients had positive Aβ42/Aβ40 (96.20% [95% C.I. = 91.99:100]), 69 had positive p-tau (87.34% [95% C.I. = 80.01:94.67]), and 66 had positive t-tau (83.54% [95% C.I. = 75.37:91.72]).
3.6. Features of iNPH Patients Classified According to Aβ42 and Aβ42/Aβ40 Status
We classified iNPH patients according to Aβ42 status (30 Aβ42+ and 14 Aβ42−). We found no differences in the demographic features and the Aβ42/Aβ40, p-tau, and t-tau values. APOE ε4 allele was not associated with positive Aβ42 status. There were no differences in proportion of cognitive impairment and urinary incontinence between Aβ42+ and Aβ42−. When we compared patients according to Aβ42/Aβ40 status (6 Aβ42/Aβ40+ and 38 Aβ42/Aβ40−, Table 5), patients with positive Aβ42/Aβ40 had higher p-tau (59.46 pg/mL [23.74] vs. 27.47 [11.81], p < 0.001, d = 1.87) than Aβ42/Aβ40− patients. Furthermore, Aβ42/Aβ40+ had higher frequencies of positive p-tau (33.33% [95% C.I. = 0:71.05] vs. 2.63% [C.I. 95% = 0:7.72, χ2 = 7.68, p = 0.006, V = 0.41) and t-tau (50.00% [95% C.I. = 9.99:90.01] vs. 5.26% [C.I. 95% = 0:12.36, χ2 = 10.29, p = 0.001, V = 0.48) as compared to Aβ42/Aβ40−. Notably, all the patients in the Aβ42/Aβ40+ group had positive Aβ42, while four had negative p-tau. Only one patient with positive p-tau had negative Aβ42/Aβ40. Urinary incontinence was more frequent in the Aβ42/Aβ40− group (76.32% [95% C.I. = 62.80:89.83] vs. 33.33% [95% C.I. 4.39:71.05], χ2 = 4.56, p = 0.032, V = 0.323), while there were no differences in cognitive impairment between Aβ42/Aβ40+ and Aβ42/Aβ40−. Particularly in the Aβ42/Aβ40+ group, all the patients had cognitive impairment, but only two out of the six had urinary incontinence.
3.7. Association between Clinical Features and CSF Biomarkers
The iNPH patients who showed cognitive impairment had lower Aβ42/Aβ40 (0.087 [0.022] vs. 0.097 [0.009], p = 0.036, d = 0.61) and higher p-tau (35.48 [18.00] vs. 22.08 [13.62], p = 0.029, d = 0.84) than patients without cognitive impairment at onset. CSF biomarker concentrations were not associated with urinary incontinence, nor with response to CSF tap test.
4. Discussion
Our first result confirmed that patients with iNPH have CSF Aβ42 concentrations comparable to AD and lower concentrations of p-tau and t-tau than AD, as widely described in previous studies [21,40,41,42]. In more detail, about 70% of patients in our series had positive CSF Aβ42, while p-tau and t-tau were positive in 7% and 11% of patients, respectively, which is consistent with a previous report by Santangelo et al. [21]. In contrast, we showed that Aβ42/Aβ40 was higher in iNPH than AD. Only 14% of iNPH patients had a Aβ42/Aβ40 ratio in the pathologic range (below the cut-off value), compared to 93% in the AD group.
When we estimated the diagnostic values of each biomarker, Aβ42/Aβ40, p-tau, and t-tau had very good accuracy in distinguishing between iNPH and AD, with no significant differences between the biomarkers. The logistic regression analysis demonstrated that Aβ42/Aβ40 and p-tau contributed to distinguishing iNPH patients from AD patients, in line with other works [43,44], with the notion that these biomarkers are more specific for AD than Aβ42 and t-tau [45,46]. Nevertheless, we would like to point out that, among iNPH patients with positive Aβ42/Aβ40, four had negative p-tau, while only one iNPH with positive p-tau had negative Aβ42/Aβ40. For the purposes of clinical practice, this remark mainly addresses to consider Aβ42/Aβ40 to identify AD pathology in iNPH patients and to use p-tau as a support biomarker. Based on the evidence that p-tau and t-tau can be increased in iNPH in association with long disease duration [47] and poor response at the CSF tap test [48], other authors suggested that p-tau and t-tau biomarkers may be prognostic factors more than diagnostic tools [49]. We aim to test this hypothesis and clarify the role of p-tau and t-tau in further works with wider samples. Notably, the cut-off values identified in our sample by automatized method were consistent with the cut-off values adopted according to LUMIPULSE producer guidelines. This result suggests using the same cut-off values adopted in clinical practice for the diagnosis of AD, as well as to distinguish iNPH from AD.
Even though several studies already showed that Aβ42 is lower in iNPH patients than in healthy controls, the discrepancy between Aβ42 and Aβ42/Aβ40 was shown only by a few previous studies [43,50]. Our results confirm these reports and are in line with the evidence that in iNPH patients, the CSF levels of all the amyloid precursor protein (APP) fragments (Aβ38, Aβ40, Aβ42, sAPPα, and sAPPβ) are decreased compared to controls [11,12,30]. In contrast, the levels of Aβ42 in AD are associated with slightly increased or steady levels of Aβ40 [29]. Consequently, the ratio between Aβ42 and Aβ40 is supposed to be normal in iNPH patients without AD copathology, as reported by previous studies [43,50] and described in our sample. In particular, we showed that in 86% of iNPH patients with pathologic Aβ42, the Aβ42/Aβ40 ratio was normal, suggesting that in the majority of cases, the reduction of Aβ42 is associated with an equal reduction of Aβ40. Furthermore, we showed that iNPH patients with positive Aβ42 had lower CSF p-tau and t-tau concentrations than AD patients. In particular, only four out of 31 iNPH patients with positive Aβ42 also had positive t-tau and two out of these patients had positive p-tau. This evidence may support the hypothesis that Aβ42 in iNPH patients does not indicate AD copathology.
The role of positive Aβ42/Aβ40 in iNPH is more difficult to interpret. We found that iNPH patients with positive Aβ42/Aβ40 had higher p-tau and t-tau concentrations than iNPH patients with negative Aβ42/Aβ40. In line with a previous result [43], we also found that iNPH patients who showed cognitive impairment had lower Aβ42/Aβ40 and higher p-tau than patients without cognitive impairment. Moreover, 100% of iNPH patients with positive Aβ42/Aβ40 also had positive Aβ42, which might suggest that, in this group of patients, the low Aβ42/Aβ40 ratio is associated with a higher reduction of Aβ42 than Aβ40, as found in the AD patients [29]. Finally, we found that urinary incontinence was uncommon in iNPH with positive Aβ42/Aβ40 (only two out of six), as most of the patients in this group showed only gait/balance disturbance and cognitive impairment, suggesting a possible misdiagnosis. Considering this evidence, positive Aβ42/Aβ40 might indicate a coexistent AD pathology in patients affected by iNPH or a diagnosis of AD dementia.
This hypothesis is supported by many studies which demonstrated that the Aβ42/Aβ40 ratio is more accurate than Aβ42 in identifying AD pathology [51,52].
If confirmed by further works, our results might suggest consideration of positive Aβ42 with negative Aβ42/Aβ40 and p-tau as the typical CSF profile of iNPH. On the contrary, positive CSFAβ42/Aβ40 should lead to suspicion of an underlying AD pathology.
This study had some limitations: (i) the relatively small sample size, especially when we classified patients according to Aβ42/Aβ40 status, which limits the impact of our conclusions; (ii) quantitative scores of gait/balance assessment are not available; (iii) data about gait/balance disturbance and urinary incontinence are not available for the AD group. However, we provided several pieces of evidence which may serve as starting points for future studies. As already stated, this is one of the first studies assessing Aβ42/Aβ40 in differential diagnostics of iNPH. Moreover, despite the small sample size, this is the first study to have classified patients according to Aβ42/Aβ40 status. Many studies divided iNPH patients according to their Aβ status, but did not distinguish between Aβ42 and Aβ42/Aβ40. As shown, Aβ42 could not be considered as an index of Aβ pathology in iNPH. On the other hand, considering only Aβ42/Aβ40 allowed us to classify iNPH patients as carriers or non-carriers of Aβ pathology with a higher accuracy.
5. Conclusions
We showed that positive CSF Aβ42 with negative Aβ42/Aβ40, p-tau, and t-tau is a frequently encountered finding in iNPH and should be considered as a typical CSF profile of iNPH. On the other hand, positive Aβ42/Aβ40 is uncommon in iNPH and is associated with a prevalent cognitive syndrome. Our results are in line with previous evidence and suggest that clinicians should not diagnose AD pathology in patients with iNPH and isolated positive CSF Aβ42. On the contrary, positive Aβ42/Aβ40 in iNPH patients, especially when associated with positive p-tau, may lead to suspicion of a coexistent AD pathology or revision of the diagnosis of iNPH.
Author Contributions
Conceptualization, S.M. and V.B.; methodology, S.M., F.E. and L.M.D.R.; software, S.M.; formal analysis, S.M.; investigation, S.M., F.E., L.M.D.R., S.P., J.B., G.G. (Giulia Giacomucci) and V.B.; resources, S.M., S.P., S.B., A.I., C.P., C.F., S.S., G.P., A.D.P. and V.B.; data curation, S.M., F.E., S.P., L.M.D.R., V.M., C.M., G.G. (Giulia Giacomucci), J.B. and G.G. (Giulia Galdo); writing—original draft preparation, S.M.; writing—review and editing, S.M. and V.B.; visualization, A.D.P., G.P., S.S. and B.N.; supervision, V.B.; project administration, V.B.; funding acquisition, S.S. and B.N. All authors have read and agreed to the published version of the manuscript.
Funding
This study was funded by RICATEN22 (Ateneo Università di Firenze, fondi Ateneo 2022) The funding source had no such involvement in the study design.
Institutional Review Board Statement
The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Institutional Review Board (or Ethics Committee) of Azienda Ospedaliero-Universitaria Careggi.
Informed Consent Statement
Informed consent was obtained from all subjects involved in the study.
Data Availability Statement
An anonymized data that support the findings of this study will be shared by request from any qualified investigator.
Conflicts of Interest
The authors declare no conflict of interest.
References
- Williams, M.A.; Malm, J. Diagnosis and treatment of idiopathic normal pressure hydrocephalus. Continuum 2016, 22, 579–599. [Google Scholar] [CrossRef]
- Hakim, S.; Adams, R.D. The special clinical problem of symptomatic hydrocephalus with normal cerebrospinal fluid pressure. Observations on cerebrospinal fluid hydrodynamics. J. Neurol. Sci. 1965, 2, 307–327. [Google Scholar] [CrossRef]
- Toma, A.K.; Papadopoulos, M.C.; Stapleton, S.; Kitchen, N.D.; Watkins, L.D. Systematic review of the outcome of shunt surgery in idiopathic normal-pressure hydrocephalus. Acta Neurochir. 2013, 155, 1977–1980. [Google Scholar] [CrossRef] [PubMed]
- Espay, A.J.; Da Prat, G.A.; Dwivedi, A.K.; Rodriguez-Porcel, F.; Vaughan, J.E.; Rosso, M.; Devoto, J.L.; Duker, A.P.; Masellis, M.; Smith, C.D.; et al. Deconstructing normal pressure hydrocephalus: Ventriculomegaly as early sign of neurodegeneration. Ann. Neurol. 2017, 82, 503–513. [Google Scholar] [CrossRef] [PubMed]
- Jaraj, D.; Rabiei, K.; Marlow, T.; Jensen, C.; Skoog, I.; Wikkelsø, C. Prevalence of idiopathic normal-pressure hydrocephalus. Neurology 2014, 82, 1449–1454. [Google Scholar] [CrossRef] [Green Version]
- Molde, K.; Söderström, L.; Laurell, K. Parkinsonian symptoms in normal pressure hydrocephalus: A population-based study. J. Neurol. 2017, 264, 2141–2148. [Google Scholar] [CrossRef]
- Relkin, N.; Marmarou, A.; Klinge, P.; Bergsneider, M.; Black, P.M. Diagnosing idiopathic normal-pressure hydrocephalus. Neurosurgery 2005, 57, S4–S16. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Schirinzi, T.; Sancesario, G.M.; Ialongo, C.; Imbriani, P.; Madeo, G.; Toniolo, S.; Martorana, A.; Pisani, A. A clinical and biochemical analysis in the differential diagnosis of idiopathic normal pressure hydrocephalus. Front. Neurol. 2015, 6, 86. [Google Scholar] [CrossRef] [Green Version]
- Tullberg, M.; Jensen, C.; Ekholm, S.; Wikkelsø, C. Normal pressure hydrocephalus: Vascular white matter changes on mr images must not exclude patients from shunt surgery. AJNR Am. J. Neuroradiol 2001, 22, 1665–1673. [Google Scholar]
- Blennow, K.; Zetterberg, H.; Fagan, A.M. Fluid biomarkers in alzheimer disease. Cold Spring Harb. Perspect. Med. 2012, 2, a006221. [Google Scholar] [CrossRef] [Green Version]
- Chen, Z.; Liu, C.; Zhang, J.; Relkin, N.; Xing, Y.; Li, Y. Cerebrospinal fluid aβ42, t-tau, and p-tau levels in the differential diagnosis of idiopathic normal-pressure hydrocephalus: A systematic review and meta-analysis. Fluids Barriers CNS 2017, 14, 13. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Jeppsson, A.; Höltta, M.; Zetterberg, H.; Blennow, K.; Wikkelsø, C.; Tullberg, M. Amyloid mis-metabolism in idiopathic normal pressure hydrocephalus. Fluids Barriers CNS 2016, 13, 13. [Google Scholar] [CrossRef] [Green Version]
- Graff-Radford, N.R. Alzheimer csf biomarkers may be misleading in normal-pressure hydrocephalus. Neurology 2014, 83, 1573–1575. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Ringstad, G.; Vatnehol, S.A.S.; Eide, P.K. Glymphatic MRI in idiopathic normal pressure hydrocephalus. Brain 2017, 140, 2691–2705. [Google Scholar] [CrossRef] [Green Version]
- Cabral, D.; Beach, T.G.; Vedders, L.; Sue, L.I.; Jacobson, S.; Myers, K.; Sabbagh, M.N. Frequency of Alzheimer’s disease pathology at autopsy in patients with clinical normal pressure hydrocephalus. Alzheimer’s Dement. 2011, 7, 509–513. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Leinonen, V.; Koivisto, A.M.; Savolainen, S.; Rummukainen, J.; Tamminen, J.N.; Tillgren, T.; Vainikka, S.; Pyykkö, O.T.; Mölsä, J.; Fraunberg, M.; et al. Amyloid and tau proteins in cortical brain biopsy and alzheimer’s disease. Ann. Neurol. 2010, 68, 446–453. [Google Scholar] [CrossRef]
- Libard, S.; Laurell, K.; Cesarini, K.G.; Alafuzoff, I. Progression of Alzheimer’s disease-related pathology and cell counts in a patient with idiopathic normal pressure hydrocephalus. J. Alzheimer’s Dis. 2018, 61, 1451–1462. [Google Scholar] [CrossRef]
- Kazui, H.; Hirono, N.; Hashimoto, M.; Nakano, Y.; Matsumoto, K.; Takatsuki, Y.; Mori, E.; Ikejiri, Y.; Takeda, M. Symptoms underlying unawareness of memory impairment in patients with mild Alzheimer’s disease. J. Geriatr. Psychiatry Neurol. 2006, 19, 3–12. [Google Scholar] [CrossRef]
- Lim, T.S.; Choi, J.Y.; Park, S.A.; Youn, Y.C.; Lee, H.Y.; Kim, B.G.; Joo, I.S.; Huh, K.; Moon, S.Y. Evaluation of coexistence of Alzheimer’s disease in idiopathic normal pressure hydrocephalus using ELISA analyses for CSF biomarkers. BMC Neurol. 2014, 14, 66. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Niermeyer, M.; Gaudet, C.; Malloy, P.; Piryatinsky, I.; Salloway, S.; Klinge, P.; Lee, A. Frontal behavior syndromes in idiopathic normal pressure hydrocephalus as a function of Alzheimer’s disease biomarker status. J. Int. Neuropsychol. Soc. 2020, 26, 883–893. [Google Scholar] [CrossRef] [PubMed]
- Santangelo, R.; Cecchetti, G.; Bernasconi, M.P.; Cardamone, R.; Barbieri, A.; Pinto, P.; Passerini, G.; Scomazzoni, F.; Comi, G.; Magnani, G. Cerebrospinal fluid amyloid-β42, total tau and phosphorylated tau are low in patients with normal pressure hydrocephalus: Analogies and differences with Alzheimer’s disease. J. Alzheimer’s Dis. 2017, 60, 183–200. [Google Scholar] [CrossRef] [PubMed]
- Abu Hamdeh, S.; Virhammar, J.; Sehlin, D.; Alafuzoff, I.; Cesarini, K.G.; Marklund, N. Brain Tissue Aβ42 Levels are linked to shunt response in idiopathic normal pressure hydrocephalus. J. Neurosurg. 2018, 130, 121–129. [Google Scholar] [CrossRef] [PubMed]
- Azuma, S.; Kazui, H.; Kanemoto, H.; Suzuki, Y.; Sato, S.; Suehiro, T.; Matsumoto, T.; Yoshiyama, K.; Kishima, H.; Shimosegawa, E.; et al. Cerebral blood flow and Alzheimer’s disease-related biomarkers in cerebrospinal fluid in idiopathic normal pressure hydrocephalus. Psychogeriatrics 2019, 19, 527–538. [Google Scholar] [CrossRef] [PubMed]
- Hong, Y.J.; Kim, M.-J.; Jeong, E.; Kim, J.-E.; Hwang, J.; Lee, J.-I.; Lee, J.-H.; Na, D.L. Preoperative biomarkers in patients with idiopathic normal pressure hydrocephalus showing a favorable shunt surgery outcome. J. Neurol. Sci. 2018, 387, 21–26. [Google Scholar] [CrossRef] [PubMed]
- Jang, H.; Park, S.B.; Kim, Y.; Kim, K.W.; Lee, J.I.; Kim, S.T.; Lee, K.H.; Kang, E.-S.; Choe, Y.S.; Seo, S.W.; et al. Prognostic Value of Amyloid PET Scan in Normal Pressure Hydrocephalus. J Neurol. 2018, 265, 63–73. [Google Scholar] [CrossRef]
- Müller-Schmitz, K.; Krasavina-Loka, N.; Yardimci, T.; Lipka, T.; Kolman, A.G.J.; Robbers, S.; Menge, T.; Kujovic, M.; Seitz, R.J. Normal Pressure Hydrocephalus Associated with Alzheimer’s Disease. Ann. Neurol. 2020, 88, 703–711. [Google Scholar] [CrossRef]
- Portelius, E.; Westman-Brinkmalm, A.; Zetterberg, H.; Blennow, K. Determination of Beta-Amyloid Peptide Signatures in Cerebrospinal Fluid Using Immunoprecipitation-Mass Spectrometry. J. Proteome Res. 2006, 5, 1010–1016. [Google Scholar] [CrossRef]
- Hansson, O.; Lehmann, S.; Otto, M.; Zetterberg, H.; Lewczuk, P. Advantages and Disadvantages of the Use of the CSF Amyloid β (Aβ) 42/40 Ratio in the Diagnosis of Alzheimer’s Disease. Alzheimer’s Res. Ther. 2019, 11, 34. [Google Scholar] [CrossRef] [PubMed]
- Blennow, K.; Hampel, H.; Weiner, M.; Zetterberg, H. Cerebrospinal Fluid and Plasma Biomarkers in Alzheimer Disease. Nat. Rev. Neurol. 2010, 6, 131–144. [Google Scholar] [CrossRef] [PubMed]
- Jeppsson, A.; Zetterberg, H.; Blennow, K.; Wikkelsø, C. Idiopathic Normal-Pressure Hydrocephalus: Pathophysiology and Diagnosis by CSF Biomarkers. Neurology 2013, 80, 1385–1392. [Google Scholar] [CrossRef] [PubMed]
- McKhann, G.M.; Knopman, D.S.; Chertkow, H.; Hyman, B.T.; Jack, C.R.; Kawas, C.H.; Klunk, W.E.; Koroshetz, W.J.; Manly, J.J.; Mayeux, R.; et al. The Diagnosis of Dementia Due to Alzheimer’s Disease: Recommendations from the National Institute on Aging-Alzheimer’s Association Workgroups on Diagnostic Guidelines for Alzheimer’s Disease-Alzheimer’s & Dementia: The Journal of the Alzheimer’s Associa. Available online: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3312027/ (accessed on 1 May 2019).
- de Oliveira, M.O.; Nitrini, R.; Yassuda, M.S.; Brucki, S.M.D. Vocabulary Is an Appropriate Measure of Premorbid Intelligence in a Sample with Heterogeneous Educational Level in Brazil. Available online: https://www.hindawi.com/journals/bn/2014/875960/ (accessed on 29 May 2018).
- Yamada, S.; Ishikawa, M.; Miyajima, M.; Atsuchi, M.; Kimura, T.; Kazui, H.; Mori, E.; SINPHONI-2 Investigators (Appendix). Disease Duration: The Key to Accurate CSF Tap Test in INPH. Acta. Neurol. Scand. 2017, 135, 189–196. [Google Scholar] [CrossRef]
- Guralnik, J.M.; Simonsick, E.M.; Ferrucci, L.; Glynn, R.J.; Berkman, L.F.; Blazer, D.G.; Scherr, P.A.; Wallace, R.B. A Short Physical Performance Battery Assessing Lower Extremity Function: Association With Self-Reported Disability and Prediction of Mortality and Nursing Home Admission. J. Gerontol. 1994, 49, M85–M94. [Google Scholar] [CrossRef]
- Magni, E.; Binetti, G.; Bianchetti, A.; Rozzini, R.; Trabucchi, M. Mini-Mental State Examination: A Normative Study in Italian Elderly Population. Eur. J. Neurol. 1996, 3, 198–202. [Google Scholar] [CrossRef] [PubMed]
- Appollonio, I.; Leone, M.; Isella, V.; Piamarta, F.; Consoli, T.; Villa, M.L.; Forapani, E.; Russo, A.; Nichelli, P. The Frontal Assessment Battery (FAB): Normative Values in an Italian Population Sample. Neurol. Sci. 2005, 26, 108–116. [Google Scholar] [CrossRef]
- Giovagnoli, A.R.; Del Pesce, M.; Mascheroni, S.; Simoncelli, M.; Laiacona, M.; Capitani, E. Trail Making Test: Normative Values from 287 Normal Adult Controls. Ital. J. Neurol. Sci. 1996, 17, 305–309. [Google Scholar] [CrossRef]
- Alcolea, D.; Pegueroles, J.; Muñoz, L.; Camacho, V.; López-Mora, D.; Fernández-León, A.; Bastard, N.L.; Huyck, E.; Nadal, A.; Olmedo, V.; et al. Agreement of Amyloid PET and CSF Biomarkers for Alzheimer’s Disease on Lumipulse. Ann. Clin. Transl. Neurol. 2019, 6, 1815–1824. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Jack, C.R.; Bennett, D.A.; Blennow, K.; Carrillo, M.C.; Dunn, B.; Haeberlein, S.B.; Holtzman, D.M.; Jagust, W.; Jessen, F.; Karlawish, J.; et al. NIA-AA Research Framework: Toward a Biological Definition of Alzheimer’s Disease. Alzheimer’s Dement. 2018, 14, 535–562. [Google Scholar] [CrossRef] [PubMed]
- Manniche, C.; Hejl, A.-M.; Hasselbalch, S.G.; Simonsen, A.H. Cerebrospinal Fluid Biomarkers in Idiopathic Normal Pressure Hydrocephalus versus Alzheimer’s Disease and Subcortical Ischemic Vascular Disease: A Systematic Review. J. Alzheimer’s Dis. 2019, 68, 267–279. [Google Scholar] [CrossRef] [PubMed]
- Taghdiri, F.; Gumus, M.; Algarni, M.; Fasano, A.; Tang-Wai, D.; Tartaglia, M.C. Association Between Cerebrospinal Fluid Biomarkers and Age-Related Brain Changes in Patients with Normal Pressure Hydrocephalus. Sci. Rep. 2020, 10, 9106. [Google Scholar] [CrossRef] [PubMed]
- Tsai, A.; Malek-Ahmadi, M.; Kahlon, V.; Sabbagh, M.N. Differences in Cerebrospinal Fluid Biomarkers between Clinically Diagnosed Idiopathic Normal Pressure Hydrocephalus and Alzheimer’s Disease. J. Alzheimer’s Dis. Parkinsonism 2014, 4, 1000150. [Google Scholar] [CrossRef] [Green Version]
- Abu-Rumeileh, S.; Giannini, G.; Polischi, B.; Albini-Riccioli, L.; Milletti, D.; Oppi, F.; Stanzani-Maserati, M.; Capellari, S.; Mantovani, P.; Palandri, G.; et al. Revisiting the Cerebrospinal Fluid Biomarker Profile in Idiopathic Normal Pressure Hydrocephalus: The Bologna Pro-Hydro Study. J. Alzheimer’s Dis. 2019, 68, 723–733. [Google Scholar] [CrossRef]
- Kapaki, E.N.; Paraskevas, G.P.; Tzerakis, N.G.; Sfagos, C.; Seretis, A.; Kararizou, E.; Vassilopoulos, D. Cerebrospinal Fluid Tau, Phospho-Tau181 and Beta-Amyloid1-42 in Idiopathic Normal Pressure Hydrocephalus: A Discrimination from Alzheimer’s Disease. Eur. J. Neurol. 2007, 14, 168–173. [Google Scholar] [CrossRef] [PubMed]
- Blennow, K. Cerebrospinal Fluid Protein Biomarkers for Alzheimer’s Disease. NeuroRX 2004, 1, 213–225. [Google Scholar] [CrossRef] [PubMed]
- Lewczuk, P.; Ermann, N.; Andreasson, U.; Schultheis, C.; Podhorna, J.; Spitzer, P.; Maler, J.M.; Kornhuber, J.; Blennow, K.; Zetterberg, H. Plasma Neurofilament Light as a Potential Biomarker of Neurodegeneration in Alzheimer’s Disease. Alzheimer’s Res. Ther. 2018, 10, 71. [Google Scholar] [CrossRef]
- Ray, B.; Reyes, P.F.; Lahiri, D.K. Biochemical Studies in Normal Pressure Hydrocephalus (NPH) Patients: Change in CSF Levels of Amyloid Precursor Protein (APP), Amyloid-Beta (Aβ) Peptide and Phospho-Tau. J. Psychiatr. Res. 2011, 45, 539–547. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Baird, G.; Montine, T.J.; Chang, J.J.; Hu, S.-C.; Avellino, A.M. Cerebrospinal Fluid Total Tau Is Increased in Normal Pressure Hydrocephalus Patients Who Undergo Successful Lumbar Drain Trials. Cureus 2017, 9, e1265. [Google Scholar] [CrossRef] [Green Version]
- Migliorati, K.; Panciani, P.P.; Pertichetti, M.; Borroni, B.; Archetti, S.; Rozzini, L.; Padovani, A.; Terzi, L.; Bruscella, S.; Fontanella, M.M. P-Tau as Prognostic Marker in Long Term Follow up for Patients with Shunted INPH. Neurol. Res. 2021, 43, 78–85. [Google Scholar] [CrossRef]
- Pyykkö, O.T.; Lumela, M.; Rummukainen, J.; Nerg, O.; Seppälä, T.T.; Herukka, S.-K.; Koivisto, A.M.; Alafuzoff, I.; Puli, L.; Savolainen, S.; et al. Cerebrospinal Fluid Biomarker and Brain Biopsy Findings in Idiopathic Normal Pressure Hydrocephalus. PLoS ONE 2014, 9, e91974. [Google Scholar] [CrossRef] [PubMed]
- Giacomucci, G.; Mazzeo, S.; Bagnoli, S.; Casini, M.; Padiglioni, S.; Polito, C.; Berti, V.; Balestrini, J.; Ferrari, C.; Lombardi, G.; et al. Matching Clinical Diagnosis and Amyloid Biomarkers in Alzheimer’s Disease and Frontotemporal Dementia. J. Pers. Med. 2021, 11, 47. [Google Scholar] [CrossRef]
- Lehmann, S.; Delaby, C.; Boursier, G.; Catteau, C.; Ginestet, N.; Tiers, L.; Maceski, A.; Navucet, S.; Paquet, C.; Dumurgier, J.; et al. Relevance of Aβ42/40 Ratio for Detection of Alzheimer Disease Pathology in Clinical Routine: The PLMR Scale. Front. Aging Neurosci. 2018, 10, 138. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Figure 1.
Correlation matrix. Values quoted in the correlation matrix are Pearson’s r correlation coefficients. Statistical significance received a Bonferroni adjustment and was accepted at p < 0.01 (significant correlations were reported as underlined characters). Color maps represent Pearson’s r correlation coefficients. * p < 0.05, ** p < 0.01.
Figure 1.
Correlation matrix. Values quoted in the correlation matrix are Pearson’s r correlation coefficients. Statistical significance received a Bonferroni adjustment and was accepted at p < 0.01 (significant correlations were reported as underlined characters). Color maps represent Pearson’s r correlation coefficients. * p < 0.05, ** p < 0.01.
Figure 2.
Comparison of the CSF biomarker concentrations and Aβ42/Aβ40 ratio between iNPH and AD. Values quoted on the y-axis indicate the CSF concentration (expressed as pg/mL) for Aβ42; p-tau, t-tau, and the value of the ratio for the Aβ42/Aβ40. p-values and Cohen’s d are reported. Statistical significance received a Bonferroni adjustment and was accepted at p < 0.003.
Figure 2.
Comparison of the CSF biomarker concentrations and Aβ42/Aβ40 ratio between iNPH and AD. Values quoted on the y-axis indicate the CSF concentration (expressed as pg/mL) for Aβ42; p-tau, t-tau, and the value of the ratio for the Aβ42/Aβ40. p-values and Cohen’s d are reported. Statistical significance received a Bonferroni adjustment and was accepted at p < 0.003.
Figure 3.
Relative frequencies of positive Aβ42, Aβ42/Aβ40, p-tau, and t-tau in iNPH and AD. Statistical significance received a Bonferroni adjustment and was accepted at p < 0.003. *** p < 0.001.
Figure 3.
Relative frequencies of positive Aβ42, Aβ42/Aβ40, p-tau, and t-tau in iNPH and AD. Statistical significance received a Bonferroni adjustment and was accepted at p < 0.003. *** p < 0.001.
Figure 4.
ROC curves for the accuracy of Aβ42, Aβ42/Aβ40, p-tau, and t-tau in distinguishing iNPH and AD. Colored shapes indicate 95% C.I.
Figure 4.
ROC curves for the accuracy of Aβ42, Aβ42/Aβ40, p-tau, and t-tau in distinguishing iNPH and AD. Colored shapes indicate 95% C.I.
Figure 5.
Comparison of CSF biomarker concentrations and Aβ42/Aβ40 ratio between iNPH/Aβ42+ and AD/Aβ42+. The values quoted on the y-axis indicate the CSF concentration (expressed as pg/mL) for Aβ42, p-tau, and t-tau.
Figure 5.
Comparison of CSF biomarker concentrations and Aβ42/Aβ40 ratio between iNPH/Aβ42+ and AD/Aβ42+. The values quoted on the y-axis indicate the CSF concentration (expressed as pg/mL) for Aβ42, p-tau, and t-tau.
Table 1.
Comparison of demographic variables and CSF biomarker values between iNPH and AD patients.
| iNPH | AD | |
|---|---|---|
| N | 44 | 101 |
| Age, mean (SD) | 73.92 (7.42) | 71.28 (6.83) |
| Sex (women/men) | 26/18 | 50/51 |
| Years of education, mean (SD) | 9.71 (3.94) | 9.98 (4.21) |
| APOE ε4+, % (95 CI %) | 24.14 (8.56:39.71) | 49.45 (39.18:59.72) |
| MMSE, mean (SD) | 24.25 (4.02) a | 19.57 (4.85) a |
| Aβ42 (pg/mL), mean (SD) | 624.89 (316.30) | 563.49 (236.94) |
| Aβ42/Aβ40, mean (SD) | 0.09 (0.02) b | 0.04 (0.02) b |
| p-tau (pg/mL), mean (SD) | 32.13 (17.85) c | 125.52 (63.09) c |
| t-tau (pg/mL), mean (SD) | 242.66 (205.57) d | 768.79 (374.22) d |
| Aβ42+, % (95% C.I.) | 70.45 (56.97:83.94) | 78.22 (70.17:86.27) |
| Aβ42/Aβ40+, % (95% C.I.) | 13.64 (3.50:23.78) e | 93.07 (88.12:98.02) e |
| T+, % (95% C.I.) | 6.82 (0:14.27) f | 88.12 (81.81:94.43) f |
| N+, % (95% C.I.) | 11.36 (1.99:20.74) g | 84.16 (77.04:91.28) g |
Values quoted in the table are mean (±SD) or n (%). Statistical significance received a Bonferroni adjustment and was accepted at p < 0.003). a p < 0.001, d = 1.05; b p < 0.001, d = 2.21; c p < 0.001, d = 2.01; d p < 0.001, d = 1.74; e χ2 = 90.35, p < 0.001, V = 0.79; f χ2 = 87.35, p < 0.001, V = 0.78; g χ2 = 68.98, p < 0.001, V = 0.69.
Table 2.
CSF biomarker accuracy.
| Cut-Off | AUC | Accuracy, % (CI.95%) | Sensitivity, % (CI.95%) | Specificity, % (CI.95%) | |
|---|---|---|---|---|---|
| Aβ42 | 776.34 | 0.567 | 64.14 (56.33:71.95) | 84.16 (78.22:90.10) | 18.18 (11.90:24.46) |
| Aβ42/Aβ40 | 0.068 | 0.943 | 86.21 (80.60:91.82) | 87.13 (81.68:92.58) | 84.09 (78.14:90.04) |
| p-tau | 65.24 | 0.969 | 88.28 (83.04:93.52) | 95.45 (92.06:98.84) | 85.15 (79.36:90.94) |
| t-tau | 509.09 | 0.941 | 80.69 (74.27:87.11) | 93.18 (89.08:97.28) | 75.25 (68.23:82.27) |
Cut-off values were estimated by Youden’s method. Area under the curve (AUC), accuracy, sensitivity, and specificity for each biomarker are reported. Accuracy, sensitivity, and specificity are expressed as percentages (95% C.I.).
Table 3.
Multivariate logistic regression models.
| B | S.E. | p | OR | 95% C.I. | ||
|---|---|---|---|---|---|---|
| Lower | Upper | |||||
| CSF biomarkers (quantitative values) | ||||||
| Age | −0.18 | 0.08 | 0.024 | 0.83 | 0.71 | 0.98 |
| Aβ42 | 0.01 | 0.00 | 0.081 | 1.00 | 0.99 | 1.01 |
| Aβ42/Aβ40 | −128.38 | 47.83 | 0.007 | 2.013 × 10−31 | 3.44 × 10−97 | 9.03 × 10−8 |
| p-tau | 0.04 | 0.03 | 0.193 | 1.04 | 0.98 | 1.09 |
| t-tau | 0.00 | 0.00 | 0.347 | 1.07 | .99 | 1.01 |
| χ2 = 137.19, p < 0.001, Nagelkerke R2 = 86.53% | ||||||
| CSF biomarkers (dichotomized values) | ||||||
| Age | −0.15 | 0.06 | 0.013 | 0.86 | 0.76 | 0.97 |
| A (Aβ42+) | −2.06 | 1.21 | 0.092 | 0.13 | 0.01 | 1.35 |
| A (Aβ42/Aβ40+) | 4.37 | 1.06 | <0.001 | 79.20 | 9.89 | 643.36 |
| T+ | 5.05 | 1.58 | 0.001 | 155.78 | 7.09 | 3420.53 |
| N+ | −1.28 | 1.46 | 0.381 | 0.278 | 0.02 | 4.86 |
| χ2 = 128.67, p < 0.001, Nagelkerke R2 = 83.21% | ||||||
Regression Coefficients (B), Standard errors (S.E), p-value (p), Odds Ratio (OR), and 95% Confidence Intervals (95% C.I.) for covariates included in the logistic regression models are reported. Statistical significance received a Bonferroni adjustment and being accepted at the p < 0.01, highlighted in bold.
Table 4.
Comparison of demographic variables and CSF biomarker values between iNPH/Aβ42+ and AD/Aβ42+ patients.
Table 4.
Comparison of demographic variables and CSF biomarker values between iNPH/Aβ42+ and AD/Aβ42+ patients.
| iNPH/Aβ42+ | AD/Aβ42+ | |
|---|---|---|
| N | 31 | 79 |
| Age, mean (SD) | 73.08 (8.24) | 70.95 (6.97) |
| Sex (women/men) | 19/12 | 37/42 |
| Years of education, mean (SD) | 9.73 (3.77) | 10.21 (4.39) |
| APOE ε4+, % (95 CI %) | 23.81 (5.59:42.03) | 50.00 (38.45:61.55) |
| MMSE, mean (SD) | 24.68 (4.02) a | 19.53 (3.42) a |
| Aβ42 (pg/mL), mean (SD) | 482.48 (110.44) | 462.76 (116.18) |
| Aβ42/Aβ40, mean (SD) | 0.08 (0.12) b | 0.04 (0.01) b |
| p-tau (pg/mL), mean (SD) | 30.44 (19.10) c | 120.02 (60.25) c |
| t-tau (pg/mL), mean (SD) | 244.74 (238.07) d | 724.65 (338.935) d |
| Aβ42/Aβ40+, % (95% C.I.) | 13.64 (3.50:23.78) e | 93.07 (88.12:98.02) e |
| T+, % (95% C.I.) | 6.82 (0:14.27) f | 88.12 (81.81:94.43) f |
| N+, % (95% C.I.) | 11.36 (1.99:20.74) g | 84.16 (77.04:91.28) g |
Values quoted in the table are mean (±SD) or n (%). Statistical significance received a Bonferroni adjustment and was accepted at p < 0.003). a p < 0.001, d = 1.50; b p < 0.001, d = 2.72; c p < 0.001, d = 2.00; d p < 0.001, d = 1.64; e χ2 = 69.29, p < 0.001, V = 0.79; f χ2 = 63.66, p < 0.001, V = 0.76; g χ2 = 48.01, p < 0.001, V = 0.66.
Table 5.
Comparison of demographic variables and CSF biomarkers values between iNPH Aβ42/Aβ40− and iNPH Aβ42/Aβ40+ groups.
Table 5.
Comparison of demographic variables and CSF biomarkers values between iNPH Aβ42/Aβ40− and iNPH Aβ42/Aβ40+ groups.
| iNPH Aβ42/Aβ40− | iNPH Aβ42/Aβ40+ | |
|---|---|---|
| N (%) | 38 (86.36%) | 6 (13.64%) |
| Age, mean (SD) | 73.36 (7.21) | 77.61 (8.61) |
| Sex (women/men) | 24/14 | 2/4 |
| Years of education, mean (SD) | 9.54 (3.94) | 10.60 (4.28) |
| APOE ε4+, % (95 CI %) | 20.00 (4.32:35.68) | 50.00 (1.00:99.00) |
| MMSE, mean (SD) | 24.52 (4.14) | 22.80 (3.35) |
| Aβ42 (pg/mL), mean (SD) | 644.66 (335.17) | 499.67 (85.63) |
| p-tau (pg/mL), mean (SD) | 27.47 (11.82) a | 59.46 (23.74) a |
| t-tau (pg/mL), mean (SD) | 222.29 (201.57) | 371.67 (199.11) |
| A (Aβ42+), % (95% C.I.) | 65.79 (50.71:80.87) | 100 |
| T+, % (95% C.I.) | 2.63 (0:7.71) b | 33.33 (0:71.05) b |
| N+, % (95% C.I.) | 5.26 (0:12.36) c | 50.00 (9.99:90.01) c |
| Cognitive impairment, % (95% C.I.) | 71.05 (56.63:85.47) | 100 |
| Urinary incontinence, % (95% C.I.) | 76.32 (62.80:89.83) d | 33.33 (4.39:71.05) d |
| Response to CSF tap test, % (95% C.I.) | 28.95 (14.53:43.37) | 33.33 (0:71.05) |
Values quoted in the table are mean (±SD) or n (%). Statistical significance received a Bonferroni adjustment and being accepted at the p < 0.004). a p < 0.001, d = 1.87; b χ2 = 7.68, p = 0.006, V = 0.41; c χ2 = 10.29, p = 0.001, V = 0.48; d χ2 = 4.56, p = 0.032, V = 0.323.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
MDPI and ACS Style
Mazzeo, S.; Emiliani, F.; Bagnoli, S.; Padiglioni, S.; Del Re, L.M.; Giacomucci, G.; Balestrini, J.; Ingannato, A.; Moschini, V.; Morinelli, C.; et al. Alzheimer’s Disease CSF Biomarker Profiles in Idiopathic Normal Pressure Hydrocephalus. J. Pers. Med. 2022, 12, 935. https://doi.org/10.3390/jpm12060935
AMA Style
Mazzeo S, Emiliani F, Bagnoli S, Padiglioni S, Del Re LM, Giacomucci G, Balestrini J, Ingannato A, Moschini V, Morinelli C, et al. Alzheimer’s Disease CSF Biomarker Profiles in Idiopathic Normal Pressure Hydrocephalus. Journal of Personalized Medicine. 2022; 12(6):935. https://doi.org/10.3390/jpm12060935
Chicago/Turabian StyleMazzeo, Salvatore, Filippo Emiliani, Silvia Bagnoli, Sonia Padiglioni, Lorenzo Maria Del Re, Giulia Giacomucci, Juri Balestrini, Assunta Ingannato, Valentina Moschini, Carmen Morinelli, and et al. 2022. "Alzheimer’s Disease CSF Biomarker Profiles in Idiopathic Normal Pressure Hydrocephalus" Journal of Personalized Medicine 12, no. 6: 935. https://doi.org/10.3390/jpm12060935
Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.
