Longitudinal Stability of Cerebrospinal Fluid Biomarker ... - IOS Press

Journal of Alzheimer’s Disease 33 (2013) 807–822 DOI 10.3233/JAD-2012-110029 IOS Press

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Longitudinal Stability of Cerebrospinal Fluid Biomarker Levels: Fulfilled Requirement for Pharmacodynamic Markers in Alzheimer’s Disease Nathalie Le Bastarda,∗ , Laetitia Aertsb,2 , Kristel Sleegersc,d , Jean-Jacques Martinb , Christine Van Broeckhovenc , Peter Paul De Deyna,b,e,f,1 and Sebastiaan Engelborghsa,e,1 a Laboratory

of Neurochemistry and Behavior, Reference Center for Biological Markers of Dementia (BIODEM), Antwerp, Belgium b Biobank, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium c Neurodegenerative Brain Disease Group, Department of Molecular Genetics, VIB, Antwerp, Belgium d Laboratory of Neurogenetics, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium e Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium f Department of Neurology and Alzheimer Research Center, University Medical Center Groningen (UMCG), Groningen, The Netherlands Handling Associate Editor: Piotr Lewczuk

Accepted 3 September 2012

Abstract. The current treatment for Alzheimer’s disease (AD) is purely symptomatic, but medications interfering with underlying pathophysiological processes are being developed. To evaluate a possible disease-modifying effect, cerebrospinal fluid (CSF) biomarkers with a direct link to the underlying pathophysiology, such as amyloid-␤1-42 (A␤1-42 ), total tau protein (T-tau), and hyperphosphorylated tau (P-tau181P ), may play an important role. If intra-individual fluctuations in biomarker levels are small, the difference between two samples could serve as a pharmacodynamic measure. The aim of this study was to evaluate the longitudinal stability of CSF A␤1-42 , T-tau, and P-tau181P levels in AD patients and control subjects. Serial CSF samples of 28 AD patients and 23 controls with a minimum time interval of 30 days were included in this study. Serial CSF samples from 10 progressive patients (7 mild cognitive impairment (MCI) patients and 3 controls progressing to MCI or AD) were

1 Joint

last authors.

2 Current affiliation: Facult´ e de Médecine, Centre de Recherche en

Infectiologie du Centre Hospitalier de l’Université Laval, Université Laval, Québec, Canada. ∗ Correspondence to: Dr. Nathalie Le Bastard, Laboratory of Neurochemistry and Behavior, Reference Center for Biological Markers of Dementia (BIODEM), Institute Born-Bunge, University of Antwerp, Universiteitsplein 1, BE-2610 Antwerp, Belgium. Tel.: +32 3 265 26 31; Fax: +32 3 265 26 18; E-mail: [email protected].

ISSN 1387-2877/13/$27.50 © 2013 – IOS Press and the authors. All rights reserved

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N.L. Bastard et al. / Longitudinal Stability of CSF Biomarker Levels

also analyzed. Intra-individual CSF A␤1-42 and P-tau181P levels were stable in AD and controls. Intra-individual CSF T-tau levels differed significantly in AD patients, but not in controls. Change in biomarker concentrations per time unit was also significant between groups, but not within groups. The difference in biomarker levels in samples from progressive patients was not significant. In conclusion, CSF levels of A␤1-42 , T-tau, and P-tau181P are relatively stable over time. Only T-tau increased in AD patients in comparison to controls, which does not preclude its use as a diagnostic marker, nor as a potential pharmacodynamic marker. Keywords: Alzheimer’s disease, biomarkers, cerebrospinal fluid, intra-individual variation, longitudinal sampling

INTRODUCTION An early and accurate clinical diagnosis of Alzheimer’s disease (AD) is of great importance to allow early treatment. The current pharmacological treatment for AD is symptomatic, but drugs interfering with the underlying pathophysiological processes, meanwhile exerting a beneficial effect on the clinical course of the disease, are being developed [1]. Efforts are being made to translate the knowledge of molecular pathways into therapeutic strategies. Presently, these so-called disease-modifying therapies are predominantly based on interference with processes that lead to the amyloid and/or tau pathology that is characteristic for AD. To evaluate a possible disease-modifying effect, markers with a direct link to the underlying pathophysiological process will have to be used. Candidate proteins for serving as efficacy markers for these disease-modifying therapies include amyloid-␤1-42 protein (A␤1-42 ), total tau protein (T-tau), and hyperphosphorylated tau (P-tau181P ) levels in cerebrospinal fluid (CSF). The diagnostic and predictive value of a combination of A␤1-42 , T-tau, and P-tau181P in CSF for AD has already been established, since decreased A␤1-42 and increased T-tau and P-tau181P levels are present in AD patients as opposed to healthy elderly, patients with other neurological/psychiatric conditions and non-AD dementias [2–5], and in patients with mild cognitive impairment (MCI) who convert to AD as opposed to MCI patients who do not convert [6–8]. Therefore, CSF A␤1-42 , T-tau, and P-tau181P were recommended for use as diagnostic markers for AD [9] and were included in the recently updated NINCDSADRDA criteria to support the clinical diagnosis of AD [10]. A requirement for their application as pharmacodynamic markers for disease-modifying therapies is that the levels of A␤1-42 , T-tau, and P-tau181P in CSF are stable in time. Indeed, if intra-individual fluctuations are small, the change in biomarker levels could serve as a pharmacodynamic measure. Also, the intraindividual difference is expected to be smaller than the

between-group difference of AD and elderly controls, given the diagnostic value of these markers for AD diagnosis. Previous studies investigating the stability of CSF biomarkers generated conflicting results. A summary of the literature on longitudinal stability of CSF biomarker levels in AD and controls is presented in Table 1. In AD, longitudinal CSF A␤1-42 levels have been shown to remain stable in several studies with varying sampling intervals [11–15], but have also been found to increase [16] and decrease [17] in long-term studies. In controls, most studies agreed on stable CSF A␤1-42 [11, 15, 18–21], except for one study that reported increasing CSF A␤1-42 levels with time, although this study included patients with subjective complaints instead of healthy elderly [17]. Longitudinal CSF T-tau levels have been reported to increase [14, 15, 17, 22] or to remain unaltered both in short-term [12, 13, 23, 24] and long-term studies [15, 16, 24, 25] in AD patients. These observations have also been made in controls [15, 18, 21]. Unchanged and increasing T-tau levels have been found in depression/dysthymia patients [23] and patients with subjective complaints [17], respectively. For CSF P-tau181P , all studies performed in AD patients agreed upon unchanged levels on short [12, 13] as well as long-term [17]. Furthermore, no longitudinal changes in P-tau181P have been observed in either controls [18–21] or patients with subjective complaints [17]. Comparing studies that reported normalized (annual or monthly) changes in biomarker concentrations with studies reporting changes in raw biomarker concentrations, some differences are observed: an increase in A␤1-42 or increase in T-tau in AD patients has not yet been observed, while a decrease in A␤1-42 in controls has [26–29]. For P-tau181P , decreasing and increasing levels have been reported in AD and controls, respectively [26, 29]. The aim of the present study was to evaluate the longitudinal stability of CSF A␤1-42 , T-tau, and P-tau181P levels in AD patients and control subjects.

Table 1 Summary of the literature on longitudinal stability of CSF biomarker concentrations in AD and controls, including the effect of APOE genotype on longitudinal stability Reference

Diagnostic groups

Time interval

Assay

Longitudinal stability A␤1-42

T-tau

P-tau

Effect APOE genotype

AD (n = 18), MCI (n = 9), NON-AD (n = 9)

Mean total group: 15 months; range total group: 1–32 months (mean AD: 14 months)

INNOTEST hTau

ND

↑AD = MCI ↓NON-AD

ND

Andreasen et al., 1998 [25] Kanai et al., 1998 [14]

AD (n = 43), MXD (n = 11), VAD (n = 21) AD (n = 32)

Mean total group: 1 year

INNOTEST hTau

ND

=

ND

Mean: 18.6 months; range: 2–43 months

=

↑

ND

Andreasen et al., 1999 [11]

AD (n = 53): EOAD (n = 17), LOAD (n = 36); controls (n = 21) Probable AD (n = 159), possible AD (n = 33), depression/dysthymia (n = 28)

Mean ± SD total group: 10.1 ± 5.7 months

In-house ELISA A␤1-42 [61] INNOTEST hTau INNOTEST ␤-AMYLOID(1-42)

Higher frequency of APOE ␧4 carriers in AD with increasing T-tau No genotype effects ND

=

ND

ND

ND

INNOTEST hTau

ND

=

ND

ND

INNOTEST ␤-AMYLOID(1-42) INNOTEST hTau In-house ELISA A␤1-42 [61] INNOTEST hTau

=

=

ND

ND

=

↑ APOE␧4+ = APOE␧4–

ND

In-house ELISA T-tau [63]

ND

=

ND

Significant increase in T-tau in APOE ␧4 carriers No genotype effects

INNOTEST ␤-AMYLOID(1-42) INNOTEST hTau

↓

=

ND


MCI-AD (n = 16)

Mean ± SD probable AD: 10.0 ± 6.1 months; mean ± SD possible AD: 8.9 ± 3.9 month; range depression/dysthymia: 6–9 months Range: 6–27 months

Kanai et al., 1999 [44]

AD (n = 33)

Mean: 20 months

Sunderland et al., 1999 [24]

AD (n = 29; long-term interval), AD (n = 5; short-term interval) AD (n = 17; 5 definite)

Long-term mean: 2 years; short-term max.: 12 weeks Mean: 3 years; range: 36–48 months


Tapiola et al., 2000 [16]


Blomberg et al., 1996 [22]

No genotype effects

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Table 1 (continued) Reference de Leon et al., 2002 [19]

Diagnostic groups

Time interval


T-tau

P-tau


In-house ELISA P-tau231P [64]

=

ND

↑ MCI* = Controls

ND

Median DLB: 55 days; range DLB: 8–357 days; median AD: 48 days; range AD: 3–263 days

INNOTEST ␤-AMYLOID(1-42) INNOTEST hTau INNOTEST PHOSPHOTAU(181P) INNOTEST hTau INNOTEST PHOSPHOTAU(181P) In-house ELISA A␤1-42 [65] In-house ELISA P-tau231P [64] A␤1-42 : IGEN International Inc. INNOTEST hTau

=

=

=

ND

↓

ND (see [43])

ND (see [43])

ND

=

ND

=

ND

↓ APOE ␧4+ = APOE ␧4–

=

ND

=

=

=

Significant decrease in A␤1-42 in APOE ε4 carriers ND

↑

↑

=

ND

=

=

=

ND

Mollenhauer et al., 2005 [12]

Bouwman et al., 2006 [60]

Neurological patients (n = 114)

Mean ± SD: 21 ± 9 months

de Leon et al., 2006 [20]

MCI (n = 7; including 1 MCI-AD), controls (n = 9)

Range total group: 22–26 months

Heuy et al., 2006 [59]

AD (n = 20; 5 definite)

Mean: 3.8 years; range: 1–11.1 years

Blennow et al., 2007 [13]

AD (n = 53)

Mean: 6 months

Bouwman et al., 2007 [17]

AD (n = 50); MCI (n = 38): non-converters (n = 13), converters (n = 25) [MCI-AD n = 21]; subjective complaints (n = 17) MCI (n = 83): non-converters (n = 68), converters (n = 15) [MCI-AD n = 12]; cognitively healthy individuals (n = 17)

Mean total group: 21 ± 9 months (at least 1 year between first and second LP)

Mean total group: 2 years

INNOTEST ␤-AMYLOID(1-42) INNOTEST T-tau INNOTEST PHOSPHOTAU(181P) INNOTEST ␤-AMYLOID(1-42) INNOTEST hTau INNOTEST PHOSPHOTAU(181P) INNO-BIA AlzBio3


Range total group: 10–14 months

MCI (n = 7), very mild AD (n = 1), controls (n = 10) DLB (n = 21), AD (n = 19; 2 definite)

Zetterberg et al., 2007 [18]

Assay

Table 1 (continued) Diagnostic groups

Time interval

Assay

Verwey et al., 2008 [43]

Neurological patients (n = 112): AD (n = 52), MCI (n = 39), subjective complaints (n = 16), other neurological disorders (n = 5) MCI-AD (n = 22), MCI-MCI (n = 43), controls (n = 21)

Mean ± SD total group: 19 ± 8 months

INNOTEST hTau INNOTEST PHOSPHOTAU(181P)

Mean ± SD MCI-AD: 2.1 ± 0.5 year; mean ± SD MCI-MCI: 2.0 ± 0.7 year; mean ± SD controls: 2.1 ± 0.7 year Mean cohort 1 : 1 year; range cohort 1 : 6–18 months; mean cohort 2 : 2 years; range cohort 2 : 18–30 months; mean controls: 4 years; range controls: 3.7–4.2 years

In-house ELISA A␤1-42 [65] INNOTEST hTau in-house ELISA P-tau231P [64] INNOTEST ␤-AMYLOID (1-42) INNOTEST htau INNOTEST PHOSPHOTAU (181P) (INNOBIA results for controls were converted to ELISA concentrations based on conversion factors from ref [66]) INNO-BIA AlzBio3

Brys et al., 2009 [27]◦

Buchhave et al., 2009 [15]

2 AD cohorts: AD cohort 1 (n = 100), AD cohort 2 (n = 45); cognitively healthy individuals (n = 34)

Stomrud et al., 2010 [21]

Cognitive healthy elderly (n = 37)

Range: 4–4.5 years

Longitudinal stability A␤1-42 ND (see [60])


T-tau

P-tau

↑ (assessed in the same assay)

=

ND

A␤1-42 /A␤1-40 ratio =

=

=

No genotype effects

=

↑ AD cohort 2 = AD cohort 1 and Controls cohort 1 and 2

ND

ND

=

=

=

APOE ␧4 carriers: greater longitudinal decrease in CSF A␤1-42 and higher T-tau at follow-up


Reference

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Table 1 (continued)

Vemuri et al., 2010 [28]◦ Lo et al., 2011 [26]◦ Seppälä et al., 2011 [29]◦

Diagnostic groups AD (n = 71), aMCI (n = 149), controls (n = 92) AD (n = 16), MCI (n = 54), controls (n = 36) AD (n = 56), MCI (n = 57): 21 MCI-AD, 26 MCI-stable; non-AD (n = 14); controls (n = 14)

Time interval

Assay


T-tau

P-tau


Mean total group: 1 year

INNO-BIA AlzBio3

=

↑controls = AD and aMCI

Not reported

No genotype effects

LP every year for 3 years

INNO-BIA AlzBio3

↓

=

↑ controls = AD and MCI

No genotype effects

Median total group: 2.98 years (range: 0.48–8.15 years)

INNOTEST ␤-AMYLOID (1-42) INNOTEST hTau INNOTEST PHOSPHOTAU(181P)

↓ AD = MCI, non-AD and Controls

↑MCI and Controls = AD and non-AD

↓ AD ↑ MCI-MCI and controls = MCI-AD and non-AD

APOE ␧4 carriers: greater longitudinal decrease in CSF A␤1-42 and lower T-tau at follow-up

↑ significant increase in concentration; ↓ significant decrease in concentration; = no significant change in concentration. Only one symbol is given for the longitudinal stability of a CSF biomarker if (1) there is only one diagnostic group included in the cited study or (2) there is more than one diagnostic group included in the cited study, but there is no significant difference in evolution of the CSF biomarker concentrations between the diagnostic groups. References marked with ◦ are studies that reported changes in biomarker concentrations over a certain amount of time (year or month). A␤1-42 , amyloid-␤1-42 protein; AD, Alzheimer’s disease; aMCI, amnestic mild cognitive impairment; APOE, apolipoprotein E; DLB, dementia with Lewy bodies; EOAD, early-onset AD; LOAD, late-onset AD; MCI-AD, MCI patients that progress to AD in follow-up; LP, lumbar puncture; MCI-MCI, MCI patients that remain stable in follow-up; MXD, mixed dementia; NON-AD, non-Alzheimer’s disease dementia; P-tau181P , hyperphosphorylated tau at threonine 181; T-tau, total tau protein; VaD, vascular dementia. *increase in P-tau in MCI only significant after adjustment for ventricular volume.


Reference


MATERIALS AND METHODS Study population Serial CSF samples with a time interval of at least 30 days were selected from the Biobank facilities of the Institute Born-Bunge (Antwerp, Belgium). First, patients with a diagnosis of AD (n = 28) or MCI (n = 7) at baseline were selected from this population. Second, patients with any other neurodegenerative diseases or (neuro-) invasive disorders were excluded. The remaining subjects were considered as controls (n = 26). At the second CSF sampling, the diagnoses of all AD patients (n = 28) and most control subjects (n = 23) were confirmed, whereas all MCI patients progressed to dementia (AD: n = 4; frontotemporal dementia (FTD): n = 2; dementia with Lewy bodies (DLB): n = 1) and some control subjects progressed to MCI (n = 1) or to AD (n = 2) (Fig. 1). Stable and progressive patients (control-MCI/MCI-AD/MCIother dementia) were analyzed separately. All AD patients fulfilled the NINCDS-ADRDA clinical diagnostic criteria of probable AD [30]. Eleven of the baseline AD patients later came to autopsy and fulfilled the neuropathological criteria for definite AD by Braak and Braak [31] and complemented by Jellinger and Bancher [32] and Braak et al. [33]. MCI was diagnosed according to the clinical diagnostic criteria of Petersen [34]. For the clinical diagnosis

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of probable FTD, the criteria described by Neary et al. [35] were applied. For the neuropathological diagnosis of FTD (n = 1), the criteria of Jackson and Lowe [36] and Markesbery [37] were applied. DLB was diagnosed applying the clinical diagnostic criteria of McKeith et al. [38, 39]. The control group (stable controls) consisted of: 1) patients requiring urogenital surgery under spinal anesthesia (n = 12); 2) patients with mechanical low back pain requiring a selective lumbar radiculography (n = 4); 3) patients with disorders of the peripheral nervous system (polyneuropathy, Guillain-Barré syndrome: n = 2); 4) patients with epilepsy (n = 2); 5) a patient with restless legs syndrome; 6) a patient with paraparesis in which central nervous system pathology was excluded after extensive neurological work-up; and 7) a patient with trigeminal nerve neuralgia and reflex epilepsy. All patients and/or their relatives (in case of dementia) gave informed consent. Approval of the medical ethics committees was obtained from the University of Antwerp and Middelheim General Hospital. CSF sampling Lumbar punctures (LP) were performed at the Department of Neurology and the Memory Clinic of Middelheim General Hospital (Antwerp, Belgium). In all patients and control subjects, CSF was obtained by

Fig. 1. Diagram of patient selection. Legend: dark grey = patients included in the repeated measures analyses; light grey = patients included in the progressive patients’ analyses.

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LP at the L3/L4 or L4/L5 intervertebral space. CSF sampling was performed according to a standard protocol. The one difference with regard to CSF sampling between patients and control subjects was the CSF volume: 3 ml in 2 consecutive fractions for the control subjects instead of 15 ml in 5 fractions in dementia patients. CSF samples were collected and stored in polypropylene cryovials (Nalgene, Rochester, NY, USA). CSF biomarker analyses CSF levels of A␤1-42 , T-tau, and P-tau181P were determined with commercially available singleparameter ELISA kits (respectively, INNOTEST® ␤-AMYLOID(1-42), INNOTEST® hTAUAg, ® INNOTEST PHOSPHOTAU(181P); Innogenetics, Ghent, Belgium). With each assay, the clinical samples, together with a blank (sample diluent), the (prepared) calibrator solutions, and the appropriate controls, were tested strictly following the test instructions provided in the kit inserts. The concentration ranges of the test kits are described in the package inserts (A␤1-42 : 125–2000 pg/ml; T-tau: 75–1200 pg/ml; P-tau181P : 15.6–500 pg/ml). APOE genotyping Genomic DNA was extracted from total blood using standard methods and the APOE genotype was determined as described earlier [40]. Statistical analyses A Kolmogorov-Smirnov test was used to test for normality of the distribution. All parameters were found to have a normal distribution, allowing us to use parametric tests. Gender distribution was analyzed using a Chi square test. Age at both samplings and sampling interval between patients and controls was analyzed using unpaired Student’s t-tests. To investigate longitudinal changes in patients whose diagnoses remained stable between first and second sampling (AD: n = 28; controls: n = 23), repeated measures ANOVA were performed with the biomarker levels in both samples as the within-subjects variables and the diagnosis as the between-subjects variable. If an interaction effect between diagnosis and the evolution of the biomarker levels in time was identified, a paired Student’s t-test was performed to analyze the groups separately. To correct for the varying time interval between baseline and follow-up sampling, change over

time was calculated as follows: [follow-up concentration – baseline concentration] / time interval in month and compared between AD patients and control subjects using an unpaired Student’s t-test. Correlation coefficients between biomarker levels of both samples were calculated using Pearson correlation statistics. To investigate the evolution of biomarker levels in progressive patients (n = 10), a paired Student’s t-test was performed. A probability level of p < 0.05 was considered statistically significant. Statistical analyses were performed using SPSS 17.0 (SPSS Inc., Chicago, USA).

RESULTS Out-of-range concentrations, i.e., values obtained outside the standard curve, were excluded from dataanalysis because the exact difference between serial biomarker levels could not be calculated (Fig. 1). Two control subjects and the MCI patient converting to DLB showed T-tau levels 1200 pg/ml in the first CSF sample as well as in the second CSF sample. One other AD patient showed T-tau >1200 pg/ml in only the first CSF sample. There were significantly more men in the control than in the AD group. AD patients were older than the control subjects at both samplings. The mean time interval between two samplings was 15 months (range 1–69 months) in the control group and 23 months (range 1–105 months) in the AD group (Table 2). The difference in mean interval between two samplings was not statistically significant (p = 0.155; t = −1.445; df = 49) comparing AD and control groups. The mean Mini-Mental Status Exam (MMSE) score of the AD patients was 17 ± 5 (range 6–25; n = 21) within 3 months of first CSF sampling and 14 ± 5 (range 5–23; n = 17) within 3 months of second CSF sampling. The mean decline in MMSE score was 5 ± 6 points (range 3–14; n = 13). Missing MMSE scores in the AD group are explained by the inability or unwillingness of the patient to complete the MMSE (first sampling: n = 1; second sampling: n = 3) and by the fact that the MMSE was not done within 3 months of CSF sampling. APOE genotyping was done in 24/28 AD patients, but not in controls. The frequency of the ␧4 allele in the AD group was 11/24 (46%). In the repeated measures analysis, a main effect of A␤1-42 and an interaction between change in A␤1-42 and diagnosis could not be identified, meaning that

Table 2 Demographic and biomarker data of the AD, control and progressive patients Control (n = 23)

Statistics

Progressive patients◦ (n = 10)

Statistics

Gender (male/female) % APOE ␧4 carriers Age at baseline (year) Age at follow-up (year) A␤1-42 (pg/ml) baseline A␤1-42 (pg/ml) follow-up

11/17 46% 77 ± 9 79 ± 8 387 ± 95 (239–554) 370 ± 132 (138–685)

18/5 ND 67 ± 14 68 ± 13 767 ± 282 (300–1266) 776 ± 221 (374–1182)

7/3 ND 72 ± 9 76 ± 8 517 ± 228 435 ± 157

NA NA NA NA p = 0.064 t = 2.113 df = 9

A␤1-42 difference (pg/ml)

−16 ± 98 (95% CI −54 ± 22) 7.76 ± 31.67 (95% CI −4.52 ± 20.04) 399 ± 203 (144–774) 487 ± 306 (127–1196)

9 ± 244 (95% CI −97 ± 144) −9.84 ± 42.14 (95% CI −28.06 ± 8.38) 303 ± 184 (77–694) 262 ± 152 (93–643)

p = 0.005; χ² = 7.820; df = 1 NA p = 0.003; t = −3.142; df = 35.681 p = 0.001; t = −3.497; df = 35.395 Main effect: p = 0.882 Interaction A␤1-42 *diagnosis: p = 0.622 Between-subjects effect: p < 0.001 NA

−82 ± 122 (95% CI −95 ± 51) 1.64 ± 11.58 (95% CI −6.64 ± 9.93) 429 ± 306 406 ± 283

NA

87 ± 204 (95% CI 3–172) 10.32 ± 34.46 (95% CI −3.90 ± 24.55) 77 ± 44 (23–214) 71 ± 46 (25–215)

−42 ± 130 (95% CI −101 ± 17) −7.22 ± 18.08 (95% CI −15.45 ± 1.01) 51 ± 25 (16–117) 50 ± 27 (16–125)

−6 ± 18 (95% CI −13 ± 1) −0.51 ± 6.89 (95% CI −3.18 ± 2.17)

−1 ± 15 (95% CI −7 ± 5) −0.02 ± 1.90 (95% CI −0.84 ± 0.80)

A␤1-42 change over time (pg/ml/month) T-tau (pg/ml) baseline T-tau (pg/ml) follow-up T-tau difference (pg/ml) T-tau change over time (pg/ml/month) P-tau181P (pg/ml) baseline P-tau181P (pg/ml) follow-up P-tau181P difference (pg/ml) P-tau181P change over time (pg/ml/month)

p = 0.095; t = −1.702; df = 49 Main effect: p = 0.383 Interaction T-tau *diagnosis: p = 0.016 Between-subjects effect: p = 0.011 NA p = 0.041; t = −2.100; df = 44 Main effect: p = 0.133 Interaction P-tau181P *diagnosis: p = 0.285 Between-subjects effect: p = 0.027 NA p = 0.744; t = 0.328; df = 49

NA p = 0.499 t = 0.709 df = 8

−22 ± 95 (95% CI −169 ± 6) 4.97 ± 11.19 (95% CI −3.63 ± 13.58) 60 ± 39 56 ± 37

NA NA p = 0.497 t = 0.707 df = 9

−3 ± 14 (95% CI −13 ± 7) 1.29 ± 3.78 (95% CI −1.41 ± 3.99)

NA NA

NA


AD (n = 28)

Data are presented as mean ± standard deviation (range; unless indicated otherwise). Significant differences are indicated in bold. ◦ Progressive patients are patients with a control or MCI diagnosis at baseline and showing progression to MCI or dementia, respectively, in follow-up. A␤1-42 , amyloid-␤1-42 protein; AD, Alzheimer’s disease; CI, confidence interval; MCI, mild cognitive impairment; NA, not applicable; ND, not done; P-tau181P , hyperphosphorylated tau at threonine 181; T-tau, total tau protein.

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intra-individual CSF A␤1-42 levels are stable and that this lack of change in A␤1-42 levels is the case for AD patients as well as control subjects (Table 2). The same results were found for P-tau181P . For Ttau, a main effect could also not be identified with the repeated measures analysis. However, an interaction effect between change in T-tau and diagnosis was found, implying that the alteration in T-tau levels occurs differently in AD patients compared to control subjects (Table 2). The alteration in intra-individual Ttau levels was subsequently investigated in both groups separately. T-tau levels in the second CSF sample of the AD patients were significantly higher (p = 0.042; t = −2.145; df = 24; Table 2 and Figs. 2 and 3). In the control group, T-tau levels were not significantly different in the first CSF sample in comparison to the second CSF sample (p = 0.155; t = 1.478; df = 20; Figs. 2 and 3). For all three biomarkers, the betweensubjects effect was significant, which means that the A␤1-42 , T-tau, and P-tau181P levels in the first CSF sample were significantly different between the AD and control group. A␤1-42 levels were significantly lower in AD patients, while T-tau and P-tau181P levels were significantly higher in AD patients as compared to the control group (Figs. 2 and 3). Consistent with the results from the repeated measures analysis, only for T-tau the change in biomarker concentration per time unit (month) was significantly different between AD and controls, but the difference between baseline and follow-up sampling in AD patients was not significant anymore. Correlation analysis of the biomarker levels in serial CSF samples revealed highly significant and moderate to strong correlations for all biomarkers in the total group as well as the diagnostic groups separately (for A␤1-42 : total group r = 0.787, AD r = 0.666, controls r = 0.550; for T-tau: total group r = 0.733, AD r = 0.753, controls r = 0.715; for P-tau181P : total group r = 0.911, AD r = 0.922, controls r = 0.841; p < 0.001, except for A␤1-42 in controls p = 0.007).

Fig. 2. Visualization of mean A␤1-42 , amyloid-␤1-42 protein; P-tau181P hyperphosphorylated tau at threonine 181; T-tau, total tau protein. levels with error bars representing the 95% confidence interval. Legend: significant differences are indicated as follows: *p < 0.05. Grey bars = results from baseline sample; white bars = results from follow-up sample. Comparisons have been made between (1) controls and AD at baseline; (2) baseline and follow-up in AD; (3) baseline and follow-up in controls. Baseline levels were significantly different between AD and controls for all three markers. Of all comparisons between baseline and follow-up, only T-tau levels were significantly higher at follow-up in AD patients.


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DISCUSSION We evaluated the longitudinal stability of CSF A␤1-42 , T-tau, and P-tau181P levels by analyzing serial CSF samples of AD patients and control subjects. The AD patient group, which was in part neuropathologically confirmed, constitutes the main group of interest because the evolution in CSF biomarker concentrations could be used as an individual pharmacodynamic measure during disease-modifying treatments. Besides the AD group, we also included a control group to verify whether changes in CSF biomarker levels that possibly occur in the AD group are part of the natural course of CSF biomarker concentrations or of the disease itself. Serial sampling

Fig. 3. Visualization of difference in biomarker concentrations in relation to time between baseline and follow-up sampling. Remark: samples (n = 2) with interval between baseline and sampling >60 months were not included in this figure.

The difference in biomarker levels in patients progressing to MCI or dementia was also analyzed. The mean time interval between 2 LP was 45 months (range 2–136 months). The difference between values measured in the baseline and follow-up sample was not significant, which applied to all three biomarkers (Table 2). Subdivisions according to the type of progression (control-MCI, control-AD, MCI-AD, or MCI-other dementias) could not be made because of the small number of progressive patients with serial CSF sampling (n = 10).

AD patients showed lower A␤1-42 and higher Ttau and P-tau181P concentrations in comparison to the control subjects, which is in accordance with multiple other studies [5]. The control population consisted of patients suffering from disorders that are not expected to lead to AD-like alterations in CSF A␤1-42 or tau levels (see method section for full overview of control diagnoses). However, the selected control group was significantly younger than the AD group, which might have influenced the results. Also, more men were included in the control group in comparison to the AD patient group. This can be explained by the fact that, in general, the prevalence of AD is greater in women [41] and that the majority of our control subjects consists of patients admitted for urogenital surgery (prostate and bladder carcinoma), which were all men. The ␧4 allele frequency of 46% in this partly neuropathologicallyconfirmed AD patient selection was slightly higher than previously reported in a Belgian population (33%) [42]. Longitudinal changes in A␤1-42 and P-tau181P levels could not be detected in both AD patients and controls. For T-tau, a significant intra-individual change in raw biomarker concentrations could be detected in AD patients but not in controls. The results of our longitudinal study on CSF biomarkers are in line with the main body of literature on this topic. Most other longitudinal CSF biomarker studies showed stable A␤1-42 and P-tau181P levels, irrespective of diagnosis (AD or control). The issue that is the most debatable is whether or not T-tau levels increase in AD patients and our study agrees to an increase in T-tau. Correlations between longitudinal CSF biomarker levels were highly significant both in AD patients as well as in controls. All other studies demonstrating an increase in T-tau also

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had mean intervals of more than one year [14, 15, 17, 22, 43, 44]. However, in this study, this difference disappeared when the individual LP interval, which varied across patients, was taken into account. According to a meta-analysis by Zhou et al. [45], combining the results of several observational studies in AD patients results in an overall small, but significant increase in T-tau (1.5 pg/ml/month) and a non-significant decrease in A␤1-42 (−0.4 pg/ml/month). However, other studies expressing the change in biomarker concentrations per time unit have not been able to find significant changes in T-tau [26–29], which is in correspondence with our results. In addition, in Fig. 3, we can visually identify five patients with varying LP intervals with a difference in T-tau concentration of more than 200 pg/ml. There were no arguments for any acute pathology in these patients, but all showed a marked worsening in cognitive status before the second LP. Even more so, three out of five patients died within three weeks after the second LP and these three patients were later on confirmed to have AD. Re-analyzing our data without these five AD patients, the repeated measures ANOVA did not show an overall significant increase in T-tau (p = 0.245) and the evolution in T-tau in AD patients and control subjects was not significantly different (p = 0.236), in contrast to the analysis that included these cases (Table 2). Comparing the monthly change in T-tau between AD and controls without these 5 AD cases, the difference was borderline non-significant (t = −2.051; df = 25,052; p = 0.051). The association of markedly increasing T-tau levels and the clinical deterioration of these patients confirms earlier reports that T-tau might reflect disease intensity, with higher levels mirroring a more rapid progression [46, 47]. However, the correlation of biomarker changes with MMSE or other cognitive measures is not straightforward. For example, Mattsson et al. [48] showed a tendency toward increasing T-tau levels in MCI patients progressing to AD over a period of 4 years, but the drop in MMSE was negatively correlated with P-tau181P , not T-tau. Sunderland et al. [24] found an increase in CSF T-tau levels over 2 years in AD patients with initially low T-tau levels (relative to the mean of the total group), although no significant differences in disease duration or dementia severity could be detected. For the progressive patients in the present study, only non-significant evolutions for all three CSF biomarkers were detected. Also, the difference in serial T-tau concentrations (raw and normalized) was not significantly correlated with the progression of cognitive decline, measured by the difference in serial MMSE

scores, nor the rate of cognitive decline, as measured by the serial MMSE scores corrected for the LP interval (data not shown). Albeit, we need to point out that there was only a small number of patients with serial MMSE scores (n = 13), and the correlation of cognitive measures with CSF biomarkers was not part of the aims of the study. Serial CSF sampling allows the evaluation of whether the CSF biomarkers can be used as markers for disease progression. The MMSE might not be a very sensitive measure for tracking disease progression, but another study also mentioned a lack of association for other cognitive measures, such as ADAS-Cog, with changes in CSF biomarkers in AD, MCI, and controls [28]. A scientifically sound hypothetical model of the temporal relationship of several AD biomarkers presumes A␤ to be the first biomarker to show alterations, even before the onset of the disease [49]. Changes in CSF biomarker concentrations are, according to this model, more likely to occur in presymptomatic (for A␤1-42 ) and early symptomatic disease stages (for T-tau and P-tau181P ). Indeed, the typical AD biomarker profile can already be seen in MCI patients that progress to AD [6–8], but changes in T-tau but not A␤1-42 still occurring in the MCI stage before the onset of the dementia [50, 51]. Our control subjects showed no notable change in any of the biomarkers. If the selected control population would have included many subjects prone to develop AD, we might have found a significant decrease in A␤1-42 . In the present study, there was a significant age difference between control subjects and AD patients and some, but not all, studies have shown that CSF biomarker levels become more abnormal, or more AD-like, with aging [2, 52–54]. The present results show that longitudinal CSF biomarker measurements can be used in (early-phase) clinical trials of disease-modifying drugs to verify whether the compound under investigation meets its target. For monitoring short-term disease progression, they are less implicated because the key factor, namely a clear-cut correlation between changes in CSF biomarker level and beneficial effects on the cognitive status of the patient undergoing treatment, is lacking. Although the CSF biomarkers reflect the fundamental features of AD pathology [30], alterations in their concentrations do not seem to coincide with an improvement in cognitive status on short term. Some studies have found plaque and tangle load to correlate with CSF A␤1-42 , T-tau, and P-tau181P [55, 56], while others have not [57]. Conflicting results of these studies could be due to methodological issues, but neverthe-


less, postmortem brain examination of patients treated with an active immunization therapy showed that the removal of A␤ plaques is not sufficient to bring the cognitive decline to a halt or even decrease the rate of cognitive decline [58]. Strengths and limitations of the study The AD patients population consisted of 28 patients, of which 11 (39%) were neuropathologically confirmed. Some other studies, aimed at investigating serial levels of CSF biomarkers, also included neuropathologically-confirmed patients, but not the same number nor percentage [12, 16, 59]. Ideally, all samples from each patient should have been analyzed within the same run because the expected intra-individual variation is low and the interrun variability/lot-to-lot variation could then be larger than the intra-individual variation. Samples from each patient were therefore analyzed on the same plate as much as possible, but the majority of the analyses was done in routine practice (A␤1-42 : 39/51, T-tau: 37/51, P-tau181P : 34/51). The intra-individual coefficient of variation (CV) of samples analyzed in the same run has been proven to be smaller than the intra-run CV for all three biomarkers, which is also smaller than the intra-individual CV of samples analyzed on different occasions [43, 60]. A repeated measures analysis investigating the evolution in biomarker concentrations between samples that were analyzed on the same plate or on two different occasions also did not show significant differences, and a repeated measures analysis with this factor as a covariate led to the same results. CONCLUSION The intra-individual variation in the CSF biomarker levels (A␤1-42 , T-tau, and P-tau181P ) is relatively small. The change in T-tau levels, that was significant in AD patients, does not preclude its use as: a) a diagnostic marker, since CSF A␤1-42 and P-tau181P are stable throughout the course of AD and CSF T-tau becomes more AD-like; or b) a pharmacodynamic marker for disease-modifying drugs, since these drugs might have different effects on CSF biomarker levels. ACKNOWLEDGMENTS This research was supported by the Special Research Fund of the University of Antwerp; the Foundation for Alzheimer Research (SAO-FRMA); the Thomas

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Riellaerts Research Fund; the Institute Born-Bunge; the agreement between the Institute Born-Bunge and the University of Antwerp; the central Biobank facility of the Institute Born-Bunge/University of Antwerp; Neurosearch Antwerp; the Research Foundation Flanders (FWO); the Interuniversity Attraction Poles (IAP) program P7/16 of the Belgian Science Policy Office; the Methusalem excellence program of the Flemish government, Belgium. The authors acknowledge the technical assistance of the VIB Genetic Service Facility and the Biobank of the Institute Born-Bunge, the administrative assistance and the clinical staff of the Department of Neurology/Memory Clinic of ZNA Middelheim and ZNA Hoge Beuken. Authors’ disclosures available online (http://www.jalz.com/disclosures/view.php?id=1511). REFERENCES [1]

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