Longitudinal Cerebrospinal Fluid Biomarkers over Four ... - IOS Press

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Journal of Alzheimer’s Disease 30 (2012) 767–778 DOI 10.3233/JAD-2012-120019 IOS Press

Longitudinal Cerebrospinal Fluid Biomarkers over Four Years in Mild Cognitive Impairment Niklas Mattssona,∗ , Erik Porteliusa , Sindre Rolstada , Mikael Gustavssona , Ulf Andreassona , Mats Stridsbergb , Anders Wallina , Kaj Blennowa and Henrik Zetterberga a Clinical

Neurochemistry Laboratory, Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden b Department of Medical Sciences, Uppsala University, Uppsala, Sweden Handling Associate Editor: Lucilla Parnetti

Accepted 28 February 2012

Abstract. Cerebrospinal fluid (CSF) measurements of amyloid-␤42 (A␤42 ), total-tau (T-tau), and phosphorylated tau (P-tau) may be used to predict future Alzheimer’s disease (AD) dementia in patients with mild cognitive impairment (MCI). The precise temporal development of these biomarkers in relation to clinical progression is unclear. Earlier studies have been hampered by short follow-up. In an MCI cohort, we selected 15 patients who developed AD (MCI-AD) and 15 who remained cognitively stable during 4 years of follow-up. CSF was sampled at three serial occasions from each patient and analyzed for A␤ peptides, the soluble amyloid-␤ protein precursor protein fragments sA␤PP␣ and sA␤PP␤, T-tau, P-tau, and chromogranin B, which is a protein linked to regulated neuronal secretion. We also measured, for the first time in MCI patients, an extended panel of A␤ peptides by matrix-assisted-laser-desorption/ionization time-of-flight mass spectrometry (MS). Most biomarkers were surprisingly stable over the four years with coefficients of variation below or close to 10%. However, MCI-AD patients decreased in CSF A␤X-40 and chromogranin B concentrations, which may indicate a reduced number of functional neurons or synapses with disease progression. The MS A␤ peptide panel was more useful than any single A␤ peptide to identify MCI-AD patients already at baseline. Knowledge on these biomarkers and their trajectories may facilitate early diagnosis of AD and be useful in future clinical trials to track effects of disease modifying drugs. Keywords: Alzheimer’s disease, amyloid-␤, biomarkers, cerebrospinal fluid, chromogranin, mild cognitive impairment, tau Supplementary data available online: http://dx.doi.org/10.3233/JAD-2012-120019

INTRODUCTION Cerebrospinal fluid (CSF) may be analyzed for biomarkers to monitor pathologies in the brain [1]. CSF biomarkers alterations seen in Alzheimer’s disease ∗ Correspondence to: Niklas Mattsson, Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital/Mölndal, 431 80 Mölndal, Sweden. Tel.: +46 706 393851; E-mail: [email protected].

(AD) include reduced concentrations of the 42 amino acid long isoform of the amyloid-␤ peptide (A␤1-42 ), which is excised from the amyloid-␤ protein precursor (A␤PP), and increased concentrations of both total tau protein (T-tau) and tau protein phosphorylated at specific residues (P-tau) [1]. These biomarker changes are believed to reflect brain amyloid pathology [2, 3], axonal degeneration [4, 5], and neurofibrillary tangle pathology [6], respectively, and are seen already at the stage of mild cognitive impairment (MCI) prior

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N. Mattsson et al. / Longitudinal CSF Biomarkers in MCI

to clinically overt dementia [7–10]. A detailed understanding of biomarker trajectories in relation to disease progression may facilitate early diagnosis of AD and be useful when monitoring disease-modifying interventions [11]. The vast majority of knowledge on CSF biomarkers comes from cross-sectional case-cohort studies. Among longitudinal CSF studies in MCI patients, most have reported stable levels of A␤X-42 or A␤1-42 (collectively called A␤42 below) [12–14], T-tau [12–16], and P-tau [13–17]. Most of these studies have only included two consecutive lumbar punctures (LPs) with a follow-up period extending up to two-three years. AD is widely recognized as a slowly progressive disease and more sampling points and longer follow-up periods are needed to establish the biomarkers’ final patterns of development. Additional biomarkers beside A␤42 , T-tau, and P-tau may also be useful for an early differentiation of MCI patients who will later be diagnosed with AD dementia (MCI-AD) from other MCI patients, and to monitor disease progression. Specifically, biomarkers related to synaptic function and activity are interesting to explore, since synaptic loss has been proposed as the neuropathological feature with strongest correlation to clinical progression of AD [18]. We therefore examined three serial CSF samples during four years of follow-up in progressive and stable MCI patients for A␤ peptides; sA␤PP␣ and sA␤PP␤, which are released from A␤PP in different processing pathways [19]; chromogranin B (CgB), which may reflect the activity of the regulated secretory pathway in neurons and previously have been linked to CSF A␤ levels [20, 21]; T-tau; and P-tau. The primary study aim was to compare longitudinal changes in biomarker levels in progressive versus stable MCI.

University Hospital (“The Gothenburg MCI study”) [22]. All subjects had been admitted to the clinic for evaluation of cognitive dysfunction. They underwent clinical and neurological examination, neuropsychological testing, basic laboratory testing, MRI of the skull, and CSF sampling. All subjects were determined to have MCI, according to the revised Petersen criteria [23], and were followed with clinical examinations and CSF samplings at two and four year follow-up visits. At the two year follow-up, nine patients had progressed to probable AD dementia according to the DSM-IV [24] and NINCDS-ADRDA [25] criteria. At the four year follow-up, six additional patients had progressed to probable AD dementia. These 15 patients are called MCI-AD. All diagnoses were made by physicians blinded to the CSF biomarker data. The other 15 patients remained in stable mild cognitive impairment (SMCI). See Table 1 for study demographics. Note that these 30 patients were not consecutively recruited but selected for this particular study. The study was approved by the local ethical committee and was done in accord with the Helsinki Declaration of 1975. CSF sampling All CSF samples were collected by LP in the L3/L4 or L4/L5 interspace. No serious adverse events were reported. The first 12 mL of CSF was collected in a polypropylene tube and immediately transported to the local laboratory for centrifugation at 2,000 g at +4◦ C for 10 min. The supernatant was pipetted off, gently mixed to avoid possible gradient effects, and aliquoted in polypropylene tubes that were stored at −70 to −80◦ C pending biochemical analyses, without being thawed and re-frozen. Biochemical procedures

MATERIALS AND METHODS Study participants The study included 30 patients selected from an ongoing study at the memory clinic of the Sahlgrenska

All biochemical analyses except for CgB were performed at the Clinical Neurochemistry Laboratory in Mölndal, Sweden, by experienced laboratory technicians who were blinded to all clinical information. CgB measurements were performed at the Clinical

Table 1 Study demographics at baseline Group SMCI MCI-AD MCI-AD 2 years MCI-AD 4 years

n 15 15 9 6

Age 64 (56–74) 66 (51–75) 68 (51–73) 58 (52–75)

Gender (M : F) 11 : 4 4 : 11 1:8 3:3

APOE

ε4−/−

ε4±

ε4+/+

11 5 3 2

3 5 4 1

1 5 2 3

Continuous data presented as median (range). Age and education presented as years.

Education

MMSE

11 (7–18.5) 10 (6–21) 11 (6–17.5) 10 (8–21)

29 (25–30) 28 (23–30) 28 (23–30) 29 (25–30)


Chemistry Laboratory in Uppsala, Sweden. All analyses were performed at one occasion, using the same batch of reagents to minimize laboratory and assay variations. Intra-assay coefficients of variation (CVs) for duplicate samples on immunoassays were ≤10%. CSF AβX-38 , AβX-40 , and AβX-42 CSF A␤X-38 , A␤X-40 , and A␤X-42 were measured using the MSD Human/Rodent Abeta Triplex Assay as described by the manufacturer (Meso Scale Discovery, Gaithersburg, MD, USA). This assay employs C-terminal specific antibodies to specifically capture A␤X-38 , A␤X-40 , and A␤X-42 . All isoforms are detected by a SULFO-TAG-labeled 4G8 detection antibody (epitope within amino acids 18-22 in the A␤1-42 sequence). CSF sAβPPα and sAβPPβ CSF sA␤PP␣ and sA␤PP␤ were measured using the MSD sAPP␣/sAPP␤ Multiplex Assay (Meso Scale Discovery) as described by the manufacturer. This assay employs the 6E10 antibody to capture sA␤PP␣ and a neoepitope-specific antibody to capture sA␤PP␤. Both isoforms are detected by a SULFO-TAG-labeled anti-A␤PP antibody p2-1. CSF T-tau and P-tau CSF levels of T-tau and tau phosphorylated at threonine 181 (P-tau) were measured using the Alzbio3 kit (Innogenetics, Ghent, Belgium) for the xMAP Luminex platform, as previously described [26]. CSF CgB CSF levels of CgB derived peptides were measured using a previously developed radioimmunoassay (RIA) [27, 28]. Antisera directed against CgB residues 439-451 was used (amino acid residues as defined in the SWISSPROT database, minus signal peptides). Immunoprecipitation and mass spectrometry We have previously used immunoprecipitation (IP) of A␤ peptides followed by matrix-assisted-laserdesorption/ionization time-of-flight/time-of-flight mass spectrometry (MALDI-TOFMS) to characterize the CSF A␤ pattern [29] in patients with sporadic AD dementia [30] and familial AD [31]. Here we used this assay for the first time on MCI patients. In brief, IP was done using A␤-specific antibodies coupled to magnetic beads [32]. Four ␮g of the anti-A␤ antibody 6E10 and 4G8 (Signet Laboratories, Dedham, MA, USA) was separately added to 50 ␮L each of magnetic Dynabeads M-280

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Sheep Anti-Mouse IgG (Invitrogen, Carlsbad, CA, USA). The 6E10 antibody-coated beads and 4G8 antibody-coated beads were mixed and added to the CSF to which 0.025% Tween20 in phosphate-buffered saline (pH 7.4) had been added. After washing, using the KingFisher magnetic particle processor (Thermo Scientific), the A␤ isoforms were eluted using 100 ␮L 0.5% formic acid. MS measurements were performed using a Bruker Daltonics AutoFlex MALDI-TOF instrument (Bruker Daltonics, Bremen, Germany). An in-house MATLAB (Mathworks Inc. Natick, MA, USA) program was used for relative quantification of the A␤ peptides. Each peak was integrated and normalized against the sum for all the integrated A␤ peaks in the spectrum followed by averaging of the sample duplicates. It should be noted that this type of relative quantification cannot be interpreted as a direct reflection of an absolute or relative abundance of a peptide due to the normalization procedure and since the ionization efficiency might be different for different peptides, which affects the peak area. Statistics The main endpoints of the study were differences in biomarker levels between groups and over time. Examined confounding factors were gender, age, and APOE genotype. Univariate statistics Since several of the biomarkers had skewed distributions as determined by the D’Agostino and Pearson omnibus normality test, non-parametric tests were used for group comparisons. The Mann-Whitney U test was used for comparisons of two samples of unrelated data (cross-sectional comparisons between the diagnostic groups) and the Friedman test with Dunn’s post hoc test was used for comparisons of multiple samples of related data (longitudinal comparisons within the same individual). Linear regression analysis was used to test relations between measurements at different time points. The regression residuals were normally distributed in most cases, justifying the use of the Pearson correlation coefficient R and R2 to describe the correlations. The Spearman coefficient R was used in the few cases when the residuals had skewed distributions. Statistical significance was determined at p < 0.01. Multivariate statistics Multivariate analysis was performed using the orthogonal projections to latent structures discriminant analysis (OPLS-DA) algorithm (SIMCA-P+, v.12, Umetrics, Ume˚a, Sweden). This method finds

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Fig. 1. CSF biomarkers in SMCI and MCI-AD patients. Each panel contains data for measurements at baseline, two year follow-up, and four year follow-up. Comparisons were done for baseline levels in SMCI versus MCI-AD (using the Mann-Whitney U test) and over-time within the groups (using the Friedman test).


Fig. 2. CSF A␤ isoforms determined by IP-MS. Representative MS spectra from a SMCI (panel A) and a MCI-AD patient (panel B).

the direction in a multivariate space spanned by the analytes that best separates the predefined groups [31, 33]. Diagnostic accuracies of the models were assessed by area under the receiver operating characteristics curve (AUC) analyses. AUCs were compared using the method proposed by DeLong et al. (suitable for curves derived from the same samples) [34]. Outliers Outlying biomarker measurements were defined as values differing >3 standard deviations (SDs) from the mean within a diagnostic group. Only one measurement fulfilled this criterion. This was a baseline measurement of P-tau (125 ng/L) in a MCI-AD patient, where levels were considerably lower at follow-up (41 ng/L and 49 ng/L). No other extreme biomarker levels or major shifts over time were found in this patient. The outlying measurement was considered most likely to represent a technical error, and was removed from all analyses. Overall, this did not affect statistical significances.

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P-tau compared to SMCI patients (Fig. 1). There were no significant differences between the groups in baseline levels of CSF A␤X-38 , A␤X-40 , sA␤PP␣, sA␤PP␤, or CgB. All samples were analyzed by IPMS (See Fig. 2 for representative spectra). There were no significant differences in normalized levels of individual IP-MS determined A␤ isoforms, except for A␤1-42 (supplementary Figure 1; available online: http://www.j-alz.com/issues/30/vol304.html#supplementarydata01). However, there were trends for reduced normalized levels of the short isoforms A␤1-14 , A␤1-15 , A␤1-16 , A␤1-17 , and A␤1-19 , and elevated normalized levels of A␤1-37 , A␤1-38 , A␤1-39 , and A␤1-40 in MCI-AD patients. We therefore combined all IP-MS A␤ isoforms in a multivariate model. This model, in which A␤1-42 , A␤1-15 , and A␤1-38 were the most important components, had high diagnostic accuracy for MCI-AD versus SMCI (Fig. 3A, B; AUC 0.95). For comparison, we also constructed a multivariate model of T-tau, P-tau, and A␤X-42 , which might be said to represent the core CSF biomarkers for AD (although the A␤X-42 assays is not limited to only A␤1 as the N-terminal peptide amino acid), which had a very similar diagnostic accuracy (Fig. 3C, D; AUC 0.96). Finally, we constructed a model of all investigated biomarkers in this study, which achieved nearly complete diagnostic separation between SMCI and MCI-AD (Fig. 3E, F; AUC 0.99). The differences between these three AUCs were not statistically significant. Longitudinal development of CSF biomarkers Generally, intra-individual biomarker levels were very stable during follow-up (Fig. 4, Table 2), except for P-tau (Fig. 4F; Table 2). In MCI-AD patients, A␤X-40 and CgB declined over time (Fig. 1B, D) and there were tendencies for reductions in sA␤PP and other A␤ peptides and increases in tau. All biomarkers were stable in most SMCI patients. The normalized levels of IP-MS determined A␤ isoforms were stable (supplementary Figure 1) and the multivariate models retained their diagnostic accuracies over time (Fig. 3). Development of biomarkers in relation to cognitive outcome

RESULTS CSF biomarkers at baseline Most MCI-AD patients had reduced baseline levels of A␤X-42 and elevated levels of T-tau and

In an exploratory analysis, limited by the small number of patients in this study, we investigated change in biomarker levels in relation to change in MiniMental Status Examination scores (MMSE) (Fig. 5). In MCI-AD patients, the drop in MMSE was paralleled

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Fig. 3. Multivariate model of CSF biomarkers. The multivariate models were constructed from IP-MS A␤ isoform measurements (panels A–B), the established core biomarkers T-tau, P-tau, and A␤X-42 (measured using Meso Scale Discovery, MSD) (panels C–D), and all biomarkers in the study (panels E–F), using only baseline measurements. The models were fed with follow-up data which acts as prediction sets that confer strength to the models. These models clearly separated SMCI from MCI-AD patients during the course of the study. The relative contributions of the different biomarkers to the different models are shown in B, D, and F (the values on the y-axes are in an arbitrary unit and describes the relative contribution of each biomarker, where the mean of the squared heights equals 1). IP-MS determined peptides are labeled as A␤1-42 , A␤1-40 , A␤1-38 , etc., and MSD determined peptides as A␤X-42 MSD , A␤X-40 MSD , and A␤X-38 MSD .


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Fig. 4. Correlations between CSF biomarkers at baseline and 4 year follow-up. Data within each panel are mean coefficient of variation and linear regression R2 . For P-tau, the Spearman coefficient R is used due to skewed distribution of the regression residuals.

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N. Mattsson et al. / Longitudinal CSF Biomarkers in MCI Table 2 Variability between measurements at different time-points

Biomarker A␤X-38 A␤X-40 A␤X-42 sA␤PP␣ sA␤PP␤ T-tau P-tau CgB

Baseline versus 2 y follow-up

2 y versus 4 y follow-up

8.3% R2 = 0.91 7.3% R2 = 0.83 6.9% R2 = 0.89 8.1% R2 = 0.83 9.9% R2 = 0.85 10.8% R2 = 0.86 23.4% R2 = 0.69 6.8% R2 = 0.79

8.6% R2 = 0.90 7.4% R2 = 0.86 13.2% R2 = 0.91 6.5% R2 = 0.92 9.9% R2 = 0.92 12.5% R2 = 0.93 25.4% R2 = 0.45 9.0% R2 = 0.79

Data is mean over-time coefficients of variation and R2 for the Pearson correlation coefficient R, except for P-tau baseline versus 2 years, where the regression residuals had a skewed distribution, and the Spearman R coefficient is reported. See Fig. 4 for comparisons between baselines versus 4 years follow-ups.

by a shift in several biomarkers, including reduced CgB, sA␤PP␣, and sA␤PP␤ and increased P-tau. Most SMCI patients were stable over time in MMSE and in most biomarkers, but a few patients dropped in A␤X-42 and sA␤PP␤ despite stable MMSE levels (Fig. 5C, F). Possible confounding factors We investigated the influence of education, age, gender, and APOE genotype on biomarker levels. The groups were similar in age and education, but differed in gender distribution and occurrence of the APOE ε4 genotype. No biomarker correlated significantly at baseline with age or education in the whole study population or with age, education, gender, or presence of the APOE ε4 genotype in the individual diagnostic groups. Among MCI-AD patients, there were no differences in baseline biomarker levels between those converting to AD dementia at the two year follow-up and those converting at the four year follow-up. DISCUSSION Here for the first time, we show that a multivariate model of several A␤ isoforms measured by IP-MS has a higher diagnostic accuracy for MCI-AD versus SMCI than any individual A␤ isoform. This supports the study of additional A␤ peptides in MCI patients, but the specific biomarker model built in this pilot study must be verified by independent studies. The differences between SMCI and MCI-AD patients in baseline A␤42 , T-tau, and P-tau are in accordance with previous studies of CSF biomarkers in early stage clinical AD [4, 7–9]. Biomarker levels were stable over four years in both SMCI and MCI-AD patients, with CVs around 10%.

This may be important in clinical trials and in clinical routine if disease-modifying treatments for AD become available, since it enables identification of subtle long-term effects of drugs on pharmacodynamic primary (e.g., A␤42 for an anti-A␤ drug) and downstream (e.g., T-tau) biomarkers. The only biomarkers that changed significantly over time were A␤X-40 and CgB which dropped in MCI-AD. A␤X-40 has been reported to be stable during one-two years in healthy controls, MCI, and AD [13, 15, 35, 36], but one study found reductions in AD after three years [37]. A␤X-40 is one of the major A␤ peptides produced in the brain and is less prone to aggregation than A␤42 [38]. The neuronal secretion of A␤ depends on synaptic activity [39]. Chromogranins are key components in the regulated secretory pathway of neurons [40] and CSF CgB may be related to the activity of this pathway [20, 21]. The precise link between activity of the secretory pathways and neuronal plasticity is not clear, but together, reduced CSF A␤X-40 and CgB might suggest impaired neuronal secretion due to a continuous loss of functional synapses or neurons in AD. The tendencies for reductions of other A␤PP and A␤ peptides in MCI-AD are in line with this. Previous studies have reported stable A␤42 over about two years in AD [15, 35, 36, 41–45], but reductions over about three years [16, 37, 46]. Most studies on MCI patients have reported stable A␤42 during two-three years [12–14]. In sum, the normal trajectories of CSF sA␤PP and A␤ peptides seem to be a slow but continuous decrease of A␤X-40 and possibly A␤42 and other A␤PP and A␤ peptides during the symptomatic stages of AD. This is supported by other recent data from our laboratory showing inverse correlations between A␤40 , sA␤PP␣ and sA␤PP␤, and disease severity in AD patients [47]. Hypothetically, such changes over time may be related to altered aggregation, clearance, or production of peptides. Since similar trends were seen for all A␤PP and A␤ measurements in this study, reduced peptide production might be the most plausible explanation. Such time or severity-depending effects are not restricted to AD, since A␤ levels were lower in severely affected patients with the neurodegenerative disease NiemannPick type C [48]. This suggests that continuous loss of A␤ secretion is a general phenomenon across neurodegenerative diseases. Although no significances were reached, T-tau and P-tau tended to increase over time in MCI-AD. Previous studies have reported stable [12–16, 41, 42, 44, 46, 49–51] or slightly increased [17, 36, 45, 52] T-tau in AD and MCI patients for up to about three years. P-tau has been stable in AD and MCI patients for


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Fig. 5. Change in biomarkers in relation to change in MMSE. Each panel contains data for an individual biomarker. Data are presented as change at the 4 year follow-up examination in relation to baseline in biomarkers (%) and MMSE (absolute difference). Large symbols with error bars represent mean levels with SDs.

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up to three years [13–17, 41, 42] and one study has reported increased levels [35]. From our data and previous reports, we conclude that changes in T-tau and P-tau are small during the symptomatic stages of AD. Healthy controls have stable [35, 45] or slightly declining [16] A␤42 over time, and stable T-tau [16, 45] and P-tau [16, 35]. Declining A␤1-42 and increasing P-tau may be more frequent in persons with a parallel cognitive deterioration [53]. Despite stable MMSE, we found declining A␤X-42 and sA␤PP␤ in some SMCI patients. Further clinical follow-up may reveal if this indicated very early AD-associated alterations in A␤PP metabolism, as has been reported for A␤42 [54–58]. General patterns of CSF biomarker trajectories emerge from this study and previous reports, but with some inconsistencies. For example, one study reported increasing A␤1-42 over time in MCI and AD [17] and another reduced A␤1-42 over time in MCI [16]. There are several possible explanations for such dissimilarities, including differences in assays, laboratory procedures, and statistical methodology [59]. Large efforts are being devoted to reducing the variability of CSF biomarkers across labs to facilitate their use in research and clinical settings [60]. Importantly, the technical between-assay variability of biomarker measurements may exceed the biological betweentime variability [61], which makes it important to analyze all samples in one analytical run to detect minor temporal changes. Different assays have different specificity for the N-terminal part of the A␤ peptide, and reported concentrations may represent for example either A␤1-42 or A␤X-42 . Although such measurements often correlate, the correlations might be broken in vivo under certain medical conditions. In sum, we report that CSF A␤ peptides determined by IP-MS may be useful to discriminate MCI-AD from SMCI years before dementia. CSF biomarkers are generally stable over four years in SMCI and MCI-AD, but certain changes parallel clinical progression. Knowledge on these biomarker trajectories may be useful in intervention studies. Specifically, a desirable outcome for a disease modifying AD therapy in MCI patients may be reduced slopes of changes in A␤X-40 and CgB levels and reduced levels of T-tau and P-tau.

by grants from the Swedish Research Council, the Söderberg Foundation, Alzheimer’s Association, Swedish Brain Power, Swedish State Support for Clinical Research, Sahlgrenska University Hospital, Sahlgrenska Academy, the Lundbeck Foundation, Stiftelsen Psykiatriska Forskningsfonden, Stiftelsen Gamla Tjänarinnor, Uppsala Universitets Medicinska Fakultet stiftelse för psykiatrisk och neurologisk forskning, the Swedish Brain Fund, Göteborgs läkaresällskap, Thuréus stiftelse, Pfannenstills stiftelse, and Demensfonden, Sweden. Authors’ disclosures available online (http://www.jalz.com/disclosures/view.php?id=1205).

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