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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Arch Neurol. Author manuscript; available in PMC 2009 September 14.
Published in final edited form as:
PMCID: PMC2742778

Sorla/LR11, A Sorting Protein Limiting Abeta Production, Is Reduced In Alzheimer’s Disease CSF

Qiu-Lan Ma, MD. PhD,1,5 Douglas R. Galasko, MD,4 John M. Ringman, MD,2 Harry V. Vinters, MD,2,3 Steven D. Edland, PhD,4 Justine Pomakian, PhD,2,3 Oliver J. Ubeda, BS,1,5 Emily R. Rosario, PhD,1,5 Bruce Teter, PhD,1,5 Sally A. Frautschy, PhD,1,2,5 and Greg M. Cole, PhD1,2,5



SorLA/LR11 is a transmembrane neuronal sorting protein that reduces amyloid precursor protein (APP) trafficking to secretases, notably BACE1 that generates beta-amyloid (Aβ), the principal component of senile plaques in Alzheimer’s disease (AD). LR11 protein is reduced in late-onset AD brain and LR11 polymorphisms have been associated with late-onset AD.


Because, like APP, LR11 is cleaved near the membrane to release a large N-terminal fragment that is secreted to media from cultured cells, we sought to detect soluble LR11 and APP in cerebrospinal fluid (CSF) from AD and Control cases.


We evaluated CSF LR11, APPs and ApoE levels by Western blot in lumbar and postmortem CSF samples.


LR11 levels were detectable and stable over 6 months in CSF of AD patients. LR11 levels were significantly reduced in lumbar samples from mild to moderate probable AD patients, as well as in ventricular CSF from autopsy-confirmed AD cases, predominantly Braak stage III–IV. Bivariate analysis with Aβ42 and LR11 improved diagnostic specificity for AD. Reduced LR11 levels are significantly correlated with soluble APP, but not ApoE.


Reduced LR11 in CSF of AD patients may have potential as a diagnostic biomarker for patients with LR11 deficits that promote Aβ production or as an index of therapeutic response in late-onset AD.

Keywords: Alzheimer disease, SorLA, LR11, cerebrospinal fluid, amyloid, biomarkers

The neuronal sortilin-related receptor SorLA/LR11 (LR11), a member of the ApoE/low-density lipoprotein receptor family functions as a sorting and trafficking protein, guiding β-amyloid precursor protein (APP) into the recycling endosome pathways that lead to production of β-amyloid peptide (Aβ) (1). Recently, LR11 was shown to reduce Aβ production and found to be a candidate genetic risk factor for late onset Alzheimer’s disease (LOAD)(2), the most common cause of dementia in aged populations. Genetic polymorphisms associated with increased AD risk and reduced LR11 expression were found in ~15% of AD cases in several but not all (3) population based studies. Further, neuronal LR11 expression is reduced in brain tissue from patients with LOAD (4, 5), but not in early onset familial AD (FAD) in which overproduction of Aβ42 is thought to be causative (6). In addition, mild cognitive impairment (MCI) subjects with low brain levels of LR11 were significantly more cognitively impaired than the high LR11 subjects. Reduced LR11 levels occur early, increase with disease severity and might predict progression to AD in a subgroup of individuals with MCI (7). Collectively, these data argue that whatever their cause, LR11 deficits in LOAD occur early and are not simply secondary to pathology. Further, because they can be predicted to increase Aβ42 production, LR11 deficits are likely to contribute to pathogenesis and could be a target of a diagnostic biomarker or therapeutic intervention.

The selective reduction of Aβ42 in the cerebrospinal fluid (CSF) of AD patients has been widely used as a biomarker to increase diagnostic accuracy. However, deposition of Aβ42 in the brain or its reduction in CSF also occurs in other non-AD dementias such as dementia with Lewy bodies (DLB) (8) and Parkinson’s disease dementia (PDD) (9). Thus, the differential diagnosis of dementia based on established clinical criteria and informed by reduced Aβ42 levels in CSF is still difficult in standard practice. Other widely used CSF biomarkers for AD are elevated total tau (T-tau) or phospho-tau (P-tau) levels. CSF levels of T-tau presumably reflect the intensity of neurodegeneration. There is no consensus whether any tau phosphorylation sites are specific for AD and not found in other tauopathies (10). Elevated CSF T-tau is also found in vascular dementia (VAD) (11) and Creutzfeldt-Jakob disease (CJD) (12). Thus, while useful, both CSF Aβ and tau levels have limitations in the differential diagnosis of dementia (13, 14). It remains a challenge to identify an “ideal” biomarker for AD that is directly linked to the primary mechanism of the disease and which can be employed to monitor the disease progression.

Although LR11 has a single transmembrane domain, it is endoproteolytically cleaved near the plasma membrane C-terminus, so that low levels of a large (~250kD) soluble LR11 N-terminal piece (LR11s) can be observed in conditioned media from three different human cell lines, including NT2 cells (neurogenic human embryonal carcinoma cells), BON cells, a pancreatic neuroendocrine tumor cell line (15) and SH-SY5Y human neuroblastoma cells (16). Therefore, we hypothesized that LR11 might be secreted into the CSF and reduced in patients with AD. To test this hypothesis, we examined LR11 levels by western blot in lumbar CSF from mild to moderate AD patients (average MMSE = 24) and ventricular CSF of autopsy-confirmed AD cases and compared with CSF from age-matched healthy controls and non-AD dementias as neurological controls.



The diagnosis of probable AD was established according to the National Institute of Neurological and Communicative Disorders and Stroke and Alzheimer’s Disease and Related Disorders Association (NINCDS-ADRDA) criteria (17). Cognitive status was examined by multiple measures including MMSE (18). Lumbar CSF samples were collected from two different research groups by lumbar puncture under standardized conditions and aliquots frozen at −80°C until used. The first group included 26 subjects (AD, n=13; age-comparable cognitively intact controls, n=13) enrolled at the University of California, San Diego AD Research Center site. MMSE scores for the AD group were mean 24 (range 17–28), compared with mean 29 (range 27–30) for the control group (Table 1). The second group included 17 AD patients with serial CSF samples collected at the UCLA AD Research Center. In this group, the second CSF was collected 6 month after the first. The stability of our measures (LR11, sAPP and ApoE) were investigated in these serial samples from AD patients. To assess the utility of LR11 as a biomarker relative to Aβ42 and tau, we increased sample numbers from the first group (to AD, n=19; age-comparable cognitively intact controls, n=18) and measured T-tau, P-tau and Aβ42 levels. For all subjects, LR11, sAPP and ApoE levels were measured using Western blots at UCLA. CSF tau and Aβ42 were assessed by the Luminex xMAP system.

Table 1
Clinical charecteristics of sample donors


Postmortem CSF samples were collected from autopsy-confirmed AD (n = 10), non-AD neurological controls (n = 5) and age-matched healthy individuals (n = 5) based on autopsy reports from the UCLA AD Research Center, (Dr. H. Vinters Neuropathology). For the pathological diagnoses of AD, plaque density was assessed using the CERAD criteria (19) and neurofibrillary tangles were evaluated by the Braak and Braak criteria (20). Three types of plaques were identified and counted and are described as follows: 1) Diffuse plaques: neuropil deposition of finely granular material on Bielschowsky-stained sections. 2) Dense core plaques: neuropil deposition of compact argyrophilic material, on Bielschowsky-stained sections. 3) Neuritic plaques: identified by the presence of dystrophic neurites, arranged radially forming a discrete spherical lesion averaging about 30 mm in diameter (21, 22). Neuritic plaques were counted on tau immunostained sections. Plaque counts were normalized and expressed as number of counts/mm2. The number of each type of plaque was also characterized according to the CERAD rating scheme of none, sparse (1–5 per 3100 field), moderate (6–15 per 3100 field), or frequent greater than 15 per 3100 field) (19, 22). The score of the neocortical region with the highest count was used as the overall score for each subject (Table 2). CERAD criteria and Braak stage (20) were combined to give an estimate of the likelihood that AD pathological changes underlie dementia using the NIA-Reagan criteria (23). Autopsy-confirmed AD stage was typically intermediate (CERAD moderate plaques and Braak stage III/IV). DLB was diagnosed according to the pathological criteria of Kosaka (24). Ventricular CSF was collected during autopsy and aliquots frozen at −80° C until used. AD patients were 83.7 ± 10.2 years old (mean ± S.D). The postmortem interval was 18.9 ± 10.4 hours (Table 1).

Table 2
Description of Senile Plaque Densities, Neurofibrillary Tangles and other Pathological Characteristics of autopsy-based samples


Western blotting was performed as described previously (25). In brief, 50 µl of CSF was electrophoresed on 6% Tris-Glycine gels, and Western blots stained with anti-LR11 (1:1000, BD Biosciences, San Jose, CA) monoclonal antibody followed with goat anti-mouse secondary at 1: 50,000 for 1 hour and developed using chemiluminescence (Supersignal, Pierce, Rockford, IL) at 1:40. α-Secretase-cleaved amyloid precursor protein (sAPPα) was detected by 6E10 antibody (1:2000, Signet Labs. Inc., Dedham, MA). After stripping immunoblots, β-Secretase-cleaved amyloid precursor protein (sAPPβ) was detected by sAPPβ polyclonal rabbit antibody (1:1000, Covance Development Services Company, Berkeley, CA) followed with goat anti-rabbit secondary antibody at 1: 100,000 for 1 hour. ApoE was detected by monoclonal mouse ApoE antibody (1:1000, Chemicon, Temecula, CA). Band intensities were scanned and quantified with densitometric software (Molecular Analyst II, Bio-Rad, Hercules, CA) and expressed as arbitrary units. Quantification was carried out blind to diagnosis.


Human SH-SY5Y neuroblastoma cells were maintained in Dulbecco’s modified Eagles medium (DMEM) supplemented with 2 mM L-glutamine. 5 × 105 cells were plated on 6-well plates and grown to 80% confluence at 37°C in a humidified 5% CO2 atmosphere incubator. Cultured media were collected for Westerns. Cultured cells were placed on ice, washed and scraped into cold PBS and 3,000 rpm microfuge pellets were dissolved in lysis buffer with protease and phosphatase inhibitors, sonicated, incubated (4°C, 30 min.), and centrifuged (14,000 rpm, 10 min). Supernatants were used for Westerns.


Stability of CSF analyte levels was assessed by Pearson correlation coefficients of serial measures six months apart and by paired t-tests on six-month change in CSF levels. Between groups differences in postmortem CSF levels were assessed by ANOVA followed by Tukey-Kramer post hoc tests. Bivariate receiver operating characteristic curves (ROC curves) were constructed using the method of Pepe, et al (26). All statistical analyses were performed with StatView 5.0 software except for the ROC curves and related statistics, which were calculated using the package ROCR (27) and the statistical programming language R.



Hamper et al reported that a soluble form of LR11 was secreted into conditioned medium of human NT2 and BON cells. The molecular mass of soluble LR11 appeared slightly smaller than that of membrane-bound ~250kD full-length LR11 form, in which the LR11 fragment was about 10 kDa less than the membrane-fraction form (15). Consistent with this report, we found that soluble LR11 was also present in cultured medium from human SH-SY5Y neuroblastoma cells (Fig 1A) and also in human CSF (Fig 1B). LR11s in cultured media and in human CSF were slightly smaller than the form found in membrane fractions on 6% gels, suggesting that LR11 could be secreted into culture media or human CSF and detected by western blot with LR11 antibody.

Fig. 1
LR11 was secreted into culture medium from SH-SY5Y cells and into CSF in human brain


To determine whether CSF LR11 is stable over time in AD patients, we examined LR11 from serial CSF samples obtained 6 months apart in a cohort of AD patients (n = 17). Western blotting showed no LR11 level differences between baseline first and second samplings in CSF from AD patients (p = 0.81, Fig 2A). A high correlation between first and second samples of LR11 was observed (r = 0.92, p<0.0001, Fig 2B), suggesting that LR11 is relatively stable within a 6 month time frame in established AD patients. The relative levels of sAPPα (p = 0.80), sAPPβ (p = 0.78) and ApoE (p = 0.65) also did not show significant differences between baseline and second sampling after a 6 month interval. Similarly, good correlations between first and second CSF samples were found for sAPPα (***p < 0.0001, r = 0.97, Fig 2C), sAPPβ (***p = 0.001, r = 0.72, Fig 2D) and ApoE (***p = 0.001, r = 0.78, Fig 2E).

Fig. 2
Stability of LR11 in CSF of AD patients


To determine whether there was any alteration of LR11 protein levels in the CSF of patients with AD, we first compared LR11s protein levels in subjects with probable AD to cognitively healthy controls by Western blotting using a monoclonal antibody against LR11. The specificity of our anti-LR11 was well characterized in vitro by siRNA to LR11 (2) and in vivo using LR11 knockout mice (16). Our results indicated that LR11 levels were significantly decreased in AD patients compared to the normal controls (*p = 0.03) (Fig 3A, B). This result is consistent with previous reports that LR11 levels were significantly decreased in LOAD brain (1, 6, 28). To further confirm this results, we increased sample numbers for each group (to Control n = 18, AD n = 19) and re-ran/re-analysed western blots for LR11 and also measured CSF Aβ42, P-tau and T-tau in this group. Mean LR11 (*p = 0.038) levels remained statistically significantly different between AD and controls in the expanded sample (Table 3). Aβ42 (**p = 0.003), T-tau (*p = 0.046) and P-tau (*p = 0.036) also showed significant differences between AD and controls (Table 3), suggesting these AD cases were typical with respect to the "established" mild AD biomarkers.

Fig. 3
LR11 and sAPP levels in CSF in patients with early AD were significantly decreased, and correlated with sAPP, but not ApoE
Table 3
Summary statistics for Comparing Means of LR11, Ab42, tau, P-tau in the expanded AD case, normal control series

We used ROC curves to characterize the potential discriminant utility of LR11, Aβ42, T-tau and P-tau using the combined sample of 18 controls and 19 AD cases. Aβ42 was the most effective univariate discriminator of AD versus normal control in our data, with an area under the ROC curve (AUC) of 0.789, compared with 0.661 for LR11. Adding T-tau or P-tau to a bivariate discriminant model with Aβ42 did not substantively improve the model as measured by AUC, only increasing the AUC to 0.793. In contrast, adding LR11 increased the AUC to 0.865 (p = 0.011). The Aβ42/LR11 ROC curve cutoff that correctly identifies 90 percent of the cases (sensitivity = 0.90) also correctly identifies 81 percent of the controls (specificity = 0.81, Fig. 5).

Fig. 5
Combining predictors for classification using the area under the receiver operating characteristic curve

Because LR11 functions as a neuronal sorting protein that binds APP and regulates APP processing to decrease Aβ production in cultured cells (2, 28), we investigated whether there was any change in sAPP in the CSF of human subjects and its correlation with LR11. The results showed that sAPPβ was significantly decreased in AD patients compared to controls (*p = 0.02) (Fig 3C), sAPPα had a trend decrease (p=0.06, data didn’t shown), consistent with several earlier reports (29, 30). The reduced sAPPα (p=0.0004, r = 0.64, data not show) and sAPPβ (p<0.0001, r = 0.72) levels significantly correlated with levels of the APP binding partner, LR11 (Fig 3E).

ApoE is involved in lipid transport and cholesterol homeostasis as a major component of brain lipoproteins. ApoE4 allele is a major risk factor for LOAD (31) and LR11 is a member of the low density lipoprotein receptor (LDL-R) family reported to interact with ApoE (32, 33). Therefore, we investigated CSF ApoE levels and their possible correlation with LR11 in these subjects. Consistent with previous reports (34), ApoE levels in CSF did not show any significant difference between AD and controls (p = 0.54, Fig 3E). Further, no correlation between ApoE and LR11 was observed (p = 0.46, r = 0.15, Fig 3F).

LR11, but not ApoE were significantly decreased in postmortem CSF of autopsy-confirmed patients with AD

To further confirm the observation that CSF LR11 is decreased in AD patients, we studied postmortem CSF of autopsy-confirmed patients with moderate AD. The results showed that LR11 levels in postmortem CSF of patients with AD were significantly diminished when compared to normal controls or patients with non-AD dementias (Fig 4A, B, p < 0.05). Again, ApoE did not show any difference in these three groups (Fig 4A, C). These results are comparable to those obtained with lumbar CSF from probable AD patients (Fig 3).

Fig. 4
LR11, but not ApoE levels in postmortem CSF of autopsy-confirmed AD patients were significantly decreased


In this study, we reported that LR11 protein can be detected and measured in CSF and that levels are significantly reduced in CSF of patients with mild to moderate AD compared to age-matched controls. This reduction was confirmed in postmortem CSF autopsy-proven AD cases, but not in non-AD dementias such as LBD, multiple system atrophy (MSA) and VAD. Perhaps not surprisingly for an APP binding protein, LR11 significantly correlated with sAPPα and sAPPβ. Despite being a LDL family member that can bind ApoE, LR11 levels did not correlate with ApoE. These findings are consistent with a primary role for LR11 as a neuronal sorting protein rather than as significant CNS ApoE receptor.

While the genetic association of LR11 with LOAD remains controversial, LR11 deficits with reductions in LR11 mRNA and protein have been a consistent finding LOAD, but not early onset familial AD cases in which overproduction of Aβ42 was known to be due to presenilin or APP mutations. This suggests that LR11 loss does not occur simply secondary to pathology and might occur at very early disease stages and even prior to diagnosis. Here we found that decreased LR11 in CSF occurred at a relatively early stage (in patients with an average MMSE score of 24), and was further confirmed in autopsy-proven AD with Braak stage III–IV. Since reduced LR11 levels have been observed in a subgroup of individuals with MCI (7), LR11 deficits in CSF might be detectable in MCI or even earlier AD stages in a subset of LOAD at risk patients Combining LR11’s essential function in trafficking APP and regulating Aβ production, these data strongly suggest that CSF LR11s might be a useful biomarker for LOAD.

LR11 contains a vacuolar protein sorting 10 protein domain (vps10p) involved in protein transport between the plasma membrane, endosomes and late Golgi compartments (33, 35, 36). Increased LR11 significantly alters the sorting and trafficking of APP to the recycling Golgi and early endosomal compartments which results in a decrease in Aβ production via the amyloidogenic pathway (1, 37). In addition, it has been reported that LR11 also sorts APP to intracellular protein complexes (retromers) that traffic APP away from α and β secretase (38, 39). Retromer trafficking dysfunction can lead to increased APP in the late endosome, an organelle where BACE activity and Aβ production are maximized (40, 41). Reductions of sAPP (including α-and β-sAPP) in CSF of AD patients have been reported and initially proposed as a diagnostic marker for AD (29, 30, 42). However, sAPP deficits have not been widely studied or used as diagnostic markers in the clinic. In this study, sAPP, including sAPPα and sAPPβ were reduced in the CSF of AD patients. Notably, LR11 levels significantly correlated with those of sAPP. It is possible that this correlation occurs as a result of the binding of LR11 with APP and regulation of its processing. These results might provide one potential explanation for the sAPP changes in the CSF of AD patients.

Considering that LR11 is a member of the ApoE receptor family, LR11 could be influenced by ApoE in CSF and vice versa. However, ApoE levels in CSF did not differ between AD and controls, and also didn’t correlate with LR11 levels. Any role for LR11 in CNS ApoE metabolism remains hypothetical.

In summary, this study demonstrates that soluble LR11 is significantly reduced in CSF of early AD patients, and correlated with reductions in sAPP, but not ApoE. Reduced LR11 in CSF was confirmed in autopsy- proven AD cases with Braak stage III–IV, but not in non-AD dementias such as LBD, MSA and VAD. LR11 mRNA is down-regulated in lymphoblasts and protein levels are reduced in cortical and hippocampal neurons from LOAD but not FAD patients (4, 6). This suggests that LR11s protein deficits might be detectable in plasma, but our attempts to measure plasma LR11 failed and any relationship with more accessible blood mRNA levels needs to be explored. Taken together, this study provides preliminary evidence that LR11 might be a potential CSF biomarker for sporadic but not familial AD. In our sample, Aβ42 was the best single CSF predictor of AD. Adding LR11 to a discriminant function with Aβ42 did improve sensitivity and specificity (AUC changes from 0.789 to 0.865, p = 0.011), while adding T-tau or P-tau did not. These are preliminary results and without a validation sample. Since LR11 expression is sensitive to dietary omega-3 fatty acids (16), it is not surprising that LR11 is not as closely connected to diagnosis as CSF Aβ42.

The stability of LR11 in CSF suggests that it may be used to monitor therapeutic effects of AD treatment. This would be particularly true in the case of drugs expected to work by modulating CNS LR11 expression, such as the omega-3 fatty acid, docosahexaenoic acid (16). Due to the limited non-AD dementia sample size used here, CSF LR11’s potential as a diagnostic marker for AD should be further investigated and combined with other biomarkers with both larger sample sets including MCI or pre-clinical cases. For example, it is possible that measuring LR11 in MCI alone or in combination with Aβ would help to predict which patients with MCI are at highest risk for progression to AD.


This work was supported by NCCAM AT3008, NIA AG13471, P50 AG005131, P50 AG16570 and the Brotman Foundation of California. Dr. Harry V. Vinters supported in part by the Daljit S. and Elaine Sarkaria Chair in Diagnostic Medicine.


Disclosure: The authors report no conflicts of interest.

The statistical analysis conducted by Drs. Steven D. Edland & Qiu-Lan Ma


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