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Polymorphisms in the gene encoding SORL1, involved in cellular trafficking of APP, have been implicated in late-onset Alzheimer’s disease, by a mechanism thought to affect mRNA expression. To search for regulatory polymorphisms, we have measured allele-specific mRNA expression of SORL1 in human autopsy tissues from the prefrontal cortex of 26 Alzheimer’s patients, and 51 controls, using two synonymous marker SNPs (rs3824968 in exon 34 (11 heterozygous AD subjects and 16 controls), and rs12364988 in exon 6 (8 heterozygous AD subjects)). Significant allelic expression imbalance (AEI), indicative of the presence of cis-acting regulatory factors, was detected in a single control subject, while allelic ratios were near unity for all other subjects. We genotyped 7 SNPs in two haplotype blocks that had previously been implicated in Alzheimer’s disease. Since each of these SNPs was heterozygous in several subjects lacking AEI, this study fails to support a regulatory role for SORL1 polymorphisms in mRNA expression.
Sortilin-1 (SORL1, SorLA/LR11; sortilin-related receptor containing LDLR class A repeats) is a sorting receptor that regulates the intracellular transport and processing of the amyloid precursor protein (APP) in neurons. SORL1 co-localizes with APP and regulates its trafficking in endocytic compartments , resulting in APP sequestration in the Golgi and protection from processing into amyloid- peptide (Aβ), the main component of senile plaques in Alzheimer’s disease (AD) .
Previous studies have shown that the expression of SORL1 protein is reduced in brain tissues from individuals with Alzheimer’s disease, which is associated with increased Aβ production . In contrast, SORL1 overexpression significantly reduces total cellular APP and extracellular Aβ . In a genetic association study , 5 SNPs clustered in two distinct regions of SOLR1 (3 SNPs at the 5′ end and 2 SNPs at the 3′ end) were found to be significantly associated with AD in several clinical studies in a North European case-control cohort. The G and T alleles of the synonymous SNPs rs2070045 and rs3824968 respectively, enhanced AD risk alleles with odds ratios of 1.79 and 2.16 . Similar associations were found in independent cohorts  and in a Chinese cohort . Since the candidate SNPs reside in two clusters of mainly intronic SNPs (Fig. 1), Rogaeva et al.  have suggested that these variants affect mRNA expression. Because the SORL1 candidate variants are frequent, SORL1 was hailed as the next significant AD biomarker after APOE4. However, no single SORL1 SNP or haplotype was associated with increased risk for AD in all data sets, and the functional polymorphisms remain unknown. Moreover, Liu et al. were unable to confirm linkage of SORL1 on 11q23.2-q24.2 to AD . A similar negative result was observed in a large Caucasian American case in a more recent study .
To assess the role of SORL1 variants in AD, it is necessary to study the molecular genetic mechanisms. Since nonsynonymous SNPs are rare, we have searched for regulatory polymorphisms affecting transcription and mRNA processing and turnover by measuring allelic mRNA expression in human autopsy brain tissues. Any difference in the mRNA generated from either of the two alleles, termed allelic expression imbalance (AEI), is a strong indicator of the presence of cis-acting factors, genetic or epigenetic . AEI ratios offer a quantitative and robust measure of allelic differences in each individual, one allele acting as the control for the other. We used two synonymous marker SNPs in exons representing the 3′ and 5′ haplotype blocks of SORL1 (Fig. 1) to measure allelic mRNA expression in AD and in control brain autopsy tissues.
Human brain tissues- 26 human autopsy brain tissues were obtained from the polar region of the frontal lobe of patients with histologically confirmed AD and 51 normal prefrontal cortex brain samples from various tissues banks (Ohio State University Neurodegenerative Disease Brain Tissue Repository (Buckeye Brain Bank), Tissue Banks at the University of Maryland). The AD patients were all Caucasians; the average estimated age at onset of AD was 69.9 ± 8.8 years, and the average age at death was 80.3 ± 9.0. Seven out of the 26 AD patients had early onset AD (estimated age at onset less than 65). The controls (subjects that had not been diagnosed as having AD) were from different ethnic origins (31 Caucasians, 7 African Americans, 8 Hispanics, 2 African Americans/Hispanics, and 3 Caucasians/Hispanics) and had died of unknown reasons at average age of 43.4 ± 15.6 years. Genotyping was performed of de-identified specimen, under a local IRB approval.
Four SNPs (rs3824968, rs12364988, rs689021, rs2070045) were analyzed by SNaPshot (Applied Biosciences, Foster City, CA) using primers listed in Supplemental table 1. The detailed method has been published previously . The extended primers, labeled with different fluorescent dyes, were run on an ABI 3730 capillary electrophoresis instrument (Applied Biosciences, Foster City, CA), then analyzed with Gene Mapper 3.0 software . The extension primers were sufficiently separated by capillary electrophoresis to permit simultaneous analysis of rs12364988, rs689021, rs2070045.
Three additional candidate SNPs in SORL1 (rs1699102, rs2282649, rs1010159) were genotyped using a GC clamp allele-specific assay , with three primers for each SNP (Supplemental table 1). The fluorescence melting curves of the amplicons were analyzed on an ABI7000 cycler.
Real-time PCR was performed with the same PCR amplification primers used for SNaPshot analysis of rs3824968, with 10 μl PCR SYBR master mixture (Applied Biosciences, Foster City, CA). The mixtures were run on an ABI 7000 thermocycler, and cycle thresholds (Ct’s) were measured. As an internal control, β-actin was amplified for the same samples. Expression levels were determined by normalizing the measured cyclic threshold to β-actin. The mRNA level was expressed as the difference CtSORL1 – Ctβ-actin  .
Two exonic (synonymous) marker SNPs rs3824968 and rs12364988 were chosen for the measurement of AEI in AD samples; only one marker SNP rs3824968 was used for measurement of AEI in control samples. PCR amplification of DNA and cDNA (see above) was followed by a primer extension reaction using primers listed in Supplemental table 1, and fluorescently labeled dideoxynucleotides. The fluorescent products were run on an ABI 3730 capillary electrophoresis instrument (Applied Biosciences, Foster City, CA) and analyzed with Gene Mapper 3.0 software . Peak area ratios were calculated to measure the relative amount of DNA and mRNA (as cDNA) of the two alleles.
Assuming that the two alleles were present in equal amounts in genomic DNA, measured DNA and cDNA ratios were normalized to the average of genomic DNA ratios using the equation: normalized ratio = measured DNA (or cDNA) ratio/mean of genomic DNA ratio. For genomic DNA, none of the samples significantly deviated from the mean, representing a 1/1 allele ratio.
26 AD human brain tissues were genotyped for the two marker SNPs used subsequently in allelic expression analysis, rs3824968 (a potential risk factor SNP) at the 3′ end (exon34) and rs12364988, located in a 5′ haplotype block of the transcribed gene (exon6) (Fig. 1). We also genotyped 5 additional SNPs; rs1699102, rs2282649, rs1010159, rs689021 and rs2070045 all implicated as potential risk factors in AD  (Supplemental Table 2). For each SNP, we determined minor allele frequency (MAF) and tested for Hardy Weinberg Equilibrium (HWE) (Table 1). All SNPs were in HWE, except for rs12364988 possibly a result of the rather small number of subjects for this analysis. For each SNP pair, we also calculated linkage disequilibrium (LD) (Table 2), showing substantial LD of SNPs rs1699102, rs2282649, rs1010159 and rs2070045 with the marker SNP rs3824968 (3′ haplotype block) and LD of rs689021 with the marker SNP rs12364988 (5′ haplotype block). Moreover, allele frequencies of marker SNPs rs3824968 and rs12364988 were similar to those of the additional 5 candidate SNPs. Therefore, the 2 marker SNPs are suitable for assessing effects of all proposed SORL1 candidate SNPs on mRNA expression. For the control brains, 19 of 51 subjects were heterozygous for the marker SNP rs3824968 and therefore eligible for allelic mRNA expression analysis.
SORL1 mRNA expression was successfully measured in 26 AD human brain tissues and 16 control human brain tissues using quantitative RT- PCR, with β-actin as internal standard. The expression of SORL1 mRNA was significantly more variable than that of β-actin, showing a normalized Ct range (relative to β-actin) of 3.9–8.5. Shown in Supplemental Figure 1, SORL1 mRNA levels varied over a 20-fold range. The mean cycle threshold for SORL1 mRNA (25.9±1.2) indicated a sufficiently robust expression in most tissues analyzed for accurate analysis of allelic mRNA expression ratios. Comparing AD subjects and controls, after normalization to the Ct’s of β-actin, the normalized SORL1 Cts in the controls ranged between 4.88 and 6.33, not significantly different from the AD tissues.
There was no significant correlation between SORL1 mRNA expression and genotype for any of the seven SNPs included in this study in AD subjects. If any effect would have occurred, a much larger sample number is needed, as total mRNA levels are subject not just to cis-acting factors but also, and more prominently, to numerous trans-effects.
The marker SNPs rs3824968 and rs12364988 yielded 11 and 8 heterozygous samples, respectively. The measured peak area ratios (SNaPshot) representing allelic ratios in genomic DNA were 1.71±0.08 (S.D.) and 0.74±0.04, respectively. The ratios did not deviate significantly from the mean in any given sample (<3SD), indicating an absence of copy number variation (although loss of one allele (hemizygocity) would not be detectable by this method). Therefore, all genomic DNA ratios for SORL1 were normalized to 1, as reference standard for mRNA ratios. After normalizing the allelic mRNA ratios to the mean genomic DNA ratio, the A/T allelic mRNA ratios of marker rs3824968 (exon 34) did not deviate significantly from unity (Fig. 2). These results indicate the absence of cis-acting factors on allelic mRNA expression, measured in the region of exon 34.
Use of SNP rs12364988 as a marker SNP, located at some distance in exon 6 (Fig. 1), similarly failed to reveal any expression imbalance, confirming and extending the absence of allelic expression imbalance in heterozygous samples for this SNP, using a 5′ upstream region of the mRNA (Fig. 2). Combined, the absence of AEI in two distinct regions of SORL1 mRNA suggest that alternative splicing or truncation events are unlikely to have occurred as a result of cis-acting factors.
Because rs3824968 and rs12364988 reside in different haplotype blocks and are not in linkage disequilibrium, it is possible that we could have missed AEI in some portion of the mRNA - for example as a result of differential processing - in subjects heterozygous for only one of the two maker SNPs. However, three subjects were compound heterozygotes, and yet each failed to show AEI at both marker SNP sites.
The marker SNP rs3824968 yielded 19 heterozygous samples, of which 16 yielded AEI measurements. The measured peak area ratios (SNaPshot) representing allelic ratios in genomic DNA and cDNA were 1.70±0.18 (S.D.) and 1.68±0.18 (S.D.), respectively. Similar to AD brain tissue results, the A/T allelic mRNA ratios normalized to the mean genomic DNA ratio of marker rs3824968 (exon 34) did not deviate significantly from unity in 15 tissues (Fig. 2). However, one sample showed a large cDNA allelic ratio of 4.9 ± 0.9 (after normalization to gDNA), demonstrating the presence of a robust cis-acting factor (this sample was treated as an outlier and not used for calculating the mean cDNA allelic ratio of the 15 subjects).
Clinical association studies implicate SORL1 variants as an AD risk factor . This potentially important finding must be validated by identifying the polymorphisms responsible for altered SORL1 functions. Because the implicated polymorphisms are frequent but do not include nonsynonymous SNPs that could have affected protein functions, and since low SORL1 expression was associated with AD, we suspected that any genetic variants would affect transcription and mRNA processing, including maturation, splicing, and turnover.
We have applied allelic mRNA expression analysis to SORL1 in prefrontal cortex tissues from AD patients and controls. This brain region is typically involved in late stage AD, and therefore relevant for assessing cis-acting regulatory polymorphisms that may vary from one tissue to another. In a series of previous studies we have demonstrated that allelic mRNA ratios can be measured accurately in human autopsy brain and yield important information on the presence or absence of cis-acting regulatory polymorphisms [11;15;18]. The results of the present study failed to detect any substantial allelic expression imbalance (less than 20% deviation from unity), except in one subject not previously diagnosed with AD. As we had measured AEI in 32 subjects total (70 chromosomes), the frequency of a possible allele causing this substantial expression difference could be as high as 2–3%, but probably much less in this population. Nevertheless, given the potential importance of SORL1 in the etiology of AD, a larger study is needed to establish allele frequency, underlying mechanism (gain or loss of function) and possible clinical relevance.
The absence of AEI in all other subjects strongly argues against a role of the frequent candidate SNPs in mRNA expression. Were any of these SNPs functionally relevant, we would have expected detectable AEI, resulting from several possible mechanisms, for example gene regulation, mRNA processing, and mRNA turnover. However, we cannot exclude the possibility that these events can occur in other brain regions.
While the present study was relatively small, the group of 26 AD subjects, and 16 with AEI measurements, it was sufficient to address possible functionality of the frequent SORL1 candidate SNPs. For each of the 7 candidate SNP analyzed, there were several subject heterozygous for one or more of them (Tables 1, Supplemental table 2), yet no AEI was present. Measuring allelic mRNA expression ratios obviates the influence of trans-acting factors and mitigates problems with post-mortem degradation, assuming both alleles degrade at similar rates. In several previous studies where we had detected AEI, we were able to identify regulatory polymorphisms consistent with these results [5;18] . The results therefore argue strongly against any of the tested SNP to affect transcription, mRNA processing and turnover in the tissues studied.
Measuring total mRNA levels (relative to β-actin), we did not find any association between mRNA levels and genotype, as expected because mRNA levels are subject to multiple trans-acting factors, and post-mortem degradation. The lower SORL1 levels in AD subjects relative to controls were offset by lower β-actin levels that we used for normalization. Possibly, mRNA levels were generally lower in these AD tissues.
The SNPs analyzed in this study have shown haplotypic association with AD in the Northern European data sets . Four SNPs at the 3′ end of SORL1 showed overlapping haplotypes of CTT at rs1699102, rs3824968, rs2282649 and TTC at rs3824968, rs2282649, rs1010159 associated with Alzheimer’s disease in the Caucasian data set. These haplotypes were also present in our study, indicating that AEI could also not have arisen from a combination of SNPs as suggested by the haplotype associations. Since two clinical studies failed to reveal an association of SORL1 with AD  , the question remains open as to whether and to what extent SORL1 variants contribute to disease risk.
Our analysis argues against regulatory mechanisms but leaves open a number of possible molecular genetic mechanisms that still need to be explored. First, we cannot exclude that alternative splicing has been affected by a cis-acting polymorphism, leading to mRNA variants that have equal turnover, thereby failing to result in detectable AEI. However, inspection of EST databases did not reveal the presence of substantial splice variants. Neither of the two exonic SNPs is associated with exonic splicing enhancer sites (using the online RESCUE-ESE tool). Second, any polymorphism, including synonymous and nonsynonymous SNPs, and SNPs in the 3′ and 5′ untranslated regions in mRNA, can affect the rate of translation and thus protein levels, by several mechanisms including altered codon usage or other regulatory effects. For example, the two selected marker SNPs rs3824968 and rs12364988, while being synonymous, are present in the mature mRNA and could alter translation. Measuring SORL1 protein levels in association with genotype will require a larger sample cohort and precisely specified brain regions because protein levels are also subject to trans-acting factors, generating more variability farther downstream of genetic variants in SORL1. Nevertheless, the previous suggestion that SNPs occurring in at least two different clusters of intronic SNPs regulate expression of SORL1 mRNA is not supported by the present study.
mRNA expression in 26 AD brain samples. Cycle threshold were normalized to β-actin, showing Δ cycle thresholds of 5.52±1.03. Cycle thresholds for SORL1 ranged from 24.3 to 29.8.
Sequences of primers used for PCR, SNaPshot and GC clamp genotyping. F: forward primer; R: reverse primer; PEF and PER: extension primers for SNaPshot in the forward or reverse direction, respectively. The small letters indicate mismatches with the w.t. sequence.
Genotyping results of seven candidate SNPs of SORL1 in AD brains samples. AEI ± SD measurements for the heterozygous samples using the two marker SNPs (rs12364988 and rs3824968). Blank cells are missing data. Since the candidate SNPs are frequent, heterozygous subjects were present for each SNP in subjects heterozygous for either one or both indicator SNPs (rs12364988 and rs3824968).
This study was in part supported by NIH, National Institute on Drug Abuse, grant DA022119.
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