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Published in final edited form as: Neurobiol Aging. 2016 Mar 21;42:217.e7–217.e13. doi: 10.1016/j.neurobiolaging.2016.03.009

Mutation analysis of the MS4A and TREM gene clusters in a case-control Alzheimer’s disease data set

Mahdi Ghani a, Christine Sato a, Erfan Ghani Kakhki a, J Raphael Gibbs b, Bryan Traynor c, Peter George-Hyslop a,d, Ekaterina Rogaeva a
PMCID: PMC8985522  NIHMSID: NIHMS940294  PMID: 27084067

Abstract

Genome wide association studies have identified an association between Alzheimer’s disease (AD) and common polymorphisms in the MS4A and TREM loci (each containing a cluster of homologous genes) and should be thoroughly investigated for the presence of potentially functional variations. We conducted a mutation analysis by next generation sequencing of 15 genes within the MS4A and TREM gene clusters; and catalogued rare coding variants detected in a North American data set of 210 cases and 233 controls. Investigation of the 5 homologues genes in the TREM locus revealed potentially damaging rare variants in TREM2, TREML1, TREML2, and TREML4. In agreement with a previous report, we observed a significant enrichment of TREM2-damaging missense substitutions in cases (N 1⁄4 9; 4.2%) compared with controls (N1⁄42; 0.9%; p 1⁄4 0.010; after Yates’ correction p 1⁄4 0.022). Among known AD-associated TREM2 substitutions, we detected p.R47H, p.D87N, and p.H157Y affecting both TREM2 isoforms (NM_018965 and NM_001271821). In addition, we identified 2 cases with novel TREM2 variants (p.L205P and p.G219C), which mapped only to the isoform NM_001271821 at the C-terminus. Investigation of the MS4A gene cluster revealed that potentially damaging missense substitutions and loss-of-function variants were twice as frequent in controls (N 1⁄4 19; 8.2%) than cases (N 1⁄4 9; 4.3%), generating a nominally significant result (p 1⁄4 0.047; after Yates’ correction p 1⁄4 0.07). Validation of our observation in large data sets might address the question whether such variants could contribute to the protective effect of the minor alleles of Genome wide association study- significant single nucleotide polymorphisms at the MS4A locus.

1. Introduction

Genome wide association studies (GWASs) have identified a link between late-onset Alzheimer’s disease (AD) and common single nucleotide polymorphisms (SNPs) in >20 loci (Ghani and Rogaeva, 2014). Apart from the APOE-ε4 allele with an odds ratio (OR) w4, GWAS hits have revealed only a modest effect with ORs of >0.5 for protective or <2 for risk alleles. However, it is possible that rare functional variations could contribute to the GWAS signals and might have bigger effect sizes than the tagging top-significant SNPs. Indeed, recent targeted sequencing of 8 well-confirmed genes detected by GWASs showed that AD cases were significantly enriched (3.1-fold) with nonsynonymous substitutions compared with controls (p 1⁄4 0.002), whereas there was no difference in synonymous variants (Vardarajan et al., 2015).

Some disease-associated SNPs detected by GWAS are located in gene-rich regions with high linkage disequilibrium, which should be thoroughly investigated for the presence of functional mutations, especially within homologous gene clusters. For instance, genome wide sequencing revealed an association between AD and a TREM2 SNP (rs75932628; p.R47H; risk allele frequency 1⁄4 0.0063; p 1⁄4 2 10 12; OR 1⁄4 2.9; Guerreiro et al., 2013; Jonsson et al., 2013), whereas one of the top-significant SNPs (rs9381040) detected by a mega-meta-analysis of GWASs (w74,000 individuals) is located nearby the homologous gene TREML2 (Lambert et al., 2013). Moreover, a recent meta-analysis of w36,000 subjects suggested that the GWAS signals at TREML2 and TREM2 at the chr6p21.1 locus are independent of each other and revealed a common TREML2 substitution (rs3747742; p.S144G) protecting against AD (p 1⁄4 9 10 5) (Benitez et al., 2014). Notably, the ClinVar database does not have any reports of deleterious variants in TREML2, whereas various damaging variations are described for TREM2, including stop mutations (p.E14X, p.Q33X, p.W44X, and p.W78X), frameshift mutations (p.G90Vfs and p.A105Rfs), a splice mutation (NM_018965:c.482þ2T>C), a deletion (NM_018965.3:c.40þ3_40þ5del), and several substitutions (p.R47H, p.V126G, p.D134G, p.H157Y, and p.K186N).

Another example of an AD-associated gene-rich linkage disequilibrium block is at the chr11q12 locus containing GWAS-significant SNPs at the 30UTR (rs610932) and upstream (rs983392) of MS4A6A (NM_152852.2) (Hollingworth et al., 2011; Lambert et al., 2013), as well as downstream of MS4A3 (rs474951; NM_006138) and upstream of MS4A4A (rs1562990; NM_024021Antunez et al., 2011; Lambert et al., 2013; Perez-Palma et al., 2014). These homologous genes encode the membrane-spanning 4A (MS4A) gene family implicated in the immune response (Liang and Tedder, 2001). Increased MS4A6A expression was associated with higher Braak scores in AD brains (Karch et al., 2012; Martiskainen et al., 2015), but no particular mutation in this locus has been functionally evaluated. Recent investigation of MS4A6A revealed a rare potentially functional SNP (rs138650483) predicted to affect splicing of transcript NM_152852 or lead to a missense substitution in the other transcripts (e.g., NM_022349 and NM_001247999) (Vardarajan et al., 2015).

The main purpose of the present study was a comprehensive mutation analysis of the homologous gene clusters at the MS4A and TREM loci by next generation sequencing of a North American case-control AD data set to catalog rare variants with potential risk or protective effects.

2. Materials and methods

2.1. Participants

Written informed consent was obtained from all participants in accordance with the ethics review board. Targeted sequencing of the MS4A and TREM gene clusters was conducted for a Canadian data set that included 210 AD cases (mean age 73 ` 7.3; 50.4% women) and 53 controls (mean age 80.3 ` 3.6; 62.3% women). Of note, the same data set was part of the study investigating 8 AD genes (Vardarajan et al., 2015) that did not include homologous genes within the TREM and MS4A loci. In addition, all rare coding variants across both loci were obtained from whole exome-sequencing data of 180 controls from the National Institutes of Health (NIH; mean age 79.6 ` 9.4; 41.6% women), in total providing us data for 233 controls.

2.2. Sequencing and analyses

At the MS4A locus (Fig. 1A), we sequenced MS4A1 (Entrez Gene: 931), MS4A2 (Entrez Gene: 2206), MS4A3 (Entrez Gene: 932), MS4A4A (Entrez Gene: 51338), MS4A6A (Entrez Gene: 64231) [previously reported (Vardarajan et al., 2015)], MS4A5 (Entrez Gene: 64232), MS4A6E (Entrez Gene: 245802), MS4A7 (Entrez Gene: 58475), MS4A12 (Entrez Gene: 54860), MS4A13 (Entrez Gene: 503497), and MS4A14 (Entrez Gene: 84689). At the TREM locus (Fig. 1B), we sequenced TREM2 (Entrez Gene: 54209), TREML1 (Entrez Gene: 340205), TREML2 (Entrez Gene: 79865), and TREML4 (Entrez Gene: 285852).

Fig. 1.

Fig. 1.

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Regions included for targeted sequencing of the MS4A and TREM gene clusters. Roche NimbleGen SeqCap EZ Designs-custom technology was applied to target the MS4A(A) and TREM (B) gene clusters. Genomic regions subjected to deep sequencing are shown by fragmented black bars. The linkage disequilibrium structure (D′ values) for the Caucasian population (CEU) is presented beneath the genomic regions.

Targeted sequencing was performed for the entire regions of interest using the Roche NimbleGen SeqCap EZ Designs-custom as previously described (Vardarajan et al., 2015). On average, we had 16,174,244 reads per sample with 98.5% perfect index reads and 88.7% !Q30 bases. For the whole exome sequencing, the DNA samples were enriched using TruSeq technology (version 1.0) and paired-end sequenced on a HiSeq2000 sequencer according to the manufacturer’s protocol (Illumina, San Diego, CA, USA). Sequence alignment and variant calling were performed against the reference human genome (UCSC hg19) using the Burrows-Wheeler Aligner (Li and Durbin, 2009) and Genome Analysis Toolkit (DePristo et al., 2011; Van der Auwera et al., 2013). Variant calling was done by the Picard software (http://picard.sourceforge.net/index.shtml). Reliably called variants were identified after removing those with DP <30, GQ <20, QD <2.0, MQ <40.0, FS >60, HaplotypeScore >13.0, MQRankSum < 12.5, and ReadPosRankSum < 8.0. Variants were annotated using the ANNOVAR program (Wang et al., 2010) and checked if they have a potentially damaging effect on protein function with either the Sorting Tolerant From Intolerant’ (SIFT) algorithm (http://sift.jcvi.org/) or Polyphen-2 programs. Conservation scores were evaluated with the GERPþþ program (Davydov et al., 2010) implemented in ANNOVAR.

We searched for rare coding variants with minor allele frequencies less than 5% in our controls and not more than 1% in the general population of the 1000 Genomes project, the Exome Aggregation Consortium or NHLBI Exome Sequencing Project Exome Variant Server (Table 1 and Supplementary Table). Where DNA was available, the detected rare variants were validated by Sanger sequencing. All 16 investigated variants in 22 subjects were confirmed, demonstrating the high quality of the obtained genotypes (Fig. S1 Supplementary Material). To assess the distribution of potentially deleterious coding variants among cases and controls, our mutation analysis was supplemented with analyses implemented in the computational tool at Microsoft Research (http://research.microsoft.com/en-us/um/redmond/projects/MSCompBio) (Castagnola et al., 2015; De Moor et al., 2009) that calculates for each variant Fisher’s exact test p-values, pooled p-values, which is based on considering marginal counts of contingency tables as random variables (Carlson et al., 2009), as well as false-positive discovery rates (FDR; Benjamini and Hochberg, 1995) and q-values (the FDR-analog of p-value; Storey, 2003) to address multiple testing for individual variants. In addition, we applied the GraphPad 1-tailed c2 test with Yates’ correction to compare the burden of variants among cases and controls for TREM2 and the MS4A locus (http://www.graphpad.com/quickcalcs/).

Table 1.

Rare potentially deleterious coding variants identified at the TREM and MS4A loci among North American AD patients (N = 210) and controls (N = 233).

Chr Location dbSNP138 Ref Alt Gene Transcript Exon Nucleotide Amino acid change Function
6 41117594 rs138237630 A T TREML1 NM_178174 6 c.T684A p.D228E Nonsynonymous
  41121999 rs201565463 G A TREML1 NM_178174 1 c.C28T p.L10F Nonsynonymous
  41126346 . C A TREM2 NM_001271821 4 c.G655T p.G219C Nonsynonymous
  41126387 . A G TREM2 NM_001271821 4 c.T614C p.L205P Nonsynonymous
  41127543 rs2234255 G A TREM2 NM_018965 3 c.C469T p.H157Y Nonsynonymous
  41129133 rs142232675 C T TREM2 NM_018965 2 c.G259A p.D87N Nonsynonymous
  41129178 . G C TREM2 NM_018965 2 c.C214G p.L72V Nonsynonymous
  41129252 rs75932628 C T TREM2 NM_018965 2 c.G140A p.R47H Nonsynonymous
  41162204 rs115991880 G T TREML2 NM_024807 3 c.C744A p.S248R Nonsynonymous
  41166063 rs147506354 C A TREML2 NM_024807 2 c.G160T p.V54F Nonsynonymous
  41196683 rs373300218 C G TREML4 NM_198153 2 c.C295G p.L99V Nonsynonymous
  41204295 . T C TREML4 NM_198153 5 c.T578C p.L193P Nonsynonymous
11 59829992 rs140838251 G A MS4A3 NM_006138 3 c.G208A p.G70S Nonsynonymous
  59857929 rs79741566 T G MS4A2 NM_000139 3 c.T307G p.W103G Nonsynonymous
  59861473 rs138180929 G T MS4A2 NM_000139 6 c.G574T p.G192X Stopgain
  59940500 rs138650483 C T MS4A6A NM_001247999;
NM_15285		 7; 8 c.G736A;
c.651þ1G>A		 p.V246M Nonsynonymous;
splicing
  59947385 rs532381110 T - MS4A6A NM_152852 4 c.201delA p.A67fs Frameshift deletion
  60064779 rs145442198 C A MS4A4A NM_024021 4 c.C254A p.T85K Nonsynonymous
  60105214 . G C MS4A6E NM_139249 2 c.G148C p.V50L Nonsynonymous
  60160173 . A T MS4A7 NM_206939 6 c.A562T p.M188L Nonsynonymous
  60160175 . G A MS4A7 NM_206939 6 c.G564A p.M188I Nonsynonymous
  60160176 rs143858799 C A MS4A7 NM_206939 6 c.C565A p.L189I Nonsynonymous
  60161278 . C T MS4A7 NM_206939 7 c.C667T p.Q223X Stopgain
  60183920 . A C MS4A14 NM_001261828 6 c.A1578C p.K526N Nonsynonymous
  60184404 rs149015522 C T MS4A14 NM_001261828 6 c.C2062T p.Q688X Stopgain
  60184467 rs151183005 C T MS4A14 NM_001261828 6 c.C2125T p.P709S Nonsynonymous
  60233409 rs201245387 A C MS4A1 NM_152866 6 c.A352C p.I118L Nonsynonymous
  60309991 . G T MS4A13 NM_001012417 7 c.403–1G>T . Splicing
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Frequencies were checked at the 1000 Genomes project (general and European populations), as well as at the Exome Variant Server (data release ESP6500si v2) and Exome Aggregation Consortium (data release exac02). Variant effect on protein function was evaluated with the SIFT and Polyphen2 programs, and conservation scores were determined with GERPþþ. Key: AD, Alzheimer’s disease; FDR, false-positive discovery rates.

3. Results

3.1. MS4A locus

We targeted a 492-Kb region on Chr11q12 (Chr11:59611961–60103563/hg18) containing 11 members of the MS4A gene family that share a CD20 domain (Fig. 1A). Potentially damaging missense and loss-of-function variants in MS4A genes were twice as frequent in controls (N 1⁄4 19; 8.2%) than cases (N 1⁄4 9; 4.3%; Table 1). However, this association was only nominally significant (p 1⁄4 0.047; after Yates’ correction p 1⁄4 0.07) and would require assessment in larger data sets.

In MS4A6A, we detected 1 NIH control with the splice and/or missense variant (rs138650483) that was previously reported in 3 AD cases and 1 control (Vardarajan et al., 2015), as well as a frameshift mutation (rs532381110; NM_152852: c.201delA: p.A67fs) in 2 controls and 1 case (Table 1). Loss-of-function variants were also detected in 4 other MS4A genes, including MS4A7: NM_206939: p.Q223X in 1 case, as well as MS4A2:NM_000139: p.G192X, MS4A14:NM_001261828: p.Q688X, and MS4A13:NM_001012417:exon7:c.403–1G>T, each in 1 control. In addition, 2 MS4A7 substitutions affecting the same codon (MS4A7:NM_206939:c.A562T:p.M188L and c.G564A:p.M188I) were identified in 2 cases, whereas 2 controls showed a potentially damaging substitution at the adjacent residue (MS4A7:NM_206939:p.L189I; Table 1). Both the p.M188 and p.L189 residues in the MS4A7 are highly conserved in evolution (GERPþþ scores 3.63 and 2.72, respectively) and among the CD20 domains of other MS4A proteins (Fig. S2 Supplementary Material).

3.2. TREM locus

We targeted a 178-Kb genomic region on Chr6p21.1 (chr6:41166294–41344491/hg18) with 5 homologous genes encoding the TREM receptor family (Fig. 1B). Potentially damaging rare variants were identified in TREML1, TREML2, TREML4, and TREM2 (Table 1). In TREM2, such variants were observed significantly more frequently in cases (N 1⁄4 9; 4.2%) than controls (N 1⁄4 2; 0.9%; p 1⁄4 0.010; after Yates’ correction p 1⁄4 0.022). This association was in part driven by the known AD-related p.R47H mutation that was marginally more frequent in cases (2.4%) than controls (0.4%; pooled p 1⁄4 0.03; FDR 1⁄4 0.36; q-value 1⁄4 0.26).

Among other previously reported TREM2 variants (Guerreiro et al., 2013), we detected p.H157Y and p.D87N (each in a single AD case; Table 1). Notably, p.D87N, which was also reported in 4 of 5 affected members of a large Italian AD family (Ghani et al., 2015), affects a codon that is even more conserved than p.R47 (GERPþþ score 5.51 and 4.56, respectively). Both the p.D87N and p.R47H variants are located in the extracellular domain of TREM2 generating a soluble form of TREM2 that is known to be increased in patients with multiple sclerosis and CNS inflammation (http://grantome.com/grant/NIH/R21-NS088928–01). Although, the p.D87N was reported in a subject with normal cognitive function and a low level of soluble TREM2 in CSF, this is in contrast with the significantly higher CSF levels of soluble TREM2 in p.R47H carriers versus non-carriers (Piccio et al., 2016).

We also identified 2 novel TREM2 variants (NM_001271821:c.T614C:p.L205P and c.G655T:p.G219C), each in a single AD case, affecting only the alternative TREM2 isoform (NM_001271821) lacking exon 4 of the main isoform (NM_018965) but with a longer coding exon at the C-terminus. The p.L205 codon is conserved (GERPþþ score 2); whereas the p.G219 codon is not (GERPþþ score 3.13) and was predicted to be neutral by PROVEAN prediction (Choi and Chan, 2015) but damaging by SIFT (Table 1).

4. Discussion

We conducted mutation analysis of 15 genes within the MS4A and TREM gene clusters and catalogued rare coding variants in 210 AD cases and 233 controls. Of note, our investigation was not intended as a conventional association study because of the modest size of the data set. A well-powered study for rare variants similar to p.R47H in TREM2 (OR 1⁄4 3; allele frequency 0.006) would require w770 matched case-control pairs to provide the desired 80% power to study a common disorder (e.g., AD), as estimated by Quanto (http://biostats.usc.edu/Quanto.html). Nevertheless, our initial statistical analyses did confirm an association of AD with TREM2 and revealed some new observations for follow-up in large data sets.

In agreement with previous studies, we observed a significant enrichment of TREM2-damaging missense substitutions in cases compared to controls, including the p.R47H variant which is a well-confirmed risk factor for AD (Finelli et al., 2015; Korvatska et al., 2015; Malkki, 2015), especially in the European population (Malkki, 2015; Rosenthal et al., 2015). Recently, the p.R47H mutation was associated with reduced binding of TREM2 to APOE (Atagi et al., 2015; Bailey et al., 2015), an increased level of total-tau in cerebrospinal fluid (Lill et al., 2015), and b-amyloid accumulation due to microglia dysfunction (Wang et al., 2015). It remains to be explored if another allele of this codon (NM_018965.3:c.140G>T: p.R47L) reported in the Latino population at the Exome Aggregation Consortium database (frequency <0.1%) is related to AD.

We also found 2 novel TREM2 variants (p.L205P and p.G219C), which were absent in the European population of the 1000 Genomes project and only affect the alternative TREM2 transcript (NM_001271821). All the missense variants described at the ClinVar database pertain to the common part of the TREM2 transcripts (NM_018965 and NM_001271821), with the exception of the NasuHakola related mutation (p.K186N) affecting only the main TREM2 isoform NM_018965 (Paloneva et al., 2002). Identification of transcript-specific substitutions at the C-terminal part of a particular TREM2 isoform suggests further functional studies to delineate a possible isoform-specific AD mechanism, which is also encouraged by the recently identified proinflammatory role of DAP12 in stabilizing the TREM2 C-terminal fragment (Zhong et al., 2015). In addition, the rare p.S248R substitution in TREML2 could be also prioritized for evaluation in large data sets, because it was observed marginally more frequently in controls (N 1⁄4 5; 2.1%) than cases (N 1⁄4 1; 0.5%), which is in the same direction as a protective GWAS-significant TREML2 p.S144G variation (Benitez et al., 2014). Previously, only the APOE-ε2 allele and the APP p.A673T substitution were reported to protect from AD (Benjamin et al., 1994; Jonsson et al., 2012); the presence of protective variants within other AD-associated genes should be carefully evaluated.

For instance, the potentially damaging missense and loss-of-function variants in MS4A genes were 2 times more frequent in our controls than AD cases, generating nominally significant results. It is tempting to speculate that such variants could contribute or explain the protective effect of minor alleles of GWAS-significant SNPs at the MS4A locus (Hollingworth et al., 2011; Lambert et al., 2013). Importantly, high MS4A6A expression has been associated with increased AD risk (Proitsi et al., 2014), suggesting that a low level of MS4A6A expression (e.g., due to loss-of-function variants) could be protective. Notably, the CD20 domain of MS4A genes was implicated in optimal B-cell immune response (Kuijpers et al., 2010); and MS4A1 CD20 positive inflammatory T-cells were reported in chronic brain lesions of patients with Multiple Sclerosis (Holley et al., 2014) suggesting the value of a similar study for AD.

Supplementary Material

Supplementary Table
Figure S1
Figure S2

Acknowledgements

This work was supported by grants from the Canadian Institutes of Health Research (Ekaterina Rogaeva, Peter St George-Hyslop), Wellcome Trust, Medical Research Council, Ontario Research Fund Alzheimer Society of Ontario (Peter St George-Hyslop), and the Intramural Research Programs (Z01-AG000949–02) of the National Institutes of Health, National Institute on Aging (Bryan Traynor).

Footnotes

Disclosure statement

The authors have no actual or potential conflicts of interest.

Appendix A. Supplementary data

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Associated Data

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Supplementary Materials

Supplementary Table
NIHMS940294-supplement-Supplementary_Table.xlsx (17.5KB, xlsx)
Figure S1
NIHMS940294-supplement-Figure_S1.jpg (676.8KB, jpg)
Figure S2
NIHMS940294-supplement-Figure_S2.jpg (177.7KB, jpg)

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