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. Author manuscript; available in PMC: 2018 Sep 1.
Published in final edited form as: Neurobiol Aging. 2017 Jun 3;57:170–177. doi: 10.1016/j.neurobiolaging.2017.05.020

Transcriptome-wide piRNA profiling in human brains of Alzheimer’s disease

Wenying Qiu 1,#, Xiaoyun Guo 2,3,#, Xiandong Lin 4, Qian Yang 1, Wanying Zhang 1, Yong Zhang 5, Lingjun Zuo 2, Yong Zhu 6, Chiang-Shan R Li 2,7, Chao Ma 1,*, Xingguang Luo 2,7,*
PMCID: PMC5542056  NIHMSID: NIHMS881704  PMID: 28654860

Abstract

Discovered in the brains of multiple animal species, piRNAs may contribute to the pathogenesis of neuropsychiatric illnesses. The present study aimed to identify brain piRNAs across transcriptome that are associated with Alzheimer’s disease (AD). Prefrontal cortical tissues of six AD cases and six controls were examined for piRNA expression levels using an Arraystar HG19 piRNA array (containing 23,677 piRNAs) and genotyped for 17 genome-wide significant and replicated risk SNPs. We examined whether piRNAs are expressed differently between AD cases and controls and explored the potential regulatory effects of risk SNPs on piRNA expression levels. We identified a total of 9453 piRNAs in human brains, with 103 nominally (p<0.05) differentially (> 1.5 fold) expressed in AD cases vs. controls and most of the 103 piRNAs nominally correlated with genome-wide significant risk SNPs. We conclude that piRNAs are abundant in human brains and may represent risk biomarkers of AD.

Keywords: piRNA, brain, Alzheimer’s disease, microarray, transcriptome, differential expression

Introduction

Alzheimer’s disease (AD) is a degenerative brain disorder, affecting millions of people worldwide. Genetic mechanisms underlying the development of AD have been widely explored, including the direct effects of protein-coding genes, e.g., APOE, and the indirect effects of the non-coding RNAs (ncRNAs), e.g., BACEAS (Zuo, et al., 2016a). The ncRNAs include long non-coding RNAs (LncRNAs) and small non-coding RNAs such as miRNAs, piwi-interacting RNAs (piRNAs), siRNAs, snoRNAs and rasiRNAs. In this study, we examined the potential association of piRNAs with AD.

piRNAs are the ncRNAs with 24–32 nucleotides (nt). They exhibit stark differences in length, expression pattern, abundance, and genomic organization from miRNAs (Mani and Juliano, 2013, Zuo, et al., 2016b). They interact with piwi proteins and function as a complex to regulate cellular activities by RNA silencing (Lau, et al., 2006). Most piRNAs are distributed in the mammalian germline cells. In recent studies piRNAs have also been discovered in the brains of multiple species (Iyengar, et al., 2014, Lee, et al., 2011, Perrat, et al., 2013, Rajasethupathy, et al., 2012, Ross, et al., 2014, Weick and Miska, 2014). The amount of piRNAs in the brain is about one-tenth of that in the germline (Dharap, et al., 2011, Lee, et al., 2011, Peng and Lin, 2013, Yan, et al., 2011). There are hundreds of thousands piRNA sequences in each species; however, because piRNAs are poorly conserved even between closely related species (Mani and Juliano, 2013) and are tissue-specific, their distributions in the human brains cannot be predicted from other species or other human tissues. The current study would be the first to investigate the presence of piRNAs in human brains and their potential roles in neurodegenerative diseases.

Numerous lines of evidence indicate that piRNAs carry important functional roles, including suppressing transposon (Mani and Juliano, 2013), preserving genomic integrity (Czech and Hannon, 2016, Stefani and Slack, 2008), remodeling euchromatin and epigenetic programming (Akkouche, et al., 2013, Ross, et al., 2014), regulating translation (Grivna, et al., 2006), regulating target mRNAs (Lee, et al., 2011), modulating mRNA stability (Grivna, et al., 2006), and developmental regulation. The most widely-recognized and well-characterized function of piRNAs is to suppress the activities of transposable elements at genomic and epigenetic levels, suggesting that piRNAs may be involved in the etiological processes of human diseases. The present study aimed to identify the piRNAs associated with AD across transcriptome. Furthermore, we explored whether these AD-associated piRNAs were brain-specific, whether their nearest protein-coding genes were expressed in brains, and whether these genes were related to the APOE expression in brains.

For a decade scientists have scanned the whole genome to search for the risk variants of AD. We reviewed all published genome-wide association studies (GWASs) and whole genome/exome sequencing studies of AD. The results showed associations of 17 variants that were genome-wide significant (1.0×10−295≤p≤9.0×10−9) and replicated across at least two independent studies at single-point level. These 17 variants are located in 11 genes/snRNAs/LncRNAs in eight loci. They are rs6859, rs157580, rs2075650, rs429358+rs7412 (ε2/ε3/ε4) and rs4420638 within APOE cluster (NECTIN2-TOMM40-APOE-APOC1) (Abraham, et al., 2008, Antunez, et al., 2011, Coon, et al., 2007, Feulner, et al., 2010, Harold, et al., 2009, Heinzen, et al., 2010, Kamboh, et al., 2012a, Kamboh, et al., 2012b, Kim, et al., 2011, Lambert, et al., 2009, Li, et al., 2008, Logue, et al., 2011, Meda, et al., 2012, Melville, et al., 2012, Naj, et al., 2010, Nelson, et al., 2014, Perez-Palma, et al., 2014, Ramanan, et al., 2014, Ramirez, et al., 2014, Seshadri, et al., 2010, Shen, et al., 2010, Webster, et al., 2008), rs2279590 and rs9331896 at APOJ (Jun, et al., 2016, Lambert, et al., 2009, Lambert, et al., 2013), rs11218343 at SORL1 (Jun, et al., 2016, Lambert, et al., 2013, Miyashita, et al., 2013), rs10498633 at SLC24A4 (Jun, et al., 2016, Lambert, et al., 2013), rs6656401 at CR1 (Lambert, et al., 2009, Lambert, et al., 2013), rs3865444 at CD33 (Lambert, et al., 2013, Naj, et al., 2011), rs7561528, rs6733839 and rs744373 at LOC105373605 (Antunez, et al., 2011, Hollingworth, et al., 2011, Hu, et al., 2011, Jun, et al., 2016, Kamboh, et al., 2012b, Lambert, et al., 2013, Naj, et al., 2011) and rs10792832 and rs3851179 at RNU6-560P (Harold, et al., 2009, Jun, et al., 2016, Lambert, et al., 2013). Numerous candidate gene studies including ours (Zuo, et al., 2006) supported these GWAS findings. However, the mechanisms underlying SNP-AD associations remain unclear. Here, we examined whether the AD-related piRNAs might mediate these associations, in support of the potential roles of piRNAs in the pathogenesis of AD.

Summary of Materials and Methods

In this pilot study we used prefrontal cortex tissues from the primary brain cohort of 6 AD cases and 6 controls. As a contrast, eight stomach tissue samples were also examined. The samples were examined using the Arraystar HG19 piRNA array (Arraystar, Inc.) that included 23,677 piRNAs. Raw signal intensities were normalized, quality checked, filtered and then log2-transformed. Three piRNAs from the array were examined by qPCR for technical validation. The transformed intensity values were compared between AD cases and controls to identify the piRNAs associated with AD; these values were also compared between control brain tissues and stomach tissues to identify piRNAs “specific” to the brain. The mRNA expression of the nearest genes, within or close to which the AD-associated piRNAs are located, and the density of the proteins encoded by these genes was examined in brain tissues of four other independent auxiliary cohorts, to explore the expression of these genes in the brain. The correlation of expression between APOE and all risk genes in the brain was tested, to examine if the risk genes were related to this most robust and well-recognized AD-associated gene. The 17 genome-wide significant and replicated risk variants for AD were genotyped in our primary cohort (6 AD cases and 6 controls) too. Associations between the genotypes and the expression level of each AD-associated piRNA were analyzed in this primary cohort, to investigate whether these robust risk DNA variants controlled piRNA expression. The details were described in the Supplementary Materials, Methods, Table S1, and Figures S1 and S2. The design of whole study was based on a regulation pathway illustrated in Figure 1.

Figure 1. Illustration for the pathways underlying piRNA-AD association.

Figure 1

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[Solid lines: Directly evidenced by our study; Dash lines: Indirectly evidenced by literatures. ➊ piRNA expression is correlated with the risk SNPs (by eQTL analysis); ➋ piRNAs are hypothesized to be most likely to regulate the expression of the nearest protein-coding genes by sequence complementarity; ➌ mRNA expression of the risk genes is correlated to APOE mRNA expression (by correlation analysis); ➍ mRNA/protein of APOE is expressed in brain (by RNA-Seq, RNA microarray and mass spectrometry-based proteomics microarray analyses); ➎ RNAs/proteins expressed in brain are assumed to have potential brain functions; ➏ many brain functions are assumed to be related to the development of AD; ➐ piRNAs are hypothesized to be related to L1 retrotransposons that are involved in brain functions; ➑ piRNAs are hypothesized to use the transposons to regulate gene expression and cellular function; ➒ mRNAs/proteins of the risk protein-coding genes are expressed in brain (by RNA-Seq, RNA microarray and mass spectrometry-based proteomics microarray analyses); ➓ association between APOE and AD is most robust and widely-recognized; ⓫ many genes have been associated with AD in literatures; ⓬ some genes regulated by piRNAs can control brain functions; ⓭ piRNA expression in brain is detected by microarray analysis; ⓮ some piRNAs can target at brain cells that may be implicated in brain functions; ⓯ piRNAs are associated with AD (by differential expression analysis), which is the main goal of the present study; ⓰ associations between SNPs and AD are identified by GWAS

Results

1. Detection of piRNAs in the brain

Among the 23k piRNAs, 9453 (41%) were detected in human brains. Among the 9453 brain piRNAs, 6853 (73%) were significantly differentially expressed between brain and stomach (1.2×10−14≤p<0.05); and 1251 (13%) were “specific” to brain (i.e., absent in stomach). The three selected piRNAs, including DQ597973, DQ576872 and DQ597479 (Table 1) were well-validated by qPCR.

Table 1.

Top piRNAs significantly differentially expressed between AD cases and controls

piRNA Alias length (nt) Chr Normalized intensity AD vs. Control Brain vs. Stomach Gene
AD Control FC p FC p
With top intensities in AD (intensities>12)
DQ571030 piR-hsa-1281 29 chr19 29291.9 15703.3 1.9 ↑ 0.024 17.1 ↑ 2.2×10−6 C19orf18 B
DQ571029 piR-hsa-1280 27 chr19 28564.7 16838.6 1.7 ↑ 0.031 14.6 ↑ 4.5×10−7 C19orf18 B
DQ571031 piR-hsa-1282 32 chr19 20583.6 11557.8 1.8 ↑ 0.049 18.8 ↑ 7.6×10−6 C19orf18 B
DQ597217 piR-hsa-27492 28 chr11 24283.1 13388.0 1.8 ↑ 0.042 17.6 ↑ 7.3×10−7 GALNT18 B
DQ597216 piR-hsa-27491 26 chr11 24078.7 12986.4 1.9 ↑ 0.037 14.9 ↑ 8.1×10−8 GALNT18 B
DQ597479 piR-hsa-27725 28 chr3 11637.5 5522.6 2.1 ↑ 0.020 14.0 ↑ 1.9×10−6 ANKRD28 B
DQ585095 piR-hsa-15406 30 chr1 9853.0 6558.0 1.5 ↑ 0.032 3.9 ↑ 5.8×10−4 ATAD3B B
DQ576872 piR-hsa-7193 31 chr2 7703.6 3777.0 2.0 ↑ 0.034 6.8 ↑ 2.2×10−5 DOCK10 B
DQ571243 piR-hsa-1580 29 chr11 9655.2 5028.9 1.9 ↑ 0.042 7.0 ↑ 8.7×10−6 to C11orf87 B
DQ597973 piR-hsa-28188 27 chr11 9039.6 4490.8 2.0 ↑ 0.027 7.2 ↑ 3.5×10−6 to C11orf87 B
DQ597974 piR-hsa-28189 28 chr11 8107.7 4113.4 2.0 ↑ 0.031 7.6 ↑ 6.6×10−6 to C11orf87 B
DQ597972 piR-hsa-28187 26 chr11 5615.2 2771.6 2.0 ↑ 0.020 6.5 ↑ 6.1×10−6 to C11orf87 B
With top FC↑ between cases and controls (FC≥2)
DQ576492 piR-hsa-6740 30 chr10 19.0 7.8 2.4 ↑ 0.021 1.1 ↑ 0.809 LINC00837
DQ590835 piR-hsa-21131 28 chr9 210.9 89.0 2.4 ↑ 0.030 5.5 ↑ 3.2×10−5 PTPRD B
DQ574023 piR-hsa-4300 26 chr13 18.7 7.9 2.4 ↑ 0.029 1.1 ↑ 0.675 B3GALTL B
DQ599205 piR-hsa-29476 26 chr1 48.0 22.1 2.2 ↑ 0.004 1.2 ↑ 0.753 KIAA0319L B
DQ598028 piR-hsa-28243 29 chr19 37.0 17.1 2.2 ↑ 0.018 1.7 ↓ 0.468 FLJ25328
DQ573352 piR-hsa-3645 26 chr7 34.4 16.3 2.1 ↑ 0.037 1.1 ↓ 0.884 ABCA13 B
DQ581610 piR-hsa-11139 29 chr17 23.1 10.9 2.1 ↑ 0.019 “Brain” - to EVPLL
DQ599207 piR-hsa-29478 29 chr22 65.6 31.5 2.1 ↑ 0.018 1.6 ↑ 0.215 to ELFN2 B
DQ597479* piR-hsa-27725 28 chr3 11637.5 5522.6 2.1 ↑ 0.020 14.0 ↑ 1.9×10−6 ANKRD28 B
DQ597973* piR-hsa-28188 27 chr11 9039.6 4490.8 2.0 ↑ 0.027 7.2 ↑ 3.5×10−6 to C11orf87 B
DQ597974* piR-hsa-28189 28 chr11 8107.7 4113.4 2.0 ↑ 0.031 7.6 ↑ 6.6×10−6 to C11orf87 B
DQ597972* piR-hsa-28187 26 chr11 5615.2 2771.6 2.0 ↑ 0.020 6.5 ↑ 6.1×10−6 to C11orf87 B
DQ576872* piR-hsa-7193 31 chr2 7703.6 3777.0 2.0 ↑ 0.034 6.8 ↑ 2.2×10−5 DOCK10 B
With top FC ↓ between cases and controls (FC≥2)
DQ579851 piR-hsa-10106 32 chr15 10.8 27.0 2.5 ↓ 0.025 2.1 ↑ 0.050 to PGPEP1L
DQ600318 piR-hsa-30518 26 chr17 14.0 34.7 2.5 ↓ 0.010 “Brain” - LRRC37A3 B
DQ571669 piR-hsa-1963 30 chr17 14.8 34.6 2.3 ↓ 0.025 “Brain” - VPS53 B
DQ586404 piR-hsa-16724 29 chr18 15.7 33.3 2.1 ↓ 0.006 1.6 ↑ 0.234 to GNAL B
With lowest p values between cases and controls and FC↑ (p≤0.010)
DQ591371 piR-hsa-21636 28 chr1 42.7 27.5 1.6 ↑ 0.002 2.0 ↑ 0.012 to NBPF4
DQ580484 piR-hsa-10710 30 chr1 17.6 9.0 1.9 ↑ 0.002 1.2 ↑ 0.448 to TDRD5
DQ577835 piR-hsa-8094 30 chr9 40.4 23.0 1.8 ↑ 0.003 1.5 ↑ 0.055 FAM225B
DQ586113 piR-hsa-16363 29 chr17 12.9 7.5 1.7 ↑ 0.003 “Brain” - to EVPLL
DQ599205* piR-hsa-29476 26 chr1 48.0 22.1 2.2 ↑ 0.004 1.2 ↑ 0.753 KIAA0319L B
DQ580261 piR-hsa-10501 28 chr10 350.2 233.2 1.5 ↑ 0.005 3.3 ↑ 7.6×10−4 NRG3 B
DQ597396 piR-hsa-27133 29 chr11 599.6 346.4 1.7 ↑ 0.007 1.4 ↑ 0.045 to UBASH3B B
DQ597397 piR-hsa-27134 31 chr11 863.9 545.2 1.6 ↑ 0.010 1.6 ↑ 0.011 to UBASH3B B
With lowest p values between cases and controls and FC ↓ (p≤0.002)
DQ575353 piR-hsa-5645 28 chr17 19.0 28.6 1.5 ↓ 0.002 2.2 ↑ 1.0×10−3 LRRC37A B
DQ577904 piR-hsa-8163 30 chr1 12.0 18.3 1.5 ↓ 0.005 2.0 ↑ 0.101 to RABGEF1 B
DQ595753 piR-hsa-25985 29 chr1 11.1 19.9 1.8 ↓ 0.005 “Brain” - SCP2 B
DQ586404* piR-hsa-16724 29 chr18 15.7 33.3 2.1 ↓ 0.006 1.6 ↑ 0.234 to GNAL B
DQ579582 piR-hsa-9851 31 chr22 60.7 91.0 1.5 ↓ 0.006 2.2 ↑ 0.012 POM121L8P
DQ584325 piR-hsa-14547 27 chr15 13.0 21.5 1.7 ↓ 0.009 1.9 ↑ 0.011 to C2CD4B
With locations at or close to AD-related genes
DQ583613 piR-hsa-13893 29 chr6 3694.9 2295.2 1.6 ↑ 0.038 4.2 ↑ 2.3×10−4 to HIST1H4H B
DQ584879 piR-hsa-14621 28 chr15 13.4 8.7 1.5 ↑ 0.011 “Brain” - CYP19A1 B
DQ597214 piR-hsa-27489 27 chr3 117.0 61.7 1.9 ↑ 0.025 3.4 ↑ 9.9×10−3 to PLCH1 B
DQ583911 piR-hsa-14148 30 chr6 16.3 9.5 1.7 ↑ 0.040 “Brain” - to CCR6 B
DQ599147 piR-hsa-29114 31 chr17 699.9 386.3 1.8 ↑ 0.048 3.1 ↑ 1.7×10−3 CTC1 B
DQ600513 piR-hsa-30713 28 chr10 311.9 182.1 1.7 ↑ 0.014 3.5 ↑ 5.1×10−4 DOCK1 B
DQ575353 piR-hsa-5645 28 chr17 19.0 28.6 1.5 ↓ 0.002 2.2 ↑ 1.0×10−3 LRRC37A B
DQ575681 piR-hsa-5959 28 chr11 31.8 47.9 1.5 ↓ 0.029 “Brain” - BACE1 B
DQ574452 piR-hsa-4685 30 chr14 9.0 13.8 1.5 ↓ 0.040 “Brain” - to KCNK10 B
DQ596958 piR-hsa-27248 30 chr15 14.0 21.3 1.5 ↓ 0.039 “Brain” - CYP19A1 B
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B

These genes are expressed in brain; chr, chromosome;

↑, up-regulated; ↓, down-regulated; “Brain”, brain-specific expression in constrast to stomach. FC, fold-changes; p, p values from t-test; AD, Alzheimer’s disease; “to”, proximate to.

*

appears at least twice in this table.

2. Differential expression of piRNAs between cases and controls (Figures 2 and S3, and Tables S2 and 1)

Figure 2. The differential expression between cases and controls.

Figure 2

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[X-axis: Fold-change; Y-axis: −log10(p); Red points: the differentially expressed piRNAs with 1.5-fold change and p< 0.05]

The mean log2-transformed normalized intensity of expression of all 9453 piRNAs was 7.00±2.91 (mean ± SD; range: 3.16–18.4) in AD cases, and 7.02±2.90 (2.87–18.4) in controls. 103 piRNAs with length of 26–32nt were nominally differentially expressed between cases and controls (FC>1.5; p<0.05; without correction) (Figure 2; Table S2). The mean transformed normalized intensity of these 103 piRNAs was 6.77±3.57 (3.16–14.8) in AD cases, and 6.30±3.43 (2.88–14.0) in controls. Among the 103 risk/protective piRNAs, 81 were up-regulated and 22 were down-regulated in cases in contrast to controls. Among the 103 piRNAs, 24 were “specific” to brain (i.e., no significant expression in stomach), 69 were expressed in brain higher than in stomach (1.0<FC<18.8), and 10 were expressed in brain lower than in stomach (1.1<FC<2.4). Among the 103 piRNAs, 100 piRNAs map to genomic locations that are located within or close to 66 protein-coding genes, and three piRNAs map to unknown locations. 42 piRNAs map to 37 protein-coding genes, and two map to ncRNA genes. Among these 103 piRNAs, 56 piRNAs are intergenic, proximate to 32 protein-coding or ncRNA genes; 50 of these protein-coding genes that 100 piRNAs map or are proximate to are expressed in brains (data not shown). 45 are located in piRNA clusters. 29 piRNA clusters are located in intergenic regions, consistent with earlier literature (Zuo, et al., 2016b). 66% of these 50 protein-coding brain genes have been related to neurodegenerative or neuropsychiatric disorders (Table S2).

9 piRNAs had log2-transformed normalized intensities > 13 (i.e., > 9000 before transformed). The top five piRNAs with highest intensities in cases were DQ571030, DQ571029 and DQ571031 at C19orf18 (on chr19) (Figure S3), and DQ597217 and DQ597216 at GALNT18 (on chr11). They were also the top five with highest intensities in controls, and the top five with highest FC (14.6≤FC≤18.8) in brain compared to stomach (Table 1).

14 piRNAs were expressed with >2 FCs in cases compared to controls; the top five were DQ590835 at PTPRD (chr9), DQ576492 at LINC00837 (chr10), DQ574023 at B3GALTL (chr13), DQ599205 at KIAA0319L (chr1), and DQ598028 at FLJ25328 (chr19). 4 piRNAs were expressed with >2 FCs in controls compared to cases; they were DQ579851 at chr15, DQ600318 at chr17, DQ571669 at VPS53 (chr17), and DQ586404 at chr18 (Table 1).

14 piRNAs were significantly differentially expressed between cases and controls with p<0.01. The five most significant ones with higher FCs in cases were DQ591371 proximate to NBPF4 on chr 1, DQ580484 proximate to TDRD5 on chr 1, DQ577835 at FAM225B on chr 9, DQ586113 proximate to EVPLL on chr 17, and DQ599205 at KIAA0319L on chr 1 (0.002≤p≤0.004). The five most significant ones with lower FCs in cases were DQ575353 at LRRC37A on chr 17, DQ577904 proximate to RABGEF1 on chr 1, DQ595753 at SCP2 on chr 1, DQ586404 proximate to GNAL on chr 18, and DQ579582 at POM121L8P on chr 22 (0.002≤p≤0.006) (Table 1).

Two piRNAs, including DQ599147 at CTC1 (FC=1.8, p=0.048) and DQ597974 near C11orf87 (FC=2.0, p=0.031), expressed in significantly higher levels in cases than controls (Table S2) replicated previous findings (Roy, et al., 2017).

Some genes that the AD-associated piRNAs are located within or near to have been reported to be associated with AD or its biomarkers, including BACE1, CYP19A1, CTC1, LRRC37A, CCR6, KCNK10, HIST1H4H, C1orf174, DOCK1, and PLCH1. Over 540 studies have reported the associations between BACE1 and AD, 9 studies for CYP19A1, 6 studies for CTC1, and at least one study for each of other genes. (Table S2)

3. Gene expression in brains

Among the 73 risk genes, 52 (71.2%) were expressed in human brains (Table S2). Among the 38 genes of strongest associations with AD risk, as listed in Table 1, 27 (71.1%) were expressed in human brains (Table 1). The expression of all of the 27 genes was significantly correlated with APOE expression in at least one brain region (2.9×10−39≤p<1.8×10−4; Table S3).

4. The piRNA expression correlated with SNPs

eQTL analysis showed that most AD-associated piRNAs were nominally correlated with the genome-wide significant risk SNPs (p<0.05; Table 2). After Bonferroni correction (α=5×10−4), the correlations of rs429358 (p=2.8×10−4) and rs4420638 (p=3.4×10−4) at APOE cluster with DQ581734, rs2075650 (p=3.3×10−4) at APOE cluster with DQ592330, rs4420638 (p=2.3×10−4) at APOE cluster with DQ600318, rs2279590 (p=2.7×10−4) at APOJ with DQ597397, and rs7561528 (p=9.2×10−5) at LOC105373605 with DQ574023 remained significant. In view of the small sample size, we may have missed some potentially significant correlations, so we listed more modest correlations in Table 2 (p<8×10−3). Most eQTL signals occurred in APOE cluster and APOJ loci, and all 5 variants at the LncRNA LOC105373605 or snRNA RNU6-560P presented modest eQTL signals (Table 2). The results presented above are also illustrated in Figure 1.

Table 2.

The expression of piRNAs correlated with the genome-wide significant replicated risk SNPs for AD (p<0.008)

Gene (chr) LOC105373605 (chr2) APOJ (chr8) SORL1 (chr11) RNU6-560P (chr11) SLC24A4 (chr14) NECTIN2-TOMM40-APOE-APOC1 (chr19) CD33 (chr19)
SNPs rs6733839 rs744373 rs7561528 rs2279590 rs9331896 rs11218343 rs3851179 rs10792832 rs10498633 rs2075650 rs429358 rs4420638 ε2/ε3/ε4 rs3865444
In cases and controls
DQ571669 VPS53 3.7×10−3 4.7×10−3
DQ573352 ABCA13 7.3×10−3
DQ573721 - 1.1×10−3
DQ574452 to_KCNK10 6.0×10−3
DQ577835 FAM225B 3.0×10−3
DQ579851 to_PGPEP1L 8.8×10−4 2.9×10−3
DQ581441 to_CHST1 3.5×10−3
DQ581734 TYSND1 2.8×10−4 3.4×10−4
DQ583613 to_HIST1H4H 6.7×10−3
DQ584325 to_C2CD4B 2.2×10−3
DQ584637 AGAP1 1.2×10−3
DQ584879 CYP19A1 7.5×10−3
DQ584936 to_METTL14 3.5×10−3
DQ592330 to_ELFN2 3.3×10−4
DQ594768 to_CHEK2P2 3.5×10−3
DQ597396 to_UBASH3B 6.1×10−3
DQ597397 to_UBASH3B 2.7×10−4 6.0×10−4
DQ597401 to_VN1R10P 3.1×10−3 5.4×10−3
DQ597402 to_VN1R10P 4.1×10−3 5.9×10−3
DQ597403 to_VN1R10P 3.4×10−3 4.6×10−3
DQ597886 to_ILF2 7.5×10−3
DQ598571 to_CHST1 4.8×10−3
DQ600318 LRRC37A3 7.0×10−3 2.3×10−4
In controls
DQ574023 to_B3GALTL 9.2×10−5
DQ576492 LINC00837 3.6×10−3
DQ577835* FAM225B 5.1×10−3
DQ584879* CYP19A1 6.4×10−3
DQ586113 to_EVPLL 3.0×10−3
DQ590261 ANKRD20A19P 1.2×10−3 1.2×10−3
DQ597109 to_HIST1H4H 5.7×10−3
DQ597397* to_UBASH3B 3.8×10−3 4.6×10−3 4.6×10−3
DQ597402* to_VN1R10P 5.4×10−3 5.4×10−3
DQ598028 FLJ25328 2.9×10−3
DQ599147 CTC1 6.0×10−3
DQ599205 KIAA0319L 5.9×10−3
In cases
DQ597973 to C11orf87 7.3×10−3
DQ597402* to_VN1R10P 7.2×10−3
DQ598571* to_CHST1 3.8×10−3
DQ581441* to_CHST1 4.9×10−3
DQ600513 to C11orf87 6.4×10−3
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The correlations with p<α=5×10−4 (=0.05/103 piRNAs) were bold; “to”, proximate to;

*

, appears at least twice in this table.

Discussion

The present study showed that piRNAs are abundant in human brains and may contribute to the risk for AD. Although most differential expressions did not survive the conservative Bonferroni correction for multiple comparisons, the potential roles of piRNAs in AD cannot be ignored considering that this was a pilot screening study with small sample sizes (Hebert, et al., 2013). Many piRNAs were brain-“specific”, and their nearest protein-coding genes were expressed in brains and related to the APOE expression in brains. Further, the expression of these piRNAs were controlled by the most robust risk DNA variants. Together, these findings support a functional role of piRNAs in the pathogenesis of AD. We illustrate possible mechanisms underlying these findings in Figure 1.

The piRNAs in the brain usually demonstrate unique biogenesis patterns with a predominantly nuclear localization (Rajasethupathy, et al., 2012). piRNAs located within genes or from the intergenic regions may modulate the stability and translation of the mRNAs of the proximate genes (Grivna, et al., 2006, Lee, et al., 2011, Mani and Juliano, 2013). However, unlike miRNAs and siRNAs, piRNAs are not derived from the dsRNA precursors, which makes it difficult to derive the unique location of each piRNA on the genome. Because piRNAs are short, they might correspond to multiple positions on the genome. Across transcriptome, only 5 percent of piRNAs can be mapped to protein-coding genes (Brennecke, et al., 2007); however, among the AD-associated piRNAs identified in this study, 41% are enriched in the protein-coding genes, suggesting a strong correlation among these genes, piRNAs and AD. Sequences of the AD-associated piRNAs are complement to or close to these protein-coding genes, and thus, the piRNAs are most likely to target and regulate these nearest genes by sequence complementarity (Roy, et al., 2017).

Furthermore, we found that 71.2% of these protein-coding genes were expressed in human brains, and their expression levels were all significantly correlated with APOE, the most robustly and well-recognized AD risk gene. 66% of these protein-coding brain genes have already been associated with neurodegenerative or neuropsychiatric disorders including AD, e.g., BACE1, CYP19A1, CTC1 and HIST1H4H, suggesting that they are potentially the direct biological targets for the AD-associated piRNAs to regulate the development of AD. Some of these genes have been implicated in the extensively-studied etiological pathways leading to AD. For example, BACE1 has been implicated in the “Alzheimer’s disease” pathway (www.genome.jp/kegg); CYP19A1 has been implicated in the “Metabolism of lipids and lipoproteins” pathway (www.reactome.org); CTC1 has been implicated in the “Oxidative phosphorylation” pathway (www.genome.jp/kegg); and HIST1H4H has been implicated in the “Telomere maintenance” pathway (www.reactome.org).

We observed that the expression of many nominally AD-related piRNAs was correlated with the AD-risk DNA variants, suggesting that these piRNAs might mediate SNP-AD associations. In particular, all of the five genome-wide and replicated risk variants at LncRNA and snRNA had nominal or even significant regulatory effects on piRNAs, which may in part explain SNP-AD associations at non-coding loci.

Numerous piRNAs are produced from the disruption of transposons in the genome (Halic and Moazed, 2009, Sai Lakshmi and Agrawal, 2008); that is, most piRNAs overlap with the transposons or transposon remnants in sequences (Brennecke, et al., 2007). piRNAs selectively target and silence the RNAs transcribed from transposons (Brennecke, et al., 2007, Gunawardane, et al., 2007), perhaps to balance or to maintain the fitness of the genome. Experimental data supported this proposition. Mili- and Miwi-2 null mice have been found to have increased activity of retrotransposons, which suggests that piRNAs could protect the genome from deleterious transposon insertions to preserve genomic integrity (Stefani and Slack, 2008). Disruption in the piRNAome may lead to uncontrolled transposition with destabilizing genomic and cellular effects (Dharap, et al., 2011, Mani and Juliano, 2013). It has been posited that the Piwi/piRNA complex uses the transposons to regulate a large group of gene expression and cellular functions (Mani and Juliano, 2013), a plausible mechanism to underscore the associations between piRNAs and AD identified in this study. Experimental data suggest that piRNAs can inhibit transposons at either genomic or epigenetic levels. The restriction of transposons by piRNAs has been demonstrated by the up-regulation of transposons as a result of mutations of the Piwi/piRNA complex.

Evidence suggests that Piwi/piRNA complex may be involved in modulating the development of dendritic spines (Lee, et al., 2011). Some Piwi/piRNA complex target Astrotactin, a protein critical to neuronal migration (Adams, et al., 2002). Some Piwi/piRNA complex potentially regulate genes to control other nervous system functions (Lee, et al., 2011). These mechanisms may also underlie piRNA-AD associations.

Another clue regarding the functions of piRNA relates to the discovery of the L1 retrotransposons in the human, mouse and rat brains. In the brains, the L1 retrotransposons are involved in neuronal differentiation, heterogeneity, and somatic mosaicism (Coufal, et al., 2009, Muotri, et al., 2005). Some piRNAs and retrotransposons co-exist in the brains. These piRNAs regulate L1 retrotransposons and their mutants elevate retrotransposon expression in the brains. The co-existence of piRNA and retrotransposons might play important roles during brain development and in maintaining functional integrity of the adult brains, and in the development of AD.

piRNAs are unevenly distributed across the genome. We found that many AD-associated piRNAs were clustered. Although individual piRNA sequences are rarely conserved, the genomic locations of the piRNA clusters are usually conserved across species (Aravin, et al., 2006, Girard, et al., 2006, Lau, et al., 2006). More studies are clearly warranted to investigate the roles of these clusters in the development of AD.

Supplementary Material

supplement

Highlights.

  • This study first profiled piRNA expression in human brains with Alzheimer’s disease

  • 9453 piRNAs were detected in human brains

  • 103 piRNAs were nominally differentially expressed between cases and controls

  • Among the genes that the AD-associated piRNAs were located within or close to, 71.2% were expressed in human brains

  • Most AD-associated piRNAs were nominally correlated with the genome-wide significant risk SNPs

Acknowledgments

This work was supported by the China Human Brain Bank Consortium and in part by National Natural Science Foundation of China (81373150; 81271239; 81202371; 81201057; 81171091 and 91632113), the IBMS/CAMS Dean’s Fund (2011RC01), the CAMS Neuroscience Center Special Fund (#2014C01), the CAMS Innovation Fund for Medical Sciences (CIFMS), the Natural Science Foundation and Major Basic Research Program of Shanghai (16JC1420500, 16JC1420502), the National High Technology Research and Development Program (“863” Program) of China (2013AA020106), Shanghai municipal commission award (#20124109), National Institute on Drug Abuse (NIDA) grant K01 DA029643, and National Institute on Alcohol Abuse and Alcoholism (NIAAA) grants R21 AA021380, R21 AA020319 and R21 AA023237. We thank for Prof. Haifan Lin’s helpful comments.

Footnotes

Conflict of Interest: The authors declare no conflict of interest.

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