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Non-coding variants in VAMP2 and SNAP25 affect gene expression: potential implications in migraine susceptibility

Abstract

Migraine is a common and complex neurological disease potentially caused by a polygenic interaction of multiple gene variants. Many genes associated with migraine are involved in pathways controlling the synaptic function and neurotransmitters release. However, the molecular mechanisms underpinning migraine need to be further explored.

Recent studies raised the possibility that migraine may arise from the effect of regulatory non-coding variants. In this study, we explored the effect of candidate non-coding variants potentially associated with migraine and predicted to lie within regulatory elements: VAMP2_rs1150, SNAP25_rs2327264, and STX1A_rs6951030. The involvement of these genes, which are constituents of the SNARE complex involved in membrane fusion and neurotransmitter release, underscores their significance in migraine pathogenesis. Our reporter gene assays confirmed the impact of at least two of these non-coding variants. VAMP2 and SNAP25 risk alleles were associated with a decrease and increase in gene expression, respectively, while STX1A risk allele showed a tendency to reduce luciferase activity in neuronal-like cells. Therefore, the VAMP2_rs1150 and SNAP25_rs2327264 non-coding variants affect gene expression, which may have implications in migraine susceptibility. Based on previous in silico analysis, it is plausible that these variants influence the binding of regulators, such as transcription factors and micro-RNAs. Still, further studies exploring these mechanisms would be important to shed light on the association between SNAREs dysregulation and migraine susceptibility.

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Background

Migraine is a common disabling multifactorial neurological disease with a heritability estimated between 30–60% [1, 2]. Migraine affects about 15% of the population and is three times more prevalent in women [2]. This type of primary headache typically causes recurrent attacks of unilateral throbbing pain along with other symptoms, such as photophobia, nausea, and/or vomiting [3]. There are two common migraine subtypes defined by the presence or absence of aura [3]. Rare monogenic forms of familial hemiplegic migraine are caused by variants in genes related to neurotransmission (CACNA1A, ATP1A2, and SCN1A) [1]. However, many migraine cases remain without a genetic cause probably because common forms of migraine result from the contribution of multiple variants with small effects at several loci [4,5,6]. Most of the genes associated with migraine are involved in the metabolism, transport, and reception of neurotransmitters, possibly causing an imbalance among them, and consequently altering the synaptic function [7].

Studies indicate that migraine possibly results from an altered state of neuronal excitability driven by enhanced responsiveness to stimuli or abnormal processing of sensory information [1, 8]. Regulation of the expression of genes involved in the release of neuropeptides/neurotransmitters may have implications in migraine susceptibility [9,10,11]. Additionally, neurovascular mechanisms may underlie migraine pathophysiology, as shown by a recent genome-wide study, in which risk variants were enriched in both vascular and central nervous system tissues [12, 13].

Following the first hypothesis, our group explored the association of variants in genes belonging to the synaptic vesicle machinery and neurotransmission pathway through gene candidate association studies [14,15,16]. From the candidate variants identified in these studies, we have previously performed an in silico analysis of non-coding variants using scoring methods and epigenetic databases, which resulted in the selection of three variants within regulatory elements: VAMP2_rs1150 (3′ UTR), predicted as a target of a miRNA; SNAP25_rs2327264, (distal enhancer), expected to lie within a binding site of a transcription factor; and STX1A_rs6951030 (proximal enhancer), predicted to affect the binding affinity of zinc-finger transcription factors and disturb TBL2 gene expression [17]. To note that VAMP2, SNAP25 and STX1A genes encode presynaptic proteins that belong to the SNARE complex (soluble N-ethylamine-sensitive factor attachment protein receptor), which is involved in plasma membrane fusion and neurotransmitter release during synaptic transmission [18]. From these non-coding variants, at least VAMP2_rs1150 was previously associated with attention deficit hyperactivity disorder (ADHD) and working memory in addition to migraine susceptibility [16, 19].

In this study, we explored for the first time the effect of these three non-coding variants on gene expression, which may have implications in migraine susceptibility or other complex diseases related to SNARE dysfunction.

Methods

Cell culture

HEK293T cells (ATCC) were cultured in high glucose in Dulbecco’s modified Eagle medium (DMEM, GlutaMAX™) supplemented with 10% fetal bovine serum (FBS) and 1% antibiotic/antimycotic (Gibco, ThermoFisher Scientific, Waltham, MA, USA). SH-SY5Y cell line (DSMZ) was grown in DMEM GlutaMAX™/Ham’s F-12 nutrient mixture supplemented with 10% FBS and 1% antibiotic/antimycotic (Gibco, ThermoFisher Scientific, Waltham, MA, USA). HEK293T and SH-SY5Y cells were maintained at 37 °C in a humidified 5% CO2 atmosphere.

Plasmids cloning

The plasmids were obtained by cloning the genomic sequences (length ~ 1500 bp) flanking the variants VAMP2_rs1150 (c.*1590 T > C) and SNAP25_rs2327264 (c.-64 + 6629 T > C) into the pGL3-promoter vector (Promega, Fitchburg, WI, USA). VAMP2 exon 5 (3' UTR) and SNAP25 intron 1 (enhancer) regions were PCR amplified from genomic DNA (Table 1), and PCR products were purified with Zymoclean Gel DNA Recovery Kit (Zymo Research, Irvine, CA, USA) and genotyped by Sanger sequencing. PCR products were inserted into the pGL3-promotor vector downstream of the firefly luciferase gene by Gibson Assembly (New England Biolabs, Ipswich, MA, USA) (Table 1).

Table 1 Primer sequences used for plasmids’ cloning

The genomic sequence (length of ~ 1500 bp) flanking STX1A_rs6951030 (c.30 + 691A > C) was obtained through the NZYTech Gene Synthesis service (NZYTech, Lisbon, Portugal). STX1A intron 1 (promotor) was cloned into the pGL3-basic (Promega, Fitchburg, WI, USA) upstream of the firefly luciferase gene by restriction with Nhel/Xhol (ThermoFisher Scientific, Waltham, MA, USA) enzymes.

Sequences were modified by site-directed mutagenesis to generate the alternative alleles (normal or risk allele) using the Q5 Site-directed mutagenesis kit (New England Biolabs, Ipswich, MA, USA), according to the manufacturer’s protocol. The following primer pairs were used to introduce c.*1590C > T (VAMP2_rs1150 normal allele), c.-64 + 6629 T > C (SNAP25_rs2327264 risk allele), and c.30 + 691A > C (STX1A_rs6951030 risk allele) variants: forward primer 5′-GTGCTGTGTTtTAGACCCCCC-3′ and reverse primer 5′-CCCCACCTCCAGCATCTC-3′; forward primer 5′-ATATGGTTCAcATTACTCAAAGATG-3′ and reverse primer 5′-CAACAACAGCAAAGAAGAG-3′; and forward primer 5′-TTCGGGCAGCcCTGGCTGGCG-3′ and reverse primer 5′-AGCCCGAAGGTGGATAGGTG-3′, respectively. All constructs were verified by Sanger sequencing.

Cell transfection and dual-luciferase reporter gene assays

HEK293T and SH-SY5Y cells were transiently transfected for 48 h with pGL3-promotor-SNAP25, pGL3-promotor-VAMP2, pGL3-basic-STX1A, pGL3-control, pGL3-promoter, or pGL3-basic plasmids (150 ng; 96-well plate) (Promega, Fitchburg, WI, USA) using DreamFect Gold (OZ Biosciences, Marseille, Provence-Alpes-Cote d'Azur, France), according to the manufacturer’s protocol. Co-transfection with the pRL-CMV renilla vector (15 ng; 96-well plate) (Promega, Fitchburg, WI, USA) was used as an internal control for transfection efficiency in a 10:1 molar ratio (firefly:renilla). Dual-luciferase assays were performed in 96-well white plates (CELLSTAR® plates—µClear® bottom; Greiner Bio-One, Kremsmünster, Austria) containing 100 µL medium (without 1% antibiotic/antimycotic) with 1.5 × 104 HEK293T cells/mL or 2.5 × 104 SH-SY5Y cells/mL. After 48 h post-transfection, Synergy Mx Microplate Reader (Agilent, Santa Clara, CA, USA) was used to measure the luciferase activity with the Dual-Luciferase Reporter System (Promega, Fitchburg, WI, USA), according to the instructions recommended by the manufacturer.

Statistical analysis

Statistical significance of the difference in the luciferase activity between normal and risk alleles was determined using unpaired student´s t-test; the threshold of statistical significance was set at p < 0.05. Statistical analysis was performed using the IBM SPSS Statistics 26.0 software (IBM, Armonk, NY, USA). Data was expressed as mean ± standard deviation (SD) considering at least four independent experiments and five replicates per experiment.

Results

Recently, variants in the SNARE genes VAMP2, SNAP25 and STX1A have been studied as potential risk factors in several neurological disorders, including migraine [15, 16, 20, 21]. Thus, following our previous in silico analysis, in which the non-coding variants VAMP2_rs1150 (3’ UTR), SNAP25_rs2327264 (distal enhancer), and STX1A_rs6951030 (proximal enhancer) were predicted to have high regulatory potential, we decided to confirm the effect of these candidate variants on gene expression through reporter gene assays [17]. After cloning the DNA sequences surrounding the variants, plasmids were transfected into two cell lines, one non-neuronal (HEK293T) and one neuronal-like (SH-SY5Y), and the luciferase gene reporter activity measured by a luminescence assay. The luciferase activity in transfected cells is approximately proportional to the mRNA levels, being used as a tool to study gene expression at the transcriptional level [22].

We compared the luciferase activity driven by the different alleles: VAMP2_rs1150 G-allele (risk allele) versus A-allele (normal allele), SNAP25_rs2327264 C-allele (risk allele) versus T-allele (normal allele), and STX1A_rs6951030 C-allele (risk allele) versus A-allele (normal allele). We found that VAMP2_rs1150 G-allele significantly decreased luciferase activity by 24% and 31% compared to the A-allele in HEK293T and SH-SY5Y cells (Fig. 1A, p = 0.022 and p = 0.005, respectively), respectively. On the other hand, SNAP25_rs2327264 C-allele significantly increased luciferase activity by ~ 20% compared to the T-allele only in SH-SY5Y cells (Fig. 1B, p = 0.006). There were no significant differences between SNAP25_rs2327264 alleles in HEK293T cells (Fig. 1B, p = 0.2999). Therefore, risk alleles in VAMP2 and SNAP25 seemed to have opposite effects on the regulation of gene expression in neuronal-like cells. STX1A_rs6951030 C-allele showed a tendency to reduce luciferase activity (~ 40%) in SH-SY5Y cells, when compared with the A-allele, but did not reach statistical significance in either cell line (Fig. 1C, p = 0.900 and p = 0.335, respectively).

Fig. 1
figure 1

Reporter gene assays showed that allelic differences at VAMP2_rs1150 (A) and SNAP25_rs2327264 (B), but not at STX1A_rs6951030 (C), influenced luciferase reporter activity. Firefly luciferase activity was normalised to renilla luciferase activity and is shown as a fold change to that of pGL3-promotor or pGL3-basic (n ≥ 4 for each group) for HEK293T and SH-SY5Y cells. Data is presented as the mean ± SD. ns, not significant, * p < 0.05, ** p < 0.01, unpaired student´s t-test

Discussion

In this study, we demonstrated that the potential regulatory variants VAMP2_rs1150 and SNAP25_rs2723264 have indeed an impact on gene expression. VAMP2_rs1150 G-allele (risk allele) significantly decreased luciferase activity, while SNAP25_rs2723264 C-allele (risk allele) increased luciferase activity when compared to the normal alleles in SH-SY5Y cells. Luciferase activity was not significantly affected by SNAP25_rs2723264 in HEK293T cells, probably because gene regulation is tissue and cell-specific. According to the Protein Atlas (https://www.proteinatlas.org/; accessed 03 January 2023), SNAP25 expression is 46.6 and 0.3 normalized transcript per million (nTPM) in SH-SY5Y and HEK293T cells, respectively. Thus, it is likely that regulators targeting this enhancer are poorly expressed in HEK293T cells, explaining the lack of differences in the luciferase activity between alleles in this cell line. On the other hand, the expression of VAMP2 and possibly of its gene regulators is more uniform and broader between cell types (37.8 and 36 nTPM in SH-SY5Y and HEK293T cells, respectively). Amongst the three genes, STX1A is the one with the lowest expression in these cell lines (22.5 and 3.9 nTPM in SH-SY5Y and HEK293T cells, respectively), which may explain the lack of statistical significance in our assays. Nevertheless, the results of the reporter gene assays provide evidence to support the effect of at least two non-coding variants here analysed. In addition, it would be interesting to explore the synergistic effect between these common variants and other variants located within the same regulatory elements.

Interestingly, our functional data partially support our previous in silico analysis [17]. VAMP2_rs1150 was our top candidate variant, with 7 scoring methods indicating deleteriousness, while SNAP25_rs2723264 and STX1A_rs6951030 were predicted to have similar potential to be deleterious (3 scoring methods, differing by a few decimals in the sum parameter) [17].

A previous study from our group has shown a risk association of VAMP2_rs1150 G-allele with migraine (p = 0.024) that was not statistically significant after Bonferroni correction (OR = 1.36; p = 0.068) [15]. Nevertheless, our reporter gene assay point to a functional role of this variant in gene expression. VAMP2_rs1150 expression quantitative trait loci (eQTLs) data suggested that the variant targets VAMP2 expression in human brain tissues, while bioinformatics tools predicted the variant region as a target of hsa-mir-5010-3p micro-RNA [17]. Similarly, SNAP25_rs2327264 CT genotype showed a borderline association with migraine susceptibility (OR = 2.28; p = 0.003) [15]. However, no allele association was identified likely due to the small sample size, particularly the number of CC genotype subjects (N = 12). In our study, the reporter gene assays showed that SNAP25_rs2327264 C-allele influences gene expression. No eQTLs data suggested that SNAP25_rs2327264 targets its expression, yet this region was expected to be a target of ONECUT2 transcription factor [17]. Regarding STX1A_rs6951030, this variant was significantly associated with migraine (OR = 1.52; p = 0.006) in a previous case–control study in the Portuguese population [16] but not in a recent GWAS study [23]. In addition, it was reported an association between migraine and a haplotype that includes STX1A_rs6051030 [20, 21]. Nevertheless, our previous bioinformatics study predicted STX1A_rs6951030 (proximal enhancer) to affect the binding affinity of transcription factors from the zinc-finger protein family, namely ZNF423, and eQTLs data suggested that it disrupts TBL2 gene expression in brain tissues [17]. TBL2 gene encodes transducin (beta)-like 2 (TBL2), an ER transmembrane protein involved in stress-signalling and cell survival through protein synthesis regulation [24, 25]. As mentioned before, our functional assays were not able to support STX1A_rs6951030 impact on gene expression, possibly due to a low expression of STX1A and its gene regulators in the cell lines tested.

The genes studied here encode for synaptobrevin-2 (or vesicle-associated membrane protein-2; VAMP2), 25-kD synaptosome-associated protein (SNAP25), and syntaxin-1A (STX1A) proteins; all belonging to the SNARE complex that controls the docking of synaptic vesicles and potentiates presynaptic membrane fusion [18]. These proteins also interact with other elements of the exocytotic machinery and ion channels involved in the regulation of presynaptic action potentials and neurotransmitter release [18]. Several studies indicated that abnormal expression, risk genetic variants, or dysfunction of SNARE proteins are present in various neurological diseases, possibly contributing to abnormal neurotransmission and synaptic dysfunction [18]. In line with our findings, VAMP2 expression was found to be reduced in animal models or patients' brain tissues of Parkinson [26], epilepsy [27], and dementia [28]. As proposed in vascular dementia, VAMP2_rs1150 risk allele may have a potential role in synaptic decline and vascular alterations [28]. In these same studies, SNAP25 and STX1A expression was decreased, in opposition to our results of the SNAP25_rs2327264 risk allele. Nevertheless, our previous study did not find data suggesting that SNAP25_rs2327264 target its expression [17], so we cannot speculate further. Migraine is considered a brain state of altered excitability, therefore, changes in SNARE gene expression might alter the control of the synaptic vesicle exocytosis and consequently unbalance the release of the neuropeptides and neurotransmitters [9].

Interestingly, an in vitro study demonstrated that 4‐aminopyridine (potassium channel inhibitor) increased the rate and extent of exocytosis, and desynchronised neurotransmitter release by prolonging local calcium availability in cellular models of VAMP2 pathogenic variants [29]. This compound has been indicated for the symptomatic treatment of multiple sclerosis, cerebellar ataxias, and Lambert–Eaton and congenital myasthenic syndrome [30]. Thus, suggesting that 4‐aminopyridine would be a highly promising treatment for patients with SNAREopathies presenting an impaired neurotransmitter release.

In conclusion, our reporter gene assays confirmed the effect of two non-coding variants in the SNARE genes VAMP2 and SNAP25. In addition to the previous in silico analysis of regulatory elements, these results suggest that these non-coding variants may have implications in migraine susceptibility. Therefore, it would be interesting to understand if unbalancing the expression of genes encoding components of the synaptic vesicle machinery may disrupt the exocytosis of neuropeptides/neurotransmitters acting on the nervous system and blood vessels. Although our findings provide novel insights into the impact of non-coding variants and gene regulation of SNARE proteins, further studies are needed clarify the link between SNAREs dysregulation and migraine risk. Furthermore, our study calls attention to the importance of analysing non-coding variants, which are continuously being demonstrated to play an important role in susceptibility and complex neurological disorders.

Availability of data and materials

All data generated during this study are included in the manuscript.

Abbreviations

ADHD:

Attention deficit hyperactivity disorder

DMEM:

Dulbecco’s modified Eagle medium

eQTLs:

Expression quantitative trait loci

FBS:

Fetal bovine serum

nTPM:

Normalised transcript per million

PCR:

Polymerase chain reaction

SD:

Standard deviation

SNAP25:

25-KD synaptosome-associated protein

SNARE:

Soluble N-ethylamine-sensitive factor attachment protein receptor

STX1A:

Syntaxin-1A

TBL2:

Transducin (beta)-like 2

VAMP2:

Vesicle-associated membrane protein-2 (or synaptobrevin-2)

References

  1. Sutherland HG, Albury CL, Griffiths LR (2019) Advances in genetics of migraine. J Headache Pain 20:72. https://0-doi-org.brum.beds.ac.uk/10.1186/s10194-019-1017-9

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Bron C, Sutherland HG, Griffiths LR (2021) Exploring the hereditary nature of migraine. Neuropsychiatr Dis Treat 17:1183–1194. https://0-doi-org.brum.beds.ac.uk/10.2147/NDT.S282562

    Article  PubMed  PubMed Central  Google Scholar 

  3. Olesen J (2018) Headache Classification Committee of the International Headache Society (IHS) The International Classification of Headache Disorders, 3rd edition. Cephalalgia 38:1–211. https://0-doi-org.brum.beds.ac.uk/10.1177/0333102417738202

  4. Mulder EJ, Van Baal C, Gaist D et al (2003) Genetic and Environmental Influences on Migraine: a twin study across six countries. Twin Res 6:422–431. https://0-doi-org.brum.beds.ac.uk/10.1375/136905203770326420

    Article  PubMed  Google Scholar 

  5. Hansen RD, Christensen AF, Olesen J (2017) Family studies to find rare high risk variants in migraine. J Headache Pain 18:32. https://0-doi-org.brum.beds.ac.uk/10.1186/s10194-017-0729-y

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Polderman TJC, Benyamin B, De Leeuw CA et al (2015) Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nat Genet 47:702–709. https://0-doi-org.brum.beds.ac.uk/10.1038/ng.3285

    Article  CAS  PubMed  Google Scholar 

  7. Kondratieva N, Azimova J, Skorobogatykh K et al (2016) Biomarkers of migraine: Part 1 – Genetic markers. J Neurol Sci 369:63–76. https://0-doi-org.brum.beds.ac.uk/10.1016/j.jns.2016.08.008

    Article  CAS  PubMed  Google Scholar 

  8. Yan J, Dussor G (2014) Ion channels and migraine. Headache 54:619–639. https://0-doi-org.brum.beds.ac.uk/10.1111/head.12323.Ion

    Article  PubMed  PubMed Central  Google Scholar 

  9. Aggarwal M, Puri V, Puri S (2012) Serotonin and CGRP in migraine. Ann Neurosci 19:88–94. https://0-doi-org.brum.beds.ac.uk/10.5214/ans.0972.7531.12190210

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Gormley P, Anttila V, Winsvold BS et al (2016) Meta-analysis of 375,000 individuals identifies 38 susceptibility loci for migraine. Nat Genet 48:856–866. https://0-doi-org.brum.beds.ac.uk/10.1038/ng.3598

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Techlo TR, Rasmussen AH, Møller PL et al (2020) Familial analysis reveals rare risk variants for migraine in regulatory regions. Neurogenetics 21:149–157. https://0-doi-org.brum.beds.ac.uk/10.1007/s10048-020-00606-5

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Hautakangas H, Winsvold BS, Ruotsalainen SE et al (2022) Genome-wide analysis of 102,084 migraine cases identifies 123 risk loci and subtype-specific risk alleles. Nat Genet 54:152–160. https://0-doi-org.brum.beds.ac.uk/10.1038/s41588-021-00990-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Hoffmann J, Baca SM, Akerman S (2019) Neurovascular mechanisms of migraine and cluster headache. J Cereb Blood Flow Metab 39:573–594. https://0-doi-org.brum.beds.ac.uk/10.1177/0271678X17733655

    Article  PubMed  Google Scholar 

  14. Quintas M, Neto JL, Pereira-Monteiro J et al (2013) Interaction between γ-aminobutyric acid a receptor genes: new evidence in migraine susceptibility. PLoS One 8:e74087. https://0-doi-org.brum.beds.ac.uk/10.1371/journal.pone.0074087

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Quintas M, Neto JL, Sequeiros J et al (2020) Going deep into synaptic vesicle machinery genes and migraine susceptibility – a case-control association study. Headache 60:2152–2165. https://0-doi-org.brum.beds.ac.uk/10.1111/head.13957

    Article  PubMed  Google Scholar 

  16. Lemos C, Pereira-Monteiro J, Mendonça D et al (2010) Evidence of syntaxin 1A involvement in migraine susceptibility: a Portuguese study. Arch Neurol 67:422–427. https://0-doi-org.brum.beds.ac.uk/10.1001/archneurol.2010.37

    Article  PubMed  Google Scholar 

  17. Felício D, Alves-ferreira M, Santos M, et al (2023) Integrating functional scoring and regulatory data to predict the effect of non-coding SNPs in a complex neurological disease. Brief Funct Genomics. 1–12. https://0-doi-org.brum.beds.ac.uk/10.1093/bfgp/elad020

  18. Chen F, Chen H, Chen Y et al (2021) Dysfunction of the SNARE complex in neurological and psychiatric disorders. Pharmacol Res 165:105469. https://0-doi-org.brum.beds.ac.uk/10.1016/j.phrs.2021.105469

    Article  CAS  PubMed  Google Scholar 

  19. Gao Q, Liu L, Chen Y et al (2015) Synaptosome-related (SNARE) genes and their interactions contribute to the susceptibility and working memory of attention-deficit/hyperactivity disorder in males. Prog Neuro-Psychopharmacology Biol Psychiatry 57:132–139. https://0-doi-org.brum.beds.ac.uk/10.1016/j.pnpbp.2014.11.001

    Article  CAS  Google Scholar 

  20. Corominas R, Ribasés M, Cuenca-León E et al (2009) Contribution of syntaxin 1A to the genetic susceptibility to migraine: a case-control association study in the Spanish population. Neurosci Lett 455:105–109. https://0-doi-org.brum.beds.ac.uk/10.1016/j.neulet.2009.03.011

    Article  CAS  PubMed  Google Scholar 

  21. Tropeano M, Wöber-Bingöl Ç, Karwautz A et al (2012) Association analysis of STX1A gene variants in common forms of migraine. Cephalalgia 32:203–212. https://0-doi-org.brum.beds.ac.uk/10.1177/0333102411433300

    Article  PubMed  Google Scholar 

  22. Smale ST (2010) Luciferase Assay. Cold Spring Harb Protoc 2010:pdb.prot5421. https://0-doi-org.brum.beds.ac.uk/10.1101/pdb.prot5421

  23. De Vries B, Anttila V, Freilinger T et al (2016) Systematic re-evaluation of genes from candidate gene association studies in migraine using a large genome-wide association data set. Cephalalgia 36:604–614. https://0-doi-org.brum.beds.ac.uk/10.1177/0333102414566820

    Article  PubMed  Google Scholar 

  24. Tsukumo Y, Tsukahara S, Furuno A, et al (2014) TBL2 Is a Novel PERK-Binding Protein that Modulates Stress-Signaling and Cell Survival during Endoplasmic Reticulum Stress. 9:e112761. https://0-doi-org.brum.beds.ac.uk/10.1371/journal.pone.0112761

  25. Tsukumo Y, Tsukahara S, Furuno A et al (2016) TBL2 Associates With ATF4 mRNA Via Its WD40 Domain and Regulates Its Translation During ER Stress. J Cell Biochem 117:500–509. https://0-doi-org.brum.beds.ac.uk/10.1002/jcb.25301

    Article  CAS  PubMed  Google Scholar 

  26. Kim K, Wi S, Seo JH et al (2021) Reduced interaction of aggregated α-Synuclein and VAMP2 by environmental enrichment alleviates hyperactivity and anxiety in a model of Parkinson’s Disease. Genes 12:392. https://0-doi-org.brum.beds.ac.uk/10.3390/genes12030392

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Matveeva EA, Price DA, Whiteheart SW et al (2012) Reduction of VAMP2 expression leads to a kindling-resistant phenotype in a murine model of epilepsy. Neuroscience 202:77–86. https://0-doi-org.brum.beds.ac.uk/10.1016/j.neuroscience.2011.11.055

    Article  CAS  PubMed  Google Scholar 

  28. Costa AS, Ferri E, Guerini FR et al (2022) VAMP2 expression and genotype are possible discriminators in different forms of dementia. Front Aging Neurosci 14:858162. https://0-doi-org.brum.beds.ac.uk/10.3389/fnagi.2022.858162

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Simmons RL, Li H, Alten B et al (2020) Overcoming presynaptic effects of VAMP2 mutations with 4-aminopyridine treatment. Hum Mutat 41:1999–2011. https://0-doi-org.brum.beds.ac.uk/10.1002/humu.24109

    Article  CAS  PubMed  Google Scholar 

  30. Strupp M, Teufel J, Zwergal A et al (2017) Aminopyridines for the treatment of neurologic disorders. Neurol Clin Pr 7:65–76. https://0-doi-org.brum.beds.ac.uk/10.1212/CPJ.0000000000000321

    Article  Google Scholar 

Download references

Acknowledgements

We would like to thank Patrícia Marques and Susana Seixas (IPATIMUP/i3S, Porto) for kindly providing the plasmids to perform the reporter gene assays, and Elsa Logarinho (IBMC/i3S, Porto) for supplying the HEK293T cell line. We acknowledge all patients for being part of this study.

Funding

This work was supported by Fundo Europeu de Desenvolvimento Regional (FEDER) funds through the COMPETE 2020 – Operational Programme for Competititveness and Internationalisation (POCI), Portugal, 2020; by Programa de Cooperação Transfronteiriça Interreg V-A Espanha-Portugal (POCTEP 2014–2020) under the project “Análisis y correlación entre la epigenética y la actividad cerebral para evaluar el riesgo de migraña crónica y episódica en mujeres” (0702_MIGRAINEE_2_E). This research was also funded by Sociedade Portuguesa de Cefaleias (SPC)/Novartis, Portugal (Grant in Neuroscience). S.M. (CEECIND/00684/2017), N.P. (2022.04997.CEECIND), and M.S. (Decreto Lei nº57/2016 de 29 de Agosto—Norma Transitória) are funded by FCT. A.D. is the recipient of a fellowship (SFRH/BD/136954/2018) funded by FCT.

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Authors and Affiliations

Authors

Contributions

M.A.-F., C.L., and N.P conceived the study and were in charge of overall administration and planning of the project; D.F. performed the vector constructions and reporter gene assays with support from M.S., A.D., and E.C.; D.F. analysed the data with support from M.S., A.D., C.L., and S.M.; D.F. wrote the original draft; all authors critically revised and edited the manuscript; M.S., C.L., and M.A.-F. supervised the work; M.A.-F., and N.P. contributed with resources and funding. All authors have read and agreed to the published version of the manuscript.

Corresponding author

Correspondence to Miguel Alves-Ferreira.

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Written informed consent was obtained from all subjects involved in the study.

Institutional Review Board Statement: The use of biological material and information from patients was approved by the Committee for Ethical and Responsible Conduct of Research—CECRI, i3S; approval code 2/CECRI/2020.

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'Not applicable'.

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The authors declare no competing interests.

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Felício, D., Dias, A., Martins, S. et al. Non-coding variants in VAMP2 and SNAP25 affect gene expression: potential implications in migraine susceptibility. J Headache Pain 24, 78 (2023). https://0-doi-org.brum.beds.ac.uk/10.1186/s10194-023-01615-z

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