Increased burden of rare deleterious variants of the KCNQ1 gene in patients with large‑vessel ischemic stroke

  • Authors:
    • Piotr K. Janicki
    • Ceren Eyileten
    • Victor Ruiz‑Velasco
    • Justyna Pordzik
    • Anna Czlonkowska
    • Iwona Kurkowska‑Jastrzebska
    • Shigekazu Sugino
    • Yuka Imamura Kawasawa
    • Dagmara Mirowska‑Guzel
    • Marek Postula
  • View Affiliations

  • Published online on: February 25, 2019     https://doi.org/10.3892/mmr.2019.9987
  • Pages: 3263-3272
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Abstract

The impact of rare and damaging variants in genes associated with platelet function in large‑vessel ischemic stroke (LVIS) remains unknown. The aim of this study was to investigate the contribution of some of these variants to the genetic susceptibility to LVIS in Polish patients using a deep re‑sequencing of 54 selected genes, coding for proteins associated with altered platelet function. Targeted pooled re‑sequencing (Illumina HiSeq 2500) was performed on genomic DNA of 500 cases (patients with history of clinically proven diagnosis of LVIS) and 500 age‑, smoking status‑, and sex‑matched controls (no history of any type of stroke), and from the same population as patients with LVIS. After quality control and prioritization based on allele frequency and damaging probability, individual genotyping of all deleterious rare variants was performed in patients from the original cohort, and stratified to concomitant cardiac conditions differing between the study and stroke groups. We demonstrated a statistically significant increase in the number of rare and potentially damaging variants in some of the investigated genes in the LVIS pool (an increase in the genomic variants burden). Furthermore, we identified an association between LVIS and 6 rare functional and damaging variants in the Kv7.1 potassium channel gene (KCNQ1). The predicted functional properties (partial loss‑of function) for the three most damaging variants in KCNQ1 coding locus were further confirmed in vitro by analyzing the membrane potential changes in cell lines co‑transfected heterogeneously with human muscarinic type 1 receptor and wild‑type or mutated KCNQ1 cDNA constructs using fluorescence imaging plate reader. The study demonstrated an increased rare variants burden for 54 genes associated with platelet function, and identified a putative role for rare damaging variants in the KCNQ1 gene on LVIS susceptibility in the Polish population.

Introduction

Previous genomic studies identified several common genetic variants that could play a role in large-vessel ischemic stroke (LVIS) (1). Precise type of their effect on brain ischemia remains unclear, and it is assumed that common genetic variants could explain between 39–66% of variation in ischemic stroke incidence (2). It has also been postulated that the accumulated effect of the remaining uncommon or rare damaging variants (called genetic burden) might explain a significant portion of the genetic predisposition to many common diseases or phenotypes (3,4). A small number of re-sequencing reports of European patients with LVIS were published so far. These studies have demonstrated that infrequent coding variants in numerous genes might be linked to stroke (58).

Platelets have an important role in the pathogenesis of LVIS based on their activation and adherence to the endothelium within cerebral arteries, as well as progression of thrombus (9,10). Most research strategies to date revealed the effect of genetic variation on reactivity of platelets and were obtained by analyzing common variants within candidate genes and/or genome-wide association studies (GWAS), followed by in vitro studies to assess platelet functions (11). Overall, previous studies on the genetic background of platelet reactivity indicated that many different genes contribute to platelet function. Thus far, the potential contribution of genetic variants within genes encoding proteins essential to thrombus formation in LVIS have been analyzed in a small number of studies and the majority of them focused on the common single nucleotide polymorphisms (SNPs) within a few genes associated with glycoproteins on the platelet surface (11). The results of these studies suggested that additional loci associated with platelet functions are yet to be found and that the known loci may contain high effect rare risk variants that have thus far gone undetected by GWAS.

Rare coding variants appear to be restricted to small populations and that was shown in only one previous study, which concentrated on the re-sequencing of the common variants in the platelet genes associated with membrane function (12). In addition, another recent investigation revealed that the rare variants in receptors commonly associated with platelet functions (e.g. purinergic receptors) could be associated with the occurrence of LVIS in the Polish population (13).

Thus, the objective of our current study was to explain the contribution played by the another set of uncommon and damaging genetic variants within selected genes associated with changes in platelet functions in LVIS. We have chosen 54 genes associated with less known or investigated biochemical processes associated with platelet functions as the focus for the re-sequencing study (1421).

Materials and methods

Clinical material

The study was permitted by both local ethics committee of the Institute of Psychiatry and Neurology, Warsaw, Poland, and Warsaw Medical University, Warsaw, Poland. The study conduct conformed to the most recent version of the Declaration of Helsinki. All participants in the study signed the informed consent. Full description of the study cohort, including the inclusion and exclusion criteria were published previously (12,13,2224). Based on the Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification we included: i) All patients classified as having ischemic stroke due to large-vessel atherosclerosis and ii) a subset of patients classified as having ischemic stroke of unknown etiology, provided they had at least 50% stenosis of the carotid artery ipsilateral to the infarct side and no evidence or no history of atrial fibrillation. Patient with the history of hemorrhagic or embolic stroke were excluded from the study. As a control group we used samples from age- and sex-matched 500 patients without history of stroke coming from the same geographical area as patients with LVIS (13) and collected for unrelated studies performed at Warsaw Medical University in Poland. Both cohorts of patients (study and control) were white Caucasian of Polish ethnicity and originated from central Poland. DNA extraction from collected blood samples was done as described before (9).

Pooled sequencing

The list of 54 re-sequenced genes is shown in Table I. These targets contain 846 exons and 10 adjoining bases beyond each exon on both sides. The genetic loci were selected using the human database (H. sapiens, hg19, GRCh37, February 2009). Pooled targeted enrichment of DNA, from LVIS patients (five polls with 100 subjects per pool) and 500 age-, sex-matched control patients, without stroke history (five pools with 100 subjects per pool), was done as described previously. Further explanation of re-sequencing and analysis of data is provided in the Supplementary material (Tables SISIV).

Table I.

List of 54 platelet genes with exons sequenced in the present study.

Table I.

List of 54 platelet genes with exons sequenced in the present study.

Author, yearGeneProtein encodedChromosome and regions(Ref.)
Janicki et al, 2017FCER1GFc fragment of IgE, high affinity I, receptor for; γ polypeptide1q23.3region(13)
Janicki et al, 2017VAV3vav 3 guanine nucleotide exchange factor1p13.3(13)
Jones et al, 2009RAF1v-raf-1 murine leukemia viral oncogene homolog 13p25.1(14)
Jones et al, 2009MAPK14Mitogen-activated protein kinase 146p21.31(14)
Jones et al, 2009JAK2Janus kinase 29p24.1(14)
Jones et al, 2009MAP2K4Mitogen-activated protein kinase kinase 4 17. p1217p12(14)
Jones et al, 2009AKT2v-akt murine thymoma viral oncogene homolog 219q13.1-q13.2(14)
Jones et al, 2009MAP2K2Mitogen-activated protein kinase kinase 219p13.3(14)
Jones et al, 2009GNAZGuanine nucleotide binding protein (G protein), α z polypeptide22q11.22(14)
Jones et al, 2009; Goodall et al, 2010TRIM27Tripartite motif containing 276p22.1(14,15)
Goodall et al, 2010LRRFIP1Leucine rich repeat (in FLII) interacting protein 12q37.3(15)
Goodall et al, 2010COMMD7COMM domain containing 720q11.21(15)
Postula et al, 2013RGS7Regulator of G-protein signaling 71q23.1(16)
Guerrero et al, 2011LPAR1Lysophosphatidic acid receptor 19q31.3(17)
Guerrero et al, 2011MYO5BMyosin VB18q21.1(17)
Mathias et al, 2010LDHAL6ALactate dehydrogenase A-like 6A11p15.1(18)
Mathias et al, 2010ANKS1BAnkyrin repeat and sterile α motif domain containing 1B12q23.1(18)
Johnson et al, 2010PIK3CG Phosphoinositide-3-kinase, catalytic, γ polypeptide7q22.3(19)
Johnson et al, 2010SHHSonic hedgehog homolog7q36.3(19)
Johnson et al, 2010JMJD1CJumonji domain containing 1C10q21.2(19)
Johnson et al, 2010MRVI1Murine retrovirus integration site 1 homolog11p15.4(19)
Johnson et al, 2010; Johnson, 2011RGS18Regulator of G-protein signaling 181q31.2(19,20)
Johnson et al, 2010; Johnson, 2011ST3GAL3ST3 β-galactoside α-2,3-sialyltransferase 31p34.1(19,20)
Johnson et al, 2010; Johnson, 2011UGT1A10UDP glucuronosyltransferase 1 family, polypeptide A102q37.1(19,20)
Johnson et al, 2010; Johnson, 2011NUP210Nucleoporin 210 kDa3p25.1(19,20)
Johnson et al, 2010; Johnson, 2011RAPGEF2Rap guanine nucleotide exchange factor (GEF) 24q32.1(19,20)
Johnson et al, 2010; Johnson, 2011ADAMTS2ADAM metallopeptidase with thrombospondin type 1 motif, 25q35.3(19,20)
Johnson et al, 2010; Johnson, 2011FBXL7F-box and leucine-rich repeat protein 75p15.1(19,20)
Johnson et al, 2010; Johnson, 2011KLHL31Kelch-like family member 316p12.1(19,20)
Johnson et al, 2010; Johnson, 2011GMDSGDP-mannose 4,6-dehydtase6p25.3(19,20)
Johnson et al, 2010; Johnson, 2011WBSCR17Williams-Beuren syndrome chromosome region 177q11.22(19,20)
Johnson et al, 2010; Johnson, 2011ATP6V1FATPase, H+ transporting, lysosomal 14 kDa, V1 subunit F7q32.1(19,20)
Johnson et al, 2010; Johnson, 2011SGCZSarcoglycan, ζ8p22(19,20)
Johnson et al, 2010; Johnson, 2011STMN4Stathmin-like 48p21.2(19,20)
Johnson et al, 2010; Johnson, 2011PSKH2Protein serine kinase H28q21.3(19,20)
Johnson et al, 2010; Johnson, 2011PIP5K1B Phosphatidylinositol-4-phosphate 5-kinase, type I, β9q21.11(19,20)
Johnson et al, 2010; Johnson, 2011PTPRDProtein tyrosine phosphatase, receptor type, D9p24.1(19,20)
Johnson et al, 2010; Johnson, 2011MIPOL1Mirror-image polydactyly 114q13.3-q21.1(19,20)
Johnson et al, 2010; Johnson, 2011SVILSupervillin10p11.23(19,20)
Johnson et al, 2010; Johnson, 2011CUBNCubilin (intrinsic factor-cobalamin receptor)10p13(19,20)
Johnson et al, 2010; Johnson, 2011ST3GAL4ST3 β-galactoside α-2,3-sialyltransferase 411q24.2(19,20)
Johnson, 2010 Johnson, 2011KCNQ1Potassium voltage-gated channel, KQT-like subfamily, member 111p15.5-p15.4(19,20)
Johnson et al, 2010; Johnson, 2011HSD17B6Hydroxysteroid (17-β) dehydrogenase 612q13.3(19,20)
Johnson et al, 2010; Johnson, 2011RAP1BRAP1B, member of RAS oncogene family12q15(19,20)
Johnson et al, 2010; Johnson, 2011PTPN11Protein tyrosine phosphatase, non-receptor type 1112q24(19,20)
Johnson et al, 2010; Johnson, 2011THSD4Thrombospondin, type I, domain containing 415q23(19,20)
Johnson et al, 2010; Johnson, 2011TAOK1TAO kinase 117q11.2(19,20)
Johnson et al, 2010; Johnson, 2011SETBP1SET binding protein 118q12.3(19,20)
Johnson et al, 2010; Johnson, 2011 KIAA0802SOGA family member 218p11.22(19,20)
Johnson et al, 2010; Johnson, 2011CTCFLCCCTC-binding factor (zinc finger protein)-like20q13.31(19,20)
Johnson et al, 2010; Johnson, 2011PCK1Phosphoenolpyruvate carboxykinase 120q13.31(19,20)
Johnson et al, 2010; Johnson, 2011PRNPPrion protein20p 13(19,20)
Shiffman et al, 2006***VAMP8Vesicle-associated membrane protein 82p12-p11.2(21)
Lee et al, 2014GLIS3GLIS family zinc finger 39p24.2(26)
Verification of selected variants by individual genotyping

Individual genotyping for selected markers in individual DNA samples was performed using a custom Sequenom iPLEX assay in conjunction with the Mass ARRAY platform (Sequenom Inc., La Jolla, CA, USA). Panels of SNP markers were designed using Sequenom Assay Design 3.2 software (Sequenom Inc.), in a similar fashion to the previously described methodology from our laboratory (9,16,17).

Statistical analysis

A cumulative minor allele frequency (cMAF) was utilized to show the allelic frequency of the investigated variants, which encompasses all rare damaging variants individually genotyped in the investigated cohorts, as well as within each of the analyzed loci. Pearson Chi-square test was used in order to analyze differences in cMAF for all individually genotyped variants between the study and control cohorts (VassarStats: Website for Statistical Computation on http://vassarstats.net/). The pooled minor allele test (CMAT) (10,000 × permutations) was used for comparison of all variants within investigated loci to estimate the statistical significance of the observed differences in the accumulation of variants. CMAT is a pooling method proposed by Zawistowski et al (25) and works by comparing weighted minor-allele counts (for cases and controls) against the weighted major-allele counts (for cases and controls). Although the CMAT test statistic is based on a chi-square statistic, it does not follow a known distribution and its significance has to be determined by a permutation procedure. The calculations of CMAT were performed using AssotesR package (0.1-10) from CRAN repository (cran.r-project.org/package=AssotesteR) and written by Gaston Sanchez (gastonsanchez.com/) as documented at www.rdocumentation.org/packages/AssotesteR/versions/0.1-10. The significance threshold was adjusted to the number of re-sequenced loci, when needed (13,25).

Power and sample size considerations

For the power calculations, instead of using individual rare variants, we decided to use predicted cMAF for all deleterious rare variants in the sequenced loci. We have followed a self-sufficient, closed-form, maximum-likelihood estimator for allele frequencies that accounts for errors associated with sequencing, and a likelihood-ratio test statistic that provides a simple means for evaluating the null hypothesis of monomorphism (13,26,27). Unbiased estimates of allele frequencies 10/N (where N is the number of individuals sampled) appear to be achievable, and near-certain identification of a single nucleotide polymorphism (SNP) requires a cMAF of at least 0.01 (i.e., 10 variants per cohort). In addition, because the power to detect significant allele-frequency differences between the two populations is limited, we set both the number of sampled individuals (500 in the cohort) and depth of sequencing coverage in excess of 100.

Fluorescence-based (FLIPR) functional assay for KCNQ1 variants

Chinese hamster ovaries cells (CHO) cultures stably transfected with human muscarinic type 1 receptor (M1) were purchased from cDNA Resource Center, Bloomberg, PA. The CHO-M1 cells were then transiently co-transfected with KCNQ1 cDNA constructs. Wild-type KCNQ1 cDNA constructs (in pcDNA3.1) were prepared by Watson Bio Sciences (Houston, TX, USA). The fidelity of the mutations for each variant was confirmed by Sanger sequencing. Details about the transfection techniques and cell culture conditions used in our laboratory were published before (13).

The heterologous expressed potassium KCNQ1 channels were inhibited by the M1 receptor agonist oxotremorine (OxoM, 10 nM), resulting in significant changes in membrane polarization (fully antagonized by muscarinic receptor antagonist atropine at 1 µM-not shown).

The Fluorescence Imaging Plate Reader (FLIPR) on Flex Station 3 (Molecular Devices, San Jose, CA, USA) was employed to measure the fluorescence changes. After the cells were loaded with membrane dye, the plate with the cells and plate containing OxoM (10 nM) were inserted into the plate reader. The raw fluorescence readings were converted and plotted as the change in relative fluorescence before (F0 baseline=100%) and after OxoM application F), according to the formula ((F/F0)*100%). For all experimental conditions, minimum fluorescence (Fmin) and maximum fluorescence (Fmax) were recorded in triplicates after administration. The summary data are presented as summary trend lines for WT and mutants, as well as averages (with standard deviations) for Fmax and Fmin and for each variant and WT cells used in FLIPR experiments. The final data represent all measurements done in triplicates and in three independent experiments (cell populations). Data and statistical analysis were performed using analysis of variance, followed by the Student's t-test. P<0.05 was considered to indicate a statistically significant difference.

Results

Study design and sequencing coverage

The design of the study is presented in Fig. 1. The enrichment of the target loci resulted in coverage of 99.6% and produced 36.1 (22.7–45.9 range) million reads which is 5.3 (3–7 range) Gbp per re-sequenced sample. It relates to an average coverage of 12,000× per pool and an average coverage of 120× per patient sample (range 21–369).

Selection of rare variants (based on MAF<1%)

The step-wise analysis of the observed variants is presented in Fig. 2. In total, 1018 unique variants, irrespective of MAF and with adequate quality were observed in both investigated cohorts. The complete list of all observed variants is provided in the Supplementary materials, Tables SII for all non-coding variants and SIII for all non-synonymous variants. Seventy two percent of all variants were previously listed in the available databases, and 28% were new. Out of all observed variants, 327 (32.1%) were located in the coding segments of the sequenced genes, and the remainder was located in untranslated regions. Out of all coding variants, 120 variants (Supplementary material, Table SIV-list of all rare non-synonymous variants) were selected based on MAF <1% (i.e. rare variants) (28), which consisted of 52 known (by dbSNP149 November 2016) and 68 unlisted, novel variants.

Verification of selected variants by individual genotyping

In total, 28 SNVs with the highest predicted damaging score calculated by Combined Annotation Dependent Depletion (CADD) score were chosen for individual genotyping. The minimum CADD score of 10 served as a threshold for predicted deleteriousness. The individual genotyping was performed in patients from the original cohort and revealed that the identity of all 28 initially selected variants could be confirmed by individual genotyping, which indicates no sequencing errors for these variants.

The initial statistical analysis utilized Pearsons Chi-square test for the assessment of the differences in the cumulative frequency of all 28 individually genotyped variants between the investigated cohorts. There was a highly statistically significant (P=0.00045) difference (cMAF control=1.2% vs. cMAF stroke=3.6%) in cMAF for all damaging variants in the LVIS group when compared with controls.

The statistical analysis of the number of variants within the single gene loci was based on combined minor allele association test (CMAT). The region-based, Bonferroni corrected, significance threshold was P=0.00092 (nominal P=0.05/54 sequenced genes). It demonstrated a statistically significant difference (P=0.0009) between control and IS cohorts for the KCNQ1 location. The KCNQ1 exons locus contained 3 novel and 3 known rare and deleterious (CADD score range 13.22-39) coding variants (Table II).

Table II.

cMAF for 28 rare and most damaging variants observed in the individually genotyped patients from control and LVIS cohorts.

Table II.

cMAF for 28 rare and most damaging variants observed in the individually genotyped patients from control and LVIS cohorts.

Gene locusNumber of carriers in control cohort, n=500Number of carriers in LVIS cohort, n=500P-value
ADAMT2  2  30.4
CUBN  0  40.06
GLIS3  2  00.1
KCNQ1  0  60.0009a
LDHAL6A  3  20.4
MAP2K2  0  20.2
MIPOL1  0  20.8
MTCL1  4  30.9
MYO5B  0  40.06
PTPRJ  0  20.1
SHH  0  20.1
SVIL  1  30.15
UGT1A1  0  20.1
Total number of carriers and cMAF for all loci1236 0.00045b
Odds ratio and 95% confidence intervals (in brackets) 3.07 (1.59–5.94)

a Statistical significance calculated using burden combined minor allele test for differences in cMAF within genetic locus

b statistical significance calculated using Pearson's χ2 test for differences in cMAF for all loci. cMAF, cumulative minor allele frequency; LVIS, large-vessel ischemic stroke.

Functional analysis of selected rare variants within KNCQ1 gene

To evaluate whether the observed variants exert a damaging effect on KCNQ1 function, we selected 3 novel and most damaging variants from the KCNQ1 locus to examine the coupling between the heterologous expressed human M1 receptor and KCNQ1 channels in CHO-M1 cells (Table III). Fig. 3 shows the summary of changes in relative fluorescence for CHO-M1 cells expressing wild-type KCNQ1, and variants KCNQ1 c. G855T p. K285N, KCNQ1 c. G1545T p. K515N, and KCNQ1 c. 1637A p. S546X. Following oxoM application (final concentration 10 nM), the fluorescence decreased rapidly, indicating corresponding changes in cell membrane potential. We expressed the changes in fluorescence both as the differences between baseline fluorescence and its changes (in % of baseline=Fo=100%) over 250 sec after administration of oxoM (shown as trend line for all observations) and average values of minimum (Fmin) and maximum (Fmax) of relative fluorescence during the recording period (separately for WT and variants). The provided trend lines represent summary values for all observations (2–3 independent cell cultures and all measurements in triplicates of plate wells). A significant decrease in fluorescence signal for each variant was observed after administration of oxoM when compared with the KCNQ1 wild-type-expressing CHO-M1 cells. Correspondingly, the statistically significant decrease (P<0.05 ANOVA, followed by t-test) in the average Fmin and Fmax was observed for all 3 investigated variants, indicating at least partial loss-of-function characteristics for variant proteins, when compared to WT.

Table III.

Rare coding variants for KCNQ1 gene observed in the study patients, as identified by exome sequencing and verified by individual genotyping.

Table III.

Rare coding variants for KCNQ1 gene observed in the study patients, as identified by exome sequencing and verified by individual genotyping.

dbSNPMAFctrl pooledMAFstroke pooledMAF individual genotyping in controlMAF in individual genotyping in strokeDNA changeAmino acid changeCADD
rs127204570.80%ND0.01%NDc.G1179Tp.K393N   6.560
novelND0.75%ND0.1%c.G4Tp.D2Y   5.53
rs199472712ND0.95%ND0.1%c.G724Tp.D242Y19.35
NovelND0.74%ND0.1%c.G855Tp.K285N15.48
NovelND0.65%ND0.1% c.G1545Tp.K515N13.22
rs199472793ND0.71%ND0.1%c.C1597Tp.R533W15.28
NovelND0.85%ND0.1% c.C1637Ap.S546X39

[i] Novel variants marked in bold were additionally investigated in the in vitro functional test. cMAF=0.01% for MAF individual genotyping in control. cMAF=0.06% MAF in individual genotyping in stroke, P=0.0009 using combined minor allele test for comparison of coding rare variants in the KCNQ1 gene. cMAF, cumulative minor allele frequency; ND, not detected; CADD, Combined Annotation Dependent Depletion score; KCNQ1, potassium voltage-gated channel subfamily Q member 1.

Discussion

We present the results of the analysis of the genetic burden of the infrequent coding variants in 54 genes associated with platelet function and its possible association with LVIS. The assessment of MAF for the investigated uncommon coding variants established that there was a significant accumulation of those variants in the LVIS group when compared to the control group. By grouping these variants by sequenced loci instead of analyzing them individually, we were able to observe associations which could be underpowered when applied to single variants, as shown in previous studies of other traits (12,13). In particular, we found an association between the increased accumulation of rare variants in KCNQ1 locus and LVIS. It is important to note that, with the exception of 3 already known variants, the remaining 3 observed damaging variants within KCNQ1 locus were novel. It is therefore likely that at least some of the observed variants might be restricted to the Polish cohort. So far detailed genotypes in the Polish population have been rather poorly characterized in the available genomic databases. This in turn might suggest that the verification of the obtained results in the independent cohorts could be challenging. For example, it was previously demonstrated that, at least in case of rare damaging variants associated with ulcerative colitis, the rare variants observed in the Dutch population could not be replicated in a German cohort (29). Another study on inflammatory bowel disease, that included several thousands of European individuals and individuals of other ancestry, showed that although the majority of the loci with MAF>5% were shared between different ancestry groups (30), no such similarities were observed for uncommon alleles. In fact, rare variants were even more likely to be specific to a particular population, as was confirmed by a recent sequencing study (31). What is more, rare variants might differ significantly among even closely related populations (32).

We were able to observe only few (out of several hundreds) of previously listed rare coding variants in the KCNQ1 locus, which might indicate either limited power of the study or population-specific distribution of these variants. Further studies in other populations will be helpful to verify if the rare damaging variants in the KCNQ1 coding locus are indeed associated with large-vessel IS, or also with other types of stroke (small-vessel and embolic).

The KCNQ channels, members of the voltage-gated (KV7.1) K+-selective channel subfamily, play a major role in K+ ion transport. For instance, previous studies have shown that both KV channels KCNA3 and G protein-gated inwardly rectifying K+ channels (GIRK) regulate platelet activation (33,34). The presence of Kv7.1 channel in blood cells, including platelets, suggests that they play a role in agonist-mediated regulation of platelet-driven thrombotic pathways that is crucial to hemostasis during IS (35,36).

Our in vitro results indicate that oxoM-mediated changes in the membrane potential of cells expressing M1 receptors and KCNQ1 channel variants were attenuated (loss-of-function characteristics) when compared to cells expressing the wild-type receptors. These findings suggest that the signaling might be diminished in cells expressing the mutant KCNQ1 channels. The coding variants in KCNQ1 were previously evaluated in different cardiovascular diseases and DM (3741). It has been also reported that obesity along with IS may modify methylation of KCNQ1 gene and plasma KCNQ1 protein concentration (38,39). The coding variants in KCNQ1 have been reported to lead to congenital long QT syndrome (42), an autosomal dominant disorder. Because of the demonstrated deleterious properties of the investigated variants, it should be also considered that the stroke patients in the study may have suffered from an ischemic stroke secondary to a congenital disorder. Whether KCNQ1 variants are disease-associated with ischemic stroke (possibly via platelet function) or disease-causing for congenital QT syndrome (with reportedly higher incidence of ischemic stroke is one of the questions which should be clarified in the future investigations (41).

Moreover, in one of the largest to date GWAS on platelet function, KCNQ1 locus was discovered to contribute to platelet function variability (19,20). The exact mechanism of these interactions remains unknown, as KCNQ1 is mostly co-assembled with the product of the KCNE1 (minimal K+-channel protein) gene in the heart to form a cardiac-delayed rectifier-like K+ current and the effect of KCNQ1 channels on platelet function has not been not directly investigated so far. However, Gallego-Fabrega et al (43) reported recently that the methylation pattern of KCNQ1 locus might be associated with vascular recurrence in aspirin-treated stroke patients.

The study is limited by the absence of independent verification of accumulation of deleterious KCNQ1 rare variants. However, it was demonstrated previously that the occurrence of rare variants, because of their private character, is often limited to very restricted cohorts and has been difficult to repeat in other cohorts, unless the confirmation cohorts are truly large (in this case several tens of thousands of patients). The added drawback of the presented research is that the direct effect of the observed genomic variants on the platelet function (e.g. aggregation) was not evaluated. This might raise an issue if the observed change in the frequency of variants were entirely related to the platelet function or, perhaps, some other mechanisms related to biochemical pathways. Moreover, it should be noted that only a limited number of all known genes related to platelet function were re-sequenced in this study. We would like to stress that the results of re-sequencing of the more frequently investigated 26 genes related to platelet function were published by our group in the past (13).

The outcome of this study indicates that the increased accumulation of rare damaging variants in the exons of the sequenced 54 platelet genes (and in particular for variants located in the region of potassium channel KCNQ1 gene) could be associated with LVIS. The mechanism of the interaction of these variants with LVIS currently appears unclear and therefore requires further investigations. It is also uncertain if our results could be directly translated to other populations, as the variants responsible for the observed associations appear to be limited to the investigated cohort. Further studies in different, as well as much larger cohorts, are required to address this problem.

Supplementary Material

Supporting Data
Supporting Data

Acknowledgements

The authors would like to thank Dr Michal Karlinski (Institute of Psychiatry and Neurology, Warsaw, Poland) and Dr Agnieszka Cudna (Center for Preclinical Research and Technology CEPT, Warsaw, Poland) for preparing the samples and database for further analysis.

Funding

Research subject was implemented with CEPT infrastructure financed by the European Union-the European Regional Development Fund within the Operational Program ‘Innovative economy’ for 2007–2013. The study was supported financially as part of the research grant from the National Science Center OPUS research grant (grant no. 2013/11/B/NZ7/01541).

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Authors' contributions

PKJ and MP conceived the concept and design for the study, were involved in data collection and analysis, and supervised the work. CE and VRV contributed to the design of the research, and were involved in data collection and analysis. SS and YIK verified the analytical methods. JP, AC, IKJ and DMG were involved in data collection and analysis. All authors read and approved the final manuscript.

Ethics approval and consent to participate

All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from all patients for being included in the study.

Patient consent for publication

The consent for publication was obtained from all patients included in the study.

Competing interests

The authors declare that they have no competing interests.

Glossary

Abbreviations

Abbreviations:

LVIS

large-vessel ischemic stroke

CHO-M1

human muscarinic type 1 receptor

FLIPR

fluorescence imaging plate reader

GWAS

genome wide association studies

SNP

single nucleotide polymorphism

CAD

coronary artery disease

cMAF

cumulative minor allele frequency

CMAT

combined minor allele test

SNVs

single nucleotide variants

Fmin

minimum fluorescence

Fmax

maximum fluorescence

CADD

Combined Annotation Dependent Depletion

CHF

congestive heart failure

DM

diabetes mellitus

GIRK

G-protein-gated inwardly rectifying K+ channels

References

1 

Welter D, MacArthur J, Morales J, Burdett T, Hall P, Junkins H, Klemm A, Flicek P, Manolio T, Hindorff L and Parkinson H: The NHGRI GWAS Catalog, a curated resource of SNP-trait associations. Nucleic Acids Res. 42:D1001–D1006. 2014. View Article : Google Scholar : PubMed/NCBI

2 

Holliday EG, Maguire JM, Evans TJ, Koblar SA, Jannes J, Sturm JW, Hankey GJ, Baker R, Golledge J, Parsons MW, et al: Common variants at 6p21.1 are associated with large artery atherosclerotic stroke. Nat Genet. 44:1147–1151. 2012. View Article : Google Scholar : PubMed/NCBI

3 

Bevan S, Traylor M, Adib-Samii P, Malik R, Paul NL, Jackson C, Farrall M, Rothwell PM, Sudlow C, Dichgans M and Markus HS: Genetic heritability of ischemic stroke and the contribution of previously reported candidate gene and genomewide associations. Stroke. 43:3161–3167. 2012. View Article : Google Scholar : PubMed/NCBI

4 

Gibson G: Rare and common variants: Twenty arguments. Nat Rev Genet. 13:135–145. 2011. View Article : Google Scholar

5 

Genome of the Netherlands Consortium, . Whole-genome sequence variation, population structure and demographic history of the Dutch population. Nat Genet. 46:818–25. 2014. View Article : Google Scholar : PubMed/NCBI

6 

Cheng YC, Cole JW, Kittner SJ and Mitchell BD: Genetics of ischemic stroke in young adults. Circ Cardiovasc Genet. 7:383–392. 2014. View Article : Google Scholar : PubMed/NCBI

7 

Auer PL, Nalls M, Meschia JF, Worrall BB, Longstreth WT Jr, Seshadri S, Kooperberg C, Burger KM, Carlson CS, Carty CL, et al: Rare and coding region genetic variants associated with risk of ischemic stroke: The NHLBI exome sequence project. JAMA Neurol. 72:781–788. 2015. View Article : Google Scholar : PubMed/NCBI

8 

Lindgren A: Stroke genetics: A review and update. J Stroke. 16:114–123. 2014. View Article : Google Scholar : PubMed/NCBI

9 

Anyanwu C, Hahn M, Nath M, Li J, Barone FC, Rosenbaum DM and Zhou L: Platelets pleiotropic roles in ischemic stroke. Austin J Cerebrovasc Dis Stroke. 3:10482016.

10 

del Zoppo GJ: The role of platelets in ischemic stroke. Neurology. 51 (Suppl 3):S9–S14. 1998. View Article : Google Scholar : PubMed/NCBI

11 

Milanowski L, Pordzik J, Janicki PK and Postula M: Common genetic variants in platelet surface receptors and its association with ischemic stroke. Pharmacogenomics. 17:953–971. 2016. View Article : Google Scholar : PubMed/NCBI

12 

Postula M, Janicki PK, Milanowski L, Pordzik J, Eyileten C, Karlinski M, Wylezol P, Solarska M, Czlonkowka A, Kurkowska-Jastrzebka I, et al: Association of frequent genetic variants in platelet activation pathway genes with large-vessel ischemic stroke in Polish population. Platelets. 28:66–73. 2017. View Article : Google Scholar : PubMed/NCBI

13 

Janicki PK, Eyileten C, Ruiz-Velasco V, Sedeek KA, Pordzik J, Czlonkowska A, Kurkowska-Jastrzebska I, Sugino S, Imamura-Kawasawa Y, Mirowska-Guzel D and Postula M: Population-specific associations of deleterious rare variants in coding region of P2RY1-P2RY12 purinergic receptor genes in large-vessel ischemic stroke patients. Int J Mol Sci. 18:E26782017. View Article : Google Scholar : PubMed/NCBI

14 

Jones CI, Bray S, Garner SF, Stephens J, de Bono B, Angenent WG, Bentley D, Burns P, Coffey A, Deloukas P, et al: A functional genomics approach reveals novel quantitative trait loci associated with platelet signaling pathways. Blood. 114:1405–1416. 2009. View Article : Google Scholar : PubMed/NCBI

15 

Goodall AH, Burns P, Salles I, Macaulay IC, Jones CI, Ardissino D, de Bono B, Bray SL, Deckmyn H, Dudbridge F, et al: Transcription profiling in human platelets reveals LRRFIP1 as a novel protein regulating platelet function. Blood. 116:4646–4656. 2010. View Article : Google Scholar : PubMed/NCBI

16 

Postula M, Janicki PK, Rosiak M, Kaplon-Cieslicka A, Trzepla E, Filipiak KJ, Kosior DA, Czlonkowski A and Opolski G: New single nucleotide polymorphisms associated with differences in platelets reactivity in patients with type 2 diabetes treated with acetylsalicylic acid: Genome-wide association approach and pooled DNA strategy. J Thromb Thrombolysis. 36:65–73. 2013. View Article : Google Scholar : PubMed/NCBI

17 

Guerrero JA, Rivera J, Quiroga T, Martinez-Perez A, Antón AI, Martínez C, Panes O, Vicente V, Mezzano D, Soria JM and Corral J: Novel loci involved in platelet function and platelet count identified by a genome-wide study performed in children. Haematologica. 96:1335–1343. 2011. View Article : Google Scholar : PubMed/NCBI

18 

Mathias RA, Kim Y, Sung H, Yanek LR, Mantese VJ, Hererra-Galeano JE, Ruczinski I, Wilson AF, Faraday N, Becker LC and Becker DM: A combined genome-wide linkage and association approach to find susceptibility loci for platelet function phenotypes in European American and African American families with coronary artery disease. BMC Med Genomics. 3:222010. View Article : Google Scholar : PubMed/NCBI

19 

Johnson AD, Yanek LR, Chen MH, Faraday N, Larson MG, Tofler G, Lin SJ, Kraja AT, Province MA, Yang Q, et al: Genome-wide meta-analyses identifies seven loci associated with platelet aggregation in response to agonists. Nat Genet. 42:608–613. 2010. View Article : Google Scholar : PubMed/NCBI

20 

Johnson AD: The genetics of common variation affecting platelet development, function and pharmaceutical targeting. J Thromb Haemost. 9 (Suppl 1):S246–S257. 2011. View Article : Google Scholar

21 

Shiffman D, Rowland CM, Louie JZ, Luke MM, Bare LA, Bolonick JI, Young BA, Catanese JJ, Stiggins CF, Pullinger CR, et al: Gene variants of VAMP8 and HNRPUL1 are associated with early-onset myocardial infarction. Arterioscler Thromb Vasc Biol. 26:1613–1618. 2006. View Article : Google Scholar : PubMed/NCBI

22 

No authors listed, . Stroke-1989. Recommendations on stroke prevention, diagnosis, and therapy. Report of the WHO task force on stroke and other cerebrovascular disorders. Stroke. 20:1407–1431. 1989. View Article : Google Scholar : PubMed/NCBI

23 

Foulkes MA, Wolf PA, Price TR, Mohr JP and Hier DB: The stroke data bank: Design, methods, and baseline characteristics. Stroke. 19:547–554. 1988. View Article : Google Scholar : PubMed/NCBI

24 

Grabska K, Gromadzka G and Członkowska A: Infections and ischemic stroke outcome. Neurol Res Int. 2011:6913482011.PubMed/NCBI

25 

Zawistowski M, Gopalahrishnan S, Ding J, Li Y, Grimm S and Zöllner S: Extending rare-variant testing strategies: Analysis of noncoding sequence and imputed genotypes. Am J Hum Genet. 87:604–617. 2010. View Article : Google Scholar : PubMed/NCBI

26 

Lee S, Abecasis GR, Boehnke M and Lin X: Rare-variant association analysis: Study designs and statistical tests. Am J Hum Genet. 95:5–23. 2014. View Article : Google Scholar : PubMed/NCBI

27 

Lynch M, Bost D, Wilson S, Maruki T and Harrison S: Population-genetic inference from pooled-sequencing data. Genome Biol Evol. 6:1210–1228. 2014. View Article : Google Scholar : PubMed/NCBI

28 

Kircher M, Witten DM, Jain P, O'Roak BJ, Cooper GM and Shendure J: A general framework for estimating the relative pathogenicity of human genetic variants. Nat Genet. 46:310–315. 2014. View Article : Google Scholar : PubMed/NCBI

29 

Visschedijk MC, Alberts R, Mucha S, Deelen P, de Jong DJ, Pierik M, Spekhorst LM, Imhann F, van der Meulen-de Jong AE, van der Woude CJ, et al: Pooled resequencing of 122 ulcerative colitis genes in a large dutch cohort suggests population-specific associations of rare variants in MUC2. PLoS One. 11:e01596092016. View Article : Google Scholar : PubMed/NCBI

30 

Liu JZ, van Sommeren S, Huang H, Ng SC, Alberts R, Takahashi A, Ripke S, Lee JC, Jostins L, Shah T, et al: Association analyses identify 38 susceptibility loci for inflammatory bowel disease and highlight shared genetic risk across populations. Nat Genet. 47:979–986. 2015. View Article : Google Scholar : PubMed/NCBI

31 

Hong KW, Shin MS, Ahn YB, Lee HJ and Kim HD: Genomewide association study on chronic periodontitis in Korean population: Results from the Yangpyeong health cohort. J Clin Periodontol. 42:703–710. 2015. View Article : Google Scholar : PubMed/NCBI

32 

Prescott NJ, Lehne B, Stone K, Lee JC, Taylor K, Knight J, Papouli E, Mirza MM, Simpson MA, Spain SL, et al: Pooled sequencing of 531 genes in inflammatory bowel disease identifies an associated rare variant in BTNL2 and implicates other immune related genes. PLoS Genet. 11:e10049552015. View Article : Google Scholar : PubMed/NCBI

33 

McCloskey C, Jones S, Amisten S, Snowden RT, Kaczmarek LK, Erlinge D, Goodall AH, Forsythe ID and Mahaut-Smith MP: Kv1.3 is the exclusive voltage-gated K+ channel of platelets and megakaryocytes: Roles in membrane potential, Ca2+ signalling and platelet count. J Physiol. 588:1399–1406. 2010. View Article : Google Scholar : PubMed/NCBI

34 

Shankar H, Kahner BN, Prabhakar J, Lakhani P, Kim S and Kunapuli SP: G-protein-gated inwardly rectifying potassium channels regulate ADP-induced cPLA2 activity in platelets through Src family kinases. Blood. 108:3027–3034. 2006. View Article : Google Scholar : PubMed/NCBI

35 

Kapural L and Fein A: Suppression of the voltage-gated K+ current of human megakaryocytes by thrombin and prostacyclin. Biochim Biophys Acta. 1355:331–342. 1997. View Article : Google Scholar : PubMed/NCBI

36 

Schmidt EM, Münzer P, Borst O, Kraemer BF, Schmid E, Urban B, Lindemann S, Ruth P, Gawaz M and Lang F: Ion channels in the regulation of platelet migration. Biochem Biophys Res Commun. 415:54–60. 2011. View Article : Google Scholar : PubMed/NCBI

37 

Al-Shammari MS, Al-Ali R, Al-Balawi N, Al-Enazi MS, Al-Muraikhi AA, Busaleh FN, Al-Sahwan AS, Al-Elq A, Al-Nafaie AN, Borgio JF, et al: Type 2 diabetes associated variants of KCNQ1 strongly confer the risk of cardiovascular disease among the Saudi Arabian population. Genet Mol Biol. 40:586–590. 2017. View Article : Google Scholar : PubMed/NCBI

38 

Gómez-Úriz AM, Milagro FI, Mansego ML, Cordero P, Abete I, De Arce A, Goyenechea E, Blázquez V, Martínez-Zabaleta M, Martínez JA, et al: Obesity and ischemic stroke modulate the methylation levels of KCNQ1 in white blood cells. Hum Mol Genet. 24:1432–1440. 2015. View Article : Google Scholar : PubMed/NCBI

39 

Abete I, Gómez-Úriz AM, Mansego ML, De Arce A, Goyenechea E, Blázquez V, Martínez-Zabaleta MT, González-Muniesa P, López De Munain A, et al: Epigenetic changes in the methylation patterns of KCNQ1 and WT1 after a weight loss intervention program in obese stroke patients. Curr Neurovasc Res. 12:321–333. 2015. View Article : Google Scholar : PubMed/NCBI

40 

Harmer SC, Mohal JS, Royal AA, McKenna WJ, Lambiase PD and Tinker A: Cellular mechanisms underlying the increased disease severity seen for patients with long QT syndrome caused by compound mutations in KCNQ1. Biochem J. 462:133–142. 2014. View Article : Google Scholar : PubMed/NCBI

41 

Liu J, Wang F, Wu Y, Huang X, Sheng L, Xu J, Zha B, Ding H, Chen Z and Sun T: Meta-analysis of the effect of KCNQ1 gene polymorphism on the risk of type 2 diabetes. Mol Biol Rep. 40:3557–3567. 2013. View Article : Google Scholar : PubMed/NCBI

42 

Henninger N, Haussen DC, Kakouros N, Selim M, Searls DE, Kumar S, Schlaug G and Caplan LR: QTc-prolongation in posterior circulation stroke. Neurocrit Care. 19:167–175. 2013. View Article : Google Scholar : PubMed/NCBI

43 

Gallego-Fabrega C, Carrera C, Reny JL, Fontana P, Slowik A, Pera J, Pezzini A, Serrano-Heras G, Segura T, Bin Dukhyil AA, et al: PPM1A methylation is associated with vascular recurrence in aspirin-treated patients. Stroke. 47:1926–1929. 2016. View Article : Google Scholar : PubMed/NCBI

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Volume 19 Issue 4

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Spandidos Publications style
Janicki PK, Eyileten C, Ruiz‑Velasco V, Pordzik J, Czlonkowska A, Kurkowska‑Jastrzebska I, Sugino S, Imamura Kawasawa Y, Mirowska‑Guzel D, Postula M, Postula M, et al: Increased burden of rare deleterious variants of the KCNQ1 gene in patients with large‑vessel ischemic stroke. Mol Med Rep 19: 3263-3272, 2019.
APA
Janicki, P.K., Eyileten, C., Ruiz‑Velasco, V., Pordzik, J., Czlonkowska, A., Kurkowska‑Jastrzebska, I. ... Postula, M. (2019). Increased burden of rare deleterious variants of the KCNQ1 gene in patients with large‑vessel ischemic stroke. Molecular Medicine Reports, 19, 3263-3272. https://doi.org/10.3892/mmr.2019.9987
MLA
Janicki, P. K., Eyileten, C., Ruiz‑Velasco, V., Pordzik, J., Czlonkowska, A., Kurkowska‑Jastrzebska, I., Sugino, S., Imamura Kawasawa, Y., Mirowska‑Guzel, D., Postula, M."Increased burden of rare deleterious variants of the KCNQ1 gene in patients with large‑vessel ischemic stroke". Molecular Medicine Reports 19.4 (2019): 3263-3272.
Chicago
Janicki, P. K., Eyileten, C., Ruiz‑Velasco, V., Pordzik, J., Czlonkowska, A., Kurkowska‑Jastrzebska, I., Sugino, S., Imamura Kawasawa, Y., Mirowska‑Guzel, D., Postula, M."Increased burden of rare deleterious variants of the KCNQ1 gene in patients with large‑vessel ischemic stroke". Molecular Medicine Reports 19, no. 4 (2019): 3263-3272. https://doi.org/10.3892/mmr.2019.9987