Международный эндокринологический журнал Том 19, №2, 2023

Оцінка впливу однонуклеотидних поліморфізмів генів рецептора вітаміну D (rs2228570), BDNF (rs6265) та NMDA (rs4880213) на експресію генів у різних тканинах

Авторы: I. Kamyshna (1), L. Pavlovych (2), I. Pankiv (2), V. Pankiv (3), A. Kamyshnyi (1)
(1) — I. Horbachevsky Ternopil National Medical University, Ternopil, Ukraine
(2) — Bukovinian State Medical University, Chernivtsi, Ukraine
(3) — Ukrainian Scientific and Practical Center for Endocrine Surgery, Transplantation of Endocrine Organs and Tissues of the Ministry of Health of Ukraine, Kyiv, Ukraine

Рубрики: Эндокринология

Разделы: Клинические исследования

Актуальність. Питання щодо асоціації окремих та комбінованих варіацій і мутацій генів з хворобами щитоподібної залози та порушеннями нервової системи залишаються недостатньо дослідженими. Важливим аспектом є виявлення впливу окремих поліморфізмів генів на функціональну активність клітин, зокрема на експресію генів. На сьогодні генетика експресії генів значною мірою залежить від ідентифікації локусів кількісних ознак експресії (eQTL). Метою дослідження був пошук eQTL для однонуклеотидних поліморфізмів (SNP) генів BDNF (rs6265), VDR (rs2228570) та NMDA (rs4880213). Матеріали та методи. Використовували публічні бази даних (QTLbase: http://www.mulinlab.org/qtlbase/index.html, GTExPortal: https://gtexportal.org). Результати представлені у вигляді номінальних рівнів значущості для кожного SNP генів BDNF, VDR та NMDA. Результати. Використовуючи базу даних QTLbase, ми виявили статистично значущі (p ≤ 0,05) асоціації rs6265 з експресію 17 генів (BDNF-AS, BDNF, LDHC, AC104563.1, BBOX1, SPTY2D1OS, YWHABP2, LINC00678, LIN7C, GTF2H1, METTL15, IMMP1L, KIF18A, HPS5, NAV2, LGR4, CCDC34) у різних тканинах. Для rs4880213 ми знайшли асоціації з рівнями експресії 49 генів (ARRDC1-AS1, TPRN, SSNA1, SAPCD2, UAP1L1, NPDC1, MAN1B1, PTGDS, SNHG7, NDOR1, TRAF2, PHPT1, EGFL7, EHMT1, RNF208, PNPLA7, LCNL1, DPP7, LCN12, STPG3, CCDC183-AS1, ABCA2, RNF224, ENTPD2, PAXX, CLIC3, C9orf163, LCN15, MAN1B1-DT, FAM166A, FAM166A, LRRC26, STPG3-AS1, AGPAT2, ANAPC2, DPH7, ZMYND19, NSMF, MRPL341, EXD, TUBB4B, NELFB, ARRDC1, EDF1, FBXW5, DIPK1B, MAMDC4, RABL6, TMEM141, TMEM203) у 16 різних тканинах. Крім того, виявили статистично значущі (p ≤ 0,05) зв’язки між rs2228570 та експресією 29 генів (ASB8, TMEM106C, KANSL2, DDX23, CCNT1, HDAC7, RPAP3, PFKM, SENP1, RND1, PCED1B, AC004466.1, AMIGO2, ZNF641, ENDOU, RAPGEF3, VDR, AC004241.1, AC004801.2, AC121338.1, LINC02354, SNORA2A, LINC02416, AC074029.3, AC004241.5, AC008083.3, COL2A1, CCDC184, SLC48A1) у 17 різних тканинах. Висновки. Однонуклеотидні поліморфізми генів BDNF (rs6265), VDR (rs2228570) і NMDA (rs4880213) впливають на експресію генів у різних клітинах і тканинах. Застосування каталога eQTL надає важливий ресурс для розуміння молекулярної основи поширених генетичних захворювань.

Background. Questions regarding the association of individual and combined gene variations and mutations with thyroid disease and nervous system disorders remain insufficiently researched and require further study to facilitate early diagnosis of nervous system damage on the background of thyroid pathology, disease prognosis, and timely treatment and prevention. An important issue is the identification of the influence of individual polymorphisms in these genes on the functional activity of cells, including gene expression. Currently, gene expression genetics largely depends on the identification of expression quantitative trait loci (eQTL), which are the links between gene expression and genotype at a locus. The purpose of the study was to search for eQTL in single nucleotide polymorphisms (SNPs) of the BDNF gene (rs6265), VDR gene (rs2228570), and NMDA gene (rs4880213). The results were presented as nominal p-values for each SNP of the BDNF, VDR, and NMDA genes. Materials and methods. We use publicly available databases (QTLbase: http://www.mulinlab.org/qtlbase/index.html, GTExPortal: https://gtexportal.org). Results. Using the QTLbase, we identified statistically significant (p ≤ 0.05) associations of rs6265 with the expression of 17 genes (BDNF-AS, BDNF, LDHC, AC104563.1, BBOX1, SPTY2D1OS, YWHABP2, LINC00678, LIN7C, GTF2H1, METTL15, IMMP1L, KIF18A, HPS5, NAV2, LGR4, CCDC34) in various tissues. For rs4880213, we found a significant association with the expression levels of 49 genes (ARRDC1-AS1, TPRN, SSNA1, SAPCD2, UAP1L1, NPDC1, MAN1B1, PTGDS, SNHG7, NDOR1, TRAF2, PHPT1, EGFL7, EHMT1, RNF208, PNPLA7, LCNL1, DPP7, LCN12, STPG3, CCDC183-AS1, ABCA2, RNF224, ENTPD2, PAXX, CLIC3, C9orf163, LCN15, MAN1B1-DT, FAM166A, FAM166A, LRRC26, STPG3-AS1, AGPAT2, ANAPC2, DPH7, ZMYND19, NSMF, MRPL41, EXD3, TUBB4B, NELFB, ARRDC1, EDF1, FBXW5, DIPK1B, MAMDC4, RABL6, TMEM141, TMEM203) in 16 different tissues. Additionally, we identified statistically significant (p ≤ 0.05) associations of rs2228570 with the expression of 29 genes (ASB8, TMEM106C, KANSL2, DDX23, CCNT1, HDAC7, RPAP3, PFKM, SENP1, RND1, PCED1B, AC004466.1, AMIGO2, ZNF641, ENDOU, RAPGEF3, VDR, AC004241.1, AC004801.2, AC121338.1, LINC02354, SNORA2A, LINC02416, AC074029.3, AC004241.5, AC008083.3, COL2A1, CCDC184, SLC48A1) in 17 different tissues. Conclusions. Single nucleotide polymorphisms of the BDNF (rs6265), VDR (rs2228570), and NMDA genes (rs4880213) affect gene expression in various cells and tissues. The use of this extensive eQTL catalog provides an important resource for understanding the molecular basis of common genetic diseases.

Ключевые слова

генотип; експресія; поліморфізм нуклеотидів; ген BDNF (rs6265); ген VDR (rs2228570); ген NMDA (rs4880213)

genotype; expression; nucleotide polymorphisms; BDNF gene (rs6265); VDR gene (rs2228570); NMDA gene (rs4880213)

doi: http://dx.doi.org/10.22141/2224-0721.19.2.2023.1250

Introduction

The modern search for effective targeted therapy for endocrine diseases is based on transcriptome [1], variome [2, 3], and proteome data [4]. Our previous studies have verified that diversities in gene expression and variomes may stipulate the appearance of neurological complications resulting from thyroid pathology [5, 6].

The exploitation of genotype-phenotype causality can enhance our understanding of the genetic basis of complex traits [7]. Currently, expression quantitative trait loci (eQTLs) are the most abundant and systematically surveyed class of functional consequence for genetic variation [8]. Recent genetic studies on gene expression have discovered thousands of eQTLs in various tissue types for the majority of human genes.

The availability of this extensive eQTL catalog provides an essential resource for investigating the molecular basis of common genetic diseases [9]. The establishment of reference datasets for eQTLs and other molecular phenotype variants will significantly reinforce the interpretation of personalized genomes and provide a valuable framework for understanding phenotypic variability and disease risk.

A standard eQTL analysis typically involves a direct association test between genetic variation markers and gene expression levels, which are usually measured in tens or hundreds of individuals [9, 10]. This association analysis can be performed either proximally or distally to the gene. Regulatory variants have been characterized as either cis or trans-acting, depending on the predicted nature of interactions and physical distance from the gene they regulate. Studies suggest that most of the regulatory control takes place locally, in the vicinity of genes.

However, it is important to note that gene expression signatures are cell-type specific, raising the question of whether regulatory control of expression is also cell-type dependent. While most human eQTL studies have been performed on blood-derived cells or cell lines, a significant tissue-specific component of cis regulation has been systematically reported [11]. Typically, variants within 1 Mb (megabase) on either side of a gene’s TSS (transcription start site) are called cis-acting (cis-QTL) in conventional eQTL mapping literature.

The aim of the study was to conduct a search for expression quantitative trait loci (eQTL) for single nucleotide polymorphisms (SNPs) of the BDNF gene (rs6265), VDR gene (rs2228570), and NMDA gene (rs4880213). The results were presented as nominal p-values for each SNP of the BDNF, VDR, and NMDA genes.

Materials and methods

We assessed expression quantitative trait loci (eQTL) for SNPs by utilizing a publicly available database (QTLbase: http://www.mulinlab.org/qtlbase/index.html). The outcomes were reported as nominal p-values for each SNP. The results were presented as nominal p-values for each SNP of the BDNF, VDR, and NMDA genes.

Results

Expression of BDNF, VDR, and GRIN1 genes is observed in a large number of cells and tissues (Fig. 1). However, a more important question is to determine the impact of individual SNPs in these genes on the functional activity of cells, including gene expression, DNA methylation, histone modification, protein expression, and microRNA expression.

The current understanding of gene expression genetics heavily relies on identifying eQTLs, which refer to the association between gene expression and the genotype at a specific locus. Genome-wide studies on eQTLs have demonstrated that these loci account for a substantial portion of gene expression variation, with up to 90 % of the variation in some genes attributed to nucleotide variants. To assess whether the three aforementioned SNPs act as eQTLs in different tissues, we investigated the QTLbase database. The eQTL analysis revealed statistically significant (p < 0.05) effective alleles and p values for all three SNPs (Table 1).

Using the QTLbase database, we established statistically significant (p ≤ 0.05) associations between rs6265 and the expression of 17 genes (BDNF-AS, BDNF, LDHC, AC104563.1, BBOX1, SPTY2D1OS, YWHABP2, LINC00678, LIN7C, GTF2H1, METTL15, IMMP1L, KIF18A, HPS5, NAV2, LGR4, CCDC34) in various tissues (Fig. 1A). Some of them are presented in Table 1. Specifically, the T allele of rs6265 is associated with increased expression of the BDNF gene in stem cell-iPSC (β = 0.32, p = 1.89E-13), decreased expression of BDNF genes in the pancreas (β = –0.19, p = 0.00647), BDNF-AS in the thyroid gland (β = –0.28, p = 5.49E-09), brain (β = –0.19, p = 0.0000563), kidney (β = – 0.28, p = 1.17E-06), and other tissues (Table 1).

We identified a significant association between rs4880213 and the expression level of 49 genes (ARRDC1-AS1, TPRN, SSNA1, SAPCD2, UAP1L1, NPDC1, MAN1B1, PTGDS, SNHG7, NDOR1, TRAF2, PHPT1, EGFL7, EHMT1, RNF208, PNPLA7, LCNL1, DPP7, LCN12, STPG3, CCDC183-AS1, ABCA2, RNF224, ENTPD2, PAXX, CLIC3, C9orf163, LCN15, MAN1B1-DT, FAM166A, FAM166A, LRRC26, STPG3-AS1, AGPAT2, ANAPC2, DPH7, ZMYND19, NSMF, MRPL41, EXD3, TUBB4B, NELFB, ARRDC1, EDF1, FBXW5, DIPK1B, MAMDC4, RABL6, TMEM141, TMEM203) in 16 different tissues (Fig. 1B, Table 1). For example, the T allele of rs4880213 is associated with the induction of transcriptional activity of the MAN1B1 gene in the thyroid gland (β = 0.16, p = 8.35E-07), peripheral nervous system (β = 0.15, p = 8.99E-06), and the SAPCD2 (β = 0.29, p = 2.22E-07) and ENTPD2 (β = 0.28, p = 2.36E-07) genes in blood. At the same time, the T allele of rs4880213 is associated with the transcriptional repression of the NPDC1 gene in fibroblasts (β = –0.16, p = 3.48E-06) and in the artery-aorta (β = –0.19, p = 1.59 E-05), as well as the FAM166A gene in the eyes (β = –0.09, p = 0.00814) (Table 1).

Additionally, we identified statistically significant (p ≤ 0.05) associations of rs2228570 with the expression of 29 genes (ASB8, TMEM106C, KANSL2, DDX23, CCNT1, HDAC7, RPAP3, PFKM, SENP1, RND1, PCED1B, AC004466.1, AMIGO2, ZNF641, ENDOU, RAPGEF3, VDR, AC004241.1, AC004801.2, AC121338.1, LINC02354, SNORA2A, LINC02416, AC074029.3, AC004241.5, AC008083.3, COL2A1, CCDC184, SLC48A1) in 17 diffe–rent tissues (although the most pronounced changes in transcriptional activity were observed in blood cells) (Fig. 1C, Table 1). Both the A and G alleles of rs2228570 have an impact on gene expression (Table 1). For instance, the A allele of rs2228570 is associated with increased expression of the VDR gene in blood CD4+ T cells (β = 2.93, p = 0.00336), the RAPGEF3 gene in blood CD14+ monocytes (β = 0.20, p = 0.00354), while the G allele of rs2228570 induces transcription of the HDAC7 gene in blood CD8+ T cells (β = 0.14, p = 0.000429) and the PCED1B gene in activated blood CD4+ T cells (β = 0.09, p = 0.00271) (Table 1).

Using another database — GTExPortal (https://gtexportal.org) — allows for additional graphical visualization of the influence of individual alleles on the expression of different genes using the online tool eQTL Dashboard (Fig. 2).

Discussion

The use of genotype-phenotype causality can enhance our understanding of the genetic basis of complex traits. So, the use of genotype-phenotype causality can help deepen our understanding of the genetic basis of complex traits [12]. Genotype-phenotype causality indicates which genes and their interactions lead to the manifestation of a particular trait in an organism. This can be especially useful for understanding complex traits that are determined by the action of many genes and environmental factors.

For example, the application of genotype-phenotype causality can help to identify which genes are responsible for the development of complex diseases. With this approach, it is possible to establish a link between individual genes and corresponding phenotypes, which allows for more accurate identification of the causes of the disease and the development of effective treatment methods [13].

In addition, genotype-phenotype causality can be useful for understanding other complex traits such as predisposition to depression and anxiety [14]. Through the analysis of genetic data and observations of phenotypes, it is possible to determine which genes are responsible for these traits and understand how they interact with each other [15, 16].

Therefore, the use of genotype-phenotype causality can help to expand our understanding of the genetic basis of complex traits, which in turn can lead to the development of new technologies and treatment methods.

Conclusions

Single nucleotide polymorphisms of the BDNF gene (rs6265), VDR gene (rs2228570), and NMDA gene (rs4880213) affect gene expression in various cells and tissues. The use of this extensive eQTL catalog provides an important resource for understanding the molecular basis of common genetic diseases.

Ethical approval. Our study was conducted according to the Declaration of Helsinki adopted in 1975 and revised in 2008, and the ethical principles were entirely respected.

Consent to participate. Written informed consent was obtained from the participants.

Data availability. The data of this study is available by request.

Conflict of interest. The authors declare that there is no conflict of interest.

Received 02.02.2023

Revised 10.03.2023

Accepted 20.03.2023

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