Association between TRP channels and glutamatergic synapse gene polymorphisms and migraine and the comorbidities anxiety and depression in a Chinese population

Frontiers in Genetics

Genetics

Yuxing Liu¹  Yujia Gu²  Yu Liu²  Yashuang Zhao³  Mingxue Wang³  Lixin Kang³  Shuhan Meng³  Ran Yan³  Chang Su⁴  Jing Yang⁵  Degang Sun⁵  Dongjie Xue⁶  Yonghui Pan⁷  Yi Shan⁸  Ze Wan⁹  Shufen Li^1,10 

[1] Catheterization Room, Beidahuang Group Hongxinglong Hospital, Shuangyashan, China;Chronic Disease Prevention and Treatment Clinic, Heilongjiang Provincial Center for Disease Control and Prevention, Harbin, China;Department of Epidemiology, School of Public Health, Harbin Medical University, Harbin, China;Department of Internal Medicine, Baoquanling Farm Hospital, Hegang, China;Department of Neurology, Beidahuang Group Hongxinglong Hospital, Shuangyashan, China;Department of Neurology, Hegang He Mine Hospital, Hegang, China;Department of Neurology, The First Affiliated Hospital of Harbin Medical University, Harbin, China;Physical Examination Section, Beidahuang Group Baoquanling Hospital, Hegang, China;Science and Education Section, Beidahuang Group Hongxinglong Hospital, Shuangyashan, China;Vaccination Clinic, Baoquanling Farm Hospital, Hegang, China;

关键词: migraine;    gene polymorphisms;    TRP channels;    glutamate pathway;    glutamatergic synapse;   

DOI  :  10.3389/fgene.2023.1158028

 received in 2023-02-03, accepted in 2023-05-17,  发布年份 2023

来源: Frontiers

【 摘 要 】

Background: Genetic and environmental factors contribute to migraine and the comorbidities of anxiety and depression. However, the association between genetic polymorphisms in the transient receptor potential (TRP) channels and glutamatergic synapse genes with the risk of migraine and the comorbidities of anxiety and depression remain unclear.Methods: 251 migraine patients containing 49 comorbidities with anxiety and 112 with depression and 600 controls were recruited. A customized 48-plex SNPscan kit was used for genotyping 13 SNPs of nine target genes. Logistic regression was conducted to analyze these SNPs’ association with the susceptibility of migraine and comorbidities. The generalized multifactor dimension reduction (GMDR) was applied to analyze the SNP-SNP and gene-environment interactions. The GTEx database was used to examine the effects of the significant SNPs on gene expressions.Results: The TRPV1 rs8065080 and TRPV3 rs7217270 were associated with an increased risk of migraine in the dominant model [ORadj (95% CI): 1.75 (1.09–2.90), p = 0.025; 1.63 (1.02–2.58), p = 0.039, respectively]. GRIK2 rs2227283 was associated with migraine in the edge of significance [ORadj (95% CI) = 1.36 (0.99–1.89), p = 0.062]. In migraine patients, TRPV1 rs222741 was associated with both anxiety risk and depression risk in the recessive model [ORadj (95% CI): 2.64 (1.24–5.73), p = 0.012; 1.97 (1.02–3.85), p = 0.046, respectively]. TRPM8 rs7577262 was associated with anxiety (ORadj = 0.27, 95% CI = 0.10–0.76, p = 0.011). TRPV4 rs3742037, TRPM8 rs17862920 and SLC17A8 rs11110359 were associated with depression in dominant model [ORadj (95% CI): 2.03 (1.06–3.96), p = 0.035; 0.48 (0.23–0.96), p = 0.042; 0.42 (0.20–0.84), p = 0.016, respectively]. Significant eQTL and sQTL signals were observed for SNP rs8065080. Individuals with GRS (Genetic risk scores) of Q4 (14–17) had a higher risk of migraine and a lower risk of comorbidity anxiety than those with Genetic risk scores scores of Q1 (0–9) groups [ORadj (95% CI): 2.31 (1.39–3.86), p = 0.001; 0.28 (0.08–0.88), p = 0.034, respectively].Conclusion: This study suggests that TRPV1 rs8065080, TRPV3 rs7217270, and GRIK2 rs2227283 polymorphism may associate with migraine risk. TRPV1 rs222741 and TRPM8 rs7577262 may associate with migraine comorbidity anxiety risk. rs222741, rs3742037, rs17862920, and rs11110359 may associate with migraine comorbidity depression risk. Higher GRS scores may increase migraine risk and decrease comorbidity anxiety risk.

【 授权许可】

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Copyright © 2023 Wang, Gu, Meng, Kang, Yang, Sun, Liu, Wan, Shan, Xue, Su, Li, Yan, Liu, Zhao and Pan.