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Re-evaluating the clinical impact of functional regulatory variants Ying Ming, Yun-Ling Du, Meng-Na Zhang Ying Ming, Molecular Diagnosis Center,The Affiliated Hospital of Chengde Medical University, Chengde, 067000, China Yun-Ling Du, Molecular Diagnosis Center,The Affiliated Hospital of Chengde Medical University, Chengde, 067000, China Meng-Na Zhang, Molecular Diagnosis Center,The Affiliated Hospital of Chengde Medical University, Chengde, 067000, China Meng-Na Zhang, Hebei Key Laboratory of Panvascular Diseases, Chengde, 067000, China ORCID number: Ying Ming (0009-0006-2161-8207) , Yun-Ling Du (0000-0001-7624-3226) , Meng-Na Zhang (0000-0001-7624-3226) Author contributions: Ying Ming contributed to the initial drafting of the work; Yun-Ling Du contributed to the drafting process; Meng-Na Zhang contributed to the initial drafting and provided overall supervision to the drafting process; All authors have read and approved the final version of the manuscript. Conflict-of-interest statement: The authors declare that they have no conflict of interest. Corresponding author: Meng-Na Zhang, Molecular Diagnosis Center,The Affiliated Hospital of Chengde Medical University, Chengde, China zhangmengna2014@sina.com Abstract Serotonin 1A receptor polymorphism (5-HTR1A) C-1019G polymorphism (rs6295) is a functional regulatory variants reported to be related with multiple phenotypes including major depression, suicidal behavior and antidepressant response. However, clinical studies investigating this variant and its potential phenotypes had incongruous findings. Molecular studies on this variant showed it does regulate HTR1A expression but meta-analysis showed it had negative relationship with antidepressant drug response in major depressive disorder (MDD), as reported by Wu et al. in the lasted issue of the World Journal of Psychiatry. This suggested the importance of re-evaluating the clinical impact of functional regulatory variants. Key words: regulatory variants, snp-meta, snp-phenotype association Core Tip: Functional regulatory variants might have negative relationship with putative phenotypes even it do regulate gene expression. Single nucleotide polymorphism (SNP) meta analysis helps to identify a more robust SNP-phenotype relationship. We carefully read the article titled “Association between 5-HTR1A gene C-1019G polymorphism and antidepressant response in patients with major depressive disorder: A meta-analysis” published in the World Journal of Psychiatry by Wu et al.[1]. In this study the authors reviewed 11 clinical studies about serotonin 1A receptor polymorphism (5-HTR1A) C-1019G polymorphism (rs6295) and antidepressant response. Though reported to be related with major depression[2], suicidal behavior[3] and antidepressant response[4], rs6295 did not show significant association with antidepressant drug response in major depressive disorder (MDD) in this meta-analysis. Genome-wide association studies (GWAS) show to be a useful tool to investigate the effect of polymorphism on clinical phenotypes. Most disease-associated variants are non-coding variants. Researchers have developed multiple methods to identify functional regulatory variants from putative regulatory regions and their cis-regulated genes, like massively parallel reporter assays (MPRAs) and expression quantitative trait loci (eQTL)[5,6]. The 5-HTR1A C-1019G polymorphism (rs6295) reviewed by Wu et al. [1] is a functional upstream variant that affects HTR1A expression but not associates with antidepressant response in patients with MDD, though the 5-HT1A receptor is a primary target for most antidepressant drugs. This variant has been reported to influence HTR1A expression in numerous molecular studies. The C-allele of this variant is capable of interacting with transcription factors (TFs) such as Hes1, Hes5, and Deaf1, whereas the G-allele fails to bind these TFs [7]. Although these three TFs are typically regarded as repressors, the activity of Deaf1 at the 5-HT1A promoter exhibits opposing effects in presynaptic versus postsynaptic neuronal cells [7]. In the human prefrontal cortex, the G-allele demonstrates a lower expression level compared to the C-allele; however, this pattern does not hold true for the midbrain and hippocampus [8]. In a humanized mouse model, subjects with GG genotype exhibited higher levels of HTR1A mRNA and protein than those with CC genotype in a line-dependent manner [9]. Furthermore, in 5-HT1A-expressing neuronal cells, the G-allele was found to downregulate 5-HT1A expression [10]. These showed the complexity of regulatory variant function. Clinical researches on rs6295 had incongruous findings, raising the need for a SNP-based meta analysis. A single variant approach is a classical method to ascertain the relationship between a variant and putative phenotypes. Selective serotonin re-uptake Inhibitors (SSRIs) like fluoxetine, paroxetine, sertraline, citalopram, and fluvoxamine were included in this meta analysis, however, the result showed no significant correlation between this variation and antidepressant drug efficacy in MDD in the dominant model (CG vs CC), recessive model (GG vs CC), and combined dominant model (CG+GG vs CC). The 11 clinical studies collected in their meta analysis included multiple populations from over 10 countries with low to moderate heterogeneity and were scored 7-9 according to the Newcastle-Ottawa Scale (NOS), suggesting a result with higher confidence. The negative correlation might due to gene-gene interactions or gene-environment interactions in MDD and its treatment. A genome-wide linkage analysis for MDD showed that association of LHPP SNPs to MDD were depended on HTR1A -1019G allele [11]. Single variant approaches are limited by lower statistical detection power because most phenotypes result from the influence of many genetic variants in many genes and pathways[12]. This limitation is particularly pronounced in pharmacogenetics and multigenic diseases like MDD. Large-scale meta-analysis of GWAS might overcome this disadvantage. However, phenotype analysis involving rs6295 through GWAS is inherently limited due to its ambiguous nature (C/G). It is challenging to distinguish which complementary allele serves as the effect allele. Furthermore, the minor allele frequency (MAF) of rs6295 is G=0.483 in gnomAD and C=0.458 in 1000G, making it impossible to solve the problem by allele frequency. Ambiguous SNPs with allele frequencies close to 0.5 are usually removed in GWAS [13]. Therefore, a SNP meta-analysis remains a viable option for investigating rs6295. The clinical impacts of regulatory variants in monogenic Mendelian diseases have also been noticed. Many bioinformatic tools were developed to predict TF binding of regulatory variants like SNEEP [14]. Many of them use eQTL datasets as training and validation sets. In rs6295’s case, the variant had different functions in different brain regions, and showed negative significance to putative related phenotype. This suggested a limitation of using these tools to predict clinical candidate variants. However, there are few clinical curated regulatory variants databases available. There are only hundreds of regulatory variants in Clinvar database classified as pathogenic/likely pathogenic/benign/likely benign (data not shown). That’s not enough to feed a complex model. Overall, the negative relationship between the functional regulatory variant rs6295 and antidepressant response underscores the importance of re-evaluating the clinical significance of functional regulatory variants. Both positive and negative meta-analyses are essential for establishing robust relationships between polymorphisms and phenotypes. References [1] Wu HN, Zhu SY, Zhang LN, Shen BH, Xu LL. Association between 5-HTR1A gene C-1019G polymorphism and antidepressant response in patients with major depressive disorder: A meta-analysis. World J Psychiatry 2024; 14(10): 1573-1582 [2]Lemonde S, Turecki G, Bakish D, Du L, Hrdina PD, Bown CD, Sequeira A, Kushwaha N, Morris SJ, Basak A, Ou XM, Albert PR. Impaired repression at a 5-hydroxytryptamine 1A receptor gene polymorphism associated with major depression and suicide. J Neurosci. 2003 Sep 24;23(25):8788-99 [3]Hernández-Díaz, Y., Tovilla-Zárate, C. A., Castillo-Avila, R. G., Juárez-Rojop, I. E., Genis-Mendoza, A. D., López-Narváez, M. L., Villar-Juárez, G. E., & González-Castro, T. B. (2023). Association between the HTR1A rs6295 gene polymorphism and suicidal behavior: an updated meta-analysis. European archives of psychiatry and clinical neuroscience, 273(1), 5–14 [4]Lemonde S, Du L, Bakish D, Hrdina P, Albert PR. Association of the C(-1019)G 5-HT1A functional promoter polymorphism with antidepressant response. Int J Neuropsychopharmacol. 2004 Dec;7(4):501-6 [5]Abell NS, DeGorter MK, Gloudemans MJ, Greenwald E, Smith KS, He Z, Montgomery SB. Multiple causal variants underlie genetic associations in humans. Science. 2022 Mar 18;375(6586):1247-1254 [6]Umans BD, Battle A, Gilad Y. Where Are the Disease-Associated eQTLs? Trends Genet. 2021 Feb;37(2):109-124 [7]Czesak M, Lemonde S, Peterson EA, Rogaeva A, Albert PR. Cell-specific repressor or enhancer activities of Deaf-1 at a serotonin 1A receptor gene polymorphism. J Neurosci. 2006 Feb 8;26(6):1864-71 [8]Donaldson ZR, le Francois B, Santos TL, Almli LM, Boldrini M, Champagne FA, Arango V, Mann JJ, Stockmeier CA, Galfalvy H, Albert PR, Ressler KJ, Hen R. The functional serotonin 1a receptor promoter polymorphism, rs6295, is associated with psychiatric illness and differences in transcription. Transl Psychiatry. 2016 Mar 1;6(3):e746 [9]Cunningham AM, Santos TL, Gutzeit VA, Hamilton H, Hen R, Donaldson ZR. Functional Interrogation of a Depression-Related Serotonergic Single Nucleotide Polymorphism, rs6295, Using a Humanized Mouse Model. ACS Chem Neurosci. 2019 Jul 17;10(7):3197-3206 [10]Czesak M, Lemonde S, Peterson EA, Rogaeva A, Albert PR. Cell-specific repressor or enhancer activities of Deaf-1 at a serotonin 1A receptor gene polymorphism. J Neurosci. 2006 Feb 8;26(6):1864-71 [11]Neff CD, Abkevich V, Packer JC, Chen Y, Potter J, Riley R, Davenport C, DeGrado Warren J, Jammulapati S, Bhathena A, Choi WS, Kroeger PE, Metzger RE, Gutin A, Skolnick MH, Shattuck D, Katz DA. Evidence for HTR1A and LHPP as interacting genetic risk factors in major depression. Mol Psychiatry. 2009 Jun;14(6):621-30 [12]Defo J, Awany D, Ramesar R. From SNP to pathway-based GWAS meta-analysis: do current meta-analysis approaches resolve power and replication in genetic association studies? Brief Bioinform. 2023 Jan 19;24(1):bbac600 [13]Ndong Sima, C.A.A., Step, K., Swart, Y. et al. Methodologies underpinning polygenic risk scores estimation: a comprehensive overview. Hum. Genet. 143, 1265–1280 (2024) [14]Baumgarten N, Rumpf L, Kessler T, Schulz MH. A statistical approach for identifying single nucleotide variants that affect transcription factor binding. iScience. 2024 Apr 18;27(5):109765

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