Association and cis-mQTL analysis of variants in serotonergic genes associated with nicotine dependence in Chinese Han smokers

Han, Haijun; Liu, Qiang; Yang, Zhongli; Wang, Mu; Ma, Yunlong; Cao, Liyu; Cui, Wenyan; Yuan, Wenji; Payne, Thomas J.; Li, Lanjuan; Li, Ming D.

doi:10.1038/s41398-018-0290-8

Cited by 12 publications

(7 citation statements)

References 60 publications

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“…Although the two SNPs of rs1800544 and rs3758987 may not directly affect the amino acid sequence of the encoded protein, they may be in some linkage disequilibrium (LD) with important, but unexplored, functions [ 50 , 51 ]. On the other hand, these SNPs might influence the regulatory processes related to their gene expression and protein function.…”

Section: Discussionmentioning

confidence: 99%

The Predictive Role of ADRA2A rs1800544 and HTR3B rs3758987 Polymorphisms in Motion Sickness Susceptibility

Zhang

Sun

2021

IJERPH

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Motion sickness is a common central nervous system response, the primary sign of which is vomiting. Its susceptibility varies between individuals. To find predictive factors, we investigated the association of ADRA2A rs1800544 and HTR3B rs3758987 with motion sickness susceptibility and examined their mRNA changes during actual voyages. A total of 315 healthy college students were enrolled for SNP genotyping by the PCR-RFLP method. Blood samples were collected from another 42 subjects during two separate voyages to detect their mRNA expression changes at three time points. The frequency of the rs1800544 GG genotype in the susceptibility group was significantly higher (52.26%), and allele G increased the risk of motion sickness (OR = 1.585, 95% CI = 1.136–2.208). In the logistic regression model, the rs3758987 CC+TC genotype and rs1800544 GG genotype increased the risk of motion sickness-induced vomiting (OR = 2.105, 95% CI = 1.112–3.984; OR = 1.992, 95% CI = 1.114–3.571). The ADRA2A mRNA baseline was lower in the GG carriers and the HTR3B mRNA baseline was lower in the TC/CC carriers before sailing, then increased significantly within 24 h and then decreased after a long-term voyage. People carrying the rs1800544 GG genotype seem more susceptible to motion sickness. In combination with the incidence of vomiting during the actual-voyage experiments, our results indicate the involvement of rs1800544 and rs3758987 in motion sickness-induced vomiting.

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Section: Discussionmentioning

confidence: 99%

The Predictive Role of ADRA2A rs1800544 and HTR3B rs3758987 Polymorphisms in Motion Sickness Susceptibility

Zhang

Sun

2021

IJERPH

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“…Specifically, we used the same five genotypes tested in the preliminary study (Johnson et al, 2013) among EAs, and a three‐genotype combination in AAs that included the same SLC6A4 genotypes (5‐HTTLPR:LL and rs1042173:TT), but a different, population‐relevant HTR3B polymorphism. As the efficacy of ondansetron has not been specifically tested in predominantly AA populations stratified by HTR3A or HTR3B variants, we chose a missense polymorphism—rs1176744 in HTR3B —that has been associated with AUD in AAs and with various metabolic and substance use disorders (Enoch et al, 2011; Hammer et al, 2009; Han et al, 2018; Horjales‐Araujo et al, 2013; Kwon et al, 2019). The prevalence of the minor rs1176744:C allele is highest among AA individuals (~40%; Sherry et al, 2001).…”

Section: Methodsmentioning

confidence: 99%

A randomized, double‐blind, placebo‐controlled, pharmacogenetic study of ondansetron for treating alcohol use disorder

Seneviratne

Gorelick

Lynch

et al. 2022

Alcoholism Clin & Exp Res

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Background: In a previous study, ondansetron, a serotonin 5-HT 3 receptor antagonist, reduced drinking intensity (drinks/drinking day [DPDD]) among European-ancestry (EA) participants with moderate-to-severe alcohol use disorder (AUD) and variants in genes encoding the serotonin transporter (SLC6A4) and 5-HT 3A (HTR3A), and 5-HT 3B (HTR3B) receptors. We tested whether (1) ondansetron reduces DPDD among individuals of either European or African ancestry (AA), and (2) that reductions in DPDD are greatest among ondansetron-treated individuals with population-specific combinations of genotypes at SLC6A4, HTR3A, and HTR3B. Methods:In this 16-week, double-blind, placebo-controlled, parallel-group clinical trial, adults with AUD were randomized to receive low-dose oral ondansetron (0.33 mg twice daily) or placebo stratified by "responsive" versus "nonresponsive" genotype defined using population-specific genotypes at the three genetic loci. Generalized estimating equation regression models and a modified intent-to-treat analysis were used to compare the treatment groups on the primary outcome-DPDD-and two secondary outcomes-heavy drinking days per week [HDD] and drinks per day [DPD] across the 16 weeks of treatment.Results: Of 296 prospective participants screened, 95 (58 EA and 37 AA) were randomized and received at least one dose of study medication. In the modified intentto-treat analysis, the ondansetron group averaged 0.40 more DPDD (p = 0.51), 1.35 times as many HDD (p = 0.16), and 1.06 times as many DPD (p = 0.59) as the placebo group. There were no significant interactions with genotype. There were no studyrelated serious adverse events (AEs) and similar proportions of participants in the two treatment groups experienced AEs across organ systems. Conclusions:We found no evidence that low-dose oral ondansetron is beneficial in the treatment of AUD, irrespective of genotype, thus failing to confirm prior study findings. However, the study was underpowered to identify medication by genotype interactions.

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“…In a case–control cohort, one approach to identify mQTLs is to select DMPs associated with the phenotype and then select SNPs with minor allele frequency (MAF) ≥ 0.05 in the same genomic region [ 91 ]. Alternatively, researchers can select SNPs associated with the phenotype, and then select CpG sites in the same genomic region [ 92 ]. Either way, we recommend limiting the maximum window between CpG sites and SNPs, so only proximal or cis-methQTLs are identified.…”

Section: Downstream Analysesmentioning

confidence: 99%

“…cis-methQTLs refer to SNPs that are associated with CpGs within the same gene. The median window size for a cis-methQTL is approximately 18kb [ 93 ]; however, common thresholds range from 50 [ 92 ] to 100 kb [ 94 ]. After feature selection, statistical modelling is commonly used to identify how the methQTLs are associated with phenotype [ 90 ].…”

Section: Downstream Analysesmentioning

confidence: 99%

Epigenome-wide association studies: current knowledge, strategies and recommendations

et al. 2021

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The aetiology and pathophysiology of complex diseases are driven by the interaction between genetic and environmental factors. The variability in risk and outcomes in these diseases are incompletely explained by genetics or environmental risk factors individually. Therefore, researchers are now exploring the epigenome, a biological interface at which genetics and the environment can interact. There is a growing body of evidence supporting the role of epigenetic mechanisms in complex disease pathophysiology. Epigenome-wide association studies (EWASes) investigate the association between a phenotype and epigenetic variants, most commonly DNA methylation. The decreasing cost of measuring epigenome-wide methylation and the increasing accessibility of bioinformatic pipelines have contributed to the rise in EWASes published in recent years. Here, we review the current literature on these EWASes and provide further recommendations and strategies for successfully conducting them. We have constrained our review to studies using methylation data as this is the most studied epigenetic mechanism; microarray-based data as whole-genome bisulphite sequencing remains prohibitively expensive for most laboratories; and blood-based studies due to the non-invasiveness of peripheral blood collection and availability of archived DNA, as well as the accessibility of publicly available blood-cell-based methylation data. Further, we address multiple novel areas of EWAS analysis that have not been covered in previous reviews: (1) longitudinal study designs, (2) the chip analysis methylation pipeline (ChAMP), (3) differentially methylated region (DMR) identification paradigms, (4) methylation quantitative trait loci (methQTL) analysis, (5) methylation age analysis and (6) identifying cell-specific differential methylation from mixed cell data using statistical deconvolution.

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Association and cis-mQTL analysis of variants in serotonergic genes associated with nicotine dependence in Chinese Han smokers

Cited by 12 publications

References 60 publications

The Predictive Role of ADRA2A rs1800544 and HTR3B rs3758987 Polymorphisms in Motion Sickness Susceptibility

The Predictive Role of ADRA2A rs1800544 and HTR3B rs3758987 Polymorphisms in Motion Sickness Susceptibility

A randomized, double‐blind, placebo‐controlled, pharmacogenetic study of ondansetron for treating alcohol use disorder

Epigenome-wide association studies: current knowledge, strategies and recommendations

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