Association Analysis Of Variants Research Articles

VikNGS: a C++ variant integration kit for next generation sequencing association analysis.

SummaryIntegration of next generation sequencing data (NGS) across different research studies can improve the power of genetic association testing by increasing sample size and can obviate the need for sequencing controls. If differential genotype uncertainty across studies is not accounted for, combining datasets can produce spurious association results. We developed the Variant Integration Kit for NGS (VikNGS), a fast cross-platform software package, to enable aggregation of several datasets for rare and common variant genetic association analysis of quantitative and binary traits with covariate adjustment. VikNGS also includes a graphical user interface, power simulation functionality and data visualization tools.Availability and implementationThe VikNGS package can be downloaded at http://www.tcag.ca/tools/index.html.Supplementary information Supplementary data are available at Bioinformatics online.

Assessment of predicted enzymatic activity of α-N-acetylglucosaminidase variants of unknown significance for CAGI 2016.

The NAGLU challenge of the fourth edition of the Critical Assessment of Genome Interpretation experiment (CAGI4) in 2016, invited participants to predict the impact of variants of unknown significance (VUS) on the enzymatic activity of the lysosomal hydrolase α-N-acetylglucosaminidase (NAGLU). Deficiencies in NAGLU activity lead to a rare, monogenic, recessive lysosomal storage disorder, Sanfilippo syndrome type B (MPS type IIIB). This challenge attracted 17 submissions from 10 groups. We observed that top models were able to predict the impact of missense mutations on enzymatic activity with Pearson's correlation coefficients of up to .61. We also observed that top methods were significantly more correlated with each other than they were with observed enzymatic activity values, which we believe speaks to the importance of sequence conservation across the different methods. Improved functional predictions on the VUS will help population-scale analysis of disease epidemiology and rare variant association analysis.

Goat SPEF2: Expression profile, indel variants identification and association analysis with litter size

SPEF2 (sperm flagella 2 gene), also known as KPL2, plays important roles in germ cell development. The aim of this study was to investigate the mRNA expression profiles of goat SPEF2 among different tissues, as well as the relationship between SPEF2 indel polymorphisms and reproductive traits of 1104 Shaanbei white cashmere (SBWC) goats, and fully explore the expression characteristics and genetic effects of goat SPEF2. Results showed that SPEF2 was widely expressed and presented dynamic changes in goat testis at different developmental stages. SPEF2 mRNA expression level during meiosis phase was approximately equal to that during mitosis phase. Additionally, three potential insertion/deletion (indel) mutations were tested and verified by PCR and sequencing methods among 14 potential indel variant which are related to reproduction traits. For L-8 (NC_030827.1:g.38459098_38459107delTCAGTTCAGT: rs644277083), association test revealed that the goats with heterozygous ID had significantly more lambs than those with homozygous type II (P < 0.05). The influences of joint genotypes of L-8 and L-1 (NC_030827.1:g.38527458_38527459insGTTCACACCCAGTT) on goat reproductive traits were significant (P < 0.05). The association between combined genotypes and litter size showed that goats with homozygous genotypes had larger litter size than that of any of the other genotypes. Furthermore, through bioinformatics analysis, the remarkable influence of indel L-8 on traits might be caused by the change in AR (androgen receptor) binding site. These preliminary results are helpful to comprehensively study the function of SPEF2 and to provide theoretical references for SBWC goats breeding.

QTL-mapping and genomic prediction for bovine respiratory disease in U.S. Holsteins using sequence imputation and feature selection

BackgroundNational genetic evaluations for disease resistance do not exist, precluding the genetic improvement of cattle for these traits. We imputed BovineHD genotypes to whole genome sequence for 2703 Holsteins that were cases or controls for Bovine Respiratory Disease and sampled from either California or New Mexico to construct and compare genomic prediction models. The sequence variation reference dataset comprised variants called for 1578 animals from Run 5 of the 1000 Bull Genomes Project, including 450 Holsteins and 29 animals sequenced from this study population. Genotypes for 9,282,726 variants with minor allele frequencies ≥5% were imputed and used to obtain genomic predictions in GEMMA using a Bayesian Sparse Linear Mixed Model.ResultsVariation explained by markers increased from 13.6% using BovineHD data to 14.4% using imputed whole genome sequence data and the resolution of genomic regions detected as harbouring QTL substantially increased. Explained variation in the analysis of the combined California and New Mexico data was less than when data for each state were separately analysed and the estimated genetic correlation between risk of Bovine Respiratory Disease in California and New Mexico Holsteins was − 0.36. Consequently, genomic predictions trained using the data from one state did not accurately predict disease risk in the other state. To determine if a prediction model could be developed with utility in both states, we selected variants within genomic regions harbouring: 1) genes involved in the normal immune response to infection by pathogens responsible for Bovine Respiratory Disease detected by RNA-Seq analysis, and/or 2) QTL identified in the association analysis of the imputed sequence variants. The model based on QTL selected variants is biased but when trained in one state generated BRD risk predictions with positive accuracies in the other state.ConclusionsWe demonstrate the utility of sequence-based and biology-driven model development for genomic selection. Disease phenotypes cannot be routinely recorded in most livestock species and the observed phenotypes may vary in their genomic architecture due to variation in the pathogen composition across environments. Elucidation of trait biology and genetic architecture may guide the development of prediction models with utility across breeds and environments.

Association analysis of the VEGF gene variants with breast cancer susceptibility and tumor characteristics in an indigenous population: A pilot study

BackgroundSingle Nucleotide Polymorphisms -2578C/A and + 936C/T in the Vascular Endothelial Growth Factor (VEGF) gene have shown associations with breast cancer susceptibility and tumor characteristics in different populations with conflicting results. AimThe present study conducted the association analyses of these polymorphisms with breast cancers in Pakistani population. Subjects and methodsThe study comprised 336 participants with 124 breast cancer patients and 212 matched controls. After informed consent, blood samples were collected followed by DNA extraction. PCR-RFLP methods were used for the genotyping of VEGF -2578C/A in the promoter region, and + 936C/T polymorphisms in 3′- untranslated region, respectively. Statistical analyses were performed. Pearson's χ2 test, Cochran-Armitage trend test, and odds ratio analysis were carried out to evaluate and quantify the breast-cancer associated risk. The association of these polymorphisms with tumor characteristics and prognostic factors including two year-survival was also evaluated. ResultsThe polymorphisms did not show statistically significant associations with either breast cancer risk or tumor characteristics including size, stage, grade, and two-year survival. ConclusionsThe pilot study presented here shows lack of association of VEGF polymorphisms with breast cancers in Pakistani population.

Association Analysis of Polymorphic Gene Variants in the JAK/STAT Signaling Pathway with Aging and Longevity

The aim of this study was to investigate the associations between the polymorphic loci in the JAK/STAT signaling pathway and the aging processes and longevity in the populations of ethnic Tatars. For this aim, we analyzed the age dynamics of genotype frequencies of the JAK1 (32454C>T, rs310216), JAK3 (14385C>T, rs3212780), STAT1 (14228A>C, rs12693591), STAT3 (19006G>C, rs2293152), and STAT5A (1985T>C, rs9889323) genes. Using logistic regression analysis, we discovered the association of these polymorphic loci with advanced age. In the general study group, the probability of the JAK1*C/*Т genotype was higher among persons of advanced age (69–80 years old, p = 0.031, OR = 1.070). In turn, the chance to reach advanced age was lower among the carriers of the JAK1*Т/*Т (58–82 years old, p = 0.014, OR = 0.958) and STAT5A*T/*T (46–109 years old, p < 0.001, OR = 0.979) genotypes. The probability of attaining longevity was higher among men with the STAT3*С/*С genotype (25–98 years old, p = 0.027, OR = 1.016) and was lower among men with the STAT3*G/*С genotype (73–98 years old, p = 0.044, OR = 0.950). In the group of women, the probability to reach 80 years of age and over was higher among carriers of the JAK3*Т/*С (48–81 years old, p = 0.046, OR = 1.024), STAT1*С/*A (61–88 years old, p = 0.041, OR = 1.035), and STAT5A*T/*C (46–82 years old, p < 0.0001, OR = 1.044) genotypes. In turn, among middle age women with the STAT1*С/*С genotype, the probability to attain longevity was lower (55–109 years old, p = 0.013, OR = 0.980).

Multiple rare and common variants in APOB gene locus associated with oxidatively modified low-density lipoprotein levels.

Oxidatively modified low-density lipoproteins (oxLDL) play an important role in the occurrence and progression of atherosclerosis. To identify the genetic factors influencing the oxLDL levels, we have genotyped 776 DNA samples of Russian individuals for 196,725 single-nucleotide polymorphisms (SNPs) using the Cardio-MetaboChip (Illumina, USA) and conducted genome-wide association study (GWAS). Fourteen common variants in the locus including APOB gene were significantly associated with the oxLDL levels (P < 2.18 × 10−7). These variants explained only 6% of the variation in the oxLDL levels. Then, we assessed the contribution of rare coding variants of APOB gene to the oxLDL levels. Individuals with the extreme oxLDL levels (48 with the lowest and 48 with the highest values) were selected for targeted sequencing of the region including APOB gene. To evaluate the contribution of the SNPs to the oxLDL levels we used various statistical methods for the association analysis of rare variants: WST, SKAT, and SKAT-O. We revealed that both synonymous and nonsynonymous SNPs affected the oxLDL levels. For the joint analysis of the rare and common variants, we conducted the SKAT-C testing and found a group of 15 SNPs significantly associated with the oxLDL levels (P = 2.14 × 10−9). Our results indicate that the oxLDL levels depend on both common and rare variants of the APOB gene.

Identification of regulatory variants associated with genetic susceptibility to meningococcal disease

Non-coding genetic variants play an important role in driving susceptibility to complex diseases but their characterization remains challenging. Here, we employed a novel approach to interrogate the genetic risk of such polymorphisms in a more systematic way by targeting specific regulatory regions relevant for the phenotype studied. We applied this method to meningococcal disease susceptibility, using the DNA binding pattern of RELA – a NF-kB subunit, master regulator of the response to infection – under bacterial stimuli in nasopharyngeal epithelial cells. We designed a custom panel to cover these RELA binding sites and used it for targeted sequencing in cases and controls. Variant calling and association analysis were performed followed by validation of candidate polymorphisms by genotyping in three independent cohorts. We identified two new polymorphisms, rs4823231 and rs11913168, showing signs of association with meningococcal disease susceptibility. In addition, using our genomic data as well as publicly available resources, we found evidences for these SNPs to have potential regulatory effects on ATXN10 and LIF genes respectively. The variants and related candidate genes are relevant for infectious diseases and may have important contribution for meningococcal disease pathology. Finally, we described a novel genetic association approach that could be applied to other phenotypes.

Genetic analysis of DNA methylation and hydroxymethylation genes in Parkinson's disease

DNA methylation is an important regulatory mechanism of Parkinson's disease (PD). To investigate the relationship between DNA methylation and hydroxymethylation genes and PD, we performed gene-targeted sequencing using molecular inversion probes in a Chinese PD population. We sequenced 12 genes related to DNA methylation and hydroxymethylation in 1657 patients and 1394 control subjects. We conducted genewise association analyses of rare variants detected in the present study and identified the TET1 gene as important in PD (p = 0.0037738, 0.013, 0.019521 (b.collapse test, variable threshold test, and skat-o test, respectively; sex + age as covariates). However, no positive results were observed when conducting association analyses on common variants in these genes. We performed a comprehensive analysis of associations between variants of DNA methylation and hydroxymethylation genes and PD, resulting in determination that TET1 might play a role in PD.

Using Whole Genome Sequencing in an African Subphenotype of Myasthenia Gravis to Generate a Pathogenetic Hypothesis.

Myasthenia gravis (MG) is a rare, treatable antibody-mediated disease which is characterized by muscle weakness. The pathogenic antibodies are most frequently directed at the acetylcholine receptors (AChRs) at the skeletal muscle endplate. An ophthalmoplegic subphenotype of MG (OP-MG), which is characterized by treatment resistant weakness of the extraocular muscles (EOMs), occurs in a proportion of myasthenics with juvenile symptom onset and African genetic ancestry. Since the pathogenetic mechanism(s) underlying OP-MG is unknown, the aim of this study was to use a hypothesis-generating genome-wide analysis to identify candidate OP-MG susceptibility genes and pathways. Whole genome sequencing (WGS) was performed on 25 AChR-antibody positive myasthenic individuals of African genetic ancestry sampled from the phenotypic extremes: 15 with OP-MG and 10 individuals with control MG (EOM treatment-responsive). Variants were called according to the Genome Analysis Toolkit (GATK) best practice guidelines using the hg38 reference genome. In addition to single variant association analysis, variants were mapped to genes (±200 kb) using VEGAS2 to calculate gene-based test statistics and HLA allele group assignment was inferred through “best-match” alignment of reads against the IMGT/HLA database. While there were no single variant associations that reached genome-wide significance in this exploratory sample, several genes with significant gene-based test statistics and known to be expressed in skeletal muscle had biological functions which converge on muscle atrophy signaling and myosin II function. The closely linked HLA-DPA1 and HLA-DPB1 genes were associated with OP-MG subjects (gene-based p < 0.05) and the frequency of a functional A > G SNP (rs9277534) in the HLA-DPB1 3′UTR, which increases HLA-DPB1 expression, differed between the two groups (G-allele 0.30 in OP-MG vs. 0.60 in control MG; p = 0.04). Furthermore, we show that rs9277534 is an HLA-DBP1 expression quantitative trait locus in patient-derived myocytes (p < 1 × 10−3). The application of a SNP to gene to pathway approach to this exploratory WGS dataset of African myasthenic individuals, and comparing dichotomous subphenotypes, resulted in the identification of candidate genes and pathways that may contribute to OP-MG susceptibility. Overall, the hypotheses generated by this work remain to be verified by interrogating candidate gene and pathway expression in patient-derived extraocular muscle.

A modified association test for rare and common variants based on affected sib-pair design

Current genome-wide association analysis has identified a great number of rare and common variants associated with common complex traits, however, more effective approaches for detecting associations between rare and common variants with common diseases are still demanded. Approaches for detecting rare variant association analysis will compromise the power when detecting the effects of rare and common variants simultaneously. In this paper, we extend an existing method of testing for rare variant association based on affected sib pairs (TOW-sib) and propose a variable weight test for rare and common variants association based on affected sib pairs (abbreviated as VW-TOWsib). The VW-TOWsib can be used to achieve the purpose of detecting the association of rare and common variants with complex diseases. Simulation results in various scenarios show that our proposed method is more powerful than existing methods for detecting effects of rare and common variants. At the same time, the VW-TOWsib also performs well as a method for rare variant association analysis.

Real world scenarios in rare variant association analysis: the impact of imbalance and sample size on the power in silico

BackgroundThe development of sequencing techniques and statistical methods provides great opportunities for identifying the impact of rare genetic variation on complex traits. However, there is a lack of knowledge on the impact of sample size, case numbers, the balance of cases vs controls for both burden and dispersion based rare variant association methods. For example, Phenome-Wide Association Studies may have a wide range of case and control sample sizes across hundreds of diagnoses and traits, and with the application of statistical methods to rare variants, it is important to understand the strengths and limitations of the analyses.ResultsWe conducted a large-scale simulation of randomly selected low-frequency protein-coding regions using twelve different balanced samples with an equal number of cases and controls as well as twenty-one unbalanced sample scenarios. We further explored statistical performance of different minor allele frequency thresholds and a range of genetic effect sizes. Our simulation results demonstrate that using an unbalanced study design has an overall higher type I error rate for both burden and dispersion tests compared with a balanced study design. Regression has an overall higher type I error with balanced cases and controls, while SKAT has higher type I error for unbalanced case-control scenarios. We also found that both type I error and power were driven by the number of cases in addition to the case to control ratio under large control group scenarios. Based on our power simulations, we observed that a SKAT analysis with case numbers larger than 200 for unbalanced case-control models yielded over 90% power with relatively well controlled type I error. To achieve similar power in regression, over 500 cases are needed. Moreover, SKAT showed higher power to detect associations in unbalanced case-control scenarios than regression.ConclusionsOur results provide important insights into rare variant association study designs by providing a landscape of type I error and statistical power for a wide range of sample sizes. These results can serve as a benchmark for making decisions about study design for rare variant analyses.

A comprehensive gene-environment interaction analysis in Ovarian Cancer using genome-wide significant common variants.

As a follow-up to genome-wide association analysis of common variants associated with ovarian carcinoma (cancer), our study considers seven well-known ovarian cancer risk factors and their interactions with 28 genome-wide significant common genetic variants. The interaction analyses were based on data from 9971 ovarian cancer cases and 15,566 controls from 17 case-control studies. Likelihood ratio and Wald tests for multiplicative interaction and for relative excess risk due to additive interaction were used. The top multiplicative interaction was noted between oral contraceptive pill (OCP) use (ever vs. never) and rs13255292 (p value = 3.48 × 10-4 ). Among women with the TT genotype for this variant, the odds ratio for OCP use was 0.53 (95% CI = 0.46-0.60) compared to 0.71 (95%CI = 0.66-0.77) for women with the CC genotype. When stratified by duration of OCP use, women with 1-5 years of OCP use exhibited differential protective benefit across genotypes. However, no interaction on either the multiplicative or additive scale was found to be statistically significant after multiple testing correction. The results suggest that OCP use may offer increased benefit for women who are carriers of the T allele in rs13255292. On the other hand, for women carrying the C allele in this variant, longer (5+ years) use of OCP may reduce the impact of carrying the risk allele of this SNP. Replication of this finding is needed. The study presents a comprehensive analytic framework for conducting gene-environment analysis in ovarian cancer.

Attention-deficit/hyperactivity disorder and lifetime cannabis use: genetic overlap and causality.

Attention-deficit/hyperactivity disorder (ADHD) is a severely impairing neurodevelopmental disorder with a prevalence of 5% in children and adolescents and of 2.5% in adults. Comorbid conditions in ADHD play a key role in symptom progression, disorder course and outcome. ADHD is associated with a significantly increased risk for substance use, abuse and dependence. ADHD and cannabis use are partly determined by genetic factors; the heritability of ADHD is estimated at 70-80% and of cannabis use initiation at 40-48%. In this study, we used summary statistics from the largest available meta-analyses of genome-wide association studies (GWAS) of ADHD (n = 53,293) and lifetime cannabis use (n = 32,330) to gain insights into the genetic overlap and causal relationship of these two traits. We estimated their genetic correlation to be r2 = 0.29 (P = 1.63 × 10-5) and identified four new genome-wide significant loci in a cross-trait analysis: two in a single variant association analysis (rs145108385, P = 3.30 × 10-8 and rs4259397, P = 4.52 × 10-8) and two in a gene-based association analysis (WDPCP, P = 9.67 × 10-7 and ZNF251, P = 1.62 × 10-6). Using a two-sample Mendelian randomization approach we found support that ADHD is causal for lifetime cannabis use, with an odds ratio of 7.9 for cannabis use in individuals with ADHD in comparison to individuals without ADHD (95% CI (3.72, 15.51), P = 5.88 × 10-5). These results substantiate the temporal relationship between ADHD and future cannabis use and reinforce the need to consider substance misuse in the context of ADHD in clinical interventions.

Association Analysis of Interleukin-1β, Interleukin-6, and HMGB1 Variants with Postictal Serum Cytokine Levels in Children with Febrile Seizure and Generalized Epilepsy with Febrile Seizure Plus.

Background and PurposeFebrile seizure (FS) is a unique type of seizure that only occurs during childhood. Genelized epilepsy with febrile seizure plus (GEFS+) is a familial epilepsy syndrome associated with FS and afebrile seizure (AFS). Both seizure types are related to fever, but whether genetic susceptibility to inflammation is implicated in them is still unclear. To analyze the associations between postictal serum cytokine levels and genetic variants in the cytokine genes interleukin (IL)-1β, IL-6, and high mobility group box-1 (HMGB1) in FS and GEFS+.MethodsGenotyping was performed in 208 subjects (57 patients with FS, 43 patients with GEFS+, and 108 controls) with the SNaPshot assay for IL-1β-31 (rs1143627), IL-1β-511 (rs16944), IL-6-572 (rs1800796), and HMGB1 3814 (rs2249825). Serum IL-1β, IL-6, and HMGB1 levels were analyzed within 2 hours after seizure attacks using the ELISA in only 68 patients (38 FS, 10 GEFS+, and 20 controls). The allele distribution, genotype distribution, and correlations with serum cytokine levels were analyzed.ResultsNear-complete linkage disequilibrium exists between IL-1β-31 and IL-1β-511 variants. CT genotypes of these variants were associated with significantly higher postictal serum IL-1β levels than were CC+TT genotypes in FS (both p<0.05). CT genotypes of IL-1β-31 and IL-1β-511 variants were more strongly associated with FS than were CC+TT genotypes (odds ratio=1.691 and 1.731, respectively). For GEFS+, serum IL-1β levels after AFS for CT genotypes of IL-1β-31 and IL-1β-511 were also higher than for CC+TT genotypes. No significant associations were found for IL-6 and HMGB1.ConclusionsGenetic variants located in IL-1β-31 and IL-1β-511 promotor regions are correlated with higher postictal IL-1β levels in FS. These results suggest that IL-1 gene cluster variants in IL-1β-31 and IL-1β-511 are a host genetic factor for provoking FS in Korean children.

Association Analysis of the HNF4A Common Genetic Variants with Type 2 Diabetes Mellitus Risk.

Type 2 diabetes mellitus (T2DM) is a complex disease that involves a wide range of genetic and environmental factors. The hepatocyte nuclear factor (HNF4A) carries out hepatic gluconeogenesis regulation and insulin secretion crucially, and the corresponding gene was shown to be linked to T2DM in several studies. The aim of the present study was to evaluate the association between HNF4A genetic variants (rs1884613 and rs1884614) and T2DM risk in a group of Iranian patients. This case-control study included 100 patients with T2DM and 100 control subjects. Genotyping of two single nucleotide polymorphisms (SNPs) (rs1884613 and rs1884614) of HNF4A was performed using the sequencing method. There was no statistically significant difference for allele and genotype distribution of the HNF4A common variants (rs1884613 and rs1884614) between subjects with and without T2DM (P=0.9 and P=0.9, respectively). Regarding diabetic complications, although the presence of mentioned polymorphisms increased the odds of developing ophthalmic complications and reduction of the odds of renal complications among diabetic patients, the mentioned risk was non- significant and cannot be generalized to the whole population. It seems that rs1884613 and rs1884614 polymorphisms are not associated with T2DM or its renal and ophthalmic complications. To investigate the precise influence of these polymorphisms, prospective cohorts with larger sample sizes are required.

The impact of a fine-scale population stratification on rare variant association test results.

Population stratification is a well-known confounding factor in both common and rare variant association analyses. Rare variants tend to be more geographically clustered than common variants, because of their more recent origin. However, it is not yet clear if population stratification at a very fine scale (neighboring administrative regions within a country) would lead to statistical bias in rare variant analyses. As the inclusion of convenience controls from external studies is indeed a common procedure, in order to increase the power to detect genetic associations, this problem is important. We studied through simulation the impact of a fine scale population structure on different rare variant association strategies, assessing type I error and power. We showed that principal component analysis (PCA) based methods of adjustment for population stratification adequately corrected type I error inflation at the largest geographical scales, but not at finest scales. We also showed in our simulations that adding controls obviously increased power, but at a considerably lower level when controls were drawn from another population.

Association analysis of RTEL1 variants with risk of adult gliomas in a Korean population.

Previous studies have identified multiple loci for inherited susceptibility to glioma development, including the regulator of telomere elongation helicase 1 (RTEL1). However, the association between RTEL1 variants and risk of glioma has not been well understood. Therefore, we sought to comprehensively examine the genetic interaction between RTEL1 variants and risk of glioma with respect to defined histological and molecular subtypes. We employed a case-control study involving 250 adult glioma patients with previous molecular alterations and 375 population–based controls within Korean populations. Statistical analyses on the association between RTEL1 single nucleotide polymorphisms (SNPs) and glioma risk were conducted using unconditional logistic regression. Additional conditional and stepwise analyses were performed on significant RTEL1 SNPs. We detected significant associations (Bonferroni P < .05) between six SNPs (rs6089953, rs3848669, rs6010620, rs3787089, rs6062302, and rs115303435) and risk of glioma in the Korean subjects. The two coding variants, rs6062302 (D664D) and rs115303435 (A1059T), were plausibly causal variants and were independent among the significantly associated RTEL1 variants. The glioma subgroup analyses showed that the causal variants (rs6062302 and rs115303435) may be associated with increased risk of glioma regardless of histological grades and molecular alterations. This study provides a deeper understanding of relationships between RTEL1 variants and risk of glioma. Further studies are required to ascertain the impact of those variants on glioma susceptibility.

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

Variants in serotonergic genes are implicated in nicotine dependence (ND) in subjects of European and African origin, but their involvement with smoking in Asians is largely unknown. Moreover, mechanisms underlying the ND risk-associated single-nucleotide polymorphisms (SNPs) in these genes are rarely investigated. The Fagerström Test for Nicotine Dependence (FTND) score was used to assess ND in 2616 male Chinese Han smokers. Both association and interaction analysis were used to examine the association of variants in the serotonergic genes with FTND. Further, expression and methylation quantitative trait loci (cis-mQTL) analysis was employed to determine the association of individual SNPs with the extent of methylation of each CpG locus. Individual SNP-based association analysis revealed that rs1176744 in HTR3B was marginally associated with FTND (p = 0.042). Haplotype-based association analysis found that one major haplotype, T-T-A-G, formed by SNPs rs3758987-rs4938056-rs1176744-rs2276305, located in the 5′ region of HTR3B, showed a significant association with FTND (p = 0.00025). Further, a significant genetic interactive effect affecting ND was detected among SNPs rs10160548 in HTR3A, and rs3758987, rs2276305, and rs1672717 in HTR3B (p = 0.0074). Finally, we found four CpG sites (CpG_4543549, CpG_4543464, CpG_4543682, and CpG_4546888) to be significantly associated with three cis-mQTL SNPs (i.e., rs3758987, rs4938056, and rs1176744) located in our detected haplotype within HTR3B. In sum, we showed SNP rs1176744 (Tyr129Ser) to be associated with ND. Together with the SNPs rs3758987 and rs4938056 in HTR3B, they formed a major haplotype, which had significant association with ND. We further showed these SNPs contribute to ND through four methylated sites in HTR3B. All these findings suggest that variants in the serotonergic system play an important role in ND in the Chinese Han population. More importantly, these findings demonstrated that the involvement of this system in ND is through gene-by-gene interaction and methylation.

Genome-wide association analysis of common genetic variants of resistant hypertension.

Resistant hypertension (RHTN), defined as uncontrolled blood pressure (BP) ≥ 140/90 using three or more drugs or controlled BP (<140/90) using four or more drugs, is associated with adverse outcomes, including decline in kidney function. We conducted a genome-wide association analysis in 1194 White and Hispanic participants with hypertension and coronary artery disease from the INternational VErapamil-SR Trandolapril STudy-GENEtic Substudy (INVEST-GENES). Top variants associated with RHTN at p < 10-4 were tested for replication in 585 White and Hispanic participants with hypertension and subcortical strokes from the Secondary Prevention of Subcortical Strokes GENEtic Substudy (SPS3-GENES). A genetic risk score for RHTN was created by summing the risk alleles of replicated RHTN signals. rs11749255 in MSX2 was associated with RHTN in INVEST (odds ratio (OR) (95% CI) = 1.50 (1.2-1.8), p = 7.3 × 10-5) and replicated in SPS3 (OR = 2.0 (1.4-2.8), p = 4.3 × 10-5), with genome-wide significance in meta-analysis (OR = 1.60 (1.3-1.9), p = 3.8 × 10-8). Other replicated signals were in IFLTD1 and PTPRD. IFLTD1 rs6487504 was associated with RHTN in INVEST (OR = 1.90 (1.4-2.5), p = 1.1 × 10-5) and SPS3 (OR = 1.70 (1.2-2.5), p = 4 × 10-3). PTPRD rs324498, a previously reported RHTN signal, was among the top signals in INVEST (OR = 1.60 (1.3-2.0), p = 3.4 × 10-5) and replicated in SPS3 (OR = 1.60 (1.1-2.4), one-sided p = 0.005). Participants with the highest number of risk alleles were at increased risk of RHTN compared to participants with a lower number (p-trend = 1.8 × 10-15). Overall, we identified and replicated associations with RHTN in the MSX2, IFLTD1, and PTPRD regions, and combined these associations to create a genetic risk score.