Genome-wide Interaction Analysis Research Articles

Large-scale genome-wide interaction analyses on multiple cardiometabolic risk factors to identify age-specific genetic risk factors.

The genetic landscape of cardiometabolic risk factors has been explored extensively. However, insight in the effects of genetic variation on these risk factors over the life course is sparse. Here, we performed genome-wide interaction studies (GWIS) on different cardiometabolic risk factors to identify age-specific genetic risks. This study included 270,276 unrelated European-ancestry participants from the UK Biobank (54.2% women, a median age of 58 [interquartile range (IQR): 50, 63] years). GWIS models with interaction terms between genetic variants and age were performed on apolipoprotein B (ApoB), low-density lipoprotein-cholesterol (LDL-C), log-transformed triglycerides (TG), body mass index (BMI) and systolic blood pressure (SBP). Replication was subsequently performed in the Copenhagen General Population Study (CGPS) and the Estonian Biobank (EstBB). Multiple lead variants were identified to have genome-wide significant interactions with age (Pinteraction < 1e - 08). In detail, rs429358 (tagging APOE4) was identified for ApoB (Pinteraction = 9.0e - 14) and TG (Pinteraction = 5.4e - 16). Three additional lead variants were identified for ApoB: rs11591147 (R46L in PCSK9, Pinteraction = 3.9e - 09), rs34601365 (near APOB, Pinteraction = 8.4e - 09) and rs17248720 (near LDLR, Pinteraction = 2.0e - 09). Effect sizes of the identified lead variants were generally closer to the null with increasing age. No variant-age interactions were identified for LDL-C, SBP and BMI. The significant interactions of rs429358 with age on ApoB and TG were replicated in both CGPS and EstBB. The majority of genetic effects on cardiometabolic risk factors remain relatively constant over age, with the noted exceptions of specific genetic effects on ApoB and TG.

A Large-Scale Genome-Wide Gene-Sleep Interaction Study in 732,564 Participants Identifies Lipid Loci Explaining Sleep-Associated Lipid Disturbances.

We performed large-scale genome-wide gene-sleep interaction analyses of lipid levels to identify novel genetic variants underpinning the biomolecular pathways of sleep-associated lipid disturbances and to suggest possible druggable targets. We collected data from 55 cohorts with a combined sample size of 732,564 participants (87% European ancestry) with data on lipid traits (high-density lipoprotein [HDL-c] and low-density lipoprotein [LDL-c] cholesterol and triglycerides [TG]). Short (STST) and long (LTST) total sleep time were defined by the extreme 20% of the age- and sex-standardized values within each cohort. Based on cohort-level summary statistics data, we performed meta-analyses for the one-degree of freedom tests of interaction and two-degree of freedom joint tests of the main and interaction effect. In the cross-population meta-analyses, the one-degree of freedom variant-sleep interaction test identified 10 loci (P int <5.0e-9) not previously observed for lipids. Of interest, the ASPH locus (TG, LTST) is a target for aspartic and succinic acid metabolism previously shown to improve sleep and cardiovascular risk. The two-degree of freedom analyses identified an additional 7 loci that showed evidence for variant-sleep interaction (P joint <5.0e-9 in combination with P int <6.6e-6). Of these, the SLC8A1 locus (TG, STST) has been considered a potential treatment target for reduction of ischemic damage after acute myocardial infarction. Collectively, the 17 (9 with STST; 8 with LTST) loci identified in this large-scale initiative provides evidence into the biomolecular mechanisms underpinning sleep-duration-associated changes in lipid levels. The identified druggable targets may contribute to the development of novel therapies for dyslipidemia in people with sleep disturbances.

Genome-Wide Interaction Analyses of Serum Calcium on Ventricular Repolarization Time in 125 393 Participants.

Ventricular repolarization time (ECG QT and JT intervals) is associated with malignant arrhythmia. Genome-wide association studies have identified 230 independent loci for QT and JT; however, 50% of their heritability remains unexplained. Previous work supports a causal effect of lower serum calcium concentrations on longer ventricular repolarization time. We hypothesized calcium interactions with QT and JT variant associations could explain a proportion of the missing heritability. We performed genome-wide calcium interaction analyses for QT and JT intervals. Participants were stratified by their calcium level relative to the study distribution (top or bottom 20%). We performed a 2-stage analysis (genome-wide discovery [N=62 532] and replication [N=59 861] of lead variants) and a single-stage genome-wide meta-analysis (N=122 393, [European ancestry N=117 581, African ancestry N=4812]). We also calculated 2-degrees of freedom joint main and interaction and 1-degree of freedom interaction P values. In 2-stage and single-stage analyses, 50 and 98 independent loci, respectively, were associated with either QT or JT intervals (2-degrees of freedom joint main and interaction P value <5×10-8). No lead variant had a significant interaction result after correcting for multiple testing and sensitivity analyses provided similar findings. Two loci in the single-stage meta-analysis were not reported previously (SPPL2B and RFX6). We have found limited support for an interaction effect of serum calcium on QT and JT variant associations despite sample sizes with suitable power to detect relevant effects. Therefore, such effects are unlikely to explain a meaningful proportion of the heritability of QT and JT, and factorsincluding rare variation and other environmental interactions need to be considered.

Genome-Wide Identification, Expression, and Interaction Analysis of the Auxin Response Factor and AUX/IAA Gene Families in Vaccinium bracteatum.

Auxin, a plant hormone, plays diverse roles in the modulation of plant growth and development. The transport and signal transduction of auxin are regulated by various factors involved in shaping plant morphology and responding to external environmental conditions. The auxin signal transduction is primarily governed by the following two gene families: the auxin response factor (ARF) and auxin/indole-3-acetic acid (AUX/IAA). However, a comprehensive genomic analysis involving the expression profiles, structures, and functional features of the ARF and AUX/IAA gene families in Vaccinium bracteatum has not been carried out to date. Through the acquisition of genomic and expression data, coupled with an analysis using online tools, two gene family members were identified. This groundwork provides a distinguishing characterization of the chosen gene families in terms of expression, interaction, and response in the growth and development of plant fruits. In our genome-wide search of the VaARF and VaIAA genes in Vaccinium bracteatum, we identified 26 VaARF and 17 VaIAA genes. We analyzed the sequence and structural characteristics of these VaARF and VaIAA genes. We found that 26 VaARF and 17 VaIAA genes were divided into six subfamilies. Based on protein interaction predictions, VaIAA1 and VaIAA20 were designated core members of VaIAA gene families. Moreover, an analysis of expression patterns showed that 14 ARF genes and 12 IAA genes exhibited significantly varied expressions during fruit development. Two key genes, namely, VaIAA1 and VaIAA20, belonging to a gene family, play a potentially crucial role in fruit development through 26 VaARF-IAAs. This study provides a valuable reference for investigating the molecular mechanism of fruit development and lays the foundation for further research on Vaccinium bracteatum.

Genome-Wide Identification and Interaction Analysis of Turbot Heat Shock Protein 40 and 70 Families Suggest the Mechanism of Chaperone Proteins Involved in Immune Response after Bacterial Infection.

Hsp40-Hsp70 typically function in concert as molecular chaperones, and their roles in post-infection immune responses are increasingly recognized. However, in the economically important fish species Scophthalmus maximus (turbot), there is still a lack in the systematic identification, interaction models, and binding site analysis of these proteins. Herein, 62 Hsp40 genes and 16 Hsp70 genes were identified in the turbot at a genome-wide level and were unevenly distributed on 22 chromosomes through chromosomal distribution analysis. Phylogenetic and syntenic analysis provided strong evidence in supporting the orthologies and paralogies of these HSPs. Protein-protein interaction and expression analysis was conducted to predict the expression profile after challenging with Aeromonas salmonicida. dnajb1b and hspa1a were found to have a co-expression trend under infection stresses. Molecular docking was performed using Auto-Dock Tool and PyMOL for this pair of chaperone proteins. It was discovered that in addition to the interaction sites in the J domain, the carboxyl-terminal domain of Hsp40 also plays a crucial role in its interaction with Hsp70. This is important for the mechanistic understanding of the Hsp40-Hsp70 chaperone system, providing a theoretical basis for turbot disease resistance breeding, and effective value for the prevention of certain diseases in turbot.

Gene-vegetarianism interactions in calcium, estimated glomerular filtration rate, and testosterone identified in genome-wide analysis across 30 biomarkers.

We examined the associations of vegetarianism with metabolic biomarkers using traditional and genetic epidemiology. First, we addressed inconsistencies in self-reported vegetarianism among UK Biobank participants by utilizing data from two dietary surveys to find a cohort of strict European vegetarians (N = 2,312). Vegetarians were matched 1:4 with nonvegetarians for non-genetic association analyses, revealing significant effects of vegetarianism in 15 of 30 biomarkers. Cholesterol measures plus vitamin D were significantly lower in vegetarians, while triglycerides were higher. A genome-wide association study revealed no genome-wide significant (GWS; 5×10-8) associations with vegetarian behavior. We performed genome-wide gene-vegetarianism interaction analyses for the biomarkers, and detected a GWS interaction impacting calcium at rs72952628 (P = 4.47×10-8). rs72952628 is in MMAA, a B12 metabolic pathway gene; B12 has major deficiency potential in vegetarians. Gene-based interaction tests revealed two significant genes, RNF168 in testosterone (P = 1.45×10-6) and DOCK4 in estimated glomerular filtration rate (eGFR) (P = 6.76×10-7), which have previously been associated with testicular and renal traits, respectively. These nutrigenetic findings indicate genotype can modify the associations between vegetarianism and health outcomes.

Genome-Wide Analysis to Assess if Heavy Alcohol Consumption Modifies the Association between SNPs and Pancreatic Cancer Risk.

Pancreatic cancer is a leading cause of cancer-related death globally. Risk factors for pancreatic cancer include common genetic variants and potentially heavy alcohol consumption. We assessed if genetic variants modify the association between heavy alcohol consumption and pancreatic cancer risk. We conducted a genome-wide interaction analysis of single-nucleotide polymorphisms (SNP) by heavy alcohol consumption (more than three drinks per day) for pancreatic cancer in European ancestry populations from genome-wide association studies. Our analysis included 3,707 cases and 4,167 controls from case-control studies and 1,098 cases and 1,162 controls from cohort studies. Fixed-effect meta-analyses were conducted. A potential novel region of association on 10p11.22, lead SNP rs7898449 (interaction P value (Pinteraction) = 5.1 × 10-8 in the meta-analysis; Pinteraction = 2.1 × 10-9 in the case-control studies; Pinteraction = 0.91 in the cohort studies), was identified. An SNP correlated with this lead SNP is an expression quantitative trait locus for the neuropilin 1 gene. Of the 17 genomic regions with genome-wide significant evidence of association with pancreatic cancer in prior studies, we observed suggestive evidence that heavy alcohol consumption modified the association for one SNP near LINC00673, rs11655237 on 17q25.1 (Pinteraction = 0.004). We identified a novel genomic region that may be associated with pancreatic cancer risk in conjunction with heavy alcohol consumption located near an expression quantitative trait locus for neuropilin 1, a protein that plays an important role in the development and progression of pancreatic cancer. This work can provide insights into the etiology of pancreatic cancer, particularly in heavy drinkers.

Genome-wide identification, expression profiling, and protein interaction analysis of the CCoAOMT gene family in the tea plant (Camellia sinensis)

BackgroundThe caffeoyl-CoA-O methyltransferase (CCoAOMT) family plays a crucial role in the oxidative methylation of phenolic substances and is involved in various plant processes, including growth, development, and stress response. However, there is a limited understanding of the interactions among CCoAOMT protein members in tea plants.ResultsIn this study, we identified 10 members of the CsCCoAOMT family in the genome of Camellia sinensis (cultivar ‘HuangDan’), characterized by conserved gene structures and motifs. These CsCCoAOMT members were located on six different chromosomes (1, 2, 3, 4, 6, and 14). Based on phylogenetic analysis, CsCCoAOMT can be divided into two groups: I and II. Notably, the CsCCoAOMT members of group Ia are likely to be candidate genes involved in lignin biosynthesis. Moreover, through the yeast two-hybrid (Y2H) assay, we established protein interaction networks for the CsCCoAOMT family, revealing 9 pairs of members with interaction relationships.ConclusionsWe identified the CCoAOMT gene family in Camellia sinensis and conducted a comprehensive analysis of their classifications, phylogenetic and synteny relationships, gene structures, protein interactions, tissue-specific expression patterns, and responses to various stresses. Our findings shed light on the evolution and composition of CsCCoAOMT. Notably, the observed interaction among CCoAOMT proteins suggests the potential formation of the O-methyltransferase (OMT) complex during the methylation modification process, expanding our understanding of the functional roles of this gene family in diverse biological processes.

Genome-Wide Interaction Study of Dietary Intake and Colorectal Cancer Risk in the UK Biobank

Candidate gene analysis approaches have shown that colorectal cancer (CRC) risk attributable to diet may differ according to genotype. A genome-wide approach further allows for the exploration of underlying pathways for associations between diet and CRC risk across the genome. To identify genetic variants that modify diet-CRC associations and to further explore the underlying pathways in the cause of CRC. This nested case-control study used data on White British participants from the prospective cohort UK Biobank. Participants were recruited between March 13, 2006, and October 1, 2010, and data were censored June 25, 2021. The average frequency intake of 11 dietary factors in the year preceding baseline was obtained via a touchscreen questionnaire. After quality control for more than 93 million variants of imputed genetic data, 4 122 345 variants remained. Colorectal cancer cases were identified according to the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision. Genome-wide interaction analysis was performed to test interactions between dietary factors and variants using a conditional logistic regression model. Summary statistics of interactions at the variant level were used to calculate empirical P values for interactions at gene and gene-set levels in gene-based and gene-set enrichment analyses. A total of 4686 participants with CRC (mean [SD] age, 60.7 [6.6] years; 2707 men [57.8%]) received a new diagnosis during a median of 12.4 years (IQR, 11.6-13.1 years) of follow-up. Once a case was detected, 3 matched controls were identified, for a total of 14 058 controls (mean [SD] age, 60.4 [6.6] years; 8121 men [57.8%]). A total of 324 variants were identified that interacted with diet consumption at the suggestive threshold (P < 1 × 10-5). In gene-based analysis, aggregation of multiple EPDR1 gene variants was found to interact with fish intake regarding CRC risk. Furthermore, gene-set enrichment analysis found that several sets of protein-coding genes, which were overrepresented with particular functions and pathways, interacted with the consumption of milk (ART), cheese (OR), tea (KRT), and alcohol (PRM and TNP). In this nested case-control study, the risk of CRC associated with fish intake was modified by multiple single-nucleotide polymorphisms of the EPDR1 gene. The findings further suggested possible functions and pathways that might link the consumption of milk, cheese, tea, and alcohol with CRC development.

Genome-Wide Identification, Expression and Interaction Analyses of PP2C Family Genes in Chenopodium quinoa.

Plant protein phosphatase 2Cs (PP2Cs) function as inhibitors in protein kinase cascades involved in various processes and are crucial participants in both plant development and signaling pathways activated by abiotic stress. In this study, a genome-wide study was conducted on the CqPP2C gene family. A total of putative 117 CqPP2C genes were identified. Comprehensive analyses of physicochemical properties, chromosome localization and subcellular localization were conducted. According to phylogenetic analysis, CqPP2Cs were divided into 13 subfamilies. CqPP2Cs in the same subfamily had similar gene structures, and conserved motifs and all the CqPP2C proteins had the type 2C phosphatase domains. The expansion of CqPP2Cs through gene duplication was primarily driven by segmental duplication, and all duplicated CqPP2Cs underwent evolutionary changes guided by purifying selection. The expression of CqPP2Cs in various tissues under different abiotic stresses was analyzed using RNA-seq data. The findings indicated that CqPP2C genes played a role in regulating both the developmental processes and stress responses of quinoa. Real-time quantitative reverse transcription PCR (qRT-PCR) analysis of six CqPP2C genes in subfamily A revealed that they were up-regulated or down-regulated under salt and drought treatments. Furthermore, the results of yeast two-hybrid assays revealed that subfamily A CqPP2Cs interacted not only with subclass III CqSnRK2s but also with subclass II CqSnRK2s. Subfamily A CqPP2Cs could interact with CqSnRK2s in different combinations and intensities in a variety of biological processes and biological threats. Overall, our results will be useful for understanding the functions of CqPP2C in regulating ABA signals and responding to abiotic stress.

Genome-Wide Gene-Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk.

High red meat and/or processed meat consumption are established colorectal cancer risk factors. We conducted a genome-wide gene-environment (GxE) interaction analysis to identify genetic variants that may modify these associations. A pooled sample of 29,842 colorectal cancer cases and 39,635 controls of European ancestry from 27 studies were included. Quantiles for red meat and processed meat intake were constructed from harmonized questionnaire data. Genotyping arrays were imputed to the Haplotype Reference Consortium. Two-step EDGE and joint tests of GxE interaction were utilized in our genome-wide scan. Meta-analyses confirmed positive associations between increased consumption of red meat and processed meat with colorectal cancer risk [per quartile red meat OR = 1.30; 95% confidence interval (CI) = 1.21-1.41; processed meat OR = 1.40; 95% CI = 1.20-1.63]. Two significant genome-wide GxE interactions for red meat consumption were found. Joint GxE tests revealed the rs4871179 SNP in chromosome 8 (downstream of HAS2); greater than median of consumption ORs = 1.38 (95% CI = 1.29-1.46), 1.20 (95% CI = 1.12-1.27), and 1.07 (95% CI = 0.95-1.19) for CC, CG, and GG, respectively. The two-step EDGE method identified the rs35352860 SNP in chromosome 18 (SMAD7 intron); greater than median of consumption ORs = 1.18 (95% CI = 1.11-1.24), 1.35 (95% CI = 1.26-1.44), and 1.46 (95% CI = 1.26-1.69) for CC, CT, and TT, respectively. We propose two novel biomarkers that support the role of meat consumption with an increased risk of colorectal cancer. The reported GxE interactions may explain the increased risk of colorectal cancer in certain population subgroups.

New Insights into Polygenic Score-Lifestyle Interactions for Cardiometabolic Risk Factors from Genome-Wide Interaction Analyses.

The relationship between lifestyles and cardiometabolic outcomes varies between individuals. In 382,275 UK Biobank Europeans, we investigate how lifestyles interact with polygenic scores (PGS) of cardiometabolic risk factors. We identify six interactions (PGS for body mass index with meat diet, physical activity, sedentary behaviour and insomnia; PGS for high-density lipoprotein cholesterol with sedentary behaviour; PGS for triglycerides with meat diet) in multivariable linear regression models including an interaction term and show stronger associations between lifestyles and cardiometabolic risk factors among individuals with high PGSs than those with low PGSs. Genome-wide interaction analyses pinpoint three genetic variants (FTO rs72805613 for BMI; CETP rs56228609 for high-density lipoprotein cholesterol; TRIB2 rs4336630 for triglycerides; PInteraction < 5 × 10-8). The associations between lifestyles and cardiometabolic risk factors differ between individuals grouped by the genotype of these variants, with the degree of differences being similar to that between individuals with high and low values for the corresponding PGSs. This study demonstrates that associations between lifestyles and cardiometabolic risk factors can differ between individuals based upon their genetic profiles. It further suggests that genetic variants with interaction effects contribute more to such differences compared to those without interaction effects, which has potential implications for developing PGSs for personalised intervention.

Abstract 13953: A Genome-Wide European Ancestry Study Identifies Coronary Artery Disease-Associated Loci Through Gene-Sex Hormone Interaction

Background: Genome-wide association studies (GWAS) have improved our understanding of the genetic basis of coronary artery disease (CAD). While sex-differences in CAD have been observed, little is known about the role of sex hormones in CAD genetics. Accounting for sex hormone levels may help identify CAD-risk loci and extend our knowledge of its genetic architecture. Methods: We performed a GWAS to identify CAD risk loci by incorporating gene-sex hormone interactions in 365,662 individuals of European ancestry enrolled in the UK Biobank (UKB). Genetic interactions of total testosterone (TT), bioavailable testosterone (BAT) and sex-hormone binding globulin (SHBG) were evaluated. GEM software was used to conduct sex-stratified genome-wide interaction analysis with prevalent CAD. Enrollment age and principal components 1-10 were model covariates. The online post-GWAS tool FUMA was used to annotate the biological functions of marginal, interaction, and joint effects summary statistics. Results: We identified 64 loci in males and 8 loci in females that reached genome-wide significance (p &lt; 5х10 -8 ) for CAD ( Table 1 ). Among males, 3 significant loci were identified for BAT, one for TT and one for SHBG using joint effect model that did not overlap with those identified with marginal effect. Among females, 5 significant loci were identified, all for TT using joint effect that that did not overlap with those identified with marginal effect. Of these 5 loci, two loci were independently identified with significant SNP-TT interaction. These loci were mapped close to the TRDN and THADA genes that have been implicated in congenital ventricular tachycardia and polycystic ovarian syndrome, respectively. Conclusion: This Genome-wide gene-sex hormone interaction study identified genomic-risk loci that may contribute to the differential CAD risk between men and women, which would otherwise not have been discovered in traditional GWAS only including marginal genetic effect.

Gene-educational attainment interactions in a multi-population genome-wide meta-analysis identify novel lipid loci.

Introduction: Educational attainment, widely used in epidemiologic studies as a surrogate for socioeconomic status, is a predictor of cardiovascular health outcomes. Methods: A two-stage genome-wide meta-analysis of low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), and triglyceride (TG) levels was performed while accounting for gene-educational attainment interactions in up to 226,315 individuals from five population groups. We considered two educational attainment variables: "Some College" (yes/no, for any education beyond high school) and "Graduated College" (yes/no, for completing a 4-year college degree). Genome-wide significant (p < 5 × 10-8) and suggestive (p < 1 × 10-6) variants were identified in Stage 1 (in up to 108,784 individuals) through genome-wide analysis, and those variants were followed up in Stage 2 studies (in up to 117,531 individuals). Results: In combined analysis of Stages 1 and 2, we identified 18 novel lipid loci (nine for LDL, seven for HDL, and two for TG) by two degree-of-freedom (2 DF) joint tests of main and interaction effects. Four loci showed significant interaction with educational attainment. Two loci were significant only in cross-population analyses. Several loci include genes with known or suggested roles in adipose (FOXP1, MBOAT4, SKP2, STIM1, STX4), brain (BRI3, FILIP1, FOXP1, LINC00290, LMTK2, MBOAT4, MYO6, SENP6, SRGAP3, STIM1, TMEM167A, TMEM30A), and liver (BRI3, FOXP1) biology, highlighting the potential importance of brain-adipose-liver communication in the regulation of lipid metabolism. An investigation of the potential druggability of genes in identified loci resulted in five gene targets shown to interact with drugs approved by the Food and Drug Administration, including genes with roles in adipose and brain tissue. Discussion: Genome-wide interaction analysis of educational attainment identified novel lipid loci not previously detected by analyses limited to main genetic effects.

Genome-wide interaction analysis of folate for colorectal cancer risk

BackgroundEpidemiological and experimental evidence suggests that higher folate intake is associated with decreased colorectal cancer (CRC) risk; however, the mechanisms underlying this relationship are not fully understood. Genetic variation that may have a direct or indirect impact on folate metabolism can provide insights into folate’s role in CRC. ObjectivesOur aim was to perform a genome-wide interaction analysis to identify genetic variants that may modify the association of folate on CRC risk. MethodsWe applied traditional case-control logistic regression, joint 3-degree of freedom, and a 2-step weighted hypothesis approach to test the interactions of common variants (allele frequency >1%) across the genome and dietary folate, folic acid supplement use, and total folate in relation to risk of CRC in 30,550 cases and 42,336 controls from 51 studies from 3 genetic consortia (CCFR, CORECT, GECCO). ResultsInverse associations of dietary, total folate, and folic acid supplement with CRC were found (odds ratio [OR]: 0.93; 95% confidence interval [CI]: 0.90, 0.96; and 0.91; 95% CI: 0.89, 0.94 per quartile higher intake, and 0.82 (95% CI: 0.78, 0.88) for users compared with nonusers, respectively). Interactions (P-interaction < 5×10-8) of folic acid supplement and variants in the 3p25.2 locus (in the region of Synapsin II [SYN2]/tissue inhibitor of metalloproteinase 4 [TIMP4]) were found using traditional interaction analysis, with variant rs150924902 (located upstream to SYN2) showing the strongest interaction. In stratified analyses by rs150924902 genotypes, folate supplementation was associated with decreased CRC risk among those carrying the TT genotype (OR: 0.82; 95% CI: 0.79, 0.86) but increased CRC risk among those carrying the TA genotype (OR: 1.63; 95% CI: 1.29, 2.05), suggesting a qualitative interaction (P-interaction = 1.4×10-8). No interactions were observed for dietary and total folate. ConclusionsVariation in 3p25.2 locus may modify the association of folate supplement with CRC risk. Experimental studies and studies incorporating other relevant omics data are warranted to validate this finding.

Differential genome-wide associated variants and enriched pathways of ECG parameters among people with versus without HIV.

People with HIV (PWH) are more likely to develop ECG abnormalities. Substantial evidence exists for genetic contribution to ECG parameters among general population. However, whether and how would host genome associate with ECG parameters among PWH is unclear. Our research aims to analyze and compare genetic variants, mapped genes, and enriched pathways of ECG parameters among PWH and HIV-negative controls. A cross-sectional study. We performed a large original genome-wide association study (GWAS) of ECG parameters among PWH ( n = 1730) and HIV-negative controls ( n = 3746). Genome-wide interaction analyses were also conducted. A total of 18 novel variants were detected among PWH, six for PR interval including rs76345397 at ATL2 , 11 for QRS duration including rs10483994 at KCNK10 and rs2478830 at JCAD , and one for QTc interval (rs9815364). Among HIV-negative controls, we identified variants located at previously reported ECG-related genes ( SCN5A , CNOT1 ). Genetic variants had a significant interaction with HIV infection ( P < 5 × 10 -8 ), implying that HIV infection and host genome might jointly influence ECG parameters. Mapped genes for PR interval and QRS duration among PWH were enriched in the biological process of viral genome replication and host response to virus, respectively, whereas enriched pathways for PR interval among HIV-negative controls were in the cellular component of voltage-gated sodium channel complex. The present GWAS indicated a distinctive impact of host genome on quantitative ECG parameters among PWH. Different from HIV-negative controls, host genome might influence the cardiac electrical activity by interfering with HIV viral infection, production, and latency among PWH.

Probing the diabetes and colorectal cancer relationship using gene – environment interaction analyses

BackgroundDiabetes is an established risk factor for colorectal cancer. However, the mechanisms underlying this relationship still require investigation and it is not known if the association is modified by genetic variants. To address these questions, we undertook a genome-wide gene-environment interaction analysis.MethodsWe used data from 3 genetic consortia (CCFR, CORECT, GECCO; 31,318 colorectal cancer cases/41,499 controls) and undertook genome-wide gene-environment interaction analyses with colorectal cancer risk, including interaction tests of genetics(G)xdiabetes (1-degree of freedom; d.f.) and joint testing of Gxdiabetes, G-colorectal cancer association (2-d.f. joint test) and G-diabetes correlation (3-d.f. joint test).ResultsBased on the joint tests, we found that the association of diabetes with colorectal cancer risk is modified by loci on chromosomes 8q24.11 (rs3802177, SLC30A8 – ORAA: 1.62, 95% CI: 1.34–1.96; ORAG: 1.41, 95% CI: 1.30–1.54; ORGG: 1.22, 95% CI: 1.13–1.31; p-value3-d.f.: 5.46 × 10−11) and 13q14.13 (rs9526201, LRCH1 – ORGG: 2.11, 95% CI: 1.56–2.83; ORGA: 1.52, 95% CI: 1.38–1.68; ORAA: 1.13, 95% CI: 1.06–1.21; p-value2-d.f.: 7.84 × 10−09).DiscussionThese results suggest that variation in genes related to insulin signaling (SLC30A8) and immune function (LRCH1) may modify the association of diabetes with colorectal cancer risk and provide novel insights into the biology underlying the diabetes and colorectal cancer relationship.

Investigating Gene-Diet Interactions Impacting the Association Between Macronutrient Intake and Glycemic Traits.

We aimed to identify genetic modifiers of the dietary macronutrient-glycemia relationship using whole-genome sequence data from 10 Trans-Omics for Precision Medicine program cohorts. Substitution models indicated a modest reduction in glycemia associated with an increase in dietary carbohydrate at the expense of fat. Genome-wide interaction analysis identified one African ancestry-enriched variant near the FRAS1 gene that may interact with macronutrient intake to influence hemoglobin A1c. Simulation-based power calculations accounting for measurement error suggested that substantially larger sample sizes may be necessary to discover further gene-macronutrient interactions.

Genome-wide associated variants of subclinical atherosclerosis among young people with HIV and gene-environment interactions

BackgroundGenome-wide association studies (GWAS) have identified some variants associated with subclinical atherosclerosis (SCA) in general population but lacking sufficient validation. Besides traditional risk factors, whether and how would genetic variants associate with SCA among people with HIV (PWH) remains to be elucidated.MethodA large original GWAS and gene-environment interaction analysis of SCA were conducted among Chinese PWH (n = 2850) and age/sex-matched HIV-negative controls (n = 5410). Subgroup analyses by age and functional annotations of variants were also performed.ResultsDifferent from HIV-negative counterparts, host genome had a greater impact on young PWH rather than the elders: one genome-wide significant variant (rs77741796, P = 2.20 × 10−9) and eight suggestively significant variants (P < 1 × 10−6) were identified to be specifically associated with SCA among PWH younger than 45 years. Seven genomic loci and 15 genes were mapped to play a potential role on SCA among young PWH, which were enriched in the biological processes of atrial cardiac muscle cell membrane repolarization and molecular function of protein kinase A subunit binding. Furthermore, genome-wide interaction analyses revealed significant HIV-gene interactions overall as well as gene-environment interactions with alcohol consumption, tobacco use and obesity among PWH. The identified gene-environment interaction on SCA among PWH might be useful for discovering high-risk individuals for the prevention of SCA, particularly among those with tobacco use and alcohol consumption.ConclusionThe present study provides new clues for the genetic contribution of SCA among young PWH and is the starting point of precision intervention targeting HIV-related atherosclerosis.

Genome-Wide Identification, Expression and Interaction Analysis of GmSnRK2 and Type A PP2C Genes in Response to Abscisic Acid Treatment and Drought Stress in Soybean Plant.

As a typical ancient tetraploid, soybean (Glycine max) is an important oil crop species and plays a crucial role in supplying edible oil, plant protein and animal fodder worldwide. As global warming intensifies, the yield of soybean in the field is often strongly restricted by drought stress. SNF1-related protein kinase 2 (SnRK2) and type A protein phosphatase 2C (PP2C-A) family members are core components of the abscisic acid (ABA) signal transduction pathway in plants and have been suggested to play important roles in increasing plant tolerance to drought stress, but genetic information supporting this idea is still lacking in soybean. Here, we cloned the GmSnRK2s and GmPP2C-A family genes from the reference genome of Williams 82 soybean. The results showed that the expression patterns of GmSnRK2s and GmPP2C-As are spatiotemporally distinct. The expression of GmSnRK2s in response to ABA and drought signals is not strictly the same as that of Arabidopsis&amp;nbsp;SnRK2 homologous genes. Moreover, our results indicated that the duplicate pairs of GmSnRK2s and GmPP2C-As have similar expression patterns, cis-elements and relationships. GmSnRK2.2 may have a distinct function in the drought-mediated ABA signaling pathway. Furthermore, the results of yeast two-hybrid (Y2H) assays between GmSnRK2s and GmPP2C-As revealed that GmSnRK2.17, GmSnRK2.18, GmSnRK2.22, GmPP2C5, GmPP2C7, GmPP2C10 and GmPP2C17 may play central roles in the crosstalk among ABA signals in response to drought stress. Furthermore, GmPP2C-As and GmSnRKs were targeted by miRNA and validated by degradome sequencing, which may play multiple roles in the crosstalk between ABA and drought signals and other stress signals. Taken together, these results indicate that GmSnRK2s and GmPP2C-As may play a variety of roles in the drought-mediated ABA signaling pathway.