Interactions Between Sugar-Sweetened Beverage Consumption and Genetic Variants in the ChREBP Locus on Lipoprotein Concentrations in the UK Biobank: A Replication Study

Abstract Objectives A meta-analysis of 11 CHARGE cohorts (N = 63,599) suggested that genetic variants within or near the CHREBP locus may modify the associations between sugar sweetened beverage (SSB) consumption and high-density lipoprotein cholesterol (HDL-C) and triglyceride (TG) concentrations. The study objective was to replicate these findings in a large independent cohort. Methods Blood lipids and 24-hour recalls were available for 57,794 adults of European ancestry in the UK Biobank (2006-‘10). SSBs included “squash” and “fizzy” drinks derived from a single 24-hr recall. A total of 875 SNPs within or near the CHREBP locus were identified and included in this analysis. Associations between these SNPs and HDL-C and TG concentrations were quantified among participants who did not report SSB consumption (non-consumers, n = 45,866), reported ≥0.5 servings/day of SSB (consumers, n = 11,928), and a subset of consumers who reported ≥2 servings/day of SSB (high consumers, n = 3742). Interaction between SSB and selected SNPs on HDL-C and TG concentrations was evaluated by examining the difference in beta coefficients between strata. Results were considered statistically significant at a Bonferroni-corrected pinteract < 0.0001 (0.05/499 effective tests). Results A significant interaction between SSB consumption and TBL2-rs71556729 on HDL-C concentration previously observed in the meta-analysis was replicated in UK Biobank. However, we observed a stronger interaction for a SNP in high linkage disequilibrium (R2 = 0.93) FZD9-rs34821369 (MAF = 0.03, pinteract = 8.2E-05) with TBL2-rs71556729 (MAF = 0.03, pinteract = 0.0004). Among only SSB consumers, each additional minor G allele at FZD9-rs34821369 was associated with mean HDL-C concentrations 1.63 mg/dL (SE = 0.53, P = 0.002) higher than those with the major T allele. Conclusions Our results suggest that adults with the minor allele at FZD9-rs34821369 may be protected against SSB-induced low HDL-C concentrations. These results are consistent the findings from a prior meta-analysis of 11 cohorts. Funding Sources NIH, AHA, USDA-ARS. This research has been conducted using the UK Biobank Resource (Application Number 35,835).

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Sugar-sweetened Beverage Consumption May Modify Associations between Genetic Variants in the CHREBP Locus and HDL-C and TG Concentrations

Circulation Genomic and Precision Medicine ◽

10.1161/circgen.120.003288 ◽

2021 ◽

Author(s):

Danielle E. Haslam ◽

Gina M. Peloso ◽

Melanie Guirette ◽

Fumiaki Imamura ◽

Traci M. Bartz ◽

...

Keyword(s):

Genetic Variants ◽

Meta Analysis ◽

Density Lipoprotein ◽

Nucleotide Polymorphisms ◽

Linear Regression Models ◽

Aging Research ◽

Sugar Sweetened Beverage ◽

Genomic Epidemiology ◽

Sweetened Beverage ◽

The Uk

Background - Carbohydrate responsive element binding protein (ChREBP) is a transcription factor that responds to sugar consumption. Sugar-sweetened beverage (SSB) consumption and genetic variants in the CHREBP locus have separately been linked to high-density lipoprotein cholesterol (HDL-C) and triglyceride (TG) concentrations. We hypothesized SSB consumption would modify the association between genetic variants in the CHREBP locus and dyslipidemia. Methods - Data from 11 cohorts from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium (N=63,599) and the UK Biobank (UKB) (N=59,220) were used to quantify associations of SSB consumption, genetic variants, and their interaction on HDL-C and TG concentrations using linear regression models. A total of 1,606 single-nucleotide polymorphisms (SNPs) within or near CHREBP were considered. SSB consumption was estimated from validated questionnaires and participants were grouped by their estimated intake. Results - In a meta-analysis, rs71556729 was significantly associated with higher HDL-C concentrations only among the highest SSB consumers [β (95% CI) = 2.12 (1.16, 3.07) mg/dl; p <0.0002], but not significantly among the lowest SSB consumers ( p =0.81; p Diff <0.0001). Similar results were observed for two additional variants (rs35709627 and rs71556736). For TG, rs55673514 was positively associated with TG concentrations only among the highest SSB consumers [β (95% CI): 0.06 (0.02, 0.09) per allele count for log(mg/dl), p =0.001], but not the lowest SSB consumers ( p =0.84; p Diff =0.0005). Conclusions - Our results identified genetic variants in the CHREBP locus that may protect against SSB-associated reductions in HDL-C and other variants that may exacerbate SSB-associated increases in TG concentrations.

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Predicting the effect of statins on cancer risk using genetic variants from a Mendelian randomization study in the UK Biobank

eLife ◽

10.7554/elife.57191 ◽

2020 ◽

Vol 9 ◽

Author(s):

Paul Carter ◽

Mathew Vithayathil ◽

Siddhartha Kar ◽

Rahul Potluri ◽

Amy M Mason ◽

...

Keyword(s):

Standard Deviation ◽

Cancer Risk ◽

Genetic Variants ◽

Ldl Cholesterol ◽

Human Genetics ◽

Density Lipoprotein ◽

Lipid Lowering ◽

Uk Biobank ◽

Standard Deviation Increase ◽

The Uk

Laboratory studies have suggested oncogenic roles of lipids, as well as anticarcinogenic effects of statins. Here we assess the potential effect of statin therapy on cancer risk using evidence from human genetics. We obtained associations of lipid-related genetic variants with the risk of overall and 22 site-specific cancers for 367,703 individuals in the UK Biobank. In total, 75,037 individuals had a cancer event. Variants in the HMGCR gene region, which represent proxies for statin treatment, were associated with overall cancer risk (odds ratio [OR] per one standard deviation decrease in low-density lipoprotein [LDL] cholesterol 0.76, 95% confidence interval [CI] 0.65–0.88, p=0.0003) but variants in gene regions representing alternative lipid-lowering treatment targets (PCSK9, LDLR, NPC1L1, APOC3, LPL) were not. Genetically predicted LDL-cholesterol was not associated with overall cancer risk (OR per standard deviation increase 1.01, 95% CI 0.98–1.05, p=0.50). Our results predict that statins reduce cancer risk but other lipid-lowering treatments do not. This suggests that statins reduce cancer risk through a cholesterol independent pathway.

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Sugar-sweetened beverage intake associations with fasting glucose and insulin concentrations are not modified by selected genetic variants in a ChREBP-FGF21 pathway: a meta-analysis

Diabetologia ◽

10.1007/s00125-017-4475-0 ◽

2017 ◽

Vol 61 (2) ◽

pp. 317-330 ◽

Cited By ~ 10

Author(s):

Nicola M. McKeown ◽

Hassan S. Dashti ◽

Jiantao Ma ◽

Danielle E. Haslam ◽

Jessica C. Kiefte-de Jong ◽

...

Keyword(s):

Genetic Variants ◽

Fasting Glucose ◽

Meta Analysis ◽

Sugar Sweetened Beverage ◽

Sweetened Beverage

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Genotype-by-environment interactions inferred from genetic effects on phenotypic variability in the UK Biobank

10.1101/519538 ◽

2019 ◽

Cited By ~ 2

Author(s):

Huanwei Wang ◽

Futao Zhang ◽

Jian Zeng ◽

Yang Wu ◽

Kathryn E. Kemper ◽

...

Keyword(s):

Environmental Factors ◽

Genetic Variants ◽

Phenotypic Variability ◽

Environmental Data ◽

European Ancestry ◽

Environment Interaction ◽

Uk Biobank ◽

Genotype By Environment ◽

A Genome ◽

The Uk

AbstractGenotype-by-environment interaction (GEI) is a fundamental component in understanding complex trait variation. However, it remains challenging to identify genetic variants with GEI effects in humans largely because of the small effect sizes and the difficulty of monitoring environmental fluctuations. Here, we demonstrate that GEI can be inferred from genetic variants associated with phenotypic variability in a large sample without the need of measuring environmental factors. We performed a genome-wide variance quantitative trait locus (vQTL) analysis of ~5.6 million variants on 348,501 unrelated individuals of European ancestry for 13 quantitative traits in the UK Biobank, and identified 75 significant vQTLs with P<2.0×10−9 for 9 traits, especially for those related to obesity. Direct GEI analysis with five environmental factors showed that the vQTLs were strongly enriched with GEI effects. Our results indicate pervasive GEI effects for obesity-related traits and demonstrate the detection of GEI without environmental data.

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Plasma adiponectin and risk of asthma: observational analysis, genetic Mendelian randomisation and meta-analysis

Thorax ◽

10.1136/thoraxjnl-2021-217675 ◽

2021 ◽

pp. thoraxjnl-2021-217675

Author(s):

Maria Booth Nielsen ◽

Børge G Nordestgaard ◽

Marianne Benn ◽

Yunus Çolak

Keyword(s):

General Population ◽

Population Study ◽

Genetic Variants ◽

Meta Analysis ◽

High Plasma ◽

Mendelian Randomisation ◽

Uk Biobank ◽

General Population Study ◽

Plasma Adiponectin ◽

The Uk

BackgroundAdiponectin, an adipocyte-secreted protein-hormone with inflammatory properties, has a potentially important role in the development and progression of asthma. Unravelling whether adiponectin is a causal risk factor for asthma is an important issue to clarify as adiponectin could be a potential novel drug target for the treatment of asthma.ObjectiveWe tested the hypothesis that plasma adiponectin is associated observationally and causally (using genetic variants as instrumental variables) with risk of asthma.MethodsIn the Copenhagen General Population Study, we did an observational analysis in 28 845 individuals (2278 asthma cases) with plasma adiponectin measurements, and a genetic one-sample Mendelian randomisation analysis in 94 868 individuals (7128 asthma cases) with 4 genetic variants. Furthermore, in the UK Biobank, we did a genetic two-sample Mendelian randomisation analysis in 462 933 individuals (53 598 asthma cases) with 12 genetic variants. Lastly, we meta-analysed the genetic findings.ResultsWhile a 1 unit log-transformed higher plasma adiponectin in the Copenhagen General Population Study was associated with an observational OR of 1.65 (95% CI 1.29 to 2.08) for asthma, the corresponding genetic causal OR was 1.03 (95% CI 0.75 to 1.42). The genetic causal OR for asthma in the UK Biobank was 1.00 (95% CI 0.99 to 1.00). Lastly, genetic meta-analysis confirmed lack of association between genetically high plasma adiponectin and causal OR for asthma.ConclusionObservationally, high plasma adiponectin is associated with increased risk of asthma; however, genetic evidence could not support a causal association between plasma adiponectin and asthma.

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Large-Scale, Genome-Wide Gene-Diet Interaction Testing for HbA1c Using Derived Dietary Patterns in the UK Biobank

Current Developments in Nutrition ◽

10.1093/cdn/nzaa058_038 ◽

2020 ◽

Vol 4 (Supplement_2) ◽

pp. 1280-1280

Author(s):

Kenneth Westerman ◽

Ye Chen ◽

Han Chen ◽

Jose Florez ◽

Joanne Cole ◽

...

Keyword(s):

Principal Components ◽

Dietary Patterns ◽

Genetic Variants ◽

Interaction Analysis ◽

European Ancestry ◽

Uk Biobank ◽

Genome Wide ◽

A Genome ◽

Gene Level ◽

The Uk

Abstract Objectives Gene-diet interaction analysis can inform the development of precision nutrition for diabetes by uncovering genetic variants whose effects on glycemic traits vary across dietary behaviors. However, due to noise in dietary datasets and the low statistical power inherent in interaction analysis, there is a lack of confident, well-replicated gene-diet interactions for glycemic traits. Emerging computationally-efficient software tools have made it feasible to conduct well-powered, genome-wide interaction analysis in hundreds of thousands of individuals. Here, our objective was to conduct a genome-wide gene-diet interaction analysis for glycated hemoglobin (HbA1c; a measure of hyperglycemia), leveraging the large sample size of the UK Biobank cohort and data-driven dietary patterns to discover genetic variants whose effect is modulated by diet. Methods Food frequency questionnaires were previously used to derive empirical dietary patterns using principal components analysis (FFQ-PCs) in the UK Biobank. FFQ-PCs were used in genome-wide interaction analysis for HbA1c levels in unrelated, non-diabetic individuals of European ancestry (N = 331,610), adjusting for age, sex, and 10 genetic principal components. P-values were calculated for both the interaction (P-int) and a joint test (significance of the variant-HbA1c association combining the main and interaction effects) and the MAGMA tool was used to calculate gene-level enrichment statistics. Results Preliminary results from the first two FFQ-PCs confirmed known genetic loci for HbA1c using the joint test, such as at G6PC2 and GCK. Though no interaction tests reached genome-wide significance, suggestive signals (P-int < 1e-5) emerged at the variant level (including one near TPSD1, which codes for a tryptase and has been linked to red blood cell traits) and the gene level (such as for GTF3C2, which has previously been shown to interact with sleep in impacting lipid traits). Conclusions We have conducted the largest genome-wide study of gene-diet interactions for glycemic traits to-date and identified regions in the genome whose effect on HbA1c may be modulated by dietary intake, suggesting that this approach has the potential to reveal new insights into the genetics of glycemic traits and inform individualized dietary guidelines for diabetes prevention and management. Funding Sources NHLBI.

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Genetically determined risk of keratinocyte carcinoma and risk of other cancers

International Journal of Epidemiology ◽

10.1093/ije/dyaa265 ◽

2020 ◽

Author(s):

Jean Claude Dusingize ◽

Catherine M Olsen ◽

Jiyuan An ◽

Nirmala Pandeya ◽

Upekha E Liyanage ◽

...

Keyword(s):

Genetic Variants ◽

Genome Wide Association Study ◽

Meta Analysis ◽

Epidemiological Studies ◽

Risk Scores ◽

Cancer Site ◽

Uk Biobank ◽

Individual Level ◽

Increased Risk ◽

The Uk

Abstract Background Epidemiological studies have consistently documented an increased risk of developing primary non-cutaneous malignancies among people with a history of keratinocyte carcinoma (KC). However, the mechanisms underlying this association remain unclear. We conducted two separate analyses to test whether genetically predicted KC is related to the risk of developing cancers at other sites. Methods In the first approach (one-sample), we calculated the polygenic risk scores (PRS) for KC using individual-level data in the UK Biobank (n = 394 306) and QSkin cohort (n = 16 896). The association between the KC PRS and each cancer site was assessed using logistic regression. In the secondary (two-sample) approach, we used genome-wide association study (GWAS) summary statistics identified from the most recent GWAS meta-analysis of KC and obtained GWAS data for each cancer site from the UK-Biobank participants only. We used inverse-variance-weighted methods to estimate risks across all genetic variants. Results Using the one-sample approach, we found that the risks of cancer at other sites increased monotonically with KC PRS quartiles, with an odds ratio (OR) of 1.16, 95% confidence interval (CI): 1.13–1.19 for those in KC PRS quartile 4 compared with those in quartile 1. In the two-sample approach, the pooled risk of developing other cancers was statistically significantly elevated, with an OR of 1.05, 95% CI: 1.03–1.07 per doubling in the odds of KC. We observed similar trends of increasing cancer risk with increasing KC PRS in the QSkin cohort. Conclusion Two different genetic approaches provide compelling evidence that an instrumental variable for KC constructed from genetic variants predicts the risk of cancers at other sites.

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Biobank scale pharmacogenomics informs the genetic underpinnings of simvastatin use

10.1101/2020.11.23.20235846 ◽

2020 ◽

Author(s):

Frank R Wendt ◽

Dora Koller ◽

Gita A Pathak ◽

Daniel Jacoby ◽

Edward J Miller ◽

...

Keyword(s):

Linear Models ◽

Association Studies ◽

Absolute Risk ◽

African Ancestry ◽

Medication Use ◽

Density Lipoprotein ◽

Interactive Effects ◽

European Ancestry ◽

Uk Biobank ◽

The Uk

AbstractBackground and PurposeStudying drug metabolizing enzymes, encoded by pharmacogenes (PGx), may inform biological mechanisms underlying the diseases for which a medication is prescribed. Until recently, PGx loci could not be studied at biobank scale. Here we analyze PGx haplotype variation to detect associations with medication use in the UK Biobank.MethodsIn 7,649 unrelated African-ancestry (AFR) and 326,214 unrelated European-ancestry (EUR) participants from the UK Biobank, aged 37-73 at time of recruitment, we associated clinically-relevant PGx haplotypes with 265 (EUR) and 17 (AFR) medication use phenotypes using generalized linear models covaried with sex, age, age2, sex×age, sex×age2, and ten principal components of ancestry. Haplotypes across 50 genes were assigned with Stargazer. Our analyses focused on the association of PGx haplotype dose (quantitative predictor), diplotype (categorical predictor), and rare haplotype burden on medication use.ResultsIn EUR, NAT2 metabolizer phenotype (OR=1.05, 95% CI: 1.03-1.08, p=7.03×10−6) and activity score (OR=1.09, 95% CI: 1.05-1.14, p=2.46×10−6) were associated with simvastatin use. The dose of N-acetyltransferase 2 (NAT2)*1 was associated with simvastatin use relative to NAT2*5 (NAT2*1 OR=1.04, 95% CI=1.03-1.07, p=1.37×10−5) and was robust to effects of low-density lipoprotein cholesterol (LDL-C) concentration (NAT2*1 given LDL-C concentration: OR=1.07, 95% CI=1.05-1.09, p=1.14×10−8) and polygenic risk for LDL-C concentration (NAT2*1 given LDL-C PRS: OR=1.09, 95% CI=1.04-1.14, p=2.26×10−4). Interactive effects between NAT2*1, simvastatin use, and LDL-C concentration (OR: 0.957, 95% CI=0.916-0.998, p=0.045) were replicated in eMERGE PGx cohort (OR: 0.987, 95% CI: 0.976-0.998, p=0.029).Conclusions and relevanceWe used biobank-scale data to uncover and replicate a novel association between NAT2 locus variation (and suggestive evidence with several other genes) and better response to simvastatin (and other statins) therapy. The presence of NAT2*1 versus NAT2*5 may therefore be useful for making clinically informative decisions regarding the potential benefit (e.g., absolute risk reduction) in LDL-C concentration prior to statin treatment.Subject termsgenetics, genetic association studies, cardiovascular disease

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Association of genetically predicted testosterone with thromboembolism, heart failure, and myocardial infarction: mendelian randomisation study in UK Biobank

BMJ ◽

10.1136/bmj.l476 ◽

2019 ◽

pp. l476 ◽

Cited By ~ 24

Author(s):

Shan Luo ◽

Shiu Lun Au Yeung ◽

Jie V Zhao ◽

Stephen Burgess ◽

C Mary Schooling

Keyword(s):

Myocardial Infarction ◽

Heart Failure ◽

Genetic Variants ◽

Controlled Trial ◽

European Ancestry ◽

Gene Region ◽

Mendelian Randomisation ◽

Uk Biobank ◽

1000 Genomes ◽

The Uk

Abstract Objective To determine whether endogenous testosterone has a causal role in thromboembolism, heart failure, and myocardial infarction. Design Two sample mendelian randomisation study using genetic variants as instrumental variables, randomly allocated at conception, to infer causality as additional randomised evidence. Setting Reduction by Dutasteride of Prostate Cancer Events (REDUCE) randomised controlled trial, UK Biobank, and CARDIoGRAMplusC4D 1000 Genomes based genome wide association study. Participants 3225 men of European ancestry aged 50-75 in REDUCE; 392 038 white British men and women aged 40-69 from the UK Biobank; and 171 875 participants of about 77% European descent, from CARDIoGRAMplusC4D 1000 Genomes based study for validation. Main outcome measures Thromboembolism, heart failure, and myocardial infarction based on self reports, hospital episodes, and death. Results Of the UK Biobank participants, 13 691 had thromboembolism (6208 men, 7483 women), 1688 had heart failure (1186, 502), and 12 882 had myocardial infarction (10 136, 2746). In men, endogenous testosterone genetically predicted by variants in the JMJD1C gene region was positively associated with thromboembolism (odds ratio per unit increase in log transformed testosterone (nmol/L) 2.09, 95% confidence interval 1.27 to 3.46) and heart failure (7.81, 2.56 to 23.8), but not myocardial infarction (1.17, 0.78 to 1.75). Associations were less obvious in women. In the validation study, genetically predicted testosterone (based on JMJD1C gene region variants) was positively associated with myocardial infarction (1.37, 1.03 to 1.82). No excess heterogeneity was observed among genetic variants in their associations with the outcomes. However, testosterone genetically predicted by potentially pleiotropic variants in the SHBG gene region had no association with the outcomes. Conclusions Endogenous testosterone was positively associated with thromboembolism, heart failure, and myocardial infarction in men. Rates of these conditions are higher in men than women. Endogenous testosterone can be controlled with existing treatments and could be a modifiable risk factor for thromboembolism and heart failure.

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Genotype-by-environment interactions inferred from genetic effects on phenotypic variability in the UK Biobank

Science Advances ◽

10.1126/sciadv.aaw3538 ◽

2019 ◽

Vol 5 (8) ◽

pp. eaaw3538 ◽

Cited By ~ 31

Author(s):

Huanwei Wang ◽

Futao Zhang ◽

Jian Zeng ◽

Yang Wu ◽

Kathryn E. Kemper ◽

...

Keyword(s):

Environmental Factors ◽

Genetic Variants ◽

Phenotypic Variability ◽

Environmental Data ◽

European Ancestry ◽

Environment Interaction ◽

Uk Biobank ◽

Genotype By Environment ◽

A Genome ◽

The Uk

Genotype-by-environment interaction (GEI) is a fundamental component in understanding complex trait variation. However, it remains challenging to identify genetic variants with GEI effects in humans largely because of the small effect sizes and the difficulty of monitoring environmental fluctuations. Here, we demonstrate that GEI can be inferred from genetic variants associated with phenotypic variability in a large sample without the need of measuring environmental factors. We performed a genome-wide variance quantitative trait locus (vQTL) analysis of ~5.6 million variants on 348,501 unrelated individuals of European ancestry for 13 quantitative traits in the UK Biobank and identified 75 significant vQTLs with P < 2.0 × 10−9 for 9 traits, especially for those related to obesity. Direct GEI analysis with five environmental factors showed that the vQTLs were strongly enriched with GEI effects. Our results indicate pervasive GEI effects for obesity-related traits and demonstrate the detection of GEI without environmental data.

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