Gene-Lifestyle Interactions in Complex Diseases: Design and Description of the GLACIER and VIKING Studies

Association of Established Blood Pressure Loci With 10-Year Change in Blood Pressure and Their Ability to Predict Incident Hypertension

Background Genome-wide association studies have identified >1000 genetic variants cross-sectionally associated with blood pressure variation and prevalent hypertension. These discoveries might aid the early identification of subpopulations at risk of developing hypertension or provide targets for drug development, amongst other applications. The aim of the present study was to analyze the association of blood pressure-associated variants with long-term changes (10 years) in blood pressure and also to assess their ability to predict hypertension incidence compared with traditional risk variables in a Swedish population. Methods and Results We constructed 6 genetic risk scores (GRSs) by summing the dosage of the effect allele at each locus of genetic variants previously associated with blood pressure traits (systolic blood pressure GRS (GRSSBP): 554 variants; diastolic blood pressure GRS (GRSDBP): 481 variants; mean arterial pressure GRS (GRSMAP): 20 variants; pulse pressure GRS (GRSPP): 478 variants; hypertension GRS (GRSHTN): 22 variants; combined GRS (GRScomb): 1152 variants). Each GRS was longitudinally associated with its corresponding blood pressure trait, with estimated effects per GRS SD unit of 0.50 to 1.21 mm Hg for quantitative traits and odds ratios (ORs) of 1.10 to 1.35 for hypertension incidence traits. The GRScomb was also significantly associated with hypertension incidence defined according to European guidelines (OR, 1.22 per SD; 95% CI, 1.10‒1.35) but not US guidelines (OR, 1.11 per SD; 95% CI, 0.99‒1.25) while controlling for traditional risk factors. The addition of GRScomb to a model containing traditional risk factors only marginally improved discrimination (Δarea under the ROC curve = 0.001-0.002). Conclusions GRSs based on discovered blood pressure-associated variants are associated with long-term changes in blood pressure traits and hypertension incidence, but the inclusion of genetic factors in a model composed of conventional hypertension risk factors did not yield a material increase in predictive ability.

The association of the glucokinase rs4607517 polymorphism with gestational diabetes mellitus and its interaction with sweets consumption in Chinese women

OBJECTIVE

To identify the association of the glucokinase gene (GCK) rs4607517 polymorphism with gestational diabetes mellitus (GDM) and determine whether sweets consumption could interact with the polymorphism on GDM in Chinese women.

DESIGN

We conducted a case-control study at a hospital including 1015 participants (562 GDM cases and 453 controls). We collected the data of pre-pregnancy BMI, sweets consumption and performed genotyping of the GCK rs4607517 polymorphism. Logistic regression was performed to test the association between the rs4607517 polymorphism and GDM, and the stratified analyses by sweets consumption were conducted, using an additive genetic model.

SETTING

A case-control study of women at a hospital in Beijing, China.

PARTICIPANTS

One thousand and fifteen Chinese women.

RESULTS

The GCK rs4607517 A allele was significantly associated with GDM (OR 1·35, 95 % CI 1·03, 1·77; P = 0·028). Furthermore, stratified analyses showed that the A allele increased the risk of GDM only in women who had a habitual consumption of sweet foods (sweets consumption ≥ once per week) (OR 1·61, 95 % CI 1·17, 2·21; P = 0·003). Significant interaction on GDM was found between the rs4607517 A allele and sweets consumption (P = 0·004).

CONCLUSIONS

This study for the first time reported the interaction between the GCK rs4607517 polymorphism and sweets consumption on GDM. The results provided novel evidence for risk assessment and personalised prevention of GDM.

Novel genetic loci associated with long-term deterioration in blood lipid concentrations and coronary artery disease in European adults

Background

Cross-sectional genome-wide association studies have identified hundreds of loci associated with blood lipids and related cardiovascular traits, but few genetic association studies have focused on long-term changes in blood lipids.

Methods

Participants from the GLACIER Study (Nmax = 3492) were genotyped with the MetaboChip array, from which 29 387 SNPs (single nucleotide polymorphisms; replication, fine-mapping regions and wildcard SNPs for lipid traits) were extracted for association tests with 10-year change in total cholesterol (ΔTC) and triglycerides (ΔTG). Four additional prospective cohort studies (MDC, PIVUS, ULSAM, MRC Ely; Nmax = 8263 participants) were used for replication. We conducted an in silico look-up for association with coronary artery disease (CAD) in the Coronary ARtery DIsease Genome-wide Replication and Meta-analysis (CARDIoGRAMplusC4D) Consortium (N ∼ 190 000) and functional annotation for the top ranking variants.

Results

In total, 956 variants were associated (P < 0.01) with either ΔTC or ΔTG in GLACIER. In GLACIER, chr19:50121999 at APOE was associated with ΔTG and multiple SNPs in the APOA1/A4/C3/A5 region at genome-wide significance (P < 5 × 10-8), whereas variants in four loci, DOCK7, BRE, SYNE1 and KCNIP1, reached study-wide significance (P < 1.7 × 10-6). The rs7412 variant at APOE was associated with ΔTC in GLACIER (P < 1.7 × 10-6). In pooled analyses of all cohorts, 139 SNPs at six and five loci were associated with ΔTC and for ΔTG, respectively (P < 10-3). Of these, a variant at CAPN3 (P = 1.2 × 10-4), multiple variants at HPR (Pmin = 1.5 × 10-6) and a variant at SIX5 (P = 1.9 × 10-4) showed evidence for association with CAD.

Conclusions

We identified seven novel genomic regions associated with long-term changes in blood lipids, of which three also raise CAD risk.

The combined effects of FADS gene variation and dietary fats in obesity-related traits in a population from the far north of Sweden: the GLACIER Study

Background

Recent analyses in Greenlandic Inuit identified six genetic polymorphisms (rs74771917, rs3168072, rs12577276, rs7115739, rs174602, and rs174570) in the fatty acid desaturase gene cluster (FADS1-FADS2-FADS3) that are associated with multiple metabolic and anthropometric traits. Our objectives were to systematically assess whether dietary polyunsaturated fat acid (PUFA) intake modifies the associations between genetic variants in the FADS gene cluster and cardiometabolic traits and to functionally annotate top ranking candidates to estimate their regulatory potential.

Methods

Data analyses consisted: interaction analyses between the six candidate genetic variants and dietary PUFA intake; gene-centric joint analyses to detect interaction signals in the FADS region; haplotype block-centric joint tests across 30 haplotype blocks in the FADS region to refine interaction signals; functional annotation of top loci. These analyses were undertaken in Swedish adults from the GLACIER Study (N=5,160); data on genetic variation and eight cardiometabolic traits was used.

Results

Interactions were observed between rs174570 and n-6 PUFA intake on fasting glucose (P_int=0.005) and between rs174602 and n-3 PUFA intake on total cholesterol (P_int=0.001). Gene-centric analyses demonstrated a statistically significant interaction effect for FADS and n-3 PUFA on triglycerides (P=0.005) considering genetic main effects as random. Haplotype analyses revealed three blocks (P_int<0.011) that could drive the interaction between FADS and n-3 PUFA on triglycerides; Functional annotation of these regions showed that each block harbours a number of highly functional regulatory variants; FADS2 rs5792235 demonstrated the highest functionality score.

Conclusions

The association between FADS variants and triglycerides may be modified by PUFA intake. The intronic FADS2 rs5792235 variant is a potential causal variant in the region having the highest regulatory potential. However, our results suggest that haplotypes may harbour multiple functional variants in a region, rather than a single variant.

The heritable basis of gene-environment interactions in cardiometabolic traits

AIMS/HYPOTHESIS

Little is known about the heritable basis of gene-environment interactions in humans. We therefore screened multiple cardiometabolic traits to assess the probability that they are influenced by genotype-environment interactions.

METHODS

Fourteen established environmental risk exposures and 11 cardiometabolic traits were analysed in the VIKING study, a cohort of 16,430 Swedish adults from 1682 extended pedigrees with available detailed genealogical, phenotypic and demographic information, using a maximum likelihood variance decomposition method in Sequential Oligogenic Linkage Analysis Routines software.

RESULTS

All cardiometabolic traits had statistically significant heritability estimates, with narrow-sense heritabilities (h ²) ranging from 24% to 47%. Genotype-environment interactions were detected for age and sex (for the majority of traits), physical activity (for triacylglycerols, 2 h glucose and diastolic BP), smoking (for weight), alcohol intake (for weight, BMI and 2 h glucose) and diet pattern (for weight, BMI, glycaemic traits and systolic BP). Genotype-age interactions for weight and systolic BP, genotype-sex interactions for BMI and triacylglycerols and genotype-alcohol intake interactions for weight remained significant after multiple test correction.

CONCLUSIONS/INTERPRETATION

Age, sex and alcohol intake are likely to be major modifiers of genetic effects for a range of cardiometabolic traits. This information may prove valuable for studies that seek to identify specific loci that modify the effects of lifestyle in cardiometabolic disease.

Statistical power considerations in genotype-based recall randomized controlled trials

Randomized controlled trials (RCT) are often underpowered for validating gene-treatment interactions. Using published data from the Diabetes Prevention Program (DPP), we examined power in conventional and genotype-based recall (GBR) trials. We calculated sample size and statistical power for gene-metformin interactions (vs. placebo) using incidence rates, gene-drug interaction effect estimates and allele frequencies reported in the DPP for the rs8065082 SLC47A1 variant, a metformin transported encoding locus. We then calculated statistical power for interactions between genetic risk scores (GRS), metformin treatment and intensive lifestyle intervention (ILI) given a range of sampling frames, clinical trial sample sizes, interaction effect estimates, and allele frequencies; outcomes were type 2 diabetes incidence (time-to-event) and change in small LDL particles (continuous outcome). Thereafter, we compared two recruitment frameworks: GBR (participants recruited from the extremes of a GRS distribution) and conventional sampling (participants recruited without explicit emphasis on genetic characteristics). We further examined the influence of outcome measurement error on statistical power. Under most simulated scenarios, GBR trials have substantially higher power to observe gene-drug and gene-lifestyle interactions than same-sized conventional RCTs. GBR trials are becoming popular for validation of gene-treatment interactions; our analyses illustrate the strengths and weaknesses of this design.

Bicycling to Work and Primordial Prevention of Cardiovascular Risk: A Cohort Study Among Swedish Men and Women

BACKGROUND

Bicycling to work may be a viable approach for achieving physical activity that provides cardiovascular health benefits. In this study we investigated the relationship of bicycling to work with incidence of obesity, hypertension, hypertriglyceridemia, and impaired glucose tolerance across a decade of follow-up in middle-aged men and women.

METHODS AND RESULTS

We followed 23 732 Swedish men and women with a mean age of 43.5 years at baseline who attended a health examination twice during a 10-year period (1990-2011). In multivariable adjusted models we calculated the odds of incident obesity, hypertension, hypertriglyceridemia, and impaired glucose tolerance, comparing individuals who commuted to work by bicycle with those who used passive modes of transportation. We also examined the relationship of change in commuting mode with incidence of these clinical risk factors. Cycling to work at baseline was associated with lower odds of incident obesity (odds ratio [OR]=0.85, 95% CI 0.73-0.99), hypertension (OR=0.87, 95% CI 0.79-0.95), hypertriglyceridemia (OR=0.85, 95% CI 0.76-0.94), and impaired glucose tolerance (OR=0.88, 95% CI 0.80-0.96) compared with passive travel after adjusting for putative confounding factors. Participants who maintained or began bicycling to work during follow-up had lower odds of obesity (OR=0.61, 95% CI 0.50-0.73), hypertension (OR=0.89, 95% CI 0.80-0.98), hypertriglyceridemia (OR=0.80, 95% CI 0.70-0.90), and impaired glucose tolerance (OR=0.82, 95% CI 0.74-0.91) compared with participants not cycling to work at both times points or who switched from cycling to other modes of transport during follow-up.

CONCLUSIONS

These data suggest that commuting by bicycle to work is an important strategy for primordial prevention of clinical cardiovascular risk factors among middle-aged men and women.

Sugar-sweetened beverage consumption and genetic predisposition to obesity in 2 Swedish cohorts

BACKGROUND

The consumption of sugar-sweetened beverages (SSBs), which has increased substantially during the last decades, has been associated with obesity and weight gain.

OBJECTIVE

Common genetic susceptibility to obesity has been shown to modify the association between SSB intake and obesity risk in 3 prospective cohorts from the United States. We aimed to replicate these findings in 2 large Swedish cohorts.

DESIGN

Data were available for 21,824 healthy participants from the Malmö Diet and Cancer study and 4902 healthy participants from the Gene-Lifestyle Interactions and Complex Traits Involved in Elevated Disease Risk Study. Self-reported SSB intake was categorized into 4 levels (seldom, low, medium, and high). Unweighted and weighted genetic risk scores (GRSs) were constructed based on 30 body mass index [(BMI) in kg/m(2)]-associated loci, and effect modification was assessed in linear regression equations by modeling the product and marginal effects of the GRS and SSB intake adjusted for age-, sex-, and cohort-specific covariates, with BMI as the outcome. In a secondary analysis, models were additionally adjusted for putative confounders (total energy intake, alcohol consumption, smoking status, and physical activity).

RESULTS

In an inverse variance-weighted fixed-effects meta-analysis, each SSB intake category increment was associated with a 0.18 higher BMI (SE = 0.02; P = 1.7 × 10(-20); n = 26,726). In the fully adjusted model, a nominal significant interaction between SSB intake category and the unweighted GRS was observed (P-interaction = 0.03). Comparing the participants within the top and bottom quartiles of the GRS to each increment in SSB intake was associated with 0.24 (SE = 0.04; P = 2.9 × 10(-8); n = 6766) and 0.15 (SE = 0.04; P = 1.3 × 10(-4); n = 6835) higher BMIs, respectively.

CONCLUSIONS

The interaction observed in the Swedish cohorts is similar in magnitude to the previous analysis in US cohorts and indicates that the relation of SSB intake and BMI is stronger in people genetically predisposed to obesity.

Innate biology versus lifestyle behaviour in the aetiology of obesity and type 2 diabetes: the GLACIER Study

AIMS/HYPOTHESIS

We compared the ability of genetic (established type 2 diabetes, fasting glucose, 2 h glucose and obesity variants) and modifiable lifestyle (diet, physical activity, smoking, alcohol and education) risk factors to predict incident type 2 diabetes and obesity in a population-based prospective cohort of 3,444 Swedish adults studied sequentially at baseline and 10 years later.

METHODS

Multivariable logistic regression analyses were used to assess the predictive ability of genetic and lifestyle risk factors on incident obesity and type 2 diabetes by calculating the AUC.

RESULTS

The predictive accuracy of lifestyle risk factors was similar to that yielded by genetic information for incident type 2 diabetes (AUC 75% and 74%, respectively) and obesity (AUC 68% and 73%, respectively) in models adjusted for age, age(2) and sex. The addition of genetic information to the lifestyle model significantly improved the prediction of type 2 diabetes (AUC 80%; p = 0.0003) and obesity (AUC 79%; p < 0.0001) and resulted in a net reclassification improvement of 58% for type 2 diabetes and 64% for obesity.

CONCLUSIONS/INTERPRETATION

These findings illustrate that lifestyle and genetic information separately provide a similarly high degree of long-range predictive accuracy for obesity and type 2 diabetes.

Impact of a Eukaryotic Translation Initiation Factor 3a Polymorphism on Susceptibility to Gastric Cancer

OBJECTIVE

To investigate single nucleotide polymorphisms in the eukaryotic translation initiation factor 3a (eIF3a) gene and the risk for gastric cancer within the Chinese population.

SUBJECTS AND METHODS

A total of 322 patients with gastric cancer were selected as the patient group and 340 non-gastric cancer patients were selected as the control group using the case-control method. Polymerase chain reaction-sequence-specific primer technology was leveraged to genotype the rs77382849 single nucleotide polymorphism in the eIF3a gene. The demographic characteristics of the study population and other exposures to risk factors were collected. Unconditional logistic regression analysis was performed to determine the association between the risk factors and gastric cancer.

RESULTS

A higher frequency of the eIF3a rs77382849 GG homozygote genotype was observed in the gastric cancer patients compared with the controls (63.98 vs. 54.41%, p < 0.05). After adjustment of exposure risks, such as age, gender, smoking, and drinking, the rs77382849 single nucleotide polymorphism was still associated with susceptibility to gastric cancer. When the eIF3a rs77382849 GG homozygote genotype was used as the reference group, the GA genotype (GA vs. GG: OR = 0.545, 95% CI: 0.386-0.769, p = 0.001) and AA genotype (AA vs. GG: OR = 0.245, 95% CI: 0.072-0.836, p = 0.025) were both correlated with a significantly decreased risk for gastric cancer development.

CONCLUSION

An association between eIF3a rs77382849 polymorphism and susceptibility to gastric cancer was observed in these Chinese patients.

Consumption of meat is associated with higher fasting glucose and insulin concentrations regardless of glucose and insulin genetic risk scores: a meta-analysis of 50,345 Caucasians

BACKGROUND

Recent studies suggest that meat intake is associated with diabetes-related phenotypes. However, whether the associations of meat intake and glucose and insulin homeostasis are modified by genes related to glucose and insulin is unknown.

OBJECTIVE

We investigated the associations of meat intake and the interaction of meat with genotype on fasting glucose and insulin concentrations in Caucasians free of diabetes mellitus.

DESIGN

Fourteen studies that are part of the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium participated in the analysis. Data were provided for up to 50,345 participants. Using linear regression within studies and a fixed-effects meta-analysis across studies, we examined 1) the associations of processed meat and unprocessed red meat intake with fasting glucose and insulin concentrations; and 2) the interactions of processed meat and unprocessed red meat with genetic risk score related to fasting glucose or insulin resistance on fasting glucose and insulin concentrations.

RESULTS

Processed meat was associated with higher fasting glucose, and unprocessed red meat was associated with both higher fasting glucose and fasting insulin concentrations after adjustment for potential confounders [not including body mass index (BMI)]. For every additional 50-g serving of processed meat per day, fasting glucose was 0.021 mmol/L (95% CI: 0.011, 0.030 mmol/L) higher. Every additional 100-g serving of unprocessed red meat per day was associated with a 0.037-mmol/L (95% CI: 0.023, 0.051-mmol/L) higher fasting glucose concentration and a 0.049-ln-pmol/L (95% CI: 0.035, 0.063-ln-pmol/L) higher fasting insulin concentration. After additional adjustment for BMI, observed associations were attenuated and no longer statistically significant. The association of processed meat and fasting insulin did not reach statistical significance after correction for multiple comparisons. Observed associations were not modified by genetic loci known to influence fasting glucose or insulin resistance.

CONCLUSION

The association of higher fasting glucose and insulin concentrations with meat consumption was not modified by an index of glucose- and insulin-related single-nucleotide polymorphisms. Six of the participating studies are registered at clinicaltrials.gov as NCT0000513 (Atherosclerosis Risk in Communities), NCT00149435 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetics of Lipid Lowering Drugs and Diet Network), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

Season-dependent associations of circadian rhythm-regulating loci (CRY1, CRY2 and MTNR1B) and glucose homeostasis: the GLACIER Study

AIMS/HYPOTHESIS

The association of single nucleotide polymorphisms (SNPs) proximal to CRY2 and MTNR1B with fasting glucose is well established. CRY1/2 and MTNR1B encode proteins that regulate circadian rhythmicity and influence energy metabolism. Here we tested whether season modified the relationship of these loci with blood glucose concentration.

METHODS

SNPs rs8192440 (CRY1), rs11605924 (CRY2) and rs10830963 (MTNR1B) were genotyped in a prospective cohort study from northern Sweden (n = 16,499). The number of hours of daylight exposure during the year ranged from 4.5 to 22 h daily. Owing to the non-linear distribution of daylight throughout the year, season was dichotomised based on the vernal and autumnal equinoxes. Effect modification was assessed using linear regression models fitted with a SNP × season interaction term, marginal effect terms and putative confounding variables, with fasting or 2 h glucose concentrations as outcomes.

RESULTS

The rs8192440 (CRY1) variant was only associated with fasting glucose among participants (n = 2,318) examined during the light season (β = -0.04 mmol/l per A allele, 95% CI -0.08, -0.01, p = 0.02, p interaction = 0.01). In addition to the established association with fasting glucose, the rs11605924 (CRY2) and rs10830963 (MTNR1B) loci were associated with 2 h glucose concentrations (β = 0.07 mmol/l per A allele, 95% CI 0.03, 0.12, p = 0.0008, n = 9,605, and β = -0.11 mmol/l per G allele, 95% CI -0.15, -0.06, p < 0.0001, n = 9,517, respectively), but only in participants examined during the dark season (p interaction = 0.006 and 0.04, respectively). Repeated measures analyses including data collected 10 years after baseline (n = 3,500) confirmed the results for the CRY1 locus (p interaction = 0.01).

CONCLUSIONS/INTERPRETATION

In summary, these observations suggest a biologically plausible season-dependent association between SNPs at CRY1, CRY2 and MTNR1B and glucose homeostasis.