Genome-Wide Interaction Analysis With DASH Diet Score Identified Novel Loci for Systolic Blood Pressure

BACKGROUND

The Dietary Approaches to Stop Hypertension (DASH) diet score lowers blood pressure (BP). We examined interactions between genotype and the DASH diet score in relation to systolic BP.

METHODS

We analyzed up to 9 420 585 single nucleotide polymorphisms in up to 127 282 individuals of 6 population groups (91% of European population) from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (n=35 660) and UK Biobank (n=91 622) and performed European population-specific and cross-population meta-analyses.

RESULTS

We identified 3 loci in European-specific analyses and an additional 4 loci in cross-population analyses at Pinteraction<5e-8. We observed a consistent interaction between rs117878928 at 15q25.1 (minor allele frequency, 0.03) and the DASH diet score (Pinteraction=4e-8; P for heterogeneity, 0.35) in European population, where the interaction effect size was 0.42±0.09 mm Hg (Pinteraction=9.4e-7) and 0.20±0.06 mm Hg (Pinteraction=0.001) in Cohorts for Heart and Aging Research in Genomic Epidemiology and the UK Biobank, respectively. The 1 Mb region surrounding rs117878928 was enriched with cis-expression quantitative trait loci (eQTL) variants (P=4e-273) and cis-DNA methylation quantitative trait loci variants (P=1e-300). Although the closest gene for rs117878928 is MTHFS, the highest narrow sense heritability accounted by single nucleotide polymorphisms potentially interacting with the DASH diet score in this locus was for gene ST20 at 15q25.1.

CONCLUSIONS

We demonstrated gene-DASH diet score interaction effects on systolic BP in several loci. Studies with larger diverse populations are needed to validate our findings.

Genome-Wide Interaction Analysis with DASH Diet Score Identified Novel Loci for Systolic Blood Pressure

Objective

We examined interactions between genotype and a Dietary Approaches to Stop Hypertension (DASH) diet score in relation to systolic blood pressure (SBP).

Methods

We analyzed up to 9,420,585 biallelic imputed single nucleotide polymorphisms (SNPs) in up to 127,282 individuals of six population groups (91% of European population) from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium (CHARGE; n=35,660) and UK Biobank (n=91,622) and performed European population-specific and cross-population meta-analyses.

Results

We identified three loci in European-specific analyses and an additional four loci in cross-population analyses at P for interaction < 5e-8. We observed a consistent interaction between rs117878928 at 15q25.1 (minor allele frequency = 0.03) and the DASH diet score (P for interaction = 4e-8; P for heterogeneity = 0.35) in European population, where the interaction effect size was 0.42±0.09 mm Hg (P for interaction = 9.4e-7) and 0.20±0.06 mm Hg (P for interaction = 0.001) in CHARGE and the UK Biobank, respectively. The 1 Mb region surrounding rs117878928 was enriched with cis-expression quantitative trait loci (eQTL) variants (P = 4e-273) and cis-DNA methylation quantitative trait loci (mQTL) variants (P = 1e-300). While the closest gene for rs117878928 is MTHFS, the highest narrow sense heritability accounted by SNPs potentially interacting with the DASH diet score in this locus was for gene ST20 at 15q25.1.

Conclusion

We demonstrated gene-DASH diet score interaction effects on SBP in several loci. Studies with larger diverse populations are needed to validate our findings.

How Accurately Can We Recall the Timing of Food Intake? A Comparison of Food Times from Recall-Based Survey Questions and Daily Food Records

BACKGROUND

There currently are no standard, low-cost, and validated methods to assess the timing of food intake.

OBJECTIVES

The aim of this study was to validate simple, recall-based questions that can characterize food timing in free-living populations.

METHODS

The concordance between recall-based survey questions and food times estimated from multiple daily food records was assessed in 249 generally healthy, free-living adults from the Shift Work, Heredity, Insulin, and Food Timing (SHIFT) Study. At baseline, participants were asked: "At what time do you first start and stop eating on weekdays/workdays and weekends/non-workdays?" and "At what time do you have your main meal on weekdays/workdays and weekends/non-workdays?" Participants were then asked to complete ≤14 d of food records noting the start time of each eating occasion. The timing of the first, last, and main (largest percentage calories) eating occasions were determined from food records. Wilcoxon matched pairs signed rank and Kendall's coefficient of concordance were used to compare differences and determine agreements between the methods for these food timing parameters, as well as for the midpoint between first and last eating occasion.

RESULTS

Eating occasions on work and free days showed significant agreements between the 2 methods, except for the main eating occasion on free days. Significant agreements were generally modest and ranged from 0.16 (workdays main eating occasion) to 0.45 (workdays first eating occasion). Generally, times based on recall were later than those estimated from food records, and the differences in estimated times were smaller on workdays compared with free days, and smaller for the first compared with the last eating occasion. Main eating occasions from food records often varied between lunch and dinner times, contributing to low concordance with recalled times.

CONCLUSIONS

Modest agreements were found between food times derived from simple, recall-based survey questions and food times estimated from multiple-day food records. Single administration of these questions can effectively characterize the overall timing of eating occasions within a population for chrononutrition research purposes.

How Accurately Can We Recall Food Timing? A Validity Study of a Novel Food Timing Questionnaire (P18-016-19)

Objectives

Emerging epidemiological and experimental studies suggest that food timing associates with obesity, weight-loss success, and other adverse cardiometabolic health outcomes. Although anecdotally simple to ascertain, the validity of recalled food timing has not been evaluated against prospectively collected data and current methods do not account for day of the week. Our objective is to validate a novel, recall-based tool, the Eating Pattern Questionnaire (EPQ), aimed at assessing food timing in healthy, free-living populations for work/school days (WD) and non-work days (NWD), against up to 2 weeks of prospectively collected 24-hour food records (FR).

Methods

A total of 95 participants (72% female; mean age: 33 ± 11 years) from the ongoing Shift Work, Heredity, Insulin, and Food Timing (SHIFT) Study (ClinicalTrials.gov: #NCT02997319) were included. On the EPQ, participants were asked to indicate whether food/beverages are always/sometimes/never consumed during every hour of a WD and NWD (hourly increments). On FR, participants were instructed by trained nutritionists to indicate type and time of all food/beverage items consumed. Food timing was averaged for WD and NWD separately across all completed FR. Five clock times in hour: minute were derived from the two tools: first/last eating episode and breakfast, lunch, and dinner. Concordance was quantified using Kendall's correlation of concordance (W).

Results

A higher level of concordance was observed for clock time of first eating episode on WD (W = 0.867) compared to NWD (W = 0.568). Clock times for breakfast, lunch, and dinner had comparable concordance on WD and NWD, with highest concordance observed for lunch (WD: W = 1; NWD: W = 0.886), followed by breakfast (WD: W = 0.759; NWD: W = 0.745) then dinner (WD: W = 0.641; NWD: W = 0.665). Lastly, low concordance was found for clock time of the last eating episode for both WD and NWD (WD: W = 0.220; NWD: W = 0.313).

Conclusions

By comparing clock times estimated from a recall-based questionnaire against prospectively collected food timing data, we observe that individuals may more accurately recall the timing of meals earlier on in the day, particularly on work days, compared to meals later in the evening. These findings provide first insights into the accuracy of food timing data ascertained through self-reported in cohort studies.

Funding Sources

NIH-R01DK105072.