Advanced Search

Study Preview



Study Title and Description

Catechol-o-methyltransferase genotype is associated with self-reported increased heart rate following caffeine consumption



Key Questions Addressed
1 For [population], is caffeine intake above [exposure dose], compared to intakes [exposure dose] or less, associated with adverse effects on cardiovascular outcomes?
  • Comments Comments (
    0
    ) |

Primary Publication Information
  • Comments Comments (
    0
    ) |
TitleData
Title Catechol-o-methyltransferase genotype is associated with self-reported increased heart rate following caffeine consumption
Author J. M. Brathwaite, L. A. Da Costa and A. El-Sohemy
Country
Year 2011
Numbers

Secondary Publication Information
There are currently no secondary publications defined for this study.


Extraction Form: Cardiovascular Design
Design Details
Question... Follow Up Answer Follow-up Answer
What outcome is being evaluated in this paper? Cardiovascular
  • Comments Comments (
    0
    ) |
What is the objective of the study (as reported by the authors)? The objective of the present study was to determine whether genetic variation in catechol-O-methyltransferase (COMT) genotype affects the likelihood of reporting any acute effects of caffeine.
  • Comments Comments (
    0
    ) |
Provide a general description of the methods as reported by the authors. Information should be extracted based on relevance to the SR (i.e., caffeine related methods) Subjects and Data Collection Subjects (n = 1310) were from the Toronto Nutrigenomics and Health study, which is a cross-sectional examination of an ethnoculturally diverse population of men and women aged 20–29 years recruited from the University of Toronto campus. Individuals were excluded if they did not speak English, were pregnant or breastfeeding, or were unable to provide a fasting blood sample. Subjects were recruited between September 2004 and June 2009 through University of Toronto campus postings, e-mail bulletins, University newspaper advertisements, and classroom announcements. Subjects completed a general health and lifestyle questionnaire reporting their sex, age, ethnoculturalgroup, smoking status, oral contraceptive use inwomen and level of physical activity. Subjects were also excluded if they were missing dietary (n = 6) or genotype data (n = 33); were current smokers (n = 88), or reported use of antidepressants or anti-anxiety medication (n = 48). After exclusions, 1135 subjects (801 women and 334 men) were retained for analysis. Caffeine and Energy Intake Caffeine consumption and energy intake over the previous month were calculated from the estimated intake of various foods and beverages, assessed using the Toronto-modified Willet food frequency questionnaire (FFQ), which is semiquantitative and includes 196 items. The FFQ assessed all major dietary sources of caffeine in North America, including coffee, tea, cola, other caffeinated soda beverages, chocolate, and energy drinks. Subjects were asked to select 1 of 10 categories of caffeinated beverage intake: never, 1 cup/week or less, 2–4 cups/week, 5–6 cups/week, 1 cup/day, 2 cups/day, 3 cups/day, 4 cups/day, 5 cups/day, or 6 or more cups/day. Daily caffeine intake levels derived from the FFQ were calculated using the USDA National Nutrient Database for Standard Reference. Caffeine intake from over-the-counter medication was determined through the general health and lifestyle questionnaire. In general, the FFQ has been shown to be a valid and reliable method for assessing caffeine consumption in epidemiological research. Caffeine Habits Questionnaire Fourteen acute effects of caffeine, including increased heart rate, were assessed using a caffeine habits questionnaire. Subjects were asked, ‘‘Do you experience any of the following effects up to 12 hours after consuming one caffeine-containing beverage (e.g., coffee, tea, cola)?’’ To each of the 14 acute effects listed, subjects chose 1 of 5 responses for each of the acute effects, indicating the presence or severity of the effect: ‘‘don’t know,’’ ‘‘none,’’ ‘‘mild,’’ ‘‘moderate,’’ or ‘‘severe.’’ The caffeine habits questionnaire was developed specifically for this study population, and a portion of the questionnaire has been used in previous research. Genotyping Genomic DNA was extracted from whole blood collected after an overnight fast. Genotyping of the COMT Val158Met (rs4680) and CYP1A2-163A/C (rs762551) polymorphisms was performed by real-time (polymerase chain reaction (PCR) using Taq- Man_ SNP Genotyping Assays from Applied Biosystems (Foster City, CA). Allelic discrimination was completed using the ABI Prism 7000 Sequence Detection System. To ensure assay validity and reproducibility, 10% of the samples within each PCR run were replicated, and each run also contained four negative controls. Statistical Analysis All statistical analyses were performed using SAS version 9.2 (SAS Institute, Cary, NC). Subject characteristics are presented by COMT genotypes using mean – standard deviation for continuous variables (age, energy intake, physical activity level, weight, and body mass index [BMI]) and frequency and percentage for categorical variables (sex, ethnocultural group, CYP1A2 genotype, and oral contraceptive use in women). Caffeine was examined both as a continuous and as a categorical (< 100, 100–200, and > 200mg/day) variable. Differences in subject characteristics between genotypes were assessed by one-way analysis of variance using the GLM procedure for continuous variables, and by chi-squared tests using the FREQ procedure for categorical variables. All p-values were two-sided and significant when lessthan or equal to 0.05. The reported severities of the acute effects experienced within 12 hours of consuming a caffeinated beverage were dichotomized as‘‘No’’ (none) and ‘‘Yes’’ (mild, moderate, and severe) due to the low number of subjects who selected moderate or severe to most of the effects. For each acute effect, subjects reporting ‘‘don’t know’’ were excluded from that analysis. Unconditional multivariate logistic regression models were adjusted for covariates and used to calculate odds ratios (OR) and 95% confidence intervals (CI). The ORs represented the likelihood of experiencing each acute effect using the Val/Val genotype as the reference group. Variables considered as covariates were those that have been shown to influence caffeine consumption, response or metabolism including ethnocultural group, sex, BMI, age, physical activity level, alcohol intake, energy intake, and oral contraceptive use in women. Non-normally distributed variables were log-transformed (BMI and alcohol intake) for inclusion in the models. All potential covariates were included in the final models since they modified the -2 log (likelihood) ratio of the model. Interactions were tested by computing the likelihood ratio statistic, which is twice the difference between the log-likelihoods of (1) a model containing gene and covariate main effects and (2) a model than includes main effects and their interaction term. The resulting chi-square statistic is then compared to the chi-square distribution to determine significance. Caffeine intake level and CYP1A2 genotype were considered as potential confounders and tested through gene–variable interactions for each acute effect. Significant interactions were then investigated through stratified analyses.
  • Comments Comments (
    0
    ) |
How many outcome-specific endpoints are evaluated? 1
  • Comments Comments (
    0
    ) |
What is the (or one of the) endpoint(s) evaluated? (Each endpoint listed separately) Heart rate
  • Comments Comments (
    0
    ) |
List additional health endpoints (separately). 2
  • Comments Comments (
    0
    ) |
List additional health endpoints (separately).3
  • Comments Comments (
    0
    ) |
List additional health endpoints (separately).4
  • Comments Comments (
    0
    ) |
List additional health endpoints (separately).5
  • Comments Comments (
    0
    ) |
List additional health endpoints (separately).6
  • Comments Comments (
    0
    ) |
Clinical, physiological, other Physiological
  • Comments Comments (
    0
    ) |
What is the study design? Cross-sectional
  • Comments Comments (
    0
    ) |
Randomized or Non-Randomized?
  • Comments Comments (
    0
    ) |
What were the diagnostics or methods used to measure the outcome? Subjective
  • Comments Comments (
    0
    ) |
Optional: Name of Method or short description Self-reported
  • Comments Comments (
    0
    ) |
Caffeine (general) Caffeine (general)
  • Comments Comments (
    0
    ) |
Coffee, Chocolate, energy drink, gum, medicine/supplement, soda, tea, other?
  • Comments Comments (
    0
    ) |
Measured or self reported? Self-report
  • Comments Comments (
    0
    ) |
Children, adolescents, adults, or pregnant included? Adults
  • Comments Comments (
    0
    ) |
What was the reference, comparison, or control group(s)? (e.g. high vs low consumption, number of cups, etc.) The control group was based on genotype (Val/Val vs. Val/Met or Met/Met); however, these groups were split into 3 caffeine intake groups (<100 mg/day, 100-200 mg/day and >200 mg/day) for purposes of evaluating heart rate.
  • Comments Comments (
    0
    ) |
What were the listed confounders or modifying factors as stated by the authors? (e.g. multi-variable components of models.  Copy from methods) Variables considered as covariates were those that have been shown to influence caffeine consumption, response or metabolism including ethnocultural group, sex, BMI, age, physical activity level, alcohol intake, energy intake, and oral contraceptive use in women.
  • Comments Comments (
    0
    ) |
What conflicts of interest were reported? A. El-Sohemy holds a Canada Research Chair in Nutrigenomics. No competing financial interests exist.
  • Comments Comments (
    0
    ) |
Refid 10074
  • Comments Comments (
    0
    ) |
What were the sources of funding? This work was supported by the Advanced Foods and Materials Network (AFMNet) (grant number 305352) and the Canadian Institutes of Health Research (MOP-89829).
  • Comments Comments (
    0
    ) |




Results & Comparisons

No Results found.