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Coffee, CYP1A2 Genotype, and Risk of Myocardial Infarction

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The association between coffee intake and risk of myocardial infarction (MI) remains controversial. Coffee is a major source of caffeine, which is metabolized by the polymorphic cytochrome P450 1A2 (CYP1A2) enzyme. Individuals who are homozygous for the CYP1A2*1A allele are "rapid" caffeine metabolizers, whereas carriers of the variant CYP1A2*1F are "slow" caffeine metabolizers. To determine whether CYP1A2 genotype modifies the association between coffee consumption and risk of acute nonfatal MI. Cases (n = 2014) with a first acute nonfatal MI and population-based controls (n = 2014) living in Costa Rica between 1994 and 2004, matched for age, sex, and area of residence, were genotyped by restriction fragment-length polymorphism polymerase chain reaction. A food frequency questionnaire was used to assess the intake of caffeinated coffee. Relative risk of nonfatal MI associated with coffee intake, calculated using unconditional logistic regression. Fifty-five percent of cases (n = 1114) and 54% of controls (n = 1082) were carriers of the slow *1F allele. For carriers of the slow *1F allele, the multivariate-adjusted odds ratios (ORs) and 95% confidence intervals (CIs) of nonfatal MI associated with consuming less than 1, 1, 2 to 3, and 4 or more cups of coffee per day were 1.00 (reference), 0.99 (0.69-1.44), 1.36 (1.01-1.83), and 1.64 (1.14-2.34), respectively. Corresponding ORs (95% CIs) for individuals with the rapid *1A/*1A genotype were 1.00, 0.75 (0.51-1.12), 0.78 (0.56-1.09), and 0.99 (0.66-1.48) (P = .04 for gene x coffee interaction). For individuals younger than the median age of 59 years, the ORs (95% CIs) associated with consuming less than 1, 1, 2 to 3, or 4 or more cups of coffee per day were 1.00, 1.24 (0.71-2.18), 1.67 (1.08-2.60), and 2.33 (1.39-3.89), respectively, among carriers of the *1F allele. The corresponding ORs (95% CIs) for those with the *1A/*1A genotype were 1.00, 0.48 (0.26-0.87), 0.57 (0.35-0.95), and 0.83 (0.46-1.51). Intake of coffee was associated with an increased risk of nonfatal MI only among individuals with slow caffeine metabolism, suggesting that caffeine plays a role in this association.
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. 2006;295(10):1135-1141 (doi:10.1001/jama.295.10.1135) JAMA
Marilyn C. Cornelis; Ahmed El-Sohemy; Edmond K. Kabagambe; et al.
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ORIGINAL CONTRIBUTION
Coffee, CYP1A2 Genotype,
and Risk of M yocardial Infarction
Marilyn C. Cornelis, BSc
Ahmed El-Sohemy, PhD
Edmond K. Kabagambe, PhD
Hannia Campos, PhD
E
PIDEMIOLOGIC STUDIES EXAMIN-
ing the association between cof-
fee consumption and risk of
myocardial infarction (MI) have
been inconclusive.
1-14
Coffee is a ma-
jor source of caffeine (1,3,7-trimethyl-
xanthine), which is the most widely
consumed stimulant in the world and
has been implicated in the develop-
ment of cardiovascular diseases such
as acute MI.
15-17
However, coffee con-
tains a number of other chemicals that
have variable effects on the cardiovas-
cular system.
18
Because of the strong
collinearity between caffeine intake and
coffee consumption in many popula-
tions, it is not clear whether caffeine
alone affects the risk of MI or whether
other chemicals found in coffee may be
responsible. Furthermore, the associa-
tion between coffee consumption and
unhealthy lifestyle factors suggests that
previous associations might have been
due to residual confounding.
19
Caffeine is metabolized primarily by
cytochrome P450 1A2 (CYP1A2) in the
liver through an initial N
3
-demethyl-
ation.
20,21
CYP1A2 accounts for approxi-
mately 95% of caffeine metabolism and
demonstrates wide variability in en-
zyme activity between individuals.
21-23
An AC substitution at position 734
(CYP1A2*1F)intheCYP1A2 gene de-
creases enzyme inducibility as mea-
sured by the ratio of plasma or urinary
caffeine to caffeine metabolites after a
dose of caffeine, resulting in impaired
caffeine metabolism.
24-26
Carriers of the
variant CYP1A2*1F allele are “slow” caf-
feine metabolizers, whereas individu-
als who are homozygous for the
CYP1A2*1A allele are “rapid” caffeine
metabolizers.
24-26
The purpose of this
study was to determine whether
CYP1A2 genotype modifies the asso-
ciation between intake of caffeinated
coffee and risk of nonfatal MI.
METHODS
Study Design and Participants
The catchment area for this study com-
prised 7071 km
2
and 2 057 000 indi-
viduals living in Costa Rica who are self-
described Hispanic Americans.
27
This
area included 36 counties in the Cen-
tral Valley of Costa Rica representing
a full range of socioeconomic levels, as
Author Affiliations: Department of Nutritional Sci-
ences, University of Toronto, Toronto, Ontario (Ms Cor-
nelis and Dr El-Sohemy); Department of Nutrition, Har-
vard School of Public Health, Boston, Mass (Drs
Kabagambe and Campos); and Centro Centroameri-
cano de Poblacion, Universidad de Costa Rica, San Pe-
dro de Montes de Oca, Costa Rica (Dr Campos).
Corresponding Author: Ahmed El-Sohemy, PhD, De-
partment of Nutritional Sciences, University of Toronto,
150 College St, Toronto, Ontario, Canada M5S 3E2
(a.el.sohemy@utoronto.ca).
Context The association between coffee intake and risk of myocardial infarction (MI)
remains controversial. Coffee is a major source of caffeine, which is metabolized by
the polymorphic cytochrome P450 1A2 (CYP1A2) enzyme. Individuals who are ho-
mozygous for the CYP1A2*1A allele are “rapid” caffeine metabolizers, whereas car-
riers of the variant CYP1A2*1F are “slow” caffeine metabolizers.
Objective To determine whether CYP1A2 genotype modifies the association be-
tween coffee consumption and risk of acute nonfatal MI.
Design, Setting, and Participants Cases (n=2014) with a first acute nonfatal MI
and population-based controls (n=2014) living in Costa Rica between 1994 and 2004,
matched for age, sex, and area of residence, were genotyped by restriction fragment–
length polymorphism polymerase chain reaction. A food frequency questionnaire was
used to assess the intake of caffeinated coffee.
Main Outcome Measure Relative risk of nonfatal MI associated with coffee in-
take, calculated using unconditional logistic regression.
Results Fifty-five percent of cases (n=1114) and 54% of controls (n=1082) were car-
riers of the slow *1F allele. For carriers of the slow *1F allele, the multivariate-adjusted
odds ratios (ORs) and 95% confidence intervals (CIs) of nonfatal MI associated with
consuming less than 1, 1, 2 to 3, and 4 or more cups of coffee per day were 1.00 (ref-
erence), 0.99 (0.69-1.44), 1.36 (1.01-1.83), and 1.64 (1.14-2.34), respectively. Corre-
sponding ORs (95% CIs) for individuals with the rapid *1A/*1A genotype were 1.00,
0.75 (0.51-1.12), 0.78 (0.56-1.09), and 0.99 (0.66-1.48) (P=.04 for genecoffee in-
teraction). For individuals younger than the median age of 59 years, the ORs (95% CIs)
associated with consuming less than 1, 1, 2 to 3, or 4 or more cups of coffee per day
were 1.00, 1.24 (0.71-2.18), 1.67 (1.08-2.60), and 2.33 (1.39-3.89), respectively, among
carriers of the *1F allele. The corresponding ORs (95% CIs) for those with the *1A/*1A
genotype were 1.00, 0.48 (0.26-0.87), 0.57 (0.35-0.95), and 0.83 (0.46-1.51).
Conclusion Intake of coffee was associated with an increased risk of nonfatal MI
only among individuals with slow caffeine metabolism, suggesting that caffeine plays
a role in this association.
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well as urban, periurban, and rural life-
styles. Medical services in this area were
covered by 6 large hospitals, which are
part of the National Social Security Sys-
tem. Eligible case participants were men
and women who were survivors of a
first acute MI as diagnosed by a cardi-
ologist at any of the 6 recruiting hos-
pitals in the catchment area between
1994 and 2004. To achieve 100% as-
certainment, the hospitals were vis-
ited daily by the study fieldworkers. All
cases were confirmed by 2 indepen-
dent cardiologists according to the
World Health Organization criteria for
MI, which require typical symptoms
plus either elevation in cardiac en-
zyme levels or diagnostic change in
electrocardiogram tracings.
28
Enroll-
ment was carried out while cases were
in the hospital’s step-down unit. Case
participants were ineligible if they died
during hospitalization, were 75 years
or older on the day of their first MI,
were physically or mentally unable to
answer the questionnaire, or had a pre-
vious hospital admission related to car-
diovascular disease.
One control participant for each case,
matched for age (±5 years), sex, and area
of residence (county), was randomly se-
lected using information available at the
National Census and Statistics Bureau
of Costa Rica. Eligible controls were
identified within 1 week of the case se-
lection. On average, it took 27 days to
complete data collection for cases and
31 days for controls. Because of the com-
prehensive social services provided in
Costa Rica, all persons living in the
catchment areas had access to medical
care without regard to income. There-
fore, control participants came from the
source population that gave rise to the
cases and are not likely to have had car-
diovascular disease that was not diag-
nosed because of poor access to medi-
cal care. Controls were ineligible if they
were physically or mentally unable to an-
swer the questionnaires or if they had
had a previous hospital admission re-
lated to MI or other cardiovascular
disease.
Participation for eligible cases and
controls was 98% and 88%, respec-
tively. All participants were visited at
their homes for collection of biologi-
cal specimens and information on diet,
medical history, and anthropometric
measurements. Cases and controls gave
written informed consent and the study
was approved by the ethics commit-
tees of the Harvard School of Public
Health and the University of Costa Rica,
the Office for the Protection from Re-
search Risks at the National Institutes
of Health, and the ethics review com-
mittee at the University of Toronto.
All data were collected by trained
fieldworkers during an interview using
2 questionnaires consisting of closed-
ended questions regarding smoking, so-
ciodemographic characteristics, socio-
economic status, physical activity, diet,
and medical history including use of
medication and personal history of dia-
betes and hypertension. Information on
dietary intake was collected using a 135-
item semiquantitative food frequency
questionnaire (FFQ) specifically devel-
oped and validated to assess dietary in-
take during the past year in the Costa
Rican population.
29
For cases, average
intake represented the year preceding
their MI. Intakes of nutrients were cal-
culated using the US Department of Ag-
riculture food composition data file. In-
cluded in the FFQ were questions related
to the consumption of caffeinated cof-
fee, tea, cola beverages, and chocolate.
The standard portion size for coffee in
the FFQ was fixed as 1 cup equivalent
to 250 mL, based on the habitual por-
tion size for coffee-drinking habits es-
tablished in this population during
methods development.
29
Participants
were asked to specify 1 of 9 categories
of coffee intake: none or less than 1 cup/
mo, 1 to 3 cups/mo, 1 cup/wk, 2 to 4
cups/wk, 5 to 6 cups/wk, 1 cup/d, 2 to
3 cups/d, 4 to 5 cups/d, or 6 cups/d or
more. The correlation coefficient for caf-
feine intake between seven 24-hour re-
calls and the average of 2 FFQ inter-
views was 0.83, and the correlation
coefficient between both FFQs was
0.77.
29
These results indicate high va-
lidity and reliability for the usual in-
take of coffee. Method of coffee prepa-
ration was ascertained for coffee
drinkers. Approximately 90% of coffee
consumed in Costa Rica is filtered. Par-
ticipants were categorized into 4 groups
with reported coffee intakes of less than
1, 1, 2 to 3, or 4 or more 250-mL cups
per day.
CYP1A2 Genotyping
Blood samples were collected in the
morning at the participant’s home after
an overnight fast and were centrifuged
to separate the plasma and leukocytes
for DNA isolation by standard proce-
dures. The CYP1A2*1F (rs762551) poly-
morphism was detected by restriction
fragment–length polymorphism poly-
merase chain reaction as previously
described,
30
without knowledge of case-
control status. The genotype distribu-
tion among controls did not deviate from
Hardy-Weinberg equilibrium accord-
ing to a Pearson
2
test with 1 df.
Statistical Analyses
All data were analyzed using SAS ver-
sion 8.2 (SAS Institute Inc, Cary, NC);
P.05 was considered statistically sig-
nificant. DNA was available from 4369
participants (2113 cases and 2256 con-
trols). A total of 341 participants were
excluded because they were missing
data on confounders (33 cases, 26 con-
trols), could not be genotyped (63 cases,
73 controls), or became unmatched
because of missing data (3 cases, 143
controls), leaving 2014 matched case-
control pairs for the final analysis. In-
dividual nutrient intakes were ad-
justed for total energy as described
elsewhere.
29,31
Because of the matched
design, significant differences in the dis-
tribution of variables between cases
and controls were tested using the
McNemar test (categorical variables)
and either paired t tests or Wilcoxon
signed rank tests (continuous vari-
ables). Categorical and continuous non-
dietary and energy-adjusted dietary
variables were assessed for potential
confounding by measuring their effect
on the model parameter estimates us-
ing the likelihood ratio test. Odds ra-
tios (ORs) and Wald 95% confidence
intervals (95% CIs) were estimated by
conditional logistic regression to de-
COFFEE, CYP1A2 GENOTYPE, AND RISK OF MYOCARDIAL INFARCTION
1136 JAMA, March 8, 2006—Vol 295, No. 10 (Reprinted) ©2006 American Medical Association. All rights reserved.
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termine the effect of coffee intake on
the risk of MI, with the lowest level of
coffee intake (1 cup/d) as the refer-
ence group. Confounders included in
the final models were smoking (never,
past, 1-19 cigarettes/d, and 20 ciga-
rettes/d); alcohol consumption (never,
past, and tertiles of intake among cur-
rent drinkers); history of diabetes (yes/
no), history of hypertension (yes/no);
quintiles of the continuous variables
waist-hip ratio, physical activity, and in-
come; and energy-adjusted intakes of
sucrose, saturated fat, polyunsatu-
rated fat, and trans fat. We evaluated po-
tential genecoffee interactions by de-
termining the relation between coffee
intake and the risk of MI for each geno-
type using conditional and uncondi-
tional logistic regression (with match-
ing variables in the model) and by
comparing –2 log (likelihood) ratios
from a model with coffee and gene main
effects only and from another that in-
cluded their interaction term. Because
results for conditional and uncondi-
tional regressions were similar, we re-
port only the data from unconditional
analyses to maximize the number of
participants. Results are presented us-
ing a dominant *1F allele model with
*1A/*1F and *1F/*1F genotypes com-
bined, because both groups have a simi-
lar rate of caffeine metabolism.
24-26
We
also investigated whether smoking sta-
tus (nonsmoker, current smoker) or age
(below/above median) modified the re-
lationship between CYP1A2 genotype
and MI associated with coffee intake,
by performing stratified analyses and
evaluating the gene coffee interac-
tion separately for each subgroup.
RESULTS
Demographic and risk factor charac-
teristics of participants based on case-
control status and coffee intake among
controls are presented in T
ABLE 1. The
proportion of *1F carriers did not dif-
fer between cases and controls or be-
tween different categories of coffee in-
take. T
ABLE 2 shows the risk of MI
associated with coffee intake for all par-
ticipants and by CYP1A2 genotype.
Compared with individuals consum-
ing less than 1 cup/d, the multivariate-
adjusted OR (95% CI) of MI associ-
ated with consuming 4 cups/day or
more was 1.40 (1.05-1.87). When par-
ticipants were stratified by CYP1A2
Table 1. Demographic and Risk Factor Characteristics by Case-Control Status and by Coffee Intake Among Controls
Characteristic
No. (%)
P Value,
Cases vs
Controls
Controls Coffee Intake, No. (%)
Cases
(n = 2014)
Controls
(n = 2014)
1
Cup/d
(n = 269)
1
Cup/d
(n = 338)
2-3
Cups/d
(n = 1133)
4
Cups/d
(n = 274)
CYP1A2*1A/*1F *1F/*F, No. (%) 1114 (55) 1082 (54) .31 156 (58) 180 (53) 595 (53) 151 (55)
Age, mean (SD), y* 58.4 (11.0) 58.1 (11.3) 56.7 (12.4) 58.4 (11.9) 58.7 (11.1) 56.7 (10.2)
Men, No. (%)* 1488 (74) 1488 (74) 190 (71) 243 (72) 818 (72) 237 (86)
Urban residence, No. (%)* 1482 (74) 1482 (74) 209 (78) 273 (81) 801 (71) 198 (72)
Secondary education or higher, No. (%) 733 (36) 806 (40) .007 148 (55) 163 (48) 392 (35) 103 (38)
Household income, mean (SD), US $/mo 499 (388) 571 (425) .001 735 (492) 632 (456) 522 (381) 543 (441)
Waist-hip ratio, mean (SD) 0.97 (0.07) 0.95 (0.07) .001 0.94 (0.08) 0.95 (0.08) 0.95 (0.08) 0.96 (0.06)
Physical activity, mean (SD), METs 1.51 (0.69) 1.57 (0.70) .01 1.46 (0.48) 1.50 (0.68) 1.56 (0.69) 1.76 (0.87)
Medical history, No. (%)
History of hypertension† 779 (39) 596 (30) .001 78 (29) 113 (33) 341 (30) 64 (23)
History of diabetes† 492 (24) 285 (14) .001 29 (11) 48 (14) 179 (16) 29 (11)
Current smoking‡ 805 (40) 425 (21) .001 32 (12) 45 (13) 230 (20) 118 (43)
Current alcohol consumption† 984 (49) 1059 (53) .01 138 (51) 200 (59) 576 (51) 145 (53)
Nutrient intakes, mean (SD)
Total energy, kcal 2714 (946) 2457 (764) .001 2461 (759) 2340 (674) 2445 (748) 2648 (894)
Carbohydrate, % energy 54.3 (7.6) 55.4 (7.3) .001 54.9 (7.9) 53.7 (7.5) 55.9 (6.8) 55.8 (8.1)
Protein, % energy 13.2 (2.2) 12.9 (2.1) .001 12.9 (2.3) 13.2 (2.2) 13.0 (2.0) 12.7 (2.2)
Fat, % energy 32.4 (5.9) 31.9 (5.9) .008 32.6 (6.6) 32.9 (6.4) 31.6 (5.3) 31.3 (6.4)
Saturated fat, % energy 12.4 (3.1) 11.7 (2.9) .001 11.4 (3.0) 11.8 (2.9) 11.7 (2.8) 12.0 (3.2)
Polyunsaturated fat, % energy 6.9 (2.3) 7.1 (2.3) .001 7.2 (2.0) 7.3 (2.4) 7.1 (2.4) 6.6 (2.4)
Monounsaturated fat, % energy 11.1 (3.5) 11.2 (4.1) .70 12.2 (5.2) 11.9 (4.8) 10.9 (3.4) 11.0 (4.1)
Trans fat, % energy 1.3 (0.6) 1.3 (0.6) .06 1.2 (0.6) 1.2 (0.6) 1.3 (0.7) 1.3 (0.6)
Cholesterol, mg/1000 kcal 127 (59) 118 (52) .001 120 (48) 113 (50) 119 (53) 117 (57)
Sucrose, g/d 80.1 (50.8) 75.2 (43.2) .001 74.3 (40.1) 63.6 (33.0) 73.9 (39.0) 95.8 (62.7)
Fiber, g/1000 kcal 9.5 (2.4) 10.0 (2.5) .001 10.1 (2.7) 9.9 (2.5) 10.1 (2.4) 9.3 (2.3)
Folate, µg/1000 kcal 170 (46) 175 (47) .001 183 (50) 174 (46) 177 (46) 162 (43)
Abbreviation: METs, metabolic equivalent tasks.
*Matching variable.
†See “Methods” for definition.
‡One or more cigarettes per day.
COFFEE, CYP1A2 GENOTYPE, AND RISK OF MYOCARDIAL INFARCTION
©2006 American Medical Association. All rights reserved. (Reprinted) JAMA, March 8, 2006—Vol 295, No. 10 1137
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genotype, the increased risk of MI as-
sociated with coffee intake was ob-
served only among carriers of the slow
*1F allele (P= .04 for gene coffee in-
teraction). In this group, the OR (95%
CI) of MI was 1.64 (1.14-2.34) for 4
cups/d or more, as compared with less
than 1 cup/d. The corresponding OR
(95% CI) among those who were ho-
mozygous for the rapid *1A allele was
0.99 (0.66-1.48). Similar results were
observed when men and women were
examined separately. Compared with
less than 1 cup/d, the ORs (95% CIs)
of MI for 4 cups/d or more among in-
dividuals with the *1A/*1A genotype
were 0.86 (0.53-1.36) for men and 1.43
(0.54-3.72) for women. Correspond-
ing ORs (95% CIs) among carriers of
the *1F allele were 1.54 (1.03-2.32) for
men and 2.83 (1.15-6.99) for women.
Because smoking is associated with
coffee consumption and is also a strong
inducer of CYP1A2,
32
we performed
analyses separately for current smok-
ers and nonsmokers (never, past). Al-
though the genecoffee interaction did
not reach significance in either group,
the modifying effect of CYP1A2 geno-
type on risk of MI associated with cof-
fee consumption was similar for both
smokers and nonsmokers (T
ABLE 3).
It has previously been suggested that
coffee may be associated with an in-
creased risk of MI only among younger
individuals.
7,8
To investigate whether
age modified the interaction between
CYP1A2 and coffee on risk of MI, we
assessed risk separately for partici-
pants above and below the median age
(59 years). A significant gene coffee
interaction (P =.003) was observed
only among the younger participants
(Table 3). For those individuals who
were carriers of the *1F allele, the ORs
(95% CIs) of MI associated with con-
suming less than 1, 1, 2 to 3, or 4 or
more cups of coffee per day were 1.00
(reference), 1.24 (0.71-2.18), 1.67
(1.08-2.60), and 2.33 (1.39-3.89), re-
spectively. Corresponding ORs (95%
CIs) for those with the *1A/*1A geno-
type were 1.00, 0.48 (0.26-0.87), 0.57
(0.35-0.95), and 0.83 (0.46-1.51). Be-
cause of the observed interaction with
participants younger than the median
age of 59 years, we also analyzed those
younger than 50 years (448 cases, 478
controls), as has been previously done.
33
For carriers of the *1F allele, the ORs
(95% CIs) of MI associated with con-
suming less than 1, 1, 2 to 3, or 4 or
more cups of coffee per day were 1.00,
2.12 (0.86-5.24), 2.43 (1.22-4.82), and
4.07 (1.89-8.74), respectively. Corre-
sponding ORs (95% CIs) for those with
the *1A/*1A genotype were 1.00, 0.39
(0.15-0.97), 0.35 (0.17-0.76), and 0.81
(0.32-2.05) (P.001 for gene coffee
interaction).
COMMENT
Coffee is a major source of caffeine,
which has multiple physiological ef-
fects that could increase the risk of MI.
17
Numerous studies have examined the
association between coffee consump-
tion and risk of MI, but the findings
have been inconclusive.
1-14
Caffeine is
detoxified primarily through an initial
N
3
-demethylation that is catalyzed
by CYP1A2, an enzyme that displays
wide interindividual variability in
activity.
21-23
We investigated whether
a common genetic polymorphism
(CYP1A2*1F) that results in a “slow”
metabolizer phenotype modifies the as-
sociation between intake of caffein-
ated coffee and risk of nonfatal MI. Our
findings show that coffee consump-
tion increases the risk of MI only among
individuals with a slow metabolizer
genotype.
Meta-analyses examining the rela-
tionship between coffee intake and risk
of coronary heart disease have ob-
served a positive association among
case-control studies but not among pro-
spective cohort studies.
1,2
According to
the most recent meta-analysis,
1
the
pooled case-control data show a 60%
increased risk for drinking 5 cups/d. It
has been suggested that the positive as-
sociations reported in case-control stud-
ies may have resulted from recall bias
or confounding by factors such as
smoking.
19,34
However, because we ob-
served an association between coffee
and risk of MI among carriers of the *1F
allele, and not among those homozy-
gous for the *1A allele, the associa-
tions between coffee and MI are un-
likely due to recall bias or residual
confounding. Moreover, when we
stratified our population by smoking
Table 2. Coffee Intake and Relative Risk of Myocardial Infarction by CYP1A2 Genotype
Coffee Intake,
Cups/d
No. (%)
OR (95% CI)
Cases Controls Model 1 Model 2
Total population n = 2014 n = 2014
1 202 (10) 269 (13) 1.00* 1.00†
1 234 (12) 338 (17) 0.92 (0.71-1.18) 0.91 (0.68-1.21)
2-3 1146 (57) 1133 (56) 1.33 (1.09-1.63) 1.13 (0.89-1.42)
4 432 (21) 274 (14) 2.11 (1.66-2.69) 1.40 (1.05-1.87)
*1A/*1A n = 900 n = 932
1 94 (10) 113 (12) 1.00‡ 1.00§
1 117 (13) 158 (17) 0.89 (0.62-1.28) 0.75 (0.51-1.12)
2-3 510 (57) 538 (58) 1.14 (0.85-1.54) 0.78 (0.56-1.09)
4 179 (10) 123 (13) 1.76 (1.23-2.52) 0.99 (0.66-1.48)
*1A/*1F *1F/*1F n = 1114 n = 1082
1 108 (9) 156 (14) 1.00‡ 1.00§
1 117 (11) 180 (17) 0.91 (0.65-1.28) 0.99 (0.69-1.44)
2-3 636 (57) 595 (55) 1.51 (1.15-1.98) 1.36 (1.01-1.83)
4 253 (23) 151 (14) 2.43 (1.77-3.35) 1.64 (1.14-2.34)
Abbreviations: CI, confidence interval; OR, odds ratio.
*Conditional logistic regression model (unadjusted).
†Conditional logistic regression model adjusted for smoking (never, past, 1-19 cigarettes/d, 20 cigarettes/d); waist-
hip ratio; income; physical activity; history of diabetes; history of hypertension; and intakes of alcohol, total energy,
and energy-adjusted saturated fat, polyunsaturated fat, trans fat, folate, and sucrose (see “Methods”).
‡Unconditional logistic regression model that included matching variables (age, sex, and area of residence).
§Results from unconditional logistic regression that included matching variables and the confounders listed above for
model 2. Gene coffee interaction, P = .04.
COFFEE, CYP1A2 GENOTYPE, AND RISK OF MYOCARDIAL INFARCTION
1138 JAMA, March 8, 2006—Vol 295, No. 10 (Reprinted) ©2006 American Medical Association. All rights reserved.
by guest on June 1, 2008 www.jama.comDownloaded from
status, the results were similar for non-
smokers and current smokers (Table 3).
A more likely explanation for the dis-
crepancies between case-control and
prospective cohort studies is that cof-
fee drinking has mainly acute effects,
which would be misclassified in pro-
spective studies with a long follow-up
and no updating of coffee intake.
1-3
In
a study by LaCroix et al,
4
the relative
risk of coronary heart disease for 5 or
more cups per day compared with none
increased from 1.89 when intake was
assessed 10 or more years previously to
2.49 when intake within the past 5 years
was used. Similarly, a strong associa-
tion between coffee consumption and
mortality from coronary heart dis-
ease, reported after 6 years of follow-
up,
5
was weakened by 6 more years of
follow-up.
6
The decreased effect of cof-
fee after longer follow-up could also be
a result of caffeine having a weaker
effect in an older population. Indeed,
the CYP1A2coffee interaction we ob-
served among individuals younger than
the median age suggests that caffeine
has a greater relative effect on younger
individuals. Among the slow metabo-
lizers, the risk associated with drink-
ing 4 cups/d or more compared with
less than 1 cup/d increased from 2-fold
for individuals younger than 59 years
to more than 4-fold for those younger
than 50 years. A similar effect of age was
observed by Palmer et al,
7
who found
a greater risk of MI with caffeinated cof-
fee consumption among women 45
through 59 years of age but not among
women 60 years or older.
The absence of an association be-
tween coffee and risk of MI in some
case-control studies may have been due
to a lower frequency of *1F carriers in
the populations that were examined. In
the present study, the frequency of car-
riers of the *1F allele was 54%, but fre-
quencies have been reported to vary by
population.
35-38
Because cases in the pre-
sent study experienced nonfatal MI, we
cannot exclude the possibility that the
observed interaction may affect sur-
vival after an acute MI.
Although smokers metabolize caf-
feine more rapidly than nonsmokers
Table 3. Coffee Intake and Relative Risk of Myocardial Infarction by CYP1A2 Genotype,
Smoking Status, and Age Category
Coffee Intake, Cups/d
No. (%)
OR (95% CI)
Cases Controls Model 1 Model 2
Smoking Status*
Nonsmokers
*1A/*1A n = 532 n = 745
1 75 (14) 101 (14) 1.00 1.00
1 84 (16) 135 (18) 0.84 (0.56-1.25) 0.73 (0.47-1.14)
2-3 312 (59) 436 (58) 0.95 (0.68-1.33) 0.75 (0.52-1.07)
4 61 (11) 73 (10) 1.13 (0.71-1.77) 1.02 (0.62-1.67)
*1A/*1F *1F/*1F n = 677 n = 844
1 85 (13) 136 (16) 1.00 1.00
1 97 (14) 158 (18) 0.96 (0.66-1.40) 1.01 (0.67-1.51)
2-3 399 (59) 467 (55) 1.32 (0.97-1.79) 1.27 (0.91-1.76)
4 98 (14) 83 (10) 1.93 (1.29-2.88) 1.72 (1.11-2.67)
Smokers
*1A/*1A n = 368 n = 187
1 19 (5) 12 (6) 1.00 1.00
1 33 (9) 23 (12) 0.90 (0.36-2.23) 0.87 (0.30-2.51)
2-3 198 (54) 102 (55) 1.23 (0.57-2.64) 1.11 (0.45-2.76)
4 118 (32) 50 (27) 1.59 (0.71-3.54) 1.22 (0.47-3.18)
*1A/*1F *1F/*1F n = 437 n = 238
1 25 (6) 20 (8) 1.00 1.00
1 20 (5) 22 (9) 0.65 (0.27-1.54) 0.90 (0.33-2.50)
2-3 237 (54) 128 (54) 1.42 (0.75-2.70) 1.77 (0.83-3.76)
4 155 (35) 68 (29) 1.83 (0.94-3.56) 1.79 (0.80-3.98)
Age Category†
Age 59 y‡
*1A/*1A n = 451 n = 446
1 51 (11) 50 (11) 1.00 1.00
1 53 (12) 78 (17) 0.66 (0.39-1.12) 0.48 (0.26-0.87)
2-3 228 (51) 252 (57) 0.89 (0.58-1.37) 0.57 (0.35-0.95)
4 119 (26) 66 (15) 1.78 (1.09-2.92) 0.83 (0.46-1.51)
*1A/*1F *1F/*1F n = 505 n = 552
1 49 (10) 98 (18) 1.00 1.00
1 46 (9) 89 (16) 1.03 (0.63-1.69) 1.24 (0.71-2.18)
2-3 266 (53) 282 (51) 1.87 (1.28-2.75) 1.67 (1.08-2.60)
4 144 (29) 83 (15) 3.47 (2.24-5.37) 2.33 (1.39-3.89)
Age 59 y
*1A/*1A n = 449 n = 486
1 43 (10) 63 (13) 1.00 1.00
1 64 (14) 80 (16) 1.17 (0.70-1.94) 1.10 (0.63-1.92)
2-3 282 (63) 286 (59) 1.44 (0.94-2.20) 1.06 (0.67-1.69)
4 60 (13) 57 (12) 1.56 (0.92-2.66) 1.06 (0.58-1.94)
*1A/*1F *1F/*1F n = 609 n = 530
1 59 (10) 58 (11) 1.00 1.00
1 71 (12) 91 (17) 0.78 (0.48-1.25) 0.79 (0.47-1.32)
2-3 370 (61) 313 (59) 1.18 (0.79-1.74) 1.06 (0.69-1.63)
4 109 (18) 68 (13) 1.54 (0.95-2.48) 1.09 (0.64-1.86)
Abbreviations: CI, confidence interval; OR, odds ratio.
*Model 1: unconditional logistic regression model adjusted for age, sex, and area of residence. Model 2: unconditional
logistic regression model adjusted for age; sex; area of residence; waist-hip ratio; income; physical activity; history of
diabetes; history of hypertension; and intakes of alcohol, total energy, and energy-adjusted saturated fat, polyun-
saturated fat, trans fat, folate and sucrose (see “Methods”). Nonsmokers were further adjusted for never and past
smoking, and smokers adjusted for cigarettes smoked per day.
†Model 1: unconditional logistic regression model adjusted for age, sex, area of residence. Model 2: unconditional
logistic regression model adjusted for age; sex; area of residence; smoking (never, past, 1-19 cigarettes/d, 20
cigarettes/d); waist-hip ratio; income; physical activity; history of diabetes; history of hypertension; and intakes of
alcohol, total energy, and energy-adjusted saturated fat, polyunsaturated fat, trans fat, folate, and sucrose (see “Meth-
ods”).
P = .003 for gene coffee interaction.
COFFEE, CYP1A2 GENOTYPE, AND RISK OF MYOCARDIAL INFARCTION
©2006 American Medical Association. All rights reserved. (Reprinted) JAMA, March 8, 2006—Vol 295, No. 10 1139
by guest on June 1, 2008 www.jama.comDownloaded from
due to the well-known CYP1A2-
inducing effect of smoking,
32
the ex-
tent of CYP1A2 induction among smok-
ers is lower for carriers of the *1F
allele.
25,26
Thus, smokers with the slow
metabolizer genotype may still have an
increased risk of MI with increasing cof-
fee consumption. Indeed, for carriers
of the *1F allele, a similar pattern of risk
associated with coffee was observed
among smokers and nonsmokers
(Table 3).
Among younger individuals who
were rapid caffeine metabolizers, cof-
fee intakes of either 1 cup/d or 2 to 3
cups/d were associated with a lower risk
of MI compared with intakes of less
than 1 cup/d. This finding is consis-
tent with a number of previous re-
ports of J- or U-shaped associations be-
tween coffee and MI,
11-14
suggesting a
protective effect of moderate coffee con-
sumption. It has been proposed that the
higher risk of heart disease among the
group with the lowest intake might be
due to individuals with underlying dis-
eases who are limiting their coffee in-
take.
12,14
However, the absence of an el-
evated risk in the lowest category of
coffee intake among the slow metabo-
lizers in the present study indicates that
this is unlikely.
Coffee contains other chemicals that
may have adverse effects on the cardio-
vascular system.
18
Distinguishing be-
tween the effects of caffeine and those
of these other compounds has been dif-
ficult, given the strong collinearity be-
tween caffeine and coffee intake in many
populations. Diterpenoids that are pre-
sent in the lipid fraction of boiled cof-
fee have been shown to increase levels
of serum cholesterol
39-41
and may in-
crease the risk of MI.
9
However, the lev-
els of diterpenoids are greatly reduced
in filtered coffee.
42
About 10% of coffee
drinkers in the current population did
not report consuming filtered coffee, and
excluding them from our analyses did
not materially alter the results (data not
shown). Besides caffeine, no other ma-
jor compound found in filtered coffee
is known to be detoxified by CYP1A2.
Thus, our findings suggest that caf-
feine is the major component of fil-
tered coffee that increases risk of non-
fatal MI. Although the mechanism by
which caffeine increases risk of MI re-
mains unclear, it is known to block the
A
1
and A
2A
adenosine receptors.
43,44
Adenosine is a potent coronary and sys-
temic vasodilator that may play an im-
portant role in the reactivity of inflam-
matory cells and platelets during periods
of myocardial ischemia.
45,46
Although the CYP1A2*1F polymor-
phism is located in a noncoding re-
gion of the gene, the polymorphism
may result in differential binding of
regulatory proteins to the surround-
ing sequence that may affect CYP1A2
expression levels.
25
The regulatory
mechanisms of intronic polymor-
phisms on transcriptional activity have
been described for several genes.
47
Al-
ternatively, the polymorphism may be
in linkage disequilibrium with other
single nucleotide polymorphisms in-
fluencing CYP1A2 inducibility.
25
Nev-
ertheless, in vivo studies clearly show
marked differences in CYP1A2 activ-
ity between carriers of the different
CYP1A2 alleles.
24-26
In summary, consistent with most
case-control studies, we found that in-
creased coffee intake is associated with
an increased risk of nonfatal MI. The
association between coffee and MI was
found only among individuals with the
slow CYP1A2*1F allele, which im-
pairs caffeine metabolism, suggesting
that caffeine plays a role in the asso-
ciation.
Author Contributions: Dr El-Sohemy had full access
to all of the data in the study and takes responsibility
for the integrity of the data and the accuracy of the
data analysis.
Study concept and design: El-Sohemy, Campos.
Acquisition of data: Cornelis, El-Sohemy, Campos.
Analysis and interpretation of data: Cornelis,
El-Sohemy, Kabagambe, Campos.
Drafting of the manuscript: Cornelis, El-Sohemy.
Critical revision of the manuscript for important in-
tellectual content: Cornelis, El-Sohemy, Kabagambe,
Campos.
Statistical analysis: Cornelis, El-Sohemy, Kabagambe,
Campos.
Obtained funding: El-Sohemy, Campos.
Administrative, technical, or material support: Campos.
Study supervision: El-Sohemy, Campos.
Financial Disclosures: None reported.
Funding/Support: This research was supported by
grants from the Canadian Institutes of Health Re-
search (MOP-53147) and the National Institutes of
Health (HL 60692 and HL 071888). Ms Cornelis is a
recipient of a Natural Sciences and Engineering Re-
search Council of Canada postgraduate scholarship.
Dr El-Sohemy holds a Canada Research Chair in Nu-
trigenomics.
Role of the Sponsor: The Canadian Institutes of Health
Research and the National Institutes of Health had no
role in the design and conduct of the study: in the col-
lection, analysis, and interpretation of the data; or the
preparation, review, or approval of the manuscript.
Acknowledgment: We thank Xinia Siles, RD, project
director at the Centro Centroamericano de Pobla-
cion, Universidad de Costa Rica, for directing all the
data collection, and Ana Baylin, MD, DrPh, Depart-
ment of Nutrition, Harvard University School of Pub-
lic Health, for data monitoring and management
throughout the study.
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COFFEE, CYP1A2 GENOTYPE, AND RISK OF MYOCARDIAL INFARCTION
©2006 American Medical Association. All rights reserved. (Reprinted) JAMA, March 8, 2006—Vol 295, No. 10 1141
by guest on June 1, 2008 www.jama.comDownloaded from
... We found no difference in variance between groups at D 19 (Levene Test,p>0.05). 17 Since the CYP1A2 enzyme metabolizes caffeine, 18 we explored the association between CYP1A2 gene mutation (rs762551 single nucleotide polymorphism) and caffeinerelated treatment effects on walking speed and endurance at Day 5. Specifically, we compared treatment effects between participants classified as "slow" (C/C and C/A genotypes) and "fast" (A/A genotype) metabolizers 19 to determine if the rate of caffeine metabolism influenced outcomes (Table 1). ...
... That leads to an observed effect size of 0.64 using the change of 10MWT at D 19 from baseline in the C+AIH group with N=10, which is close to the planned effect size of 0.7. A post-hoc power calculation with multivariate T 2 test for the 4-period cross-over design, a sample size of N=10 would be required to have the statistical power of 80% at alpha=0.05 when the effect sizes of change from baseline are estimated to be 0.5 (D 5 ), 0.55 (D 12 ), 0.65 (D 19 ) from the current study, and the correlation between outcomes from different periods is 0.8. A minimum of a 3-week washout yielded intervention arms with baseline 10MWT medians the same across the intervention rounds (Median Test, p=0.638).5 ...
... Participants with CYP1A2*1F A/A alleles (N=3) improved their 10MWT time by 9.8±3.6s versus 2.6±1.1s for C/A heterozygotes at Day 5.Walking endurance also increased after daily C+AIH, but this improvement did not differ from P+AIH at D 5 , D 12 , and D19 . The 6MWT distance improved with C+AIH ...
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Incomplete spinal cord injury (iSCI) often results in lifelong walking impairments that limit functional independence. Thus, treatments that trigger enduring improvement in walking after iSCI are in high demand. Breathing brief episodes of low oxygen (i.e., acute intermittent hypoxia, AIH) enhances breathing and walking function in rodents and humans with chronic iSCI. Pre-clinical studies found that AIH also causes the accumulation of extracellular adenosine that undermines AIH-induced functional plasticity. Pharmacologically blocking adenosine A2a receptors (A2aR) prior to AIH resulted in a dramatic improvement in motor facilitation in rodents with iSCI; however, a similar beneficial effect in humans is unclear. Thus, we conducted a double-blind, placebo-controlled, crossover randomized study to test the hypothesis that a non-selective A2aR antagonist (i.e., caffeine) enhances AIH-induced effects on walking function in people with chronic (>1yr) iSCI. We enrolled twelve participants to receive daily (5 days) caffeine or placebo (4 mg/kg) 30 minutes before breathing 15, 1.5-minute low oxygen (AIH; FIO2=0.10) or SHAM (FIO2=0.21) episodes with 1-minute intervals. We quantified walking function as the change in the 10-meter walk test (speed) and 6-minute walk test (endurance) relative to baseline, on day 5 post-intervention, and on follow-up days 12 and 19. Participants walked faster (day 19; p<0.001) and farther (day 19; p=0.012) after caffeine+AIH and the boost in speed persisted more than placebo+AIH or caffeine+SHAM (day 19; p<0.05). These results support our hypothesis that a caffeine pre-treatment to AIH training shows promise as a strategy to augment walking speed in persons with chronic iSCI.
... Some specific caffeine-metabolizing gene polymorphisms might be related to cardiovascular risks. Several studies have observed that cytochrome oxidase CYP1A2 gene polymorphism could impair the metabolization of caffeine and increase the risk of CVD (El-Sohemy et al. 2007;Palatini et al. 2009). Another study indicated that the association between habitual coffee intake and CVD risk was non-linear. ...
Article
Dietary intake of caffeine has significantly increased in recent years, and beneficial and harmful effects of caffeine have been extensively studied. This paper reviews antioxidant and anti-inflammatory activities of caffeine as well as its protective effects on cardiovascular diseases, obesity, diabetes mellitus, cancers, and neurodegenerative and liver diseases. In addition, we summarize the side effects of long-term or excessive caffeine consumption on sleep, migraine, intraocular pressure, pregnant women, children, and adolescents. The health benefits of caffeine depend on the amount of caffeine intake and the physical condition of consumers. Moderate intake of caffeine helps to prevent and modulate several diseases. However, the long-term or over-consumption of caffeine can lead to addiction, insomnia, migraine, and other side effects. In addition, children, adolescents, pregnant women, and people who are sensitive to caffeine should be recommended to restrict/reduce their intake to avoid potential adverse effects.
... Prolonged caffeine metabolites potentiate stress-related neuronal changes as hyperactivity of intrinsic autonomic ganglia on the heart maintains an electrical activation which can initiate and maintain AF [60] . Persons possessing a slow metabolic profile especially during pregnancy have been shown to have a high prevalence of hypertension and myocardial infarction and so, elevated cardiac markers [61] . Metabolites of caffeine act on specific enzymes in the heart tissues. ...
... A total of 95% of caffeine is metabolized by cytochrome P450 1A2 (CYP1A2) in the liver, which exhibits great individual enzyme variability [264]. Numerous studies showed that different individuals have different degradation capacities and that the risk associated with caffeine consumption, for example, myocardial infarction, varies according to the enzymatic capacity dictated by the genetic profile [265]. A missense mutation of this gene (rs762551) reduces its enzymatic activity, and consequently, carriers of the C-allele, both in homozygosity and heterozygosity, are considered "slow metabolizers". ...
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Increasing evidence on the significance of nutrition in reproduction is emerging from both animal and human studies, suggesting a mutual association between nutrition and female fertility. Different “fertile” dietary patterns have been studied; however, in humans, conflicting results or weak correlations are often reported, probably because of the individual variations in genome, proteome, metabolome, and microbiome and the extent of exposure to different environmental conditions. In this scenario, “precision nutrition”, namely personalized dietary patterns based on deep phenotyping and on metabolomics, microbiome, and nutrigenetics of each case, might be more efficient for infertile patients than applying a generic nutritional approach. In this review, we report on new insights into the nutritional management of infertile patients, discussing the main nutrigenetic, nutrigenomic, and microbiomic aspects that should be investigated to achieve effective personalized nutritional interventions. Specifically, we will focus on the management of low-grade chronic inflammation, which is associated with several infertility-related diseases.
... C-allele carriers are "slow" caffeine metabolizers compared to those with the AA genotype, as evidenced by lower levels of caffeine metabolites such as 1,7-dimethylxanthine and 1,7-dimethyluric after a dose of caffeine [9]. A prospective study of individuals screened for stage 1 hypertension [16] and two case-control studies in myocardial infarction (MI) patients [17,18] suggest that C-allele carriers should limit coffee consumption to less than 1 cup/day or caffeine from other drinks to less than 100 mg/day to avoid being at higher risk of hypertension and myocardial infarction. In contrast, those with the AA genotype are "rapid" caffeine metabolizers and may benefit from consuming 1-4 cups of coffee/day due to increased consumption of phytonutrients presumed to be protective against heart disease. ...
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Metabolic detoxification (detox)—or biotransformation—is a physiological function that removes toxic substances from our body. Genetic variability and dietary factors may affect the function of detox enzymes, thus impacting the body’s sensitivity to toxic substances of endogenous and exogenous origin. From a genetic perspective, most of the current knowledge relies on observational studies in humans or experimental models in vivo and in vitro, with very limited proof of causality and clinical value. This review provides health practitioners with a list of single nucleotide polymorphisms (SNPs) located within genes involved in Phase I and Phase II detoxification reactions, for which evidence of clinical utility does exist. We have selected these SNPs based on their association with interindividual variability of detox metabolism in response to certain nutrients in the context of human clinical trials. In order to facilitate clinical interpretation and usage of these SNPs, we provide, for each of them, a strength of evidence score based on recent guidelines for genotype-based dietary advice. We also present the association of these SNPs with functional biomarkers of detox metabolism in a pragmatic clinical trial, the LIFEHOUSE study.
... Less than half of the population carry the CYP1A2 gene associated with fast metabolism. Some evidence suggest that higher CA intakes increases the risk of insulin resistance [10], high blood pressure [11], and heart attacks [12] in intermediate and slow but not rapid caffeine metabolizers [8] with fast metabolizer seeing greater improvements in athletic performance [13,14] and reduced appetite [15,16]. ...
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Paraxanthine (PXN) is a metabolite of caffeine that has recently been reported to enhance cognition at a dose of 200 mg. Objective: To determine the acute and short-term (7-day) effects of varying doses of PXN on cognitive function and side effects. Methods: In a double blind, placebo-controlled, crossover, and counterbalanced manner, 12 healthy male and female volunteers (22.7 ± 4 years, 165 ± 7 cm, 66.5 ± 11 kg, 24.4 ± 3 kg/m2) ingested 200 mg of a placebo (PLA), 50 mg of PXN (ENFINITY™, Ingenious Ingredients, L.P.) + 150 mg PLA, 100 mg PXN + 100 mg PLA, or 200 mg of PXN. With each treatment experiment, participants completed side effect questionnaires and donated a fasting blood sample. Participants then performed a series of tests assessing cognition, executive function, memory, and reaction time. Participants then ingested one capsule of PLA or PXN treatments. Participants then completed side effects and cognitive function tests after 1, 2, 3, 4, 5, and 6 h of treatment ingestion. Participants continued ingesting one dose of the assigned treatment daily for 6-days and returned to the lab on day 7 to donate a fasting blood sample, assess side effects, and perform cognitive function tests. Participants repeated the experiment while ingesting remaining treatments in a counterbalanced manner after at least a 7-day washout period until all treatments were assessed. Results: The Sternberg Task Test (STT) 4-Letter Length Present Reaction Time tended to differ among groups (p = 0.06). Assessment of mean changes from baseline with 95% CI's revealed several significant differences among treatments in Berg-Wisconsin Card Sorting Correct Responses, Preservative Errors (PEBL), and Preservative Errors (PAR Rules). There was also evidence of significant differences among treatments in the Go/No-Go Task tests in Mean Accuracy as well as several time points of increasing complexity among STT variables. Finally, there was evidence from Psychomotor Vigilance Task Test assessment that response time improved over the series of 20 trials assessed as well as during the 6-h experiment in the PXN treatment. Acute and short-term benefits compared to PLA were seen with each dose studied but more consistent effects appeared to be at 100 mg and 200 mg doses. No significant differences were observed among treatments in clinical chemistry panels or the frequency or severity of reported side effects. Results provide evidence that acute ingestion of 100 mg and 200 mg of PXN may affect some measures of cognition, memory, reasoning, and response time as well as help sustain attention. Additionally, that acute and daily ingestion of PXN for 7 days is not associated with any clinically significant side effects. Conclusions: PXN may serve as an effective nootropic agent at doses as low as 50 mg.
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The current ideal goal of rheumatoid arthritis (RA) management is to resolve joint and systemic inflammation by using pharmacological interventions, assuming this will correspondingly lead to overall well-being. Nonetheless, it has emerged that a substantial number of RA patients do not reach optimal disease control. Thus suggesting the holistic management of subjective symptoms might be overlooked. This poses significant medical challenges; hence the proposal of incorporating lifestyle interventions as part of a multidimensional approach. Among these aspects, both patients and physicians perceive the important role of nutrition. This review shall examine how caffeine, one of the most studied bioactive components of the most widely consumed beverages, may potentially interfere with RA management. In particular, the mechanism by which caffeine affects RA pathogenesis, as a trigger for RA onset or flare, including its influence on rheumatic drug metabolism and the most common RA comorbidities and constitutional symptoms are outlined, highlighting important knowledge gaps and unmet research needs.
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Aims/introduction: The evidence regarding the effects of coffee consumption on incident chronic kidney disease is inconclusive, and no studies have investigated the relationship in patients with diabetes. We aimed to prospectively investigate the relationship between coffee consumption and the decline in estimated glomerular function rate (eGFR) in patients with type 2 diabetes. Materials and methods: A total of 3,805 patients (2,112 men, 1,693 women) with type 2 diabetes (mean age, 64.2 years) and eGFR ≥60 mL/min/1.73 m2 were followed (completion of follow-up, 97.6%; median 5.3 years). Coffee consumption was assessed at baseline. The end point was a decline in eGFR to <60 mL/min/1.73 m2 during the follow-up period. Results: During follow-up, 840 participants experienced a decline in eGFR to <60 mL/min/1.73 m2 . Higher coffee consumption reduced the risk of decline in eGFR. Compared with no coffee consumption, the multivariate-adjusted hazard ratios (95% confidence intervals) were 0.77 (0.63-0.93) for <1 cup per day, 0.76 (0.61-0.94) for 1 cup per day, and 0.76 (0.62-0.92) for ≥2 cups per day (P for trend 0.02). This trend was unaffected by further adjustment for baseline eGFR and albuminuria. The mean eGFR change per year was -2.16 mL/min/1.73 m2 with no coffee consumption, -1.89 mL/min/1.73 m2 with <1 cup per day, -1.80 mL/min/1.73 m2 with 1 cup per day, and -1.78 mL/min/1.73 m2 with ≥2 cups per day (P for trend 0.03). Conclusions: Coffee consumption is significantly associated with a lower risk of decline in eGFR in patients with type 2 diabetes.
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Background The COVID-19 pandemic has exposed the fragility of the global food supply chain, strengthened consumers' awareness of the traceability system throughout the supply chain, and gradually changed consumers' consumption concepts and consumption patterns. Therefore, the aim of this study was to analyse the relevant literature on food safety in the food supply chain, examine its current status, hot spots, and development trends, and provide some suggestions for academics and relevant government departments in food supply chain safety research. Methods We collected the literature on the food safety research of the food supply chain from the Scopus database, used BibExcel to count the subject categories, published journals, geographical distributions, research institutions, authors, and keywords in the literature, and used Pajek software to analyse the keywords in the literature, perform co-occurrence analysis, draw related knowledge maps, and perform cluster analysis on primary keywords. Finally, to study the development trend, we used CorTexT software to illustrate the theme evolution path map in this research field. Results The keyword visualization network revealed the following key research topics: (1) food safety at the consumer end of the food supply chain, (2) food safety management in the food supply chain, (3) risk management of food safety in the food safety chain, and (4) food safety at the production end of the food supply chain. Conclusions After comprehensive discussion and analysis, we concluded that food supply chain management may be a hot topic in the future, especially in traceability management combined with the blockchain. It is necessary to explore in-depth how the blockchain can affect the food supply chain to provide a theoretical basis for managing the latter.
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Whether coffee consumption increases the risk of coronary heart disease has not yet been established. In a case-control study of nonfatal myocardial infarction among Massachusetts women aged 45–69 years in 1986–1990, 858 cases with first infarctions were compared with 858 community controls matched on age and town precinct. Detailed information on coffee drinking, cigarette smoking, and other factors was obtained by telephone interview. Relative risks (as estimated by odds ratios) and their 95% confidence intervals were computed from multiple logistic regression analyses that controlled for smoking and other risk factors. The risk of myocardial infarction increased with increasing number of cups per day among both drinkers of any type of coffee and drinkers of caffeine-containing coffee only: tests for trend, p = 0.002 and p = 0.0004, respectively. For consumption of caffeine-containing coffee alone, the relative risk estimates for 5–6 cups, 7–9 cups, and 10 or more cups per day relative to less than 1 cup per day were 1.4 (95% confidence interval (Cl) 0.8–2.5), 2.1 (95– Cl 0.9–4.9), and 2.5 (95– Cl 1.0–6.5), respectively. No increase was observed for fewer than 5 cups per day. The positive association with heavy coffee drinking was present among nonsmokers as well as smokers. These findings and other recent studies suggest that heavy coffee consumption increases the risk of myocardial infarction. Am J Epidemiol 1995;141:724–31.
Article
Whether coffee consumption increases the risk of coronary heart disease has not yet been established. In a case-control study of nonfatal myocardial infarction among Massachusetts women aged 45-69 years in 1986-1990, 858 cases with first infarctions were compared with 858 community controls matched on age and town precinct. Detailed information on coffee drinking, cigarette smoking, and other factors was obtained by telephone interview. Relative risks (as estimated by odds ratios) and their 95% confidence intervals were computed from multiple logistic regression analyses that controlled for smoking and other risk factors. The risk of myocardial infarction increased with increasing number of cups per day among both drinkers of any type of coffee and drinkers of caffeine-containing coffee only: tests for trend, p = 0.002 and p = 0.0004, respectively. For consumption of caffeine-containing coffee alone, the relative risk estimates for 5-6 cups, 7-9 cups, and 10 or more cups per day relative to less than 1 cup per day were 1.4 (95% confidence interval (CI) 0.8-2.5), 2.1 (95% CI 0.9-4.9), and 2.5 (95% CI 1.0-6.5), respectively. No increase was observed for fewer than 5 cups per day. The positive association with heavy coffee drinking was present among nonsmokers as well as smokers. These findings and other recent studies suggest that heavy coffee consumption increases the risk of myocardial infarction.
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A genetic polymorphism was identified in the 5′-flanking region of human CYP1A2 gene, and its effect on the transcriptional activation of the CYP1A2 gene was investigated. Nucleotide sequence analysis revealed the existence of a point mutation from guanine (wild type) to adenine (mutated type) at position –2964 in the gene. This point mutation was detected by a polymerase chain reaction-restriction fragment length polymorphism method using Ddel or BslI restriction enzyme, and was proven to be genetically inherited. Allele frequency in 116 Japanese subjects showed 0.77 and 0.23 for the wild and mutated types of allele, respectively. The point mutation caused a significant decrease of CYP1A2 activity measured by the rate of caffeine 3-demethylation in Japanese smokers (p<0.05). Gel retardation analysis showed the existence of protein bound to the polymorphic locus. These results suggest that this polymorphism is a causal factor of decreased CYP1A2 inducibility
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Six human cytochrome P450s expressed in HepG2 cells using vaccinia virus cDNA-directed expression, were used to study the biotransformation of caffeine and its metabolites. CYP1A2 alone was responsible for caffeine 3-demethylation and paraxanthine 7-demethylation; in addition, 1A2 catalysed virtually all reactions related to caffeine and its metabolites. The metabolic profile of caffeine biotransformation by CYP1A2 averaged 81.5% for paraxanthine, 10.8% for theobromine and 5.4% for theophylline formation. It remained quite uniform when caffeine concentrations were varied. The most striking finding was that CYP2E1 (the ethanol-inducible form) had major influences upon caffeine metabolism: in particular, it catalysed the formation of theophylline and theobromine from caffeine. Thus, the in vivo metabolite profiling of caffeine may reveal CYP2E1 activities in addition to the previously documented activities of CYP1A2, polymorphic N-acetyltransferase and xanthine oxidase.
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We determined if coffee consumption is associated with an increased risk of developing coronary heart disease. Articles published between 1966 and August 1991 examining a possible link between coffee and coronary heart disease were identified by a computer-aided literature search (Medline) and by standard bibliographic searches. All prospective cohort studies providing data on daily coffee consumption and coronary events (acute myocardial infarction and/or coronary death) were included. Data from each published article were extracted. Additional unpublished data augmenting those published for one study were also included. Each cohort was categorized by reported daily coffee consumption. Incidence of coronary events at each level of coffee consumption was the primary outcome. Eleven prospective studies were included. The coronary events for subjects consuming little or no coffee (less than or equal to 1 cup per day) were compared with event rates for those consuming greater amounts of coffee. The studies exhibited heterogeneity of results. The typical odds ratios and 95% confidence intervals across studies were estimated by logistic regression analysis. Coffee intake from 1 to 4 cups per day was not associated with any increase in coronary heart disease occurrence compared with 1 cup or less per day (odds ratio, 1.01; confidence interval [0.93, 1.11]). The odds ratios for 4 to 6 and 6 cups or more per day compared with up to 1 cup per day were 1.01 (0.90, 1.12) and 1.09 (0.97, 1.22), respectively. There is no association between coffee consumption and the occurrence of coronary heart disease. This conclusion holds in the absence of adjustment for other coronary risk factors.
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Adenosine is known to regulate myocardial and coronary circulatory functions. Adenosine not only dilates coronary vessels, but attenuates beta-adrenergic receptor-mediated increases in myocardial contractility and depresses both sinoatrial and atrioventricular node activities. The effects of adenosine are mediated by two distinct receptors (i.e., A1 and A2 receptors). A1 adenosine receptors, located in atrial and ventricular myocardium and sinoatrial/atrioventricular nodes, are responsible for inhibition of adenylyl cyclase activity. A2 adenosine receptors, located in coronary endothelial and smooth muscle cells, are responsible for stimulation of this enzyme activity. During increased myocardial oxygen demand due to rapid pacing and exercise, although both coronary blood flow and adenosine concentrations in the myocardium and coronary efflux increased, there is no clear consensus explaining its cause and effect relation at present. However, ischemia/reperfusion-induced coronary hyperemia is believed to be mostly attributed to released adenosine, and it has been proven that adenosine attenuates the severity of ischemia due to its coronary vasodilatory action. The beneficial effects of adenosine during ischemia/reperfusion processes do not seem simple. This is because myocardial ischemia and reperfusion injury is caused by 1) activated leukocytes and platelets, 2) ATP depletion and calcium overload of myocardium, and 3) catecholamine release from the presynaptic nerves as well as 4) the impaired coronary circulation. Intriguingly adenosine attenuates all of these deleterious actions and thereby attenuates ischemia/reperfusion injury. Indeed, adenosine attenuates the severity of contractile dysfunction (myocardial stunning) and limits the infarct size. Thus, administration of adenosine or potentiators of adenosine production in the ischemic myocardium may be beneficial for the attenuation of ischemic and reperfusion injuries, although further clinical investigations are necessary.
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It has been realized recently that the primary metabolism of caffeine in humans is catalyzed by P-450IA2 and that the rate of caffeine metabolism can be estimated from a metabolic ratio in a single urine sample. A population of 178 students including 19 smokers were subjected to this caffeine test to establish their P-450IA2 index. Both stated numbers of cigarettes smoked per day and urinary cotinine levels as a confirmatory measure correlated significantly with enzyme activity showing dose-effect relationships (r = 0.62 and 0.89, respectively). Nevertheless, more nonsmokers than smokers had the highest enzyme indexes, suggesting that dietary elements or other factors may determine P-450IA2 activities in populations. Because P-450IA2 is a monooxygenase that may be confined to the liver, caffeine reveals directly the Ah-receptor-dependent enzyme induction only in the liver, but it may also be a signal of induction elsewhere.