Do the omeprazole family compounds exert a protective effect against influenza-like illness?

Abstract

Background
Infections by influenza viruses place a heavy burden on public health and economies worldwide. Although vaccines are the best weapons against influenza, antiviral drugs could offer an opportunity to alleviate the burden of influenza. Since omeprazole family compounds block the “proton pump”, we hypothesized that they could interfere with the mechanism of fusion of the virus envelope and endosomal membrane, thereby hindering the M2 proton pump mechanism of influenza viruses.

Methods
A matched case-control study was performed in 2010-2011 in Italy. Cases were subjects aged over 18 years with a diagnosis of Influenza-like Illness (ILI); 254 case-control pairs were recruited. A multivariable conditional logistic regression analysis was used to assess the association between the prevention of ILI and the administration of omeprazole family compounds. The interaction between omeprazole family compounds and influenza vaccination was also examined.

Results
After control for potential confounders, subjects treated with omeprazole family compounds displayed a lower risk of catching ILI (ORadj = 0.29, 95% CI: 0.15-0.52). The risk of ILI in unvaccinated non-OFC users was about six times than that in vaccinated OFC users.

Conclusions
Although confirmation is necessary, these results suggest that omeprazole family compounds could be profitably used in the prevention of ILI.

Full text

R E S E A R C H A R T I C L E Open Access
Do the omeprazole family compounds exert a
protective effect against influenza-like illness?
Roberto Gasparini
1,2*
, Piero Luigi Lai
1,2
, Francesca Casabona
1
, Cecilia Trucchi
1
, Sara Boccalini
3
, Maria Luisa Cristina
1
,
Stefania Rossi
2,4
, Daniela Amicizia
1,2
and Donatella Panatto
1,2
Abstract
Background: Infections by influenza viruses place a heavy burden on public health and economies worldwide.
Although vaccines are the best weapons against influenza, antiviral drugs could offer an opportunity to alleviate
the burden of influenza. Since omeprazole family compounds block the “proton pump”, we hypothesized that they
could interfere with the mechanism of fusion of the virus envelope and endosomal membrane, thereby hindering
the M2 proton pump mechanism of influenza viruses.
Methods: A matched case-control study was performed in 2010-2011 in Italy. Cases were subjects aged over
18 years with a diagnosis of Influenza-like Illness (ILI); 254 case-control pairs were recruited. A multivariable
conditional logistic regression analysis was used to assess the association between the prevention of ILI and the
administration of omeprazole family compounds. The interaction between omeprazole family compounds and
influenza vaccination was also examined.
Results: After control for potential confounders, subjects treated with omeprazole family compounds displayed a
lower risk of catching ILI (OR
adj
= 0.29, 95% CI: 0.15-0.52). The risk of ILI in unvaccinated non-OFC users was about
six times than that in vaccinated OFC users.
Conclusions: Although confirmation is necessary, these results suggest that omeprazole family compounds could
be profitably used in the prevention of ILI.
Keywords: Influenza-like illness (ILI), Omeprazole family compounds, Epidemiology, Prevention
Background
Infections by influenza viruses place a heavy burden on
public health and economies worldwide. The World
Health Organisation (WHO) has estimated that 1 billion
cases of illness, 3-5 million complicated cases and
300,000 –500,000 deaths occur worldwide every year
[1]. In the United States, more than 200,000 hospitaliza-
tions per year for respiratory and heart conditions have
been attributed to seasonal influenza [2]. In Italy, con-
sidering seasonal epidemic periods alone, it has been
estimated that 25 million cases of Influenza-like Illness
(ILI) occurred from 1999 to 2008, with an average of 2.5
million cases per year [3].
Molinari et al. estimated that, on the basis of the US
population in 2003, annual influenza epidemics resulted
in an average of 610,660 life-years lost, 3.1 million days
of hospitalization and 31.4 million outpatient visits.
These authors also estimated that, of the 31.4 million
outpatient visits, 9.6 and 14.3 million involved subjects
aged 18-64 years and over 65 years, respectively [4].
Vaccines are the principal weapons against influenza.
However, because it takes time to produce an antigeni-
cally appropriate immunogenic vaccine and to deliver it
to populations, especially in the event of a pandemic,
antiviral drugs could offer a good opportunity to allevi-
ate the burden of seasonal and pandemic influenza [5].
To date, there are 4 main anti-influenza medications:
two amantadanes (amantadine and rimantadine) and
two neuroaminidase (NA) inhibitors (oseltamivir and
zanamivir).
* Correspondence: gasparini@unige.it
1
Department of Health Sciences, Genoa University, Genoa, Italy
2
Inter-University Centre for Research on Influenza and other Transmitted
Infections (CIRI-IT), Genoa, Italy
Full list of author information is available at the end of the article
© 2014 Gasparini et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative
Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is properly credited.
Gasparini et al. BMC Infectious Diseases 2014, 14:297
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Amantadine and rimantadine constituted the first gen-
eration of influenza antiviral drugs. At low concentra-
tions, amantadine and rimantadine specifically inhibit
the ion-channel activity of the M2 protein [6]. The use
of M2 inhibitors has been limited by the emergence of
drug-resistant strains of influenza viruses. Although re-
sistant viruses were previously uncommon [7], they have
now become more frequent. Indeed, in a recent study,
Bright et al. observed that, over a decade (1994-2004) of
surveillance, drug resistance significantly increased: from
0.4% in 1994–1995 to 12.3% in 2003–2004 [8].
The WHO has declared oseltamivir phosphate to be
the main anti-influenza medication [9]. However, oselta-
mivir has been linked to a surprisingly high frequency of
drug-resistant strains in children [10].
It is therefore very important to develop alternative
molecules for the prevention and treatment of influenza
[11]. Indeed, other antiviral compounds, such as perami-
vir and lanamivir, are now under development and many
molecules, such as chloroquine, cyanomivir, clarithromy-
cin (CAM), nitric oxide and small interfering RNA
(siRNA), have proved to be active against influenza in-
fection in vitro and/or in animal models [12-16].
The combination of two antivirals or of antivirals with
immunomodulators (for instance with polyriboinosinic
polyribocytidylic acid [Poly ICLC] and Interferon-alpha)
[17] has also been suggested, while Thymosin-alpha 1
has been shown to potentiate the immune-response elic-
ited by contemporary vaccination in humans [18].
Drugs such as omeprazole, lansoprazole and pantopra-
zole selectively and irreversibly inhibit the part of the
“proton pump”that performs the final step in the acid
secretory process [19]. In 2005, Sasaki et al. demon-
strated an anti-Rhinovirus activity of lansoprazole, which
was probably due to an endosomal anti-acidic mechan-
ism [20].
The mechanism of endosomal acidification also plays a
crucial role in the replication of influenza viruses. In-
deed, after the influenza virus is coupled to the cellular
receptor, the virus-receptor complex is incorporated into
the cytoplasm through the mechanism of endocytosis.
As the endosome moves towards the nucleus, its pH de-
creases. This change is takes place through a cellular
channel that pumps protons (H+) into the endosome.
When, the pH inside the endosome reaches 5.0, hemag-
glutinin undergoes a structural rearrangement. This
change allows the exposure of a short peptide that en-
ables the viral envelope to fuse with the membrane of
the endosome. When this happens, the viral nucleic acid
is released into the cytoplasm. The nucleic acid is then
transported to the nucleus of the cell. However, the
RNA cannot enter the nucleus, as this latter is sur-
rounded by the capsid proteins of the shell, such as the
M1 protein. However, at the level of the envelope, the
virus has an abundance of M2 protein, which creates a
channel that actively pumps protons from the endosome
into the virion; the lowering of the pH within the capsid
enables the M1 protein to detach from the viral RNA,
which, once free, can enter the cell nucleus, where repli-
cation can occur [21]. Therefore, hypothetically, by
hindering the M2 ion channel, omeprazole and its deriv-
atives could be useful in the prevention and/or therapy
of Influenza-like Illness (ILI).
In order to evaluate the hypothesized protective action of
Omeprazole Family Compounds (OFC) against Influenza-
like Illness, a matched case-control study was performed.
We chose to conduct this type of study because, in com-
parison with other study designs, a case-control study can
yield important scientific findings at relatively little cost in
terms of time, money and effort [22]. Furthermore, it pro-
vides a basis on which prospective studies can be planned.
Methods
The Ethics Committee of S. Martino Hospital (Genoa,
Italy) approved the study protocol and the written in-
formed consent form (N° 17/2010).
Study design
A matched case-control study was performed during the
2010-11 influenza season in Genoa (Italy). Both cases
and controls were recruited by 4 General Practitioners
(GPs), each of whom has about 1,200 patients aged over
18 years. Cases and controls were matched in a 1:1 ratio
on the basis of gender, age (+/- 3 years) and socio-
economic status (evaluated on the basis of educational
level and the district of residence). Each case and
matched control had the same GP.
Case definition and selection
The potential cases were all subjects who had had at least
one episode of ILI during the study period (December
2010-March 2011). Only subjects who communicated the
disease to their GP were recruited. The case-definition of
ILI was: presence of fever >38°C (100.4°F) and at least one
other systemic symptom (headache, malaise, myalgia,
chills or sweats, retrosternal pain, asthenia) and at least
one respiratory symptom (cough, sore throat, nasal con-
gestion or runny nose) during the study period [23,24].
The exclusion criteria for cases were: refusal to partici-
pate in the study and inability to provide informed
consent.
Control definition and selection
The controls were all subjects who had not had ILI dur-
ing the study period (December 2010-March 2011).
At the moment of recruitment of each case, GP identi-
fied potential control subjects corresponding to match-
ing criteria from among the patients registered in his
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databases. At the end of the study period (31 March
2011) controls were entered into the study by randomly
selecting each control from within the group of potential
candidates identified at the time of recruitment of the
cases. Each GP then contacted the chosen control by
telephone in order to ascertain that he/she had not had
ILI during the study period. To minimize the possibility
of enlisting a false negative control, the GP read the def-
inition of ILI and provided any information necessary. In
the event of refusal to participate (no signed informed
consent), the GP excluded the subject and contacted the
next subject on the list of potential controls.
Study period (recruitment)
The diagnosis of ILI was based on clinical definition. In
order to improve the specificity of diagnoses, the study
period was therefore limited to the weeks of the influenza
peak (December 2010-March 2011) according to the
Italian Influenza Surveillance Network (INFLUNET) [25].
Data collection
All GPs and researchers who carried out the study
strictly complied with Italian regulations on privacy [26].
GPs administered an ad hoc written questionnaire to
both cases and controls. The questionnaire was adminis-
tered either by telephone or by face-to-face interview,
after written informed consent had been obtained. The
following data were recorded: personal habits (smoking,
alcohol consumption [more than 2 glasses of wine or
more than one glass of spirits a day]) and the presence
of underlying diseases, which were classified in accord-
ance with the International Statistical Classification
of Diseases and Related Health Problems (ICD-10)
[27]. Specifically, cardiovascular diseases (ICD-10 codes:
I00-I02; I05-I09; I20-I99), hypertension (ICD-10 codes:
I10 –I15), respiratory diseases (ICD-10 codes: J00 –J99
excluding J09 –J18), kidney diseases (ICD-10 codes:
N00 –N99), diabetes (ICD-10 codes: E10-E14), cancer
(ICD-10 codes: C00-D48), dyslipidemia (ICD-10 code:
E78), gastric ulcer (ICD-10 code: K-25) and gastric dis-
eases (ICD-10 codes K-21; K28-K31) were recorded. Fur-
thermore, GPs collected data on influenza vaccination
and therapy with OFC (omeprazole, esomeprazole,
lansoprazole, pantoprazole, rabeprazole), fibrates (bezafi-
brate, ciprofibrate, clofibrate, gemfibrozil, etc), statins
(atorvastatin, fluvastatin, lovastatin, simvastatin, etc) and
antibiotics. OFC were administered at a dosage of
20-40 mg/day for a period of at least 2 weeks before en-
rolment, and this therapy was continued for at least
8 weeks. With regard to fibrates, these had to be as-
sumed by at least 30 days before the moment of enrol-
ment; Gemfibrozil, for instance, was administered at a
dosage of between 900 and 1200 mg/day, preferably
1200 mg, and was continued for long periods of time.
Finally, with regard to statins, these also had to be
assumed by at least 30 days before the moment of enrol-
ment. As an example of the dosage of statins, atorva-
statin was administered at dosages of 10-80 mg/day for
long periods.
All data collected from questionnaires regarding the
anamnesis, therapy and vaccination status were verified
by patients’electronic records.
Statistical analysis
The characteristics of the study population are reported
as means and standard deviation (SD) for continuous
variables and as proportions for categorical variables.
Differences between cases and controls were analysed by
means of McNemar’s test for matched case-control stud-
ies (two-tailed p-value).
A multivariable conditional logistic regression model
was used to evaluate the effectiveness of OFC use pre-
liminarily and to estimate the adjusted odds ratio and its
95% Confidence Interval (CI). In the model, the binary
variables “ILI”and “OFC”were designated as the “out-
come”and “main exposure”, respectively. The decision
regarding which factors to include in the multivariable
model was based on a conceptual framework describing
the hierarchical relationships [28] between exposures
(Table 1), with the interaction term (OFC & Influenza
vaccination) being entered at a separate level. The re-
sults of the interaction analyses are presented both as
the separate effects of the two exposures and as their
joint effects (Table 2). In accordance with the general
consensus in the epidemiological community [29,30], we
presented the interaction effects on the additive scale, as
this approach is the most appropriate for public health
purposes. To calculate the measure of interaction, the
two exposures “OFC”and “Influenza vaccination”,as
preventive factors, were recoded “in such a way that the
stratum with the lowest risk, when both factors are con-
sidered jointly, becomes the reference category”[31].
The measure of interaction RERI (Relative Excess
Risk due to Interaction) was then calculated (Table 2)
in order to examine the presence of interaction by
using measurements derived from the logistic regression
[31-34]. In order to estimate all three ORs that are
needed to assess biological interaction, the model was
set up in such a way as to include terms for three of the
four possible combinations of exposure, while the fourth
category served as a reference category.
Analyses were performed by means of SPSS vers.16.0
for Windows, EpiInfo vers. 3.5.3, Graph-Pad software
and an Excel sheet available at: www.epinet.se for the
assessment of biological interaction. The coefficients es-
timated by the conditional logistic regression were ob-
tained by using the procedure of SPSS COXREGR; this
is equivalent to the conditional logistic regression when
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there is only one case and one or more controls in each
layer.
Results
In the Liguria Region, influenza activity was moderate in
the 2010-2011 season. The influenza epidemic began in
the 50
th
week of 2010 and lasted until the 10
th
week
of 2011. The predominant circulating influenza virus
was A/California/07/09
pdm
(67%), followed by B virus
(B/Brisbane/60/2008) (23.5%) and A/H3N2 (A/Perth/16/
2009) (9.3%). In the 2010-2011 season there was
optimal matching between circulating viruses and vac-
cine strains. No drifted influenza strains were isolated in
the Genoa district.
Nine cases and 12 controls refused to participate in
the study.
A total of 508 subjects (256 males and 252 females)
were recruited: mean age 51.4 (SD = 14.5) years (males
51.7 (SD = 14.6); females 51.1 (SD = 14.3)); median age
49; interquartile range (IR) 42-61 years; range 29-94
years. The mean age (SD) of cases and controls was 51.3
(SD = 14.5) and 51.6 (SD = 14.5), respectively.
Table 3 shows the main characteristics of the cases
and controls, broken down by demographic characteris-
tics, lifestyle habits, underlying pathologies, drug use
and influenza vaccination status. Cases and controls had
similar lifestyle habits. Cardiovascular diseases, dyslipi-
daemia and gastric ulcers were significantly more com-
mon among controls than among cases. Furthermore,
more controls than cases took fibrates (p= 0.046) and
statins (p< 0.0001). Regarding OFC use, these drugs
were taken by 7.5% of cases and 28.7% of controls
(p< 0.0001). Only 25.6% of the subjects studied had
received the influenza vaccine, the frequency of vaccin-
ation being significantly higher among controls (44/254
cases, 17.3%; 86/254 controls, 33.9%, p< 0.0001).
Table 4 shows the results of the multivariable analysis
(hierarchical approach), which was carried out in order
to examine the overall contribution of demographic and
lifestyle variables and underlying pathologies (Level 1),
drug use (Level 2) and influenza vaccination status
(Level 3) and the interactive effects of OFC and influ-
enza vaccination in predicting ILI.
The use of OFC was associated with a lower probability
of ILI (OR
adj
= 0.31; 95% CI: 0.13-0.76), after controlling for
demographic and lifestyle variables, underlying pathologies
and the use of other drugs (p< 0.001; Level 2). The associ-
ation was very similar after adjustment for influenza vaccin-
ation status (OFC OR
adj
= 0.29; 95% CI: 0.15-0.52, Level 3).
The results of the analyses of the interaction between
Omeprazole compounds (exposure of interest) and
Influenza Vaccination on the risk of ILI are showed
in Table 2, which reports the separate effect of each ex-
posure and their joint effects; this approach enables the
Table 1 Hierarchical theoretical model of potential
proactive action of the omeprazole family compounds
against influenza viruses
First Level
Demographic
characteristics
Lifestyle
habits
Underlying
Pathologies
Aged 65 + Smoking Cardiovascular diseases
Drinking Hypertension
Respiratory diseases
Diabetes
Cancer
Kidney diseases
Dyslipidaemia
Gastric ulcer
Gastric diseases
Second Level
Drugs taken
Fibrates
Statins
Antibiotics
Omeprazole Family Compounds (OFC)
Third Level
Vaccination status
Influenza vaccination
Outcome
Influenza-Like Illness (ILI)
Table 2 Separate and joint effects of the preventive
exposures “Influenza vaccination”and “OFC”on the risk
of ILI after recoding and results of analyses of interaction
Odds Ratios representing separate effects OR (95% CI)
Non-OFC users 4.38 (2.54 –7.53)
Users of OFC 1 (reference category)
Not Vaccinated 3.8 (2.15 –6.71)
Vaccinated 1 (reference category)
Odds Ratios representing joint effects
OR11 non-OFC users and unvaccinated 5.75 (2.71 –12.22)*
OR10 non-OFC users but vaccinated 1.48 (0.64 –3.40)
OR01 users of OFC but unvaccinated 0.92 (0.33 –2.53)
OR00 users of OFC and vaccinated 1 (reference category)
Measure of effect of interaction
on additive scale
RERI 4.34 (1.46 - 7.26)
*Observed OR= 5.75, while expected OR in the absence of interaction on an
additive scale was 1.40, calculated as [(1.48 –1)+ ( 0.92 –1) + 1], where 1.48 = OR
non-OFC users but vaccinated and 0.92= OR users of OFC but unvaccinated.
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presence of interaction to be evaluated on both an addi-
tive and a multiplicative scale. A measure of interaction
on the additive scale, RERI (Relative Excess Risk due to
Interaction), was used to assess whether there was syner-
gism between the two exposures. RERI >0 implies such
synergism. In our analysis, we found RERI = 4.34; this
means that, owing to the presence of interaction, the ILI
risk for unvaccinated non-OFC users was higher than
would be expected in the absence of interaction on an
additive scale (observed: OR = 5.75 vs. expected: OR =
1.40, obtained by OR for non-OFC users but vaccinated
and OR for users of OFC but unvaccinated, see Table 2),
and that the test for interaction was statistically signifi-
cant (RERI = 4.34; 95% CI: 1.46–7.26). Thus, there were
interesting indications of a joint effect, but this needs to
be confirmed in future ad hoc studies.
Discussion
Although influenza vaccines provide a “suboptimal”rate
of protection, they are the best means of avoiding
influenza infection. However, in terms of both preven-
tion and treatment, antivirals could be a complementary
means of fighting the disease and mitigating its conse-
quences. For this reason, numerous studies have been
aimed at obtaining efficacious antiviral molecules. In
particular, compounds of the amantadane group and
the anti-neurominidase drugs have been studied and li-
censed for human use.
Moreover, other types of treatment are being sought.
An innovative approach might be to use omeprazole
family compounds as a preventive measure or as a cura-
tive treatment for influenza disease. Because of the
mechanism of action of these molecules, their effect on
rhinoviruses and other types of viral infection has been
studied [20,35].
The results of the present study seem to confirm our
hypothesis that treatment with omeprazole or similar
molecules can prevent ILI. Indeed, on the basis of the
results of multivariable conditional logistic regression,
after control for potential confounders, the subjects
Table 3 Main characteristics of cases and controls, broken down by demographic features, lifestyle habits, underlying
pathologies, drug use and influenza vaccination status
VARIABLES Cases (n = 254) Controls (n = 254) p-value
*
Demographic features and lifestyle habits
Aged 65 yrs or more
^
53 (20.9%) 50 (19.7%) 0.45
Smoking
§
37 (14.6%) 45 (17.7%) 0.40
Drinking
†§
23 (9.1%) 13 (5.1%) 0.12
Underlying Pathologies
Cardiovascular diseases
§
14 (5.5%) 38 (15.0%) 0.0004
Hypertension
§
56 (22.0%) 53 (20.9%) 0.80
Respiratory diseases
§
21 (8.3%) 21 (8.3%) 0.87
Diabetes
§
9 (3.5%) 19 (7.5%) 0.06
Cancer
§
3 (1.2%) 5 (2.0%) 0.72
Kidney diseases
§
7 (2.8%) 8 (3.1%) 1.00
Dyslipidemia
§
9 (3.5%) 45 (17.7%) <0.0001
Gastric ulcer
§
5 (2.0%) 29 (11.4%) <0.0001
Gastric diseases
§ǂ
5 (2.0%) 14 (5.5%) 0.07
Drugs taken
Fibrates
§
1 (0.4%) 8 (3.1%) 0.046
**
Statins
§
9 (3.5%) 44 (17.3%) <0.0001
Antibiotics
§
8 (3.1%) 5 (2.0%) 0.58
Omeprazole family compounds
§
19 (7.5%) 73 (28.7%) <0.0001
Vaccination status
Influenza vaccination
§
44 (17.3%) 86 (33.9%) <0.0001
^
Reference: Less than 65 yrs.
†
Reference: More than 2 glasses of wine or more than one glass of spirits a day.
§
Reference: NO.
ǂ
Except Gastric ulcer.
*Two-tailed p-value (McNemar’s test for matched case-control studies).
**According to conventional criteria, this difference is considered to be statistically significant.
The statistical significant p values are reported in bold.
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treated with omeprazole family drugs displayed a lower
risk of catching ILI. Specifically, this risk (OR
adj
= 0.29,
95% CI: 0.15-0.52) was about two-thirds lower than that
of subjects not treated with OFC. We also evaluated the
joint effects of the absence of influenza vaccination and
OFC treatment, and found that the risk of ILI in unvac-
cinated non-OFC users was about six times than that in
vaccinated OFC users (Table 2).
Our study appears to confirm the hypothesis that, by
blockading the acidification of the cell environment, the
omeprazole family compounds may interfere with the
mechanism of fusion of the virus envelope and endoso-
mal membrane. More specifically, it is possible tenta-
tively to offer an explanation of the mechanism of action
of OFC in protecting against influenza infection. Indeed,
OFC specifically and irreversibly inhibit the H+/K + -ATPase
proton pump. Furthermore, like other molecules, such as
N-ethylmaleimide (NEM), OFC inhibit ATP synthase, thus
modifying Cys residues [36]. This would result in the
block of the proton pump in a centripetal direction, too.
Consequently, the mechanism of acidification may be
inhibited in different cellular compartments, including
mitochondria and endosomes. All this could reduce the ef-
ficiency of the M2 proton pump of influenza viruses,
which is mediated by a small integral membrane protein
(A/M2 and B/M2 for influenza A and B viruses, respect-
ively) [37]. Our hypothesis is supported by the results ob-
tained by Sasaki et al. (2005), who studied the inhibition of
Rhinovirus infection in cultured human tracheal epithelial
cells treated with lansoprazole. The entry of RNA of type
14 Rhinovirus into the cytoplasm of infected cells is
thought to be mediated by the destabilization of receptor
Table 4 Odds Ratios for ILI occurrence in the study population in the 2010/11 influenza season as a function of
demographic features, lifestyle, underlying diseases and drug use, n = 508 (Multivariable analysis –Hierarchical
approach)
Multivariable analysis
Variables Adjusted OR
§
95% CI pAdjusted OR
§
95% CI pAdjusted OR
§
95% CI p
Level 1 Level 2 Level 3
Demographic features and
lifestyle habits
Aged 65 yrs or more* 1.94 0.24;15.6 0.53
Smoking** 0.64 0.37;1.14 0.13
Drinking**
#
3.04 1.22;7.59 0.02 2.17 0.87;5.51 0.09
^
2.10 0.87;4.94 0.10
Underlying pathologies
Cardiovascular diseases** 0.34 0.14;0.83 0.02 0.56 0.22;1.39 0.21
Hypertension** 1.26 0.68;2.35 0.47
Respiratory diseases** 1.64 0.73;3.71 0.23
Diabetes** 0.96 0.29;3.17 0.94
Cancer** 1.08 0.15;7.93 0.94
Kidney diseases** 0.61 0.14;2.71 0.51
Dyslipidaemia** 0.17 0.07;0.42 0.0001 0.12 1.56 0.20
Gastric ulcer** 0.20 0.07;0.54 0.002 1.18 0.31;4.57 0.82
Gastric diseases**° 0.38 0.13;1.12 0.08
^
1.18 0.30;4.57 0.81
Drugs taken
Fibrates** 0.08 0.05;1.41 0.09
^
0.03 0.01;0.50 0.02
Statins** 0.28 0.07;1.15 0.08
^
0.15 0.05;0.43 <0.001
Antibiotics** 1.75 0.53;5.79 0.36
Omeprazole family compounds** 0.31 0.13;0.76 0.01 0.29 0.15;0.52 <0.001
Vaccination status
Influenza vaccination** 0.31 0.16;0.58 <0.001
§
Conditional logistic regression models.
^
As several variables were included in each level, only those variables reaching p <0.1 were kept in the next step, in order to avoid unstable estimates in
subsequent models.
*
Reference: Less than 65 yrs.
**
Reference: NO.
#
Reference: More than 2 glasses of wine or more than one glass of spirits a day.
°Except Gastric ulcer.
The statistical significant p values are reported in bold.
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binding and by endosomal acidification [20]. Sasaki et al.
found that lansoprazole reduced the fluorescence intensity
of acidic endosomes in the cells and decreased the titres of
Rhinoviruses and their RNA in the supernatant cell cul-
ture medium [20]. Moreover, the drug reduced cytokine
concentrations, including that of interleukin-1beta, and
consequently their proinflammatory effect. Finally, lanso-
prazole has been seen to reduce the expression of the inter-
cellular Rhinovirus adhesion molecule-1 (ICAM-1) [38].
Nevertheless, our results are in partial contrast with
those obtained by Laheij et al. [39], who found an in-
creased risk of pneumonia in patients treated with
omeprazole family molecules. However, the authors
themselves admitted that various types of bias could
have influenced their results, such as errors of classi-
fication (e.g. mild cases of pneumonia were neither
confirmed radiologically nor microbiologically) or uncer-
tainties regarding exposure to the drug. Finally, Laheij
et al. [39] commented that the increased risk of pneu-
monia was very probably related to an increased suscep-
tibility to bacterial infections, with colonization of the
oral space occurring via the stomach.
Regarding underlying pathologies, our analysis showed
that respiratory and cardiovascular diseases were not as-
sociated with a higher risk of catching ILI (Table 4),
whereas it is well known that these underlying patholo-
gies are associated with a higher risk of hospitalization
for influenza and pneumonia. The fact that respiratory
and cardiovascular diseases were more frequent in con-
trols than in cases can probably be explained by the fact
that patients with these disorders are among those for
whom influenza vaccination is particularly recommended.
Furthermore, dyslipidemia and gastric diseases seemed
to reduce the risk of ILI. The possible explanation for
this “paradox”could be that subjects with gastric dis-
eases regularly take OFC, and these drugs displayed a
protective effect against ILI. In addition, subjects with
dyslipidemia regularly take statins or fibrates, which dis-
played potential protection against ILI (OR
adj
0.15; 95%
CI: 0.05-0.43). This finding is consistent with the results
of other authors, who have found a protective role of
these molecules (statins) with regard to hospitalization
for influenza complications, such as pneumonia, in dia-
betic patients [40]. However, we almost always consid-
ered only uncomplicated cases of ILI.
Regarding the limitations of present study, it is well
known that case-control studies are susceptible to vari-
ous types of bias. Although we tried to minimize any
such biases, it is possible that there may have been mis-
classifications regarding the diagnosis of ILI in both
cases and controls. However, in order to minimize this
possibility with regard to cases, we performed our study
during the peak influenza period, and the criteria of case
definition were rigorously applied by GPs. Misclassification
among controls was minimized by rigorously explaining
the definition of ILI to the subjects. Moreover, the risk of
information bias regarding drug use was low, as the GPs
scrupulously recorded their patients’therapies in elec-
tronic files.
In addition, in order to minimize any selection bias,
controls were matched to cases on the basis of age, sex
and socio-economic status. Indeed, controls and cases
were randomly selected from among the same GPs’lists.
Consequently, as they lived in the same area of the city,
their socio-economic status was fairly similar.
Finally, to minimize the possibility of any confounding
bias, we considered a large number of variables, such as
the presence of underlying diseases, and analysed our
data by means of multivariate conditional analysis.
Conclusions
Although further confirmation is necessary, it may be
concluded that omeprazole molecules could be profit-
ably used in the prevention and, perhaps, treatment of
ILI. This latter application could be particularly useful in
complicated forms of the disease, the treatment of which
might also involve combination with other antiviral and/
or antibiotic drugs.
Our findings could prompt the planning of clinical tri-
als aimed at establishing the best protocol of preventive
or/and therapeutic treatment with OFC (dosage, timing,
contraindications, side effects, etc.).
To confirm these results, our research group has planned
a prospective study for the 2013-2014 influenza season,
possibly involving viral confirmation of influenza in the
laboratory.
Abbreviations
ILI: Influenza-like Illness; OR: Odds Ratio; OR
adj
: Odds Ratio adjusted;
CI: Confidence Interval; WHO: World Health Organization; NA: Neuroaminidase;
CAM: Clarithromycin; siRNA: Small interfering RNA; Poly ICLC: Polyriboinosinic
polyribocytidylic acid; OFC: Omeprazole Family Compounds; GPs: General
Practitioners; INFLUNET: Italian Influenza Surveillance Network; SD: Standard
Deviation; RERI: Relative Excess Risk due to Interaction; NEM: N-ethylmaleimide.
Competing interests
The authors declare that they have no competing interests.
Authors’contributions
RG conceived, designed and coordinated the research. PLL, FC, CT, SB, MLC
and DA collected data. PLL, FC, CT SB and MLC performed the data quality
control. PLL and SR optimized the informatics database. RG, PLL, SR and DP
performed the statistical analyses. RG, PLL, SR, DA and DP evaluated the
results. RG, DA, SR and DP wrote the manuscript. All Authors revised the
manuscript and gave their contribution to improve the paper. All authors
read and approved the final manuscript.
Acknowledgements
The study was supported by Department Health Sciences –University of
Genoa (Italy).
The authors thank: Dr. Paolo Montarsolo, Dr. Giovanni Filippo Bignone,
Dr. Enza Bruscolini and Dr. Riccardo Masserano for their support in data
collection.
The authors thank Dr. Luca Berisso for data entry in the data-base.
The authors thank Dr. Bernard Patrick for revising the manuscript.
Gasparini et al. BMC Infectious Diseases 2014, 14:297 Page 7 of 8
http://www.biomedcentral.com/1471-2334/14/297

Author details
1
Department of Health Sciences, Genoa University, Genoa, Italy.
2
Inter-University Centre for Research on Influenza and other Transmitted
Infections (CIRI-IT), Genoa, Italy.
3
Department of Health Sciences, Florence
University, Firenze, Italy.
4
Department of Molecular and Developmental
Medicine, Siena University, Siena, Italy.
Received: 11 March 2013 Accepted: 28 May 2014
Published: 2 June 2014
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doi:10.1186/1471-2334-14-297
Cite this article as: Gasparini et al.:Do the omeprazole family
compounds exert a protective effect against influenza-like illness? BMC
Infectious Diseases 2014 14:297.
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