In addition, exposure to secondhand smoke increases a person's risk of disease and death. Smoking is also associated with many other non-fatal diseases and problems, including osteoporosis, skin wrinkling, peptic ulcer disease, impotence, and pregnancy complications.

Even smoking a small amount, such as one cigarette a day, is associated with increased health risks. Quitting and staying smoke-free can be a challenge, but many people have done it successfully.

This topic review discusses the benefits of stopping smoking and approaches that can help you succeed. BENEFITS OF QUITTING SMOKING. Quitting smoking has significant and immediate health benefits for men and women of all ages.

The sooner you quit, the greater the benefits. People who quit smoking before age 50 reduce their risk of dying over the next 15 years by one-half, as compared with those who continue to smoke. Reducing your risk of disease. Cardiovascular disease — Cigarette smoking doubles a person's risk of developing coronary heart disease, a condition that can lead to a heart attack.

Quitting smoking can rapidly reduce this risk. One year after stopping smoking, the risk of dying from coronary heart disease is reduced by about one-half and continues to decline over time. Smoking also increases the risk of stroke and peripheral artery disease a condition in which the blood vessels that carry blood to the legs are blocked or narrowed, causing leg pain.

These risks also decrease after a person quits smoking. See "Patient education: Heart attack Beyond the Basics " and "Patient education: Stroke symptoms and diagnosis Beyond the Basics " and "Patient education: Peripheral artery disease and claudication Beyond the Basics ". Lung disease — Smoking increases the risk of long-term lung diseases such as chronic obstructive pulmonary disease.

While much of the lung damage caused by smoking is not reversible, stopping smoking can reduce further damage to the lungs, and many smokers with a chronic cough and sputum phlegm coughed up from the lungs notice an improvement in these symptoms during the first year after they stop smoking.

See "Patient education: Chronic obstructive pulmonary disease COPD Beyond the Basics ". Smoking is also associated with an increased risk of asthma, and asthma is more difficult to treat in people who smoke. Cancer — Cigarette smoking is responsible for almost 90 percent of cases of lung cancer. Quitting smoking reduces the risk of lung cancer within five years of stopping, although former smokers still have a higher risk of lung cancer than people who have never smoked.

See "Patient education: Lung cancer risks, symptoms, and diagnosis Beyond the Basics ". Stopping smoking may also reduce the risk of other cancers, such as cancers of the head and neck, esophagus, pancreas, and bladder.

Stopping smoking is beneficial even after one of these cancers is diagnosed, since it reduces the risk of getting a second cancer and may improve the chance of survival from the first cancer.

Peptic ulcer disease — Cigarette smoking increases the risk of developing peptic ulcer disease. Quitting smoking decreases that risk and increases the rate of ulcer healing, if ulcers have developed.

See "Patient education: Peptic ulcer disease Beyond the Basics ". Osteoporosis — Smoking increases bone loss and increases the risk of hip fracture in women. Stopping smoking begins to reverse this risk after about 10 years.

Increased bone loss has also been noted in men who smoke, although it is not clear how much a man's risk of fracture is increased by smoking.

See "Patient education: Bone density testing Beyond the Basics ". Other diseases — Smoking also causes or contributes to many other conditions, including type 2 diabetes, sexual problems eg, erectile dysfunction in men , problems with the teeth or gums, and certain infections.

Quitting smoking can reduce your risk of developing these problems. Reducing your family and friends' risk of disease — Quitting smoking will also benefit your family and other people who spend time with you, since exposure to secondhand cigarette smoke is associated with a number of serious health conditions.

Adults who are exposed to secondhand smoke have an increased risk of lung cancer, coronary heart disease, and stroke. Women who smoke during pregnancy have an increased risk of complications including preterm labor, miscarriage, and stillbirth. Their babies are also more likely to be underweight at birth.

PREPARING TO QUIT. Smoking is recognized as a chronic addictive disease, and for some but not all smokers it can be extremely challenging to quit. People can differ greatly in the way in which they smoke, their success in quitting, symptoms they have when trying to quit, and factors that may lead to relapse.

Many people try to quit on their own, without any help from medications or other supports. The success rate in this situation is much lower. If you tried to quit on your own without success, seeking help the next time you try to quit can make the difference. Once you decide to quit smoking, the first step is usually to set a quit date.

This is the day when you will completely quit smoking. Ideally, this date should be in the next two weeks, although some people choose a special date that is significant to them eg, a birthday, anniversary, or holiday.

Many doctors recommend stopping smoking all at once on your quit date. However, some people prefer to gradually reduce the number of cigarettes they smoke prior to the quit date.

Once you have set your quit date, there are things you can do to help you prepare. It can help to:. Changing behaviors and taking a medication are the two main methods of quitting smoking. Using both methods together increases your chances of successfully quitting.

What worked? What did not work? What contributed to relapse? Is there anything you have learned that you can do differently this time to be more successful?

Other symptoms are more general and often not recognized as related to nicotine withdrawal. These include anxiety, difficulty sleeping, irritability, difficulty concentrating, restlessness, frustration or anger, and depression. These symptoms are reduced and more tolerable if you use a stop-smoking medication.

These include over-the-counter medications, like nicotine patches, gum, or lozenges, or prescription medications like varenicline or bupropion. See 'Medications for quitting' below. Withdrawal symptoms usually become manageable within a few weeks of stopping smoking completely.

Symptoms generally peak in the first three days and decrease over the next three to four weeks, so keep in mind that it will get easier. Symptoms vary in intensity but are generally stronger in heavier smokers.

Examples include having other smokers in the household or workplace, stressful situations, and drinking alcohol. If you are in the habit of smoking during the work day, it might be easier to quit during a vacation from work. If you live with someone else who smokes, consider asking that person not to smoke in the house or car to help you succeed in becoming smoke-free.

Cravings may be brought on by situations associated with smoking, by stress, or by drinking alcohol. These cravings are a common reason people relapse after quitting. It is important to remember that a craving will typically go away in a few minutes if you distract yourself by doing something else for a few minutes.

Weight gain may occur because people tend to eat more after quitting. Typically, people gain two to five pounds in the first two weeks, followed by an additional four to seven pounds over the next four to five months.

The average total weight gain is 8 to 10 pounds. While this can be frustrating, it can help to keep in mind that the benefits of quitting smoking are much greater than the risks associated with gaining weight.

See "Patient education: Exercise Beyond the Basics ". You can make changes in your daily behavior to help you quit smoking on your own; some people also choose to participate in individual or group support sessions see 'In-person support' below.

Combining behavioral changes with a medication increases your chances of quitting successfully. After identifying these situations, you may need to develop new coping skills. This may include one or more of the following:.

Vigorous exercise can enhance the ability to stop smoking and avoid relapse and also helps to minimize or avoid weight gain. People who live with smokers can consider negotiating with them to stop smoking at home or in the car.

Cravings can be prevented to some degree by avoiding situations associated with smoking, by minimizing stress, and by avoiding alcohol. Cravings will subside. Keep oral substitutes such as sugarless gum, carrots, sunflower seeds, etc handy for when cravings develop.

These can easily be found online, by calling a smokers' quitline, or by talking with a health care provider or counselor. Support groups can be helpful. Some medical centers have patient resources or learning centers with self-help materials. See 'Where to get more information' below. Support — Having consistent support is extremely helpful in quitting smoking and staying off cigarettes.

Support can come from family and friends, a health care provider, a counselor, a telephone hotline in the United States, QUIT-NOW , a text messaging program in the United States, sign up at www.

In addition to getting ongoing encouragement, it is important to have someone you can talk to about any problems you have while trying to quit, such as weight gain, lack of support from family and friends, or prolonged withdrawal symptoms. In-person support — Some people find it helpful to talk with a "coach" who can help support you throughout the process.

This often involves regular visits beginning before your quit date and continuing for several months afterwards.

Group counseling sessions are another option; many different organizations offer group programs. These typically include lectures, group meetings for mutual support, discussion of coping skills, and suggestions for preventing relapse.

Hypnosis and acupuncture — Hypnosis and acupuncture are popular stop-smoking methods. Although there is not convincing scientific evidence that these are effective, some people who have not had success with other techniques find these treatments to be helpful.

There are several medications that can help you stop smoking; in the United States, some of these are available without a prescription while others require a prescription. Effective medications include nicotine gum, patches, or lozenges available over the counter and the prescription medications varenicline brand name: Chantix and bupropion brand names: Zyban, Wellbutrin.

Nicotine replacement therapy — Nicotine is the substance in cigarettes that makes them addictive. When nicotine levels fall, most smokers develop withdrawal symptoms. These include irritability, frustration, anger, anxiety, difficulty concentrating, restlessness, depression, difficulty falling or staying asleep, and nicotine craving.

Nicotine replacement therapy is designed to reduce the intensity of withdrawal symptoms after you quit. However, while it can make it easier to quit, it will not prevent symptoms completely. Nicotine is available in several forms as a gum or lozenge, a patch, a nasal spray, or an inhaler.

All appear similarly effective, although different people may find that they prefer one form over another. Using more than one form of nicotine replacement therapy in combination is more effective than using one form alone.

Generally, a smoker will use a nicotine patch to provide a constant level of nicotine and add the nicotine gum or lozenge or inhaler or nasal spray as needed to control cigarette cravings. Skin patches — Nicotine patches deliver nicotine to the blood through a skin patch.

Several doses are available. People who smoke less might choose a lower-dose 14 mg patch. Patches reduce your withdrawal symptoms but do not eliminate them.

The combination of an intensive behavioral program and nicotine patches can double your chances of quitting. See 'Behavioral changes to help you quit' above.

It is generally recommended that you wear the patch for at least 12 weeks. Some brands of patch include a tapering of the dose over the last few weeks of use. For example, one strategy is to switch to a lower-dose patch after six or eight weeks.

Using the patch for longer than 12 weeks is associated with more success in quitting, and using the patch for as long as needed is generally recommended. Some people who use the patch at night have trouble with insomnia or vivid dreams. On the other hand, wearing the patch at night may help prevent difficult early morning withdrawal symptoms.

If you have bothersome sleep-related symptoms, one approach is to remove the patch at night and put on a new one in the morning. You can also use another form of nicotine replacement therapy such as gum the first thing in the morning before your new patch takes effect.

Gum — Nicotine gum contains nicotine that is slowly released as you chew. Gum is available in two doses, 4 mg for people who smoke their first cigarette within 30 minutes after getting up and 2 mg for people who smoke their first cigarette after being awake for 30 minutes or longer.

You can use up to 24 pieces of nicotine gum per day. While the gum does not prevent withdrawal symptoms, it may reduce the intensity of symptoms.

A very small percentage of people who quit smoking become chronic gum users; however, using the gum long-term is far less risky than smoking. When used with an intensive behavioral program, nicotine gum can double your chances of successfully quitting see 'Behavioral changes to help you quit' above.

Without a behavioral program, your chances of quitting are likely to be lower. Gum use is generally recommended for three to six months. Nicotine gum is meant to be chewed differently than regular chewing gum.

To be effective, the nicotine must be absorbed through your cheek or gums. If you chew too quickly, the nicotine will instead be swallowed, which can cause an upset stomach and is not very effective for relieving withdrawal symptoms.

To be absorbed well, you will need to chew the gum just enough to feel the nicotine being released; this feels like a tingling sensation.

Then, hold or "park" the gum inside your cheek until the tingling goes away. Repeat this cycle chewing the gum again until you feel tingling, then holding it in your cheek for 30 minutes, and then remove and dispose of the gum.

It is better to avoid drinking coffee, sodas, or orange juice while chewing the gum or for 15 minutes beforehand. These drinks make your saliva acidic, which limits nicotine absorption. in the press. Thompson, J. Article CAS Google Scholar. Goodman, L. Download references.

Department of Experimental Biology, The Upjohn Company, Kalamazoo, Michigan, ANDRÉ ROBERT, DAVID F. You can also search for this author in PubMed Google Scholar. Reprints and permissions. ROBERT, A. Possible Relationship between Smoking and Peptic Ulcer.

Nature , — Download citation. Received : 14 June Revised : 04 August Issue Date : 15 October Anyone you share the following link with will be able to read this content:. Sorry, a shareable link is not currently available for this article.

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Buy or subscribe. Change institution. Learn more. References Smoking and Health , Report of the Advisory Committee to the Surgeon General of the Public Health Service. Google Scholar Konturek, S. CAS PubMed Google Scholar Robert, A. Google Scholar Thompson, J. Article CAS Google Scholar Goodman, L.

Google Scholar Download references. Author information Authors and Affiliations Department of Experimental Biology, The Upjohn Company, Kalamazoo, Michigan, ANDRÉ ROBERT, DAVID F. NEZAMIS Authors ANDRÉ ROBERT View author publications.

py command was applied using a Phred quality threshold of Q py command [ 33 ]. The Greengenes database version The resulting OTU table was chimera-checked using ChimeraSlayer [ 35 ] and subsequently filtered to remove sequences with a relative abundance of less than 0.

These specific OTUs were then filtered from the small intestinal samples to generate an OTU table which represented contamination-free small intestinal sequences. All samples with a final read count of less than sequence reads were also excluded from the OTU table Additional file 3 : Table S3.

To assess bacterial diversity alpha-diversity , rarefaction curves were generated on the raw OTU table and a read depth of reads was selected for analysis of diversity. py workflow script in QIIME. Significance was tested using Kruskal-Wallis. Multivariate analysis linear regression model was performed via ANOVA.

To assess relative abundance of bacterial taxa, the OTU table was normalised via total sum scaling, followed by centred-log ratio transformation. Average relative abundances were calculated and significant differences assessed using Kruskal-Wallis KW with false discovery rate FDR correction for multiple comparisons.

In order to confirm differences in OTU relative abundance and further avoid potential issues with compositional data [ 38 , 39 ], the ALDEx2 function [ 40 ], implemented in the microbiome analysis tool Calypso [ 41 ], was utilised on non-normalised data.

To assess beta-diversity and the relationship between smoking status and the overall bacterial community, weighted and unweighted UniFrac, along with Bray-Curtis, distance matrices were constructed. The OTU table was normalised via random sub-sampling times to a depth of sequence reads [ 42 ].

py script as implemented in QIIME. Principal coordinate plots were generated from the distance matrix using the first two coordinates and coded based on smoking status and patient diagnosis. To test differences in overall community composition based on smoking status, the ADONIS [ 43 ] permutational MANOVA, as implemented in Calypso [ 41 ], was used, adjusting for sex, age, body mass index BMI , proton pump inhibitor PPI use, and patient diagnosis.

Linear discriminant analysis effect size LEfSe [ 44 ] was used to identify taxa associated with smoking status. This was performed on the OTU table normalised by total sum scaling and centred-log ratio transformation, as implemented in Calypso [ 41 ].

To generate a constrained multivariate model and to differentiate current smokers from those individuals who had never smoked, the sparse partial least squares discriminant analysis method MixMC [ 45 ] was utilised. The OTU table was filtered to include only samples from patients with FD or ID, only current and never smokers, and normalised by total sum scaling followed by centred-log ratio transformation [ 45 ].

This data was used as the training set to generate the model. The model was validated using the leave-one-out validation method. A plot was also generated based on the first two components of the model, following prediction of smoking status, on both the training and test sets.

A total of patients were recruited into the study. There was no significant difference in smoking status when patients were grouped according to diagnosis FD, ID, or CD ; however, there were no current smokers in the iron deficiency screening cohort.

Additionally, there were no significant differences in the sex distribution, PPI use, or BMI across smoking status; however, former smokers were significantly older than current or never smokers Table 1. The density of bacteria adherent to the small intestinal mucosa was assessed via qPCR.

There was no significant difference in bacterial load observed between current, previous, and never smokers Fig. Bacterial load on the small intestinal mucosa in all patients. Load was assessed by qPCR and expressed as the ratio between copies of the bacterial 16S rRNA gene and copies of the human beta-actin gene.

Significance testing was undertaken using Kruskal-Wallis; in addition, a multivariate analysis was undertaken in which patient diagnosis, age, sex, BMI and PPI use were included. In both cases, no significant differences in bacterial load were observed based on smoking status. The composition of the upper small intestinal MAM was established via 16S rRNA gene amplicon sequencing.

Overall, the alpha within sample diversity of the MAM was significantly reduced in current smokers compared to those individuals who have never smoked Fig.

In addition, previous smokers were found to have significantly reduced MAM diversity compared to never smokers. Patient age, sex, BMI, PPI use, and diagnosis did not significantly impact diversity, and the significantly lower diversity in current smokers was still observed when controlling for these factors Additional file 1 : Figure S2.

Bacterial diversity within the mucosa-associated microbiota from duodenal 2nd part biopsies. Patients were grouped based on smoking status current smokers, previous smokers, and having never smoked.

Mean and standard deviation are shown. However, this was not the case for CD Fig. While factors including time since diagnosis and previous surgery in the CD cohort did not impact diversity, patients treated with monoclonal antibody therapies anti-TNF or anti-integrin had greater MAM diversity Additional file 1 : Figure S3.

Controlling for monoclonal antibody therapy in the CD cohort did not alter the findings regarding diversity and smoking status Additional file 1 : Figure S3. Using parallel analyses on raw read data using ALDEx2 for analysis of compositional data; Additional file 1 : S4 and S5 , the significant differences in the phyla Firmicutes and Actinobacteria , along with the genus Rothia , between current and never smokers were confirmed.

In addition, a significant difference in the genus Neisseria was identified, with this taxon being lower in relative abundance in current smokers. Relative abundances of bacterial genera present in the duodenal 2nd part mucosa-associated microbiota of all patients. Patients were grouped based on smoking status.

Data was normalised via total sum scaling and is expressed as relative abundance. The 15 most abundant genera are displayed. Error bars represent standard deviation. None of these factors resulted in differences in any phyla or genera in the model Additional file 1 : Tables S6 and S7.

In addition, this model confirmed the results in regard to smoking status, for Firmicutes , Bacteroidetes, and Actinobacteria at the phylum level Additional file 1 : Table S6 , and Streptococcus , Veillonella , and Prevotella at the genus level Additional file 1 : Table S7.

At the OTU level, four OTUs affiliated with the genus Streptococcus , along with a single Rothia sp. and a single Veillonella sp.

The differences in three of the Streptococcus OTUs were confirmed on multivariate analysis controlling for other patient factors; none of the OTUs were significantly different in abundance using ALDEx2 Additional file 1 : Table S8.

Interestingly, when comparing current to previous smokers, or previous to never smokers, no significant differences at the phylum or genus level of classification were observed Additional file 1 : Tables S4 and S5. At the OTU level, no significant differences between current and previous smokers were observed; however, several Streptococcus -, Veillonella -, and Prevotella -affiliated OTUs showed significantly different relative abundances between previous and never smokers Additional file 1 : Table S8.

There were no remarkable effects on these results when CD patients were excluded from the analysis, and no significant differences were observed in the CD group alone Additional file 1 : Table S9. Principal coordinates analysis of overall MAM profiles suggested some clustering by smoking status unweighted UniFrac and Bray-Curtis distance matrices , after controlling for sex, age, BMI, PPI use, and diagnosis, although this was not observed in the case of the weighted UniFrac matrix Fig.

Multivariate analyses to identify bacterial groups that differentiate current smokers from those patients who have never smoked, based on duodenal 2nd part mucosa-associated microbiota profiles.

a—c Principal coordinates analysis performed on a weighted UniFrac a , unweighted UniFrac b and Bray-Curtis c distance matrices. Each point represents an individual patient, colour coded by smoking status.

Data normalised by random subsampling to even depth. d Linear discriminant analysis effect size LEfSe method to identify bacterial OTUs that are associated with smoking status.

The bar chart represents the strength of contribution of a particular OTU between current, previous and never smokers. Data was normalised via total sum scaling and centred-log ratio transformation. Specific taxa contributing to small intestinal MAM profiles, based on smoking status, were revealed by linear discriminant analysis effect size LEfSe, Fig.

OTUs affiliated with the genera Veillonella were discriminatory for current smokers. Particular members of the genus Prevotella were also discriminatory for previous smokers and persons never having smoked. Taxa affiliated with the Neisseria , Streptococcus , Prevotella , and Veillonella genera were identified as the key contributing factors that differentiate current smokers from those who have never smoked Table 2.

The model was validated using the leave-one-out method and was able to correctly classify all never smokers and 13 of 14 current smokers Table 3 , Fig. When the model was applied to the CD patients, however, the performance was not as robust Table 3.

Constrained multivariate analysis using MixMC method sparse partial least squares discriminant analysis to differentiate patients based on smoking status current or never with respect to duodenal 2nd part mucosa-associated microbiota profiles.

The figure displays the resulting predicted classification of each sample, with closed circles representing the FD-ID cohort, and open triangles representing the CD cohort. Samples misclassified by the model are circled in red. In summation, there are hallmark upper small intestinal MAM profiles that differentiate between active smokers and persons who have never smoked.

For those persons categorised as previous smokers, there is a partial but perhaps not complete restoration of the MAM. This is the first study that has assessed the effects of cigarette smoking on the small intestinal MAM and highlights the importance of considering smoking as a factor in clinical studies of the microbiota.

Our data reveal that cigarette smoking, both current and previous, alters the bacterial community and reduces diversity, both, to the best of our knowledge, novel observations regarding the upper small intestinal MAM.

These changes likely translate into functional differences at the host-microbe interface, which may be relevant to the risk and clinical course of inflammatory conditions affecting the intestine.

This is of particular relevance given the large body of work that indicates smoking is a risk factor for important GI diseases, including inflammatory bowel disease, irritable bowel syndrome, Clostridium difficile infection, and duodenal ulcer [ 1 , 2 , 3 , 46 ], many of which have also been associated with alterations of the microbiota.

For individuals who had never smoked, small intestinal MAM diversity was significantly greater than for current smokers. A number of hypotheses relating to this finding, along with the observed alterations to the composition of the bacterial community, could be suggested based on the known effects of smoking, including alterations to the immune system, direct antimicrobial activity [ 17 ], and changes to oxygen tension [ 16 ].

Overall, a diverse microbiota is generally associated with health, and alterations to immune homeostasis, along with a reduction in diversity induced through smoking, could be suggested to contribute to the adverse impact of smoking on the disease states in which microbiota-immune interactions are considered important.

Further studies specifically investigating these interactions are warranted. We included previous smokers in our analyses, and trends indicated that the previous smokers group may represent an intermediate between smokers and those who have never smoked.

In particular, previous smokers had a reduced diversity of the MAM compared to individuals who had never smoked. However, given patients can tend to under-report their smoking habits [ 47 ], it may be speculated that some patients in the previous smokers cohort may represent current smokers under-reporting their status.

Time since ceasing smoking, as well as other factors such as environmental tobacco exposure passive smoking , may also influence the results, and thus, further investigation of these factors would provide more specific insight into the beneficial effects of quitting smoking on the microbiota and associated disease risks.

Smoking did not alter the total density of bacteria present on the small intestinal mucosa. This suggests that the reduced diversity observed in current smokers is not the result of overgrowth of certain members of the microbiota, which would result in higher load and lower diversity, nor it is a result of an overall decrease in bacteria adherent to the mucosa.

Rather, our results indicate a shift in composition within the existing microbial community. A particular impact on the small intestinal MAM from smoking is the reduction of the relative abundance Prevotella and Neisseria spp. and an increased relative abundance of Firmicutes , principally Streptococcus spp.

These differentiating taxa were identified by both models used in our study. Interestingly, a number of these taxa have been identified in studies investigating the effects of smoking on the oral cavity, both culture-based studies [ 48 ], and more recently, microbiota profiling studies, which reported increased relative abundances of Streptococcus spp.

and decreased relative abundances of Neisseria spp. among others [ 12 ]. There is a clear overlap between the taxa observed in the oral cavity and the small intestine, particularly at broader taxonomic levels, and the oral microbiota has been suggested as a driver of the composition of the gastric microbiota [ 49 ].

It would be informative to consider the impact of oral health on the small intestinal microbiota, both generally and in the context of smoking, for example, using matched saliva and biopsy samples, particularly given the negative impact smoking has on oral health and the risk of caries [ 50 ].

A variety of mechanisms may be relevant regarding the influence of smoking on particular members of the microbiota. Oxygen tension has been suggested as an important driver of changes, with microaerophilic and fermentative anaerobic bacteria able to predominate due to lower oxygenation [ 11 , 51 ].

The differences we observe in Neisseria, Streptococcus , and Rothia spp. in current smokers indicate that changes in oxygen tension in the small intestine may be a strong selective pressure on the MAM, but there are also likely to be other physicochemical factors in play.

For instance, the relative abundance of select Prevotella - and Veillonella -affiliated OTUs were discriminatory of persons based on smoking status. These bacteria are strict anaerobes and likely to be sensitive to the oxygen radicals produced as a consequence of smoking [ 52 , 53 ]. Furthermore, alterations in duodenal bicarbonate secretion [ 19 ] and lower duodenal pH [ 18 ] in smokers also provide selective pressure, with particular impact on the growth of Neisseria that is much more sensitive to acid conditions [ 54 ], whereas Streptococcus and Rothia spp.

are acidogenic and acid tolerant. A number of studies have recently associated alterations in the small intestinal MAM with various disease states. A particular focus has been Coeliac disease, with alterations to the microbiota, including lower diversity, observed in adult patients with untreated disease or those with disease refractory to treatment [ 22 , 23 ].

Interestingly, in a cohort of patients with type 1 diabetes, a reduction in relative abundance of Proteobacteria present in the small intestinal MAM was observed, although this study did not differentiate between children and adults [ 24 ]. In chronic liver disease, again, changes in the relative abundance of taxa affiliated with the Proteobacteria and Firmicutes phyla were observed [ 25 ].

However, none of these studies controlled for, or indeed reported, smoking status. Our study indicates smoking as a relevant confounding factor that may preclude or confound identification of disease-specific microbial changes if not considered. Thus, the data generated here can be considered to specifically reflect the upper small intestinal MAM and the smoking related changes particular to this site.

As our own data highlights, in addition to sampling methodology, environmental factors also have an important impact on the microbiota, and thus, we have considered a variety of factors including age, sex, BMI, and PPI use.

One limitation is that the impact of diet on the small intestinal MAM is very poorly characterised, and we did not have access to dietary history for this patient cohort. However, endoscopic procedures, during which biopsy samples were obtained, were undertaken following overnight fasting for all patients.

It is also possible that unique medication combinations that individual patients are exposed to, depending on their medical history, may influence the microbiota and increase variation between individuals. The results may also be partly driven by the small sample size for CD patients.

In summary, this study provides important new insights into the impact of cigarette smoking on the MAM. The reduction in diversity, along with particular bacterial taxa, may have implications for GI disorders in which the microbiota is also implicated.

Studies investigating the MAM, particularly in the small intestine, must consider smoking status of participants, as this represents a potentially significant confounding variable.

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