Tag: smoking

E-cigarette use linked to increased risk of heart failure, large study finds

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People who use e-cigarettes are significantly more likely to develop heart failure compared with those who have never used them, according to one of the largest prospective studies to date investigating possible links between vaping and heart failure. The findings are being presented at the American College of Cardiology’s Annual Scientific Session.

Heart failure is a condition affecting more than 6 million U.S. adults in which the heart becomes too stiff or too weak to pump blood as effectively as it should. It can often lead to debilitating symptoms and frequent hospitalizations as people age. Electronic nicotine products, which include e-cigarettes, vape pens, hookah pens, personal vaporizers and mods, e-cigars, e-pipes and e-hookahs, deliver nicotine in aerosol form without combustion. Since they were first introduced in the U.S. in the late 2000s, electronic nicotine products have often been portrayed as a safer alternative to smoking, but a growing body of research has led to increased concern about potential negative health effects.

More and more studies are linking e-cigarettes to harmful effects and finding that it might not be as safe as previously thought. The difference we saw was substantial. It’s worth considering the consequences to your health, especially with regard to heart health.”

Yakubu Bene-Alhasan, MD, a resident physician at MedStar Health in Baltimore and the study’s lead author

For the study, researchers used data from surveys and electronic health records in All of Us, a large national study of U.S. adults run by the National Institutes of Health, to analyze associations between e-cigarette use and new diagnoses of heart failure in 175,667 study participants (an average age of 52 years and 60.5% female). Of this sample, 3,242 participants developed heart failure within a median follow-up time of 45 months.

The results showed that people who used e-cigarettes at any point were 19% more likely to develop heart failure compared with people who had never used e-cigarettes. In calculating this difference, researchers accounted for a variety of demographic and socioeconomic factors, other heart disease risk factors and participants’ past and current use of other substances, including alcohol and tobacco products. The researchers also found no evidence that participants’ age, sex or smoking status modified the relationship between e-cigarettes and heart failure.

Breaking the data down by type of heart failure, the increased risk associated with e-cigarette use was statistically significant for heart failure with preserved ejection fraction (HFpEF)-;in which the heart muscle becomes stiff and does not properly fill with blood between contractions. However, this association was not significant for heart failure with reduced ejection fraction (HFrEF)-;in which the heart muscle becomes weak and the left ventricle does not squeeze as hard as it should during contractions. Rates of HFpEF have risen in recent decades, which has led to an increased focus on determining risk factors and improving treatment options for this type of heart failure.

The findings align with previous studies conducted in animals, which signaled e-cigarette use can affect the heart in ways that are relevant to the heart changes involved in heart failure. Other studies in humans have also shown links between e-cigarette use and some risk factors associated with developing heart failure. However, previous studies attempting to assess the direct connection between e-cigarette use and heart failure have been inconclusive, which Bene-Alhasan said is due to the inherent limitations of the cross-sectional study designs, smaller sample sizes and the smaller number of heart failure events seen in previous research.

Researchers said the new study findings point to a need for additional investigations of the potential impacts of vaping on heart health, especially considering the prevalence of e-cigarette use among younger people. Surveys indicate that about 5% to 10% of U.S. teens and adults use e-cigarettes. In 2018, the U.S. Surgeon General called youth e-cigarette use an epidemic and warned about the health risks associated with nicotine addiction.

“I think this research is long overdue, especially considering how much e-cigarettes have gained traction,” Bene-Alhasan said. “We don’t want to wait too long to find out eventually that it might be harmful, and by that time a lot of harm might already have been done. With more research, we will get to uncover a lot more about the potential health consequences and improve the information out to the public.”

Bene-Alhasan also said e-cigarettes are not recommended as a tool to quit smoking, since many people may continue vaping long after they quit smoking. The U.S. Centers for Disease Control and Prevention recommends a combination of counseling and medications as the best strategy for quitting smoking.

Researchers said that the study’s prospective observational design allows them to infer, but not conclusively determine, a causal relationship between e-cigarette use and heart failure. However, with its large sample size and detailed data on substance use and health information, Bene-Alhasan said the study is one of the most comprehensive studies to assess this relationship to date.

Source:

American College of Cardiology

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April 2, 2024
Irritable bowel syndrome not linked to higher Parkinson’s risk, study finds
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In a recent study published in npj Parkinson’s Disease, researchers explore the relationship between Parkinson’s disease (PD) and irritable bowel syndrome (IBS).

Study: Association between irritable bowel syndrome and Parkinson’s disease by Cohort study and Mendelian randomization analysis. Image Credit: Kotcha K / Shutterstock.com

What causes PD?

PD is a common neurodegenerative disease, with symptoms including resting tremors, bradykinesia, and stiffness. Typically, these symptoms arise several years before being diagnosed with PD, with cognitive impairment and gastrointestinal problems preceding motor symptoms.

The specific etiology of PD is unknown; however, the disease may caused by environmental and genetic factors. There is evidence linking PD to gastrointestinal symptoms, which might be related to changes in the gut microbiome, enhanced intestinal permeability, or gut-brain communication.

IBS is a functional gastrointestinal disease characterized by recurring or chronic abdominal discomfort and bowel alterations. Current research indicates a possible association between PD and IBS; however, the results of these studies have been inconsistent.

About the study

Data from the United Kingdom Biobank (UKBB) of 426,911 individuals between 40 and 69 years of age enrolled in 22 centers between 2006 and 2010 were used for the current analysis. Five healthy control individuals based on age and sex were also used for each IBS patient diagnosed at follow-up. All study participants were monitored until PD diagnosis, study termination in June 2023, or death, whichever occurred first.

Any individuals with missing data, as well as those with other neurological and gastrointestinal disorders, were excluded from the study. Likewise, any individuals diagnosed with PD before study initiation and those with indeterminate dates for IBS diagnosis were also excluded. Taken together, 26,944 individuals were diagnosed with PD and 2,460 with IBS using the International Classification of Disease-10 (ICD-10) codes.

Cox proportional hazard models were used to determine the hazard ratios (HRs), whereas logistic regression analysis was used to calculate the odds ratios (ORs) for the association between PD and IBS. Study covariates included age, sex, body mass index (BMI), Townsend deprivation index, educational attainment, ethnicity, smoking status, alcohol intake, overall health, and chronic medical conditions.

Sensitivity analyses were also performed by excluding individuals with self-reported IBS diagnoses and stratifying participants by IBS diagnosis before or after 2000. The association between PD and IBS was also analyzed by Mendelian randomization (MR) analyses using genotype data as instrumental variables, including simple mode, weighted mode, weighted median, MR Egger, and inverse variance weighting (IVW) methods.

Study findings

Of the 419,685 individuals involved in Cox modeling, 95% comprised the control study group, and 4.7% were diagnosed with IBS before study initiation. Both groups were monitored for a mean of 14 years.

As compared to controls, IBS patients were more likely to be female, less educated, non-smokers, consume less alcohol, have poorer health, and have more comorbidities. At follow-up, 90 IBS patients and 2,321 controls received a PD diagnosis, with incidence rates of 3.2 and 4.2 in 10,000 individual years in the case and control groups, respectively.

Univariable Cox regression analysis demonstrated that PD risk was reduced among IBS patients with an HR of 0.8. In a certain subgroup analyses, IBS individuals were associated with a reduced likelihood of developing PD, as did individuals receiving an IBS diagnosis after 2000 with an HR of 0.6.

Subgroup analysis revealed that IBS was associated with a lower incidence of PD among white individuals, individuals with a smoking history, BMI between 25-29.90, and less than college-level educational attainment, with HRs of 0.8, 0.6, 0.6, and 0.8, respectively.

IBS was significantly associated with 11 study covariates, including advanced age, male sex, and comorbidities, with HRs of 1.2, 2.1, and 1.7, respectively. Individuals who frequently consumed alcohol were also at a reduced risk of PD risk than occasional and non-consumers; however, for those with excess alcohol intake, this correlation was not apparent.

Logistic regression analysis revealed that IBS was unrelated to PD risk with an OR of 1.2. Likewise, MR analyses showed no significant evidence of causal associations between IBS and PD, with an OR of 0.8.

A significantly increased risk of PD was observed among non-IBS patients with a polygenic risk score of PD with an HR of 2.2. In the sensitivity analysis, excluding self-reported IBS patients yielded similar results.

Among individuals diagnosed with IBS after 2000, a reduced risk of PD was related to IBS with an HR of 0.6. Case-control analysis showed that IBS occurrence did not reduce PD risk, with MR analysis results supporting these findings.

Conclusions

IBS patients do not appear to be at a greater risk of developing PD; however, some patient subgroups may be less likely to be diagnosed with PD. Nevertheless, future studies are needed to better understand the potential relationship between IBS and PD and elucidate underlying mechanisms.
Journal reference:

Wang, Z., Ma, D., Li, M., et al. (2024). Association between irritable bowel syndrome and Parkinson’s disease by Cohort study and Mendelian randomization analysis. npj Parkinson’s Disease 10(70). doi:10.1038/s41531-024-00691-5
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April 1, 2024
Research from NY highlights pollution as a key factor in rising cancer rates among youth

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In a recent study published in Scientific Reports, researchers investigated cancer incidence trends among adults in the New York State (NYS) and associations with common population-level exposures.

Study: Cancer incidence trends in New York State and associations with common population-level exposures 2010–2018: an ecological study. Image Credit: nyker/Shutterstock.com

Background

In the United States (US), cancer remains the leading cause of morbidity and mortality. Exogenous factors, like lifestyle factors and environmental exposures, account for 70% to 90% of cancer risk and can influence cancer trends. Cancer incidence in the US has increased over time.

Identification of modifiable exogenous factors driving these increases could inform cancer prevention. Studies have demonstrated that higher-level environmental exposures can elevate cancer risks.

Environmental carcinogens exist at low levels in water and air and can potentially contribute to cancer risk. Some studies have revealed associations between air pollutants and specific cancers, and fewer studies have evaluated water contaminants, yielding mixed findings.

However, the impact of low-dose, persistent, chronic environmental exposure on the risk of cancer is understudied.

About the study

The present study examined cancer incidence trends in NYS and associations with common exposures. They used cancer incidence data from 2010 to 2018 and risk factor data between 2000-09, accounting for an induction time of 10 years. They focused on cancers with the highest incidence rates in NYS and selected ten cancers.

Cancers included 1) colorectal, 2) thyroid, 3) kidney and renal pelvis, 4) non-Hodgkin lymphoma, 5) melanoma, 6) leukemia, and 7) lung and bronchus cancer for both sexes, 8) prostate cancer in males, and 9) breast and 10) corpus uteri cancer in females.

Age-standardized incidence rates were calculated by sex and age group across 62 NYS counties. Statewide sex- and site-specific annual rates of cancer incidence for each year.

Risk factor data were compiled from several sources. They included six types of measures – 1) environmental exposure, 2) socioeconomic status (SES) and race composition, 3) general health conditions, 4) community characteristics, 5) lifestyle factors, and 6) spatial differences.

Temporal incidence trends were analyzed in the 25–49 age group to examine changes in early-onset cancers. Linear regression models were used to assess associations with exposures.

Findings

The NYS shared the nine most prevalent cancers with the US. Incidence rates for most cancers in the NYS were higher than in the US overall, ranging from 0.2% higher for lung and bronchus cancer to 36.6% higher for thyroid cancer.

Incidence rates in the 25–49 age group were also higher by 24.1% for non-Hodgkin lymphoma, 25% for prostate cancer, and 39.7% for thyroid cancer.

The incidence of six cancers (breast, prostate, corpus uteri, thyroid, colorectal, and kidney and renal pelvis) significantly increased between 2000 and 2018.

The models explained ≥ 30% variation in incidence data for six, five, and four cancers in the 25–49, 50–69, and 70–84 age groups, respectively. Moreover, models revealed a positive association between various PM_2.5-related variables and several cancers in males.

Moreover, for breast cancer cases in the 25–49 age group, a positive association was observed with ambient PM_2.5 levels.

Among 15 environmental variables, positive associations were observed between ambient ozone levels and prostate cancer; mineral dust levels and acute toxic substance release rate were associated with melanoma in males. In females, the percentage of land used for agriculture was negatively associated with thyroid cancer.

Among race and SES variables, counties with lower insurance coverage and higher poverty had reduced incidence rates of breast cancer and thyroid cancer.

Counties with increased proportions of white residents had higher melanoma incidence rates in both sexes and across age groups; these counties also had higher incidence rates of uterine cancer across age groups.

Among four lifestyle factors, smoking was positively associated with lung cancer in both sexes and across age groups. Besides, physical inactivity was positively associated with thyroid cancer in the 25–49 age group in both sexes.

Two spatial patterns were identified; counties in northern NYS had higher incidence rates of lung cancer and lower incidence rates of thyroid cancer.

Conclusions

In sum, the study found positive associations between ambient air pollutants and melanoma, breast cancer and prostate cancer, physical inactivity and thyroid cancer, and smoking and lung cancer.

In general, models could better explain the variation in incidence data in the 25–49 age group than in older age groups. This reflects higher relative risk contributions of exogenous factors during younger ages than for older ages when aging may have more influence on cancer risk.

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March 28, 2024
Exercise could be the cure to your insomnia
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In a recent study published in the journal BMJ Open, an international team of researchers conducted a longitudinal study over 10 years to understand the association between physical activity and sleep duration, daytime sleepiness, and current insomnia symptoms in adults.

Study: Association between physical activity over a 10-year period and current insomnia symptoms, sleep duration and daytime sleepiness: a European population-based study. Image Credit: Ground Picture/Shutterstock.com

Background

Adequate sleep is one of the major aspects of life and health that has suffered due to the fast-paced nature of modern lives and an increase in the use of electronic devices such as mobile phones.

Sleep disturbance and insomnia have a direct impact on overall health, can increase the risk of metabolic dysfunction, cardiovascular disease, and psychiatric disorders, and impact the quality of life.

Physical activity or exercise is known to improve sleep quality, reduce symptoms of insomnia, and benefit overall health. Exercise has been associated with reduced daytime sleepiness, and low levels of physical activity are believed to increase daytime sleepiness.

However, factors such as age, gender, body mass index (BMI), general state of health, fitness levels, and type of physical activity can moderate the association between exercise and sleep quality through numerous psychological and physiological pathways.

Furthermore, there is a dearth of long-term data from studies involving large cohorts, making it difficult to decipher whether the positive impact on sleep outcomes is due to higher physical activity levels, or inadequate physical activity is due to disturbed sleep.

About the study

In the present study, the researchers aimed to assess whether the frequency, intensity, and duration of physical activity were interrelated with daytime sleepiness, disturbed sleep, and symptoms of insomnia.

The study was conducted across nine countries, twice over a span of 10 years, among adults between the ages of 39 and 67 years.

The data for this study was obtained from two follow-ups of the European Community Respiratory Health Survey. Assessments of physical activity levels were conducted using participant responses to questionnaires.

The queries aimed at determining how often the participants exercised, and the number of hours per week they needed to exercise to get to a stage where they were sweaty or out of breath.

A minimum of one hour of physical activity a week or an exercise frequency of twice a week or more was considered physically active.

Based on the change in physical activity levels between the two follow-ups, the participants were grouped into four categories — those who remained non-active, those who went from active to inactive, those who became more active, and those who maintained their physical activity levels over the 10 years of follow-up.

The Basic Nordic Sleep Questionnaire was used to evaluate the symptoms related to disturbed sleep and insomnia. These questions addressed the occurrence and frequency of symptoms such as difficulty initiating or maintaining sleep, as well as awakening too early in the morning.

The Epworth Sleepiness Scale was used to assess daytime sleepiness. Additionally, the average sleep duration was used to classify the participants into short, normal, and long sleepers based on more than six hours, between six and nine hours, and more than nine hours of sleep, respectively.

Results

The results showed that adequate physical activity was associated with a lower incidence of either short or long sleep durations and decreased risk of some symptoms of insomnia.

Individuals who maintained adequate physical activity levels through the 10 years of follow-up were found to be less likely to report symptoms of insomnia during the follow-up.

Furthermore, persistently active individuals also reported achieving the recommended six to nine hours of sleep, and these associations were found to be significant even after adjusting for confounders such as age, sex, BMI, and smoking behavior.

On average, individuals who were persistently active over the 10 years of follow-up had lower BMI, were younger, and were male. They were also less likely to be smokers and more likely to be currently employed.

Although daytime sleepiness or symptoms such as difficulty maintaining sleep were not found to be linked to physical activity levels, smoking behavior was found to have independent associations with daytime sleepiness.

Conclusions

Overall, the findings suggested that consistent, long-term physical activity can decrease the risk of various insomnia symptoms and help achieve adequate sleep.

Furthermore, although physical activity levels did not seem to impact the occurrence of daytime sleepiness, lifestyle factors such as smoking behavior were associated with daytime sleepiness.
Journal reference:

Bjornsdottir E., Thorarinsdottir E.H., Lindberg E., et al. (2024). Association between physical activity over a 10-year period and current insomnia symptoms, sleep duration and daytime sleepiness: a European population-based study. BMJ Open. doi:https://doi.org/10.1136/bmjopen-2022-067197.
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March 27, 2024
Study reveals risk factors for faster aging in the brain

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The researchers had previously identified a ‘weak spot’ in the brain, which is a specific network of higher-order regions that not only develop later during adolescence, but also show earlier degeneration in old age. They showed that this brain network is also particularly vulnerable to schizophrenia and Alzheimer’s disease.

In this new study, published in Nature Communications, they investigated the genetic and modifiable influences on these fragile brain regions by looking at the brain scans of 40,000 UK Biobank participants aged over 45.

The researchers examined 161 risk factors for dementia, and ranked their impact on this vulnerable brain network, over and above the natural effects of age. They classified these so-called ‘modifiable’ risk factors – as they can potentially be changed throughout life to reduce the risk of dementia – into 15 broad categories: blood pressure, cholesterol, diabetes, weight, alcohol consumption, smoking, depressive mood, inflammation, pollution, hearing, sleep, socialization, diet, physical activity, and education.

Prof. Gwenaëlle Douaud, who led this study, said: ‘We know that a constellation of brain regions degenerates earlier in aging, and in this new study we have shown that these specific parts of the brain are most vulnerable to diabetes, traffic-related air pollution – increasingly a major player in dementia – and alcohol, of all the common risk factors for dementia.’

‘We have found that several variations in the genome influence this brain network, and they are implicated in cardiovascular deaths, schizophrenia, Alzheimer’s and Parkinson’s diseases, as well as with the two antigens of a little-known blood group, the elusive XG antigen system, which was an entirely new and unexpected finding.’

In fact, two of our seven genetic findings are located in this particular region containing the genes of the XG blood group, and that region is highly atypical because it is shared by both X and Y sex chromosomes. This is really quite intriguing as we do not know much about these parts of the genome; our work shows there is benefit in exploring further this genetic terra incognita.”

Prof. Lloyd Elliott, co-author from Simon Fraser University in Canada

Importantly, as Prof. Anderson Winkler, a co-author from the National Institutes of Health and The University of Texas Rio Grande Valley in the US, points out: ‘What makes this study special is that we examined the unique contribution of each modifiable risk factor by looking at all of them together to assess the resulting degeneration of this particular brain ‘weak spot’. It is with this kind of comprehensive, holistic approach – and once we had taken into account the effects of age and sex – that three emerged as the most harmful: diabetes, air pollution, and alcohol.’

This research sheds light on some of the most critical risk factors for dementia, and provides novel information that can contribute to prevention and future strategies for targeted intervention.

Source:

Journal reference:

Manuello, J., et al. (2024). The effects of genetic and modifiable risk factors on brain regions vulnerable to ageing and disease. Nature Communications. doi.org/10.1038/s41467-024-46344-2.

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March 27, 2024
Is smoking linked to abdominal obesity?
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Previously, Mendelian randomization (MR) studies have explored the causal relationship between smoking and abdominal obesity using a single genetic variant for smoking heaviness. Similarly, a recent Addiction study uses multiple genetic instruments to estimate the causal relationship between smoking and abdominal obesity.

Study: Estimating causality between smoking and abdominal obesity by Mendelian randomization. Image Credit: kong-photo / Shutterstock.com

How does smoking affect obesity?

Smoking leads to several chronic disorders, particularly cardiovascular and respiratory diseases. In fact, smokers often have more abdominal fat as compared to non-smokers, which further increases their risk of cardiometabolic diseases.

It remains unclear whether the association between body fat distribution and smoking is causal. Genetic variants associated with exposure traits have been used as instrumental variables by MR studies to assess this potentially causal relationship. MR is similar to a naturally randomized controlled trial as, during conception, paternal and maternal alleles are randomly allocated.

Previously, MR studies have explored the causal relationship between the heaviness of smoking and abdominal obesity using a single genetic variant. Two studies noted no causal relationship, whereas a third suggested a causal link between the number of cigarettes smoked each day and the waist-hip ratio (WHR), even after controlling for the body mass index (BMI).

About the study

The current causal analysis using summary effect estimates (CAUSE) study involved two-sample MR analyses to quantify the effect of smoking initiation, heaviness, and life-time smoking on abdominal adiposity. To this end, genome-wide association studies (GWAS) summary statistics were obtained from the GWAS and Sequencing Consortium of Alcohol and Nicotine Use (GSCAN), United Kingdom Biobank, and Genetic Investigation of Anthropometric Traits (GIANT) Consortium.

All study participants were of European ancestry. Exposure traits included smoking initiation, heaviness, and lifetime smoking were used, whereas outcome traits including WHR, as well as waist and hip circumferences (WC and HC) were used. The outcome traits were considered with and without adjustment for BMI.

Study findings

Lifetime smoking and smoking initiation causally increased abdominal adiposity, independent of socio-economic status, alcohol consumption, and other factors. Visceral fat or visceral adipose tissue (VAT) increased more than abdominal subcutaneous fat (ASAT).

The causal relationship between abdominal fat and smoking heaviness could not be established. However, reverse causality analyses indicated that smoking heaviness could be increased causally by abdominal adiposity.

Previous studies have used a single genetic variant in the CHRNA3/5 locus to establish causality between abdominal adiposity and smoking heaviness, both of which did not identify a causal relationship between these two factors. The Wald ratio estimates for the CHRNA3/5 locus in the current study observed causal effects; however, upon instrumenting smoking heaviness with all known genetic loci, this effect was not present.

Consistent with previous studies, two-sample MR analyses with 13 smoking heaviness variants showed negative causality between BMI and smoking heaviness due to the CHRNA3/5 locus. Moreover, LHC-MR and CAUSE analysis failed to establish causality between lower BMI and smoking heaviness, thus suggesting a pleiotropic effect of the CHRNA3/5 locus on BMI and smoking heaviness, rather than a causal effect.

Smoking could lead to higher abdominal fat by increasing ASAT or visceral fat. The results for magnetic resonance imaging (MRI)-based adipose depot volumes suggested increased VAT to be primarily responsible for higher abdominal adiposity, rather than ASAT, which is consistent with the findings in existing research.

Conclusions

Lifetime smoking and smoking initiation may causally lead to higher abdominal and particularly visceral fat. Thus, public health efforts to reduce and prevent smoking could aid in lowering abdominal fat and the associated risk of chronic illnesses.

The strengths of the current study include the application of different complementary MR methods and sensitivity analyses, as well as the use of large-scale GWAS summary-level data to reduce reverse causality, sample overlap, and pleiotropic effects.

The main limitation of the present study involves the presence of residual pleiotropic effects and their influence on causal estimates. These effects could not be completely removed, despite performing multiple sensitivity analyses.

Additionally, in the sub-sample of current smokers, the sample size for body fat distribution was small. This restricted the statistical power of the analysis of smoking heaviness. Another limitation involved the inability to evaluate the effect of smoking cessation on body fat distribution.

Importantly, cigarettes depict unstandardized tobacco doses, which could have had a non-negligible impact on the accuracy of the estimates for smoking heaviness. Furthermore, the study population, which was restricted to individuals of European genetic ancestry, limits the generalizability of the study findings to other diverse populations.
Journal reference:

Carrasquilla, G. D., Garcia-Urena, M., Romero-Lado, M. J., & Kilpelainen, T. O. (2024). Estimating causality between smoking and abdominal obesity by Mendelian randomization. Addiction. doi:10.1111/add.16454
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March 27, 2024
Study sheds light on the interplay of genes in smoking addiction

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Take a puff of nicotine for the first time, and your DNA plays an important role, alongside social and environmental factors, in shaping what happens next.

In recent years, scientists have identified thousands of genetic variants believed to influence everything from when people first try smoking to how good that first cigarette feels to how often they light up and how hard it is to quit. Some variants influence how quickly we metabolize nicotine, while others underlie how sensitive we are to it. But little is known about how they interact with each other and with other genetic differences.

A new University of Colorado Boulder study sheds unprecedented light on these interactions and provides new insight on the most well-known smoking-related variant to date – commonly nicknamed “Mr. Big”.

“We know that smoking is highly heritable, with genetic differences accounting for 40% to 75% of the differences in people’s smoking behaviors,” said Pamela Romero Villela, a PhD student in the Department of Psychology and Neuroscience and first author of the study in the journal Drug and Alcohol Dependence. “The more we can understand what those genes do and how they interact, the better equipped we will be to develop personalized approaches to helping people quit.”

Beyond Mr. Big

About 22% adults worldwide use nicotine and smoking is linked to one in five deaths in the United States.

A lot of people still smoke, and it is one of the hardest drugs to quit.”

Romero Villela, researcher with CU Boulder’s Institute for Behavioral Genetics

For the study, Romero Villela collaborated with Integrative Physiology Professor Marissa Ehringer, who has studied substance use disorders for more than 20 years.

They zeroed in on the single nucleotide polymorphism (SNP), or genetic variant, rs16969968, known as “Mr. Big” because it has been the mostly widely replicated genetic variant associated with smoking behaviors.

Mr. Big is located in a gene called CHRNA5F (nicotinic acetylcholine receptor 5) and influences how well nicotine binds to receptors in the brain. People with a certain version of Mr. Big, known as the AA version, are less sensitive to nicotine and have been shown to smoke more.

“It kind of numbs your response so in order for you to feel the same effect as someone who smoked one cigarette you might have to smoke almost one and a half cigarettes,” said Romero Villela.

As their study reveals, the story does not end there.

A personalized approach

When analyzing genetic information from about 165,000 current or former smokers of European, South Asian, and Finnish descent, the team discovered genes and variants in a completely different region of the genome that appear to interact with Mr. Big in a way that influences smoking habits.

Notably, when people had the risk-boosting version of Mr. Big but also had a genetic variant called rs73586411, they smoked significantly less than expected.

“We basically found another variant that ameliorates the effect of Mr. Big,” said Romero Villela.

More research is needed to understand just what the genes highlighted in the study do. (Interestingly, one called TMEM230 has previously been associated with Parkinson’s disease. Nicotine is known to blunt some symptoms of the disease).

The study authors imagine a day when people could be given a “polygenic risk score” which considers their gene variants and interactions to provide personalized recommendations for quitting. For instance, preliminary studies have already suggested that people with high-risk genotypes in the CHRNA5 region may benefit more from medications targeting nicotinic receptors.

Eventually, if researchers could determine what a variant does to dull the craving to smoke, they might be able to develop medications that mimic that action.
Bigger picture, the authors hope the study inspires more research looking not just at individual genes but also how genetic variants work together.

“Genes don’t operate in a vacuum,” said Ehringer. “If our ultimate goal is more personalized medicine, we have to understand these interactions better.”

Source:

University of Colorado at Boulder

Journal reference:

Romero, P. N., et al. (2024). Loci on Chromosome 20 Interact with rs16969968 to Influence Cigarettes per Day in European Ancestry Individuals. Drug and Alcohol Dependence. doi.org/10.1016/j.drugalcdep.2024.111126.

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March 27, 2024
Consistent exercise improves sleep and reduces insomnia

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Consistently exercising 2-3 times a week over the long term is linked to a lower current risk of insomnia as well as the ability to clock up the recommended 6-9 hours of shut eye every night, suggests an international 10-year study published in the open access journal BMJ Open.

Regular exercise is associated with better overall health, and several studies have suggested that physical activity promotes better quality sleep and may improve symptoms of chronic insomnia, note the researchers.

But it’s not entirely clear how much gender, age, weight (BMI), overall fitness, general health and exercise type contribute to this association, they add.

To explore this further, the researchers assessed the frequency, duration, and intensity of weekly physical activity and symptoms of insomnia, nightly sleep clocked up, and daytime sleepiness among middle-aged adults from 21 centers in nine European countries.

The 4399 study participants (2085 men; 2254 women) were drawn from the European Community Respiratory Health Survey.

They had answered questions on the frequency and duration of physical activity at baseline (ECRHS II;1998-2002) and on physical activity, insomnia symptoms (Basic Nordic Sleep Questionnaire; scale 1-5), sleep duration and daytime sleepiness (Epworth Sleepiness Scale) 10 years later (ECRHS III; 2011-14).

Participants who reported that they exercised at least two or more times a week, for 1 hour/week or more, were classified as being physically active.

Over the 10 year period, 37% (1601) of participants were persistently inactive; 18% (775) became physically active; 20% (881) became inactive; and 25% (1082) were persistently active.

Participants in Norway were most likely to be persistently active, while participants in Spain, followed by Estonia, were most likely to be persistently inactive.

Persistently active participants were more likely to be men, younger, and to weigh slightly less. They were also less likely to be current smokers and more likely to be currently working.

After adjusting for age, sex, weight (BMI), smoking history, and study centre, those who were persistently active were significantly (42%) less likely to find it difficult to fall asleep, 22% less likely to have any symptom of insomnia, and 40% less likely to report 2 or 3 (37% less likely) insomnia symptoms.

Insomnia symptoms were also independently associated with age, female gender, and weight.

As for total nightly hours of sleep and daytime sleepiness, after adjusting for age, sex, weight, smoking history, and study center, persistently active participants were most likely to be normal sleepers while the persistently inactive were least likely to be in that category.

The persistently active were significantly (55%) more likely to be normal sleepers and significantly less likely (29%) to be short (6 hours or less), and 52% less likely to be long, sleepers (9 hours or more). And those who became active were 21% more likely to be normal sleepers than those who were persistently inactive.

The researchers acknowledge that they weren’t able to objectively assess changes in physical activity levels between the two time points and that all the elements relied on subjective assessment via questionnaire.

But they nevertheless conclude: “Our results are in line with previous studies that have shown the beneficial effect of [physical activity] on symptoms of insomnia, but the current study additionally shows the importance of consistency in exercising over time, because the association was lost for initially active subjects who became inactive.”

Source:

Journal reference:

Bjornsdottir, E., et al. (2024). Association between physical activity over a 10-year period and current insomnia symptoms, sleep duration and daytime sleepiness: a European population-based study. BMJ Open. doi.org/10.1136/bmjopen-2022-067197

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March 27, 2024
Multiomic approach boosts disease prediction accuracy beyond traditional methods

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In a recent study published in the journal Nature Aging, researchers assessed the added predictive value of integrating polygenic risk scores (PRSs) and gut microbiome scores with conventional risk factors for common diseases in a long-term cohort study.

Analysis: Integration of polygenic and gut metagenomic risk prediction for common diseases. Image Credit: remotevfx.com / Shutterstock

Background

Multiomic technologies are transforming disease prediction by integrating genomic and microbiomic data, offering new insights into age-related conditions like heart disease, diabetes, and cancer. Previously, risk assessments relied mainly on demographic, lifestyle, and clinical metrics. Now, the integration of PRSs and gut microbiome analysis into risk models promises to improve predictive accuracy beyond traditional factors. PRSs provide a cost-effective genetic predisposition metric, while the gut microbiome adds a novel dimension to understanding disease risk. This emerging approach necessitates further research to refine its accuracy and ensure its effectiveness across various populations and healthcare systems.

About the study

The FINRISK 2002 cohort, part of a series of Finnish surveys aimed at exploring chronic disease risk factors since 1972, served as the foundation for this study, focusing on the interplay between gut microbiota and health outcomes. Spanning six Finnish regions, this cohort engaged 8,783 participants from a pool of 13,498 invitees, including a diverse demographic aged 25–74. Under stringent ethical guidelines, these participants underwent comprehensive health examinations and contributed biological samples, including blood and stool.

This research, grounded in detailed baseline data collection, aimed to explore the predictive power of genetic and microbiomic factors alongside traditional risk indicators for diseases like coronary artery disease (CAD), type 2 diabetes (T2D), Alzheimer’s disease (AD), and prostate cancer. Through careful sample handling and state-of-the-art genomic and metagenomic analyses, the study capitalized on advanced multiomic technologies to build predictive models. These models were refined through rigorous statistical methods, evaluating their predictive performance against conventional risk assessment tools.

Study results

In the FINRISK 2002 cohort, a longitudinal study spanning over 17.8 years and including electronic health records (EHRs), 579 of T2D, 333 cases of CAD, 273 of AD, and 141 of prostate cancer were identified among participants with both imputed genotypes and gut metagenomic sequencing. The baseline clinical risk factors exhibited significant differences between incident cases and non-cases for CAD, T2D, and AD, with certain factors like smoking for T2D and sex, diastolic blood pressure (DBP), and High-Density Lipoprotein (HDL) for AD not differing significantly. Prostate cancer cases differed significantly from non-cases in terms of baseline age and smoking habits.

PRSs and conventional risk factors were assessed for their predictive performance in incident diseases through Cox regression models. The analysis revealed that PRSs, when assessed individually or in combination with conventional risk factors, significantly correlated with incident diseases, enhancing the predictive performance beyond baseline clinical risk factors alone. Notably, for diseases like CAD, T2D, and prostate cancer, PRSs offered a distinct advantage over traditional family history indicators, emphasizing their potential to complement existing risk assessment models.

Subanalyses exploring additional risk factors, such as glucose levels determined through nuclear magnetic resonance (NMR) for T2D, consistently supported the PRSs’ predictive value. The gut microbiome also emerged as a significant factor, with its composition at baseline correlating with incident diseases. The study delved into the gut microbiome’s diversity and its association with disease incidence, finding specific patterns that could potentially enhance disease prediction models.

The research underscored the potential of integrating polygenic, metagenomic, and conventional factors into a cohesive model for predicting incident diseases. Such a model, which combines PRSs and gut microbiome scores with conventional risk factors, showed a marked improvement in predictive accuracy for CAD, T2D, AD, and prostate cancer. This integrative approach illustrates the promise of multiomic data in refining disease prediction and tailoring preventive measures more effectively.

Subgroup analyses reaffirmed the significant associations between PRSs, gut microbiome scores, and disease incidence, highlighting these factors’ contributions across different conditions.

Conclusions

To summarize, this study contrasts the predictive power of well-established PRSs, baseline gut microbiome, and traditional risk factors across a median follow-up of 17.8 years. Findings reveal that while age stands as the most influential individual risk factor for CAD, AD, and prostate cancer, the inclusion of PRSs and gut microbiome scores notably enhances predictive accuracy. PRSs alone significantly correlate with higher disease incidence, underscoring their potential to augment conventional risk assessments. Furthermore, the study suggests that PRSs can refine predictions for CAD, T2D, and prostate cancer, even beyond family history’s established risk implications. Although the gut microbiome’s predictive contribution appears modest, it shows promise in enhancing disease forecasts when combined with conventional factors. The analysis points to a subtle role of the gut microbiome across different conditions, suggesting that its predictive value may vary due to the complex interplay between host aging and microbial changes.

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March 27, 2024
Study reveals e-cigarette users with limited smoking history show similar DNA alterations as smokers

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A recent Cancer Research study assessed the effect of tobacco smoking and electronic cigarette (e-cigarettes) use on DNA methylation changes associated with carcinogenesis.

Study: Cigarette smoking and e-cigarette use induce shared DNA methylation changes linked to carcinogenesis. Image Credit: Andrey_Popov/Shutterstock.com

Background

In comparison to tobacco smoking, the use of e-cigarettes and smokeless, non-combustible tobacco has often been considered to be less harmful. However, recent studies have highlighted some of the potential adverse effects linked to e-cigarette use, including DNA damage and endothelial dysfunction. Therefore, it is imperative to understand the molecular changes and their long-term effects on health.

E-cigarette use has been associated with similar biomarker changes to cigarette smoking. It is essential to identify biomarkers that indicate the risk of cancer. Some of the characteristic features that must be present in biomarkers are (a) modifiability through tobacco smoking and e-cigarette use, (b) lie in genes linked to carcinogenesis, (c) induce cancer progression in a premalignant lesion, and (d) reflective of long-term cancer risk in a surrogate tissue to aid non-invasive monitoring.

The epigenome is a set of chemical modifications of DNA or proteins linked to DNA. Many studies have elucidated the role of epigenomics in carcinogenesis. This information has helped shed light on the long-term impacts of tobacco smoking and e-cigarette use.

DNA methylation (DNAme) at the cytosine C-5 position is an epigenetic modification. Its alterations enriched in genes are associated with smoking-related diseases. Some epigenetic changes remain persistent even after smoking cessation. These biomarkers could be used as an indicator of lung cancer.

Epithelial cells that are exposed (e.g., oral mucosa and lungs) or not (e.g., cervix) to smoking or e-cigarette use are the key cells of origin for tobacco-related malignancies. Furthermore, smoking-related DNAme changes found in buccal samples are primarily of epithelial origin.

About the study

The current study addressed the aforementioned issues to understand better tissue- and cell-specific epigenetic impacts of e-cigarette or tobacco use on DNAme. It used more than 3,500 cervical, buccal/saliva, or blood samples from immune and epithelial cells at directly and indirectly exposed sites. Additionally, a control sample set was used for validation.

This study is a part of the female cancer prediction using cervical omics to individualize screening and prevention (FORECEE) study. The participants came from five European countries, were between 18 and 86 years of age, and completed an epidemiological questionnaire. The effect of tobacco use on epithelial and immune cells was analyzed systematically using computational deconvolution and cell type-specific DNAme inference.

The effect of direct (proximal) and indirect (distal) exposure to the use of smoking, smokeless tobacco (e.g., snuffs), or e-cigarettes on epithelial and immune cells was assessed. Furthermore, whether these uses also affected lung cancer tissue and prognosis were evaluated. The evaluation of the biomarkers at the cell-level is a key contribution of this study, as the majority of existing studies, including those predicting lung cancer, have used blood samples.

Study findings

The cell-specific alterations following cigarette and e-cigarette use that are associated with carcinogenesis have been uncovered in this study. Smoking was found to elicit changes in protected stem and submucosal gland cells. Cigarette smoking affected epithelial hypoM and this change was found in both proximal and distal exposure. Furthermore, DNAme alterations linked to specific proximal epithelial hyperM and distal epithelial hyperM were also identified.

Smoking was seen to affect the myeloid more prominently than the lymphoid lineage. No significant genetic overlap linked with specific functions was observed in the samples obtained from five different sites. Mostly, epithelial hypoM sites were linked with detoxification responses, whereas proximal epithelial hyperM sites entailed DNA damage responses.

The smoking-related DNAme loci (CpGs) identified here were clustered into four functional group based on anatomical site and cell type. Loci hypermethylated in cheek cells of smokers associated with the NOTCH1/RUNX3/growth factor receptor signaling showed a higher level of methylation in progressing lung carcinoma in situ lesions and cancer tissue. Alarmingly, the aforementioned CpGs were also noted to be hypermethylated in e-cigarette users who reported a limited smoking history.

This study further highlighted a partial reversibility of smoking-induced epigenetic alterations in former tobacco smokers. This observation was based on the fact that epithelial hypoM could not be distinguished between ex-smokers and those who never smoked. This observation could imply that the hypermethylated cells disappeared due to cell death or the displacement of the methyl group in the living cell.

Smokeless tobacco induces similar changes in DNAme in the epithelial hypoM and proximal epithelial hyperM sets, as cigarette smoking. It must be noted that only cigarette smokers exhibited changes in DNAme at immune hypoM sites. Proximal epithelial hypermethylation was robustly associated with lung cancer progression and cervical cancer.

Conclusions

In sum, the results presented here shed light on cell type-specific epigenetic changes following cigarette smoking. Some of these changes, which could also predict lung cancer, are similar to e-cigarette users.

A key limitation of this study was the use of pathway analysis based on gene names, which limited the investigation to cis genes alone. In the future, scientists must perform multi-omics profiling to investigate the association between methylation changes and gene transcription function more comprehensively.

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March 25, 2024