Effects of Cigarette Smoking on Transplant Survival: Extending or Shortening It?

Impact of air pollution on postoperative outcomes following organ transplantation: Evidence from clinical investigations

INTRODUCTION

Air pollution is a worldwide problem affecting human health via various body systems, resulting in numerous significant adverse events. Air pollutants, including particulate matter < or = 2.5 microns (PM2.5), particulate matter < or = 10 microns (PM10), ozone (O3 ), nitrogen dioxide (NO2 ), and traffic-related air pollution (TRAP), have demonstrated the negative effects on human health (e.g., increased cerebrovascular, cardiovascular, and respiratory diseases, malignancy, and mortality). Organ transplant patients, who are taking immunosuppressive agents, are especially vulnerable to the adverse effects of air pollutants. The evidence from clinical investigation has shown that exposure to air pollution after organ transplantation is associated with organ rejection, cardiovascular disease, coronary heart disease, cerebrovascular disease, infection-related mortality, and vitamin D deficiency.

OBJECTIVES AND METHOD

This review aims to summarize and discuss the association of exposure to air pollutants and serum 25-hydroxyvitamin D level and outcomes after transplantation. Controversial findings are also included and discussed.

CONCLUSION

All of the findings suggest that air pollution results in a hazardous environment, which not only impacts human health worldwide but also affects post-transplant outcomes.

Interpretable prediction of mortality in liver transplant recipients based on machine learning

BACKGROUND

Accurate prediction of the mortality of post-liver transplantation is an important but challenging task. It relates to optimizing organ allocation and estimating the risk of possible dysfunction. Existing risk scoring models, such as the Balance of Risk (BAR) score and the Survival Outcomes Following Liver Transplantation (SOFT) score, do not predict the mortality of post-liver transplantation with sufficient accuracy. In this study, we evaluate the performance of machine learning models and establish an explainable machine learning model for predicting mortality in liver transplant recipients.

METHOD

The optimal feature set for the prediction of the mortality was selected by a wrapper method based on binary particle swarm optimization (BPSO). With the selected optimal feature set, seven machine learning models were applied to predict mortality over different time windows. The best-performing model was used to predict mortality through a comprehensive comparison and evaluation. An interpretable approach based on machine learning and SHapley Additive exPlanations (SHAP) is used to explicitly explain the model's decision and make new discoveries.

RESULTS

With regard to predictive power, our results demonstrated that the feature set selected by BPSO outperformed both the feature set in the existing risk score model (BAR score, SOFT score) and the feature set processed by principal component analysis (PCA). The best-performing model, extreme gradient boosting (XGBoost), was found to improve the Area Under a Curve (AUC) values for mortality prediction by 6.7%, 11.6%, and 17.4% at 3 months, 3 years, and 10 years, respectively, compared to the SOFT score. The main predictors of mortality and their impact were discussed for different age groups and different follow-up periods.

CONCLUSIONS

Our analysis demonstrates that XGBoost can be an ideal method to assess the mortality risk in liver transplantation. In combination with the SHAP approach, the proposed framework provides a more intuitive and comprehensive interpretation of the predictive model, thereby allowing the clinician to better understand the decision-making process of the model and the impact of factors associated with mortality risk in liver transplantation.

The Effect of Smoking on Humoral Response to COVID-19 Vaccines: A Systematic Review of Epidemiological Studies

While the role of active smoking on response to vaccines is yet to be fully understood, some real-world studies have outlined a possible link between smoking and humoral response to COVID-19 vaccines. Thus, the present rapid systematic review aimed at summarizing the current epidemiological evidence on this association. Following PRISMA and WHO guidelines on rapid systematic reviews, we systematically reviewed published literature on this topic and discussed the findings according to the aim of analysing smoking and its impact on humoral response to COVID-19 postvaccination antibody titres. The search strategy yielded a total of 23 articles. The sample size amongst the studies ranged between 74 and 3475 participants (median, 360), with the proportion of smokers being between 4.2% and 40.8% (median, 26.0%). The studies included in this review analysis investigated the dynamics of antibody response to different type of COVID-19 vaccines. In 17 out of 23 studies, current smokers showed much lower antibody titres or more rapid lowering of the vaccine-induced IgG compared with nonsmokers. This rapid systematic review indicates that active smoking negatively impacts humoral response to COVID-19 vaccines, although the pathophysiologic mechanisms for this association have not been entirely suggested. The results advocate targeted policies to promote tailored health promotion initiatives, which can increase risk perception and ensure appropriate protection measures to be taken to avoid the health consequences of COVID-19 in smokers.

Correlation between genetic variation in thymine DNA glycosylase and smoking behavior

Cigarette smoking is a major lifestyle factor leading to different human diseases. The DNA repair gene, thymine DNA glycosylase, is important to cell survival because it stops cells from becoming cancerous protecting/preventing DNA. Exposure to CS may induce genetic changes such as single nucleotide polymorphisms in DNA repair genes. Therefore, the purpose of this study was to investigate the genotype and allele distributions of four TDG SNPs with only smoking behavior in normal patients. Four TDG SNPs-rs4135066 (C/T), rs3751209 (A/G), rs1866074 (C/T), and rs1882018 (C/T) were analyzed by genotyping 235 and 239 blood samples collected from cigarette smokers and non-smokers, among the Saudi population. The results showed that TDG rs4135066 has a significant susceptibility effect observed in long-term smokers (>5 years; OR = 4.53; P = 0.0347) but not in short-term smokers (≤5 years) in contrast with non-smokers. Also, in smokers aged less than 29 years, the "CT," "TT," and "CT + TT" alleles of rs1882018 increased the risk of developing all diseases related to smoking by approximately 6, 4, and 5 times, respectively, in contrast with the ancestral "CC" homozygous allele. A comparison of the allele distributions of TDG SNPs in a Saudi population with those in other populations represented in the HapMap project showed that the genetic makeup of the Saudi Arabian population appears to differ from that of other ethnicities. Exceptions include the Yoruba people in Ibadan, Nigeria; those of Mexican ancestry in Los Angeles, California; the Luhya population in Webuye, Kenya; Gujarati Indians in Houston, Texas; and the Tuscan population in Italy, which showed similar allelic frequencies for rs3751209 compared to our Saudi population. In this ethnic, we have found a high variation in the distribution of the alleles and genotype frequencies on TDG gene. This variation on TDG SNP's with smoking could lead to increase the susceptibility to many diseases related to smoking habits in this population.

History of cigarette smoking and heart transplant outcomes

Background: Active cigarette smoking (CS) is a contraindication for Orthotopic Heart Transplantation (OHT) with a recommendation that HT candidates be free from CS for at minimum 6 months prior to HT. Animal studies have shown that a history of CS is associated with increased risk of allograft rejection, but few studies have examined the association of past CS and HT outcomes. Methods: Data were analyzed from HT recipients captured in the United Network for Organ Sharing (UNOS) transplant registry. Adults aged 18–79 who underwent HT from 1987 to 2018 and with data for all covariates (N = 32,260) were included in this study. The cohort was categorized by past smoking history (CS vs non-CS). Post-transplant outcomes of interest included survival, graft failure, treated rejection, malignancy and hospitalization for infection. Baseline characteristics were compared between the two groups using the chi-squared analysis. Unadjusted associations between CS and patient survival were determined using the Kaplan-Meier estimations and confounding was addressed using multivariable Cox proportional hazards models. Results: HT recipients with a history of CS were older (55 vs 50, p = <0.0001), more likely to be Caucasian (75.7 vs 62.3, p = <0.0001), male (81.7 vs 68.2, p =< 0.0001), and diabetic (27.4 vs 24.4, p =< 0.0001). CS was associated with significantly worse survival (HR: 1.23, p < 0.0001). A history of CS was also associated with increased risk of acute rejection (OR: 1.20, p < 0.0001), hospitalization for infection (OR:1.24, p < 0.0001), graft failure (OR:1.23, p < 0.0001) and post-transplant malignancy (OR:1.43, p < 0.0001). Conclusion: A history of CS is associated with increased risk of adverse events post OHT.

TSLP and TSLP receptors variants are associated with smoking

Background

To search for new prevention markers for early detection of the diseases caused by tobacco, we aimed to investigate the polymorphisms in TSLP and TSLPRs associated with cigarette smoking in the Saudi population.

Materials and methods

Samples were collected from 177 smokers and 126 healthy controls. Three TSLP SNPs [rs3806933, rs2289276, and rs10043985], three TSLPR SNPs [rs36133495, rs36177645, and rs36139698], and two IL7R SNPs rs1053496 and rs12516866 were analyzed by genotyping.

Results

Two TSLP SNPs (rs10043985 and rs3806933) and one TSLPR SNP (rs36139698) showed significant correlations with smoking behavior, but not IL7R rs12516866 and rs1053496. rs10043985 showed a clear association with long‐term smoking regardless of daily cigarette consumption. rs2289276 was associated with short‐term smoking but not with daily cigarette consumption. rs3806933 was highly associated with different smoker subgroups. Rs36139698 was highly associated with long‐term smokers who consumed ≥20 cigarettes/day, and the “T” allele was associated only with individuals who smoked ≤20 cigarettes/day. Rs36139698 corresponds to a P195L substitution and produces a TSLPR mutant with a predicted ΔΔG increase of 2.15 kcal/mol and has a more stable structure than the wild‐type variant.

Conclusions

Investigating TSLP and TSLPR polymorphisms is crucial for elucidating the mechanisms underlying tobacco‐induced diseases.

Effect of the thymine-DNA glycosylase rs4135050 variant on Saudi smoker population

Background

Thymine‐DNA glycosylase (TDG) is an essential DNA‐repair enzyme which works in both epigenetic regulation and genome maintenance. It is also responsible for efficient correction of multiple endogenous DNA lesions which occur commonly in mammalian genomes. Research of genetic variants such as SNPs, resulting in disease, is predicted to yield clinical advancements through the identification of sensitive genetic markers and the development of disease prevention and therapy. To that end, the main objective of the present study is to identify the possible interactions between cigarette smoking and the rs4135050 variant of the TDG gene, situated in the intron position, among Saudi individuals.

Methods

TDG rs4135050 (A/T) was investigated by genotyping 239, and 235 blood specimens were obtained from nonsmokers and smokers of cigarette respectively.

Results

T allele frequency was found which showed a significant protective effect on Saudi male smokers (OR = 0.64, p = 0.0187) compared to nonsmoking subjects, but not in female smokers. Furthermore, smokers aged less than 29 years, the AT and AT+TT genotypes decreased more than four times the risk of initiation of smoking related‐diseases compare to the ancestral AA homozygous genotype. Paradoxically, the AT (OR = 3.88, p = 0.0169) and AT+TT (OR = 2.86, p = 0.0420) genotypes were present at a higher frequency in smoking patients aged more than 29 years as compared to nonsmokers at the same ages.

Conclusion

Depending on the gender and age of patients, TDG rs4135050 may provide a novel biomarker for the early diagnosis and prevention of several diseases caused by cigarette smoking.