Smoking-related dysregulation of plasma circulating microRNAs:the Rotterdam study

Background: MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression. Differential miRNA expression, which is widely shown to be associated with the pathogenesis of various diseases, can be influenced by lifestyle factors, including smoking. This study aimed to investigate the plasma miRNA signature of smoking habits, the potential effect of smoking cessation on miRNA levels, and relate the findings with lung cancer incidence. Results: A targeted RNA-sequencing approach measured plasma miRNA levels in 2686 participants from the population-based Rotterdam study cohort. The association between cigarette smoking (current versus never) and 591 well-expressed miRNAs was assessed via adjusted linear regression models, identifying 41 smoking-associated miRNAs that passed the Bonferroni-corrected threshold (P &lt; 0.05/591 = 8.46 × 10–5). Moreover, we found 42 miRNAs with a significant association (P &lt; 8.46 × 10–5) between current (reference group) and former smokers. Then, we used adjusted linear regression models to explore the effect of smoking cessation time on miRNA expression levels. The expression levels of two miRNAs were significantly different within 5 years of cessation (P &lt; 0.05/41 = 1.22 × 10–3) from current smokers, while for cessation time between 5 and 15 years we found 19 miRNAs to be significantly different from current smokers, and finally, 38 miRNAs were significantly different after more than 15 years of cessation time (P &lt; 1.22 × 10–3). These results imply the reversibility of the smoking effect on plasma levels of at least 38 out of the 41 smoking-miRNAs following smoking cessation. Next, we found 8 out of the 41 smoking-related miRNAs to be nominally associated (P &lt; 0.05) with the incidence of lung cancer. Conclusions: This study demonstrates smoking-related dysregulation of plasma miRNAs, which might have a potential for reversibility when comparing different smoking cessation groups. The identified miRNAs are involved in several cancer-related pathways and include 8 miRNAs associated with lung cancer incidence. Our results may lay the groundwork for further investigation of miRNAs as potential mechanism linking smoking, gene expression and cancer.</p

Plasma MicroRNA Signature of Alcohol Consumption: The Rotterdam Study

Background: MicroRNAs (miRNAs) represent a class of noncoding RNAs that regulate gene expression and are implicated in the pathogenesis of different diseases. Alcohol consumption might affect the expression of miRNAs, which in turn could play a role in risk of diseases.Objectives: We investigated whether plasma concentrations of miRNAs are altered by alcohol consumption. Given the existing evidence showing the link between alcohol and liver diseases, we further explored the extent to which these associations are mediated by miRNAs.Methods: Profiling of plasma miRNAs was conducted using the HTG EdgeSeq miRNA Whole Transcriptome Assay in 1933 participants of the Rotterdam Study. Linear regression was implemented to explore the link between alcohol consumption (glasses/d) and miRNA concentrations, adjusted for age, sex, cohort, BMI, and smoking. Sensitivity analysis for alcohol categories (nondrinkers, light drinkers, and heavy drinkers) was performed, where light drinkers corresponded to 0–2 glasses/d in men and 0–1 glasses/d in women, and heavy drinkers to >2 glasses/d in men and >1 glass/d in women. Moreover, we utilized the alcohol-associated miRNAs to explore their potential mediatory role between alcohol consumption and liver-related traits. Finally, we retrieved putative target genes of identified miRNAs to gain an understanding of the molecular pathways concerning alcohol consumption.Results: Plasma concentrations of miR-193b-3p, miR-122-5p, miR-3937, and miR-4507 were significantly associated with alcohol consumption surpassing the Bonferroni-corrected P Conclusions: This study indicates that alcohol consumption is associated with plasma concentrations of 4 miRNAs. We outline a potential mediatory role of 2 alcohol-associated miRNAs (miR-3937 and miR-122-5p), laying the groundwork for further exploration of miRNAs as potential mediators between lifestyle factors and disease development

Plasma MicroRNA Signature of Alcohol Consumption: The Rotterdam Study

BACKGROUND: MicroRNAs (miRNAs) represent a class of noncoding RNAs that regulate gene expression and are implicated in the pathogenesis of different diseases. Alcohol consumption might affect the expression of miRNAs, which in turn could play a role in risk of diseases. OBJECTIVES: We investigated whether plasma concentrations of miRNAs are altered by alcohol consumption. Given the existing evidence showing the link between alcohol and liver diseases, we further explored the extent to which these associations are mediated by miRNAs. METHODS: Profiling of plasma miRNAs was conducted using the HTG EdgeSeq miRNA Whole Transcriptome Assay in 1933 participants of the Rotterdam Study. Linear regression was implemented to explore the link between alcohol consumption (glasses/d) and miRNA concentrations, adjusted for age, sex, cohort, BMI, and smoking. Sensitivity analysis for alcohol categories (nondrinkers, light drinkers, and heavy drinkers) was performed, where light drinkers corresponded to 0-2 glasses/d in men and 0-1 glasses/d in women, and heavy drinkers to >2 glasses/d in men and >1 glass/d in women. Moreover, we utilized the alcohol-associated miRNAs to explore their potential mediatory role between alcohol consumption and liver-related traits. Finally, we retrieved putative target genes of identified miRNAs to gain an understanding of the molecular pathways concerning alcohol consumption. RESULTS: Plasma concentrations of miR-193b-3p, miR-122-5p, miR-3937, and miR-4507 were significantly associated with alcohol consumption surpassing the Bonferroni-corrected P < 8.46 × 10-5. The top significant association was observed for miR-193b-3p (β = 0.087, P = 2.90 × 10-5). Furthermore, a potential mediatory role of miR-3937 and miR-122-5p was observed between alcohol consumption and liver traits. Pathway analysis of putative target genes revealed involvement in biological regulation and cellular processes. CONCLUSIONS: This study indicates that alcohol consumption is associated with plasma concentrations of 4 miRNAs. We outline a potential mediatory role of 2 alcohol-associated miRNAs (miR-3937 and miR-122-5p), laying the groundwork for further exploration of miRNAs as potential mediators between lifestyle factors and disease development

Targeted DNA methylation analysis and prediction of smoking habits in blood based on massively parallel sequencing

Tobacco smoking is a frequent habit sustained by > 1.3 billion people in 2020 and the leading preventable factor for health risk and premature mortality worldwide. In the forensic context, predicting smoking habits from biological samples may allow broadening DNA phenotyping. In this study, we aimed to implement previously published smoking habit classification models based on blood DNA methylation at 13 CpGs. First, we developed a matching lab tool based on bisulfite conversion and multiplex PCR followed by amplification-free library preparation and targeted paired-end massively parallel sequencing (MPS). Analysis of six technical duplicates revealed high reproducibility of methylation measurements (Pearson correlation of 0.983). Artificially methylated standards uncovered marker-specific amplification bias, which we corrected via bi-exponential models. We then applied our MPS tool to 232 blood samples from Europeans of a wide age range, of which 90 were current, 71 former and 71 never smokers. On average, we obtained 189,000 reads/sample and 15,000 reads/CpG, without marker drop-out. Methylation distributions per smoking category roughly corresponded to previous microarray analysis, showcasing large inter-individual variation but with technology-driven bias. Methylation at 11 out of 13 smoking-CpGs correlated with daily cigarettes in current smokers, while solely one was weakly correlated with time since cessation in former smokers. Interestingly, eight smoking-CpGs correlated with age, and one displayed weak but significant sex-associated methylation differences. Using bias-uncorrected MPS data, smoking habits were relatively accurately predicted using both two- (current/non-current) and three- (never/former/current) category model, but bias correction resulted in worse prediction performance for both models. Finally, to account for technology-driven variation, we built new, joint models with inter-technology corrections, which resulted in improved prediction results for both models, with or without PCR bias correction (e.g. MPS cross-validation F1-score > 0.8; 2-categories). Overall, our novel assay takes us one step closer towards the forensic application of viable smoking habit prediction from blood traces. However, future research is needed towards forensically validating the assay, especially in terms of sensitivity. We also need to further shed light on the employed biomarkers, particularly on the mechanistics, tissue specificity and putative confounders of smoking epigenetic signatures

Validating biomarkers and models for epigenetic inference of alcohol consumption from blood

BACKGROUND: Information on long-term alcohol consumption is relevant for medical and public health research, disease therapy, and other areas. Recently, DNA methylation-based inference of alcohol consumption from blood was reported with high accuracy, but these results were based on employing the same dataset for model training and testing, which can lead to accuracy overestimation. Moreover, only subsets of alcohol consumption categories were used, which makes it impossible to extrapolate such models to the general population. By using data from eight population-based European cohorts (N = 4677), we internally and externally validated the previously reported biomarkers and models for epigenetic inference of alcohol consumption from blood and developed new models comprising all data from all categories. RESULTS: By employing data from six European cohorts (N = 2883), we empirically tested the reproducibility of the previously suggested biomarkers and prediction models via ten-fold internal cross-validation. In contrast to previous findings, all seven models based on 144-CpGs yielded lower mean AUCs compared to the models with less CpGs. For instance, the 144-CpG heavy versus non-drinkers model gave an AUC of 0.78 ± 0.06, while the 5 and 23 CpG models achieved 0.83 ± 0.05, respectively. The transportability of the models was empirically tested via external validation in three independent European cohorts (N = 1794), revealing high AUC variance between datasets within models. For instance, the 144-CpG heavy versus non-drinkers model yielded AUCs ranging from 0.60 to 0.84 between datasets. The newly developed models that considered data from all categories showed low AUCs but gave low AUC variation in the external validation. For instance, the 144-CpG heavy and at-risk versus light and non-drinkers model achieved AUCs of 0.67 ± 0.02 in the internal cross-validation and 0.61–0.66 in the external validation datasets. CONCLUSIONS: The outcomes of our internal and external validation demonstrate that the previously reported prediction models suffer from both overfitting and accuracy overestimation. Our results show that the previously proposed biomarkers are not yet sufficient for accurate and robust inference of alcohol consumption from blood. Overall, our findings imply that DNA methylation prediction biomarkers and models need to be improved considerably before epigenetic inference of alcohol consumption from blood can be considered for practical applications. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13148-021-01186-3

Growing knowledge: an overview of Seed Plant diversity in Brazil

Abstract An updated inventory of Brazilian seed plants is presented and offers important insights into the country's biodiversity. This work started in 2010, with the publication of the Plants and Fungi Catalogue, and has been updated since by more than 430 specialists working online. Brazil is home to 32,086 native Angiosperms and 23 native Gymnosperms, showing an increase of 3% in its species richness in relation to 2010. The Amazon Rainforest is the richest Brazilian biome for Gymnosperms, while the Atlantic Rainforest is the richest one for Angiosperms. There was a considerable increment in the number of species and endemism rates for biomes, except for the Amazon that showed a decrease of 2.5% of recorded endemics. However, well over half of Brazillian seed plant species (57.4%) is endemic to this territory. The proportion of life-forms varies among different biomes: trees are more expressive in the Amazon and Atlantic Rainforest biomes while herbs predominate in the Pampa, and lianas are more expressive in the Amazon, Atlantic Rainforest, and Pantanal. This compilation serves not only to quantify Brazilian biodiversity, but also to highlight areas where there information is lacking and to provide a framework for the challenge faced in conserving Brazil's unique and diverse flora