Rxivist combines preprints from bioRxiv with data from Twitter to help you find the papers being discussed in your field. Currently indexing 73,690 bioRxiv papers from 320,698 authors.

Tobacco smoking is a risk factor for multiple diseases, including cardiovascular disease and diabetes. Many smoking-associated signals have been detected in the blood methylome, but the extent to which these changes are widespread to metabolically relevant tissues, and impact gene expression or cardio-metabolic health, remains unclear. We investigated smoking-associated DNA methylation and gene expression variation in adipose tissue from 542 healthy female twins with available well-characterized cardio-metabolic phenotype profiles. We identified 42 smoking-methylation and 42 smoking-expression signals, where five genes (AHRR, CYP1A1, CYP1B1, CYTL1, F2RL3) were both hypo-methylated and up-regulated in smokers. We replicated and validated a proportion of the signals in blood, adipose, skin, and lung tissue datasets, identifying tissue-shared effects. Smoking leaves systemic imprints on DNA methylation after smoking cessation, with stronger but shorter-lived effects on gene expression. We tested for associations between the observed smoking signals and several adiposity phenotypes that constitute cardio-metabolic disease risk. Visceral fat and android/gynoid ratio were associated with methylation at smoking-markers with functional impacts on expression, such as CYP1A1, and in signals shared across tissues, such as NOTCH1. At smoking-signals BHLHE40 and AHRR DNA methylation and gene expression levels in current smokers were predictive of future gain in visceral fat upon smoking cessation. Our results provide the first comprehensive characterization of coordinated DNA methylation and gene expression markers of smoking in adipose tissue, a subset of which link to human cardio-metabolic health and may give insights into the wide-ranging risk effects of smoking across the body.

Download data

• Downloaded 391 times
• Download rankings, all-time:
  • Site-wide: 31,978 out of 73,697
  • In genomics: 3,161 out of 4,889
• Year to date:
  • Site-wide: 53,574 out of 73,697
• Since beginning of last month:
  • Site-wide: 53,574 out of 73,697

Altmetric data

Downloads over time

Distribution of downloads per paper, site-wide