Heavy smoking can have a damaging effect on facial aging

Summary: In addition to being detrimental to general health, heavy smoking has a causal effect on facial aging. Heavy smoking affects facial attractiveness and spurs earlier and increased skin wrinkling.

Source: University of Bristol

Heavy smoking may have a causal effect on facial ageing, according to new research led by the University of Bristol. The study searched across 18,000 traits from the UK Biobank cohort to identify those that may be affected by how heavily someone smokes. As well as recognising several known adverse effects such as on lung health, the research also found heavy smoking could influence appearance.

The study, published in PLOS Genetics today, was led by the University’s MRC Integrative Epidemiology Unit (IEU) and also supported by the NIHR Bristol Biomedical Research Centre (BRC).

The researchers wanted to demonstrate a new approach that could be used to systematically test for causal effects across thousands of outcomes, by combining two existing methods: the Mendelian randomization phenome-wide association study approach and gene-by-environment interaction tests. To test their new method, the Bristol team searched for the effects of heavy smoking using the UK Biobank cohort.

The research team found their approach worked, as their results included several known effects of heavier smoking e.g. on lung function. They also identified an interesting potential effect of heavier smoking on more facial ageing.

Their finding adds to evidence that found heavier smoking affects facial attractiveness and the amount of wrinkling, which might be reasons to encourage someone to stop smoking or deter them from starting in the first place.

By showing that the approach works, it could be used to search for the effects of other exposures, such as alcohol intake.

Dr Louise Millard, Vice Chancellor’s Research Fellow in the Bristol Medical School: Population Health Sciences (PHS) who led the research, said: “We proposed a novel approach that could be used to search for causal effects of health exposures, and demonstrated this approach to search for the effects of smoking heaviness. We searched across thousands of traits to identify those that may be affected by how heavily someone smokes. As well as identifying several known adverse effects such as on lung health, we also identified an adverse effect of heavier smoking on facial aging.”

Mendelian randomization is a technique that uses genetic variation in a person’s DNA to help understand the causal relationships between risk factors and health outcomes – here whether how heavily someone smokes causally affects health outcomes.

This shows a smokey face

The research team found their approach worked, as their results included several known effects of heavier smoking e.g. on lung function. They also identified an interesting potential effect of heavier smoking on more facial ageing. The image is in the public domain.

However, Mendelian randomization is biased if the genetic variant also affects the outcome via other pathways. The research team used additional information – that the effect of heavy smoking only occurs in people who actually smoke – to overcome this problem. By testing associations in ever and never smokers separately they were able to assess whether the genetic variant affects an outcome via smoking or another pathway. If the effect is at least partially via smoking heaviness, the researchers would expect the effect to differ in ever versus never smokers, and this would suggest that smoking causally influences the outcome.

Further work is needed to find out whether being told that smoking could affect appearance is an effective strategy for smoking prevention or stopping.

About this neuroscience research article

Source:
University of Bristol
Media Contacts:
Caroline Clancy – University of Bristol
Image Source:
The image is in the public domain.

Original Research: Open access
“MR-pheWAS with stratification and interaction: Searching for the causal effects of smoking heaviness identified an effect on facial aging”. Louise A C Millard, Marcus R Munafò, Kate Tilling, Robyn E Wootton, George Davey Smith.
PLOS Genetics doi:10.1371/journal.pgen.1008353.

Abstract

MR-pheWAS with stratification and interaction: Searching for the causal effects of smoking heaviness identified an effect on facial aging

Mendelian randomization (MR) is an established approach to evaluate the effect of an exposure on an outcome. The gene-by-environment (GxE) study design can be used to determine whether the genetic instrument affects the outcome through pathways other than via the exposure of interest (horizontal pleiotropy). MR phenome-wide association studies (MR-pheWAS) search for the effects of an exposure, and can be conducted in UK Biobank using the PHESANT package. In this proof-of-principle study, we introduce the novel GxE MR-pheWAS approach, that combines MR-pheWAS with the use of GxE interactions. This method aims to identify the presence of effects of an exposure while simultaneously investigating horizontal pleiotropy. We systematically test for the presence of causal effects of smoking heaviness–stratifying on smoking status (ever versus never)–as an exemplar. If a genetic variant is associated with smoking heaviness (but not smoking initiation), and this variant affects an outcome (at least partially) via tobacco intake, we would expect the effect of the variant on the outcome to differ in ever versus never smokers. We used PHESANT to test for the presence of effects of smoking heaviness, instrumented by genetic variant rs16969968, among never and ever smokers respectively, in UK Biobank. We ranked results by the strength of interaction between ever and never smokers. We replicated previously established effects of smoking heaviness, including detrimental effects on lung function. Novel results included a detrimental effect of heavier smoking on facial aging. We have demonstrated how GxE MR-pheWAS can be used to identify potential effects of an exposure, while simultaneously assessing whether results may be biased by horizontal pleiotropy.

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