Understanding associations between smoking behaviour and poorer health: conventional and Mendelian randomization approaches

Jareebi, Mohammad A. (2022) Understanding associations between smoking behaviour and poorer health: conventional and Mendelian randomization approaches. PhD thesis, University of Glasgow.

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Background: Cigarette smoking is the leading preventable risk factor of morbidity and mortality in the world. Many studies have examined the association between smoking and health outcomes. Observational, cross-sectional studies can be confounded, and hence the casualty of associations between smoking and health outcomes cannot be established. A genetic epidemiological approach such as Mendelian randomization (MR) can be informative concerning potential causal associations between smoking and health outcomes. MR leverages the availability of genetic data on smoking and health outcomes to estimate confounder-free associations. The current thesis was carried out to investigate the observational and causal associations between smoking behaviour and cardiometabolic diseases, stroke, and lipid biomarkers.

Methods: Firstly, detailed reviews of prior research were conducted, highlighting that the majority of previous research was observational in nature. The thesis utilised the relatively large sample of UK Biobank (N=~502k) to conduct observational as well as MR-based analyses. The observational approach was based on self-report for multiple smoking phenotypes (smoking status, smoking intensity, and age at smoking initiation), clinical diagnoses for cardiometabolic diseases (CMDs; coronary heart disease (CHD), hypertension (HTN), and diabetes mellitus (DM)), stroke, and lipid biomarkers (total cholesterol, low-density lipoproteins, triglycerides, and high-density lipoproteins). The genetic analysis was based on 14 single-nucleotide polymorphisms (SNPs) for smoking intensity (cigarettes smoked per day: CperD) and 15 SNPs for smoking history. The genetic analysis was conducted in the UK Biobank sample (one-sample MR) as well as publicly available ‘summary statistic’ genetic data (two-sample MR). The analyses were conducted using R software and the MR-Base platform.

Results: Observationally (analysis: chapter four), current smokers had a higher risk of CHD (odds ratio [OR]: 1.61, P<0.001), stroke (OR: 1.64, P<0.001), and DM (OR: 1.12, P<0.001), and lower risk for HTN (OR=0.89, P<0.001) compared to never smokers. Additionally, as individuals smoke one more cigarette per day on average (smoking intensity), the risk for all CMDs increases (CHD, stroke, and HTN: OR=1.01, DM: 1.02, all P<0.001 per average daily cigarette). Finally, as an individual initiates smoking one year later in life, the risk of all CMDs decreases except for HTN (CHD and stroke: OR = 0.96, P<0.001, DM: OR=0.99, P>0.05, and HTN: 1.01, P<0.001). For lipid biomarkers (analysis: chapter five), current smokers showed higher levels of cholesterol (β: 0.05 mmol/L, P<0.001), LDL (β: 0.06 mmol/L, P<0.001), and TG (β: 0.09 mmol/L, P<0.001), and lower level of HDL (β=-0.14 mmol/L, P<0.001) compared to never smokers. Similarly, as individuals smoke one more cigarette per day (smoking intensity), the levels of cholesterol, LDL, and TG increase, and the level of HDL decreases (cholesterol: β=0.02 mmol/L, LDL: β=0.03 mmol/L, TG: β=0.02 mmol/L, and HDL: β=-0.04 mmol/L, all P<0.001). Lastly, as an individual starts to smoke one year later in life, the levels of all lipid biomarkers increase except for TG (cholesterol: β=0.01 mmol/L, P=0.026, LDL: β=0.001 mmol/L, P>0.05, TG: β=-0.01 mmol/L, P<0.001, HDL: β=0.04 mmol/L, P<0.001). In terms of MR-based causal estimates (analysis: chapter four), there was no evidence of any causal relationship between smoking behaviour variables with CHD, stroke, and lipid biomarkers (analysis: chapter five) in the UK Biobank sample (one-sample MR) nor in other samples or approaches (summary-level in MR-Base platform or R). The only significant causal associations were observed in two isolated MR analyses; one between smoking status (ever) and HTN in one sample MR in the UKB sample and the other was between smoking intensity (CperD) and DM in two sample MR in R.

Conclusion: The observational findings indicated that cigarette smoking increases the risk of CHD, stroke, DM, and levels of total cholesterol, LDL, and TG observationally, but this was not supported by ‘causal’ genetic evidence. Smoking behaviour seems to be associated with lower blood pressure (observationally and genetically) and HDL levels (observationally, not genetically). Finally, findings on HTN, cholesterol, LDL, and HDL have varied depending on the smoking variable. These ambiguous findings point toward some of smoking’s association with poorer health perhaps being due to poor lifestyle generally and not smoking itself in isolation. Evidence of potentially protective findings of smoking is likely to be driven by instrumentation or attrition bias. More research is needed to meticulously determine the impact of each smoking variable on health outcomes, both observationally and genetically.

Item Type: Thesis (PhD)
Qualification Level: Doctoral
Keywords: Smoking behaviour, cardiometabolic disease, stroke, lipid biomarkers, Mendelian randomization, UKB.
Subjects: R Medicine > RA Public aspects of medicine
R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Colleges/Schools: College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > Public Health
Supervisor's Name: Lyall, Dr. Donald
Date of Award: 2022
Depositing User: Theses Team
Unique ID: glathesis:2022-83357
Copyright: Copyright of this thesis is held by the author.
Date Deposited: 13 Jan 2023 09:13
Last Modified: 13 Jan 2023 09:23
Thesis DOI: 10.5525/gla.thesis.83357
URI: http://theses.gla.ac.uk/id/eprint/83357

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