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Clinical risk factors for smoking-related neurobiological damage
Catherine A Spilling1, Mohani-Preet K Bajaj1, Daniel R Burrage2, Sachelle Ruickbie3, Emma H Baker2, Thomas R Barrick1, and Paul W Jones2
1Neurosciences Research Centre, Molecular and Clinical Sciences Research Institute, St George's University of London, London, United Kingdom, 2Institute for Infection and Immunity, St George's University of London, London, United Kingdom, 3Respiratory Medicine, St George's University Hospital NHS Foundation Trust, London, United Kingdom

Synopsis

Elderly cigarette smokers have an elevated risk of cognitive decline and neurological disease, however, the pathophysiological mechanisms are unclear. This study investigated which biological factors are responsible. 100 participants (age: 68±8 years, 69% male) with significant smoking history and range of respiratory and cardiovascular disease were recruited. Multiple linear regression showed that higher blood pressure, reduced respiratory function, hypoperfusion and biomarkers of cardiac (troponin T) damage and systemic inflammation (C-reactive protein) were associated with brain magnetic resonance markers of neurobiological damage and there may be complex interactions between them. Results support a vascular aetiology with contributions from systemic inflammation.

INTRODUCTION

Elderly cigarette smokers have an elevated risk of cognitive decline and neurological disease.1 Previous magnetic resonance (MR) studies show that smoking is associated with progression of white matter hyperintensities (WMHs), 2 global and local reductions in cortical and subcortical grey matter3 and microstructural abnormalities.4 The neuropathological mechanisms are unclear, however smoking has known adverse effects on the cardiovascular system, causes systemic inflammation and oxidative stress5-7 and leads to medical conditions including Chronic Obstructive Pulmonary Disease (COPD) and Coronary Artery Disease, which are themselves linked with cognitive impairment and brain change.8,9 This study investigated the relationship between biological risk factors and neurobiological damage in an elderly cohort with significant history of smoking and range of airflow limitation and cardiovascular disease.

METHODS

100 participants with significant smoking history (age: 68±8 years, 69% male, >10 pack years smoking). Demographic, clinical and biochemical markers assessing respiratory function, oxygen saturations, blood pressure, aortic stiffness (pulse wave velocity and augmentation index), breathlessness, COPD disease status, psychological status, cognitive impairment, systemic inflammation (high-sensitivity C-reactive protein, hs-CRP, fibrinogen, neutrophils) and cardiac damage (troponin T) were acquired. Retinal fundus photography provided measures of retinal microcirculation. Whole-brain T1-weighted (T1W), Fluid-attenuated Inversion Recovery (FLAIR), Diffusion Tensor Imaging (DTI) and pseudo-continuous arterial spin labelling (pCASL) scans were acquired using a 3-Tesla Phillips Achieva dual TX MR system. Measures of cerebral atrophy, WMH volume, white matter microstructural damage (fractional anisotropy and mean diffusivity) and cerebral blood flow (CBF) were computed. All analyses controlled for age and sex. Principal component analysis was used to reduce brain, retinal, cardiovascular, and respiratory variables into components. Relationships between clinical measures and brain variables and components were tested using Pearson’s correlations and multiple linear regression. Multivariate relationships were plotted on three-dimensional polynomial surface diagrams.

RESULTS

Principal components representing cerebral atrophy, white matter microstructural damage, retinal vessel calibre, retinal vessel tortuosity, respiratory function and blood pressure were extracted. Inflammatory markers did not form a component. A large number of correlations were found between clinical and brain MR measures (Figures 1 and 2). Multiple linear regression showed that higher blood pressure (p=0.013), troponin T (p=0.041) and lower respiratory function (p=0.010) were independent predictors of greater white matter microstructural damage. Higher hs-CRP independently predicted WMH volume (p=0.004) and lower CBF (p<0.001) independently predicted cerebral atrophy. Multivariate relationships are shown in Figure 3. High blood pressure and low lung function appeared to have an additive effect on white matter microstructural damage. Whereas high blood pressure and high troponin were individually associated with greater white matter microstructural damage but did not have an additive effect. Similarly, high troponin and low respiratory function individually were associated with greater white matter microstructural damage but did not have an additive effect.

DISCUSSION

Independent associations between higher blood pressure, higher troponin T, lower respiratory function and greater white matter microstructural damage are consistent with a vascular aetiology for smoking-related neurobiological decline. Cigarette smoking and hypertension are established risk factors for cardiovascular disease.10,11 Associations have also been reported between raised blood pressure, cardiac troponins, reduced respiratory function (or presence of COPD) and several MR markers of cerebral small vessel disease (CSVD).12-14 Prolonged hypertension promotes vessel wall remodelling and endothelial dysfunction, 15 compromising autoregulation and leaving the brain vulnerable to hypoperfusion or oxygen desaturation e.g. due to lung disease.15 This is consistent with this study's finding of an additive effect of high blood pressure and reduced respiratory function on white matter microstructural damage. Chronic low-level troponin release may be symptomatic of diffuse subclinical small vessel heart disease, 16 suggesting vascular disease may be affecting multiple end-organs.17

The independent association between hs-CRP and WMH volume is consistent with previous studies showing relationships between serum CRP or upregulation of inflammation-related genes, and markers of CSVD.18,19 It is presently unknown whether systemic inflammation has an aetiological role in CSVD or is an epiphenomenon.

The independent association between lower CBF and cerebral atrophy adds to a large body of evidence showing the adverse effects of reduced CBF on brain structure.20,21 This study’s cross-sectional design does not allow the direction of causality to be determined. However, global22 and regional reductions in CBF are known to occur in chronic smokers, 23 with proposed mechanisms including smoking-induced oxidative stress and endothelial dysfunction, nitric oxide vasodilatation, neurovascular coupling, hypocapnia, and autoregulatory dysfunction.23 Furthermore, aberrant vascular autoregulation, for example, as a result of CSVD or atherosclerosis is likely to exacerbate hypoperfusion and cerebral atrophy.

CONCLUSION

This study provided a cross-sectional investigation of the relationship between a range of biological risk factors for neurobiological damage in an elderly cohort with significant history of cigarette smoking and range of airflow limitation and cardiovascular disease. Higher blood pressure, serum troponin T and lower respiratory function appear to be independent and possibly additive risk factors for white matter microstructural damage. Associations were also found between higher serum hs-CRP and greater WMH volume and between lower CBF function and cerebral atrophy. This suggests that multiple preventative or therapeutic interventions are required to target a range of pathophysiological mechanisms in any attempts to reduce neurobiological decline and the development of cognitive impairment people with a history of smoking.

Acknowledgements

This study was partially funded as part of a National Institute for Health Research (NIHR) clinical doctoral fellowship: DRF-2016-09-088.

References

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Figures

Figure 1 – Network graph showing correlations between clinical measures and brain measures. (A) Whole network (B-D) subnetworks showing connections between measures which correlate with cerebral atrophy (green), WMH volume (blue) and white matter microstructural damage (orange). Line thickness = strength of correlation, solid line = significant (p < 0.05), dashed line = approaching significance (0.05 > p <0.10). Results are uncorrected for multiple comparisons See Figure 2 for abbreviations.

Figure 2 – list of abbreviations for the clinical and brain measures included in the network graph diagram (Figure 1). †Principal component.

Figure 3 - surface diagrams representing the relationship between (A) respiratory function, blood pressure and white matter microstructural damage, (B) respiratory function, troponin T and white matter microstructural damage (C) blood pressure, troponin T and white matter microstructural damage. Data are z-transformed. Polynomial surfaces are fitted with a maximum of two degrees of freedom in x and y. Goodness of fit is indicated by adjusted r2 (adj. r2) and root mean square error (RMSE).

Proc. Intl. Soc. Mag. Reson. Med. 28 (2020)
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