Biomarkers of Potential Harm: Summary of an FDA-Sponsored Public Workshop

Abstract

Introduction

Since 2009, the United States (US) Food and Drug Administration (FDA) Center for Tobacco Products (CTP) has had the authority to regulate the manufacture, distribution, and marketing of tobacco products in order to reduce the death and disease caused by tobacco use. Biomarkers could play an important role across a number of FDA regulatory activities, including assessing new and modified risk tobacco products and identifying and evaluating potential product standards.

Methods

On April 4–5, 2016, FDA/CTP hosted a public workshop focused on biomarkers of potential harm (BOPH) with participants from government, industry, academia, and other organizations. The workshop was divided into five sessions focused on: (1) overview of BOPH; (2) cardiovascular disease (CVD); (3) chronic obstructive pulmonary disease (COPD); (4) cancer; and (5) new areas of research.

Results and Conclusions

The deliberations from the workshop noted some promising BOPH but also highlighted the lack of systematic effort to identify BOPH that would have utility and validity for evaluating tobacco products. Research areas that could further strengthen the applicability of BOPH to tobacco regulatory science include the exploration of composite biomarkers as predictors of disease risk, “omics” biomarkers, and examining biomarkers using existing cohorts, surveys, and experimental studies.

Implications

This paper synthesizes the main findings from the 2016 FDA-sponsored workshop focused on BOPH and highlights research areas that could further strengthen the science around BOPH and their applicability to tobacco regulatory science.

Introduction

The United States (US) Food and Drug Administration (FDA) Center for Tobacco Products (CTP), established in 2009 by the Family Smoking Prevention and Tobacco Control Act (Tobacco Control Act), has the broad authority to regulate the manufacturing, distribution, and marketing of tobacco products with the ultimate goal of reducing harm caused by tobacco use.¹ Under the 2009 Tobacco Control Act, FDA immediately regulated cigarettes, roll-your-own tobacco and smokeless tobacco. In 2016, FDA finalized a rule extending the FDA’s authority to regulate all tobacco products, including electronic nicotine delivery systems (ENDS), cigars, hookah tobacco, pipe tobacco and nicotine gels, and any future tobacco products.² Although the health risks of cigarettes and, to a lesser extent, other traditional tobacco products have been well characterized, less is known about the health risks of more novel combustible and noncombustible tobacco products that have been introduced in recent years. FDA’s regulatory authorities include the review of premarket tobacco product applications and modified risk tobacco product applications, as well as, setting tobacco product standards. FDA uses a population health standard to make regulatory decisions by taking into account the benefits and risks of the product to both users and nonusers of tobacco products and assessing the “net” population-level health impacts of tobacco products.

Biomarkers can play an important role in characterizing the potential health risks of tobacco products, and, therefore, help assess the impact of FDA actions on the population health. In the 2001 Institute of Medicine report Clearing the Smoke, biomarkers of potential harm (BOPH) are defined as the “measurement of an effect due to exposure; these include early biological effects, alterations in morphology, structure, or function, and clinical symptoms consistent with harm; also includes ‘preclinical changes’”.³ Although clinical outcomes such as cancer, cardiovascular disease (CVD), and chronic obstructive pulmonary disease (COPD) are definitive endpoints, they take decades to develop and thus are not always practical to quickly assess in the premarket regulatory setting. BOPH could serve as more intermediate endpoints for assessing potential health risk of new and novel tobacco products in the absence of long-term epidemiological evidence.³ However, as stated in the 2001 IOM report, “Few specific early indicators of biomarkers have been validated as predictive of later disease development.”³ To understand the current state of the science on BOPH, the FDA invited experts in the field to participate in a public workshop. This report is an integration of the different viewpoints expressed at the workshop.

Materials and Methods

On April 4–5, 2016, FDA/CTP hosted a public workshop to gather information on: (1) approaches to assessing and selecting BOPH; (2) the processes of identifying BOPH that may be useful in tobacco product regulation; and (3) areas of research that may further strengthen knowledge about BOPH.⁴ Previously, FDA/CTP hosted a public workshop on biomarkers of exposure (BOE).⁵ The BOPH workshop consisted of participants from government, industry, academia, and other organizations (Supplementary Table 1). The five sessions focused on: (1) overview of BOPH; (2) CVD; (3) COPD; (4) cancer; and (5) new areas of research.

Results

Overview of BOPH

BOPH can encompass a number of types of biomarkers, from those that indicate a risk factor for disease (biomarker of risk) to those that are meant to substitute for a clinical endpoint (surrogate endpoint; Table 1). Biomarkers used as validated surrogate endpoints often fail to predict the clinical outcome of interest.^6,7 One well-known example is the Cardiac Arrhythmia Suppression Trial in which patients randomized to the study drugs designed to suppress arrhythmia were more (rather than less) likely to die of arrhythmia or shock than placebo patients.⁸ Fleming and DeMets explained the reasons for such failures as one or more of the following: (1) the biomarker under study is not found on the pathophysiologic pathway that leads to the clinical outcome of interest; (2) the biomarker is used to test an intervention associated with only one pathway when multiple causal pathways to a particular clinical outcome exist; (3) the biomarker is insensitive to or is not a part of the causal pathway of the intervention’s effect or is insensitive to this effect; or (4) the intervention results in additional mechanisms of action (including other harmful effects) independent of the disease process.⁹

Table 1.

Additional Definitions/Terms for Biomarkers of Potential Harm (BOPH)

Biomarker	Definition	Reference
Biomarkers of risk	Biomarker that indicates a risk factor for disease.	14
Surrogate endpoint	An endpoint that is used in clinical trials as a substitute for a direct measure of how a patient feels, functions, or survives. A surrogate endpoint does not measure the clinical benefit of primary interest in and of itself, but rather is expected to predict that clinical benefit or harm based on epidemiologic, therapeutic, pathophysiologic, or other scientific evidence.	99
Reasonably likely surrogate endpoint	An endpoint supported by strong mechanistic and/or epidemiologic rationale such that an effect on the surrogate endpoint is expected to be correlated with an endpoint intended to assess clinical benefit in clinical trials, but without sufficient clinical data to show that it is a validated surrogate endpoint. Such endpoints may be used for accelerated approval for drugs and potentially also for approval or clearance of medical devices. In the case of accelerated approval for drugs, postmarketing confirmatory trials have been required to verify and describe the anticipated effect on the irreversible morbidity or mortality or other clinical benefit.	99
Pharmacodynamic/response biomarker	A biomarker used to show that a biological response has occurred in an individual who has received an intervention or exposure.	99
Predictive biomarker	A biomarker used to identify individuals who are more likely than similar individuals without the biomarker to experience a favorable or unfavorable effect from exposure to a medical product or an environmental agent.	99
Biomarkers of effect	Indicators of a change in biologic function in response to a chemical exposure.	100

Thus, the criteria (eg, biomarker characteristics and pathophysiology) for identifying, evaluating, and selecting BOPH require careful consideration.^10–12 In the context of tobacco product evaluation, the criteria for biomarker evaluation and selection are described in the Institute of Medicine (IOM) 2001 (Clearing the Smoke) and 2012 (Modified Risk Tobacco Products) reports and are based on those developed by Hill.^3,13,14Table 2 presents the questions that might be considered in determining whether a biomarker is an adequate indicator of potential harm, and we provide some examples for the criteria in the following.

Table 2.

Questions for Supporting Adequacy of Biomarker as Indicator of Potential Harm

Criteria	Question
Reflective of pathological process as a consequence of exposure	Plausibility: Is the data elucidating the biological pathways from exposure to effect plausible? Coherence: Is the cause and effect interpretation of the data not seriously in conflict with [the] generally known facts of the natural history and biology of the disease?
Sensitivity	How sensitive is the biomarker in assessing alterations in biology and in its ability to detect disease?
Predictive	To what extent are the biomarkers predictive of disease?
Temporality	Does exposure precede the effect?
Experiment	Is there evidence showing the removal of exposure lessens or removes the effect?
Biological gradient	Is the magnitude of exposure proportional to the magnitude of effect?
Specificity	Is the effect specific or are there other known causes?
Analogy	Can inferences be made based on data from other agents?
Consistency	Is the relationship reproducible and observed by multiple investigators in different populations using different methodologies?

Plausibility

“Plausibility” that the potential biomarker can occur along one or more of the physiological pathways to disease is helpful, especially for tobacco-related disease pathways that are well characterized, including cancer and CVD.¹⁵ However, plausibility is limited to the current state of the knowledge and may not be known yet for every given biomarker.

Coherence

“Coherence” between different lines of evidence, including laboratory and epidemiological, can also strengthen the case of a given biomarker. For example, in vitro studies on cells exposed to cigarette smoke or cigarette smoke condensate observed the increased expression of oxidative stress markers, whereas studies of humans have also demonstrated evidence of both local and systemic oxidative stress after short-term exposure to cigarette smoke.¹⁵

Sensitivity

“Sensitivity” of biomarkers can be assessed by examining the distribution and level of biomarkers in a population without the exposure/disease and by comparing the distribution of the biomarker in a population with the exposure/disease to assess the degree of discrimination.¹⁶ For example, in the cross-sectional, multi-center Total Exposure Study (TES, funded by Altria), 21 of the 29 selected BOPH, including many markers specific to cardiovascular risk, had shown significant differences between adult smokers and nonsmokers; seven of these had a greater than 10% difference, demonstrating sensitivity to differences by smoking status for some of the selected BOPH.¹⁷

Predictive Potential

The “predictive potential” of biomarkers include determining the extent to which the biomarker is predictive of a disease.¹⁶ For example, a pooled study of nine prospective observational studies demonstrated positive associations between diastolic blood pressure (DBP) and risks of stroke and coronary heart disease (CHD) and, most importantly, no evidence of a “threshold” below which lower levels of DBP were not associated with lower risk of stroke and CHD.¹⁸

Temporality, Experimentation, and Biological Gradient

“Temporality” can be determined by longitudinal studies but also inferred by experimentation and biological gradient. “Experimentation” includes examining the extent of changes as a result of cessation of the product. This type of study can also determine the “half-life” of the biomarker. The “biological gradient” is determined by the dose–response relationship between the level of harmful and potentially harmful constituents or exposure biomarkers with the biomarker of potential harm, and also by the change in biomarkers of harm with reduction in the extent of use of a product or in constituent yields within or across products.

Specificity, Analogy, and Consistency

Most biomarkers of potential harm have not shown “specificity” to tobacco and can be influenced by diet, cooking methods, ambient air, occupational settings, physical activity, etc.; therefore, these potential confounders should be considered and controlled. For example, in TES, body mass index, a potentially confounding factor, was the most important factor for 12 of the BOPH, demonstrating a lack of specificity to smoking.¹⁷ With regards to “analogy,” several nontobacco agents have demonstrated that lowering BOPH will reduce disease risk (eg, hypertension). Finally, some biomarkers have shown “consistency” or similar results across different study methods, tobacco products, and investigators (eg, white blood cells) demonstrating sensitivity to tobacco exposure effects.

Biomarker Development and Testing

Biomarker development and testing may include the following types of studies:¹⁶ (1) preclinical experimentation where potential biomarkers reflecting pathophysiology of disease are identified and assays for these biomarkers are validated; (2) cross-sectional biomarker studies involving people with and without the disease or by tobacco use status at a specific point in time; (3) experiments to determine whether levels and changes in tobacco use or exposure including secondhand smoke will affect the measured biomarker; (4) nested case–control studies where biospecimens have been collected prior to disease development and analyzed to determine whether predisease biomarker levels predict eventual disease; and (5) prospective longitudinal studies to determine whether changes in biomarker(s) will be able to predict disease development, either by reaching a certain threshold or continuously (no threshold). Several general factors should be considered when testing and characterizing BOPH in tobacco users: the representativeness of the population, which does not preclude focusing on special populations, including smokers at risk for the disease outcome (eg, genetics) or who are currently experiencing the disease; pharmacokinetic properties (half-life) of the biomarker, which will inform the required duration of a study testing tobacco products; use of a range of biomarkers reflective of a disease condition or different disease conditions; and assessment of confounding environmental, behavioral, and individual factors (eg, diet, environmental/occupational exposures, level of physical activity, sex, age, race, body mass index [BMI], alcohol use).

Pathophysiology and Biomarkers Associated With CVD, COPD, and Cancer

For the remaining sections of this report, definitions of physiological processes and other terms discussed are provided in Supplementary Table 2.

Biomarkers That Cut Across Diseases: Inflammation and Oxidative Stress

Inflammation and oxidative stress play roles across smoking-related CVD, COPD, and cancer and can be induced by smoking along with infection and other processes. Supplementary Table 3 characterizes some commonly studied inflammatory and oxidative stress markers as they relate to smoking and disease risk.

Cardiovascular Disease

CVD generally reflects conditions that involve the narrowing or blockage of blood vessels that can lead to myocardial infarction or stroke. Exposure to constituents of cigarette smoking known to contribute to CVD include: (1) oxidizing chemicals and particulates, both of which can increase inflammation and thrombosis or lead to blood clot formation and endothelial dysfunction; (2) carbon monoxide, which reduces the delivery of oxygen; (3) volatile organic compounds (VOCs) such as acrolein, which can cause cardiovascular toxicity; (4) heavy metals, which can damage endothelial cells; and (5) nicotine, known to activate the sympathetic nervous system and increase heart rate and blood pressure.¹⁵

Oxidative Stress and Inflammation

Oxidative stress resulting from smoke inhalation can lead to chronic inflammation, endothelial damage and dysfunction, platelet activation, impaired vasodilatation, adverse effects on blood lipids, pathologic angiogenesis, and enhanced thrombosis.¹⁹ Cigarette smoke activates the endothelium by the induction of adhesion molecule expression, as well as macrophages and platelets. In response to in vitro smoke exposure, endothelial cells are known to release inflammatory and proatherogenic cytokines, leading to endothelial dysfunction. Inflammation plays a key role in both atherogenesis and thrombotic events, two key processes that lead to acute coronary events such as a myocardial infarction.²⁰

C-reactive protein (CRP) is a nonspecific marker of inflammation, and increased plasma CRP levels are associated with smoking and increased risk for CVD (Supplementary Table 3). A meta-analysis showed that risk of future coronary heart disease was approximately 50% higher in individuals with CRP levels in the top third of the distribution compared with those with CRP levels in the lower third of the distribution.²¹ A similar association was also found for interleukin-6 (IL-6), an inflammatory biomarker upstream of CRP.²² Fibrinogen is another inflammatory biomarker associated with cardiovascular events, though also associated with non-CVD deaths, suggesting low specificity for predicting CVD risk.²³ Strong statistical associations between these biomarkers and CVD risk do not necessarily translate into their increased ability to predict future risk of disease development.^21,24

Endothelial Dysfunction

The endothelium (inner lining of blood vessels) is critical for maintaining blood flow to various organs, including the heart and the brain. Thus, endothelial injury and dysfunction caused by smoking is thought to play a major role in acute cardiovascular events. Oxidants destroy and reduce nitric oxide, an effect considered to be the hallmark of endothelial dysfunction leading to impaired vasodilatation. The established biomarkers of the endothelial dysfunction include: % flow-mediated dilation (FMD) as measured by brachial artery ultrasound imaging, circulating plasma endothelial precursor cells and microvesicles, E-selectin, P-selectin, and von Willebrand factor.^25–27 In the cross-sectional Tobacco Exposure Study (TES), plasma von Willebrand factor levels were significantly higher in smokers than in nonsmokers, though no trend was observed for increasing cigarettes per day.²⁸ In a 1-year longitudinal study, smoking cessation was significantly associated with improved % FMD, whereas no change in % FMD occurred for continued smokers.²⁷

Enhanced Thrombosis

Cigarette smoking increases the number and activation of platelets, leading to a prothrombotic and procoagulative state in the vascular wall of smokers. Platelets play a pivotal role in the pathogenesis of thrombosis, atherogenesis, and angiogenesis. Thus, platelet-derived biomarkers are promising, and include measurements of thrombocytosis or an overabundance of platelets, mean platelet volume, and immature platelets, all of which have been associated with adverse cardiac events or mortality.²⁹ Other biomarkers of the hypercoagulable state include markers of platelet activation, red blood cell mass, and fibrinogen have been shown to be higher in smokers than in nonsmokers in cross-sectional studies.^17,30

Hemodynamic Stress

Mediated primarily by nicotine, acute smoking leads to hemodynamic changes, including elevated heart rate, blood pressure, and cardiac output.¹⁵ As a result, the reserve of blood flow in the heart needed to respond to increased myocardial demand is inappropriately reduced in smokers, contributing to ischemic cardiac events. In an experimental study of 10 healthy volunteers, both heart rate and blood pressure increased with use of all forms of nicotine (cigarettes, oral snuff, chewing tobacco, nicotine gum) and returned to baseline values within 90 min.³¹ In another experimental study, 10 healthy volunteers smoking different types of cigarettes (usual brand, high- and low-nicotine research cigarettes) resulted in similar increases over a 24-h period in heart rate and blood pressure as compared with abstinence.³² Smoking cessation has been shown to immediately result in lower blood pressure.³³ Despite the evidence of acute increases in blood pressure due to smoking, chronic effects on blood pressure, including hypertension, have not been consistently shown to be higher in smokers compared with nonsmokers in the general population.³⁴

Blood levels of natriuretic peptides increase under cardiac dysfunction and can serve as biomarkers of subclinical hemodynamic stress. The increase of plasma B-type natriuretic peptide (BNP) was strongly associated with a variety of CVD risks, including sudden death, heart failure, atrial fibrillation, coronary heart disease, and stroke.^35,36 In one study, current smokers had about a threefold increase in BNP levels than never smokers, suggesting smoking is one of the factors that causes subclinical increase in cardiac stress or dysfunction.³⁷

Blood Lipids

Cigarette smoking is associated with changes in the blood lipid profile that can contribute to the development of fatty plaques and atherosclerosis.¹⁵ For example, in an analysis based on 54 studies, smokers compared with nonsmokers had significantly higher serum concentrations of total cholesterol (3% difference from values in nonsmokers), triglycerides (9%), and very low-density lipoprotein (VLDL; 10%), as well as decreased high-density lipoprotein (HDL) cholesterol (−6%).³⁸ In a longitudinal study, smokers who quit had significantly increased HDL cholesterol after 1 year.³⁹

Insulin Resistance

Cigarette smoking is associated with diabetes, a major risk factor for CVD.⁴⁰ Insulin resistance and diabetes can be measured with glycated hemoglobin (hemoglobin A_1c (HbA_1c)), a glucose tolerance test, and glucose clamping studies. An analysis from the large cross-sectional Scottish Health Survey observed that smokers were twice as likely to have HbA_1c in the “pre-diabetic” range as compared with nonsmokers (OR = 2.25, 95% CI = 1.84 to 2.75), suggesting that smoking adversely affects glucose homeostasis.⁴¹

Arrhythmogenesis

Smoking is associated with sudden cardiac death and arrhythmia, and catecholamine release is thought to play a role.⁴² This effect was observed in an experimental study of 12 smokers who received three doses of transdermal nicotine patches (21, 42, and 63 mg/24 h) and placebo (0 mg) each for 5 days, including 4 days of smoking (days 1–4) and smoking abstinence on the fifth day. While on the placebo patch, urinary epinephrine concentrations were higher by about 60% during the smoking period when compared with the nonsmoking period. Though epinephrine concentrations increased in participants on nicotine-containing patches, the dose–response was flat, suggesting that only a small level of nicotine was needed to cause this effect.⁴³

Atherosclerosis

Atherosclerosis involves the narrowing and hardening of the arteries due to the build-up of fatty material or plaque, leading to reduced or blocked blood flow that can progress to adverse events, including heart attack or stroke. Coronary artery calcification (CAC) score is one example of a marker of subclinical atherosclerosis and has been shown to be predictive of coronary heart disease independent of conventional risk factors.⁴⁴ In the Multi-Ethnic Study of Atherosclerosis (MESA) cohort, both former smoking and current smoking were associated with a CAC > 0 (compared to never smokers).⁴⁵ One potential limitation of CAC is that it is a marker of an advanced stage of the disease process, and thus may not be reversible.⁴⁶

Tobacco Product Evaluation With CVD Biomarkers

A cross-sectional study compared several CVD biomarkers among exclusive smokers, exclusive moist snuff consumers, and nonusers of tobacco (n = 48–60 in each condition) and found that the three BOPH that best differentiated the smokers from the two nonsmoking groups were the inflammatory biomarkers: soluble intercellular adhesion molecule (sICAM), IL-8, and IL-12(p70).^47,48 However, no measurable differences in sICAM, IL-6, or IL-8 were detected among moist snuff users compared with nontobacco users, a finding that has also been observed in other studies.^28,49

In a clinical multi-site switching study, 150 smokers were randomized to switch to a tobacco-heating cigarette (TH), snus (S), or an ultra-low machine yield tobacco-burning cigarette (TB) for 24 weeks with a comparison group of never smokers (n = 30) at baseline.⁵⁰ At weeks 12 and 24 compared with baseline, significant reductions in sICAM were observed in all three product groups. In both weeks 12 and 24, researchers observed reductions in platelets (TH), increases in glycated hemoglobin (HbA_1c; TH, S), and reductions in the F2-isoprostane biomarker (±)5-iPF_2α –VI (TB). Thus, sICAM showed differences across product categories in the cross-sectional study with smokers showing higher levels of sICAM than ST users or nonusers of tobacco and sICAM was reduced when smokers were switched to the other tobacco products in the switching study. Similar results were observed for white blood cells and the F2-isoprostane biomarker iPF_2α–III. Overall, the most consistent and significant improvements in biomarkers were found in smokers who switched to TH. Due to varied compliance across treatment groups, these findings reflect differences in poly-tobacco use rather than complete product switching.

These studies demonstrate the types of experiments that can be conducted to identify biomarkers that might be sensitive to differences across tobacco product categories and as compared with nonusers of tobacco. They also highlight how the biomarkers that show differences across tobacco type in cross-sectional studies are not necessarily the same biomarkers that show differences in switching studies.

Chronic Obstructive Pulmonary Disease

Many of the same components of tobacco smoke that lead to CVD also adversely affect the respiratory system, increasing the risk of COPD. Bronchitis and emphysema are the two most common underlying diseases of COPD.⁵¹ Tobacco smoke constituents cause lung injury through a number of mechanisms, including: impairment of the lung’s innate defense system, leading to potential for infection and inflammation (eg, acrolein); toxicity to the cilia or microscopic hairs along air passages (eg, acrolein, formaldehyde); lung irritation (eg, formaldehyde); oxidative damage (eg, nitrogen oxides, cadmium); and disruption of the oxidative metabolism of cells (eg, hydrogen cyanide).⁵²

Forced Expiratory Volume in 1 Second

Forced expiratory volume in 1 second (FEV1) is a reproducible and well-established surrogate endpoint for COPD.⁵³ Decreasing FEV1 is associated with increased COPD exacerbations, hospitalizations, and mortality.⁵⁴ In a prospective cohort study of about 800 manual workers in London, the authors observed that FEV1 decreased over time for both smokers and nonsmokers, though at a steeper decline in smokers.⁵⁵ Although smoking cessation did not recover lung function, the rate of FEV1 decline slowed to a normal level in former smokers. FEV1 has long been used to grade COPD and is strongly correlated with disease severity. However, patients with lung abnormalities may still have normal FEV1; thus, FEV1 is not considered to be highly sensitive to detection of disease.⁵⁶ Additionally, changes in FEV1 may require several years to detect depending on factors such as study design, study size, and patient characteristics.⁵³

Imaging Biomarkers

Some imaging tools, such as computed tomography (CT) scanning and magnetic resonance imaging (MRI), may have greater sensitivity for detecting emphysema and airway disease compared with FEV1.^57,58 In the COPDGene cohort of approximately 10000 smokers followed over time, about 40% were considered controls based on FEV1 evaluation, and 60% had various grades of COPD at baseline.⁵⁶ CT scans were taken at baseline as a type of micro-mapping of the lung, with individual pixels followed over time using a computer program. In a subset of 2300 study participants observed over 5 years, the CT scan detected progression of COPD in about 40% of the participants.⁵⁶ Additionally, CT scanning provided evidence of airway disease and emphysema in 15% and 20%, respectively, of the smokers who were considered normal based on FEV1. Although preliminary findings suggest that imaging biomarkers may have greater sensitivity for detecting disease than spirometry, additional studies of smokers versus nonsmokers and smoking cessation could help strengthen their potential role in the tobacco regulatory setting.

Inflammatory Markers

The relationship between plasma inflammatory markers and poor clinical outcomes in COPD has been assessed. In the Evaluation of COPD Longitudinally to Identify Predictive Surrogate Endpoints (ECLIPSE) cohort of COPD patients, persistent systemic inflammation based on white blood cell count, CRP, IL-6, TNF-alpha, fibrinogen, and IL-8 was associated with increased all-cause mortality and exacerbation.⁵⁹ In another example, soluble receptor for advanced glycation end products (sRAGE) is thought to be anti-inflammatory by binding to damaged ligands and preventing them from activating cell signaling pathways. In a subset of participants enrolled in COPDGene cohort (n = 588), sRAGE was inversely associated with more severe emphysema.⁶⁰ Similarly, in the ECLIPSE cohort of COPD patients (n = 1928), higher levels of sRAGE at baseline were associated with less emphysema and less disease progression over time.⁶¹

The relationship between markers of inflammation and smoking has also been assessed directly in the lung.⁶² Neutrophils measured in samples using bronchoaveolar lavage bronchoscopies have been observed to be higher in individuals with chronic bronchitis than asymptomatic smokers, but higher in asymptomatic smokers as compared with normal nonsmokers.⁶³ In another study, the relative amount of M1 macrophages, which are pro-inflammatory, and M2 macrophages, which are anti-inflammatory, were observed to differ between nonsymptomatic smokers and nonsmokers.⁶⁴

Cystic Fibrosis Transmembrane Conductance Regulator

Chronic bronchitis is characterized by sputum production and inflammation and shares similar symptoms with early cystic fibrosis (CF). Biomarkers for CF lung disease have recently been assessed for utility as BOPH. CF is caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) ion channel that reduce activity, leading to airway surface dehydration.⁶⁵ Tobacco exposure can also inhibit CFTR function, which further supports a potential role in COPD. In a study measuring the CFTR function in the nose using an electrode connected to a voltmeter, the authors observed reduced CFTR-mediated ion transport among nonsymptomatic smokers (n = 4) compared to nonsmokers (n = 12).⁶⁶ This study also found that acute smoke exposure decreased CFTR ion transport activity for up to 3 h after cigarette smoke exposure.

Cancer

In the central mechanism of tobacco carcinogenesis, carcinogens in cigarette smoke are metabolically activated by cytochrome P450 enzymes and bind to DNA.⁵² The DNA adducts that are formed can cause miscoding, resulting in uncontrolled cell growth and leading to cancer development. Based on the initiation-promotion-progression mouse model originally developed by Berenblum and Shubik in the late 1940s, mouse experiments have shown that tumor development occurs only in the presence of both initiators that form mutations in cells (eg, benzo[a]pyrene, nitrosamine) and promoters that facilitate survival and growth of the mutated cells (eg, inflammatory agents such as lipopolysaccharide and smoke condensate).^67,68

Inflammation and Oxidative Stress

Different lines of evidence support the role of inflammation in lung cancer. COPD, an inflammatory condition, is a risk factor for lung cancer.⁶⁹ Use of aspirin and nonsteroidal anti-inflammatory drugs is associated with lower lung cancer risk.⁷⁰ In prospective studies, inflammatory markers, including CRP, IL-6, and IL-8, have been associated with lung cancer risk.⁷¹ Another promising inflammatory marker is prostaglandin E2 metabolite (PGE-M), which is associated with a number of cancers including colorectal, lung, breast, and head and neck cancers; increased levels have been observed in smokers in a limited number of studies.⁷² As described previously, smoking causes oxidative damage. Although F2-isoprostane biomarkers can be reliably measured and are increased with smoking, their relationship with cancer risk is not yet established.

Biomarkers of Exposure (BOE) and DNA Adducts as BOPH

Several BOE, including 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (NNAL), N-nitrosonornicotine (NNN), and phenanthrene tetraol, are associated with subsequent cancer risk, as observed in the Shanghai Cohort Study, and thus seem to fulfill many of the criteria for BOPH (Table 2).^73,74 For example, NNN causes esophageal tumors in rats which demonstrates biologic plausibility.⁷⁵ In a nested case–control study, NNN was associated with a subsequent risk of esophageal cancer in a dose-dependent manner, demonstrating, temporality, predictivity, biological gradient, and coherence.⁷⁴ Genetic variants have been observed to modify the effect of these biomarkers and cancer risk and may be important for stratification in study populations. For example, variation in the α5 nicotinic cholinergic receptor subunit gene (CHRNA5) on chromosome 15q25.1 is associated with smoking intensity and nicotine dependence as well as age at lung cancer diagnosis.^76,77 Variants of CYP2A6 also modify nicotine and carcinogen uptake in smokers and are related to lung cancer risk.⁷⁸ Finally, biomarkers such as DNA adducts play a central role in carcinogenesis, but challenges include low concentrations and nonquantitative methods. Recent developments for detecting DNA adducts in human oral cell DNA include use of nanospray ionization, which concentrates the sample, and quantification by high-resolution mass spectrometry.⁷⁹

Airway Epithelial Biomarkers

Biomarkers investigated within the context of chemoprevention of lung cancer include bronchial epithelia dysplasia. Typically, biopsies taken from sites along the respiratory tract using bronchoscopy are examined for dysplasia based on a scoring system.⁸⁰ In a clinical trial of oral iloprost (a prostacyclin analog) in current and former smokers, endobronchial histology was significantly worse in current smokers compared with former smokers at baseline.⁸¹ The persistence or progression of bronchial dysplasia may be predictive of lung cancer risk. In a small cohort of 188 participants at a high risk of pulmonary squamous cell carcinoma, having a higher frequency of sites that persisted or progressed to high-grade dysplasia was associated with a higher risk of invasive squamous cell carcinoma (hazards ratio = 7.84, 95% CI = 1.56 to 39.39).⁸² Less invasive methods are currently being investigated for use in lung cancer screening.^83,84

Gene Expression

Smoking alters epithelial cell gene expression throughout the respiratory tract, and there is variability in the gene expression across individuals in response to damage from smoking and risk for developing lung cancer.⁸⁵ Gene expression of the bronchial airway epithelium, collected using an endoscopic cytobrush, may serve as an early diagnostic biomarker for lung cancer.⁸⁶ In the Airway Epithelium Gene Expression In the Diagnosis of Lung Cancer (AEGIS) clinical trial, investigators found that their 23 gene-expression classifier showed a higher sensitivity for detecting lung cancer, especially for small peripheral lung lesions (ranging from 90 to 92%), than bronchoscopy (ranging from 55% to 58%).⁸⁶ In another study comparing non-symptomatic smokers and nonsmokers, active exposure to tobacco smoke altered the expression of 175 genes in the bronchial airway epithelium, and many of these changes reverted back to never smoker levels within a few months of quitting among former smokers. However, about 28 (16%) of the alterations in gene expression persisted after smoking cessation.⁸⁷ Current studies are underway for detecting changes in gene expression using nasal epithelium samples with respect to smoking cessation and other clinical applications.⁸⁸ Furthermore, in vitro experiments on bronchial epithelium cells showed that tobacco flavoring and the presence of nicotine induced most of the gene expression changes which may be relevant to ENDS use.⁸⁵

Novel Biomarkers

Although more traditional approaches are based on a priori hypotheses, a less targeted approach has emerged with the development of high-throughput technologies and concurrent testing of massive numbers of markers, including “omics” biomarkers. Below are examples of studies of “omics” biomarkers as they relate to tobacco use.

Epigenome

Epigenetics involves the heritable changes in gene function that occur without a change in the DNA sequence, such as changes in microRNAs, polycomb proteins, histone modifications, and DNA methylation.⁸⁹ Epigenetic changes can turn genes on or off and may lead to adverse health outcomes. For example, recent epigenome-wide studies observed that smoking was strongly associated with DNA methylation alterations of the aryl hydrocarbon receptor repressor (AHRR).⁹⁰ A further study of AHRR methylation in current, former, and never smokers from the MESA cohort found that methylation of cg05575921 was most significantly associated with smoking status (current vs. never).⁹⁰ Cg05575921 methylation also demonstrated reversibility with cessation, a dose-dependent relationship with smoking, and an association with carotid plaque scores. Another study of methylation profiling in buccal cells from smokers, moist snuff users, and nontobacco users observed that smokers exhibited a greater hypo-methylation pattern of methylation as compared with the moist snuff users and nontobacco users, including six out of seven loci of the AHRR gene that were hypo-methylated.⁹¹

Microbiome

The human body can be considered as an ecosystem where different microbiome patterns are present in different parts of the body. Recent investigations focused on whether the microbiome may mediate the adverse health effects of tobacco use. For example, a study conducted in China showed that current smokers appeared to have higher levels of unique microbial species and genera present in the upper gastrointestinal tract microbiome compared with never smokers whereas the levels of microbial species and genera in former smokers did not differ from those in never smokers.⁹² However, no significant associations between microbiome and pack-years of smoking (current smokers) or years since quitting (former smokers) were observed, though the analysis was based on a small sample. Overall, previous studies have shown inconsistent associations between the microbiome (eg, numbers of unique microbes) and current smoking, and future studies involving larger sample sizes and examining different types of tobacco use could further strengthen this area of research.⁹³

Risk Assessment Using “Omics” Biomarkers

“Omics” biomarkers may enhance risk assessment at agencies such as the US Environmental Protection Agency (EPA) and The National Institute for Occupational Safety and Health (NIOSH). The development of an occupational exposure limit can be facilitated by a thorough understanding of comprehensive exposure assessments including use of “omics” biomarkers.⁹⁴ As early biomarkers of effect, they may provide information on mode of action and dose–response relationship. However, challenges in using biomarkers of early effect in the risk assessment process include the fact that scientific tools for facilitating biomarker development, such as computational toxicology and systems biology, are still being developed. Additionally, few biomarkers have been validated in human populations, and appropriate interpretation of biomarker data is lacking.⁹⁵

One tool that can facilitate the interpretation of biomarker data is the adverse outcome pathway (AOP), a conceptual framework developed by EPA scientists that connects molecular-level changes to adverse outcomes in a biological system. As high-throughput toxicity testing has become increasingly used for determining chemical toxicity (in addition to the more traditional animal testing), the AOP was developed to better interpret in vitro perturbations in terms of consequences to the whole organism as well as to identify the full set of toxicity pathways leading to all of the potential adverse outcomes in vivo.⁹⁶ The AOP framework systematically organizes and summarizes data into the following components: molecular initiating event indicating initial chemical contact, key events such as changes in biological state, and adverse outcomes that are measurable and essential for adverse outcome progression. The advantage of the AOP framework is that it connects molecular initiating events to toxicity pathways without considering specific chemicals, unlike mode of action which is chemical-specific.⁹⁷ As one potential application of this framework for tobacco evaluation, in vitro and clinical studies based on “omics” techniques could identify candidate biomarkers that differentiate exposure from nonexposure to cigarette smoke and then be screened based on their associations with the established adverse outcomes in order to serve as potential key events.

Future Directions

The deliberations from the workshop noted some promising BOPH but also highlighted the lack of systematic effort to identify BOPH that would have utility and validity for evaluating tobacco products. Because of the important role played by BOPH, a concerted effort would be useful to engage in multi-disciplinary, collaborative, and integrative biomarker research. Additionally, a common framework to guide this research would be helpful in accelerating progress. The following recommendations describe additional research that could further strengthen the utility of BOPH in the tobacco regulatory setting.

Utilize Current Knowledge of Critical and Common Pathways to Disease

Identifying BOPH based on our current knowledge of major smoking-mediated pathways to disease is a reasonable approach. Given that many of the smoking-related diseases share some of the same pathways, such as inflammation and oxidative stress, biomarkers that are relevant across disease areas (eg, CVD, COPD, cancer) may be especially useful to identify. How these biomarkers relate to each other, to tobacco use, and to each disease outcome separately may be important to investigate in future studies.

Explore Composite Biomarkers as Predictors of Disease Risk

For the major tobacco-related diseases (CVD, pulmonary disease, and cancer), a set of biomarkers, rather than a single biomarker, could better represent the multiple mechanisms by which tobacco causes these diseases. One possible approach is to improve disease risk prediction by combining multiple biomarkers into a composite variable. Specific considerations for testing composite biomarkers may include: pre-analytical considerations (eg, stability of individual biomarkers, sample collection times); analytical validation of all individual biomarker assays; factors influencing the variability of individual biomarker levels and the composite measure (eg, age, weight); weighting of individual biomarkers (ie, whether equal or unequal); and identifying a threshold score to define a significant change.⁹⁸

Consider Novel Technologies

As some key events may be missed by focusing on known biomarkers and pathways, a more comprehensive and nontargeted approach based on novel technologies, including “omics” biomarkers, can be considered. Novel technologies can help identify new biomarkers that are less likely to be correlated with known biomarkers and lead to the development of a composite biomarker profile that is also specific for tobacco use. The main challenge is that few “omics” biomarkers have been fully validated with respect to reproducibility of results in human populations. Additionally, their roles in causal pathways and disease prediction have yet to be established.

Systematically Examine BOPH Using Existing Cohorts, Surveys, and Experimental Studies

BOPH can be further evaluated by leveraging existing studies with available biosamples or biomarker data, including cross-sectional, case-control, prospective cohorts (eg, MESA, Framingham study, Atherosclerosis Risk in Communities study [ARIC], Prostate, Lung, Colorectal and Ovarian [PLCO] Cancer Screening Trial, Population Assessment of Tobacco and Health [PATH] Study), intervention, and smoking cessation studies. In particular, prospective studies could help to establish temporality as well as to identify the magnitude of change needed to observe clinically meaningful changes. To date, most studies of biomarkers and tobacco have been conducted in cohorts of cigarette smokers. Thus, additional studies using existing cohorts of users of other established tobacco products, such as smokeless tobacco, cigar, and hookah, as well as cohorts of nonusers exposed to secondhand smoke, could further strengthen our understanding of how biomarkers relate to tobacco use/exposure and disease risk. Another consideration is focusing on special populations, including smokers at risk for the disease outcome (eg, genetics). A major challenge is that few BOPH are tobacco-specific, and approaches that could help distinguish effects of tobacco use from effects of other confounding factors are important to explore.

Supplementary Material

Supplementary data are available at Nicotine and Tobacco Research online

Funding

This work was supported by funds from the Food and Drug Administration.

Declaration of Interests

None declared.

Disclaimer

The findings and conclusions of this report are those of the authors and do not necessarily represent FDA positions or policies.

Acknowledgments

The authors thank the CTP Office of Science (OS) and the members of the OS Biomarker Workgroup, Aarthi Arab, Jiping Chen, Susan Chemerynski, Carolyn Dresler, Selvin Edwards, Dhanya John, Maocheng Yang, and Ling Yang for their contributions to the planning and execution of the BOPH Workshop.