Smoking is a major cause of morbidity and mortality worldwide. The adverse health effects of chronic cigarette smoke exposure are widely known. Active smoking increases the risk of developing several pathologies including pulmonary disease, cardiovascular disease and cancer. Importantly, the sequelae of smoking also extend to non-smokers via frequent passive inhalation. Accurate measures of cigarette smoke exposure then are required to draw meaningful conclusions about the healthcare risks to both smokers and non-smokers. Cotinine is the major primary metabolite of nicotine and is the biochemical marker of choice for measuring exposure to cigarette smoke.

by Dr A. Dunlop, Dr B. L. Croal and J. Allison

Background
Chronic exposure to tobacco products is amongst the leading causes of preventable morbidity and mortality worldwide, being responsible for approximately 6 million deaths per annum [1]. Typically this involves inhalation of cigarette smoke which contains in excess of 5000 different chemicals; many of these are known toxins and carcinogens [2].  Upon inhalation of cigarette smoke, nicotine is transported to the lungs within tar droplets, dissolving in the alveolar fluid, and is then absorbed into the bloodstream. Following entry into the pulmonary circulation, nicotine quickly travels to the brain – within a matter of seconds – and exerts its pharmacological effects [3].

Nicotine is the addictive component of tobacco products, stimulating dopamine release in the brain and leading to heightened feelings of pleasure and reward [4]. In active smokers this nicotine dependence sustains chronic exposure to the toxins present in cigarette smoke [5]. Active smokers are therefore at increased risk of developing multiple pathologies including pulmonary disease, cardiovascular disease and cancer [6, 7]. Importantly, non-smokers are also at increased risk via involuntary or passive/second-hand smoke (SHS) exposure [8, 9]. Children are particularly susceptible to involuntary exposure, mainly occurring in enclosed spaces such as the parental home/car, via maternal smoking or passive exposure during pregnancy [10]. The adverse health effects of SHS exposure in children include increased risk of miscarriage, sudden infant death syndrome, lower respiratory tract infections, asthma and invasive meningococcal disease [10].

In addition, an emerging area of interest surrounds involuntary exposure via so-called third-hand smoke (THS). THS is a term used to describe the deposits of tobacco smoke that accumulate on surfaces, objects and in dust particles, persisting long after the dispersal of cigarette smoke. There is some evidence to suggest that atmospheric reactions may lead to re-release of smoke-derived toxins into the environment [11]. However, the health risks of THS are not yet known and remain the subject of ongoing research [12].

Assessing cigarette smoke exposure
The healthcare risks associated with cigarette smoking and SHS exposure ensure that smoking status should always be included in any routine clinical assessment. Monitoring of smoking status may also be indicated in specific circumstances, such as epidemiological studies, smoking cessation programmes, lung transplant patients, employee and health/life insurance screening. The most convenient and cost-effective means of assessing cigarette smoke exposure is by self-report. This may occur either during face-to-face consultation with healthcare professionals or often as part of a generic healthcare questionnaire. However self-report is frequently unreliable in estimating smoking status [13].

Moreover, the risk and extent of SHS exposure to non-smokers cannot be adequately assessed using these methods. For example, self-report cannot reliably quantify exposure in those who co-habit and/or socialise with smokers nor can it inform on fetal exposure in maternal smoking. Consequently, cigarette smoke exposure should be accurately quantified by measuring biomarkers to draw meaningful conclusions between smoking status and health outcomes [14, 15].

Biomarkers of cigarette smoke exposure
Numerous biomarkers have been examined in the analysis of cigarette smoke exposure, e.g. carbon monoxide, carboxyhaemoglobin, thiocyanate and polycyclic aromatic hydrocarbons [4]. However, many are non-specific for tobacco use and contribution from other environmental or dietary sources can cause interference [4]. In contrast, nicotine is a more specific marker of cigarette smoke exposure, being derived solely from tobacco [3]. Biochemical measurements of nicotine and its metabolites then are typically used to provide reliable measures of cigarette smoke exposure. Nicotine largely undergoes hepatic metabolism (with a half-life of approximately 2 h) and the plasma of active smokers typically contains 10–50 ng/mL of nicotine [3]. Cotinine is the major breakdown product of nicotine accounting for around 80% of all metabolites [3]. The half-life of cotinine, at around 16 h, is substantially longer than nicotine and plasma levels in active smokers are approximately 250–300 ng/mL [4]. Consequently, cotinine is the preferred biomarker for measuring cigarette smoke exposure.

Quantifying cotinine in biological matrices
A variety of methods have been developed for quantification of cotinine in several biological matrices including urine, blood, saliva and hair [14, 15]. There is good agreement between cotinine levels in plasma/serum and saliva, whilst levels in urine are typically higher [15].

Immunoassay methods have traditionally been used for the detection of cotinine in urine, offering rapid turnaround with minimal sample preparation. In addition, commercially available immunoassay kits are easily integrated into most core automated analysers available in modern clinical laboratories. However, reagent costs are typically high and it would be fair to say that immunoassays may be susceptible to cross-reactivity with other nicotine and cotinine-derived metabolites and thus may be of questionable accuracy [16, 17].

Gas chromatography–mass spectrometry (GC-MS) methods are also available; although sample preparation is typically labour intensive and time consuming, proving impractical for high sample throughput. Not surprisingly, liquid chromatography-tandem mass spectrometry (LC-MS/MS) methods have emerged as the sine qua non for quantification of cotinine in biological fluids.

LC-MS/MS analyses
Liquid chromatography–tandem mass spectrometry (LC-MS/MS) affords the requisite specificity and sensitivity to detect and quantify cotinine at levels encountered throughout the spectrum of cigarette smoke exposure. The majority of recently published methods now routinely quote lower limits of quantification (LLOQ) in the region of <0.5 ng/mL, in both plasma/serum and in urine [15]. Cut-points to distinguish smokers from non-smokers have been variously proposed from 12 ng/mL down to 3 ng/mL, depending on the population [15]. Nevertheless, regular active smokers can be expected to have serum/plasma cotinine levels in marked excess of 100 ng/mL, although non-smokers are usually comfortably below 10 ng/mL. The majority of LC-MS/MS methods for cotinine have been developed in-house, an important advantage compared with immunoassay techniques. This not only affords flexibility in the choice of matrix to be analysed but also permits the inclusion of more than one analyte in the assay. Thus nicotine, cotinine and various metabolites thereof may be detected in a multiplexed assay. Published guidelines are also widely available to assist in the development and validation of LC-MS/MS methods [18]. The advent of enhanced chromatographic separation techniques, such as ultra-performance liquid chromatography (UPLC), has significantly shortened run times thereby facilitating higher sample throughput. Development of uncomplicated sample preparation procedures has further simplified analyses. For example, in our own laboratory we recently developed a rapid and straightforward UPLC-MS/MS protocol for the determination of cotinine in plasma (Fig. 1) [19]. Analytical run time was 4 min per sample with a LLOQ of 0.2 ng/mL and the assay was linear from 0.5 to 1000 ng/mL; comfortably covering the concentration range of active and non-smokers (Fig. 2). A simple 5-step automated SPE process was also developed, permitting minimal sample handling and using only water and methanol, both cheap and readily available. To date we have successfully deployed this method for the analyses of two large patient cohorts (each comprising several hundred samples) associated with independent epidemiological studies. Although the initial outlay for equipment is high, thereafter LC-MS/MS assays can be run relatively cheaply using readily available inexpensive solvents. Furthermore, sample preparation procedures can usually be streamlined/simplified and therefore easily adapted for high-throughput analyses [19]. Matrix effects, chiefly ion suppression, are a particular disadvantage of LC-MS/MS techniques; however careful consideration and troubleshooting during method development can often overcome this issue [20]. Conclusions and future directions
Despite widespread awareness of the adverse effects of tobacco use and increasing public health initiatives to combat this, cigarette smoking continues to be a major global cause of morbidity and mortality and is likely to remain so for the foreseeable future. Accurate quantification of cigarette smoke exposure via biomarkers is therefore an important measure in stratifying the risk of both active and non-smokers.

The need to quantify ever decreasing amounts of nicotine, cotinine and their metabolites in monitoring exposure to tobacco products ensures that LC-MS/MS techniques and modifications thereof remain at the forefront of detection methods in this field. Similarly, as new biomarkers become available which inform on the detrimental health effects of smoking these methods are ideally placed to keep pace, both in research and in clinical laboratories.

The recent emergence of electronic cigarette devices (e-cigarettes) is currently the subject of much debate. E-cigarettes typically deliver nicotine in a vapour generated via heating a liquid that also contains propylene glycol and other additives e.g. flavouring [21]. Exponents propose e-cigarettes as a safer alternative to smoking associated with tobacco combustion and promote the benefits for smoking cessation. However, some healthcare professionals believe that while e-cigarettes are safer, they may still act as a gateway or as a way of prolonging or even enhancing dependency on nicotine. In addition, the long-term health effects of these products are unknown, as is the need to monitor biomarkers such as nicotine and/or cotinine in so-called ‘e-smokers’.

References
1. WHO report on the global tobacco epidemic 2013. http://www.who.int/tobacco/global_report/2013/en/
2. Talhout R, et al. Hazardous compounds in tobacco smoke. Int J Environ Res Public Health 2011; 8(2): 613–628.
3. Hukkanen J,  et al. Metabolism and disposition kinetics of nicotine. Pharmacol Rev. 2005; 57(1): 79–115.
4. Benowitz NL, et al. Nicotine chemistry, metabolism, kinetics and biomarkers. Handb Exp Pharmacol. 2009; 192(192): 29–60.
5. Berrendero F, et al. Neurobiological mechanisms involved in nicotine dependence and reward: participation of the endogenous opioid system. Neurosci Biobehav Rev. 2010; 35(2): 220–231.
6. Doll R, et al. Mortality in relation to smoking: 50 years’ observations on male British doctors. BMJ (Clinical research ed.). 2004; 328(7455): 1519.
7. Jha P. Avoidable global cancer deaths and total deaths from smoking. Nature reviews.Cancer. 2011; 9(9): 655–664.
8. Scientific Committee on Tobacco and Health. Secondhand smoke: Review of evidence since 1998. Update of evidence on health effects of secondhand smoke.  Department of Health, UK 2004. http://www.smokefreeengland.co.uk/files/scoth_secondhandsmoke.pdf
9. Vardavas CI, Panagiotakos DB. The causal relationship between passive smoking and inflammation on the development of cardiovascular disease: a review of the evidence. Inflamm Allergy Drug Targets 2009; 8(5): 328–333.
10. Action on Smoking and Health. Research Report. Secondhand smoke: the impact on children. March 2014. http://www.ash.org.uk/files/documents/ASH_596.pdf
11. Sleiman M, et al. Formation of carcinogens indoors by surface-mediated reactions of nicotine with nitrous acid, leading to potential thirdhand smoke hazards. PNAS 2010; 107(15): 6576–6581.
12. Matt GE, et al. Thirdhand tobacco smoke: emerging evidence and arguments for a multidisciplinary research agenda. Environ Health Perspect. 2011; 119(9): 1218–1226.
13. Connor Gorber S, et al. The accuracy of self-reported smoking: a systematic review of the relationship between self-reported and cotinine-assessed smoking status. Nicotine Tob Res. 2009; 11(1): 12–24.
14. Florescu A, et al. Methods for quantification of exposure to cigarette smoking and environmental tobacco smoke: focus on developmental toxicology. Ther Drug Monitg. 2009; 31(1): 14–30.
15. Avila-Tang E, et al. Assesing secondhand smoke using biological markers. Tob Control 2013; 22: 164–171.
16. Schepers G, Walk RA. Cotinine determination by immunoassays may be influenced by other nicotine metabolites. Arch Toxicol. 1988; 62(5): 395–397.
17. Tate J, Ward G. Interferences in immunoassay. Clin Biochem Rev. 2004; 25(2): 105–120.
18. Honour JW. Development and validation of a quantitative assay based on tandem mass spectrometry. Ann Clin Biochem. 2001; 48(2): 97–111.
19. Dunlop AJ, et al. Determination of cotinine by LC-MS-MS with automated solid-phase extraction. J Chromatogr Sci. 2014; 52(4): 351–356.
20. Matuszewski BK, et al. Strategies for the assessment of matrix effect in quantitative bioanalytical methods based on HPLC-MS/MS. Anal Chem. 2003; 75(13): 3019–3030.
21. Grana R, et al. E-cigarettes: a scientific review. Circulation 2014; 129(19): 1972–1986.

The authors
Allan Dunlop¹* PhD, Bernard Croal² MD and James Allison² BSc
¹Department of Clinical Biochemistry Laboratory, Southern General Hospital, Glasgow G51 4TF, UK
²Department of Clinical Biochemistry, Aberdeen Royal Infirmary, Aberdeen AB25 2ZD, UK
*Corresponding author
E-mail: allandunlop@nhs.net

Helicobacter cinaedi is a relatively recently identified bacterium, but it is recognized as an increasingly important cause of disease in humans. This article summarizes methods for its detection and identification as well as routes of infection and treatment.

by Prof. Yoshiaki Kawamura, Dr Tatsuya Okamoto, Dr Shigemoto Fujii and Prof. Takaaki Akaike

What is Helicobacter cinaedi?
Within the genus Helicobacter, 33 species to date have been proposed and validated, but only 7 species have been isolated from human clinical specimens (Table 1). H. pylori, classified as a ‘gastric Helicobacter species’, is a well-known member of Helicobacter, but some less well-known ‘enterohepatic Helicobacter species’, such as H. cinaedi, H. bilis, H. canadensis, H. canis, H. fennelliae, and H. pullorum, have also been isolated from human clinical specimens.

H. cinaedi was first isolated as a Campylobacter-like organism type 1 (CLO-1) in 1984 from rectal swabs from homosexual men displaying intestinal symptoms [1] and the following year the organism was named ‘Campylobacter cinaedi’; however, it was subsequently reclassified as Helicobacter [2]. During the last two decades, there have been many reports of the isolation of H. cinaedi from blood or intestinal tract of human immunodeficiency virus-infected or immunocompromised patients, but, recently, increasing numbers of infections have also been reported in immunocompetent patients.

In Japan, the isolation of H. cinaedi was first reported in 2003; since then, its isolation has been reported from patients regardless of gender and within a wide age range, from the newborn to the elderly, in many hospitals throughout the country. We have experienced many cases of H. cinaedi cellulitis and bacteremia in both immunocompromised and immunocompetent subjects in hospitals. This microorganism should, therefore, be considered a causative agent of nosocomial infection [3].

Illnesses caused by H. cinaedi
Clinical symptoms of H. cinaedi infection include fever, diarrhoea, abdominal pain, gastroenteritis, proctitis, cellulitis, erysipelas, arthritis, meningitis, and bacteremia. In contrast to other Helicobacter species, numerous reports have causally linked H. cinaedi infection with bacteremia, which contributes to this organism’s strong vascular invasion ability. In many cases of H. cinaedi bacteremia, the main symptom is fever accompanied by arthritis and cellulitis at various sites. In addition to these sites providing a source of primary infection, the resultant bacteremia can serve as a source of secondary infections; thus, all these various symptoms are clinically important.

In our experience, at various times after orthopedic surgery (range, 8–113 days; mean, 29 days), some patients had a sudden onset of local flat cellulitis (salmon-pink in colour) at different sites on the operated side, along with fever and an increase in C-reactive protein level (Fig. 1) [3]. Cellulitis was often multifocal without wound infection. Many of these patients had been treated for fracture and were immunocompetent.

In recent years, we have demonstrated the potential association of H. cinaedi with atrial arrhythmias and atherosclerosis [4]. This could be through bacterial translocation of H. cinaedi from the intestinal tract into the blood stream. The possible cause-and-effect relationship between H. cinaedi and vascular diseases may warrant further epidemiological study on proatherosclerotic effect of H. cinaedi infection.

The virulence factor of H. cinaedi is largely unknown. The complete genome sequence of a human clinical isolate was announced in 2012 [5] and revealed that the organism holds a Type VI secretion system, which is expected to be related to its virulence, together with two known virulence factors, cytolethal distending toxin and alkyl hydroperoxide reductase.

Detection, cultivation and identification of H. cinaedi
It is well known that H. cinaedi is a fastidious and slow-growing organism, and that detection and cultivation are extremely difficult. In many cases, H. cinaedi is first detected from a blood culture using an automatic blood culture system. It is generally noted that 4–10 days (average 5.6 days, in our experience) are needed for a positive result in the culture bottle of an automatic blood culture system, such as the BACTEC system (Becton Dickinson) using an aerobic bottle. Therefore, when the culture test using this system is terminated within 3–4 days, the bacterial growth may be still below its detection limit. Information on the detection of H. cinaedi using the BacT/ALERT system (Biomérieux) is scanty. In our experience, the VersaTREK system (Thermo Scientific) is superior for the detection of this microorganism.

Both H. cinaedi and H. pylori are members of the genus Helicobacter; however, the former is extremely difficult to culture. H. cinaedi isolates essentially require microaerobic conditions (5–10% O₂) and a high level of humidity. Often a blood agar plate stored in a refrigerator for a few days may fail to support the growth of H. cinaedi because of low water content. Use of fresh medium is strongly recommended. It is established that H. cinaedi growth is accelerated by adding hydrogen gas (5–10%) to microaerobic conditions. The culture success rate can be improved by using a gas mixture such as 6% O₂, 7% H₂, 7% CO₂, and 80% N2 at the initial culture from the clinical specimen or in the culture bottle. Unfortunately, many of the commercially available microaerobic gas-generating packs, such as the GasPak system (Becton Dickinson), deoxidize and generate CO₂ but do not generate hydrogen gas; therefore, in some cases H. cinaedi does not grow, or growth is inadequate.

H. cinaedi cultured on an agar plate grows in a film, which is difficult to identify visually. Therefore, the culture should be carefully checked on the plate.

The biochemical identification of this organism is problematic owing to unstable phenotypic reactions. In many cases commercially available identification kits do not produce reliable results. Therefore, identification based on nucleotide sequence or species-specific polymerase chain reaction (PCR) has been used. We have developed a nested PCR system with high specificity and sensitivity (approximately 10² CFU/ml) for detecting H. cinaedi [6]. We have also established an immunological diagnosis method (antibody detecting test) with high specificity to detect the exposure history of H. cinaedi [7].

Antimicrobial therapy and prognosis
To date, antimicrobial susceptibility testing for H. cinaedi has mainly used the agar-dilution method, but this method is too cumbersome for routine use in hospital laboratories. A broth microdilution method for antimicrobial susceptibility testing of H. cinaedi, which can be performed easily, has been developed by our research group [8].

H. cinaedi strains generally show low minimum inhibitory concentration (MIC) values for carbapenems, aminoglycosides, and tetracycline (MIC₉₀ = 1 µg/ml for imipenem/cilastatin, gentamicin, and tetracycline). In contrast, H. cinaedi has well-known resistance to macrolides, with especially high MIC values (MIC₉₀ >64 µg/ml for erythromycin). Recently in Japan and elsewhere, H. cinaedi isolates have shown high resistance to quinolones (MIC₉₀ = 64 µg/ml for ciprofloxacin and levofloxacin) due to point mutation(s) of DNA gyrase genes [8].

Symptoms caused by H. cinaedi, such as fever or cellulitis, usually resolve after 2 to 3 days of drug therapy, but the Centers for Disease Control and Prevention recommended long-term therapy for about 2 to 6 weeks, rather than short-term therapy for only 10 days [9]. Prognosis is generally good, but it is noteworthy that, depending on the study, about 30–60% of patients have recurrent symptoms. Unfortunately, there are no guidelines for the treatment of H. cinaedi infections, including the clinical breakpoints of antimicrobial agents. The MIC values described above are based on our data.

Infection route
H. cinaedi has been found in a wide range of animals including cats, dogs, hamsters, rats, and foxes. There have been many reports of zoonotic transmission vectors, but no reports of the simultaneous isolation of H. cinaedi from human patients and the animals that they have been in close contact with. It is noteworthy that H. cinaedi isolates from human, dog, and hamster formed a distinct ribotype pattern group by host source [10].

Epidemiological analysis methods, such as pulse-field gel electrophoresis, randomly amplified polymorphic DNA, and multilocus sequence typing, have been proposed for H. cinaedi isolates [3, 11]. As described above, we developed a nested PCR system and immunological diagnosis method. Using these methods, we tested many healthy hospital employees (doctors, nurses, staff members, etc.) and found that some currently uninfected individuals had previously had H. cinaedi infections, indicating that there could be asymptomatic carriers with intestinal colonization of H. cinaedi. Our study also suggested that occurrence of such asymptomatic carriers may be related to nosocomial infection.

However, the complete route of infection route, including nosocomial transmission, of H. cinaedi remains unclear.

Summary
A full understanding of H. cinaedi infection remains elusive; however, some features and the clinical relevance of this infection have become increasingly recognized recently. To detect and isolate H. cinaedi from human blood samples using an automated blood culture system, a long-term incubation (up to 10 days) is needed and further skillful culture techniques are required. In many clinical laboratories, however, appropriate culture for isolation of this bacteria might not performed, which may lead to false-negative findings for H. cinaedi. As H. cinaedi was considered not to cause acute severe disease, it seems that its importance may have not been recognized clinically. However, we now know that this microorganism likely causes nosocomial infections that are difficult to eradicate and have a high incidence of recurrence. In recent years, a possible association with chronic illnesses such as arrhythmia and arteriosclerosis has been reported, and therefore we will need to carefully monitor and ascertain trends in H. cinaedi infections.

References
1. Fennell CL, et al. E. Characterization of Campylobacter-like organisms isolated from homosexual men. J Infect Dis. 1984; 149: 58–66.
2. Vandamme P, et al. Revision of Campylobacter, Helicobacter, and Wolinella taxonomy: emendation of generic descriptions and proposal of Arcobacter gen. nov. Int J Syst Bacteriol. 1991; 41: 88–103.
3. Kitamura T, et al. Helicobacter cinaedi cellulitis and bacteremia in immunocompetent hosts after orthopedic surgery. J Clin Microbiol. 2007; 45: 31–38.
4. Khan S, et al. Promotion of atherosclerosis by Helicobacter cinaedi infection that involves macrophage-driven proinflammatory responses. Sci Reports 2014; In press.
5. Goto T, et al. Complete genome sequence of Helicobacter cinaedi strain PAGU611, isolated in a case of human bacteremia. J Bacteriol. 2012; 194: 3744–3745.
6. Oyama K, et al. Identification of and screening for human Helicobacter cinaedi infections and carriers via nested PCR. J Clin Microbiol. 2012; 50: 3893–3900.
7. Iwashita H, et al. Identification of the major antigenic protein of Helicobacter cinaedi and its immunogenicity in humans with H. cinaedi infections. Clin Vaccine Immunol. 2008; 15: 513–521.
8. Tomida J, et al. Comparative evaluation of agar dilution and broth microdilution methods for antibiotic susceptibility testing of Helicobacter cinaedi. Microbiol Immunol. 2013; 57: 353–358.
9. Kiehlbauch JA, et al. Helicobacter cinaedi-associated bacteremia and cellulitis in immunocompromised patients. Ann Intern Med. 1994; 121: 90–93.
10. Kiehlbauch JA, et al. Genotypic and phenotypic characterization of Helicobacter cinaedi and Helicobacter fennelliae strains isolated from humans and animals. J Clin Microbiol. 1995; 33: 2940–2947.
11. Rimbara E, et al. Molecular epidemiologic analysis and antimicrobial resistance of Helicobacter cinaedi isolated from seven hospitals in Japan. J Clin Microbiol. 2012; 50: 2553–2560.
12. Solnick JV, Schauer DB. Emergence of diverse Helicobacter species in the pathogenesis of gastric and enterohepatic diseases Clin Microbiol Rev. 2001; 14: 59–97.
 
The authors
Yoshiaki Kawamura¹ PhD; Tatsuya Okamoto² MD, PhD; Shigemoto Fujii³ PhD; Takaaki Akaike³* MD, PhD
¹Department of Microbiology, School of Pharmacy, Aichi Gakuin University, Nagoya, Japan
²Intensive Care Unit, National Center for Global Health and Medicine, Tokyo, Japan
³Department of Environmental Health Sciences and Molecular Toxicology, Tohoku University Graduate School of Medicine, Sendai, Japan
*Corresponding author
E-mail: takaike@med.tohoku.ac.jp