A new and simple analytical approach consisting of an automated headspace solid-phase microextraction (HS-SPME) sampler coupled to gas chromatography-ion trap/mass spectrometry detection (GC-IT/MS) with a prior derivatization step with O-(2,3,4,5,6-pentafluorobenzyl)hydroxylamine hydrochloride (PFBHA) was developed to detect volatile carbonyl metabolites with low molecular weights in human urine. A central composite design (CCD) was used to optimise the PFBHA concentration and extraction conditions that affect the efficiency of the SPME procedure. With a sample volume of 1 mL, optimal conditions were achieved by adding 300 mg/L of PFBHA and allowing the sample to equilibrate for 6 min at 62°C and then extracting the samples for 51 min at the same temperature, using a divinylbenzene/polydimethylsiloxane (DVB/PDMS) fibre. The method allowed the simultaneous identification and quantification of 44 carbonyl compounds consisting of aldehydes, dialdehydes, heterocyclic aldehydes and ketones. The method was validated with regards to the linearity, inter- and intra-day precision and accuracy. The detection limits ranged from 0.009 to 0.942 ng/mL, except for 4-hydroxy-2-nonenal (15 ng/mL), and the quantification limits varied from 0.029 to 1.66 ng/mL, except for butanal (2.78 ng/mL), 2-butanone (2.67 ng/mL), 4-heptanone (3.14 ng/mL) and 4-hydroxy-2-nonenal (50.0 ng/mL). The method accuracy was satisfactory, with recoveries ranging from 90 to 107%. The proof of applicability of the methodology was performed in a pilot target analysis of urine samples obtained from 18 healthy smokers and 18 healthy non-smokers (control group). Chemometric supervised analysis was performed using the volatile patterns acquired for these samples and clearly showed the potential of the volatile carbonyl profiles to discriminate urine from smoker and non-smoker subjects. 5-Methyl-2-furfural (p<0.0001), 2-methylpropanal, nonanal and 2-methylbutanal (p<0.05) were identified as potentially useful biomarkers to identify smoking habits.
- Carbonyl compounds
- Central Composite Design (CCD)
- HS-SPME-GC-IT/MS method
- Smoking habits
- Urinary biomarkers