Anthony Macherone

A primary impediment to cannabinoid research is the fact that materials possessing psychoactive Δ

-tetrahydrocannabinol (THC) are considered Schedule I drugs as defined in the U.S. Controlled Substances Act. An alternative source of cannabinoids may be found in hemp oil extracts. Hemp contains a low percentage of THC by weight but relatively high amounts of nonpsychoactive cannabinoids. The liquid chromatography–time-of-flight mass spectrometry (LC–TOF-MS) method presented herein allows for the accurate, precise, and robust speciation, profiling, and quantification of cannabinoids in hemp oil extracts and commercial cannabinoid products for research and development laboratories. The method was determined to chromatographically separate 11 cannabinoids including differentiation of Δ

-tetrahdrocannabinol and THC with excellent linear dynamic range, specificity, and sensitivity.

	Analysis of hemp extracts has increasingly become an area of scientific interest. Hemp is a fibrous variety of 

-tetrahydrocannabinol (THC) component and contains as many as 60 nonpsychoactive cannabinoid compounds (1). Hemp oil and hemp extracts therefore offer a source of cannabinoids that can be used for research purposes in many laboratories.

	Common analyses for cannabis and cannabinoid products include residual solvent analysis, terpene profiling and quantitation, pesticide residue analysis, toxic metal analysis, and cannabinoid profiling and quantitation. Traditional analytical platforms for profiling and quantification of cannabis and cannabinoid products include thin layer chromatography (TLC), gas chromatography–flame ionization detection (GC–FID), gas chromatography–mass spectrometry (GC–MS), and high performance liquid chromatography with ultraviolet (HPLC–UV) detection. The method presented herein allows for the profiling and quantification of cannabinoids in hemp oil products via liquid chromatography with time-of-flight mass spectrometry detection (LC–TOF-MS). Using LC–TOF-MS improves cannabinoid analysis through high resolution, accurate mass information for speciation and increased linear dynamic range compared to traditional fixed-wavelength UV detection.

	An Agilent 1290 Infinity II ultrahigh-pressure liquid chromatography (UHPLC) system and 6230B LC–TOF-MS system (Agilent Technologies) were used for these analyses. The LC–TOF-MS data were compared to data collected on the UHPLC system with diode-array detection (DAD) for range and linearity comparisons.

	The UHPLC system used for both the UHPLC–DAD investigations and the LC–TOF-MS work included a quaternary pump, a multisampler automated sampling system with flush port, a multicolumn thermostated column oven, and a diode-array detector. The analytical column was a 100 mm x 2.1 mm, 1.8-µm 

 Zorbax Bonus RP column (Agilent Technologies). The column oven and autosampler temperatures were 50 °C and 23 °C, respectively. The needle wash was set to 3.5 s at the flush port with a solution of 25:25:50 water–isopropanol–methanol and the injection volume was 0.05 µL. The diode-array detector was fixed to a wavelength of 280 nm. Mobile-phase A was water, B was methanol, and C was 0.1% (v/v) formic acid plus 2.2 mL of 5.0 M ammonium formate per liter in water. The flow rate was set to 0.50 mL/min and the mobile-phase gradient started at 23% A, 72% B, and 5% C increasing B to 95% linearly from time = 0.00 min to time = 12.5 min while holding C constant at 5%. The method stop time was 15 min and the reequilibration time was 5.0 min, resulting in an overall cycle time of 20 min. It should be noted that the analytical run time can be reduced to 7.25 min (including a 1.0-min post time) by using a 50 mm x 2.1 mm, 1.8-µm 

 Zorbax Bonus RP column (Agilent Technologies) and decreasing the gradient time from 12.5 min to 6.25 min, keeping all other parameters as above. Figure 1 shows the chemical structures for the compounds used in this work.

	The experimental conditions for the LC–TOF-MS system were as follows: dual electrospray ionization (ESI) source in positive ionization mode, drying gas (nitrogen) at 10 L/min, drying gas temperature at 350 °C, nebulizer gas (nitrogen) at 40 psi, capillary voltage at 4000 V, and fragmentor voltage at 70 V. The spectral acquisition rate was 1.0 Hz over 100–1700 

. The internal reference mass was enabled using 121.0508730 

 as the target ions to correct for TOF drift over time.

	Commercially available cannabinoid standards prepared at 1.0mg/mL in organic solvent were purchased from Cerilliant Corporation and used for method development and unknown analysis. Table I illustrates the empirical formula, accurate mass, and retention time for these compounds. Seven samples of commercially available hemp oil products were purchased from four manufacturers for unknown analysis, profiling, and quantification. Table II lists these with product descriptions and masked identifiers.

	For LC–DAD analyses, calibrators containing a mixture of the commercial standard solutions were prepared over a range of 50–1000 µg/mL. For LC–TOF-MS analyses, calibrators containing a mixture of the commercial standard solutions were prepared over a range of 100–5000 µg/mL for method development and 10–1000 µg/mL for the analysis of the unknown samples. A second lower concentration calibration curve was created to establish THC limits of detection via LC–TOF-MS for samples ostensibly containing very low levels of this compound. The THC curve ranged from 12.5 ng/mL to 1000 ng/mL in solvent.

	Aliquots (100 µL) of each commercially purchased sample were diluted 100-fold with dichloromethane followed by a 10-fold dilution in methanol. This limited cleanup of the samples requires a longer analysis time to allow for all the noncannabinoid components to be eluted from the column. Allowing for the longer analysis time of 20 min ensures reproducible retention times and lower carryover.

	Using software packages inherent to the Agilent MassHunter software suite, a custom spectral library was created. The library format is referred to as a personal compound database library (PCDL) and contains spectral data, accurate mass, retention time, CAS number, and other optional information for each unique compound including MDL *.MOL files or SMILES strings. The input data were acquired for each standard solution using the LC–TOF-MS method described above for the 100-mm column. Spectral data were copied into the PCDL. Other pertinent information was captured using the copy–paste clipboard or entered manually. After the library was built, it was used to identify cannabinoids in unknown samples akin to other common library searching workflows.

	A series of known calibrator and unknown sample data was acquired on both the UHPLC–DAD and LC–TOF-MS systems through an automated sequence. Calibration curves were constructed for each targeted analyte for both methods. Concentrations of the various cannabinoids in the unknowns were determined using externally standardized curves-that is, the slope and intercept of the linear regression curves were used for quantification. Equation 1 illustrates this relationship:

	where “absolute abundance” is the calculated UV absorption via UHPLC–DAD as determined by Beer’s law or total ion counts for the LC–TOF-MS data.

	The UHPLC–DAD calibration curves span 50–1000 µg/mL with linear regression coefficients (

) ≥ 0.999 for the targeted cannabinoids. Similarly, the 

 coefficients for the LC–TOF-MS data were at least 0.999 for all compounds over both the 100–5000 µg/mL and the 10–1000 µg/mL calibrator ranges. Limits of quantitation (LOQ) over these ranges were similar on both the UHPLC–DAD and LC–TOF-MS systems for all cannabinoids. Since the nonpsychoactive cannabinoid concentration in the samples is very high compared to THC levels, and the laboratory was not limited by sample amounts, LOQ and limit of detection (LOD) may not be as important for these compounds. However, the unknown samples were purported to contain very low levels of THC and this assertion should be confirmed. Therefore, we also evaluated the LC–TOF-MS data down to 12.5 ng/mL for THC LOD and LOQ experiments. A limit of detection of 1.0ng/mL could be achieved using a signal-to-noise ratio (S/N) of 3:1 as the criterion, and an LOQ of 3.0 ng/mL (S/N ≥ 10:1) for THC was determined.

	The seven commercial hemp oil samples were prepared with the dilution schema described above and analyzed on the LC–TOF-MS system. Four replicate injections of each were acquired and the average, standard deviation, standard error, and confidence interval at the 99% confidence level were determined. Table III illustrates these results.

	Traditionally, analysis of cannabinoid potency and profiling of cannabinoids is performed via LC with UV detectors with fixed wavelengths or diode-array detectors that offer a third spectral dimension for each chromatographic peak. However, this methodology may lack the required specificity and sensitivity to properly analyze the diversity of hemp oil products commercially available. Herein we used LC–TOF-MS to evaluate the advantages of dynamic range, linearity, specificity, and ability to profile and quantify cannabinoids in commercially available hemp extract products as compared to HPLC–UV methods. Figure 2 illustrates the DAD chromatogram and extracted ion chromatograms for the cannabinoids identified in this work using the shorter UHPLC method. In these experiments we targeted â

-THC, THCV, THCA, CBN, CBC, CBD, CBDV, CBDA, CBG, and GBGA. In many cases, even with known references and retention time information, UV detection alone is not sufficient for compound identification because unknown interferences are common in real samples and can coelute and confound compound identification. The added information of accurate mass and high mass resolving power offers empirical formula generation to assist in compound identification and the ability to extract ions of interest from the background matrix, which greatly improves specificity as compared to UV or diode-array detection. LC–TOF-MS offers good linearity over a large dynamic range with limits of detection and quantitation that are lower than the UHPLC–DAD method employed herein for comparison. This method achieves excellent chromatographic separation for cannabinoids studied, including separation of Δ

	Analysis of the commercial samples resulted in quantitative values close to the purported concentrations offered on the product label or product website. For sample SIB, no cannabinoids were detected. Deviations occurred for SIC at 2.3 mg CBD/mL and SID was determined to be 9.3 mg CBD/mL, for which the product label suggests an approximate 8-mg/mL concentration. The ~3.5-fold lower concentration of SIC may be the result of the filtering process but this must be further evaluated. Samples SIE and SIF resulted in an approximately 50% higher concentration of cannabinoids than suggested on the product label. Lastly, samples SIA-1 and SIA-2 (same manufacturer and lot) differed in concentration determination by about 10%, but were double the purported 250 mg CBD/mL suggested on the product label. The authors acknowledge that these samples were not matrix matched to the calibrators and that may be a source for the discrepancies. Future studies will endeavor to do so and to rigorously determine method detection limits (MDL) through replicate analyses at multiple concentrations bracketing the above estimates.

	HPLC with UV detection and GC–MS are the most common analytical tools used for cannabinoid potency determinations. The UHPLC conditions given here can be equally applied to systems with UV detectors, single or tandem-quadrupole mass spectrometers, and time-of-flight mass spectrometers. The LC–TOF-MS method uses UHPLC to chromatographically separate the compounds. LC–TOF-MS allows for a rapid and robust method for the speciation and of quantification of cannabinoids in commercial hemp oil extract products. In addition, limits of quantification and detection are lower than those of traditional HPLC–UV and GC–MS methods. Lastly, the large dynamic concentration range of this LC–TOF-MS method enables the identification and quantification of cannabinoids in diverse commercial products.

What’s the Difference Between Hemp and Marijuana?

http://www.alternet.org/drugs/whats-difference-between-hemp-and-marijuana

 is Laboratory Director of CWC Labs in Austin, Texas. 

 are all Application Scientists with Agilent Technologies in Wilmington, Delaware. 

 is a Senior Scientist at Agilent Technologies and a Visiting Professor at The Johns Hopkins University School of Medicine in Baltimore, Maryland. Direct correspondence to: 

Articles

The method presented here allows for the accurate, precise, and robust speciation, profiling, and quantification of cannabinoids in hemp oil extracts and commercial cannabinoid products for research and development laboratories.

Liquid Chromatography–Time-of-Flight Mass Spectrometry for Cannabinoid Profiling and Quantitation in Hemp Oil Extracts

Estrogens play a key role in developing and maintaining the female phenotype, germ cell maturation, and pregnancy. Processes that are not gender specific, such as overall body growth, nervous system maturation, bone metabolism/remodeling, and endothelial responsiveness are also mediated by estrogenic compounds.. Although present in both genders, estrogen concentrations are significantly higher in females. Estrone (E1) and estradiol (E2) are the two major biologically active estrogens in nonpregnant humans, while a third bioactive estrogen, estriol (E3), is the main pregnancy estrogen (1). The clinical determination of serum estrogen levels often is used to monitor low-dose female hormone replacement therapy (HRT) and assess fracture risk in postmenopausal women. In premenopausal women, estrogen levels can be monitored to assess ovarian status, including follicle development, for assisted reproduction protocols such as in vitro fertilization. Estrogens also play a role in precocious as well as delayed puberty in females, and can be monitored as part of estrogen replacement therapy in hypogonadal premenopausal women, in conjunction with luteinizing hormone (LH) measurements. Estrogen level measurements are taken as well during aromatase inhibitor treatment of hormone-dependent breast cancer. 

Some of the metabolites of the estrogens have been implicated in disease development, such as increased systolic blood pressure in both males and females. Because the metabolites can have a longer half life than the estrogens themselves, there is interest in using them as biomarkers of disease. There is a clear association between excessive exposure to estrogens and the development of cancer in hormone-sensitive tissue such as breast and endometrium (2). The estrogen quinone metabolite, E2-3,4-quinone, has been identified as a potential risk factor, and a subset of women with particular cytochrome P450 enzyme haplotypes have an increased risk of breast cancer as a result (3). The catechol metabolites of estrogens are considered intermediates in estrogen-induced carcinogenesis and their mode of action might be to induce deoxyribonucleoside adducts (4,5). Estradiol is a potent preventative against oxidative neurodegenerative disease by virtue of the hyperoxide-dependent hydroxylation of E2 to its catechol metabolites. In addition, E2 and its metabolites 2-hydroxyestrone (2-OHE1) and 16 a-hydroxyestrone (16-OHE1) also are believed to curtail oxidative stress that can lead to disease conditions including atherosclerosis (6,7). Utilization of the estrogen metabolites as biomarkers will require reliable detection at ultra-low concentrations. 

Distinguishing serum E2 levels within the low postmenopausal range of <1 pg/mL to 30 pg/mL is a valuable tool in the study of common diseases of older women such as osteoporosis, cognitive dysfunction, cardiovascular disease, and breast cancer (8). Ultralow estrogen measurements  also are needed to diagnose inborn errors of sex steroid metabolism, disorders of puberty, and estrogen deficiency in men. Reaching the lowest levels also might be important in predicting risk of fractures (9) as well as monitoring response to antiestrogens for prevention of breast cancer (10) and degree of E2 suppression in women receiving aromatase inhibitor therapy (11,12).  

During second-line treatment of hormone-dependent breast cancer, basal and suppressed serum E2 levels are monitored in women receiving aromatase inhibitor therapy. However, assays for E2 were developed originally for younger women — that is, with a range of interest higher than 50 pg/mL. At decreased postmenopausal levels, these assays have varied in accuracy and have lacked standardization. Moreover, aromatase inhibitor therapy requires measurement of E2 at an order of magnitude lower than normal basal levels in postmenopausal women. Ultrasensitive cell bioassays can reach the required levels but are difficult to employ, not widely available, and are not completely specific. Isotopic kinetic methods have been used to determine the degree of E2 suppression but are not practical for clinical use (12). 

Direct and indirect immunoassays have been employed widely in clinical settings to measure E2. Indirect assays such as RIAs require an initial extraction step, whereas direct assays do not require extraction. However, both types of immunoassays have overestimated E2 concentrations in postmenopausal women versus mass spectral methods, and are less reproducible. 

Liquid chromatography–electrospray ionization tandem mass spectrometry (LC–ESI-MS-MS) methods have been developed to measure estrogens. ESI typically offers one the ability to analyze a compound, or panel of compounds, without the need for derivatization techniques commonly used in gas chromatography (GC)–MS applications. However, for an LC–MS-MS method to approach the detection limits described herein, derivatization is required. One such report states a detection limit of 1 pg/mL of dansyl derivatized E2 in serum (13). GC–MS-MS methods in the electron ionization (EI) mode also have been developed, but again do not have the sensitivity required for these applications. 

GC–MS-MS in NCI Mode Delivers Selectivity and Ultralow Detection

The power of negative chemical ionization (NCI) to eliminate chemical interferences provides the ability to quantify therapeutic and subtherapeutic levels of estrogens in complex matrices, when utilized on a GC–MS-MS platform (14,15). These assays typically provide much lower limits of quantification than the LC–MS-MS counterparts, which do not have the sensitivity required for these applications.  

Assays for estrogens performed on a GC–NCI-MS-MS platform usually require isolation of the analytes by solid-phase extraction (SPE) followed by derivatization. With automated extraction procedures and advancements in derivatization techniques, GC analysis has become competitive with LC sample preparation and sample analysis cycle times.  

Operation in NCI mode using halogenated derivatives allows for electron-capture processes to take place. Compared with EI mode, there is less fragmentation of the molecular ion, hence the term, "soft ionization." The result is a high degree of selectivity and sensitivity, with significantly improved detection limits. In NCI mode, selectivity for the analyte is higher relative to that for the matrix and other common interfering ions observed in EI or positive chemical ionization (PCI) modes. The result is less chemical noise, which translates directly into improved detection limits.  

Therefore, the key to sensitive detection when using GC–MS-MS in NCI mode is the optimal derivatization moiety. The pentafluorobenzoyl ester derivatives of estrogens have been shown to be stable and provide diagnostic negative molecular ions (16). These derivatives have proven to be superior to trifluoroacetyl, heptafluorobutyl, pentadecafluorooctanoyl, and perfluorotolyl derivatives (17).  

Table I: Regression analysis for estradiol and estrone standard curves*			

Sensitive, Precise, and Accurate Quantification of Estrogens 

An estrogen-specific assay has been developed on the GC–NCI-MS-MS that can detect as little as 0.15 pg/mL of estradiol reliably. Derivatization of the estrogens was carried out using pentafluorobenzoyl chloride and N-methyl-N-trimethylsilyltrifluoroacetamide (MSTFA), which resulted in the formation of the benzoyl ester for the phenol groups, and the trimethylsilyl (TMS) ether for the 17-hydroxyl group of estradiol. Figure 1 shows the structures of the resulting derivatives of estradiol and estrone. The GC method analysis time is approximately 5 min and the cycle time is approximately 6 min.  

The assay is repeatable as well as reproducible. Nearly 100 injections were made without the need for any routine maintenance. The signal-to-noise ratio (S/N) is greater than 10 and chemical interferences that could affect quantification are not detected. The assay is linear from 0.3 to 80 pg/mL of estrone and 0.75 to 200 pg/mL of estradiol, giving an R

  > 0.996 for both E2 and E1. Precision (%CV) and bias (% difference from expected) are less than 15% across the quantification range for both analytes as well (Table I). Three concentrations of serum QC samples were prepared and analyzed that bracketed the quantification range of the assay for both estrogens. Precision and bias are less than 11% (accuracy >89%) at all concentrations for estradiol, and less than 15% for all concentrations of estrone (Table II). Figure 2 illustrates the ease of detection at the lowest limit of detection (LLOD) for estradiol, 0.15 pg/mL (S/N = 41), as well as the lowest limit of quantification (LLOQ), 0.3 pg/mL. The LLOQ for estrone using this assay is 0.8 pg/mL (Figure 3). 

Table II: QC serum sample results for estradiol and estrone*			

There is a current and growing need to detect very low levels of estrogens and their catechol metabolites reliably. Traditional immunoassays cannot provide the selectivity needed, and LC–MS-MS systems, the current industry standard for bioanalytical analysis, fall short in the ability to chromatographically separate interferences and provide the sensitivity required to quantify levels of certain endogenous compounds. Analysis by GC–NCI-MS-MS has been the primary analytical tool for monitoring endogenous levels of analytes considered to be biomarkers. The selectivity of the derivative, the high performance separation of GC, the response of the halogenated derivatives in NCI mode, and the elimination of matrix interference by SRM analysis provide the needed performance in the development of a biomarker assay.  

There also have been significant advancements in the past few years in GC–MS-MS technology that maximize ion transmission and detection, and the use of fast GC would further reduce runtime. When the ultimate level of detection and quantification is required to measure an ultra-low level endogenous compound, then a GC–NCI-MS-MS system might be the best alternative. 

 are application scientists with Agilent Technologies, Santa Clara, California. 

 is with Taylor Technology, Inc., Princeton, New Jersey.  

(1) Mayo Medical Laboratories web site, accessed 3/2/2010.  

http://www.mayomedicallaboratories.com/test-catalog/Clinical+and+Interpretive/81816

A number of clinical situations now call for high-sensitivity measurement of estrogens, including monitoring during female hormone replacement therapy, antiestrogen treatment, and estrogen deficiency in men. Traditional immunoassay methods and liquid chromatography–tandem mass spectrometry (LC–MS-MS) do not provide the sensitivity and selectivity required for these applications. In contrast, a gas chromatography–negative chemical ionization–tandem mass spectrometry (GC–NCI-MS-MS) platform can provide detection limits below 1 pg/mL when used in conjunction with the appropriate derivatization protocol, with very short cycle times.

Anthony Macherone

Articles

Liquid Chromatography–Time-of-Flight Mass Spectrometry for Cannabinoid Profiling and Quantitation in Hemp Oil Extracts

Ultralow Detection of Estrogenic Compounds by GC–NCI-MS-MS