Analysis of volatile biomarkers In Pursuit of Pregnancy — Sniffing Out the Potential
Women can turn to a variety of methods to determine the best time in their menstrual cycle for conception. Volatile biomarkers have proven useful indicators in other contexts and now, the analysis of biogenic VOCs has been shown to provide insights on female fertility.
When it comes to choosing a mate, or indeed a time to mate, Homo sapiens seems to rely more on olfactory than on visual sensing. The human sniffing organ has a range of talents; it detects olfactory information as well as virtually odorless pheromones emitted by others, allowing bodies to communicate subconsciously. Volatile organic compounds (VOCs) emitted from the female body are capable of triggering sexual desire in men. The VOCs in question are metabolites of female sex hormones, of which the most important are estrogen and progesterone. These hormones regulate the female menstrual cycle and influence a woman’s fertility. From an evolutionary and biological viewpoint, it is useful that ovulating females are perceived as particularly attractive by the male nose. It has been established that men are particularly attracted to women with a high level of estrogen combined with a low level of progesterone .
Estrogen and Progesterone —Female fertility at a Glance
The combination of a high estrogen level and low progesterone level is a clear indicator of female fertility. However, fertility varies throughout a woman’s life, and decreases with age. On a biological level, this can be explained by a decline in the estrogen level, which unfortunately doesn’t necessarily correlate with women’s individual desires to choose the time of pregnancy and motherhood adapted to their individual life planning. If Mother Nature plays along, planned motherhood is achievable. For an estimated 1.6 Million women under the age of 44 in the US alone, however, the path to pregnancy is long and arduous, with natural conception proving a persistent challenge, according to Stephanie Marie Ong from Arizona State University, USA .
The US market for fertility diagnostics is valued at 3.5 billion US dollars, but Ong states that it’s impossible to make reliable statements about the probability of a woman becoming pregnant, both in general, but also with increasing age. What is possible, however, is to determine the time of ovulation in a number of ways (and hence determine the optimum time to procreate), for example by monitoring the body temperature, using the calendar method and using special ultrasound or endocrinological examinations. However, according to Ong, all common means of conceiving, both clinically and otherwise, lack the ability to evaluate a woman’s fertility at a single point in time. In other words, they lack the ability to “quantify changes in the hormonal metabolism over time,” which would make it easier to draw more general conclusions about a woman’s fertility. A range of open questions concerning ovulation and physiological conditions as well as time-limiting factors remain. Ong is convinced that answering these questions would lead to a breakthrough in female reproductive health.
Analytical Set-up for Metabolism Study Needed
In order to understand the requirements for developing this kind of approach, methods are needed that can detect reproductive hormones in real time throughout a woman’s reproductive lifespan, as Ong writes in her master’s thesis . This might be achieved, for example, by analyzing the metabolites of the hormonal metabolism. The analysis of the totality of all metabolites in biological samples (metabolomics) has already proven useful in diagnosing certain hormone-related diseases.
In order to be effective, a metabolic study must be based on a method of analysis that can process a large enough number of biological samples containing the volatile metabolites to be statistically relevant. Those samples then need to be analyzed efficiently within a reasonable time frame . Urine, saliva and blood are all suitable samples. Ong selected urine as the sample basis since it can be obtained in a sufficiently large quantity in the simplest possible way. Sample extraction was carried out by automated solid phase microextraction (SPME) and a GC x GC-TOF-MS system was used for analysis. To develop an initial database, urine samples were collected daily for 28 days from ten women aged 18 to 28, of different ethnic backgrounds; none of the test subjects were using oral contraceptives or other drugs that could interfere with the hormonal balance and falsify the results of the analysis.
The aim was to monitor concentrations of volatile metabolites and determine their correlation with sex hormone levels throughout the entire menstrual cycle. Prior to sampling (midstream urine), which took place under conditions of maximum sterility, the women were not allowed to eat for two hours. The samples were aliquoted within four hours after sampling and stored at -80 °C. To avoid contamination that might impact analysis results, Ong used 10 mL vials sealed with PTFE/silicone caps for the analysis, which had been conditioned at 100 °C for 12 hours to reduce the VOC background. Approximately one hour prior to analysis, they were brought to room temperature and one milliliter of sample was added just before the vials were sealed and placed on the cooled sample tray of the analysis system used (Gerstel Multi Purpose Sampler, MPS) where they were kept at 4 °C until analyzed. Each urine sample was then individually agitated at 250 rpm for five minutes at 60 °C and incubated. Volatile metabolites were extracted from the headspace above the sample using a SPME fiber coated with 30/50 µm DVB/CAR/PDMS. Before each sample extraction, the fiber was baked out at 270 °C for ten minutes. Extraction was carried out at 60 °C for 60 minutes while simultaneously agitating the sample at 250 rpm. The fiber was then positioned in the GC injector at 250 °C for five minutes to transfer analytes to the GC separation column. All steps from sample preparation to sample introduction were automated by the MPS.
Ong separated the analytes using a 2D-column set (GCxGC; Restek) (column 1: Rxi-624Sil MS [60 m x 250 μm x 1.4 μm], column 2: Stabilwax [1 m x 250 μm x 0.5 μm]). The columns were independently heated. The temperature program of the first column was as follows: 50 °C (2 min) -5 °C/min -225 °C (2 min) -30 °C/min -230 °C (30 min). The second column was heated with an offset of 5 °C relative to the primary GC oven. The detection was performed with a TOF-MS. A quad-jet modulator was used with 2 s modulation periods (0.5 s hot and 0.5 s cold pulses) with an offset of 15 °C relative to the secondary GC oven. Helium with a flow of 2 mL/min was used as carrier gas. Mass spectra were recorded at 100 Hz over a range of m/z = 35 to 550, using the ChromaTOF software (Leco).
Promising Results and Further Research
The method parameters described above are the result of extensive optimization with regard to the sample volume and the extraction time used. Ong calibrated the method daily and identified a total of 935 different analytes in the urine of the test subjects. Among them were ten compounds, which were found in the urine of all test subjects and which, after appropriate statistical evaluation, can be classified as key analytes for the female menstrual cycle. These included O-cymene, 4,7-dimethylbenzofuran, 3-octen-2-one, butyl-cyclobutane, 2,2-dimethylbutanal and 2-hexylfuran, among others, which showed either a clear increase during ovulation or a statistically significant correlation with hormonal changes. These could potentially serve as biomarkers for female fertility.
Further research on these key compounds is planned to validate the results and test the robustness based on additional independent data sets. n
 Janek S. Lobmaier, Urs Fischbacher, Urs Wirthmüller, and Daria Knoch, The scent of attractiveness: levels of reproductive hormones explain individual differences in women’s body odour. Proceedings of the Royal Society B, 12. September 2018, doi:10.1098/rspb.2018.1520, http://bit.ly/2XosFEE
 Stephanie Marie Ong, Comprehensive Analysis of Volatile Biomarkers for Female Fertility, Arizona State University, May 2018, http://bit.ly/2KrYCFY
 Guido Deußing, Automatisierte Massenanalyse – Epidemiologische Probensätze auf dem Prüfstand, Laborpraxis 9 (2016) 64-66, https://www.laborpraxis.vogel.de/epidemiologische-probensaetze-auf-