The Breathprint of COVID-19

Bad breath in those infected with COVID-19 might be the least of their problems. But studying it helps in understanding the mechanisms of this deadly respiratory disease and developing diagnostic tests. 

Dozens of confirmed cases of halitosis owing to active infection by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) have been reported in the literature (Patel & Woolley, 2020; Riad et al, 2020)

Possible explanations were decreased salivatory flow due to angiotensin‐converting enzyme 2 receptor-mediated alterations in the tongue, a greater risk of bad breath for mouth breathers who are also more prone to halitosis and increased attention to odor when wearing face masks. Another likely explanation is bacterial co‐infections arising from the novel coronavirus.

DNA analyses of microbial communities in the respiratory tract of those infected with SARS‐CoV‐2 frequently detect abnormally high bacterial reads of Prevotella, Streptococci, Treponema, Veillonella and Fusobacteria, known to emit malodorous volatile sulfur compounds and volatile fatty acids (VFAs). In addition to odor, VFAs could impair T- and B-cell proliferation responses and cytokine production.

What molecules could we expect to find in a person infected with the novel coronavirus? Lamote and colleagues review dozens of (often overlapping) molecules detected in other infections. Among those are aliphatic alcohols, branched hydrocarbons, alkane derivatives, terpenes, dimethyl sulfide and other sulfur and nitrogen-containing compounds. Three aldehydes (octanal, nonanal, and heptanal) drew special attention as candidate biomarkers in pediatric SARS-Cov-2 infection (Berna et al., 2020). These three biomarkers demonstrated 100% sensitivity and 66.6% specificity. Analysis of breath in two groups of adults with median ages 40 and 60 identified aldehydes (ethanal, octanal), ketones (acetone, butanone), and methanol that discriminated COVID-19 from other conditions. Aldehyde Heptanal had significant predictive power for severity of the disease.

It has been shown that properly trained dogs  are able to detect an olfactory signature of SARS-CoV-2 infection with a specificity greater than 90%. Several clinical trials have been initiated to study biomarkers of COVID-19 in breath by e-nose and other technologies. Two studies have been already completed and one paper reported successful detection using Aeronose (Wintjens et al, 2020) with 86% sensitivity and negative predictive value of 92%. Gas Chromatography-Ion Mobility Spectrometry allowed differentiation of patients with definite diagnosis of Covid-19 from non-Covid-19 with about 80% accuracy and 82.4%/75% to 90%/80% sensitivity/specificity. 

REFERENCES

Patel J, Woolley J. Necrotizing periodontal disease: Oral manifestation of COVID‐19. Oral diseases. 2020 Jun 7.

Riad A, Kassem I, Hockova B, Badrah M, Klugar M. Halitosis in COVID-19 patients. Special care in dentistry: official publication of the American Association of Hospital Dentists, the Academy of Dentistry for the Handicapped, and the American Society for Geriatric Dentistry. 2020 Nov.29

Lamote K, Janssens E, Schillebeeckx E, Lapperre TS, De Winter BY, Van Meerbeeck JP. The scent of COVID-19: viral (semi-) volatiles as fast diagnostic biomarkers?. Journal of breath research. 2020 Jun 29.

Berna AZ, Akaho EH, Harris RM, Congdon M, Korn E, Neher S, Farrej MM, Burns J, John AO. Breath biomarkers of pediatric SARS-CoV-2 infection: a pilot study. medRxiv. 2020 Dec. 7

Ruszkiewicz DM, Sanders D, O'Brien R, Hempel F, Reed MJ, Riepe AC, Bailie K, Brodrick E, Darnley K, Ellerkmann R, Mueller O. Diagnosis of COVID-19 by analysis of breath with gas chromatography-ion mobility spectrometry-a feasibility study. EClinicalMedicine. 2020 Oct 24:100609.

Wintjens AG, Hintzen KF, Engelen SM, Lubbers T, Savelkoul PH, Wesseling G, van der Palen JA, Bouvy ND. Applying the electronic nose for pre-operative SARS-CoV-2 screening. Surgical endoscopy. 2020 Dec 2:1-8.

Of blood and breath: metabolite-based diagnosis of ovarian cancer

Physicians always knew that breath contains clues to diseases. Chemicals in breath often correlate with chemicals in saliva and blood - be it alcohol, anaesthetics or other metabolites (see, for example, this study by Dr Andreas Hengstenberg).

As one of my interests is breath-based detection of ovarian cancer, I took note of the recent paper claiming 99% to 100% accuracy of detecting ovarian cancer by metabolites in blood.
The authors used customized functional support vector machine-based machine-learning algorithms to classify thousands of metabolites measured by mass spectrometry (JEOL AccuTOF™ DART® that allowed to forego conventional liquid chromatography as sufficient resolution was achieved without separation) in peripheral blood. 

100% sensitivity and 100% specificity was achieved with 64-30 split validation technique, while 100% sensitivity and 98% specificity was the accuracy of leave-one-out-cross-validation. Very large number of metabolites, from 2,000 to 3,000 features, contributed to such discriminatory power (see the list of 14,000+ in supplemental material) 
 

Set of 25 canonical metabolic pathways relevant to the uploaded elemental
formulae ranked according to their p-values (hypergeometric distribution).

Histamine, amino acid, fructose and glucose metabolism were among the most prominent processes discriminating cancer and healthy blood.
It's that simple: sugar feeds cancer. Scientists have long found that cancer cells slurp fructose, and that fructose intake can be linked to some cancers. Histamine/polyamine interplay in cancers is also known. Histamine may be involved in inhibition of the local immune response against cancer. Is amino acid metabolism also linked to cancer? Well, what is not.   




Metabolomic biomarkers were always known to have diagnostic potential - cholesterol and glucose are among the oldest and most widely performed diagnostic tests. Yet, most bleeding edge cancer detection platforms are genomic or proteomic in nature.  Of the thousands of known biomarkers, only a handful have made it into the clinic. Existing ovarian cancer tests mostly rely on detecting a protein -  carbohydrate antigen 125. Vermillion's OVA1 and HealthLinx OvPlex tests use five proteins. This may be extended to 7.

Metabolites represent the end products of the genome and proteome, thus metabolomics-based diagnostics  holds the promise of providing powerful diagnostics,  allowing for differentiation of increased and decreased levels of chemicals with low process coefficient of variation.


Metabolomic tests were used for medical diagnostics starting with Hippocrates and Lavoisier. They continue to be explored by modern scientists. Dr Michael Phillips, for example, developed HeartsBreath Test, approved by the US Food and Drug Agency for early diagnosis of heart transplant rejection. Research proved the potential of inexpensive breath tests in discriminating lung, breast, colon and prostate cancers. Let's hope the new article  - along with others - will lead to novel consumer products, not only more academic research and peer-reviewed publications.



Zhou M, Guan W, Walker LD, Mezencev R, Benigno BB, Gray A, Fernández FM, & McDonald JF (2010). Rapid Mass Spectrometric Metabolic Profiling of Blood Sera Detects Ovarian Cancer with High Accuracy. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology PMID: 20699376

Odor-prints: individual but genetic connections unclear

Odor is like fingerprints or facial features - it's unique.  Yet no single measurement could be easily applied to recognize an individual.

GC/MS measurements can be used to analyze mixtures of acids, alcohols, aldehydes, hydrocarbons, esters, ketones, and nitrogenous molecules in human odor. Complex algorithms mining patterns help to pinpoint the signatures. But could these signatures be easily derived from genetic makeups?

Recent article published in the Journal of Chemical Ecology looked at the usual suspects -  major histocompatibility locus (MHC) and found that these genes do not determine major patterns. 


Volatile carboxylic acids are the most diverse class of known axillary odorants, and the pattern of these acids is genetically determined. These acids  - like vast majority of human odorous compounds - are produced by human microbiome, in this case by skin bacteria. Odors of 12 families, comprising 3 to 6 siblings,were analyzed with comprehensive two-dimensional gas chromatography (GC x GC) and time-of-flight mass spectrometry (ToF MS). the analysis onfirmed the presence of individual signatures. but failed to find odors specific to HLA genes.

Even though paternally inherited HLA-associated odors were proposed to influence women odor preferences, genetic basis of odors may be more complicated than previously thought.

References

Natsch A, Kuhn F, & Tiercy JM (2010). Lack of Evidence for HLA-Linked Patterns of Odorous Carboxylic Acids Released from Glutamine Conjugates Secreted in the Human Axilla. Journal of chemical ecology PMID: 20623248

Thompson EE, Haller G, Pinto JM, Sun Y, Zelano B, Jacob S, McClintock MK, Nicolae DL, Ober C. (2010) Sequence variations at the human leukocyte antigen-linked olfactory receptor cluster do not influence female preferences for male odors. Hum Immunol. 2010 Jan;71(1):100-3. PMID: 19833159 
 
Jacob S, McClintock MK, Zelano B, Ober C (2002) Paternally inherited HLA alleles are associated with women's choice of male odor. Nature Genet 30: 175-179  PMID: 11799397  PDF