Wikipedia

User:Blueriver01/sandbox

Smells as Evidence of Diseases

Smell as evidences of disease has been long used, dating back to Hippocrates around 400 years BCE.[1][2] It is still employed with the focus on volatile organic compounds (VOCs) found in body odor.[1] VOCs are carbon-based molecular groups with a low molecular weight secreted from cells’ metabolic processes.[1] Their profiles may be affected by diseases such as cancer, metabolic disorders, genetic disorders, infections, and among others. Identifying abnormal changes in  VOC composition is available through equipment, such as gas chromatography-mass spectrometry(GC-MS), electronic noses, and trained non-human olfaction.[1][3]

History

edit

Physicians historically used odors as a diagnostic indicator to judge the patient’s health. Hippocrates saw the breath of patients as a potential indicator in around 400 BCE.[4] Galen, Avicenna, and more physicians considered urine scent alongside color, density, sediments, and more in urinalysis.[5] Urine with sweet odor was deemed to be caused by dominating sanguine humor- possessing too much blood; pungent odor was associated with an excess amount of bile; foul odor indicated the presence of ulcers in the urinary tract or development of putrefactive fever - fever occurring in the humours.[4][5][6]

VOCs are currently deemed as potentially valuable, noninvasive diagnostic biomarkers.[7]

Volatile Organic Compound (VOC)

edit

The biochemical mechanism of VOC generation in the human body is not fully comprehended.[8] Their occurrence is due to change in cell metabolism, inflammation, and oxidative stress, where reactive oxygen species (ROS) produced from cellular respiration interact with cellular structures as the membrane, proteins, DNA, and RNA to create VOCs.[8][9] The accumulation occurs in breath, skin, sweat, blood, urine, and faeces.[7] Difference in samples and methods of analysis chosen may explain the high heterogeneity observed in VOCs identified by various research concerning diseases.[4]

VOCs analysis are seen in asthma, chronic obstructive pulmonary disease (COPD), cystic fibrosis (CF), chronic obstructive sleep apnea (OSA), inflammatory bowel disease, metabolic disease, cancer, infections and among others.[7][4][10][11]

 
Schematics of electronic nose and biological olfactory system

Non-compound-specific identification

edit

Electronic nose (e-noses) is another standard method used for non-compound-specific identification where arrays of broadly tuned sensors capture patterns or fingerprints of VOCs to distinguish between healthy and disease individuals.[12][13][14] The limitation is the inability of them to identify individual biomarkers and subsequently unable to identify unique biomarkers for diseases.[12]

Compound-specific identification

edit

Gas chromatography with mass spectrometry (GC-MS)is considered the gold standard for VOC analysis.[15] The chromatography separates the sample mixture in a gaseous state by forcing them through a column using a carrier gas, and the mass spectrometer identifies the compound.[16] The limitation of the method is the requirement of expensive specialized equipment and highly trained personnel.[17] Other methods of detection used are selected-ion flow-tube mass spectrometry (SIFT-MS) and field asymmetric ion mobility spectrometry (FAIMS).[11]

Potential diagnostic applications

edit

Cancer

edit

Lung cancer-specific VOCs are 1-propanol, endogenous primary alcohol, and pentane.[4] Pentane's presence in exhaled breath of patients has been hypothesized to originate from the increased peroxidation of fatty acids seen in severe lung disease.[4] While not specific to a type of cancer, foul-smelling p-cresol was found solely in colorectal and gastric cancer, expected to be caused by cancer’s alteration of the microbiome.[4] No singular compound could be exclusively considered a biomarker, but VOCs patterns observed may aid in distinguishing certain diseases. [4]

Metabolic disorder

edit

People with diabetes were found to have an increased concentration of ketones, the cause of sweet urine smell, derived from the oxidation of non-esterified fatty acids.[13][18] Exhaled acetone is often used as a biomarker, but its relevance as a sole biomarker for diabetes is ambiguous as acetone is deemed a biomarker in other diseases, such as lung cancer and cystic fibrosis (CF), and reports on acetone and blood glucose have been mixed.[19]

Maple syrup urine disease, characterized by a strong maple syrup scent in urine, is found to have higher keto acid levels.[20]

Infectious disease

edit

The breath of patients infected with Aspergillus fumigatus- a fungus responsible for invasive aspergillosis- showed the presence of 2-pentylfuran, a compound not ordinarily produced in mammalian metabolism.[21] VOC profiles may be affected by intakes of peanuts, soy milk, and more, which also display 2-pentylfuran.[21]

Non-human olfaction

edit
 
Sagittal magnetic resonance imaging highlighting the inner structures of the canine olfactory system

Dogs

edit

Dogs have been used to effectively diagnose symptomatic and asymptomatic individuals with metabolic and infectious diseases due to their highly sensitive olfaction composed of 3 folds the number of functional genes encoding olfactory receptors than humans.[22] The dog’s highly developed sniffing specializes in recognizing messenger chemicals by receptors enables it to have 10,000 to 100,000 times more accuracy than a human’s smell.[22] Dogs have been frequently used to diagnose asymptomatic individuals with infectious diseases such as SARS CoV-2 and H1N1 Influenza.[22] Along with the functional genes coding for olfactory receptors, dogs are found to have high packing density of neurons compared to humans, enabling the dogs to effectively recognize VOC biomarkers.[22]

Cancer

edit

The first study on trained dogs to detect cancer was published by the research team of Willis in the early 2000s where the dogs could detect bladder cancer from the urine samples.[22] It was confirmed by Pickel and researchers that dogs had ability to successfully diagnose melanoma.[22] The research team of Horvath confirmed dogs were successful in differentiating between cancerous and normal tissue as well as in distinguishing non-cancerous pathological tissue from cancerous tissue.[22] The dogs were also found to show over 90% specificity in detecting ovarian cancer from blood sample, colorectal cancer from respiratory air, and  prostate cancer from dog urine.[22]   

Clostridium difficile diarrhea

edit

The first study on dogs used for detection of infectious disease was conducted by Bomers and researchers, in which they detected C. difficile in saliva samples with 100% specificity and sensitivity.[22] The dogs were trained with food rewards to detect individuals with C. difficile diarrhea.[22] The advantage of usage of dogs for detection of C. difficile compared to the traditional culture-based diagnostic method is the fast detection speed, which takes a few minutes.[23] Whether sniffing dogs could be universally used for the diagnostics is dubious withstanding the advantage as preexisting C. difficile nucleic amplification tests could yield their results within an hour with significantly higher responsiveness than the dogs.[23] The dogs additionally had ability to detect C.difficile in the environment with responsiveness of 92.3% and 95.4% for odor detection and search ability.[23] During the canine scent recognition program developed at Vancouver Canada hospital, the trained dogs showed positive ability to detect C.difficile on hospital surfaces, equipment and found sufficient places where C. difficile reservoirs lay.[23]

COVID-19

edit

Since the outbreak of COVID-19 pandemic of 2020, dogs were trained to sniff VOCs related with SARS CoV-2 and overall success rates were similar or higher than Reverse transcription polymerase chain reaction (RT-PCR) and antigen testing procedures.[24] A research team of Grandjen trained the dogs to sit in front of samples from COVID-positive patients.[24] The success rate of distinguishing odor of sweat from individuals with COVID-19 from that of those without COVID-19 was between 83% and 100%.[24] They could be used to screen individuals with various stages of COVID-19 infections, ranging from asymptotic, presymptomatic, mild to severe, in schools, transportation centers like airports, hospitals, and public gatherings.[24] Because dogs are animal species that have low risk for binding between ACE2 receptor and SARS CoV-2 , they are less likely to be transmitters of COVID-19 compared to primates or cats, which have high and medium risk, respectively.[24] Regarding the future COVID-19 detection using dogs, sweat sniffing is the most ideal choice as it minimizes the chance of transmitting COVID-19 to the dogs.[24] The main advantage of using dogs for screening of COVID-19 over current RT-PCR method are less cost, intrusiveness to the subject and no delaying in reporting of the results.[24]

Rats

edit

African giant pouched rats were trained to diagnose more than 14000 tuberculosis patients by smelling sputum.[23] Compared to dogs used to detect C. difficile in saliva or E.coli in urine samples, the rats could sniff up to 100 samples in 20 minutes.[23] Their success rates of detection were comparable to smear examination by microscopy after Ziehl-Neelsen staining with responsiveness of 94%, which are common tools to diagnose tuberculosis in low-income countries.[23] The responsiveness was lower in comparison to nucleic acid amplification tests (80%) or with culture (60-70%).[23] The rats were regarded as good tools to diagnose tuberculosis in despite the lower responsiveness than nucleic acid tests if the settings of the diagnostics were highly endemic countries with peripheral medical centers with no proper laboratory set-ups.[23]

Mosquitoes

edit

Mosquitoes were found to be attracted to skin odors of individuals infected by malaria parasites (Plasmodium falciparum gametocytes).[23] Attraction of uninfected mosquitoes was two to three times higher to children infected with gametocytes, and the attraction resumed to baseline between infected and healthy individuals following the antimalarial treatment.[23]  Malaria infection had consistent effects on skin VOC profiles, as well as notable distinguishable effects of asymptomatic and symptomatic infections.[23]

  1. ^ a b c d Buljubasic, Fanis; Buchbauer, Gerhard (2014-10-10). "The scent of human diseases: a review on specific volatile organic compounds as diagnostic biomarkers". Flavour and Fragrance Journal. 30 (1): 5–25. doi:10.1002/ffj.3219. ISSN 0882-5734.
  2. ^ Gouzerh, Flora; Bessière, Jean-Marie; Ujvari, Beata; Thomas, Frédéric; Dujon, Antoine M.; Dormont, Laurent (2022-01-01). "Odors and cancer: Current status and future directions". Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 1877 (1): 188644. doi:10.1016/j.bbcan.2021.188644. ISSN 0304-419X.
  3. ^ Rondanelli, Mariangela; Perdoni, Federica; Infantino, Vittoria; Faliva, Milena Anna; Peroni, Gabriella; Iannello, Giancarlo; Nichetti, Mara; Alalwan, Tariq A.; Perna, Simone; Cocuzza, Clementina (2019-09-10). "Volatile Organic Compounds as Biomarkers of Gastrointestinal Diseases and Nutritional Status". Journal of Analytical Methods in Chemistry. 2019: e7247802. doi:10.1155/2019/7247802. ISSN 2090-8865. PMC 6754926. PMID 31583160.{{cite journal}}: CS1 maint: PMC format (link) CS1 maint: unflagged free DOI (link)
  4. ^ a b c d e f g h Gouzerh, Flora; Bessière, Jean-Marie; Ujvari, Beata; Thomas, Frédéric; Dujon, Antoine M.; Dormont, Laurent (2022-01-01). "Odors and cancer: Current status and future directions". Biochimica et Biophysica Acta (BBA) - Reviews on Cancer. 1877 (1): 188644. doi:10.1016/j.bbcan.2021.188644. ISSN 0304-419X.
  5. ^ a b Bano, Shaista; Zulkifle, Mohd; Khan, Tariq Nadeem (2018-07). "Urinalysis: A Diagnostic Tool in Unani System of Medicine". International Journal of Health Sciences and Research. 8. ISSN 2249-9571. {{cite journal}}: Check date values in: |date= (help); Unknown parameter |First name 4= ignored (help); Unknown parameter |Last name 4= ignored (help)
  6. ^ Bos, Gerrit (2000). Ibn Al-Jazzar On Fevers. Routledge. ISBN 978-0-7103-0570-1. OCLC 1247641946.
  7. ^ a b c Buljubasic, Fanis; Buchbauer, Gerhard (2014-10-10). "The scent of human diseases: a review on specific volatile organic compounds as diagnostic biomarkers". Flavour and Fragrance Journal. 30 (1): 5–25. doi:10.1002/ffj.3219. ISSN 0882-5734.
  8. ^ a b Janssens, Eline; van Meerbeeck, Jan P; Lamote, Kevin (2020-09-01). "Volatile organic compounds in human matrices as lung cancer biomarkers: a systematic review". Critical Reviews in Oncology/Hematology. 153: 103037. doi:10.1016/j.critrevonc.2020.103037. ISSN 1040-8428.
  9. ^ Lukman Hekiem, Nurul Liyana; Md Ralib, Aliza Aini; Mat Hattar, Maziati Akmal bt; B. Ahmad, Farah; Nordin, Anis Nurashikin; Rahim, Rosminazuin Ab; Za’bah, Nor Farahidah (2021-10-01). "Advanced vapour sensing materials: Existing and latent to acoustic wave sensors for VOCs detection as the potential exhaled breath biomarkers for lung cancer". Sensors and Actuators A: Physical. 329: 112792. doi:10.1016/j.sna.2021.112792. ISSN 0924-4247.
  10. ^ Rondanelli, Mariangela; Perdoni, Federica; Infantino, Vittoria; Faliva, Milena Anna; Peroni, Gabriella; Iannello, Giancarlo; Nichetti, Mara; Alalwan, Tariq A.; Perna, Simone; Cocuzza, Clementina (2019-09-10). "Volatile Organic Compounds as Biomarkers of Gastrointestinal Diseases and Nutritional Status". Journal of Analytical Methods in Chemistry. 2019: e7247802. doi:10.1155/2019/7247802. ISSN 2090-8865. PMC 6754926. PMID 31583160.{{cite journal}}: CS1 maint: PMC format (link) CS1 maint: unflagged free DOI (link)
  11. ^ a b Dragonieri, Silvano; Pennazza, Giorgio; Carratu, Pierluigi; Resta, Onofrio (2017-04). "Electronic Nose Technology in Respiratory Diseases". Lung. 195 (2): 157–165. doi:10.1007/s00408-017-9987-3. ISSN 0341-2040. {{cite journal}}: Check date values in: |date= (help)
  12. ^ a b Dospinescu, Valentin-Mihai; Tiele, Akira; Covington, James A. (2020-08). "Sniffing Out Urinary Tract Infection—Diagnosis Based on Volatile Organic Compounds and Smell Profile". Biosensors. 10 (8): 83. doi:10.3390/bios10080083. ISSN 2079-6374. PMC 7460005. PMID 32717983. {{cite journal}}: Check date values in: |date= (help)CS1 maint: PMC format (link) CS1 maint: unflagged free DOI (link)
  13. ^ a b Behera, Bhagaban; Joshi, Rathin; Anil Vishnu, G K; Bhalerao, Sanjay; Pandya, Hardik J (2019-03-06). "Electronic nose: a non-invasive technology for breath analysis of diabetes and lung cancer patients". Journal of Breath Research. 13 (2): 024001. doi:10.1088/1752-7163/aafc77. ISSN 1752-7163.
  14. ^ Dixit, Kaushiki; Fardindoost, Somayeh; Ravishankara, Adithya; Tasnim, Nishat; Hoorfar, Mina (2021-12). "Exhaled Breath Analysis for Diabetes Diagnosis and Monitoring: Relevance, Challenges and Possibilities". Biosensors. 11 (12): 476. doi:10.3390/bios11120476. ISSN 2079-6374. PMC 8699302. PMID 34940233. {{cite journal}}: Check date values in: |date= (help)CS1 maint: PMC format (link) CS1 maint: unflagged free DOI (link)
  15. ^ Oakley-Girvan, Ingrid; Davis, Sharon Watkins (2017-12-12). "Breath based volatile organic compounds in the detection of breast, lung, and colorectal cancers: A systematic review". Cancer Biomarkers. 21 (1): 29–39. doi:10.3233/CBM-170177.
  16. ^ Das, Sagnik; Pal, Mrinal (2020-01-02). "Review—Non-Invasive Monitoring of Human Health by Exhaled Breath Analysis: A Comprehensive Review". Journal of The Electrochemical Society. 167 (3): 037562. doi:10.1149/1945-7111/ab67a6. ISSN 0013-4651.
  17. ^ Dragonieri, Silvano; Pennazza, Giorgio; Carratu, Pierluigi; Resta, Onofrio (2017-04-01). "Electronic Nose Technology in Respiratory Diseases". Lung. 195 (2): 157–165. doi:10.1007/s00408-017-9987-3. ISSN 1432-1750.
  18. ^ Saasa, Valentine; Malwela, Thomas; Beukes, Mervyn; Mokgotho, Matlou; Liu, Chaun-Pu; Mwakikunga, Bonex (2018-03). "Sensing Technologies for Detection of Acetone in Human Breath for Diabetes Diagnosis and Monitoring". Diagnostics. 8 (1): 12. doi:10.3390/diagnostics8010012. ISSN 2075-4418. PMC 5871995. PMID 29385067. {{cite journal}}: Check date values in: |date= (help)CS1 maint: PMC format (link) CS1 maint: unflagged free DOI (link)
  19. ^ Dixit, Kaushiki; Fardindoost, Somayeh; Ravishankara, Adithya; Tasnim, Nishat; Hoorfar, Mina (2021-12). "Exhaled Breath Analysis for Diabetes Diagnosis and Monitoring: Relevance, Challenges and Possibilities". Biosensors. 11 (12): 476. doi:10.3390/bios11120476. ISSN 2079-6374. PMC 8699302. PMID 34940233. {{cite journal}}: Check date values in: |date= (help)CS1 maint: PMC format (link) CS1 maint: unflagged free DOI (link)
  20. ^ da Costa, Bruno Ruiz Brandão; De Martinis, Bruno Spinosa (2020-11-01). "Analysis of urinary VOCs using mass spectrometric methods to diagnose cancer: A review". Clinical Mass Spectrometry. 18: 27–37. doi:10.1016/j.clinms.2020.10.004. ISSN 2376-9998.
  21. ^ a b Inamdar, Arati A.; Morath, Shannon; Bennett, Joan W. (2020-09-08). "Fungal Volatile Organic Compounds: More Than Just a Funky Smell?". Annual Review of Microbiology. 74 (1): 101–116. doi:10.1146/annurev-micro-012420-080428. ISSN 0066-4227.
  22. ^ a b c d e f g h i j Salgirli Demi̇Rbaş, Yasemin; Sareyyüpoğlu, Barış; Öztürk, Hakan; Ki̇Smali̇, Gorkem; Alpay, Merve; Seçi̇Lmi̇Ş Canbay, Hale; Emen, Fatih; Baş, Bülent; Özkul, Aykut (2021-03-16). "The role of bio-detection dogs in prevention and diagnosis of infectious disease: A systematic review". Ankara Üniversitesi Veteriner Fakültesi Dergisi. doi:10.33988/auvfd.834133. ISSN 1300-0861.
  23. ^ a b c d e f g h i j k l Cambau, E.; Poljak, M. (2020-04-01). "Sniffing animals as a diagnostic tool in infectious diseases". Clinical Microbiology and Infection. 26 (4): 431–435. doi:10.1016/j.cmi.2019.10.036. ISSN 1198-743X. PMID 31734357.
  24. ^ a b c d e f g Dickey, Tommy; Junqueira, Heather (2021-02-01). "Toward the use of medical scent detection dogs for COVID-19 screening". Journal of Osteopathic Medicine. 121 (2): 141–148. doi:10.1515/jom-2020-0222. ISSN 2702-3648.
Retrieved from "https://en.wikipedia.org/w/index.php?title=User:Blueriver01/sandbox&oldid=1080406745"