Skip to Content

An Easier Test for TB

A study suggests that an electronic nose could sniff out tuberculosis in a urine sample.

Electronic noses, which detect chemicals in the air, have shown promise as a tool for diagnosing disease. A recent study in Analytical Chemistry offers a first step toward developing an electronic nose to detect tuberculosis (TB) infection in a urine sample, which could be especially useful in poor countries.

Many diseases affect the chemical components of patients’ breath and bodily fluids in characteristic ways, and scientists have been trying to exploit these chemical fingerprints as a disease-detection method. Electronic noses, which pair chemical sensors with a pattern-recognition system, are being developed to spot bacterial infections and lung cancer.

Treating TB in developing countries is hampered by diagnostic tests that are invasive and time-consuming and require technical skill and laboratory equipment. An inexpensive, fast, and simple test would be a boon. Several research groups have begun investigating electronic-nose technologies for TB diagnosis, primarily with samples of sputum, the mucus that lines the lower respiratory tract. However, a study led by Virander Chauhan and Ranjan Nanda from the International Centre for Genetic Engineering and Biotechnology in New Delhi, India, has taken a new approach by studying urine, which can be collected without stressing a patient, is not infectious, and can be stored more easily and for longer periods of time.

The researchers collected urine samples from more than 100 newly diagnosed TB patients in New Delhi. They analyzed molecules from the urine that evaporate quickly in the air, called volatile organic compounds (VOCs), using gas chromatography and mass spectrometry, which give a detailed readout of chemical components and their concentrations. Using this method to hunt for patterns, they identified several VOCs that occurred in significantly different concentrations in infected individuals. Using this signature, they were able to predict TB infection in another group of patients with nearly 99 percent accuracy.

This method could also be used to distinguish TB from other lung diseases. And, Nanda says, although the current study focused on diagnosing the disease, it may also be possible to use an electronic nose to monitor the extent of the infection as patients undergo treatment.

Hossam Haick, a chemical engineer at the Technion-Israel Institute of Technology who is researching sensors for biomarkers, says that these initial results show promise, but more studies on larger numbers of patients will be needed to validate the results. He adds that although the research demonstrates the feasibility of a urine test for TB, a simple, quick test is still a ways off, because the method used to identify the VOC signatures is expensive and time-consuming. The next step is to develop a small, inexpensive, and easy-to-use device that can detect the TB-specific VOCs accurately. Nanda says that this “is going to be a hugely complex job” and that his team is currently investigating appropriate sensor technologies.

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

OpenAI teases an amazing new generative video model called Sora

The firm is sharing Sora with a small group of safety testers but the rest of us will have to wait to learn more.

Google’s Gemini is now in everything. Here’s how you can try it out.

Gmail, Docs, and more will now come with Gemini baked in. But Europeans will have to wait before they can download the app.

This baby with a head camera helped teach an AI how kids learn language

A neural network trained on the experiences of a single young child managed to learn one of the core components of language: how to match words to the objects they represent.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.