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Detecting diseases through body odor? New laser technology shows potential for non-invasive diagnostics (opens in a new tab)

medicalxpress.com · 2026-09-29

Short answerEvidenceSource

Short answer

Mostly supported

Mostly supported.

The claims we could check match the study, but some claims were not covered by the evidence reviewed.

  • 3 supported
  • 1 not covered

Checked against the study summary. The full text wasn't available, so some details couldn't be settled either way.

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1
2

NewsLink checks it

Mostly supported

Every claim we could check holds up. Three of four claims match the study. This overall rating is based only on the claims we could check. One claim the study doesn't address.

  • 3 supported
  • 1 not covered
Open claim evidence
3
Then inspect each claim

Evidence layer

Claim by claim

Each claim gets a verdict. Expand it to see the evidence directly below.

4 claims in this story

Showing all 4 claimsChoose a verdict to focus the list.

Claim 1 of 4Not coveredThe article says the proof-of-concept study was conducted under controlled laboratory conditions with 24 randomly selected participants from a larger study, including six healthy controls and six people each with Parkinson's disease, COVID-19, and other conditions, and that follow-up samples from three Parkinson's disease participants after two weeks suggested stability over time.View evidenceHide evidence

As stated24 participants; 6 healthy controls; 6 Parkinson's disease; 6 COVID-19; 6 other conditions; 3 follow-up participants

Why this verdict

The abstract-level profile supports a 24-participant cohort with healthy, Parkinson's disease, COVID-19, and mild cognitive impairment groups, but it does not verify several specifics in the story: random selection from a larger study, exact six-person group sizes, controlled laboratory conditions, or two-week follow-up samples from three Parkinson's participants showing stability over time. These details may require full-text evidence.

1

Study evidence

Projection of LPAS-measured swab spectra (after Savitzky–Golay filtering) onto the first two principal components revealed group-level structure corresponding to healthy (H), Parkinson’s disease (PD), COVID-19 (C), and mild cognitive impairment (MC).

“Cotton swabs were used to swab the nose, navel, and ear of 24 patients, after which the odor of the cotton swabs was analyzed using Laser-based photoacoustic spectroscopy (LPAS).”
Claim 2 of 4SupportedResearchers at the Fraunhofer Institute for Integrated Circuits IIS and the Technical University of Dresden tested a new approach for investigating disease-related changes in body odor using laser-based photoacoustic spectroscopy on simple body swabs.View evidenceHide evidence

Why this verdict

The abstract-level profile supports the scientific content: a human observational proof-of-concept used cotton swabs from body sites and analyzed swab odor/VOC signatures with mid-infrared laser-based photoacoustic spectroscopy. The supplied paper profile does not independently verify the named institutional affiliations, but the described method and aim are supported.

1

Study evidence

Projection of LPAS-measured swab spectra (after Savitzky–Golay filtering) onto the first two principal components revealed group-level structure corresponding to healthy (H), Parkinson’s disease (PD), COVID-19 (C), and mild cognitive impairment (MC).

“Cotton swabs were used to swab the nose, navel, and ear of 24 patients, after which the odor of the cotton swabs was analyzed using Laser-based photoacoustic spectroscopy (LPAS).”
Claim 3 of 4SupportedAn initial study found differences between samples from healthy individuals and samples from people with Parkinson's disease, COVID-19, and other diseases.View evidenceHide evidence

Why this verdict

The profile reports group-level PCA structure/separation corresponding to healthy participants, Parkinson's disease, COVID-19, and mild cognitive impairment. The story frames this as initial, hedged differences rather than validated diagnosis, which matches the abstract-level evidence.

1

Study evidence

Projection of LPAS-measured swab spectra (after Savitzky–Golay filtering) onto the first two principal components revealed group-level structure corresponding to healthy (H), Parkinson’s disease (PD), COVID-19 (C), and mild cognitive impairment (MC).

“Cotton swabs were used to swab the nose, navel, and ear of 24 patients, after which the odor of the cotton swabs was analyzed using Laser-based photoacoustic spectroscopy (LPAS).”
Claim 4 of 4SupportedThe results are not a substitute for a medical diagnosis; the article says larger real-world studies are needed before clinical use, though the technology could eventually help with early indications of disease and decisions about further testing.View evidenceHide evidence

Why this verdict

The profile presents the work as proof-of-concept screening/separation rather than a validated diagnostic test, notes small-cohort limitations and the need for larger cohorts, and lacks diagnostic performance metrics or validation. The story's hedged framing that the technology could eventually support early indications and decisions about further testing is consistent with the abstract-level discussion.

1

Study evidence

Projection of LPAS-measured swab spectra (after Savitzky–Golay filtering) onto the first two principal components revealed group-level structure corresponding to healthy (H), Parkinson’s disease (PD), COVID-19 (C), and mild cognitive impairment (MC).

“Cotton swabs were used to swab the nose, navel, and ear of 24 patients, after which the odor of the cotton swabs was analyzed using Laser-based photoacoustic spectroscopy (LPAS).”
2

Study evidence

Exploratory correlation check found no consistent associations between demographic/lifestyle variables and the LPAS-derived principal components, except for age.

“Investigations into possible correlations with demographic factors and lifestyle habits showed no consistent association with the principal components, with the exception of age”
Then look for missing context

Context layer

What the story left out

Important study details the story did not include.

  • Potential confounding was explored: demographic/lifestyle variables showed no consistent association with PCs except age, and larger cohorts are needed to confirm independence from confounding.

    The story mentions the need for larger studies generally, but it does not report the age association or the limited confounding analysis, which is material because disease groups such as Parkinson's disease and mild cognitive impairment can differ by age.

    From Exploratory correlation/association assessment between PCA scores and covariates

  • Secondary feasibility finding: as few as five wavelengths may be sufficient to separate the samples, but the abstract lacks details on wavelength selection and validation.

    The story does not mention the reduced-wavelength result or its validation caveats.

    From feature-reduction/minimal-wavelength analysis (abstract-level)

4 things the story did carry across
  • Core finding: swab-derived odor/VOC spectra measured by LPAS showed group-level structure corresponding to healthy, Parkinson's disease, COVID-19, and mild cognitive impairment participants.
  • Study design and scale: small observational human cohort with n=24, limiting power, stability, and generalizability.
  • The abstract-level evidence reports PCA/group-level separation, not a validated diagnostic classifier with sensitivity, specificity, accuracy, cross-validation, or external validation.
  • Sampling details: cotton swabs were taken from nose, navel, and ear, and odors were analyzed using LPAS/QCL mid-infrared spectroscopy.
Then read the study layer

Study layer

Study at a glance

Scan the study first. Expand only the parts you want to inspect.

Pieces of work

3

Evidence read

study summary

Lead result

human in vivo

1Lead resulthuman in vivoUse odor/VOC signatures collected from body swabs (nose, navel, ear) and measured by mid-infrared LPAS to distinguish between health and multiple diseases (PD, COVID-19, mild cognitive impairment) via multivariate analysis (PCA).Observational human cohort; ex vivo analysis of swab odors using LPASExpand

In plain English

In a human observational cohort (n=24) cotton swabs taken from nose, navel, and ear were analyzed by mid-infrared laser photoacoustic spectroscopy (LPAS) using three QCL modules spanning 5.6–12.9 μm. Spectra were preprocessed (Savitzky–Golay) and subjected to principal component analysis (PCA). Projection onto the first two principal components revealed group-level structure aligning with healthy (H), Parkinson’s disease (PD), COVID-19 (C), and mild cognitive impairment (MC) participants. The authors report that as few as five wavelengths can be sufficient to separate the samples. No consistent associations were found between principal components and demographic or lifestyle factors aside from age.

Key findings

  • Projection of LPAS-measured swab spectra (after Savitzky–Golay filtering) onto the first two principal components revealed group-level structure corresponding to healthy (H), Parkinson’s disease (PD), COVID-19 (C), and mild cognitive impairment (MC).
  • Authors report that as few as five wavelengths are sufficient to separate the samples in their analyses.
“Cotton swabs were used to swab the nose, navel, and ear of 24 patients, after which the odor of the cotton swabs was analyzed using Laser-based photoacoustic spectroscopy (LPAS).”
What this piece can’t prove
  • Small cohort (n=24) with multiple groups limits statistical power and generalizability.
  • Potential confounding (notably age) cannot be definitively excluded on the basis of the reported cohort size and analyses.

3 further details could not be confirmed from the summary.

2human in vivoAssess whether demographic/lifestyle factors correlate with the main spectral principal components (i.e., explore potential confounding), noting age as an exception.Exploratory correlation/association assessment between PCA scores and covariatesExpand

In plain English

In an exploratory analysis of the same n=24 cohort used for LPAS PCA, investigators evaluated correlations between the first principal components of the spectra and demographic/lifestyle variables. They report no consistent associations for the tested covariates except for age, and note that larger cohorts are needed to confirm independence from confounding.

Key findings

  • Exploratory correlation check found no consistent associations between demographic/lifestyle variables and the LPAS-derived principal components, except for age.
“Investigations into possible correlations with demographic factors and lifestyle habits showed no consistent association with the principal components, with the exception of age”
What this piece can’t prove
  • Very small cohort (n=24) for exploratory covariate association analyses.
  • Potential residual confounding cannot be excluded; age association could reflect disease-related age differences.
  • Analysis described as exploratory; results require replication in larger, more detailed studies.

1 further detail could not be confirmed from the summary.

3human in vivoShow that a reduced set of discrete wavelengths (as few as five) may be sufficient to separate the disease/health groups, supporting feasibility of simplified sensing.feature-reduction/minimal-wavelength analysis (abstract-level)Expand

In plain English

Using LPAS spectra collected from cotton swabs of nose, navel, and ear in 24 participants, the authors state that a reduced set of discrete wavelengths — reportedly as few as five — can be sufficient to separate samples by group (healthy, Parkinson’s disease, COVID-19, mild cognitive impairment). This claim is presented alongside their PCA-based analysis of full spectra; details of how the five-wavelength subset was selected or validated are not provided in the abstract.

Key findings

  • The authors state that a reduced set of discrete mid-infrared wavelengths — reportedly as few as five — is sufficient to separate samples from healthy and disease groups in their LPAS dataset.
“Moreover, it could be shown that as little as five wavelengths are sufficient to separate the samples.”
What this piece can’t prove
  • Small sample size (24 participants) and multiple disease groups increase risk that the reported sufficiency may not generalize.
  • Unclear whether the five-wavelength result was derived from the same data used to evaluate separation (risk of circular analysis) — abstraction provides no information on held-out testing or cross-validation.

2 further details could not be confirmed from the summary.

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Method layer

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Open the paper in Tessa

Detection of disease-associated VOC signatures with laser-based photoacoustic spectroscopy (LPAS)

Scientific Reports · 2026

Source record (opens in a new tab)

Why this one

Near certain

NewsLink found the paper. Tessa is where you inspect it deeply.

Papers considered

The selected paper, plus nearby candidates.

Crossref, PubMed, Europe PMC · 16 candidate papers

Selected

Detection of disease-associated VOC signatures with laser-based photoacoustic spectroscopy (LPAS)

Scientific Reports · 2026 · Crossref

Source (opens in a new tab)

And 10 more candidates considered.