Tiny genetic signals in gum fluid may help future testing

Summarised from:

MicroRNA-146a and microRNA-155 as novel crevicular fluid biomarkers for periodontitis in non-diabetic and type 2 diabetic patients
(Journal of Clinical Periodontology; doi: 10.1111/jcpe.12888)

Authors:

Nikola Radović, Nataša Nikolić Jakoba, Nina Petrović, Aleksandra Milosavljević, Božidar Brković, Jelena Roganović

Summarised by:

Dr Varkha Rattu

Research Topic:

Why does this matter?

MicroRNAs are small molecules that help regulate how cells use genetic information. Researchers studied whether two of them in gum fluid could help identify periodontitis in people with and without diabetes.

What was studied?

Ninety-six adults were divided into four groups according to diabetes and gum disease status. Researchers examined the gums and measured the markers. People with periodontitis then received treatment and were reassessed after six weeks.

What did the researchers find?

The markers were higher with periodontitis and decreased after treatment. They also related to gum pocket depth. Within this selected sample, they separated disease groups very accurately. However, the same participants were used to develop and assess the test thresholds, which can make accuracy look better than it would be in new patients.

What does this mean for me?

The findings are useful for developing possible future tests, but they do not establish a routine diagnostic tool. Smokers and people with higher HbA1c levels were excluded, so the sample did not cover everyone likely to need care. Short-term marker changes also do not prove reliable long-term monitoring. For now, the research supports further validation alongside clinical examinations rather than replacing those examinations with a laboratory result.

What should I keep in mind?

An experimental test can look promising in a carefully selected research sample but perform less well in everyday practice. It needs checking in independent groups, including people with other conditions that could affect the result. Researchers must also establish how often it misses disease or incorrectly suggests disease is present. Even good statistical performance does not automatically mean that using the test improves health. Until those questions are answered, these findings should be understood as test-development research rather than a replacement for established clinical assessment.

Read the full article Back to Research

Research  |  15.05.18

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