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How keeping teeth clean can ward off the misery of arthritis

It underlines the importance of regular brushing - and has implications for cancer, heart and lung disease.

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(Photo by Rudi Fargo via Unsplash)

By Mark Waghorn via SWNS

Keeping your teeth clean can ward off the misery of arthritis, according to new research.

Gum disease can leak bugs into the blood stream - triggering chronic joint pain, say scientists.

The findings were based on blood samples collected from rheumatoid arthritis patients.

It underlines the importance of regular brushing - and has implications for cancer, heart and lung disease.

Lead author Dr. Vicky Yao, of Rice University, said: "Data gathered in experiments from living organisms or cells or tissue grown in petri dishes is really important to confirm hypotheses, but, at the same time, this data perhaps holds more information than we are immediately able to derive from it."

The study, published in the journal Science Translational Medicine, found germs associated with gum disease changed consistently prior to flare ups.

It opens the door to developing better therapies.

(Photo via SWNS)

Yao explained: "I was curious about this tool that allowed you to detect microbes in human samples.

"It was sort of like, for free, you’re getting an extra perspective on the data. At the time, I hadn’t worked much on microbial data at all. Since then, Dana leveraged all this expertise and got together with people studying these bacteria.

"One of the things that came up when we were discussing this was, how cool would it be if you could prescribe some kind of mouthwash to help prevent rheumatoid arthritis flares."

The breakthrough came about serendipitously.

Yao said: "Data gathered in experiments from living organisms or cells or tissue grown in petri dishes is really important to confirm hypotheses, but, at the same time, this data perhaps holds more information than we are immediately able to derive from it."

She took a deeper look into data collected from rheumatoid arthritis patients by colleagues she was working with on a different project that tracked changes in gene expression during arthritis attacks.

Yao said: "The idea was that perhaps looking at this data retroactively, some pattern would become visible giving clues as to what might cause the arthritis to flare up.

"While I was working on that project, I went to this talk that I thought was really cool because it pointed out that in the data that gets ignored or thrown out, you can actually find traces of microbes.

"You are looking at a human sample but you get a snapshot of the microbes floating around. I was intrigued by this."

The discovery of meaningful information in data that would usually be ignored or discarded inspired her to take a similar approach in looking at data from cancer patients.

She said: "I got really interested in what else we can find mining for microbial signatures in human samples.

"Now, we are doing something similar in looking at cancer. The hope here is that if we find some interesting microbial or viral signatures that are associated with cancer, we can then identify productive experimental directions to pursue.

"For instance, if having a tumor creates this hotbed of specific microbes that we recognize, then we can maybe use that knowledge as a means to diagnose the cancer sooner or in a less invasive or costly way.

"Or, if you have microbes that have a very strong association with survival rates, that can help with prognosis. And if experiments confirm a causal link between a specific virus or bacteria and a type of cancer, then, of course, that could be useful for therapeutics."

One of the better known examples of a pathogen associated with cancer is the human papillomavirus (HPV).

Yao added: "When we did the same exercise looking at cervical cancer tumor samples, we consistently detected the virus.

"I am really interested in using computational approaches to bridge the gap between available experimental data and ways to interpret it.

"Computational analysis is a way to help interpret data and prioritize hypotheses for clinicians or experimental scientists to test."

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