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    Scientists accurately predict age using just a saliva sample

    Patented test could offer new tool for crime investigations, personalised medicine.
    Dr. Eric Vilain: "Our approach supplies one answer to the enduring quest for reliable markers of aging."
    Dr. Eric Vilain: "Our approach supplies one answer to the enduring quest for reliable markers of aging."

    Self-conscious about your age? Be careful where you spit. UCLA geneticists now can use saliva to reveal how old you are.

    The findings, which appear June 22 in PLoS One, an online journal of the Public Library of Science, offer a myriad of potential applications. A newly patented test based on the research, for example, could offer crime-scene investigators a new forensic tool for pinpointing a suspect's age.

    "Our approach supplies one answer to the enduring quest for reliable markers of aging," said principal investigator Dr. Eric Vilain, a professor of human genetics, paediatrics and urology at the David Geffen School of Medicine at UCLA. "With just a saliva sample, we can accurately predict a person's age without knowing anything else about them."

    Vilain and his colleagues looked at a process called methylation, a chemical modification of one of the four building blocks that make up our DNA.

    Genes play a role in aging, but so do environmental influences

    "While genes partly shape how our body ages, environmental influences also can change our DNA as we age," Vilain said. "Methylation patterns shift as we grow older and contribute to aging-related disease."

    Using saliva samples contributed by 34 pairs of identical male twins between the ages of 21 and 55, UCLA researchers scoured the men's genomes and identified 88 sites on the DNA that strongly correlated methylation to age. They replicated their findings in a general population of 31 men and 29 women between the ages of 18 and 70.

    Next, the scientists built a predictive model using two of the three genes with the strongest age-related linkage to methylation. When they plugged in the data from the twins' and the other group's saliva samples, they were able to correctly predict a person's age within five years - an unprecedented level of accuracy.

    "Methylation's relationship with age is so strong that we can identify how old someone is by examining just two of the 3 billion building blocks that make up our genome," said first author Sven Bocklandt, a former UCLA geneticist now at Bioline.

    A tool to fight crime?

    Vilain and his team envision the test becoming a forensic tool in crime-scene investigations. By analysing traces of saliva left in a tooth bite or on a coffee cup, lab experts could narrow the age of a criminal suspect to a five-year range.

    In a minority of the population, methylation does not correlate with chronological age. Using the data they are gathering on this population, scientists may one day be able to calculate a person's "bio-age," the measurement of a person's biological age versus their chronological age.

    Physicians could evaluate the risk of age-related diseases in routine medical screenings and tailor interventions based on the patient's bio-age rather than their chronological age. Instead of requiring everyone to undergo a colonoscopy at age 50, for example, physicians would recommend preventive tests according to a person's bio-age.

    "Doctors could predict your medical risk for a particular disease and customise treatment based on your DNA's true biological age, as opposed to how old you are," Vilain said. "By eliminating costly and unnecessary tests, we could target those patients who really need them."

    The UCLA team is currently exploring whether people with a lower bio-age live longer and suffer less disease. They also are examining if the reverse is true - whether a higher bio-age is linked to a greater rate of disease and early death.

    The study was internally funded by UCLA. Vilain's co-authors included Bocklandt, Wen Lin, Mary Sehl, Francisco Sáncheza, Janet Sinsheimer and Steve Horvath, all of UCLA.

    Source: UCLA

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