Gene Signature Predicts Alzheimer's Disease
By LabMedica International staff writers Posted on 20 Sep 2015 |
Novel genomic diagnostics that predict future health risks will help guide targeted preventative measures and enable the evaluation of individualized treatment strategies for many prevalent diseases of older age.
A transcriptomics approach has been developed to build the first reproducible multi-tissue ribonucleic acid (RNA) expression signature by gene-chip profiling tissue from sedentary normal subjects who reached 65 years of age in good health.
Scientists at King's College London, UK) and a team of international collaborators identified 150 RNA markers of muscle aging using samples and gene-chip profiles from 15 young subjects, aged 19 to 28 years and 15 older subjects, aged 59 to 77 years, free from metabolic and signs of cardiovascular disease and validated this observation in more than 500 independent samples.
Total RNA was extracted from frozen vastas lateralis muscle biopsy samples. A total of 113 samples provided sufficient RNA and 50 ng total RNA was amplified using an expression kit to produce complementary DNA (cDNA). The cDNA was fragmented and labeled with GeneChip WT Terminal labeling kit (Affymetrix, Inc.; Santa Clara, CA, USA). Hybridization, washing, staining, and scanning of the arrays were then performed. RNA was obtained from whole venous blood and it was collected from the subjects who had fasted 2 hours prior to collection into a PAXgene Blood RNA tube (QIAGEN Inc.; Valencia, CA, USA).
The signature was found to be a reliable predictor for risk of age-related disease when studying RNA from tissues including human muscle, brain and skin. With this RNA signature, the investigators developed a “healthy age gene score,” which they used to test and compare the RNA profiles of different individuals, and demonstrated that a greater score was associated with better health in men and women.
The scientists studied RNA from healthy 70 year old subjects and analyzed follow-up health data over two decades. Despite all subjects being born within a year of each other, their RNA at around 70 years of age demonstrated a very wide distribution in “healthy age gene score,” varying over a four-fold range. This variation was shown to link to long term health. A greater gene score was also associated with better cognitive health and renal function across a 12 year span, both important determinants of mortality. In particular, they demonstrated that patients diagnosed with Alzheimer's Disease had an altered “healthy aging” RNA signature in their blood, and therefore a lower healthy age gene score, suggesting significant association with the disease.
James A. Timmons, PhD, a professor and the lead author of the study said, “This is the first blood test of its kind that has shown that the same set of molecules are regulated in both the blood and the brain regions associated with dementia, and it can help contribute to a dementia diagnosis. This also provides strong evidence that dementia in humans could be called a type of ‘accelerated aging’ or ‘failure to activate the healthy aging program.’” The study was published on September 7, 2015, in the journal Genome Biology.
Related Links:
King's College London
Affymetrix, Inc.
QIAGEN Inc.
A transcriptomics approach has been developed to build the first reproducible multi-tissue ribonucleic acid (RNA) expression signature by gene-chip profiling tissue from sedentary normal subjects who reached 65 years of age in good health.
Scientists at King's College London, UK) and a team of international collaborators identified 150 RNA markers of muscle aging using samples and gene-chip profiles from 15 young subjects, aged 19 to 28 years and 15 older subjects, aged 59 to 77 years, free from metabolic and signs of cardiovascular disease and validated this observation in more than 500 independent samples.
Total RNA was extracted from frozen vastas lateralis muscle biopsy samples. A total of 113 samples provided sufficient RNA and 50 ng total RNA was amplified using an expression kit to produce complementary DNA (cDNA). The cDNA was fragmented and labeled with GeneChip WT Terminal labeling kit (Affymetrix, Inc.; Santa Clara, CA, USA). Hybridization, washing, staining, and scanning of the arrays were then performed. RNA was obtained from whole venous blood and it was collected from the subjects who had fasted 2 hours prior to collection into a PAXgene Blood RNA tube (QIAGEN Inc.; Valencia, CA, USA).
The signature was found to be a reliable predictor for risk of age-related disease when studying RNA from tissues including human muscle, brain and skin. With this RNA signature, the investigators developed a “healthy age gene score,” which they used to test and compare the RNA profiles of different individuals, and demonstrated that a greater score was associated with better health in men and women.
The scientists studied RNA from healthy 70 year old subjects and analyzed follow-up health data over two decades. Despite all subjects being born within a year of each other, their RNA at around 70 years of age demonstrated a very wide distribution in “healthy age gene score,” varying over a four-fold range. This variation was shown to link to long term health. A greater gene score was also associated with better cognitive health and renal function across a 12 year span, both important determinants of mortality. In particular, they demonstrated that patients diagnosed with Alzheimer's Disease had an altered “healthy aging” RNA signature in their blood, and therefore a lower healthy age gene score, suggesting significant association with the disease.
James A. Timmons, PhD, a professor and the lead author of the study said, “This is the first blood test of its kind that has shown that the same set of molecules are regulated in both the blood and the brain regions associated with dementia, and it can help contribute to a dementia diagnosis. This also provides strong evidence that dementia in humans could be called a type of ‘accelerated aging’ or ‘failure to activate the healthy aging program.’” The study was published on September 7, 2015, in the journal Genome Biology.
Related Links:
King's College London
Affymetrix, Inc.
QIAGEN Inc.
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