Genetic regulation of metabolomic biomarkers - paths to cardiovascular diseases and type 2 diabetes

Public release date: 29-Jan-2012
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Contact: Dr. Samuli Ripatti
samuli.ripatti@fimm.fi
358-206-108-159
University of Helsinki

In a study to the genetic variance of human metabolism, researchers have identified thirty one regions of the genome that were associated with levels of circulating metabolites, i.e., small molecules that take part in various chemical reactions of human body. Many of the studied metabolites are biomarkers for cardiovascular disease or related disorders, thus the loci uncovered may provide valuable insight into the biological processes leading to common diseases.

Laboratory tests used in the clinic typically monitor one or few circulating metabolites. The researchers at the Institute for Molecular Medicine Finland (FIMM) used a high throughput method called nuclear magnetic resonance (NMR) that can measure more than hundred different metabolites in one assay. This provides a much more in-depth picture of circulating metabolic compounds.

"Using this extensive analysis in thousands of people, we could identify a large number of genetic loci regulating the level of compounds circulating in the blood stream", says Dr. Samuli Ripatti, the leader of the study.

The team assayed 117 detailed metabolic markers, including lipoprotein subclasses, amino acids and lipids, and conducted the largest genome-wide association analysis of this type, in terms of study sample size of 8330 individuals from six Finnish population-based cohorts and 7.7 million genomic markers studied. They revealed, in total, 31 genetic regions associated with the blood levels of the metabolites.

Eleven of the loci had not been previously shown to be associated with any metabolic measures.

Among the findings were two new loci affecting serum cholesterol subclass measures, well-established risk markers for cardiovascular disease, and five new loci affecting levels of amino acids recently discovered to be potential biomarkers for type 2 diabetes. The discovered variants have significant effects on the metabolite levels, the effect sizes being in general considerably larger than the known common variants for complex disease have.

Also, using Finnish twin pair samples, the researchers indicated that the metabolite levels show a high degree of heritability. "This result suggests that the studied metabolites are describing better the underlying biology than the routinely used laboratory tests. Therefore, the study provides further support for the use of detailed data on multitude of metabolites in genetic studies to provide novel biological insights and to help in elucidating the processes leading to common diseases", Dr. Ripatti says.

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Dr. Samuli Ripatti is a FIMM-EMBL Group Leader at the Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Finland (http://www.fimm.fi) and a Honorary Faculty Member at the Wellcome Trust Sanger Institute, UK (http://www.sanger.ac.uk)

The Institute for Molecular Medicine Finland FIMM is an international research institute focusing on building a bridge from discovery to medical applications. FIMM investigates molecular mechanisms of disease using genomics and medical systems biology in order to promote human health. FIMM is a multi-disciplinary institute combining high-quality science with unique research cohorts and patient materials, and state-of-the-art technologies. Website http://www.fimm.fi

The Wellcome Trust Sanger Institute is one of the world's leading genome centres. Through its ability to conduct research at scale, it is able to engage in bold and long-term exploratory projects that are designed to influence and empower medical science globally. Institute research findings, generated through its own research programmes and through its leading role in international consortia, are being used to develop new diagnostics and treatments for human disease. Website http://www.sanger.ac.uk/

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Public release date: 29-Jan-2012
[ | E-mail | Share ]

Contact: Dr. Samuli Ripatti
samuli.ripatti@fimm.fi
358-206-108-159
University of Helsinki

In a study to the genetic variance of human metabolism, researchers have identified thirty one regions of the genome that were associated with levels of circulating metabolites, i.e., small molecules that take part in various chemical reactions of human body. Many of the studied metabolites are biomarkers for cardiovascular disease or related disorders, thus the loci uncovered may provide valuable insight into the biological processes leading to common diseases.

Laboratory tests used in the clinic typically monitor one or few circulating metabolites. The researchers at the Institute for Molecular Medicine Finland (FIMM) used a high throughput method called nuclear magnetic resonance (NMR) that can measure more than hundred different metabolites in one assay. This provides a much more in-depth picture of circulating metabolic compounds.

"Using this extensive analysis in thousands of people, we could identify a large number of genetic loci regulating the level of compounds circulating in the blood stream", says Dr. Samuli Ripatti, the leader of the study.

The team assayed 117 detailed metabolic markers, including lipoprotein subclasses, amino acids and lipids, and conducted the largest genome-wide association analysis of this type, in terms of study sample size of 8330 individuals from six Finnish population-based cohorts and 7.7 million genomic markers studied. They revealed, in total, 31 genetic regions associated with the blood levels of the metabolites.

Eleven of the loci had not been previously shown to be associated with any metabolic measures.

Among the findings were two new loci affecting serum cholesterol subclass measures, well-established risk markers for cardiovascular disease, and five new loci affecting levels of amino acids recently discovered to be potential biomarkers for type 2 diabetes. The discovered variants have significant effects on the metabolite levels, the effect sizes being in general considerably larger than the known common variants for complex disease have.

Also, using Finnish twin pair samples, the researchers indicated that the metabolite levels show a high degree of heritability. "This result suggests that the studied metabolites are describing better the underlying biology than the routinely used laboratory tests. Therefore, the study provides further support for the use of detailed data on multitude of metabolites in genetic studies to provide novel biological insights and to help in elucidating the processes leading to common diseases", Dr. Ripatti says.

###

Dr. Samuli Ripatti is a FIMM-EMBL Group Leader at the Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Finland (http://www.fimm.fi) and a Honorary Faculty Member at the Wellcome Trust Sanger Institute, UK (http://www.sanger.ac.uk)

The Institute for Molecular Medicine Finland FIMM is an international research institute focusing on building a bridge from discovery to medical applications. FIMM investigates molecular mechanisms of disease using genomics and medical systems biology in order to promote human health. FIMM is a multi-disciplinary institute combining high-quality science with unique research cohorts and patient materials, and state-of-the-art technologies. Website http://www.fimm.fi

The Wellcome Trust Sanger Institute is one of the world's leading genome centres. Through its ability to conduct research at scale, it is able to engage in bold and long-term exploratory projects that are designed to influence and empower medical science globally. Institute research findings, generated through its own research programmes and through its leading role in international consortia, are being used to develop new diagnostics and treatments for human disease. Website http://www.sanger.ac.uk/

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?

AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert! system.

Source: http://www.eurekalert.org/pub_releases/2012-01/uoh-gro012712.php

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