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Quantitative variability of 342 plasma proteins in a human twin population.

Liu Y, Buil A, Collins BC, Gillet LC, Blum LC, Cheng LY, Vitek O, Mouritsen J, Lachance G, Spector TD, Dermitzakis ET, Aebersold R - Mol. Syst. Biol. (2015)

Bottom Line: Because the twin study design provides a natural opportunity to estimate the relative contribution of heritability and environment to different traits in human population, we applied here the highly accurate and reproducible SWATH mass spectrometry technique to quantify 1,904 peptides defining 342 unique plasma proteins in 232 plasma samples collected longitudinally from pairs of monozygotic and dizygotic twins at intervals of 2-7 years, and proportioned the observed total quantitative variability to its root causes, genes, and environmental and longitudinal factors.The data further strongly suggest that the plasma concentrations of clinical biomarkers need to be calibrated against genetic and temporal factors.These results therefore have immediate implications for the effective design of blood-based biomarker studies.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland liu@imsb.biol.ethz.ch aebersold@imsb.biol.ethz.ch.

No MeSH data available.


Experimental designThe plasma proteomic survey of a longitudinal twin cohort was performed with SWATH-MS, an emerging mass spectrometry technique providing high quantitative accuracy and reproducibility. The observed overall variance of protein abundance was partitioned into four biological contributing factors (heritable, common environmental, individual environmental and longitudinally contributing factors) and unexplained effects using a linear mixed model.
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fig01: Experimental designThe plasma proteomic survey of a longitudinal twin cohort was performed with SWATH-MS, an emerging mass spectrometry technique providing high quantitative accuracy and reproducibility. The observed overall variance of protein abundance was partitioned into four biological contributing factors (heritable, common environmental, individual environmental and longitudinally contributing factors) and unexplained effects using a linear mixed model.

Mentions: To quantify the levels of human plasma proteins, we applied the newly developed SWATH-MS technique (Gillet et al, 2012) in a longitudinal twin cohort. The cohort consisted of 44 DZ and 72 MZ twins from the Twins UK Adult Twin Registry where blood samples were drawn at two different time points (Fig1). Twins were selected at an average age of 57.8 years at the first visit, ranging from 38 to 74 years of age. The time interval between the two samplings was 5.2 ± 1.4 years. The twins had an average age of 63.1 at the time of second visit, ranging from 44 to 78 years of age (see Supplementary Fig S1 for the distribution of actual age in the cohort at the two visits). Fasted plasma samples were collected at identical conditions (see Materials and Methods and Supplementary Table S1). Females were chosen to simplify the experimental design by excluding the gender variance.


Quantitative variability of 342 plasma proteins in a human twin population.

Liu Y, Buil A, Collins BC, Gillet LC, Blum LC, Cheng LY, Vitek O, Mouritsen J, Lachance G, Spector TD, Dermitzakis ET, Aebersold R - Mol. Syst. Biol. (2015)

Experimental designThe plasma proteomic survey of a longitudinal twin cohort was performed with SWATH-MS, an emerging mass spectrometry technique providing high quantitative accuracy and reproducibility. The observed overall variance of protein abundance was partitioned into four biological contributing factors (heritable, common environmental, individual environmental and longitudinally contributing factors) and unexplained effects using a linear mixed model.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4358658&req=5

fig01: Experimental designThe plasma proteomic survey of a longitudinal twin cohort was performed with SWATH-MS, an emerging mass spectrometry technique providing high quantitative accuracy and reproducibility. The observed overall variance of protein abundance was partitioned into four biological contributing factors (heritable, common environmental, individual environmental and longitudinally contributing factors) and unexplained effects using a linear mixed model.
Mentions: To quantify the levels of human plasma proteins, we applied the newly developed SWATH-MS technique (Gillet et al, 2012) in a longitudinal twin cohort. The cohort consisted of 44 DZ and 72 MZ twins from the Twins UK Adult Twin Registry where blood samples were drawn at two different time points (Fig1). Twins were selected at an average age of 57.8 years at the first visit, ranging from 38 to 74 years of age. The time interval between the two samplings was 5.2 ± 1.4 years. The twins had an average age of 63.1 at the time of second visit, ranging from 44 to 78 years of age (see Supplementary Fig S1 for the distribution of actual age in the cohort at the two visits). Fasted plasma samples were collected at identical conditions (see Materials and Methods and Supplementary Table S1). Females were chosen to simplify the experimental design by excluding the gender variance.

Bottom Line: Because the twin study design provides a natural opportunity to estimate the relative contribution of heritability and environment to different traits in human population, we applied here the highly accurate and reproducible SWATH mass spectrometry technique to quantify 1,904 peptides defining 342 unique plasma proteins in 232 plasma samples collected longitudinally from pairs of monozygotic and dizygotic twins at intervals of 2-7 years, and proportioned the observed total quantitative variability to its root causes, genes, and environmental and longitudinal factors.The data further strongly suggest that the plasma concentrations of clinical biomarkers need to be calibrated against genetic and temporal factors.These results therefore have immediate implications for the effective design of blood-based biomarker studies.

View Article: PubMed Central - PubMed

Affiliation: Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Zurich, Switzerland liu@imsb.biol.ethz.ch aebersold@imsb.biol.ethz.ch.

No MeSH data available.