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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.


Related in: MedlinePlus

Proteomic identification and reproducible quantification among the twin cohortA The establishment of a comprehensive, specific spectral library of human plasma proteome that is ready for SWATH-MS analysis. The reference spectra were generated a priori by extensive shotgun proteomic sequencing of fractionated plasma peptides and complemented with spectra of additional known plasma proteins (Farrah et al, 2011).B The coefficient of variance (CV) analysis at technical, whole-process experimental and cohort levels.C Heatmap of hierarchical clustering analysis of the protein vs. sample matrix indicates that plasma proteins were reproducibly quantified by SWATH-MS across the sample cohort.D The distribution of the fold changes of protein SWATH-MS intensities from their average abundance levels across the cohort is shown as box plots. Antithrombin III (ANT3) and vitamin D-binding protein (VTDB) are shown as examples of the most stable proteins, whereas apolipoprotein(a) (APOA) and serum amyloid A-1 protein (SAA1) are shown as examples of the most variable proteins. The red bars show the positions of the protein analytes whose measurement has been cleared or approved by FDA in human blood.
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fig02: Proteomic identification and reproducible quantification among the twin cohortA The establishment of a comprehensive, specific spectral library of human plasma proteome that is ready for SWATH-MS analysis. The reference spectra were generated a priori by extensive shotgun proteomic sequencing of fractionated plasma peptides and complemented with spectra of additional known plasma proteins (Farrah et al, 2011).B The coefficient of variance (CV) analysis at technical, whole-process experimental and cohort levels.C Heatmap of hierarchical clustering analysis of the protein vs. sample matrix indicates that plasma proteins were reproducibly quantified by SWATH-MS across the sample cohort.D The distribution of the fold changes of protein SWATH-MS intensities from their average abundance levels across the cohort is shown as box plots. Antithrombin III (ANT3) and vitamin D-binding protein (VTDB) are shown as examples of the most stable proteins, whereas apolipoprotein(a) (APOA) and serum amyloid A-1 protein (SAA1) are shown as examples of the most variable proteins. The red bars show the positions of the protein analytes whose measurement has been cleared or approved by FDA in human blood.

Mentions: The data-independent acquisition (DIA) mass spectrometric quantification method of SWATH-MS essentially converts all the peptides ionized from a biological sample into a high-resolution, digital map of fragment ion signals (Gillet et al, 2012; Liu et al, 2013a) (Fig1). In these maps, specific proteins were monitored via a targeted data analysis strategy, where fragment ion signal groups uniquely identifying a targeted peptide were detected and quantified in each of the 232 SWATH-MS maps. The parameters of the signal group for each peptide, including the fragment ion masses, their relative intensity and chromatographic concordance, the peptide retention time and precursor mass range, constituted a specific assay for each targeted peptide that was prepared a priori from a spectral library of the human plasma proteome (Fig2A). Specifically, to generate this spectral library, we deployed comprehensive shotgun proteomic sequencing of the plasma digest of a mixed plasma sample, which was firstly depleted of the 14 most abundant proteins and then fractionated by strong anion exchanger at the peptide level, yielding specific assays for 652 proteins. Further, we included in the library additional MS assays for plasma proteins (Farrah et al, 2011) from an in-house SWATH assay compendium for the human proteome (Rosenberger et al, 2014). The final combined library contained more than 43,000 peptides, representing 1,667 unique plasma proteins, which represents, as of to date, the largest SWATH-ready spectral library for the human plasma proteome (freely provided with raw data), and therefore maximized the number of identified proteins from the SWATH maps.


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)

Proteomic identification and reproducible quantification among the twin cohortA The establishment of a comprehensive, specific spectral library of human plasma proteome that is ready for SWATH-MS analysis. The reference spectra were generated a priori by extensive shotgun proteomic sequencing of fractionated plasma peptides and complemented with spectra of additional known plasma proteins (Farrah et al, 2011).B The coefficient of variance (CV) analysis at technical, whole-process experimental and cohort levels.C Heatmap of hierarchical clustering analysis of the protein vs. sample matrix indicates that plasma proteins were reproducibly quantified by SWATH-MS across the sample cohort.D The distribution of the fold changes of protein SWATH-MS intensities from their average abundance levels across the cohort is shown as box plots. Antithrombin III (ANT3) and vitamin D-binding protein (VTDB) are shown as examples of the most stable proteins, whereas apolipoprotein(a) (APOA) and serum amyloid A-1 protein (SAA1) are shown as examples of the most variable proteins. The red bars show the positions of the protein analytes whose measurement has been cleared or approved by FDA in human blood.
© Copyright Policy - open-access
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4358658&req=5

fig02: Proteomic identification and reproducible quantification among the twin cohortA The establishment of a comprehensive, specific spectral library of human plasma proteome that is ready for SWATH-MS analysis. The reference spectra were generated a priori by extensive shotgun proteomic sequencing of fractionated plasma peptides and complemented with spectra of additional known plasma proteins (Farrah et al, 2011).B The coefficient of variance (CV) analysis at technical, whole-process experimental and cohort levels.C Heatmap of hierarchical clustering analysis of the protein vs. sample matrix indicates that plasma proteins were reproducibly quantified by SWATH-MS across the sample cohort.D The distribution of the fold changes of protein SWATH-MS intensities from their average abundance levels across the cohort is shown as box plots. Antithrombin III (ANT3) and vitamin D-binding protein (VTDB) are shown as examples of the most stable proteins, whereas apolipoprotein(a) (APOA) and serum amyloid A-1 protein (SAA1) are shown as examples of the most variable proteins. The red bars show the positions of the protein analytes whose measurement has been cleared or approved by FDA in human blood.
Mentions: The data-independent acquisition (DIA) mass spectrometric quantification method of SWATH-MS essentially converts all the peptides ionized from a biological sample into a high-resolution, digital map of fragment ion signals (Gillet et al, 2012; Liu et al, 2013a) (Fig1). In these maps, specific proteins were monitored via a targeted data analysis strategy, where fragment ion signal groups uniquely identifying a targeted peptide were detected and quantified in each of the 232 SWATH-MS maps. The parameters of the signal group for each peptide, including the fragment ion masses, their relative intensity and chromatographic concordance, the peptide retention time and precursor mass range, constituted a specific assay for each targeted peptide that was prepared a priori from a spectral library of the human plasma proteome (Fig2A). Specifically, to generate this spectral library, we deployed comprehensive shotgun proteomic sequencing of the plasma digest of a mixed plasma sample, which was firstly depleted of the 14 most abundant proteins and then fractionated by strong anion exchanger at the peptide level, yielding specific assays for 652 proteins. Further, we included in the library additional MS assays for plasma proteins (Farrah et al, 2011) from an in-house SWATH assay compendium for the human proteome (Rosenberger et al, 2014). The final combined library contained more than 43,000 peptides, representing 1,667 unique plasma proteins, which represents, as of to date, the largest SWATH-ready spectral library for the human plasma proteome (freely provided with raw data), and therefore maximized the number of identified proteins from the SWATH maps.

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.


Related in: MedlinePlus