A fully joint Bayesian quantitative trait locus mapping of human protein abundance in plasma

Ruffieux, Hélène; Carayol, Jérôme; Popescu, Radu; Harper, Mary‐Ellen; Dent, Robert; Astrup, Arne; Hager, Jörg; Davison, A. C.; Valsesia, Armand

doi:10.1371/journal.pcbi.1007882

Cited by 21 publications

(19 citation statements)

References 43 publications

(86 reference statements)

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“…In this work, Petrera et al reported a limited overlap of just 35 proteins but argued for the complementarity of the methods . In another study by Ruffieux et al, two sample cohorts were analyzed by SomaScan, detecting 1096 proteins in both cohorts, and MS-based assays using immunodepleted and 6-plex isobaric labeling, detecting 133 proteins in both cohorts . In the common set of 72 proteins detected by both methods, they found agreement between some of the reported protein levels (e.g., SHBG, CAH1, or CXCL7) and another 25 proteins with concordant effects associated with pQTL (e.g., CFB, CO7, or FETUA).…”

Section: Recent Advancesmentioning

confidence: 60%

“…31−34 SomaLogic and Olink data have been used more widely to confirm the identification of protein quantitative trait loci (pQTL) in genome-wide associations studies (GWAS). 35,36 39 In the common set of 72 proteins detected by both methods, they found agreement between some of the reported protein levels (e.g., SHBG, CAH1, or CXCL7) and another 25 proteins with concordant effects associated with pQTL (e.g., CFB, CO7, or FETUA). Consequently, there are factors other than analytical sensitivity that need to be considered.…”

Section: ■ Recent Advancesmentioning

confidence: 61%

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Advances and Utility of the Human Plasma Proteome

et al. 2021

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The study of proteins circulating in blood offers tremendous opportunities to diagnose, stratify, or possibly prevent diseases. With recent technological advances and the urgent need to understand the effects of COVID-19, the proteomic analysis of blood-derived serum and plasma has become even more important for studying human biology and pathophysiology. Here we provide views and perspectives about technological developments and possible clinical applications that use mass-spectrometry(MS)- or affinity-based methods. We discuss examples where plasma proteomics contributed valuable insights into SARS-CoV-2 infections, aging, and hemostasis and the opportunities offered by combining proteomics with genetic data. As a contribution to the Human Proteome Organization (HUPO) Human Plasma Proteome Project (HPPP), we present the Human Plasma PeptideAtlas build 2021-07 that comprises 4395 canonical and 1482 additional nonredundant human proteins detected in 240 MS-based experiments. In addition, we report the new Human Extracellular Vesicle PeptideAtlas 2021-06, which comprises five studies and 2757 canonical proteins detected in extracellular vesicles circulating in blood, of which 74% (2047) are in common with the plasma PeptideAtlas. Our overview summarizes the recent advances, impactful applications, and ongoing challenges for translating plasma proteomics into utility for precision medicine.

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Section: Recent Advancesmentioning

confidence: 60%

Section: ■ Recent Advancesmentioning

confidence: 61%

Advances and Utility of the Human Plasma Proteome

et al. 2021

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“…GASP1/WFKINN2 has mainly been involved in skeletal and muscle fiber development in the heart 60 . Higher WFIKKN2 protein levels were associated with lower levels of fasting insulin, triglycerides, HOMA-IR, and visceral fat 61 suggesting a protective role against metabolic dysregulation.…”

Section: Discussionmentioning

confidence: 94%

Revealing the role of the human blood plasma proteome in obesity using genetic drivers

et al. 2021

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Blood circulating proteins are confounded readouts of the biological processes that occur in different tissues and organs. Many proteins have been linked to complex disorders and are also under substantial genetic control. Here, we investigate the associations between over 1000 blood circulating proteins and body mass index (BMI) in three studies including over 4600 participants. We show that BMI is associated with widespread changes in the plasma proteome. We observe 152 replicated protein associations with BMI. 24 proteins also associate with a genome-wide polygenic score (GPS) for BMI. These proteins are involved in lipid metabolism and inflammatory pathways impacting clinically relevant pathways of adiposity. Mendelian randomization suggests a bi-directional causal relationship of BMI with LEPR/LEP, IGFBP1, and WFIKKN2, a protein-to-BMI relationship for AGER, DPT, and CTSA, and a BMI-to-protein relationship for another 21 proteins. Combined with animal model and tissue-specific gene expression data, our findings suggest potential therapeutic targets further elucidating the role of these proteins in obesity associated pathologies.

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“…To manage this tension between scalable inference and comprehensive joint modeling, we recently proposed a variational inference approach, called ATLASQTL, 5 which explicitly borrows information across thousands of molecular traits controlled by shared pathways and offers a robust fully Bayesian parametrization of hotspots; its increased sensitivity and that of earlier related models have been demonstrated in different molecular QTL studies. 4 , 5 , 6 , 7 …”

Section: Introductionmentioning

confidence: 99%

EPISPOT: An epigenome-driven approach for detecting and interpreting hotspots in molecular QTL studies

Ruffieux

Fairfax

Nassiri

et al. 2021

The American Journal of Human Genetics

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We present EPISPOT, a fully joint framework which exploits large panels of epigenetic annotations as variant-level information to enhance molecular quantitative trait locus (QTL) mapping. Thanks to a purpose-built Bayesian inferential algorithm, EPISPOT accommodates functional information for both cis and trans actions, including QTL hotspot effects. It effectively couples simultaneous QTL analysis of thousands of genetic variants and molecular traits with hypothesis-free selection of biologically interpretable annotations which directly contribute to the QTL effects. This unified, epigenome-aided learning boosts statistical power and sheds light on the regulatory basis of the uncovered hits; EPISPOT therefore marks an essential step toward improving the challenging detection and functional interpretation of trans-acting genetic variants and hotspots. We illustrate the advantages of EPISPOT in simulations emulating real-data conditions and in a monocyte expression QTL study, which confirms known hotspots and finds other signals, as well as plausible mechanisms of action. In particular, by highlighting the role of monocyte DNase-I sensitivity sites from >150 epigenetic annotations, we clarify the mediation effects and cell-type specificity of major hotspots close to the lysozyme gene. Our approach forgoes the daunting and underpowered task of one-annotation-at-a-time enrichment analyses for prioritizing cis and trans QTL hits and is tailored to any transcriptomic, proteomic, or metabolomic QTL problem. By enabling principled epigenome-driven QTL mapping transcriptome-wide, EPISPOT helps progress toward a better functional understanding of genetic regulation.

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A fully joint Bayesian quantitative trait locus mapping of human protein abundance in plasma

Cited by 21 publications

References 43 publications

Advances and Utility of the Human Plasma Proteome

Advances and Utility of the Human Plasma Proteome

Revealing the role of the human blood plasma proteome in obesity using genetic drivers

EPISPOT: An epigenome-driven approach for detecting and interpreting hotspots in molecular QTL studies

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