Here you find all published genome-wide association studies with multiplexed protein traits in blood (pGWAS). If a study is missing from this list, please let me know.
This table was initially published as Supplementary Table 1 in Suhre et al. (2017) (with 6 entries at the time). A much extended version can be found in our recent Nature Reviews Genetics paper “Genetics meets proteomics: perspectives for large population-based studies” (https://doi.org/10.1038/s41576-020-0268-2). The full paper can be read online using this link: https://t.co/DjWAknSqWq
As pGWAS expand, I also now include GWAS on other human body fluids and tissues (there are three pGWAS in CSF for now).
There are four pGWAS in human cell lines, which I keep here for the time being:
- Garge et al. Identification of Quantitative Trait Loci Underlying Proteome Variation in Human Lymphoblastoid Cells, Molecular & Cellar Protemics, 2010.
- Wu et al., Variation and Genetic Control of Protein Abundance in Humans, Nature 2013.
- Hause et al., Identification and Validation of Genetic Variants That Influence Transcription Factor and Cell Signaling Protein Levels, Am J Hum Genet 2014.
- Mirauta et al., Population-scale proteome variation in human induced pluripotent stem cells, eLife, 2020.
If you are interested in associations at specific loci you may also use the SNiPA block annotation tool [read this post], and if you are looking for associations specific to certain proteins, try the Proteomics GWAS Server [read this post].
The Proteome PheWAS browser is a great tool to find out which proteins may be causal for certain diseases – using Mendelian Randomization [read the paper on BioRxiv].
Olink-improve – Genetics of the Cardiovascular Proteome is a web-server for pQTLs of the Olink platform.
| Reference | Study population | #Samples in study | #Proteins assayed | #pQTLs reported | Platform type |
|---|---|---|---|---|---|
| Melzer et al. (PLoS Genet, 2008) | Population study | 1200 | 42 | 8 | Immuno-assay |
| Lourdusamy et al. (Hum Mol Genet, 2012) | Elderly Europeans | 96 | 778 | 60 | Aptamer-based (SOMAscan v1) |
| Johansson et al. (PNAS, 2013) | Two population cohorts | 1060 | 163 | 5 | Mass-spectrometry |
| Kim et al. (PLoS One, 2013) | Altzheimer's disease cohort | 521 | 132 | 28 | Immuno-assay |
| Orru et al. (Cell, 2013) | Individuals from four clustered Sardinian villages | 1629 | 272 | 23 | Immune traits (not really proteomics) |
| Stark et al. (PLoS Genetics, 2014) | Yoruba HapMap lymphoblastoid cell lines | 68 | 441 | NA | Micro-western and reverse phase protein arrays |
| Enroth et al. (Nature Comm, 2014) | Population study | 970 | 77 | 18 | Immuno-assay |
| Kauve et al., (PLoS Genet., 2014) | CSF fluid from two Altzheimer's disease cohorts | 574 | 59 | 5 | Immuno-assay for proteins relevant to Altzheimer's disease |
| Liu et al. (Mol Syst Biol, 2015) | Female twins | 113 | 342 | 18 | Mass-spectrometry |
| Sun et al. (PLOS Genetics, 2016) | Current and former smokers with and without COPD (SPIROMICS & COPDGene ) | 1340 | 88 | 527 | Multiplex immuno assays (Myriad-RBM) |
| Deming et al. (Sci Rep, 2016) | Alzheimer cohort | 818 | 146 | 56 | Immuno-assay |
| Solomon et al. (Circ Cardiovasc Genet, 2016) | Population study | 330 | 51 | 27 | Immuno-assay for proteins implicated in cardiovascular diseases |
| Ahola-Olli et al. (Am J Hum Genet, 2017) | Population study | 8293 | 48 | 27 | Immuno-assay for cytokines and growth factors |
| Di Narzo et al. (PLoS Genet, 2017) | Inflammatory bowel disease (IBD) patients | 187 | 1128 | 41 | Aptamer-based (SOMAscan 1.1k) |
| Suhre et al. (Nature Comm, 2017) | KORA and QMDiab study (Germany and Qatar) | 1335 | 1124 | 539 | Aptamer-based (SOMAscan 1.1k) |
| Sasayama et al. (Hum Mol Genet, 2017) | CSF fluid from a Japanese population | 133 | 1126 | 476 | Aptamer-based (SOMAscan 1.1k) |
| Folkersen et al. (PLoS Genet., 2017) | Population study | 3394 | 83 | 79 | Immuno-assay for proteins implicated in cardiovascular diseases |
| de Vries et al. (Hum. Mol. Genet., 2017) | 1,552 European Americans and 1,872 African Americans (ARIC study) | 3424 | 25 | 22 | Mass-spectrometry (small peptide subset of the non-targeted Metabolon metabolomics platform) |
| Ahsan et al. (PLoS Genet., 2017) | Population study | 1033 | 121 | 45 | Antibody-based proximity extension assay |
| Carayol et al. (Nature Comm, 2017) | Obese subjects | 494 | 1129 | 55 | Aptamer-based (SOMAscan 1.1k) |
| Benson et al. (Circulation, 2017) | Framingham Heart Study and Malmö Diet and Cancer Study | 2180 | 1129 | 161 | Aptamer-based, array based genotyping and exome seq |
| Patin et al. (Nature Immunology, 2018) | unrelated, Western European ancestry, Milieu Intérieur cohort | 1000 | 87 | 36 | Mean fluorescence intensity (MFI), cell surface marker (not really proteomics) |
| Sun et al. (Nature, 2018); pre-print on bioRxiv | Interval study (UK blood donors) | 3301 | 2994 | 1927 | Aptamer-based (SOMAscan in-house) |
| Emilsson et al. (Science, 2018) | AGES Reykjavik study (Islanders over 65) | 5457 | 4137 | 3134 | Aptamer-based (SOMAscan in-house) |
| Yao et al. (Nature Comm, 2018); pre-print on bioRxiv | Framingham Heart Study | 6861 | 71 | 105 | Immuno-assay for proteins implicated in cardiovascular diseases, replication aptamer-based |
| Sliz et al. (J. Med. Genet., 2019), pre-print on bioRxiv | Northern Finland Birth Cohort 1966 + meta-analysis in N=13,577 | 5284 | 16 | 16 | Immuno-assay (Luminex / Milliplex, targeting chemokines & cytokines) |
| Mirauta et al. (BioRxiv, 2018) | Human induced pluripotent stem cell lines (iPSC) | 202 | NA | 712 | Tandem Mass Tag Mass Spectrometry (TMT-MS) |
| Zhernakova et al. (Nature Gen. 2018) | LifeLines Dutch population cohort | 1264 | 92 | 214 | Immuno-assay (Olink CVD II panel) |
| Solomon et al. (Circulation: Genomic and Precision Medicine, 2018) | Tromsø Study | 165 | 664 | 60 | Tandem mass tag mass spectrometry, with whole-exome sequencing |
| Zheng et al. (BioRxiv, 2019) | A Mendelian Randomization study based on pGWAS (somewhat out of scope for this table, but VERY interesting) | NA | 1002 | NA | Proteome PheWAS browser |
| Hillary et al. (Nat. Comm., 2019) | Lothian Birth Cohort 1936 | 750 | 92 | 41 | Immuno-assay (Olink neurology panel) |
| Peters et al. (ASHG 2019 abstract) | SCALLOP consortium | 15335 | 92 | at least one pQTL for 71 out of 91 proteins; 12 had cis pQTLs only, 14 trans only, and 45 both cis and trans | Immuno-assay (Olink INF panel) |
| Wilson et al. (ASHG 2019 abstract) | SCALLOP consortium | 19578 | 184 | 22,518 genome-wide significant SNPs | Immuno-assay (Olink CVD II & III panels) |
| Klaric et al. (ASHG 2019 abstract) | genetically isolated ORCADES cohort (Scotland) | 1059 | 1102 | 3,545 pQTLs between 374 proteins and 968 genes mapping to 377 genomic regions | Immuno-assay (multiple Olink panels) |
| Yang et al. (ASHG 2019 abstract) | CSF fluid, Alzheimer's disease, cases and controls | 520 | 713 | 82 proteins with cis-pQTLs, 20 proteins with novel trans-pQTLs | Probably aptamer-based (SOMAscan 1.3k) |
| Robins et al. (bioRxiv, 2019) previously presented at ASHG 2019 | Dorsolateral prefrontal cortex (DLPFC) tissue from ROSMAP | 144 cognitively normal individuals | 7901 (tested in cis) | 28,221 pQTLs with 864 proteins | Tandem mass tag (TMT) proteomics of brain tissue; uses Whole Genome Sequencing |
| Höglund et al. (Scientific Rep., 2019) | Northern Swedish population health study (NSPHS) | 1005 | 72 | 18 novel | Immuno-assay (from Olink panels Oncology I and CVD I); uses Whole Genome Sequencing |
| Nath et al. (AJHG 2019) | three population-based cohorts | 9267 | 18 | 8 loci | Cytokines using multiplex fluorescent bead-based immunoassays (Bio-Rad) |
| Folkersen et al. (BioRxiv, 2020), previously presented at ASHG 2019 | SCALLOP consortium, incl. 13 studies | 21758 | 90 | 467 | Immuno-assay (Olink CVD-I panel) |
| Sjaarda et al. (AJHG, 2020) | Latin Americans, ORIGIN study | 2216 | 237 | 46 regions (not a GWAS, uses admixture mapping) | Cardiometabolic biomarkers, Luminex 100/200 immunoassay platform |
| Gilly et al. (bioRxiv 2020) | Hellenic Isolated Cohorts MANOLIS study | 1328 | 257 | 131 | Immuno-assay (Olink CVD-II, CVD-III, and MET panels), uses Whole Genome Sequencing |
| Emilsson et al. (bioRxiv 2020) | AGES Reykjavik study (Islanders over 65) | 5457 | 4782 | 5553 | Aptamer-based (SOMAscan in-house) |
| Zhong et al. (BMC Genome Med, 2020) | Longitudinal wellness cohort from Sweden | 101 | 794 | 144 pQTLs across 107 proteins | Immuno-assay (11 Olink panels) |
| Hillary et al. (Genome Medicine 2020), pre-print on BioRxiv | Lothian Birth Cohort 1936 | 876 | 70 | 13 | Immuno-assay (Olink inflammation panel) |
| Ruffieu et al. (PLoS Comp Bio 2020), presented at ASHG 2018 abstract, pre-print on bioRxiv | Optifast Canadian cohort & DiOGenes cohort | 2433 | 1230 | 136 | MS proteomics (130 proteins) and Aptamer-based (1100 proteins) |
| Bretherick et al. (PLoS Genetics, 2020) | Isolated populations from the islands of Orkney (Scotland) and Vis (Croatia) | up to 1992 | 249 | 154 | Immuno-assay (Olink CVD2, CVD3, and INF panels) |
| Pietzner et al. (bioRxiv, 2020) | Fenland study (UK) | 10,708 | 4,775 proteins evaluated by 4,979 aptamers | 678 (regional sentinel pQTLs, reported in ST3) | Aptamer-based (Somalogic V4 platform) |
| Wang et al. (PLoS Genetics, 2020) | Neonatal blood spots from the Danish iPSYCH initiative | 9,459 | 10 cytokines | 16 | Immuno-assay (Luminex) |
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