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
| Reference | #Samples in study | Study population | #Proteins assayed | #pQTLs reported | Platform type |
|---|---|---|---|---|---|
| Melzer et al. (PLoS Genet, 2008) | 1200 | Population study | 42 | 8 | Immuno-assay |
| Lourdusamy et al. (Hum Mol Genet, 2012) | 96 | Elderly Europeans | 778 | 60 | Aptamer-based (SOMAscan v1) |
| Johansson et al. (PNAS, 2013) | 1060 | Two population cohorts | 163 | 5 | Mass-spectrometry |
| Kim et al. (PLoS One, 2013) | 521 | Altzheimer's disease cohort | 132 | 28 | Immuno-assay |
| Orru et al. (Cell, 2013) | 1629 | Individuals from four clustered Sardinian villages | 272 | 23 | Immune traits (not really proteomics) |
| Stark et al. (PLoS Genetics, 2014) | 68 | Yoruba HapMap lymphoblastoid cell lines | 441 | NA | Micro-western and reverse phase protein arrays |
| Enroth et al. (Nature Comm, 2014) | 970 | Population study | 77 | 18 | Immuno-assay |
| Kauve et al., (PLoS Genet., 2014) | 574 | CSF fluid from two Altzheimer's disease cohorts | 59 | 5 | Immuno-assay for proteins relevant to Altzheimer's disease |
| Liu et al. (Mol Syst Biol, 2015) | 113 | Female twins | 342 | 18 | Mass-spectrometry |
| Sun et al. (PLOS Genetics, 2016) | 1340 | Current and former smokers with and without COPD (SPIROMICS & COPDGene ) | 88 | 527 | Multiplex immuno assays (Myriad-RBM) |
| Deming et al. (Sci Rep, 2016) | 818 | Alzheimer cohort | 146 | 56 | Immuno-assay |
| Solomon et al. (Circ Cardiovasc Genet, 2016) | 330 | Population study | 51 | 27 | Immuno-assay for proteins implicated in cardiovascular diseases |
| Ahola-Olli et al. (Am J Hum Genet, 2017) | 8293 | Population study | 48 | 27 | Immuno-assay for cytokines and growth factors |
| Di Narzo et al. (PLoS Genet, 2017) | 187 | Inflammatory bowel disease (IBD) patients | 1128 | 41 | Aptamer-based (SOMAscan 1.1k) |
| Suhre et al. (Nature Comm, 2017) | 1335 | KORA and QMDiab study (Germany and Qatar) | 1124 | 539 | Aptamer-based (SOMAscan 1.1k) |
| Sasayama et al. (Hum Mol Genet, 2017) | 133 | CSF fluid from a Japanese population | 1126 | 476 | Aptamer-based (SOMAscan 1.1k) |
| Folkersen et al. (PLoS Genet., 2017) | 3394 | Population study | 83 | 79 | Immuno-assay for proteins implicated in cardiovascular diseases |
| de Vries et al. (Hum. Mol. Genet., 2017) | 3424 | 1,552 European Americans and 1,872 African Americans (ARIC study) | 25 | 22 | Mass-spectrometry (small peptide subset of the non-targeted Metabolon metabolomics platform) |
| Ahsan et al. (PLoS Genet., 2017) | 1033 | Population study | 121 | 45 | Antibody-based proximity extension assay |
| Carayol et al. (Nature Comm, 2017) | 494 | Obese subjects | 1129 | 55 | Aptamer-based (SOMAscan 1.1k) |
| Benson et al. (Circulation, 2017) | 2180 | Framingham Heart Study and Malmö Diet and Cancer Study | 1129 | 161 | Aptamer-based, array based genotyping and exome seq |
| Patin et al. (Nature Immunology, 2018) | 1000 | unrelated, Western European ancestry, Milieu Intérieur cohort | 87 | 36 | Mean fluorescence intensity (MFI), cell surface marker (not really proteomics) |
| Sun et al. (Nature, 2018); pre-print on bioRxiv | 3301 | Interval study (UK blood donors) | 2994 | 1927 | Aptamer-based (SOMAscan in-house) |
| Emilsson et al. (Science, 2018) | 5457 | AGES Reykjavik study (Islanders over 65) | 4137 | 3134 | Aptamer-based (SOMAscan in-house) |
| Yao et al. (Nature Comm, 2018); pre-print on bioRxiv | 6861 | Framingham Heart Study | 71 | 105 | Immuno-assay for proteins implicated in cardiovascular diseases, replication aptamer-based |
| Sliz et al. (J. Med. Genet., 2019), pre-print on bioRxiv | 5284 | Northern Finland Birth Cohort 1966 + meta-analysis in N=13,577 | 16 | 16 | Immuno-assay (Luminex / Milliplex, targeting chemokines & cytokines) |
| Mirauta et al. (eLife, 2020), preprint on BioRxiv, 2018 | 202 | Human induced pluripotent stem cell lines (iPSC) | NA | 712 | Tandem Mass Tag Mass Spectrometry (TMT-MS) |
| Zhernakova et al. (Nature Gen. 2018) | 1264 | LifeLines Dutch population cohort | 92 | 214 | Immuno-assay (Olink CVD II panel) |
| Solomon et al. (Circulation: Genomic and Precision Medicine, 2018) | 165 | Tromsø Study | 664 | 60 | Tandem mass tag mass spectrometry, with whole-exome sequencing |
| Zheng et al. (Nature Genetics, 2020), preprint on BioRxiv, 2019 | NA | A Mendelian Randomization study based on pGWAS (somewhat out of scope for this table, but VERY interesting) | 1002 | NA | Proteome PheWAS browser |
| Hillary et al. (Nat. Comm., 2019) | 750 | Lothian Birth Cohort 1936 | 92 | 41 | Immuno-assay (Olink neurology panel) |
| Peters et al. (ASHG 2019 abstract) | 15335 | SCALLOP consortium | 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) | 19578 | SCALLOP consortium | 184 | 22,518 genome-wide significant SNPs | Immuno-assay (Olink CVD II & III panels) |
| Klaric et al. (ASHG 2019 abstract) | 1059 | genetically isolated ORCADES cohort (Scotland) | 1102 | 3,545 pQTLs between 374 proteins and 968 genes mapping to 377 genomic regions | Immuno-assay (multiple Olink panels) |
| Robins et al. (AJHG 2021), preprint on bioRxiv, 2019 | 330 | Dorsolateral prefrontal cortex (DLPFC) tissue from ROSMAP | 7376 | 8,451 independent proximal brain pQTLs for 2,474 genes | Tandem mass tag (TMT) proteomics of brain tissue; uses Whole Genome Sequencing |
| Höglund et al. (Scientific Rep., 2019) | 1005 | Northern Swedish population health study (NSPHS) | 72 | 18 novel | Immuno-assay (from Olink panels Oncology I and CVD I); uses Whole Genome Sequencing |
| Nath et al. (AJHG 2019) | 9267 | three population-based cohorts | 18 | 8 loci | Cytokines using multiplex fluorescent bead-based immunoassays (Bio-Rad) |
| Folkersen et al. (Nature Metabolism, 2020), preprint on bioRxiv, 2020 | 30,931 | SCALLOP consortium, incl. 13 studies | 90 | 451 pQTLs for 85 proteins | Immuno-assay (Olink CVD-I panel) |
| Sjaarda et al. (AJHG, 2020) | 2216 | Latin Americans, ORIGIN study | 237 | 46 regions (not a GWAS, uses admixture mapping) | Cardiometabolic biomarkers, Luminex 100/200 immunoassay platform |
| Gilly et al. (Nat. Comm. 2020), preprint on bioRxiv | 1328 | Hellenic Isolated Cohorts MANOLIS study | 257 | 131 | Immuno-assay (Olink CVD-II, CVD-III, and MET panels), uses Whole Genome Sequencing |
| Emilson et al. (Nat. Comm. 2022), preprint bioRxiv 2020 | 5343 | AGES Reykjavik study (Islanders over 65) | 4782 | 5451 | Aptamer-based (SOMAscan in-house) |
| Zhong et al. (BMC Genome Med, 2020) | 101 | Longitudinal wellness cohort from Sweden | 794 | 144 pQTLs across 107 proteins | Immuno-assay (11 Olink panels) |
| Dodig-Crnkovic et al. (EBioMedicine 2020) | 2,592 twins | Swedish Twin Registry (STR), participants born between 1911-1958 | 734 | 15 cis-pQTLs | Antibodies in suspension bead arrays |
| Hillary et al. (Genome Medicine 2020), pre-print on BioRxiv | 876 | Lothian Birth Cohort 1936 | 70 | 13 | Immuno-assay (Olink inflammation panel) |
| Ruffieu et al. (PLoS Comp Bio 2020), pre-print on bioRxiv | 2433 | Optifast Canadian cohort & DiOGenes cohort | 1230 | 136 | MS proteomics (130 proteins) and Aptamer-based (1100 proteins) |
| Bretherick et al. (PLoS Genetics, 2020) | up to 1992 | Isolated populations from the islands of Orkney (Scotland) and Vis (Croatia) | 249 | 154 | Immuno-assay (Olink CVD2, CVD3, and INF panels) |
| Pietzner et al. (Nature Comm, 2021), preprint on bioRxiv | 10,708 | Fenland study (UK) | 4,775 proteins evaluated by 4,979 aptamers | 220 cis-pQTLs for 97 proteins | Aptamer-based (Somalogic V4 platform) |
| Zhang et al. (Nature Genetics, 2022), preprint on (bioRxiv) | 7,213 European Americans (EA) and 1,871 African Americans (AA) | Atherosclerosis Risk in Communities (ARIC) cohort study | 4657 | 1005 (AA) and 1384 (EA) cis-associations (trans not analyzed) | Aptamer-based (Somalogic V4) |
| Brown et al. (Nat. Comms. 2023) | 3,029 | DIRECT study | 373 | 1,590 cis-pQTLs, 533 trans-pQTLs | Immuno-assay (four Olink panels: CVD I, II, II, Development & Metabolism); study also incl. metabolomics & transcriptomics GWAS |
| Zhong et al., (Nature Comm. 2021) | 101 | Longitudinal wellness cohort from Sweden | 1463 | 331 associations between 143 proteins and 321 independent genetic variants | Immuno-assay (Olink Explorer platform) |
| Gurinovich et al. (GeroScience, 2021) | 224 | New England Centenarian Study (NECS) | 4131 | Supp Tab 3 provides pQTL data for 21 age-associated variants with 3641 aptamers | Aptamer-based (Somalogic V4? platform) |
| Gudjonsson et al. (Nat. Comm. 2022), (bioRxiv 2021) | 5368 | AGES study (Islanders over 65) | 4782 | 4113 | Aptamer-based (SOMAscan in-house) |
| Yang et al. (Nature Neuroscience, 2021), preprint medRxiv | 835, 529, and 380 CSF, plasma, and brain samples, resp. | Three tissues (cerebrospinal fluid, plasma, brain) from Europeans with and without Alzheimer's disease | 713, 931, and 1079 proteins after QC in in CSF, plasma, and brain, resp. | 274, 127 and 32 pQTLs for CSF, plasma, and brain, resp. | Aptamer-based (SOMAscan 1.3k) |
| Pietzner et al. (Science, 2021) | 12,084 | fasted EDTA-plasma samples from the Fenland study | 4,775 | 10,674 pQTLs for 3,892 proteins | Aptamer-based (Somalogic V4 platform) |
| Katz et al. (Circulation, 2021) | 1,852 | Black adults from the Jackson Heart Study | 1,301 | 569 | Aptamer-based (SOMAscan 1.3k) |
| Ferkingstad et al. (Nature Genetics, 2021) | 35,559 | Icelanders | 4,907 | 18,084 | Aptamer-based (Somalogic V4 platform) |
| Png et al. (Nat Comm, 2021) | 2,893 | MANOLIS and Pomak, part of the Hellenic Isolated Cohorts (HELIC) | 184 | 214 pQTLs for 107 proteins | Immuno-assay (Olink neurology and neuro-exploratory panels) |
| Preprint on Research Square, 2022 | 288 | postmortem human brain samples (179 males, 109 females) from the Stanley Medical Research Institute (SMRI) and Banner Sun Health Research Institute (BSHRI) | 11,672 | 788 cis-pQTLs with 883 proteins | 11-plex tandem mass tag (TMT) coupled with two-dimensional liquid chromatography-tandem mass spectrometry (LC/LC-MS/MS) |
| Sun et al., bioRxiv 2022 | 1,472 | UK Biobank, frequent variants with imputed genotype | 35,571 (discovery) and 18,181 (replication) | 10,248 primary associations across 2,928 independent genetic regions | Olink Explore 1536 platform |
| Katz et al., Science Advances 2022 | 568 (Jackson Heart Study), 219 (HERITAGE Family Study) | Jackson Heart Study and HERITAGE Family Study | 1301 (SomaScan1.3K), 4979 (SomaScan5K), 1472 (Olink Explore) | 425 known + 373 new cis-pQTLs | SomaScan1.3K, SomaScan5K, Olink Explore |
| Thareja et al., Human Mol. Genetics (in press) | 2,935 | Qatar Biobank, whole genome sequencing | 1,301 | 2,685 | SomaScan1.3k |
| He et al., BMC Biology, 2020 | 287 | normal human liver samples | 1,508 | 900 local pQTL variants and 4026 distant pQTL variants | LC-MS/MS using DIA-TPA |
| Dhindsa et al. medRxiv 2022 | 50,829 | UK Biobank, rare variants with exome seq | 1,472 | 3,674 | Olink Explore 1536 platform |
| Hou et al. (ASHG abstract, 2022) | 13,227 | UK Biobank European participants with WGS data | 1,463 | 2,374 | Olink Explore 1536 platform |
| Chen et al. (ASHG abstract, 2022) | 1,002 | Women’s Health Initiative (WHI) | 552 | not specified | targeted Olink panels |
| Koprulu et al. (ASHG abstract, 2022) | 1,180 | not specified | 2,923 | 1,553 cis-pQTLs | a novel antibody-based assay (source not specified) |
| Richardson et al. (ASHG abstract, 2022) | 42,000 | UK Biobank Pharma Proteomics Project | 1,462 | not specified | Olink Explore 1536 platform |
| Kuliesius et al. (ASHG abstract, 2022) | not specified | Viking Health Study - Shetland | 6,434 | 456 | Somalogic aptamer-based technology |
| Cruchaga et alk. (ASHG abstract, 2022) | 3,065 | Cerebrospinal fluid (CSF) | 7,584 | 2,472 | Somalogic aptamer-based technology [study also has Metabolon mQTLs] |
| Cai et al. (ASHG abstract, 2022) | 1,537 AA, 883 EA,1062 EA from Framingham Heart Study | African American (AA) and European American (EA) from the Women's Health Initiative | 1,472 | 1,678 (AA), 1,153 (EA) | Olink Explore 1536 platform |
| Siddiqui et al. (ASHG abstract, 2022) | 139 | Late-stage Alzheimer’s disease (case/control) | 5,060/4,706 from DDA/DIA | 73/59 cis-pQTLs and 1,527/3,288 trans-pQTLs from DDA/DIA | Proteograph Product Suite (Seer Inc.) using nanoparticle-based enrichment, DIA and DDA MS/MS |
| Chiou et al. (ASHG abstract, 2022) | 35,306 | UK Biobank Pharma Proteomics Project | 1,424 | 28,867 | Olink Explore 1536 platform |
| Wingo et al. (ASHG abstract, 2022) | 1,100 | Brain proteomes (dorsolateral prefrontal cortex), European ancestry | 10,198 | 1,171 SNP-by-sex interactions | not specified |
| Surapaneni et al. (Kidney International, 2022) | 466 | Serum of African Americans | 6,790 | 696 | SOMAScan 4.1 |
| Hansson et al. (EMBO Mol. Med. 2022) | 1,591 | Cerebrospinal fluid (CSF) | 398 | 176 | Olink panels (CVD-III, INF-I, NEU-I, NEUEXP) + other assays (ELISA, Meso Scale Discovery, ..) |
| Caron et al. (Genome Medicine, 2022) | 400 | Milieu Intérieur cohort, France | 229 | 152 | Luminex |
| Hillary et al. (Alzheimers Dement, 2022) | 1,064 | Scottish Family Health Study | 282 AD associated proteins | 64 | SOMAscan v4 |
| Koprulu et al. (Nature Metabolism, 2023) | 2,923 | EPIC-Norfolk (UK) | 1,180 | 256 unreported pQTLs | Olink Explore 1536 and Explore Expansion assays |
| Niu et al., medRxiv 2023 | 1,914 | HOLBAEK Study, children and adolescents (Denmark) | 420 | 712 for 158 proteins | DIA-MS |
| Xu et al. (Nat. Comm., 2023) | 2,958 | Han Chinese | 304 | 195 | SWATH-MS |
| Wingo et al. (Nat. Med. 2023) | 1,277 human brain proteomes | Donors of European ancestry from multiple studies | 10,198 | 1,036,025 pQTLs identified in the first stage | Isobaric tandem mass tag peptide labeling with peptides analyzed by liquid chromatography coupled to tandem mass spectrometry (MS) |
| Wingo et al. (Nat. Genet. 2023) | 376 human brain proteomes | Donors of European ancestry from multiple studies | 8,356 | N/A | Isobaric tandem mass tag peptide labeling with peptides analyzed by liquid chromatography coupled to tandem mass spectrometry (MS) |
| Zhao et al. (Nat. Immun. 2023) | 14,824 | 11 cohorts from the Scallop consortium | 91 | 180 pQTLs (59 cis, 121 trans) | Olink Inflamation panel |
| Sun et al. (Nature 2023) | 54,219 | UK Biobank Pharma Proteomics Project | 2,923 | 14,287 | Olink Explore 3072 |
| Dhindsa et al. (Nature 2023) | 49,736 | UK Biobank Pharma Proteomics Project | 2,923 | 5,433 rare genotype–protein associations | Olink Explore 3072 |
| Eldjarn et al. (Nature 2023) | >50,000 | UK Biobank Pharma Proteomics Project | 2,941 | 2,102 cis and 24,824 trans in the British or Irish ancestry group | Olink Explore 3072 |
| Macdonald-Dunlop et al. (medRxiv 2021) | 26,494 | 18 cohorts of European ancestry from Scallop | 184 | 1,308 | Olink CVD2 and CVD3 panels |
| Carland et al. (Clin. Proteom. 2023) | 22,997 | 12 cohorts of primary European ancestry from Scallop | 92 | 503 | Olink Metabolism panel |
| Gilly et al. (Molecular Metabolism, 2023) | 3,005 | two isolated Greek populations | 92 | 322 | Olink Cardiometabolic panel |
| Said et al. (MedRxiv, 2023) | 3,974 | China Kadoorie Biobank | 1,451 | 2,872 | Olink Explore 1536 platform |
| Suhre (Cell Genomics 2024) | 52,705 | UK Biobank Pharma Proteomics Project | 2,821 ratios | 8,462 rQTLs | Olink Explore 1536 platform |
| Kalnapenkis et al. (Scientific Reports 2024) | 500 | Estonian Biobank | 326 | 278 (184 cis, 94 trans) | Olink CVD II, CVD III, Inflammation, Oncology II |
| Fang et al. medRxiv 2025 | 700 | GTEx | 10,841 | 1981 cis-pQTLs | LC-TMT-MS |
As pGWAS expand, I also now include GWAS on other human body fluids and tissues.
Here are three older pGWAS in human cell lines, which I did not incorporate into the table:
- 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.
And here a pGWAS conducted in mice:
- Chick et al., Defining the consequences of genetic variation on a proteome-wide scale, Nature, 2016.
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.
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