Contribution of rare whole-genome sequencing variants to plasma protein levels and the missing heritability
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Abstract
Despite the success of genome-wide association studies, much of the genetic contribution to complex traits remains unexplained. Here, we analyse high coverage whole-genome sequencing data, to evaluate the contribution of rare genetic variants to 414 plasma proteins. The frequency distribution of genetic variants is skewed towards the rare spectrum, and damaging variants are more often rare. We estimate that less than 4.3% of the narrow-sense heritability is expected to be explained by rare variants in our cohort. Using a gene-based approach, we identify Cis -associations for 237 of the proteins, which is slightly more compared to a GWAS ( N = 213), and we identify 34 associated loci in Trans . Several associations are driven by rare variants, which have larger effects, on average. We therefore conclude that rare variants could be of importance for precision medicine applications, but have a more limited contribution to the missing heritability of complex diseases.
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Kierczak et al. detected cis-region rare variant associations for four proteins (CTSZ, CYR61, GDF-15 and PON3) and trans associations of rare GAL3ST2 variants affecting the MUC16 level.
“Kierczak et al.13 detected cis-region rare variant associations for four proteins (CTSZ, CYR61, GDF-15 and PON3) and trans associations of rare GAL3ST2 variants affecting the MUC16 level”
From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [13]
The Discussion (page unavailable) identifies rare variants as likely contributors to a CTSZ association, supporting that part of the claim. The retrieved passages do not establish the claimed cis associations for CYR61, GDF-15, or PON3. The Results section on rare-variant trans associations (page unavailable) lists six proteins with significant associations, none of them MUC16, and does not identify GAL3ST2. (LLM, conf=0.86)
Experimental — accuracy not yet measuredKierczak et al. used a maximum MAF threshold 0.0239, whereas we used a standard conservative threshold of 0.01.
“they used a maximum MAF threshold 0.0239, whereas we used a standard conservative threshold of 0.01.”
From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [13]
The Results (SKAT analyses) and Methods (Statistical analyses) state that 0.0239 was the cutoff between rare and common variants in the CommonRare analyses. It was not a maximum MAF for the study overall: the Methods say the primary SKAT analyses included all variants passing quality control, regardless of MAF. The citing authors’ own 0.01 threshold is not a claim about Kierczak et al. (LLM, conf=0.84)
Experimental — accuracy not yet measuredThe influence of rare variants on the plasma proteome is largely unknown because previous rare variant proteogenomic studies have been limited in scale.
“However, their influence on the plasma proteome is largely unknown because previous rare variant proteogenomic studies have been limited in scale9,10.”
From Rare variant associations with plasma protein levels in the UK Biobank (2023) · cites this paper as [9]
Gene-based pQTL analyses of rare variants constitute an emerging approach.
“Gene-based pQTL analyses of rare variants constitute an emerging approach10–13”
From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [13]
Previous studies indicate that few proteins are driven by rare variants.
“Previous studies indicate that few proteins are driven by rare variants11–13.”
From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [13]
The effect of rare GAL3ST2 variants on MUC16 level was also detected in our study.
“the effect also detected in our study”
From Genetic determinants of plasma protein levels in the Estonian population (2024) · cites this paper as [13]
The Results section discusses rare-variant associations with plasma protein levels, but the passages retrieved for “GAL3ST2,” “MUC16,” and their combination do not mention either gene–protein association. Our copy therefore does not verify the attributed effect; this is not evidence that the paper contradicts it. No page numbers were available for the indexed passages. (LLM, conf=0.72)
Experimental — accuracy not yet measured
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Cites
The variant call format and VCFtools
Danecek, P., Auton, A., Abecasis, G. R., Albers, C. A., Banks, E., DePristo, M. A., Handsaker, R. E., Lunter, G. A., Marth, G., Sherry, S. T., et al. (2011) · Bioinformatics · doi:10.1093/bioinformatics/btr330 · Cited by 16,008 · see citing works
The mutational constraint spectrum quantified from variation in 141,456 humans
Karczewski, K. J., Francioli, L. C., Tiao, G., Cummings, B. B., Alföldi, J., Wang, Q., Collins, R. L., Laricchia, K. M., Ganna, A., Birnbaum, D. P., et al. (2020) · Nature · doi:10.1038/s41586-020-2308-7 · Cited by 9,434 · see citing works
A general framework for estimating the relative pathogenicity of human genetic variants
Kircher, M., Witten, D. M., Jain, P., O'Roak, B. J., Cooper, G. M., & Shendure, J. (2014) · Nature Genetics · doi:10.1038/ng.2892 · Cited by 6,183 · see citing works
Genetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534 · see citing works
Rare-Variant Association Testing for Sequencing Data with the Sequence Kernel Association Test
Wu, M. C., Lee, S., Cai, T., Li, Y., Boehnke, M., & Lin, X. (2011) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2011.05.029 · Cited by 2,317 · see citing works
Yengo, L., Sidorenko, J., Kemper, K. E., Zheng, Z., Wood, A. R., Weedon, M. N., Frayling, T. M., Hirschhorn, J. N., Yang, J., & Visscher, P. M. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy271 · Cited by 2,305 · see citing works
Clinical Spectrum of Obesity and Mutations in the Melanocortin 4 Receptor Gene
Farooqi, I. S., Keogh, J. M., Yeo, G. S. H., Lank, E. J., Cheetham, T., & O'Rahilly, S. (2003) · New England Journal of Medicine · doi:10.1056/nejmoa022050 · Cited by 1,778 · see citing works
Li, B., & Leal, S. M. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2008.06.024 · Cited by 1,527 · see citing works
A Groupwise Association Test for Rare Mutations Using a Weighted Sum Statistic
Madsen, B. E., & Browning, S. R. (2009) · PLoS Genetics · doi:10.1371/journal.pgen.1000384 · Cited by 1,113 · see citing works
Lee, S., Emond, M. J., Bamshad, M. J., Barnes, K. C., Rieder, M. J., Nickerson, D. A., Christiani, D. C., Wurfel, M. M., & Lin, X. (2012) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2012.06.007 · Cited by 1,040 · see citing works
Exome sequencing and analysis of 454,787 UK Biobank participants
Backman, J., Li, A. H., Marcketta, A., Sun, D., Mbatchou, J. S., Kessler, M. D., Benner, C., Liu, D., Locke, A. E., Balasubramanian, S., et al. (2021) · Nature · doi:10.1038/s41586-021-04103-z · Cited by 915 · see citing works
Toward better understanding of artifacts in variant calling from high-coverage samples
Li, H. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu356 · Cited by 896 · see citing works
Genetics of 35 blood and urine biomarkers in the UK Biobank
Sinnott-Armstrong, N., Tanigawa, Y., Amar, D., Mars, N., Benner, C., Aguirre, M., Venkataraman, G. R., Wainberg, M., Ollila, H. M., Kiiskinen, T., et al. (2021) · Nature Genetics · doi:10.1038/s41588-020-00757-z · Cited by 744 · see citing works
Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals
Folkersen, L., Gustafsson, S., Wang, Q., Hansen, D. H., Hedman, Å. K., Schork, A., Page, K., Zhernakova, D. V., Wu, Y., Peters, J., et al. (2020) · Nature Metabolism · doi:10.1038/s42255-020-00287-2 · Cited by 705 · see citing works
Self-citationRare variant contribution to human disease in 281,104 UK Biobank exomes
Wang, Q., Dhindsa, R. S., Carss, K., Harper, A. R., Nag, A., Tachmazidou, I., Vitsios, D., Deevi, S. V. V., Mackay, A., Muthas, D., et al. (2021) · Nature · doi:10.1038/s41586-021-03855-y · Cited by 604 · see citing works
A spectral approach integrating functional genomic annotations for coding and noncoding variants
Ionita‐Laza, I., McCallum, K., Xu, B., & Buxbaum, J. D. (2016) · Nature Genetics · doi:10.1038/ng.3477 · Cited by 588 · see citing works
Exome sequencing and characterization of 49,960 individuals in the UK Biobank
Van Hout, C. V., Tachmazidou, I., Backman, J. D., Hoffman, J. D., Liu, D., Pandey, A. K., Gonzaga-Jauregui, C., Khalid, S., Ye, B., Banerjee, N., et al. (2020) · Nature · doi:10.1038/s41586-020-2853-0 · Cited by 561 · see citing works
Morgenthaler, S., & Thilly, W. G. (2007) · Mutation Research - Fundamental and Molecular Mechanisms of Mutagenesis · doi:10.1016/j.mrfmmm.2006.09.003 · Cited by 507 · cited 1× · see citing works
“5), model (6) CommonRare, model (7) Rare only, model.”
Sequence Kernel Association Tests for the Combined Effect of Rare and Common Variants
Ionita-Laza, I., Lee, S., Makarov, V., Buxbaum, J. D., & Lin, X. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.04.015 · Cited by 433 · see citing works
Zerbino, D. R., Wilder, S. P., Johnson, N., Juettemann, T., & Flicek, P. R. (2015) · Genome Biology · doi:10.1186/s13059-015-0621-5 · Cited by 429 · see citing works
ABO(H) blood groups and vascular disease: a systematic review and meta‐analysis
Wu, O., Bayoumi, N., Vickers, M. A., & Clark, P. (2008) · Journal of Thrombosis and Haemostasis · doi:10.1111/j.1538-7836.2007.02818.x · Cited by 425 · see citing works
Karlsson, T., Rask‐Andersen, M., Pan, G., Höglund, J., Wadelius, C., Ek, W. E., & Johansson, Å. (2019) · Nature Medicine · doi:10.1038/s41591-019-0563-7 · Cited by 318 · see citing works
Self-citationAkbari, P., Gilani, A., Sosina, O., Kosmicki, J. A., Khrimian, L., Fang, Y.-Y., Persaud, T., Garcia, V., Sun, D., Li, A., et al. (2021) · Science · doi:10.1126/science.abf8683 · Cited by 276 · see citing works
A general framework for estimating the relative pathogenicity of human genetic variants
Kircher, M., Witten, D., Cooper, G. M., & Shendure, J. (2014) · F1000Research · doi:10.7490/f1000research.1095265.1 · Cited by 234 · see citing works
Ameur, A., Dahlberg, J., Olason, P. I., Vezzi, F., Karlsson, R., Martin, M., Viklund, J., Kähäri, A., Lundin, P., Che, H., et al. (2017) · European Journal of Human Genetics · doi:10.1038/ejhg.2017.130 · Cited by 203 · see citing works
Self-citationEnroth, S., Johansson, Å., Enroth, S. B., & Gyllensten, U. B. (2014) · Nature Communications · doi:10.1038/ncomms5684 · Cited by 176 · see citing works
Self-citationABO Research in the Modern Era of Genomics
Yamamoto, F., Cid, E., Yamamoto, M., & Blancher, A. (2011) · Transfusion Medicine Reviews · doi:10.1016/j.tmrv.2011.08.002 · Cited by 171 · see citing works
Jurgens, S. J., Choi, S. H., Morrill, V. N., Chaffin, M. D., Pirruccello, J. P., Halford, J. L., Weng, L.-C. C., Nauffal, V., Roselli, C., Hall, A. W., et al. (2022) · Nature Genetics · doi:10.1038/s41588-021-01011-w · Cited by 158 · see citing works
Genome-wide rare variant analysis for thousands of phenotypes in over 70,000 exomes from two cohorts
Cirulli, E. T., White, S., Read, R. W., Elhanan, G., Metcalf, W. J., Tanudjaja, F., Fath, D. M., Sandoval, E., Isaksson, M., Schlauch, K. A., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-14288-y · Cited by 135 · see citing works
Ganna, A., Genovese, G., Howrigan, D. P., Byrnes, A., Kurki, M., Zekavat, S. M., Whelan, C. W., Kals, M., Nivard, M. G., Bloemendal, A., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4404 · Cited by 89 · see citing works
Hillary, R. F., McCartney, D. L., Harris, S. E., Stevenson, A. J., Seeboth, A., Zhang, Q., Liewald, D. C., Evans, K. L., Ritchie, C. W., Tucker-Drob, E. M., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11177-x · Cited by 78 · see citing works
Phylogeography of the Bitter Apple, Citrullus Colocynthis
Dane, F., Liu, J., & Zhang, C. (2006) · Genetic Resources and Crop Evolution · doi:10.1007/s10722-005-4897-2 · Cited by 77 · see citing works
Ahsan, M., Ek, W. E., Rask‐Andersen, M., Karlsson, T., Lind-Thomsen, A., Enroth, S., Gyllensten, U., & Johansson, Å. (2017) · PLoS Genetics · doi:10.1371/journal.pgen.1007005 · Cited by 73 · see citing works
Self-citationHöglund, J., Rafati, N., Rask‐Andersen, M., Enroth, S., Karlsson, T., Ek, W. E., & Johansson, Å. (2019) · Scientific Reports · doi:10.1038/s41598-019-53111-7 · Cited by 53 · see citing works
Self-citationEnroth, S., Maturi, V., Berggrund, M., Enroth, S. B., Moustakas, A., Johansson, Å., & Gyllensten, U. (2018) · Scientific Reports · doi:10.1038/s41598-018-23860-y · Cited by 43 · see citing works
Self-citationIgl, W., Johansson, Å., & Gyllensten, U. B. (2010) · Rural and Remote Health · doi:10.22605/rrh1363 · Cited by 41 · see citing works
Self-citationCohort-wide deep whole genome sequencing and the allelic architecture of complex traits
Gilly, A., Süveges, D., Kuchenbaecker, K. B., Pollard, M., Southam, L., Hatzikotoulas, K., Farmaki, A., Bjørnland, T., Waples, R. K., Appel, E. V. R., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-07070-8 · Cited by 30 · see citing works
Höglund, J., Karlsson, T., Johansson, T., Ek, W. E., & Johansson, Å. (2021) · American Journal of Hematology · doi:10.1002/ajh.26307 · Cited by 27 · see citing works
Self-citationEnroth, S., Enroth, S. B., Johansson, Å., & Gyllensten, U. B. (2015) · Biomarkers · doi:10.3109/1354750x.2015.1093546 · Cited by 19 · see citing works
Self-citationThe influence of rare variants in circulating metabolic biomarkers
Riveros-Mckay, F., Oliver‐Williams, C., Karthikeyan, S., Walter, K., Kundu, K., Ouwehand, W. H., Roberts, D. J., Angelantonio, E. D., Soranzo, N., Danesh, J., et al. (2020) · PLoS Genetics · doi:10.1371/journal.pgen.1008605 · Cited by 19 · see citing works
Cohort-wide deep whole genome sequencing and the allelic architecture of complex traitsPreprint
Gilly, A., Süveges, D., Kuchenbaecker, K. B., Pollard, M., Southam, L., Hatzikotoulas, K., Farmaki, A., Bjørnland, T., Waples, R. K., Appel, E. V. R., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/283481 · Cited by 4 · see citing works
Figure1_Variances_Heritability.R
Johansson, Å. (2022) · Zenodo (CERN European Organization for Nuclear Research) · doi:10.5281/zenodo.6380151 · Cited by 1 · see citing works
Self-citation
Flagged first, then by citations
1 of the 43 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- [15]Dane, F., Liu, J. & Zhang, C. TCS: A Computer Program to Estimate Gene Genealogies. Genetic Resources and Crop Evolution. Vol. 54 (Cambridge University Press, 2007).
Cited by
Sorted by citations
Rare variant associations with plasma protein levels in the UK Biobank
Dhindsa, R. S., Burren, O. S., Sun, B. B., Prins, B. P., Matelska, D., Wheeler, E., Mitchell, J., Oerton, E., Hristova, V. A., Smith, K. R., et al. (2023) · Nature · doi:10.1038/s41586-023-06547-x · Cited by 193 · see citing works
An atlas of genetic scores to predict multi-omic traits
Xu, Y., Ritchie, S. C., Liang, Y., Timmers, P. R. H. J., Pietzner, M., Lannelongue, L., Lambert, S. A., Tahir, U. A., May-Wilson, S., Foguet, C., et al. (2023) · Nature · doi:10.1038/s41586-023-05844-9 · Cited by 143 · see citing works
Self-citationJohansson, Å., Andreassen, O. A., Brunak, S., Franks, P. W., Hedman, H., Loos, R. J. F., Meder, B., Melén, E., Wheelock, C. E., & Jacobsson, B. (2023) · Journal of Internal Medicine · doi:10.1111/joim.13640 · Cited by 98 · see citing works
Self-citationAlemu, R. G., Sharew, N. T., Arsano, Y. Y., Ahmed, M. B., Ayele, F. T., Baye, T. M., & Amare, A. T. (2025) · Human Genomics · doi:10.1186/s40246-025-00718-9 · Cited by 94 · see citing works
The complete and fully-phased diploid genome of a male Han Chinese
Yang, C., Zhou, Y., Song, Y., Wu, D., Zeng, Y., Nie, L., Liu, P., Zhang, S., Chen, G., Xu, J., et al. (2023) · Cell Research · doi:10.1038/s41422-023-00849-5 · Cited by 81 · see citing works
Xiang, R., Fang, L., Liu, S., MacLeod, I. M., Liu, Z., Breen, E. J., Gao, Y., Liu, G. E., Tenesa, A., Mason, B., et al. (2023) · Cell Genomics · doi:10.1016/j.xgen.2023.100385 · Cited by 59 · see citing works
Common host variation drives malaria parasite fitness in healthy human red cells
Ebel, E. R., Kuypers, F. A., Lin, C., Petrov, D. A., & Egan, E. S. (2021) · eLife · doi:10.7554/elife.69808 · Cited by 26 · see citing works
Unravelling the genetic architecture of human complex traits through whole genome sequencing
Bocher, O., Willer, C. J., & Zeggini, E. (2023) · Nature Communications · doi:10.1038/s41467-023-39259-x · Cited by 18 · see citing works
Functional evaluation of rare OASL variants by analysis of SLE patient-derived iPSCs
Natsumoto, B., Shoda, H., Nagafuchi, Y., Ota, M., Okumura, T., Horie, Y., Okamura, T., Yamamoto, K., Tsuji, M., Otsu, M., et al. (2023) · Journal of Autoimmunity · doi:10.1016/j.jaut.2023.103085 · Cited by 13 · see citing works
Genetic determinants of plasma protein levels in the Estonian population
Kalnapenkis, A., Jõeloo, M., Lepik, K., Kukuškina, V., Kals, M., Alasoo, K., Estonian Biobank Research Team, Metspalu, A., Milani, L., Nelis, M., et al. (2024) · Scientific Reports · doi:10.1038/s41598-024-57966-3 · Cited by 11 · see citing works
GWAS advancements to investigate disease associations and biological mechanisms
Omidiran, O., Patel, A., Usman, S., Mhatre, I., Abdelhalim, H., DeGroat, W., Narayanan, R., Singh, K., Mendhe, D., & Ahmed, Z. (2024) · Clinical and Translational Discovery · doi:10.1002/ctd2.296 · Cited by 11 · see citing works
Application of Genomic Data in Translational Medicine During the Big Data Era
Zhang, Y., Yu, J. M., Xie, X., Jiang, F., & Wu, C. (2024) · Frontiers in Bioscience-Landmark · doi:10.31083/j.fbl2901007 · Cited by 10 · see citing works
Parsons, B. L., Beal, M. A., Dearfield, K. L., Douglas, G. R., Gi, M., Gollapudi, B. B., Heflich, R. H., Horibata, K., Kenyon, M., Long, A. S., et al. (2024) · Environmental and Molecular Mutagenesis · doi:10.1002/em.22599 · Cited by 8 · see citing works
Stinson, S. E., Balboa, R. F., Andersen, M. K., Stæger, F. F., He, S., Thuesen, A. C. B., Lin, L., Jørsboe, E., Bjerregaard, P., Larsen, C. V. L., et al. (2025) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2025.10.013 · Cited by 8 · see citing works
Venous thromboembolic disease genetics: from variants to function
Underwood, M. I., Bidlack, C., & Desch, K. C. (2024) · Journal of Thrombosis and Haemostasis · doi:10.1016/j.jtha.2024.06.004 · Cited by 7 · see citing works
Genetic and epigenetic drivers of neurodegenerative disorders
Roy, K., Syed, M., Narad, P., & Sengupta, A. (2025) · Progress in brain research · doi:10.1016/bs.pbr.2025.08.002 · Cited by 5 · see citing works
Pestoff, R. (2023) · Linköping University medical dissertations · doi:10.3384/9789179295943 · Cited by 3 · see citing works
Copy number variations and their effect on the plasma proteome
Schmitz, D., Li, Z., Faro, V. L., Rask‐Andersen, M., Ameur, A., Rafati, N., & Johansson, Å. (2023) · Genetics · doi:10.1093/genetics/iyad179 · Cited by 2 · see citing works
Self-citationProteogenomics in human populations.
Zhai, R.-R., Mälarstig, A., & Shen, X. (2026) · Nature reviews genetics · doi:10.1038/s41576-026-00998-4 · Cited by 1 · see citing works
Elnour, A. A. M. (2025) · Springer eBooks · doi:10.1007/978-981-97-8518-6_5 · Cited by 1 · see citing works
A modeling of complex trait phenotypic variance determinants
Hussain, S. (2024) · PNAS Nexus · doi:10.1093/pnasnexus/pgae472
Jung, H., Jung, H., Kang, J., Lim, J. H., & Oh, B. (2026) · Genome biology · doi:10.1186/s13059-026-04140-9
- Authors
- Kierczak, M., Rafati, N., Höglund, J., Gourlé, H., Lo Faro, V., Schmitz, D., Ek, W. E., Gyllensten, U., Enroth, S., Ekman, D., Nystedt, B., Karlsson, T., & Johansson, Å.
- Affiliations
- Uppsala University (SE)
- Stockholm University (SE)
- Corresponding author
- Johansson, Åsa
- ORCID
- Venue
- Nature Communications
- Published
- 2022-05-09
- Volume
- 13
- Issue
- 1
- Pages
- 2532-2532
- ISSN
- 2041-1723 (ISSN-L)
- PMC
- PMC9085767
- OpenAlex
- W4229379051
- Cited by
- 22
- References
- 43
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 6 · 2023: 9 · 2021: 1
- FWCI
- 2.87
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Nature Communications (publishedVersion, cc-by)
- Research Square (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Uppsala University Publications (Uppsala University) (submittedVersion, other-oa)
- RePEc: Research Papers in Economics (submittedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Funders
- Vetenskapsrådet (2018-05973)
- Hjärt-Lungfonden (20200687)
- Science for Life Laboratory
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Keywords
- rare variants, plasma proteins, missing heritability, narrow-sense heritability, gene-based association, complex traits, precision medicine
- MeSH terms
- Whole Genome Sequencing, Blood Proteins, Humans, Genetic Variation, Genetic Predisposition to Disease, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Genome-Wide Association Study
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