Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals

doi:10.1038/s42255-020-00287-2

. 2020 Oct;2(10):1135-1148.

doi: 10.1038/s42255-020-00287-2. Epub 2020 Oct 16.

Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals

Lasse Folkersen^#^{1

2

3}, Stefan Gustafsson^#^{3

4}, Qin Wang^#^{3

5

6}, Daniel Hvidberg Hansen^{3

7}, Åsa K Hedman^{1

3

8}, Andrew Schork^{3

9

10}, Karen Page^{3

11}, Daria V Zhernakova^{3

12}, Yang Wu^{3

13}, James Peters^{3

14

15

16}, Niclas Eriksson^{3

17}, Sarah E Bergen^{3

18}, Thibaud S Boutin^{3

19}, Andrew D Bretherick^{3

19}, Stefan Enroth^{3

20}, Anette Kalnapenkis^{3

21

22}, Jesper R Gådin^{1

3}, Bianca E Suur^{3

23}, Yan Chen^{1

3}, Ljubica Matic^{3

23}, Jeremy D Gale^{3

24}, Julie Lee^{3

11}, Weidong Zhang^{3

25}, Amira Quazi^{3

11}, Mika Ala-Korpela^{3

5

6

26}, Seung Hoan Choi^{3

27}, Annique Claringbould^{3

12}, John Danesh^{3

14

15

28

29

30

31}, George Davey Smith^{3

32}, Federico de Masi^{3

7}, Sölve Elmståhl^{3

33}, Gunnar Engström^{3

33}, Eric Fauman^{3

34}, Celine Fernandez^{3

33}, Lude Franke^{3

12}, Paul W Franks^{3

35}, Vilmantas Giedraitis^{3

36}, Chris Haley^{3

19}, Anders Hamsten^{1

3}, Andres Ingason^{3

9}, Åsa Johansson^{3

20}, Peter K Joshi^{3

37}, Lars Lind^{3

38}, Cecilia M Lindgren^{3

27

39

40}, Steven Lubitz^{3

27

41}, Tom Palmer^{3

42}, Erin Macdonald-Dunlop^{3

37}, Martin Magnusson^{3

43

44

45}, Olle Melander^{3

33}, Karl Michaelsson^{3

46}, Andrew P Morris^{3

40

47

48}, Reedik Mägi^{3

21}, Michael W Nagle^{3

34}, Peter M Nilsson^{3

33}, Jan Nilsson^{3

33}, Marju Orho-Melander^{3

49}, Ozren Polasek^{3

50}, Bram Prins^{3

14

15}, Erik Pålsson^{3

51}, Ting Qi^{3

13}, Marketa Sjögren^{3

33}, Johan Sundström^{3

52

53}, Praveen Surendran^{3

14

15

28

54}, Urmo Võsa^{3

21}, Thomas Werge^{3

9}, Rasmus Wernersson^{3

7}, Harm-Jan Westra^{3

12}, Jian Yang^{3

13

55

56}, Alexandra Zhernakova^{3

12}, Johan Ärnlöv^{3

57}, Jingyuan Fu^{3

12

58}, J Gustav Smith^{3

44

59}, Tõnu Esko^{3

21

27}, Caroline Hayward^{3

19}, Ulf Gyllensten^{3

20}, Mikael Landen^{3

51}, Agneta Siegbahn^{3

60}, James F Wilson^{3

19

37}, Lars Wallentin^{3

61}, Adam S Butterworth^{3

14

15

28

29

30}, Michael V Holmes^#^{3

62

63}, Erik Ingelsson^#^{3

64}, Anders Mälarstig^#^{65

66

67}

Affiliations

¹ Department of Medicine, Karolinska Institute, Solna, Sweden.
² Danish National Genome Center, Copenhagen, Denmark.
³ SCALLOP consortium.
⁴ Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
⁵ Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
⁶ Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.
⁷ Intomics A/S, Kgs. Lyngby, Denmark.
⁸ Pfizer Worldwide Research, Development and Medical, Cambridge, MA, USA.
⁹ Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Capital Region, Roskilde, Denmark.
¹⁰ Neurogenomics Division, The Translational Genomics Research Institute (TGEN), Phoenix, AZ, USA.
¹¹ Early Clinical Development, Pfizer Worldwide Research, Development and Medical, Cambridge, MA, USA.
¹² Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
¹³ Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
¹⁴ BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
¹⁵ Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
¹⁶ Department of Immunology and Inflammation, Faculty of Medicine, Imperial College London, London, UK.
¹⁷ Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden.
¹⁸ Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
¹⁹ MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, Scotland.
²⁰ Department of Immunology, Genetics, and Pathology, Biomedical Center, Science for Life Laboratory (SciLifeLab) Uppsala University, Uppsala, Sweden.
²¹ Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
²² Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia.
²³ Department of Molecular Medicine and Surgery, Karolinska Institute, Solna, Sweden.
²⁴ Inflammation and Immunology Research Unit, Pfizer Worldwide Research, Development and Medical, Cambridge, MA, USA.
²⁵ Pfizer Global Product Development, Cambridge, MA, USA.
²⁶ NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland.
²⁷ Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.
²⁸ British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK.
²⁹ National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK.
³⁰ National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK.
³¹ Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK.
³² MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
³³ Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden.
³⁴ Internal Medicine Research Unit, Pfizer Worldwide Research, Development and Medical, Cambridge, MA, USA.
³⁵ Department of Clinical Sciences, Lund University Diabetes Center, Malmö, Sweden.
³⁶ Department of Public Health and Caring Sciences/Geriatrics, Uppsala University, Uppsala, Sweden.
³⁷ Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.
³⁸ Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
³⁹ Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
⁴⁰ Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
⁴¹ Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
⁴² Department of Mathematics and Statistics, University of Lancaster, Lancaster, UK.
⁴³ Department of Cardiology, Skåne University Hospital Malmö, Malmö, Sweden.
⁴⁴ Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden.
⁴⁵ North-West University, Hypertension in Africa Research Team (HART), Potchefstroom, South Africa.
⁴⁶ Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
⁴⁷ Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, University of Manchester, Manchester, UK.
⁴⁸ Department of Biostatistics, University of Liverpool, Liverpool, UK.
⁴⁹ Department of Clinical Sciences, Clinical Research Center, Lund University, Malmö, Sweden.
⁵⁰ Faculty of Medicine, University of Split, Split, Croatia.
⁵¹ Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.
⁵² Department of Medical Sciences, Clinical Epidemiology, Uppsala University, Uppsala, Sweden.
⁵³ The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia.
⁵⁴ Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
⁵⁵ Institute for Advanced Research, Wenzhou Medical University, Wenzhou, China.
⁵⁶ School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China.
⁵⁷ Department of Neurobiology, Care Sciences and Society (NVS) Division of Family Medicine and Primary Care, Karolinska Institute, Solna, Sweden.
⁵⁸ Department of Paediatrics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
⁵⁹ Department of Cardiology, Clinical Sciences, Lund University and Skåne University Hospital, Lund, Sweden.
⁶⁰ Department of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden.
⁶¹ Department of Medical Sciences, Cardiology and Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden.
⁶² Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
⁶³ Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK.
⁶⁴ Department of Medicine, Division of Cardiovascular Medicine, Falk Cardiovascular Research Center, Stanford University School of Medicine, Stanford, CA, USA.
⁶⁵ Department of Medicine, Karolinska Institute, Solna, Sweden. anders.malarstig@ki.se.
⁶⁶ SCALLOP consortium, . anders.malarstig@ki.se.
⁶⁷ Emerging Science & Innovation, Pfizer Worldwide Research, Development and Medical, Cambridge, MA, USA. anders.malarstig@ki.se.

^# Contributed equally.

PMID: 33067605
PMCID: PMC7611474
DOI: 10.1038/s42255-020-00287-2

Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals

Lasse Folkersen et al. Nat Metab. 2020 Oct.

. 2020 Oct;2(10):1135-1148.

doi: 10.1038/s42255-020-00287-2. Epub 2020 Oct 16.

Authors

Affiliations

¹ Department of Medicine, Karolinska Institute, Solna, Sweden.
² Danish National Genome Center, Copenhagen, Denmark.
³ SCALLOP consortium.
⁴ Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden.
⁵ Systems Epidemiology, Baker Heart and Diabetes Institute, Melbourne, Victoria, Australia.
⁶ Computational Medicine, Faculty of Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland.
⁷ Intomics A/S, Kgs. Lyngby, Denmark.
⁸ Pfizer Worldwide Research, Development and Medical, Cambridge, MA, USA.
⁹ Institute of Biological Psychiatry, Mental Health Center Sct. Hans, Mental Health Services Capital Region, Roskilde, Denmark.
¹⁰ Neurogenomics Division, The Translational Genomics Research Institute (TGEN), Phoenix, AZ, USA.
¹¹ Early Clinical Development, Pfizer Worldwide Research, Development and Medical, Cambridge, MA, USA.
¹² Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
¹³ Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia.
¹⁴ BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
¹⁵ Health Data Research UK Cambridge, Wellcome Genome Campus and University of Cambridge, Cambridge, UK.
¹⁶ Department of Immunology and Inflammation, Faculty of Medicine, Imperial College London, London, UK.
¹⁷ Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden.
¹⁸ Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden.
¹⁹ MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, Scotland.
²⁰ Department of Immunology, Genetics, and Pathology, Biomedical Center, Science for Life Laboratory (SciLifeLab) Uppsala University, Uppsala, Sweden.
²¹ Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia.
²² Institute of Molecular and Cell Biology, University of Tartu, Tartu, Estonia.
²³ Department of Molecular Medicine and Surgery, Karolinska Institute, Solna, Sweden.
²⁴ Inflammation and Immunology Research Unit, Pfizer Worldwide Research, Development and Medical, Cambridge, MA, USA.
²⁵ Pfizer Global Product Development, Cambridge, MA, USA.
²⁶ NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio, Finland.
²⁷ Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.
²⁸ British Heart Foundation Centre of Research Excellence, University of Cambridge, Cambridge, UK.
²⁹ National Institute for Health Research Blood and Transplant Research Unit in Donor Health and Genomics, University of Cambridge, Cambridge, UK.
³⁰ National Institute for Health Research Cambridge Biomedical Research Centre, University of Cambridge and Cambridge University Hospitals, Cambridge, UK.
³¹ Department of Human Genetics, Wellcome Sanger Institute, Hinxton, UK.
³² MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
³³ Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden.
³⁴ Internal Medicine Research Unit, Pfizer Worldwide Research, Development and Medical, Cambridge, MA, USA.
³⁵ Department of Clinical Sciences, Lund University Diabetes Center, Malmö, Sweden.
³⁶ Department of Public Health and Caring Sciences/Geriatrics, Uppsala University, Uppsala, Sweden.
³⁷ Centre for Global Health Research, Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK.
³⁸ Department of Medical Sciences, Uppsala University, Uppsala, Sweden.
³⁹ Big Data Institute at the Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
⁴⁰ Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
⁴¹ Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, USA.
⁴² Department of Mathematics and Statistics, University of Lancaster, Lancaster, UK.
⁴³ Department of Cardiology, Skåne University Hospital Malmö, Malmö, Sweden.
⁴⁴ Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden.
⁴⁵ North-West University, Hypertension in Africa Research Team (HART), Potchefstroom, South Africa.
⁴⁶ Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
⁴⁷ Centre for Genetics and Genomics Versus Arthritis, Centre for Musculoskeletal Research, Division of Musculoskeletal and Dermatological Sciences, University of Manchester, Manchester, UK.
⁴⁸ Department of Biostatistics, University of Liverpool, Liverpool, UK.
⁴⁹ Department of Clinical Sciences, Clinical Research Center, Lund University, Malmö, Sweden.
⁵⁰ Faculty of Medicine, University of Split, Split, Croatia.
⁵¹ Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden.
⁵² Department of Medical Sciences, Clinical Epidemiology, Uppsala University, Uppsala, Sweden.
⁵³ The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia.
⁵⁴ Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
⁵⁵ Institute for Advanced Research, Wenzhou Medical University, Wenzhou, China.
⁵⁶ School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China.
⁵⁷ Department of Neurobiology, Care Sciences and Society (NVS) Division of Family Medicine and Primary Care, Karolinska Institute, Solna, Sweden.
⁵⁸ Department of Paediatrics, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
⁵⁹ Department of Cardiology, Clinical Sciences, Lund University and Skåne University Hospital, Lund, Sweden.
⁶⁰ Department of Medical Sciences, Clinical Chemistry, Uppsala University, Uppsala, Sweden.
⁶¹ Department of Medical Sciences, Cardiology and Uppsala Clinical Research Center, Uppsala University, Uppsala, Sweden.
⁶² Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
⁶³ Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK.
⁶⁴ Department of Medicine, Division of Cardiovascular Medicine, Falk Cardiovascular Research Center, Stanford University School of Medicine, Stanford, CA, USA.
⁶⁵ Department of Medicine, Karolinska Institute, Solna, Sweden. anders.malarstig@ki.se.
⁶⁶ SCALLOP consortium, . anders.malarstig@ki.se.
⁶⁷ Emerging Science & Innovation, Pfizer Worldwide Research, Development and Medical, Cambridge, MA, USA. anders.malarstig@ki.se.

^# Contributed equally.

PMID: 33067605
PMCID: PMC7611474
DOI: 10.1038/s42255-020-00287-2

Abstract

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health.

PubMed Disclaimer

Conflict of interest statement

Competing Interests Statement

The other authors declare no competing interests

Figures

**Figure 1. Chromosomal location of all associations discovered.**
Cis-pQTLs are shown in red (bold) and trans-pQTLs in blue if they are significant at a conventional GWAS significance threshold of P<5x10^-8. The gene annotations refer to the gene closest to the pQTL. A version of this figure with only loci selected according to the criteria for Mendelian randomization is available as [Extended figure 1].

**Figure 2. Classification of cis- and trans-pQTL genes.**
A. The gene ontology label of all cis-pQTL genes, i.e. the protein-encoding genes. B. The gene-ontology label of all best-guess trans-pQTL genes. C. Gene set enrichment analysis of genes assigned to all significant trans-pQTLs, showing the top-gene sets from the Gene Ontology set Molecular Function.

**Figure 3. Clinical trial in humans and knock down experiment in mice corresponds to trans pQTL effects.**
A) In humans treated with a small molecule dual-inhibitor of CCR5 and CCR2 (PF-04634817) the induction of MCP-1 and CCL4, mirrors the observed CVD-I trans-pQTLs. Box plots elements are according to standards for box-and-whisker diagrams. B) In mice, knockdown of ABCA1 or TRIB1 resulted in decreased circulating SCF levels mirroring CVD-I trans-pQTLs for SCF. Shown in the plot are SCF levels of individual mice represented by circles (wild-type in blue and transgenic mice in red) and the median level per group. P-value is calculated using a two-sided T-test.

**Figure 4. Main findings of Mendelian randomization analysis.**
A. Heatmap of Mendelian randomization analyses of 38 complex traits. ICD-10 chapter of indication and clinical trial stage indicated for each target B. Forest plot showing CVD-I proteins with strong evidence of causality in the Mendelian randomization analysis. Drug development abbreviations: PC: pre-clinical, Ph1: Phase 1, Ph2: Phase 2, Ph3: Phase 3, post-MA: post-marketing authorisation. ICD-10 chapters of disease: A-B: infectious and parasitic; C-D: neoplasms; D: blood and immune; E: endocrine, nutritional and metabolic; F: mental and behavioural; G: nervous system; H: eye, adnexa, ear and mastoid; I: circulatory system; J: respiratory system; K: digestive system; L: skin and subcutaneous tissue; M: musculoskeletal and connective tissue; N: genitourinary; O: pregnancy, childbirth, puerperium; P: perinatal; Q: congenital, deformations and chromosomal; R: clinical and lab findings; S-T: injury, poisoning; U: provisional assignment (new diseases unknown aetiology); V-Y: external causes; Z: health status & health services

**Figure 5. SNP heritability and variance explained by genetics.**
A. SNP-Heritability in the SCALLOP consortium discovery cohorts stratified by contributions major loci (light red) and polygenic effects (dark red). In the independent MDC cohort, additional variability explained by adding major loci (light blue) and polygenic risk scores (dark blue). Significance was reported according to the LDSC algorithm (blue) or a linear regression model (red). B. Differences in how protein levels are affected by polygenic (non-genome-wide significant) loci vs major loci, shown for both the SCALLOP consortium discovery cohorts as h_SNP² and for the MDC cohort as variability explained.

**Figure 6. Mendelian randomization using polygenic risk scores.**
A. Association of a polygenic risk score (PRS) with ST2 levels in the independent MDC cohort. B. Association of the ST2 PRS with asthma in the UK-biobank. B. Association of the ST2 PRS with inflammatory bowel disease (IBD) in the UK-biobank. The ST2 PRS was divided into 11 quantiles, with the middle group (quantile number 6) as the reference category. Effect estimates are presented as quantile-specific mean differences (ST2) and odds ratios (asthma and IBD) relative to the reference category.

**Figure 7. Mendelian randomization with proteins as outcome.**
A. Heatmap showing the causal estimates of 38 complex traits on CVD-I protein levels. B. Correlation between beta-values for association between body mass index and circulating levels of CVD-I proteins in the IMPROVE cohort, and causal estimates from the Mendelian randomization analysis of body mass index genetic liability on same CVD-I proteins. C. Same as B but for estimated glomerular filtration rate.

**Figure 8. Protein-trait relationships that support target validation, repositioning, target-mediated safety and new candidates for drug development.**
For more information, see data presented in [Supplementary Table 7].

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References

1. Chames P, Van Regenmortel M, Weiss E, Baty D. Therapeutic antibodies: successes, limitations and hopes for the future. Br J Pharmacol. 2009;157:220–233. - PMC - PubMed
1. Holmes MV, Ala-Korpela M, Smith GD. Mendelian randomization in cardiometabolic disease: challenges in evaluating causality. Nat Rev Cardiol. 2017;14:577–590. - PMC - PubMed
1. Folkersen L, et al. Mapping of 79 loci for 83 plasma protein biomarkers in cardiovascular disease. PLoS Genet. 2017;13:e1006706. - PMC - PubMed
1. Sun BB, et al. Genomic atlas of the human plasma proteome. Nature. 2018;558:73–79. - PMC - PubMed
1. Williams SA, et al. Plasma protein patterns as comprehensive indicators of health. Nat Med. 2019;25:1851–1857. - PMC - PubMed

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[1] Chames P, Van Regenmortel M, Weiss E, Baty D. Therapeutic antibodies: successes, limitations and hopes for the future. Br J Pharmacol. 2009;157:220–233. - PMC - PubMed

[2] Chames P, Van Regenmortel M, Weiss E, Baty D. Therapeutic antibodies: successes, limitations and hopes for the future. Br J Pharmacol. 2009;157:220–233. - PMC - PubMed

[3] Holmes MV, Ala-Korpela M, Smith GD. Mendelian randomization in cardiometabolic disease: challenges in evaluating causality. Nat Rev Cardiol. 2017;14:577–590. - PMC - PubMed

[4] Holmes MV, Ala-Korpela M, Smith GD. Mendelian randomization in cardiometabolic disease: challenges in evaluating causality. Nat Rev Cardiol. 2017;14:577–590. - PMC - PubMed

[5] Folkersen L, et al. Mapping of 79 loci for 83 plasma protein biomarkers in cardiovascular disease. PLoS Genet. 2017;13:e1006706. - PMC - PubMed

[6] Folkersen L, et al. Mapping of 79 loci for 83 plasma protein biomarkers in cardiovascular disease. PLoS Genet. 2017;13:e1006706. - PMC - PubMed

[7] Sun BB, et al. Genomic atlas of the human plasma proteome. Nature. 2018;558:73–79. - PMC - PubMed

[8] Sun BB, et al. Genomic atlas of the human plasma proteome. Nature. 2018;558:73–79. - PMC - PubMed

[9] Williams SA, et al. Plasma protein patterns as comprehensive indicators of health. Nat Med. 2019;25:1851–1857. - PMC - PubMed

[10] Williams SA, et al. Plasma protein patterns as comprehensive indicators of health. Nat Med. 2019;25:1851–1857. - PMC - PubMed

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Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals

Affiliations

Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals

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