Abstract
Growth differentiation factor 15 (GDF15) is a secreted protein that regulates food intake, body weight and stress responses in pre-clinical models1. The physiological function of GDF15 in humans remains unclear. Pharmacologically, GDF15 agonism in humans causes nausea without accompanying weight loss2, and GDF15 antagonism is being tested in clinical trials to treat cachexia and anorexia. Human genetics point to a role for GDF15 in hyperemesis gravidarum, but the safety or impact of complete GDF15 loss, particularly during pregnancy, is unknown3,4,5,6,7. Here we show the absence of an overt phenotype in human GDF15 loss-of-function carriers, including stop gains, frameshifts and the fully inactivating missense variant C211G3. These individuals were identified from 75,018 whole-exome/genome-sequenced participants in the Pakistan Genomic Resource8,9 and recall-by-genotype studies with family-based recruitment of variant carrier probands. We describe 8 homozygous (‘knockouts’) and 227 heterozygous carriers of loss-of-function alleles, including C211G. GDF15 knockouts range in age from 31 to 75 years, are fertile, have multiple children and show no consistent overt phenotypes, including metabolic dysfunction. Our data support the hypothesis that GDF15 is not required for fertility, healthy pregnancy, foetal development or survival into adulthood. These observations support the safety of therapeutics that block GDF15.
This is a preview of subscription content, access via your institution
Access options
Access Nature and 54 other Nature Portfolio journals
Get Nature+, our best-value online-access subscription
$32.99 / 30 days
cancel any time
Subscribe to this journal
Receive 12 digital issues and online access to articles
$119.00 per year
only $9.92 per issue
Buy this article
- Purchase on SpringerLink
- Instant access to full article PDF
Prices may be subject to local taxes which are calculated during checkout
Similar content being viewed by others
Data availability
All academic requests to access relevant CNCD data or samples should be sent to ks76@cncdpk.com. CNCD will ask relevant investigators to sign a data confidentiality agreement, which would require investigators to maintain de-identification of study participants. All summary statistics generated as part of this study are provided within the paper. The UKB WES data can be analysed through the DNAnexus Research Analysis Portal after obtaining access through UKB (https://biobank.ndph.ox.ac.uk/).
References
Tsai, V. W. W., Husaini, Y., Sainsbury, A., Brown, D. A. & Breit, S. N. The MIC-1/GDF15-GFRAL pathway in energy homeostasis: implications for obesity, cachexia, and other associated diseases. Cell Metab. 28, 353–368 (2018).
Benichou, O. et al. Discovery, development, and clinical proof of mechanism of LY3463251, a long-acting GDF15 receptor agonist. Cell Metab. 35, 274–286 e210 (2023).
Fejzo, M. et al. GDF15 linked to maternal risk of nausea and vomiting during pregnancy. Nature https://doi.org/10.1038/s41586-023-06921-9 (2023).
Fejzo, M. S., Arzy, D., Tian, R., MacGibbon, K. W. & Mullin, P. M. Evidence GDF15 plays a role in familial and recurrent hyperemesis gravidarum. Geburtshilfe Frauenheilkd. 78, 866–870 (2018).
Fejzo, M. S. et al. Analysis of GDF15 and IGFBP7 in hyperemesis gravidarum support causality. Geburtshilfe Frauenheilkd. 79, 382–388 (2019).
Fejzo, M. S., MacGibbon, K. W., First, O., Quan, C. & Mullin, P. M. Whole-exome sequencing uncovers new variants in GDF15 associated with hyperemesis gravidarum. BJOG 129, 1845–1852 (2022).
Fejzo, M. S. et al. Placenta and appetite genes GDF15 and IGFBP7 are associated with hyperemesis gravidarum. Nat. Commun. 9, 1178 (2018).
Saleheen, D. et al. Human knockouts and phenotypic analysis in a cohort with a high rate of consanguinity. Nature 544, 235–239 (2017).
Saleheen, D. et al. The Pakistan Risk of Myocardial Infarction Study: a resource for the study of genetic, lifestyle and other determinants of myocardial infarction in South Asia. Eur. J. Epidemiol. 24, 329–338 (2009).
Jastreboff, A. M. et al. Tirzepatide once weekly for the treatment of obesity. N. Engl. J. Med. 387, 205–216 (2022).
Watanabe, H. & Oshima, T. The latest treatments for cancer cachexia: an overview. Anticancer Res. 43, 511–521 (2023).
Mullican, S. E. et al. GFRAL is the receptor for GDF15 and the ligand promotes weight loss in mice and nonhuman primates. Nat. Med. 23, 1150–1157 (2017).
Emmerson, P. J. et al. The metabolic effects of GDF15 are mediated by the orphan receptor GFRAL. Nat. Med. 23, 1215–1219 (2017).
Hsu, J. Y. et al. Non-homeostatic body weight regulation through a brainstem-restricted receptor for GDF15. Nature 550, 255–259 (2017).
Tsai, V. W. et al. TGF-b superfamily cytokine MIC-1/GDF15 is a physiological appetite and body weight regulator. PLoS One 8, e55174 (2013).
Johnen, H. et al. Tumor-induced anorexia and weight loss are mediated by the TGF-beta superfamily cytokine MIC-1. Nat. Med. 13, 1333–1340 (2007).
Macia, L. et al. Macrophage inhibitory cytokine 1 (MIC-1/GDF15) decreases food intake, body weight and improves glucose tolerance in mice on normal & obesogenic diets. PLoS ONE 7, e34868 (2012).
Chrysovergis, K. et al. NAG-1/GDF-15 prevents obesity by increasing thermogenesis, lipolysis and oxidative metabolism. Int J. Obes. 38, 1555–1564 (2014).
Coll, A. P. et al. GDF15 mediates the effects of metformin on body weight and energy balance. Nature 578, 444–448 (2020).
Patel, S. et al. GDF15 provides an endocrine signal of nutritional stress in mice and humans. Cell Metab. 29, 707–718 e708 (2019).
Breit, S. N., Brown, D. A. & Tsai, V. W. W. GDF15 analogs as obesity therapeutics. Cell Metab. 35, 227–228 (2023).
Breit, S. N., Brown, D. A. & Tsai, V. W. The GDF15-GFRAL pathway in health and metabolic disease: friend or foe? Annu Rev. Physiol. 83, 127–151 (2021).
Wiklund, F. E. et al. Macrophage inhibitory cytokine-1 (MIC-1/GDF15): a new marker of all-cause mortality. Aging Cell 9, 1057–1064 (2010).
Karusheva, Y. et al. The common H202D variant in GDF-15 does not affect its bioactivity but can significantly interfere with measurement of its circulating levels. J. Appl. Lab Med. 7, 1388–1400 (2022).
Graves, J. M. et al. Fibroblast growth factor 23 (FGF23) induces ventricular arrhythmias and prolongs QTc interval in mice in an FGF receptor 4-dependent manner. Am. J. Physiol. Heart Circ. Physiol. 320, H2283–H2294 (2021).
Welsh, P. et al. Reference ranges for GDF-15, and risk factors associated with GDF-15, in a large general population cohort. Clin. Chem. Lab. Med. 60, 1820–1829 (2022).
Crawford, J. et al. A phase Ib first-in-patient study assessing the safety, tolerability, pharmacokinetics, and pharmacodynamics of ponsegromab in participants with cancer and cachexia. Clin. Cancer Res. 30, 489–497 (2024).
Groarke, J. D. et al. Phase 2 study of the efficacy and safety of ponsegromab in patients with cancer cachexia: PROACC-1 study design. J. Cachexia Sarcopenia Muscle 15, 1054–1061 (2024).
Klein, A. B. et al. Cross-species comparison of pregnancy-induced GDF15. Am. J. Physiol. Endocrinol. Metab. 325, E303–E309 (2023).
Zeng, Y. T., Liu, W. F., Zheng, P. S. & Li, S. GDF15 deficiency hinders human trophoblast invasion to mediate pregnancy loss through downregulating Smad1/5 phosphorylation. iScience 26, 107902 (2023).
Szustakowski, J. D. et al. Advancing human genetics research and drug discovery through exome sequencing of the UK Biobank. Nat. Genet. 53, 942–948 (2021).
Mbatchou, J. et al. Computationally efficient whole-genome regression for quantitative and binary traits. Nat. Genet. 53, 1097–1103 (2021).
Willer, C. J., Li, Y. & Abecasis, G. R. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics 26, 2190–2191 (2010).
Seabold, S. & Perktold, J. Statsmodels: econometric and modeling with Python. In Proc. 9th Python in Science Conference (eds van der Walt, S. & Millman, J.) 57–61 (SciPy, 2010).
Acknowledgements
This research has been conducted using the UK Biobank Resource under application number 59456. D.S. has received grants from the National Institutes of Health (www.nih.gov): R01-HL-145437, R01-HG-010689, R01-HL133339, X01HL139399, RC2 HL101834-01, RC1 TW008485-01. We thank V. George, P. Runge and P. Schroeder of Novartis for their contributions to compliance documentation associated with human tissue samples. We are additionally grateful to all of the PGR, RBG and UKB participants for their vital contributions to this research.
Author information
Authors and Affiliations
Contributions
A.M.G., D.P.D., I.S., J.E.D. and D.S. conceived of the proposal to characterize GDF15 LOF individuals. S.K., C.K. and M.Z.K. conducted gene–phenotype association studies. A.M.G., C.K., S.K., A.A., J.L.H., K.T., M.A., I.K., A.R.S., J.L.R.-F., A.R., J.E.D. and D.S. led efforts to conduct whole-exome sequencing of PGR. L.B.L., E.D., A.M.C., R.Z., M.E.C., L.D.L., Y.-H.C. and B.D. conducted in vitro experiments. Z.C. and R.S.S. designed and conducted in vivo experiments. A.M.G., S.K., C.K., M.Z.K., D.P.D., A.B.G., A.R., J.E.D. and D.S. contributed to recall by genotype study design. A.R., M.J., M.R.M., M.B.L., S.S.R., R.S., A.J., M.H.S., S.A., F.R.M. and M.I. conducted participant recruitment and clinical characterization. A.M.G., S.K., C.K., M.Z.K., L.B.L., I.S., E.D., A.M.C., R.Z., Z.C., R.S.S., D.P.D., A.B.G., A.A., J.L.H., K.T., M.A., I.K., A.R.S., J.L.R.-F., A.R., J.E.D. and D.S. contributed to writing the paper.
Corresponding authors
Ethics declarations
Competing interests
D.S. has received funding from Regeneron Pharmaceuticals, Eli Lilly & Company, Novartis, Merck, Astra Zeneca, NGM Biopharmaceuticals Inc., GSK, Astellas Pharma Inc. and Novo Nordisk. A.M.G., C.K., L.B.L., E.D., A.M.C., R.Z., M.E.C., Z.C., L.D.L., Y.H.C., R.S.S., D.P.D., A.B.G. and J.E.D. are employees of Novartis. I.S. was an employee of Novartis and is currently an employee of Yarrow Biotechnology. B.D. was an employee of Novartis and is currently an employee of Tango Therapeutics. A.A. and J.L.H. are employees of AstraZeneca. K.T., M.A. and I.K. are employees of Astellas Pharma. A.R.S. and J.L.R. are employees of the Regeneron Genetics Center. The other authors declare no competing interests.
Peer review
Peer review information
Nature Metabolism thanks Samuel Breit, Rachel Freathy and Stephen O’Rahilly for their contribution to the peer review of this work. Primary Handling Editor: Yanina-Yasmin Pesch, in collaboration with the Nature Metabolism team.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Extended data
Extended Data Fig. 1 Western blot evaluation of GDF15 variants under non-reducing PAGE conditions.
GDF15 variant expression under non-reducing conditions. GDF15 variants were transiently expressed and characterized by western blot in non-reducing SDS-PAGE. Two independent experiments were conducted with similar results.
Extended Data Fig. 2 Forest plot summaries of quantitative and binary trait associations with GDF15 LOF and C211G variants.
Forest plots, with per standard deviation (S.D.) units and 95% confidence intervals, of traits for GDF15 LOF and C211G carriers from 75,018 samples (158 heterozygotes, 5 knockouts) of PGR. (a) Quantitative traits. (b) Binary traits. Genotype counts for cases and controls are given as HomRR|HetRA|HomAA; R=reference allele; A=alternate allele. P-values are generated using whole genome regression models adjusting for age, sex, age*sex, age2 and top 10 genetic principal components (PCs). Additionally, Firth correction was used for binary traits. Quantitative effect estimates, per standard deviation (S.D.) units, are generated by standard linear regression adjusting for age, sex, age*sex, age2 and top 10 genetic PCs. No phenotype had FDR-5% p-value < 0.05 after applying Benjamini-Hochberg correction.
Extended Data Fig. 3 Oral glucose tolerance test (OGTT) data from RBG studies.
Oral glucose tolerance test (OGTT) findings from RBG studies. Data shown are mean and standard error of the mean from non-diabetic individuals identified in the RBG study. For glucose, HomRR (n = 59), HetRA (n = 26), HomAA (n = 4). For insulin, proinsulin, c-peptide, GIP, and GLP-1, HomRR (n = 32), HetRA (n = 14), HomAA (n = 4). The 30-minute timepoint was assessed in only a subset of individuals, HomRR (n = 25), HetRA (n = 6), HomAA (n = 1). Statistical analysis was performed for each timepoint as well as area under the curve (AUC) using additive linear mixed models with age and gender as fixed effects, and family ID as a random effect. P-values were calculated using Wald tests. No significant associations were detected. dl, deciliter; GIP, glucose-dependent insulinotropic polypeptide; GLP-1, glucagon-like peptide-1; mL, milliliters; µIU, micro international units; pg, picograms; pM, picomolar.
Supplementary information
Supplementary Tables 1–10
Genotypes, phenotypes and analyses.
Source data
Source Data Fig. 1
Unprocessed western blots for Fig. 1 and Extended Data Fig. 1.
Source Data Fig. 2
Raw data from mouse HDI experiments related to ELISA measurements of GDF15, body weight and food intake.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Gurtan, A.M., Khalid, S., Koch, C. et al. Identification and characterization of human GDF15 knockouts. Nat Metab 6, 1913–1921 (2024). https://doi.org/10.1038/s42255-024-01135-3
Received:
Accepted:
Published:
Issue date:
DOI: https://doi.org/10.1038/s42255-024-01135-3
