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Meta-Analysis
. 2022 Aug 2:11:e76272.
doi: 10.7554/eLife.76272.

Integrated analyses of growth differentiation factor-15 concentration and cardiometabolic diseases in humans

Susanna Lemmelä #  1 , Eleanor M Wigmore #  2 , Christian Benner  1 , Aki S Havulinna  1   3 , Rachel M Y Ong  4 , Tibor Kempf  5 , Kai C Wollert  5 , Stefan Blankenberg  6   7   8 , Tanja Zeller  6   8   9 , James E Peters  10   11 , Veikko Salomaa  3 , Maria Fritsch  12 , Ruth March  13 , Aarno Palotie  1   14   15 , Mark Daly  1   14   15 , Adam S Butterworth  4   11   16   17 , Mervi Kinnunen  1 , Dirk S Paul  2   4   16 , Athena Matakidou  2
Affiliations
Meta-Analysis

Integrated analyses of growth differentiation factor-15 concentration and cardiometabolic diseases in humans

Susanna Lemmelä et al. Elife. .

Abstract

Growth differentiation factor-15 (GDF15) is a stress response cytokine that is elevated in several cardiometabolic diseases and has attracted interest as a potential therapeutic target. To further explore the association of GDF15 with human disease, we conducted a broad study into the phenotypic and genetic correlates of GDF15 concentration in up to 14,099 individuals. Assessment of 772 traits across 6610 participants in FINRISK identified associations of GDF15 concentration with a range of phenotypes including all-cause mortality, cardiometabolic disease, respiratory diseases and psychiatric disorders, as well as inflammatory markers. A meta-analysis of genome-wide association studies (GWAS) of GDF15 concentration across three different assay platforms (n=14,099) confirmed significant heterogeneity due to a common missense variant (rs1058587; p.H202D) in GDF15, potentially due to epitope-binding artefacts. After conditioning on rs1058587, statistical fine mapping identified four independent putative causal signals at the locus. Mendelian randomisation (MR) analysis found evidence of a causal relationship between GDF15 concentration and high-density lipoprotein (HDL) but not body mass index (BMI). Using reverse MR, we identified a potential causal association of BMI on GDF15 (IVW pFDR = 0.0040). Taken together, our data derived from human population cohorts do not support a role for moderately elevated GDF15 concentrations as a causal factor in human cardiometabolic disease but support its role as a biomarker of metabolic stress.

Keywords: BMI; GDF15; Mendelian randomisation; causality; epidemiology; genetics; genomics; global health; human; obesity.

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Conflict of interest statement

SL, CB, AH, TK, KW, SB, TZ, JP, AP, MD, MK No competing interests declared, EW, MF, RM, DP are employees of AstraZeneca, RO is currently an employee of GlaxoSmithKline (although was not when this work was carried out), VS has received honoraria from Novo Nordisk and Sanofi for consulting. He also has ongoing research collaboration with Bayer Ltd (all outside this work), AB reports grants outside of this work from Biogen, BioMarin, Bioverativ, Merck, Novartis, Pfizer and Sanofi and personal fees from Novartis, AM is an employee of AstraZeneca and currently an employee of GlaxoSmithKline (although not an employee of GlaxoSmithKline when this work was carried out)

Figures

Figure 1.
Figure 1.. Forest plots of Cox proportional hazard models for independent predictors of (a) all-cause mortality, (b) diabetes, and (c) cardiovascular disease.
The plot reports hazard ratios and 95% condidence intervals (error bars) with the dashed line representing the null effect. GDF15 is highlighted in red and variables are ordered by highest hazards ratio. Sample sizes are as follows; (a) n=393, (b) n=97 and (c) n=438. Abbreviations: BMI, body mass index; GDF15, growth differentiation factor-15; CHD, coronary heart disease; STR, stroke; HDL, high-density lipoprotein.
Figure 1—figure supplement 1.
Figure 1—figure supplement 1.. Survival curves of Cox proportional hazards model for (a) all-cause mortality (b) diabetes, and (c) cardiovascular disease stratified by GDF15 quartiles.
Survival curves include data from 10-year follow-up and GDF15 levels are divided into quartiles. Type 2 diabetes shows only a comparison of the last quartile (75–100%) with the rest (0–75%) due to insufficient power when treating the other quartiles separately. Abbreviations: T2DM, type 2 diabetes mellitus; CHD, coronary heart disease; STR, stroke; GDF15, growth differentiation factor-15.
Figure 2.
Figure 2.. Manhattan and Quantile-Quantile (QQ) plots for genome-wide association study (GWAS) meta-analysis of conditioned growth differentiation factor-15 (GDF15) plasma levels in 14,099 individuals for (a) the GDF15 region and (b) all chromosomes.
The dotted line (a) and red line (b) represent genome-wide significance (p-value < 5 × 10–8).
See this image and copyright information in PMC

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