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. 2024 Oct;17(5):e004755.
doi: 10.1161/CIRCGEN.124.004755. Epub 2024 Aug 9.

Proteome- and Transcriptome-Wide Genetic Analysis Identifies Biological Pathways and Candidate Drug Targets for Preeclampsia

Maddalena Ardissino #  1   2   3   4 , Buu Truong #  5   6 , Eric A W Slob  7   8   9   10 , Art Schuermans  5   6   11 , Satoshi Yoshiji  12 , Alec P Morley  13   14 , Stephen Burgess  7 , Fu Siong Ng  3 , Antonio de Marvao  15   16   17 , Pradeep Natarajan  5   6 , Kypros Nicolaides  15   17 , Liam Gaziano  1   18 , Adam Butterworth  2   19   20   21 , Michael C Honigberg  5   22
Affiliations

Proteome- and Transcriptome-Wide Genetic Analysis Identifies Biological Pathways and Candidate Drug Targets for Preeclampsia

Maddalena Ardissino et al. Circ Genom Precis Med. 2024 Oct.

Abstract

Background: Preeclampsia is a leading cause of maternal and perinatal morbidity and mortality. However, the current understanding of its underlying biological pathways remains limited.

Methods: In this study, we performed a cross-platform proteome- and transcriptome-wide genetic analysis aimed at evaluating the causal relevance of >2000 circulating proteins with preeclampsia, supported by data on the expression of over 15 000 genes across 36 tissues leveraging large-scale preeclampsia genetic association data from women of European ancestry.

Results: We demonstrate genetic associations of 18 circulating proteins with preeclampsia (SULT1A1 [sulfotransferase 1A1], SH2B3 [SH2B adapter protein 3], SERPINE2 [serpin family E member 2], RGS18 [regulator of G-protein signaling 18], PZP [pregnancy zone protein], NOTUM [notum, palmitoleoyl-protein carboxylesterase], METAP1 [methionyl aminopeptidase 1], MANEA [mannosidase endo-alpha], jun-D [JunD proto-oncogene], GDF15 [growth differentiation factor 15], FGL1 [fibrinogen like 1], FGF5 [fibroblast growth factor 5], FES [FES proto-oncogene], APOBR [apolipoprotein B receptor], ANP [natriuretic peptide A], ALDH-E2 [aldehyde dehydrogenase 2 family member], ADAMTS13 [ADAM metallopeptidase with thrombospondin type 1 motif 13], and 3MG [N-methylpurine DNA glycosylase]), among which 11 were either directly or indirectly supported by gene expression data, 9 were supported by Bayesian colocalization analyses, and 5 (SERPINE2, PZP, FGF5, FES, and ANP) were supported by all lines of evidence examined. Protein interaction mapping identified potential shared biological pathways through natriuretic peptide signaling, blood pressure regulation, immune tolerance, and thrombin activity regulation.

Conclusions: This investigation identified multiple targetable proteins linked to cardiovascular, inflammatory, and coagulation pathways, with SERPINE2, PZP, FGF5, FES, and ANP identified as pivotal proteins with likely causal roles in the development of preeclampsia. The identification of these potential targets may guide the development of targeted therapies for preeclampsia.

Keywords: genes; genetics; preeclampsia; proteins; risk factors.

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Conflict of interest statement

Dr Natarajan reports research grants from Allelica, Amgen, Apple, Boston Scientific, Genentech/Roche, and Novartis; personal fees from Allelica, Apple, AstraZeneca, Blackstone Life Sciences, Creative Education Concepts, CRISPR Therapeutics, Eli Lilly & Co, Foresite Labs, Genentech/Roche, GV, HeartFlow, Magnet Biomedicine, Merck, and Novartis; scientific advisory board membership of Esperion Therapeutics, Preciseli, and TenSixteen Bio; is a scientific co-founder of TenSixteen Bio; has equity in MyOme, Preciseli, and TenSixteen Bio, and spousal employment at Vertex Pharmaceuticals, all unrelated to the present work. Dr Butterworth reports institutional grants from AstraZeneca, Bayer, Biogen, BioMarin, Bioverativ, Novartis, Regeneron, and Sanofi. Dr Honigberg reports consulting fees from Comanche Biopharma, advisory board service for Miga Health, and grant support from Genentech, all unrelated to the present work. The other authors report no conflicts.

Figures

Figure 1
Figure 1
Flowchart outlining project design and statistical analysis. pQTLs = protein quantitative trait loci, EUR = European
Figure 2
Figure 2
Genetic associations of protein levels with preeclampsia, displaying all proteins associated with preeclampsia after correction for multiple testing in the main analysis. Grey fields indicate data was not available for analysis. PPH4 = Posterior probability of shared causal variant, PPH3 = Posterior probability of distinct causal variant. * = nominally significant (p<0.05) ** = p<0.001, *** = significant after Benjamini-Hochberg correction for multiple testing
Figure 3
Figure 3
Bayesian colocalization analysis evaluating the posterior probability of a shared causal variants influencing protein levels and preeclampsia risk, and probability of colocalization versus non-colocalization conditional on there being a causal variant for both traits [PPH4/(PPH3+PPH4)]. Grey fields indicate data was not available for analysis
Figure 4
Figure 4
Genetic associations of gene expression levels with preeclampsia, limited to the proteins identified as significant on the proteome-wide analysis or their closest interacting proteins (maximum of 5 proteins, all with STRING interaction score >0.90). Grey fields indicate data was not available for analysis. * = nominally significant (p<0.05) ** = p<0.001, *** = significant after Benjamini-Hochberg correction for multiple testing
See this image and copyright information in PMC

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