Search bioRxiv⌕ Search

bioRxiv · 10.1101/664961

Rapid response to the Alpha-1 Adrenergic Agent Phenylephrine in the Perioperative Period is Impacted by Genomics and Ancestry

Abstract

BackgroundThe emergence of genomic data in biobanks and health systems offers new ways to derive medically important phenotypes, including acute phenotypes that occur during in-patient clinical care. We hypothesized that there is a genetic underpinning to the magnitude of the response to phenylephrine, an 1-adrenergic receptor agonist commonly used to treat hypotension during anesthesia and surgery.\n\nMethodsWe quantified the response to phenylephrine by determining the delta between the minimum blood pressure (BP) within five minutes before and the maximum BP within five minutes after bolus administration. We then performed a genome-wide association study (GWAS) adjusted for genetic ancestry, demographics, and relevant clinical covariates to investigate genetic factors underlying individual differences systolic BP response to phenylephrine ({Delta}SBP), as well as mean arterial pressure ({Delta}MAP) and diastolic BP ({Delta}DBP), for both the entire study cohort as well as for each of 3 ancestry sub-cohorts; European American(EA), African American(AA), and Hispanic American(HA).\n\nResults4,317 patients met inclusion criteria, of which 3,699 were genotyped. Average {Delta}BP values over the entire cohort were {Delta}SBP=17(+-25) mmHg, {Delta}MAP=14(+-18) mmHg, {Delta}DBP=11(+-14) mmHg. The largest difference between populations was observed for {Delta}SBP ({Delta}SBPEA=20(+-24) mmHg; {Delta}SBPHA=16(+-25) mmHg; {Delta}SBPAA=15(+-25) mmHg). The differences remained after adjusting for clinical covariates and ancestry (EA vs. HA: {Delta}SBP, p<0.032;{Delta}MAP, p<0.021;{Delta}DBP,p<0.008);(EA vs. AA:{Delta}SBP,p<5.13x10-5;{Delta}MAP,p<2.1x10-4;{Delta}DBP,p<3.3x10-4). GWAS revealed significant associations between loci and BP response in 5 different genome regions (p<5x10-8) in the entire cohort, and suggestive associations in 2 different regions in EAs (p<6x10-8,p<7x10-8). We observed non-random enrichment in association with SBP drug response in 165 loci previously reported to be associated with systolic blood pressure. Finally, we discovered rare variants, rs188427942 and rs147664194 present at [~]1% in EAs and rs146535276 present at [~]1% in AAs respectively, where patients carrying one copy of these variants show no response to phenylephrine.\n\nConclusionsIt is possible to derive a quantitative phenotype suited for comparative statistics and genome-wide association studies from routinely collected perioperative data. There are population differences in rapid response to phenylephrine, large effect alleles and novel genes affecting pharmaceutical response, and phenylephrine non-responders, with implications for personalized treatment during surgery.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Wenric, S., Jeff, J. M., Joseph, T., Yee, M.-C., Belbin, G. M., Regeneron Genetics Center,, CBIPM Genomics Group,, Owusu Obeng, A., Ellis, S. B., Bottinger, E. P., Gottesman, O., Levin, M. A., Kenny, E. E.. 2019-06-10. Rapid response to the Alpha-1 Adrenergic Agent Phenylephrine in the Perioperative Period is Impacted by Genomics and Ancestry. https://doi.org/10.1101/664961

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Long-read DNA sequencing reveals global hypomethylation and focal hypermethylation in SDHx-deficient pheochromocytoma and paraganglioma

Pheochromocytomas and paragangliomas (PPGL) are highly heritable neuroendocrine tumors of the autonomic ganglia. Genomic DNA in most cancer cells is hypomethylated. However, DNA in PPGLs secondary to mutations in succinate dehydrogenase complex (SDHx) genes is reportedly hypermethylated due to succinate-mediated inhibition of DNA demethylases. We used nanopore long-read sequencing to characterize the methylome of tumor and white blood cell DNA from SDHx and non-SDHx PPGL patients, alongside normal adrenal medulla. We find that both SDHx and non-SDHx PPGLs are globally hypomethylated, particularly at centromeres. In normal adrenal medulla, CpG islands marked by H3K4 methylation are hypomethylated, whereas CpG islands lacking H3K4 methylation are hypermethylated. In SDHx-related PPGL, some H3K4me-marked CpG islands are hypermethylated, but most are not. We propose that DNA methylation in SDHx-related PPGL reflects the global hypomethylation generally observed in tumors, partly offset by succinate-mediated inhibition of TET DNA demethylases. Opposing effects of succinate may alter the balance between DNA methylation (indirect inhibition of the DNMT3A/B DNA methylases via inhibition of H3K4me demethylases) and DNA demethylation (inhibition of TET DNA demethylases) at active CpG islands.

genomics↗

High piRNA abundance is a hallmark of evolutionarily persistent piRNA-producing loci.

PIWI-interacting RNAs (piRNAs) silence transposons in the germline, and the loci that produce them diverge rapidly between species. Yet, some loci retain both their genomic location and their piRNA production across large evolutionary distances, and the basis for this conservation is unclear. To identify the features that distinguish these persistent loci, we compared piRNA production at orthologous loci in three closely related mouse species, contrasting loci that produce piRNAs in all three species with those that do so in only one. Transposon content and UTR features, often linked to piRNA production, did not distinguish the two groups. Transcription extending beyond gene ends (readthrough) was more frequent at conserved loci, but did not explain conservation once the amount of piRNAs produced was taken into account. Instead, we found that the conserved loci are those that produce the most piRNAs. The same association holds true in human and two other primate species. We speculate that most piRNAs expressed in testis are tolerated molecular noise, and that only the highly expressed minority are likely to be functional.

genomics↗

Epigenome-informed Polymer Modeling Reveals Chromosome Folding Landscapes across Distinct Genetic and Epigenetic Contexts

Three-dimensional (3D) genome organization is critical for gene regulation, enabling long-range interactions between genes and distal regulatory elements. Genomic structural variations and epigenetic differences can perturb this organization, contributing to phenotypic variation and tissue-specific gene regulation. Prior studies have assessed the impact of these genetic and epigenetic changes on 3D genome folding, primarily using population-averaged features such as topologically associating domains and loops. However, growing evidence from single-cell and live-imaging studies indicates that chromosomes are highly dynamic and exist as heterogeneous ensembles of conformations. Here, we applied an epigenetic-state-informed polymer modeling framework to generate chromosomal conformational ensembles directly from cell- and tissue-specific epigenomic data. The resulting ensembles reproduced experimental Hi-C maps across cell lines and tissue types. Comparison of these conformational ensembles revealed that, although polymer dynamics were conserved across cell lines, their folding landscapes diverged. These differences arose primarily from cell-line-specific chromatin-state interaction networks and were concentrated in rare, long-lived contacts. Furthermore, modeling a TAD-boundary-disrupting deletion without re-optimizing the model parameters indicated a shift in the chromatin conformational ensemble from predominantly insulated to predominantly fused states. The modeled deletion also selectively strengthened active chromatin contacts and differentially disrupted enhancer contacts involving neighboring genes. Finally, comparison of two tissue types from the same donor revealed epigenetically driven rewiring of chromatin-state interaction networks. These findings establish chromosomal conformational ensembles as a sensitive readout of genome reorganization across distinct genetic and epigenetic contexts.

genomics↗