Pharmacogenomics landscape of COVID-19 therapy response in Serbian population and comparison with worldwide populations

J Med Biochem. 2020 Oct 2;39(4):488-499. doi: 10.5937/jomb0-26725.

Abstract

Background: Since there are no certified therapeutics to treat COVID-19 patients, drug repurposing became important. With lack of time to test individual pharmacogenomics markers, population pharmacogenomics could be helpful in predicting a higher risk of developing adverse reactions and treatment failure in COVID-19 patients. Aim of our study was to identify pharmacogenes and pharmacogenomics markers associated with drugs recommended for COVID-19 treatment, chloroquine/hydroxychloroquine, azithromycin, lopinavir and ritonavir, in population of Serbia and other world populations.

Methods: Genotype information of 143 individuals of Serbian origin was extracted from database previously obtained using TruSight One Gene Panel (Illumina). Genotype data of individuals from different world populations were extracted from the 1000 Genome Project. Fisher's exact test was used for comparison of allele frequencies.

Results: We have identified 11 potential pharmacogenomics markers in 7 pharmacogenes relevant for COVID-19 treatment. Based on high alternative allele frequencies in population and the functional effect of the variants, ABCB1 rs1045642 and rs2032582 could be relevant for reduced clearance of azithromycin, lopinavir and ritonavir drugs and UGT1A7 rs17868323 for hyperbilirubinemia in ritonavir treated COVID-19 patients in Serbian population. SLCO1B1 rs4149056 is a potential marker of lopinavir response, especially in Italian population. Our results confirmed that pharmacogenomics profile of African population is different from the rest of the world.

Conclusions: Considering population specific pharmacogenomics landscape, preemptive testing for pharmacogenes relevant for drugs used in COVID-19 treatment could contribute to better understanding of the inconsistency in therapy response and could be applied to improve the outcome of the COVID-19 patients.

Uvod: Kako ne postoje odobreni terapeutici za lečenje pacijenata sa COVID-19, mogućnost upotrebe postojećih lekova je postala važna. U nedostatku vremena za testiranje farmakogenomskih markera kod pojedinaca, populaciona farmakogenomika bi mogla biti od koristi u predviđanju povećanog rizika za pojavu neželjenih reakcija i neuspeha lečenja kod pacijenata sa COVID-19. Cilj naše studije bio je identifikovanje farmakogena i farmakogenomskih markera povezanih sa lekovima koji se preporučuju za lečenje COVID-19, hlorokin/hidroksihlorokin, azitromicin, lopinavir i ritonavir, u populaciji Srbije i drugim svetskim populacijama.

Metode: Podaci o genotipu 143 osobe srpskog porekla dobijeni su iz baze podataka prethodno formirane analizama genoma korišćenjem TruSight One Gene Panel (Illumina). Podaci o genotipu pojedinaca iz različitih svetskih populacija dobijeni su iz Projekta 1000 genoma. Fišerov egzaktni test korišćen je za poređenje učestalosti alela.

Rezultati: Identifikovali smo 11 potencijalnih farmakogenomskih markera u 7 farmakogena značajnih za lečenje COVID-19. Na osnovu visoke alterativne učestalosti alela u populaciji Srbije i funkcionalnog efekta varijanti, ABCB1 rs1045642 i rs2032582 mogu biti značajne za smanjeni klirens lekova azitromicina, lopinavira i ritonavira, a varijanta UGT1A7 rs17868323 za hiperbilirubinemiju kod bolesnika sa COVID-19 koji se leče ritonavirom. SLCO1B1 rs4149056 je potencijalni marker odgovora na lopinavir, posebno u populaciji Italije. Naši rezultati potvrdili su da se farmakogenomski profil afričke populacije razlikuje od ostatka sveta.

Zaključak: Uzimajući u obzir farmakogenomski profil specifičan za populaciju, preventivno testiranje farmakogena značajnih za lekove koji se koriste u lečenju COVID-19 moglo bi doprineti boljem razumevanju interindividualnih razlika u odgovorima na terapiju i poboljšanju ishoda lečenja pacijenata sa COVID-19.

Keywords: COVID-19; azithromycin; chloroquine/hydroxychloroquine; lopinavir; pharmacogenomics markers; population pharmacogenomics; ritonavir.