Exploring the genetics of adverse events in pharmacotherapy using Biobanks and Electronic Health Records
Date
2020-07-11
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Abstract
Individuaalsed geneetilised variandid võivad mõjutada ravimite efektiivsust ja ohutust ning selle kaudu farmakoteraapia tulemust. Farmakogenoomika valdkonna eesmärk on leida sellised eelsoodumust põhjustavad geneetilised riskitegurid, et ravi personaliseerimise kaudu saavutada soovitud ravivastus. Geneetiliste variantide olulist osa ravimite efektiivsuses näitavad mitmed uuringud, kuid vähem on läbi viidud ravimite kõrvaltoimeid käsitlevaid uuringuid. Kuna kõrvaltoimed esinevad harva, on piisava hulga juhtumite kogumine ja sellega ka nende uurimine keerukas. Populatsiooni põhised biopangad koos elektrooniliste terviseandmetega annavad võimaluse koguda piisavalt suuri valimeid ja leida retrospektiivselt spetsiifilisi fenotüüpe korraga tuhandetele indiviididele. Uurisime oma teadustöös ravimite kõrvaltoimete tekkimist mõjutavate geneetiliste riskifaktorite tuvastamise ja valideerimise võimalusi, kasutades selleks Eesti geenivaramu ja teiste riikide biopankade geeniandmeid koos informatsiooniga ravimite kõrvaltoimete kohta. Me tuvastasime tugeva statistiliselt olulise seose penitsilliiniallergia ja inimese leukotsüütide antigeeni alleeli kandluse vahel ning kinnitasime selle tulemuse kahes täiendavas andmestikus, mis sisaldasid kokku 1,14 miljoni isiku andmeid. Täiendavalt näitame oma töös seost kliinilises arendusfaasis oleva osteoporoosi ravimikandidaadi terapeutilist toimet jäljendavate geneetiliste variantide ja kardiovaskulaarsete kõrvaltoimete vahel, mis illustreerib inimese geneetika uuringute kasutamise võimalusi ravimiarenduses. Oma töös toome välja Eesti geenivaramu andmete alusel loodud potentsiaalselt kulutõhusa, aga samas laiahaardelise alternatiivi selliste geenivariantide tuvastamiseks, mille puhul on olemas soovitused sobiva ravimi valikuks. Leidsime, et selliste inimeste osakaal, kes võivad saada kasu ravimite määramise eelsest geneetilisest testimisest on suur. Kokkuvõtteks anname oma tööga panuse farmakogenoomika valdkonna arengusse, tuues uusi teadmisi farmakoteraapiasse, mis edasiste täiendavate uurimistööde lisandumisel aitavad tuua kliinilisse praktikasse rohkem juhendeid personaalselt sobivate ravimite valikuks.
Individual genetic variants may influence pharmacotherapy by affecting the efficacy and safety of a drug. The aim of the field of pharmacogenomics (PGx) is to find these predisposing genetic risk factors to help personalize treatment towards a desired outcome. Although there are various studies indicating the role of genetic variants in drug efficacy, there are less studies on drugs adverse events (ADEs). The rarer nature of ADEs has made the collection of sufficiently large sample sizes more challenging. Coupling population-based biobanks with electronic health records (EHRs) provides the opportunity to retrospectively retrieve specific phenotypes for thousands of individuals simultaneously, thereby bringing a potential asset to studies in different routes of PGx research. We explored here the genetic data of over 15,000 participants of the Estonian biobank (EstBB) with the information on ADEs imbedded in their EHRs for the discovery of potential genetic risk factors for such events. We identified a strongly significant association between penicillin allergy and an allele of the human leukocyte antigen (HLA) gene and validated this result in two additional cohorts involving a total of 1.14 million individuals. Our work further revealed an association between adverse cardiovascular events and genetic variants that mimic the therapeutic effect of a drug in clinical development for the treatment of osteoporosis, thus illustrating the potential of human genetics studies for the guidance of drug development processes. Finally, we show a potential cost-effective and comprehensive alternative for the detection of genetic variants with drug treatment recommendations based on the EstBB and highlight the large proportion of individuals who are anticipated to benefit from genetic testing prior to treatment. In conclusion, with our work we contribute to the field of pharmacogenomics by bringing new knowledge in pharmacotherapy that with further in-depth research has the potential to yield more clinically actionable recommendations.
Individual genetic variants may influence pharmacotherapy by affecting the efficacy and safety of a drug. The aim of the field of pharmacogenomics (PGx) is to find these predisposing genetic risk factors to help personalize treatment towards a desired outcome. Although there are various studies indicating the role of genetic variants in drug efficacy, there are less studies on drugs adverse events (ADEs). The rarer nature of ADEs has made the collection of sufficiently large sample sizes more challenging. Coupling population-based biobanks with electronic health records (EHRs) provides the opportunity to retrospectively retrieve specific phenotypes for thousands of individuals simultaneously, thereby bringing a potential asset to studies in different routes of PGx research. We explored here the genetic data of over 15,000 participants of the Estonian biobank (EstBB) with the information on ADEs imbedded in their EHRs for the discovery of potential genetic risk factors for such events. We identified a strongly significant association between penicillin allergy and an allele of the human leukocyte antigen (HLA) gene and validated this result in two additional cohorts involving a total of 1.14 million individuals. Our work further revealed an association between adverse cardiovascular events and genetic variants that mimic the therapeutic effect of a drug in clinical development for the treatment of osteoporosis, thus illustrating the potential of human genetics studies for the guidance of drug development processes. Finally, we show a potential cost-effective and comprehensive alternative for the detection of genetic variants with drug treatment recommendations based on the EstBB and highlight the large proportion of individuals who are anticipated to benefit from genetic testing prior to treatment. In conclusion, with our work we contribute to the field of pharmacogenomics by bringing new knowledge in pharmacotherapy that with further in-depth research has the potential to yield more clinically actionable recommendations.
Description
Väitekirja elektrooniline versioon ei sisalda publikatsioone
Keywords
pharmacotherapy, genetics, biobanks, health data