Developing Computational Solutions for Personalized Medicine
Date
2019-06-27
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Abstract
Kuigi meditsiin on alati põhinenud patsiendi ja arsti vahelisel individuaalsel suhtlusel, on viimasel aastakümnel, seoses digitaalsete geeniandmete mahu hüppelise kasvuga, tulnud laiemasse kasutusse mõiste “personaalmeditsiin”, mille sisuks on muuta haiguste ennetus ja ravi senisest efektiivsemaks, võttes muuhulgas arvesse infot iga patsiendi individuaalse geneetilise tausta kohta.
Sulev Reisbergi doktoritöö on seotud personaalmeditsiini rakendamisega Eesti tervishoiusüsteemis, kasutades Eesti Geenivaramu geeniandmeid ning käsitledes suuremahuliste arvutustega seotud küsimusi.
Polügeensed riskiskoorid on matemaatilised arvutusmudelid, mis isiku geneetilise info põhjal ennustavad, kas tal on madal, keskmine või kõrge geneetiline risk teatud haiguse tekkimiseks. Käesolev doktoritöö on üks esimesi, kus sõnastati probleem, et need mudelid sobivad eelkõige eurooplastele, kuid teisest populatsoonist pärit isikule antud haiguse riskihinnang võib olla väär.
Farmakogeneetika on valdkond, mis uurib, millise kiirusega meie kehad omastavad ravimeid. Kuigi vastavat teadmust on juba üsnagi palju, puudus seni selge samm-sammuline otsustusloogika, mis kirjeldaks, kuidas isiku geeniandmetest jõuda konkreetse ravimikoguse soovituseni. Sulev Reisbergi doktoritöö raames loodi tarkvara, mis selle töö ära teeb ning mille abil koostati farmakogeneetilise info raportid 44 tuhandele geenidoonorile. Selgus, et tervelt 99,8% geenidoonoritel esineb niisuguseid geenivariante, mis nõuaksid mõne ravimi puhul koguse kohandamist.
Selleks, et personaalmeditsiini lahendused jõuaks kliinilistesse protsessidesse, aga ka uute geenide ja haiguste vaheliste seoste uurimiseks, on tarvis need lahendused integreerida olemasolevate terviseinfosüsteemidega. Doktoritöös ühendati omavahel geeniandmed ja digitaalsed terviseandmed ning viidi läbi nn fenoomiülene assotsiatsiooniuuring. Uuringus vaadeldi, milliste muude haigustega on seotud geenimutatsioonid, mis varasemalt on seostatud astma ja maksahaigustega.
Tänaseks on käivitunud riiklik projekt vajaliku IT-infratstruktuuri loomiseks, mis võimaldaks võtta Sulev Reisbergi doktoritöö tulemusi kasutusele igapäevases kliinilises praktikas.
Although medicine has always been an individualized interaction between a patient and a doctor, the term „personalized medicine” has entered into common use during recent decades. The general idea behind it is to provide more effective clinical care and prevention of the diseases by more finely dividing patients and diseases into subgroups based on the genetic data. Doctoral thesis of Sulev Reisberg is strongly related to Estonian state-level approach to integrating personalized medicine into routine clinical practice. It uses genetic data from Estonian Biobank and focuses on computational issues. Polygenic risk scores are mathematical models that estimate based on individual genetic data whether the patient has a low, medium or high risk of developing certain diseases. This thesis was one of the first studies that indicated a problem that existing models are most suitable for Europeans. For other populations, the estimated risk could be the opposite to the true risk. Pharmacogenomics is a field that investigates, how fast we metabolize medical drugs. Although a lot of information of this kind was already available, so far there was no concrete step-by-step decision algorithm on how to make specific recommendations based on the genetic data of a patient. In this doctoral thesis, software was built and used for producing pharmacogenomic reports for 44 thousand gene donors. It turned out that for 99.8% of the gene donors a dosage adjustment for at least one investigated drug is recommended. In order to bring personalized medicine solutions into clinical practice, but also for investigating gene-disease associations, these solutions have to be integrated with health information systems. In this thesis, genetic data and electronic health records were linked to conduct a phenome-wide association study. In this study, it was investigated whether there are any diseases, that are linked to genetic mutations that were previously been associated with asthma and liver diseases. As of today, a state-level project has been started to build an IT-infrastructure to bring the outcomes of the doctoral thesis of Sulev Reisberg to routine clinical practice.
Although medicine has always been an individualized interaction between a patient and a doctor, the term „personalized medicine” has entered into common use during recent decades. The general idea behind it is to provide more effective clinical care and prevention of the diseases by more finely dividing patients and diseases into subgroups based on the genetic data. Doctoral thesis of Sulev Reisberg is strongly related to Estonian state-level approach to integrating personalized medicine into routine clinical practice. It uses genetic data from Estonian Biobank and focuses on computational issues. Polygenic risk scores are mathematical models that estimate based on individual genetic data whether the patient has a low, medium or high risk of developing certain diseases. This thesis was one of the first studies that indicated a problem that existing models are most suitable for Europeans. For other populations, the estimated risk could be the opposite to the true risk. Pharmacogenomics is a field that investigates, how fast we metabolize medical drugs. Although a lot of information of this kind was already available, so far there was no concrete step-by-step decision algorithm on how to make specific recommendations based on the genetic data of a patient. In this doctoral thesis, software was built and used for producing pharmacogenomic reports for 44 thousand gene donors. It turned out that for 99.8% of the gene donors a dosage adjustment for at least one investigated drug is recommended. In order to bring personalized medicine solutions into clinical practice, but also for investigating gene-disease associations, these solutions have to be integrated with health information systems. In this thesis, genetic data and electronic health records were linked to conduct a phenome-wide association study. In this study, it was investigated whether there are any diseases, that are linked to genetic mutations that were previously been associated with asthma and liver diseases. As of today, a state-level project has been started to build an IT-infrastructure to bring the outcomes of the doctoral thesis of Sulev Reisberg to routine clinical practice.
Description
Väitekirja elektrooniline versioon ei sisalda publikatsioone
Keywords
personaalmeditsiin, matemaatilised mudelid, bioinformaatika, biopangad, Eesti