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Title:Analiza genskih regij povezanih z astmo ter napoved tveganja in odziva na terapijo pri otroški astmi
Authors:ID Ovniček, Petra (Author)
ID Potočnik, Uroš (Mentor) More about this mentor... New window
ID Berce, Vojko (Comentor)
Files:.pdf DOK_Ovnicek_Petra_2018.pdf (4,05 MB)
MD5: EB2306CD48232471A4FC4E44FD23855A
 
Language:Slovenian
Work type:Doctoral dissertation
Organization:MF - Faculty of Medicine
Abstract:Astma je kompleksna poligenska bolezen dihal. Številne študije so v povezavi z astmo, njenimi značilnostmi ali odzivom na terapijo analizirale že mnogo genov, a se rezultati raziskav med sabo močno razlikujejo, prav tako pa mnogi kandidatni geni identificirani v nedavnih študijah na celotnem genomu (GWA študije) še niso bili potrjeni v neodvisnih replikacijih študijah. Večina GWA študij pri astmi ni analiziralo morebitnih povezav med genotipi in kliničnimi podatki ter odzivom na zdravljenje. Le malo je znanega o funkciji z astmo ali njenimi značilnostmi povezanih polimorfizmov posameznega nukleotida (SNP), ki se nahajajo v nekodirajočih področjih genoma. Namen naše raziskave je bil identificirati nove genetske markerje, ki opredeljujejo resnost astme oz. katerega od njenih podtipov ter vplivajo na odziv na terapije. Nadalje smo v raziskavi želeli ugotoviti, kakšen je vpliv kandidatnih SNP-jev povezanih z astmo in njenimi značilnostmi na ekspresijo bližnjih genov. Prav tako je bil namen študije tudi napoved tveganja za razvoj astme in odziva na terapijo. V študijo smo zajeli 340 otrok z astmo in 276 zdravih posameznikov. Genotipizacijo smo izvedli z verižno reakcijo s polimerazo (PCR), ki ji je sledil polimorfizem dolžin restrikcijskih fragmentov ali analiza talilne krivulje visoke ločljivosti. Rezultate smo statistično analizirali z uporabo programskega paketa SPSS. Z izdelavo profilov tveganja, izračuna tveganja iz razmerja obetov ter logistično regresijo smo skušali napovedati tveganje za razvoj bolezni ali odziva na terapijo z inhalacijskimi glukokortikoidi. Izbranim genom, ki se nahajajo v bližini nekodirajočih SNP-jev, ki kažejo na pomembno vlogo pri astmi, smo z uporabo kvantitativnega PCR izmerili gensko ekspresijo in analizirali morebitne razlike v ekspresiji med posameznimi fenotipskimi in genotipskimi skupinami. Identificirali smo nove genetske markerje ki imajo pomemben doprinos k dovzetnosti za razvoj astme, vplivajo na njeno težo in fenotip oz. pogojujejo odgovor na različne proti-astmatične terapije. Najpomembnejša odkritja so nove povezave med SNP-ji na oz. v bližini genov SFXN1, SLC22A4 in SLC22A5 ter odgovorom na terapijo z inhalacijskimi glukokortikoidi. Kot prvi smo ugotovili, da delecija na genu CCR5 ter SNP-ja na genih IL4 in GLCCI1 pogojujejo odziv na proti-astmatično terapijo z anti-levkotrieni pri posameznih pod-tipih astme. Identificirali smo nove povezave med SNP-ji na genih CA10, CTNNA3 in SFXN1 in njenimi fenotipskimi značilnostmi. Prav tako je naša raziskava prva neodvisna replikacijska študija nekaterih v nedavnih GWA študijah identificiranih astma SNP-jev; potrdili smo povezavo med SNP-jema na genih CA10 in SGK493 in tveganjem za astmo. Kot prvi smo s povečanim tveganjem za astmo povezali alel C za SNP rs10496195 v intronu gena HK2. Nadaljnja ekspresijska študija je pokazala povečano izražanje izoforme tega gena pri bolnikih z astmo oz. pri osebah z rizičnim alelom C za omenjen SNP. Ugotovili smo da alel C vpliva na spremenjeno razmerje med izoformama transkripta gena HK2 v limfocitih periferne krvi. Nadalje, naši rezultati potrjujejo hipotezo, da gre pri astmi za heterogeno bolezen pri kateri se genetski markerji lahko razlikujejo glede na podtip bolezni, saj mnoge povezave v skupini ne-atopijskih astmatikov niso bile potrjene v skupini atopikov in obratno. Na podlagi rezultatov izračunov napovedi tveganja lahko zaključimo, da zaenkrat genetski testi pri astmi žal še niso dovolj zanesljivi za prenos v klinično prakso. Najvišjo specifičnost (77,7 %) in občutljivost (63,0 %) smo dosegli pri genetskem profilu za napoved tveganja za ne-atopijsko obliko astme, ki vključuje 9 SNP-jev. Vsekakor bo v prihodnje potrebnih še mnogo nadaljnjih raziskav, funkcijskih študij in meta-statističnih analiz, kakorkoli pa lahko rečemo, da pomemben delček pri razumevanju genetskih mehanizmov pri astmi in korak k individualizirani obravnavi bolnikov predstavlja tudi naša študija.
Keywords:astma, polimorfizem enega nukleotida, asociacijska študija, genska ekspresija, napoved tveganja
Place of publishing:Maribor
Year of publishing:2017
PID:20.500.12556/DKUM-64695 New window
COBISS.SI-ID:293317376 New window
NUK URN:URN:SI:UM:DK:HIQNM41G
Publication date in DKUM:22.01.2018
Views:1755
Downloads:199
Metadata:XML RDF-CHPDL DC-XML DC-RDF
Categories:MF
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Secondary language

Language:English
Title:Analysis of loci associated with asthma and estimation of risk and response to therapy for childhood asthma
Abstract:Asthma is a complex polygenetic respiratory disease. Many studies have analyzed numerous genes and their relation to asthma, its characteristics or the response to anti-asthmatic therapies, but results of different studies are often contradictory; in addition, many candidate genes identified in recent asthma Genome-Wide Association Studies (GWAs) have not been replicated yet. There is also lack of information about the function of non-coding single nucleotide polymorphisms (SNPs) of asthma candidates. The aim of our study was to identified new genetic markers that define the characteristics of asthma or. any of its subtypes, and affect the response to therapy. Furthermore, we decided to determine the impact of chosen candidate SNPs, which are associated with asthma or its characteristics, on the gene expression of nearby genes. The aim of our study was also to calculate risks for the development of asthma, and the response to inhaling glucocorticoids. 340 asthmatic children and 276 members of a healthy control group were involved in our study. Genotyping was provided, using polymerase chain reaction (PCR) followed by restriction fragments length polymorphism or high resolution melting. Correlations were calculated using appropriate statistical tests and software SPSS. By using risk profiles, risk calculation from odds ratio and logistic regression analysis, we calculated the risk of asthma the odds for a good (over average) response to therapy. We measured gene expression of chosen genes located near non-coding SNPs, which have shown important impact on the development of asthma, on behavior or on the response to therapy. We calculated the correlation between gene expression and different phenotypes, as well as different genotypes. In our study, we identified many new genetic markers with important impact on asthma development, clinical characteristics and treatment response. The most important findings are new associations of SNPs on or near genes SFXN1, SLC22A4 and SLC22A5 on response to therapy with inhaled glucocorticoids. As first we found the that deletion on gene CCR5 and SNPs in genes IL4 and GLCCI1 influence response to anti-asthmatic therapy with anti-leukotrienes in certain sub-types of asthma. We have identified new association among SNPs on genes CA10, CTNNA3 and SFXN1 and asthma behavior. In addition, our study is the first independent replication study of asthma-candidate SNPs, which were identified in recent GWA studies; we confirmed SNPs on genes CA10 and SGK493 as asthma risk factor. We were the first to discover that allele C for rs10496195 in intron of HK2 gene represents an asthma risk factor. Further expression study showed that isoform of HK2 is overexpressed in asthmatics, as well as in individuals with risk allele for the mentioned SNP. We discovered that allele C influences the changed ratio between isoforms of HK2 gene transcript in samples. In addition, our results confirm the hypothesis that asthma is a heterogeneous disease and that some of its genetic markers differ between different subtypes. According to our result of risk prediction calculations, we can unfortunately conclude that genetic tests on/ in regard to asthma are not reliable enough to transfer to clinical practice at this point. The highest specificity and sensitivity were achieved with genetic profile for the non-atopic asthma risk prediction, which includes 9 SNPs. The specificity and sensitivity are 77.7% and 63.0%, respectively. However, further studies such as independent replication studies, meta-statistical and also functional analysis are necessary to get a clearer picture of the genetic mechanisms in asthma, to identify or to confirm molecular targets for development of new potential therapies, and to get a statistically strong genetic associations for different disease phenotypes, which will be based on a big number of samples, and will enable a personalized approach to patient management and to anti-asthmatic therapy.
Keywords:asthma, single nucleotide polymorphism, association study, gene expression, risk prediction


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