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Genetska heterogenost pri otrocih z amelogenesis imperfecta v Sloveniji in njen vpliv na rentgensko določljivo morfologijo zob : doktorska disertacija
ID Leban, Tina (Author), ID Fidler, Aleš (Mentor) More about this mentor... This link opens in a new window, ID Trebušak Podkrajšek, Katarina (Comentor)

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Abstract
Amelogenesis imperfecta (AI) je heterogena skupina dednih bolezni s kliničnimi znaki razvojno okvarjene zobne sklenine. V raziskavi smo analizirali eksom pri 24 slovenskih otrocih z nesindromskimi oblikami AI in skušali opredelili genetsko etiologijo v genih znano povezanih z AI. Nadalje smo z uporabo programa Fiji ImageJ analizirali ortopantomogramske posnetke (OPT) otrok z AI in OPT posnetke otrok v kontrolni skupini ter določili tri rentgenske parametre: skleninski kot (SK), dentinski kot (DK) ter razmerje mineralizacije sklenine in dentina (RM), s katerimi smo kvantitativno vrednotili spremenjeno sklenino neizraslih drugih spodnjih stalnih kočnikov. V 13 družinah smo opredelili patološke različice v treh genih znano povezanih z AI: v osmih družinah (61,5 %) v genu ENAM, v treh družinah (23,1 %) v genu AMELX in v dveh družinah (15,4 %) v genu MMP20. Od teh je bilo pet različic novih. Na podlagi rezultatov kontrolne skupine smo neodvisno izračunali mejne vrednosti SK, DK in RM, določili območje hipomineralizacije in hipoplazije ter prikazali odstopanja v količini in kakovosti sklenine z visoko ponovljivostjo. Primerjava povezanosti vseh treh rentgenskih parametrov skupaj (SK, DK in RM), kot tudi posamično za DK in RM, je bila, glede na opredeljene patološke različice v treh genih znano povezanih z AI, statistično značilna. Z analizo modela smo ocenili vpliv vseh treh rentgenskih parametrov skupaj na prisotnost patoloških različic v treh genih znano povezanih z AI, z 90 % (84,0 – 98,0 %) AUC-napovedno močjo. V raziskavi smo predstavili potencial preprostega orodja za natančnejše prepoznavanje značilnosti razvojno okvarjene sklenine, s katerim bi lahko izboljšali diagnostiko AI.

Language:Slovenian
Keywords:Amelogenesis imperfecta, razvojno okvarjena sklenina, genetska analiza, rentgenska analiza, neizrasli drugi spodnji stalni kočniki, novo interpretativno orodje
Work type:Doctoral dissertation
Typology:2.08 - Doctoral Dissertation
Organization:BF - Biotechnical Faculty
Year:2024
PID:20.500.12556/RUL-164306 This link opens in a new window
COBISS.SI-ID:214071043 This link opens in a new window
Publication date in RUL:21.10.2024
Views:85
Downloads:24
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Secondary language

Language:English
Title:Genetic heterogeneity in children with amelogenesis imperfecta in Slovenia and its influence on X-ray detectable tooth morphology : doctoral dissertation
Abstract:
Amelogenesis imperfecta (AI) is a heterogeneous group of genetic disorders affecting dental enamel. In this research, we analysed the exomes of 24 Slovenian children with non-syndromic forms of AI to identify the genetic etiology in AI-related genes. Additionally, using the Fiji ImageJ programme, we analysed the panoramic radiographs (OPTs) of children with AI and those in a control group. We determined three radiographic parameters: enamel angle (EA), dentin angle (DA), and enamel/dentin mineralisation ratio (EDMR), to quantitatively evaluate changes in the enamel of second lower permanent molar buds. In 13 families we identified pathological variants in three AI-related genes: eight families (61.5%) had variants in the ENAM gene, three families (23.1%) in the AMELX gene, and two families (15.4%) in the MMP20 gene. Among these, five variants were novel. Based on the results the control group, we independently calculated the cut-off values for EA, DA, and EDMR. Hypomineralization and hypoplastic regions were observed, indicating significant deviations in enamel quantity and quality with high reproducibility. The correlation of all three parameters, as well as individually for DA and EDMR, was statistically significant based on the identified pathological variants. Assessing the influence of all three parameters on the presence of pathological variants in three AI-related genes yielded a 90% (84.0 – 98.0%) AUC-estimated predictive power using the random forest model. This research highlights the potential of a novel interpretive tool in diagnosing developmental enamel defects, offering insights into the genetic basis and radiographic features of AI.

Keywords:Amelogenesis imperfecta, developmentally defective enamel, molecular genetic analysis, radiographic analysis, lower second permanent molar buds, new evaluation tool

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