2024. gadā aizstāvētie promocijas darbi un kopsavilkumi

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Browsing 2024. gadā aizstāvētie promocijas darbi un kopsavilkumi by Author "Berga-Švītiņa, Egija"

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    Ģenētisko faktoru, kas saistīti ar krūts vai olnīcu vēža risku, identificēšana BRCA1 patogēno variantu nesējās. Promocijas darba kopsavilkums
    (Rīgas Stradiņa universitāte, 2024) Berga-Švītiņa, Egija; Miklaševičs, Edvīns; Vilne, Baiba
    Krūts vēzis (KV) ir visizplatītākais vēzis sieviešu vidū visā pasaulē, kā arī olnīcu vēzis (OV) ir nozīmīgs veselības aprūpes slogs, ieņemot astoto vietu incidences un mirstības rādītājos. Šo ļaundabīgo audzēju etioloģija iekļauj kompleksu mijiedarbību starp modificējamiem un nemodificējamiem riska faktoriem. Viens no šādiem riska faktoriem ir ģenētiskā predispozīcija, tai skaitā, BRCA1 gēna patogēnie varianti (PV), kas ievērojami palielina KV vai OV attīstības risku. Tomēr risks BRCA1 PV nesējās ir atšķirīgs, jo to ietekmē citi ģenētiskie faktori. Šīs disertācijas mērķis ir izpētīt ģenētiskos faktorus, kas ietekmē KV un OV attīstības risku sievietēs ar reģionam specifiskiem pārmantojamiem BRCA1 PV, kā arī izvērtēt poligēnā riska modeļa (angl. PRS) ietekmi uz individualizētu kopējo ģenētisko risku. Šajā disertācijā tika veikta genoma mēroga asociāciju analīze (angl. GWAS) 406 sievietēs ar pārmantojamu BRCA1 PV (c.4035del un c.5266dup) un KV vai OV salīdzinājumā ar sievietēm ar pārmantojamu BRCA1 PV bez audzēja diagnozes, kam sekoja statistiski nozīmīgi asociēto viena nukleotīda variantu (angl. SNV) funkcionālā anotācija. Tālāk tika pētīta nesen izveidoto genoma-mēroga PRS asociācija ar KV vai OV attīstības risku BRCA1 PV nesējās, kas tika pārbaudīta ar binomiālās loģistiskās regresijas modeli. KV pacientēs statistiski nozīmīgāk saistītais SNV bija rs2609813 (p = 2,33 × 10−7, izredžu attiecība (angl. OR) = 0,28), kas ir intronisks variants proteīnu kodējošā FAM107B gēnā (genomiskajā pozīcijā (GRCh37) 10:14800320) un tiek prognozēts kā regulējošā reģiona variants. Otrs statistiski nozīmīgākais ar KV saistītais SNV bija rs4688094 (p = 7,76 × 10−7, OR = 0,38), kas atrodas garās nekodējošās RNS (angl. lncRNA) gēnā (genomiskajā pozīcijā (GRCh37) 3:118003477) un nozīmīgākais ar OV saistītais SNV bija rs79732499 (p = 1,38 × 10−7, OR = 0,00031), kas atrodas genomiskajā pozīcijā (GRCh37) 20:3404208 un tiek prognozēts kā regulējošā reģiona variants enhanserī (angl. enhancer). Abi minētie varianti atrodas genoma nekodējošā daļā. Rezultāti liecina, ka atklātie varianti visticamāk ietekmē gēnu ekspresiju vai citus regulatorus procesus, nevis specifiski proteīna struktūru vai funkciju. Nelielās kohortas izmēra dēļ mūsu rezultāti nesasniedza genoma mēroga statistisko nozīmīgumu p = 5 × 10−8. Savukārt PRS aprēķinos atbilstošākais modelis bija BayesW PRS, ar kuru varēja efektīvi paredzēt indivīda KV risku (OR = 1.37; 95 % ticamības intervāls (angl. CI) = 1,03–1,81, p = 0,029 ar laukumu zem uztvērēja operatora līknes (angl. AUC) = 0,76). Vienlaicīgi neviens no izmantotajiem PRS nebija labs OV attīstības riska prognozētājs, kas liecina par nepieciešamību veikt padziļinātus pētījumus lielākā OV kohortā. Šī pētījuma rezultātus ir iespējams izmantot kā preliminārus datus plašākiem pētījumiem, un tie varētu veicināt individualizētu PRS izstrādi un pielietošanu sievietēs ar pārmantojamu BRCA1 PV. Iepriekš izstrādātais BayesW PRS ir efektīvs un palīdz novērtēt KV attīstības risku BRCA1 PV (c.4035del vai c.5266dup) nesējās. Šis modelis var veicināt precīzāku un savlaicīgāku pacienšu riska stratifikāciju un palīdzēt lēmumu pieņemšanā par KV ārstēšanas vai profilakses stratēģiju.
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    Identifying Genetic Factors Associated with Breast or Ovarian Cancer Risk in BRCA1 Pathogenic Variant Carriers. Doctoral Thesis
    (Rīga Stradiņš University, 2024) Berga-Švītiņa, Egija; Miklaševičs, Edvīns; Vilne, Baiba
    Breast cancer (BC) is a most prevalent cancer among women globally and ovarian cancer (OC) is also a significant healthcare burden, ranking eighth in terms of incidence and mortality in females. The aetiology of these malignancies involves a complex interplay between modifiable and non-modifiable risk factors. Among these, genetic predisposition, particularly pathogenic variants (PVs) in BRCA1 gene, significantly elevate a risk of BC or OC development. However, BC and OC risk for germline BRCA1 PV carriers differ by individual and are affected by genetic factors. The aim of this study is to explore genetic factors that might modulate BC and OC risk and to assess the effect of polygenic risk score (PRS) to estimate the overall genetic risk of a women carrying region-specific germline BRCA1 PVs to develop BC or OC due to additional genetic variations. We performed a genome-wide association study (GWAS) in 406 female BRCA1 PV (c.4035del or c.5266dup) carriers, affected with BC or OC vs. unaffected individuals, followed by functional annotations of the most significantly associated single nucleotide variants (SNVs). Next, we investigated recently developed novel genome-wise PRS association with BC and OC risk in BRCA1 PV carriers. A binomial logistic regression model was applied to assess the association of PRS with BC or OC development risk. In BC patients, the most significantly associated SNV was rs2609813 (p = 2.33 × 10−7, odds ratio (OR) = 0.28) in FAM107B gene (genomic position (GRCh37) 10:14800320). The variant is intronic in the protein coding gene and predicted to be a regulatory region variant. The second most significant BC-associated SNV was rs4688094 (p = 7.76 × 10−7, OR = 0.38) in long non-coding RNA (lncRNA) gene (genomic position (GRCh37) 3:118003477) and the most significant OC-associated SNV was rs79732499 (p = 1.38 × 10−7, OR = 0.00031) located in genomic position (GRCh37) 20:3404208 and is predicted to be a regulatory region variant located in enhancer. Both variants are in the non-coding genome. This suggests that they may influence gene expression or other regulatory processes rather than directly altering protein structure or function. Due to the small sample size, our results did not reach a genome-wide significance of p = 5 × 10−8. Regarding PRS calculations, best-fitting BayesW PRS model could effectively predict the individual’s BC risk (OR = 1.37; 95 % confidence interval (CI) = 1.03–1.81, p = 0.029 with area under receiver-operator curve (AUC) = 0.76). At the same time, none of the applied PRS was a good predictor of OC development risk, suggesting the need for further investigation in larger OC cohort. The results of this study can be used as preliminary data for a more comprehensive study and might contribute to customised PRS development for BRCA1 PV carriers. Previously developed BayesW PRS model contributed to assessing the risk of developing BC for germline 4 BRCA1 PV (c.4035del or c.5266dup) carriers and may facilitate more precise and timelier patient stratification and decision-making to improve the current BC treatment or even prevention strategies.
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    Identifying Genetic Factors Associated with Breast or Ovarian Cancer Risk in BRCA1 Pathogenic Variant Carriers. Summary of the Doctoral Thesis
    (Rīga Stradiņš University, 2024) Berga-Švītiņa, Egija; Miklaševičs, Edvīns; Vilne, Baiba
    Breast cancer (BC) is a most prevalent cancer among women globally and ovarian cancer (OC) is also a significant healthcare burden, ranking eighth in terms of incidence and mortality in females. The aetiology of these malignancies involves a complex interplay between modifiable and non-modifiable risk factors. Among these, genetic predisposition, particularly pathogenic variants (PVs) in BRCA1 gene, significantly elevate a risk of BC or OC development. However, BC and OC risk for germline BRCA1 PV carriers differ by individual and are affected by genetic factors. The aim of this study is to explore genetic factors that might modulate BC and OC risk and to assess the effect of polygenic risk score (PRS) to estimate the overall genetic risk of a women carrying region-specific germline BRCA1 PVs to develop BC or OC due to additional genetic variations. We performed a genome-wide association study (GWAS) in 406 female BRCA1 PV (c.4035del or c.5266dup) carriers, affected with BC or OC vs. unaffected individuals, followed by functional annotations of the most significantly associated single nucleotide variants (SNVs). Next, we investigated recently developed novel genome-wise PRS association with BC and OC risk in BRCA1 PV carriers. A binomial logistic regression model was applied to assess the association of PRS with BC or OC development risk. In BC patients, the most significantly associated SNV was rs2609813 (p = 2.33 × 10−7, odds ratio (OR) = 0.28) in FAM107B gene (genomic position (GRCh37) 10:14800320). The variant is intronic in the protein coding gene and predicted to be a regulatory region variant. The second most significant BC-associated SNV was rs4688094 (p = 7.76 × 10−7, OR = 0.38) in long non-coding RNA (lncRNA) gene (genomic position (GRCh37) 3:118003477) and the most significant OC-associated SNV was rs79732499 (p = 1.38 × 10−7, OR = 0.00031) located in genomic position (GRCh37) 20:3404208 and is predicted to be a regulatory region variant located in enhancer. Both variants are in the non-coding genome. This suggests that they may influence gene expression or other regulatory processes rather than directly altering protein structure or function. Due to the small sample size, our results did not reach a genome-wide significance of p = 5 × 10−8. Regarding PRS calculations, best-fitting BayesW PRS model could effectively predict the individual’s BC risk (OR = 1.37; 95 % confidence interval (CI) = 1.03–1.81, p = 0.029 with area under receiver-operator curve (AUC) = 0.76). At the same time, none of the applied PRS was a good predictor of OC development risk, suggesting the need for further investigation in larger OC cohort. The results of this study can be used as preliminary data for a more comprehensive study and might contribute to customised PRS development for BRCA1 PV carriers. Previously developed BayesW PRS model contributed to assessing the risk of developing BC for germline 4 BRCA1 PV (c.4035del or c.5266dup) carriers and may facilitate more precise and timelier patient stratification and decision-making to improve the current BC treatment or even prevention strategies.