4 research outputs found
LENGTH HETEROPLASMY IN THE PREDOMINATE MITOCHONDRIAL DNA HAPLOGROUPS IN THE CROATIAN POPULATION
Mitochondrial control region represents the most variable segment of the mitochondrial genome. The frequency and pattern of heteroplasmy has been described in several studies; however, none of the reports documented the Croatian population. In the present study, we screened the control region (1122 bp) of 95 individuals belonging to two predominant mitochondrial phylogenetic branches in the Croatian population, haplogroups H and U. Length heteroplasmy occurred in polycytosine (poly-C) tracts within three hypervariable segments of the control region with the following frequencies: HVSI - 26.3%, HVSII - 52.6% and HVSIII - 7.4%. Furthermore, the association between certain polymorphisms in HVSI and length heteroplasmy was investigated. Our results indicate that only polymorphisms located in the poly-C tract are associated with HVSI length heteroplasmy. The T to C transition at np 16189 is significantly associated with the occurrence of length heteroplasmy (p<0.0001). This effect was even stronger if the C insertion was present in the position 16193. The data support the hypothesis that an uninterrupted poly-C tract of more than eight cytosines leads to length heteroplasmy. Length heteroplasmy associated with the T to C substitution in np 16189 was predominantly found in haplogroup U
LENGTH HETEROPLASMY IN THE PREDOMINATE MITOCHONDRIAL DNA HAPLOGROUPS IN THE CROATIAN POPULATION
Mitochondrial control region represents the most variable segment of the mitochondrial genome. The frequency and pattern of heteroplasmy has been described in several studies; however, none of the reports documented the Croatian population. In the present study, we screened the control region (1122 bp) of 95 individuals belonging to two predominant mitochondrial phylogenetic branches in the Croatian population, haplogroups H and U. Length heteroplasmy occurred in polycytosine (poly-C) tracts within three hypervariable segments of the control region with the following frequencies: HVSI - 26.3%, HVSII - 52.6% and HVSIII - 7.4%. Furthermore, the association between certain polymorphisms in HVSI and length heteroplasmy was investigated. Our results indicate that only polymorphisms located in the poly-C tract are associated with HVSI length heteroplasmy. The T to C transition at np 16189 is significantly associated with the occurrence of length heteroplasmy (p<0.0001). This effect was even stronger if the C insertion was present in the position 16193. The data support the hypothesis that an uninterrupted poly-C tract of more than eight cytosines leads to length heteroplasmy. Length heteroplasmy associated with the T to C substitution in np 16189 was predominantly found in haplogroup U
The role of biochemical methods in the diagnosis of inherited metabolic diseases in the new technology era
U izazovnom podruÄju nasljednih metaboliÄkih bolesti težimo preventivnom, prediktivnom, personaliziranom i participativnom pristupu bolesniku. Suvremene laboratorijske tehnologije u podruÄju ā-omikaā: genomike, transkriptomike, epigenomike, proteomike, glikomike, metabolomike i lipidomike pružaju velike dijagnostiÄke moguÄnosti, omoguÄuju bolje patofizioloÅ”ko razumijevanje poremeÄaja kao i razvoj novih terapijskih pristupa. Jedan od vodeÄih izazova u ovom podruÄju postaje integracija i kliniÄka važnost velikog broja dobivenih podataka. UnatoÄ dostupnosti mnogobrojnih novih tehnologija, biokemijske metode i nadalje zauzimaju važno mjesto u dijagnostici i praÄenju tijeka lijeÄenja rijetkih bolesti. U kliniÄkoj praksi, osim ciljane metabolomike, neciljana metabolomika postaje neizostavna tehnologija koja omoguÄuje pronalazak novih specifiÄnih biljega, metabolomiÄko profiliranje te personaliziran pristup lijeÄenju.In a challenging field of inherited metabolic diseases, the aim is preventive, predictive, personalized and participative approach to the patient. Modern laboratory technologies in the following omics fields: genomics, transcriptomics, epigenomics, proteomics, glycomics, metabolomics and lipidomics, provide great diagnostic possibilities, allow better pathophysiological understanding of disorders and enable development of novel therapeutic approaches. One of the principal challenges in this area turns out to be the integration and clinical significance of a large number of obtained data. Despite availability of numerous new technologies, biochemical methods still have an important place in diagnostics and monitoring of the therapy course of rare diseases. In addition to targeted metabolomics, untargeted metabolomics is in clinical practice becoming a dependable technology that allows detection of novel specific markers, metabolic profiling and personalized approach to treatment