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Predictive value of 8 genetic Loci for serum uric Acid concentration


Gunjača, Grgo; Boban, Mladen; Pehlić, Marina; Zemunik, Tatijana; Budimir, Danijela; Kolčić, Ivana; Lauc, Gordan; Rudan, Igor; Polašek, Ozren
Predictive value of 8 genetic Loci for serum uric Acid concentration // Croatian medical journal, 51 (2010), 1; 23-31 doi:10.3325/cmj.2010.51.23 (međunarodna recenzija, članak, znanstveni)


Naslov
Predictive value of 8 genetic Loci for serum uric Acid concentration

Autori
Gunjača, Grgo ; Boban, Mladen ; Pehlić, Marina ; Zemunik, Tatijana ; Budimir, Danijela ; Kolčić, Ivana ; Lauc, Gordan ; Rudan, Igor ; Polašek, Ozren

Izvornik
Croatian medical journal (0353-9504) 51 (2010), 1; 23-31

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Uric acid; prediction; data mining; SNP; genome-wide association; variance

Sažetak
To investigate the possibility to predict individual serum uric acid concentrations based on genomic information. Three population samples were investigated: isolated communities of the Adriatic Islands of Vis (n=980) and Korcula (n=944), and general population of Split (n=507). Serum uric acid concentration was correlated to the genetic risk score based on eight previously described genes: PDZK1, GCKR, SLC2A9, ABCG2, LRRC16A, SLC17A1, SLC16A9 and SLC22A12, represented by a total of 16 single-nucleotide polymorphisms (SNPs). The data were analyzed using classification and regression tree (CART) and general linear modeling (GLM). The most important variable for uric acid prediction with CART was genetic risk score in men and age in women. The percent of variance for any single SNP in predicting serum uric acid concentration varied from 0.0-2.0%. The use of genetic risk score explained 0.1-2.5% of uric acid variance in men and 3.9-4.9% in women. The highest percent of variance was obtained when age, gender and genetic risk score were used as predictors, with a total of 30.9% of variance in pooled analysis. Despite overall low percent of explained variance, uric acid seems to be among the most predictive human quantitative traits based on the currently available SNP information. The use of genetic risk scores provides a valuable approach in genetic epidemiology and increases the predictability of human quantitative traits based on genomic information, compared to single SNP approach.

Izvorni jezik
Engleski

Znanstvena područja
Biologija, Temeljne medicinske znanosti, Kliničke medicinske znanosti



POVEZANOST RADA


Projekt / tema
216-1080315-0293 - Genetska epidemiologija šećerne bolesti tip 1 u populaciji Hrvatske (Tatijana Zemunik, )
216-1080315-0302 - Odrednice zdravlja i bolesti u općoj i izoliranim ljudskim populacijama (Ozren Polašek, )
216-2160547-0537 - Kardiovaskularni učinci vina i njegovih sastojaka (Mladen Boban, )

Ustanove
Medicinski fakultet, Zagreb,
Medicinski fakultet, Split

Časopis indeksira:


  • Current Contents Connect (CCC)
  • Web of Science Core Collection (WoSCC)
    • Science Citation Index Expanded (SCI-EXP)
    • SCI-EXP, SSCI i/ili A&HCI
  • Scopus
  • MEDLINE


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