AIMS: To improve sensitivity and specificity of the diabetes risk assessment of the population-based genetic screening used in the Finnish Diabetes Prediction and Prevention (DIPP) trial. METHODS: One thousand consecutive newborns enrolled in the DIPP were compared with 316 samples from children with Type 1 diabetes mellitus. A modification of the previously described technique based on hybridization of relevant PCR products with five lanthanide-labelled probes detected by time-resolved fluorometry (TRF) was used. A new probe was designed and allowed discrimination between DQB1*0602 and 0603 alleles, in addition to DQB1*02, *0301 or *0302, each of which required specific probes. A new, added screening strategy was developed for individuals carrying low-risk genotypes through specific typing of DQA1 *05 and *0201 alleles in DQB1*02 positive, and DRB1 typing for DR4 subtypes in DQB1*0302 positive subjects, with a new specifically designed high-resolution TRF-based DR4 subtyping technique. RESULTS: This two-step screening approach enhanced the sensitivity of the detection of genetic risk for Type 1 diabetes mellitus in this cohort up to 85.4%. In the general population cohort, 24.4% were identified for prospective follow-up, 2.6% of these are expected to develop Type 1 diabetes mellitus before the age of 15 years. Exclusive typing for HLA-DQB1 locus as an alternative screening strategy had sensitivities of 26.3-77.2% with general population cohorts of 2.3-23.1% identified for follow-up. CONCLUSIONS: The described strategy for genetic prediction of Type 1 diabetes mellitus relies on the convenient genotyping procedure and could be applied in large scale screening projects such as DIPP.
AIMS: To improve sensitivity and specificity of the diabetes risk assessment of the population-based genetic screening used in the Finnish Diabetes Prediction and Prevention (DIPP) trial. METHODS: One thousand consecutive newborns enrolled in the DIPP were compared with 316 samples from children with Type 1 diabetes mellitus. A modification of the previously described technique based on hybridization of relevant PCR products with five lanthanide-labelled probes detected by time-resolved fluorometry (TRF) was used. A new probe was designed and allowed discrimination between DQB1*0602 and 0603 alleles, in addition to DQB1*02, *0301 or *0302, each of which required specific probes. A new, added screening strategy was developed for individuals carrying low-risk genotypes through specific typing of DQA1 *05 and *0201 alleles in DQB1*02 positive, and DRB1 typing for DR4 subtypes in DQB1*0302 positive subjects, with a new specifically designed high-resolution TRF-based DR4 subtyping technique. RESULTS: This two-step screening approach enhanced the sensitivity of the detection of genetic risk for Type 1 diabetes mellitus in this cohort up to 85.4%. In the general population cohort, 24.4% were identified for prospective follow-up, 2.6% of these are expected to develop Type 1 diabetes mellitus before the age of 15 years. Exclusive typing for HLA-DQB1 locus as an alternative screening strategy had sensitivities of 26.3-77.2% with general population cohorts of 2.3-23.1% identified for follow-up. CONCLUSIONS: The described strategy for genetic prediction of Type 1 diabetes mellitus relies on the convenient genotyping procedure and could be applied in large scale screening projects such as DIPP.
Authors: R Hermann; M Knip; R Veijola; O Simell; A-P Laine; H K Akerblom; P-H Groop; C Forsblom; K Pettersson-Fernholm; J Ilonen Journal: Diabetologia Date: 2003-03-18 Impact factor: 10.122
Authors: S Laivoranta-Nyman; T Möttönen; R Hermann; J Tuokko; R Luukkainen; M Hakala; P Hannonen; M Korpela; U Yli-Kerttula; A Toivanen; J Ilonen Journal: Ann Rheum Dis Date: 2004-11 Impact factor: 19.103
Authors: Adriana Mimbacas; Fernando Pérez-Bravo; Jose Luis Santos; Carmen Pisciottano; Rosario Grignola; Gerardo Javiel; Ana Maria Jorge; Horacio Cardoso Journal: Eur J Epidemiol Date: 2004 Impact factor: 8.082
Authors: V Parikka; K Näntö-Salonen; M Saarinen; T Simell; J Ilonen; H Hyöty; R Veijola; M Knip; O Simell Journal: Diabetologia Date: 2012-03-23 Impact factor: 10.122
Authors: Igor C Borges; Dafne C Andrade; Maria Regina A Cardoso; Jorma Toppari; Mari Vähä-Mäkilä; Jorma Ilonen; Mikael Knip; Heikki Hyöty; Riitta Veijola; Olli Simell; Tuomas Jartti; Helena Käyhty; Olli Ruuskanen; Cristiana M Nascimento-Carvalho Journal: Clin Vaccine Immunol Date: 2016-11-04
Authors: Jarmo Hahl; Tuula Simell; Antti Kupila; Päivi Keskinen; Mikael Knip; Jorma Ilonen; Olli Simell Journal: Pharmacoeconomics Date: 2003 Impact factor: 4.981
Authors: H Viskari; J Paronen; P Keskinen; S Simell; B Zawilinska; I Zgorniak-Nowosielska; S Korhonen; J Ilonen; O Simell; A-M Haapala; M Knip; H Hyöty Journal: Clin Exp Immunol Date: 2003-09 Impact factor: 4.330
Authors: Satu Simell; Sanna Hoppu; Tuu Simell; Marja-Riitta Ståhlberg; Markku Viander; Taina Routi; Ville Simell; Riitta Veijola; Jorma Ilonen; Heikki Hyöty; Mikael Knip; Olli Simell Journal: Diabetes Care Date: 2010-01-07 Impact factor: 19.112