Background and aims: Diabetic complications and namely nephropathy (DN) contribute significantly to morbidity and mortality of diabetic patients. Their development and progression is influenced by several factors incl. treatment/compensation of diabetes, presence of co-morbidities, life style and genetic factors. The latter one is being intensively studied as potentially very powerful tool of personalised medicine. Using follow-up data from prospective study of diabetic population of South Moravia region of Czech Republic the aim of our study was to analyse contribution of genetic factors to progression of DN (primary end-point) and to major non-fatal cardiovascular event (MCVE), cardiovascular (CVM) and all-cause mortality (ACM) as secondary end-points using combination of analytical approaches. Materials and methods: Study comprised a total of 459 diabetic subject with variable stage of DN (i.e. normoalbuminuria, persist. microalbuminuria, proteinuria and ESRD) prospectively followed for a median of 39 [IQR 21 - 59] months. Following end-points were considered:  progression of DN by stage,  MCVE (non-fatal myocardial infarction or stroke, limb amputation),  CVM (fatal myocardial infarction, stroke, heart failure or sudden death) and  ACM. Presently, 86 single nucleotide polymorphisms (SNPs) in 37 candidate genes were genotyped. After quality control, 82 SNPs remained. For each endpoint and SNP, two association statistics were computed, chi-square in 2x2 tables of alleles and chi-square in 2x3 tables of genotypes. Associated P-values were assessed in 10,000 permutation samples with the Sumstat program. For nominal P values <0.05 a corresponding experiment-wise significance levels were corrected for multiple testing. Selected best associated variants were subsequently used in time-to-event analysis of individual end-points. Results: Kaplan-Meier curves were constructed for four best associated SNPs for given end-points: (1) progression of DN between genotype groups of cytochrome b-245 242C/T (CYBA, rs4673) log rank test P=0.03738, (2) MCVE and ACM vs. coagulation factor V R506Q genotypes (F5, rs6025) log rank test P=0.02539 and P=0.00151, respectively, and (3) ACM vs. dimethylarginine dimethylaminohydrolase 2 449C/G (DDAH2, rs805305) and DDAH2 1151A/C (rs805304) genotypes, log-rank test marginally significant (P=0.06030 and P=0.06710, respectively). In case of CYBA 242C/T heterozygotes and TT homozygotes were risk genotypes for DN progression, in case of F5 R506Q heterozygotes were associated with MCVE and ACM. Conclusion: In the pilot analysis of our on-going prospective study we identified F5 506RQ and CYBA 242CT+TT (marginally also DDAH2) genotypes as risk factors for progression of DN, MCVE and ACM. Using combined approach of multi-locus and time-to-event analysis it is possible to analyse large amount of genetic and clinical data generated in follow-up studies.