Research objectives: Parkinson's disease is a common neurodegenerative disorder that affects up to 1% of the population over 65 years of age, with predictions of a gradual increase in prevalence up to 2% in the next few decades. The genetic basis of the disease can be found in 15% to 30% of patients, with the number increasing thanks to new sequencing technologies. In previous research, the South Slavic population was not represented, so the specific goal of this research is to determine the frequency of known genetic variants in Croatian patients. Materials and methods: Inclusion criteria for the trial were confirmed Parkinson's disease, using the most relevant clinical diagnostic criteria. All subjects gave informed consent and filled out a genetic questionnaire before blood sampling and were divided into three groups depending on the type of origin (early, familial, and sporadic). The entire exome sequencing procedure was done according to established methods. Results: 152 patients were included in the study. In the total cohort, 14 causative mutations were detected according to the criteria declared as pathogenic and probably pathogenic (GBA, n=11; PRKN, n=2; ITM2B n=1). Furthermore, in the entire cohort of 152 patients, 41 of them had at least one variant of unclear significance (n=41, 26.97%). Pathogens were present in all groups, with differences in frequency: early onset - 12.2%, familial onset - 12.5%, sporadic onset - 5.63%. For variants of unclear significance, the frequency within the groups was as follows: early onset - 29.27%, familial onset - 15%, sporadic onset - 32.39% Conclusion: Whole-exome sequencing has applications in research into the genetic basis of Parkinson's disease. Pathogenic variants were found in all three groups of subjects, most often in the GBA gene, which corresponds to current knowledge for European populations. In addition, several interesting variants of unclear significance were discovered, which require further analysis. This approach has both research and clinical value since individual prediction of specific risk factors is possible.