A common genetic basis of various substance and behavioral addictions has long been suggested considering the rate of co-occurrences and the overlaps in psychological and molecular mechanisms. The goal of the current study is to investigate possible genetic overlaps between different types of substance-related, addictive and compulsive behaviors conducted as part of the Psychological and Genetic Factors of Addictions (PGA) study. The genetic analysis of both substance and behavioral addictions was conducted within the same cohort of 3003 Hungarian young adults. Participants were assessed for a wide range of potentially addictive substances (nicotine, alcohol, cannabis, and other drugs) and potentially addictive behaviors (internet use, gaming, social networking site use, gambling, exercising, hair-pulling and eating) in order to investigate possible shared genetic factors utilizing the large sample of the PGA study. A Genetic Addiction Risk Score (GARS) was also calculated for the participants based on a set of 11 genetic polymorphisms in order to estimate addiction vulnerability risk scores for possible future prevention strategy as well as personalized pharmacological and non-pharmacological therapy. The genetic association analysis included 32 single-nucleotide polymorphisms (SNPs) selected from earlier GWAS and candidate gene association studies in the literature in order to best represent the expected distribution pattern of the various phenotypes assessed in the sample. The genotyping was carried out by the The QuantStudio™ 12K Flex OpenArray® System, fluorescent intensities were evaluated by the QuantStudio 12K Flex Software and the Thermo Fisher Cloud service. The genetic association analysis was conducted applying an allele-wise design. The phenotype measures were assessed using multiple questionnaires. The GARS score was calculated based on the risk scores of 11 genetic variants (SNPs and VNTRs). The statistical analyses revealed 29 nominally significant genetic associations, from which nine survived FDRbl correction for multiple testing. Four of the nine significant associations were observed between the FOXN3 rs759364 SNP and certain potentially addictive behavioral traits: frequency of alcohol consumption and mean scores of scales assessing internet addiction, gaming disorder and exercise addiction. Significant associations were found between GDNF rs1549250, rs2973033, CNR1 rs806380 and DRD2/ANKK1 rs1800497 variants and the ‘lifetime other drugs’ variable. The GARS score was calculated for each participants and significant score differences have been identified between different subgroups of the cohort. The results indicate a pleiotropic effect, ie. that certain genetic factors may contribute to multiple forms of addiction. Based on the presented results, rs759364 of FOXN3 is shown to constitute genetic risk for increased alcohol consumption, internet use, gaming and exercise, while rs1549250, rs2973033 of GDNF may be non-specific genetic risk factors for various types of addictive behaviors. The GARS scoring is a useful tool to evaluate the individual susceptibility for substance use disorders. Future studies should examine functional correlates and potential mechanisms underlying these relationships.