This dataset presents genotype data for 43 single nucleotide polymorphisms (SNPs) that have been genotyped in an anonymised sample of 314 oldest-old individuals (85+ years) from Croatia. The SNPs are located in or near candidate genes for longevity, and were selected from publicly available literature databases (PubMed and repositories specialized for human longevity such as https://genomics.senescence.info/longevity/, http://ageing-map.org/). They were selected based on their strong or repeatedly reported association with human longevity and involvement in various metabolic pathways. Genotyping was performed by Kompetitive Allele Specific PCR (KASP) on genomic DNA isolated from peripheral blood using the salting-out method. The dataset also contains recoding of the genotypes for each participant according to their association with longevity: a value of 2 was assigned to the homozygous genotype of longevity allele, a value of 1 to the heterozygous genotype, and a value of 0 to the homozygous genotype of an allele not associated with longevity in our sample. In cases where there were less than 10 of either homozygous genotypes, and in cases where a dominant or recessive coding gave a more significant result in further analyses, they were additionally recoded as binary variables with only the values 0 and 1, with heterozygote being added to the less common homozygote. This data was used to perform logistic regression analyses to create the best models for predicting survival to the ages of 90 and 95. Those models were then used to create genetic risk scores (here named genetic longevity scores, GLS) for predicting that phenotype, which are shown in this dataset as well. Information about the selected SNPs is also presented: rs code, nearest gene, chromosome position, and references for literature sources where association with longevity is reported; along with data that refers to the studied Croatian population: alleles (major/minor), minor allele frequencies (MAF), genotyping success rate, and HWE p-values.

Research funded by Croatian Science Foundation (grant number IP-01-2018-2497).