inclusion in the study were used: healthy elderly individuals with age over 75 years and no chronic physical or mental diseases, acute infections in the last 4 months, or abnormal hematological and biochemical parameters. The study group consisted of 17 elderly Bulgarians (mean age: 78.9 ± 8.9 years), six male and 11 female, and 23 family members (age range: 18-57 years), nine male and 14 female. The control group consisted of 105 randomly selected healthy controls aged 25-53 years (40 male and 65 female) matched for geographical distribution. For the T-cell subset study, 47 individuals were randomly selected from the total control population. Twenty-one of them were young (mean age: 27.3 ± 2.4 years) and 26 were middle-aged (mean age: 40.4 ± 5.8 years) subjects with a male/female ratio of 1:2 in the two groups.

2.2. HLA and cytokine gene polymorphism

In order to clarify immunogenetic markers contributing to successful aging, HLA and cytokine gene profiles were analyzed in healthy elderly Bulgarians. Family segregation analysis was performed to define the combined effect of haplotypes and immunophenotype profiles.

Genomic DNA was extracted from whole venous blood using the standard proteinase K digestion method followed by salting-out extraction and ethanol precipitation (Miller et al., 1988). HLA class I (HLA-A, -B, and -C) and class II (-DRB, and -DQB1) genotyping was performed by PCR-SSP method using GENOVISION kits.

Gene polymorphism of TNFα, TGFβ1, IL-10, IL-6, and IFNγ was tested by PCR-SSP method with Cytokine Genotyping Tray OneLambda. Eight polymorphisms, previously shown to be associated with the level of cytokine production, were analyzed (Table 1).

3. Results and discussion

The results of this study did not reveal any statistically significant allele and haplotype frequency differences between the elderly and control group. In families with two generations of longevity members, we did not observe HLA alleles and haplotypes associated with autoimmunity.

IL-10 genotype 21082G/A, 2819 C/C, 2592 C/C, related to intermediate production, was positively associated, while genotype 21082A/A, 2819 C/T, 2592 C/A, related to the low level of production, was negatively associated with longevity in Bulgarians. This effect was modulated by IL-6 and IFNγ genotypes associated with the low level of these pro-inflammatory cytokines.

Immunophenotypic studies indicated lower relative and absolute numbers of CD3+8+, CD8+28+, and CD8+57+ cells in elderly people. Analysis in families showed that although most pronounced in the elderly group, lower numbers of CD8+ T cells were also found in middle-aged and young members of the families compared to the age-matched controls. A progressive CD8+28+ cell subsets decline was seen with aging. In addition, we did not observe the immune risk phenotype which is a marker of increased inflammatory activity.

Based on the results of this study, it seems reasonable to suggest that a combination of specific immunogenetic and immunophenotype profiles could contribute to successful aging and maintaining healthy status in elderly individuals.

4. Conclusion

Aging is a complex process determined by genetic and environmental factors. The present study focused on immunogenetic markers contributing to successful aging in healthy elderly Bulgarians. The results suggest that a combination of specific immunogenetic and immunophenotype profiles could contribute to successful aging and maintaining a healthy status in elderly individuals. Further studies are necessary to confirm these findings and to investigate the underlying mechanisms.Family selection criteria were applied, including two generations of longevity members (octogenarians and nonagenarians) with no family history of inherited diseases. A total of 40 individuals were included, consisting of 17 unrelated elderly subjects (age 65-90). Complete blood cell counts were assessed for each subject, and peripheral blood lymphocyte subsets were determined using flow cytometric analysis with a panel of monoclonal antibodies (Becton-Dickinson, USA). Direct four-color immunofluorescence in whole blood was performed according to standard techniques. FACSCalibur flow cytometer, CellQuest and Multitest software (Becton Dickinson, USA) were used for data acquisition and analysis. Results were documented as % positive cells and cells/mm3.

Cytokine gene polymorphism was analyzed to determine the relationship between genotype and level of production. The cytokine gene polymorphism, genotype, and level of production are presented in Table 1. The statistical significance was evaluated using non-parametric Mann-Whitney U-test. A P-value lower than 0.05 was considered to indicate a significant difference between groups.

HLA class I and class II allele frequencies were estimated by maximum-likelihood analysis using the Arlequin program v1.1 (Shneider et al., 1996). Standard deviations were calculated from 100 bootstrap iterations. Hardy-Weinberg equilibrium was tested by two methods: a hidden Markov chain with 100,000 steps implemented in the Arlequin program and a conventional chi-square heterozygosity test. Arlequin software was also used to estimate through an expectation-maximization (EM) algorithm maximum-likelihood frequencies of haplotypes defined in family studies.

Comparisons of HLA allele and haplotype frequencies, as well as pro- and anti-inflammatory cytokine genotypes between elderly individuals and controls, were performed by chi-square test or Fisher's exact test when appropriate. Bonferroni correction for multiple comparisons was applied. For T cell subset analysis, the statistical significance was evaluated using non-parametric Mann-Whitney U-test. The differences were not statistically significant after correction of p-values.