years, mean age: 78.9 8.9 years)—6 male and 11 female, and 23 family members (age 18–57 years)—9 male and 14 female were included. The control group consisted of 105 randomly selected, matched for geographical distribution healthy controls aged 25–53 years (40 male and 65 female). For the T-cell subset study 47 individuals were randomly selected among the total control population. Twenty one of ^ them were young (mean age: 27.3 2.4 years) and 26- ^ middle-aged (mean age: 40.4 5.8 years) subjects with a male/female ratio 1:2 in the two groups. All individuals included in the analysis did not suffer from any chronic physical or mental disease, and did not experience any acute infection in the last 4 months before the enrolment. Their hematological and biochemical parameters were within the normal ranges. The blood samples were obtained after an informed consent.

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 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 GENOVISIONe kits.

2. Material and methods

Gene polymorphism of TNFa, TGFb1, IL-10, IL-6, and IFNg was tested by PCR-SSP method with Cytokine Genotyping Tray OneLambda. Eight polymorphism, previously shown to be associated with the level of cytokine production were analyzed (Table 1).

2.1. Subjects

Ten families with longevity members from the Bulgarian population were analyzed in the present study. The following criteria for family selection were applied: two generation longevity members (octogenarians and nona- genarians) and no family history of inherited diseases. A total of 40 individuals: 17 unrelated elderly (age 65–90

2.3. Flow cytometric analysis of T-cell

Completebloodcellcountswereassessedforeachsubject. Peripheral blood lymphocyte subsets were determined by

Table 1

between analyzed cytokine gene polymorphism and level of

Cytokine polymorphism Genotype Level of production Reference TNF-a (2308) G/G Low Kroeger et al. (2000) G/A, A/A High Haung et al. (1999) TGF-b1 (codons 10,25) T/T G/G, T/C G/C High Awad et al. (1998) T/C G/C, C/C G/G, T/T G/C Intermediate Awad et al. (1998) C/C G/C, C/C C/C, T/T C/C, T/C C/C Low Awad et al. (1998) IL-10 (21082, 2 819, 2 592) GCC/GCC High Crawley et al. (1999) GCC/ACC, GCC/ATA Intermediate Maurer et al. (2000) ACC/ACC, ACC/ATA, ATA/ATA Low Crawley et al. (1999) IL-6 (2174) G/G G/C High Fishman et al. (1998) C/C Low Fishman et al. (1998) IFN-g (þ874) T/T High Turner et al. (1997) T/A Intermediate Turner et al. (1997) A/A Low Turner et al. (1997)

E. Naumova et al. / Experimental Gerontology 39 (2004) 637–644

Flow cytometric analysis using a panel of monoclonal antibodies (Becton-Dickinson, USA). Direct four-color immunofluorescence in whole blood was performed accord- ing to standard techniques. FACSCalibur flow cytometer, CellQuest and Multitest softwares (Becton Dickinson, USA) were used for data acquisition and analysis. Results were documented as % positive cells and cells/mm3.

the Arlequin program v1.1 (Shneider et al., 1996). Standard deviations were calculated from 100 bootstrap iteractions. Hardy–Weinberg equilibrium was tested by two methods: a hidden Markov chain with 100,000 steps, implemented in the Arlequin program and a conventional x2 heterosigosity test. Arlequin software was also used to estimate through an expectation-maximization (EM) (Slatkin and Excoffier, 1996) algorithm maximum-likelihood frequencies of hap- lotypes defined in family studies.

Comparisons of HLA allele and haplotype frequencies, and pro- and anti-inflammatory cytokine genotypes between elderly individuals and controls were performed by x2 test

HLA class I and class II allele frequencies were estimated by maximum-likelihood analysis using

Table 2

class I and class II allele frequencies in elderly Bulgarians compared to the controls

HLA allele Allele frequency P Pc HLA allele Allele frequency P Pc Elderly Controls Elderly Controls HLA-A HLA-C *01 0.118 0.099 *01 0.059 0.071 *02 0.412 0.333 *02 0.000 0.090 ,0.05 ns *03 0.088 0.057 *03 0.088 0.052 *11 0.088 0.056 *04 0.235 0.167 *23 0.029 0.040 *05 0.000 0.038 *24 0.059 0.131 *06 0.029 0.071 *25 0.029 0.020 *07 0.265 0.205 *26 0.029 0.048 *08 0.029 0.048 *29 0.000 0.016 *12 0.118 0.138 *30 0.029 0.016 *14 0.029 0.038 *31 0.059 0.036 *15 0.118 0.043 *32 0.029 0.044 *16 0.000 0.029 *33 0.000 0.032 *17 0.029 0.009 *36 0.000 0.004 *68 0.000 0.040 DRB1 *69 0.029 0.008 *01 0.118 0.143 HLA-B *03 0.059 0.075 *07 0.000 0.048 *04 0.088 0.095 *08 0.059 0.032 *07 0.000 0.060 *13 0.029 0.016 *08 0.029 0.020 *14 0.029 0.036 *1001 0.000 0.012 *15 0.043 0.016 *11 0.235 0.218 *18 0.147 0.083 *12 0.059 0.008 ,0.05 ns *27 0.000 0.048 *13 0.176 0.115 *35 0.265 0.131 ,0.05 ns *14 0.059 0.067 *37 0.000 0.004 *15 0.059 0.075 *38 0.029 0.036 *16 0.118 0.111 *39 0.029 0.024 *40 0.029 0.075 DQB1 *41 0.029 0.012 *02 0.059 0.098 *42 0.000 0.004 *03 0.382 0.402 *44 0.088 0.087 *04 0.059 0.009 *47 0.000 0.008 *05 0.294 0.366 *49 0.029 0.028 *06 0.206 0.116 *50 0.000 0.020 *51 0.147 0.194 *52 0.000 0.036 *53 0.000 0.008 *55 0.059 0.020 *56 0.000 0.008 *57 0.000 0.012 *58 0.000 0.016

E. Naumova et al. / Experimental Gerontology 39 (2004) 637–644

or Fisher’s exact test when appropriate. Bonferoni correc- tion for multiple comparisons was applied. For T cell subset analysis the statistical significance was evaluated using non- parametric Mann–Whitney U-test. P-value lower than 0.05 was considered to indicate a significant difference between groups.