All the subjects included in the study had given their informed consent.

Materials and Methods

Lipidemic Parameters

Samples

Venous blood samples were collected in EDTA tubes after 12 h overnight fast. Serum concentration of to- tal cholesterol (TC), HDL cholesterol (HDL-C), and Tryglycerides (TG) were measured by enzymatic col- orimetry methods by commercial kits (Dade Behring) using an automated chemistry analyser (DimensionR Clinical Chemistry System). Log transformation of 10 Tryglyceride values was made before analysis, because of their skewed distribution. Serum LDL cholesterol con- centration (LDL-C) was calculated by the Friedewald’s − formula: LDL-C = TC HDL-C–TG/5 (Friedewald ± et al. 1972). Lipid values were expressed as mean SD, mg/dL. All the hematological analyses were carried out at the Italian National Research Centre on Ageing (INRCA, Cosenza).

in Calabria (southern Italy) in 1999 for the present study, except for centenarians whose recruitment started in 1994. Subjects older than 18 years, born and living in Calabria, and whose parents and grandparents were na- tives of the area, were invited to take part in the study. For each subject who complied with the request, his/her origin in Calabria was verified in the birth-registers of the Municipality Office where the subject was born. Routine blood analyses were carried out and, in addi- tion, subjects older than 60 years underwent a complete clinical and geriatric assessment. A total of 800 unre- lated subjects (327 males and 473 females), none tak- ing regular medication, and all free of clinically overt pathologies, and having emato-chemical parameters in the normal sex- and age-specific range, were enrolled in the study. The sample comprised 304 subjects aged 18–45 years (median age 29 years), 267 subjects aged

DNA Analyses

DNA was extracted from blood buffy coats following − standard procedures. APOA1-MspI-RFLP ( 75nt from

S. Garasto et al.

the transcription starting site), APOC3-SstI-RFLP 31 (3 UTR, 3238nt), and APOA4-HincII-RFLP (Asp / 127 Ser ) were analysed by restriction analysis after PCR- 127 amplification of the DNA regions containing the restri- ction sites. Regions, primers and PCR experimental conditions are available on request from the e-mail address of the corresponding author ( g.debenedictis@ unical.it).

locus on the lipidemic parameters were estimated ac- cording to Christiansen & Feldman (1986). The 95% α α confidence intervals of and were calculated A P by bootstrap (10,000 replications, MATLAB Statistic toolbox).

Results

Genotypic and allelic data of APOA1-MspI-RFLP, APOC3-SstI-RFLP, and APOA4-HincII-RFLP were analysed in three age classes (18–45 years; 46–80 years; 81–109 years) for each sex. All the sample groups were > in HWE (p 0.05).

Statistical Analyses

For single markers, allele frequencies were by counting genes from the observed genotypes χ2 tests were applied to verify Hardy-Weinberg librium (HWE) in each sample. Homogeneity of typic and allelic frequency distributions among the groups of different age (18–45 years; 46–80 years; 109 years) in each sex was tested by a chi-squared test.

in males (Table 1a) among the age-related genotypic counts (χ2 = 9.63 with 4 df., p = 0.045 with Yates’ correction). Accordingly, allele counts were different among the three age-groups (χ2 = 8.29 with 2 df., p = 0.016). On inspecting the data, the P allele fre- quency showed a minimum (and the A allele frequency a maximum) in the intermediate age-class. To investi- gate this finding and outline the age-related frequency trajectory of the P (or A) allele, the group of 327 males was sub-divided into five age-classes (18–25 years; 26– 45 years; 46–65 years; 66–80 years; 81–109 years), and P allele frequency was estimated in each class. A concave frequency trajectory was observed, the significance of which was tested as described in the methods. The es- timated value of the leading coefficient b = 0.217 was 2 significantly larger than zero, because the central 95% β empirical confidence interval of was 0.112–0.495. 2 Out of the 10,000 trajectories simulated by bootstrap, 9,987 were concave, only 1 was convex, 10 were mono- tone increasing, and 2 monotone decreasing. By assum- ing that a trend in the data is significant if more than 95% of the simulated trajectories show that trend, the concave pattern of the P allele frequency fully satis- fied this requirement. Denoting age as x, and letting f (x) be the age-related frequency trajectory of the al- P lele P, the age-related frequency trajectory of the A allele (absence of the restriction site) was given by f (x) = A 1 – f (x) because only two alleles are present in the P population. Fig. 1 shows the relative frequency of the P allele in the five age-groups, the fitting curve, and the lower and upper envelopes of the 10,000 simulated

The age-related frequency trajectory of the APOA1 allele P (Presence of the MspI restriction site) was anal- ysed by least squares method. MATLAB function poly- fit was used to fit a 2nd degree polynomial y = β + 0 β x/x¯ + β x2/x¯2 to the frequencies of allele P observed 1 2 in five classes of age (18–25 years; 26–45 years; 46–65 years; 66–80 years; 81–109 years), thus obtaining esti- mates b , b , b . The mean of the ages of individuals 0 1 2 belonging to each age-class was taken as the x¯ value for that class. Ten thousand replicates of b , b , b were then 0 1 2 generated by the bootstrap method (MATLAB Statistic β toolbox), from which the empirical distribution of , 0 β β , was obtained and confidence limits were calcu- 1 2 lated for the age-related frequency trajectory.