Participants and Phenotyping

was recruited as previously described (2,20–22). The Ashkenazi population is descended from a founder pop- ulation (estimated to be several thousands) originating in the 15th century. This ‘‘founder effect’’ resulted in a population both culturally and genetically homogeneous, from which several disease-related genes have been successfully identified (23). Most of our study group were born in the United States, or moved there prior to World War II. We report here on 118 Ashkenazi probands with exceptional longevity (defined as living independently at age 95 years or older) whose adiponectin and body mass index (BMI) were measured; birth certificates or dates of birth as stated on passports were used to verify the participants’ ages. DNA was available from an additional 54 probands for a total of 172 probands used in the genotype frequency analysis. Offspring of the long-lived probands consisted of 228 participants (with adiponectin levels and BMI measure- ments as well), half of whom were women, with a mean age of 68 years (range 50–92 years). DNA was available for an additional 55 offspring for a total of 283 offspring used in the frequency analysis. The control group consisted of spouses of the offspring (n ¼ 78) with adiponectin and BMI measurements and a mean age of 76 (range 59–94) years. An additional 48 spouses as well as a group of indepen- dently recruited Ashkenazi Jews from the Einstein Aging Study (n ¼ 167) (24), for a total of 293 control participants (mean age 77 [range 51–94] years), were included in the frequency analysis (neither phenotypic significant nor geno- typic significant differences were observed between the two control groups). Controls who had parents older than the usual survival age (.85 years) were excluded. The mean age of the entire control group was 77 years [range 51–94 years]; 59.9% were women. Thus a total of 424 individuals with adiponectin and BMI levels were available for quantitative/metabolic syndrome traits, and a total of 748 individuals were available for genotype frequency analysis. Written informed consent was obtained in accor- dance with the policy of the Committee on Clinical Inves- tigation of the Albert Einstein College of Medicine.

Genotyping

and contains three exons, one noncoding and two coding. From public databases and previous publications (3,16), we selected eight single nucleotide polymorphisms (SNPs) of ADIPOQ (rs17300539 [promoter], rs266729 [promoter], rs182052 [promoter], rs822396 [intron 1], rs2241766 [exon 2; synonymous], rs1501299 [intron 2], rs17366743 [exon 3; synonymous], and a single base pair insertion/deletion polymorphism 2019 bp downstream of the ATG start codon in the 39 untranslated region [hereafter denoted as SNP þ2019]). These polymorphisms were chosen because they were distributed throughout the gene, had been previously reported to be common, and in some studies had been found to be associated with diabetes and related phenotypes (28).

Five SNPs (rs182052, rs822396, rs2241766, rs1501299, and rs17366743) were genotyped using Taqman (Applied Biosystems) according to the manufacturer’s instructions. The remaining three SNPs (rs17300539, rs266729, and SNP þ2019) were genotyped using the PSQ HS 96A Pyrose- quencer according to the manufacturer’s methods (Pyrose- quencing, Uppsala, Sweden; www.pyrosequencing.com). Primer sequences are available from the authors upon re- quest. All polymorphisms were found to be in Hardy– Weinberg equilibrium in the control group except rs1501299 (p ¼ .0005), which was excluded from further analysis.

Statistical Analysis

Data in Table 1 are expressed as mean (standard error [SE]). Crude means are shown. Triglycerides, which were not normally distributed, were ln-transformed for analysis and back-transformed for presentation. Three comparisons have been established: (i) between probands and controls where crude data were adjusted for BMI (except BMI, % fat, sex, and age) and sex (except sex and age); (ii) between offspring and controls unadjusted crude data; and (iii) between offspring and controls where crude data were adjusted for age (except age and sex), sex (except sex), and BMI (except age, sex, BMI, and % fat).

examination were performed as previously described (2,20,21). The presence of metabolic syndrome was deter- mined using National Cholesterol Education Program (NCEP), Adult Treatment Panel III (ATP III) criteria (25). Percentage body fat was determined using bioelectric impedance analysis (BIA), performed with a Tanita BIA body fat analyzer (Body Fat Monitor Scale, BF-625; Tanita Corporation of America Inc., Arlington Heights, IL). BIA is used in many of the epidemiological studies including the age group of the offspring and controls, and has been shown to be better representative of risks associated with increased fat mass compared to BMI. Therefore, it should be helpful

Associations of adiponectin levels with other variables were estimated using regression on an indicator variable for group, stratifying for age, sex, and BMI. In defining strata for age, cut points of 65, 70, 75, 80, and 85 years were used (Figure 1). Spearman correlations for BMI, % fat, and age were adjusted for age and sex (except age). Spearman

Table 1. Characteristics of Study Populations