Here, for testing the association of a number of polymorphic genes with longevity, we used a two- stage design, an approach that has proven to be useful for the identification of a number of genetic variants associated with pathological phenotypes such as cancer, ’ Crohn s disease, and migraine (Milne et al. 2006; Beckly et al. 2008; Corominas et al. 2009). We analyzed 317 SNPs in 104 selected genes involved in longevity pathways (DNA repair, apoptosis and cell cycles regu- lation, metabolism of xenobiotics, insulin/IGF-1, and neuromodulation). A first sample (stage 1) was used to test all selected SNPs, and only those showing some hint of association were subsequently retested in a second sample (stage 2), thus reducing the number of associa- tion tests (Zuo et al. 2006; Satagopan and Elston 2003; Satagopan et al. 2004; Thomas et al. 2004; Skol et al. 2007; Zheng et al. 2008).

Research in human longevity mainly focused on the orthologues of such candidate loci. Studies of cente- narians or long-lived subjects have been successful in identifying specific genes and genotypes that influ- ence human lifespan (for reviews see Christensen et al. 2006; Bonafè and Olivieri 2009; Chung et al. 2010; Slagboom et al. 2011). Particular striking examples include GH/IGF-1/insulin signaling (GHR, IGF1R, and FOXO3A), antioxidant (SOD1, SOD2, PON1, and FOXO3A), and inflammatory (IL6, CETP, and Klotho) pathways, silencing genes (SIRT1 and SIRT3), and elements of lipid metabolism (APOE, APOB, ACE, and APOC3).

Materials and methods

Stage 1 sample was recruited between 1994 and 1997 in Calabria (southern Italy) and included 149 unrelated

subjects of which 78 were considered as cases ≥ ( 90 years; median age, 98 years; 36 males and 42 females) and 71 as controls (<90 years; median age, 67 years; 39 males and 32 females). Stage 2 sample was recruited subsequently between 2005 and 2008, also in Calabria, and included 842 unrelated subjects ≥ of which 288 are cases ( 90 years; median age, 92 years; 125 males and 163 females) and 554 are controls (<90 years; median age, 67 years; 277 males and 277 females). Study participants, their parents, and grandparents were all born in Calabria, as ascer- tained from population registers.

The chromosomal region encompassing the candi- date genes were identified through the databases http://www.ncbi.nlm.nih.gov/ (gene and mapview) and http://www.ensembl.org/index.html. The gene re- gion was defined as the region from up to 5 kbp upstream of the transcription start site to up to 5 kbp downstream of the transcription stop site, allowing no overlap with the neighboring genes. In the choice of candidate SNPs, we used different online databases (eg., http://www.ncbi.nlm.nih.gov/projects/SNP; http://www.ensembl.org/index.html; and http://www. hapmap.org/cgi-perl/gbrowse/hapmap).

Younger subjects were contacted through general physicians. Subjects older than 90 years were identi- fied by screening of population registers in different municipalities distributed across the entire Calabria region. Subjects who were eligible for the study were contacted and invited to participate in the study. A written informed consent was obtained from all par- ticipants before enrolling in the study. The healthy status was ascertained by medical visit carried out by a geriatrician who also administered a structured ques- tionnaire validated within European recruitment proj- ects (available at the following web site: http:// biologia.unical.it/echa/results.htm). The questionnaire was aimed to the collection of sociodemographic in- formation, evaluation of physical and cognitive status, medications, and information on common diseases that occurred in the past. Subjects with dementia and/or neurologic disorders were not included. At the time of the visit, peripheral venous blood samples were also obtained. White blood cells from blood buffy coats were used as source of DNA.

SNPs selection was based on the following criteria: minor allele frequency (MAF) >10 % in Caucasians, coding SNPs and SNPs having potential functional im- pact (non-synonymous SNPs, SNPs located in potential regulatory region), and SNPs previously identified in relevant association studies. Tagging SNPs were selected with the use of the Tagger program within Haploview (http://www.broad.mit.edu/mpg/haploview/; http://www. broad.mit.edu/mpg/tagger/; de Bakker et al. 2005), using

In total we identified 317 SNPs in 104 genes which are involved in the above-mentioned pathways. The complete list of genes, SNPs, and other relevant infor- mation is provided in Supplementary Table S1.

Genotyping

Genotyping of the samples in stage 1 was carried out using a microarray technique based on the arrayed primer extension (Kurg et al. 2000). Genotyping of samples in stage 2 was carried out using an allele- specific PCR-based KASPar SNP genotyping system (KBiosciences, Hoddesdon, UK) (Cuppen 2007). Genotyping quality control procedures consisted of inclusion of duplicates and inclusion of both positive and negative (water blanks) controls in each assay reaction.

Candidate genes and SNP selection

Candidate genes were chosen from genetic pathways related to DNA repair, apoptosis and cell cycle regu- lation, metabolism of xenobiotics, insulin/IGF-1, and neuromodulation. The selection was based on their biological relevance and on published reports indicat- ing their involvement in aging and longevity in either “ model organisms or humans. Using keywords as ag- ” “ ” “ ing AND longevity , human aging , human longev- ” “ ” ity , aging AND model organism , a range of online databases were employed including Pubmed (http:// www.ncbi.nlm.nih.gov/pubmed/) and GenAge (http:// genomics.senescence.info/genes)/. Additionally, path- “ ” way analysis tools, such as Biocarta (http://

Quality control