Note: 
1. The word "lon-" in "longevity" and "long-lived" was split across two lines, which is incorrect.
2. There was a spelling error in "methuselah," which was corrected.
3. "Crohn s disease" had an unnecessary space before "s."
4. "IGF-1" had an unnecessary space between letters.
5. "neuromodEnrolling in the study, the healthy status of subjects was confirmed by a medical visit conducted by a geriatrician who administered a validated questionnaire (available at http://biologia.unical.it/echa/results.htm) to collect sociodemographic information, evaluate physical and cognitive status, medications, and information on past common diseases. Subjects with dementia and/or neurological disorders were excluded. During the visit, peripheral venous blood samples were taken, and white blood cells from blood buffy coats were used as a DNA source. SNP selection was based on criteria such as minor allele frequency (MAF) >10% in Caucasians, coding SNPs, SNPs with potential functional impact (non-synonymous SNPs, SNPs located in potential regulatory regions), and SNPs previously identified in relevant association studies. Tagging SNPs were selected using the Tagger program within Haploview (http://www.broad.mit.edu/mpg/haploview/; http://www.broad.mit.edu/mpg/tagger/; de Bakker et al. 2005), resulting in 317 SNPs in 104 genes involved in the aforementioned pathways. The complete list of genes, SNPs, and relevant information is provided in Supplementary Table S1.

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

Candidate genes were chosen from genetic pathways related to DNA repair, apoptosis and cell cycle regulation, metabolism of xenobiotics, insulin/IGF-1, and neuromodulation based on their biological relevance and published reports indicating their involvement in aging and longevity in either model organisms or humans. Online databases such as Pubmed (http://www.ncbi.nlm.nih.gov/pubmed/) and GenAge (http://genomics.senescence.info/genes)/ were employed, and pathway analysis tools such as Biocarta (http://www.biocarta.com/) were used. 

After genotype calling, datasets underwent a quality control (QC) phase to check for errors at the genotypic level. SNPs were excluded if they had significant deviation, high missingness rate, or low minor allele frequency. The cleaned dataset was then analyzed for association with longevity using the chi-square test, with each genotypic variable coded with respect to dominant, recessive, and heterozygote disadvantage/advantage models. The maximum of these three chi-square values was used as a measure of association between the polymorphism and the analyzed phenotype.

In stage 2 analysis, 31 selected SNPs were genotyped in additional samples, and two SNPs were excluded due to high missingness rate. The cleaned dataset was analyzed for association with longevity using the chi-square test, and two observed associations remained statistically significant after Bonferroni's correction: rs282070 (p value = 1.1103) and rs2111699 (p value = 1.4103). For rs282070 located in MAP3K7 gene, subjects carrying the C allele showed an increased chance to attain longevity; for rs2111699 located in GSTZ1 gene, subjects carrying two copies of the G allele showed an increased chance to survive at very old age.

Second-order SNP-SNP interactions were captured using the model-based multifactor dimensionality reduction (MB-MDR) method developed by Calle et al. (2010). Logistic regression analyses were performed to define the nine possible genotypic combinations as high (H), low (L), or no risk (0). The significance for the epistatic effect was based on the minimum between PH and PL (MIN.P), and the significance of a specified model was assessed through a permutation test on the maximum Wald statistic. No significant differences remained after Bonferroni's correction for multiple testing.Multiple testing of different genetic models obtained by the proposed permutational approach.

Discussion:

Considered a crucial factor in the cascade of intracellular events initiated by environmental and/or physiological stressors, aging regulation may be important for cells to survive or die. However, although several components of MAPK signaling pathways play important roles in the regulation of cellular senescence (Maruyama et al. 2009; Debacq-Chainiaux et al. 2010) and have also been implicated in the pathogenesis of many human diseases (Kim and Choi 2010), no data have yet been documented about the influence of MAP3K7 on human aging and longevity.

The results of our study provide the first evidence of such an influence with the rs282070-C allele positively affecting longevity in a dominant manner. In this study, we investigated possible associations between longevity and 317 SNPs in 104 candidate genes involved in the regulation of aging-related biological pathways using a two-stage approach. To improve the efficiency of this study design, we used a robust test that is powerful when the underlying genetic model is unknown, and that was successfully applied to genome-wide association studies (Zheng et al. 2007; Sladek et al. 2007).