To go beyond statistical association, we chose to investigate the possible functional role of these genes in regulating lifespan by evaluating their influence on lifespan in the nematode, C. elegans, a robust model organism for candidate lifespan gene discovery. The A-to-I RNA editing gene family and their enzymatic editing activity have been well-conserved in a broad array of species including humans, mice, flies, zebrafish, xenopus and notably, C. elegans. Our analysis provides strong evidence for association of ADARB1 and ADARB2 with extreme old age. Our findings of strongest association in the NECS sample are consistent with that sample being both the largest and oldest of the four studies. The lack of reproducibility for some SNPs may have been due to differences in overall genetic background (ethnicity), size and younger ages of the oldest old samples. Nonetheless, associations were noted across four different study populations suggesting that the associations between ADARB1 and ADARB2 and EL are robust to different genetic backgrounds and environmental exposures.

ADARB2 is a very large gene spanning more than 500Kb in chromosome 10, but our analysis narrows the association to a region of approximately 100Kb that could be followed-up by fine mapping or sequencing for discovering functional variants and to provide a better understanding of the function of these genes in human aging. The precise role for A-to-I RNA editing gene activity in human aging, which remains unknown, warrants validation in other species, particularly humans, and provides a novel regulatory axis for future studies on regulatory pathways that influence the aging process. We speculate that as-of-yet unidentified ADAR variants delay age-associated declines in ADAR activity. We note that a reduction in ADAR enzymatic activity is associated with Dementia, ALS and Alzheimer's disease in normal aging individuals [46]. Consistent with this interpretation, analysis of published transcriptional profiles of aging in C. elegans indicate that adr-1 and adr-2 expression peak in early adulthood and decline with age rather precipitously. The declines observed in that study are compatible with a protective role for ADAR alleles in aging.

Although the impact upon lifespan that we observed in C. elegans appears to be independent of insulin signaling (Figure 6a), the interaction between RNA editing and RNA interference is likely to be complex since decreased insulin signaling in C. elegans can also affect RNA interference [47] and may suggest threshold effects associated with declining levels of insulin signaling. Future studies will be needed to identify and characterize targets of RNA editing and their potential role(s) in modulating RNA interference activity, in the context of aging and age-related diseases.

Materials and Methods

Ethics Statement

Subjects included in the NECS, SICS, AJCS, and JCS provided written informed consent, and all research involving human subjects was approved by the Institutional Review Boards of Boston University, Boston, USA (NECS), the Istituto di Ricovero e Cura a Carattere Scientifico Multimedica, Milano, Italy (SICS), Albert Einstein College of Medicine, Bronx, USA (AJCS), Keio.

Table 6. Replication in the JCSStatistical significance was observed in this set, specifically in rows 1, 5, and 10. However, one of them had an opposite effect compared to the NECS and SICS in row 1. We did not attempt to merge the results from different populations due to substantial differences in allele frequencies. The study was conducted anonymously at the University of Tokyo, Japan (JCS). Control data from the Illumina iControlDB database was anonymized. It was found that both the NECS and the Illumina controls were comprised of three major clusters corresponding to northwest, northeast, and southwest Europeans. However, in the Illumina controls sample, there were also subjects with different levels of admixture between the three clusters (Figure S3). Therefore, we randomly sampled 1,538 subjects from the three major clusters to create a control set that matched the genetic background of the NECS extreme old sample set as suggested in [49]. We used the same procedure to identify 81 female and 16 male subjects to be added to the set of SICS controls. The random-selection procedure was repeated twice and led to the same results.

SNP genotyping was performed on the Illumina 370 CNV chip (Illumina, San Diego, CA) for the NECS and SICS samples. Only samples with at least a 93% call rate were used for analysis. For AJCS and JCS, genotyping was originally performed with Affymetrix 6.0 chip and 5.0 chips, respectively with required call rates of 99% or greater. Affymetrix Birdseed algorithm and Illumina Beadstudio were used for genotype calling. Non-overlapping SNPs that were not approximated by SNPs with substantial LD (D9.0.8) were genotyped with Sequenom (AJCS) and BigDye Terminator cycle sequencing kit and an ABI Prism 3730xl DNA analyzer (Applied Biosystems, CA, USA). The sequence data was analyzed with ABI PRISM SeqScape Software version 2.6 (Applied Biosystems).

In creating a genetically matched control set, a referent cohort sample for the NECS subjects was constructed utilizing genotype data from the Illumina iControlDB database. Principal components analysis was used to match cases and controls by genetic background. To reduce chances of stratification, we identified 2,077 Caucasian referent subjects from the Illumina iControlDB, all genotyped with Illumina arrays, with known age at enrollment between 30 and 75 years. We used the principal component analysis implemented in the program EIGENSTRAT [48] to examine the structure of this referent group compared to the NECS and SICS subjects. The analysis showed that both the NECS and the Illumina controls are comprised of three major clusters that correspond to northwest, northeast, and southwest Europeans.