from Tonkin et al [45], wherein they demonstrated that a mild chemotaxis defect of the adr-1;adr-2 double mutant could be rescued by an rde-1 mutant [45]. Therefore, to evaluate the potential for cross-regulation between RNA editing and RNA interference in the context of lifespan, we evaluated adr-1; adr-2 mediated declines in lifespan in the presence of the RNAi defective strain, rde-1(ne-219). Remarkably, and consistent with previous results, the loss of rde-1 completely restored lifespan declines associated with adr-1; adr-2 loss-of-function (Figure 6b). We interpret these data as expanding the interaction between these two RNA regulatory pathways to include lifespan determination.

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precise role for A-to-I RNA editing gene activity in human aging, which remains unknown. However, the demonstration that this family of genes is implicated in the regulation of aging in other organisms 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 Alzheimers 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.

Prior to this study, RNA editing had not been directly implicated in the regulation of aging in humans or C. elegans. 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.

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.

Materials and Methods

Ethic 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 Eistein College of Medicine, Bronx, USA (AJCS), Keio

Table 6. Replication in the JCS subject set.

Risk versus Row SNP referent alleles CEPH NECS+SICS JPT JCS (470 oldest old, 538 controls) OR Bayes sig p(A) OR Bayes sig p(A) ADARB2 1 rs10903420 AA v AG/GG 0.327 1.25(1.07;1.45) 0.0020 0.28/0.24 0.058 0.51(0.23;1.07) 0.0397 0.03/0.045 2 rs1007147 AA v AG/GG 0.312 1.34(1.15;1.59) 0.0003 0.27/0.22 0.091 1.10(0.68;1.81) 0.3435 0.08/0.075 3 rs2805562 AA v AG/GG 0.15 1.32(1.09;1.59) 0.0022 0.16/0.13 0.058 0.67(0.26;1.56) 0.1813 0.02/0.03 4 rs884949 AA v AC/CC 0.124 1.24(1.01;1.54) 0.0211 0.12/0.10 0 5 rs2805533 AA/AG v GG 0.77 0.86(0.72;1.02) 0.0381 0.79/0.81 0.92 0.59(0.37;0.92) 0.0110 0.88/0.93 6 rs2387653 AA v AG/GG 0.097 1.21(0.99;1.49) 0.0343 0.15/0.13 0 7 rs2805535 AA v AG/GG 0.699 1.37(1.11;1.68) 0.0017 0.74/0.68 0.151 1.02(0.69;1.49) 0.4690 0.14/0.14 8 rs2805543 AA v AG/GG 0.46 1.24(1.08;1.42) 0.0008 0.53/0.48 0.105 0.86(0.57;1.30) 0.2381 0.10/0.12 9 rs3898610 AA v AG/GG 0.841 1.36(1.12;1.67) 0.0015 0.87/0.84 0.686 1.09(0.83;1.43) 0.2619 0.66/0.64 10 rs1533484 AA/AG v GG 0.442 0.86(0.75;0.98) 0.0147 0.38/0.42 0.791 0.79(0.58;1.07) 0.0641 0.76/0.80 11 rs2676192 AA v AG/GG 0.301 0.83(0.71;0.96) 0.0086 0.26/0.30 0.419 0.92(0.71;1.19) 0.2542 0.40/0.42 12 rs2387952 AA v AG/GG 0.69 1.20(1.04;1.40) 0.0073 0.72/0.68 0.616 0.98(0.76;1.28) 0.4576 0.59/0.60 13 rs17294019 AA/AG v GG 0.196 0.78(0.65;0.93) 0.0030 0.17/0.21 0.012 0.54(0.12;2.03) 0.1846 0.01/0.02 ADARB1 14 rs3788157 AA v AG/GG 0.63 1.16(1.00;1.34) 0.0204 0.65/0.62 0.65 1.03(0.79;1.36) 0.4080 0.67/0.66 15 rs414743 AA/AG v GG 0.47 0.83(0.72;0.96) 0.0053 0.43/0.48 0.31 1.14(0.86;1.52) 0.183 0.29/0.26 16 rs2838809 AA v AG/GG 0.009 0.46(0.19;1.08) 0.0297 0.005/0.01 0 0.81(0.36;1.81) 0.2959 0.028/0.034 17 rs2838810 AA/AG v GG 1 2.73(1.11;8.25) 0.0136 0.995/0.99 1 1.14(0.50;2.60) 0.3791 0.974/0.970 18 rs2838816 AA v AG/GG 0.009 0.48(0.18;1.04) 0.0309 0.005/0.01 0 0.81(0.36;1.79) 0.3032 0.029/0.034