A genome-wide scan for linkage to human exceptional longevity identifies a locus on chromosome 4

Results

An obvious consequence of studying the exceptional longevity phenotype is that neither unaffected family members nor parents are available for the study. Because no prior hypothesis of a specific genetic mechanism for extreme longevity existed, and the limited information from most of these families precluded a meaningful estimate of such a model, an affected-only multipoint nonparametric analysis was performed (9). This analysis tested for excess sharing of chromosomal regions that were identical by descent in the sibships. The nonparametric analysis [maximum lod score (MLS)] was performed by using the genehunter 2.0 program (10).

The genome screen of 308 individuals belonging to 137 families identified a region on chromosome 4 between D4S1572 and D4S406 as highly suggestive of linkage (MLS = 2.67) (see Fig. 1). Fine mapping at an average of 1 marker every 3 cM was performed in a 20-cM region around this peak, resulting in an increased MLS (3.65) at marker D4S1564 (see Table 1).

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Figure 1

Multipoint lod scores for the genome-wide scan. Individuals in 137 sibships demonstrating exceptional longevity were genotyped at 400 marker loci throughout the genome. Scores are plotted as a function of specific markers. Chromosome number is designated at the top of each plot. The horizontal threshold lines on each graph represent MLS = 2.0, a score slightly higher than the average maximum score expected by chance once in a genome scan.

To estimate the significance of the observation of linkage to chromosome 4, simulations under the hypothesis of no linkage were designed that match the family structure and marker heterozygosity of our study. One thousand genome scans were simulated with a genome-wide map density of 1 marker every 3 cM (matching the fine-mapping density performed in the region of maximum linkage), and in only 44 of those 1,000 genome scans was the observed MLS of 3.65 exceeded (P = 0.044).

Previous studies indicate that parametric linkage analyses by using both a dominant and recessive inheritance model may be more powerful in some cases than nonparametric studies for detecting genes contributing to complex traits (11). In this case, a positive result from an independent parametric analysis could serve as a validity check of the nonparametric findings. In addition, nonparametric methods do not easily allow for the presence of locus heterogeneity. Therefore, multipoint genome-wide affected-only parametric linkage analyses were conducted by using the allegro program under both a dominant and recessive model with reduced penetrance and allowing for heterogeneity (12).

The disease allele frequency under each model was determined such that the penetrance model fit a population prevalence of 5% (0.047 for dominant and 0.30 for recessive). Because we analyzed only affecteds, the penetrance of the susceptible genotypes was set to 1 and to 0.005 for the unsusceptible genotypes (phenocopies). As these penetrance parameters are necessarily based on assumptions about the frequency of nongenetic cases, after performing our analysis with this predefined model, we repeated the analysis by varying the penetrance parameters (penetrance ratio varied from 200:1 to 50:1). These variations on our model had a negligible effect on our results.

The finely mapped region of chromosome 4 provided the strongest results, with a maximum heterogeneity logarithm of odds (hlod) of 3.3 under the dominant model (with 57% of families linked) and a maximum hlod of 2.9 under the recessive model (with 45% of families linked), both occurring at marker D4S1564. Empiric P values were determined by genome-wide simulations. One thousand unlinked replicates were generated to match the actual study. These replicates were analyzed exactly as was the original dataset. Of 1,000 replicates, 26 had a lod score >3.3 under the dominant model (P = 0.026), and 77 had a lod score >2.9 under the recessive model (P = 0.077). Because two inheritance models were evaluated, these parametric results are appropriately summarized and corrected by multiplying the more significant associated P value by 2, thus producing a final parametric P value of 0.052. These analyses provide significant evidence for heterogeneity, with odds in favor of heterogeneity of 1,800:1. For this dataset and trait, the parametric and nonparametric analyses corroborate each other and demonstrate that the results are robust to different sets of assumptions.

Discussion

Of the 4-fold risk to siblings of centenarians (λ_s) to achieve at least their early nineties (4), the degree of excess allele sharing indicates that a locus in the D4S1564 region could explain ≈1.65-fold of that risk, and thus a more modest common polymorphism might be inferred. A number of genetic mechanisms are likely to be at play in effecting such an influence. A relative lack of polymorphisms predisposing to age-associated diseases appears to be one prerequisite to achieving exceptional old age (13). The marked decreased frequency of the apolipoprotein (apo)E ɛ-4 allele among centenarians exemplifies such a mechanism (14). Another prerequisite may be some degree of genetic control over how fast a person ages and the consequent impact on susceptibility to a myriad of diseases normally associated with aging (3). The possibility that we are tracing a locus effecting a single common disease is less likely given recent findings by scientists working with the French Centenarian Study sample set. Simulations performed by Nemani et al. indicate that the allele-sharing method is unable to detect polymorphisms that predispose young individuals to significant mortality and occur at low frequency, as in the case of carriers of the apoE ɛ-4 allele (15). Consistent with this observation, we have not detected any linkage at the apoE or other known disease loci.

Alternatives to this linkage study are case-control studies performed on a priori-selected candidate genes hypothesized to effect fundamental mechanisms of aging (14, 16). The drawbacks of such studies include the improbability of picking the right gene to study the myriad of known and unknown genes affecting the process of interest (17). The linkage study described here markedly improves the efficiency of such association studies by defining a region likely to contain polymorphism(s) with significant influence on life span.

Additional association studies with these families and replication of these results with an independent data set should facilitate the positional cloning of a gene that influences the ability to age well and achieve exceptional longevity. Identification of the genes in humans that allow certain individuals to live to extreme old age should lead to insights on cellular pathways that are important to the aging process.