TABLE 1. Genome stability pathways that control large rearrangements and aging

Symptoms of accelerated Genome senescence stability pathway Genes Null mice In vitro In vivo Human syndrome DSB-repair KU70, KU86, Ku70, Ku86 Yes Yes DNA-PKcs PKcs, SCID SIR2/3/4 RAD51 Yes Yes BRCA1/2 Brca1/2 Hereditary breast Yes Yes cancer ERCC1 Ercc1 Recombination RECQ1-5 Wrn, Blm Werner, Bloom, suppression Rothmund Thomson Telomere mTR, hTERT mTR Yes Yes maintenance TERF1/2 TNKS TIN2 Cell cycle ATM Atm Yes Ataxia telangiectasia check-point TP53 Tp53 Li-Fraumeni activity

play an increased rate of somatic mutations and a variety of cytogenetic abnormali- ties, such as deletions and translocations.21 This high level of genomic instability could be the cause of the severe limitation of in vitro life span demonstrated in Wern- er cells.18 Also other so-called progeroid syndromes, such as ataxia telangiectasia and Bloom syndrome show increased genomic instability.18

TABLE 1 summarizes the pathways and some of the genes thus far identified that are involved in the suppression of large genomic mutations. As discussed above, de- fects in many of these genes have been found associated with accelerated senes- cence, but not always and not to the same extent. This is expected, since even if aging would be totally based on genomic instability it would be highly unlikely that com- plete inactivation of any gene in any of these pathways would closely mimic the nor- mal aging process. Instead, one would expect combinations of subtle allelic variants of these genes to determine the aging phenotype. It is possible to test this by creating mouse models with a variety of knock-in variants of the relevant genome stability genes. However, an alternative and reasonable approach would be to compare fre- quencies of the various alleles of loci involved in genome maintenance and repair and more specifically the pathways listed in TABLE 1 in different human populations with characteristic aging-related phenotypes. Such phenotypes could include ex- tremely short or extremely long life, extreme susceptibility or extreme resistance to organ-specific age-related loss of function and extreme susceptibility or extreme re- sistance to age-related disease. One would expect that at least some of those allelic variants that give rise to amino acid changes, has functional consequences in terms of the level of proficiency at which genome maintenance operates. At present, it is

  Comprehensive survey of candidate genes for potentiallyfunctional polymorphisms in elderly populations J Define haplotypes, i.e., alleles, and assess allele and genotype frequencies  Predict functional impact at the protein and pathway level     

FIGURE 1. Flow chart of the sequential steps in gene-based asssociation studies.

not possible to accurately predict functionality directly from variations in the gene coding sequences. However, statistically significant variations among populations with well-defined aging-related characteristics could provide a good starting point for subsequent functional studies. This approach is schematically depicted in FIGURE 1.

Thus far, association studies have been based on single polymorphisms in candi- date genes. The best known example in this respect is the observed lower frequency of the APOE4 variant in centenarians,22 a higher frequency of which had previously been found associated with sporadic Alzheimer’s disease.23 However, any positive result could be due to an effect of the polymorphism on the function of the candidate gene or it could be due to some other gene variant that is in linkage disequilibrium with the marker locus. It has recently been shown that the distances over which link- age disequilibrium acts are small, i.e., typically less than 3 kb,24 although these data have recently been challenged.25 Nevertheless, unless all polymorphic variation in a large number of candidate genes is detected, this type of studies is unlikely to yield significant results in most cases.

With the rapid emergence of complete sequence information for all human genes it is theoretically possible to scrutinize all genes or families of genes suspected to be involved in a complex phenotype for all possible polymorphic variation in a group of subjects as compared to a control group. Individual differences in complex phe- notypes, of which familial aggregation or twin studies suggest a genetic component, could be due to common variants of genes controlling one or more functional path- ways thought to play a role in the phenotype. In a recent study, Cargill et al.26 sys- tematically surveyed the coding regions of 106 genes relevant to cardiovascular disease, endocrinology and neuropsychiatry for all possible variants in a sample of mixed ethnic groups. For this purpose, they used a combination of oligonucleotide chip array hybridization and DHPLC (HPLC of DNA fragments in a temperature gradient). In these 106 genes a total of 560 single nucleotide polymorphisms were discovered.

To identify potentially functional SNPs involved in blood pressure homeostasis and hypertension Halushka et al.27 used the same technology to assay 75 candidate

VIJG et al.: BRCA1 GENE SEQUENCE VARIATION IN CENTENARIANS

genes in a sample of 74 ethnically heterogeneous individuals with a range of hyper- tension phenotype diversity. A total of 387 SNPs were detected in gene coding se- % quences, 54 of which were predicted to lead to altered protein.