Genetics of Human Aging - Molepi · 50 Genetics of Human Aging The Search for Genes Contributing to Human Longevity and Diseases of the Old P. ELINE SLAGBOOM,a,b BASTIAAN T. HEIJMANS,b,c

50

Genetics of Human Aging

The Search for Genes Contributing to HumanLongevity and Diseases of the Old

P. ELINE SLAGBOOM,a,b BASTIAAN T. HEIJMANS,b,c MARIAN BEEKMAN,d RUDI G.J. WESTENDORP,c AND INGRID MEULENBELTb

bGaubius Laboratory, TNO Prevention and Health, Leiden, The NetherlandscSection of Gerontology and Geriatrics, Department of General Medicine and dDepartment of Human Genetics, Leiden University Medical Centre, Leiden,The Netherlands

ABSTRACT: An aging population of humans reflects early-onset morbidity andmortality as well as late-onset disease in the phase when the mortality rate dou-bles and, finally, longevity of extremely long-lived subjects. Genetic influenceshave been reported to be relevant for each of these three phases. A growingfield in genetic research is aimed at the identification of genes involved in multi-factorial diseases of the old and in longevity. Important issues in these studiesinclude the definition of phenotype, which maximally highlights the geneticcontribution, whether earlier and later onset phenotypes have loci in common,and how to rank or reject the many candidate disease loci found in differentstudies. These issues will be illustrated from research on cardiovascular diseaseand osteoarthritis.

INTRODUCTION

Aging in higher species is associated with a gradual accumulation of a diversespectrum of pathological conditions. This process seems to be partly under the con-trol of genetic factors. The maximum life span (age at death of the single last survi-vor), among others, is a species-specific characteristic. This implicates the presenceof species-specific genes that influence a basic aging rate and longevity. Evolution-ary theories predict that such genes contribute to aging because of germline muta-tions that affect the organism only late in life (after the period of maximalreproductivity,1 or because of germline mutations that have a positive effect early inlife and a deleterious effect late in life (antagonistic pleiotropy2). The disposablesoma theory3 predicts that sets of such genes act in a broad network of somatic main-tenance functions and that the energy reserved for these functions is in evolutionarilydefined balance with energy reserved for reproduction. According to this concept,aging rates are determined by the interplay between accumulation of damaged (mac-

aAddress for correspondence: P. Eline Slagboom, TNO-PG, Department of Vascular and Con-nective Tissue Research, Leiden, The Netherlands.

[email protected]

51SLAGBOOM et al.: GENETICS OF HUMAN AGING

ro) molecules in somatic tissue and maintenance/repair functions evolved to restrictsuch accumulation. Because energy resources allocated to reproduction and somaticmaintenance vary among species, the effectiveness of maintenance functions to con-trol somatic damage varies among species. This is reflected, for example, in howerror-prone DNA repair enzymes determining the accumulation rate of somatic mu-tations in the genome are.

The genome should be considered both determinant and target of aging.4 Here,we focus on the determinant role of the genome in aging, the nature of the genes ex-pected to contribute to aging, and the methods used to find such genes in humans.

EVOLUTIONARY CONCEPTS AND HUMAN AGING

Genes contributing to species differences in basic aging rate may also determinedifferences in aging rate between individuals of one species by variations in suchgenes. Many different genes may be expected to contribute to the variance betweenhumans in physical condition, occurrence of disease, age of onset of disease, age atdeath, cause of death, and so forth. The evolutionary concepts given above help usto imagine how gene variants contributing to aging may become distributed in thehuman population. Neutral germline mutations, slightly altering gene products and/or expression levels affecting health only late in life, may become distributed slowlythroughout human populations. Such mutations escape natural selection if they haveno impact on reproductive success. The apolipoprotein E (ApoE) ε4 allele, for ex-ample, is carried by 15% of Caucasians, 20% of African Americans, and 10% of Jap-anese. This allele is associated with the risk of dementia5–7 and cardiovasculardisease.8 The even more common 4G allele in the promoter of the plasminogen ac-tivator inhibitor–1 (PAI-1) gene,9 associated with risk of cardiovascular disease,10 ispresent in 45–50% of Caucasians. Such frequent variants are expected to have arisen100,000–150,000 years ago and may contribute to aging phenomena in all humanpopulations. Pleiotropic mutations may, when advantageous early in life, becomedispersed throughout the population more rapidly. Such mutations may be those thatwould result in an increased inflammatory response, protecting against infection ear-ly in life and contributing (by chronic inflammation) to cardiovascular disease or de-mentia late in life. Gene variants that alter the balance of energy involved in somaticmaintenance and reproduction may also become actively distributed throughout thepopulation. Recently, a study on the relation between age at death and the number ofprogeny in a historical dataset from the British aristocracy revealed that either theconcept of the disposable soma (trade-offs between fertility and lifespan) or that ofantagonistic pleiotropy may indeed contribute to aging in humans.11 A larger studyon progeny and age at death in the Icelandic population, however, did not reveal suchassociations between fertility and longevity.12

The completion of the map and sequence (2000–2003) of the human genome,combined with the development of statistical methods for genetic studies of complextraits, has greatly stimulated research programs aimed at the localization and identi-fication of genes involved in longevity and common diseases of the old.

52 ANNALS NEW YORK ACADEMY OF SCIENCES

HUMAN DISEASE

Common late-onset diseases in humans may arise through a combination of basicprocesses of tissue aging (shared by all humans but at different rates) and the sum ofgenetic and environmental risk factors to which the individual is exposed. Together,these determine the individual disease risk. The process of atherosclerosis, for ex-ample, is a universal aspect of aging vasculature in humans contributing to cardio-vascular disease. Only a part of the population, however, develops a myocardialinfarction (MI) due to a number of genetic and environmental risk factors and eventssuch as rupture of the atherosclerotic plaque that leads to MI. Many studies are cur-rently being focused on the dissection of genetic influences on common complexdiseases such as cardiovascular disease, osteoporosis, osteoarthritis, type II diabetes,cancer, and dementia. The genetic make-up of individuals contributes considerablyto the risk of disease within the context of age, various systemic risk factors, comor-bidity, lifestyle, and environment. For most of the diseases mentioned, systematicand elaborate genome searches are being performed aimed at the localization of themajor gene loci that contribute to the disease. Such studies use a tool provided bynature itself: neutral variations between individuals in DNA sequence organization(polymorphisms). These polymorphic markers are present at high density in the hu-man genome and can be detected quite easily in the laboratory. The approach of agenome search using markers evenly spaced over the entire genome allows for theunbiased identification of yet-unknown genes with a major effect on the disease.13,14

In addition to the approach of genome searching/scanning to find disease genes,there is the candidate gene approach, in which case known genes are being investi-gated as potential disease susceptibility loci. The hypothesis that a specific (candi-date) gene is involved in a disease is usually based on the function of the gene in aprocess assumed to contribute to the pathophysiology of the disease. Alternatively,the gene may be identified as the causal gene in an early-onset form of the disease,with a relatively simple mode of inheritance, or in an animal model.

In contrast to the study of shorter lived individuals, extremely long-lived humansand animal strains may be studied. Identification of factors contributing to the “risk”of becoming extremely long-lived may reveal pathways of protection against basicaspects of aging and disease. It is an intriguing issue whether pathways can be iden-tified that modulate a basic aging rate of tissues. It may be expected that some ofthese basic pathways will contribute to aging in many species.

Genetic research of human aging summarized in the next sections deals with thefollowing questions. Which genes determine early-onset disease and how do we in-vestigate their relevance to diseases of the old? How are causal genes specific forcommon diseases identified in elderly patients? Which of these genes contribute tothe exponential increase in mortality of the population that occurs late in life? Howdo disease loci relate to longevity; how could longevity loci be found and be relatedto disease?

EARLY-ONSET DISEASE GENES

The most feasible strategy for identifying loci that contribute to human aging isby studying animal models or early-onset human diseases that resemble common


diseases of the old. Such early-onset diseases may be caused by a relatively smallnumber of genes (mono- or oligogenic). Affected subjects can more accurately bedistinguished from unaffected subjects than is often the case for common late-onsetdiseases. Usually, DNA is collected from families in which the disease is transmittedin two or more generations. Linkage studies can be performed using polymorphicDNA markers with known locations in the genome. It is tested whether a given mark-er and the disease phenotype are transmitted together from parents to offspring. Theextent to which marker and disease phenotype segregate together in a pedigree (link-age) indicates how close the marker and disease gene must be located on a singlechromosome. Because the location of the markers is known, the location of the dis-ease gene, close to the marker that shows statistically significant evidence for link-age, can be estimated. Positive findings of linkage are eventually followed by anextensive search for mutations in the gene with the shortest physical distance to themarker. Mutations have, for example, been identified in linkage studies of familieswith early-onset cardiovascular disease (hypercholesterolemia caused by mutationsin the low-density lipoprotein receptor gene,15,16 osteoarthritis (generalized osteoar-thritis with mild dysplasia caused by mutations in the collagen type II gene17,18), de-mentia (familial Alzheimer’s dementia caused by mutations in the presenilline 1 and2 genes19), and progeroid/accelerated aging showing multiple features of aging (theWerner syndrome caused by mutations in a gene of the recQ helicase family20,21).The early-onset disease gene may contribute to more common forms of disease whenadditional mutations of the gene reside in the population with a mild effect, resultingin late-onset symptoms. Mild mutations are, for example, sequence variations in thepromoter region of genes (promoter variants) leading to slightly altered levels ofgene expression. Even if the early-onset disease gene itself is not relevant for themore common disease, the study of early-onset disease may reveal pathophysiologicpathways that contribute to more common forms of disease in older patients.

LATE-ONSET DISEASE GENES

The relevance of an early-onset disease gene to a more common form of the dis-ease can be investigated by genetic association studies comparing gene frequenciesin DNA from patient and control groups. Because functional (mild) variations areusually not yet identified in a candidate gene, variants (alleles) of a polymorphicmarker within or close to the candidate gene are compared between unrelated sub-jects with and without the disease (cases and controls, respectively). A significantlyincreased frequency of an allele in patients compared to controls (positive associa-tion) may indicate that the marker segregates in the population together (in linkagedisequilibrium) with a nearby mutation that increases the risk for disease. This im-plies that the gene(s) close to the marker may harbor mutations with a late deleteri-ous effect. Common alleles of polymorphisms in the Werner gene have beenassociated with the risk of myocardial infarction in the Japanese population22; com-mon alleles of the collagen type II (COL2A1) gene have been associated with therisk of osteoarthritis in Caucasians.23 The presence of gene defects underlying thesedisease associations remains to be identified.


It can be expected that many of the genes causing early-onset disease are not themajor contributors to the common disease phenotype. A huge number of candidategenes are usually hypothesized to play an important role in the disease. Associationstudies are very sensitive detectors of both major and minor disease loci in the pop-ulation. However, since the function of only a minority (about 6000) of the 100,000–150,000 genes in the human genome is known, the odds are high that the major dis-ease loci will go undetected by the candidate gene approach. This is why genomescanning is frequently applied. First, the site of a major disease gene in the genomeis localized in steps of increasing accuracy (initial scan and fine mapping). Then ev-idence is obtained to show which of the genes at a specific genome location is theactual disease gene (identification of the gene by physical mapping and mutationanalysis), followed by an in-depth study of the function of the gene and its defectsin different patients.

To localize and identify major causal genes directly in elderly patients is muchmore complex then to perform linkage studies in families with a monogenic disease.Common diseases of the old mostly aggregate in families (rather than showing aclear pattern of inheritance), and multiple generations cannot be collected. Parentsof patients are usually not alive, and children are too young to reveal whether theywill become affected or not. A typical genome scan for a late-onset disease is there-fore done by genotyping marker loci at regular distances (10–20 cM) over the entiregenome in populations of sibling pairs both affected by the disease. For each marker,the number of siblings sharing alleles identical by descent is tested. For markerslinked to the disease locus, significantly more sibling pairs affected by the trait areassumed to share (0, 1, 2) alleles than would be expected by chance (25%, 50%,25%, respectively). Today, many variations of such genome searches are being used(including nonaffected siblings).24,25 This is a very elaborate approach. Localizationof the genes requires 10 to hundreds of thousands of genotypings in the initial ge-nome searches indicating genome areas containing 10 to hundreds of genes. By finemapping, physical mapping, and mutation analysis, the evidence must be providedto tell which of the genes in a genomic fragment is the disease gene.

Much attention lately is focused on the prospects for performing genome scansin populations of unrelated individuals (instead of sibling pairs) by using dense mapsof single nucleotide polymorphisms (SNPs). A complete genome search in such as-sociation (linkage disequilibrium) studies would require the typing of 500,000 SNPmarkers,26 which can only be performed using advanced and expensive automatedDNA chip technology. Such studies will also be performed for fine mapping of ge-nome regions that have shown positive linkage in sibling-pair studies. Because sib-lings share much larger pieces of chromosome than unrelated subjects, the sibling-pair approach does not allow fine mapping of gene loci beyond 2–4 cM, whereaslinkage diseqilibrium mapping in unrelated individuals with SNPs does allow this.

Although many diseases are importantly influenced by genetic factors, the genesinvolved may be hard to find. Many different genes may interactively cause the dis-ease in different patients (genetic heterogeneity), and the clinical expression of a dis-ease gene may vary widely among patients (clinical heterogeneity). Measurableendpoints other than presence or absence of disease may allow the identification ofmajor loci contributing to disease more easily. Therefore, in addition to genomesearches for disease in patients and their relatives, genome searches are being per-


formed in healthy subjects for loci determining (quantitative) risk factors of disease.Examples are the searches that are being performed for quantitative trait loci (QTLs)determining blood pressure, cholesterol (and other lipid) levels,27 weight, and scoresfor personality traits such as anxiety or depression.

Genetic research on osteoarthritis is now described to illustrate the different as-pects of genetic research into a complex common disease: linkage studies in early-onset disease; establishing the genetic component of osteoarthritis in the generalpopulation, and subsequent candidate gene studies and genome searches.

THE GENETICS OF OSTEOARTHRITIS

Osteoarthritis (OA) is a prevalent chronic disease of the joints that causes consid-erable pain and mobility problems in the elderly. Radiological characteristics of OAare joint space narrowing (representing degeneration of articular cartilage) and for-mation of osteophytes (representing the formation of new subchondral bone) (seeFIG. 1). Cartilage degradation, as observed by radiographic photography, is a basicaspect of human aging in all humans, but only a part of the population develops theclinical symptoms of OA. Because radiological characteristics of OA (ROA) canmuch better be measured and quantified than clinical ones such as pain, most geneticstudies have used ROA as a measure for OA. The role of genetic factors in increasingsusceptibility to OA is being investigated both in early-onset families (age of onset20–50 years) and at later ages of onset in the population at large.

ROA records for Dutch families expressing early-onset, generalized OA (GOAoccurring in multiple joints before the age of 50 years) were collected.28 In these

FIGURE 1. Schematic representation of a normal and osteoarthritic joint.


families the disease was transmitted in a dominant Mendelian fashion, probablycaused by a single gene. Linkage studies were initially performed for a large numberof candidate genes encoding components of the extracellular matrix in cartilage andproteins involved in cartilage metabolism and repair.28 Because most of these geneswere excluded as causal factors, a genome-wide scan was performed in seven early-onset Dutch GOA families. The results of this genome-wide scan indicated the pres-ence of a novel disease gene on chromosome 2q. Studies are now being pursued toidentify this gene and to find the mutation(s) in the various OA families. Because OAis such a common disease, the question is raised whether the gene at 2q plays a rolein common OA. But is OA in the population at large influenced by genetic factors atall?

This was investigated in a Dutch prospective, population-based study, called theRotterdam study.29 Radiographic characteristics of OA were assessed in hip, knee,hand, and spine in a random sample of 1600 subjects of the ages between 55 and 70years. For 118 of these subjects (probands), brothers and sisters were included in thestudy (257 siblings in total). By comparing the occurrence of ROA in these siblingswith the prevalence of ROA in the population sample, heritabilities of ROA could beestimated. This revealed that essentially three definitions of ROA were influencedsignificantly by genetic factors29:

(1) ROA at multiple joints with a heritability of 0.78, 95% CIL 0.34–0.76(meaning that 78% of the variation in the population is due to genetic variationbetween individuals);

(2) ROA in hands (0.56, 95% CIL 0.34–0.76);(3) Disk degeneration of the spine, which is clinically not considered to be OA

but still represents degradation of cartilage (heritability 0.75, 95% CIL 0.30–1.00).The first definition is relatively rare and was present in only 14% of 55- to 65-

year-old subjects. Hand OA and disk degeneration of the spine are very frequent inthe population. As yet, it is not clear whether these definitions represent different pa-tient subgroups in which the disease in caused by different sets of genes or differentclinical expressions of one set of OA genes. Other groups also demonstrated consid-erable genetic influences for different definitions of OA.30–32

Candidate gene studies for OA revealed associations for a number of genes,among which are the collagen type II gene,23 the insulin-like growth factor-1 gene,33

and two genes encoding components of the extracellular matrix, the cartilage matrixprotein (CRTM) gene34 and the aggrecan gene.35 The influence of these loci, how-ever, explains only a small fraction of the genetic influences on OA in the populationat large.

Genome searches of OA demonstrated different areas of positive linkage depend-ing on OA definitions that were used to collect sibling pair populations (presence ofOA in hands or in hip, for example).36–38 Linkage was found at chromosomes 11q12(LOD score 2.40), 9q33-34 (LOD score 2.23), 4q26-q27 (LOD score 2.02), Xp11.3(LOD score 1.65), and 7p15-p21 (LOD score 1.29). Three groups reported linkagein a broad region on human chromosome 2q. Summarized, these studies indicatelinkage at a 5-cM interval at 2q12-q14 containing the interleukin-1 (IL-1) gene clus-ter and linkages at 2q13-q32 and 2q32-q35. The last location on chromosome 2q,found in patients with hip OA, overlaps with the region detected in Dutch familieswith early-onset generalized OA. If these results point to a single disease gene, the


gene may harbor different mutations in the population, leading to milder and moresevere symptoms of the disease. Fine mapping and mutation analysis will eventuallylead to identification of OA susceptibility genes.

CARDIOVASCULAR DISEASE GENES AND MORTALITY

Between the ages of 65 and 95, the mortality rate increases exponentially. Theheritability of age at death in this phase as established in a Danish twin study is 20–30%.39 Over the last few years, a large number of common functional variants havebeen identified in genes that may contribute to major age-related pathologic condi-tions. More than 30 gene loci were shown to be associated with the risk of cardio-vascular disease. The gene products of these loci have a function in lipidmetabolism, fibrinolysis, coagulation, blood pressure, methionine/homocysteinemetabolism, extracellular matrix metabolism, inflammation, and so forth. A greatvariety of populations and clinical endpoints was selected in different studies. Ingeneral therefore, it has not yet been possible to rank or reject these loci for their rolein cardiovascular disease. As the number of polymorphisms associated with diseaseis growing, the need for distinguishing major ones for in-depth studies increases.The relation between a number of functional variants and polymorphisms previouslyassociated with cardiovascular disease was examined in a population-based studyamong subjects aged 85 years and over (Leiden 85-plus Study40). Associations ofthese gene variants with mortality before the age of 85 years was studied cross-sec-tionally by comparing gene frequencies in the elderly with a control group of youngsubjects with families from the same geographic region. In a 10-year follow-upperiod, the relation of the gene variants to all-cause and cause-specific mortality ofthe Leiden 85-plus population was studied prospectively. Functional variants in theparaoxonase,41 factor V,42 angiotensin-converting enzyme (ACE),43 and tumor ne-crosis factor-α (TNF-α) genes did not reveal any major associations with populationmortality. Such associations were, however, observed for the apolipoprotein (Apo)E gene with mortality before 85 years, for the PAI-1 gene with the risk of ischemicheart disease after the age of 85 years,43 and for the methylene tetrahydrofolate re-ductase (MTHFR) gene.44

A common ala-to-val mutation (677C→T) in the MTHFR gene is considered afactor that could contribute to mortality. The mutation is associated with a disturbedmethionine/homocysteine metabolism (FIG. 2) and with increased plasma homocys-teine levels,45 which are associated with cardiovascular disease46 and death fromcoronary artery disease.47 The frequency of the mutation was significantly lower inthe subset of 365 elderly subjects who were born in Leiden, The Netherlands, thanin 250 young subjects whose families originated from the same geographic region.This difference was only present in men. The estimated mortality risk up to 85 yearsin men homozygous for the mutation was 3.7 (95% CI, 1.3–10.9). The complete co-hort of 666 elderly subjects was followed over a period of 10 years for all-cause andcause-specific mortality. Over the age of 85 years, mortality in men homozygous forthe mutation was increased 2.0-fold (95% CI, 1.1–3.9) (FIG. 3), and gene environ-ment interactions with smoking habits were observed. Among women aged 85 yearsand over, no deleterious effect of the MTHFR mutation was detected. Replication of


our findings in a 65- to 85-year-old Dutch population sample is currently being test-ed. The findings obtained in our studies may be universal but could also reflect se-lection bottlenecks specific for the Dutch population or this cohort. Our findings forthe MTHFR mutation were supported by reduction in the frequency of the homozy-gous mutated genotype among French centenarians,48 but not by two other cross-sectional studies of elderly populations.49,50

Surprisingly, cancer rather than cardiovascular diseases contributed to the in-creased mortality in men homozygous for the mutation. The MTHFR mutation haspreviously been associated with colon cancer,51,52 and a recent meta-analysis has

FIGURE 2. Schematic representation of the function of the MTHFR gene product inthe methionine–homocysteine pathway.

FIGURE 3. Kaplan-Meier estimate of 10-year cumulative survival according toMTHFR genotype for men and women aged 85 years and over.


shown that the mutation was not associated with vascular disease.53 Genes may con-tribute to multiple pathologic conditions simultaneously (such as ApoE variantscontribute to both dementia and cardiovascular disease). This may be a common fea-ture of gene variants contributing to mortality at older ages.

LONGEVITY

Extreme longevity aggregates in families,54 showing a tendency for a maternalcomponent of inheritance.55 The quest for identification of longevity loci is very ap-pealing. A growing number of groups is investigating candidate loci in centenari-ans.56–59 Analogous to other genetic association studies, the design of a propercontrol group is very critical in these studies. Many of the loci investigated thus farare those that have been associated with increased disease risk in younger cohorts.Also, drug metabolism loci60 and polymorphisms in the mitochondrial genome havebeen investigated. The results of genetic association studies in centenarians need avery careful interpretation. Toupance et al.61 have shown that risk alleles contribut-ing to the period of exponential mortality increase can be expected to occur at higherfrequencies in centenarians than in younger cohorts. To test whether disease genescontribute to mortality may therefore be better investigated in cohorts of increasingages between 65 and 95 than in centenarians. Centenarian studies have revealed,however, that gene variants or other factors associated with disease risk in the pop-ulation at large may have beneficial (or neutral) effects at extremely high ages.62,63

The longevity studies performed thus far do not yet suggest which pathways arecritical to achieving an extreme old age. In view of the disposable soma theory ofaging, general candidate longevity loci may be considered to be those involved in so-matic maintenance (DNA replication and repair; systemic and cellular response toendo/exogenic exposure, etc.) linked in interaction or in other ways related to net-works involved in fecundity. Because of the limited knowledge that exists so far onthe rate-limiting pathways of human aging, genome-scanning approaches seem to bethe best option for finding major longevity loci.

The phenotype in longevity that is expected to be a genetically influenced traithas not yet been thoroughly described. Does the genetic component in longevity pro-mote a long life by simultaneously providing protection from all major diseases orfrom specific diseases or just from death due to such diseases? Longevity may, forexample, be compatible with atherosclerosis that does not lead to myocardial infarc-tion; with joint space narrowing that does not lead to OA; with insulin resistance thatdoes not lead to diabetes and cardiovascular disease. Families with a high proportionof extremely long-lived members in each generation are being identified world-wide. A description of the long-lived phenotype in such families, including age atdeath, specific cause of death, medical history of diseases, age of onset of such dis-eases, clinical assays, lifestyle factors, and so forth, will be imperative in the searchfor longevity loci. Investigating extreme old age at death as the trait may not revealmajor longevity loci in a genome scan, because of the etiological heterogeneity un-derlying this characteristic. Other (quantitative) phenotypes representing basic agingmay have higher heritabilities and may help reveal major longevity loci in a search.Longevity studies in animal models and the concept of the disposable soma theoryoffer interesting phenotypic characteristics and candidate pathways to be studied in


relation to longevity, such as parameters of metabolic control (insulin signaling),stress resistance, and genetic instability. Studies in C. elegans indicated the presenceof interactions between pathways of insulin signaling and antioxidant defense pro-moting longevity.61

FUTURE PERSPECTIVES

One of the challenges of genetic research in the next millennium will be to iden-tify genetic variations that have a major role in affecting the basic aging rate (of allhumans), the variation in susceptibility to diseases of the old, and in the potential tobecome extremely long-lived. This requires an understanding of the human genomein terms of gene sequence and function, epigenetic mechanisms of gene regulation,gene–gene and gene–environment interactions. Such research will eventually revealpathophysiologic pathways underlying the clinical heterogeneity in complex diseas-es. Once a disease gene or pathway is identified, a search can be performed for en-vironmental factors modulating its action, potentially leading to new strategies andtargets for therapeutic intervention or prevention. For some true polygenic diseases,however, it may not become feasible to dissect the genetic component. In the nearfuture SNP mapping will become available for the localization of common diseasegenes. The study of extremely long-lived subjects and their families, on the otherhand, may uncover shortcuts to disease-protecting mechanisms.

REFERENCES

1. MEDAWAR, P.B. 1952. An Unsolved Problem of Biology. Lewis. London.2. WILLIAMS, G.C. 1999. Pleiotropy, natural selection, and the evolution of ageing. Evo-

lution 11: 398–411.3. KIRKWOOD, T.B. 1977. Evolution of ageing. Nature 270: 301–304.4. SLAGBOOM, P.E. 1990. The aging genome: determinant or target? Report of the

EURAGE meeting on “Genomic Instability and Aging,” Nerja (Spain). Mutat. Res.237: 183–187.

5. CORDER, E.H., A.M. SAUNDERS, W.J. STRITTMATTER, et al. 1993. Gene dose of apolipo-protein E type 4 allele and the risk of Alzheimer's disease in late onset families. Sci-ence 261: 921–923.

6. STRITTMATTER, W.J., A.M. SAUNDERS, D. SCHMECHEL, et al. 1993. Apolipoprotein E:high-avidity binding to beta-amyloid and increased frequency of type 4 allele in late-onset familial Alzheimer disease. Proc. Natl. Acad. Sci. USA 90: 1977–1981.

7. FARRER, L.A., L.A. CUPPLES, J.L. HAINES, et al. 1997. Effects of age, sex, and ethnicityon the association between apolipoprotein E genotype and Alzheimer disease. Ameta-analysis. APOE and Alzheimer Disease Meta Analysis Consortium [see com-ments]. JAMA 278 : 1349–1356.

8. VAN DER CAMMEN, T.J., C.J. VERSCHOOR, C.P. VAN LOON, et al. 1998. Risk of left ven-tricular dysfunction in patients with probable Alzheimer's disease with APOE*4allele. J. Am. Geriatr. Soc. 46: 962–967.

9. DAWSON, S.J., B. WINNAN, A. HAMSTEN, et al. 1993. The two allele sequences of acommon polymorphism in the promoter of the plasminogen activator inhibitor-1(PAI-1) gene respond differently to interleukin-l in HEPG2 cells. J. Biol. Chem. 268:10739–10745.

10. ERIKSSON, P., B. KALLIN, H. VAN ‘T, et al. 1995. Allele-specific increase in basaltranscription of the plasminogen-activator inhibitor 1 gene is associated with myo-cardial infarction. Proc. Natl. Acad. Sci. USA 92: 1851–1855.


11. WESTENDORP, R.G. & T.B. KIRKWOOD. 1998. Human longevity at the cost of repro-ductive success. Nature 396: 743–746.

12. FRIGGLE, M.L., D.F. GUDBJARTSSON, H. GUDMUNDSSON & K. STEFANSSON. 1999. Lon-gevity in Iceland: fertility and genetics. Am. J. Hum. Genet. 65: 1118.

13. LANDER, E.S. & D. BOTSTEIN. 1986. Strategies for studying heterogeneous genetictraits in humans by using a linkage map of restriction fragment length polymor-phisms. Proc. Natl. Acad. Sci. USA 83: 7353–7357.

14. LANDER, E.S. & D. BOTSTEIN. 1986. Mapping complex genetic traits in humans: newmethods using a complete RFLP linkage map. Cold Spring Harbor Symp. Quant.Biol. 51: 49–62.

15. WIDHALM, K., C. IRO, A. LINDEMAYR, et al. 1999. Heterozygous familial hypercholes-terolemia: a new point-mutation (1372del2) in the LDL-receptor gene whichcauses severe hypercholesterolemia. Hum. Mutat. 14: 357.

16. OSE, L. 1999. An update on familial hypercholesterolaemia. Ann. Med. 31(Suppl. 1):13–18.

17. BLEASEL, J.F., D. HOLDERBAUM, V. BRANCOLINI, et al. 1998. Five families with argi-nine 519-cysteine mutation in COL2A1: evidence for three distinct founders. Hum.Mutat. 12: 172–176.

18. PROCKOP, D.J., L. ALA-KOKKO, D.A. MCLAIN & C. WILLIAMS. 1997. Can mutatedgenes cause common osteoarthritis? Br. J. Rheumatol. 36: 827–829.

19. LENDON, C.L., F. ASHALL & A.M. GOATE. 1997. Exploring the etiology of Alzheimerdisease using molecular genetics. JAMA 277: 825–831.

20. YU, C.E., J. OSHIMA, Y.H. FU, et al. 1996. Positional cloning of the Werner's syn-drome gene. Science 272: 258–262.

21. PENNISI, E. 1996. Premature aging gene discovered [news; comment]. Science 272:193–194.

22. YE, L., T. MIKI, J. NAKURA, et al. 1997. Association of a polymorphic variant of theWerner helicase gene with myocardial infarction in a Japanese population [pub-lished erratum appears in Am. J. Med. Genet. 1997. 70(1): 103]. Am. J. Med.Genet. 68: 494–498.

23. MEULENBELT, I., C. BIJKERK, S.C.M. DE WILDT, et al. 1999. Haplotype analysis ofthree polymorphisms of the COL2A1 gene and associations with generalised radio-logical osteoarthritis. Ann. Hum. Genet. 63: 393–400.

24. RISCH, N. & K. MERIKANGAS. 1996. The future of genetic studies of complex humandiseases. Science 273: 1516–1517.

25. RISCH, N. & H. ZHANG. 1995. Extreme discordant sib pairs for mapping quantitativetrait loci in humans. Science 268: 1584–1589.

26. KRUGLYAK, L. 1999. Prospects for whole-genome linkage disequilibrium mapping ofcommon disease genes. Nat. Genet. 22: 139–144.

27. VOGLER, G.P., G.E. MCCLEARN, H. SNIEDER, et al. 1997. Genetics and behavioralmedicine: risk factors for cardiovascular disease. Behav. Med 22: 141–149.

28. MEULENBELT, I., C. BIJKERK, F.C. BREEDVELD & P.E. SLAGBOOM. 1997. Genetic link-age analysis of 14 candidate gene loci in a family with autosomal dominantosteoarthritis without dysplasia. J. Med. Genet. 34: 1024–1027.

29. BIJKERK, C., J.J. HOUWING-DUISTERMAAT, H.A. VALKENBURG, et al. 1999. Heritabili-ties of radiologic osteoarthritis in peripheral joints and of disc degeneration of thespine. Arthritis Rheum. 42: 1729–1735.

30. FELSON, D.T., N.N. COUROPMITREE, C.E. CHAISSON, et al. 1998. Evidence for a Men-delian gene in a segregation analysis of generalized radiographic osteoarthritis: theFramingham Study. Arthritis Rheum. 41: 1064–1071.

31. HIRSCH, R., M. LETHBRIDGE-CEJKU, R. HANSON, et al. 1998. Familial aggregation ofosteoarthritis. Arthritis Rheum. 41: 1227–1232.

32. WRIGHT, G.D., M. REGAN, C.M. DEIGHTON, et al. 1998. Evidence for genetic anticipa-tion in nodal osteoarthritis. Ann. Rheum. Dis. 57: 524–526.

33. MEULENBELT, I., C. BIJKERK, H.S. MIEDEMA, et al. 1998. A genetic association studyof the IGF-1 gene and radiological osteoarthritis in a population-based cohortstudy (the Rotterdam Study). Ann. Rheum. Dis. 57: 371–374.


34. MEULENBELT, I., C. BIJKERK, S.C. DE WILDT, et al. 1997. Investigation of the associa-tion of the CRTM and CRTL1 genes with radiographically evident osteoarthritis insubjects from the Rotterdam study. Arthritis Rheum. 40: 1760–1765.

35. HORTON, W.E.J., M. LETHBRIDGE-CEJKU, M.C. HOCHBERG, et al. 1998. An associationbetween an aggrecan polymorphic allele and bilateral hand osteoarthritis in elderlywhite men: data from the Baltimore Longitudinal Study of Aging (BLSA).Osteoarth. Cartil. 6: 245–251.

36. CHAPMAN, K., Z. MUSTAFA, C. IRVEN, et al. 1999. Osteoarthritis-susceptibility locuson chromosome 11q, detected by linkage. Am. J. Hum. Genet. 65: 167–174.

37. LEPPAVUORI, J., U. KUJALA, J. KINNUNEN, et al. 1999. Genome Scan for PredisposingLoci for Distal Interphalangeal Joint Osteoarthritis: evidence for a locus on 2q.Am. J. Hum. Genet. 65: 1060–1067.

38. WRIGHT, G.D., A.E. HUGHES, M. REGAN & M. DOHERTY. 1996. Association of twoloci on chromosome 2q with nodal osteoarthritis. Ann. Rheum. Dis. 55: 317–319.

39. LJUNGQUIST, B., S. BERG, J. LANKE, et al. 1998. The effect of genetic factors for lon-gevity: a comparison of identical and fraternal twins in the Swedish Twin Registry.J. Gerontol. A Biol. Sci. Med. Sci. 53: M441–M446.

40. LAGAAY, A.M., J. D'AMARO, G.J. LIGTHART, et al. 1991. Longevity and heredity inhumans. Association with the human leucocyte antigen phenotype. Ann. N.Y.Acad. Sci. 621: 78–89.

41. HEIJMANS, B.T., R.G.J. WESTENDORP, A.M. LAGAAY, et al. 1999. Common paraoxo-nase gene variants, mortality risk and fatal cardiovascular events in elderly sub-jects. Atherosclerosis, in press.

42. HEIJMANS, B.T., R.G. WESTENDORP, D.L. KNOOK, et al. 1998. The risk of mortalityand the factor V Leiden mutation in a population-based cohort. Thromb. Haemost.80: 607–609.

43. HEIJMANS, B.T., R.G.J. WESTENDORP, D.L. KNOOK, et al. 1999. Angiotensin I–con-verting enzyme and plasminogen activator inhibitor-1 gene variants: the risk ofmortality and fatal cardiovascular disease in an elderly population-based cohort. J.Am. Coll. Cardiol. 34: 1176–1183.

44. HEIJMANS, B.T., J. GUSSEKLOO, C. KLUFT, et al. 1999. Mortality risk in men is associ-ated with a common mutation in the methylenetetrahydrofolate reductase gene(MTHFR). Eur. J. Hum. Genet. 7: 197–204.

45. FROSST, P., H.J. BLOM, R. MILOS, et al. 1995. A candidate genetic risk factor for vas-cular disease: a common mutation in methylenetetrahydrofolate reductase. Nat.Genet. 10: 111–113.

46. BOUSHEY, C.J., S.A. BERESFORD, G.S. OMENN & A.G. MOTULSKY. 1995. A quantitativeassessment of plasma homocysteine as a risk factor for vascular disease. Probablebenefits of increasing folic acid intakes. JAMA 274: 1049–1057.

47. NYGARD, O., J.E. NORDREHAUG, H. REFSUM, et al. 1997. Plasma homocysteine levels andmortality in patients with coronary artery disease. N. Engl. J. Med. 337: 230–236.

48. FAURE-DELANEF, L., I. QUERE, J.F. CHASSE, et al. 1997. Methylenetetrahydrofolatereductase thermolabile variant and human longevity. Am. J. Hum. Genet. 60: 999–1001.

49. GALINSKY, D., C. TYSOE, C.E. BRAYNE, et al. 1997. Analysis of the apo E/apo C-I,angiotensin converting enzyme and methylenetetrahydrofolate reductase genes ascandidates affecting human longevity. Atherosclerosis 129: 177–183.

50. HARMON, D.L., D. MCMASTER, D.C. SHIELDS, et al. 1997. MTHFR thermolabile geno-type frequencies and longevity in Northern Ireland. Atherosclerosis 131: 137–138.

51. MA, J., M.J. STAMPFER, E. GIOVANNUCCI, et al. 1997. Methylenetetrahydrofolatereductase polymorphism, dietary interactions, and risk of colorectal cancer. CancerRes. 57: 1098–1102.

52. CHEN, J., E. GIOVANNUCCI, K. KELSEY, et al. 1996. A methylenetetrahydrofolate reduc-tase polymorphism and the risk of colorectal cancer. Cancer Res. 56: 4862–4864.

53. BRATTSTROM, L., D.E. WILCKEN, J. OHRVIK & L. BRUDIN. 1998. Common methylene-tetrahydrofolate reductase gene mutation leads to hyperhomocysteinemia but notto vascular disease: the result of a meta-analysis. Circulation 98: 2520–2526.


54. PERLS, T.T., E. BUBRICK, C.G. WAGER, et al. 1998. Siblings of centenarians livelonger. Lancet 351: 1560.

55. KORPELAINEN, H. 1999. Genetic maternal effects on human life span through theinheritance of mitochondrial DNA. Hum. Hered. 49: 183–185.

56. DE BENEDICTIS, G., L. CAROTENUTO, G. CARRIERI, et al. 1998. Gene/longevity associ-ation studies at four autosomal loci (REN, THO, PARP, SOD2). Eur. J. Hum.Genet. 6: 534–541.

57. DE BENEDICTIS, G., G. ROSE, G. CARRIERI, et al. 1999. Mitochondrial DNA inheritedvariants are associated with successful aging and longevity in humans. FASEB J.13: 1532–1536.

58. IVANOVA, R., V. LEPAGE, D. CHARRON & F. SCHACHTER. 1998. Mitochondrial genotypeassociated with French Caucasian centenarians. Gerontology 44: 349.

59. IVANOVA, R., N. HENON, V. LEPAGE, et al. 1998. HLA-DR alleles display sex-depen-dent effects on survival and discriminate between individual and familial longev-ity. Hum. Mol. Genet. 7: 187–194.

60. MUIRAS, M.L., P. VERASDONCK, F. COTTET & F. SCHACHTER. 1998. Lack of associationbetween human longevity and genetic polymorphisms in drug-metabolizingenzymes at the NAT2, GSTM1 and CYP2D6 loci. Hum. Genet. 102: 526–532.

61. TOUPANCE, B., B. GODELLE, P.H. GOUYON & F. SCHACHTER. 1998. A model for antago-nistic pleiotropic gene action for mortality and advanced age. Am. J. Hum. Genet.62: 1525–1534.

62. SCHACHTER, F., L. FAURE-DELANEF, F. GUENOT, et al. 1994. Genetic associations withhuman longevity at the APOE and ACE loci. Nat. Genet. 6: 29–32.

63. LUFT, F.C. 1999. Bad genes, good people, association, linkage, longevity and theprevention of cardiovascular disease. Clin. Exp. Pharmacol. Physiol. 26: 576–579.

64. HONDA, Y. & S. HONDA. 1999. The daf-2 gene network for longevity regulates oxida-tive stress resistance and Mn-superoxide dismutase gene expression in Caenorhab-ditis elegans. FASEB J. 13: 1385–1393.

Documents

Genetics of Human Aging - Molepi · 50 Genetics of Human Aging The Search for Genes Contributing to Human Longevity and Diseases of the Old P. ELINE SLAGBOOM,a,b BASTIAAN T. HEIJMANS,b,c