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The mechanisms of incomplete penetrance of risk-modifying impacts of apolipoprotein E (APOE) ε2 and ε4 alleles on Alzheimer’s disease (AD) have not been fully understood. We performed genome-wide analysis of differences in linkage disequilibrium (LD) patterns between 6,136 AD-affected and 10,555 AD-unaffected subjects from five independent studies to explore whether the association of the APOE ε2 allele (encoded by rs7412 polymorphism) and ε4 allele (encoded by rs429358 polymorphism) with AD was modulated by autosomal polymorphisms. The LD analysis identified 24 (mostly inter-chromosomal) and 57 (primarily intra-chromosomal) autosomal polymorphisms with significant differences in LD with either rs7412 or rs429358, respectively, between AD-affected and AD-unaffected subjects, indicating their potential modulatory roles. Our Cox regression analysis showed that minor alleles of four inter-chromosomal and ten intra-chromosomal polymorphisms exerted significant modulating effects on the ε2- and ε4-associated AD risks, respectively, and identified ε2-independent (rs2884183 polymorphism, 11q22.3) and ε4-independent (rs483082 polymorphism, 19q13.32) associations with AD. Our functional analysis highlighted ε2- and/or ε4-linked processes affecting the lipid and lipoprotein metabolism and cell junction organization which may contribute to AD pathogenesis. These findings provide insights into the ε2- and ε4-associated mechanisms of AD pathogenesis, underlying their incomplete penetrance.

Epidemiological studies report beneficial associations of higher educational attainment (EDU) with Alzheimer’s disease (AD). Prior genome-wide association studies (GWAS) also reported variants associated with AD and EDU separately. The analysis of pleiotropic associations with these phenotypes may shed light on EDU-related protection against AD. We performed pleiotropic meta-analyses using Fisher’s method and omnibus test applied to summary statistics for single nucleotide polymorphisms (SNPs) associated with AD and EDU in large-scale univariate GWAS at suggestive-effect (5 × 10−8 < p < 0.1) and genome-wide (p ≤ 5 × 10−8) significance levels. We report 53 SNPs that attained p ≤ 5 × 10−8 at least in one of the pleiotropic meta-analyses and were reported in the univariate GWAS at 5 × 10−8 < p < 0.1. Of them, there were 46 pleiotropic SNPs according to Fisher’s method. Additionally, Fisher’s method identified 25 of 206 SNPs with pleiotropic effects, which attained p ≤ 5 × 10−8 in the univariate GWAS. We showed that a large fraction of the pleiotropic associations was affected by a counterintuitive phenomenon of antagonistic genetic heterogeneity, which explains the increase, rather than decrease, of the significance of the pleiotropic associations in the omnibus test. Functional enrichment analysis showed that apart from cancers, gene set harboring the non-pleiotropic SNPs was characterized by late-onset AD and neurodevelopmental disorders. The pleiotropic gene set was characterized by a broad spectrum of progressive neurological and neuromuscular diseases and immune-mediated conditions, including progressive motor neuropathy, multiple sclerosis, Parkinson’s disease, and severe AD. Our results suggest that disentangling genes harboring variants with and without pleiotropic associations with AD and EDU is promising for dissecting heterogeneity in biological mechanisms of AD. Supplementary Information The online version contains supplementary material available at 10.1007/s11357-021-00484-1.

Age-related diseases characteristic of post-reproductive life, aging, and life span are the examples of polygenic non-Mendelian traits with intricate genetic architectures. Polygenicity of these traits implies that multiple variants can impact their risks independently or jointly as combinations of specific variants. Here, we examined chances to live to older ages, 85 years and older, for carriers of compound genotypes comprised of combinations of genotypes of rs429358 (APOE ɛ4 encoding polymorphism), rs2075650 (TOMM40), and rs12721046 (APOC1) polymorphisms using data from four human studies. The choice of these polymorphisms was motivated by our prior results showing that the ɛ4 carriers having minor alleles of the other two polymorphisms were at exceptionally high risk of Alzheimer's disease (AD), compared with non-carriers of the minor alleles. Consistent with our prior findings for AD, we show here that the adverse effect of the ɛ4 allele on survival to older ages is significantly higher in carriers of minor alleles of rs2075650 and/or rs12721046 polymorphisms compared with their non-carriers. The exclusion of AD cases made this effect stronger. Our results provide compelling evidence that AD does not mediate the associations of the same compound genotypes with chances to survive until older ages, indicating the existence of genetically heterogeneous mechanisms. The survival chances can be mainly associated with lipid- and immunity-related mechanisms, whereas the AD risk, can be driven by the AD-biomarker-related mechanism, among others. Targeting heterogeneous polygenic profiles of individuals at high risks of complex traits is promising for the translation of genetic discoveries to health care.

INTRODUCTION Despite advances, understanding the protective role of the apolipoprotein E (APOE) e2 allele in Alzheimer's disease (AD) remains elusive. METHODS We examined associations of variants comprised of the TOMM40 rs8106922 and APOE rs405509, rs440446, and e2-encoding rs7412 polymorphisms with AD in a sample of 2862 AD-affected and 169,516 AD-unaffected non-carriers of the e4 allele. RESULTS Association of the e2/e3 heterozygote of men with AD is 38% (P = 1.65 × 10-2 ) more beneficial when it is accompanied by rs8106922 major allele homozygote and rs405509 and rs440446 heterozygotes than by rs8106922 heterozygote and rs405509 and rs440446 major allele homozygotes. No difference in the beneficial associations of these two most common e2/e3-bearing variants with AD was identified in women. The role of e2/e3 heterozygote may be affected by different immunomodulation functions of rs8106922, rs405509, and rs440446 variants in a sex-specific manner. DISCUSSION Combination of TOMM40 and APOE variants defines a more homogeneous AD-protective e2/e3-bearing profile in men.

Capturing the genetic architecture of Alzheimer's disease (AD) is challenging because of the complex interplay of genetic and non-genetic factors in its etiology. It has been suggested that AD biomarkers may improve the characterization of AD pathology and its genetic architecture. Most studies have focused on connections of individual genetic variants with AD biomarkers, whereas the role of combinations of genetic variants is substantially underexplored. We examined the associations of the

The mechanisms of incomplete penetrance of risk modifying impacts of apolipoprotein E (APOE) ε2 and ε4 alleles on Alzheimer’s disease (AD) have not been fully understood. We performed genome-wide analysis of differences in linkage disequilibrium (LD) patterns between 6136 AD-affected and 10555 AD-unaffected subjects from five independent studies to explore whether the association of the APOE ε2 allele (encoded by rs7412 polymorphism) and ε4 allele (encoded by rs429358 polymorphism) with AD was modulated by autosomal polymorphisms. The LD analysis identified 24 (mostly inter-chromosomal) and 57 (primarily intra-chromosomal) autosomal polymorphisms with significant differences in LD with either rs7412 or rs429358, respectively, between AD-affected and AD-unaffected subjects, indicating their potential modulatory roles. Our Cox regression analysis showed that minor alleles of four inter-chromosomal and ten intra-chromosomal polymorphisms exerted significant modulating effects on the ε2- and ε4-associated AD risks, respectively, and identified ε2-independent (rs2884183 polymorphism, 11q22.3) and ε4-independent (rs483082 polymorphism, 19q13.32) associations with AD. Our functional analysis highlighted ε2- and/or ε4-linked processes affecting the lipid and lipoprotein metabolism, and cell junction organization which may contribute to AD pathogenesis. These findings provide insights into the ε2- and ε4-associated mechanisms of AD pathogenesis, underlying their incomplete penetrance.

Health of brain, heart and blood vessels are closely connected, which means that Alzheimer’s (AD) and cardiovascular (CVD) diseases may have overlapping etiologies including genetic component. Most of previous genetic association studies considered different traits (AD, CVD, and their risk factors) separately. The analysis of pleiotropic predisposition to these traits may shed light on the trait-specific mechanisms in protection against AD. We carried out pair-wise pleiotropic exome-wide association study (~250K common genetic variants) in predisposition to AD and each of 17 traits in a sample of 118K individuals from UK biobank. The analysis included seven qualitative traits (CVD, coronary-heart disease, type 2 diabetes, stroke, myocardial infarction, heart failure and hypertension), as well as their 10 risk factors (blood glucose, body-mass index, height, weight, 4 lipid traits, systolic and diastolic blood pressure). Fisher’s method and omnibus test were used in pleiotropic analyses. In addition to the APOE-TOMM40 locus, the analysis identified 12 genetic loci in which genetic polymorphisms demonstrated significant associations with AD at p≤5×10-4 and pleiotropic associations at genome-wide level, p≤5×10-8. The identified genes are involved in processes of phosphorylation; regulation of cell growth, differentiation, and brain development; signal transduction and neurotransmission; mitochondrial and cytoskeleton organization; regulation of gene expression, apoptotic processes, and adaptive immune response. Our results provide novel evidence supporting the hypothesis of complex pleiotropic mechanisms contributing to the development and progression of AD and provide more insights into understanding of underlying biological functions and regulatory mechanisms behind these effects.

Despite advances, the roles of genetic variants from the APOE-harboring 19q13.32 region in Alzheimer's disease (AD) remain controversial. We leverage a comprehensive approach to gain insights into a more homogeneous genetic architecture of AD in this region. We use a sample of 2,673 AD-affected and 16,246 unaffected subjects from 4 studies and validate our main findings in the landmark Alzheimer's Disease Genetics Consortium cohort (3,662 AD-cases and 1,541 controls). We report the remarkably high excesses of the AD risk for carriers of the e4 allele who also carry minor alleles of rs2075650 (TOMM40) and rs12721046 (APOC1) polymorphisms compared to carriers of their major alleles. The exceptionally high 4.37-fold (p=1.34 × 10−3) excess was particularly identified for the minor allele homozygotes. The beneficial and adverse variants were significantly depleted and enriched, respectively, in the AD-affected families. This study provides compelling evidence for the definitive roles of the APOE-TOMM40-APOC1 variants in the AD risk.

The apolipoprotein E (APOE) ε2 and ε4 alleles have beneficial and adverse impacts on Alzheimer's disease (AD), respectively, with incomplete penetrance, which may be modulated by other genetic variants.We examined whether the associations of the APOE alleles with other polymorphisms in the genome can be sensitive to AD-affection status.We identified associations of the ε2 and ε4 alleles with 314 and 232 polymorphisms, respectively. Of them, 35 and 31 polymorphisms had significantly different effects in AD-affected and -unaffected groups, suggesting their potential involvement in the AD pathogenesis by modulating the effects of the ε2 and ε4 alleles, respectively. Our survival-type analysis of the AD risk supported modulating roles of multiple group-specific polymorphisms. Our functional analysis identified gene enrichment in multiple immune-related biological processes, for example, B cell function.These findings suggest involvement of local and inter-chromosomal modulators of the effects of the APOE alleles on the AD risk.

Late life disability is a highly devastating condition affecting 20% or more of persons aged 65 years and older in the USA; it is an important determinant of acute medical and long-term care costs which represent a growing burden on national economies. Disability is a multifactorial trait that contributes substantially to decline of health/wellbeing. Accordingly, gaining insights into the genetics of disability could help in identifying molecular mechanisms of this devastating condition and age-related processes contributing to a large fraction of specific geriatric conditions, concordantly with geroscience. We performed a genome-wide association study of disability in a sample of 24,068 subjects from five studies with 12,550 disabled individuals. We identified 30 promising disability-associated polymorphisms in 19 loci at p < 10(−4); four of them attained suggestive significance, p < 10(−5). In contrast, polygenic risk scores aggregating effects of minor alleles of independent SNPs that were adversely or beneficially associated with disability showed highly significant associations in meta-analysis, p = 3.13 × 10(−45) and p = 5.60 × 10(−23), respectively, and were replicated in each study. The analysis of genetic pathways, related diseases, and biological functions supported the connections of genes for the identified SNPs with disabling and age-related conditions primarily through oxidative/nitrosative stress, inflammatory response, and ciliary signaling. We identified musculoskeletal system development, maintenance, and regeneration as important components of gene functions. The beneficial and adverse gene sets may be differently implicated in the development of musculoskeletal-related disability with the beneficial set characterized, e.g., by regulation of chondrocyte proliferation and bone formation, and the adverse set by inflammation and bone loss. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11357-019-00125-8) contains supplementary material, which is available to authorized users.

Polygenic risk scores (PRSs) discriminate trait risks better than single genetic markers because they aggregate the effects of risk alleles from multiple genetic loci. Constructing pleiotropic PRSs and understanding heterogeneity, and the replication of PRS-trait associations can strengthen its applications. By using variational Bayesian multivariate high-dimensional regression, we constructed pleiotropic PRSs jointly associated with body mass index, systolic and diastolic blood pressure, total and high-density lipoprotein cholesterol in a sample of 18,108 Caucasians from three independent cohorts. We found that dissecting heterogeneity associated with birth year, which is a proxy of exogenous exposures, improved the replication of significant PRS-trait associations from 37.5% (6 of 16) in the entire sample to 90% (18 of 20) in the more homogeneous sample of individuals born before the year 1925. Our findings suggest that secular changes in exogenous exposures may substantially modify pleiotropic risk profiles affecting translation of genetic discoveries into health care. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s11357-020-00203-2) contains supplementary material, which is available to authorized users.

Despite evident success in clarifying many important features of Alzheimer's disease (AD) the efficient methods of its prevention and treatment are not yet available. The reasons are likely to be the fact that AD is a multifactorial and heterogeneous health disorder with multiple alternative pathways of disease development and progression. The availability of genetic data on individuals participated in longitudinal studies of aging health and longevity, as well as on participants of cross-sectional case-control studies allow for investigating genetic and non-genetic connections with AD and to link the results of these analyses with research findings obtained in clinical, experimental, and molecular biological studies of this health disorder. The objective of this paper is to perform GWAS of AD in several study populations and investigate possible roles of detected genetic factors in developing AD hallmarks and in other health disorders. The data collected in the Framingham Heart Study (FHS), Cardiovascular Health Study (CHS), Health and Retirement Study (HRS) and Late Onset Alzheimer's Disease Family Study (LOADFS) were used in these analyses. The logistic regression and Cox's regression were used as statistical models in GWAS. The results of analyses confirmed strong associations of genetic variants from well-known genes APOE, TOMM40, PVRL2 (NECTIN2), and APOC1 with AD. Possible roles of these genes in pathological mechanisms resulting in development of hallmarks of AD are described. Many genes whose connection with AD was detected in other studies showed nominally significant associations with this health disorder in our study. The evidence on genetic connections between AD and vulnerability to infection, as well as between AD and other health disorders, such as cancer and type 2 diabetes, were investigated. The progress in uncovering hidden heterogeneity in AD would be substantially facilitated if common mechanisms involved in development of AD, its hallmarks, and AD related chronic conditions were investigated in their mutual connection.

A conceptual difficulty in genetics of age-related phenotypes that make individuals vulnerable to disease in post-reproductive life is genetic heterogeneity attributed to an undefined role of evolution in establishing their molecular mechanisms. Here, we performed univariate and pleiotropic genome-wide meta-analyses of 20 age-related phenotypes leveraging longitudinal information in a sample of 33,431 individuals and dealing with the natural-selection–free genetic heterogeneity. We identified 142 non-proxy single nucleotide polymorphisms (SNPs) with phenotype-specific (18 SNPs) and pleiotropic (124 SNPs) associations at genome-wide level. Univariate meta-analysis identified two novel (11.1%) and replicated 16 SNPs whereas pleiotropic meta-analysis identified 115 novel (92.7%) and nine replicated SNPs. Pleiotropic associations for most novel (93.9%) and all replicated SNPs were strongly impacted by the natural-selection–free genetic heterogeneity in its unconventional form of antagonistic heterogeneity, implying antagonistic directions of genetic effects for directly correlated phenotypes. Our results show that the common genome-wide approach is well adapted to handle homogeneous univariate associations within Mendelian framework whereas most associations with age-related phenotypes are more complex and well beyond that framework. Dissecting the natural-selection–free genetic heterogeneity is critical for gaining insights into genetics of age-related phenotypes and has substantial and unexplored yet potential for improving efficiency of genome-wide analysis.

Introduction Apolipoprotein E (APOE) ε2 and ε4 alleles encoded by rs7412 and rs429358 polymorphisms, respectively, are landmark contra and pro “risk” factors for Alzheimer's disease (AD). Methods We examined differences in linkage disequilibrium (LD) structures between (1) AD‐affected and unaffected subjects and (2) older AD‐unaffected and younger subjects in the 19q13.3 region harboring rs7412 and rs429358. Results AD is associated with sex‐nonspecific heterogeneous patterns of decreased and increased LD of rs7412 and rs429358, respectively, with other polymorphisms from five genes in this region in AD‐affected subjects. The LD patterns in older AD‐unaffected subjects resembled those in younger individuals. Polarization of the ε4‐ and ε2 allele–related heterogeneous LD clusters differentiated cell types and implicated specific tissues in AD pathogenesis. Discussion Protection and predisposition to AD is characterized by an interplay of rs7412 and rs429358, with multiple polymorphisms in the 19q13.3 region in a tissue‐specific manner, which is not driven by common evolutionary forces.

Age-related phenotypes are characterized by genetic heterogeneity attributed to an uncertain role of evolution in establishing their molecular mechanisms. Here, we performed univariate and pleiotropic meta-analyses of 24 age-related phenotypes dealing with such evolutionary uncertainty and leveraging longitudinal information. Our analysis identified 237 novel single nucleotide polymorphisms (SNPs) in 199 loci with phenotype-specific (61 SNPs) and pleiotropic (176 SNPs) associations and replicated associations for 160 SNPs in 68 loci in a modest sample of 26,371 individuals from five longitudinal studies. Most pleiotropic associations (65.3%, 115 of 176 SNPs) were impacted by heterogeneity, with the natural-selection—free genetic heterogeneity as its inevitable component. This pleiotropic heterogeneity was dominated (93%, 107 of 115 SNPs) by antagonistic genetic heterogeneity, a phenomenon that is characterized by antagonistic directions of genetic effects for directly correlated phenotypes. Genetic association studies of age-related phenotypes addressing the evolutionary uncertainty in establishing their molecular mechanisms have power to substantially improve the efficiency of the analyses. A dominant form of heterogeneous pleiotropy, antagonistic genetic heterogeneity, provides unprecedented insight into the genetic origin of age-related phenotypes and side effects in medical care that is counter-intuitive in medical genetics but naturally expected when molecular mechanisms of age-related phenotypes are not due to direct evolutionary selection.

Summary Traditionally, genomewide association studies (GWAS) have emphasized the benefits of large samples in the analyses of age-related traits rather than their specific properties. We adopted a realistic concept of genetic susceptibility to inherently heterogeneous, age-related traits driven by the elusive role of evolution in their properties. We analyzed in detail the associations of rs693 and rs562338 polymorphisms representing the Apolipoprotein B locus with endophenotypes (total cholesterol [TC] and high-density lipoprotein cholesterol) and phenotypes (myocardial infarction [MI] and survival) in four large-scale studies, which include 20 748 individuals with 2357 MI events. We showed that a strong, robust predisposition of rs693 and rs562338 to TC (β = 0.72, P = 7.7 × 10−30 for rs693 and β = −1.08, P = 9.8 × 10−42 for rs562338) is not translated into a predisposition to MI and survival. The rs693_A allele influences risks of MI and mortality after MI additively with lipids. This allele shows antagonistic effects—protecting against MI risks (β = −0.18, P = 1.1 × 10−5) or increasing MI risks (β = 0.15, P = 2.8 × 10−3) and mortality after MI, in different populations. Paradoxically, increased TC concentrations can be protective against MI for the rs693_A allele carriers. Our results uncouple the influences of the same alleles on endophenotypes and phenotypes despite potential causal relationships among the latter. Our strategy reveals virtually genomewide significance for the associations of rs693 with MI (P = 5.5 × 10−8) that is contrasted with a weak estimate following the traditional, sample-size-centered GWAS strategy (P = 0.16) in the same sample. These results caution against the use of the traditional GWAS strategy for gaining profound insights into genetic predisposition to healthspan and lifespan.

The role of even the strongest genetic risk factor for Alzheimer's disease (AD), the apolipoprotein E (APOE) e4 allele, in its etiology remains poorly understood. We examined molecular signatures of AD defined as differences in linkage disequilibrium patterns between AD-affected and -unaffected whites (2673/16,246), Hispanics (392/867), and African Americans (285/1789), separately. We focused on 29 polymorphisms from 5 genes in the APOE region emphasizing beneficial and adverse effects of the APOE e2- and e4-coding single-nucleotide polymorphisms, respectively, and the differences in the linkage disequilibrium structures involving these alleles between AD-affected and -unaffected subjects. Susceptibility to AD is likely the result of complex interactions of the e2 and e4 alleles with other polymorphisms in the APOE region, and these interactions differ across races/ethnicities corroborating differences in the adverse and beneficial effects of the e4 and e2 alleles. Our findings support complex race/ethnicity-specific haplotypes promoting and protecting against AD in this region. They contribute to better understanding of polygenic and resilient mechanisms, which can explain why even homozygous e4 carriers may not develop AD.

Decades of research in genetics of Alzheimer’s disease (AD) established the APOE genomic region as the strongest genetic risk factor for AD in Caucasians, although its role in African-Americans (AAs) and Hispanics seems to be less pronounced. Even pathogenic role of this region in Caucasians, however, remains poorly understood. Elucidating genetic predisposition to AD, which represents a subset of age-related diseases characteristic for post-reproductive period, is hampered by the undefined role of evolution in establishing molecular mechanisms of such diseases. We examined linkage disequilibrium (LD) structures characterized by nine single nucleotide polymorphisms (SNPs) from TOMM40-APOE-APOC1 locus in 18,740 (2,661 AD-cases) Caucasians, 2,069 (285 AD-cases) AAs, and 1,313 (394 AD-cases) Hispanics. We found that the LD structures, being heterogeneous, are significantly different in Caucasians with and without AD, p

The lack of evolutionary established mechanisms linking genes to age-related traits makes the problem of genetic susceptibility to health span inherently complex. One complicating factor is genetic trade-off. Here we focused on long-living participants of the Long Life Family Study (LLFS), their offspring, and spouses to: (1) Elucidate whether trade-offs in the effect of the apolipoprotein E e4 allele documented in the Framingham Heart Study (FHS) are a more general phenomenon, and (2) explore potential mechanisms generating age- and gender-specific trade-offs in the effect of the e4 allele on cancer, diseases of the heart, and neurodegenerative disorders assessed retrospectively in the LLFS populations. The e4 allele can diminish risks of cancer and diseases of the heart and confer risks of diseases of the heart in a sex-, age-, and LLFS-population-specific manner. A protective effect against cancer is seen in older long-living men and, potentially, their sons (>75 years, relative risk [RR]>75=0.48, p=0.086), which resembles our findings in the FHS. The protective effect against diseases of the heart is limited to long-living older men (RR>76=0.50, p=0.016), as well. A detrimental effect against diseases of the heart is characteristic for a normal LLFS population of male spouses and is specific for myocardial infarction (RR=3.07, p=2.1×10−3). These trade-offs are likely associated with two inherently different mechanisms, including disease-specific (detrimental; characteristic for a normal male population) and systemic, aging-related (protective; characteristic for older long-living men) mechanisms. The e4 allele confers risks of neurological disorders in men and women (RR=1.98, p=0.046). The results highlight the complex role of the e4 allele in genetic susceptibility to health span.

Genome-wide association studies (GWAS) are traditionally based on principles of medical genetics. This strategy is well adapted for Mendelian disorders. Genetics of phenotypes that leave human organisms vulnerable to diseases in late life (called age-related phenotypes) is, however, more complex. The fundamental complicating factor is the elusive role of evolution in fixing molecular mechanism of these phenotypes. This complexity implies a special type of an inherent genetic heterogeneity reflecting sensitivity of genetic associations with age-related phenotypes to the life course of individuals in different environments. Here we follow a two-stage genome-wide approach that leverages this heterogeneity. This approach is demonstrated by examining non-pleiotropic and pleiotropic genetic predisposition to 24 age-related phenotypes (16 biomarkers, 7 diseases, and death) in a modest sample (N=26,371) from five studies (ARIC, FHS, MESA, CHS, and CARDIA) from the Candidate Gene Association Resource. In Stage 1, we performed the traditional univariate GWAS for each of 24 phenotypes improved by leveraging information from longitudinal follow up in each study separately. In Stage 2, we used Fisher’s and two omnibus tests to combine statistics from Stage 1 leveraging different types of heterogeneity. Our analyses replicated 212 SNPs in 49 loci at genome-wide level and identified 53 novel or firstly attained genome-wide significance non-pleiotropic SNPs in 49 loci and 202 pleiotropic SNPs in 154 loci in a modest sample (all loci exclude the Major Histocompatibility Complex). Our findings demonstrate benefits of more comprehensive approaches than the currently prevailing ones to gain insights into the genetics of healthspan and lifespan.

BACKGROUNDS: Elucidating the causal effects of common intermediate risk factors on the onset of age-related diseases is indispensable for developing prevention and intervention procedures. METHODS: We conducted two-stage time-to-event Mendelian randomization meta-analyses combining five large-scale longitudinal cohorts to investigate the dynamic causal effects of cardiovascular disease risk factors including body mass index (BMI), systolic blood pressure (SBP), and lipids on the age-at-onset of age-related diseases. We constructed weighted polygenic scores based on genetic markers from previously reported genome-wide association studies as instrumental variables to estimate the causal effects. To examine potential pleiotropic effect, we also performed a leave-one-out sensitivity analysis and an MR-Egger sensitivity analysis that we expanded to the survival context. RESULTS: Our results show that elevated BMI increases the absolute risk of type 2 diabetes (T2D) (p=7.68e-04), heart failure (p=9.03e-03), and cardiovascular diseases (CVD) (p=1.69e-03) and the effects start at different ages. A significant association between BMI and the risk of stroke is observed; however, the sensitivity analyses show that the association with stroke is attributed to the potential pleiotropic effects of rs2867125 and rs1558902 on BMI and stroke. Raised SBP levels are significantly associated with the development of atrial fibrillation (p=6.42e-03). Low-density lipoprotein cholesterol (LDL-C) levels are inversely associated with the age-at-onset of T2D (p=1.05e-02). In addition, LDL-C and triglycerides are inversely associated with the hazards of cancer and T2D, respectively. Nevertheless, the sensitivity analyses suggest that these associations are probably due to pleiotropic effects of several single-nucleotide polymorphisms including rs4970834 and rs1260326. CONCLUSIONS: Our results highlight the involvement of BMI in the development of multiple age-related diseases. We found that some observed causal associations can attribute to pleiotropic effects of some genetic variations. These findings have important implications in unraveling causal effects of common risk factors on age-related diseases and guiding effective intervention strategies to reduce the incidence of these diseases.

Disability and frailty increase steeply with age after midlife. They comprise broad, non-specific aging-related health/well-being declines. Understanding the molecular mechanisms of these declines could help in combating processes related to intrinsic aging. We performed genome-wide meta-analysis of disability using data on N=12,550 disabled individuals of Caucasian ancestry from five independent studies with N=24,068 genotyped participants. Disability was measured using the Activities of Daily Living (ADL) scale. A subject was considered disabled if he/she had at least one ADL impairment. All subjects in our study were aged 50+ years. The analysis followed a discovery-replication strategy using two studies as discovery samples and three others as replication samples. At the discovery stage, we selected SNPs at nominal significance (p

Summary The inherent complexity of aging-related traits can temper progress in unraveling the genetic origins of healthspan. We focus on two generations in the Framingham Heart Study, the original (FHS) and offspring (FHSO) cohorts, to determine whether aging-related processes in changing environments can substantially impact the role of lipid-related genes discovered in candidate gene (the apolipoprotein E (APOE) e2/3/4 polymorphism) and genome-wide (the APOB rs1042034 (C/T)) studies, in regulation of total cholesterol (TC) and onset of cardiovascular disease (CVD). We demonstrate that the APOE e4 allele and APOB CC genotype can play detrimental, neutral, and protective sex-specific roles in the etiology of CVD at different ages and in different environments. We document antagonistic roles for the e4 allele in the onset of CVD characterized by detrimental effects at younger ages (RR≤ 75 years = 1.49, P = 7.5 × 10−4) and protective effects at older ages (RR76+years = 0.77, P = 0.044) for FHS participants. We found that disregarding the role of aging erroneously nullifies the significant effects of the e4 allele in this sample (RR = 0.92, P = 0.387). The leading biogenetic pathways mediating genetic effects on CVD may be more relevant to lipid metabolism for APOB than APOE. Aging-related processes can modulate the strength of genetic associations with TC in the same individuals at different chronological ages. We found substantial differences in the effects of the same APOE and APOB alleles on CVD and TC across generations. The results suggest that aging-related processes in changing environments may play key roles in the genetics of healthspan. Detailed systemic integrative analyses may substantially advance the progress.

The apolipoprotein E (apoE) is a classic example of a gene exhibiting pleiotropism. We examine potential pleiotropic associations of the apoE2 allele in three biodemographic cohorts of long-living individuals, offspring, and spouses from the Long Life Family Study, and intermediate mechanisms, which can link this allele with age-related phenotypes. We focused on age-related macular degeneration, bronchitis, asthma, pneumonia, stroke, creatinine, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol, diseases of heart (HD), cancer, and survival. Our analysis detected favorable associations of the ε2 allele with lower LDL-C levels, lower risks of HD, and better survival. The ε2 allele was associated with LDL-C in each gender and biodemographic cohort, including long-living individuals, offspring, and spouses, resulting in highly significant association in the entire sample (β = −7.1, p = 6.6 × 10 −44). This allele was significantly associated with HD in long-living individuals and offspring (relative risk [RR] = 0.60, p = 3.1 × 10 −6) but this association was not mediated by LDL-C. The protective effect on survival was specific for long-living women but it was not explained by LDL-C and HD in the adjusted model (RR = 0.70, p = 2.1 × 10 −2). These results show that ε2 allele may favorably influence LDL-C, HD, and survival through three mechanisms. Two of them (HD- and survival-related) are pronounced in the long-living parents and their offspring; the survival-related mechanism is also sensitive to gender. The LDL-C-related mechanism appears to be independent of these factors. Insights into mechanisms linking ε2 allele with age-related phenotypes given biodemographic structure of the population studied may benefit translation of genetic discoveries to health care and personalized medicine.

Common strategy of genome-wide association studies (GWAS) relying on large samples faces difficulties, which raise concerns that GWAS have exhausted their potential, particularly for complex traits. Here, we examine the efficiency of the traditional sample-size-centered strategy in GWAS of these traits, and its potential for improvement. The paper focuses on the results of the four largest GWAS meta-analyses of body mass index (BMI) and lipids. We show that just increasing sample size may not make p-values of genetic effects in large (N > 100,000) samples smaller but can make them larger. The efficiency of these GWAS, defined as ratio of the log-transformed p-value to the sample size, in larger samples was larger than in smaller samples for a small fraction of loci. These results emphasize the important role of heterogeneity in genetic associations with complex traits such as BMI and lipids. They highlight the substantial potential for improving GWAS by explicating this role (affecting 11–79% of loci in the selected GWAS), especially the effects of biodemographic processes, which are heavily underexplored in current GWAS and which are important sources of heterogeneity in the various study populations. Further progress in this direction is crucial for efficient use of genetic discoveries in health care.

Studies focusing on unraveling the genetic origin of health span in humans assume that polygenic, aging-related phenotypes are inherited through Mendelian mechanisms of inheritance of individual genes. We use the Framingham Heart Study (FHS) data to examine whether non-Mendelian mechanisms of inheritance can drive linkage of loci on non-homologous chromosomes and whether such mechanisms can be relevant to longevity-related phenotypes. We report on genome-wide inter-chromosomal linkage disequilibrium (LD) and on chromosome-wide intra-chromosomal LD and show that these are real phenomena in the FHS data. Genetic analysis of inheritance in families based on Mendelian segregation reveals that the alleles of single nucleotide polymorphisms (SNPs) in LD at loci on non-homologous chromosomes are inherited as a complex resembling haplotypes of a genetic unit. This result implies that the inter-chromosomal LD is likely caused by non-random assortment of non-homologous chromosomes during meiosis. The risk allele haplotypes can be subject to dominant-negative selection primary through the mechanisms of non-Mendelian inheritance. They can go to extinction within two human generations. The set of SNPs in inter-chromosomal LD (N = 68) is nearly threefold enriched, with high significance (p = 1.6 × 10−9), on non-synonymous coding variants (N = 28) compared to the entire qualified set of the studied SNPs. Genes for the tightly linked SNPs are involved in fundamental biological processes in an organism. Survival analyses show that the revealed non-genetic linkage is associated with heritable complex phenotype of premature death. Our results suggest the presence of inter-chromosomal level of functional organization in the human genome and highlight a challenging problem of genomics of human health and aging.

Summary Progress in unraveling the genetic origins of healthy aging is tempered, in part, by a lack of replication of effects, which is often considered a signature of false-positive findings. We convincingly demonstrate that the lack of genetic effects on an aging-related trait can be because of trade-offs in the gene action. We focus on the well-studied apolipoprotein E (APOE) e2/3/4 polymorphism and on lifespan and ages at onset of cardiovascular diseases (CVD) and cancer, using data on 3924 participants of the Framingham Heart Study Offspring cohort. Kaplan–Meier estimates show that the e4 allele carriers live shorter lives than the non-e4 allele carriers (log rank = 0.016). The adverse effect was attributed to the poor survival of the e4 homozygotes, whereas the effect of the common e3/4 genotype was insignificant. The e3/4 genotype, however, was antagonistically associated with onsets of those diseases predisposing to an earlier onset of CVD and a later onset of cancer compared to the non-e4 allele genotypes. This trade-off explains the lack of a significant effect of the e3/4 genotype on survival; adjustment for it in the Cox regression model makes the detrimental effect of the e4 allele highly significant (P = 0.002). This trade-off is likely caused by the lipid-metabolism-related (for CVD) and nonrelated (for cancer) mechanisms. An evolutionary rationale suggests that genetic trade-offs should not be an exception in studies of aging-related traits. Deeper insights into biological mechanisms mediating gene action are critical for understanding the genetic regulation of a healthy lifespan and for personalizing medical care.

Summary Although the APOE region is the strongest genetic risk factor for Alzheimer's diseases (ADs), its pathogenic role remains poorly understood. Elucidating genetic predisposition to ADs, a subset of age‐related diseases characteristic for postreproductive period, is hampered by the undefined role of evolution in establishing molecular mechanisms of such diseases. This uncertainty is inevitable source of natural‐selection–free genetic heterogeneity in predisposition to ADs. We performed first large‐scale analysis of linkage disequilibrium (LD) structures characterized by 30 polymorphisms from five genes in the APOE 19q13.3 region (BCAM,NECTIN2,TOMM40,APOE, and APOC1) in 2,673 AD‐affected and 16,246 unaffected individuals from five cohorts. Consistent with the undefined role of evolution in age‐related diseases, we found that these structures, being highly heterogeneous, are significantly different in subjects with and without ADs. The pattern of the difference represents molecular signature of AD comprised of single nucleotide polymorphisms (SNPs) from all five genes in the APOE region. Significant differences in LD in subjects with and without ADs indicate SNPs from different genes likely involved in AD pathogenesis. Significant and highly heterogeneous molecular signatures of ADs provide unprecedented insight into complex polygenetic predisposition to ADs in the APOE region. These findings are more consistent with a complex haplotype than with a single genetic variant origin of ADs in this region.

Multiple functions of the beta2-adrenergic receptor (ADRB2) and angiotensin-converting enzyme (ACE) genes warrant studies of their associations with aging-related phenotypes. We focus on multimarker analyses and analyses of the effects of compound genotypes of two polymorphisms in the ADRB2 gene, rs1042713 and rs1042714, and 11 polymorphisms of the ACE gene, on the risk of such an aging-associated phenotype as myocardial infarction (MI). We used the data from a genotyped sample of the Framingham Heart Study Offspring (FHSO) cohort (n = 1500) followed for about 36 years with six examinations. The ADRB2 rs1042714 (C-->G) polymorphism and two moderately correlated (r(2) = 0.77) ACE polymorphisms, rs4363 (A-->G) and rs12449782 (A-->G), were significantly associated with risks of MI in this aging cohort in multimarker models. Predominantly linked ACE genotypes exhibited opposite effects on MI risks, e.g., the AA (rs12449782) genotype had a detrimental effect, whereas the predominantly linked AA (rs4363) genotype exhibited a protective effect. This trade-off occurs as a result of the opposite effects of rare compound genotypes of the ACE polymorphisms with a single dose of the AG heterozygote. This genetic trade-off is further augmented by the selective modulating effect of the rs1042714 ADRB2 polymorphism. The associations were not altered by adjustment for common MI risk factors. The results suggest that effects of single specific genetic variants of the ADRB2 and ACE genes on MI can be readily altered by gene-gene or/and gene-environmental interactions, especially in large heterogeneous samples. Multimarker genetic analyses should benefit studies of complex aging-associated phenotypes.

Exceptional survival results from complicated interplay between genetic and environmental factors. The effects of these factors on survival are mediated by the biological and physiological variables, which affect mortality risk. In this paper, we evaluated the role of blood glucose (BG) in exceptional survival using the Framingham Heart Study data for the main (FHS) and offspring (FHSO) cohorts. We found that: (i) the average cross-sectional age patterns of BG change over time; (ii) the values of BG level among the longest lived individuals in this study differ for different sub-cohorts; (iii) the longitudinal age patterns of BG differ from those of cross-sectional ones. We investigated mechanisms forming average age trajectories of BG in the FHS cohort. We found that the two curves: one, characterizing the average effects of allostatic adaptation, and another, minimizing mortality risk for any given age, play the central role in this process. We found that the average BG age trajectories for exceptional survivors are closer to the curve minimizing mortality risk than those of individuals having shorter life spans. We concluded that individuals whose age trajectories of BG are located around the curve minimizing chances of premature death at each given age have highest chances of reaching exceptional longevity.

We evaluated the predictive potential for long-term (24-year) survival and longevity (85+ years) of an index of cumulative deficits (DI) and six physiological indices (pulse pressure, diastolic blood pressure, pulse rate, serum cholesterol, blood glucose, and hematocrit) measured in mid- to late life (44-88 years) for participants of the 9th and 14th Framingham Heart Study examinations. For all ages combined, the DI, pulse pressure, and blood glucose are the strongest determinants of both long-term survival and longevity, contributing cumulatively to their explanation. Diastolic blood pressure and hematocrit are less significant determinants of both of these outcomes. The pulse rate is more relevant to survival, whereas serum cholesterol is more relevant to longevity. Only the DI is a significant predictor of longevity and mortality for each 5-year age group ranging from 45 to 85 years. The DI appears to be a more important determinant of long-term risks of death and longevity than are the physiological indices.

Increasing proportions of elderly individuals in developed countries combined with substantial increases in related medical expenditures make the improvement of the health of the elderly a high priority today. If the process of aging by individuals is a major cause of age related health declines then postponing aging could be an efficient strategy for improving the health of the elderly. Implementing this strategy requires a better understanding of genetic and non-genetic connections among aging, health, and longevity. We review progress and problems in research areas whose development may contribute to analyses of such connections. These include genetic studies of human aging and longevity, the heterogeneity of populations with respect to their susceptibility to disease and death, forces that shape age patterns of human mortality, secular trends in mortality decline, and integrative mortality modeling using longitudinal data. The dynamic involvement of genetic factors in (i) morbidity/mortality risks, (ii) responses to stresses of life, (iii) multi-morbidities of many elderly individuals, (iv) trade-offs for diseases, (v) genetic heterogeneity, and (vi) other relevant aging-related health declines, underscores the need for a comprehensive, integrated approach to analyze the genetic connections for all of the above aspects of aging-related changes. The dynamic relationships among aging, health, and longevity traits would be better understood if one linked several research fields within one conceptual framework that allowed for efficient analyses of available longitudinal data using the wealth of available knowledge about aging, health, and longevity already accumulated in the research field.

Insights into genetic origin of diseases and related traits could substantially impact strategies for improving human health. The results of genome-wide association studies (GWAS) are often positioned as discoveries of unconditional risk alleles of complex health traits. We re-analyzed the associations of single nucleotide polymorphisms (SNPs) associated with total cholesterol (TC) in a large-scale GWAS meta-analysis. We focused on three generations of genotyped participants of the Framingham Heart Study (FHS). We show that the effects of all ten directly-genotyped SNPs were clustered in different FHS generations and/or birth cohorts in a sex-specific or sex-unspecific manner. The sample size and procedure-therapeutic issues play, at most, a minor role in this clustering. An important result was clustering of significant associations with the strongest effects in the youngest, or 3rd Generation, cohort. These results imply that an assumption of unconditional connections of these SNPs with TC is generally implausible and that a demographic perspective can substantially improve GWAS efficiency. The analyses of genetic effects in age-matched samples suggest a role of environmental and age-related mechanisms in the associations of different SNPs with TC. Analysis of the literature supports systemic roles for genes for these SNPs beyond those related to lipid metabolism. Our analyses reveal strong antagonistic effects of rs2479409 (the PCSK9 gene) that cautions strategies aimed at targeting this gene in the next generation of lipid drugs. Our results suggest that standard GWAS strategies need to be advanced in order to appropriately address the problem of genetic susceptibility to complex traits that is imperative for translation to health care.

Dear Dr. Ingram, We would like to clarify principal limitations of, and erroneous statements in, the comments expressed by Dr. Paterson in his recent letter to the editor published in Age. Paterson A. D. (2013) Letter to the editor: expression of concern, reaffirmed. Age. This letter outlines what the author views as “a series of limitations” in our analyses. Dr. Paterson’s main concern is that our analyses do not follow standard Genome-Wide Association Studies (GWAS) strategies. The author argues that by following standard GWAS majority of SNPs reported in our papers might be excluded from the analyses right away. As a consequence, there would be no matter for “any downstream analysis”. We agree with Dr. Paterson that following standard GWAS strategies it might be possible to come to such a conclusion. It does not mean, however, that this conclusion is correct because standard GWAS strategies themselves may not be always valid. Specifically, a principal problem seen by Dr. Paterson is “that there were highly significant differences in genotype frequency” for SNPs from genotyping phases 3 and 4. Then, following the logic of standard GWAS strategies Dr. Paterson concluded that it was “consistent with major genotyping error.” Table 1 in his letter is intended to illustrate this concern (this table should list rs1390694 but not rs139069). Unfortunately, standard GWAS strategies are not designed to appropriately handle specific of age-related traits. They are not adapted for longitudinal studies either. Specifically, in longitudinal studies individuals are followed for a certain period of time which, in our case of the Framingham Heart Study (FHS), is very extensive, up to about 60 years. People can die during follow up. Even this obvious bio-demographic aspect of the problem is not within standard GWAS framework. It is, however, evident that if there are genes which influence survival, this selection may result in disproportion in frequencies of the risk allele(s) among individuals with shorter and longer lifespan. If survival is influenced by more than one allele, this selection may cause age-related clustering. Age-related selection is widely documented in gerontology in our studies (De Benedictis et al. 1998) and elsewhere (Atzmon et al. 2006; Christensen et al. 2006). This property is a central tenet of longevity studies (Martin et al. 2007). Clearly, such selection may result in deviation from Hardy-Weinberg equilibrium (HWE) that has nothing to do with genotyping errors. According to standard GWAS strategy pursued by Dr. Paterson, SNPs with deviation from HWE and any type of clustering associated with it are just eliminated. Thus, if we are looking for genes involved in regulation of survival-related traits in an aging study, following standard GWAS strategy will a priori eliminate such effects. Then, the question is whether survival selection can indeed play a role and can explain the observed frequencies in phases 3 and 4. Figure 1 (Fig. 6a and b in (Kulminski et al. 2013)) ensures that this is the case. Specifically, virtually all individuals genotyped in phase 4 and major part of individuals genotyped in phase 3 died during follow up in the FHS. This is an important finding which ensures that “major genotyping error” is not a unique explanation of genotype clustering in aging studies. Accordingly, just disregarding strong evidence of mortality selection (which has nothing to do with genotyping errors) is scientifically implausible because the selected groups of individuals with phenotypes of premature death can carry vulnerable alleles which are not carried by more successfully aging individuals. Fig. 1 Survival of the genotyped individuals selected for four genotyping phases from (A) FHS and (B) FHSO cohorts. Kaplan-Meier survival curves show age at death (line) or the end of follow up in 2007 (crosses). Sample size (n) is for all/died individuals. ... Next, Dr. Paterson notes that call rate is “so low that for all three SNPs in phase 4, these SNPs would be excluded from any standard analysis.” Phase 4 is associated with the worst survival (Fig. 1). Therefore, we have to understand why we observe low call rate for SNPs in phase 4 rather than merely exclude them given that such SNPs can be characteristic for the very vulnerable subsample of the FHS participants. Phase 4 included so-called legacy samples with DNA extracted from 1,133 frozen blood samples kept in refrigerators since 1970s to 1980s (Cupples et al. 2009). It is a recognized problem that frozen blood is of lower quality than the whole blood. Given this problem all these 1,133 samples were carefully inspected and only well qualified samples were released to the FHS SHARe. This rigorous selection resulted in 674 qualified samples that implied 59.5 % call rate. Thus, disregarding these samples would be implausible because low call rate is a priori expected for them as a result of quality control selection. Dr. Paterson states that “phases of genotyping are confounded with generation (i.e., cohorts) in the study” and, accordingly, “this would be expected to demonstrate association with any phenotype that differs by generation, and/or age.” Figure 1 explicitly shows that this statement is not correct. Phases 3 and 4 are not associated with generations (or specific age) because they are present in the FHS original and Offspring cohorts. These phases, however, are associated with phenotypes of premature deaths of different severity. Therefore, by definition we have to expect differences in allele frequencies between these phases due to age-related processes. This is exactly what aging studies are looking for. Dr. Paterson writes that “since phases are related to the cohorts, one would imagine that drastic differences in genotypes between family members would be expected to result in Mendelian errors.” First, it is incorrect that “phases are related to the cohorts” (see the above paragraph). Next, Mendelian errors imply that offspring could have alleles which are not inherited from their parents. All phases (including phases 3 and 4) are present in parents (i.e., the original FHS cohort) and offspring. Dr. Paterson explicitly shows in Table 1 in his letter that all alleles are concordant in phases 3 and 4. The fact that there is no Mendelian errors in families is evident from Table 1 in (Kulminski et al. 2013). Besides, SNPs and families with Mendel errors more than 2 % were excluded from the analyses. Thus, Dr. Paterson statement contradicts to the presented evidences. Dr. Paterson suggests that crucial step would be to analyze cluster plots for specific SNPs. It is, however, entirely unclear how the analyses of cluster plots of individual SNPs could help in explaining collective phenomena of inter-chromosomal linkage disequilibrium (LD). In the response to a recent letter of concern by Dr. Paterson published in the Experimental Gerontology (Kulminski 2012), it was detailed that neither bad nor good cluster plots of individual SNPs could explain that. Dr. Paterson further suggests that technical errors may not necessarily be randomly distributed that would result in spurious clustering. This statement, however, contradicts to the statement that the analysis of cluster plots of individual SNPs could be crucial step for detecting non-random technical artifacts because the analysis of individual cluster plots cannot explain spurious clustering. What this analysis is intended to suggest is just to exclude SNPs with “bad” plots, if any. The latter, however, is not reasonable strategy given that SNPs in inter-chromosomal LD are associated with phenotype of premature death. Our analyses provide another relevant result which ensures that “technical problems” unlikely play a role in the observed phenomena of inter-chromosomal LD. This is the observation of highly significant, nearly three-fold enrichment of non-synonymous coding SNPs, SNPs which can alter amino acid sequence of proteins, among those in inter-chromosomal LD compared to non-synonymous coding SNPs present in the qualified set of about 38 K SNPs from the Affymetrix 50 K array, i.e., 41.2 % vs. 15 %, p = 1.6 × 10−9 (Kulminski et al. 2013). This is remarkably important result because it undoubtedly shows that technical artifacts of either random or non-random origin highly unlikely play a role in this phenomenon because they have to be “smart” enough to selectively indicate functionally significant SNPs. Contrarily to technical artifacts, functional significance of SNPs is in perfect agreement with the nature of phenotype of premature death (Fig. 1). All these evidences have been presented in our papers cited by Dr. Paterson. The fact that Dr. Paterson disregards them in favor of standard GWAS strategies implies that standardization of GWAS may be not helpful for studies aimed to reveal genetic origin of age-related phenotypes because it detracts attention from the specific of the problem.

Elucidating the causal effects of common intermediate phenotypes on the onset of age-related diseases such as cardiovascular diseases (CVD), diabetes mellitus (DM), Alzheimer’s disease and cancer is indispensable for developing prevention and intervention procedures. We conducted a Mendelian randomization study to investigate the causal effects of cardiovascular risk factors including body mass index (BMI), systolic blood pressure (SBP), and lipids on the age-of-onset of various age-related diseases using three large-scale longitudinal cohorts (ARIC, CHS and MESA). We performed a two-stage time-to-event analyses using additive hazard models followed by a meta-analysis using a fixed-effects model, in which we constructed weighted polygenic scores based on genetic markers from previously reported genome-wide association studies as instrumental variables to estimate the causal effects. Our results show that elevated BMI at the baseline increases the hazard of stroke with a meta-analysis p-value of 1.82e-02 (beta=3.11e-04, i.e., one unit increase of BMI is associated with 0.311 extra cases per 1,000 person years). Raised SBP significantly increases the hazards of coronary heart diseases (beta=3.66e-04, p=1.44e-03) and CVD (beta=4.17e-04, p=2.51e-02). We confirm that the association between low-density lipoprotein cholesterol and onset of Alzheimer’s disease is due to the pleiotropic effect in APOE. Surprisingly, we observe that triglycerides have a significant negative causal effect on the hazard of DM consistently across the three cohorts (beta=-1.88e-05, p=9.93e-03). These findings have important implications in guiding effective intervention strategies to reduce the incidence of these diseases.

Enduring interest in the Apolipoprotein E (ApoE) polymorphism is ensured by its evolutionary-driven uniqueness in humans and its prominent role in geriatrics and gerontology. We use large samples of longitudinally followed populations from the Framingham Heart Study (FHS) original and offspring cohorts and the Long Life Family Study (LLFS) to investigate gender-specific effects of the ApoE4 allele on human survival in a wide range of ages from midlife to extreme old ages, and the sensitivity of these effects to cardiovascular disease (CVD), cancer, and neurodegenerative disorders (ND). The analyses show that women's lifespan is more sensitive to the e4 allele than men's in all these populations. A highly significant adverse effect of the e4 allele is limited to women with moderate lifespan of about 70 to 95 years in two FHS cohorts and the LLFS with relative risk of death RR = 1.48 (p = 3.6×10−6) in the FHS cohorts. Major human diseases including CVD, ND, and cancer, whose risks can be sensitive to the e4 allele, do not mediate the association of this allele with lifespan in large FHS samples. Non-skin cancer non-additively increases mortality of the FHS women with moderate lifespans increasing the risks of death of the e4 carriers with cancer two-fold compared to the non-e4 carriers, i.e., RR = 2.07 (p = 5.0×10−7). The results suggest a pivotal role of non-sex-specific cancer as a nonlinear modulator of survival in this sample that increases the risk of death of the ApoE4 carriers by 150% (p = 5.3×10−8) compared to the non-carriers. This risk explains the 4.2 year shorter life expectancy of the e4 carriers compared to the non-carriers in this sample. The analyses suggest the existence of age- and gender-sensitive systemic mechanisms linking the e4 allele to lifespan which can non-additively interfere with cancer-related mechanisms., Author Summary Discovering genetic origins of healthspan and lifespan could lead to breakthroughs in increasing the years of healthy and long life. In this paper we characterize the association of the e4 allele of the well-studied ApoE gene with lifespan in two generations of participants of large longitudinal studies, the Framingham Heart Study and the Long Life Family Study, and investigate the role of major human diseases such as cardiovascular disease, cancer, and neurodegenerative disorders in this association. This wide range of systemic analyses is possible given the large sample with directly genotyped ApoE polymorphism available from these studies (N = 9841, with 2557 deaths). The analyses show that women's lifespan is more sensitive to the e4 allele than men's in these populations. However, the strongly adverse effect of the e4 allele is not observed for all women, but only for those 70 to 95 years old. Cardiovascular disease, cancer, and neurodegenerative disorders do not mediate the association of the e4 allele with lifespan. However, cancer, but not cardiovascular and neurodegenerative diseases, non-additively enhances this effect resulting in 4.2 years of difference in mean lifespan for the e4 allele carriers compared to the non-carriers.

Most connections between phenotype and genetic variants detected in genome wide association studies (GWAS) of human longevity-related traits did not reach the genome-wide level of statistical significance. These estimates also suffer from the lack of replication of research findings in studies of independent populations (Deelen et al., 2011; Nebel et al., 2011). Critical analysis of these studies reveals underused reserves in the data that may improve the accuracy of genetic estimates. One such reserve deals with the proper use of genetic information contained in the age structure of study participants at the time of bio-specimen collection. As we will see later, this information has been ignored in genetic analyses of follow-up data. In this paper, we explain how such information can be used in analyses of follow up data and elucidate the benefits of joint analyses of both types of data. The proposed approach exploits the fact that participants in prospective studies often have different ages at baseline. The bio-specimen collection is often (but not always) done at baseline. Studies included in the CHARGE Consortium [except for the Original cohort of the Framingham Heart Study (FHS) where the bio-specimen collection was done some time after baseline] are typical examples. Since data on lifespan or other durations are often incomplete (e.g., censored), the Cox's type regression models is usually implemented in GWAS of these data (where, in addition to other covariates, conditioning on age at baseline is used). Note that using follow up data alone and conditioning on age at baseline may be required by the goal of the study (e.g., in the search for genes responsible for longest survival after reaching certain age, e.g., after 95 or 100 years). However, conditioning on the ages at bio-specimen collection when some of these ages are high enough may diminish or even totally exclude a substantial part of the genetic variation in longevity, i.e., eliminate the effects we are looking for. This is because the oldest old individuals participating in bio-specimen collection are precisely those who passed the process of mortality selection in the genetically heterogeneous population, and, therefore, are likely to carry genetic variants linked with “longevity” alleles (assuming that such alleles exist). Thus conditioning on the age at genotyping, especially when the oldest old study participants are in the sample, may leave little hope that associations of remaining genetic variants with human longevity will reach genome-wide significance. Such conditioning, however, seems to be a common practice in GWAS of human longevity-related traits dealing with prospective data. For example, a large group of researchers performed comprehensive genetic analyses of human lifespan and free of major diseases lifespan using data from nine studies of the CHARGE Consortium (Walter et al., 2011). The authors “conducted a survival analysis, adjusted for age at baseline and sex, to model continuous time to death or end of follow-up” [Walter et al. (2011), section “Methods”]. The Cox proportional hazards model was used to describe the connections between genetic variants and time to event. Note that, in addition to eliminating useful associations, adjusting for age at baseline may produce a bias in the analyses if the bio-specimen collection has been performed well after the time of the first examination (baseline). Such a situation characterizes the FHS data, which is the part of the CHARGE Consortium. It turns out, however, that in cases when the ages at bio-specimen collection include young adults and the oldest old individuals, the additional information about the role of genetic variants in lifespan can be obtained from the age patterns of genetic frequencies evaluated for any genetic variant even without using the follow up data. The approach based on comparison of genetic frequencies among individuals of different age categories is typically used in genetic studies of centenarians (Weir, 1996; Yashin et al., 1999, 2000; Tan et al., 2004). A monotonic increase in genetic frequency with age indicates that the corresponding variant is associated with lifespan increase (“longevity” allele). A monotonic decline in such frequency indicates that this variant contributes to shortening lifespan (deleterious, or “frailty” allele). In cases when genotyping involves individuals from a large spectrum of ages including young adults, old, and oldest old ages, there is an additional opportunity to improve the quality of genetic analyses which typically is not used in genetic association studies of follow up data. To realize such potential, new methods of association analyses are required.

Background and Objective: The influence of genes on human lifespan is mediated by biological processes that characterize body's functioning. The age trajectories of these processes contain important information about mechanisms linking aging, health, and lifespan. The objective of this paper is to investigate regularities of aging changes in different groups of individuals, including individuals with different genetic background, as well as their connections with health and lifespan. Data and Method: To reach this objective we used longitudinal data on four physiological variables, information about health and lifespan collected in the Framingham Heart Study (FHS), data on longevity alleles detected in earlier study, as well as methods of statistical modeling. Results: We found that phenotypes of exceptional longevity and health are linked to distinct types of changes in physiological indices during aging. We also found that components of aging changes differ in groups of individuals with different genetic background. Conclusions: These results suggest that factors responsible for exceptional longevity and health are not necessary the same, and that postponing aging changes is associated with extreme longevity. The genetic factors which increase lifespan are associated with physiological changes typical of healthy and long-living individuals, smaller mortality risks from cancer and CVD and better estimates of adaptive capacity in statistical modeling. This indicates that extreme longevity and health related traits are likely to be less heterogeneous phenotypes than lifespan, and studying these phenotypes separately from lifespan may provide additional information about mechanisms of human aging and its relation to chronic diseases and lifespan.

Gaining insights into genetic predisposition to age-related diseases and lifespan is a challenging task complicated by the elusive role of evolution in these phenotypes. To gain more insights, we combined methods of genome-wide and candidate-gene studies. Genome-wide scan in the Atherosclerosis Risk in Communities (ARIC) Study (N = 9,573) was used to pre-select promising loci. Candidate-gene methods were used to comprehensively analyze associations of novel uncommon variants in Caucasians (minor allele frequency~2.5%) located in band 2q22.3 with risks of coronary heart disease (CHD), heart failure (HF), stroke, diabetes, cancer, neurodegenerative diseases (ND), and mortality in the ARIC study, the Framingham Heart Study (N = 4,434), and the Health and Retirement Study (N = 9,676). We leveraged the analyses of pleiotropy, age-related heterogeneity, and causal inferences. Meta-analysis of the results from these comprehensive analyses shows that the minor allele increases risks of death by about 50% (p = 4.6×10−9), CHD by 35% (p = 8.9×10−6), HF by 55% (p = 9.7×10−5), stroke by 25% (p = 4.0×10−2), and ND by 100% (p = 1.3×10−3). This allele also significantly influences each of two diseases, diabetes and cancer, in antagonistic fashion in different populations. Combined significance of the pleiotropic effects was p = 6.6×10−21. Causal mediation analyses show that endophenotypes explained only small fractions of these effects. This locus harbors an evolutionary conserved gene-desert region with non-coding intergenic sequences likely involved in regulation of protein-coding flanking genes ZEB2 and ACVR2A. This region is intensively studied for mutations causing severe developmental/genetic disorders. Our analyses indicate a promising target region for interventions aimed to reduce risks of many major human diseases and mortality., Author Summary Biomedical research and medical care are traditionally focused on individual health conditions in order to postpone, ameliorate, or prevent the accumulation of morbidities in late life. An attractive idea is to find factors, which could reduce burden of not just one disease but a major subset of them to efficiently extend healthy lifespan. Here we focus on the analyses of genetic predisposition to risks of major human age-related diseases and mortality. The analyses highlight a locus in band 2q22.3 associated with risks of coronary heart disease, heart failure, stroke, diabetes, cancer, neurodegenerative diseases, and death. Our analyses indicate a promising target region for interventions aimed to reduce risks of many major human diseases and mortality.

Decades of studies of candidate genes show their complex role in aging-related traits. We focus on apolipoprotein E e2/3/4 polymorphism and ages at onset of cardiovascular diseases (CVD) and cancer in the parental and offspring generations of the Framingham Heart Study participants to gain insights on the role of age and gender across generations in genetic trade-offs. The analyses show that the apolipoprotein E e4 allele carriers live longer lives without cancer than the non-e4 allele carriers in each generation. The role of the e4 allele in onset of CVD is age- and generation-specific, constituting two modes of sexually dimorphic genetic trade-offs. In offspring, the e4 allele confers risk of CVD primarily in women and can protect against cancer primarily in men of the same age. In the parental generation, genetic trade-off is seen in different age groups, with a protective role of the e4 allele against cancer in older men and its detrimental role in CVD in younger women. The puzzling complexity of genetic mechanisms working in different genders, ages, and environments calls for more detail and systemic analyses beyond those adapted in current large-scale genetic association studies.

We evaluated effects of the APOE polymorphism (carriers versus noncarriers of the e4 allele) and age trajectories of total cholesterol (CH) and diastolic blood pressure (DBP) on mortality risk in the Framingham Heart Study (original cohort). We found that long-lived carriers and noncarriers have different average age trajectories and long-lived individuals have consistently higher levels and less steep declines at old ages compared to short-lived individuals. We applied the stochastic process model of aging aimed at joint analyses of genetic and nongenetic subsamples of longitudinal data and estimated different aging-related characteristics for carriers and noncarriers which otherwise cannot be evaluated from data. We found that such characteristics differ in carriers and noncarriers: (1) carriers have better adaptive capacity than noncarriers in case of CH, whereas for DBP the opposite situation is observed; (2) mean allostatic trajectories are higher in carriers and they differ from “optimal” trajectories minimizing mortality risk; (3) noncarriers have lower baseline mortality rates at younger ages but they increase faster than those for carriers resulting in intersection at the oldest ages. Such observations strongly indicate the presence of a genetic component in respective aging-related mechanisms. Such differences may contribute to patterns of allele- and sex-specific mortality rates.

Despite notable progress of the candidate-gene and genome-wide association studies (GWAS), understanding the role of genes contributing to human health and lifespan is still very limited. We use the Framingham Heart Study to elucidate if recognizing the role of evolution and systemic processes in an aging organism could advance such studies. We combine throughput methods of GWAS with more detail methods typical for candidate-gene analyses and show that both lifespan and ages at onset of CVD and cancer can be controlled by the same allelic variants. The risk allele carriers are at highly significant risk of premature death (e.g., RR = 2.9, p = 5.0 × 10−66), onset of CVD (e.g., RR = 1.6, p = 4.6 × 10−17), and onset of cancer (e.g., RR = 1.6, p = 1.5 × 10−6). The mechanism mediating the revealed genetic associations is likely associated with biological aging. These aging-related phenotypes are associated with a complex network which includes, in this study, 62 correlated SNPs even so these SNPs can be on non-homologous chromosomes. A striking result is three-fold, highly significant (p = 3.6 × 10−10) enrichment of non-synonymous SNPs (N = 27) in this network compared to the entire qualified set of the studied SNPs. Functional significance of this network is strengthened by involvement of genes for these SNPs in fundamental biological processes related to aging (e.g., response to stimuli, protein degradation, apoptosis) and by connections of these genes with neurological (20 genes) and cardio-vascular (nine genes) processes and tumorigenesis (10 genes). These results document challenging role of gene networks in regulating human health and aging and call for broadening focus on genomics of such phenotypes.