From 3fa31b50af2861382fbe2c76406f5a04c3fefc93 Mon Sep 17 00:00:00 2001 From: SoloDShelby Date: Fri, 19 Jul 2024 14:41:40 +0300 Subject: Evaluation code for paper 1 --- .../src/data/datasets/old/aging1_dataset.json | 128 +++++++++++++++++++++ 1 file changed, 128 insertions(+) create mode 100644 gnqa/paper1_eval/src/data/datasets/old/aging1_dataset.json (limited to 'gnqa/paper1_eval/src/data/datasets/old/aging1_dataset.json') diff --git a/gnqa/paper1_eval/src/data/datasets/old/aging1_dataset.json b/gnqa/paper1_eval/src/data/datasets/old/aging1_dataset.json new file mode 100644 index 0000000..f5b979c --- /dev/null +++ b/gnqa/paper1_eval/src/data/datasets/old/aging1_dataset.json @@ -0,0 +1,128 @@ +{ + "question": [ + "List as many studies are you can that include rapamycin", + "Why is it so difficult to map gene loci that control aging in humans?", + "How would one evaluate a candidate gene for mouse lifespan?", + "Do we find significant quantitative trait loci in aging studies, if so give the top three examples with descriptions?", + "What are the most fundamental human life expectancy extending geroscience studies?" + ], + "answer": [ + "1. A study assessing the impact of a rapamycin derivative on healthy aging in people (Mannick et al. 2014). 2. A veterinary clinical trial testing rapamycin as a treatment for osteosarcoma (Paoloni et al. 2010). 3. A veterinary clinical trial assessing the side effect profile and effects on age-associated cardiac function following 10 weeks of rapamycin treatment in healthy elderly dogs (Kaeberlein 2015). 4. A study on the pharmacokinetic analysis of rapamycin treatment in healthy dogs (Larson et al. 2016). 5. A study on the effects of rapamycin in aging mice (Johnson et al. 2015). 6. A study on the effects of rapamycin in rodents (Johnson et al. 2013). 7. A study on the effects of rapamycin on the replicative life of yeast (Reference [57]). 8. A study on the effects of rapamycin in 20-month-old mice (Reference [58]). 9. A study on the combination of rapamycin with other compounds for anti-aging activity (Reference [59]).", + "Mapping gene loci that control aging in humans is difficult due to several reasons. Firstly, aging is a complex phenotype influenced by multiple genes and their interactions with each other and the environment. Secondly, the effects of common genetic variations on longevity are small, requiring large studies for identification. Thirdly, human studies often face issues such as environmental heterogeneity, genetic diversity, and lack of birth matched controls. Lastly, the influence of social, economic, and cultural factors, which are unique to humans, can't be replicated in traditional model organisms, adding to the complexity.", + "One would evaluate a candidate gene for mouse lifespan by conducting gene mapping methods and using mouse life span as a surrogate for aging. This involves studying the genetic contributions to mortality rates, conducting sex-specific analyses, and determining any changes in pathology associated with the loci. The study would involve a large population of mice, and the results would be compared to Mendelian expectations. Additionally, epigenetic predictors and differential methylation analysis could be used to assess the relationship between the gene and lifespan. The gene's influence on specific late-life diseases and its effect on the risk of these diseases would also be evaluated.", + "Yes, significant quantitative trait loci (QTLs) have been found in aging studies. Three examples include: 1. Lfdr1: This QTL was found on chromosome 7 and affects lifespan and fertility in response to dietary restriction. It also has suggestive effects on fuel efficiency (FE). 2. Fedr1 and Fedr2: These QTLs were identified on chromosomes 9 and 15 respectively. They have significant effects on fuel efficiency in response to dietary restriction. 3. QTLs associated with age-related thymic involution: These were identified in a study using C57BL/6 J X DBA/2 J (BXD) recombinant inbred (RI) strains of mice.", + "The most fundamental human life expectancy extending geroscience studies include genetic and genomic research into longevity. These studies use both hypothesis-driven candidate gene approaches and explorative genome-wide analyses. They also involve the study of biomarkers related to aging, deep phenotyping, and the use of novel technologies like next-generation sequencing. Additionally, they examine the role of environmental factors, lifestyle, and heritability in human lifespan variation." + ], + "contexts": [ + [ + "Intervention trials and cell-based monotherapy", + "Rapamycin has been shown to be well tolerated in dogs, improves outcome in a glycogen storage disease model (Yi et al. 2014), and is currently being tested in veterinary clinical trials as a treatment for osteosarcoma (Paoloni et al. 2010).A veterinary clinical trial is underway to assess the side effect profile and effects on age-associated cardiac function following 10 weeks of rapamycin treatment in healthy elderly dogs (Kaeberlein 2015).", + "Rapamycin is used clinically to prevent organ transplant rejection, for some forms of cancer, and to prevent restenosis in cardiac stents (Kaeberlein 2013b).Shortterm treatment with the rapamycin derivative RAD001 improves ageassociated decline in immune function, as measured by antibody response to an influenza vaccine, in healthy elderly people (Mannick et al. 2014).", + "To date, only one study has been performed assessing the impact of a rapamycin derivative on healthy aging in people.In this trial, it was observed that 6 weeks of treatment with the rapamycin derivative RAD001 (everolimus) was sufficient to enhance function of the aged immune system, as assessed by response to an influenza vaccine (Mannick et al. 2014).This recapitulates what was observed in elderly mice (Chen et al. 2009), and suggests that at least some of the mechanisms by which rapamycin delays aging in mice work similarly in humans.Although both compounds have essentially identical biological activities, RAD001 was used in this study instead of rapamycin because the study was funded by Novartis, who holds the patent rights for RAD001 (rapamycin is now off patent and sold as a generic drug).The doses of RAD001 used in the human immune aging study were lower than those typically used to prevent organ transplant rejection and showed improved side effect profiles, although some adverse effects, including the presence of mouth sores in a subset of the patients, were noted.", + "This trial is designed to determine whether treatment with the drug rapamycin (see Table 1) can significantly reduce age-related disease and disability as well as mortality in middle-aged large dogs.The initial phase of this trial, which is in progress at the time of this writing, is intended to enroll at least 32 dogs 6 years of age or older and 40 lb in weight or greater.Each animal receives an initial veterinary exam and comprehensive blood work along with a cardiac exam including echocardiography (Fig. 3).Those dogs that do not present with any abnormalities or significant pre-existing health conditions are randomized into either placebo or rapamycin treatment groups for a 10-week treatment period.Initial rapamycin dosing regimens were determined, in part, based on pharmacokinetic analysis of rapamycin treatment in healthy dogs (Larson et al. 2016).After 10 weeks in the study, each dog receives another full exam and blood chemistry panel as well as repeat cardiac exam.The primary goals of this first phase are to establish appropriate dosing of rapamycin in the absence of significant adverse events and to determine whether similar improvements in cardiac function are achieved in aged dogs after 10 weeks of rapamycin treatment, as has been observed in laboratory mice (Dai et al. 2014;Flynn et al. 2013).", + "Fig. 3 Design of the current short-term rapamycin intervention trial.Dogs must weigh at least 40 pounds and be at least 6 years old at time of entry into the study.If no significant pre-existing health conditions are detected at the first exam, dogs are randomized into either placebo or one of the rapamycin treatment groups.Red indicates the 10-week period during which the dogs receive either rapamycin or placebo.Dogs receive the same generic rapamycin (sirolimus) pill that is provided to human patients.Asterisk Serum and feces are collected at each appointment for future metabolomic and microbiome analyses and for quantitation of circulating rapamycin levels", + "Pending the outcome of phase 1, we anticipate enrolling several hundred additional dogs with similar entry criteria into a longer-term, 3-5 year study, to carefully assess the extent to which rapamycin improves health and reduces mortality in middle-age companion dogs.In addition to cardiac function, assessments of multiple age-related phenotypes will be performed including measures of cognitive function, muscle function, kidney function, glucose homeostasis, and cancer incidence.Many of these parameters are beneficially impacted by rapamycin in aging mice (Johnson et al. 2015), and we predict that rapamycin will induce similar improvements in aging dogs.", + "Rapamycin is currently the most effective pharmacological intervention for extending lifespan and delaying a broad range of age-related functional declines in rodents (Johnson et al. 2013).However, the doses used clinically to prevent organ transplant rejection are associated with side effects, such as impaired wound healing, edema, elevated circulating triglycerides, impaired glucose homeostasis, gastrointestinal discomfort, and mouth ulcers (Augustine et al. 2007;de Oliveira et al. 2011).These adverse side effects would likely preclude long-term use of rapamycin at these levels in otherwise healthy people.With the possible exception of impaired glucose homeostasis (Lamming et al. 2012), these side effects have not been observed at doses that are associated with increased lifespan and healthspan in mice, however, raising the possibility that lower doses of this drug could promote healthy aging with minimal adverse effects.", + "Rapamycin Rapamycin is a macrolide isolated from Streptomyces hygroscopicus, a bacteria from Pascua Island (Rapa Nui).It has functions as an antibiotic, an immune suppressant drug, and it is also proposed as a CRM.After the first studies, it was found that rapamycin could induce the extension of the replicative life of yeast through the inhibition of TOR signaling [57].This compound could extend the lifetime useful in 20-month-old mice in correlation with TOR activity [58].These studies were the basis of the research to determine the function of rapamycin as a CRM, due to its modulating properties over proteostasis.In addition, studies suggest that rapamycin can be combined with other compounds (metformin, losartan, statins, propranolol, and aspirin among others) to potentiate their anti-aging activity [59].", + "Rapamycin Rapamycin is a macrolide isolated from Streptomyces hygroscopicus, a bacteria from Pascua Island (Rapa Nui).It has functions as an antibiotic, an immune suppressant drug, and it is also proposed as a CRM.After the first studies, it was found that rapamycin could induce the extension of the replicative life of yeast through the inhibition of TOR signaling [57].This compound could extend the lifetime useful in 20-month-old mice in correlation with TOR activity [58].These studies were the basis of the research to determine the function of rapamycin as a CRM, due to its modulating properties over proteostasis.In addition, studies suggest that rapamycin can be combined with other compounds (metformin, losartan, statins, propranolol, and aspirin among others) to potentiate their anti-aging activity [59].", + "One out of the 25 FDA approved Breast cancer drugs (Gemcitabine), was found in the top 20 drug list from LINCS from breast cancer stage I (dark magenta). As shown in Fig. 12, one drug out of 25 FDA approved Breast cancer drugs, Gemcitabine, was found as repurposed drug from LINCS for breast cancer stage III. Letrozole (Breast cancer drug) has similar structure (greater than 60%) with Ruxolitinib (repurposed drug from LINCS) a drug for the treatment of intermediate or high-risk myelofibrosis (Fig. 13).", + "One out of the 25 FDA approved Breast cancer drugs (Palbociclib), was found in the top 20 drug list from LINCS from breast cancer stage II (deep pink). Scientific Reports | 6:20518 | DOI: 10.1038/srep20518 13 www.nature.com/scientificreports/ Figure 11. Highlighted target genes that physically interact with genes from the breast cancer stage II common network pattern and their corresponding repurposed drugs from LINCS, along with their structurally similar Breast cancer drugs. As shown in Figs 16\u201317 two target genes (TOP2A and TYMS) are also involved in the Triple Negative pattern.", + "Two of them (Gemcitabine and Palbociclib) are included in the list of the 25 known FDA-approved Breast cancer therapeutic drugs. We performed a Hypergeometric distribution test in order to find the statistical significance of this drug overlapping. More precisely, LINCS_L1000 database is comprised from 20,413 chemical reagents. Twenty two out of twenty five breast cancer drugs are also included in LINCS database. Finally, from the 105 drugs that were found from our analysis, the probability of finding two drugs to overlap with the Breast Cancer drugs in LINCS is 0.005471157, pointing out that there is statistical significance in their selection.", + "Two from the 25 FDA approved Breast cancer drugs (Gemcitabine and Palbociclib), was found in the top 20 drug list from LINCS from Luminal A breast cancer (dark magenta and deep pink respectively).", + "18 two drugs out of 25 FDA approved Breast cancer drugs \u2013 Gemcitabine and Palbociclib \u2013 were also found as repurposed drugs from LINCS for breast cancer Luminal A (Fig. 18). Two genes from the Luminal A network pattern physically interact with four genes that involved in Histone deacetylases class (HDAC1, HDAC2, HDAC3 and HDAC8), which are target genes of Vorinostat (repurposed drug from LINCS). Vorinostat is a member of a larger class of compounds that inhibit histone deacetylases (HDAC) and it is used to treat cutaneous T cell lymphoma (CTCL).", + "One out of the 25 FDA approved Breast cancer drugs (Gemcitabine), was found in the top 20 drug list from LINCS from breast cancer stage III (dark magenta). that was found from the drug repurposing analysis of HER2 pattern. It has similar structure - 75% with WZ-4002 repurposed drug, which is a novel mutant-selective inhibitor of EGFR. Finally, both Palbociclib and WZ-4002 are structurally similar to Dasatinib (more than 60%), which is a cancer drug used to treat acute lymphoblastic leukemia.", + "Network pattern for each breast cancer subtype and the common interactions across Luminal A and Luminal B. As shown in Fig. 8, one drug out of 25 FDA approved Breast cancer drugs, Gemcitabine, was proposed as repurposed drug by the LINCS for breast cancer stage I. Furthermore, Gemcitabine is quite similar (tanimoto31 similarity greater than 80%) with Clofarabine and Kinetin-riboside (repurposed drugs from LINCS). Clofarabine is also an anti-cancer, antineoplastic chemotherapy drug and is classified as an antimetabolite.", + "Hierarchical clustering using tanimoto similarity (Soergel distance) was applied to each of the top 20 drug list from LINCS and the 25 known FDA-approved Breast cancer therapeutic drugs (Supplementary Figs 54\u201361). LINCS Drug Names were transformed into ChemSpider IDs (see Supplementary Table 1) In synopsis, the unique drugs for the breast cancer stages were 63 and for the breast cancer subtypes 58, as we have located common drugs across them. Taking their union and removing the duplicates we conclude to a total of 105 repurposed drugs.", + "13, is also structurally similar (greater than 60%) with 6-(1,3-Benzodioxol-5-yl)-N-(cyclopentylmethyl)-4-quinazolinamine (repurposed small molecule from LINCS). As in breast cancer stages I and III one drug out of 25 FDA approved Breast cancer drugs \u2013 Gemcitabine \u2013 was found as repurposed drug from LINCS for breast cancer stage IV (Fig. 14). A repurposed drug from LINCS \u2013 Homoharringtonine was found to be structurally similar with Everolimus and Vinblastine Breast cancer drugs (greater than 70%). On the other hand, as shown in Fig.", + "Rapamycin has serious side effects, particularly as an immunosuppressor, and thus it is not suitable as an antiaging drug.As in sirtuins, however, these studies highlight the road from basic discovery on the biology of aging to antiaging interventions.Further studies of the TOR pathway and of repressors more specific of its downstream signaling pathway are ongoing.Whether rapamycin produces a change in another parameter related to energy uptake or utilization is unknown, and determining which of its effects modulate lifespan is an important unsolved question.Like resveratrol, TOR has attracted considerable attention from the pharmaceutical industry, particularly in the context of cancer (Meric-Bernstam and Gonzalez-Angulo, 2009)." + ], + [ + "FUTURE DIRECTIONS: HIGHER RESOLUTION DATA VIA HIGHER THROUGHPUT ASSAYS One inescapable conclusion of the aggregate results of genome-wide studies of aging to date (see summary Table 1) is that we have not come close to saturating the number of potentially lifespan-altering genes in any organism.This is in no small part because directly generating survival curves is a relatively time-consuming process in most model organisms using current methods.There are several possible ways to address this.One way that has been tried is by attempting to find surrogate phenotypes [72,73,126] that can be screened more rapidly, or even scored under selection.Another is mining candidates from the many whole-genome expression profiles.Results to date with these have been very fruitful, but have not suggested that these methods alone will rapidly saturate our search for lifespan-and healthspan-altering genes in tractable model organisms.", + "Genetic linkage studies of long-lived human families identified a longevity locus while candidate gene approaches have been used to identify and confirm the association between specific variants in the FOXO3A gene and human longevity [3\u20137]. Genome-wide association studies have also been used to identify the association of APOE with life 123 Aging Clin Exp Res span and have yielded insights into potential biological pathways and processes related to aging. Despite these successes, several problems are inherent in human longevity studies including potentially high degrees of environmental heterogeneity, genetic diversity, and lack of birth matched controls, among others [8].", + "Additional association studies with these families and replication of these results with an independent data set should facilitate the positional cloning of a gene that influences the ability to age well and achieve exceptional longevity.Identification of the genes in humans that allow certain individuals to live to extreme old age should lead to insights on cellular pathways that are important to the aging process.", + "The aging process most certainly is under highly polygenic controls\u2026 This should not discourage us from pursuing a search for those loci which may be of profound importance to human aging as it ordinarily occurs in most human beings.", + "In most experimentally modified animal model systems, single-gene mutations in many different genes have major life extension effects (Fontana et al., 2010;Kenyon, 2010).However, natural human and animal longevity is presumed to be a complex trait (Finch & Tanzi, 1997).In humans, both candidate gene and genome-wide genetic association approaches have been applied in an attempt to identify longevity loci.The frequency of genetic variants has been typically compared between nonagenarian cases and young controls, revealing loci at which genetic variants may contribute to a higher or lower probability of survival into old age.The initial candidate gene studies aimed at finding human longevity genes were dominated by contradictory results (Christensen et al., 2006).The more consistent evidence obtained by repeated observation in independent cohort studies for association with longevity has so far only been observed for three loci, the apolipoprotein E (APOE) locus (Schachter et al., 1994;Christensen et al., 2006), the FOXO3A locus (Willcox et al., 2008;Flachsbart et al., 2009;Pawlikowska et al., 2009;Soerensen et al., 2010), and the AKT1 locus (Pawlikowska et al., 2009).Thus, despite the expectation that longevity would be influenced by many genetic variants with small effect sizes, the effect of variants has consistently been shown in only three genes.", + "1993), and gene expression microarrays (Pletcher et al. 2002). Given the ambiguities and limitations of large-effect mutant studies of aging, discussed earlier, those publications do not provide very useful evidence with respect to the question of the number of loci that affect aging. At present, the best answer to the question of the number of genes controlling aging is many (Rose and Long 2002), in keeping with the original expectations of evolutionary biologists. However, studies of the genetics of the experimental evolution of aging are now amenable to the application of genomic methods.", + "Accepted Article \u00a9 2013 The Authors Aging Cell \u00a9 2013 Blackwell Publishing Ltd/Anatomical Society of Great Britain and Ireland over 90 years and 1,955 controls between 55 and 80 years did not reveal genome-wide significant loci (Newman et al., 2010) and neither did the analyses of all-cause mortality and survival free of major disease in this cohort (Walter et al., 2011).A smaller Dutch study of 403 nonagenarians and 1,670 controls younger than 65 years identified the APOE gene as a mortality locus (Deelen et al., 2011), which was confirmed in a German study of 763 long-lived individuals and 1,085 younger controls (Nebel et al., 2011) and a longitudinal study of 1,606 Danes showed that the effect size of this association increases at the highest ages (Jacobsen et al., 2010).Apparently, the influence of the common genetic variation on longevity is small which requires large meta-GWA studies for identification.Alternatively, rare genetic variants may play a more important role in longevity.Since the previous linkage studies showed contradictory results potentially due to heterogeneity in the longevity phenotype, it is expected that longevity is influenced by many private rare variants.", + "The lack of success in the identification of genes related to aging in humans may be due to the complexity of the phenotype.One approach to investigate aging and longevity is to compare frequencies of genetic variants between nonagenarians or centenarians and the general population.This approach led to the discovery of an association between APOE (Deelen et al., 2011;Ewbank, 2007;Gerdes et al., 2000) and more recently FOXO3A (Anselmi et al., 2009;Flachsbart et al., 2009;Li et al., 2009a;Pawlikowska et al., 2009;Willcox et al., 2008) and human aging and longevity.However, a recent genome-wide association study (GWAS) of individuals reaching the age of 90 or older failed to identify genome-wide significant variants (Newman et al., 2010).", + "Several explanations are possible for the lack of genomewide significant findings.First, mortality is arguably 1 of the most complex phenotypes, and several trajectories toward extreme old age have been identified (Evert et al., 2003).Multiple genes could mediate the aging process but would have their effects through numerous different patho-physiological processes and diseases that act as intermediate factors on the pathway to death (de Magalhaes et al., 2010).Therefore, any common variation in genes associated with aging probably has a small effect.", + "Second, the largely negative findings of this and other studies contrast with the intriguing animal studies of longevity.Very large effects of single genes on lifespan have indeed been observed in laboratory animals, but humans often have several homologues of these genes which might significantly differ in function or compensate for mutated genes through redundant mechanisms (Kuningas et al., 2008).This could explain why our top findings did not include genes in these pathways found in animal models.Animal models also represent genetically homogenous populations and are exposed to controlled environmental influences.The lack of replication of animal model findings in humans suggests that the use of knockout animals may not provide the optimal approach to understanding the variation in survival in humans as interactions with environmental factors may obscure the associations and prevent the identification of loci in humans.", + "1993), and gene expression microarrays (Pletcher et al. 2002). Given the ambiguities and limitations of large-effect mutant studies of aging, discussed earlier, those publications do not provide very useful evidence with respect to the question of the number of loci that affect aging. At present, the best answer to the question of the number of genes controlling aging is many (Rose and Long 2002), in keeping with the original expectations of evolutionary biologists. However, studies of the genetics of the experimental evolution of aging are now amenable to the application of genomic methods.", + "The remarkable discoveries of the past 2 decades showing that single genes can regulate aging in model organisms demonstrate that aging can be genetically manipulated (Finch and Ruvkun, 2001;Kenyon, 2010).Hundreds of genes that modulate longevity have now been identified in model organisms (de Magalha \u02dces et al., 2009a).In some cases (e.g., in worms), mutations in single genes can extend lifespan by almost 10-fold (Ayyadevara et al., 2008).Nonetheless, aging is a complex process that derives not from single genes but from the interactions of multiple genes with each other and with the environment.Evidence from animal systems shows a major impact of the environment on aging, yet environmental manipulations of aging act through genes and proteins, usually by triggering signaling pathways and modulating gene expression.In fact, some genes have been shown in model organisms to have varying effects on lifespan depending on diet (Heikkinen et al., 2009).Genes that can regulate aging in model organisms cannot be directly applied to humans through genetic manipulations for numerous legal, ethical, and technical reasons.If we could understand how the environment modulates these aging-related genes, we might be able to create antiaging therapies applicable to humans, potentially through diet, lifestyle, and even pharmacological interventions.Therefore, understanding genome-environment interactions in the context of aging can be a powerful approach to identify attractive targets for drug design.", + "Results from mutational analysis across eukaryote model organisms have shown unexpected conservation of genes and processes regulating aging.While unique properties exist within particular organisms that modulate these foundational networks, the conservation provides a tool to refine human genetic studies.As noted, GWAS for human longevity metrics suffer from large sample size requirements to obtain statistical resolution due to multiple hypothesis testing across the genome.Assuming that evolutionary genesets for longevity could be generated with confidence, an intersection of them with human variation data would increase the sensitivity of association studies.This would serve as a selective filter to refine the number of loci investigated for association in human populations.Similarly, such evolutionary filters could refine analysis of rare, unique variation within genome sequence data from extremely long-lived cohorts.A similar approach to refine human longevity GWAS used an intersection with age-related disease datasets.This 'disease-informed' GWAS helped refine candidates (iGWAS, Fortney et al., 2015), though, it should be noted that this particular strategy would further blur the distinction between aging and longevity as discussed above.The definition of gene sets from evolutionary experiments in longevity, across clades, would similarly empower detection of networks previously hidden under GWAS in human population analyses (Figure 3).", + "ANALYSIS OF HUMAN VARIATION IN THE GENETIC CONTROL OF LONGEVITY Heritability studies have convincingly demonstrated that at least some fraction of human lifespan is heritable.In tandem, large-scale genome-wide association studies (GWAS) have identified numerous loci associated with age-related traits (Buniello et al., 2019).While genetic studies have functionally shown an inverse effect of multiple age-related, diseaseassociated variants on lifespan regulation, the number of well-replicated longevity-conferring variants remains limited to variants in APOE (ApoE \u03b52), and more recently, CDKN2A/B and IL6 (see Table 1).To date, studies in humans have been hampered by the specific phenotype definitions used, sample sizes of the extreme phenotypes, and modest heritability of the longevity-related traits (Breitbach et al., 2019).This is due to the complex interplay of biological and social factors involved in human aging, as well as the limited power of GWAS, which require sampling thousands of subjects to achieve statistical significance (Breitbach et al., 2019).Genetic studies of aging have also been hindered by an inconsistent use of definitions of aging (reviewed in Baghdadi et al., 2020).The two main ways of conducting research on the genetics of longevity in human populations are by studying (i) the lifespan (continuous trait, years lived) and (ii) the longevity (dichotomous trait, i.e., being among the longest-lived individuals within a specific population).These complexities have limited the resolution and capability of broad association studies of human longevity.Importantly, these genomic analyses focus on a shift of survival in a population; these variables may be genetically distinct from the mechanisms establishing potential for longevity overall (Figure 1A).We argue that an understanding of this shift in lifespan as well as genetic mechanisms of regulating a species specific 'set points' (Figure 1B) will aid in the conceptual distinction of aging and longevity in humans.", + "TRANSLATION OF LONGEVITY MODEL ORGANISMS AND CORE AGING PATHWAYS Genetic studies on lifespan have proven to be challenging.While longevity is a defining trait for a given species, the lifespan of individuals is of limited heritability, making analyses more difficult.Exceptional human life span, although a rare phenotype, is likely multifactorial; refined analyses are required to obtain statistically robust genomic signatures of longevity (Zhang et al., 2020) and these have proven elusive.Unlike laboratory models, the effect of environmental variance cannot be controlled in human studies, potentially masking purely biological aging mechanisms.Even laboratory models cannot replicate the complex \"environment\" of humans; it includes psychosocial, economic, and cultural factors, rather than strictly biological.These human-specific confounders are difficult or impossible to target in traditional model organisms.Despite these limitations, experimentally tractable model organisms have proven invaluable in deciphering the purely genetic contribution to lifespan, including genes and pathways conserved across the tree of life.", + "Our analyses show that it is extremely unlikely that there is a single gene harboring rare protein-altering variants shared by all supercentenarians but no controls.It is not surprising that a highly complex trait such as longevity is not explained by a single Mendelian gene.", + "With modern genomic technologies and largescale data analysis methods, it is possible to sift through the genes of populations to find the loci that act to postpone aging. [3]There are uncertainties with the comparison of populations with different rates of aging.However, it is superior to experimental designs that only consider age-dependence or dietary-response, without determining causal mechanisms.", + "Although the models data set comprises all genes (to our knowledge) shown by the time of the latest update to statistically increase longevity or alter the aging process in a noticeable way, in the human data set we try to evaluate whether a given intervention is affecting the aging process itself or not.For example, many mutations may increase longevity by decreasing the incidence of specific diseases, rather than by altering the basic process of aging (de Magalh\u00e3es et al ., 2005a(de Magalh\u00e3es et al ., , 2005b)).Therefore, the human data set is not merely an extension of the work conducted in model organisms and of its bibliography, but a manually selected list of the most pertinent human aging candidate genes, each presented with a higher annotation level.We cite studies on whether the functions of aging-associated genes in model organisms are conserved in their human orthologues.Likewise, we cite flaws in previous studies based on new published observations, although we have a neutral stance on conflicting findings from different research groups.Our policy is to cite all conflicting reports and let visitors make their own decisions on how to interpret them.By contrast, each entry in GenAge model organisms has only one reference: the first publication reporting an association of the gene with longevity or aging.Moreover, one of the latest enhancements in the human data set was the inclusion of Gene Ontology annotation.Gene Ontology terms and annotation files were obtained from the Gene Ontology Consortium website (http://www.geneontology.org/ ) and provide an additional layer of description for the gene products in a cellular context (Ashburner et al ., 2000).", + "Conclusions and prospects Over the past two decades the human aging field has built up the necessary resources to study the biology of aging and longevity by establishing human populations with a diversity of designs.Meta-analyses integrating genetic and phenotypic datasets have successfully identified variants associated with a range of age-related traits and diseases.Despite these accomplishments, the number of novel leads contributing to human lifespan regulation is limited.Although positive regions of linkage and suggestive GWAS hits have been reported, the field has not yet identified the loci that explain the clustering of longevity in families and the variation in biological aging rate in the population.As for animal models, down-signaling of the IIS and mTOR pathway appeared to be relevant in humans.These findings are being followed up by molecular and physiological profiling using skin, fat and muscle tissue of long-lived family members and controls.Human studies now also include the response of nutrient sensing systems to the application of dietary and physical challenges.", + "Most of the human candidate gene studies were performed in cross-sectional designs (Box 1 and Fig. 1), comparing allele frequencies of potential longevity loci between highly aged individuals and young controls.The candidate gene studies based on single genes have pointed a role for genes involved in, e.g., GH/insulin/IGF-1 signaling, immune regulation, and lipoprotein metabolism (Supporting Information Table S1), although most of these results have not (yet) been confirmed in sufficient independent studies.The most convincing human longevity loci today are APOE and FOXO3A which have frequently been associated with longevity in cross-sectional studies (see for a review [26]) and survival in prospective studies [27][28][29] (Fig. 3).APOE encodes the protein apolipoprotein E which seems to play a role in e.g., lipoprotein metabolism, cognitive function, and immune regulation [30].FOXO3A encodes the protein forkhead box O3 which acts as a transcription factor for many different genes involved in processes like apoptosis and oxidative stress [31]." + ], + [ + "Funding: See page 22 Preprinted: 24 June 2021 Received: 03 November 2021 Accepted: 01 April 2022 Published: 07 April 2022 Reviewing Editor: Joris Deelen, Max Planck Institute for Biology of Ageing, Germany \u200d \u200dCopyright Mozhui et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited. Editor's evaluation This article used three newly generated epigenetic predictors to test how they differ between genetically diverse mice from the BXD family (by looking at metabolic traits and lifespan).", + "Longevity data was obtained from a parallel cohort of BXD mice housed in the same UTHSC colony, and members of this \u2018longevity cohort\u2019 were allowed to age until natural death (more detail on the longevity cohort can be found in Roy et al. , 2021). Males were excluded and strain-\u00adby-\u00addiet lifespan summary statistics were derived. Only strain-\u00adby-\u00addiet groups with five or more observations for lifespan were included in the correlational analyses with the epigenetic predictors. Multivariable EWAS Site-\u00adby-\u00adsite differential methylation analysis (EWAS) was performed on the 27,966 CpGs using a multivariable regression model.", + "Funding: See page 22 Preprinted: 24 June 2021 Received: 03 November 2021 Accepted: 01 April 2022 Published: 07 April 2022 Reviewing Editor: Joris Deelen, Max Planck Institute for Biology of Ageing, Germany \u200d \u200dCopyright Mozhui et al. This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited. Editor's evaluation This article used three newly generated epigenetic predictors to test how they differ between genetically diverse mice from the BXD family (by looking at metabolic traits and lifespan).", + "Longevity data was obtained from a parallel cohort of BXD mice housed in the same UTHSC colony, and members of this \u2018longevity cohort\u2019 were allowed to age until natural death (more detail on the longevity cohort can be found in Roy et al. , 2021). Males were excluded and strain-\u00adby-\u00addiet lifespan summary statistics were derived. Only strain-\u00adby-\u00addiet groups with five or more observations for lifespan were included in the correlational analyses with the epigenetic predictors. Multivariable EWAS Site-\u00adby-\u00adsite differential methylation analysis (EWAS) was performed on the 27,966 CpGs using a multivariable regression model.", + "Conclusions These results suggest a novel locus influencing survival in the B6/D2 genetic background, perhaps via a metabolic disorder that emerges by 200 days of age in male animals. Keywords Pathology Longevity \u2401 Lifespan \u2401 Mouse \u2401 Linkage \u2401 Introduction Longevity, the quintessential complex trait, likely reflects all aspects of an organism\u2019s life history. In humans, the estimated heritability of age at death is estimated at 25\u201333 % [1]. Genetic contributions to mortality rates are thus of great interest and may aid in the understanding of disease etiology and the process of aging itself [2].", + "Leduc MS, Hageman RS, Meng Q et al (2010) Identification of genetic determinants of IGF-1 levels and longevity among mouse inbred strains. Aging Cell 9(5):823\u2013836. doi:10.1111/j.14749726.2010.00612.x 10. Lang DH, Gerhard GS, Griffith JW et al (2010) Quantitative trait loci (QTL) analysis of longevity in C57BL/6J by DBA/2J (BXD) recombinant inbred mice. Aging Clin Exp Res 22(1):8\u201319 11. Gelman R, Watson A, Bronson R et al (1988) Murine chromosomal regions correlated with longevity. Genetics 118(4):693\u2013704 12. Jackson AU, Galecki AT, Burke DT et al (2002) Mouse loci associated with life span exhibit sex-specific and epistatic effects.", + "Here, we have extended this analysis to search for genotypes related to survival to the age of 800 days in a population of a reciprocal F2 cross between (B6) and (D2) mice. Since QTL for longevity in mice have shown strong sex specificity [10, 12], we conducted sex-specific analyses. In addition, we also determined whether there were any change in pathology changes associated with the loci that showed frequency distortions with aging. To confirm the associations of the loci of interest with longevity and pathology, we performed replication analyses on a panel of BXD recombinant inbred strains.", + "Methods We examined a population of 1200 mice that were F2 generation offspring of a 4-way reciprocal cross between C57BL6/J and DBA2/J strains. Animals were sacrificed at age 200, 500, or 800 days and genotyped at 96 markers. The 800 days old cohort, which were the survivors of a much larger breeding group, were examined for enriched frequency of alleles that benefit survival and depletion of alleles that reduce survival. Results Loci on Chr 13 in males and on Chr X in females were significantly distorted from Mendelian expectations, even after conservative correction for multiple testing.", + "Assessing epigenetic age in long-lived mice The epigenetic-aging model was applied to the methylation profiles of long-lived mice and the age-matched controls not used for training (Additional file 2: Datasets used summary).Reductions in age were calculated by subtracting the epigenetic ages of the untreated, wild-type mice from those of the treated mice of the same genetic background.To assess the significance, we used an ANOVA for all 22-month-old mice or only 22-month-old UM-HET3 mice.We also compared the epigenetic ages between treatments with their agematched controls from the same genetic background using a t-test (Additional file 4: Treatment vs wild type stats).", + "Editor's evaluation This article used three newly generated epigenetic predictors to test how they differ between genetically diverse mice from the BXD family (by looking at metabolic traits and lifespan).The authors subsequently identified several quantitative trait loci for the different predictors, using linkage analysis, and performed transcriptome and proteome analyses of liver and adipose tissue.The described results provide some important new insights on the underlying biology of epigenetic mouse aging and may be used to inform future studies in other model organisms and humans focused on studying the relationship between epigenetic aging and metabolism.", + "352(6291): p. aad0189. Liao, C.Y. , et al. , Genetic variation in the murine lifespan response to dietary restriction: from life extension to life shortening. Aging Cell, 2010. 9(1): p. 92-5. Johnson, M., Laboratory Mice and Rats. Mater. Methods, 2012. 2: p. 113. Fontaine, D.A. and D.B. Davis, Attention to Background Strain Is Essential for Metabolic Research: C57BL/6 and the International Knockout Mouse Consortium. Diabetes, 2016. 65(1): p. 25-33. Simon, M.M. , et al. , A comparative phenotypic and genomic analysis of C57BL/6J and C57BL/6N mouse strains. Genome Biol, 2013. 14(7): p. R82. Lilue, J., et al.", + "Materials and Methods Study Design.Female mice of the long-lived F 1 hybrid strain C3B10RF1 were fed and maintained as described (7).Briefly, mice were weaned at 28 days, individually housed, given free access to water, and randomly assigned to study groups.Comparisons between five groups of mice were used to determine the effects of aging and CR on gene expression.Control young (7-month-old; n \u03ed 3) and old (27-month-old; n \u03ed 3) mice were fed 95 kcal of a semipurified control diet (Harlan Teklad, Madison, WI; no.TD94145) per week after weaning.Long-term CR (LT-CR) young (7-month-old; n \u03ed 3) and old (27-month-old; n \u03ed 3) mice were fed 53 kcal of a semipurified CR diet (Harlan Teklad; no.TD94146) per week after weaning.Short-term CR (ST-CR) mice were 34-monthold control mice that were switched to 80 kcal of CR diet for 2 weeks, followed by 53 kcal for 2 weeks (n \u03ed 3).The effects of age on gene expression in control mice were determined by comparison between results from the young control and the old control groups.The effects of LT-CR on gene expression were determined by comparison between results from the young control and the young LT-CR groups, and from the old control and the old LT-CR groups.The effects of ST-CR were determined by comparison between results from the old control and the ST-CR groups.Mice were fasted for 48 h before killing.Mice were killed by cervical dislocation, and the livers were rapidly excised and flash frozen in liquid nitrogen.No signs of pathology were detected in any of the animals used.All animal use protocols were approved by the institutional animal use committee of the University of California, Riverside.", + "Accessing data resources in the mouse phenome database for genetic analysis of murine life span and health span. J. Gerontol. A Biol. Sci. Med. Sci. 71 (2), 170\u2013177. Brown, R.E. , Stanford, L., Schellinck, H.M., 2000. Developing standardized behavioral tests for knockout and mutant mice. ILAR J. 41 (3), 163\u2013174. Bubier, J.A. , Jay, J.J., Baker, C.L. , Bergeson, S.E. , Ohno, H., Metten, P., Crabbe, J.C., Chesler, E.J. , 2014. Identi\ufb01cation of a QTL in Mus musculus for alcohol preference, withdrawal, and Ap3m2 expression using integrative functional genomics and precision genetics. Genetics 197 (4), 1377\u20131393. Burn, C.C. , 2008.", + "Our own work has taken a different tack: we have attempted to determine whether mutations with differential effects on aging may be present within the many available populations of laboratory-adopted inbred mice.The goal is not so much to clone these genes-if indeed they existbecause positional cloning strategies of this kind require many thousands of animals and would be extremely expensive using an assay, age at death, that is itself so costly.Instead, the goal has been to use gene mapping methods to test hypotheses about aging and to develop new animal models that will be useful for testing well-specified hypotheses about the molecular basis for age-dependent changes.In the absence of a validated battery of biomarkers of aging, we (like most others) have reluctantly decided to use mouse life span as a crude surrogate for aging itself, reasoning that genetic alleles that extend life span well beyond the median for the tested population may be operating via an influence on aging itself.Work conducted using recombinant inbred mouse stocks (Gelman et al., 1988;de Haan and Van Zant, 1999) has suggested that life-span differences between pairs of inbred mouse lines might reflect the influence of as few as 4-7 polymorphic loci, providing some basis for hope that some of these would have an effect large enough to be detected by a genome scan experiment involving 300-1,200 mice.", + "The available dataset also provides examples in which genetic variants seem to influence the risk of specific late-life diseases.Figure 8-6, for example, shows longevity results for mice stratified by their inheritance at the 12th chromosome locus D12Mit167.This is a locus associated with differential longevity in both male and female mice, with the strongest effect (adjusted p < 0.01) seen in those mice living more than 657 days (Jackson et al., unpublished results).The longest-lived mice are those that inherit both the C57BL/6 allele from their mother and the C3H allele from their father; on average, they survive 93 days longer than siblings with the BALB plus C3H combination.Figure 8-6 shows that the D12Mit167, like the pair of loci illustrated in Figure 8-5, has significant and similar effects in mice dying of cancer (85 days) and in mice dying of non-neoplastic diseases (126 days).A more detailed analysis of the cancers, however, suggests that while lymphoma and hepatoma victims are equally protected by the favorable alleles (effect sizes of 93 and 167 days, respec- mice of two subgroups: those dying of the urinary syndrome MUS, and those dying of all other causes.The genetic analysis contrasts mice with both the C57BL/6 allele at D4Mit84 and the C3H allele at D9Mit110 to mice with any of the three other allele combinations.In the males dying of causes other than MUS, this allele pair is associated with a 170-day increment in longevity (post-hoc p < 0.00003).But for males that do die of MUS, the same allele combination is associated with a 187-day decline in mean life span (post-hoc p < 0.03).This effect is thus pleiotropic, in that these alleles accelerate death in mice susceptible to MUS, while postponing death for all other males in the population.Although these loci are associated with differential longevity in mice that do develop MUS, they do not have a significant effect on the chances that MUS will indeed occur (not shown).The risk of developing MUS seems to be under control of a separate locus on chromosome 6.As shown in the bottom panel of Figure 8-7, males that inherit the C3H allele at D6Mit268 are far more likely to develop MUS (28 percent risk) than are their brothers who receive the DBA/2 allele at this locus (7 percent risk; p = 0.012 by two-tailed Fisher's exact test).", + "Previously, the methylation status of CpG sites within the genes Prima1, Hsf4, Kcns1 was shown to qualify as a reliable predictor of chronological age of B6 mice.10 This same study also revealed enhanced epigenetic aging of the D2 strain in accordance with its general reduced mean life span, supporting the possibility that the panel might also serve as a marker for the biological age in mice. Applying this B6trained marker panel to our (congenic) experimental strains, we observed that epigenetic age predictions correlated with chronological age in B6 (R2=0.93) and line A mice (R2=0.89).", + "34. Gelman R, Watson A, Bronson R & Yunis E Murine chromosomal regions correlated with longevity. Genetics 118, 693\u2013704 (1988). [PubMed: 3163317] 35. Houtkooper RHet al.The metabolic footprint of aging in mice. Sci. Rep1, (2011). 36. Houtkooper RHet al.Mitonuclear protein imbalance as a conserved longevity mechanism. Nature497, 451\u2013457 (2013). [PubMed: 23698443] 37. Williams EGet al.An Evolutionarily conserved role for the aryl hydrocarbon receptor in the regulation of movement. PLOS Genet. 10, e1004673 (2014). [PubMed: 25255223] 38. Lang DHet al.Quantitative trait loci (QTL) analysis of longevity in C57BL/6J by DBA/2J (BXD) recombinant inbred mice. Aging Clin. Exp. Res. 22, 8\u201319 (2010).", + "For females, hairs of the congenic mice grew 31% faster, also highly significant (P = 0.0006, 1-tailed). These results validated the presence of a gene in the differential region affecting FE. Discussion We report the outcomes of a quantitative genetic study on aging and longevity in the mouse. We studied an extant series of recombinant inbred strains (ILSXISS) that have been used both in DR aging studies as well as to study alcohol sensitivity (Williams et al. , 2004).", + "FOURTH STEP: MEDICAL TESTING OF CANDIDATE DRUGS Many genes are common between fruit flies and mammals, but by no means all.Therefore, it is important to test biochemical pathways that work in fruit flies with mammals.Mice are the system of choice, as they have relatively short lifespans (2 -3 years) and a great deal is known of their genetics.Mortality rate measurements, like those studied in fruit flies, [10] might speed up mouse trials to just 6-12 months.Mouse trials would also help address issues of safety, such as liver and kidney toxicity, before going on to human trials.", + "Experimental Procedures Mouse Breeding, Maintenance, and Longevity.Cdc42GAP \u03ea/\u03ea and p53 \u03ea/\u03ea mice were generated as previously described (6,35), and the mice used in the studies were mixed C57BL/6 \u03e9/\u03ea 129/Sv inbred.Littermates of different genotypes were housed and fed freely with standard mouse chow over their life span in a pathogen-free environment and were monitored for vitality and longevity.Mice exhibiting extreme morbidity were euthanized and subjected to necropsy.All animal procedures were approved by the Institutional Animal Care and Use Committee at the Children's Hospital Research Foundation." + ], + [ + "Genetic associations for two biological age measures point to distinct aging phenotypes. Aging Cell 20:e13376. DOI: https://doi.org/10.1111/acel.13376, PMID: 34038024 Lang DH, Gerhard GS, Griffith JW, Vogler GP, Vandenbergh DJ, Blizard DA, Stout JT, Lakoski JM, McClearn GE. 2010. Quantitative trait loci (QTL) analysis of longevity in C57BL/6J by DBA/2J (BXD) recombinant inbred mice. Aging Clinical and Experimental Research 22:8\u201319. DOI: https://doi.org/10.1007/BF03324809, PMID: 20305363 Lappalainen T. 2015. Functional genomics bridges the gap between quantitative genetics and molecular biology. Genome Research 25:1427\u20131431.", + "Pharmacol Biochem Behav 81, 764\u2013768. Hsu, H.C., Lu, L., Yi, N., Van Zant, G., Williams, R.W. & Mountz, J.D. (2007) Quantitative trait locus (QTL) mapping in aging systems. Methods Mol Biol 371, 321\u2013348. Hurlin, P.J. & Huang, J. (2006) The MAX-interacting transcription factor network. Semin Cancer Biol 16, 265\u2013274. Jones, B.C. , Tarantino, L.M. , Rodriguez, L.A., Reed, C.L. , McClearn, G.E. , Plomin, R. & Erwin, V.G. (1999) Quantitative-trait loci analysis of cocaine-related behaviours and neurochemistry. Pharmacogenetics 9, 607\u2013617. Jones, B.C. , Beard, J.L. , Gibson, J.N. , Unger, E.L., Allen, R.P. , McCarthy, K.A. & Earley, C.J.", + "Genetic associations for two biological age measures point to distinct aging phenotypes. Aging Cell 20:e13376. DOI: https://doi.org/10.1111/acel.13376, PMID: 34038024 Lang DH, Gerhard GS, Griffith JW, Vogler GP, Vandenbergh DJ, Blizard DA, Stout JT, Lakoski JM, McClearn GE. 2010. Quantitative trait loci (QTL) analysis of longevity in C57BL/6J by DBA/2J (BXD) recombinant inbred mice. Aging Clinical and Experimental Research 22:8\u201319. DOI: https://doi.org/10.1007/BF03324809, PMID: 20305363 Lappalainen T. 2015. Functional genomics bridges the gap between quantitative genetics and molecular biology. Genome Research 25:1427\u20131431.", + "Interestingly, the correlation analysis indicates QTL Mapping in Aging Systems 333 Fig. 5. Basic statistics provided by the WebQTL GeneNetwork website. The strain distribution pattern (SDP) of the quantitative trait is presented in the basic statistics page of WebQTL in the following ways: (A) the raw data of the quantitative trait obtained from each BXD recombinant inbred (RI) strain, (B) data mean and distribution, (C) bar graph showing the mean and variable of each strain, and (D) the normal probability plot of the SDP.", + "23 Quantitative Trait Locus (QTL) Mapping in Aging Systems Hui-Chen Hsu, Lu Lu, Nengjun Yi, Gary Van Zant, Robert W. Williams, and John D. Mountz Summary Understanding the genetic basis of the effects of aging on the decline in the immune response is an enormous undertaking. The most prominent age-related change in the immune system is thymic involution. This chapter will focus on the use of C57BL/6 J X DBA/2 J (BXD) recombinant inbred (RI) strains of mice to map genetic loci associated with age-related thymic involution in mice.", + "For further prioritization, we converted the mouse QTL regions to the corresponding syntenic regions in the human genome and retrieved GWAS annotations for these intervals (Buniello et al., 2019).We specifically searched for the traits: epigenetic aging, longevity, age of menarche/menopause/puberty, Alzheimer's disease, and age-related cognitive decline and dementia.This highlighted five genes in Eaa11 and three genes in Eaa19 (Supplementary file 4c).We also identified a GWAS that found associations between variants near Myof-Cyp26a1 and human longevity (Yashin et al., 2018), and a meta-GWAS that found gene-level associations between Nkx2-3 and Cutc, and epigenetic aging (Supplementary file 4c; McCartney et al., 2021).", + "Jiang, C. and Zeng, Z. B. (1995). Multiple trait analysis of genetic mapping for quantitative trait loci. Genetics 140, 1111\u20131127. Jin, W., Riley, R. M., Wolfinger, R. D.et al. (2001). The contributions of sex, genotype and age to transcriptional variance in Drosophila melanogaster. Nat Genet 29, 389\u2013395. Kempermann, G., Chesler, E. J., Lu, L. et al. (2006). Natural variation and genetic covariance in adult hippocampal neurogenesis. Proc Natl Acad Sci U S A 103, 780\u2013785. Kendziorski, C. M., Chen, M., Yuan, M. et al. (2006). Statistical methods for expression quantitative trait loci (eQTL) mapping. Biometrics 62, 19\u201327.", + "Hypothesis-free genome-wide approaches have also been undertaken.Genome-wide linkage scans reported evidence for linkage with longevity on chromosome 4q25 (Puca et al., 2001), 3p24-22, 9q31-34, and12q24 (Boyden &Kunkel, 2010).However, the evidence for these loci is still very weak as the results, obtained in centenarians and their families, could not be replicated in nonagenarian sibling pairs (Beekman et al., 2006) or have yet to be tested in other studies.A meta GWAS of survival to 90 years or older in 1836 cases and 1955 controls did not find any significant genome-wide associations (Newman et al., 2010).Thus far, hypothesis-free approaches have not identified any loci involved in longevity.", + "Abiola O, Angel JM, Avner P, Bachmanov AA, Belknap JK, Bennett B, et al. The nature and identification of quantitative trait loci: a community\u2019s view. Nat Rev Genet. Nature Publishing Group; 2003; 4: 911\u2013916. https://doi.org/10.1038/nrg1206 PMID: 14634638 18. Grupe A, Germer S, Usuka J, Aud D, Belknap JK, Klein RF, et al. In silico mapping of complex diseaserelated traits in mice. Science. American Association for the Advancement of Science; 2001; 292: 1915\u20131918. https://doi.org/10.1126/science.1058889 PMID: 11397946 19. Pletcher MT, McClurg P, Batalov S, Su AI, Barnes SW, Lagler E, et al.", + "coid levels, etc.The mapping project should thus help to guide the search for human genes that regulate these interesting phenotypes and at the same time spark new investigations, in animal models, for the biochemical differences that mediate the genetic effects we detect.At the same time, the dataset that emerges should also allow us to test more general questions about the nature of aging and its genetic control.We may, for example, be able to identify QTLs that not only retard the development of one or more age-sensitive T-cell subsets, but also retard age-dependent changes in protein conformation, bone matrix turnover, and brain GFAP levels.Such a finding would imply that these changes are influenced, together, by a common biochemical pathway, and the corresponding QTLs would be excellent candidates for genes that regulate aging per se, rather than merely one among the many more agesensitive traits.In the same way, it will be of particular interest to determine if QTLs that regulate age-sensitive traits also are associated with differences in life span, and conversely if QTLs identified on the basis of longevity effects modify one (or nearly all?) of the age-sensitive traits in our test battery.", + "The strategy for mapping such quantitative trait loci (QTL) involves looking for preferential segregation of specific alleles or allele combina-tions in mice that differ in life span (or, more generally, any age-sensitive trait of interest).Our test population, called UM-HET3, consisted of a group of mice bred as the progeny of females of the (BALB/c \u00d7 C57BL/6)F1 genotype and males of the (C3H/HeJ \u00d7 DBA/2)F1 genotype.Mice bred in this way are, from a genetic perspective, all siblings; each shares a random half of its alleles with every other animal in the UM-HET3 population.The current set of analyses was conducted when genotype and longevity data were available from a group of 110 virgin males and 143 virgin females.The analytical method adjusted, by permutation testing, for Type I errors attributable to the simultaneous evaluation of multiple linkage hypotheses, and also included gender as a covariate to look for instances of sex-specific genetic effects.Because we had particular interest in regulation of late-life diseases rather than in causes of premature death, and because of evidence that genetic influences on mouse longevity were particularly strong when early deaths were not considered (Covelli et al., 1989), we repeated each analysis after exclusion of those animals dying before 657 days of age, i.e., the age at which 20 percent of the animals had already died.", + "The proportion of the phenotypic variance accounted for by the QTL yield for Hbact and Hbrear was substantial and of the same order of magnitude as that contributed by age. A small number of age-dependent QTL were found in the midst of a majority of age-stable QTL (see discussion above). These age-sensitive loci point toward genes whose functions are correlated with important behavioral changes during aging.", + "Ageing genes and pathways.Assessing the loci of interest for colocalisation with gene expression quantitative trait loci (eQTL), we find strong evidence (FDR SMR < 5%; P HEIDI > 1%; see \"Methods\") of cis-acting eQTL colocalisation for eight out of 10 loci.In total, we highlight 27 unique genes acting across 32 tissues, especially whole blood (12 genes) and the tibial nerve (7 genes) (Supplementary Data 5).In blood, higher expression levels of BCL3 and CKM (near APOE); CTC-510F12.2, ILF3, KANK2 and PDE4A (near LDLR); USP28 and ANKK1 (near ZW10); and CDKN2B are linked to an increase in multivariate ageing traits (i.e.improved survival), while the opposite is true for EXOC3L2 (near APOE), TTC12 (near ZW10), and FOXO3.For the multivariate signal near SLC4A7 we find colocalisation with expression of NEK10 (liver); for the signal near LPA we find colocalisation with expression of SLC22A1/A3 (multiple tissues) and MAP3K4 (pituitary); and for the signal near FGD6 we find colocalisation with expression of FGD6 itself (adipose/arterial).Including trans-acting eQTL from blood, while keeping the same thresholds for colocalisation, we additionally discover higher expression levels of FOXO3B colocalises with the life-extending signal near FOXO3.When we include genes which could not be tested for heterogeneity (N eQTL < 3), we identify one additional cis-acting and 49 additional trans-acting genes (of which 10 colocalise with the signal near LINC02513) (Table 2; Supplementary Data 5).", + "Jiang, C. and Zeng, Z. B. (1995). Multiple trait analysis of genetic mapping for quantitative trait loci. Genetics 140, 1111\u20131127. Jin, W., Riley, R. M., Wolfinger, R. D.et al. (2001). The contributions of sex, genotype and age to transcriptional variance in Drosophila melanogaster. Nat Genet 29, 389\u2013395. Kempermann, G., Chesler, E. J., Lu, L. et al. (2006). Natural variation and genetic covariance in adult hippocampal neurogenesis. Proc Natl Acad Sci U S A 103, 780\u2013785. Kendziorski, C. M., Chen, M., Yuan, M. et al. (2006). Statistical methods for expression quantitative trait loci (eQTL) mapping. Biometrics 62, 19\u201327.", + "Quantitative trait loci (QTLs) can be identified in several ways, but is there a definitive test of whether a candidate locus actually corresponds to a specific QTL? NIH-PA Author Manuscript Much of the genetic variation that underlies disease susceptibility and morphology is complex and is governed by loci that have quantitative effects on the phenotype. Gene-gene and geneenvironment interactions are common and make these loci difficult to analyse. Here, we present a community\u2019s view on the steps that are necessary to identify genetic loci that govern quantitative traits, along with a set of interpretive guidelines.", + "QTL Analysis in Hematopoiesis 47 3 Quantitative Trait Analysis in the Investigation of Function and Aging of Hematopoietic Stem Cells Hans-Willem Snoeck Summary Extensive genetically determined quantitative variation exists in the number and function of hematopoietic stem cells in inbred mouse strains. Furthermore, aging of hematopoietic stem cells is genetically determined. Gene identification of quantitative trait loci involved in the regulation and aging of hematopoietic stem cells would provide novel insights into regulatory mechanisms that are relevant in vivo and may be clinically important.", + "In order to find the causal loci for heritable differences in transcript levels and possible interactions between age and genotype, we applied a two-time-point model.In this model, we used three factors-(1) relative age, (2) genotype (marker), and (3) the interaction between factors 1 and 2-to explain the differences in gene expression between RILs and age groups.With this mapping procedure, we found almost 900 genes that had an eQTL or gxa eQTL in developing and/or aging worms (P < 0.0001; Fig. 2).Almost half of these genes with heritable transcript differences were found to have a genotype-by-age effect (396 at P < 0.0001; Table 1) allocated to a specific marker, which we coined genotype-by-age expression-QTL ( gxa eQTL).One specific hotspot (trans-band) for gxa eQTL was found on chromosome IV for aging worms and a trans-band for eQTL on chromosome I was detected in developing worms (Fig. 2).", + "NIH-PA Author Manuscript We found three significant QTLs (genetic regions harboring genes controlling these various aging traits, Supplementary Table 5). On chromosome 7, we found a QTL affecting lifespan and fertility after DR that we have named Lfdr1 for \u201clongevity and fertility response to dietary restriction, QTL 1; this QTL also has suggestive effects on FE (Fig. 5D). Two QTLs having significant effects on FE were identified on chromosomes 9 and 15. These we have named Fedr1 and Fedr2, respectively, for \u201cfuel efficiency response to dietary restriction\u201d QTLs 1 and 2.", + "Quantitative trait locus (QTL) mapping in aging systems. Methods in Molecular Biology (Clifton, NJ ). 2007; 371:321\u2013348. Hunter KW, Crawford NPS. The future of mouse QTL mapping to diagnose disease in mice in the age of whole-genome association studies. Annual Review of Genetics. 2008; 42:131\u2013141. Ito R, Robbins TW, Everitt BJ. Differential control over cocaine-seeking behavior by nucleus accumbens core and shell. Nature Neuroscience. 2004; 7:389\u2013397. [PubMed: 15034590] Kapp MB. Ethical and legal issues in research involving human subjects: do you want a piece of me? Journal of Clinical Pathology. 2006; 59:335\u2013339.", + "Jiang, C. and Zeng, Z. B. (1995). Multiple trait analysis of genetic mapping for quantitative trait loci. Genetics 140, 1111\u20131127. Jin, W., Riley, R. M., Wolfinger, R. D.et al. (2001). The contributions of sex, genotype and age to transcriptional variance in Drosophila melanogaster. Nat Genet 29, 389\u2013395. Kempermann, G., Chesler, E. J., Lu, L. et al. (2006). Natural variation and genetic covariance in adult hippocampal neurogenesis. Proc Natl Acad Sci U S A 103, 780\u2013785. Kendziorski, C. M., Chen, M., Yuan, M. et al. (2006). Statistical methods for expression quantitative trait loci (eQTL) mapping. Biometrics 62, 19\u201327." + ], + [ + "Introduction With the development of human genomics research, a large number of studies of the genetics of longevity have been conducted.Scientists from various countries have proposed many different theories concerning the mechanisms of aging from different perspectives, involving oxidative stress, energy metabolism, signal transduction pathways, immune response, etc. [1,2].These mechanisms interact with each other and are influenced by heredity to some degree [2,3].The identification of longevity-related biological markers is critical to an indepth understanding of the mechanisms of carrier protection against common disease and/or of the retardation of the process of aging.", + "INTRODUCTION Human aging is affected by genes, life style, and environmental factors.The genetic contribution to average human aging can be modest with genes explaining \u223c20-25% of the variability of human survival to the mid-eighties (Herskind et al., 1996;Fraser and Shavlik, 2001).By contrast, genetic factors may have greater impact on survival to the ninth through eleventh decades (Tan et al., 2008).Notably, exceptional longevity is rare and may involve biological mechanisms that differ from those implicated in usual human aging.", + "Introduction Geroscience refers to research aimed at understanding the mechanisms of biological aging (Kennedy et al. 2014).A major goal of geroscience is to define the genetic, epigenetic, and environmental features that determine individual rates of aging.From a translational perspective, a further goal is to use this knowledge to develop interventions that can slow or delay aging in order to promote healthy longevity and increase healthspan, the period of life spent in good health free from chronic disease and disability (Burch et al. 2014;Pitt and Kaeberlein 2015).", + "the maximum human life span.Several avenues to studying aging have placed us on Department of Biology Massachusetts Institute of Technology the threshold of understanding basic underlying mechanisms.These approaches include the identification of Cambridge, Massachusetts 02139 key genes and pathways important in aging; genetic studies of heritable diseases that cause the appearance of premature aging in affected people; physiological ex-Introduction periments that relate the pace of aging to caloric intake; Is aging the final act in the script of developmental bioland advances in human genetics, as well as cell and ogy?The characteristic changes that are part and parcel molecular biology leading to an understanding of the of aging appear similar to developmentally regulated basis of many diseases of aging.Strikingly, single gene programs.But why would aging mechanisms have been mutations have been found to significantly extend the evolutionarily selected as advantageous?Indeed, evolife span in C. elegans, yeast, and, most recently, Drolutionary biologists might argue that aging occurs by sophila, suggesting that aging may be relatively simple, default due to the absence of selection in the postreproat least in these organisms.Further, the limited replicaductive phase of life.By this view, the aging process is tion potential of human cells in culture has been attribnot programmed, but, rather, the detritus of the absence uted to a specific mechanism (i.e., the shortening of of selection for maintenance (Medawar, 1952; Kirkwood, telomeric ends of chromosomes).An important chal- 1977).However, it is quite reasonable that any mechalenge is now to relate these recent findings to the more nisms that sprang up to slow or regulate the pace of complex case of human aging.aging would be selected, because lucky individualsIn this review, we will discuss several important mocould potentially give rise to more progeny.Therefore, lecular models of aging that come from current research.it is reasonable to suppose that life span extending pro-These are damage by reactive oxygen species (ROS) cesses have been selected and that these can be viewed generated by metabolism, genome instability, genetias an elaboration of development itself.In principle, cally programmed extension mechanisms, cell death, such extension mechanisms may act to slow or forestall and systemic aging.Questions to be posed include the deleterious changes in an organism that progressively following.What evidence exists for and against these lead to death.The life span of an organism, therefore, models?Can more than one of these models apply to is the sum of deleterious changes and counteracting aging of different tissues in humans-specifically do repair and maintenance mechanisms that respond to organs with continually dividing cells age by the same the damage (Figure 1).mechanism as organs that are postmitotic?Finally, is A priori, one imagines such longevity mechanisms to aging amenable to therapeutic intervention, and would be much less complex than those regulating embryonic such intervention be advisable?development.The spatial and temporal constraints on embryonic development are many, while requirements Oxidative Damage for longevity mechanisms might be much more specific One theory of aging proposes that ROS which are generif there were a single process (or a few processes) whose ated by metabolism cause cumulative damage over a breakdown is the limiting event in longevity (i.e., the lifetime (Harman, 1981).Roughly two to three percent Achilles heel).of oxygen taken up is chemically reduced by the addition Aging is defined when two criteria are met.First, the of single electrons, which are sequentially converted probability of death at any point in time increases with into ROS, including the superoxide anion, hydrogen perthe age of the organism.This statistical definition applies oxide, and the hydroxyl radical.ROS have been shown from yeast to mammals and reflects the progressive to cause molecular damage relatively indiscriminately nature of aging.Second, characteristic changes in pheto proteins, lipids, and nucleic acids.In addition, specific notype occur in all individuals over time due to the limdamage has been observed in the mitochondrial DNA, iting processes.which we consider below in Genome Instability.The phenotypic definition is equally general and is What is the evidence that oxidative damage causes useful in distinguishing the aging process itself from aging?One category of study that is supportive of this diseases of aging, such as cancer and heart disease.view involves animals transgenic for genes encoding Phenotypes of aging affect all of the individuals in a antioxidants.Transgenic Drosophila overexpressing both population, while diseases of aging affect only a subset.Cu/Zn SOD and catalase live 34% longer than controls Both impact on life span, but in different ways.For exam-(Orr and Sohal, 1994).A more recent study shows that ple, the many advances in medicine and public health expression of human SOD1 exclusively in Drosophila in this century have caused a large increase in the averadult motor neurons leads to a 40% extension in life age life span of humans in developed countries.Howspan (Parkes et al., 1998).Further experiments are necever, because these advances have not altered the aging essary to clarify the nature of this primary role of motor neurons in life span.Conversely, mice knocked out for either GPX1 (encoding glutathione peroxidase), SOD1,", + "the maximum human life span.Several avenues to studying aging have placed us on Department of Biology Massachusetts Institute of Technology the threshold of understanding basic underlying mechanisms.These approaches include the identification of Cambridge, Massachusetts 02139 key genes and pathways important in aging; genetic studies of heritable diseases that cause the appearance of premature aging in affected people; physiological ex-Introduction periments that relate the pace of aging to caloric intake; Is aging the final act in the script of developmental bioland advances in human genetics, as well as cell and ogy?The characteristic changes that are part and parcel molecular biology leading to an understanding of the of aging appear similar to developmentally regulated basis of many diseases of aging.Strikingly, single gene programs.But why would aging mechanisms have been mutations have been found to significantly extend the evolutionarily selected as advantageous?Indeed, evolife span in C. elegans, yeast, and, most recently, Drolutionary biologists might argue that aging occurs by sophila, suggesting that aging may be relatively simple, default due to the absence of selection in the postreproat least in these organisms.Further, the limited replicaductive phase of life.By this view, the aging process is tion potential of human cells in culture has been attribnot programmed, but, rather, the detritus of the absence uted to a specific mechanism (i.e., the shortening of of selection for maintenance (Medawar, 1952; Kirkwood, telomeric ends of chromosomes).An important chal- 1977).However, it is quite reasonable that any mechalenge is now to relate these recent findings to the more nisms that sprang up to slow or regulate the pace of complex case of human aging.aging would be selected, because lucky individuals", + "Currently prevailing studies of genetic and biological origin of human health and longevity follow largely two approaches which focus on the aging-related diseases and on individuals with exceptionally long lives (Martin et al. 2007).This study provides de facto the rationale for a new approach.Specifically, Fig. 2 suggests that a promising strategy could be to focus on individuals who died prematurely.Studies of genetic profiles of short-lived subjects compared to those who aged more successfully (i.e., those who lived longer and perhaps healthier lives) can be a core of this strategy.Importantly, this strategy can be naturally implemented in longitudinal studies of aging and longevity by focusing on individuals who died first.", + "T he average human life expectancy has been increasing for centuries 1 .Based on twin studies, the heritability of human lifespan has been estimated to be ~25%, although this estimate differs among studies 2 .On the other hand, the heritability of lifespan based on the correlation of the mid-parent (i.e., the average of the father and mother) and offspring difference between age at death and expected lifespan was estimated to be 12% 3 .A recent study has indicated that the different heritability estimates may be inflated due to assortative mating, leaving a true heritability that is below 10% 4 .The heritability of lifespan, estimated using the sibling relative risk, increases with age 5 and is assumed to be enriched in long-lived families, particularly when belonging to the 10% longest-lived of their generation 6 .To identify genetic associations with human lifespan, several genome-wide association (GWA) studies have been performed [7][8][9][10][11][12][13][14][15][16][17][18][19][20] .These studies have used a discrete (i.e., older cases versus younger controls) or a continuous phenotype (such as age at death of individuals or their parents).The selection of cases for the studies using a discrete longevity phenotype has been based on the survival to ages above 90 or 100 years or belonging to the top 10% or 1% of survivors in a population.Studies defining cases using a discrete longevity phenotype often need to rely on controls from more contemporary birth cohorts, because all others from the case birth cohorts have died before sample collection.Previous GWA studies have identified several genetic variants, but the only locus that has shown genome-wide significance (P \u2264 5 \u00d7 10 \u22128 ) in multiple independent meta-analyses of GWA studies is apolipoprotein E (APOE) 21 , where the ApoE \u03b54 variant is associated with lower odds of being a long-lived case.", + "Introduction Worldwide human populations have shown an increase in mean life expectancy in the past two centuries (Oeppen & Vaupel, 2002).This is mainly because of environmental factors such as improved hygiene, nutrition, and health care.The large variation in healthy lifespan among the elderly has prompted research into the determinants of aging and lifespan regulation.The genetic contribution to human lifespan variation was estimated at 25-30% in twin studies (Gudmundsson et al., 2000;Skytthe et al., 2003;Hjelmborg et al., 2006).The most prominent genetic influence is observed in families in which the capacity to attain a long lifespan clusters (Perls et al., 2000;Schoenmaker et al., 2006).Exceptional longevity can be reached with a low degree of age-related disability (Christensen et al., 2008;Terry et al., 2008), raising the question whether protective mechanisms against disease exist in long-lived subjects.", + "Introduction Human life expectancies are increasing almost everywhere in the world where socio-economic circumstances are permissive (Tuljapurkar et al., 2000) and there is no evidence that a limit to life is anywhere near (Oeppen and Vaupel, 2002).While this increase in life span would prevent a proposed compression of morbidity (Fries, 1980), there is no evidence that higher average life spans are associated with an extension of the period of increased morbidity (Manton and Gu, 2001).On the contrary, older individuals have never been so healthy and further improvements in life style, environmental conditions and medical care are likely to help this trend to continue.Especially the medical sciences now seem poised to push the biological limits of longevity further by a number of innovations that seem to affect basic mechanisms of ageing and disease rather than merely alleviating its symptoms.While in the past medicine contributed mainly to public health advances by redu-cing infectious diseases, thereby helping infant mortality to decline, more recent developments hold promise for a more basic intervention in the processes that underlie age-related decline.An example is atherosclerosis, a common problem in ageing and, along with hypertension, the cause of most cardiovascular disease.Basic medical research has likely contributed significantly to the current dramatic decline in cardiovascular disease by actively intervening in some of its main risk factors, i.e., lipid levels and hypertension (Levi et al., 2002).However, one could question whether age-related diseases should be seen as separate from ageing.In this respect, ageing has been considered as a process of cellular degeneration and death universal to all or most species, increasing the risk of fatal disease in humans and other mammals.Would it be possible to define such a process and ultimately understand it in terms of the timedependent, coordinated action of the products of multiple genes interacting with the environment?If so, then ageing per se rather than the diseases associated with it, may offer a more logical starting point for further increasing healthy life expectancies through prevention and therapy.This is especially true now that we have a working draft of the human genome and are in a position to determine the functional significance of each gene as part of the dynamic network of all genes that ultimately determine the physiology of an organism.Termed 'Functional Genomics', this new discipline is now often called upon to solve the complex problems in biology, such as to understand functional control mechanisms and investigate the role that genotype and environment play in determining disease phenotypes.The question is then if this same approach would apply to ageing as a complex phenotype.What is ageing, how does it differ from its diametrical opposite, i.e., organismal development, and what role can functional genomics play in unraveling the basic causes of ageing and exploit such knowledge for developing new, rational strategies for extending healthy life span?", + "Introduction As a result of improvements in health care and living conditions over the past two centuries, the average human life expectancy has dramatically increased in many regions of the world [1].This major success reflects the great malleability of the ageing process.Unfortunately, for most people, ageing is accompanied with an increased risk of developing age-related illnesses/disabilities and frailty.Therefore new approaches are required to understand the genetic, cellular, and molecular factors controlling ageing to identify strategies to extend healthy life span.", + "The search for the genetic determinants of extreme human longevity has been challenged by the phenotype's rarity and its nonspecific definition by investigators.To address these issues, we established a consortium of four studies of extreme longevity that contributed 2,070 individuals who survived to the oldest one percentile of survival for the 1900 U.S. birth year cohort.We conducted various analyses to discover longevity-associated variants (LAV) and characterized those LAVs that differentiate survival to extreme age at death (eSAVs) from those LAVs that become more frequent in centenarians because of mortality selection (eg, survival to younger years).The analyses identified new rare variants in chromosomes 4 and 7 associated with extreme survival and with reduced risk for cardiovascular disease and Alzheimer's disease.The results confirm the importance of studying truly rare survival to discover those combinations of common and rare variants associated with extreme longevity and longer health span.", + "The search for the genetic determinants of extreme human longevity has been challenged by the phenotype's rarity and its nonspecific definition by investigators.To address these issues, we established a consortium of four studies of extreme longevity that contributed 2,070 individuals who survived to the oldest one percentile of survival for the 1900 U.S. birth year cohort.We conducted various analyses to discover longevity-associated variants (LAV) and characterized those LAVs that differentiate survival to extreme age at death (eSAVs) from those LAVs that become more frequent in centenarians because of mortality selection (eg, survival to younger years).The analyses identified new rare variants in chromosomes 4 and 7 associated with extreme survival and with reduced risk for cardiovascular disease and Alzheimer's disease.The results confirm the importance of studying truly rare survival to discover those combinations of common and rare variants associated with extreme longevity and longer health span.", + "Introduction The recent, remarkable extension of life expectancy is largely attributed to the postponement of mortality at old age (Vaupel, 1997(Vaupel, , 2010)).The years of life gained in the older population residing in developed nations are a success story of public health measures and improved health care.In addition to such external factors, longevity and healthy aging consistently show a modest heritability between 20% and 50% and aging-associated genetic research may provide further insights into the mechanisms of aging (Herskind et al., 1996;McGue et al., 1993;Reed and Dick, 2003).It has been postulated that genes involved in pathways associated with aging identified in animal models, such as insulin-like growth factor (IGF)-insulin signaling, regulation of lipoprotein metabolism, the mTOR pathway, and the oxidative stress response may also influence survival to old or even exceptionally old age in humans (Christensen et al., 2006;Kenyon, 2010;Vellai et al., 2003).However, in humans, common variants within genes involved in these pathways have not been consistently associated with lifespan (Chris-tensen et al., 2006;Kenyon, 2010;Kuningas et al., 2008;Vijg and Suh, 2005).", + "DESIGNS TO STUDY PARAMETERS OF HEALTHY AGEING, MORBIDITY, MORTALITY AND LONGEVITY Human cohorts may vary considerably in their morbidity, mortality and longevity characteristics and yet they have shown a common increase in mean life expectancy in the past two centuries [5].This is mainly due to improved hygiene, nutrition and healthcare.There is a large variation in healthy lifespan among the elderly and remarkably exceptional longevity (EL) can be reached with a low degree of agerelated disability [6,7].Heritability studies comparing the concordance of lifespan in monozygous and dizygous twins estimated a 25 -30% genetic contribution to human lifespan variation [8 -11], which becomes increasingly important at higher ages.The most prominent genetic influence is present in families in which survival to high ages clusters [12,13].Unlike model systems where single-gene mutations have major life extension effects, human longevity is presumed to be a complex trait [14].", + "INTRODUCTION Genomic studies into human longevity are inspired by the fact that, in animal models, healthy lifespan has proved to be remarkably plastic, and major pathways of lifespan regulation have been identified.Considerable lifespan extension has been induced in models as diverse as yeast, worms, fish, flies and rodents by applying genetic manipulation and dietary restriction (DR) (see [1] for review).Reduced activity of nutrient-sensing pathways such as insulin/insulin-like growth factor (IGF-1) signalling (IIS) and target of rapamycin (TOR) signalling mediated lifespan extension, and also the extension of lifespan by DR [2].An interesting observation from the perspective of human ageing is that, in rodents and monkeys, diets restricted in glucose, fat or protein uptake reduced or delayed the risk of cancer and metabolic disease, thus extending the healthspan of the animals [2].Following the discovery of genes and pathways involved in animal lifespan extension, human research has focused on the corresponding candidate human genes with genetic, genomic and epigenetic studies into ageing and longevity.The designs of these studies differ with respect to the selection of naturally occurring phenotypes and the study populations, which include population-based, patient-based, family-based and exposure-based cohorts.", + "GENETIC STUDIES OF HUMAN LONGEVITY Genetic and genomic studies into longevity have been performed based on a hypothesis, referred to as a candidate gene approach.Alternatively, explorative genome-wide analyses have been applied in which genetic variation and gene transcription across the complete genome are being studied for associations with longevity and related traits.Genetic studies into human disease and longevity include candidate gene approaches, genome-wide association studies (GWASs) and genome-wide linkage studies.", + "ANALYSIS OF HUMAN VARIATION IN THE GENETIC CONTROL OF LONGEVITY Heritability studies have convincingly demonstrated that at least some fraction of human lifespan is heritable.In tandem, large-scale genome-wide association studies (GWAS) have identified numerous loci associated with age-related traits (Buniello et al., 2019).While genetic studies have functionally shown an inverse effect of multiple age-related, diseaseassociated variants on lifespan regulation, the number of well-replicated longevity-conferring variants remains limited to variants in APOE (ApoE \u03b52), and more recently, CDKN2A/B and IL6 (see Table 1).To date, studies in humans have been hampered by the specific phenotype definitions used, sample sizes of the extreme phenotypes, and modest heritability of the longevity-related traits (Breitbach et al., 2019).This is due to the complex interplay of biological and social factors involved in human aging, as well as the limited power of GWAS, which require sampling thousands of subjects to achieve statistical significance (Breitbach et al., 2019).Genetic studies of aging have also been hindered by an inconsistent use of definitions of aging (reviewed in Baghdadi et al., 2020).The two main ways of conducting research on the genetics of longevity in human populations are by studying (i) the lifespan (continuous trait, years lived) and (ii) the longevity (dichotomous trait, i.e., being among the longest-lived individuals within a specific population).These complexities have limited the resolution and capability of broad association studies of human longevity.Importantly, these genomic analyses focus on a shift of survival in a population; these variables may be genetically distinct from the mechanisms establishing potential for longevity overall (Figure 1A).We argue that an understanding of this shift in lifespan as well as genetic mechanisms of regulating a species specific 'set points' (Figure 1B) will aid in the conceptual distinction of aging and longevity in humans.", + "Introduction Human longevity is influenced by multiple genetic and environmental factors.Approximately 25-32% of the overall variation in adult lifespan is because of genetic variation that becomes particularly important for survival at advanced age (Hjelmborg et al., 2006).Epidemiological studies have revealed that long-lived individuals (LLI), that is, people surviving to the 95th percentile of the respective birth cohort-specific age distributions (Gudmundsson et al., 2000), frequently show a favorable ('healthy') course of the aging process, with the absence or a delayed onset of agerelated diseases (Hitt et al., 1999).Hence, the LLI offer the key to elucidate the molecular mechanisms underlying the 'healthy aging' phenotype (Perls, 2006).", + "Conclusions and prospects Over the past two decades the human aging field has built up the necessary resources to study the biology of aging and longevity by establishing human populations with a diversity of designs.Meta-analyses integrating genetic and phenotypic datasets have successfully identified variants associated with a range of age-related traits and diseases.Despite these accomplishments, the number of novel leads contributing to human lifespan regulation is limited.Although positive regions of linkage and suggestive GWAS hits have been reported, the field has not yet identified the loci that explain the clustering of longevity in families and the variation in biological aging rate in the population.As for animal models, down-signaling of the IIS and mTOR pathway appeared to be relevant in humans.These findings are being followed up by molecular and physiological profiling using skin, fat and muscle tissue of long-lived family members and controls.Human studies now also include the response of nutrient sensing systems to the application of dietary and physical challenges.", + "Human lifespan variation is mainly determined by environmental factors, whereas the genetic contribution is 25-30% and expected to be polygenic.Two complementary fields go hand in hand in order to unravel the mechanisms of biological aging: genomic and biomarker research.Explorative and candidate gene studies of the human genome by genetic, transcriptomic, and epigenomic approaches have resulted in the identification of a limited number of interesting positive linkage regions, genes, and pathways that contribute to lifespan variation.The possibilities to further exploit these findings are rapidly increasing through the use of novel technologies, such as next-generation sequencing.Genomic research is progressively being integrated with biomarker studies on aging, including the application of (noninvasive) deep phenotyping and omics data -generated using novel technologies -in a wealth of studies in human populations.Hence, these studies may assist in obtaining a more holistic perspective on the role of the genome in aging and lifespan regulation." + ] + ] +} -- cgit v1.2.3