diff options
Diffstat (limited to 'gnqa/data/study1/responses/aging/experts/expert_aging_06.json')
| -rw-r--r-- | gnqa/data/study1/responses/aging/experts/expert_aging_06.json | 150 |
1 files changed, 150 insertions, 0 deletions
diff --git a/gnqa/data/study1/responses/aging/experts/expert_aging_06.json b/gnqa/data/study1/responses/aging/experts/expert_aging_06.json new file mode 100644 index 0000000..e47f351 --- /dev/null +++ b/gnqa/data/study1/responses/aging/experts/expert_aging_06.json @@ -0,0 +1,150 @@ +{ + "created_at": "2024-05-31T20:53:55.182883Z", + "data": { + "amplify": false, + "answer": "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 numerous different pathophysiological processes and diseases. Secondly, any common variation in genes associated with aging probably has a small effect, requiring large studies for identification. Thirdly, human studies face issues like environmental heterogeneity, genetic diversity, and lack of birth matched controls. Lastly, the influence of environmental factors and human-specific confounders like psychosocial, economic, and cultural factors can potentially mask purely biological aging mechanisms, making the analysis more difficult.", + "context": { + "03a4f57c-3a11-4d3d-a1e9-6d0d8bdb7cb7": [ + { + "document_id": "03a4f57c-3a11-4d3d-a1e9-6d0d8bdb7cb7", + "text": "\n\nRecent developments on the genetics of aging can be seen as several streams of effort.In general, humans show a relatively modest (<50%) heritability of life spans (results obtained from twin studies discussed below).The apoE polymorphisms are remarkable for their influence on both cardiovascular disease and Alzheimer disease.In contrast, rare mutant genes with high penetrance cause these same diseases but with early onset and a major shortening of the life span.Shortlived laboratory models (fruit flies, nematodes, mice) are yielding rapid advances, with the discovery of mutants that increase life spans in association with altered metabolism, which leads to questions on the physiological organization of aging processes.Although these early findings do not show that a conserved genetic program actually controls aging processes across animal phylogeny, it is striking how frequently findings of metabolic rate, insulin signaling, and free radicals have emerged from very different approaches to aging in nematodes and mammals, for example.These findings hint that the genetic control of life span was already developed in the common ancestor of modern animals so that subsequent evolution of life spans was mediated by quantitative changes in the control of metabolism through insulin and the production of free radicals." + } + ], + "0d6942b4-e75f-4f44-98ac-b8378ef1d3c7": [ + { + "document_id": "0d6942b4-e75f-4f44-98ac-b8378ef1d3c7", + "text": "FUTURE DIRECTIONS: HIGHER RESOLUTION DATA VIA HIGHER THROUGHPUT ASSAYS\n\nOne 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." + } + ], + "113cb521-b79d-4b44-8250-dc1013ea2cb3": [ + { + "document_id": "113cb521-b79d-4b44-8250-dc1013ea2cb3", + "text": "\n\nChromosome mapping of genes that were differentially expressed in mice of different ages and/or in response to CR revealed a wide distribution of genes with some physical clustering of responsive genes within the genome.The latter findings are consistent with the concept that aging is a complex process and that evolutionary adaptations to aging, if they exist, may or may not involve geographic clustering of functionally related genes." + } + ], + "43d5140a-ad39-438e-8ba6-76dd3c7c42bc": [ + { + "document_id": "43d5140a-ad39-438e-8ba6-76dd3c7c42bc", + "text": "Genetic\nlinkage studies of long-lived human families identified a\nlongevity locus while candidate gene approaches have been\nused to identify and confirm the association between\nspecific variants in the FOXO3A gene and human\nlongevity [3–7]. Genome-wide association studies have\nalso been used to identify the association of APOE with life\n\n123\nAging Clin Exp Res\n\nspan and have yielded insights into potential biological\npathways and processes related to aging. Despite these\nsuccesses, several problems are inherent in human\nlongevity studies including potentially high degrees of\nenvironmental heterogeneity, genetic diversity, and lack of\nbirth matched controls, among others [8]." + } + ], + "4ca8d070-8b58-4bd5-86be-127089b70324": [ + { + "document_id": "4ca8d070-8b58-4bd5-86be-127089b70324", + "text": "\n\nThe aging process most certainly is under highly polygenic controls… 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." + } + ], + "5fefb0e4-e7f9-4df3-a984-ad4f61756cf7": [ + { + "document_id": "5fefb0e4-e7f9-4df3-a984-ad4f61756cf7", + "text": "\n\nIn 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." + } + ], + "606c59c5-5ae4-47e9-b3eb-58afa55669d1": [ + { + "document_id": "606c59c5-5ae4-47e9-b3eb-58afa55669d1", + "text": "1993), and\ngene expression microarrays (Pletcher et al. 2002). Given the ambiguities and limitations of large-effect mutant studies of aging, discussed earlier, those publications do not\nprovide very useful evidence with respect to the question of the number of loci that\naffect 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\nevolutionary biologists. However, studies of the genetics of the experimental evolution of aging are now\namenable to the application of genomic methods." + } + ], + "690a2ae6-962a-438c-91ca-60425a0c8d02": [ + { + "document_id": "690a2ae6-962a-438c-91ca-60425a0c8d02", + "text": "Accepted Article\n\n© 2013 The Authors Aging Cell © 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." + } + ], + "78a43a45-84b0-4d73-9396-95b99cfd3983": [ + { + "document_id": "78a43a45-84b0-4d73-9396-95b99cfd3983", + "text": "\n\nAgeing is complex and takes a long time to study -a lifetime in fact.This makes it difficult to discern its causes, among the countless possibilities based on an individual's genes, behaviour or environment.While thousands of regions in an individual's genetic makeup are known to influence their risk of different diseases, those that affect how long they will live have proved harder to disentangle.Timmers et al. sought to pinpoint such regions, and then use this information to predict, based on their DNA, whether someone had a better or worse chance of living longer than average." + } + ], + "932ef21b-9235-4210-a99c-6153a901bb89": [ + { + "document_id": "932ef21b-9235-4210-a99c-6153a901bb89", + "text": "\n\nSeveral 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." + }, + { + "document_id": "932ef21b-9235-4210-a99c-6153a901bb89", + "text": "\n\nSecond, 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." + }, + { + "document_id": "932ef21b-9235-4210-a99c-6153a901bb89", + "text": "\n\nThe 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)." + } + ], + "97290894-086d-438a-bbd2-907dd4cea2ab": [ + { + "document_id": "97290894-086d-438a-bbd2-907dd4cea2ab", + "text": "\n\nIn addition to timing differences, a small proportion of genes (10%-15%) exhibit opposite trends of expression changes with age in humans and macaques (Supplemental Fig. S13).Interestingly, such differences are ;1.5 times more common in aging than in development, an observation consistent with the lower strength of purifying selection on the gene regulation at old age (discussed below).These differences could also reflect extreme shifts in developmental timing between species, as well as technical artifacts.Future studies, using additional species and alternative methodology, are needed to address this issue." + } + ], + "a440a3fa-74e7-4fd8-8a7f-d0391300d6ed": [ + { + "document_id": "a440a3fa-74e7-4fd8-8a7f-d0391300d6ed", + "text": "1993), and\ngene expression microarrays (Pletcher et al. 2002). Given the ambiguities and limitations of large-effect mutant studies of aging, discussed earlier, those publications do not\nprovide very useful evidence with respect to the question of the number of loci that\naffect 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\nevolutionary biologists. However, studies of the genetics of the experimental evolution of aging are now\namenable to the application of genomic methods." + } + ], + "a95e6806-06d3-4775-8287-fda4cf6ac42f": [ + { + "document_id": "a95e6806-06d3-4775-8287-fda4cf6ac42f", + "text": "\n\nThe 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 ˜es 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." + } + ], + "b0e49b4c-954d-476a-ba3a-0215e63c98b6": [ + { + "document_id": "b0e49b4c-954d-476a-ba3a-0215e63c98b6", + "text": "TRANSLATION OF LONGEVITY MODEL ORGANISMS AND CORE AGING PATHWAYS\n\nGenetic 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." + }, + { + "document_id": "b0e49b4c-954d-476a-ba3a-0215e63c98b6", + "text": "ANALYSIS OF HUMAN VARIATION IN THE GENETIC CONTROL OF LONGEVITY\n\nHeritability 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 ε2), 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." + } + ], + "efd5747f-9e8b-45e8-9e04-bb31131d44fa": [ + { + "document_id": "efd5747f-9e8b-45e8-9e04-bb31131d44fa", + "text": "\n\nWith 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." + } + ], + "f6bde053-64e5-42d9-966d-9d5d5d82a068": [ + { + "document_id": "f6bde053-64e5-42d9-966d-9d5d5d82a068", + "text": "\n\nMost 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]." + }, + { + "document_id": "f6bde053-64e5-42d9-966d-9d5d5d82a068", + "text": "Conclusions and prospects\n\nOver 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." + } + ] + }, + "data_source": [], + "document_id": "E1F24400EE215327FE987A4DDC0768C8", + "engine": "gpt-4", + "first_load": false, + "focus": "api", + "keywords": [ + "APOE", + "FOXO3A", + "GWAS", + "longevity", + "aging", + "human", + "gene", + "lifespan", + "genetic", + "environment" + ], + "metadata": [], + "question": "Why is it so diffuclut to map gene loci that control aging in humans?", + "subquestions": null, + "task_id": "E1F24400EE215327FE987A4DDC0768C8", + "usage": { + "chatgpt": 7866, + "gpt-4": 4669, + "gpt-4-turbo-preview": 3717 + }, + "user_id": 2 + }, + "document_id": "E1F24400EE215327FE987A4DDC0768C8", + "task_id": "E1F24400EE215327FE987A4DDC0768C8" +} |