{
"question": [
"How does the information on GeneNetwork.org help in developing new treatments for diseases?",
"What is a gene network, and why is it important for understanding genetics?",
"How do researchers identify which genes are important for certain traits using GeneNetwork.org?",
"How can GeneNetwork.org help in understanding complex traits like height or intelligence?",
"Are there any known genetic mutations that cause premature aging?"
],
"answer": [
"Please try to rephrase your question to receive feedback",
"Please try to rephrase your question to receive feedback",
"Researchers can identify important genes for certain traits using GeneNetwork.org by utilizing its various features. They can use the global search bar to search for genes, mRNAs, or proteins across all datasets. They can also use the Calculate Correlations tab to assess genetic correlations of the trait of interest with all other records in the database. The platform also allows for the construction of association networks using phenotype or transcript abundance. Additionally, GeneNetwork.org provides background information about genes of interest, including the trait identifier, gene symbol, chromosomal location, and megabase position of the gene. It also allows for data mining in genomic regions containing candidates for quantitative trait genes.",
"GeneNetwork.org can help in understanding complex traits like height or intelligence by using both routine and advanced statistical methods to explore and test relations between these phenotypes and underlying genetic variation. It enables complex queries in real time, including very fast QTL mapping. The platform allows for the correlation and comparison across traits, and the identification of common genetic determinants of correlated phenotypes. It also facilitates the construction of molecular networks that drive these traits, providing a comprehensive view of the trait and aiding in the identification of key genes underlying these processes.",
"Yes, there are several known genetic mutations that cause premature aging. These include mutations in genes involved in DNA metabolism or regulation, such as those seen in Werner syndrome (WS), Bloom syndrome (BLM), Cockayne syndrome (CS), ataxia-telangiectasia (AT), Hutchinson-Gilford progeria syndrome (HGPS), and restrictive dermopathy (RD). Other examples include mutations in the LMNA gene causing Hutchinson-Gilford progeria syndrome, and mutations in RecQ genes causing Werner syndrome, Bloom syndrome, and Rothmund-Thomson syndrome."
],
"contexts": [
[],
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"The GeneNetwork is an open resource and consists of a set of linked resources for systemsgenetics. It has been designed for integration of networks of genes, transcripts, and traits suchas toxicity, cancer susceptibility, and behavior for several species. Phenotypic QTLs using theroo lines were identified in numerous other QTL mapping studies [46,47,60,69,75,89,114,115]. For sets of phenotypes, particularly those in Gene Network's databases (Drosophilaphenotypes are not yet in this database), a variety of correlation analyses can be performedwith the gene expression data.",
"Author ManuscriptGeneNetwork main search page and organization. Most analyses in GeneNetwork willfollow the steps shown in panels A through D. In this workfl ow, a data set is selected (A)and mined for traits of interest based on user search queries (B). Traits are then selectedfrom the search (C) and placed in a collection for further inspection and quantitative analysis(D). The banner menu contains additional search options and helpful resources under theSearch and Help tab, respectively (E)Author ManuscriptMethods Mol Biol. Author manuscript; available in PMC 2020 September 17. Mulligan et al.",
"GeneNetwork.org is a tool for quantitative genetics that started in 2001 as WebQTL [38].It evolved from analyses of forward genetics in the BXD mouse family, to phenome-wide association studies and reverse genetics in a variety of species.Although GeneNetwork.orgcontains data for many species and populations, it most prominently contains data for the BXD family.Over 10,000 \"classical\" phenotypes, measured under a variety of environmental conditions and over 100 'omics datasets, are available on GeneNetwork.orgfor the BXD family.GeneNetwork.organd the BXD RI population are therefore a powerful tool for systems genetics and experimental precision medicine.The great advantage of inbred lines, with stable genometypes that can be resampled is that data can be reused and reanalysed over time, as tools improve.From the very start of the genome sequencing revolution, when loci were first mapped to causative genes, new tools and a greater understanding of the genome have allowed us to go back to old data and gain new insight.",
"Exploring genes, molecules, and phenotypes is easily accomplished using GeneNetwork. In thismanuscript we will outline some simple use cases, and show how a small number of plausiblecandidate genes can be identified for an immune phenotype. 1. DataOnce you have navigated to genenetwork.org, there are two ways to search for data in GN. Thefirst is to use the global search bar located at the top of the page (Figure 1). This is a newfeature in GN that allows researchers to search for genes, mRNAs, or proteins across all of thedatasets.Alternatively, with the handful of candidatesidentified, it is practical to move to wet lab assays, for example seeing if over- or underexpression of our candidate genes in vitro leads to changes in CCL5 levels. ConclusionGeneNetwork is an excellent tool for exploring complex phenotypes with systems genetics. Here we have used GeneNetwork to explore an inflammatory phenotype, and identified a smallnumber of plausible candidate genes. A similar workflow can be used for any trait onGeneNetwork, or for any phenotype collected by an investigator in a genetically diversepopulation.Similarly, by using the dropdown menu on the left (Figure 1), a user can switch to phenotypes,and search for any phenotype of interest in the same way. Figure 1: The global search bar, also called the Search All function, is a good area to start exploringgenes, mRNA, and proteins within GeneNetwork. To best use this new tool, use standard gene symbolscontaining more than two characters in the name. Another area to acquire data is the Select and search pull-down menus (Figure 2). To getstarted, the user has to choose a population of interest.",
"Author ManuscriptGeneNetwork main search page and organization. Most analyses in GeneNetwork willfollow the steps shown in panels A through D. In this workfl ow, a data set is selected (A)and mined for traits of interest based on user search queries (B). Traits are then selectedfrom the search (C) and placed in a collection for further inspection and quantitative analysis(D). The banner menu contains additional search options and helpful resources under theSearch and Help tab, respectively (E)Author ManuscriptMethods Mol Biol. Author manuscript; available in PMC 2020 September 17. Mulligan et al.",
"Using the GeneNetwork database, we performedthe analysis in a two-step fashion: (1) we ranked correlationsusing Spearman rank test with n-numbers larger than 15 overlapping strains, and with P-values < 0.01; and (2) we performeda trait overrepresentation test using key word searches, in whichsignificantly correlated traits should be overrepresented in theGeneNetwork database. This approach should prevent finding ofa correlation by pure chance, albeit that there still could be abias toward studies with more in depth phenotyping. In total,we selected 34 traits (Table 1, Figure 1).",
", (Chesler et al. , 2005; Galperin and Cochrane,2009; Gentleman et al. , 2004; Mailman et al. , 2007; Saal et al. , 2002; Swertz et al. , 2010)). One relatively well-known database is GeneNetwork (www.genenetwork.org) (Chesler etal. , 2005). GeneNetwork is designed primarily as a web service for exploratory andstatistical analysis of large published phenotype and genome datasets, and includes datafrom several species (see Supplementary Discussion). GeneNetwork includes extensivephenotype data extracted from the literature and submitted by users, which makes itpractical to compare data on drug responses with gene expression patterns.",
"Exploring genes, molecules, and phenotypes is easily accomplished using GeneNetwork. In thismanuscript we will outline some simple use cases, and show how a small number of plausiblecandidate genes can be identified for an immune phenotype. 1. DataOnce you have navigated to genenetwork.org, there are two ways to search for data in GN. Thefirst is to use the global search bar located at the top of the page (Figure 1). This is a newfeature in GN that allows researchers to search for genes, mRNAs, or proteins across all of thedatasets.Alternatively, with the handful of candidatesidentified, it is practical to move to wet lab assays, for example seeing if over- or underexpression of our candidate genes in vitro leads to changes in CCL5 levels. ConclusionGeneNetwork is an excellent tool for exploring complex phenotypes with systems genetics. Here we have used GeneNetwork to explore an inflammatory phenotype, and identified a smallnumber of plausible candidate genes. A similar workflow can be used for any trait onGeneNetwork, or for any phenotype collected by an investigator in a genetically diversepopulation.",
"GeneNetwork provides users withuseful background information regarding their gene or genes of interest including the traitidentifier, gene symbol, chromosomal location, and megabase position of the gene. Inaddition to this, GeneNetwork can be used to study correlations between traits and toperform data mining in genomic regions containing candidates for quantitative trait genes(Hoffman et al. , 2011). All datasets in GeneNetwork are linked to a materials and methodsinformation page that summarizes experimental details relating to the dataset.",
"As mentioned previously, GeneNetwork(www.genenetwork.org) is a collaborative Web-based resource equipped with tools andfeatures for studying gene/gene and exploring genetic correlates to neurobehavioralphenotypes (Chesler et al. , 2003, 2004). The Web site is home to a growing collection ofgene expression and phenotypic data from a variety of species and brain regions, with a hostof links to external resources for tracing the interrelationships of a gene among multipleWeb-based resources. GeneNetwork also offers a number of correlation and mappingstrategies for assessing associations among multiple genes and QTLs.",
"Here we provide open access and availability tothese data by integrating them into the GeneNetwork, aweb-based analytical tool that has been designed for multiscale integration of networks of genes, transcripts andtraits and optimized for on-line analysis of traits controlled by a combination of allelic variants and environmental factors. GeneNetwork with its central module WebQTLfacilitates the exploitation of permanent genetic referencepopulations that are accompanied by genotypic, phenotypic and mRNA abundance datasets.GeneNetwork has a function that constructs such association networks using either phenotype or transcript abundance, or indeed both simultaneously. It provides avisualization of the relative positions and numbers of possible interacting partners, how they interact (positive ornegative correlation) and in some situations, based onprior knowledge, it may suggest the directionality of theinteraction. An association network using principal component scorescalculated using a selected set of malting quality andyield-related trait data as variables provides an overview ofthe key barley traits that segregate in the St/Mx population(Figure 3, Additional File 3).DiscussionUsing GeneNetwork for barleyThe framework for analysis using GeneNetwork for barleyis shown in Figure 1A. Associations between transcriptabundance, phenotypic traits and genotype can be established either using correlation or genetic linkage mappingfunctions [29,30]. The main page of GeneNetwork athttp://www.genenetwork.org provides access to subsets ofdata through pull-down menus that allow specific datasets to be queried. The datasets can be further restrictedusing a single text box for specific database entries toquery probe set or trait ID, or annotations associated withthe database entries.",
"GeneNetwork.org also offers a powerful statistical platform foronline network analyses and mapping, enabling numerous molecular questions to be probed in one centralized location(Chesler et al. , 2003, 2005; Li et al. , 2010; Mulligan et al. , 2012,2017, 2019). Most data are from groups of animals or humanswho have been fully genotyped or even sequenced. As a result, itcan be used to model causal networks that link DNA differencesto traits such as differences in expression, cell number, volumes,and behavior using real-time computation and graphing.Forexample, given the intense current interest in opiate addiction, it is important toremap decade-old data using new linearmixed-model mapping algorithms available in GeneNetwork.org. There is agreat amount of amassed data on opiateinduced changes in locomotion, and hundreds of other drug-related traits (Philip etal. , 2010) for .60 strains of recombinantinbred mice that have all been fully genotyped. This analysis can identify thegene variants that influence responsesto these drugs-of-abuse. Figure 5. Example workflow in GeneNetwork.org.",
"Using GeneNetwork, click on the Calculate Correlations tab to assessgenetic correlations of the trait of interest with all other records in thedatabase, including BXD published phenotypes, BXD genotypes, andmRNA from various brain regions as well as other tissues. To begin,select BXD Published Phenotypes from the Database pull-down menuand click Compute. The default option returns the top 500 phenotypesassociated with the trait of interest, but the Return pull-down barallows researchers to choose how many results to display. Researcherscan also choose between selecting Pearson or Spearman Rankcorrelations.",
"However, prioritizingthe long lists of genes produced bycomparative microarray studies conducted in either species has provenexceedingly difficult. As the costs associated with validating a given genesrole in driving a complex trait are considerable, an effective strategy for prioritizing candidate genes is crucial. Investigators therefore have used moresystems-level approaches that combinegenetic, genomic, and pharmacologicalmethods to better delineate gene networks causally related to ethanolbehaviors. Networks allow us to inferrelationships between genes and determine which are most important."
],
[
"Using the relationships between genotype,gene expression, and behavior in three databases created in the same recombinant inbredstrain set, advances in genome analysis technology have been applied to the reanalysis oftraits that have been historically importantfoundations in neuroscientific research. Directly building on these early achievementsis possible by using bioinformatics approaches to pull together newly developed resourcesand tools with the wide body of previousresults in the field. As complete genomesequences in both of these strains become available, the exact locations of SNPs, which maybe responsible for these phenotypic differences,will be determined.",
"Forexample, while the structure learned for this example dataset showsthat the Genotype in the dataset directly impacts Gene1 andGene3, the network structure alone is not able to fully describe thisimpact (e.g. , Does having Genotype = 1 tend to increase or decreasethe value of Gene1 and Gene3?). To more fully investigate thequantitative relationships between variables, users can click on aparticular node of the network and enter a value for the variable aseither evidence or an intervention (see Subheading 2.3.3).",
"These lines have been used for three decades to map thegenetic basis of complex phenotypes, and allow detection ofcausative genetic loci even for traits with modest heritability(Belknap 1998). The population also serves as a geneticreference population, allowing correlation and comparisonacross traits, both within and among different laboratoriesto evaluate common genetic determinants of correlatedphenotypes (Crabbe et al . 1996). This approach has beenfacilitated through the development of GeneNetwork(www.genenetwork.org), an Internet resource for the multivariate genetic analysis of complex traits in genetic referencepopulations (Chesler et al .",
"These networks may be exploited to identifyrelationships among complex phenotypes, polymorphic and non-polymorphic therapeutic targets, and sources of genetic variability in drug response or disease. Understanding these networks will also allow us to understand how different individualscan use highly polymorphic networks to achieve very similar phenotypic states inmany cases, and highly variable phenotypic states in others. Such analyses will necessarily require special adaptations of QTL analysis for gene expression, though, inBioinformatics for Geneticists, Second Edition.",
"It is of great interest to unravel the inner workings of how genotypes influence molecular networks to affect a phenotype such as agility, seizures, and even drug addiction, toname a few. Geneticists have already achieved great success in associating a genotype andphenotype for a trait determined by one gene (i.e. monogenic traits), but much presentattention is now focused on traits that are determined by many genes (i.e. complex traits). These traits are continuously distributed random variables and thus referred to as quantitative traits. Linear modeling is used to identify genotypes that predict phenotype values.",
"This strategy required a considerable eort, but also expanded the range of studies and possibleforms of analysis. In many cases, however, per subject phenotype datawere not available. GeneNetwork uses both routine and advanced statistical methods to extract, explore, and test relations among phenotypes and underlying genetic variation. It enables complex queries inreal time, including very fast QTL mapping.",
"As an example, Figure 1figure supplement 1A illustrates a sample networkand Figure 1figure supplement 1B depicts a group of correlated traits in this network. Relyingentirely on trait information, however, makes it difficult to identify the shared mechanisms and todistinguish shared molecular mechanisms from shared environmental influences. Alternatively,a common way to improve predictions is by integrating relationships between genes and traits,using genetrait correlations, associations, or causal mutations (Rzhetsky et al. , 2007; Cotsapaset al. , 2011; Baker et al. , 2012; Hwang et al. , 2012; Gat-Viks et al. , 2013).",
"When applied to the field of neuroscience, this can revealbiologically relevant meaning and render novel insights into the molecular mechanisms thatgovern behavior. Focusing on these interactions and the gene networks that emergecapitalize on the unbiased investigational methods imparted in whole-genome analysis. Moreover, due to the complexity of neurobehavioral traits, it may be more relevant andinformative to correlate the function of a network of genes with a phenotype, rather than anindividual gene. NIH-PA Author Manuscript4.1.",
"Using the relationships between genotype,gene expression, and behavior in three databases created in the same recombinant inbredstrain set, advances in genome analysis technology have been applied to the reanalysis oftraits that have been historically importantfoundations in neuroscientific research. Directly building on these early achievementsis possible by using bioinformatics approaches to pull together newly developed resourcesand tools with the wide body of previousresults in the field. As complete genomesequences in both of these strains become available, the exact locations of SNPs, which maybe responsible for these phenotypic differences,will be determined.",
"The combinationof expression genetics with classical linkage analysis, however,allows the in silico identification of candidate genes controllingpolygenic phenotypes as complex as adult neurogenesis and, at thesame time, reveals insights into regulatory transcriptional networksunderlying such phenotypes (18). Genetic polymorphisms influence systems-level phenotypesthrough a network of genes. The small molecular variation is anaturally occurring perturbation of this network that can reveal thegenes that comprise it. Discovering this network and the consequences of this variation are facilitated by the use of geneticreference populations.",
"These networks may be exploited to identifyrelationships among complex phenotypes, polymorphic and non-polymorphic therapeutic targets, and sources of genetic variability in drug response or disease. Understanding these networks will also allow us to understand how different individualscan use highly polymorphic networks to achieve very similar phenotypic states inmany cases, and highly variable phenotypic states in others. Such analyses will necessarily require special adaptations of QTL analysis for gene expression, though, inBioinformatics for Geneticists, Second Edition.",
"Theinformation that defines how variations in DNA lead to variations in complex traitsof interest flows through molecular networks that actually define the complex traits. Therefore, characterizing the molecular networks that underlie complex traits likedisease can provide a more comprehensive view of disease, and this in turn can leadto the direct identification of key genes underlying disease processes, as well as providing a rich biological context within which to infer the functional roles played bythese key genes.An alternative to the forward genetics approach to dissecting complex traits likedisease is the construction of molecular networks that drive disease, where suchnetworks are constructed from molecular phenotype data scored in populations thatmanifest disease. The information that defines how variations in DNA lead to variations in complex traits of interest flows through molecular networks that actuallydefine the complex traits.Therefore, characterizing the molecular networks thatunderlie complex traits like disease can provide a more comprehensive view of disease, and this in turn can lead to the direct identification of key genes underlyingdisease processes, as well as providing a rich biological context within which toinfer the functional roles played by these key genes.",
"The great thing about having accessto the data in Table 1 in GeneNetwork is that we can let these numbers speak forthemselves. Do the traits map strongly to any chromosomal location? If so, what fraction ofthe variance in the trait can be causally linked to the location(s)? Does performance on thistask, whatever it may be measuring, covary with hippocampal size or body weight? To whatextent does the speed of finding the platform during the learning phase of the studycorrespond to the persistence with which the strains search for the missing platform?",
"Detection of putative genetic networks underlyingcomplex traitsComplementary epistasis may be of especially greatimportanceDetecting and characterizing genetic networks underlying acomplex trait involves determining the number, genetic relationships, and hierarchy of segregating FGUs (or loci) associated withthe trait in a biparental population. Two general approaches arereadily available - the quantitative genetics approach and thepopulation genetics approach. The power to detect a geneticnetwork is largely dependent on its complexity, which isdetermined largely by the number of segregating loci, r, withineach of the signaling pathways underlying the trait.While gene networks controlling biological processes presumably include the genetic determinants of complex trait variation,these two important areas of study have remained largelyindependent. For example, gene networks consisting of multiplehierarchical signaling pathways might explain high-order epistasis,but only digenic epistasis affecting complex traits has been possibleto map [24,25]. Recent modeling efforts have suggested thatepistasis might be better explained by functional relationships inIntroductionGreat progress has been made in genetic dissection of quantitativetrait variation during the past two decades, but a few puzzling resultshave recurred in many QTL mapping studies.",
"Using the relationships between genotype,gene expression, and behavior in three databases created in the same recombinant inbredstrain set, advances in genome analysis technology have been applied to the reanalysis oftraits that have been historically importantfoundations in neuroscientific research. Directly building on these early achievementsis possible by using bioinformatics approaches to pull together newly developed resourcesand tools with the wide body of previousresults in the field. As complete genomesequences in both of these strains become available, the exact locations of SNPs, which maybe responsible for these phenotypic differences,will be determined.",
"These networks may be exploited to identifyrelationships among complex phenotypes, polymorphic and non-polymorphic therapeutic targets, and sources of genetic variability in drug response or disease. Understanding these networks will also allow us to understand how different individualscan use highly polymorphic networks to achieve very similar phenotypic states inmany cases, and highly variable phenotypic states in others. Such analyses will necessarily require special adaptations of QTL analysis for gene expression, though, inBioinformatics for Geneticists, Second Edition.",
"These networks may be exploited to identifyrelationships among complex phenotypes, polymorphic and non-polymorphic therapeutic targets, and sources of genetic variability in drug response or disease. Understanding these networks will also allow us to understand how different individualscan use highly polymorphic networks to achieve very similar phenotypic states inmany cases, and highly variable phenotypic states in others. Such analyses will necessarily require special adaptations of QTL analysis for gene expression, though, inBioinformatics for Geneticists, Second Edition."
],
[
"Studies of genes and molecular processes that are associated with segmental progeroid disorders, such as Hutchinson-Gilford progeria syndrome (HGPS, progeria, OMIM#176670), could be of importance when studying the genetic mechanisms of aging (Martin, 2005;Baker et al., 1981).For example, most cases of HGPS are caused by a de novo point mutation in the LMNA gene (LMNA c.1824C>T; p.G608G).This mutation activates a cryptic splice site that results in aberrant splicing of the lamin A transcript (Eriksson et al., 2003).Interestingly, it has been shown that the products of this aberrant splicing, the truncated transcript and resultant protein (named progerin), increase in number with aging in HGPS (Goldman et al., 2004;Cao et al., 2007;Rodriguez et al., 2009).In addition, several reports have found progerin, and increasing levels of progerin, in normal cells over the course of normal aging (Scaffidi & Misteli, 2006;McClintock et al., 2007;Cao et al., 2007;Rodriguez et al., 2009), which suggests a similar genetic mechanism in HGPS and normal aging.Moreover, genome-scale expression profiling in cells from HGPS patients, as well as in physiological aging, has revealed widespread transcriptional misregulation in multiple mammalian tissues (Ly et al., 2000;Csoka et al., 2004;Zahn et al., 2007;Scaffidi & Misteli, 2008;Cao et al., 2011;McCord et al., 2013).",
"DNA Repair and Accelerated Aging SyndromesThe association of human syndromes of accelerated aging with inherited mutations in DNA repair genes strongly implicates DNA damage in the human aging process.These disorders, known as segmental progeroid syndromes, are characterized by accelerated onset of a subset of human aging phenotypes that frequently include neurodegeneration (50).Mutations in genes involved in singleor double-strand DNA break repair result in cerebellar degenerative syndromes known as ataxias, which are manifested by movement disorders.The continued proliferation of cerebellar granule cells during postnatal development may underlie the vulnerability of the cerebellum to inherited deficits in genome stability.In contrast, inherited mutations in DNA helicases, such as Werner and Rothmund-Thomson syndromes, give rise to features of accelerated aging that often do not include nervous system dysfunction.This may reflect the role of RecQ-like helicases in recombinant events in replicating cells.Inherited mutations in enzymes involved in nucleotide and base excision repair, including xeroderma pigmentosum and Cockayne syndrome, are characterized by accelerated aging phenotypes that include neurodegeneration, mental retardation, and delayed psychomotor development (50).A new human progeroid syndrome that is caused by a loss of function mutation in the XPF-ERCC1 endonuclease that repairs helix-distorting DNA lesions was recently described.Mice deficient in ERCC1 recapitulate the progeroid features and exhibit a gene expression profile in the liver that overlaps with that of normal aging mice (correlation coefficient 0.32), suggesting that this type of DNA damage may contribute to the aging process (51).Segmental progerias typically have a short life span of less than 20 years, which may account for the absence of Alzheimer-type neuropathological Double-strand break (DSB): a severe form of DNA damage involving scission of both DNA strands, usually induced by ionizing radiation or ROS NHEJ: nonhomologous end joining changes.However, individuals with Werner syndrome, a longer-lived progeroid syndrome, can have variable neuropathology, with one 57-year-old case reportedly showing unusually high levels of amyloid -protein deposition in the brain (52).",
"Hutchinson-Gilford progeria syndrome (HGPS) and Werner syndrome are rare human genetic disorders characterized by premature aging phenotypes with a shortened life span.This group of diseases resembles physiological aging to a certain extent, serving as excellent models to gain insight into the biology of aging in humans (24,25).These diseases are due to either a mutation in genes encoding the DNA repair machinery or the A-type lamin, leading to disorganized chromatin structures.The causative mutations behind these progeria syndromes indicate that genomic instability and chromatin deterioration are causes of human aging.Furthermore, the knowledge we gain from understanding the molecular pathology of these human premature aging diseases provides us with useful information to understand the complex aging process.Individuals with HGPS do not recapitulate all aging phenotypes because they usually show segmental progeria affecting multiple tissues.By recapitulating some molecular and cellular changes that are characteristics of the natural aging process, these models provide us with a unique opportunity to understand the aging process in a human model (24,25).",
"Researchers in recent studies have focused on gene mutations accompanying known progeroid syndromes, such as Hutchinson-Gilford progeria, Werner syndrome, Rothmund-Thomson syndrome, Cockayne syndrome, ataxia telangiectasia, and Down syndrome. 143The most common skin disorders of these syndromes, which are characterized by an acceleration of the aging phenotype, are alopecia, skin atrophy and sclerosis, telangiectasia, poikiloderma, thinning and graying of hair, and several malignancies.Most of these syndromes are inherited in an autosomal recessive way and mostly display defects in DNA replication, recombination, repair, and transcription.Expression gene patterns of skin cells derived from old and young donors with Werner syndrome, 144 show that 91% of the analyzed genes have similar expression changes in Werner syndrome and in normal aging, implying transcription alterations common to Werner syndrome and normal aging represent general events in the aging process.",
"DNA Repair-Related Progeroid SyndromesAs mentioned previously, premature aging syndromes are often caused by mutations in genes whose function is to preserve genomic integrity.In this respect, the RecQ family of DNA helicases has been found to function in DNA damage repair, including base excision repair and in DNA double-strand break (DBS) repair, as well as in DNA replication subjected to a normal or stressed state [36].Mutations in three RecQ genes (WRN, BLM, and RECQL4) give rise to the Werner syndrome (WS), Bloom syndrome (BS), and Rothmund-Thomson syndrome (RTS), respectively [37].Additional genetic defects in the DNA damage repair system also cause the following disorders: Cockayne syndrome (CS), xeroderma pigmentosum (XP), and trichothiodystrophy (TTD).An alternative strategy to the investigation of aging using the humans themselves is the study of progeroid syndromes, a group of very rare genetic disorders characterized by accelerated aging and the presence of clinical features that resemble physiological aging, including osteoarthritis and osteoporosis, loss of muscle mass, hair loss, short stature, skin tightness, and cardiovascular diseases [4].In addition to the genuine medical interest in improving the quality of life of these patients, the study of progeroid syndromes has attracted great interest in the past 10 years, in that they constitute an invaluable source of information for understanding the molecular basis of human aging.ConclusionsRecent advances in the study of progeroid syndromes, especially HGPS, have provided novel insights into our understanding of the aging process in humans.The main progeroid syndromes revised in this chapter are caused by mutations in genes encoding for DNA repair enzymes or the nuclear lamina protein lamin A, which reinforces the notion that genome instability is a critical determinant of aging.The study models that recapitulate progeroid syndromes have dramatically stimulated aging research; while cellular models have allowed the dissection of basic cellular and molecular processes linked to aging, mice models have facilitated screening of therapeutic drugs.It is expected that upcoming technologies and the design of novel optimized animal models will help to accomplish a translational medicine approach in aging research, with HGPS being the ideal model for such a goal.",
"Progeroid syndromesPatients suffering from progeroid syndromes, or accelerated aging phenotypes, display an array of physical and biological features that vary widely between tissues and diseases and among individuals.Some of the main characteristics for the specific disorders of interest to this review are cited below (for further review of molecules involved and clinical presentation, see Ref. 96).A general dilemma in studies on the role of telomeres in progeroid syndromes (and aging) is that telomere involvement could be direct as well as indirect.For example, the increased cell death resulting from defective DNA repair could result in telomere shortening via increased compensatory (stem) cell turnover or via direct effects on (repair of) telomeric DNA.For many segmental aging disorders, it has proven to be very difficult to distinguish between direct and indirect effects on telomere length.Perhaps phenotypically the most striking segmental aging genetic disorder in humans, Hutchinson-Gilford Progeria syndrome (HGPS), is caused by point mutations in lamin A, a key component of nuclear scaffolding (34,72).Lamin A deficiency results in absence of hair, craniofacial deformities (\"pinched\" facial features), emaciated and wrinkled appearance, as well as cardiovascular defects that eventually lead to stroke or heart attack at a very young age.The disease is characterized by specific defects in FIG. 8. Defects in human telomerase.The human telomerase complex is minimally composed of two proteins, telomerase reverse transcriptase (hTERT, green) and dyskerin (or DKC1, blue), that both bind specifically to a folded RNA molecule (or hTERC, black) containing a telomere repeat anchoring sequence and a template (red box).Known mutations in each component have now been linked to autosomal dominant dyskeratosis congenita (AD DC), bone marrow failure (BMF), and idiopathic pulmonary fibrosis (IPF) (6,63,127,134,151,217,231,234).The telomerase complex is thought to dimerize, bind to the single-strand G-rich telomere end, and catalyze the addition of new repeats (see also Figs. 3 and 4).The complex translocates along (newly added) telomere tracts for further elongation.Mutations affecting telomerase function lead to failure to assemble a functional complex.In the majority of cases, the level of telomerase activity is reduced by 50%.Such a reduction in telomerase activity compromises telomere length maintenance and increases apoptosis and senescence in proliferating cells (see Fig. 4).nuclear shape (183).Because expression of (defective) lamin A is limited to certain cell types, some cells and tissues are more affected than others.While there is evidence that DNA damage responses in cells expressing mutant lamin A are abnormal (133), the role of telomeres in this disorders (if any) remains to be clarified.A number of other segmental aging disorders have been more directly linked to telomere (dys)function.Among these, Fanconi anemia (FA) and ataxia telangiectasia (AT) are generally autosomal recessive diseases caused by mutations in, respectively, Fanconi genes (encoding any of 12 Fanconi anemia complementation group proteins) and the ataxia telangiectasia mutated gene (encoding the ATM protein).These proteins are implicated in DNA damage and repair pathways; in addition, ATM is known to phosphorylate FANCD2 (for reviews, see Refs.64,118,190).Both diseases are associated with accelerated telomere shortening (29,121,123,146), and abnormalities in telomere replication or repair are thought to play a role in the pathogenesis, particularly in the progression of the disease to immunodeficiency and bone marrow failure, as well as in the increased predisposition to malignancy in young adults.Other syndromes related to the Fanconi DNA damage response pathway include Nijmegen breakage syndrome (NBS) and Seckel syndrome.Other \"progeroid\" genes that have been implicated in DNA replication and repair are the family of genes encoding the RecQ DNA helicases.One of the functions of these enzymes is to assist in the resolution and repair of broken or stalled replication forks.Telomeric DNA is known to readily form higher order DNA structures such as G quadruplex structures in vitro (159), and it seems plausible, based on work in C. elegans (42), that specialized helicases are required to resolve structures of G-rich DNA arising sporadically during lagging strand DNA synthesis (62).Helicases that could be involved include RecQ protein-like 2 (RecQL2), RecQL3, and RecQL4 with known mutations that give rise to Werner (WRN), Bloom (BLM), and Rothmund Thompson syndromes, respectively.Accelerated telomere shortening is observed in Werner's syndrome (51), and pathology in animal model systems is accentuated in the context of telomerase deficiency (40,156).",
"The relationship between DNA damage accumulation and aging has gained maximum credibility through studies conducted on various human progeria syndromes, which are genetic disorders where patients precociously develop features resembling natural aging.Most of the reported progeria syndromes, including Werner syndrome (WS), Bloom's syndrome (BS), Rothmund-Thomson syndrome (RTS), Cockayne syndrome type A and type B (CSA and CSB), Xeroderma pigmentosum (XP), Trichothiodystrophy (TTD) and Hutchinson-Gilford progeria syndrome (HGPS) are caused by mutations of genes that are directly or indirectly involved in DNA repair.Of these, WS, BS and RTS are associated with defects in RecQ helicases, i.e.RECQL2 (WRN), RECQL3 (BLM) and RECQL4 respectively, whereas CS, XP and TTD shared similar defects in NER pathway.RecQ helicases are a group of highly conserved proteins from bacteria to humans.The roles of RecQ helicases in DNA metabolism, including DNA replication, transcription, repair and recombination, have been extensively investigated and are demonstrated to be the underlying pathological basis of WS, BS and RTS [139][140][141][142].Most recently, delayed DNA damage checkpoint response and defective DNA repair were found to contribute to the progeria phenotypes in HGPS as well [143].",
"They arise from mutations in one or several genes involved in DNA metabolism or in its regulation.Accelerated aging also may result from partial genome imbalances as seen in the chromosomal disorders of Down, Klinefelter and Turner syndromes.These defects result in part from accumulated damage to DNA.Such damage may result inability to maintain replicative fidelity of the genome [2][3][4].Thus, organisms with mutations to genes directly involved in basic genome structure, maintenance and replicative fidelity would understandably have an accelerated aging phenotype and/or shortened life spans.Individuals with a progeroid syndrome have a premature aging phenotype and, depending on the specific mutations involved, the effects on lifespan may range from moderate to severe.Examples include Werner syndrome (WS), Bloom syndrome (BLM), Cockayne syndrome (CS), ataxia-telangiectasia (AT), Hutchinson-Gilford progeria syndrome (HGPS), and restrictive dermopathy (RD).",
"The identification of these diseases spurred the creation of numerous animal models, and the characterization of engineered laboratory mutants led to the identification of many new human diseases of systemic and segmental accelerated aging.The animal models are useful for discovering how, when, and where (in what tissues) DNA damage contributes to aging, an area in which much work is still needed.The models, because of their accelerated aging, are useful for rapid hypothesis and drug testing.The models for the large part faithfully recapitulate the human genetic diseases; however, it is notable that mice tend to display a milder phenotype than humans.This might arise from the environmental contribution to human disease, which is not well reproduced in experimental model systems.Collectively, however, these human diseases and their conservation in multiple animal model systems strongly support the role of DNA damage as a proximal contributor to aging.",
"The number of identified genes associated with progeroid syndromes has increased in recent years, possibly shedding light as well on mechanisms underlying ageing in general.Several heritable premature aging syndromes have for a long time been linked to defects in genome maintenance, due to altered DNA repair mechanisms.These mainly include the following autosomal recessive syndromes: (i) Werner syndrome, due to mutations in RecQL2 DNA helicase; (ii) Cockayne syndrome (CS) type A and B, due to mutations in the genes encoding the group 8 or 6 excision-repair cross-complementing proteins (ERCC8 and ERCC6), respectively; (iii) Rothmund-Thomson syndrome (RTS), due to RecQL4 mutations; (iv) trichothiodystrophy (TTD), due to mutations in the genes ERCC2/XPD and ERCC3/XPB, encoding the two helicase subunits of the transcription/repair factor TFIIH, as well as in TFB5, encoding the tenth subunit of TFIIH (Giglia-Mari et al., 2004); (v) ataxia-telangiectasia, due to mutations in the ataxia-telangiectasia mutated gene (ATM); (vi) xeroderma pigmentosum (XP), a genetically heterogeneous autosomal recessive disorder in which can be distinguished at least seven complementation groups, due to mutations of different DNA excisionrepair proteins (Hasty et al., 2003;Kipling et al., 2004).All these progeroid diseases, involving heritable defects in DNA repair, suggest a central role of genome integrity maintenance in the aging process.ConclusionFrom a pathophysiological point of view, the known Progeroid syndromes are caused either by mutations in genes encoding DNA repair proteins, such as in WS, Bloom syndrome (BS), Rothmund-Thomson syndrome, Cockayne syndrome, xeroderma pigmentosum or trichothiodystrophy (Hasty et al., 2003;Wood et al., 2005), or by mutations in genes encoding Lamins A/C or partners involved in their biological pathway, such as HGPS or RD (De Sandre-Giovannoli et al., 2003;Eriksson et al., 2003;Navarro et al., 2004Navarro et al., , 2005)).Progeroid syndromes are heritable human disorders displaying features that recall premature ageing.In these syndromes, premature aging is defined as ''segmental'' since only some of its features are accelerated.A number of cellular biological pathways have been linked to aging, including regulation of the insulin/growth hormone axis, pathways involving ROS metabolism, caloric restriction, and DNA repair.Different animal models, ranging from yeast, to nematodes, to mice, have been instrumental in obtaining evidence for these connections (Hasty et al., 2003).Several heritable premature aging syndromes have for a long time been linked to defects in genome maintenance, due to altered DNA repair mechanisms.These mainly include the following autosomal recessive syndromes: (i) Werner syndrome, due to mutations in RecQL2 DNA helicase; (ii) Cockayne syndrome (CS) type A and B, due to mutations in the genes encoding the group 8 or 6 excision-repair cross-complementing proteins (ERCC8 and ERCC6), respectively; (iii) Rothmund-Thomson syndrome (RTS), due to RecQL4 mutations; (iv) trichothiodystrophy (TTD), due to mutations in the genes ERCC2/XPD and ERCC3/XPB, encoding the two helicase subunits of the transcription/repair factor TFIIH, as well as in TFB5, encoding the tenth subunit of TFIIH (Giglia-Mari et al., 2004); (v) ataxia-telangiectasia, due to mutations in the ataxia-telangiectasia mutated gene (ATM); (vi) xeroderma pigmentosum (XP), a genetically heterogeneous autosomal recessive disorder in which can be distinguished at least seven complementation groups, due to mutations of different DNA excisionrepair proteins (Hasty et al., 2003;Kipling et al., 2004).All these progeroid diseases, involving heritable defects in DNA repair, suggest a central role of genome integrity maintenance in the aging process.The number of identified genes associated with progeroid syndromes has increased in recent years, possibly shedding light as well on mechanisms underlying ageing in general.Among these, premature aging syndromes related to alterations of the LMNA gene have recently been identified.LMNA encodes Lamins A/C, ubiquitous nuclear proteins belonging to the intermediate filament superfamily.These premature aging disorders have thus been classified as ''Laminopathies'', the large group of diseases associated to Lamin A/C defects.This group of heterogeneous disorders includes three main subgroups: (1) neuromuscular disorders (Emery-Dreifuss muscular dystrophy, limb-girdle",
"However, only those genetic disorders that exhibit premature aging, neurodegeneration (mental defects), and some form of chromosomal/DNA damage all together will be empha-sized here.Perhaps the most appropriate disorder under this category is Down's syndrome.It has several features of premature aging and the genetic defect is trisomy of the distal part of the long arm of chromosome 21.The critical segment of chromosome 21 is shown to have three genes coding for copper-and zinc-dependent superoxide dismutase, oncogene ets-2, and cystathione ~-synthase (Delabar et al., 1987).Since elevated levels of superoxide dismutase are found in various tissues of these individuals, it is postulated that the accelerated aging of these patients may be caused by overproduction of superoxide dismutase, which is responsible for the production of H20 2 while scavenging the oxygen-free radicals.The brains of Down's syndrome individuals are particularly vulnerable to oxidative DNA damage because the high levels of superoxide dismutase found in this tissue are not accompanied by an elevation in the glutathione peroxidase and catalase (Balazs and Brookshank, 1985) that would have normally helped in removing the overproduced H202.Other genetic syndromes characterized by signs of nervous debility, premature aging, and DNA damage/ decreased DNA-repair capacity, are Ataxia Telangiectasia (AT) and Cockayne syndrome (CS).",
"Rare genetic disorders of agingProgeria, also known as Hutchinson-Gilford progeria syndrome, affects one in four million births worldwide with equal distribution between sex and race, causing a child's body to age more rapidly (Genetics Home Reference, 2019a).Symptoms typically occur within the first year of life, and most children do not live past 13 years.Mutation in the LMNA gene (not an adduct or telomere factor) contributes to abnormal lamin A protein, called progerin, causing cell instability and cells to easily breakdown (Genetics Home Reference, 2019a).There is no current cure for progeria but farnesyltransferase inhibitors, a cancer drug, has shown promise in reversing cell damage (Genetics Home Reference, 2019a).Other supportive treatments include cardiovascular diseaserelated issues, growth hormones, and bone/joint health.Adalia Rose has taken to social media, with multiple YouTube and Facebook postings, to help others understand her case of progeria.",
"Mitochondrial DNA (mtDNA) mutations are thought to have a causal role in many age-related pathologies.Here we identify mtDNA deletions as a driving force behind the premature aging phenotype of mitochondrial mutator mice, and provide evidence for a homology-directed DNA repair mechanism in mitochondria that is directly linked to the formation of mtDNA deletions.In addition, our results demonstrate that the rate at which mtDNA mutations reach phenotypic expression differs markedly among tissues, which may be an important factor in determining the tolerance of a tissue to random mitochondrial mutagenesis.",
"INTRODUCTIONIn genetics, identification of genotype-phenotype relationships relies on generated or selected mutants, which highlight underlying mechanisms.For the biology of aging, mutants that display delayed or accelerated aging have been invaluable.Rare heritable syndromes have been identified in the human population that exhibit multiple features of premature aging.A search in the Online Mendelian Inheritance in Man database (OMIM version February 25, 2015) using the keywords \"premature aging,\" \"progeria,\" or \"progeroid\" yielded 20 syndromes with at least one known mutated gene.Certainly this list is far from complete; for example, ataxia telangiectasia, fanconi anemia, and maternally transmitted mitochondrial syndromes such as maternally inherited diabetes and deafness and mitochondrial encephalomyopathy (MIDD/MELAS) are missing.Additionally, many more conditions await identification as unrecognized progeroid syndrome.The application of powerful exome and whole genome sequencing technologies will dramatically accelerate molecular resolution of genetic defects in rare patients with features of accelerated aging, and through this process, many new genes underlying these conditions will be identified.However, when we assign a primary function to each of the causally mutated genes in the known syndromes, it appears that the majority is linked to perturbed genome integrity, a second class represents metabolism, and one syndrome appears connected with cell adhesion (Figure 1).Recently, evidence has emerged for bidirectional interactions between the main aging-related processes: For instance, most DNA damage is derived from endogenous metabolic sources, and compromised genome function indirectly affects many cellular processes including metabolism (1, 2).This suggests the existence of a tightly interwoven network that underlies aging, which is the focus of this review.Progeria-associated syndromes classified by primary function of the causal genetic defect.These 20 human syndromes, listed outside of the circle, were selected from the OMIM database using the keywords \"premature aging,\" \"progeria,\" and \"progeroid. \"Related primary functions were combined in the categories genome integrity, metabolism, and adhesion (inner circle).Abbreviations: DSB, DNA double-strand break; MDPL, mandibular hypoplasia, deafness, progeroid features, and lipodystrophy; PI3K, phosphoinositide-3-kinase; PS, phosphatidylserine; XFE, XpF-Ercc1.GAPO indicates growth retardation, alopecia, pseudoanodontia, and optic atrophy.SHORT indicates short stature, hyperextensibility, hernia, ocular depression, Rieger anomaly, and teething delay."
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