Drosophila using a collection of transgenic lines providing conditional expression of micro-RNAs (miRNAs). Here, we describe a methodological algorithm to identify and rank genes that are candidate to be targeted by miRNAs that shorten lifespan when expressed in adult glia. We have used four different databases for miRNA target prediction inDrosophila but find little agreement between them, overall. However, top candidate gene analysis shows potential to identify essential genes involved in adult glial functions. One example from our top candidates’ analysis isgartenzwerg (garz). We establish thatgarz is necessary in many glial cell types, that it affects motor behaviour and, at the sub-cellular level, is responsible for defects in cellular membranes, autophagy and mitochondria quality control. We also verify the remarkable conservation of functions betweengarz and its mammalian orthologue, GBF1, validating the use ofDrosophila as an alternative 3Rs-beneficial model to knock-out mice for studying the biology of GBF1, potentially involved in human neurodegenerative diseases.Invertebrate glia performs most of the key functions controlled by mammalian glia in the nervous system and provides an ideal model for genetic studies of glial functions. To study the influence of adult glial cells in ageing we have performed a genetic screen in Research highlightsThis screen has provided a thorough analysis of glial functions in ageingPotential to shortcut gene discovery through miRNAs effect. The screening of only ~200 mutant lines potentially targets >6000 genes.Potential to identify complex regulatory networks that include miRNAs and target genes.Validated the identification of essential genes for the adult nervous system and their functions specifically in motor control.An open-access searchable database for future discoveries upon improved precision of miRNA-target predictions.This screening method provides an alternative approach for studying genes important in glial biology, without the need for animal experiments.Drosophila can be used to study the biology of GBF1, instead ofin vivo vertebrate animal models, such as zebrafish or mouse.Example validation thatThe searchable database can be easily updated upon emergence of updated miRNA target predictions.RNAi lines are publicly available from the Vienna Drosophila Resource Centre stock collection.Genetic studies in Drosophila are quicker and more sophisticated compared to vertebrate studies. They also maintain high conservation of functions.garz in glial cells for membrane trafficking, autophagy and mitochondria quality control.Uncovered the function ofStudy of genes, such as GBF1, involved in ageing and neurodegenerationIdentification of novel miRNA targets in gliaStudy of novel miRNA targets in gliaStudy of glial functions in controlling lifespan and healthspan1, work developed in the past decades has shed a light on a much more intricate role for these cells in developing and maintaining nervous system homeostasis  is a focal point of the investigation, given that these complex environments are more difficult to modelDrosophila’s lifespan upon ectopic expression in glial cells in adult flies and have validated this screen through the analysis ofrepo, an already-established key glia gene11. The experimental advantage of performing a miRNA-based screen followed byin silico identification and ranking of predicted miRNAs target transcripts12 has, however, its bottleneck in the validation of the action of the genes of interest. In principle, the specific knockdown of predicted target genes should mimic, to some extent, the phenotype obtained upon corresponding miRNA overexpression.We have tackled the functions of glial cells in ageing. We have previously screened a large collection of miRNAs regarding their effects onrepo as an important player for maintaining glial function and, consequently, homeostasis in the adult brain11. We have shown that while themiR-1-repo axis is physiologically relevant only in the embryo during the glia versus haemocyte cell fate choice13, the miRNA-target relationship can be exploited as a discovery tool to identify the functions of a target gene in a different context, namely adult glial functions11.In fact, using databases of predicted miRNA-target genes previously allowed us to identifyrepo was based on its already-established role in glia cell function, here we attempt a global and unbiased systematicin silico approach. In order to systematically identify potential target genes that could account for the lifespan phenotype, focusing on the miRNAs that shortened lifespan, we set out to devise a quantitative algorithm. The aim of this algorithm is to identify and rank the predicted target genes so that those ranking on top would be the most relevant for adult glia in lifespan and ageing.While the focus onThis is followed by experimental validation of the function of these targets in adult glia in the same paradigm used in the miRNAs screen.Drosophila, with the tools identified here, rather than in genetically modified mouse models or in zebrafish, providing an incentive towards animal replacement and reduction and advancing the 3Rs. Mouse and zebrafish neuroscientists and geneticists could take advantage of this information to test preliminary approaches and exploratory experiments inDrosophila, prior to validation in their system reducing the number of animals used. Alternatively, they may entirely replace vertebrate animals withDrosophila to study highly conserved genes and glial functions.We conclude that this approach is valid but has issues of efficiency given the large number of predicted targets that do not recapitulate the expected phenotype. We also establish that there is no significant synergy generated by focusing on the common predictions between all available miRNAs target databases. Nevertheless, the main outcome of our work is a list of candidate genes whose function is essential in glial cells during ageing. These genes can be studied in the future inin silico approach is exemplified by our analysis of one of the top predicted targets:gartenzwerg (garz), the fly orthologue of GBF1 (golgi brefeldin A resistant guanine nucleotide exchange factor 1), a small GTPase guanine exchange factor. Here, we show thatgarz is an essential factor in glia homeostasis maintenance.The success of this14. The conversion from GDP-bound (inactive) to GTP-bound (active) forms of these enzymes relies on the activity of GTPase activating proteins (GAPs) and guanine nucleotide exchange factors (GEFs). While GAPs are responsible for their inactivation through GTP hydrolysis, GEFs are responsible for their activation promoting the exchange of GDP by GTP15.Small GTPases regulate a wide range of cellular events such as proliferation, morphology, nuclear transport and vesicle formation18. GBF1 is part of this family19 and is highly conserved in all eukaryotes, conferring significant translatability of the findings obtained using different model organisms.GEFs belonging to the Sec7 domain protein family are responsible for the activation of Arf (ADP-ribosylation factor) GTPases which are associated with the recruitment of coat proteins (COP) to vesicle budding sites24. Mutated versions or knock-down ofgarz expression brings about epithelial morphogenesis defects during development conditioning embryonic trachea and larval salivary gland formation21. Additionally, in accordance with a role in membrane delivery and vesicular trafficking, silencing ofgarz in these glands impairs membrane delivery of adhesion molecules25. Independently from its role in secretion, GBF1/garz has also been implicated in pinocytosis26; intestinal stem cell survival27; cell cycle29; unfolded protein response events29; mitochondria morphology and function30; and autophagy32.Strongly localized in the cis-Golgi compartment, GBF1 has been shown to regulate vesicle trafficking between the endoplasmic reticulum (ER) and the Golgi apparatusgarz knock-down resulted not only in lifespan reduction but also in motor deficits of adult flies and in subcellular phenotypes indicative of dysfunctions in trafficking, autophagy and mitochondria. Additionally, miRNAs overexpression andgarz knockdown phenotypes were reverted by expression of its mammalian orthologue GBF1, stressing the conservation of functions and the appropriateness of usingDrosophila in place of vertebrate models to study the biology of GBF1.Here we show thathttps://www.ebi.ac.uk/enright-srv/microcosm/htdocs/targets/v5/)MicroCosm (http://www.microrna.org/microrna/home.do)microRNA.org (http://www.targetscan.org/fly_72/)TargetScan (https://pictar.mdc-berlin.de/)PicTar . For MicroCosm and PicTar this was used without additional steps. In the case of miRNA.org this score is a negative value and we have squared it to obtain a positive number. In the case of TargetScan a numerical score was calculated on the basis of the information provided by the database as follows: conserved 8mer = 10 points, conserved 7mer-m8 = 6 points, conserved 7mer-1A = 4 points, poorly conserved 8mer = 8 points, poorly conserved 7mer-m8 = 4 points and poorly conserved 7mer-1A = 2 points. A detailed explanation of the 8mer and 7mer species can be found on the TargetScan website and in the original publicationThe algorithm for ranking targets within each database consists of two steps.2) or (Score2)*Av(χ2):Step 1 - column (Score)*Av(χ2) obtained in the miRNAs screen  was multiplied by the Average Chi square (χeen from. Informa2)] or Σ(Score2)*Av(χ2)]:Step 2 - column Σ(Score)*Av] or Normalised Σ[(Score2)*Av(χ2)]Step1 - column Normalised Σ[(Score)*Av(χ2)] was normalised to 100 and then weighted for the fraction of miRNAs present in the database, out of the total tested in our miRNAs screen. For TargetScan the groups of miRNAs families were counted as one unit in each case.For each database the Σ(Score)*Av(χ(2))*Av(χ2)]} For each target gene, all values from all databases were summed into a final ranking number.Step 2 – column Σ{Normalised Σ. In the case of TargetScan, some miRNAs are grouped in families and we have considered them as a single unit value. This underweights these miRNAs in comparison to others and the genes targeted by them *Av(χ2)] that is the sum of three (Score)*Av(χ2) in the other databases, but for TargetScan it would only reflect one (Score)*Av(χ2). Our reasoning was that grouped miRNAs in TargetScan was not taking into account valuable information and this should be reflected in a penalisation in the ranking.Because a given gene can be targeted by more than one miRNA, to rank its overall importance in adult glia, we have summed all the values obtained for a given gene that were calculated for different miRNAs, obtaining the parameter Σ[(Score)*Av(χ2)] for EBI MicroCosm (Extended data Table 1)38, PicTar (Extended data Table 2)38, microRNA.org (Extended data Table 3)38 and TargetScan (Extended data Table 4)38. Surprisingly, this revealed that there was very little agreement among the four databases. The top-ranking genes obtained using the same algorithm were very different and only 5.6% (i.e. 520 genes) of target predictions were common to all four databases (In conclusion we have ranked target genes according to Σ[(Score)*Av(χtabases .2)] parameter by normalising the maximum value to 100. Additionally, we have weighted this number for the fraction of miRNAs present in each database, out of the total tested in our miRNAs screen. Out of 44 miRNAs screened, 31 were present in EBI Microscosm, 28 in PicTar, 43 in microRNA.org and 40 in TargetScan. The rationale for this weighting was to prioritise the databases carrying more information that was relevant to our screen. Then, for each target gene, we have combined all these scores from the four databases generating the final parameter Σ{Normalised Σ[(Score(2))*Av(χ2)]} for all targets, including the 520 that were commonly predicted by all databases *Av(χtabases .Drosophila Resource Center (VDRC) that were already present in our stock collection. These corresponded to a random selection of approximately 10% (51 out of 520) of commonly predicted target genes. Adopting a similar strategy used for the miRNA screen, we have used therepo-Gal4, tub-Gal80ts inducible system to trigger the RNAi expression in all glial cells in adult flies. As negative control, we used the offspring of crossingrepo-Gal4, tub-Gal80ts to1118w throughout the screen. The expectation was that RNAi against these target genes in adult glia, would phenocopy the effect of the miRNAs that are predicted to target them, therefore shortening lifespan.To test these predictions, we decided to screen for the lifespan effect, a number of RNAi lines from ViennaDrosophila community to gain confidence about the effects of RNAi knock-down is to obtain a similar effect when testing two RNAi lines against the same gene (2-RNAi lines criterion). Remarkably, only in six cases at least two different RNAi lines tested for the same gene delivered the shorter lifespan phenotype that was predicted (The gold standard commonly used by theedicted . In anotIn other cases (11/51) there was an overall confirmation of the prediction, but the two RNAi lines tested for one given target did not share the same effect or we were able to test only one line. The largest group (19/51) was made by cases in which there was no effect and surprisingly in a remarkable number of cases (14/51) there was an overall effect opposite to that predicted, albeit either the two RNAi lines tested for one given target did not share the same effect or we were able to test only one line.2)IR) with the strength of the prediction in all combined databases *Av(χ2)]}).In addition to the 2-RNAi lines criterion we have devised a quantitative index for ranking these targets by combining their effect in the RNAi screen ]}*{Av(χ2)IR}) highlightedgarz, one of the six targets satisfying the 2-RNAi lines criterion, as the top target *Av is paradoxically higher in the commonly predicted group .2)] *{Av(χ2)IR} parameter by combining the quantification of the lifespan effect of the RNAi lines (average Chi square in the RNAi screen) with the normalised predicted score from each database. Then, to rank databases we have summed all these results  to determine the predicting power score. TargetScan had the highest predicting power for the list of common targets, while MicroCosm had the highest capacity for target identification among the differential targets. PicTar had the lowest predicting power in all cases. However, MicroCosm also predicted the largest number of genes as targets of our miRNA screen, with over 44% of them not shared by the other databases. We reasoned that this lack of efficiency in EBI Microcosm had to be considered and when normalising for the total number of predicted targets from each database, as a measure of the predicting power efficiency, TargetScan showed a greater efficiency in both cases, followed by miRNA.org.Considering the lack of tangible benefits of focusing on the commonalities between the different databases, we have then exploited our validation analysis to quantify the prediction capability of each of the four databases to identify the most valid for our screen. For all targets tested, both from the common group  and fromgarz, the fly orthologue forGBF139).As mentioned, we ranked the target genes from the RNAi confirmed predictions and decided to further investigate the top ranked target,garz withrepo-Gal4 specifically during adulthood strongly reduced lifespan. This was true for both RNAi lines tested when compared to1118w median lifespan control , cortex , subperineural  and peripheral  glia. In all sup-populations tested, the downregulation ofgarz caused a reduction in lifespan, albeit not as strong as the pan-glial knockdown  knockdown ofgarz. This also led to a significant shortening of lifespan although the effect was milder than the one obtained with pan-glialgarz knockdown . When using this paradigm, we unravelled an impact of glialgarz knockdown on the amplitude of the response to a train of stimuli and GBF1 co-overexpression rescued this response .It has been reported thatrepo-Gal4) CD8-GFP expression in a control brain. Note the smooth appearance of the glial membranes highlighted by the green signal. The full dataset can be accessed at DOI 10.17605/OSF.IO/96TS3.3D reconstruction of confocal stacks imaging of panglial  CD8-GFP expression in a garz knock-down brain. Note the clustering and blebs formed by the glial membranes highlighted by the green signal. The full dataset can be accessed at DOI 10.17605/OSF.IO/96TS3.3D reconstruction of confocal stacks imaging of panglial p  autophagy receptor43 revealed Ref(2)p accumulation in puncta, suggesting a potential block in autophagic clearance in glial cells  and by at least one (22/65) is much larger than what usually expected in siRNA screens and suggests a 3/5-fold enrichment in positive hits. Thus, our method makesDrosophila screens a more appealing platform with reduced workload in comparison to traditional single gene targeted screens, whether by RNAi or genomic mutagenesis. This may have 3Rs benefits, facilitating the use ofDrosophila as a model for preliminary studies on the genetic factors that influence a given biomedical process.Therefore, the benefits of using miRNAs-based screens andDrosophila can therefore be used to study in detail the functions of these genes in the adult glial cells, in place of genetically modified mouse models.Our screen has also highlighted a number of genes that are strong, and in most cases unexpected, candidates for essential functions in adult glia in ageing. This list of genes provides a useful tool for scientists studying glial functions in ageing. In particular, all identified genes that have been validated by two RNAi lines have clear mammalian orthologues.garz, the fly orthologue of the human GBF1.To validate our findings, we focused on the top target of the genes commonly predicted by all databases and also by TargetScan, i.e.garz confirmed that this gene is absolutely required in adult glia, and also in neurons, for fly survival. Using our automated behavioural set up we could also establish thatgarz is essential in glia for locomotor activity in response to a stimulus or endogenously generated. Analysing the effects of silencinggarz in different glial sub-populations showed that the strong reduction in lifespan could not be accounted for by one specific type of glia but rather due to a combined effect of silencinggarz in all glial cells simultaneously, indicating thatgarz is essential for any glial cell type.The analysis ofOur subcellular analysis suggests that the locomotor and lifespan defects correlate and possibly originate from a number of cellular defects in protein trafficking, autophagy and mitochondria quality control.Drosophila, mutated versions or knockdown ofgarz resulted in developmental epithelial morphogenesis defects21 and impaired membrane delivery of adhesion molecules25. We have been able to identify membrane defects in glial membrane distribution, although not all membrane proteins seemed to be affected bygarz knockdown.garz andGBF1 have been identified as a positive autophagy regulator inDrosophila primary cultured muscle cells32 and mammalian cells31. An accumulation of Ref(2)P upongarz-RNAi expression in adult glia suggests an autophagic clearance deficits, in agreement with these studies.InGBF1-RNAi has been shown to affect mitochondrial morphology and function30. Chemical inhibition of GBF1 in mammalian cells also showed condensed mitochondria and mislocalisation in the cell45. Although mislocalisation of mitochondria is difficult to assess due to glial cell morphology in theDrosophila brain,garz-RNAi strongly affected mitochondria morphology suggesting a more condensed state which may be a reflection of an unbalanced fission/fusion regulation and mitochondria quality control46.garz and human GBF1. While the lack of toxicity of GBF1 overexpression, in comparison to Garz, may indicate some divergence and lack of dominant negative activity, this may also be due to different levels of expression or tags. Nevertheless, GBF1 was able to fully rescue, partially in a Sec7-domain dependent manner, the shorter lifespan and motor behaviour phenotypes caused by the silencing ofgarz. GBF1 was also able to rescue the lifespan shortening by three different miRNAs, miR-1, miR-79 and miR-315, validating that in our screen their effect is at least partially, and in some cases almost entirely, due to downregulation ofgarz.Our analysis further suggested that there was remarkable functional conservation betweenDrosophila as a valid organism to study the biology ofgarz/GBF1.Thus, these data validate both the logic and principles of miRNA screens, despite inefficiencies, and the use ofgarz/GBF149 has targeted such molecules for health and disease studies18. Recently, it has been shown that siRNA knockdown of GBF1 causes intracellular Amyloid Precursor Protein (APP) accumulation in primary cortical neurons; overexpression of GBF1 contributes to APP trafficking and is dependent on its GEF activity50. Inhibition of GBF1 with brefeldin A was also shown to lead to a new form of cellular degeneration and death in neurodegenerative diseases, based on destruction of the nuclear lamina51.The identification of major cellular events regulated byhttps://www.mousephenotype.org/data/genes/MGI:1861607). We demonstrate here thatDrosophila would constitute an ideal organism to put forward 3Rs-compliant alternatives and, at least partially, replace this mouse line in studies aiming at understanding the role of GBF1 in health and disease.Gbf1 conditional mutant mice have been generated in the Wellcome Trust Sanger Institute and are being phenotyped by the International Mouse Phenotyping Consortium . . . . . . . . (Data underlyingExtended data Table 1.)Extended data Table 1- Data - Pimentelet al., 2020 (XLSX). (Data underlyingExtended data Table 2.)Extended data Table 2- Data - Pimentelet al., 2020 (XLSX). (Data underlyingExtended data Table 3.)Extended data Table 3- Data - Pimentelet al., 2020 (XLSX). (Data underlyingExtended data Table 4.)Extended data Table 4- Data - PimentelData not shown. (ZIP files containing images of membrane delivery of the cell adhesion cadherin molecule CadN.)This project contains the following underlying data:https://doi.org/10.17605/OSF.IO/K5HW938.Open Science Framework: miRNA-garz.Extended Data Table 1. MicroCosm target prediction and ranking tables. For each miRNA, ranking of target prediction - column (Score)*Av(χ2) - was made by multiplying the Average χ2 obtained in the screen (from2)]. This table and the full dataset can be accessed at DOI10.17605/OSF.IO/R3ZX9.Extended data Table 2. PicTar target prediction and ranking tables. For each miRNA, ranking of target prediction - column (Score)*Av(χ2) - was made by multiplying the Average χ2 obtained in the screen (from2)]. This table and the full dataset can be accessed at DOI10.17605/OSF.IO/MDKHR.een from by the SExtended data Table 3. miRNA.org target prediction and ranking tables. For each miRNA, ranking of target prediction - column (Score2)*Av(χ2) - was made by multiplying the Average χ2 obtained in the screen (from2)*Av(χ2)]. This table and the full dataset can be accessed at DOI10.17605/OSF.IO/539J8.een from by the sExtended data Table 4. TargetScan target prediction and ranking tables. The TargetScan database does not provide a scoring system for its predictions, rather a list of 8mer or 7mer sequences matched by the miRNA on the target and an information on the conservation of these sequences. We have attributed a numerical score to these sequences privileging the importance of 8mer vs 7mer and of conservation according to the scheme described in the Methods section. For each miRNA, ranking of target prediction - column (Score)*Av(χ2) - was made by multiplying the Average χ2 obtained in the screen (from2)]. This table and the full dataset can be accessed at DOI10.17605/OSF.IO/WD6ZR.This project contains the following extended data:Creative Commons Attribution 4.0 International license (CC-BY 4.0).Data are available under the terms of the Drosophila to screen by miRNAs for essential glial genes, identifying and briefly investigating one of the candidates (gartenzweg orgarz). The screen appears to be conducted well, the data logically presented and the outcomes interesting and novel. The screening method and methodological algorithm is straight-forward and described well. I have no negative issues with the experiments and believe this is a valid topic for publication that will prove useful to the community. In addition, I agree whole-heartedly that the 3Rs benefits are well demonstrated for studying miRNAs, glia and GBF1 biology specifically.This manuscript usesgarz function in glia rather than glial function itself.The overall interpretations of the manuscript are that this screen is identifying glial functions. From the manuscript, however, it is not clear what these functions actually are? The experiments manipulate expression in glial cells – and then measure broad outcome phenotypes such as lifespan and locomotion. However, I don’t think the authors are necessarily suggesting that the function of glia is lifespan or locomotion.  Later there are experiments that infer potential alterations to intracellular trafficking in glia, but I find these experiments more representative ofThe glia are targeted by miRNA expression and RNAi in the glia themselves. As miRNAs can be potentially released by exocytosis, it would be worthwhile to discuss the possibility for effects originating in other cells. The authors have done a nice control with the RNAi in neurons; however, this has partially replicated the glial RNAi effects and thus overall may reflect some transcellular effects.garz and GBF1; however, I would suggest tempering that conclusion given that they do have divergent effects .The manuscript indicates remarkable conservation in function betweenIt isn’t entirely clear why CD8 trafficking was selected for investigation over other possibilities. Given the lack of effect on cadherin trafficking, the speculation that overall trafficking in glia is impaired seems premature. I have only minor suggestions for improvement, where the authors may want to reconsider wording to accurately reflect outcomes.Is the rationale for developing the new method (or application) clearly explained?YesAre the 3Rs implications of the work described accurately?YesIs the description of the method technically sound?YesIf applicable, is the statistical analysis and its interpretation appropriate?YesAre the conclusions about the method and its performance adequately supported by the findings presented in the article?YesIf any results are presented, are all the source data underlying the results available to ensure full reproducibility?YesAre a suitable application and appropriate end-users identified?YesAre sufficient details provided to allow replication of the method development and its use by others?YesReviewer Expertise:Invertebrate models, genetics, neuroscience. Referee suggested by the NC3Rs for their scientific expertise and experience in assessing 3Rs impact.I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. We thank both reviewer for their competent assessment of our manuscript. We have now provided a revised version of our paper and reply here to the questions and the issues raised by both reviewers.1. The overall interpretations of the manuscript are that this screen is identifying glial functions. From the manuscript, however, it is not clear what these functions actually are? The experiments manipulate expression in glial cells – and then measure broad outcome phenotypes such as lifespan and locomotion. However, I don’t think the authors are necessarily suggesting that the function of glia is lifespan or locomotion.  Later there are experiments that infer potential alterations to intracellular trafficking in glia, but I find these experiments more representative of garz function in glia rather than glial function itself.garz in adult glial cells, exactly as the reviewer points out. The defects in autophagy, protein localization and mitochondria are likely to underlie the defects in glial functions, but we are not focusing here on the precise way in which glial functions are affected, rather on the validation of the screen via identification ofgarz as an essential molecule in adult glia. We understand the point of the reviewer. To clarify, we start from the assumption that affecting glial functions  will impact the functionality of the nervous system, hence it will affect lifespan and behaviour. This is the assumption of our screen, which indirectly addresses the functions of glias. Similarly, we find that any alterations at the subcellular level reveal a function for2. The glia are targeted by miRNA expression and RNAi in the glia themselves. As miRNAs can be potentially released by exocytosis, it would be worthwhile to discuss the possibility for effects originating in other cells. The authors have done a nice control with the RNAi in neurons; however, this has partially replicated the glial RNAi effects and thus overall may reflect some transcellular effects.C. elegans the transcellular effect of miRNA is well documented to be a potent effector, this appears to be much more limited inDrosophila and mammals. With respect to Garz, the simplest explanation is that this ubiquitous Golgi protein is necessary also in neurons, and, as such, it will affect lifespan also from neurons. The reviewer is correct that miRNAs can be released by exocytosis, however it is still unclear what the overall impact of this release (and uptake) is, when looking at the global organism level. While in plants and in3. The manuscript indicates remarkable conservation in function between garz and GBF1; however, I would suggest tempering that conclusion given that they do have divergent effects .Different expression levels.Epitope tag: GFP-Garz vs HA-GBF1.Dominant negative effect of Garz but not of GBF1. We agree that explanation 3 would be in line with some difference between GBF1 and Garz and have slightly modified our text in the discussion to account for this effect. We still think that the conservation of effect between Garz and GBF1 is remarkable in consideration of the other two possibilities and of the rescue effects. While a negative result (lack of toxicity) could be attributed to several reason, the remarkable rescue obtained by GBF1 can be explained with a high level of confidence with GBF1 performing Garz functions. While we agree with this observation toxicity levels may be due to:4. It isn’t entirely clear why CD8 trafficking was selected for investigation over other possibilities. Given the lack of effect on cadherin trafficking, the speculation that overall trafficking in glia is impaired seems premature. Using CD8::GFP as a general membrane reporter we aimed at checking overall intracellular membrane trafficking effects specifically within glia. CadN is expressed in many but not all glial cells and it is much more widely expressed in neurons. In this sense any defect in glial cell distribution of CadN might have been masked by the largely normal distribution of CadN in neurons. We have further clarified this point in our manuscript and apologize for not having made that clearer in our first version. This manuscript by Gonçalves-Pimentel et al. describes an impressive series of very elegant and demanding longevity experiments used to develop an innovative methodological algorithm to identify and rank candidate genes that are targeted by miRNAs and that shorten lifespan when downregulated in adult glial cells. The work presented offers a comprehensive comparison of different miRNA target databases and link those to the longevity analysis screen. Advantage of miRNA is targeting multiple genes at once. For instance by screening 200 miRNA lines, this examines effect of down-regulation of approximately 6000 genes. However this subsequently presents a challenge to determine which genes are targeted with a particular miRNA and which gene is accountable for a given phenotype. Therefore, here, Gonçalves-Pimentel et al. produce an algorithm in which they link their miRNA lifespan screen results to multiple miRNA databases, with the final aim to rank genes that are predicted targets by these miRNA and that affect lifespan and ageing of the glial cells. Briefly, within each data base, each target score was multiplied by values of the lifespan screen results, and then ranking value for each target gene obtain for different data bases. Values obtained from all miRNA databases for each gene were summed for final ranking. This approach combined the effect of the miRNA on lifespan with the prediction of a gene being targeted by particular miRNA, using a variety of databases to strengthen the approach. Combining different databases is particularly important given a surprising difference in their target prediction.garz, , for which they predict that its down-regulation in the glia shorten lifespan. Advantage of such approach is that it offers possibility for screening in an invertebrate organism to uncover genes potentially important in mammalian glia. The top candidate from the screen is a genegarz is a target for three miRNA,miRNA-1,miRNA-79,and miRNA-315. The authors carefully examine its affect in different population of glial cells, replicate shorter lifespan using two differentgarz RNAi lines, overexpress human GBF1 to rescue short lifespan by these different miRNAs. Downregulation ofgarz in adult glial cells also leads to significant impairment of fly motor functions. The authors expanded their characterisation ofgarz-RNAi overexpressor flies further to show accumulation of Ref(2)P and likely consequent alterations/enlargement of mitochondria. Overall this is a detailed and exhaustive study. The algorithm is clearly explained and well presented, and will certainly be useful in other miRNA studies and will inspire its adaptation to other miRNA screens. Moreover the authors developed a valuable list of genes that when down-regulated in glia impact lifespan. This is a really significant resource and dataset that the authors present and should be commended for. I only have a few minor points: Were the longevity analysis done using males or females flies? Why do the authors think that some of their predictions actually resulted in lifespan extension rather than shortening? Could the down-regulation of given gene have different outcomes when it occurs in concert with other miRNA gene target downregulation? Could this be commented in discussion perhaps? How easily can their method be adapted for a different screen using a different output, such as for instance miRNA screen for stress resilience? In the ageing field, lifespan extension is a gold standard to detect anti-ageing genes and interventions. Could the authors comment on finding genes that extend lifespan in glia rather than shorten it? The authors say” Recently, it has been shown that siRNA knockdown of GBF1 causes intracellular APP accumulation in primary cortical neurons” , could they please define APP.    In Figure 1 and 2 driver names are not very visible, could this be improved for clarity or genotypes be written in full perhaps? In Figure 3A, it is not very visible what the arrows is pointing at, at least not in my downloaded version of the article. Overall, this is a very valuable resource for anyone working on miRNA and glial cell. This research is an excellent example how screens in invertebrate organisms can lead to discoveries of important biological functions of mammalian orthologues.Is the rationale for developing the new method (or application) clearly explained?YesAre the 3Rs implications of the work described accurately?YesIs the description of the method technically sound?YesIf applicable, is the statistical analysis and its interpretation appropriate?YesAre the conclusions about the method and its performance adequately supported by the findings presented in the article?YesIf any results are presented, are all the source data underlying the results available to ensure full reproducibility?YesAre a suitable application and appropriate end-users identified?YesAre sufficient details provided to allow replication of the method development and its use by others?YesReviewer Expertise:ageing, mTOR, autophagy, DrosophilaI confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. We thank both reviewer for their competent assessment of our manuscript. We have now provided a revised version of our paper and reply here to the questions and the issues raised by both reviewers.1) Were the longevity analysis done using males or females flies? We apologize for not having made this clear enough but lifespan analysis was done on equal numbers of males and females. This has been stressed in the revised Methods2) Why do the authors think that some of their predictions actually resulted in lifespan extension rather than shortening? Could the down-regulation of given gene have different outcomes when it occurs in concert with other miRNA gene target downregulation? Could this be commented in discussion perhaps? While an additive effect cannot be ruled out. All verifications were done using siRNAs against single genes, the fact that some resulted in the expected phenotype and others in the opposite phenotype than that expected is probably just due to these genes not being really targeted by the miRNA that originate the prediction, or by the fact that the effect of the miRNA is predominantly recapitulated by one of the other targets.3) How easily can their method be adapted for a different screen using a different output, such as for instance miRNA screen for stress resilience? We believe that this method can be applied to different outputs, provided that the appropriate UAS/Gal4 combination of lines and screen methods are used.4) In the ageing field, lifespan extension is a gold standard to detect anti-ageing genes and interventions. Could the authors comment on finding genes that extend lifespan in glia rather than shorten it?Sirt2, which mildly extends lifespan when downregulated in our screen, but we feel it would be inappropriate to speculate on this candidate gene without a deeper investigation, like the one done here forgarz. We have not focused on these genes as they were not the intended scope of our work, and we also notice that in a wt background, lifespan extension is usually much milder. A possible case of interest would be5) The authors say ”Recently, it has been shown that siRNA knockdown of GBF1 causes intracellular APP accumulation in primary cortical neurons”, could they please define APP. We apologize for having overlooked this abbreviation; it is now corrected. APP is the Amyloid Precursor Protein   6) In Figure 1 and 2 driver names are not very visible, could this be improved for clarity or genotypes be written in full perhaps?repo-Gal4, as stated in the figure legend. This has now been modified in a revised Fig.1. In Fig.2 we actually do not write the name of the driver as all experiments use7)In Figure 3A, it is not very visible what the arrows is pointing at, at least not in my downloaded version of the article. This has now been modified with some zoomed-in inset to make better visible the details pointed at by the arrow.


It is useful for surgical decision making and simulation, hands-on surgical training (HOST) and cardiovascular morphology teaching. 3D-printed models allow easy understanding of surgical morphology and preoperative surgical simulation. The most common indications for its clinical use include complex forms of double outlet right ventricle and transposition of the great arteries, anomalous systemic and pulmonary venous connections, and heterotaxy. Its utility in congenital heart surgery is indisputable, although it is hard to “scientifically” prove the impact of its use in surgery because of many confounding factors that contribute to the surgical outcome. 3D-printed models are valuable resources for morphology teaching. Educational models can be produced for almost all different variations of congenital heart diseases, and replicated in any number. HOST using 3D-printed models enables efficient education of surgeons in-training. Implementation of the HOST courses in congenital heart surgical training programs is not an option but an absolute necessity. In conclusion, 3D printing is entering the stage of maturation in its use for congenital heart surgery. It is now time for imagers and surgeons to find how to effectively utilize 3D printing and how to improve the quality of the products for improved patient outcomes and impact of education and training. Congenital heart diseases (CHDs) are structural heart diseases that are characterized by extremely wide anatomical variations and complexity with a number of individual pathologic entities that are only rarely encountered in practice. CHDs usually require surgical treatment or catheter-based intervention that requires proper understanding of three-dimensional (3D) surgical anatomy. Understanding of these complex structures requires both 2D and 3D imaging. While 2D imaging is for exploration of the composition of a 3D structure, 3D imaging is for intuitive understanding of a structure's shape. The more complex the structure, the higher the need for 3D demonstration. This can be represented on a computer screen, in a simulated environment  or through physical 3D-printed models. Among these three paradigms of 3D demonstration, 3D printing allows the most realistic perception of the pathology without the requirement of devices such as a computer screen or virtual headset. The tactile properties of 3D-printed models enhance understanding of the anatomy with clarity and unambiguity, minimizing the risks of misinterpretation and miscommunication. In addition, the models provide an opportunity for hands-on simulation of surgical or interventional procedures, which is not available on the other platforms.In the last two decades, 3D printing has become practically applicable and valuable for congenital heart surgery –9. In thContrast-enhanced computed tomography (CT) and magnetic resonance (MR) angiograms provide the 3D image data that are best suited for 3D modeling and printing owing to excellent contrast and spatial resolutions. For the best quality of images and 3D printing, imaging should be performed with electrocardiographic (ECG) gating and breath-holding (for CT) or respiration navigation (for MR). As cardiac surgery is usually performed with cardioplegia, ECG-gating is preferred to target end diastole. When ECG-gating or breath-holding/respiration navigation is not applicable, non-ECG-gated imaging during quiet respiration is acceptable with the detail compromised. CT provides a high spatial resolution ranging between 0.5 and 0.65 mm, while the spatial resolution of MR is limited to 1–2 mm. In both CT and MR, homogeneous opacification of the cardiac structures is important as postprocessing for 3D printing relies primarily on thresholding based on signal intensity. Although MR requires a long imaging time, homogeneity of contrast enhancement is easier to achieve at MR than at CT. CT images reconstructed from rotational angiograms obtained during cardiac catheterization are also applicable for 3D printing . 3D echoAcquired DICOM  data are processed for 3D modeling using threshold-based segmentation and additional manual editing –4. The sApplications of 3D printing in congenital heart surgery can be divided into the clinical applications for surgical decision making and planning, preoperative surgical simulation and computer-aided design of the required patches and baffles, and the applications for education and surgical skill training .A choice between biventricular and univentricular repairs in complex CHDs is frequently a binary decision that determines the ultimate fate of the patient's health , 18. TheDouble outlet right ventricle (DORV) is by far the most common referral indication for 3D printing , 19–23. Surgical or interventional procedures can be simulated on 3D-printed models made of soft materials  11, 29––29–31. CFor experienced surgeons, simulation can be beneficial in cases where there are more than one potential surgical approach to treating the defect. Usually these complex decisions are made based on the surgeon's own experience and training background as well as by referencing the literature. For complex cases where the surgical treatment strategy can be controversial, the surgeon may use 3D models to simulate different surgical strategies to help refine what is the best applicable procedure for the given patient's anatomy . FurtherTraditionally, patches for septal defect closure, intraventicular baffles and vascular augmentation patches are trimmed during surgical procedures. While simple closure patches are easy to trim, complex patches and baffles require surgeon's best guess of the result for appropriate trimming and application. Such empirical approaches to complex surgical procedures are hard to be standardized and frequently associated with unsatisfactory anatomical results , 37. TheSurgical training for CHDs is challenging and requires a long training period because of relative rarity of individual lesions and demanding surgical techniques. Furthermore, intraoperative training presents a potential risk to patient safety. As a consequence, surgical trainees have been provided with limited operative experience in congenital heart surgery. Therefore, surgical simulation has long been sought to develop surgeons' technical skills without compromising patient safety , 41. Unt3D-printed models are applicable for training of both extracardiac and intracardiac procedures. They can also be useful in training of minimally invasive surgery such as closure of an atrial septal defect through a lateral thoracotomy. Models can be designed in various forms depending on the purpose of the training. Before any procedure is started, an inexperienced surgeon may want to master the skills for cutting, suturing and cannulation. Such entry level skills can be easily practiced on a sheet or tube made of soft material. The surgical procedures can be practiced in a step-by-step fashion from basic bench top models to complex surgical models. For instance, models for patch closure of a VSD can be made in three different forms: a model with a well-exposed hole, a model with cardiac valve leaflets added, and a model with chordae tendinae as well as valve leaflets added . For mosThe surgeons' operative performance on 3D-printed models can be objectively assessed by using assessment tools such as the Objective Structured Assessment of Technical Skills (OSATS) with Global Rating Scale (GRS) , 50 and Proper understanding of the pathological features of a wide variety of congenital heart diseases is fundamentally important in the accurate diagnosis and surgical treatment of patients. Traditionally, congenital heart morphology teaching has heavily relied on observation of pathologic specimens removed from deceased patients or at cardiac transplantation. However, pathologic specimens are rare resources that are available in the limited number of institutions where specimens have been collected from the old era of high surgical mortalities. While old specimens are deteriorating with time, the sources of new specimens have increasingly been scarce due to ever improving surgical outcomes as well as ethical and legal issues related to retaining human bodies or body parts for educational purposes . 3D-prin3D-printed models of either the patient's own heart or other individuals' with a similar pathology are very helpful for patient counseling  66). Wi. Wi66). This information is summarised in 3D printing is an inefficient method of building a 3D object as it requires deposition of thin layers of print material(s), layer upon layer. Using polyjet technology, it takes up to 15 h to print a high-quality model of an adult heart size. The print materials that allow surgical procedures are relatively expensive. Furthermore, post-processing of image data requires the knowledge and hands of experienced specialists as well as expensive software. It is often a painstaking long process. Therefore, a high cost is a major limitation of 3D printing, while it has not yet been recognized as a standard service for reimbursement by the government or insurance companies in most countries. The cost for post-processing software, 3D printing equipment and printing materials will be reduced with increasing utilization of the service as well as technological improvement such as printing time.Although most surgical procedures are applicable on the models printed with currently available soft materials, further improvements in the materials' physical properties such as elasticity and strength is required. The addition of fiber-like structures to the model may improve the strength as well as the elasticity of the models. Further efforts should be made to simulate the different physical characteristics of cardiac valves, endocardium and pericardium as well as myocardium.3D printing of cardiac valves and supporting apparatuses is an important area to explore as valve abnormalities are not only common but also surgically challenging. Although accurate replication of the pathology will remain difficult because of the limitation in 3D imaging of the valve leaflets and chords that are constantly moving, delicate structures –70, the The accuracy of anatomical representation in 3D-printed models will continue to improve with improvement of spatial, contrast and temporal resolutions of 3D imaging as well as printing resolution of 3D printers. The evolution of 3D printing technology will follow a path similar to that of digital paper printing. The printer will become smaller and cheaper, and the resolution will become higher. In the future, 3D printers might become as ubiquitous as digital paper printers are now. Furthermore, 3D printing capability could be an element of sophisticated imaging equipment.3D bioprinting has been an attractive application of 3D printing as bioprinted tissue may provide the characteristics of human tissue with growth potential , 71, 72.The HOST course for congenital heart surgery using 3D-printed models has not yet been widely disseminated partly because of its relatively short history and also due to rather expensive costs. However, young surgeons' effective surgical skill development is worth the current associate cost of the course. The investment will be recovered indirectly from improved short and long term outcomes of congenital heart surgeries performed by well-trained surgeons. The HOST course will turn out to be affordable, cost-effective program with wide utilization of the service as well as reduced costs. With further improvements in the quality and variety of the models and the development of procedure-specific HOST-CHS assessment tools for all applicable procedures, HOST courses will contribute to the improvement and standardization of congenital heart surgery training and potentially contribute toward surgeons' certification examinations.3D printing is useful for surgical decision making and simulation, computer-aided desing of surgical baffles and patches, hands-on surgical training and cardiovascular morphology teaching for medical personnel and patients/family. 3D printing is entering the stage of maturation in its use for congenital heart surgery. It is now time for imagers and surgeons to find how to uniquely utilize 3D printing and how to improve the quality of the products for both better patient outcomes and education of CHD morphology and surgery. Although it is relatively expensive, the cost can be recovered indirectly from improvement of patients' surgical outcome and quality of life. Furthermore, hands-on surgical training with 3D-printed models allows efficient education of surgeons in-training. Implementation of HOST courses in congenital heart surgical training programs is not an option but an absolute must.All authors contributed in 3D modeling and printing of congenital heart diseases for patient management, education and surgical training, and approved the content of the article.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


MAP3K15, CHRM2, and GALNT13 were upregulated in the Younger group, whereas COL17A1 and EDA2R were upregulated in the Older group. Multivariate analysis with adjustment for covariates showed that EDA2R was a risk factor for lung aging. Our study identified differences in the gene expression of the lungs of older subjects compared with younger subjects. These findings may have implications in lung aging.Aging is a multifactorial process that leads to molecular and cellular changes, contributing to the susceptibility of most lung diseases. However, the molecular and genetic mechanism of lung aging remains poorly understood. Here, we performed RNA-seq transcriptome analysis of the lung tissues of 68 subjects and analyzed their gene expression profile to evaluate candidate genes related to lung aging. The subjects were classified into two groups (Younger group and Older group) based on their age. Lung tissues were obtained from surgically resected specimens, processed, and analyzed with RNA-seq. The median age of the subjects was 45 years in the Younger group and 74 years in the Older group. Around 71% and 53% of the subjects were female in the Younger and Older groups, respectively. After gene quality control and filtering, differentially expressed gene analysis showed that  With the large increase in life expectancy, population aging has rapidly become a major issue worldwide. Aging is one of the most well-known risk factors for many diseases and has been associated with increases in morbidity and mortality in various lung diseases . The incIn terms of molecular and cellular changes, the nine hallmarks of aging have been proposed in a landmark paper , i.e., gOf the 68 subjects included in this study, 42 (61.8%) subjects were female . The medOf 14,775 genes, 4,108 genes were differentially expressed between the age groups by Student’s t-test with p value < 0.01. After adjusting the p value using the false discovery rate (FDR) method, 2,442 genes were differentially expressed. Among these genes, 897 genes were upregulated in the Older group, and 1,545 genes were upregulated in the Younger group. We performed linear regression analysis to adjust for the effect of smoking, and 3,565 genes were differentially expressed between the two groups with p value < 0.01. Of these genes, only 158 genes were significantly associated with smoking rather than aging; thus, we used the former differential gene expression data by the t-test for further evaluation due to little effect of smoking on DEGs. Hierarchical clustering analysis was also performed, and a heatmap for the two groups was generated .MAP3K15, CHRM2, and GALNT13 from the Younger group and COL17A1, MUC16, and EDA2R from the Older group were re-tested and validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR)  with significance, the top 10 genes with the largest fold changes in both the Younger and Older groups are shown in qRT-PCR) .EDA2R was a significant contributing factor in the Older group  was an independent risk factor in the Older group after additionally adjusting for history of smoking and gender. In addition to EDA2R, GALNT13  and history of smoking  were significant risk factors , which have been found to increase in patients with COPD with/without emphysema in our previous study, and these genes showed no significant difference between the two groups in the validation.For technical validation, qRT-PCR was performed to identify DEGs . The mRNanalysis . We alsoEDA2R), was recently reported as a strong candidate gene for aging [EDA2R was also highly associated with aging in the adipose tissues, artery, heart, muscle, and skin tissues in the GTEx project, which evaluated the aging signature of these tissues [EDA2R was the most differentially expressed according to the p value in the Older group compared with the Younger group as well as the fourth most upregulated gene according to the fold change. Moreover, when multivariate linear regression analysis was performed, EDA2R was the only significantly different gene in DEG analysis. Although little is known about this gene, EDA2R belongs to the tumor necrosis factor receptor superfamily, which is involved in various signaling pathways. It is known to be associated with nuclear factor kappa B (NF-kB) and p53 signaling pathways and can promote apoptotic signaling through the binding of its ligand EDA-A2 [In this study, we identified several genes with increased expression in the Older group, and there were significant differences in the gene expression between the two groups according to the age. One of the genes, ectodysplasin A2 receptor (or aging . Accordi tissues . In the d EDA-A2 .COL17A1), encodes the alpha chain of type XVII collagen, which is a major structural component of hemidesmosomes and plays an essential role in strengthening and stabilizing the skin. Mutations in this gene are associated with both generalized atrophic benign and junctional epidermolysis bullosa [COL17A1 mutation have been reported to exhibit a premature aged skin phenotype, including hair and hair loss [COL17A1 was the only procollagen gene that was increased with aging among 8 procollagen genes, which were altered with aging in a study of mouse skeletal muscles [COL17A1 in lung aging remains unknown and should be further evaluated. Mucin 16 (MUC16) is known as ovarian cancer antigen CA-125. It was reported that CA-125 level could be increased in chronic medical conditions including cancer. [MUC16 was one of the genes in a second large cluster that included dynein and other MUC genes, which are exclusive to the respiratory epithelium and goblet cells of bronchial structures [MUC16 showed increased expression in the Older group compared with the Younger group, qRT-PCR did not show consistent results; thus, we excluded MUC16 from linear regression analysis.Another gene with increased expression in the Older group, collagen type 17 alpha 1 ( bullosa . Recentlair loss . Interes muscles . Howeverructures . In addiCHRM2) was downregulated in the Older group compared with the Younger group. The CHRM2 gene encodes the M2 muscarinic acetylcholine receptor and belongs to the superfamily of G protein-coupled receptors, which show functional diversity in various cellular responses via the binding of acetylcholine to these receptors [CHRM2 is known to activate several signaling pathways in the nervous system, and little is known about the effect of this gene in pulmonary disease. Recent studies of the pathogenesis of allergies and asthma have reported that muscarinic receptors may modulate airway reactivity [CHRM2 polymorphism may be associated with disease severity, lower lung function test values, frequent exacerbations, and poor response to anti-cholinergic drugs [CHRM2 has also been reported as a candidate gene for nicotinic addiction by modulating presynaptic auto-regulation in the cholinergic system [CHRM2 showed significantly reduced hyperoxia-induced lung injury in a mouse experiment [CHRM2 in modulating the response to hyperoxia. Polypeptide N-acetylgalactosaminyltransferase 13 (GALNT13) was another gene with decreased expression in the Older group compared with the Younger group. GALNT13 belongs to the GalNAcT family of enzymes, which initiate the O-glycosylation of mucins. A previous study reported that the expression of GALNT13 mRNA was the highest in brain tissues, and it may be a strong predictor of poor clinical outcome in neuroblastoma patients [GALNT13 is unknown in terms of lung disease. A genome-wide interaction study on occupational exposures in relation to the level of lung function reported that GALNT13 was one of the candidate genes that might be involved in biological pathways leading to lung function impairment [Cholinergic receptor muscarinic 2 . In addition, most patients had malignancy; however, it was in the early stage . This may be explained by the characteristics of the cohort, which consisted of patients who underwent surgery because of the presence of nodules in the lungs. However, the proportion of patients with malignancy was similar in both groups, and most patients (88%) who had malignancy remained at stage I or II. This could offset the effect of cancer on gene expression in the two groups.EDA2R was an independent factor after confounder adjustment for subjects without chronic lung disease in the Older group. Further larger studies are needed to validate these results.In conclusion, we identified several genes that may be associated with normal lung aging by RNA-seq. The subjects were selected from a registered in-house tissue storage system (the Asan Biobank), in which lung tissues for this study had been stored from 2012 to 2016. The lungs were resected mostly due to the presence of tumors . Immediately after the resection, lung tissues were obtained at a site as far away as possible from the tumor tissues and stored under -170°C of vaporized nitrogen in the Asan Biobank. Subjects who had abnormal lung function before lung resection or any history of chronic lung diseases , lungs destroyed by tuberculosis, or bronchiectasis) were excluded. Current smokers who smoked within one month before lung resection were also excluded. Subjects finally diagnosed as having a malignancy with TNM stage II or higher after lung resection were excluded. To compare differences in the gene expression of the lungs according to age, the subjects were classified into two groups based on their age: the Younger group and Older group. Among the subjects who met the inclusion criteria, we chose two contrasting groups consisting of younger subjects (Younger group) vs. older subjects (Older group) with an appropriate number of sample size in each group (see below). We excluded subjects with intermediate ages.The hypothesis of this study was that there would be a significant difference between the Younger and Older groups. Based on a level of significance of α = 0.05 and a power of 80% for detecting a difference in the expression level of a gene(s) of two times higher, the sample size per group was calculated to be 17. Considering additional adjustment for smoking and gender, the final sample size was determined as 34 per group with a total sample size of 68 for two groups.Total RNA was isolated from apparently normal fresh frozen lung tissues that were remote from the lung cancer. RNA integrity was assessed using an Agilent Bioanalyzer system, and RNA purity was assessed using a NanoDrop spectrophotometer. The total RNA (1 μg) was used to generate cDNA libraries with the TruSeq RNA Library Prep Kit. The protocol consisted of poly A-selected RNA extraction, RNA fragmentation, reverse transcription using random hexamer primers, and 101 bp paired-end sequencing using the Illumina HiSeq 2500 system.For quality control, read quality was verified using FastQC, and read alignment was verified using Picard. All samples had a Phred score higher than 20. To preprocess RNA-seq data, we removed the adapter sequence using Trimmomatic and removed reads with a Phred score below 15. UCSC hg19 human genome and transcriptome references were used to map the cDNA fragment obtained from preprocessing. We used bowtie2 aligner and HISAT2 to map reads and used StringTie to calculate the fragments per kilobase of transcript per million mapped reads (FPKM). We only used genes with a FPKM value above 0 in at least one sample. Further analysis was conducted on 14,775 out of 27,685 genes after filtering for genes with 0 counts in the whole samples, noncoding genes, and low-variance genes.For technical validation, we re-tested some of the genes that were differentially expressed by qRT-PCR. Gene expression in the lung tissues was quantified by qRT-PCR using LightCycler 480  with LightCycler 480 SYBR Green I Master . Total RNA was isolated using the RNeasy Plus Mini Kit , and 1 μg of each sample was reverse-transcribed using the Maxima First Strand cDNA Synthesis Kit  for real-time qRT-PCR.Clinical statistical analyses were performed using SPSS v26.0 . We performed quantile normalization to adjust for between-sample bias using the preprocessCore R library. Linear regression was performed using Python StatsModels 0.10.2 to identify DEGs between the Younger and Older groups and correct the effects of smoking.Supplementary Figure 1Supplementary Tables