Carcharhinus amblyrhynchos, using acoustic telemetry in New Caledonia. The distribution of home range was then compared to local MPA sizes. We report a home range of 12 km2 of reef for the species with strong differences between adult males (21 km2), adult females (4.4 km2) and juveniles . Whereas local historic MPA size seemed adequate to protect reef shark home range in general, these were clearly too small when considering adult males only, which is consistent with the reported failure of MPAs to protect sharks in New Caledonia. Fortunately, the recent implementation of several orders of magnitude larger MPAs in New Caledonia and abroad show that recent Indo-Pacific MPAs are now sufficiently large to protect the home ranges of this species, including males, across its geographical range. However, protection efforts are concentrated in a few regions and cannot provide adequate protection at a global scale.Dramatic declines in reef shark populations have been documented worldwide in response to human activities. Marine Protected Areas (MPAs) offer a useful mechanism to protect these species and their roles in coral reef ecosystems. The effectiveness of MPAs notably relies on compliance together with sufficient size to encompass animal home range. Here, we measured home range of 147 grey reef sharks,  Due to their conservative demography, reef sharks are particularly vulnerable to anthropogenic mortalities from fisheries, particularly overfishing and bycatch6. Dramatic declines of populations have been documented worldwide11, raising concern about the potential ecological impacts of the extirpation of these predators in coral reef and other ecosystems12.Reef sharks are among the largest resident predators on coral reefs, playing a variety of ecological roles that could potentially be important for reef communities16. However, the ability of MPAs, including no-take zones, to protect mobile top predators such as reef sharks is increasingly being questioned18. For instance, no-take MPAs have been reported to have almost no effect on reef shark abundance on the Australian Great Barrier Reef (GBR)8. Similarly, in the Chagos archipelago, one of the largest marine protected areas in the world, current abundances of reef sharks have been shown to be low compared to estimated baseline levels11. In New Caledonia (South-Western Pacific), even an established (40 years), relatively large (170 km2) and highly-restrictive (no-entry) MPA failed to protect or restore baseline levels of reef shark abundance9 and behaviour19.Excluding fishing activities through the implementation of Marine Protected Areas (MPAs) has often been proposed as the main solution to prevent the collapse of reef shark populations13. These species are indeed highly vulnerable to even low levels of anthropogenic mortality due to their life history traits20. In addition, fishing efforts tend to increase in the vicinity of MPAs, thereby increasing mortality in the proximate outside22. As such, besides the need for a strict enforcement of regulations within their boundaries, MPAs should be sufficiently large to limit the spread of individuals exiting to surrounding areas open to fishing. This can be an issue for mobile species such as sharks.The incidence of illegal fishing inside MPAs is believed to be partly responsible for the lack of effectiveness in protecting reef sharks24. Through a meta-analysis of 87 MPAs around the world, size and isolation by deep water or sand have been highlighted as key factors in MPAs’ efficiency to protect predator species25, with only a small subset of these MPAs qualified as large (> 100 km2). For coastal sharks, MPAs > 20,000 km2 have been identified as the most efficient6. Recognizing that the effectiveness of an MPA to protect mobile species partly relies on its ability to encompass the home range of individuals, i.e. the area where animals spend most of their time31, a critical step in assessing the effectiveness of current MPAs for mobile reef shark species should thus consist in comparing individuals’ home ranges with the size of protected areas.The inability of MPAs to encompass individuals’ movements has been identified as contributing to their failure to protect mobile speciesCarcharhinus amblyrhynchos, is one of the most common reef shark species in the Indo-Pacific34. The estimated home range for this species36, along with its high level of site residency39 and long-term fidelity42, suggest that MPAs > 100 km2 would be appropriate for its protection. However, in New Caledonia, such MPAs were assessed as failing to protect this species .The grey reef shark, 19, this inconsistency raises questions about the current assessments of grey reef shark home range. Indeed, current knowledge of home range and movement abilities of this species is often based on relatively small sample sizes, typically less than 40 individuals39, and female-skewed sampling41. Subsequent estimations of home ranges could then have overlooked individual variations with a loss of pertinent information for the assessment of MPA ability to protect all components of a shark population.Since illegal fishing pressure is believed to be low in New Caledonia2), ages (established 1970–2018) and restrictions (no-take and no-entry) exist. The distributions of shark home range was calculated and compared to the size of MPAs in New Caledonia and in the Indo-Pacific to assess the extent to which MPAs encompass the majority of grey reef shark home range, and thus offer adequate protection for this species.In order to overcome these limitations, 147 adult and juvenile grey reef sharks of both sexes were tracked with acoustic telemetry for over three years within an array of 70 acoustic receivers across the New Caledonian archipelago, where 25 protected areas of various sizes : three no-entry MPAs at Petrie atoll, Petit Astrolabe reef and Grand Astrolabe reef, respectively encompassing 600, 200 and 725 km2, and two no-take MPAs at the atolls of Entrecasteaux and Chesterfield & Bellona, encompassing respectively 3500 and 27,150 km2, and comprising several no-entry zones up to 6, 600 km2 . All methods, including shark capture, handling, tagging and release, were carried out in accordance with relevant guidelines and regulations in New Caledonia. All experimental protocols were approved and authorised by the Government of New Caledonia (permit 2015-1351/GNC), the Southern Province of New Caledonia (permit 479-2016/ARR/DENV and 2093-2016/ARR/DENV) and the Northern Province of New Caledonia (permit 60912-1508-2015/JJC).A total of 147 grey reef sharks were internally fitted with V16 acoustic transmitters . Seventy VR2W acoustic receivers  were deployed from July 2015 to December 2018 across four regions of the New Caledonian archipelago . Kernel-based density methods are usually used to calculate UDods Fig. . Insteaders Fig. . The out95 and UD100 values varied between sex and maturity stage (juvenile or adult). The aovp function from the lmPerm R package was used, considering the Anscombe criterion to determine the number of permutations. Pairwise permutation Student tests (n = 999 permutations) were performed to compare the UD95 and UD100 values of adult males, adult females, juvenile males and juvenile females. UD values were log-transformed (y = log10(1 + x)) before analyses.Two-way PERMANOVAs were performed to test if UD34), outside the mating season (October–June), or during both seasons. Then, the percentage of UD100 exclusively used during the mating season was computed and compared among sex and maturity stage by PERMANOVA. UD95 and UD100 values were then computed for each season and compared among sex and maturity stage by PERMANOVA.Seasonal variations in shark home range were investigated by identifying reef portions used during the mating season  to determine 95% confidence intervals.Cumulative UDS of outer reef slope to cover shark home range. We first discretized S in n intervals of size dS = 1 km2. The probability Pij that the UDj of a shark j centred in interval i would be fully covered by protection was set to one when the UDj of shark j centred in i was fully covered by the MPA, and set to zero otherwise. For this interval i, a probability Pi was calculated as the average of {Pij} for all shark j from the distribution. Then, the probabilities {Pi}n for all interval i encompassed by the S-large protected area were averaged to estimate the probability Π that the UD of any shark, located at any place in the protected area, would be fully covered , had their centroid comprised between latitudes 26°S and 26°N and between longitudes 25°E and 150°W  and if their year of creation was informed. Inclusion of MPAs from New Caledonia resulted in a non-exhaustive dataset of 622 MPAs.In order to test if existing MPAs encompassed grey reef shark home ranges, we calculated surfaces of reef slopes covered by existing MPAs in New Caledonia and across sites in the Indo-Pacific, using the World Database of Protected AreasAmong the 147 grey reef sharks fitted with acoustic transmitters  and a mean UD100 of 12 km2 (7.3–15.7 km2 CI) of reef. Adult males had significantly and substantially larger home range  than adult females , juvenile males  and juvenile females . On average, adult males used 52% of their home range exclusively during the mating season, compared to only 9% for other groups . However, maturity stage had a significant effect on UD100 during this season , with adults showing a significantly higher home range than juveniles , with adult males showing significantly higher home ranges than adult females and juveniles of both sexes  and 76% (95% bootstrapped-CI: 69–83%) of sampled sharks had UD95 and UD100 values lower than 10 km2 of reef, respectively. When considering adult males only, respectively 83% (95% bootstrapped-CI: 74–94%) and barely half of individuals  had UD95 and UD100 values lower than 10 km2 of reef  would be able to fully cover the UD95 for 84% of sharks, and the UD100 for 59% of sharks only , would encompass the UD100 for 78% and 98% of adult males, respectively.Cumulative curves of UD values were then used to model the proportion of sharks whose home range could be fully covered by an MPA of a given size, considering a homogeneous distribution of individuals in the area Fig. A. The moly Table . These p2 of reef can achieve the ambitious management objective of protecting the home range (UD100) of 80% of adult males. Only 26 out of the 622 Indo-Pacific MPAs exceeded this threshold. These 26 MPAs were all created after 2004. Only two old MPAs came close to this size: the Iriomote Ishigaki National Park and the Johnston Island National Wildlife Refuge, respectively created in 1972 and 1926 by Japan and the United States and covering 94 and 75 km2 of reef  and the Coral Triangle (n = 4), followed by Micronesia (n = 1), Tropical North-West Pacific (n = 1) and Polynesia (n = 1)  Fig. C. These 19 may be attributed to a large suite of factors, such as illegal fishing52 and human proximity-induced fitness alterations19. However, we focused here on the hypothesis that MPA ineffectiveness may also be due to their small size and their failure to protect reef shark home range.The lack of efficiency of MPAs implemented in New Caledonia before 2010 to protect reef shark populations9. However, our results confirm the relevance of recent efforts of the Government of New Caledonia in implementing 1–2 orders of magnitude larger MPAs in the remote D’Entrecasteaux, Chesterfield, and Bellona atolls. Beyond protecting reef sharks, such very large MPAs should be able to protect the function played by large and mobile fish, predators especially, and thus key ecosystem properties and functional diversity53.Our results revealed that until very recently, the size of MPAs in New Caledonia were insufficient to protect grey reef shark home range, especially adult males. This may explain in part local MPAs’ failure to restore levels of abundances observed at remote reefs54.According to our model, very large MPAs enable coverage of the home range of nearly, if not all, local grey reef sharks. Moreover, the outputs of our model are likely conservative since its framework did not allow to consider habitat limitations. With more than a hundred individuals tagged, none was observed to cross oceanic channels greater than 35 km Appendix , Fig. S656. Moreover, in species where mating include male harassment57, male density can be deleterious for population growth56. Yet, males’ lesser importance for population dynamics remains theoretical and has not been confirmed in this species, thus should not be used to draw males out of conservation efforts. Moreover, grey reef shark adult males provide an essential function in promoting genetic diversity, as they provide most gene dispersal in this species59. In this perspective, we think that conservation management deserves particular focus on this population segment.Our results also highlight the greater vulnerability of adult males, which are characterized by larger home ranges than females and juveniles. In non-monogamous species, males’ importance in population dynamics is often considered as lesser than females’, as females are likely to find a mate irrespective of male density60. Outer reef slopes were thus considered as a linear system, and movements were interpreted as mostly occurring in this habitat. A similar approach was used by42. This species often uses the pelagic and lagoon habitat as well61, thus our results potentially underestimate the real magnitude of their space use. Nevertheless, our conclusions about MPA size should remain valid as MPAs were considered in their ability to cover sharks’ home range on their most critical habitat at the least.Grey reef sharks were monitored in the outer reef slope habitat only, as it is their preferred habitatThirty-seven individuals were detected on one receiver only, highlighting a second source of home range underestimation with our methodology. Indeed, this methodology was limited by the resolution of the acoustic array. As the Utilization Distribution of individuals detected on one receiver was likely lower than receiver spacing in the array, these individuals were attributed null values of UD. Yet, this skew of small UD values to null UD values was of little consequences over following modelling of MPA’s ability to cover shark range, considering our modelling framework and the use of cumulative curves of UD values.28 but a homogeneous distribution of individuals in the theoretical MPA was considered here. Each discretized MPA interval was considered independently from the others, which implied that there was no consideration for potential consequences of an overlap of home ranges between neighbouring intervals. However, such overlapping would not impair our reasoning because the grey reef shark is a relatively social species that is not known to generally exclude conspecifics from its territory64.This modelling procedure was similar to the one used in42 and residency39 in this species. Our results concur with these findings, as 37 out of the 118 tagged animals were detected on one receiver only, the one they were tagged at. Estimates of home range size are also well documented for this species36 but values from previous studies are difficult to relate to ours, partly due to differences in the UD estimators that were used, but mainly due to differences in receiver arrays configuration. When we report an average UD100 of about 12 km2 of reef over 118 individuals in three years of study, Speed et al.35 reported an average UD of about 20 km2 total area over 2 individuals in two years  and Udyawer et al.36 reported an average UD of about 30 km2 total area over 27 individuals in three years . Both these studies monitored sharks on an array covering the lagoon habitat in addition to the outer reef slope, making comparisons difficult. Still, given that such arrays cover much larger areas of available habitat than ours, our estimates were expected to be several times lesser than the one reported in these studies. These higher values could be explained by the larger sampling size of our study, potentially enabling to better reflect inter-individual variations and thus unveiling a larger range of values. It could also indicate the preference for grey reef sharks to travel along corridors where our receivers were deployed. The incidence of adult male values in our average population estimate could also play a role in this, as neither of these previous studies accounted for variations of home range with sex and ontogeny.Grey reef shark movement patterns are well described in the literature and numerous acoustic telemetry studies revealed a high level of long-term site-fidelity95 and UD100. The determination of MPAs’ size requirements is thus affected by the choice of the home range metric to consider, and this choice depends on whether it is essential to cover areas where animals spend most of their time or the entirety of visited areas. This decision relies on the level of risk that animals are exposed to outside MPAs. Assuming that MPAs protect from mortality, if risk is considered to be proportional to the time spent outside MPAs, protecting the UD95 may be adequate. However, in cases of greater risk level (e.g. high surrounding fishing pressure), any time spent outside MPAs may be lethal for an individual, and protecting animals’ UD100 may reveal necessary. Species’ need for protection may also be higher at particular times of their life cycle, and a change in space use during periods of vulnerability would not necessarily translate into greater UD95 if such periods are short enough. In our case, adult males showed range expansion during mating season, most likely linked to reproduction. Yet, this spatial scale is not well described by UD95 values, and considering UD100 would be more appropriate to protect areas required by adult males for reproduction. This consideration may also partly explain why previous knowledge about the grey reef shark home range, whose estimates were based on most frequented areas36, was inconsistent with MPAs’ inability to protect this species in New Caledonia19.The modelling of MPAs’ ability to protect grey reef shark home range was based on two metrics: UD31 implemented a similar modelling procedure to provide recommendations on MPA size requirements to protect several species of reef sharks. They conclude that a 30 km-wide MPA would be theoretically able to fully protect only 50% of grey reef sharks. These conclusions concur with ours, as the Abore MPA, which roughly cover 35 km of continuous barrier reef, is expected to cover the UD100 of 59% of grey reef sharks in our system.With activity space metrics based on dispersal distances, Dwyer et al.65. Yet, a meta-analysis of 1800 tropical reefs have concluded that effective conservation of marine predators could only be attained in remote areas, as even small rates of illegal extraction in protected areas close to human populations can be deleterious to such vulnerable species13. Moreover, remoteness is becoming increasingly less of an obstacle for industrial fishers68, raising concerns about the future exploitation of wilderness reefs such as D’Entrecasteaux and Chesterfield in a context of raising fish price69. This should be particularly emphasized for the case of sharks, given the high value of their fins on Asian markets70.Irrespectively of the home range metric considered, our results highlighted the adequacy of the recent MPAs implemented in the remote D’Entrecasteaux atolls and Chesterfield & Bellona atolls to protect grey reef sharks. Protecting such remote areas, which constitute de facto refuges in the way that they are already almost free from human activities, may seem superfluous, and is often even considered to mislead conservation efforts by preventing resources being spent on areas under higher threats71 proposed seasonal zoning in a marine park in the island of Zakynthos, Greece, based on seasonal space use of loggerhead turtles, Caretta caretta, around a critical breeding site. Our results provide reliable information to support the relevance of implementing seasonal protection measures, e.g. fishing gear restrictions or local MPA expansion. Such seasonal measures are all the more necessary when considering the case of New Caledonian migratory adult males34, capable of travelling several hundreds of km during the mating season. The protection of these few individuals, perhaps anecdotal when considering total population dynamics, may yet be essential to enable gene flow and metapopulation resilience.Protecting large areas may arguably be feasible only in remote areas. Conservation management in areas closer to human activities may thus be achieved through alternative measures. For example, Schofiel et al.72. The latter has spillover toward non-protected areas as the primary objective, and calls for the implementation of numerous closely-spaced MPAs73. Here however, protection is essentially considered in the perspective of conservation. The objective is to sustain populations in protected areas and thus to prevent spillover of individuals toward open areas where mortality risk is increased. Within a conservation framework, our results concur with those of6 and call for the implementation of much larger MPAs to protect coastal sharks globally. The grey reef shark was used here as a case study because of its abundance, but these findings should illustrate the importance of implementing large MPAs for the conservation of other coastal shark species, with less documented but similar movement abilities and whose conservation status is of even greater concern74.The implementation of MPAs for the protection of marine ecosystems is usually based on either conservation or optimization of fishery yields75 brings new hope for marine ecosystem conservation, and especially for mobile species like reef sharks. Such hope has yet to be moderated as (i) large Indo-Pacific MPAs are concentrated in one region, the Coral Sea, and Australia is responsible for establishing a large majority of them, and (ii) the existence alone of such MPAs does not necessarily warranty conservation efficiency. Other factors, such as a lack of monitoring and enforcement, poor governance or lack of local support, can indeed compromise MPAs efficiency78.Expanding our conclusions to the Indo-Pacific region revealed that very few MPAs were large enough to protect a mobile reef shark species such as the grey reef shark. Furthermore, such very large MPAs were all implemented recently, from the years 2000’s. This Indo-Pacific trend, notably impelled by the Convention on Biological Diversity that set a target of 10% of global marine areas to be protected before 2020Supplementary Information.


The highly conserved trans-acting response element (TAR) present in the RNA genome of human immunodeficiency virus 1 (HIV-1) is a stably folded hairpin structure involved in viral replication. However, TAR is also sensed by viral sensors, leading to antiviral immunity. While high variation in the TAR RNA structure renders the virus replication-incompetent, effects on viral sensing remain unclear. Here, we investigated the role of TAR RNA structure and stability on viral sensing. TAR mutants with deletions in the TAR hairpin that enhanced thermodynamic stability increased antiviral responses. Strikingly, TAR mutants with lower stability due to destabilization of the TAR hairpin also increased antiviral responses without affecting pro-inflammatory responses. Moreover, mutations that affected the TAR RNA sequence also enhanced specific antiviral responses. Our data suggest that mutations in TAR of replication-incompetent viruses can still induce immune responses via viral sensors, hereby underscoring the robustness of HIV-1 RNA sensing mechanisms. In HIV provirus ,7,8,9. Tprovirus ,4,10,11.provirus ,13,14,15Upon transcription initiation, RNA-polymerase-II (RNAP II)-mediated transcription along the HIV-1 proviral DNA genome is halted after 58 nts, hereby generating prematurely aborted HIV-1 RNA transcripts that can adopt the complete TAR hairpin structure (abortive HIV-1 RNA) . These sIFNB and interferon-stimulated gene (ISG) transcription, a full antiviral type I interferon (IFN) response capable of limiting HIV-1 replication in vitro [Sensing of abortive HIV-1 RNA triggers various responses via either RNA sensor DDX3 ,13 or PKin vitro . Little Here, we introduced mutations within the aborted HIV-1 TAR RNA to study the effect of its thermodynamic stability and RNA structure on viral sensing by PRRs. Notably, we observed that mutations that increased or decreased thermodynamic stability of the TAR hairpin enhanced viral sensing and antiviral immune responses. These data suggest that viral sensors are able to sense a variety of HIV-1 TAR RNA variants. Moreover, changes in the TAR RNA sequence also enhanced viral sensing. Thus, while virus replication is highly dependent on the integrity and stability of HIV-1 TAR, our study suggests that viral sensors are able to sense many different variations in TAR, underscoring the robustness of the sensing mechanisms for HIV-1 TAR RNA.trans-activation, and described that this prevents viral replication [Here, we examined the effect of variation in the structure and thermodynamic stability of the TAR RNA hairpin on the induction of antiviral immunity. First, the sequence variation in the TAR motif in natural virus isolates of HIV-1 subtype B was examined. The TAR region of >1600 sequences was assessed, and a consensus sequence was derived A. Minimalication ,24,25. HWe developed synthetic abortive HIV-1 RNA based on the consensus sequence ,13 TAR A and desIn addition, we designed mutants in which the hairpin was destabilized. We introduced four clustered mutations on the 5′ (TAR mutant Substitution AUCA-9) or 3′ side (TAR mutant Substitution UGGU-47). These mutations prevented base pairing, leading to a profound destabilization of the lower TAR stem, which decreased TAR stability to delta G −19.1 kcal/mol and −20.5 kcal/mol, respectively B. Next, IFNB transcription was assessed every 2 h (h) after stimulation. Similar to what was previously reported, TAR wt induced strong IFNB transcription, which peaked around 10 h after stimulation [IFNB transcription at higher levels than observed for TAR wt, starting at 4 h after stimulation and persisting at peak level  and ISG15 transcription; however, these responses were similar to the TAR wt-induced responses and were not further enhanced  were treated with TAR wt or mutants with higher stability, and mulation   and IRF7. TAR wt induced IRF3 transcription that peaked at both 4 h and 10 h after stimulation  induces NLRP3 inflammasome activation and the secretion of IL-1β in the supernatant of LPS-primed DCs . For theTAR RNA consists of a 58 nt-long, stably formed hairpin structure present at the 5′ extremity of all HIV-1 transcripts and plays a crucial role in HIV-1 transcription and viral gene expression ,3,10. TALimited or no variation occurs in the highly conserved three-nt-long bulge element on the 5′ side or the six-nt-long apical loop structure, which is likely due to the crucial role of these regions in Tat-mediated transcription and thus viral replication ,7,8,9. IOur data suggest that the sequence of the TAR RNA mutant Del-C4-A16-UCU-22, possibly in combination with high thermodynamic stability, is favored by PRRs to induce strong antiviral responses compared to the sequence of TAR mutant Ins-G4-U16-AGA-22, while TAR mutant Del-UCU-22 only showed a trend towards enhanced antiviral responses. These data indicate that removal of the UCU sequence at nt position 22 is partially, but not solely, responsible for enhanced type I IFN. Moreover, the distance between TAR and 5′cap might also be a factor leading to enhanced sensing. DDX3 recognizes TAR RNA by the presence of the 5′cap in close proximity to the complex secondary structure, after which type I IFN responses are induced ,17. SotoIRF7, an ISG that is dependent on IFN-dependent JAK/STAT signaling and subsequent activation of ISGF3, and is responsible for the induction of different IFNα species [Strikingly, destabilization of the TAR hairpin enhanced antiviral immune responses, suggesting that this is important for viral sensing. It is possible that upon destabilization, more DDX3 molecules can bind to the lower TAR stem or that other parts of the TAR stem become available for other viral sensors, which may enhance antiviral responses. Interestingly, we observed that the Substitutions 9 + 47 mutant increased transcription of  species . TherefoRecently, we have shown that sensing of abortive HIV-1 RNA by PKR triggers NLRP3 inflammasome activation and subsequent processing of pro-IL-1β . NotablyTo conclude, while the mutations we introduced here in TAR RNA likely interfere with the Tat-TAR interactions and negatively affect or even completely abort HIV-1 replication ,31, thishttps://weblogo.berkeley.edu, accessed on 9 July 2021) to assess sequence conservation in silico. Sequences were used to obtain a consensus sequence based on sequence prevalence . The 1662 retrieved sequences were aligned and visualized using Weblogo  [Seven TAR RNA mutants were designed containing different mutations in the hairpin structure. TAR wild-type (wt) was derived from the consensus sequence A and wasTX, USA) ,13. Qual2 for 6 days. DCs were seeded (1 × 105 cells/well) in a 96-well round bottom plate  and stimulated with 1 nM of the different TAR mutants complexed in transfection reagent lyovec . Stimulation of DCs with lipopolysaccharide (LPS) Salmonella enterica serotype typhimurium  were performed in the presence or absence of PKR inhibitor C16  or the dimethylsulfoxide (DMSO) control for 2 h (h), or in the presence of recombinant adenosine triphosphate  for the final 4 h of the stimulation.This study was performed using human buffy coats  according to the Amsterdam University Medical Centers, location AMC, Medical Ethics Committee guidelines, and the Declaration of Helsinki. Buffy coats were processed as previously described . In brieGAPDH was used to normalize the expression levels of target genes: Nt = 2Ct(GAPDH)−Ct(target). Relative expression levels were calculated when Nt in TAR wt-treated cells was set at 1.mRNA was isolated using lysis buffer from an mRNA capture kit , reversely transcribed to cDNA using a reverse transcriptase kit  and PCR amplification was performed with primer sets  that were developed with Primer Express 2.0  secretion levels in the DC supernatant were quantified 24 h after stimulation using Enzyme-linked Immunosorbent assay (ELISA) according to manufacturer’s instructions . OD450 nm values were measured using BioTek Synergy HT.t-test for paired observations using GraphPad version 8. Statistical significance was set at p < 0.05.Statistical analysis was performed using Student’s


Preferences for foods high in sugar and fat are near universal and major contributors to obesity. Additionally, human food choices are sophisticated and individualistic: we choose by evaluating a food’s nutrients and sensory features and trading them against quantity and cost. To understand the mechanisms behind human-like food choices, we developed an experimental paradigm in which monkeys chose nutrient rewards offered in varying quantities. Resembling human suboptimal eating, the monkeys’ fat and sugar preferences shifted their nutrient balance away from dietary reference points. Formally defined economic values for specific nutrients and food textures explained the monkeys’ preferences and individual differences. Our findings show how human-like preferences derive from biologically critical food components and open up investigations of underlying neural mechanisms. Value is a foundational concept in reinforcement learning and economic choice theory. In these frameworks, individuals choose by assigning values to objects and learn by updating values with experience. These theories have been instrumental for revealing influences of probability, risk, and delay on choices. However, they do not explain how values are shaped by intrinsic properties of the choice objects themselves. Here, we investigated how economic value derives from the biologically critical components of foods: their nutrients and sensory qualities. When monkeys chose nutrient-defined liquids, they consistently preferred fat and sugar to low-nutrient alternatives. Rather than maximizing energy indiscriminately, they seemed to assign subjective values to specific nutrients, flexibly trading them against offered reward amounts. Nutrient–value functions accurately modeled these preferences, predicted choices across contexts, and accounted for individual differences. The monkeys’ preferences shifted their daily nutrient balance away from dietary reference points, contrary to ecological foraging models but resembling human suboptimal eating in free-choice situations. To identify the sensory basis of nutrient values, we developed engineering tools that measured food textures on biological surfaces, mimicking oral conditions. Subjective valuations of two key texture parameters—viscosity and sliding friction—explained the monkeys’ fat preferences, suggesting a texture-sensing mechanism for nutrient values. Extended reinforcement learning and choice models identified candidate neuronal mechanisms for nutrient-sensitive decision-making. These findings indicate that nutrients and food textures constitute critical reward components that shape economic values. Our nutrient-choice paradigm represents a promising tool for studying food–reward mechanisms in primates to better understand human-like eating behavior and obesity. The concept of “value” plays a fundamental role in behavioral theories that formalize learning and decision-making. Economic choice theory examines whether individuals behave as if they assigned subjective values to goods, which are inferred from observable choices , 2. In rMacaca mulatta) for nutrient-defined liquid rewards.The reward value of food is commonly thought to derive from its nutrients and sensory properties: sugar and fat make foods attractive because of their sweet taste and rich mouthfeel. Sensory scientists and food engineers seek to uncover rules that link food composition to palatability –10. SimiLike humans, macaques are experts in scrutinizing rewards for sophisticated, value-guided decision-making , 12–15. 12Previous studies in macaques uncovered key reward functions and their neuronal implementations, including the assignment of values to choice options , 18–25, 18First, we tested whether macaques’ choices were sensitive to the nutrient composition of rewards, consistent with the assignment of subjective values. In previous studies, macaques showed subjective trade-offs between flavored liquid rewards , 13. We Second, to identify a physical, sensory basis for nutrient preferences, we developed engineering tools to measure nutrient-dependent food textures on biological surfaces that mimicked oral conditions. Although sugar is directly sensed by taste receptors , the mec38Third, we compared the monkeys’ choices to ecologically relevant dietary reference points. In optimal foraging theory , animals42Finally, based on our behavioral data, we explored in computational simulations how theories of reinforcement learning and economic choice can be extended by a nutrient–value function. Together with recently proposed homeostatic reinforcement learning , nutrienSI Appendix). Each testing day, two liquids were pseudorandomly selected from a 2 × 2 factorial design with fat and sugar level as factors : the low-fat low-sugar liquid (LFLS), the high-fat low-sugar liquid (HFLS), the low-fat high-sugar liquid (LFHS), and the high-fat high-sugar liquid (HFHS). The LFLS liquid was lowest in energy content; the HFLS and LFHS liquids were matched in energy content  at an intermediate level; and the HFHS liquid was highest in energy content. Liquid types were cued by conditioned visual stimuli; varying reward amounts were cued by pretrained magnitude bars. This design allowed us to test how fat, sugar, and their interactions influenced the monkeys’ choices. Importantly, the rewards were matched in juice flavor (peach or blackcurrant), temperature, and other ingredients . Systematic choice biases could therefore only be attributed to manipulated nutrient content and nutrient-related sensory qualities.Three rhesus monkeys performed in a binary choice task in which they repeatedly chose between varying amounts of dairy-based liquid rewards that differed in nutrient content  and higher repeated choice counts . To quantify the monkey’s willingness to trade reward magnitudes for fat and sugar , we calculated the percentage intake of nutrients and liquid amounts compared to the total offers in each session. The monkey gave up 8% of offered reward magnitudes to obtain an additional 33% of fat (compared to an agent who maximized reward magnitudes) and gave up 26% of offered magnitudes to obtain an additional 45% of sugar. These trade-offs suggested that the monkey assigned subjective, economic values to fat and sugar for making choices.In the two sessions shown in Inset).We constructed “nutrient–value functions” that related the ratio of offered liquid magnitudes to the monkey’s choice frequency to quantify subjective nutrient values F. From fThus, the monkey’s preferences systematically reflected trade-offs between reward amounts and nutrient compositions, consistent with the assignment of economic values to choice options.SI Appendix, Fig. S1). Nutrient–value functions showed that all three animals gave up more low-nutrient liquid in exchange for fat and sugar, with particularly strong trade-offs in monkeys V and Ya (SI Appendix). The resulting value differences in units of the low-nutrient reference predicted the animals’ choices well in all three monkeys, as indicated by orderly psychometric curves and model-fit statistics .We found clear nutrient preferences in aggregated choice data across testing days and monkeys, despite individual differences. Choice frequencies, choice repetitions, and explicit nutrient–magnitude trade-offs indicated that the monkeys preferred the high-fat and high-sugar liquids to the low-nutrient reference  identified significant positive coefficients for fat and sugar in each animal . By quantifying the subjective weight of specific nutrients on choices, the regression coefficients modeled each animal’s nutrient–value function. Regression coefficients for fat and sugar were stable in all animals .We used mixed-effects multinomial logistic regression to estimate nutrient–value functions from the animals’ trial-by-trial choices across all stimuli while controlling for reward magnitudes, left–right biases, and random effects across testing sessions. Our main regression ; the effect of sugar in animal V was captured by a significant fat–sugar interaction, likely indicating subjective flavor–nutrient interaction. To quantify cross-flavor generalization of nutrient preferences, we derived nutrient–value functions from logistic regressions for one flavor to predict choices for the other flavor. Model-fit statistics  confirmed accurate cross-flavor predictions for two animals  and lower but above-chance accuracy for animal V . Using pairwise PDIs, we constructed a triangle whose side-lengths visualized discrepancies between animals’ nutrient preferences  based on averaged log-likelihood ratios of mutual cross-animal predictions . We also included diluted cream as a high-fat, low-sugar stimulus. Choice frequencies confirmed the preference rankings observed in our main task, and regressions confirmed significant sugar and fat influences on choices and individual differences .We replicated and extended these findings in an additional experiment in which monkeys chose directly between all nutrient rewards, offered randomly in the same session at constant magnitudes  . B. B39). Bppendix) . To mitiSI Appendix, Fig. S6). To link these texture measurements to texture perceptions, we performed a psychophysical experiment in which human participants (n = 23) sampled the liquids used in the monkey experiments and rated subjective perceptions of the mouthfeel produced by the liquids (SI Appendix). We found that human psychophysical ratings of the thickness and oiliness of liquid rewards were positively related to stimulus viscosity and negatively related to CSF , suggesting that both texture properties contributed to texture sensations. Notably, oiliness was more strongly related to CSF than to viscosity .In validation tests, the CSF measurements reliably reflected increases in fat content in a series of fatty liquids B. We nexThus, viscosity and sliding friction tracked the fat content of liquid nutrient rewards and produced distinct oral texture perceptions in humans. High-fat liquids were more viscous and slippery, which humans perceived as thick and oily mouthfeel, respectively.To test whether oral texture parameters mediated the effect of nutrients on choices, we used structural equation modeling (SEM) based on a series of logistic regressions. We hypothesized that sugar was mainly sensed from sweetness  and exerRegression-derived path coefficients within this framework supported our hypothesis E and F. SI Appendix, Fig. S7). As in the main data set, CSF had a significant negative effect on choice in two animals; different from the main data set, viscosity had a significant positive effect on choice in all animals, likely due to the addition of cream as a preferred high-viscosity liquid.We replicated and extended these findings in follow-up experiments involving choices between all rewards in the same session and an additional cream stimulus for wider nutrient and texture variation. In this independent data set, sugar again had a significant positive and direct effect on choice and the fat effect was accounted for by texture parameters  . We examSI Appendix, Fig. S8).We first focused on sessions in which monkeys chose between isocaloric high-fat and high-sugar rewards. Cumulative choice plots showed the animals’ dynamic, trial-by-trial choice trajectories and aggregated choice frequencies, which allowed comparisons between choice strategies based on nutrient preferences or energy maximization A. SessioSI Appendix) and compared the energy model to the nutrient model with independent fat and sugar regressors. The nutrient model outperformed the energy model in explaining choices in all three monkeys  is crucial for health benefits and a choice strategy adopted by various animal species –44. TherIn the mixer triangle, the monkeys’ aggregate choices occupied distinct and stable regions depending on the offered rewards B. SpecifTo appreciate the physiological implications of the observed nutrient balances, we compared them with two reference points, 1) a standard recommended diet composition for adult macaques, consisting of a low-fat, high-protein, and intermediate-carbohydrate diet , and 2) Thus, the monkeys’ preferences for high-sugar and high-fat rewards resulted in offer-dependent nutrient balances that deviated from dietary reference points.Canonical behavioral frameworks such as reinforcement learning and economic choice theory do not specify how rewards with particular properties can differentially affect learning and choice. Based on the above findings, we examined whether a nutrient–value function could meaningfully extend such choice models to explain nutrient-sensitive choices.SI Appendix, Fig. S9). By updating values solely based on past reward frequency, the standard RL model learned equally for both rewards regardless of nutrient composition. By contrast, the nutrient-sensitive model assigned higher value to high-nutrient reward outcomes, governed by a nutrient-sensitivity parameter . Thus, sensitivity to nutrient composition optimized learning performance when an agent’s value function prioritized specific nutrients.Using simulations, we compared the performances of a Rescorla–Wagner model and an extended reinforcement learning model with a nutrient–value function A. In a barameter B. AccordSI Appendix, Fig. S10), although constructing complete nutrient–value functions would require more exhaustive tests.In economic revealed-preference theory, indifference curves derived from choices connect multidimensional goods that differ in composition  but have the same level of satisfaction (utility) , 12. MulThese results suggest that incorporating nutrient-sensitivity in reinforcement learning and economic choice models can extend the predictive and explanatory validity of these models, especially when learning and choice depend on intrinsic reward components. Our data and simulations suggested candidate neuronal mechanisms for nutrient-sensitive decision-making E–G, on wSI Appendix, Table S3). Although object properties alone cannot fully explain reward functions and must be combined with behavioral assessment , other food properties (which we controlled), or task variables . Accordingly, the fat and sugar preferences reported here may differ from those of wild macaques and resemble more closely eating phenotypes observed in human free-choice scenarios. Under conditions of scarcity, macaques would likely adjust their choice strategy to counter deficit states. Thus, we expect nutrient–value functions to be state dependent.Previous studies in humans documented hedonic liking for sugar, fat, and their interactions  but did SI Appendix, Fig. S4), and ecological observations of nutrient-balancing  participated in the present experiments: monkey Ya , monkey V , and monkey Ym . The animals had free access to their standard diet before and after the experiments and received their main liquid intake in the laboratory (SI Appendix). The animals were on a standard diet for laboratory macaques. All animal procedures conformed to US NIH Guidelines and were approved by the Home Office of the United Kingdom.Three adult male rhesus macaques .We used commercial skimmed milk and whole milk  as baseline low-fat and high-fat liquids and flavored the liquids with fruit juice to increase palatability (SI Appendix). To reflect realistic lubrication conditions in the oral cavity, we devised a custom-designed tribometer using pig tongues as biological contacting surfaces (Right).Rheology was performed using a Rheometric Scientific ARES controlled strain rheometer (TA Instruments). We measured the CSF at the Department of Engineering, University of Cambridge  to model the animals’ trial-by-trial choices.Unless otherwise specified, all data were analyzed separately for each animal and different juice flavors (peach and blackcurrant) using custom code and in-built functions in MATLAB R2017b. We adopted mixed-effects multinomial logistic regression analysis (We used the right-angled mixer triangle developed by Raubenheimer which implements a proportion-based variant of the Geometric Framework for Nutrition , 49 in wSupplementary File


The human transcriptome comprises a complex network of coding and non-coding RNAs implicated in a myriad of biological functions. Non-coding RNAs exhibit highly organized spatial and temporal expression patterns and are emerging as critical regulators of differentiation, homeostasis, and pathological states, including in the cardiovascular system. This review defines the current knowledge gaps, unmet methodological needs, and describes the challenges in dissecting and understanding the role and regulation of the non-coding transcriptome in cardiovascular disease. These challenges include poor annotation of the non-coding genome, determination of the cellular distribution of transcripts, assessment of the role of RNA processing and identification of cell-type specific changes in cardiovascular physiology and disease. We highlight similarities and differences in the hurdles associated with the analysis of the non-coding and protein-coding transcriptomes. In addition, we discuss how the lack of consensus and absence of standardized methods affect reproducibility of data. These shortcomings should be defeated in order to make significant scientific progress and foster the development of clinically applicable non-coding RNA-based therapeutic strategies to lessen the burden of cardiovascular disease. The completion of the human genome project in 2003—an international joint public and private effort—is a date that will go down in history.We now know that the human transcriptome is much more complex than previously thought. The advent of deep sequencing tools of the last 15 years has revealed a complex network of at least 10,000 long non-coding RNAs, encoded in a myriad of genomic contexts.Non-coding RNAs are functional RNA molecules that lack protein-coding potential. Only a subset have so far been characterized, and many exhibit high spatial and temporal expression patterns and are emerging as key regulators of differentiation, development, homeostasis, and disease pathology, including in cardiovascular disease (CVD).Delineating the transcriptome changes in cardiac cell types and defining their regulation in disease remodelling could not only enable us to further understand the cellular and molecular processes underlying pathology, but also provides the opportunity to select new, specific and more effective therapeutic targets to treat CVD.This review describes the challenges in dissecting and understanding transcriptome remodelling in CVD, focusing on non-coding genes. We will then discuss strategies being implemented to overcome these confounding factors. Finally, we review hurdles yet to overcome to improve reproducibility of data, convincingly delineate the cellular and molecular processes underlying cardiovascular pathology and catalyse translational impact.MicroRNAs (miRNAs) are 21- to 23-nt-long short, single-stranded non-coding RNAs involved in post-transcriptional regulation of gene expression through binding to complementary sites predominantly in the 3’ untranslated regions (UTR) of pre-messenger RNA .MiRNA therapy has gained a lot of attention due to its specific targetability using chemically modified antisense technology, enabled by the inherent complementary base-pairing properties of nucleic acids. Whilst a handful of antisense therapies have been approved to date by the US Food and Drug Administration (FDA) targeting messenger RNAs, no miRNA drugs have thus far made it onto the market. Contributing to the low rate of translation to the clinic is a lack of consensus methodologies and experimental approaches. Pre-clinical work in large animal models has preceded clinical trials, which are currently ongoing.Another facet of miRNA research in biomedical science is as circulating predictive, diagnostic, and prognostic biomarkers of disease. Blood, plasma, serum, and other biological fluids such as urine and tear drops have been found to be rich in RNA, either through release into the circulation from necrotic or apoptotic cells or having been actively secreted in microvesicles such as exosomes.Long non-coding RNAs (lncRNAs) are defined as transcribed non-protein-coding RNA molecules longer than 200 nt in length. LncRNA genes can overlap protein-coding genes, be located in an antisense orientation to protein-coding genes, intronic or intergenic .Among lncRNAs, enhancer RNAs (eRNAs) describe a family of non-coding transcripts generated from enhancer regions of annotated genes that have a cis-regulatory role in transcription. Enhancer RNAs have been identified as regulators in cardiomyocyte(CM) differentiation development and homeostasis as well as being altered in response to pathological stimuli.A further recently discovered class of non-coding RNAs are the circular RNAs (circRNAs). CircRNAs are single-stranded and created by back splicing of 3’-5’ linear coding or non-coding RNAs, forming covalently closed loops.,CircRNAs are being examined not only for their intracellular activity but also as stable and specific circulating biomarkers reflecting cardiac dysfunction and pathology. The stability of circRNAs in the circulation exceed that of linear RNAs and their diagnostic value for CVD has started to be evaluated.We are now aware that a significant number of lncRNAs and unannotated transcripts originally defined as purely non-coding have short, translated open reading frames (sORFs).Whilst some aspects of CVD can be modelled in animals, due to our lack of understanding along with practicalities, biological differences, and multi-factorial aetiologies, human CVD can never be perfectly emulated in pre-clinical models. Thus, to confirm the translational potential of findings in cellular and animal studies, human specimen can be used to show conservation of transcriptome analyses.Human specimens used in CVD research include, but are not limited to, liquid biopsies such blood, plasma, serum, buffy coat, isolated blood cells, and solid tissues, such as cardiac biopsies, explanted cardiac tissue from heart transplant patients and hearts extracted from cadavers of victims of sudden death . Guidelines for standardized sample collection and storage are not well established, which leads to variability in the quality of RNA available.,Isolation of good quality, intact RNA is required for techniques used for RNA and gene expression analysis including RTqPCR, RNA-sequencing (RNA-seq) and northern blotting. RNA integrity can be assessed qualitatively by running on a denaturing gel  and stained with a nucleic acid stain such as ethidium bromide. Intact RNA will give sharp, clean 28S and 18S ribosomal RNA (rRNA) bands, with the 28S approximately twice as intense as the 18S band. Degraded RNA will lack these sharp rRNA bands with a 2:1 ratio and have a smear-like appearance. A faint smear may appear between 1–2 kb, containing other RNAs such as mRNAs and lncRNAs. With the knowledge that at least 80% of the total cellular RNA is rRNA, RNA integrity can additionally be assessed with the knowledge of the mass of total RNA loaded and the rRNA bands compared against an RNA ladder of known marker size and mass. Elementary variations of this method have been devised to avoid the use of hazardous denaturing substances and improve resolution.The gold standard for assessing RNA integrity is the 2100 Bioanalyzer (Agilent). This device provides an automated electrophoresis strategy using microfluidics technology for RNA integrity analysis based on the relative rRNA species intensity. A range of microfluidics chips are available for different concentrations of RNA sample, with as little as 50 pg required by the Pico RNA analysis products. The 2100 Bioanalyzer calculates an RNA Integrity Number (RIN), which is an algorithm for robust and reliable assignment of quality values to RNA samples.Of note, these methods to assess RNA integrity are based on ribosomal RNAs. This is not suitable for assessing the quality of nuclear RNA or polyA RNA preparations, which are depleted of rRNA. Some semi-quantitative methodologies have been suggested for assessment of polyA RNA samples.There is a lack of consensus regarding the minimal RIN value that should be used for accurate execution of RNA analysis. Moreover, different techniques for RNA analysis may be able to withstand different RNA integrity thresholds to be accurate and reproducible. For example, cDNA library synthesis requires initial RNA degradation into fragments either through heating or enzymatic digestion. Many researchers and next-generation sequencing (NGS) technology companies and facilities arbitrarily state a minimum RIN value of 7 or 8 for deep RNA-sequencing. In the context of clinical samples in translational cardiovascular research, this minimum RIN is often unrealistic, with the example of fluid biopsies remaining on the bench at room temperature while the cardiologist tends to the patient.Table 1 provides an overview of confounding factors and pre-analytical variables affecting RNA integrity and outcomes of gene expression analysis.In the context of transcriptome analysis, a number of confounding factors can affect the outcome of research findings. In particular, the quality and integrity of RNA, determined by a number of pre-analytical variables along with sampling and storage methods.The post-mortem interval (PMI) is a primary confounding factor affecting quality and integrity of subsequently isolated biological material, such as DNA and RNA.Firstly, at ambient temperatures, RNA is highly labile and RNase enzymes remain catalytically active, naturally causing a decrease in RNA integrity with increased PMI. Evidence also suggests that not all RNAs are created equal, some being more susceptible to degradation.Secondly, one could envisage stress-associated gene programmes, such as those induced by hypoxia, to be activated in the early PMI period. These two main influences can greatly affect the outcome of transcriptome analysis in CVD.rigor mortis. What’s more, heart tissue collected during procedures involved in treatment and investigation of cardiovascular disease, such as endomyocardial biopsies, valve replacements or heart transplants, is handled very differently, generally placed into cardioplegic solution followed by appropriate and rapid storage.For extraction of tissues from sudden-death victims, the exact PMI is not always easy to determine and will inevitably not be consistent between samples. This is a common means by which tissues from ‘healthy/control’ individuals are collected. PMI in this case is usually determined by a pathologist based on physical observations of the corpse such as body temperature and Significantly, an analysis of GTEx (Genotype-Tissue Expression project) tissues and expression data of different human tissues with PMIs ranging from 1 to 27 hours and good quality RNA-seq data is available. A systematic analysis showed that cardiac and skeletal muscle displayed the greatest influence of PMI on the transcriptome, with over 850 genes significantly differentially expressed depending on PMI.Comparing the transcriptome profiles between diseased and healthy heart samples, the vastly different and heterogeneous PMIs and handling protocols will influence the findings. In addition, there are no published guidelines set by standardisation bodies or networks of experts presenting consensus procedures in sample attainment, handling, or storage. A first step to improve reproducibility should be a detailed description of sample harvesting and handling in all scientific publications, information that is often missing.,The effect of the pre-processing time, as well as RNA integrity on the global depth of RNA-seq and on the outcome of gene expression analysis, was evaluated in only two studies of human peripheral blood mononuclear cells and human tissue .The European Commission has acknowledged a need for international unity in governance and coordination of clinical biobanks.In conclusion, careful and correct collection, storage and sharing of information on pre-clinical variables as well as RNA integrity, evaluated by the gold standard RIN value, will enable consideration of these elements in translational cardiovascular research. These factors can then be incorporated as covariables in analysis platforms to identify independent gene expression changes.,Figure 1 depicts the composition of the adult heart and how different cell types are typically altered in response to chronic pathological stimuli.The heart is a highly heterogeneous organ, composed of at least six major cell types. The relative composition of the mammalian heart is a debated area, but it is generally accepted that CMs, cardiac fibroblasts (CFs), and endothelial cells (ECs) are the dominant cell types.Alike, the vasculature is composed of smooth muscle cells, ECs, pericytes as well as a significant layer of connective tissue and elastic fibres. Remodelling of the vessel bed composition, cellular biology, morphology, and structure occurs in injury and atherosclerosis.Considering all the aforementioned factors and substantial remodelling of cardiac cellular composition in disease, transcriptomic data from whole heart tissue are not representative for a true comparison of changes within a particular cell type and make translating bulk molecular changes to biological function difficult. The resulting data sets represent only composite changes across the constituent cell types for that sample, often diluting changes that are of relevance in cellular and functional remodelling.A number of established protocols exist for isolation of CMs, CFs, ECs and immune cells from fresh heart tissue from animals and humans. These methods are centred around enzymatic digestion, often involving specialist equipment such as Langendorff apparatus for lengthy periods of aortic and coronary perfusion. Achieving high quality, high purity and consistent cell preparations proves variable between protocols, different laboratories as well as between species, samples and experimental conditions.One further significant caveat to isolation and separation of different cell types by enzymatic digestion is that fresh tissue is required, which needs to be maintained in cardioplegic solution since the point of extraction. Not only in some cases is access to fresh tissue impractical, such as in the case of biobanked human material, but the time of the preparations undertaken at ambient temperatures and conditions are conducive to DNA synthesis, transcription, RNA degradation as well as epigenetic modifier activity during the preparation time.Furthermore, as previously indicated, anti-coagulants such as heparin administered during extraction of the heart as well as anti-thrombotic medication in patients, have been shown to interfere with cDNA synthesis reactions used in RT-qPCR or RNA-seq library preparations.ex vivo.,Variations on these methods for fresh CM and CF isolation have been developed with the aim of optimizing purity, cellular integrity, and minimizing the need for anti-coagulants and complex apparatus, including through direct needle perfusion of the extracted heart All confounding factors and circumstances considered, further approaches have been formulated to obtain cell type-specific gene expression or epigenomic information. Whilst intact living cells can only be isolated from fresh cardiac tissue, nuclei can be extracted from frozen tissue. Fluorescence immunolabelling of cell-type-specific nuclear antigens followed by flow cytometry enables collection of cell-type-specific DNA and nuclear RNA. Examples include the use of pericentriolar material-1 (PCM-1), nuclear-retained phospholamban, or troponin T for CM nuclear isolation.,It should be noted that nuclear transcriptome data give a different readout to cellular or bulk tissue RNA analysis. Firstly, 90% of the total RNA in the cell is in the cytoplasm as mature processed RNA species. The nucleus is home to pre-processed RNA such as pre-mRNA, pri- and pre-miRNAs, and nascent lncRNA transcripts. In addition, nuclear-localized RNA species, such as lncRNAs, will be overly represented in the nucleus. Nuclear content gives a readout of more of the nascent transcription rates whereas cellular RNA is reflective of additional post-transcriptional regulation such as miRNA mechanisms and mRNA stability.One further approach to deducing the relative contribution of cell types in big transcriptomic data from bulk tissue or a mixed cell population is through bioinformatic deconvolution using established knowledge drawn from gene expression profiles of the individual composing cell types. One such example of where this strategy is employed very effectively is with whole blood specimen, where gene expression profiles of blood cell types—predominantly white blood cells—and sub-types are well described.Major advantages of this strategy include minimization of confounding factors involved in tissue separation and specific cell or nuclear isolation and sequencing, with the resulting data representing the relative cell population and tissue transcriptome close to that in vivo, provided appropriate extraction and storage of the biospecimen.,That said, published examples of where bioinformatical deconvolution in this manner has been successfully employed in cardiovascular tissues are lacking. One probable reason for this is that transcriptional dysregulation is commonly seen in the context of disease, with cells of the cardiovascular system ectopically expressing genes atypical of their differentiated cell state. For example, CMs have been shown to express extracellular matrix protein in pro-fibrotic conditions and as fibroblasts are activated towards a myofibroblast state, express contractile fibres.The advent of scRNA-seq technology provides an unparalleled opportunity for high-resolution profiling of the global transcriptional signature of individual cells in models of disease and human tissue. Since the seminal report of transcriptome sequencing at the single-cell level of a mouse blastomere a decade ago, there has been an early exponential rise in studies applying this technology in the cardiovascular system.Analyses of bulk tissues produce signals that are an average across several cell-types in the tissue and so are unsuited to defining the role of individual cells. However, scRNA-seq allows the characterization of gene expression changes in individual cells and therefore an opportunity to deconvolve both cellular and disease-induced heterogeneities that serve biological functions.cytoskeleton-associated protein 4 (Ckap4) as a specific marker of activated CFs following injury. In another study, Forte and colleagues used scRNA-seq to characterize the dynamic transcriptional changes in non-CM cells at multiple timepoints following MI, identifying the occurrence of an early myofibroblast response as a predictor of cardiac rupture.,In the heart, several papers reporting single-cell transcriptional profiling of cardiac lineages from adult mice have emerged over the past two years. In a landmark study, single-cell transcriptomic was applied to map changing cell subpopulations in the healthy and injured mouse heart 3 days after ischaemia-reperfusion.,,,Outside the heart in the peripheral vascular setting, a number of studies have reported scRNA-seq of cells in blood vessels, for example in healthy and atherosclerotic mouse tissue.Gas5 and Sghrt, as regulators of gene expression networks associated with CM proliferation.See and colleagues applied single nuclear sequencing technology (snSeq) to identify both coding and non-coding RNA targets in CMs isolated from the left ventricles of healthy and failing hearts in mice and humans.et al. found widespread expression of Ckap4 across virtually all cardiac stromal populations in their analyses, dissimilar to the findings of Gladka and colleagues that Ckap4 was specific to injured and activated CFs.,Figure 2. Great care must be taken when interpreting individual datasets following stand-alone analysis, and recent studies have emphasized the benefit of aligning multiple independent datasets using integrated bioinformatics pipelines, including from different species, as a means to identifying more robust and conserved targets. Archiving of raw sequencing datasets in open-access repositories may help to promote reproducibility and reduce potential issues caused by technical and biological discrepancies. An overview of the pros and cons of scRNA-seq technology is displayed in Figure 3.The application of single-cell technology has highlighted dynamic transcriptional plasticity and heterogeneity, including classification of previously unreported or rare cell subpopulations. However, discrepancies are already apparent. For example, Farbehi ,Although several statistical frameworks exist for differential gene expression (DE) analysis for the bulk RNA-seq, methods for scRNA-seq are just emerging.,The fast-paced evolution of snRNA-seq technology, and emerging applications such as snSeq of frozen tissues, will undoubtedly continue to provide critical new insights into cardiovascular homeostasis and disease processes that then inform critical proof-of-concept mechanistic studies. To complement the information obtainable by these techniques based on tissue disaggregation, another emerging application of next-generation sequencing is that of spatial transcriptomics. This method is an expansion on in situ hybridization into an unbiased high throughput method to analyse the presence and abundance of transcripts in a two- or three-dimensional context in complex tissues. One such example, Tomo-Seq , is able to obtain a genome-wide gene expression signature with high-spatial 2-D resolution in a mouse model of myocardial infarct (MI) spanning from the infarcted area to the remote area to identify new regulators of cardiac remodelling as well as in a zebrafish model of cryoinjury to identify mediators of cardiac regeneration.circSlc8a1-1, was found to act as a miR-133a competing endogenous sponge, and its inhibition in pre-clinical pressure-overloaded models attenuated the pathological cardiac hypertrophic response.Most mRNAs and lncRNAs generated in mammalian cells are composed of exons separated by introns. Certain introns are spliced-out constitutively, but many splicing signals are not used by all cells nor in all circumstances, leading to alternative splicing (AS). AS allows expansion of the genome to generate a diverse array of functional RNA transcripts from a single gene. Being estimated to occur in about 90% of human genes, AS greatly increases the coding potential of the genome.,Figure 4.It has been known for a long time that transcripts that are important for cardiac homeostasis and function can be aberrantly spliced in human heart disease, but the magnitude of mis-splicing events has only become evident in the past decade. Widespread use of microarrays and RNA-seq techniques has established a robust association of altered AS of pivotal cardiac genes, including many sarcomeric and ion channel genes, with cardiac hypertrophy, dilated cardiomyopathy (DCM), and HF.,cis-elements around the splicing site in both introns and exons, and trans-acting RNA-binding proteins (RBPs) that bind to specific cis-elements. RBPs are dynamically regulated with a variety of mechanisms and can promote or inhibit the splicing of a specific intron. A subset of RBPs regulating AS in the heart have been identified, including RBFOX-1 and -2, MBNL1 (muscleblind-like protein 1), CELF1 (CUGBP Elav-Like Family Member 1), and RBM-20 and -24 (RNA Binding Motif Protein 20 and 24).The first generation of transcriptomic analyses used exon-microarrays to identify splicing events, and, more recently, RNA-seq has revealed the pervasiveness of AS in an unbiased manner.RBM20 mutations cause an early-onset and clinically aggressive form of familial DCM, associated with aberrant inclusion of specific exons in the Titin (TTN) transcript.TTN is a very large multi-exon gene encoding many transcript variants regulated by still poorly understood AS events. Transcriptomic analysis of cardiac-specific knockout mice indicates that TTN is also one of the direct splicing targets of murine Rbm24.RBPs can engage in antagonistic actions, as observed for CELF1 and MBNL1. While CELF1 decreases during heart development, MBNL1 increases.In particular, in myotonic dystrophy type 1 (DM1), extensive AS changes result from the CUG expansions in the DMPK gene characterizing the disease.Another mechanism of AS regulation is made possible by splicing occurring co-transcriptionally for most genes, allowing the interaction between the splicing and the RNA-synthesis machinery.Many computational methods have been developed to analyse RNA-seq datasets at exon level. All these methods rely on reads spanning each exonic junction, to estimate an abundance ratio between the two spliced isoforms (exclusion and inclusion isoforms), followed by a statistical test to assess the significance of the observed difference in splicing. Although implemented with a variety of statistical frameworks, all available methods suffer from high uncertainty for the AS events sampled with low sequencing coverage. High sequencing depth is necessary to obtain a representative picture of the gene expression pattern at isoform level. The situation may be even more critical for circRNAs: these RNA species are devoid of a 3’-end and published datasets deriving from poly-A positive RNA cannot be used for their detection.de novo gene assembly for poorly annotated genomes and genes as well as valuation of copy number variants. This has been reviewed extensively previously.A further, so-called third-generation sequencing technology, which may be beneficial in the identification of novel transcript isoforms, is that of long-read sequencing. Such long-read sequencing technologies have been developed by, for example, Pacific Biosciences PacBio or single-molecule, real-time (SMRT) sequencing and Oxford Nanopore Technologies (ONT) and are able to sequence full-length transcripts in excess of 10 kb in length. The advantages of long-read sequencing over classic short read include lower error rates in mapping, and reduce amplification bias, easier accurate assembly of regions of the genome comprising repetitive sequences, and Although there has been significant progress in the characterisation of isoform-level transcriptomics and the discovery of the regulatory aspects of AS networks, demonstration of the functional consequences of the expression of different isoforms of individual genes is still scarce. Therefore, understanding the physio-pathological relevance of AS is one of the biggest challenges of CVD functional genomics.Unequal cellular distribution is characteristic of the majority of RNA species. Concentrations of RNAs at specific locations are highly associated with their functionality. A prime example is the transport of mRNAs from their site of production, the nucleus, to the cytoplasm, where they are actively translated.foci, each representing a functional step in the silencing pathway leading to mRNA degradation. On the other hand, the miRNA-loaded RISC can shuttle back into the nucleus, where it can exert additional regulatory function on transcription and splicing in the nucleoplasm or even in the chromatin. Finally, mature miRNAs are also found in mitochondria.MiRNA processing and maturation is an example of regulated changes in localisation. MiRNA genes are genomically encoded individually or as clusters, intergenically or intronically to protein-coding genes.There is a further emerging role for Argonaute proteins in the formation of RNA-induced transcriptional activation (RITA) complexes in association with small activating RNAs (saRNAs). RITAs translocate into the nucleus to enhance gene expression. Description and understanding of endogenous saRNAs in cardiovascular disease are yet to be unveiled, and there may be a potential to harness saRNA biology as a therapeutic strategy.in situ hybridisation identifies lncRNAs either in discrete nuclear foci or more homogeneously in the nucleoplasm. Foci of chromatin-bound lncRNAs reflect active lncRNAs transcription, lncRNAs that remain tethered to their own locus or accumulation at target loci, for instance through formation of RNA-DNA triplexes, a mechanism of lncRNA-mediated regulation of gene expression. Moreover, lncRNAs are observed in other compartments such as nuclear speckles and paraspeckles, organelles implicated in mRNA processing. In addition, lncRNAs can also be nuclear and cytoplasmic, or purely cytoplasmic.Molecular mechanisms controlling the correct targeting of lncRNAs to their ultimate site of action are intrinsic parts of their functionality. Nuclear-enriched lncRNAs are mainly involved in transcriptional and epigenetic regulation through cis- or trans-mechanisms, acting at their site of transcription or via travelling to remote locations in the genome respectively. A large number of lncRNAs are also exported to the cytoplasm. Visualisation of nuclear lncRNAs using RNA fluorescent ,Surprisingly, despite the fact that lncRNAs are not translated, many lncRNAs are found associated with ribosomes in polysome profiling experiments. As mentioned previously, this might reflect a role for lncRNAs in translation regulation or micropeptide production.Mechanistic studies support peripheral blood RNAs as regulators of CVD. Since peripheral blood is easily accessible, it is a promising source of biomarkers for personalized healthcare in areas with room for improved diagnosis and treatment . The first studies on circulating miRNAs in cardiovascular disease focused on their diagnostic potential. Plasma levels of miR-1a and miR-133a/b were among the first miRNAs identified to be upregulated in acute MI. Many subsequent studies postulated dynamic changes in peripheral blood miRNAs in different areas of CVD, systematically reviewed elsewhere.,,When considering studies with miRNAs in larger populations with independent validation, the largest body of evidence is available for miR-1, miR-133a/b, miR-208, and miR-499. These muscle- and cardiac-enriched miRNAs increased significantly in patients undergoing septal ablation for hypertrophy, suggesting a troponin-like biomarker potential.,LIPCAR and whole blood levels of QSOX1 and the circRNA MICRA have been identified and replicated as novel prognostic markers of subsequent left ventricular dysfunction in patients with MI, independent from classical prognostic markers including NT-proBNP.,,Besides miRNAs, the biomarker potential of mRNAs, lncRNAs, and circRNAs was investigated after a few landmark reports in stable coronary artery disease (CAD), acute MI, and HF.Figure 5). These challenges include the timing of blood sampling (e.g. lifestyle-related time-of-day fluctuations as well as stage of disease onset and progression), selecting the appropriate sample type, sample handling prior to storage, RNA isolation strategy, RNA quality and correct downstream RNA expression measurement with appropriate normalisation. RNA degradation is a serious limitation of transcriptomic studies in peripheral blood samples. In a clinical setting, liquid biospecimen cannot always be extracted and stored optimally to preserve the blood transcriptome. To overcome this challenge and eliminate other pre-analytical variables, blood collection tubes containing RNA stabilizers have been developed. Even with these precautions, RNA integrity and potential genomic DNA contamination should be assessed before starting downstream applications. For cell-free RNA (e.g. in plasma or exosomes), no dedicated approach to minimize RNA degradation has been described. Heparin administration to the patient or in the sample may also result in spurious RNA expression results.Nevertheless, none of these RNAs has as yet been assessed in a large interventional clinical study to tailor therapies or improve patient outcome. Several considerations may explain the challenge to translate experimental findings from transcriptomic studies back to the bedside  uses whole blood RNA for the diagnosis of stable coronary artery disease in non-diabetic patients, and AlloMap®  uses peripheral blood mononuclear cells for the detection of acute rejection in patients who underwent cardiac transplantation.,Only two RNA-based biomarkers in vitro diagnostic assays for cardiac conditions are commercially available. CorusAs previously discussed, the revolution in deeper and faster clinical genetic and transcriptomic phenotyping is enabling us to understand disease-associated changes in each patient. This allows the opportunity for personalizing therapeutic strategies.Transcriptome changes in the blood (cells or plasma) may help to better diagnose or determine the prognosis of our patients. Indeed, many clinical guidelines emphasize the unmet need for personalized medicine approaches. For instance, biomarker-guided cardiovascular therapy represents an interesting approach to identify the right patients, make accurate diagnostic decisions, and monitor efficacy. NcRNA signatures provide valuable molecular insight of patient phenotypes and could add to traditional markers and established clinical variables.et al. classified the clinical response to LVAD therapy based on NT-proBNP concentration at 3 months.Short circulating miRNAs show promise for making predictions of cardiovascular patients; plasma miRNA-1254 levels predicted changes in left ventricular (LV) volumes and LV ejection fraction at 6 months after ST elevation myocardial infarction (STEMI). The value of miR-1254 to inform tailored treatment selection and monitor ongoing efficacy deserves further investigation.Figure 6).These examples illustrate that personalized medicine approaches show promise in becoming a reality in the near future. The rise of new technologies such as global and single-cell sequencing, the use of artificial intelligence, and machine-learning concepts will lead to tremendous new discoveries and clinically useful applications and finally also to better and safer therapies (Recent breakthroughs in deep-sequencing technology have enabled us to delineate transcriptomes, genomes, and epigenomes from individual cells and cell types in complex heterogeneous organs and tissues of the CV system and unveil novel types, low or rarely expressed ncRNA transcripts.With the rapid speed and reduced costs of DNA and RNA-sequencing, we are now on the brink of being in a position to fully characterize each individual patient at the molecular level. To fully realize personalized medicine, we need to bridge interdisciplinary gaps to address the challenges posed by a deeper insight into the transcriptome regulation in the cardiovascular system, and to create unity and standardisation of methodologies: from sample preparation to bioinformatics analysis to interventional studies, for ultimately translating the findings into high-impact outcomes for public health.


New technologies have greatly shaped the scientific and medical landscape within the last years. The unprecedented expansion of data and information on RNA biology has led to the discovery of new RNA classes with unique functions and unexpected modifications. Today, the biggest challenge is to transfer the large number of findings in basic RNA biology into corresponding clinical RNA-based therapeutics. Lately, this research begins to yield positive outcomes. RNA drugs advance to the final phases of clinical trials or even receive FDA approval. Furthermore, the introduction of the RNA-guided gene-editing technology CRISPR and advances in the delivery of messenger RNAs have triggered a major progression in the field of RNA-therapeutics. Especially short interfering RNAs and antisense oligonucleotides are promising examples for novel categories of therapeutics. However, several issues need to be addressed including intracellular delivery, toxicity, and immune responses before utilizing RNAs in a clinical setting. In this review, we provide an overview on opportunities and challenges for clinical translation of RNA-based therapeutics, with an emphasis on advances in novel delivery technologies and abdominal aortic aneurysm disease where non-coding RNAs have been shown to play a crucial regulatory role. We believe that through the hereby provided review, we can give the interested readership a thoughtfully cured overview regarding the following topics:A broad review on the ever-growing spectrum of RNAs with a focus on non-coding RNAs .An introduction to a widespread range of translational methods to apply RNAs as therapeutics (including nanocarriers and extracellular vesicles).A comprehensive insight into challenges of translation in the field of RNAs.Instructive examples where the mentioned challenges have been accepted and first results have been reached (including atherosclerosis and aneurysm disease).Abdominal aortic aneurysm (AAA) is a common disease and defined as an abnormal focal dilation of the infrarenal aorta over 50% of the normal diameter . The norFactors increasing the risk for AAA development include smoking, male sex, and age >65 years  apoptosis, vascular inflammation, and extra cellular matrix (ECM) remodeling . Over thWhen discussing the clinical potential of novel RNA-based approaches, there are several therapeutic categories that need to be distinguished. Most obviously, RNAs can serve as direct therapeutic targets to modify disease . AdditioAs of 2020, 10 nucleic acid based drugs have gained FDA-approval, of which two are implicated in cardiovascular conditions. Mipomersen, a gapmeR targeting ApoB, has been approved for homozygous familial hypercholesterolemia. The agent aids to reduce cardiovascular disease risk by reducing low-density lipoprotein (LDL) cholesterol levels. Defibrotide is a polydisperse oligo-nucleotide purified from porcine intestinal mucosa that has been approved as a drug against severe hepatic veno-occlusive disease, where it acts in a complex sequence-independent mechanism on fibrosis, angiogenesis, apoptosis, and aggregation of thrombocytes , 16. OthDuring the last years of the RNA revolution, small non-coding RNA molecules that are only ~20–30 nucleotides long, have emerged as important regulators of the eukaryotic genome  and hairpin precursors) of both classes are processed via a Dicer-dependent mechanism that then enter the silencing machinery of the RNA-induced silencing complex (RISC) in their single-stranded form. The mRNAs of interest are targeted via base pairing of the small RNA component. This eventually results in sequence specific gene silencing . PerfectFire and Mello were the first to proof that experimental introduction of dsRNAs into a cell can be used to synthetically interfere with the function of an endogenous gene . Today, On the opposite site of the non-coding RNA spectrum, we find so called long non-coding RNAs (lncRNAs) . These cSome lncRNAs are pseudogenic, copies of coding genes harboring mutations rendering them non-coding . Many lnRegarding target sites, it is possible to distinguish between cis- and trans-acting lncRNAs. Cis-acting lncRNAs control the expression of genes in close neighborhood, whereas trans-acting lncRNAs function from a distance .Regarding lncRNA location, one can differentiate between cytoplasmatic lncRNAs that modulate translational control and nuclear lncRNAs that guide chromatin modifiers to specific genomic loci –35. The However, transcriptional activation has also been reported especially via activation of specific enhancer regions or by “sponging” miRs. LncRNAs that act as negative regulators of miRs and thereby achieve mRNA upregulation function as competing endogenous RNAs (ceRNAs) , 37. LinMoreover, some of the best-characterized lncRNAs are involved in processes like X chromosomal inactivation (XIST)  and genoIn the context of aneurysm disease H19 has been identified to boost aneurysm progression .Using RNAs for therapeutic approaches has many advantages due to their unique biology. Targeting and editing the undruggable human genome, modulating gene expression and altering epigenetic processes are just some of the many opportunities .However, current RNA-related methods are restraint by a couple of significant factors. RNAs are predisposed to endonuclease degradation , can cauToday, single-stranded antisense oligonucleotides (ASOs) usually contain a phophorythioate backbone replacing the early phophodiester bonds. This results in increased stability and hydrophobicity, thereby facilitating cellular uptake, enhancing bioavailability, and improving pharmacokinetics by binding serum proteins like albumin , 46.ASOs usually function via cleavage of a formed mRNA:ASO duplex by a recognition enzyme termed RNase H . One setNaked (unconjugated) ASOs—just like other RNAs—enter the cell via endocytosis . Yet, thThe specific delivery to many cell and tissue types remains difficult via current ASO methods. In this context, conjugating cell-type-specific targeting domains to ASOs might help to overcome this huge challenge. Successful examples for the mentioned approach include the N-acetylgalactosamine  ligand that is used for targeted ASO delivery to hepatocytes via the hepatocyte-specific asialoglycoprotein receptor , 55.ASOs that include a 2′,4′-O-methylene link between two joint rings (rendering the molecule bicyclic) are known as locked nucleic acids (LNAs). LNAs have an overall enhanced resistance toward degradation by 3′-exonucleases and show a great affinity to their mRNA target. The latter decreasing molecule length and improving delivery , 57.LNAs can be further divided into two main groups: mixmers and gapmers. Mixmers contain LNAs and DNA nucleosides that are spread throughout the oligonucleotide sequence. Mixmers block protein translation but are not able to support mRNA cleavage . ConversAnother subclass of ASOs are so called “antagomirs” or “anti-miRs.” These terms are used to describe single-stranded oligonucleotides that prevent miRs from exerting their inhibitory effect on their respective target mRNAs . Antagom-induced silencing complex (RISC)  . This dex (RISC) , 64.Introduction of phosphorothioates has improved siRNA stability and shortening of the siRNA double strand has reduced overall charge for enhanced local delivery –67. OtheLipid nanoparticles (LNPs) and synthetic nanoparticles were early attempts to master the siRNA delivery dilemma. Both systems were originally used for DNA-mediated gene therapy and required optimization for a siRNA approach , 70. ButWhen it comes to hepatic targeting, GalNac conjugation—similar to the ASOs approach described in the section above—has been successfully applied . For extA novel and utmost elegant way of using RNAs for therapeutic modulation is genome engineering via Clustered Regulatory Interspaced Short Palindromic Repeats (CRISPR) and the CRISPR-associated Proteins (Cas) proteins. Originally, CRISPR/Cas is a bacterial defense mechanism that prokaryotes use against viral and plasmid intruders. Prokaryotes integrate DNA sequences that match past intruders into their genome as part of their adaptive immune response. This intruder library or memory helps the organism to recognize and defend itself during future attacks .Today, the CRISPR/Cas9 type II system is commonly used in the research set-up. There have been other nuclease-based systems that contain genome editing capabilities but CRISPR is highly user friendly due to its simplicity and flexibility . In shorJust as with the above described techniques there are several delivery hurdles to take when transferring CRISPR/Cas9 into a clinical context. Both Cas9 and the sgRNA are charged macromolecules that are difficult to introduce into the cell's nucleus .Other concerns include off-target effects that could be reduced by adapting the sgRNA design , 80. DesSome of the main questions linked to genome engineering via CRISPR/Cas are of ethical nature as editing a patient's genome would cause a life-long alteration of the human “code” . At the The following section will give an overview on different delivery systems used for RNA therapy including viral and non-viral vectors  represent the most successful type of RNA nanocarrier . LNPs artoxicity .A new type of RNA-delivery for therapeutic purposes are extracellular vesicles (EVs) that have recently been discovered to be endogenous RNA carriers. EVs are released by cells and serve as means of intracellular communication. Since cells use miR-loaeded EVs to regulate gene expression in other cells and different sorts of RNAs, including lncRNAs, were found to be presented in these vesicles, they might represent a safer and more effective method of RNA-delivery –126.Interestingly, there seems to be a clear pattern when it comes to RNA vesicle packaging. Certain sequence motifs are favorably integrated into EVs . MoreoveOne major advantage of RNAs that are loaded into EVs is that they are protected from degradation by extracellular RNases . EVs serRNAs have successfully been loaded into EVs prior to isolation which raised concerns about the purity of the generated RNA-loaded vesicles. Consequently, several different mechanisms have been established to incorporate RNAs into EVs after isolation, including electroporation, sonication, and incubation with varying degree of success, as extensively reviewed in Jiang et al. .There are two major types of off-target effects that can be distinguished  protein, leading to increased phosphorylation and activation of AKT thus having protective effect on AAA development  on endothelial cells. Coated cationic lipoparticles were modified using a ligand for the VCAM-1 internalizing sequence . This aparticles . Therefoarticles .With regards to treatment of AAA, targeted delivery will be more difficult, since a potential receptor on SMCs or fibroblasts will not be in direct contact with the systemic blood stream. However, recent studies show progress in side-specific administration .Another study used microspheres to deliver antagomiR-92 into the coronary arteries in a pig model of perfused acute myocardial infarction to limit post-infarct remodeling, dysfunction of vessel wall motion, and promote vessel growth . This waTo our knowledge, there is no study using extracellular vesicles to target RNA therapeutics to AAA. However, it was shown that when administering mesenchymal stem cell derived extracellular vesicles to a murine model of intracranial aneurysm the rate of aneurysm rupture was decreased . While tin vivo. For example, one study found miR-24 to be protective against AAA development using lentiviral vectors to deliver pre-miR-24 in two different murine models of AAA. In both models decreased aneurysm development was demonstrated. The results could be confirmed using lentiviral vectors expressing anti-miR-24 which led to aggravated aneurysm development  are drug-eluting stents. This stent approach has been tested in a humanized myointimal hyperplasia model for in-stent restenosis using balloon-injured human internal mammary arteries that were transplanted into Nowett-nude rats . The miRIn a pig model of acute ischemia and reperfusion injury, delivery of LNA-anti-miR-92a was tested in a catheter-based approach. The study compared systemic, retrograde, and anterograde delivery to the heart, all resulting in significant downregulation of miR-92a . MiR-92aDespite local delivery, miR-92a levels were found to be affected in liver, kidney, and spleen, while the impact in lung tissue was lower compared to systemic delivery. However, significant decrease in infarct size and cell death as well as significantly improved global heart function were only observed after catheter-mediated anti-miR-92a delivery and not after systemic application . FurtherWhile many revolutionary developments regarding RNA knowledge and technology have been mentioned in the sections above, this review will close with some short notes on a method that has just started to evolve in the DNA/RNA field and that might be promising in the context of AAA disease as well.The DNA origami method is named after a famous Japanese paper folding art. Origami artists aim to sculpture a flat sheet of paper into a desired object by applying complex folding sequences. DNA origami aims to create a long single-stranded DNA molecule (scaffold) out of hundreds of short synthetic DNA nucleotides (staples), thereby folding specifically shaped objects at a nanoscale .At first it was only possible to generate planar, two-dimensional objects , but sinDNA-origami objects can load drugs and thereby function as miniature transporters. These so called “nanorobots” have been experimentally tested in the oncology field . But oriAlthough RNA molecules display many similarities to DNA molecules, it was not until 2013 that RNA origami had been reported by the Sugiyama and Mao groups , 164. InThe RNA revolution has taken the modern research world by storm. It presented some major successes when it comes to discovering new biological paradigms and clinical-translatable technology. One disease that benefited from this extensive research effort—by reaching a better understanding of disease mechanisms—was AAA disease. Discovering underlying pathological mechanisms helped to outline solution strategies. Still, years of further research will be needed to take several technological hurdles and achieve the ultimate goal of clinical translation.IS and AD drafted the manuscript. IS, UR, and PT contributed the initial idea, funding, and drafting. KM contributed ideas to the manuscript and created the figures. All authors contributed to the article and approved the submitted version.IS and UR are cofounders of Angiolutions. Angiolutions is a company developing vascular devices for aneurysm diseases. The remaining 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.