Caenorhabditis elegans (C. elegans) is a popular invertebrate model organism to study neurobiological disease states. This is due in part to the intricate mapping of all neurons and synapses of the entire animal, the wide availability of mutant strains, and the genetic and molecular tools that can be used to manipulate the genome and gene expression. We have shown that, C. elegans develops a conditioned preference for cues that had previously been paired with either cocaine or methamphetamine exposure that is dependent on dopamine neurotransmission, similar to findings using place conditioning with rats and mice. In the current study, we show C. elegans also display a preference for, and self-exposure to, cocaine and nicotine. This substance of abuse (SOA) preference response can be selectively blocked by pretreatment with naltrexone and is consistent with the recent discovery of an opioid receptor system in C. elegans. In addition, pre-exposure to the smoking cessation treatment varenicline also inhibits self-exposure to nicotine. Exposure to concentrations of treatments that inhibit SOA preference/self-exposure did not induce any significant inhibition of locomotor activity or affect food or benzaldehyde chemotaxis. These data provide predictive validity for the development of high-throughput C. elegans behavioral medication screens. These screens could enable fast and accurate generation of data to identify compounds that may be effective in treating human addiction. The successful development and validation of such models would introduce powerful and novel tools in the search for new pharmacological treatments for substance use disorders, and provide a platform to study the mechanisms that underlie addictions.The nematode  Drosophila melanogaster, ethanol (EtOH) conditioning and self-administration paradigms have demonstrated that flies develop conditioned preference responses to cues previously paired with EtOH , and varenicline tartrate was purchased from Biotang . Vehicle  and naltrexone HCl  were used to pretreat animals prior to SOA preference testing. Benzaldehyde  was used to test for non-selective effects of naltrexone HCl. 2-nonanone  was used to show that animals could move away from the SOA target zone.E. coli strain NA22 as a food source on maintenance plates, produced by filling 60-mm petri dishes with 10-ml regular NGM agar . The potassium phosphate buffer contained 5 g of K2HPO4 dibasic/anhydrous, 30 g of KH2PO4 monobasic, and 500 ml of H20, pH adjusted to 6.0 (The N2 Bristol wild-type (WT) strain was used in all assays. All animals were maintained at 22°C, and all general culturing techniques have been described previously by d to 6.0 .E. coli bacterial lawns until reaching adulthood. Testing began approximately 72 h post-plating the L1 larvae, when worms were adults.Adult worms were used for all experiments to control for any effects of different sensitivities and responses to SOAs at varying developmental stages. Worms were age synchronized by lysing gravid adults with bleach and sodium hydroxide, allowing eggs to be released into solution and hatched in M9 buffer . After 1TM cell culture plates were used to determine SOA preference (Fisher cat. no. 07-200-80). Clear templates were taped to the bottom each 6-well plate to create two 1.2 cm diameter circular target zones within the 3.5 cm diameter of each well. Test plates were produced by filling each well of the plates with 3.8 ml of NaCl free agar . Cholesterol was not included in the salt-free agar in order to obtain clearer images of worms during testing. Although the lack of salts and cholesterol in the agar may have long-term effects on worms, our previous work indicating intact cue-conditioned learning  or treatment agent naltrexone HCl  and inhibitor agent solutions were prepared fresh, prior to each day of testing. All concentrations of SOAs include the salt and each experiment was conducted over 2 to 4 days.Food: 1 μl of water or food  was spotted to the two target zones of each well. Images were taken at 30 min. Benzaldehyde: 2 μl of a 1%(v/v) benzaldehyde solution dissolved in 25%(v/v) EtOH was spotted in one target zone, while 25% EtOH was spotted in the opposite target zone, 30 min before testing. Images were taken at 30 min. The amounts/concentrations of food and benzaldehyde were selected to produce preference indices similar to those observed with cocaine and nicotine in this paradigm.Figure 1) immediately after taking 30 min images for SOA preference experiments in order to determine if animals were capable of moving away from the SOA target zones and were not rendered ataxic by the SOA test compounds themselves. Therefore, images were taken immediately before and 10 min after placing nonanone into each well. Pre- and post-nonanone preference indexes (PIs) (as described below under SOA preference testing) were calculated for each well in order to compute the change in preference from the SOA target zone in response to nonanone. In this way the effects of nonanone are tested at the time and under the conditions in which the animals are displaying the preference response.Nonanone (an aversive compound) was spotted [2 μl of 10%(v/v)] to the outer edge of the SOA target zone of each well  and the response to nonanone. Individual images were analyzed using ImageJ software to count the number of worms in the target zones of the test plates. Using ImageJ, the target zone was cropped from each photo and the color threshold of the image was adjusted. Specifically, threshold color was set to red, color space was set to RGB, and color threshold was adjusted so worms were highlighted in red. Particles were analyzed with a pixel size of 80 to infinity. The number of worms counted in each target zone was recorded and analyzed in Microsoft Excel.A chemotaxic PI for each SOA concentration was then calculated by dividing the number of worms in the SOA target zone by the total sum of worms counted in both the SOA and vehicle zones converted to a percentage.post hoc tests as appropriate and previously conducted  = 2.7; p < 0.05] and a significant interaction between pretreatment and cocaine concentration  on cocaine preference. For vehicle pretreated worms, a one-way ANOVA found a main effect of cocaine concentration on preference , and post hoc tests revealed significant (p < 0.05) preference indices for 250 and 500 μM cocaine compared to water. Post hoc tests also found significant (p < 0.05) differences in cocaine preference between the 50 μM and 250 μM cocaine concentrations, for vehicle treated worms. For naltrexone pretreated worms, a one-way ANOVA did not find a main effect of cocaine concentration on preference . One-way ANOVAs examining differences between vehicle and naltrexone pretreatment for each cocaine concentration found no main effect of pretreatment on water  or 50 μM cocaine  preference. However, naltrexone pretreatment decreased 250 μM  and 500 μM  cocaine preference compared to vehicle pretreatment.The effect of cocaine  to induce preference and the effect of pretreatment with 10 mM naltrexone to inhibit the response are shown in Figure 3 and Supplementary Figure 1. For naltrexone, a two-way ANOVA found main effects of concentration  and treatment , and a significant interaction between concentration and treatment  on nicotine preference at 30 min. Overall, the findings indicate a significant preference response at each nicotine concentration that is significantly reduced by pretreatment with naltrexone .The effect of nicotine  to induce a preference response and the effect of pretreatment with 10 mM naltrexone to inhibit the response is shown in Figure 4 at both the 10 min (A) and 30 min (B) time points. For 1 mM varenicline, a two-way ANOVA found a main effect of nicotine concentration  on nicotine preference at 10 and 30 min. There was however no effect of 1 mM varenicline pretreatment on nicotine preference at either time-point or nicotine concentration (p > 0.05).Varenicline pretreatment revealed robust effects at the 10 min time point in some cases, thus preference data were analyzed and presented for both the 10 and 30 min time points. The effect of pretreatment with 1 mM varenicline to inhibit the nicotine preference response is shown in Figure 5 at both the 10 min (A) and 30 min (B) time points. A three-way ANOVA found main effects of time (10 and 30 min) , concentration , treatment , a significant interaction between concentration and treatment , and a significant interaction between time and treatment  on nicotine preference. Overall, pretreatment with 9.0 mM varenicline significantly reduced the preference response to nicotine at both time points.The effect of pretreatment with 9 mM varenicline to inhibit the nicotine preference response is shown in t-test found that naltrexone (10 mM) pretreatment had no significant effect  on 1% (v/v) benzaldehyde preference  compared to vehicle (0.97 mM HCl) pretreatment .The effect of pretreatment with 10 mM naltrexone to modify benzaldehyde preference was conducted in order to examine the effect naltrexone on the preference response to a known volatile attractant. An independent t-tests found significant effects of nonanone on 250 and 500 μM cocaine preference . Paired t-tests found significant effects of nonanone on 5, 50, and 100 mM nicotine preference .In order to determine if animals were anesthetized after moving into target zones containing either cocaine or nicotine, the aversive compound nonanone was applied between the target zone and the edge of the plate after the animals had established a preference response. Independent Supplementary Video 1. A similar time-lapsed video illustrating the effects of pretreatment with 10 mM naltrexone on the preference test with 100 mM nicotine is presented in Supplementary Video 2.To better illustrate the development of drug preference and the aversive response to nonanone in this paradigm, videos of a preference test with 100 mM nicotine and the subsequent response to nonanone were recorded and compressed into time-lapsed format and are presented in Table 1). An independent t-test found no significant effect of pretreatment  on food preference . In addition, 9 mM varenicline pretreatment did not significantly affect food preference (Table 1). An independent t-test found no effect of varenicline on food preference .For vehicle and naltrexone pretreatment, both conditions showed a normal chemotaxis to food and food preference was 86.1 ± 2.8 and 80.3 ± 5.7%, respectively  = 0.02; ns]. Specifically, the number of body bends in 20 s for vehicle and naltrexone treatments were 54 ± 7 (n = 6) and 53 ± 3 (n = 6), respectively.Naltrexone: We found that exposure to 10 mM naltrexone for 30 min prior to testing had no significant effect on locomotor activity compared to vehicle exposure [n = 9), while body bends were 47.0 ± 3.6 (n = 8) for varenicline (9 mM) treated worms. Independent t-tests found no significant difference in body bends after varenicline treatment.Varenicline: Mean (±SEM) body bends/20 s for vehicle treated worms were 46.3 ± 3.6  and nicotine . Naltrexone pretreatment selectively reduced preference for both cocaine  and nicotine  in this paradigm, but had no effect on preference for food or benzaldehyde preference. Moreover, the SOA preference response was not likely due to an anesthetic or paralytic effect, since worms were able to move away from the SOA target zones following the application the chemorepellent, nonanone , and continue to move in the SOA target zone after entering (Supplementary Video 1). Pretreatment with varenicline, a treatment agent approved for smoking cessation in humans, also was found to reduce the nicotine preference response at concentrations that did not affect locomotor activity or food preference. These data are consistent with observations in vertebrate animal models showing efficacy and selectivity of the SOAs and begins to provide face and predictive validity for the model in medications screening applications. Importantly, the 6-well plates enable a high-throughput system for behavioral screening, and are able to reduce the number of C. elegans needed to conduct preference testing. This also limits the time required for imaging, and ultimately enhances throughput. Combined, these findings suggest that procedures using C. elegans may be developed to screen medications for the treatment of substance use disorders. In addition, the development of this technology will allow for the future investigation of the molecular mechanisms that underlie the efficacious effects of novel agents using the fully tractable C. elegans model.The present studies found a concentration-dependent attraction by C. elegans respond behaviorally to a chemical or substance is the simple chemotaxis assay  previously paired with cocaine or methamphetamine which utilized a procedure analogous to Pavlovian conditioning models of reward in rodents  at concentrations that do not inhibit food consumption (Table 1), benzaldehyde chemotaxis, or locomotor activity (body-bend data). These data are consistent with rodent data showing that naltrexone can inhibit intake of SOAs at doses that do not affect sucrose intake or body weight . This could be a reflection of the apparent strength of the nicotine preference response, or possibly rapid clearance of varenicline. In support of this idea is the apparent greater strength of the preference response, and resistance to nonanone for nicotine compared with cocaine at the concentrations used in this study . Although it is somewhat difficult to make direct comparisons between the cocaine and nicotine data due to the differences in systems and mechanisms, and also in concentrations used to produce the respective preference responses, there are clear differences in the response to nonanone. One possible explanation is that animals are being paralyzed by the SOAs at these concentrations. This cannot be completely ruled out as previous work has indicated that nicotine uniformly mixed in agar to concentrations from 1 to 10 mM can induce paralysis (Supplementary Video 1) which clearly show animals continuing to move in the nicotine target zone after entering during a preference test on a plate spotted with 100 mM nicotine, and a clear movement out of the zone after the addition of nonanone. One possible explanation for the greater effect of nonanone to displace cocaine exposing animals compared to nicotine is the somewhat stronger preference response observed with nicotine vs. cocaine in these assays . The increased preference response for nicotine over cocaine suggests a greater reinforcing property of the SOA as tested and as such would confer greater aversion resistance. Future experiments will provide additional evaluation and characterization of varenicline and other compounds to inhibit the SOA preference response. Such work is needed to further demonstrate predictive validity and provide a strong case for the model’s utility as a screening tool to help identify compounds that have potential as treatments for SOA and alcohol use disorders.Based on the data presented here, we anticipate that potential compounds that have efficacy in reducing SOA intake and/or seeking in vertebrate models and humans will also inhibit the SOA preference response in y weight . In most elegans . Our dat elegans . Althougeceptors . Other paralysis . HoweverC. elegans to date have mostly focused on EtOH (C. elegans (cat-2) reduced or inhibited SOA-induced behaviors for each SOA of abuse  of the species rather than complexities in the neuroanatomy. Interestingly, differences in receptor systems and molecular pharmacology in C. elegans could also provide an advantage of this model providing a unique perspective concerning how some classes of putative treatments affect SOAs. As an example, topiramate is under investigation as a possible treatment for EtOH use disorders  in addition, the ability to manipulate genes and gene expression quickly, and the availability of many mutant strains in this well studied and simple organism, greatly enhances the capability to discover specific genes and proteins involved in SOA preference behavior in this model; (c) the low cost and potential to fully automate the assays allows for a dramatic increase in the number of experiments that can be conducted for a fraction of the cost and time needed with other animal models. Thus, this model might be used in conjunction with gene editing techniques like CRISPR where C. elegans receptors can be replaced with their human orthologs to create transgenic C. elegans that might show human-like pharmacology. Such an application could improve the translational utility of the model and possibly enhance predictive validity.Further development of the model employed here is anticipated to provide the field with a new and powerful tool to discover novel targets and treatments for addiction. This work will combine the advances in our knowledge of human addiction and insight gained through the use of vertebrate behavioral models, and apply them to invertebrate models with tremendous advantages and potential for discovery on a number of levels: (a) the current work contributes to the establishment of a new behavioral model in Once a high-throughput system is fully established, one could conceivably screen entire potential treatment agent libraries using tiny amounts of expensive compounds relative to other animal models. Future collaborative projects will employ transgenic approaches to express human genes in this model to enhance the predictive validity of the model. Finally, the data will be bi-directionally informative with other animal models of medications development for substance use disorders and compounds in clinical trials, such that the diversity in pharmacology and molecular systems between different species will help to better identify the mechanisms of action of putative and/or validated treatment compounds.EE and SK wrote the initial drafts and designed and directed the experiments. KS, KB, MB, and HK performed the experiments and provided critical feedback for method development and manuscript preparation. RB and BN-B reviewed content, data, and final draft of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Unconventional protein secretion (UPS) is an important phenomenon with fundamental implications to cargo export. How eukaryotic proteins transported by UPS are recognized without a conventional signal peptide has been an open question. It was recently observed that a diacidic amino acid motif (ASP-GLU or DE) is necessary for the secretion of superoxide dismutase 1 (SOD1) from yeast under nutrient starvation. Taking cue from this discovery, we explore the hypothesis of whether the diacidic motif DE, which can occur fairly ubiquitously, along with its context, can be a generic signal for unconventional secretion of proteins. Four different contexts were evaluated: a physical context encompassing the structural order and charge signature in the neighbourhood of DE, two signalling contexts reflecting the presence of either a phosphorylatable amino acid  or an LC3 interacting region (LIR) which can trigger autophagy and a co-evolutionary constraint relative to other amino acids in the protein interpreted by examining sequences across different species. Among the 100 proteins we curated from different physiological or pathological conditions, we observe a pattern in the unconventional secretion of heat shock proteins in the cancer secretome, where DE in an ordered structural region has higher odds of being a UPS signal. In eukaryotes, proteins with an N-terminal signal peptide are known to get conventionally secreted in a vesicular mode through the endoplasmic reticulum (ER) – Golgi secretory pathway (ER-Golgi-secretory vesicles)5. However, interestingly, many proteins which lack in such well-defined signal peptides are also secreted, mostly under cellular stress6. This important class of unconventional protein secretion (UPS) reflects the cellular response to stressors such as inflammation, nutrient stress, ER stress, mechanical stress, etc., and continues to grow in relevance as many such instances are detected in disease associated with dysfunctional autophagy such as neurodegeneration7. Secretion of leaderless proteins  is intriguing, and this non-canonical export mechanism raises several mechanistic questions on their presumably unique secretory pathways6. While at least four different UPS mechanisms have been identified so far8, even simpler and fundamental questions on how these leaderless proteins are identified remain open.Proteins need to be secreted outside the cell for several physiologically important reasons9. These signal peptides have a characteristic tripartite structure – positively charged N-region, a hydrophobic H-region, and a polar C-region; which makes it easier for the export machinery in the cells, as well as for the computational models, to sort the secretory from the non-secretory proteins. Several predictive models for identifying these signals have been developed11. On the other hand, identifying unconventionally secreted proteins has not been equally intuitive, as they lack in the pattern of canonical leader sequence12. Modelling attempts to predict the unconventional secretion have had limited success so far in deciphering the signatures of non-canonical secretion13. Using artificial neural networks, which work by recognizing implicit patterns in protein sequences, unconventional secretory proteins were categorized by properties such as amino acid composition, secondary structure, and disordered regions, but do not explicitly reveal the patterns among the unconventional secretory proteins15. A rational basis for how non-classically secreted proteins are identified has been missing thus far.Conventional signal peptides are 15–50 amino acid tags (“zip code”) at the N-terminus of the proteins16. As a first and concrete observation, this finding raises the possibility that DE could be a generic UPS signal motif. However, as the short two amino acid length motif could occur in most proteins, in this study, we nucleate a minimal but rational hypothesis for the role of DE and its structural and charge context to act as a trigger for UPS.In a recent landmark work, a motif which drives a protein through the non-canonical secretion pathway was identified for the first time. By systematically comparing the superoxide dismutase 1 (SOD1) from human and mouse cells with their extracellular SOD1 counterparts from human, mouse and yeast cells, a diacidic motif (Asp-Glu or DE) had been identified to be responsible for its unconventional secretion. Of the 6 amino acid insertion in SOD1, compared to its extracellular homologs, UPS was found to be sensitive to the mutation of two amino acids aspartate (D) and glutamate (E)16 , we intended to check the same in all other neurodegeneration causing aggregates such as α-synuclein, β-amyloid, TDP-43, Tau followed by Group 2 that encompasses all the known UPS cargoes known to date. All these Group 2 secretory proteins were chosen from Keulerset al.17, Group 3 were chosen from the dataset of heat shock proteins that are reported to be secreted in an unconventional manner in cancer18 and the proteins from the breast cancer secretome where UPS is the major contributor19. Group 4: While the list of non-secretory proteins could be very large, we did not add any more of them than the number of secretory proteins to keep the data set groups unbiased. Non–secretory proteins (cytoplasmic), were chosen from theHuman Protein Atlas. The complete list of proteins used in the analysis is tabulated in Dataset 120. The final curated set included 100 different eukaryotic proteins, 57 secretory and 43 non-secretory, whose DE sequence details, and the nature of protein are mentioned in20.All the proteins used in this analysis are eukaryotic proteins. Since the hypothesis was centred on the contexts in which DE acts as a UPS trigger, any protein which had no DE motif was discarded from the analysis. The proteins used in the analysis were chosen from four different groups:- Group 1: Since it was recently demonstrated that the presence of DE in UPS of SOD121 of 3 amino acids on either side of the DE motif (2) Charge (C) of the local region, by summing the charge of 3 amino acids flanking on either side of DE and (3) structural order – the local structure around DE was initially categorically classified as ordered (O) if DE is in α- helix or β- sheet, disordered (D) if DE is in a loop or disordered region  Hydrophobicity (H) of the local region, by adding the hydrophobicity scoreFor every protein used in the analysis, we characterized all DE motifs by their physical descriptors . DE motif occurs in several places in many protein, and we wanted to identify the most important DE motif for UPS signalling using the analysis of the curated data. To identify the most relevant DE motif, we generated 16 possible hypotheses listed as cases inscikit-learn module (version 0.19.1) inPython (version 2.7)22. Significance quantified by p-values were obtained from these Python analyses. The choice of the hypothesis comesa posteriori, comparing the quality of multivariate binary logistic regression model for the prediction of secretion , we performed 16 independent binary logistic regression calculations usingcretion .iLIR database23. The details of the LIR motifs in the proteins analysed are tabulated in Dataset 120.We predicted the occurrence of microtubule-associated protein, LC3 interacting motifs in the proteins using thePfam website using their identitiesPf00080 andPf00887 respectively. From the 3904 and 3489 sequences downloaded for the homologs of SOD1 and Acb1, we used a maximum gap frequency of 0.2, and used the selected sequences for co-evolutionary analyses. A consensus sequence was created by choosing the most common amino acid in each position. The entire MSA was then binarized, substituting 1 if the amino acid in a certain position is the same as the one in the consensus sequence, and 0 otherwise. A co-evolution matrix was created with a home-written Python code, following the protocol used in Statistical Coupling Analysis (SCA)24. The pairwise co-evolution possibility was used to compare the co-evolutionary couplings different DE motifs have.Homologous sequences and their multiple sequence alignments (MSA) for SOD1 and Acb1 proteins were obtained from theDependency on single variable. Before building a multivariate predictive model, the curated data was classified as either secretory (UPS) or non-secretory, and their relation to each of the individually chosen variables describing the structural context of where DE occurs in the protein was examined. The secretory nature has a dependence, although not very strong, on all three physical context variables hydrophobicity (H) , charge (C), and (dis)order D/O that we calculated based on the protein sequence and structure data (see Methods). The most significant difference between the physical variables describing secreted and unsecreted proteins was observed in our analysis of the data from the cancer secretome  or three N-phosphorylated amino acids 27. The analysis separated the proteins into those which have at least one such motif, and those which do not and studying their relevance for secretion. The contingency tables for the possibility of secretion along with insertions DXE  triggers UPS. Most secretory proteins had DE and LIR motifs that are discontiguous (Dataset 120). The group I had 4/5 , group II with 20/26, group IV – secretory proteins within 7/8 and HSPs with 10/11 discontiguous stretches. No significant conclusion could be derived either about the presence of LIR or about its proximity to the DE motif.The LIR is a motif that aids in autophagy16. We explored to see if the motifs implicated in UPS signalling have co-evolutionary patterns that are conspicuously different from the other two. D102 in SOD1 had a co-evolutionary relation with three other amino acids , but a similar pattern could not be seen in the other DE motifs from SOD1 and Acb1. The identification of the DE signature16 involved the knowledge of sequences as well an additional information on the protein localization. Thus sequence alignment and coevolution information alone used in the present analysis could not distinguish the DE that acts as a UPS signature.By using over 3000 homologous sequences (see Methods), pairwise co-evolutionary relationships were constructed among all the amino acids in SOD1 and Acb1. Both these proteins had two DE motifs each, specifically one motif being implicated in UPS (amino acids 77–78 in SOD1 and 23–24 in Acb1)29. For example, it had long been known that KDEL or HDEL sequences at the C-terminus act as retention signal to keep the proteins in ER29. Further, DXE was identified as the signal for the export of transmembrane proteins such as VSV-G by COPII-coated vesicles from the endoplasmic reticulum to Golgi25. Although exporting proteins containing these signals work through conventional secretory pathway, DE signal in SOD1 directs the protein export through the UPS. Thus, it is clear that the same DE motif depending on its flanking residues and insertions can assume a different signalling role16. In this work, we examine several eukaryotic proteins to find clues for the patterns leading to UPS.The role of diacidic motif DE as a component of retention or export signals has been noted in several contextsSince the knowledge of the factors contributing to unconventional secretion is in its nascent stages, the aim of this work was not to predict the possibility of cargo secretion by unconventional pathways but rather to build a hypothesis which may be accepted or rejected as and when more data will be available. The known secreted cargoes that take the UPS route are limited. In this direction, we curated available data which could allow us to make comparisons between the secretory and non-secretory proteins. Towards this, we gathered data from different pathological conditions – cancer secretome, neurodegeneration, and cellular stress. In terms of analysis, we examined the occurrence of DE motif in four different contexts, namely in ordered regions such as helix or sheets, in disordered regions such as loops, or alternatively in the border region between the ordered and disordered regions. We also considered the possible post-translational modifications of the “X” in the DXE motif, co-evolution of DE motif in Acb1 and SOD1, and charge, hydrophobicity and order of DE motif. Specifically, the physical context defining DE was further dissected into 16 different cases to build a hypothesis to identify the most relevant DE among all that were present in the proteins analyzed.p-values for the binary logistic regression predictions were significant in some of the cases, the dependence on some of the individual variables used was not significant. One of the reasons for this observation might be the limited sample size of UPS cargoes. There are two ways to validate the hypothesis. The first is to curate data on more eukaryotic proteins which certainly go through UPS and ascertain if the statistics improve significantly. Alternatively, since the hypothesis is centred around the structural order and charge on the amino acids flanking DE, SOD1 secretion may be re-examined with mutations which promotes structural order or by increasing the charges, in addition to the substitutions to alanine that have been already explored by the Malhotra group16.Our analyses suggest that when the diacidic motif DE appears in an ordered structural environment with lower charge and higher hydrophobicity, it is likely to increase the odds of unconventional protein secretion. While the overall25. Serine, threonine, tyrosine, as well as arginine30, histidine and lysine28 can undergo phosphorylation under oxidative stress, which is also known to be the external cue that triggers UPS. This hypothesis can be validated by searching for similar patterns in a larger dataset as well as by introducing the DXE motif and observing its chances for unconventional protein secretion.Considering the alternative hypothesis proposed in this work that DXE motif could be a signatory sequence for UPS, it is plausible that the post-translational modifications, especially, phosphorylation of the inserted amino acids may act as a signal for UPS. It was observed that among the analysed data, the amino acids with propensity for hydroxyl or amino group phosphorylation (O- or N-phosphorylation) are inserted as DXE in the proteins that undergo UPS. Contrary to this, the DXE motif that was seen in COPII is with aliphatic amino acid insertions19, intracellular pH31, surface charge of the tumour cells32, etc., may allow proteins with buried DXE motif to be exposed and accessible for the UPS machinery as has been suggested for the secretion of Acb1 and SOD116. Our analysis that the odds of secretion is significant in terms of minimum charge and maximum hydrophobicity . We did not observe any significance in the proximal position of the LIR motifs with the DE signal. Moreover, it is seen that the sequence alignment and coevolution information alone used in the present analysis could not distinguish the DE that acts as a UPS signature.We also tested the hypothesis that DE motif in the immediate proximity of LIR motif (joined in the primary sequence) triggers UPS. Most secretory proteins had DE and LIR motifs that are discontiguous  have not been characterized sufficiently to understand whether they have a common signal for the UPS pathway. These authors address this important question. Work from the Malhotra lab identified such a sequence in one protein, superoxide dismutase (SOD1) from human and mouse cells. This turned out to be a diacidic (DE) motif. However, because such a minimal sequence could be present in many proteins, not all of which are likely to be substrates for UPS, and similar   are used in other sorting pathways, the authors have used a bioinformatic approach to compare 100 different eukaryotic proteins, 57 secretory and 43 non-secretory, with DE sequences. They examined features, such as hydrophobicity, charge and protein order, in the vicinity of the diacidic motif, in proteins sorted via the UPS, but that are absent in non-secretory proteins.. They also looked for the presence of a proximal LIR motif presumably because the UPS relies on autophagy. The authors suggest that suggest that when the diacidic motif DE appears in an ordered structural environment with lower charge and higher hydrophobicity, it is likely to increase the odds of unconventional protein secretion. They did not find a significant presence of a proximal LIR. The paper presents reasonable and testable hypotheses, but falls short in leaving the testing to others, or for the accumulation of a larger list of UPS cargos. It seems reasonable to publish this as a hypothesis.I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. The DE motif has been identified in proteins like SOD1 and Acb1 for their ER-Golgi independent pathway of secretion. But this di-acidic motif is quite common and it is unclear how cells exploit this signal to export a specific class of proteins. Prakash and colleagues provide useful clues to help place the significance of these residues as a potential export signal. They find that it helps if DE sequence  is contained in the ordered domains of the proteins with less charge and higher overall hydrophobicity. This could in principle be used for membrane attachment. They also suggest the significance of LIR sequences in close proximity to increase the potential usage of the di-acidic motif for export. This is particularly interesting because LIR containing proteins have specific membrane associated receptors and the cells use this combination to clear cellular proteins by autophagy.  A combination of DE and LIR motif could be used to bind specific membranes for export and to  avoid autophagic clearance. This information will help move the field forward and I strongly support the publication of this data.I have read this submission. I believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.


Progressive muscle relaxation (PMR) is an under-utilized Level A evidence-based treatment for migraine prevention. We studied the feasibility and acceptability of smartphone application (app)-based PMR for migraine in a neurology setting, explored whether app-based PMR might reduce headache (HA) days, and examined potential predictors of app and/or PMR use. In this single-arm pilot study, adults with ICHD3 migraine, 4+ HA days/month, a smartphone, and no prior behavioral migraine therapy in the past year were asked to complete a daily HA diary and do PMR for 20 min/day for 90 days. Outcomes were: adherence to PMR (no. and duration of audio plays) and frequency of diary use. Predictors in the models were baseline demographics, HA-specific variables, baseline PROMIS (patient-reported outcomes measurement information system) depression and anxiety scores, presence of overlapping pain conditions studied and app satisfaction scores at time of enrollment. Fifty-one patients enrolled . Mean age was 39 ± 13 years. The majority (63%) had severe migraine disability at baseline (MIDAS). PMR was played 22 ± 21 days on average. Mean/session duration was 11 ± 7 min. About half (47%) of uses were 1+ time/week and 35% of uses were 2+ times/week. There was a decline in use/week. On average, high users (PMR 2+ days/week in the first month) had 4 fewer days of reported HAs in month 2 vs. month 1, whereas low PMR users (PMR < 2 days/week in the first month) had only 2 fewer HA days in month 2. PROMIS depression score was negatively associated with the log odds of using the diary at least once (vs. no activity) in a week  and of doing the PMR at least once in a week . PROMIS anxiety was positively associated with using the diary at least once every week  and with doing the PMR at least once every week . In conclusion, about half of participants used smartphone-based PMR intervention based upon a brief, initial introduction to the app. App use was associated with reduction in HA days. Higher depression scores were negatively associated with diary and PMR use, whereas higher anxiety scores were positively associated. There are access issues: few providers are trained in these therapies for migraine, there is difficulty paying for the therapy on the part of the patients, and patients have difficulty finding the time to attend therapy appointments. A prospective cohort study of outpatients seeing a HA fellowship trained and certified headache (HA) specialist found that only about half (56.6%) of the patients initiated behavioral migraine treatment. In addition, of those who do partake in therapy, there are issues related to adherence to therapy. A recent review found few studies that attempted to assess adherence to nonpharmacologic treatments.6 In studies that did assess adherence, adherence was suboptimal.Migraine affects over 36 million Americans and is the second most disabling condition in life adjusted years according to the World Health Organization.8 Long-term, PLOT is more cost effective than both traditional clinically based treatments and many preventive pharmacologic treatments.9 More recently, electronically delivered behavioral treatments for HA have been studied, however, smartphone-based electronically delivered HA interventions have not been studied to date.10To improve the uptake and initiation of behavioral therapy for HA, researchers have investigated alternative methods for delivering behavioral therapy for HA beyond the traditionally studied behavioral therapy typically consisting of 8–12 in-person sessions with a therapist. Years ago, researchers showed that prudent limited office treatment (PLOT) for the delivery of behavioral therapy, not just traditional clinic-based behavioral treatment programs, can reduce the frequency and intensity of migraine for up to 6 months.12 Prior research demonstrates that pain self-management training increases self-efficacy and self-management behaviors while improving pain and depression outcomes.13 Prior research has also shown that most people with migraine who present for care are between ages 18 and 50 years, and between 89 and 94% of Americans in this age group have smartphones.15 Migraine patients can successfully use smartphone applications.16We sought to leverage increased smartphone technology use to integrate smartphone-based progressive muscle relaxation (PMR) for migraine. PMR was the mind–body intervention selected because it is successful as a technique that patients can do independently.The purpose of this study was (1) to examine whether smartphone-based, electronically delivered nonpharmacologic intervention, specifically PMR, using the RELAXaHEAD smartphone application (app) is feasible and acceptable for the self-management of migraine in a neurology outpatient setting using both quantitative methods  and qualitative methods , (2) to explore whether smartphone-based PMR might be efficacious in reducing HA days, and (3) to examine potential predictors of app and/or PMR use to aide in future HA-related mobile health  studies.SD years; 32 (63%) had severe migraine disability at baseline (MIDAS). Mean HA days reported per month at baseline was 13 ± 8 SD , with a median of 10 HA days (IQR = 1.5) per month. All 51 (100%) patients had previously used abortive medications to stop migraine attacks and 38 (75%) had previously been on migraine preventive medication. Nine (18%) had previously been on opioids as part of their migraine treatment regimen. Fifteen (29%) of the enrolled patients had previously undergone behavioral therapy  > 1 year prior to enrollment. Twenty (39%) had at least one of four overlapping pain conditions . In addition, 20 (39%) reported having anxiety and 17 (33%) reported having depression. The mean PROMIS (patient-reported outcomes measurement information system) depression screen score was 50 ± 10 SD  and the mean PROMIS anxiety depression score was 50 ± 10 SD .Fifty-one patients enrolled in the study between 7 July 2017 and 12 April 2018. As shown in Table After being shown how to use the app and after doing one PMR session, participants were asked to complete the satisfaction survey. As shown in Table SD  days by each participant. Of the 1053 total uses of the diary by all participants, 665 (63%) days were reported as HA-free days. Over the period of 90 days 63% (370/612) of per week total diary uses among the 51 users were 1+ time/week and 58% (338/612) of uses were 2+ times/week. PMR was played on average 22 ± 21 SD  days by each participant, with a mean per session duration of 11 ± 7 SD min. The average number of days of the PMR short and long audio files played were similar: 14 ± 16 SD versus 14 ± 15 SD, respectively. Over the period of 90 days, 47 percent (260/612) of total PMR uses per week (among 51 participants) were 1+ time/week and 35% (179/612) of uses were 2+ times/week.The quantitative HA diary data and PMR use data were obtained from the RELAXaHEAD application. Tables As shown in Fig. The qualitative data were obtained during the follow-up telephone calls. Table y axis = 1) and low (y axis = 0) PMR users. On average, high users had 4 fewer days of reported HAs in month 2 compared with month 1, whereas low PMR users had only 2 fewer HA days in month 2. The difference in changes in HA days for low and high PMR users was significantly different than zero . With the informative missingness, using the same approach as above to compare changes in HA days in high PMR users and low PMR users, the mean HA days were reduced by 2 days in high PMR users from month 1 to 2, however, mean HA days increased by 3 days in low PMR users. Reduction in HA days from month 1 to 2 for high PMR users was different than for low PMR users .Figure PROMIS depression score, PROMIS anxiety score and response to a questionnaire about whether the app maintained their interest remained in the prediction model post selection for both PMR outcome and Diary use outcomes. PROMIS depression score was negatively associated with the log odds of using the Diary at least once (versus no activity) in a week . PROMIS anxiety  and the satisfaction questionnaire about the app keeping interest  were both positively associated with using the Diary at least once every week. Similar results were observed for PMR use, with odds ratios of 0.77  for PROMIS depression score, 1.14  for PROMIS anxiety and 5.4  for app keeping interest questionnaire, respectively.Area under the curve (AUC) for the diary use model was 0.98, whereas that for the PMR use model was 0.96, both indicating a good prediction performance of the model.Box 1 Themes and subthemes for when participants were queried about what obstacles they encountered when performing the smartphone-based PMRDisliking the PMR behavior/audio filesApp-specific complaints- Redundancy of PMR (5)- Dislike of audio/voice recording (3)PMR as a therapy- Inability to sit still/lack of focus for long PMR (5)- Able to do relaxation without audio (2)Physical effects of therapy- Increases tension (1)- Painful to use during headache or migraine (2)- Increases tiredness (1)- Visual disturbances (1)- Increases anxiety (1)- Uncomfortable with breathing exercises (1)Difficulty maintaining the PMR practiceTime/logistical constraints- Time management (17)- Difficult to schedule both PMR sessions (6)- Unable to find time for long PMR (5)- Difficult to find private space to complete PMR (4)- Vacation (2)- Other health problems (3)Behavioral obstacles- Lack of self discipline (2)- Forgets to complete PMR (5)Technical issues- Personal phone issues (2)- Technical issues with app (1)Positive opinions on PMR- Enjoys short PMR (4)- Enjoys long PMR (1)- Enjoys PMR prior to bedtime (3)In the first study exploring smartphone-based PMR on neurology patients with migraine, we found that participants who meet criteria for migraine preventive therapy were willing to try a low cost, traditionally evidence-based minimal intervention behavioral therapy delivered via a smartphone application. We had the following key findings: (1) About one out of every two participants demonstrated uptake of the smartphone-based PMR intervention based upon a brief, initial introduction to the app. (2) Participants averaged ~11 min of PMR on the days that they used it. (3) There appeared time limited acceptability of the intervention by 6 weeks. (4) There appeared to be a dose relationship in using PMR and a decrease in HA days. Personal characteristics, however, which were not examined in this study, may be associated with adherence and may confound the study.17 We showed that in a population of migraine with the majority having severe migraine disability, 84% used the PMR in the first week and 51% used in at week 6. This is significantly better than a prior study of 221 severe tertiary care HA inpatients who were advised to do relaxation therapy in the 7-day period before discharge, in which only slightly more than the majority (59%) used relaxation as a preventive measure.6Given that this was a low-cost study with an uptake rate of one out of two, we believe this initial study demonstrates feasibility, especially given the fact that so many people do not receive psychological treatments for pain owing to barriers to access such as a shortage of providers, expense, and geographic distance from treatment centers.18 We trialed the PMR dose duration in this population based on the SMILE study.20 Dosing decisions must be made based on feasibility.21 The fact that people were willing to do the PMR for a shorter duration is not surprising. We did not ask patients to do the PMR the way it is typically taught in clinical practice; we did not use the gradually shortened PMR, which reduces 16 muscle groups down to 4 muscle groups time nor did we use PMR by recall.22Participants averaged 11 min of PMR use on the days in which PMR was used. There is no known dose that is considered most efficacious across migraine behavioral treatment trials, let alone behavioral treatment studies in general. Although Jacobson initially developed PMR to be used for an hour each day, it was later modified to be used for briefer periods of time.There was an initial signal that there may be a dose–response relationship between PMR use and a decrease in HA days. Many participants were not reporting HA days in month 2 compared with 1 in low PMR user group and our imputation accounted for that. We believe that the increase in HA days for low users from month 1 to 2 using imputation method is the consequence of underreporting in month 2 stipulation.23 Reasons for discontinuation of internet-based psychotherapies for pain previously cited in the literature include being disenchanted or seeking a better alternative,24 health problems and illness, difficulty using a computer or being physically uncomfortable using a computer, and personal problems.25 This is similar to our reasons for withdrawal which were: disenchanted, time, and worsened symptoms. In addition, our withdrawal rate of 16% , is similar to rates of attrition of other internet-based studies of psychological interventions for pain. A Cochrane review of internet-based psychologic therapies for pain showed that the overall attrition was 17.4% on average (range 0–25).25 The studies in the Cochrane review had a mean duration of 11 weeks (range 3–46 weeks). This is a much lower rate than the dropout rate of a third of recruited patients in traditional randomized controlled trials (RCTs) of pharmacological treatments, with rates even > 80% in some long-term relapse prevention trials.24Overall, the usage is similar to rates of adherence in other migraine-preventive studies, including both preventive behavioral and migraine medication studies. The discontinuation rate for migraine medication preventive treatment is >44% based on claims database studies.By 6 weeks, it was clear that user engagement diminishes over time. This is in line with other mHealth studies, which tend to have short lengths. Ninety days may not be feasible for patients nor realistic or clinically applicable per expert opinion from HA behavioral specialists who state that by four weeks, participants would be able to learn the PMR technique and integrate it into their lives. Adjustments may be made to the protocol so that the study duration might be 6 weeks and participants may be asked to participate for fewer days of the week.26 Outcomes can be tied to motivation, symptom severity, and patient expectancy.26In our study, depression was a negative predictor for use of the app and PMR, whereas anxiety was a positive predictor of use. This is not surprising given that a prior study showed that those with lower levels of depression did better in a RCT using an online CBT intervention.To ensure the best quality data and to maximize chances of proving efficacy, many study designs seek motivated participants. They screen outpatients after a certain baseline period. They may also screen out those who do not show for initial enrollment sessions and thus do not re-schedule prospective participants. They may also leave it to the personal interview or interviewer to judge that a person would not be a good candidate for a behavioral trial. In order to be as pragmatic as possible, we did not do any of the above—we included all of those who demonstrated some willingness to engage in research. In addition, most studies do not include those who are as severely disabled as our study population and/or do not include people who have failed as many preventive treatment regimens.25 We had back-end analytics to capture what other studies have not had the capability to do.In the prior Cochrane review of internet-based psychotherapy for pain, for those who remained in the studies, overall compliance rates with interventions, e.g., number of sessions completed are generally not reported and planned analyses of secondary outcomes  were limited because data were limited.27 In addition, we did not control for changes in meds during the study period.The study had several limitations. This was a pilot study with 51 subjects, and it was a single-arm feasibility study not powered to examine efficacy. Although a strength of the study was that we had back-end analytics to control for the amount of time playing the PMR, it was not possible to ensure that participants were fully engaged and as prior researchers note in their studies, it is not feasible to control for multitasking.24 Larger funded studies may compare such factors. Also, much of the current research and clinical practice for migraine behavioral intervention involves multiple components. Future work might also investigate the use of additional behavioral techniques such as deep breathing or imagery in addition to the PMR.This was a rigorous study design that focused exclusively on smartphone-based PMR and may not reflect what expert clinicians use in actual clinical practice. In the case of PMR, some HA behavioral therapists will start with the full PMR (up to 16 muscle groups) and will then gradually lessen the number of muscle groups over a brief period of time (approximately two weeks). Others may start with a short version and have people gradually increase the duration of PMR over time. They will also move from practiced PMR with audio-recordings to the PMR being done by self-recall. This is an important area to investigate both because participants may be dissatisfied with the intervention  or because the intervention has met their needs (attainers).28 In addition, gamification may also help to improve adherence to the PMR. Future studies may examine how to improve/better engage those with higher depression scores or may trial other methods for these patients. Future studies may also seek to target those with migraine and comorbid anxiety to optimize treatment efficacy.We might also test additional strategies for engaging participants in the therapy. We had difficulty reaching participants during the follow-up calls. Almost three quarters of enrollment (37/51) took place for the study before funding was received to hire a part-time paid research coordinator. Prior research has found that migraine patients may accept up to five prompts per day for electronic diary keeping. Beep reminders with time limits on the silence mode to a maximum of 2 h and voice prompts might be used.24 We found that in a convenience sample of 51 patients, more than half of whom had severe migraine, about one of every two patients demonstrated engagement with smartphone-based PMR intervention based upon a brief, initial introduction to the app. Also, there appeared to be time- limited acceptability of the intervention by 6 weeks. This is a promising area given its low cost, scalable method, and future studies can begin to examine efficacy.In conclusion, mHealth studies are at an advantage of some other behavioral studies in being able to monitor the usage patterns by tracking the frequency, duration, and length of the intervention. In addition, mHealth interventions have high fidelity: the same intervention is offered to all the participants.Feasibility and acceptability of the intervention and predictors of the RELAXaHEAD app diary use and performance of PMR were examined in a single-arm prospective study of 3 months duration, with baseline, 1-, 2-, and 3-month measurements.The study was approved by the NYU Medical Center Institutional Review Board, and written informed consent was provided by research volunteers.29 NYU-approved research volunteers pre-screened prospective subjects using Epic30 and then approached patients and/or their physicians to inform them that the patient may be eligible for a study examining electronic treatment for migraine prevention. Participants were recruited using convenience sampling. In order to be eligible, patients had to be between the ages of 18–80 years, speak English, own a smartphone, have a diagnosis of migraine from a neurologist , self-report four or more HA days/month, be willing to engage in a smartphone-based behavioral therapy, and be free of behavioral therapy  for migraine in the past year. If eligible, research volunteers provided signed informed consent.From 7 July 2017 to 12 April 2018, participants were recruited from the New York University Langone Health Neurology practice. The neurology setting was selected as nearly a quarter (23.2%) of people with migraine who present for care present to specialty outpatient settings, presumably neurology or HA specialty clinics.33 was selected as the behavioral intervention because of its success as a technique that patients can do independently.12 The RELAXaHEAD app was modeled after the app used in the SMILE study that examined smartphone-based PMR for epilepsy patients.20 (It has the same PMR used in that study and the Human Epilepsy Project (HEP) app.)34 There is an ~ 5-minute PMR session and an ~ 15-minute PMR session embedded in the app. For the RELAXaHEAD app, modifications were based on input from migraine patients and HA specialists using methods described elsewhere.35 Our RELAXaHEAD app has back-end analytics built in to record the amount of time spent playing the PMR. Pain intensity, duration, and medications taken may be recorded using the app. In addition, the RELAXaHEAD app allows the use of reminders and timely follow-up of non-compliant participants via real-time investigator data monitoring capabilities. The RELAXaHEAD application uses a platform developed by IRODY, and NYUMC MCIT previously approved its development. Participants were asked to use the app for 90 days by completing the HA diary daily and performing PMR using the app for 20 min/day. To cover data plan charges associated with use of their personal phones, participants who enrolled after the funding date (1 November 2017) were paid $25 at enrollment and $1/day for each day that data were entered into the app.PMR, a standardized, evidence-based behavioral treatment used for migraine since the 1980sPrimary outcome measures included the following quantitative data: (1) number of days of HA diary use/90-day period, (2) number of days of PMR use/90-day period, and (3) dose (minutes) of PMR use/day in those who used it. These data were abstracted from back-end report maintained by the app.Secondary outcomes were (1) the number of HA days recorded in the app for the high and low PMR users and (2) predictors of app use and PMR use. App diary (or PMR) use for every week following the enrollment was determined based on whether the participant used the diary (or the PMR) at least once a week in a given week during the 90-day period.Predictors of app diary use and performance of PMR included age, gender, race, self-reported age at first HA, self-reported number of HA days in the past month, self-reported average HA intensity, self-reported current HA intensity at time of enrollment into the study, total MIDAS based on the five-question score, self-reported usage of behavioral therapy for migraine prior to 1 year of enrollment in the study (yes/no), PROMIS depression, PROMIS anxiety, self-reported presence of the overlapping pain conditions studied (yes/no), self-reported use of any migraine preventive medicines (yes/no), the response  to the satisfaction questionnaires asked during the enrollment, and whether they were compensated for participation in the study.Specific measures were as follows:36 is a validated five-item questionnaire that has internal consistency and test–retest reliability and was developed to assess HA-related disability with the goal of improving migraine care. Questions ask about prior activity limitations over the past 3 months. Examples include “On how many days in the last 3 months did you miss family, social or leisure activities because of your HAs?” and “On how many days in the last 3 months did you miss work or school because of your HAs?”The MIDAS38 They are calibrated by each item question. The PROMIS depression assesses self-reported negative mood, views of self, social cognition, and decreased positive affect and engagement. Somatic symptoms are not included so as not to be confused with potential confounders, e.g., changes in sleep. The PROMIS anxiety measures self-reported fear, anxious misery, hyperarousal, and somatic symptoms related to arousal. Behavioral avoidance is not emphasized.The PROMIS depression and anxiety questionnaires are disease agnostic questionnaires developed by the National Institutes of Health to assess depression and anxiety, respectively, over the prior seven days.The satisfaction questions were developed specifically for this study by the HA specialist and appear in Table Data were collected by the research study team at baseline (in-person enrollment), from the app, and during 1-, 2-, and 3-month follow-up telephone calls. We also collected qualitative data during these phone calls. During the follow-up telephone calls, participants were asked the following three open-ended questions: 1. What do you think of the relaxation therapy? 2. What obstacles have you encountered in doing the therapy as recommended? 3. Would you recommend the therapy to others with migraine?Descriptive statistics were used to describe baseline participant characteristics and use of the app diary and PMR. Use of the app was described in terms of the mean number of days the diary was used in the 90-day period. PMR performance was described in terms of the mean number of days PMR was used, mean duration of PMR, and proportion of short (~5-minute long PMR) and long (~15-minute PMR) PMR sessions during the 90-day period.Logistic regression was used to explore predictors of app diary and PMR performance. Two stage mixed effects logistic regression model, with random effects for each participant and for each study week, was used to account for repeated measures per participant and potential differences across study weeks since enrollment. The outcome variable was a dichotomous variable of whether the participant used the diary (or the PMR for predicting PMR use) at least once in a given week during the 90-day period. In the first stage, the best set of predictors were selected using Likelihood-ratio tests with a backward selection procedure to avoid overfitting. There were estimates of odds ratio of the fixed effects using the parsimonious set of predictors post selection in the second stage of the logistic regression. AUC measure was computed using the final model to assess how well the fitted model predicts PMR and diary use.We also sought to examine when the diary and PMR were most likely to be used over the 90-day period. This was assessed by summing the number of days/week of diary and PMR use.t test. (High PMR users were any user with two or more weekly uses in the first 4 weeks of enrollment.) The first analysis of efficacy assumed that the days in which the diary was not used are HA-free days. However, to account for informative missingness, we also imputed HA days in the second set of analysis. For participants with at least one reported HA day in a month post enrollment, we computed rate of reported HA days as a ratio of observed number of HA days and total number of days the diary was used. Expected HA days per month was then computed as a product of the rate of HA days and the total number of days in a month for each participant, and for months 1 and 2, respectively. Sixteen participants did not use the diary at all in month 2. These participants were excluded from the analysis that used imputed HA days.We assessed whether there was a signal of efficacy of PMR use in the outcome of HA days by comparing the changes in total number of HA days reported on the diary from month 1 to month 2 for high and low PMR users in month 1, using a two-sided Using the data collected during the follow-up calls, qualitative analyses were conducted using general thematic analysis, allowing themes and subthemes to emerge iteratively. Contextual evaluation was accomplished as two members of the study team individually created a list of codes for each patients’ response to the obstacles question and then collaboratively compared and agreed upon codes with the help of a HA expert with experience in qualitative research. Based upon the codes, two study team members then developed themes and subthemes with the help of the same HA expert with qualitative research experience.Further information on research design is available in the Reporting Summary


The membrane-anchored enzyme Cytochrome P450 2D6 (CYP2D6) is involved in the metabolism of around 25% of marketed drugs and its metabolic performance shows a high interindividual variation. While it was suggested that ligands access the buried active site of the enzyme from the membrane, no proof from unbiased simulations has been provided to support this hypothesis. Laboratory experiments fail to capture the access process which is suspected to influence binding kinetics. Here, we applied unbiased molecular dynamics (MD) simulations to investigate the access of ligands to wild-type CYP2D6, as well as the allelic variant CYP2D6*53. In multiple simulations, substrates accessed the active site of the enzyme from the protein-membrane interface to ultimately adopt a conformation that would allow a metabolic reaction. We propose the necessary steps for ligand access and the results suggest that the increased metabolic activity of CYP2D6*53 might be caused by a facilitated ligand uptake. The allelic variant CYP2D6*53, which harbors the two amino acid mutations F120I and A122S, shows an increased metabolic rate towards several substrates in experiments indicating a pending designation as ultrarapid metabolizer (UM) phenotype7.Cytochrome P450 enzymes (CYPs) are essential proteins involved in the detoxification of foreign compounds reaching the human body. CYP2D6 accounts for the oxidative metabolism of roughly 25% of all marketed drugs and therefore belongs to the most relevant enzymes involved in phase I biotransformation. In addition, the enzyme is subject to a high interindividual variation in metabolic performance due to a genetic polymorphism. In drug therapy, this can ultimately lead to either severe adverse effects or the suppression of a therapeutic effect14. These tunnels are believed to influence both the poorly understood substrate specificity and binding kinetics of CYPs15. As the prediction of CYP metabolism is of major importance for drug development1, the influence of enzyme tunnels on small molecule binding has been intensively investigated17. Available experimental methods have only limited applicability for the determination and characterization of enzyme tunnels or complex transport phenomena. While crystal structures only provide a static view of the protein and fail to capture dynamic events, techniques such as NMR spectroscopy can produce dynamic information on the conformations of a protein16. Nonetheless, atomic details on the dynamic uptake of CYP2D6 ligands has not yet been produced by any experimental method16. Computer simulations, on the other hand, have provided fundamental insight into the transport process of ligands in CYPs. Various molecular dynamics (MD) simulation techniques have been applied to study the dynamic tunnels and their capability to transport ligands in CYPs19. While most groups focused on the egress routes of ligands from the active site, only a handful of studies were focused on access routes19 which are likely to be different20. Due to the long timescale of such molecular processes21, biasing potentials have been applied in nearly all studies to increase the likeliness of a successful translocation. Although two studies applied unbiased MD protocols to study the access to a CYP, they were focused on a soluble, bacterial enzyme12. Studies with CYP2D6 were limited to the determination and characterization of enzyme tunnels independent of a particular ligand22. Overall, the access of ligands to mammalian CYPs is poorly understood and could not yet be observed in its full complexity in unbiased simulations.The active site of CYPs is located in a buried cavity inside the enzyme that is connected to the surrounding environment by tunnels14. Based on the spatial location of several tunnels at the protein-membrane interface and the rather lipophilic character of many CYP ligands, it was suggested that ligands may access the active site from the membrane compartment and leave it efficiently through solvent-facing tunnels20. For example, it was shown that the preferred position of ibuprofen relative to a membrane agrees with superficial entry points of access tunnels in CYP2C913. In another study, the spontaneous, non-reproducible insertion of a membrane lipid in an enzyme tunnel was observed10. No unbiased MD protocol was applied to confirm this hypothesis in a mammalian CYP, let alone in CYP2D6.In contrast to prokaryotes, mammalian drug-metabolizing CYPs are membrane-anchored and their globular domain is partially embedded in the membraneμs of unbiased MD simulations with the aim to study the access of ligands to the buried active site of CYP2D6 in a model of the full-length structure of the enzyme anchored and partly embedded in a biological membrane2. In eight simulations, we observed substrates accessing the buried active site cavity of the enzyme via specific tunnels located at the protein-membrane interface. We propose the key steps governing a successful access of the ligand. Further, the results support the pending designation of the allelic variant CYP2D6*53 as a cause for ultrarapid metabolizer phenotype based on a more efficient ligand uptake compared to the wild-type.In this study, we performed over 20 23. Simulations of events such as ligand binding can not only improve our understanding of fundamental molecular processes, but can also be used to estimate binding affinities and residence times of drug candidates24. Specifically for CYPs it was shown that distinct tunnels, predominantly located at the protein-membrane interface, connect the buried active site to its surrounding environment. Together with the general hydrophobicity of CYP substrates, this led to the widely discussed hypothesis of ligand access from the membrane20. Although, this hypothesis could not yet be proven based on a complete, unbiased trajectory of a ligand accessing the active site, it was supported by a study applying accelerated MD simulations to CYP3A4. However, the used technique might not have accounted for the exact dynamics of the system due to the biasing potential25. Further, the accordance of other simulation techniques involving biasing potentials to conventional MD is not inherently given as it was shown for adaptive sampling methods26. Therefore, unbiased simulations could serve as a blueprint to validate accelerated simulations and other biased simulation techniques that can then be used to tackle complex issues such as the determination of drug binding affinities. Previously, unbiased simulations were limited to the soluble, bacterial Camphor 5-monooxygenase (CYP101A1) meaning that the involvement of the membrane could not be considered27. Here, we conducted unbiased MD simulations to investigate the access of ligands to CYP2D6 in a membrane-anchored model. We were able, for the first time, to observe the complete translocation of a ligand from the solvent to the buried active site cavity of a mammalian CYP in multiple simulations  that would ultimately result in a metabolite in agreement with experiment31. In simulation #4, two ligands occupied the binding site simultaneously and one molecule was accommodated distant (>10 Å) from the heme. Further, simulation #8 with the wild-type structure did not result in a pose that was in agreement with metabolism of APAP.In two simulations, we observed two ligands entering the active site consecutively. Notably, we observed only one, with 1.42 ne Movie . The oth2. Here, we evaluated key parameters and proved their accordance to our previous observations and experimentally derived literature values , describing the general preference of ligands towards a hydrophobic environment, revealed a peak around 2.5 for CYP2D6 ligands  during the nine simulations with APAP included in this analysis. Site H1 corresponded to a pocket around helices C, E, and H similar to the described allosteric site in CYP101A1, while site H2 highlighted a broad surface around helices F and A as well as the β sheet 4 close to the entrance of tunnel 2f  from the ligand during the exploration of the active site such as the movements of the HI loop. In general, structural adaptations and protein flexibility are not only important to improve our understanding of the structural mechanism behind ligand access8, but are also crucial to be considered in molecular docking calculations35. Even though MD-simulations are regularly used in a supporting role to post-process and refine poses obtained from docking, it was recently suggested that docking might even be replaced by MD-based techniques36. Since our simulations lead from an unbound state to a bound state in the active site, this further supports these suggestions. Additionally, the results from docking APAP and BTD indicated, that the poses generated by flexible docking were strongly dependent on the used receptor structure 42, leading to a favorable contribution for its desolvation. This suggests the partial desolvation of BTD as a favorable contribution toward its translocation. The, in this case, negligible influence of the conformational flexibility  phenotype for this allelic variant, which is usually only granted to phenotypes resulting from gene duplication7. Similar to our previous observations, tunnel 2b had a wider average bottleneck radius in CYP2D6*53 compared to the wild-type, likely due to the F120I mutation located at the entrance to the active site2. Further, the ligand access was faster in the CYP2D6*53 variant compared to the wild-type (Table Measurements of the enzymatic activity of allelic variant CYP2D6*53 have revealed increased metabolic rates towards bufuralol, dextromethorphan, and N-desmethyltamoxifenThe results presented here revealed the atomic mechanism of ligand uptake to the buried active site of membrane-anchored CYP2D6 from the protein-membrane interface. The ligands APAP and BTD accessed the enzyme via different enzyme tunnels, which supports the notion of multiple functional tunnels within a single protein system. The tunnels varied in their burying depth in the membrane which would allow ligands differing in lipophilicity to access the active site. However, presumably due to the relative bulkiness of DEB, CZX and PPF and their increased partitioning towards the membrane core, the simulations with these ligands did not result in any binding events in this timescale. We show that the access process is linked to conformational adaptations of the protein backbone that can occur either in close proximity or in significant distance from the ligand molecule. While the conformational change at tunnel 4 followed an induced-fit mechanism, we also observed motions of residues that could be better described by a conformational selection model suggesting that both processes can occur in CYP2D6 depending on the tunnel. Together with the fact, that our simulations lead from an unbound to a bound state in a fully flexible unbiased manner, we support the use of MD-based techniques as opposed to docking, which stands in accordance with recent suggestions in the literature. Further, we show that the uptake process is mainly driven by hydrophobic interactions with a secondary role for polar contacts during recognition and translocation of the ligand molecules. In addition, the binding process was potentially facilitated by a modest desolvation of the active site. The difference in burying depth, physicochemical properties, and geometrical features of the tunnels influence their capability to transport certain ligands and therefore likely influence the specificity of the enzyme. Similarly, our results indicate that the increased metabolic rates of the allelic variant CYP2D6*53 might be caused by an efficient uptake of ligands compared to the wild-type enzyme. Our study could serve as a blueprint for simulations employing biasing potentials and it proves the capability of unbiased MD simulations to study ligand transport processes.2. After randomly distributing multiple substrates in the solvent space around the enzyme, we performed over 20 μs of total unbiased MD simulations with multiple replica systems and various ligands with the aim to study ligand partitioning and to observe a translocation from the bulk solvent to the buried active site of the enzyme. All simulations were performed using the Desmond engine44. To determine the enzyme tunnels, we used CAVER 3.045. For the subsequent calculations, we either used workflows included in the Schrodinger Small-Molecule Drug Discovery Suite46 or in-house routines. For a complete set of detailed materials and methods, please refer to SI Methods.As a starting point for our simulations we used our previously validated full-length model of wild-type CYP2D6 and CYP2D6*53 anchored to a membraneSupplementary Information


Aquaporin-4 (AQP4) is a water channel expressed on astrocytic endfeet in the brain. The role of AQP4 has been studied in health and in a range of pathological conditions. Interest in AQP4 has increased since it was discovered to be the target antigen in the inflammatory autoimmune disease neuromyelitis optica spectrum disorder (NMOSD). Emerging data suggest that AQP4 may also be implicated in the glymphatic system and may be involved in the clearance of beta-amyloid in Alzheimer’s disease (AD). In this review, we will describe the role of AQP4 in the adult and developing brain as well as its implication for disease. AQP4 belongs to a family of channels that is selectively permeable to water. AQP 1, 4 and 9 are expressed in the mammalian brain ,3. This A growing numbers of neurological conditions are now associated with an alteration in AQP4 expression or localization. An imbalance in water homeostasis in the brain has been associated with pathological conditions such as traumatic brain injury and stroke ,10. IncrA loss of AQP4 polarization in perivascular astrocytic endfeet such as occurs in many brain injuries, may result in BBB breakdown. This may be particular relevant for the aging brain and Alzheimer’s disease (AD) . In contrast to the role of AQP4 in the adult brain, little is known about the role of AQP4 during early development in the fetal brain. In this review, we will discuss the role of AQP4 in health and will share some novel insights from pathological conditions involving AQP4. There are scant data about the role of AQP4 during development. Since AQP4 is expressed in the adult brain on astrocyte endfeet, AQP4 expression during development is mostly considered to be linked to the time astrocytes appear in the brain. In the early postnatal phase of development, astrocytes have been described to contribute to postnatal angiogenesis and the formation of the BBB . TranscrIn the CNS, AQP4 is highly expressed in the perivascular astrocyte foot processes and glial limiting membrane and at lower levels in perisynaptic astrocytic processes ,3,18. ThAQP4 monomers are ~30 kDa . Each moIn addition to the relevance of OAP, little is known about the regulation of the polarized expression of AQP4 at the perivascular endfeet. It has been hypothesized that AQP4 interacts with α-syntrophin or agrin, which both show polarized expression in astrocyte endfoot processes . ContactConstitutive AQP4 deficient mice as well as glial-conditional AQP4 deficient mice have been used to understand the role of AQP4 in the brain ,36.AQP4 deficient mice revealed a role for AQP4 in cognition and memory. These mice show cognitive deficit in the object location memory test  and a spOne study suggested that AQP4 deficient mice have an impaired BBB, decreased tight junction proteins and swollen astrocyte endfeet , yet, otAQP4 deficient mice show a more pronounced phenotype under certain insults or injury. When the role of AQP4 in brain water balance was studied in non-stressed conditions, no obvious change in water homeostasis was observed in vivo . In contOver recent years, interest in AQP4 has increased due to the discovery that it is the target antigen in the neurological autoimmune disease Neuromyelitis spectrum disorder (NMOSD) ,44. NMOSAs the presence of AQP4-IgG is an important biomarker for NMOSD, which can predict disease development ,47 and aCell based assays are now considered the gold standard for AQP4-IgG testing ,31,32,53It is suggested that the higher binding affinity of AQP4-IgG to OAP is associated with structural changes in the AQP4 epitope upon array assembly  or enhanIt is not clear whether the antibodies by themselves are sufficient to cause pathology, or whether ongoing inflammation is required. CNS reactive T cells may be important to breach the BBB and allow antibody entry into the brain . In rodeIt has also been proposed that patients with NMOSD have, in addition to anti-AQP4 antibodies, anti-endothelial antibodies that can breach the BBB . Using aSeveral mechanisms can account for the tissue damage following the binding of AQP4-IgG to AQP4 expressed in the brain. The mechanism for which there is most evidence is complement dependent cytotoxicity (CDC) ,69, in wSome studies have suggested that rodent complement, particularly mouse, may not be sufficient to activate human antibody mediated CDC ,73. HumaNew evidence suggests that AQP4-IgG can also induce complement independent pathologies ,67,68,75Understanding the mechanisms of tissue destruction caused by AQP4-IgG will pave the way for therapeutic intervention. To date most patients with NMOSD receive immunosuppressive medications. Acute symptoms are commonly treated with Methylprednisolone or plasma exchange ,77,78. ABlocking the binding of pathogenic AQP4-IgG through administration of non-pathogenic AQP4-IgG that lacks CDC and ADCC is emerging as potential therapeutic intervention in NMOSD , which wHydrocephalus is a pathologic condition in which increased CSF accumulation in the ventricles often results in increased pressure. Untreated hydrocephalus can lead to brain swelling, brain damage and death. Hydrocephalus is usually caused by impaired clearance of CSF outflow from the brain into the circulatory system. l-alysophosphatidylcholinestearoyl injection, upregulation in AQP4 expression in astrocytes, both on astrocytic endfeet and on the entire membrane of the astrocyte was recorded [Animal models have implicated AQP4 in both hydrocephalus initiation and resolution. The role of AQP4 depends on the disease stage and brain region. In models that use kaolin to induce acute hydrocephalus, there is an increase of AQP4 expression ,87. In arecorded . AQP4 derecorded  and kaolrecorded . In patirecorded . In addirecorded  as well recorded . While it is clear that AQP4 has a role in hydrocephalus, it remains unclear whether AQP4 has a protective or deleterious effect. It may contribute to hydrocephalus development at the initial disease stage or be important for edema resolution at a later time point. In addition, AQP4 is considered to have different roles for cytotoxic brain edema, vasogenic brain edema, and hydrocephalus, which may reflect to the different sites where water is accumulated in these conditions. This needs to be resolved before addressing a potential treatment approach that would limit water flow into the brain and accelerate outflow into the systemic circulation by modulating AQP4 and might diminish the need for a surgical intervention. With the elucidation of the glymphatic  system in 2012 as a system of waste clearance for the brain , severalAQP4 is also implicated in regulating glutamate transporter-1 (GLT-1) function. Astrocytes in AQP4 deficient mice have reduced GLT-1 levels as well as reduced glutamate clearance, which in turns affects synaptic plasticity and memory since function can be rescued by a potent GLT-1 stimulator . This fuAlterations in AQP4 expression or loss of polarization, or both, is now reported in many diseases . In someAQP4 function, particularly regarding its role in brain water balance, may differ in different brain areas. Moreover the consequence of AQP4 dysfunction may depend on the stage of the disease that is being studied. Rodent models trying to elucidate the role of AQP4 in different disease models can therefore be conflicting. Moreover, it is emerging that AQP4 helps regulate glutamate levels and GLT-1 expression . More wiAQP4 inhibitors or down regulators may provide future potential treatment of some conditions such as for cytotoxic brain edema . 2-(nicoTherapeutic strategies need to address access of AQP4 modulators across a functionally intact BBB, since not all pathological conditions are associated with impaired BBB. Aquaporumab is an example of an AQP4-targeted antibody therapeutics . This isIt is abundantly clear that the functions of AQP4 in the CNS are more diverse and more complex than previously appreciated. Targeted therapeutics with maximum benefit and limited toxicity will depend on a thorough understanding of the biology or AQP4 in health and in the myriad pathologic conditions that we know include aberrant AQP4 expression.


Background and purpose — Little is known about heterogeneity in early recovery after primary total hip arthroplasty (THA). Therefore, we characterized subgroups of patients according to their hip function trajectory during the first 6 weeks after THA in a fast-track setting.Patients and methods — 94 patients  from a single hospital participated in a diary study. Patients recorded their severity of hip problems  weekly for 6 weeks after THA. Latent class growth modelling (LCGM) was used to identify patients with the same hip function trajectory and to compare these subgroups on patient characteristics.Results — LCGM revealed a fast (n = 17), an average (n = 53), and a slow (n = 24) recovery subgroup. Subgroups differed on the estimated weekly growth rate during the first 2 weeks , with fewer differences between groups in the last 4 weeks . Patients in the slow recovery group could be characterized as women of older age (mean age =69) who rated their health as lower preoperatively, needed more assistance during recovery, and were less satisfied with the outcomes of the surgery.Interpretation — We identified distinct recovery trajectories in the first 6 weeks after fast-track primary THA which were associated with patient characteristics. Between 7% and 15% of patients are dissatisfied with the results of total hip arthroplasty (THA)   by the same orthopedic surgeon.Discharge criteria for all patients were functional and evaluated by a doctor, a physiotherapist, and a nurse. Patients had to be able to walk 30 meters with crutches or walker, to climb stairs if they were able to walk with crutches, to dress independently, and to go to the toilet independently. Adequate pain relief had to be achieved by means of oral medication before discharge, assessed with a numeric rating scale  for pain below 3 at rest and below 5 during mobilization. Last, the wound had to be dry, or nearly dry, and the patient should not experience dizziness or nausea.A diary method was used for data collection; patients received a booklet after discharge with a variety of questions regarding their recovery, which they had to complete every day. To reduce patient burden not all questions were assessed daily. Preoperatively (approximately 1 week before surgery) a subset of questions was probed as part of standard routine.Patients who were planned for primary unilateral THA between February 2015 and October 2015 were considered eligible for inclusion. Exclusion criteria were an insufficient command of the Dutch language, being mentally disabled, and a prosthesis in another joint of the ipsilateral or contralateral lower limb placed within 6 months before THA surgery. Of the 144 eligible patients, 43 did not participate in the study . Of the 101 included patients, 7 were excluded from analyses for various reasons.The main outcome measure of this study was reported severity of problems with the operated hip, as measured with the Oxford Hip Score (OHS). Higher scores (0–48) indicate better functioning and less pain. Patients had to complete the OHS questionnaire at 1 week before surgery and once every week starting on the 7th day after discharge.We assessed a variety of patient characteristics to explore whether the identified subgroups based on OHS trajectories match the profile of a “typical” patient. These variables can be divided into preoperative or pre-discharge characteristics, healthcare utilization and assistance during the 6-week recovery period, and postoperative patient-reported experience measures (PREMs) after the 6-week recovery period.Preoperative demographic and patient characteristics included age, sex, BMI, and whether the patient lived alone. Preoperative radiographic OA severity was assessed by the last author (SV) using the Kellgren–Lawrence (K–L) grading (0–4) system. The Charlson comorbidity index (CCI) and the American Society of Anesthesiologists (ASA) physical status classification system (1–4) were used as co-morbidity measures. Health-related quality of life was measured with the EQ-5D (5L). All 5 individual domain scores (1–5) were used, where a higher score indicated more problems, as well as the overall health Visual Analog Scale . Length of stay (LOS) in hospital was recorded, as well as surgical complications.Once a week patients recorded in their diary whether they had a physiotherapy session, a visit to the doctor, whether they needed aids  to walk inside or outside their house and whether they received help  with personal hygiene or with housekeeping. Pain medication was recorded daily.At the end of the 6-week recovery period patients completed the PREMs in their diary. They indicated on an 11-point scale how satisfied they were with the results of surgery (0–10). On several 5-point scales they indicated their satisfaction with the general result of surgery, current pain, activities of daily living, and their quality of life. In addition, we asked whether they would opt for THA surgery again if needed (yes/no) and if they would recommend it to others (yes/no). Patient’s attitude towards fast-track THA, provided support during recovery, and the information provided were also assessed through yes/no questions.https://www.statmodel.com/version6.12.shtml) was used to handle missing data. LCGM is an extension to latent growth curve models, which are commonly used to assess inter-individual differences in intra-individual change   old and 56 were women . Almost Supplementary data). The entropy values all exceeded the minimum of 0.8, indicating that the classes were sufficiently distinct from each other.As can be seen from the BIC values and the outcomes of the BLRT, model fit improved by adding classes up to the 4-class model , as well as an average (Class 2) and fast recovery group (Class 1), and statistical fit improved. Even though fit improved even further in a 4-class model, clinical interpretability did not improve. In this model the average recovery subgroup in the 3-class model was divided into 2 separate subgroups (Class 1 and 2) differing only marginally from each other in their initial growth rate. We therefore chose the 3-class model for further analyses.The average change in OHS from baseline until week 6 for the fast recovery group was 23, for the average recovery group 19, and for the slow recovery group 9.9 . The biggest difference between the classes became apparent in the first 2 weeks of recovery. Both the fast (Class 1) and average recovery group (Class 2) showed a steep initial increase in reported functioning of the operated hip in the first 2 weeks, levelling off in the subsequent 4 weeks. The levelling off phase was a little more pronounced in the fast recovery group. In stark contrast, the slow recovery group showed a slow and steady improvement, lacking the exponential increase in the first 2 weeks. In addition, growth seemed to already level off after week 4. It is also notable that the classes were similar in their preoperative baseline OHS.There were distinct differences between the 3 different early recovery trajectory classes in preoperative characteristics, healthcare utilization and assistance during recovery, and postoperative PREMs.The largest class of patients  can be characterized as slightly overweight patients (average BMI =27) with an average age of 65, having an average preoperative movement-evoked NRS pain score of 7 and staying on average 1 night in hospital after surgery. Patients in this class on average did not report mental health problems preoperatively or problems with self-care, but they did report slight problems with mobility, usual activities, and pain. For the majority of the 6-week recovery period they used walking aids, attended weekly physical therapy sessions, and took pain medication. After 6 weeks they were highly satisfied with the results of the surgery. In the subsequent analyses we compared the other smaller classes with this dominant class.The patients in Class 1 (fast recovery) were younger (mean age =59) and were operated more often in an outpatient setting. During the 6-week recovery they used pain medication and required walking aids for a shorter period (median =3 weeks) than patients in the average trajectory class (median =5 weeks).Patients in Class 3 (slow recovery) were more often female (four-fifths) and older (mean age =69) than patients classified in the average recovery trajectory. They were less often operated on in an outpatient setting and rated their overall health as lower and reported more hip pain at rest before the surgery. More patients already had another prosthesis, and although not statistically significant, co-morbidities (ASA and CCI) were more common. Compared with the average recovery class patients required more weeks with personal hygiene assistance (median =6 weeks) and longer use of walking aids outside (median =5 weeks). After the 6-week recovery period patients were less satisfied with the results of the surgery and were also less positive about the support provided during recovery.In this prospective cohort study we identified 3 different trajectories of early recovery after primary unilateral THA in a fast-track setting.In the slow recovery group, healthcare utilization and assistance during recovery was higher, in combination with lower satisfaction of provided care. Preoperatively, health perception was more negative and patients reported more pain at rest. Together with being older and having more co-morbidities, clinicians might describe this group of patients as being more “difficult” (Hahn et al. At the other end of the spectrum the subgroup of patients displaying a fast recovery presented a very different profile. The majority of these patients left hospital on the day of surgery. In line with their pronounced improvement in pain and function during the first 2 weeks after discharge, they used pain medication and walking aids for a much shorter period of time than the average patient subgroup. Their quick recovery may in part be explained by having fewer co-morbidities and their younger age. However, these patients did not rate their health as better, or have less pain preoperatively. Perhaps being scheduled for the outpatient treatment and meeting the discharge criteria to leave on the same day as the surgery may have instilled more positive recovery expectations. Positive outcome expectations can enhance the effects of medical treatments (Crow et al. Our results underscore the need for tailored care and provide directions to achieve such an outcome. Patients fitting the slow recovery trajectory were less satisfied with the surgery and less positive about the support provided during recovery. Although we are not able to tell what kind of support this subgroup of patients wanted, their higher healthcare utilization suggests unfulfilled needs when it comes to pain management and assistance with daily activities. This is in line with previous work stressing the importance of postoperative pain management after THA to improve patient satisfaction (Bergés et al. The most important limitations concern the generalizability of our findings and that we did not try to identify potentially important preoperative psychosocial predictors of early recovery. Being an exploratory study with a relatively small sample size, replication of our findings in other larger samples in different settings is essential.Previous studies have pointed to the importance of psychosocial predictors of responses to arthroplasty, such as pain catastrophizing or psychological distress (Vissers et al. In summary, 3 distinct subgroups of patients were identified with markedly different recovery rates. By comparing these groups we were able to develop preliminary patient profiles of early recovery. Our study demonstrates the necessity to further explore the specific needs of these different subgroups, as well as clinical and psychosocial predictors of early recovery.supplementary data in the online version of this article, http://dx.doi.org/ 10.1080/17453674. 2018.1519095The authors are grateful to all the patients for their efforts in completing their diaries, and especially thank N. de Esch for her help during the study.JP performed data analysis, wrote and revised the manuscript, NM designed the study, supported data analysis and reviewed the manuscript. LK supported data collection and reviewed the manuscript. JE helped composing the diary, performed data collection, and reviewed the manuscript. MM supported the data analysis and reviewed the manuscript. SV designed the study, operated on all patients and reviewed the manuscript.Acta thanks Henrik Husted for help with peer review of this study.