Plant defense activators offer advantages over pesticides by avoiding the emergence of drug-resistant pathogens. However, only a limited number of compounds have been reported. Reactive oxygen species (ROS) act as not only antimicrobial agents but also signaling molecules that trigger immune responses. They also affect various cellular processes, highlighting the potential ROS modulators as plant defense activators. Establishing a high-throughput screening system for ROS modulators holds great promise for identifying lead chemical compounds with novel modes of action (MoAs).We established a novel in silico screening system for plant defense activators using deep learning-based predictions of ROS accumulation combined with the chemical properties of the compounds as explanatory variables. Our screening strategy comprised four phases: (1) development of a ROS inference system based on a deep neural network that combines ROS production data in plant cells and multidimensional chemical features of chemical compounds; (2) in silico extensive-scale screening of seven million commercially available compounds using the ROS inference model; (3) secondary screening by visualization of the chemical space of compounds using the generative topographic mapping; and (4) confirmation and validation of the identified compounds as potential ROS modulators within plant cells. We further characterized the effects of selected chemical compounds on plant cells using molecular biology methods, including pathogenic signal-triggered enzymatic ROS induction and programmed cell death as immune responses. Our results indicate that deep learning-based screening systems can rapidly and effectively identify potential immune signal-inducible ROS modulators with distinct chemical characteristics compared with the actual ROS measurement system in plant cells.in-silico screening methods for identifying plant ROS modulators hold the potential to facilitate the development of diverse plant defense activators with novel MoAs.We developed a model system capable of inferring a diverse range of ROS activity control agents that activate immune responses through the assimilation of chemical features of candidate pesticide compounds. By employing this system in the prescreening phase of actual ROS measurement in plant cells, we anticipate enhanced efficiency and reduced pesticide discovery costs. The The online version contains supplementary material available at 10.1186/s13007-023-01118-7. Development of pesticides, such as herbicides, fungicides, and plant defense activators, has been drastically decreasing because conventional visual selection methods to explore useful pesticide candidates from compounds are experimentally time-consuming and expensive . Additio2˗•, H2O2, OH•, and 1O2) are partially reduced or excited forms of atmospheric oxygen that are thought to play crucial roles in plant cells ) due to the wide range of chemiluminescence values, spanning approximately 9.5–540,000. ROS modulators were selected by converting the ROS production of each compound to a logarithmic scale and sorting the changes in ascending order. As shown in Fig. 10[4.67] that showed a sharp change in activity among all compounds were identified as ROS modulators. The ROS production data used in this study are presented in Supplementary Information  data on a vast collection of approximately seven million commercially accessible compounds with diverse synthesizable frameworks from the Namiki Shoji Chemical Cupid database. Next, we performed in silico screening of these compound datasets to explore ROS modulator candidates by inferring the magnitude of ROS production.A GTM is a highly utilized and powerful technique employed for the visualization and reduction of dimensionality in data . It emplNicotiana tabacum L. ‘Bright Yellow 2’) cultured cells were maintained through weekly dilutions (1/100) of cells in modified Linsmaier and Skoog medium, as described previously ) were selected and consolidated as candidate compounds. This system enabled the analysis of one million compounds per day, resulting in 2500 times faster screening speed than that of our previous method [Using a ROS inference model, we established an in silico screening system for ROS modulators. A flowchart illustrating the in silico screening system based on the ROS inference model developed in this study is presented in Fig. s method .Fig. 4InOverall, 8476 compounds were selected from a vast pool of seven million compounds as potential candidates for ROS modulators based on in silico screening using the ROS inference model , and 16 and 21 chemicals were selected from the selected compound groups at each screening stage, respectively. Five control compounds (random compounds) were also randomly selected from 7 million commercially available compounds using a random-number generator. Approximately 56.3% of the potential ROS modulators (9 out of 16 compounds) selected in the first screening stage based on the ROS inference model induced high ROS production triggered by cryptogein in tobacco BY-2 cultured cells compared to that of the DMSO control (Fig. To verify whether the potential ROS modulators predicted using the in silico screening system exhibited high ROS activity, we evaluated the effects of the selected compounds on cryptogein-induced ROS production mediated by NADPH oxidase in tobacco BY-2 cultured cells Fig. a. The evOverall, our data suggest that DNN-based screening systems can be used to rapidly and effectively identify potential immune signal-inducible ROS modulators with distinct chemical characteristics compared with the actual ROS measurement system.Plant defense activators are analogs of the defense hormone salicylic acid, which protects plants from pathogens by activating the plant immune system –51. CompWe investigated whether the selected compounds could act as ROS modulators in whole plants and in other plant species. As shown in Fig. ROS have direct antimicrobial properties and also serve as signaling molecules that activate further immune responses . When cuOur results indicate that accurate ROS prediction by our inference model based on DNN learning is possible for a group of compounds with a certain degree of similarity in chemical characteristics to the candidate compounds used for training Fig. . In contin planta (Figs. Conventional chemical screening of whole plants requires large quantities of chemicals, may be costly, and requires a strictly controlled growth space. ROS are antimicrobial products but also serve as signaling molecules that activate immune responses and have multiple physiological action points in cells, indicating that ROS modulator have the potential to function as a plant defense activator, and the high-throughput screening system of ROS modulator is strongly expected to create lead chemical compounds with novel MoAs. In this study, we established a novel in silico screening system for ROS modulators using deep learning-based prediction of ROS accumulation combined with the chemical properties of the compounds as explanatory variables. The importance of this strategy was demonstrated by identifying candidates for ROS modulators that might function as potential plant defense activators with novel MoAs ta Figs. , 7, 8, 9Additional file 1: Table S1. ROS and chemical features data of the library.Additional file 2: Table S2. The ROS peak height and time of Fig. 8a.


Magnetic sphincter augmentation (MSA) is a surgical intervention for well-characterized gastroesophageal reflux disease (GERD), where the esophagogastric junction barrier is augmented using a bracelet of magnetized titanium beads. MSA could be an attractive option for patients with documented GERD who wish to avoid long-term pharmacologic therapy or whose symptoms are not adequately managed with lifestyle modifications and pharmacologic therapy. The ‘ideal’ MSA patient is one with prominent regurgitation, without dysphagia or esophageal motor dysfunction, with objective evidence of GERD on upper endoscopy and/or ambulatory reflux monitoring. Appropriate candidates with significant hiatus hernia may pursue MSA with concomitant hiatus hernia repair. The increasing adoption of MSA in the GERD treatment pathway reflects research that shows benefits in long-term outcomes and healthcare costs compared with other established therapies in appropriate clinical settings. Gastroesophageal reflux disease (GERD) carries a high symptomatic and economic burden, with estimated prevalence of 9–28% in Western populations,,  In typical GERD presentations of heartburn, chest pain and/or regurgitation and without alarm symptoms, a pragmatic initial approach consists of an empiric PPI trial.,  Further evaluation in endoscopy-negative (unproven) GERD may include ambulatory reflux monitoring performed off PPI therapy, where findings of elevated distal esophageal acid exposure time , high numbers of reflux events (>80), and/or low distal mean nocturnal baseline impedance (<1500 ohms) may constitute stand-alone evidence for GERD.,  In selected patients with confirmed or proven GERD, where symptoms and/or complications are inadequately managed with lifestyle modifications and pharmacologic therapies, endoscopic and surgical antireflux interventions are management considerations.MSA was first introduced into clinical practice approximately a decade ago,Despite regurgitation representing the primary symptomatic target of the pivotal MSA studies, there is ample evidence that heartburn in the context of proven GERD also improves with MSA. Moderate to severe heartburn decreased from 89% at baseline to 12% at 5 years in a well-characterized international cohort treated with MSA.The pivotal studies that evaluated MSA excluded patients with high body mass index (BMI), large hiatus hernias, prior foregut surgery, and/or complications of GERD. The modern-day invasive options for patients with morbid obesity include Roux-en-Y gastric bypass (RYGB), which can reduce GERD symptoms, including regurgitation, by disconnecting the major portion of the acid-producing stomach from continuity with the esophagus.,  As post-MSA dysphagia is the most common reason for device removal,Rarely, achalasia spectrum disorders can present with symptoms mimicking GERD. Esophageal high-resolution manometry (HRM) serves to exclude achalasia spectrum disorders prior to invasive reflux management and needs to be performed prior to MSA for similar reasons.,  ,  The multiple rapid swallow (MRS) maneuver during HRM can be particularly helpful in this setting, through assessment for contraction reserve, defined as augmentation of esophageal body contractile vigor following MRS compared with supine wet swallows.,  Therefore, the ideal patient for MSA has proven GERD (with endoscopic and/or ambulatory reflux monitoring evidence), without dysphagia or significant esophageal motor dysfunction apparent on HRM, with predominant regurgitation symptoms despite optimal medical management and without significant hiatus herniation (unless concomitant hernia repair is considered) .4,  30 AThere has been interest in the expansion of potential indications for MSA to include ongoing reflux in post-surgical patients, such as after sleeve gastrectomy, RYGB, or myotomy for achalasia . AlthougWhile RYGB represents a more effective bariatric intervention for reflux than sleeve gastrectomy due to disconnection of most of the acid-producing stomach from the esophagus as discussed above, regurgitation from the gastric pouch can persist, and remain refractory to medical management. MSA implantation has been described after RYGB with promising results.A primary management option for achalasia spectrum disorders is Heller myotomy, at which time a partial fundoplication is typically performed given decreased esophageal clearance of refluxate in the setting of esophageal motor dysfunction. MSA may have a potential role as an antireflux intervention with Heller myotomy or following per-oral endoscopic myotomy (POEM). However, more data are needed to better understand the risks of dysphagia with MSA implantation representing an obstruction in the setting of esophageal aperistalsis typical of achalasia, as well as any potential increase in risk of MSA device erosion in the setting of prior myotomy.Although rigorous outcome data are lacking, there has also been interest in expanding indications for MSA to patients with weakly acidic reflux. Among 67 patients with preoperative weakly acidic reflux detected on pH-impedance monitoring, with median follow-up of 24 months, GERD-HRQL improved from 20 to 2, with symptom improvement of 95% for heartburn and regurgitation, similar to outcomes noted in those with GERD.Patients with Barrett’s esophagus tend to have significant reflux and could have less esophageal perception of reflux compared with patients without Barrett’s esophagus.While the initial data for MSA were acquired in patients without significant EGJ disruption , there may be a role for MSA with concomitant hernia repair in the setting of larger hernias. One prospective study of 200 patients with hiatus hernias >3 cm in size treated with MSA at the time of hernia repair reported complete independence from PPI in 94% at a median follow-up of 9 months, with improvement in median GERD-HRQL from 26 to 2.The potential utility of this combined intervention has also been demonstrated with longer-term outcome data. In one cohort of 192 total patients with MSA with median follow-up of 20 months, mean GERD-HRQL improved from 19 to 5; a subset of 52 patients with larger hernias (≥3 cm in size) who underwent combined MSA and hiatus hernia repair demonstrated a more profound improvement in mean GERD-HRQL of 21 to 4, and <10% required post-MSA PPI therapy.The primary mechanism by which MSA prevents reflux is by augmenting EGJ barrier function and by keeping the LES/EGJ closed, thereby preventing retrograde flow of gastric content. The closing force from the magnetized titanium beads can be overcome by intact esophageal peristalsis propelling an ingested bolus through. However, if the closing force is higher than what can be easily overcome by esophageal peristalsis, bolus retention can occur, and the patient presents with post-MSA dysphagia. The same consequence can be expected if there are alternate structural or motor etiologies for dysphagia that are overlooked on the preoperative work-up.Dysphagia is therefore the most common side effect reported after MSA. Within a cohort of 380 patients, rates of persistent dysphagia >3 months after MSA was 16%.If dysphagia persists or worsens after MSA despite conservative management and endoscopic dilation, one management option is device removal. Among the first approximately 30,000 devices implanted globally, the 7-year cumulative risk of explantation was estimated at 4.8%, with smaller sizes more likely to be explanted for etiologies that included dysphagia or odynophagia (48%) and persistent GERD (21%).Promising longer-term outcomes over follow up of 5 years and longer are now available for MSA. Follow-up of 33 patients 5 years after MSA demonstrated mean GERD-HRQoL score improvement from 26 to 3, with complete PPI discontinuation in 88% of these patients.n = 631) comparing MSA and fundoplication over 3 years demonstrated similar improvements in GERD-HRQoL scores, PPI discontinuation, and satisfaction, but higher proportions in the MSA group were able to vomit as needed (91% vs. 68%).Studies comparing MSA to fundoplication generally demonstrate at least equivalent outcomes.While we are not aware of any published direct or randomized comparisons between MSA and transoral incisionless fundoplication, a meta-analysis including 24 studies with 1942 patients found comparable improvements in GERD-HRQoL scores (78–80%), with greater proportions with improvement in regurgitation (91% vs. 73%) and PPI discontinuation (91% vs. 64%) for MSA compared with transoral incisionless fundoplication.An economic budget impact model for a hypothetical commercial insurance population of 1 million members over a 1-year time horizon estimated a net cost savings of $111,367 with introduction of MSA compared with medical management or laparoscopic Nissen fundoplication, primarily driven by the avoidance of hospital admission.Overall, outcomes appear comparable between MSA and other invasive antireflux interventions, with preserved ability to belch or vomit, and lesser gas-bloat compared with laparoscopic fundoplication.When the optimal patient is carefully identified , MSA represents a valid management option in the GERD treatment pathway and may have benefits over traditional laparoscopic fundoplication. While significant hiatus herniation previously represented an exclusion criterion for MSA, there is accumulating evidence supporting a role for combined MSA and hiatus hernia repair for patients with EGJ disruption. Emerging data also show increased adoption and uptake of MSA, suggesting equivalency or even benefit in terms of healthcare costs compared with alternate GERD management options. While further high-quality data around long-term outcomes and safety, comparisons with other antireflux interventions, and predictors of clinical success are warranted, MSA represents a valuable option in the GERD management algorithm.


Injectable surgical sealants and adhesives, such as biologically derived fibrin gels and synthetic hydrogels, are widely used in medical products. While such products adequately adhere to blood proteins and tissue amines, they have poor adhesion with polymer biomaterials used in medical implants. To address these shortcomings, we developed a novel bio-adhesive mesh system utilizing the combined application of two patented technologies: a bifunctional poloxamine hydrogel adhesive and a surface modification technique that provides a poly-glycidyl methacrylate (PGMA) layer grafted with human serum albumin (HSA) to form a highly adhesive protein surface on polymer biomaterials. Our initial in vitro tests confirmed significantly improved adhesive strength for PGMA/HSA grafted polypropylene mesh fixed with the hydrogel adhesive compared to unmodified mesh. Toward the development of our bio-adhesive mesh system for abdominal hernia repair, we evaluated its surgical utility and in vivo performance in a rabbit model with retromuscular repair mimicking the totally extra-peritoneal surgical technique used in humans. We assessed mesh slippage/contraction using gross assessment and imaging, mesh fixation using tensile mechanical testing, and biocompatibility using histology. Compared to polypropylene mesh fixed with fibrin sealant, our bio-adhesive mesh system exhibited superior fixation without the gross bunching or distortion that was observed in the majority (80%) of the fibrin-fixed polypropylene mesh. This was evidenced by tissue integration within the bio-adhesive mesh pores after 42 days of implantation and adhesive strength sufficient to withstand the physiological forces expected in hernia repair applications. These results support the combined use of PGMA/HSA grafted polypropylene and bifunctional poloxamine hydrogel adhesive for medical implant applications. Synthetic and biological meshes are widely used in surgical practice, particularly for hernia repair. A hernia occurs when abdominal organs or tissues, such as the small intestine, bulge through a weakened or damaged abdominal wall. This can cause pain and discomfort, and, if untreated, can result in part of the small intestine becoming incarcerated within the abdominal wall or strangulated from inadequate blood supply . HerniasMore than 90% of incisional and inguinal hernias involve placing surgical mesh fabricated from medical-grade polymers at the site of the hernia . Polypro® or Tissucol®  has been shown to potentially reduce pain and improve overall post-operative outcomes compared to standard suture or tack fixation for inguinal hernia repair . Th. Th® T11To evaluate the applicability of this hydrogel adhesive to hernia repair surgery, it was tested with multiple types of PP mesh, but the adhesive strength was lower than the adhesive strength for collagen tissues ,32. It w® fibrin sealant  in a rabbit abdominal hernia repair model. A retromuscular repair was performed on five rabbits that mimicked the totally extra-peritoneal (TEP) surgical technique used in humans for hernia repair. After 42 days in situ, we characterized mesh slippage and contraction using gross assessment and imaging. Following the explant on day 42, we measured mesh fixation strength using tensile mechanical testing and assessed biocompatibility using histology.In this study, we compared the in vivo performance of our novel bio-adhesive mesh system, consisting of PGMA/HSA grafted polymer mesh secured with our bio-adhesive hydrogel, versus the performance of unmodified PP mesh secured with TisseelSurface modifications are part of an emerging trend toward improved bio-functionality of surgical mesh polymers ,44 and bWe successfully anchored a bio-plastic HSA protein layer onto the PP mesh surface using a “grafting to” surface modification technique ,36,37,41® 1107 (T1107), a bifunctional poloxamine four-arm poly (propylene oxide)-poly (ethylene oxide) (PPO-PEO) block co-polymer was first partially acrylated to form T1107-ACR and unreacted arms were further modified by coupling NHS to form T1107-ACR-NHS , 1.8–2.1 ppm (b) , 3–2.5 ppm (e) and 3.5–4.7 ppm (c) , and 3.3 ppm (d) . It confirmed the synthesis of the targeted PGMA , methylene , functional ends , and acryloyl . T1107 has approximately 19 propylene oxide monomer units and 60 ethylene oxide monomer units for each arm and the NMR peak areas were 298 and 57, respectively, consistent with predicted calculated values . QualitaThe bifunctional poloxamine hydrogel adhesive was made using polymer solutions consisting of T1107-ACR and T1107-ACR-NHS in 1x PBS, with the final formulation containing a 30 wt% mixture of 75 wt% T1107-ACR (ACR conversion: 92%) and 25 wt% T1107-ACR-NHS (ACR conversion: 30%). The polymer solution was left in a cold room under continuous orbital mixing overnight and then stored refrigerated and in vials covered in aluminum foil to avoid light exposure. The polymer solution required chemical crosslinking via a Michael-Type addition reaction using DTT as the thiol donor crosslinker. DTT solutions were prepared fresh at a concentration of 3 mg of DTT in 10 μL of PBS. The polymer solution and DTT solutions were transported to the animal facility on ice in an insulated cooler.To make the bifunctional poloxamine hydrogel adhesive, polymer solutions and DTT solutions were mixed at a thiol to acrylate molar ratio of 1:1, and vortexed for at least 5 s immediately before surgical use in the implantation of the mesh. Because the thermal gelation temperature of the poloxamine hydrogel adhesive was room temperature, the bifunctional poloxamine hydrogel adhesive was kept on ice (~4 °C) at the point of use ,31.All animal work was reviewed and approved by the Institutional Animal Use and Care Committee (IACUC) at Clemson University (protocol number AUP2019-022). The experimental work was conducted in compliance with ethical principles and animal care standards established by the US Animal Welfare Act regulations and US Public Health Service (PHS) policy for the Humane Care and Use of Laboratory Animals. The University has an Animal Welfare Assurance on file (assurance number D16-00435) with the NIH Office of Laboratory Animal Welfare. The rabbits were housed at the animal facility, which is registered with the US Department of Agriculture and undergoes annual inspection by that agency, for a mandatory 14-day acclimatization period before the study and throughout the 42-day study period. The rabbits were given free access to water and food with 12-h cycles of light and dark under centrally controlled and monitored ambient temperatures, airflow, and pressure differentials. There were 5 rabbits assigned to the experimental group (mesh implants) and one rabbit assigned to the control group (sham-operated without mesh). All rabbits were anesthetized using acepromazine 1.1 mg/kg and isoflurane in oxygen 4–5%.® fibrin sealant applied across the mesh surface with the provided applicator. The rabbit in the control group was incised as described but not implanted with mesh. The anterior fascia was then closed in the midline with 3–0 polydioxanone suture in a running fashion and the skin was sutured with 3–0 polydioxanone sutures.At implantation, each rabbit was operated on using a retromuscular repair, as previously described in a rabbit model , to mimiThe rabbits were euthanized on day 42, and the skin was resected to expose the implant sites. The implant sites were photographed in situ with a transparent calibration grid overlay to assess mesh slippage and contraction . The mesMesh slippage and contraction at the implant sites were grossly assessed in situ immediately after euthanasia and skin resection and were visualized using calibrated digital images (300 DPI) acquired under ambient lighting conditions . Mesh slThe adhesive strength was measured consistent with ASTM F2255-05  and ASTM F2256-05  using a 23 N load cell . Sections designated for mechanical testing were tested within two hours of euthanasia. Sections were quickly removed from the cold PBS-saturated gauze, and all testing was performed at 37 °C. For lap shear testing, the sub-dermal muscle of each section was mounted to a 1 cm × 3 cm aluminum sample holder and then firmly clamped into the test rig, and the opposite edge of the mesh with intraperitoneal muscle was firmly clamped to the load cell fixture . For T-pThe adhesive strength was defined as the peak load divided by the gauge length measured at the tissue/mesh/adhesive interface. The gauge length was the contact area of the mesh–tissue interface for lap shear testing and the contact width of the mesh–tissue interface for T-peel testing. The maximum load required to disrupt the mesh from the tissues was recorded, and the adhesive strength was calculated for n = 2 mesh types per rabbit and n = 1 muscle tissue margin without mesh per rabbit. The type of test performed was determined by the amount of tissue available for clamping, but some sections could not be tested , so not all rabbits had all data points.Specimens designated for histology were cut into two 1.5 cm pieces, placed into tissue cassettes, and processed for paraffin embedding using an automated tissue processor. Microtomed sections (5 μm thick) were mounted on glass slides and stained using standard histological protocols. Stains included hematoxylin and eosin to identify signs of an inflammatory response and foreign body reaction, Masson’s trichrome to identify fibrous connective tissues and degree of collagen synthesis, and Herovici’s stain to differentiate immature and mature collagen. The host tissue response was quantitatively graded in a blinded manner.Representative digital images of the stained slides (4 images per mesh per rabbit for each stain) were generated using a transmitted light microscope  equipped with a digital camera . We acquired images at 2.5× magnification that were subdivided into a grid of 64 regions and then used a random number generator to select 8 individual regions for quantitative analysis.Selected regions were imaged at 20× magnification and analyzed using image analysis software . Images were post-processed using preset algorithms (“background subtract” and “adjust levels” to accommodate variations in light microscopy and provide uniform brightness. Hue analysis was performed based on published methodology . Briefly


When multiple viral populations propagate within the same host environment, they often shape each other’s dynamics. These interactions can be positive or negative and can occur at multiple scales, from coinfection of a cell to co-circulation at a global population level. For influenza A viruses (IAVs), the delivery of multiple viral genomes to a cell substantially increases burst size. However, despite its relevance for IAV evolution through reassortment, the implications of this positive density dependence for coinfection between distinct IAVs has not been explored. Furthermore, the extent to which these interactions within the cell shape viral dynamics at the level of the host remains unclear. Here we show that, within cells, diverse coinfecting IAVs strongly augment the replication of a focal strain, irrespective of their homology to the focal strain. Coinfecting viruses with a low intrinsic reliance on multiple infection offer the greatest benefit. Nevertheless, virus-virus interactions at the level of the whole host are antagonistic. This antagonism is recapitulated in cell culture when the coinfecting virus is introduced several hours prior to the focal strain or under conditions conducive to multiple rounds of viral replication. Together, these data suggest that beneficial virus-virus interactions within cells are counterbalanced by competition for susceptible cells during viral propagation through a tissue. The integration of virus-virus interactions across scales is critical in defining the outcomes of viral coinfection. The co-occurrence of distinct virus populations within a single host occurs commonly, when an individual acquires a second infection before a prior one has been cleared. Under these circumstances, each virus can influence the replication of the other, positively or negatively. These interactions can involve viruses of different species but here we focus on interactions between distinct influenza A viruses (IAVs). For IAVs, coinfection is important to viral evolution and emergence because it can result in the formation of novel, chimeric viruses. We find that two IAVs infecting the same cell often interact synergistically, such that replication is improved compared to a singular infection. Conversely, when monitoring viral dynamics within a mammalian model, we see that virus-virus interactions at the level of the whole host are antagonistic. Our data suggest that, when viruses are propagating through a population of cells, beneficial interactions within cells are counterbalanced by competition for susceptible target cells. This antagonistic interaction is likely a major factor limiting the formation of chimeric IAVs during coinfection. The past three influenza A virus (IAV) pandemics arose through reassortment involving human and non-human IAVs in coinfected hosts –6. Due tWhen viruses coinfect the same host or cell, each can affect the other’s replication. These virus-virus interactions can occur between conspecific viruses (as investigated herein) or taxonomically distinct viruses. They furthermore range from antagonistic to beneficial, depending on the context. At the cellular scale, viruses may compete directly for limited resources within the cell or indirectly through the triggering of antiviral responses. These antagonistic effects are typically potent in the case of defective viral genomes . ConversOur prior work focused on virus-virus interactions between homologous IAVs. We previously reported that coinfection of a cell with multiple IAV particles is often required to initiate a productive infection . FurtherHere, we investigate what viral traits define the extent to which a coinfecting IAV can augment the replication of another. Specifically, we examine the importance of a coinfecting virus’ intrinsic reliance on multiple infection, the host species to which it is adapted, and its homology to the focal virus. To this end, we evaluated the outcomes of coinfection with a set of previously well-characterized IAV strains that vary in host adaptation and reliance on coinfection: influenza A/guinea fowl/Hong Kong/WF10/99 (H9N2) (GFHK99), A/mallard/Minnesota/199106/99 (H3N8) (MaMN99), A/Netherlands/602/2009 (H1N1) (NL09), and A/Panama/2007/99 (H3N2) (Pan99) viruses (16). Our results indicate that homology and host adaptation are not critical for defining IAV-IAV interactions within cells. Conversely, IAVs having a low intrinsic reliance on coinfection more effectively augment replication of the focal virus. While these beneficial interactions are readily detected when infection is limited to a single viral generation, under conditions that allow further propagation, antagonistic effects become predominant. Dynamics in vivo and during multiple rounds of viral infection in cell culture suggest that competition for target cells and superinfection exclusion typically limit the opportunity for distinct viral populations to interact within cells.Previously we showed that influenza A virus replication is strongly dependent on viral density. Namely, progeny production is enhanced when population density is sufficient to ensure delivery of many viral genomes to a cell. The extent of this dependence was, however, noted to vary with virus strain. To investigate the importance of this phenotype for interactions between distinct coinfecting strains, we sought to identify a panel of viruses that vary in their reliance on multiple infection. To this end, we evaluated the sensitivity of viral RNA (vRNA) replication to multiplicity of infection (MOI) for a diverse set of IAV strains, including two of avian-origin and two of human-origin. This was done by infecting Madin Darby canine kidney (MDCK) cells with a wild type (wt) virus at a consistent dose of 0.005 genome copies (GC) per cell and infecting simultaneously with increasing doses of a homologous virus, termed var. The var virus carries synonymous mutations to allow differentiation of its genome from that of the corresponding wt virus. Coinfections were limited to a single cycle of infection to ensure that results reflected processes occurring within cells. In line with previous observations, GFHK99wt virus replication is enhanced ~100-fold by co-inoculation with GFHK99var virus . HoweverTo date, our examination of IAV density dependence has centered on homologous interactions that would occur within a given viral population. Here, we sought to test whether the positive effects of increased density would extend to coinfection with distinct IAV strains. Although virus-virus interactions would typically be bi-directional, for the purposes of our experimental design, we measure the impact of coinfection on only one strain in the pairing, referred to here as the focal virus.influenzavirus A is not required for beneficial interactions within the cell  or NL09, MaMN99, or Pan99 virus, then quantified levels of GFHK99wt genomes in the cells. These coinfections were again limited to a single cycle to ensure that results reflected processes occurring within cells. The results show that GFHK99wt genome levels increase with increasing doses of every coinfecting var virus, indicating that phylogenetic relatedness within the genus the cell . Howeverthe cell  while cothe cell . These rTo more rigorously examine how the intrinsic reliance on multiple infection displayed by a coinfecting virus modulates its impact on a focal virus, we used a mutant strain of GFHK99 virus. We previously showed that introduction of a PA K26E mutation into the GFHK99 strain reduces reliance on multiple infection . We confTo test the extent to which the beneficial interaction observed in our cell culture model shapes viral dynamics in vivo, we used a guinea pig model. Mimicking the experiments in cell culture, guinea pigs were inoculated simultaneously with a low dose of GFHK99wt virus and increasing doses of GFHK99var or GFHK99 PA K26E viruses. The titer of GFHK99wt virus was assessed in daily nasal wash samples. Contrary to expectation, GFHK99wt virus replication over the course of the infection was suppressed by the coinfecting virus: relative to GFHK99wt-only controls, GFHK99wt virus vRNA levels were lower during coinfection with either GFHK99var or GFHK99 PA K26E viruses .Unlike in cell culture, multiplicity of infection cannot be controlled in vivo and mixing of coinfecting viruses can be constrained by spatial structure, limiting the potential for cellular coinfection ,19–21. TTaken together, these experiments revealed that the dynamics of coinfecting viruses within an intact animal host are antagonistic. Combined with our cell culture experiments, which indicate that beneficial interactions occur within individual coinfected cells, these data suggest that either the enhancement of focal vRNA replication within cells is not translated into increased viral release or that antagonistic interactions occurring at a higher spatial scale are predominant.To assess whether beneficial virus-virus interactions within cells results in increased virus release, we evaluated the impact of coinfection in cultured cells by quantifying focal viral genomes in both infected cells and released progeny in the supernatant. Similar to the experiments outlined above, a low dose GFHK99wt virus and a high dose of a homologous var or heterologous GFHK99 PA K26E, MaMN99, or NL09 viruses were used. After 24 h, GFHK99wt virus genomes within cells and in the supernatant containing released progeny virions were quantified. Under the conditions of MOI used and at this time point, GFHK99wt virus genome replication in the cells was enhanced during coinfection with MaMN99var and NL09var viruses, but not with GFHK99var or GFHK99 PA K26E viruses . HoweverThe cell culture-based experiments outlined above were all performed under conditions that limited viral replication to a single round, an approach that allows tight control of MOI and detection of intra-cellular virus-virus interactions. Concomitantly, this strategy eliminates the potential for coinfecting viruses to modulate each other’s dynamics during spread through the cellular population. To better understand the dynamics observed in vivo, we therefore adopted a cell culture model in which multiple cycles of viral replication could occur, thereby allowing virus-virus interactions at this higher spatial scale.Thus, cells were infected at low MOIs in medium conducive to multicycle replication. GFHK99wt virus was used at an MOI of 0.005 GC/cell and GFHK99var or GFHK99 PA K26E virus at an MOI of 0.1 GC/cell. GFHK99wt virus replication was monitored up to 48 h post infection. Consistent with minimal interaction between these relatively small viral populations early in the infection, GFHK99wt virus replication was comparable with or without coinfection up to 24 h post infection . HoweverTo further evaluate this concept, we tested the impact of modulating the timing of coinfection on the replication of a focal virus. Here, cells were pre-inoculated at varying times up to 24 h before infection with GFHK99var or GFHK99 PA K26E virus at a high MOI and with GFHK99wt virus at a low MOI. The replication of the focal virus, GFHK99wt, was then assessed. This experimental design was chosen to model a situation in which most cells were infected  by the coinfecting virus prior to introduction of the focal virus. Thus, the potential for cellular coinfection would be high only if cells remain susceptible to infection at the time of GFHK99wt virus introduction. The results show little change to GFHK99wt replication when the coinfecting virus was added up to 4 h before GFHK99wt virus. However, there is a significant decrease in GFHK99wt replication as the interval between infections was increased . These dOur results reveal that, within cells, IAV coinfection can be strongly beneficial. The extent of benefit is not primarily defined by a coinfecting virus’s native host or its homology to the focal strain. Not all coinfecting viruses confer an equal benefit, however, and the magnitude of the benefit is defined by the coinfecting strain’s intrinsic reliance on multiple infection. Despite this clearly cooperative effect within cells, virus-virus interactions at the level of the whole host are largely antagonistic, as competition for susceptible target cells dominates at this scale. Examination of this effect in cell culture suggests that this negative interaction arises at least in part because coinfecting viruses access potential target cells asynchronously, leading to competition for a limited supply of susceptible cells.Our data suggest a model in which dominant virus-virus interactions differ at the within-cell and within-host scales . Within For IAVs, cellular coinfection is beneficial in large part because it allows complementation of (very common) incomplete viral genomes, increasing the likelihood of productive infection ,15,24. IAt the within-host scale, our data reveal a competitive effect wherein the virus introduced at a higher dose or an earlier time point suppresses the replication of the other. Similar dynamics have been reported previously. In particular, superinfection exclusion, in which the replication of the secondary virus diminished if it is introduced outside of a somewhat narrow time window, is well documented. The duration of the window observed here (4–8 h) is in line with previous work ,22,23,25in vivo  as injected into the bottom of the tube and the sample was centrifuged (Beckman Coulter Optima XL-100K Ultracentrifuge) at 25,000 rpm for 2 h at 4°C. The resultant viral pellet was resuspended in PBS and RNA extracted using the Qiagen Viral RNA mini kit and protocol instructions.MDCK cells were seeded into T75 flasks at 5 x 10Female Hartley strain guinea pigs weighing 300–350 g were obtained from Charles River Laboratories  and housed by Emory University’s Department of Animal resources. Prior to intranasal inoculation, nasal lavage and euthanasia, guinea pigs were anesthetized by intramuscular injection with 30 mg/kg ketamine and 4 mg/kg xylazine. Guinea pigs were inoculated intranasally with IAV in 300 μl PBS. Daily nasal washes were performed up to 6 d post GFHK99wt inoculation. Briefly, with the animal’s nose suspended in a downward orientation over a Petri dish, 1 mL PBS was instilled into the nares in 200 μl increments and allowed to drop back out. Liquid was pooled into a 1.5 mL tube, aliquoted and stored at -80°C.RNA was extracted from cells and viral samples using the Qiagen RNeasy mini kit and the Qiagen Viral RNA mini kit, respectively, using included protocol instructions. Extracted vRNA was reverse transcribed using a 1:1 ratio of universal influenza primers  S2 Tabl and MaxiAll statistical analyses were performed in R (version 1.3.959). Log transformed values for genome copy numbers and the mean of technical replicates were used for statistical analyses.S1 Fig(Related to (TIF)Click here for additional data file.S2 Fig3 GC and increasing doses of GFHK99var (A) or GFHK99 PA K26E (B) virus. The viral titer in nasal washes collected from each guinea pig is plotted and the limit of is indicated by the dashed line. Guinea pig ID numbers are shown in grey boxes appended to each facet.(Related to (TIF)Click here for additional data file.S3 Fig4 GC of either GFHK99var (A) or GFHK99 PA K26E (B) virus either 12 or 24 h prior to a dose of 104 GC of GFHK99wt virus. The viral titer in nasal washes is plotted and the limit of detection is indicated by the dashed line. Guinea pig ID numbers are shown in grey boxes appended to each facet.(Related to (TIF)Click here for additional data file.S4 FigLevels of defective viral genomes (DVGs) were quantified by ddPCR using primers targeting the terminal and internal regions of the PB2, PB1, PA, and M gene segments. Ratios of terminal to internal copies that are <2.0 indicate low DVG content. Virus stocks tested are named above each facet. Two different stocks of GFHK99wt virus were used.(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S1 Data(XLSX)Click here for additional data file.


Our work provides functional evidence for epigenetic targets contributing to endometriosis risk and pathogenesis. Data generated serve as a valuable resource for understanding tissue-specific effects of methylation on endometrial biology in health and disease.Endometriosis is a leading cause of pain and infertility affecting millions of women globally. Herein, we characterize variation in DNA methylation (DNAm) and its association with menstrual cycle phase, endometriosis, and genetic variants through analysis of genotype data and methylation in endometrial samples from 984 deeply-phenotyped participants. We estimate that 15.4% of the variation in endometriosis is captured by DNAm and identify significant differences in DNAm profiles associated with stage III/IV endometriosis, endometriosis sub-phenotypes and menstrual cycle phase, including opening of the window for embryo implantation. Menstrual cycle phase was a major source of DNAm variation suggesting cellular and hormonally-driven changes across the cycle can regulate genes and pathways responsible for endometrial physiology and function. DNAm quantitative trait locus (mQTL) analysis identified 118,185 independent  A comparison of genetic variation among a large dataset of patients with confirmed and without endometriosis shows differences in DNA methylation profiles linked to stage III/IV endometriosis, sub-phenotypes and menstrual cycle phase. It is associated with pain and infertility, affects an estimates 190 million women and contributes hundreds of billions of dollars to healthcare costs globally4. Pelvic disease likely derives from retrograde menstruation of steroid hormone-sensitive endometrial cells that elicit inflammation, neuroangiogenesis, fibrosis, and scarring7. Disease classification is based primarily on lesion appearance and location without correlation to symptoms or responses to surgical and hormonal therapies, and molecular classifications of disease subtypes are wanting. Although mechanisms driving the pathogenesis and pathophysiology of this heterogeneous disorder are largely unknown, studies suggest that diverse endometrial cellular components of women with disease respond abnormally to cyclic steroid hormones and exhibit aberrant signaling pathways, gene expression, decreased apoptosis, enhanced proliferation, and an inflammatory phenotype as compared to controls9. A recent genome-wide association meta-analysis identified disease-associated genomic loci in women with versus without endometriosis involving sex steroid and hormone signaling pathways, inflammatory pathways, oncogenesis and angiogenesis, with greater effect sizes observed in those with more advanced disease stage10. Genetic risk factors for endometriosis have also been associated with other reproductive traits including irregular menses, uterine fibroids, and ovarian cancer11.Endometriosis is a common, estrogen-dependent, inflammatory disorder defined by the presence of endometrial-like tissue at extra-uterine (ectopic) sites, commonly within the pelvis12. Endometrial whole methylome and candidate gene DNAm profiles in bulk tissue and select cell populations identify genes involved with steroid hormone dependence and abnormalities in women with versus without endometriosis. However, most results fail to be replicated due to limited sample size, cellular heterogeneity in bulk tissue specimens, poor cycle phase assignments, and limited clinical metadata18. Notably, aberrant candidate gene promoter DNAm includes HOX-A1019, steroid hormone receptors (PR and ESR1)20, CYP19/aromatase14, SF-116, and COX-217 and altered expression of DNMTs18. DNA methylome-wide studies that use a small number of samples have suggested DNAm profiles differ in patients with endometriosis—both between endometriosis lesion and eutopic endometrial tissues, and compared to eutopic endometrium of women without disease23. One study of 16 patients with and without endometriosis was designed not to test the hypothesis of differential DNAm between cases and controls but to quantify intra-tissue variation and determine sample sizes necessary for large-scale discovery;21 a second study evaluated the DNAm in 17 patients with endometriosis and 16 controls, across the menstrual cycle and noted marked phase- and disease-dependent signatures9. Both studies determined that menstrual cycle phase accounted for the majority of variability in DNAm patterns within the endometrium. Estradiol, progesterone, and their combination were found to regulate genome-wide DNAm signatures and gene transcription in endometrial stromal fibroblasts isolated from eight women with endometriosis (four with stage I/II and four with stage III/IV disease) and seven women without endometriosis, with marked aberrances in endometriosis patients8. Other recent small studies on genetic regulation of endometrial gene expression 24 and DNAm 25 demonstrate associations between specific genotypes and expression of genes in signaling pathways and between DNAm sites near GREB1 and KDR, genes involved in endometriosis pathogenesis.While genetic variation underpinning complex disease etiology is actively studied, epigenetic processes such as acquired alterations in DNA methylation (DNAm) are increasingly recognized as providing an important biological link between individual exposures and disease-specific phenotypesn = 637) and women without endometriosis (n = 347). Importantly, the dataset is based on patients with well-documented clinical annotation, demographic characteristics, and symptomatology28. Our robust analysis reveals factors affecting epigenetic regulation in endometrium associated with endometriosis risk and disease heterogeneity and provides an important data resource for reproductive medicine.This study reports global DNAm profiles and networks in endometrium associated with endometriosis, menstrual cycle and genetic variation using data collected from a large sample of patients with surgically and histologically confirmed endometriosis (No Uterine or Pelvic Pathology (NUPP) controls)) contributed to the analyses .Eutopic endometrial samples from 1074 women were included. Following sample quality control (QC) filtering, 984 participants  and DNAm in endometrium (16.1%).Using residual maximum likelihood analyses we estimated the proportion of variation in endometriosis case-control status captured by all genome-wide DNAm sites and compared this to the variation captured by genetics  and regional association analyses were performed using a set of linear models. Genome-wide DNAm was measured across 759,345 DNAm sites in 984 samples using the Illumina Infinium MethylationEPIC Beadchip  had higher DNAm in stage III/IV cases and passed the threshold for Bonferroni-corrected significance for a single test (P < 6.58 × 10−8). We also conducted an analysis of cases compared to the restricted NUPP control group. Only one site  with lower DNAm on chromosome 11 in cases, and one site on chromosome 19  with higher DNAm in stage III/IV cases, passed the threshold for Bonferroni-corrected significance for a single test. Differences in DNAm at cg02623400 and cg0201172 were only nominally significant when restricted to NUPP controls.Overall, we observed no significant difference (at genome-wide threshold) in single site or regional methylation signals between cases and controls. As effect sizes for many genetic risk factors are consistently greater in patients with rASRM stage III/IV disease33 was used to identify clusters (modules) of highly correlated DNAm sites that are associated with menstrual cycle phase or endometriosis case:control status. Thirty five DNAm modules were identified based on the WGCNA clustering of the DNAm profiles  with menstrual cycle phase and four with endometriosis case:control status tus Fig. . Genes atus Fig. . These ptus Fig. . The toptus Fig. ; Fig. 2.cis-mQTLs were identified in endometrium across 107,627 DNAm sites following Bonferroni correction . Stepwise regression identified 118,185 independent cis-mQTL signals, evidence that some sites are regulated by multiple independent genetic variants. In total, mQTLs for 90,856 DNAm sites were not reported in endometrium previously25. There was evidence of mild genomic inflation in test statistics (lambda = 1.16). This is, however, consistent with inflation observed in differential DNAm models and is likely the result of residual variation from unknown mediators of variation in DNAm in endometrium. We were able to replicate 98% of endometrial mQTLs previously reported in a small preliminary study (n = 66)25. The proportion of variance captured by DNAm sites can be driven by genetics given the presence of endometrial mQTLs. To estimate of the proportion of variance captured by DNAm, independent of known genetic regulation, DNAm sites with mQTLs were removed and the variance captured by DNAm was re-calculated. In the absence of genetically regulated DNAm sites 15.4% of the variance was captured by DNAm , brain (p < 5 × 10−8), muscle (p < 5 × 10−8), or adipose tissue  and may represent tissue-specific genetic regulation  associated with endometriosis status. Similarly, we found evidence of significant association between the effects of 12 mQTLs and menstrual cycle phase  and different effects on the same gene in different tissues were also observed (e.g. ADK in lung vs colon). Expression of several of these genes  has been associated with risk of endometriosis previously42. Expression of four of the genes  was also significantly associated with endometriosis risk when SMR analyses were conducted using the eQTL and GWAS summary statistics (Supplementary Data r2 > 0.8).To identify any associations between genetic regulation of DNAm in endometrium and risk of endometriosis, we integrated summary statistics from both endometrial mQTLs and an endometriosis genome-wide association (GWA) meta-analysis including 31,021 cases and 524,419 controls  was located in an active chromatin area predicted to interact with EEFSEC and RUVBL1 in immortalized endometrial cells  , lesion type  and three different pelvic pain symptoms: dyspareunia (pain with intercourse), acyclic pain, and dyschezia (bowel movement pain). To minimize the number of tests conducted and maximize the a-priori chance of detecting signals, we focused the analysis on 11,698 sites within 500Kb± of 44 SNPs previously found to be genome-wide significantly associated with endometriosisp < 4.3 × 10−6) across all comparisons, only one DNAm site—located in ADAMTSL2 on chromosome 9 (cg13469396)—was significantly different, comparing cases with acyclical pain only vs. NUPP controls. When a less stringent threshold was applied (p < 0.05/N of DNAm sites per GWAS locus) a total of 66/11,698 DNAm sites showed differential DNAm with at least one of the sub-phenotypes  with a lead endometriosis-associated risk variants in these regions.Adopting a genome-wide Bonferroni-corrected threshold   is in high LD (r2 = 0.97) with an endometriosis-associated variant in this locus (rs1903068) , as a symptom previously shown to be predictive of endometriosis−5) Fig. . One of NP rs123397 is in There was no evidence for systematic differences in effect sizes across all 66 DNAm sites comparing endometrioma or deep endometriosis with stage I/II vs. stage III/IV  test associations between differentially methylated DNAm sites and complex diseases51 and both causes and consequences of disease54. Our study of methylation signals in endometrium has a ten-fold increase in cases compared with previous studies25 and suggests individual changes in methylation signals associated with endometriosis will be small. For example, a recent comparison of 924 monozygotic and 1033 dizygotic twin individuals identified a signature of 243 epigenome-wide significant differentially methylated positions between MZ and DZ twins55. Effects of nominally significant differentially methylated sites between endometriosis cases and controls in our study  were much smaller than absolute differences in the MZ twin signature which ranged from 0.3 to 6%, with a mean of 2.2%55. This suggests even larger sample sizes would be needed to achieve sufficient power to detect the smaller effects.Variation in DNAm between individuals and populations can arise as consequences of environmental exposures, stochastic and genetic perturbations56 and 15–31% for amyotrophic lateral sclerosis57, to almost 100% for age. For our study, we have done our best to match our case and control groups by age and therefore have chosen not to include age as an additional surrogate variable. We do believe that the turnover of the uterus likely precludes age as a factor in DNAme, but this is something that could be explored in future studies. Although we did not identify significant individual signals, DNAm in endometrium was estimated to capture 15.4% of the variance in endometriosis case control status. On the flip side, the methylation differences attributable to the disease that we observe are quite low (0.03–0.08%). This suggests many small effects of methylation across the genome, or within pathways or networks of genes, may contribute to this variation. The ability to detect differentially methylated sites associated with disease may be attributed to amount, duration, and/or time of critical exposures and the expected effect size of these exposures. The critical window to quantify etiologically relevant differential methylation at DNAm sites in endometrium associated with risk may be prior to overt symptoms or diagnosis. Moreover, endometriosis case vs. control differences may be affected by cell-type composition of tissues, endometriosis disease heterogeneity or mediated by previous use of medications or behavioral changes to reduce symptoms59. Single-cell RNA-sequencing and deconvolution of bulk endometrial samples has highlighted signatures for cellular subtypes in endometrium that likely contribute to variation between samples62. However, in the absence of reference datasets for these cell-types appropriate corrections for cell-type composition cannot be applied to methylation analyses. Future investigations into cell type-specific effects may be facilitated by emerging technologies in single-cell epigenetics.Previous studies have estimated the amount of variation in complex traits captured by methylation, with estimates ranging from 0% for height, 6.5% for BMI32 and transcriptomic studies showing differences in endometrium of patients with stage III/IV versus stage I/II endometriosis support lower implantation and pregnancy rates in in those with more advanced disease in both natural and assisted reproduction cycles63. One of the genes annotated to these differentially methylated sites, EEF2 (eukaryotic translation elongation factor 2), is downregulated in ectopic endometriosis lesions64. Similarly, TNPO2 (Transportin 2), a nuclear transport receptor highly expressed in the ovary, uterus, testis and brain, is a predicted target of a microRNA found to be differentially expressed between ectopic and eutopic endometrial tissue65, and overexpressed in human ectopic endometrial epithelial cells66. ELAVL4 (ELAV Like RNA Binding Protein 4) encodes an RNA-binding protein with roles in post-transcriptional regulation of mRNAs and is predominantly expressed in neurons, pituitary, and testis and has been associated with neurodegenerative diseases, type 2 diabetes and prognosis of endometrial adenocarcinoma68. Interestingly, network analysis identified modules of DNAm sites associated with endometriosis case:control status. Genes annotated to these modules were enriched in WNT and MAPK signaling, adhesion and cancer pathways. Both the WNT and MAPK signaling pathways have been associated with endometriosis in previous expression studies and have been identified as potential treatment targets72. Consequently, larger sample sizes will be needed to identify changes in methylation signals in disease subtypes and account for differences across the menstrual cycle.In support of the effects of disease heterogeneity, we found evidence of genome-wide differences in methylation at four DNAm sites when cases were restricted to stage III/IV disease despite reduced power. Larger molecular effects in severe disease are consistent with genetic studies that show evidence of larger genetic effects in stage III/IV endometriosis73. Differences observed in this study are consistent with those reported in smaller studies on endometrium with the addition of many more differentially methylated sites as a result of increased power76. We validate previous observations of changes in methylation of DNA methyltransferases , hormone response genes  and genes associated with transcription regulation (e.g. RUNX3), decidualization  and embryo implantation 73. A recent study also highlighted the importance of epigenetic modifications during endometrial decidualization and whilst they did not observe methylation decidualization-associated genes  they did report increased level of histone H4 hyperacetylation in these regions during in vitro ESC decidualization77. Evidence suggests that changes in DNAm profiles across the menstrual cycle is a phenomenon that may be specific to endometrium and is not observed in blood73.Numerous DNAm sites distributed across the genome are differentially methylated in human endometrium across the menstrual cycle, with variation likely driven by cyclicity of cell differentiation and turnover, and tissue-specific response to circulating steroid hormones78, which contains 238 genes in total, representing a significant enrichment (p = 1.46 × 10−6). One of these genes (ABCC3) was annotated to a DNAm site differentially methylated between early and mid-secretory phases with lower methylation in the mid-secretory phase consistent with previous reports of higher gene expression78, suggesting that changes in DNAm may also influence endometrial receptivity to embryo implantation and/or the accuracy of estimating the window of implantation using these genes. Indeed, a recent review highlighted changes in methylation observed during the implantation window and the association of alterations in methylation with defective receptivity and implantation failure79. Interestingly, prior to correction with SVs we also observe variation in endometrial methylation associated with genetic ancestry however, given the small sample size of the non-European ancestral groups we lacked power to test for differences between ancestries. Future work in more diverse populations is instrumental in investigating ancestry-dependent effects. Consideration of changes in DNAm across the menstrual cycle is vital when assessing effects of regulation of molecular mechanisms on endometrial pathologies and fertility traits.Pathways enriched for genes annotated to DNAm sites differentially methylated between the proliferative and secretory phases reflect changes in endometrial function including cell cycle progression (RHO and CDC42 GTPase cycle) and tissue remodeling . Seventy-eight genes annotated to DNAm sites differentially methylated across the menstrual cycle are present on the Endometrial Receptivity Array (ERA)cis-mQTLs including >3000 potential tissue-specific mQTLs and numerous mQTLs associated with endometriosis risk. We identified 51 mQTLs, distributed in 21 genomic loci, that were significantly associated with endometriosis risk from the SMR analysis. Associations between endometriosis and QTLs at 10 loci have not previously been reported to the best of our knowledge41. These results provide evidence that endometriosis-associated variants have functional effects on endometrial methylation for ~40% of endometriosis risk loci identified in the most recent endometriosis GWAS10. This is more than that observed previously for eQTLs41, suggesting the genetic contribution to endometriosis may have a bigger effect on methylation and/or larger eQTL studies are needed in endometrial cell types to detect significant effects at these loci.Epigenetic regulation in endometrium has the potential to influence vital aspects of endometrial function, female fertility, and disease. Integration with genetic data identified 118,185 independent GREB1, and genes on chromosomes 1, 6, 12, and 17. GREB1 is an estrogen- and androgen-regulated gene which mediates cell proliferation and migration, and induces EMT in ovarian cancer80 and hormone-stimulated proliferation in breast cancer81. mQTLs significantly associated with endometriosis featured DNAm sites and SNPs located in predicted enhancers that interact with GREB1 in uterus and ovary including rs1865573 that is associated with a splicing (s)QTL for GREB1 in ovary reported in GTEx82, suggesting a possible role of alternative splicing of GREB1 in endometriosis susceptibility. Signals for mQTLs significantly associated with endometriosis on chromosome 1p36.12, including two potentially endometrial-specific mQTLs, were located in regulatory regions and associated with the expression of known genes of interest LINC00339, CDC42, and WNT442. Similarly, potential endometrial-specific endometriosis-associated mQTLs lie in a predicted promoter for CCDC170 and enhancer regions that may mediate regulatory effects on multiple genes in the chromosome 6q25.1–6q25.2 risk region. Expression of genes in this region is known to be highly correlated with nearby ESR1 expression in endometrium83. Finally, endometriosis-associated mQTLs associated with expression of GDAP1, SRP14, and HOXB9 are in moderate LD (r2 > 0.6) with SNPs significantly associated with endometriosis and with eQTLs for these genes in the recent endometriosis meta-analysis10.Examples of new evidence for known endometriosis target genes that warrant further discussion include r2 = 0.89) and rs6538618 (r2 = 0.99) respectively, risk SNPs shared between endometriosis and epithelial ovarian cancer. These mQTLs are located in predicted promoter regions for MLLT10 and a bidirectional promoter for VEZT and FGD6 and the latter is associated with expression of both genes in endometrium84. Epidemiological studies report an increased risk of ovarian cancer in women with endometriosis and recent genetic studies report a strong genetic correlation and causal relationship between endometriosis and specific epithelial ovarian cancer subtypes86.Genetic regulation of DNAm in endometrium may also influence other reproductive pathologies including cancer. Variants significantly associated with both endometriosis risk and DNAm in endometrium on chromosomes 10p12 and 12q22 were in LD with rs7084454 , cell adhesion, calcium signaling, and ECM receptor interaction, important for endometrial tissue integrity and differentiation, decidualization, embryo implantation, and establishment of early pregnancy91. To our knowledge this study is the largest collection of DNAm data from human endometrium with associated detailed clinical information, a powerful resource for advancing reproductive medicine.Characterizing endometrial specific genetic regulation is important when investigating functional effects of gynecological disorders and fertility traits. The majority of mQTLs we identified in endometrium have also been reported in blood, suggesting the genetic regulation of these DNAm sites is shared between tissues, consistent with tissue overlap reported in previous studies35. The complex relationship may instead be driven by genetic effects on other regulatory factors that affect DNAm and the trait through diverging pathways , reverse causation, cell-type or context specific effects or a non-linear causal path involving several interactions of regulatory features35. Context-specific genetic effects on DNAm in endometrium for several mQTLs varied between menstrual cycle stages and endometriosis cases and controls, warranting replication in independent datasets. Although we are unable to distinguish causal and pleiotropic pathways, we identified several endometrial mQTLs that were statistically significantly associated with endometriosis risk, providing further functional evidence for endometriosis target genes than previous studies in eQTLs41.An atlas of genetic effects on DNAm in blood generated from 32,851 individuals demonstrated that although many genetic signals are shared between DNAm sites and complex traits, altered DNAm signals are not necessarily on a causal path from genotype to phenotypeEEFSEC  on chromosome 3q21.3, SRD5A3 (steroid 5 α-reductase 3) on chromosome 4q12, ADK (adenosine kinase) on chromosome 10q22.2, and HOXC cluster on chromosome 12. Endometriosis-associated mQTL SNPs on chromosome 3q21.3 in EEFSEC are in LD with variants previously associated with gestational length, spontaneous preterm birth92 and age at menarche94, risk factors for endometriosis patients. Epigenetic marks and chromatin interactions suggest these mQTLs fall in EEFSEC promotor and enhancer regions in uterus and ovary, where the gene is highly expressed95, and immortalized endometrial cells97. In addition, methylation at DNAm sites located near the KDR promoter on chromosome 4 are associated with endometriosis risk and expression of nearby SRD5A3 in blood. KDR encodes vascular endothelial growth factor receptor 2 (VEGFR-2), a major mediator of angiogenesis, proliferation, migration, and differentiation of endothelial cells. Dysregulation of angiogenic activity in endometriotic lesions and the eutopic endometrium of women with endometriosis and is mediated by VEGF signaling99.New endometriosis target genes detected include ADK, an enzyme that regulates concentrations of extracellular adenosine and intracellular adenine nucleotides. Evidence from epigenetic marks suggests that one of these DNAm sites is located in the promoter region of ADK in fibroblasts, uterus and ovary and is in an anchor point for chromatin interaction with ADK in immortalized endometrial cells. Notably, adenosine nucleotides as targets for endometriosis pain management are currently under investigation100. Whether endometrial mQTLs or eQTLs for ADK influence eutopic endometrial tissue-specific inflammation in women with endometriosis is an attractive hypothesis and warrants further study100.Several mQTLs specifically associated with severe (rASRM stage III/IV) endometriosis including five on chromosome 10q22.2 are also associated with eQTLs for 10. The results showed multiple differentially methylated sites associated with surgical phenotypes in particular with rASRM stage III/IV and endometrioma, suggesting different genetic regulatory mechanism for this particular sub-type of endometriosis. Several of the associated DNAm sites were located in enhancer and promoter regions in uterus including enhancers predicted to interact with WT1 on 11q14, important in gonad development, and promoters for genes associated with genitourinary anomalies (MMPED2). Immunostaining evidence suggests WT1 is downregulated in the eutopic endometrium from women with endometriosis but is expressed in neurons of deep endometriosis44. Moreover, we identified that regulation of DNAm at cg24360069, in STK3 on 8q22, was associated with a greater extent of endometriotic pelvic disease, presence of dyspareunia, and had an mQTL in high LD with the lead GWAS variant at this locus. STK3 encodes Serine/threonine-protein kinase 3, which is part of the Hippo pathway that plays an important role in tumor suppression by reducing cellular growth and promoting apoptosis. Notably, for the pain subphenotypes, dyschezia had the largest number of DNAm sites. One of these, located in the promoter of KDR, had an mQTL in LD with the lead GWAS variant. The single genome wide significant DNAm site, associated with acyclical pain, was located within an exon of ADAMTSL2 on chromosome 9, a disintegrin and metalloproteinase with thrombospondin motifs and is suspected to interact with latent transforming growth factor beta binding protein 1.Detailed differential DNAm sub-phenotype analyses, based on surgically visualized disease phenotypes, endometriosis-associated pain symptomatology, and rASRM staging, could facilitate understanding mechanisms underlying particular biological sub-types of endometriosis and lead to stratified diagnosis and therapeutic target discovery. To maximize power of detection, given the relatively small sample size of sub-phenotype groups ranging from 50–600 cases, we focused sub-phenotype analyses on differential DNAm signatures linked to 44 endometriosis-associated GWAS lociThis study presents the largest and most comprehensive analysis of regulation of DNAm in the human endometrium. Menstrual cycle stage is a major source of variation in DNAm in endometrium—providing strong support for hormonally driven changes in DNAm across the cycle being associated with known changes in gene expression and pathways responsible for endometrial physiology, function, and dysfunction. We found no evidence for large site-specific DNAm differences between endometriosis cases and controls. However, variation in DNAm signals captured 15.4% of the variance in endometriosis case control status and differences at four DNAm sites were significant when cases were restricted to stage III/IV disease. We also report previously unreported disease-associated genetic effects on DNAm in endometrium that provide new insights into epigenetic regulation of pathways important for endometrial biology and function and identify target genes with a potential role in the causal pathway between genetic variation and endometriosis pathogenesis. Functional validation of these genomic targets may yield new therapeutic targets with the potential to disrupt pathogenic processes. Possible differences in DNAm associated with disease sub-phenotypes highlights the need to generate larger datasets with sample collection timed with menstrual cycle phase and comprehensive clinical information. Validation of methylation profiles associated with sub-phenotypes of disease may also allow molecular subtyping of disease that can be associated with patient outcomes to guide personalized disease management. Findings from this study will direct future endometriosis research and datasets generated will be a valuable resource for subsequent investigations into tissue-specific effects of methylation on endometrial biology and disease, and development of potential novel, targeted therapeutics.All participants provided the site-specific study investigator with informed consent. All patient data were de-identified and followed HIPAA and the Convention of the Declaration of Helsinki. This study was approved by the institutional review boards of UCSF , Michigan State University , University of Oxford, University of Melbourne and University of Edinburgh.n = 480 samples), University of Melbourne, Melbourne, Australia , Endometriosis CaRe Centre in Oxford, Oxford, UK , and EXPPECT Centre, The University of Edinburgh (EDIN), Edinburgh, Scotland, UK (n = 86 samples), with collection at all sites using the World Endometriosis Research Foundation Endometriosis Phenome and Biobanking Harmonization Project (WERF EPHect) standardized protocols for tissue collection and processing, and participant characteristics and clinical annotation  and no evidence of endometrial hyperplasia or cancer. Women without visualized endometriosis at the time of surgery or without a history of endometriosis were defined as controls: some of these had pelvic pain and documented uterine fibroids or other non-malignant gynecologic conditions including endometrial polyps, ovarian cysts, cervical abnormalities, and pelvic organ prolapse; a subset was defined as no uterine or pelvic pathology (NUPP) controls (n = 201) if they had no visualized or documented uterine or pelvic pathology. Controls were sourced from all four recruitment sites in roughly equal proportions to avoid bias , 389 controls without endometriosis and six participants with unconfirmed endometriosis status were recruited through the University of California San Francisco, California  metrics  before quantitative assessment of DNAm on the Illumina Infinium platform.Each participant contributed a single endometrial tissue sample. Primary tissue samples were stored as fresh frozen (FF) specimens in liquid nitrogen or at −80 °C. Samples from the contributing sites were combined at UCSF into two batches, prepared consistently and randomized among plates. Batch I consisted of 767 samples  from UCSF, UM, and ENDOX. Batch II consisted of samples from additional recruitment and included 307 samples  from all four sites , mid-proliferative (MP), late proliferative (LP), early secretory (ESE), mid-secretory (MSE), and late secretory (LSE) for all specimens. Not all cohorts had assigned proliferative substages and as such all proliferative samples were consolidated as PE. A small number of samples (n = 23) were not assigned a secretory substage and were assigned SE. If two phases were found in reports or on review of histology, the later phase was selected . Serum estradiol (E2) and progesterone (P4) facilitated phase assignments, and sometimes two or more pathologists re-reviewed the histology. Unsuitable samples  were excluded. Benign histology descriptor and unknown were assigned as unknown in the absence of last menstrual period (LMP) and/or serum E2 and P4 levels  Ligand Core). Endometrial samples from women with a history of endometriosis but no disease identified at surgery were not considered as controls and were not suitable for DNAm quantification, and thus were excluded from that analysis. All four sites completed histology assessments and/or cycle phase determinations for their respective sample specimens.Cycle phase was assigned using the criteria of Noyes et al.:Site: A categorical variable with a unique value for each of the five sample contributing sites/institutions . Cycle phase: A categorical variable with a unique value for each of the six menstrual cycle phases defined previously . Endometriosis case:control status: A binary variable assigning samples as either a case or control. Sample plate: A categorical variable with a unique value for each of the 12 sample plates used during processing. Batch: A binary variable assigning samples as either Batch I or II.Variables across all site-specific datasets were combined and harmonized . DNA from only one endometrial tissue sample per participant was included. DNAm QC and processing were conducted on the dataset through a series of steps . Probes were masked based on the SeSAME package. These included the 59 Illumina tagged probes and three classes of probes that could be potentially problematic or ambiguously mapped  as well as chromosome Y probes (n = 26 probes). Finally, the minfi104 function ‘getSex’ was used to generate a predicted sex for each sample, in order to ensure all samples were confirmed as genetically female based on the median values of measurements on the X and Y chromosomes (n = 0 samples were removed). The next QC stage involved probe removal of non-overlapping probes in the data between batch I and II (n = 275 probes). These sample and probe level QC steps resulted in a processed dataset of 759,345 DNAm sites for n = 707 and n = 277 endometrial samples in batch I and II, respectively, with a final total of 984 samples (from 637 cases and 347 controls)  at USC Epigenome Center Core Facilities, with data on 865,859 DNAm sites for 767 samples in batch I and 307 in batch II , (2) batch II samples , (3) Merged batch I and II samples. In each stage (i) per-individual QC included identification and filtering of samples with genotype call rate < 95%, heterozygosity rate > 3 standard deviations away from the mean heterozygosity rate and removal of related (IBD > 0.200) samples, (ii) per-variant QC included filtering variants with MAF < 1%, call-rate >95% and HWE p-value < 1 × 10−5. Post-QC combined datasets included 953 individuals  and 621,613 variants. Post-QC, data from all ancestries was pre-phased using SHAPEIT2 and imputed using the 1000 Genomes reference (1000G P3v5) all together. Not all samples that passed the methylation QC also passed the genotype QC and as such only samples passing both were included in the subsequent mQTL analysis.Batch I and II samples that passed the DNAm QC were genotyped using the Axiom Precision Medicine Research array. Quality control of the data was conducted in three stages; (1) batch I samples   was performed using the M-values from the DNAm dataset and PCA plots were generated  was evaluated, and then the SVs were calculated while protecting contrasts for two variables—endometriosis case:control status and menstrual cycle phase at endometrial sample collection—as those were the two variables we were interested in exploring biologically. SVA was run separately for the stratified analyses.In order to remove batch effects coming from covariates such as batch, institute, plate, and genetic ancestry, we used the SVA algorithm using R package 107 R package with the significance cutoff of Benjamini Hochberg corrected p-value of 0.05. The following model was used: DNAm values ~ endometriosis case:control status + Cycle phase + SVs and interrogated via contrasts to capture case:control and cycle phase differences. All 347 women without endometriosis were included as controls. Both cases and controls were included in the cycle phase analysis. Data were visualized using heatmaps with the Complex Heatmap108 package in R. Endometriosis case vs. control and cycle phase differences were also tested using a conservative mixed linear model (MLM) based approach, MLM-based omic association (MOA)56  vs. proliferative (PE) vs. menstrual, where secretory consists of early (ESE), mid (MSE) and late (LSE) secretory phases, and also on more finely categorized cycle phase definitions using the secretory sub-phases . A sensitivity analysis was carried out for a endometriosis case vs. control comparison using the 201 pathology-free controls. Given that larger genetic effects are observed in rASRM stage III–IV disease compared to stage I–II endometriosisIlluminaHumanMethylationEPICanno.ilm10b4.hg19 annotation109 R package. The DNAm sites were mapped to genes if they were upstream of the gene body  or within the gene body. The resulting gene sets were analyzed for pathway overrepresentation using the enrichKEGG and enrichPathway functions from the clusterProfiler R package110. The over-representation analyses were also run using stratified gene mapping schemes based on the genomic features (upstream or gene body) from which DNAm sites were mapped. The analysis was carried out using the KEGG111 and Reactome databases112. The top 5 statistically significant pathway gene sets were visualized using the emapplot function from the enrichplot113 R package.Pathway analysis was carried out on all significant DNAm sites (FDR < 0.05) as input into the analysis and significance cutoff on the pathway overrepresentation of FDR < 0.05. Statistically significant DNAm sites were mapped to genes using the DMRCate114. A nominal p-value cutoff of 0.05 was used for the input DNAm sites into the analysis and Fisher p-value of <0.1 was used to identify significant regions.Comparisons made in the single site analysis were repeated using regional analysis. Regional analysis was carried out with an R package 33 was applied to a reduced dataset using 50% of most variable DNAm sites resulting in a dataset of 379,672 DNAm sites from the 984 samples. First, co-methylated modules were identified using the ‘blockwiseModules’ command33 with minimum block size of 30 and maximum block size of 40,000 selected. Associations between the two traits of interest  and menstrual cycle phase) and the modules were identified through use of the Limma107 R package linear models using the SVs from SVA as covariates. Statistical significance was defined as a Benjamini-Hochberg adjusted p-value of <0.05. Significant modules were aggregated into gene sets. More specifically, for each linear model, all DNAm sites in modules with positive direction of effect were mapped to genes using the IlluminaHumanMethylationEPICanno.ilm10b4.hg19 annotation109 and aggregated into a gene set, and all DNAm sites in modules with negative direction of effect were mapped to genes and aggregated into a gene set. The resulting gene sets were analyzed for pathway overrepresentation using the enrichKEGG and enrichPathway functions from the clusterProfiler R package110.Weighted correlation network analysis (WGCNA)cis distance of 1 Mb was carried out using a linear regression model in the MatrixeQTL115 R package. Menstrual cycle phase, endometriosis case:control status and 39 SVA components were included as covariates in the model to adjust for known biological and technical variation. Women without endometriosis were classified as controls (n = 221). A Bonferroni threshold of p-value < 1.7 × 10−11 was applied to account for multiple testing. Independent mQTL signals were identified using a stepwise model selection procedure in GCTA116 for Bonferroni significant DNAm sites. Due to extensive storage requirements to compute the genomic inflation factor (λ), λ was calculated based on associations of 759,345 DNAm sites with a random subsample of 100,000 SNPs selected from the 1000 Genomes Project panel (EUR phase 3).DNAm and genotype data from 658 European samples was used to test for associations between genotype and DNAm in endometrium Table . DNAm M-35, skeletal muscle36, adipose tissue37, and brain38. All datasets were previously generated using the Illumina HumanMethylation450 array with the exception of significant blood mQTLs reported by Hannon et al. who used the Illumina EPIC array allowing comparison of the additional DNAm sites on this array. Full summary statistics were only available for blood mQTLs published by Min et al.46, allowing us to match cis-mQTLs between the tissues based on the same eSNP and DNAm site associations and direction of effect. We also limited the analysis to those DNAm sites and SNPs present in both datasets to calculate the proportion of endometrial mQTLs shared with blood. For the remaining tissues where the full SNP information was not available, we matched cis-mQTLs between the tissues based on DNAm site. Genes annotated to DNAm sites with mQTLs unique to endometrium were included in a pathway analysis in FUMA.We compared mQTLs identified in endometrium to those that have been reported as significant in bloodTo investigate if the effects of mQTLs differed between women with and without endometriosis and between proliferative and secretory menstrual cycle phases, we conducted context-specific mQTL analyses. A total of 118,185 independent Bonferroni significant mQTLs were included in the analysis. Anova was used to compare the following two models:H0: DNAm ~ genotype + condition + covariatesH1: DNAm ~ genotype + condition + condition*genotype + covariatesp-value < 4.2 × 10−7 . Results were filtered to only include comparisons that had at least 10 samples homozygous for the minor allele in each group.Conditions tested included endometriosis case vs. control and proliferative (PE) versus secretory (ES + MS + LS) menstrual cycle phases. SVA components and either menstrual cycle phase or endometriosis, depending on the condition tested, were included as covariates. H1 differed from H0 by the inclusion of an interaction term between genotype and the condition being tested. To account for multiple testing, statistically significant context-specific mQTLs for each condition were defined as those with a 39 was used to test the association between genetic variants, DNAm levels and endometriosis risk by integrating mQTL summary statistics with endometriosis GWAS summary statistics. Summary statistics used were generated from a subset of European cohorts from the largest endometriosis GWA meta-analysis to date conducted by Rahmioglu et al.10 with the addition of a FinnGen endometriosis cohort  and a HEIDI p-value of PHEIDI > 0.05/(number of genes passing the SMR test) was applied as the threshold for statistical significance.Summary data-based Mendelian Randomization (SMR)41, blood117, and 49 GTEx Tissues95 using the top associated mQTL in each dataset, and the association between eQTLs and endometriosis using the top associated eQTL. We combined results from pleiotropic associations between DNAm, gene expression and endometriosis using the stringent criterion that both the DNAm site and gene of each pair were statistically significantly associated with endometriosis at a genome-wide threshold with no association rejected by the HEIDI test. The gene–endometriosis association analysis was not dependent on the DNAm–endometriosis association analysis to account for potential discrepancies in SNPs tagging the causal SNP between the datasets.Consistent association signals at genomic loci across multiple omics layers can help identify functionally relevant genes and regulatory elements. As such we also used SMR to test the association between mQTLs and eQTLs in endometrium118 and GWAS Catalog119. EpiMap96 was also used to functionally annotate SMR significant SNPs and DNAm sites using epigenome maps from relevant tissues  to define chromatin states, high-resolution enhancers, enhancer modules, upstream regulators and downstream target genes. Valid promoter-associated chromatin loops generated from H3K27Ac HiChIP libraries from a normal immortalized endometrial cell line (E6E7hTERT)97 were also used to annotate SNPs and DNAm sites located in chromatin interaction anchor points.Association between SNPs significant in the SMR analyses and other traits and diseases was investigated using PhenoScanner116, was used to estimate the variation in endometriosis case-control status captured by common genetic variants (SNPs), also known as the SNP-based heritability. The genetic relationship matrix (GRM) used in the GREML analysis was calculated using genotype data for 5,358,309 SNPs in 953 individuals in GCTA. Similarly, omics residual maximum likelihood analyses (OREML), as implemented in the Omic-data-based Complex Trait Analysis (OSCA) software56, was used to estimate the proportion of variance in endometriosis case-control status captured by DNAm sites and SNPs. Three different OREML models were compared, one including all DNAm sites  for 984 individuals in the form of an omics relationship matrix (ORM), one including the ORM and the GRM for 953 individuals with matched genetic and DNAm data and one including the ORM, calculated following exclusion of DNAm sites with mQTLs , and the GRM for the 953 individuals.Genome-based restricted maximum likelihood (GREML), as implemented in the Genome-wide Complex Trait Analysis (GCTA) software10 was conducted for 11 comparisons of endometriosis-case-specific surgical sub-phenotypes  and six comparisons of common endometriosis-associated pain symptom sub-phenotypes   and a less stringent locus-specific Bonferroni multiple testing correction (0.05/N of DNAm sites per GWAS locus) was applied. The statistically significantly differentially methylated sites were checked in the endometrium mQTL map and SMR results generated. If an mQTL was identified for a differentially methylated probe, whether the DNAm-associated SNP was in LD with an endometriosis-associated SNP in the respective region was determined. Associated DNAm sites were also annotated using EpiMap. Correlation between the effect sizes of differentially methylated sites between subtypes were calculated utilizing Spearman’s rank correlations.Differential DNAm analysis for 11,698 DNAm sites within 500 Kb± of 44 lead SNPs genome-wide statistically significantly associated with endometriosisAll the analysis and code was implemented in R and shared via github for reproducibility. Power analysis was conducted prior to the study to ensure the findings would be robust.Further information on research design is available in the Peer Review FileSupplementary FiguresDescription of Additional Supplementary FilesSupplementary Data 1-20Reporting Summary


The possible application of a simple analytical method based on a UV (ultraviolet) spectral dataset coupled with SIMCA  for authentication of Indonesian specialty ground roasted coffee with different botanical and geographical indications (GIs) was demonstrated. Three types of Indonesian specialty ground roasted coffee were used: GIs arabica coffee from Gayo Aceh (96 samples), GIs liberica coffee from Meranti-Riau (119 samples), and GIs robusta coffee from Lampung (150 samples) with 1 g weight of each sample. All samples were extracted using hot distilled water and 3 mL aqueous filtered samples were pipetted into a 10 mm quartz cell. Original UV spectral datasets were recorded in the range of 190–399 nm. The pre-processed spectral dataset was generated using three simultaneous different preprocessing techniques: moving average smoothing with 11 segments, standard normal variate (SNV), and Savitzky-Golay (SG) first derivative with window size and polynomial order value of 11 and 2. The supervised classification based on the SIMCA method was applied for preprocessed selected spectral data (250–399 nm). The PCA data showed that GIs coffee with different botanical and geographical indications can be well separated. The SIMCA classification was accepted with 100 % of correct classification (100 % CC). This dataset demonstrated the potential use of UV spectroscopy with chemometrics to perform simple and affordable authentication of Indonesian specialty ground roasted coffee with different botanical and geographical indications (GIs). Specifications Table1•Spectral dataset acquired from UV spectroscopy provides a simple, easy, and affordable authentication method of Indonesian specialty ground roasted coffee with different botanical and geographical indications (GIs).•UV spectral dataset can be benefited those who are working and concerned with food authentication, especially for coffee authentication, from growers, retailers, industry, and coffee shops as well as the government.•UV spectral dataset can be employed in foods and agricultural products industries, especially for food quality evaluations purpose: authenticating and food traceability.•The authentication of Indonesian specialty ground roasted coffee with different botanical and geographical indications is easy to be realized due to the low-cost UV spectrometer. It will help developing countries establish an authentication system based on UV spectroscopy shortly.•The established coffee authentication system based on UV spectroscopy may lead to a certification system of Indonesian specialty ground roasted coffee. This certification is benefitable for both producers and customers and provides fair trading of specialty coffee.2In 2007, the Indonesian government officially announced Government Regulation No. 51 about Geographical Indication (GIs). According to this regulation, GIs can be defined as any indication which identifies goods and/or a product as originating from a particular region of which its geographical environment factors including nature, labour, or a combination of both factors are attributable to a given reputation, quality, and characteristics of the produced goods and/or product 2 versus Q-residual presented in Concerning the low-cost spectroscopy method, Suhandy and Yulia propose to develop an authentication for Indonesian specialty ground roasted coffee using UV spectroscopy along with the SIMCA method. The averaged original UV spectral dataset from 365 samples with different botanical and geographical indications (GIs) were presented in 33.1Indonesian specialty coffee green bean samples were directly collected from trusted farmers in Indonesia from three different botanical and geographical indications (GIs): Arabica Gayo-Aceh, Liberica Meranti-Riau, and Robusta Lampung as depicted in 3.2Three mL of aqueous coffee samples were pipetted in the 10 mm of quartz cell. All the UV spectral data were acquired using a dual-beam UV-Visible benchtop spectrometer , equipped with a high-intensity xenon lamp and dual Silicon photodiodes as a detector. Spectra were measured between 190 and 399 nm with an interval of 1 nm.3.3The original UV spectral dataset of 365 samples was exported to The Unscrambler® X version 10.4 (64-bit)  for further processing and analysis including spectral preprocessing and chemometrics calculation. The preprocessed spectral data were obtained by applying simultaneously three different preprocessing techniques, namely, moving average smoothing with 11 segments, standard normal variate (SNV), and Savitzky-Golay (SG) first derivative with window size and polynomial order value of 11 and 2. In general, smoothing was used to reduce the noise and improve the signal-to-noise ratio (SNR). SNV and derivative are frequently used spectral preprocessing methods for scatter correction, removing baseline offsets, and enhancing the resolution of overlapped peaks 3.42 statistics and to perform unsupervised classification of Indonesian specialty ground roasted coffee samples with different botanical and geographical indications (GIs). Hotelling's T2 is the variation within the PCA model, while Q-residual is used to measure the dimensional data in the model 2 and Q-residual values are greater than the 95 % confidence interval or 5 % confidence level (black dotted line). 2 and Q-residual values were lower than the 95 % confidence interval (black dotted line). Therefore, no outlier was detected, and this led to the use of all 365 samples for further analysis. The first two principal components (PC1 and PC2) were plotted for preprocessed spectra as depicted in PCA was widely used for reducing the dimensionality of the spectral dataset 3.5SIMCA is one of the supervised classification methods and is frequently used in the classification of spectroscopic data Not applicable.The authors have read and follow the ethical requirements for publication in Data in Brief and confirming that the current work does not involve human subjects, animal experiments, or any data collected from social media platforms.Diding Suhandy: Conceptualization, Methodology, Writing – review & editing, Writing – original draft. Meinilwita Yulia: Data curation, Software, Validation, Writing – original draft, Writing – review & editing. Agus Arip Munawar: Visualization, Investigation, Writing – original draft. Kusumiyati Kusumiyati: Software, Investigation, Supervision, Writing – review & editing.