Patients with inflammatory bowel disease (IBD) are at higher risk of venous thromboembolism (VTE), though physicians may be unaware of this risk or hesitant to start pharmacologic VTE prophylaxis in the presence of active gastrointestinal bleeding. We report a case of a 38-year-old patient hospitalized with acute severe ulcerative colitis (UC) who was not placed on pharmacologic VTE prophylaxis and developed bilateral pulmonary embolism (PE). The patient's UC did not respond to medical therapy. Due to his PE, the patient’s total proctocolectomy was delayed six months. He also developed a large pelvic hematoma after colectomy requiring further surgical intervention. Hospitalized inflammatory bowel disease (IBD) patients require pharmacologic VTE prophylaxis unless they have life-threatening bleeding. Inflammatory bowel disease (IBD) is a chronic inflammatory condition of the gastrointestinal (GI) tract that includes Crohn’s disease and ulcerative colitis (UC). The prevalence of IBD has increased from 3.7 million affected individuals in 1990 to 6.8 million affected individuals in 2017 worldwide [Additionally, patients with IBD are at a two-to-three-fold increased risk of developing venous thromboembolism (VTE) compared to the general population, which encompasses deep vein thrombosis and pulmonary embolism (PE) . This riCurrent guidelines support that all hospitalized IBD patients with non-severe GI bleeding should receive pharmacologic VTE prophylaxis with low molecular weight heparin, low-dose unfractionated heparin, or fondaparinux . We presThis article was previously presented as a meeting abstract at the 2020 Hospital Medicine Virtual Competition held by the Society of Hospital Medicine in August 2020.A 38-year-old male with a five-year history of UC was hospitalized with an acute severe UC flare after experiencing up to 42 bloody bowel movements daily and a 60-pound weight loss over the past year. The patient was found to have fulminant ulcerative pancolitis with pseudomembranes Figure . ClostriThe patient was admitted for intravenous corticosteroids, cyclosporine salvage therapy, and total parenteral nutrition with plans for colectomy if his disease did not respond to therapy. Due to the patient’s hematochezia, he was given sequential compression devices for VTE prophylaxis. Despite his hematochezia, his hemoglobin remained stable, and he did not require packed red blood cell transfusion.On hospital day three, the patient reported chest pain and shortness of breath. Contrast-enhanced computed tomography revealed pulmonary emboli involving segmental arterial branches to the right and left upper lobes and the right lower lobe Figure .Following his PE diagnosis, the patient was started on a heparin drip and, interestingly, reported a decrease in the number of total bowel movements after starting anticoagulation. The patient was discharged on warfarin for anticoagulation and prednisone with plans to start tofacitinib as an outpatient. The patient, unfortunately, did not respond to treatment with tofacitinib and 20mg prednisone as an outpatient and required a total proctocolectomy. However, due to surgical risks with his acute PE, his surgery was delayed six months from initial hospitalization. During the six-month waiting period, he remained on tofacitinib and prednisone as maintenance therapy. The patient had total proctocolectomy completed, but postoperative was complicated by a large pelvic hematoma requiring further surgical intervention. He was discharged and recovered well afterward.Although literature demonstrates the increased risk of VTE in IBD patients, thromboprophylaxis in hospitalized patients with IBD needs to be better addressed. A single-center study of 3758 IBD admissions found that VTE prophylaxis is underutilized in 50% of IBD patients that developed VTE [A more recent study of hospitalized patients between January 2013 and August 2018 found that IBD patients were less likely to be placed on VTE prophylaxis, with 79% of IBD patients placed on VTE prophylaxis, compared to 87% of hospitalized patients without IBD . This isUnderutilization of pharmacologic VTE prophylaxis in patients with IBD may be related to a lack of awareness as well as safety concerns regarding bleeding risk. In a survey of 591 gastroenterologists, 19.4% failed to acknowledge the increased risk of thrombosis in IBD patients, while 29.1% were unaware of practice guidelines for VTE prophylaxis in hospitalized IBD patients . AnotherGuidelines provided by the Canadian Association of Gastroenterology recommend anticoagulant prophylaxis for all hospitalized patients with IBD with low molecular weight heparin (LMWH), low-dose unfractionated heparin, or fondaparinux unless severe bleeding is present. Patients admitted for reasons other than an IBD flare, including those in clinical remission, and patients who have undergone major abdominal-pelvic or general surgery are included in this recommendation. For hospitalized IBD patients with severe IBD-related gastrointestinal (GI) bleeding, mechanical thromboprophylaxis, preferably with intermittent pneumatic compression (IPC), is recommended. Once the bleeding becomes non-severe, anticoagulant thromboprophylaxis is recommended during the hospital stay due to the increased effectiveness of anticoagulant prophylaxis in VTE prevention compared to IPC . LMWH reThis case highlights the importance of VTE prophylaxis in IBD patients. These patients are at an increased risk for thromboembolic events with the potential for significant morbidity and mortality ,17. PhysThis case illustrates the need for pharmacologic VTE prophylaxis in hospitalized IBD patients due to the increased risk of thromboembolic events. More awareness is needed among physicians that hospitalized IBD patients require proper pharmacologic VTE prophylaxis in the absence of life-threatening bleeding due to a higher risk of VTE as it carries the potential for significant morbidity and mortality in IBD patients. The benefits of pharmacologic VTE prophylaxis outweigh the risks.


Quantitative and qualitative changes to adipose tissue, organs, and muscle compartments, particularly of the trunk and extremities, could present important biomarkers for phenotyping cachexia and determining its onset in patients. In this review, we present and compare the imaging techniques that have been used in the setting of cancer cachexia. Their individual limitations, drawbacks in the face of clinical routine care, and relevance in oncology are also discussed.Cachexia, a multifactorial wasting syndrome, is highly prevalent among advanced-stage cancer patients. Unlike weight loss in healthy humans, the progressive loss of body weight in cancer cachexia primarily implicates lean body mass, caused by an aberrant metabolism and systemic inflammation. This may lead to disease aggravation, poorer quality of life, and increased mortality. Timely detection is, therefore, crucial, as is the careful monitoring of cancer progression, in an effort to improve management, facilitate individual treatment and minimize disease complications. A detailed analysis of body composition and tissue changes using imaging modalities—that is, computed tomography, magnetic resonance imaging, ( Cachexia is a multifactorial wasting disorder associated with neoplastic diseases such as cancer and other, mainly chronic, diseases. Cancer cachexia is characterized by a substantial loss of body weight, including muscle wasting and, but not necessarily, adipose tissue loss. These features are driven by disturbances in protein, carbohydrate, and lipid metabolism and are associated with a systemic inflammatory state, conferring a negative energy balance , 2. SimuCancer cachexia is classified into three linear stages: (1) Precachexia describes the early stage of the disease where minor weight loss changes occur that may present with prior glucose intolerance and anorexia. 2) Cachexia describes a body weight loss of > 5% within 6 months, a weight loss of > 2% in patients with a BMI of < 20, or sarcopenia. 3) Refractory cachexia describes the state at which reversibility of the disease, given the current day treatment strategies, is dramatically decreased, and average life expectancies reach below 3 months, with tumor treatments remaining unresponsive [ Refracto CachexiaThe heterogeneous presentation of cachexia in cancer is a culmination of multiple interplaying factors. This has hindered a clear consensus regarding clinical description in the past, leading to the frequent omission of cachexia-related deaths in national statistical databases, occluding prevalence and clinical relevance data . The vasThe high prevalence rate of cancer cachexia calls for cancer patient treatment frameworks which incorporate adequate cachexia management as well as transparent documentation of therapy outcomes. The dramatic sarcopenia, anorexia and fatigue experienced by patients have a severely detrimental impact on their quality of life . This exDespite an ever-increasing research base and support from the pharmaceutical industry, cancer cachexia largely remains an untreatable and unnoticed entity. With 20–30% of cancer deaths resulting from cachexia alone , the necIn recent years, research focused on understanding the etiology of cancer cachexia has begun to shift from a muscle-focused field to a multi-organ view, as increasing evidence reveals a complex network of organ participation , 17. FigFirst, systemic inflammation drives the communication in this network through inflammatory factors derived from both the tumor as well as other organs in the network itself. The liver plays a key role in the systemic inflammatory state of cachexia via the acute phase response (APR) , 19. BeySecond, the composition and distribution of adipose tissue is altered in cancer cachexia. On the one hand, induced lipolysis contributes to the loss of white adipose tissue (WAT), which can precede muscle wasting . Fat masThird, the brain conduces pathogenically increased energy expenditure. While inflammation of the hypothalamus (a common topic in obesity research) may blunt food intake via a decreased appetite , the braFourth, there is a convincing amount of evidence linking gut homeostasis to cancer cachexia. These links range from gut barrier dysfunction—due to epithelial layer breakdown and consequent systemic inflammation through invading pathogens—to an altered gut microbiome , 17.Finally, cancer cachexia affects cardiac muscle tissue, leading to cardiac tissue atrophy and dysfunction –31. IndeTo summarize, cancer cachexia is a complex systemic disease comprised of an intricate network of signals from multiple organs. Currently, body weight remains the standard diagnostic tool in clinics for cachexia detection, yet if detection timescales are to improve, newer, more sensitive methods are required.Since cancer cachexia constitutes a multi-organ syndrome that alters body composition and tissue quality over time, and given that many noninvasive imaging modalities can simultaneously assess these longitudinal changes, medical imaging holds the greatest potential in improving the phenotyping of cachexia developing cancer patients. Expanding the role of noninvasive imaging-based phenotyping could improve the efficacy of diagnosing cancer cachexia, anticipating high-risk individuals, systematically assessing the multi-organ effects of therapeutic interventions and enhancing our understanding of cancer cachexia pathophysiology. We provide below a short overview of the main technical characteristics of imaging modalities available for assessing tissue changes in cancer cachexia:Dual-energy X-ray absorptiometry (DXA) is a widely available, fast and inexpensive two-dimensional (2D) projection technique suitable to assess body composition by estimating body fat, lean tissue mass and bone mineral density . In the Computed tomography (CT) is a cross-sectional radiological imaging technique that is routinely practiced as part of the clinical staging of cancer patients. It is therefore the most commonly used imaging modality to assess body composition changes in cancer patients . The disMagnetic resonance imaging (MRI) is a cross-sectional radiological imaging technique, which, although widely adopted in the diagnostic setting, is not part of routine clinical staging in oncology. However, MRI is gaining significant attention for noninvasively assessing patients with metabolic dysfunction. MRI provides volumetric images without the burden of ionizing radiation and is therefore very attractive for longitudinally assessing tissues changes in patients with metabolic diseases undergoing lifestyle interventions , 34. The18F) fluoro-2-deoxy-d-glucose (18FDG) PET is being clinically routinely used to detect lesions and to measure the metabolic activity of tumors by quantifying the standardized uptake value (SUV). In cancer cachexia, 18FDG-PET enables imaging the metabolic activity of both the primary tumor and other affected tissues. By mapping the metabolic activity of primary tumors, researchers could relate this to cachexia progression. In addition, 18FDG-PET has been used to map white and BAT metabolic activity in cancer patients.Positron emission tomography (PET) is a Nuclear Medicine imaging modality which applies radioactive tracers to measure tissue changes in metabolism and other physiological activities. (http://www.ncbi.nlm.nih.gov/pubmed) was performed without a starting date up to May 2021 using as search terms “cancer cachexia” and one of the following terms: “Computed Tomography” “Magnetic Resonance Imaging”, “Positron Emission Tomography”, “Dual-energy X-ray absorptiometry”, “Imaging”. The search resulted in 488 entries, which included investigations in both animals and humans. The reference lists of relevant articles were also screened. The present review focuses on imaging modalities for diagnosis and monitoring of cancer cachexia used primarily in human studies. We have structured the review below based on the use of the imaging modalities for assessing changes in different tissue types, including imaging the primary tumor, imaging the skeletal muscle, imaging the WAT, and imaging the BAT.An electronic search in PubMed . In this study, DXA-based lean tissue loss did not appear to be a significant predictor of survival.A loss of muscle mass and body fat is a frequent observation when using DXA techniques in patients with advanced cancer , 52. OneSimilar studies using DXA showed that appendicular lean mass can predict functional muscle performance in cancer patients , 55. As A sexual dimorphism regarding muscle mass and muscle depletion in cachectic cancer patients is known –59. In aBody composition analysis in cancer patients using CT is considered superior over DXA , as it pSarcopenia, the loss of skeletal muscle mass, is frequent among cancer patients, is commonly associated with cachexia and leads to a decline in physical and strength performance . SarcopeWhile functional performance and muscle mass were diminished in cancer patients suffering from cachexia, radiodensity was not reduced . It has The drastically diminished time period of survival among cachectic cancer patients suffering from muscle depletion and low muscle attenuation was found to be independent of individual BMI . Low musThere is strong evidence that CT and MRI measurements are equally suitable to assess biomarkers of skeletal muscle quality and quantity . MyosteaUsing MRI, the muscle tissue can be further investigated and contractile tissue volume and muscle fat volume can be obtained. MRI also enables the discrimination of intra- and intermuscular fat depots. However, as MRI is not typically part of the clinical staging routine of most cancer patients, it is not routinely used to assess body composition and cachexia in cancer patients. Therefore, little is in general known about MRI-derived measurements of cachexia-induced changes in body composition.A loss of skeletal muscle volume and decrease in muscle quality has been observed with MRI in cachectic cancer patients –91 Fig.. The thiMRI-derived muscle signal intensity as a semi-quantitative measure of myosteatosis in periampullary cancer patients was found to correlate with muscle attenuation assessed with CT . In womeSingle-slice analysis of the fat-free muscle area in patients undergoing radioembolization of colorectal cancer liver metastasis revealed a prognostic value on overall survival . TherebyTo date, research on imaging WAT in cancer-associated cachexia remains limited. The loss of WAT, which can be further subclassified into visceral- (VAT) or subcutaneous adipose tissue (SAT), is considered to predate skeletal muscle loss in cancer cachexia. When compared to weight-stable cancer patients, individuals with cancer cachexia exhibit a reduced adipose tissue mass  Fig. 4)4). WAT lWhole-body and regional distribution of WAT has been assessed with DXA in cancer patients. A longitudinal observational study on palliative cancer patients predominantly with gastrointestinal tumors reported increasing WAT loss in all body compartments with disease progression, even with maintenance or increase of caloric intake . These bCT-based assessment of WAT changes has also shed light on cancer cachexia. In a retrospective review of patients with head and neck squamous cell carcinoma (HNSCC), CT attenuation yielded substantially higher HU values for VAT than SAT. This was most prevalent in patients with T3 or T4  classifi18FDG-PET/CT has been used to calculate volume and evaluate the metabolic activity within a single fat compartment by measuring FDG uptake. SUV values can be calculated for both WAT types in PET images through referencing corresponding region of interests in CT images, typically at the level of the lumbar spine [While tumors often exhibit an elevated glucose metabolism, marked variations are detectable in WAT. ar spine . Simultaar spine . It is kar spine . Greaterar spine , 106. Inar spine . VAT volar spine . Thus, fTo the best of our knowledge, there is no study on the use of MR or MR-spectroscopy (MRS) imaging of WAT in patients with cancer-associated cachexia. Non-human trials, however, have been reported. MRI methods measured total body adipose tissue and lean mass in transgenic model mice with hepatocellular carcinoma (HCC)-associated cachexia . In vivoBAT is found primarily in the supraclavicular region in human adults. Heat is generated there in the mitochondrial membrane by glycolysis and beta-oxidation, which is triggered by sympathetic nerval innervation. This happens as a response to cold exposure or post-prandially , 114. In18FDG-PET detects regions in the body with active glycolysis and is widely used for cancer diagnosis and for staging of tumors. In this context, active brown fat was perceived as nuisance signal and prevention of its activation during 18FDG-PET imaging was strived for [18FDG-PET/CT data in certain cancer types had been conducted. Some suggest a positive correlation between cancer and BAT activity [ived for . Only afactivity –121, whiactivity . A more activity . BAT act18FDG-PET/CT can only visualize active glycolysis in BAT and is therefore unable to detect currently non-active BAT or thermogenesis via beta oxidation. In other words, if glycolysis is not triggered in BAT during the examination, 18FDG-PET is little sensitive in detecting BAT. Various MRI contrast mechanisms have been used to detect brown fat presence and activation in rodents and humans [2* contrast and fat fraction images for evaluating BAT activation status and the change in brown fat volume, respectively [d humans . Howeverd humans . One worectively .18FDG-PET are challenging and have found contradictive results in cancer cachexia because retrospective studies could not account for confounding factors for BAT activation and because 18FDG-PET only detects glycolytic activity of BAT. Future studies should control confounding factors [In summary, in vivo BAT quantification studies using  factors , 126 andWhile available studies primarily focused on the classical cachexia-related tissue compartments, we briefly review here the use of imaging for studying other organs beyond the primary tumor, the skeletal muscle, and the adipose tissue.18FDG and survival in cancer patients  [18FDG uptake (SUVmean ≤ 1.78) of the liver substantially increases the risk of developing cachexia, leading to worse overall survival [18FDG-PET. These patients commonly presented with anemia, impaired liver function, systemic inflammation and poor nutritional status, characteristics which also predominate the cancer cachexia population.Recent work has uncovered a link between liver uptake of  et al.) , highligsurvival . An evenChanges in visceral organ size have been monitored using quantitative CT image analysis in patients with advanced colorectal cancer. An exponential increase in liver volume, hepatic metastases, and an increase in spleen volume concurrent to muscle and fat loss were recorded in patients until death . The per1H MRS of brains of cachectic pancreatic tumor-bearing mice have identified a unique "cachexia brain metabolic signature" characterized by changes to the levels of metabolites, specifically an increase in cholines and a decrease in glutamine and formate [Analyses of  formate . These aCT and MRI are accepted as gold standard methods to determine body composition Table . They enMany clinicians are limited to using only single-slice 2D analysis due to the time-consuming nature of manual segmentation and correction of tissue boundaries. However, single 2D slices are prone to greater variability in volume calculation than a series of images. Recent advancements in artificial intelligence (AI) have allowed for the conversion of CT and MRI images into mineable data that can be accessed for quantitative features analyses. This process called radiomics offers an automated three-dimensional (3D) approach of whole-body tissue assessment. The transition from manual 2D segmentation to automated 3D volumetric assessment using AI-based methods can thus improve the accuracy in determining body composition and more importantly allow for a better individualization of treatment plan for cancer patients .DXA is overall a fast technique for assessing body composition but lacks the precision of the aforementioned imaging modalities Table . It is aNevertheless, DXA is relevant for cancer intervention because the relative proportions of LBM and adipose tissue impact the degree of chemotherapy-induced toxicity. Previous work has demonstrated the impacts of chemotherapy on body composition: although generally fat mass and fat-free mass were shown to decrease after neoadjuvant chemotherapy, a relative increment in patients with sarcopenic obesity was observed, and sarcopenic obesity was an important independent predictor of survival in patients with respiratory and gastrointestinal tract tumors , 137. Gi18FDG-PET describes the metabolic activity of adipose tissue compartments [18FDG-PET/CT not only provides anatomical but important functional information on body tissues. 8FDG -uptake of AT could be a valuable qualitative imaging biomarker for fat analysis. However, there is currently no standard method for SUV of WAT. This could explain some of the contradictive results presented by studies on cancer patients where measurements were based either on a single-slice region of interest or whole tissue assessments using multiple slices [artments . 18FDG-Pe slices . An agreThere is an urgent need of impetus to find better treatment options for cachexia patients. Progress is certainly being made in this domain, however much work remains, particularly in advancing from an ad hoc treatment approach toward identifying methods of early detection and prevention. As reviewed in this piece, an array of imaging methodologies is capable of delineating aspects of the disease, however often fall short as comprehensive standalone diagnostic tools.Biomarkers obtainable from circulation are often of high diagnostic value, while keeping invasiveness low. Blood-borne biomarkers can be subdivided into 4 groups; Cachexia-inducing, inflammation related, skeletal muscle and adipose tissue wasting markers or cachexia-related micro-RNAs and have been reviewed in detail elsewhere . These bMany of the current cachexia blood-borne biomarkers are simultaneously potential therapeutic targets. Unfortunately, if a biomarker is targeted in a therapeutic manner, this diminishes its value as a marker of disease progression/state, which would be necessary to measure therapeutic success. The imaging biomarkers described in this review on the other hand, remain unperturbed by therapeutic intervention in the short term and so reveal themselves as powerful tools in the clinical setting of cancer cachexia. Future clinical studies may employ suitable imaging techniques to measure the outcome of cachexia therapies, providing valuable insight into body composition and skeletal muscle and adipose tissue architecture.Therefore, although blood-borne biomarkers are an important piece of the cachexia puzzle, it is clear that alternative methods of detection are necessary. Combining blood-borne biomarkers with the described innovative imaging biomarkers may yield promising therapeutic strategies. To further reveal this potential, future clinical studies with a focus on imaging biomarkers are desperately needed in the context of cancer cachexia.Noninvasive imaging enables the multi-organ assessment of cachexia effects in cancer patients. However, despite the recent successes, imaging currently only helps in part in pathophysiology understanding and has not provided a clear widely used biomarker for cachexia risk assessment. CT techniques will remain most probably the most popular approach for assessing cachexia given the wide use of CT in the staging of many oncological entities. However, as many oncological centers use more MRI exams, the use of MRI for assessing body composition and organ-specific changes is expected to increase in cancer cachexia. When MRI or CT is already performed in the clinical work-up of the patient, an imaging analysis of the cachectic phenotype could be combined with the main diagnostic reporting, especially when facilitated by the use of automated analysis tools. However, more clinical studies using modern imaging methods in answering cachexia development-driven questions based on large-scale prospective and homogeneous cohorts are needed toward establishing quantitative CT and MR imaging biomarkers for cachexia early prediction.Cancer remains a leading cause of death in all countries and its stable increase in incidence and mortality is concerning. Although imaging of body composition change in cancer is well documented, few studies have informed us on the niche of cachectic cancer patients. This owes partially to the wide variations in clinical presentation and the absence of a validated international consensus for the diagnostic criteria of cancer-associated cachexia. While cancer cachexia is principally characterized by involuntary weight loss, it can also manifest with a constellation of other medical conditions such as malnutrition, anorexia or systemic inflammation . It occuOverwhelming evidence suffices the competencies of imaging tools to measure body composition and delineate tissue compartments. CT and MRI stand here as favorable approaches that produce high spatial and contrast resolution images . We need


The horse reference genome assemblies, EquCab2.0 and EquCab3.0, have enabled great advancements in the equine genomics field, from tools to novel discoveries. However, significant gaps of knowledge regarding genome function remain, hindering the study of complex traits in horses. In an effort to address these gaps and with inspiration from the Encyclopedia of DNA Elements (ENCODE) project, the equine Functional Annotation of Animal Genome (FAANG) initiative was proposed to bridge the gap between genome and gene expression, providing further insights into functional regulation within the horse genome. Three years after launching the initiative, the equine FAANG group has generated data from more than 400 experiments using over 50 tissues, targeting a variety of regulatory features of the equine genome. In this review, we examine how valuable lessons learned from the ENCODE project informed our decisions in the equine FAANG project. We report the current state of the equine FAANG project and discuss how FAANG can serve as a template for future expansion of functional annotation in the equine genome and be used as a reference for studies of complex traits in horse. A well-annotated reference functional atlas will also help advance equine genetics in the pan-genome and precision medicine era. Twilight and remain the only high-quality genome assemblies for equids. EquCab2.0 has 42,304 gaps comprising 55 Mb (2.2% of the genome) in total, with a scaffold N50 of 46 Mb. In comparison, EquCab3.0 contains 3771 gaps comprising 9 Mb (0.34% of the genome) with a scaffold N50 of 86 Mb. It has 99.7% mammalian Benchmarking Universal Single-Copy Orthologs (BUSCO) , compared to that of 99.0% (4064 complete orthologs) in EquCab2.0 [The horse reference genomes (Equcab2.0  and EquCGRM6) associated with congenital stationary night blindness [RAPGEF5) associated with equine familial isolated hypoparathyroidism [Using these tools, successful identification of the genetic variants responsible for simple Mendelian traits have been identified, including a novel variant in glutamate metabotropic receptor 6  region [Twilight to achieve this goal while still aligning well with the reference sequence. A unique aspect of this biobank is that horses were extensively phenotyped, both antemortem by experienced veterinarians and postmortem by veterinary pathologists. This not only ensured that there was no evidence of clinical or subclinical disease in these animals, but it also provided insight into the cellular composition of the tissues selected for assays. These tissues are stored at −80 °C in a biobank at UC Davis and are available to all equine FAANG researchers.The first stage of the equine FAANG initiative was to generate a biobank of reference tissues from comprehensively phenotyped animals. Burns et al.  and Donn) region , the decHere, we briefly discuss some of the most relevant findings from ENCODE and their implications for functionally annotating the equine genome.The transcriptome is the collection of all transcripts in an organism. It includes protein-coding mRNAs as well as noncoding RNAs. During the second phase of ENCODE, 62% of the human genome was found to be transcribed with 31% of transcribed bases located in intergenic regions . Many ofAs part of ENCODE, GENCODE was initially founded to provide high-quality reference gene annotation for the human genome and subsequently expanded into a long-running partnership between several groups and institutes. In its most recent release based on GRCh38, a total of 60,649 genes have been identified in the human genome, of which 19,955 are protein coding, with an average isoform-to-gene ratio of 3.9 . It was In addition to protein-coding transcripts, the transcriptome also consists of many noncoding RNA species, including both small and long noncoding RNAs. The functions of these RNAs have been extensively examined and implicated in important biological pathways ,26,27,28Taken together, these findings from ENCODE demonstrated the importance of noncoding RNAs and of alternative splicing in cell-specific expression and regulation. Both Ensembl  and RefSThe FAANG initiative proposed RNA-seq assays for both mRNA and smRNA to identify and quantify these transcripts in a tissue-specific manner . These aTo facilitate data generation for the remaining biobanked tissues, we proposed a unique “Adopt-A-Tissue” model for mRNA-seq. Researchers were invited to “adopt” a tissue or tissues fitting their research interests, which meant they would cover the assay and sequencing costs. All library preparations and sequencing were performed at the same two locations  to minimize variability. This approach allowed the community to contribute to the initiative together while still being able to limit technical variations across laboratories during library constructions . Owing tMore recently, long-read sequencing assays such as PacBio Isoform sequencing (Iso-seq) have emerged as powerful tools to determine the splicing patterns of transcripts. To address the poor isoform annotations currently available for the horse genome, Iso-seq assays are being performed in 8 tissues  across eight PacBio Sequel 8M SMRT cells. By combining a wide variety of assays, the equine FAANG initiative aims to deliver a comprehensively annotated transcriptome for the horse genome.In mammalian cells, DNA molecules are packed by histone proteins to form nucleosomes and are subsequently compacted into chromatin ,38. CompEchoing their strong functional implications, accessible chromatin was also shown to be associated with noncoding variants identified in GWAS studies of common traits. Maurano et al. examined 5654 noncoding variants identified in the GWAS studies of 207 diseases and 447 quantitative traits and found 76.6% of these variants lie either within a DHS or in complete linkage disequilibrium (LD) with another SNP in DHS . The datAlthough DNase-seq has proven successful in identifying accessible chromatin, its laborious protocol, slow turn-around time, and large sample size requirements severely limit large-scale applications ,51. BuenUsing ATAC-seq on cryopreserved nuclei from eight tissues across pig, cattle, and mouse, Halstead et al. showed a lack of conservation of sequence and accessibility in accessible sites across evolutionary distance, with 20% shared sites between pig and cattle and only 10% between mouse and ungulates . TherefoHistone proteins form the basic building blocks of hierarchical chromatin structures and have been recognized to play an important role in modulating gene expression through post-transcriptional modifications ,59,60,61Barski et al. first comprehensively assayed histone modifications across the human genome using high-throughput sequencing . ConsistTaken together, the four histone modifications discussed in this manuscript represent major regulatory elements and can provide valuable information regarding tissue-specific regulatory activities in the horse genome. Using genome-wide chromatin immunoprecipitation sequencing (ChIP-seq) for these four marks in eight prioritized tissues in the two female FAANG horses, Kingsley et al. reported over one million putative regulatory sites . The utiMYC [LYZ [APP) [HBB [CCCTC-binding factor (CTCF) is a well-studied zinc finger protein that serves a central role in the formation of chromatin topology and remodeling. It was first discovered as a repressive transcription factor in chicken for c-MYC  as well MYC [LYZ . It was YZ [APP) . In 1999PP) [HBB . InsulatPP) [HBB . This siPP) [HBB , a typicPP) [HBB ,79. Many seemingly contradictory functions of CTCF have attracted extensive efforts to understand the mechanisms of its multivalent roles. CTCF is highly conserved across species ,81 and eThe introduction of Hi-C technology that enabled genome-wide interrogation of long-range interactions  quickly WAPL results in enlarged chromatin loops between incorrectly orientated CTCF motifs [WAPL knockout cells are a result of aggregated CTCF loop anchors, or a “cohesin traffic jam” [These findings led to a proposed extrusion model ,95, wherF motifs . Allahyafic jam” .Given its central role in chromatin loop formation, CTCF binding sites can be considered an intermediate between the 1D genomic sequence and 3D chromatin topology. Although there is no simple rule to determine the functional outcome of a disrupted CTCF binding site, as it largely depends on its interaction with surrounding regulatory elements, there is no doubt that a catalog of CTCF binding sites in a given cellular context can provide valuable information when decoding the functional implications of DNA variants. Following the practices established by the FAANG community, characterization of CTCF binding sites using ChIP-seq is being performed on eight prioritized tissues for both sexes. Analyses to identify both tissue and sex-specific CTCF binding and integrate all of the FAANG ChIP-seq data into chromatin state annotations are currently underway.While the associations between individual histone marks and regulatory activities are noteworthy, combinations of histone marks have proven to be more reliable in the fine-scale predictions of regulatory elements. For example, Creyghton et al. observed that the H3K27ac mark could distinguish active enhancers from inactive/poised enhancers, which are both marked by H3K4me1 . BernsteThe recognition of chromatin states and introduction of computation tools such as ChromHMM  providedEquus [Centromeres are enigmatic structures because, contrary to other genetic loci, their function is not determined by the underlying DNA sequence but depends on epigenetic factors. The Centromere Protein A (CENP-A) is a centromere-specific variant of histone H3 that epigenetically identifies, maintains, and propagates centromere function . The chaEquus ,108,109.Equus . The position of the ECA11 satellite-less centromere, identified as the CENP-A binding domain, is not fixed in the horse population but slides within an about the 500 kb region, giving rise to different positional alleles or “epialleles” ,111,112.The absence of satellite DNA at these centromeres also provides a unique opportunity to understand whether some typical features of mammalian centromeres depend on the presence of satellite DNA. In particular, it was possible to demonstrate that satellite DNA was not necessary for segregation fidelity of the centromere  and was The rich repository of tissues from different developmental origins available through the FAANG project will allow us to answer other important questions on centromere biology using the ECA11 centromere as model system. We will test whether the centromere position is conserved during development or if it can slide during tissue differentiation. In addition, thanks to the large amount of data regarding the functional annotation of the horse genome, generated within the FAANG effort, we will be able to map the epigenetic marks available through the consortium in the ECA11 centromeric region. The results will indicate whether chromatin markers and transcriptional activity at ECA11 centromere vary across tissues and individuals, and with respect to centromere position. Furthermore, CENP-A has been shown to bind at TF binding sites and promoters, suggesting potential regulatory activities . TherefoJust three years after starting the tissue and data collection for the equine FAANG initiative, the community has completed over 400 experiments from more than 50 tissues using a variety of assays targeting different features of the horse regulatory landscape . Data arWith over 80 tissues collected from four healthy and comprehensively phenotyped animals, we will be able to generate a map of gene expression and regulation throughout the horse body, providing unique opportunities to investigate tissue-specific gene expression and gene networks. However, this tissue collection presents a serious challenge for data analyses. Heterogeneity both within tissues as a result of cell-type differentiation and across tissues as a result of tissue infiltration or contamination during collection, can confound analysis of tissue-specific expression and regulation. The prevalence of this issue was recently reported by Sturm et al. . To mitiWhile the equine FAANG biobank represents a wide variety of tissue types, the four horses these tissues were collected from represent only a narrow subset of the horse population, as well as developmental stages. These horses were intentionally selected to be of the same breed as the reference genome assembly in order to better annotate the reference genome assembly. However, caution should be taken with interpretation and extrapolation of these data to other breeds or developmental stages. Regardless, this initiative will serve as a template and reference point for the future expansion of the transcriptome and epigenome of equids. FAANG represents a notable international collaborative effort in the equine community that has brought together equine researchers and practitioners from around the globe. Most importantly, FAANG collaborators have been vocal proponents of open science and broad data accessibility within the equine community. The growing number of publicly available datasets is accelerating discoveries and powering large-scale analyses. Well-annotated and carefully documented FAANG data with accompanying comprehensive metadata will serve as a reference point for many future discoveries in horse.


The slim modiolar electrode has been reported to ensure better modiolar proximity than previous conventional perimodiolar electrodes and consistently high scala tympani localization. Nonetheless, variability in modiolar proximity exists even among slim modiolar electrodes, still leaving room for further improvement of modiolar proximity, which may positively affect functional outcomes. Given this, the pull-back maneuver was reported to increase the modiolar proximity of slim modiolar electrodes in a cadaveric study, but in vivo repositioning effects remain to be established. Here we identified that the pull-back maneuver led to better modiolar proximity than conventional insertion while maintaining a similar angular insertion depth. Notably, the reduced electrode-modiolus distance from the pull-back maneuver was associated with significantly lower impedances across electrodes postoperatively as well as reduced intraoperative electrophysiological thresholds than conventional insertion. Among adult cochlear implant recipients, this maneuver resulted in significantly better sentence recognition scores at three months postoperatively when compared to those with a conventional insertion; however, this benefit was not observed at later intervals. Collectively, slim modiolar electrodes with the pull-back maneuver further enhance the modiolar proximity, possibly leading to better open-set sentence recognition, at least in the early postoperative stage. Modiolar distance and scalar translocation of the electrodes have been suggested as significant positional determinants of hearing outcomes for conventional perimodiolar electrodes, while the depth of insertion was the most significant factor for straight electrode arrays12. Better modiolar proximity has been shown to yield more specific electrical stimulation with a smaller spread of excitation13, leading to better electrode discrimination capability and potentially better speech perception performance15.The slim modiolar electrode   has been reported to ensure better modiolar proximity than other currently available electrodes while reducing intracochlear trauma16, as well as improved battery efficiency18, outdoing conventional perimodiolar electrodes. In addition, the slim structure with controlled insertion via a sheath deployment system enabled consistently higher scala tympani position than did the conventional perimodiolar electrodes20, leaving the degree of modiolar proximity an important adjustable positional determinant influencing speech outcome in slim modiolar electrodes. However, it is still true that modiolar proximity shows considerable variability even among patients implanted with slim modiolar electrodes21.Indeed, there has been recent growing evidence that this new slim modiolar electrode significantly enhanced the efficiency of neural-electrode interaction by reducing electrode modiolar distance (EMD), as evidenced by decreased telemetry threshold levels14, and speech perception outcomes22. However, not all reports in the literature fully support this24, possibly due to presence of other influential/confounding factors, limited sample numbers for statistical significance, or heterogeneous degrees of modiolar proximity even among subjects with slim modiolar electrodes. Alternatively, outcome improvement due to reduction of EMD may have a saturation exactly at the level of EMD provided by conventional perimodiolar electrode, reaching the ceiling effect. Nevertheless, identifying maneuvers or adjustable parameters that could further improve the modiolar proximity of slim modiolar electrodes may help to better test the hypothesis that speech outcome inversely correlates with EMD.A growing body of evidence suggests that the enhanced modiolar proximity of slim modiolar electrodes compared with conventional perimodiolar electrodes would lead to improved place-pitch spectral discrimination25. While advancing past the first marker  of the electrode array led to an increase in EMD, subsequently pulling back to the first white marker of the electrode could elicit significantly enhanced modiolar proximity without any changes in the total insertion depth4. These findings suggest that adjusting the marker position in and out across the round window using this surgical maneuver may affect the electrode position mediolaterally without advancing the tip anteriorly. Despite putative evidence of a link between the pull-back maneuver and better modiolar proximity for modiolar hugging electrodes30, in vivo effects of the pull-back maneuver on EMD and electrophysiological parameters related to slim modiolar electrodes are still lacking. Additionally, the effects on speech outcome due to the change in mediolateral position of electrodes after using this surgical maneuver has never been addressed, even for conventional perimodiolar electrodes, let alone slim modiolar electrodes. Here we explore the in vivo effect of the pull-back maneuver-assisted insertion of slim modiolar electrodes on modiolar proximity, electrophysiological thresholds, and speech perception. Through this study, we aim to reach optimal modiolar proximity by coupling the slim modiolar electrode with a complementary surgical maneuver.Given this, a delicate surgical technique called the “pull-back maneuver” previously demonstrated in human cadaveric temporal bones to enhance the modiolar proximity of slim modiolar electrodes, merits special attentionP < 0.001 by Spearman’s rank-order correlation). However, cochlear duct length reflecting cochlear size did not differ between the conventional insertion and pull-back maneuver groups. Molecular genetic testing was conducted before cochlear implantation on all subjects, while congenital cytomegalovirus (cCMV) screening was conducted before cochlear implantation for subjects with congenital or prelingual deafness. The causative etiology for deafness was heterogeneous, regardless of groups.We conducted a retrospective study consisting of subjects who underwent implantation with a novel slim modiolar electrode  performed by a single surgeon (B.Y.C.) through a round or extended round window approach. Ultimately, a total of 95 ears from 81 subjects with CI532  or CI632  implants were enrolled. Stratified by insertion techniques   of the slim modiolar electrodes in situ on transorbital X-ray were compared between different insertion techniques. This pull-back maneuver did not elicit a significant difference in AID relative to conventional insertion (difference between means ± standard error of mean (SEM), 7.652 ± 5.165, 31. Specifically, the pull-back group  had a significantly shorter spiral diameter than the conventional insertion group  , which evaluates the degree of modiolar proximity based on high-resolution computed tomographyP < 0.05 for E6-E12 by independent t-test) . Overall, significant decrease in electrophysiological thresholds, especially in the upper basal and middle electrodes, indicate that the electrode array is placed closer to the modiolus when the pull-back maneuver is employed, which is congruent with the significantly reduced spiral diameter of slim modiolar electrodes following the pull-back maneuver.After final intracochlear positioning of the electrode arrays, electrically evoked compound action potential (ECAP) thresholds were measured in every channel for all subjects using automatic neural response telemetry (NRT) intraoperatively. Intraoperative ECAP thresholds varied across electrode arrays, regardless of the insertion technique Fig. . We obsest) Fig. . These e25, we then measured ECAP thresholds and took simple X-ray to check spiral diameters in all three techniques of insertion in a single subject: conventional insertion of the electrode first, then over-insertion, followed by pulling back   were subclassified into two groups based on the insertion techniques  and speech perception improvements between baseline and 3 and 6 months, and last follow-up (between 6 months and 1 year) postoperatively were compared. Preoperative speech evaluation was based on the test score with hearing aids considering the implanted ear only Fig. . Considely) Fig. , we decily) Fig.  to minimly) Fig. . Howeverly) Fig. .Figure 6P = 0.022 by Mann–Whitney U test) , which was not statistically significant. These results may exclude the hypothesis that speech outcome improvement due to reduction of EMD may have a saturation at the level of EMD of the conventional perimodiolar electrode. However, the in vivo effects of the pull-back maneuver on speech outcomes would confer more clinical significance in the early stage after surgery. For example, at 6 months postoperatively, the statistical significance for greater speech improvement in the pull-back group was not observed, even though the pull-back maneuver still showed a tendency of greater improvement of spondee word scores compared with the conventional insertion  . In parallel with observations from Fig. P = 0.67; standard rechargeable, P = 0.94; compact rechargeable, P = 0.56)  Fig. .25. As illustrated in Fig. 36. Similarly, a significant decrease in electrophysiological thresholds, coupled with reduced spiral diameters, clearly indicates that the electrode array is placed closer to the modiolus if the pull-back maneuver is employed.To the best of our knowledge, this is the first study to demonstrate the in vivo effects of the pull-back maneuver, coupled with slim modiolar electrodes, on speech outcomes, EMD and electrophysiological parameters. Adjusting the marker position in and out across the round window using this surgical maneuver affected the electrode position mediolaterally without advancing the tip of it anteriorly, replicating those of previous ex vivo studies37. Specifically, Basta et al. suggested that the pull-back technique has its greatest effect exclusively in the basal region of the cochlea  for conventional perimodiolar electrodes , as evidenced by the significantly lower spread of excitation and increased frequency discrimination in the basal electrode  than those in the middle electrodes 27. To interest, our current study elucidates that pull-back maneuver-assisted insertion of slim modiolar electrodes exerts a slightly different effect on electrophysiological parameters than those of conventional perimodiolar electrodes. Specifically, as presented herein, ECAP thresholds of electrode channels corresponding to the upper basal and middle turns (E6-E12) most significantly dropped down when aided by the pull-back maneuver compared with the conventional insertion. This electrophysiologic data was supported by our recent radiological observation that modified ICPI, a reflection of the distance of each electrode contact relative to the modiolus at specific points, marked the lowest value at the upper basal and middle turn regions of cochlear implantees with pull-back maneuver-assisted insertion of slim modiolar electrodes31. Different tonotopic effect from the same maneuver between conventional perimodiolar and slim modiolar electrodes would be attributed to differences in electrode array size, inter-electrode contact distance, and electrode properties . Although the ECAP thresholds of the most basal cochlear electrode channels (E2-3) were relatively higher with pull-back maneuver–assisted insertion than with conventional insertion, as if it were a trade-off, the clinical significance of the loss of modiolar proximity in the distal basal region (E2-3) still requires further research.Which cochlear regions would benefit from electrode repositioning by the pull-back maneuver? The observed effect of the electrode position mediolaterally on the neuronal spread of excitation has extensively been reported for conventional perimodiolar electrodes13. In addition, a generalized linear model has recently shown that the average EMD was one of the most significant factors to predict speech perception scores in cochlear implant recipients with pre-curved arrays12. Our study merits special attention in a sense that further improvement of modiolar proximity by the pull-back maneuver, even at the enhanced level of EMD provided by slim modiolar electrodes compared with conventional perimodiolar electrodes, would again lead to better speech perception outcomes, especially at least in the early stage after surgery, in adult cochlear implant recipients.Previously, Holden et al. suggested an indicator evaluating the medial–lateral position of electrode array  and confirmed that a closer modiolar placement of electrode array remained positively correlated with outcome in postlingually deaf adults, even after adjustment of cofactors23. Additionally, Holder et al. reported that lateral wall electrodes showed higher impedances than the slim modiolar electrode postoperatively1, probably due to greater distance between the electrode and neural tissues38. Consistent with these findings, impedance levels in the pull-back maneuver group presented herein were significantly lower postoperatively compared with those from the conventional insertion group among implantees with slim modiolar electrodes.It could be that improved electrophysiological parameters coupled with enhanced modiolar proximity accounts for the observed functional benefit related to the pull-back maneuver in our study. Indeed, a higher mean ECAP threshold was previously found to be associated with worse speech recognition scores for cochlear implant recipients with slim modiolar electrode1. Notably, the recipients with lateral wall electrode showed not only the higher absolute value but also more variation in impedances over time. Specifically, Shaul et al. showed that lateral wall electrodes significantly led to increase in impedance spikes, related to immunological reaction in the inner ear, compared with the pre-curved arrays39. These results suggest that the physical location of electrodes could affect impedances in several ways. Of course, higher impedance has been proposed to reduce the dynamic range of the stimulation, while requiring higher voltage across the electrode-tissue interface. Taken together, the impedance reduction provided by the pull-back maneuver could be a result of less vulnerability/high tolerance to tissue reaction and would in turn help to formulate mapping strategy, thus enhancing the functional benefits as evidenced by early stages of the sentence domain.Theoretically, impedance levels confer messages also on the status of the electrode-fibrous tissue formation or changes to the resistive properties of the surrounding fluid and tissue40, perhaps due to the presence of confounding factors and small sample sizes limiting the power to identify statistically significant differences. Alternatively, audiological rehabilitation and central brain plasticity may also have diluted the advantage from the improved EMD, resulting in the similar functional outcomes over time between groups, as already shown in several other studies41. Given this, focusing on short-term improvements in speech perception might be a better strategy for deciphering the in vivo effect of the pull-back maneuver-assisted insertion of slim modiolar electrodes on speech perception. In a situation where the importance of EMD can be more pronounced such as cochlear nerve hypoplasia or reduced number of spiral ganglion cells, the effect of this pull-back maneuver might be sustained for a longer time.Intriguingly, our data showed significantly higher speech perception scores at 3 months postoperatively, albeit only in the sentence domain, for the pull-back maneuver group. Particularly, if context clues were provided, the focused electrical stimulation by the pull-back maneuver together with the top-down processing may have improved the sentence score. Unfortunately, this observation was not replicated in the words score domain. Furthermore, improved EMD by the pull-back maneuver on speech perception outcomes has failed to demonstrate long-term functional improvement. This finding is not different from those in previous studies42. Based on the evidence that the electrode-modiolus distance is closely correlated with the ECAP thresholds of the electrodes including slim modiolar electrodes43, a better modiolar proximity with the pull-back maneuver would potentially lead to more favorable outcomes in those with cochlear nerve deficiency than those requiring conventional insertion. In other words, slim modiolar electrodes with pull-back maneuvers could be better in cases with cochlear nerve deficiency, if not completely defective modiolus; however, future studies are required to fully elucidate the effects of modiolar proximity on outcomes among cochlear implant recipients with cochlear nerve deficiency.Although MR imaing indicates cochlear nerve agenesis, such cases may have extremely low, but still exist residual spiral ganglion neurons (SGNs) near the modiolusThere are limitations in this study that should be addressed in the future. Our current study was designed to be a cross-sectional evaluation, which, along with the retrospective study design, may weaken the clinical implications of the results. In addition, selection bias and pre-conceived bias of what was happening would limit the generalization of our results. Future studies employing randomization and correction for multiple comparisons in large-scale cases would be the best fit for proving effects of the pull-back maneuver on electrophysiological and audiological outcomes after cochlear implantation. For the first time, we showed the clinical effect of the pull-back technique using slim modiolar electrodes on speech perception scores, thus strengthening the importance of modiolar proximity of slim modiolar electrodes. However, the results were limited by the short-term follow-up and relatively small number of study subjects consisting of only recipients with post-lingual deafness. Finally, confounding variables related to the final position of the electrode arrays were minimized, but not eliminated. The subjects enrolled in this study had relatively heterogeneous etiologies of deafness. Thus, more efforts to minimize confounding factors are necessary to draw firm conclusions. Future studies with more strict matching strategies should also be considered.We, for the first time, demonstrated the advantages and safety of the pull-back maneuver-assisted insertion of slim modiolar electrodes in adult cochlear implantees, which include maximizing modiolar proximity, better electrophysiological findings, and improved open-set sentence recognition at least in the early stage after implant surgery compared with the conventional insertion.This retrospective study was conducted from July 2018 to December 2019 at Seoul National University Bundang Hospital. Subjects with the following conditions were excluded from this study: (1) definite retro-cochlear pathology  on radiological imaging, (2) history of explantation due to device failure, and (3) severe craniofacial syndrome. This study was approved by the Seoul National University Bundang Hospital Institutional Review Board (IRB No. B-2020-869) and was conducted in accordance with the principles of the Declaration of Helsinki. We obtained written informed consent from either the parents of children or participants themselves in this study.4, the electrode arrays can be advanced or retreated in reference to three white markers of the electrode array and their relationship with the round window, facilitating a finely tuned insertion technique: conventional insertion (first white marker)  Fig. a, over ier) Fig. b, and puer) Fig. c. The in31, upon transorbital X-ray which is taken on the day after implantation, the spiral diameter of the electrode turn was defined as the distance of the electrode turn measured on a horizontal line across the modiolus. As for a single subject in Fig. The depth of angular insertion made by the slim modiolar electrodes in situ on transorbital X-ray were compared between different insertion techniques by an otorhinolaryngologist  who was blind to the insertion technique. As previously describedAfter final intracochlear positioning of the electrode arrays, telemetry recordings were made under sterile conditions in the operating field. As a reference to telemetric measurement via NRT, ECAP thresholds were measured in every channel for all subjects. Only when we were able to obtain ECAP responses from at least nineteen electrodes, the NRT thresholds of such subjects were used for comparison. The threshold of electrodes which did not elicit any NRT response even at the maximum stimulus was judged as 255 (CL) for statistical analyses. Further, stimulation rate (Hz) and the number of sweeps were set as 250 Hz, and 35, respectively, as outlined by guideline.Using the Cochlear custom sound EP 5.2 software, impedances were determined with MP2 and CG stimulation configurations using biphasic pulses at a rate of 250 Hz and were measured intraoperatively and postoperatively (approximately 3–5 weeks). During the test, Custom Sound EP software stimulates each electrode at 80 Current Level in postoperative and intraoperative testing, using a pulse width of 25 us.43, a readily available surgical pre-planning tool  used the Elliptic-Circular Approximation (ECA) method44 was employed to determine individual cochlear duct length from all our subjects.As described in our previous study46, speech performance was thoroughly assessed preoperatively, and 3, 6, and 10–12 months after cochlear implantation using Korean version of the Central Institute for the Deaf (K-CID) and the Korean Spondees and phonetically balanced (PB) words by experienced speech-therapists. The Korean Central Institute for Deafness (K-CID) test, designed to assess understanding of speech performance in everyday conversational situations, was scored based on the percentage of correctly identified words. Speech perception performance was also evaluated through word-recognition tasks using Spondees and phonetically balanced (PB) words at 70 dB SPL in sound-field under a condition of audio-only without any visual cues. Subjects were instructed to repeat the speech stimulus verbally, and the score was recorded as the percent correct (%). The speech perception performance was based on the test score only for each implanted ear while the contralateral ear was masked or plugged when necessary. Specifically, plugging or masking for better ear was performed in cases with asymmetric sensorineural hearing loss between two ears. In case of severe-to-profound sensorineural hearing loss in both ears, plugging or masking was selectively performed in better ears if they had meaningful residual hearing that affects the performance in the implanted ears.As previously describedIndeed, there are differences in the test battery of speech evaluation, depending on the age of 15 years  here in South Korea. Specifically, the perception tests, including PB word, Spondee word, and K-CID Sentence, were conducted in those over 15 years, while only PB word and Sentence tests were conducted in participants below 15. In addition, most cochlear implant recipients with post-lingual onset of deafness were older than 15 years in this cohort. Thus, we explored whether the pull-back maneuver-based physical advantage can lead to improvement in speech outcomes of adult cochlear implant recipients (> 15 years).www.graphpad.com). To compare the outcomes depending on the insertion technique, an independent t-test was performed if the values were normally distributed. Alternatively, the Mann–Whitney U test to obtain comparable results, as appropriate, if the variables were not normally distributed. P values < 0.05 were considered statistically significant.The data are represented as the mean ± SEM. All analyses were done and illustrated using the R statistical package . Again, all the analyses employed and illustrated used the GraphPad Prism version 9.0.0 for Windows, GraphPad Software, San Diego, California USA (Supplementary Figure S1.Supplementary Figure S2.Supplementary Figure S3.Supplementary Figure S4.


Identifying of these genes (hidden genes) is of great significance for understanding disease pathogenesis and guiding drug repurposing. Here, we presented a novel computational tool, called KDDANet, for systematic and accurate uncovering the hidden genes mediating KDDA from the perspective of genome-wide functional gene interaction network. KDDANet demonstrated the competitive performances in both sensitivity and specificity of identifying genes in mediating KDDA in comparison to the existing state-of-the-art methods. Case studies on Alzheimer’s disease (AD) and obesity uncovered the mechanistic relevance of KDDANet predictions. Furthermore, when applied with multiple types of cancer-omics datasets, KDDANet not only recapitulated known genes mediating KDDAs related to cancer, but also revealed novel candidates that offer new biological insights. Importantly, KDDANet can be used to discover the shared genes mediating multiple KDDAs. KDDANet can be accessed at  In addition, only about 10% of new drugs are approved by FDA per year, meaning most new drugs are never approved and taken to market, which prevents them from being used in practice1. The decrease in pharmaceutical research productivity towards new drug development has left a gap between the therapeutic needs of patients and the available treatment paradigms1. Compared with traditional drug development, drug repositioning, i.e., finding the novel indications of existing drugs, offers an alternative approach for safer and faster drug development because of several procedures of traditional drug development workflow are not involved during repurposing efforts2. There are multiple examples of repositioned drugs that are on the market now including Minoxidil, a drug designed to treat hypertension but is now used to treat hair loss3, and Sildenafil, a drug originally developed for patients with heart disease but is now commonly used to treat erectile dysfunction4. However, these examples of repositioned drugs were primarily based on clinical observations of the side effects of the drug5. Thanks to the advance in next-generation omics sequencing and qualification technologies, a large volume of biomedical data, for example, the pharmacogenomics datasets produced by Connective Map project, The Cancer Genome Atlas (TCGA) project, Cancer Cell Line Encyclopedia (CCLE) project, Genomics of Drug Sensitivity in Cancer 1000 human cancer cell lines (GDSC1000) project and Library of Integrated Network-based Cellular Signatures project, has been rapidly accumulated for enabling drug repurposing14. Based on these datasets, various computational methods have been designed for facilitating the process of drug repurposing  On the other hand, one drug can exert impacts on many targets and perturb multiple biological processes35. As a result, the genes of shared biological pathways in the cellular network manifested in certain disease state and induced by a known drug administration suggest potential drug repurposing38. However, many of these genes mediating Known Drug-Disease Associations (KDDAs) across various types of diseases have not yet been identified  and sparse network-regularized partial least square (SNPLS) to identify co-modules related to specific cancer cell lines of NCI-60 and Cancer Genome Projects, respectively41. However, these two methods need to integrate gene-expression and drug-response data of cancer cell lines for constructing models and do not carry out prediction for other types of diseases. The other two methods of comCIPHER and DGPsubNet have been designed to identify the coherent subnetworks linking drugs and diseases (not limited in cancer) with the related genes43. The common shortcomings of these methods are the identified co-modules including multiple drugs and diseases and thus are unable to uncover genes specifically mediating individual KDDA. To this end, we designed a novel computational pipeline, called KDDANet, which uses known functional gene interaction network to identify hidden genes of cellular pathways mediating KDDA in a genome-wide scale. Our KDDANet pipeline depends on three existing network algorithms: minimum cost network flow optimization, depth-first searching, and graph clustering algorithm. The minimum cost network flow optimization has been effectively employed to identify cellular response subnetwork connecting genetic hits and differentially expressed genes, including components of the response that are otherwise hidden or missed from experiments44. KDDANet can be applied to two contexts: (1) uncovering hidden genes mediating the association between a query drug and its related disease (SDrTDi); (2) unveiling hidden genes mediating the association between a query disease and its related drug (SDiTDr). The computational procedure of KDDANet in SDrTDi context was showed in Fig. Theoretically, drug repurposing has been proposed based on two molecular aspects. 1) On one hand, complex diseases often involve multiple genetic and environmental determinants, including multifactor driven alterations and dysregulation of a series of genes On one hhttp://www.kddanet.cn, was provided for user to access the subnetwork of genes mediating KDDA, and the source codes of KDDANet were freely available at https://github.com/huayu1111/KDDANet. In summary, we developed an effective and universal computational tool and an online web source for accurate and systematic discovering hidden genes mediating KDDA and thus providing novel insights into mechanism basis of drug repurposing and disease treatments. We believed that KDDANet can provide additional contributions to the development of new therapies.The key novelty of the KDDANet method lay in that the original designation of a unified flow network model and effective implementing multiple network-based algorithms on this unified flow network model. We demonstrated that KDDANet showed competitive performance in discovering known and novel genes mediating KDDA through a comparison with existing methods. KEGG pathway enrichment analysis on KDDANet resulting subnetworks and case studies on Alzheimer’s disease (AD) and obesity further showed the mechanistic relevance of KDDANet predictions. Validated with multiple types of cancer-omics’ datasets, KDDANet did not only revealed known genes mediating KDDAs associating drug with cancer, but also uncovered new candidates that offer novel biological insights. Particularly, our results demonstrated that KDDANet can reveal the shared genes mediating multiple KDDAs. These outcomes showed the importance of incorporating hidden genes in drug discovery pipelines. For facilitating biomedical researchers to explore the molecular mechanism of KDDA and guiding drug repurposing, an online web server, 12. For a KDDA, we defined the overlap ratio as the number of shared genes between KDTGs and KDRGs divided by the number of total KDTG and KDRG genes. We observed that the most gene sets demonstrated extremely low overlap ratio, with the increasing of gene number, the overlap ratio was sharply decreased  and Known Disease-Related Genes (KDRGs) should be highly overlapped if the genes mediating this KDDA have been fully identified. We analyzed the overlap between KDTGs and KDRGs of 53124 KDDAs obtained from Comparative Toxicogenomics Database (CTD)45 that were included in the drug’s ADME pathways and were responsible for mediating KDDA. Meanwhile, we collected a recently updated set of disease-related genes (B) from DisGeNet v6.0 database46, which were not included in KDDANet flow network model. Based on these, we defined, for each KDDA, the NTKGs as the shared genes between A and B. A parameter γ effected the size and quality of KDDANet output subnetwork, higher γ values will identify more gene links mediating KDDA but with lower confidence. Using gene set enrichment analysis, we observed that KDDANet can consistently and effectively capture the KTKGs and NTKGs mediating KDDA under different γ settings  and “novel true KDDA genes” (NTKGs). For a given KDDA, KTKGs were defined as the shared genes between KDTGs and KDRGs inputted for constructing KDDANet flow network model (see “Dataset” section for details). To obtain NTKGs, we collected a set of drug’s non-target genes (A) from SMPDB 2.0 databaseγ . Among all the methods tested, KDDANet demonstrated the competitive performance with the averages of AUROC 0.733 and 0.715 and AUPRC 0.793 and 0.825 in SDrTDi and SDiTDr contexts, respectively  and Precision-Recall (PR) curves (see “Methods” section for details). We observed that the performance of KDDANet was obviously better than random permutation across a widely settings of γ Fig. , b. We nely Fig. . We furtrks Fig. , f. Coll48. A subnetwork including 46 genes and 44 links were uncovered mediating this association . The top ten enriched KEGG terms of this subnetwork, such as Phospholipase D signaling pathway and Neurotrophin signaling pathway50, were closely related with AD . Three genes used to infer this KDDA, including ARK1, PARP1, and TNF, were also effectively captured in the resulting subnetwork. The top ten enriched functions of this subnetwork were showed in Fig. 63. In addition, proteoglycans, lipolysis, and AMPK signaling pathway were also highly related with Insulin resistance66. In consistent with this, the AUROC and AUPRC values of KDDANet for this subnetwork were 0.854 and 0.849, respectively  and obesity (601665) was inferred by multiple genes as described in CTD database. For this association, KDDANet predicted a subnetwork containing 168 edges connecting 169 genes Fig. . We foun73. For this reason, substantial genetic, genomic and pharmacogenomics efforts, including TCGA, CCLE, and GDSC10009, have been undertaken to improve existing therapies or to guide early-phase clinical trials of compounds under development. With these efforts, an increasing amount of available high-throughput datasets at both levels of genomic data and pharmacogenomics data were produced at recent years. In addition, COSMIC, the world’s largest and most comprehensive resource for exploring the impact of somatic mutations in human cancer, collected a catalog of genes with mutations that were causally implicated in cancer (https://cancer.sanger.ac.uk/cosmic). With these datasets, we observed that the genes of KDDANet resulting subnetworks mediating the associations between drugs and cancer were significantly enriched in COSMIC Cancer Gene Census, and these genes harbored more oncogenic alterations in tumor samples than randomly selected genes  was normally used to treat life-threatening ventricular arrhytmias. It has been reported that sotalol was associated with decreased prostate cancer (176807) risknks Fig. . By appl83. For this association, KDDANet predicted 237 genes connected by 238 links that constituted a subnetwork without apparent modular structure -lung cancer (211980) that was inferred by ADA targeted by nebularineure Fig. . The onlure Fig. . Interesure Fig. . These rComprehensive analysis above fully demonstrated that KDDANet can uncover true genes mediating individual KDDA. We further asked whether KDDANet can reveal the shared genes mediating multiple KDDAs. We answered this from two aspects as follow: (1) Multiple Diseases associating with One Drug (MDiODr); (2) Multiple Drugs associating with One Disease (MDrODi). Considering the practical merits for the first one analysis, we required multiple diseases belongs to the same type of diseases. To evaluate the capability of KDDANet for revealing the shared genes mediating multiple KDDAs, we produced meta-subnetworks by integrating multiple KDDANet resulting subnetworks for 12386 MDiODr combinations and 773 MDrODi combinations produced in SDrTDi context, and 12189 MDiODr combinations and 773 MDrODi combinations in SDiTDr context. The weight of an edge in the meta-subnetwork was defined as the number of KDDA resulting subnetworks containing this edge divided by the total number of KDDA resulting subnetworks. The higher weight value of a link in the meta-subnetwork indicated more conservation and commonality. Thus, we used the weight value to evaluate the capacity of KDDANet in unveiling the shared gene interactions mediating multiple KDDAs. We carried out a permutation test by producing random meta-subnetworks with the same number of edges for comparing with random background. As shown in Fig. 85. Interestingly, we found that GNAI2 and GNA11 were two mostly shared genes linking profenamine with neurological diseases. These two genes were recently discovered involving in the pathological pathways of neurological diseases87. Mirtazapine was associated with nine types of cancers, including Colorectal Neoplasms, Breast Neoplasms, Neuroblastoma, Glioma, Urinary Bladder Neoplasms, Stomach Neoplasms, Esophageal Neoplasms, Lung Neoplasms, and Prostatic Neoplasms. Supplementary Figure 89.We presented some examples for describing the capability of KDDANet in identifying shared genes mediating multiple KDDAs. For MDiODr, we selected two cases: (1) profenamine (DB00392) and neurological disease associations and (2) mirtazapine (DB00370) and cancer associations. As reported in CTD database, profenamine was associated with three neurological diseases, including Parkinsonian Disorders, Multiple Sclerosis, and Alzheimer Disease. The shared meta-subnetwork contained 75 edges linking 43 unknown genes with three profenamine’s target genes and 30 neurological disease-related genes Fig. . The top90. It was also not surprising that the neurological diseases related genes were also enriched in this meta-subnetwork as patients with GRACILE syndrome had severe neurological problems90. Another example was the Keratoconus (148300), an ophthamological disease, which was associated with three different drugs, including acetaminophen, valproic acid and theophylline. Keratoconus and these three drugs shared a meta-subnetwork consisting of 54 genes and 51 edges  mediating KDDA become a great challenge for guiding novel target discovery and drug repurposing. In this work, we developed a novel computational tool, KDDANet, which integrated minimum cost network flow optimization, depth-first searching and graph clustering algorithm to reveal hidden genes and modules mediating KDDA. KDDANet allowed for a global and systematic exploration of the hidden genes mediating KDDA. We applied KDDANet to unravel the subnetworks of genes mediating 53124 KDDAs. The comprehensive and system-level evaluations fully demonstrated the effective prediction capability and general applicability of KDDANet. Case studies on both AD and obesity showed that the subnetworks of genes identified by KDDANet were reliable and useful. Further validated by integrating analysis of genomic, transcriptomic, pharmacogenomic and survival data on primary tumors and cancer cell lines highlighted that KDDANet captured novel candidates from interactome mediating the associations between drugs and different types of cancer. Based on these, we concluded that the inferred subnetworks mediating KDDA can serve as genome-wide molecular landscapes for guiding drug repurposing and disease treatment. Insights learned from our predictions would also enable to help researchers to design repurposing drugs to reverse disease phenotypes via targeting key genes in the subnetwork mediating KDDA. An important capability of KDDANet method was that it can reveal the shared genes mediating multiple KDDAs. This provided more valuable guides for drug repositioning and disease treatment since the shared genes mediating multiple KDDAs were closely linked to the molecular basis of drug repurposing. We constructed a user-friendly online web tool (http://www.kddanet.cn), which allowed users to explore the subnetwork of genes mediating individual KDDA and the meta-subnetworks mediating multiple KDDAs . In this study, we selected 4861 drugs with at least one known target that was contained in the gene networks for further analysis. In total, 2196 KDTGs included in the gene networks were connected to these drugs by 12014 interactions  with the following parameters “ILLUMINACLIP:TruSeq3-PE.fa:2:30:10 LEADING:3 TRAILING:3 SLIDINGWINDOW:4:15 MINLEN:36” (Version 0.36), and were further quality-filtered using FASTX Toolkit’s fastq_quality_trimmer command (http://hannonlab.cshl.edu/fastx_toolkit/) (Version 0.0.13) with the minimum quality score 20 and minimum percent of 80% bases that had a quality score larger than this cutoff value. The high-quality reads were mapped to the hg38 genome by HISAT2, a fast and sensitive spliced alignment program for mapping RNA-seq reads, with -dta paramenter (http://daehwankimlab.github.io/hisat2/). PCR duplicate reads were removed using Picard tools (http://broadinstitute.github.io/picard/) and only uniquely mapped reads were kept for further analysis. The expression levels of genes were calculated by StringTie (http://ccb.jhu.edu/software/stringtie/) (Version v1.3.4d) with -e -B -G parameters using Release 29 (GRCh38.p12) gene annotations downloaded from GENCODE data portal (https://www.gencodegenes.org/). To obtain comparable expression abundance estimation for each gene, reads mapped to hg38 were counted as Fragments Per Kilobase Of Exon Per Million Fragments Mapped based on their genome locations. Differential expression analysis of genes was performed by DESeq2 using the reads count matrix produced from a python script “prepDE.py” provided in StringTie website (http://ccb.jhu.edu/software/stringtie/).The primary RNA-seq datasets of AD patients, obesity patients, and normal individuals were downloaded from NCBI GEO Datasets under the accession number of GSE53697, GSE81965, and GSE63887. After the SRA files were gathered, the archives were extracted and saved in FASTQ format using the SRA Toolkit. RNA-seq reads were trimmed using Trimmomatic software (https://xenabrowser.net/datapages/). As the DNA methylation datasets were quantified as beta value in the DNA probe level, we mapped Illumina Human Methylation 450 probe ID to gene name using HumanMethylation450 annotation file. If a gene was mapped by multiple probes, we considered the averaged signals of these probes as the methylation level of this gene. We used Wilcox signed rank test for differential analysis of gene expression and DNA methylation of KDDANet resulting subnetwork genes mediating the associations between drug and cancer. For this analysis, we only used the tumor samples which have adjacent normal tissue samples as control. GDSC1000 cancer cell line pharmacogenomic datasets were downloaded from GDSC website (https://www.cancerrxgene.org/gdsc1000/GDSC1000_WebResources/Home.html). Since this website provided only the CpG island methylation data, we downloaded the beta value matrix of probe-level DNA methylation from NCBI GEO Dataset under accession number of GSE68379 and then converted it to gene-level beta value matrix using the same method as TCGA DNA methylation data. CCLE pharmacogenomic datasets were directly downloaded from Broad Institute data portal .TCGA cancer genomics datasets were directly downloaded via the UCSC Xena project data portal (S) and integrated it into gene network by introducing the directed edges from it point to its target genes. For each its related disease, we mapped the disease to gene network by introducing the directed edges from its related genes point to it. We incorporated a sink node T and introduced a directed edge pointing from each disease to it. With these definitions, a unified flow network model was constructed as a complex heterogeneous graph G = , where V was the set of vertices and E was the set of edges. This graph included two types of edges  and three types of nodes . Each edge was assigned with a weight and a capacity. Flow goes from a source node to a sink node through the graph edges. The assigning scheme of weight and capacity was illustrated as follow:For each query drug and all its related diseases, the unified flow network model in SDrTDi context was built by integrating the query drug and all its related diseases into the gene network based on known drug-target relationships and gene-disease associations. As shown in Fig. Wij) to reflect the probability that two genes gi and gj were functionally linked in the biological processes. The weight value between gi and gj was derived from a Bayesian statistics approach by integrating diverse functional genomics datasets47. Briefly, each dataset was benchmarked for its real capability of reconstructing known cellular pathways by measuring the likelihood that pairs of genes (linkages) were functionally connected conditioned on the experimental evidence, calculated as a log likelihood score LLS97:F(L|E) and ~F(L|E) represented the observed numbers of linkages L appear in the given experiment E between functionally annotated human genes interacting within the same pathway and between different pathways, respectively, F(L) and ~F(L) denoted the total observed numbers of linkages between all annotated human genes interacting within the same pathway and between different pathways, respectively. The weight value (W) of a given linkage between two genes was produced by combining LLS score of each dataset using the formula:Edges between gene nodes were weighted  to reflect the normalized reliability of the interaction between drug and target protein based on experimental and computational evidence. The weighting scheme was based on the predicted score of drug and target protein interaction25. The weight value (WSi) was calculated as:T denoted the set of each drug’s targets, Pi denotes the predicted score between drug S and target i, Pj denoted the predicted score between drug S and target j.Edges between each drug and the drug’s target gene nodes were weighted (wjd) to reflect the normalized reliability of the linkage between disease and gene based on experimental and computational evidence. The weighting scheme was based on the predicted score of gene-disease association derived from MAXIF algorithm99. We calculated the weight value (Wjd) as follow:D denoted the set of genes linked to disease d, Fi denoted the predicted score between gene i and disease d, Pj denoted the predicted score between gene j and disease d.Edges between disease-related gene and disease nodes were weighted . The solution With the purpose of identifying hidden genes mediating KDDA, we search for an possible solution that would (1) capture the subset of the query drug’s target genes which closely modulate all its related diseases by the disease-related genes without restrict to the prior KDDA genes, (2) determine hidden genes that were likely to be part of cellular pathways connecting the query drug’s target genes to all its related diseases but escaped detection by experiments, (3) give high priority to genes that lie on paths with highest probability connecting the query drug to all its related diseases without making constraints on the network structure. The rationality for proposing this solution including two aspects: (1) this needed less computational time than that finding the highest-probability subnetwork connects a query drug to each its related diseases at a time; (2) this can effectively find the shared genes mediating multiple KDDAs. Similar to how a fluid flows through the path of least resistance, we formulated this goal as a minimum cost flow optimization problem102 on this subgraph to find the subnetwork made up of all paths linking the query drug (disease) to each it’s related disease (drug). All genes in the solution were ranked by the amount of flow they carry. The more flow that passes through a protein, the more important it was in mediating KDDA. After obtaining the subnetwork mediating individual KDDA, MCL (https://micans.org/mcl/) was employed to further discover gene modules mediating KDDA by using the flow quantities through edges of subnetwork as weight values.Once the highest-probability subnetwork mediating the query drug (disease) with all its related diseases (drugs) was obtained, we implemented depth-first searchingS), substituting query drug-related diseases with query disease-related drugs, substituting query drug’s target genes with query disease-related genes, substituting disease-related genes with drug’s target genes, and incorporating a sink node T and introducing a directed edge pointing from each drug to it. Implementing minimum cost flow optimization, depth-first searching, and MCL on the unified flow network was same as SDrTDi context.To apply KDDANet in SDiTDr context, the query disease, and a set of all its related drugs were mapped into gene network by disease-related genes and drug target genes. For constructing flow network model, the weights and capacities of network edges can be assigned using the similar method as described in SDrTDi context by substituting query drug with query disease and using query disease as source node  Based on the hypothesis that the larger functional similarity between a gene and known KDDA genes, the higher probability this gene was positive one mediating KDDA, we compiled a standard set of positive and negative KDDA genes for each KDDA resulting subnetwork to unbiasedly evaluate the performance of KDDANet using the following strategy:103.(1) For each gene in the KDDA resulting subnetwork, we first calculated the mean functional similarity scores of it with KDTGs and KDRGs by our previous published method using gene ontology (GO), KEGG pathways, and InterPro annotation as functional terms(2) We performed a permutation test by randomly producing KDTGs and KDRGs 1000 times to compute the empirical significance level of functional similarity. We selected the genes having significant functional similarities with both KDTGs and KDRGs from KDDA resulting subnetwork as positive KDDA genes using the criterion that the similarity score was larger than 95th percentiles of the simulated background distributions. The other genes were considered as negative KDDA genes.g mediating the association between drug i and a type of cancer j was defined as averaged prediction score across all cell lines of this type of cancer41. For comCHIPER, the probability score of a gene g mediating the association between drug i and disease j was defined as the sum of the products of posterior indicator probabilities across all co-modules42. For DGPsubNet, we defined the probability score of a gene g mediating the association between drug i and disease j as the calculated z score zij43. The areas of under curve of ROC and PR (AUROC and AUPR) were calculated using R package of PRROC. KDDANet resulting subnetwork visualization was carried out using Cytoscape software (https://cytoscape.org/). KEGG pathway enrichment analysis was performed by clusterProfiler R package104. The visualization of results was carried out in R software. Case studies were conducted in SDrTDi context unless specifically indicated.Based on this gold standard, ROC and PR curves were produced and the areas of under curve of ROC and PR (AUROC and AUPRC) were calculated for gene list ranked by flow amount of each KDDANet resulting subnetwork. For comparison with PPA, SNPLS, comCHIPER, and DGPsubNet, we used the default parameters as mentioned in their published papers. We considered that all genes contained in a co-module mediating KDDA of each drug and disease pair in the co-module. The genes were ranked by probability score mediating a KDDA. For PPA and SNPLS, the probability score of a gene Further information on research design is available in the Supplementary InformationReporting SummarySupplementary Data 1Supplementary Data 2Supplementary Data 3Supplementary Data 4