Primary osteoarthritis chondrocyte map of chromatin conformation reveals novel candidate effector genes.

OBJECTIVES: Osteoarthritis is a complex disease with a huge public health burden. Genome-wide association studies (GWAS) have identified hundreds of osteoarthritis-associated sequence variants, but the effector genes underpinning these signals remain largely elusive. Understanding chromosome organisation in three-dimensional (3D) space is essential for identifying long-range contacts between distant genomic features (e.g., between genes and regulatory elements), in a tissue-specific manner. Here, we generate the first whole genome chromosome conformation analysis (Hi-C) map of primary osteoarthritis chondrocytes and identify novel candidate effector genes for the disease. METHODS: Primary chondrocytes collected from 8 patients with knee osteoarthritis underwent Hi-C analysis to link chromosomal structure to genomic sequence. The identified loops were then combined with osteoarthritis GWAS results and epigenomic data from primary knee osteoarthritis chondrocytes to identify variants involved in gene regulation via enhancer-promoter interactions. RESULTS: We identified 345 genetic variants residing within chromatin loop anchors that are associated with 77 osteoarthritis GWAS signals. Ten of these variants reside directly in enhancer regions of 10 newly described active enhancer-promoter loops, identified with multiomics analysis of publicly available chromatin immunoprecipitation sequencing (ChIP-seq) and assay for transposase-accessible chromatin using sequencing (ATAC-seq) data from primary knee chondrocyte cells, pointing to two new candidate effector genes SPRY4 and PAPPA (pregnancy-associated plasma protein A) as well as further support for the gene SLC44A2 known to be involved in osteoarthritis. For example, PAPPA is directly associated with the turnover of insulin-like growth factor 1 (IGF-1) proteins, and IGF-1 is an important factor in the repair of damaged chondrocytes. CONCLUSIONS: We have constructed the first Hi-C map of primary human chondrocytes and have made it available as a resource for the scientific community. By integrating 3D genomics with large-scale genetic association and epigenetic data, we identify novel candidate effector genes for osteoarthritis, which enhance our understanding of disease and can serve as putative high-value novel drug targets.

Assessing Baseline Knowledge and Usage Patterns of Sexual Orientation/Gender Identity Affirming Electronic Health Record Modules Within a Urology Division at a Single Tertiary Care Institution.

OBJECTIVE: To evaluate how sexual orientation and gender identity (SOGI)-affirming electronic health record (EHR) modules (which enable seamless location and documentation of patient SOGI data) are being used by providers/staff within a urology practice. MATERIALS AND METHODS: All 120 patient-facing providers/staff at a tertiary urology program were offered a 39-question Qualtrics-based survey, which assessed respondents' cultural competency, baseline knowledge of SOGI EHR modules, and SOGI module usage patterns. Cultural competency was assessed using the LGBT-Development of Clinical Skills Scale (LGBT-DOCCS). RESULTS: 96 qualified providers/staff completed the survey (response rate, 89%). Only 25% of respondents received training on finding/collecting SOGI data in the EHR. Respondents possessed high levels of LGBTQ attitudinal awareness (M=6.38/7) but low clinical preparedness (M=4.32/7), in large part due to perceived inadequate training to work with LGBT patients. Major drivers of clinical preparedness were respondent role and number of LGBT patients seen in the past year. While respondents uniformly report ease finding SOGI data, all providers/staff (particularly physicians) rarely use formal SOGI documentation tools. Few respondents partook in SOGI EHR training; those that did were significantly more likely to use formal SOGI documentation tools. CONCLUSION: This study revealed that providers/staff possess high general LGBTQ cultural competency and ability to find relevant SOGI data in the EHR, while also highlighting limited training in SOGI-affirming EHR tools and low usage of formal documentation tools. This framework could be a roadmap for evaluating SOGI-affirming EHR use by urology practices as such features increase in popularity.

Identification of Mechanisms by Which Genetic Susceptibility Loci Influence Systemic Sclerosis Risk Using Functional Genomics in Primary T Cells and Monocytes.

OBJECTIVE: Systemic sclerosis (SSc) is a complex autoimmune disease with a strong genetic component. However, most of the genes associated with the disease are still unknown because associated variants affect mostly noncoding intergenic elements of the genome. We used functional genomics to translate the genetic findings into a better understanding of the disease. METHODS: Promoter capture Hi-C and RNA-sequencing experiments were performed in CD4+ T cells and CD14+ monocytes from 10 SSc patients and 5 healthy controls to link SSc-associated variants with their target genes, followed by differential expression and differential interaction analyses between cell types. RESULTS: We linked SSc-associated loci to 39 new potential target genes and confirmed 7 previously known SSc-associated genes. We highlight novel causal genes, such as CXCR5, as the most probable candidate gene for the DDX6 locus. Some previously known SSc-associated genes, such as IRF8, STAT4, and CD247, showed cell type-specific interactions. We also identified 15 potential drug targets already in use in other similar immune-mediated diseases that could be repurposed for SSc treatment. Furthermore, we observed that interactions were directly correlated with the expression of important genes implicated in cell type-specific pathways and found evidence that chromatin conformation is associated with genotype. CONCLUSION: Our study revealed potential causal genes for SSc-associated loci, some of them acting in a cell type-specific manner, suggesting novel biologic mechanisms that might mediate SSc pathogenesis.

Prognostic significance of sarcomatoid features in metastatic renal cell carcinoma treated with cytoreductive nephrectomy and targeted therapy.

INTRODUCTION: The presence of sarcomatoid features in localized renal cell carcinoma (RCC) is associated with worse outcomes. We sought to use a national database to evaluate the outcomes and prognosis of metastatic RCC (mRCC) with sarcomatoid features treated with cytoreductive nephrectomy (CN) and targeted therapy (TT). METHODS: The National Cancer Database (2010-2013) was used to identify patients with mRCC at diagnosis. Only patients who underwent CN followed by TT were included. Kaplan-Meier curves, log-rank test, and multivariate Cox regression analysis were used to compare overall survival (OS) between mRCC with and without sarcomatoid features. Subgroup analysis in patients with clear cell RCC (ccRCC) was performed. RESULTS: A total of 1,427 patients with mRCC treated with CN followed by TT were included of which 364 (26%) had mRCC with sarcomatoid features. mRCC with sarcomatoid features were more likely to have Fuhrman grade 4 cancer. mRCC with sarcomatoid features had worse OS than mRCC without sarcomatoid features (24.6 vs 12.0 months, P < 0.001). For the clear cell cohort, mRCC with sarcomatoid features had worse OS than mRCC without sarcomatoid features (26.2 vs 14.0 months, P < 0.001). Multivariate Cox regression showed sarcomatoid features was significantly associated with worse OS in the overall cohort (hazard ratio [HR] =1.63, 95% confidence interval [CI] =1.38-1.91, P < 0.001) and the ccRCC subcohort (HR=1.53, 95% CI=1.23-1.90, P < 0.001). DISCUSSION/CONCLUSION: mRCC with sarcomatoid features treated with CN and TT has a very poor and drastically different prognosis compared with mRCC without sarcomatoid features. With the expansion of systemic RCC therapies, investigation is needed to optimize treatment in this high-risk cohort.

Automated Machine Learning Segmentation and Measurement of Urinary Stones on CT Scan.

OBJECTIVES: To evaluate the performance of an engineered machine learning algorithm to identify kidney stones and measure stone characteristics without the need for human input. METHODS: We performed a cross-sectional study of 94 children and adults who had kidney stones identified on non-contrast CT. A previously developed deep learning algorithm was trained to segment renal anatomy and kidney stones and to measure stone features. The performance and speed of the algorithm to measure renal anatomy and kidney stone features were compared to the current gold standard of human measurement performed by 3 independent reviewers. RESULTS: The algorithm was 100% sensitive and 100% specific in detecting individual kidney stones. The mean stone volume segmented by the algorithm was smaller than that of human reviewers and had moderate overlap (Dice score: 0.66). There was substantial variation between human reviewers in total segmented stone volume (Jaccard score: 0.17) and volume of the single largest stone (Jaccard score: 0.33). Stone segmentations performed by the machine learning algorithm more precisely approximated stone borders than those performed by human reviewers on qualitative assessment. CONCLUSION: An engineered machine learning algorithm can identify and characterize stones more accurately and reliably than humans, which has the potential to improve the precision and efficiency of assessing kidney stone burden.

Association of Inherited Mutations in DNA Repair Genes with Localized Prostate Cancer.

BACKGROUND: Identification of germline mutations in DNA repair genes has significant implications for the personalized treatment of individuals with prostate cancer (PrCa). OBJECTIVE: To determine DNA repair genes associated with localized PrCa in a diverse academic biobank and to determine genetic testing burden. DESIGN, SETTING, AND PARTICIPANTS: A cross-sectional study of 2391 localized PrCa patients was carried out. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Genetic ancestry and mutation rates (excluding somatic interference) in 17 DNA repair genes were determined in 1588 localized PrCa patients and 3273 cancer-free males. Burden testing within individuals of genetically determined European (EUR) and African (AFR) ancestry was performed between biobank PrCa cases and cancer-free biobank and gnomAD males. RESULTS AND LIMITATIONS: AFR individuals with localized PrCa had lower DNA repair gene mutation rates than EUR individuals (1.4% vs 4.0%, p = 0.02). Mutation rates in localized PrCa patients were similar to those in biobank and gnomAD controls (EUR: 4.0% vs 2.8%, p = 0.15, vs 3.1%, p = 0.04; AFR: 1.4% vs 1.8%, p = 0.8, vs 2.1%, p = 0.5). Gene-based rare variant association testing revealed that only BRCA2 mutations were significantly enriched compared with gnomAD controls of EUR ancestry (1.0% vs 0.28%, p = 0.03). Of the participants, 21% and 11% met high-risk and very-high-risk criteria; of them, 3.7% and 6.2% had any germline genetic mutation and 1.0% and 2.5% had a BRCA2 mutation, respectively. Limitations of this study include an analysis of a relatively small, single-institution cohort. CONCLUSIONS: DNA repair gene germline mutation rates are low in an academic biobank cohort of localized PrCa patients, particularly among individuals of AFR genetic ancestry. Mutation rates in genes with published evidence of association with PrCa exceed 2.5% only in high-risk, very-high-risk localized, and node-positive PrCa patients. These findings highlight the importance of risk stratification in localized PrCa patients to identify appropriate patients for germline genetic testing. PATIENT SUMMARY: In the majority of patients who develop localized prostate cancer, germline genetic testing is unlikely to reveal an inherited DNA repair mutation, regardless of race. High-risk features increase the possibility of a germline DNA repair mutation.

Functional interrogation of autoimmune disease genetics using CRISPR/Cas9 technologies and massively parallel reporter assays.

Genetic studies, including genome-wide association studies, have identified many common variants that are associated with autoimmune diseases. Strikingly, in addition to being frequently observed in healthy individuals, a number of these variants are shared across diseases with diverse clinical presentations. This highlights the potential for improved autoimmune disease understanding which could be achieved by characterising the mechanism by which variants lead to increased risk of disease. Of particular interest is the potential for identifying novel drug targets or of repositioning drugs currently used in other diseases. The majority of autoimmune disease variants do not alter coding regions and it is often difficult to generate a plausible hypothetical mechanism by which variants affect disease-relevant genes and pathways. Given the interest in this area, considerable effort has been invested in developing and applying appropriate methodologies. Two of the most important technologies in this space include both low- and high-throughput genomic perturbation using the CRISPR/Cas9 system and massively parallel reporter assays. In this review, we introduce the field of autoimmune disease functional genomics and use numerous examples to demonstrate the recent and potential future impact of these technologies.

Chromatin Looping Links Target Genes with Genetic Risk Loci for Dermatological Traits.

Chromatin looping between regulatory elements and gene promoters presents a potential mechanism whereby disease risk variants affect their target genes. In this study, we use H3K27ac HiChIP, a method for assaying the active chromatin interactome in two cell lines: keratinocytes and skin lymphoma-derived CD8+ T cells. We integrate public datasets for a lymphoblastoid cell line and primary CD4+ T cells and identify gene targets at risk loci for skin-related disorders. Interacting genes enrich for pathways of known importance in each trait, such as cytokine response (psoriatic arthritis and psoriasis) and replicative senescence (melanoma). We show examples of how our analysis can inform changes in the current understanding of multiple psoriasis-associated risk loci. For example, the variant rs10794648, which is generally assigned to IFNLR1, was linked to GRHL3, a gene essential in skin repair and development, in our dataset. Our findings, therefore, indicate a renewed importance of skin-related factors in the risk of disease.

Process for Delivering Timely Antibiotics to Febrile Bone Marrow Transplant Patients in the Emergency Department.

PURPOSE: Patients with a history of a bone marrow transplant (BMT) have a higher risk of infectious complications because of an immunocompromised state. It has been shown that giving timely antibiotics in 1 hour or less from presentation to the emergency department (ED) decreases morbidity and mortality in this patient population. We hypothesize that a quality improvement (QI) process, termed BMT Fever, will improve timely administration of antibiotics for this population presenting to the ED. METHODS: This is a QI process designed to improve the administration of antibiotics to BMT patients with a subjective or objective fever presenting to the ED. The percent of patients receiving antibiotics within 1 hour or less was compared pre- and post-intervention. RESULTS: Upon implementation of the BMT Fever QI process, the percentage of patients with febrile BMT receiving antibiotics within 1 hour or less per fiscal quarter significantly improved from six out of 28 patients (21%) to 147 out of 173 patients (85%), P value < .05. CONCLUSION: By implementing a QI process that addresses five structural obstacles, we were able to improve our timely administration of antibiotics to patients with febrile BMT presenting to the ED.

Characterisation of CD4+ T-cell subtypes using single cell RNA sequencing and the impact of cell number and sequencing depth.

CD4+ T-cells represent a heterogeneous collection of specialised sub-types and are a key cell type in the pathogenesis of many diseases due to their role in the adaptive immune system. By investigating CD4+ T-cells at the single cell level, using RNA sequencing (scRNA-seq), there is the potential to identify specific cell states driving disease or treatment response. However, the impact of sequencing depth and cell numbers, two important factors in scRNA-seq, has not been determined for a complex cell population such as CD4+ T-cells. We therefore generated a high depth, high cell number dataset to determine the effect of reduced sequencing depth and cell number on the ability to accurately identify CD4+ T-cell subtypes. Furthermore, we investigated T-cell signatures under resting and stimulated conditions to assess cluster specific effects of stimulation. We found that firstly, cell number has a much more profound effect than sequencing depth on the ability to classify cells; secondly, this effect is greater when cells are unstimulated and finally, resting and stimulated samples can be combined to leverage additional power whilst still allowing differences between samples to be observed. While based on one individual, these results could inform future scRNA-seq studies to ensure the most efficient experimental design.

Stakeholder Perspective on Opioid Stewardship After Prostatectomy: Evaluating Barriers and Facilitators From the Pennsylvania Urology Regional Collaborative.

OBJECTIVE: To evaluate existing practice patterns and potential barriers to implementing opioid stewardship protocols after robot-assisted prostatectomies among providers in the Pennsylvania Urology Regional Collaborative. METHODS: The Pennsylvania Urology Regional Collaborative (PURC) is a voluntary quality improvement initiative of 11 academic and community urology practices in Pennsylvania and New Jersey representing 97 urologists. PURC distributed a web-based survey of 24 questions, with 74 respondents, including 56 attendings, 11 residents, and 7 advanced practice providers. RESULTS: More pills were prescribed if there was a default number of pills from the electronic health record (median 30) then if the number of pills was manually placed (P = .01). Only 8% discussed how to dispose of opioids with their patients, and less than a third of respondents discussed postoperative pain expectations or risks of opioid use. Patient level risk factors were often not reviewed, as 42% did not ask about previous opioid exposure. CONCLUSION: This study revealed extensive knowledge disparities among providers about opioid stewardship and significant gaps in the evidence-to-practice continuum of care. In the next year, PURC will be implementing targeted interventions to augment provider education, establish clear pathways for opioid disposal, improve utilization of known resources and implement opioid reduction protocols in all participating sites.

Functional genomics in autoimmune diseases.

Associations between genetic loci and increased susceptibility to autoimmune disease have been well characterized, however, translating this knowledge into mechanistic insight and patient benefit remains a challenge. While improvements in the precision, completeness and accuracy of our genetic understanding of autoimmune diseases will undoubtedly be helpful, meeting this challenge will require two interlinked problems to be addressed: first which of the highly correlated variants at an individual locus is responsible for increased disease risk, and second what are the downstream effects of this variant. Given that the majority of loci are thought to affect non-coding regulatory elements, the second question is often reframed as what are the target gene(s) and pathways affected by causal variants. Currently, these questions are being addressed using a wide variety of novel techniques and datasets. In many cases, these approaches are complementary and it is likely that the most accurate picture will be generated by consolidating information relating to transcription, regulatory activity, chromatin accessibility, chromatin conformation and readouts from functional experiments, such as genome editing and reporter assays. It is clear that it will be necessary to gather this information from disease relevant cell types and conditions and that by doing so our understanding of disease etiology will be improved. This review is focused on the field of autoimmune disease functional genomics with a particular focus on the most exciting and significant research to be published within the last couple of years.

Mapping DNA interaction landscapes in psoriasis susceptibility loci highlights KLF4 as a target gene in 9q31.

BACKGROUND: Genome-wide association studies (GWAS) have uncovered many genetic risk loci for psoriasis, yet many remain uncharacterised in terms of the causal gene and their biological mechanism in disease. This is largely a result of the findings that over 90% of GWAS variants map outside of protein-coding DNA and instead are enriched in cell type- and stimulation-specific gene regulatory regions. RESULTS: Here, we use a disease-focused Capture Hi-C (CHi-C) experiment to link psoriasis-associated variants with their target genes in psoriasis-relevant cell lines (HaCaT keratinocytes and My-La CD8+ T cells). We confirm previously assigned genes, suggest novel candidates and provide evidence for complexity at psoriasis GWAS loci. For one locus, uniquely, we combine further epigenomic evidence to demonstrate how a psoriasis-associated region forms a functional interaction with the distant (> 500 kb) KLF4 gene. This interaction occurs between the gene and active enhancers in HaCaT cells, but not in My-La cells. We go on to investigate this long-distance interaction further with Cas9 fusion protein-mediated chromatin modification (CRISPR activation) coupled with RNA-seq, demonstrating how activation of the psoriasis-associated enhancer upregulates KLF4 and its downstream targets, relevant to skin cells and apoptosis. CONCLUSIONS: This approach utilises multiple functional genomic techniques to follow up GWAS-associated variants implicating relevant cell types and causal genes in each locus; these are vital next steps for the translation of genetic findings into clinical benefit.

Exploring the overlap between rheumatoid arthritis susceptibility loci and long non-coding RNA annotations.

Whilst susceptibility variants for many complex diseases, such as rheumatoid arthritis (RA), have been well characterised, the mechanism by which risk is mediated is still unclear for many loci. This is especially true for the majority of variants that do not affect protein-coding regions. lncRNA represent a group of molecules that have been shown to be enriched amongst variants associated with RA and other complex diseases, compared to random variants. In order to establish to what degree direct disruption of lncRNA may represent a potential mechanism for mediating RA susceptibility, we chose to further explore this overlap. By testing the ability of annotated features to improve a model of disease susceptibility, we were able to demonstrate a local enrichment of enhancers from immune-relevant cell types amongst RA susceptibility variants (log2 enrichment 3.40). This was not possible for lncRNA annotations in general, however a small, but significant enrichment was observed for immune-enriched lncRNA (log2 enrichment 0.867002). This enrichment was no longer apparent when the model was conditioned on immune-relevant enhancers (log2 enrichment -0.372734), suggesting that direct disruption of lncRNA sequence, independent of enhancer disruption, does not represent a major mechanism by which susceptibility to complex diseases is mediated. Furthermore, we demonstrated that, in keeping with general lncRNA characteristics, immune-enriched lncRNA are expressed at low levels that may not be amenable to functional characterisation.

Preventing Excess Narcotic Prescriptions in New Robotic Surgery Discharges: The PENN Prospective Cohort Quality Improvement Initiative.

Purpose: To reduce the amount of opioids prescribed at discharge after robotic surgery, we hypothesized that the majority patients do not require opioids for pain control after robotic urologic oncologic procedures. Materials and Methods: This prospective study aimed to reduce opioids prescribed at discharge after robot-assisted radical prostatectomy (RARP), robot-assisted radical nephrectomy (RARN), and robot-assisted partial nephrectomy (RAPN). Before 9/2018, 100% of patients were discharged on varying amounts of oxycodone (range: 75-337.5 oral morphine milligram equivalents [MME]). We implemented a standardized nonopioid analgesia pathway with escalation options (Fig. 1). To assess the safety of our approach, we analyzed pain scores, telephone encounters, and emergency department visits in our cohort. Results: Our cohort (n = 170) consisted of patients undergoing RARP (n = 87), RARN (n = 25), and RAPN (n = 58) between September 2018 and January 2019. Overall, 67.7% were discharged without opioids, 24.4% with 10 pills of tramadol (50 MME), and 8.2% with 10 pills of oxycodone (75 MME). On multivariable analysis, older age (odds ratio: 0.961, 95% confidence interval: 0.923-0.995, p = 0.026) was associated with lower odds of needing opioids at discharge. There was no difference in pain scores at the postoperative outpatient visit (p = 0.66) or postoperative telephone encounters (p = 0.45) between those discharged with and without opioids. Conclusion: The majority of robotic surgery patients do not require opioids upon discharge. Implementation of a simple, standardized nonopioid protocol resulted in a dramatic reduction in the amount of opioids prescribed in our patient population. An escalation protocol allows for a patient-centered approach to reduce narcotic prescribing, although still addressing surgical pain.

A Model for Improving Health Care Quality for Transgender and Gender Nonconforming Patients.

PROBLEM DEFINITION: Transgender and gender nonconforming (TGNC) populations are disproportionately affected by limited health care access and poor health outcomes and commonly report discrimination and mistreatment in health care settings. Despite these disparities, comprehensive approaches to improve the quality of health care of TGNC patient populations are currently lacking. INITIAL APPROACH: The Vanderbilt Program for LGBTQ Health has developed a multifaceted, community-engaged approach to improve the quality of health care of TGNC patients, which includes the creation of a transgender patient advocacy program, a community advisory board, and a transgender health clinic. To support the continuous quality improvement of transgender health care, the program is currently piloting a novel multilevel monitoring and evaluation (M&E) system to collect information at the individual patient visit and health systems levels. NEXT STEPS: The next steps for Vanderbilt's community-engaged M&E system are to identify the clinics and health services most used by TGNC patients and assess the level of patient satisfaction in each area. This process will support the identification of high- and low-performing clinics and health services and allow for targeted delivery of trainings to improve the quality of culturally competent health care TGNC patients receive systemwide. CONCLUSION: In collaboration with TGNC patient populations and community stakeholders, Vanderbilt has created a model to improve the quality of both transition- and non-transition-related health care at the systems level that can be adopted by other health care systems nationally.

Chromatin interactions reveal novel gene targets for drug repositioning in rheumatic diseases.

OBJECTIVES: There is a need to identify effective treatments for rheumatic diseases, and while genetic studies have been successful it is unclear which genes contribute to the disease. Using our existing Capture Hi-C data on three rheumatic diseases, we can identify potential causal genes which are targets for existing drugs and could be repositioned for use in rheumatic diseases. METHODS: High confidence candidate causal genes were identified using Capture Hi-C data from B cells and T cells. These genes were used to interrogate drug target information from DrugBank to identify existing treatments, which could be repositioned to treat these diseases. The approach was refined using Ingenuity Pathway Analysis to identify enriched pathways and therefore further treatments relevant to the disease. RESULTS: Overall, 454 high confidence genes were identified. Of these, 48 were drug targets (108 drugs) and 11 were existing therapies used in the treatment of rheumatic diseases. After pathway analysis refinement, 50 genes remained, 13 of which were drug targets (33 drugs). However considering targets across all enriched pathways, a further 367 drugs were identified for potential repositioning. CONCLUSION: Capture Hi-C has the potential to identify therapies which could be repositioned to treat rheumatic diseases. This was particularly successful for rheumatoid arthritis, where six effective, biologic treatments were identified. This approach may therefore yield new ways to treat patients, enhancing their quality of life and reducing the economic impact on healthcare providers. As additional cell types and other epigenomic data sets are generated, this prospect will improve further.