Opioid Switch Dosing in Chronic Cancer Pain: A Prospective Longitudinal Study

Background: Opioid switching is common, however, conversion tables have limitations. Guidelines suggest postswitch dose reduction, yet, observations show opioid doses may increase postswitch. Objectives: To document the opioid conversion factor postswitch in cancer, and whether pain and adverse effect outcomes differ between switched opioid groups. Design/Setting: This multicenter prospective longitudinal study included people with advanced cancer in Australia. Clinical data (demographics, opioids) and validated instruments (pain, adverse effects) were collected twice, seven days apart. Results: Opioid switch resulted in dose increase (median oral morphine equivalent daily dose 90 mg [interquartile range {IQR} 45-184] to 150 mg [IQR 79-270]), reduced average pain (5.1 [standard deviation {SD} 1.7] to 3.8 [SD 1.6]), and reduced adverse effects. Hydromorphone dose increased 2.5 times (IQR 1.0-3.6) above the original conversion factor used. Conclusions: Opioid switching resulted in overall dose increase, particularly when switching to hydromorphone. Higher preswitch dosing may require higher dose conversion ratios. Dose reduction postswitch risks undertreatment and may not be always appropriate.

Effect of gene variants on opioid dose, pain and adverse effect outcomes in advanced cancer: an explorative study

Aim: Associations between gene variants and opioid net effect are unclear. We conducted an exploratory pharmacogenetic analysis of 35 gene variants and opioid response in advanced cancer. Patients & methods: This multi-center prospective cohort study included clinical data, questionnaires (pain and adverse effects) and DNA (blood). Negative binomial regression and logistic regression were used. Results: Within 54 participants, eight statistically significant associations (p = 0.002-0.038) were observed between gene variants and opioid dose, pain scores or adverse effects, the majority being within the neuroimmune TLR4 pathway (IL1B [rs1143634], IL2 [rs2069762], IL6 [rs1800795], BDNF [rs6265]) and ARRB2 pathway (ARRB2 [rs3786047], DRD2 [rs6275]). Conclusion: Neuroimmune pathway genes may contribute to differences in opioid response in cancer and may be included in future similar studies.

Atlas of primary cell-type-specific sequence models of gene expression and variant effects

Human biology is rooted in highly specialized cell types programmed by a common genome, 98% of which is outside of genes. Genetic variation in the enormous noncoding space is linked to the majority of disease risk. To address the problem of linking these variants to expression changes in primary human cells, we introduce ExPectoSC, an atlas of modular deep-learning-based models for predicting cell-type-specific gene expression directly from sequence. We provide models for 105 primary human cell types covering 7 organ systems, demonstrate their accuracy, and then apply them to prioritize relevant cell types for complex human diseases. The resulting atlas of sequence-based gene expression and variant effects is publicly available in a user-friendly interface and readily extensible to any primary cell types. We demonstrate the accuracy of our approach through systematic evaluations and apply the models to prioritize ClinVar clinical variants of uncertain significance, verifying our top predictions experimentally.

Prevalence, Severity, and Predictors of Insomnia in Advanced Colorectal Cancer

CONTEXT

Insomnia is an under-recognized and undertreated symptom in palliative care and advanced cancer cohorts. Insomnia in an advanced colorectal cancer cohort is yet to be investigated despite colorectal cancer being the third commonest cancer worldwide and one with a high symptom burden.

OBJECTIVES

To examine the prevalence of insomnia and its associations in a large advanced colorectal cancer cohort.

METHODS

A consecutive cohort study of 18,302 patients with colorectal cancer seen by palliative care services across various settings (inpatient, outpatient, and ambulatory) was conducted from an Australia-wide database (2013-2019). The Symptom Assessment Score (SAS) was used to assess the severity of insomnia. Clinically significant insomnia was defined as SAS score ≥3/10, and used to compare associations with other symptoms and functional scores from validated questionnaires.

RESULTS

The prevalence of any insomnia was 50.5%, and clinically significant insomnia 35.6%, particularly affecting people who were younger (<45-years-old), more mobile (AKPS score ≥70), or physically capable (RUG-ADL score ≤5). Outpatients and patients living at home had higher prevalence of insomnia. Nausea, anorexia and psychological distress were the commonest concurrent symptoms in patients with clinically significant insomnia.

CONCLUSIONS

To our knowledge, this study was the first to investigate the prevalence and associations of insomnia in an advanced colorectal cancer cohort. Our findings demonstrate several groups at greater risk of suffering from insomnia (younger, greater physical capacity, living at home, and those with greater psychological distress). This may guide earlier recognition and management of insomnia to improve overall quality of life in this population.

Effectiveness of Opioid Switching in Advanced Cancer Pain: A Prospective Observational Cohort Study

Opioid switching is a common practice of substituting one opioid for another to improve analgesia or adverse effects; however, it has limited evidence. This study aimed to examine the effectiveness of opioid switching in advanced cancer. This multi-center prospective cohort study recruited patients assessed to switch opioids (opioid switch group) or to continue ongoing opioid treatment (control group). Clinical data (demographics, opioids) and validated instruments (pain and adverse effects) were collected over two timepoints seven days apart. Descriptive analyses were utilized. Non-parametric tests were used to determine differences. Fifty-four participants were recruited (23 control group, 31 switch group). At the follow-up, opioid switching reduced pain (worst, average, and now) (p < 0.05), uncontrolled breakthrough pain (3-fold reduction, p = 0.008), and psychological distress (48% to 16%, p < 0.005). The switch group had a ≥25% reduction in the reported frequency of seven moderate-to-severe adverse effects (score ≥ 4), compared to a reduction in only one adverse effect in the control group. The control group experienced no significant pain differences at the follow-up. Opioid switching is effective at reducing pain, adverse effects, and psychological distress in a population with advanced cancer pain, to levels of satisfactory symptom control in most patients within 1 week.

Defining research priorities and needs in cancer symptoms for adults diagnosed with cancer: an Australian/New Zealand modified Delphi study

PURPOSE

This study asked consumers (patients, carers) and healthcare professionals (HCPs) to identify the most important symptoms for adults with cancer and potential treatment interventions.

METHODS

A modified Delphi study was conducted involving two rounds of electronic surveys based on prevalent cancer symptoms identified from the literature. Round 1 gathered information on participant demographics, opinions and/or experience on cancer symptom frequency and impact, and suggestions for interventions and/or service delivery models for further research to improve management of cancer symptoms. In Round 2, respondents ranked the importance of the top ten interventions identified in Round 1. In Round 3, separate expert panels of consumers and healthcare professionals (HCPs) attempted to reach consensus on the symptoms and interventions previously identified.

RESULTS

Consensus was reached for six symptoms across both groups: fatigue, constipation, diarrhoea, incontinence, and difficulty with urination. Notably, fatigue was the only symptom to reach consensus across both groups in Round 1. Similarly, consensus was reached for six interventions across both groups. These were the following: medicinal cannabis, physical activity, psychological therapies, non-opioid interventions for pain, opioids for breathlessness and cough, and other pharmacological interventions.

CONCLUSIONS

Consumers and HCPs prioritise differently; however, the symptoms and interventions that reached consensus provide a basis for future research. Fatigue should be considered a high priority given its prevalence and its influence on other symptoms. The lack of consumer consensus indicates the uniqueness of their experience and the need for a patient-centred approach. Understanding individual consumer experience is important when planning research into better symptom management.

Does cancer type and adjuvant analgesic prescribing influence opioid dose?-a retrospective cross-sectional study

Opioids are the backbone of cancer pain management. Minimal evidence exists examining the relationship between cancer type and opioid dose. Similarly, the use of adjuvant analgesics and its impact within an inpatient cancer setting is understudied. This study examined the influence of cancer type upon opioid dose, measured by oral morphine equivalent daily dose (oMEDD). The effect of adjuvant analgesics on patient oMEDD was also examined. This retrospective cross-sectional study examined records of 520 patients admitted to Royal Melbourne Hospital or Peter MacCallum Cancer Centre between 2016 and 2018 with advanced cancer. Number and dose of both opioid and adjuvant analgesics were collected along with demographic and cancer data. Comparisons of median oMEDD by cancer type [analysis of variance (ANOVA), non-parametric t-tests] and adjuvant analgesics (Kruskal-Wallis test) were performed. There were no statistically significant differences in oMEDD between the 12 cancer types (P=0.83; n=215). Patients co-prescribed pregabalin (n=102) and paracetamol (n=73) as adjuvant analgesics were on significantly higher daily oMEDD [60 mg (P=0.015), 90 mg (P<0.001), respectively]. Opioid dose did not differ significantly between cancer types. The observed use of adjuvant analgesics coincided with significantly higher oMEDD prescription which may relate to complex pain seen in this cohort of inpatients in a quarternary cancer centre. Future research should focus on pain type and aetiology, and pain scores in different cancer pain syndromes to determine the net effect of opioids and adjuvants in cancer pain prescribing.

ENhANCE trial protocol: A multi-centre, randomised, phase IV trial comparing the efficacy of oxycodone/naloxone prolonged release (OXN PR) versus oxycodone prolonged release (Oxy PR) tablets in patients with advanced cancer

Background

Oxycodone is a frequently used opioid in cancer. Opioid-induced constipation (OIC) is common. Oxycodone/Naloxone Prolonged Release (OXN PR) contains naloxone, which mitigates OIC. Trials have either focused on non-cancer pain, or conducted before significant experience of using OXN PR. This trial aims to: demonstrate (1) analgesic equivalence between OXN PR and Oxycodone Prolonged Release (Oxy PR), and (2) superiority of constipation outcomes in OXN PR compared to Oxy PR in cancer pain. Unlike other trials, it will only include patients with at least moderate pain scores (≥4/10), allow usual laxatives, and exclude potential liver dysfunction.

Methods

This is a multi-centre, open-label, randomised, phase IV study of OXN PR vs Oxy PR in patients with cancer-related pain. The primary outcome is pain difference on Brief Pain Inventory-Short Form (BPI-SF) at 5 weeks. Secondary outcomes are comparison of other pain outcomes (BPI-SF) and neuropathic pain measures (Leeds Assessment of Neuropathic Symptoms & Signs (S-LANNS)), constipation (Bowel Function Index (BFI)), quality of life (EORTC-QLQ-C30), rescue analgesia use, total opioid dose, and total laxative dose over 5 weeks.

Conclusion

The comparison of analgesic efficacy between both arms, and superiority of constipation in the OXN PR arm will add new knowledge on the comparisons of both agents, and oxycodone independently. This trial will extend knowledge of the effectiveness, safety, and adverse effect profiles of both drugs in terms of pain, constipation, quality of life outcomes for patients with cancer pain, and provide clinicians with high quality data to guide decision making.

Trial registration

Name of the registry: ANZCTR

Trial registration number

ACTRN12619001282178

Date of registration

17/09/2019

URL of trial registry record

https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377673&isReview=true

Protocol version 2.1_28 August 2020

•

Opioid-induced constipation is the commonest side effect in cancer pain management.

•

Oxycodone/naloxone prolonged release aims to reduce opioid-induced constipation.

•

Trials have little focus on cancer pain, concurrent liver impairment, and laxatives.

•

This trial evaluates these key problems practically to guide decision making.

Do Patient Demographics and Performance Status Influence Opioid Dose in Cancer Pain?

Context: There is limited evidence on the role of objective parameters in influencing analgesic use in cancer pain management.Objective: To investigate the significance of objective parameters (age, male/female and performance status) in influencing opioid dose. Methods: We conducted a retrospective cross-sectional audit of adult inpatients with metastatic cancer at a major cancer centre from 1 January 2016 to 31 December 2018, who were prescribed slow release opioids for cancer pain on discharge. Main outcome measures were demographics (age, male/female and performance status), oral morphine equivalent daily dose (oMEDD) and adjuvant analgesic use. Results: Of the 7,747 eligible records, 215 patient records fulfilled inclusion criteria. Older patients (≥75 years) received half of the median oMEDD dose (30 mg) compared to their youngest counterparts (60 mg oMEDD in age ≤50 years) (P = .003). No significant differences were observed between oMEDD and male/female and performance status. Conclusion: Older patients are prescribed half the opioid dose compared to their younger counterparts. This highlights the importance of vigilance in opioid prescribing in the elderly in order to balance side effects with under treatment. Although no other significant relationships were observed, future studies comparing objective patient parameters with opioid prescription may uncover other at risk populations.

A Multi-Centre COVID-19 Study Examining Symptoms and Medication Use in the Final Week of Life

CONTEXT

Guidelines exist to direct end-of-life symptom management in COVID-19 patients. However, the real-world symptom patterns, and degree of concordance with guidelines on medication use, and palliative care involvement has received limited attention.

OBJECTIVES

To describe the evolution of COVID-19 symptoms, medication used to alleviate these, and degree of palliative care involvement in the final week of life.

METHODS

This retrospective study reviewed all COVID-19 inpatient deaths across five metropolitan hospitals in Australia from January 1 to December 31, 2020. Outcome measures were collected at day of death, and days one, two, five and seven before death. These were COVID-19 symptom severity (measured by the Palliative Care Outcome Scale), and use of supportive pharmacological and non-pharmacological therapies. Palliative care referral timepoint was also collected.

RESULTS

Within the sample of 230 patients, commonest symptoms were breathlessness, agitation, pain, and respiratory secretions. On day of death, 79% (n = 181) experienced at least one symptom, and 30% (n = 68) experienced severe/extreme symptoms. The use of midazolam, glycopyrrolate, and infusions for symptom management occurred late, less frequently, and at lower doses than suggested in guidelines and other studies. Palliative care referrals were made late, at median three days before death (IQR 1-6 days), and for only half of people dying from COVID-19 (51%; n = 118).

CONCLUSION

Symptoms peaked in final three days of life. Earlier use of in fusional and breakthrough medications should be considered in anticipation of symptoms given high likelihood of dying in discomfort. Earlier palliative care referral for high-risk patients should be considered at hospital admission.

A multi-centre study on patients dying from COVID-19: Communication Between Clinicians, Patients, and their Families

Background

COVID−19 has led to challenges in providing effective and timely communication in healthcare. Services have been required to adapt and evolve as successful communication remains core to high quality patient‐centred care.

Aim

This study aims to describe the communication between admitted patients, their families and clinicians (medical, nursing, allied health) during end‐of‐life care.

Methods

This retrospective review included all patients (n = 230) who died directly due to COVID‐19 at five Melbourne hospitals between 1 January and 31 December 2020. Contacts and modality used (face to face, video, telephone) during the 8 days prior to death were recorded.

Results

Patients were predominantly elderly (median age 86 years) and from residential aged care facilities (62% (n = 141)). Communication frequency increased the closer the patient was to death, where on day of death, contact between clinicians and patients was 93% (n = 213) clinicians and families 97%(n = 222) and between patients and families 50% (n = 115). Most contact between patients and families was facilitated by a clinician (91.3% (n = 105) day of death) with the most commonly used mode being video call (n = 30 day of death).

Conclusion

This study is one of the first and largest Australian reports on how communication occurs at the end of life for patients dying of COVID‐19. Contact rates were relatively low between patients and families, compared to other cohorts dying from non COVID‐19 related causes. The impact of this difference on bereavement outcomes requires surveillance and attention.

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Modeling transcriptional regulation of model species with deep learning

To enable large-scale analyses of transcription regulation in model species, we developed DeepArk, a set of deep learning models of the cis-regulatory activities for four widely studied species: Caenorhabditis elegans, Danio rerio, Drosophila melanogaster, and Mus musculus DeepArk accurately predicts the presence of thousands of different context-specific regulatory features, including chromatin states, histone marks, and transcription factors. In vivo studies show that DeepArk can predict the regulatory impact of any genomic variant (including rare or not previously observed) and enables the regulatory annotation of understudied model species.

COVID-19 End-of-life Care: Symptoms and Supportive Therapy Use in an Australian Hospital

Background

Descriptions of symptoms and medication use at end of life in COVID‐19 are limited to small cross‐sectional studies, with no Australian longitudinal data.

Aims

To describe end‐of‐life symptoms and care needs of people dying of COVID‐19.

Methods

This retrospective cohort study included consecutive admitted patients who died at a Victorian tertiary referral hospital from 1 January to 30 September directly due to COVID‐19. Clinical characteristics, symptoms and use of supportive therapies, including medications and non‐pharmacological interventions in the last 3 days of life were extracted.

Results

The cohort comprised 58 patients (median age 87 years, interquartile range (IQR) 81–90) predominantly admitted from home (n = 30), who died after a median of 11 days (IQR 6–28) in the acute medical (n = 31) or aged care (n = 27) wards of the hospital. The median Charlson Comorbidity Score was 7 (IQR 5–8). Breathlessness (n = 42), agitation (n = 36) and pain (n = 33) were the most frequent clinician‐reported symptoms in the final 3 days of life, with most requiring opioids (n = 52), midazolam (n = 40), with dose escalation commonly being required. While oxygen therapy was commonly used (n = 47), few (n = 13) required an anti‐secretory agent.

Conclusions

This study presents one of the first and largest Australian report of the end of life and symptom experience of people dying of COVID‐19. This information should help clinicians to anticipate palliative care needs of these patients, for example, recognising that higher starting doses of opioids and sedatives may help reduce prevalence and severity of breathlessness and agitation near death.

Tissue-specific enhancer functional networks for associating distal regulatory regions to disease

Systematic study of tissue-specific function of enhancers and their disease associations is a major challenge. We present an integrative machine-learning framework, FENRIR, that integrates thousands of disparate epigenetic and functional genomics datasets to infer tissue-specific functional relationships between enhancers for 140 diverse human tissues and cell types, providing a regulatory-region-centric approach to systematically identify disease-associated enhancers. We demonstrated its power to accurately prioritize enhancers associated with 25 complex diseases. In a case study on autism, FENRIR-prioritized enhancers showed a significant proband-specific de novo mutation enrichment in a large, sibling-controlled cohort, indicating pathogenic signal. We experimentally validated transcriptional regulatory activities of eight enhancers, including enhancers not previously reported with autism, and demonstrated their differential regulatory potential between proband and sibling alleles. Thus, FENRIR is an accurate and effective framework for the study of tissue-specific enhancers and their role in disease. FENRIR can be accessed at fenrir.flatironinstitute.org/.

Genome-wide landscape of RNA-binding protein target site dysregulation reveals a major impact on psychiatric disorder risk

Despite the strong genetic basis of psychiatric disorders, the underlying molecular mechanisms are largely unmapped. RNA-binding proteins (RBPs) are responsible for most post-transcriptional regulation, from splicing to translation to localization. RBPs thus act as key gatekeepers of cellular homeostasis, especially in the brain. However, quantifying the pathogenic contribution of noncoding variants impacting RBP target sites is challenging. Here, we leverage a deep learning approach that can accurately predict the RBP target site dysregulation effects of mutations and discover that RBP dysregulation is a principal contributor to psychiatric disorder risk. RBP dysregulation explains a substantial amount of heritability not captured by large-scale molecular quantitative trait loci studies and has a stronger impact than common coding region variants. We share the genome-wide profiles of RBP dysregulation, which we use to identify DDHD2 as a candidate schizophrenia risk gene. This resource provides a new analytical framework to connect the full range of RNA regulation to complex disease.

GIANT 2.0: genome-scale integrated analysis of gene networks in tissues

GIANT2 (Genome-wide Integrated Analysis of gene Networks in Tissues) is an interactive web server that enables biomedical researchers to analyze their proteins and pathways of interest and generate hypotheses in the context of genome-scale functional maps of human tissues. The precise actions of genes are frequently dependent on their tissue context, yet direct assay of tissue-specific protein function and interactions remains infeasible in many normal human tissues and cell-types. With GIANT2, researchers can explore predicted tissue-specific functional roles of genes and reveal changes in those roles across tissues, all through interactive multi-network visualizations and analyses. Additionally, the NetWAS approach available through the server uses tissue-specific/cell-type networks predicted by GIANT2 to re-prioritize statistical associations from GWAS studies and identify disease-associated genes. GIANT2 predicts tissue-specific interactions by integrating diverse functional genomics data from now over 61 400 experiments for 283 diverse tissues and cell-types. GIANT2 does not require any registration or installation and is freely available for use at http://giant-v2.princeton.edu.

Whole-genome deep-learning analysis identifies contribution of noncoding mutations to autism risk

We address the challenge of detecting the contribution of noncoding mutations to disease with a deep-learning-based framework that predicts the specific regulatory effects and the deleterious impact of genetic variants. Applying this framework to 1,790 autism spectrum disorder (ASD) simplex families reveals a role in disease for noncoding mutations-ASD probands harbor both transcriptional- and post-transcriptional-regulation-disrupting de novo mutations of significantly higher functional impact than those in unaffected siblings. Further analysis suggests involvement of noncoding mutations in synaptic transmission and neuronal development and, taken together with previous studies, reveals a convergent genetic landscape of coding and noncoding mutations in ASD. We demonstrate that sequences carrying prioritized mutations identified in probands possess allele-specific regulatory activity, and we highlight a link between noncoding mutations and heterogeneity in the IQ of ASD probands. Our predictive genomics framework illuminates the role of noncoding mutations in ASD and prioritizes mutations with high impact for further study, and is broadly applicable to complex human diseases.

Interpretation of an individual functional genomics experiment guided by massive public data

A key unmet challenge in interpreting omics experiments is inferring biological meaning in the context of public functional genomics data. We developed a computational framework, Your Evidence Tailored Integration (YETI; http://yeti.princeton.edu/ ), which creates specialized functional interaction maps from large public datasets relevant to an individual omics experiment. Using this tailored integration, we predicted and experimentally confirmed an unexpected divergence in viral replication after seasonal or pandemic human influenza virus infection.

Extended care unit: a feasible economic solution for longer-term palliative inpatients

Palliative patients who cannot go home are placed into nursing homes. This involves moving between up to five locations in the final weeks of life. We censored all inpatients on a single day from a large tertiary centre to investigate the feasibility of a proposed extended care unit to accommodate patients with a prognosis of less than 90 days, unable to return home, and with nursing home referral process commenced. This study identifies a present demand for an extended care unit (15 patients identified), outlines admission criteria, and proposes a funding model that is predicted to save hospital costs (savings of $207.70 per patient per bed day). This patient-focused approach is a feasible economic solution to the current unmet needs of this patient demographic.

An integrative tissue-network approach to identify and test human disease genes

Effective discovery of causal disease genes must overcome the statistical challenges of quantitative genetics studies and the practical limitations of human biology experiments. Here we developed diseaseQUEST, an integrative approach that combines data from human genome-wide disease studies with in silico network models of tissue- and cell-type-specific function in model organisms to prioritize candidates within functionally conserved processes and pathways. We used diseaseQUEST to predict candidate genes for 25 different diseases and traits, including cancer, longevity, and neurodegenerative diseases. Focusing on Parkinson's disease (PD), a diseaseQUEST-directed Caenhorhabditis elegans behavioral screen identified several candidate genes, which we experimentally verified and found to be associated with age-dependent motility defects mirroring PD clinical symptoms. Furthermore, knockdown of the top candidate gene, bcat-1, encoding a branched chain amino acid transferase, caused spasm-like 'curling' and neurodegeneration in C. elegans, paralleling decreased BCAT1 expression in PD patient brains. diseaseQUEST is modular and generalizable to other model organisms and human diseases of interest.

Deep learning sequence-based ab initio prediction of variant effects on expression and disease risk

Key challenges for human genetics, precision medicine and evolutionary biology include deciphering the regulatory code of gene expression and understanding the transcriptional effects of genome variation. However, this is extremely difficult because of the enormous scale of the noncoding mutation space. We developed a deep learning-based framework, ExPecto, that can accurately predict, ab initio from a DNA sequence, the tissue-specific transcriptional effects of mutations, including those that are rare or that have not been observed. We prioritized causal variants within disease- or trait-associated loci from all publicly available genome-wide association studies and experimentally validated predictions for four immune-related diseases. By exploiting the scalability of ExPecto, we characterized the regulatory mutation space for human RNA polymerase II-transcribed genes by in silico saturation mutagenesis and profiled > 140 million promoter-proximal mutations. This enables probing of evolutionary constraints on gene expression and ab initio prediction of mutation disease effects, making ExPecto an end-to-end computational framework for the in silico prediction of expression and disease risk.

GIANT API: an application programming interface for functional genomics

GIANT API provides biomedical researchers programmatic access to tissue-specific and global networks in humans and model organisms, and associated tools, which includes functional re-prioritization of existing genome-wide association study (GWAS) data. Using tissue-specific interaction networks, researchers are able to predict relationships between genes specific to a tissue or cell lineage, identify the changing roles of genes across tissues and uncover disease-gene associations. Additionally, GIANT API enables computational tools like NetWAS, which leverages tissue-specific networks for re-prioritization of GWAS results. The web services covered by the API include 144 tissue-specific functional gene networks in human, global functional networks for human and six common model organisms and the NetWAS method. GIANT API conforms to the REST architecture, which makes it stateless, cacheable and highly scalable. It can be used by a diverse range of clients including web browsers, command terminals, programming languages and standalone apps for data analysis and visualization. The API is freely available for use at http://giant-api.princeton.edu.

Network-based analysis of genetic variants associated with hippocampal volume in Alzheimer's disease: a study of ADNI cohorts

Background

Alzheimer’s disease (AD) is a neurodegenerative disease that causes dementia. While molecular basis of AD is not fully understood, genetic factors are expected to participate in the development and progression of the disease. Our goal was to uncover novel genetic underpinnings of Alzheimer’s disease with a bioinformatics approach that accounts for tissue specificity.

Findings

We performed genome-wide association studies (GWAS) for hippocampal volume in two Alzheimer’s Disease Neuroimaging Initiative (ADNI) cohorts. We used these GWAS in a subsequent tissue-specific network-wide association study (NetWAS), which applied nominally significant associations in the initial GWAS to identify disease relevant patterns in a functional network for the hippocampus. We compared prioritized gene lists from NetWAS and GWAS with literature curated AD-associated genes from the Online Mendelian Inheritance in Man (OMIM) database. In the ADNI-1 GWAS, where we also observed an enrichment of low p-values, NetWAS prioritized disease-gene associations in accordance with OMIM annotations. This was not observed in the ADNI-2 dataset. We provide source code to replicate these analyses as well as complete results under permissive licenses.

Conclusions

We performed the first analysis of hippocampal volume using NetWAS, which uses machine learning algorithms applied to tissue-specific functional interaction network to prioritize GWAS results. Our findings support the idea that tissue-specific networks may provide helpful context for understanding the etiology of common human diseases and reveal challenges that network-based approaches encounter in some datasets. Our source code and intermediate results files can facilitate the development of methods to address these challenges.

Electronic supplementary material

The online version of this article (doi:10.1186/s13040-016-0082-8) contains supplementary material, which is available to authorized users.

Interactive Big Data Resource to Elucidate Human Immune Pathways and Diseases

Many functionally important interactions between genes and proteins involved in immunological diseases and processes are unknown. The exponential growth in public high-throughput data offers an opportunity to expand this knowledge. To unlock human-immunology-relevant insight contained in the global biomedical research effort, including all public high-throughput datasets, we performed immunological-pathway-focused Bayesian integration of a comprehensive, heterogeneous compendium comprising 38,088 genome-scale experiments. The distillation of this knowledge into immunological networks of functional relationships between molecular entities (ImmuNet), and tools to mine this resource, are accessible to the public at http://immunet.princeton.edu. The predictive capacity of ImmuNet, established by rigorous statistical validation, is easily accessed by experimentalists to generate data-driven hypotheses. We demonstrate the power of this approach through the identification of unique host-virus interaction responses, and we show how ImmuNet complements genetic studies by predicting disease-associated genes. ImmuNet should be widely beneficial for investigating the mechanisms of the human immune system and immunological diseases.

IMP 2.0: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks

IMP (Integrative Multi-species Prediction), originally released in 2012, is an interactive web server that enables molecular biologists to interpret experimental results and to generate hypotheses in the context of a large cross-organism compendium of functional predictions and networks. The system provides biologists with a framework to analyze their candidate gene sets in the context of functional networks, expanding or refining their sets using functional relationships predicted from integrated high-throughput data. IMP 2.0 integrates updated prior knowledge and data collections from the last three years in the seven supported organisms (Homo sapiens, Mus musculus, Rattus norvegicus, Drosophila melanogaster, Danio rerio, Caenorhabditis elegans, and Saccharomyces cerevisiae) and extends function prediction coverage to include human disease. IMP identifies homologs with conserved functional roles for disease knowledge transfer, allowing biologists to analyze disease contexts and predictions across all organisms. Additionally, IMP 2.0 implements a new flexible platform for experts to generate custom hypotheses about biological processes or diseases, making sophisticated data-driven methods easily accessible to researchers. IMP does not require any registration or installation and is freely available for use at http://imp.princeton.edu.

FNTM: a server for predicting functional networks of tissues in mouse

Functional Networks of Tissues in Mouse (FNTM) provides biomedical researchers with tissue-specific predictions of functional relationships between proteins in the most widely used model organism for human disease, the laboratory mouse. Users can explore FNTM-predicted functional relationships for their tissues and genes of interest or examine gene function and interaction predictions across multiple tissues, all through an interactive, multi-tissue network browser. FNTM makes predictions based on integration of a variety of functional genomic data, including over 13 000 gene expression experiments, and prior knowledge of gene function. FNTM is an ideal starting point for clinical and translational researchers considering a mouse model for their disease of interest, researchers already working with mouse models who are interested in discovering new genes related to their pathways or phenotypes of interest, and biologists working with other organisms to explore the functional relationships of their genes of interest in specific mouse tissue contexts. FNTM predicts tissue-specific functional relationships in 200 tissues, does not require any registration or installation and is freely available for use at http://fntm.princeton.edu.

Low-variance RNAs identify Parkinson's disease molecular signature in blood

The diagnosis of Parkinson's disease (PD) is usually not established until advanced neurodegeneration leads to clinically detectable symptoms. Previous blood PD transcriptome studies show low concordance, possibly resulting from the use of microarray technology, which has high measurement variation. The Leucine-rich repeat kinase 2 (LRRK2) G2019S mutation predisposes to PD. Using preclinical and clinical studies, we sought to develop a novel statistically motivated transcriptomic-based approach to identify a molecular signature in the blood of Ashkenazi Jewish PD patients, including LRRK2 mutation carriers. Using a digital gene expression platform to quantify 175 messenger RNA (mRNA) markers with low coefficients of variation (CV), we first compared whole-blood transcript levels in mouse models (1) overexpressing wild-type (WT) LRRK2, (2) overexpressing G2019S LRRK2, (3) lacking LRRK2 (knockout), and (4) and in WT controls. We then studied an Ashkenazi Jewish cohort of 34 symptomatic PD patients (both WT LRRK2 and G2019S LRRK2) and 32 asymptomatic controls. The expression profiles distinguished the four mouse groups with different genetic background. In patients, we detected significant differences in blood transcript levels both between individuals differing in LRRK2 genotype and between PD patients and controls. Discriminatory PD markers included genes associated with innate and adaptive immunity and inflammatory disease. Notably, gene expression patterns in levodopa-treated PD patients were significantly closer to those of healthy controls in a dose-dependent manner. We identify whole-blood mRNA signatures correlating with LRRK2 genotype and with PD disease state. This approach may provide insight into pathogenesis and a route to early disease detection.

Tissue-aware data integration approach for the inference of pathway interactions in metazoan organisms

MOTIVATION

Leveraging the large compendium of genomic data to predict biomedical pathways and specific mechanisms of protein interactions genome-wide in metazoan organisms has been challenging. In contrast to unicellular organisms, biological and technical variation originating from diverse tissues and cell-lineages is often the largest source of variation in metazoan data compendia. Therefore, a new computational strategy accounting for the tissue heterogeneity in the functional genomic data is needed to accurately translate the vast amount of human genomic data into specific interaction-level hypotheses.

RESULTS

We developed an integrated, scalable strategy for inferring multiple human gene interaction types that takes advantage of data from diverse tissue and cell-lineage origins. Our approach specifically predicts both the presence of a functional association and also the most likely interaction type among human genes or its protein products on a whole-genome scale. We demonstrate that directly incorporating tissue contextual information improves the accuracy of our predictions, and further, that such genome-wide results can be used to significantly refine regulatory interactions from primary experimental datasets (e.g. ChIP-Seq, mass spectrometry).

AVAILABILITY AND IMPLEMENTATION

An interactive website hosting all of our interaction predictions is publically available at http://pathwaynet.princeton.edu. Software was implemented using the open-source Sleipnir library, which is available for download at https://bitbucket.org/libsleipnir/libsleipnir.bitbucket.org.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Homing of neural stem cells from the venous compartment into a brain infarct does not involve conventional interactions with vascular endothelium

Human neural stem cells (hNSCs) hold great potential for treatment of a wide variety of neurodegenerative and neurotraumatic conditions. Heretofore, administration has been through intracranial injection or implantation of cells. Because neural stem cells are capable of migrating to the injured brain from the intravascular space, it seemed feasible to administer them intravenously if their ability to circumvent the blood-brain barrier was enhanced. In the present studies, we found that interactions of hNSCs in vitro on the luminal surface of human umbilical vein endothelial cells was enhanced following enforced expression of cutaneous lymphocyte antigen on cell surface moieties by incubation of hNSCs with fucosyltransferase VI and GDP-fucose (fhNSCs). Interestingly, ex vivo fucosylation of hNSCs not only did not improve the cells homing into the brain injured by stroke following intravenous administration but also increased mortality of rats compared with the nonfucosylated hNSC group. Efforts to explain these unexpected findings using a three-dimensional flow chamber device revealed that transmigration of fhNSCs (under conditions of physiological shear stress) mediated by stromal cell-derived factor 1α was significantly decreased compared with controls. Further analysis revealed that hNSCs poorly withstand physiological shear stress, and their ability is further decreased following fucosylation. In addition, fhNSCs demonstrated a higher frequency of cellular aggregate formation as well as a tendency for removal of fucose from the cell surface. In summary, our findings suggest that the behavior of hNSCs in circulation is different from that observed with other cell types and that, at least for stroke, intravenous administration is a suboptimal route, even when the in vitro rolling ability of hNSCs is optimized by enforced fucosylation.

Functional knowledge transfer for high-accuracy prediction of under-studied biological processes

A key challenge in genetics is identifying the functional roles of genes in pathways. Numerous functional genomics techniques (e.g. machine learning) that predict protein function have been developed to address this question. These methods generally build from existing annotations of genes to pathways and thus are often unable to identify additional genes participating in processes that are not already well studied. Many of these processes are well studied in some organism, but not necessarily in an investigator's organism of interest. Sequence-based search methods (e.g. BLAST) have been used to transfer such annotation information between organisms. We demonstrate that functional genomics can complement traditional sequence similarity to improve the transfer of gene annotations between organisms. Our method transfers annotations only when functionally appropriate as determined by genomic data and can be used with any prediction algorithm to combine transferred gene function knowledge with organism-specific high-throughput data to enable accurate function prediction.

We show that diverse state-of-art machine learning algorithms leveraging functional knowledge transfer (FKT) dramatically improve their accuracy in predicting gene-pathway membership, particularly for processes with little experimental knowledge in an organism. We also show that our method compares favorably to annotation transfer by sequence similarity. Next, we deploy FKT with state-of-the-art SVM classifier to predict novel genes to 11,000 biological processes across six diverse organisms and expand the coverage of accurate function predictions to processes that are often ignored because of a dearth of annotated genes in an organism. Finally, we perform in vivo experimental investigation in Danio rerio and confirm the regulatory role of our top predicted novel gene, wnt5b, in leftward cell migration during heart development. FKT is immediately applicable to many bioinformatics techniques and will help biologists systematically integrate prior knowledge from diverse systems to direct targeted experiments in their organism of study.

Due to technical and ethical challenges many human diseases or biological processes are studied in model organisms. Discoveries in these organisms are then transferred back to human or other model organisms. Traditional methods for transferring novel gene function annotations have relied on finding genes with high sequence similarity believed to share evolutionary ancestry. However, sequence similarity does not guarantee a shared functional role in molecular pathways. In this study, we show that functional genomics can complement traditional sequence similarity measures to improve the transfer of gene annotations between organisms. We coupled our knowledge transfer method with current state-of-the-art machine learning algorithms and predicted gene function for 11,000 biological processes across six organisms. We experimentally validated our prediction of wnt5b's involvement in the determination of left-right heart asymmetry in zebrafish. Our results show that functional knowledge transfer can improve the coverage and accuracy of machine learning methods used for gene function prediction in a diverse set of organisms. Such an approach can be applied to additional organisms, and will be especially beneficial in organisms that have high-throughput genomic data with sparse annotations.

Marker panels for genealogy-based mapping, breed demographics, and inference-of-ancestry in the dog

Short tandem repeat polymorphisms (STRPs) are robust and informative markers for a range of genetic applications. STRPs are advantageous in experimental designs that derive power from sampling many individuals rather than many loci (e.g., pedigree-based studies, fine-scale mapping, and conservation genetics). STRPs have proven useful for vetting samples prior to costly high-density SNP analysis. Here we present validated STRPs (n = 1,012) spanning the canine genome (2.1 +/-1.4 Mb; 2.1 +/-2.1 cM). Standardized design, pre-multiplexing, M13-based dye-labeling, and selection for loci amenable to semi-automated allele-scoring minimize cost and facilitate efficient genotyping. The markers are leveraged from the canine linkage map, and thus are backed by genetic data useful for parametric multipoint analysis and assessment of empiric coverage. We demonstrate several applications with different marker subsets. The complete set provides a genome scan for linkage at ∼5 cM resolution. A subset of the markers measures molecular diversity between domestic and wild canid populations. Another subset reflects ancestry within breeds, uncovering hidden stratification and flagging genetic outliers prior to SNP genotyping. Thus, the markers described here add flexibility and cost effectiveness to several genetic applications in the dog that complement genome-wide SNP genotyping studies. Supplemental material is available for this article. Go to the publisher's online edition of Animal Biotechnology.

A de novo mutation in KIT causes white spotting in a subpopulation of German Shepherd dogs

Although variation in the KIT gene is a common cause of white spotting among domesticated animals, KIT has not been implicated in the diverse white spotting observed in the dog. Here, we show that a loss-of-function mutation in KIT recapitulates the coat color phenotypes observed in other species. A spontaneous white spotting observed in a pedigree of German Shepherd dogs was mapped by linkage analysis to a single locus on CFA13 containing KIT (pairwise LOD = 15). DNA sequence analysis identified a novel 1-bp insertion in the second exon that co-segregated with the phenotype. The expected frameshift and resulting premature stop codons predicted a severely truncated c-Kit receptor with presumably abolished activity. No dogs homozygous for the mutation were recovered from multiple intercrosses (P = 0.01), suggesting the mutation is recessively embryonic lethal. These observations are consistent with the effects of null alleles of KIT in other species.

Tissue-specific functional networks for prioritizing phenotype and disease genes

Integrated analyses of functional genomics data have enormous potential for identifying phenotype-associated genes. Tissue-specificity is an important aspect of many genetic diseases, reflecting the potentially different roles of proteins and pathways in diverse cell lineages. Accounting for tissue specificity in global integration of functional genomics data is challenging, as “functionality” and “functional relationships” are often not resolved for specific tissue types. We address this challenge by generating tissue-specific functional networks, which can effectively represent the diversity of protein function for more accurate identification of phenotype-associated genes in the laboratory mouse. Specifically, we created 107 tissue-specific functional relationship networks through integration of genomic data utilizing knowledge of tissue-specific gene expression patterns. Cross-network comparison revealed significantly changed genes enriched for functions related to specific tissue development. We then utilized these tissue-specific networks to predict genes associated with different phenotypes. Our results demonstrate that prediction performance is significantly improved through using the tissue-specific networks as compared to the global functional network. We used a testis-specific functional relationship network to predict genes associated with male fertility and spermatogenesis phenotypes, and experimentally confirmed one top prediction, Mbyl1. We then focused on a less-common genetic disease, ataxia, and identified candidates uniquely predicted by the cerebellum network, which are supported by both literature and experimental evidence. Our systems-level, tissue-specific scheme advances over traditional global integration and analyses and establishes a prototype to address the tissue-specific effects of genetic perturbations, diseases and drugs.

Tissue specificity is an important aspect of many genetic diseases, reflecting the potentially different roles of proteins and pathways in diverse cell lineages. We propose an effective strategy to model tissue-specific functional relationship networks in the laboratory mouse. We integrated large scale genomics datasets as well as low-throughput tissue-specific expression profiles to estimate the probability that two proteins are co-functioning in the tissue under study. These networks can accurately reflect the diversity of protein functions across different organs and tissue compartments. By computationally exploring the tissue-specific networks, we can accurately predict novel phenotype-related gene candidates. We experimentally confirmed a top candidate gene, Mybl1, to affect several male fertility phenotypes, predicted based on male-reproductive system-specific networks and we predicted candidates related to a rare genetic disease ataxia, which are supported by experimental and literature evidence. The above results demonstrate the power of modeling tissue-specific dynamics of co-functionality through computational approaches.

IMP: a multi-species functional genomics portal for integration, visualization and prediction of protein functions and networks

Integrative multi-species prediction (IMP) is an interactive web server that enables molecular biologists to interpret experimental results and to generate hypotheses in the context of a large cross-organism compendium of functional predictions and networks. The system provides a framework for biologists to analyze their candidate gene sets in the context of functional networks, as they expand or focus these sets by mining functional relationships predicted from integrated high-throughput data. IMP integrates prior knowledge and data collections from multiple organisms in its analyses. Through flexible and interactive visualizations, researchers can compare functional contexts and interpret the behavior of their gene sets across organisms. Additionally, IMP identifies homologs with conserved functional roles for knowledge transfer, allowing for accurate function predictions even for biological processes that have very few experimental annotations in a given organism. IMP currently supports seven organisms (Homo sapiens, Mus musculus, Rattus novegicus, Drosophila melanogaster, Danio rerio, Caenorhabditis elegans and Saccharomyces cerevisiae), does not require any registration or installation and is freely available for use at http://imp.princeton.edu.

Necrotizing meningoencephalitis of Pug dogs associates with dog leukocyte antigen class II and resembles acute variant forms of multiple sclerosis

Necrotizing meningoencephalitis (NME) is a disorder of Pug Dogs that appears to have an immune etiology and high heritability based on population studies. The present study was undertaken to identify a genetic basis for the disease. A genome-wide association scan with single tandem repeat (STR) markers showed a single strong association near the dog leukocyte antigen (DLA) complex on CFA12. Fine resolution mapping with 27 STR markers on CFA12 further narrowed association to the region containing DLA-DRB1, -DQA1 and, -DQB1 genes. Sequencing confirmed that affected dogs were more likely to be homozygous for specific alleles at each locus and that these alleles were linked, forming a single high risk haplotype. The strong DLA class II association of NME in Pug Dogs resembles that of human multiple sclerosis (MS). Like MS, NME appears to have an autoimmune basis, involves genetic and nongenetic factors, has a relatively low incidence, is more frequent in females than males, and is associated with a vascularly orientated nonsuppurative inflammation. However, NME of Pug Dogs is more aggressive in disease course than classical human MS, appears to be relatively earlier in onset, and involves necrosis rather than demyelination as the central pathobiologic feature. Thus, Pug Dog encephalitis (PDE) shares clinical features with the less common acute variant forms of MS. Accordingly, NME of Pug Dogs may represent a naturally occurring canine model of certain idiopathic inflammatory disorders of the human central nervous system.

A comprehensive linkage map of the dog genome

We have leveraged the reference sequence of a boxer to construct the first complete linkage map for the domestic dog. The new map improves access to the dog's unique biology, from human disease counterparts to fascinating evolutionary adaptations. The map was constructed with approximately 3000 microsatellite markers developed from the reference sequence. Familial resources afforded 450 mostly phase-known meioses for map assembly. The genotype data supported a framework map with approximately 1500 loci. An additional approximately 1500 markers served as map validators, contributing modestly to estimates of recombination rate but supporting the framework content. Data from approximately 22,000 SNPs informing on a subset of meioses supported map integrity. The sex-averaged map extended 21 M and revealed marked region- and sex-specific differences in recombination rate. The map will enable empiric coverage estimates and multipoint linkage analysis. Knowledge of the variation in recombination rate will also inform on genomewide patterns of linkage disequilibrium (LD), and thus benefit association, selective sweep, and phylogenetic mapping approaches. The computational and wet-bench strategies can be applied to the reference genome of any nonmodel organism to assemble a de novo linkage map.

DOGSET: pre-designed primer sets for fine-scale mapping and DNA sequence interrogation in the dog

DOGSET is an online resource that provides access to primer sequences that have been computationally mined from the reference genome using heuristic algorithms. The electronic repository includes PCR primers corresponding to 32,135 markers for genetic mapping and 334,657 sequence-tagged gene elements for targeted re-sequencing and mutation discovery. A customized report that tailors primer design to wet bench protocols can be exported for a region of interest by specifying genome coordinates in a graphical user interface.

Evidence for unique association signals in SLE at the CD28-CTLA4-ICOS locus in a family-based study

CD28, CTLA4 (cytotoxic T lymphocyte-associated protein 4) and ICOS (inducible T cell co-stimulator) are good candidate genes for systemic lupus erythematosus (SLE) because of their role in regulating T cell activation. CTLA4 inhibits CD28-mediated T cell activation. CTLA4 is expressed on CD4+ and CD8+ activated T cells, and also B cells, but CD28 and ICOS are largely restricted to T cells. An interval encompassing the CD28-CTLA4-ICOS locus on chromosome 2q33 was linked to lupus in two genome-wide linkage scans. This large family-based association study in 532 UK SLE families represents the first high-density genetic screen of 80 SNPs at this locus. There are seven haplotype blocks across the locus. In CTLA4, the strongest signal comes from two variants, located 2.1 kb downstream from the 3'-UTR. These polymorphisms, rs231726 (SNP 43) and rs231726 (SNP 44), are in complete linkage disequilibrium (LD) (r(2)=1) and are associated with SLE P=0.0008 (GH) and P=0.01 (family-based association test). There is also a signal in the distal 3' flanking region of CTLA4/ICOS promoter (P=0.003). There was no confirmation of published associations for SLE in the promoter or coding region of CTLA4. These SLE risk alleles are more distal than those identified in Graves' disease and are in LD with Graves' disease protective alleles identified in both of these regions of CTLA4 (Ueda et al. 2003). These factors suggest an SLE-specific pattern of association. The functional consequences of the associated polymorphisms are likely to influence CTLA4 expression, although it is possible that genetically modulated ICOS expression is involved in SLE susceptibility.

Breed distribution and history of canine mdr1-1Delta, a pharmacogenetic mutation that marks the emergence of breeds from the collie lineage

A mutation in the canine multidrug resistance gene, MDR1, has previously been associated with drug sensitivities in two breeds from the collie lineage. We exploited breed phylogeny and reports of drug sensitivity to survey other purebred populations that might be genetically at risk. We found that the same allele, mdr1-1Delta, segregated in seven additional breeds, including two sighthounds that were not expected to share collie ancestry. A mutant haplotype that was conserved among affected breeds indicated that the allele was identical by descent. Based on breed histories and the extent of linkage disequilibrium, we conclude that all dogs carrying mdr1-1Delta are descendants of a dog that lived in Great Britain before the genetic isolation of breeds by registry (ca. 1873). The breed distribution and frequency of mdr1-1Delta have applications in veterinary medicine and selective breeding, whereas the allele's history recounts the emergence of formally recognized breeds from an admixed population of working sheepdogs.

Circulating antibodies to guanosine in systemic lupus erythematosus: correlation with nephritis and polyserositis by acute and longitudinal analyses

Systemic lupus erythematosus (SLE) is characterized by autoantibodies, including antibodies to the nucleosides of DNA. Guanosine is the most immunogenic nucleoside. In this study serum antiguanosine antibody levels were compared with disease activity, determined by their SLEDI score, in 86 patients with SLE. Sera from these patients were tested, by ELISA, for autoantibodies to guanosine, single-stranded DNA (ssDNA), and double-stranded DNA (dsDNA). Anti-double-stranded DNA levels were also measured by RIA. Resultant values from these assays were correlated with SLE disease activity, and compared with specific features of SLE. The strongest correlation was higher levels of antiguanosine antibodies in patients with active lupus nephritis and polyserositis compared to patients with inactive disease (P < 0.0001). Antiguanosine levels also correlated with arthritis (P < 0.006), CNS lupus (P < 0.005), and hematologic manifestations of SLE (P < 0.002). To test the validity of this association in chronic SLE, serum antiguanosine antibodies were measured in patients with SLE at various phases of disease activity. Twelve patients with SLE had serum samples drawn at active, active-improved, and inactive phases over a 3-7 y period. Differences were significant for serum antiguanosine antibodies in the active group compared to the inactive group (P < 0.05) and the active vs the active-improved group (P < 0.02), unlike those for dsDNA and ssDNA by ELISA or RIA. Antiguanosine antibodies correlated more closely with disease activity in SLE patients in this longitudinal study than either anti-dsDNA or ssDNA antibodies. Thus, antibodies to guanosine correlated as well or better with disease activity than the other anti-DNA antibodies measured and should be considered to contribute to the pathology of SLE, especially lupus nephritis.

Prevention of recurrent central venous stenosis using endovascular irradiation following stent placement in hemodialysis patients

This study was done to evaluate the outcome after brachytherapy (BT) given to prevent restenosis after stent insertion for central venous stenosis in patients with ipsilateral hemodialysis arteriovenous fistulas (AVF). Angioplasty and stenting were performed on 9 primary central venous stenoses in 8 patients with AVF followed by BT, delivering Iridium-192 radiation using an afterloading technique. BT was also administered to three patients with five recurrent stenoses at the stent margins. There was no residual stenosis after angioplasty and stenting. Venographic follow-up (77-644 days, mean 272 days) showed no restenosis in seven primary stenoses. New strictures (45%-100%) developed at the stent margin in six veins (five patients). Angioplasty or stenting was performed for five margin stenoses in three patients, followed by a second BT. Residual stenosis before BT was 0-30%. In our venographic follow-up (140-329 days, mean 215 days), three restenoses occurred (35%-100%). All progressed to complete occlusion on later venographic follow-up irrespective of whether BT was given to the stent margin or not. The mean primary and assisted primary patency of the central veins were 359 days and 639 days, respectively. Endovascular irradiation with a noncentering source does not prolong the patency after angioplasty and stenting of central venous stenosis in hemodialysis patients.

Relationship between adequacy of dialysis and nutritional status, and their impact on patient survival on CAPD in Hong Kong

OBJECTIVE

Superior patient survival on continuous ambulatory peritoneal dialysis (CAPD) with 3 x 2-L exchanges has been reported from Hong Kong. This study examined the relationship between indices of dialysis adequacy and nutrition and patient survival on CAPD in Hong Kong.

DESIGN

A cross-sectional study on prevalent CAPD patients. Patients were assessed for indices of dialysis adequacy and nutritional status with a composite nutritional index (CNI). Patients were then followed for 24 months. Survival data were analyzed according to adequacy indices and nutritional status.

SETTING

All prevalent CAPD patients in nine dialysis centers in Hong Kong as of 1 April 1996.

MAIN OUTCOME MEASURE

Mortality.

RESULTS

937 patients were assessed: 68.2% were using 3 x 2-L exchanges per day; mean age was 54.6 +/- 13 years. Mean total Kt/V was 1.83 +/- 0.42 and total creatinine clearance was 55.6 +/- 19.5 L/week/1.73 m2. 19% of patients were moderately to severely malnourished according to the CNI. There was no significant correlation between indices of adequacy and serum albumin or CNI. The 1- and 2-year patient survival from the time of assessment was 90.9% and 79.8%. There was a trend toward better survival in patients with Kt/V greater than 2.0, but it was not statistically significant. Peritoneal Kt/V did not impact survival in anuric patients. Malnourished patients had poorer survival than patients who were better nourished (p = 0.0259). After adjusting for age and diabetes, CNI was predictive of mortality but Kt/V and creatinine clearance were not.

CONCLUSIONS

This study demonstrates the importance of nutritional status over adequacy indices in predicting patient survival. There was a lack of correlation between nutritional status and conventional indices of dialysis adequacy.

Excessive tumor-elaborated VEGF and its neutralization define a lethal paraneoplastic syndrome

Vascular endothelial growth factor (VEGF) is a potent endothelial cell mitogen and key regulator of both physiologic and pathologic (e.g., tumor) angiogenesis. In the course of studies designed to assess the ability of constitutive VEGF to block tumor regression in an inducible RAS melanoma model, mice implanted with VEGF-expressing tumors sustained high morbidity and mortality that were out of proportion to the tumor burden. Documented elevated serum levels of VEGF were associated with a lethal hepatic syndrome characterized by massive sinusoidal dilation and endothelial cell proliferation and apoptosis. Systemic levels of VEGF correlated with the severity of liver pathology and overall clinical compromise. A striking reversal of VEGF-induced liver pathology and prolonged survival were achieved by surgical excision of VEGF-secreting tumor or by systemic administration of a potent VEGF antagonist (VEGF-TRAP(R1R2)), thus defining a paraneoplastic syndrome caused by excessive VEGF activity. Moreover, this VEGF-induced syndrome resembles peliosis hepatis, a rare human condition that is encountered in the setting of advanced malignancies, high-dose androgen therapy, and Bartonella henselae infection. Thus, our findings in the mouse have suggested an etiologic role for VEGF in this disease and may lead to diagnostic and therapeutic options for this debilitating condition in humans.

Mutation analyses of 268 candidate genes in human tumor cell lines

We have performed a homozygous deletion screen on 268 candidate genes in 90 human tumor cell lines derived from multiple types of cancers. Most of the candidate genes investigated have been proposed to be involved in cellular processes that are germane to cancer progression, such as cell cycle control, genome maintenance, chromatin remodeling, cell adhesion, and apoptosis. We have detected novel homozygous deletions affecting four independent loci: Brahma-related gene (SMARCA4) on chromosome 19p in the TSU-Pr1 prostate and A427 lung carcinoma lines, Map Kinase Kinase 3 (MAP2K3) on 17q in the NCI-H774 lung tumor cell line, TMPRSS2 on 21q in the Bx PC-3 pancreatic carcinoma line, and Cadherin 6 (CDH6) on 5p in the SK-LU-1 lung carcinoma line. Subsequent analyses of the coding sequences of these four genes using cDNAs from a panel of tumor cell lines revealed multiple sequence variants. The results of this mutation study serve to demonstrate the feasibility of performing high-throughput screens of candidate genes in tumor cell lines to identify genes that may be targeted for mutation during the development of cancer.

Prospective study on renal outcome of IgA nephropathy superimposed on diabetic glomerulosclerosis in type 2 diabetic patients

BACKGROUND AND METHODS

In order to examine the clinical outcome of IgA nephropathy (IgAN) superimposed on diabetic glomerulosclerosis in type 2 patients we studied 36 Chinese patients (26 men, 10 women), who were recruited for renal biopsy when they had proteinuria of more than 1 g/day. Twenty-seven had isolated diabetic glomerulosclerosis and nine had IgAN superimposed on diabetic glomerulosclerosis (combined). Renal function was assessed by serial serum creatinine, 24-h urine protein and creatinine measurements. Patient survival rate, incidence of end-stage renal disease (ESRD), blood pressure, and glycaemic control status were determined.

RESULTS

The age at the time of renal biopsy was younger for the combined group when compared with the diabetic glomerulosclerosis group (44+/-3.6 vs 58+/-2.1 years, P=0.006). The duration of diabetes was, however, similar for the two groups (8.0+/-2.3 vs 6.7+/-1.2 years, P=NS). After a mean follow-up of 31.6+/-15.3 months, 15 patients (one in the combined group and 14 in the diabetic glomerulosclerosis group) developed ESRD. Nine patients (all in the diabetic glomerulosclerosis group) died during follow-up. With similar glycaemic and blood pressure control, the two groups had comparable rate of decline of creatinine clearance (CrCl) (-0.73+/-0.26 vs -0.73+/- 0.18 ml/min/1.73 m(2)/month, P=NS), final serum creatinine (363+/-134 vs 426+/-52 micromol/l, P=NS) and proteinuria levels (4.3+/-0.9 vs 4.4+/-0.6 g/day, P=NS), as well as CrCl (44.1+/-19.0 vs 33.4+/-6.9 ml/min/ 1.73 m(2), P=NS).

CONCLUSION

It is concluded that the superimposed IgAN does not significantly alter the medium-term clinical outcome of patients with diabetic glomerulosclerosis.

Species dependence for binding of small molecule agonist and antagonists to the C5a receptor on polymorphonuclear leukocytes

This study investigated the receptor binding affinities of a C5a agonist and cyclic antagonists for polymorphonuclear leukocytes (PMNs) isolated from human, sheep, pig, dog, rabbit, guinea pig, rat and mouse. The affinities of the two small molecule antagonists, F-[OPdChaWR] and AcF-[OPdChaWR], and the agonist, YSFKPMPLaR, revealed large differences in C5a receptor (C5aR) affinities between species. The antagonists bound to human, rat and dog PMNs with similar high affinities, but with lower affinities to PMNs from all other species. The C5a agonist also bound with varying affinities between species, but showed a different affinity profile to the antagonists. In contrast, recombinant human C5a had similar affinity for PMNs of all species investigated. The low correlation between the affinities of the antagonists and the agonist between species either suggests that different receptor residues are important for distinguishing between agonist/antagonist binding, or that the agonist and antagonist peptides bind to two distinct sites within the C5aR.

An inducible melanoma model implicates a role for RAS in tumor maintenance and angiogenesis

The established tumor is maintained through complex and poorly understood host-tumor interactions guiding processes such as angiogenesis. The numerous and diverse genetic alterations that accompany tumor genesis raises questions as to whether experimental cancer-promoting mutations remain relevant to tumor maintenance. Utilizing a new doxycycline-inducible H-RASV12G INK4a null mouse melanoma model, we have shown that melanoma genesis and maintenance are strictly dependent upon H-RASV12G expression. Withdrawal of doxycycline and H-RASV12G down-regulation resulted in clinical and histological regression of primary and explanted tumors. Moreover, the initial stages of regression were highlighted by dramatic activation of apoptosis in the tumor cells as well as host-derived endothelial cells. These data provide genetic evidence that H-RASV12G plays a critical role in tumor maintenance and tumor angiogenesis.

BRG1, a component of the SWI-SNF complex, is mutated in multiple human tumor cell lines

Human BRG1 is a component of the evolutionarily conserved SWI-SNF chromatin remodeling complex. BRG1 has been implicated in growth control through its interaction with the tumor suppressor pRb and may consequently serve as a negative regulator of proliferation. Postulating that BRG1 may itself be a tumor suppressor gene, we screened a panel of tumor cell lines to determine whether the gene is targeted for mutation. We report that the COOH-terminal region of BRG1 is homozygously deleted in two carcinoma cell lines, prostate TSU-Pr1 and lung A-427. In addition, biallelic inactivations of BRG1 were observed in four other cell lines derived from carcinomas of the breast, lung, pancreas, and prostate; their mutations in BRG1 included three frameshift lesions and one nonsense lesion. Point mutations were also discovered in a number of other cell lines, however in most cases any effect of these mutations on BRG1 function remains to be established. A variety of different mutations within BRG1, in several cell lines, suggest that BRG1 may be targeted for disruption in human tumors. Significantly, reintroduction of BRG1 into cells lacking BRG1 expression was sufficient to reverse their transformed phenotype inducing growth arrest and a flattened morphology. These data strongly support the model that BRG1 may function as a tumor suppressor and strengthen the hypothesis that the regulation of gene expression through chromatin remodeling is critical for cancer progression. It will be important to confirm these observations in primary tumors.

Efficacy of mycophenolate mofetil in patients with diffuse proliferative lupus nephritis. Hong Kong-Guangzhou Nephrology Study Group

BACKGROUND

The combination of cyclophosphamide and prednisolone is effective for the treatment of severe lupus nephritis but has serious adverse effects. Whether mycophenolate mofetil can be substituted for cyclophosphamide is not known.

METHODS

In 42 patients with diffuse proliferative lupus nephritis we compared the efficacy and side effects of a regimen of prednisolone and mycophenolate mofetil given for 12 months with those of a regimen of prednisolone and cyclophosphamide given for 6 months, followed by prednisolone and azathioprine for 6 months. Complete remission was defined as a value for urinary protein excretion that was less than 0.3 g per 24 hours, with normal urinary sediment, a normal serum albumin concentration, and values for serum creatinine and creatinine clearance that were no more than 15 percent above the base-line values. Partial remission was defined as a value for urinary protein excretion that was between 0.3 and 2.9 g per 24 hours, with a serum albumin concentration of at least 30 g per liter.

RESULTS

Eighty-one percent of the 21 patients treated with mycophenolate mofetil and prednisolone (group 1) had a complete remission, and 14 percent had a partial remission, as compared with 76 percent and 14 percent, respectively, of the 21 patients treated with cyclophosphamide and prednisolone followed by azathioprine and prednisolone (group 2). The improvements in the degree of proteinuria and the serum albumin and creatinine concentrations were similar in the two groups. One patient in each group discontinued treatment because of side effects. Infections were noted in 19 percent of the patients in group 1 and in 33 percent of those in group 2 (P = 0.29). Other adverse effects occurred only in group 2; they included amenorrhea (in 23 percent of the patients), hair loss (19 percent), leukopenia (10 percent), and death (10 percent). The rates of relapse were 15 percent and 11 percent, respectively.

CONCLUSIONS

For the treatment of diffuse proliferative lupus nephritis, the combination of mycophenolate mofetil and prednisolone is as effective as a regimen of cyclophosphamide and prednisolone followed by azathioprine and prednisolone but is less toxic.