Garvan Institute of Medical Research

SUMMARY: It is expected that emerging digital gene expression (DGE) technologies will overtake microarray technologies in the near future for many functional genomics applications. One of the fundamental data analysis tasks, especially for gene expression studies, involves determining whether there is evidence that counts for a transcript or exon are significantly different across experimental conditions. edgeR is a Bioconductor software package for examining differential expression of replicated count data. An overdispersed Poisson model is used to account for both biological and technical variability. Empirical Bayes methods are used to moderate the degree of overdispersion across transcripts, improving the reliability of inference. The methodology can be used even with the most minimal levels of replication, provided at least one phenotype or experimental condition is replicated. The software may have other applications beyond sequencing data, such as proteome peptide count data. AVAILABILITY: The package is freely available under the LGPL licence from the Bioconductor web site (http://bioconductor.org).

Abstract Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.

The fine detail provided by sequencing-based transcriptome surveys suggests that RNA-seq is likely to become the platform of choice for interrogating steady state RNA. In order to discover biologically important changes in expression, we show that normalization continues to be an essential step in the analysis. We outline a simple and effective method for performing normalization and show dramatically improved results for inferring differential expression in simulated and publicly available data sets.

High-throughput experimental technologies often identify dozens to hundreds of genes related to, or changed in, a biological or pathological process. From these genes one wants to identify biological pathways that may be involved and diseases that may be implicated. Here, we report a web server, KOBAS 2.0, which annotates an input set of genes with putative pathways and disease relationships based on mapping to genes with known annotations. It allows for both ID mapping and cross-species sequence similarity mapping. It then performs statistical tests to identify statistically significantly enriched pathways and diseases. KOBAS 2.0 incorporates knowledge across 1327 species from 5 pathway databases (KEGG PATHWAY, PID, BioCyc, Reactome and Panther) and 5 human disease databases (OMIM, KEGG DISEASE, FunDO, GAD and NHGRI GWAS Catalog). KOBAS 2.0 can be accessed at http://kobas.cbi.pku.edu.cn.

The upcoming 5th edition of the World Health Organization (WHO) Classification of Haematolymphoid Tumours is part of an effort to hierarchically catalogue human cancers arising in various organ systems within a single relational database. This paper summarizes the new WHO classification scheme for myeloid and histiocytic/dendritic neoplasms and provides an overview of the principles and rationale underpinning changes from the prior edition. The definition and diagnosis of disease types continues to be based on multiple clinicopathologic parameters, but with refinement of diagnostic criteria and emphasis on therapeutically and/or prognostically actionable biomarkers. While a genetic basis for defining diseases is sought where possible, the classification strives to keep practical worldwide applicability in perspective. The result is an enhanced, contemporary, evidence-based classification of myeloid and histiocytic/dendritic neoplasms, rooted in molecular biology and an organizational structure that permits future scalability as new discoveries continue to inexorably inform future editions.

Abstract Somatic mutations in cancer genomes are caused by multiple mutational processes, each of which generates a characteristic mutational signature 1 . Here, as part of the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium 2 of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA), we characterized mutational signatures using 84,729,690 somatic mutations from 4,645 whole-genome and 19,184 exome sequences that encompass most types of cancer. We identified 49 single-base-substitution, 11 doublet-base-substitution, 4 clustered-base-substitution and 17 small insertion-and-deletion signatures. The substantial size of our dataset, compared with previous analyses 3–15 , enabled the discovery of new signatures, the separation of overlapping signatures and the decomposition of signatures into components that may represent associated—but distinct—DNA damage, repair and/or replication mechanisms. By estimating the contribution of each signature to the mutational catalogues of individual cancer genomes, we revealed associations of signatures to exogenous or endogenous exposures, as well as to defective DNA-maintenance processes. However, many signatures are of unknown cause. This analysis provides a systematic perspective on the repertoire of mutational processes that contribute to the development of human cancer.

Abstract We herein present an overview of the upcoming 5 th edition of the World Health Organization Classification of Haematolymphoid Tumours focussing on lymphoid neoplasms. Myeloid and histiocytic neoplasms will be presented in a separate accompanying article. Besides listing the entities of the classification, we highlight and explain changes from the revised 4 th edition. These include reorganization of entities by a hierarchical system as is adopted throughout the 5 th edition of the WHO classification of tumours of all organ systems, modification of nomenclature for some entities, revision of diagnostic criteria or subtypes, deletion of certain entities, and introduction of new entities, as well as inclusion of tumour-like lesions, mesenchymal lesions specific to lymph node and spleen, and germline predisposition syndromes associated with the lymphoid neoplasms.

Abstract Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale 1–3 . Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter 4 ; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation 5,6 ; analyses timings and patterns of tumour evolution 7 ; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity 8,9 ; and evaluates a range of more-specialized features of cancer genomes 8,10–18 .

The genetics underlying severe COVID-19 The immune system is complex and involves many genes, including those that encode cytokines known as interferons (IFNs). Individuals that lack specific IFNs can be more susceptible to infectious diseases. Furthermore, the autoantibody system dampens IFN response to prevent damage from pathogen-induced inflammation. Two studies now examine the likelihood that genetics affects the risk of severe coronavirus disease 2019 (COVID-19) through components of this system (see the Perspective by Beck and Aksentijevich). Q. Zhang et al. used a candidate gene approach and identified patients with severe COVID-19 who have mutations in genes involved in the regulation of type I and III IFN immunity. They found enrichment of these genes in patients and conclude that genetics may determine the clinical course of the infection. Bastard et al. identified individuals with high titers of neutralizing autoantibodies against type I IFN-α2 and IFN-ω in about 10% of patients with severe COVID-19 pneumonia. These autoantibodies were not found either in infected people who were asymptomatic or had milder phenotype or in healthy individuals. Together, these studies identify a means by which individuals at highest risk of life-threatening COVID-19 can be identified. Science , this issue p. eabd4570 , p. eabd4585 ; see also p. 404

The coefficient of determination R 2 quantifies the proportion of variance explained by a statistical model and is an important summary statistic of biological interest. However, estimating R 2 for generalized linear mixed models (GLMMs) remains challenging. We have previously introduced a version of R 2 that we called for Poisson and binomial GLMMs, but not for other distributional families. Similarly, we earlier discussed how to estimate intra-class correlation coefficients (ICCs) using Poisson and binomial GLMMs. In this paper, we generalize our methods to all other non-Gaussian distributions, in particular to negative binomial and gamma distributions that are commonly used for modelling biological data. While expanding our approach, we highlight two useful concepts for biologists, Jensen's inequality and the delta method, both of which help us in understanding the properties of GLMMs. Jensen's inequality has important implications for biologically meaningful interpretation of GLMMs, whereas the delta method allows a general derivation of variance associated with non-Gaussian distributions. We also discuss some special considerations for binomial GLMMs with binary or proportion data. We illustrate the implementation of our extension by worked examples from the field of ecology and evolution in the R environment. However, our method can be used across disciplines and regardless of statistical environments.

autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

OBJECTIVE: To describe a syndrome of peripheral lipodystrophy (fat wasting of the face, limbs and upper trunk), hyperlipidaemia and insulin resistance in patients receiving potent HIV protease inhibitor therapy. DESIGN: Cross-sectional study. SETTING: Outpatient clinic of a university teaching hospital. PATIENTS: HIV-infected patients either receiving at least one protease inhibitor (n=116) or protease inhibitor-naive (n=32), and healthy men (n=47). INTERVENTIONS AND MAIN OUTCOME MEASURES: Lipodystrophy was assessed by physical examination and questionnaire and body composition by dual-energy X-ray absorptiometry. Fasting triglyceride, cholesterol, free fatty acid, glucose, insulin, C-peptide and fructosamine levels, other metabolic parameters, CD4 lymphocyte counts, and HIV RNA load were also assessed. RESULTS: HIV protease inhibitor-naive patients had similar body composition to healthy men. HIV protease inhibitor therapy was associated with substantially lower total body fat (13.2 versus 18.7 kg in protease inhibitor-naive patients; P=0.005), and significantly higher total cholesterol and triglyceride levels. Lipodystrophy was observed clinically in 74 (64%) protease inhibitor recipients after a mean 13.9 months and 1(3%) protease inhibitor-naive patient (P=0.0001). Fat loss occurred in all regions except the abdomen after a median 10 months. Patients with lipodystrophy experienced a relative weight loss of 0.5 kg per month and had significantly higher triglyceride, cholesterol, insulin and C-peptide levels and were more insulin-resistant than protease inhibitor recipients without lipodystrophy. Patients receiving ritonavir and saquinavir in combination had significantly lower body fat, higher lipids and shorter time to lipodystrophy than patients receiving indinavir. Three (2%) patients developed new or worsening diabetes mellitus. CONCLUSION: A syndrome of peripheral lipodystrophy, hyperlipidaemia and insulin resistance is a common complication of HIV protease inhibitors. Diabetes mellitus is relatively uncommon.

Empirical evidence supporting the competitive endogenous RNA (ceRNA) hypothesis is accumulating, but studies that model transcriptome-wide binding site abundance suggest that physiological expression changes of most individual transcripts do not compromise microRNA (miRNA) activity. This Review aims to critically evaluate the evidence for and against the ceRNA hypothesis to assess the impact of endogenous miRNA-sponge interactions. The competitive endogenous RNA (ceRNA) hypothesis proposes that transcripts with shared microRNA (miRNA) binding sites compete for post-transcriptional control. This hypothesis has gained substantial attention as a unifying function for long non-coding RNAs, pseudogene transcripts and circular RNAs, as well as an alternative function for messenger RNAs. Empirical evidence supporting the hypothesis is accumulating but not without attracting scepticism. Recent studies that model transcriptome-wide binding-site abundance suggest that physiological changes in expression of most individual transcripts will not compromise miRNA activity. In this Review, we critically evaluate the evidence for and against the ceRNA hypothesis to assess the impact of endogenous miRNA-sponge interactions.

Summary Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes critical for an organism’s function will be depleted for such variants in natural populations, while non-essential genes will tolerate their accumulation. However, predicted loss-of-function (pLoF) variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here, we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence pLoF variants in this cohort after filtering for sequencing and annotation artifacts. Using an improved human mutation rate model, we classify human protein-coding genes along a spectrum representing tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve gene discovery power for both common and rare diseases.

CONTEXT: There are few data on long-term mortality following osteoporotic fracture and fewer following subsequent fracture. OBJECTIVES: To examine long-term mortality risk in women and men following all osteoporotic fractures and to assess the association of subsequent fracture with that risk. DESIGN, SETTING, AND PARTICIPANTS: Prospective cohort from the Dubbo Osteoporosis Epidemiology Study of community-dwelling women and men aged 60 years and older from Dubbo, Australia, who sustained a fracture between April 1989 and May 2007. MAIN OUTCOME MEASURES: Age- and sex-specific standardized mortality ratios (SMRs) compared with the overall Dubbo population for hip, vertebral, major, and minor fractures. RESULTS: In women, there were 952 low-trauma fractures followed by 461 deaths, and in men, 343 fractures were followed by 197 deaths. Age-adjusted SMRs were increased following hip fractures (SMRs, 2.43 [95% confidence interval [CI], 2.02-2.93] and 3.51 [95% CI, 2.65-4.66]), vertebral fractures (SMRs, 1.82 [95% CI, 1.52-2.17] and 2.12 [95% CI, 1.66-2.72]), major fractures (SMRs, 1.65 [95% CI, 1.31-2.08] and 1.70 [95% CI, 1.23-2.36]), and minor fractures (SMRs, 1.42 [95% CI, 1.19-1.70] and 1.33 [95% CI, 0.99-1.80]) for both women and men, respectively. Mortality was increased for all ages for all fractures except minor fractures for which increased mortality was only apparent for those older than 75 years. Increased mortality risk persisted for 5 years for all fractures and up to 10 years for hip fractures. Increases in absolute mortality that were above expected, for 5 years after fracture, ranged from 1.3 to 13.2 per 100 person-years in women and from 2.7 to 22.3 per 100 person-years in men, depending on fracture type. Subsequent fracture was associated with an increased mortality hazard ratio of 1.91 (95% CI, 1.54-2.37) in women and 2.99 (95% CI, 2.11-4.24) in men. Mortality risk following a subsequent fracture then declined but beyond 5 years still remained higher than in the general population (SMR, 1.41 [95% CI, 1.01-1.97] and SMR, 1.78 [95% CI, 0.96-3.31] for women and men, respectively). Predictors of mortality after any fragility fracture for both men and women included age, quadriceps weakness, and subsequent fracture but not comorbidities. Low bone mineral density, having smoked, and sway were also predictors for women and less physical activity for men. CONCLUSIONS: In a sample of older women and men, all low-trauma fractures were associated with increased mortality risk for 5 to 10 years. Subsequent fracture was associated with increased mortality risk for an additional 5 years.

BACKGROUND: In recent years the Illumina HumanMethylation450 (HM450) BeadChip has provided a user-friendly platform to profile DNA methylation in human samples. However, HM450 lacked coverage of distal regulatory elements. Illumina have now released the MethylationEPIC (EPIC) BeadChip, with new content specifically designed to target these regions. We have used HM450 and whole-genome bisulphite sequencing (WGBS) to perform a critical evaluation of the new EPIC array platform. RESULTS: EPIC covers over 850,000 CpG sites, including >90 % of the CpGs from the HM450 and an additional 413,743 CpGs. Even though the additional probes improve the coverage of regulatory elements, including 58 % of FANTOM5 enhancers, only 7 % distal and 27 % proximal ENCODE regulatory elements are represented. Detailed comparisons of regulatory elements from EPIC and WGBS show that a single EPIC probe is not always informative for those distal regulatory elements showing variable methylation across the region. However, overall data from the EPIC array at single loci are highly reproducible across technical and biological replicates and demonstrate high correlation with HM450 and WGBS data. We show that the HM450 and EPIC arrays distinguish differentially methylated probes, but the absolute agreement depends on the threshold set for each platform. Finally, we provide an annotated list of probes whose signal could be affected by cross-hybridisation or underlying genetic variation. CONCLUSION: The EPIC array is a significant improvement over the HM450 array, with increased genome coverage of regulatory regions and high reproducibility and reliability, providing a valuable tool for high-throughput human methylome analyses from diverse clinical samples.

BACKGROUND: Enzalutamide, an androgen-receptor inhibitor, has been associated with improved overall survival in men with castration-resistant prostate cancer. It is not known whether adding enzalutamide to testosterone suppression, with or without early docetaxel, will improve survival in men with metastatic, hormone-sensitive prostate cancer. METHODS: In this open-label, randomized, phase 3 trial, we assigned patients to receive testosterone suppression plus either open-label enzalutamide or a standard nonsteroidal antiandrogen therapy (standard-care group). The primary end point was overall survival. Secondary end points included progression-free survival as determined by the prostate-specific antigen (PSA) level, clinical progression-free survival, and adverse events. RESULTS: A total of 1125 men underwent randomization; the median follow-up was 34 months. There were 102 deaths in the enzalutamide group and 143 deaths in the standard-care group (hazard ratio, 0.67; 95% confidence interval [CI], 0.52 to 0.86; P = 0.002). Kaplan-Meier estimates of overall survival at 3 years were 80% (based on 94 events) in the enzalutamide group and 72% (based on 130 events) in the standard-care group. Better results with enzalutamide were also seen in PSA progression-free survival (174 and 333 events, respectively; hazard ratio, 0.39; P<0.001) and in clinical progression-free survival (167 and 320 events, respectively; hazard ratio, 0.40; P<0.001). Treatment discontinuation due to adverse events was more frequent in the enzalutamide group than in the standard-care group (33 events and 14 events, respectively). Fatigue was more common in the enzalutamide group; seizures occurred in 7 patients in the enzalutamide group (1%) and in no patients in the standard-care group. CONCLUSIONS: Enzalutamide was associated with significantly longer progression-free and overall survival than standard care in men with metastatic, hormone-sensitive prostate cancer receiving testosterone suppression. The enzalutamide group had a higher incidence of seizures and other toxic effects, especially among those treated with early docetaxel. (Funded by Astellas Scientific and Medical Affairs and others; ENZAMET (ANZUP 1304) ANZCTR number, ACTRN12614000110684; ClinicalTrials.gov number, NCT02446405; and EU Clinical Trials Register number, 2014-003190-42.).

Recent studies have demonstrated that fatty acids induce insulin resistance in skeletal muscle by blocking insulin activation of insulin receptor substrate-1 (IRS-1)-associated phosphatidylinositol 3-kinase (PI3-kinase). To examine the mechanism by which fatty acids mediate this effect, rats were infused with either a lipid emulsion (consisting mostly of 18:2 fatty acids) or glycerol. Intracellular C18:2 CoA increased in a time-dependent fashion, reaching an approximately 6-fold elevation by 5 h, whereas there was no change in the concentration of any other fatty acyl-CoAs. Diacylglycerol (DAG) also increased transiently after 3-4 h of lipid infusion. In contrast there was no increase in intracellular ceramide or triglyceride concentrations during the lipid infusion. Increases in intracellular C18:2 CoA and DAG concentration were associated with protein kinase C (PKC)-theta activation and a reduction in both insulin-stimulated IRS-1 tyrosine phosphorylation and IRS-1 associated PI3-kinase activity, which were associated with an increase in IRS-1 Ser(307) phosphorylation. These data support the hypothesis that an increase in plasma fatty acid concentration results in an increase in intracellular fatty acyl-CoA and DAG concentrations, which results in activation of PKC-theta leading to increased IRS-1 Ser(307) phosphorylation. This in turn leads to decreased IRS-1 tyrosine phosphorylation and decreased activation of IRS-1-associated PI3-kinase activity resulting in decreased insulin-stimulated glucose transport activity.

UNLABELLED: The relationship between BMD and fracture risk was estimated in a meta-analysis of data from 12 cohort studies of approximately 39,000 men and women. Low hip BMD was an important predictor of fracture risk. The prediction of hip fracture with hip BMD also depended on age and z score. INTRODUCTION: The aim of this study was to quantify the relationship between BMD and fracture risk and examine the effect of age, sex, time since measurement, and initial BMD value. MATERIALS AND METHODS: We studied 9891 men and 29,082 women from 12 cohorts comprising EVOS/EPOS, EPIDOS, OFELY, CaMos, Rochester, Sheffield, Rotterdam, Kuopio, DOES, Hiroshima, and 2 cohorts from Gothenburg. Cohorts were followed for up to 16.3 years and a total of 168,366 person-years. The effect of BMD on fracture risk was examined using a Poisson model in each cohort and each sex separately. Results of the different studies were then merged using weighted coefficients. RESULTS: BMD measurement at the femoral neck with DXA was a strong predictor of hip fractures both in men and women with a similar predictive ability. At the age of 65 years, risk ratio increased by 2.94 (95% CI = 2.02-4.27) in men and by 2.88 (95% CI = 2.31-3.59) in women for each SD decrease in BMD. However, the effect was dependent on age, with a significantly higher gradient of risk at age 50 years than at age 80 years. Although the gradient of hip fracture risk decreased with age, the absolute risk still rose markedly with age. For any fracture and for any osteoporotic fracture, the gradient of risk was lower than for hip fractures. At the age of 65 years, the risk of osteoporotic fractures increased in men by 1.41 per SD decrease in BMD (95% CI = 1.33-1.51) and in women by 1.38 per SD (95% CI = 1.28-1.48). In contrast with hip fracture risk, the gradient of risk increased with age. For the prediction of any osteoporotic fracture (and any fracture), there was a higher gradient of risk the lower the BMD. At a z score of -4 SD, the risk gradient was 2.10 per SD (95% CI = 1.63-2.71) and at a z score of -1 SD, the risk was 1.73 per SD (95% CI = 1.59-1.89) in men and women combined. A similar but less pronounced and nonsignificant effect was observed for hip fractures. Data for ultrasound and peripheral measurements were available from three cohorts. The predictive ability of these devices was somewhat less than that of DXA measurements at the femoral neck by age, sex, and BMD value. CONCLUSIONS: We conclude that BMD is a risk factor for fracture of substantial importance and is similar in both sexes. Its validation on an international basis permits its use in case finding strategies. Its use should, however, take account of the variations in predictive value with age and BMD.

Since the pioneering work of Gowans and colleagues in the 1960s,1,2 much progress has been made in understanding the pivotal role of cell migration in immunity. We now have considerable knowledge of the way in which specialized leukocytes are channeled to distinct target tissues in immune responses and inflammation (Figure 1). This review will concentrate on the migration of T cells, which are at the heart of most adaptive immune responses.Since T cells respond to pathogens only on direct contact with pathogen-derived antigen, they must migrate to sites where antigen is found. The T-cell receptor recognizes a peptide . . .