Gene filtering strategies for machine learning guided biomarker discovery using neonatal sepsis RNA-seq data.

Machine learning (ML) algorithms are powerful tools that are increasingly being used for sepsis biomarker discovery in RNA-Seq data. RNA-Seq datasets contain multiple sources and types of noise (operator, technical and non-systematic) that may bias ML classification. Normalisation and independent gene filtering approaches described in RNA-Seq workflows account for some of this variability and are typically only targeted at differential expression analysis rather than ML applications. Pre-processing normalisation steps significantly reduce the number of variables in the data and thereby increase the power of statistical testing, but can potentially discard valuable and insightful classification features. A systematic assessment of applying transcript level filtering on the robustness and stability of ML based RNA-seq classification remains to be fully explored. In this report we examine the impact of filtering out low count transcripts and those with influential outliers read counts on downstream ML analysis for sepsis biomarker discovery using elastic net regularised logistic regression, L1-reguarlised support vector machines and random forests. We demonstrate that applying a systematic objective strategy for removal of uninformative and potentially biasing biomarkers representing up to 60% of transcripts in different sample size datasets, including two illustrative neonatal sepsis cohorts, leads to substantial improvements in classification performance, higher stability of the resulting gene signatures, and better agreement with previously reported sepsis biomarkers. We also demonstrate that the performance uplift from gene filtering depends on the ML classifier chosen, with L1-regularlised support vector machines showing the greatest performance improvements with our experimental data.

Immune and metabolic markers for identifying and investigating severe Coronavirus disease and Sepsis in children and young people (pSeP/COVID ChYP study): protocol for a prospective cohort study.

INTRODUCTION: Early recognition and appropriate management of paediatric sepsis are known to improve outcomes. A previous system's biology investigation of the systemic immune response in neonates to sepsis identified immune and metabolic markers that showed high accuracy for detecting bacterial infection. Further gene expression markers have also been reported previously in the paediatric age group for discriminating sepsis from control cases. More recently, specific gene signatures were identified to discriminate between COVID-19 and its associated inflammatory sequelae. Through the current prospective cohort study, we aim to evaluate immune and metabolic blood markers which discriminate between sepses (including COVID-19) from other acute illnesses in critically unwell children and young persons, up to 18 years of age. METHODS AND ANALYSIS: We describe a prospective cohort study for comparing the immune and metabolic whole-blood markers in patients with sepsis, COVID-19 and other illnesses. Clinical phenotyping and blood culture test results will provide a reference standard to evaluate the performance of blood markers from the research sample analysis. Serial sampling of whole blood (50 µL each) will be collected from children admitted to intensive care and with an acute illness to follow time dependent changes in biomarkers. An integrated lipidomics and RNASeq transcriptomics analyses will be conducted to evaluate immune-metabolic networks that discriminate sepsis and COVID-19 from other acute illnesses. This study received approval for deferred consent. ETHICS AND DISSEMINATION: The study has received research ethics committee approval from the Yorkshire and Humber Leeds West Research Ethics Committee 2 (reference 20/YH/0214; IRAS reference 250612). Submission of study results for publication will involve making available all anonymised primary and processed data on public repository sites. TRIAL REGISTRATION NUMBER: NCT04904523.

mSep: investigating physiological and immune-metabolic biomarkers in septic and healthy pregnant women to predict feto-maternal immune health - a prospective observational cohort study protocol.

INTRODUCTION: Maternal sepsis remains a leading cause of death in pregnancy. Physiological adaptations to pregnancy obscure early signs of sepsis and can result in delays in recognition and treatment. Identifying biomarkers that can reliably diagnose sepsis will reduce morbidity and mortality and antibiotic overuse. We have previously identified an immune-metabolic biomarker network comprising three pathways with a >99% accuracy for detecting bacterial neonatal sepsis. In this prospective study, we will describe physiological parameters and novel biomarkers in two cohorts-healthy pregnant women and pregnant women with suspected sepsis-with the aim of mapping pathophysiological drivers and evaluating predictive biomarkers for diagnosing maternal sepsis. METHODS AND ANALYSIS: Women aged over 18 with an ultrasound-confirmed pregnancy will be recruited to a pilot and two main study cohorts. The pilot will involve blood sample collection from 30 pregnant women undergoing an elective caesarean section. Cohort A will follow 100 healthy pregnant women throughout their pregnancy journey, with collection of blood samples from participants at routine time points in their pregnancy: week 12 'booking', week 28 and during labour. Cohort B will follow 100 pregnant women who present with suspected sepsis in pregnancy or labour and will have at least two blood samples taken during their care pathway. Study blood samples will be collected during routine clinical blood sampling. Detailed medical history and physiological parameters at the time of blood sampling will be recorded, along with the results of routine biochemical tests, including C reactive protein, lactate and white blood cell count. In addition, study blood samples will be processed and analysed for transcriptomic, lipidomic and metabolomic analyses and both qualitative and functional immunophenotyping. ETHICS AND DISSEMINATION: Ethical approval has been obtained from the Wales Research Ethics Committee 2 (SPON1752-19, 30 October 2019). TRIAL REGISTRATION NUMBER: NCT05023954.

nSeP: immune and metabolic biomarkers for early detection of neonatal sepsis-protocol for a prospective multicohort study.

INTRODUCTION: Diagnosing neonatal sepsis is heavily dependent on clinical phenotyping as culture-positive body fluid has poor sensitivity, and existing blood biomarkers have poor specificity.A combination of machine learning, statistical and deep pathway biology analyses led to the identification of a tripartite panel of biologically connected immune and metabolic markers that showed greater than 99% accuracy for detecting bacterial infection with 100% sensitivity. The cohort study described here is designed as a large-scale clinical validation of this previous work. METHODS AND ANALYSIS: This multicentre observational study will prospectively recruit a total of 1445 newborn infants (all gestations)-1084 with suspected early-or late-onset sepsis, and 361 controls-over 4 years. A small volume of whole blood will be collected from infants with suspected sepsis at the time of presentation. This sample will be used for integrated transcriptomic, lipidomic and targeted proteomics profiling. In addition, a subset of samples will be subjected to cellular phenotype and proteomic analyses. A second sample from the same patient will be collected at 24 hours, with an opportunistic sampling for stool culture. For control infants, only one set of blood and stool sample will be collected to coincide with clinical blood sampling. Along with detailed clinical information, blood and stool samples will be analysed and the information will be used to identify and validate the efficacy of immune-metabolic networks in the diagnosis of bacterial neonatal sepsis and to identify new host biomarkers for viral sepsis. ETHICS AND DISSEMINATION: The study has received research ethics committee approval from the Wales Research Ethics Committee 2 (reference 19/WA/0008) and operational approval from Health and Care Research Wales. Submission of study results for publication will involve making available all anonymised primary and processed data on public repository sites. TRIAL REGISTRATION NUMBER: NCT03777670.

Zeb1 modulates hematopoietic stem cell fates required for suppressing acute myeloid leukemia.

Zeb1, a zinc finger E-box binding homeobox epithelial-mesenchymal transition (EMT) transcription factor, confers properties of "stemness," such as self-renewal, in cancer. Yet little is known about the function of Zeb1 in adult stem cells. Here, we used the hematopoietic system as a well-established paradigm of stem cell biology to evaluate Zeb1-mediated regulation of adult stem cells. We employed a conditional genetic approach using the Mx1-Cre system to specifically knock out (KO) Zeb1 in adult hematopoietic stem cells (HSCs) and their downstream progeny. Acute genetic deletion of Zeb1 led to rapid-onset thymic atrophy and apoptosis-driven loss of thymocytes and T cells. A profound cell-autonomous self-renewal defect and multilineage differentiation block were observed in Zeb1-KO HSCs. Loss of Zeb1 in HSCs activated transcriptional programs of deregulated HSC maintenance and multilineage differentiation genes and of cell polarity consisting of cytoskeleton-, lipid metabolism/lipid membrane-, and cell adhesion-related genes. Notably, epithelial cell adhesion molecule (EpCAM) expression was prodigiously upregulated in Zeb1-KO HSCs, which correlated with enhanced cell survival, diminished mitochondrial metabolism, ribosome biogenesis, and differentiation capacity and an activated transcriptomic signature associated with acute myeloid leukemia (AML) signaling. ZEB1 expression was downregulated in AML patients, and Zeb1 KO in the malignant counterparts of HSCs - leukemic stem cells (LSCs) - accelerated MLL-AF9- and Meis1a/Hoxa9-driven AML progression, implicating Zeb1 as a tumor suppressor in AML LSCs. Thus, Zeb1 acts as a transcriptional regulator in hematopoiesis, critically coordinating HSC self-renewal, apoptotic, and multilineage differentiation fates required to suppress leukemic potential in AML.

Distinctive Features of Orbital Adipose Tissue (OAT) in Graves' Orbitopathy.

Depot specific expansion of orbital-adipose-tissue (OAT) in Graves' Orbitopathy (GO) is associated with lipid metabolism signaling defects. We hypothesize that the unique adipocyte biology of OAT facilitates its expansion in GO. A comprehensive comparison of OAT and white-adipose-tissue (WAT) was performed by light/electron-microscopy, lipidomic and transcriptional analysis using ex vivo WAT, healthy OAT (OAT-H) and OAT from GO (OAT-GO). OAT-H/OAT-GO have a single lipid-vacuole and low mitochondrial number. Lower lipolytic activity and smaller adipocytes of OAT-H/OAT-GO, accompanied by similar essential linoleic fatty acid (FA) and (low) FA synthesis to WAT, revealed a hyperplastic OAT expansion through external FA-uptake via abundant SLC27A6 (FA-transporter) expression. Mitochondrial dysfunction of OAT in GO was apparent, as evidenced by the increased mRNA expression of uncoupling protein 1 (UCP1) and mitofusin-2 (MFN2) in OAT-GO compared to OAT-H. Transcriptional profiles of OAT-H revealed high expression of Iroquois homeobox-family (IRX-3&5), and low expression in HOX-family/TBX5 (essential for WAT/BAT (brown-adipose-tissue)/BRITE (BRown-in-whITE) development). We demonstrated unique features of OAT not presented in either WAT or BAT/BRITE. This study reveals that the pathologically enhanced FA-uptake driven hyperplastic expansion of OAT in GO is associated with a depot specific mechanism (the SLC27A6 FA-transporter) and mitochondrial dysfunction. We uncovered that OAT functions as a distinctive fat depot, providing novel insights into adipocyte biology and the pathological development of OAT expansion in GO.

Gata2 as a Crucial Regulator of Stem Cells in Adult Hematopoiesis and Acute Myeloid Leukemia.

Subversion of transcription factor (TF) activity in hematopoietic stem/progenitor cells (HSPCs) leads to the development of therapy-resistant leukemic stem cells (LSCs) that drive fulminant acute myeloid leukemia (AML). Using a conditional mouse model where zinc-finger TF Gata2 was deleted specifically in hematopoietic cells, we show that knockout of Gata2 leads to rapid and complete cell-autonomous loss of adult hematopoietic stem cells. By using short hairpin RNAi to target GATA2, we also identify a requirement for GATA2 in human HSPCs. In Meis1a/Hoxa9-driven AML, deletion of Gata2 impedes maintenance and self-renewal of LSCs. Ablation of Gata2 enforces an LSC-specific program of enhanced apoptosis, exemplified by attenuation of anti-apoptotic factor BCL2, and re-instigation of myeloid differentiation--which is characteristically blocked in AML. Thus, GATA2 acts as a critical regulator of normal and leukemic stem cells and mediates transcriptional networks that may be exploited therapeutically to target key facets of LSC behavior in AML.

Polymorphism in a lincRNA Associates with a Doubled Risk of Pneumococcal Bacteremia in Kenyan Children.

Bacteremia (bacterial bloodstream infection) is a major cause of illness and death in sub-Saharan Africa but little is known about the role of human genetics in susceptibility. We conducted a genome-wide association study of bacteremia susceptibility in more than 5,000 Kenyan children as part of the Wellcome Trust Case Control Consortium 2 (WTCCC2). Both the blood-culture-proven bacteremia case subjects and healthy infants as controls were recruited from Kilifi, on the east coast of Kenya. Streptococcus pneumoniae is the most common cause of bacteremia in Kilifi and was thus the focus of this study. We identified an association between polymorphisms in a long intergenic non-coding RNA (lincRNA) gene (AC011288.2) and pneumococcal bacteremia and replicated the results in the same population (p combined = 1.69 × 10(-9); OR = 2.47, 95% CI = 1.84-3.31). The susceptibility allele is African specific, derived rather than ancestral, and occurs at low frequency (2.7% in control subjects and 6.4% in case subjects). Our further studies showed AC011288.2 expression only in neutrophils, a cell type that is known to play a major role in pneumococcal clearance. Identification of this novel association will further focus research on the role of lincRNAs in human infectious disease.

The correlation between reading and mathematics ability at age twelve has a substantial genetic component.

Dissecting how genetic and environmental influences impact on learning is helpful for maximizing numeracy and literacy. Here we show, using twin and genome-wide analysis, that there is a substantial genetic component to children's ability in reading and mathematics, and estimate that around one half of the observed correlation in these traits is due to shared genetic effects (so-called Generalist Genes). Thus, our results highlight the potential role of the learning environment in contributing to differences in a child's cognitive abilities at age twelve.

A genome-wide association analysis of a broad psychosis phenotype identifies three loci for further investigation.

BACKGROUND: Genome-wide association studies (GWAS) have identified several loci associated with schizophrenia and/or bipolar disorder. We performed a GWAS of psychosis as a broad syndrome rather than within specific diagnostic categories. METHODS: 1239 cases with schizophrenia, schizoaffective disorder, or psychotic bipolar disorder; 857 of their unaffected relatives, and 2739 healthy controls were genotyped with the Affymetrix 6.0 single nucleotide polymorphism (SNP) array. Analyses of 695,193 SNPs were conducted using UNPHASED, which combines information across families and unrelated individuals. We attempted to replicate signals found in 23 genomic regions using existing data on nonoverlapping samples from the Psychiatric GWAS Consortium and Schizophrenia-GENE-plus cohorts (10,352 schizophrenia patients and 24,474 controls). RESULTS: No individual SNP showed compelling evidence for association with psychosis in our data. However, we observed a trend for association with same risk alleles at loci previously associated with schizophrenia (one-sided p = .003). A polygenic score analysis found that the Psychiatric GWAS Consortium's panel of SNPs associated with schizophrenia significantly predicted disease status in our sample (p = 5 × 10(-14)) and explained approximately 2% of the phenotypic variance. CONCLUSIONS: Although narrowly defined phenotypes have their advantages, we believe new loci may also be discovered through meta-analysis across broad phenotypes. The novel statistical methodology we introduced to model effect size heterogeneity between studies should help future GWAS that combine association evidence from related phenotypes. Applying these approaches, we highlight three loci that warrant further investigation. We found that SNPs conveying risk for schizophrenia are also predictive of disease status in our data.

A variant in LDLR is associated with abdominal aortic aneurysm.

BACKGROUND: Abdominal aortic aneurysm (AAA) is a common cardiovascular disease among older people and demonstrates significant heritability. In contrast to similar complex diseases, relatively few genetic associations with AAA have been confirmed. We reanalyzed our genome-wide study and carried through to replication suggestive discovery associations at a lower level of significance. METHODS AND RESULTS: A genome-wide association study was conducted using 1830 cases from the United Kingdom, New Zealand, and Australia with infrarenal aorta diameter≥30 mm or ruptured AAA and 5435 unscreened controls from the 1958 Birth Cohort and National Blood Service cohort from the Wellcome Trust Case Control Consortium. Eight suggestive associations with P<1×10(-4) were carried through to in silico replication in 1292 AAA cases and 30,503 controls. One single-nucleotide polymorphism associated with P<0.05 after Bonferroni correction in the in silico study underwent further replication (706 AAA cases and 1063 controls from the United Kingdom, 507 AAA cases and 199 controls from Denmark, and 885 AAA cases and 1000 controls from New Zealand). Low-density lipoprotein receptor (LDLR) rs6511720 A was significantly associated overall and in 3 of 5 individual replication studies. The full study showed an association that reached genome-wide significance (odds ratio, 0.76; 95% confidence interval, 0.70-0.83; P=2.08×10(-10)). CONCLUSIONS: LDLR rs6511720 is associated with AAA. This finding is consistent with established effects of this variant on coronary artery disease. Shared causal pathways with other cardiovascular diseases may present novel opportunities for preventative and therapeutic strategies for AAA.

Imputation-based meta-analysis of severe malaria in three African populations.

Combining data from genome-wide association studies (GWAS) conducted at different locations, using genotype imputation and fixed-effects meta-analysis, has been a powerful approach for dissecting complex disease genetics in populations of European ancestry. Here we investigate the feasibility of applying the same approach in Africa, where genetic diversity, both within and between populations, is far more extensive. We analyse genome-wide data from approximately 5,000 individuals with severe malaria and 7,000 population controls from three different locations in Africa. Our results show that the standard approach is well powered to detect known malaria susceptibility loci when sample sizes are large, and that modern methods for association analysis can control the potential confounding effects of population structure. We show that pattern of association around the haemoglobin S allele differs substantially across populations due to differences in haplotype structure. Motivated by these observations we consider new approaches to association analysis that might prove valuable for multicentre GWAS in Africa: we relax the assumptions of SNP-based fixed effect analysis; we apply Bayesian approaches to allow for heterogeneity in the effect of an allele on risk across studies; and we introduce a region-based test to allow for heterogeneity in the location of causal alleles.

Dense genotyping of immune-related disease regions identifies 14 new susceptibility loci for juvenile idiopathic arthritis.

We used the Immunochip array to analyze 2,816 individuals with juvenile idiopathic arthritis (JIA), comprising the most common subtypes (oligoarticular and rheumatoid factor-negative polyarticular JIA), and 13,056 controls. We confirmed association of 3 known JIA risk loci (the human leukocyte antigen (HLA) region, PTPN22 and PTPN2) and identified 14 loci reaching genome-wide significance (P < 5 × 10(-8)) for the first time. Eleven additional new regions showed suggestive evidence of association with JIA (P < 1 × 10(-6)). Dense mapping of loci along with bioinformatics analysis refined the associations to one gene in each of eight regions, highlighting crucial pathways, including the interleukin (IL)-2 pathway, in JIA disease pathogenesis. The entire Immunochip content, the HLA region and the top 27 loci (P < 1 × 10(-6)) explain an estimated 18, 13 and 6% of the risk of JIA, respectively. In summary, this is the largest collection of JIA cases investigated so far and provides new insight into the genetic basis of this childhood autoimmune disease.

Common variants in the HLA-DRB1-HLA-DQA1 HLA class II region are associated with susceptibility to visceral leishmaniasis.

To identify susceptibility loci for visceral leishmaniasis, we undertook genome-wide association studies in two populations: 989 cases and 1,089 controls from India and 357 cases in 308 Brazilian families (1,970 individuals). The HLA-DRB1-HLA-DQA1 locus was the only region to show strong evidence of association in both populations. Replication at this region was undertaken in a second Indian population comprising 941 cases and 990 controls, and combined analysis across the three cohorts for rs9271858 at this locus showed P(combined) = 2.76 × 10(-17) and odds ratio (OR) = 1.41, 95% confidence interval (CI) = 1.30-1.52. A conditional analysis provided evidence for multiple associations within the HLA-DRB1-HLA-DQA1 region, and a model in which risk differed between three groups of haplotypes better explained the signal and was significant in the Indian discovery and replication cohorts. In conclusion, the HLA-DRB1-HLA-DQA1 HLA class II region contributes to visceral leishmaniasis susceptibility in India and Brazil, suggesting shared genetic risk factors for visceral leishmaniasis that cross the epidemiological divides of geography and parasite species.

Identification of 15 new psoriasis susceptibility loci highlights the role of innate immunity.

To gain further insight into the genetic architecture of psoriasis, we conducted a meta-analysis of 3 genome-wide association studies (GWAS) and 2 independent data sets genotyped on the Immunochip, including 10,588 cases and 22,806 controls. We identified 15 new susceptibility loci, increasing to 36 the number associated with psoriasis in European individuals. We also identified, using conditional analyses, five independent signals within previously known loci. The newly identified loci shared with other autoimmune diseases include candidate genes with roles in regulating T-cell function (such as RUNX3, TAGAP and STAT3). Notably, they included candidate genes whose products are involved in innate host defense, including interferon-mediated antiviral responses (DDX58), macrophage activation (ZC3H12C) and nuclear factor (NF)-κB signaling (CARD14 and CARM1). These results portend a better understanding of shared and distinctive genetic determinants of immune-mediated inflammatory disorders and emphasize the importance of the skin in innate and acquired host defense.

High-density genetic mapping identifies new susceptibility loci for rheumatoid arthritis.

Using the Immunochip custom SNP array, which was designed for dense genotyping of 186 loci identified through genome-wide association studies (GWAS), we analyzed 11,475 individuals with rheumatoid arthritis (cases) of European ancestry and 15,870 controls for 129,464 markers. We combined these data in a meta-analysis with GWAS data from additional independent cases (n = 2,363) and controls (n = 17,872). We identified 14 new susceptibility loci, 9 of which were associated with rheumatoid arthritis overall and five of which were specifically associated with disease that was positive for anticitrullinated peptide antibodies, bringing the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at 6 loci and identified association to low-frequency variants at 4 loci. Bioinformatic analyses generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations.

Common variants at the MHC locus and at chromosome 16q24.1 predispose to Barrett's esophagus.

Barrett's esophagus is an increasingly common disease that is strongly associated with reflux of stomach acid and usually a hiatus hernia, and it strongly predisposes to esophageal adenocarcinoma (EAC), a tumor with a very poor prognosis. We report the first genome-wide association study on Barrett's esophagus, comprising 1,852 UK cases and 5,172 UK controls in the discovery stage and 5,986 cases and 12,825 controls in the replication stage. Variants at two loci were associated with disease risk: chromosome 6p21, rs9257809 (Pcombined=4.09×10(-9); odds ratio (OR)=1.21, 95% confidence interval (CI)=1.13-1.28), within the major histocompatibility complex locus, and chromosome 16q24, rs9936833 (Pcombined=2.74×10(-10); OR=1.14, 95% CI=1.10-1.19), for which the closest protein-coding gene is FOXF1, which is implicated in esophageal development and structure. We found evidence that many common variants of small effect contribute to genetic susceptibility to Barrett's esophagus and that SNP alleles predisposing to obesity also increase risk for Barrett's esophagus.

Genome-wide association study identifies a variant in HDAC9 associated with large vessel ischemic stroke.

Genetic factors have been implicated in stroke risk, but few replicated associations have been reported. We conducted a genome-wide association study (GWAS) for ischemic stroke and its subtypes in 3,548 affected individuals and 5,972 controls, all of European ancestry. Replication of potential signals was performed in 5,859 affected individuals and 6,281 controls. We replicated previous associations for cardioembolic stroke near PITX2 and ZFHX3 and for large vessel stroke at a 9p21 locus. We identified a new association for large vessel stroke within HDAC9 (encoding histone deacetylase 9) on chromosome 7p21.1 (including further replication in an additional 735 affected individuals and 28,583 controls) (rs11984041; combined P = 1.87 × 10(-11); odds ratio (OR) = 1.42, 95% confidence interval (CI) = 1.28-1.57). All four loci exhibited evidence for heterogeneity of effect across the stroke subtypes, with some and possibly all affecting risk for only one subtype. This suggests distinct genetic architectures for different stroke subtypes.

An evaluation of different target enrichment methods in pooled sequencing designs for complex disease association studies.

Pooled sequencing can be a cost-effective approach to disease variant discovery, but its applicability in association studies remains unclear. We compare sequence enrichment methods coupled to next-generation sequencing in non-indexed pools of 1, 2, 10, 20 and 50 individuals and assess their ability to discover variants and to estimate their allele frequencies. We find that pooled resequencing is most usefully applied as a variant discovery tool due to limitations in estimating allele frequency with high enough accuracy for association studies, and that in-solution hybrid-capture performs best among the enrichment methods examined regardless of pool size.