Genome-wide SNP-sex interaction analysis of susceptibility to idiopathic pulmonary fibrosis.

Background: Idiopathic pulmonary fibrosis (IPF) is a chronic lung condition that is more prevalent in males than females. The reasons for this are not fully understood, with differing environmental exposures due to historically sex-biased occupations, or diagnostic bias, being possible explanations. To date, over 20 independent genetic variants have been identified to be associated with IPF susceptibility, but these have been discovered when combining males and females. Our aim was to test for the presence of sex-specific associations with IPF susceptibility and assess whether there is a need to consider sex-specific effects when evaluating genetic risk in clinical prediction models for IPF. Methods: We performed genome-wide single nucleotide polymorphism (SNP)-by-sex interaction studies of IPF risk in six independent IPF case-control studies and combined them using inverse-variance weighted fixed effect meta-analysis. In total, 4,561 cases (1,280 females and 2,281 males) and 23,500 controls (8,360 females and 14,528 males) of European genetic ancestry were analysed. We used polygenic risk scores (PRS) to assess differences in genetic risk prediction between males and females. Findings: Three independent genetic association signals were identified. All showed a consistent direction of effect across all individual IPF studies and an opposite direction of effect in IPF susceptibility between females and males. None had been previously identified in IPF susceptibility genome-wide association studies (GWAS). The predictive accuracy of the PRSs were similar between males and females, regardless of whether using combined or sex-specific GWAS results. Interpretation: We prioritised three genetic variants whose effect on IPF risk may be modified by sex, however these require further study. We found no evidence that the predictive accuracy of common SNP-based PRSs varies significantly between males and females.

Scaling of an antibody validation procedure enables quantification of antibody performance in major research applications.

Antibodies are critical reagents to detect and characterize proteins. It is commonly understood that many commercial antibodies do not recognize their intended targets, but information on the scope of the problem remains largely anecdotal, and as such, feasibility of the goal of at least one potent and specific antibody targeting each protein in a proteome cannot be assessed. Focusing on antibodies for human proteins, we have scaled a standardized characterization approach using parental and knockout cell lines (Laflamme et al., 2019) to assess the performance of 614 commercial antibodies for 65 neuroscience-related proteins. Side-by-side comparisons of all antibodies against each target, obtained from multiple commercial partners, have demonstrated that: (i) more than 50% of all antibodies failed in one or more applications, (ii) yet, ~50-75% of the protein set was covered by at least one high-performing antibody, depending on application, suggesting that coverage of human proteins by commercial antibodies is significant; and (iii) recombinant antibodies performed better than monoclonal or polyclonal antibodies. The hundreds of underperforming antibodies identified in this study were found to have been used in a large number of published articles, which should raise alarm. Encouragingly, more than half of the underperforming commercial antibodies were reassessed by the manufacturers, and many had alterations to their recommended usage or were removed from the market. This first study helps demonstrate the scale of the antibody specificity problem but also suggests an efficient strategy toward achieving coverage of the human proteome; mine the existing commercial antibody repertoire, and use the data to focus new renewable antibody generation efforts.

Commercially produced antibodies are essential research tools. Investigators at universities and pharmaceutical companies use them to study human proteins, which carry out all the functions of the cells. Scientists usually buy antibodies from commercial manufacturers who produce more than 6 million antibody products altogether. Yet many commercial antibodies do not work as advertised. They do not recognize their intended protein target or may flag untargeted proteins. Both can skew research results and make it challenging to reproduce scientific studies, which is vital to scientific integrity. Using ineffective commercial antibodies likely wastes $1 billion in research funding each year. Large-scale validation of commercial antibodies by an independent third party could reduce the waste and misinformation associated with using ineffective commercial antibodies. Previous research testing an antibody validation pipeline showed that a commercial antibody widely used in studies to detect a protein involved in amyotrophic lateral sclerosis did not work. Meanwhile, the best-performing commercial antibodies were not used in research. Testing commercial antibodies and making the resulting data available would help scientists identify the best study tools and improve research reliability. Ayoubi et al. collaborated with antibody manufacturers and organizations that produce genetic knock-out cell lines to develop a system validating the effectiveness of commercial antibodies. In the experiments, Ayoubi et al. tested 614 commercial antibodies intended to detect 65 proteins involved in neurologic diseases. An effective antibody was available for about two thirds of the 65 proteins. Yet, hundreds of the antibodies, including many used widely in studies, were ineffective. Manufacturers removed some underperforming antibodies from the market or altered their recommended uses based on these data. Ayoubi et al. shared the resulting data on Zenodo, a publicly available preprint database. The experiments suggest that 20-30% of protein studies use ineffective antibodies, indicating a substantial need for independent assessment of commercial antibodies. Ayoubi et al. demonstrated their side-by-side antibody comparison methods were an effective and efficient way of validating commercial antibodies. Using this approach to test commercial antibodies against all human proteins would cost about $50 million. But it could save much of the $1 billion wasted each year on research involving ineffective antibodies. Independent validation of commercial antibodies could also reduce wasted efforts by scientists using ineffective antibodies and improve the reliability of research results. It would also enable faster, more reliable research that may help scientists understand diseases and develop new therapies to improve patient's lives.

YCharOS open antibody characterisation data: Lessons learned and progress made.

YCharOS is a collaborative initiative aimed at characterising antibodies against the entire human proteome. As of August 2023, they have presented comprehensive knockout characterisation data for 812 antibodies and 78 proteins using techniques such as Western blot, immunoprecipitation, and immunofluorescence. YCharOS consolidates its data into reports (one protein per report) available on Zenodo, a public repository controlled by CERN, to ensure open access. To enhance the visibility of their work, the group is progressively converting their Zenodo reports into F1000 articles, collected on the YCharOS Gateway, and indexed via PubMed. Their data is also accessible through searches on the Antibody Registry. The provided data is a valuable resource for researchers when selecting antibodies for specific applications, although certain limitations should be considered. The data accumulated thus far has illuminated the extent of the problem when poorly performing antibodies are employed in research. While the scientific community was already aware that this was likely a widespread issue, the establishment of a collaborative open science project with industry partners introduces an innovative solution that holds the potential to yield significant returns on investment in the public interest. This potential is substantiated by the number of antibodies that have either been withdrawn or had their recommended usage altered by the vendor. However, despite the discovery of high-performing renewable antibodies for most of the studied proteins, this accounts for a tiny fraction of the human proteome and the commercial antibody market. To realise the full potential of this work, end-users must adjust their antibody procurement and usage practises in line with the provided data. This editorial offers a guide on how individual scientists can utilise the YCharOS data, in addition to sharing the insights gained from the data thus far with the wider scientific community.

Scaling of an antibody validation procedure enables quantification of antibody performance in major research applications.

Antibodies are critical reagents to detect and characterize proteins. It is commonly understood that many commercial antibodies do not recognize their intended targets, but information on the scope of the problem remains largely anecdotal, and as such, feasibility of the goal of at least one potent and specific antibody targeting each protein in a proteome cannot be assessed. Focusing on antibodies for human proteins, we have scaled a standardized characterization approach using parental and knockout cell lines (Laflamme et al., 2019) to assess the performance of 614 commercial antibodies for 65 neuroscience-related proteins. Side-by-side comparisons of all antibodies against each target, obtained from multiple commercial partners, demonstrates that: i) more than 50% of all antibodies failed in one or more tests, ii) yet, ~50-75% of the protein set was covered by at least one high-performing antibody, depending on application, suggesting that coverage of human proteins by commercial antibodies is significant; and iii) recombinant antibodies performed better than monoclonal or polyclonal antibodies. The hundreds of underperforming antibodies identified in this study were found to have been used in a large number of published articles, which should raise alarm. Encouragingly, more than half of the underperforming commercial antibodies were reassessed by the manufacturers, and many had alterations to their recommended usage or were removed from the market. This first such study helps demonstrate the scale of the antibody specificity problem but also suggests an efficient strategy toward achieving coverage of the human proteome; mine the existing commercial antibody repertoire, and use the data to focus new renewable antibody generation efforts.

Tales of the unexpected.

A single event can completely change the direction of a career in science; four researchers share their stories.

Lack of Benefit of High Flow Nasal Oxygen Therapy as Ceiling of Treatment for Severe COVID-19 Pneumonitis in Elderly Frail Patients: A Single Centre Observational Study.

Background: Severe COVID-19 pneumonitis in elderly frail patients is associated with poor outcomes, and therefore invasive mechanical ventilation is often deemed an inappropriate course of action. Some evidence suggests high-flow nasal oxygen (HFNO) may prevent the need for invasive ventilation in other groups of patients, but whether it is an appropriate ceiling of care for older frail patients is unknown. Methods: We retrospectively identified patients with severe COVID-19 pneumonitis requiring FiO2>60% who were deemed inappropriate for invasive ventilation or non-invasive continuous positive airway pressure ventilation (CPAP). Our local protocol based on national guidance suggested these patients should be considered for HFNO. We observed whether the patients received HFNO or standard oxygen therapy (SOT) and compared mortality and survival time in these groups. Results: We identified 81 patients meeting the inclusion criteria. From this group, 24 received HFNO and 57 received SOT. The HFNO group was similar in age, BMI and co-morbidities to the SOT group but less frail, as determined by the Clinical Frailty Scale (CFS). All 24 patients that received HFNO died in comparison to 46 patients (80.7%) in the SOT group. Mortality in the HFNO group was significantly higher than in the SOT group. Conclusion: Elderly frail patients with severe COVID-19 pneumonitis deemed inappropriate for invasive ventilation and did not benefit from HFNO. Further, HFNO may have been associated with harm in this group.

TGFß1 induces resistance of human lung myofibroblasts to cell death via down-regulation of TRPA1 channels.

BACKGROUND AND PURPOSE: TGFß1-mediated myofibroblast activation contributes to pathological fibrosis in many diseases including idiopathic pulmonary fibrosis (IPF), where myofibroblast resistance to oxidant-mediated apoptosis is also evident. We therefore investigated the involvement of redox-sensitive TRPA1 ion channels on human lung myofibroblasts (HLMFs) cell death and TGFß1-mediated pro-fibrotic responses. EXPERIMENTAL APPROACH: The effects of TGFß1 stimulation on TRPA1 expression and cell viability was studied in HLMFs derived from IPF patients and non-fibrotic patients. We also examined a model of TGFß1-dependent fibrogenesis in human lung. We used qRT-PCR, immunofluorescent assays, overexpression with lentiviral vectors and electrophysiological methods. KEY RESULTS: TRPA1 mRNA, protein and ion currents were expressed in HLMFs derived from both non-fibrotic patient controls and IPF patients, and expression was reduced by TGFß1. TRPA1 mRNA was also down-regulated by TGFß1 in a model of lung fibrogenesis in human lung. TRPA1 over-expression or activation induced HLMF apoptosis, and activation of TRPA1 channel activation by H2 O2 induced necrosis. TRPA1 inhibition following TGFß1 down-regulation or pharmacological inhibition, protected HLMFs from both apoptosis and necrosis. Lentiviral vector mediated TRPA1 expression was also found to induce sensitivity to H2 O2 induced cell death in a TRPA1-negative HEK293T cell line. CONCLUSION AND IMPLICATIONS: TGFß1 induces resistance of HLMFs to TRPA1 agonist- and H2 O2 -mediated cell death via down-regulation of TRPA1 channels. Our data suggest that therapeutic strategies which prevent TGFß1-dependent down-regulation of TRPA1 may reduce myofibroblast survival in IPF and therefore improve clinical outcomes.

Mast cells and their activation in lung disease.

Mast cells and their activation contribute to lung health via innate and adaptive immune responses to respiratory pathogens. They are also involved in the normal response to tissue injury. However, mast cells are involved in disease processes characterized by inflammation and remodeling of tissue structure. In these diseases mast cells are often inappropriately and chronically activated. There is evidence for activation of mast cells contributing to the pathophysiology of asthma, pulmonary fibrosis, and pulmonary hypertension. They may also play a role in chronic obstructive pulmonary disease, acute respiratory distress syndrome, and lung cancer. The diverse mechanisms through which mast cells sense and interact with the external and internal microenvironment account for their role in these diseases. Newly discovered mechanisms of redistribution and interaction between mast cells, airway structural cells, and other inflammatory cells may offer novel therapeutic targets in these disease processes.

The subjective meaning of sleep quality: a comparison of individuals with and without insomnia.

STUDY OBJECTIVES: "Sleep quality" is poorly defined yet ubiquitously used by researchers, clinicians and patients. While poor sleep quality is a key feature of insomnia, there are few empirical investigations of sleep quality in insomnia patients. Accordingly, our aim was to investigate the subjective meaning of sleep quality among individuals with insomnia and normal sleepers. DESIGN: Cross sectional between groups (insomnia vs. good sleeper). Analyses were conducted across three outcome variables: (1) a "Speak Freely" procedure in which participants' descriptions of good and poor sleep quality nights were analysed, (2) a "Sleep Quality Interview" in which participants judged the relative importance of variables included in previous research on sleep quality and (3) a sleep quality diary completed over seven consecutive nights. SETTING: University Department of Psychiatry. PARTICIPANTS: Individuals with insomnia (n = 25) and normal sleepers (n = 28). INTERVENTIONS: N/A. RESULTS: Both the insomnia and normal sleeper groups defined sleep quality by tiredness on waking and throughout the day, feeling rested and restored on waking, and the number of awakenings they experienced in the night. The insomnia group had more requirements for judging sleep to be of good quality. CONCLUSION: The meaning of sleep quality among individuals with insomnia and normal sleepers was broadly similar. A comprehensive assessment of a patient's appraisal of their sleep quality may require an assessment of waking and daytime variables.