Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease.

One in ten severe acute respiratory syndrome coronavirus 2 infections result in prolonged symptoms termed long coronavirus disease (COVID), yet disease phenotypes and mechanisms are poorly understood1. Here we profiled 368 plasma proteins in 657 participants ≥3 months following hospitalization. Of these, 426 had at least one long COVID symptom and 233 had fully recovered. Elevated markers of myeloid inflammation and complement activation were associated with long COVID. IL-1R2, MATN2 and COLEC12 were associated with cardiorespiratory symptoms, fatigue and anxiety/depression; MATN2, CSF3 and C1QA were elevated in gastrointestinal symptoms and C1QA was elevated in cognitive impairment. Additional markers of alterations in nerve tissue repair (SPON-1 and NFASC) were elevated in those with cognitive impairment and SCG3, suggestive of brain-gut axis disturbance, was elevated in gastrointestinal symptoms. Severe acute respiratory syndrome coronavirus 2-specific immunoglobulin G (IgG) was persistently elevated in some individuals with long COVID, but virus was not detected in sputum. Analysis of inflammatory markers in nasal fluids showed no association with symptoms. Our study aimed to understand inflammatory processes that underlie long COVID and was not designed for biomarker discovery. Our findings suggest that specific inflammatory pathways related to tissue damage are implicated in subtypes of long COVID, which might be targeted in future therapeutic trials.

Uganda Genome Resource Enables Insights into Population History and Genomic Discovery in Africa.

Genomic studies in African populations provide unique opportunities to understand disease etiology, human diversity, and population history. In the largest study of its kind, comprising genome-wide data from 6,400 individuals and whole-genome sequences from 1,978 individuals from rural Uganda, we find evidence of geographically correlated fine-scale population substructure. Historically, the ancestry of modern Ugandans was best represented by a mixture of ancient East African pastoralists. We demonstrate the value of the largest sequence panel from Africa to date as an imputation resource. Examining 34 cardiometabolic traits, we show systematic differences in trait heritability between European and African populations, probably reflecting the differential impact of genes and environment. In a multi-trait pan-African GWAS of up to 14,126 individuals, we identify novel loci associated with anthropometric, hematological, lipid, and glycemic traits. We find that several functionally important signals are driven by Africa-specific variants, highlighting the value of studying diverse populations across the region.

A statistical framework to identify cell types whose genetically regulated proportions are associated with complex diseases.

Finding disease-relevant tissues and cell types can facilitate the identification and investigation of functional genes and variants. In particular, cell type proportions can serve as potential disease predictive biomarkers. In this manuscript, we introduce a novel statistical framework, cell-type Wide Association Study (cWAS), that integrates genetic data with transcriptomics data to identify cell types whose genetically regulated proportions (GRPs) are disease/trait-associated. On simulated and real GWAS data, cWAS showed good statistical power with newly identified significant GRP associations in disease-associated tissues. More specifically, GRPs of endothelial and myofibroblasts in lung tissue were associated with Idiopathic Pulmonary Fibrosis and Chronic Obstructive Pulmonary Disease, respectively. For breast cancer, the GRP of blood CD8+ T cells was negatively associated with breast cancer (BC) risk as well as survival. Overall, cWAS is a powerful tool to reveal cell types associated with complex diseases mediated by GRPs.

Rheumatoid arthritis and idiopathic pulmonary fibrosis: a bidirectional Mendelian randomisation study.

BACKGROUND: A usual interstitial pneumonia (UIP) pattern of lung injury is a key feature of idiopathic pulmonary fibrosis (IPF) and is also observed in up to 40% of individuals with rheumatoid arthritis (RA)-associated interstitial lung disease (RA-ILD). The RA-UIP phenotype could result from either a causal relationship of RA on UIP or vice versa, or from a simple co-occurrence of RA and IPF due to shared demographic, genetic or environmental risk factors. METHODS: We used two-sample bidirectional Mendelian randomisation (MR) to test the hypothesis of a causal effect of RA on UIP and of UIP on RA, using variants from genome-wide association studies (GWAS) of RA (separately for seropositive (18 019 cases and 991 604 controls) and seronegative (8515 cases and 1 015 471 controls) RA) and of IPF (4125 cases and 20 464 controls) as genetic instruments. Sensitivity analyses were conducted to assess the robustness of the results to violations of the MR assumptions. FINDINGS: IPF showed a significant causal effect on seropositive RA, with developing IPF increasing the risk of seropositive RA (OR=1.06, 95% CI: 1.04 to 1.08, p<0.001) which was robust under all models. For the MR in the other direction, seropositive RA showed a significant protective effect on IPF (OR=0.93; 95% CI: 0.87 to 0.99; p=0.032), but the effect was not significant when sensitivity analyses were applied. This was likely because of bias due to exclusion of patients with RA from among the cases in the IPF GWAS, or possibly because our genetic instruments did not fully capture the effect of the complex human leucocyte antigen region, the strongest RA genetic risk factor. INTERPRETATION: Our findings support the hypothesis that RA-UIP may be due to a cause-effect relationship between UIP and RA, rather than due to a coincidental occurrence of IPF in patients with RA. The significant causal effect of IPF on seropositive RA suggests that pathomechanisms involved in the development of UIP may promote RA, and this may help inform future guidelines on screening for ILD in patients with RA.

DeepPheWAS: an R package for phenotype generation and association analysis for phenome-wide association studies.

SUMMARY: DeepPheWAS is an R package for phenome-wide association studies that creates clinically curated composite phenotypes and integrates quantitative phenotypes from primary care data, longitudinal trajectories of quantitative measures, disease progression and drug response phenotypes. Tools are provided for efficient analysis of association with any genetic input, under any genetic model, with optional sex-stratified analysis, and for developing novel phenotypes. AVAILABILITY AND IMPLEMENTATION: The DeepPheWAS R package is freely available under GNU general public licence v3.0 from at https://github.com/Richard-Packer/DeepPheWAS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Plasma steroid concentrations reflect acute disease severity and normalise during recovery in people hospitalised with COVID-19.

OBJECTIVE: Endocrine systems are disrupted in acute illness, and symptoms reported following coronavirus disease 2019 (COVID-19) are similar to those found with clinical hormone deficiencies. We hypothesised that people with severe acute COVID-19 and with post-COVID symptoms have glucocorticoid and sex hormone deficiencies. DESIGN/PATIENTS: Samples were obtained for analysis from two UK multicentre cohorts during hospitalisation with COVID-19 (International Severe Acute Respiratory Infection Consortium/World Health Organisation [WHO] Clinical Characterization Protocol for Severe Emerging Infections in the UK study), and at follow-up 5 months after hospitalisation (Post-hospitalisation COVID-19 study). MEASUREMENTS: Plasma steroids were quantified by liquid chromatography-mass spectrometry. Steroid concentrations were compared against disease severity (WHO ordinal scale) and validated symptom scores. Data are presented as geometric mean (SD). RESULTS: In the acute cohort (n = 239, 66.5% male), plasma cortisol concentration increased with disease severity (cortisol 753.3 [1.6] vs. 429.2 [1.7] nmol/L in fatal vs. least severe, p < .001). In males, testosterone concentrations decreased with severity (testosterone 1.2 [2.2] vs. 6.9 [1.9] nmol/L in fatal vs. least severe, p < .001). In the follow-up cohort (n = 198, 62.1% male, 68.9% ongoing symptoms, 165 [121-192] days postdischarge), plasma cortisol concentrations (275.6 [1.5] nmol/L) did not differ with in-hospital severity, perception of recovery, or patient-reported symptoms. Male testosterone concentrations (12.6 [1.5] nmol/L) were not related to in-hospital severity, perception of recovery or symptom scores. CONCLUSIONS: Circulating glucocorticoids in patients hospitalised with COVID-19 reflect acute illness, with a marked rise in cortisol and fall in male testosterone. These findings are not observed 5 months from discharge. The lack of association between hormone concentrations and common post-COVID symptoms suggests steroid insufficiency does not play a causal role in this condition.

Accelarated immune ageing is associated with COVID-19 disease severity.

BACKGROUND: The striking increase in COVID-19 severity in older adults provides a clear example of immunesenescence, the age-related remodelling of the immune system. To better characterise the association between convalescent immunesenescence and acute disease severity, we determined the immune phenotype of COVID-19 survivors and non-infected controls. RESULTS: We performed detailed immune phenotyping of peripheral blood mononuclear cells isolated from 103 COVID-19 survivors 3-5 months post recovery who were classified as having had severe (n = 56; age 53.12 ± 11.30 years), moderate (n = 32; age 52.28 ± 11.43 years) or mild (n = 15; age 49.67 ± 7.30 years) disease and compared with age and sex-matched healthy adults (n = 59; age 50.49 ± 10.68 years). We assessed a broad range of immune cell phenotypes to generate a composite score, IMM-AGE, to determine the degree of immune senescence. We found increased immunesenescence features in severe COVID-19 survivors compared to controls including: a reduced frequency and number of naïve CD4 and CD8 T cells (p < 0.0001); increased frequency of EMRA CD4 (p < 0.003) and CD8 T cells (p < 0.001); a higher frequency (p < 0.0001) and absolute numbers (p < 0.001) of CD28-ve CD57+ve senescent CD4 and CD8 T cells; higher frequency (p < 0.003) and absolute numbers (p < 0.02) of PD-1 expressing exhausted CD8 T cells; a two-fold increase in Th17 polarisation (p < 0.0001); higher frequency of memory B cells (p < 0.001) and increased frequency (p < 0.0001) and numbers (p < 0.001) of CD57+ve senescent NK cells. As a result, the IMM-AGE score was significantly higher in severe COVID-19 survivors than in controls (p < 0.001). Few differences were seen for those with moderate disease and none for mild disease. Regression analysis revealed the only pre-existing variable influencing the IMM-AGE score was South Asian ethnicity ([Formula: see text] = 0.174, p = 0.043), with a major influence being disease severity ([Formula: see text] = 0.188, p = 0.01). CONCLUSIONS: Our analyses reveal a state of enhanced immune ageing in survivors of severe COVID-19 and suggest this could be related to SARS-Cov-2 infection. Our data support the rationale for trials of anti-immune ageing interventions for improving clinical outcomes in these patients with severe disease.

PCSK6 and Survival in Idiopathic Pulmonary Fibrosis.

Rationale: Idiopathic pulmonary fibrosis (IPF) is a devastating disease characterized by limited treatment options and high mortality. A better understanding of the molecular drivers of IPF progression is needed. Objectives: To identify and validate molecular determinants of IPF survival. Methods: A staged genome-wide association study was performed using paired genomic and survival data. Stage I cases were drawn from centers across the United States and Europe and stage II cases from Vanderbilt University. Cox proportional hazards regression was used to identify gene variants associated with differential transplantation-free survival (TFS). Stage I variants with nominal significance (P < 5 × 10-5) were advanced for stage II testing and meta-analyzed to identify those reaching genome-wide significance (P < 5 × 10-8). Downstream analyses were performed for genes and proteins associated with variants reaching genome-wide significance. Measurements and Main Results: After quality controls, 1,481 stage I cases and 397 stage II cases were included in the analysis. After filtering, 9,075,629 variants were tested in stage I, with 158 meeting advancement criteria. Four variants associated with TFS with consistent effect direction were identified in stage II, including one in an intron of PCSK6 (proprotein convertase subtilisin/kexin type 6) reaching genome-wide significance (hazard ratio, 4.11 [95% confidence interval, 2.54-6.67]; P = 9.45 × 10-9). PCSK6 protein was highly expressed in IPF lung parenchyma. PCSK6 lung staining intensity, peripheral blood gene expression, and plasma concentration were associated with reduced TFS. Conclusions: We identified four novel variants associated with IPF survival, including one in PCSK6 that reached genome-wide significance. Downstream analyses suggested that PCSK6 protein plays a potentially important role in IPF progression.

A Polygenic Risk Score for Idiopathic Pulmonary Fibrosis and Interstitial Lung Abnormalities.

Rationale: In addition to rare genetic variants and the MUC5B locus, common genetic variants contribute to idiopathic pulmonary fibrosis (IPF) risk. The predictive power of common variants outside the MUC5B locus for IPF and interstitial lung abnormalities (ILAs) is unknown. Objectives: We tested the predictive value of IPF polygenic risk scores (PRSs) with and without the MUC5B region on IPF, ILA, and ILA progression. Methods: We developed PRSs that included (PRS-M5B) and excluded (PRS-NO-M5B) the MUC5B region (500-kb window around rs35705950-T) using an IPF genome-wide association study. We assessed PRS associations with area under the receiver operating characteristic curve (AUC) metrics for IPF, ILA, and ILA progression. Measurements and Main Results: We included 14,650 participants (1,970 IPF; 1,068 ILA) from six multi-ancestry population-based and case-control cohorts. In cases excluded from genome-wide association study, the PRS-M5B (odds ratio [OR] per SD of the score, 3.1; P = 7.1 × 10-95) and PRS-NO-M5B (OR per SD, 2.8; P = 2.5 × 10-87) were associated with IPF. Participants in the top PRS-NO-M5B quintile had ∼sevenfold odds for IPF compared with those in the first quintile. A clinical model predicted IPF (AUC, 0.61); rs35705950-T and PRS-NO-M5B demonstrated higher AUCs (0.73 and 0.7, respectively), and adding both genetic predictors to a clinical model yielded the highest performance (AUC, 0.81). The PRS-NO-M5B was associated with ILA (OR, 1.25) and ILA progression (OR, 1.16) in European ancestry participants. Conclusions: A common genetic variant risk score complements the MUC5B variant to identify individuals at high risk of interstitial lung abnormalities and pulmonary fibrosis.

Reassessing the association of MUC5B with survival in idiopathic pulmonary fibrosis.

A variant in the mucin 5B gene (MUC5B) is strongly associated with the risk of idiopathic pulmonary fibrosis. However, the same variant is associated with increased survival time. Previous work suggested that this may be explained by index event bias, with the true effect being to decrease survival. Here, we reassessed this claim using more recent methods and datasets. We found that the statistical assumptions of the previous analysis did not hold, and instead, we applied recent methods of corrected weighted least squares, MR-RAPS and Slope-hunter to both the previous data and an updated consortium meta-analysis. However, these analyses did not yield robust evidence for increased or decreased survival. In simulations of a true effect of decreased survival, we did not observe any realistic scenario in which index event bias led to an observed effect of increased survival. We therefore regard as unsafe the claim that MUC5B has a true effect of decreased survival. Alternative explanations should be sought to explain the observed association with increased survival.

Integrative analyses for the identification of idiopathic pulmonary fibrosis-associated genes and shared loci with other diseases.

BACKGROUND: Although genome-wide association studies (GWAS) have identified many genomic regions associated with idiopathic pulmonary fibrosis (IPF), the causal genes and functions remain largely unknown. Many single-cell expression data have become available for IPF, and there is increasing evidence suggesting a shared genetic basis between IPF and other diseases. METHODS: We conducted integrative analyses to improve the power of GWAS. First, we calculated global and local genetic correlations to identify IPF genetically associated traits and local regions. Then, we prioritised candidate genes contributing to local genetic correlation. Second, we performed transcriptome-wide association analysis (TWAS) of 44 tissues to identify candidate genes whose genetically predicted expression level is associated with IPF. To replicate our findings and investigate the regulatory role of the transcription factors (TF) in identified candidate genes, we first conducted the heritability enrichment analysis in TF binding sites. Then, we examined the enrichment of the TF target genes in cell-type-specific differentially expressed genes (DEGs) identified from single-cell expression data of IPF and healthy lung samples. FINDINGS: We identified 12 candidate genes across 13 genomic regions using local genetic correlation, including the POT1 locus (p value=0.00041), which contained variants with protective effects on lung cancer but increasing IPF risk. We identified another 13 novel genes using TWAS. Two TFs, MAFK and SMAD2, showed significant enrichment in both partitioned heritability and cell-type-specific DEGs. INTERPRETATION: Our integrative analysis identified new genes for IPF susceptibility and expanded the understanding of the complex genetic architecture and disease mechanism of IPF.

Mendelian randomisation of eosinophils and other cell types in relation to lung function and disease.

RATIONALE: Eosinophils are associated with airway inflammation in respiratory disease. Eosinophil production and survival is controlled partly by interleukin-5: anti-interleukin-5 agents reduce asthma and response correlates with baseline eosinophil counts. However, whether raised eosinophils are causally related to chronic obstructive pulmonary disease (COPD) and other respiratory phenotypes is not well understood. OBJECTIVES: We investigated causality between eosinophils and: lung function, acute exacerbations of COPD, asthma-COPD overlap (ACO), moderate-to-severe asthma and respiratory infections. METHODS: We performed Mendelian randomisation (MR) using 151 variants from genome-wide association studies of blood eosinophils in UK Biobank/INTERVAL, and respiratory traits in UK Biobank/SpiroMeta, using methods relying on different assumptions for validity. We performed multivariable analyses using eight cell types where there was possible evidence of causation by eosinophils. MEASUREMENTS AND MAIN RESULTS: Causal estimates derived from individual variants were highly heterogeneous, which may arise from pleiotropy. The average effect of raising eosinophils was to increase risk of ACO (weighted median OR per SD eosinophils, 1.44 (95%CI 1.19 to 1.74)), and moderate-severe asthma (weighted median OR 1.50 (95%CI 1.23 to 1.83)), and to reduce forced expiratory volume in 1 s (FEV1)/forced vital capacity (FVC) and FEV1 (weighted median estimator, SD FEV1/FVC: -0.054 (95% CI -0.078 to -0.029), effect only prominent in individuals with asthma). CONCLUSIONS: Broad consistency across MR methods may suggest causation by eosinophils (although of uncertain magnitude), yet heterogeneity necessitates caution: other important mechanisms may be responsible for the impairment of respiratory health by these eosinophil-raising variants. These results could suggest that anti-IL5 agents (designed to lower eosinophils) may be valuable in treating other respiratory conditions, including people with overlapping features of asthma and COPD.

Cluster analysis of transcriptomic datasets to identify endotypes of idiopathic pulmonary fibrosis.

BACKGROUND: Considerable clinical heterogeneity in idiopathic pulmonary fibrosis (IPF) suggests the existence of multiple disease endotypes. Identifying these endotypes would improve our understanding of the pathogenesis of IPF and could allow for a biomarker-driven personalised medicine approach. We aimed to identify clinically distinct groups of patients with IPF that could represent distinct disease endotypes. METHODS: We co-normalised, pooled and clustered three publicly available blood transcriptomic datasets (total 220 IPF cases). We compared clinical traits across clusters and used gene enrichment analysis to identify biological pathways and processes that were over-represented among the genes that were differentially expressed across clusters. A gene-based classifier was developed and validated using three additional independent datasets (total 194 IPF cases). FINDINGS: We identified three clusters of patients with IPF with statistically significant differences in lung function (p=0.009) and mortality (p=0.009) between groups. Gene enrichment analysis implicated mitochondrial homeostasis, apoptosis, cell cycle and innate and adaptive immunity in the pathogenesis underlying these groups. We developed and validated a 13-gene cluster classifier that predicted mortality in IPF (high-risk clusters vs low-risk cluster: HR 4.25, 95% CI 2.14 to 8.46, p=3.7×10-5). INTERPRETATION: We have identified blood gene expression signatures capable of discerning groups of patients with IPF with significant differences in survival. These clusters could be representative of distinct pathophysiological states, which would support the theory of multiple endotypes of IPF. Although more work must be done to confirm the existence of these endotypes, our classifier could be a useful tool in patient stratification and outcome prediction in IPF.

The causal relationship between gastro-oesophageal reflux disease and idiopathic pulmonary fibrosis: a bidirectional two-sample Mendelian randomisation study.

BACKGROUND: Gastro-oesophageal reflux disease (GORD) is associated with idiopathic pulmonary fibrosis (IPF) in observational studies. It is not known if this association arises because GORD causes IPF or because IPF causes GORD, or because of confounding by factors, such as smoking, associated with both GORD and IPF. We used bidirectional Mendelian randomisation (MR), where genetic variants are used as instrumental variables to address issues of confounding and reverse causation, to examine how, if at all, GORD and IPF are causally related. METHODS: A bidirectional two-sample MR was performed to estimate the causal effect of GORD on IPF risk and of IPF on GORD risk, using genetic data from the largest GORD (78 707 cases and 288 734 controls) and IPF (4125 cases and 20 464 controls) genome-wide association meta-analyses currently available. RESULTS: GORD increased the risk of IPF, with an OR of 1.6 (95% CI 1.04-2.49; p=0.032). There was no evidence of a causal effect of IPF on the risk of GORD, with an OR of 0.999 (95% CI 0.997-1.000; p=0.245). CONCLUSIONS: We found that GORD increases the risk of IPF, but found no evidence that IPF increases the risk of GORD. GORD should be considered in future studies of IPF risk and interest in it as a potential therapeutic target should be renewed. The mechanisms underlying the effect of GORD on IPF should also be investigated.

Genome-wide association study of chronic sputum production implicates loci involved in mucus production and infection.

BACKGROUND: Chronic sputum production impacts on quality of life and is a feature of many respiratory diseases. Identification of the genetic variants associated with chronic sputum production in a disease agnostic sample could improve understanding of its causes and identify new molecular targets for treatment. METHODS: We conducted a genome-wide association study (GWAS) of chronic sputum production in UK Biobank. Signals meeting genome-wide significance (p<5×10-8) were investigated in additional independent studies, were fine-mapped and putative causal genes identified by gene expression analysis. GWASs of respiratory traits were interrogated to identify whether the signals were driven by existing respiratory disease among the cases and variants were further investigated for wider pleiotropic effects using phenome-wide association studies (PheWASs). RESULTS: From a GWAS of 9714 cases and 48 471 controls, we identified six novel genome-wide significant signals for chronic sputum production including signals in the human leukocyte antigen (HLA) locus, chromosome 11 mucin locus (containing MUC2, MUC5AC and MUC5B) and FUT2 locus. The four common variant associations were supported by independent studies with a combined sample size of up to 2203 cases and 17 627 controls. The mucin locus signal had previously been reported for association with moderate-to-severe asthma. The HLA signal was fine-mapped to an amino acid change of threonine to arginine (frequency 36.8%) in HLA-DRB1 (HLA-DRB1*03:147). The signal near FUT2 was associated with expression of several genes including FUT2, for which the direction of effect was tissue dependent. Our PheWAS identified a wide range of associations including blood cell traits, liver biomarkers, infections, gastrointestinal and thyroid-associated diseases, and respiratory disease. CONCLUSIONS: Novel signals at the FUT2 and mucin loci suggest that mucin fucosylation may be a driver of chronic sputum production even in the absence of diagnosed respiratory disease and provide genetic support for this pathway as a target for therapeutic intervention.

Implementable Deep Learning for Multi-sequence Proton MRI Lung Segmentation: A Multi-center, Multi-vendor, and Multi-disease Study.

BACKGROUND: Recently, deep learning via convolutional neural networks (CNNs) has largely superseded conventional methods for proton (1 H)-MRI lung segmentation. However, previous deep learning studies have utilized single-center data and limited acquisition parameters. PURPOSE: Develop a generalizable CNN for lung segmentation in 1 H-MRI, robust to pathology, acquisition protocol, vendor, and center. STUDY TYPE: Retrospective. POPULATION: A total of 809 1 H-MRI scans from 258 participants with various pulmonary pathologies (median age (range): 57 (6-85); 42% females) and 31 healthy participants (median age (range): 34 (23-76); 34% females) that were split into training (593 scans (74%); 157 participants (55%)), testing (50 scans (6%); 50 participants (17%)) and external validation (164 scans (20%); 82 participants (28%)) sets. FIELD STRENGTH/SEQUENCE: 1.5-T and 3-T/3D spoiled-gradient recalled and ultrashort echo-time 1 H-MRI. ASSESSMENT: 2D and 3D CNNs, trained on single-center, multi-sequence data, and the conventional spatial fuzzy c-means (SFCM) method were compared to manually delineated expert segmentations. Each method was validated on external data originating from several centers. Dice similarity coefficient (DSC), average boundary Hausdorff distance (Average HD), and relative error (XOR) metrics to assess segmentation performance. STATISTICAL TESTS: Kruskal-Wallis tests assessed significances of differences between acquisitions in the testing set. Friedman tests with post hoc multiple comparisons assessed differences between the 2D CNN, 3D CNN, and SFCM. Bland-Altman analyses assessed agreement with manually derived lung volumes. A P value of <0.05 was considered statistically significant. RESULTS: The 3D CNN significantly outperformed its 2D analog and SFCM, yielding a median (range) DSC of 0.961 (0.880-0.987), Average HD of 1.63 mm (0.65-5.45) and XOR of 0.079 (0.025-0.240) on the testing set and a DSC of 0.973 (0.866-0.987), Average HD of 1.11 mm (0.47-8.13) and XOR of 0.054 (0.026-0.255) on external validation data. DATA CONCLUSION: The 3D CNN generated accurate 1 H-MRI lung segmentations on a heterogenous dataset, demonstrating robustness to disease pathology, sequence, vendor, and center. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 1.

Genome-wide association study across five cohorts identifies five novel loci associated with idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a chronic lung condition with poor survival times. We previously published a genome-wide meta-analysis of IPF risk across three studies with independent replication of associated variants in two additional studies. To maximise power and to generate more accurate effect size estimates, we performed a genome-wide meta-analysis across all five studies included in the previous IPF risk genome-wide association studies. We used the distribution of effect sizes across the five studies to assess the replicability of the results and identified five robust novel genetic association signals implicating mTOR (mammalian target of rapamycin) signalling, telomere maintenance and spindle assembly genes in IPF risk.

Joint patient and clinician priority setting to identify 10 key research questions regarding the long-term sequelae of COVID-19.

Given the large numbers of people infected and high rates of ongoing morbidity, research is clearly required to address the needs of adult survivors of COVID-19 living with ongoing symptoms (long COVID). To help direct resource and research efforts, we completed a research prioritisation process incorporating views from adults with ongoing symptoms of COVID-19, carers, clinicians and clinical researchers. The final top 10 research questions were agreed at an independently mediated workshop and included: identifying underlying mechanisms of long COVID, establishing diagnostic tools, understanding trajectory of recovery and evaluating the role of interventions both during the acute and persistent phases of the illness.

Genetically increased circulating FUT3 level leads to reduced risk of idiopathic pulmonary fibrosis: a Mendelian randomisation study.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is a progressive, fatal fibrotic interstitial lung disease. Few circulating biomarkers have been identified to have causal effects on IPF. METHODS: To identify candidate IPF-influencing circulating proteins, we undertook an efficient screen of circulating proteins by applying a two-sample Mendelian randomisation (MR) approach with existing publicly available data. For instruments, we used genetic determinants of circulating proteins which reside cis to the encoded gene (cis-single nucleotide polymorphisms (SNPs)), identified by two genome-wide association studies (GWASs) in European individuals (3301 and 3200 subjects). We then applied MR methods to test if the levels of these circulating proteins influenced IPF susceptibility in the largest IPF GWAS (2668 cases and 8591 controls). We validated the MR results using colocalisation analyses to ensure that both the circulating proteins and IPF shared a common genetic signal. RESULTS: MR analyses of 834 proteins found that a 1 sd increase in circulating galactoside 3(4)-l-fucosyltransferase (FUT3) and α-(1,3)-fucosyltransferase 5 (FUT5) was associated with a reduced risk of IPF (OR 0.81, 95% CI 0.74-0.88; p=6.3×10-7 and OR 0.76, 95% CI 0.68-0.86; p=1.1×10-5, respectively). Sensitivity analyses including multiple cis-SNPs provided similar estimates both for FUT3 (inverse variance weighted (IVW) OR 0.84, 95% CI 0.78-0.91; p=9.8×10-6 and MR-Egger OR 0.69, 95% CI 0.50-0.97; p=0.03) and FUT5 (IVW OR 0.84, 95% CI 0.77-0.92; p=1.4×10-4 and MR-Egger OR 0.59, 95% CI 0.38-0.90; p=0.01). FUT3 and FUT5 signals colocalised with IPF signals, with posterior probabilities of a shared genetic signal of 99.9% and 97.7%, respectively. Further transcriptomic investigations supported the protective effects of FUT3 for IPF. CONCLUSIONS: An efficient MR scan of 834 circulating proteins provided evidence that genetically increased circulating FUT3 level is associated with reduced risk of IPF.

Genetic and clinical characteristics of treatment-resistant depression using primary care records in two UK cohorts.

Treatment-resistant depression (TRD) is a major contributor to the disability caused by major depressive disorder (MDD). Primary care electronic health records provide an easily accessible approach to investigate TRD clinical and genetic characteristics. MDD defined from primary care records in UK Biobank (UKB) and EXCEED studies was compared with other measures of depression and tested for association with MDD polygenic risk score (PRS). Using prescribing records, TRD was defined from at least two switches between antidepressant drugs, each prescribed for at least 6 weeks. Clinical-demographic characteristics, SNP-based heritability (h2SNP) and genetic overlap with psychiatric and non-psychiatric traits were compared in TRD and non-TRD MDD cases. In 230,096 and 8926 UKB and EXCEED participants with primary care data, respectively, the prevalence of MDD was 8.7% and 14.2%, of which 13.2% and 13.5% was TRD, respectively. In both cohorts, MDD defined from primary care records was strongly associated with MDD PRS, and in UKB it showed overlap of 71-88% with other MDD definitions. In UKB, TRD vs healthy controls and non-TRD vs healthy controls h2SNP was comparable (0.25 [SE = 0.04] and 0.19 [SE = 0.02], respectively). TRD vs non-TRD was positively associated with the PRS of attention deficit hyperactivity disorder, with lower socio-economic status, obesity, higher neuroticism and other unfavourable clinical characteristics. This study demonstrated that MDD and TRD can be reliably defined using primary care records and provides the first large scale population assessment of the genetic, clinical and demographic characteristics of TRD.