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How useful is Nanopore adaptive sampling for sequencing Schistosoma mansoni miracidia?
Background Whole-genome sequencing (WGS) is now widely used in Schistosoma genomics. Whilst adult worms typically provide sufficient DNA for molecular analyses, their inaccessibility in live definitive hosts presents a challenge for population studies. Larval stages, such as miracidia can be collected non-invasively and preserved on Whatman FTA cards, however these samples typically yield low quantities of DNA and have high levels of contamination, particularly when obtained from stool samples. To counteract contamination, multiple washing steps prior to placement onto Whatman FTA cards can be performed, but this is labour-intensive and can limit the number of larvae collected. Methods Nanopore sequencing technologies includes an “adaptive sampling” feature, which enables selective enrichment or depletion of target DNA sequences during sequencing. In this study, we evaluated the potential of adaptive sampling to selectively enrich S. mansoni DNA from both washed and unwashed larval stage miracidia. We used Kraken2 to characterise sample contamination and assessed sequencing breadth and depth of genome coverage to determine whether adaptive sampling could provide sufficient S. mansoni DNA for WGS. Results and conclusion Our results demonstrate that washed samples contained a higher proportion of S. mansoni DNA, validating the effectiveness of washing for contamination removal. However, adaptive sampling failed to generate sufficient S. mansoni reads for effective WGS. These findings suggest that, at present, washing remains critical for maximising S. mansoni DNA purity as adaptive sampling alone is insufficient for enrichment. Alternative enrichment strategies will be necessary to improve sequencing efficiency and data quality for S. mansoni WGS.
Convergent evidence linking neonatal vitamin D status and risk of neurodevelopmental disorders: a Danish case-cohort study.
BACKGROUND: There is growing evidence linking neonatal vitamin D deficiency to an increased risk of schizophrenia, ADHD, and autism spectrum disorder (ASD). The aim of this study was to examine the association between two vitamin D biomarkers (25 hydroxyvitamin D [25(OH)D] and vitamin D-binding protein [DBP], and their related genetic correlates) and the risk of six mental disorders. METHODS: We used a population-based, case-cohort sample of all individuals born in Denmark between 1981 and 2005. Using Danish health registers with follow-up to Dec 31, 2012, we identified individuals diagnosed with major depressive disorder, bipolar disorder, schizophrenia, ADHD, ASD, and anorexia nervosa based on ICD-10 criteria. Additionally, a random subcohort from the general population was selected. Based on neonatal dried blood spots, we measured concentrations of 25(OH)D and DBP. Our primary analyses were based on hazard ratios (HR) with 95% CI and absolute risks for the six mental disorders according to measured concentrations of 25(OH)D and DBP. As secondary analyses, we examined the association between genetic predictors of 25(OH)D and DBP, and the six mental disorders, and Mendelian randomisation analyses based on published summary statistics for 25(OH)D, DBP, and the six mental disorders. People with lived experience contributed to the development of the guiding hypothesis. FINDINGS: We used the total population from the iPSYCH2012 design (n=88 764), which included individuals who developed the six mental disorders, major depressive disorder (n=24 240), bipolar disorder (n=1928), schizophrenia (n=3540), ADHD (n=18 726), ASD (n=16 146), anorexia nervosa (n=3643), and the randomly sampled subcohort (n=30 000). Among those who met a range of inclusion criteria (eg, measured 25[OH]D, DBP or genotype, and predominantly European ancestry), we measured 25(OH)D or DBP in 71 793 individuals (38 118 [53·1%] male and 33 675 [46·9%] female); 65 952 had 25(OH)D and 66 797 the DBP measurements. Significant inverse relationships were found between 25(OH)D and schizophrenia (HR 0·82, 95% CI 0·78-0·86), ASD (HR 0·93, 95% CI 0·90-0·96), and ADHD (HR 0·89, 95% CI 0·86-0·92). A significant inverse relationship was found between DBP and schizophrenia (HR 0·84, 95% CI 0·80-0·88). Based on polygenic risk scores, higher concentrations of 25(OH)D (adjusted for DBP) were significantly associated with a reduced risk of both ASD and schizophrenia. Analyses based on Mendelian randomisation provided support for a causal association between both lower 25(OH)D and DBP concentrations and an increased risk of ADHD. INTERPRETATION: Convergent evidence finds that neonatal vitamin D status is associated with an altered risk of mental disorders. Our study supports the hypothesis that optimising neonatal vitamin D status might reduce the incidence of a range of neurodevelopmental disorders. FUNDING: The Danish National Research Foundation.
Impact of the first national COVID-19 lockdown on referral of women experiencing domestic violence and abuse in England and Wales.
BackgroundThe lockdown periods to curb COVID-19 transmission have made it harder for survivors of domestic violence and abuse (DVA) to disclose abuse and access support services. Our study describes the impact of the first COVID-19 wave and the associated national lockdown in England and Wales on the referrals from general practice to the Identification and Referral to Improve Safety (IRIS) DVA programme. We compare this to the change in referrals in the same months in the previous year, during the school holidays in the 3 years preceding the pandemic and the period just after the first COVID-19 wave. School holiday periods were chosen as a comparator, since families, including the perpetrator, are together, affecting access to services.MethodsWe used anonymised data on daily referrals received by the IRIS DVA service in 33 areas from general practices over the period April 2017-September 2020. Interrupted-time series and non-linear regression were used to quantify the impact of the first national lockdown in March-June 2020 comparing analogous months the year before, and the impact of school holidays (01/04/2017-30/09/2020) on number of referrals, reporting Incidence Rate Ratio (IRR), 95% confidence intervals and p-values.ResultsThe first national lockdown in 2020 led to reduced number of referrals to DVA services (27%, 95%CI = (21,34%)) compared to the period before and after, and 19% fewer referrals compared to the same period in the year before. A reduction in the number of referrals was also evident during the school holidays with the highest reduction in referrals during the winter 2019 pre-pandemic school holiday (44%, 95%CI = (32,54%)) followed by the effect from the summer of 2020 school holidays (20%, 95%CI = (10,30%)). There was also a smaller reduction (13-15%) in referrals during the longer summer holidays 2017-2019; and some reduction (5-16%) during the shorter spring holidays 2017-2019.ConclusionsWe show that the COVID-19 lockdown in 2020 led to decline in referrals to DVA services. Our findings suggest an association between decline in referrals to DVA services for women experiencing DVA and prolonged periods of systemic closure proxied here by both the first COVID-19 national lockdown or school holidays. This highlights the need for future planning to provide adequate access and support for people experiencing DVA during future national lockdowns and during the school holidays.
Identification of undetected SARS-CoV-2 infections by clustering of Nucleocapsid antibody trajectories.
During the COVID-19 pandemic, numerous SARS-CoV-2 infections remained undetected. We combined results from routine monthly nose and throat swabs, and self-reported positive swab tests, from a UK household survey, linked to national swab testing programme data from England and Wales, together with Nucleocapsid (N-)antibody trajectories clustered using a longitudinal variation of K-means (N = 185,646) to estimate the number of infections undetected by either approach. Using N-antibody (hypothetical) infections and swab-positivity, we estimated that 7.4% (95%CI: 7.0-7.8%) of all true infections (detected and undetected) were undetected by both approaches, 25.8% (25.5-26.1%) by swab-positivity-only and 28.6% (28.4-28.9%) by trajectory-based N-antibody-classifications-only. Congruence with swab-positivity was respectively much poorer and slightly better with N-antibody classifications based on fixed thresholds or fourfold increases. Using multivariable logistic regression N-antibody seroconversion was more likely as age increased between 30-60 years, in non-white participants, those less (recently/frequently) vaccinated, for lower cycle threshold values in the range above 30, and in symptomatic and Delta (vs. BA.1) infections. Comparing swab-positivity data sources showed that routine monthly swabs were insufficient to detect infections and incorporating national testing programme/self-reported data substantially increased detection. Overall, whilst N-antibody serosurveillance can identify infections undetected by swab-positivity, optimal use requires fourfold-increase-based or trajectory-based analysis.
Global, regional, and national burden of epilepsy, 1990-2016: a systematic analysis for the Global Burden of Disease Study 2016.
BackgroundSeizures and their consequences contribute to the burden of epilepsy because they can cause health loss (premature mortality and residual disability). Data on the burden of epilepsy are needed for health-care planning and resource allocation. The aim of this study was to quantify health loss due to epilepsy by age, sex, year, and location using data from the Global Burden of Diseases, Injuries, and Risk Factors Study.MethodsWe assessed the burden of epilepsy in 195 countries and territories from 1990 to 2016. Burden was measured as deaths, prevalence, and disability-adjusted life-years (DALYs; a summary measure of health loss defined by the sum of years of life lost [YLLs] for premature mortality and years lived with disability), by age, sex, year, location, and Socio-demographic Index (SDI; a compound measure of income per capita, education, and fertility). Vital registrations and verbal autopsies provided information about deaths, and data on the prevalence and severity of epilepsy largely came from population representative surveys. All estimates were calculated with 95% uncertainty intervals (UIs).FindingsIn 2016, there were 45·9 million (95% UI 39·9-54·6) patients with all-active epilepsy (both idiopathic and secondary epilepsy globally; age-standardised prevalence 621·5 per 100 000 population; 540·1-737·0). Of these patients, 24·0 million (20·4-27·7) had active idiopathic epilepsy (prevalence 326·7 per 100 000 population; 278·4-378·1). Prevalence of active epilepsy increased with age, with peaks at 5-9 years (374·8 [280·1-490·0]) and at older than 80 years of age (545·1 [444·2-652·0]). Age-standardised prevalence of active idiopathic epilepsy was 329·3 per 100 000 population (280·3-381·2) in men and 318·9 per 100 000 population (271·1-369·4) in women, and was similar among SDI quintiles. Global age-standardised mortality rates of idiopathic epilepsy were 1·74 per 100 000 population (1·64-1·87; 1·40 per 100 000 population [1·23-1·54] for women and 2·09 per 100 000 population [1·96-2·25] for men). Age-standardised DALYs were 182·6 per 100 000 population (149·0-223·5; 163·6 per 100 000 population [130·6-204·3] for women and 201·2 per 100 000 population [166·9-241·4] for men). The higher DALY rates in men were due to higher YLL rates compared with women. Between 1990 and 2016, there was a non-significant 6·0% (-4·0 to 16·7) change in the age-standardised prevalence of idiopathic epilepsy, but a significant decrease in age-standardised mortality rates (24·5% [10·8 to 31·8]) and age-standardised DALY rates (19·4% [9·0 to 27·6]). A third of the difference in age-standardised DALY rates between low and high SDI quintile countries was due to the greater severity of epilepsy in low-income settings, and two-thirds were due to a higher YLL rate in low SDI countries.InterpretationDespite the decrease in the disease burden from 1990 to 2016, epilepsy is still an important cause of disability and mortality. Standardised collection of data on epilepsy in population representative surveys will strengthen the estimates, particularly in countries for which we currently have no or sparse data and if additional data is collected on severity, causes, and treatment. Sizeable gains in reducing the burden of epilepsy might be expected from improved access to existing treatments in low-income countries and from the development of new effective drugs worldwide.FundingBill & Melinda Gates Foundation.
Multimorbidity Management: A Scoping Review of Interventions and Health Outcomes
Multimorbidity, defined as the co-occurrence of two or more chronic conditions in an individual, has emerged as a worldwide public health concern contributing to mortality and morbidity. This complex health phenomenon is becoming increasingly prevalent worldwide, particularly as populations continue to age. Despite the growing burden of multimorbidity, the development and implementation of interventions published by scholars are still in their early stages with significant variability in strategies and outcomes. The variability in strategy and outcome may result from factors such as lack of infrastructure, socioeconomic status and lifestyle factors. The review aims to synthesize interventions designed to manage and mitigate multimorbidity and explore a range of approaches, including pharmacological treatments, lifestyle modifications, care coordination models, and technological innovations. The scoping review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) Checklist. It included 1,553,877 individuals with multimorbidity with no age restriction; in the studies that included gender difference, 463,339 male participants and 1,091,538 female participants were involved. Multimorbidity interventions were defined as strategies or programs designed to manage and improve the health and quality of life of individuals with multiple chronic conditions. Of the downloaded articles, those that met the inclusion criteria were published between 2012 and 2024. The final analysis included 100 articles from 3119 published articles, which resulted in 9 themes and 15 subthemes. Themes on the need for lifestyle and behavioural interventions, patient empowerment and engagement, multimorbidity management, health integration, pharmacotherapy optimization, community and policy interventions, healthcare system improvements, technology and digital health, as well as research and evidence-based practice interventions, emerged. The reviewed literature emphasizes the necessity of multidisciplinary approaches to effectively combat the growing public health challenge of multimorbidity.
Determining a role for Patient and Public Involvement and Engagement (PPIE) in genomic data governance for cancer care
Abstract Comprehensive collections of cancer data, including genomic data, are needed to improve cancer risk prediction and treatments. A recent government review, Better, Broader, Safer: Using health data for research and analysis, has argued for high-quality Patient and Public Involvement and Engagement (PPIE) for ethical data use. In this paper we determine a role and justification for PPIE to govern uses of genomic data in fields like cancer. First, we analyse two public attitudes studies about the role of PPIE in genomics governance. Second, we characterise two ethically-significant features of the context of governing genomic data: 1) data aggregation leading to novel group formation, and 2) the hybrid territory of genomic cancer data uses. Thirdly, we bring together these aspects to describe a fully determined role for PPIE within an approach to governing cancer genomic data, which is tailored to major areas of ethical consideration. Our account is a novel interpretation of what PPIE is for in governance, how it may foster public support and how its success in so doing depends on it being tailored to context.
Methodological opportunities in genomic data analysis to advance health equity.
The causes and consequences of inequities in genomic research and medicine are complex and widespread. However, it is widely acknowledged that underrepresentation of diverse populations in human genetics research risks exacerbating existing health disparities. Efforts to improve diversity are ongoing, but an often-overlooked source of inequity is the choice of analytical methods used to process, analyse and interpret genomic data. This choice can influence all areas of genomic research, from genome-wide association studies and polygenic score development to variant prioritization and functional genomics. New statistical and machine learning techniques to understand, quantify and correct for the impact of biases in genomic data are emerging within the wider genomic research and genomic medicine ecosystems. At this crucial time point, it is important to clarify where improvements in methods and practices can, or cannot, have a role in improving equity in genomics. Here, we review existing approaches to promote equity and fairness in statistical analysis for genomics, and propose future methodological developments that are likely to yield the most impact for equity.
Molnupiravir or nirmatrelvir-ritonavir plus usual care versus usual care alone in patients admitted to hospital with COVID-19: a randomised, controlled, open-label, platform trial (RECOVERY)
Background: Molnupiravir and nirmatrelvir-ritonavir (Paxlovid) are oral antivirals that were assessed in separate treatment comparisons in the RECOVERY trial, a randomised, controlled, open-label, adaptive platform trial evaluating treatments for patients hospitalised with COVID-19 pneumonia. Methods: Adult participants could join the molnupiravir comparison, the nirmatrelvir-ritonavir comparison, or both. In each comparison, they were randomly allocated in a 1:1 ratio to the relevant antiviral (five days of molnupiravir 800mg twice daily or nirmatrelvir-ritonavir 300mg/100mg twice daily) in addition to usual care, or to usual care alone. The primary outcome was 28-day mortality, and secondary outcomes were time to discharge alive from hospital, and progression to invasive ventilation or death. Analysis was by intention-to-treat. Both comparisons were stopped because of low recruitment. ISRCTN50189673; clinicaltrials.gov NCT04381936. Findings: From January 2022 to May 2023, 923 patients were recruited to the molnupiravir comparison (445 allocated molnupiravir and 478 allocated usual care), and from March 2022 to May 2023, 137 patients were recruited to the nirmatrelvir-ritonavir comparison (68 allocated nirmatrelvir-ritonavir and 69 allocated usual care). Over three-quarters of the patients were vaccinated and had anti-spike antibodies at randomisation, and over two-thirds were receiving other SARS-CoV-2 antivirals. In the molnupiravir comparison, 74 (17%) patients allocated molnupiravir and 79 (17%) patients allocated usual care died within 28 days (hazard ratio [HR] 0.93; 95% confidence interval [CI] 0.68-1.28; p=0.66). In the nirmatrelvir-ritonavir comparison, 13 (19%) patients allocated nirmatrelvir-ritonavir and 13 (19%) patients allocated usual care died within 28 days (HR 1.02; 95% CI 0.47-2.23; p=0.96). In neither comparison was there evidence of any difference in the duration of hospitalisation or the proportion of patients progressing to invasive ventilation or death. Interpretation: Adding molnupiravir or nirmatrelvir-ritonavir to usual care was not associated with improvements in clinical outcomes. However, limited recruitment meant a clinically meaningful benefit of treatment could not be ruled-out, particularly for nirmatrelvir-ritonavir.
The recency and geographical origins of the bat viruses ancestral to SARS-CoV and SARS-CoV-2.
The emergence of SARS-CoV in 2002 and SARS-CoV-2 in 2019 led to increased sampling of sarbecoviruses circulating in horseshoe bats. Employing phylogenetic inference while accounting for recombination of bat sarbecoviruses, we find that the closest-inferred bat virus ancestors of SARS-CoV and SARS-CoV-2 existed less than a decade prior to their emergence in humans. Phylogeographic analyses show bat sarbecoviruses traveled at rates approximating their horseshoe bat hosts and circulated in Asia for millennia. We find that the direct ancestors of SARS-CoV and SARS-CoV-2 are unlikely to have reached their respective sites of emergence via dispersal in the bat reservoir alone, supporting interactions with intermediate hosts through wildlife trade playing a role in zoonotic spillover. These results can guide future sampling efforts and demonstrate that viral genomic regions extremely closely related to SARS-CoV and SARS-CoV-2 were circulating in horseshoe bats, confirming their importance as the reservoir species for SARS viruses.
Dominant variants in major spliceosome U4 and U5 small nuclear RNA genes cause neurodevelopmental disorders through splicing disruption.
The major spliceosome contains five small nuclear RNAs (snRNAs; U1, U2, U4, U5 and U6) essential for splicing. Variants in RNU4-2, encoding U4, cause a neurodevelopmental disorder called ReNU syndrome. We investigated de novo variants in 50 snRNA-encoding genes in a French cohort of 23,649 individuals with rare disorders and gathered additional cases through international collaborations. Altogether, we identified 145 previously unreported probands with (likely) pathogenic variants in RNU4-2 and 21 individuals with de novo and/or recurrent variants in RNU5B-1 and RNU5A-1, encoding U5. Pathogenic variants typically arose de novo on the maternal allele and cluster in regions critical for splicing. RNU4-2 variants mainly localize to two structures, the stem III and T-loop/quasi-pseudoknot, which position the U6 ACAGAGA box for 5' splice site recognition and associate with different phenotypic severity. RNU4-2 variants result in specific defects in alternative 5' splice site usage and methylation patterns (episignatures) that correlate with variant location and clinical severity. This study establishes RNU5B-1 as a neurodevelopmental disorder gene, suggests RNU5A-1 as a strong candidate and highlights the role of de novo variants in snRNAs.
Systematic identification of disease-causing promoter and untranslated region variants in 8040 undiagnosed individuals with rare disease.
BackgroundBoth promoters and untranslated regions (UTRs) have critical regulatory roles, yet variants in these regions are largely excluded from clinical genetic testing due to difficulty in interpreting pathogenicity. The extent to which these regions may harbour diagnoses for individuals with rare disease is currently unknown.MethodsWe present a framework for the identification and annotation of potentially deleterious proximal promoter and UTR variants in known dominant disease genes. We use this framework to annotate de novo variants (DNVs) in 8040 undiagnosed individuals in the Genomics England 100,000 genomes project, which were subject to strict region-based filtering, clinical review, and validation studies where possible. In addition, we performed region and variant annotation-based burden testing in 7862 unrelated probands against matched unaffected controls.ResultsWe prioritised eleven DNVs and identified an additional variant overlapping one of the eleven. Ten of these twelve variants (82%) are in genes that are a strong match to the individual's phenotype and six had not previously been identified. Through burden testing, we did not observe a significant enrichment of potentially deleterious promoter and/or UTR variants in individuals with rare disease collectively across any of our region or variant annotations.ConclusionsWhilst screening promoters and UTRs can uncover additional diagnoses for individuals with rare disease, including these regions in diagnostic pipelines is not likely to dramatically increase diagnostic yield. Nevertheless, we provide a framework to aid identification of these variants.
Incongruent Multimodal Federated Learning for Medical Vision and Language-based Multi-label Disease Detection
Federated Learning (FL) in healthcare ensures patient privacy by allowing hospitals to collaboratively train machine learning models while keeping sensitive medical data secure and localized. Most existing research in FL has concentrated on unimodal scenarios, where all healthcare institutes share the same type of data. However, in real-world healthcare situations, some clients may have access to multiple types of data pertaining to the same disease. Multimodal Federated Learning (MMFL) utilizes multiple modalities to build a more powerful FL model than its unimodal counterpart. However, the impact of missing modality in different clients, called modality incongruity, has been greatly overlooked. This paper, for the first time, analyses the impact of modality incongruity and reveals its connection with data heterogeneity across participating clients. We particularly inspect whether incongruent MMFL with unimodal and multimodal clients is more beneficial than unimodal FL. Furthermore, we examine three potential routes of addressing this issue. Firstly, we study the effectiveness of various self-attention mechanisms towards incongruity-agnostic information fusion in MMFL. Secondly, we introduce a modality imputation network (MIN) pre-trained in a multimodal client for modality translation in unimodal clients and investigate its potential towards mitigating the missing modality problem. Thirdly, we introduce several client-level and server-level regularization techniques including Modality-aware knowledge Distillation (MAD) and Leave-one-out teacher (LOOT) towards mitigating modality incongruity effects. Experiments are conducted with Chest X-Ray and radiology reports under several MMFL settings on two publicly available real-world datasets, MIMIC-CXR and Open-I.