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Background: Congenital heart defects (CHD) are structural defects of the heart affecting approximately 1% of newborns. They exhibit low penetrance and non-Mendelian patterns of inheritance as varied and complex traits. While genetic factors are known to play an important role in the development of CHD, the specific genetics remain unknown for the majority of patients. To elucidate the underlying genetic risk, we performed a genome wide association study (GWAS) of CHDs in general and specific CHD subgroups using the FinnGen Release 10 (R10) (N > 393,000), followed by functional fine-mapping through eQTL and co-localization analyses using the GTEx database. Results: We discovered three genome-wide significant loci associated with general CHD. Two of them were located in chromosome 17: 17q21.32 (rs2316327, intronic: LRRC37A2, Odds ratio (OR) [95% Confidence Interval (CI)] = 1.17[1.12–1.23], p = 1.5 × 10–9) and 17q25.3 (rs1293973611, nearest: BAHCC1, OR[95%CI] = 4.48[2.80–7.17], p = 7.0 × 10–10), respectively, and in addition to general CHD, the rs1293973611 locus was associated with the septal defect subtype. The third locus was in band 1p21.2 (rs35046143, nearest: PALMD, OR[95%CI] = 1.15[1.09–1.21], p = 7.1 × 10–9), and it was associated with general CHD and left-sided lesions. In the subgroup analysis, two additional loci were associated with septal defects (rs75230966 and rs6824295), and one with left-sided lesions (rs1305393195). In the eQTL analysis the variants rs2316327 (general CHD), and rs75230966 (septal defects) both located in 17q21.32 (with a LD r2 of 0.41) were both predicted to significantly associate with the expression of WNT9B in the atrial appendage tissue category. This effect was further confirmed by co-localization analysis, which also implicated WNT3 expression in the atrial appendage. A meta-analysis of general CHD together with the UK Biobank (combined N = 881,678) provided a different genome-wide significant locus in LRRC37A2; rs16941382 (OR[95%CI] = 1.15[1.11–1.20], p = 1.5 × 10–9) which is in significant LD with rs2316327. Conclusions: Our results of general CHD and different CHD subcategories identified a complex risk locus on chromosome 17 near BAHCC1 and LRRC37A2, interacting with the genes WNT9B, WNT3 and MYL4, may constitute potential novel CHD risk associated loci, warranting future experimental tests to determine their role. [ABSTRACT FROM AUTHOR]

Rare variants in ten genes have been reported to cause Mendelian sleep conditions characterised by extreme sleep duration or timing. These include familial natural short sleep (ADRB1, DEC2/BHLHE41, GRM1 and NPSR1), advanced sleep phase (PER2, PER3, CRY2, CSNK1D and TIMELESS) and delayed sleep phase (CRY1). The association of variants in these genes with extreme sleep conditions were usually based on clinically ascertained families, and their effects when identified in the population are unknown. We aimed to determine the effects of these variants on sleep traits in large population-based cohorts. We performed genetic association analysis of variants previously reported to be causal for Mendelian sleep and circadian conditions. Analyses were performed using 191,929 individuals with data on sleep and whole-exome or genome-sequence data from 4 population-based studies: UK Biobank, FINRISK, Health-2000-2001, and the Multi-Ethnic Study of Atherosclerosis (MESA). We identified sleep disorders from self-report, hospital and primary care data. We estimated sleep duration and timing measures from self-report and accelerometery data. We identified carriers for 10 out of 12 previously reported pathogenic variants for 8 of the 10 genes. They ranged in frequency from 1 individual with the variant in CSNK1D to 1,574 individuals with a reported variant in the PER3 gene in the UK Biobank. No carriers for variants reported in NPSR1 or PER2 were identified. We found no association between variants analyzed and extreme sleep or circadian phenotypes. Using sleep timing as a proxy measure for sleep phase, only PER3 and CRY1 variants demonstrated association with earlier and later sleep timing, respectively; however, the magnitude of effect was smaller than previously reported (sleep midpoint ~7 mins earlier and ~5 mins later, respectively). We also performed burden tests of protein truncating (PTVs) or rare missense variants for the 10 genes. Only PTVs in PER2 and PER3 were associated with a relevant trait (for example, 64 individuals with a PTV in PER2 had an odds ratio of 4.4 for being "definitely a morning person", P = 4x10-8; and had a 57-minute earlier midpoint sleep, P = 5x10-7). Our results indicate that previously reported variants for Mendelian sleep and circadian conditions are often not highly penetrant when ascertained incidentally from the general population. Author summary: Clinically ascertained family-based studies have previously identified rare genetic variation associated with causing life-long sleep conditions, specifically shorter sleep, and earlier or later sleep timing. However, the effects of previously reported genetic variants on sleep duration and timing when identified incidentally through population-based studies are not known. Here, we take advantage of up to 191,929 individuals from four population-based studies, including the UK Biobank, to estimate the effects of these variants on sleep duration and timing using self-reported and accelerometer-based sleep estimates coupled with sequencing data. Our analysis revealed no association between variants previously reported and extreme sleep conditions. Two variants located in two genes (PER3 and CRY1) showed evidence of association with sleep timing, but their estimated effects (~5 to 7 minutes) on sleep timing are much smaller relative to those previously reported. Our results indicate that previously reported variants are not causal for extreme sleep conditions in the general population. Finally, although we were unable to analyse a previously reported variant in the PER2 gene associated with sleep timing, additional analysis in the UK Biobank revealed carries of protein-truncating variants in this gene have an approximately 1-hour earlier sleep midpoint compared to non-carriers. These population-based estimates are important because of the recent dramatic increase in direct-to-consumer and health service genome-wide genetic testing. [ABSTRACT FROM AUTHOR]

Background: Sleep problems are both symptoms of and modifiable risk factors for many psychiatric disorders. Wrist-worn accelerometers enable objective measurement of sleep at scale. Here, we aimed to examine the association of accelerometer-derived sleep measures with psychiatric diagnoses and polygenic risk scores in a large community-based cohort.Methods and Findings: In this post hoc cross-sectional analysis of the UK Biobank cohort, 10 interpretable sleep measures-bedtime, wake-up time, sleep duration, wake after sleep onset, sleep efficiency, number of awakenings, duration of longest sleep bout, number of naps, and variability in bedtime and sleep duration-were derived from 7-day accelerometry recordings across 89,205 participants (aged 43 to 79, 56% female, 97% self-reported white) taken between 2013 and 2015. These measures were examined for association with lifetime inpatient diagnoses of major depressive disorder, anxiety disorders, bipolar disorder/mania, and schizophrenia spectrum disorders from any time before the date of accelerometry, as well as polygenic risk scores for major depression, bipolar disorder, and schizophrenia. Covariates consisted of age and season at the time of the accelerometry recording, sex, Townsend deprivation index (an indicator of socioeconomic status), and the top 10 genotype principal components. We found that sleep pattern differences were ubiquitous across diagnoses: each diagnosis was associated with a median of 8.5 of the 10 accelerometer-derived sleep measures, with measures of sleep quality (for instance, sleep efficiency) generally more affected than mere sleep duration. Effect sizes were generally small: for instance, the largest magnitude effect size across the 4 diagnoses was β = -0.11 (95% confidence interval -0.13 to -0.10, p = 3 × 10-56, FDR = 6 × 10-55) for the association between lifetime inpatient major depressive disorder diagnosis and sleep efficiency. Associations largely replicated across ancestries and sexes, and accelerometry-derived measures were concordant with self-reported sleep properties. Limitations include the use of accelerometer-based sleep measurement and the time lag between psychiatric diagnoses and accelerometry.Conclusions: In this study, we observed that sleep pattern differences are a transdiagnostic feature of individuals with lifetime mental illness, suggesting that they should be considered regardless of diagnosis. Accelerometry provides a scalable way to objectively measure sleep properties in psychiatric clinical research and practice, even across tens of thousands of individuals. [ABSTRACT FROM AUTHOR]

Daytime napping is a common, heritable behavior, but its genetic basis and causal relationship with cardiometabolic health remain unclear. Here, we perform a genome-wide association study of self-reported daytime napping in the UK Biobank (n = 452,633) and identify 123 loci of which 61 replicate in the 23andMe research cohort (n = 541,333). Findings include missense variants in established drug targets for sleep disorders (HCRTR1, HCRTR2), genes with roles in arousal (TRPC6, PNOC), and genes suggesting an obesity-hypersomnolence pathway (PNOC, PATJ). Association signals are concordant with accelerometer-measured daytime inactivity duration and 33 loci colocalize with loci for other sleep phenotypes. Cluster analysis identifies three distinct clusters of nap-promoting mechanisms with heterogeneous associations with cardiometabolic outcomes. Mendelian randomization shows potential causal links between more frequent daytime napping and higher blood pressure and waist circumference. The genetic basis of daytime napping and the directional effect of daytime napping on cardiometabolic health are unknown. Here, the authors perform a genome-wide association study on self-reported daytime napping in the UK Biobank and Mendelian randomization to explore causal associations. [ABSTRACT FROM AUTHOR]

Summary: Background: Single nucleotide polymorphism–based genetic risk scores (GRS) model genetic risk as a continuum and can discriminate coeliac disease but have not been validated in clinic. Human leukocyte antigen (HLA) DQ gene testing is available in clinic but does not include non‐HLA attributed risk and is limited by discrete risk stratification. Aims: To accurately characterise both HLA and non‐HLA coeliac disease genetic risk as a single nucleotide polymorphism–based GRS and evaluate diagnostic utility. Methods: We developed a 42 single nucleotide polymorphism coeliac disease GRS from a European case‐control study (12 041 cases vs 12 228 controls) using HLA‐DQ imputation and published genome‐wide association studies. We validated the GRS in UK Biobank (1237 cases) and developed direct genotyping assays. We tested the coeliac disease GRS in a pilot clinical cohort of 128 children presenting with suspected coeliac disease. Results: The GRS was more discriminative of coeliac disease than HLA‐DQ stratification in UK Biobank (receiver operating characteristic area under the curve [ROC‐AUC] = 0.88 [95% CIs: 0.87‐0.89] vs 0.82 [95% CIs: 0.80‐0.83]). We demonstrated similar discrimination in the pilot clinical cohort (114 cases vs 40 controls, ROC‐AUC = 0.84 [95% CIs: 0.76‐0.91]). As a rule‐out test, no children with coeliac disease in the clinical cohort had a GRS below 38th population centile. Conclusions: A single nucleotide polymorphism–based GRS may offer more effective and cost‐efficient testing of coeliac disease genetic risk in comparison to HLA‐DQ stratification. As a comparatively inexpensive test it could facilitate non‐invasive coeliac disease diagnosis but needs detailed assessment in the context of other diagnostic tests and against current diagnostic algorithms. [ABSTRACT FROM AUTHOR]

Background: We assessed whether body mass index (BMI) affects social and socio-economic outcomes.Methods: We used Mendelian randomization (MR), non-linear MR and non-genetic and MR within-sibling analyses, to estimate relationships of BMI with six socio-economic and four social outcomes in 378 244 people of European ancestry in UK Biobank.Results: In MR of minimally related individuals, higher BMI was related to higher deprivation, lower income, fewer years of education, lower odds of degree-level education and skilled employment. Non-linear MR suggested both low (bottom decile, <22 kg/m2) and high (top seven deciles, >24.6 kg/m2) BMI, increased deprivation and reduced income. Non-genetic within-sibling analysis supported an effect of BMI on socio-economic position (SEP); precision in within-sibling MR was too low to draw inference about effects of BMI on SEP. There was some evidence of pleiotropy, with MR Egger suggesting limited effects of BMI on deprivation, although precision of these estimates is also low. Non-linear MR suggested that low BMI (bottom three deciles, <23.5 kg/m2) reduces the odds of cohabiting with a partner or spouse in men, whereas high BMI (top two deciles, >30.7 kg/m2) reduces the odds of cohabitation in women. Both non-genetic and MR within-sibling analyses supported this sex-specific effect of BMI on cohabitation. In men only, higher BMI was related to lower participation in leisure and social activities. There was little evidence that BMI affects visits from friends and family or having someone to confide in.Conclusions: BMI may affect social and socio-economic outcomes, with both high and low BMI being detrimental for SEP, although larger within-family MR studies may help to test the robustness of MR results in unrelated individuals. Triangulation of evidence across MR and within-family analyses supports evidence of a sex-specific effect of BMI on cohabitation. [ABSTRACT FROM AUTHOR]

Background: Gastro-oesophageal reflux disease (GORD) is associated with multiple risk factors but determining causality is difficult. We used a genetic approach [Mendelian randomization (MR)] to identify potential causal modifiable risk factors for GORD.Methods: We used data from 451 097 European participants in the UK Biobank and defined GORD using hospital-defined ICD10 and OPCS4 codes and self-report data (N = 41 024 GORD cases). We tested observational and MR-based associations between GORD and four adiposity measures [body mass index (BMI), waist-hip ratio (WHR), a metabolically favourable higher body-fat percentage and waist circumference], smoking status, smoking frequency and caffeine consumption.Results: Observationally, all adiposity measures were associated with higher odds of GORD. Ever and current smoking were associated with higher odds of GORD. Coffee consumption was associated with lower odds of GORD but, among coffee drinkers, more caffeinated-coffee consumption was associated with higher odds of GORD. Using MR, we provide strong evidence that higher WHR and higher WHR adjusted for BMI lead to GORD. There was weak evidence that higher BMI, body-fat percentage, coffee drinking or smoking caused GORD, but only the observational effects for BMI and body-fat percentage could be excluded. This MR estimated effect for WHR equates to a 1.23-fold higher odds of GORD per 5-cm increase in waist circumference.Conclusions: These results provide strong evidence that a higher waist-hip ratio leads to GORD. Our study suggests that central fat distribution is crucial in causing GORD rather than overall weight. [ABSTRACT FROM AUTHOR]

Importance: Insomnia, hypersomnia, and an evening chronotype are common in individuals with bipolar disorder (BD), but whether this reflects shared genetic liability is unclear. Stratifying by BD subtypes could elucidate this association and inform sleep and BD research.Objective: To assess whether polygenic risk scores (PRSs) for sleep traits are associated with BD subtypes I and II.Design, Setting, and Participants: This case-control study was conducted in the United Kingdom and Sweden with participants with BD and control participants. Multinomial regression was used to assess whether PRSs for insomnia, daytime sleepiness, sleep duration, and chronotype are associated with BD subtypes compared with control participants. Affected individuals were recruited from the Bipolar Disorder Research Network. Control participants were recruited from the 1958 British Birth Cohort and the UK Blood Service. Analyses were repeated in an independent Swedish sample from August 2018 to July 2019. All participants were of European ancestry.Exposures: Standardized PRSs derived using alleles from genome-wide association studies of insomnia, sleep duration, daytime sleepiness, and chronotype. These were adjusted for the first 10 population principal components, genotyping platforms, and sex.Main Outcomes and Measures: Association of PRSs with BD subtypes, determined by semistructured psychiatric interview and case notes.Results: The main analysis included 4672 participants with BD (3132 female participants [67.0%]; 3404 with BD-I [72.9%]) and 5714 control participants (2812 female participants [49.2%]). Insomnia PRS was associated with increased risk of BD-II (relative risk [RR], 1.14 [95% CI, 1.07-1.21]; P = 8.26 × 10-5) but not BD-I (RR, 0.98 [95% CI, 0.94-1.03]; P = .409) relative to control participants. Sleep-duration PRS was associated with BD-I (RR, 1.10 [95% CI, 1.06-1.15]; P = 1.13 × 10-5) but not BD-II (RR, 0.99 [95% CI, 0.93-1.06]; P = .818). Associations between (1) insomnia PRS and BD-II and (2) sleep-duration PRS and BD-I were replicated in the Swedish sample of 4366 individuals with BD (2697 female participants [61.8%]; 2627 with BD-I [60.2%]) and 6091 control participants (3767 female participants [61.8%]). Chronotype and daytime-sleepiness PRS were not associated with BD subtypes.Conclusions and Relevance: Per this analysis, BD subtypes differ in genetic liability to insomnia and hypersomnia, providing further evidence that the distinction between BD-I and BD-II has genetic validity. This distinction will be crucial in selecting participants for future research on the role of sleep disturbance in BD. [ABSTRACT FROM AUTHOR]

Background: Depression is more common in obese than non-obese individuals, especially in women, but the causal relationship between obesity and depression is complex and uncertain. Previous studies have used genetic variants associated with BMI to provide evidence that higher body mass index (BMI) causes depression, but have not tested whether this relationship is driven by the metabolic consequences of BMI nor for differences between men and women.Methods: We performed a Mendelian randomization study using 48 791 individuals with depression and 291 995 controls in the UK Biobank, to test for causal effects of higher BMI on depression (defined using self-report and Hospital Episode data). We used two genetic instruments, both representing higher BMI, but one with and one without its adverse metabolic consequences, in an attempt to 'uncouple' the psychological component of obesity from the metabolic consequences. We further tested causal relationships in men and women separately, and using subsets of BMI variants from known physiological pathways.Results: Higher BMI was strongly associated with higher odds of depression, especially in women. Mendelian randomization provided evidence that higher BMI partly causes depression. Using a 73-variant BMI genetic risk score, a genetically determined one standard deviation (1 SD) higher BMI (4.9 kg/m2) was associated with higher odds of depression in all individuals [odds ratio (OR): 1.18, 95% confidence interval (CI): 1.09, 1.28, P = 0.00007) and women only (OR: 1.24, 95% CI: 1.11, 1.39, P = 0.0001). Meta-analysis with 45 591 depression cases and 97 647 controls from the Psychiatric Genomics Consortium (PGC) strengthened the statistical confidence of the findings in all individuals. Similar effect size estimates were obtained using different Mendelian randomization methods, although not all reached P < 0.05. Using a metabolically favourable adiposity genetic risk score, and meta-analysing data from the UK biobank and PGC, a genetically determined 1 SD higher BMI (4.9 kg/m2) was associated with higher odds of depression in all individuals (OR: 1.26, 95% CI: 1.06, 1.50], P = 0.010), but with weaker statistical confidence.Conclusions: Higher BMI, with and without its adverse metabolic consequences, is likely to have a causal role in determining the likelihood of an individual developing depression. [ABSTRACT FROM AUTHOR]

Background: Psoriasis is a common inflammatory skin disease that has been reported to be associated with obesity. We aimed to investigate a possible causal relationship between body mass index (BMI) and psoriasis.Methods and Findings: Following a review of published epidemiological evidence of the association between obesity and psoriasis, mendelian randomization (MR) was used to test for a causal relationship with BMI. We used a genetic instrument comprising 97 single-nucleotide polymorphisms (SNPs) associated with BMI as a proxy for BMI (expected to be much less confounded than measured BMI). One-sample MR was conducted using individual-level data (396,495 individuals) from the UK Biobank and the Nord-Trøndelag Health Study (HUNT), Norway. Two-sample MR was performed with summary-level data (356,926 individuals) from published BMI and psoriasis genome-wide association studies (GWASs). The one-sample and two-sample MR estimates were meta-analysed using a fixed-effect model. To test for a potential reverse causal effect, MR analysis with genetic instruments comprising variants from recent genome-wide analyses for psoriasis were used to test whether genetic risk for this skin disease has a causal effect on BMI. Published observational data showed an association of higher BMI with psoriasis. A mean difference in BMI of 1.26 kg/m2 (95% CI 1.02-1.51) between psoriasis cases and controls was observed in adults, while a 1.55 kg/m2 mean difference (95% CI 1.13-1.98) was observed in children. The observational association was confirmed in UK Biobank and HUNT data sets. Overall, a 1 kg/m2 increase in BMI was associated with 4% higher odds of psoriasis (meta-analysis odds ratio [OR] = 1.04; 95% CI 1.03-1.04; P = 1.73 × 10(-60)). MR analyses provided evidence that higher BMI causally increases the odds of psoriasis (by 9% per 1 unit increase in BMI; OR = 1.09 (1.06-1.12) per 1 kg/m2; P = 4.67 × 10(-9)). In contrast, MR estimates gave little support to a possible causal effect of psoriasis genetic risk on BMI (0.004 kg/m2 change in BMI per doubling odds of psoriasis (-0.003 to 0.011). Limitations of our study include possible misreporting of psoriasis by patients, as well as potential misdiagnosis by clinicians. In addition, there is also limited ethnic variation in the cohorts studied.Conclusions: Our study, using genetic variants as instrumental variables for BMI, provides evidence that higher BMI leads to a higher risk of psoriasis. This supports the prioritization of therapies and lifestyle interventions aimed at controlling weight for the prevention or treatment of this common skin disease. Mechanistic studies are required to improve understanding of this relationship. [ABSTRACT FROM AUTHOR]

Conservation, as a profession, is facing a series of challenges. The closure of training courses is a well-documented and depressing reality,from Australia to the UK. Within institutions, conservators have found it increasingly difficult to fight their corner as the nature of the museum sector changes. New demands are being made on organizations in receipt of public money and, in the wake of the financial crisis,funding will become even harder to conic by. At the same time, social and technological changes have altered the operating environment of many sectors in all walks of life as the public come to have new expectations and the concept of the professional and expert changes. Conservation is no exception. However, these changes bring opportunities as well as challenges. Building on the Demos pamphlet It's a Material World (2008), this paper argues that conservators constantly deal with ideas and concepts that are at the very heart of the public realm, caring for the values around which society is built. Drawing on these and making them explicit could help the profession make its case anew, and could also help policy-makers - and society - meet some of the most significant challenges that we collectively face. [ABSTRACT FROM AUTHOR]

Excessive daytime sleepiness (EDS) affects 10–20% of the population and is associated with substantial functional deficits. Here, we identify 42 loci for self-reported daytime sleepiness in GWAS of 452,071 individuals from the UK Biobank, with enrichment for genes expressed in brain tissues and in neuronal transmission pathways. We confirm the aggregate effect of a genetic risk score of 42 SNPs on daytime sleepiness in independent Scandinavian cohorts and on other sleep disorders (restless legs syndrome, insomnia) and sleep traits (duration, chronotype, accelerometer-derived sleep efficiency and daytime naps or inactivity). However, individual daytime sleepiness signals vary in their associations with objective short vs long sleep, and with markers of sleep continuity. The 42 sleepiness variants primarily cluster into two predominant composite biological subtypes - sleep propensity and sleep fragmentation. Shared genetic links are also seen with obesity, coronary heart disease, psychiatric diseases, cognitive traits and reproductive ageing. A main symptom of chronic insufficient sleep is excessive daytime sleepiness. Here, Wang et al. report 42 genome-wide significant loci for self-reported daytime sleepiness in 452,071 individuals from the UK Biobank that cluster into two biological subtypes of either sleep propensity or sleep fragmentation. [ABSTRACT FROM AUTHOR]

Background: Sleep disturbance is common following hospital admission both for COVID-19 and other causes. The clinical associations of this for recovery after hospital admission are poorly understood despite sleep disturbance contributing to morbidity in other scenarios. We aimed to investigate the prevalence and nature of sleep disturbance after discharge following hospital admission for COVID-19 and to assess whether this was associated with dyspnoea., Methods: CircCOVID was a prospective multicentre cohort substudy designed to investigate the effects of circadian disruption and sleep disturbance on recovery after COVID-19 in a cohort of participants aged 18 years or older, admitted to hospital for COVID-19 in the UK, and discharged between March, 2020, and October, 2021. Participants were recruited from the Post-hospitalisation COVID-19 study (PHOSP-COVID). Follow-up data were collected at two timepoints: an early time point 2-7 months after hospital discharge and a later time point 10-14 months after hospital discharge. Sleep quality was assessed subjectively using the Pittsburgh Sleep Quality Index questionnaire and a numerical rating scale. Sleep quality was also assessed with an accelerometer worn on the wrist (actigraphy) for 14 days. Participants were also clinically phenotyped, including assessment of symptoms (ie, anxiety [Generalised Anxiety Disorder 7-item scale questionnaire], muscle function [SARC-F questionnaire], dyspnoea [Dyspnoea-12 questionnaire] and measurement of lung function), at the early timepoint after discharge. Actigraphy results were also compared to a matched UK Biobank cohort (non-hospitalised individuals and recently hospitalised individuals). Multivariable linear regression was used to define associations of sleep disturbance with the primary outcome of breathlessness and the other clinical symptoms. PHOSP-COVID is registered on the ISRCTN Registry (ISRCTN10980107)., Findings: 2320 of 2468 participants in the PHOSP-COVID study attended an early timepoint research visit a median of 5 months (IQR 4-6) following discharge from 83 hospitals in the UK. Data for sleep quality were assessed by subjective measures (the Pittsburgh Sleep Quality Index questionnaire and the numerical rating scale) for 638 participants at the early time point. Sleep quality was also assessed using device-based measures (actigraphy) a median of 7 months (IQR 5-8 months) after discharge from hospital for 729 participants. After discharge from hospital, the majority (396 [62%] of 638) of participants who had been admitted to hospital for COVID-19 reported poor sleep quality in response to the Pittsburgh Sleep Quality Index questionnaire. A comparable proportion (338 [53%] of 638) of participants felt their sleep quality had deteriorated following discharge after COVID-19 admission, as assessed by the numerical rating scale. Device-based measurements were compared to an age-matched, sex-matched, BMI-matched, and time from discharge-matched UK Biobank cohort who had recently been admitted to hospital. Compared to the recently hospitalised matched UK Biobank cohort, participants in our study slept on average 65 min (95% CI 59 to 71) longer, had a lower sleep regularity index (-19%; 95% CI -20 to -16), and a lower sleep efficiency (3·83 percentage points; 95% CI 3·40 to 4·26). Similar results were obtained when comparisons were made with the non-hospitalised UK Biobank cohort. Overall sleep quality (unadjusted effect estimate 3·94; 95% CI 2·78 to 5·10), deterioration in sleep quality following hospital admission (3·00; 1·82 to 4·28), and sleep regularity (4·38; 2·10 to 6·65) were associated with higher dyspnoea scores. Poor sleep quality, deterioration in sleep quality, and sleep regularity were also associated with impaired lung function, as assessed by forced vital capacity. Depending on the sleep metric, anxiety mediated 18-39% of the effect of sleep disturbance on dyspnoea, while muscle weakness mediated 27-41% of this effect., Interpretation: Sleep disturbance following hospital admission for COVID-19 is associated with dyspnoea, anxiety, and muscle weakness. Due to the association with multiple symptoms, targeting sleep disturbance might be beneficial in treating the post-COVID-19 condition., Funding: UK Research and Innovation, National Institute for Health Research, and Engineering and Physical Sciences Research Council., Competing Interests: Declaration of interests IDS declares a statistical editor honoraria role with Thorax. TP declares support from the National Institute for Health Research (NIHR) Leicester Biomedical Research Centre (BRC) to complete the work. ALH declares an editor-in-chief role for Computer Physics Communications. RA declares speaker fees and travel support from Boehringer Ingelheim. CEB declares their institute was awarded a grant from the UK Research and Innovation (UKRI)/NIHR and institutional support from NIHR Nottingham BRC to complete this work; the author reports grants from Nottingham Hospitals Charity and Nottingham University Hospitals Research and Innovation Department. TC declares support from the NIHR South London and Maudsley NHS Foundation Trust, King's College London BRC to complete the work; the author reports grants from Guy's and St Thomas' Charity, NIHR, and UKRI; the author has published self-help books on chronic fatigue for which she receives royalties; the author has received ad-hoc payments for workshops carried out in long-term conditions; the author declares travel and accommodation support; the author is part of the scientific committee of the British Association for Behavioural and Cognitive Psychotherapies (BABCP) and she is on the expert advisory panel for COVID-19 Rapid Guidelines. JDC declares grants from AstraZeneca, Novartis, Boehringer Ingelheim, Genentech, Gilead Sciences, Insmed, GlaxoSmithKline, and Grifols; the author reports consulting fees from AstraZeneca, Insmed, Boehringer Ingelheim, Janssen, Antabio, Chiesi, Novartis, Pfizer, Zambon, GlaxoSmithKline, and Grifols. GD declares support from the NIHR Imperial BRC, Royal Brompton and Harefield NGS Foundation Trust, Royal Brompton & Harefield Hospitals Charity, Imperial College Healthcare NHS Trust, and the Medical Research Council (MRC) to complete this work; the author reports grants from Genentech, AstraZeneca, British Lung Foundation (BLF) Early Cohort, GlaxoSmithKline, Novartis, Chiesi, and Boehringer Ingelheim; the author has a published chapter in a textbook for which he receives payment; the author declares a role in the advisory boards for AstraZeneca and Novartis and as honorarium as deputy editor of the American Journal of Respiratory and Critical Care Medicine (AJRCCM). L-PH declares grants from NIHR Oxford BRC. MGJ declares grants from the Royal Society, MRC, BLF, Boehringer Ingelheim, and the Asthma, Allergy and Inflammatory Research Charity. BR declares support from the British Heart Foundation (BHF) Oxford Centre of Research Excellence (CRE) to complete this work. SLR-J declares support for her institute from UKRI to complete the work; the author reports grants from UKRI, The European and Developing Countries Clinical Trials Partnership (EDCTP), MRC, Rosetrees Trust, and the Global Challenges Research Fund (GCRF); the author reports an honorarium for chapter contribution from the Federation of European Academies of Medicine; the author is Data and Safety Monitoring Board (DSMB) Chair for a Bexsero trial funded by Wellcome Trust; the author declares an editor role for AIDS journal. AVR declares support from NIHR Leicester BRC to complete the work. MS declares support for his institute from MRC/Department of Health and Social Care (DHSC) to complete the work. ASi declares support for her institute from UKRI/NIHR to complete the work. DGW declares an advanced Fellowship grant from NIHR; the author receives an honorarium from bioMérieux to present. TY declares support from the NIHR Leicester BRC to complete the work. RGJ declares grants from AstraZeneca, Biogen, Galecto, GlaxoSmithKline, Nordic Biosciences, RedX, Pliant; the author received consulting fees from AstraZeneca, Brainomix, Bristol Myers Squibb, Chiesi, Cohbar, Daewoong, GlaxoSmithKline, Veracyte, Resolution Therapeutics, and Pliant; the author has received payments from Boehringer Ingelheim, Chiesi, Roche, patientMpower, and AstraZeneca; the author was paid for expert testimony by Pinsent Masons LLP; the author has participated on a DSMB for Boehringer Ingelheim, Galapagos, and Vicore; the author has held a leadership role at NuMedii and is President of Action for Pulmonary Fibrosis. SJS declares grants from NIHR, Wellcome Doctoral Training Programme (DTP), the Human Tissue Authority, NIHR DHSC/UKRI COVID-19 Rapid Response Initiative, NIHR Global Research Group, Actegy Limited, and as an NIHR Senior Investigator; the author has presented for GlaxoSmithKline, Ministry of Justice, CIPLA, and Sherbourne Gibbs; the author is on the National Institute for Health and Care Excellence (NICE) Expert Advisor Panel for Long COVID and was on the Wales Long COVID Advisory Board; the author is the American Thoracic Society (ATS) Pulmonary Rehabilitation Assembly Chair, Clinical Lead Royal Society of Physicians (RSP) Pulmonary Rehabilitation Accreditation Scheme, and Clinical Lead Nation Asthma and COPD Audit Programme (NACAP) for Pulmonary Rehabilitation. WD-CM declares grants for his institution from NIHR, National Health Service (NHS) Accelerated Access Collaborative, and BLF; the author is the honorary President of the Association for Respiratory Technology and Physiology but receives no payment. CEBr declares support from UKRI/DHSC and NIHR Leicester BRC to complete the work; the author reports grants from GlaxoSmithKline, AstraZeneca, Sanofi, CI, Chiesi, Novartis, Roche, Genentech, Mologic, and 4DPharma; the author received consulting fees paid to his institution from GlaxoSmithKline, AstraZeneca, Sanofi, BI, Chiesi, Novartis, Roche, Genentech, Mologic, 4DPharma, and TEVA. LVW declares support from UKRI, GlaxoSmithKline/Asthma + Lung UK, and NIHR to complete this work; the author receives grants from Orion Pharma, GlaxoSmithKline, Genentech, and AstraZeneca; the author received consulting fees paid to her institution from Galapagos and Boehringer Ingelheim; the author received support for attending a meeting from Genentech. JCP received consulting fees from Istesso and The Limbic; the author participated on a DSMB for Vicore. AART declares a fellowship grant from BHF and a grant from NIHR to his institution; the author received an honorarium for lectures from Janssen-Cilag Ltd; the author received support for attending meetings from Janssen-Cilag Ltd. AH declares support from UKRI, NIHR, and NIHR Manchester BRC to complete the work; the author is Chair NIHR Translational Research Collaboration (unpaid). PLM declares a grant for his institution from AstraZeneca; the author received consulting fees from Hoffmann-La Roche, Boehringer Ingelheim, AstraZeneca, Trevi, and Qureight; the author received speaker fees from Boehringer Ingelheim and Hoffmann-La Roche. RAE declares support from UKRI/MRC to complete the work; the author reports a grant from NIHR/Wolfson Foundation; the author received consulting fees from AstraZeneca for Long COVID; the author received a speaker fee from Boehringer Ingelheim for a lecture on Long COVID; the author received support to attend BTS conference virtually from Chiesi; the author is the European Respiratory Society Group 01.02 Pulmonary Rehabilitation Secretary (unpaid). JFB declares support to his institute from an MRC Transition Fellowship, Asthma + Lung UK, NIHR Manchester BRC, and UKRI; the author reports grants paid to his institution from the Small Business Research Initiative Home Spirometer and the National Institute of Academic Anaesthesia; the author has received support for attending meetings from TEVA and Therakos; the author is a committee member of the Royal Society of Medicine (RSM). All other authors declare no competing interests., (Copyright © 2023 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Background: Prostate cancer is highly heritable, with >250 common variants associated in genome-wide association studies. It commonly presents with non-specific lower urinary tract symptoms that are frequently associated with benign conditions., Methods: Cohort study using UK Biobank data linked to primary care records. Participants were men with a record showing a general practice consultation for a lower urinary tract symptom. The outcome measure was prostate cancer diagnosis within 2 years of consultation. The predictor was a genetic risk score of 269 genetic variants for prostate cancer., Results: A genetic risk score (GRS) is associated with prostate cancer in symptomatic men (OR per SD increase = 2.12 [1.86-2.41] P = 3.5e-30). An integrated risk model including age and GRS applied to symptomatic men predicted prostate cancer (AUC 0.768 [0.739-0.796]). Prostate cancer incidence was 8.1% (6.7-9.7) in the highest risk quintile. In the lowest quintile, prostate cancer incidence was <1%., Conclusions: This study is the first to apply GRS in primary care to improve the triage of symptomatic patients. Men with the lowest genetic risk of developing prostate cancer could safely avoid invasive investigation, whilst those identified with the greatest risk could be fast-tracked for further investigation. These results show that a GRS has potential application to improve the diagnostic pathway of symptomatic patients in primary care., (© 2022. The Author(s).)

Purpose: The study aimed to systematically ascertain male sex chromosome abnormalities, 47,XXY (Klinefelter syndrome [KS]) and 47,XYY, and characterize their risks of adverse health outcomes., Methods: We analyzed genotyping array or exome sequence data in 207,067 men of European ancestry aged 40 to 70 years from the UK Biobank and related these to extensive routine health record data., Results: Only 49 of 213 (23%) of men whom we identified with KS and only 1 of 143 (0.7%) with 47,XYY had a diagnosis of abnormal karyotype on their medical records or self-report. We observed expected associations for KS with reproductive dysfunction (late puberty: risk ratio [RR] = 2.7; childlessness: RR = 4.2; testosterone concentration: RR = -3.8 nmol/L, all P < 2 × 10 -8 ), whereas XYY men appeared to have normal reproductive function. Despite this difference, we identified several higher disease risks shared across both KS and 47,XYY, including type 2 diabetes (RR = 3.0 and 2.6, respectively), venous thrombosis (RR = 6.4 and 7.4, respectively), pulmonary embolism (RR = 3.3 and 3.7, respectively), and chronic obstructive pulmonary disease (RR = 4.4 and 4.6, respectively) (all P < 7 × 10 -6 )., Conclusion: KS and 47,XYY were mostly unrecognized but conferred substantially higher risks for metabolic, vascular, and respiratory diseases, which were only partially explained by higher levels of body mass index, deprivation, and smoking., Competing Interests: Conflict of Interest The authors declare no conflicts of interest., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

We aimed to obtain reliable reference charts for sleep duration, estimate the prevalence of sleep complaints across the lifespan and identify risk indicators of poor sleep. Studies were identified through systematic literature search in Embase, Medline and Web of Science (9 August 2019) and through personal contacts. Eligible studies had to be published between 2000 and 2017 with data on sleep assessed with questionnaires including ≥100 participants from the general population. We assembled individual participant data from 200,358 people (aged 1-100 years, 55% female) from 36 studies from the Netherlands, 471,759 people (40-69 years, 55.5% female) from the United Kingdom and 409,617 people (≥18 years, 55.8% female) from the United States. One in four people slept less than age-specific recommendations, but only 5.8% slept outside of the 'acceptable' sleep duration. Among teenagers, 51.5% reported total sleep times (TST) of less than the recommended 8-10 h and 18% report daytime sleepiness. In adults (≥18 years), poor sleep quality (13.3%) and insomnia symptoms (9.6-19.4%) were more prevalent than short sleep duration (6.5% with TST < 6 h). Insomnia symptoms were most frequent in people spending ≥9 h in bed, whereas poor sleep quality was more frequent in those spending <6 h in bed. TST was similar across countries, but insomnia symptoms were 1.5-2.9 times higher in the United States. Women (≥41 years) reported sleeping shorter times or slightly less efficiently than men, whereas with actigraphy they were estimated to sleep longer and more efficiently than man. This study provides age- and sex-specific population reference charts for sleep duration and efficiency which can help guide personalized advice on sleep length and preventive practices.

Raised albumin-creatinine ratio (ACR) is an indicator of microvascular damage and renal disease. We aimed to identify genetic variants associated with raised ACR and study the implications of carrying multiple ACR-raising alleles with metabolic and vascular-related disease. We performed a genome-wide association study of ACR using 437 027 individuals from the UK Biobank in the discovery phase, 54 527 more than previous studies, and followed up our findings in independent studies. We identified 62 independent associations with ACR across 56 loci (P < 5 × 10-8), of which 20 were not previously reported. Pathway analyses and the identification of 20 of the 62 variants (at r2 > 0.8) coinciding with signals for at least 16 related metabolic and vascular traits, suggested multiple pathways leading to raised ACR levels. After excluding variants at the CUBN locus, known to alter ACR via effects on renal absorption, an ACR genetic risk score was associated with a higher risk of hypertension, and less strongly, type 2 diabetes and stroke. For some rare genotype combinations at the CUBN locus, most individuals had ACR levels above the microalbuminuria clinical threshold. Contrary to our hypothesis, individuals carrying more CUBN ACR-raising alleles, and above the clinical threshold, had a higher frequency of vascular disease. The CUBN allele effects on ACR were twice as strong in people with diabetes-a result robust to an optimization-algorithm approach to simulating interactions, validating previously reported gene-diabetes interactions (P ≤ 4 × 10-5). In conclusion, a variety of genetic mechanisms and traits contribute to variation in ACR., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background and Aims: The causes of microscopic colitis are currently poorly understood. Previous reports have found clinical associations with coeliac disease and genetic associations at the human leukocyte antigen [HLA] locus on the ancestral 8.1 haplotype. We investigated pharmacological and genetic factors associated with microscopic colitis in the UK Biobank., Methods: In total, 483 European UK Biobank participants were identified by ICD10 coding, and a genome-wide association study was performed using BOLT-LMM, with a sensitivity analysis performed excluding potential confounders. The HLA*IMP:02 algorithm was used to estimate allele frequency at 11 classical HLA genes, and downstream analysis was performed using FUMA. Genetic overlap with inflammatory bowel disease [Crohn's disease and ulcerative colitis] was investigated using genetic risk scores., Results: We found significant phenotypic associations with smoking status, coeliac disease and the use of proton-pump inhibitors but not with other commonly reported pharmacological risk factors. Using the largest sample size to date, we confirmed a recently reported association with the MHC Ancestral 8.1 Haplotype. Downstream analysis suggests association with digestive tract morphogenesis. By calculating genetic risk scores, we also report suggestive evidence of shared genetic risk with Crohn's disease, but not with ulcerative colitis., Conclusions: This report confirms the role of genetic determinants in the HLA in the pathogenesis of microscopic colitis. The genetic overlap with Crohn's disease suggests a common underlying mechanism of disease., (© European Crohn’s and Colitis Organisation (ECCO) 2019.)

Purpose: Many women with X chromosome aneuploidy undergo lifetime clinical monitoring for possible complications. However, ascertainment of cases in the clinic may mean that the penetrance has been overestimated., Methods: We characterized the prevalence and phenotypic consequences of X chromosome aneuploidy in a population of 244,848 women over 40 years of age from UK Biobank, using single-nucleotide polymorphism (SNP) array data., Results: We detected 30 women with 45,X; 186 with mosaic 45,X/46,XX; and 110 with 47,XXX. The prevalence of nonmosaic 45,X (12/100,000) and 47,XXX (45/100,000) was lower than expected, but was higher for mosaic 45,X/46,XX (76/100,000). The characteristics of women with 45,X were consistent with the characteristics of a clinically recognized Turner syndrome phenotype, including short stature and primary amenorrhea. In contrast, women with mosaic 45,X/46,XX were less short, had a normal reproductive lifespan and birth rate, and no reported cardiovascular complications. The phenotype of women with 47,XXX included taller stature (5.3 cm; SD = 5.52 cm; P = 5.8 × 10 -20 ) and earlier menopause age (5.12 years; SD = 5.1 years; P = 1.2 × 10 -14 )., Conclusion: Our results suggest that the clinical management of women with 45,X/46,XX mosaicism should be minimal, particularly those identified incidentally.

Sleep is an essential state of decreased activity and alertness but molecular factors regulating sleep duration remain unknown. Through genome-wide association analysis in 446,118 adults of European ancestry from the UK Biobank, we identify 78 loci for self-reported habitual sleep duration (p < 5 × 10 -8 ; 43 loci at p < 6 × 10 -9 ). Replication is observed for PAX8, VRK2, and FBXL12/UBL5/PIN1 loci in the CHARGE study (n = 47,180; p < 6.3 × 10 -4 ), and 55 signals show sign-concordant effects. The 78 loci further associate with accelerometer-derived sleep duration, daytime inactivity, sleep efficiency and number of sleep bouts in secondary analysis (n = 85,499). Loci are enriched for pathways including striatum and subpallium development, mechanosensory response, dopamine binding, synaptic neurotransmission and plasticity, among others. Genetic correlation indicates shared links with anthropometric, cognitive, metabolic, and psychiatric traits and two-sample Mendelian randomization highlights a bidirectional causal link with schizophrenia. This work provides insights into the genetic basis for inter-individual variation in sleep duration implicating multiple biological pathways.

More than 100,000 genetic variants are classified as disease causing in public databases. However, the true penetrance of many of these rare alleles is uncertain and might be over-estimated by clinical ascertainment. Here, we use data from 379,768 UK Biobank (UKB) participants of European ancestry to assess the pathogenicity and penetrance of putatively clinically important rare variants. Although rare variants are harder to genotype accurately than common variants, we were able to classify as high quality 1,244 of 4,585 (27%) putatively clinically relevant rare (MAF < 1%) variants genotyped on the UKB microarray. We defined as "clinically relevant" variants that were classified as either pathogenic or likely pathogenic in ClinVar or are in genes known to cause two specific monogenic diseases: maturity-onset diabetes of the young (MODY) and severe developmental disorders (DDs). We assessed the penetrance and pathogenicity of these high-quality variants by testing their association with 401 clinically relevant traits. 27 of the variants were associated with a UKB trait, and we were able to refine the penetrance estimate for some of the variants. For example, the HNF4A c.340C>T (p.Arg114Trp) (GenBank: NM&#95;175914.4) variant associated with diabetes is <10% penetrant by the time an individual is 40 years old. We also observed associations with relevant traits for heterozygous carriers of some rare recessive conditions, e.g., heterozygous carriers of the ERCC4 c.2395C>T (p.Arg799Trp) variant that causes Xeroderma pigmentosum were more susceptible to sunburn. Finally, we refute the previous disease association of RNF135 in developmental disorders. In conclusion, this study shows that very large population-based studies will help refine our understanding of the pathogenicity of rare genetic variants., (Copyright © 2019 The Authors. Published by Elsevier Inc. All rights reserved.)

Objective: Previously generated genetic risk scores (GRSs) for type 1 diabetes (T1D) have not captured all known information at non-HLA loci or, particularly, at HLA risk loci. We aimed to more completely incorporate HLA alleles, their interactions, and recently discovered non-HLA loci into an improved T1D GRS (termed the "T1D GRS2") to better discriminate diabetes subtypes and to predict T1D in newborn screening studies., Research Design and Methods: In 6,481 case and 9,247 control subjects from the Type 1 Diabetes Genetics Consortium, we analyzed variants associated with T1D both in the HLA region and across the genome. We modeled interactions between variants marking strongly associated HLA haplotypes and generated odds ratios to create the improved GRS, the T1D GRS2. We validated our findings in UK Biobank. We assessed the impact of the T1D GRS2 in newborn screening and diabetes classification and sought to provide a framework for comparison with previous scores., Results: The T1D GRS2 used 67 single nucleotide polymorphisms (SNPs) and accounted for interactions between 18 HLA DR-DQ haplotype combinations. The T1D GRS2 was highly discriminative for all T1D (area under the curve [AUC] 0.92; P < 0.0001 vs. older scores) and even more discriminative for early-onset T1D (AUC 0.96). In simulated newborn screening, the T1D GRS2 was nearly twice as efficient as HLA genotyping alone and 50% better than current genetic scores in general population T1D prediction., Conclusions: An improved T1D GRS, the T1D GRS2, is highly useful for classifying adult incident diabetes type and improving newborn screening. Given the cost-effectiveness of SNP genotyping, this approach has great clinical and research potential in T1D., (© 2019 by the American Diabetes Association.)

Being a morning person is a behavioural indicator of a person's underlying circadian rhythm. Using genome-wide data from 697,828 UK Biobank and 23andMe participants we increase the number of genetic loci associated with being a morning person from 24 to 351. Using data from 85,760 individuals with activity-monitor derived measures of sleep timing we find that the chronotype loci associate with sleep timing: the mean sleep timing of the 5% of individuals carrying the most morningness alleles is 25 min earlier than the 5% carrying the fewest. The loci are enriched for genes involved in circadian regulation, cAMP, glutamate and insulin signalling pathways, and those expressed in the retina, hindbrain, hypothalamus, and pituitary. Using Mendelian Randomisation, we show that being a morning person is causally associated with better mental health but does not affect BMI or risk of Type 2 diabetes. This study offers insights into circadian biology and its links to disease in humans.

Fibroblast growth factor 21 (FGF21) is a hormone that has insulin-sensitizing properties. Some trials of FGF21 analogs show weight loss and lipid-lowering effects. Recent studies have shown that a common allele in the FGF21 gene alters the balance of macronutrients consumed, but there was little evidence of an effect on metabolic traits. We studied a common FGF21 allele (A:rs838133) in 451,099 people from the UK Biobank study, aiming to use the human allele to inform potential adverse and beneficial effects of targeting FGF21. We replicated the association between the A allele and higher percentage carbohydrate intake. We then showed that this allele is more strongly associated with higher blood pressure and waist-hip ratio, despite an association with lower total body-fat percentage, than it is with BMI or type 2 diabetes. These human phenotypes of variation in the FGF21 gene will inform research into FGF21's mechanisms and therapeutic potential., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)