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We thank all EPIC participants and staff for their contribution to the study. We also thank staff from the EPIC-CVD coordinating centres for sample preparation and data handling. This research has been conducted using the UK Biobank Resource (application number 29916). Data on coronary artery disease have been contributed by CARDIoGRAMplusC4D investigators and have been downloaded from www.CARDIOGRAMPLUSC4D.ORG.I Sluijswas supported by a personal Dr. Dekker postdoctoral grant (2015T019) from the Netherlands Heart Foundation. NGF and FI acknowledge core Medical Research Council Epidemiology Unit support (MC_UU_12015/5) and NGF acknowledges NIHR Biomedical Research Centre Cambridge: Nutrition, Diet, and Lifestyle Research Theme (IS-BRC-1215-20014). The InterAct project was funded by the EU FP6 programme (grant number LSHM_CT_2006_037197) and provided the biomarker data in the sub-cohort that was used in the current study. These analyses were supported by Cancer Research UK (C8221/A19170). The coordination of EPIC is financially supported by the European Commission (DG-SANCO) and the International Agency for Research on Cancer. The national cohorts are supported by Danish Cancer Society (Denmark); German Cancer Aid, German Cancer Research Center (DKFZ), Federal Ministry of Education and Research (BMBF), Deutsche Krebshilfe, Deutsches Krebsforschungszentrum and Federal Ministry of Education and Research (Germany); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF), Statistics Netherlands (The Netherlands); Health Research Fund (FIS) PI13/00061 (EPIC-Granada) and PI13/01162 (EPIC-Murcia), Regional Governments of Andalucia, Asturias, Basque Country, Murcia and Navarra, ISCIII Health Research Funds RD12/0036/0018 (cofounded by FEDER funds/European Regional Development Fund ERDF) (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Skane and Vasterbotten (Sweden); Cancer Research UK (14136 to EPIC-Norfolk; C570/A16491 and C8221/A19170 for EPIC-Oxford), Medical Research Council (1000143 to EPIC-Norfolk, MR/M012190/1 to EPIC-Oxford) (UK). EPIC-CVD has been supported by the European Commission Framework Programme 7 (HEALTH-F2-2012-279233), the European Research Council (268834), the UK Medical Research Council (MR/L003120/1), the British Heart Foundation (RG13/13/30194 and RG/18/13/33946) and the National Institute for Health Research (Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust). The MEGASTROKE project received funding from sources specified at http://www.megastroke.org/acknowledgments.html. L.E.T.V.analysed the data and drafted the manuscript. L. E. T. V., I. S. and Y. T. vdS. had access to all data for this study. L. E. T. V., I. S., Y. T. vdS., S. B., N. G. F., H. F., F. I., T. K. N., F. R., E. W., K. A., C. D., A. P. C., M. B. S., T. Y. N. T. and A. S. B. contributed to study conception, design and interpretation of data. All authors contributed to critical revision of the manuscript and approval of version to be published., Higher milk intake has been associated with a lower stroke risk, but not with risk of CHD. Residual confounding or reverse causation cannot be excluded. Therefore, we estimated the causal association of milk consumption with stroke and CHD risk through instrumental variable (IV) and gene-outcome analyses. IV analysis included 29 328 participants (4611 stroke; 9828 CHD) of the European Prospective Investigation into Cancer and Nutrition (EPIC)-CVD (eight European countries) and European Prospective Investigation into Cancer and Nutrition-Netherlands (EPIC-NL) case-cohort studies. rs4988235, a lactase persistence (LP) SNP which enables digestion of lactose in adulthood was used as genetic instrument. Intake of milk was first regressed on rs4988235 in a linear regression model. Next, associations of genetically predicted milk consumption with stroke and CHD were estimated using Prentice-weighted Cox regression. Gene-outcome analysis included 777 024 participants (50 804 cases) from MEGASTROKE (including EPIC-CVD), UK Biobank and EPIC-NL for stroke, and 483 966 participants (61 612 cases) from CARDIoGRAM, UK Biobank, EPIC-CVD and EPIC-NL for CHD. In IV analyses, each additional LP allele was associated with a higher intake of milk in EPIC-CVD (beta = 13 center dot 7 g/d; 95 % CI 8 center dot 4, 19 center dot 1) and EPIC-NL (36 center dot 8 g/d; 95 % CI 20 center dot 0, 53 center dot 5). Genetically predicted milk intake was not associated with stroke (HR per 25 g/d 1 center dot 05; 95 % CI 0 center dot 94, 1 center dot 16) or CHD (1 center dot 02; 95 % CI 0 center dot 96, 1 center dot 08). In gene-outcome analyses, there was no association of rs4988235 with risk of stroke (OR 1 center dot 02; 95 % CI 0 center dot 99, 1 center dot 05) or CHD (OR 0 center dot 99; 95 % CI 0 center dot 95, 1 center dot 03). Current Mendelian randomisation analysis does not provide evidence for a causal inverse relationship between milk consumption and stroke or CHD risk., Netherlands Heart Foundation 2015T019, UK Research & Innovation (UKRI) Medical Research Council UK (MRC), European Commission MC_UU_12015/5, NIHR Biomedical Research Centre Cambridge: Nutrition, Diet, and Lifestyle Research Theme IS-BRC-1215-20014, European Commission LSHM_CT_2006_037197, Cancer Research UK C8221/A19170, European Commission European Commission Joint Research Centre, International Agency for Research on Cancer, Danish Cancer Society, Deutsche Krebshilfe German Cancer Research Center (DKFZ) (Germany), Federal Ministry of Education & Research (BMBF), Deutsche Krebshilfe Deutsches Krebsforschungszentrum (Germany), Fondazione AIRC per la ricerca sul cancro Consiglio Nazionale delle Ricerche (CNR), Netherlands Government Netherlands Government, World Cancer Research Fund International (WCRF), Netherlands Government, Instituto de Salud Carlos III PI13/00061 PI13/01162, Junta de Andalucia Regional Government of Asturias (Spain) Regional Government of Basque Country (Spain) Regional Government of Murcia (Spain) Regional Government of Navarra (Spain), ISCIII Health Research Funds (FEDER funds/European Regional Development Fund ERDF) (Spain) RD12/0036/0018, Swedish Cancer Society Swedish Research Council County Council of Skane (Sweden) County Council of Vasterbotten (Sweden), European Commission Framework Programme 7 HEALTH-F2-2012-279233 European Research Council (ERC) European Commission 268834, UK Research & Innovation (UKRI) Medical Research Council UK (MRC) MR/L003120/1 British Heart Foundation RG13/13/30194 RG/18/13/33946 National Institute for Health Research (Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust) UK Research & Innovation (UKRI) Medical Research Council UK (MRC) 1000143 MR/M012190/1 Cancer Research UK C8221/A19170 14136 C570/A16491

We present the Polygenic Score (PGS) Catalog ( https://www.PGSCatalog.org ), an open resource of published scores (including variants, alleles and weights) and consistently curated metadata required for reproducibility and independent applications. The PGS Catalog has capabilities for user deposition, expert curation and programmatic access, thus providing the community with a platform for PGS dissemination, research and translation.

In cross-platform analyses of 174 metabolites, we identify 499 associations (P

OBJECTIVE Higher plasma vitamin C levels are associated with lower type 2 diabetes risk, but whether this association is causal is uncertain. To investigate this, we studied the association of genetically predicted plasma vitamin C with type 2 diabetes. RESEARCH DESIGN AND METHODS We conducted genome-wide association studies of plasma vitamin C among 52,018 individuals of European ancestry to discover novel genetic variants. We performed Mendelian randomization analyses to estimate the association of genetically predicted differences in plasma vitamin C with type 2 diabetes in up to 80,983 case participants and 842,909 noncase participants. We compared this estimate with the observational association between plasma vitamin C and incident type 2 diabetes, including 8,133 case participants and 11,073 noncase participants. RESULTS We identified 11 genomic regions associated with plasma vitamin C (P < 5 × 10−8), with the strongest signal at SLC23A1, and 10 novel genetic loci including SLC23A3, CHPT1, BCAS3, SNRPF, RER1, MAF, GSTA5, RGS14, AKT1, and FADS1. Plasma vitamin C was inversely associated with type 2 diabetes (hazard ratio per SD 0.88; 95% CI 0.82, 0.94), but there was no association between genetically predicted plasma vitamin C (excluding FADS1 variant due to its apparent pleiotropic effect) and type 2 diabetes (1.03; 95% CI 0.96, 1.10). CONCLUSIONS These findings indicate discordance between biochemically measured and genetically predicted plasma vitamin C levels in the association with type 2 diabetes among European populations. The null Mendelian randomization findings provide no strong evidence to suggest the use of vitamin C supplementation for type 2 diabetes prevention.

The human proteome is a major source of therapeutic targets. Recent genetic association analyses of the plasma proteome enable systematic evaluation of the causal consequences of variation in plasma protein levels. Here, we estimated the effects of 1002 proteins on 225 phenotypes using two-sample Mendelian randomization (MR) and colocalization. Of 413 associations supported by evidence from MR, 130 (31.5%) were not supported by results of colocalization analyses, suggesting that genetic confounding due to linkage disequilibrium (LD) is widespread in naive phenome-wide association studies of proteins. Combining MR and colocalization evidence in cis-only analyses, we identified 111 putatively causal effects between 65 proteins and 52 disease-related phenotypes (www.epigraphdb.org/pqtl/). Evaluation of data from historic drug development programmes showed that target-indication pairs with MR and colocalization support were more likely to be approved, evidencing the value of our approach in identifying and prioritising potential therapeutic targets.

BACKGROUND: Genome-wide polygenic scores (GPS) integrate information from many common DNA variants into a single number. Because rates of coronary artery disease (CAD) are substantially higher among South Asians, a GPS to identify high-risk individuals may be particularly useful in this population. OBJECTIVES: This analysis used summary statistics from a prior genome-wide association study to derive a new GPSCAD for South Asians. METHODS: This GPSCAD was validated in 7,244 South Asian UK Biobank participants and tested in 491 individuals from a case-control study in Bangladesh. Next, a static ancestry and GPSCAD reference distribution was built using whole-genome sequencing from 1,522 Indian individuals, and a framework was tested for projecting individuals onto this static ancestry and GPSCAD reference distribution using 1,800 CAD cases and 1,163 control subjects newly recruited in India. RESULTS: The GPSCAD, containing 6,630,150 common DNA variants, had an odds ratio (OR) per SD of 1.58 in South Asian UK Biobank participants and 1.60 in the Bangladeshi study (p

Most loci identified by GWASs have been found in populations of European ancestry (EUR). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EUR individuals, we identified 5,552 trait-variant associations at p < 5 × 10-9, including 71 novel associations not found in EUR populations. We also identified 28 additional novel variants in ancestry-specific, non-EUR meta-analyses, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL-7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EUR-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations and compared genetic architecture and the effect of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.

Iron is essential for many biological functions and iron deficiency and overload have major health implications. We performed a meta-analysis of three genome-wide association studies from Iceland, the UK and Denmark of blood levels of ferritin (N = 246,139), total iron binding capacity (N = 135,430), iron (N = 163,511) and transferrin saturation (N = 131,471). We found 62 independent sequence variants associating with iron homeostasis parameters at 56 loci, including 46 novel loci. Variants at DUOX2, F5, SLC11A2 and TMPRSS6 associate with iron deficiency anemia, while variants at TF, HFE, TFR2 and TMPRSS6 associate with iron overload. A HBS1L-MYB intergenic region variant associates both with increased risk of iron overload and reduced risk of iron deficiency anemia. The DUOX2 missense variant is present in 14% of the population, associates with all iron homeostasis biomarkers, and increases the risk of iron deficiency anemia by 29%. The associations implicate proteins contributing to the main physiological processes involved in iron homeostasis: iron sensing and storage, inflammation, absorption of iron from the gut, iron recycling, erythropoiesis and bleeding/menstruation., Bell et al. report 46 new loci associated with biomarkers of iron homeostasis, including ferritin levels, iron binding capacity, and iron saturation, in the Icelandic, Danish and UK populations. The associated loci point to new iron-regulating proteins and important genetic differences between men and women.

EPIC-CVD was supported by the European Commission Framework Programme 7 (HEALTH-F2-2012-279233), and the European Research Council (268834). The coordinating center was supported by core funding from the: United Kingdom MRC (G0800270; MR/L003120/1), British Heart Foundation (BHF) (SP/09/002; RG13/13/30194; RG/18/13/33946), and National Institute for Health Research (NIHR) Cambridge Biomedical Research Centre (BRC) (BRC-1215-20014).* The establishment of the study subcohort was supported by the European Union Sixth Framework Programme (grant LSHM_CT_ 2006_037197 to the InterAct project) and the MRC Epidemiology Unit (grant MC_UU_00006/1). The coordination of EPIC is financially supported by International Agency for Research on Cancer and also by the Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, which has additional infrastructure support provided by NIHR Imperial BRC. The national cohorts are supported by: Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Generale de l'Education Nationale, Institut National de la Sante et de la Recherche Medicale (France); German Cancer Aid, German Cancer Research Center, German Institute of Human Nutrition Potsdam-Rehbruecke, Federal Ministry of Education and Research (Germany); Associazione Italiana per la Ricerca sul Cancro--AIRC--Italy, Compagnia di SanPaolo and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports, Netherlands Cancer Registry, LK Research Funds, Dutch Prevention Funds, Zorg Onderzoek Nederland, World Cancer Research Fund, Statistics Netherlands (the Netherlands); Health Research Fund-Instituto de Salud Carlos III, Regional Governments of Andalucia, Asturias, Basque Country, Murcia and Navarra, and the Catalan Institute of Oncology (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Skane and Vasterbotten (Sweden); Cancer Research UK (14136 to EPIC-Norfolk; C8221/A29017 to EPIC-Oxford), MRC (1000143 to EPIC-Norfolk; MR/M012190/1 to EPIC-Oxford) (United Kingdom). EPIC-Greece was supported by the Hellenic Health Foundation (Greece). M.S., N.J.W., N.G.F., and F.I. acknowledge support from MRC Epidemiology Unit (MC_UU_ 00006/1 and MC_UU_00006/3). N.J.W. and N.G.F. acknowledge support from NIHR* Cambridge BRC: Nutrition, Diet, and Lifestyle Research Theme (IS-BRC-1215--20014) and NGF is a NIHR Senior Investigator Award holder. M.S. was also supported by BHF for part of this work while working in the BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. R. Z.-R. thanks the "Miguel Servet" program (CP15/00100) from the Institute of Health Carlos III (co-funded by the European Social Fund--European Social Fund Investing in Your Future). A.W. was supported by a BHF-Turing Cardiovascular Data Science Award and by the European Commission-Innovative Medicines Initiative (BigData@Heart).R.C.was funded by a MRC-Newton project grant to study genetic risk factors of cardiovascular disease among Southeast Asian people and the Academy of Sciences Malaysia (grant no. MR/P013880/1) and a United Kingdom Research and Innovation-Global Challenges Research Fund Project Grant to study risk factors of noncommunicable diseases in Bangladesh. J.D. holds a BHF Professorship and a NIHR Senior Investigator Award. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. Where authors are identified as personnel of the International Agency for Research on Cancer/World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy, or views of the International Agency for Research on Cancer/World Health Organization. The funders of the study had no role in study design, data collection, analysis, data interpretation, or writing of the article, or in the decision to submit for publication. M.S. had full access to all the data in the study, and M.S. and N.G.F. had final responsibility for the decision to submit for publication., BACKGROUND: There is controversy about associations between total dietary fatty acids, their classes (saturated fatty acids [SFAs], monounsaturated fatty acids, and polyunsaturated fatty acids), and risk of coronary heart disease (CHD). Specifically, the relevance of food sources of SFAs to CHD associations is uncertain. METHODS AND RESULTS: We conducted a case-cohort study involving 10 529 incident CHD cases and a random subcohort of 16 730 adults selected from a cohort of 385 747 participants in 9 countries of the EPIC (European Prospective Investigation into Cancer and Nutrition) study. We estimated multivariable adjusted country-specific hazard ratios (HRs) and 95% CIs per 5% of energy intake from dietary fatty acids, with and without isocaloric macronutrient substitutions, using Prentice-weighted Cox regression models and pooled results using random-effects meta-analysis. We found no evidence for associations of the consumption of total or fatty acid classes with CHD, regardless of macronutrient substitutions. In analyses considering food sources, CHD incidence was lower per 1% higher energy intake of SFAs from yogurt (HR, 0.93 [95% CI, 0.88–0.99]), cheese (HR, 0.98 [95% CI, 0.96–1.00]), and fish (HR, 0.87 [95% CI, 0.75–1.00]), but higher for SFAs from red meat (HR, 1.07 [95% CI, 1.02–1.12]) and butter (HR, 1.02 [95% CI, 1.00–1.04]). CONCLUSIONS: This observational study found no strong associations of total fatty acids, SFAs, monounsaturated fatty acids, and polyunsaturated fatty acids, with incident CHD. By contrast, we found associations of SFAs with CHD in opposite directions dependent on the food source. These findings should be further confirmed, but support public health recommendations to consider food sources alongside the macronutrients they contain, and suggest the importance of the overall food matrix., European Commission Framework Programme 7 HEALTH-F2-2012-279233, European Research Council (ERC), European Commission 268834, UK Research & Innovation (UKRI), Medical Research Council UK (MRC) G0800270 MR/L003120/1, British Heart Foundation SP/09/002 RG13/13/30194 RG/18/13/33946, National Institute for Health Research (NIHR) BRC-1215-20014, European Commission LSHM_CT_ 2006_037197, Medical Research Council UK (MRC) MC_UU_ 00006/1 MC_UU_00006/3, International Agency for Research on Cancer, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Danish Cancer Society, Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Generale de l'Education Nationale, Institut National de la Sante et de la Recherche Medicale (France), German Cancer Aid, German Cancer Research Center, German Institute of Human Nutrition Potsdam, Rehbruecke, Federal Ministry of Education and Research (Germany), Fondazione AIRC per la ricerca sul cancro, Compagnia di San Paolo, Dutch Ministry of Public Health, Welfare and Sports, Netherlands Cancer Registry, LK Research Funds, Dutch Prevention Funds, Zorg Onderzoek Nederland, World Cancer Research Fund International (WCRF), Netherlands Government, Instituto de Salud Carlos III, Junta de Andalucia, Regional Government of Asturias, Basque Government, Regional Government of Murcia, Regional Government of Navarra, Catalan Institute of Oncology (Spain), Swedish Cancer Society, County Council of Skane (Sweden), County Council of Vasterbotten (Sweden), Cancer Research UK 14136 C8221/A29017, Medical Research Council UK (MRC) 1000143 MR/M012190/1, Hellenic Health Foundation (Greece), NIHR* Cambridge BRC: Nutrition, Diet, and Lifestyle Research Theme IS-BRC-1215-20014, British Heart Foundation, Institute of Health Carlos III (European Social Fund-European Social Fund Investing in Your Future) CP15/00100, BHF-Turing Cardiovascular Data Science Award, European Commission-Innovative Medicines Initiative (BigData@Heart), MRC-Newton project grant MR/P013880/1, United Kingdom Research and Innovation-Global Challenges Research Fund, NIHR Senior Investigator Award

ObjectiveTo determine the contribution of common genetic variants to risk of early onset ischemic stroke (IS).MethodsWe performed a meta-analysis of genome-wide association studies of early onset IS, ages 18-59, using individual level data or summary statistics in 16,927 cases and 576,353 non-stroke controls from 48 different studies across North America, Europe, and Asia. We further compared effect sizes at our most genome-wide significant loci between early and late onset IS and compared polygenic risk scores for venous thromboembolism between early versus later onset IS.ResultsWe observed an association between early onset IS and ABO, a known stroke locus. The effect size of the peak ABO SNP, rs8176685, was significantly larger in early compared to late onset IS (OR 1.17 (95% C.I.: 1.11-1.22) vs 1.05 (0.99-1.12); p for interaction = 0.008). Analysis of genetically determined ABO blood groups revealed that early onset IS cases were more likely to have blood group A and less likely to have blood group O compared to both non-stroke controls and to late onset IS cases. Using polygenic risk scores, we observed that greater genetic risk for venous thromboembolism, another prothrombotic condition, was more strongly associated with early, compared to late, onset IS (p=0.008).ConclusionThe ABO locus, genetically predicted blood group A, and higher genetic propensity for venous thrombosis are more strongly associated with early onset IS, compared with late onset IS, supporting a stronger role of prothrombotic factors in early onset IS.

Background Genetic, lifestyle, and environmental factors can lead to perturbations in circulating lipid levels and increase the risk of cardiovascular and metabolic diseases. However, how changes in individual lipid species contribute to disease risk is often unclear. Moreover, little is known about the role of lipids on cardiovascular disease in Pakistan, a population historically underrepresented in cardiovascular studies. Methods We characterised the genetic architecture of the human blood lipidome in 5662 hospital controls from the Pakistan Risk of Myocardial Infarction Study (PROMIS) and 13,814 healthy British blood donors from the INTERVAL study. We applied a candidate causal gene prioritisation tool to link the genetic variants associated with each lipid to the most likely causal genes, and Gaussian Graphical Modelling network analysis to identify and illustrate relationships between lipids and genetic loci. Results We identified 253 genetic associations with 181 lipids measured using direct infusion high-resolution mass spectrometry in PROMIS, and 502 genetic associations with 244 lipids in INTERVAL. Our analyses revealed new biological insights at genetic loci associated with cardiometabolic diseases, including novel lipid associations at the LPL, MBOAT7, LIPC, APOE-C1-C2-C4, SGPP1, and SPTLC3 loci. Conclusions Our findings, generated using a distinctive lipidomics platform in an understudied South Asian population, strengthen and expand the knowledge base of the genetic determinants of lipids and their association with cardiometabolic disease-related loci.

We report severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike ΔH69/V70 in multiple independent lineages, often occurring after acquisition of receptor binding motif replacements such as N439K and Y453F, known to increase binding affinity to the ACE2 receptor and confer antibody escape. In vitro, we show that, although ΔH69/V70 itself is not an antibody evasion mechanism, it increases infectivity associated with enhanced incorporation of cleaved spike into virions. ΔH69/V70 is able to partially rescue infectivity of spike proteins that have acquired N439K and Y453F escape mutations by increased spike incorporation. In addition, replacement of the H69 and V70 residues in the Alpha variant B.1.1.7 spike (where ΔH69/V70 occurs naturally) impairs spike incorporation and entry efficiency of the B.1.1.7 spike pseudotyped virus. Alpha variant B.1.1.7 spike mediates faster kinetics of cell-cell fusion than wild-type Wuhan-1 D614G, dependent on ΔH69/V70. Therefore, as ΔH69/V70 compensates for immune escape mutations that impair infectivity, continued surveillance for deletions with functional effects is warranted., Graphical abstract, Meng et al. report that the SARS-CoV-2 spike ΔH69/V70 has arisen multiple times. The deletion increases entry efficiency associated with increased cleaved spike in virions and can compensate for loss of infectivity. The B.1.1.7 spike requires ΔH69/V70 for efficient cell entry and cell-cell fusion activity.

Background: The SARS-CoV-2 variant B.1.1.7 was first identified in December, 2020, in England. We aimed to investigate whether increases in the proportion of infections with this variant are associated with differences in symptoms or disease course, reinfection rates, or transmissibility. Methods: We did an ecological study to examine the association between the regional proportion of infections with the SARS-CoV-2 B.1.1.7 variant and reported symptoms, disease course, rates of reinfection, and transmissibility. Data on types and duration of symptoms were obtained from longitudinal reports from users of the COVID Symptom Study app who reported a positive test for COVID-19 between Sept 28 and Dec 27, 2020 (during which the prevalence of B.1.1.7 increased most notably in parts of the UK). From this dataset, we also estimated the frequency of possible reinfection, defined as the presence of two reported positive tests separated by more than 90 days with a period of reporting no symptoms for more than 7 days before the second positive test. The proportion of SARS-CoV-2 infections with the B.1.1.7 variant across the UK was estimated with use of genomic data from the COVID-19 Genomics UK Consortium and data from Public Health England on spike-gene target failure (a non-specific indicator of the B.1.1.7 variant) in community cases in England. We used linear regression to examine the association between reported symptoms and proportion of B.1.1.7. We assessed the Spearman correlation between the proportion of B.1.1.7 cases and number of reinfections over time, and between the number of positive tests and reinfections. We estimated incidence for B.1.1.7 and previous variants, and compared the effective reproduction number, R t, for the two incidence estimates. Findings: From Sept 28 to Dec 27, 2020, positive COVID-19 tests were reported by 36 920 COVID Symptom Study app users whose region was known and who reported as healthy on app sign-up. We found no changes in reported symptoms or disease duration associated with B.1.1.7. For the same period, possible reinfections were identified in 249 (0·7% [95% CI 0·6–0·8]) of 36 509 app users who reported a positive swab test before Oct 1, 2020, but there was no evidence that the frequency of reinfections was higher for the B.1.1.7 variant than for pre-existing variants. Reinfection occurrences were more positively correlated with the overall regional rise in cases (Spearman correlation 0·56–0·69 for South East, London, and East of England) than with the regional increase in the proportion of infections with the B.1.1.7 variant (Spearman correlation 0·38–0·56 in the same regions), suggesting B.1.1.7 does not substantially alter the risk of reinfection. We found a multiplicative increase in the R t of B.1.1.7 by a factor of 1·35 (95% CI 1·02–1·69) relative to pre-existing variants. However, R t fell below 1 during regional and national lockdowns, even in regions with high proportions of infections with the B.1.1.7 variant. Interpretation: The lack of change in symptoms identified in this study indicates that existing testing and surveillance infrastructure do not need to change specifically for the B.1.1.7 variant. In addition, given that there was no apparent increase in the reinfection rate, vaccines are likely to remain effective against the B.1.1.7 variant. Funding: Zoe Global, Department of Health (UK), Wellcome Trust, Engineering and Physical Sciences Research Council (UK), National Institute for Health Research (UK), Medical Research Council (UK), Alzheimer's Society.

Aims Genetic disposition and lifestyle factors are understood as independent components underlying the risk of multiple diseases. In this study, we aim to investigate the interplay between genetics, educational attainment—an important denominator of lifestyle—and coronary artery disease (CAD) risk. Methods and results Based on the effect sizes of 74 genetic variants associated with educational attainment, we calculated a ‘genetic education score’ in 13 080 cases and 14 471 controls and observed an inverse correlation between the score and risk of CAD [P = 1.52 × 10−8; odds ratio (OR) 0.79, 95% confidence interval (CI) 0.73–0.85 for the higher compared with the lowest score quintile]. We replicated in 146 514 individuals from UK Biobank (P = 1.85 × 10−6) and also found strong associations between the ‘genetic education score’ with ‘modifiable’ risk factors including smoking (P = 5.36 × 10−23), body mass index (BMI) (P = 1.66 × 10−30), and hypertension (P = 3.86 × 10−8). Interestingly, these associations were only modestly attenuated by adjustment for years spent in school. In contrast, a model adjusting for BMI and smoking abolished the association signal between the ‘genetic education score’ and CAD risk suggesting an intermediary role of these two risk factors. Mendelian randomization analyses performed with summary statistics from large genome-wide meta-analyses and sensitivity analysis using 1271 variants affecting educational attainment (OR 0.68 for the higher compared with the lowest score quintile; 95% CI 0.63–0.74; P = 3.99 × 10−21) further strengthened these findings. Conclusion Genetic variants known to affect educational attainment may have implications for a health-conscious lifestyle later in life and subsequently affect the risk of CAD.

Reduced lung function predicts mortality and is key to the diagnosis of chronic obstructive pulmonary disease (COPD). In a genome-wide association study in 400,102 individuals of European ancestry, we define 279 lung function signals, 139 of which are new. In combination, these variants strongly predict COPD in independent patient populations. Furthermore, the combined effect of these variants showed generalizability across smokers and never-smokers, and across ancestral groups. We highlight biological pathways, known and potential drug targets for COPD and, in phenome-wide association studies, autoimmune-related and other pleiotropic effects of lung function associated variants. This new genetic evidence has potential to improve future preventive and therapeutic strategies for COPD., Editorial summary: A genome-wide association study in over 400,000 individuals identifies 139 new signals for lung function. These variants can predict chronic obstructive pulmonary disease in independent, trans-ethnic cohorts.

Background: \ud Spontaneous coronary artery dissection (SCAD) is an increasingly recognized cause of acute coronary syndromes (ACS) afflicting predominantly younger to middle-aged women. Observational studies have reported a high prevalence of extracoronary vascular anomalies, especially fibromuscular dysplasia (FMD) and a low prevalence of coincidental cases of atherosclerosis. PHACTR1/EDN1 is a genetic risk locus for several vascular diseases, including FMD and coronary artery disease, with the putative causal noncoding variant at the rs9349379 locus acting as a potential enhancer for the endothelin-1 (EDN1) gene.\ud \ud Objectives: \ud This study sought to test the association between the rs9349379 genotype and SCAD.\ud \ud Methods: \ud Results from case control studies from France, United Kingdom, United States, and Australia were analyzed to test the association with SCAD risk, including age at first event, pregnancy-associated SCAD (P-SCAD), and recurrent SCAD.\ud \ud Results: \ud The previously reported risk allele for FMD (rs9349379-A) was associated with a higher risk of SCAD in all studies. In a meta-analysis of 1,055 SCAD patients and 7,190 controls, the odds ratio (OR) was 1.67 (95% confidence interval [CI]: 1.50 to 1.86) per copy of rs9349379-A. In a subset of 491 SCAD patients, the OR estimate was found to be higher for the association with SCAD in patients without FMD (OR: 1.89; 95% CI: 1.53 to 2.33) than in SCAD cases with FMD (OR: 1.60; 95% CI: 1.28 to 1.99). There was no effect of genotype on age at first event, P-SCAD, or recurrence.\ud \ud Conclusions: \ud The first genetic risk factor for SCAD was identified in the largest study conducted to date for this condition. This genetic link may contribute to the clinical overlap between SCAD and FMD.

A genetic predisposition to higher waist-to-hip ratio adjusted for BMI (WHRadjBMI), a measure of body fat distribution, associates with increased risk for type 2 diabetes. We conducted an exome-wide association study of coding variation in UK Biobank (405,569 individuals) to identify variants that lower WHRadjBMI and protect against type 2 diabetes. We identified four variants in the gene ACVR1C (encoding the activin receptor-like kinase 7 receptor expressed on adipocytes and pancreatic β-cells), which independently associated with reduced WHRadjBMI: Asn150His (-0.09 SD, P = 3.4 × 10-17), Ile195Thr (-0.15 SD, P = 1.0 × 10-9), Ile482Val (-0.019 SD, P = 1.6 × 10-5), and rs72927479 (-0.035 SD, P = 2.6 × 10-12). Carriers of these variants exhibited reduced percent abdominal fat in DEXA imaging. Pooling across all four variants, a 0.2 SD decrease in WHRadjBMI through ACVR1C was associated with a 30% lower risk of type 2 diabetes (odds ratio [OR] 0.70, 95% CI 0.63, 0.77; P = 5.6 × 10-13). In an analysis of exome sequences from 55,516 individuals, carriers of predicted damaging variants in ACVR1C were at 54% lower risk of type 2 diabetes (OR 0.46, 95% CI 0.27, 0.81; P = 0.006). These findings indicate that variants predicted to lead to loss of ACVR1C gene function influence body fat distribution and protect from type 2 diabetes. This work was funded by the National Institutes of Health (R01 HL127564 to S.K.), which had no involvement in the design and conduct of the study; the collection, analysis, and interpretation of the data; or the preparation, review, and approval of the manuscript. This project was also conducted using the Type 2 Diabetes Knowledge Portal resource which is funded by the Accelerating Medicines Partnership. REGICOR study was supported by the Spanish Ministry of Economy and Innovation through the Carlos III Health Institute (Red Investigación Cardiovascular RD12/0042, PI09/90506), European Funds for Development (ERDF-FEDER), and by the Catalan Research andTechnology Innovation Interdepartmental Commission (2014SGR240). Samples for the Leicester cohort were collected as part of projects funded by the British Heart Foundation (British Heart Foundation Family Heart Study, RG2000010; UK Aneurysm Growth Study, CS/14/2/30841) and the National Institute for Health Research (NIHR Leicester Cardiovascular Biomedical Research Unit Biomedical Research Informatics Centre for Cardiovascular Science, IS_BRU_0211_20033). NJS is supported by the British Heart Foundation and is a NIHR Senior Investigator. The Munich MI Study is supported by the German Federal Ministry of Education and Research (BMBF) in the context of the e:Med program (e:AtheroSysMed) and the FP7 European Union project CVgenes@target (261123). Additional grants were received from the Fondation Leducq (CADgenomics: Understanding Coronary Artery Disease Genes, 12CVD02).This study was also supported through the Deutsche Forschungsgemeinschaft cluster of excellence Vascular Biology (ATVB) Study was supported by a grant from RFPS-2007-3-644382 and Programma di ricerca Regione-Università 2010-2012 Area 1–Strategic Programmes– Diabetes Page 30 of 53 30 Regione Emilia-Romagna. Funding for the exome-sequencing project (ESP) was provided by RC2 HL103010 (HeartGO), RC2 HL102923 (LungGO), and RC2 HL102924 (WHISP). Exome sequencing was performed through RC2 HL102925 (BroadGO) and RC2 HL102926 (SeattleGO). The JHS is supported by contracts HHSN268201300046C, HHSN268201300047C, HHSN268201300048C, HHSN268201300049C, HHSN268201300050C from the National Heart, Lung, and Blood Institute and the National Institute on Minority Health and Health Disparities. Dr. Wilson is supported by U54GM115428 from the National Institute of General Medical Sciences. Exome sequencing in ATVB, PROCARDIS, Ottawa, PROMIS, Southern German Myocardial Infarction Study, and the Jackson Heart Study was supported by 5U54HG003067 (to Dr. Gabriel).

Aims Angiopoietin-like protein 3 (ANGPTL3) and 4 (ANGPTL4) inhibit lipoprotein lipase (LPL) and represent emerging drug targets to lower circulating triglycerides and reduce cardiovascular risk. To investigate the molecular effects of genetic mimicry of ANGPTL3 and ANGPTL4 inhibition and compare them to the effects of genetic mimicry of LPL enhancement. Methods and results Associations of genetic variants in ANGPTL3 (rs11207977-T), ANGPTL4 (rs116843064-A), and LPL (rs115849089-A) with an extensive serum lipid and metabolite profile (208 measures) were characterized in six cohorts of up to 61 240 participants. Genetic associations with anthropometric measures, glucose-insulin metabolism, blood pressure, markers of kidney function, and cardiometabolic endpoints via genome-wide summary data were also explored. ANGPTL4 rs116843064-A and LPL rs115849089-A displayed a strikingly similar pattern of associations across the lipoprotein and lipid measures. However, the corresponding associations with ANGPTL3 rs11207977-T differed, including those for low-density lipoprotein and high-density lipoprotein particle concentrations and compositions. All three genotypes associated with lower concentrations of an inflammatory biomarker glycoprotein acetyls and genetic mimicry of ANGPTL3 inhibition and LPL enhancement were also associated with lower C-reactive protein. Genetic mimicry of ANGPTL4 inhibition and LPL enhancement were associated with a lower waist-to-hip ratio, improved insulin-glucose metabolism, and lower risk of coronary heart disease and type 2 diabetes, whilst genetic mimicry of ANGPTL3 was associated with improved kidney function. Conclusions Genetic mimicry of ANGPTL4 inhibition and LPL enhancement have very similar systemic metabolic effects, whereas genetic mimicry of ANGPTL3 inhibition showed differing metabolic effects, suggesting potential involvement of pathways independent of LPL. Genetic mimicry of ANGPTL4 inhibition and LPL enhancement were associated with a lower risk of coronary heart disease and type 2 diabetes. These findings reinforce evidence that enhancing LPL activity (either directly or via upstream effects) through pharmacological approaches is likely to yield benefits to human health., Graphical Abstract

Background Variation in adiposity is associated with cardiometabolic disease outcomes, but mechanisms leading from this exposure to disease are unclear. This study aimed to estimate effects of body mass index (BMI) on an extensive set of circulating proteins. Methods We used SomaLogic proteomic data from up to 2737 healthy participants from the INTERVAL study. Associations between self-reported BMI and 3622 unique plasma proteins were explored using linear regression. These were complemented by Mendelian randomisation (MR) analyses using a genetic risk score (GRS) comprised of 654 BMI-associated polymorphisms from a recent genome-wide association study (GWAS) of adult BMI. A disease enrichment analysis was performed using DAVID Bioinformatics 6.8 for proteins which were altered by BMI. Results Observationally, BMI was associated with 1576 proteins (P −5), with particularly strong evidence for a positive association with leptin and fatty acid-binding protein-4 (FABP4), and a negative association with sex hormone-binding globulin (SHBG). Observational estimates were likely confounded, but the GRS for BMI did not associate with measured confounders. MR analyses provided evidence for a causal relationship between BMI and eight proteins including leptin (0.63 standard deviation (SD) per SD BMI, 95% CI 0.48–0.79, P = 1.6 × 10−15), FABP4 (0.64 SD per SD BMI, 95% CI 0.46–0.83, P = 6.7 × 10−12) and SHBG (−0.45 SD per SD BMI, 95% CI −0.65 to −0.25, P = 1.4 × 10−5). There was agreement in the magnitude of observational and MR estimates (R2 = 0.33) and evidence that proteins most strongly altered by BMI were enriched for genes involved in cardiovascular disease. Conclusions This study provides evidence for a broad impact of adiposity on the human proteome. Proteins strongly altered by BMI include those involved in regulating appetite, sex hormones and inflammation; such proteins are also enriched for cardiovascular disease-related genes. Altogether, results help focus attention onto new proteomic signatures of obesity-related disease.

Background Polygenic risk scores (PRSs) can stratify populations into cardiovascular disease (CVD) risk groups. We aimed to quantify the potential advantage of adding information on PRSs to conventional risk factors in the primary prevention of CVD. Methods and findings Using data from UK Biobank on 306,654 individuals without a history of CVD and not on lipid-lowering treatments (mean age [SD]: 56.0 [8.0] years; females: 57%; median follow-up: 8.1 years), we calculated measures of risk discrimination and reclassification upon addition of PRSs to risk factors in a conventional risk prediction model (i.e., age, sex, systolic blood pressure, smoking status, history of diabetes, and total and high-density lipoprotein cholesterol). We then modelled the implications of initiating guideline-recommended statin therapy in a primary care setting using incidence rates from 2.1 million individuals from the Clinical Practice Research Datalink. The C-index, a measure of risk discrimination, was 0.710 (95% CI 0.703–0.717) for a CVD prediction model containing conventional risk predictors alone. Addition of information on PRSs increased the C-index by 0.012 (95% CI 0.009–0.015), and resulted in continuous net reclassification improvements of about 10% and 12% in cases and non-cases, respectively. If a PRS were assessed in the entire UK primary care population aged 40–75 years, assuming that statin therapy would be initiated in accordance with the UK National Institute for Health and Care Excellence guidelines (i.e., for persons with a predicted risk of ≥10% and for those with certain other risk factors, such as diabetes, irrespective of their 10-year predicted risk), then it could help prevent 1 additional CVD event for approximately every 5,750 individuals screened. By contrast, targeted assessment only among people at intermediate (i.e., 5% to, Luanluan Sun and colleagues investigate whether adding polygenic risk scores to conventional risk factors of cardiovascular disease helps predict disease risk., Author summary Why was this study done? Application of polygenic risk scores (PRSs) has opened opportunities to enhance risk stratification and prevention for common diseases. The clinical utility of PRSs in cardiovascular disease (CVD) risk prediction is, however, uncertain. Previous analyses have generally focused only on coronary heart disease (CHD) rather than the composite outcome of CHD and stroke, and have often lacked modelling of clinical implications of initiating guideline-recommended interventions (e.g., statin therapy). What did the researchers do and find? We quantified the incremental predictive gain with PRSs on top of conventional risk factors using data on 306,654 individuals from UK Biobank. We modelled the population health implications of initiating statin therapy as recommended by current guidelines using data from 2.1 million individuals from the Clinical Practice Research Datalink. Addition of information on PRSs to a conventional risk prediction model increased the C-index (a measure of risk discrimination) and improved risk classification of cases and non-cases. We estimated that targeted assessment of PRSs among people at intermediate (i.e., 5% to

SUMMARYObjectiveTo compare four haemoglobin measurement methods in whole blood donors.BackgroundTo safeguard donors, blood services measure haemoglobin concentration in advance of each donation. NHS Blood and Transplant’s (NHSBT) usual method has been capillary gravimetry (copper sulphate), followed by venous HemoCue® (spectrophotometry) for donors failing gravimetry. However, gravimetry/venous HemoCue® results in 10% of donors being inappropriately bled (i.e., with haemoglobin values below the regulatory threshold).MethodsThe following were compared in 21,840 blood donors (aged ≥18 years) recruited from 10 mobile centres of NHSBT in England, with each method compared with the Sysmex XN-2000 haematology analyser, the reference standard: 1) gravimetry/venous HemoCue®; 2) “post donation” approach, i.e., estimating current haemoglobin concentration from that measured by a haematology analyser at a donor’s most recent prior donation; 3) capillary HemoCue®; and 4) non-invasive spectrometry (MBR Haemospect® or Orsense NMB200®). We assessed each method for sensitivity; specificity; proportion of donors who would have been inappropriately bled, or rejected from donation (“deferred”) incorrectly; and test preference.ResultsCompared with the reference standard, the methods ranged in test sensitivity from 17.0% (MBR Haemospect®) to 79.0% (HemoCue®) in men, and from 19.0% (MBR Haemospect®) to 82.8% (HemoCue®) in women. For specificity, the methods ranged from 87.2% (MBR Haemospect®) to 99.9% (gravimetry/venous HemoCue®) in men, and from 74.1% (Orsense NMB200®) to 99.8% (gravimetry/venous HemoCue®) in women. The proportion of donors who would have been inappropriately bled ranged from 2.2% in men for HemoCue® to 18.9% in women for MBR Haemospect®. The proportion of donors who would have been deferred incorrectly with haemoglobin concentration above the minimum threshold ranged from 0.1% in men for gravimetry/venous HemoCue® to 20.3% in women for OrSense®. Most donors preferred non-invasive spectrometry.ConclusionIn the largest study reporting head-to-head comparisons of four methods to measure haemoglobin prior to blood donation, our results support replacement of venous HemoCue® with the capillary HemoCue® when donors fail gravimetry. These results have had direct translational implications for NHS Blood and Transplant in England.

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant., Graphical Abstract, Highlights • Increasing frequency of SARS-CoV-2 D614G is consistent with a selective advantage • Phylodynamic analyses do not show significantly different growth of D614G clusters • There is no association of D614G replacement with greater severity of infection • The D614G replacement is associated with higher viral loads and younger patient age, Analysis of the spread and frequency of SARS-CoV-2 D614G in the United Kingdom suggests a selective advantage for this strain that is associated with higher viral loads in younger patients but not higher COVID-19 clinical severity or mortality.

Large-scale gene sequencing studies for complex traits have the potential to identify causal genes with therapeutic implications. We performed gene-based association testing of blood lipid levels with rare (minor allele frequency170,000 individuals from multiple ancestries: 97,493 European, 30,025 South Asian, 16,507 African, 16,440 Hispanic/Latino, 10,420 East Asian, and 1,182 Samoan. We identified 35 genes associated with circulating lipid levels. Ten of these: ALB, SRSF2, JAK2, CREB3L3, TMEM136, VARS, NR1H3, PLA2G12A, PPARG and STAB1 have not been implicated for lipid levels using rare coding variation in population-based samples. We prioritize 32 genes identified in array-based genome-wide association study (GWAS) loci based on gene-based associations, of which three: EVI5, SH2B3, and PLIN1, had no prior evidence of rare coding variant associations. Most of the associated genes showed evidence of association in multiple ancestries. Also, we observed an enrichment of gene-based associations for low-density lipoprotein cholesterol drug target genes, and for genes closest to GWAS index single nucleotide polymorphisms (SNP). Our results demonstrate that gene-based associations can be beneficial for drug target development and provide evidence that the gene closest to the array-based GWAS index SNP is often the functional gene for blood lipid levels.

Polygenic risk scores (PRSs), which often aggregate results from genome-wide association studies, can bridge the gap between initial discovery efforts and clinical applications for the estimation of disease risk using genetics. However, there is notable heterogeneity in the application and reporting of these risk scores, which hinders the translation of PRSs into clinical care. Here, in a collaboration between the Clinical Genome Resource (ClinGen) Complex Disease Working Group and the Polygenic Score (PGS) Catalog, we present the Polygenic Risk Score Reporting Standards (PRS-RS), in which we update the Genetic Risk Prediction Studies (GRIPS) Statement to reflect the present state of the field. Drawing on the input of experts in epidemiology, statistics, disease-specific applications, implementation and policy, this comprehensive reporting framework defines the minimal information that is needed to interpret and evaluate PRSs, especially with respect to downstream clinical applications. Items span detailed descriptions of study populations, statistical methods for the development and validation of PRSs and considerations for the potential limitations of these scores. In addition, we emphasize the need for data availability and transparency, and we encourage researchers to deposit and share PRSs through the PGS Catalog to facilitate reproducibility and comparative benchmarking. By providing these criteria in a structured format that builds on existing standards and ontologies, the use of this framework in publishing PRSs will facilitate translation into clinical care and progress towards defining best practice.

Funder: Scottish Government; doi: https://doi.org/10.13039/100012095, Funder: Cancer Research UK (CRUK); doi: https://doi.org/10.13039/501100000289, Restless legs syndrome (RLS) is a common neurological sensorimotor disorder often described as an unpleasant sensation associated with an urge to move the legs. Here we report findings from a meta-analysis of genome-wide association studies of RLS including 480,982 Caucasians (cases = 10,257) and a follow up sample of 24,977 (cases = 6,651). We confirm 19 of the 20 previously reported RLS sequence variants at 19 loci and report three novel RLS associations; rs112716420-G (OR = 1.25, P = 1.5 × 10−18), rs10068599-T (OR = 1.09, P = 6.9 × 10−10) and rs10769894-A (OR = 0.90, P = 9.4 × 10−14). At four of the 22 RLS loci, cis-eQTL analysis indicates a causal impact on gene expression. Through polygenic risk score for RLS we extended prior epidemiological findings implicating obesity, smoking and high alcohol intake as risk factors for RLS. To improve our understanding, with the purpose of seeking better treatments, more genetics studies yielding deeper insights into the disease biology are needed.

Background Prior research suggested a differential association of 25-hydroxyvitamin D (25(OH)D) metabolites with type 2 diabetes (T2D), with total 25(OH)D and 25(OH)D3 inversely associated with T2D, but the epimeric form (C3-epi-25(OH)D3) positively associated with T2D. Whether or not these observational associations are causal remains uncertain. We aimed to examine the potential causality of these associations using Mendelian randomisation (MR) analysis. Methods and findings We performed a meta-analysis of genome-wide association studies for total 25(OH)D (N = 120,618), 25(OH)D3 (N = 40,562), and C3-epi-25(OH)D3 (N = 40,562) in participants of European descent (European Prospective Investigation into Cancer and Nutrition [EPIC]–InterAct study, EPIC-Norfolk study, EPIC-CVD study, Ely study, and the SUNLIGHT consortium). We identified genetic variants for MR analysis to investigate the causal association of the 25(OH)D metabolites with T2D (including 80,983 T2D cases and 842,909 non-cases). We also estimated the observational association of 25(OH)D metabolites with T2D by performing random effects meta-analysis of results from previous studies and results from the EPIC-InterAct study. We identified 10 genetic loci associated with total 25(OH)D, 7 loci associated with 25(OH)D3 and 3 loci associated with C3-epi-25(OH)D3. Based on the meta-analysis of observational studies, each 1–standard deviation (SD) higher level of 25(OH)D was associated with a 20% lower risk of T2D (relative risk [RR]: 0.80; 95% CI 0.77, 0.84; p < 0.001), but a genetically predicted 1-SD increase in 25(OH)D was not significantly associated with T2D (odds ratio [OR]: 0.96; 95% CI 0.89, 1.03; p = 0.23); this result was consistent across sensitivity analyses. In EPIC-InterAct, 25(OH)D3 (per 1-SD) was associated with a lower risk of T2D (RR: 0.81; 95% CI 0.77, 0.86; p < 0.001), while C3-epi-25(OH)D3 (above versus below lower limit of quantification) was positively associated with T2D (RR: 1.12; 95% CI 1.03, 1.22; p = 0.006), but neither 25(OH)D3 (OR: 0.97; 95% CI 0.93, 1.01; p = 0.14) nor C3-epi-25(OH)D3 (OR: 0.98; 95% CI 0.93, 1.04; p = 0.53) was causally associated with T2D risk in the MR analysis. Main limitations include the lack of a non-linear MR analysis and of the generalisability of the current findings from European populations to other populations of different ethnicities. Conclusions Our study found discordant associations of biochemically measured and genetically predicted differences in blood 25(OH)D with T2D risk. The findings based on MR analysis in a large sample of European ancestry do not support a causal association of total 25(OH)D or 25(OH)D metabolites with T2D and argue against the use of vitamin D supplementation for the prevention of T2D., Using both observational and genetic analyses, Ju-Sheng Zheng and colleagues investigate the relationship between vitamin D metabolites and type 2 diabetes among European individuals., Author summary Why was this study done? There is ongoing uncertainty on whether the body’s vitamin D status indicated by blood 25-hydroxyvitamin D (25(OH)D) is relevant to the prevention of type 2 diabetes. There are conflicting findings from observational studies and a limited number of randomised controlled trials. Prior research did not distinguish between different metabolites of total 25(OH)D, including 25(OH)D3 and C3-epi-25(OH)D3, an isomer of 25(OH)D3. It is not clear whether the associations of 25(OH)D metabolites with type 2 diabetes are causal, with conflicting findings from prior Mendelian randomisation studies of total 25(OH)D and no previous Mendelian randomisation studies appraising 25(OH)D metabolites. What did the researchers do and find? The current research compared observational estimates of the association between 25(OH)D metabolites and incident type 2 diabetes with Mendelian randomisation estimates based on genetic instruments. Using multiple data sources, we performed genome-wide association studies among 120,618 individuals for total 25(OH)D, and among 40,562 individuals for the other vitamin D metabolites. Among participants of European descent, 10 genetic loci were identified for total 25(OH)D, 7 loci for 25(OH)D3 and 3 loci for C3-epi-25(OH)D3. In meta-analysis of observational studies, we found that each 1–standard deviation higher level of total 25(OH)D was associated with 20% lower risk of type 2 diabetes. The result was similar for 25(OH)D3, but for C3-epi-25(OH)D3, a positive association with type 2 diabetes was found. With up to 80,983 type 2 diabetes cases and 842,909 controls, we assessed the association of genetically predicted differences in total 25(OH)D and its metabolites with type 2 diabetes. Neither genetically predicted higher total 25(OH)D level nor genetically predicted higher levels of 25(OH)D metabolites were significantly associated with type 2 diabetes. What do these findings mean? There were conflicting findings for a link with type 2 diabetes for the observational analysis of biochemically measured 25(OH)D metabolites versus the genetically predicted levels of these metabolites. The null findings based on Mendelian randomisation analysis indicate that blood levels of 25(OH)D or its metabolites are not likely to be causal factors for the development of type 2 diabetes. The current findings together with other evidence from randomised controlled trials do not support the use of vitamin D supplementation for the prevention of type 2 diabetes.

47 p.-11 fig., Mitochondrial DNA (mtDNA) variants influence the risk of late-onset human diseases, but the reasons for this are poorly understood. Undertaking a hypothesis-free analysis of 5,689 blood-derived biomarkers with mtDNA variants in 16,220 healthy donors, here we show that variants defining mtDNA haplogroups Uk and H4 modulate the level of circulating N-formylmethionine (fMet), which initiates mitochondrial protein translation. In human cytoplasmic hybrid (cybrid) lines, fMet modulated both mitochondrial and cytosolic proteins on multiple levels, through transcription, post-translational modification and proteolysis by an N-degron pathway, abolishing known differences between mtDNA haplogroups. In a further 11,966 individuals, fMet levels contributed to all-cause mortality and the disease risk of several common cardiovascular disorders. Together, these findings indicate that fMet plays a key role in common age-related disease through pleiotropic effects on cell proteostasis., This work was supported by Health Data Research UK, which is funded by the UK Medical Research Council, the Engineering and Physical Sciences Research Council, the Economic and Social Research Council, the Department of Health and Social Care (England), the Chief Scientist Office of the Scottish Government Health and Social Care Directorates, the Health and Social Care Research and Development Division (Welsh Government), the Public Health Agency (Northern Ireland), the British Heart Foundation and Wellcome. N.C. is supported by an EBI–Sanger Postdoctoral Fellowship. A.G.-D. receives funding from the NIHR Biomedical Research Centre based at Cambridge University Hospitals NHS Foundation Trust. E.Y.-D. was funded by the Isaac Newton Trust/Wellcome Trust ISSF/University of Cambridge Joint Research Grants Scheme. J.M.M.H. was funded by the NIHR Cambridge BRC (BRC-1215-20014)*. P.F.C.is a Wellcome Trust Principal Research Fellow (212219/Z/18/Z) and a UK NIHR Senior Investigator, who receives support from the Medical Research Council Mitochondrial Biology Unit (MC_UU_00015/9), the Evelyn Trust and the NIHR Biomedical Research Centre based at Cambridge University Hospitals NHS Foundation Trust and the University of Cambridge. C.H.W.-G. is supported by a RCUK/UKRI Research Innovation Fellowship awarded by the Medical Research Council (MR/R007446/1) and by the Cambridge Centre for Parkinson-Plus. N.S. is supported by the Wellcome Trust(grant number 098051 until 30 September 2016 and 206194 from 1 October 2016),the Cambridge BHF Centre of Research Excellence (RE/18/1/34212) and the NIHR Cambridge Biomedical Research Centre Biomedical Resources Grant, University of Cambridge, Cardiovascular Theme (RG64226). J.D. holds a British Heart Foundation Professorship and an NIHR Senior Investigator Award*. R.A.L. is supported by grants from Parkinson’s UK. Sequencing of INTERVAL samples was supported by the Wellcome Trust (grant number 206194). Metabolon metabolomics assays were funded by the NIHR BioResource, the Wellcome Trust (grant number 206194) and the NIHR Cambridge BRC (BRC-1215-20014)*. Nightingale Health NMR assays were funded by the European Commission Framework Programme 7 (HEALTH-F2-2012-279233). SomaLogic assays were funded by Merck and the NIHR Cambridge BRC (BRC-1215-20014)*. ICICLE-PD was funded by Parkinson’s UK (J-0802, G-1301, G-1507) and the Lockhart Parkinson’s Disease Research Fund and supported by the NIHR Newcastle Biomedical Research Unit and the NIHR Cambridge Biomedical Research Centre (146281). The EPIC-Norfolk study (https://doi.org/10.22025/2019.10.105.00004) has received funding from the Medical Research Council (MR/N003284/1 and MC-UU_12015/1) and Cancer Research UK (C864/A14136). Genetic work in the EPIC-Norfolk study was funded by the Medical Research Council (MC_PC_13048). Metabolite measurements in the EPIC-Norfolk study were supported by the MRC Cambridge Initiative in Metabolic Science (MR/L00002/1) and the Innovative Medicines Initiative Joint Undertaking under EMIF grant agreement no. 115372.

ObjectiveTo monitor hospital activity for presentation, diagnosis and treatment of cardiovascular diseases during the COVID-19) pandemic to inform on indirect effects.MethodsRetrospective serial cross-sectional study in nine UK hospitals using hospital activity data from 28 October 2019 (pre-COVID-19) to 10 May 2020 (pre-easing of lockdown) and for the same weeks during 2018–2019. We analysed aggregate data for selected cardiovascular diseases before and during the epidemic. We produced an online visualisation tool to enable near real-time monitoring of trends.ResultsAcross nine hospitals, total admissions and emergency department (ED) attendances decreased after lockdown (23 March 2020) by 57.9% (57.1%–58.6%) and 52.9% (52.2%–53.5%), respectively, compared with the previous year. Activity for cardiac, cerebrovascular and other vascular conditions started to decline 1–2 weeks before lockdown and fell by 31%–88% after lockdown, with the greatest reductions observed for coronary artery bypass grafts, carotid endarterectomy, aortic aneurysm repair and peripheral arterial disease procedures. Compared with before the first UK COVID-19 (31 January 2020), activity declined across diseases and specialties between the first case and lockdown (total ED attendances relative reduction (RR) 0.94, 0.93–0.95; total hospital admissions RR 0.96, 0.95–0.97) and after lockdown (attendances RR 0.63, 0.62–0.64; admissions RR 0.59, 0.57–0.60). There was limited recovery towards usual levels of some activities from mid-April 2020.ConclusionsSubstantial reductions in total and cardiovascular activities are likely to contribute to a major burden of indirect effects of the pandemic, suggesting they should be monitored and mitigated urgently.

Population-scale genetic studies can identify drug targets and allow disease risk to be predicted with resulting benefit for management of individual health risks and system-wide allocation of health care delivery resources. Although population-scale projects are underway in many parts of the world, genetic variation between population groups means that additional projects are warranted. South Asia has a population whose genetics is the least characterized of any of the world’s major populations. Here we describe GenomeAsia studies that characterize population structure in South Asia and that create tools for economical and accurate genotyping at population-scale. Prior work on population structure characterized isolated population groups, the relevance of which to large-scale studies of disease genetics is unclear. For our studies we used whole genome sequence information from 4,807 individuals recruited in the health care delivery systems of Pakistan, India and Bangladesh to ensure relevance to population-scale studies of disease genetics. We combined this with WGS data from 927 individuals from isolated South Asian population groups, and developed a custom SNP array (called SARGAM) that is optimized for future human genetic studies in South Asia. We find evidence for high rates of reproductive isolation, endogamy and consanguinity that vary across the subcontinent and that lead to levels of homozygosity that approach 100 times that seen in outbred populations. We describe founder effects that increase the power to associate functional variants with disease processes and that make South Asia a uniquely powerful place for population-scale genetic studies.

Background:Familial sitosterolemia is a rare Mendelian disorder characterized by hyperabsorption and decreased biliary excretion of dietary sterols. Affected individuals typically have complete genetic deficiency—homozygous loss-of-function (LoF) variants—in theABCG5orABCG8genes and have substantially elevated plasma sitosterol and LDL (low-density lipoprotein) cholesterol (LDL-C) levels. The impact of partial genetic deficiency ofABCG5orABCG8—as occurs in heterozygous carriers of LoF variants—on LDL-C and risk of coronary artery disease (CAD) has remained uncertain.Methods:We first recruited 9 sitosterolemia families, identified causative LoF variants inABCG5orABCG8, and evaluated the associations of theseABCG5orABCG8LoF variants with plasma phytosterols and lipid levels. We next assessed for LoF variants inABCG5orABCG8in CAD cases (n=29 321) versus controls (n=357 326). We tested the association of rare LoF variants inABCG5orABCG8with blood lipids and risk for CAD. Rare LoF variants were defined as protein-truncating variants with minor allele frequency ABCG5orABCG8.Results:In sitosterolemia families, 7 pedigrees harbored causative LoF variants inABCG5and 2 pedigrees inABCG8. Homozygous LoF variants in eitherABCG5orABCG8led to marked elevations in sitosterol and LDL-C. Of those sitosterolemia families, heterozygous carriers ofABCG5LoF variants exhibited increased sitosterol and LDL-C levels compared with noncarriers. Within large-scale CAD case-control cohorts, prevalence of rare LoF variants inABCG5and inABCG8was ≈0.1% each.ABCG5heterozygous LoF variant carriers had significantly elevated LDL-C levels (25 mg/dL [95% CI, 14–35];P=1.1×10−6) and were at 2-fold increased risk of CAD (odds ratio, 2.06 [95% CI, 1.27–3.35];P=0.004). By contrast,ABCG8heterozygous LoF carrier status was not associated with increased LDL-C or risk of CAD.Conclusions:Although familial sitosterolemia is traditionally considered as a recessive disorder, we observed that heterozygous carriers of an LoF variant inABCG5had significantly increased sitosterol and LDL-C levels and a 2-fold increase in risk of CAD.

Background Studies on the relationship between renal function and the human plasma proteome have identified several potential biomarkers. However, investigations have been conducted largely in European populations, and causality of the associations between plasma proteins and kidney function has never been addressed. Methods A cross-sectional study of 993 plasma proteins among 2,882 participants in four studies of European and admixed ancestries (KORA, INTERVAL, HUNT, QMDiab) identified trans-ethnic associations between eGFR/CKD and proteomic biomarkers. For the replicated associations, two-sample bidirectional Mendelian randomization (MR) was used to investigate potential causal relationships. Publicly available datasets and transcriptomic data from independent studies were used to examine the association between gene expression in kidney tissue and eGFR . Results Fifty-seven plasma proteins were associated with eGFR, including one novel protein. Twenty-three of these were additionally associated with CKD. The strongest inferred causal effect was the positive effect of eGFR on testican-2, in line with the known biological role of this protein and the expression of its protein-coding gene (SPOCK2) in renal tissue. We also observed suggestive evidence of an effect of melanoma inhibitory activity (MIA), carbonic anhydrase III, and cystatin-M on eGFR. Conclusions In a discovery-replication setting, we identified 57 proteins trans-ethnically associated with eGFR. The revealed causal relationships are an important stepping-stone in establishing testican-2 as a clinically relevant physiological marker of kidney disease progression, and point to additional proteins warranting further investigation.

Polygenic risk scores (PRS), often aggregating the results from genome-wide association studies, can bridge the gap between the initial variant discovery efforts and disease risk estimation for clinical applications. However, there is remarkable heterogeneity in the reporting of these risk scores due to a lack of adherence to reporting standards and no accepted standards suited for the current state of PRS development and application. This lack of adherence and best practices hinders the translation of PRS into clinical care. The ClinGen Complex Disease Working Group, in a collaboration with the Polygenic Score (PGS) Catalog, have developed a novel PRS Reporting Statement (PRS-RS), updating previous standards to the current state of the field and to enable downstream utility. Drawing upon experts in epidemiology, statistics, disease-specific applications, implementation, and policy, this 23-item reporting framework defines the minimal information needed to interpret and evaluate a PRS, especially with respect to any downstream clinical applications. Items span detailed descriptions of the study population (recruitment method, key demographics, inclusion/exclusion criteria, and phenotype definition), statistical methods for both PRS development and validation, and considerations for potential limitations of the published risk score and downstream clinical utility. Additionally, emphasis has been placed on data availability and transparency to facilitate reproducibility and benchmarking against other PRS, such as deposition in the publicly available PGS Catalog (www.PGScatalog.org). By providing these criteria in a structured format that builds upon existing standards and ontologies, the use of this framework in publishing PRS will facilitate translation of PRS into clinical care and progress towards defining best practices.SummaryIn recent years, polygenic risk scores (PRS) have become an increasingly studied tool to capture the genome-wide liability underlying many human traits and diseases, hoping to better inform an individual’s genetic risk. However, a lack of tailored reporting standards has hindered the translation of this important tool into clinical and public health practice with the heterogeneous underreporting of details necessary for benchmarking and reproducibility. To address this gap, the ClinGen Complex Disease Working Group and Polygenic Score (PGS) Catalog have collaborated to develop the 23-item Polygenic Risk Score Reporting Statement (PRS-RS). This framework provides the minimal information expected of authors to promote the validity, transparency, and reproducibility of PRS by requiring authors to detail the study population, statistical methods, and potential clinical utility of a published score. The widespread adoption of this framework will encourage rigorous methodological consideration and facilitate benchmarking to ensure high quality scores are translated into the clinic.

ObjectivesTo use human genetic variants that proxy angiotensin-converting enzyme (ACE) inhibitor drug effects and cardiovascular risk factors to provide insight into how these exposures affect lung ACE2 and TMPRSS2 gene expression and circulating ACE2 levels.DesignTwo-sample Mendelian randomization (MR) analysis.SettingSummary-level genetic association data.ParticipantsParticipants were predominantly of European ancestry. Variants that proxy ACE inhibitor drug effects and cardiometabolic risk factors (body mass index, chronic obstructive pulmonary disease, lifetime smoking index, low-density lipoprotein cholesterol, systolic blood pressure and type 2 diabetes mellitus) were selected from publicly available genome-wide association study data (sample sizes ranging from 188,577 to 898,130 participants). Genetic association estimates for lung expression of ACE2 and TMPRSS2 were obtained from the Gene-Tissue Expression (GTEx) project (515 participants) and the Lung eQTL Consortium (1,038 participants). Genetic association estimates for circulating plasma ACE2 levels were obtained from the INTERVAL study (4,947 participants).Main outcomes and measuresLung ACE2 and TMPRSS2 expression and plasma ACE2 levels.ResultsThere were no association of genetically proxied ACE inhibition with any of the outcomes considered here. There was evidence of a positive association of genetic liability to type 2 diabetes mellitus with lung ACE2 gene expression in GTEx (p = 4×10−4) and with circulating plasma ACE2 levels in INTERVAL (p = 0.03), but not with lung ACE2 expression in the Lung eQTL Consortium study (p = 0.68). There were no associations between genetically predicted levels of the other cardiometabolic traits with the outcomes.ConclusionsThis study does not provide evidence to support that ACE inhibitor antihypertensive drugs affect lung ACE2 and TMPRSS2 expression or plasma ACE2 levels. In the current COVID-19 pandemic, our findings do not support a change in ACE inhibitor medication use without clinical justification.Summary boxesWhat is already known on this topicSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is responsible for the current coronavirus disease 2019 (COVID-19) pandemic.Serine protease TMPRSS2 is involved in priming the SARS-CoV-2 spike protein for cellular entry through the angiotensin-converting enzyme 2 (ACE2) receptor.Expression of ACE2 and TMPRSS2 in the lung epithelium might have implications for risk of SARS-CoV-2 infection and severity of COVID-19.What this study addsWe used human genetic variants that proxy ACE inhibitor drug effects and cardiometabolic risk factors to provide insight into how these exposures affect lung ACE2 and TMPRSS2 expression and circulating ACE2 levels.Our findings do not support the hypothesis that ACE inhibitors have effects on ACE2 expression.We found some support for an association of genetic liability to type 2 diabetes mellitus with higher lung ACE2 expression and plasma ACE2 levels, but evidence was inconsistent across studies.

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. By mapping and replicating protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, we identified 467 pQTLs for 85 proteins. The pQTLs were used in combination with other sources of information to evaluate known drug targets, and suggest new target candidates or repositioning opportunities, underpinned by a) causality assessment using Mendelian randomization, b) pathway mapping usingtrans-pQTL gene assignments, and c) protein-centric polygenic risk scores enabling matching of plausible target mechanisms to sub-groups of individuals enabling precision medicine.

Genome-wide association studies have identified many individual genetic loci associated with multiple complex traits and common diseases. There are, however, few examples where the molecular basis of such pleiotropy has been elucidated. To address this challenge, we describe an integrative approach, focusing on the p.Ser219Gly (rs867186 A>G) variant in thePROCRgene (encoding the endothelial protein C receptor, EPCR), which has been associated with lower coronary artery disease (CAD) risk but higher venous thromboembolism (VTE) risk. In a phenome scan of 12 cardiometabolic diseases and 24 molecular factors, we found thatPROCR-219Gly associated with higher plasma levels of zymogenic and activated protein C as well as coagulation factor VII. Using statistical colocalization and Mendelian randomization analyses, we uncovered shared genetic etiology across activated protein C, factor VII, CAD and VTE, identifying p.S219G as the likely causal variant at the locus. In a recall-by-genotype study of 52 healthy volunteers stratified by p.S219G, we detected 2.5-fold higher soluble EPCR levels and 1.2-fold higher protein C levels in plasma per effect allele, suggesting the allele induces EPCR shedding from the membrane of endothelial cells. Finally, in cell adhesion assays, we found that increasing concentrations of activated protein C, but not soluble EPCR, reduced leukocyte–endothelial cell adhesion, a marker for vascular inflammation. These results support a role for protein C as a causal factor in arterial and venous diseases, suggesting thatPROCR-219Gly protects against CAD through anti-inflammatory mechanisms while it promotes VTE risk through pro-thrombotic mechanisms. Overall, our study illustrates a multi-modal approach that can help reveal molecular underpinnings of cross-disease associations.

Circulating metabolite levels are biomarkers for cardiovascular disease (CVD). Here we studied, association of rare variants and 226 serum lipoproteins, lipids and amino acids in 7,142 (discovery plus follow-up) healthy participants. We leveraged the information from multiple metabolite measurements on the same participants to improve discovery in rare variant association analyses for gene-based and gene-set tests by incorporating correlated metabolites as covariates in the validation stage. Gene-based analysis corrected for the effective number of tests performed, confirmed established associations at APOB, APOC3, PAH, HAL and PCSK (p, Author summary Cardiovascular diseases (CVD) are the number one cause of death globally. Various metabolic biomarkers including lipid and lipoprotein particles have been implicated as risk factors for the development of CVD. Understanding how these biomarkers are regulated can lead to increased understanding of CVD aetiology and the potential identification of drug targets. Here we take advantage of high resolution measurements on a large cohort of 7,142 healthy blood donors with whole-exome and whole-genome sequencing data to explore the influence of rare variation on circulating metabolic biomarker levels. Using a novel approach leveraging the information gained from various measurements on the same participants we are able to identify a novel biological pathway involved in the regulation of intermediate-density and low-density lipoproteins as well as circulating cholesterol, confirm various established gene associations and identify potential novel gene associations that merit further replication. This work highlights the advantages that can be gained by combining high resolution genotypic and phenotypic measurements in one large cohort.

Polygenic scores (PGSs) for blood cell traits can be constructed using summary statistics from genome-wide association studies. As the selection of variants and the modelling of their interactions in PGSs may be limited by univariate analysis, therefore, such a conventional method may yield sub-optional performance. This study evaluated the relative effectiveness of four machine learning and deep learning methods, as well as a univariate method, in the construction of PGSs for 26 blood cell traits, using data from UK Biobank (n=~400,000) and INTERVAL (n=~40,000). Our results showed that learning methods can improve PGSs construction for nearly every blood cell trait considered, with this superiority explained by the ability of machine learning methods to capture interactions among variants. This study also demonstrated that populations can be well stratified by the PGSs of these blood cell traits, even for traits that exhibit large differences between ages and sexes, suggesting potential for disease prevention. As our study found genetic correlations between the PGSs for blood cell traits and PGSs for several common human diseases (recapitulating well-known associations between the blood cell traits themselves and certain diseases), it suggests that blood cell traits may be indicators or/and mediators for a variety of common disorders via shared genetic variants and functional pathways.

Circulating levels of small molecules or metabolites are highly heritable, but the impact of genetic differences in metabolism on human health is not well understood. In this cross-platform, genome-wide meta-analysis of 174 metabolite levels across six cohorts including up to 86,507 participants (70% unpublished data), we identify 499 (362 novel) genome-wide significant associations (p-10) at 144 (94 novel) genomic regions. We show that inheritance of blood metabolite levels in the general population is characterized by pleiotropy, allelic heterogeneity, rare and common variants with large effects, non-linear associations, and enrichment for nonsynonymous variation in transporter and enzyme encoding genes. The majority of identified genes are known to be involved in biochemical processes regulating metabolite levels and to cause monogenic inborn errors of metabolism linked to specific metabolites, such as ASNS (rs17345286, MAF=0.27) and asparagine levels. We illustrate the influence of metabolite-associated variants on human health including a shared signal at GLP2R (p.Asp470Asn) associated with higher citrulline levels, body mass index, fasting glucose-dependent insulinotropic peptide and type 2 diabetes risk, and demonstrate beta-arrestin signalling as the underlying mechanism in cellular models. We link genetically-higher serine levels to a 95% reduction in the likelihood of developing macular telangiectasia type 2 [odds ratio (95% confidence interval) per standard deviation higher levels 0.05 (0.03-0.08; p=9.5×10-30)]. We further demonstrate the predictive value of genetic variants identified for serine or glycine levels for this rare and difficult to diagnose degenerative retinal disease [area under the receiver operating characteristic curve: 0.73 (95% confidence interval: 0.70-0.75)], for which low serine availability, through generation of deoxysphingolipids, has recently been shown to be causally relevant. These results show that integration of human genomic variation with circulating small molecule data obtained across different measurement platforms enables efficient discovery of genetic regulators of human metabolism and translation into clinical insights.

SUMMARYThousands of genetic associations with phenotypes of blood cells are known, but few are with phenotypes relevant to cell function. We performed GWAS of 63 flow-cytometry phenotypes, including measures of cell granularity, nucleic acid content, and reactivity, in 39,656 participants in the INTERVAL study, identifying 2,172 variant-trait associations. These include associations mediated by functional cellular structures such as secretory granules, implicated in vascular, thrombotic, inflammatory and neoplastic diseases. By integrating our results with epigenetic data and with signals from molecular abundance/disease GWAS, we infer the hematopoietic origins of population phenotypic variation and identify the transcription factor FOG2 as a regulator of plateletα-granularity. We show how flow cytometry genetics can suggest cell types mediating complex disease risk and suggest efficacious drug targets, presenting Daclizumab/Vedolizumab in autoimmune disease as positive controls. Finally, we add to existing evidence supporting IL7/IL7-R as drug targets for multiple sclerosis.

Cholesteryl ester transfer protein (CETP) inhibition reduces vascular event risk, but confusion surrounds its effects on low-density lipoprotein (LDL) cholesterol. Here, we clarify associations of genetic inhibition of CETP on detailed lipoprotein measures and compare those to genetic inhibition of 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR). We used an allele associated with lower CETP expression (rs247617) to mimic CETP inhibition and an allele associated with lower HMGCR expression (rs12916) to mimic the well-known effects of statins for comparison. The study consists of 65,427 participants of European ancestries with detailed lipoprotein subclass profiling from nuclear magnetic resonance spectroscopy. Genetic associations were scaled to 10% reduction in relative risk of coronary heart disease (CHD). We also examined observational associations of the lipoprotein subclass measures with risk of incident CHD in 3 population-based cohorts totalling 616 incident cases and 13,564 controls during 8-year follow-up. Genetic inhibition of CETP and HMGCR resulted in near-identical associations with LDL cholesterol concentration estimated by the Friedewald equation. Inhibition of HMGCR had relatively consistent associations on lower cholesterol concentrations across all apolipoprotein B-containing lipoproteins. In contrast, the associations of the inhibition of CETP were stronger on lower remnant and very-low-density lipoprotein (VLDL) cholesterol, but there were no associations on cholesterol concentrations in LDL defined by particle size (diameter 18–26 nm) (−0.02 SD LDL defined by particle size; 95% CI: −0.10 to 0.05 for CETP versus −0.24 SD, 95% CI −0.30 to −0.18 for HMGCR). Inhibition of CETP was strongly associated with lower proportion of triglycerides in all high-density lipoprotein (HDL) particles. In observational analyses, a higher triglyceride composition within HDL subclasses was associated with higher risk of CHD, independently of total cholesterol and triglycerides (strongest hazard ratio per 1 SD higher triglyceride composition in very large HDL 1.35; 95% CI: 1.18–1.54). In conclusion, CETP inhibition does not appear to affect size-specific LDL cholesterol but is likely to lower CHD risk by lowering concentrations of other atherogenic, apolipoprotein B-containing lipoproteins (such as remnant and VLDLs). Inhibition of CETP also lowers triglyceride composition in HDL particles, a phenomenon reflecting combined effects of circulating HDL, triglycerides, and apolipoprotein B-containing particles and is associated with a lower CHD risk in observational analyses. Our results reveal that conventional composite lipid assays may mask heterogeneous effects of emerging lipid-altering therapies., Inhibition of cholesteryl ester transfer protein does not affect size-specific low-density lipoprotein cholesterol, but may lower coronary heart disease risk by lowering cholesterol concentrations in other apolipoprotein-B containing atherogenic lipoproteins, and by lowering triglyceride content of high-density lipoprotein particles.

SUMMARYMost loci identified by GWAS have been found in populations of European ancestry (EA). In trans-ethnic meta-analyses for 15 hematological traits in 746,667 participants, including 184,535 non-EA individuals, we identified 5,552 trait-variant associations at P−9, including 71 novel loci not found in EA populations. We also identified novel ancestry-specific variants not found in EA, including an IL7 missense variant in South Asians associated with lymphocyte count in vivo and IL7 secretion levels in vitro. Fine-mapping prioritized variants annotated as functional, and generated 95% credible sets that were 30% smaller when using the trans-ethnic as opposed to the EA-only results. We explored the clinical significance and predictive value of trans-ethnic variants in multiple populations, and compared genetic architecture and the impact of natural selection on these blood phenotypes between populations. Altogether, our results for hematological traits highlight the value of a more global representation of populations in genetic studies.

Each year, blood transfusions save millions of lives. However, under current blood-matching practices, sensitization to non–self-antigens is an unavoidable adverse side effect of transfusion. We describe a universal donor typing platform that could be adopted by blood services worldwide to facilitate a universal extended blood-matching policy and reduce sensitization rates. This DNA-based test is capable of simultaneously typing most clinically relevant red blood cell (RBC), human platelet (HPA), and human leukocyte (HLA) antigens. Validation was performed, using samples from 7927 European, 27 South Asian, 21 East Asian, and 9 African blood donors enrolled in 2 national biobanks. We illustrated the usefulness of the platform by analyzing antibody data from patients sensitized with multiple RBC alloantibodies. Genotyping results demonstrated concordance of 99.91%, 99.97%, and 99.03% with RBC, HPA, and HLA clinically validated typing results in 89 371, 3016, and 9289 comparisons, respectively. Genotyping increased the total number of antigen typing results available from 110 980 to >1 200 000. Dense donor typing allowed identification of 2 to 6 times more compatible donors to serve 3146 patients with multiple RBC alloantibodies, providing at least 1 match for 176 individuals for whom previously no blood could be found among the same donors. This genotyping technology is already being used to type thousands of donors taking part in national genotyping studies. Extraction of dense antigen-typing data from these cohorts provides blood supply organizations with the opportunity to implement a policy of genomics-based precision matching of blood.

Objective To investigate the association of plasma vitamin C and carotenoids, as indicators of fruit and vegetable intake, with the risk of type 2 diabetes. Design Prospective case-cohort study. Setting Populations from eight European countries. Participants 9754 participants with incident type 2 diabetes, and a subcohort of 13 662 individuals from the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort of 340 234 participants: EPIC-InterAct case-cohort study. Main outcome measure Incident type 2 diabetes. Results In a multivariable adjusted model, higher plasma vitamin C was associated with a lower risk of developing type 2 diabetes (hazard ratio per standard deviation 0.82, 95% confidence interval 0.76 to 0.89). A similar inverse association was shown for total carotenoids (hazard ratio per standard deviation 0.75, 0.68 to 0.82). A composite biomarker score (split into five equal groups), comprising vitamin C and individual carotenoids, was inversely associated with type 2 diabetes with hazard ratios 0.77, 0.66, 0.59, and 0.50 for groups 2-5 compared with group 1 (the lowest group). Self-reported median fruit and vegetable intake was 274 g/day, 396 g/day, and 508 g/day for participants in categories defined by groups 1, 3, and 5 of the composite biomarker score, respectively. One standard deviation difference in the composite biomarker score, equivalent to a 66 (95% confidence interval 61 to 71) g/day difference in total fruit and vegetable intake, was associated with a hazard ratio of 0.75 (0.67 to 0.83). This would be equivalent to an absolute risk reduction of 0.95 per 1000 person years of follow up if achieved across an entire population with the characteristics of the eight European countries included in this analysis. Conclusions These findings indicate an inverse association between plasma vitamin C, carotenoids, and their composite biomarker score, and incident type 2 diabetes in different European countries. These biomarkers are objective indicators of fruit and vegetable consumption, and suggest that diets rich in even modestly higher fruit and vegetable consumption could help to prevent development of type 2 diabetes.

Leukocyte telomere length (LTL) is a heritable biomarker of genomic aging. In this study, we perform a genome-wide meta-analysis of LTL by pooling densely genotyped and imputed association results across large-scale European-descent studies including up to 78,592 individuals. We identify 49 genomic regions at a false dicovery rate (FDR) < 0.05 threshold and prioritize genes at 31, with five highlighting nucleotide metabolism as an important regulator of LTL. We report six genome-wide significant loci in or near SENP7, MOB1B, CARMIL1, PRRC2A, TERF2, and RFWD3, and our results support recently identified PARP1, POT1, ATM, and MPHOSPH6 loci. Phenome-wide analyses in >350,000 UK Biobank participants suggest that genetically shorter telomere length increases the risk of hypothyroidism and decreases the risk of thyroid cancer, lymphoma, and a range of proliferative conditions. Our results replicate previously reported associations with increased risk of coronary artery disease and lower risk for multiple cancer types. Our findings substantially expand current knowledge on genes that regulate LTL and their impact on human health and disease.

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health.

Analyzing 12,361 all-cause cirrhosis cases and 790,095 controls from eight cohorts, we identify a common missense variant in the Mitochondrial Amidoxime Reducing Component 1 gene (MARC1 p.A165T) that associates with protection from all-cause cirrhosis (OR 0.91, p = 2.3*10−11). This same variant also associates with lower levels of hepatic fat on computed tomographic imaging and lower odds of physician-diagnosed fatty liver as well as lower blood levels of alanine transaminase (-0.025 SD, 3.7*10−43), alkaline phosphatase (-0.025 SD, 1.2*10−37), total cholesterol (-0.030 SD, p = 1.9*10−36) and LDL cholesterol (-0.027 SD, p = 5.1*10−30) levels. We identified a series of additional MARC1 alleles (low-frequency missense p.M187K and rare protein-truncating p.R200Ter) that also associated with lower cholesterol levels, liver enzyme levels and reduced risk of cirrhosis (0 cirrhosis cases for 238 R200Ter carriers versus 17,046 cases of cirrhosis among 759,027 non-carriers, p = 0.04) suggesting that deficiency of the MARC1 enzyme may lower blood cholesterol levels and protect against cirrhosis., Author summary Cirrhosis is a leading cause of death worldwide. However, the genetic underpinnings of cirrhosis remain poorly understood. In this study, we analyze twelve thousand individuals with cirrhosis and identify a common missense variant in a gene called MARC1 that protects against cirrhosis. Carriers of this missense variant also have lower blood cholesterol levels, lower liver enzyme levels and reduced liver fat. We identify an additional two low-frequency coding variants in MARC1 that are also associated with lower cholesterol levels, lower liver enzyme levels and protection from cirrhosis. Finally, we identify an individual homozygous for a predicted loss-of-function variant in MARC1 who exhibits very low blood LDL cholesterol levels. These genetic findings suggest that MARC1 deficiency may lower blood cholesterol levels and protect against cirrhosis, pointing to MARC1 as a potential therapeutic target for liver disease.

Supplemental Digital Content is available in the text., Background: Coronary artery disease (CAD) is accelerated in subjects with type 2 diabetes mellitus (T2D). Methods: To test whether this reflects differential genetic influences on CAD risk in subjects with T2D, we performed a systematic assessment of genetic overlap between CAD and T2D in 66 643 subjects (27 708 with CAD and 24 259 with T2D). Variants showing apparent association with CAD in stratified analyses or evidence of interaction were evaluated in a further 117 787 subjects (16 694 with CAD and 11 537 with T2D). Results: None of the previously characterized CAD loci was found to have specific effects on CAD in T2D individuals, and a genome-wide interaction analysis found no new variants for CAD that could be considered T2D specific. When we considered the overall genetic correlations between CAD and its risk factors, we found no substantial differences in these relationships by T2D background. Conclusions: This study found no evidence that the genetic architecture of CAD differs in those with T2D compared with those without T2D.

Analyses were supported by the UK Medical Research Council (MR/M012190/1), Cancer Research UK (C8221/A19170 and 570/A16491) and the Wellcome Trust (Our Planet Our Health, Livestock Environment and People 205212/Z/16/Z). A.P.C. is supported by a Cancer Research UK Population Research Fellowship (C60192/A28516) and by the World Cancer Research Fund (WCRF UK), as part of the Word Cancer Research Fund International grant programme (2019/1953). EPIC-CVD has been supported by the European Union Framework 7 (HEALTH-F2-2012-279233), the European Research Council (268834), the UK Medical Research Council (G0800270 and MR/L003120/1), the British Heart Foundation (SP/09/002 and RG/08/014 and RG13/13/30194) and the UK National Institute of Health Research. The InterAct project was funded by the EU FP6 programme (grant number LSHM_CT_2006_037197) and provided the biomarker data in the sub-cohort that was used in the current study. The coordination of EPIC is financially supported by the European Commission (DGSANCO) and the International Agency for Research on Cancer. The national cohorts are supported by: Danish Cancer Society (Denmark); Ligue Contre le Cancer, Institut Gustave Roussy, Mutuelle Ge ' ne ' rale de l'Education Nationale, Institut National de la Sante ' et de la Recherche Me ' dicale (INSERM) (France); German Cancer Aid, German Cancer Research Center (DKFZ), Federal Ministry of Education and Research (BMBF) (Germany); the Hellenic Health Foundation (Greece); Associazione Italiana per la Ricerca sul Cancro-AIRC-Italy and National Research Council (Italy); Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Dutch ZON (Zorg Onderzoek Nederland), World Cancer Research Fund (WCRF); Health Research Fund (FIS), PI13/00061 to Granada, PI13/01162 to EPIC-Murcia, Regional Governments of Andaluci ' a, Asturias, Basque Country, Murcia (no. 6236) and Navarra, ISCIII RETIC (RD06/0020) (Spain); Swedish Cancer Society, Swedish Research Council and County Councils of Ska degrees ne and Va sterbotten (Sweden); Cancer Research UK (14136 to EPIC-Norfolk; C570/A16491 and C8221/A19170 to EPIC-Oxford), UK Medical Research Council [1000143 to EPIC-Norfolk, MR/M012190/1 to EPIC-Oxford, MC_UU_12015/1 (N.J.W.), MC_UU_12015/5 (NGF), and MC_UU_12015/520], and NIHR Biomedical Research Centre Cambridge: Nutrition, Diet, and Lifestyle Research Theme (IS-BRC-1215-20014) to the MRC Epidemiology Unit Cambridge (N.J.W., N.G.F.). J.D. holds a British Heart Foundation Chair and an NIHR Senior Investigator Award. K.E.B. holds a Girdlers' New Zealand Health Research Council Fellowship. J.D. is funded by the National Institute for Health Research [Senior Investigator Award] [*]. A.W is supported by a BHF-Turing Cardiovascular Data Science Award and by the ECInnovative Medicines Initiative (BigData@Heart).M.S.reports funding from the Alpro Foundation whilst at the Cardiovascular Epidemiology Unit (up to 15-08-2016), and Core MRC Unit support through the Nutritional Epidemiology Programme (MC_UU_12015/5) whilst at the MRC Epidemiology Unit (15-08-2016 until now), during the conduct of the study., The authors thank all participants in the EPIC cohort for their invaluable contribution to the study., Epidemiological evidence indicates that diets rich in plant foods are associated with a lower risk of ischaemic heart disease (IHD), but there is sparse information on fruit and vegetable subtypes and sources of dietary fibre. This study examined the associations of major plant foods, their subtypes and dietary fibre with risk of IHD in the European Prospective Investigation into Cancer and Nutrition (EPIC). Methods We conducted a prospective analysis of 490 311 men and women without a history of myocardial infarction or stroke at recruitment (12.6 years of follow-up, n cases = 8504), in 10 European countries. Dietary intake was assessed using validated questionnaires, calibrated with 24-h recalls. Multivariable Cox regressions were used to estimate hazard ratios (HR) of IHD. Results There was a lower risk of IHD with a higher intake of fruit and vegetables combined [HR per 200 g/day higher intake 0.94, 95% confidence interval (CI): 0.90–0.99, P-trend = 0.009], and with total fruits (per 100 g/day 0.97, 0.95–1.00, P-trend = 0.021). There was no evidence for a reduced risk for fruit subtypes, except for bananas. Risk was lower with higher intakes of nuts and seeds (per 10 g/day 0.90, 0.82–0.98, P-trend = 0.020), total fibre (per 10 g/day 0.91, 0.85–0.98, P-trend = 0.015), fruit and vegetable fibre (per 4 g/day 0.95, 0.91–0.99, P-trend = 0.022) and fruit fibre (per 2 g/day 0.97, 0.95–1.00, P-trend = 0.045). No associations were observed between vegetables, vegetables subtypes, legumes, cereals and IHD risk. Conclusions In this large prospective study, we found some small inverse associations between plant foods and IHD risk, with fruit and vegetables combined being the most strongly inversely associated with risk. Whether these small associations are causal remains unclear., UK Research & Innovation (UKRI) Medical Research Council UK (MRC) MR/M012190/1 G0800270 MR/L003120/1 1000143 MC_UU_12015/1 MC_UU_12015/5 MC_UU_12015/520, Cancer Research UK C8221/A19170 570/A16491 14136 C570/A16491, Wellcome Trust (Our Planet Our Health, Livestock Environment and People) 205212/Z/16/Z, Cancer Research UK Population Research Fellowship C60192/A28516, World Cancer Research Fund (WCRF UK), as part of the Word Cancer Research Fund International grant programme 2019/1953, European Commission HEALTH-F2-2012-279233, European Research Council (ERC) European Commission 268834, British Heart Foundation SP/09/002 RG/08/014 RG13/13/30194, National Institute for Health Research (NIHR), European Commission LSHM_CT_2006_037197, European Commission European Commission Joint Research Centre, International Agency for Research on Cancer, Danish Cancer Society, Ligue Contre le Cancer (France), Institut Gustave Roussy (France), Mutuelle Generale de l'Education Nationale (France), Institut National de la Sante et de la Recherche Medicale (Inserm), Deutsche Krebshilfe, German Cancer Research Center (DKFZ) (Germany), Federal Ministry of Education & Research (BMBF), Hellenic Health Foundation (Greece), Associazione Italiana per la Ricerca sul Cancro (AIRC), Consiglio Nazionale delle Ricerche (CNR), Dutch Ministry of Public Health, Welfare and Sports (VWS), Netherlands Cancer Registry (NKR), LK Research Funds, Dutch Prevention Funds, Netherlands Organization for Scientific Research (NWO), World Cancer Research Fund International (WCRF), Instituto de Salud Carlos III PI13/00061 PI13/01162, Junta de Andalucia, Regional Government of Asturias (Spain), Regional Government of Basque Country (Spain), Regional Government of Murcia (Spain) 6236, Regional Government of Navarra (Spain), Instituto de Salud Carlos III RD06/0020, Swedish Cancer Society, Swedish Research Council, County Council of Skane (Sweden), County Council of Vasterbotten (Sweden), NIHR Biomedical Research Centre Cambridge: Nutrition, Diet, and Lifestyle Research Theme IS-BRC-1215-20014, British Heart Foundation, NIHR Senior Investigator Award, Girdlers' New Zealand Health Research Council Fellowship, BHF-Turing Cardiovascular Data Science Award, ECInnovative Medicines Initiative (BigData@Heart), Alpro Foundation 15-08-2016, Core MRC Unit support through the Nutritional Epidemiology Programme MC_UU_12015/5

Summary Blood cells play essential roles in human health, underpinning physiological processes such as immunity, oxygen transport, and clotting, which when perturbed cause a significant global health burden. Here we integrate data from UK Biobank and a large-scale international collaborative effort, including data for 563,085 European ancestry participants, and discover 5,106 new genetic variants independently associated with 29 blood cell phenotypes covering a range of variation impacting hematopoiesis. We holistically characterize the genetic architecture of hematopoiesis, assess the relevance of the omnigenic model to blood cell phenotypes, delineate relevant hematopoietic cell states influenced by regulatory genetic variants and gene networks, identify novel splice-altering variants mediating the associations, and assess the polygenic prediction potential for blood traits and clinical disorders at the interface of complex and Mendelian genetics. These results show the power of large-scale blood cell trait GWAS to interrogate clinically meaningful variants across a wide allelic spectrum of human variation., Graphical Abstract, Highlights • Largest genome-wide association study of blood cell traits to date • Empiric assessments of omnigenic and infinitesimal models of polygenic variation • Functional insights into how genetic variants impact human hematopoiesis • Assessment of the effect of polygenic trait scores upon blood diseases, Analysis of blood cell traits in the UK Biobank and other cohorts illuminates the full genetic architecture of hematopoietic phenotypes, with evidence supporting the omnigenic model for complex traits and linking polygenic burden with monogenic blood diseases.

Background Although lifestyle factors have been studied in relation to individual non-communicable diseases (NCDs), their association with development of a subsequent NCD, defined as multimorbidity, has been scarcely investigated. The aim of this study was to investigate associations between five lifestyle factors and incident multimorbidity of cancer and cardiometabolic diseases. Methods In this prospective cohort study, 291,778 participants (64% women) from seven European countries, mostly aged 43 to 58 years and free of cancer, cardiovascular disease (CVD), and type 2 diabetes (T2D) at recruitment, were included. Incident multimorbidity of cancer and cardiometabolic diseases was defined as developing subsequently two diseases including first cancer at any site, CVD, and T2D in an individual. Multi-state modelling based on Cox regression was used to compute hazard ratios (HR) and 95% confidence intervals (95% CI) of developing cancer, CVD, or T2D, and subsequent transitions to multimorbidity, in relation to body mass index (BMI), smoking status, alcohol intake, physical activity, adherence to the Mediterranean diet, and their combination as a healthy lifestyle index (HLI) score. Cumulative incidence functions (CIFs) were estimated to compute 10-year absolute risks for transitions from healthy to cancer at any site, CVD (both fatal and non-fatal), or T2D, and to subsequent multimorbidity after each of the three NCDs. Results During a median follow-up of 11 years, 1910 men and 1334 women developed multimorbidity of cancer and cardiometabolic diseases. A higher HLI, reflecting healthy lifestyles, was strongly inversely associated with multimorbidity, with hazard ratios per 3-unit increment of 0.75 (95% CI, 0.71 to 0.81), 0.84 (0.79 to 0.90), and 0.82 (0.77 to 0.88) after cancer, CVD, and T2D, respectively. After T2D, the 10-year absolute risks of multimorbidity were 40% and 25% for men and women, respectively, with unhealthy lifestyle, and 30% and 18% for men and women with healthy lifestyles. Conclusion Pre-diagnostic healthy lifestyle behaviours were strongly inversely associated with the risk of cancer and cardiometabolic diseases, and with the prognosis of these diseases by reducing risk of multimorbidity.