Complex patterns of multimorbidity associated with severe COVID-19 and long COVID.

BACKGROUND: Early evidence that patients with (multiple) pre-existing diseases are at highest risk for severe COVID-19 has been instrumental in the pandemic to allocate critical care resources and later vaccination schemes. However, systematic studies exploring the breadth of medical diagnoses are scarce but may help to understand severe COVID-19 among patients at supposedly low risk. METHODS: We systematically harmonized >12 million primary care and hospitalisation health records from ~500,000 UK Biobank participants into 1448 collated disease terms to systematically identify diseases predisposing to severe COVID-19 (requiring hospitalisation or death) and its post-acute sequalae, Long COVID. RESULTS: Here we identify 679 diseases associated with an increased risk for severe COVID-19 (n = 672) and/or Long COVID (n = 72) that span almost all clinical specialties and are strongly enriched in clusters of cardio-respiratory and endocrine-renal diseases. For 57 diseases, we establish consistent evidence to predispose to severe COVID-19 based on survival and genetic susceptibility analyses. This includes a possible role of symptoms of malaise and fatigue as a so far largely overlooked risk factor for severe COVID-19. We finally observe partially opposing risk estimates at known risk loci for severe COVID-19 for etiologically related diseases, such as post-inflammatory pulmonary fibrosis or rheumatoid arthritis, possibly indicating a segregation of disease mechanisms. CONCLUSIONS: Our results provide a unique reference that demonstrates how 1) complex co-occurrence of multiple - including non-fatal - conditions predispose to increased COVID-19 severity and 2) how incorporating the whole breadth of medical diagnosis can guide the interpretation of genetic risk loci.

Early in the COVID-19 pandemic it was clear that people with multiple chronic diseases were vulnerable and needed special protection, such as shielding. However, many people without such diseases required hospital care or died from COVID-19. Here, we investigated the importance of underlying diseases, including mild diseases not requiring hospitalization, for COVID-19 outcomes. Using information from electronic health records we find that many severe, but also less severe diseases increase the risk for severe COVID-19 and its impact on health even months after acute infection (Long COVID). This included an almost two-fold higher risk among people that reported poor well-being and fatigue. Our findings show the value of using primary care health records and the need to consider all the medical history of patients to identify those in need of special protection.

Complex patterns of multimorbidity associated with severe COVID-19 and Long COVID.

Early evidence that patients with (multiple) pre-existing diseases are at highest risk for severe COVID-19 has been instrumental in the pandemic to allocate critical care resources and later vaccination schemes. However, systematic studies exploring the breadth of medical diagnoses, including common, but non-fatal diseases are scarce, but may help to understand severe COVID-19 among patients at supposedly low risk. Here, we systematically harmonized >12 million primary care and hospitalisation health records from ~500,000 UK Biobank participants into 1448 collated disease terms to systematically identify diseases predisposing to severe COVID-19 (requiring hospitalisation or death) and its post-acute sequalae, Long COVID. We identified a total of 679 diseases associated with an increased risk for severe COVID-19 (n=672) and/or Long COVID (n=72) that spanned almost all clinical specialties and were strongly enriched in clusters of cardio-respiratory and endocrine-renal diseases. For 57 diseases, we established consistent evidence to predispose to severe COVID-19 based on survival and genetic susceptibility analyses. This included a possible role of symptoms of malaise and fatigue as a so far largely overlooked risk factor for severe COVID-19. We finally observed partially opposing risk estimates at known risk loci for severe COVID-19 for etiologically related diseases, such as post-inflammatory pulmonary fibrosis (e.g., MUC5B, NPNT, and PSMD3) or rheumatoid arthritis (e.g., TYK2), possibly indicating a segregation of disease mechanisms. Our results provide a unique reference that demonstrates how 1) complex co-occurrence of multiple - including non-fatal - conditions predispose to increased COVID-19 severity and 2) how incorporating the whole breadth of medical diagnosis can guide the interpretation of genetic risk loci.

Proteogenomic analyses identify coagulation factor XI as a thromboinflammatory mediator of long COVID.

SARS-CoV-2 infection can result in long COVID, characterized by post-acute symptoms from multiple organ systems. Current hypotheses on mechanisms underlying long COVID include persistent inflammation and dysregulated coagulation; however, precise mechanisms and causal mediators remain unclear. Here, we tested the associations of genetic instruments for 49 complement and coagulation factors from the UK Biobank ( N =34,557) with long COVID in the Long COVID Host Genetics Initiative ( N =997,600). Primary analyses revealed that genetically predicted higher factor XI increased long COVID risk (odds ratio, 1.17 [95% confidence interval, 1.08-1.27] per standard deviation; P =1.7×10 -4 ). This association was robust to sensitivity analyses using pleiotropy-robust methods and different genetic instruments and was replicated using proteogenomic data from an Icelandic cohort. Genetically predicted factor XI was also associated with venous thromboembolism, but not with acute COVID-19 or long COVID-resembling conditions. Collectively, these findings provide genetic evidence implicating factor XI in the biology of long COVID.

Sustained IFN signaling is associated with delayed development of SARS-CoV-2-specific immunity.

Plasma RNAemia, delayed antibody responses and inflammation predict COVID-19 outcomes, but the mechanisms underlying these immunovirological patterns are poorly understood. We profile 782 longitudinal plasma samples from 318 hospitalized patients with COVID-19. Integrated analysis using k-means reveals four patient clusters in a discovery cohort: mechanically ventilated critically-ill cases are subdivided into good prognosis and high-fatality clusters (reproduced in a validation cohort), while non-critical survivors segregate into high and low early antibody responders. Only the high-fatality cluster is enriched for transcriptomic signatures associated with COVID-19 severity, and each cluster has distinct RBD-specific antibody elicitation kinetics. Both critical and non-critical clusters with delayed antibody responses exhibit sustained IFN signatures, which negatively correlate with contemporaneous RBD-specific IgG levels and absolute SARS-CoV-2-specific B and CD4+ T cell frequencies. These data suggest that the "Interferon paradox" previously described in murine LCMV models is operative in COVID-19, with excessive IFN signaling delaying development of adaptive virus-specific immunity.

Metabolomic pattern associated with physical sequelae in patients presenting with respiratory symptoms validates the aestivation concept in dehydrated patients.

Hypertonic dehydration is associated with muscle wasting and synthesis of organic osmolytes. We recently showed a metabolic shift to amino acid production and urea cycle activation in coronavirus-2019 (COVID-19), consistent with the aestivation response. The aim of the present investigation was to validate the metabolic shift and development of long-term physical outcomes in the non-COVID cohort of the Biobanque Québécoise de la COVID-19 (BQC19). We included 824 patients from BQC19, where 571 patients had data of dehydration in the form of estimated osmolality (eOSM = 2Na + 2K + glucose + urea), and 284 patients had metabolome data and long-term follow-up. We correlated the degree of dehydration to mortality, invasive mechanical ventilation, acute kidney injury, and long-term symptoms. As found in the COVID cohort, higher eOSM correlated with a higher proportion of urea and glucose of total eOSM, and an enrichment of amino acids compared with other metabolites. Sex-stratified analysis indicated that women may show a weaker aestivation response. More severe dehydration was associated with mortality, invasive mechanical ventilation, and acute kidney injury during the acute illness. Importantly, more severe dehydration was associated with physical long-term symptoms but not mental long-term symptoms after adjustment for age, sex, and disease severity. Patients with water deficit in the form of increased eOSM tend to have more severe disease and experience more physical symptoms after an acute episode of care. This is associated with amino acid and urea production, indicating dehydration-induced muscle wasting.NEW & NOTEWORTHY We have previously shown that humans exhibit an aestivation-like response where dehydration leads to a metabolic shift to urea synthesis, which is associated with long-term weakness indicating muscle wasting. In the present study, we validate this response in a new cohort and present a deeper metabolomic analysis and pathway analysis. Finally, we present a sex-stratified analysis suggesting weaker aestivation in women. However, women show less dehydration, so the association warrants further study.

Cadmium accumulation dynamics in the rice endosperm during grain filling revealed by autoradiography.

Cadmium (Cd) is one of the environmental pollutants contaminated in our food. Several previous reports showed that rice polishing cannot be efficient to reduce Cd content in white rice, implying the characteristic Cd distribution in rice grain. However, Cd distribution has not been fully elucidated so far. Herein, 109Cd radiotracer experiment was performed using the rice seedlings at various time points after flowering to obtain autoradiographs of the brown rice to visually understand the Cd transport and distribution during the grain-filling process. It was shown that 109Cd accumulated in the outermost area of the brown rice, and also in the middle part of the starchy endosperm, resulting in the appearance of the double circle distribution pattern, which was not observed in the autoradiographs of 65Zn. The inner circle of 109Cd located around the center of the endosperm was developed particularly at around 8 and 10 days after flowering. After this period, 109Cd started to deposit at the outer part of the endosperm, which was also found in the autoradiograph of 14C-sucrose. Considering the physiology of grain development, the contribution of water transport and protein synthesis in the endosperm on the characteristic Cd distribution pattern was hypothesized.

Weekdays' sleeping condition and its influence on occurrence of general malaise in Japanese children aged 10 to 12 years.

The present study aimed to elucidate weekdays' sleeping condition and its influence on occurrence of general malaise in children. A total of 761 Japanese children aged 10 to 12 years were surveyed regarding their weekdays' waking time and bedtime and general malaise using a self-administered questionnaire. As the result of hierarchical cluster analysis on the sleep condition, the participants were classified into three clusters. Sleep duration was significantly longer in cluster 1 (9.35 ± 0.52 h) than in clusters 2 (7.83 ± 0.77 h) and 3 (9.02 ± 0.30 h) and significantly longer in cluster 3 than in cluster 2. Waking time was significantly later in cluster 3 (7:01 ± 0:12) than in clusters 1 (6:22 ± 0:31) and 2 (6:24 ± 0:33, p < 0.001). Bedtime was significantly later in cluster 2 (22:34 ± 0:47) than in clusters 3 (21:59 ± 0:19) and 1 (21:01 ± 0:22) and significantly later in cluster 3 than in cluster 1. There were significantly more subjects in cluster 2 than in clusters 1 and 3 who responded "nearly every day" or "occasionally" to the five of seven questionnaires related to general malaise. The current results indicate that in Japanese children aged 10 to 12 years, (1) sleeping condition of weekdays are classified into three clusters with different mean values for each of sleep duration, bedtime, and waking time, and (2) the occurrence of general malaise may be enhanced in individuals whose sleep duration is less than 8 h.