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.

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.

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.

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.

HLA allele-calling using multi-ancestry whole-exome sequencing from the UK Biobank identifies 129 novel associations in 11 autoimmune diseases.

The human leukocyte antigen (HLA) region on chromosome 6 is strongly associated with many immune-mediated and infection-related diseases. Due to its highly polymorphic nature and complex linkage disequilibrium patterns, traditional genetic association studies of single nucleotide polymorphisms do not perform well in this region. Instead, the field has adopted the assessment of the association of HLA alleles (i.e., entire HLA gene haplotypes) with disease. Often based on genotyping arrays, these association studies impute HLA alleles, decreasing accuracy and thus statistical power for rare alleles and in non-European ancestries. Here, we use whole-exome sequencing (WES) from 454,824 UK Biobank (UKB) participants to directly call HLA alleles using the HLA-HD algorithm. We show this method is more accurate than imputing HLA alleles and harness the improved statistical power to identify 360 associations for 11 auto-immune phenotypes (at least 129 likely novel), leading to better insights into the specific coding polymorphisms that underlie these diseases. We show that HLA alleles with synonymous variants, often overlooked in HLA studies, can significantly influence these phenotypes. Lastly, we show that HLA sequencing may improve polygenic risk scores accuracy across ancestries. These findings allow better characterization of the role of the HLA region in human disease.

Gene therapy for alopecia in type II rickets model rats using vitamin D receptor-expressing adenovirus vector.

Type II rickets is a hereditary disease caused by a mutation in the vitamin D receptor (VDR) gene. The main symptoms of this disease are bone dysplasia and alopecia. Bone dysplasia can be ameliorated by high calcium intake; however, there is no suitable treatment for alopecia. In this study, we verified whether gene therapy using an adenoviral vector (AdV) had a therapeutic effect on alopecia in Vdr-KO rats. The VDR-expressing AdV was injected into six 7-week-old female Vdr-KO rats (VDR-AdV rats). On the other hand, control-AdV was injected into 7-week-old female rats (control-AdV rats); non-infected Vdr-KO rats (control rats) were also examined. The hair on the backs of the rats was shaved with hair clippers, and VDR-AdV or control-AdV was intradermally injected. Part of the back skin was collected from each rat after AdV administration. Hair follicles were observed using hematoxylin and eosin staining, and VDR expression was examined using immunostaining and western blotting. VDR-AdV rats showed significant VDR expression in the skin, enhanced hair growth, and low cyst formation, whereas control-AdV and non-infected rats did not show any of these effects. The effect of VDR-AdV lasted for nearly 60 days. These results indicate that gene therapy using VDR-AdV may be useful to treat alopecia associated with type II rickets, if multiple injections are possible after a sufficient period of time.

Alternative splicing in lung influences COVID-19 severity and respiratory diseases.

Alternative splicing generates functional diversity in isoforms, impacting immune response to infection. Here, we evaluate the causal role of alternative splicing in COVID-19 severity and susceptibility by applying two-sample Mendelian randomization to cis-splicing quantitative trait loci and the results from COVID-19 Host Genetics Initiative. We identify that alternative splicing in lung, rather than total expression of OAS1, ATP11A, DPP9 and NPNT, is associated with COVID-19 severity. MUC1 and PMF1 splicing is associated with COVID-19 susceptibility. Colocalization analyses support a shared genetic mechanism between COVID-19 severity with idiopathic pulmonary fibrosis at the ATP11A and DPP9 loci, and with chronic obstructive lung diseases at the NPNT locus. Last, we show that ATP11A, DPP9, NPNT, and MUC1 are highly expressed in lung alveolar epithelial cells, both in COVID-19 uninfected and infected samples. These findings clarify the importance of alternative splicing in lung for COVID-19 and respiratory diseases, providing isoform-based targets for drug discovery.

Colocalization of expression transcripts with COVID-19 outcomes is rare across cell states, cell types and organs.

Identifying causal genes at GWAS loci can help pinpoint targets for therapeutic interventions. Expression studies can disentangle such loci but signals from expression quantitative trait loci (eQTLs) often fail to colocalize-which means that the genetic control of measured expression is not shared with the genetic control of disease risk. This may be because gene expression is measured in the wrong cell type, physiological state, or organ. We tested whether Mendelian randomization (MR) could identify genes at loci influencing COVID-19 outcomes and whether the colocalization of genetic control of expression and COVID-19 outcomes was influenced by cell type, cell stimulation, and organ. We conducted MR of cis-eQTLs from single cell (scRNA-seq) and bulk RNA sequencing. We then tested variables that could influence colocalization, including cell type, cell stimulation, RNA sequencing modality, organ, symptoms of COVID-19, and SARS-CoV-2 status among individuals with symptoms of COVID-19. The outcomes used to test colocalization were COVID-19 severity and susceptibility as assessed in the Host Genetics Initiative release 7. Most transcripts identified using MR did not colocalize when tested across cell types, cell state and in different organs. Most that did colocalize likely represented false positives due to linkage disequilibrium. In general, colocalization was highly variable and at times inconsistent for the same transcript across cell type, cell stimulation and organ. While we identified factors that influenced colocalization for select transcripts, identifying 33 that mediate COVID-19 outcomes, our study suggests that colocalization of expression with COVID-19 outcomes is partially due to noisy signals even after following quality control and sensitivity testing. These findings illustrate the present difficulty of linking expression transcripts to disease outcomes and the need for skepticism when observing eQTL MR results, even accounting for cell types, stimulation state and different organs.

Dose-dependent Association of Alcohol Consumption With Obesity and Type 2 Diabetes: Mendelian Randomization Analyses.

CONTEXT: Effects of modest alcohol consumption remain controversial. Mendelian randomization (MR) can help to mitigate biases due to confounding and reverse causation in observational studies, and evaluate the potential causal role of alcohol consumption. OBJECTIVE: This work aimed to evaluate dose-dependent effect of alcohol consumption on obesity and type 2 diabetes. METHODS: Assessing 408 540 participants of European ancestry in the UK Biobank, we first tested the association between self-reported alcohol intake frequency and 10 anthropometric measurements, obesity, and type 2 diabetes. We then conducted MR analyses both in the overall population and in subpopulations stratified by alcohol intake frequency. RESULTS: Among individuals having more than 14 drinks per week, a 1-drink-per-week increase in genetically predicted alcohol intake frequency was associated with a 0.36-kg increase in fat mass (SD = 0.03 kg), a 1.08-fold increased odds of obesity (95% CI, 1.06-1.10), and a 1.10-fold increased odds of type 2 diabetes (95% CI, 1.06-1.13). These associations were stronger in women than in men. Furthermore, no evidence was found supporting the association between genetically increased alcohol intake frequency and improved health outcomes among individuals having 7 or fewer drinks per week, as MR estimates largely overlapped with the null. These results withstood multiple sensitivity analyses assessing the validity of MR assumptions. CONCLUSION: As opposed to observational associations, MR results suggest there may not be protective effects of modest alcohol consumption on obesity traits and type 2 diabetes. Heavy alcohol consumption could lead to increased measures of obesity as well as increased risk of type 2 diabetes.

Circulating proteins to predict COVID-19 severity.

Predicting COVID-19 severity is difficult, and the biological pathways involved are not fully understood. To approach this problem, we measured 4701 circulating human protein abundances in two independent cohorts totaling 986 individuals. We then trained prediction models including protein abundances and clinical risk factors to predict COVID-19 severity in 417 subjects and tested these models in a separate cohort of 569 individuals. For severe COVID-19, a baseline model including age and sex provided an area under the receiver operator curve (AUC) of 65% in the test cohort. Selecting 92 proteins from the 4701 unique protein abundances improved the AUC to 88% in the training cohort, which remained relatively stable in the testing cohort at 86%, suggesting good generalizability. Proteins selected from different COVID-19 severity were enriched for cytokine and cytokine receptors, but more than half of the enriched pathways were not immune-related. Taken together, these findings suggest that circulating proteins measured at early stages of disease progression are reasonably accurate predictors of COVID-19 severity. Further research is needed to understand how to incorporate protein measurement into clinical care.

Expression of Rat Cyp27b1 in HepG2 Cells Using Adenovirus Vector and Its Application to Evaluation of Self-Made and Commercially Available Anti-Cyp27b1 Antibodies.

Rat Cyp27b1 was successfully expressed in HepG2 cells using an adenovirus vector. High vitamin D 1α-hydroxylation activity was detected in them, whereas no activity was observed in non-infected cells. Similarly, vitamin D 1α-hydroxylation activity was also observed in HepG2 cells expressing Cyp27b1-Flag, which is tagged with a Flag at the C-terminus of Cyp27b1. Western blot analysis using an anti-Flag antibody showed a clear band of Cyp27b1-Flag. Next, we screened three types of anti-Cyp27b1 antibodies, which consist of two commercially available antibodies and our self-made antibody using Cyp27b1- or Cyp27b1-Flag expressing HepG2 cell lysate as a positive control. Surprisingly, Western blot analysis revealed that two commercially available antibodies did not detect Cyp27b1 but specifically detect other proteins. In contrast, our self-made antisera specifically detected Cyp27b1 and Cyp27b1-Flag in the HepG2 cells expressing Cyp27b1 or Cyp27b1-Flag. These commercially available antibodies have been used for the detection of Cyp27b1 by Western blotting and immunohistochemistry. Our results suggest that those data should be reanalyzed.

Increasing serum iron levels and their role in the risk of infectious diseases: a Mendelian randomization approach.

OBJECTIVES: Increased iron stores have been associated with elevated risks of different infectious diseases, suggesting that iron supplementation may increase the risk of infections. However, these associations may be biased by confounding or reverse causation. This is important, since up to 19% of the population takes iron supplementation. We used Mendelian randomization (MR) to bypass these biases and estimate the causal effect of iron on infections. METHODS: As instrumental variables, we used genetic variants associated with iron biomarkers in two genome-wide association studies (GWASs) of European ancestry participants. For outcomes, we used GWAS results from the UK Biobank, FinnGen, the COVID-19 Host Genetics Initiative or 23andMe, for seven infection phenotypes: 'any infections', combined, COVID-19 hospitalization, candidiasis, pneumonia, sepsis, skin and soft tissue infection (SSTI) and urinary tract infection (UTI). RESULTS: Most of our analyses showed increasing iron (measured by its biomarkers) was associated with only modest changes in the odds of infectious outcomes, with all 95% odds ratios confidence intervals within the 0.88 to 1.26 range. However, for the three predominantly bacterial infections (sepsis, SSTI, UTI), at least one analysis showed a nominally elevated risk with increased iron stores (P <0.05). CONCLUSION: Using MR, we did not observe an increase in risk of most infectious diseases with increases in iron stores. However for bacterial infections, higher iron stores may increase odds of infections. Hence, using genetic variation in iron pathways as a proxy for iron supplementation, iron supplements are likely safe on a population level, but we should continue the current practice of conservative iron supplementation during bacterial infections or in those at high risk of developing them.

Proteome-wide Mendelian randomization implicates nephronectin as an actionable mediator of the effect of obesity on COVID-19 severity.

Obesity is a major risk factor for Coronavirus disease (COVID-19) severity; however, the mechanisms underlying this relationship are not fully understood. As obesity influences the plasma proteome, we sought to identify circulating proteins mediating the effects of obesity on COVID-19 severity in humans. Here, we screened 4,907 plasma proteins to identify proteins influenced by body mass index using Mendelian randomization. This yielded 1,216 proteins, whose effect on COVID-19 severity was assessed, again using Mendelian randomization. We found that an s.d. increase in nephronectin (NPNT) was associated with increased odds of critically ill COVID-19 (OR = 1.71, P = 1.63 × 10-10). The effect was driven by an NPNT splice isoform. Mediation analyses supported NPNT as a mediator. In single-cell RNA-sequencing, NPNT was expressed in alveolar cells and fibroblasts of the lung in individuals who died of COVID-19. Finally, decreasing body fat mass and increasing fat-free mass were found to lower NPNT levels. These findings provide actionable insights into how obesity influences COVID-19 severity.

Functional analysis of vitamin D receptor (VDR) using adenovirus vector.

Recently, we generated type II rickets model rats, including Vdr(R270L), Vdr(H301Q), Vdr(R270L/H301Q), and Vdr-knockout (KO), by genome editing. All generated animals showed symptoms of rickets, including growth retardation and abnormal bone formation. Among these, only Vdr-KO rats exhibited abnormal skin formation and alopecia. To elucidate the relationship between VDR function and rickets symptoms, each VDR was expressed in human HaCaT-VDR-KO cells using an adenovirus vector. We also constructed an adenovirus vector expressing VDR(V342M) corresponding to human VDR(V346M) which causes alopecia. We compared the nuclear translocation of VDRs after adding 1α,25-dihydroxyvitamin D3 (1,25D3) or 25-hydroxyvitamin D3 (25D3) at final concentrations of 10 and 100 nM, respectively. Both 25D3 and 1,25D3 induced the nuclear translocation of wild type VDR and VDR(V342M). Conversely, VDR(R270L) translocation was observed in the presence of 100 nM 25D3, with almost no translocation following treatment with 10 nM 1,25D3. VDR(R270L/H301Q) failed to undergo nuclear translocation. These results were consistent with their affinity for each ligand. Notably, VDR(R270L/H301Q) may exist in an unliganded form under physiological conditions, and factors interacting with VDR(R270L/H301Q) may be involved in the hair growth cycle. Thus, this novel system using an adenovirus vector could be valuable in elucidating vitamin D receptor functions.

Mutations in RZF1, a zinc-finger protein, reduce magnesium uptake in roots and translocation to shoots in rice.

Magnesium (Mg) homeostasis is critical for maintaining many biological processes, but little information is available to comprehend the molecular mechanisms regulating Mg concentration in rice (Oryza sativa). To make up for the lack of information, we aimed to identify mutants defective in Mg homeostasis through a forward genetic approach. As a result of the screening of 2,825 M2 seedlings mutated by ion-beam irradiation, we found a rice mutant that showed reduced Mg content in leaves and slightly increased Mg content in roots. Radiotracer 28Mg experiments showed that this mutant, named low-magnesium content 1 (LMGC1), has decreased Mg2+ influx in the root and Mg2+ translocation from root to shoot. Consequently, LMGC1 is sensitive to the low Mg condition and prone to develop chlorosis in the young mature leaf. The MutMap method identified a 7.4-kbp deletion in the LMGC1 genome leading to a loss of two genes. Genome editing using CRISPR-Cas9 further revealed that one of the two lost genes, a gene belonging to the RanBP2-type zinc-finger family that we named RanBP2-TYPE ZINC FINGER1 (OsRZF1), was the causal gene of the low Mg phenotype. OsRZF1 is a nuclear protein and may have a fundamental role in maintaining Mg homeostasis in rice plants.

Genomic atlas of the plasma metabolome prioritizes metabolites implicated in human diseases.

Metabolic processes can influence disease risk and provide therapeutic targets. By conducting genome-wide association studies of 1,091 blood metabolites and 309 metabolite ratios, we identified associations with 690 metabolites at 248 loci and associations with 143 metabolite ratios at 69 loci. Integrating metabolite-gene and gene expression information identified 94 effector genes for 109 metabolites and 48 metabolite ratios. Using Mendelian randomization (MR), we identified 22 metabolites and 20 metabolite ratios having estimated causal effect on 12 traits and diseases, including orotate for estimated bone mineral density, α-hydroxyisovalerate for body mass index and ergothioneine for inflammatory bowel disease and asthma. We further measured the orotate level in a separate cohort and demonstrated that, consistent with MR, orotate levels were positively associated with incident hip fractures. This study provides a valuable resource describing the genetic architecture of metabolites and delivers insights into their roles in common diseases, thereby offering opportunities for therapeutic targets.

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.