A comprehensive benchmark for COVID-19 predictive modeling using electronic health records in intensive care.

The COVID-19 pandemic highlighted the need for predictive deep-learning models in health care. However, practical prediction task design, fair comparison, and model selection for clinical applications remain a challenge. To address this, we introduce and evaluate two new prediction tasks-outcome-specific length-of-stay and early-mortality prediction for COVID-19 patients in intensive care-which better reflect clinical realities. We developed evaluation metrics, model adaptation designs, and open-source data preprocessing pipelines for these tasks while also evaluating 18 predictive models, including clinical scoring methods and traditional machine-learning, basic deep-learning, and advanced deep-learning models, tailored for electronic health record (EHR) data. Benchmarking results from two real-world COVID-19 EHR datasets are provided, and all results and trained models have been released on an online platform for use by clinicians and researchers. Our efforts contribute to the advancement of deep-learning and machine-learning research in pandemic predictive modeling.

Preconception folic acid supplementation for the prevention of birth defects: a prospective, population-based cohort study in mainland China.

BACKGROUND: Folic acid supplementation is recommended for reducing the risk of birth defects. We aimed to assess the protective association of periconception folic acid supplements with birth defects in real-world setting. METHODS: This prospective, population-based cohort study utilized national preconception registered data of married Chinese couples planning a pregnancy within 6 months between 2010 and 2012 in Mainland China. Participated women are freely provided folic acid starting 3 months before conception till 3 months after conception. Birth defects were self-reported at 42 days postpartumn followup. R software (v4.0.2) was applied for statistical analyses. RESULTS: Complete data of 567,547 couples with pregnancy outcomes and folic acid supplementation were extracted for final analysis. A total of 74.7% women were with folic acid supplementation, and 599 birth defects were self-reported. The odd of birth defects was lower among women taking folic acid compared to their counterparts not taking (0.102% vs 0.116%, P < 0.001). In the multiple logistic regression analyses, the odd of birth defects was lower among couples with maternal folic acid supplementation (OR = 0.78, 95%CI: 0.66-0.95, P = 0.011), especially decreased odd of neural tube defects (NTDs) (OR = 0.56, 95%CI: 0.39-0.82, P = 0.003). This association was confirmed by 1:4 and 1:10 case control analysis. Odds of birth defects were significantly lower among women with folic acid supplementation more than 3 months before pregnancy (P < 0.001), and moreover, the odds of cleft (P = 0.007) and NTDs (P = 0.007) were of notable decrease. CONCLUSION: This retrospective case cohort study provides programmatic evidence for public health strategy-making to for reducing the risk of NTDs and clefts.

Common and disorder-specific cortical thickness alterations in internalizing, externalizing and thought disorders during early adolescence: an Adolescent Brain and Cognitive Development study.

BACKGROUND: A growing body of neuroimaging studies has reported common neural abnormalities among mental disorders in adults. However, it is unclear whether the distinct disorder-specific mechanisms operate during adolescence despite the overlap among disorders. METHODS: We studied a large cohort of more than 11 000 preadolescent (age 9-10 yr) children from the Adolescent Brain and Cognitive Development cohort. We adopted a regrouping approach to compare cortical thickness (CT) alterations and longitudinal changes between healthy controls (n = 4041) and externalizing (n = 1182), internalizing (n = 1959) and thought disorder (n = 347) groups. Genome-wide association study (GWAS) was performed on regional CT across 4468 unrelated European youth. RESULTS: Youth with externalizing or internalizing disorders exhibited increased regional CT compared with controls. Externalizing (p = 8 × 10-4, Cohen d = 0.10) and internalizing disorders (p = 2 × 10-3, Cohen d = 0.08) shared thicker CT in the left pars opercularis. The somatosensory and the primary auditory cortex were uniquely affected in externalizing disorders, whereas the primary motor cortex and higher-order visual association areas were uniquely affected in internalizing disorders. Only youth with externalizing disorders showed decelerated cortical thinning from age 10-12 years. The GWAS found 59 genome-wide significant associated genetic variants across these regions. Cortical thickness in common regions was associated with glutamatergic neurons, while internalizing-specific regional CT was associated with astrocytes, oligodendrocyte progenitor cells and GABAergic neurons. LIMITATIONS: The sample size of the GWAS was relatively small. CONCLUSION: Our study provides strong evidence for the presence of specificity in CT, developmental trajectories and underlying genetic underpinnings among externalizing and internalizing disorders during early adolescence. Our results support the neurobiological validity of the regrouping approach that could supplement the use of a dimensional approach in future clinical practice.

Neurodevelopmental risk and adaptation as a model for comorbidity among internalizing and externalizing disorders: genomics and cell-specific expression enriched morphometric study.

BACKGROUND: Comorbidity is the rule rather than the exception for childhood and adolescent onset mental disorders, but we cannot predict its occurrence and do not know the neural mechanisms underlying comorbidity. We investigate if the effects of comorbid internalizing and externalizing disorders on anatomical differences represent a simple aggregate of the effects on each disorder and if these comorbidity-associated cortical surface differences relate to a distinct genetic underpinning. METHODS: We studied the cortical surface area (SA) and thickness (CT) of 11,878 preadolescents (9-10 years) from the Adolescent Brain and Cognitive Development Study. Linear mixed models were implemented in comparative and association analyses among internalizing (dysthymia, major depressive disorder, disruptive mood dysregulation disorder, agoraphobia, panic disorder, specific phobia, separation anxiety disorder, social anxiety disorder, generalized anxiety disorder, post-traumatic stress disorder), externalizing (attention-deficit/hyperactivity disorder, oppositional defiant disorder, conduct disorder) diagnostic groups, a group with comorbidity of the two and a healthy control group. Genome-wide association analysis (GWAS) and cell type specificity analysis were performed on 4468 unrelated European participants from this cohort. RESULTS: Smaller cortical surface area but higher thickness was noted across patient groups when compared to controls. Children with comorbid internalizing and externalizing disorders had more pronounced areal reduction than those without comorbidity, indicating an additive burden. In contrast, cortical thickness had a non-linear effect with comorbidity: the comorbid group had no significant CT differences, while those patient groups without comorbidity had significantly higher thickness compare to healthy controls. Distinct biological pathways were implicated in regional SA and CT differences. Specifically, CT differences were associated with immune-related processes implicating astrocytes and oligodendrocytes, while SA-related differences related mainly to inhibitory neurons. CONCLUSION: The emergence of comorbidity across distinct clusters of psychopathology is unlikely to be due to a simple additive neurobiological effect alone. Distinct developmental risk moderated by immune-related adaptation processes, with unique genetic and cell-specific factors, may contribute to underlying SA and CT differences. Children with the highest risk but lowest resilience, both captured in their developmental morphometry, may develop a comorbid illness pattern.

Improving Alzheimer's Disease Diagnosis With Multi-Modal PET Embedding Features by a 3D Multi-Task MLP-Mixer Neural Network.

Positron emission tomography (PET) with fluorodeoxyglucose (FDG) or florbetapir (AV45) has been proved effective in the diagnosis of Alzheimer's disease. However, the expensive and radioactive nature of PET has limited its application. Here, employing multi-layer perceptron mixer architecture, we present a deep learning model, namely 3-dimensional multi-task multi-layer perceptron mixer, for simultaneously predicting the standardized uptake value ratios (SUVRs) for FDG-PET and AV45-PET from the cheap and widely used structural magnetic resonance imaging data, and the model can be further used for Alzheimer's disease diagnosis based on embedding features derived from SUVR prediction. Experiment results demonstrate the high prediction accuracy of the proposed method for FDG/AV45-PET SUVRs, where we achieved Pearson's correlation coefficients of 0.66 and 0.61 respectively between the estimated and actual SUVR and the estimated SUVRs also show high sensitivity and distinct longitudinal patterns for different disease status. By taking into account PET embedding features, the proposed method outperforms other competing methods on five independent datasets in the diagnosis of Alzheimer's disease and discriminating between stable and progressive mild cognitive impairments, achieving the area under receiver operating characteristic curves of 0.968 and 0.776 respectively on ADNI dataset, and generalizes better to other external datasets. Moreover, the top-weighted patches extracted from the trained model involve important brain regions related to Alzheimer's disease, suggesting good biological interpretability of our proposed method."

Comparison of clinical characteristics of first-episode thrombotic thrombocytopenic purpura and TTP-like syndrome: a retrospective cohort study in a level I hematology center in China.

Comparing the characteristics of thrombotic thrombocytopenic purpura (TTP) and TTP-like syndrome patients at admission will allow early differentiation of TTP from TTP-like syndrome and help tailor initial treatment. The medical records of 78 patients with suspected TTP in the Emergency Department of Peking University People's Hospital in the past 5 years were retrospectively analyzed and divided into TTP and TTP-like syndrome groups based on ADAMTS13 activity and ADAMTS13 antibody titer. There were 25 and 53 patients in the TTP group and the TTP-like syndrome group, respectively. The neutrophil-to-lymphocyte ratio (P = 0.025) was tremendously higher, and albumin (P = 0.002) was lower in the TTP-like syndrome group, indicating a more severe inflammation. Compared with the TTP-like syndrome group, the TTP group had an approximately two-fold to three-fold higher prevalence of central nervous system dysfunction (P < 0.001). Also, hemolysis was more substantial in the TTP group as evidenced by higher schistocytes (P < 0.001), reticulocyte (P < 0.001), total bilirubin (P = 0.002), indirect bilirubin (P < 0.001), lactate dehydrogenase (P = 0.007) and cell-free hemoglobin (P < 0.001), simultaneously lower platelet (P < 0.001), haptoglobin (P = 0.044), and ADAMTS13 activity (P < 0.001). The Kaplan-Meier survival analysis showed that the TTP group significantly predicted poor prognosis (log-rank test: X2 = 5.368, P = 0.021). TTP and TTP-like syndrome are two kinds of distinct phenotypes with different hemolysis statuses and illustrated differentiated inflammatory reactions, target organ damage (TOD), and the clinical outcome.

Campylobacter jejuni-Associated Hemophagocytic Lymphohistiocytosis and Guillain-Barre Syndrome: A Case Report.

Campylobacter jejuni (C. jejuni), a Gram-negative bacterium, belongs to microaerobic bacteria. We reported a 21-year-old male patient diagnosed with hemophagocytic lymphohistiocytosis (HLH) due to C. jejuni infection, who presented with multiple clinical manifestations of peripheral nerve injury, such as ophthalmoplegia, facial paralysis, and urinary retention during the treatment. Electromyography showed neurogenic injury and the final diagnosis was Guillain-Barre Syndrome (GBS). After treatment of dexamethasone combined with immunoglobulin, the patient was discharged from the hospital with partial recovery of neurological symptoms.

MorbidGCN: prediction of multimorbidity with a graph convolutional network based on integration of population phenotypes and disease network.

Exploring multimorbidity relationships among diseases is of great importance for understanding their shared mechanisms, precise diagnosis and treatment. However, the landscape of multimorbidities is still far from complete due to the complex nature of multimorbidity. Although various types of biological data, such as biomolecules and clinical symptoms, have been used to identify multimorbidities, the population phenotype information (e.g. physical activity and diet) remains less explored for multimorbidity. Here, we present a graph convolutional network (GCN) model, named MorbidGCN, for multimorbidity prediction by integrating population phenotypes and disease network. Specifically, MorbidGCN treats the multimorbidity prediction as a missing link prediction problem in the disease network, where a novel feature selection method is embedded to select important phenotypes. Benchmarking results on two large-scale multimorbidity data sets, i.e. the UK Biobank (UKB) and Human Disease Network (HuDiNe) data sets, demonstrate that MorbidGCN outperforms other competitive methods. With MorbidGCN, 9742 and 14 010 novel multimorbidities are identified in the UKB and HuDiNe data sets, respectively. Moreover, we notice that the selected phenotypes that are generally differentially distributed between multimorbidity patients and single-disease patients can help interpret multimorbidities and show potential for prognosis of multimorbidities.

Associations of Social Isolation and Loneliness With Later Dementia.

ObjectiveTo investigate the independent associations of social isolation and loneliness with incident dementia and to explore the potential neurobiological mechanisms.MethodsWe utilized the UK Biobank cohort to establish Cox proportional hazard models with social isolation and loneliness as separate exposures. Demographic (sex, age and ethnicity), socioeconomic (education level, household income and Townsend deprivation index), biological (BMI, APOE genotype, diabetes, cancer, cardiovascular disease and other disabilities), cognitive (speed of processing and visual memory), behavioral (current smoker, alcohol intake and physical activity), and psychological (social isolation or loneliness, depressive symptoms and neuroticism) factors measured at baseline were adjusted. Then, voxel-wise brain-wide association analyses were used to identify gray matter volumes (GMV) associated with social isolation and with loneliness. Partial least squares regression was performed to test the spatial correlation of GMV differences and gene expression using the Allen Human Brain Atlas.ResultsWe included 462,619 participants (mean age at baseline 57.0 years [SD 8.1]). With a mean follow-up of 11.7 years (SD 1.7), 4,998 developed all-cause dementia. Social isolation was associated with a 1.26-fold increased risk of dementia (95% CI, 1.15-1.37) independently of various risk factors including loneliness and depression (i.e., full adjustment). However, the fully adjusted hazard ratio for dementia related to loneliness was 1.04 (95% CI, 0.94-1.16); and 75% of this relationship was attributable to depressive symptoms. Structural MRI data were obtained from 32,263 participants (mean age 63.5 years [SD 7.5]). Socially isolated individuals had lower GMVs in temporal, frontal and other (e.g., hippocampal) regions. Mediation analysis showed that the identified GMVs partly mediated the association between social isolation at baseline and cognitive function at follow-up. Social isolation-related lower GMVs were related to under-expression of genes that are down-regulated in Alzheimer's disease and to genes that are involved in mitochondrial dysfunction and oxidative phosphorylation.ConclusionSocial isolation is a risk factor for dementia that is independent of loneliness and many other covariates. Social isolation-related brain structural differences coupled with different molecular functions also support the associations of social isolation with cognition and dementia. Social isolation may thus be an early indicator of an increased risk of dementia.

Longer screen time utilization is associated with the polygenic risk for Attention-deficit/hyperactivity disorder with mediation by brain white matter microstructure.

BACKGROUND: Attention-deficit/hyperactivity disorder (ADHD) has been reported to be associated with longer screen time utilization (STU) at the behavioral level. However, whether there are shared neural links between ADHD symptoms and prolonged STU is not clear and has not been explored in a single large-scale dataset. METHODS: Leveraging the genetics, neuroimaging and behavioral data of 11,000+ children aged 9-11 from the Adolescent Brain Cognitive Development cohort, this study investigates the associations between the polygenic risk and trait for ADHD, STU, and white matter microstructure through cross-sectionally and longitudinal analyses. FINDINGS: Children with higher polygenic risk scores for ADHD tend to have longer STU and more severe ADHD symptoms. Fractional anisotropy (FA) values in several white matter tracts are negatively correlated with both the ADHD polygenic risk score and STU, including the inferior frontal-striatal tract, inferior frontal-occipital fasciculus, superior longitudinal fasciculus and corpus callosum. Most of these tracts are linked to visual-related functions. Longitudinal analyses indicate a directional effect of white matter microstructure on the ADHD scale, and a bi-directional effect between the ADHD scale and STU. Furthermore, reduction of FA in several white matter tracts mediates the association between the ADHD polygenic risk score and STU. INTERPRETATION: These findings shed new light on the shared neural overlaps between ADHD symptoms and prolonged STU, and provide evidence that the polygenic risk for ADHD is related, via white matter microstructure and the ADHD trait, to STU. FUNDING: This study was mainly supported by NSFC and National Key R&D Program of China.

Disrupted long-range gene regulations elucidate shared tissue-specific mechanisms of neuropsychiatric disorders.

Neurological and psychiatric disorders have overlapped phenotypic profiles, but the underlying tissue-specific functional processes remain largely unknown. In this study, we explore the shared tissue-specificity among 14 neuropsychiatric disorders through the disrupted long-range gene regulations by GWAS-identified regulatory SNPs. Through Hi-C interactions, averagely 38.0% and 17.2% of the intergenic regulatory SNPs can be linked to target protein-coding genes in brain and non-brain tissues, respectively. Interestingly, while the regulatory target genes in the brain tend to enrich in nervous system development related processes, those in the non-brain tissues are inclined to interfere with synapse and neuroinflammation related processes. Compared to psychiatric disorders, neurological disorders present more prominently the neuroinflammatory processes in both brain and non-brain tissues, indicating an intrinsic difference in mechanisms. Through tissue-specific gene regulatory networks, we then constructed disorder similarity networks in two brain and three non-brain tissues, highlighting both known disorder clusters (e.g. the neurodevelopmental disorders) and unexpected disorder clusters (e.g. Parkinson's disease is consistently grouped with psychiatric disorders). We showcase the potential pharmaceutical applications of the small bowel and its disorder clusters, illustrated by the known drug targets NR1I3 and NFACT1, and their small bowel-specific regulatory modules. In conclusion, disrupted long-range gene regulations in both brain and non-brain tissues contribute to the similarity among distinct clusters of neuropsychiatric disorders, and the tissue-specifically shared functions and regulators for disease clusters may provide insights for future therapeutic investigations.

Efficacy and Safety of Chinese Herbal Medicine Compared With Losartan for Mild Essential Hypertension: A Randomized, Multicenter, Double-Blind, Noninferiority Trial.

BACKGROUND: Hypertension is one of the most challenging public health problems worldwide. Previous studies suggested that the Songling Xuemaikang capsule (SXC)-a Chinese herbal formula-was effective for essential hypertension. However, the efficacy of SXC monotherapy for hypertension remains unclear. We aimed to compare the blood pressure (BP)-lowering efficacy and safety of SXC versus losartan in patients with essential hypertension. METHODS: In this multicenter, randomized, double-blind, noninferiority trial in China, patients 18 to 65 years of age with mild essential hypertension were randomly allocated to receive either SXC or losartan for 8 weeks. The primary outcome was the change in sitting diastolic BP from baseline to 8 weeks, with a predefined noninferiority margin of -2.5 mm Hg. RESULTS: Of the 755 patients who entered a 2-week run-in period, 628 patients (327 women and 301 men; mean [SD] age, 52.6 [9.2] years) were randomly assigned to the SXC (n=314) or losartan (n=314) group. The primary analysis based on the intention-to-treat principle showed that the change in diastolic BP from baseline to 8 weeks was similar between the SXC and losartan groups (-7.9 [8.0] versus -8.1 [7.9]). The lower boundary of 95% CI (mean difference, -0.24 [95% CI, -1.51 to 1.03]) was above the margin of -2.5 mm Hg, showing noninferiority. Results were consistent with per-protocol analysis. SXC produced greater improvements in total hypertension symptom score (-5.7 [4.2] versus -5.0 [4.0]; P=0.020) and total cholesterol (-0.1 [1.0] versus 0.1 [1.2]; P=0.025). There were no differences between groups in the other BP and patient-reported outcomes. Incidence and severity of adverse events were similar between groups. CONCLUSIONS: SXC was well tolerated and demonstrated noninferior to losartan in BP lowering in patients with mild hypertension. SXC might be an alternative for mild hypertension, particularly for patients with a preference for natural medicine. REGISTRATION: URL: www.chictr.org.cn; Unique identifier: ChiCTR-IPR-16008108.

Exploratory COVID-19 death risk score based on basic laboratory tests and physiological clinical measurements.

BACKGROUND: In the event of a sudden shortage of medical resources, a rapid, simple, and accurate prediction model is essential for the 30-day mortality rate of patients with COVID-19. METHODS: This retrospective study compared the characteristics of the survivals and non-survivals of 278 patients with COVID-19. Logistic regression analysis was performed to obtain the "COVID-19 death risk score" (CDRS) model. Using the area under the receiver operating characteristic (AUROC) curve and Hosmer-Lemeshow goodness-of-fit test, discrimination and calibration were assessed. Internal validation was conducted using a regular bootstrap method. RESULTS: A total of 63 (22.66%) of 278 included patients died. The logistic regression analysis revealed that high-sensitivity C-reactive protein (hsCRP; odds ratio [OR]=1.018), D-dimer (OR=1.101), and respiratory rate (RR; OR=1.185) were independently associated with 30-day mortality. CDRS was calculated as follows: CDRS=-10.245+(0.022×hsCRP)+(0.172×D-dimer)+(0.203×RR). CDRS had the same predictive effect as the sequential organ failure assessment (SOFA) and "confusion, uremia, respiratory rate, blood pressure, and age over 65 years" (CURB-65) scores, with AUROCs of 0.984 for CDRS, 0.975 for SOFA, and 0.971 for CURB-65, respectively. And CDRS showed good calibration. The AUROC through internal validations was 0.980 (95% confidence interval [CI]: 0.965-0.995). Regarding the clinical value, the decision curve analysis of CDRS showed a net value similar to that of CURB-65 in this cohort. CONCLUSION: CDRS is a novel, efficient and accurate prediction model for the early identification of COVID-19 patients with poor outcomes. Although it is not as advanced as the other models, CDRS had a similar performance to that of SOFA and CURB-65.

Hemophagocytosis, hyper-inflammatory responses, and multiple organ damages in COVID-19-associated hyperferritinemia.

Hyperferritinemia comes to light frequently in general practice. However, the characteristics of COVID-19-associated hyperferritinemia and the relationship with the prognosis were not well described. The retrospective study included 268 documented COVID-19 patients. They were divided into the hyperferritinemia group (≥ 500 µg/L) and the non-hyperferritinemia group (< 500 µg/L). The prevalence of fever and thrombocytopenia and the proportion of patients with mechanical ventilator support and in-hospital death were much higher in the hyperferritinemia group (P < 0.001). The hyperferritinemia patients showed higher median IL-6, D-dimer, and hsCRP (P < 0.001) and lowered FIB level (P = 0.036). The hyperferritinemia group had a higher proportion of patients with AKI, ARDS, and CSAC (P < 0.001). According to the multivariate analysis, age, chronic pulmonary disease, and hyperferritinemia were found to be significant independent predictors for in-hospital mortality [HR 1.041 (95% CI 1.015-1.068), P = 0.002; HR 0.427 (95% CI 0.206-0.882), P = 0.022; HR 6.176 (95% CI 2.447-15.587), P < 0.001, respectively]. The AUROC curve was 0.88, with a cut-off value of ≥ 971 µg/L. COVID-19 patients with hyperferritinemia had a high proportion of organ dysfunction, were more likely to show hyper-inflammation, progressed to hemophagocytic lymphohistiocytosis, and indicated a higher proportion of death.

Utilizing reclassification to explore characteristics and prognosis of KDIGOSCr AKI subgroups: a retrospective analysis of a multicenter prospective cohort study.

BACKGROUND: Acute kidney injury (AKI) is widespread in the intensive care unit (ICU) and affects patient prognosis. According to Kidney Disease: Improving Global Outcomes (KDIGO) guidelines, the absolute and relative increases of serum creatinine (Scr) are classified into the same stage. Whether the prognosis of the two types of patients is similar in the ICU remains unclear. METHODS: According to the absolute and relative increase of Scr, AKI stage 1 and stage 3 patients were divided into stage 1a and 1b, stage 3a and 3b groups, respectively. Their demographics, laboratory results, clinical characteristics, and outcomes were analyzed retrospectively. RESULTS: Of the 345 eligible cases, we analyzed stage 1 because stage 3a group had only one patient. Using 53 or 61.88 µmol/L as the reference Scr (Scrref), no significant differences were observed in ICU mortality (P53=0.076, P61.88=0.070) or renal replacement therapy (RRT) ratio, (P53=0.356, P61.88=0.471) between stage 1a and 1b, but stage 1b had longer ICU length of stay (LOS) than stage 1a (P53<0.001, P61.88=0.032). In the Kaplan-Meier survival analysis, no differences were observed in ICU mortality between stage 1a and 1b (P53=0.378, P61.88=0.255). In a multivariate analysis, respiratory failure [HR = 4.462 (95% CI 1.144-17.401), p = 0.031] and vasoactive drug therapy [HR = 4.023 (95% CI 1.584-10.216), p = 0.003] were found to be independently associated with increased risk of death. CONCLUSION: ICU LOS benefit was more prominent in KDIGOSCr AKI stage 1a patients than in stage 1 b. Further prospective studies with a larger sample size are necessary to confirm the effectiveness of reclassification.

Integration of Multimodal Data for Deciphering Brain Disorders.

The accumulation of vast amounts of multimodal data for the human brain, in both normal and disease conditions, has provided unprecedented opportunities for understanding why and how brain disorders arise. Compared with traditional analyses of single datasets, the integration of multimodal datasets covering different types of data (i.e., genomics, transcriptomics, imaging, etc.) has shed light on the mechanisms underlying brain disorders in greater detail across both the microscopic and macroscopic levels. In this review, we first briefly introduce the popular large datasets for the brain. Then, we discuss in detail how integration of multimodal human brain datasets can reveal the genetic predispositions and the abnormal molecular pathways of brain disorders. Finally, we present an outlook on how future data integration efforts may advance the diagnosis and treatment of brain disorders.

A global overview of genetically interpretable multimorbidities among common diseases in the UK Biobank.

BACKGROUND: Multimorbidities greatly increase the global health burdens, but the landscapes of their genetic risks have not been systematically investigated. METHODS: We used the hospital inpatient data of 385,335 patients in the UK Biobank to investigate the multimorbid relations among 439 common diseases. Post-GWAS analyses were performed to identify multimorbidity shared genetic risks at the genomic loci, network, as well as overall genetic architecture levels. We conducted network decomposition for the networks of genetically interpretable multimorbidities to detect the hub diseases and the involved molecules and functions in each module. RESULTS: In total, 11,285 multimorbidities among 439 common diseases were identified, and 46% of them were genetically interpretable at the loci, network, or overall genetic architecture levels. Multimorbidities affecting the same and different physiological systems displayed different patterns of the shared genetic components, with the former more likely to share loci-level genetic components while the latter more likely to share network-level genetic components. Moreover, both the loci- and network-level genetic components shared by multimorbidities converged on cell immunity, protein metabolism, and gene silencing. Furthermore, we found that the genetically interpretable multimorbidities tend to form network modules, mediated by hub diseases and featuring physiological categories. Finally, we showcased how hub diseases mediating the multimorbidity modules could help provide useful insights for the genetic contributors of multimorbidities. CONCLUSIONS: Our results provide a systematic resource for understanding the genetic predispositions of multimorbidities and indicate that hub diseases and converged molecules and functions may be the key for treating multimorbidities. We have created an online database that facilitates researchers and physicians to browse, search, or download these multimorbidities ( https://multimorbidity.comp-sysbio.org ).

The clinical characteristics and prognosis of COVID-19 patients with comorbidities: a retrospective analysis of the infection peak in Wuhan.

BACKGROUND: This study aims to determine the clinical characteristics and prognosis of COVID-19 patients with comorbidities and to identify survival factors. METHODS: A retrospective study was conducted in Wuhan, China, between February 8, 2020, and March 9, 2020. Based on underlying diseases, patients were assigned to either the comorbidity group or the non-comorbidity group. The clinical characteristics and outcomes of COVID-19 were analyzed and a Kaplan-Meier survival analysis was used to evaluate the prognosis predictive value of each comorbidity. RESULTS: During the study period, 278 COVID-19 patients were enrolled, 175 (62.95%) were assigned to the comorbidity group, and 103 (37.05%) to the non-comorbidity group. Of the patients in the comorbidity group, 34.86% were classified as critical. Further, patients in the comorbidity group had lower lymphocyte cell counts, and higher concentrations of D-dimer, high sensitivity C-reactive protein, interleukin 6, and serum ferritin as well as higher critical illness severity scores than patients in the non-comorbidity group (P<0.05). Patients in the comorbidity group also had higher mortality, acute respiratory distress syndrome, and ventilation treatment rates than patients in the non-comorbidity group (P<0.05). The length of hospital stay was longer in the comorbidity group than in the non-comorbidity group (P<0.05). The most common underlying diseases included hypertension (40.65%), diabetes mellitus (20.5%), and cardiovascular disease (19.42%). Patients with comorbidities were more likely to develop cardiovascular sequelae associated with COVID-19, shock, acute kidney injury, and multiple organ dysfunction syndrome (30.86% vs. 12.62%, P=0.001; 18.86% vs. 8.74%, P=0.023; 24.57% vs. 11.65%, P=0.009; 33.71% vs. 14.56%, P=0.000, respectively). In the Kaplan-Meier survival analysis, older patients (¡Ý65 years) (log-rank test: χ2=4.202, P=0.040) and patients with chronic obstructive pulmonary disease (COPD) (log-rank test: χ2=4.839, P=0.028) or diabetes mellitus (log-rank test: χ2=4.377, P=0.036) had shorter survival than those without comorbidities. CONCLUSIONS: Patients with comorbidities were more severely affected and had a higher mortality rate. Age, COPD and diabetes mellitus were the main factors affecting the survival of patients.

Prominent coagulation disorder is closely related to inflammatory response and could be as a prognostic indicator for ICU patients with COVID-19.

The new outbreak of Coronavirus Disease 2019 (COVID-19) has emerged as a serious global public health concern. A more in-depth study of blood coagulation abnormality is needed. We retrospectively analyzed 147 consecutive patients with COVID-19 who were admitted to three ICUs in Wuhan from February 9th, 2020 to March 20th, 2020. The baseline coagulation and other characteristics were studied. Our results showed that the prolonged PT, FDP, DD were positively correlated with the levels of neutrophils, ferritin, LDH, total bilirubin, multi-inflammation cytokines, and negatively correlated with the lymphocytes level (p < 0.01). The level of ATIII was significantly negatively correlated with the levels of neutrophils, ferritin, LDH, total bilirubin, IL2R, IL6 and IL8 (p < 0.05). The patients in the ARDS group had a more prominent abnormality in PT, FDP, DD and ATIII, while the patients in the AKI group had more prolonged PT, more severe FDP and DD level, more inferior ATIII and Fib level than those in the non-AKI group (p < 0.01). The value of PT, DD and FDP were positively correlated with the classical APACHE II, SOFA and qSOFA scores, while the ATIII was negatively correlated with them (p < 0.001). The high levels of PT, FDP and DD were correlated with in-hospital mortality (p < 0.001). In conclusion, blood coagulation disorder was prominent in ICU patients with COVID-19 and was correlated with multi-inflammation factors. The abnormality of blood coagulation parameters could be an adverse prognostic indicator for ICU patients with COVID-19.

[Stratified outcomes of "Kidney Disease: Improving Global Outcomes" serum creatinine criteria in critical ill patients: a secondary analysis of a multicenter prospective study].

OBJECTIVE: To investigate the different outcomes of two types of acute kidney injury (AKI) according to standard of Kidney Disease: Improving Global Outcomes-AKI (KDIGO-AKI), and to analyze the risk factors that affect the prognosis of intensive care unit (ICU) patients in China. METHODS: A secondary analysis was performed on the database of a previous study conducted by China Critical Care Clinical Trial Group (CCCCTG), which was a multicenter prospective study involving 3 063 patients in 22 tertiary ICUs in 19 provinces and autonomous regions of China. The demographic data, scores reflecting severity of illness, laboratory findings, intervention during ICU stay were extracted. All patients were divided into pure AKI (PAKI) and acute on chronic kidney disease (AoCKD). PAKI was defined as meeting the serum creatinine (SCr) standard of KDIGO-AKI (KDIGO-AKISCr) and the estimated glomerular filtration rate (eGFR) at baseline was ≥ 60 mL×min-1×1.73 m-2, and AoCKD was defined as meeting the KDIGO-AKISCr standard and baseline eGFR was 15-59 mL×min-1×1.73 m-2. All-cause mortality in ICU within 28 days was the primary outcome, while the length of ICU stay and renal replacement therapy (RRT) were the secondary outcome. The differences in baseline data and outcomes between the two groups were compared. The cumulative survival rate of ICU within 28 days was analyzed by Kaplan-Meier survival curve, and the risk factors of ICU death within 28 days were screened by Cox multivariate analysis. RESULTS: Of the 3 063 patients, 1 042 were enrolled, 345 with AKI, 697 without AKI. The AKI incidence was 33.11%, while ICU mortality within 28 days of AKI patients was 13.91% (48/345). Compared with PAKI patients (n = 322), AoCKD patients (n = 23) were older [years old: 74 (59, 77) vs. 58 (41, 72)] and more critical when entering ICU [acute physiology and chronic health evaluation II (APACHE II) score: 23 (19, 27) vs. 15 (11, 22)], had worse basic renal function [eGFR (mL×min-1×1.73 m-2): 49 (38, 54) vs. 115 (94, 136)], more basic complications [Charlson comorbidity index (CCI): 3 (2, 4) vs. 0 (0, 1)] and higher SCr during ICU stay [peak SCr for diagnosis of AKI (µmol/L): 412 (280, 515) vs. 176 (124, 340), all P < 0.01]. The mortality and RRT incidence within 28 days in ICU of AoCKD patients were significantly higher than those of PAKI patients [39.13% (9/23) vs. 12.11% (39/322), 26.09% (6/23) vs. 4.04% (13/322), both P < 0.01], while no significant difference was found in the length of ICU stay. Kaplan-Meier survival curve analysis showed that the 28-day cumulative survival rate in ICU in AoCKD patients was significantly lower than PAKI patients (Log-Rank: χ 2 = 5.939, P = 0.015). Multivariate Cox regression analysis showed that admission to ICU due to respiratory failure [hazard ratio (HR) = 4.458, 95% confidence interval (95%CI) was 1.141-17.413, P = 0.032], vasoactive agents treatment in ICU (HR = 5.181, 95%CI was 2.033-13.199, P = 0.001), and AoCKD (HR = 5.377, 95%CI was 1.303-22.186, P = 0.020) were independent risk factors for ICU death within 28 days. CONCLUSIONS: Further detailed classification (PAKI, AoCKD) based on KDIGO-AKISCr standard combined with eGFR is related to ICU mortality in critical patients within 28 days.