Observationally, higher basal metabolic rate (BMR) is associated with metabolism-related disorders, cancer, aging, and mortality. In this Mendelian randomization (MR) phenome-wide association study, using two-sample MR methods, we systematically and comprehensively investigated the health effects of genetically predicted BMR across the phenome sex-specifically. We obtained sex-specific genetic variants strongly (p < 5 × 10- 8) and independently (r2 < 0.001) predicting BMR from the UK Biobank and applied them to over 1,000 phenotypes within the same study. We combined genetic variant-specific Wald estimates using inverse-variance weighting, supplemented by sensitivity analysis. We used a false-discovery rate correction to allow for multiple comparisons as well as multivariable MR adjusted for body mass index and testosterone to investigate the independent effects of BMR on phenotypes with significant univariable associations. We obtained 217/219 genetic variants predicting BMR and applied them to 1,150/1,242 phenotypes in men/women, respectively. BMR was associated with 190/270 phenotypes in univariable analysis and 122/123 phenotypes in multivariable analysis in men/women. Examples of robust associations in multivariable analysis included those with neoplasms, diseases of the circulatory system, and growth and reproductive investment. In conclusion, BMR might affect a wide range of health-related outcomes. The underlying mechanisms and interactions between phenotypes warrant further study, as BMR is modifiable.

The protective effects of higher educational attainment (EA) and intelligence on COVID-19 outcomes are not yet understood with regard to their dependency on income. The objective of our study was to examine the overall as well as independent effects of the three psychosocial factors on the susceptibility to and severity of COVID-19. To accomplish this, we utilized genetic correlation, Mendelian randomization (MR), and multivariable MR (MVMR) analyses to evaluate genetic associations between EA, intelligence, household income, and three specific COVID-19 outcomes: SARS-CoV-2 infection, hospitalized COVID-19, and critical COVID-19.

The genetic correlation analysis revealed that COVID-19 outcomes were negatively correlated with the three psychosocial factors (rg: -0.19‒-0.36). The MR analysis indicated that genetic liability to EA, intelligence, and income exerted overall protective effects against SARS-CoV-2 infection (OR: 0.86‒0.92), hospitalized COVID-19 (OR: 0.70‒0.80), and critical COVID-19 (OR: 0.65‒0.85). MVMR analysis revealed that elevated levels of EA conferred independent protective effects against SARS-CoV-2 infection (OR: 0.85), hospitalization due to COVID-19 (OR: 0.79), and critical COVID-19 (OR: 0.63). Furthermore, intelligence exhibited a negative association with the risk of SARS-CoV-2 infection (OR: 0.91), whereas a higher income was linked to an elevated risk of SARS-CoV-2 infection (OR: 1.13).

Our findings indicated that EA could significantly reduce the risk and severity of COVID-19, regardless of intelligence and income. However, the impact of intelligence or income on COVID-19 severity was not supported by our research.

To investigate the association between smoking behavior and COVID-19 hospitalization, integrating individual and regional factors such as community resilience and social determinants of health (SDOH), addressing gaps in existing research.

Retrospective cohort study utilizing multilevel analytical methods to evaluate the effects of individual smoking status and regional SDOH on COVID-19 hospitalization.

Washoe County, Nevada, during the first year of the COVID-19 pandemic (March 5, 2020, to April 30, 2021).

All reported laboratory-positive COVID-19-infected adult residents of Washoe County collected by the Washoe County Health District through mandated disease surveillance for which smoking status was recorded, totaling 10,215 cases after data cleaning.

Hospitalization among those with COVID-19 was the primary outcome measure, analyzed in relation to individual smoking status and zip code tabulation area (ZCTA)-level SDOH variables.

The analysis found that individuals infected with COVID-19 who currently and formerly smoked had significantly higher odds of hospitalization compared to those who never had smoked, with odds ratios adjusted for demographics and comorbidities. An increased odds of hospitalization among those with COVID-19 were associated with higher local unemployment, a significant ZCTA-level factor.

Smoking may have increased the odds of hospitalization among those infected with COVID-19, as well as the socioeconomic factor of unemployment. The integration of SDOH into the assessment of health outcomes underscores the need for targeted public health interventions that address both individual behaviors and community-level factors. Future research should continue to explore these factors to inform more effective public health strategies and policy decisions.

In response to the SARS-CoV-2 pandemic, the United States declared a state of emergency and implemented large-scale shutdowns and public health initiatives to prevent overwhelming public resources. The success of these prevention methods remains unresolved as restrictions and implementation varied from national, state, and local levels. Despite national and local regulations, individual adherence to preventative guidelines presented an additional layer of variability. Cases of COVID-19 continued to rise and fall over a two-year period on a national level, despite masking recommendations, ease of testing, and availability of vaccines. The Ysleta del Sur Pueblo is a Native American tribal community and sovereign nation located in El Paso, Texas. Speaking Rock Entertainment Center is a major business operated by the tribe, employing many tribal and non-tribal members from the El Paso area. Following nationwide re-openings of non-essential businesses, Speaking Rock implemented an infection control program with strict adherence to recommendations provided by the Center for Disease Control and Prevention (CDC) and additional disease control. This response would result in a fully vaccinated workforce within the wider community of El Paso, where the vaccination rate was less than 80%. Herein, we examine the efficacy of these measures and report on the success of the program resulting in zero hospitalizations or deaths compared with rates of 1 in 250 and 1 in 40, respectively, in the surrounding community.

Owing to the recent emergence of COVID-19, there is a lack of published research and clinical recommendations for posttraumatic stress disorder (PTSD) risk factors in patients who contracted or received treatment for the virus. This research aims to identify potential molecular targets to inform therapeutic strategies for this patient population. RNA sequence data for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and PTSD (from the National Center for Biotechnology Information [NCBI]) were processed using the GREIN database. Protein-protein interaction (PPI) networks, pathway enrichment analyses, miRNA interactions, gene regulatory network (GRN) studies, and identification of linked drugs, chemicals, and diseases were conducted using STRING, DAVID, Enrichr, Metascape, ShinyGO, and NetworkAnalyst v3.0. Our analysis identified 15 potentially unique hub proteins within significantly enriched pathways, including PSMB9, MX1, HLA-DOB, HLA-DRA, IFIT3, OASL, RSAD2, and so on, filtered from a pool of 201 common differentially expressed genes (DEGs). Gene ontology (GO) terms and metabolic pathway analyses revealed the significance of the extracellular region, extracellular space, extracellular exosome, adaptive immune system, and interleukin (IL)-18 signaling pathways. In addition, we discovered several miRNAs (hsa-mir-124-3p, hsa-mir-146a-5p, hsa-mir-148b-3p, and hsa-mir-21-3p), transcription factors (TF) (WRNIP1, FOXC1, GATA2, CREB1, and RELA), a potentially repurposable drug carfilzomib and chemicals (tetrachlorodibenzodioxin, estradiol, arsenic trioxide, and valproic acid) that could regulate the expression levels of hub proteins at both the transcription and posttranscription stages. Our investigations have identified several potential therapeutic targets that elucidate the probability that victims of COVID-19 experience PTSD. However, they require further exploration through clinical and pharmacological studies to explain their efficacy in preventing PTSD in COVID-19 patients.

Our centre followed a stepwise approach in the nonpharmacological treatment of respiratory failure in COVID-19 in accordance with German national guidelines, escalating non-invasive measures before invasive mechanical ventilation (IMV) or extracorporeal membrane oxygenation (ECMO). The aim of this study was to analyse this individualized approach to non-pharmacologic therapy in terms of patient characteristics and clinical features that may help predict more severe disease, particularly the need for intensive care.

This retrospective single-centre study of COVID-19 inpatients between March 2020 and December 2021 analysed anthropometric data, non-pharmacological maximum therapy and survival status via a manual medical file review.

Of 1052 COVID-19-related admissions, 835 patients were included in the analysis cohort (54% male, median 58 years); 34% (n=284) received no therapy, 40% (n=337) conventional oxygen therapy (COT), 3% (n=22) high flow nasal cannula (NHFC), 9% (n=73) continuous positive airway pressure (CPAP), 7% (n=56) non-invasive ventilation (NIV), 4% (n=34) intermittent mandatory ventilation (IMV), and 3% (n=29) extracorporeal membrane oxygenation (ECMO). Of 551 patients treated with at least COT, 12.3% required intubation. A total of 183 patients required ICU treatment, and 106 (13%) died. 25 (74%) IMV patients and 23 (79%) ECMO patients died. Arterial hypertension, diabetes and dyslipidemia was more prevalent in non-survivors. Binary logistic analysis revealed the following risk factors for increased mortality: an oxygen supplementation of ≥2 L/min at baseline (OR 6.96 [4.01-12.08]), age (OR 1.09 [1.05-1.14]), and male sex (OR 2.23 [0.79-6.31]).

The physician's immediate clinical decision to provide oxygen therapy, along with other recognized risk factors, plays an important role in predicting the severity of the disease course and thus aiding in the management of COVID-19.

The global healthcare burden of COVID-19 pandemic has been unprecedented with a high mortality. Metabolomics, a powerful technique, has been increasingly utilized to study the host response to infections and to understand the progression of multi-system disorders such as COVID-19. Analysis of the host metabolites in response to SARS-CoV-2 infection can provide a snapshot of the endogenous metabolic landscape of the host and its role in shaping the interaction with SARS-CoV-2. Disease severity and consequently the clinical outcomes may be associated with a metabolic imbalance related to amino acids, lipids, and energy-generating pathways. Hence, the host metabolome can help predict potential clinical risks and outcomes.

In this prospective study, using a targeted metabolomics approach, we studied the metabolic signature in 154 COVID-19 patients (males=138, age range 48-69 yrs) and related it to disease severity and mortality. Blood plasma concentrations of metabolites were quantified through LC-MS using MxP Quant 500 kit, which has a coverage of 630 metabolites from 26 biochemical classes including distinct classes of lipids and small organic molecules. We then employed Kaplan-Meier survival analysis to investigate the correlation between various metabolic markers, disease severity and patient outcomes.

A comparison of survival outcomes between individuals with high levels of various metabolites (amino acids, tryptophan, kynurenine, serotonin, creatine, SDMA, ADMA, 1-MH and carnitine palmitoyltransferase 1 and 2 enzymes) and those with low levels revealed statistically significant differences in survival outcomes. We further used four key metabolic markers (tryptophan, kynurenine, asymmetric dimethylarginine, and 1-Methylhistidine) to develop a COVID-19 mortality risk model through the application of multiple machine-learning methods.

Metabolomics analysis revealed distinct metabolic signatures among different severity groups, reflecting discernible alterations in amino acid levels and perturbations in tryptophan metabolism. Notably, critical patients exhibited higher levels of short chain acylcarnitines, concomitant with higher concentrations of SDMA, ADMA, and 1-MH in severe cases and non-survivors. Conversely, levels of 3-methylhistidine were lower in this context.

Previous studies have observed a significant comorbidity between Alzheimer's disease (AD) and some other neuropsychiatric disorders. However, the mechanistic connections between neuropsychiatric disorders and AD are not well understood. We conducted a Mendelian randomization analysis to appraise the potential influences of 18 neurodegenerative and neuropsychiatric disorders on AD. We found that four disorders are causally associated with increased risk for AD, including bipolar disorder (BD) (OR: 1.09), migraine (OR: 1.09), schizophrenia (OR: 1.05), and Parkinson's disease (PD) (OR: 1.07), while attention-deficit/hyperactivity disorder (ADHD) was associated with a decreased risk for AD (OR: 0.80). In case of amyotrophic lateral sclerosis (OR: 1.04) and Tourette's syndrome (OR: 1.05), there was suggestive evidence of their causal effects of on AD. Our study shows that genetic components predisposing to BD, migraine, schizophrenia, and PD may promote the development of AD, while ADHD may be associated with a reduced risk of AD. The treatments aimed at alleviating neuropsychiatric diseases with earlier onset may also influence the risk of AD-related cognitive decline, which is typically observed later in life.

Physical activity and athletic performance are complex phenotypes influenced by environmental and genetic factors. Recent advances in lifestyle and behavioral genomics led to the discovery of dozens of DNA polymorphisms (variants) associated with physical activity and allowed to use them as genetic instruments in Mendelian randomization studies for identifying the causal links between physical activity and health outcomes. On the other hand, exercise and sports genomics studies are focused on the search for genetic variants associated with athlete status, sports injuries and individual responses to training and supplement use. In this review, the findings of studies investigating genetic markers and their associations with physical activity and athlete status are reported. As of the end of September 2023, a total of 149 variants have been associated with various physical activity traits (of which 42 variants are genome-wide significant) and 253 variants have been linked to athlete status (115 endurance-related, 96 power-related, and 42 strength-related).

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can invade both the peripheral and central nervous systems and impact the function of the brain. Therefore, it is necessary to evaluate the mutual influences between COVID-19 outcomes and childhood mental disorders.

We examined genetic correlations and potential causalities between three childhood mental disorders and three COVID-19 phenotypes by genetically proxied analyses. The three mental disorders included attention-deficit/hyperactivity disorder (ADHD, N = 292,548), Tourette's syndrome (TS, N = 14,307), and autism spectrum disorder (ASD, N = 46,350). The three COVID-19 traits included SARS-CoV-2 infection (N = 2,597,856), hospitalized COVID-19 (N = 2,095,324), and critical COVID-19 (N = 1,086,211). Literature-based analysis was used to build gene-based pathways connecting ADHD and COVID-19.

ADHD was positively correlated with the three COVID-19 outcomes (Rg: 0.22 ~ 0.30). Our Mendelian randomization (MR) analyses found that ADHD confers a causal effect on hospitalized COVID-19 (odds ratio (OR): 1.36, 95% confidence interval (CI): 1.10-1.69). TS confers a causal effect on critical COVID-19 (OR: 1.14, 95% CI: 1.04-1.25). Genetic liability to the COVID-19 outcomes may not increase the risk for the childhood mental disorders. Pathway analysis identified several immunity-related genes that may link ADHD to COVID-19, including CRP, OXT, IL6, PON1, AR, TNFSF12, and IL10.

Our study suggests that both ADHD and TS may augment the severity of COVID-19 through immunity-related pathways. However, our results did not support a causal role of COVID-19 in the risk for the childhood mental disorders.

Coronavirus disease 2019 (COVID-19), resulting from severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), remains a persistent global health concern. Evidence has highlighted a significant association between COVID-19 and ischemic heart failure (IHF), contributing to disease progression and increased mortality. This study identified diagnostic biomarkers for these comorbidities and elucidated disease progression's molecular mechanisms.

We retrieved differentially expressed gene (DEG) data for COVID-19 and IHF from publicly available microarray and RNA-Seq datasets to investigate the underlying mechanisms and potential pathways associated with the co-occurrence of COVID-19 and IHF. By intersecting the results from the two diseases, we obtained diagnostic biomarkers using SVM-RFE and LASSO algorithms. Animal experiments and immunological analyses were conducted to help understand the association between SARS-CoV-2 and IHF in patients, enabling early diagnosis of disease progression. Finally, we analyzed the regulatory network of critical genes and identified potential drug compounds that could target the genetic links identified in our study.

1974 common DEGs were identified between COVID-19 and IHF, contributing to disease progression and potential cancer risk by participating in immune and cancer-related pathways. In addition, we identified six hub genes (VDAC3, EIF2AK2, CHMP5, FTL, VPS4A, and CHMP4B) associated with the co-morbidity, and their diagnostic potential was confirmed through validation using relevant datasets and a mouse model. Functional enrichment analysis and examination of immune cell infiltration revealed immune dysregulation after disease progression. The comorbid hub genes exhibited outstanding immunomodulatory capacities. We also constructed regulatory networks tightly linked to both disorders, including transcription factors (TFs), miRNAs, and genes at both transcriptional and post-transcriptional levels. Finally, we identified 92 potential drug candidates to enhance the precision of anti-comorbidity treatment strategies.

Our study reveals a shared pathogenesis between COVID-19 and IHF, demonstrating that their coexistence exacerbates disease severity. By identifying and consolidating hub genes as pivotal diagnostic biomarkers for COVID-19 and IHF comorbidity, we have made significant advancements in understanding the underlying mechanisms of these conditions. Moreover, our study highlights dysregulated immunity and increased cancer risk in the advanced stages of disease progression. These findings offer novel perspectives for diagnosing and treating IHF progression during SARS-CoV-2 infection.

Since 2020, COVID-19 has caused serious mortality around the world. Given the ambiguity in establishing COVID-19 as the direct cause of death, we first investigate the effects of age and sex on all-cause mortality during 2020 and 2021 in England and Wales. Since infectious agents have their own unique age profile for death, we use a 9-year time series and several different methods to adjust single-year-of-age deaths in England and Wales during 2019 (the pre-COVID-19 base year) to a pathogen-neutral single-year-of-age baseline. This adjusted base year is then used to confirm the widely reported higher deaths in males for most ages above 43 in both 2020 and 2021. During 2020 (+COVID-19 but no vaccination), both male and female population-adjusted deaths significantly increased above age 35. A significant reduction in all-cause mortality among both males and females aged 75+ could be demonstrated in 2021 during the widespread COVID-19 vaccination period; however, deaths below age 75 progressively increased. This finding arises from a mix of vaccination coverage and year-of-age profiles of deaths for the different SARS-CoV-2 variants. In addition, specific effects of age around puberty were demonstrated, where females had higher deaths than males. There is evidence that year-of-birth cohorts may also be involved, indicating that immune priming to specific pathogen outbreaks in the past may have led to lower deaths for some birth cohorts. To specifically identify the age profile for the COVID-19 variants from 2020 to 2023, we employ the proportion of total deaths at each age that are potentially due to or 'with' COVID-19. The original Wuhan strain and the Alpha variant show somewhat limited divergence in the age profile, with the Alpha variant shifting to a moderately higher proportion of deaths below age 84. The Delta variant specifically targeted individuals below age 65. The Omicron variants showed a significantly lower proportion of overall mortality, with a markedly higher relative proportion of deaths above age 65, steeply increasing with age to a maximum around 100 years of age. A similar age profile for the variants can be seen in the age-banded deaths in US states, although they are slightly obscured by using age bands rather than single years of age. However, the US data shows that higher male deaths are greatly dependent on age and the COVID variant. Deaths assessed to be 'due to' COVID-19 (as opposed to 'involving' COVID-19) in England and Wales were especially overestimated in 2021 relative to the change in all-cause mortality. This arose as a by-product of an increase in COVID-19 testing capacity in late 2020. Potential structure-function mechanisms for the age-specificity of SARS-CoV-2 variants are discussed, along with potential roles for small noncoding RNAs (miRNAs). Using data from England, it is possible to show that the unvaccinated do indeed have a unique age profile for death from each variant and that vaccination alters the shape of the age profile in a manner dependent on age, sex, and the variant. The question is posed as to whether vaccines based on different variants carry a specific age profile.

COVID-19 might cause neuroinflammation in the brain, which could decrease neurocognitive function. We aimed to evaluate the causal associations and genetic overlap between COVID-19 and intelligence.

We performed Mendelian randomization (MR) analyses to assess potential associations between three COVID-19 outcomes and intelligence (N = 269 867). The COVID phenotypes included severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection (N = 2 501 486), hospitalized COVID-19 (N = 1 965 329) and critical COVID-19 (N = 743 167). Genome-wide risk genes were compared between the genome-wide association study (GWAS) datasets on hospitalized COVID-19 and intelligence. In addition, functional pathways were constructed to explore molecular connections between COVID-19 and intelligence.

The MR analyses indicated that genetic liabilities to SARS-CoV-2 infection (odds ratio [OR]: 0.965, 95% confidence interval [CI]: 0.939-0.993) and critical COVID-19 (OR: 0.989, 95% CI: 0.979-0.999) confer causal effects on intelligence. There was suggestive evidence supporting the causal effect of hospitalized COVID-19 on intelligence (OR: 0.988, 95% CI: 0.972-1.003). Hospitalized COVID-19 and intelligence share 10 risk genes within 2 genomic loci, including MAPT and WNT3. Enrichment analysis showed that these genes are functionally connected within distinct subnetworks of 30 phenotypes linked to cognitive decline. The functional pathway revealed that COVID-19-driven pathological changes within the brain and multiple peripheral systems may lead to cognitive impairment.

Our study suggests that COVID-19 may exert a detrimental effect on intelligence. The tau protein and Wnt signaling may mediate the influence of COVID-19 on intelligence.

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.

The correlation between smoking and alcohol consumption and the development of Dupuytren's disease (DD) has been acknowledged. However, the definitive causal relationship between these two factors and DD remains elusive. In order to establish a causal connection, we employed the two-sample Mendelian randomization method to evaluate the relationship between smoking and alcohol consumption and DD.

Based on publicly available genome-wide association studies (GWAS), two-sample univariate MR analyses were performed to assess the causal effects of drinks per week, cigarettes per day, smoking initiation, age of initiation, and smoking cessation on DD. We used inverse variance weighted (IVW) to generate the primary results for the MR analysis. Furthermore, we performed sensitivity MR analyses based on various methods to assess the robustness of estimations. Bidirectional MR analyses were used to study the interaction between smoking and alcohol consumption. Multivariate MR analyses were used to obtain independent causal effects of smoking or drinking on DD.

Our two-sample MR, which was predominately based on IVW, revealed a causal relationship between drinks per week and DD (OR = 2.948, 95%CI: 1.746-4.975, P = 5.16E-05). In addition, there is no causal association between cigarettes per day, smoking initiation, age of initiation, smoking cessation and DD. Similar conclusions were reached by other MR methods. The results of the bidirectional MR analyses showed that the causal relationships between age of initiation and drinks per week were robust and significant. Multivariate MR results indicated that the causal effect of alcohol consumption on DD was independent of smoking.

Our Mendelian Randomization study indicated that there is a causality between drinking alcohol and DD, but no such causality was found between smoking and DD. This is the first study to prove that drinking alcohol could cause DD. This could help people who are trying to prevent DD from happening in the first place.

The severe acute respiratory syndrome coronavirus in 2019 (COVID-19) is still spreading and causing deaths worldwide, which further increased the burden of chronic diseases. Dyslipidemia is a common metabolic syndrome, which is a major risk factor for cardiovascular disease. However, studies on whether there is a direct causal relationship between COVID-19 and the exacerbation of hyperlipidemia are still scarce.

Two-sample Mendelian randomization was conducted using publicly available summary statistics from independent cohorts of European ancestry. For COVID-19 and hyperlipidemia, we used data from the ieu open GWAS project database. Inverse variance-weighted, mendelian randomization Egger, weighted median, simple mode, and weighted mode mendelian randomization analyses were performed, together with a range of sensitivity analyses.

There is no direct causal relationship between COVID-19 and dyslipidemia, regardless of COVID-19 severity or either dyslipidemic outcome. In combination with previous studies, the reason for the clinical outcome that COVID-19 increased the burden of dyslipidemia may be due to the exacerbation of pre-existing disease caused by COVID-19.

COVID-19 has no direct causal relationship with dyslipidemia.

The association between gut microbiome and coronavirus disease 2019 (COVID-19) has attracted much attention, but its causality remains unclear and requires more direct evidence.

In this study, we conducted the bidirectional Mendelian randomization (MR) analysis to assess the causal association between gut microbiome and COVID-19 based on the summary statistics data of genome-wide association studies (GWASs). Over 1.8 million individuals with three COVID-19 phenotypes (severity, hospitalization and infection) were included. And 196 bacterial taxa from phylum to genus were analyzed. The inverse-variance weighted (IVW) analysis was chosen as the primary method. Besides, false discovery rate (FDR) correction of p-value was used. To test the robustness of the causal relationships with p-FDR < 0.05, sensitivity analyses including the secondary MR analyses, horizontal pleiotropy test, outliers test, and "leave-one-out" analysis were conducted.

In the forward MR, we found that 3, 8, and 10 bacterial taxa had suggestive effects on COVID-19 severity, hospitalization and infection, respectively. The genus Alloprevotella [odds ratio (OR) = 1.67; 95% confidence interval (95% CI), 1.32-2.11; p = 1.69×10^-5, p-FDR = 2.01×10^-3] was causally associated with a higher COVID-19 severity risk. In the reverse MR, COVID-19 severity, hospitalization and infection had suggestive effects on the abundance of 4, 8 and 10 bacterial taxa, respectively. COVID-19 hospitalization causally increased the abundance of the phylum Bacteroidetes (OR = 1.13; 95% CI, 1.04-1.22; p = 3.02×10^-3; p-FDR = 2.72×10^-2). However, secondary MR analyses indicated that the result of COVID-19 hospitalization on the phylum Bacteroidetes required careful consideration.

Our study revealed the causal association between gut microbiome and COVID-19 and highlighted the role of "gut-lung axis" in the progression of COVID-19.

We carried out a bidirectional Mendelian randomization (MR) including cases of eczema (N = 218,792), asthma (N = 462,933), and allergic rhinitis (N = 112,583). COVID-19 susceptibility (N = 1,683,768), COVID-19 hospitalization (N = 1,887,658), and COVID-19 severe respiratory symptom (N = 1,388,342) were sampled from GWAS database. The MR analysis was primarily based on inverse variance weighted (IVW), supplemented by several other algorithms. In the bidirectional MR analysis, eczema was negatively associated with COVID-19 susceptibility (odds ratio (OR) _IVW = 0.92; p = 0.031) and COVID-19 hospitalization (OR_IVW = 0.81, p = 0.010); asthma was negatively associated with COVID-19 susceptibility (OR_IVW = 0.65, p = 0.005) and COVID-19 severe respiratory symptom (OR_IVW = 0.20, p = 0.001). No significant association was found between allergic rhinitis and COVID-19 susceptibility (OR_IVW = 0.80, p = 0.174), COVID-19 hospitalization (OR_IVW = 0.71, p = 0.207), or COVID-19 severe respiratory symptom (OR_IVW = 0.56; p = 0.167). The reverse MR analysis showed no potential reverse causal association. Our findings provided new evidence that allergic diseases might be associated with different risks of COVID-19 susceptibility, hospitalization, and severe respiratory symptom.

Patients with osteoarthritis (OA) are exposed to an increased risk of adverse outcomes of COVID-19, and they tend to experience disruption in access to healthcare services and exercise facilities. However, a deep understanding of this comorbidity phenomenon and the underlying genetic architecture of the two diseases is still unclear. In this study, we aimed to untangle the relationship between OA and COVID-19 outcomes by conducting a large-scale genome-wide cross-trait analysis.

Genetic correlation and causal relationships between OA and COVID-19 outcomes (critical COVID-19, COVID-19 hospitalization, and COVID-19 infection) were estimated by linkage disequilibrium score regression and Mendelian Randomization approaches. We further applied Multi-Trait Analysis of GWAS and colocalization analysis to identify putative functional genes associated with both OA and COVID-19 outcomes.

Significant positive genetic correlations between OA susceptibility and both critical COVID-19 (rg=0.266, P=0.0097) and COVID-19 hospitalization (rg=0.361, P=0.0006) were detected. However, there was no evidence to support causal genetic relationships between OA and critical COVID-19 (OR=1.17[1.00-1.36], P=0.049) or OA and COVID-19 hospitalization OR=1.08[0.97-1.20], P=0.143). These results were robustly consistent after the removal of obesity-related single nucleotide polymorphisms (SNPs). Moreover, we identified a strong association signal located near the FYCO1 gene (lead SNPs: rs71325101 for critical COVID-19, Pmeta=1.02×10-34; rs13079478 for COVID-19 hospitalization, Pmeta=1.09×10-25).

Our findings further confirmed the comorbidity of OA and COVID-19 severity, but indicate a non-causal impact of OA on COVID-19 outcomes. The study offers an instructive perspective that OA patients did not generate negative COVID-19 outcomes during the pandemic in a causal way. Further clinical guidance can be formulated to enhance the quality of self-management in vulnerable OA patients.

Ca2+/cAMP ratio could serve as an inflammatory index for diseases like hyp-ertension, diabetes, and coronavirus disease 2019.

Background: Tobacco smoking and alcohol consumption have been associated with frailty in observational studies. We sought to examine whether these associations reflect causality using the two-sample Mendelian randomization (MR) design. Methods: We used summary genome-wide association statistics for smoking initiation (N = 2,669,029), alcohol consumption (N = 2,428,851), and the frailty index (FI, N = 175,226) in participants of European ancestry. Both univariable and multivariable MR were performed to comprehensively evaluate the independent effects of smoking and alcohol consumption on the FI, accompanied by multiple sensitivity analyses. Results were verified using lifetime smoking and alcohol use disorder. Reverse direction MR was undertaken to assess the potential for reverse causation. Results: Genetic predisposition to smoking initiation was significantly associated with increased FI (univariable MR: β = 0.345; 95% confidence interval [CI] = 0.316 to 0.374; p = 1.36E-113; multivariable MR: β = 0.219; 95% CI = 0.197 to 0.241; p = 2.44E-83). Genetically predicted alcohol consumption showed a suggestive association with the FI (univariable MR: β = -0.090; 95% CI = -0.151 to -0.029; p = 0.003; multivariable MR β = -0.153; 95% CI = -0.212 to -0.094; p = 2.03E-07), with inconsistent results in sensitivity analyses. In complementary analysis, genetic predicted lifetime smoking, but not alcohol use disorder was associated with the FI. There is no convincing evidence for reverse causation. Conclusion: The present MR study supported smoking as a causal risk factor of frailty. Further research is warranted to investigate whether alcohol consumption has a causal role in frailty.

Tea ingredients can effectively inhibit SARS-CoV-2 infection at adequate concentrations. It is not known whether tea intake could impact the susceptibility to COVID-19 or its severity. We aimed to evaluate the causal effects of tea intake on COVID-19 outcomes. We performed Mendelian randomization (MR) analyses to assess the causal associations between tea intake (N = 441,279) and three COVID-19 outcomes, including SARS-CoV-2 infection (122,616 cases and 2,475,240 controls), hospitalized COVID-19 (32,519 cases and 2,062,805 controls), and critical COVID-19 (13,769 cases and 1,072,442 controls). The MR analyses indicated that genetic propensity for tea consumption conferred a negative causal effect on the risk of SARS-CoV-2 infection (OR: 0.87, 95% confidence interval (CI): 0.78-0.97, P = 0.015). No causal effects on hospitalized COVID-19 (0.84, 0.64-1.10, P = 0.201) or critical COVID-19 (0.73, 0.51-1.03, P = 0.074) were detected. Our study revealed that tea intake could decrease the risk of SARS-CoV-2 infection, highlighting the potential preventive effect of tea consumption on COVID-19 transmission.

Type 2 diabetes (T2D) is a chronic metabolic disorder with high comorbidity with mental disorders. The genetic links between attention-deficit/hyperactivity disorder (ADHD) and T2D have yet to be elucidated.

We aim to assess shared genetics and potential associations between ADHD and T2D.

We performed genetic correlation, two-sample Mendelian randomisation and polygenic overlap analyses between ADHD and T2D. The genome-wide association study (GWAS) summary results of T2D (80 154 cases and 853 816 controls), ADHD2019 (20 183 cases and 35 191 controls from the 2019 GWAS ADHD dataset) and ADHD2022 (38 691 cases and 275 986 controls from the 2022 GWAS ADHD dataset) were used for the analyses. The T2D dataset was obtained from the DIAGRAM Consortium. The ADHD datasets were obtained from the Psychiatric Genomics Consortium. We compared genome-wide association signals to reveal shared genetic variation between T2D and ADHD using the larger ADHD2022 dataset. Moreover, molecular pathways were constructed based on large-scale literature data to understand the connection between ADHD and T2D.

T2D has positive genetic correlations with ADHD2019 (r_g=0.33) and ADHD2022 (r_g=0.31). Genetic liability to ADHD2019 was associated with an increased risk for T2D (odds ratio (OR): 1.30, p<0.001), while genetic liability to ADHD2022 had a suggestive causal effect on T2D (OR: 1.30, p=0.086). Genetic liability to T2D was associated with a higher risk for ADHD2019 (OR: 1.05, p=0.001) and ADHD2022 (OR: 1.03, p<0.001). The polygenic overlap analysis showed that most causal variants of T2D are shared with ADHD2022. T2D and ADHD2022 have three overlapping loci. Molecular pathway analysis suggests that ADHD and T2D could promote the risk of each other through inflammatory pathways.

Our study demonstrates substantial shared genetics and bidirectional causal associations between ADHD and T2D.

The coronavirus disease 2019 (COVID-19) has been a major challenge to global health and a financial burden. Little is known regarding the possible causal effects of COVID-19 on the macro- and micro-structures of the human brain.

To determine the causal links between susceptibility, hospitalization, and the severity of COVID-19 and brain imaging-derived phenotypes (IDPs).

Mendelian randomization (MR) analyses were performed to investigate the causal effect of three COVID-19 exposures (SARS-CoV-2 infection, hospitalized COVID-19, and critical COVID-19) on brain structure employing summary datasets of genome-wide association studies.

In terms of cortical phenotypes, hospitalization due to COVID-19 was associated with a global decrease in the surface area (SA) of the cortex structure (β= -624.77, 95% CI: -1227.88 to -21.66, p = 0.042). At the regional level, SARS-CoV-2 infection was found to have a nominally causal effect on the thickness (TH) of the postcentral region (β= -0.004, 95% CI: -0.007 to -0.001, p = 0.01), as well as eight other IDPs. Hospitalized COVID-19 has a nominally causal relationship with TH of postcentral (β= -0.004, 95% CI: -0.007 to -0.001, p = 0.01) and other 6 IDPs. The nominally causal effects of critical COVID-19 on TH of medial orbitofrontal (β=0.004, 95% CI: 0.001to 0.007, p = 0.004) and other 7 IDPs were revealed.

Our study provides compelling genetic evidence supporting causal relationships between three COVID-19 traits and brain IDPs. This discovery holds promise for enhancing predictions and interventions in brain imaging.

We aimed to evaluate whether major depressive disorder (MDD) could aggravate the outcomes of coronavirus disease 2019 (COVID-19) or whether the genetic liability to COVID-19 could trigger MDD.

We aimed to assess bidirectional causal associations between MDD and COVID-19.

We performed genetic correlation and Mendelian randomisation (MR) analyses to assess potential associations between MDD and three COVID-19 outcomes. Literature-based network analysis was conducted to construct molecular pathways connecting MDD and COVID-19.

We found that MDD has positive genetic correlations with COVID-19 outcomes (r_g: 0.10-0.15). Our MR analysis indicated that genetic liability to MDD is associated with increased risks of COVID-19 infection (odds ratio (OR)=1.05, 95% confidence interval (CI): 1.00 to 1.10, p=0.039). However, genetic liability to the three COVID-19 outcomes did not confer any causal effects on MDD. Pathway analysis identified a panel of immunity-related genes that may mediate the links between MDD and COVID-19.

Our study suggests that MDD may increase the susceptibility to COVID-19. Our findings emphasise the need to increase social support and improve mental health intervention networks for people with mood disorders during the pandemic.

(1) To summarize the mental conditions that may accompany persistent symptoms following acute infection by SARS-CoV-2, often termed Long Covid; (2) to formulate treatment based upon the brain cells that are dominantly affected.

(1) Review the reports relating to the mental symptoms occurring in Long Covid. (2) Review the drugs that address the brain cells affected in Long Covid, and suggest pharmacotherapy for those patients whose response to psychotherapy is suboptimal.

Long Covid affects ~ 10% of patients infected by SARS-CoV-2, and mental symptoms affect ~ 20% of persons with Long Covid. The brain cell-types that have been demonstrated as dominantly affected in Long Covid are astrocytes, oligodendrocytes, neurons, endothelial cells/pericytes, and microglia. Lithium and fluoxetine each address all of those four cell-types. Low dosage of each is likely to be well-tolerated and to cause neither clinically important adverse events (AE) nor serious adverse events (SAE).

For those patients whose response to psychotherapy is suboptimal, lithium and fluoxetine should be administered in combination for both depth of benefit and reduction of dosages.

Due to the COVID-19 pandemic, both the university hospital and the city hospital have faced a significant patient load in our city. During this period, academic articles were written that contributed significantly to the literature on both hospitals struggling with patient density. In our study, we aimed to compile medical articles about COVID-19 in our city using the Web of Science and PubMed database.