Zheng et al reported the first genomewide association study (GWAS) to identify genetic risk factors of haemorrhoidal disease (HEM). In the study, the authors observed that HEM patients had a higher incidence of gastrointestinal domains, particularly diverticular disease and irritable bowel syndrome (IBS). Subsequently, they concluded the standpoint by analysing healthcare records, diagnoses and medication datasets. Nevertheless, such associations reported in the epidemiological study are often unreliable estimates of causal effects and can be interfered with by confounding or other forms of bias. To evaluate the causality of HEM on diverticular disease and IBS more accurately, we conducted an indepth statistical analysis based on twosample Mendelian randomisation (MR). Different from the conventional observational study, MR analysis treated genetic variants as instrumental variables (IVs) for exposures, effectively minimising potential bias caused by confounding and reverse causation (figure 1A). Genetic variants for investigating the causal effects of HEM (Ncase=218 920, Ncontrol=725 213) on diverticular disease (Ncase=31 964, Ncontrol=419 135) 4 and IBS (Ncase=11 168, Ncontrol=473 430) 5 were screened from the GWAS summary statistics of European descent. Briefly, the genetic variant that satisfies the following relevance assumptions was regarded as IV: (1) having a strong correlation with HEM (p<5×10); (2) not in linkage disequilibrium (R<0.001 within 10 kb, the 1000 Genomes Project European panel); and (3) having no correlation with diverticular disease and IBS (p>0.05). These standards allowed us to construct powerful aggregate IVs for making MR inferences. Here we mainly used the inversevariance weighted (IVW) method for MR analysis. When genetic variants affect the outcome via pathways independent of the exposure, it will cause pleiotropy, a violation of exclusion restriction assumption and a source of bias in MR studies. Hence, the MREgger regression was conducted for pleiotropy evaluation, which slope can provide pleiotropycorrected causal estimates. Unexpectedly, the IVW result demonstrated that HEM significantly decreased the incidence of diverticular disease (bIVW=−4.64×10 , PIVW=3.65×10 , figure 1B) and IBS (bIVW=−1.97×10 , PIVW=1.21×10 , figure 1B) both genetically and statistically, which was not in line with the observation of Zheng et al. Subsequently, the low intercepts obtained from MREgger regression further indicated that the directional genetic pleiotropy was unlikely to cause a bias in diverticular disease. The pleiotropy impacts on IBS were not neglected, potentially due to the large number of single nucleotide polymorphisms (SNPs) considered or the heterogenous grouping of IBS (table 1). The Q statistics were calculated to explain why there was little evidence of heterogeneity in the association between HEM and diverticular disease or IBS (table 1). Besides, the weighted median and simple median methods yielded similar causal estimates in magnitude and direction, and the reliability and robustness were indicated by sensitivity analyses (table 1). Finally, we assessed the global exploration of the homogeneity assumption to manifest a consistent trend across the validation set, despite partial results with slightly decreased statistical power (table 1, figure 1C), possibly caused by differences in genotyping procedure and study design. Our findings emphasised the unpredictable genetic protective effect of HEM against diverticular disease and IBS might exceed expectations. The patients might attribute any anorectal symptoms to HEM, thereby being selfmedicated with Letter

ObjectiveWe aimed to investigate the relationships among nut consumption, gut microbiota, and body fat distribution.MethodsWe studied 2255 Chinese adults in the Lanxi Cohort living in urban areas in Lanxi City, China. Fat distribution was assessed by dual-energy x-ray absorptiometry, and nut consumption was assessed using food frequency questionnaires. 16S ribosomal RNA (rRNA) sequencing was performed on stool samples from 1724 participants. Linear regression and Spearman correlation were used in all analyses. A validation study was performed using 1274 participants in the Lanxi Cohort living in rural areas.ResultsNut consumption was beneficially associated with regional fat accumulation. Gut microbial analysis suggested that a high intake of nuts was associated with greater microbial alpha diversity. Six genera were found to be associated with nut consumption, and the abundance of genera Anaerobutyricum, Anaerotaenia, and Fusobacterium was significantly associated with fat distribution. Favorable relationships between alpha diversity and fat distribution were also observed. Similar relationships between gut microbiota and fat distribution were obtained in the validation analysis.ConclusionsWe have shown that nut consumption is beneficially associated with body fat distribution and gut microbiota diversity and taxonomy. Furthermore, the microbial features related to high nut intake are associated with a favorable pattern of fat distribution.

Comprehending the molecular basis of quantitative genetic variation is a principal goal for complex diseases or traits. Molecular quantitative trait loci (molQTLs) have made it possible to investigate the effects of genetic variants hiding behind large-scale omics data. A deeper understanding of molQTL is urgently required in light of the multi-dimensionalization of omics data to more fully elucidate the pertinent biological mechanisms. Herein, we reviewed molQTLs with the corresponding resource from the omics perspective and further discussed the integrative strategy of GWAS-molQTL to infer their causal effects. Subsequently, we described the opportunities and challenges encountered by molQTL. The case studies showed that molQTL is essential for complex diseases and traits, whether single- or multi-omics QTLs. Overall, we highlighted the functional significance of genetic variants to employ the discovery of molQTL in complex diseases and traits.

Genome‐wide association study (GWAS) could identify host genetic factors associated with coronavirus disease 2019 (COVID‐19). The genes or functional DNA elements through which genetic factors affect COVID‐19 remain uncharted. The expression quantitative trait locus (eQTL) provides a path to assess the correlation between genetic variations and gene expression. Here, we firstly annotated GWAS data to describe genetic effects, obtaining genome‐wide mapped genes. Subsequently, the genetic mechanisms and characteristics of COVID‐19 were investigated by an integrated strategy that included three GWAS‐eQTL analysis approaches. It was found that 20 genes were significantly associated with immunity and neurological disorders, including prior and novel genes such as OAS3 and LRRC37A2. The findings were then replicated in single‐cell datasets to explore the cell‐specific expression of causal genes. Furthermore, associations between COVID‐19 and neurological disorders were assessed as a causal relationship. Finally, the effects of causal protein‐coding genes of COVID‐19 were discussed using cell experiments. The results revealed some novel COVID‐19‐related genes to emphasize disease characteristics, offering a broader insight into the genetic architecture underlying the pathophysiology of COVID‐19.

The elevated levels of inflammatory cytokines have attracted much attention during the treatment of COVID-19 patients. The conclusions of current observational studies are often controversial in terms of the causal effects of COVID-19 on various cytokines because of the confounding factors involving underlying diseases. To resolve this problem, we conducted a Mendelian randomization analysis by integrating the GWAS data of COVID-19 and 41 cytokines. As a result, the levels of 2 cytokines were identified to be promoted by COVID-19 and had unsignificant pleiotropy. In comparison, the levels of 10 cytokines were found to be inhibited and had unsignificant pleiotropy. Among down-regulated cytokines, CCL2, CCL3 and CCL7 were members of CC chemokine family. We then explored the potential molecular mechanism for a significant causal association at a single cell resolution based on single-cell RNA data, and discovered the suppression of CCL3 and the inhibition of CCL3-CCR1 interaction in classical monocytes (CMs) of COVID-19 patients. Our findings may indicate that the capability of COVID-19 in decreasing the chemotaxis of lymphocytes by inhibiting the CCL3-CCR1 interaction in CMs.

Since the first report of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019, over 100 million people have been infected by COVID-19, millions of whom have died. In the latest year, a large number of omics data have sprung up and helped researchers broadly study the sequence, chemical structure and function of SARS-CoV-2, as well as molecular abnormal mechanisms of COVID-19 patients. Though some successes have been achieved in these areas, it is necessary to analyze and mine omics data for comprehensively understanding SARS-CoV-2 and COVID-19. Hence, we reviewed the current advantages and limitations of the integration of omics data herein. Firstly, we sorted out the sequence resources and database resources of SARS-CoV-2, including protein chemical structure, potential drug information and research literature resources. Next, we collected omics data of the COVID-19 hosts, including genomics, transcriptomics, microbiology and potential drug information data. And subsequently, based on the integration of omics data, we summarized the existing data analysis methods and the related research results of COVID-19 multi-omics data in recent years. Finally, we put forward SARS-CoV-2 (COVID-19) multi-omics data integration research direction and gave a case study to mine deeper for the disease mechanisms of COVID-19.

This study aims to investigate the impact of COVID-19 lockdown on lifestyle behaviors and depressive symptom among patients with NCDs (noncommunicable diseases). We incorporated a COVID-19 survey to the WELL China cohort, a prospective cohort study with the baseline survey conducted 8–16 months before the COVID-19 outbreak in Hangzhou, China. The COVID-19 survey was carried out to collect information on lifestyle and depressive symptom during lockdown. A total of 3327 participants were included in the COVID-19 survey, including 2098 (63.1%) reported having NCDs at baseline and 1457 (44%) without NCDs. The prevalence of current drinkers decreased from 42.9% before COVID-19 lockdown to 23.7% during lockdown, current smokers from 15.9 to 13.5%, and poor sleepers from 23.9 to 15.3%, while low physical activity increased from 13.4 to 25.2%, among participants with NCDs (P < 0.05 for all comparisons using McNemar's test). Participants with NCDs were more likely than those without to have depressive symptom (OR, 1.30; 95% CI 1.05–1.61), especially among those who need to refill their medication during the COVID-19 lockdown (OR, 1.52; 95% CI 1.15–2.02). Our findings provide insight into the development of targeted interventions to better prepare patients with NCDs and healthcare system to meet the challenge of future pandemic and lockdown.

Microbial communities are found throughout the biosphere, from human guts to glaciers, from soil to activated sludge. Understanding the statistical properties of such diverse communities can pave the way to elucidate the common mechanisms ...Multiple ecological forces act together to shape the composition of microbial communities. Phyloecology approaches—which combine phylogenetic relationships between species with community ecology—have the potential to disentangle such forces but are often ...

Abstract Since the first report of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in December 2019, over 100 million people have been infected by COVID-19, millions of whom have died. In the latest year, a large number of omics data have sprung up and helped researchers broadly study the sequence, chemical structure and function of SARS-CoV-2, as well as molecular abnormal mechanisms of COVID-19 patients. Though some successes have been achieved in these areas, it is necessary to analyze and mine omics data for comprehensively understanding SARS-CoV-2 and COVID-19. Hence, we reviewed the current advantages and limitations of the integration of omics data herein. Firstly, we sorted out the sequence resources and database resources of SARS-CoV-2, including protein chemical structure, potential drug information and research literature resources. Next, we collected omics data of the COVID-19 hosts, including genomics, transcriptomics, microbiology and potential drug information data. And subsequently, based on the integration of omics data, we summarized the existing data analysis methods and the related research results of COVID-19 multi-omics data in recent years. Finally, we put forward SARS-CoV-2 (COVID-19) multi-omics data integration research direction and gave a case study to mine deeper for the disease mechanisms of COVID-19.

Transcriptional regulation is an important part of human gene expression regulation. Transcription factors(TF) are important components of transcription regulation. Because of the development of ChIP-chip and ChIP-seq as well as the development of bioinformatics. In recent years, many databases of transcription factor have been generated.These databases are very important for studying on transcription regulation and TFs. This paper reviews current well-known databases related to human TFs, and provides helps for further exploring the molecular mechanisms underlying transcriptional regulation.

The population is commonly susceptible to the 2019 novel coronavirus (2019-nCoV), especially the elderly with comorbidities. Elderly patients infected with 2019-nCoV tend to have higher rates of severe illness and mortality. Immunosenescence is an important cause of severe novel coronavirus pneumonia (NCP) in the elderly. Due to the combination of underlying diseases, elderly patients may exhibit atypical manifestations in clinical symptoms, supplementary examinations, and pulmonary imaging, deserving particular attention. The general condition of the elderly should be considered during diagnosis and treatment. In addition to routine care and measures-such as oxygen therapy, antiviral therapy, and respiratory support-treatment of underlying disease, nutritional support, sputum expectoration complication prevention, and psychological support should also be considered for elderly patients. Based on a literature review and expert panel discussion, we drafted the "Recommendations for the Prevention and Treatment of the Novel Coronavirus Pneumonia in the elderly in China," aiming to provide help with the prevention and treatment of NCP and the reduction of harm to the elderly population.