Reconstruction of the full transmission dynamics of COVID-19 in Wuhan.

As countries in the world review interventions for containing the pandemic of coronavirus disease 2019 (COVID-19), important lessons can be drawn from the study of the full transmission dynamics of its causative agent-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)- in Wuhan (China), where vigorous non-pharmaceutical interventions have suppressed the local outbreak of this disease1. Here we use a modelling approach to reconstruct the full-spectrum dynamics of COVID-19 in Wuhan between 1 January and 8 March 2020 across 5 periods defined by events and interventions, on the basis of 32,583 laboratory-confirmed cases1. Accounting for presymptomatic infectiousness2, time-varying ascertainment rates, transmission rates and population movements3, we identify two key features of the outbreak: high covertness and high transmissibility. We estimate 87% (lower bound, 53%) of the infections before 8 March 2020 were unascertained (potentially including asymptomatic and mildly symptomatic individuals); and a basic reproduction number (R0) of 3.54 (95% credible interval 3.40-3.67) in the early outbreak, much higher than that of severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS)4,5. We observe that multipronged interventions had considerable positive effects on controlling the outbreak, decreasing the reproduction number to 0.28 (95% credible interval 0.23-0.33) and-by projection-reducing the total infections in Wuhan by 96.0% as of 8 March 2020. We also explore the probability of resurgence following the lifting of all interventions after 14 consecutive days of no ascertained infections; we estimate this probability at 0.32 and 0.06 on the basis of models with 87% and 53% unascertained cases, respectively-highlighting the risk posed by substantial covert infections when changing control measures. These results have important implications when considering strategies of continuing surveillance and interventions to eventually contain outbreaks of COVID-19.

Investigating the shared genetic architecture and causal relationship between pain and neuropsychiatric disorders.

Pain often occurs in parallel with neuropsychiatric disorders. However, the underlying mechanisms and potential causality have not been well studied. We collected the genome-wide association study (GWAS) summary statistics of 26 common pain and neuropsychiatric disorders with sample size ranging from 17,310 to 482,730 in European population. The genetic correlation between pair of pain and neuropsychiatric disorders, as well as the relevant cell types were investigated by linkage disequilibrium (LD) score regression analyses. Then, transcriptome-wide association study (TWAS) was applied to identify the potential shared genes by integrating the gene expression information and GWAS. In addition, Mendelian randomization (MR) analyses were conducted to infer the potential causality between pain and neuropsychiatric disorders. Among the 169 pairwise pain and neuropsychiatric disorders, 55 pairs showed positive correlations (median rg = 0.43) and 9 pairs showed negative correlations (median rg = -0.31). Using MR analyses, 26 likely causal associations were identified, including that neuroticism and insomnia were risk factors for most of short-term pain, and multisite chronic pain was risk factor for neuroticism, insomnia, major depressive disorder and attention deficit/hyperactivity disorder, and vice versa. The signals of pain and neuropsychiatric disorders tended to be enriched in the functional regions of cell types from central nervous system (CNS). A total of 19 genes shared in at least one pain and neuropsychiatric disorder pair were identified by TWAS, including AMT, NCOA6, and UNC45A, which involved in glycine degradation, insulin secretion, and cell proliferation, respectively. Our findings provided the evidence of shared genetic structure, causality and potential shared pathogenic mechanisms between pain and neuropsychiatric disorders, and enhanced our understanding of the comorbidities of pain and neuropsychiatric disorders.

Genetic and observational associations of lung function with gastrointestinal tract diseases: pleiotropic and mendelian randomization analysis.

BACKGROUND: The two-way communications along the gut-lung axis influence the immune function in both gut and lung. However, the shared genetic characteristics of lung function with gastrointestinal tract (GIT) diseases remain to be investigated. METHODS: We first investigated the genetic correlations between three lung function traits and four GIT diseases. Second, we illustrated the genetic overlap by genome-wide pleiotropic analysis (PLACO) and further pinpointed the relevant tissue and cell types by partitioning heritability. Furthermore, we proposed pleiotropic genes as potential drug targets by drug database mining. Finally, we evaluated the causal relationships by epidemiologic observational study and Mendelian randomization (MR) analysis. RESULTS: We found lung function and GIT diseases were genetically correlated. We identified 258 pleiotropic loci, which were enriched in gut- and lung-specific regions marked by H3K4me1. Among these, 16 pleiotropic genes were targets of drugs, such as tofacitinib and baricitinib targeting TYK2 for the treatment of ulcer colitis and COVID-19, respectively. We identified a missense variant in TYK2, exhibiting a shared causal effect on FEV1/FVC and inflammatory bowel disease (rs12720356, PPLACO=1.38 × 10- 8). These findings suggested TYK2 as a promising drug target. Although the epidemiologic observational study suggested the protective role of lung function in the development of GIT diseases, no causalities were found by MR analysis. CONCLUSIONS: Our study suggested the shared genetic characteristics between lung function and GIT diseases. The pleiotropic variants could exert their effects by modulating gene expression marked by histone modifications. Finally, we highlighted the potential of pleiotropic analyses in drug repurposing.

Feasible intervention combinations for achieving a safe exit of the Zero-COVID policy in China and its determinants: an individual-based model study.

BACKGROUND: Although several pathways have been proposed as the prerequisite for a safe phase-out in China, it is not clear which of them are the most important for keeping the mortality rate low, what thresholds should be achieved for these most important interventions, and how the thresholds change with the assumed key epidemiological parameters and population characteristics. METHODS: We developed an individual-based model (IBM) to simulate the transmission of the Omicron variant in the synthetic population, accounting for the age-dependent probabilities of severe clinical outcomes, waning vaccine-induced immunity, increased mortality rates when hospitals are overburdened, and reduced transmission when self-isolated at home after testing positive. We applied machine learning algorithms on the simulation outputs to examine the importance of each intervention parameter and the feasible intervention parameter combinations for safe exits, which is defined as having mortality rates lower than that of influenza in China (14.3 per 100, 000 persons). RESULTS: We identified vaccine coverage in those above 70 years old, number of ICU beds per capita, and the availability of antiviral treatment as the most important interventions for safe exits across all studied locations, although the thresholds required for safe exits vary remarkably with the assumed vaccine effectiveness, as well as the age structure, age-specific vaccine coverage, community healthcare capacity of the studied locations. CONCLUSIONS: The analytical framework developed here can provide the basis for further policy decisions that incorporate considerations about economic costs and societal impacts. Achieving safe exits from the Zero-COVID policy is possible, but challenging for China's cities. When planning for safe exits, local realities such as the age structure and current age-specific vaccine coverage must be taken into consideration.

Integrative analysis of scRNA-seq and GWAS data pinpoints periportal hepatocytes as the relevant liver cell types for blood lipids.

Liver, a heterogeneous tissue consisting of various cell types, is known to be relevant for blood lipid traits. By integrating summary statistics from genome-wide association studies (GWAS) of lipid traits and single-cell transcriptome data of the liver, we sought to identify specific cell types in the liver that were most relevant for blood lipid levels. We conducted differential expression analyses for 40 cell types from human and mouse livers in order to construct the cell-type specifically expressed gene sets, which we refer to as construction of the liver cell-type specifically expressed gene sets (CT-SEGS). Under the assumption that CT-SEGS represented specific functions of each cell type, we applied stratified linkage disequilibrium score regression to determine cell types that were most relevant for complex traits and diseases. We first confirmed the validity of this method (of delineating functionally relevant cell types) by identifying the immune cell types as relevant for autoimmune diseases. We further showed that lipid GWAS signals were enriched in the human and mouse periportal hepatocytes. Our results provide important information to facilitate future cellular studies of the metabolic mechanism affecting blood lipid levels.

Propagation dynamics and control policies of COVID-19 pandemic at early stages: Implications on future resurgence response.

The spreading of novel coronavirus (SARS-CoV-2) has gravely impacted the world in the last year and a half. Understanding the spatial and temporal patterns of how it spreads at the early stage and the effectiveness of a governments' immediate response helps our society prepare for future COVID-19 waves or the next pandemic and contain it before the spreading gets out of control. In this article, a susceptible-exposed-infectious-removed model is used to model the city-to-city spreading patterns of the disease at the early stage of its emergence in China (from December 2019 to February 2020). Publicly available reported case numbers in 312 Chinese cities and between-city mobility data are leveraged to estimate key epidemiological characteristics, such as the transmission rate and the number of infectious people for each city. It is discovered that during any given time period, there are always only a few cities that are responsible for spreading the disease to other cities. We term these few cities as transmission centers. The spatial and temporal changes in transmission centers demonstrate predictable patterns. Moreover, rigorously designed experiments show that in controlling the disease spread in a city, non-pharmaceutical interventions (NPIs) implemented at transmission centers are more effective than the NPI implemented in the city itself. These findings have implications on the control of an infectious disease at the early stage of its spreading: implementing NPIs at transmission centers at early stages is effective in controlling the spread of infectious diseases.

Incubation period of coronavirus disease 2019: new implications for intervention and control.

The COVID-19 pandemic has been causing serious disasters to mankind. The incubation period is a key parameter for epidemic control and also an important basis for epidemic prediction, but its distribution law remains unclear. This paper analyzed the epidemiological information of 787 confirmed non-Wuhan resident cases, and systematically studied the characteristics of the incubation period of COVID-19 based on the interval-censored data estimation method. The results show that the incubation period of COVID-19 approximately conforms to the Gamma distribution with a mean value of 7.8 (95%CI:7.4-8.5) days and a median value of 7.0 (95%CI:6.7-7.3) days. The incubation period was positively correlated with age and negatively correlated with disease severity. Female cases presented a slightly higher incubation period than that of males. The proportion of infected persons who developed symptoms within 14 days was 91.6%. These results are of great significance to the prevention and control of the COVID-19 pandemic.

Identifying and exploiting trait-relevant tissues with multiple functional annotations in genome-wide association studies.

Genome-wide association studies (GWASs) have identified many disease associated loci, the majority of which have unknown biological functions. Understanding the mechanism underlying trait associations requires identifying trait-relevant tissues and investigating associations in a trait-specific fashion. Here, we extend the widely used linear mixed model to incorporate multiple SNP functional annotations from omics studies with GWAS summary statistics to facilitate the identification of trait-relevant tissues, with which to further construct powerful association tests. Specifically, we rely on a generalized estimating equation based algorithm for parameter inference, a mixture modeling framework for trait-tissue relevance classification, and a weighted sequence kernel association test constructed based on the identified trait-relevant tissues for powerful association analysis. We refer to our analytic procedure as the Scalable Multiple Annotation integration for trait-Relevant Tissue identification and usage (SMART). With extensive simulations, we show how our method can make use of multiple complementary annotations to improve the accuracy for identifying trait-relevant tissues. In addition, our procedure allows us to make use of the inferred trait-relevant tissues, for the first time, to construct more powerful SNP set tests. We apply our method for an in-depth analysis of 43 traits from 28 GWASs using tissue-specific annotations in 105 tissues derived from ENCODE and Roadmap. Our results reveal new trait-tissue relevance, pinpoint important annotations that are informative of trait-tissue relationship, and illustrate how we can use the inferred trait-relevant tissues to construct more powerful association tests in the Wellcome trust case control consortium study.

Association of Public Health Interventions With the Epidemiology of the COVID-19 Outbreak in Wuhan, China.

IMPORTANCE: Coronavirus disease 2019 (COVID-19) has become a pandemic, and it is unknown whether a combination of public health interventions can improve control of the outbreak. OBJECTIVE: To evaluate the association of public health interventions with the epidemiological features of the COVID-19 outbreak in Wuhan by 5 periods according to key events and interventions. DESIGN, SETTING, AND PARTICIPANTS: In this cohort study, individual-level data on 32 583 laboratory-confirmed COVID-19 cases reported between December 8, 2019, and March 8, 2020, were extracted from the municipal Notifiable Disease Report System, including patients' age, sex, residential location, occupation, and severity classification. EXPOSURES: Nonpharmaceutical public health interventions including cordons sanitaire, traffic restriction, social distancing, home confinement, centralized quarantine, and universal symptom survey. MAIN OUTCOMES AND MEASURES: Rates of laboratory-confirmed COVID-19 infections (defined as the number of cases per day per million people), across age, sex, and geographic locations were calculated across 5 periods: December 8 to January 9 (no intervention), January 10 to 22 (massive human movement due to the Chinese New Year holiday), January 23 to February 1 (cordons sanitaire, traffic restriction and home quarantine), February 2 to 16 (centralized quarantine and treatment), and February 17 to March 8 (universal symptom survey). The effective reproduction number of SARS-CoV-2 (an indicator of secondary transmission) was also calculated over the periods. RESULTS: Among 32 583 laboratory-confirmed COVID-19 cases, the median patient age was 56.7 years (range, 0-103; interquartile range, 43.4-66.8) and 16 817 (51.6%) were women. The daily confirmed case rate peaked in the third period and declined afterward across geographic regions and sex and age groups, except for children and adolescents, whose rate of confirmed cases continued to increase. The daily confirmed case rate over the whole period in local health care workers (130.5 per million people [95% CI, 123.9-137.2]) was higher than that in the general population (41.5 per million people [95% CI, 41.0-41.9]). The proportion of severe and critical cases decreased from 53.1% to 10.3% over the 5 periods. The severity risk increased with age: compared with those aged 20 to 39 years (proportion of severe and critical cases, 12.1%), elderly people (≥80 years) had a higher risk of having severe or critical disease (proportion, 41.3%; risk ratio, 3.61 [95% CI, 3.31-3.95]) while younger people (<20 years) had a lower risk (proportion, 4.1%; risk ratio, 0.47 [95% CI, 0.31-0.70]). The effective reproduction number fluctuated above 3.0 before January 26, decreased to below 1.0 after February 6, and decreased further to less than 0.3 after March 1. CONCLUSIONS AND RELEVANCE: A series of multifaceted public health interventions was temporally associated with improved control of the COVID-19 outbreak in Wuhan, China. These findings may inform public health policy in other countries and regions.

Pleiotropic mapping and annotation selection in genome-wide association studies with penalized Gaussian mixture models.

Motivation: Genome-wide association studies (GWASs) have identified many genetic loci associated with complex traits. A substantial fraction of these identified loci is associated with multiple traits-a phenomena known as pleiotropy. Identification of pleiotropic associations can help characterize the genetic relationship among complex traits and can facilitate our understanding of disease etiology. Effective pleiotropic association mapping requires the development of statistical methods that can jointly model multiple traits with genome-wide single nucleic polymorphisms (SNPs) together. Results: We develop a joint modeling method, which we refer to as the integrative MApping of Pleiotropic association (iMAP). iMAP models summary statistics from GWASs, uses a multivariate Gaussian distribution to account for phenotypic correlation, simultaneously infers genome-wide SNP association pattern using mixture modeling and has the potential to reveal causal relationship between traits. Importantly, iMAP integrates a large number of SNP functional annotations to substantially improve association mapping power, and, with a sparsity-inducing penalty, is capable of selecting informative annotations from a large, potentially non-informative set. To enable scalable inference of iMAP to association studies with hundreds of thousands of individuals and millions of SNPs, we develop an efficient expectation maximization algorithm based on an approximate penalized regression algorithm. With simulations and comparisons to existing methods, we illustrate the benefits of iMAP in terms of both high association mapping power and accurate estimation of genome-wide SNP association patterns. Finally, we apply iMAP to perform a joint analysis of 48 traits from 31 GWAS consortia together with 40 tissue-specific SNP annotations generated from the Roadmap Project. Availability and implementation: iMAP is freely available at http://www.xzlab.org/software.html. Supplementary information: Supplementary data are available at Bioinformatics online.

Polymorphisms of HOMER1 gene are associated with piglet splay leg syndrome and one significant SNP can affect its intronic promoter activity in vitro.

BACKGROUND: In our previous genome-wide association study (GWAS) on the piglet splay leg (PSL) syndrome, the homer scaffolding protein 1 (HOMER1) was detected as a candidate gene. The aim of this work was to further verify the candidate gene by sequencing the gene and find the significantly associated mutation. Then we preliminarily analyzed the effect of the significant SNP on intronic promoter activity. This research provided a reference for further investigation of the pathogenesis of PSL. RESULT: We investigated the 19 SNPs on HOMER1 and found 12 SNPs significant associated with PSL, including 8 SNPs resided in the potential intronic promoter region in intron 4. The - 663~ - 276 bp upstream the exon 5 had promoter activity and it could be an intronic promoter that regulated the transcription of HOMER1-205 transcript. The promoter activity of the - 663~ - 276 bp containing the rs339135425 and rs325197091 mutant alleles was significantly higher than of the wild type (P < 0.05). The G allele of rs325197091 (A > G) may create a new binding site of transcription factor aryl hydrocarbon receptor nuclear translocator (ARNT) and could enhance HOMER1 intronic promoter activity. CONCLUSIONS: HOMER1 gene was associated with the PSL, and the rs325197091 could influence HOMER1 intronic promoter activity in vitro.

Rab11a is required for porcine reproductive and respiratory syndrome virus induced autophagy to promote viral replication.

Porcine reproductive and respiratory syndrome virus (PRRSV) is the leading virus known to cause massive economic loss in pig industry worldwide. In our previous study, transcriptional profiling of PRRSV-infected lung tissue of Tongcheng and Landrane pigs, which have highly pathogenic PRRSV (HP-PRRSV) susceptibility differences, showed differential expression of Rab11a. The small GTPase Rab11a regulates intracellular membrane trafficking events involved in autophagy. However, the involvement of the convergence of endosomal Rab11a and autophagy pathways during PRRSV infection is still unclear. In this study, we demonstrated that PRRSV infection induced complete autophagy and up-regulated the expression of Rab11a. Furthermore, interference of the expression of Rab11a resulted in the accumulation of endogenous LC3-II and p62, indicating that Rab11a played a vital role in autophagosome maturation. Silencing of Rab11a resulted in a compromise the expression of intracellular viral NSP2 and ORF7. Besides, confocal microscopy analysis showed that viral NSP2 was colocalized with Rab11a in Marc145 cells. Collectively, our findings revealed that Rab11a acted as a proviral host factor that benefited PRRSV replication in a manner that correlates with autophagy.

Genome-wide association study identifies candidate genes for piglet splay leg syndrome in different populations.

BACKGROUND: Piglet splay leg syndrome (PSL) is one of the most frequent genetic defects, and can cause considerable economic loss in pig production. The present understanding of etiology and pathogenesis of PSL is poor. The current study focused on identifying loci associated with PSL through a genome-wide association study (GWAS) performed with the Illumina Porcine60 SNP Beadchip v2.0. The study was a case/control design with four pig populations (Duroc, Landrace, Yorkshire and one crossbred of Landrace × Yorkshire). RESULT: After quality control of the genotyping data, 185 animals (73 cases, 112 controls) and 43,495 SNPs were retained for further analysis. Principal components (PCs) identified from the genomic kinship matrix were included in the statistical model for correcting the effect of population structure. Seven chromosome-wide significant SNPs were identified on Sus scrofa chromosome 1 (SSC1), SSC2 (2 SNPs), SSC7, SSC15 (2 SNPs) and SSC16 after strict Bonferroni correction. Four genes (HOMER1 and JMY on SSC2, ITGA1 on SSC16, and RAB32 on SSC1) related to muscle development, glycogen metabolism and mitochondrial dynamics were identified as potential candidate genes for PSL. CONCLUSIONS: We identified seven chromosome-wide significant SNPs associated with PSL and four potential candidate genes for PSL. To our knowledge, this is the first pilot study aiming to identify the loci associated with PSL using GWAS. Further investigations and validations for those findings are encouraged.

Association of MAP4K4 gene single nucleotide polymorphism with mastitis and milk traits in Chinese Holstein cattle.

The objective of the studies presented in this Research Communication was to investigate the association of single nucleotide polymorphisms present in the MAP4K4 gene with different milk traits in dairy cows. Based on previous QTL fine mapping results on bovine chromosome 11, the MAP4K4 gene was selected as a candidate gene to evaluate its effect on somatic cell count and milk traits in ChineseHolstein cows. Milk production traits including milk yield, fat percentage, and protein percentage of each cow were collected using 305 d lactation records. Association between MAP4K4 genotype and different traits and Somatic Cell Score (SCS) was performed using General Linear Regression Model of R. Two SNPs at exon 18 (c.2061T > G and c.2196T > C) with genotype TT in both SNPs were found significantly higher for somatic SCS. We found the significant effect of exon 18 (c.2061T > G) on protein percentage, milk yield and SCS. We identified SNPs at different location of MAP4K4 gene of the cattle and several of them were significantly associated with the somatic cell score and other different milk traits. Thus, MAP4K4 gene could be a useful candidate gene for selection of dairy cattle against mastitis and the identified polymorphisms might potentially be strong genetic markers.

SUMOylation: A link to future therapeutics.

SUMOylation, much of a similar process like ubiquitination catches attention across various research groups as a potential therapeutic target to fight various infectious and cancerous diseases. This idea take its strength from recent reports which unearth the molecular mechanisms of SUMOylation and its involvement in important diseases distributed across various kingdoms. At the beginning SUMOylation was considered a process affected only by viral diseases but subsequent reports enlighten its role in diseases caused by bacteria as well. This enhances the SUMOylation canvas and demanded more in-depth study of the process. The present review is an attempt to study the regulatory mechanism of genes when the natural SUMOylation pathway is disturbed, the cross-talk among SUMOylation and other post translational modifications, the role of miRNAs in controlling the function of transcripts, loading of RNA species into exosomes and the possible SUMOylation related therapeutic targets.

Associations of prior pulmonary tuberculosis with the incident COPD: a prospective cohort study.

BACKGROUND: Prior pulmonary tuberculosis (PTB) might be associated with the development of chronic obstructive pulmonary disease (COPD). However, the impact of prior PTB on the risk of incident COPD has not been studied in a large prospective cohort study of the European population. OBJECTIVES: This study aimed to investigate the association of prior PTB with the risk of COPD. DESIGN: Prospective cohort study. METHODS: A multivariable Cox proportional model was used to estimate the hazard ratio (HR) and 95% confidence interval (95% CI) for the association of prior PTB with COPD. Subgroup analyses were further conducted among individuals stratified by age, sex, body mass index, smoking status, drinking status, physical activity, and polygenic risk score (PRS). RESULTS: The study involved a total of 216,130 participants, with a median follow-up period of 12.6 years and 2788 incident cases of COPD. Individuals with a prior history of PTB at baseline had an 87% higher risk of developing incident COPD compared to those without such history [adjusted hazard ratio (aHR) = 1.87; 95% confidence interval (CI): 1.26-2.77; p = 0.002]. Subgroup analysis revealed that individuals having prior PTB history presented a higher risk of incident COPD among individuals who were aged from 50 to 59 years with aHR of 2.47 (1.02-5.95, p = 0.044), older than 59 years with aHR of 1.81 (1.16-2.81, p = 0.008), male with aHR of 2.37 (1.47-3.83, p < 0.001), obesity with aHR of 3.35 (2.16-5.82, p < 0.001), previous smoking with aHR of 2.27 (1.39-3.72, p < 0.001), current drinking with aHR of 1.98 (1.47-3.83, p < 0.001), low physical activity with aHR of 2.62 (1.30-5.26, p = 0.007), and low PRS with aHR of 3.24 (1.61-6.53, p < 0.001), as well as high PRS with aHR of 2.43 (1.15-5.14, p = 0.019). CONCLUSION: A history of PTB is an important independent risk factor for COPD. Clinical staff should be aware of this risk factor in patients with prior PTB, particularly in countries or regions with high burdens of PTB.

Associations of prior pulmonary tuberculosis with the incident COPDPrior pulmonary tuberculosis (PTB) indicates that an individual has a history of PTB. The impact of prior PTB on the risk of incident chronic obstructive pulmonary disease (COPD) has not been studied in a large prospective cohort study of European population. Here, we investigated the association between prior PTB and risk of COPD in 216,130 participants from the UK biobank (a large biomedical database). After a median follow up of more than 12 years, 2,788 incident COPD cases were recorded. Individuals with prior PTB at baseline had an 87% higher risk of developing incident COPD compared to those without history of PTB. Specifically, individuals with prior PTB presented with a higher risk of incident COPD among those who were older than 50 years, male, obese, had a previous history of smoking, are currently drinking, have low physical activity, and have a low and high genetic predicted lung function. This study suggested prior PTB as an important and independent risk factor for COPD. Clinical staff should be aware of this risk factor in patients with prior PTB, particularly in countries or regions with high burdens of PTB.

Blood Calcium, Genetic Risk, and Risk of Incident Kidney Stone: A Population-Based Cohort Study.

OBJECTIVE: To investigate the association between blood calcium concentration and incident kidney stone as well as to assess the role played by genetic susceptibility. METHODS: We performed a population-based cohort study based on participants from the UK Biobank. A multivariable Cox proportional hazards regression model was used to estimate hazard ratios (HRs) and 95% CIs of incident kidney stone for blood calcium level and polygenic risk score (PRS). In addition, the potential interaction was explored. The study was conducted from January 28, 2023, through June 4, 2023. RESULTS: During the follow-up of 423,301 participants with a total of 5,490,332 person-years (median follow-up of 13.4 years), 4502 cases of kidney stone were recorded. Compared with the low blood calcium concentration group (first tertile), individuals in the high (third tertile) and moderate (second tertile) concentration groups had higher risks of kidney stone with HRs of 1.24 (95% CI, 1.15 to 1.33) and 1.11 (1.04 to 1.20), respectively. The PRS for kidney stone contained 40 independent single-nucleotide polymorphisms and was used to assign individuals to 3 groups according to the quintile. Participants with high (Q5) and moderate (Q2 to Q4) genetic risks had increased risks of kidney stone compared with low (Q1) genetic risk with HRs of 1.70 (1.53 to 1.89) and 1.31 (1.20 to 1.44), respectively. There was a joint cumulative risk of incident kidney stone between blood calcium concentration and genetic susceptibility. CONCLUSIONS: Blood calcium concentration and PRS are significantly associated with incident kidney stone risk. Excessive blood calcium concentration might bring additional stone risk in populations at high genetic risk. A nonlinear correlation between blood calcium concentration and kidney stone risk was indicated.

Identification of biomarkers and potential therapeutic targets for pancreatic cancer by proteomic analysis in two prospective cohorts.

Pancreatic cancer (PC) is the deadliest malignancy due to late diagnosis. Aberrant alterations in the blood proteome might serve as biomarkers to facilitate early detection of PC. We designed a nested case-control study of incident PC based on a prospective cohort of 38,295 elderly Chinese participants with ∼5.7 years' follow-up. Forty matched case-control pairs passed the quality controls for the proximity extension assay of 1,463 serum proteins. With a lenient threshold of p < 0.005, we discovered regenerating family member 1A (REG1A), REG1B, tumor necrosis factor (TNF), and phospholipase A2 group IB (PLA2G1B) in association with incident PC, among which the two REG1 proteins were replicated using the UK Biobank Pharma Proteomics Project, with effect sizes increasing steadily as diagnosis time approaches the baseline. Mendelian randomization analysis further supported the potential causal effects of REG1 proteins on PC. Taken together, circulating REG1A and REG1B are promising biomarkers and potential therapeutic targets for the early detection and prevention of PC.

Associations of Various Physical Activities with Mortality and Life Expectancy are Mediated by Telomere Length.

OBJECTIVES: Physical activity (PA) and telomeres both contribute to healthy aging and longevity. To investigate the optimal dosage of various PA for longevity and the role of telomere length in PA and mortality. DESIGN: Prospective cohort study. SETTING AND PARTICIPANTS: A total of 333,865 adults (mean age of 56 years) from the UK Biobank were analyzed. METHODS: Walking, moderate PA (MPA), and vigorous PA (VPA) were self-reported via questionnaire, and leukocyte telomere length (LTL) was measured. Cox proportional hazards regression was used to predict all-cause mortality risk. A flexible parametric Royston-Parmar survival model was used to estimate life expectancy. RESULTS: During a median follow-up of 13.8 years, 19,789 deaths were recorded. Compared with the no-walking group, 90 to 720 minutes/week of walking was similarly associated with 27% to 31% of lower mortality and about 6 years of additional life expectancy. We observed nearly major benefits for mortality and life expectancy among those meeting the PA guidelines [151-300 minutes/wk for MPA: hazard ratio (HR) 0.80, 95% CI 0.75-0.85, 3.40-3.42 additional life years; 76-150 minutes/wk for VPA: HR 0.78, 95% CI 0.75-0.82, 2.61 years (2.33-2.89)] vs the no-PA group. Similar benefits were also observed at 76-150 and 301-375 minutes/wk of MPA (18%-19% lower mortality, 3.20-3.42 gained years) or 151-300 minutes/wk of VPA (20%-26% lower mortality, 2.41-2.61 gained years). The associations between MPA, VPA, and mortality risk were slightly mediated by LTL (≈1% mediation proportion, both P < .001). CONCLUSIONS AND IMPLICATIONS: Our study suggests a more flexible range of PA than the current PA guidelines, which could gain similar benefits and is easier to achieve: 90 to 720 minutes/wk of walking, 75 to 375 minutes/wk of MPA, and 75 to 300 minutes/wk of VPA. Telomeres might be a potential mechanism by which PA promotes longevity.

Single cell transcriptome profiling of infrapatellar fat pad highlights the role of interstitial inflammatory fibroblasts in osteoarthritis.

OBJECTIVES: Osteoarthritis (OA) is a whole-joint disease in which the role of the infrapatellar fat pad (IFP) in its pathogenesis is unclear. Our study explored the cellular heterogeneity of IFP to understand OA and identify therapeutic targets. METHODS: Single-cell and single-nuclei RNA sequencing were used to analyze 10 IFP samples, comprising 5 from OA patients and 5 from healthy controls. Analyses included differential gene expression, enrichment, pseudotime trajectory, and cellular communication, along with comparative studies with visceral and subcutaneous fats. Key subcluster and pathways were validated using multiplex immunohistochemistry. RESULTS: The scRNA-seq performed on the IFPs of the OA and control group profiled the gene expressions of over 49,674 cells belonging to 11 major cell types. We discovered that adipose stem and progenitor cells (ASPCs), contributing to the formation of both adipocytes and synovial-lining fibroblasts (SLF). Interstitial inflammatory fibroblasts (iiFBs) were a subcluster of ASPCs that exhibit notable pro-inflammatory and proliferative characteristics. We identified four adipocyte subtypes, with one subtype showing a reduced lipid synthesis ability. Furthermore, iiFBs modulated the activities of macrophages and T cells in the IFP. Compared to subcutaneous and visceral adipose tissues, iiFBs represented a distinctive subpopulation of ASPCs in IFP that regulated cartilage proliferation through the MK pathway. CONCLUSION: This study presents a comprehensive single-cell transcriptomic atlas of IFP, uncovering its complex cellular landscape and potential impact on OA progression. Our findings highlight the role of iiFBs in OA, especially through MK pathway, opening new avenues for understanding OA pathogenesis and developing novel targeted therapies.