BACKGROUND AND OBJECTIVE

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) as the causative agent of COVID-19 has significantly challenged the public health landscape in late 2019. After almost 3 years of the first ever SARS-CoV-2 case, the World Health Organization (WHO) declared the end of this global health emergency in May 2023. Although, despite the subsequent drop of COVID-19 cases, the SARS-CoV-2 infection still exhibited multiple waves of infection, primarily attributed to the appearance of new variants. Five of these variants have been classified as Variants of Concern (VOC): Alpha, Beta, Gamma, Delta, and the most recent, Omicron. Therefore, the development of methods for the timely and accurate detection of viral variants remains fundamental, ensuring an ongoing and effective response to the disease. This study aims to evaluate the feasibility of the application of an in-house approach in genomic surveillance for the detection of SARS-CoV-2 variants using in silico designed primers.

METHODS

The primers used for the study were particularly designed based on conserved regions of certain genes in the virus, targeting distinct mutations found in known variants of SARS-CoV-2. Viral RNA extracts from nasopharyngeal samples (n=14) were subjected to quantitative and qualitative tests (Nanodrop and AGE). Selected samples were then analyzed by RT-PCR and amplicons were submitted for sequencing. Sequence alignment analysis was carried out to identify the prevailing COVID-19 variant present in the sample population.

RESULTS

The study findings demonstrated that the in-house method was able to successfully amplify conserved sequences (spike, envelope, membrane, ORF1ab) and enabled identification of the circulating SARS-CoV-2 variant among the samples. Majority of the samples were identified as Omicron variant. Three out of four designed primers effectively bound into the conserved sequence of target genes present in the sample, revealing the specific SARSCoV-2 variant. The detected mutations characterized for Omicron found in the identified lineages included K417N, S477N, and P681H which were also identified as mutations of interest. Furthermore, identification of the B.1.448 lineage which was not classified in any known variant also provided the potential of the developed in-house method in detecting unknown variants of COVID-19.

CONCLUSION

Among the five VOCs, Omicron is the most prevalent and dominant variant. The in-house direct PCR product sequencing surveillance (DPPSS) method provided an alternative platform for SAR-CoV-2 variant analysis which is accessible and affordable than the conventional diagnostic surveillance methods and the whole genome sequencing. Further evaluation and improvements on the oligonucleotide primers may offer significant contribution to the development of a specific and direct PCRbased detection of new emerging COVID-19 variants.

Sars-cov-2 ; Polymerase Chain Reaction ; Dna Primers ; Oligonucleotide Primers ; Computer Simulation ; Conserved Sequence ; Coronavirus ; Covid-19 ; Disease ; Emergencies ; Evaluation Studies As Topic ; Genes ; Genome ; Global Health ; Health ; Identification (psychology) ; Infection ; Infections ; Membranes ; Methods ; Mutation ; Oligonucleotides ; Organizations ; Population ; Public Health ; Rna ; Rna, Viral ; Sars Virus ; Sequence Alignment ; Severe Acute Respiratory Syndrome ; Syndrome ; Viruses ; Whole Genome Sequencing ; World Health Organization

OBJECTIVE: To explore the potential causal relationship between intervertebral disc degeneration and certain autoimmune diseases. METHODS: Genome-wide association study (GWAS) data of 5 autoimmune diseases were obtained from large-scale GWAS databases. Data on internal vertebral disc degeneration (IVDD) were derived from the FinnGen consortium, which included 294, 770 controls and 41, 669 cases. A two-sample bidirectional Mendelian randomization (MR) analysis was performed to investigate the potential causal relationship between the 5 autoimmune diseases and IVDD. Multiple analytical methods were adopted, including MR methods such as inverse variance weighting(IVW), MR-Egger, weighted median, weighted mode, and simple mode. Cochran's Q test, leave-one-out analysis, and MR-Egger intercept test were conducted to assess heterogeneity, robustness, and pleiotropy. For the robustness of the results, MR-PRESSO was used to detect outliers, and MR analysis was re-conducted after removing the outliers. RESULTS: The MR analysis results showed that there might be a bidirectional causal relationship between ankylosing spondylitis(AS) and IVDD:AS on IVDD, OR=1.038, 95%CI (1.024, 1.053), P=0.000;and IVDD on AS, OR=2.117, 95%CI(1.065, 4.207), P=0.032. There might be a positive correlation between IVDD and rheumatoid arthritis(RA) as well as systemic lupus erythematosus(SLE):IVDD on RA, OR=1.184, 95%CI(1.071, 1.309), P=0.001;and IVDD on SLE, OR=1.678, 95%CI(1.187, 2.372), P=0.003. There was no significant correlation between ulcerative colitis(UC), autoimmune thyroiditis(ATD) and IVDD. After removing outliers by MR-PRESSO and re-conducting MR analysis, the results did not change qualitatively. Sensitivity analysis indicated that the results were robust to potential sources of bias. CONCLUSION AS and IVDD may be risk factors for each other, and IVDD may be a potential risk factor for RA and SLE. These findings provide a basis for guiding the prevention and combined diagnosis and treatment of IVDD, AS, RA, and SLE, while the specific underlying mechanisms still require further experimental basic research.
Humans ; Intervertebral Disc Degeneration/etiology* ; Mendelian Randomization Analysis ; Autoimmune Diseases/complications* ; Genome-Wide Association Study ; Spondylitis, Ankylosing/genetics* ; Arthritis, Rheumatoid/genetics*

OBJECTIVE: To screen out the key metabolites related to diabetic foot (DF) by integrating genome-wide association studies (GWAS) and metabolome genome-wide association studies (mGWAS). METHODS: The literature databases such as PubMed and China national knowledge infrastructure(CNKI), as well as genomics databases such as PAN UKBB, FinnGen, and IEU Open GWAS were systematically retrieved from database estobilishment to November 2024 on DF-related single nucleotide polymorphisms and genome-wide association studies. DF-single nucleotide polymorphism-metabolite network was constructed by mGWAS package and mGWAS-Explorer platform. The causal relationship between key factors was evaluated by two-sample Mendelian randomization. The genetic correlation between DF and 575 metabolites (source:IEU Open GWAS) was evaluated by linkage disequilibrium score regression. In vitro experiments were conducted to induce injury of human umbilical vein endothelial cells with 30 mM glucose and intervene with 20 μM γ-tocopherol. Changes in cell migration, scratch healing and tube formation function were detected. RESULTS: Twenty-senen literatures on single nucleotide polymorphism literatures and 3 studies on GWAS were included. Genetic analysis results showed DF-related single nucleotide polymorphisms were enriched in vascular endothelial dysfunction-related pathways (such as fluid shear stress and atherosclerosis). The results of metabolic network analysis screened out 19 associated metabolites, among which 12 such as γ -tocopherol and pyruvate had significant genetic correlations with DF. Mendelian randomization suggested matrix metalloproteinase-9(MMP-9) might be a potential driver of DF (β=0.658, P=0.063 8), and the occurrence of DF could reduce the level of high-density lipoprotein (β=-0.002, P=0.015 2). The results of in vitro experiments confirmed that γ -tocopherol could improve endothelial dysfunction induced by high glucose, specifically manifested as an increase in the number of cell migrations, improvement in the scratch healing rate, and recovery of tubule formation ability (P<0.05). CONCLUSION DF has a genetic basis centered on vascular endothelial dysfunction, and its occurrence can lead to further metabolic disorders. The key single nucleotide polymorphism loci integrated provided molecular markers for the risk stratification of foot ulcers in diabetic patients. In addition, γ -tocopherol has demonstrated clinical application potential as a therapeutic drug for DF by significantly improving the function of vascular endothelial cells in a high-glucose environment.
Humans ; Diabetic Foot/drug therapy* ; Polymorphism, Single Nucleotide ; Genome-Wide Association Study ; Genomics ; Metabolomics ; Metabolome

OBJECTIVES: To analyze the potential causal relationship between gut microbiota and food allergy (FA) using two-sample Mendelian randomization (MR) methods. METHODS: Data from genome-wide association studies on gut microbiota and FA were utilized. MR analysis was conducted employing inverse variance weighting, MR-Egger regression, and weighted median methods to assess the causal relationship between gut microbiota and FA. Cochrane's Q test was used to evaluate heterogeneity of instrumental variables, MR-PRESSO analysis was conducted to test for outliers and pleiotropy, and MR-Egger regression was employed to assess horizontal pleiotropy. The "leave-one-out" method was used to evaluate the impact of removing individual single nucleotide polymorphisms on the causal relationship. RESULTS: Inverse variance weighting analysis revealed that the phylum Verrucomicrobia, family Verrucomicrobiaceae, order Verrucomicrobiales, genus Ruminococcaceae UCG013, and genus Akkermansia were negatively associated with FA (P<0.05). Sensitivity analyses confirmed the reliability of the findings, indicating no heterogeneity or pleiotropy present. CONCLUSIONS There is a causal relationship between gut microbiota and FA, with Verrucomicrobia, Verrucomicrobiaceae, Verrucomicrobiales, Ruminococcaceae UCG013, and Akkermansia potentially reducing the risk of developing FA. These findings provide potential targets for the treatment and prevention of FA; however, further research is needed to explore the specific mechanisms by which the microbiota influence FA.
Humans ; Mendelian Randomization Analysis ; Gastrointestinal Microbiome ; Food Hypersensitivity/microbiology* ; Genome-Wide Association Study ; Polymorphism, Single Nucleotide

OBJECTIVES: To evaluate the causal association between circulating levels of zinc, magnesium, and other minerals and autism spectrum disorder (ASD). METHODS: A two-sample Mendelian randomization (MR) analysis was performed using summary statistics from large-scale genome-wide association studies of European populations, including 18 382 ASD cases and 27 969 controls. Genetic data for iron, calcium, and magnesium were obtained from the UK Biobank, and data for zinc and selenium were sourced from an Australian-British cohort. A total of 351 genetic instrumental variables were selected. Causal inference was performed using inverse-variance weighting as the primary analysis method. Sensitivity analyses were performed by Cochran's Q test and MR-PRESSO global test to assess the robustness of the findings. RESULTS: No statistically significant causal effect was observed for circulating zinc, magnesium, calcium, selenium, or iron levels on ASD risk (all P>0.05). The odds ratios and 95% confidence intervals from the inverse-variance weighting analysis were 0.934 (0.869-1.003) for zinc, 1.315 (0.971-1.850) for magnesium, 1.055 (0.960-1.159) for calcium, 1.015 (0.953-1.080) for selenium, and 0.946 (0.687-1.303) for iron. Sensitivity analysis revealed significant heterogeneity in the causal association between circulating calcium and ASD (P=0.006), while the effect estimate remained stable after MR-PRESSO correction (P=0.487). The causal effect estimates for the remaining minerals demonstrated good robustness. CONCLUSIONS This study did not find significant evidence supporting a causal association between circulating zinc, magnesium, calcium, selenium, or iron levels and ASD risk, providing important clues for the etiology of ASD and precision nutritional interventions.
Humans ; Mendelian Randomization Analysis ; Autism Spectrum Disorder/genetics* ; Magnesium/blood* ; Zinc/blood* ; Minerals/blood* ; Genome-Wide Association Study ; Selenium/blood*

OBJECTIVES: The gut microbiota plays a crucial role in the pathophysiology of various types of diabetes. However, the causal relationship between them has yet to be systematically elucidated. This study aims to explore the potential causal associations between gut microbiota and diabetes using a two-sample Mendelian randomization (MR) analysis, based on multiple taxonomic levels. METHODS: Eligible instrumental variables were extracted from the selected genome-wide association study (GWAS) data on gut microbiota. These were combined with GWAS datasets on type 1 diabetes (T1D), type 2 diabetes (T2D), and gestational diabetes mellitus (GDM) to conduct forward MR analysis, sensitivity analysis, reverse MR analysis, and validation of significant estimates. Microbial taxa with causal effects on T1D, T2D, and GDM were identified based on a comprehensive assessment of all analytical stages. RESULTS: A total of 2 179, 2 176, and 2 166 single nucleotide polymorphisms (SNP) were included in the MR analyses for gut microbiota with T1D, T2D, and GDM, respectively. MR results indicated causal associations between: Six microbial taxa (Eggerthella, Lachnospira, Bacillales, Desulfovibrionales, Parasutterella, and Turicibacter) and T1D; 9 microbial taxa (Verrucomicrobia, Deltaproteobacteria, Actinomycetales, Desulfovibrionale, Actinomycetaceae, Desulfovibrionaceae, Actinomyces, Alcaligenaceae, and Lachnospiraceae NC2004 group) and T2D; 10 microbial taxa (Betaproteobacteria, Coprobacter, Ruminococcus2, Tenericutes, Clostridia, Methanobacteria, Mollicutes, Methanobacteriales, Methanobacteriaceae, and Methanobrevibacter) and GDM. CONCLUSIONS This study identified specific gut microbial taxa that may significantly increase or decrease the risk of developing diabetes. Some findings were fully replicated in independent validation datasets. However, the underlying biological mechanisms of these causal relationships warrant further investigation through mechanistic studies and population-based research.
Gastrointestinal Microbiome/genetics* ; Humans ; Mendelian Randomization Analysis ; Genome-Wide Association Study ; Diabetes Mellitus, Type 2/genetics* ; Diabetes Mellitus, Type 1/genetics* ; Female ; Polymorphism, Single Nucleotide ; Diabetes, Gestational/genetics* ; Pregnancy

OBJECTIVES: Keloids are fibrotic skin disorders characterized by excessive collagen deposition and a high recurrence rate, closely associated with inflammatory mediators. However, existing epidemiological studies are limited by confounding factors and reverse causality, making it difficult to establish causation. This study aims to investigate the causal relationship between circulating cytokines and keloids using Mendelian randomization analysis. METHODS: Significant single nucleotide polymorphisms (SNPs) associated with circulating cytokines (exposures) and keloids (outcomes) were extracted from genome-wide association study (GWAS) summary datasets. Eligible SNPs were selected as instrumental variables (IVs). Exposure data were derived from a cytokine GWAS including 8 293 Finnish participants, and outcome data from a keloid GWAS based on the UK Biobank. The inverse-variance weighted (IVW) method served as the primary analytical approach to estimate causal effects, supplemented by weighted median (WME), MR-Egger regression, and other sensitivity analyses. Horizontal pleiotropy was assessed using MR-Egger regression and the MR pleiotropy residual sum and outlier (MR-PRESSO) test, while Cochran's Q test evaluated heterogeneity. Leave-one-out analysis was used to verify robustness and consistency. A reverse MR analysis was also conducted, with keloid as the exposure and cytokines as outcomes, to rule out reverse causation. RESULTS: IVW analysis identified significant positive causal associations between two cytokines and keloids-macrophage migration inhibitory factor (MIF) [odds ratio (OR)=2.081, 95% confidence interval (CI) 1.219 to 3.552, P=0.007] and monocyte chemoattractant protein-1 (MCP-1) (OR=1.673, 95% CI 1.036 to 2.701, P=0.035). Conversely, stem cell factor (SCF) showed a negative causal relationship with keloids (OR=0.518, 95% CI 0.269 to 0.998, P=0.049). Results from the MR-Egger and weighted median analyses were consistent with IVW findings. No evidence of horizontal pleiotropy was observed (P>0.05). Except for interleukin-6 (P=0.014), no heterogeneity was detected in other cytokines. Leave-one-out analysis further confirmed the robustness of the causal associations. In reverse MR analysis, keloids were causally related only to β-nerve growth factor (beta-NGF) (OR=1.048, 95% CI 1.002 to 1.095, P=0.039), with no heterogeneity or pleiotropy detected in most cytokines (P>0.05). CONCLUSIONS MIF and MCP-1 exhibit positive causal associations with keloid formation, while SCF shows a negative causal relationship. These findings provide new evidence for the causal involvement of inflammatory cytokines in keloid pathogenesis and offer potential molecular targets for developing novel keloid therapies.
Humans ; Keloid/blood* ; Mendelian Randomization Analysis ; Cytokines/genetics* ; Polymorphism, Single Nucleotide ; Genome-Wide Association Study ; Chemokine CCL2/genetics* ; Interleukin-6/genetics* ; Macrophage Migration-Inhibitory Factors/genetics* ; Male ; Stem Cell Factor/blood* ; Female ; Intramolecular Oxidoreductases

OBJECTIVES: To investigate the causal associations between autoimmune diseases and aplastic anemia (AA) using Mendelian randomization analysis. METHODS: Publicly available genome-wide association study (GWAS) data were utilized to obtain single nucleotide polymorphisms (SNPs) associated with autoimmune diseases and AA for analysis. The inverse variance weighted (IVW) method was employed as the primary analytical approach, with MR Egger, Weighted Mode, Weighted Median, and Simple Mode methods serving as complementary analyses. Heterogeneity and pleiotropy analyses were conducted using designated functions, and the robustness of Mendelian randomization results was assessed using leave-one-out analysis. RESULTS: The two-sample Mendelian randomization analysis using the IVW method revealed significant positive causal associations of rheumatoid arthritis (OR=1.094, 95% CI: 1.023-1.170, P=0.009, adjusted P=0.042), systemic lupus erythematosus (OR=1.111, 95% CI: 1.021-1.208, P=0.015, adjusted P=0.036), Hashimoto thyroiditis (OR=1.206, 95% CI: 1.049-1.387, P=0.009, adjusted P=0.029), and Sicca syndrome (OR=1.173, 95% CI: 1.054-1.306, P=0.004, adjusted P=0.035) with AA, which was supported by the results from the Weighted Median method. Sensitivity analyses indicated no evidence of pleiotropy or heterogeneity, and leave-one-out analysis confirmed the robustness of the causal relationships. No direct evidence was found linking Graves' disease, ulcerative colitis, Crohn's disease, autoimmune hepatitis, primary biliary cholangitis, or primary sclerosing cholangitis with AA (P>0.05, adjusted P>0.05), indicating a lack of causal association. Reverse Mendelian randomization results and multiple corrections indicated that AA was not an influencing factor for autoimmune diseases (adjusted P>0.05). CONCLUSIONS Our findings support at the genetic level that rheumatoid arthritis, systemic lupus erythematosus, Hashimoto thyroiditis, and Sicca syndrome are risk factors for AA, and confirm a causal association of the these 4 autoimmune diseases with an increased risk of AA.
Humans ; Mendelian Randomization Analysis ; Anemia, Aplastic/genetics* ; Autoimmune Diseases/complications* ; Polymorphism, Single Nucleotide ; Genome-Wide Association Study ; Arthritis, Rheumatoid/genetics* ; Lupus Erythematosus, Systemic/genetics* ; Genetic Predisposition to Disease

Early-onset colorectal cancer (EOCRC) shows a different epidemiological trend compared to later-onset colorectal cancer, with its incidence rising in most regions and countries worldwide. However, the reasons behind this trend remain unclear. The etiology of EOCRC is complex and could involve both genetic and environmental factors. Apart from Lynch syndrome and Familial Adenomatous Polyposis, sporadic EOCRC exhibits a broad spectrum of pathogenic germline mutations, genetic polymorphisms, methylation changes, and chromosomal instability. Early-life exposures and environmental risk factors, including lifestyle and dietary risk factors, have been found to be associated with EOCRC risk. Meanwhile, specific chronic diseases, such as inflammatory bowel disease, diabetes, and metabolic syndrome, have been associated with EOCRC. Interactions between genetic and environmental risk factors in EOCRC have also been explored. Here we present findings from a narrative review of epidemiological studies on the assessment of early-life exposures, of EOCRC-specific environmental factors, and their interactions with susceptible loci. We also present results from EOCRC-specific genome-wide association studies that could be used to perform Mendelian randomization analyses to ascertain potential causal links between environmental factors and EOCRC.
Humans ; Colorectal Neoplasms/etiology* ; Risk Factors ; Genome-Wide Association Study ; Genetic Predisposition to Disease/genetics*

Intelligence encompasses various abilities, including logical reasoning, comprehension, self-awareness, learning, planning, creativity, and problem-solving. Extensive research and practical experience suggest that there are sex differences in intellectual development, with females typically maturing earlier than males. However, the key genes and molecular network mechanisms underlying these sex differences in intellectual development remain unclear. To date, Genome-Wide Association Studies (GWAS) have identified 507 genes that are significantly associated with intelligence. This study first analyzed RNA sequencing data from different stages of brain development (from BrainSpan), revealing that during the late embryonic stage, the average expression levels of intelligence-related genes are higher in males than in females, while the opposite is observed during puberty. This study further constructed interaction networks of intelligence-related genes with sex-differential expression in the brain, including the prenatal male network (HELP-M: intelligence genes with higher expression levels in prenatal males) and the pubertal female network (HELP-F: intelligence genes with higher expression levels in pubertal females). The findings indicate that the key genes in both networks are Ep300 and Ctnnb1. Specifically, Ep300 regulates the transcription of 53 genes in both HELP-M and HELP-F, while Ctnnb1 regulates the transcription of 45 genes. Ctnnb1 plays a more prominent role in HELP-M, while Ep300 is more crucial in HELP-F. Finally, this study conducted sequencing validation on rats at different developmental stages, and the results indicated that in the prefrontal cortex of female rats during adolescence, the expression levels of the intelligence genes in HELP-F, as well as key genes Ep300 and Ctnnb1, were higher than those in male rats. These genes were also involved in neurodevelopment-related biological processes. The findings reveal a sex-differentiated intelligence gene network and its key genes, which exhibit varying expression levels during the neurodevelopmental process.
Female ; Intelligence/physiology* ; Male ; Sex Characteristics ; Animals ; Brain/growth & development* ; E1A-Associated p300 Protein/physiology* ; beta Catenin/physiology* ; Transcriptome ; Rats ; Gene Expression Profiling ; Genome-Wide Association Study