Genome-Wide Association Studies

Exploration of causal relationship between shoulder impingement syndrome and rotator cuff injury: a bidirectional mendelian randomization

BACKGROUP

The pathogenesis of shoulder impingement syndrome (SIS) is still unclear, and its questionable causal relationship with rotator cuff (RC) injury has led to confusion in treatment. The purpose of this study was to explore the bidirectional causal relationship between SIS and RC injury.

METHODS

SIS and RC injury datasets downloaded from the IEU Open GWAS project and GWAS catalog databases. Inverse variance weighted (IVW), MR Egger, Weighted median, and Weighted mode were used in this Mendelian randomization (MR) analysis. Cochran's Q test, leave-one-out, and funnel plot method were used to evaluate heterogeneity between single nucleotide polymorphisms (SNPs). MR-Egger regression was used to test the horizontal pleiotropy of this study.

RESULTS

The IVW method (OR = 1.189, P = 0.0059) suggest the putative causal effect of RC injury on SIS. The results of MR Egger method (OR = 1.236, P = 0.2013), weighted median method (OR = 1.097, P = 0.2428) and weighted mode method (OR = 1.013, P = 0.930) showed no statistically significant (OR = 1.069071, P = 0.6173). Heterogeneity test and horizontal pleiotropy analysis suggested that there was no significant heterogeneity and horizontal pleiotropy in the results of this MR analysis. The reverse MR analysis showed heterogeneity, and the conclusion needs to be further explored.

CONCLUSIONS

The results of MR analysis support that RC injury may be causally associated with SIS.

Novel Genes Associated With Atrial Fibrillation and the Predictive Models for AF Incorporating Polygenic Risk Score and PheWAS-Derived Risk Factors

BACKGROUND

Atrial fibrillation (AF), the most common atrial arrhythmia, presents with varied clinical manifestations. Despite the identification of genetic loci associated with AF, particularly in specific populations, research within Asian ethnicities remains limited. In this study we aimed to develop predictive models for AF using AF-associated single-nucleotide polymorphisms (SNPs) from a genome-wide association study (GWAS) on a substantial cohort of Taiwanese individuals, to evaluate the predictive efficacy of the model.

METHODS

There were 75,121 subjects, that included 5694 AF patients and 69,427 normal control subjects with GWAS data, and we merged polygenic risk scores from AF-associated SNPs with phenome-wide association study-derived risk factors. Advanced statistical and machine learning techniques were used to develop and evaluate AF predictive models for discrimination and calibration.

RESULTS

The study identified the top 30 significant SNPs associated with AF, predominantly on chromosomes 10 and 16, implicating genes like NEURL1, SH3PXD2A, INA, NT5C2, STN1, and ZFHX3. Notably, INA, NT5C2, and STN1 were newly linked to AF. The GWAS predictive power using polygenic risk score-continuous shrinkage analysis for AF exhibited an area under the curve of 0.600 (P < 0.001), which improved to 0.855 (P < 0.001) after adjusting for age and sex. Phenome-wide association study analysis showed the top 10 diseases associated with these genes were circulatory system diseases.

CONCLUSIONS

Integrating genetic and phenotypic data enhanced the accuracy and clinical relevance of AF predictive models. The findings suggest promise for refining AF risk assessment, enabling personalized interventions, and reducing AF-related morbidity and mortality burdens.

Genetic Analysis of Soybean Flower Size Phenotypes Based on Computer Vision and Genome-Wide Association Studies

The dimensions of organs such as flowers, leaves, and seeds are governed by processes of cellular proliferation and expansion. In soybeans, the dimensions of these organs exhibit a strong correlation with crop yield, quality, and other phenotypic traits. Nevertheless, there exists a scarcity of research concerning the regulatory genes influencing flower size, particularly within the soybean species. In this study, 309 samples of 3 soybean types (123 cultivar, 90 landrace, and 96 wild) were re-sequenced. The microscopic phenotype of soybean flower organs was photographed using a three-eye microscope, and the phenotypic data were extracted by means of computer vision. Pearson correlation analysis was employed to assess the relationship between petal and seed phenotypes, revealing a strong correlation between the sizes of these two organs. Through GWASs, SNP loci significantly associated with flower organ size were identified. Subsequently, haplotype analysis was conducted to screen for upstream and downstream genes of these loci, thereby identifying potential candidate genes. In total, 77 significant SNPs associated with vexil petals, 562 significant SNPs associated with wing petals, and 34 significant SNPs associated with keel petals were found. Candidate genes were screened by candidate sites, and haplotype analysis was performed on the candidate genes. Finally, the present investigation yielded 25 and 10 genes of notable significance through haplotype analysis in the vexil and wing regions, respectively. Notably, Glyma.07G234200, previously documented for its high expression across various plant organs, including flowers, pods, leaves, roots, and seeds, was among these identified genes. The research contributes novel insights to soybean breeding endeavors, particularly in the exploration of genes governing organ development, the selection of field materials, and the enhancement of crop yield. It played a role in the process of material selection during the growth period and further accelerated the process of soybean breeding material selection.

A Genotype-Phenotype Model for Predicting Resistance Training Effects on Leg Press Performance

This study develops a comprehensive genotype-phenotype model for predicting the effects of resistance training on leg press performance. A cohort of physically inactive adults (N=193) underwent 12 weeks of resistance training, and measurements of maximum isokinetic leg press peak force, muscle mass, and thickness were taken before and after the intervention. Whole-genome genotyping was performed, and genome-wide association analysis identified 85 novel SNPs significantly associated with changes in leg press strength after training. A prediction model was constructed using stepwise linear regression, incorporating seven lead SNPs that explained 40.4% of the training effect variance. The polygenic score showed a significant positive correlation with changes in leg press strength. By integrating genomic markers and phenotypic indicators, the comprehensive prediction model explained 75.4% of the variance in the training effect. Additionally, five SNPs were found to potentially impact muscle contraction, metabolism, growth, and development through their association with REACTOME pathways. Individual responses to resistance training varied, with changes in leg press strength ranging from -55.83% to 151.20%. The study highlights the importance of genetic factors in predicting training outcomes and provides insights into the potential biological functions underlying resistance training effects. The comprehensive model offers valuable guidance for personalized fitness programs based on individual genetic profiles and phenotypic characteristics.

SEEI: spherical evolution with feedback mechanism for identifying epistatic interactions

BACKGROUND

Detecting epistatic interactions (EIs) involves the exploration of associations among single nucleotide polymorphisms (SNPs) and complex diseases, which is an important task in genome-wide association studies. The EI detection problem is dependent on epistasis models and corresponding optimization methods. Although various models and methods have been proposed to detect EIs, identifying EIs efficiently and accurately is still a challenge.

RESULTS

Here, we propose a linear mixed statistical epistasis model (LMSE) and a spherical evolution approach with a feedback mechanism (named SEEI). The LMSE model expands the existing single epistasis models such as LR-Score, K2-Score, Mutual information, and Gini index. The SEEI includes an adaptive spherical search strategy and population updating strategy, which ensures that the algorithm is not easily trapped in local optima. We analyzed the performances of 8 random disease models, 12 disease models with marginal effects, 30 disease models without marginal effects, and 10 high-order disease models. The 60 simulated disease models and a real breast cancer dataset were used to evaluate eight algorithms (SEEI, EACO, EpiACO, FDHEIW, MP-HS-DHSI, NHSA-DHSC, SNPHarvester, CSE). Three evaluation criteria (pow1, pow2, pow3), a T-test, and a Friedman test were used to compare the performances of these algorithms. The results show that the SEEI algorithm (order 1, averages ranks = 13.125) outperformed the other algorithms in detecting EIs.

CONCLUSIONS

Here, we propose an LMSE model and an evolutionary computing method (SEEI) to solve the optimization problem of the LMSE model. The proposed method performed better than the other seven algorithms tested in its ability to identify EIs in genome-wide association datasets. We identified new SNP-SNP combinations in the real breast cancer dataset and verified the results. Our findings provide new insights for the diagnosis and treatment of breast cancer.

AVAILABILITY AND IMPLEMENTATION

https://github.com/scutdy/SSO/blob/master/SEEI.zip .

Genomic characterization and related functional genes of γ- poly glutamic acid producing Bacillus subtilis

γ- poly glutamic acid (γ-PGA), a high molecular weight polymer, is synthesized by microorganisms and secreted into the extracellular space. Due to its excellent performance, γ-PGA has been widely used in various fields, including food, biomedical and environmental fields. In this study, we screened natto samples for two strains of Bacillus subtilis N3378-2at and N3378-3At that produce γ-PGA. We then identified the γ-PGA synthetase gene cluster (PgsB, PgsC, PgsA, YwtC and PgdS), glutamate racemase RacE, phage-derived γ-PGA hydrolase (PghB and PghC) and exo-γ-glutamyl peptidase (GGT) from the genome of these strains. Based on these γ-PGA-related protein sequences from isolated Bacillus subtilis and 181 B. subtilis obtained from GenBank, we carried out genotyping analysis and classified them into types 1-5. Since we found B. amyloliquefaciens LL3 can produce γ-PGA, we obtained the B. velezensis and B. amyloliquefaciens strains from GenBank and classified them into types 6 and 7 based on LL3. Finally, we constructed evolutionary trees for these protein sequences. This study analyzed the distribution of γ-PGA-related protein sequences in the genomes of B. subtilis, B. velezensis and B. amyloliquefaciens strains, then the evolutionary diversity of these protein sequences was analyzed, which provided novel information for the development and utilization of γ-PGA-producing strains.

Causal relationship between atrial fibrillation/warfarin and cutaneous melanoma: a two-sample Mendelian randomization study

Purpose

In recent years, the relationship between malignant tumors and atrial fibrillation has attracted more and more attention. Atrial fibrillation can also cause a series of adverse events, such as the risk of thromboembolism. Also, Warfarin is often used here. But, the relationship between cutaneous melanoma and atrial fibrillation, and between cutaneous melanoma and warfarin is still unclear. Therefore, we used a two-sample Mendelian randomization to assess the causal relationship between atrial fibrillation/warfarin and cutaneous melanoma (cM).

Methods

Firstly, atrial fibrillation (ukb-b-11550; nCase = 3,518, nControl = 459,415) and warfarin (ukb-b-13248; nCase = 4,623, nControl = 458,310) as exposures, with genome-wide association studies (GWAS) data from the United Kingdom Biobank. And cM (ieu-b-4969; nCase = 3,751, nControl = 372,016) as outcome, with GWAS data from the IEU Open GWAS project. Subsequently, single-nucleotide polymorphisms (SNPs) were filtered from GWAS studies using quality control measures. In addition, two-sample Mendelian randomization (MR) analysis was performed to explore the causal relationship between atrial fibrillation or warfarin and cM and used inverse variance weighting (IVW) as the primary analytical method. Finally, relevant heterogeneity and sensitivity analysis were performed to ensure the accuracy of the results.

Results

A causal relationship between atrial fibrillation and cutaneous melanoma was observed, and between warfarin and cutaneous melanoma.

Conclusion

The atrial fibrillation may play a causal role in the development of cutaneous melanoma, but the mechanism and the causal relationship between warfarin and cutaneous melanoma needs to be further elucidated.

[Genetic factors associated with long COVID]

INTRODUCTION

The variability in expression and evolution of COVID is not completely explained by clinical factors. In fact, genetic factors play an important role. Moreover, it is unknown whether the genetic factor that contribute to susceptibility and severity are also involved in the onset and evolution of long-COVID. The objective of this review is to gather information from literature to understand which genetic factors are involved in the onset of persistent COVID.

MATERIAL AND METHODS

Systematic review in PubMed and bioRxiv and medRxiv repositories based on MeSH-descriptors and MeSH-terms related to COVID and genetic factors. Using these terms 2715 articles were pooled. An initial screening performed by authors independently, selected 205 articles of interest. A final deeper screening a total of 85 articles were chosen for complete reading and summarized in this review.

RESULTS

Although ACE2 and TMPSS6 are involved in COVID susceptibility, their involvement in long-COVID has not been found. On the other hand, the severity of the disease and the onset of long-COVID has been associated with different genes involved in the inflammatory and immune response. Particularly interesting has been the association found with the FOXP4 locus.

CONCLUSIONS

Although studies on long-COVID are insufficient to fully comprehend the cause, it is clear that the current identified genetic factors do not fully explain the progression and onset of long-COVID. Other factors such as polygenic action, pleiotropic genes, the microbiota and epigenetic changes must be considered and studied.

Leveraging the transcriptome to further our understanding of GWAS findings: eQTLs associated with genes related to LDL and LDL subclasses, in a cohort of African Americans

Background: GWAS discoveries often pose a significant challenge in terms of understanding their underlying mechanisms. Further research, such as an integration with expression quantitative trait locus (eQTL) analyses, are required to decipher the mechanisms connecting GWAS variants to phenotypes. An eQTL analysis was conducted on genes associated with low-density lipoprotein (LDL) cholesterol and its subclasses, with the aim of pinpointing genetic variants previously implicated in GWAS studies focused on lipid-related traits. Notably, the study cohort consisted of African Americans, a population characterized by a heightened prevalence of hypercholesterolemia. Methods: A comprehensive differential expression (DE) analysis was undertaken, with a dataset of 17,948 protein-coding mRNA transcripts extracted from the whole-blood transcriptomes of 416 samples to identify mRNA transcripts associated with LDL, with further granularity delineated between small LDL and large LDL subclasses. Subsequently, eQTL analysis was conducted with a subset of 242 samples for which whole-genome sequencing data were available to identify single-nucleotide polymorphisms (SNPs) associated with the LDL-related mRNA transcripts. Lastly, plausible functional connections were established between the identified eQTLs and genetic variants reported in the GWAS catalogue. Results: DE analysis revealed 1,048, 284, and 94 mRNA transcripts that exhibited differential expression in response to LDL, small LDL, and large LDL, respectively. The eQTL analysis identified a total of 9,950 significant SNP-mRNA associations involving 6,955 SNPs including a subset 101 SNPs previously documented in GWAS of LDL and LDL-related traits. Conclusion: Through comprehensive differential expression analysis, we identified numerous mRNA transcripts responsive to LDL, small LDL, and large LDL. Subsequent eQTL analysis revealed a rich landscape of eQTL-mRNA associations, including a subset of eQTL reported in GWAS studies of LDL and related traits. The study serves as a testament to the important role of integrative genomics in unraveling the enigmatic GWAS relationships between genetic variants and the complex fabric of human traits and diseases.

Genome-wide association study of Nelore and Angus heifers with low and high ovarian follicle counts

The number of antral follicles is considered an important fertility trait because animals with a high follicle count (HFC) produce more oocytes and embryos per cycle. Identification of these animals by genetic markers such as single nucleotide polymorphisms (SNPs) can accelerate selection of future generations. The aim of this study was to perform a genome wide association study (GWAS) on Nelore and Angus heifers with HFC and low (LFC) antral follicle counts. The groups HFC and LFC for genotyping were formed based on the average of total follicles (≥ 3 mm) counted in each breed consistently ± standard deviation. A total of 72 Nelore heifers (32 HFC and 40 LFC) and 48 Angus heifers (21 HFC and 27 LFC) were selected and the DNA was extracted from blood and hair bulb. Genotyping was done using the Illumina Bovine HD 770K BeadChip. The GWAS analysis showed 181 and 201 SNPs with genotype/phenotype association (P ≤ 0.01) in Nelore and Angus heifers, respectively. Functional enrichment analysis was performed on candidate genes that were associated with SNPs. A total of 97 genes were associated to the 181 SNPs in the Nelore heifers and the functional analysis identified genes (ROBO1 and SLIT3) in the ROBO-SLIT pathway that can be involved in the control of germ cell migration in the ovary as it is involved in lutheal cell migration and fetal ovary development. In the Angus heifers, 57 genes were associated with the 201 SNPs, highlighting Fribilin 1 (FBN1) gene, involved in regulation of growth factors directly involved in follicle activation and development. In summary, GWAS for Nelore and Angus heifers showed SNPs associated with higher follicle count phenotype. Furthermore, these findings offer valuable insights for the further investigation of potential mechanism involved in follicle formation and development, important for breeding programs for both breeds.

Using Genomics to Identify Novel Therapeutic Targets for Aortic Disease

Aortic disease, including dissection, aneurysm, and rupture, carries significant morbidity and mortality and is a notable cause of sudden cardiac death. Much of our knowledge regarding the genetic basis of aortic disease has relied on the study of individuals with Mendelian aortopathies and, until recently, the genetic determinants of population-level variance in aortic phenotypes remained unclear. However, the application of machine learning methodologies to large imaging datasets has enabled researchers to rapidly define aortic traits and mine dozens of novel genetic associations for phenotypes such as aortic diameter and distensibility. In this review, we highlight the emerging potential of genomics for identifying causal genes and candidate drug targets for aortic disease. We describe how deep learning technologies have accelerated the pace of genetic discovery in this field. We then provide a blueprint for translating genetic associations to biological insights, reviewing techniques for locus and cell type prioritization, high-throughput functional screening, and disease modeling using cellular and animal models of aortic disease.

Causal association of leisure sedentary behavior and cervical spondylosis, sciatica, intervertebral disk disorders, and low back pain: a Mendelian randomization study

Background

Some studies suggest sedentary behavior is a risk factor for musculoskeletal disorders. This study aimed to investigate the potential causal association between leisure sedentary behavior (LSB) (including television (TV) viewing, computer use, and driving) and the incidence of sciatica, intervertebral disk degeneration (IVDD), low back pain (LBP), and cervical spondylosis (CS).

Methods

We obtained the data of LSB, CS, IVDD, LBP, sciatica and proposed mediators from the gene-wide association studies (GWAS). The causal effects were examined by Inverse Variance Weighted (IVW) test, MR-Egger, weighted median, weighted mode and simple mode. And sensitivity analysis was performed using MR-Pleiotropy Residual Sum and Outlier (MR-PRESSO) and MR-Egger intercept test. Multivariable MR (MVMR) was conducted to investigate the independent factor of other LSB; while two-step MR analysis was used to explore the potential mediators including Body mass index (BMI), smoking initiation, type 2 diabetes mellitus (T2DM), major depressive disorder (MDD), schizophrenia, bipolar disorder between the causal association of LSB and these diseases based on previous studies.

Results

Genetically associated TV viewing was positively associated with the risk of CS (OR = 1.61, 95%CI = 1.25 to 2.07, p = 0.002), IVDD (OR = 2.10, 95%CI = 1.77 to 2.48, p = 3.79 × 10-18), LBP (OR = 1.84, 95%CI = 1.53 to 2.21, p = 1.04 × 10-10) and sciatica (OR = 1.82, 95% CI = 1.45 to 2.27, p = 1.42 × 10-7). While computer use was associated with a reduced risk of IVDD (OR = 0.66, 95%CI = 0.55 to 0.79, p = 8.06 × 10-6), LBP (OR = 0.49, 95%CI = 0.40 to 0.59, p = 2.68 × 10-13) and sciatica (OR = 0.58, 95%CI = 0.46 to 0.75, p = 1.98 × 10-5). Sensitivity analysis validated the robustness of MR outcomes. MVMR analysis showed that the causal effect of TV viewing on IVDD (OR = 1.59, 95%CI = 1.13 to 2.25, p = 0.008), LBP (OR = 2.15, 95%CI = 1.50 to 3.08, p = 3.38 × 10-5), and sciatica (OR = 1.61, 95%CI = 1.03 to 2.52, p = 0.037) was independent of other LSB. Furthermore, two-step MR analysis indicated that BMI, smoking initiation, T2DM may mediate the causal effect of TV viewing on these diseases.

Conclusion

This study provides empirical evidence supporting a positive causal association between TV viewing and sciatica, IVDD and LBP, which were potentially mediated by BMI, smoking initiation and T2DM.

The landscape of the methodology in drug repurposing using human genomic data: a systematic review

The process of drug development is expensive and time-consuming. In contrast, drug repurposing can be introduced to clinical practice more quickly and at a reduced cost. Over the last decade, there has been a significant expansion of large biobanks that link genomic data to electronic health record data, public availability of various databases containing biological and clinical information and rapid development of novel methodologies and algorithms in integrating different sources of data. This review aims to provide a thorough summary of different strategies that utilize genomic data to seek drug-repositioning opportunities. We searched MEDLINE and EMBASE databases to identify eligible studies up until 1 May 2023, with a total of 102 studies finally included after two-step parallel screening. We summarized commonly used strategies for drug repurposing, including Mendelian randomization, multi-omic-based and network-based studies and illustrated each strategy with examples, as well as the data sources implemented. By leveraging existing knowledge and infrastructure to expedite the drug discovery process and reduce costs, drug repurposing potentially identifies new therapeutic uses for approved drugs in a more efficient and targeted manner. However, technical challenges when integrating different types of data and biased or incomplete understanding of drug interactions are important hindrances that cannot be disregarded in the pursuit of identifying novel therapeutic applications. This review offers an overview of drug repurposing methodologies, providing valuable insights and guiding future directions for advancing drug repurposing studies.

Assessment of causal association between differentiated thyroid cancer and disordered serum lipid profile: a Mendelian randomization study

Background

Research has shown that the disordered serum lipid profile may be associated with the risk of differentiated thyroid cancer (DTC). Whether this association reflect causal effect is still unclear. The aim of this study was to evaluate the causality of circulating lipoprotein lipids on DTC.

Methods

Mendelian randomization (MR) analysis was conducted to evaluate the relationship between the circulating lipoprotein lipids and DTC risk using single-nucleotide polymorphisms (SNPs) from a genome-wide association (GWA) study containing a high-incidence Italian population of 690 cases samples with DTC and 497 controls.

Results

Univariate and multivariate mendelian randomization analysis demonstrated that 'total cholesterol', 'HDL cholesterol', 'apolipoprotein B' and 'ratio of apolipoprotein B to apolipoprotein A1' were correlated with DTC. According to sensitivity analysis, our results were reliable. Furthermore, multivariate analysis revealed that there is no causative association between DTC and any of the many cause factors when they interact with one another, suggesting that there was a deep interaction between the four factors, which could affect each other. Finally, the mechanism of the related effects each other as well as the target genes with significant SNP regulatory effects in DTC was explored by conducting functional enrichment analysis and constructing the regulatory networks.

Conclusions

We obtained four exposure factors (total cholesterol, HDL cholesterol, apolipoprotein B and ratio of apolipoprotein B to apolipoprotein A1) closely related to DTC, which laid a theoretical foundation for the treatment of DTC.

Genotype and phenotype data standardization, utilization and integration in the big data era for agricultural sciences

Large-scale genotype and phenotype data have been increasingly generated to identify genetic markers, understand gene function and evolution and facilitate genomic selection. These datasets hold immense value for both current and future studies, as they are vital for crop breeding, yield improvement and overall agricultural sustainability. However, integrating these datasets from heterogeneous sources presents significant challenges and hinders their effective utilization. We established the Genotype-Phenotype Working Group in November 2021 as a part of the AgBioData Consortium (https://www.agbiodata.org) to review current data types and resources that support archiving, analysis and visualization of genotype and phenotype data to understand the needs and challenges of the plant genomic research community. For 2021-22, we identified different types of datasets and examined metadata annotations related to experimental design/methods/sample collection, etc. Furthermore, we thoroughly reviewed publicly funded repositories for raw and processed data as well as secondary databases and knowledgebases that enable the integration of heterogeneous data in the context of the genome browser, pathway networks and tissue-specific gene expression. Based on our survey, we recommend a need for (i) additional infrastructural support for archiving many new data types, (ii) development of community standards for data annotation and formatting, (iii) resources for biocuration and (iv) analysis and visualization tools to connect genotype data with phenotype data to enhance knowledge synthesis and to foster translational research. Although this paper only covers the data and resources relevant to the plant research community, we expect that similar issues and needs are shared by researchers working on animals. Database URL: https://www.agbiodata.org.

Understanding the impact of structural modifications at the NNAT gene's post-translational acetylation site: in silico approach for predicting its drug-interaction role in anorexia nervosa

PURPOSE

Anorexia nervosa (AN) is a neuropsychological public health concern with a socially disabling routine and affects a person's healthy relationship with food. The role of the NNAT (Neuronatin) gene in AN is well established. The impact of mutation at the protein's post-translational modification (PTM) site has been exclusively associated with the worsening of the protein's biochemical dynamics.

METHODS

To understand the relationship between genotype and phenotype, it is essential to investigate the appropriate molecular stability of protein required for proper biological functioning. In this regard, we investigated the PTM-acetylation site of the NNAT gene in terms of 19 other specific amino acid probabilities in place of wild type (WT) through various in silico algorithms. Based on the highest pathogenic impact computed through the consensus classifier tool, we generated 3 residue-specific (K59D, P, W) structurally modified 3D models of NNAT. These models were further tested through the AutoDock Vina tool to compute the molecular drug binding affinities and inhibition constant (Ki) of structural variants and WT 3D models.

RESULTS

With trained in silico machine learning algorithms and consensus classifier; the three structural modifications (K59D, P, W), which were also the most deleterious substitution at the acetylation site of the NNAT gene, showed the highest structural destabilization and decreased molecular flexibility. The validation and quality assessment of the 3D model of these structural modifications and WT were performed. They were further docked with drugs used to manage AN, it was found that the ΔGbind (kcal/mol) values and the inhibition constants (Ki) were relatively lower in structurally modified models as compared to WT.

CONCLUSION

We concluded that any future structural variation(s) at the PTM-acetylation site of the NNAT gene due to possible mutational consequences, will serve as a basis to explore its relationship with the propensity of developing AN.

LEVEL OF EVIDENCE

No level of evidence-open access bioinformatics research.

Research progress and challenges of preimplantation genetic testing for polygenic diseases

Preimplantation genetic testing is an important part in assisted reproductive technology, which can block the intergenerational inheritance of a single gene or chromosomal diseases. Preimplantation genetic testing for polygenic disease risk (PGT-P) is one of the latest developments in the field. With the development of artificial intelligence and genetic detection technology, PGT-P can be used to analyze genetic material, calculate polygenic risk scores and convert these into incidence probability. Embryos with relatively low incidence probability can be screened for transfer, in order to reduce the possibility that the offspring suffers from the disease in the future. This has significant clinical and social significance. At present, PGT-P has been applied clinically and made phased progress at home and abroad. But as a developing technology, PGT-P still has some technical limitations as unstable results, environmental influences and racial differences cannot be ruled out. From the ethical perspective, if the screening indications are not strictly regulated, it is likely to cause new social problems. In this paper, we review the technical details and recent progress in PGT-P, and discuss the prospects of its future development, especially how to establish a complete and suitable screening model for Chinese population.

Bidirectional relationship between 56 peripheral inflammatory regulators and sleep apnea syndrome: A Mendelian randomization study

BACKGROUND

Peripheral inflammation plays an potential role in both pathogenesis and outcomes of sleep apnea syndrome (SAS). However, this topic has not been explored at the genetic level.

OBJECTIVES

The aim of the study was to investigate the genetic interaction between a total of 56 peripheral inflammatory regulators and SAS, and to further reveal the genetic association of SAS-related inflammatory regulators with several neurological disorders.

METHODS

Summary data for SAS, cerebral atherosclerosis, vascular dementia and peripheral concentrations of these inflammatory regulators were collected from genome-wide association studies. Instrumental variables were extracted from these data for causal inference of exposure and outcome using Two-sample Mendelian randomization methods. All analyses were performed using R (version 3.5.2).

RESULTS

First, of the included 56 inflammatory regulators, higher IL-25 level and lower IL-23, IL-24, IL-36γ and MIP-1a levels in peripheral circulation significantly increased the risk of SAS (P<0.05). Second, SAS significantly decreased the peripheral levels of IL-17A, IL-23, IL-27, IL-36α and TRAIL (P<0.05). Third, there was no genetic relationship between SAS and other inflammatory regulators (P>0.05). Fourth, in the SAS-related inflammatory regulators mentioned above, decreased levels of IL-17A and IL-27 in peripheral circulation were significantly associated with the increased risk of cerebral atherosclerosis, and decreased level of TRAIL promoted the elevation of vascular dementia risk (P<0.05).

CONCLUSION

There was a interaction between peripheral inflammation and SAS at the genetic level. Furthermore, peripheral inflammation might involved in the mechanism for SAS causing some neurological diseases mentioned above.

Unraveling the role of VLDL in the relationship between type 2 diabetes and coronary atherosclerosis: a Mendelian randomization analysis

Background

The causal link between Type 2 diabetes (T2D) and coronary atherosclerosis has been established through wet lab experiments; however, its analysis with Genome-wide association studies (GWAS) data remains unexplored. This study aims to validate this relationship using Mendelian randomization analysis and explore the potential mediation of VLDL in this mechanism.

Methods

Employing Mendelian randomization analysis, we investigated the causal connection between T2D and coronary atherosclerosis. We utilized GWAS summary statistics from European ancestry cohorts, comprising 23,363 coronary atherosclerosis patients and 195,429 controls, along with 32,469 T2D patients and 183,185 controls. VLDL levels, linked to SNPs, were considered as a potential mediating causal factor that might contribute to coronary atherosclerosis in the presence of T2D. We employed the inverse variance weighted (IVW), Egger regression (MR-Egger), weighted median, and weighted model methods for causal effect estimation. A leave-one-out sensitivity analysis was conducted to ensure robustness.

Results

Our Mendelian randomization analysis demonstrated a genetic association between T2D and an increased coronary atherosclerosis risk, with the IVW estimate at 1.13 [95% confidence interval (CI): 1.07-1.20]. Additionally, we observed a suggestive causal link between T2D and VLDL levels, as evidenced by the IVW estimate of 1.02 (95% CI: 0.98-1.07). Further supporting lipid involvement in coronary atherosclerosis pathogenesis, the IVW-Egger estimate was 1.30 (95% CI: 1.06-1.58).

Conclusion

In conclusion, this study highlights the autonomous contributions of T2D and VLDL levels to coronary atherosclerosis development. T2D is linked to a 13.35% elevated risk of coronary atherosclerosis, and within T2D patients, VLDL concentration rises by 2.49%. Notably, each standard deviation increase in VLDL raises the likelihood of heart disease by 29.6%. This underscores the significant role of lipid regulation, particularly VLDL, as a mediating pathway in coronary atherosclerosis progression.

metGWAS 1.0: an R workflow for network-driven over-representation analysis between independent metabolomic and meta-genome-wide association studies

MOTIVATION

The method of genome-wide association studies (GWAS) and metabolomics combined provide an quantitative approach to pinpoint metabolic pathways and genes linked to specific diseases; however, such analyses require both genomics and metabolomics datasets from the same individuals/samples. In most cases, this approach is not feasible due to high costs, lack of technical infrastructure, unavailability of samples, and other factors. Therefore, an unmet need exists for a bioinformatics tool that can identify gene loci-associated polymorphic variants for metabolite alterations seen in disease states using standalone metabolomics.

RESULTS

Here, we developed a bioinformatics tool, metGWAS 1.0, that integrates independent GWAS data from the GWAS database and standalone metabolomics data using a network-based systems biology approach to identify novel disease/trait-specific metabolite-gene associations. The tool was evaluated using standalone metabolomics datasets extracted from two metabolomics-GWAS case studies. It discovered both the observed and novel gene loci with known single nucleotide polymorphisms when compared to the original studies.

AVAILABILITY AND IMPLEMENTATION

The developed metGWAS 1.0 framework is implemented in an R pipeline and available at: https://github.com/saifurbd28/metGWAS-1.0.

A Pilot Genome-Wide Association Study Identifies Novel Markers of Metabolic Syndrome in Patients with Psoriasis

BACKGROUND

Recent studies have reported that psoriasis is associated with the development of metabolic syndrome. Genome-wide association studies have been used to discover gene variant markers that occur frequently in case group in relation to specific diseases.

OBJECTIVE

The aim of the present study was to investigate the variants of specific genes involved in metabolic syndrome associated with psoriasis.

METHODS

A total of 95 psoriasis patients were recruited and divided into two groups: one with metabolic syndrome (38 patients) and the other without (57 patients). After genotyping, imputation, and quality checking, the association between the several single nucleotide polymorphisms and metabolic syndrome in psoriasis was tested, followed by gene set enrichment analysis.

RESULTS

We found 76 gene polymorphisms that conferred an increased risk for metabolic syndrome in patients with psoriasis. Four single nucleotide polymorphisms (rs17154774 of FRMD4A, rs77498336 of GPR116, rs75949580 and rs187682251 of MAPK4) showed the strongest association between metabolic syndrome and psoriasis. The epidermal growth factor receptor protein was located at the center of the protein interactions for the gene polymorphisms.

CONCLUSION

This study identified several previously unknown polymorphisms associated with metabolic syndrome in psoriasis. These results highlight the potential for future genetic studies to elucidate the development, and ultimately prevent the onset, of metabolic syndrome in patients with psoriasis.

Genetic association of hypertension and several other metabolic disorders with Bell's palsy

Background: Effects of hypertension, type 2 diabetes and obesity on Bell's palsy risk remains unclear. The aim of the study was to explore whether hypertension and these metabolic disorders promoted Bell's palsy at the genetic level. Methods: Genetic variants from genome-wide association studies for hypertension, type 2 diabetes, body mass index and several lipid metabolites were adopted as instrumental variables. Two-sample Mendelian randomization including IVW and MR-Egger was used to measure the genetic relationship between the exposures and Bell's palsy. Sensitivity analyses (i.e., Cochran's Q test, MR-Egger intercept test, "leave-one-SNP-out" analysis and funnel plot) were carried out to assess heterogeneity and horizontal pleiotropy. All statistical analyses were performed using R software. Results: Hypertension was significantly associated with the increased risk of Bell's palsy (IVW: OR = 2.291, 95%CI = 1.025-5.122, p = 0.043; MR-Egger: OR = 16.445, 95%CI = 1.377-196.414, p = 0.029). Increased level of LDL cholesterol might upexpectedly decrease the risk of the disease (IVW: OR = 0.805, 95%CI = 0.649-0.998, p = 0.048; MR-Egger: OR = 0.784, 95%CI = 0.573-1.074, p = 0.132). In addition, type 2 diabetes, body mass index and other lipid metabolites were not related to the risk of Bell's palsy. No heterogeneity and horizontal pleiotropy had been found. Conclusion: Hypertension might be a risk factor for Bell's palsy at the genetic level, and LDL cholesterol might reduce the risk of the disease. These findings (especially for LDL cholesterol) need to be validated by further studies.

Progress in genome-inspired treatment decisions for multifocal lung adenocarcinoma

INTRODUCTION

Multifocal lung adenocarcinoma (MFLA) is becoming increasingly recognized as a distinct subset of lung cancer, with unique biology, disease course, and treatment outcomes. While definitions remain controversial, MFLA is characterized by the development and concurrent presence of multiple independent (non-metastatic) lesions on the lung adenocarcinoma spectrum. Disease progression typically follows an indolent course measured in years, with a lower propensity for nodal and distant metastases than other more common forms of non-small cell lung cancer.

AREAS COVERED

Traditional imaging and histopathological analyses of tumor biopsies are frequently unable to fully characterize the disease, prompting interest in molecular diagnosis. We highlight some of the key questions in the field, including accurate definitions to identify and stage MLFA, molecular tests to stratify patients and treatment decisions, and the lack of clinical trial data to delineate best management for this poorly understood subset of lung cancer patients. We review the existing literature and progress toward a genomic diagnosis for this unique disease entity.

EXPERT OPINION

Multifocal lung adenocarcinoma behaves differently than other forms of non-small cell lung cancer. Progress in molecular diagnosis may enhance potential for accurate definition, diagnosis, and optimizing treatment approach.

Causal relationships of neonatal jaundice, direct bilirubin and indirect bilirubin with autism spectrum disorder: A two-sample Mendelian randomization analysis

Background

Multiple systematic reviews and meta-analyses have examined the association between neonatal jaundice and autism spectrum disorder (ASD) risk, but their results have been inconsistent. This may be because the included observational studies could not adjust for all potential confounders. Mendelian randomization study can overcome this drawback and explore the causal relationship between the both.

Methods

We used the data of neonatal jaundice, direct bilirubin (DBIL), indirect bilirubin (IBIL), and ASD collected by genome-wide association study (GWAS) to evaluate the effects of neonatal jaundice, DBIL and IBIL on ASD by using a two-sample Mendelian randomized (MR). The inverse variance-weighted method (IVW) was the main method of MR analysis in this study. Weighted median method, MR-Egger regression and mendelian randomization pleiotropy residual sum and outlier (MR-PRESSO) test were used for sensitivity analysis.

Results

There was no evidence of an effect of neonatal jaundice (OR, 1.002, 95% CI, 0.977-1.027), DBIL (OR, 0.970, 95% CI, 0.884-1.064) and IBIL (OR, 1.074, 95% CI, 0.882-1.308) on ASD risk by IVW test. In the weighted median method, MR-Egger regression and leave-one-out analysis, the results were robust and no heterogeneity or pleiotropy was observed.

Conclusions

We found that neonatal jaundice, DBIL and IBIL were not associated with ASD in this study. However, this paper did not explore the effect of severity and duration of jaundice on ASD in different ethnic populations, which may require further research.

Hunting for Genes Underlying Emotionality in the Laboratory Rat: Maps, Tools and Traps

Scientists have systematically investigated the hereditary bases of behaviors since the 19th century, moved by either evolutionary questions or clinically-motivated purposes. The pioneer studies on the genetic selection of laboratory animals had already indicated, one hundred years ago, the immense complexity of analyzing behaviors that were influenced by a large number of small-effect genes and an incalculable amount of environmental factors. Merging Mendelian, quantitative and molecular approaches in the 1990s made it possible to map specific rodent behaviors to known chromosome regions. From that point on, Quantitative Trait Locus (QTL) analyses coupled with behavioral and molecular techniques, which involved in vivo isolation of relevant blocks of genes, opened new avenues for gene mapping and characterization. This review examines the QTL strategy applied to the behavioral study of emotionality, with a focus on the laboratory rat. We discuss the challenges, advances and limitations of the search for Quantitative Trait Genes (QTG) playing a role in regulating emotionality. For the past 25 years, we have marched the long journey from emotionality-related behaviors to genes. In this context, our experiences are used to illustrate why and how one should move forward in the molecular understanding of complex psychiatric illnesses. The promise of exploring genetic links between immunological and emotional responses are also discussed. New strategies based on humans, rodents and other animals (such as zebrafish) are also acknowledged, as they are likely to allow substantial progress to be made in the near future.

Pancan-MNVQTLdb: systematic identification of multi-nucleotide variant quantitative trait loci in 33 cancer types

Multi-nucleotide variants (MNVs) are defined as clusters of two or more nearby variants existing on the same haplotype in an individual. Recent studies have identified millions of MNVs in human populations, but their functions remain largely unknown. Numerous studies have demonstrated that single-nucleotide variants could serve as quantitative trait loci (QTLs) by affecting molecular phenotypes. Therefore, we propose that MNVs can also affect molecular phenotypes by influencing regulatory elements. Using the genotype data from The Cancer Genome Atlas (TCGA), we first identified 223 759 unique MNVs in 33 cancer types. Then, to decipher the functions of these MNVs, we investigated the associations between MNVs and six molecular phenotypes, including coding gene expression, miRNA expression, lncRNA expression, alternative splicing, DNA methylation and alternative polyadenylation. As a result, we identified 1 397 821 cis-MNVQTLs and 402 381 trans-MNVQTLs. We further performed survival analysis and identified 46 173 MNVQTLs associated with patient overall survival. We also linked the MNVQTLs to genome-wide association studies (GWAS) data and identified 119 762 MNVQTLs that overlap with existing GWAS loci. Finally, we developed Pancan-MNVQTLdb (http://gong_lab.hzau.edu.cn/mnvQTLdb/) for data retrieval and download. Pancan-MNVQTLdb will help decipher the functions of MNVs in different cancer types and be an important resource for genetic and cancer research.

Integrated genomic analysis identifies novel low-frequency cis-regulatory variant rs2279658 associated with VSD risk in Chinese children

VSD combined with other cardiac or extracardiac malformations (defined as "complex VSD" by us) is one of the major causes of perinatal morbidity and mortality. Functional non-coding SNPs (cis-regulatory SNPs) have not been systematically studied in CHDs, including complex VSD. Here we report an exome-wide association analysis using WES data of 60 PA/VSD cases, 20 TOF cases and 100 controls in Chinese children. We identify 93 low-frequency non-coding SNPs associated with complex VSD risk. A functional genomics pipeline integrating ATAC-seq, ChIP-seq and promoter CHi-C recognizes the rs2279658 variant as a candidate cis-regulatory SNP. Specifically, rs2279658 resides in a cardiac-specific enhancer bound by FOXH1 and PITX2, and would abrogate binding of these two transcription factors to the identified enhancer during cardiac morphogenesis. COQ2 and FAM175A are predicted to be target genes for "rs2279658-FOXH1 or PITX2" pairs in the heart. These findings highlight the importance of cis-regulatory SNPs in the pathogenesis of complex VSD and broaden our understanding of this disease.

Identification of New Genes and Genetic Variant Loci Associated with Breast Muscle Development in the Mini-Cobb F2 Chicken Population Using a Genome-Wide Association Study

Native chicken has become a favorite choice for consumers in many Asian countries recently, not only for its potential nutritional value but also for its deep ties to local food culture. However, low growth performance and limited meat production restrict their economic potential. Conducting a genome-wide association study (GWAS) for chicken-breast muscle development will help identify loci or candidate genes for different traits and potentially provide new insight into this phenotype in chickens and other species. To improve native chicken growth performance, especially breast muscle development, we performed a GWAS to explore the potential genetic mechanisms of breast muscle development in an F2 population constructed by reciprocal crosses between a fast-growing broiler chicken (Cobb500) and a slow-growing native chicken (Daweishan mini chicken). The results showed that 11 SNPs, which exceeded the 10% genome significance level (p = 1.79 × 10-8) were considered associated with breast muscle development traits, where six SNPS, NC_006126.5: g.3138376T>G, NC_006126.5: g.3138452A>G, NC_006088.5: g.73837197A>G, NC_006088.5: g.159574275A>G, NC_006089.5: g.80832197A>G, and NC_006127.5: g.48759869G>T was first identified in this study. In total, 13 genes near the SNPs were chosen as candidate genes, and none of them had previously been studied for their role in breast muscle development. After grouping the F2 population according to partial SNPs, significant differences in breast muscle weight were found among different genotypes (p < 0.05), and the expression levels of ALOX5AP, USPL1, CHRNA9, and EFNA5 among candidate genes were also significantly different (p < 0.05). The results of this study will contribute to the future exploration of the potential genetic mechanisms of breast muscle development in domestic chickens and also support the expansion of the market for native chicken in the world.

Genomewide association study identifies a novel variant associated with tacrolimus trough concentration in Chinese renal transplant recipients

Tacrolimus (TAC) is an immunosuppressant widely used in kidney transplantation. TAC displays considerable interindividual variability in pharmacokinetics (PKs). Genetic and clinical factors play important roles in TAC PKs. We enrolled a total of 251 Chinese renal transplant recipients and conducted a genomewide association study (GWAS), linkage disequilibrium (LD), and one-way analysis of variance (ANOVA) to find genetic variants affecting log-transformed TAC trough blood concentration/dose ratio (log[C0 /D]). In addition, we performed dual luciferase reporter gene assays and multivariate regression models to evaluate the effect of the genetic variants. The GWAS results showed that all 23 genomewide significant single-nucleotide polymorphisms (p < 5 × 10-8 ) were located on chromosome 7, including CYP3A5*3. LD, conditional association analysis, and one-way ANOVA showed that rs75125371 T > C independently influenced TAC log(C0 /D). Dual luciferase reporter gene assays indicated that rs75125371 minor allele (C) was significantly associated with increased normalized luciferase activity than the major allele (T) in the Huh7 cells (p = 1.2 × 10-5 ) and HepaRG cells (p = 0.0097). A model inclusive of age, sex, hematocrit, CYP3A5*3, and rs75125371 explained 37.34% variance in TAC C0 . These results suggest that rs75125371 T > C is a functional and population-specific variant affecting TAC C0 in Chinese renal transplant recipients.

A single-nucleus and spatial transcriptomic atlas of the COVID-19 liver reveals topological, functional, and regenerative organ disruption in patients

The molecular underpinnings of organ dysfunction in acute COVID-19 and its potential long-term sequelae are under intense investigation. To shed light on these in the context of liver function, we performed single-nucleus RNA-seq and spatial transcriptomic profiling of livers from 17 COVID-19 decedents. We identified hepatocytes positive for SARS-CoV-2 RNA with an expression phenotype resembling infected lung epithelial cells. Integrated analysis and comparisons with healthy controls revealed extensive changes in the cellular composition and expression states in COVID-19 liver, reflecting hepatocellular injury, ductular reaction, pathologic vascular expansion, and fibrogenesis. We also observed Kupffer cell proliferation and erythrocyte progenitors for the first time in a human liver single-cell atlas, resembling similar responses in liver injury in mice and in sepsis, respectively. Despite the absence of a clinical acute liver injury phenotype, endothelial cell composition was dramatically impacted in COVID-19, concomitantly with extensive alterations and profibrogenic activation of reactive cholangiocytes and mesenchymal cells. Our atlas provides novel insights into liver physiology and pathology in COVID-19 and forms a foundational resource for its investigation and understanding.

Benchmarking post-GWAS analysis tools in major depression: Challenges and implications

Our knowledge of complex disorders has increased in the last years thanks to the identification of genetic variants (GVs) significantly associated with disease phenotypes by genome-wide association studies (GWAS). However, we do not understand yet how these GVs functionally impact disease pathogenesis or their underlying biological mechanisms. Among the multiple post-GWAS methods available, fine-mapping and colocalization approaches are commonly used to identify causal GVs, meaning those with a biological effect on the trait, and their functional effects. Despite the variety of post-GWAS tools available, there is no guideline for method eligibility or validity, even though these methods work under different assumptions when accounting for linkage disequilibrium and integrating molecular annotation data. Moreover, there is no benchmarking of the available tools. In this context, we have applied two different fine-mapping and colocalization methods to the same GWAS on major depression (MD) and expression quantitative trait loci (eQTL) datasets. Our goal is to perform a systematic comparison of the results obtained by the different tools. To that end, we have evaluated their results at different levels: fine-mapped and colocalizing GVs, their target genes and tissue specificity according to gene expression information, as well as the biological processes in which they are involved. Our findings highlight the importance of fine-mapping as a key step for subsequent analysis. Notably, the colocalizing variants, altered genes and targeted tissues differed between methods, even regarding their biological implications. This contribution illustrates an important issue in post-GWAS analysis with relevant consequences on the use of GWAS results for elucidation of disease pathobiology, drug target prioritization and biomarker discovery.

A review of brain imaging biomarker genomics in Alzheimer’s disease: implementation and perspectives

Alzheimer’s disease (AD) is a progressive neurodegenerative disease with phenotypic changes closely associated with both genetic variants and imaging pathology. Brain imaging biomarker genomics has been developed in recent years to reveal potential AD pathological mechanisms and provide early diagnoses. This technique integrates multimodal imaging phenotypes with genetic data in a noninvasive and high-throughput manner. In this review, we summarize the basic analytical framework of brain imaging biomarker genomics and elucidate two main implementation scenarios of this technique in AD studies: (1) exploring novel biomarkers and seeking mutual interpretability and (2) providing a diagnosis and prognosis for AD with combined use of machine learning methods and brain imaging biomarker genomics. Importantly, we highlight the necessity of brain imaging biomarker genomics, discuss the strengths and limitations of current methods, and propose directions for development of this research field.

PLCγ2 impacts microglia-related effectors revealing variants and pathways important in Alzheimer’s disease

Alzheimer’s disease (AD) is an irreversible neurodegenerative disease mainly characterized by memory loss and cognitive decline. The etiology of AD is complex and remains incompletely understood. In recent years, genome-wide association studies (GWAS) have increasingly highlighted the central role of microglia in AD pathology. As a trans-membrane receptor specifically present on the microglia in the central nervous system, phosphatidylinositol-specific phospholipase C gamma 2 (PLCγ2) plays an important role in neuroinflammation. GWAS data and corresponding pathological research have explored the effects of PLCG2 variants on amyloid burden and tau pathologies that underline AD. The link between PLCγ2 and other AD-related effectors in human and mouse microglia has also been established, placing PLCγ2 downstream of the triggering receptor expressed on myeloid cells 2 (TREM2), toll-like receptor 4 (TLR4), Bruton’s tyrosine kinase (BTK), and colony-stimulating factor 1 receptor (CSF1R). Because the research on PLCγ2’s role in AD is still in its early stages, few articles have been published, therefore in this paper, we integrate the relevant research published to date, review the structural features, expression patterns, and related pathways of PLCγ2, and summarize the recent studies on important PLCG2 variants related to AD. Furthermore, the possibility and challenge of using PLCγ2 to develop therapeutic drugs for AD are also discussed.

Lung- and liver-dominant phenotypes of Korean eight constitution medicine have different profiles of genotype associated with each organ function

Eight Constitution Medicine (ECM), a ramification of traditional Korean medicine, has categorized people into eight constitutions. The main criteria of classification are inherited differences or predominance in the functions of organs, such as the liver or lung, diagnosed through ECM-specific pulse patterns. This study investigated the association between single nucleotide polymorphism (SNP) genotypes and ECM phenotypes and explored candidate genetic makeups responsible for each constitution using a genome-wide association study (GWAS). Sixty-three healthy volunteers, who were either categorized as the Hepatonia (HEP, n = 32) or Pulmotonia (PUL, n = 31) constitution, were enrolled. HEP and PUL are two contrasting ECM types representing the dominant liver and lung phenotypes, respectively. SNPs were analyzed from the oral mucosa DNA using a commercially available microarray chip that can identify 820,000 SNPs. We conducted GWAS using logistic regression analysis and additive mode genotypes and constructed phylogenetic trees using the SNPhylo program with 8 SNPs specific for the liver phenotype and 15 SNPs for the lung phenotype. Although genome-wide significant SNPs were not found, the phylogenetic tree showed a clear difference between the two constitutions. This is the first observation suggesting genetic involvement in the ECM and can be extended to all ECM constitutions.

Identification of Novel Regulators of Radiosensitivity Using High-Throughput Genetic Screening

The biological impact of ionizing radiation (IR) on humans depends not only on the physical properties and absorbed dose of radiation but also on the unique susceptibility of the exposed individual. A critical target of IR is DNA, and the DNA damage response is a safeguard mechanism for maintaining genomic integrity in response to the induced cellular stress. Unrepaired DNA lesions lead to various mutations, contributing to adverse health effects. Cellular sensitivity to IR is highly correlated with the ability of cells to repair DNA lesions, in particular coding sequences of genes that affect that process and of others that contribute to preserving genomic integrity. However, accurate profiling of the molecular events underlying individual sensitivity requires techniques with sensitive readouts. Here we summarize recent studies that have used whole-genome analysis and identified genes that impact individual radiosensitivity. Whereas microarray and RNA-seq provide a snapshot of the transcriptome, RNA interference (RNAi) and CRISPR-Cas9 techniques are powerful tools that enable modulation of gene expression and characterizing the function of specific genes involved in radiosensitivity or radioresistance. Notably, CRISPR-Cas9 has altered the landscape of genome-editing technology with its increased readiness, precision, and sensitivity. Identifying critical regulators of cellular radiosensitivity would help tailor regimens that enhance the efficacy of therapeutic treatments and fast-track prediction of clinical outcomes. It would also contribute to occupational protection based on average individual sensitivity, as well as the formulation of countermeasures to the harmful effects of radiation.

The Impact of Donor and Recipient Genetic Variation on Outcomes After Solid Organ Transplantation: A Scoping Review and Future Perspectives

At the outset of solid organ transplantation, genetic variation between donors and recipients was recognized as a major player in mechanisms such as allograft tolerance and rejection. Genome-wide association studies have been very successful in identifying novel variant-trait associations, but have been difficult to perform in the field of solid organ transplantation due to complex covariates, era effects, and poor statistical power for detecting donor-recipient interactions. To overcome a lack of statistical power, consortia such as the International Genetics and Translational Research in Transplantation Network have been established. Studies have focused on the consequences of genetic dissimilarities between donors and recipients and have reported associations between polymorphisms in candidate genes or their regulatory regions with transplantation outcomes. However, knowledge on the exact influence of genetic variation is limited due to a lack of comprehensive characterization and harmonization of recipients' or donors' phenotypes and validation using an experimental approach. Causal research in genetics has evolved from agnostic discovery in genome-wide association studies to functional annotation and clarification of underlying molecular mechanisms in translational studies. In this overview, we summarize how the recent advances and progresses in the field of genetics and genomics have improved the understanding of outcomes after solid organ transplantation.

Exploring the genetic relationship between deep vein thrombosis and plasma protein: a new research idea

BACKGROUND

The aim of this article is to scan and analyze the genetic correlation between plasma proteome and deep venous thrombosis(DVT), and to explore the correlation between plasma protein and DVT.

RESEARCH DESIGN AND METHODS

GWAS data of DVT and plasma proteins were analyzed with linkage disequilibrium scores, and plasma proteins that were genetically associated with DVT were screened out. To ascertain the causal link between potential plasma proteins and DVT, a Mendelian randomized (MR) study was used. This study used STRING to examine the pathogenesis of DVT in connection with the gene encoding plasma protein.

RESULTS

Several suggestive plasma proteins were detected for DVT, such as Complement factor B (correlation coefficient =0.3883 P value=0.0177), Chromogranin-A (correlation coefficient =-0.4786, P value=0.0158). Through MR analysis, we found that there was a significant positive causal relationship between Chromogranin-A (exposure) and DVT (outcome) (β=-0.0117, SE=0.0013, P<0.0001). Our STRING analysis revealed that hsa04610 was associated with coagulation cascade in the KEGG pathway of Complement factor B(P<0.0001), which was based on GO and KEGG analysis of 8 selected plasma proteins.

CONCLUSIONS

A genetic link between plasma protein and DVT was thoroughly investigated. Our findings provide a fresh perspective on the genetics and pathogenesis of DVT.

Applicability of polygenic risk scores in endometriosis clinical presentation

Background

Risk prediction is an essential part of preventative medicine and in recent years genomic information has become an interesting factor in risk models. Polygenic risk scores (PRS) combine the effect of many genetic variations into a single score which has been shown to have predictive value for many diseases. This study aimed to investigate the association between PRS for endometriosis and the clinical presentation of the disease.

Methods

Women with endometriosis (N = 172) were identified at the Department of Gynecology. All participants answered questionnaires regarding sociodemographic factors, lifestyle habits and medical history, registered bowel symptoms on the Visual Analog Scale for Irritable Bowel Syndrome and passed blood samples. DNA was extracted and samples were genotyped, and a PRS was calculated based on previous genome-wide association studies of endometriosis. Inflammatory proteins and TSH receptor antibodies (TRAb) in serum were analyzed.

Results

Inverse associations were identified between PRS and spread of endometriosis, involvement of the gastrointestinal tract and hormone treatment. However, significance was lost when calculated as p for trend and the specificity and sensitivity were low. There were no correlations between PRS and TRAb or inflammatory proteins.

Conclusion

The findings indicate that specific PRS should be developed to predict clinical presentations in patient with endometriosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12905-022-01788-w.

Preliminary study of genome-wide association identifies novel susceptibility genes for serum mineral elements in the Chinese Han population

Mineral elements (copper (Cu), zinc (Zn), calcium (Ca), magnesium (Mg), iron (Fe)) play important biological roles in enzymes, hormones, vitamins, and normal metabolism. The deficiency of mineral elements can lead to abnormal physiological functions. And some elements (such as lead (Pb)) are harmful to the body. We aim to identify genetic loci which can influence the serum levels of mineral elements (Cu, Zn, Ca, Mg, Fe, and Pb). Genotyping was performed using Applied Biosystems Axiom™ PMDA in 587 individuals, and 6,423,076 single-nucleotide polymorphisms (SNPs) were available for the genome-wide association study (GWAS) analysis. The association between genotype and phenotype was analyzed using mixed linear regression (additive genetic model) adjusting by age and gender combined with identical by descent (IBD) matrix. Genetic loci in BCHE-LOC105374194, DTX2P1-UPK3BP1-PMS2P11, VAT1L, LINC00908-LINC00683, LINC01310-NONE, and rs6747410 in VWA3B were identified to be associated with serum Cu element concentration (p < 5 × 10^-6). ADAMTSL1 rs17229526 (p = 4.96 × 10^-6) was significantly associated with serum Zn element levels. Genetic loci in LRP1B, PIGZ-MELTF, LINC01365-LINC02502, and HAPLN3 were related to serum Ca element levels (p < 5 ×1 0^-6). Three SNPs in ALPK1, ASAP1-ADCY8 and IER3IP1-SKOR2 also achieved a significant association with Mg element levels (p < 5 × 10^-6). TACSTD2-MYSM1, LRP1B, and ASAP1-ADCY8 showed suggestive associations with serum Fe element levels (p < 5 × 10^-6). Moreover, the two most significant SNPs associated with Pb were rs304234 in CADPS-LINC00698 (p = 2.47 × 10^-6) and rs12666460 in LOC101928211-GPR37 (p = 1.81 × 10^-6). In summary, we reported 19 suggestive loci associated with serum mineral elements in the Chinese Han population. These findings provided new insights into the potential mechanisms regulating serum mineral elements levels.

Genetics and sports performance: the present and future in the identification of talent for sports based on DNA testing

The impact of genetics on physiology and sports performance is one of the most debated research aspects in sports sciences. Nearly 200 genetic polymorphisms have been found to influence sports performance traits, and over 20 polymorphisms may condition the status of the elite athlete. However, with the current evidence, it is certainly too early a stage to determine how to use genotyping as a tool for predicting exercise/sports performance or improving current methods of training. Research on this topic presents methodological limitations such as the lack of measurement of valid exercise performance phenotypes that make the study results difficult to interpret. Additionally, many studies present an insufficient cohort of athletes, or their classification as elite is dubious, which may introduce expectancy effects. Finally, the assessment of a progressively higher number of polymorphisms in the studies and the introduction of new analysis tools, such as the total genotype score (TGS) and genome-wide association studies (GWAS), have produced a considerable advance in the power of the analyses and a change from the study of single variants to determine pathways and systems associated with performance. The purpose of the present study was to comprehensively review evidence on the impact of genetics on endurance- and power-based exercise performance to clearly determine the potential utility of genotyping for detecting sports talent, enhancing training, or preventing exercise-related injuries, and to present an overview of recent research that has attempted to correct the methodological issues found in previous investigations.

A large-scale genetic correlation scan between rheumatoid arthritis and human plasma protein

Aims

The aim of this study was to explore the genetic correlation and causal relationship between blood plasma proteins and rheumatoid arthritis (RA).

Methods

Based on the genome-wide association studies (GWAS) summary statistics of RA from European descent and the GWAS summary datasets of 3,622 plasma proteins, we explored the relationship between RA and plasma proteins from three aspects. First, linkage disequilibrium score regression (LD score regression) was applied to detect the genetic correlation between RA and plasma proteins. Mendelian randomization (MR) analysis was then used to evaluate the causal association between RA and plasma proteins. Finally, GEO2R was used to screen the differentially expressed genes (DEGs) between patients with RA and healthy controls.

Results

We found that seven kinds of plasma proteins had genetic correlations with RA, such as Soluble Receptor for Advanced Glycation End Products (sRAGE) (correlation coefficient = 0.2582, p = 0.049), vesicle transport protein USE1 (correlation coefficient = 0.1337, p = 0.018), and spermatogenesis-associated protein 20 (correlation coefficient = 0.3706, p = 0.018). There was a significant causal relationship between sRAGE and RA. By comparing the genes encoding seven plasma proteins, we found that only USE1 was a DEG associated with RA.

Conclusion

Our study identified a set of candidate plasma proteins that showed signals correlated with RA. Since the results of this study need further experimental verification, they should be interpreted with caution. However, we hope that this paper will provide new insights for the discovery of pathogenic genes and RA pathogenesis in the future.

Cite this article: Bone Joint Res 2022;11(2):134–142.

Brain Immunoinformatics: A Symmetrical Link between Informatics, Wet Lab and the Clinic

Breakthrough advances in informatics over the last decade have thoroughly influenced the field of immunology. The intermingling of machine learning with wet lab applications and clinical results has hatched the newly defined immunoinformatics society. Immunoinformatics of the central neural system, referred to as neuroimmunoinformatics (NII), investigates symmetrical and asymmetrical interactions of the brain-immune interface. This interdisciplinary overview on NII is addressed to bioscientists and computer scientists. We delineate the dominating trajectories and field-shaping achievements and elaborate on future directions using bridging language and terminology. Computation, varying from linear modeling to complex deep learning approaches, fuels neuroimmunology through three core directions. Firstly, by providing big-data analysis software for high-throughput methods such as next-generation sequencing and genome-wide association studies. Secondly, by designing models for the prediction of protein morphology, functions, and symmetrical and asymmetrical protein–protein interactions. Finally, NII boosts the output of quantitative pathology by enabling the automatization of tedious processes such as cell counting, tracing, and arbor analysis. The new classification of microglia, the brain’s innate immune cells, was an NII achievement. Deep sequencing classifies microglia in “sensotypes” to accurately describe the versatility of immune responses to physiological and pathological challenges, as well as to experimental conditions such as xenografting and organoids. NII approaches complex tasks in the brain-immune interface, recognizes patterns and allows for hypothesis-free predictions with ultimate targeted individualized treatment strategies, and personalizes disease prognosis and treatment response.

A large-scale genomic association analysis identifies a fragment in Dt11 chromosome conferring cotton Verticillium wilt resistance

Verticillium wilt (VW) is a destructive disease that results in great losses in cotton yield and quality. Identifying genetic variation that enhances crop disease resistance is a primary objective in plant breeding. Here we reported a GWAS of cotton VW resistance in a natural-variation population, challenged by different pathogenicity stains and different environments, and found 382 SNPs significantly associated with VW resistance. The associated signal repeatedly peaked in chromosome Dt11 (68 798 494-69 212 808) containing 13 core elite alleles undescribed previously. The core SNPs can make the disease reaction type from susceptible to tolerant or resistant in accessions with alternate genotype compared to reference genotype. Of the genes associated with the Dt11 signal, 25 genes differentially expressed upon Verticillium dahliae stress, with 21 genes verified in VW resistance via gene knockdown and/or overexpression experiments. We firstly discovered that a gene cluster of L-type lectin-domain containing receptor kinase (GhLecRKs-V.9) played an important role in VW resistance. These results proved that the associated Dt11 region was a major genetic locus responsible for VW resistance. The frequency of the core elite alleles (FEA) in modern varieties was significantly higher than the early/middle varieties (12.55% vs 4.29%), indicating that the FEA increased during artificial selection breeding. The current developmental resistant cultivars, JND23 and JND24, had fixed these core elite alleles during breeding without yield penalty. These findings unprecedentedly provided genomic variations and promising alleles for promoting cotton VW resistance improvement.

Gene-based association analysis identified a novel gene associated with systemic lupus erythematosus

OBJECTIVE

Systemic lupus erythematosus (SLE) is a complex autoimmune disease with strong genetic predisposition. Genome-wide association studies (GWAS) of SLE have identified more than 50 robust susceptibility loci. However, traditional individual SNP-based GWAS have made it difficult to identify variants with small effects. Moreover, variants revealed by GWAS only explain a limited disease heritability, suggesting that many susceptibility genes remain uncovered.

METHODS

We first curated the published SLE GWAS data from 1047 SLE patients and 1205 healthy controls of Chinese ancestry and performed a gene-based association study. Then quantitative reverse transcription-polymerase chain reaction (qRT-PCR) was conducted to verify novel genes identified above.

RESULTS

Gene-based association study identified 10 SLE-associated genes, nine of which were reported by previous GWAS, the other one, ILRUN, is a newly identified gene and was further validated by qRT-PCR. Gene expression analysis of Gene Expression Omnibus (GEO) datasets also showed that the expression of ILRUN in patients with SLE was lower than that in normal subjects.

CONCLUSION

In this study, gene-based association study and qRT-PCR identified that ILRUN is a novel susceptibility gene of SLE. ILRUN may regulate inflammation and antiviral response through its effect on the transcription of type I interferons )I-IFN, and participate in the pathogenesis of SLE.

Networks in the Field of Tourette Syndrome

Gilles de la Tourette syndrome (TS) is a neuropsychiatric neurodevelopmental disorder with the cardinal clinical features of motor and phonic tics. Clinical phenomenology can be complex since, besides tics, there are other features including premonitory urges preceding tics, pali-, echo-, and coprophenomena, hypersensitivity to external stimuli, and symptom dependency on stress, attention, and other less well-defined factors. Also, the rate of comorbidities, particularly attention deficit hyperactivity disorder and obsessive-compulsive disorder, is high. Mirroring the complexities of the clinical course and phenomenology, pathophysiological findings are very diverse, and etiology is disputed. It has become clear, though, that abnormalities in the basal ganglia and their connections with cortical areas are key for the understanding of the pathophysiology and as regards etiology, genetic factors are crucial. Against this background, both adequate clinical management of TS and TS-related research require multidisciplinary preferably international cooperation in larger groups or networks to address the multiple facets of this disorder and yield valid and useful data. In particular, large numbers of patients are needed for brain imaging and genetic studies. To meet these requirements, a number of networks and groups in the field of TS have developed over the years creating an efficient, lively, and supportive international research community. In this review, we will provide an overview of these groups and networks.

The current review of adolescent obesity: the role of genetic factors

Obesity, a complex, multi-factor and heterogeneous condition, is thought to result from the interaction of environmental and genetic factors. Considering the result of adolescence obesity in adulthood, the role of genetic factors comes to the fore. Recently, many genome-wide association studies (GWAS) have been conducted and many loci associated with adiposity have been identified. In adolescents, the strongest association with obesity has been found in single nucleotide polymorphisms (SNP) in the FTO gene. Besides FTO, GWAS showed consistent effects between variants in MC4R, TMEM18, TNNI3K, SEC16B, GNPDA2, POMC and obesity. However, these variants may not have similar effects for all ethnic groups. Although recently genetic factors are considered to contribute to obesity, relatively little is known about the specific loci related to obesity and the mechanisms by which they cause obesity.

Current Insights in Genetics of Sarcoidosis: Functional and Clinical Impacts

Sarcoidosis is a complex disease that belongs to the vast group of autoinflammatory disorders, but the etiological mechanisms of which are not known. At the crosstalk of environmental, infectious, and genetic factors, sarcoidosis is a multifactorial disease that requires a multidisciplinary approach for which genetic research, in particular, next generation sequencing (NGS) tools, has made it possible to identify new pathways and propose mechanistic hypotheses. Codified treatments for the disease cannot always respond to the most progressive forms and the identification of new genetic and metabolic tracks is a challenge for the future management of the most severe patients. Here, we review the current knowledge regarding the genes identified by both genome wide association studies (GWAS) and whole exome sequencing (WES), as well the connection of these pathways with the current research on sarcoidosis immune-related disorders.

Genetics of Diabetic Retinopathy

PURPOSE OF REVIEW

The goal of this paper is to review the latest findings in understanding the genetics of diabetic retinopathy. We highlight recent literature using a variety of molecular genetic techniques to identify variants which contribute to genetic susceptibility for diabetic retinopathy.

RECENT FINDINGS

New genome-wide association study (GWAS) and whole-exome sequencing approaches have been utilized to identify both common and rare variants associated with diabetic retinopathy. While variants have been identified in isolated studies, no variants have been replicated across multiple studies. The identification of genetic factors associated with diabetic retinopathy remains elusive. This is due to the multifactorial nature of the disease, small sample sizes for GWAS, and difficulty in controlling covariates of the disease. Larger populations as well as utilization of new sequencing and data analysis techniques may lead to new insights into genetic factors associated with diabetic retinopathy in the future.

Evolutionary couplings of amino acid residues reveal structure and function of bacterial signaling proteins

The genomic era along with major advances in high-throughput sequencing technology has led to a rapid expansion of the genomic and consequently the protein sequence space. Bacterial extracytoplasmic function sigma factors have emerged as an important group of signaling proteins in bacteria involved in many regulatory decisions, most notably the adaptation to cell envelope stress. Their wide prevalence and amplification among bacterial genomes has led to sub-group classification and the realization of diverse signaling mechanisms. Mathematical frameworks have been developed to utilize extensive protein sequence alignments to extract co-evolutionary signals of interaction. This has proven useful in a number of different biological fields, including de novo structure prediction, protein-protein partner identification and the elucidation of alternative protein conformations for signal proteins, to name a few. The mathematical tools, commonly referred to under the name 'Direct Coupling Analysis' have now been applied to deduce molecular mechanisms of activation for sub-groups of extracytoplasmic sigma factors adding to previous successes on bacterial two-component signaling proteins. The amplification of signal transduction protein genes in bacterial genomes made them the first to be amenable to this approach but the sequences are available now to aid the molecular microbiologist, no matter their protein pathway of interest.