scholarly journals Association of Polygenetic Risk Scores Related to Immunity and Inflammation with Hyperthyroidism Risk and Interactions between the Polygenetic Scores and Dietary Factors in a Large Cohort

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Mi Young Song ◽  
Sunmin Park
Keyword(s):  
Metabolic Syndrome ◽  
Genome Wide Association Study ◽  
Human Leukocyte ◽  
Dietary Factors ◽  
Risk Scores ◽  
Nucleotide Polymorphisms ◽  
Dietary Intakes ◽  
Urban Hospital ◽  
Coffee Intake ◽  
A Genome

Graves’s disease and thyroiditis induce hyperthyroidism, the causes of which remain unclear, although they are involved with genetic and environmental factors. We aimed to evaluate polygenetic variants for hyperthyroidism risk and their interaction with metabolic parameters and nutritional intakes in an urban hospital-based cohort. A genome-wide association study (GWAS) of participants with (cases; n = 842) and without (controls, n = 38,799) hyperthyroidism was used to identify and select genetic variants. In clinical and lifestyle interaction with PRS, 312 participants cured of hyperthyroidism were excluded. Single nucleotide polymorphisms (SNPs) associated with gene-gene interactions were selected by hyperthyroidism generalized multifactor dimensionality reduction. Polygenic risk scores (PRSs) were generated by summing the numbers of selected SNP risk alleles. The best gene-gene interaction model included tumor-necrosis factor (TNF)_rs1800610, mucin 22 (MUC22)_rs1304322089, tribbles pseudokinase 2 (TRIB2)_rs1881145, cytotoxic T-lymphocyte-associated antigen 4 (CTLA4)_rs231775, lipoma-preferred partner (LPP)_rs6780858, and human leukocyte antigen (HLA)-J_ rs767861647. The PRS of the best model was positively associated with hyperthyroidism risk by 1.939-fold (1.317–2.854) after adjusting for covariates. PRSs interacted with age, metabolic syndrome, and dietary inflammatory index (DII), while hyperthyroidism risk interacted with energy, calcium, seaweed, milk, and coffee intake ( P < 0.05 ). The PRS impact on hyperthyroidism risk was observed in younger (<55 years) participants and adults without metabolic syndrome. PRSs were positively associated with hyperthyroidism risk in participants with low dietary intakes of energy (OR = 2.74), calcium (OR = 2.84), seaweed (OR = 3.43), milk (OR = 2.91), coffee (OR = 2.44), and DII (OR = 3.45). In conclusion, adults with high PRS involved in inflammation and immunity had a high hyperthyroidism risk exacerbated under low intakes of energy, calcium, seaweed, milk, or coffee. These results can be applied to personalized nutrition in a clinical setting.

scholarly journals Identification of 38 novel loci for systemic lupus erythematosus and genetic heterogeneity between ancestral groups

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Yong-Fei Wang ◽  
Yan Zhang ◽  
Zhiming Lin ◽  
Huoru Zhang ◽  
Ting-You Wang ◽  
...  
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Lupus Erythematosus ◽  
Genome Wide Association Study ◽  
Age Of Onset ◽  
Treatment Options ◽  
Human Leukocyte ◽  
Risk Scores ◽  
Systemic Lupus ◽  
Disease Manifestation ◽  
A Genome

AbstractSystemic lupus erythematosus (SLE), a worldwide autoimmune disease with high heritability, shows differences in prevalence, severity and age of onset among different ancestral groups. Previous genetic studies have focused more on European populations, which appear to be the least affected. Consequently, the genetic variations that underlie the commonalities, differences and treatment options in SLE among ancestral groups have not been well elucidated. To address this, we undertake a genome-wide association study, increasing the sample size of Chinese populations to the level of existing European studies. Thirty-eight novel SLE-associated loci and incomplete sharing of genetic architecture are identified. In addition to the human leukocyte antigen (HLA) region, nine disease loci show clear ancestral differences and implicate antibody production as a potential mechanism for differences in disease manifestation. Polygenic risk scores perform significantly better when trained on ancestry-matched data sets. These analyses help to reveal the genetic basis for disparities in SLE among ancestral groups.

scholarly journals Development and Validation of an Insulin Resistance Predicting Model Using a Machine-Learning Approach in a Population-Based Cohort in Korea

Diagnostics ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 212
Author(s):  
Sunmin Park ◽  
Chaeyeon Kim ◽  
Xuangao Wu
Keyword(s):  
Machine Learning ◽  
Insulin Resistance ◽  
Metabolic Syndrome ◽  
Logistic Regression ◽  
Random Forest ◽  
Roc Curve ◽  
Genome Wide Association Study ◽  
Prediction Models ◽  
Risk Scores ◽  
A Genome

Background: Insulin resistance is a common etiology of metabolic syndrome, but receiver operating characteristic (ROC) curve analysis shows a weak association in Koreans. Using a machine learning (ML) approach, we aimed to generate the best model for predicting insulin resistance in Korean adults aged > 40 of the Ansan/Ansung cohort using a machine learning (ML) approach. Methods: The demographic, anthropometric, biochemical, genetic, nutrient, and lifestyle variables of 8842 participants were included. The polygenetic risk scores (PRS) generated by a genome-wide association study were added to represent the genetic impact of insulin resistance. They were divided randomly into the training (n = 7037) and test (n = 1769) sets. Potentially important features were selected in the highest area under the curve (AUC) of the ROC curve from 99 features using seven different ML algorithms. The AUC target was ≥0.85 for the best prediction of insulin resistance with the lowest number of features. Results: The cutoff of insulin resistance defined with HOMA-IR was 2.31 using logistic regression before conducting ML. XGBoost and logistic regression algorithms generated the highest AUC (0.86) of the prediction models using 99 features, while the random forest algorithm generated a model with 0.82 AUC. These models showed high accuracy and k-fold values (>0.85). The prediction model containing 15 features had the highest AUC of the ROC curve in XGBoost and random forest algorithms. PRS was one of 15 features. The final prediction models for insulin resistance were generated with the same nine features in the XGBoost (AUC = 0.86), random forest (AUC = 0.84), and artificial neural network (AUC = 0.86) algorithms. The model included the fasting serum glucose, ALT, total bilirubin, HDL concentrations, waist circumference, body fat, pulse, season to enroll in the study, and gender. Conclusion: The liver function, regular pulse checking, and seasonal variation in addition to metabolic syndrome components should be considered to predict insulin resistance in Koreans aged over 40 years.

scholarly journals Causal Relationship between Adiponectin and Diabetic Retinopathy: A Mendelian Randomization Study in an Asian Population

Genes ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 17
Author(s):  
Yu-Chuen Huang ◽  
Ya-Wen Chang ◽  
Chun-Wen Cheng ◽  
Chia-Ming Wu ◽  
Wen-Ling Liao ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Asian Population ◽  
Risk Scores ◽  
Diabetic Patients ◽  
Nucleotide Polymorphisms ◽  
Significance Level ◽  
A Genome ◽  
Potential Biomarker

Adiponectin (APN) is suggested to be a potential biomarker for predicting diabetic retinopathy (DR) risk, but the association between APN and DR has been inconsistent in observational studies. We used a Mendelian randomization (MR) analysis to evaluate if circulating APN levels result in DR. We applied three different genetic risk scores (GRS): GRSAll combined all 47 single nucleotide polymorphisms (SNPs), which from a genome-wide association study (GWAS) database-catalog reach significance level; GRSLimited comprised 16 GRSAll-SNPs with a rigorous threshold (p < 5.0 × 10−8 for GWAS), and GRSAPN combined 5 SNPs significantly associated with APN level. The MR-inverse-variance weighted method analysis showed that for each 1-SD increase in genetically induced increase in plasma APN, the OR of having DR was β = 0.20 (95% CI: −0.46–0.85, p = 0.553) for GRSAPN, 0.61 (95% CI: 0.10–1.13, p = 0.020) for GRSAll, and 0.57 (95% CI: −0.06 to 1.20, p = 0.078) for GRSLimited. Sensitivity analysis, including MR-egger regression and the weighted-median approach, did not provide evidence of the pleiotropic effect of IVs. Limited evidence for the causal role of APN in DR risk among Taiwanese diabetic patients was shown based on MR analysis in the present study.

EXPRESS: Effect of genetic liability to visceral adiposity on stroke and its subtypes: a Mendelian randomization study

2021 ◽  
pp. 174749302110062
Author(s):  
Bin Yan ◽  
Jian Yang ◽  
Li Qian ◽  
Fengjie Gao ◽  
Ling Bai ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Ischemic Stroke ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Visceral Adiposity ◽  
Large Artery ◽  
Nucleotide Polymorphisms ◽  
Genetic Liability ◽  
A Genome ◽  
Increased Risk

Background: Observational studies have found an association between visceral adiposity and stroke. Aims: The purpose of this study was to investigate the role and genetic effect of visceral adipose tissue (VAT) accumulation on stroke and its subtypes. Methods: In this two-sample Mendelian randomization (MR) study, genetic variants (221 single nucleotide polymorphisms; P<5×10-8) using as instrumental variables for MR analysis was obtained from a genome-wide association study (GWAS) of VAT. The outcome datasets for stroke and its subtypes were obtained from the MEGASTROKE consortium (up to 67,162 cases and 453,702 controls). MR standard analysis (inverse variance weighted method) was conducted to investigate the effect of genetic liability to visceral adiposity on stroke and its subtypes. Sensitivity analysis (MR-Egger, weighted median, MR-PRESSO) were also utilized to assess horizontal pleiotropy and remove outliers. Multi-variable MR analysis was employed to adjust potential confounders. Results: In the standard MR analysis, genetically determined visceral adiposity (per 1 SD) was significantly associated with a higher risk of stroke (odds ratio [OR] 1.30; 95% confidence interval [CI] 1.21-1.41, P=1.48×10-11), ischemic stroke (OR 1.30; 95% CI 1.20-1.41, P=4.01×10-10), and large artery stroke (OR 1.49; 95% CI 1.22-1.83, P=1.16×10-4). The significant association was also found in sensitivity analysis and multi-variable MR analysis. Conclusions: Genetic liability to visceral adiposity was significantly associated with an increased risk of stroke, ischemic stroke, and large artery stroke. The effect of genetic susceptibility to visceral adiposity on the stroke warrants further investigation.

scholarly journals An artificial neural network approach integrating plasma proteomics and genetic data identifies PLXNA4 as a new susceptibility locus for pulmonary embolism

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Misbah Razzaq ◽  
Maria Jesus Iglesias ◽  
Manal Ibrahim-Kosta ◽  
Louisa Goumidi ◽  
Omar Soukarieh ◽  
...  
Keyword(s):  
Pulmonary Embolism ◽  
Genome Wide Association Study ◽  
Susceptibility Gene ◽  
Biological Traits ◽  
Nucleotide Polymorphisms ◽  
Ann Model ◽  
Neural Network Approach ◽  
A Genome ◽  
Increased Risk ◽  
Artificial Neural

AbstractVenous thromboembolism is the third common cardiovascular disease and is composed of two entities, deep vein thrombosis (DVT) and its potential fatal form, pulmonary embolism (PE). While PE is observed in ~ 40% of patients with documented DVT, there is limited biomarkers that can help identifying patients at high PE risk. To fill this need, we implemented a two hidden-layers artificial neural networks (ANN) on 376 antibodies and 19 biological traits measured in the plasma of 1388 DVT patients, with or without PE, of the MARTHA study. We used the LIME algorithm to obtain a linear approximate of the resulting ANN prediction model. As MARTHA patients were typed for genotyping DNA arrays, a genome wide association study (GWAS) was conducted on the LIME estimate. Detected single nucleotide polymorphisms (SNPs) were tested for association with PE risk in MARTHA. Main findings were replicated in the EOVT study composed of 143 PE patients and 196 DVT only patients. The derived ANN model for PE achieved an accuracy of 0.89 and 0.79 in our training and testing sets, respectively. A GWAS on the LIME approximate identified a strong statistical association peak (rs1424597: p = 5.3 × 10–7) at the PLXNA4 locus. Homozygote carriers for the rs1424597-A allele were then more frequently observed in PE than in DVT patients from the MARTHA (2% vs. 0.4%, p = 0.005) and the EOVT (3% vs. 0%, p = 0.013) studies. In a sample of 112 COVID-19 patients known to have endotheliopathy leading to acute lung injury and an increased risk of PE, decreased PLXNA4 levels were associated (p = 0.025) with worsened respiratory function. Using an original integrated proteomics and genetics strategy, we identified PLXNA4 as a new susceptibility gene for PE whose exact role now needs to be further elucidated.

scholarly journals Genome-Wide Association Study (GWAS) for Examining the Genomics Controlling Prickle Production in Red Raspberry (Rubus idaeus L.)

Agronomy ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 27
Author(s):  
Archana Khadgi ◽  
Courtney A. Weber
Keyword(s):  
Association Study ◽  
Genome Wide Association Study ◽  
Genomic Region ◽  
Rubus Idaeus ◽  
Genome Wide Association ◽  
Nucleotide Polymorphisms ◽  
Red Raspberry ◽  
Genome Wide ◽  
A Genome ◽  
Genotype By Sequencing

Red raspberry (Rubus idaeus L.) is an expanding high-value berry crop worldwide. The presence of prickles, outgrowths of epidermal tissues lacking vasculature, on the canes, petioles, and undersides of leaves complicates both field management and harvest. The utilization of cultivars with fewer prickles or prickle-free canes simplifies production. A previously generated population segregating for prickles utilizing the s locus between the prickle-free cultivar Joan J (ss) and the prickled cultivar Caroline (Ss) was analyzed to identify the genomic region associated with prickle development in red raspberry. Genotype by sequencing (GBS) was combined with a genome-wide association study (GWAS) using fixed and random model circulating probability unification (FarmCPU) to analyze 8474 single nucleotide polymorphisms (SNPs) and identify significant markers associated with the prickle-free trait. A total of four SNPs were identified on chromosome 4 that were associated with the phenotype and were located near or in annotated genes. This study demonstrates how association genetics can be used to decipher the genetic control of important horticultural traits in Rubus, and provides valuable information about the genomic region and potential genes underlying the prickle-free trait.

scholarly journals Genome-Wide Association Analysis of Growth Curve Parameters in Chinese Simmental Beef Cattle

Animals ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 192
Author(s):  
Xinghai Duan ◽  
Bingxing An ◽  
Lili Du ◽  
Tianpeng Chang ◽  
Mang Liang ◽  
...  
Keyword(s):  
Beef Cattle ◽  
Candidate Genes ◽  
Growth Curve ◽  
Growth And Development ◽  
Genome Wide Association Study ◽  
Genome Wide Association ◽  
Coefficient Of Determination ◽  
Nucleotide Polymorphisms ◽  
Genome Wide ◽  
A Genome

The objective of the present study was to perform a genome-wide association study (GWAS) for growth curve parameters using nonlinear models that fit original weight–age records. In this study, data from 808 Chinese Simmental beef cattle that were weighed at 0, 6, 12, and 18 months of age were used to fit the growth curve. The Gompertz model showed the highest coefficient of determination (R2 = 0.954). The parameters’ mature body weight (A), time-scale parameter (b), and maturity rate (K) were treated as phenotypes for single-trait GWAS and multi-trait GWAS. In total, 9, 49, and 7 significant SNPs associated with A, b, and K were identified by single-trait GWAS; 22 significant single nucleotide polymorphisms (SNPs) were identified by multi-trait GWAS. Among them, we observed several candidate genes, including PLIN3, KCNS3, TMCO1, PRKAG3, ANGPTL2, IGF-1, SHISA9, and STK3, which were previously reported to associate with growth and development. Further research for these candidate genes may be useful for exploring the full genetic architecture underlying growth and development traits in livestock.

scholarly journals Genome-wide association study of psychiatric and substance use comorbidity in Mexican individuals

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
José Jaime Martínez-Magaña ◽  
Alma Delia Genis-Mendoza ◽  
Jorge Ameth Villatoro Velázquez ◽  
Marycarmen Bustos-Gamiño ◽  
Isela Esther Juárez-Rojop ◽  
...  
Keyword(s):  
Substance Use ◽  
Association Study ◽  
Genome Wide Association Study ◽  
Logistic Models ◽  
Genome Wide Association ◽  
Risk Scores ◽  
Multinomial Models ◽  
Gamma Receptor ◽  
Genome Wide ◽  
A Genome

AbstractThe combination of substance use and psychiatric disorders is one of the most common comorbidities. The objective of this study was to perform a genome-wide association study of this comorbidity (Com), substance use alone (Subs), and psychiatric symptomatology alone (Psych) in the Mexican population. The study included 3914 individuals of Mexican descent. Genotyping was carried out using the PsychArray microarray and genome-wide correlations were calculated. Genome-wide associations were analyzed using multiple logistic models, polygenic risk scores (PRSs) were evaluated using multinomial models, and vertical pleiotropy was evaluated by generalized summary-data-based Mendelian randomization. Brain DNA methylation quantitative loci (brain meQTL) were also evaluated in the prefrontal cortex. Genome-wide correlation and vertical pleiotropy were found between all traits. No genome-wide association signals were found, but 64 single-nucleotide polymorphism (SNPs) reached nominal associations (p < 5.00e−05). The SNPs associated with each trait were independent, and the individuals with high PRSs had a higher prevalence of tobacco and alcohol use. In the multinomial models all of the PRSs (Subs-PRS, Com-PRS, and Psych-PRS) were associated with all of the traits. Brain meQTL of the Subs-associated SNPs had an effect on the genes enriched in insulin signaling pathway, and that of the Psych-associated SNPs had an effect on the Fc gamma receptor phagocytosis pathway.

scholarly journals Haplotype- and SNP-Based GWAS for Growth and Wood Quality Traits in Eucalyptus cladocalyx Trees under Arid Conditions

Plants ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 148
Author(s):  
Camilo E. Valenzuela ◽  
Paulina Ballesta ◽  
Sunny Ahmar ◽  
Sajid Fiaz ◽  
Parviz Heidari ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Wood Quality ◽  
Tree Height ◽  
Mediterranean Ecosystems ◽  
Primary Metabolism ◽  
Arid Environments ◽  
Nucleotide Polymorphisms ◽  
Haplotype Blocks ◽  
A Genome ◽  
Stem Straightness

The agricultural and forestry productivity of Mediterranean ecosystems is strongly threatened by the adverse effects of climate change, including an increase in severe droughts and changes in rainfall distribution. In the present study, we performed a genome-wide association study (GWAS) to identify single-nucleotide polymorphisms (SNPs) and haplotype blocks associated with the growth and wood quality of Eucalyptus cladocalyx, a tree species suitable for low-rainfall sites. The study was conducted in a progeny-provenance trial established in an arid site with Mediterranean patterns located in the southern Atacama Desert, Chile. A total of 87 SNPs and 3 haplotype blocks were significantly associated with the 6 traits under study (tree height, diameter at breast height, slenderness coefficient, first bifurcation height, stem straightness, and pilodyn penetration). In addition, 11 loci were identified as pleiotropic through Bayesian multivariate regression and were mainly associated with wood hardness, height, and diameter. In general, the GWAS revealed associations with genes related to primary metabolism and biosynthesis of cell wall components. Additionally, associations coinciding with stress response genes, such as GEM-related 5 and prohibitin-3, were detected. The findings of this study provide valuable information regarding genetic control of morphological traits related to adaptation to arid environments.

Bisphosphonate-related osteonecrosis of the jaw is associated with polymorphisms of the cytochrome P450 CYP2C8 in multiple myeloma: a genome-wide single nucleotide polymorphism analysis

Blood ◽  
2008 ◽  
Vol 112 (7) ◽  
pp. 2709-2712 ◽  
Author(s):  
Maria E. Sarasquete ◽  
Ramon García-Sanz ◽  
Luis Marín ◽  
Miguel Alcoceba ◽  
Maria C. Chillón ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Cytochrome P450 ◽  
Genome Wide Association Study ◽  
Osteonecrosis Of The Jaw ◽  
Bisphosphonate Therapy ◽  
Polymorphism Analysis ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Genome Wide ◽  
A Genome

Abstract We have explored the potential role of genetics in the development of osteonecrosis of the jaw (ONJ) in multiple myeloma (MM) patients under bisphosphonate therapy. A genome-wide association study was performed using 500 568 single nucleotide polymorphisms (SNPs) in 2 series of homogeneously treated MM patients, one with ONJ (22 MM cases) and another without ONJ (65 matched MM controls). Four SNPs (rs1934951, rs1934980, rs1341162, and rs17110453) mapped within the cytochrome P450-2C gene (CYP2C8) showed a different distribution between cases and controls with statistically significant differences (P = 1.07 × 10−6, P = 4.231 × 10−6, P = 6.22 × 10−6, and P = 2.15 × 10−6, respectively). SNP rs1934951 was significantly associated with a higher risk of ONJ development even after Bonferroni correction (P corrected value = .02). Genotyping results displayed an overrepresentation of the T allele in cases compared with controls (48% vs 12%). Thus, individuals homozygous for the T allele had an increased likelihood of developing ONJ (odds ratio 12.75, 95% confidence interval 3.7-43.5).

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