Genetic Association Analysis Research Articles

Type 2 diabetes prevention: genetic association analysis of dried fruit intake and disease risk.

Prior research has suggested an inverse correlation between dried fruit intake and type 2 diabetes mellitus (T2DM), yet the causal link remains uncertain. This study seeks to investigate the potential causal impact of dried fruit intake on T2DM, covering cases both with and without various complications, as well as glycaemic traits, using a two-sample Mendelian randomisation (MR) approach. Using MR analysis with genome-wide association study summary statistics, the primary analysis investigated the causal relationship between dried fruit intake and T2DM, both with and without complications, as well as glycaemic traits, employing the inverse variance weighted method. Supplementary analyses were conducted using MR-Egger and the weighted median method. Heterogeneity and intercept tests were utilised to evaluate the robustness of the study outcomes. The results show a significant association between dried fruit intake and T2DM without complications, as well as fasting insulin. Sensitivity analyses confirmed the robustness of the results and the independence from multicollinearity. However, no association was found between dried fruit intake and T2DM with various complications or other glycaemic traits. The significant association between dried fruit intake and T2DM without complications and fasting insulin persisted even after adjusting for BMI. This study offers genetic evidence endorsing the protective effects of dried fruit intake against T2DM, specifically for cases without complications, and in regulating fasting insulin. These findings suggest that dried fruit intake might serve as a primary preventive strategy for T2DM.

Genetic Diversity and Association Analysis of Traits Related to Water-Use Efficiency and Nitrogen-Use Efficiency of Populus deltoides Based on SSR Markers.

Populus deltoides is one of the primary tree species for bioenergy production in temperate regions. In arid/semi-arid northern China, the scarcity of water and nitrogen significantly limits the productivity of poplar plantations. The identification of relevant molecular markers can promote the breeding of resource-efficient varieties. In this study, 188 genotypes of P. deltoides from six provenances served as experimental material. Genetic differentiation analysis, analysis of molecular variance (AMOVA), principal coordinate analysis (PCoA), unweighted pair group method with arithmetic mean (UPGMA) clustering, and genetic structure analysis were performed using selected simple sequence repeat (SSR) markers. Based on these analyses, the association analysis of water-use efficiency (WUE) and nitrogen-use efficiency (NUE) were conducted using general linear model (GLM) and mixed linear model (MLM) approaches. The results showed that 15 pairs of SSR primers successfully amplified across all 188 individuals, with an average of 7.33 alleles (Na) observed per primer pair. The polymorphism information content (PIC) ranged from 0.060 to 0.897, with an average of 0.544, indicating high genetic diversity in the selected markers. The average inbreeding coefficient intra-population (Fis), inbreeding coefficient inter-population (Fit), and inter-population genetic fraction coefficient (Fst) values were 0.005, 0.135, and 0.132, respectively, indicating high heterozygosity, substantial inbreeding within populations, and moderate genetic differentiation, with an average gene flow (Nm) of 1.964, suggesting substantial gene flow between populations. Additionally, molecular variance was primarily within individuals (84.12%). Genetic structure analysis revealed four subgroups, with some degree of genetic admixture among the provenances. In the GLM model, 11 markers were significantly associated with five traits (p < 0.05), with an average contribution rate of 15.82%. Notably, SSR132 and SSR143 were significantly associated with multiple traits (p < 0.05). The MLM model identified two markers (SSR47 and SSR85) significantly associated with ground diameter (p < 0.05) and one marker (SSR80) significantly associated with NUE (p < 0.05). This study identifies loci associated with WUE and NUE, laying a foundation for future genetic improvement and marker-assisted breeding strategies in poplar.

Genetic variability, character association and path analyses effects on fiber yield and yield attributing morpho-agronomic traits of tossa jute (Corchorus olitorius L.)

Jute (Corchorus spp.) is a natural fiber crop having a lower extent of genetic variability due to its self-pollinating nature. The success of any breeding program for variety development primarily depends on the presence of genetic variation in the parental genotypes. A field experiment was conducted in a randomized complete block design at ManikganjStation of Bangladesh Jute Research Institute (BJRI) during 2019-2020. The genetic divergence of 58 tossa jute (C. olitorius) genotypes including two pre-released standard varieties (O-9897, BJRI Tossa pat 4) and 56 accessions were studied to select genotypes having the most divergence in natural rainy condition. The jute genotypes were categorized into five clusters based on Mahalanobis D2 analysis. Cluster I and IV showed maximum inter-cluster distance (181.44) while the maximum intra-cluster distance (16.15) was recorded in cluster I. Cluster V revealed the highest values for number of nodes, stem mid-diameter, core diameter, green weight with leaves, dry stick weight and dry fiber weight per plant while cluster IV showed higher means for plant height, green bark thickness and leaf area. The highest contribution (47.14%) was wielded by plant height of total deviations. The results recommended that hybridization between genotypes of cluster V, IV and III could provide a wide range of discrepancies in the segregating generation which could offer chance for isolation of good genotypes with high fibre yielding lines.

Genetic association and computational analysis of MTHFR gene polymorphisms rs1801131 and rs1801133 with breast cancer in the Bangladeshi population

Methylenetetrahydrofolate reductase (MTHFR) plays a crucial role in regulating one-carbon metabolism. Polymorphisms within the MTHFR gene have been found to increase the risk of breast cancer in different populations. In this study, we evaluated the association of polymorphisms of the MTHFR gene (rs1801133 and rs1801131) with the risk of breast cancer in the Bangladeshi population. This case‒control study included 202 breast cancer patients and 104 healthy controls. After the organic extraction of DNA, genotyping was performed via the PCR-RFLP method. Sanger sequencing was performed to validate the RFLP data. Statistical analyses were performed to evaluate the associations of the polymorphisms. Different computational tools were used to predict the structural and functional consequences of the SNPs. Our study revealed that the MTHFR gene polymorphism rs1801131 is associated with an increased risk of developing breast cancer (p < 0.001, OR = 3.85, 95% CI = 2.06–7.25 for the AC genotype and p < 0.001, OR = 7.82, 95% CI = 2.69–22.05 for the CC genotype). An association was also observed in the dominant model (AC + CC) (p < 0.001, OR = 4.19, 95% CI = 2.28–7.78). For rs1801131, premenopausal status was significantly associated with breast cancer risk (p < 0.001). For rs1801133, no significant association was found with breast cancer risk (p > 0.05, OR = 1.57, 95% CI = 0.90–2.74 for the CT genotype; p > 0.05, OR = 1.35, 95% CI = 0.36–4.92 for the TT genotype). Computational analyses predicted rs1801131 to be tolerated and rs1801133 to be deleterious. Structural analyses demonstrated no significant changes in protein structure but revealed alterations in neighboring interactions according to both bond distances and angles. In conclusion, rs1801131 but not rs1801133 is significantly associated with breast cancer risk in the Bangladeshi population. Moreover, in silico analyses demonstrated changes in the interaction pattern of polymorphic residues with adjacent amino acids.

Pharmacogenetics of tuberculosis treatment toxicity and effectiveness in a large Brazilian cohort.

Genetic polymorphisms have been associated with risk of antituberculosis treatment toxicity. We characterized associations with adverse events and treatment failure/recurrence among adults treated for tuberculosis in Brazil. Participants were followed in Regional Prospective Observational Research in Tuberculosis (RePORT)-Brazil. We included persons with culture-confirmed drug-susceptible pulmonary tuberculosis who started treatment between 2015 and 2019, and who were eligible for pharmacogenetics. Treatment included 2 months of isoniazid, rifampin or rifabutin, pyrazinamide, and ethambutol, then 4 months of isoniazid and rifampin or rifabutin, with 24-month follow-up. Analyses included 43 polymorphisms in 20 genes related to antituberculosis drug hepatotoxicity or pharmacokinetics. Whole exome sequencing was done in a case-control toxicity subset. Among 903 participants in multivariable genetic association analyses, NAT2 slow acetylator status was associated with increased risk of treatment-related grade 2 or greater adverse events, including hepatotoxicity. Treatment failure/recurrence was more likely among NAT2 rapid acetylators, but not statistically significant at the 5% level. A GSTM1 polymorphism (rs412543) was associated with increased risk of treatment-related adverse events, including hepatotoxicity. SLCO1B1 polymorphisms were associated with increased risk of treatment-related hepatoxicity and treatment failure/recurrence. Polymorphisms in NR1/2 were associated with decreased risk of adverse events and increased risk of failure/recurrence. In whole exome sequencing, hepatotoxicity was associated with a polymorphism in VTI1A, and the genes METTL17 and PRSS57, but none achieved genome-wide significance. In a clinical cohort representing three regions of Brazil, NAT2 acetylator status was associated with risk for treatment-related adverse events. Additional significant polymorphisms merit investigation in larger study populations, particularly regarding risk of treatment failure/recurrence.

Unveiling the genetic variability, character association and principal component analysis for yield and yield contributing traits in brinjal (Solanum melongena) genotypes

The experiment was conducted during rainy (kharif) and winter (rabi) seasons of 2023 and 2024 at Tamil Nadu Agricultural University, Coimbatore, Tamil Nadu to assess 45 brinjal (Solanum melongena L.) genotypes for growth and yield related parameters. The experiment was laid out in randomized block design (RBD) with three replications. The result showed high genotypic coefficient of variance (GCV) and phenotypic coefficient of variance (PCV) values for plant height, number of primary branches/plant, length of fruit and weight of fruit and yield/plant. Whereas, the traits such as days to first flowering, days to 50% flowering, fruit girth, fruit borer infestation and number of fruits/ plant exhibited medium GCV and PCV values. The registered high heritability values ranged from 94.29–99.49% and genetic advance as a percentage of the mean ranged from 19.25–70.25%. Correlation analysis on number of fruits/ plant showed positive and significant association with fruit yield/plant. Principal component analysis showed four principal components with eigen values of unity and accounted for 75.81% of total variance.

Analysis of genetic diversity and environmental associations of wild citron (Citrus medica L.) in northeast India

Citron (Citrus medica L.) is a major citrus fruit crop known for its medicinal, nutritional, and aromatic uses. Native to northeast India, Myanmar, and south China, citron is cultivated mostly in the Mediterranean and South Asian countries. The truly wild populations of citron are found in the hills and valleys of northeast India. The extent of genetic diversity in wild citron in relation to environmental variables has not been documented. In the present study, we analyzed genetic diversity and environmental association of wild populations of C. medica in northeast India using 15 polymorphic nuclear SSR (simple sequence repeat) markers and 21 environmental variables. SSR profiling revealed a moderate genetic diversity (Ho = 0.40; He = 0.41; I = 0.70). Neighbor-joining (NJ) and principal coordinate analysis (PCoA) grouped 16 natural populations into two genetic clusters. Bayesian structure results showed two genetic populations with a high admixture of individuals. Analysis of molecular variance (AMOVA) revealed low genetic differentiation (Fst = 0.14; P < 0.001), indicative of high gene flow (Nm = 1.53) in citron. The isolation by distance (IBD) analysis showed a weak correlation, indicating that geographic distance was not a determining factor for genetic distance in C. medica populations. The higher metrics of outcrossing rate (tm > 0.9) revealed outbreeding nature of the species. The genetic diversity of citron showed a positive correlation with precipitation of driest month and precipitation of coldest quarter, but negative with mean diurnal range and isothermality. Overall, the results of the present study could benefit the conservation and management of citron resources and their natural habitat in northeast India. Genetically highly diverse populations identified in the present study can be used for conservation and utilization of citron genetic resources.

Genetic variability, trait association and path coefficient analysis for yield and yield attributing traits in sesame (Sesamum Indicum L.)

Genetic variability, trait association and path coefficient analysis for yield and yield attributing traits in sesame (Sesamum Indicum L.)

Genome Sequencing and Genetic Association Analyses of Primary Glomerular Disorders in CureGN, NEPTUNE, and Columbia CKD Biobank

Genome Sequencing and Genetic Association Analyses of Primary Glomerular Disorders in CureGN, NEPTUNE, and Columbia CKD Biobank

Genetic variability, character association and path coefficient analysis in okra

A study was conducted to investigate the genetic architecture of different lines for fruit yield and its associated traits in okra. Fourteen parents, consisting of twelve lines and two testers, were crossed using a Line × Tester mating design in the spring-summer season of 2019-20 at Vegetable Research Farm, CCSHAU, Hisar. The resulting twenty-four hybrids were cultivated in a randomized block design with three replications during the rainy season of 2020-21. Fruit yield/hectare showed a significant range from 87.86 to 150.18 quintals with an average of 117.73 quintals. The phenotypic coefficient of variation ranged from 3.91% (test weight) to 20.23% (Number of branches per plant), slightly surpassing the genotypic coefficient of variation which ranged from 1.98% (test weight) to 12.15% (fruit yield) with high estimate of PCV for the number of branches per plant (20.23%) and a moderate estimate of both PCV and GCV for fruit yield (14.67%, 12.15%), number of fruits per plant (14.34%, 12.06%), respectively. This suggests that the traits studied were more influenced by genetic factors than environmental factors. High heritability coupled with high genetic advance as percentage of mean for traits such as number of fruits/plant (70.74%, 20.89%) and fruit yield/hectare (68.65%, 20.74%) suggested that additive genes play a major role in determining these traits respectively. This indicates that it is possible to select high-yielding genotypes by selecting parents with desirable traits. Fruit yield/hectare displayed positive and significant associations with most of the traits like number of fruits per plant (0.95) and plant height (0.36) at phenotypic levels. The number of fruits per plant, 1000 seeds test weight, fruit diameter, and number of branches per plant had the most significant positive effect on fruit yield. Ultimately, such analysis has the potential to assist breeders in formulating their selection strategies aimed at enhancing fruit yield.

Genetic Variability, Character Association and Path Analysis for Yield and Yield Components in Foxtail Millet [Setaria italica (L.) P. Beauv.] Accessions under Multi Environments in Foothills of Nagaland

Background: Foxtail millet cultivation inIndia’s North Eastern Hill regionholds promise due to its adaptation to diverse environments and high-quality grain. The objective of this study was to assess the amount of variability present among the genotypes, association of traits and find out foxtail millet genotypes that produce high yield in diverse environments. Methods: The investigation was carried out during July 2022 to May 2023 in four different dates of sowing. Two environments maintained under rainfed condition and the remaining two environments are maintained under irrigated condition. The experiment was conducted in randomized complete block design with three replications in all environments. Result: Analysis of variance revealed statistically significant differences (at 5%) among the 30 genotypes for all yield variables under evaluation. Genotype ‘G1’ exhibited superior performance for both yield and yield-related traits. The present study revealed considerable genetic variation among the yield traits, with all traits demonstrating high heritability except for harvest index.Traits such as fodder yield per plant, panicle length, biological yield, flag leaf width, peduncle length, panicle width and grain yield per plant show high heritability coupled with high genetic advance. A strong correlation was observed between grain yield per plant and several traits including days to 50% flowering, days to maturity, plant height, panicle length, flag leaf length, peduncle length, biological yield and fodder yield per plant. This correlation was consistent at both the genotypic and phenotypic levels. Biological yield exhibited the strongest direct influence on grain yield per plant, followed by harvest index, flag leaf width and number of base tillers on genotypic and phenotypic levels.

Multi-step gene set analysis identified HTR3 family genes involving childhood acute lymphoblastic leukemia susceptibility.

In our previous conventional genome-wide association study (GWAS), WWOX was a susceptibility gene associated with acute lymphoblastic leukemia (ALL) development. Nowadays, advancements in genetic association analyses promote an in-depth exploration of ALL genomics. We conducted a two-step enrichment analysis at both gene and pathway levels based on ALL GWAS data including 269 cases and 1039 controls of Chinese descent. The following functional prediction and experiments were used to evaluate the genetic biology of candidate variants and genes. The serotonin-activated cation-selective channel complex gene-set was a potential biological pathway involved in ALL occurrence. Of which, individuals carrying the T allele of rs33940208 exhibited a prominent reduced risk of ALL [odds ratio (OR) = 0.71, 95% confidence interval (CI) = 0.53 to 0.96, P = 2.81 × 10-2], whereas those with the A allele of rs6779545 demonstrated an increased risk (OR = 1.23, 95% CI = 1.01 to 1.51, P = 4.11 × 10-2). Notably, the two variants displayed a better prediction capability when combined, that the risk of developing childhood ALL increased by 131% in subjects with 2-4 risk alleles compared to those with 0-1 risk alleles (Ptrend = 2.05 × 10-3). In addition, the T allele of rs33940208 could reduce HTR3A mRNA level, while the A allele of rs6779545 increased HTR3D mRNA expression. In this study, we identified HTR3A rs33940208 and HTR3D rs6779545 as potential susceptibility loci for ALL in Chinese children. Future validation and functional research will elucidate the underlying molecular processes, refining preventive strategies for this disease.

Impact of SGLT2 inhibitors on lower limb complications: a mendelian randomization perspective.

While Sodium-glucose cotransporter 2 (SGLT2) inhibitors are effective in managing diabetes and reducing cardiovascular risk, concerns about their association with lower limb complications, including, osteomyelitis, ulcers, and peripheral artery disease (PAD), persist. This study employs Mendelian Randomization (MR) to assess the causal relationship between SGLT2 inhibitors and these lower limb safety outcomes. A two-sample drug-target MR approach was used, complemented by a one-sample MR and genetic association analysis. Six SNPs were selected as instrumental variables to proxy the effect of SGLT2 inhibition. Primary outcomes were major limb safety outcomes, including osteomyelitis, lower limb ulcers, PAD, and cellulitis. The primary analytical method was the generalized inverse variance-weighted (IVW) approach, along with several sensitivity analyses. The MR analysis indicated no significant causal association between genetically proxied SGLT2 inhibition and most of the studied lower limb safety outcomes. However, a significant association with PAD was observed, necessitating careful interpretation due to discrepancies between IVW and MR-Egger results. Sensitivity analyses supported these findings, showing little evidence of heterogeneity or directional pleiotropy. This study suggests that SGLT2 inhibitors may not be significantly associated with an increased risk of most lower limb safety outcomes, including osteomyelitis, lower limb ulcers, and cellulitis, in patients with type 2 diabetes. However, the complex relationship with PAD highlights the need for further research. These findings contribute to the understanding of the safety profile of SGLT2 inhibitors, supporting their continued use in diabetes management while underlining the importance of continuous safety monitoring.

IGFBP7 promotes the proliferation and differentiation of primary myoblasts and intramuscular preadipocytes in chicken

Though it is well known that insulin-like growth factor (IGF) binding protein 7 (IGFBP7) plays an important role in myogenesis and adipogenesis in mammals, its impact on the proliferation, differentiation, and lipid deposition in chicken primary myoblasts (CPM) and intramuscular preadipocytes remains unexplored. In the present study, we firstly examined the correlation between SNPs within the genomic sequence of the IGFBP7 gene and carcass and blood chemical traits in a F2 resource population by genetic association analysis, and found that a significant correlation between the SNP (4_49499525) located in the intron region of IGFBP7 and serum high-density lipoproteins (HDL). We then examined the expression patterns of IGFBP7 across different stages of proliferation and differentiation in CPMs and intramuscular preadipocytes via qPCR, and explored the biological functions of IGFBP7 through gain- and loss-of-function experiments and a range of techniques including qPCR, CCK-8, EdU, flow cytometry, Western blot, immunofluorescence, and Oil Red O staining to detect the proliferation, differentiation, and lipid deposition in CPMs and intramuscular preadipocytes. We ascertained that the expression levels of the IGFBP7 gene increased as cell differentiation progresses in CPMs and intramuscular preadipocytes, and that IGFBP7 promotes the proliferation and differentiation of these cells, as well as facilitates intracellular lipid deposition. Furthermore, we investigated the regulatory mechanism of IGFBP7 expression by using co-transfection strategy and dual-luciferase reporter assay, and discovered that the myogenic transcription factors (MRF), myoblast determination factor (MyoD) and myogenin (MyoG), along with the adipocyte-specific transcription factor (TF) CCAAT/enhancer-binding protein α (C/EBPα), can bind to the core transcription activation region of the IGFBP7 promoter located 500 bp upstream from the transcription start site, thereby promoting IGFBP7 transcription and expression. Taken together, our study underscores the role of IGFBP7 as a positive regulator for myogenesis and adipogenesis, while also elucidating the functional and transcriptional regulatory mechanisms of IGFBP7 in chicken skeletal muscle development and intramuscular adipogenesis.

Disease prediction with multi-omics and biomarkers empowers case–control genetic discoveries in the UK Biobank

The emergence of biobank-level datasets offers new opportunities to discover novel biomarkers and develop predictive algorithms for human disease. Here, we present an ensemble machine-learning framework (machine learning with phenotype associations, MILTON) utilizing a range of biomarkers to predict 3,213 diseases in the UK Biobank. Leveraging the UK Biobank’s longitudinal health record data, MILTON predicts incident disease cases undiagnosed at time of recruitment, largely outperforming available polygenic risk scores. We further demonstrate the utility of MILTON in augmenting genetic association analyses in a phenome-wide association study of 484,230 genome-sequenced samples, along with 46,327 samples with matched plasma proteomics data. This resulted in improved signals for 88 known (P < 1 × 10−8) gene–disease relationships alongside 182 gene–disease relationships that did not achieve genome-wide significance in the nonaugmented baseline cohorts. We validated these discoveries in the FinnGen biobank alongside two orthogonal machine-learning methods built for gene–disease prioritization. All extracted gene–disease associations and incident disease predictive biomarkers are publicly available (http://milton.public.cgr.astrazeneca.com).

Genetic association of GJA8 with long-segment Hirschsprung's disease in southern Chinese children.

Hirschsprung's disease (HSCR) is a complex congenital neurodevelopmental disorder affecting colons caused by both genetic and environmental factors. Although several genes have been identified as contributing factors in HSCR, the pathogenesis is still largely unclear, especially for the low prevalent long-segment HSCR (L-HSCR). Gap junction protein alpha 8 (GJA8) is involved in several physiological processes and has been implicated in several diseases. However, the relationship between GJA8 single nucleotide polymorphism (SNP) rs17160783 and HSCR in the southern Chinese population remains unknown. The study aimed to explore the association of genetic variants in GJA8 and HSCR susceptibility in southern Chinese. SNP rs17160783 A>G in GJA8 was genotyped by TaqMan SNP Genotyping Assay in all samples, which included 1,329 HSCR children (cases) and 1,473 healthy children (controls). Odds ratio (OR) and 95% confidence interval (CI) were used to evaluate the association of GJA8 polymorphisms with HSCR susceptibility. The GTEx database and transcription factor binding site (TFBS) prediction were used to analyze the potential regulatory function of rs17160783. Genetic association analysis illustrated that rs17160783 could increase the risk of L-HSCR (Padj=0.04, ORadj =1.48, 95% CI: 1.02-2.14). We also found that GJA8 expression was increased in HSCR and neurodevelopmentally impaired animal models. External epigenetic data revealed that GJA8 rs17160783 may have the potential to regulate the expression of the GJA8, possibly by altering the binding of transcription factors for GJA8, and consequently impacting the PI3K-Akt signaling pathway during the enteric nervous system (ENS) development. Our results suggested that rs17160783 might play a regulatory role in GJA8 expression and increase the susceptibility of L-HSCR in children from southern China.

Functional Polymorphisms Regulate FOXO1 Transcript Expression and Contribute to the Risk and Symptom Severity of HDM-Induced Allergic Rhinitis

Introduction: FOXO1 plays an important role in regulating immune processes that contribute to allergic inflammation; however, genetic variants influencing FOXO1 expression in AR pathogenesis remains unclear. This study aimed to investigate the functional effect of FOXO1 single nucleotide polymorphisms (SNPs) on AR development by performing genetic association and functional analysis studies. Methods: This study belongs to a part of an ongoing Singapore/Malaysia cross-sectional genetics and epidemiological study (SMCSGES). We assessed the associations of FOXO1 transcript expression levels in peripheral blood mononuclear cells (PBMC) with AR phenotype, total nasal symptom score (TNSS), and SNP genotype in a sub-cohort of n = 658 individuals from the SMCSGES population. Associations of FOXO1 SNPs with AR were assessed in a cohort of n = 5,072 individuals from the SMCSGES population. In vitro promoter luciferase assay was used to evaluate the effect of AR-associated SNPs on FOXO1 promoter activity. Results: FOXO1 transcript expression in PBMC was significantly associated with the risk of AR (p < 0.05) and TNSS among AR patients (p < 0.0001). We identified a significant association between tag-SNPs rs9549246 and FOXO1 transcript expression in PBMC from the SMCSGES sub-cohort and the multiethnic eQTLGen consortium (false discovery rate-adjusted p < 0.05). The minor allele “A” of tag-SNP rs9549246 was significantly associated with a higher risk of AR (p = 0.04422, odds ratio = 1.21, 95% confidence interval = 1.01–1.45) in the SMCSGES genotyping cohort (n = 5,072). In vitro luciferase assay showed the minor allele “A” of rs35594717 (tagged by rs9549246) was significantly associated with a higher FOXO1 promoter activity (p < 0.05). Conclusion: FOXO1 transcript expression in PBMC has a strong association with the risk and symptom severity of AR. Genetic variants tagged by rs9549246 were shown to affect the expression of FOXO1 and contribute to the development of AR in the SMCSGES population.

Analysis of genetic association of vitamin D receptor (VDR) gene FokI polymorphism in Bangladeshi patients with type 2 diabetes mellitus

AimsType 2 diabetes mellitus (T2DM) is a complex and multifaceted disease that contributes significantly to Bangladesh’s disease burden. Both polygene abnormalities and environmental factors contribute to this genetic condition. Vitamin D receptor (VDR) has immunomodulatory functions that may contribute to the developmentof type 2 diabetes. This investigation examined the association between the vitamin D receptor gene (rs2228570) FokI polymorphism and genetic susceptibility to T2DM in the Bangladeshi population. MethodsA total of 203 subjects (108 clinically identified T2DM patients and 95 healthy controls) participated in this research study with the ethical committee’s approval. Genomic DNA was isolated from venous blood collected from the volunteers with prior consent. Extracted DNA was then genotyped for single nucleotide polymorphism (SNPs) for VDR (rs2228570) FokI gene by PCR-RFLP analysis, where the genotypes were assessed by agarose gel electrophoresis. ResultsGenotype distribution for VDR (rs2228570) FokI polymorphism exhibited a significant difference between T2DM patients and the control group, whereas allele frequencies for both genes did not differ evidently between the patient and control group. ConclusionsOur finding demonstrates a possible link between the risk of T2DM and the FokI polymorphism of the VDR (rs2228570) gene.

Balancing the efforts of chart review and gains in PRS prediction accuracy: An empirical study

ObjectivePhenotypic misclassification in genetic association analyses can impact the accuracy of PRS-based prediction models. The bias reduction method proposed by Tong et al. (2019) has demonstrated its efficacy in reducing the effects of bias on the estimation of association parameters between genotype and phenotype while minimizing variance by employing chart reviews on a subset of the data for validating phenotypes, however its improvement of subsequent PRS prediction accuracy remains unclear. Our study aims to fill this gap by assessing the performance of simulated PRS models and estimating the optimal number of chart reviews needed for validation. MethodsTo comprehensively assess the efficacy of the bias reduction method proposed by Tong et al. in enhancing the accuracy of PRS-based prediction models, we simulated each phenotype under different correlation structures (an independent model, a weakly correlated model, a strongly correlated model) and introduced error-prone phenotypes using two distinct error mechanisms (differential and non-differential phenotyping errors). To facilitate this, we used genotype and phenotype data from 12 case-control datasets in the Alzheimer’s Disease Genetics Consortium (ADGC) to produce simulated phenotypes. The evaluation included analyses across various misclassification rates of original phenotypes as well as quantities of validation set. Additionally, we determined the median threshold, identifying the minimal validation size required for a meaningful improvement in the accuracy of PRS-based predictions across a broad spectrum. ResultsThis simulation study demonstrated that incorporating chart review does not universally guarantee enhanced performance of PRS-based prediction models. Specifically, in scenarios with minimal misclassification rates and limited validation sizes, PRS models utilizing debiased regression coefficients demonstrated inferior predictive capabilities compared to models using error-prone phenotypes. Put differently, the effectiveness of the bias reduction method is contingent upon the misclassification rates of phenotypes and the size of the validation set employed during chart reviews. Notably, when dealing with datasets featuring higher misclassification rates, the advantages of utilizing this bias reduction method become more evident, requiring a smaller validation set to achieve better performance. ConclusionThis study highlights the importance of choosing an appropriate validation set size to balance between the efforts of chart review and the gain in PRS prediction accuracy. Consequently, our study establishes a valuable guidance for validation planning, across a diverse array of sensitivity and specificity combinations.

Association between Kidney Stones and CKD: A Bidirectional Mendelian Randomization Study.

Kidney stones and CKD are common disorders with a substantial interaction. Although observational studies have suggested a potential for enhanced CKD risk after prior kidney stones, the exact relationship remains ambiguous. Shared comorbidities between two diseases were identified using unbiased screening. Genome-wide association study summary statistics were obtained from the UK Biobank (UKBB), FinnGen, and CKDGen, followed by genetic association analyses across various traits. Bidirectional Mendelian randomization (MR) analyses were performed to define causal links, complemented by multivariable MR that included the shared comorbidities including hypertension, diabetes, and obesity. Observational analyses were undertaken using cohorts from the Mayo Clinic and a UKBB subset. Despite identifying a total of 123 conditions as shared comorbidities, there was no significant genetic correlation between kidney stones and CKD. Unadjusted MR analysis revealed no significant association between kidney stones and CKD risk (UKBB [exposure]/FinnGen [outcome]: OR=0.97, 95% CI: 0.88∼1.06; FinnGen/UKBB: OR=1.17, 95% CI:0.98∼1.39). Kidney stones did significantly associate with a higher urinary albumin-creatinine ratio (UACR) (β=0.014, 95% CI: 0.002∼0.025), but this association disappeared in the multivariable MR model (β=0.009, 95% CI: -0.003∼0.020). Furthermore, in a cross-sectional analysis limited to the UKBB cohort, a robust regression model did not detect an independent association between kidney stones and UACR (β=0.16, 95% CI: -0.04∼0.35) or eGFR (β=0.10, 95% CI: -0.07∼0.28). Conversely, CKD associated with a diminished risk of kidney stones in multivariable MR models (UKBB/FinnGen: OR=0.77, 95% CI: 0.69∼0.87; FinnGen/UKBB: OR=0.73, 95% CI: 0.66∼0.81). Furthermore, in the Mayo Clinic cohort with available urinary biochemistries, lower eGFR was associated with lower urinary calcium excretion and urinary calcium oxalate/phosphate supersaturation. In this study, kidney stones were not independently associated with CKD. Conversely, CKD was associated with a lower risk of calcium kidney stones likely via changes in key urinary traits, including lower calcium excretion.