INTRODUCTION:High-mobility group box 1 (HMGB1) protein plays a significant role in cancer development and treatment response. The current research on the role of HMGB1 in lung cancer and its treatment outcomes is limited and inconsistent. This exploratory study investigated the association between HMGB1 common genetic variants and lung cancer susceptibility, as well as cisplatin chemotherapy response, in a Chinese cohort. METHODS:The current study included 106 individuals diagnosed with lung cancer and 93 healthy subjects, all of whom were part of a Chinese population cohort. HMGB1 polymorphisms (rs1045411, rs1412125, rs2249825, and rs1360485) were genotyped using the TaqMan single-nucleotide polymorphism typing method. HMGB1 gene expression in the lung tissue of patients was quantified using real-time PCR. All patients were administered cisplatin, and their response to the drug was evaluated. All statistical analyses were performed using GraphPad Prism v10. RESULTS:The control group exhibited a higher frequency of heterozygous variants for HMGB1 polymorphisms rs1045411 (p = 0.01, odds ratio [OR] = 0.45) and rs1412125 (p = 0.03, OR = 0.46) than the patients. Moreover, the combined mutant genotypes for HMGB1 rs1045411 (p = 0.0001, OR = 0.15) and rs2249825 (p = 0.003, OR = 0.19) exhibited favorable responses to cisplatin treatment. Moreover, the wild-type variants of rs1045411 and rs2249825 exhibited higher HMGB1 expression than the mutants; however, this difference was not statistically significant. CONCLUSION:This preliminary investigation indicated potential associations between HMGB1 genetic variants and lung cancer susceptibility and treatment response. These exploratory findings necessitate further validation through larger multicenter studies incorporating functional assays to elucidate the biological significance and clinical utility of HMGB1 polymorphisms in the management of lung cancer.
INTRODUCTION:We show that generalizations of stable population (GSPM) and agent-based models (ABMs) are useful tools to simulate trajectories of human phenotypes. Although mathematically very different, both classes of models can simultaneously account for multiple determinants of the population distribution of a phenotype across time and space. These include genetic transmission, assortative mating, differential fertility, vertical and horizontal cultural heredity, gene-environments interactions (GxE), and environmental feedback. We propose an application to obesity, a condition that has spread rapidly around the globe, increasing the risk of adult chronic illnesses and mortality. METHODS:We choose body mass index as the target phenotype, and formulate GSPM and ABMs that include genetic inheritance, GxE, assortative mating, and fertility differentials. We exclude, in this version, the role of vertical cultural heredity. The GSPM is built on time-varying stochastic matrices that trace the trajectory of the phenotype by groups. The ABM models the behavior of individual agents integrating a stochastic component modifying each agent's behavior. RESULTS:There are four key results. First, differential fertility dominates the phenotype's time trajectory, followed by assortative mating and GxE. Second, contrary to research in other phenotypes, the impact of assortative mating cannot offset the influence of fertility differentials. Third, concerning the formal representation of the transmission process, we show that the use of simple Mendelian models to represent complex phenotypes can produce badly biased inferences. Fourth, despite their mathematical differences, the GSPM and ABM produce virtually identical results. CONCLUSIONS:Modeling phenotypes with complex genetic transmission and heavily dependent on regimes of fertility differentials, assortative mating and GxE ought not to rely on excessive simplifications, as has traditional been done in past research. Both, the GSPM and ABM are useful, accessible, and effective tools to introduce more realism in the modeling of these phenotypes, and can be used as guides for policy interventions.
Colocalization analyses assess whether two traits are affected by the same or distinct causal genetic variants in a single gene region. A class of Bayesian colocalization tests are now routinely used in practice; for example, for genetic analyses in drug development pipelines. In this work, we consider an alternative frequentist approach to colocalization testing that examines the proportionality of genetic associations with each trait. The proportional colocalization approach uses markedly different assumptions to Bayesian colocalization tests, and therefore can provide valuable complementary evidence in cases where Bayesian colocalization results are inconclusive or sensitive to priors. We propose a novel conditional test of proportional colocalization, prop-coloc-cond, that aims to account for the uncertainty in variant selection, in order to recover accurate type I error control. The test can be implemented straightforwardly, requiring only summary data on genetic associations. Simulation evidence and an empirical investigation into GLP1R gene expression demonstrates how tests of proportional colocalization can offer important insights in conjunction with Bayesian colocalization tests.
INTRODUCTION:A previous study of 200,000 exome-sequenced UK Biobank participants investigating the association between rare coding variants and BMI had implicated two genes, MC4R and PCSK1, at exome-wide significance. In addition, further 66 genes were significant with an uncorrected p value of <0.001. METHODS:Exome sequence data have become available for further 270,000 participants, and weighted burden analyses to test for association with BMI were carried out in this sample for all the 68 genes highlighted by the previous study. RESULTS:Three novel genes, in addition to MC4R and PCSK1, were significant after correction for multiple testing: PTOV1, GALNT9, and ATP8B2. All five genes were exome-wide significant in the whole sample of 470,000 participants. Rare coding variants impairing gene function were associated with reduced BMI for ATP8B2 but increased BMI for the other genes, and for all genes, loss of function variants had larger effect sizes than nonsynonymous variants. CONCLUSION:The biological mechanisms whereby the novel genes might affect BMI are not clear, although impairment of ATP8B2 might possibly have an effect on insulin secretion. Functional studies might throw further light on how these genes are involved in regulation of body weight. Collectively, the identified variants are very rare and do not make a major contribution to variation in BMI in the population. This research has been conducted using the UK Biobank Resource.
Introduction: Asthma is a chronic respiratory disorder characterized by airway inflammation, hyperresponsiveness, and reversible airflow obstruction. Despite therapeutic strategies, asthma remains inadequately controlled in many patients. Genetic predisposition plays a significant role in asthma pathogenesis, and the proteinase-activated receptor 2 (PAR-2), encoded by the F2RL1 gene, has been associated with asthma. However, the role of PAR-2 and F2RL1 variants in the Chinese population remains unclear. This study aimed to investigate the relationship between common F2RL1 polymorphisms and PAR-2 expression and their association with asthma susceptibility and clinical severity in a Chinese population. Methods: This study enrolled 250 clinically diagnosed Chinese patients with asthma and matched healthy controls of a similar age and geographical region. Four single nucleotide polymorphisms in the F2RL1 gene (rs1529505, rs631465, rs2242991, and rs2243057) were genotyped using the TaqMan genotyping method. PAR-2 mRNA expression was quantified through real-time PCR in intravenous blood samples. Statistical analyses were conducted using GraphPad Prism v10 and other software. Results: Variants of the F2RL1 gene, specifically rs1529505 (odds ratio [OR] = 1.65, 95% confidence interval [CI] = 1.26–2.14, p = 0.0002) and rs2272991 (OR = 1.89, 95% CI = 1.32–2.71, p = 0.0005), were associated with asthma predisposition. Genetic variants rs1529505 and rs631465 were associated with susceptibility and clinical severity in Chinese patients with asthma. The mutant genotypes of rs2272991 and rs1529505 correlated with elevated PAR-2 mRNA expression levels. Haplotype distribution did not reveal significant differences between asthma cases and controls, nor among severity groups. Conclusion: This study elucidated the influence of F2RL1 polymorphisms on PAR-2 mRNA expression and their impact on asthma pathogenesis within the Chinese population. Further research involving diverse populations is necessary to validate these findings.
Asthma is a chronic respiratory disorder characterized by airway inflammation, hyperresponsiveness, and reversible airflow obstruction. Despite therapeutic strategies, asthma remains inadequately controlled in many patients. Genetic predisposition plays a significant role in asthma pathogenesis, and the Proteinase-Activated Receptor 2 (PAR-2), encoded by the F2RL1 gene, has been associated with asthma. However, the role of PAR-2 and F2RL1 variants in the Chinese population remains unclear. This study aims to investigate the relationship between common F2RL1 polymorphisms and PAR-2 expression, and their association with asthma susceptibility and clinical severity in a Chinese population. This study enrolled 250 clinically diagnosed Chinese patients with asthma and matched healthy controls of a similar age and geographical region. Four single nucleotide polymorphisms in the F2RL1 gene (rs1529505, rs631465, rs2242991, and rs2243057) were genotyped using the TaqMan genotyping method. PAR-2 mRNA expression was quantified through real-time PCR in intravenous blood samples. Statistical analyses were conducted using GraphPad Prism v10 and other software. Variants of F2RL1 gene, specifically rs1529505 (OR= 1.65, 95%CI: 1.26 to 2.14, P =0.0002) and rs2272991 (OR= 1.89, 95%CI: 1.32 to 2.71, P =0.0005), were associated with asthma predisposition. Genetic variants rs1529505 and rs631465 were associated with susceptibility and clinical severity in Chinese patients with asthma. The mutant genotypes of rs2272991 and rs1529505 correlated with elevated PAR-2 mRNA expression levels. Haplotype distribution did not reveal significant differences between asthma cases and controls, nor among severity groups. This study elucidated the influence of F2RL1 polymorphisms on PAR-2 mRNA expression and their impact on asthma pathogenesis within the Chinese population. Further research involving diverse populations is necessary to validate these findings.
OBJECTIVES:To explore the relationships between mitochondrial tRNA (mt-tRNA) mutations and essential hypertension (EH), and providing the valuable information for molecular diagnosis of EH. MATERIALS AND METHODS:We reported here clinical, genetic and molecular characterizations of two Han Chinese pedigrees with maternally inherited EH. We first amplified the mitochondrial genomes of the matrilineal relatives with EH, furthermore, Sanger sequencing was used to screen mitochondrial DNA (mtDNA) mutations. Phylogenetic conservation, mt-tRNA structural analyses, as well as mitochondrial functional evaluations were performed to assess the potential pathogenicity of mtDNA mutations. RESULTS:EH-1 and EH-2 pedigrees exhibited typically maternally transmission; analysis of mitochondrial genomes revealed the co-existence of tRNAGln 4386T>C mutation in both families. Moreover, members of EH-2 pedigree carried the tRNAAla 5601C>T mutation. The m.4386T>C and m.5601C>T mutations were very conserved and implicated to have impact on mitochondrial functions. Compared with the control cells and cells with only the m.4386T>C mutation, cells carrying both m.4386T>C and m.5601C>T mutations exhibited much lower levels of ATP, membrane potential and mtDNA copy number, whereas ROS increased significantly. Thus, the m.5601C>T and m.4386T>C mutations caused mitochondrial dysfunctions and involved in EH progression. CONCLUSIONS:The m.5601C>T may be a secondary variant that increase the penetrance and expressivity of hypertension-associated tRNAGln 4386T>C mutation.
Introduction Previous study has demonstrated the protective effect of NID1 on myocardial infarction. This study aimed to assess the correlation between NID1 polymorphisms and the prognosis of heart failure (HF). In this study, we aimed to evaluate the association of NID1 polymorphisms with heart failure (HF). Methods A total of 1000 patients with HF were enrolled in the discovery cohort. Genotyping was conducted to assess the relationship between common variants in the NID1 gene and the prognosis of HF. A replication cohort involving 2266 HF patients was used to validate the association between variants and the prognosis of HF. A series of function analysis were conducted to illuminate the underlying mechanism. Results Synonymous variant rs3738530 was identified to be associated with the prognosis of HF in both the discovery cohort (adjusted P = 0.006, HR = 1.58, 95% CI= 1.14-2.19) and replication cohort (adjusted P = 0.005, HR = 1.83, 95% CI= 1.20-2.80). Western blot analysis demonstrated that the protein level of NID1 was significantly higher in the rs3738530-T allele compared to the A allele (P < 0.05). Transcription assays indicated that individuals with the rs3738530-AT+TT genotype exhibited elevated levels of NID1 mRNA relative to those with the AA genotype. Apoptosis assay indicated that overexpression of NID1 could protect AC16 cells from H/R-induced apoptosis. Furthermore, patients with rs3738530-AT+TT genotype exhibited a higher left ventricular ejection fraction and decreased left ventricular end-diastolic diameter compared to those with rs3738530-AA genotype (P< 0.05). Conclusion Common variant rs3738530 in the NID1 gene is associated with the prognosis of HF. NID1 may be a promising therapeutic target for HF in the future.
INTRODUCTION:Next-generation sequencing (NGS) data analysis has become an integral part of clinical genetic diagnosis, raising the question of variant prioritization. The Population Sampling Probability (PSAP) method has been developed to tackle the issue of variant prioritization in the exome of a single patient, by leveraging allele frequencies from population databases and a variant pathogenicity score. METHODS:Here, we present Easy-PSAP, a completely new implementation of the PSAP method comprising two user-friendly and highly adaptable pipelines. Easy-PSAP allows the gene-based recalibration of any in silico pathogenicity prediction score compared to scores of variants seen in the general population, including popular scores like CADD or AlphaMissense. Easy-PSAP can evaluate genetic variants at the scale of a whole exome or a whole genome using information from the latest population and annotation databases. RESULTS:Through simulations on synthetic disease exomes, we show that Easy-PSAP is able to rank more than 50% of causal pathogenic variants in the top 10 variants for an autosomal dominant model of transmission and in top 1 for an autosomal recessive model of transmission. DISCUSSION:These findings, along with the accessibility of the pipeline to both researchers and clinicians, make Easy-PSAP a state-of-the-art tool for variant prioritization in NGS data that can continue to evolve as new frameworks and databases become available. Easy-PSAP is implemented in R and bash within an open-source Snakemake framework. It is available on GitHub alongside conda environments containing the required dependencies (https://github.com/msogloblinsky/Easy-PSAP).
INTRODUCTION:Rheumatoid arthritis (RA) has become a serious threat to human health and quality of life worldwide. Previous studies have demonstrated that genetic factors play a crucial role in the onset and progression of RA. Due to the rapid development of genome-wide association study (GWAS) and large-scale genetic analysis, GWAS research on RA has received widespread attention in recent years. Therefore, we conducted a comprehensive visualization and bibliometric analysis of publications to identify hotspots and future trends in GWAS research on RA. METHODS:Literature on RA and GWAS published between 2002 and 2024 was extracted from the Web of Science Core Collection database by strategic screening. Collected data were further analyzed by using VOSviewer, CiteSpace, and Excel. The collaborations networks of countries, authors, institutions, and the co-citation networks of publications were visualized. Finally, research hotspots and fronts were examined. RESULTS:A total of 713 publications with 45,773 citations were identified. The number of publications and citations has had a significant surge since 2007. The United States contributed the most publications globally. Okada, Yukinori, was the most influential author. The most productive institution in this field was the University of Manchester. The analysis of keywords revealed that "mendelian randomization analysis", "association", "innate", "instruments", "bias", "pathogenesis", and "genome-wide association study" are likely to be the frontiers of research in this field. CONCLUSION:This study can be used to predict future research advances in the fields of GWAS on RA and helps to promote academic collaboration among scholars.
INTRODUCTION:Lung cancer is a global health concern. Molecular analysis of tumor tissues, especially in non-small cell lung cancers, has become an integral part of a holistic approach to the management of the disease. Here, molecular genetic data obtained from tumor tissues collected from 373 male and 89 female patients referred to our clinic with a diagnosis of non-small cell lung cancer are presented. METHODS:Patient samples (n = 462) were assessed via next-generation sequencing using an RNA-based kit containing 36 genes. Data obtained were analyzed using relevant software, and results of analysis are presented together with the demographic characteristics of the patients. RESULTS:Significant somatic variations were detected in 208 of 462 patients. KRAS and EGFR had the greatest variations. Rearrangements, mostly involving ALK, were observed in 37 patients, and rare complex changes involving different genes were detected in 10 patients. CONCLUSION:This study presents the comprehensive molecular data obtained using an RNA-based kit that provided information on single-nucleotide variation/insertion-deletion variants (InDel) and rearrangements in a large-patient series from a single center. Somatic variants were detected in approximately 45% of all patients. According to the Catalogue Of Somatic Mutations In Cancer (COSMIC) database, our rate of variants detected in KRAS and FGFR3 genes was higher. The rate of variants detected in other genes was lower. In addition, fusions not reported in COSMIC were detected. With the development of next-generation sequencing-based tests and an increase in their use, a broad perspective has been provided to many disease groups, including solid tissue cancers, especially non-small cell lung cancers.
Introduction: Psoriasis is caused by an interplay between intrinsic and extrinsic factors. Parental consanguinity increases homozygosity in the genome of the offspring, which in turn increases disease risk. The association between parental consanguinity and psoriasis in the offspring remains unexplored. Therefore, this study sought to evaluate the association of parental consanguinity and family history with psoriasis in the offspring and to determine whether sex modulates the aforementioned associations. Methods: A case-control study enrolled adults aged 21 years and more. Psoriasis cases (n = 139) diagnosed by dermatologists were enrolled from dermatology clinics. Controls (psoriasis-free subjects; n = 278) were enrolled from workplaces. Study subjects reported information on parental consanguinity and family history of psoriasis. Logistic regression was applied to evaluate associations, and adjusted odds ratios (aOR) and 95% confidence intervals (CIs) were estimated. Results: Cases compared to controls were more likely to report parental consanguinity (59.7% vs. 35.6%; p < 0.001) and family history of psoriasis (56.8% vs. 23.7%; p < 0.001). Both parental consanguinity (aOR: 2.13, 95% CI: 1.29–3.50) and family history of psoriasis (aOR: 3.43, 95% CI: 2.07–5.67) were associated with increased odds of having psoriasis. The observed association between parental consanguinity and psoriasis differed according to sex (pinteraction = 0.008), with parental consanguinity being associated with psoriasis among males (aOR: 5.96, 95% CI: 2.39–14.82), but not among females (aOR: 1.36, 95% CI: 0.75–2.49). Conclusion: Psoriasis cases compared to controls were significantly more likely to report parental consanguinity and family history of psoriasis, with parental consanguinity being associated with psoriasis among males only.
Introduction: Systemic lupus erythematosus (SLE) is a common autoimmune disease with unknown etiology. Recently, a growing number of evidence suggested that mitochondrial dysfunctions played active roles in the pathogenesis of SLE, but its detailed mechanism remains largely undetermined. The aim of this study was to analyze the frequencies of mitochondrial tRNA (mt-tRNA) variants in Chinese individuals with SLE. Methods: We carried out a mutational screening of mt-tRNA variants in a cohort of 200 patients with SLE and 200 control subjects by PCR-Sanger sequencing. The potential pathogenicity of mt-tRNA variants was evaluated by phylogenetic conservation and haplogroup analyses. In addition, trans-mitochondrial cybrid cell lines were established, and mitochondrial functions including ATP, reactive oxygen species (ROS), mitochondrial DNA (mtDNA) copy number, mitochondrial membrane potential (MMP), superoxide dismutase (SOD), and mt-RNA transcription were analyzed in cybrids with and without these putative pathogenic mt-tRNA variants. Results: We identified five possible pathogenic variants: tRNAVal G1606A, tRNALeu(UUR) A3243G, tRNAIle A4295G, tRNAGly T9997C, and tRNAThr A15924G that only found in SLE patients but were absent in controls. Interestingly, these variants were located at extremely conserved nucleotides of the corresponding tRNAs and may alter tRNAs’ structure and function. Furthermore, cells carrying these tRNA variants had much lower levels of ATP, mtDNA copy number, MMP, and SOD than controls; by contrast, the levels of ROS increased significantly (p < 0.05 for all). Furthermore, a significant reduction in mt-ND1, ND2, ND3, ND5, and A6 mRNA expression was observed in cells with these mt-tRNA variants, while compared with controls. Thus, failures in tRNA metabolism caused by these variants would impair mitochondrial translation and subsequently lead to mitochondrial dysfunction that was involved in the progression and pathogenesis of SLE. Conclusions: Our study suggested that mt-tRNA variants were important causes for SLE, and screening for mt-tRNA pathogenic variants was recommended for early detection and prevention for this disorder.
Introduction: Ideally, evaluating next-generation sequencing performance requires a gold standard; in its absence, concordance between replicates is often used as substitute standard. However, the appropriateness of the concordance-discordance criterion has been rarely evaluated. This study analyses the relationship between the probability of discordance and the probability of error under different conditions. Methods: This study used a conditional probability approach under conditional dependence then conditional independence between two sequencing results and compares the probabilities of discordance and error in different theoretical conditions of sensitivity, specificity, and correlation between replicates, then on real results of sequencing genome NA12878. The study examines also covariate effects on discordance and error using generalized additive models with smooth functions. Results: With 99% sensitivity and 99.9% specificity under conditional independence, the probability of error for a positive concordant pair of calls is 0.1%. With additional hypotheses of 0.1% prevalence and 0.9 correlation between replicates, the probability of error for a positive concordant pair is 47.4%. With real data, the estimated sensitivity, specificity, and correlation between tests for variants are around 98.98%, 99.996%, and 93%, respectively, and the error rate for positive concordant calls approximates 2.5%. In covariate effect analyses, the effects’ functional form is close between discordance and error models, though the parts of deviance explained by the covariates differ between discordance and error models. Conclusion: With conditional independence of two sequencing results, the concordance-discordance criterion seems acceptable as substitute standard. However, with high correlation, the criterion becomes questionable because a high percentage of false concordant results appears among concordant results.
Introduction: Lung cancer is the most common cancer worldwide in mortality and the second in incidence. Epidemiological studies found a higher lung cancer risk for smoking women in comparison to men, but these sex differences, irrespective of smoking habits, remains controversial. One of the hypotheses concerns the genetic contribution of the sex chromosomes. However, while genomewide association studies identified many lung cancer susceptibility loci, these analyses have excluded X-linked loci. Methods: To account for non-genetic factors, we first presented an association test based on an additive-multiplicative hazard model accounting for random/non-random X-inactivation process. A simulation study was performed to investigate the properties of the proposed test as compared with the Wald test from a Cox model with random X-inactivation process and the partial likelihood ratio test proposed by Xu et al. accounting for non-random X-inactivation process. Then, we performed an X chromosome-wide association study on 9,261 individuals from the population based cohort CARTaGENE to identify susceptibility loci for lung cancer among current and past smokers. We adjusted for the PLCOm2012 lung cancer risk score used in screening programs. Results: Simulation results show the good behavior of the proposed test in terms of power and Type I error probability as compared to the Xu et al. and the Wald test. Using the proposed test statistic and adjusting for the PLCOm2012 score, the X chromosome-wide statistical analysis identified two SNPs in low-linkage disequilibrium located in the IL1RAPL1 (IL-1 R accessory protein-like) gene: rs12558491 (p=2.75*10-9) and rs12835699 (p=1.26*10-6). For both SNPs, the minor allele was associated with lower lung cancer risk. Adjusting for multiple testing, no signal was detected using the Wald or the Xu et al. likelihood ratio tests. Conclusion: By taking into account smoking behavior and the X-inactivation process, the investigation of the X chromosome has shed a new light on the association between X-linked loci and lung cancer. We identified two loci associated with lung cancer located in the IL1RAPL1 gene. This finding would have been overlooked by examining only results from other test statistics.
Introduction Recessive mutations in the CAPN3 gene can lead to Limb-girdle muscular dystrophy Recessive 1 (LGMD R1). Targeted next-generation sequencing facilitates the discovery of new mutations linked with disease, owing to its ability to selectively enrich specific genomic regions. Methods We performed targeted next-generation sequencing of all exons of the CAPN3 gene in four patients with sporadic LGMD and further analyzed the effects of the novel identified variant using various software tools. Results We found 5 variants in CAPN3 gene in four patients, c.82_83insC (insertion mutation) and c.1115+2T>C (splicing mutation) are reported for the first time in CAPN3 (NM_000070.2). The bioinformatics analysis indicated that these two novel variants affected CAPN3 transcription as well as translation. Discussion Our findings reveal previously unreported splicing mutation and insertion mutation in CAPN3 gene, further expanding the pathogenic gene profile of LGMD.
Introduction: Previous studies have demonstrated effects of rare coding variants on common, clinically relevant phenotypes although the additive burden of these variants makes only a small contribution to overall trait variance. Although recessive effects of individual homozygous variants have been studied, little work has been done to elucidate the impact of rare coding variants occurring together as compound heterozygotes. Methods: In this study, attempts were made to identify pairs of variants likely to be occurring as compound heterozygotes using 200,000 exome-sequenced subjects from the UK Biobank. Pairs of variants, which were seen together in the same subject more often than would be expected by chance, were excluded as it was assumed that these might be present in the same haplotype. Attention was restricted to variants with minor allele frequency <= 0.05 and to those predicted to alter amino acid sequence or prevent normal gene expression. For each gene, compound heterozygotes were assigned scores based on the rarity and predicted functional consequences of the constituent variants and the scores were used in a logistic regression analysis to test for association with hypertension, hyperlipidaemia, and type 2 diabetes. Results: No statistically significant associations were observed and the results conformed to the distribution, which would be expected under the null hypothesis. The average number of apparently compound heterozygous subjects for each gene was only 282.2. Conclusion: It seems difficult to detect an effect of compound heterozygotes on the risk of these phenotypes. Even if recessive effects from compound heterozygotes do occur, they would only affect a small number of people and overall would not make a substantial contribution to phenotypic variance. This research has been conducted using the UK Biobank Resource.
INTRODUCTION:Joint linkage and association (JLA) analysis combines two disease gene mapping strategies: linkage information contained in families and association information contained in populations. Such a JLA analysis can increase mapping power, especially when the evidence for both linkage and association is low to moderate. Similarly, an association analysis based on haplotypes instead of single markers can increase mapping power when the association pattern is complex.METHODS:In this paper, we present an extension to the GENEHUNTER-MODSCORE software package that enables a JLA analysis based on haplotypes and uses information from arbitrary pedigree types and unrelated individuals. Our new JLA method is an extension of the MOD score approach for linkage analysis, which allows the estimation of trait-model and linkage disequilibrium (LD) parameters, i.e., penetrance, disease-allele frequency, and haplotype frequencies. LD is modeled between alleles at a single diallelic disease locus and up to three diallelic test markers. Linkage information is contributed by additional multi-allelic flanking markers. We investigated the statistical properties of our JLA implementation using extensive simulations, and we compared our approach to another commonly used single-marker JLA test. To demonstrate the applicability of our new method in practice, we analyzed pedigree data from the German National Case Collection for Familial Pancreatic Cancer (FaPaCa).RESULTS:Based on the simulated data, we demonstrated the validity of our JLA-MOD score analysis implementation and identified scenarios in which haplotype-based tests outperformed the single-marker test. The estimated trait-model and LD parameters were in good accordance with the simulated values. Our method outperformed another commonly used JLA single-marker test when the LD pattern was complex. The exploratory analysis of the FaPaCa families led to the identification of a promising genetic region on chromosome 22q13.33, which can serve as a starting point for future mutation analysis and molecular research in pancreatic cancer.CONCLUSION:Our newly proposed JLA-MOD score method proves to be a valuable gene mapping and characterization tool, especially when either linkage or association information alone provide insufficient power to identify the disease-causing genetic variants.
INTRODUCTION:Ideally, evaluating NGS performance requires a gold standard; in its absence, concordance between replicates is often used as substitute standard. However, the appropriateness of the concordance-discordance criterion has been rarely evaluated. This study analyzes the relationship between the probability of discordance and the probability of error under different conditions. METHODS:This study used a conditional probability approach under conditional dependence then conditional independence between two sequencing results and compares the probabilities of discordance and error in different theoretical conditions of sensitivity, specificity, and correlation between replicates, then on real results of sequencing genome NA12878. The study examines also covariate effects on discordance and error using generalized additive models with smooth functions. RESULTS:With 99% sensitivity and 99.9% specificity under conditional independence, the probability of error for a positive concordant pair of calls is 0.1%. With additional hypotheses of 0.1% prevalence and 0.9 correlation between replicates, the probability of error for a positive concordant pair is 47.4%. With real data, the estimated sensitivity, specificity, and correlation between tests for variants are around 98.98%, 99.996%, and 93%, respectively, and the error rate for positive concordant calls approximates 2.5%. In covariate effect analyses, the effects' functional form are close between discordance and error models, though the parts of deviance explained by the covariates differ between discordance and error models. CONCLUSION:With conditional independence of two sequencing results, the concordance-discordance criterion seems acceptable as substitute standard. However, with high correlation, the criterion becomes questionable because a high percentage of false concordant results appears among concordant results.
INTRODUCTION:The standard way of using tests for compatibility of genetic markers with the Hardy-Weinberg equilibrium (HWE) assumptionvas a means of quality control in genetic association studies (GAS) is to vcarry out this step of preliminary data analysis with the sample of non-diseased vindividuals only. We show that this strategy has no rational basis whenever the genotype--phenotype relation for avmarker under consideration satisfies the assumption of co-dominance.METHODS/RESULTS:The justification of this statement is the fact rigorously shown here that under co-dominance, the genotype distribution of a diallelic marker is in HWE among the controls if and only if the same holds true for the cases.CONCLUSION:The major practical consequence of that theoretical result is that under the co-dominance model, testing for HWE should be done both for cases and controls aiming to establish the combined (intersection) hypothesis of compatibility of both underlying genotype distributions with the HWE assumption. A particularly useful procedure serving this purpose is obtained through applying the confidence-interval inclusion rule derived by Wellek, Goddard and Ziegler (Biom J. 2010; 52:253-270) to both samples separately and combining these two tests by means of the intersection-union principle.
