Human Heredity最新文献

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) technology and large-scale genetic analysis, research on GWAS and 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 research on RA and GWAS. Methods Literature on RA and GWAS published between 2002 and 2024 was extracted from the Web of Science Core Collection (WoSCC) 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. Moreover, 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 a significant surge since 2007. The United States (U.S.) contributed the most publications globally. Okada, Yukinori was the most influential author. The highest productive institutions 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 in 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: 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.

Introduction: Polygenic score (PGS) is a valuable method for assessing the estimated genetic liability to a given outcome or genetic variability contributing to a quantitative trait. While polygenic risk scores are widely used for complex traits, their application in uncovering shared genetic predisposition between phenotypes, i.e., when genetic variants influence more than one phenotype, remains limited.

Methods: We developed an R package, comorbidPGS, which facilitates a systematic evaluation of shared genetic effects among (cor)related phenotypes using PGSs. The comorbidPGS package takes as input a set of single nucleotide polymorphisms along with their established effects on the original phenotype (Po), referred to as Po-PGS. It generates a comprehensive summary of effect(s) of Po-PGS on target phenotype(s) (Pt) with customisable graphical features.

Results: We applied comorbidPGS to investigate the shared genetic predisposition between phenotypes defining elevated blood pressure (systolic blood pressure, SBP; diastolic blood pressure, DBP; pulse pressure) and several cancers (breast cancer; pancreatic cancer, PanC; kidney cancer, KidC; prostate cancer, PrC; colorectal cancer, CrC) using the European ancestry UK Biobank individuals and GWAS meta-analyses summary statistics from independent set of European ancestry individuals. We report a significant association between elevated DBP and the genetic risk of PrC (β [SE] = 0.066 [0.017], p value = 9.64 × 10-5), as well as between CrC PGS and both, lower SBP (β [SE] = -0.10 [0.029], p value = 3.83 × 10-4) and lower DBP (β [SE] = -0.055 [0.017], p value = 1.05 × 10-3). Our analysis highlights two nominally significant relationships for individuals with genetic predisposition to elevated SBP leading to higher risk of KidC (OR [95% CI] = 1.04 [1.0039-1.087], p value = 2.82 × 10-2) and PrC (OR [95% CI] = 1.02 [1.003-1.041], p value = 2.22 × 10-2).

Conclusion: Using comorbidPGS, we underscore mechanistic relationships between blood pressure regulation and susceptibility to three comorbid malignancies. This package offers valuable means to evaluate shared genetic susceptibility between (cor)related phenotypes through polygenic scores.

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 4 patients with sporadic limb-girdle muscular dystrophy (LGMD) and further analyzed the effects of the novel identified variant using various software tools.

Results: We found 5 variants in CAPN3 gene in 4 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: 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: 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: 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.