Human Mutation最新文献

S. S. Cornelis, M. Bauwens, L. Haer-Wigman, et al., “Compendium of Clinical Variant Classification for 2,246 Unique ABCA4 Variants to Clarify Variant Pathogenicity in Stargardt Disease Using a Modified ACMG/AMP Framework,” Human Mutation 2023 (2023): 6815504, https://doi.org/10.1155/2023/6815504.

In the article titled “Compendium of Clinical Variant Classification for 2,246 Unique ABCA4 Variants to Clarify Variant Pathogenicity in Stargardt Disease Using a Modified ACMG/AMP Framework,” there was an error in Figure 1 artwork and caption. The corrected Figure 1 artwork and caption are shown below:

We apologize for this error.

Variants of uncertain significance (VUS) in the DNA mismatch repair (MMR) genes can confound the diagnosis and treatment of suspected Lynch syndrome (LS) patients. To aid the reclassification of VUS, we developed the in cellulo analysis of MMR variants (inCAMA) and used known control variants to calibrate this assay such that results can be readily applied as functional evidence by expert classification panels. We used CRISPR gene engineering to introduce known pathogenic and benign variants into the MSH6 or MSH2 loci in human embryonic stem cells and assessed their effects on cellular MMR repair and damage response functions. Our functional assay successfully discerned known pathogenic and benign variants. Using these results and performing a linear regression analysis with available odds of pathogenicity scores for the known calibration variants, we created equations that can generate a functional odds of pathogenicity score for any future MSH6 or MSH2 variant tested. In summary, inCAMA represents a new, calibrated assay for testing the function of virtually any MSH6 or MSH2 variant. The conversion of assay results directly into odds of pathogenicity scores makes it possible to use any PS3 or BS3 evidence strength level toward the reclassification of VUS.

Over the past decade, genome-wide association studies (GWASs) have found genetic variants associated with elevated risk for nonsyndromic orofacial cleft (NSOFC). In the post-GWAS era of NSOFC genetic research, an important aim is to identify the pathogenic variants that influence craniofacial development processes, towards understanding how they lead to disease manifestation. However, two major challenges hinder the translation of GWAS results into a mechanistic understanding. Firstly, it is uncertain whether the variants pinpointed by GWAS represent the underlying pathogenic variants; secondly, the bulk of genetic variants identified through GWAS are situated in noncoding regions of the genome, complicating their biological interpretation. Presently, research on noncoding genetic variants associated with NSOFC predominantly centers on variants located in transcriptional regulatory elements. These variants modulate transcription, subsequently altering the expression of downstream target genes and disrupting gene regulatory networks. We provide a systematic summary of the recent NSOFC-associated GWAS findings for the first time. With a particular focus on variants located in noncoding regions, we delve into current statistical methods and functional approaches for identifying and validating causal variants, aiming to bridge the gap between genetic variants identified by GWAS and their underlying pathogenic mechanism responsible for NSOFC. Deciphering causal variants underlying NSOFC offers valuable clinical insights that may advance early diagnosis, enhance risk stratification, and facilitate the discovery of novel therapeutic targets.

Dyskeratosis congenita (DC) is an inherited bone marrow failure syndrome characterized by defects in telomere biology and clinical manifestations such as nail dystrophy, skin pigmentation abnormalities, and mucosal leukoplakia. Here, using whole exome sequencing (WES), whole genome sequencing (WGS), optical mapping sequencing (OGM), third-generation sequencing, and mRNA sequencing, we diagnosed a participant with PARN gene complex compound heterozygous variants. In addition, protein structure simulation, immunohistochemistry, and western blot were conducted to investigate the structure and expression level of the PARN protein. WES revealed a maternal PARN variant, c.204G>T (p.Gln68His) (NM_002582.3). An insertion variant in the PARN gene from the father was identified by OGM and mRNA sequencing. Third-generation sequencing results determined the insertion position of the SINE-VNTR-Alu (SVA) transposon and its size (2537 bp), which was found to lead to a premature stop codon (p.Gly469delinsGlu∗). The PARN protein level of the parents was reduced due to complex heterozygous variants. Overall, OGM diagnosed the structural variants of the participant with DC, supplementing the disease variant spectrum of DC. This case highlights a novel disease-causing structural variant and the importance of transposon analysis in a clinical diagnostic setting.

Atherosclerosis is a common and significant cardiovascular condition that frequently goes undiagnosed by conventional diagnostic and treatment techniques until it reaches a more advanced stage. This challenge impedes the capacity to apply early detection and intervention measures. As a result, the creation of innovative and more accurate biomarkers is critically important. The study first recognizes genes associated with macrophages through single-cell analysis, investigating their functions. Subsequently, various machine learning approaches are utilized to identify significant regulatory genes related to macrophages. In addition, molecular docking studies are performed to evaluate the binding affinity of these crucial markers with therapeutics targeting atherosclerosis. The ImmuCellAI platform is also utilized to assess immune cell scores in atherosclerotic samples, aiding in the examination of connections between vital diagnostic markers and immune cells. Finally, the expression changes of the selected key genes are confirmed using qRT-PCR and Western blot methods. Through analyses at the single-cell level and differential assessments, we discovered 58 genes related to macrophages that exhibited differential expression. Functional evaluations indicated a strong correlation between these genes and the immune microenvironment. By conducting cluster analysis, we assessed how different subgroups of patients with atherosclerosis respond to immunotherapy. Utilizing techniques such as XGBoost, random forest, and the GOsemsim algorithm, we pinpointed five crucial diagnostic markers. Studies on molecular docking validated that these important markers could act as potential drug targets for atherosclerosis. Finally, our experimental analysis revealed a significant overexpression of these five diagnostic markers in tissues affected by atherosclerosis. This research introduces novel diagnostic indicators associated with macrophages in atherosclerosis and emphasizes their potential as targets for therapies related to the immune system.

Purpose: The purpose of this study is to identify genes and transcription factors underlying functional differences in neonatal versus adult peripheral blood monocytes, elucidating mechanisms of severe Group B streptococcus (GBS) infection in neonates.

Methods: Differentially expressed genes (DEGs) in neonatal and adult peripheral blood monocytes were detected via RNA sequencing (RNA-seq), followed by assay for transposase-accessible chromatin sequencing (ATAC-seq) to characterize differentially accessible region (DAR)–associated genes. Integrated analyses of RNA-seq and ATAC-seq pinpointed candidate genes and transcription factors. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) validated the mRNA expression of common genes and transcription factors.

Results: RNA-seq profiling of neonatal and adult peripheral monocytes identified 669 overexpressed and 440 underexpressed genes in neonates, with overexpressed genes enriched in bacterial response pathways and underexpressed genes in cytokine production and cell killing pathways. Chromatin accessibility analysis revealed 36,782 differential peaks (21,192 gained, 15,590 lost) in neonatal peripheral monocytes. Integrated RNA-seq and ATAC-seq analysis pinpointed 30 overlapping genes among DEGs, DAR-associated genes, and immunologically relevant genes (IRGs). qRT-PCR validated higher expression of CEBPB, JUN, BATF, PTK2B, and ITGAV and lower ADA2 and RORA expression in neonatal peripheral monocytes compared to that in adults.

Conclusions: The study revealed distinct differences in the transcriptome and chromatin accessibility between neonatal and adult peripheral monocytes, identifying potential genes linked to GBS infection vulnerability of neonates. These findings advance our understanding of neonatal immune dysfunction in severe GBS disease, informing future therapeutic targets.

Background: The high morbidity and mortality of lung adenocarcinoma (LUAD) are partly caused by a lack of sensitive and reliable molecular markers for early diagnosis. Programmed cell death (PCD) is a crucial process involved in tumorigenesis and immune regulation, and identifying PCD-correlated genes may contribute to the precision diagnosis and targeted therapy of LUAD.

Methods: LUAD samples were acquired from UCSC Xena and Gene Expression Omnibus (GEO) database. PCD-correlated module genes were identified by WGCNA. “Limma” package was employed for screening differentially expressed genes (DEGs) between LUAD and control samples, followed by conducting functional enrichment analysis with “ClusterProfiler” package. Hub genes were selected through machine learning algorithms. Biomarkers for LUAD were screened and further validated by receiver operating characteristic (ROC) analysis. The robustness of the diagnostic model was verified by the confusion matrix. Immune cell infiltration was assessed employing “ESTIMATE” and “GSVA” packages. HALLMARK pathway score was calculated with the “GSVA” package. Transcription factor (TF)–biomarker–chemical network was established using NetworkAnalyst and Cytoscape software. The expressions of the biomarkers in LUAD cells were detected by in vitro experiments. The viability, migration, and invasion of the LUAD cells were measured by CCK-8, wound healing, and Transwell assays.

Results: We identified 160 module genes and 5934 DEGs. Then, eight hub genes were selected applying LASSO and support vector machine–recursive feature elimination (SVM-RFE) analyses. Further, FGR, TLR4, and NLRC4, which showed an area under the ROC curve (AUC) > 0.7, were determined as the diagnostic biomarkers for LUAD. Interestingly, they were all low expressed in LUAD samples. We developed a diagnostic model that demonstrated robust performance in distinguishing LUAD samples from normal controls. The three biomarkers showed positive correlation to the infiltration of most immune cells and enrichment in HALLMARK pathways associated with inflammation, immune regulation, and cytokine signaling. Moreover, nine TFs and nine small-molecule compounds targeting the three biomarkers were predicted to construct a TF–biomarker–chemical network. Functional validation revealed that all the three biomarkers were significantly downregulated in LUAD cells. Notably, FGR overexpression markedly suppressed LUAD cell proliferation, migration, and invasion.

Conclusion: This study identified three PCD-related biomarkers for LUAD diagnosis, providing new potential therapeutic targets.

Peutz–Jeghers syndrome (PJS) is a rare autosomal dominant disorder hallmarked by mucocutaneous melanocytic macules and gastrointestinal hamartomatous polyposis associated with germline/somatic pathogenic variants in the tumor suppressor STK11. PJS is clinically heterogeneous; however, the relationship between clinical phenotype and genotype remains elusive. Here, we report a family with PJS that harbors a heterozygous STK11 whole gene deletion combined with a heterozygous variant in TP53AIP1 that segregates with mucocutaneous pigmentation in the family. RNA-seq analysis followed by qRT-PCR confirmed that the expression of STK11, TP53, and TP53AIP1 and a large fraction of p53 signaling pathway components are significantly reduced, while Wnt signaling pathway effectors are upregulated in cells from an affected individual. Our findings shed light on transcriptome-level pathway dysregulation in PJS with germline deletion of STK11. Further evaluation of mutational burden across relevant signaling pathways can likely inform disease prognosis.

Colorectal cancer (CRC) is a leading cause of cancer-related morbidity and mortality worldwide. Despite the efficacy of oxaliplatin-based chemotherapy (CT) in CRC treatment, CT resistance remains a major obstacle to successful patient outcomes. Epithelial–mesenchymal transition (EMT), a key cellular process in cancer metastasis, plays a pivotal role in resistance to CT. The tumor microenvironment (TME), particularly cancer-associated fibroblasts (CAFs), is known to contribute to EMT and therapy resistance. Here, we employ single-cell RNA sequencing (scRNA-seq) to analyze primary CRC tumor samples from patients undergoing CT and nonchemotherapy (nCT) treatments. Our study identifies specific epithelial cell clusters resistant to oxaliplatin, elucidating the molecular pathways involved in EMT and resistance. Furthermore, we explore the role of CAF subpopulations in promoting resistance within the TME. Our findings highlight the importance of functional immune profiling and genomic analyses in identifying potential biomarkers for predicting CT responses and improving personalized treatment strategies. This work provides new insights into the molecular mechanisms of oxaliplatin resistance in CRC and supports the development of novel immune-based therapeutic approaches to enhance patient outcomes.