Frontiers in Genetics最新文献

The FK506 Binding Protein 5 (FKBP5) gene encodes a protein that binds to the immunosuppressive agent FK506. FKBP5 expression is regulated by genetic variation and epigenetic mechanisms, including DNA methylation (DNAm). This gene regulates the glucocorticoid receptor (GR), and aberrant FKBP5 methylation is associated with psychiatric and metabolic disorders. Recent evidence also indicates that FKBP5 methylation significantly influences malignant tumors. The methylation status of FKBP5 not only modulates its own expression but also contributes to disease pathogenesis by regulating downstream signaling pathways. Despite extensive research on FKBP5 in individual disease contexts, a critical gap remains in understanding how its DNAm serves as a unifying epigenetic mechanism across psychiatric, metabolic, and neoplastic disorders. Existing reviews often focus on single disease domains or on genetic and protein-level regulation, lacking a systematic, horizontal integration analysis centered on DNAm-a dynamic and reversible modification. This review aims to fill this gap by proposing a coherent "epigenetic regulatory framework" that elucidates how tissue-and site-specific FKBP5 DNAm patterns, through modulating glucocorticoid (GC) signaling, stress responses, and inflammatory pathways (e.g., NF-κB), contribute to divergent pathological outcomes. By integrating evidence from disparate fields, this review summarizes the role of FKBP5 DNAm in disease biology, its functions across various disorders, and its potential as a biomarker and therapeutic target, aiming to provide a theoretical foundation and strategic insights for disease diagnosis and treatment.

Individuals with rare genetic diseases collectively comprise 3.5%-5.9% of the population, roughly 400 million people worldwide. Undiagnosed rare disease programs have leveraged next-generation sequencing technologies to facilitate genetic diagnoses, thereby shortening the complex diagnostic odysseys that many of these patients and their families endure. However, enrollment data suggest disparities in access to undiagnosed genetic disease programs among racial and ethnic minorities. To better understand this issue, we conducted a retrospective review of our rare undiagnosed disease program to assess whether referral route was a determinant of disparities for minoritized racial and ethnic communities. Participants enrolled in the Yale Pediatric Genomics Discovery Program from 2016 to 2022 were self-categorized into four racial and ethnic groups: Hispanic/Latinx (any race), non-Hispanic White, non-Hispanic Black/African American, non-Hispanic Other. Route of referral was classified as Inpatient, Outpatient, or Outside/Self referrals. Completion rates were the percentage of participants who completed enrollment compared to their respective group. Demographics for program participants were different from Yale-New Haven Children's Hospital demographics, with over-representation of non-Hispanics Whites. Direct inpatient recruitment had a higher yield of Hispanic individuals, which was offset by under-representation of minoritized individuals in the Outside/Self setting. Inpatients had lower referral completion rates compared to Outpatient and Outside/Self referrals. These data suggest that the route of referral may represent different levels of access to care, and inpatient recruitment may be leveraged to promote participation by some minoritized communities. We encourage other programs to examine their cohorts for representation and identify strategies for improving participation.

Elective Genomic Testing (EGT) can identify individuals at risk for actionable conditions that would not come to clinical attention following current testing guidelines. We describe the results of a checkup unit from a leading Spanish University hospital (Clínica Universidad de Navarra, Spain) that has incorporated EGT to their regular clinical practice. Medical anamnesis, biochemistry, low-intensity whole body scan and EGT with interpretation of over 560 genes related to actionable adult-onset diseases (Veritas Intercontinental, Spain) was performed in 400 participants, including medical consultation before and after the checkup. Clinically relevant variants were identified in 79/400 participants (19.8%). Thirteen individuals (3.3%) presented with clinical variants included in the American College of Medical Genetics and Genomics secondary finding list (ACMG SF list); 69.2% of these variants showed potential association with personal or family history (PFH). The study presents the results of the first hospital integrating EGT into the checkup unit.

Objective: This study was conducted to investigate the clinical and genetic characteristics of a family affected by hereditary spherocytosis (HS) combined with familial chylomicronemia syndrome (FCS), identify the pathogenic cause, and provide a basis for the clinical diagnosis, treatment, and genetic counseling of affected children.

Methods: Clinical data were collected from family members. High-throughput sequencing was performed to identify pathogenic variants in genes associated with HS and FCS in the proband. Suspected pathogenic mutations were confirmed in family members via PCR-Sanger sequencing. Bioinformatics analysis and three-dimensional protein structure prediction were also conducted.

Results: The proband presented with severe anemia, splenomegaly, and jaundice. Genetic testing revealed a heterozygous mutation, c.6005G>A (p.Trp2002*), in the spectrin beta chain (SPTB)gene (NM_001355436.2) and a missense mutation, c.292G>A (p.Ala98Thr), in the lipoprotein lipase (LPL) gene (NM_000237.3). The SPTB c.6005G>A (p.Trp2002*) mutation was inherited from the mother, who exhibited mild anemia, jaundice, and splenomegaly. The LPL c.292G>A (p.Ala98Thr) mutation was inherited from the father, who had hypertriglyceridemia. The SPTB c.6005G>A (p.Trp2002*) mutation is extremely rare in the general population.

Conclusion: The heterozygous mutations SPTB c.6005G>A (p.Trp2002*) and LPL c.292G>A (p.Ala98Thr) are the pathogenic causes in this family and provide a basis for clinical management and genetic counseling. Based on the HGMD, 1000G, and ExAC databases, the SPTB c.6005G>A (p.Trp2002*) mutation is reported here for the first time, enriching the mutation spectrum of the SPTB gene.

Background: Intervertebral disc degeneration (IDD) is a major contributor to low back pain, yet its molecular mechanisms remain unclear. Identifying potential druggable genes (PDGs) associated with IDD could facilitate early diagnosis and targeted therapy. This study aimed to explore the diagnostic and mechanistic significance of PDGs in IDD.

Methods and results: Three GEO datasets were merged as a training set, with another blood-based dataset as testing. PDGs were obtained from the literature and intersected with differentially expressed genes (DEGs). Functional enrichment and immune infiltration analyses were performed. A Lasso regression model was developed for diagnosis, and Mendelian Randomization (MR) analysis inferred causality. Cellular experiments validated key gene expression. Fourteen differentially expressed PDGs were identified, primarily involved in immune responses and neutrophil activity. A five-gene diagnostic model (BPI, CD160, CTSG, CYP27A1, KIF11) was constructed and demonstrated high accuracy. MR analysis confirmed a causal relationship between BPI and CTSG with IDD. GSEA revealed that BPI was negatively associated with oxidative phosphorylation, while CTSG was linked to the G2M checkpoint. Cellular experiments confirmed BPI and CTSG upregulation in TNF-α-induced NPCs.

Conclusion: This study constructed a diagnostic model and identified BPI and CTSG as potential biomarkers for IDD, providing new insights into IDD treatment.

Polycystin-1 (PC1), encoded by the PKD1 gene, forms a complex with polycystin-2 (PKD2; 173910) that regulates multiple signaling pathways to maintain normal renal tubular structure and function. Mutations in the PKD1 gene are the primary cause of type 1 PKD (polycystic kidney disease), accounting for 78%-85% of all PKD cases. In this study, we report a case of a boy presenting with microscopic hematuria with multiple renal cysts and carrying an unreported intronic variant, c.12445-34_12445-10del, in the PKD1 gene inherited from his father who also presented PKD. Sanger sequencing and reverse transcription polymerase chain reaction (RT-PCR) for minigene splicing assays showed two abnormal splicing alterations with the c.12445-34_12445-10del variant at the mRNA level: one causes a 16-bp deletion in exon 46, resulting in premature protein termination (p.Phe4149GlyfsTer45), and the other results in a 205-bp deletion, leading to delayed termination (p.Phe4149ProfsTer139). Based on the clinical characteristics and gene mutations with functional verification, the patient was finally diagnosed with PKD caused by PKD1 function defection, as confirmed by the combined clinical features and genetic analysis. Management strategies include dietary management, blood pressure monitoring, and regular follow-up of kidney function. This is the first study to report an intronic deletion in the PKD1 gene that influences alternative splicing. Our findings expand the mutation spectrum leading to PKD1-related diseases and highlight the importance of genetic counseling for the family.

Introduction: A novel set of pyramided lines for durable blast resistance was developed using marker-assisted backcross breeding (MABB) strategy in the genetic background of the aromatic landrace Mushk Budji (MB).

Methods: Simultaneous-but-stepwise transfer of the blast resistance genes Pi54 and Pi9 was achieved through the integration of foreground selection (FS) and background genome recovery processes, aided by genome-wide SSR and >1500 KASP markers. MABB, whole genome re-sequencing, coupled with stringent phenotypic selection for aroma, amylose content, kernel dimensions, and cooking quality, helped minimize the linkage drag and achieve early recurrent parent genome (RPG) recovery in the inter-cross BC₂F_2:3 generation.

Results: The two-gene lines carrying Pi9 + Pi54 were developed through inter-crossing corresponding near-isogenic lines (NILs) with an RPG of approximately 90%. With the help of sequencing of the derived NILs, we were able, for the first time, to establish the role of major alleles underlying rice quality and stress resilience in MB. In the process, we confirmed the retention of favorable alleles at key genetic loci, such as BADH2 (aroma), Wx (amylose content), Rc (white pericarp), Hd1/Hd4/Hd5 (heading date), and COLD1/COLD6 (cold tolerance) in the derived NILs. GGE biplot analysis revealed stable performance of five advanced lines across target ecologies.

Discussion: The set of NILs was useful in elucidating the phenotypic effects of 11 genes related to grain type, quality, and adaptability traits in the landrace MB. Multi-environment screening for blast resistance, at hot spot locations, in addition to artificial inoculation, validated the resistance response of the lines to both leaf and neck blast. This study demonstrates the successful integration of genomics-assisted breeding and phenotypic selection to improve a heritage rice variety for enhanced disease resistance and ecological adaptation. The development of improved MB lines represents a rare endeavor towards the area expansion and conservation of the heirloom rice.

Introduction: Coronary atherosclerotic heart disease (CHD) is a leading cause of morbidity and mortality worldwide, making timely identification critical for improving patient prognosis. However, traditional imaging examinations are limited by high costs and patient selection bias, while existing prediction models often lack interpretability and generalization ability. This study aimed to develop a robust, interpretable machine learning approach to address these challenges.

Methods: This retrospective study analyzed hospitalized patients at Quzhou People's Hospital from July 2021 to March 2025. Patients diagnosed with CHD were categorized as positive samples, while those without cardiovascular disease served as negative controls. The dataset integrated demographic data, blood biomarkers, and vital signs. A Generative Adversarial Imputation Network (GAIN) was utilized to handle missing values, and multiple machine learning models were constructed and compared for prediction performance.

Results: Among the evaluated algorithms, the XGBoost model achieved superior performance on the test set with an Area Under the Curve (AUC) of 0.9053. To enhance clinical utility, the integration of SHAP (SHapley Additive exPlanations) values enabled both global and local interpretation of model decisions. Key predictive factors identified included mean respiratory rate during hospitalization, age, high-sensitivity troponin I (hs-cTnI), and hypertension.

Discussion: The developed model demonstrates robust prediction performance combined with high clinical interpretability. Unlike traditional "black box" models, this approach clarifies the contribution of specific risk factors. Crucially, the tool is well-suited for dual deployment: serving as an automated screening tool integrated into hospital electronic health records (EHRs) and as a self-monitoring aid for individuals with underlying health conditions via mobile health applications.