Disease Genes Research Articles

Identification and Validation of STC1 Act as a Biomarker for High-Altitude Diseases and Its Pan-Cancer Analysis.

High-altitude diseases, including acute mountain sickness (AMS), high-altitude cerebral edema (HACE), and high-altitude pulmonary edema (HAPE), are closely related to an individual's ability to adapt to hypoxic environments. However, specific research in this field is relatively limited, and further biomarker research and clinical trials are needed to clarify the exact role and potential therapeutic applications of key genes in high-altitude diseases. This study focuses on the role of the STC1 gene in high-altitude diseases and explores its expression patterns in different types of cancer. By using gene expression data analysis and functional experiments, we identified STC1 as a key gene affecting the development of altitude sickness. In addition, we also conducted expression and mutation analysis on STC1 in various cancer samples and found significant differences in the expression of this gene in 13 types of malignant tumors, which is associated with the hypoxic state in the tumor microenvironment. In addition, STC1 is significantly associated with patient prognosis and influences tumor immunity by mediating six types of immune cells (CD8+T cells, CD4+T cells, neutrophils, macrophages, monocytes, and B cells) in the tumor microenvironment. The expression and diagnostic value of STC1 were confirmed through GEO datasets and qPCR testing, indicating consistency with the results of bioinformatics analysis. These results indicate that STC1 is not only an important factor in the adaptive response to high-altitude diseases but may also play a role in the adaptation of cancer to low-oxygen environments. Our research provides a new perspective and potential targets for the discovery of biomarkers for high-altitude diseases and cancer treatment.

Machine Learning in Identifying Marker Genes for Congenital Heart Diseases of Different Cardiac Cell Types.

Congenital heart disease (CHD) represents a spectrum of inborn heart defects influenced by genetic and environmental factors. This study advances the field by analyzing gene expression profiles in 21,034 cardiac fibroblasts, 73,296 cardiomyocytes, and 35,673 endothelial cells, utilizing single-cell level analysis and machine learning techniques. Six CHD conditions: dilated cardiomyopathy (DCM), donor hearts (used as healthy controls), hypertrophic cardiomyopathy (HCM), heart failure with hypoplastic left heart syndrome (HF_HLHS), Neonatal Hypoplastic Left Heart Syndrome (Neo_HLHS), and Tetralogy of Fallot (TOF), were investigated for each cardiac cell type. Each cell sample was represented by 29,266 gene features. These features were first analyzed by six feature-ranking algorithms, resulting in several feature lists. Then, these lists were fed into incremental feature selection, containing two classification algorithms, to extract essential gene features and classification rules and build efficient classifiers. The identified essential genes can be potential CHD markers in different cardiac cell types. For instance, the LASSO identified key genes specific to various heart cell types in CHD subtypes. FOXO3 was found to be up-regulated in cardiac fibroblasts for both Dilated and hypertrophic cardiomyopathy. In cardiomyocytes, distinct genes such as TMTC1, ART3, ARHGAP24, SHROOM3, and XIST were linked to dilated cardiomyopathy, Neo-Hypoplastic Left Heart Syndrome, hypertrophic cardiomyopathy, HF-Hypoplastic Left Heart Syndrome, and Tetralogy of Fallot, respectively. Endothelial cell analysis further revealed COL25A1, NFIB, and KLF7 as significant genes for dilated cardiomyopathy, hypertrophic cardiomyopathy, and Tetralogy of Fallot. LightGBM, Catboost, MCFS, RF, and XGBoost further delineated key genes for specific CHD subtypes, demonstrating the efficacy of machine learning in identifying CHD-specific genes. Additionally, this study developed quantitative rules for representing the gene expression patterns related to CHDs. This research underscores the potential of machine learning in unraveling the molecular complexities of CHD and establishes a foundation for future mechanism-based studies.

Genetic Variants Associated with Body Mass Index Changes in Korean Adults: The Anseong and Ansan Cohorts of the Korean Genome and Epidemiology Study.

Although previous studies have examined the relationship between obesity and genetics in response to the growing obesity epidemic, research on the relationship between obesity and long-term changes in body mass index (BMI) is limited. To investigate this relationship, data from 1030 cases in the Anseong and Ansan cohorts were collected from the Korean Genome and Epidemiology Study conducted by the Korea National Institute of Health between 2000 and 2014. Cases lacking participants' BMI data throughout the study were excluded, resulting in a final sample size of 3074. An increase or decrease in BMI was analyzed using PLINK, STRING, and DAVID, with significant differences observed in the AEN, ANKS1B, CSF1, EEF2K, FRAS1, GRIK4, PDGFC, THTPA, and TREH genes. These genes were observed to cluster with pathways related to type 2 diabetes, cardiovascular disease, metabolic processes, and endocytosis-related genes. These results suggest that several genes are involved in BMI changes and that several pathways are associated with obesity risk. Moreover, some genetic variants appear to influence BMI changes in Korean adults.

Resolving unsolved whole-genome sequencing data in paediatric neurological disorders: a cohort study

ObjectiveTo resolve unsolved whole-genome sequencing (WGS) data in individuals with paediatric neurological disorders.DesignA cohort study method using updated bioinformatic tools, new analysis targets, clinical information and literature databases was employed...

Overlooked poor-quality patient samples in sequencing data impair reproducibility of published clinically relevant datasets

BackgroundReproducibility is a major concern in biomedical studies, and existing publication guidelines do not solve the problem. Batch effects and quality imbalances between groups of biological samples are major factors hampering reproducibility. Yet, the latter is rarely considered in the scientific literature.ResultsOur analysis uses 40 clinically relevant RNA-seq datasets to quantify the impact of quality imbalance between groups of samples on the reproducibility of gene expression studies. High-quality imbalance is frequent (14 datasets; 35%), and hundreds of quality markers are present in more than 50% of the datasets. Enrichment analysis suggests common stress-driven effects among the low-quality samples and highlights a complementary role of transcription factors and miRNAs to regulate stress response. Preliminary ChIP-seq results show similar trends. Quality imbalance has an impact on the number of differential genes derived by comparing control to disease samples (the higher the imbalance, the higher the number of genes), on the proportion of quality markers in top differential genes (the higher the imbalance, the higher the proportion; up to 22%) and on the proportion of known disease genes in top differential genes (the higher the imbalance, the lower the proportion). We show that removing outliers based on their quality score improves the resulting downstream analysis.ConclusionsThanks to a stringent selection of well-designed datasets, we demonstrate that quality imbalance between groups of samples can significantly reduce the relevance of differential genes, consequently reducing reproducibility between studies. Appropriate experimental design and analysis methods can substantially reduce the problem.

Alzheimer's disease risk gene CD2AP is a dose-sensitive determinant of synaptic structure and plasticity.

CD2-Associated protein (CD2AP) is a candidate susceptibility gene for Alzheimer's disease, but its role in the mammalian central nervous system remains largely unknown. We show that CD2AP protein is broadly expressed in the adult mouse brain, including within cortical and hippocampal neurons, where it is detected at pre-synaptic terminals. Deletion of Cd2ap altered dendritic branching and spine density, and impaired ubiquitin-proteasome system activity. Moreover, in mice harboring either one or two copies of a germline Cd2ap null allele, we noted increased paired-pulse facilitation at hippocampal Schaffer-collateral synapses, consistent with a haploinsufficient requirement for pre-synaptic release. Whereas conditional Cd2ap knockout in the brain revealed no gross behavioral deficits in either 3.5- or 12-month-old mice, Cd2ap heterozygous mice demonstrated subtle impairments in discrimination learning using a touchscreen task. Based on unbiased proteomics, partial or complete loss of Cd2ap triggered perturbation of proteins with roles in protein folding, lipid metabolism, proteostasis, and synaptic function. Overall, our results reveal conserved, dose-sensitive requirements for CD2AP in the maintenance of neuronal structure and function, including synaptic homeostasis and plasticity, and inform our understanding of possible cell-type specific mechanisms in Alzheimer's Disease.

Bulk-RNA and single-nuclei RNA seq analyses reveal the role of lactate metabolism-related genes in Alzheimer's disease.

Dysfunctional lactate metabolism in the brain has been implicated in neuroinflammation, Aβ deposition, and cell disturbance, all of which play a significant role in the pathogenesis of Alzheimer's disease (AD). In this study, we aimed to investigate the lactate metabolism-related genes (LMRGs) in AD via an integrated bulk RNA and single-nuclei RNA sequencing (snRNA-seq) analysis, with a specific focus on microglia. We obtained 26 HC and 24 AD snRNA-seq samples originated from human prefrontal cortex in Gene Expression Omnibus (GEO) database and collected 873 LMRGs from three databases, namely MSigDB, The Human Protein Atlas and GeneCards. Bulk RNA was analyzed with LMRG characteristics in AD by using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), the protein-protein interaction (PPI), CytoHubba-MCC, Support Vector Machine (SVM) algorithms analyses. Then we conducted the Receiver Operating Characteristic (ROC) curve, correlation, and connection network analyses for biomarkers. Their differential expression validation was performed using AlzData database. The single-nuclei RNA analysis of microglia was applied to identify hub genes and pathways using cell-cell communication analysis and high dimensional Weighted Gene Co-Expression Network Analysis (hdWGCNA). Support Vector Machine (SVM) algorithm showed an AUC of 0.967, a sensitivity of 93.30% and a specificity of 100.00%. Our analysis identified biomarkers with LMRG characteristics, namely INSR, CDKL1, and PNISR. ROC analysis revealed that each of these biomarkers exhibited excellent diagnostic potential, as evidenced by their respective area under the curve (AUC) values: INSR (AUC: 0.679), CDKL1 (AUC: 0.788), and PNISR (AUC: 0.724). Correlation analysis showed that biomarkers exhibited a positive correlation with each other. Connection network illustrated their shared biological processes: aging, phosphorylation, metabolic process, and apoptosis. Cell-cell communication analysis revealed that GALECTIN signaling pathway was exclusively expressed in AD microglia, and only LGALS9 exhibited significant overexpression. HdWGCNA identified FTH1 as a hub gene enriched in ferroptosis and mineral absorption pathways within microglia. The roles of INSR, CDKL1, PNISR, LGALS9, and FTH1 should be taken into account to enhance our understanding of lactate metabolism in the context of AD.

Joint, multifaceted genomic analysis enables diagnosis of diverse, ultra-rare monogenic presentations.

Genomics for rare disease diagnosis has advanced at a rapid pace due to our ability to perform "N-of-1" analyses on individual patients with ultra-rare diseases. The increasing sizes of ultra-rare disease cohorts internationally newly enables cohort-wide analyses for new discoveries, but well-calibrated statistical genetics approaches for jointly analyzing these patients are still under development.1,2 The Undiagnosed Diseases Network (UDN) brings multiple clinical, research and experimental centers under the same umbrella across the United States to facilitate and scale N-of-1 analyses. Here, we present the first joint analysis of whole genome sequencing data of UDN patients across the network. We introduce new, well-calibrated statistical methods for prioritizing disease genes with de novo recurrence and compound heterozygosity. We also detect pathways enriched with candidate and known diagnostic genes. Our computational analysis, coupled with a systematic clinical review, recapitulated known diagnoses and revealed new disease associations. We further release a software package, RaMeDiES, enabling automated cross-analysis of deidentified sequenced cohorts for new diagnostic and research discoveries. Gene-level findings and variant-level information across the cohort are available in a public-facing browser (https://dbmi-bgm.github.io/udn-browser/). These results show that N-of-1 efforts should be supplemented by a joint genomic analysis across cohorts.

Molecular autopsy for fetal structural anomaly: diagnostic and clinical utility of multidisciplinary team approach.

In the West Midlands regional genetics service, cases of perinatal death with a possible genetic diagnosis are evaluated by the perinatal pathology genetic multidisciplinary team (MDT). The MDT assesses autopsy findings and suggests appropriate genomic assessment. The objective of this retrospective service evaluation was to determine the clinical utility of the MDT in assessing perinatal deaths associated with structural anomaly. This is the first evaluation since the introduction of whole-genome and whole-exome sequencing in routine clinical care. This was a retrospective service evaluation including all cases of perinatal death with an associated structural anomaly and suspected genetic etiology that underwent perinatal MDT assessment between January and December 2021. All cases received a full or partial postmortem examination and at least a chromosomal microarray analysis. Demographic characteristics, phenotype, genotype, MDT recommendations, diagnoses, outcomes and impact of postmortem analysis and genetic testing data were collected from patient case notes. Overall, 123 cases were discussed at the MDT meetings in 2021. Genetic evaluation was recommended in 84 cases and accepted in 64 cases. A range of genetic tests were requested according to indication and availability. Thirty diagnoses were made in 29 cases from 26 unrelated families. The diagnostic yield was 24% (29/123) in all cases or 45% (29/64) in cases with a suspected genetic diagnosis who underwent genetic testing. Postmortem examination provided clinically actionable phenotypic data in 79% of cases. A genetic diagnosis enabled accurate recurrence risk counseling and provision of appropriate follow-up, including prenatal testing and preimplantation diagnosis for patients with inherited conditions. Genomic testing was a clinically useful addition to (but not a substitute for) postmortem examination in cases of perinatal death associated with structural anomaly. The MDT approach helped assess cases and plan appropriate follow-up. Expedited whole-genome sequencing or panel-agnostic analysis were most appropriate for heterogeneous presentations. This broad approach can also expand knowledge of prenatal phenotypes and detect novel disease genes, and should be a priority in future research. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.

A practically efficient algorithm for identifying critical control proteins in directed probabilistic biological networks

Network controllability is unifying the traditional control theory with the structural network information rooted in many large-scale biological systems of interest, from intracellular networks in molecular biology to brain neuronal networks. In controllability approaches, the set of minimum driver nodes is not unique, and critical nodes are the most important control elements because they appear in all possible solution sets. On the other hand, a common but largely unexplored feature in network control approaches is the probabilistic failure of edges or the uncertainty in the determination of interactions between molecules. This is particularly true when directed probabilistic interactions are considered. Until now, no efficient algorithm existed to determine critical nodes in probabilistic directed networks. Here we present a probabilistic control model based on a minimum dominating set framework that integrates the probabilistic nature of directed edges between molecules and determines the critical control nodes that drive the entire network functionality. The proposed algorithm, combined with the developed mathematical tools, offers practical efficiency in determining critical control nodes in large probabilistic networks. The method is then applied to the human intracellular signal transduction network revealing that critical control nodes are associated with important biological features and perturbed sets of genes in human diseases, including SARS-CoV-2 target proteins and rare disorders. We believe that the proposed methodology can be useful to investigate multiple biological systems in which directed edges are probabilistic in nature, both in natural systems or when determined with large uncertainties in-silico.

Whole exome sequencing analyses identified novel genes for Alzheimer's disease and related dementia.

The heritability of Alzheimer's disease (AD) is estimated to be 58%-79%. However, known genes can only partially explain the heritability. Here, we conducted gene-based exome-wide association study (ExWAS) of rare variants and single-variant ExWAS of common variants, utilizing data of 54,569 clinically diagnosed/proxy AD and related dementia (ADRD) and 295,421 controls from the UK Biobank. Gene-based ExWAS identified 11 genes predicting a higher ADRD risk, including five novel ones, namely FRMD8, DDX1, DNMT3L, MORC1, and TGM2, along with six previously reported ones, SORL1, GRN, PSEN1, ABCA7, GBA, and ADAM10. Single-variant ExWAS identified two ADRD-associated novel genes, SLCO1C1 and NDNF. The identified genes were predominantly enriched in amyloid-β process pathways, microglia, and brain regions like hippocampus. The druggability evidence suggests that DDX1, DNMT3L, TGM2, SLCO1C1, and NDNF could be effective drug targets. Our study contributes to the current body of evidence on the genetic etiology of ADRD. Gene-based analyses of rare variants identified five novel genes for Alzheimer's disease and related dementia (ADRD), including FRMD8, DDX1, DNMT3L, MORC1, and TGM2. Single-variant analyses of common variants identified two novel genes for ADRD, including SLCO1C1 and NDNF. The identified genes were predominantly enriched in amyloid-β process pathways, microglia, and brain regions like hippocampus. DDX1, DNMT3L, TGM2, SLCO1C1, and NDNF could be effective drug targets.

How exome sequencing improves the diagnostics and management of men with non-syndromic infertility.

Male infertility affects approximately 17% of all men and represents a complex disorder in which not only semen parameters such as sperm motility, morphology, and number of sperm are highly variable, but also testicular phenotypes range from normal spermatogenesis to complete absence of germ cells. Genetic factors significantly contribute to the disease but chromosomal aberrations, mostly Klinefelter syndrome, and microdeletions of the Y-chromosome have remained the only diagnostically and clinically considered genetic causes. Monogenic causes remain understudied and, thus, often unidentified, leaving the majority of the male factor couple infertility pathomechanistically unexplained. This has been changing mostly because of the introduction of exome sequencing that allows the analysis of multiple genes in large patient cohorts. As a result, pathogenic variants in single genes have been associated with non-syndromic forms of all aetiologic sub-categories in the last decade. This review highlights the contribution of exome sequencing to the identification of novel disease genes for isolated (non-syndromic) male infertility by presenting the results of a comprehensive literature search. Both, reduced sperm count in azoospermic and oligozoospermic patients, and impaired sperm motility and/or morphology, in asthenozoospermic and/or teratozoospermic patients are highly heterogeneous diseases with well over 100 different candidate genes described for each entity. Applying the standardized evaluation criteria of the ClinGen gene curation working group, 70 genes with at least moderate evidence to contribute to the disease are highlighted. The implementation of these valid disease genes in clinical exome sequencing is important to increase the diagnostic yield in male infertility and, thus, improve clinical decision-making and appropriate genetic counseling. Future advances in androgenetics will continue to depend on large-scale exome and genome sequencing studies of comprehensive international patient cohorts, which are the most promising approaches to identify additional disease genes and provide reliable data on the gene-disease relationship.

The Molecular Landscape of Premature Aging Diseases Defined by Multilayer Network Exploration.

Premature Aging (PA) diseases are rare genetic disorders that mimic some aspects of physiological aging at an early age. Various causative genes of PA diseases have been identified in recent years, providing insights into some dysfunctional cellular processes. However, the identification of PA genes also revealed significant genetic heterogeneity and highlighted the gaps in this understanding of PA-associated molecular mechanisms. Furthermore, many patients remain undiagnosed. Overall, the current lack of knowledge about PA diseases hinders the development of effective diagnosis and therapies and poses significant challenges to improving patientcare. Here, a network-based approach to systematically unravel the cellular functions disrupted in PA diseases is presented. Leveraging a network community identification algorithm, it is delved into a vast multilayer network of biological interactions to extract the communities of 67 PA diseases from their 132 associated genes. It is found that these communities can be grouped into six distinct clusters, each reflecting specific cellular functions: DNA repair, cell cycle, transcription regulation, inflammation, cell communication, and vesicle-mediated transport. That these clusters collectively represent the landscape of the molecular mechanisms that are perturbed in PA diseases, providing a framework for better understanding their pathogenesis is proposed. Intriguingly, most clusters also exhibited a significant enrichment in genes associated with physiological aging, suggesting a potential overlap between the molecular underpinnings of PA diseases and natural aging.

Advances in Gene and Cellular Therapeutic Approaches for Huntington's Disease.

Huntington's disease (HD) is an inherited neurodegenerative disorder caused by the abnormal expansion of CAG trinucleotide repeats in the Huntingtin gene (HTT) located on chromosome 4. It is transmitted in an autosomal dominant manner and is characterized by motor dysfunction, cognitive decline, and emotional disturbances. To date, there are no curative treatments for HD have been developed; current therapeutic approaches focus on symptom relief and comprehensive care through coordinated pharmacological and non-pharmacological methods to manage the diverse phenotypes of the disease. International clinical guidelines for the treatment of HD are continually being revised in an effort to enhance care within a multidisciplinary framework. Additionally, innovative gene and cell therapy strategies are being actively researched and developed to address the complexities of the disorder and improve treatment outcomes. This review endeavours to elucidate the current and emerging gene and cell therapy strategies for HD, offering a detailed insight into the complexities of the disorder and looking forward to future treatment paradigms. Considering the complexity of the underlying mechanisms driving HD, a synergistic treatment strategy that integrates various factors-such as distinct cell types, epigenetic patterns, genetic components, and methods to improve the cerebral microenvironment-may significantly enhance therapeutic outcomes. In the future, we eagerly anticipate ongoing innovations in interdisciplinary research that will bring profound advancements and refinements in the treatment of HD.

Parkinson’s disease gene, Synaptojanin1, dysregulates the surface maintenance of the dopamine transporter

Missense mutations of PARK20/SYNJ1 (synaptojanin1/Synj1) were found in complex forms of familial Parkinsonism. However, the Synj1-regulated molecular and cellular changes associated with dopaminergic dysfunction remain unknown. We now report a fast depletion of evoked dopamine and impaired maintenance of the axonal dopamine transporter (DAT) in the Synj1 haploinsufficient (Synj1+/−) neurons. While Synj1 has been traditionally known to facilitate the endocytosis of synaptic vesicles, we provide in vitro and in vivo evidence demonstrating that Synj1 haploinsufficiency results in an increase of total DAT but a reduction of the surface DAT. Synj1+/− neurons exhibit maladaptive DAT trafficking, which could contribute to the altered DA release. We showed that the loss of surface DAT is associated with the impaired 5’-phosphatase activity and the hyperactive PI(4,5)P2–PKCβ pathway downstream of Synj1 deficiency. Thus, our findings provided important mechanistic insight for Synj1-regulated DAT trafficking integral to dysfunctional DA signaling, which might be relevant to early Parkinsonism.

Phenotype Distinctions in Mice Deficient in the Neuron-Specific α3 Subunit of Na,K-ATPase: Atp1a3tm1Ling/+ and Atp1a3 +/D801Y.

ATP1A3 is a Na,K-ATPase gene expressed specifically in neurons in the brain. Human mutations are dominant and produce an unusually wide spectrum of neurological phenotypes, most notably rapid-onset dystonia parkinsonism (RDP) and alternating hemiplegia of childhood (AHC). Here we compared heterozygotes of two mouse lines, a line with little or no expression (Atp1a3tm1Ling/+) and a knock-in expressing p.Asp801Tyr (D801Y, Atp1a3 +/D801Y). Both mouse lines had normal lifespans, but Atp1a3 +/D801Y had mild perinatal mortality contrasting with D801N mice (Atp1a3 +/D801N), which had high mortality. The phenotypes of Atp1a3tm1Ling/+ and Atp1a3 +/D801Y were different, and testing of each strain was tailored to its symptom range. Atp1a3tm1Ling/+ mice displayed little at baseline, but repeated ethanol intoxication produced hyperkinetic motor abnormalities not seen in littermate controls. Atp1a3 +/D801Y mice displayed robust phenotypes: hyperactivity, diminished posture consistent with hypotonia, and deficiencies in beam walk and wire hang tests. Symptoms also included qualitative motor abnormalities that are not well quantified by conventional tests. Paradoxically, Atp1a3 +/D801Y showed sustained better performance than wild type on the accelerating rotarod. Atp1a3 +/D801Y mice were overactive in forced swimming and afterward had intense shivering, transient dystonic postures, and delayed recovery. Remarkably, Atp1a3 +/D801Y mice were refractory to ketamine anesthesia, which elicited hyperactivity and dyskinesia even at higher dose. Neither mouse line exhibited fixed dystonia (typical of RDP patients), spontaneous paroxysmal weakness (typical of AHC patients), or seizures but had consistent, measurable neurological abnormalities. A gradient of variation supports the importance of studying multiple Atp1a3 mutations in animal models to understand the roles of this gene in human disease.

Whole-exome and whole-genome sequencing of 1064 individuals with type 1 diabetes reveals novel genes for diabetic kidney disease

Aims/hypothesisDiabetic kidney disease (DKD) is a severe diabetic complication that affects one third of individuals with type 1 diabetes. Although several genes and common variants have been shown to be associated with DKD, much of the predicted inheritance remains unexplained. Here, we performed next-generation sequencing to assess whether low-frequency variants, extending to a minor allele frequency (MAF) ≤10% (single or aggregated) contribute to the missing heritability in DKD.MethodsWe performed whole-exome sequencing (WES) of 498 individuals and whole-genome sequencing (WGS) of 599 individuals with type 1 diabetes. After quality control, next-generation sequencing data were available for a total of 1064 individuals, of whom 541 had developed either severe albuminuria or end-stage kidney disease, and 523 had retained normal albumin excretion despite a long duration of type 1 diabetes. Single-variant and gene-aggregate tests for protein-altering variants (PAV) and protein-truncating variants (PTV) were performed separately for WES and WGS data and combined in a meta-analysis. We also performed genome-wide aggregate analyses on genomic windows (sliding window), promoters and enhancers using the WGS dataset.ResultsIn the single-variant meta-analysis, no variant reached genome-wide significance, but a suggestively associated common THAP7 rs369250 variant (p=1.50 × 10−5, MAF=49%) was replicated in the FinnGen general population genome-wide association study (GWAS) data for chronic kidney disease and DKD phenotypes. The gene-aggregate meta-analysis provided suggestive evidence (p<4.0 × 10−4) at four genes for DKD, of which NAT16 (MAFPAV≤10%) and LTA (also known as TNFβ, MAFPAV≤5%) are replicated in the FinnGen general population GWAS data. The LTA rs2229092 C allele was associated with significantly lower TNFR1, TNFR2 and TNFR3 serum levels in a subset of FinnDiane participants. Of the intergenic regions suggestively associated with DKD, the enhancer on chromosome 18q12.3 (p=3.94 × 10−5, MAFvariants≤5%) showed interaction with the METTL4 gene; the lead variant was replicated, and predicted to alter binding of the MafB transcription factor.Conclusions/interpretationOur sequencing-based meta-analysis revealed multiple genes, variants and regulatory regions that were suggestively associated with DKD. However, as no variant or gene reached genome-wide significance, further studies are needed to validate the findings.Graphical

Prevalence and Clinical Characteristics of Heterozygous RNF213 p.Arg4810Lys Variant Carriers Diagnosed With Chronic Thromboembolic Pulmonary Hypertension.

Ring finger protein 213 (RNF213) p.Arg4810Lys is a susceptibility gene for moyamoya disease, peripheral pulmonary artery stenosis (PPS), and other vascular diseases and thrombosis. We investigated the prevalence and clinical characteristics of RNF213 variant carriers diagnosed with chronic thromboembolic pulmonary hypertension (CTEPH). We retrospectively analyzed the prevalence of the RNF213 p.Arg4810Lys variant in patients diagnosed with CTEPH (n=112) and PPS (n=10). Clinical and angiographic characteristics were evaluated between RNF213 variant carriers diagnosed with CTEPH and noncarriers with CTEPH and homozygous variant carriers with PPS. Eight heterozygous RNF213 p.Arg4810Lys variant carriers (7.1%) were identified among patients diagnosed with CTEPH, while 5 patients with PPS (50%) carried the homozygous variant. The clinical characteristics of heterozygous variant carriers with CTEPH were not remarkably different from those of noncarriers with CTEPH. All heterozygous variant carriers with CTEPH showed webs/bands lesions at the segmental/subsegmental level, with 75% showing distal tortuous vessels. None of the heterozygous variant carriers with CTEPH exhibited the string-of-beads pattern or elongated stenosis. Homozygous variant carriers with PPS showed the string-of-beads pattern, elongated stenosis, and distal tortuous vessels without webs/bands lesions. A subset of patients diagnosed with CTEPH (7.1%) carried the heterozygous RNF213 p.Arg4810Lys variant. Clinical and angiographic characteristics of heterozygous variant carriers were not remarkably different from those of noncarriers of CTEPH. However, both heterozygous variant carriers with CTEPH and homozygous variant carriers with PPS showed tortuous vessels on angiography.

Non-linear transcriptional responses to gradual modulation of transcription factor dosage.

Genomic loci associated with common traits and diseases are typically non-coding and likely impact gene expression, sometimes coinciding with rare loss-of-function variants in the target gene. However, our understanding of how gradual changes in gene dosage affect molecular, cellular, and organismal traits is currently limited. To address this gap, we induced gradual changes in gene expression of four genes using CRISPR activation and inactivation. Downstream transcriptional consequences of dosage modulation of three master trans-regulators associated with blood cell traits (GFI1B, NFE2, and MYB) were examined using targeted single-cell multimodal sequencing. We showed that guide tiling around the TSS is the most effective way to modulate cis gene expression across a wide range of fold-changes, with further effects from chromatin accessibility and histone marks that differ between the inhibition and activation systems. Our single-cell data allowed us to precisely detect subtle to large gene expression changes in dozens of trans genes, revealing that many responses to dosage changes of these three TFs are non-linear, including non-monotonic behaviours, even when constraining the fold-changes of the master regulators to a copy number gain or loss. We found that the dosage properties are linked to gene constraint and that some of these non-linear responses are enriched for disease and GWAS genes. Overall, our study provides a straightforward and scalable method to precisely modulate gene expression and gain insights into its downstream consequences at high resolution.

Exploration of the Mechanisms of Bu-Yang-Huan-Wu Decoction in the Treatment of Diabetic Peripheral Neuropathy by Integrating of Serum Pharmacochemistry and Network Pharmacology.

Diabetic peripheral neuropathy (DPN) is a significant and frequent complication of diabetes. Bu-Yang-Huan-Wu Decoction (BHD) is a classic traditional Chinese herbal prescription that is commonly used in modern clinical practice for the effective treatment of DPN, but the underlying mechanism is not yet clearly defined. The chemical constituents of BHD were characterized by UPLC-Q-Orbitrap HR MS/MS, and a total of 101 chemical components were identified, including 30 components absorbed into blood. An interaction network of "compound-target-disease" interactions was constructed based on the compounds detected absorbed in blood and their corresponding targets of diabetic neuropathy acquired from disease gene databases, and the possible biological targets and potential signalling pathways of BHD were predicted via network pharmacology analysis. Subsequently, methylglyoxal-induced (MGO-induced) Schwann cells (SCs) were used to identify the active ingredients in blood components of BHD and verify the molecular mechanisms of BHD. Through network topological analysis, 30 shared targets strongly implicated in the anti-DPN effects of BHD were identifed. Combined network pharmacology and in vitro cellular analysis, we found that the active ingredient of BHD may treat DPN by modulating the AGEs/RAGE pathway. This study provides valuable evidence for future mechanistic studies and potential therapeutic applications for patients with DPN.