HGG Advances最新文献

Monocarboxylate transporter 8 (MCT8) deficiency is a rare, X-linked condition caused by pathogenic variants in the SLC16A2 gene, resulting in dysfunctional thyroid hormone transport throughout the body. Human Phenotype Ontology (HPO) terms provide a standardized clinical vocabulary of symptomology in human disease. Here, we contribute a cohort of individuals with fully categorized SLC16A2 variants and associated HPO terms to the phenotypic spectrum of MCT8 deficiency. We queried de-identified genetic data for SLC16A2 variants mostly determined through exome sequencing. Clinical abstraction of medical records was performed to generate HPO terms. In a cohort of 122 individuals with SLC16A2 variants, we identified 68 cases with likely pathogenic/pathogenic (L/PATH) variants and 54 individuals with variants of uncertain significance (VUSs). A total of 611 different HPO terms were retrieved for 108 individuals with characterized SLC16A2 variants. Common HPO terms included global developmental delay (79/108, 73.1%), generalized hypotonia (40/108, 37.0%), and delayed speech and language development (29/108, 26.9%). Some HPO terms associated with a severe MCT8 deficiency phenotype, such as failure to thrive, feeding difficulties, and delayed myelination, were more common in individuals with L/PATH variants than in those with VUSs. HPO terms related to thyroid function and/or hormone levels were not commonly reported, with hypothyroidism the most frequently reported term, seen in six individuals. This study highlights the utility of comprehensive genetic testing and standardized clinical vocabulary in diagnosing rare genetic conditions. In MCT8 deficiency, this approach can help characterize genotype-phenotype correlations, expedite concurrent thyroid hormone testing, and improve affected individual and caregiver support.

Mendelian histonopathies are rare neurodevelopmental disorders (NDDs) caused by germline variants in histone-encoding genes. Here, we perform a more expansive pan-histonopathy interrogation than previously possible. We analyze data from 192 individuals affected by histonopathies. This analysis includes representation of the 185 published individuals with HIST1H1E syndrome, Bryant-Li-Bhoj syndrome, and Tessadori-Bicknell-van Haaften NDD; as well as from seven unpublished individuals, five of whom harbor variants in genes not previously associated with disease (HIST1H2AL/H2AC16, H2AFZ/H2AZ1, HIST1H3D/H3C4, and HIST3H3/H3-4). By intersecting clinician-reported phenotypic data with next-generation phenotyping of published 2D facial photographs (n = 98), we sought to address the lack of established craniofacial gestalts or characteristic phenotypic patterns for this community. While these analyses may suggest a histone core versus linker protein basis of delineation, they more strikingly highlight data gaps that confound the identification of phenotypic patterns at this time. Based on this, we developed an updated standardized clinical survey, which allowed us to identify the second known individual with a germline histonopathy and a cancer diagnosis. Notably, the community-wide cancer incidence is currently 1%, which falls below the recommended 5% cut off for routine surveillance. Ultimately, this work highlights the ways in which histonopathy-associated phenotypes change throughout the lifespan, necessitating longitudinal re-evaluation; that every identified individual shapes our understanding of these syndromes in a way that improves care for this community; and the value of ongoing translational work to address the outstanding question of cancer predisposition for individuals living with germline histonopathies.

We report two rare homozygous variants, including a recurrent missense and intronic variant, in the EIF3K gene in four unrelated individuals with global developmental delay, microcephaly, proportionate short stature, dysmorphic craniofacial features, digit flexion deformities, and the cardiac anomaly, patent ductus arteriosus. Three individuals, who were all of Puerto Rican descent, were homozygous for the NM_013234.3:c.128A>G; p.(Asp43Gly) variant in EIF3K and homozygous for a missense variant in SYNE4 (NM_001039876.2:c.355C>T; p.(Arg119Trp)). SYNE4 is associated with autosomal recessive bilateral sensorineural hearing loss, which was also reported in these probands. Analysis of our dataset confirmed these EIF3K and SYNE4 variants were in linkage disequilibrium in affected individuals, suggesting a possible common ancestor and founder event. A fourth individual from Egypt harbored the homozygous intronic variant c.355-13A>G in EIF3K, which segregated with the phenotype in the family and led to aberrant splicing of EIF3K pre-mRNAs, as shown by insertion of 12 intronic base pairs, skipping of 2 exons, and significantly reduced EIF3K protein levels in skin fibroblasts. Through genetic and functional approaches, we suggest that biallelic EIF3K variants are associated with an autosomal recessive syndromic neurodevelopmental disorder with growth retardation, microcephaly, congenital heart defect, and other anomalies.

Chromosomal abnormalities in human pre-implantation embryos, originating from either meiotic or mitotic errors, present a significant challenge in reproductive biology. Complete aneuploidy is primarily linked to errors during the resumption of meiosis in oocyte maturation, which increase with maternal age, while mosaic aneuploidies result from mitotic errors after fertilization. The biological causes of these abnormalities are increasingly becoming a topic of interest for research groups and clinical specialists. This review explores the intricate processes of meiotic and early mitotic divisions in embryos, shedding light on the mechanisms that lead to changes in chromosome number in daughter cells. Key factors in meiotic division include difficulties in spindle assembly without centrosomes, kinetochore (KT) orientation disturbances, and inefficient cell-cycle checkpoints. The weakening of cohesion molecules that bind chromosomes, exacerbated by maternal aging, further complicates chromosomal segregation. Mitotic errors in early development are influenced by defects in sperm centrosomes, KT misalignment, and the gradual depletion of maternal regulatory factors. Coupled with the inactive or partially active embryonic genome, this depletion increases the likelihood of chromosomal aberrations. While various theoretical mechanisms for these abnormalities exist, current data remain insufficient to determine their exact contributions. Continued research is essential to unravel these complex processes and improve outcomes in assisted reproductive technologies.

Mendelian randomization (MR) is a widely used method for assessing causal relationships between risk factors and outcomes using genetic variants as instrumental variables (IVs). While traditional MR assumes uni-directional causality, bi-directional MR aims to identify the true causal direction. In uni-directional MR, invalid IVs due to pleiotropy can violate assumptions and introduce biases. In bi-directional MR, traditional MR can be performed separately for each direction, but the presence of invalid IVs poses even greater challenges. We introduce a new bi-directional MR method incorporating stepwise selection (Bidir-SW) designed to address these challenges. Our approach leverages public genome-wide association study (GWAS) datasets for two traits and uses model selection criteria to identify invalid IVs iteratively by stepwise selection. This method accounts for potential bi-directional causality in the presence of common invalid IVs for both directions, even if only GWAS summary statistics are provided. Through simulation studies, we demonstrate that our method outperforms traditional MR techniques, such as MR-Egger and inverse-variance weighted (IVW), with uncorrelated SNPs. We also provide simulations to compare our approach with existing transcriptome-wide association study (TWAS) to show its effectiveness. Finally, we apply the proposed method to genetic traits such as CRP levels and BMI to explore possible bi-directional relationships among these traits. We also used the proposed method to discover causal protein biomarkers. Our findings suggest that the Bidir-SW approach is a powerful tool for bi-directional MR or TWAS, which can provide a valuable framework for future genetic epidemiology studies.

Trzupek et al. describe a rare disease Open Science Data Challenge, using data collected systematically on RARE-X across 27 neurodevelopmental disorders. Clinical diagnoses, symptoms, genetic data, and PROs were included. Researchers and statisticians generated solutions that identified previously underappreciated symptoms and used machine learning to test predictive models for diagnosis.

Heterozygous pathogenic variants in the Mediator complex subunit 13-like gene located in the locus 12q21.21 (MED13L) are associated with intellectual disability, developmental delay, and distinctive facial features. While nonsense and frameshift variants typically cause haploinsufficiency, resulting in a well-characterized clinical presentation, missense variants have been associated with a broader range of phenotypes, including epilepsy and severe motor delay. In this study, we investigated five pathogenic missense variants in MED13L-c.2597C>T p.Pro866Leu, c.2605C>T p.Pro869Ser, c.3392G>A p.Cys1131Tyr, c.5695G>A p.Gly1899Arg, and c.6485C>T p.Thr2162Met-associated with different clinical severities. We identified significant reductions in protein stability across these variants, with some exhibiting aberrant cytoplasmic localization, suggesting disruptions in structural integrity and function. In particular, exon 15 variants (p.Pro866Leu and p.Pro869Ser) correlated with severe phenotypes, including epilepsy and severe motor impairment, whereas p.Gly1899Arg and p.Thr2162Met were associated with milder manifestations. 3D protein modeling suggested that these missense variants may disrupt MED13L's interaction with the CDK8 kinase module, leading to functional deficits. Our findings highlight different pathogenic mechanisms, ranging from protein instability to altered molecular interactions, that contribute to the clinical variability observed in MED13L-related disorders.

Spatial transcriptomics (ST) data provide spatially informed gene expression profiles. However, power is limited for spatially informed differential gene expression (DGE) of complex diseases such as Alzheimer disease (AD), due to small sample sizes of ST data. Conversely, single-nucleus RNA sequencing (snRNA-seq) data offer larger sample sizes for cell-type-specific (CTS) analyses but lack spatial information. Here, we integrated ST and snRNA-seq data to enhance the power of spatially informed CTS DGE analysis of AD-related phenotypes. We first utilized the CeLEry tool to infer six cortical layers of ∼1.5 million cells in the snRNA-seq data that were profiled from the dorsolateral prefrontal cortex (DLPFC) tissue of 436 postmortem brains. Then, we conducted cortical layer- and cell-type-specific (LCS) and CTS DGE analyses based on the linear mixed model, for β-amyloid, tangle density, and cognitive decline. We identified 138 LCS significant genes with false discovery rate (FDR) q <0.05, including 103 for β-amyloid, 24 for tangle density, and 25 for cognitive decline. The majority of these LCS significant genes, including known AD risk genes such as APOE, KCNIP3, and CTSD, cannot be detected by CTS analyses. We also identified 2 genes shared across all 3 phenotypes and 10 shared between 2 phenotypes. Gene set enrichment analyses with the LCS DGE results of microglia in cortical layer 6 of β-amyloid identified 12 significant AD-related pathways. In conclusion, incorporating spatial information with snRNA-seq data enhanced the power of spatially informed DGE analyses. These identified LCS significant genes not only help illustrate the pathogenesis of AD but they also provide potential targets for developing therapeutics of AD.

Calcific aortic valve stenosis (CAVS) is the most frequent heart valve disease. Elucidating specific gene expression patterns in the aortic valve could provide new insights for understanding disease pathophysiology. We used local RNA sequencing data from 500 explanted human aortic valves to identify aortic valve-specific genes and compared their expression according to disease status and CAVS severity. We identified 100 specific protein-coding genes in the aortic valve compared to 45 other tissues from the Genotype-Tissue Expression (GTEx) project. Among them, 38 were differentially expressed in CAVS. Ten had a gradient of expression between severity levels and were central in a protein-protein interaction network, most of which were involved in extracellular matrix regulation or inflammation. Among the aortic valve-specific genes, four of the corresponding proteins had a significantly different plasma level in individuals with CAVS. These findings represent a robust foundation for the development of specific biomarkers and therapies for CAVS.

Fish oil supplements (FOS) are known to alter circulating levels of polyunsaturated fatty acids (PUFAs) but in a heterogeneous manner across individuals. These varied responses may result from unidentified gene-FOS interactions. To identify genetic factors that interact with FOS to alter the circulating levels of PUFAs, we performed a multi-level genome-wide interaction study (GWIS) of FOS on 14 plasma measurements in 200,060 unrelated European-ancestry individuals from the UK Biobank. From our single-variant tests, we identified genome-wide significant interacting SNPs (p < 5 × 10^-8) in the FADS1-FADS2 gene cluster for total omega-3, omega-3%, docosapentaenoic acid (DHA), DHA%, and the omega-6 to omega-3 ratio. Among the interaction signals for omega-3%, the lead SNP, rs35473591 (C>CT, CT allele frequency = 0.34), had a lower association effect size in the FOS-taking group (β = 0.35 for allele C) than that in the group without FOS (β = 0.42). Likewise, the effect sizes of associations between FOS and omega-3% varied across the three genotype groups (β = 0.45, 0.50, and 0.59, respectively, in C/C, C/CT, and CT/CT). Our gene-level aggregate and transcriptome-wide interaction analyses identified significant signals at two loci around FADS1-FADS2 and GPR12. The contribution of genome-wide gene-FOS interactions to phenotypic variance was statistically significant in omega-3-related traits. This systematic gene-FOS GWIS contributes to our understanding of the genetic architecture of circulating PUFAs underlying FOS response and informs personalized dietary recommendations.