American journal of human genetics最新文献

The secreted mucins MUC5AC and MUC5B are large glycoproteins that play critical defensive roles in pathogen entrapment and mucociliary clearance. Their respective genes contain polymorphic and degenerate protein-coding variable number tandem repeats (VNTRs) that make the loci difficult to investigate with short reads. We characterize the structural diversity of MUC5AC and MUC5B by long-read sequencing and assembly of 206 human and 20 nonhuman primate (NHP) haplotypes. We find that human MUC5B is largely invariant (5,761-5,762 amino acids [aa]); however, seven haplotypes have expanded VNTRs (6,291-7,019 aa). In contrast, 30 allelic variants of MUC5AC encode 16 distinct proteins (5,249-6,325 aa) with cysteine-rich domain and VNTR copy-number variation. We group MUC5AC alleles into three phylogenetic clades: H1 (46%, ∼5,654 aa), H2 (33%, ∼5,742 aa), and H3 (7%, ∼6,325 aa). The two most common human MUC5AC variants are smaller than NHP gene models, suggesting a reduction in protein length during recent human evolution. Linkage disequilibrium and Tajima's D analyses reveal that East Asians carry exceptionally large blocks with an excess of rare variation (p < 0.05) at MUC5AC. To validate this result, we use Locityper for genotyping MUC5AC haplogroups in 2,600 unrelated samples from the 1000 Genomes Project. We observe a signature of positive selection in H1 among East Asians and a depletion of the likely ancestral haplogroup (H3). In Europeans, H3 alleles show an excess of common variation and deviate from Hardy-Weinberg equilibrium (p < 0.05), consistent with heterozygote advantage and balancing selection. This study provides a generalizable strategy to characterize complex protein-coding VNTRs for improved disease associations.

Recurrent copy-number variation represents one of the most well-established genetic drivers in neurodevelopmental disorders, including autism spectrum disorder. Duplication of 15q11-q13 (dup15q) is a well-described neurodevelopmental syndrome that increases the risk of autism more than 40-fold. However, the effects of this duplication on gene expression and chromatin accessibility in specific cell types in the human brain remain unknown. To identify the cell-type-specific transcriptional and epigenetic effects of dup15q in the human frontal cortex, we conducted single-nucleus RNA sequencing and multi-omic sequencing on dup15q-affected individuals (n = 6) as well as individuals with non-dup15q autism (n = 7) and neurotypical control individuals (n = 7). Cell-type-specific differential expression analysis identified significantly regulated genes, critical biological pathways, and differentially accessible genomic regions. Although there was overall increased gene expression across the duplicated genomic region, cellular identity represented an important factor mediating gene-expression changes. As compared to other cell types, neuronal subtypes showed greater upregulation of gene expression across a critical region within the duplication. Genes that fell within the duplicated region and had high baseline expression in control individuals showed only modest changes in dup15q, regardless of cell type. Of note, dup15q and autism had largely distinct signatures of chromatin accessibility but shared the majority of transcriptional regulatory motifs, suggesting convergent biological pathways. However, the transcriptional binding-factor motifs implicated in each condition implicated distinct biological mechanisms: neuronal JUN and FOS networks in autism vs. an inflammatory transcriptional network in dup15q microglia. This work provides a cell-type-specific analysis of how dup15q changes gene expression and chromatin accessibility in the human brain, and it finds evidence of marked cell-type-specific effects of this genetic driver. These findings have implications for guiding therapeutic development in dup15q syndrome, as well as understanding the functional effects of copy-number variants more broadly in neurodevelopmental disorders.

The term "recurrent constellations of embryonic malformations" (RCEM) is used to describe a number of multiple malformation associations that affect three or more body structures. The causes of these disorders are currently unknown, and no diagnostic marker has been identified. Consequently, providing a definitive diagnosis in suspected individuals is challenging. In this study, genome-wide DNA methylation analysis was conducted on DNA samples obtained from the peripheral blood of 53 individuals with RCEM characterized by clinical features recognized as VACTERL and/or oculoauriculovertebral spectrum association. We identified a common DNA methylation episignature in 40 out of the 53 individuals. Subsequently, a sensitive and specific binary classifier was developed based on the DNA methylation episignature. This classifier can facilitate the use of RCEM episignature as a diagnostic biomarker in a clinical setting. The study also investigated the functional correlation of RCEM DNA methylation relative to other genetic disorders with known episignatures, highlighting the common genomic regulatory pathways involved in the pathophysiology of RCEM.

Recent studies have highlighted the essential role of RNA splicing, a key mechanism of alternative RNA processing, in establishing connections between genetic variations and disease. Genetic loci influencing RNA splicing variations show considerable influence on complex traits, possibly surpassing those affecting total gene expression. Dysregulated RNA splicing has emerged as a major potential contributor to neurological and psychiatric disorders, likely due to the exceptionally high prevalence of alternatively spliced genes in the human brain. Nevertheless, establishing direct associations between genetically altered splicing and complex traits has remained an enduring challenge. We introduce Spliced-Transcriptome-Wide Associations (SpliTWAS) to integrate alternative splicing information with genome-wide association studies to pinpoint genes linked to traits through exon splicing events. We applied SpliTWAS to two schizophrenia (SCZ) RNA-sequencing datasets, BrainGVEX and CommonMind, revealing 137 and 88 trait-associated exons (in 84 and 67 genes), respectively. Enriched biological functions in the associated gene sets converged on neuronal function and development, immune cell activation, and cellular transport, which are highly relevant to SCZ. SpliTWAS variants impacted RNA-binding protein binding sites, revealing potential disruption of RNA-protein interactions affecting splicing. We extended the probabilistic fine-mapping method FOCUS to the exon level, identifying 36 genes and 48 exons as putatively causal for SCZ. We highlight VPS45 and APOPT1, where splicing of specific exons was associated with disease risk, eluding detection by conventional gene expression analysis. Collectively, this study supports the substantial role of alternative splicing in shaping the genetic basis of SCZ, providing a valuable approach for future investigations in this area.

Implementation of genomic medicine into healthcare requires a workforce educated through effective educational approaches. However, ascertaining the impact of genomics education activities or resources is limited by a lack of evaluation and inconsistent descriptions in the literature. We aim to support those developing genomics education to consider how best to capture evaluation data that demonstrate program outcomes and effectiveness within scope. Here, we present an evaluation framework that is adaptable to multiple settings for use by genomics educators with or without education or evaluation backgrounds. The framework was developed as part of a broader program supporting genomic research translation coordinated by the Australian Genomics consortium. We detail our mixed-methods approach involving an expert workshop, literature review and iterative expert input to reach consensus and synthesis of a new evaluation framework for genomics education. The resulting theory-informed and evidence-based framework encompasses evaluation across all stages of education program development, implementation and reporting, and acknowledges the critical role of stakeholders and the effects of external influences.

Trithorax-related H3K4 methyltransferases, KMT2C and KMT2D, are critical epigenetic modifiers. Haploinsufficiency of KMT2C was only recently recognized as a cause of neurodevelopmental disorder (NDD), so the clinical and molecular spectrums of the KMT2C-related NDD (now designated as Kleefstra syndrome 2) are largely unknown. We ascertained 98 individuals with rare KMT2C variants, including 75 with protein-truncating variants (PTVs). Notably, ∼15% of KMT2C PTVs were inherited. Although the most highly expressed KMT2C transcript consists of only the last four exons, pathogenic PTVs were found in almost all the exons of this large gene. KMT2C variant interpretation can be challenging due to segmental duplications and clonal hematopoesis-induced artifacts. Using samples from 27 affected individuals, divided into discovery and validation cohorts, we generated a moderate strength disorder-specific KMT2C DNA methylation (DNAm) signature and demonstrate its utility in classifying non-truncating variants. Based on 81 individuals with pathogenic/likely pathogenic variants, we demonstrate that the KMT2C-related NDD is characterized by developmental delay, intellectual disability, behavioral and psychiatric problems, hypotonia, seizures, short stature, and other comorbidities. The facial module of PhenoScore, applied to photographs of 34 affected individuals, reveals that the KMT2C-related facial gestalt is significantly different from the general NDD population. Finally, using PhenoScore and DNAm signatures, we demonstrate that the KMT2C-related NDD is clinically and epigenetically distinct from Kleefstra and Kabuki syndromes. Overall, we define the clinical features, molecular spectrum, and DNAm signature of the KMT2C-related NDD and demonstrate they are distinct from Kleefstra and Kabuki syndromes highlighting the need to rename this condition.

The shift to a genotype-first approach in genetic diagnostics has revolutionized our understanding of neurodevelopmental disorders, expanding both their molecular and phenotypic spectra. Kleefstra syndrome (KLEFS1) is caused by EHMT1 haploinsufficiency and exhibits broad clinical manifestations. EHMT1 encodes euchromatic histone methyltransferase-1-a pivotal component of the epigenetic machinery. We have recruited 209 individuals with a rare EHMT1 variant and performed comprehensive molecular in silico and in vitro testing alongside DNA methylation (DNAm) signature analysis for the identified variants. We (re)classified the variants as likely pathogenic/pathogenic (molecularly confirming Kleefstra syndrome) in 191 individuals. We provide an updated and broader clinical and molecular spectrum of Kleefstra syndrome, including individuals with normal intelligence and familial occurrence. Analysis of the EHMT1 variants reveals a broad range of molecular effects and their associated phenotypes, including distinct genotype-phenotype associations. Notably, we showed that disruption of the "reader" function of the ankyrin repeat domain by a protein altering variant (PAV) results in a KLEFS1-specific DNAm signature and milder phenotype, while disruption of only "writer" methyltransferase activity of the SET domain does not result in KLEFS1 DNAm signature or typical KLEFS1 phenotype. Similarly, N-terminal truncating variants result in a mild phenotype without the DNAm signature. We demonstrate how comprehensive variant analysis can provide insights into pathogenesis of the disorder and DNAm signature. In summary, this study presents a comprehensive overview of KLEFS1 and EHMT1, revealing its broader spectrum and deepening our understanding of its molecular mechanisms, thereby informing accurate variant interpretation, counseling, and clinical management.

Mendelian randomization (MR) provides valuable assessments of the causal effect of exposure on outcome, yet the application of conventional MR methods for mapping risk genes encounters new challenges. One of the issues is the limited availability of expression quantitative trait loci (eQTLs) as instrumental variables (IVs), hampering the estimation of sparse causal effects. Additionally, the often context- or tissue-specific eQTL effects challenge the MR assumption of consistent IV effects across eQTL and GWAS data. To address these challenges, we propose a multi-context multivariable integrative MR framework, mintMR, for mapping expression and molecular traits as joint exposures. It models the effects of molecular exposures across multiple tissues in each gene region, while simultaneously estimating across multiple gene regions. It uses eQTLs with consistent effects across more than one tissue type as IVs, improving IV consistency. A major innovation of mintMR involves employing multi-view learning methods to collectively model latent indicators of disease relevance across multiple tissues, molecular traits, and gene regions. The multi-view learning captures the major patterns of disease relevance and uses these patterns to update the estimated tissue relevance probabilities. The proposed mintMR iterates between performing a multi-tissue MR for each gene region and joint learning the disease-relevant tissue probabilities across gene regions, improving the estimation of sparse effects across genes. We apply mintMR to evaluate the causal effects of gene expression and DNA methylation for 35 complex traits using multi-tissue QTLs as IVs. The proposed mintMR controls genome-wide inflation and offers insights into disease mechanisms.

Gene misexpression is the aberrant transcription of a gene in a context where it is usually inactive. Despite its known pathological consequences in specific rare diseases, we have a limited understanding of its wider prevalence and mechanisms in humans. To address this, we analyzed gene misexpression in 4,568 whole-blood bulk RNA sequencing samples from INTERVAL study blood donors. We found that while individual misexpression events occur rarely, in aggregate they were found in almost all samples and a third of inactive protein-coding genes. Using 2,821 paired whole-genome and RNA sequencing samples, we identified that misexpression events are enriched in cis for rare structural variants. We established putative mechanisms through which a subset of SVs lead to gene misexpression, including transcriptional readthrough, transcript fusions, and gene inversion. Overall, we develop misexpression as a type of transcriptomic outlier analysis and extend our understanding of the variety of mechanisms by which genetic variants can influence gene expression.

Highlighting the Distinguished Speakers Symposium on "The Future of Human Genetics and Genomics," this collection of articles is based on presentations at the ASHG 2023 Annual Meeting in Washington, DC, in celebration of all our field has accomplished in the past 75 years, since the founding of ASHG in 1948.