HGG Advances最新文献

Bioactive fatty acid-derived oxylipin molecules play key roles mediating inflammation and oxidative stress. Circulating levels of fatty acids and oxylipins are influenced by environmental and genetic factors; characterizing the genetic architecture of bioactive lipids could yield new insights into underlying biology. We performed a genome-wide association study (GWAS) of 81 fatty acids and oxylipins in 11,584 Hispanic Community Health Study/Study of Latinos (HCHS/SOL) participants with genetic and lipidomic data measured at study baseline (58.6% female, mean age = 46.1 years (standard deviation 13.8)). Additionally, given the effects of central obesity on inflammation, we examined interactions with waist circumference using two-degree-of-freedom joint tests. Thirty-three of the 81 oxylipins and fatty acids were significantly heritable (heritability range: 0-32.7%). Forty (49.4%) oxylipins and fatty acids had at least one genome-wide significant (p < 6.94E-11) variant resulting in 19 independent genetic loci. Six loci (lead variant minor allele frequency [MAF] range: 0.08-0.50), including desaturase-encoding FADS and OATP1B1 transporter protein-encoding SLCO1B1, exhibited associations with two or more fatty acids and oxylipins. At several of these loci, there was evidence of colocalization of the top variant across fatty acids and oxylipins. The remaining loci were only associated with one oxylipin or fatty acid and included several CYP loci. We also identified an additional rare variant (MAF = 0.002) near CARS2 in two-degree-of-freedom tests. Our analyses revealed shared and distinct genetic architecture underlying fatty acids and oxylipins, providing insights into genetic factors and motivating work to characterize these compounds and elucidate their roles in disease.

Cerebellar atrophy and hypoplasia are usually identified on MRI performed on children presenting signs of cerebellar ataxias, developmental delay, and intellectual disability. These signs can be associated with hypo- or de-myelinating leukodystrophies. A recent study reported two cases: one child diagnosed with leukodystrophy and cerebellar atrophy, harboring a homozygous variant in LSM7, and another who died in utero, presumed to have another homozygous variant in LSM7, based on the parents' genotype. LSM7 encodes a subunit of the LSM complex, involved in pre-RNA maturation and mRNA degradation. Consequently, it has been suggested as a strong candidate disease gene. This hypothesis was supported by functional investigations of the variants. Here, we report a patient with neurodevelopmental defects, leukodystrophy, and cerebellar atrophy, harboring compound heterozygous missense variants in the LSM7 gene. One of these variants is the same as the one carried by the first case reported previously. The other one is at the same position as the variant potentially carried by the second case reported previously. Based on comparable neuroimaging, clinical features, and the involvement of the same amino acids previously demonstrated as key for LSM complex function, we confirm that LSM7 disruption causes a neurodevelopmental disorder characterized by leukodystrophy and cerebellar atrophy.

Multiple lines of evidence indicate that ankylosing spondylitis (AS) is a lymphocyte-driven disease. However, which lymphocyte populations are critical in AS pathogenesis is not known. In this study, we aimed to identify the key cell types mediating the genetic risk in AS using an unbiased functional genomics approach. We integrated genome-wide association study (GWAS) data with epigenomic and transcriptomic datasets of human immune cells. To quantify enrichment of cell type-specific open chromatin or gene expression in AS risk loci, we used three published methods-LDSC-SEG, SNPsea, and scDRS-that have successfully identified relevant cell types in other diseases. Natural killer (NK) cell-specific open chromatin regions are significantly enriched in heritability for AS, compared to other immune cell types such as T cells, B cells, and monocytes. This finding was consistent between two AS GWAS. Using RNA sequencing data, we validated that genes in AS risk loci are enriched in NK cell-specific gene expression. Using the human Space-Time Gut Cell Atlas, we also found significant upregulation of AS-associated genes predominantly in NK cells. We performed co-localization analyses between GWAS risk loci and genetic variants associated with gene expression (eQTL) to find putative target genes. This revealed four AS risk loci affecting regulation of candidate target genes in NK cells: two known loci, ERAP1 and TNFRSF1A, and two understudied loci, ENTR1 (SDCCAG3) and B3GNT2. Our findings suggest that NK cells may play a crucial role in AS development and highlight four putative target genes for functional follow-up in NK cells.

De novo variants in CSNK2A1 cause autosomal dominant Okur-Chung neurodevelopmental syndrome (OCNDS). OCNDS has an evolving clinical phenotype predominantly characterized by intellectual disability, global delays, dysmorphic features, and immunological manifestations. Microcephaly, defined as a small head circumference, is not widely recognized as a classical clinical presentation. Here, we describe four individuals from three unrelated families who shared several clinical features characteristic of an underlying syndromic neurodevelopmental condition. Trio clinical exome and research genome sequencing revealed that all affected individuals had heterozygous pathogenic missense variants in CSNK2A1. Two variants (c.468T>A p.Asp156Glu and c.149A>G p.Tyr50Cys) were de novo and previously reported, but the third variant (c.137G>T p.Gly46Val) is novel and segregated in two affected individuals in a family. This adds to growing evidence of inherited disease-causing variants in CSNK2A1, an observation reported only twice previously. A detailed phenotypic analysis of our cohort together with those individuals reported in the literature revealed that OCNDS individuals, on average, have a smaller head circumference with one-third presenting with microcephaly. We also show that the incidence of microcephaly is significantly correlated with the location of the variant in the encoded protein. Our findings suggest that small head circumference is a common but under-recognized feature of OCNDS, which may not be apparent at birth.

Epileptic encephalopathies are severe epilepsy syndromes characterized by early onset and progressive cerebral dysfunction. A nonsense variant in the DALR anticodon binding domain containing 3 (DALRD3) gene has been implicated in epileptic encephalopathy, but no other disease-associated variants in DALRD3 have been described. In human cells, the DALRD3 protein forms a complex with the METTL2 methyltransferase to generate the 3-methylcytosine (m3C) modification in specific arginine tRNAs. Here, we identify an individual with a homozygous missense variant in DALRD3 who displays developmental delay, cognitive deficiencies, and multifocal epilepsy. The missense variant substitutes an arginine residue to cysteine (R517C) within the DALR domain of the DALRD3 protein that is required for binding tRNAs. Cells derived from the individual homozygous for the DALRD3-R517C variant exhibit reduced levels of m3C modification in arginine tRNAs, indicating that the R517C variant impairs DALRD3 function. Notably, the DALRD3-R517C protein displays reduced association with METTL2 and loss of interaction with substrate tRNAs. Our results uncover another loss-of-function variant in DALRD3 linked to epileptic encephalopathy disorders. Importantly, these findings underscore DALRD3-dependent tRNA modification as a key contributor to proper brain development and function.

Hearing impairment (HI) is the most common neurosensory disorder globally and is reported to be more prevalent in low-income countries. In high-income countries, up to 50% of congenital childhood HI is of genetic origin. However, there are limited genetic data on HI from sub-Saharan African populations. In this study, we investigated the genetic causes of HI in the Malian populations, using whole-exome sequencing. Furthermore, cDNA was transfected into HEK293T cells for localization and expression analysis in a candidate gene. Twenty-four multiplex families were enrolled, 50% (12/24) of which are consanguineous. Clustering methods showed patterns of admixture from non-African sources in some Malian populations. Variants were found in six known nonsyndromic HI (NSHI) genes, four genes that can underlie either syndromic HI (SHI) or NSHI, one SHI gene, and one novel candidate HI gene. Overall, 75% of families (18/24) were solved, and 94.4% (17/18) had variants in known HI genes including MYO15A, CDH23, MYO7A, GJB2, SLC26A4, PJVK, OTOGL, TMC1, CIB2, GAS2, PDCH15, and EYA1. A digenic inheritance (CDH23 and PDCH15) was found in one family. Most variants (59.1%, 13/22) in known HI genes were not previously reported or associated with HI. The UBFD1 candidate HI gene, which was identified in one consanguineous family, is expressed in human inner ear organoids. Cell-based experiments in HEK293T showed that mutants UBFD1 had a lower expression, compared to wild type. We report the profile of known genes and the UBFD1 candidate gene for HI in Mali and emphasize the potential of gene discovery in African populations.

Blood lipid traits are treatable and heritable risk factors for heart disease, a leading cause of mortality worldwide. Although genome-wide association studies (GWASs) have discovered hundreds of variants associated with lipids in humans, most of the causal mechanisms of lipids remain unknown. To better understand the biological processes underlying lipid metabolism, we investigated the associations of plasma protein levels with total cholesterol (TC), triglycerides (TG), high-density lipoprotein (HDL) cholesterol, and low-density lipoprotein (LDL) cholesterol in blood. We trained protein prediction models based on samples in the Multi-Ethnic Study of Atherosclerosis (MESA) and applied them to conduct proteome-wide association studies (PWASs) for lipids using the Global Lipids Genetics Consortium (GLGC) data. Of the 749 proteins tested, 42 were significantly associated with at least one lipid trait. Furthermore, we performed transcriptome-wide association studies (TWASs) for lipids using 9,714 gene expression prediction models trained on samples from peripheral blood mononuclear cells (PBMCs) in MESA and 49 tissues in the Genotype-Tissue Expression (GTEx) project. We found that although PWASs and TWASs can show different directions of associations in an individual gene, 40 out of 49 tissues showed a positive correlation between PWAS and TWAS signed p values across all the genes, which suggests high-level consistency between proteome-lipid associations and transcriptome-lipid associations.

The Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema was released in 2022 and approved by ISO as a standard for sharing clinical and genomic information about an individual, including phenotypic descriptions, numerical measurements, genetic information, diagnoses, and treatments. A phenopacket can be used as an input file for software that supports phenotype-driven genomic diagnostics and for algorithms that facilitate patient classification and stratification for identifying new diseases and treatments. There has been a great need for a collection of phenopackets to test software pipelines and algorithms. Here, we present Phenopacket Store. Phenopacket Store v.0.1.19 includes 6,668 phenopackets representing 475 Mendelian and chromosomal diseases associated with 423 genes and 3,834 unique pathogenic alleles curated from 959 different publications. This represents the first large-scale collection of case-level, standardized phenotypic information derived from case reports in the literature with detailed descriptions of the clinical data and will be useful for many purposes, including the development and testing of software for prioritizing genes and diseases in diagnostic genomics, machine learning analysis of clinical phenotype data, patient stratification, and genotype-phenotype correlations. This corpus also provides best-practice examples for curating literature-derived data using the GA4GH Phenopacket Schema.

Inherited genetics represents an important contributor to risk of esophageal adenocarcinoma (EAC), and its precursor Barrett's esophagus (BE). Genome-wide association studies have identified ∼30 susceptibility variants for BE/EAC, yet genetic interactions remain unexamined. To address challenges in large-scale G×G scans, we combined knowledge-guided filtering and machine learning approaches, focusing on genes with (1) known/plausible links to BE/EAC pathogenesis (n = 493) or (2) prior evidence of biological interactions (n = 4,196). Approximately 75 × 10⁶ SNP×SNP interactions were screened via hierarchical group lasso (glinternet) using BEACON GWAS data. The top ∼2,000 interactions retained in each scan were prioritized using p values from single logistic models. Identical scans were repeated among males only (78%), with two independent GWAS datasets used for replication. In overall and male-specific primary replications, 11 of 187 and 20 of 191 interactions satisfied p < 0.05, respectively. The strongest evidence for secondary replication was for rs17744726×rs3217992 among males, with consistent directionality across all cohorts (P_meta = 2.19 × 10^-8); rs3217992 "T" was associated with reduced risk only in individuals homozygous for rs17744726 "G." Rs3217992 maps to the CDKN2B 3' UTR and reportedly disrupts microRNA-mediated repression. Rs17744726 maps to an intronic enhancer region in BLK. Through in silico prioritization and experimental validation, we identified a nearby proxy variant (rs4841556) as a functional modulator of enhancer activity. Enhancer-gene mapping and eQTLs implicated BLK and FAM167A as targets. The first systematic G×G investigation in BE/EAC, this study uncovers differential risk associations for CDKN2B variation by BLK genotype, suggesting novel biological dependency between two risk loci encoding key mediators of tumor suppression and inflammation.

Single-cell transcriptome data can provide insights into how genetic variation influences biological processes involved in human physiology and disease. However, the identification of gene-level associations in distinct cell types faces several challenges, including the limited reference resources from population-scale studies, data sparsity in single-cell RNA sequencing, and the complex cell state pattern of expression within individual cell types. Here, we develop genetic models of cell-type-specific and cell-state-adjusted gene expression in mid-brain neurons undergoing differentiation from induced pluripotent stem cells. The resulting framework quantifies the dynamics of the genetic regulation of gene expression and estimates its cell-type specificity. As an application, we show that the approach detects known and new genes associated with schizophrenia and enables insights into context-dependent disease mechanisms. We provide a genomic resource from a phenome-wide application of our models to more than 1,500 phenotypes from the UK Biobank. Using longitudinal, genetically determined expression, we implement a predictive causality framework, evaluating the prediction of future values of a target gene expression using prior values of a putative regulatory gene. Collectively, the results of this work demonstrate the insights that can be gained into the molecular underpinnings of disease by quantifying the genetic control of gene expression at single-cell resolution.