American journal of human genetics最新文献

Large biobank samples provide an opportunity to integrate broad phenotyping, familial records, and molecular genetics data to study complex traits and diseases. We introduce Pearson-Aitken Family Genetic Risk Scores (PA-FGRS), a method for estimating disease liability from patterns of diagnoses in extended, age-censored genealogical records. We then apply the method to study a paradigmatic complex disorder, major depressive disorder (MDD), using the iPSYCH2015 case-cohort study of 30,949 MDD cases, 39,655 random population controls, and more than 2 million relatives. We show that combining PA-FGRS liabilities estimated from family records with molecular genotypes of probands improves three lines of inquiry. Incorporating PA-FGRS liabilities improves classification of MDD over and above polygenic scores, identifies robust genetic contributions to clinical heterogeneity in MDD associated with comorbidity, recurrence, and severity and can improve the power of genome-wide association studies. Our method is flexible and easy to use, and our study approaches are generalizable to other datasets and other complex traits and diseases.

Mechanisms of abdominal obesity GWAS variants have remained largely unknown. To elucidate these mechanisms, we leveraged subcutaneous adipose tissue (SAT) single nucleus RNA-sequencing and genomics data. After discovering that heritability of abdominal obesity is enriched in adipocytes, we focused on a SAT unique adipocyte marker gene, the transcription factor TBX15, and its abdominal obesity-associated deleterious missense variant, rs10494217. The allele frequency of rs10494217 revealed a north-to-south decreasing gradient, with consistent significant F_ST values observed for 25 different populations when compared to Finns, a population with a history of genetic isolation. Given the role of Tbx15 in mouse thermogenesis, the frequency may have increased as an adaptation to cold in Finns. Our selection analysis provided significant evidence of selection for the abdominal obesity risk allele T of rs10494217 in Finns, with a north-to-south decreasing trend in other populations, and demonstrated that latitude significantly predicts the allele frequency. We also discovered that the risk allele status significantly affects SAT adipocyte expression of multiple adipocyte marker genes in trans in two cohorts. Two of these trans genes have been connected to thermogenesis, supporting the thermogenic effect of the TBX15 missense variant as a possible cause of its selection. Adipose expression of one trans gene, a lncRNA, AC002066.1, was strongly associated with adipocyte size, implicating it in metabolically unhealthy adipocyte hypertrophy. In summary, the abdominal obesity variant rs10494217 was selected in Finns, and individuals with the risk allele have trans effects on adipocyte expression of genes relating to thermogenesis and adipocyte hypertrophy.

Research on brain expression quantitative trait loci (eQTLs) has illuminated the genetic underpinnings of schizophrenia (SCZ). Yet most of these studies have been centered on European populations, leading to a constrained understanding of population diversities and disease risks. To address this gap, we examined genotype and RNA-seq data from African Americans (AA, n = 158), Europeans (EUR, n = 408), and East Asians (EAS, n = 217). When comparing eQTLs between EUR and non-EUR populations, we observed concordant patterns of genetic regulatory effect, particularly in terms of the effect sizes of the eQTLs. However, 343,737 cis-eQTLs linked to 1,276 genes and 198,769 SNPs were found to be specific to non-EUR populations. Over 90% of observed population differences in eQTLs could be traced back to differences in allele frequency. Furthermore, 35% of these eQTLs were notably rare in the EUR population. Integrating brain eQTLs with SCZ signals from diverse populations, we observed a higher disease heritability enrichment of brain eQTLs in matched populations compared to mismatched ones. Prioritization analysis identified five risk genes (SFXN2, VPS37B, DENR, FTCDNL1, and NT5DC2) and three potential regulatory variants in known risk genes (CNNM2, MTRFR, and MPHOSPH9) that were missed in the EUR dataset. Our findings underscore that increasing genetic ancestral diversity is more efficient for power improvement than merely increasing the sample size within single-ancestry eQTLs datasets. Such a strategy will not only improve our understanding of the biological underpinnings of population structures but also pave the way for the identification of risk genes in SCZ.

Pathogenic constitutional APC variants underlie familial adenomatous polyposis, the most common hereditary gastrointestinal polyposis syndrome. To improve variant classification and resolve the interpretative challenges of variants of uncertain significance (VUSs), APC-specific variant classification criteria were developed by the ClinGen-InSiGHT Hereditary Colorectal Cancer/Polyposis Variant Curation Expert Panel (VCEP) based on the criteria of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP). A streamlined algorithm using the APC-specific criteria was developed and applied to assess all APC variants in ClinVar and the International Society for Gastrointestinal Hereditary Tumours (InSiGHT) international reference APC Leiden Open Variation Database (LOVD) variant database, which included a total of 10,228 unique APC variants. Among the ClinVar and LOVD variants with an initial classification of (likely) benign or (likely) pathogenic, 94% and 96% remained in their original categories, respectively. In contrast, 41% ClinVar and 61% LOVD VUSs were reclassified into clinically meaningful classes, the vast majority as (likely) benign. The total number of VUSs was reduced by 37%. In 24 out of 37 (65%) promising APC variants that remained VUS despite evidence for pathogenicity, a data-mining-driven work-up allowed their reclassification as (likely) pathogenic. These results demonstrated that the application of APC-specific criteria substantially reduced the number of VUSs in ClinVar and LOVD. The study also demonstrated the feasibility of a systematic approach to variant classification in large datasets, which might serve as a generalizable model for other gene- or disease-specific variant interpretation initiatives. It also allowed for the prioritization of VUSs that will benefit from in-depth evidence collection. This subset of APC variants was approved by the VCEP and made publicly available through ClinVar and LOVD for widespread clinical use.

Gene therapy has made significant progress in the treatment of hereditary hearing loss. However, most research has focused on deafness-related genes that are primarily expressed in hair cells with less attention given to multisite-expressed deafness genes. MPZL2, the second leading cause of mild-to-moderate hereditary deafness, is widely expressed in different inner ear cells. We generated a mouse model with a deletion in the Mpzl2 gene, which displayed moderate and slowly progressive hearing loss, mimicking the phenotype of individuals with DFNB111. We developed a gene replacement therapy system mediated by AAV-ie for efficient transduction in various types of cochlear cells. AAV-ie-Mpzl2 administration significantly lowered the auditory brainstem response and distortion product otoacoustic emission thresholds of Mpzl2^-/- mice for at least seven months. AAV-ie-Mpzl2 delivery restored the structural integrity in both outer hair cells and Deiters cells. This study suggests the potential of gene therapy for MPZL2-related deafness and provides a proof of concept for gene therapy targeting other deafness-related genes that are expressed in different cell populations in the cochlea.

Multi-ancestry genome-wide association studies (GWASs) have highlighted the existence of variants with ancestry-specific effect sizes. Understanding where and why these ancestry-specific effects occur is fundamental to understanding the genetic basis of human diseases and complex traits. Here, we characterized genes differentially expressed across ancestries (ancDE genes) at the cell-type level by leveraging single-cell RNA-sequencing data in peripheral blood mononuclear cells for 21 individuals with East Asian (EAS) ancestry and 23 individuals with European (EUR) ancestry (172,385 cells); then, we tested whether variants surrounding those genes were enriched in disease variants with ancestry-specific effect sizes by leveraging ancestry-matched GWASs of 31 diseases and complex traits (average n ∼ 90,000 and ∼ 267,000 in EAS and EUR, respectively). We observed that ancDE genes tended to be cell-type specific and enriched in genes interacting with the environment and in variants with ancestry-specific disease effect sizes, which suggests cell-type-specific, gene-by-environment interactions shared between regulatory and disease architectures. Finally, we illustrated how different environments might have led to ancestry-specific myeloid cell leukemia 1 (MCL1) expression in B cells and ancestry-specific allele effect sizes in lymphocyte count GWASs for variants surrounding MCL1. Our results imply that large single-cell and GWAS datasets from diverse ancestries are required to improve our understanding of human diseases.

Variants that alter gene splicing are estimated to comprise up to a third of all disease-causing variants, yet they are hard to predict from DNA sequencing data alone. To overcome this, many groups are incorporating RNA-based analyses, which are resource intensive, particularly for diagnostic laboratories. There are thousands of functionally validated variants that induce mis-splicing; however, this information is not consolidated, and they are under-represented in ClinVar, which presents a barrier to variant interpretation and can result in duplication of validation efforts. To address this issue, we developed SpliceVarDB, an online database consolidating over 50,000 variants assayed for their effects on splicing in over 8,000 human genes. We evaluated over 500 published data sources and established a spliceogenicity scale to standardize, harmonize, and consolidate variant validation data generated by a range of experimental protocols. According to the strength of their supporting evidence, variants were classified as "splice-altering" (∼25%), "not splice-altering" (∼25%), and "low-frequency splice-altering" (∼50%), which correspond to weak or indeterminate evidence of spliceogenicity. Importantly, 55% of the splice-altering variants in SpliceVarDB are outside the canonical splice sites (5.6% are deep intronic). These variants can support the variant curation diagnostic pathway and can be used to provide the high-quality data necessary to develop more accurate in silico splicing predictors. The variants are accessible through an online platform, SpliceVarDB, with additional features for visualization, variant information, in silico predictions, and validation metrics. SpliceVarDB is a very large collection of splice-altering variants and is available at https://splicevardb.org.

Bicuspid aortic valve (BAV) is the most common congenital heart lesion with an estimated population prevalence of 1%. We hypothesize that specific gene variants predispose to early-onset complications of BAV (EBAV). We analyzed whole-exome sequences (WESs) to identify rare coding variants that contribute to BAV disease in 215 EBAV-affected families. Predicted damaging variants in candidate genes with moderate or strong supportive evidence to cause developmental cardiac phenotypes were present in 107 EBAV-affected families (50% of total), including genes that cause BAV (9%) or heritable thoracic aortic disease (HTAD, 19%). After appropriate filtration, we also identified 129 variants in 54 candidate genes that are associated with autosomal-dominant congenital heart phenotypes, including recurrent deleterious variation of FBN2, MYH6, channelopathy genes, and type 1 and 5 collagen genes. These findings confirm our hypothesis that unique rare genetic variants drive early-onset presentations of BAV disease.

The BAF chromatin remodeler regulates lineage commitment including cranial neural crest cell (CNCC) specification. Variants in BAF subunits cause Coffin-Siris syndrome (CSS), a congenital disorder characterized by coarse craniofacial features and intellectual disability. Approximately 50% of individuals with CSS harbor variants in one of the mutually exclusive BAF subunits, ARID1A/ARID1B. While Arid1a deletion in mouse neural crest causes severe craniofacial phenotypes, little is known about the role of ARID1A in CNCC specification. Using CSS-patient-derived ARID1A^+/- induced pluripotent stem cells to model CNCC specification, we discovered that ARID1A-haploinsufficiency impairs epithelial-to-mesenchymal transition (EMT), a process necessary for CNCC delamination and migration from the neural tube. Furthermore, wild-type ARID1A-BAF regulates enhancers associated with EMT genes. ARID1A-BAF binding at these enhancers is impaired in heterozygotes while binding at promoters is unaffected. At the sequence level, these EMT enhancers contain binding motifs for ZIC2, and ZIC2 binding at these sites is ARID1A-dependent. When excluded from EMT enhancers, ZIC2 relocates to neuronal enhancers, triggering aberrant neuronal gene activation. In mice, deletion of Zic2 impairs NCC delamination, while ZIC2 overexpression in chick embryos at post-migratory neural crest stages elicits ectopic delamination from the neural tube. These findings reveal an essential ARID1A-ZIC2 axis essential for EMT and CNCC delamination.