American journal of human genetics最新文献

{"title":"Identification of genes associated with testicular germ cell tumor susceptibility through a transcriptome-wide association study.","authors":"Emilio Ugalde-Morales, Rona Wilf, John Pluta, Alexander Ploner, Mengyao Fan, Mohammad Damra, Katja K Aben, Lynn Anson-Cartwright, Chu Chen, Victoria K Cortessis, Siamak Daneshmand, Alberto Ferlin, Marija Gamulin, Jourik A Gietema, Anna Gonzalez-Niera, Tom Grotmol, Robert J Hamilton, Mark Harland, Trine B Haugen, Russ Hauser, Michelle A T Hildebrandt, Robert Karlsson, Lambertus A Kiemeney, Jung Kim, Davor Lessel, Ragnhild A Lothe, Chey Loveday, Stephen J Chanock, Katherine A McGlynn, Coby Meijer, Kevin T Nead, Jeremie Nsengimana, Maja Popovic, Thorunn Rafnar, Lorenzo Richiardi, Maria S Rocca, Stephen M Schwartz, Rolf I Skotheim, Kari Stefansson, Douglas R Stewart, Clare Turnbull, David J Vaughn, Sofia B Winge, Tongzhang Zheng, Alvaro N Monteiro, Kristian Almstrup, Peter A Kanetsky, Katherine L Nathanson, Fredrik Wiklund","doi":"10.1016/j.ajhg.2025.01.022","DOIUrl":"10.1016/j.ajhg.2025.01.022","url":null,"abstract":"<p><p>Transcriptome-wide association studies (TWASs) have the potential to identify susceptibility genes associated with testicular germ cell tumors (TGCTs). We conducted a comprehensive TGCT TWAS by integrating genome-wide association study (GWAS) summary data with predicted expression models from normal testis, TGCT tissues, and a cross-tissue panel that encompasses shared regulatory features across 22 normal tissues, including the testis. Gene associations were evaluated while accounting for variant-level effects from GWASs, followed by fine-mapping analyses in regions exhibiting multiple TWAS signals, and finally supplemented by colocalization analysis. Expression and protein patterns of identified TWAS genes were further examined in relevant tissues. Our analysis tested 19,805 gene-disease links, revealing 165 TGCT-associated genes with a false discovery rate of less than 0.01. We prioritized 46 candidate genes by considering GWAS-inflated signals, correlations between neighboring genes, and evidence of colocalization. Among these, 23 genes overlap with 22 GWAS loci, with 7 being associations not previously implicated in TGCT risk. Additionally, 23 genes located within 21 loci are at least 1 Mb away from published GWAS index variants. The 46 prioritized genes display expression levels consistent with expected expression levels in human gonadal cell types and precursor tumor cells and significant enrichment in TGCTs. Additionally, immunohistochemistry revealed protein-level accumulation of two candidate genes, ARID3B and GINM1, in both precursor and tumor cells. These findings enhance our understanding of the genetic predisposition to TGCTs and underscore the importance of further functional investigations into these candidate genes.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":"630-643"},"PeriodicalIF":8.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11947167/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143497586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Isogenic hiPSC models of Turner syndrome development reveal shared roles of inactive X and Y in the human cranial neural crest network.","authors":"Darcy T Ahern, Prakhar Bansal, Isaac V Faustino, Owen M Chambers, Erin C Banda, Heather R Glatt-Deeley, Rachael E Massey, Yuvabharath Kondaveeti, Stefan F Pinter","doi":"10.1016/j.ajhg.2025.01.013","DOIUrl":"10.1016/j.ajhg.2025.01.013","url":null,"abstract":"<p><p>Viable human aneuploidy can be challenging to model in rodents due to syntenic boundaries or primate-specific biology. Human monosomy-X (45,X) causes Turner syndrome (TS), altering craniofacial, skeletal, endocrine, and cardiovascular development, which in contrast remain unaffected in X-monosomic mice. To learn how monosomy-X may impact embryonic development, we turned to 45,X and isogenic euploid human induced pluripotent stem cells (hiPSCs) from male and female mosaic donors. Because the neural crest (NC) is hypothesized to give rise to craniofacial and cardiovascular changes in TS, we assessed differential expression of hiPSC-derived anterior NC cells (NCCs). Across three independent isogenic panels, 45,X NCCs show impaired acquisition of PAX7⁺SOX10⁺ markers and disrupted expression of other NCC-specific genes relative to isogenic euploid controls. Additionally, 45,X NCCs increase cholesterol biosynthesis genes while reducing transcripts with 5' terminal oligopyrimidine (TOP) motifs, including those of ribosomal and nuclear-encoded mitochondrial proteins. Such metabolic pathways are also over-represented in weighted co-expression modules that are preserved in monogenic neurocristopathy and reflect 28% of all TS-associated terms of the human phenotype ontology. We demonstrate that 45,X NCCs reduce protein synthesis despite activation of mammalian target of rapamycin (mTOR) but are partially rescued by mild mTOR suppression. Our analysis identifies specific sex-linked genes that are expressed from two copies in euploid males and females alike and qualify as candidate haploinsufficient drivers of TS phenotypes in NC-derived lineages. This study demonstrates that isogenic hiPSC-derived NCC panels representing monosomy-X can serve as powerful models of early NC development in TS and inform new hypotheses toward its etiology.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":"615-629"},"PeriodicalIF":8.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11947172/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143373698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distinct explanations underlie gene-environment interactions in the UK Biobank.","authors":"Arun Durvasula, Alkes L Price","doi":"10.1016/j.ajhg.2025.01.014","DOIUrl":"10.1016/j.ajhg.2025.01.014","url":null,"abstract":"<p><p>The role of gene-environment (GxE) interaction in disease and complex trait architectures is widely hypothesized but currently unknown. Here, we apply three statistical approaches to quantify and distinguish three different types of GxE interaction for a given trait and environmental (E) variable. First, we detect locus-specific GxE interaction by testing for genetic correlation (r_g) < 1 across E bins. Second, we detect genome-wide effects of the E variable on genetic variance by leveraging polygenic risk scores (PRSs) to test for significant PRSxE in a regression of phenotypes on PRS, E, and PRSxE, together with differences in SNP heritability across E bins. Third, we detect genome-wide proportional amplification of genetic and environmental effects as a function of the E variable by testing for significant PRSxE with no differences in SNP heritability across E bins. We applied our framework to 33 UK Biobank traits (25 quantitative traits and 8 diseases; average n = 325,000) and 10 E variables spanning lifestyle, diet, and other environmental exposures. First, we identified 19 trait-E pairs with r_g significantly <1 (false discovery rate < 5%); 28 trait-E pairs with significant PRSxE and significant SNP heritability differences across E bins; and 15 trait-E pairs with significant PRSxE but no SNP heritability differences across E bins. Across the three scenarios, eight of the trait-E pairs involved disease traits, whose interpretation is complicated by scale effects. Analyses using biological sex as the E variable produced additional significant findings in each of these scenarios. Overall, we infer a significant contribution of GxE and GxSex effects to complex trait variance.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":"644-658"},"PeriodicalIF":8.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11947178/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143447817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"2024 ASHG awards and addresses.","authors":"","doi":"10.1016/j.ajhg.2025.01.023","DOIUrl":"https://doi.org/10.1016/j.ajhg.2025.01.023","url":null,"abstract":"<p><p>Each year at the annual meeting of The American Society of Human Genetics (ASHG), addresses are given in honor of the Society and several award winners. A summary of each of these is provided below. On the following pages, we have printed the Presidential Address as well as the addresses for the Lifetime Achievement, Scientific Achievement, and Leadership awards. Recordings of these addresses, as well as those of many other presentations, can be found at http://www.ashg.org.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":"112 3","pages":"459-460"},"PeriodicalIF":8.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143584358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"reg-eQTL: Integrating transcription factor effects to unveil regulatory variants.","authors":"Rekha Mudappathi, Tatiana Patton, Hai Chen, Ping Yang, Zhifu Sun, Panwen Wang, Chang-Xin Shi, Junwen Wang, Li Liu","doi":"10.1016/j.ajhg.2025.01.015","DOIUrl":"10.1016/j.ajhg.2025.01.015","url":null,"abstract":"<p><p>Regulatory single-nucleotide variants (rSNVs) in noncoding regions of the genome play a crucial role in gene transcription by altering transcription factor (TF) binding, chromatin states, and other epigenetic modifications. Existing expression quantitative trait locus (eQTL) methods identify genomic loci associated with gene-expression changes, but they often fall short in pinpointing causal variants. We introduce reg-eQTL, a computational method that incorporates TF effects and interactions with genetic variants into eQTL analysis. This approach provides deeper insights into the regulatory mechanisms, bringing us one step closer to identifying potential causal variants by uncovering how TFs interact with SNVs to influence gene expression. This method defines a trio consisting of a genetic variant, a target gene, and a TF and tests its impact on gene transcription. In comprehensive simulations, reg-eQTL shows improved power of detecting rSNVs with low population frequency, weak effects, and synergetic interaction with TF as compared to traditional eQTL methods. Application of reg-eQTL to GTEx data from lung, brain, and whole-blood tissues uncovered regulatory trios that include eQTLs and increased the number of eQTLs shared across tissue types. Regulatory networks constructed on the basis of these trios reveal intricate gene regulation across tissue types.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":"659-674"},"PeriodicalIF":8.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11947170/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143373705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"2024 ASHG Lifetime Achievement Award.","authors":"Margaret A Pericak-Vance","doi":"10.1016/j.ajhg.2025.02.002","DOIUrl":"10.1016/j.ajhg.2025.02.002","url":null,"abstract":"<p><p>This article is based on the address given by the author at the 2024 meeting of The American Society of Human Genetics (ASHG) in Denver, CO. A video of the original address can be found at the ASHG website.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":"112 3","pages":"470-472"},"PeriodicalIF":8.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11993870/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143584360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genome-wide prediction of dominant and recessive neurodevelopmental disorder-associated genes.","authors":"Ryan S Dhindsa, Blake A Weido, Justin S Dhindsa, Arya J Shetty, Chloe F Sands, Slavé Petrovski, Dimitrios Vitsios, Anthony W Zoghbi","doi":"10.1016/j.ajhg.2025.02.001","DOIUrl":"10.1016/j.ajhg.2025.02.001","url":null,"abstract":"<p><p>Despite great progress, thousands of neurodevelopmental disorder (NDD) risk genes remain to be discovered. We present a computational approach that accelerates NDD risk gene identification using machine learning. First, we demonstrate that models trained solely on single-cell RNA sequencing data can robustly predict genes implicated in autism spectrum disorder (ASD), developmental and epileptic encephalopathy (DEE), and developmental delay (DD). Notably, we find differences in gene expression patterns of genes with monoallelic and bi-allelic inheritance patterns in the developing human cortex. We then integrate expression data with 300 orthogonal features, including intolerance metrics, protein-protein interaction data, and others, in a semi-supervised machine learning framework (mantis-ml) to train inheritance-specific models for these disorders. The models have high predictive power (area under the receiver operator curves [AUCs]: 0.84-0.95), and the top-ranked genes were up to 2-fold (monoallelic models) and 6-fold (bi-allelic models) more enriched for high-confidence NDD risk genes compared to genic intolerance metrics alone. Additionally, genes ranking in the top decile were 45 to 180 times more likely to have literature support than those in the bottom decile. Collectively, this work provides robust NDD risk gene predictions that can complement large-scale gene discovery efforts and underscores the importance of considering inheritance in gene risk prediction.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":"693-708"},"PeriodicalIF":8.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11947176/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143522309","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experience using conventional compared to ancestry-based population descriptors in clinical genomics laboratories.","authors":"Kathryn E Hatchell, Sarah R Poll, Emily M Russell, Trevor J Williams, Rachel E Ellsworth, Flavia M Facio, Sienna Aguilar, Edward D Esplin, Alice B Popejoy, Robert L Nussbaum, Swaroop Aradhya","doi":"10.1016/j.ajhg.2025.01.008","DOIUrl":"10.1016/j.ajhg.2025.01.008","url":null,"abstract":"<p><p>Various scientific and professional groups, including the American Medical Association (AMA), American Society of Human Genetics (ASHG), American College of Medical Genetics (ACMG), and the National Academies of Sciences, Engineering, and Medicine (NASEM), have appropriately clarified that certain population descriptors, such as race and ethnicity, are social and cultural constructs with no basis in genetics. Nevertheless, these conventional population descriptors are routinely collected during the course of clinical genetic testing and may be used to interpret test results. Experts who have examined the use of population descriptors, both conventional and ancestry based, in human genetics and genomics have offered guidance on using these descriptors in research but not in clinical laboratory settings. This perspective piece is based on a decade of experience in a clinical genomics laboratory and provides insight into the relevance of conventional and ancestry-based population descriptors for clinical genetic testing, reporting, and clinical research on aggregated data. As clinicians, laboratory geneticists, genetic counselors, and researchers, we describe real-world experiences collecting conventional population descriptors in the course of clinical genetic testing and expose challenges in ensuring clarity and consistency in the use of population descriptors. Current practices in clinical genomics laboratories that are influenced by population descriptors are identified and discussed through case examples. In relation to this, we describe specific types of clinical research projects in which population descriptors were used and helped derive useful insights related to practicing and improving genomic medicine.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":"481-491"},"PeriodicalIF":8.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11947177/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143063249","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"2024 ASHG presidential address: Incomplete penetrance and variable expressivity: Old concepts, new urgency.","authors":"Bruce D Gelb","doi":"10.1016/j.ajhg.2025.01.010","DOIUrl":"10.1016/j.ajhg.2025.01.010","url":null,"abstract":"<p><p>This article is based on the address given by the author at the 2024 meeting of The American Society of Human Genetics (ASHG) in Denver, CO. A video of the original address can be found at the ASHG website.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":"112 3","pages":"461-466"},"PeriodicalIF":8.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11993877/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143584362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"SeqFirst: Building equity access to a precise genetic diagnosis in critically ill newborns.","authors":"Tara L Wenger, Abbey Scott, Lukas Kruidenier, Megan Sikes, Alexandra Keefe, Kati J Buckingham, Colby T Marvin, Kathryn M Shively, Tamara Bacus, Olivia M Sommerland, Kailyn Anderson, Heidi Gildersleeve, Chayna J Davis, Jamie Love-Nichols, Katherine E MacDuffie, Danny E Miller, Joon-Ho Yu, Amy Snook, Britt Johnson, David L Veenstra, Julia Parish-Morris, Kirsty McWalter, Kyle Retterer, Deborah Copenheaver, Bethany Friedman, Jane Juusola, Erin Ryan, Renee Varga, Daniel A Doherty, Katrina Dipple, Jessica X Chong, Paul Kruszka, Michael J Bamshad","doi":"10.1016/j.ajhg.2025.02.003","DOIUrl":"10.1016/j.ajhg.2025.02.003","url":null,"abstract":"<p><p>Access to a precise genetic diagnosis (PrGD) in critically ill newborns is limited and inequitable because the complex inclusion criteria used to prioritize testing eligibility omit many patients at high risk for a genetic condition. SeqFirst-neo is a program to test whether a genotype-driven workflow using simple, broad exclusion criteria to assess eligibility for rapid genome sequencing (rGS) increases access to a PrGD in critically ill newborns. All 408 newborns admitted to a neonatal intensive care unit between January 2021 and February 2022 were assessed, and of 240 eligible infants, 126 were offered rGS (i.e., intervention group [IG]) and compared to 114 infants who received conventional care in parallel (i.e., conventional care group [CCG]). A PrGD was made in 62/126 (49.2%) IG neonates compared to 11/114 (9.7%) CCG infants. The odds of receiving a PrGD were ∼9 times greater in the IG vs. the CCG, and this difference was maintained at 12 months follow-up. Access to a PrGD in the IG vs. CCG differed significantly between infants identified as non-White (34/74, 45.9% vs. 6/29, 20.7%; p = 0.024) and Black (8/10, 80.0% vs. 0/4; p = 0.015). Neonatologists were significantly less successful at predicting a PrGD in non-White than non-Hispanic White infants. The use of a standard workflow in the IG with a PrGD revealed that a PrGD would have been missed in 26/62 (42%) infants. The use of simple, broad exclusion criteria that increase access to genetic testing significantly increases access to a PrGD, improves access equity, and results in fewer missed diagnoses.</p>","PeriodicalId":7659,"journal":{"name":"American journal of human genetics","volume":" ","pages":"508-522"},"PeriodicalIF":8.1,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11947171/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143497663","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}