Genome Medicine最新文献

{"title":"Mitoferrin2 is a synthetic lethal target for chromosome 8p deleted cancers.","authors":"Stephan Krieg, Thomas Rohde, Tobias Rausch, Luise Butthof, Lena Wendler-Link, Christoph Eckert, Kai Breuhahn, Bruno Galy, Jan Korbel, Maximilian Billmann, Marco Breinig, Darjus F Tschaharganeh","doi":"10.1186/s13073-024-01357-w","DOIUrl":"10.1186/s13073-024-01357-w","url":null,"abstract":"<p><strong>Background: </strong>Somatic copy number alterations are a hallmark of cancer that offer unique opportunities for therapeutic exploitation. Here, we focused on the identification of specific vulnerabilities for tumors harboring chromosome 8p deletions.</p><p><strong>Methods: </strong>We developed and applied an integrative analysis of The Cancer Genome Atlas (TCGA), the Cancer Dependency Map (DepMap), and the Cancer Cell Line Encyclopedia to identify chromosome 8p-specific vulnerabilities. We employ orthogonal gene targeting strategies, both in vitro and in vivo, including short hairpin RNA-mediated gene knockdown and CRISPR/Cas9-mediated gene knockout to validate vulnerabilities.</p><p><strong>Results: </strong>We identified SLC25A28 (also known as MFRN2), as a specific vulnerability for tumors harboring chromosome 8p deletions. We demonstrate that vulnerability towards MFRN2 loss is dictated by the expression of its paralog, SLC25A37 (also known as MFRN1), which resides on chromosome 8p. In line with their function as mitochondrial iron transporters, MFRN1/2 paralog protein deficiency profoundly impaired mitochondrial respiration, induced global depletion of iron-sulfur cluster proteins, and resulted in DNA-damage and cell death. MFRN2 depletion in MFRN1-deficient tumors led to impaired growth and even tumor eradication in preclinical mouse xenograft experiments, highlighting its therapeutic potential.</p><p><strong>Conclusions: </strong>Our data reveal MFRN2 as a therapeutic target of chromosome 8p deleted cancers and nominate MFNR1 as the complimentary biomarker for MFRN2-directed therapies.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11181659/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141418576","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":"Developing an optimal stratification model for colorectal cancer screening and reducing racial disparities in multi-center population-based studies.","authors":"Jianbo Tian, Ming Zhang, Fuwei Zhang, Kai Gao, Zequn Lu, Yimin Cai, Can Chen, Caibo Ning, Yanmin Li, Sangni Qian, Hao Bai, Yizhuo Liu, Heng Zhang, Shuoni Chen, Xiangpan Li, Yongchang Wei, Bin Li, Ying Zhu, Jinhua Yang, Mingjuan Jin, Xiaoping Miao, Kun Chen","doi":"10.1186/s13073-024-01355-y","DOIUrl":"10.1186/s13073-024-01355-y","url":null,"abstract":"<p><strong>Background: </strong>Early detection of colorectal neoplasms can reduce the colorectal cancer (CRC) burden by timely intervention for high-risk individuals. However, effective risk prediction models are lacking for personalized CRC early screening in East Asian (EAS) population. We aimed to develop, validate, and optimize a comprehensive risk prediction model across all stages of the dynamic adenoma-carcinoma sequence in EAS population.</p><p><strong>Methods: </strong>To develop precision risk-stratification and intervention strategies, we developed three trans-ancestry PRSs targeting colorectal neoplasms: (1) using 148 previously identified CRC risk loci (PRS₁₄₈); (2) SNPs selection from large-scale meta-analysis data by clumping and thresholding (PRS₁₈₃); (3) PRS-CSx, a Bayesian approach for genome-wide risk prediction (PRS_Genomewide). Then, the performance of each PRS was assessed and validated in two independent cross-sectional screening sets, including 4600 patients with advanced colorectal neoplasm, 4495 patients with non-advanced adenoma, and 21,199 normal individuals from the ZJCRC (Zhejiang colorectal cancer set; EAS) and PLCO (the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; European, EUR) studies. The optimal PRS was further incorporated with lifestyle factors to stratify individual risk and ultimately tested in the PLCO and UK Biobank prospective cohorts, totaling 350,013 participants.</p><p><strong>Results: </strong>Three trans-ancestry PRSs achieved moderately improved predictive performance in EAS compared to EUR populations. Remarkably, the PRSs effectively facilitated a thorough risk assessment across all stages of the dynamic adenoma-carcinoma sequence. Among these models, PRS₁₈₃ demonstrated the optimal discriminatory ability in both EAS and EUR validation datasets, particularly for individuals at risk of colorectal neoplasms. Using two large-scale and independent prospective cohorts, we further confirmed a significant dose-response effect of PRS₁₈₃ on incident colorectal neoplasms. Incorporating PRS₁₈₃ with lifestyle factors into a comprehensive strategy improves risk stratification and discriminatory accuracy compared to using PRS or lifestyle factors separately. This comprehensive risk-stratified model shows potential in addressing missed diagnoses in screening tests (best NPV = 0.93), while moderately reducing unnecessary screening (best PPV = 0.32).</p><p><strong>Conclusions: </strong>Our comprehensive risk-stratified model in population-based CRC screening trials represents a promising advancement in personalized risk assessment, facilitating tailored CRC screening in the EAS population. This approach enhances the transferability of PRSs across ancestries and thereby helps address health disparity.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11170922/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141316994","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":"Machine learning integrative approaches to advance computational immunology.","authors":"Fabiola Curion, Fabian J Theis","doi":"10.1186/s13073-024-01350-3","DOIUrl":"10.1186/s13073-024-01350-3","url":null,"abstract":"<p><p>The study of immunology, traditionally reliant on proteomics to evaluate individual immune cells, has been revolutionized by single-cell RNA sequencing. Computational immunologists play a crucial role in analysing these datasets, moving beyond traditional protein marker identification to encompass a more detailed view of cellular phenotypes and their functional roles. Recent technological advancements allow the simultaneous measurements of multiple cellular components-transcriptome, proteome, chromatin, epigenetic modifications and metabolites-within single cells, including in spatial contexts within tissues. This has led to the generation of complex multiscale datasets that can include multimodal measurements from the same cells or a mix of paired and unpaired modalities. Modern machine learning (ML) techniques allow for the integration of multiple \"omics\" data without the need for extensive independent modelling of each modality. This review focuses on recent advancements in ML integrative approaches applied to immunological studies. We highlight the importance of these methods in creating a unified representation of multiscale data collections, particularly for single-cell and spatial profiling technologies. Finally, we discuss the challenges of these holistic approaches and how they will be instrumental in the development of a common coordinate framework for multiscale studies, thereby accelerating research and enabling discoveries in the computational immunology field.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11165829/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141305763","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":"Multi-dimensional cell-free DNA-based liquid biopsy for sensitive early detection of gastric cancer.","authors":"Pengfei Yu, Ping Chen, Min Wu, Guangyu Ding, Hua Bao, Yian Du, Zhiyuan Xu, Litao Yang, Jingquan Fang, Xingmao Huang, Qian Lai, Jia Wei, Junrong Yan, Shanshan Yang, Peng He, Xue Wu, Yang Shao, Dan Su, Xiangdong Cheng","doi":"10.1186/s13073-024-01352-1","DOIUrl":"10.1186/s13073-024-01352-1","url":null,"abstract":"<p><strong>Background: </strong>Gastric cancer is the fifth most common cancer type. Most patients are diagnosed at advanced stages with poor prognosis. A non-invasive assay for the detection of early-stage gastric cancer is highly desirable for reducing associated mortality.</p><p><strong>Methods: </strong>We collected a prospective study cohort of 110 stage I-II gastric cancer patients and 139 non-cancer individuals. We performed whole-genome sequencing with plasma samples and profiled four types of cell-free DNA (cfDNA) characteristics, fragment size pattern, copy number variation, nucleosome coverage pattern, and single nucleotide substitution. With these differential profiles, we developed an ensemble model to detect gastric cancer signals. Further, we validated the assay in an in-house first validation cohort of 73 gastric cancer patients and 94 non-cancer individuals and an independent second validation cohort of 47 gastric cancer patients and 49 non-cancer individuals. Additionally, we evaluated the assay in a hypothetical 100,000 screening population by Monte Carlo simulation.</p><p><strong>Results: </strong>Our cfDNA-based assay could distinguish early-stage gastric cancer from non-cancer at an AUROC of 0.962 (95% CI: 0.942-0.982) in the study cohort, 0.972 (95% CI: 0.953-0.992) in the first validation cohort and 0.937 (95% CI: 0.890-0.983) in the second validation cohort. The model reached a specificity of 92.1% (128/139) and a sensitivity of 88.2% (97/110) in the study cohort. In the first validation cohort, 91.5% (86/94) of non-cancer individuals and 91.8% (67/73) of gastric cancer patients were correctly identified. In the second validation cohort, 89.8% (44/49) of non-cancer individuals and 87.2% (41/47) of gastric cancer patients were accurately classified.</p><p><strong>Conclusions: </strong>We introduced a liquid biopsy assay using multiple dimensions of cfDNA characteristics that could accurately identify early-stage gastric cancer from non-cancerous conditions. As a cost-effective non-invasive approach, it may provide population-wide benefits for the early detection of gastric cancer.</p><p><strong>Trial registration: </strong>This study was registered on ClinicalTrials.gov under the identifier NCT05269056 on March 7, 2022.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11157707/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141288007","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":"Keeping up with the pathogens: improved antimicrobial resistance detection and prediction from Pseudomonas aeruginosa genomes.","authors":"Danielle E Madden, Timothy Baird, Scott C Bell, Kate L McCarthy, Erin P Price, Derek S Sarovich","doi":"10.1186/s13073-024-01346-z","DOIUrl":"10.1186/s13073-024-01346-z","url":null,"abstract":"<p><strong>Background: </strong>Antimicrobial resistance (AMR) is an intensifying threat that requires urgent mitigation to avoid a post-antibiotic era. Pseudomonas aeruginosa represents one of the greatest AMR concerns due to increasing multi- and pan-drug resistance rates. Shotgun sequencing is gaining traction for in silico AMR profiling due to its unambiguity and transferability; however, accurate and comprehensive AMR prediction from P. aeruginosa genomes remains an unsolved problem.</p><p><strong>Methods: </strong>We first curated the most comprehensive database yet of known P. aeruginosa AMR variants. Next, we performed comparative genomics and microbial genome-wide association study analysis across a Global isolate Dataset (n = 1877) with paired antimicrobial phenotype and genomic data to identify novel AMR variants. Finally, the performance of our P. aeruginosa AMR database, implemented in our AMR detection and prediction tool, ARDaP, was compared with three previously published in silico AMR gene detection or phenotype prediction tools-abritAMR, AMRFinderPlus, ResFinder-across both the Global Dataset and an analysis-naïve Validation Dataset (n = 102).</p><p><strong>Results: </strong>Our AMR database comprises 3639 mobile AMR genes and 728 chromosomal variants, including 75 previously unreported chromosomal AMR variants, 10 variants associated with unusual antimicrobial susceptibility, and 281 chromosomal variants that we show are unlikely to confer AMR. Our pipeline achieved a genotype-phenotype balanced accuracy (bACC) of 85% and 81% across 10 clinically relevant antibiotics when tested against the Global and Validation Datasets, respectively, vs. just 56% and 54% with abritAMR, 58% and 54% with AMRFinderPlus, and 60% and 53% with ResFinder. ARDaP's superior performance was predominantly due to the inclusion of chromosomal AMR variants, which are generally not identified with most AMR identification tools.</p><p><strong>Conclusions: </strong>Our ARDaP software and associated AMR variant database provides an accurate tool for predicting AMR phenotypes in P. aeruginosa, far surpassing the performance of current tools. Implementation of ARDaP for routine AMR prediction from P. aeruginosa genomes and metagenomes will improve AMR identification, addressing a critical facet in combatting this treatment-refractory pathogen. However, knowledge gaps remain in our understanding of the P. aeruginosa resistome, particularly the basis of colistin AMR.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11157771/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141288006","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":"Colorectal cancer microbiome programs DNA methylation of host cells by affecting methyl donor metabolism","authors":"Zhi Liu, Qingqing Zhang, Hong Zhang, Zhongyuan Yi, Huihui Ma, Xiaoyi Wang, Jingjing Wang, Yang Liu, Yi Zheng, Weijia Fang, Ping Huang, Xingyin Liu","doi":"10.1186/s13073-024-01344-1","DOIUrl":"https://doi.org/10.1186/s13073-024-01344-1","url":null,"abstract":"Colorectal cancer (CRC) arises from complex interactions between host and environment, which include the gut and tissue microbiome. It is hypothesized that epigenetic regulation by gut microbiota is a fundamental interface by which commensal microbes dynamically influence intestinal biology. The aim of this study is to explore the interplay between gut and tissue microbiota and host DNA methylation in CRC. Metagenomic sequencing of fecal samples was performed on matched CRC patients (n = 18) and healthy controls (n = 18). Additionally, tissue microbiome was profiled with 16S rRNA gene sequencing on tumor (n = 24) and tumor-adjacent normal (n = 24) tissues of CRC patients, while host DNA methylation was assessed through whole-genome bisulfite sequencing (WGBS) in a subset of 13 individuals. Our analysis revealed substantial alterations in the DNA methylome of CRC tissues compared to adjacent normal tissues. An extensive meta-analysis, incorporating publicly available and in-house data, identified significant shifts in microbial-derived methyl donor-related pathways between tumor and adjacent normal tissues. Of note, we observed a pronounced enrichment of microbial-associated CpGs within the promoter regions of genes in adjacent normal tissues, a phenomenon notably absent in tumor tissues. Furthermore, we established consistent and recurring associations between methylation patterns of tumor-related genes and specific bacterial taxa. This study emphasizes the pivotal role of the gut microbiota and pathogenic bacteria in dynamically shaping DNA methylation patterns, impacting physiological homeostasis, and contributing to CRC tumorigenesis. These findings provide valuable insights into the intricate host-environment interactions in CRC development and offer potential avenues for therapeutic interventions in this disease.","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141254312","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":"Optimizing clinico-genomic disease prediction across ancestries: a machine learning strategy with Pareto improvement.","authors":"Yan Gao, Yan Cui","doi":"10.1186/s13073-024-01345-0","DOIUrl":"10.1186/s13073-024-01345-0","url":null,"abstract":"<p><strong>Background: </strong>Accurate prediction of an individual's predisposition to diseases is vital for preventive medicine and early intervention. Various statistical and machine learning models have been developed for disease prediction using clinico-genomic data. However, the accuracy of clinico-genomic prediction of diseases may vary significantly across ancestry groups due to their unequal representation in clinical genomic datasets.</p><p><strong>Methods: </strong>We introduced a deep transfer learning approach to improve the performance of clinico-genomic prediction models for data-disadvantaged ancestry groups. We conducted machine learning experiments on multi-ancestral genomic datasets of lung cancer, prostate cancer, and Alzheimer's disease, as well as on synthetic datasets with built-in data inequality and distribution shifts across ancestry groups.</p><p><strong>Results: </strong>Deep transfer learning significantly improved disease prediction accuracy for data-disadvantaged populations in our multi-ancestral machine learning experiments. In contrast, transfer learning based on linear frameworks did not achieve comparable improvements for these data-disadvantaged populations.</p><p><strong>Conclusions: </strong>This study shows that deep transfer learning can enhance fairness in multi-ancestral machine learning by improving prediction accuracy for data-disadvantaged populations without compromising prediction accuracy for other populations, thus providing a Pareto improvement towards equitable clinico-genomic prediction of diseases.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11149372/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141247869","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":"Knockout mice with pituitary malformations help identify human cases of hypopituitarism.","authors":"Julian Martinez-Mayer, Michelle L Brinkmeier, Sean P O'Connell, Arnold Ukagwu, Marcelo A Marti, Mirta Miras, Maria V Forclaz, Maria G Benzrihen, Leonard Y M Cheung, Sally A Camper, Buffy S Ellsworth, Lori T Raetzman, Maria I Pérez-Millán, Shannon W Davis","doi":"10.1186/s13073-024-01347-y","DOIUrl":"10.1186/s13073-024-01347-y","url":null,"abstract":"<p><strong>Background: </strong>Congenital hypopituitarism (CH) and its associated syndromes, septo-optic dysplasia (SOD) and holoprosencephaly (HPE), are midline defects that cause significant morbidity for affected people. Variants in 67 genes are associated with CH, but a vast majority of CH cases lack a genetic diagnosis. Whole exome and whole genome sequencing of CH patients identifies sequence variants in genes known to cause CH, and in new candidate genes, but many of these are variants of uncertain significance (VUS).</p><p><strong>Methods: </strong>The International Mouse Phenotyping Consortium (IMPC) is an effort to establish gene function by knocking-out all genes in the mouse genome and generating corresponding phenotype data. We used mouse embryonic imaging data generated by the Deciphering Mechanisms of Developmental Disorders (DMDD) project to screen 209 embryonic lethal and sub-viable knockout mouse lines for pituitary malformations.</p><p><strong>Results: </strong>Of the 209 knockout mouse lines, we identified 51 that have embryonic pituitary malformations. These genes not only represent new candidates for CH, but also reveal new molecular pathways not previously associated with pituitary organogenesis. We used this list of candidate genes to mine whole exome sequencing data of a cohort of patients with CH, and we identified variants in two unrelated cases for two genes, MORC2 and SETD5, with CH and other syndromic features.</p><p><strong>Conclusions: </strong>The screening and analysis of IMPC phenotyping data provide proof-of-principle that recessive lethal mouse mutants generated by the knockout mouse project are an excellent source of candidate genes for congenital hypopituitarism in children.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11140907/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141186251","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":"Variability of polygenic prediction for body mass index in Africa.","authors":"Tinashe Chikowore, Kristi Läll, Lisa K Micklesfield, Zane Lombard, Julia H Goedecke, Segun Fatumo, Shane A Norris, Reedik Magi, Michele Ramsay, Paul W Franks, Guillaume Pare, Andrew P Morris","doi":"10.1186/s13073-024-01348-x","DOIUrl":"10.1186/s13073-024-01348-x","url":null,"abstract":"<p><strong>Background: </strong>Polygenic prediction studies in continental Africans are scarce. Africa's genetic and environmental diversity pose a challenge that limits the generalizability of polygenic risk scores (PRS) for body mass index (BMI) within the continent. Studies to understand the factors that affect PRS variability within Africa are required.</p><p><strong>Methods: </strong>Using the first multi-ancestry genome-wide association study (GWAS) meta-analysis for BMI involving continental Africans, we derived a multi-ancestry PRS and compared its performance to a European ancestry-specific PRS in continental Africans (AWI-Gen study) and a European cohort (Estonian Biobank). We then evaluated the factors affecting the performance of the PRS in Africans which included fine-mapping resolution, allele frequencies, linkage disequilibrium patterns, and PRS-environment interactions.</p><p><strong>Results: </strong>Polygenic prediction of BMI in continental Africans is poor compared to that in European ancestry individuals. However, we show that the multi-ancestry PRS is more predictive than the European ancestry-specific PRS due to its improved fine-mapping resolution. We noted regional variation in polygenic prediction across Africa's East, South, and West regions, which was driven by a complex interplay of the PRS with environmental factors, such as physical activity, smoking, alcohol intake, and socioeconomic status.</p><p><strong>Conclusions: </strong>Our findings highlight the role of gene-environment interactions in PRS prediction variability in Africa. PRS methods that correct for these interactions, coupled with the increased representation of Africans in GWAS, may improve PRS prediction in Africa.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11140909/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141179499","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":"Variant-specific pathophysiological mechanisms of AFF3 differently influence transcriptome profiles.","authors":"Sissy Bassani, Jacqueline Chrast, Giovanna Ambrosini, Norine Voisin, Frédéric Schütz, Alfredo Brusco, Fabio Sirchia, Lydia Turban, Susanna Schubert, Rami Abou Jamra, Jan-Ulrich Schlump, Desiree DeMille, Pinar Bayrak-Toydemir, Gary Rex Nelson, Kristen Nicole Wong, Laura Duncan, Mackenzie Mosera, Christian Gilissen, Lisenka E L M Vissers, Rolph Pfundt, Rogier Kersseboom, Hilde Yttervik, Geir Åsmund Myge Hansen, Marie Falkenberg Smeland, Kameryn M Butler, Michael J Lyons, Claudia M B Carvalho, Chaofan Zhang, James R Lupski, Lorraine Potocki, Leticia Flores-Gallegos, Rodrigo Morales-Toquero, Florence Petit, Binnaz Yalcin, Annabelle Tuttle, Houda Zghal Elloumi, Lane McCormick, Mary Kukolich, Oliver Klaas, Judit Horvath, Marcello Scala, Michele Iacomino, Francesca Operto, Federico Zara, Karin Writzl, Aleš Maver, Maria K Haanpää, Pia Pohjola, Harri Arikka, Anneke J A Kievit, Camilla Calandrini, Christian Iseli, Nicolas Guex, Alexandre Reymond","doi":"10.1186/s13073-024-01339-y","DOIUrl":"10.1186/s13073-024-01339-y","url":null,"abstract":"<p><strong>Background: </strong>We previously described the KINSSHIP syndrome, an autosomal dominant disorder associated with intellectual disability (ID), mesomelic dysplasia and horseshoe kidney, caused by de novo variants in the degron of AFF3. Mouse knock-ins and overexpression in zebrafish provided evidence for a dominant-negative mode of action, wherein an increased level of AFF3 resulted in pathological effects.</p><p><strong>Methods: </strong>Evolutionary constraints suggest that other modes-of-inheritance could be at play. We challenged this hypothesis by screening ID cohorts for individuals with predicted-to-be damaging variants in AFF3. We used both animal and cellular models to assess the deleteriousness of the identified variants.</p><p><strong>Results: </strong>We identified an individual with a KINSSHIP-like phenotype carrying a de novo partial duplication of AFF3 further strengthening the hypothesis that an increased level of AFF3 is pathological. We also detected seventeen individuals displaying a milder syndrome with either heterozygous Loss-of-Function (LoF) or biallelic missense variants in AFF3. Consistent with semi-dominance, we discovered three patients with homozygous LoF and one compound heterozygote for a LoF and a missense variant, who presented more severe phenotypes than their heterozygous parents. Matching zebrafish knockdowns exhibit neurological defects that could be rescued by expressing human AFF3 mRNA, confirming their association with the ablation of aff3. Conversely, some of the human AFF3 mRNAs carrying missense variants identified in affected individuals did not rescue these phenotypes. Overexpression of mutated AFF3 mRNAs in zebrafish embryos produced a significant increase of abnormal larvae compared to wild-type overexpression further demonstrating deleteriousness. To further assess the effect of AFF3 variation, we profiled the transcriptome of fibroblasts from affected individuals and engineered isogenic cells harboring + / + , KINSSHIP/KINSSHIP, LoF/ + , LoF/LoF or KINSSHIP/LoF AFF3 genotypes. The expression of more than a third of the AFF3 bound loci is modified in either the KINSSHIP/KINSSHIP or the LoF/LoF lines. While the same pathways are affected, only about one third of the differentially expressed genes are common to the homozygote datasets, indicating that AFF3 LoF and KINSSHIP variants largely modulate transcriptomes differently, e.g. the DNA repair pathway displayed opposite modulation.</p><p><strong>Conclusions: </strong>Our results and the high pleiotropy shown by variation at this locus suggest that minute changes in AFF3 function are deleterious.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":10.4,"publicationDate":"2024-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11137988/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141174291","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}