Frontiers in Genetics最新文献

{"title":"Genetic etiology of autism spectrum disorder in the African population: a scoping review.","authors":"Olivier Hakizimana, Janvier Hitayezu, Jeanne P Uyisenga, Hope Onohuean, Leonor Palmeira, Vincent Bours, Abdullateef Isiaka Alagbonsi, Annette Uwineza","doi":"10.3389/fgene.2024.1431093","DOIUrl":"10.3389/fgene.2024.1431093","url":null,"abstract":"<p><strong>Background: </strong>Autism spectrum disorder (ASD) is a neurodevelopmental disorder (NDD) characterized by significant impairments in social, communicative, and behavioral abilities. However, only a limited number of studies address the genetic basis of ASD in the African population. This study aims to document the genes associated with ASD in Africa and the techniques used to identify them. Additionally, genes identified elsewhere but not yet in Africa are also noted.</p><p><strong>Methods: </strong>Online databases such as Wiley Online Library, PubMed, and Africa Journal Online were used. The review was conducted using the keyword related to genetic and genomic ASD study in the African population.</p><p><strong>Result: </strong>In this scoping review, 40 genetic studies on ASD in Africa were reviewed. The Egyptian and South African populations were the most studied, with 25 and 5 studies, respectively. Countries with fewer studies included Tunisia (4), East African countries (3), Libya (1), Nigeria (1), and Morocco (1). Some 61 genes responsible for ASD were identified in the African population: 26 were identified using a polymerase chain reaction (PCR)-based method, 22 were identified using sequencing technologies, and 12 genes and one <i>de novo</i> chromosomal aberration were identified through other techniques. No African study identified any ASD gene with genome-wide association studies (GWAS). Notably, at least 20 ASD risk genes reported in non-African countries were yet to be confirmed in Africa's population.</p><p><strong>Conclusion: </strong>There are insufficient genetic studies on ASD in the African population, with sample size being a major limitation in most genetic association studies, leading to inconclusive results. Thus, there is a need to conduct more studies with large sample sizes to identify other genes associated with ASD in Africa's population using high-throughput sequencing technology.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11464363/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142400115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Case report: Two siblings with very late onset of holocarboxylase synthase deficiency and a mini-review.","authors":"Margaux Gaschignard, Louis Domenach, Delphine Lamireau, Claire Guibet, Sandrine Roche, Emmanuel Richard, Isabelle Redonnet-Vernhet, Samir Mesli, Louis Lebreton","doi":"10.3389/fgene.2024.1249480","DOIUrl":"10.3389/fgene.2024.1249480","url":null,"abstract":"<p><p>Holocarboxylase synthase (HCS) deficiency is an extremely rare metabolic disorder typically presenting as severe neonatal metabolic acidosis, lethargy, hypotonia, vomiting, and seizures. This report describes two siblings in a family with late-onset forms of HCS deficiency. The younger sister presented at the age of 11 years and manifested as acute metabolic acidosis, which promptly resolved following rehydration and biotin administration. The results of the organic urine profile confirmed multiple carboxylase deficiency, and genetic testing revealed a novel pathogenic variant in the <i>HLCS</i> gene (NM_000411.8) in the homozygous state: c.995A>G; p. (Gln332Arg). No further decompensation was observed for her during the 3-year follow-up period. His older brother was diagnosed at the age of 23 years-old through biochemical tests, without any history of acidotic decompensation. A mini-review of HCS deficiency with late onset (>1 year) or early onset (<1 month) revealed that splice variants are associated with late onset, while both variants p. (Leu216Arg) and p. (Leu237Pro) are associated with early onset. However, the majority of genotypes do not show a clear correlation with the timing of HCS deficiency onset. The most significant point here is the description of extremely late-onset cases of HCS deficiency. This can prompt metabolic investigations and raise suspicion of this rare disease in cases of unexplained metabolic acidosis, even beyond early childhood.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11464450/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142400113","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cell type specification and diversity in subpallial organoids.","authors":"Narciso Pavon, Yubing Sun, ChangHui Pak","doi":"10.3389/fgene.2024.1440583","DOIUrl":"10.3389/fgene.2024.1440583","url":null,"abstract":"<p><p>Neural organoids have emerged as valuable tools for studying the developing brain, sparking enthusiasm and driving their adoption in disease modeling, drug screening, and investigating fetal neural development. The increasing popularity of neural organoids as models has led to a wide range of methodologies aimed at continuous improvement and refinement. Consequently, research groups often improve and reconfigure protocols to create region-specific organoids, resulting in diverse phenotypes, including variations in morphology, gene expression, and cell populations. While these improvements are exciting, routine adoptions of such modifications and protocols in the research laboratories are often challenging due to the reiterative empirical testing necessary to validate the cell types generated. To address this challenge, we systematically compare the similarities and differences that exist across published protocols that generates subpallial-specific organoids to date. In this review, we focus specifically on exploring the production of major GABAergic neuronal subtypes, especially Medium Spiny Neurons (MSNs) and Interneurons (INs), from multiple subpallial organoid protocols. Importantly, we look to evaluate the cell type diversity and the molecular pathways manipulated to generate them, thus broadening our understanding of the existing subpallial organoids as well as assessing the <i>in vitro</i> applicability of specific patterning factors. Lastly, we discuss the current challenges and outlook on the improved patterning of region-specific neural organoids. Given the critical roles MSN and IN dysfunction play in neurological disorders, comprehending the GABAergic neurons generated by neural organoids will undoubtedly facilitate clinical translation.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11465425/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142400114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating transcriptomics, eQTL, and Mendelian randomization to dissect monocyte roles in severe COVID-19 and gout flare.","authors":"Jiajia Li, Guixian Yang, Junnan Liu, Guofeng Li, Huiling Zhou, Yuan He, Xinru Fei, Dongkai Zhao","doi":"10.3389/fgene.2024.1385316","DOIUrl":"10.3389/fgene.2024.1385316","url":null,"abstract":"<p><strong>Introduction: </strong>There are considerable similarities between the pathophysiology of gout flare and the dysregulated inflammatory response in severe COVID-19 infection. Monocytes are the key immune cells involved in the pathogenesis of both diseases. Therefore, it is critical to elucidate the molecular basis of the function of monocytes in gout and COVID-19 in order to develop more effective therapeutic approaches.</p><p><strong>Methods: </strong>The single-cell RNA sequencing (scRNA-seq), large-scale genome-wide association studies (GWAS), and expression quantitative trait loci (eQTL) data of gout and severe COVID-19 were comprehensively analyzed. Cellular heterogeneity and intercellular communication were identified using the scRNA-seq datasets, and the monocyte-specific differentially expressed genes (DEGs) between COVID-19, gout and normal subjects were screened. In addition, the correlation of the DEGs with severe COVID-19 and gout flare was analyzed through GWAS statistics and eQTL data.</p><p><strong>Results: </strong>The scRNA-seq analysis exhibited that the proportion of classical monocytes was increased in both severe COVID-19 and gout patient groups compared to healthy controls. Differential expression analysis and MR analysis showed that <i>NLRP3</i> was positively associated with the risk of severe COVID-19 and involved 11 SNPs, of which rs4925547 was not significantly co-localized. In contrast, <i>IER3</i> was positively associated with the risk of gout and involved 9 SNPs, of which rs1264372 was significantly co-localized.</p><p><strong>Discussion: </strong>Monocytes have a complex role in gout flare and severe COVID-19, which underscores the potential mechanisms and clinical significance of the interaction between the two diseases.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11461236/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142389833","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Editorial: Application of novel statistical and machine-learning methods to high-dimensional clinical cancer and (multi-) omics data volume II.","authors":"Chao Xu, Shaolong Cao, Md Ashad Alam","doi":"10.3389/fgene.2024.1487893","DOIUrl":"https://doi.org/10.3389/fgene.2024.1487893","url":null,"abstract":"","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11461318/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142389831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quantifying uncertainty of molecular mismatch introduced by mislabeled ancestry using haplotype-based HLA genotype imputation.","authors":"Benedict M Matern, Eric Spierings, Selle Bandstra, Abeer Madbouly, Stefan Schaub, Eric T Weimer, Matthias Niemann","doi":"10.3389/fgene.2024.1444554","DOIUrl":"10.3389/fgene.2024.1444554","url":null,"abstract":"<p><strong>Introduction: </strong>Modern histocompatibility algorithms depend on the comparison and analysis of high-resolution HLA protein sequences and structures, especially when considering epitope-based algorithms, which aim to model the interactions involved in antibody or T cell binding. HLA genotype imputation can be performed in the cases where only low/intermediate-resolution HLA genotype is available or if specific loci are missing, and by providing an individuals' race/ethnicity/ancestry information, imputation results can be more accurate. This study assesses the effect of imputing high-resolution genotypes on molecular mismatch scores under a variety of ancestry assumptions.</p><p><strong>Methods: </strong>We compared molecular matching scores from \"ground-truth\" high-resolution genotypes against scores from genotypes which are imputed from low-resolution genotypes. Analysis was focused on a simulated patient-donor dataset and confirmed using two real-world datasets, and deviations were aggregated based on various ancestry assumptions.</p><p><strong>Results: </strong>We observed that using multiple imputation generally results in lower error in molecular matching scores compared to single imputation, and that using the correct ancestry assumptions can reduce error introduced during imputation.</p><p><strong>Discussion: </strong>We conclude that for epitope analysis, imputation is a valuable and low-risk strategy, as long as care is taken regarding epitope analysis context, ancestry assumptions, and (multiple) imputation strategy.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11461215/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142389838","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Whole-genome sequencing reveals rare variants associated with gout in Taiwanese males.","authors":"Yu-Ping Tseng, Ya-Sian Chang, Venugopala R Mekala, Ting-Yuan Liu, Jan-Gowth Chang, Grace S Shieh","doi":"10.3389/fgene.2024.1423714","DOIUrl":"10.3389/fgene.2024.1423714","url":null,"abstract":"<p><p>To identify rare variants (RVs) of gout, we sequenced the whole genomes of 321 male gout patients and combined these with those of 64 male gout patients and 682 normal controls at Taiwan Biobank. We performed ACAT-O to identify 682 significant RVs (<i>p</i> < 3.8 × 10^-8) clustered on chromosomes 1, 7, 10, 16, and 18. To prioritize causal variants effectively, we sifted them by Combined Annotation-Dependent Depletion score >10 or |effect size| ≥ 1.5 for those without CADD scores. In particular, to the best of our knowledge, we identified the rare variants rs559954634, rs186763678, and 13-85340782-G-A for the first time to be associated with gout in Taiwanese males. Importantly, the RV rs559954634 positively affects gout, and its neighboring gene <i>NPHS2</i> is involved in serum urate and expressed in kidney tissues. The kidneys play a major role in regulating uric acid levels. This suggests that rs559954634 may be involved in gout. Furthermore, rs186763678 is in the intron of <i>NFIA</i> that interacts with <i>SLC2A9,</i> which has the most significant effect on serum urate. Note that gene-gene interaction <i>NFIA-SLC2A9</i> is significantly associated with serum urate in the Italian MICROS population and a Croatian population. Moreover, 13-85340782-G-A significantly affects gout susceptibility (odds ratio 6.0; <i>P</i> = 0.038). The >1% carrier frequencies of these potentially pathogenic (protective) RVs in cases (controls) suggest the revealed associations may be true; these RVs deserve further studies for the mechanism. Finally, multivariate logistic regression analysis shows that the rare variants rs559954634 and 13-85340782-G-A jointly are significantly associated with gout susceptibility.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11462091/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142389841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Personality and <i>COMT</i> gene: molecular-genetic and epigenetic associations with NEO-PI-R personality domains and facets in monozygotic twins.","authors":"Dušanka Mitrović, Snežana Smederevac, Lissette Delgado-Cruzata, Selka Sadiković, Dejan Pajić, Mechthild Prinz, Zoran Budimlija, Milan Oljača, Jelena Kušić-Tišma, Nataša Vučinić, Aleksandra Milutinović","doi":"10.3389/fgene.2024.1455872","DOIUrl":"10.3389/fgene.2024.1455872","url":null,"abstract":"<p><strong>Background: </strong>This study investigates the relationship between <i>MB-COMT</i> DNA methylation (DNAm) and the personality traits outlined in the NEO-PI-R model through an epigenetic study of monozygotic twins. DNAm, a critical epigenetic mechanism, regulates gene expression and has been linked to various biological processes and disorders. By leveraging the genetic similarities of monozygotic twins, this research explores how epigenetic variations influenced by environmental factors correlate with personality differences.</p><p><strong>Methods: </strong>The study utilized the Five-Factor Model (FFM) to categorize personality traits into five domains: Neuroticism, Extraversion, Conscientiousness, Agreeableness, and Openness to Experience. Each domain comprises six facets, providing a granular view of personality. The research centered on the catechol-O-methyltransferase (<i>COMT</i>) gene, focusing on its role in dopamine metabolism, which is hypothesized to influence personality traits through the dopaminergic system. DNAm status in the MB-COMT promoter region was examined to determine its association with personality facets.</p><p><strong>Results: </strong>Preliminary findings suggest a complex interaction between <i>MB-COMT</i> DNAm patterns and personality traits. Specific methylation patterns at different CpG sites were linked to varying expressions of traits such as impulsivity and aggression, highlighting the nuanced impact of epigenetics on personality.</p><p><strong>Conclusion: </strong>This study underscores the potential of integrating genetic, epigenetic, and environmental data to enhance our understanding of personality formation. The results contribute to a broader understanding of how genetic predispositions shaped by environmental factors manifest in complex trait differences, paving the way for future research in genetic psychiatry and personalized medicine.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11461223/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142389835","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ML-GAP: machine learning-enhanced genomic analysis pipeline using autoencoders and data augmentation.","authors":"Melih Agraz, Dincer Goksuluk, Peng Zhang, Bum-Rak Choi, Richard T Clements, Gaurav Choudhary, George Em Karniadakis","doi":"10.3389/fgene.2024.1442759","DOIUrl":"https://doi.org/10.3389/fgene.2024.1442759","url":null,"abstract":"<p><strong>Introduction: </strong>The advent of RNA sequencing (RNA-Seq) has significantly advanced our understanding of the transcriptomic landscape, revealing intricate gene expression patterns across biological states and conditions. However, the complexity and volume of RNA-Seq data pose challenges in identifying differentially expressed genes (DEGs), critical for understanding the molecular basis of diseases like cancer.</p><p><strong>Methods: </strong>We introduce a novel Machine Learning-Enhanced Genomic Data Analysis Pipeline (ML-GAP) that incorporates autoencoders and innovative data augmentation strategies, notably the MixUp method, to overcome these challenges. By creating synthetic training examples through a linear combination of input pairs and their labels, MixUp significantly enhances the model's ability to generalize from the training data to unseen examples.</p><p><strong>Results: </strong>Our results demonstrate the ML-GAP's superiority in accuracy, efficiency, and insights, particularly crediting the MixUp method for its substantial contribution to the pipeline's effectiveness, advancing greatly genomic data analysis and setting a new standard in the field.</p><p><strong>Discussion: </strong>This, in turn, suggests that ML-GAP has the potential to perform more accurate detection of DEGs but also offers new avenues for therapeutic intervention and research. By integrating explainable artificial intelligence (XAI) techniques, ML-GAP ensures a transparent and interpretable analysis, highlighting the significance of identified genetic markers.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11467662/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142463224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TimeNorm: a novel normalization method for time course microbiome data.","authors":"Qianwen Luo, Meng Lu, Hamza Butt, Nicholas Lytal, Ruofei Du, Hongmei Jiang, Lingling An","doi":"10.3389/fgene.2024.1417533","DOIUrl":"https://doi.org/10.3389/fgene.2024.1417533","url":null,"abstract":"<p><p>Metagenomic time-course studies provide valuable insights into the dynamics of microbial systems and have become increasingly popular alongside the reduction in costs of next-generation sequencing technologies. Normalization is a common but critical preprocessing step before proceeding with downstream analysis. To the best of our knowledge, currently there is no reported method to appropriately normalize microbial time-series data. We propose TimeNorm, a novel normalization method that considers the compositional property and time dependency in time-course microbiome data. It is the first method designed for normalizing time-series data within the same time point (intra-time normalization) and across time points (bridge normalization), separately. Intra-time normalization normalizes microbial samples under the same condition based on common dominant features. Bridge normalization detects and utilizes a group of most stable features across two adjacent time points for normalization. Through comprehensive simulation studies and application to a real study, we demonstrate that TimeNorm outperforms existing normalization methods and boosts the power of downstream differential abundance analysis.</p>","PeriodicalId":12750,"journal":{"name":"Frontiers in Genetics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2024-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11458461/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142389839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}