Human Genetics最新文献

{"title":"Assessing the predicted impact of single amino acid substitutions in calmodulin for CAGI6 challenges.","authors":"Paola Turina, Giuditta Dal Cortivo, Carlos A Enriquez Sandoval, Emil Alexov, David B Ascher, Giulia Babbi, Constantina Bakolitsa, Rita Casadio, Piero Fariselli, Lukas Folkman, Akash Kamandula, Panagiotis Katsonis, Dong Li, Olivier Lichtarge, Pier Luigi Martelli, Shailesh Kumar Panday, Douglas E V Pires, Stephanie Portelli, Fabrizio Pucci, Carlos H M Rodrigues, Marianne Rooman, Castrense Savojardo, Martin Schwersensky, Yang Shen, Alexey V Strokach, Yuanfei Sun, Junwoo Woo, Predrag Radivojac, Steven E Brenner, Daniele Dell'Orco, Emidio Capriotti","doi":"10.1007/s00439-024-02720-y","DOIUrl":"10.1007/s00439-024-02720-y","url":null,"abstract":"<p><p>Recent thermodynamic and functional studies have been conducted to evaluate the impact of amino acid substitutions on Calmodulin (CaM). The Critical Assessment of Genome Interpretation (CAGI) data provider at University of Verona (Italy) measured the melting temperature (T_m) and the percentage of unfolding (%unfold) of a set of CaM variants (CaM challenge dataset). Thermodynamic measurements for the equilibrium unfolding of CaM were obtained by monitoring far-UV Circular Dichroism as a function of temperature. These measurements were used to determine the T_m and the percentage of protein remaining unfolded at the highest temperature. The CaM challenge dataset, comprising a total of 15 single amino acid substitutions, was used to evaluate the effectiveness of computational methods in predicting the T_m and unfolding percentages associated with the variants, and categorizing them as destabilizing or not. For the sixth edition of CAGI, nine independent research groups from four continents (Asia, Australia, Europe, and North America) submitted over 52 sets of predictions, derived from various approaches. In this manuscript, we summarize the results of our assessment to highlight the potential limitations of current algorithms and provide insights into the future development of more accurate prediction tools. By evaluating the thermodynamic stability of CaM variants, this study aims to enhance our understanding of the relationship between amino acid substitutions and protein stability, ultimately contributing to more accurate predictions of the effects of genetic variants.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":" ","pages":"113-125"},"PeriodicalIF":3.8,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11975486/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An augmented transformer model trained on protein family specific variant data leads to improved prediction of variants of uncertain significance.","authors":"Dinesh Joshi, Swatantra Pradhan, Rakshanda Sajeed, Rajgopal Srinivasan, Sadhna Rana","doi":"10.1007/s00439-025-02727-z","DOIUrl":"10.1007/s00439-025-02727-z","url":null,"abstract":"<p><p>Variants of uncertain significance (VUS) represent variants that lack sufficient evidence to be confidently associated with a disease, thus posing a challenge in the interpretation of genetic testing results. Here we report an improved method for predicting the VUS of Arylsulfatase A (ARSA) gene as part of the Critical Assessment of Genome Interpretation challenge (CAGI6). Our method uses a transfer learning approach that leverages a pre-trained protein language model to predict the impact of mutations on the activity of the ARSA enzyme, whose deficiency is known to cause a rare genetic disorder, metachromatic leukodystrophy. Our innovative framework combines zero-shot log odds scores and embeddings from the ESM, an evolutionary scale model as features for training a supervised model on gene variants functionally related to the ARSA gene. The zero-shot log odds score feature captures the generic properties of the proteins learned due to its pre-training on millions of sequences in the UniProt data, while the ESM embeddings for the proteins in the ARSA family capture features specific to the family. We also tested our approach on another enzyme, N-acetyl-glucosaminidase (NAGLU), that belongs to the same superfamily as ARSA. Our results demonstrate that the performance of our family models (augmented ESM models) is either comparable or better than the ESM models. The ARSA model compares favorably with the majority of state-of-the-art predictors on area under precision and recall curve (AUPRC) performance metric. However, the NAGLU model outperforms all pathogenicity predictors evaluated in this study on AUPRC metric. The improved AUPRC has relevance in a diagnostic setting where variant prioritization generally entails identifying a small number of pathogenic variants from a larger number of benign variants. Our results also indicate that genes that have sparse or no experimental variant impact data, the family variant data can serve as a proxy training data for making accurate predictions. Attention analysis of active sites and binding sites in ARSA and NAGLU proteins shed light on probable mechanisms of pathogenicity for positions that are highly attended.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":" ","pages":"143-158"},"PeriodicalIF":3.8,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12166291/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143046678","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrative analysis of transcriptome and proteome wide association studies prioritized functional genes for obesity.","authors":"Qi-Gang Zhao, Xin-Ling Ma, Qian Xu, Zi-Tong Song, Fan Bu, Kuan Li, Bai-Xue Han, Shan-Shan Yan, Lei Zhang, Yuan Luo, Yu-Fang Pei","doi":"10.1007/s00439-024-02714-w","DOIUrl":"10.1007/s00439-024-02714-w","url":null,"abstract":"<p><strong>Background: </strong>Genome-wide association studies have identified dozens of genomic loci for obesity. However, functional genes and their detailed genetic mechanisms underlying these loci are mainly unknown. In this study, we conducted an integrative study to prioritize plausibly functional genes by combining information from genome-, transcriptome- and proteome-wide association analyses.</p><p><strong>Methods: </strong>We first conducted proteome-wide association analyses and transcriptome-wide association analyses for the six obesity-related traits. We then performed colocalization analysis on the identified loci shared between the proteome- and transcriptome-association analyses. Finally, we validated the identified genes with other plasma/blood reference panels. The highlighted genes were assessed for expression of other tissues, single-cell and tissue specificity, and druggability.</p><p><strong>Results: </strong>We prioritized 4 high-confidence genes (FASN, ICAM1, PDCD6IP, and YWHAB) by proteome-wide association studies, transcriptome-wide association studies, and colocalization analyses, which consistently influenced the variation of obesity traits at both mRNA and protein levels. These 4 genes were successfully validated using other plasma/blood reference panels. These 4 genes shared regulatory structures in obesity-related tissues. Single-cell and tissue-specific analyses showed that FASN and ICAM1 were explicitly expressed in metabolism- and immunity-related tissues and cells. Furthermore, FASN and ICAM1 had been developed as drug targets.</p><p><strong>Conclusion: </strong>Our study provided novel promising protein targets for further mechanistic and therapeutic studies of obesity.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":" ","pages":"31-41"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142568057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrating transcriptomic and polygenic risk scores to enhance predictive accuracy for ischemic stroke subtypes.","authors":"Xuehong Cai, Haochang Li, Xiaoxiao Cao, Xinyan Ma, Wenhao Zhu, Lei Xu, Sheng Yang, Rongbin Yu, Peng Huang","doi":"10.1007/s00439-024-02717-7","DOIUrl":"10.1007/s00439-024-02717-7","url":null,"abstract":"<p><p>Ischemic stroke (IS), characterized by complex etiological diversity, is a significant global health challenge. Recent advancements in genome-wide association studies (GWAS) and transcriptomic profiling offer promising avenues for enhanced risk prediction and understanding of disease mechanisms. GWAS summary statistics from the GIGASTROKE Consortium and genetic and phenotypic data from the UK Biobank (UKB) were used. Transcriptome-Wide Association Studies (TWAS) were conducted using FUSION to identify genes associated with IS and its subtypes across eight tissues. Colocalization analysis identified shared genetic variants influencing both gene expression and disease risk. Sum Transcriptome-Polygenic Risk Scores (STPRS) models were constructed by combining polygenic risk scores (PRS) and polygenic transcriptome risk scores (PTRS) using logistic regression. The predictive performance of STPRS was evaluated using the area under the curve (AUC). A Phenome-wide association study (PheWAS) explored associations between STPRS and various phenotypes. TWAS identified 34 susceptibility genes associated with IS and its subtypes. Colocalization analysis revealed 18 genes with a posterior probability (PP) H4 > 75% for joint expression quantitative trait loci (eQTL) and GWAS associations, highlighting their genetic relevance. The STPRS models demonstrated superior predictive accuracy compared to conventional PRS, showing significant associations with numerous UKB phenotypes, including atrial fibrillation and blood pressure. Integrating transcriptomic data with polygenic risk scores through STPRS enhances predictive accuracy for IS and its subtypes. This approach refines our understanding of the genetic and molecular landscape of stroke and paves the way for tailored preventive and therapeutic strategies.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":" ","pages":"43-54"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142647531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetic landscape in undiagnosed patients with syndromic hearing loss revealed by whole exome sequencing and phenotype similarity search.","authors":"Hideki Mutai, Fuyuki Miya, Kiyomitsu Nara, Nobuko Yamamoto, Satomi Inoue, Haruka Murakami, Kazunori Namba, Hiroshi Shitara, Shujiro Minami, Atsuko Nakano, Yukiko Arimoto, Noriko Morimoto, Taiji Kawasaki, Koichiro Wasano, Masato Fujioka, Yasue Uchida, Kimitaka Kaga, Kazuki Yamazawa, Yoshiaki Kikkawa, Kenjiro Kosaki, Tatsuhiko Tsunoda, Tatsuo Matsunaga","doi":"10.1007/s00439-024-02719-5","DOIUrl":"10.1007/s00439-024-02719-5","url":null,"abstract":"<p><p>There are hundreds of rare syndromic diseases involving hearing loss, many of which are not targeted for clinical genetic testing. We systematically explored the genetic causes of undiagnosed syndromic hearing loss using a combination of whole exome sequencing (WES) and a phenotype similarity search system called PubCaseFinder. Fifty-five families with syndromic hearing loss of unknown cause were analyzed using WES after prescreening of several deafness genes depending on patient clinical features. Causative genes were identified in 22 families, including both established genes associated with syndromic hearing loss (PTPN11, CHD7, KARS1, OPA1, DLX5, MITF, SOX10, MYO7A, and USH2A) and those associated with nonsyndromic hearing loss (STRC, EYA4, and KCNQ4). Association of a DLX5 variant with incomplete partition type I (IP-I) anomaly of the inner ear was identified in a patient with cleft lip and palate and acetabular dysplasia. The study identified COL1A1, CFAP52, and NSD1 as causative genes through phenotype similarity search or by analogy. ZBTB10 was proposed as a novel candidate gene for syndromic hearing loss with IP-I. A mouse model with homozygous Zbtb10 frameshift variant resulted in embryonic lethality, suggesting the importance of this gene for early embryonic development. Our data highlight a wide spectrum of rare causative genes in patients with syndromic hearing loss, and demonstrate that WES analysis combined with phenotype similarity search is a valuable approach for clinical genetic testing of undiagnosed disease.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":" ","pages":"93-112"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142927239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The obesity-related mutation gene on nonalcoholic fatty liver disease.","authors":"Yen-Yu Chen, Chi-Sheng Chen, Jee-Fu Huang, Wen-Hsiu Su, Chia-Yang Li, Wei-Shiun Chen, En-Sheng Lin, Wan-Long Chuang, Ming-Lung Yu, Shu-Chi Wang","doi":"10.1007/s00439-024-02686-x","DOIUrl":"10.1007/s00439-024-02686-x","url":null,"abstract":"<p><p>The prevalence of overweight and obesity is increasing, leading to metabolic-associated fatty liver disease (MAFLD) characterized by excessive accumulation of liver fat and a risk of developing hepatocellular carcinoma (HCC). The driver gene mutations may play the roles of passengers that occur in single 'hotspots' and can promote tumorigenesis from benign to malignant lesions. We investigated the impact of high body weight and BMI on HCC survival using The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) dataset. To explore the effects of obesity-related gene mutations on HCC, we collected driver mutation genes in 34 TCGA patients with BMI ≥ 27 and 23 TCGA patients with BMI < 27. The digital PCR performing the PBMC samples for the variant rate by clinical cohort of 96 NAFLD patients. Our analysis showed that obesity leads to significantly worse survival outcomes in HCC. Using cbioportal, we identified 414 driver mutation genes in patients with obesity and 127 driver mutation genes in non-obese patients. Functional analysis showed that obese-related genes significantly enriched the regulated lipid and insulin pathways in HCC. The insulin secretion pathway in patients with obesity HCC-specific survival identified ABCC8 and PRKCB as significant genes (p < 0.001). It revealed significant differences in gene mutation and gene expression profiles compared to non-obese patients. The digital PCR test ABCC8 variants were detected in PBMC samples and caused a 14.5% variant rate, significantly higher than that of non-obese NAFLD patients. The study findings showed that the gene ABCC8 was a patient with the obesity-related gene in NAFLD, which provides the probability that ABCC8 mutation contributes to the pre-cancer lesion biomarker for HCC.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":" ","pages":"1-14"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141563310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"T1R2/T1R3 polymorphism affects sweet and fat perception: Correlation between SNP and BMI in the context of obesity development.","authors":"Vinithra Ponnusamy, Gowtham Subramanian, Keerthana Vasanthakumar, Karthi Muthuswamy, Prabha Panneerselvan, Vasanth Krishnan, Selvakumar Subramaniam","doi":"10.1007/s00439-024-02690-1","DOIUrl":"10.1007/s00439-024-02690-1","url":null,"abstract":"<p><p>Genetic variations in taste receptors are associated with gustatory perception and obesity, which in turn affects dietary preferences. Given the increasing tendency of people with obesity choosing sweet, high-fat meals, the current study assessed the cross-regulation of two polymorphisms of the sweet taste receptor (T1R2/T1R3), rs35874116 and rs307355, on fat sensitivity in Indian adults. We investigated the association between taste sensitivity and BMI in the T1R2, T1R3, and CD36 polymorphic and non-polymorphic groups. The general labelled magnitude scale (gLMS) was used to assess the taste sensitivity of 249 participants in addition to anthropometric data. TaqMan Probe-based RT-PCR was employed to determine the polymorphisms. Additionally, the colorimetric method utilizing 3, 5-dinitro salicylic acid was used to evaluate the participants' salivary amylase activity. The mean detection thresholds for linoleic acid (LA) and sucrose were greater in individuals with obesity (i.e., 0.97 ± 0.08 mM and 0.22 ± 0.02 M, respectively) than in healthy adults (p < 0.0001), indicating lower sensitivity. Moreover, it was found that a greater proportion of persons with obesity fall into the polymorphic groups (i.e., 52% with genotype CD36 AA, 44% with genotype T1R2 CC, and 40% with genotype T1R3 TT). All three single nucleotide polymorphisms support the Hardy-Weinberg equilibrium (p = 0.78). The Pearson correlation analysis between LA and the sucrose detection threshold revealed a significant (p < 0.0001) positive relationship with an r value of 0.5299. Moreover, salivary amylase activity was significantly (p < 0.05) higher in the polymorphic sub-groups. The results of our study imply that genetic variations in T1R2/T1R3 receptors affect perception of both sweetness and fat, which may have an effect on obesity.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":" ","pages":"15-30"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141897334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Further evidence of biallelic NAV3 variants associated with recessive neurodevelopmental disorder with dysmorphism, developmental delay, intellectual disability, and behavioral abnormalities.","authors":"Naseebullah Kakar, Selinda Mascarenhas, Asmat Ali, Azmatullah, Syed M Ijlal Haider, Vaishnavi Ashok Badiger, Mobina Shadman Ghofrani, Nathalie Kruse, Sohana Nadeem Hashmi, Jelena Pozojevic, Saranya Balachandran, Mathias Toft, Sajid Malik, Kristian Händler, Ambrin Fatima, Zafar Iqbal, Anju Shukla, Malte Spielmann, Periyasamy Radhakrishnan","doi":"10.1007/s00439-024-02718-6","DOIUrl":"10.1007/s00439-024-02718-6","url":null,"abstract":"<p><p>Neuron navigators (NAVs) are cytoskeleton-associated proteins well known for their role in axonal guidance, neuronal migration, and neurite growth necessary for neurodevelopment. Neuron navigator 3 (NAV3) is one of the three NAV proteins highly expressed in the embryonic and adult brain. However, the role of the NAV3 gene in human disease is not well-studied. Recently, five bi-allelic and three mono-allelic variants in NAV3 were reported in 12 individuals from eight unrelated families with neurodevelopmental disorder (NDD). Here, we report five patients from three unrelated consanguineous families segregating autosomal recessive NDD. Patients have symptoms of dysmorphism, intellectual disability, developmental delay, and behavioral abnormalities. Exome sequencing (ES) was performed on two affected individuals from one large family, and one affected individual from each of the other two families. ES revealed two homozygous nonsense c.6325C > T; p.(Gln2109Ter) and c.6577C > T; p.(Arg2193Ter) and a homozygous splice site (c.243 + 1G > T) variants in the NAV3 (NM_001024383.2). Analysis of single-cell sequencing datasets from embryonic and young adult human brains revealed that NAV3 is highly expressed in the excitatory neurons, inhibitory neurons, and microglia, consistent with its role in neurodevelopment. In conclusion, in this study, we further validate biallelic protein truncating variants in NAV3 as a cause of NDD, expanding the spectrum of pathogenic variants in this newly discovered NDD gene.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":" ","pages":"55-65"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11754320/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142871876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A genome-wide scan of non-coding RNAs and enhancers for refractive error and myopia.","authors":"Milly S Tedja, Joanna Swierkowska-Janc, Clair A Enthoven, Magda A Meester-Smoor, Pirro G Hysi, Janine F Felix, Cameron S Cowan, Timothy J Cherry, Peter J van der Spek, Mohsen Ghanbari, Stefan J Erkeland, Tahsin Stefan Barakat, Caroline C W Klaver, Virginie J M Verhoeven","doi":"10.1007/s00439-024-02721-x","DOIUrl":"10.1007/s00439-024-02721-x","url":null,"abstract":"<p><p>Refractive error (RE) and myopia are complex polygenic conditions with the majority of genome-wide associated genetic variants in non-exonic regions. Given this, and the onset during childhood, gene-regulation is expected to play an important role in its pathogenesis. This prompted us to explore beyond traditional gene finding approaches. We performed a genetic association study between variants in non-coding RNAs and enhancers, and RE and myopia. We obtained single-nucleotide polymorphisms (SNPs) in microRNA (miRNA) genes, miRNA-binding sites, long non-coding RNAs genes (lncRNAs) and enhancers from publicly available databases: miRNASNPv2, PolymiRTS, VISTA Enhancer Browser, FANTOM5 and lncRNASNP2. We investigated whether SNPs overlapping these elements were associated with RE and myopia leveraged from a large GWAS meta-analysis (N = 160,420). With genetic risk scores (GRSs) per element, we investigated the joint effect of associated variants on RE, axial length (AL)/corneal radius (CR), and AL progression in an independent child cohort, the Generation R Study (N = 3638 children). We constructed a score for biological plausibility per SNP in highly confident miRNA-binding sites and enhancers in chromatin accessible regions. We found that SNPs in two miRNA genes, 14 enhancers and 81 lncRNA genes in chromatin accessible regions and 54 highly confident miRNA-binding sites, were in RE and myopia-associated loci. GRSs from SNPs in enhancers were significantly associated with RE, AL/CR and AL progression. GRSs from lncRNAs were significantly associated with all AL/CR and AL progression. GRSs from miRNAs were not associated with any ocular biometric measurement. GRSs from miRNA-binding sites showed suggestive but inconsistent significance. We prioritized candidate miRNA binding sites and candidate enhancers for future functional validation. Pathways of target and host genes of highly ranked variants included eye development (BMP4, MPPED2), neurogenesis (DDIT4, NTM), extracellular matrix (ANTXR2, BMP3), photoreceptor metabolism (DNAJB12), photoreceptor morphogenesis (CHDR1), neural signaling (VIPR2) and TGF-beta signaling (ANAPC16). This is the first large-scale study of non-coding RNAs and enhancers for RE and myopia. Enhancers and lncRNAs could be of large importance as they are associated with childhood myopia. We provide a confident blueprint for future functional validation by prioritizing candidate miRNA binding sites and candidate enhancers.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":" ","pages":"67-91"},"PeriodicalIF":3.8,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11754329/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142947994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advancements and limitations in polygenic risk score methods for genomic prediction: a scoping review.","authors":"Dovini Jayasinghe, Setegn Eshetie, Kerri Beckmann, Beben Benyamin, S Hong Lee","doi":"10.1007/s00439-024-02716-8","DOIUrl":"10.1007/s00439-024-02716-8","url":null,"abstract":"<p><p>This scoping review aims to identify and evaluate the landscape of Polygenic Risk Score (PRS)-based methods for genomic prediction from 2013 to 2023, highlighting their advancements, key concepts, and existing gaps in knowledge, research, and technology. Over the past decade, various PRS-based methods have emerged, each employing different statistical frameworks aimed at enhancing prediction accuracy, processing speed and memory efficiency. Despite notable advancements, challenges persist, including unrealistic assumptions regarding sample sizes and the polygenicity of traits necessary for accurate predictions, as well as limitations in exploring hyper-parameter spaces and considering environmental interactions. We included studies focusing on PRS-based methods for risk prediction that underwent methodological evaluations using valid approaches and released computational tools/software. Additionally, we restricted our selection to studies involving human participants that were published in English language. This review followed the standard protocol recommended by Joanna Briggs Institute Reviewer's Manual, systematically searching Ovid MEDLINE, Ovid Embase, Scopus and Web of Science databases. Additionally, searches included grey literature sources like pre-print servers such as bioRxiv, and articles recommended by experts to ensure comprehensive and diverse coverage of relevant records. This study identified 34 studies detailing 37 genomic prediction methods, the majority of which rely on linkage disequilibrium (LD) information and necessitate hyper-parameter tuning. Nine methods integrate functional/gene annotation, while 12 are suitable for cross-ancestry genomic prediction, with only one considering gene-environment (GxE) interaction. While some methods require individual-level data, most leverage summary statistics, offering flexibility. Despite progress, challenges remain. These include computational complexity and the need for large sample sizes for high prediction accuracy. Furthermore, recent methods exhibit varying effectiveness across traits, with absolute accuracies often falling short of clinical utility. Transferability across ancestries varies, influenced by trait heritability and diversity of training data, while handling admixed populations remains challenging. Additionally, the absence of standard error measurements for individual PRSs, crucial in clinical settings, underscores a critical gap. Another issue is the lack of customizable graphical visualization tools among current software packages. While genomic prediction methods have advanced significantly, there is still room for improvement. Addressing current challenges and embracing future research directions will lead to the development of more universally applicable, robust, and clinically relevant genomic prediction tools.</p>","PeriodicalId":13175,"journal":{"name":"Human Genetics","volume":" ","pages":"1401-1431"},"PeriodicalIF":3.8,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142619298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}