Pub Date : 2024-07-18Epub Date: 2024-05-27DOI: 10.1016/j.xhgg.2024.100313
Toshiyuki Itai, Fangfang Yan, Andi Liu, Yulin Dai, Chihiro Iwaya, Sarah W Curtis, Elizabeth J Leslie, Lukas M Simon, Peilin Jia, Xiangning Chen, Junichi Iwata, Zhongming Zhao
Orofacial clefts (OFCs) are common congenital birth defects with various etiologies, including genetic variants. Online Mendelian Inheritance in Man (OMIM) annotated several hundred genes involving OFCs. Furthermore, several hundreds of de novo variants (DNVs) have been identified from individuals with OFCs. Some DNVs are related to known OFC genes or pathways, but there are still many DNVs whose relevance to OFC development is unknown. To explore novel gene functions and their cellular expression profiles, we focused on DNVs in genes that were not listed in OMIM. We collected 960 DNVs in 853 genes from published studies and curated these genes, based on the DNVs' deleteriousness, into 230 and 23 genes related to cleft lip with or without cleft palate (CL/P) and cleft palate only (CPO), respectively. For comparison, we curated 178 CL/P and 277 CPO genes from OMIM. In CL/P, the pathways enriched in DNV and OMIM genes were significantly overlapped (p = 0.002). Single-cell RNA sequencing (scRNA-seq) analysis of mouse lip development revealed that both gene sets had abundant expression in the ectoderm (DNV genes: adjusted p = 0.032, OMIM genes: adjusted p < 0.0002), while only DNV genes were enriched in the endothelium (adjusted p = 0.032). Although we did not achieve significant findings using CPO gene sets, which was mainly due to the limited number of DNV genes, scRNA-seq analysis implicated various expression patterns among DNV and OMIM genes. Our results suggest that combinatory pathway and scRNA-seq data analyses are helpful for contextualizing genes in OFC development.
{"title":"Investigating gene functions and single-cell expression profiles of de novo variants in orofacial clefts.","authors":"Toshiyuki Itai, Fangfang Yan, Andi Liu, Yulin Dai, Chihiro Iwaya, Sarah W Curtis, Elizabeth J Leslie, Lukas M Simon, Peilin Jia, Xiangning Chen, Junichi Iwata, Zhongming Zhao","doi":"10.1016/j.xhgg.2024.100313","DOIUrl":"10.1016/j.xhgg.2024.100313","url":null,"abstract":"<p><p>Orofacial clefts (OFCs) are common congenital birth defects with various etiologies, including genetic variants. Online Mendelian Inheritance in Man (OMIM) annotated several hundred genes involving OFCs. Furthermore, several hundreds of de novo variants (DNVs) have been identified from individuals with OFCs. Some DNVs are related to known OFC genes or pathways, but there are still many DNVs whose relevance to OFC development is unknown. To explore novel gene functions and their cellular expression profiles, we focused on DNVs in genes that were not listed in OMIM. We collected 960 DNVs in 853 genes from published studies and curated these genes, based on the DNVs' deleteriousness, into 230 and 23 genes related to cleft lip with or without cleft palate (CL/P) and cleft palate only (CPO), respectively. For comparison, we curated 178 CL/P and 277 CPO genes from OMIM. In CL/P, the pathways enriched in DNV and OMIM genes were significantly overlapped (p = 0.002). Single-cell RNA sequencing (scRNA-seq) analysis of mouse lip development revealed that both gene sets had abundant expression in the ectoderm (DNV genes: adjusted p = 0.032, OMIM genes: adjusted p < 0.0002), while only DNV genes were enriched in the endothelium (adjusted p = 0.032). Although we did not achieve significant findings using CPO gene sets, which was mainly due to the limited number of DNV genes, scRNA-seq analysis implicated various expression patterns among DNV and OMIM genes. Our results suggest that combinatory pathway and scRNA-seq data analyses are helpful for contextualizing genes in OFC development.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11318074/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141162523","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-18Epub Date: 2024-05-29DOI: 10.1016/j.xhgg.2024.100314
Roberta Zeuli, Marianthi Karali, Suzanne E de Bruijn, Kim Rodenburg, Margherita Scarpato, Dalila Capasso, Galuh D N Astuti, Christian Gilissen, María Rodríguez-Hidalgo, Javier Ruiz-Ederra, Francesco Testa, Francesca Simonelli, Frans P M Cremers, Sandro Banfi, Susanne Roosing
Inherited retinal diseases (IRDs) are a group of rare monogenic diseases with high genetic heterogeneity (pathogenic variants identified in over 280 causative genes). The genetic diagnostic rate for IRDs is around 60%, mainly thanks to the routine application of next-generation sequencing (NGS) approaches such as extensive gene panels or whole exome analyses. Whole-genome sequencing (WGS) has been reported to improve this diagnostic rate by revealing elusive variants, such as structural variants (SVs) and deep intronic variants (DIVs). We performed WGS on 33 unsolved cases with suspected autosomal recessive IRD, aiming to identify causative genetic variants in non-coding regions or to detect SVs that were unexplored in the initial screening. Most of the selected cases (30 of 33, 90.9%) carried monoallelic pathogenic variants in genes associated with their clinical presentation, hence we first analyzed the non-coding regions of these candidate genes. Whenever additional pathogenic variants were not identified with this approach, we extended the search for SVs and DIVs to all IRD-associated genes. Overall, we identified the missing causative variants in 11 patients (11 of 33, 33.3%). These included three DIVs in ABCA4, CEP290 and RPGRIP1; one non-canonical splice site (NCSS) variant in PROM1 and three SVs (large deletions) in EYS, PCDH15 and USH2A. For the previously unreported DIV in CEP290 and for the NCCS variant in PROM1, we confirmed the effect on splicing by reverse transcription (RT)-PCR on patient-derived RNA. This study demonstrates the power and clinical utility of WGS as an all-in-one test to identify disease-causing variants missed by standard NGS diagnostic methodologies.
{"title":"Whole genome sequencing identifies elusive variants in genetically unsolved Italian inherited retinal disease patients.","authors":"Roberta Zeuli, Marianthi Karali, Suzanne E de Bruijn, Kim Rodenburg, Margherita Scarpato, Dalila Capasso, Galuh D N Astuti, Christian Gilissen, María Rodríguez-Hidalgo, Javier Ruiz-Ederra, Francesco Testa, Francesca Simonelli, Frans P M Cremers, Sandro Banfi, Susanne Roosing","doi":"10.1016/j.xhgg.2024.100314","DOIUrl":"10.1016/j.xhgg.2024.100314","url":null,"abstract":"<p><p>Inherited retinal diseases (IRDs) are a group of rare monogenic diseases with high genetic heterogeneity (pathogenic variants identified in over 280 causative genes). The genetic diagnostic rate for IRDs is around 60%, mainly thanks to the routine application of next-generation sequencing (NGS) approaches such as extensive gene panels or whole exome analyses. Whole-genome sequencing (WGS) has been reported to improve this diagnostic rate by revealing elusive variants, such as structural variants (SVs) and deep intronic variants (DIVs). We performed WGS on 33 unsolved cases with suspected autosomal recessive IRD, aiming to identify causative genetic variants in non-coding regions or to detect SVs that were unexplored in the initial screening. Most of the selected cases (30 of 33, 90.9%) carried monoallelic pathogenic variants in genes associated with their clinical presentation, hence we first analyzed the non-coding regions of these candidate genes. Whenever additional pathogenic variants were not identified with this approach, we extended the search for SVs and DIVs to all IRD-associated genes. Overall, we identified the missing causative variants in 11 patients (11 of 33, 33.3%). These included three DIVs in ABCA4, CEP290 and RPGRIP1; one non-canonical splice site (NCSS) variant in PROM1 and three SVs (large deletions) in EYS, PCDH15 and USH2A. For the previously unreported DIV in CEP290 and for the NCCS variant in PROM1, we confirmed the effect on splicing by reverse transcription (RT)-PCR on patient-derived RNA. This study demonstrates the power and clinical utility of WGS as an all-in-one test to identify disease-causing variants missed by standard NGS diagnostic methodologies.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11225895/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141181006","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-18Epub Date: 2024-05-21DOI: 10.1016/j.xhgg.2024.100310
Qianqian Liang, Abin Abraham, John A Capra, Dennis Kostka
Non-protein-coding genetic variants are a major driver of the genetic risk for human disease; however, identifying which non-coding variants contribute to diseases and their mechanisms remains challenging. In silico variant prioritization methods quantify a variant's severity, but for most methods, the specific phenotype and disease context of the prediction remain poorly defined. For example, many commonly used methods provide a single, organism-wide score for each variant, while other methods summarize a variant's impact in certain tissues and/or cell types. Here, we propose a complementary disease-specific variant prioritization scheme, which is motivated by the observation that variants contributing to disease often operate through specific biological mechanisms. We combine tissue/cell-type-specific variant scores (e.g., GenoSkyline, FitCons2, DNA accessibility) into disease-specific scores with a logistic regression approach and apply it to ∼25,000 non-coding variants spanning 111 diseases. We show that this disease-specific aggregation significantly improves the association of common non-coding genetic variants with disease (average precision: 0.151, baseline = 0.09), compared with organism-wide scores (GenoCanyon, LINSIGHT, GWAVA, Eigen, CADD; average precision: 0.129, baseline = 0.09). Further on, disease similarities based on data-driven aggregation weights highlight meaningful disease groups, and it provides information about tissues and cell types that drive these similarities. We also show that so-learned similarities are complementary to genetic similarities as quantified by genetic correlation. Overall, our approach demonstrates the strengths of disease-specific variant prioritization, leads to improvement in non-coding variant prioritization, and enables interpretable models that link variants to disease via specific tissues and/or cell types.
{"title":"Disease-specific prioritization of non-coding GWAS variants based on chromatin accessibility.","authors":"Qianqian Liang, Abin Abraham, John A Capra, Dennis Kostka","doi":"10.1016/j.xhgg.2024.100310","DOIUrl":"10.1016/j.xhgg.2024.100310","url":null,"abstract":"<p><p>Non-protein-coding genetic variants are a major driver of the genetic risk for human disease; however, identifying which non-coding variants contribute to diseases and their mechanisms remains challenging. In silico variant prioritization methods quantify a variant's severity, but for most methods, the specific phenotype and disease context of the prediction remain poorly defined. For example, many commonly used methods provide a single, organism-wide score for each variant, while other methods summarize a variant's impact in certain tissues and/or cell types. Here, we propose a complementary disease-specific variant prioritization scheme, which is motivated by the observation that variants contributing to disease often operate through specific biological mechanisms. We combine tissue/cell-type-specific variant scores (e.g., GenoSkyline, FitCons2, DNA accessibility) into disease-specific scores with a logistic regression approach and apply it to ∼25,000 non-coding variants spanning 111 diseases. We show that this disease-specific aggregation significantly improves the association of common non-coding genetic variants with disease (average precision: 0.151, baseline = 0.09), compared with organism-wide scores (GenoCanyon, LINSIGHT, GWAVA, Eigen, CADD; average precision: 0.129, baseline = 0.09). Further on, disease similarities based on data-driven aggregation weights highlight meaningful disease groups, and it provides information about tissues and cell types that drive these similarities. We also show that so-learned similarities are complementary to genetic similarities as quantified by genetic correlation. Overall, our approach demonstrates the strengths of disease-specific variant prioritization, leads to improvement in non-coding variant prioritization, and enables interpretable models that link variants to disease via specific tissues and/or cell types.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11259938/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141076825","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-18Epub Date: 2024-05-03DOI: 10.1016/j.xhgg.2024.100303
Marah H Wahbeh, Rachel J Boyd, Christian Yovo, Bailey Rike, Andrew S McCallion, Dimitrios Avramopoulos
Recent collaborative genome-wide association studies (GWAS) have identified >200 independent loci contributing to risk for schizophrenia (SCZ). The genes closest to these loci have diverse functions, supporting the potential involvement of multiple relevant biological processes, yet there is no direct evidence that individual variants are functional or directly linked to specific genes. Nevertheless, overlap with certain epigenetic marks suggest that most GWAS-implicated variants are regulatory. Based on the strength of association with SCZ and the presence of regulatory epigenetic marks, we chose one such variant near TSNARE1 and ADGRB1, rs4129585, to test for functional potential and assay differences that may drive the pathogenicity of the risk allele. We observed that the variant-containing sequence drives reporter expression in relevant neuronal populations in zebrafish. Next, we introduced each allele into human induced pluripotent cells and differentiated four isogenic clones homozygous for the risk allele and five clones homozygous for the non-risk allele into neural progenitor cells. Employing RNA sequencing, we found that the two alleles yield significant transcriptional differences in the expression of 109 genes at a false discovery rate (FDR) of <0.05 and 259 genes at a FDR of <0.1. We demonstrate that these genes are highly interconnected in pathways enriched for synaptic proteins, axon guidance, and regulation of synapse assembly. Exploration of genes near rs4129585 suggests that this variant does not regulate TSNARE1 transcripts, as previously thought, but may regulate the neighboring ADGRB1, a regulator of synaptogenesis. Our results suggest that rs4129585 is a functional common variant that functions in specific pathways likely involved in SCZ risk.
{"title":"A functional schizophrenia-associated genetic variant near the TSNARE1 and ADGRB1 genes.","authors":"Marah H Wahbeh, Rachel J Boyd, Christian Yovo, Bailey Rike, Andrew S McCallion, Dimitrios Avramopoulos","doi":"10.1016/j.xhgg.2024.100303","DOIUrl":"10.1016/j.xhgg.2024.100303","url":null,"abstract":"<p><p>Recent collaborative genome-wide association studies (GWAS) have identified >200 independent loci contributing to risk for schizophrenia (SCZ). The genes closest to these loci have diverse functions, supporting the potential involvement of multiple relevant biological processes, yet there is no direct evidence that individual variants are functional or directly linked to specific genes. Nevertheless, overlap with certain epigenetic marks suggest that most GWAS-implicated variants are regulatory. Based on the strength of association with SCZ and the presence of regulatory epigenetic marks, we chose one such variant near TSNARE1 and ADGRB1, rs4129585, to test for functional potential and assay differences that may drive the pathogenicity of the risk allele. We observed that the variant-containing sequence drives reporter expression in relevant neuronal populations in zebrafish. Next, we introduced each allele into human induced pluripotent cells and differentiated four isogenic clones homozygous for the risk allele and five clones homozygous for the non-risk allele into neural progenitor cells. Employing RNA sequencing, we found that the two alleles yield significant transcriptional differences in the expression of 109 genes at a false discovery rate (FDR) of <0.05 and 259 genes at a FDR of <0.1. We demonstrate that these genes are highly interconnected in pathways enriched for synaptic proteins, axon guidance, and regulation of synapse assembly. Exploration of genes near rs4129585 suggests that this variant does not regulate TSNARE1 transcripts, as previously thought, but may regulate the neighboring ADGRB1, a regulator of synaptogenesis. Our results suggest that rs4129585 is a functional common variant that functions in specific pathways likely involved in SCZ risk.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11130735/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140869396","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-18Epub Date: 2024-05-14DOI: 10.1016/j.xhgg.2024.100308
Cary O Harding, Michael Martinez
{"title":"Letter to the editor.","authors":"Cary O Harding, Michael Martinez","doi":"10.1016/j.xhgg.2024.100308","DOIUrl":"10.1016/j.xhgg.2024.100308","url":null,"abstract":"","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11192771/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141288713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-18Epub Date: 2024-03-19DOI: 10.1016/j.xhgg.2024.100284
Elizabeth T Cirulli, Kelly M Schiabor Barrett, Alexandre Bolze, Daniel P Judge, Pamala A Pawloski, Joseph J Grzymski, William Lee, Nicole L Washington
Systematic determination of novel variant pathogenicity remains a major challenge, even when there is an established association between a gene and phenotype. Here we present Power Window (PW), a sliding window technique that identifies the impactful regions of a gene using population-scale clinico-genomic datasets. By sizing analysis windows on the number of variant carriers, rather than the number of variants or nucleotides, statistical power is held constant, enabling the localization of clinical phenotypes and removal of unassociated gene regions. The windows can be built by sliding across either the nucleotide sequence of the gene (through 1D space) or the positions of the amino acids in the folded protein (through 3D space). Using a training set of 350k exomes from the UK Biobank (UKB), we developed PW models for well-established gene-disease associations and tested their accuracy in two independent cohorts (117k UKB exomes and 65k exomes sequenced at Helix in the Healthy Nevada Project, myGenetics, or In Our DNA SC studies). The significant models retained a median of 49% of the qualifying variant carriers in each gene (range 2%-98%), with quantitative traits showing a median effect size improvement of 66% compared with aggregating variants across the entire gene, and binary traits' odds ratios improving by a median of 2.2-fold. PW showcases that electronic health record-based statistical analyses can accurately distinguish between novel coding variants in established genes that will have high phenotypic penetrance and those that will not, unlocking new potential for human genomics research, drug development, variant interpretation, and precision medicine.
{"title":"A power-based sliding window approach to evaluate the clinical impact of rare genetic variants in the nucleotide sequence or the spatial position of the folded protein.","authors":"Elizabeth T Cirulli, Kelly M Schiabor Barrett, Alexandre Bolze, Daniel P Judge, Pamala A Pawloski, Joseph J Grzymski, William Lee, Nicole L Washington","doi":"10.1016/j.xhgg.2024.100284","DOIUrl":"10.1016/j.xhgg.2024.100284","url":null,"abstract":"<p><p>Systematic determination of novel variant pathogenicity remains a major challenge, even when there is an established association between a gene and phenotype. Here we present Power Window (PW), a sliding window technique that identifies the impactful regions of a gene using population-scale clinico-genomic datasets. By sizing analysis windows on the number of variant carriers, rather than the number of variants or nucleotides, statistical power is held constant, enabling the localization of clinical phenotypes and removal of unassociated gene regions. The windows can be built by sliding across either the nucleotide sequence of the gene (through 1D space) or the positions of the amino acids in the folded protein (through 3D space). Using a training set of 350k exomes from the UK Biobank (UKB), we developed PW models for well-established gene-disease associations and tested their accuracy in two independent cohorts (117k UKB exomes and 65k exomes sequenced at Helix in the Healthy Nevada Project, myGenetics, or In Our DNA SC studies). The significant models retained a median of 49% of the qualifying variant carriers in each gene (range 2%-98%), with quantitative traits showing a median effect size improvement of 66% compared with aggregating variants across the entire gene, and binary traits' odds ratios improving by a median of 2.2-fold. PW showcases that electronic health record-based statistical analyses can accurately distinguish between novel coding variants in established genes that will have high phenotypic penetrance and those that will not, unlocking new potential for human genomics research, drug development, variant interpretation, and precision medicine.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11004801/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140176784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-17DOI: 10.1016/j.xhgg.2024.100333
Andrew C Liu, Yang Shen, Carolyn R Serbinski, Hongzhi He, Destino Roman, Mehari Endale, Lindsey Aschbacher-Smith, Katherine A King, Jorge L Granadillo, Isabel López, Darcy A Krueger, Thomas J Dye, David F Smith, John B Hogenesch, Carlos E Prada
Heterozygous de novo or inherited gain-of-function mutations in the MTOR gene cause Smith-Kingsmore syndrome (SKS). SKS is a rare autosomal dominant condition, and individuals with SKS display macrocephaly/megalencephaly, developmental delay, intellectual disability, and seizures. A few dozen individuals are reported in the literature. Here, we report a cohort of 28 individuals with SKS that represent nine MTOR pathogenic variants. We conducted a detailed natural history study and found pathophysiological deficits among individuals with SKS in addition to the common neurodevelopmental symptoms. These symptoms include sleep-wake disturbance, hyperphagia, and hyperactivity, indicative of homeostatic imbalance. To characterize these variants, we developed cell models and characterized their functional consequences. We showed that these SKS variants display a range of mechanistic target of rapamycin (mTOR) activities and respond to the mTOR inhibitor, rapamycin, differently. For example, the R1480_C1483del variant we identified here and the previously known C1483F are more active than wild-type controls and less responsive to rapamycin. Further, we showed that SKS mutations dampened circadian rhythms and low-dose rapamycin improved the rhythm amplitude, suggesting that optimal mTOR activity is required for normal circadian function. As SKS is caused by gain-of-function mutations in MTOR, rapamycin was used to treat several patients. While higher doses of rapamycin caused delayed sleep-wake phase disorder in a subset of patients, optimized lower doses improved sleep. Our study expands the clinical and molecular spectrum of SKS and supports further studies for mechanism-guided treatment options to improve sleep-wake behavior and overall health.
MTOR 基因中的异卵新生突变或遗传性功能增益突变会导致史密斯-金斯莫尔综合征(SKS)。SKS 是一种罕见的常染色体显性遗传病,SKS 患者会出现巨脑畸形/巨脑症、发育迟缓、智力障碍和癫痫发作。文献中仅报道了几十例患者。在此,我们报告了一个由 28 名 SKS 患者组成的队列,这些患者代表了 9 种 MTOR 致病变异。我们进行了详细的自然史研究,发现除了常见的神经发育症状外,SKS 患者还存在病理生理缺陷。这些症状包括睡眠-觉醒障碍、多食和多动,表明体内平衡失调。为了描述这些变体的特征,我们开发了细胞模型,并描述了它们的功能后果。我们发现,这些 SKS 变体显示出一系列 mTOR 活性,并对 mTOR 抑制剂雷帕霉素做出不同的反应。例如,我们在此发现的 R1480_C1483del 变异和之前已知的 C1483F 变异比野生型对照更活跃,对雷帕霉素的反应更弱。此外,我们发现 SKS 突变抑制了昼夜节律,而低剂量雷帕霉素改善了节律幅度,这表明正常的昼夜节律功能需要最佳的 mTOR 活性。由于 SKS 是由 MTOR 功能增益突变引起的,因此雷帕霉素被用于治疗几名患者。虽然高剂量雷帕霉素会导致部分患者出现睡眠觉醒期延迟紊乱,但优化后的低剂量雷帕霉素却能改善睡眠。我们的研究扩展了SKS的临床和分子谱,支持进一步研究以机制为导向的治疗方案,以改善睡眠-觉醒行为和整体健康。
{"title":"Clinical and functional studies of MTOR variants in Smith-Kingsmore syndrome reveal deficits of circadian rhythm and sleep-wake behavior.","authors":"Andrew C Liu, Yang Shen, Carolyn R Serbinski, Hongzhi He, Destino Roman, Mehari Endale, Lindsey Aschbacher-Smith, Katherine A King, Jorge L Granadillo, Isabel López, Darcy A Krueger, Thomas J Dye, David F Smith, John B Hogenesch, Carlos E Prada","doi":"10.1016/j.xhgg.2024.100333","DOIUrl":"10.1016/j.xhgg.2024.100333","url":null,"abstract":"<p><p>Heterozygous de novo or inherited gain-of-function mutations in the MTOR gene cause Smith-Kingsmore syndrome (SKS). SKS is a rare autosomal dominant condition, and individuals with SKS display macrocephaly/megalencephaly, developmental delay, intellectual disability, and seizures. A few dozen individuals are reported in the literature. Here, we report a cohort of 28 individuals with SKS that represent nine MTOR pathogenic variants. We conducted a detailed natural history study and found pathophysiological deficits among individuals with SKS in addition to the common neurodevelopmental symptoms. These symptoms include sleep-wake disturbance, hyperphagia, and hyperactivity, indicative of homeostatic imbalance. To characterize these variants, we developed cell models and characterized their functional consequences. We showed that these SKS variants display a range of mechanistic target of rapamycin (mTOR) activities and respond to the mTOR inhibitor, rapamycin, differently. For example, the R1480_C1483del variant we identified here and the previously known C1483F are more active than wild-type controls and less responsive to rapamycin. Further, we showed that SKS mutations dampened circadian rhythms and low-dose rapamycin improved the rhythm amplitude, suggesting that optimal mTOR activity is required for normal circadian function. As SKS is caused by gain-of-function mutations in MTOR, rapamycin was used to treat several patients. While higher doses of rapamycin caused delayed sleep-wake phase disorder in a subset of patients, optimized lower doses improved sleep. Our study expands the clinical and molecular spectrum of SKS and supports further studies for mechanism-guided treatment options to improve sleep-wake behavior and overall health.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11342114/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141731490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-14DOI: 10.1016/j.xhgg.2024.100327
Daphne J Smits, Jordy Dekker, Hannie Douben, Rachel Schot, Helen Magee, Somayeh Bakhtiari, Katrin Koehler, Angela Huebner, Markus Schuelke, Hossein Darvish, Shohreh Vosoogh, Abbas Tafakhori, Melika Jameie, Ehsan Taghiabadi, Yana Wilson, Margit Shah, Marjon A van Slegtenhorst, Evita G Medici-van den Herik, Tjakko J van Ham, Michael C Kruer, Grazia M S Mancini
Nuclear pore complexes (NPCs) regulate nucleocytoplasmic transport and are anchored in the nuclear envelope by the transmembrane nucleoporin NDC1. NDC1 is essential for post-mitotic NPC assembly and the recruitment of ALADIN to the nuclear envelope. While no human disorder has been associated to one of the three transmembrane nucleoporins, biallelic variants in AAAS, encoding ALADIN, cause triple A syndrome (Allgrove syndrome). Triple A syndrome, characterized by alacrima, achalasia, and adrenal insufficiency, often includes progressive demyelinating polyneuropathy and other neurological complaints. In this report, diagnostic exome and/or RNA sequencing was performed in seven individuals from four unrelated consanguineous families with AAAS-negative triple A syndrome. Molecular and clinical studies followed to elucidate the pathogenic mechanism. The affected individuals presented with intellectual disability, motor impairment, severe demyelinating with secondary axonal polyneuropathy, alacrima, and achalasia. None of the affected individuals has adrenal insufficiency. All individuals presented with biallelic NDC1 in-frame deletions or missense variants that affect amino acids and protein domains required for ALADIN binding. No other significant variants associated with the phenotypic features were reported. Skin fibroblasts derived from affected individuals show decreased recruitment of ALADIN to the NE and decreased post-mitotic NPC insertion, confirming pathogenicity of the variants. Taken together, our results implicate biallelic NDC1 variants in the pathogenesis of polyneuropathy and a triple A-like disorder without adrenal insufficiency, by interfering with physiological NDC1 functions, including the recruitment of ALADIN to the NPC.
{"title":"Biallelic NDC1 variants that interfere with ALADIN binding are associated with neuropathy and triple A-like syndrome.","authors":"Daphne J Smits, Jordy Dekker, Hannie Douben, Rachel Schot, Helen Magee, Somayeh Bakhtiari, Katrin Koehler, Angela Huebner, Markus Schuelke, Hossein Darvish, Shohreh Vosoogh, Abbas Tafakhori, Melika Jameie, Ehsan Taghiabadi, Yana Wilson, Margit Shah, Marjon A van Slegtenhorst, Evita G Medici-van den Herik, Tjakko J van Ham, Michael C Kruer, Grazia M S Mancini","doi":"10.1016/j.xhgg.2024.100327","DOIUrl":"10.1016/j.xhgg.2024.100327","url":null,"abstract":"<p><p>Nuclear pore complexes (NPCs) regulate nucleocytoplasmic transport and are anchored in the nuclear envelope by the transmembrane nucleoporin NDC1. NDC1 is essential for post-mitotic NPC assembly and the recruitment of ALADIN to the nuclear envelope. While no human disorder has been associated to one of the three transmembrane nucleoporins, biallelic variants in AAAS, encoding ALADIN, cause triple A syndrome (Allgrove syndrome). Triple A syndrome, characterized by alacrima, achalasia, and adrenal insufficiency, often includes progressive demyelinating polyneuropathy and other neurological complaints. In this report, diagnostic exome and/or RNA sequencing was performed in seven individuals from four unrelated consanguineous families with AAAS-negative triple A syndrome. Molecular and clinical studies followed to elucidate the pathogenic mechanism. The affected individuals presented with intellectual disability, motor impairment, severe demyelinating with secondary axonal polyneuropathy, alacrima, and achalasia. None of the affected individuals has adrenal insufficiency. All individuals presented with biallelic NDC1 in-frame deletions or missense variants that affect amino acids and protein domains required for ALADIN binding. No other significant variants associated with the phenotypic features were reported. Skin fibroblasts derived from affected individuals show decreased recruitment of ALADIN to the NE and decreased post-mitotic NPC insertion, confirming pathogenicity of the variants. Taken together, our results implicate biallelic NDC1 variants in the pathogenesis of polyneuropathy and a triple A-like disorder without adrenal insufficiency, by interfering with physiological NDC1 functions, including the recruitment of ALADIN to the NPC.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11375137/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141604271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-10DOI: 10.1016/j.xhgg.2024.100326
Linda Dieckmann, Marius Lahti-Pulkkinen, Cristiana Cruceanu, Katri Räikkönen, Elisabeth B Binder, Darina Czamara
The placenta, a pivotal player in the prenatal environment, holds crucial insights into early developmental pathways and future health outcomes. In this study, we explored genetic molecular regulation in chorionic villus samples (CVS) from the first trimester and placenta tissue at birth. We assessed quantitative trait locus (QTL) mapping on DNA methylation and gene expression data in a Finnish cohort of 574 individuals. We found more QTLs in birth placenta than in first-trimester placenta. Nevertheless, a substantial amount of associations overlapped in their effects and showed consistent direction in both tissues, with increasing molecular genetic effects from early pregnancy to birth placenta. The identified QTLs in birth placenta were most enriched in genes with placenta-specific expression. Conducting a phenome-wide-association study (PheWAS) on the associated SNPs, we observed numerous overlaps with genome-wide association study (GWAS) hits (spanning 57 distinct traits and 23 SNPs), with notable enrichments for immunological, skeletal, and respiratory traits. The QTL-SNP rs1737028 (chr6:29737993) presented with the highest number of GWAS hits. This SNP was related to HLA-G expression via DNA methylation and was associated with various immune, respiratory, and psychiatric traits. Our findings implicate increasing genetic molecular regulation during the course of pregnancy and support the involvement of placenta gene regulation, particularly in immunological traits. This study presents a framework for understanding placenta-specific gene regulation during pregnancy and its connection to health-related traits.
胎盘是产前环境中的关键角色,对早期发育途径和未来健康状况有着至关重要的影响。在这项研究中,我们探索了妊娠头三个月的绒毛样本(CVS)和出生时胎盘组织的遗传分子调控。我们对芬兰 574 人队列中 DNA 甲基化和基因表达数据的定量性状位点图(QTL)进行了评估。与初产胎盘相比,我们在出生胎盘中发现了更多的 QTLs。然而,在这两种组织中,大量的关联效应是重叠的,并显示出一致的方向,从怀孕早期到出生胎盘,分子遗传效应不断增加。在出生胎盘中鉴定出的 QTLs 主要富集在胎盘特异性表达的基因中。在对相关的 SNPs 进行 PheWAS 研究时,我们观察到了与 GWAS 点击的大量重叠(跨越 57 个不同性状和 23 个 SNPs),其中免疫、骨骼和呼吸性状明显富集。QTL-SNP rs1737028(chr6:29737993)在 GWAS 中的命中率最高。该 SNP 通过 DNA 甲基化与 HLA-G 的表达有关,并与各种免疫、呼吸和精神特征相关。我们的研究结果表明,在妊娠过程中,遗传分子调控不断增加,并支持胎盘基因调控的参与,尤其是在免疫学特征方面。这项研究为了解孕期胎盘特异性基因调控及其与健康相关特征的联系提供了一个框架。
{"title":"Quantitative trait locus mapping in placenta: A comparative study of chorionic villus and birth placenta.","authors":"Linda Dieckmann, Marius Lahti-Pulkkinen, Cristiana Cruceanu, Katri Räikkönen, Elisabeth B Binder, Darina Czamara","doi":"10.1016/j.xhgg.2024.100326","DOIUrl":"10.1016/j.xhgg.2024.100326","url":null,"abstract":"<p><p>The placenta, a pivotal player in the prenatal environment, holds crucial insights into early developmental pathways and future health outcomes. In this study, we explored genetic molecular regulation in chorionic villus samples (CVS) from the first trimester and placenta tissue at birth. We assessed quantitative trait locus (QTL) mapping on DNA methylation and gene expression data in a Finnish cohort of 574 individuals. We found more QTLs in birth placenta than in first-trimester placenta. Nevertheless, a substantial amount of associations overlapped in their effects and showed consistent direction in both tissues, with increasing molecular genetic effects from early pregnancy to birth placenta. The identified QTLs in birth placenta were most enriched in genes with placenta-specific expression. Conducting a phenome-wide-association study (PheWAS) on the associated SNPs, we observed numerous overlaps with genome-wide association study (GWAS) hits (spanning 57 distinct traits and 23 SNPs), with notable enrichments for immunological, skeletal, and respiratory traits. The QTL-SNP rs1737028 (chr6:29737993) presented with the highest number of GWAS hits. This SNP was related to HLA-G expression via DNA methylation and was associated with various immune, respiratory, and psychiatric traits. Our findings implicate increasing genetic molecular regulation during the course of pregnancy and support the involvement of placenta gene regulation, particularly in immunological traits. This study presents a framework for understanding placenta-specific gene regulation during pregnancy and its connection to health-related traits.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11365441/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141591578","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Small insertions and deletions (indels) are critical yet challenging genetic variations with significant clinical implications. However, the identification of pathogenic indels from neutral variants in clinical contexts remains an understudied problem. Here, we developed INDELpred, a machine-learning-based predictive model for discerning pathogenic from benign indels. INDELpred was established based on key features, including allele frequency, indel length, function-based features, and gene-based features. A set of comprehensive evaluation analyses demonstrated that INDELpred exhibited superior performance over competing methods in terms of computational efficiency and prediction accuracy. Importantly, INDELpred highlighted the crucial role of function-based features in identifying pathogenic indels, with a clear interpretability of the features in understanding the disease-causing variants. We envisage INDELpred as a desirable tool for the detection of pathogenic indels within large-scale genomic datasets, thereby enhancing the precision of genetic diagnoses in clinical settings.
{"title":"INDELpred: Improving the prediction and interpretation of indel pathogenicity within the clinical genome.","authors":"Yilin Wei, Tongda Zhang, Bangyao Wang, Xiaosen Jiang, Fei Ling, Mingyan Fang, Xin Jin, Yong Bai","doi":"10.1016/j.xhgg.2024.100325","DOIUrl":"10.1016/j.xhgg.2024.100325","url":null,"abstract":"<p><p>Small insertions and deletions (indels) are critical yet challenging genetic variations with significant clinical implications. However, the identification of pathogenic indels from neutral variants in clinical contexts remains an understudied problem. Here, we developed INDELpred, a machine-learning-based predictive model for discerning pathogenic from benign indels. INDELpred was established based on key features, including allele frequency, indel length, function-based features, and gene-based features. A set of comprehensive evaluation analyses demonstrated that INDELpred exhibited superior performance over competing methods in terms of computational efficiency and prediction accuracy. Importantly, INDELpred highlighted the crucial role of function-based features in identifying pathogenic indels, with a clear interpretability of the features in understanding the disease-causing variants. We envisage INDELpred as a desirable tool for the detection of pathogenic indels within large-scale genomic datasets, thereby enhancing the precision of genetic diagnoses in clinical settings.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11321314/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141591577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}