HGG Advances最新文献

{"title":"Stratified analyses refine association between TLR7 rare variants and severe COVID-19.","authors":"Jannik Boos, Caspar I van der Made, Gayatri Ramakrishnan, Eamon Coughlan, Rosanna Asselta, Britt-Sabina Löscher, Luca V C Valenti, Rafael de Cid, Luis Bujanda, Antonio Julià, Erola Pairo-Castineira, J Kenneth Baillie, Sandra May, Berina Zametica, Julia Heggemann, Agustín Albillos, Jesus M Banales, Jordi Barretina, Natalia Blay, Paolo Bonfanti, Maria Buti, Javier Fernandez, Sara Marsal, Daniele Prati, Luisa Ronzoni, Nicoletta Sacchi, Joachim L Schultze, Olaf Riess, Andre Franke, Konrad Rawlik, David Ellinghaus, Alexander Hoischen, Axel Schmidt, Kerstin U Ludwig","doi":"10.1016/j.xhgg.2024.100323","DOIUrl":"10.1016/j.xhgg.2024.100323","url":null,"abstract":"<p><p>Despite extensive global research into genetic predisposition for severe COVID-19, knowledge on the role of rare host genetic variants and their relation to other risk factors remains limited. Here, 52 genes with prior etiological evidence were sequenced in 1,772 severe COVID-19 cases and 5,347 population-based controls from Spain/Italy. Rare deleterious TLR7 variants were present in 2.4% of young (<60 years) cases with no reported clinical risk factors (n = 378), compared to 0.24% of controls (odds ratio [OR] = 12.3, p = 1.27 × 10^-10). Incorporation of the results of either functional assays or protein modeling led to a pronounced increase in effect size (OR_max = 46.5, p = 1.74 × 10^-15). Association signals for the X-chromosomal gene TLR7 were also detected in the female-only subgroup, suggesting the existence of additional mechanisms beyond X-linked recessive inheritance in males. Additionally, supporting evidence was generated for a contribution to severe COVID-19 of the previously implicated genes IFNAR2, IFIH1, and TBK1. Our results refine the genetic contribution of rare TLR7 variants to severe COVID-19 and strengthen evidence for the etiological relevance of genes in the interferon signaling pathway.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100323"},"PeriodicalIF":3.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11320601/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141471225","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}

{"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":" ","pages":"100326"},"PeriodicalIF":3.3,"publicationDate":"2024-10-10","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}

{"title":"Estimating prevalence of rare genetic disease diagnoses using electronic health records in a children's hospital.","authors":"Kate Herr, Peixin Lu, Kessi Diamreyan, Huan Xu, Eneida Mendonca, K Nicole Weaver, Jing Chen","doi":"10.1016/j.xhgg.2024.100341","DOIUrl":"10.1016/j.xhgg.2024.100341","url":null,"abstract":"<p><p>Rare genetic diseases (RGDs) affect a significant number of individuals, particularly in pediatric populations. This study investigates the efficacy of identifying RGD diagnoses through electronic health records (EHRs) and natural language processing (NLP) tools, and analyzes the prevalence of identified RGDs for potential underdiagnosis at Cincinnati Children's Hospital Medical Center (CCHMC). EHR data from 659,139 pediatric patients at CCHMC were utilized. Diagnoses corresponding to RGDs in Orphanet were identified using rule-based and machine learning-based NLP methods. Manual evaluation assessed the precision of the NLP strategies, with 100 diagnosis descriptions reviewed for each method. The rule-based method achieved a precision of 97.5% (95% CI: 91.5%, 99.4%), while the machine-learning-based method had a precision of 73.5% (95% CI: 63.6%, 81.6%). A manual chart review of 70 randomly selected patients with RGD diagnoses confirmed the diagnoses in 90.3% (95% CI: 82.0%, 95.2%) of cases. A total of 37,326 pediatric patients were identified with 977 RGD diagnoses based on the rule-based method, resulting in a prevalence of 5.66% in this population. While a majority of the disorders showed a higher prevalence at CCHMC compared with Orphanet, some diseases, such as 1p36 deletion syndrome, indicated potential underdiagnosis. Analyses further uncovered disparities in RGD prevalence and age of diagnosis across gender and racial groups. This study demonstrates the utility of employing EHR data with NLP tools to systematically investigate RGD diagnoses in large cohorts. The identified disparities underscore the need for enhanced approaches to guarantee timely and accurate diagnosis and management of pediatric RGDs.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100341"},"PeriodicalIF":3.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11401171/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141989095","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}

{"title":"Investigation of cryptic JAG1 splice variants as a cause of Alagille syndrome and performance evaluation of splice predictor tools.","authors":"Ernest Keefer-Jacques, Nicolette Valente, Anastasia M Jacko, Grace Matwijec, Apsara Reese, Aarna Tekriwal, Kathleen M Loomes, Nancy B Spinner, Melissa A Gilbert","doi":"10.1016/j.xhgg.2024.100351","DOIUrl":"10.1016/j.xhgg.2024.100351","url":null,"abstract":"<p><p>Haploinsufficiency of JAG1 is the primary cause of Alagille syndrome (ALGS), a rare, multisystem disorder. The identification of JAG1 intronic variants outside of the canonical splice region as well as missense variants, both of which lead to uncertain associations with disease, confuses diagnostics. Strategies to determine whether these variants affect splicing include the study of patient RNA or minigene constructs, which are not always available or can be laborious to design, as well as the utilization of computational splice prediction tools. These tools, including SpliceAI and Pangolin, use algorithms to calculate the probability that a variant results in a splice alteration, expressed as a Δ score, with higher Δ scores (>0.2 on a 0-1 scale) positively correlated with aberrant splicing. We studied the consequence of 10 putative splice variants in ALGS patient samples through RNA analysis and compared this to SpliceAI and Pangolin predictions. We identified eight variants with aberrant splicing, seven of which had not been previously validated. Combining these data with non-canonical and missense splice variants reported in the literature, we identified a predictive threshold for SpliceAI and Pangolin with high sensitivity (Δ score >0.6). Moreover, we showed reduced specificity for variants with low Δ scores (<0.2), highlighting a limitation of these tools that results in the misidentification of true splice variants. These results improve genomic diagnostics for ALGS by confirming splice effects for seven variants and suggest that the integration of splice prediction tools with RNA analysis is important to ensure accurate clinical variant classifications.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100351"},"PeriodicalIF":3.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11440345/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142146465","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}

{"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":" ","pages":"100325"},"PeriodicalIF":3.3,"publicationDate":"2024-10-10","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}

{"title":"A novel framework with automated horizontal pleiotropy adjustment in mendelian randomization.","authors":"Zhaotong Lin","doi":"10.1016/j.xhgg.2024.100339","DOIUrl":"10.1016/j.xhgg.2024.100339","url":null,"abstract":"<p><p>The presence of horizontal pleiotropy in Mendelian randomization (MR) analysis has long been a concern due to its potential to induce substantial bias. In recent years, many robust MR methods have been proposed to address this by relaxing the \"no horizontal pleiotropy\" assumption. Here, we propose a novel two-stage framework called CMR, which integrates a conditional analysis of multiple genetic variants to remove pleiotropy induced by linkage disequilibrium, followed by the application of robust MR methods to model the conditional genetic effect estimates. We demonstrate how the conditional analysis can reduce horizontal pleiotropy and improve the performance of existing MR methods. Extensive simulation studies covering a wide range of scenarios of horizontal pleiotropy showcased the superior performance of the proposed CMR framework over the standard MR framework in which marginal genetic effects are modeled. Moreover, the application of CMR in a negative control outcome analysis and investigation into the causal role of body mass index across various diseases highlighted its potential to deliver more reliable results in real-world applications.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100339"},"PeriodicalIF":3.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11375132/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141890278","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}

{"title":"WES-based screening of 7,000 newborns: A pilot study in Russia.","authors":"Jekaterina Shubina, Ekaterina Tolmacheva, Dmitry Maslennikov, Taisiya Kochetkova, Irina Mukosey, Igor Sadelov, Andrey Goltsov, Ilya Barkov, Aleksey Ekimov, Margarita Rogacheva, Olga Stupko, Nadezhda Pavlova, Maria Kuznetsova, Alina Dokshukina, Grigory Vasiliev, Anna Bolshakova, Valeriia Kovalskaia, Anastasia Korovko, Ekaterina Pomerantseva, Polina Tsabai, Olga Buyanovskaya, Nadezhda Zaretskaya, Natalia Karetnikova, Elena Grebenshchikova, Anna Degtyareva, Ekaterina Bokerija, Alexey Kholin, Denis Rebrikov, Dmitry Degtyarev, Dmitriy Trofimov, Gennady Sukhih","doi":"10.1016/j.xhgg.2024.100334","DOIUrl":"10.1016/j.xhgg.2024.100334","url":null,"abstract":"<p><p>The effective implementation of whole-exome sequencing- and whole-genome sequencing-based diagnostics in the management of children affected with genetic diseases and the rapid decrease in the cost of next-generation sequencing (NGS) enables the expansion of this method to newborn genetic screening programs. Such NGS-based screening greatly increases the number of diseases that can be detected compared to conventional newborn screening, as the latter is aimed at early detection of a limited number of inborn diseases. Moreover, genetic testing provides new possibilities for family members of the proband, as many variants responsible for adult-onset conditions are inherited from the parents. However, the idea of NGS-based screening in healthy children raises issues of medical and ethical integrity as well as technical questions, including interpretation of the observed variants. Pilot studies have shown that both parents and medical professionals have moved forward and are enthused about these new possibilities. However, either the number of participants or the number of genes studied in previous investigations thus far has been limited to a few hundred, restricting the scope of potential findings. Our current study (NCT05325749) includes 7,000 apparently healthy infants born at our center between February 2021 and May 2023, who were screened for pathogenic variants in 2,350 genes. Clinically significant variants associated with early-onset diseases that can be treated, prevented, or where symptoms can be alleviated with timely introduced symptomatic therapy, were observed in 0.9% of phenotypically normal infants, 2.1% of the screened newborns were found to carry variants associated with reduced penetrance or monogenic diseases of adult-onset and/or variable expressivity, and 0.3% had chromosomal abnormalities. Here, we report our results and address questions regarding the interpretation of variants in newborns who were presumed to be healthy.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100334"},"PeriodicalIF":3.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11350501/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141735204","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}

{"title":"Extensive co-regulation of neighboring genes complicates the use of eQTLs in target gene prioritization.","authors":"Ralf Tambets, Anastassia Kolde, Peep Kolberg, Michael I Love, Kaur Alasoo","doi":"10.1016/j.xhgg.2024.100348","DOIUrl":"10.1016/j.xhgg.2024.100348","url":null,"abstract":"<p><p>Identifying causal genes underlying genome-wide association studies (GWASs) is a fundamental problem in human genetics. Although colocalization with gene expression quantitative trait loci (eQTLs) is often used to prioritize GWAS target genes, systematic benchmarking has been limited due to unavailability of large ground truth datasets. Here, we re-analyzed plasma protein QTL data from 3,301 individuals of the INTERVAL cohort together with 131 eQTL Catalog datasets. Focusing on variants located within or close to the affected protein identified 793 proteins with at least one cis-pQTL where we could assume that the most likely causal gene was the gene coding for the protein. We then benchmarked the ability of cis-eQTLs to recover these causal genes by comparing three Bayesian colocalization methods (coloc.susie, coloc.abf, and CLPP) and five Mendelian randomization (MR) approaches (three varieties of inverse-variance weighted MR, MR-RAPS, and MRLocus). We found that assigning fine-mapped pQTLs to their closest protein coding genes outperformed all colocalization methods regarding both precision (71.9%) and recall (76.9%). Furthermore, the colocalization method with the highest recall (coloc.susie - 46.3%) also had the lowest precision (45.1%). Combining evidence from multiple conditionally distinct colocalizing QTLs with MR increased precision to 81%, but this was accompanied by a large reduction in recall to 7.1%. Furthermore, the choice of the MR method greatly affected performance, with the standard inverse-variance-weighted MR often producing many false positives. Our results highlight that linking GWAS variants to target genes remains challenging with eQTL evidence alone, and prioritizing novel targets requires triangulation of evidence from multiple sources.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100348"},"PeriodicalIF":3.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11416642/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142112846","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}

{"title":"Genotype-phenotype correlation over time in Angelman syndrome: Researching 134 patients.","authors":"Masanori Fujimoto, Yuji Nakamura, Kana Hosoki, Toshihiko Iwaki, Emi Sato, Daisuke Ieda, Ikumi Hori, Yutaka Negishi, Ayako Hattori, Hideaki Shiraishi, Shinji Saitoh","doi":"10.1016/j.xhgg.2024.100342","DOIUrl":"10.1016/j.xhgg.2024.100342","url":null,"abstract":"<p><p>Angelman syndrome (AS) is a severe neurodevelopmental disorder caused by the loss of function of maternal UBE3A. The major cause of AS is a maternal deletion in 15q11.2-q13, and the minor causes are a UBE3A mutation, uniparental disomy (UPD), and imprinting defect (ID). Previous reports suggest that all patients with AS exhibit developmental delay, movement or balance disorders, behavioral characteristics, and speech impairment. In contrast, a substantial number of AS patients with a UBE3A mutation, UPD, or ID were reported not to show these consistent features and to show age-dependent changes in their features. In this study, we investigated 134 patients with AS, including 57 patients with a UBE3A mutation and 48 patients with UPD or ID. Although developmental delay was present in all patients, 20% of patients with AS caused by UPD or ID did not exhibit movement or balance disorders. Differences were also seen in hypopigmentation and seizures, depending on the causes. Moreover, patients with a UBE3A mutation, UPD, or ID tended to show fewer of the specific phenotypes depending on their age. In particular, in patients with UPD or ID, easily provoked laughter and hyperactivity tended to become more pronounced as they aged. Therefore, the clinical features of AS based on cause and age should be understood, and genetic testing should not be limited to patients with the typical clinical features of AS.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100342"},"PeriodicalIF":3.3,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11404063/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142018950","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}

{"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":" ","pages":"100333"},"PeriodicalIF":3.3,"publicationDate":"2024-10-10","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}