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Phenomics | Phenomics期刊2024年第五期文章合集

2025-4-7 12:23

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Disease Modules Associated with Unfavorable Sleep Patterns and Their Genetic Determinants: A Prospective Cohort Study of the UK Biobank

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引用格式：

Yang, H., Hou, C., Chen, W. et al. Disease Modules Associated with Unfavorable Sleep Patterns and Their Genetic Determinants: A Prospective Cohort Study of the UK Biobank. Phenomics 4, 415–429 (2024). https://doi.org/10.1007/s43657-023-00144-8

Abstract

Despite the established associations between sleep-related traits and major diseases, comprehensive assessment on affected disease modules and their genetic determinants is lacking. Using multiple correspondence analysis and the k-means clustering algorithm, 235,826 eligible participants were clustered into distinct unfavorable sleep patterns [short sleep duration (n = 10,073), snoring (22,419), insomnia (102,771), insomnia and snoring (62,909)] and favorable sleep pattern groups (37,654). The associations of unfavorable sleep patterns with 134 diseases were estimated using Cox regression models; and comorbidity network analyses were applied for disease module identification. Genetic determinants associated with each disease module were identified by genome-wide association studies (GWAS). During an average follow-up of 10.80 years, unfavorable sleep patterns featured by ‘short sleep duration’, ‘snoring’, ‘insomnia’, and ‘insomnia and snoring’ were associated with increased risk of 0, 9, 10, and 19 diseases, respectively. Furthermore, comorbidity network analyses categorized these affected diseases into three disease modules, characterized by predominant diseases related to digestive system, circulatory and endocrine systems (snoring-related patterns only), and musculoskeletal system (insomnia-related patterns only). Using the number of affected diseases, as an index of a person's susceptibility to each disease module [i.e., susceptible score (SS)], GWAS analyses identified five, one, and three significant loci associated with the residual SS of these aforementioned disease modules, respectively, which mapped to several potential biological pathways, including those related to hormone regulation and catecholamine uptake. In conclusion, individuals with unfavorable sleep patterns, particularly snoring and insomnia, had increased risk of multiple diseases. The identification of three major disease modules with their relevant genetic determinants may facilitate strategy development for precision prevention of future health decline.

Study design

Cellular Senescence-Related Long Non-coding RNA Signatures Predict Prognosis in Juvenile Osteosarcoma

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引文格式：

Zhao, P., Chang, J., Chen, Y. et al. Cellular Senescence-Related Long Non-coding RNA Signatures Predict Prognosis in Juvenile Osteosarcoma. Phenomics 4, 430–452 (2024). https://doi.org/10.1007/s43657-023-00132-y

Abstract

Osteosarcoma is the most common malignant bone tumor and is frequently diagnosed in juvenile. Cellular senescence is a fundamental hallmark of osteosarcoma and plays a vital role in the initiation and progression of aging and tumorigenesis. Long non-coding RNAs (lncRNAs) are implicated in tumorigenesis. In this study, six cellular senescence-related lncRNAs with independent prognostic significance in juvenile osteosarcoma patients were identified through univariate Cox regression analysis, least absolute shrinkage and selection operator (LASSO) regression analysis, and multivariate Cox regression analysis. Prognostic significance was further confirmed by Kaplan–Meier (KM) survival curves, co-expression interaction networks, and sankey diagrams. A prognostic model of cellular senescence-related genes in juvenile osteosarcoma patients was then constructed using multivariate Cox regression analysis based on these six genes. High- and low-risk groups were identified according to the median risk score calculated by the prognostic model. The favorable prognostic significance of this model was demonstrated through survival curves, receiver operating characteristic (ROC) curves, distribution scatter plots and lncRNA expression heatmaps. Furthermore, cellular senescence-related lncRNAs were validated by enrichment analysis, immunological correlation analysis, m6A correlation analysis, and drug sensitivity correlation analysis. These findings are important for improving the prognosis of juvenile osteosarcoma patients and understanding the mechanisms underlying cellular senescence in juvenile osteosarcoma development.

The forest map showing the hazard ratio and p-value of the 67 Cellular senescence-related lncRNAs with prognostic potential in juvenile osteosarcoma by univariate Cox regression analysis

Prognostic Significance of Methyl-CpG Binding Domain4 Polymorphism rs140693 and Clinical Characteristics in Chinese Lung Cancer Patients

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引文格式：

Li, Z., Hu, Y., Xu, C. et al. Prognostic Significance of Methyl-CpG Binding Domain4 Polymorphism rs140693 and Clinical Characteristics in Chinese Lung Cancer Patients. Phenomics 4, 453–464 (2024). https://doi.org/10.1007/s43657-024-00171-z

Abstract

Lung cancer remains the leading cause of death among cancer patients, and the five-year survival rate is less than 25%. However, Methyl-CpG Binding Domain (MBD)4 polymorphism rs140693 predicts the prognosis of lung cancer patients still needs further verification. Primary lung cancer patients (n = 839) were collected from two hospitals, genomic DNA was extracted from blood, and genotyping was performed using SNPcan technology. Kaplan-Meier technique and multivariate Cox proportional hazards model were used to analyze the prognosis association between MBD4 and clinical characteristics. Significantly conferred a poorer prognosis was associated with the CT genotype (CT vs. CC; adjusted hazard ratio [HR] = 1.21, 95% CI: 1.03–1.43, p = 0.023) and dominant CT + TT genotype (CT + TT vs. CC; HR = 1.19, 95% CI: 1.02–1.39, p = 0.029) of MBD4 polymorphism rs140693 for all lung cancer patients, compared with the CC genotype. Stratified analysis showed that polymorphism rs140693 CT and dominant CT + TT genotype conferred a significantly poorer prognosis in female and lung adenocarcinoma (ADC) cancer patients, compared with the CC genotype. Non-small cell lung cancer (NSCLC) patients with the CT genotype had a poorer prognosis than those with the CC genotype. Additionally, the allele T of small cell lung cancer (SCLC) patients compared with the allele C was associated with a poor prognosis, and the CT and recessive TT genotype of SCLC patients conferred a significantly poor prognosis. The MBD4 polymorphism rs140693 is a significant prognostic genetic marker for predicting the prognosis of lung cancer patients.

The Kaplan-Meier survival curve analysis of the impact of MBD4 polymorphism rs140693 on the prognosis of patients with lung cancer

Improved prediction of swimming talent through random forest analysis of anthropometric and physiological phenotypes

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引文格式：

Liu, C., Xu, B., Wan, K. et al. Improved prediction of swimming talent through random forest analysis of anthropometric and physiological phenotypes. Phenomics 4, 465–472 (2024). https://doi.org/10.1007/s43657-024-00176-8

Abstract

The field of competitive swimming lacks broadly applicable predictive models for talent identification across various age groups of adolescent swimmers. This study aimed to construct a predictive model for athletic talent using machine learning methods based on anthropometric and physiological data. Baseline data were collected from 5444 participants aged 10–18 in Shanghai, China, between 2015 and 2018, with 4969 completing a 3-year follow-up. Talents were discerned based on their performance over the follow-up period, revealing age- and sex- dependent developmental differences between swimmers classified as talented versus non-talented. After controlling for confounding variables, age and sex, nine machine learning algorithms were employed, with Random Forest achieving the highest performance and being selected as the final model. The model demonstrated excellent predictive performance on both the test dataset and an independent validation dataset from Shandong (n = 118), indicating its strong generalizability. Furthermore, using the SHapley Additive exPlanations (SHAP) method to interpret the model, abdominal skinfold, lung capacity, chest circumference, shoulder width, and triceps skinfold were identified as the five most critical indicators for talent identification.

Pre-processing, model building, and model performance evaluation

Alterations of Sensory-related Functional Brain Network Connectivity in Nrsn2 Homozygous Knockout Mice

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引文格式：

Yi, Y., Dai, F., Zhang, Y. et al. Alterations of Sensory-related Functional Brain Network Connectivity in Nrsn2 Homozygous Knockout Mice. Phenomics 4, 473–486 (2024). https://doi.org/10.1007/s43657-024-00181-x

Abstract

Neurensin-2 (Nrsn2) is a neuro-specific gene linked to neurodevelopmental disorders and has recently been reported to function as a bidirectional emotional regulator, highlighting its molecular roles in the nervous system. However, the connections between Nrsn2, brain architecture, and functionality remain to be fully elucidated. Our study utilized 11.7 T multimodal magnetic resonance imaging (MRI) to assess the impact of Nrsn2 gene knockout on the brain’s microstructure, regional functional activity, and network connectivity during different developmental phases in mice. We observed significant changes in the functional brain network connectivity of Nrsn2−/− mice without marked differences in brain microstructure or regional activity. These changes were particularly pronounced in sensory-related areas, such as the gustatory and auditory systems, in both juvenile and adult specimens. Previous studies have correlated the enhanced Default Mode Network (DMN) with depression, and Nrsn2 knockout has been associated with stress resilience. Our findings further revealed reduced connectivity in various DMN regions in adult Nrsn2−/− mice, suggesting a potential link to increased stress tolerance. Moreover, the sensory system’s critical role in environmental perception implies that alterations in network connectivity due to Nrsn2 knockout could affect the processing and integration of external inputs, thereby influencing emotional experiences.

Schematic of the present study

Reference Materials for Improving Reliability of Multiomics Profiling

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引文格式：

Ren, L., Shi, L. & Zheng, Y. Reference Materials for Improving Reliability of Multiomics Profiling. Phenomics 4, 487–521 (2024). https://doi.org/10.1007/s43657-023-00153-7

Abstract

High-throughput technologies for multiomics or molecular phenomics profiling have been extensively adopted in biomedical research and clinical applications, offering a more comprehensive understanding of biological processes and diseases. Omics reference materials play a pivotal role in ensuring the accuracy, reliability, and comparability of laboratory measurements and analyses. However, the current application of omics reference materials has revealed several issues, including inappropriate selection and underutilization, leading to inconsistencies across laboratories. This review aims to address these concerns by emphasizing the importance of well-characterized reference materials at each level of omics, encompassing (epi-)genomics, transcriptomics, proteomics, and metabolomics. By summarizing their characteristics, advantages, and limitations along with appropriate performance metrics pertinent to study purposes, we provide an overview of how omics reference materials can enhance data quality and data integration, thus fostering robust scientific investigations with omics technologies.

The quartet project for quality control of multiomics profiling

No Association of Polycystic Ovary Syndrome with Pancreatic Cancer: A Mendelian Randomization Study

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引文格式：

Gao, X., Wang, Y., Wang, Y. et al. No Association of Polycystic Ovary Syndrome with Pancreatic Cancer: A Mendelian Randomization Study. Phenomics 4, 522–524 (2024). https://doi.org/10.1007/s43657-024-00156-y

Abstract

Recently, there has been a debate regarding the association between polycystic ovary syndrome (PCOS) and pancreatic cancer (PC). In order to examine the causal relationship between PCOS and PC, we conducted a Mendelian randomization study, which utilized 12 single nucleotide polymorphisms (SNPs) identified from a genome-wide association study (GWAS) meta-analysis that included 10,074 PCOS cases and 103,164 controls of European ancestry as instrumental variables (IVs). The outcome data were obtained from the FinnGen database (including 605 cases and 218,187 controls). We demonstrate that genetically predicted PCOS is not causally associated with PC risk in Europeans (odds ratio = 0.99, 95% confidence interval (CI) = 0.72–1.36, p > 0.05). Sensitivity analysis showed horizontal pleiotropy (intercept p > 0.05), heterogeneity (Cochran Q p > 0.05), and the leave-one-out sensitivity test showed that individual SNP effects had no influence on the results. In conclusion, our study did not provide evidence of a causal link between PCOS and PC.

Forest plots of the associated SNPs with the risk for pancreatic cancer

Unveiling Metabolic Signatures in Osteoarthritis Progression through Non-Targeted Metabolomics Analysis: A Paradigm Shift in Diagnosis and Treatment Prospects

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引文格式：

Wu, P. Unveiling Metabolic Signatures in Osteoarthritis Progression through Non-Targeted Metabolomics Analysis: A Paradigm Shift in Diagnosis and Treatment Prospects. Phenomics 4, 525–526 (2024). https://doi.org/10.1007/s43657-024-00177-7

Conclusion

The research conducted by Sun et al. markedly deepens our comprehension of the metabolic shifts linked to the advancement of OA. By leveraging non-targeted metabolomics, this research unveils novel metabolic markers and pathways, offering promising directions for diagnosis, monitoring, and treatment. As we continue to unravel OA’s metabolic complexity, these findings lay the groundwork for innovative therapeutic strategies, heralding a new progress of personalized medicine in OA management.

Towards Risk Stratification in Clinical Care for IgA Nephropathy: Genetic Risk Scores

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引文格式：

Berthier, C.C., Ju, W. Towards Risk Stratification in Clinical Care for IgA Nephropathy: Genetic Risk Scores. Phenomics 4, 527–530 (2024). https://doi.org/10.1007/s43657-024-00184-8

Abstract

Patients with immunoglobulin A nephropathy (IgAN) can present with diverse clinical manifestations from asymptomatic microscopic hematuria or proteinuria to rapid decline of renal function (Stamellou et al. 2023). Many patients with IgAN progress to kidney failure within a span of 10–15 years and nearly all of the patients are at risk of progression to kidney failure over the course of their expected lifetimes (Pitcher et al. 2023). However, early identification of IgAN patients at high risk of progression and those who would benefit from early and targeted intervention is a key challenge in the clinical management of IgAN patients. These unmet needs are partly due to a lack of in depth understanding of factors triggering IgAN and its pathogenesis and progression. Recent genome-wide association studies (GWAS) revealed genetic loci associated with susceptibility to IgAN (Feehally et al. 2010; Gharavi et al. 2011; Kiryluk et al. 2014, 2023; Li et al. 2015, 2020, 2023; Xu et al. 2023; Yu et al. 2011; Zhou et al. 2021) and offered a foundation for developing polygenic risk scores (PRSs), through integrating alleles that are associated with the risk of IgAN, to represent an individual’s genetic predisposition. PRSs can be computed at young age, providing a predictive tool for risk assessment and stratification prior to the onset of clinical symptoms.