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Biomedical subjects

Li Guo

Publications and source records attributed to Li Guo.

3 recordsLinked to original sources

Phenotypes of Hereditary Diseases Associated With Rauch-Steindl Syndrome.

PURPOSE: Prenatal phenotypic manifestations of genetic disorders associated with NSD2 variants remain poorly characterized. This study presents our institutional experience with the prenatal diagnosis of NSD2-associated genetic disorders, specifically Rauch-Steindl syndrome (RAUST), aiming to improve understanding of both the molecular and clinical features of RAUST. METHODS: We performed a retrospective analysis of six fetuses and one adult diagnosed with RAUST at our institution and thoroughly reviewed the prenatal ultrasound reports of six fetuses. Prenatal and postnatal phenotypes of RAUST cases were summarized alongside findings from previously published literature. Correlations between NSD2 variant locations, variant types, and phenotypes were analyzed. Additionally, protein modeling was used to visualize structural changes in NSD2 protein before and after C-terminal variants. We integrated single-cell transcriptomic and gene expression data from multiple public databases to investigate spatiotemporal expression patterns of NSD2 during human fetal development. RESULTS: Fetal growth restriction (FGR) was the most prevalent prenatal manifestation in RAUST fetuses, followed by microcephaly. Bilateral renal hypoplasia emerged as a novel prenatal ultrasonographic feature. Postnatally, speech and motor developmental delays were the most commonly reported phenotypes, followed by physical developmental delays and intellectual disability. Genotype-phenotype correlation analysis revealed an association between N-terminal truncating variants in NSD2 and impaired fetal growth parameters. Notably, C-terminal truncating variants-predicted not to directly impact NSD2 functional domains-also exerted disease-causing effects. CONCLUSION: This study provides a comprehensive analysis of prenatal phenotypes in RAUST cases, enriching the prenatal phenotypic spectrum of the disease and facilitating early diagnosis and clinical management of RAUST. Furthermore, our genotype-phenotype correlation findings lay a foundational basis for future research into the complex molecular mechanisms underlying NSD2-associated genetic disorders.

Humans

DIA proteomics of FFPE renal biopsies reveals two molecular subtypes of lupus nephritis and identifies APOL1 as candidate biomarker for stratification.

INTRODUCTION: Lupus nephritis (LN) exhibits substantial clinical and pathological heterogeneity. We aimed to define proteomics-based molecular subtypes of LN and identify candidate biomarkers for subtype discrimination. METHODS: We analysed formalin-fixed paraffin-embedded (FFPE) renal biopsy specimens from 292 patients with biopsy-proven LN from four tertiary hospitals using data-independent acquisition (DIA)-liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomics. Molecular subtypes were identified by non-negative matrix factorisation. Differential proteins, functional enrichment, immune pathway activity, protein-protein interaction networks and subtype-associated clinical/pathological features were evaluated. Extreme Gradient Boosting (XGBoost) with SHapley Additive exPlanations (SHAP) and Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression were used to identify key subtype-related features and derive a protein panel distinguishing proliferative (class III/IV) from membranous (class V) LN. RESULTS: Two stable molecular subtypes were identified, with 1002 differential proteins between them. Subtype_2 was enriched for interferon-related innate immunity, complement activation, phagocytosis-endocytosis-lysosome pathways and ribosome biogenesis/RNA metabolism, whereas Subtype_1 was characterised by keratinisation and epithelial structural remodelling. Subtype_2 was associated with higher serum creatinine, lower estimated glomerular filtration rate and higher chronicity index. APOL1 showed discriminatory value between subtypes, and serum ELISA demonstrated a consistent pattern with FFPE proteomic findings. A five-protein LASSO panel achieved an area under the curve of approximately 0.76 for distinguishing class III/IV from class V LN. CONCLUSION: DIA-based proteomic profiling of FFPE renal biopsies identifies biologically and clinically relevant LN molecular subtypes and may support tissue-informed classification and risk stratification.

Humans

Proteomic Analysis of 442 Clinical Plasma Samples From Individuals With Symptom Records Revealed Subtypes of Convalescent Patients Who Had COVID-19.

After the coronavirus disease 2019 (COVID-19) pandemic, the postacute effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection have gradually attracted attention. To precisely evaluate the health status of convalescent patients with COVID-19, we analyzed symptom and proteome data of 442 plasma samples from healthy controls, hospitalized patients, and convalescent patients 6 or 12 months after SARS-CoV-2 infection. Symptoms analysis revealed distinct relationships in convalescent patients. Results of plasma protein expression levels showed that C1QA, C1QB, C2, CFH, CFHR1, and F10, which regulate the complement system and coagulation, remained highly expressed even at the 12-month follow-up compared with their levels in healthy individuals. By combining symptom and proteome data, 442 plasma samples were categorized into three subtypes: S1 (metabolism-healthy), S2 (COVID-19 retention), and S3 (long COVID). We speculated that convalescent patients reporting hair loss could have a better health status than those experiencing headaches and dyspnea. Compared to other convalescent patients, those reporting sleep disorders, appetite decrease, and muscle weakness may need more attention because they were classified into the S2 subtype, which had the most samples from hospitalized patients with COVID-19. Subtyping convalescent patients with COVID-19 may enable personalized treatments tailored to individual needs. This study provides valuable plasma proteomic datasets for further studies associated with long COVID.

Humans