Biomedical subjects

Lin Han

Publications and source records attributed to Lin Han.

4 recordsLinked to original sources

PubMed2026

Low-Dose Radiation-Induced Expression of Exosomal miRNAs in the Serum of Medical Radiation Workers.

Objective: Long-term low-dose ionizing radiation may alter genomes and cause diseases. This study examined serum exosomal miRNA differences among radiation-exposed medical workers by work types. Methods: High-throughput sequencing screened serum exosomal miRNAs in diagnostic radiologists, interventional radiologists, and nuclear medicine doctors. qRT-PCR validated differentially expressed miRNAs. Results: 410 differentially expressed miRNAs, including 102 downregulated and 308 upregulated miRNAs, enriched in 15 KEGG pathways. Four miRNAs were validated. miR-30e-5p, miR-155-5p and miR-486-5p differed significantly among groups(P<0.01).The expression levels of these three miRNAs were lower in the nuclear medicine group than in the diagnostic group (0.25±0.05vs3.89±8.62,0.10±0.15vs7.03±15.75,0.37±0.39vs4.46±9.64;Z=3.542,3.335,9.859;P<0.01), whereas miR-155-5p was lower in the interventional group than in the diagnostic group(1.32±2.43vs 7.03±15.75;H=11.889,P=0.003), miR-486-5p was higher(9.54±19.39vs4.46±9.64; H=9.859,P=0.007). All four miRNAs showed higher expression in the 14-31-year work-experience group, and all four also showed age-dependent differences, with miR-30d-5p and miR-486-5p showing the age-related differences (P<0.01). Combined detection of the four miRNAs improved discrimination among occupational categories (AUC=0.784). Multiple linear regression analysis showed that sex was associated with all four miRNAs, whereas work type was associated with miR-30d-5p and miR-155-5p (P<0.05). Conclusion: Serum exosomal miR-30e-5p, miR-155-5p, and miR-486-5p are promising biomarkers for monitoring radiation-induced damage, supporting occupational protection and health management.

exosomes↗

PubMed2026

Revealing potential biomarkers and metabolic mechanisms of ovarian aging in hens during late laying period based on machine learning and metabolomics.

Ovarian function decline during the late laying period represents a major bottleneck for the economic efficiency of the global poultry industry. However, the underlying metabolic mechanisms and reliable early-warning biomarkers for ovarian aging remain poorly understood. In this study, we performed the first untargeted LC-MS/MS metabolomics analysis of ovarian tissues from Taihe silky fowls at peak laying (30 weeks) and late laying (50 weeks) stages, and employed an ensemble machine learning strategy integrating LASSO, random forest, and support vector machine (SVM) algorithms to identify high-confidence core biomarkers of ovarian aging. Gene expression analysis was further conducted to validate the potential molecular mechanisms. Our results showed that the metabolic profiles of ovarian tissues differed significantly between the two groups. A total of 6 core biomarkers were identified, 4 of which were long-chain acylcarnitines. Mechanistic analysis revealed that downregulation of key genes in the carnitine shuttle system led to impaired mitochondrial fatty acid β-oxidation, which in turn triggered excessive oxidative stress and compromised ovarian endocrine function. In conclusion, this study identifies long-chain acylcarnitines as potential metabolic biomarkers for ovarian aging in Taihe silky fowls. These findings provide novel insights into the metabolic basis of poultry ovarian aging and lay a theoretical foundation for the precise regulation of reproductive performance in indigenous poultry breeds.

Animals↗

PubMed2024

Novel Genetic Loci in Early-Onset Gout Derived From Whole-Genome Sequencing of an Adolescent Gout Cohort.

OBJECTIVE: Mechanisms underlying the adolescent-onset and early-onset gout are unclear. This study aimed to discover variants associated with early-onset gout. METHODS: We conducted whole-genome sequencing in a discovery adolescent-onset gout cohort of 905 individuals (gout onset 12 to 19 years) to discover common and low-frequency single-nucleotide variants (SNVs) associated with gout. Candidate common SNVs were genotyped in an early-onset gout cohort of 2,834 individuals (gout onset ≤30 years old), and meta-analysis was performed with the discovery and replication cohorts to identify loci associated with early-onset gout. Transcriptome and epigenomic analyses, quantitative real-time polymerase chain reaction and RNA sequencing in human peripheral blood leukocytes, and knock-down experiments in human THP-1 macrophage cells investigated the regulation and function of candidate gene RCOR1. RESULTS: In addition to ABCG2, a urate transporter previously linked to pediatric-onset and early-onset gout, we identified two novel loci (Pmeta < 5.0 × 10-8): rs12887440 (RCOR1) and rs35213808 (FSTL5-MIR4454). Additionally, we found associations at ABCG2 and SLC22A12 that were driven by low-frequency SNVs. SNVs in RCOR1 were linked to elevated blood leukocyte messenger RNA levels. THP-1 macrophage culture studies revealed the potential of decreased RCOR1 to suppress gouty inflammation. CONCLUSION: This is the first comprehensive genetic characterization of adolescent-onset gout. The identified risk loci of early-onset gout mediate inflammatory responsiveness to crystals that could mediate gouty arthritis. This study will contribute to risk prediction and therapeutic interventions to prevent adolescent-onset gout.

Humans↗

PubMed2024

Mendelian randomization study of lipid metabolism characteristics and migraine risk.

BACKGROUND: The association between serum lipids and migraine is controversial. However, randomized controlled trials have suggested that statins may be efficacious for the prevention of migraine. In this study, we aim to investigate the relationship between lipids metabolism and migraine risk. METHODS: Single-nucleotide polymorphisms (SNPs), relating to the serum lipid traits and the effect of lipid-lowering drugs that target APOB, CETP, HMGCR, NPC1L1, and PCSK9, were extracted from genome-wide association studies (GWAS) summary data. The GWAS summary data were obtained from the Global Lipids Genetic Consortium (GLGC), the UK Biobank, and the FinnGen study, respectively. Mendelian randomization (MR) analysis was performed to evaluate the association between serum lipid traits and lipid-lowering drugs with migraine risk. RESULTS: Regarding serum lipids, it was found that SNPs related to high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), total cholesterol (TC), or triglycerides (TG) levels were not associated with migraine, migraine with aura (MA) or migraine without aura (MO). In addition, genotypes of HMGCR related to higher LDL-C levels were associated with increased risk of migraine (OR = 1.46, p = 0.035) and MA (OR = 2.03, p = 0.008); However, genotypes of PCSK9 related to higher LDL-C levels were associated with decreased risk of migraine (OR = 0.75, p = 0.001) and MA (OR = 0.69, p = 0.004); And genotypes of APOB related to higher LDL-C levels were associated with decreased risk of MO (OR = 0.62, p = 0.000). CONCLUSIONS: There is a relationship between lipid metabolism characteristics and migraine risk. SIGNIFICANCE: Based on the genome-wide association summary data, single-nucleotide polymorphisms (SNPs) related to high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), total cholesterol (TC), or triglycerides (TG) level were not associated with risk of migraine, migraine with aura (MA) or migraine without aura (MO). However, genotypes of HMGCR related to higher LDL-C levels have shown an increased risk on migraine and MA. And genotypes of APOB or PCSK9 related to higher LDL-C levels have shown a decreased risk on MO, or migraine and MA, respectively. These results suggested that there may be a relationship between lipid metabolism characteristics and the risk for migraine development.

Humans↗