A genome-wide association study for melatonin secretion

The hematopoietic function, histological characteristics, and transcriptome profiling of Wanxi white geese ovary during nesting and late-laying stages

Despite several factors influencing reproduction in geese, but the precise molecular mechanisms of egg cessation are not fully understood. In the present study, the hematopoietic parameters and serum hormone levels in Wanxi white geese were analyzed. RNA-Seq was utilized to identify the differentially expressed mRNAs (DEGs) and lncRNAs (DE lncRNAs) in the ovarian tissues associated with nesting in geese during the late-laying and nesting periods. Triglyceride (TG) and alkaline phosphatase (ALP) levels were higher in late-laying geese, while white blood cell (WBC), neutrophil (NEU), hemoglobin (HGB), and hematocrit (HCT) levels were significantly lower in late-laying geese. Serum levels of luteinizing hormone (LH), estrogen (E2), and progesterone (P4) increased significantly during the late-laying period, whereas prolactin (PRL) level was lower in the late-laying period than the nesting period. During the late-laying period, geese had a clear follicular hierarchy, with ovaries exhibiting mature and primary follicles. In the nesting period, the ovaries were degenerated and had many primary follicles without follicular development. Analysis of mRNA-lncRNA expression revealed 1,257 DEGs between the nesting and the late-laying stages, of which 841 were up-regulated and 416 were down-regulated DEGs. A total of 340 DE lncRNAs were identified between the nesting and the late-laying periods, with 113 being up-regulated and 227 down-regulated lncRNAs. DEGs, including TMEM, DRD3, IGFBP7, MAPK13, GnRHR2, HECTD3, KCNU1, OPRD1, and VCAM1, along with DE lncRNAs, including XR_001203613.1, XR_001206155.1, XR_001207759.1, XR_001213571.1 and XR_001214368.1 participate in reproduction in geese. Correlation analysis indicated that the cis-regulation of XR_001213096.1-ITPR3, XR_001203613.1-GALNT15, XR_001206155.1-COL6A3, XR_001207759.1-ANKS1B, and XR_001214368.1-VPS45 participate in the molecular mechanisms underlying nesting in geese. Functional enrichment analysis revealed the DEGs and DE lncRNAs associated with focal adhesion, extracellular matrix (ECM)-receptor interaction, cell adhesion molecules (CAMs), and PI3K-Akt signaling pathways, were responsible for the differences in the ovaries between the nesting and late-laying periods. This study offers valuable information on the roles of genes and lncRNAs, and the mechanisms underlying variations in reproductive performance between the late-laying and nesting periods.

Blood leukocytes as a non-invasive diagnostic tool for thyroid nodules: a prospective cohort study

BACKGROUND

Thyroid nodule (TN) patients in China are subject to overdiagnosis and overtreatment. The implementation of existing technologies such as thyroid ultrasonography has indeed contributed to the improved diagnostic accuracy of TNs. However, a significant issue persists, where many patients undergo unnecessary biopsies, and patients with malignant thyroid nodules (MTNs) are advised to undergo surgery therapy.

METHODS

This study included a total of 293 patients diagnosed with TNs. Differential methylation haplotype blocks (MHBs) in blood leukocytes between MTNs and benign thyroid nodules (BTNs) were detected using reduced representation bisulfite sequencing (RRBS). Subsequently, an artificial intelligence blood leukocyte DNA methylation (BLDM) model was designed to optimize the management and treatment of patients with TNs for more effective outcomes.

RESULTS

The DNA methylation profiles of peripheral blood leukocytes exhibited distinctions between MTNs and BTNs. The BLDM model we developed for diagnosing TNs achieved an area under the curve (AUC) of 0.858 in the validation cohort and 0.863 in the independent test cohort. Its specificity reached 90.91% and 88.68% in the validation and independent test cohorts, respectively, outperforming the specificity of ultrasonography (43.64% in the validation cohort and 47.17% in the independent test cohort), albeit with a slightly lower sensitivity (83.33% in the validation cohort and 82.86% in the independent test cohort) compared to ultrasonography (97.62% in the validation cohort and 100.00% in the independent test cohort). The BLDM model could correctly identify 89.83% patients whose nodules were suspected malignant by ultrasonography but finally histological benign. In micronodules, the model displayed higher specificity (93.33% in the validation cohort and 92.00% in the independent test cohort) and accuracy (88.24% in the validation cohort and 87.50% in the independent test cohort) for diagnosing TNs. This performance surpassed the specificity and accuracy observed with ultrasonography. A TN diagnostic and treatment framework that prioritizes patients is provided, with fine-needle aspiration (FNA) biopsy performed only on patients with indications of MTNs in both BLDM and ultrasonography results, thus avoiding unnecessary biopsies.

CONCLUSIONS

This is the first study to demonstrate the potential of non-invasive blood leukocytes in diagnosing TNs, thereby making TN diagnosis and treatment more efficient in China.

Genome-Wide Association Study of Alopecia Areata in Taiwan: The Conflict Between Individuals and Hair Follicles

Purpose

Alopecia areata (AA) is one of the most prevalent autoimmune diseases affecting humans. Given that hair follicles are immune-privileged, autoimmunity can result in disfiguring hair loss. However, the genetic basis for AA in the Taiwanese population remains unknown.

Materials and Methods

A genome-wide association study was conducted using a cohort of 408 AA cases and 8167 controls. To link variants to gene relationships, we used 882 SNPs (P<1E-05) within 74 genes that were associated with AA group to build the biological networks by IPA software. HLA diplotypes and haplotypes were analyzed using Attribute Bagging (HIBAG)-R package and chi-square analysis.

Results

Seven single nucleotide polymorphisms (SNPs) including LINC02006 (rs531166736, rs187306735), APC (rs112800832_C_CAT), SRP19 (rs139948960, rs144784670), EGFLAM (rs16903975) and LDLRAD3 (rs79874564) were closely associated with the AA phenotype (P<5E-08). Examination of biological networks revealed that these genomic areas are associated with antigen presentation signaling, B cell and T cell development, Th1 and Th2 activation pathways, Notch signaling, crosstalk signaling between dendritic cells and natural killer cells, and phagosome maturation. Based on human leukocyte antigen (HLA) genotype analysis, four HLA genotypes (HLA-B*15:01-*40:01, HLA-DQA1*01:02-*03:03, HLA-DQA1*01:02, and HLA-DQB1*02:01) were found to be associated with AA (adjusted p-value<0.05). HLA-DQA1*01:02 is the most significantly related gene in the Taiwanese population (adjusted p-value = 2.09E-05).

Conclusion

This study successfully identified susceptibility loci associated with AA in the Taiwanese population. These findings not only shed light on the origins of AA within the Taiwanese context but also contribute to a comprehensive understanding of the genetic factors influencing AA susceptibility.