Histone deacetylase inhibitors VPA and WT161 ameliorate the pathological features and cognitive impairments of the APP/PS1 Alzheimer's disease mouse model by regulating the expression of APP secretases.

BACKGROUND: Alzheimer's disease (AD) is a degenerative neurological disorder. Recent studies have indicated that histone deacetylases (HDACs) are among the most prominent epigenetic therapy targets and that HDAC inhibitors have therapeutic effects on AD. Here, we identified sodium valproate (VPA), a pan-HDAC inhibitor, and WT161, a novel HDAC6 selective inhibitor, as potential therapeutic agents for AD. Underlying molecular mechanisms were investigated. METHODS: A cellular model, N2a-APPswe, was established via lentiviral infection, and the APPswe/PSEN1dE9 transgenic mouse model was employed in the study. LC-MS/MS was applied to quantify the concentration of WT161 in the mouse brain. Western blotting, immunohistochemical staining, thioflavin-S staining and ELISA were applied to detect protein expression in cells, tissues, or serum. RNA interference was utilized to knockdown the expression of specific genes in cells. The cognitive function of mice was assessed via the nest-building test, novel object recognition test and Morris water maze test. RESULTS: Previous studies have focused mainly on the impact of HDAC inhibitors on histone deacetylase activity. Our study discovered that VPA and WT161 can downregulate the expression of multiple HDACs, such as HDAC1 and HDAC6, in both AD cell and mouse models. Moreover, they also affect the expression of APP and APP secretases (BACE1, PSEN1, ADAM10). RNA interference and subsequent vitamin C induction further confirmed that the expression of APP and APP secretases is indeed regulated by HDAC1 and HDAC6, with the JNK pathway being the intermediate link in this regulatory process. Through the above pathways, VPA and WT161 effectively reduced Aß deposition in both AD cell and mouse models and significantly improved cognitive function in AD mice. CONCLUSIONS: In general, we have discovered that the HDAC6-JNK-APP secretases cascade is an important pathway for VPA and WT161 to exert their therapeutic effects on AD. Investigations into the safety and efficacy of VPA and WT161 were also conducted, providing essential preclinical evidence for assessing these two epigenetic drugs for the treatment of AD.

An early prediction model for type 2 diabetes mellitus based on genetic variants and nongenetic risk factors in a Han Chinese cohort.

Aims: We aimed to construct a prediction model of type 2 diabetes mellitus (T2DM) in a Han Chinese cohort using a genetic risk score (GRS) and a nongenetic risk score (NGRS). Methods: A total of 297 Han Chinese subjects who were free from type 2 diabetes mellitus were selected from the Tianjin Medical University Chronic Disease Cohort for a prospective cohort study. Clinical characteristics were collected at baseline and subsequently tracked for a duration of 9 years. Genome-wide association studies (GWASs) were performed for T2DM-related phenotypes. The GRS was constructed using 13 T2DM-related quantitative trait single nucleotide polymorphisms (SNPs) loci derived from GWASs, and NGRS was calculated from 4 biochemical indicators of independent risk that screened by multifactorial Cox regressions. Results: We found that HOMA-IR, uric acid, and low HDL were independent risk factors for T2DM (HR >1; P<0.05), and the NGRS model was created using these three nongenetic risk factors, with an area under the ROC curve (AUC) of 0.678; high fasting glucose (FPG >5 mmol/L) was a key risk factor for T2DM (HR = 7.174, P< 0.001), and its addition to the NGRS model caused a significant improvement in AUC (from 0.678 to 0.764). By adding 13 SNPs associated with T2DM to the GRS prediction model, the AUC increased to 0.892. The final combined prediction model was created by taking the arithmetic sum of the two models, which had an AUC of 0.908, a sensitivity of 0.845, and a specificity of 0.839. Conclusions: We constructed a comprehensive prediction model for type 2 diabetes out of a Han Chinese cohort. Along with independent risk factors, GRS is a crucial element to predicting the risk of type 2 diabetes mellitus.

Comparative analyses and phylogenetic relationships of thirteen Pholidota species (Orchidaceae) inferred from complete chloroplast genomes.

BACKGROUND: The orchid genus Pholidota Lindl. ex Hook. is economically important as some species has long been used in traditional medicine. However, the systematic status of the genus and intergeneric relationships inferred from previous molecular studies are unclear due to insufficient sampling and lack of informative sites. So far, only limited genomic information has been available. The taxonomy of Pholidota remains unresolved and somewhat controversial. In this study, the complete chloroplast (cp.) genomes of thirteen Pholidota species were sequenced and analyzed to gain insight into the phylogeny of Pholidota and mutation patterns in their cp. genomes. RESULTS: All examined thirteen Pholidota cp. genomes exhibited typical quadripartite circular structures, with the size ranging from 158,786 to 159,781 bp. The annotation contained a total of 135 genes in each cp. genome, i.e., 89 protein-coding genes, 38 tRNA genes, and eight rRNA genes. The codon usage analysis indicated the preference of A/U-ending codons. Repeat sequence analysis identified 444 tandem repeats, 322 palindromic repeats and 189 dispersed repeats. A total of 525 SSRs, 13,834 SNPs and 8,630 InDels were detected. Six mutational hotspots were identified as potential molecular markers. These molecular markers and highly variable regions are expected to facilitate future genetic and genomic studies. Our phylogenetic analyses confirmed the polyphyletic status of the genus Pholidota, with species grouped into four main clades: Pholidota s.s. was resolved as the sister to a clade containing species of Coelogyne; the other two clades clustered together with species of Bulleyia and Panisea, respectively; species P. ventricosa was placed at the basal position, deviated from all other species. CONCLUSION: This is the first study to comprehensively examine the genetic variations and systematically analyze the phylogeny and evolution of Pholidota based on plastid genomic data. These findings contribute to a better understanding of plastid genome evolution of Pholidota and provide new insights into the phylogeny of Pholidota and its closely related genera within the subtribe Coelogyninae. Our research has laid the foundation for future studies on the evolutionary mechanisms and classification of this economically and medicinally important genus.

The complete chloroplast genome of Pholidota yunnanensis Rolfe (Orchidaceae: Coelogyninae).

In this study, the complete chloroplast genome of Pholidota yunnanensis is presented, which represents first complete plastid genome of the genus Pholidota in the subtribe Coelogyninae. The chloroplast genome size is 159,729 bp, including a GC content of 37.3% and 135 genes (89 protein-coding genes, 38 tRNA genes, 8 rRNA genes). The genome structure is typical quadripartite, consisting of a pair of inverted repeat regions (26,638 bp) separated by a large single-copy region (LSC, 87,610 bp) and a small single-copy region (SSC, 18,843 bp). Phylogenetic analysis among 15 species based on cp genomes recovered a well-supported phylogenetic tree and indicated a close relationship between Pholidota yunnanensis and Pleione bulbocodioides.

The taxonomic identities of Pholidota wenshanica and P. subcalceata (Orchidaceae, Coelogyninae).

P. wenshanica S.C.Chen & Z.H.Tsi and P. subcalceata Gagnep. have long been recognized as synonyms of P. leveilleana Schltr. In the present study, detailed morphological comparisons suggest that specimens referred to as P. wenshanica and P. subcalceata differ significantly in both vegetative and floral characters from those of P. leveilleana. Here we resurrect P. wenshanica and P. subcalceata as independent species. Key diagnostic characters essential for delineating identities of these species are presented.