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Background Common and rare variants of guanosine triphosphate cyclohydrolase 1 ( GCH1 ) gene may play important roles in Parkinson’s disease (PD). However, there is a lack of comprehensive analysis of GCH1 genotypes, especially in non-coding regions. The aim of this study was to explore the genetic characteristics of GCH1 , including rare and common variants in coding and non-coding regions, in a large population of PD patients in Chinese mainland, as well as the phenotypic characteristics of GCH1 variant carriers. Methods In the first cohort of this case-control study, we performed whole-exome sequencing in 1555 patients with early-onset or familial PD and 2234 healthy controls; then in the second cohort, whole-genome sequencing was performed in sporadic late-onset PD samples (1962 patients), as well as 1279 controls. Variants at target GCH1 regions were extracted, and then genetic and detailed phenotypic data were analyzed using regression models and the sequence kernel association test. We also performed a meta-analysis to correlate deleterious GCH1 variants with age at onset (AAO) in PD patients. Results For coding variants, we identified a significant burden of GCH1 deleterious variants in early-onset or familial PD cases compared to controls (1.2% vs 0.1%, P  < 0.0001). In the analysis of possible regulatory variants in GCH1 non-coding regions, rs12323905 ( P  = 0.001, odds ratio = 1.19, 95%CI 1.07–1.32) was significantly associated with PD, and variant sets in untranslated regions and intron regions, GCH1 brain-specific expression quantitative trait loci, and two possible promoter/enhancer (GH14J054857 and GH14J054880) were suggestively associated with PD. Genotype-phenotype correlation analysis revealed that the carriers of GCH1 deleterious variants manifested younger AAO ( P  < 0.0001), and had milder motor symptoms, milder fatigue symptoms and more autonomic nervous dysfunctions. Meta-analysis of six studies demonstrated 6.4-year earlier onset in GCH1 deleterious variant carriers ( P  = 0.0009). Conclusions The results highlight the importance of deleterious variants and non-coding variants of GCH1 in PD in Chinese mainland and suggest that GCH1 mutation can influence the PD phenotype, which may help design experimental studies to elucidate the mechanisms of GCH1 in the pathogenesis of PD.

Age-related macular degeneration (AMD) is a leading cause of irreversible central blindness among the elderly worldwide. We use exome sequencing to analyse nonsynonymous single-nucleotide variants (SNVs) across the whole genome of 216 neovascular AMD cases and 1,553 controls. As a follow-up validation, we evaluate 3,772 neovascular AMD cases and 6,942 controls from five independent cohorts in the East Asian population. Here we show strong evidence of an association at a novel, missense SNV, rs7739323, which is located in the ubiquitin protein ligase E3D ( UBE3D ) gene ( P meta =1.46 × 10 −9 , odds ratio (OR)=0.74, 95% confidence interval (CI): 0.63–0.88). Furthermore, ablation of the UBE3D protein lead to an abnormal amount of pigment granules deposited in retinal pigment epithelium microvilli area and an abnormal response on electroretinography (ERG) in UBE3D +/− heterozygous mice. Our findings indicate that the ubiquitin-proteasome system may play a role in the pathogenesis of neovascular AMD. Age-related macular degeneration is a prominent cause of irreversible blindness among the elderly. Here Huang et al. identify a novel missense variant in UBE3D that sheds new light on the pathogenesis of the disease.

Dopa-responsive dystonia, a rare disorder typically presenting in early childhood with lower limb dystonia and gait abnormality, responds well to levodopa. However, it is often misdiagnosed with the wide spectrum of phenotypes. By exome sequencing, we make a rapid genetic diagnosis for two atypical dopa-responsive dystonia pedigrees. One pedigree, presented with prominent parkinsonism, was misdiagnosed as Parkinson's disease until a known mutation in GCH1 (GTP cyclohydrolase 1) gene (NM_000161.2: c.631_632delAT, p.Met211ValfsX38) was found. The other pedigree was detected with a new compound heterozygous mutation in TH (tyrosine hydroxylase) gene [(NM_000360.3: c.911C>T, p.Ala304Val) and (NM_000360.3: c.1358G>A, p.Arg453His)], whose proband, a pregnant woman, required a rapid and less-biased genetic diagnosis. In conclusion, we demonstrated that exome sequencing could provide a precise and rapid genetic testing in the diagnosis of Mendelian diseases, especially for diseases with wide phenotypes.

Whole-exome sequencing has been successful in identifying genetic factors contributing to familial or sporadic Parkinson’s disease (PD). However, this approach has not been applied to explore the impact of de novo mutations on PD pathogenesis. Here, we sequenced the exomes of 39 early onset patients, their parents, and 20 unaffected siblings to investigate the effects of de novo mutations on PD. We identified 12 genes with de novo mutations (MAD1L1, NUP98, PPP2CB, PKMYT1, TRIM24, CEP131, CTTNBP2, NUS1, SMPD3, MGRN1, IFI35, and RUSC2), which could be functionally relevant to PD pathogenesis. Further analyses of two independent case-control cohorts (1,852 patients and 1,565 controls in one cohort and 3,237 patients and 2,858 controls in the other) revealed that NUS1 harbors significantly more rare nonsynonymous variants (P = 1.01E-5, odds ratio = 11.3) in PD patients than in controls. Functional studies in Drosophila demonstrated that the loss of NUS1 could reduce the climbing ability, dopamine level, and number of dopaminergic neurons in 30-day-old flies and could induce apoptosis in fly brain. Together, our data suggest that de novo mutations could contribute to early onset PD pathogenesis and identify NUS1 as a candidate gene for PD.

Germ-free mice exhibit profound immunological immaturity. Despite recent studies emphasizing the role of specific bacterium-derived metabolites in immune cell development and differentiation, the mechanisms linking microbiota absence to systemic immune deficits remain incompletely defined. Here, droplet-based single-cell RNA sequencing of bone marrow and peripheral blood from both germ-free and specific pathogen-free mice was performed, identifying 25 transcriptionally distinct cell types. Neutrophil apoptosis was elevated in germ-free mice, potentially due to the absence of niacin dehydrogenase, a metabolite primarily produced by Pseudomonas. In addition, germ-free mice exhibited increased excretion of 5'-methylthioadenosine, enhanced ERK activation driven by reactive oxygen species, and disruption of bone marrow stromal antigen 2 signaling. Monocytes and CD8· T cells from germ-free mice showed diminished responses to interferon-B and interferon-y, consistent with heightened viral susceptibility. These findings establish a microbiota-dependent regulatory pathway linking immunodeficiency to microbial absence in germ-free mice, confirmed through complementary validation techniques.

Dopa-responsive dystonia, a rare disorder typically presenting in early childhood with lower limb dystonia and gait abnormality, responds well to levodopa. However, it is often misdiagnosed with the wide spectrum of phenotypes. By exome sequencing, we make a rapid genetic diagnosis for two atypical dopa-responsive dystonia pedigrees. One pedigree, presented with prominent parkinsonism, was misdiagnosed as Parkinson's disease until a known mutation in GCH1 (GTP cyclohydrolase 1) gene (NM_000161.2: c.631_632delAT, p.Met211ValfsX38) was found. The other pedigree was detected with a new compound heterozygous mutation in TH (tyrosine hydroxylase) gene [(NM_000360.3: c.911C>T, p.Ala304Val) and (NM_000360.3: c.1358G>A, p.Arg453His)], whose proband, a pregnant woman, required a rapid and less-biased genetic diagnosis. In conclusion, we demonstrated that exome sequencing could provide a precise and rapid genetic testing in the diagnosis of Mendelian diseases, especially for diseases with wide phenotypes.

The aim of this study was to determine the impact of glycyrrhizin, an inhibitor of high mobility group box 1, on glucose metabolic disorders and ovarian dysfunction in mice with polycystic ovary syndrome. We generated a polycystic ovary syndrome mouse model by using dehydroepiandrosterone plus high-fat diet. Glycyrrhizin (100 mg/kg) was intraperitoneally injected into the polycystic ovary syndrome mice and the effects on body weight, glucose tolerance, insulin sensitivity, estrous cycle, hormone profiles, ovarian pathology, glucolipid metabolism, and some molecular mechanisms were investigated. Increased number of cystic follicles, hormonal disorders, impaired glucose tolerance, and decreased insulin sensitivity in the polycystic ovary syndrome mice were reverted by glycyrrhizin. The increased high mobility group box 1 levels in the serum and ovarian tissues of the polycystic ovary syndrome mice were also reduced by glycyrrhizin. Furthermore, increased expressions of toll-like receptor 9, myeloid differentiation factor 88, and nuclear factor kappa B as well as reduced expressions of insulin receptor, phosphorylated protein kinase B, and glucose transporter type 4 were restored by glycyrrhizin in the polycystic ovary syndrome mice. Glycyrrhizin could suppress the polycystic ovary syndrome-induced upregulation of high mobility group box 1, several inflammatory marker genes, and the toll-like receptor 9/myeloid differentiation factor 88/nuclear factor kappa B pathways, while inhibiting the insulin receptor/phosphorylated protein kinase B/glucose transporter type 4 pathways. Hence, glycyrrhizin is a promising therapeutic agent against polycystic ovary syndrome. Summary Sentence Glycyrrhizin could improve inflammation, glucose metabolic disorders, and ovarian dysfunction in polycystic ovary syndrome mice by inhibiting the expression of high mobility group box 1.

Problem: Natural killer (NK) cells from the peripheral blood and spleen represent the source from which various tissues replenish their immune cell populations. Hyperandrogenism and high interleukin-2 (IL-2) levels are factors present in polycystic ovary syndrome (PCOS). These factors and metformin, one of the commonest medications used in treating PCOS, may have an impact on NK cells. However, this is presently unknown. Here, we aimed to assess the distribution of peripheral blood and splenic NK cells and their CD2 and CD94 expression patterns in a PCOS mouse model and test whether metformin could reverse these effects. Method of study: Four mouse groups were designed as follows (n = 15/group): control, PCOS, PCOS plus vehicle, PCOS plus metformin. Dehydroepiandrosterone and a high-fat diet were administered to induce the PCOS mouse model. Flow cytometry was used to analyze the expressions of CD2 and CD94 on peripheral blood and splenic NK cells. Results: PCOS mice had a low surface-density of CD2 on peripheral blood NK cells and a decreased percentage of CD2+ splenic NK cells. Metformin administration did not significantly influence these changes; however, it reduced the splenic NK cell counts. Conclusions: Our findings proved the association of PCOS with an altered expression of CD2 on peripheral blood and splenic NK cells and that of metformin with a lowered splenic NK cell reserve in PCOS conditions. These findings could further unlock key mechanisms in PCOS pathophysiology and in the mechanism of action of metformin, towards improving PCOS management. Summary Sentence A decreased density of CD2 receptor expression on peripheral blood NK cells and a decreased percentage of CD2+ splenic NK cells were associated with PCOS but not influenced by metformin administration in a DHEA-induced PCOS mouse model. Graphical Abstract

Heart failure (HF) is a significant global public health concern with a high readmission rate, posing a serious threat to the health of the elderly population. While several studies have used machine learning (ML) to develop all-cause readmission risk prediction models for elderly patients with HF, few have integrated ML-selected features with those chosen by human experts to assess HF patients readmission. A retrospective analysis of 8396 elderly HF patients hospitalized at the Affiliated Hospital of North Sichuan Medical College from January 1, 2018 to December 31, 2021 was conducted. Variables selected by XGBoost, LASSO regression, and random forest constituted the machine group, while the human expert group comprised variables chosen by two experienced cardiovascular professors. The variables selected by both groups were combined to form a human–machine collaboration group. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC). The SHapley Additive exPlanations (SHAP) method was used to elucidate the importance of each predictive feature, explain the impact of individual features on the model, and provide visual representation. A total of 73 features were included for model development. The human–machine collaboration model, utilizing CatBoost, achieved an AUC of 0.83617, an F1-score of 0.73521, and a Brier score of 0.16536 on the validation set. This model demonstrated superior predictive performance compared to those created solely by human experts or machine. The SHAP plot was then used to visually display the feature analysis of the human–machine collaboration model, revealing HGB, NT-proBNP, smoking history, NYHA classification, and LVEF as the 5 most important features. This study indicate that the human–machine collaboration model outperforms those relying solely on human expert selection or machine algorithm at predicting all-cause readmission in elderly HF patients. The application of the SHAP method enhanced the interpretability of the model outcomes, aiding clinicians in accurately pinpointing risk factors associated with HF readmission. This advancement enables the formulation of tailored treatment strategies, offering a more personalized approach to patient care.

With environmental degradation and energy shortages, green and low-carbon development has become an industry trend, especially in regards to cold chain logistics (CCL), where energy consumption and emissions are substantial. In this context, determining how to scientifically evaluate the cold chain logistics efficiency (CCLE) under carbon emission constraints is of great significance for achieving sustainable development. This study uses the three-stage data envelopment analysis (DEA) and the Malmquist index model to analyze the overall level and regional differences regarding CCLE in China’s four major urban agglomerations, under carbon constraints, from 2010 to 2020. Then, the influencing factors of CCLE are identified through Tobit regression. The results reveal that: (1) the CCLE in the four urban agglomerations is overestimated when carbon constraints are not considered; (2) the CCLE in the four urban agglomerations shows an upward trend from 2010 to 2020, with an average annual growth rate of 1.25% in regards to total factor productivity. However, there are significant spatial and temporal variations, with low-scale efficiency being the primary constraint. (3) Different influencing factors have different directions and exert different effects on CCLE in different urban agglomerations, and the improvement of economic development levels positively affects all regions.