Primary coenzyme Q10 deficiency due to COQ8A

Abstract Background Primary deficiency of coenzyme Q10 deficiency‐4 (COQ10D4) is an autosomal recessive cerebellar ataxia with mitochondrial respiratory chain disfunction. The main clinical manifestation involves early‐onset exercise intolerance, progressive cerebellar ataxia, and movement disorders. COQ8A gene mutations are responsible for this disease. Here, we provide clinical, laboratory, and genetic findings of a patient with cerebellar ataxia caused by compound heterozygous mutations in COQ8A gene. Methods A male patient from a non‐consanguineous Chinese family underwent detailed physical and auxiliary examination. After exclusion of acquired causes of ataxia, Friedreich's Ataxia, and common types of spinocerebellar ataxia, the patient was subjected to whole exome sequencing (WES) followed by confirmation of sequence variants using Sanger sequencing. His asymptomatic parents, two brothers and one sister were genotyped for these variants. Results This patient showed early‐onset exercise intolerance and progressive cerebellar ataxia, wide‐based gait and tremor, accompanied by symptoms of dysautonomia. His serum lactate level was elevated and plasma total Coenzyme Q10 (CoQ10) was decreased. Brain MRI showed cerebellar atrophy, and X‐ray of the spine revealed thoraco‐lumbar scoliosis. Compound heterozygous mutations in the COQ8A gene were identified through WES: c.1844_1845insG, p.Ser616Leufs*114 and c.902G>A, p.Arg301Gln. After treatment with ubidecarenone, 40 mg three times per day for 2 years, the symptoms dramatically improved. Conclusions We identified a patient with COQ10D4 caused by novel COQ8A mutations. Our findings widen the spectrum of COQ8A gene mutations and clinical manifestations

Hyperphosphorylation of Tau Protein in Hippocampus of Central Insulin-Resistant Rats is Associated with Cognitive Impairment

Background: Alzheimer's disease (AD) is one of the most common neurodegenerative diseases. Peripheral insulin resistance increases the risk for memory impairment and the development of AD. Objective: This study aims to assess changes in cognitive functions and the level of hyperphosphorylated tau proteins in central insulin-resistant rats. Methods: An in vivo central insulin-resistant (CIR) animal model was generated through intracerebroventricular injection of streptozotocin (STZ) into insulin-resistant (IR) rats that were induced by feeding a high-glucose/-protein/-fat diet. The Morris water maze test was used to assess changes in cognitive functions, pathological changes in the cornu ammonis 1 (CA1) region of the hippocampus were detected by immunohistochemistry, and the phosphorylation levels of tau proteins at specific sites were determined by Western blot analysis. Results: The escape latency time in the Morris water maze test was significantly prolonged; the number of phosphorylated tau proteins in the CA1 region of the hippocampus was significantly increased; and the phosphorylation levels of tau proteins at Ser199, Thr205, Thr212, Thr217 and Ser396 were significantly elevated in the CIR group compared with the IR and control groups. Conclusion: This study provides direct evidence that CIR plays an important role in AD pathogenesis by facilitating tau hyperphosphorylation

A large scale 16S ribosomal RNA gene amplicon dataset of hand, foot and mouth patients and healthy individuals

Abstract There is evidence linking hand, foot and mouth disease (HFMD) to gut microbiota dysbiosis, and this relationship was corroborated in a large HFMD patient population in our previous study. Here, we present a bacterial 16S rRNA gene dataset from faecal samples of 713 individuals (254 HFMD patients, 459 healthy controls) aged 2 to 7 years residing in Heyuan and Jiangmen counties, Guangdong Province, southern China. Microbiome analysis indicated a significant increase in genus Prevotella, Cetobacterium, and Megamonas was observed in patients with HFMD, whereas a large increase in genus Bacteroides, Ruminococcus, and Faecalibacterium were seen in the control group. We also share the bioinformatic analytical pipeline for this analysis, from data preprocessing to data filtering and amplicon sequence variant (ASV) table generation. We expect that the dataset will be reprocessed, evaluated and fully analysed with various analysis methods to further elucidate the role of the gut microbiota in HFMD development

Effect of renal function on the diagnostic performance of plasma biomarkers for Alzheimer’s disease

BackgroundSeveral blood-based biomarkers are promising to be used in the diagnosis of Alzheimer’s disease (AD) including Aβ42/40, p-tau181, and neurofilament light (NfL). The kidney is associated with the clearance of proteins. It is crucial to evaluate the effect of renal function on the diagnostic performance of these biomarkers before clinical implementation, which is important for the establishment of reference ranges and the interpretation of results.MethodsThis study is a cross-sectional analysis based on ADNI cohort. Renal function was determined by the estimated glomerular filtration rate (eGFR). Plasma Aβ42/40 was measured by liquid chromatography–tandem mass spectrometry (LC–MS/MS). Plasma p-tau181 and NfL were analyzed by Single Molecule array (Simoa) technique. [18F] florbetapir-PET (Aβ-PET) was used as a reference standard to estimate the brain amyloid load. The cutoff of Aβ-PET positivity was defined as ≥1.11. Linear regression models were used to investigate the associations of continuous eGFR with each plasma biomarker separately. The diagnostic accuracies of plasma biomarkers for positive brain amyloid across different renal function groups were analyzed by Receiver operating characteristic (ROC) curve. Youden-Index was used to determine the cutoff levels.ResultsA total of 645 participants were included in this study. The levels and diagnostic performance of Aβ42/40 were not affected by renal function. eGFR was only found negatively associated with p-tau181 levels in Aβ-PET negetive sample (β = −0.09, p = 0.039). eGFR was found negatively associated with NfL levels both in whole sample and Aβ-PET stratified groups (β = −0.27, p < 0.001 in whole sample; β = −0.28, p = 0.004 in A−; β = −0.27, p < 0.001 in A+). The diagnostic accuracies of p-tau181 and NfL were not affected by renal function. But the cutoff values of p-tau181 and NfL changed in participants with mild to moderate eGFR decline compared to participants with normal eGFR.ConclusionPlasma Aβ42/40 was a robust biomarker for AD which was not affected by renal function. Plasma p-tau181 and NfL levels were affected by renal function, specific reference values of them should be considered in populations with different renal function stages

Identification of novel diagnostic panel for mild cognitive impairment and Alzheimer’s disease: findings based on urine proteomics and machine learning

Abstract Background Alzheimer’s disease is a prevalent disease with a heavy global burden. Proteomics is the systematic study of proteins and peptides to provide comprehensive descriptions. Aiming to obtain a more accurate and convenient clinical diagnosis, researchers are working for better biomarkers. Urine is more convenient which could reflect the change of disease at an earlier stage. Thus, we conducted a cross-sectional study to investigate novel diagnostic panels. Methods We firstly enrolled participants from China-Japan Friendship Hospital from April 2022 to November 2022, collected urine samples, and conducted an LC–MS/MS analysis. In parallel, clinical data were collected, and clinical examinations were performed. After statistical and bioinformatics analyses, significant risk factors and differential urinary proteins were determined. We attempt to investigate diagnostic panels based on machine learning including LASSO and SVM. Results Fifty-seven AD patients, 43 MCI patients, and 62 CN subjects were enrolled. A total of 3366 proteins were identified, and 608 urine proteins were finally included in the analysis. There were 33 significantly differential proteins between the AD and CN groups and 15 significantly differential proteins between the MCI and CN groups. AD diagnostic panel included DDC, CTSC, EHD4, GSTA3, SLC44A4, GNS, GSTA1, ANXA4, PLD3, CTSH, HP, RPS3, CPVL, age, and APOE ε4 with an AUC of 0.9989 in the training test and 0.8824 in the test set while MCI diagnostic panel included TUBB, SUCLG2, PROCR, TCP1, ACE, FLOT2, EHD4, PROZ, C9, SERPINA3, age, and APOE ε4 with an AUC of 0.9985 in the training test and 0.8143 in the test set. Besides, diagnostic proteins were weakly correlated with cognitive functions. Conclusions In conclusion, the procedure is convenient, non-invasive, and useful for diagnosis, which could assist physicians in differentiating AD and MCI from CN

The cost of Alzheimer\u27s disease in China and re-estimation of costs worldwide

INTRODUCTION: The socioeconomic costs of Alzheimer\u27s disease (AD) in China and its impact on global economic burden remain uncertain. METHODS: We collected data from 3098 patients with AD in 81 representative centers across China and estimated AD costs for individual patient and total patients in China in 2015. Based on this data, we re-estimated the worldwide costs of AD. RESULTS: The annual socioeconomic cost per patient was US $19,144.36, and total costs were US$167.74 billion in 2015. The annual total costs are predicted to reach US $507.49 billion in 2030 and US$1.89 trillion in 2050. Based on our results, the global estimates of costs for dementia were US $957.56 billion in 2015, and will be US$2.54 trillion in 2030, and US $9.12 trillion in 2050, much more than the predictions by the World Alzheimer Report 2015. DISCUSSION: China bears a heavy burden of AD costs, which greatly change the estimates of AD cost worldwide