The risk of Alzheimer's disease and cognitive impairment characteristics in eight mental disorders: A UK Biobank observational study and Mendelian randomization analysis.

INTRODUCTION: The cognitive impairment patterns and the association with Alzheimer's disease (AD) in mental disorders remain poorly understood. METHODS: We analyzed data from 486,297 UK Biobank participants, categorizing them by mental disorder history to identify the risk of AD and the cognitive impairment characteristics. Causation was further assessed using Mendelian randomization (MR). RESULTS: AD risk was higher in individuals with bipolar disorder (BD; hazard ratio [HR] = 2.37, P < 0.01) and major depressive disorder (MDD; HR = 1.63, P < 0.001). MR confirmed a causal link between BD and AD (ORIVW = 1.098), as well as obsessive-compulsive disorder (OCD) and AD (ORIVW = 1.050). Cognitive impairments varied, with BD and schizophrenia showing widespread deficits, and OCD affecting complex task performance. DISCUSSION: Observational study and MR provide consistent evidence that mental disorders are independent risk factors for AD. Mental disorders exhibit distinct cognitive impairment prior to dementia, indicating the potential different mechanisms in AD pathogenesis. Early detection of these impairments in mental disorders is crucial for AD prevention. HIGHLIGHTS: This is the most comprehensive study that investigates the risk and causal relationships between a history of mental disorders and the development of Alzheimer's disease (AD), alongside exploring the cognitive impairment characteristics associated with different mental disorders. Individuals with bipolar disorder (BD) exhibited the highest risk of developing AD (hazard ratio [HR] = 2.37, P < 0.01), followed by those with major depressive disorder (MDD; HR = 1.63, P < 0.001). Individuals with schizophrenia (SCZ) showed a borderline higher risk of AD (HR = 2.36, P = 0.056). Two-sample Mendelian randomization (MR) confirmed a causal association between BD and AD (ORIVW = 1.098, P < 0.05), as well as AD family history (proxy-AD, ORIVW = 1.098, P < 0.001), and kept significant after false discovery rate correction. MR also identified a nominal significant causal relationship between the obsessive-compulsive disorder (OCD) spectrum and AD (ORIVW = 1.050, P < 0.05). Individuals with SCZ, BD, and MDD exhibited impairments in multiple cognitive domains with distinct patterns, whereas those with OCD showed only slight declines in complex tasks.

A detection model of cognitive impairment via the integrated gait and eye movement analysis from a large Chinese community cohort.

INTRODUCTION: Whether the integration of eye-tracking, gait, and corresponding dual-task analysis can distinguish cognitive impairment (CI) patients from controls remains unclear. METHODS: One thousand four hundred eighty-one participants, including 724 CI and 757 controls, were enrolled in this study. Eye movement and gait, combined with dual-task patterns, were measured. The LightGBM machine learning models were constructed. RESULTS: A total of 105 gait and eye-tracking features were extracted. Forty-six parameters, including 32 gait and 14 eye-tracking features, showed significant differences between two groups (P < 0.05). Of these, the Gait_3Back-TurnTime and Dual-task cost-TurnTime patterns were significantly correlated with plasma phosphorylated tau 181 (p-tau181) level. A model based on dual-task gait, dual-task smooth pursuit, prosaccade, and anti-saccade achieved the best area under the receiver operating characteristics curve (AUC) of 0.987 for CI detection, while combined with p-tau181, the model discriminated mild cognitive impairment from controls with an AUC of 0.824. DISCUSSION: Combining dual-task gait and dual-task eye-tracking analysis is feasible for the detection of CI. HIGHLIGHTS: This is the first study to report the efficiency of integrated parameters of dual-task gait and eye-tracking for cognitive impairment (CI) detection in a large cohort. We identified 46 gait and eye-tracking features associated with CI, and two were correlated to plasma phosphorylated tau 181. We constructed the model based on dual-task gait, smooth pursuit, prosaccade, and anti-saccade, achieving the best area under the curve of 0.987 for CI detection.

Specific serum autoantibodies predict the development and progression of Alzheimer's disease with high accuracy.

Autoimmunity plays a key role in the pathogenesis of Alzheimer's disease (AD). However, whether autoantibodies in peripheral blood can be used as biomarkers for AD has been elusive. Serum samples were obtained from 1,686 participants, including 767 with AD, 146 with mild cognitive impairment (MCI), 255 with other neurodegenerative diseases, and 518 healthy controls. Specific autoantibodies were measured using a custom-made immunoassay. Multivariate support vector machine models were employed to investigate the correlation between serum autoantibody levels and disease states. As a result, seven candidate AD-specific autoantibodies were identified, including MAPT, DNAJC8, KDM4D, SERF1A, CDKN1A, AGER, and ASXL1. A classification model with high accuracy (area under the curve (AUC) = 0.94) was established. Importantly, these autoantibodies could distinguish AD from other neurodegenerative diseases and out-performed amyloid and tau protein concentrations in cerebrospinal fluid in predicting cognitive decline (P < 0.001). This study indicated that AD onset and progression are possibly accompanied by an unappreciated serum autoantibody response. Therefore, future studies could optimize its application as a convenient biomarker for the early detection of AD.

Development of a deep learning-based model to diagnose mixed-type gastric cancer accurately.

OBJECTIVE: The accurate diagnosis of mixed-type gastric cancer from pathology images presents a formidable challenge for pathologists, given its intricate features and resemblance to other subtypes of gastric cancer. Artificial Intelligence has the potential to overcome this hurdle. This study aimed to leverage deep machine learning techniques to establish a precise and efficient diagnostic approach for this cancer type which can also predict the metastatic risk using two software, U-Net and QuPath, which have not been trialled in gastric cancers. METHODS: A U-Net neural network was trained to recognise, and segment differentiated components from 186 pathology images of mixed-type gastric cancer. Undifferentiated components in the same images were annotated using the open-source pathology imaging software QuPath. The outcomes from U-Net and QuPath were used to calculate the ratios of differentiation/undifferentiated components which were correlated to lymph node metastasis. RESULTS: The models established by U-Net recognised ∼91% of the regions of interest, with precision, recall, and F1 values of 90.2%, 90.9% and 94.6%, respectively, indicating a high level of accuracy and reliability. Furthermore, the receiver operating characteristic curve analysis showed an area under the cure of 91%, indicating good performance. A bell-curve correlation between the differentiated/undifferentiated ratio and lymphatic metastasis was found (highest risk between 0.683 and 1.03), which is paradigm-shifting. CONCLUSION: U-Net and QuPath exhibit promising accuracy in the identification of differentiated and undifferentiated components in mixed-type gastric cancer, as well as paradigm-shifting prediction of metastasis. These findings bring us one step closer to their potential clinical application.

Mendelian randomization analyses of smoking and Alzheimer's disease in Chinese and Japanese populations.

Background: Previous epidemiological studies have reported controversial results on the relationship between smoking and Alzheimer's disease (AD). Therefore, we sought to assess the association using Mendelian randomization (MR) analysis. Methods: We used single nucleotide polymorphisms (SNPs) associated with smoking quantity (cigarettes per day, CPD) from genome-wide association studies (GWAS) of Japanese population as instrumental variables, then we performed two-sample MR analysis to investigate the association between smoking and AD in a Chinese cohort (1,000 AD cases and 500 controls) and a Japanese cohort (3,962 AD cases and 4,074 controls), respectively. Results: Genetically higher smoking quantity showed no statistical causal association with AD risk (the inverse variance weighted (IVW) estimate in the Chinese cohort: odds ratio (OR) = 0.510, 95% confidence interval (CI) = 0.149-1.744, p = 0.284; IVW estimate in the Japanese cohort: OR = 1.170, 95% confidence interval CI = 0.790-1.734, p = 0.434). Conclusion: This MR study, for the first time in Chinese and Japanese populations, found no significant association between smoking and AD.

Correlation between retinal structure and brain multimodal magnetic resonance imaging in patients with Alzheimer's disease.

Background: The retina imaging and brain magnetic resonance imaging (MRI) can both reflect early changes in Alzheimer's disease (AD) and may serve as potential biomarker for early diagnosis, but their correlation and the internal mechanism of retinal structural changes remain unclear. This study aimed to explore the possible correlation between retinal structure and visual pathway, brain structure, intrinsic activity changes in AD patients, as well as to build a classification model to identify AD patients. Methods: In the study, 49 AD patients and 48 healthy controls (HCs) were enrolled. Retinal images were obtained by optical coherence tomography (OCT). Multimodal MRI sequences of all subjects were collected. Spearman correlation analysis and multiple linear regression models were used to assess the correlation between OCT parameters and multimodal MRI findings. The diagnostic value of combination of retinal imaging and brain multimodal MRI was assessed by performing a receiver operating characteristic (ROC) curve. Results: Compared with HCs, retinal thickness and multimodal MRI findings of AD patients were significantly altered (p < 0.05). Significant correlations were presented between the fractional anisotropy (FA) value of optic tract and mean retinal thickness, macular volume, macular ganglion cell layer (GCL) thickness, inner plexiform layer (IPL) thickness in AD patients (p < 0.01). The fractional amplitude of low frequency fluctuations (fALFF) value of primary visual cortex (V1) was correlated with temporal quadrant peripapillary retinal nerve fiber layer (pRNFL) thickness (p < 0.05). The model combining thickness of GCL and temporal quadrant pRNFL, volume of hippocampus and lateral geniculate nucleus, and age showed the best performance to identify AD patients [area under the curve (AUC) = 0.936, sensitivity = 89.1%, specificity = 87.0%]. Conclusion: Our study demonstrated that retinal structure change was related to the loss of integrity of white matter fiber tracts in the visual pathway and the decreased LGN volume and functional metabolism of V1 in AD patients. Trans-synaptic axonal retrograde lesions may be the underlying mechanism. Combining retinal imaging and multimodal MRI may provide new insight into the mechanism of retinal structural changes in AD and may serve as new target for early auxiliary diagnosis of AD.

Oncogenic zinc finger protein ZNF687 accelerates lung adenocarcinoma cell proliferation and tumor progression by activating the PI3K/AKT signaling pathway.

BACKGROUND: Zinc finger protein 687 (ZNF687) has previously been discovered as a potential oncogene in individuals with giant cell tumors of the bone, acute myeloid leukemia, and hepatocellular carcinoma. However, its role and mechanism in lung adenocarcinoma (LUAD) remain unclear. METHODS: In LUAD cells, tumor, and matched adjacent tissue specimens, quantitative real-time RT- polymerase chain reaction (qRT-PCR), western blotting analyses, and immunohistochemistry staining (IHC) were conducted. Cell counting kit-8 (CCK8) assay, clonogenicity analysis, flow cytometry, and transwell assays were utilized to detect ZNF687 overexpression and knockdown impacts on cell growth, colony formation, cell cycle, migration, and invasion. Bioinformatic studies, qRT-PCR and western blotting studies were employed to validate the underlying mechanisms and signaling pathways implicated in the oncogenic effect of ZNF687. RESULTS: This study demonstrated that ZNF687 expression was elevated in LUAD cells and tissues. Individuals with upregulated ZNF687 had a poorer prognosis than those with downregulatedZNF687 (p < 0.001). ZNF687 overexpression enhanced LUAD growth, migration, invasion and colony formation, and the cell cycle G1-S transition; additionally, it promoted the epithelial-mesenchymal transition (EMT). In contrast, knocking down ZNF687 showed to have the opposite impact. Moreover, these effects were associated with the activity of the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling mechanism. CONCLUSION: ZNF687 was upregulated in LUAD, and high ZNF687 expression levels are associated with poor prognoses. The activation of the PI3K/AKT signaling pathway by upregulated ZNF687 increased the proliferation of LUAD cells and tumor progression. ZNF687 may be a beneficial predictive marker and a therapeutic target in LUAD.

Neural biomarker diagnosis and prediction to mild cognitive impairment and Alzheimer's disease using EEG technology.

BACKGROUND: Electroencephalogram (EEG) has emerged as a non-invasive tool to detect the aberrant neuronal activity related to different stages of Alzheimer's disease (AD). However, the effectiveness of EEG in the precise diagnosis and assessment of AD and its preclinical stage, amnestic mild cognitive impairment (MCI), has yet to be fully elucidated. In this study, we aimed to identify key EEG biomarkers that are effective in distinguishing patients at the early stage of AD and monitoring the progression of AD. METHODS: A total of 890 participants, including 189 patients with MCI, 330 patients with AD, 125 patients with other dementias (frontotemporal dementia, dementia with Lewy bodies, and vascular cognitive impairment), and 246 healthy controls (HC) were enrolled. Biomarkers were extracted from resting-state EEG recordings for a three-level classification of HC, MCI, and AD. The optimal EEG biomarkers were then identified based on the classification performance. Random forest regression was used to train a series of models by combining participants' EEG biomarkers, demographic information (i.e., sex, age), CSF biomarkers, and APOE phenotype for assessing the disease progression and individual's cognitive function. RESULTS: The identified EEG biomarkers achieved over 70% accuracy in the three-level classification of HC, MCI, and AD. Among all six groups, the most prominent effects of AD-linked neurodegeneration on EEG metrics were localized at parieto-occipital regions. In the cross-validation predictive analyses, the optimal EEG features were more effective than the CSF + APOE biomarkers in predicting the age of onset and disease course, whereas the combination of EEG + CSF + APOE measures achieved the best performance for all targets of prediction. CONCLUSIONS: Our study indicates that EEG can be used as a useful screening tool for the diagnosis and disease progression evaluation of MCI and AD.

GSN gene frameshift mutations in Alzheimer's disease.

BACKGROUND: The pathogenic missense mutations of the gelsolin (GSN) gene lead to familial amyloidosis of the Finnish type (FAF); however, our previous study identified GSN frameshift mutations existed in patients with Alzheimer's disease (AD). The GSN genotype-phenotype heterogeneity and the role of GSN frameshift mutations in patients with AD are unclear. METHOD: In total, 1192 patients with AD and 1403 controls were screened through whole genome sequencing, and 884 patients with AD were enrolled for validation. Effects of GSN mutations were evaluated in vitro. GSN, Aß42, Aß40 and Aß42/40 were detected in both plasma and cerebrospinal fluid (CSF). RESULTS: Six patients with AD with GSN P3fs and K346fs mutations (0.50%, 6/1192) were identified, who were diagnosed with AD but not FAF. In addition, 13 patients with AD with GSN frameshift mutations were found in the validation cohort (1.47%, 13/884). Further in vitro experiments showed that both K346fs and P3fs mutations led to the GSN loss of function in inhibiting Aß-induced toxicity. Moreover, a higher level of plasma (p=0.001) and CSF (p=0.005) GSN was observed in AD cases than controls, and a positive correlation was found between the CSF GSN and CSF Aß42 (r=0.289, p=0.009). Besides, the GSN level was initially increasing and then decreasing with the disease course and cognitive decline. CONCLUSIONS: GSN frameshift mutations may be associated with AD. An increase in plasma GSN is probably a compensatory reaction in AD, which is a potential biomarker for early AD.

The associations of APP, PSEN1, and PSEN2 genes with Alzheimer's disease: A large case-control study in Chinese population.

AIM: The associations of non-pathogenic variants of APP, PSEN1, and PSEN2 with Alzheimer's disease (AD) remain unclear. This study is aimed at determining the role of these variants in AD. METHODS: Our study recruited 1154 AD patients and 2403 controls. APP, PSEN1, PSEN2, and APOE were sequenced using a targeted panel. Variants were classified into common or rare variants with the minor allele frequencies (MAF) cutoff of 0.01. Common variant (MAF≥0.01)-based association test was performed by PLINK 1.9, and gene-based (MAF <0.01) association analysis was conducted using Sequence Kernel Association Test-Optimal (SKAT-O test). Additionally, using PLINK 1.9, we performed AD endophenotypes association studies. RESULTS: A common variant, PSEN2 rs11405, was suggestively associated with AD risk (p = 1.08 × 10-2 ). The gene-based association analysis revealed that the APP gene exhibited a significant association with AD (p = 1.43 × 10-2 ). In the AD endophenotypes association studies, APP rs459543 was nominally correlated with CSF Aß42 level (p = 7.91 × 10-3 ). CONCLUSION: Our study indicated that non-pathogenic variants in PSEN2 and APP may be involved in AD pathogenesis in the Chinese population.

Clinical characteristics and genotype-phenotype correlation analysis of familial Alzheimer's disease patients with pathogenic/likely pathogenic amyloid protein precursor mutations.

Alzheimer's disease (AD) is a progressive neurodegenerative disease associated with aging, environmental, and genetic factors. Amyloid protein precursor (APP) is a known pathogenic gene for familial Alzheimer's disease (FAD), and now more than 70 APP mutations have been reported, but the genotype-phenotype correlation remains unclear. In this study, we collected clinical data from patients carrying APP mutations defined as pathogenic/likely pathogenic according to the American college of medical genetics and genomics (ACMG) guidelines. Then, we reanalyzed the clinical characteristics and identified genotype-phenotype correlations in APP mutations. Our results indicated that the clinical phenotypes of APP mutations are generally consistent with typical AD despite the fact that they show more non-demented symptoms and neurological symptoms. We also performed genotype-phenotype analysis according to the difference in APP processing caused by the mutations, and we found that there were indeed differences in onset age, behavioral and psychological disorders of dementia (BPSD) and myoclonus.

Associations of multiple visual rating scales based on structural magnetic resonance imaging with disease severity and cerebrospinal fluid biomarkers in patients with Alzheimer's disease.

The relationships between multiple visual rating scales based on structural magnetic resonance imaging (sMRI) with disease severity and cerebrospinal fluid (CSF) biomarkers in patients with Alzheimer's disease (AD) were ambiguous. In this study, a total of 438 patients with clinically diagnosed AD were recruited. All participants underwent brain sMRI scan, and medial temporal lobe atrophy (MTA), posterior atrophy (PA), global cerebral atrophy-frontal sub-scale (GCA-F), and Fazekas rating scores were visually evaluated. Meanwhile, disease severity was assessed by neuropsychological tests such as the Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), and Clinical Dementia Rating (CDR). Among them, 95 patients were tested for CSF core biomarkers, including Aß1-42, Aß1-40, Aß1-42/Aß1-40, p-tau, and t-tau. As a result, the GCA-F and Fazekas scales showed positively significant correlations with onset age (r = 0.181, p < 0.001; r = 0.411, p < 0.001, respectively). Patients with late-onset AD (LOAD) showed higher GCA-F and Fazekas scores (p < 0.001, p < 0.001). With regard to the disease duration, the MTA and GCA-F were positively correlated (r = 0.137, p < 0.05; r = 0.106, p < 0.05, respectively). In terms of disease severity, a positively significant association emerged between disease severity and the MTA, PA GCA-F, and Fazekas scores (p < 0.001, p < 0.001, p < 0.001, p < 0.05, respectively). Moreover, after adjusting for age, gender, and APOE alleles, the MTA scale contributed to moderate to severe AD in statistical significance independently by multivariate logistic regression analysis (p < 0.05). The model combining visual rating scales, age, gender, and APOE alleles showed the best performance for the prediction of moderate to severe AD significantly (AUC = 0.712, sensitivity = 51.5%, specificity = 84.6%). In addition, we observed that the MTA and Fazekas scores were associated with a lower concentration of Aß1-42 (p < 0.031, p < 0.022, respectively). In summary, we systematically analyzed the benefits of multiple visual rating scales in predicting the clinical status of AD. The visual rating scales combined with age, gender, and APOE alleles showed best performance in predicting the severity of AD. MRI biomarkers in combination with CSF biomarkers can be used in clinical practice.

CYLD variants identified in Alzheimer's disease and frontotemporal dementia patients.

OBJECTIVES: CYLD was a novel causative gene for frontotemporal dementia (FTD) and amyotrophic lateral sclerosis. Given the clinical and pathological overlap of FTD and Alzheimer's disease (AD), it is necessary to screen CYLD in AD patients and FTD patients in the Chinese population. METHODS: In our study, using a targeted sequencing panel, we sequenced the CYLD gene in a large cohort of 2485 participants in the Chinese population, including 1008 AD patients, 105 FTD patients, and 1372 controls. RESULTS: In the present study, the average onset age of AD and FTD patients was 66.84 ± 30.42 years old and 60 ± 10.00 years old, respectively. Our study reported three novel CYLD variants: p.Phe288Leu (patient No. 1, AD), p.Tyr485Phe (patients No. 6-9, all AD) and p.Thr951Ala (patient No. 10, AD), plus a previously reported variant: p.Arg397Ser (patient No. 2-5, AD and No. 11, FTD). These variants were absent in our in-house controls and predicted to be deleterious according to the MutationTaster. The variant carriers were composed of 10 AD patients and one FTD patient, and the average onset age was 61.2 ± 10.9 years. The frequency of CYLD variants in AD was similar to that in FTD, which was 0.99% (10/1008) and 0.95% (1/105), respectively. INTERPRETATION: Our finding extended the genotype and phenotype of the CYLD gene and demonstrated that CYLD rare damaging variants may be implicated in AD and FTD pathogenesis.

Genetics of progressive supranuclear palsy in a Chinese population.

BACKGROUND: Genetics plays an important role in progressive supranuclear palsy (PSP) and remains poorly understood. A detailed literature search identified 19 PSP-associated genes: MAPT, LRRK2, LRP10, DCTN1, GRN, NPC1, PARK, TARDBP, TBK1, BSN, GBA, STX6, EIF2AK3, MOBP, DUSP10, SLCO1A2, RUNX2, CXCR4, and APOE. To date, genetic studies on PSP have focused on Caucasian population. The gaps in PSP genetic study on East Asian populations need to be filled. METHODS: Exon and flanking regions of the PSP-associated genes were sequenced in 104 patients with PSP and 488 healthy controls. Common variant-based association analysis and gene-based association tests of rare variants were performed using PLINK 1.9 and the sequence kernel association test-optimal, respectively. Additionally, the association of APOE and MAPT genotypes with PSP was evaluated. The above association analyses were repeated among probable PSP patients. Finally, PLINK 1.9 was used to test variants associated with the onset age of PSP. RESULTS: A rare non-pathogenic variant of MAPT (c.425C > T,p.A142V) was detected in a PSP patient. No common variants were significantly associated with PSP. In both the rare-variant and the rare-damaging-variant groups, the combined effect for GBA reached statistical significance (p = 1.43 × 10-3, p = 4.98 × 10-4). The result between APOE, MAPT genotypes and PSP risk were inconsistent across all PSP group and probably PSP group. CONCLUSIONS: The pathogenic variant in MAPT were uncommon in PSP patients. Moreover, GBA gene was likely to increase the risk of PSP, and GBA-associated diseases were beyond α-synucleinopathies. The association between APOE, MAPT and PSP is still unclear among the non-Caucasian population.

Variants in the Niemann-pick type C genes are not associated with Alzheimer's disease: a large case-control study in the Chinese population.

Despite the similar clinical and pathological features between Niemann-Pick type C (NPC) disease and Alzheimer's disease (AD), few studies have investigated the role of NPC genes in AD. To elucidate the role of NPC genes in AD, we sequenced NPC1 and NPC2 in 1192 AD patients and 2412 controls. Variants were divided into common variants and rare variants according to minor allele frequency (MAF). Common variant (MAF≥0.01) based association analysis was conducted by PLINK 1.9. Gene-based aggregation testing of rare variants was performed by Sequence Kernel Association Test-Optimal (SKAT-O test), respectively. Age at onset (AAO) and mini-mental state examination (MMSE) association studies were also performed with PLINK 1.9. Six common variants were identified and exhibited no association with AD. Gene-based aggregation testing revealed that both NPC1 and NPC2 were not associated with AD risk. Additionally, AAO and MMSE association studies revealed that no common variants were linked with AD endophenotypes. Taken together, our study indicated that NPC1 and NPC2 may not be implicated in AD pathogenesis in the Chinese population.

Maternal Cigarette Smoke Exposure Exaggerates the Behavioral Defects and Neuronal Loss Caused by Hypoxic-Ischemic Brain Injury in Female Offspring.

OBJECTIVE: Hypoxic-ischemic encephalopathy affects ∼6 in 1,000 preterm neonates, leading to significant neurological sequela (e.g., cognitive deficits and cerebral palsy). Maternal smoke exposure (SE) is one of the common causes of neurological disorders; however, female offspring seems to be less affected than males in our previous study. We also showed that maternal SE exaggerated neurological disorders caused by neonatal hypoxic-ischemic brain injury in adolescent male offspring. Here, we aimed to examine whether female littermates of these males are protected from such insult. METHODS: BALB/c dams were exposed to cigarette smoke generated from 2 cigarettes twice daily for 6 weeks before mating, during gestation and lactation. To induce hypoxic-ischemic brain injury, half of the pups from each litter underwent left carotid artery occlusion, followed by exposure to 8% oxygen (92% nitrogen) at postnatal day (P) 10. Behavioral tests were performed at P40-44, and brain tissues were collected at P45. RESULTS: Maternal SE worsened the defects in short-term memory and motor function in females with hypoxic-ischemic injury; however, reduced anxiety due to injury was observed in the control offspring, but not the SE offspring. Both hypoxic-ischemic injury and maternal SE caused significant loss of neuronal cells and synaptic proteins, along with increased oxidative stress and inflammatory responses. CONCLUSION: Oxidative stress and inflammatory response due to maternal SE may be the mechanism of worsened neurological outcomes by hypoxic-ischemic brain injury in females, which was similar to their male littermates shown in our previous study.

Associations of risk genes with onset age and plasma biomarkers of Alzheimer's disease: a large case-control study in mainland China.

Most genetic studies concerning risk genes in Alzheimer's disease (AD) are from Caucasian populations, whereas the data remain limited in the Chinese population. In this study, we systematically explored the relationship between AD and risk genes in mainland China. We sequenced 33 risk genes previously reported to be associated with AD in a total of 3604 individuals in the mainland Chinese population. Common variant (MAF ≥ 0.01) based association analysis and gene-based (MAF < 0.01) association test were performed by PLINK 1.9 and Sequence Kernel Association Test-Optimal, respectively. Polygenic risk score (PRS) was calculated, and receiver operating characteristic curve (AUC) was computed. Plasma Aß42, Aß40, total tau (T-tau), and neurofilament light chain (NFL) were tested in a subgroup, and their associations with PRS were conducted using the Spearman correlation test. Six common variants varied significantly between AD patients and cognitively normal controls after the adjustment of age, gender, and APOE ε4 status, including variants in ABCA7 (n = 5) and APOE (n = 1). Among them, four variants were novel and two were reported previously. The AUC of PRS was 0.71. The high PRS was significantly associated with an earlier age at onset (P = 4.30 × 10-4). PRS was correlated with plasma Aß42, Aß42/Aß40 ratio, T-tau, and NFL levels. Gene-based association test revealed that ABCA7 and UNC5C reached statistical significance. The common variants in APOE and ABCA7, as well as rare variants in ABCA7 and UNC5C, may contribute to the etiology of AD. Moreover, the PRS, to some extent, could predict the risk, onset age, and biological changes of AD.

Mutations in GBA, SNCA, and VPS35 are not associated with Alzheimer's disease in a Chinese population: a case-control study.

SNCA, GBA, and VPS35 are three common genes associated with Parkinson's disease. Previous studies have shown that these three genes may be associated with Alzheimer's disease (AD). However, it is unclear whether these genes increase the risk of AD in Chinese populations. In this study, we used a targeted gene sequencing panel to screen all the exon regions and the nearby sequences of GBA, SNCA, and VPS35 in a cohort including 721 AD patients and 365 healthy controls from China. The results revealed that neither common variants nor rare variants of these three genes were associated with AD in a Chinese population. These findings suggest that the mutations in GBA, SNCA, and VPS35 are not likely to play an important role in the genetic susceptibility to AD in Chinese populations. The study was approved by the Ethics Committee of Xiangya Hospital, Central South University, China on March 9, 2016 (approval No. 201603198).

Association Between Serum Vitamins and the Risk of Alzheimer's Disease in Chinese Population.

BACKGROUND: Alzheimer's disease (AD) is a chronic and fatal neurodegenerative disease; accumulating evidence suggests that vitamin deficiency is associated with the risk of AD. However, studies attempting to elucidate the relationship between vitamins and AD varied widely. OBJECTIVE: This study aimed to investigate the relationship between serum vitamin levels and AD in a cohort of the Chinese population. METHODS: A total of 368 AD patients and 574 healthy controls were recruited in this study; serum vitamin A, B1, B6, B9, B12, C, D, and E were measured in all participants. RESULTS: Compared with the controls, vitamin B2, B9, B12, D, and E were significantly reduced in AD patients. Lower levels of vitamin B2, B9, B12, D, and E were associated with the risk of AD. After adjusting for age and gender, low levels of vitamin B2, B9, and B12 were still related to the risk of AD. In addition, a negative correlation was determined between vitamin E concentration and Activity of Daily Living Scale score while no significant association was found between serum vitamins and age at onset, disease duration, Mini-Mental State Examination, and Neuropsychiatric Inventory Questionnaire score. CONCLUSION: We conclude that lower vitamin B2, B9, B12, D, and E might be associated with the risk of AD, especially vitamin B2, B9, and B12. And lower vitamin E might be related to severe ability impairment of daily activities.

Performance of Plasma Amyloid ß, Total Tau, and Neurofilament Light Chain in the Identification of Probable Alzheimer's Disease in South China.

Background: Alzheimer's disease (AD) is the most common type of dementia and has no effective treatment to date. It is essential to develop a minimally invasive blood-based biomarker as a tool for screening the general population, but the efficacy remains controversial. This cross-sectional study aimed to evaluate the ability of plasma biomarkers, including amyloid ß (Aß), total tau (t-tau), and neurofilament light chain (NfL), to detect probable AD in the South Chinese population. Methods: A total of 277 patients with a clinical diagnosis of probable AD and 153 healthy controls with normal cognitive function (CN) were enrolled in this study. The levels of plasma Aß42, Aß40, t-tau, and NfL were detected using ultra-sensitive immune-based assays (SIMOA). Lumbar puncture was conducted in 89 patients with AD to detect Aß42, Aß40, t-tau, and phosphorylated (p)-tau levels in the cerebrospinal fluid (CSF) and to evaluate the consistency between plasma and CSF biomarkers through correlation analysis. Finally, the diagnostic value of plasma biomarkers was further assessed by constructing a receiver operating characteristic (ROC) curve. Results: After adjusting for age, sex, and the apolipoprotein E (APOE) alleles, compared to the CN group, the plasma t-tau, and NfL were significantly increased in the AD group (p < 0.01, Bonferroni correction). Correlation analysis showed that only the plasma t-tau level was positively correlated with the CSF t-tau levels (r = 0.319, p = 0.003). The diagnostic model combining plasma t-tau and NfL levels, and age, sex, and APOE alleles, showed the best performance for the identification of probable AD [area under the curve (AUC) = 0.89, sensitivity = 82.31%, specificity = 83.66%]. Conclusion: Blood biomarkers can effectively distinguish patients with probable AD from controls and may be a non-invasive and efficient method for AD pre-screening.