BackgroundWe aimed to explore the impact of hepatitis B virus (HBV) infection on the prevalence of nonalcoholic fatty liver disease (NAFLD) based on clinical big data.MethodsData were collected from the health examination center of the First Affiliated Hospital of Fujian Medical University. Univariate and multivariate analysis were applied to investigate the relationship between HBV and NAFLD.ResultsA total of 14 452 patients were included, with an average age of 43.84 ± 13.03 years. Cases of HBV current infection, past infection, and noninfection were 21 102 110 (14.6%), 90 039 003 (62.3%), and 33 393 339 (23.1%), respectively. The prevalence of NAFLD was significantly lower in the current infection group (29.9%) than in the past infection group (35.8%) and noninfection group (31.9%) (P < .001). After adjusting for age, the prevalence of NAFLD in the current infection group remained the lowest across all of the age groups. Multivariate analysis showed that current infection was at a lower risk of NAFLD (odds ratio [OR] = 0.717, 95% CI: 0.608‐0.846), whereas past infection had no effect on NAFLD.ConclusionsCurrent HBV infection may lower the risk of NAFLD. This effect becomes insignificant when the patient is no longer infected.

Background Autosomal-dominant Alzheimer's disease (ADAD) is caused by pathogenic mutations in APP, PSEN1, and PSEN2, which usually lead to an early age at onset (< 65). Circular RNAs are a family of non-coding RNAs highly expressed in the nervous system and especially in synapses. We aimed to investigate differences in brain gene expression of linear and circular transcripts from the three ADAD genes in controls, sporadic AD, and ADAD. Methods We obtained and sequenced RNA from brain cortex using standard protocols. Linear counts were obtained using the TOPMed pipeline; circular counts, using python package DCC. After stringent quality control (QC), we obtained the counts for PSEN1, PSEN2 and APP genes. Only circPSEN1 passed QC. We used DESeq2 to compare the counts across groups, correcting for biological and technical variables. Finally, we performed in-silico functional analyses using the Circular RNA interactome website and DIANA mirPath software. Results Our results show significant differences in gene counts of circPSEN1 in ADAD individuals, when compared to sporadic AD and controls (ADAD = 21, AD = 253, Controls = 23—ADADvsCO: log2FC = 0.794, p = 1.63 × 10–04, ADADvsAD: log2FC = 0.602, p = 8.22 × 10–04). The high gene counts are contributed by two circPSEN1 species (hsa_circ_0008521 and hsa_circ_0003848). No significant differences were observed in linear PSEN1 gene expression between cases and controls, indicating that this finding is specific to the circular forms. In addition, the high circPSEN1 levels do not seem to be specific to PSEN1 mutation carriers; the counts are also elevated in APP and PSEN2 mutation carriers. In-silico functional analyses suggest that circPSEN1 is involved in several pathways such as axon guidance (p = 3.39 × 10–07), hippo signaling pathway (p = 7.38 × 10–07), lysine degradation (p = 2.48 × 10–05) or Wnt signaling pathway (p = 5.58 × 10–04) among other KEGG pathways. Additionally, circPSEN1 counts were able to discriminate ADAD from sporadic AD and controls with an AUC above 0.70. Conclusions Our findings show the differential expression of circPSEN1 is increased in ADAD. Given the biological function previously ascribed to circular RNAs and the results of our in-silico analyses, we hypothesize that this finding might be related to neuroinflammatory events that lead or that are caused by the accumulation of amyloid-beta.

Introduction:The identification of multiple genetic risk factors for Alzheimer's disease (AD) suggests that many pathways contribute to AD onset and progression. However, the metabolomic and lipidomic profiles in carriers of distinct genetic risk factors are not fully understood. The metabolome can provide a direct image of dysregulated pathways in the brain. Methods:We interrogated metabolomic signatures in the AD brain, including carriers of pathogenic variants in APP, PSEN1, and PSEN2 (autosomal dominant AD; ADAD), APOE ɛ4, and TREM2 risk variant carriers, and sporadic AD (sAD). Results:We identified 133 unique and shared metabolites associated with ADAD, TREM2, and sAD. We identified a signature of 16 metabolites significantly altered between groups and associated with AD duration.Discussion: AD genetic variants show distinct metabolic perturbations. Investigation of these metabolites may provide greater insight into the etiology of AD and its impact on clinical presentation.

Brain metabolism perturbation can contribute to traits and diseases. We conducted the first large-scale CSF and brain genome-wide association studies, which identified 219 independent associations (59.8% novel) for 144 CSF metabolites and 36 independent associations (55.6% novel) for 34 brain metabolites. Most of the novel signals (97.7% and 70.0% in CSF and brain) were tissue specific. We also integrated MWAS-FUSION approaches with Mendelian Randomization and colocalization to identify causal metabolites for 27 brain and human wellness phenotypes and identified eight metabolites to be causal for eight traits (11 relationships). Low mannose level was causal to bipolar disorder and as dietary supplement it may provide therapeutic benefits. Low galactosylglycerol level was found causal to Parkinson’s Disease (PD). Our study expanded the knowledge of MQTL in central nervous system, provided insights into human wellness, and successfully demonstrates the utility of combined statistical approaches to inform interventions.