Alzheimer’s disease (AD) is a progressive, neurodegenerative disease and the most common form of dementia in elderly people. It is an emerging public health problem that poses a huge societal burden. Linkage analysis was the first milestone in unraveling the mutations in APP, PSEN1, and PSEN2 that cause early-onset AD, followed by the discovery of apolipoprotein E-ε4 allele as the only one genetic risk factor for late-onset AD. Genome-wide association studies have revolutionized genetic research and have identified over 20 genetic loci associated with late-onset AD. Recently, next-generation sequencing technologies have enabled the identification of rare disease variants, including unmasking small mutations with intermediate risk of AD in PLD3, TREM2, UNC5C, AKAP9, and ADAM10. This review provides an overview of the genetic basis of AD and the relationship between these risk genes and the neuropathologic features of AD. An understanding of genetic mechanisms underlying AD pathogenesis and the potentially implicated pathways will lead to the development of novel treatment for this devastating disease.

Epilepsy is a common episodic neurological disorder or condition characterized by recurrent epileptic seizures, and genetics seems to play a key role in its etiology. Early linkage studies have localized multiple loci that may harbor susceptibility genes to epilepsy, and mutational analyses have detected a number of mutations involved in both ion channel and nonion channel genes in patients with idiopathic epilepsy. Genome-wide studies of epilepsy have found copy number variants at 2q24.2-q24.3, 7q11.22, 15q11.2-q13.3, and 16p13.11-p13.2, some of which disrupt multiple genes, such as NRXN1, AUTS2, NLGN1, CNTNAP2, GRIN2A, PRRT2, NIPA2, and BMP5, implicated for neurodevelopmental disorders, including intellectual disability and autism. Unfortunately, only a few common genetic variants have been associated with epilepsy. Recent exome-sequencing studies have found some genetic mutations, most of which are located in nonion channel genes such as the LGI1, PRRT2, EFHC1, PRICKLE, RBFOX1, and DEPDC5 and in probands with rare forms of familial epilepsy, and some of these genes are involved with the neurodevelopment. Since epigenetics plays a role in neuronal function from embryogenesis and early brain development to tissue-specific gene expression, epigenetic regulation may contribute to the genetic mechanism of neurodevelopment through which a gene and the environment interacting with each other affect the development of epilepsy. This review focused on the analytic tools used to identify epilepsy and then provided a summary of recent linkage and association findings, indicating the existence of novel genes on several chromosomes for further understanding of the biology of epilepsy.

Background: Cognitive impairment and depression are major mental health problems affecting older people. The current study was designed to explore the prevalence of cognitive impairment and depression in representative sample of elderly people aged ≥60 years and to examine the correlates of cognitive impairment and depression with other sociodemographic variables. Methods: A cross-sectional study based on comprehensive geriatric assessment of 538 elderly Chinese people was conducted from September 2011 to August 2012. Cognitive impairment was assessed using the Chinese version of Mini-Mental State Examination, and depressive symptoms were assessed by 30-item geriatric depression scale. Results: The prevalence of cognitive impairment was 12.6%. Multiple logistic regression analysis revealed that the following were significant independent predictors of cognitive impairment: female, having a low level of education, increasing age, and depression. The overall prevalence of depression was 24.3%, and in adjusted model, cognitive impairment was only associated with increased risk of depression. Conclusion: Cognitive impairment and depression are prevalent in elderly Chinese people. Among a number of factors identified in our study, cognitive impairment and depression were highly correlated in elderly people aged ≥60 years.

Background: Venous thromboembolism (VTE) can be fatal if not treated promptly, and individual studies have reported wide variability in rates of VTE associated with peripherally inserted central catheters (PICC). We thus conducted this meta-analysis to investigate the overall incidence and risk of developing PICC-related VTE in hospitalized patients.Methods: We searched PubMed, Embase, Scopus, and Web of Science databases from inception until January 26, 2022. In studies with a non-comparison arm, the pooled incidence of PICC-related VTE was calculated. The pooled odds ratio (OR) was calculated to assess the risk of VTE in the studies that compared PICC to the central venous catheter (CVC). The Newcastle-Ottawa Scale was used to assess methodological quality.Results: A total of 75 articles (58 without a comparison arm and 17 with), including 109292 patients, were included in the meta-analysis. The overall pooled incidence of symptomatic VTE was 3.7% (95% CI: 3.1–4.4) in non-comparative studies. In the subgroup meta-analysis, the incidence of VTE was highest in patients who were in a critical care setting (10.6%; 95% CI: 5.0–17.7). Meta-analysis of comparative studies revealed that PICC was associated with a statistically significant increase in the odds of VTE events compared with CVC (OR, 2.48; 95% CI, 1.83–3.37; P < 0.01). However, in subgroup analysis stratified by the study design, there was no significant difference in VTE events between the PICC and CVC in randomized controlled trials (OR, 2.28; 95% CI, 0.77–6.74; P = 0.13).Conclusion: Best practice standards such as PICC tip verification and VTE prophylaxis can help reduce the incidence and risk of PICC-related VTE. The risk-benefit of inserting PICC should be carefully weighed, especially in critically ill patients. Cautious interpretation of our results is important owing to substantial heterogeneity among the studies included in this study.

The global pandemic of novel coronavirus disease 2019 (COVID-19) has become an emergency of major international concern. We aim to assess the prevalence of clinical manifestations, pre-existing comorbidities, complications and treatment modalities in COVID-19 patients and compare incidence of these clinical data of severe patients with non-severe patients. An electronic search was performed in four databases to identify studies reporting clinical data of severe and non-severe COVID-19 patients. We calculated the odds ratio (OR) using fixed or random effect model. The analysis included 41 studies with 16,495 patients. The most prevalent clinical manifestations were fever 78.1%, cough 64.6%, fatigue 40.8%, and dyspnea 38.6%. Dyspnea (OR: 4.20, 95% CI: 3.09–5.72), cough (OR: 1.45, 95% CI: 1.18–1.78), and fatigue (OR: 1.40, 95% CI: 1.14–1.72) were found to be statistically significant higher in severe COVID-19 patients. We found that the most prevalent comorbidities were hypertension 32.2%, diabetes 17.1%, and cardiovascular disease 15.3%. Compared with non-severe group, proportion of hypertension (OR: 1.98, 95% CI: 1.62–2.42), diabetes (OR: 2.04, 95% CI: 1.67–2.50), cardiovascular disease (OR: 2.78, 95% CI: 2.00–3.86), and cancer (OR: 1.75, 95% CI: 1.40–2.18) were statistically significant higher in severe group. 24.7% patients presented with ARDS. The pooled effect of ARDS in severe and non-severe cases was 42.69 (OR: 42.69, 95% CI: 21.62–84.31). There was significant higher incidence of antiviral drugs, antibiotics, and glucocorticoids use in severe patients. Compared with non-severe patients, symptoms such as fever, cough, dyspnea, existing comorbidities, and complications are prevalent in severe COVID-19 patients.

Background: Elevated blood urea nitrogen (BUN) level is associated with a higher risk of mortality in various diseases; however, the association between BUN level and in-hospital mortality in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD) admitted to the intensive care unit (ICU) is not known. This study aimed to investigate the relationship between BUN level and in-hospital mortality in patients with AECOPD admitted to the ICU. Methods: In this retrospective cohort study, AECOPD patients were identified from the Medical Information Mart for Intensive Care (MIMIC-IV) database. Multivariate regression was used to elucidate the relationship between BUN level and in-hospital mortality, and propensity score matching (PSM) was used to adjust confounders. Receiver operating characteristics and Kaplan–Meier curves were used to evaluate the relationship between BUN level and in-hospital mortality. Results: Data from 1201 patients were analyzed. The all-cause in-hospital mortality was 13.7%. BUN levels were significantly higher in non-survivors compared to the survival group before (p < 0.001) and after (p = 0.005) PSM. Multivariate analysis indicated that elevated BUN levels were independently associated with increased risk of in-hospital mortality both before (p = 0.002) and after (p = 0.015) PSM. The optimal BUN cut-off value for in-hospital mortality in critical patients with AECOPD before (>23 mg/dL) and after (>22 mg/dL) PSM was comparable. Compared with the low BUN group, the hazard ratio (HR) of the high BUN group was 1.8987 (before PSM) and 1.7358 (after PSM). Conclusions: Higher BUN levels were significantly associated with an increased risk of in-hospital mortality in critically ill patients with AECOPD. As a widely available and rapidly measured biomarker, BUN may be useful in the risk stratification of critically ill AECOPD patients. The results need to be verified in prospective studies.