The relationship between Apolipoprotein E (ApoE) genotype and the risk of Alzheimer's disease (AD) is relatively well established in Caucasians, but less established in other ethnicities. To examine the association between ApoE polymorphism and the onset of AD in Chinese population, we searched the commonly used electronic databases between January 2000 and November 2013 for relevant studies. Total 20 studies, including 1576 cases and 1741 controls, were retrieved. The results showed statistically significant positive association between risk factor ε4 allele carriers and AD in Chinese population (OR = 3.93, 95% CI = 3.37-4.58, P < 0.00001). Genotype ApoE ε4/ε4 and ε4/ε3 have statistically significant association with AD as well (ε4/ε4: OR = 11.76, 95% CI = 6.38-21.47, P < 0.00001; ε4/ε3: OR = 3.08, 95% CI = 2.57-3.69, P < 0.00001). Furthermore, the frequency of the ApoE ε3 is lower in AD than that in the health controls, and the difference of ε3 allele is also statistically significant (OR = 0.42, 95% CI = 0.37-0.47, P < 0.00001). No significant heterogeneity was observed among all studies. This meta-analysis suggests that the subject with at least one ApoE ε4 allele has higher risk suffering from AD than controls in Chinese population. The results also provide a support for the protection effect of ApoE ε3 allele in developing AD.

Porcine epidemic diarrhea virus (PEDV), a leading cause of piglet diarrhea outbreaks, poses a significant danger to the swine industry. The aim of this study was to investigate the epidemic characteristics ofPEDVthat was circulating in Guangdong province, one of China’s major pig producing provinces. Clinical samples were collected from eight pig farms in Guangdong province between 2018 and 2019 and tested for the major porcine enteric pathogens, includingPEDV, transmissible gastroenteritis virus (TGEV), Swine enteric coronavirus (SeCoV), Swine acute diarrhea syndrome coronavirus (SADS-CoV), porcine deltacoronavirus (PDCoV), and porcine rotavirus (RV). As a result, onlyPEDVandRVwere detected at a rate of 47.0% (16/34) and 18.6% (8/34), respectively. Coinfectoin withPEDVand RV occurred at a rate ofPEDV12.5% (2/16). Subsequently, the full-length S gene sequences of 13PEDVstrains were obtained, and phylogenetic analysis suggested the presence of GII-c group PEDV strains in this region (non-S-INDEL). Two novel common amino acid insertions (⁵⁵T/IG⁵⁶and 551L) and one novel glycosylation site (1199^G+) were detected when the CV777 and ZJ08 vaccine strains were compared. Furthermore, intragroup recombination events in theSgene regions 51–548 and 2478–4208 were observed in thePEDVstrains studied. In summary, the observations provide current information on the incidence of viral agents causing swine diarrhea in southern China and detailed the genetic characteristics and evolutionary history of the dominantPEDVfield strains. Our findings will aid in the development of an updated vaccine for the prevention and control ofPEDVvariant strains.

An outbreak of respiratory disease caused by the equine-origin influenza A(H3N8) virus was first detected in dogs in 2004 and since then has been enzootic among dogs. Currently, the molecular mechanisms underlying host adaption of this virus from horses to dogs is unknown. Here, we have applied quantitative binding, growth kinetics, and immunofluorescence analyses to elucidate these mechanisms. Our findings suggest that a substitution of W222L in the hemagglutinin of the equine-origin A(H3N8) virus facilitated its host adaption to dogs. This mutation increased binding avidity of the virus specifically to receptor glycans with N-glycolylneuraminic acid (Neu5Gc) and sialyl Lewis X (SLe^X) motifs. We have demonstrated these motifs are abundantly located in the submucosal glands of dog trachea. Our findings also suggest that in addition to the type of glycosidic linkage (e.g., α2,3-linkage or α2,6-linkage), the type of sialic acid (Neu5Gc or 5-N-acetyl neuraminic acid) and the glycan substructure (e.g., SLe^X) also play an important role in host tropism of influenza A viruses. IMPORTANCE Influenza A viruses (IAVs) cause a significant burden on human and animal health, and mechanisms for interspecies transmission of IAVs are far from being understood. Findings from this study suggest that an equine-origin A(H3N8) IAV with mutation W222L at its hemagglutinin increased binding to canine-specific receptors with sialyl Lewis X and Neu5Gc motifs and, thereby, may have facilitated viral adaption from horses to dogs. These findings suggest that in addition to the glycosidic linkage (e.g., α2,3-linked and α2,6-linked), the substructure in the receptor saccharides (e.g., sialyl Lewis X and Neu5Gc) could present an interspecies transmission barrier for IAVs and drive viral mutations to overcome such barriers.

Motivation: Influenza virus antigenic variants continue to emerge and cause disease outbreaks. Time-consuming, costly and middle-throughput serologic methods using virus isolates are routinely used to identify influenza antigenic variants for vaccine strain selection. However, the resulting data are notoriously noisy and difficult to interpret and integrate because of variations in reagents, supplies and protocol implementation. A novel method without such limitations is needed for antigenic variant identification. Results: We developed a Graph-Guided Multi-Task Sparse Learning (GG-MTSL) model that uses multi-sourced serologic data to learn antigenicity-associated mutations and infer antigenic variants. By applying GG-MTSL to influenza H3N2 hemagglutinin sequences, we showed the method enables rapid characterization of antigenic profiles and identification of antigenic variants in real time and on a large scale. Furthermore, sequences can be generated directly by using clinical samples, thus minimizing biases due to culture-adapted mutation during virus isolation. Availability and implementation: MATLAB source codes developed for GG-MTSL are available through http://sysbio.cvm.msstate.edu/files/GG-MTSL/. Supplementary information: Supplementary data are available at Bioinformatics online.