Automated System for Multiplexing Detection of COVID-19 and Other Respiratory Pathogens.

OBJECTIVE: Infectious diseases are global health challenge, impacted the communities worldwide particularly in the midst of COVID-19 pandemic. The need of rapid and accurate automated systems for detecting pathogens of concern has always been critical. Ideally, such systems shall detect a large panel of pathogens simultaneously regardless of well-equipped facilities and highly trained operators, thus realizing on-site diagnosis for frontline healthcare providers and in critical locations such as borders and airports. METHODS & RESULTS: Avalon Automated Multiplex System, AAMST, is developed to automate a series of biochemistry protocols to detect nucleic acid sequences from multiple pathogens in one test. Automated processes include isolation of nucleic acids from unprocessed samples, reverse transcription and two rounds of amplifications. All procedures are carried out in a microfluidic cartridge performed by a desktop analyzer. The system was validated with reference controls and showed good agreement with their laboratory counterparts. In total 63 clinical samples, 13 positives including those from COVID-19 patients and 50 negative cases were detected, consistent with clinical diagnosis using conventional laboratory methods. CONCLUSIONS: The proposed system has demonstrated promising utility. It would benefit the screening and diagnosis of COVID-19 and other infectious diseases in a simple, rapid and accurate fashion. Clinical and Translational Impact Statement- A rapid and multiplex diagnostic system proposed in this work can clinically help to control spread of COVID-19 and other infectious agents as it can provide timely diagnosis, isolation and treatment to patients. Using the system at remoted clinical sites can facilitate early clinical management and surveillance.

Non-targeted detection of food adulteration using an ensemble machine-learning model.

Recurrent incidents of economically motivated adulteration have long-lasting and devastating effects on public health, economy, and society. With the current food authentication methods being target-oriented, the lack of an effective methodology to detect unencountered adulterants can lead to the next melamine-like outbreak. In this study, an ensemble machine-learning model that can help detect unprecedented adulteration without looking for specific substances, that is, in a non-targeted approach, is proposed. Using raw milk as an example, the proposed model achieved an accuracy and F1 score of 0.9924 and 0. 0.9913, respectively, when the same type of adulterants was presented in the training data. Cross-validation with spiked contaminants not routinely tested in the food industry and blinded from the training data provided an F1 score of 0.8657. This is the first study that demonstrates the feasibility of non-targeted detection with no a priori knowledge of the presence of certain adulterants using data from standard industrial testing as input. By uncovering discriminative profiling patterns, the ensemble machine-learning model can monitor and flag suspicious samples; this technique can potentially be extended to other food commodities and thus become an important contributor to public food safety.

Apolipoprotein E Gene Revisited: Contribution of Rare Variants to Alzheimer's Disease Susceptibility in Southern Chinese.

BACKGROUND: APOE ε4 is the best-known risk factor for late-onset alzheimer's disease (AD). Population studies have demonstrated a relatively low prevalence of APOE ε4 among Chinese population, implying additional risk factors that are Chinese-specific may exist. Apart from - alleles, genetic variation profile along the full-length APOE has rarely been investigated. OBJECTIVE: In this study, we filled this gap by comprehensively determining all genetic variations in APOE and investigated their potential associations with late-onset AD and mild cognitive impairment (MCI) in southern Chinese. METHODS: Two hundred and fifty-seven southern Chinese participants were recruited, of whom 69 were AD patients, 83 had MCI, and 105 were normal controls. Full-length APOE from promoter to 3'UTR regions were sequenced. Genetic variants were identified and compared among the three groups. RESULTS: While APOE ε4 was more significantly found in AD patients, the prevalence of APOE ε4 in southern Chinese AD patients was the lowest when compared to other areas of China and nearby regions, as well as other countries worldwide. We further identified 13 rare non-singleton variants in APOE. Significantly more AD patients carried any of the rare non-singleton variants than MCI and normal subjects. Such difference was observed in the non-carriers of ε4-allele only. Among the identified rare variants, the potential functional impact was predicted for rs532314089, rs553874843, rs533904656 and rs370594287. CONCLUSION: Our study suggests an ethnic difference in genetic risk composition of AD in southern Chinese. Rare variants on APOE are a potential candidate for AD risk stratification biomarker in addition to APOE-ε4.

Population-Wide Genetic Risk Prediction of Complex Diseases: A Pilot Feasibility Study in Macau Population for Precision Public Healthcare Planning.

The genetic bases of many common diseases have been identified through genome-wide association studies in the past decade. However, the application of this approach on public healthcare planning has not been well established. Using Macau with population of around 650,000 as a basis, we conducted a pilot study to evaluate the feasibility of population genomic research and its potential on public health decisions. By performing genome-wide SNP genotyping of over a thousand Macau individuals, we evaluated the population genetic risk profiles of 47 non-communicable diseases and traits, as well as two traits associated with influenza infection. We found that for most of the diseases, the genetic risks of Macau population were different from those of Caucasian, but with similar profile with mainland Chinese. We also identified a panel of diseases that Macau population may have a high or elevated genetic risks. This pilot study showed that (1) population genomic study is feasible in Asian regions like Macau; (2) Macau may have different profile of population-based genetic risks than Caucasians, (3) the different prevalence of genetic risk profile indicates the importance of Asian-specific studies for Asian populations; and (4) the results generated may have an impact for going forward healthcare planning.