Shared signaling pathways in Alzheimer's and metabolic disease may point to new treatment approaches.

'A peculiar severe disease process of the cerebral cortex' are the exact words used by A. Alzheimer in 1906 to describe a patient's increasingly severe condition of memory loss, changes in personality, and sleep disturbance. A century later, this 'peculiar' disease has become widely known as Alzheimer's disease (AD), the world's most common neurodegenerative disease, affecting more than 35 million people globally. At the same time, its pathology remains unclear and no successful treatment exists. Several theories for AD etiology have emerged throughout the past century. In this review, we focus on the metabolic mechanisms that are similar between AD and metabolic diseases, based on the results from genome-wide association studies. We discuss signaling pathways involved in both types of disease and look into new optogenetic methods to study the in vivo mechanisms of AD.

"Who is watching the watchdog?": ethical perspectives of sharing health-related data for precision medicine in Singapore.

BACKGROUND: We aimed to examine the ethical concerns Singaporeans have about sharing health-data for precision medicine (PM) and identify suggestions for governance strategies. Just as Asian genomes are under-represented in PM, the views of Asian populations about the risks and benefits of data sharing are under-represented in prior attitudinal research. METHODS: We conducted seven focus groups with 62 participants in Singapore from May to July 2019. They were conducted in three languages (English, Mandarin and Malay) and analysed with qualitative content and thematic analysis. RESULTS: Four key themes emerged: nuanced understandings of data security and data sensitivity; trade-offs between data protection and research benefits; trust (and distrust) in the public and private sectors; and governance and control options. Participants were aware of the inherent risks associated with data sharing for research. Participants expressed conditional support for data sharing, including genomic sequence data and information contained within electronic medical records. This support included sharing data with researchers from universities and healthcare institutions, both in Singapore and overseas. Support was conditional on the perceived social value of the research and appropriate de-identification and data security processes. Participants suggested that a data sharing oversight body would help strengthen public trust and comfort in data research for PM in Singapore. CONCLUSION: Maintenance of public trust in data security systems and governance regimes can enhance participation in PM and data sharing for research. Contrary to themes in much prior research, participants demonstrated a sophisticated understanding of the inherent risks of data sharing, analysed trade-offs between risks and potential benefits of PM, and often adopted an international perspective.

Genome-Wide Association for HbA1c in Malay Identified Deletion on SLC4A1 that Influences HbA1c Independent of Glycemia.

CONTEXT: Glycated hemoglobin A1c (HbA1c) level is used to screen and diagnose diabetes. Genetic determinants of HbA1c can vary across populations and many of the genetic variants influencing HbA1c level were specific to populations. OBJECTIVE: To discover genetic variants associated with HbA1c level in nondiabetic Malay individuals. DESIGN AND PARTICIPANTS: We conducted a genome-wide association study (GWAS) analysis for HbA1c using 2 Malay studies, the Singapore Malay Eye Study (SiMES, N = 1721 on GWAS array) and the Living Biobank study (N = 983 on GWAS array and whole-exome sequenced). We built a Malay-specific reference panel to impute ethnic-specific variants and validate the associations with HbA1c at ethnic-specific variants. RESULTS: Meta-analysis of the 1000 Genomes imputed array data identified 4 loci at genome-wide significance (P < 5 × 10-8). Of the 4 loci, 3 (ADAM15, LINC02226, JUP) were novel for HbA1c associations. At the previously reported HbA1c locus ATXN7L3-G6PC3, association analysis using the exome data fine-mapped the HbA1c associations to a 27-bp deletion (rs769664228) at SLC4A1 that reduced HbA1c by 0.38 ±â€…0.06% (P = 3.5 × 10-10). Further imputation of this variant in SiMES confirmed the association with HbA1c at SLC4A1. We also showed that these genetic variants influence HbA1c level independent of glucose level. CONCLUSION: We identified a deletion at SLC4A1 associated with HbA1c in Malay. The nonglycemic lowering of HbA1c at rs769664228 might cause individuals carrying this variant to be underdiagnosed for diabetes or prediabetes when HbA1c is used as the only diagnostic test for diabetes.

Associations with metabolites in Chinese suggest new metabolic roles in Alzheimer's and Parkinson's diseases.

Metabolites are small intermediate products of cellular metabolism perturbed in a variety of complex disorders. Identifying genetic markers associated with metabolite concentrations could delineate disease-related metabolic pathways in humans. We tested genetic variants for associations with 136 metabolites in 1954 Chinese from Singapore. At a conservative genome-wide threshold (3.7 × 10-10), we detected 1899 variant-metabolite associations at 16 genetic loci. Three loci (ABCA7, A4GALT, GSTM2) represented novel associations with metabolites, with the strongest association observed between ABCA7 and d18:1/24:1 dihexosylceramide. Among 13 replicated loci, we identified six new variants independent of previously reported metabolite or lipid signals. We observed variant-metabolite associations at two loci (ABCA7, CHCHD2) that have been linked to neurodegenerative diseases. At SGPP1 and SPTLC3 loci, genetic variants showed preferential selectivity for sphingolipids with d16 (rather than d18) sphingosine backbone, including sphingosine-1-phosphate (S1P). Our results provide new genetic associations for metabolites and highlight the role of metabolites as intermediate modulators in disease metabolic pathways.

Big data and machine learning algorithms for health-care delivery.

Analysis of big data by machine learning offers considerable advantages for assimilation and evaluation of large amounts of complex health-care data. However, to effectively use machine learning tools in health care, several limitations must be addressed and key issues considered, such as its clinical implementation and ethics in health-care delivery. Advantages of machine learning include flexibility and scalability compared with traditional biostatistical methods, which makes it deployable for many tasks, such as risk stratification, diagnosis and classification, and survival predictions. Another advantage of machine learning algorithms is the ability to analyse diverse data types (eg, demographic data, laboratory findings, imaging data, and doctors' free-text notes) and incorporate them into predictions for disease risk, diagnosis, prognosis, and appropriate treatments. Despite these advantages, the application of machine learning in health-care delivery also presents unique challenges that require data pre-processing, model training, and refinement of the system with respect to the actual clinical problem. Also crucial are ethical considerations, which include medico-legal implications, doctors' understanding of machine learning tools, and data privacy and security. In this Review, we discuss some of the benefits and challenges of big data and machine learning in health care.

Systemic trafficking of plant virus nanoparticles in mice via the oral route.

The plant virus, cowpea mosaic virus (CPMV), is increasingly being used as a nanoparticle platform for multivalent display of peptides. A growing variety of applications have employed the CPMV display technology including vaccines, antiviral therapeutics, nanoblock chemistry, and materials science. CPMV chimeras can be inexpensively produced from experimentally infected cowpea plants and are completely stable at 37 degrees C and low pH, suggesting that they could be used as edible or mucosally-delivered vaccines or therapeutics. However, the fate of CPMV particles in vivo, or following delivery via the oral route, is unknown. To address this question, we examined CPMV in vitro and in vivo. CPMV was shown to be stable under simulated gastric conditions in vitro. The pattern of localization of CPMV particles to mouse tissues following oral or intravenous dosing was then determined. For several days following oral or intravenous inoculation, CPMV was found in a wide variety of tissues throughout the body, including the spleen, kidney, liver, lung, stomach, small intestine, lymph nodes, brain, and bone marrow. CPMV particles were detected after cardiac perfusion, suggesting that the particles entered the tissues. This pattern was confirmed using methods to specifically detect the viral capsid proteins and the internal viral RNA. The stability of CPMV virions in the gastrointestinal tract followed by their systemic dissemination supports their use as orally bioavailable nanoparticles.

Novel strategy for inhibiting viral entry by use of a cellular receptor-plant virus chimera.

The plant virus cowpea mosaic virus (CPMV) has recently been developed as a biomolecular platform to display heterologous peptide sequences. Such CPMV-peptide chimeras can be easily and inexpensively produced in large quantities from experimentally infected plants. This study utilized the CPMV chimera platform to create an antiviral against measles virus (MV) by displaying a peptide known to inhibit MV infection. This peptide sequence corresponds to a portion of the MV binding site on the human MV receptor CD46. The CPMV-CD46 chimera efficiently inhibited MV infection of HeLa cells in vitro, while wild-type CPMV did not. Furthermore, CPMV-CD46 protected mice from mortality induced by an intracranial challenge with MV. Our results indicate that the inhibitory CD46 peptide expressed on the surface of CPMV retains virus-binding activity and is capable of inhibiting viral entry both in vitro and in vivo. The CD46 peptide presented in the context of CPMV is also up to 100-fold more effective than the soluble CD46 peptide at inhibiting MV infection in vitro. To our knowledge, this study represents the first utilization of a plant virus chimera as an antiviral agent.