Transcriptional Patterns in Stages of Alzheimer's Disease are Cell Type Specific and Partially Converge with the Effects of Alcohol Use Disorder in Humans.

Advances in single cell technologies have led to the discovery and characterization of new brain cell-types, that in turn lead to a better understanding of the pathogenesis of Alzheimer's disease (AD). Here, we present a detailed analysis of single nucleus (sn)RNA-seq data for three stages of AD from middle temporal gyrus (MTG) and compare it with snRNA-seq data from the prefrontal cortices from individuals with alcohol use disorder (AUD). We observed a significant decrease in both inhibitory and excitatory neurons, in general agreement with previous reports. We observed several cell-type specific gene expressions and pathways dysregulations that delineate AD stages. Endothelial and VLMCs (vascular leptomeningeal cells) showed the greatest degree of gene expression changes. Cell-type specific evidence of neurodegeneration was seen in multiple neuronal cell-types particularly in SST (somatostatin) and L5 ET (layer-5 extra-telencephalic) neurons, among others. Evidence of inflammatory responses were seen in non-neuronal cells, particularly in intermediate and advanced AD. We observed common perturbations in AD and AUD, particularly in pathways, like transcription, translation, apoptosis, autophagy, calcium signaling, neuroinflammation, and phosphorylation, that imply shared transcriptional pathogenic mechanisms and support a role for excessive alcohol intake in AD progression. Major AUD gene markers form and perturb a network of genes significantly associated with intermediate and advanced AD. Master regulator analysis from AUD gene markers revealed significant correlation with advanced AD of transcription factors that have implications in intellectual disability, neuroinflammation, and other neurodegenerative conditions, further suggesting a shared nexus of transcriptional changes between AD and AUD.Significance Statement This study holds significant implications for understanding the intricate molecular landscape of Alzheimer's disease (AD) and its intersection with alcohol use disorder (AUD). By profiling transcriptional changes in the neocortex associated with AD progression and comparing them with those in AUD, we shed light on shared gene expression and pathway dysregulations between the two conditions. Our findings corroborate prior research on neuronal depletion and highlight novel insights into cell-type-specific gene expression patterns in AD stages. Moreover, the identification of common genetic signatures suggests a potential exacerbating effect of AUD on AD progression. This comprehensive analysis not only deepens our understanding of AD pathology but also underscores the importance of considering AUD as a potential risk factor for accelerating AD onset or severity.

Risk management in a clinical pathology laboratory: Application of brainstorming and probability analysis for risk reduction.

INTRODUCTION: Risk management includes identifying various risks, assessing the probability of occurrence, and evaluating the severity of their consequences. As clinical laboratories are integrally involved in patient care, risks in the laboratories could present grave consequences in some instances. This study aimed to utilize simple techniques for risk management in a clinical laboratory. MATERIALS AND METHODS: All potential risks in the pathology laboratory of a tertiary-level hospital were identified and classified into natural calamity, environmental, manpower-related, pre-analytical, analytical, post-analytical, and laboratory hazard-related risks through a brainstorming session. The probability of occurrence of each risk was estimated from departmental and hospital records. The possible impact of risk (score 1-10) was categorized into catastrophic, critical, serious, minor negligible, and insignificant. The unweighted risk score was calculated by multiplying the probability of occurrence and impact score. RESULTS: Inadequate sample-to-anticoagulant ratio had the highest probability of occurrence (22.85%), followed by quantity insufficient for analysis (7.30%) and laboratory information system (LIS) breakdown (6.58%). The highest unweighted risk score in our study was inadequate sample-to-anticoagulant ratio (score 91.40), followed by improperly labeled samples (score 35.61), manpower competency issues (score 32.88), sample insufficient for analysis (score 29.20), and LIS breakdown (score 26.30). CONCLUSION: We found that among all the categories, risks involving the pre-analytical phase had the highest risk scores. The other important risks included manpower competency issues requiring continued on-the-job training of staff as a risk reduction strategy. Brainstorming and probability analysis could be easily used for risk management in a clinical laboratory.

Quality control of large genome datasets.

The 1000 Genomes Project (TGP) is a foundational resource that serves the biomedical community as a standard reference cohort for human genetic variation. There are now seven public versions of these genomes. The TGP Consortium produced the first by mapping its final data release against human reference sequence GRCh37, then "lifted over" these genomes to the improved reference sequence (GRCh38) when it was released, and remapped the original data to GRCh38 with two similar pipelines. As best-practice quality validation, the pipelines that generated these versions were benchmarked against the Genome In A Bottle Consortium's "platinum quality" genome (NA12878). The New York Genome Center recently released the results of independently resequencing the cohort at greater depth (30×), a phased version informed by the inclusion of related individuals, and independently remapped the original variant calls to GRCh38. We performed a cross-comparison evaluation of all seven versions using genome fingerprinting, which supports ultrafast genome comparison even across reference versions. We noted multiple issues, including discrepancies in cohort membership, disagreement on the overall level of variation, evidence of substandard pipeline performance on specific genomes and in specific regions of the genome, cryptic relationships between individuals, inconsistent phasing, and annotation distortions caused by the history of the reference genome itself. We therefore recommend global quality assessment by rapid genome comparisons, alongside benchmarking as part of best-practice quality assessment of large genome datasets. Our observations also help inform the decision of which version to use, to support analyses by individual researchers.

Biolink Model: A universal schema for knowledge graphs in clinical, biomedical, and translational science.

Within clinical, biomedical, and translational science, an increasing number of projects are adopting graphs for knowledge representation. Graph-based data models elucidate the interconnectedness among core biomedical concepts, enable data structures to be easily updated, and support intuitive queries, visualizations, and inference algorithms. However, knowledge discovery across these "knowledge graphs" (KGs) has remained difficult. Data set heterogeneity and complexity; the proliferation of ad hoc data formats; poor compliance with guidelines on findability, accessibility, interoperability, and reusability; and, in particular, the lack of a universally accepted, open-access model for standardization across biomedical KGs has left the task of reconciling data sources to downstream consumers. Biolink Model is an open-source data model that can be used to formalize the relationships between data structures in translational science. It incorporates object-oriented classification and graph-oriented features. The core of the model is a set of hierarchical, interconnected classes (or categories) and relationships between them (or predicates) representing biomedical entities such as gene, disease, chemical, anatomic structure, and phenotype. The model provides class and edge attributes and associations that guide how entities should relate to one another. Here, we highlight the need for a standardized data model for KGs, describe Biolink Model, and compare it with other models. We demonstrate the utility of Biolink Model in various initiatives, including the Biomedical Data Translator Consortium and the Monarch Initiative, and show how it has supported easier integration and interoperability of biomedical KGs, bringing together knowledge from multiple sources and helping to realize the goals of translational science.

Assessment of the availability of technology for trauma care in Nepal.

BACKGROUND: We sought to assess the availability of technology-related equipment for trauma care in Nepal and to identify factors leading to optimal availability as well as deficiencies. We also sought to identify potential solutions addressing the deficits in terms of health systems management and product development. METHODS: Thirty-two items for large hospitals and sixteen items for small hospitals related to the technological aspect of trauma care were selected from the World Health Organization's Guidelines for Essential Trauma Care for the current study. Fifty-six small and 29 large hospitals were assessed for availability of these items in the study area. Site visits included direct inspection and interviews with administrative, clinical, and bioengineering staff. RESULTS: Deficiencies of many specific items were noted, including many that were inexpensive and which could have been easily supplied. Shortage of electricity was identified as a major infrastructural deficiency present in all parts of the country. Deficiencies of pulse oximetry and ventilators were observed in most hospitals, attributed in most part to frequent breakdowns and long downtimes because of lack of vendor-based service contracts or in-house maintenance staff. Sub-optimal oxygen supply was identified as a major and frequent deficiency contributing to disruption of services. All equipment was imported except for a small percent of suction machines and haemoglobinometers. CONCLUSIONS: The study identified a range of items which were deficient and whose availability could be improved cost-effectively and sustainably by better planning and organisation. The electricity deficit has been dealt with successfully in a few hospitals via direct feeder lines and installation of solar panels; wider implementation of these methods would help solve a large portion of the technological deficiencies. From a health systems management view-point, strengthening procurement and stocking of low cost items especially in remote parts of the country is needed. From a product development view-point, there is a need for robust pulse-oximeters and ventilators that are lower cost and which have longer durability and less need for repairs. Increasing capabilities for local manufacture is another potential method to increase availability of a range of equipment and spare parts.