Statin Intake and All-Cause Mortality among Older Nursing Home Residents.

BACKGROUND: Statins are progressively accepted as being associated with reduced mortality. However, few real-world statin studies have been conducted on statin use in older people and especially the most frail, that is, the nursing home residents. OBJECTIVE: The aim of this study was to evaluate the impact of statin intake in nursing home residents on all-cause mortality. METHOD: This is a cross-sectional study of 1,094 older people residing in 6 nursing homes in Flanders (Belgium) between March 1, 2020 and May 30, 2020. We considered all residents who were taking statins for at least 5 days as statin users. All-cause mortality during the 3 months of data collection was the primary outcome. Propensity score overlap-weighted logistic regression models were applied with age, sex, functional status, diabetes, and cardiac failure/ischemia as potential confounders. RESULTS: 185 out of 1,094 residents were on statin therapy (17%). The statin intake was associated with decreased all-cause mortality: 4% absolute risk reduction; adjusted odds ratio 0.50; CI 0.31-0.81, p = 0.005. CONCLUSIONS: The statin intake was associated with decreased all-cause mortality in older people residing in nursing homes. More in-depth studies investigating the potential geroprotector effect of statins in this population are needed.

The Effects of ARBs, ACEis, and Statins on Clinical Outcomes of COVID-19 Infection Among Nursing Home Residents.

OBJECTIVES: Angiotensin-converting enzyme inhibitors (ACEi), angiotensin II receptor blockers (ARBs), and HMG-CoA reductase inhibitors ("statins") have been hypothesized to affect COVID-19 severity. However, up to now, no studies investigating this association have been conducted in the most vulnerable and affected population groups (ie, older adults residing in nursing homes). The objective of this study was to explore the association of ACEi/ARB and/or statins with clinical manifestations in COVID-19-infected older adults residing in nursing homes. DESIGN: We undertook a retrospective multicenter cohort study to analyze the association between ACEi/ARB and/or statin use with clinical outcome of COVID-19. The outcomes were (1) serious COVID-19 defined as long-stay hospital admission or death within 14 days of disease onset, and (2) asymptomatic (ie, no disease symptoms in the whole study period while still being diagnosed by polymerase chain reaction). SETTING AND PARTICIPANTS: A total of 154 COVID-19-positive subjects were identified, residing in 1 of 2 Belgian nursing homes that experienced similar COVID-19 outbreaks. MEASURES: Logistic regression models were applied with age, sex, functional status, diabetes, and hypertension as covariates. RESULTS: We found a statistically significant association between statin intake and the absence of symptoms during COVID-19 (odds ratio [OR] 2.91; confidence interval [CI] 1.27-6.71), which remained statistically significant after adjusting for covariates (OR 2.65; CI 1.13-6.68). Although the effects of statin intake on serious clinical outcome were in the same beneficial direction, these were not statistically significant (OR 0.75; CI 0.24-1.87). There was also no statistically significant association between ACEi/ARB and asymptomatic status (OR 2.72; CI 0.59-25.1) or serious clinical outcome (OR 0.48; CI 0.10-1.97). CONCLUSIONS AND IMPLICATIONS: Our data indicate that statin intake in older, frail adults could be associated with a considerable beneficial effect on COVID-19 clinical symptoms. The role of statins and renin-angiotensin system drugs needs to be further explored in larger observational studies as well as randomized clinical trials.

An Ontology to Standardize Research Output of Nutritional Epidemiology: From Paper-Based Standards to Linked Content.

BACKGROUND: The use of linked data in the Semantic Web is a promising approach to add value to nutrition research. An ontology, which defines the logical relationships between well-defined taxonomic terms, enables linking and harmonizing research output. To enable the description of domain-specific output in nutritional epidemiology, we propose the Ontology for Nutritional Epidemiology (ONE) according to authoritative guidance for nutritional epidemiology. METHODS: Firstly, a scoping review was conducted to identify existing ontology terms for reuse in ONE. Secondly, existing data standards and reporting guidelines for nutritional epidemiology were converted into an ontology. The terms used in the standards were summarized and listed separately in a taxonomic hierarchy. Thirdly, the ontologies of the nutritional epidemiologic standards, reporting guidelines, and the core concepts were gathered in ONE. Three case studies were included to illustrate potential applications: (i) annotation of existing manuscripts and data, (ii) ontology-based inference, and (iii) estimation of reporting completeness in a sample of nine manuscripts. RESULTS: Ontologies for "food and nutrition" (n = 37), "disease and specific population" (n = 100), "data description" (n = 21), "research description" (n = 35), and "supplementary (meta) data description" (n = 44) were reviewed and listed. ONE consists of 339 classes: 79 new classes to describe data and 24 new classes to describe the content of manuscripts. CONCLUSION: ONE is a resource to automate data integration, searching, and browsing, and can be used to assess reporting completeness in nutritional epidemiology.

Disbiome database: linking the microbiome to disease.

BACKGROUND: Recent research has provided fascinating indications and evidence that the host health is linked to its microbial inhabitants. Due to the development of high-throughput sequencing technologies, more and more data covering microbial composition changes in different disease types are emerging. However, this information is dispersed over a wide variety of medical and biomedical disciplines. DESCRIPTION: Disbiome is a database which collects and presents published microbiota-disease information in a standardized way. The diseases are classified using the MedDRA classification system and the micro-organisms are linked to their NCBI and SILVA taxonomy. Finally, each study included in the Disbiome database is assessed for its reporting quality using a standardized questionnaire. CONCLUSIONS: Disbiome is the first database giving a clear, concise and up-to-date overview of microbial composition differences in diseases, together with the relevant information of the studies published. The strength of this database lies within the combination of the presence of references to other databases, which enables both specific and diverse search strategies within the Disbiome database, and the human annotation which ensures a simple and structured presentation of the available data.

Perspective: Essential Study Quality Descriptors for Data from Nutritional Epidemiologic Research.

Pooled analysis of secondary data increases the power of research and enables scientific discovery in nutritional epidemiology. Information on study characteristics that determine data quality is needed to enable correct reuse and interpretation of data. This study aims to define essential quality characteristics for data from observational studies in nutrition. First, a literature review was performed to get an insight on existing instruments that assess the quality of cohort, case-control, and cross-sectional studies and dietary measurement. Second, 2 face-to-face workshops were organized to determine the study characteristics that affect data quality. Third, consensus on the data descriptors and controlled vocabulary was obtained. From 4884 papers retrieved, 26 relevant instruments, containing 164 characteristics for study design and 93 characteristics for measurements, were selected. The workshop and consensus process resulted in 10 descriptors allocated to "study design" and 22 to "measurement" domains. Data descriptors were organized as an ordinal scale of items to facilitate the identification, storage, and querying of nutrition data. Further integration of an Ontology for Nutrition Studies will facilitate interoperability of data repositories.

Quorumpeps database: chemical space, microbial origin and functionality of quorum sensing peptides.

Quorum-sensing (QS) peptides are biologically attractive molecules, with a wide diversity of structures and prone to modifications altering or presenting new functionalities. Therefore, the Quorumpeps database (http://quorumpeps.ugent.be) is developed to give a structured overview of the QS oligopeptides, describing their microbial origin (species), functionality (method, result and receptor), peptide links and chemical characteristics (3D-structure-derived physicochemical properties). The chemical diversity observed within this group of QS signalling molecules can be used to develop new synthetic bio-active compounds.

Alkamid database: Chemistry, occurrence and functionality of plant N-alkylamides.

ETHNOPHARMACOLOGICAL RELEVANCE: N-Alkylamides (NAAs) are a promising group of bioactive compounds, which are anticipated to act as important lead compounds for plant protection and biocidal products, functional food, cosmeceuticals and drugs in the next decennia. These molecules, currently found in more than 25 plant families and with a wide structural diversity, exert a variety of biological-pharmacological effects and are of high ethnopharmacological importance. However, information is scattered in literature, with different, often unstandardized, pharmacological methodologies being used. Therefore, a comprehensive NAA database (acronym: Alkamid) was constructed to collect the available structural and functional NAA data, linked to their occurrence in plants (family, tribe, species, genus). MATERIALS AND METHODS: For loading information in the database, literature data was gathered over the period 1950-2010, by using several search engines. In order to represent the collected information about NAAs, the plants in which they occur and the functionalities for which they have been examined, a relational database is constructed and implemented on a MySQL back-end. RESULTS: The database is supported by describing the NAA plant-, functional- and chemical-space. The chemical space includes a NAA classification, according to their fatty acid and amine structures. CONCLUSIONS: The Alkamid database (publicly available on the website http://alkamid.ugent.be/) is not only a central information point, but can also function as a useful tool to prioritize the NAA choice in the evaluation of their functionality, to perform data mining leading to quantitative structure-property relationships (QSPRs), functionality comparisons, clustering, plant biochemistry and taxonomic evaluations.

Brainpeps: the blood-brain barrier peptide database.

Peptides are able to cross the blood-brain barrier (BBB) through various mechanisms, opening new diagnostic and therapeutic avenues. However, their BBB transport data are scattered in the literature over different disciplines, using different methodologies reporting different influx or efflux aspects. Therefore, a comprehensive BBB peptide database (Brainpeps) was constructed to collect the BBB data available in the literature. Brainpeps currently contains BBB transport information with positive as well as negative results. The database is a useful tool to prioritize peptide choices for evaluating different BBB responses or studying quantitative structure-property (BBB behaviour) relationships of peptides. Because a multitude of methods have been used to assess the BBB behaviour of compounds, we classified these methods and their responses. Moreover, the relationships between the different BBB transport methods have been clarified and visualized.