Search

Background: Genomic technologies and particularly bioinformatics have significantly changed biomedical research along the last decade and are being recognized as potential methods for application also in medical practice and public health. There exists a growing need for different collectives of the healthcare sector to receive training in the methods, tools and databases related with these new areas.Objectives: This paper describes the teaching experience of our department during the last ten years and analyzes past activities designed for teaching bioinformatics to different groups of health professionals. We aim to illustrate the main lessons learned and offer useful clues to other groups interested in setting up training initiatives in bioinformatics for health professionals.Methods: The group selected several methodologies for the training activities ("face-to-face", online/e-learning) on the basis of three criteria: 1) the target collective, 2) the contents of the course, and 3) its length. Courses were evaluated and the results are hereby presented and discussed.Results: National and international training courses on bioinformatics, biomedical informatics and genomics were developed according to specific requirements defined by the profile of each of the targeted health professional group. These activities provided the students with the necessary skills for better understanding the use of bioinformatics tools and databases and the appropriate way of applying them into specific health domains.Conclusions: The increasing demand of training courses in new technologies related to genomics and bioinformatics by health professionals provides a good opportunity for the development of tailored courses based on their specific needs, expectations and demands geared to bridge the gap between research and practice and facilitating their everyday work. [ABSTRACT FROM AUTHOR]

BackgroundPatient-reported outcomes (PROs) from social media use in chronic disease management continue to emerge. While many published articles suggest the potential for social media is positive, there is a lack of robust examination into mediating mechanisms that might help explain social media’s therapeutic value. This study presents findings from a global online survey of people with chronic pain (PWCP) to better understand how they use social media as part of self-management. ObjectiveOur aim is to improve understanding of the various health outcomes reported by PWCP by paying close attention to therapeutic affordances of social media. We wish to examine if demographics of participants underpin health outcomes and whether the concept of therapeutic affordances explains links between social media use and PROs. The goal is for this to help tailor future recommendations for use of social media to meet individuals’ health needs and improve clinical practice of social media use. MethodsA total of 231 PWCP took part in a global online survey investigating PROs from social media use. Recruited through various chronic disease entities and social networks, participants provided information on demographics, health/pain status, social media use, therapeutic affordances, and PROs from use. Quantitative analysis was performed on the data using descriptive statistics, cross-tabulation, and cluster analysis. ResultsThe total dataset represented 218 completed surveys. The majority of participants were university educated (67.0%, 146/218) and female (83.9%, 183/218). More than half (58.7%, 128/218) were married/partnered and not working for pay (75.9%, 88/116 of these due to ill health). Fibromyalgia (46.6%, 55/118) and arthritis (27.1%, 32/118) were the most commonly reported conditions causing pain. Participants showed a clear affinity for social network site use (90.0%, 189/210), followed by discussion forums and blogs. PROs were consistent, suggesting that social media positively impact psychological, social, and cognitive health. Analysis also highlighted two strong correlations linking platform used and health outcomes (particularly psychological, social, and cognitive) to (1) the narrative affordance of social media and (2) frequency of use of the platforms. ConclusionsResults did not uncover definitive demographics or characteristics of PWCP for which health outcomes are impacted. However, findings corroborate literature within this domain suggesting that there is a typical profile of people who use social media for health and that social media are more suited to particular health outcomes. Exploration of the relationship between social media’s therapeutic affordances and health outcomes, in particular the narration affordance, warrants further attention by patients and clinicians.

Objectives: Genes implicated in monogenic human cardiac hypertrophy (CH) might also be involved in the more common polygenic forms. The Hypertrophic Heart Rat (HHR) is a unique normotensive model of spontaneous polygenic ventricular hypertrophy leading to cardiac failure and premature death. Our aim was to survey mRNA expression and genetic variants in genes previously associated with monogenic forms of dilated and hypertrophic cardiomyopathy in humans utilising the HHR.Design and methods: We used Affymetrix GeneChip® Rat Gene 1.0 ST arrays to measure whole-genome mRNA in left ventricles of HHR and its normal control, the Normal Heart Rat (NHR) (n=8 per group). We also performed whole-genome DNA sequencing of both strains using the HiSeq 2000 platform. We aligned and compared sequences to the Rat Genome Database v3.4 and identified four types of variants: SNPs, insertions and deletions (InDels), copy number variations (CNVs) and structural variants (SVs).Results: We found 15 (Cryab, Dsg2, Lama4, Mybpc3, Myh6, Myh7,Myl2, Nexn, Psen2, Rbm20, Tnnc1, Tnni3, Tnnt2, Tpm1, Ttn) of the initial known 40 candidate genes significantly differentially expressed in the HHR (FDR<0.05). Their fold change was small (∼1.3) consistent with a polygenic contribution. Overall, we found 182 variants unique to the HHR in our gene subset. Most variants were SNPs (n=101), followed by InDels (n=67), CNVs (n=12) and SVs (n=2). No major mutations typical of human monogenic cardiomyopathies were found. The majority of SNPs are located in non-coding regions (n=98) except for two variants in the coding region for the gene for troponin T type 2 (Tnnt2) and one in its 3' untranslated region. Interestingly, both mutations in the coding region are synonymous and do not cause a change in the amino acid or protein sequence. Although the variants found in gene for Tnnt2 are synonymous, silent mutations may alter gene expression levels by transfer RNA availability and influence phenotypically variability.Conclusions: Our study is the first to show that genes involved in monogenic human forms of hypertrophy may also contribute through changed expression and subtle variants in DNA sequence to the common polygenic form of left ventricular hypertrophy. [ABSTRACT FROM AUTHOR]

Objective: Cardiac hypertrophy (CH) is the main risk factor for heart disease after age. Multiple genetic factors are known to be involved but still poorly understood. We have previously described a quantitative trait locus (QTL) cardiac mass 22 (Cm22) on chromosome 2 which influences heart size independently of blood pressure. Our aim was to determine which genes in QTL Cm22 contribute to CH using a polygenic genetic model.Design and method: We used a genomic and transcriptomic approach to identify genes in Cm22 contributing to CH. Firstly, we used the Illumina HiSeq 2000 platform to sequence the whole-genome of the Hypertrophic Heart Rat (HHR), a normotensive genetic model of CH, and its control, the Normal Heart Rat (NHR). Both genomes were aligned and compared to Rat Genome Database v3.4 and four types of variants were analysed: single nucleotide polymorphisms (SNPs), insertions and deletions (InDels), copy number variations (CNVs) and structural variants (SVs). Secondly, we investigated gene expression of all Cm22 genes in left ventricles of HHR and NHR (n=8 per group) using Affymetrix GeneChip® Rat Gene 1.0 ST arrays. We then combined these data to identify unique variants in genes differentially expressed in QTL Cm22.Results: Overall, approximately 5.7 and 5 million variants are present in HHR and NHR, respectively, and the majority of the variants (80%) were SNPs. In QTL Cm22, we found approximately 10 thousand variants in each strain. The array data showed that gene for tripartite motif-containing 55 (Trim55) was significantly downregulated in HHR (FC=-2.08; FDR=0.049). We validated these findings by real-time polymerase chain reaction (qPCR), which showed that Trim55 mRNA is down-regulated from neonatal to late adulthood in the CH model.Analysis of the gene region of Trim55 identified 12 and 24 variants in HHR and NHR, respectively. One missense mutation in the HHR was located in its ninth exon. In silico studies demonstrated that this mutation may cause a change in the protein structure which may affect function.Conclusion: The Trim55 gene in QTL CM22 is a novel candidate gene for polygenic hypertrophy development independent of blood pressure. [ABSTRACT FROM PUBLISHER]

The World Health Organization's Operational Framework for Climate Resilient and Low Carbon Health Systems outlines 10 broad components for the development and maintenance of health systems that respond effectively to climate-related challenges. This work analyses the WHO framework from a participatory health informatics perspective and identifies specific initiatives involving non-professionals that align with the framework. Citizen and patient participation in the development of climate-resilient health systems is not only possible but also necessary to maximize climate resiliency at the community and global levels.

Interferons (IFN) constitute a primary line of protection against mucosal infection, with IFN research spanning over 60 years and encompassing a vast ever-expanding amount of literature. Most of what is currently understood has been derived from extensive research defining the roles of "classical" type I IFNs, IFNα and IFNβ. However, little is known regarding responses elicited by less well-characterized IFN subtypes such as IFNε. In this paper, we combined a deductive text mining analysis of IFNε literature characterizing literature-derived knowledge with a comparative analysis of other type I and type III IFNs. Utilizing these approaches, three clusters of terms were extracted from the literature covering different aspects of IFNε research and a set of 47 genes uniquely cited in the context of IFNε. The use of these "in silico" approaches support the expansion of current understanding and the creation of new knowledge surrounding IFNε.

The application of digital interventions in healthcare beyond research has been translated in the development of software as a medical device. Along with corresponding regulations for medical devices, there is a need for assessing adverse events to conduct post-market surveillance and to appropriately label digital health interventions to ensure proper use and patient safety. To date unexpected consequences of digital health interventions are neglected or ignored, or at least remain undescribed in literature. This paper is intended to raise awareness across the research community about these upcoming challenges. We recommend that - together with developing a new research field of digitalovigilance - a systematic assessment and monitoring of adverse events and unexpected interactions be included in clinical trials, along with the reporting of such events and the conduct of meta-analyses on critical aspects.

Gram-negative bacteria use type VI secretion systems (T6SSs) to antagonize neighbouring cells. Although primarily involved in bacterial competition, the T6SS is also implicated in pathogenesis, biofilm formation and ion scavenging. Enterobacter species belong to the ESKAPE pathogens, and while their antibiotic resistance has been well studied, less is known about their pathogenesis. Here, we investigated the distribution and diversity of T6SS components in isolates of two clinically relevant Enterobacter species, E. cloacae and E. bugandensis . T6SS clusters are grouped into four types (T6SS i -T6SS iv ), of which type i can be further divided into six subtypes (i1, i2, i3, i4a, i4b, i5). Analysis of a curated dataset of 31 strains demonstrated that most of them encode T6SS clusters belonging to the T6SS i type. All T6SS-positive strains possessed a conserved i3 cluster, and many harboured one or two additional i2 clusters. These clusters were less conserved, and some strains displayed evidence of deletion. We focused on a pathogenic E. bugandensis clinical isolate for comprehensive in silico effector prediction, with comparative analyses across the 31 isolates. Several new effector candidates were identified, including an evolved VgrG with a metallopeptidase domain and a Tse6-like protein. Additional effectors included an anti-eukaryotic catalase (KatN), M23 peptidase, PAAR and VgrG proteins. Our findings highlight the diversity of Enterobacter T6SSs and reveal new putative effectors that may be important for the interaction of these species with neighbouring cells and their environment.

Background: Health care has evolved to support the involvement of individuals in decision making by, for example, using mobile apps and wearables that may help empower people to actively participate in their treatment and health monitoring. While the term "participatory health informatics" (PHI) has emerged in literature to describe these activities, along with the use of social media for health purposes, the scope of the research field of PHI is not yet well defined., Objective: This article proposes a preliminary definition of PHI and defines the scope of the field., Methods: We used an adapted Delphi study design to gain consensus from participants on a definition developed from a previous review of literature. From the literature we derived a set of attributes describing PHI as comprising 18 characteristics, 14 aims, and 4 relations. We invited researchers, health professionals, and health informaticians to score these characteristics and aims of PHI and their relations to other fields over three survey rounds. In the first round participants were able to offer additional attributes for voting., Results: The first round had 44 participants, with 28 participants participating in all three rounds. These 28 participants were gender-balanced and comprised participants from industry, academia, and health sectors from all continents. Consensus was reached on 16 characteristics, 9 aims, and 6 related fields., Discussion: The consensus reached on attributes of PHI describe PHI as a multidisciplinary field that uses information technology and delivers tools with a focus on individual-centered care. It studies various effects of the use of such tools and technology. Its aims address the individuals in the role of patients, but also the health of a society as a whole. There are relationships to the fields of health informatics, digital health, medical informatics, and consumer health informatics., Conclusion: We have proposed a preliminary definition, aims, and relationships of PHI based on literature and expert consensus. These can begin to be used to support development of research priorities and outcomes measurements., Competing Interests: None declared., (The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).)

Background: Ventilator-associated pneumonia (VAP) represents a transitory status of immunoparalysis, and we hypothesized that ventilator-associated tracheobronchitis (VAT) could share also some degree of immune response to a respiratory infection., Research Design and Methods: A prospective observational study in five medical ICUs to evaluate immunological alterations of patients with VA-LRTI. Immunological gene expression profiles in the blood using whole transcriptome microarrays in the first 24 hours following diagnosis. The area under the receiver operating characteristic curve (AUROC) was used to assess the accuracy of mRNA levels to differentiate VA-LRTI and lack of infection. A principal component analysis (PCA) was employed for analyzing the impact of each genetic expression footprint variable in explaining the variance of the cohort., Results: There was overlapping between the three classes of patients encompassing gene expression levels of 8 genes (i.e. HLA, IL2RA, CD40LG, ICOS, CCR7, CD1C, CD3E). HLA-DRA was equally low among VAT and VAP patients characterizing immune depression, and significantly lower than the control group., Conclusions: Our findings suggest that VAP and VAT are not so different regarding gene expression levels suggesting a degree of immunosuppression. Our results indicate a state of immunoparalysis in respiratory infections in critically ill patients.

Human phenotypes define the healthy or diseased status of an individual and they arise from the complex interactions between environmental and genetic factors. The whole set of human exposures constitute the human exposome. These exposures have multiple sources including physical and socioeconomic factors. In this manuscript we have used text mining techniques to retrieve 1295 and 1903 Human Phenotype Ontology terms associated with these exposome factors and we have subsequently mapped 83% and 90% of the HPO terms respectively) into SNOMED as a clinically actionable code. We have developed a proof-of-concept approach to facilitate the integration of exposomic and clinical data.

During the last century technological advances have increased the number of anthropogenic electromagnetic fields (EMFs) and therefore human exposures. In this work we have mined from more than 30,000 EMF-related publications the genes, diseases and molecular mechanisms associated with the exposure to six different subsets of EMFs. Results show 3653 unique disease MeSH terms and 9966 unique genes identified of which only 4340 genes are human. Overall, our approach highlights the molecular aspects of the increasing exposure to EMFs.

Klebsiella pneumoniae is a leading cause of nosocomial and community acquired infections, making K. pneumoniae the pathogen that is associated with the second largest number of deaths attributed to any antibiotic resistant infection. K. pneumoniae colonizes the nasopharynx and the gastrointestinal tract in an asymptomatic manner without dissemination to other tissues. Importantly, gastrointestinal colonization is a requisite for infection. Our understanding of K. pneumoniae colonization is still based on interrogating mouse models in which animals are pretreated with antibiotics to disturb the colonization resistance imposed by the gut microbiome. In these models, infections disseminate to other tissues. Here, we report a murine model to allow for the study of the gastrointestinal colonization of K. pneumoniae without tissue dissemination. Hypervirulent and antibiotic resistant strains stably colonize the gastrointestinal tract of in an inbred mouse population without antibiotic treatment. The small intestine is the primary site of colonization and is followed by a transition to the colon over time, without dissemination to other tissues. Our model recapitulates the disease dynamics of the metastatic K. pneumoniae strains that are able to disseminate from the gastrointestinal tract to other sterile sites. Colonization is associated with mild to moderate histopathology, no significant inflammation, and no effect on the richness of the microbiome. Our model sums up the clinical scenario in which antibiotic treatment disturbs the colonization of K. pneumoniae and results in dissemination to other tissues. Finally, we establish that the capsule polysaccharide is necessary for the colonization of the large intestine, whereas the type VI secretion system contributes to colonization across the gastrointestinal tract. IMPORTANCE Klebsiella pneumoniae is one of the pathogens that is sweeping the world in the antibiotic resistance pandemic. Klebsiella colonizes the nasopharynx and the gut of healthy subjects in an asymptomatic manner, making gut colonization a requisite for infection. This makes it essential to understand the gastrointestinal carriage in preventing Klebsiella infections. Current research models rely on the perturbation of the gut microbiome by antibiotics, resulting in an invasive infection. Here, we report a new model of K. pneumoniae gut colonization that recapitulates key features of the asymptomatic human gastrointestinal tract colonization. In our model, there is no need to disturb the microbiota to achieve stable colonization, and there is no dissemination to other tissues. Our model sums up the clinical scenario in which antibiotic treatment triggers invasive infection. We envision that our model will be an excellent platform upon which to investigate factors enhancing colonization and invasive infections and to test therapeutics to eliminate Klebsiella asymptomatic colonization.

We found that histamine (10-9 M) did not have any effect on the in vitro capture of Escherichia coli by neutrophils but accelerated its intracellular killing. In contrast, histamine (10-6 M) delayed the capture of Escherichia coli by neutrophils and reduced the amounts of pHrodo zymosan particles inside acidic mature phagosomes. Histamine acted through the H4R and the H2R, which are coupled to the Src family tyrosine kinases or the cAMP/protein kinase A pathway, respectively. The protein kinase A inhibitor H-89 abrogated the delay in bacterial capture induced by histamine (10-6 M) and the Src family tyrosine kinase inhibitor PP2 blocked histamine (10-9 M) induced acceleration of bacterial intracellular killing and tyrosine phosphorylation of proteins. To investigate the role of histamine in pathogenicity, we designed an Acinetobacter baumannii strain deficient in histamine production (hdc::TOPO). Galleria mellonella larvae inoculated with the wild-type Acinetobacter baumannii ATCC 17978 strain (1.1 × 105 CFU) died rapidly (100% death within 40 h) but not when inoculated with the Acinetobacter baumannii hdc::TOPO mutant (10% mortality). The concentration of histamine rose in the larval haemolymph upon inoculation of the wild type but not the Acinetobacter baumannii hdc::TOPO mutant, such concentration of histamine blocks the ability of hemocytes from Galleria mellonella to capture Candida albicans in vitro. Thus, bacteria-producing histamine, by maintaining high levels of histamine, may impair neutrophil phagocytosis by hijacking the H2R., (© 2022 The Author(s). Published by S. Karger AG, Basel.)

Since the emergence of SARS-CoV-2 in November 2019, there has been an exponential production of literature due to worldwide efforts to understand the interactions between the virus and the human body. Using an "in-house" developed script we retrieved gene annotations and identified phenotype enrichments. Human Phenotype Ontology terms were retrieved from the literature using the Onassis R package. This produced both disease-gene and disease-phenotype data as well as data for gene-phenotype interactions. Overall, we retrieved 181 human phenotypes that were identified by both approaches. Further in-depth analysis of these relationships could provide further insights in the molecular mechanisms related with the observed phenotypes, answers and hypotheses for key concepts within COVID-19 research.

Text mining of the biomedical literature enables vast quantities of information to be extracted and summarised. Here we describe an updated and improved version of previous methodology for the analysis of gene and protein biomarkers that enables the use of the newer Pubtator Central annotations, based in full text, improving the performance using a local SQLite database, that reduces the running time and resources required to perform the analyses facilitating its use in any computer, and expands its capabilities to enable the retrieval and analysis of chemical and metabolic biomarkers.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of the coronavirus disease-19 (COVID-19) pandemic, was identified in late 2019 and caused >5 million deaths by February 2022. To date, targeted antiviral interventions against COVID-19 are limited. The spectrum of SARS-CoV-2 infection ranges from asymptomatic to fatal disease. However, the reasons for varying outcomes to SARS-CoV-2 infection are yet to be elucidated. Here we show that an endogenously activated interferon lambda (IFNλ1) pathway leads to resistance against SARS-CoV-2 infection. Using a well-differentiated primary nasal epithelial cell (WD-PNEC) culture model derived from multiple adult donors, we discovered that susceptibility to SARS-CoV-2 infection, but not respiratory syncytial virus (RSV) infection, varied. One of four donors was resistant to SARS-CoV-2 infection. High baseline IFNλ1 expression levels and associated interferon stimulated genes correlated with resistance to SARS-CoV-2 infection. Inhibition of the JAK/STAT pathway in WD-PNECs with high endogenous IFNλ1 secretion resulted in higher SARS-CoV-2 titres. Conversely, prophylactic IFNλ treatment of WD-PNECs susceptible to infection resulted in reduced viral titres. An endogenously activated IFNλ response, possibly due to genetic differences, may be one explanation for the differences in susceptibility to SARS-CoV-2 infection in humans. Importantly, our work supports the continued exploration of IFNλ as a potential pharmaceutical against SARS-CoV-2 infection., Competing Interests: The authors have declared that no competing interests exist.

SARS-CoV-2 can efficiently infect both children and adults, albeit with morbidity and mortality positively associated with increasing host age and presence of co-morbidities. SARS-CoV-2 continues to adapt to the human population, resulting in several variants of concern (VOC) with novel properties, such as Alpha and Delta. However, factors driving SARS-CoV-2 fitness and evolution in paediatric cohorts remain poorly explored. Here, we provide evidence that both viral and host factors co-operate to shape SARS-CoV-2 genotypic and phenotypic change in primary airway cell cultures derived from children. Through viral whole-genome sequencing, we explored changes in genetic diversity over time of two pre-VOC clinical isolates of SARS-CoV-2 during passage in paediatric well-differentiated primary nasal epithelial cell (WD-PNEC) cultures and in parallel, in unmodified Vero-derived cell lines. We identified a consistent, rich genetic diversity arising in vitro, variants of which could rapidly rise to near fixation within two passages. Within isolates, SARS-CoV-2 evolution was dependent on host cells, with paediatric WD-PNECs showing a reduced diversity compared to Vero (E6) cells. However, mutations were not shared between strains. Furthermore, comparison of both Vero-grown isolates on WD-PNECs disclosed marked growth attenuation mapping to the loss of the polybasic cleavage site (PBCS) in Spike, while the strain with mutations in Nsp12 (T293I), Spike (P812R) and a truncation of Orf7a remained viable in WD-PNECs. Altogether, our work demonstrates that pre-VOC SARS-CoV-2 efficiently infects paediatric respiratory epithelial cells, and its evolution is restrained compared to Vero (E6) cells, similar to the case of adult cells. We highlight the significant genetic plasticity of SARS-CoV-2 while uncovering an influential role for collaboration between viral and host cell factors in shaping viral evolution and ultimately fitness in human respiratory epithelium.

In recent years, microbiota has become an increasingly relevant factor for the understanding and potential treatment of diseases. In this work, based on the data reported by the largest study of microbioma in the world, a classification model has been developed based on Machine Learning (ML) capable of predicting the country of origin (United Kingdom vs United States) according to metagenomic data. The data were used for the training of a glmnet algorithm and a Random Forest algorithm. Both algorithms obtained similar results (0.698 and 0.672 in AUC, respectively). Furthermore, thanks to the application of a multivariate feature selection algorithm, eleven metagenomic genres highly correlated with the country of origin were obtained. An in-depth study of the variables used in each model is shown in the present work.

Objective: Most diseases result from the complex interplay between genetic and environmental factors. The exposome can be defined as a systematic approach to acquire large data sets corresponding to environmental exposures of an individual along her/ his life. The objective of this contribution is to raise awareness within the health informatics community about the importance of dealing with data related to the contribution of environmental factors to individual health, particularly in the context of precision medicine informatics., Methods: This article summarizes the main findings after a panel organized by the International Medical Informatics Association - Exposome Informatics Working Group held during the last MEDINFO, in Lyon (France) in August 2019., Results: The members of our community presented four initiatives (PULSE, Digital exposome, Cloudy with a chance of pain, Wearable clinics), providing a detailed view of current challenges and accomplishments in processing environmental and social data from a health research perspective. Projects illustrate a wide range of research methods, digital data collection technologies, and analytics and visualization tools. This reinforces the idea that this area is now ready for health informaticians to step in and contribute their expertise, leading the application of informatics strategies to understand environmental health problems., Conclusions: The featured projects illustrate applications that use exposome data for the investigation of the causes of diseases, health care, patient empowerment, and public health. They offer a rich overview of the expanding range of applications that informatics is finding in the field of environmental health, with potential impact in precision medicine., Competing Interests: Disclosure The authors report no conflicts of interest in this work., (Georg Thieme Verlag KG Stuttgart.)

Objectives: Preeclampsia is a cardiovascular pregnancy complication that occurs in 5-10% of pregnancies and it can lead to a number of pregnancy complications including maternal and foetal death. Long-term, preeclampsia is associated with up to 8-fold increased risk of cardiovascular disease (CVD) for both mothers and their offspring. The lack of mechanistic data in relation to the causes or consequences of preeclampsia has prevented the development of effective therapeutic and monitoring strategies., Study Design: This study investigates common underlying mechanisms of preeclampsia and CVD, specifically hypertension and heart failure with preserved ejection fraction (HFpEF), using "in silico" approach of publicly available datasets. Integrated techniques were designed to mine data repositories and identify relevant biomarkers associated with these three conditions., Main Outcomes Measures: The knowledge base tools were employed that enabled the analysis of these biomarkers to discover potential molecular and biological links between these three conditions., Results: Our bioinformatics "in silico" analyses of the publically available datasets identified 76 common biomarkers between preeclampsia, hypertension and HFpEF. These biomarkers were representative of 29 pathways commonly enriched across the three conditions which were largely related to inflammation, metabolism, angiogenesis, remodelling, haemostasis, apoptosis and the renin-angiotensin-aldosterone (RAAS) system., Conclusions: This bioinformatics approach uses the wealth of scientific data available in public repositories to gain a deeper understanding of the overlapping pathogenic mechanisms of associated diseases, which could be explored as biomarkers or targets to prevent long-term cardiovascular complications such as hypertension and HFpEF following preeclampsia., (Copyright © 2020 International Society for the Study of Hypertension in Pregnancy. Published by Elsevier B.V. All rights reserved.)