Decoding the mechanism of hypertension through multiomics profiling

Hypertension, characterised by a constant high blood pressure, is the primary risk factor for multiple cardiovascular events and a major cause of death in adults. Excitingly, innovations in high-throughput technologies have enabled the global exploration of the whole genome (genomics), revealing dysregulated genes that are linked to hypertension. Moreover, post-genomic biomarkers, from the emerging fields of transcriptomics, proteomics, glycomics and lipidomics, have provided new insights into the molecular underpinnings of hypertension. In this paper, we review the pathophysiology of hypertension, and highlight the multi-omics approaches for hypertension prediction and diagnosis

N-Glycosylation profiles as a risk stratification biomarker for Type II Diabetes Mellitus and its associated factors

Worldwide, the prevalence of cardiometabolic diseases, particularly type II diabetes mellitus (T2DM), and to a lesser extent, metabolic syndrome (MetS), has increased dramatically. Despite this increase, there is still a lack of robust biomarkers for cardiometabolic diseases to secure better clinical outcomes. The enzymatic attachment of oligosaccharides (glycans) to proteins-glycosylation is of metabolic and physiological significance, as exploring aberrations of glycosylation profiles can reveal novel biomarkers. In parallel, this process could also explain the biological mechanisms that underpin a suboptimal health status (SHS), a reversible subclinical stage of a cardiometabolic disease. However, studies on the correlation between glycosylation and MetS/T2DM are scarce and none has thus far been performed on a West African population. Thus, the overall aim of this thesis was to explore complementary biomarker panels of healthy and diseased patients considered relevant to Ghanaian residents. The thesis is structured in the form of five related studies, each addressing a specific aim. From January 2016 to October 2016, a longitudinal case-control study comprising 253 T2DM patients and 260 controls, aged 18-80 years was conducted in Ghana. Fasting plasma samples were collected for clinical assessment, after which plasma N-glycans were analysed by Ultra-Performance Liquid Chromatography (UPLC) and statistical analyses performed. Central adiposity, underweight, high systolic blood pressure (SBP), high diastolic blood pressure (DBP) and high triglycerides (TG) were found to be independent risk factors associated with high SHS after adjusting for age and gender (Study I). SHS score was associated with age, physical inactivity, fasting plasma glucose (FPG), TG and MetS. MetS was associated with increased high branching (HB), trigalactosylated (G3), antennary fucosylated (FUC_A), triantennary (TRIA) and decreased low branching (LB) glycan structures (Study II). The levels of HB, G3, FUC_A, and TRIA N-glycans were increased in T2DM whereas levels of LB, non-sialylated (S0), monogalactosylation (G1), core fucosylation (FUC_C), biantennary galactosylation (A2G) and biantennary (BA) Nglycans were decreased compared to controls (Study III). Biguanides alone, or in combination with sulfonylurea and thiazolidinedione, did not improve glycaemic status at follow-up. Many participants using angiotensin converting enzyme inhibitors achieved desired targets for blood pressure control while statins were effective for control of plasma lipids (Study IV). At a population level, the variability of N-glycan structures ranged from 11% to 56% at both baseline and follow-up, with an average coefficient of variation of 28% and 29%, respectively. The intra-individual N-glycan peak (GP) variations were minor except for GP1 and GP29. However, there were no statistically significant differences in N-glycosylation profiles from baseline to follow-up (Study V). This thesis shows an association between SHS and MetS/T2DM while MetS and T2DM are characterised by increased levels of complex N-glycan structures, and these structures are stable in T2DM over six months. Many of the findings in this thesis agree with earlier studies from Chinese and Croatian populations with major differences attributed to genetic and environmental factors. Future longitudinal studies are required to provide a better understanding of the transition from SHS to T2DM, as well as to validate N-glycans as generic risk stratification biomarkers for a general population

Environmentally friendly agent against fall armyworm (Spodoptera frugiperda): Antifeedant potency of mentha spicata aqueous extracts

The rising trends of insect resistance, coupled with escalating environmental pollution from synthetic pesticides, heighten the need for a more effective and, non-hazardous agents to control insect/pests. Different aqueous extracts of Mentha spicata were screened for their phytochemical constituents and their antifeedant activities against Spodoptera frugiperda. Screening of the different aqueous extracts of Mentha spicata obtained by cold maceration revealed the presence of phenolics and tannins. The concentration of phenols and tannins in the water, glycerine, and glycerine plus water (glycerine-water) extracts were significantly different (p \u3c 0.05). Mentha spicata water extract had a greater antifeedant activity against Spodoptera frugiperda as compared to glycerine and glycerine-water (60 : 40, v/v) extracts at a concentration of 5g/100 mL. The estimated % antifeedant activity recorded were 97 as against 8.21 and 49.81, respectively. Aqueous neem seed water extracts gave an estimated % antifeedant activity of 93.07 and it served as a control. Saponins were absent in all extracts and only water extracts had alkaloids present. The simple, non-hazardous, and cost-saving extraction method demonstrated could be applied in both commercial and subsistent farming to counteract the damnable effects of Spodoptera frugiperda infestation

Unravelling immunoglobulin G Fc N-glycosylation: A dynamic marker potentiating predictive, preventive and personalised medicine

Multiple factors influence immunoglobulin G glycosylation, which in turn affect the glycoproteins’ function on eliciting an anti-inflammatory or pro-inflammatory response. It is prudent to underscore these processes when considering the use of immunoglobulin G N-glycan moieties as an indication of disease presence, progress, or response to therapeutics. It has been demonstrated that the altered expression of genes that encode enzymes involved in the biosynthesis of immunoglobulin G N-glycans, receptors, or complement factors may significantly modify immunoglobulin G effector response, which is important for regulating the immune system. The immunoglobulin G N-glycome is highly heterogenous; however, it is considered an interphenotype of disease (a link between genetic predisposition and environmental exposure) and so has the potential to be used as a dynamic biomarker from the perspective of predictive, preventive, and personalised medicine. Undoubtedly, a deeper understanding of how the multiple factors interact with each other to alter immunoglobulin G glycosylation is crucial. Herein we review the current literature on immunoglobulin G glycoprotein structure, immunoglobulin G Fc glycosylation, associated receptors, and complement factors, the downstream effector functions, and the factors associated with the heterogeneity of immunoglobulin G glycosylation

IMass time: The future, in future!

Joseph John Thomson discovered and proved the existence of electrons through a series of experiments. His work earned him a Nobel Prize in 1906 and initiated the era of mass spectrometry (MS). In the intervening time, other researchers have also been awarded the Nobel Prize for significant advances in MS technology. The development of soft ionization techniques was central to the application of MS to large biological molecules and led to an unprecedented interest in the study of biomolecules such as proteins (proteomics), metabolites (metabolomics), carbohydrates (glycomics), and lipids (lipidomics), allowing a better understanding of the molecular underpinnings of health and disease. The interest in large molecules drove improvements in MS resolution and now the challenge is in data deconvolution, intelligent exploitation of heterogeneous data, and interpretation, all of which can be ameliorated with a proposed IMass technology. We define IMass as a combination of MS and artificial intelligence, with each performing a specific role. IMass will offer advantages such as improving speed, sensitivity, and analyses of large data that are presently not possible with MS alone. In this study, we present an overview of the MS considering historical perspectives and applications, challenges, as well as insightful highlights of IMass

Integration of suboptimal health status evaluation as a criterion for prediction of preeclampsia is strongly recommended for healthcare management in pregnancy: A prospective cohort study in a Ghanaian population

Background: Normotensive pregnancy may develop into preeclampsia (PE) and other adverse pregnancy complications (APCs), for which the causes are still unknown. Suboptimal health status (SHS), a physical state between health and disease, might contribute to the development and progression of PE. By integration of a routine health measure in this Ghanaian Suboptimal Health Cohort Study, we explored the usefulness of a 25-question item SHS questionnaire (SHSQ-25) for early screening and prediction of normotensive pregnant women (NTN-PW) likely to develop PE. Methods: We assessed the overall health status among a cohort of 593 NTN-PW at baseline (10–20 weeks gestation) and followed them at 21–31 weeks until 32–42 weeks. After an average of 20 weeks follow-up, 498 participants returned and were included in the final analysis. Hematobiochemical, clinical and sociodemographic data were obtained. Results: Of the 498 participants, 49.8% (248/498) had ‘high SHS’ at baseline (61.7% (153/248) later developed PE) and 38.3% (95/248) were NTN-PW, whereas 50.2% (250/498) had ‘optimal health’ (17.6% (44/250) later developed PE) and 82.4% (206/ 250) were NTN-PW. At baseline, high SHS score yielded a significantly (p \u3c 0.05) increased adjusted odds ratio, a wider area under the curve (AUC) and a higher sensitivity and specificity for the prediction of PE (3.67; 0.898; 91.9% and 87.8%), PE coexisting with intrauterine growth restriction (2.86, 0.838; 91.5% and 75.9%), stillbirth (2.52; 0.783; 96.6% and 60.0%), hemolysis elevated liver enzymes and low platelet count (HELLP) syndrome (2.08; 0.800; 97.2% and 63.8%), acute kidney injury (2.20; 0.825; 95.3% and 70.0%) and dyslipidaemia (2.80; 0.8205; 95.7% and 68.4%) at 32–42 weeks gestation. Conclusions: High SHS score is associated with increased incidence of PE; hence, SHSQ-25 can be used independently as a risk stratification tool for adverse pregnancy outcomes thereby creating an opportunity for predictive, preventive and personalized medicine

Conceptualised psycho-medical footprint for health status outcomes and the potential impacts for early detection and prevention of chronic diseases in the context of 3P medicine

Background: The Suboptimal Health Status Questionnaire-25 (SHSQ-25) is a distinctive medical psychometric diagnostic tool designed for the early detection of chronic diseases. However, the synaptic connections between the 25 symptomatic items and their relevance in supporting the monitoring of suboptimal health outcomes, which are precursors for chronic diseases, have not been thoroughly evaluated within the framework of predictive, preventive, and personalised medicine (PPPM/3PM). This baseline study explores the internal structure of the SHSQ-25 and demonstrates its discriminatory power to predict optimal and suboptimal health status (SHS) and develop photogenic representations of their distinct relationship patterns. Methods: The cross-sectional study involved healthy Ghanaian participants (n = 217; aged 30–80 years; ~ 61% female), who responded to the SHSQ-25. The median SHS score was used to categorise the population into optimal and SHS. Graphical LASSO model and multi-dimensional scaling configuration methods were employed to describe the network structures for the two populations. Results: We observed differences in the structural, node placement and node distance of the synaptic networks for the optimal and suboptimal populations. A statistically significant variance in connectivity levels was noted between the optimal (58 non-zero edges) and suboptimal (43 non-zero edges) networks (p = 0.024). Fatigue emerged as a prominently central subclinical condition within the suboptimal population, whilst the cardiovascular system domain had the greatest relevance for the optimal population. The contrast in connectivity levels and the divergent prominence of specific subclinical conditions across domain networks shed light on potential health distinctions. Conclusions: We have demonstrated the feasibility of creating dynamic visualizers of the evolutionary trends in the relationships between the domains of SHSQ-25 relative to health status outcomes. This will provide in-depth comprehension of the conceptual model to inform personalised strategies to circumvent SHS. Additionally, the findings have implications for both health care and disease prevention because at-risk individuals can be predicted and prioritised for monitoring, and targeted intervention can begin before their symptoms reach an irreversible stage. We observed differences in the structural, node placement and node distance of the synaptic networks for the optimal and suboptimal populations. A statistically significant variance in connectivity levels was noted between the optimal (58 non-zero edges) and suboptimal (43 non-zero edges) networks (p = 0.024). Fatigue emerged as a prominently central subclinical condition within the suboptimal population, whilst the cardiovascular system domain had the greatest relevance for the optimal population. The contrast in connectivity levels and the divergent prominence of specific subclinical conditions across domain networks shed light on potential health distinctions

Evaluation of dyslipidaemia using an algorithm of lipid profile measures among newly diagnosed type II diabetes mellitus patients: A cross-sectional study at Dormaa Presbyterian Hospital, Ghana

Background and Objectives: Dyslipidaemia and its associated complications have been reported to increase mortality among type 2 diabetes mellitus (T2DM) patients. However, there is a dearth of data on the incidence of dyslipidemia among Ghanaian patients with T2DM. This study evaluated dyslipidemia among newly diagnosed T2DM patients at Dormaa Presbyterian Hospital, Ghana. Materials and Methods: This cross-sectional study recruited a total of 215 participants at the Presbyterian Hospital, Dormaa-Ghana. A well-structured questionnaire was administered to collect demographic data. Predisposing factors of dyslipidemia such as BMI, hypertension, and family history of diabetes were also obtained. Lipid profile was performed on the serum obtained from each respondent. Dyslipidaemia was defined as total cholesterol (TC) \u3e200 mg/dL, triglyceride (TG) \u3e150 mg/dL, low density lipoprotein cholesterol (LDL-c) \u3e100 mg/dL, and high-density lipoprotein cholesterol (HDL-c)/dL in females. Combinations of the individual parameters of dyslipidaemia were further evaluated. Results: Of the total (215) participants, 86 (40%) were males and 129 (60%) were females, representing a ratio of 1:1.5. High total cholesterol was more prevalent in females (69.0%) than males (53.5%). Generally, dyslipidaemia was predominant among those aged \u3e40 years, with the exception of increased LDL-c (25.1%), which was higher among the 20–40 years age group. The male participants exhibited significantly (p \u3c 0.001) higher percentages of all combined measures of dyslipidaemia—such as high TG and reduced HDL-c (77.9%), high TG and elevated LDL-c (75.6%) and high LDL and low HDL (65.1%). BMI was significantly associated with HDL levels (p = 0.02), whereas family history of diabetes was associated with TC (p = 0.004) and TG levels (p = 0.019). Conclusion: Combined dyslipidaemia is relatively high among newly diagnosed T2DM patients in Ghana, and in those \u3e40 years. Gender is significantly associated with combined dyslipidaemia in T2DM, and males may be at a higher risk than females. BMI and family history of diabetes are potential risk factors of dyslipidaemia in T2DM

Suboptimal health pregnant women are associated with increased oxidative stress and unbalanced pro- and antiangiogenic growth mediators: A cross-sectional study in a Ghanaian population

Optimal oxidative stress (OS) is important throughout pregnancy; however, an increased OS may alter placental angiogenesis culminating in an imbalanced of angiogenic growth mediators (AGMs). Suboptimal Health Status (SHS), a physical state between health and disease, may be associated with increased OS and unbalanced AGMs. In this study, we explored the association between SHS, biomarkers of OS (BOS) and AGMs among normotensive pregnant women (NTN-PW) in a Ghanaian Suboptimal Health Cohort Study (GHOACS). This comparative GHOACS recruited 593 NTN-PW from the Komfo Anokye Teaching Hospital, Ghana. SHS was measured using a Suboptimal Health Status Questionnaire-25 (SHSQ-25). Along with the subjective SHS measure, objective BOS: 8-hydroxy-2-deoxyguanosine (8-OHdG), 8-epiprostaglandinF2 alpha (8-epi-PGF2α), total antioxidant capacity (TAC), and AGMs: vascular endothelial growth factor-A (VEGF-A), soluble fms-like tyrosine kinase receptor 1 (sFlt-1), placental growth factor (PIGF) and soluble endoglin (sEng) were evaluated. Compared to optimal health NTN-PW, levels of PlGF, VEGF-A and TAC were significantly (p \u3c 0.05) reduced and negatively associated with SHS whilst sEng, sFlt-1, 8-epiPGF2α, 8-OHdG, and combined ratios of sFlt-1/PlGF, 8-epiPGF2α/PlGF, 8-OHdG/PlGF, and sEng/PlGF were significantly increased and positively associated with SHS. The first quartile for PIGF (2.79-fold) and VEGF-A (5.35-fold), and the fourth quartile for sEng (4.31-fold), sFlt-1 (1.84-fold), 8-epiPGF2α (2.23-fold), 8-OHdG (1.90-fold) and urinary 8-OHdG (1.95-fold) were independently associated with SHS (p \u3c 0.05). SHS is associated with increased OS and unbalanced AGMs. Early identification of SHS-related OS and unbalanced AGMs may inform clinicians of the need for therapeutic options

Multi-block data integration analysis for identifying and validating targeted N-glycans as biomarkers for type II diabetes mellitus

Plasma N-glycan profiles have been shown to be defective in type II diabetes Mellitus (T2DM) and holds a promise to discovering biomarkers. The study comprised 232 T2DM patients and 219 healthy individuals. N-glycans were analysed by high-performance liquid chromatography. The multivariate integrative framework, DIABLO was employed for the statistical analysis. N-glycan groups (GPs 34, 32, 26, 31, 36 and 30) were significantly expressed in T2DM in component 1 and GPs 38 and 20 were related to T2DM in component 2. Four clusters were observed based on the correlation of the expressive signatures of the 39 N-glycans across T2DM and controls. Cluster A, B, C and D had 16, 16, 4 and 3 N-glycans respectively, of which 11, 8, 1 and 1 were found to express differently between controls and T2DM in a univariate analysis (p\u3c 0.05). Multi-block analysis revealed that trigalactosylated (G3), triantennary (TRIA), high branching (HB) and trisialylated (S3) expressed significantly highly in T2DM than healthy controls. A bipartite relevance network revealed that HB, monogalactosylated (G1) and G3 were central in the network and observed more connections, highlighting their importance in discriminating between T2DM and healthy controls. Investigation of these N-glycans can enhance the understanding of T2DM