Fine-scale haplotype mapping of MUT, AACS, SLC6A15 and PRKCA genes indicates association with insulin resistance of metabolic syndrome and relationship with branched chain amino acid metabolism or regulation

Bioinformatics analysis identifies key secretory protein-encoding differentially expressed genes in adipose tissue of metabolic syndrome

The objective of this study was to identify key secretory protein-encoding differentially expressed genes (SP-DEGs) in adipose tissue in female metabolic syndrome, thus detecting potential targets in treatment. We examined gene expression profiles in 8 women with metabolic syndrome and 7 healthy, normal body weight women. A total of 143 SP-DEGs were screened, including 83 upregulated genes and 60 downregulated genes. GO analyses of these SP-DEGs included proteolysis, angiogenesis, positive regulation of endothelial cell proliferation, immune response, protein processing, positive regulation of neuroblast proliferation, cell adhesion and ER to Golgi vesicle-mediated transport. KEGG pathway analysis of the SP-DEGs were involved in the TGF-beta signalling pathway, cytokine‒cytokine receptor interactions, the hippo signalling pathway, Malaria. Two modules were identified from the PPI network, namely, Module 1 (DNMT1, KDM1A, NCoR1, and E2F1) and Module 2 (IL-7 R, IL-12A, and CSF3). The gene DNMT1 was shared between the network modules and the WGCNA brown module. According to the single-gene GSEA results, DNMT1 was significantly positively correlated with histidine metabolism and phenylalanine metabolism. This study identified 7 key SP-DEGs in adipose tissue. DNMT1 was selected as the central gene in the development of metabolic syndrome and might be a potential therapeutic target.

Proteomics exploration of metformin hydrochloride for diabetic kidney disease treatment via the butanoate metabolism pathway

Diabetic nephropathy (DKD) is a diabetesrelated kidney injury with an increasing incidence every year. Metformin hydrochloride (MET), a cornerstone treatment for glucose lowering, has been widely reported for the treatment of DKD, but the specific molecular mechanisms and potential therapeutic targets still need to be further explored. We used kidney tissues from db/db mice as samples and used proteomics and bioinformatics to analyse the function, distribution and related pathways of differential proteins in DKD, focusing on the assessment of the binding energies of key proteins in the butyrate pathway and drugs at the molecular level, which showed that the expression profiles of differential proteins in kidney tissues were altered after MET treatment, involving energy metabolism. The key proteins involved in the butanoate metabolism pathway, including AACS, ACSM3, EHHADH and HMGCS2, exhibit binding energies to MET of ＜-5 kcal. It is therefore plausible that MET treatment may affect the butanoate metabolism pathway, potentially ameliorating the progression of DKD by modulating mitochondrial function and inflammatory responses.

Effectiveness of a short-term oxygen therapy training program in Liberia during and after COVID-19

Background

Access to high-quality medical oxygen has been a long-standing challenge in Liberia due to barriers that span across the health system, which were amplified during the COVID-19 pandemic. The surge in cases requiring oxygen therapy necessitated rapid capacity-building for healthcare workers. In response, an emergency oxygen training package was adapted and implemented by the Liberia Ministry of Health and the National Incidence Management System. This manuscript evaluates the implementation of a short-term respiratory care training package to rapidly build healthcare worker capacity during the COVID-19 response and its adaptation for routine in-service training post-response.

Methods

The emergency training used the "hot and cold" simulation approach from the 2014 Ebola response, consisting of a cold phase (3-days) with didactic lectures and practical sessions, and mock COVID treatment unit simulations (2-days); and a hot phase within an active CTU. Participants were doctors, physician assistants, nurses, or midwives, deployed to COVID treatment units at major health centers and hospitals across all counties in Liberia. Training assessments consisted of a paper-based knowledge test pre- and post-training, and Objective Structured Clinical Examinations post-training.

Results

The emergency training as part of COVID response included 123 health care workers from 43 health facilities and saw a significant increase in knowledge (median score of 46% pre-training vs. 84% post-training, p < 0.001). Adaptation and piloting of the package for routine in-service training was also effective at increasing knowledge amongst 81 health care workers (median score of 41% pre-training vs. 78% post-training, p < 0.001). High post-training Objective Structured Clinical Examination scores demonstrated clinical competency achievement in both cohorts. For emergency training, median scores were 92% (pulse oximetry), 81% (oxygen cylinders), and 83% (oxygen concentrators). For routine in-service training, scores were 88, 82, and 84%, respectively.

Conclusion

We demonstrate that the implementation of a healthcare worker training package in oxygen therapy during the COVID response in Liberia and its eventual integration into a routine in-service training program was able to achieve significant improvements in health care worker knowledge and skills. This highlights the feasibility of using rapid and short-term training to enhance clinical capacity within both emergency and post-response settings in a resource-limited country.

Analysis of type 2 diabetes mellitus-related genes by constructing the pathway-based weighted network

Complex network is an effective approach to studying complex diseases, and provides another perspective for understanding their pathological mechanisms by illustrating the interactions between various factors of diseases. Type 2 diabetes mellitus (T2DM) is a complex polygenic metabolic disease involving genetic and environmental factors. By combining the complex network approach with biological data, this study constructs a pathway-based weighted network model of T2DM-related genes to explore the interrelationships between genes, here a weight is assigned to each edge in terms of the number of the same pathways in which the two nodes (genes) connected to the edge are involved. The edge weights can reflect differences in the strength of connections (interactions) between nodes (genes), which intuitively reflect the extent of biological correlations between genes and contribute to the importance of the nodes. Analysis of statistical and topological characteristics shows that the edge weights are correlated to the network topology, and the edge weight distribution decays as a power-law. The disparity of the weights indicates that the edge weight distribution for the nodes with the same degree is of approximately equal weights; and most edges with the higher weights tend to connect with the higher degree nodes. To determine the key hub genes of the weighted network, an integrated ranking index is used to comprehensively reflect the contribution of the three indices (strength, degree and number of pathways) of nodes; by taking the threshold of integrated ranking index greater than 0.56, 12 key hub genes are identified: MAPK1, PIK3CD, PIK3CA, PIK3R1, AKT2, AKT1, KRAS, TNF, MAPK8, PRKCA, IL6 and MTOR. These genes should play an important role in the occurrence and development of T2DM, and can be regarded as potential therapeutic targets for further biological and medical research on their functions in T2DM. It can be expected that combining complex network approach with other data analysis techniques can provide more clues for exploring the pathogenesis and treatment of T2DM and other complex diseases in the future.

Fine-Scale Haplotype Mapping Reveals an Association of the FTO Gene with Osteoporosis and Fracture Risk in Postmenopausal Women

INTRODUCTION

The Fat Mass and Obesity-Associated (FTO) gene encodes a demethylase, which modulates RNA N6-methyladenosine (m6A) and plays a regulatory role in adipocyte differentiation and the pathogenesis of human obesity.

METHODS

To understand the potential role of FTO in osteoporosis (OP), we investigated five single nucleotide variations (SNVs) in intron 1 (rs8057044, rs8050136, rs9939609, rs62033406, and rs9930506) of the FTO gene, and a missense SNV i.e., rs3736228 (A1330V), located in exon 18 of the LRP5 gene, in a cohort of postmenopausal women (n = 188) from Central Europe. Genotyping was performed with an allele discrimination assay, while haplotypes were reconstructed in the population by PHASE 2.1.

RESULTS

The rs9930506 was strongly associated with OP (p < 0.0035), which was supported by Bonferroni correction (p < 0.0175), and all SNVs located in the FTO gene were more strongly associated with severe OP with fragility fractures. Among seventeen haplotypes detected for the FTO gene, two haplotypes (H1 and H9) were frequent (frequency > 10%) and distributed in three main haplotypes pairs (H1/H1, H1/H9 and H9/H9, respectively). The pathogenic pair H1/H9 was associated with a leaner phenotype, increased fracture risk, and a lower bone mineral density (BMD), and carried the heterozygous GA of rs9930506, while the protective pair H9/H9 was associated with an increased obesity risk and carried AA alleles of rs9939609.

CONCLUSIONS

Concordant associations with OP, an increased fracture risk, and a lower BMD at all skeletal sites indicate that the FTO gene is a promising candidate for OP, explaining the complex relationship with obesity and offering new perspectives for the study of the epigenetic regulation of bone metabolism.

Relative Contribution of Metabolic Syndrome Components in Relation to Obesity and Insulin Resistance in Postmenopausal Osteoporosis

Introduction. Osteoporosis (OP) affects 30% of postmenopausal women, often complicated by metabolic syndrome (MetS) with a still controversial role. We aimed to characterize MetS and its components in relation to bone mineral density (BMD), body mass index (BMI), and insulin resistance. Methods. Patients (n = 188) underwent DEXA scans, spine X-rays, and metabolic and hormonal investigations, including bone biomarkers, muscular strength, and physical performance tests, while insulin resistance was evaluated by the Homeostasis Model Assessment (HOMA-IR). Results. Patients with a normal BMD or osteopenia (n = 68) and with OP (n = 120) displayed 51.5% and 30.8% of MetS, but without differences in insulin resistance. When BMD was studied as a function of the cumulative MetS criteria and centiles of BMI, lower levels of BMD were observed beyond an inflection point of 27.2 kg/m2 for BMI, allowing for further stratification as lean and overweight/obese (OW/OB) subjects. In contrast with lean individuals (n = 74), in OW/OB patients (n = 46), MetS was associated with HbA1c (p < 0.0037, OR 9.6, 95% CI [1.64-55.6]) and insulin resistance (p < 0.0076, OR 6.7, 95% CI [1.49-30.8]) in the context where BMD values were lower than those predicted from BMI in non-OP subjects. In OP patients with fragility fractures (31% of MetS), glycemia also appeared to be the dominant factor for MetS (p < 0.0005, OR 4.1, 95% CI [1.63-10.39]). Conclusions. These data indicate a detrimental effect of insulin resistance in MetS on OP patients, while the prevalence of the syndrome depends on the proportion of obesity. These findings provide new insights into the pathogenic role of MetS and reveal the need to consider different strata of BMI and insulin resistance when studying postmenopausal OP.

Lipodystrophy in methylmalonic acidemia associated with elevated FGF21 and abnormal methylmalonylation

A distinct adipose tissue distribution pattern was observed in patients with methylmalonyl-CoA mutase deficiency, an inborn error of branched-chain amino acid (BCAA) metabolism, characterized by centripetal obesity with proximal upper and lower extremity fat deposition and paucity of visceral fat, that resembles familial multiple lipomatosis syndrome. To explore brown and white fat physiology in methylmalonic acidemia (MMA), body composition, adipokines, and inflammatory markers were assessed in 46 patients with MMA and 99 matched controls. Fibroblast growth factor 21 levels were associated with acyl-CoA accretion, aberrant methylmalonylation in adipose tissue, and an attenuated inflammatory cytokine profile. In parallel, brown and white fat were examined in a liver-specific transgenic MMA mouse model (Mmut-/- TgINS-Alb-Mmut). The MMA mice exhibited abnormal nonshivering thermogenesis with whitened brown fat and had an ineffective transcriptional response to cold stress. Treatment of the MMA mice with bezafibrates led to clinical improvement with beiging of subcutaneous fat depots, which resembled the distribution seen in the patients. These studies defined what we believe to be a novel lipodystrophy phenotype in patients with defects in the terminal steps of BCAA oxidation and demonstrated that beiging of subcutaneous adipose tissue in MMA could readily be induced with small molecules.

Bioinformatics prediction and experimental verification of key biomarkers for diabetic kidney disease based on transcriptome sequencing in mice

Background

Diabetic kidney disease (DKD) is the leading cause of death in people with type 2 diabetes mellitus (T2DM). The main objective of this study is to find the potential biomarkers for DKD.

Materials and Methods

Two datasets (GSE86300 and GSE184836) retrieved from Gene Expression Omnibus (GEO) database were used, combined with our RNA sequencing (RNA-seq) results of DKD mice (C57 BLKS-32w db/db) and non-diabetic (db/m) mice for further analysis. After processing the expression matrix of the three sets of data using R software "Limma", differential expression analysis was performed. The significantly differentially expressed genes (DEGs) (-logFC- > 1, p-value < 0.05) were visualized by heatmaps and volcano plots respectively. Next, the co-expression genes expressed in the three groups of DEGs were obtained by constructing a Venn diagram. In addition, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were further analyzed the related functions and enrichment pathways of these co-expression genes. Then, qRT-PCR was used to verify the expression levels of co-expression genes in the kidney of DKD and control mice. Finally, protein-protein interaction network (PPI), GO, KEGG analysis and Pearson correlation test were performed on the experimentally validated genes, in order to clarify the possible mechanism of them in DKD.

Results

Our RNA-seq results identified a total of 125 DEGs, including 59 up-regulated and 66 down-regulated DEGs. At the same time, 183 up-regulated and 153 down-regulated DEGs were obtained in GEO database GSE86300, and 76 up-regulated and 117 down-regulated DEGs were obtained in GSE184836. Venn diagram showed that 13 co-expression DEGs among the three groups of DEGs. GO analysis showed that biological processes (BP) were mainly enriched inresponse to stilbenoid, response to fatty acid, response to nutrient, positive regulation of macrophage derived foam cell differentiation, triglyceride metabolic process. KEGG pathway analysis showed that the three major enriched pathways were cholesterol metabolism, drug metabolism-cytochrome P450, PPAR signaling pathway. After qRT-PCR validation, we obtained 11 genes that were significant differentially expressed in the kidney tissues of DKD mice compared with control mice. (The mRNA expression levels of Aacs, Cpe, Cd36, Slc22a7, Slc1a4, Lpl, Cyp7b1, Akr1c14 and Apoh were declined, whereas Abcc4 and Gsta2 were elevated).

Conclusion

Our study, based on RNA-seq results, GEO databases and qRT-PCR, identified 11 significant dysregulated DEGs, which play an important role in lipid metabolism and the PPAR signaling pathway, which provide novel targets for diagnosis and treatment of DKD.

Potential biomarkers of endocrine and habitat disruption identified via RNA-Seq in Salvelinus fontinalis with proximity to fracking operations in Pennsylvania headwater stream ecosystems

Unconventional natural gas development (fracking) has been a rapidly expanding technique used for the extraction of natural gas from the Marcellus Shale formation in Pennsylvania. There remains a knowledge gap regarding the ecological impacts of fracking, especially regarding the long-term health of native Brook trout (Salvelinus fontinalis) populations. During the summer of 2015, Brook trout were sampled from twelve streams located in forested, northwestern Pennsylvania in order to evaluate the impacts of fracking on Brook trout. Four stream sites were undisturbed (no fracking activity), three had a developed well pad without fracking activity, and five had active fracking with natural gas production. Liver tissue was isolated from two to five fish per stream and underwent RNA-Seq analysis to identify differentially expressed genes between ecosystems with differing fracking status. Data were analyzed individually and with samples pooled within-stream to account for hierarchical data structure and variation in sample coverage within streams. Differentially expressed and differentially alternatively spliced genes had functions related to lipid and steroid metabolism, mRNA processing, RNA polymerase and protein regulation. Unique to our study, genes related to xenobiotic and stress responses were found as well as potential markers for endocrine disruption and saline adaptation that were identified in watersheds with active fracking activity. These results support the utility of RNA-Seq to assess trout health and suggest detrimental impacts of fracking on sensitive trout populations.

Identification of candidate biomarkers and pathways associated with type 1 diabetes mellitus using bioinformatics analysis

Type 1 diabetes mellitus (T1DM) is a metabolic disorder for which the underlying molecular mechanisms remain largely unclear. This investigation aimed to elucidate essential candidate genes and pathways in T1DM by integrated bioinformatics analysis. In this study, differentially expressed genes (DEGs) were analyzed using DESeq2 of R package from GSE162689 of the Gene Expression Omnibus (GEO). Gene ontology (GO) enrichment analysis, REACTOME pathway enrichment analysis, and construction and analysis of protein–protein interaction (PPI) network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network, and validation of hub genes were performed. A total of 952 DEGs (477 up regulated and 475 down regulated genes) were identified in T1DM. GO and REACTOME enrichment result results showed that DEGs mainly enriched in multicellular organism development, detection of stimulus, diseases of signal transduction by growth factor receptors and second messengers, and olfactory signaling pathway. The top hub genes such as MYC, EGFR, LNX1, YBX1, HSP90AA1, ESR1, FN1, TK1, ANLN and SMAD9 were screened out as the critical genes among the DEGs from the PPI network, modules, miRNA-hub gene regulatory network and TF-hub gene regulatory network. Receiver operating characteristic curve (ROC) analysis confirmed that these genes were significantly associated with T1DM. In conclusion, the identified DEGs, particularly the hub genes, strengthen the understanding of the advancement and progression of T1DM, and certain genes might be used as candidate target molecules to diagnose, monitor and treat T1DM.

Genetic pleiotropy between pulmonary function and age-related traits: The Long Life Family Study

BACKGROUND

Pulmonary function (PF) progressively declines with aging. Forced expiratory volume in the first second (FEV1) and forced vital capacity (FVC) are predictors of morbidity of pulmonary and cardiovascular diseases and all-cause mortality. In addition, reduced PF is associated with elevated chronic low-grade systemic inflammation, glucose metabolism, body fatness, and low muscle strength. It may suggest pleiotropic genetic effects between PF with these age-related factors.

METHODS

We evaluated whether FEV1 and FVC share common pleiotropic genetic effects factors with interleukin-6, high-sensitivity C-reactive protein, body mass index, muscle (grip) strength, plasma glucose, and glycosylated hemoglobin in 3,888 individuals (age range: 26-106). We employed sex-combined and sex-specific correlated meta-analyses to test whether combining genome-wide association p-values from two or more traits enhances the ability to detect variants sharing effects on these correlated traits.

RESULTS

We identified 32 loci for PF, including 29 novel pleiotropic loci associated with pulmonary function and (i) body fatness (CYP2U1/SGMS2), (ii) glucose metabolism (CBWD1/DOCK8 and MMUT/CENPQ), (iii) inflammatory markers (GLRA3/HPGD, TRIM9, CALN1, CTNNB1/ZNF621, GATA5/SLCO4A1/NTSR1, and NPVF/C7orf31/CYCS), and (iv) muscle strength (MAL2, AC008825.1/LINC02103, AL136418.1).

CONCLUSIONS

The identified genes/loci for PF and age-related traits suggest their underlying shared genetic effects, which can explain part of their phenotypic correlations. Integration of gene expression and genomic annotation data shows enrichment of our genetic variants in lung, blood, adipose, pancreas, and muscles, among others. Our findings highlight the critical roles of identified gene/locus in systemic inflammation, glucose metabolism, strength performance, PF, and pulmonary disease, which are involved in accelerated biological aging.

DNA methylation profile of liver of mice conceived by in vitro fertilization

Offspring generated by in vitro fertilization (IVF) are believed to be healthy but display a possible predisposition to chronic diseases, like hypertension and glucose intolerance. Since epigenetic changes are believed to underlie such phenotype, this study aimed at describing global DNA methylation changes in the liver of adult mice generated by natural mating (FB group) or by IVF. Embryos were generated by IVF or natural mating. At 30 weeks of age, mice were sacrificed. The liver was removed, and global DNA methylation was assessed using whole-genome bisulfite sequencing (WGBS). Genomic Regions for Enrichment Analysis Tool (GREAT) and G:Profilerβ were used to identify differentially methylated regions (DMRs) and for functional enrichment analysis. Overrepresented gene ontology terms were summarized with REVIGO, while canonical pathways (CPs) were identified with Ingenuity® Pathway Analysis. Overall, 2692 DMRs (4.91%) were different between the groups. The majority of DMRs (84.92%) were hypomethylated in the IVF group. Surprisingly, only 0.16% of CpG islands were differentially methylated and only a few DMRs were located on known gene promoters (n = 283) or enhancers (n = 190). Notably, the long-interspersed element (LINE), short-interspersed element (SINE), and long terminal repeat (LTR1) transposable elements showed reduced methylation (P < 0.05) in IVF livers. Cellular metabolic process, hepatic fibrosis, and insulin receptor signaling were some of the principal biological processes and CPs modified by IVF. In summary, IVF modifies the DNA methylation signature in the adult liver, resulting in hypomethylation of genes involved in metabolism and gene transcription regulation. These findings may shed light on the mechanisms underlying the developmental origin of health and disease.

Association of estrogen receptor gene variants (ESR1 and ESR2) with polycystic ovary syndrome in Tunisia

SNV (single nucleotide variation) in estrogen receptor (ESR1 and ESR2) genes are susceptibility markers for complex diseases, such as cancer, metabolic disorders and women infertility. We explored six widely used SNVs in ESR1 (rs2234693, rs9340799, rs3798577, rs3020314) and ESR2 (rs1256049, rs4986938) in polycystic ovary syndrome (PCOS) in women from Tunisia (n = 254) compared to controls (n = 170). Genotyping was performed by RFLP-PCR or real-time PCR and analyzed in GoldenHelix statistical package. Logistic regression revealed association of rs2234693, rs3798577 and rs3020314 (ESR1) and rs1256049 (ESR2), the association of rs2234693 (C/T) being the strongest with P < 4.81 × 10^-6, 2.88 × 10^-5 after Bonferroni correction, OR 0.31, 95%CI (0.18-0.53)). Correlations were found with LH, LH/FSH or hyperandrogenism and even more significant with metabolic syndrome (rs9340799) and hyperglycemia (rs3798577). Among 14 haplotypes reconstructed in ESR1gene, four haplotypes (H1 to H4) were associated with PCOS the strongest being that of H1 (P < 0.002) supported by Bonferroni (P < 0.033) and permutation tests (P < 4 x10^-4). In haplotype trend regression, concordant correlations were found with insulin resistance (P < 0.033) for H2 and with high blood pressure for H3 (P < 0.048). While these data revealed influential role on metabolic rather and hormonal features of PCOS, the association of rs2234693 was the strongest among all ethnic populations studied thus far giving a new insight on estrogen receptor gene variation in distant North African populations and their role in metabolic alteration of PCOS.

PORTABILITY OF GWAS RESULTS BETWEEN ETHNIC POPULATIONS: GENETIC MARKERS FOR POLYCYSTIC OVARY SYNDROME (PCOS) IN MEDITERRANEAN AREA

Genome Wide Association Studies (GWAS) are excellent opportunities to define culprit genes in complex disorders such as the polycystic ovary syndrome (PCOS). PCOS is a prevalent disorder characterized by anovulation, hyperandrogenism and polycystic ovaries, which benefitted from several GWASs in Asians and Europeans revealing more than 20 potential culprit genes near associated single nucleotide variations (SNV). Translation of these findings into the clinical practice raises difficulties since positive hits are surrogate SNVs linked with causative mutations by linkage disequilibrium (LD). Studies in Mediterranean populations (e.g. Southern Europe and North Africa) raise supplementary problems because of a different LD-pattern, which may disrupt the link with causative mutations. Our experience in MEDIGENE program between Tunisia and France enforces the necessity of genetic anthropology studies before translating GWAS data. Tunisians are a heterogeneous population with ancestral Berbers, European, Arab and Sub-Saharan African components while South Europeans display a high level of genetic diversity, partially explained by gene flow from North Africa. Human diversity studies require sampling from Middle East and North Africa (MENA) region that will help to understand genetic factors in complex diseases.