Proteomics in cardiovascular disease: recent progress and clinical implication and implementation

Introduction: Although multiple efforts have been initiated to shed light into the molecular mechanisms underlying cardiovascular disease, it still remains one of the major causes of death worldwide. Proteomic approaches are unequivocally powerful tools that may provide deeper understanding into the molecular mechanisms associated with cardiovascular disease and improve its management.

Areas covered: Cardiovascular proteomics is an emerging field and significant progress has been made during the past few years with the aim of defining novel candidate biomarkers and obtaining insight into molecular pathophysiology. To summarize the recent progress in the field, a literature search was conducted in PubMed and Web of Science. As a result, 704 studies from PubMed and 320 studies from Web of Science were retrieved. Findings from original research articles using proteomics technologies for the discovery of biomarkers for cardiovascular disease in human are summarized in this review.

Expert commentary: Proteins associated with cardiovascular disease represent pathways in inflammation, wound healing and coagulation, proteolysis and extracellular matrix organization, handling of cholesterol and LDL. Future research in the field should target to increase proteome coverage as well as integrate proteomics with other omics data to facilitate both drug development as well as clinical implementation of findings.     

Molecular Data and the Dynamic Nature of Polyploidy

During the past decade, molecular techniques have provided a wealth of data that have facilitated the resolution of several controversial questions in polyploid evolution. Herein we have focused on several of these issues: (1) the frequency of recurrent formation of polyploid species; (2) the genetic consequences of multiple polyploidizations within a species; (3) the prevalence and genetic attributes of autopolyploids; and (4) the genetic changes that occur in polyploid genomes following their formation.

Molecular data provide a more dynamic picture of polyploid evolution than has been traditionally espoused. Numerous studies have demonstrated multiple origins of both allopolyploids and autopolyploids. In several polyploid species studied in detail, multiple origins were found to be frequent on a local geographic scale, as well as during a short span of time. Molecular data strongly suggest that recurrent formation of polyploid species is the rule, rather than the exception. In addition, molecular data indicate that recurrent formation of polyploids has important genetic consequences, introducing considerable genetic variation from diploid progenitors into polyploid derivatives.

Molecular data also suggest a much more important role for natural autopolyploids than has been historically envisioned. In contrast to the longstanding view of autopolyploidy as being rare, molecular data continue to reveal steadily increasing numbers of well-documented autoploids having tetrasomic or higher-level polysomic inheritance. Although autopolyploidy undoubtedly occurs much less frequently than allopolyploidy in natural populations, it nonetheless has been a significant evolutionary mechanism. Molecular data also provide compelling genetic evidence that contradicts the traditional view of autopolyploidy as being maladaptive. Electrophoretic studies have revealed three important attributes of autopolyploids compared to their diploid progenitors: (1) enzyme multiplicity, (2) increased heterozygosity, and (3) increased allelic diversity. Genetic variability is, in fact, typically substantially higher in autopoloids than in their diploid progenitors. These genetic attributes of autopolyploids are due to polysomic inheritance and provide strong genetic arguments for the potential success of autopolyploids in nature.

In addition to providing numerous important insights into the formation of polyploids and the immediate genetic consequences of polyploidy, molecular data also have been used to study the subsequent evolution of polyploid genomes. Common hypotheses on the subsequent evolution of polyploid genomes include (1) gene silencing, eventually leading to extensively diploidized polyploid genomes; (2) gene diversification, resulting in regulatory or functional divergence of duplicate genes; and (3) genome diversification, resulting in chromosomal repatterning. Compelling, but limited, genetic evidence for all of these factors has been obtained in molecular analyses of polyploid species. The occurrence of these processes in polyploid genomes indicates that polyploid genomes are plastic and susceptible to evolutionary change.

In summary, molecular data continue to demonstrate that polyploidization and the subsequent evolution of polyploid genomes are very dynamic processes.     

Circulating microRNAs in human obesity: a systematic review

Context: Differential expression profiles of microRNAs have been reported in human obesity suggesting a miRNAs role in the development of obesity and associated disorders.

Objective: To review circulating microRNAs (c-miRNAs) dysregulated in human obesity and to predict their possible target genes.

Methods: We performed a systematic review on PubMed database (PROSPERO, CRD42017077742) for original works on c-miRNAs and human obesity and recorded c-miRNAs with differential expression profiles. Potential target genes and metabolic pathways for dysregulated miRNAs with at least two independent reports were searched using bioinformatic tools.

Results: Twenty-two c-miRNAs are overexpressed, nine underexpressed and two c-miRNAs dysregulated in both directions in people with obesity compared to lean controls. Bioinformatic analyses suggest these c-miRNAs target on genes associated with fatty acid metabolism and PI3k/Akt pathway.

Conclusion: Literature records 33 c-miRNAs confirmedly dysregulated in human obesity. Their predicted target genes are involved in pathways that could explain the development of obesity and its comorbidities. Further research will clarify the role of these miRNAs on metabolic diseases and their usefulness for the prognosis, prevention and treatment of obesity.     

Identifying Relationships among Genomic Disease Regions: Predicting Genes at Pathogenic SNP Associations and Rare Deletions

Translating a set of disease regions into insight about pathogenic mechanisms requires not only the ability to identify the key disease genes within them, but also the biological relationships among those key genes. Here we describe a statistical method, Gene Relationships Among Implicated Loci (GRAIL), that takes a list of disease regions and automatically assesses the degree of relatedness of implicated genes using 250,000 PubMed abstracts. We first evaluated GRAIL by assessing its ability to identify subsets of highly related genes in common pathways from validated lipid and height SNP associations from recent genome-wide studies. We then tested GRAIL, by assessing its ability to separate true disease regions from many false positive disease regions in two separate practical applications in human genetics. First, we took 74 nominally associated Crohn''s disease SNPs and applied GRAIL to identify a subset of 13 SNPs with highly related genes. Of these, ten convincingly validated in follow-up genotyping; genotyping results for the remaining three were inconclusive. Next, we applied GRAIL to 165 rare deletion events seen in schizophrenia cases (less than one-third of which are contributing to disease risk). We demonstrate that GRAIL is able to identify a subset of 16 deletions containing highly related genes; many of these genes are expressed in the central nervous system and play a role in neuronal synapses. GRAIL offers a statistically robust approach to identifying functionally related genes from across multiple disease regions—that likely represent key disease pathways. An online version of this method is available for public use (http://www.broad.mit.edu/mpg/grail/).     

Mutation in the beta3 subunit of Guanine nucleotide-binding protein (GNB3) gene is not associated with Type II diabetes mellitus risk: a case–control study of a North Indian population

Context: Genetics play a major role in development and pathophysiology of Type 2 diabetes mellitus (T2DM).

Objective: To asses the association of Guanine nucleotide-binding protein (GNB3) (C825T) gene's polymorphism with T2DM.

Materials and methods: A case–control study including 400 North Indians was performed using Polymerase Chain Reaction–Restriction Fragment Length Polymorphism (PCR-RFLP) approach to analyze genetic polymorphism.

Results: No significant difference was observed in genotype and allele frequencies of GNB3 gene on comparing cases with controls.

Discussion: Our study is in agreement with studies on Polish, Japanese, Hispanic-American and Danish populations who observed no significant association between GNB3 (C825T) polymorphism and T2DM.

Conclusion: GNB3 (C825T) polymorphism is not associated with T2DM.     

GapCoder automates the use of indel characters in phylogenetic analysis

Background

Several ways of incorporating indels into phylogenetic analysis have been suggested. Simple indel coding has two strengths: (1) biological realism and (2) efficiency of analysis. In the method, each indel with different start and/or end positions is considered to be a separate character. The presence/absence of these indel characters is then added to the data set.

Algorithm

We have written a program, GapCoder to automate this procedure. The program can input PIR format aligned datasets, find the indels and add the indel-based characters. The output is a NEXUS format file, which includes a table showing what region each indel characters is based on. If regions are excluded from analysis, this table makes it easy to identify the corresponding indel characters for exclusion.

Discussion

Manual implementation of the simple indel coding method can be very time-consuming, especially in data sets where indels are numerous and/or overlapping. GapCoder automates this method and is therefore particularly useful during procedures where phylogenetic analyses need to be repeated many times, such as when different alignments are being explored or when various taxon or character sets are being explored. GapCoder is currently available for Windows from http://www.home.duq.edu/~youngnd/GapCoder.

     

Fruit production along roads and footpaths in an Atlantic rain forest area

Background: Pathways (footpaths and roads) in forests are associated with edge effects, affecting forest structure and composition and associated wildlife. However, little is known about how edge effects along pathways may impact the dynamics of fruit production and their availability for frugivores.

Aim: We related pathway width as a proxy for edge effects to fruit production. Our underlying hypothesis was that pathway width would be positively related to fruit production.

Methods: We observed fruit production along three pathways of different widths – 2, 10 and 20 m wide – and in a control area of undisturbed forest in an Atlantic rain forest stand monthly over a 2-year period.

Results: The number of species and individuals-bearing fruit was higher along the wider pathways than along the narrowest pathway and in the control area. The amount of zoochorous fruits was higher in the control area than along pathways, and the widest pathway had higher non-zoochorous fruits production. Fruiting peaks occurred along pathways, while fruiting in the control area was aseasonal.

Conclusions: Pathway width is related to fruit type and its quantity and temporal availability. These effects extend towards the forest interior beyond 35 m. The presence of paths affects food resources for frugivores and thus can contribute to reconfiguring the spatio-temporal distribution of the fauna.     

Movements and landscape use of Eastern Imperial Eagles Aquila heliaca in Central Asia

Capsule: We describe ecological factors associated with movements of a globally declining raptor species, the Eastern Imperial Eagle Aquila heliaca.

Aims: To describe the movements, habitat associations and resource selection of Eastern Imperial Eagles marked in Central Asia.

Methods: We used global positioning system (GPS) data sent via satellite telemetry devices deployed on Eastern Imperial Eagles captured in Kazakhstan to calculate distances travelled and to associate habitat and weather variables with eagle locations collected throughout the annual cycle. We also used resource selection models to evaluate habitat use of tracked birds during autumn migration. Separately, we used wing-tagging recovery data to broaden our understanding of wintering locations of eagles.

Results: Eagles tagged in Kazakhstan wintered in most countries on the Arabian Peninsula, as well as Iran and India. The adult eagle we tracked travelled more efficiently than did the four pre-adults. During autumn migration, telemetered eagles used a mixture of vegetation types, but during winter and summer, they primarily used bare and sparsely vegetated areas. Finally, telemetered birds used orographic updrafts to subsidize their autumn migration flight, but they relied on thermal updrafts during spring migration.

Conclusion: Our study is the first to use GPS telemetry to describe year-round movements and habitat associations of Eastern Imperial Eagles in Central Asia. Our findings provide insight into the ecology of this vulnerable raptor species that can contribute to conservation efforts on its behalf.     

Proteomics for cancer drug design

Introduction: Signal transduction cascades drive cellular proliferation, apoptosis, immune, and survival pathways. Proteins have emerged as actionable drug targets because they are often dysregulated in cancer, due to underlying genetic mutations, or dysregulated signaling pathways. Cancer drug development relies on proteomic technologies to identify potential biomarkers, mechanisms-of-action, and to identify protein binding hot spots.

Areas covered: Brief summaries of proteomic technologies for drug discovery include mass spectrometry, reverse phase protein arrays, chemoproteomics, and fragment based screening. Protein-protein interface mapping is presented as a promising method for peptide therapeutic development. The topic of biosimilar therapeutics is presented as an opportunity to apply proteomic technologies to this new class of cancer drug.

Expert opinion: Proteomic technologies are indispensable for drug discovery. A suite of technologies including mass spectrometry, reverse phase protein arrays, and protein-protein interaction mapping provide complimentary information for drug development. These assays have matured into well controlled, robust technologies. Recent regulatory approval of biosimilar therapeutics provides another opportunity to decipher the molecular nuances of their unique mechanisms of action. The ability to identify previously hidden protein hot spots is expanding the gamut of potential drug targets. Proteomic profiling permits lead compound evaluation beyond the one drug, one target paradigm.     

Local sequence determinants of two in-frame triplet deletion/duplication hotspots in the RHD/RHCE genes

A genetic association study is a complicated process that involves collecting phenotypic data, generating genotypic data, analyzing associations between genotypic and phenotypic data, and interpreting genetic biomarkers identified. SNPTrack is an integrated bioinformatics system developed by the US Food and Drug Administration (FDA) to support the review and analysis of pharmacogenetics data resulting from FDA research or submitted by sponsors. The system integrates data management, analysis, and interpretation in a single platform for genetic association studies. Specifically, it stores genotyping data and single-nucleotide polymorphism (SNP) annotations along with study design data in an Oracle database. It also integrates popular genetic analysis tools, such as PLINK and Haploview. SNPTrack provides genetic analysis capabilities and captures analysis results in its database as SNP lists that can be cross-linked for biological interpretation to gene/protein annotations, Gene Ontology, and pathway analysis data. With SNPTrack, users can do the entire stream of bioinformatics jobs for genetic association studies. SNPTrack is freely available to the public at http://www.fda.gov/ScienceResearch/BioinformaticsTools/SNPTrack/default.htm.     

Advances in understanding the role of disease-associated proteins in spinal muscular atrophy

Introduction: Spinal muscular atrophy (SMA) is a neurodegenerative disorder characterized by alpha motor neuron loss in the spinal cord due to reduced survival motor neuron (SMN) protein level. While the genetic basis of SMA is well described, the specific molecular pathway underlying SMA is still not fully understood.

Areas covered: This review discusses the recent advancements in understanding the molecular pathways in SMA using different omics approaches and genetic modifiers identified in both vertebrate and invertebrate systems. The findings that are summarized in this article were deduced from original articles and reviews with a particular focus on the latest advancements in the field.

Expert commentary: The identification of genetic modifiers such as PLS3 and NCALD in humans or of SMA modulators such as Elavl4 (HuD), Copa, Uba1, Mapk10 (Jnk3), Nrxn2 and Tmem41b (Stasimon) in various SMA animal models improved our knowledge of impaired cellular pathways in SMA. Inspiration from modifier genes and their functions in motor neuron and neuromuscular junctions may open a new avenue for future SMA combinatorial therapies.     

Lipidomic analysis of epidermal lipids: a tool to predict progression of inflammatory skin disease in humans

Introduction: Lipidomics is the large-scale profiling and characterization of lipid species in a biological system using mass spectrometry. The skin barrier is mainly comprised of corneocytes and a lipid-enriched extracellular matrix. The major skin lipids are ceramides, cholesterol and free fatty acids (FFA). Lipid compositions are altered in inflammatory skin disorders with disrupted skin barrier such as atopic dermatitis (AD).

Areas covered: Here we discuss some of the recent applications of lipidomics in human skin biology and in inflammatory skin diseases such as AD, psoriasis and Netherton syndrome. We also review applications of lipidomics in human skin equivalent and in pre-clinical animal models of skin diseases to gain insight into the pathogenesis of the skin disease.

Expert commentary: Skin lipidomics analysis could be a fast, reliable and noninvasive tool to characterize the skin lipid profile and to monitor the progression of inflammatory skin diseases such as AD.     

Identification of two poorly prognosed ovarian carcinoma subtypes associated with CHEK2 germ-line mutation and non-CHEK2 somatic mutation gene signatures

High-grade serous ovarian cancer (HG-SOC), a major histologic type of epithelial ovarian cancer (EOC), is a poorly-characterized, heterogeneous and lethal disease where somatic mutations of TP53 are common and inherited loss-of-function mutations in BRCA1/2 predispose to cancer in 9.5–13% of EOC patients. However, the overall burden of disease due to either inherited or sporadic mutations is not known.

We performed bioinformatics analyses of mutational and clinical data of 334 HG-SOC tumor samples from The Cancer Genome Atlas to identify novel tumor-driving mutations, survival-significant patient subgroups and tumor subtypes potentially driven by either hereditary or sporadic factors.

We identified a sub-cluster of high-frequency mutations in 22 patients and 58 genes associated with DNA damage repair, apoptosis and cell cycle. Mutations of CHEK2, observed with the highest intensity, were associated with poor therapy response and overall survival (OS) of these patients (P = 8.00e-05), possibly due to detrimental effect of mutations at the nuclear localization signal. A 21-gene mutational prognostic signature significantly stratifies patients into relatively low or high-risk subgroups with 5-y OS of 37% or 6%, respectively (P = 7.31e-08). Further analysis of these genes and high-risk subgroup revealed 2 distinct classes of tumors characterized by either germline mutations of genes such as CHEK2, RPS6KA2 and MLL4, or somatic mutations of other genes in the signature.

Our results could provide improvement in prediction and clinical management of HG-SOC, facilitate our understanding of this complex disease, guide the design of targeted therapeutics and improve screening efforts to identify women at high-risk of hereditary ovarian cancers distinct from those associated with BRCA1/2 mutations.     

Cigarette smoking affects microRNAs and inflammatory biomarkers in healthy individuals and an association to single nucleotide polymorphisms is indicated

Background: Cigarette smoke induces inflammation and remodels immune response. Genetic and epigenetic alterations might be involved in the pathogenesis of smoking related diseases. In this study, we investigated the effect of smoking on systemic inflammation biomarkers and epigenetic changes at microRNA (miRNA) expression level. We also examined if the levels of inflammatory biomarkers were associated with selected single nucleotide polymorphisms (SNPs).

Method: From 39 smokers and 101 non-smokers, levels of total white blood cells (WBCs) and its subpopulations, plasma cytokines/chemokines/proteins and miRNAs were analysed. For three biomarkers, C-reactive protein (CRP), MCP-1 and IFN-γ that were affected by smoking, the influence of SNPs was analyzed.

Result: Elevated levels of total WBCs, neutrophils, monocytes, lymphocytes, CRP, MCP-1, IFN-γ and lower levels of miR-21 were detected in smokers. The elevated levels of IFN-γ in smokers was only statistically significantly associated with rs2069705 AG/GG SNP-genotype.

Conclusions: A lower level of oncomir miRNA-21 and a higher level of immune modelling cytokine IFN-γ detected in smokers could be a protective immune response to cigarette smoke. The higher level of IFN-γ in smokers with a specific SNP genotype also suggests that a genetic interaction with smoking might predict the pathobiology of smoking related disease.     

Using high-density DNA methylation arrays to profile copy number alterations

The integration of genomic and epigenomic data is an increasingly popular approach for studying the complex mechanisms driving cancer development. We have developed a method for evaluating both methylation and copy number from high-density DNA methylation arrays. Comparing copy number data from Infinium HumanMethylation450 BeadChips and SNP arrays, we demonstrate that Infinium arrays detect copy number alterations with the sensitivity of SNP platforms. These results show that high-density methylation arrays provide a robust and economic platform for detecting copy number and methylation changes in a single experiment. Our method is available in the ChAMP Bioconductor package: http://www.bioconductor.org/packages/2.13/bioc/html/ChAMP.html.     

Hydrogen peroxide- and nitric oxide-induced systemic antioxidant prime-like activity under NaCl-stress and stress-free conditions in citrus plants

We tested whether pre-treatments of roots with H₂O₂ (10 mM for 8 h) or sodium nitroprusside (SNP; 100 μM for 48 h), a donor of NO, could induce prime antioxidant defense responses in the leaves of citrus plants grown in the absence or presence of 150 mM NaCl for 16 d. Both root pre-treatments increased leaf superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX) and glutathione reductase (GR) activities, and induced related-isoform(s) expression under non-NaCl-stress conditions. When followed by salinity, certain enzymatic activities also exhibited an up-regulation in response to H₂O₂ or SNP pre-exposure. An NaCl-stress-provoked decrease in the ascorbate redox state was partially prevented by both pre-treatments, whereas the glutathione redox state under normal and NaCl-stress conditions was increased by SNP. Real-time imaging of NO production was found in vascular tissues and epidermal cells. Furthermore, NaCl-induced inhibition in OH scavenging activity and promotion of OH-mediated DNA strand cleavage was partially prevented by SNP. Moreover, NaCl-dependent protein oxidation (carbonylation) was totally reversed by both pre-treatments as revealed by quantitative assay and protein blotting analysis. These results provide strong evidence that H₂O₂ and NO elicit long-lasting systemic primer-like antioxidant activity in citrus plants under physiological and NaCl-stress conditions.     

Circulating liver-specific microRNAs as noninvasive diagnostic biomarkers of hepatic diseases in human

Context: Hepatitis is an endemic disease worldwide leading to chronic and debilitating cancers. The viral agents and hepatotoxic substances lead to damage of hepatocytes and release of damage associated molecules in circulation. The lack of timely and rapid diagnosis of hepatitis results in chronic disease.

Objective: The present review aimed to describe regulation, release and functions of microRNAs (miR) during human liver pathology and insights into their promising use as noninvasive biomarkers of hepatitis.

Methods: Comprehensive data were collected from PubMed, ScienceDirect and the Web of Science databases utilizing the keywords “biomarkers”, “microRNAs” and “hepatic diseases”.

Results: The miRs are readily released in the body fluids and blood during HBV/HCV associated hepatitis as well as metabolic, alcoholic, drug induced and autoimmune hepatitis. The liver-specific microRNAs including miR-122, miR-130, miR-183, miR-196, miR-209 and miR-96 are potential indicators of liver injury (mainly via apoptosis, necrosis and necroptosis) or hepatitis with their varied expression during acute/fulminant, chronic, liver fibrosis/cirrhosis and hepato-cellular carcinoma.

Conclusions: The liver-specific miRs can be used as rapid and noninvasive biomarkers of hepatitis to discern different stages of hepatitis. Blocking or stimulating pathways associated with miR regulation in liver could unveil novel therapeutic strategies in the management of liver diseases.

• Clinical significance

• Liver specific microRNAs interact with cellular proteins and signaling molecules to regulate the expression of various genes controlling biological processes.

• The circulatory level of liver specific microRNAs is indicator of severity of HBV and HCV infections as well as prognostic and therapeutic candidates.

• The expression of liver specific microRNAs is strongly associated with infectious, drug-induced, hepatotoxic, nonalcoholic steatohepatitis and nonalcoholic fatty liver diseases.