Codon-level information improves predictions of inter-residue contacts in proteins by correlated mutation analysis.

Elife. 2015;4:e08932

Authors: Jacob E, Unger R, Horovitz A

Abstract
Methods for analysing correlated mutations in proteins are becoming an increasingly powerful tool for predicting contacts within and between proteins. Nevertheless, limitations remain due to the requirement for large multiple sequence alignments (MSA) and the fact that, in general, only the relatively small number of top-ranking predictions are reliable. To date, methods for analysing correlated mutations have relied exclusively on amino acid MSAs as inputs. Here, we describe a new approach for analysing correlated mutations that is based on combined analysis of amino acid and codon MSAs. We show that a direct contact is more likely to be present when the correlation between the positions is strong at the amino acid level but weak at the codon level. The performance of different methods for analysing correlated mutations in predicting contacts is shown to be enhanced significantly when amino acid and codon data are combined.

PMID: 26371555 [PubMed - indexed for MEDLINE]

Advanced continuous cultivation methods for systems microbiology.

Microbiology. 2015 Sep;161(9):1707-19

Authors: Adamberg K, Valgepea K, Vilu R

Abstract
Increasing the throughput of systems biology-based experimental characterization of in silico-designed strains has great potential for accelerating the development of cell factories. For this, analysis of metabolism in the steady state is essential as only this enables the unequivocal definition of the physiological state of cells, which is needed for the complete description and in silico reconstruction of their phenotypes. In this review, we show that for a systems microbiology approach, high-resolution characterization of metabolism in the steady state--growth space analysis (GSA)--can be achieved by using advanced continuous cultivation methods termed changestats. In changestats, an environmental parameter is continuously changed at a constant rate within one experiment whilst maintaining cells in the physiological steady state similar to chemostats. This increases the resolution and throughput of GSA compared with chemostats, and, moreover, enables following of the dynamics of metabolism and detection of metabolic switch-points and optimal growth conditions. We also describe the concept, challenge and necessary criteria of the systematic analysis of steady-state metabolism. Finally, we propose that such systematic characterization of the steady-state growth space of cells using changestats has value not only for fundamental studies of metabolism, but also for systems biology-based metabolic engineering of cell factories.

PMID: 26220303 [PubMed - indexed for MEDLINE]

Analysis of the effect of sentiment analysis on extracting adverse drug reactions from tweets and forum posts.

J Biomed Inform. 2016 Jun 27;

Authors: Korkontzelos I, Nikfarjam A, Shardlow M, Sarker A, Ananiadou S, Gonzalez GH

Abstract
OBJECTIVE: The abundance of text available in social media and health related forums along with the rich expression of public opinion have recently attracted the interest of the public health community to use these sources for pharmacovigilance. Based on the intuition that patients post about Adverse Drug Reactions (ADRs) expressing negative sentiments, we investigate the effect of sentiment analysis features in locating ADR mentions.
METHODS: We enrich the feature space of a state-of-the-art ADR identification method with sentiment analysis features. Using a corpus of posts from the DailyStrength forum and tweets annotated for ADR and indication mentions, we evaluate the extent to which sentiment analysis features help in locating ADR mentions and distinguishing them from indication mentions.
RESULTS: Evaluation results show that sentiment analysis features marginally improve ADR identification in tweets and health related forum posts. Adding sentiment analysis features achieved a statistically significant F-measure increase from 72.14% to 73.22% in the Twitter part of an existing corpus using its original train/test split. Using stratified 10 × 10-fold cross-validation, statistically significant F-measure increases were shown in the DailyStrength part of the corpus, from 79.57% to 80.14%, and in the Twitter part of the corpus, from 66.91% to 69.16%. Moreover, sentiment analysis features are shown to reduce the number of ADRs being recognised as indications.
CONCLUSION: This study shows that adding sentiment analysis features can marginally improve the performance of even a state-of-the-art ADR identification method. This improvement can be of use to pharmacovigilance practice, due to the rapidly increasing popularity of social media and health forums.

PMID: 27363901 [PubMed - as supplied by publisher]

12 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

("orphan disease" OR "rare disease" OR "orphan diseases" OR "rare diseases")

These pubmed results were generated on 2016/07/01

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

12 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

"Cystic Fibrosis"

These pubmed results were generated on 2016/07/01

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Sex-differential heterologous (non-specific) effects of vaccines: an emerging public health issue that needs to be understood and exploited.

Expert Rev Vaccines. 2016 Jun 30;:1-9

Authors: Flanagan KL, Plebanski M

Abstract
INTRODUCTION: Vaccines have heterologous effects on the immune system, leading to altered susceptibility to a range of pathogens, and possibly allergy and autoimmunity. Effects are often sex-differential. This review discusses the evidence, mechanisms and public health implications of the non-specific effects of vaccines (NSEs).
AREAS COVERED: This article firstly discusses the World Health Organization systematic review of the evidence for sex-differential heterologous effects of vaccines, and further PubMed indexed studies on NSEs on susceptibility to infectious diseases, allergy, autoimmunity and malignancy in animals and humans. Potential immunological mechanisms are evaluated, including sex-differential effects. Finally it describes how advances in systems biology might be applied to study such effects. Expert commentary: This section points out the need to understand immune mechanisms in order to exploit beneficial vaccine effects, and diminish deleterious ones. It suggests analysis of vaccine effects by sex is important, and discusses the future for personalised vaccines that take these effects into account.

PMID: 27362915 [PubMed - as supplied by publisher]

Recon 2.2: from reconstruction to model of human metabolism.

Metabolomics. 2016;12:109

Authors: Swainston N, Smallbone K, Hefzi H, Dobson PD, Brewer J, Hanscho M, Zielinski DC, Ang KS, Gardiner NJ, Gutierrez JM, Kyriakopoulos S, Lakshmanan M, Li S, Liu JK, Martínez VS, Orellana CA, Quek LE, Thomas A, Zanghellini J, Borth N, Lee DY, Nielsen LK, Kell DB, Lewis NE, Mendes P

Abstract
INTRODUCTION: The human genome-scale metabolic reconstruction details all known metabolic reactions occurring in humans, and thereby holds substantial promise for studying complex diseases and phenotypes. Capturing the whole human metabolic reconstruction is an on-going task and since the last community effort generated a consensus reconstruction, several updates have been developed.
OBJECTIVES: We report a new consensus version, Recon 2.2, which integrates various alternative versions with significant additional updates. In addition to re-establishing a consensus reconstruction, further key objectives included providing more comprehensive annotation of metabolites and genes, ensuring full mass and charge balance in all reactions, and developing a model that correctly predicts ATP production on a range of carbon sources.
METHODS: Recon 2.2 has been developed through a combination of manual curation and automated error checking. Specific and significant manual updates include a respecification of fatty acid metabolism, oxidative phosphorylation and a coupling of the electron transport chain to ATP synthase activity. All metabolites have definitive chemical formulae and charges specified, and these are used to ensure full mass and charge reaction balancing through an automated linear programming approach. Additionally, improved integration with transcriptomics and proteomics data has been facilitated with the updated curation of relationships between genes, proteins and reactions.
RESULTS: Recon 2.2 now represents the most predictive model of human metabolism to date as demonstrated here. Extensive manual curation has increased the reconstruction size to 5324 metabolites, 7785 reactions and 1675 associated genes, which now are mapped to a single standard. The focus upon mass and charge balancing of all reactions, along with better representation of energy generation, has produced a flux model that correctly predicts ATP yield on different carbon sources.
CONCLUSION: Through these updates we have achieved the most complete and best annotated consensus human metabolic reconstruction available, thereby increasing the ability of this resource to provide novel insights into normal and disease states in human. The model is freely available from the Biomodels database (http://identifiers.org/biomodels.db/MODEL1603150001).

PMID: 27358602 [PubMed - as supplied by publisher]

Mapping transcription factor interactome networks using HaloTag protein arrays.

Proc Natl Acad Sci U S A. 2016 Jun 29;

Authors: Yazaki J, Galli M, Kim AY, Nito K, Aleman F, Chang KN, Carvunis AR, Quan R, Nguyen H, Song L, Alvarez JM, Huang SC, Chen H, Ramachandran N, Altmann S, Gutiérrez RA, Hill DE, Schroeder JI, Chory J, LaBaer J, Vidal M, Braun P, Ecker JR

Abstract
Protein microarrays enable investigation of diverse biochemical properties for thousands of proteins in a single experiment, an unparalleled capacity. Using a high-density system called HaloTag nucleic acid programmable protein array (HaloTag-NAPPA), we created high-density protein arrays comprising 12,000 Arabidopsis ORFs. We used these arrays to query protein-protein interactions for a set of 38 transcription factors and transcriptional regulators (TFs) that function in diverse plant hormone regulatory pathways. The resulting transcription factor interactome network, TF-NAPPA, contains thousands of novel interactions. Validation in a benchmarked in vitro pull-down assay revealed that a random subset of TF-NAPPA validated at the same rate of 64% as a positive reference set of literature-curated interactions. Moreover, using a bimolecular fluorescence complementation (BiFC) assay, we confirmed in planta several interactions of biological interest and determined the interaction localizations for seven pairs. The application of HaloTag-NAPPA technology to plant hormone signaling pathways allowed the identification of many novel transcription factor-protein interactions and led to the development of a proteome-wide plant hormone TF interactome network.

PMID: 27357687 [PubMed - as supplied by publisher]

Quantitative deep-mapping of the cultured podocyte proteome uncovers shifts in proteostatic mechanisms during differentiation.

Am J Physiol Cell Physiol. 2016 Jun 29;:ajpcell.00121.2016

Authors: Rinschen MM, Schroeter CB, Koehler S, Ising C, Schermer B, Kann M, Benzing T, Brinkkoetter PT

Abstract
The renal filtration barrier is maintained by the renal podocyte, an epithelial postmitotic cell. Immortalized mouse podocyte cell lines - both in the differentiated and undifferentiated state - are widely utilized tools to estimate podocyte injury and cytoskeletal rearrangement processes in vitro. Here, we mapped the cultured podocyte proteome at a depth of more than 8800 proteins and quantified 7240 proteins. Copy numbers of proteins mutated in forms of hereditary nephrotic syndrome or focal segmental glomerulosclerosis (FSGS) were assessed. We found that cultured podocytes express abundant copy numbers of endogenous receptors such as tyrosine kinase membrane receptors, the G-protein coupled receptor (GPCR), NPR3 (ANP receptor) and several poorly characterized GPCRs. The dataset was correlated with deep mapping mRNA sequencing ("mRNAseq") data from the native mouse podocyte, the native mouse podocyte proteome and staining intensities from the human protein atlas. The generated dataset was similar to these previously published resources, but several native and high-abundant podocyte-specific proteins were not identified in the dataset. Notably, this dataset detected general perturbations in proteostatic mechanisms as a dominant alteration during podocyte differentiation, with high proteasome activity in the undifferentiated state and markedly increased expression of lysosomal proteins in the differentiated state. Phosphoproteomics analysis of mouse podocytes at a resolution of more than 3000 sites suggested a preference of phosphorylation of actin-filament associated proteins in the differentiated state. The dataset obtained here provides a resource and provides the means for deep mapping of the native podocyte proteome and phosphoproteome in a similar manner.

PMID: 27357545 [PubMed - as supplied by publisher]

Unified pre- and postsynaptic long-term plasticity enables reliable and flexible learning.

Elife. 2015;4

Authors: Costa RP, Froemke RC, Sjöström PJ, van Rossum MC

Abstract
Although it is well known that long-term synaptic plasticity can be expressed both pre- and postsynaptically, the functional consequences of this arrangement have remained elusive. We show that spike-timing-dependent plasticity with both pre- and postsynaptic expression develops receptive fields with reduced variability and improved discriminability compared to postsynaptic plasticity alone. These long-term modifications in receptive field statistics match recent sensory perception experiments. Moreover, learning with this form of plasticity leaves a hidden postsynaptic memory trace that enables fast relearning of previously stored information, providing a cellular substrate for memory savings. Our results reveal essential roles for presynaptic plasticity that are missed when only postsynaptic expression of long-term plasticity is considered, and suggest an experience-dependent distribution of pre- and postsynaptic strength changes.

PMID: 26308579 [PubMed - indexed for MEDLINE]

Systems Biology Approaches to a Rational Drug Discovery Paradigm.

Curr Top Med Chem. 2016;16(9):1009-25

Authors: Prathipati P, Mizuguchi K

Abstract
Ligand- and structure-based drug design approaches complement phenotypic and target screens, respectively, and are the two major frameworks for guiding early-stage drug discovery efforts. Since the beginning of this century, the advent of the genomic era has presented researchers with a myriad of high throughput biological data (parts lists and their interaction networks) to address efficacy and toxicity, augmenting the traditional ligand- and structure-based approaches. This data rich era has also presented us with challenges related to integrating and analyzing these multi-platform and multi-dimensional datasets and translating them into viable hypotheses. Hence in the present paper, we review these existing approaches to drug discovery research and argue the case for a new systems biology based approach. We present the basic principles and the foundational arguments/underlying assumptions of the systems biology based approaches to drug design. Also discussed are systems biology data types (key entities, their attributes and their relationships with each other, and data models/representations), software and tools used for both retrospective and prospective analysis, and the hypotheses that can be inferred. In addition, we summarize some of the existing resources for a systems biology based drug discovery paradigm (open TG-GATEs, DrugMatrix, CMap and LINCs) in terms of their strengths and limitations.

PMID: 26306988 [PubMed - indexed for MEDLINE]

The Next Generation of Dietitians: Implementing Dietetics Education and Practice in Integrative Medicine.

J Am Coll Nutr. 2015;34(5):430-5

Authors: Wagner LE, Evans RG, Noland D, Barkley R, Sullivan DK, Drisko J

Abstract
Integrative medicine is a quickly expanding field of health care that emphasizes nutrition as a key component. Dietitians and nutritionists have an opportunity to meet workforce demands by practicing dietetics and integrative medicine (DIM). The purpose of this article is to describe a DIM education program and practicum. We report the results of an interprofessional nutrition education and practicum program between the University of Kansas Medical Center (KUMC) Department of Dietetics and Nutrition and KU Integrative Medicine. This partnered program provides training that builds on the strong foundation of the Nutrition Care Process and adds graduate-level educational and practicum experiences in foundational integrative medicine knowledge, including nutritional approaches from a systems biology perspective, nutrigenomics, and biochemistry as the core knowledge to understand the root cause of a chronic disorder and to choose appropriate nutritional tools for interventions. This interprofessional KUMC program provides a dietetic internship, master's degree, and graduate certificate in DIM and fulfills a need for dietitians and nutritionists who seek careers practicing in an integrative medicine setting. The program fulfills expanding workforce needs to provide quality health care for patients with chronic illnesses.

PMID: 25961884 [PubMed - indexed for MEDLINE]

DEVELOPMENT OF AN ANNOTATION SCHEME FOR STANDARDIZED DESCRIPTION OF MATHEMATICAL MODELS IN THE FIELD OF PLANT PROTECTION.

Commun Agric Appl Biol Sci. 2015;80(3):579-82

Authors: Günther T, Büttner C, Käsbohrer A, Filter M

Abstract
Mathematical models on properties and behavior of harmful organisms in the food chain are an increas- ingly relevant approach of the agriculture and food industry. As a consequence, there are many efforts to develop biological models in science, economics and risk assessment nowadays. However, there is a lack of international harmonized standards on model annotation and model formats, which would be neces- sary to set up efficient tools supporting broad model application and information exchange. There are some established standards in the field of systems biology, but there is currently no corresponding provi- sion in the area of plant protection. This work therefore aimed at the development of an annotation scheme using domain-specific metadata. The proposed scheme has been validated in a prototype implementation of a web-database model repository. This prototypic community resource currently contains models on aflatoxin secreting fungal Aspergillus flavus in maize, as these models have a high relevance to food safety and economic impact. Specifically, models describing biological processes of the fungus (growth, Aflatoxin secreting), as well as dose-response- and carry over models were included. Furthermore, phenological models for maize were integrated as well. The developed annotation scheme is based on the well-established data exchange format SBML, which is broadly applied in the field of systems biology. The identified example models were annotated according to the developed scheme and entered into a Web-table (Google Sheets), which was transferred to a web based demonstrator available at https://sites.google.com/site/test782726372685/. By implementation of a software demonstrator it became clear that the proposed annotation scheme can be applied to models on plant pathogens and that broad adoption within the domain could promote communication and application of mathematical models.

PMID: 27141756 [PubMed - indexed for MEDLINE]

Ron receptor-dependent gene regulation of Kupffer cells during endotoxemia.

Hepatobiliary Pancreat Dis Int. 2014 Jun;13(3):281-92

Authors: Kulkarni RM, Stuart WD, Waltz SE

Abstract
BACKGROUND: Ron receptor tyrosine kinase signaling in macrophages, including Kupffer cells and alveolar macrophages, suppresses endotoxin-induced proinflammatory cytokine/chemokine production. Further, we have also identified genes from Ron replete and Ron deplete livers that were differentially expressed during the progression of liver inflammation associated with acute liver failure in mice by microarray analyses. While important genes and signaling pathways have been identified downstream of Ron signaling during progression of inflammation by this approach, the precise role that Ron receptor plays in regulating the transcriptional landscape in macrophages, and particular in isolated Kupffer cells, has still not been investigated.
METHODS: Kupffer cells were isolated from wild-type (TK+/+) and Ron tyrosine kinase deficient (TK-/-) mice. Ex vivo, the cells were treated with lipopolysaccharide (LPS) in the presence or absence of the Ron ligand, hepatocyte growth factor-like protein (HGFL). Microarray and qRT-PCR analyses were utilized to identify alterations in gene expression between genotypes.
RESULTS: Microarray analyses identified genes expressed differentially in TK+/+ and TK-/- Kupffer cells basally as well as after HGFL and LPS treatment. Interestingly, our studies identified Mefv, a gene that codes for the anti-inflammatory protein pyrin, as an HGFL-stimulated Ron-dependent gene. Moreover, lipocalin 2, a proinflammatory gene, which is induced by LPS, was significantly suppressed by HGFL treatment. Microarray results were validated by qRT-PCR studies on Kupffer cells treated with LPS and HGFL.
CONCLUSION: The studies herein suggest a novel mechanism whereby HGFL-induced Ron receptor activation promotes the expression of anti-inflammatory genes while inhibiting genes involved in inflammation with a net effect of diminished inflammation in macrophages.

PMID: 24919612 [PubMed - indexed for MEDLINE]

Advocating for the Use of Pharmacogenomics: One Nurse's Story.

J Psychosoc Nurs Ment Health Serv. 2016 Jul 1;54(7):38-42

Authors: Pestka EL, Shea CE

Abstract
The current article describes the experiences of a motivated nurse who gained an understanding of pharmacogenomics and advocated for the use cytochrome P450 testing for patients in her clinical practice, her family members, herself, and for changing the health care delivery system to more readily recognize and address drug-metabolizing-enzyme abnormalities. Recommendations for nurses interested in promoting the use of pharmacogenomics include learning as much as possible about testing and implications, networking with other providers, identifying a knowledgeable pharmacist, assessing for a family history of problems with medication side effects or lack of efficacy, and keeping records of relevant medical and medication information to share with providers. [Journal of Psychosocial Nursing and Mental Health Services, 54(7), 38-42.].

PMID: 27362384 [PubMed - as supplied by publisher]

Hotspot mutations delineating diverse mutational signatures and biological utilities across cancer types.

BMC Genomics. 2016;17 Suppl 2:394

Authors: Chen T, Wang Z, Zhou W, Chong Z, Meric-Bernstam F, Mills GB, Chen K

Abstract
BACKGROUND: An important step towards personalizing cancer treatment is to integrate heterogeneous evidences to catalog mutational hotspots that are biologically and therapeutically relevant and thus represent where targeted therapy would likely be beneficial. However, existing methods do not sufficiently delineate varying functionality of individual mutations within the same genes.
RESULTS: We observed a large discordancy of mutation rates across different mutation subtypes and tumor types, and nominated 702 hotspot mutations in 549 genes in the Catalog of Somatic Mutations in Cancer (COSMIC) by considering context specific mutation characteristics such as genes, cancer types, mutation rates, mutation subtypes and sequence contexts. We observed that hotspot mutations were highly prevalent in Non CpG-island C/G transition and transversion sequence contexts in 10 tumor types, and specific insertion hotspot mutations were enriched in breast cancer and deletion hotspot mutations in colorectal cancer. We found that the hotspot mutations nominated by our approach were significantly more conserved than non-hotspot mutations in the corresponding cancer genes. We also examined the biological significance and pharmacogenomics properties of these hotspot mutations using data in the Cancer Genome Atlas (TCGA) and the Cancer Cell-Line Encyclopedia (CCLE), and found that 53 hotspot mutations are independently associated with diverse functional evidences in 1) mRNA and protein expression, 2) pathway activity, or 3) drug sensitivity and 82 were highly enriched in specific tumor types. We highlighted the distinct functional indications of hotspot mutations under different contexts and nominated novel hotspot mutations such as MAP3K4 A1199 deletion, NR1H2 Q175 insertion, and GATA3 P409 insertion as potential biomarkers or drug targets.
CONCLUSION: We identified a set of hotspot mutations across 17 tumor types by considering the background mutation rate variations among genes, tumor subtypes, mutation subtypes, and sequence contexts. We illustrated the common and distinct mutational signatures of hotspot mutations among different tumor types and investigated their variable functional relevance under different contexts, which could potentially serve as a resource for explicitly selecting targets for diagnosis, drug development, and patient management.

PMID: 27356755 [PubMed - in process]

11 new pubmed citations were retrieved for your search. Click on the search hyperlink below to display the complete search results:

("orphan disease" OR "rare disease" OR "orphan diseases" OR "rare diseases")

These pubmed results were generated on 2016/06/30

PubMed comprises more than 24 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full-text content from PubMed Central and publisher web sites.

Drug repurposing for chronic myeloid leukemia: in silico and in vitro investigation of DrugBank database for allosteric Bcr-Abl inhibitors.

J Biomol Struct Dyn. 2016 Jun 29;:1-16

Authors: Singh VK, Chang HH, Kuo CC, Shiao HY, Hsieh HP, Coumar MS

Abstract
Chronic myeloid leukemia (CML) is caused by chromosomal rearrangement resulting in the expression of Bcr-Abl fusion protein with deregulated Abl tyrosine kinase activity. Approved drugs - imatinib, dasatinib, nilotinib, and ponatinib - target the ATP-binding site of Abl kinase. Even though these drugs are initially effective, long-term usefulness is limited by the development of resistance. To overcome this problem, targeting the allosteric site of Abl kinase, which is remote from the ATP-binding site is found to be a useful strategy. In this study, structure-based and ligand-based virtual screening methods were applied to narrow down possible drugs (from DrugBank database) that could target the allosteric site of Abl kinase. Detailed investigations of the selected drugs in the allosteric site of Abl kinase, using molecular dynamics and steered molecular dynamics simulation shows that gefitinib, an EGFR inhibitor approved for the treatment of lung cancer, could bind effectively to the allosteric site of Bcr-Abl. More interestingly, gefitinib was found to enhance the ability of imatinib to bind at the ATP-binding site of Bcr-Abl kinase. Based on the in silico findings, gefitinib was tested in combination with imatinib in K562 CML cell line using MTT cell proliferation assay and found to have a synergistic antiproliferative activity. Further detailed mechanistic study could help to unravel the full potential of imatinib - gefitinib combination for the treatment of CML.

PMID: 27353341 [PubMed - as supplied by publisher]

Pharmacogenomics for infectious diseases in sub-Saharan Africa: Successes and opportunities.

Appl Transl Genom. 2016 Jun;9:3-5

Authors: Chaudhry M, Alessandrini M, Pepper MS

PMID: 27354934 [PubMed]

Proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors: Present perspectives and future horizons.

Nutr Metab Cardiovasc Dis. 2016 May 30;

Authors: Yadav K, Sharma M, Ferdinand KC

Abstract
AIMS: Our comprehensive review highlights the drug development and pharmacogenomics leading to the recent approval of PCSK9 inhibitors. We also review the anticipated future advances into the uses of PCSK9 inhibition.
BACKGROUND: Despite the present advances in pharmacotherapy, atherosclerotic cardiovascular disease (ASCVD) remains the leading cause of mortality worldwide. Low density lipoprotein-cholesterol (LDL-C) lowering is the primary target for ASCVD risk reduction, showing demonstrable benefits in mortality. However, 70% of events occur even in the presence of statins. This residual risk may be approached with additional LDL-C reduction. Statin intolerance is a common clinical concern affecting adherence and the benefit with statins. There is also significant variation of individual lipid-lowering. Following rapid development, proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors have progressed from genetic observations, to mechanistic studies, to closer realization of the goal of CVD risk reduction. This review discusses the science behind PCSK9 inhibition, evidence of trials involving efficacy and safety, and reflections of its present and future role in clinical care, especially in high-risk patients with ASCVD, persons with suboptimal responses to statins and familial hyperlipidemia. Monoclonal antibodies have demonstrated LDL-C lowering of up to 57% as monotherapy and up to 73% when added to statins. Statins have limited efficacy in reduction of LDL-C due to an increased number of LDL-receptors. Elevated lipoprotein (a) levels may also be significantly lowered by PCSK9i. The journey from discovery to PSCK9 target validation took less than five years, and development and approval of therapeutic modalities for PCSK9 inhibitors happened over the next seven. This review highlights the drug development and pharmacogenomics leading to the recent approval of two agents, alirocumab and evolocumab, with a third bococizumab, and other novel approaches to the pathway pending.
DATA SYNTHESIS: We searched MEDLINE database via Pubmed for reviews, research publications and relevant trials available on PCSK9 inhibition.
CONCLUSION: Despite decades of medical advances, ASCVD remains one of the major causes of morbidity and mortality worldwide. Statin use has multiplied since the validation of LDL hypothesis, however, it is undeniable a more effective and well-tolerated agent is needed in significant number or patients. With the arrival of the era of unprecedented CV protection with PCSK9 inhibition, this exciting new therapy holds a pivotal promise as the future of lipid management. The data available already indicate safety, tolerability and superb efficacy of these agents, which are already changing contemporary cholesterol management. The rapid translation of innovative basic science research into drug development may lead to CV outcomes reduction and confirm that this pathway will become prominently utilized.

PMID: 27352986 [PubMed - as supplied by publisher]