About: Harnessing publicly available genetic data to prioritize lipid modifying therapeutic targets for prevention of coronary heart disease based on dysglycemic risk

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Harnessing publicly available genetic data to prioritize lipid modifying therapeutic targets for prevention of coronary heart disease based on dysglycemic risk Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Harnessing publicly available genetic data to prioritize lipid modifying therapeutic targets for prevention of coronary heart disease based on dysglycemic risk
Creator	Holmes, Michael Paul, · Michael, · Asselbergs, W De Bakker, I Folkert, · Holmes, V Keating, Brendan Moore, Jason Palmer, Tom Swerdlow, Daniel Tragante, Vinicius
topic	covid:b81981d8c6365181b93e5b67e1b64752139b926b#this
Source	PMC
abstract	Therapeutic interventions that lower LDL-cholesterol effectively reduce the risk of coronary artery disease (CAD). However, statins, the most widely prescribed LDL-cholesterol lowering drugs, increase diabetes risk. We used genome-wide association study (GWAS) data in the public domain to investigate the relationship of LDL-C and diabetes and identify loci encoding potential drug targets for LDL-cholesterol modification without causing dysglycemia. We obtained summary-level GWAS data for LDL-C from GLGC, glycemic traits from MAGIC, diabetes from DIAGRAM and CAD from CARDIoGRAMplusC4D consortia. Mendelian randomization analyses identified a one standard deviation (SD) increase in LDL-C caused an increased risk of CAD (odds ratio [OR] 1.63 (95 % confidence interval [CI] 1.55, 1.71), which was not influenced by removing SNPs associated with diabetes. LDL-C/CAD-associated SNPs showed consistent effect directions (binomial P = 6.85 × 10(−5)). Conversely, a 1-SD increase in LDL-C was causally protective of diabetes (OR 0.86; 95 % CI 0.81, 0.91), however LDL-cholesterol/diabetes-associated SNPs did not show consistent effect directions (binomial P = 0.15). HMGCR, our positive control, associated with LDL-C, CAD and a glycemic composite (derived from GWAS meta-analysis of four glycemic traits and diabetes). In contrast, PCSK9, APOB, LPA, CETP, PLG, NPC1L1 and ALDH2 were identified as “druggable” loci that alter LDL-C and risk of CAD without displaying associations with dysglycemia. In conclusion, LDL-C increases the risk of CAD and the relationship is independent of any association of LDL-C with diabetes. Loci that encode targets of emerging LDL-C lowering drugs do not associate with dysglycemia, and this provides provisional evidence that new LDL-C lowering drugs (such as PCSK9 inhibitors) may not influence risk of diabetes. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00439-016-1647-9) contains supplementary material, which is available to authorized users.
has issue date	2016-03-05(xsd:dateTime)
bibo:doi	10.1007/s00439-016-1647-9
bibo:pmid	26946290
has license	no-cc
sha1sum (hex)	b81981d8c6365181b93e5b67e1b64752139b926b
schema:url	https://doi.org/10.1007/s00439-016-1647-9
resource representing a document's title	Harnessing publicly available genetic data to prioritize lipid modifying therapeutic targets for prevention of coronary heart disease based on dysglycemic risk
has PubMed Central identifier	PMC4835528
has PubMed identifier	26946290
schema:publication	Hum Genet
resource representing a document's body	covid:b81981d8c6365181b93e5b67e1b64752139b926b#body_text
is http://vocab.deri.ie/void#inDataset of	proxy:http/ns.inria.fr/covid19/b81981d8c6365181b93e5b67e1b64752139b926b
is schema:about of	named entity 'removing' named entity 'consistent' named entity 'risk' named entity 'diabetes' named entity 'composite' named entity 'SNPs' named entity 'lipid' named entity 'INCREASED RISK' named entity 'ARTICLE' named entity 'CAUSED' named entity 'GLYCEMIC' named entity 'CORONARY ARTERY DISEASE' named entity 'POSITIVE CONTROL' named entity 'LDL-C' named entity 'causing' named entity 'binomial' named entity 'directions' named entity 'loci' named entity 'LDL-C' named entity 'consortia' named entity 'potential' named entity 'caused' named entity 'risk' named entity 'SNPs' named entity 'diabetes' named entity 'LDL-C' named entity 'statins' named entity 'odds ratio' named entity 'standard deviation' named entity 'LDL-cholesterol' named entity 'Mendelian randomization' named entity 'drug targets' named entity 'CAD' named entity 'confidence interval' named entity 'therapeutic targets' named entity 'diabetes' named entity 'Cholesterol' named entity 'loci' named entity 'loci' named entity 'GWAS' named entity 'locus' named entity 'CAD' named entity 'causal mechanisms' named entity 'SNPs' named entity 'correlation' named entity 'loci' named entity 'SNPs' named entity 'T2D' named entity 'standard deviation' named entity 'SNPs' named entity 'LPA' named entity 'protein products' named entity 'CAD' named entity 'APOB' named entity 'CAD' named entity 'SNPs' named entity 'CAD' named entity 'fasting glucose' named entity 'lipid levels' named entity 'SNPs' named entity 'LDL-C' named entity 'loci' named entity 'fasting' named entity 'CAD' named entity 'LDL-C' named entity 'SNPs' named entity 'CAD' named entity 'SNPs'

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software