LOGIN TO YOUR ACCOUNT

Username
Password
Remember Me
Or use your Academic/Social account:

CREATE AN ACCOUNT

Or use your Academic/Social account:

Congratulations!

You have just completed your registration at OpenAire.

Before you can login to the site, you will need to activate your account. An e-mail will be sent to you with the proper instructions.

Important!

Please note that this site is currently undergoing Beta testing.
Any new content you create is not guaranteed to be present to the final version of the site upon release.

Thank you for your patience,
OpenAire Dev Team.

Close This Message

CREATE AN ACCOUNT

Name:
Username:
Password:
Verify Password:
E-mail:
Verify E-mail:
*All Fields Are Required.
Please Verify You Are Human:
fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
David Melzer; John R B Perry; Dena Hernandez; Anna-Maria Corsi; Kara Stevens; Ian Rafferty; Fulvio Lauretani; Anna Murray; J Raphael Gibbs; Giuseppe Paolisso; Sajjad Rafiq; Javier Simon-Sanchez; Hana Lango; Sonja Scholz; Michael N Weedon; Sampath Arepalli; Neil Rice; Nicole Washecka; Alison Hurst; Angela Britton; William Henley; Joyce van de Leemput; Rongling Li; Anne B Newman; Greg Tranah; Tamara Harris; Vijay Panicker; Colin Dayan; Amanda Bennett; Mark I McCarthy ... view all 37 authors View less authors (2008)
Publisher: Public Library of Science (PLoS)
Journal: PLoS Genetics
Languages: English
Types: Article
Subjects: Research Article, Cardiovascular Disorders, Quantitative Trait Loci, QH426-470, Genetics, Genetics and Genomics/Gene Expression, Genetics and Genomics/Genome Projects, Blood Proteins, Genetics and Genomics/Genetics of Disease, Polymorphism, Single Nucleotide, Gene Dosage, Transcription, Genetic, Female, Biochemistry/Transcription and Translation, Diabetes and Endocrinology, Genome, Human, Aged, Genetic Linkage, QH426, Genetics and Genomics/Functional Genomics, Genetic Variation, Middle Aged, Genetics and Genomics/Physiogenomics, Genotype, Biochemistry/Protein Chemistry, Genetics and Genomics/Complex Traits, Adult, Aged, 80 and over, Humans, Male, R1
There is considerable evidence that human genetic variation influences gene expression. Genome-wide studies have revealed that mRNA levels are associated with genetic variation in or close to the gene coding for those mRNA transcripts - cis effects, and elsewhere in the genome - trans effects. The role of genetic variation in determining protein levels has not been systematically assessed. Using a genome-wide association approach we show that common genetic variation influences levels of clinically relevant proteins in human serum and plasma. We evaluated the role of 496,032 polymorphisms on levels of 42 proteins measured in 1200 fasting individuals from the population based InCHIANTI study. Proteins included insulin, several interleukins, adipokines, chemokines, and liver function markers that are implicated in many common diseases including metabolic, inflammatory, and infectious conditions. We identified eight Cis effects, including variants in or near the IL6R (p = 1.8x10(-57)), CCL4L1 (p = 3.9x10(-21)), IL18 (p = 6.8x10(-13)), LPA (p = 4.4x10(-10)), GGT1 (p = 1.5x10(-7)), SHBG (p = 3.1x10(-7)), CRP (p = 6.4x10(-6)) and IL1RN (p = 7.3x10(-6)) genes, all associated with their respective protein products with effect sizes ranging from 0.19 to 0.69 standard deviations per allele. Mechanisms implicated include altered rates of cleavage of bound to unbound soluble receptor (IL6R), altered secretion rates of different sized proteins (LPA), variation in gene copy number (CCL4L1) and altered transcription (GGT1). We identified one novel trans effect that was an association between ABO blood group and tumour necrosis factor alpha (TNF-alpha) levels (p = 6.8x10(-40)), but this finding was not present when TNF-alpha was measured using a different assay , or in a second study, suggesting an assay-specific association. Our results show that protein levels share some of the features of the genetics of gene expression. These include the presence of strong genetic effects in cis locations. The identification of protein quantitative trait loci (pQTLs) may be a powerful complementary method of improving our understanding of disease pathways.

Share - Bookmark

Funded by projects

Cite this article