English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Improved prediction of complex diseases by common genetic markers: State of the art and further perspectives

Müller, B., Wilcke, A., Boulesteix, A.-L., Brauer, J., Passarge, E., Boltze, J., et al. (2016). Improved prediction of complex diseases by common genetic markers: State of the art and further perspectives. Human Genetics, 135(3), 259-272. doi:10.1007/s00439-016-1636-z.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-002B-1FD0-1 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-1EF0-D
Genre: Journal Article

Files

show Files
hide Files
:
Müller_Wilcke_2016.pdf (Publisher version), 771KB
Name:
Müller_Wilcke_2016.pdf
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Müller, Bent1, Author
Wilcke, Arndt1, 2, Author
Boulesteix, Anne-Laure3, Author
Brauer, Jens4, Author              
Passarge, Eberhard5, 6, Author
Boltze, Johannes1, 2, 7, 8, Author
Kirsten, Holger1, 2, 9, Author
Affiliations:
1Department of Cell Therapy, Fraunhofer Institute for Cell Therapy and Immunology, Leipzig, Germany, ou_persistent22              
2Translational Centre for Regenerative Medicine (TRM), University of Leipzig, Germany, ou_persistent22              
3Department of Medical Informatics, Biometry and Epidemiology, Ludwig Maximilians University Munich, Germany, ou_persistent22              
4Department Neuropsychology, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634551              
5Institute of Human Genetics, University of Leipzig, Germany, ou_persistent22              
6Institute of Human Genetics, University Hospital Essen, Germany, ou_persistent22              
7Stroke and Neurovascular Regulation Laboratory, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA, ou_persistent22              
8Fraunhofer Institute for Marine Biotechnology, Lübeck, Germany, ou_persistent22              
9Institute for Medical Informatics, Statistics and Epidemiology (IMISE), University of Leipzig, Germany, ou_persistent22              

Content

show
hide
Free keywords: -
 Abstract: Reliable risk assessment of frequent, but treatable diseases and disorders has considerable clinical and socio-economic relevance. However, as these conditions usually originate from a complex interplay between genetic and environmental factors, precise prediction remains a considerable challenge. The current progress in genotyping technology has resulted in a substantial increase of knowledge regarding the genetic basis of such diseases and disorders. Consequently, common genetic risk variants are increasingly being included in epidemiological models to improve risk prediction. This work reviews recent high-quality publications targeting the prediction of common complex diseases. To be included in this review, articles had to report both, numerical measures of prediction performance based on traditional (non-genetic) risk factors, as well as measures of prediction performance when adding common genetic variants to the model. Systematic PubMed-based search finally identified 55 eligible studies. These studies were compared with respect to the chosen approach and methodology as well as results and clinical impact. Phenotypes analysed included tumours, diabetes mellitus, and cardiovascular diseases. All studies applied one or more statistical measures reporting on calibration, discrimination, or reclassification to quantify the benefit of including SNPs, but differed substantially regarding the methodological details that were reported. Several examples for improved risk assessments by considering disease-related SNPs were identified. Although the add-on benefit of including SNP genotyping data was mostly moderate, the strategy can be of clinical relevance and may, when being paralleled by an even deeper understanding of disease-related genetics, further explain the development of enhanced predictive and diagnostic strategies for complex diseases.

Details

show
hide
Language(s): eng - English
 Dates: 2015-09-162016-01-152016-02-022016-03
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: Peer
 Identifiers: DOI: 10.1007/s00439-016-1636-z
PMID: 26839113
PMC: PMC4759222
Other: Epub 2016
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Human Genetics
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: Berlin : Springer-Verlag
Pages: - Volume / Issue: 135 (3) Sequence Number: - Start / End Page: 259 - 272 Identifier: ISSN: 0340-6717
CoNE: /journals/resource/954925519623