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Stroke genetics: a review and update.

Lindgren, Arne LU (2014) In Journal of Stroke 16(3). p.114-123
Abstract
Stroke genetics includes several topics of clinical interest, including (1) molecular genetic variations affecting risk of monogenic stroke syndromes; (2) molecular genetic variations affecting risk of common stroke syndromes, sometimes with specific effects on risk of specific main types of stroke or subtypes of ischemic and hemorrhagic stroke; (3) genetics of conditions associated with stroke risk e.g. white matter hyperintensities, atrial fibrillation and hypertension; (4) hereditary causes of familial aggregation of stroke; (5) epigenetic impact on protein expression during acute brain injury; (6) genetic influence on stroke recovery; and (7) pharmacogenetics. Genetic research methods include candidate gene studies; Genome Wide... (More)
Stroke genetics includes several topics of clinical interest, including (1) molecular genetic variations affecting risk of monogenic stroke syndromes; (2) molecular genetic variations affecting risk of common stroke syndromes, sometimes with specific effects on risk of specific main types of stroke or subtypes of ischemic and hemorrhagic stroke; (3) genetics of conditions associated with stroke risk e.g. white matter hyperintensities, atrial fibrillation and hypertension; (4) hereditary causes of familial aggregation of stroke; (5) epigenetic impact on protein expression during acute brain injury; (6) genetic influence on stroke recovery; and (7) pharmacogenetics. Genetic research methods include candidate gene studies; Genome Wide Association Studies; family studies; RNA and protein analyses; and advanced computer-aided analytical methods to detect statistically significant associations. Several methods that could improve our knowledge of stroke genetics are being developed e.g.: Exome content analysis; Next-generation sequencing; Whole genome sequencing; and Epigenetics. During 2012-2014, several Single Nucleotide Polymorphisms (SNPs) have been related to common ischemic stroke risk. Certain SNPs have been associated with risk of specific ischemic stroke subtypes such as large vessel disease and cardiac embolism, particular subtypes of intracerebral hemorrhage (ICH), especially lobar ICH, and with prognosis after ICH. Large international studies on stroke recovery and exome content are ongoing. Advanced mathematical models have been used to study how several SNPs can act together and increase stroke risk burden. Such efforts require large numbers of patients and controls, which is achieved by co-operation in large international consortia such as the International Stroke Genetics Consortium. This overview includes an introduction to genetics, stroke genetics in general, and different genetic variations that may influence stroke risk. It presents some of the latest reports on stroke genetics published in high impact journals. The role of pharmacogenetics, the current clinical situation, and future prospects will also be discussed. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
in
Journal of Stroke
volume
16
issue
3
pages
114 - 123
publisher
KOREAN STROKE SOC
external identifiers
  • pmid:25328870
  • wos:000342855900002
ISSN
2287-6391
DOI
10.5853/jos.2014.16.3.114
language
English
LU publication?
yes
id
ee40300d-dbcd-4489-a2c8-1d43407ba3ed (old id 4733778)
alternative location
http://www.ncbi.nlm.nih.gov/pubmed/25328870?dopt=Abstract
date added to LUP
2014-11-09 23:36:44
date last changed
2016-09-30 05:45:33
@article{ee40300d-dbcd-4489-a2c8-1d43407ba3ed,
  abstract     = {Stroke genetics includes several topics of clinical interest, including (1) molecular genetic variations affecting risk of monogenic stroke syndromes; (2) molecular genetic variations affecting risk of common stroke syndromes, sometimes with specific effects on risk of specific main types of stroke or subtypes of ischemic and hemorrhagic stroke; (3) genetics of conditions associated with stroke risk e.g. white matter hyperintensities, atrial fibrillation and hypertension; (4) hereditary causes of familial aggregation of stroke; (5) epigenetic impact on protein expression during acute brain injury; (6) genetic influence on stroke recovery; and (7) pharmacogenetics. Genetic research methods include candidate gene studies; Genome Wide Association Studies; family studies; RNA and protein analyses; and advanced computer-aided analytical methods to detect statistically significant associations. Several methods that could improve our knowledge of stroke genetics are being developed e.g.: Exome content analysis; Next-generation sequencing; Whole genome sequencing; and Epigenetics. During 2012-2014, several Single Nucleotide Polymorphisms (SNPs) have been related to common ischemic stroke risk. Certain SNPs have been associated with risk of specific ischemic stroke subtypes such as large vessel disease and cardiac embolism, particular subtypes of intracerebral hemorrhage (ICH), especially lobar ICH, and with prognosis after ICH. Large international studies on stroke recovery and exome content are ongoing. Advanced mathematical models have been used to study how several SNPs can act together and increase stroke risk burden. Such efforts require large numbers of patients and controls, which is achieved by co-operation in large international consortia such as the International Stroke Genetics Consortium. This overview includes an introduction to genetics, stroke genetics in general, and different genetic variations that may influence stroke risk. It presents some of the latest reports on stroke genetics published in high impact journals. The role of pharmacogenetics, the current clinical situation, and future prospects will also be discussed.},
  author       = {Lindgren, Arne},
  issn         = {2287-6391},
  language     = {eng},
  number       = {3},
  pages        = {114--123},
  publisher    = {KOREAN STROKE SOC},
  series       = {Journal of Stroke},
  title        = {Stroke genetics: a review and update.},
  url          = {http://dx.doi.org/10.5853/jos.2014.16.3.114},
  volume       = {16},
  year         = {2014},
}