Novel functional insights into ischemic stroke biology provided by the first genome-wide association study of stroke in indigenous Africans Article Swipe
Rufus Akinyemi
,
Hemant K. Tiwari
,
Vinodh Srinivasasainagendra
,
Onoja Akpa
,
Fred Stephen Sarfo
,
Albert Akpalu
,
Kolawole Wahab
,
Reginald Obiako
,
Morenikeji Komolafe
,
Lukman Owolabi
,
Godwin Osaigbovo
,
Olga Mamaeva
,
Brian Halloran
,
Joshua Akinyemi
,
Daniel T. Lackland
,
Olugbo Y. Obiabo
,
Taofik O. Sunmonu
,
Innocent Ijezie Chukwuonye
,
Oyedunni Arulogun
,
Carolyn Jenkins
,
Abiodun M. Adeoye
,
Atinuke Agunloye
,
Okechukwu S. Ogah
,
Godwin Ogbole
,
Adekunle Fakunle
,
Ezinne Uvere
,
Motunrayo M. Coker
,
Akinkunmi Paul Okekunle
,
Osahon Jeffery Asowata
,
Samuel Diala
,
Mayowa Ogunronbi
,
Osi Adeleye
,
Ruth Laryea
,
Raelle Tagge
,
Sunday Adeniyi
,
Nathaniel Adusei
,
Wisdom Oguike
,
Paul Olowoyo
,
Olayinka Adebajo
,
Abimbola Olalere
,
Olayinka Oladele
,
Joseph Yaria
,
Bimbo Fawale
,
Philip Ibinaye
,
Olalekan Oyinloye
,
Yaw Mensah
,
Omotola Oladimeji
,
Josephine Akpalu
,
Benedict Calys‐Tagoe
,
Hamisu A. Dambatta
,
Adesola Ogunniyi
,
Raj N. Kalaria
,
Donna K. Arnett
,
Charles N. Rotimi
,
Bruce Ovbiagele
,
Mayowa Owolabi
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1186/s13073-023-01273-5
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1186/s13073-023-01273-5
Background African ancestry populations have the highest burden of stroke worldwide, yet the genetic basis of stroke in these populations is obscure. The Stroke Investigative Research and Educational Network (SIREN) is a multicenter study involving 16 sites in West Africa. We conducted the first-ever genome-wide association study (GWAS) of stroke in indigenous Africans. Methods Cases were consecutively recruited consenting adults (aged > 18 years) with neuroimaging-confirmed ischemic stroke. Stroke-free controls were ascertained using a locally validated Questionnaire for Verifying Stroke-Free Status. DNA genotyping with the H3Africa array was performed, and following initial quality control, GWAS datasets were imputed into the NIH Trans-Omics for Precision Medicine (TOPMed) release2 from BioData Catalyst. Furthermore, we performed fine-mapping, trans-ethnic meta-analysis, and in silico functional characterization to identify likely causal variants with a functional interpretation. Results We observed genome-wide significant ( P -value < 5.0E−8) SNPs associations near AADACL2 and miRNA ( MIR5186 ) genes in chromosome 3 after adjusting for hypertension, diabetes, dyslipidemia, and cardiac status in the base model as covariates. SNPs near the miRNA ( MIR4458 ) gene in chromosome 5 were also associated with stroke ( P -value < 1.0E−6). The putative genes near AADACL2 , MIR5186 , and MIR4458 genes were protective and novel. SNPs associations with stroke in chromosome 2 were more than 77 kb from the closest gene LINC01854 and SNPs in chromosome 7 were more than 116 kb to the closest gene LINC01446 ( P -value < 1.0E−6). In addition, we observed SNPs in genes STXBP5-AS1 (chromosome 6), GALTN9 (chromosome 12), FANCA (chromosome 16), and DLGAP1 (chromosome 18) ( P -value < 1.0E−6). Both genomic regions near genes AADACL2 and MIR4458 remained significant following fine mapping. Conclusions Our findings identify potential roles of regulatory miRNA, intergenic non-coding DNA, and intronic non-coding RNA in the biology of ischemic stroke. These findings reveal new molecular targets that promise to help close the current gaps in accurate African ancestry-based genetic stroke’s risk prediction and development of new targeted interventions to prevent or treat stroke.
Related Topics
Concepts
Genome-wide association study
Single-nucleotide polymorphism
Stroke (engine)
Genotyping
Genetic association
Genetics
Medicine
Gene
Bioinformatics
Biology
Genotype
Mechanical engineering
Engineering
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1186/s13073-023-01273-5
- https://genomemedicine.biomedcentral.com/counter/pdf/10.1186/s13073-023-01273-5
- OA Status
- gold
- Cited By
- 15
- References
- 62
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391540167
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4391540167Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1186/s13073-023-01273-5Digital Object Identifier
- Title
-
Novel functional insights into ischemic stroke biology provided by the first genome-wide association study of stroke in indigenous AfricansWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-02-05Full publication date if available
- Authors
-
Rufus Akinyemi, Hemant K. Tiwari, Vinodh Srinivasasainagendra, Onoja Akpa, Fred Stephen Sarfo, Albert Akpalu, Kolawole Wahab, Reginald Obiako, Morenikeji Komolafe, Lukman Owolabi, Godwin Osaigbovo, Olga Mamaeva, Brian Halloran, Joshua Akinyemi, Daniel T. Lackland, Olugbo Y. Obiabo, Taofik O. Sunmonu, Innocent Ijezie Chukwuonye, Oyedunni Arulogun, Carolyn Jenkins, Abiodun M. Adeoye, Atinuke Agunloye, Okechukwu S. Ogah, Godwin Ogbole, Adekunle Fakunle, Ezinne Uvere, Motunrayo M. Coker, Akinkunmi Paul Okekunle, Osahon Jeffery Asowata, Samuel Diala, Mayowa Ogunronbi, Osi Adeleye, Ruth Laryea, Raelle Tagge, Sunday Adeniyi, Nathaniel Adusei, Wisdom Oguike, Paul Olowoyo, Olayinka Adebajo, Abimbola Olalere, Olayinka Oladele, Joseph Yaria, Bimbo Fawale, Philip Ibinaye, Olalekan Oyinloye, Yaw Mensah, Omotola Oladimeji, Josephine Akpalu, Benedict Calys‐Tagoe, Hamisu A. Dambatta, Adesola Ogunniyi, Raj N. Kalaria, Donna K. Arnett, Charles N. Rotimi, Bruce Ovbiagele, Mayowa OwolabiList of authors in order
- Landing page
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https://doi.org/10.1186/s13073-023-01273-5Publisher landing page
- PDF URL
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https://genomemedicine.biomedcentral.com/counter/pdf/10.1186/s13073-023-01273-5Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
- OA URL
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https://genomemedicine.biomedcentral.com/counter/pdf/10.1186/s13073-023-01273-5Direct OA link when available
- Concepts
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Genome-wide association study, Single-nucleotide polymorphism, Stroke (engine), Genotyping, Genetic association, Genetics, Medicine, Gene, Bioinformatics, Biology, Genotype, Mechanical engineering, EngineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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15Total citation count in OpenAlex
- Citations by year (recent)
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2025: 13, 2024: 2Per-year citation counts (last 5 years)
- References (count)
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62Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.Cases | 55 |
| abstract_inverted_index.FANCA | 255 |
| abstract_inverted_index.These | 302 |
| abstract_inverted_index.after | 154 |
| abstract_inverted_index.array | 87 |
| abstract_inverted_index.basis | 15 |
| abstract_inverted_index.close | 312 |
| abstract_inverted_index.genes | 150, 192, 200, 248, 271 |
| abstract_inverted_index.miRNA | 146, 172 |
| abstract_inverted_index.model | 166 |
| abstract_inverted_index.roles | 285 |
| abstract_inverted_index.sites | 37 |
| abstract_inverted_index.study | 34, 47 |
| abstract_inverted_index.these | 19 |
| abstract_inverted_index.treat | 333 |
| abstract_inverted_index.using | 73 |
| abstract_inverted_index.(GWAS) | 48 |
| abstract_inverted_index.-value | 138, 187, 239, 264 |
| abstract_inverted_index.DLGAP1 | 259 |
| abstract_inverted_index.GALTN9 | 252 |
| abstract_inverted_index.Stroke | 24 |
| abstract_inverted_index.adults | 60 |
| abstract_inverted_index.burden | 8 |
| abstract_inverted_index.causal | 125 |
| abstract_inverted_index.likely | 124 |
| abstract_inverted_index.miRNA, | 288 |
| abstract_inverted_index.novel. | 204 |
| abstract_inverted_index.reveal | 304 |
| abstract_inverted_index.silico | 119 |
| abstract_inverted_index.status | 162 |
| abstract_inverted_index.stroke | 10, 17, 50, 184, 208 |
| abstract_inverted_index.years) | 64 |
| abstract_inverted_index.(SIREN) | 30 |
| abstract_inverted_index.AADACL2 | 144, 194, 272 |
| abstract_inverted_index.Africa. | 40 |
| abstract_inverted_index.African | 2, 318 |
| abstract_inverted_index.BioData | 109 |
| abstract_inverted_index.MIR4458 | 174, 199, 274 |
| abstract_inverted_index.MIR5186 | 148, 196 |
| abstract_inverted_index.Methods | 54 |
| abstract_inverted_index.Network | 29 |
| abstract_inverted_index.Results | 131 |
| abstract_inverted_index.Status. | 81 |
| abstract_inverted_index.biology | 298 |
| abstract_inverted_index.cardiac | 161 |
| abstract_inverted_index.closest | 219, 234 |
| abstract_inverted_index.current | 314 |
| abstract_inverted_index.genetic | 14, 320 |
| abstract_inverted_index.genomic | 268 |
| abstract_inverted_index.highest | 7 |
| abstract_inverted_index.imputed | 98 |
| abstract_inverted_index.initial | 92 |
| abstract_inverted_index.locally | 75 |
| abstract_inverted_index.prevent | 331 |
| abstract_inverted_index.promise | 309 |
| abstract_inverted_index.quality | 93 |
| abstract_inverted_index.regions | 269 |
| abstract_inverted_index.stroke. | 68, 301, 334 |
| abstract_inverted_index.targets | 307 |
| abstract_inverted_index.(TOPMed) | 106 |
| abstract_inverted_index.Abstract | 0 |
| abstract_inverted_index.H3Africa | 86 |
| abstract_inverted_index.Medicine | 105 |
| abstract_inverted_index.Research | 26 |
| abstract_inverted_index.accurate | 317 |
| abstract_inverted_index.ancestry | 3 |
| abstract_inverted_index.control, | 94 |
| abstract_inverted_index.controls | 70 |
| abstract_inverted_index.datasets | 96 |
| abstract_inverted_index.findings | 282, 303 |
| abstract_inverted_index.identify | 123, 283 |
| abstract_inverted_index.intronic | 293 |
| abstract_inverted_index.ischemic | 67, 300 |
| abstract_inverted_index.mapping. | 279 |
| abstract_inverted_index.obscure. | 22 |
| abstract_inverted_index.observed | 133, 245 |
| abstract_inverted_index.putative | 191 |
| abstract_inverted_index.release2 | 107 |
| abstract_inverted_index.remained | 275 |
| abstract_inverted_index.targeted | 328 |
| abstract_inverted_index.variants | 126 |
| abstract_inverted_index.5.0E−8) | 140 |
| abstract_inverted_index.Africans. | 53 |
| abstract_inverted_index.Catalyst. | 110 |
| abstract_inverted_index.LINC01446 | 236 |
| abstract_inverted_index.LINC01854 | 221 |
| abstract_inverted_index.Precision | 104 |
| abstract_inverted_index.Verifying | 79 |
| abstract_inverted_index.addition, | 243 |
| abstract_inverted_index.adjusting | 155 |
| abstract_inverted_index.conducted | 42 |
| abstract_inverted_index.diabetes, | 158 |
| abstract_inverted_index.following | 91, 277 |
| abstract_inverted_index.involving | 35 |
| abstract_inverted_index.molecular | 306 |
| abstract_inverted_index.performed | 113 |
| abstract_inverted_index.potential | 284 |
| abstract_inverted_index.recruited | 58 |
| abstract_inverted_index.validated | 76 |
| abstract_inverted_index.1.0E−6). | 189, 241, 266 |
| abstract_inverted_index.Background | 1 |
| abstract_inverted_index.STXBP5-AS1 | 249 |
| abstract_inverted_index.associated | 182 |
| abstract_inverted_index.chromosome | 152, 178, 210, 225 |
| abstract_inverted_index.consenting | 59 |
| abstract_inverted_index.first-ever | 44 |
| abstract_inverted_index.functional | 120, 129 |
| abstract_inverted_index.genotyping | 83 |
| abstract_inverted_index.indigenous | 52 |
| abstract_inverted_index.intergenic | 289 |
| abstract_inverted_index.non-coding | 290, 294 |
| abstract_inverted_index.performed, | 89 |
| abstract_inverted_index.prediction | 323 |
| abstract_inverted_index.protective | 202 |
| abstract_inverted_index.regulatory | 287 |
| abstract_inverted_index.stroke’s | 321 |
| abstract_inverted_index.worldwide, | 11 |
| abstract_inverted_index.(chromosome | 250, 253, 256, 260 |
| abstract_inverted_index.Conclusions | 280 |
| abstract_inverted_index.Educational | 28 |
| abstract_inverted_index.Stroke-Free | 80 |
| abstract_inverted_index.Stroke-free | 69 |
| abstract_inverted_index.Trans-Omics | 102 |
| abstract_inverted_index.ascertained | 72 |
| abstract_inverted_index.association | 46 |
| abstract_inverted_index.covariates. | 168 |
| abstract_inverted_index.development | 325 |
| abstract_inverted_index.genome-wide | 45, 134 |
| abstract_inverted_index.multicenter | 33 |
| abstract_inverted_index.populations | 4, 20 |
| abstract_inverted_index.significant | 135, 276 |
| abstract_inverted_index.Furthermore, | 111 |
| abstract_inverted_index.associations | 142, 206 |
| abstract_inverted_index.trans-ethnic | 115 |
| abstract_inverted_index.Investigative | 25 |
| abstract_inverted_index.Questionnaire | 77 |
| abstract_inverted_index.consecutively | 57 |
| abstract_inverted_index.dyslipidemia, | 159 |
| abstract_inverted_index.fine-mapping, | 114 |
| abstract_inverted_index.hypertension, | 157 |
| abstract_inverted_index.interventions | 329 |
| abstract_inverted_index.ancestry-based | 319 |
| abstract_inverted_index.meta-analysis, | 116 |
| abstract_inverted_index.interpretation. | 130 |
| abstract_inverted_index.characterization | 121 |
| abstract_inverted_index.neuroimaging-confirmed | 66 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 94 |
| corresponding_author_ids | https://openalex.org/A5031904244 |
| countries_distinct_count | 5 |
| institutions_distinct_count | 56 |
| corresponding_institution_ids | https://openalex.org/I2800598127 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.5600000023841858 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.98591783 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |