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Meta-Analysis
. 2024 Feb 5;16(1):25.
doi: 10.1186/s13073-023-01273-5.

Novel functional insights into ischemic stroke biology provided by the first genome-wide association study of stroke in indigenous Africans

Rufus O Akinyemi #  1   2   3 , Hemant K Tiwari #  4 , Vinodh Srinivasasainagendra  4 , Onoja Akpa  2 , Fred S Sarfo  5 , Albert Akpalu  6 , Kolawole Wahab  7 , Reginald Obiako  8 , Morenikeji Komolafe  9 , Lukman Owolabi  10 , Godwin O Osaigbovo  11 , Olga A Mamaeva  12 , Brian A Halloran  13 , Joshua Akinyemi  14 , Daniel Lackland  15 , Olugbo Y Obiabo  16 , Taofik Sunmonu  17 , Innocent I Chukwuonye  18 , Oyedunni Arulogun  19 , Carolyn Jenkins  15 , Abiodun Adeoye  3 , Atinuke Agunloye  3 , Okechukwu S Ogah  3 , Godwin Ogbole  3 , Adekunle Fakunle  3   20 , Ezinne Uvere  3 , Motunrayo M Coker  1   21 , Akinkunmi Okekunle  22 , Osahon Asowata  14 , Samuel Diala  3 , Mayowa Ogunronbi  23 , Osi Adeleye  23 , Ruth Laryea  6 , Raelle Tagge  24 , Sunday Adeniyi  7 , Nathaniel Adusei  5 , Wisdom Oguike  8 , Paul Olowoyo  25 , Olayinka Adebajo  3 , Abimbola Olalere  3 , Olayinka Oladele  3 , Joseph Yaria  3 , Bimbo Fawale  9 , Philip Ibinaye  8 , Olalekan Oyinloye  9 , Yaw Mensah  5 , Omotola Oladimeji  3 , Josephine Akpalu  6 , Benedict Calys-Tagoe  5 , Hamisu A Dambatta  10 , Adesola Ogunniyi  3 , Rajesh Kalaria  26 , Donna Arnett  27 , Charles Rotimi  28 , Bruce Ovbiagele #  21 , Mayowa O Owolabi #  29   30   31   32   33 ; SIREN Team
Affiliations
Meta-Analysis

Novel functional insights into ischemic stroke biology provided by the first genome-wide association study of stroke in indigenous Africans

Rufus O Akinyemi et al. Genome Med. .

Abstract

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.

Keywords: African ancestry, Ischemic stroke, SNP, miRNA; GWAS; Genomics; Stroke.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Manhattan plots. a The base model adjusted for sex, age, 10 PCs, and SNP as in model 0. b Hypertension is added to the base model 0. c Diabetes is added to the model 1. d Dyslipidemia is added to model 2. e Cardiac status is added to model 3. f Waist-to-hip ratio is added to model 4
Fig. 2
Fig. 2
Locus zoom plots for SNPs rs6440776 (hg19: chr3:151396081 and hg38:151678293) and rs77326269 (hg19: chr5:8499398 and hg38:chr5:8499286) based on P-values using the base model
Fig. 3
Fig. 3
a Fine-mapping of AADACL2 gene region. b MIR4458HG gene region. Panel 1 depicts a scatterplot of location versus posterior probabilities with a 99% credible interval; panel 2 provides functional annotation tracks
Fig. 4
Fig. 4
a Circos plot showcasing chromatin interaction (orange arcs) and eQTL interactions (green arcs) originating from SNP rs6440776 (AADAC gene region). b Genomic landscape for AADACL2 illustrating CpG islands, enhancer/promoter presence, histone modification sites, and regulatory interaction activity from UCSC browser
Fig. 5
Fig. 5
a Circos plot showcasing chromatin interaction (orange arcs) and eQTL interactions (green arcs) originating from SNP rs57085803 (MIR4458HG gene region). b Genomic landscape for MIR4458HG illustrating CpG islands, enhancer/promoter presence, histone modification sites, and regulatory interaction activity from UCSC browser
See this image and copyright information in PMC

References

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