Author:
Akinyemi Rufus O.,Tiwari Hemant K.,Srinivasasainagendra Vinodh,Akpa Onoja,Sarfo Fred S.,Akpalu Albert,Wahab Kolawole,Obiako Reginald,Komolafe Morenikeji,Owolabi Lukman,Osaigbovo Godwin O.,Mamaeva Olga A.,Halloran Brian A.,Akinyemi Joshua,Lackland Daniel,Obiabo Olugbo Y.,Sunmonu Taofik,Chukwuonye Innocent I.,Arulogun Oyedunni,Jenkins Carolyn,Adeoye Abiodun,Agunloye Atinuke,Ogah Okechukwu S.,Ogbole Godwin,Fakunle Adekunle,Uvere Ezinne,Coker Motunrayo M.,Okekunle Akinkunmi,Asowata Osahon,Diala Samuel,Ogunronbi Mayowa,Adeleye Osi,Laryea Ruth,Tagge Raelle,Adeniyi Sunday,Adusei Nathaniel,Oguike Wisdom,Olowoyo Paul,Adebajo Olayinka,Olalere Abimbola,Oladele Olayinka,Yaria Joseph,Fawale Bimbo,Ibinaye Philip,Oyinloye Olalekan,Mensah Yaw,Oladimeji Omotola,Akpalu Josephine,Calys-Tagoe Benedict,Dambatta Hamisu A.,Ogunniyi Adesola,Kalaria Rajesh,Arnett Donna,Rotimi Charles,Ovbiagele Bruce,Owolabi Mayowa O.,
Abstract
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.
Publisher
Springer Science and Business Media LLC
Subject
Genetics (clinical),Genetics,Molecular Biology,Molecular Medicine