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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., (© 2024. The Author(s).)

Background: Type 2 diabetes (T2D) is a worldwide scourge caused by both genetic and environmental risk factors that disproportionately afflicts communities of color. Leveraging existing large-scale genome-wide association studies (GWAS), polygenic risk scores (PRS) have shown promise to complement established clinical risk factors and intervention paradigms, and improve early diagnosis and prevention of T2D. However, to date, T2D PRS have been most widely developed and validated in individuals of European descent. Comprehensive assessment of T2D PRS in non-European populations is critical for equitable deployment of PRS to clinical practice that benefits global populations., Methods: We integrated T2D GWAS in European, African, and East Asian populations to construct a trans-ancestry T2D PRS using a newly developed Bayesian polygenic modeling method, and assessed the prediction accuracy of the PRS in the multi-ethnic Electronic Medical Records and Genomics (eMERGE) study (11,945 cases; 57,694 controls), four Black cohorts (5137 cases; 9657 controls), and the Taiwan Biobank (4570 cases; 84,996 controls). We additionally evaluated a post hoc ancestry adjustment method that can express the polygenic risk on the same scale across ancestrally diverse individuals and facilitate the clinical implementation of the PRS in prospective cohorts., Results: The trans-ancestry PRS was significantly associated with T2D status across the ancestral groups examined. The top 2% of the PRS distribution can identify individuals with an approximately 2.5-4.5-fold of increase in T2D risk, which corresponds to the increased risk of T2D for first-degree relatives. The post hoc ancestry adjustment method eliminated major distributional differences in the PRS across ancestries without compromising its predictive performance., Conclusions: By integrating T2D GWAS from multiple populations, we developed and validated a trans-ancestry PRS, and demonstrated its potential as a meaningful index of risk among diverse patients in clinical settings. Our efforts represent the first step towards the implementation of the T2D PRS into routine healthcare., (© 2022. The Author(s).)

Background: Cardiovascular disease, diabetes, and kidney disease are among the leading causes of death and disability worldwide. However, knowledge of genetic determinants of those diseases in African Americans remains limited., Results: In our study, associations between 4956 GWAS catalog reported SNPs and 67 traits were examined among 7726 African Americans from the REasons for Geographic and Racial Differences in Stroke (REGARDS) study, which is focused on identifying factors that increase stroke risk. The prevalent and incident phenotypes studied included inflammation, kidney traits, cardiovascular traits and cognition. Our results validated 29 known associations, of which eight associations were reported for the first time in African Americans., Conclusion: Our cross-racial validation of GWAS findings provide additional evidence for the important roles of these loci in the disease process and may help identify genes especially important for future functional validation.

Background: Recently, epigenetic age acceleration-or older epigenetic age in comparison to chronological age-has been robustly associated with mortality and various morbidities. However, accelerated epigenetic aging has not been widely investigated in relation to inflammatory or metabolic markers, including postprandial lipids., Methods: We estimated measures of epigenetic age acceleration in 830 Caucasian participants from the Genetics Of Lipid Lowering Drugs and diet Network (GOLDN) considering two epigenetic age calculations based on differing sets of 5'-Cytosine-phosphate-guanine-3' genomic site, derived from the Horvath and Hannum DNA methylation age calculators, respectively. GOLDN participants underwent a standardized high-fat meal challenge after fasting for at least 8 h followed by timed blood draws, the last being 6 h postmeal. We used adjusted linear mixed models to examine the association of the epigenetic age acceleration estimate with fasting and postprandial (0- and 6-h time points) low-density lipoprotein (LDL), high-density lipoprotein (HDL), and triglyceride (TG) levels as well as five fasting inflammatory markers plus adiponectin., Results: Both DNA methylation age estimates were highly correlated with chronological age ( r  > 0.90). We found that the Horvath and Hannum measures of epigenetic age acceleration were moderately correlated ( r  = 0.50). The regression models revealed that the Horvath age acceleration measure exhibited marginal associations with increased postprandial HDL ( p  = 0.05), increased postprandial total cholesterol ( p  = 0.06), and decreased soluble interleukin 2 receptor subunit alpha (IL2sRα, p  = 0.02). The Hannum measure of epigenetic age acceleration was inversely associated with fasting HDL ( p  = 0.02) and positively associated with postprandial TG ( p  = 0.02), interleukin-6 (IL6, p  = 0.007), C-reactive protein (C-reactive protein, p  = 0.0001), and tumor necrosis factor alpha (TNFα, p  = 0.0001). Overall, the observed effect sizes were small and the association of the Hannum residual with inflammatory markers was attenuated by adjustment for estimated T cell type percentages., Conclusions: Our study demonstrates that epigenetic age acceleration in blood relates to inflammatory biomarkers and certain lipid classes in Caucasian individuals of the GOLDN study. Future studies should consider epigenetic age acceleration in other tissues and extend the analysis to other ethnic groups., Competing Interests: The GOLDN study was approved by the University of Minnesota’s Human Research Protection Program Institutional Review Board, University of Alabama at Birmingham’s Institutional Review Board for Human Use, University of Utah’s Institutional Review Board, Washington University in St Louis’s Human Research Protection Office Institutional Review Board, and the University of Kentucky’s Office of Research Integrity Institutional Review Board.Not applicable.The authors declare that they have no competing interests.Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Background: Ribosomal proteins (RPs) have about 2000 pseudogenes in the human genome. While anecdotal reports for RP pseudogene transcription exists, it is unclear to what extent these pseudogenes are transcribed. The RP pseudogene transcription is difficult to identify in microarrays due to potential cross-hybridization between transcripts from the parent genes and pseudogenes. Recently, transcriptome sequencing (RNA-seq) provides an opportunity to ascertain the transcription of pseudogenes. A challenge for pseudogene expression discovery in RNA-seq data lies in the difficulty to uniquely identify reads mapped to pseudogene regions, which are typically also similar to the parent genes., Results: Here we developed a specialized pipeline for pseudogene transcription discovery. We first construct a "composite genome" that includes the entire human genome sequence as well as mRNA sequences of real ribosomal protein genes. We then map all sequence reads to the composite genome, and only exact matches were retained. Moreover, we restrict our analysis to strictly defined mappable regions and calculate the RPKM values as measurement of pseudogene transcription levels. We report evidences for the transcription of RP pseudogenes in 16 human tissues. By analyzing the Human Body Map 2.0 study RNA-sequencing data using our pipeline, we identified that one ribosomal protein (RP) pseudogene (PGOHUM-249508) is transcribed with RPKM 170 in thyroid. Moreover, three other RP pseudogenes are transcribed with RPKM > 10, a level similar to that of the normal RP genes, in white blood cell, kidney, and testes, respectively. Furthermore, an additional thirteen RP pseudogenes are of RPKM > 5, corresponding to the 20-30 percentile among all genes. Unlike ribosomal protein genes that are constitutively expressed in almost all tissues, RP pseudogenes are differentially expressed, suggesting that they may contribute to tissue-specific biological processes., Conclusions: Using a specialized bioinformatics method, we identified the transcription of ribosomal protein pseudogenes in human tissues using RNA-seq data.

Background: Many efforts in microarray data analysis are focused on providing tools and methods for the qualitative analysis of microarray data. HDBStat! (High-Dimensional Biology-Statistics) is a software package designed for analysis of high dimensional biology data such as microarray data. It was initially developed for the analysis of microarray gene expression data, but it can also be used for some applications in proteomics and other aspects of genomics. HDBStat! provides statisticians and biologists a flexible and easy-to-use interface to analyze complex microarray data using a variety of methods for data preprocessing, quality control analysis and hypothesis testing., Results: Results generated from data preprocessing methods, quality control analysis and hypothesis testing methods are output in the form of Excel CSV tables, graphs and an Html report summarizing data analysis., Conclusion: HDBStat! is a platform-independent software that is freely available to academic institutions and non-profit organizations. It can be downloaded from our website http://www.soph.uab.edu/ssg&#95;content.asp?id=1164.