Comparing Alzheimer's genes in African, European, and Amerindian induced pluripotent stem cell-derived microglia

Abstract

Introduction: Genome-wide association studies (GWAS) studies in Alzheimer's disease (AD) demonstrate ancestry-specific loci. Previous studies in the regulatory architecture have only been conducted in Europeans (EUs), thus studies in additional ancestries are needed. Given the prevalence of AD genes expressed in microglia, we initiated our studies in induced pluripotent stem cell (iPSC) -derived microglia.

Methods: We created iPSC-derived microglia from 13 individuals of either high Amerindian (AI), African (AF), or EU global ancestry, including both AD and controls. RNA-seq, ATAC-seq, and pathway analyses were compared between ancestries in both AD and non-AD genes.

Results: Twelve AD genes were differentially expressed genes (DEGs) and/or accessible between ancestries, including ABI3, CTSB, and MS4A6A. A total of 5% of all genes had differential ancestral expression, but differences in accessibility were less than 1%. The DEGs were enriched in known AD pathways.

Discussion: This resource will be valuable in evaluating AD in admixed populations and other neurological disorders and understanding the AD risk differences between populations.

Highlights: First comparison of the genomics of AI, AF, and EU microglia. Report differences in expression and accessibility of AD genes between ancestries. Ancestral expression differences are greater than differences in accessibility. Good transcriptome correlation was seen between brain and iPSC-derived microglia. Differentially expressed AD genes were in known AD pathways.

Keywords: ATAC‐seq; Alzheimer's disease; RNA‐seq; diversity; genetic ancestry; genetic regulatory architecture; iPSC‐derived microglia.

FIGURE 1

Gene expression across ancestries. (A) Chromosome maps per pair‐wise ancestral comparison demonstrating the distribution of DEGs genome‐wide. The dark green color represents DEGs. (B) Volcano plots representing gene expression (log₂ fold change) per pair‐wise comparison between ancestries (AF vs. EU, AI vs. AF, and AI vs. EU). All 60,656 expressed variables are represented by the circles. The blue and red colored circles represent the genes that are differentially expressed (fold change cutoff of ± 1.25 and have an adjusted p‐value (FDR) ≤ 0.05). AD risk‐modifying genes were highlighted in the white boxes. (C) Gene expression (FPM) of AD‐related genes that were differentially expressed between ancestries. Box plots represent minimum to maximum FPM values and error bars denote the standard deviation. Asterisks denote adjusted p‐value (FDR) with p ≤ 0.05 (*), p ≤ 0.01 (**), and p ≤ 0.001 (***). AF, Africans; AI, Amerindian; DEGs, differentially expressed genes; EU, European; FDR, false discovery rate; FPM, fragments per million.

FIGURE 2

Chromatin accessibility across ancestries. (A) Chromosome maps per pair‐wise ancestral group comparison demonstrating the distribution of DAGs genome‐wide. The dark blue color represents DAGs. (B) Pie charts illustrate the regions of the genome in which the differentially accessible peaks lie for each of the ancestral comparisons. (C) Volcano plots representing chromatin accessible peaks (log₂ fold change) per pair‐wise comparison between ancestries (AF vs. EU, AI vs. AF, and AI vs. EU). All 171,929 peaks are represented by the circles. The blue and red colored circles represent the genes that are differentially accessible (log₂ fold change cutoff of ±0.322 and adjusted p‐value (FDR) ≤ 0.05. AD risk‐modifying genes were highlighted in the white boxes. AD, Alzheimer's disease; AF, Africans; AI, Amerindian; DAGs, differentially accessible genes; EU, European; FDR, false discovery rate.

FIGURE 3

Differentially accessible peaks in AD‐risk modifying genes across ancestries. (A) Differential chromatin accessible peaks in PRDM7. (B) Differential chromatin accessible peak in a distal intergenic enhancer of SCIMP. Note that the peaks represent merged data of all individuals within the same ancestry group. AD, Alzheimer's disease.

FIGURE 4

Functional enrichment pathway enrichment across ancestries relevant to AD. Pathway enrichment analyses between (A) AI and AF, and (B) AI and EU. See Tables S4 and S5, respectively, for all significantly enriched pathways. AD, Alzheimer's disease; AF, Africans; AI, Amerindian; EU, European.

FIGURE 5

Overlap between differentially accessible ATAC‐seq genes, differentially expressed RNA‐seq genes, and AD GWAS genes between ancestry‐group comparisons. AD, Alzheimer's disease; GWAS, genome‐wide association studies.

FIGURE 6

The GRA in iMGL of diverse ancestries as a useful resource to study other neurological and associated diseases. We illustrate the overlap between ancestry‐specific (A) DEGs and (B) DAGs from our study with previously identified GWAS genes for ASD, SZ, BP, PD, stroke, MS, CAD, and HLD. Gray boxes represent the total number of genes queried. ASD, autism spectrum disorder; BP, bipolar disorder; CAD, coronary artery disease; DAGs, differentially accessible genes; DEGs, differentially expressed genes; GRA, genetic regulatory architecture; GWAS, genome‐wide association studies; HLD, hyperlipidemia; iMGL, induced pluripotent stem cell‐derived microglia; MS, multiple sclerosis; PD, Parkinson's disease; SZ, schizophrenia.