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Pericak-Vance, M.

Publications and source records attributed to Pericak-Vance, M..

3 recordsLinked to original sources

MU-BRAIN: MUltiethnic Brain Rna-seq for Alzheimer INitiative

Alzheimers Disease (AD) exhibits a complex molecular and phenotypic profile. Investigating gene expression plays a crucial role in unraveling the diseases etiology and progression. Transcriptome data across ethnic groups lack, negatively impacting equity in intervention and research. We employed 565 brains across six U.S. brain banks (n=399 non-Hispanic Whites, n=113 Hispanics, n=12 African Americans) to generated bulk RNA sequencing from prefrontal cortex. We sought to identify cross-ancestry and ancestry-specific differentially expressed genes (DEG) across Braak stages, adjusting for sex, age at death, and RNA quality metrics. We further validated our findings using the Religious Orders Study/Memory Aging Project brains (ROS/MAP; n=1,095) and performed metanalysis (n=1,660). We conducted Gene Set and Variation and Enrichment analysis (GSVA; GSEA). We employed a machine-learning approach for phenotype prediction and gene prioritization to construct a polytranscriptomics risk score (PTRS) splitting our sample into training and testing sub-samples, either randomly or by ethnicity ("ancestry-agnostic" and "ancestry-aware", respectively). Lastly, we validated top DEG using single-nucleus RNA sequencing (snRNAseq) data. We identified several DEG associated with Braak staging: AD-known genes VGF (Padj =3.78E- 07) and ADAMTS2 (Pad j=1.21E-04) were consistently differentially expressed across statistical models, ethnicities, and replicated in ROS/MAP. Genes from the heat shock protein (HSP) family, e.g. HSPB7 (Padj =3.78E-07), were the top differentially expressed genes and replicated in ROS/MAP. Ethnic-stratified analyses prioritized TNFSF14 and SPOCD1 as top Hispanics DEG. GSEA highlighted "Alzheimer disease" (Padj =4.24E-06) and "TYROBP causal network in microglia" (Padj =1.68E-08) pathways. Up- and down-regulated genes were enriched in several pathways (e.g. "Immune response activation signal pathways", "Vesicle-mediated transport in synapse", "cognition"). Ancestry-agnostic and ancestry-aware PTRS effectively classified brains (AUC=0.77 and 0.73 respectively) and replicated in ROS/MAP. snRNAseq validated prioritized genes, including VGF (downregulated in neurons; Padj=1.1 E-07). This is the largest diverse AD transcriptome in post-mortem brain tissue, to our knowledge. We identified perturbated genes, pathways and network expressions in AD brains resulting in cross- ethnic and ethnic-specific findings, ultimately highlighting the diversity within AD pathogenesis. The latter underscores the need for an integrative and personalized approach in AD studies.

genetics↗

An Association Test of the Spatial Distribution of Rare Missense Variants within Protein Structures Improves Statistical Power of Sequencing Studies

Over 90% of variants are rare, and 50% of them are singletons in the Alzheimers Disease Sequencing Project Whole Exome Sequencing (ADSP WES) data. However, either single variant tests or unit-based tests are limited in the statistical power to detect the association between rare variants and phenotypes. To best utilize rare variants and investigate their biological effect, we exam their association with phenotypes in the context of protein. We developed a protein structure-based approach, POKEMON (Protein Optimized Kernel Evaluation of Missense Nucleotides), which evaluates rare missense variants based on their spatial distribution on the protein rather than allele frequency. The hypothesis behind this is that the three-dimensional spatial distribution of variants within a protein structure provides functional context and improves the power of association tests. POKEMON identified four candidate genes from the ADSP WES data, namely two known Alzheimers disease (AD) genes (TREM2 and SORL) and two novel genes (DUSP18 and CSF1R). For known AD genes, the signal from the spatial cluster is stable even if we exclude known AD risk variants, indicating the presence of additional low frequency risk variants within these genes. DUSP18 has a cluster of variants primarily shared by case subjects around the ligand-binding domain, and this cluster is further validated in a replication dataset with a larger sample size. POKEMON is an open-source tool available at https://github.com/bushlab-genomics/POKEMON.

bioinformatics↗

A common haplotype lowers SPI1 (PU.1) expression in myeloid cells and delays age at onset for Alzheimer’s disease

In this study we used age at onset of Alzheimers disease (AD), cerebrospinal fluid (CSF) biomarkers, and cis-expression quantitative trait loci (cis-eQTL) datasets to identify candidate causal genes and mechanisms underlying AD GWAS loci. In a genome-wide survival analysis of 40,255 samples, eight of the previously reported AD risk loci are significantly (P < 5x10-8) or suggestively (P < 1x10-5) associated with age at onset-defined survival (AAOS) and a further fourteen novel loci reached suggestive significance. Using stratified LD score regression we demonstrated a significant enrichment of AD heritability in hematopoietic cells of the myeloid and B-lymphoid lineage. We then investigated the impact of these 22 AAOS-associated variants on CSF biomarkers and gene expression in cells of the myeloid lineage. In particular, the minor allele of rs1057233 (G), within the previously reported CELF1 AD risk locus, shows association with higher age at onset of AD (P=8.40x10-6), higher CSF levels of A{beta}42 (P=1.2x10-4), and lower expression of SPI1 in monocytes (P=1.50x10-105) and macrophages (P=6.41x10-87). SPI1 encodes PU.1, a transcription factor critical for myeloid cell development and function. AD heritability is enriched within the SPI1 cistromes of monocytes and macrophages, implicating a myeloid PU.1 target gene network in the etiology of AD. Finally, experimentally altered PU.1 levels are correlated with phagocytic activity of BV2 mouse microglial cells and specific changes in the expression of multiple myeloid-expressed genes, including the mouse orthologs of AD-associated genes, APOE, CLU/APOJ, CD33, MS4A4A/MS4A6A, and TYROBP. Our results collectively suggest that lower SPI1 expression reduces AD risk by modulating myeloid cell gene expression and function.

neuroscience↗