PILRA

Last update 08 May 2025

Basic Info

Synonyms

Cell surface receptor FDF03, FDF03, Inhibitory receptor PILR-alpha

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Introduction

Paired receptors consist of highly related activating and inhibitory receptors and are widely involved in the regulation of the immune system. PILRA is thought to act as a cellular signaling inhibitory receptor by recruiting cytoplasmic phosphatases like PTPN6/SHP-1 and PTPN11/SHP-2 via their SH2 domains that block signal transduction through dephosphorylation of signaling molecules. Receptor for PIANP. (Microbial infection) Acts as an entry co-receptor for herpes simplex virus 1.

100 Clinical Results associated with PILRA

100 Translational Medicine associated with PILRA

0 Patents (Medical) associated with PILRA

Literatures (Medical) associated with PILRA

23 Jan 2025·Human Molecular Genetics

Loss of paired immunoglobin-like type 2 receptor B gene associated with age-related macular degeneration impairs photoreceptor function in mouse retina

Article

Author: Swaroop, Anand ; Dey, Partha Narayan ; Nellissery, Jacob ; Dong, Lijin ; Zelinger, Lina ; Fariss, Robert N ; Batz, Zachary ; Li, Tiansen ; White Carreiro, Noor D ; Singh, Nivedita ; Qian, Haohua

AbstractGenome-wide association studies have uncovered mostly non-coding variants at over 60 genetic loci linked to susceptibility for age-related macular degeneration (AMD). To ascertain the causal gene at the PILRB/PILRA locus, we used a CRISPR strategy to produce germline deletions in the mouse paired immunoglobin-like type 2 receptor (Pilr) genes that encode highly related activating (PILRB) and inhibitory (PILRA) receptors. We show that a combined loss of Pilrb1 and Pilrb2, but not Pilra, leads to an early but relatively stationary defect as the electroretinography (ERG) amplitudes of Pilrb1/2−/− mice exhibit a marked reduction as early as postnatal day 15 and do not show additional significant decrease at 3 and 12-months. No alterations are evident in Müller glia, microglia, bipolar, amacrine and horizontal cells based on immunohistochemistry using cell-type specific markers. PILRB immunostaining is specifically detected at the proximal part of photoreceptor outer segment. Reduced expression of select calcium-regulated phototransduction and synapse-associated proteins, including GCAP1 and 2, PDE6b, AIPL1, PSD95, and CTBP1 indicates dysregulation of calcium homeostasis as a possible mechanism of retinal phenotype in Pilrb1/2−/− mice. Our studies suggest a novel function of PILRB in retinal photoreceptors and an association of PILRB, but not PILRA, with AMD pathogenesis.

01 Dec 2024·Cell Genomics

Deciphering proteins in Alzheimer’s disease: A new Mendelian randomization method integrated with AlphaFold3 for 3D structure prediction

Article

Author: Miller, Gary W ; Vardarajan, Badri N ; Yao, Minhao ; Baccarelli, Andrea A ; Guo, Zijian ; Liu, Zhonghua

Hidden confounding biases hinder identifying causal protein biomarkers for Alzheimer's disease in non-randomized studies. While Mendelian randomization (MR) can mitigate these biases using protein quantitative trait loci (pQTLs) as instrumental variables, some pQTLs violate core assumptions, leading to biased conclusions. To address this, we propose MR-SPI, a novel MR method that selects valid pQTL instruments using Leo Tolstoy's Anna Karenina principle and performs robust post-selection inference. Integrating MR-SPI with AlphaFold3, we developed a computational pipeline to identify causal protein biomarkers and predict 3D structural changes. Applied to genome-wide proteomics data from 54,306 UK Biobank participants and 455,258 subjects (71,880 cases and 383,378 controls) for a genome-wide association study of Alzheimer's disease, we identified seven proteins (TREM2, PILRB, PILRA, EPHA1, CD33, RET, and CD55) with structural alterations due to missense mutations. These findings offer insights into the etiology and potential drug targets for Alzheimer's disease.

01 Dec 2024·Alzheimer's & Dementia

Ancestry‐specific studies on Alzheimer’s disease using iPSC‐derived microglia

Article

Author: Coombs, Lauren ; Illanes‐Manrique, Maryenela Z. ; Shepherd, Jihanne J ; Vance, Jeffery M. ; Cornejo‐Olivas, Mario ; Mena, Pedro R. ; Wang, Liyong ; Adams, Larry D. ; Feliciano‐Astacio, Briseida E. ; Rajabli, Farid ; Simon, Shaina A. ; Pericak‐Vance, Margaret A. ; Rivero, Joe ; Whitehead, Patrice L. ; DeRosa, Brooke A. ; Starks, Takiyah D. ; Byrd, Goldie S. ; Ramirez, Aura M ; Nasciben, Luciana Bertholim ; Moura, Sofia ; Tejada, Sergio J. ; Dykxhoorn, Derek M. ; Young, Juan I ; Van Booven, Derek ; Griswold, Anthony J.

AbstractBackgroundIn the US, African Americans (admixed with African and European) followed by Hispanics (admixed with Amerindian, African, and European) are the most affected groups compared to non‐Hispanic Whites (NHW). While genetic diversity and admixture play crucial roles in disease risk, the ancestry‐specific mechanisms remain poorly understood with most AD‐related studies focusing on NHW. Despite the recent field efforts to include genetically admixed populations, there continues to be a lack of functional studies in AD across the different cell types in these populations. Given the importance of Microglia in AD, we here characterize the genetic regulatory architecture (GRA) on iPSC‐derived Microglia (MGL) in African and Amerindian genomes.MethodiPSC lines derived from controls and AD patients with >90% genomic content from different ancestries (Amerindian, African, and European) were differentiated into MGL. We performed bulk RNA‐seq and ATAC‐seq, followed by differential expression and accessibility analyses to study the GRA of these admixed populations and its contributions to AD.ResultWe identified 1,103 differentially expressed genes (DEGs) and 267 differentially accessible genes (DAGs) across ancestries. We observed the most differences on both chromatin accessibility and gene expression levels between AI and AF. On the chromatin level and in the context of AD, we observed 2 DAGs (PRDM7 and SCIMP) between AI and AF, and 1 DAG between AI and EU (PRDM7). In addition, we identified 10 AD‐risk modifying genes that are differentially expressed between AI and AF ancestries (ABI3, CTSB, JAZF1, MS4A6A, PILRA, PLEKHA1, RASGEF1C, SORL1, TREM2, and TREML2) and 3 DEGs between AI and EU (JAZF1, MS4A6A, and SORL1). We identified several DEGs to be involved in lipid metabolism, cholesterol biosynthesis and metabolism, lysosomal activity, and immune response ‐ all highly relevant processes in AD pathology.ConclusionWe provide new insights into ancestry‐specific genetic risk factors in AD pathophysiology. Here, we report novel transcriptomic and chromatin accessibility data in microglia of AI and AF ancestries that potentially contribute to a differential genetic risk in AD in the different ancestries. Interestingly, those ancestries with greatest migratory differences revealed the largest DEG.

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PILRA

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