Back

Sex-stratified analysis of the potential association between PGLYRP2 rs892145 variant and Parkinson's disease across diverse ancestral populations

Avila, C. L.; Chaparro Solano, H. M.; Quintana-Pena, V.; Aberg, K.; the Global Parkinson's Genetics Program (GP2), ; Atterling Brolin, K.

2025-07-24 genetic and genomic medicine
10.1101/2025.07.23.25331993 medRxiv
Show abstract

Variants in PGLYRP2, particularly rs892145-T, have been suggested as Parkinsons disease (PD) risk factors. We analyzed data from 31,334 PD patients and 17,772 controls across diverse ancestries. A significant sex-dependent effect of rs892145-T was observed in African (AFR) ancestry males (OR=0.73, 95%CI: 0.57-0.94, p=0.014). Gene-based analyses identified another variant, rs7251871-A, as significantly associated with PD in AFR males (OR=1.34, 95%CI:1.13-1.59, p=6.65E-04, Bonferroni p=0.0432). No associations were observed in other ancestries. Further studies are needed to understand PGLYRP2s role in PD. Plain language summary (PLS)Genetic variations in the PGLYRP2 gene have been linked to the risk of developing Parkinsons disease (PD), but the research reports have been inconclusive. In this study, we therefore investigated whether genetic variants in this gene are associated with PD. We analyzed data from 32,334 people with PD and 17,772 people without the disease, all from diverse ancestral backgrounds. We found that a previously reported genetic variant, called rs892145-T, appeared to have a possible protective effect against PD specifically in males of African descent. We also identified a different variant, rs7251871-A, which had not been linked to PD before, that seemed to increase PD risk in the same group. No significant results were found in other ancestry groups or for the females group. These findings need to be confirmed in future studies with larger numbers of participants to better understand the role of the gene PGLYRP2 in PD.

Matching journals

The top 1 journal accounts for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.