rs10887024 - ATE1

Magnitude 2.2 · 2 studies on file

Reported associations

• Using human genetics to understand the phenotypic association between chronotype and breast cancer. - Journal of sleep research (2024) · Wu X, Yang C, Zou Y, Jones SE, Zhao X, Zhang L, Han Z, Hao Y, Xiao J, Xiao C, Zhang W, Yan P, Cui H, Tang M, Wang Y, Chen L, Zhang L, Yao Y, Liu Z, Li J, Jiang X, Zhang B · PubMed 37380357

  Little is known regarding the shared genetic influences underlying the observed phenotypic association between chronotype and breast cancer in women. Leveraging summary statistics from the hitherto largest genome-wide association study conducted in each trait, we investigated the genetic correlation, pleiotropic loci, and causal relationship of chronotype with overall breast cancer, and with its subtypes defined by the status of oestrogen receptor. We identified a negative genomic correlation between chronotype and overall breast cancer ( = -0.06, p = 3.00 × 10 ), consistent across oestrogen receptor-positive ( = -0.05, p = 3.30 × 10 ) and oestrogen receptor-negative subtypes ( = -0.05, p = 1.11 × 10 ). Five specific genomic regions were further identified

• Complex genetic signatures in immune cells underlie autoimmunity and inform therapy - Unknown journal (n.d.) · Unknown authors · PubMed 32929287

  ABSTRACT: We report on the influence of ~22 million variants on 731 immune cell traits in a cohort of 3,757 Sardinians. We detected 122 significant (P < 1.28 × 10−11) independent association signals for 459 cell traits at 70 loci (53 of them novel) identifying several molecules and mechanisms involved in cell regulation. Furthermore, 53 signals at 36 loci overlapped with previously reported disease-associated signals, predominantly for autoimmune disorders, highlighting intermediate phenotypes in pathogenesis. Collectively, our findings illustrate complex genetic regulation of immune cells with highly selective effects on autoimmune disease risk at the cell-subtype level. These results identify drug-targetable pathways informing the design of more specific treatments for autoimmune dise

Auto-generated from study metadata. AI-synthesised commentary is added when this entry is regenerated through content-service's LLM mode.