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Unique genetic architecture of CSF and brain metabolites pinpoints the novel targets for the traits of human wellness

Brain metabolism perturbation can contribute to traits and diseases. We conducted the first large-scale CSF and brain genome-wide association studies, which identified 219 independent associations (59.8% novel) for 144 CSF metabolites and 36 independent associations (55.6% novel) for 34 brain metabo...

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Detalles Bibliográficos
Autores principales: Wang, Ciyang, Western, Dan, Yang, Chengran, Ali, Muhammad, Wang, Lihua, Gorijala, Priyanka, Timsina, Jigyasha, Ruiz, Agustín, Pastor, Pau, Fernandez, Maria, Panyard, Daniel, Engelman, Corinne, Deming, Yuetiva, Boada, Merce, Cano, Amanda, García-González, Pablo, Graff-Radford, Neill, Mori, Hiroshi, Lee, Jae-Hong, Perrin, Richard, Sung, Yun Ju, Cruchaga, Carlos
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Journal Experts 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10274943/
https://www.ncbi.nlm.nih.gov/pubmed/37333177
http://dx.doi.org/10.21203/rs.3.rs-2923409/v1
Descripción
Sumario:Brain metabolism perturbation can contribute to traits and diseases. We conducted the first large-scale CSF and brain genome-wide association studies, which identified 219 independent associations (59.8% novel) for 144 CSF metabolites and 36 independent associations (55.6% novel) for 34 brain metabolites. Most of the novel signals (97.7% and 70.0% in CSF and brain) were tissue specific. We also integrated MWAS-FUSION approaches with Mendelian Randomization and colocalization to identify causal metabolites for 27 brain and human wellness phenotypes and identified eight metabolites to be causal for eight traits (11 relationships). Low mannose level was causal to bipolar disorder and as dietary supplement it may provide therapeutic benefits. Low galactosylglycerol level was found causal to Parkinson’s Disease (PD). Our study expanded the knowledge of MQTL in central nervous system, provided insights into human wellness, and successfully demonstrates the utility of combined statistical approaches to inform interventions.