Co-expression-based models improve eQTL predictions for transcriptome-wide association studies and highlight new schizophrenia-associated genes.
Rossi F, Sportelli L, Kikidis GC, Grassi G, Di Camillo F, Bertolino A, Blasi G, Borcuk CJ, Fusco D, Hyde TM, Kleinman JE, Marnetto D, Pellegrini S, Rampino A, Vitiello B, Ripke S, Braun A, Kraft J, Belangero SI, Menezes PR, Arango C, Walters JTR, O'Donovan MC, Owen MJ, Braff D, Corvin A, Morris DW, Domenici E, van Os J, Atbaşoğlu E, Saka MC, Di Forti M, Baune BT, Pato CN, McQuillin A, Golimbet V, Kondratyev N, Escott-Price V, Gareeva A, Khusnutdinova E, Cervilla JA, Rivera M, Campion D, Laurent-Levinson C, Serretti A, Andreassen OA, St Clair D, Lencz T, Malhotra AK, McCarthy NS, Mowry BJ, Rujescu D, Giegling I, Hartmann AM, Konte B, Nöthen MM, Rietschel M, Kirov G, Sullivan PF, Petryshen TL, Werge T, McIntosh AM, Esko T, Jönsson EG, Ehrenreich H, Riley BP, Levinson DF, Buxbaum JD, Bramon E, Hultman CM, Ophoff RA, Adolfsson R, Stahl EA, Guloksuz S, Rutten BPF, Del-Ben CM, Thibaut F, Weinberger DR, Pergola G.
Rossi F, et al. Among authors: riley bp.
Nat Genet. 2026 Jul;58(7):1559-1572. doi: 10.1038/s41588-026-02646-3. Epub 2026 Jun 22.
Nat Genet. 2026.
PMID: 42332269
Free PMC article.