Thalamocortical Structural Covariation Networks Are Related to Familial Risk for Schizophrenia in the Context of Lower Nuclei Volume Estimates in Patients: An ENIGMA Study.
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Lella Annalisa, Antonucci Linda A, Passiatore Roberta, Bellantuono Loredana, Selvaggi Pierluigi, Popolizio Teresa, Di Sciascio Guido, Saponaro Alessandro, Ricci Patrizia, Altamura Mario, Blasi Giuseppe, Rampino Antonio, Vriend Chris, Calhoun Vince D, Rootes-Murdy Kelly, Goldman Aaron L, Baeza Inmaculada, Castro-Fornieles Josefina, Sugranyes Gisela, De la Serna Elena, Pomarol-Clotet Edith, Fatjó-Vilas Mar, Salvador Raymond, Karuk Andriana, Fuentes-Claramonte Paola, Glahn David C, Rodrigue Amanda L, Blangero John, Wang Lei, Lee Taeyoung, Einenkel Karolin E, Hamers Saskia, Gruber Oliver, Preda Adrian, Chung Young-Chul, Odkhuu Soyolsaikhan, Vallée Corentin, Dazzan Paola, Marcelis Machteld, Michielse Stijn, Brosch Katharina, Stein Frederike, Nenadić Igor, Straube Benjamin, Thomas-Odenthal Florian, Kircher Tilo, Carruthers Sean, Rossell Susan L, Sumner Phillip J, Van Rheenen Tamsyn E, Demro Caroline, Ramsay Ian S, Sponheim Scott R, Lencer Rebekka, Meinert Susanne, Hahn Tim, Dannlowski Udo, Grotegerd Dominik, Ciccarelli Mariateresa, Iasevoli Felice, Pontillo Giuseppe, Pearlson Godfrey D, Cobia Derin, Piras Fabrizio, Banaj Nerisa, Vecchio Daniela, Barendse Marjolein E A, van Haren Neeltje E M, Jo Hang Joon, Sim Kang, Quidé Yann, Green Melissa J, Slate Rachael, Cecere Giacomo, Omlor Wolfgang, Homan Stephanie, Homan Philipp, Thomopoulos Sophia I, Apulian Network on Risk for Psychosis, Turner Jessica A, van Erp Theo G M, Thompson Paul M, Bertolino Alessandro, Pergola Giulio
Аннотация
METHODS: Structural magnetic resonance imaging scans were obtained from 5197 participants (NC, n = 3409; FHR, n = 257; SCZ, n = 1531) across 32 cross-sectional samples within the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Consortium. Random-effects meta-analyses and network analyses were conducted on 1) local thalamic alterations (volume estimates of 7 thalamic subdivisions) and 2) network-wide thalamic alterations (thickness and surface-related thalamocortical/corticocortical covariation patterns) across groups (NC, FHR, SCZ).
RESULTS: Individuals with SCZ showed significantly lower gray matter volume estimates in the anterior, pulvinar, medial, posterior, and ventral thalamic subdivisions compared with NCs (false discovery rate-corrected q [qFDR] < .05). FHRs did not differ from NCs. At the network-wide level, thalamocortical covariations discriminated FHRs from NCs (qFDR < .05), with FHRs showing intermediate covariation between individuals with SCZ and NCs. Corticocortical covariation patterns revealed that individuals with SCZ and FHRs shared similarly disconnected clustering configurations, distinct from NCs (qFDR < .05).
CONCLUSIONS: Results revealed lower thalamic volume estimates in individuals with SCZ but not in FHRs, hence yielding no evidence of a familial risk trait, whereas thalamocortical and corticocortical covariation estimates were associated with familial risk for SCZ. These findings suggest that, once the thalamus is parsed into subdivisions, network-wide thalamocortical features may identify trait-dependent, neurobiological correlates of genetic risk for SCZ.