Publications by Year: 2018

2018
Hatzimanolis A, Avramopoulos D, Arking DE, Moes A, Bhatnagar P, Lencz T, Malhotra AK, Giakoumaki SG, Roussos P, Smyrnis N, et al. Stress-Dependent Association Between Polygenic Risk for Schizophrenia and Schizotypal Traits in Young Army Recruits. Schizophr Bull [Internet]. 2018;44(2):338-347. Publisher's VersionAbstract
Schizotypal personality traits may increase proneness to psychosis and likely index familial vulnerability to schizophrenia (SZ), implying shared genetic determinants with SZ. Here, we sought to investigate the contribution of common genetic risk variation for SZ on self-reported schizotypy in 2 ethnically homogeneous cohorts of healthy young males during compulsory military service, enrolled in the Athens Study of Proneness and Incidence of Schizophrenia (ASPIS, N = 875) and the Learning on Genetics of Schizophrenia Spectrum study (LOGOS, N = 690). A follow-up psychometric assessment was performed in a sub-sample of the ASPIS (N = 121), 18 months later at military service completion. Polygenic risk scores (PRS) for SZ were derived based on genome-wide association meta-analysis results from the Psychiatric Genomics Consortium. In the ASPIS, higher PRSSZ significantly associated with lower levels of positive (ie, perceptual distortions), disorganization and paranoid facets of schizotypy, whereas no association with negative (ie, interpersonal) facets was noted. Importantly, longitudinal data analysis in the ASPIS subsample revealed that PRSSZ was inversely associated with positive schizotypy at military induction (stressed condition) but not at follow-up (nonstressed condition), providing evidence for environmental rather than SZ-implicated genetic influences. Moreover, consistent with prior reports, PRSSZ was positively correlated with trait anxiety in the LOGOS and additionally the recruits with higher PRSSZ and trait anxiety exhibited attenuated paranoid ideation. Together, these findings do not support an etiological link between increased polygenic liability for SZ and schizotypy, suggesting that psychosocial stress or trait anxiety may impact schizotypal phenotypic expressions among healthy young adults not genetically predisposed to SZ.
Fish S, Toumaian M, Pappa E, Davies TJ, Tanti R, Saville CWN, Theleritis C, Economou M, Klein C, Smyrnis N. Modelling reaction time distribution of fast decision tasks in schizophrenia: Evidence for novel candidate endophenotypes. Psychiatry Research [Internet]. 2018;269:212 - 220. Website
Stefanatou P, Karatosidi C-S, Tsompanaki E, Kattoulas E, Stefanis NC, Smyrnis N. Premorbid adjustment predictors of cognitive dysfunction in schizophrenia. Psychiatry Research [Internet]. 2018;267:249 - 255. Website
Davies G, Lam M, Harris SE, Trampush JW, Luciano M, Hill DW, Hagenaars SP, Ritchie SJ, Marioni RE, Fawns-Ritchie C, et al. Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function. Nature communications. 2018;9:2098.
Valakos D, Karantinos T, Evdokimidis I, Stefanis NC, Avramopoulos D, Smyrnis N. Shared variance of oculomotor phenotypes in a large sample of healthy young men. Experimental Brain Research. 2018:1–12.
Salunkhe G, Weissbrodt K, Feige B, Saville CWN, Berger A, Dundon NM, Bender S, Smyrnis N, Beauducel A, Biscaldi M, et al. Examining the Overlap Between ADHD and Autism Spectrum Disorder (ASD) Using Candidate Endophenotypes of ADHD. Journal of attention disorders. 2018:1087054718778114.
Savage JE, Jansen PR, Stringer S, Watanabe K, Bryois J, de Leeuw CA, Nagel M, Awasthi S, Barr PB, Coleman JRI, et al. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence. Nature Genetics. 2018:1.
Lam M, Trampush JW, Yu J, Knowles E, Djurovic S, Melle I, Sundet K, Christoforou A, Reinvang I, DeRosse P, et al. Multi-Trait Analysis of GWAS and Biological Insights Into Cognition: A Response to Hill (2018). Twin Research and Human Genetics. 2018:1–4.
Korda AI, Asvestas PA, Matsopoulos GK, Ventouras EM, Smyrnis N. Automatic identification of eye movements using the largest lyapunov exponent. Biomedical Signal Processing and Control. 2018;41:10–20.