Rapporteur summaries of plenary, symposia, and oral sessions from the XXIIIrd World Congress of Psychiatric Genetics Meeting in Toronto, Canada, 16-20 October 2015

The XXIIIrd World Congress of Psychiatric Genetics meeting, sponsored by the International Society of Psychiatric Genetics, was held in Toronto, ON, Canada, on 16-20 October 2015. Approximately 700 participants attended to discuss the latest state-of-the-art findings in this rapidly advancing and evolving field. The following report was written by trainee travel awardees. Each was assigned one session as a rapporteur. This manuscript represents the highlights and topics that were covered in the plenary sessions, symposia, and oral sessions during the conference, and contains major notable and new findings. © 2016 Wolters Kluwer Health, Inc

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

BACKGROUND: Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. METHODS: We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. RESULTS: Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. CONCLUSIONS: Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders

Can rate of brain atrophy in multiple sclerosis be explained by clinical and MRI characteristics?

INTRODUCTION: Multiple sclerosis (MS) is characterized, besides focal lesions, by brain atrophy. The determinants of atrophy rates in individual patients are poorly understood. AIM: This study investigated the predictive value of clinical and magnetic resonance imaging (MRI) factors, including short-term changes thereof, for concurrent and future atrophy evolution using Spearman's rank correlations and stepwise multiple linear regression. METHODS: We retrospectively identified a group of 115 active, early relapsing-remitting (RR) patients relatively homogeneous in terms of disease course and MRI activity compared to a second group of 96 patients with broader spectrum of MS phenotypes and inactive scans. All patients had undergone three MRI investigations with interscan intervals of at least 12 and 24 months, respectively. RESULTS: In the RR patients, 23% of variance in concurrent atrophy rates (over the first interval) could be explained by the combination of baseline T2 lesion volume and change in EDSS score over the first interval, whereas only 6% in future atrophy rates (over the second interval) was explained. In the heterogeneous group, 20.2% of the variance in future atrophy rates could be explained, but slightly less in concurrent atrophy rates (16.2%). CONCLUSION: We concluded that variance in brain atrophy rates can partially be explained by clinical and MRI measures of disease. Future atrophy rates in individual MS patients are difficult to predict even when including previous atrophy rates

Intercenter agreement of brain atrophy measurement in multiple sclerosis patients using manually-edited SIENA and SIENAX

PURPOSE: To investigate intercenter agreement of brain volume (change) measurement in multiple sclerosis (MS) using structural image evaluation using normalization of atrophy (SIENA) and the cross-sectional version of SIENA (SIENAX) with additional manual editing to correct for inadequate brain extraction. MATERIALS AND METHODS: Baseline and follow-up T1-weighted MR images of 20 MS patients were dispatched to five centers. Each center performed fully-automated and manually-edited analyses for SIENAX, yielding normalized brain volume (NBV), and SIENA, yielding percentage brain volume change (PBVC). Intercenter agreement was assessed with the concordance correlation coefficient (CCC). RESULTS: Intercenter agreement was perfect for fully automated NBV and PBVC (both CCC = 1.0), and remained substantial upon manual editing (CCC = 0.94 for NBV, CCC = 0.95 for PBVC). Mean NBV values for each center decreased significantly after manual editing (overall mean NBV = 1605.3 cm(3) vs. 1651.1 cm(3) without manual editing; t = -4.58, P < 0.001). Total variance in PBVC decreased significantly by a factor of 1.8 after manual editing (sigma(2) = 2.82 before, and sigma(2) = 1.54 after manual editing, P < 0.05). CONCLUSION: Substantial intercenter agreement was found for manually-edited SIENAX and SIENA, suggesting that measurements from multiple centers may be pooled. Manual editing reduces overestimation of NBV, and is likely to increase statistical power for PBVC