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While the hippocampus remains a region of high interest for neuropsychiatric research, the precise contributors to hippocampal morphometry are still not well understood. We and others previously reported a hippocampus specific effect of a tescalcin gene (TESC) regulating single nucleotide polymorphism (rs7294919) on gray matter volume. Here we aimed to replicate and extend these findings. Two complementary morphometric approaches (voxel based morphometry (VBM) and automated volumetric segmentation) were applied in a well-powered cohort from the Marburg-Münster Affective Disorder Cohort Study (MACS) including N=1137 participants (n=636 healthy controls, n=501 depressed patients). rs7294919 homozygous T-allele genotype was significantly associated with lower hippocampal gray matter density as well as with reduced hippocampal volume. Exploratory whole brain VBM analyses revealed no further associations with gray matter volume outside the hippocampus. No interaction effects of rs7294919 with depression nor with childhood trauma on hippocampal morphometry could be detected. Hippocampal subfield analyses revealed similar effects of rs7294919 in all hippocampal subfields. In sum, our results replicate a hippocampus specific effect of rs7294919 on brain structure. Due to the robust evidence for a pronounced association between the reported polymorphism and hippocampal morphometry, future research should consider investigating the potential clinical and functional relevance of the reported association.

The field of neuroimaging has embraced methods from machine learning in a variety of ways. Although an increasing number of initiatives have published open-access neuroimaging datasets, specifically designed benchmarks are rare in the field. In this article, we first describe how benchmarks in computer science and biomedical imaging have fostered methodological progress in machine learning. Second, we identify the special characteristics of neuroimaging data and outline what researchers have to ensure when establishing a neuroimaging benchmark, how datasets should be composed and how adequate evaluation criteria can be chosen. Based on lessons learned from machine learning benchmarks, we argue for an extended evaluation procedure that, next to applying suitable performance metrics, focuses on scientifically relevant aspects such as explainability, robustness, uncertainty, computational efficiency and code quality. Lastly, we envision a collaborative neuroimaging benchmarking platform that combines the discussed aspects in a collaborative and agile framework, allowing researchers across disciplines to work together on the key predictive problems of the field of neuroimaging and psychiatry.

Obesity has been associated with a variety of neurobiological alterations. Recent neuroimaging research has pointed to the relevance of brain structural and functional alterations in the development of obesity. However, while the role of gray matter atrophy in obesity has been evidenced in several well powered studies, large scale evidence for altered white matter integrity in obese subjects is still absent. With this study, we therefore aimed to investigate potential associations between white matter abnormalities and body mass index (BMI) in two large independent samples of healthy adults. Associations between BMI values and whole brain fractional anisotropy (FA) were investigated in two independent cohorts: A sample of n = 369 healthy subjects from the Munster Neuroimaging Cohort (MNC), as well as a public available sample of n = 1064 healthy subjects of the Humane Connectome Project (HCP) were included in the present study. Tract based spatial statistics (TBSS) analyses of BMI on whole brain FA were conducted including age and sex as nuisance covariates using the FMRIB library (FSL Version 5.0). Threshold-free cluster enhancement was applied to control for multiple comparisons. In both samples higher BMI was significantly associated with strong and widespread FA reductions. These effects were most pronounced in the corpus callosum, bilateral posterior thalamic radiation, bilateral internal capsule and external capsule, bilateral inferior longitudinal fasciculus and inferior fronto-occipital fasciculus. The association was found to be independent of age, sex and other cardiovascular risk factors. No significant positive associations between BMI and FA occurred. With this highly powered study, we provide robust evidence for globally reduced white matter integrity associated with elevated BMI including replication in an independent sample. The present work thus points out the relevance of white matter alterations as a neurobiological correlate of obesity.