Identification of gene ontologies linked to prefrontal-hippocampal functional coupling in the human brain

The Emerging Neurobiology of Bipolar Disorder

(Reprinted with permission from Trends in Neurosciences, January 2018, Vol. 41, No. 1 ).

Baby brain atlases

The baby brain is constantly changing due to its active neurodevelopment, and research into the baby brain is one of the frontiers in neuroscience. To help guide neuroscientists and clinicians in their investigation of this frontier, maps of the baby brain, which contain a priori knowledge about neurodevelopment and anatomy, are essential. "Brain atlas" in this review refers to a 3D-brain image with a set of reference labels, such as a parcellation map, as the anatomical reference that guides the mapping of the brain. Recent advancements in scanners, sequences, and motion control methodologies enable the creation of various types of high-resolution baby brain atlases. What is becoming clear is that one atlas is not sufficient to characterize the existing knowledge about the anatomical variations, disease-related anatomical alterations, and the variations in time-dependent changes. In this review, the types and roles of the human baby brain MRI atlases that are currently available are described and discussed, and future directions in the field of developmental neuroscience and its clinical applications are proposed. The potential use of disease-based atlases to characterize clinically relevant information, such as clinical labels, in addition to conventional anatomical labels, is also discussed.

Brain-derived neurotrophic factor Val66Met genotype and ovarian steroids interactively modulate working memory-related hippocampal function in women: a multimodal neuroimaging study

Preclinical evidence suggests that the actions of ovarian steroid hormones and brain-derived neurotrophic factor (BDNF) are highly convergent on brain function. Studies in humanized mice document an interaction between estrus cycle-related changes in estradiol secretion and BDNF Val⁶⁶Met genotype on measures of hippocampal function and anxiety-like behavior. We believe our multimodal imaging data provide the first demonstration in women that the effects of the BDNF Val/Met polymorphism on hippocampal function are selectively modulated by estradiol. In a 6-month pharmacological hormone manipulation protocol, healthy, regularly menstruating, asymptomatic women completed positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) scans while performing the n-back working memory task during three hormone conditions: ovarian suppression induced by the gonadotropin-releasing hormone agonist, leuprolide acetate; leuprolide plus estradiol; and leuprolide plus progesterone. For each of the three hormone conditions, a discovery data set was obtained with oxygen-15 water regional cerebral blood flow PET in 39 healthy women genotyped for BDNF Val⁶⁶Met, and a confirmatory data set was obtained with fMRI in 27 women. Our results, in close agreement across the two imaging platforms, demonstrate an ovarian hormone-by-BDNF interaction on working memory-related hippocampal function (PET: F_2,37=9.11, P=0.00026 uncorrected, P=0.05, familywise error corrected with small volume correction; fMRI: F_2,25=5.43, P=0.01, uncorrected) that reflects differential hippocampal recruitment in Met carriers but only in the presence of estradiol. These findings have clinical relevance for understanding the neurobiological basis of individual differences in the cognitive and behavioral effects of ovarian steroids in women, and may provide a neurogenetic framework for understanding neuropsychiatric disorders related to reproductive hormones as well as illnesses with sex differences in disease expression and course.

The Emerging Neurobiology of Bipolar Disorder

Bipolar disorder (BD) is a leading cause of global disability. Its biological basis is unknown, and its treatment unsatisfactory. Here, we review two recent areas of progress. First, the discovery of risk genes and their implications, with a focus on voltage-gated calcium channels as part of the disease process and as a drug target. Second, facilitated by new technologies, it is increasingly apparent that the bipolar phenotype is more complex and nuanced than simply one of recurring manic and depressive episodes. One such feature is persistent mood instability, and efforts are underway to understand its mechanisms and its therapeutic potential. BD illustrates how psychiatry is being transformed by contemporary neuroscience, genomics, and digital approaches.

Gene Set Enrichment Analyses: lessons learned from the heart failure phenotype

BACKGROUND

Genetic studies for complex diseases have predominantly discovered main effects at individual loci, but have not focused on genomic and environmental contexts important for a phenotype. Gene Set Enrichment Analysis (GSEA) aims to address this by identifying sets of genes or biological pathways contributing to a phenotype, through gene-gene interactions or other mechanisms, which are not the focus of conventional association methods.

RESULTS

Approaches that utilize GSEA can now take input from array chips, either gene-centric or genome-wide, but are highly sensitive to study design, SNP selection and pruning strategies, SNP-to-gene mapping, and pathway definitions. Here, we present lessons learned from our experience with GSEA of heart failure, a particularly challenging phenotype due to its underlying heterogeneous etiology.

CONCLUSIONS

This case study shows that proper data handling is essential to avoid false-positive results. Well-defined pipelines for quality control are needed to avoid reporting spurious results using GSEA.

Molecular genetic aetiology of general cognitive function is enriched in evolutionarily conserved regions

Differences in general cognitive function have been shown to be partly heritable and to show genetic correlations with several psychiatric and physical disease states. However, to date, few single-nucleotide polymorphisms (SNPs) have demonstrated genome-wide significance, hampering efforts aimed at determining which genetic variants are most important for cognitive function and which regions drive the genetic associations between cognitive function and disease states. Here, we combine multiple large genome-wide association study (GWAS) data sets, from the CHARGE cognitive consortium (n=53 949) and UK Biobank (n=36 035), to partition the genome into 52 functional annotations and an additional 10 annotations describing tissue-specific histone marks. Using stratified linkage disequilibrium score regression we show that, in two measures of cognitive function, SNPs associated with cognitive function cluster in regions of the genome that are under evolutionary negative selective pressure. These conserved regions contained ~2.6% of the SNPs from each GWAS but accounted for ~40% of the SNP-based heritability. The results suggest that the search for causal variants associated with cognitive function, and those variants that exert a pleiotropic effect between cognitive function and health, will be facilitated by examining these enriched regions.

Biomarkers of postoperative delirium and cognitive dysfunction

Elderly surgical patients frequently experience postoperative delirium (POD) and the subsequent development of postoperative cognitive dysfunction (POCD). Clinical features include deterioration in cognition, disturbance in attention and reduced awareness of the environment and result in higher morbidity, mortality and greater utilization of social financial assistance. The aging Western societies can expect an increase in the incidence of POD and POCD. The underlying pathophysiological mechanisms have been studied on the molecular level albeit with unsatisfying small research efforts given their societal burden. Here, we review the known physiological and immunological changes and genetic risk factors, identify candidates for further studies and integrate the information into a draft network for exploration on a systems level. The pathogenesis of these postoperative cognitive impairments is multifactorial; application of integrated systems biology has the potential to reconstruct the underlying network of molecular mechanisms and help in the identification of prognostic and diagnostic biomarkers.