Neurocognitive phenotypes and genetic dissection of disorders of brain and behavior

Integrative omics analysis identifies differential biological pathways that are associated with regional grey matter volume changes in major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is accompanied by alterations in grey matter volume. However, the biological processes associated with regional structural perturbations remain elusive.

METHODS

We applied integrative omics analysis to investigate specialized transcriptome signatures and translational determinants associated with regional grey matter variations in 2737 MDD patients relative to 3098 controls by summarizing the results from gene co-expression network analysis of Allen human brain transcriptome profiles in six donors, enrichment analysis of gene-sets and cellular structure from rodents and mediation analysis of BrainSpan proteome profile in six donors.

RESULTS

We found convergent alterations of grey matter volume in MDD were associated with transcriptome profiles enriched for synaptic transmission, metabolism, immune processes and transmembrane transport. Genes with abnormal expression in post-mortem tissue in MDD were also associated with transcriptome signatures. Further gene co-expression network and enrichment analysis of MDD-related genes in these signatures revealed the modules with higher neuronal expression were enriched in the medial temporal cortex and temporo-parietal junction with genes differentially associated with neuronal development and metabolism. Also, the modules with higher non-neuronal (e.g. astrocyte and oligodendrocyte) expression were concentrated in the rostral and dorsal anterior cingulate cortex and were separately associated with immune response and transmembrane transport. Moreover, proteins as the gene expression products mediated the association between transcriptome signatures and brain volume changes in the visual and dorsolateral prefrontal cortex.

CONCLUSIONS

Our multidimensional analyses offer a novel approach to detect specific biological pathways that capture regional structural variations in MDD, which suggests structural endophenotypes associated with MDD.

Assessing inter-individual differences with task-related functional neuroimaging

Explaining and predicting individual behavioural differences induced by clinical and social factors constitutes one of the most promising applications of neuroimaging. In this Perspective, we discuss the theoretical and statistical foundations of the analyses of inter-individual differences in task-related functional neuroimaging. Leveraging a five-year literature review (July 2013-2018), we show that researchers often assess how activations elicited by a variable of interest differ between individuals. We argue that the rationale for such analyses, typically grounded in resource theory, offers an over-large analytical and interpretational flexibility that undermines their validity. We also recall how, in the established framework of the general linear model, inter-individual differences in behaviour can act as hidden moderators and spuriously induce differences in activations. We conclude with a set of recommendations and directions, which we hope will contribute to improving the statistical validity and the neurobiological interpretability of inter-individual difference analyses in task-related functional neuroimaging.

Behavioral and Psychological Phenotyping of Physical Activity and Sedentary Behavior: Implications for Weight Management

OBJECTIVE

Risk for obesity is determined by a complex mix of genetics and lifetime exposures at multiple levels, from the metabolic milieu to psychosocial and environmental influences. These phenotypic differences underlie the variability in risk for obesity and response to weight management interventions, including differences in physical activity and sedentary behavior.

METHODS

As part of a broader effort focused on behavioral and psychological phenotyping in obesity research, the National Institutes of Health convened a multidisciplinary workshop to explore the state of the science in behavioral and psychological phenotyping in humans to explain individual differences in physical activity, both as a risk factor for obesity development and in response to activity-enhancing interventions.

RESULTS

Understanding the behavioral and psychological phenotypes that contribute to differences in physical activity and sedentary behavior could allow for improved treatment matching and inform new targets for tailored, innovative, and effective weight management interventions.

CONCLUSIONS

This summary provides the rationale for identifying psychological and behavioral phenotypes relevant to physical activity and identifies opportunities for future research to better understand, define, measure, and validate putative phenotypic factors and characterize emerging phenotypes that are empirically associated with initiation of physical activity, response to intervention, and sustained changes in physical activity.

Systems biology and gene networks in neurodevelopmental and neurodegenerative disorders

Genetic and genomic approaches have implicated hundreds of genetic loci in neurodevelopmental disorders and neurodegeneration, but mechanistic understanding continues to lag behind the pace of gene discovery. Understanding the role of specific genetic variants in the brain involves dissecting a functional hierarchy that encompasses molecular pathways, diverse cell types, neural circuits and, ultimately, cognition and behaviour. With a focus on transcriptomics, this Review discusses how high-throughput molecular, integrative and network approaches inform disease biology by placing human genetics in a molecular systems and neurobiological context. We provide a framework for interpreting network biology studies and leveraging big genomics data sets in neurobiology.

Genomic view of bipolar disorder revealed by whole genome sequencing in a genetic isolate

Bipolar disorder is a common, heritable mental illness characterized by recurrent episodes of mania and depression. Despite considerable effort to elucidate the genetic underpinnings of bipolar disorder, causative genetic risk factors remain elusive. We conducted a comprehensive genomic analysis of bipolar disorder in a large Old Order Amish pedigree. Microsatellite genotypes and high-density SNP-array genotypes of 388 family members were combined with whole genome sequence data for 50 of these subjects, comprising 18 parent-child trios. This study design permitted evaluation of candidate variants within the context of haplotype structure by resolving the phase in sequenced parent-child trios and by imputation of variants into multiple unsequenced siblings. Non-parametric and parametric linkage analysis of the entire pedigree as well as on smaller clusters of families identified several nominally significant linkage peaks, each of which included dozens of predicted deleterious variants. Close inspection of exonic and regulatory variants in genes under the linkage peaks using family-based association tests revealed additional credible candidate genes for functional studies and further replication in population-based cohorts. However, despite the in-depth genomic characterization of this unique, large and multigenerational pedigree from a genetic isolate, there was no convergence of evidence implicating a particular set of risk loci or common pathways. The striking haplotype and locus heterogeneity we observed has profound implications for the design of studies of bipolar and other related disorders.

Bipolar disorder is a common, heritable mental illness characterized by recurrent episodes of mania and depression. Despite considerable efforts genetic studies have yet to reveal the precise genetic underpinnings of the disorder. In this study we have analyzed a large extended pedigree of Old Order Amish that segregates bipolar disorder. Our study design integrates both dense genotype and whole-genome sequence data. In a combined linkage and association analysis we identify five chromosomal regions with nominally significant or suggestive evidence for linkage, several of which constitute replication of earlier linkage findings for bipolar disorder in non-Amish families. Association analysis of genetic variants in each of the linkage regions yielded a number of plausible candidate genes for bipolar disorder. The striking genetic heterogeneity we observed in this genetic isolate has profound implications for the study of bipolar disorder in the general population.

Genes encoding heterotrimeric G-proteins are associated with gray matter volume variations in the medial frontal cortex

G-protein-coupled signal transduction mediates most cellular responses to hormones and neurotransmitters; this signaling system transduces a large variety of extracellular stimuli into neurons and is the most widely used mechanism for cell communication at the synaptic level. The heterotrimeric G-proteins have been well established as key regulators of neuronal growth, differentiation, and function. More recently, the heterotrimeric G-protein genes group was associated with general cognitive ability. Although heterotrimeric G-proteins are linked to both cognitive ability and neuron signaling, it is unknown whether heterotrimeric G-proteins are also important for brain structure. We tested for association between local cerebral gray matter volume and the heterotrimeric G-protein genes group in 294 subjects; a replication analysis was performed in an independent sample of 238 subjects. Voxel-based morphometry revealed a strong replicated association between 2 genes encoding heterotrimeric G-proteins with specific local increase in medial frontal cortex volume, an area known to be involved in cognitive control and negative affect. This finding suggests that heterotrimeric G-proteins might modulate medial frontal cortex gray matter volume. The differences in gray matter volume due to variations in genes encoding G-proteins may be explained by the role of G-proteins in prenatal and postnatal neocortex development.

Aberrant sodium channel activity in the complex seizure disorder of Celf4 mutant mice

Mice deficient for CELF4, a neuronal RNA-binding protein, have a complex seizure disorder that includes both convulsive and non-convulsive seizures, and is dependent upon Celf4 gene dosage and mouse strain background. It was previously shown that Celf4 is expressed predominantly in excitatory neurons, and that deficiency results in abnormal excitatory synaptic neurotransmission. To examine the physiological and molecular basis of this, we studied Celf4-deficient neurons in brain slices. Assessment of intrinsic properties of layer V cortical pyramidal neurons showed that neurons from mutant heterozygotes and homozygotes have a lower action potential (AP) initiation threshold and a larger AP gain when compared with wild-type neurons. Celf4 mutant neurons also demonstrate an increase in persistent sodium current (I(NaP)) and a hyperpolarizing shift in the voltage dependence of activation. As part of a related study, we find that CELF4 directly binds Scn8a mRNA, encoding sodium channel Na(v)1.6, the primary instigator of AP at the axon initial segment (AIS) and the main carrier of I(NaP). In the present study we find that CELF4 deficiency results in a dramatic elevation in the expression of Na(v)1.6 protein at the AIS in both null and heterozygous neurons. Together these results suggest that activation of Na(v)1.6 plays a crucial role in seizure generation in this complex model of neurological disease.

Discovering relations between mind, brain, and mental disorders using topic mapping

Neuroimaging research has largely focused on the identification of associations between brain activation and specific mental functions. Here we show that data mining techniques applied to a large database of neuroimaging results can be used to identify the conceptual structure of mental functions and their mapping to brain systems. This analysis confirms many current ideas regarding the neural organization of cognition, but also provides some new insights into the roles of particular brain systems in mental function. We further show that the same methods can be used to identify the relations between mental disorders. Finally, we show that these two approaches can be combined to empirically identify novel relations between mental disorders and mental functions via their common involvement of particular brain networks. This approach has the potential to discover novel endophenotypes for neuropsychiatric disorders and to better characterize the structure of these disorders and the relations between them.

One of the major challenges of neuroscience research is to integrate the results of the large number of published research studies in order to better understand how psychological functions are mapped onto brain systems. In this research, we take advantage of a large database of neuroimaging studies, along with text mining methods, to extract information about the topics that are found in the brain imaging literature and their mapping onto reported brain activation data. We also show that this method can be used to identify new relations between psychological functions and mental disorders, through their shared brain activity patterns. This work provides a new way to discover the underlying structure that relates brain function and mental processes.

The neurobehavior ontology: an ontology for annotation and integration of behavior and behavioral phenotypes

In recent years, considerable advances have been made toward our understanding of the genetic architecture of behavior and the physical, mental, and environmental influences that underpin behavioral processes. The provision of a method for recording behavior-related phenomena is necessary to enable integrative and comparative analyses of data and knowledge about behavior. The neurobehavior ontology facilitates the systematic representation of behavior and behavioral phenotypes, thereby improving the unification and integration behavioral data in neuroscience research.