Genomics of lithium action and response

Lithium is the most successful mood stabiliser treatment for bipolar disorder. However, unlike conventional drugs that are designed to interact with a specific molecular target, the actions of lithium are distributed across many biological processes and pathways. Treatment response is subject to genetic variation between individuals and similar genetic variation may dictate susceptibility to side-effects. Transcriptomic, genomic and cell model research strategies have all been deployed in the search for the genetic factors and biological systems that mediate the interaction between genetics and the therapeutic actions of lithium. In this review, recent findings from genome-wide studies and patient cell lines will be summarised and discussed from a standpoint that genuine progress is being made to define clinically useful mechanisms of this treatment, to place it in the context of bipolar disorder pathology, and to move towards a time when the prescription of lithium is targeted to those individuals who will derive the greatest benefit

Loss of CSMD1 expression disrupts mammary duct formation while enhancing proliferation, migration and invasion

The CUB and sushi multiple domains 1 (CSMD1) gene maps to chromosome 8p23, a region deleted in many cancers. Loss of CSMD1 expression is associated with poor prognosis in breast cancer suggesting that it acts as a tumour suppressor in this cancer. However, the function of CSMD1 is largely unknown. Herein, we investigated CSMD1 functions in cell line models. CSMD1 expression was suppressed in MCF10A and LNCaP cells using short hairpin RNA. Functional assays were performed focusing on the 'normal' MCF10A cell line. Suppression of CSMD1 significantly increased the proliferation, cell migration and invasiveness of MCF10A cells compared to shcontrols. shCSMD1 cells also showed significantly reduced adhesion to Matrigel and fibronectin. In a three-dimensional Matrigel model of MCF10A cells, reduced CSMD1 expression resulted in the development of larger and more poorly differentiated breast acini-like structures that displayed impaired lumen formation. Loss of CSMD1 expression disrupts a model of mammary duct formation while enhancing proliferation, migration and invasion. Our data suggest that CSMD1 is involved in the suppression of a transformed phenotype

Detection of circulating tumour DNA is associated with inferior outcomes in Ewing sarcoma and osteosarcoma: a report from the Children's Oncology Group.

BackgroundNew prognostic markers are needed to identify patients with Ewing sarcoma (EWS) and osteosarcoma unlikely to benefit from standard therapy. We describe the incidence and association with outcome of circulating tumour DNA (ctDNA) using next-generation sequencing (NGS) assays.MethodsA NGS hybrid capture assay and an ultra-low-pass whole-genome sequencing assay were used to detect ctDNA in banked plasma from patients with EWS and osteosarcoma, respectively. Patients were coded as positive or negative for ctDNA and tested for association with clinical features and outcome.ResultsThe analytic cohort included 94 patients with EWS (82% from initial diagnosis) and 72 patients with primary localised osteosarcoma (100% from initial diagnosis). ctDNA was detectable in 53% and 57% of newly diagnosed patients with EWS and osteosarcoma, respectively. Among patients with newly diagnosed localised EWS, detectable ctDNA was associated with inferior 3-year event-free survival (48.6% vs. 82.1%; p = 0.006) and overall survival (79.8% vs. 92.6%; p = 0.01). In both EWS and osteosarcoma, risk of event and death increased with ctDNA levels.ConclusionsNGS assays agnostic of primary tumour sequencing results detect ctDNA in half of the plasma samples from patients with newly diagnosed EWS and osteosarcoma. Detectable ctDNA is associated with inferior outcomes

A Genetic Deconstruction of Neurocognitive Traits in Schizophrenia and Bipolar Disorder

Background: Impairments in cognitive functions are common in patients suffering from psychiatric disorders, such as schizophrenia and bipolar disorder. Cognitive traits have been proposed as useful for understanding the biological and genetic mechanisms implicated in cognitive function in healthy individuals and in the dysfunction observed in psychiatric disorders. Methods: Sets of genes associated with a range of cognitive functions often impaired in schizophrenia and bipolar disorder were generated from a genome-wide association study (GWAS) on a sample comprising 670 healthy Norwegian adults who were phenotyped for a broad battery of cognitive tests. These gene sets were then tested for enrichment of association in GWASs of schizophrenia and bipolar disorder. The GWAS data was derived from three independent single-centre schizophrenia samples, three independent single-centre bipolar disorder samples, and the multi-centre schizophrenia and bipolar disorder samples from the Psychiatric Genomics Consortium. Results: The strongest enrichments were observed for visuospatial attention and verbal abilities sets in bipolar disorder. Delayed verbal memory was also enriched in one sample of bipolar disorder. For schizophrenia, the strongest evidence of enrichment was observed for the sets of genes associated with performance in a colour-word interference test and for sets associated with memory learning slope. Conclusions: Our results are consistent with the increasing evidence that cognitive functions share genetic factors with schizophrenia and bipolar disorder. Our data provides evidence that genetic studies using polygenic and pleiotropic models can be used to link specific cognitive functions with psychiatric disorders

Increasing power for voxel-wise genome-wide association studies : the random field theory, least square kernel machines and fast permutation procedures

Imaging traits are thought to have more direct links to genetic variation than diagnostic measures based on cognitive or clinical assessments and provide a powerful substrate to examine the influence of genetics on human brains. Although imaging genetics has attracted growing attention and interest, most brain-wide genome-wide association studies focus on voxel-wise single-locus approaches, without taking advantage of the spatial information in images or combining the effect of multiple genetic variants. In this paper we present a fast implementation of voxel- and cluster-wise inferences based on the random field theory to fully use the spatial information in images. The approach is combined with a multi-locus model based on least square kernel machines to associate the joint effect of several single nucleotide polymorphisms (SNP) with imaging traits. A fast permutation procedure is also proposed which significantly reduces the number of permutations needed relative to the standard empirical method and provides accurate small p-value estimates based on parametric tail approximation. We explored the relation between 448,294 single nucleotide polymorphisms and 18,043 genes in 31,662 voxels of the entire brain across 740 elderly subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Structural MRI scans were analyzed using tensor-based morphometry (TBM) to compute 3D maps of regional brain volume differences compared to an average template image based on healthy elderly subjects. We find method to be more sensitive compared with voxel-wise single-locus approaches. A number of genes were identified as having significant associations with volumetric changes. The most associated gene was GRIN2B, which encodes the N-methyl-d-aspartate (NMDA) glutamate receptor NR2B subunit and affects both the parietal and temporal lobes in human brains. Its role in Alzheimer's disease has been widely acknowledged and studied, suggesting the validity of the approach. The various advantages over existing approaches indicate a great potential offered by this novel framework to detect genetic influences on human brains

Analysis of Germline Gene Copy Number Variants of Patients with Sporadic Pancreatic Adenocarcinoma Reveals Specific Variations

Objectives: The rapid fatality of pancreatic cancer is, in large part, the result of diagnosis at an advanced stage in the majority of patients. Identification of individuals at risk of developing pancreatic adenocarcinoma would be useful to improve the prognosis of this disease. There is presently no biological or genetic indicator allowing the detection of patients at risk. Our main goal was to identify copy number variants (CNVs) common to all patients with sporadic pancreatic cancer. Methods: We analyzed gene CNVs in leukocyte DNA from 31 patients with sporadic pancreatic adenocarcinoma and from 93 matched controls. Genotyping was performed with the use of the GeneChip Human Mapping 500K Array Set (Affymetrix). Results: We identified 431 single nucleotide polymorphism (SNP) probes with abnormal hy-bridization signal present in the DNA of all 31 patients. Of these SNP probes, 284 corresponded to 3 or more copies and 147 corresponded to 1 or 0 copies. Several cancer-associated genes were amplified in all patients. Conversely, several genes supposed to oppose cancer development were present as single copy. Conclusions: These data suggest that a set of 431 CNVs could be associated with the disease. This set could be useful for early diagnosis

Genetically predicted complement component 4A expression: effects on memory function and middle temporal lobe activation

Background The longstanding association between the major histocompatibility complex (MHC) locus and schizophrenia (SZ) risk has recently been accounted for, partially, by structural variation at the complement component 4 (C4) gene. This structural variation generates varying levels of C4 RNA expression, and genetic information from the MHC region can now be used to predict C4 RNA expression in the brain. Increased predicted C4A RNA expression is associated with the risk of SZ, and C4 is reported to influence synaptic pruning in animal models. Methods Based on our previous studies associating MHC SZ risk variants with poorer memory performance, we tested whether increased predicted C4A RNA expression was associated with reduced memory function in a large (n = 1238) dataset of psychosis cases and healthy participants, and with altered task-dependent cortical activation in a subset of these samples. Results We observed that increased predicted C4A RNA expression predicted poorer performance on measures of memory recall (p = 0.016, corrected). Furthermore, in healthy participants, we found that increased predicted C4A RNA expression was associated with a pattern of reduced cortical activity in middle temporal cortex during a measure of visual processing (p < 0.05, corrected). Conclusions These data suggest that the effects of C4 on cognition were observable at both a cortical and behavioural level, and may represent one mechanism by which illness risk is mediated. As such, deficits in learning and memory may represent a therapeutic target for new molecular developments aimed at altering C4’s developmental role