Hippocampus Shape Analysis and Late-Life Depression

Major depression in the elderly is associated with brain structural changes and vascular lesions. Changes in the subcortical regions of the limbic system have also been noted. Studies examining hippocampus volumetric differences in depression have shown variable results, possibly due to any volume differences being secondary to local shape changes rather than differences in the overall volume. Shape analysis offers the potential to detect such changes. The present study applied spherical harmonic (SPHARM) shape analysis to the left and right hippocampi of 61 elderly subjects with major depression and 43 non-depressed elderly subjects. Statistical models controlling for age, sex, and total cerebral volume showed a significant reduction in depressed compared with control subjects in the left hippocampus (F1,103 = 5.26; p = 0.0240) but not right hippocampus volume (F1,103 = 0.41; p = 0.5213). Shape analysis showed significant differences in the mid-body of the left (but not the right) hippocampus between depressed and controls. When the depressed group was dichotomized into those whose depression was remitted at time of imaging and those who were unremitted, the shape comparison showed remitted subjects to be indistinguishable from controls (both sides) while the unremitted subjects differed in the midbody and the lateral side near the head. Hippocampal volume showed no difference between controls and remitted subjects but nonremitted subjects had significantly smaller left hippocampal volumes with no significant group differences in the right hippocampus. These findings may provide support to other reports of neurogenic effects of antidepressants and their relation to successful treatment for depressive symptoms

'Omic approaches to preventing or managing metastatic breast cancer

Early detection of metastasis-prone breast cancers and characterization of residual metastatic cancers are important in efforts to improve management of breast cancer. Applications of genome-scale molecular analysis technologies are making these complementary approaches possible by revealing molecular features uniquely associated with metastatic disease. Assays that reveal these molecular features will facilitate development of anatomic, histological and blood-based strategies that may enable detection prior to metastatic spread. Knowledge of these features also will guide development of therapeutic strategies that can be applied when metastatic disease burden is low, thereby increasing the probability of a curative response

PEDIA: prioritization of exome data by image analysis

Purpose Phenotype information is crucial for the interpretation of genomic variants. So far it has only been accessible for bioinformatics workflows after encoding into clinical terms by expert dysmorphologists. Methods Here, we introduce an approach driven by artificial intelligence that uses portrait photographs for the interpretation of clinical exome data. We measured the value added by computer-assisted image analysis to the diagnostic yield on a cohort consisting of 679 individuals with 105 different monogenic disorders. For each case in the cohort we compiled frontal photos, clinical features, and the disease-causing variants, and simulated multiple exomes of different ethnic backgrounds. Results The additional use of similarity scores from computer-assisted analysis of frontal photos improved the top 1 accuracy rate by more than 20–89% and the top 10 accuracy rate by more than 5–99% for the disease-causing gene. Conclusion Image analysis by deep-learning algorithms can be used to quantify the phenotypic similarity (PP4 criterion of the American College of Medical Genetics and Genomics guidelines) and to advance the performance of bioinformatics pipelines for exome analysis

Exploration of Shared Genetic Architecture Between Subcortical Brain Volumes and Anorexia Nervosa

In MRI scans of patients with anorexia nervosa (AN), reductions in brain volume are often apparent. However, it is unknown whether such brain abnormalities are influenced by genetic determinants that partially overlap with those underlying AN. Here, we used a battery of methods (LD score regression, genetic risk scores, sign test, SNP effect concordance analysis, and Mendelian randomization) to investigate the genetic covariation between subcortical brain volumes and risk for AN based on summary measures retrieved from genome-wide association studies of regional brain volumes (ENIGMA consortium, n = 13,170) and genetic risk for AN (PGC-ED consortium, n = 14,477). Genetic correlations ranged from − 0.10 to 0.23 (all p > 0.05). There were some signs of an inverse concordance between greater thalamus volume and risk for AN (permuted p = 0.009, 95% CI: [0.005, 0.017]). A genetic variant in the vicinity of ZW10, a gene involved in cell division, and neurotransmitter and immune system relevant genes, in particular DRD2, was significantly associated with AN only after conditioning on its association with caudate volume (pFDR = 0.025). Another genetic variant linked to LRRC4C, important in axonal and synaptic development, reached significance after conditioning on hippocampal volume (pFDR = 0.021). In this comprehensive set of analyses and based on the largest available sample sizes to date, there was weak evidence for associations between risk for AN and risk for abnormal subcortical brain volumes at a global level (that is, common variant genetic architecture), but suggestive evidence for effects of single genetic markers. Highly powered multimodal brain- and disorder-related genome-wide studies are needed to further dissect the shared genetic influences on brain structure and risk for AN

Cortisol, cognition and the ageing prefrontal cortex

The structural and functional decline of the ageing human brain varies by brain region, cognitive function and individual. The underlying biological mechanisms are poorly understood. One potentially important mechanism is exposure to glucocorticoids (GCs; cortisol in humans); GC production is increasingly varied with age in humans, and chronic exposure to high levels is hypothesised to result in cognitive decline via cerebral remodelling. However, studies of GC exposure in humans are scarce and methodological differences confound cross-study comparison. Furthermore, there has been little focus on the effects of GCs on the frontal lobes and key white matter tracts in the ageing brain. This thesis therefore examines relationships among cortisol levels, structural brain measures and cognitive performance in 90 healthy, elderly community-dwelling males from the Lothian Birth Cohort 1936. Salivary cortisol samples characterised diurnal (morning and evening) and reactive profiles (before and after a cognitive test battery). Structural variables comprised Diffusion Tensor Imaging measures of major brain tracts and a novel manual parcellation method for the frontal lobes. The latter was based on a systematic review of current manual methods in the context of putative function and cytoarchitecture. Manual frontal lobe brain parcellation conferred greater spatial and volumetric accuracy when compared to both single- and multi-atlas parcellation at the lobar level. Cognitive ability was assessed via tests of general cognitive ability, and neuropsychological tests thought to show differential sensitivity to the integrity of frontal lobe sub-regions. The majority of, but not all frontal lobe test scores shared considerable overlap with general cognitive ability, and cognitive scores correlated most consistently with the volumes of the anterior cingulate. This is discussed in light of the diverse connective profile of the cingulate and a need to integrate information over more diffuse cognitive networks according to proposed de-differentiation or compensation in ageing. Individuals with higher morning, evening or pre-test cortisol levels showed consistently negative relationships with specific regional volumes and tract integrity. Participants whose cortisol levels increased between the start and end of cognitive testing showed selectively larger regional volumes and lower tract diffusivity (correlation magnitudes <.44). The significant relationships between cortisol levels and cognition indicated that flatter diurnal slopes or higher pre-test levels related to poorer test performance. In contrast, higher levels in the morning generally correlated with better scores (correlation magnitudes <.25). Interpretation of all findings was moderated by sensitivity to type I error, given the large number of comparisons conducted. Though there were limited candidates for mediation analysis, cortisol-function relationships were partially mediated by tract integrity (but not sub-regional frontal volumes) for memory and post-error slowing. This thesis offers a novel perspective on the complex interplay among glucocorticoids, cognition and the structure of the ageing brain. The findings suggest some role for cortisol exposure in determining age-related decline in complex cognition, mediated via brain structure

Microenvironmental regulation of metastasis

Metastasis is a multistage process that requires cancer cells to escape from the primary tumour, survive in the circulation, seed at distant sites and grow. Each of these processes involves rate-limiting steps that are influenced by non-malignant cells of the tumour microenvironment. Many of these cells are derived from the bone marrow, particularly the myeloid lineage, and are recruited by cancer cells to enhance their survival, growth, invasion and dissemination. This Review describes experimental data demonstrating the role of the microenvironment in metastasis, identifies areas for future research and suggests possible new therapeutic avenues