We recently surveyed the relationship between the human brain transcriptome and genome in a series of neuropathologically normal postmortem samples. We have now analyzed additional samples with a confirmed pathologic diagnosis of late-onset Alzheimer disease (LOAD; final n = 188 controls, 176 cases). Nine percent of the cortical transcripts that we analyzed had expression profiles correlated with their genotypes in the combined cohort, and approximately 5% of transcripts had SNP-transcript relationships that could distinguish LOAD samples. Two of these transcripts have been previously implicated in LOAD candidate-gene SNP-expression screens. This study shows how the relationship between common inherited genetic variants and brain transcript expression can be used in the study of human brain disorders. We suggest that studying the transcriptome as a quantitative endo-phenotype has greater power for discovering risk SNPs influencing expression than the use of discrete diagnostic categories such as presence or absence of disease.
We have defined a strategy for treatment of patients with advanced-stage ovarian cancer that uses therapeutic stratification based on predictions of response to chemotherapy, coupled with prediction of oncogenic pathway deregulation, as a method to direct the use of targeted agents.
Aims Recent research has revealed that early life trauma (ELS), including abuse (sexual and/or physical) and neglect, produce lasting changes in the CNS. We posited that cognitive deficits, often observed in psychiatric patients, result, in part, due to the neurobiological consequences of ELS. Additionally, we hypothesized that the nature and magnitude of cognitive deficits would differ according to the subtype of ELS experienced. Method The Cambridge Neuropsychological Test Automated Battery (CANTAB) was used to assess neurocognitive functioning in 93 subjects (60 with ELS and 33 without). In the patients with a history of ELS, 35% and 16.7%, respectively, met criteria for current major depression and PTSD. Results Significant associations between ELS status and CANTAB measures of memory and executive and emotional functioning were found. Conclusions These data suggest that exposure to ELS results in a cascade of neurobiological changes associated with cognitive deficits in adulthood that vary according to the type of trauma experienced.
Given the powerful implications of relationship quality for health and well-being, a central mission of relationship science is explaining why some romantic relationships thrive more than others. This large-scale project used machine learning (i.e., Random Forests) to 1) quantify the extent to which relationship quality is predictable and 2) identify which constructs reliably predict relationship quality. Across 43 dyadic longitudinal datasets from 29 laboratories, the top relationship-specific predictors of relationship quality were perceived-partner commitment, appreciation, sexual satisfaction, perceived-partner satisfaction, and conflict. The top individual-difference predictors were life satisfaction, negative affect, depression, attachment avoidance, and attachment anxiety. Overall, relationship-specific variables predicted up to 45% of variance at baseline, and up to 18% of variance at the end of each study. Individual differences also performed well (21% and 12%, respectively). Actor-reported variables (i.e., own relationship-specific and individual-difference variables) predicted two to four times more variance than partner-reported variables (i.e., the partner’s ratings on those variables). Importantly, individual differences and partner reports had no predictive effects beyond actor-reported relationship-specific variables alone. These findings imply that the sum of all individual differences and partner experiences exert their influence on relationship quality via a person’s own relationship-specific experiences, and effects due to moderation by individual differences and moderation by partner-reports may be quite small. Finally, relationship-quality change (i.e., increases or decreases in relationship quality over the course of a study) was largely unpredictable from any combination of self-report variables. This collective effort should guide future models of relationships.
Breast cancer is the most common cancer in women, and this prevalence has a major impact on health worldwide. Localized breast cancer has an excellent prognosis, with a 5-year relative survival rate of 85%. However, the survival rate drops to only 23% for women with distant metastases. To date, the study of breast cancer metastasis has been hampered by a lack of reliable metastatic models. Here we describe a novel in vivo model using human breast cancer xenografts in NOD scid gamma (NSG) mice; in this model human breast cancer cells reliably metastasize to distant organs from primary tumors grown within the mammary fat pad. This model enables the study of the entire metastatic process from the proper anatomical site, providing an important new approach to examine the mechanisms underlying breast cancer metastasis. We used this model to identify gene expression changes that occur at metastatic sites relative to the primary mammary fat pad tumor. By comparing multiple metastatic sites and independent cell lines, we have identified several gene expression changes that may be important for tumor growth at distant sites.
BackgroundOne way to improve both the ecological performance and functionality of probiotic bacteria is by combining them with a prebiotic in the form of a synbiotic. However, the degree to which such synbiotic formulations improve probiotic strain functionality in humans has not been tested systematically. Our goal was to use a randomized, double-blind, placebo-controlled, parallel-arm clinical trial in obese humans to compare the ecological and physiological impact of the prebiotic galactooligosaccharides (GOS) and the probiotic strains Bifidobacterium adolescentis IVS-1 (autochthonous and selected via in vivo selection) and Bifidobacterium lactis BB-12 (commercial probiotic allochthonous to the human gut) when used on their own or as synbiotic combinations. After 3 weeks of consumption, strain-specific quantitative real-time PCR and 16S rRNA gene sequencing were performed on fecal samples to assess changes in the microbiota. Intestinal permeability was determined by measuring sugar recovery in urine by GC after consumption of a sugar mixture. Serum-based endotoxin exposure was also assessed.ResultsIVS-1 reached significantly higher cell numbers in fecal samples than BB-12 (P < 0.01) and, remarkably, its administration induced an increase in total bifidobacteria that was comparable to that of GOS. Although GOS showed a clear bifidogenic effect on the resident gut microbiota, both probiotic strains showed only a non-significant trend of higher fecal cell numbers when administered with GOS. Post-aspirin sucralose:lactulose ratios were reduced in groups IVS-1 (P = 0.050), IVS-1 + GOS (P = 0.022), and GOS (P = 0.010), while sucralose excretion was reduced with BB-12 (P = 0.002) and GOS (P = 0.020), indicating improvements in colonic permeability but no synergistic effects. No changes in markers of endotoxemia were observed.ConclusionThis study demonstrated that “autochthony” of the probiotic strain has a larger effect on ecological performance than the provision of a prebiotic substrate, likely due to competitive interactions with members of the resident microbiota. Although the synbiotic combinations tested in this study did not demonstrate functional synergism, our findings clearly showed that the pro- and prebiotic components by themselves improved markers of colonic permeability, providing a rational for their use in pathologies with an underlying leakiness of the gut.Electronic supplementary materialThe online version of this article (10.1186/s40168-018-0494-4) contains supplementary material, which is available to authorized users.
Quantitative proteomics analysis of cortical samples of ten Alzheimer's disease (AD) brains versus ten normally aged brains was performed by following the accurate mass and time tag (AMT) approach with the high resolution LTQ Orbitrap mass spectrometer. More than 1400 proteins were identified and quantitated. A conservative approach of selecting only the consensus results of four normalization methods was suggested and used. A total of 197 proteins were shown to be significantly differentially abundant (p-values<0.05, corrected for multiplicity of testing) in AD versus control brain samples. Thirty seven of these proteins were reported as differentially abundant or modified in AD in the previous proteomics and transcriptomics publications. The rest to the best of our knowledge are new. Mapping of the discovered proteins with bioinformatic tools revealed significant enrichment with differentially abundant proteins of pathways and processes known to be important in AD, including signal transduction, regulation of protein phosphorylation, immune response, cytoskeleton organization, lipid metabolism, energy production, and cell death.
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