157 research outputs found

    Recommendations for Bayesian hierarchical model specifications for case-control studies in mental health

    Full text link
    Hierarchical model fitting has become commonplace for case-control studies of cognition and behaviour in mental health. However, these techniques require us to formalise assumptions about the data-generating process at the group level, which may not be known. Specifically, researchers typically must choose whether to assume all subjects are drawn from a common population, or to model them as deriving from separate populations. These assumptions have profound implications for computational psychiatry, as they affect the resulting inference (latent parameter recovery) and may conflate or mask true group-level differences. To test these assumptions we ran systematic simulations on synthetic multi-group behavioural data from a commonly used multi-armed bandit task (reinforcement learning task). We then examined recovery of group differences in latent parameter space under the two commonly used generative modelling assumptions: (1) modelling groups under a common shared group-level prior (assuming all participants are generated from a common distribution, and are likely to share common characteristics); (2) modelling separate groups based on symptomatology or diagnostic labels, resulting in separate group-level priors. We evaluated the robustness of these approaches to variations in data quality and prior specifications on a variety of metrics. We found that fitting groups separately (assumptions 2), provided the most accurate and robust inference across all conditions. Our results suggest that when dealing with data from multiple clinical groups, researchers should analyse patient and control groups separately as it provides the most accurate and robust recovery of the parameters of interest.Comment: Machine Learning for Health (ML4H) at NeurIPS 2020 - Extended Abstrac

    Power-up: a reanalysis of 'power failure' in neuroscience using mixture modelling

    Get PDF
    Evidence for endemically low statistical power has recently cast neuroscience findings into doubt. If low statistical power plagues neuroscience, this reduces confidence in reported effects. However, if statistical power is not uniformly low, such blanket mistrust might not be warranted. Here, we provide a different perspective on this issue, analysing data from an influential paper reporting a median power of 21% across 49 meta-analyses (Button et al., 2013). We demonstrate, using Gaussian mixture modelling, that the sample of 730 studies included in that analysis comprises several subcomponents; therefore the use of a single summary statistic is insufficient to characterise the nature of the distribution. We find that statistical power is extremely low for studies included in meta-analyses that reported a null result; and that it varies substantially across subfields of neuroscience, with particularly low power in candidate gene association studies. Thus, while power in neuroscience remains a critical issue, the notion that studies are systematically underpowered is not the full story: low power is far from a universal problem. SIGNIFICANCE STATEMENT: Recently, researchers across the biomedical and psychological sciences have become concerned with the reliability of results. One marker for reliability is statistical power: the probability of finding a statistically significant result, given that the effect exists. Previous evidence suggests that statistical power is low across the field of neuroscience. Our results present a more comprehensive picture of statistical power in neuroscience: on average, studies are indeed underpowered-some very seriously so-but many studies show acceptable or even exemplary statistical power. We show that this heterogeneity in statistical power is common across most subfields in neuroscience (psychology, neuroimaging, etc.). This new, more nuanced picture of statistical power in neuroscience could affect not only scientific understanding, but potentially policy and funding decisions for neuroscience research

    The impact of induced anxiety on affective response inhibition

    Get PDF
    Studying the effects of experimentally induced anxiety in healthy volunteers may increase our understanding of the mechanisms underpinning anxiety disorders. Experimentally induced stress (via threat of unpredictable shock) improves accuracy at withholding a response on the sustained attention to response task (SART), and in separate studies improves accuracy to classify fearful faces, creating an affective bias. Integrating these findings, participants at two public science engagement events (n = 46, n = 55) were recruited to explore the effects of experimentally induced stress on an affective version of the SART. We hypothesized that we would see an improved accuracy at withholding a response to affectively congruent stimuli (i.e. increased accuracy at withholding a response to fearful 'no-go' distractors) under threat of shock. Induced anxiety slowed reaction time, and at the second event quicker responses were made to fearful stimuli. However, we did not observe improved inhibition overall during induced anxiety, and there was no evidence to suggest an interaction between induced anxiety and stimulus valence on response accuracy. Indeed Bayesian analysis provided decisive evidence against this hypothesis. We suggest that the presence of emotional stimuli might make the safe condition more anxiogenic, reducing the differential between conditions and knocking out any threat-potentiated improvement

    Anhedonia, apathy, pleasure, and effort-based decision-making in adult and adolescent cannabis users and controls

    Get PDF
    BACKGROUND: Cannabis use may be linked with anhedonia and apathy. However, previous studies have shown mixed results and few have examined the association between cannabis use and specific reward sub-processes. Adolescents may be more vulnerable to harmful effects of cannabis than adults. This study investigated (1) the association between non-acute cannabis use and apathy, anhedonia, pleasure, and effort-based decision-making for reward, and (2) whether these relationships were moderated by age-group. METHODS: We used data from the 'CannTeen' study. Participants were 274 adult (26-29 years) and adolescent (16-17 years) cannabis users (1-7 days/week use in the past three months), and gender- and age-matched controls. Anhedonia was measured with the Snaith-Hamilton Pleasure Scale (n=274), and apathy was measured with the Apathy Evaluation Scale (n=215). Effort-based decision-making for reward was measured with the Physical Effort task (n=139), and subjective wanting and liking of rewards was measured with the novel Real Reward Pleasure task (n=137). RESULTS: Controls had higher levels of anhedonia than cannabis users (F1,258=5.35, p=.02, ηp2=.02). There were no other significant effects of User-Group and no significant User-Group*Age-Group interactions. Null findings were supported by post hoc Bayesian analyses. CONCLUSION: Our results suggest that cannabis use at a frequency of three to four days per week is not associated with apathy, effort-based decision-making for reward, reward wanting, or reward liking in adults or adolescents. Cannabis users had lower anhedonia than controls, albeit at a small effect size. These findings are not consistent with the hypothesis that non-acute cannabis use is associated with amotivation

    Cohesin mutations alter DNA damage repair and chromatin structure and create therapeutic vulnerabilities in MDS/AML

    Get PDF
    The cohesin complex plays an essential role in chromosome maintenance and transcriptional regulation. Recurrent somatic mutations in the cohesin complex are frequent genetic drivers in cancer including myelodysplatic syndromes (MDS) and acute myeloid leukemia (AML). Here, using genetic dependency screens of STAG2-mutant AML, we identified DNA damage repair and replication as genetic dependencies in cohesin-mutant cells. We demonstrated increased levels of DNA damage and sensitivity of cohesin-mutant cells to PARP inhibition. We developed a mouse model of MDS in which Stag2 mutations arise as clonal secondary lesions in the background of clonal hematopoiesis driven by Tet2 mutations, and demonstrated selective depletion of cohesin-mutant cells with PARP inhibition in vivo. Finally, we demonstrated a shift from STAG2- to STAG1-containing cohesin complexes in cohesin-mutant cells, which is associated with longer DNA loop extrusion, more intermixing of chromatin compartments, and increased interaction with PARP and RPA proteins. Our findings inform the biology and therapeutic opportunities for cohesin-mutant malignancies

    When TADs go bad: chromatin structure and nuclear organisation in human disease

    Get PDF
    Chromatin in the interphase nucleus is organised as a hierarchical series of structural domains, including self-interacting domains called topologically associating domains (TADs). This arrangement is thought to bring enhancers into closer physical proximity with their target genes, which often are located hundreds of kilobases away in linear genomic distance. TADs are demarcated by boundary regions bound by architectural proteins, such as CTCF and cohesin, although much remains to be discovered about the structure and function of these domains. Recent studies of TAD boundaries disrupted in engineered mouse models show that boundary mutations can recapitulate human developmental disorders as a result of aberrant promoter-enhancer interactions in the affected TADs. Similar boundary disruptions in certain cancers can result in oncogene overexpression, and CTCF binding sites at boundaries appear to be hyper-mutated across cancers. Further insights into chromatin organisation, in parallel with accumulating whole genome sequence data for disease cohorts, are likely to yield additional valuable insights into the roles of noncoding sequence variation in human disease

    Epigenetic reprogramming at estrogen-receptor binding sites alters 3D chromatin landscape in endocrine-resistant breast cancer

    Get PDF
    Endocrine therapy resistance frequently develops in estrogen receptor positive (ER+) breast cancer, but the underlying molecular mechanisms are largely unknown. Here, we show that 3-dimensional (3D) chromatin interactions both within and between topologically associating domains (TADs) frequently change in ER+ endocrine-resistant breast cancer cells and that the differential interactions are enriched for resistance-associated genetic variants at CTCF-bound anchors. Ectopic chromatin interactions are preferentially enriched at active enhancers and promoters and ER binding sites, and are associated with altered expression of ER-regulated genes, consistent with dynamic remodelling of ER pathways accompanying the development of endocrine resistance. We observe that loss of 3D chromatin interactions often occurs coincidently with hypermethylation and loss of ER binding. Alterations in active A and inactive B chromosomal compartments are also associated with decreased ER binding and atypical interactions and gene expression. Together, our results suggest that 3D epigenome remodelling is a key mechanism underlying endocrine resistance in ER+ breast cancer

    Chromatin loop anchors are associated with genome instability in cancer and recombination hotspots in the germline

    Get PDF
    Abstract Background Chromatin loops form a basic unit of interphase nuclear organization, with chromatin loop anchor points providing contacts between regulatory regions and promoters. However, the mutational landscape at these anchor points remains under-studied. Here, we describe the unusual patterns of somatic mutations and germline variation associated with loop anchor points and explore the underlying features influencing these patterns. Results Analyses of whole genome sequencing datasets reveal that anchor points are strongly depleted for single nucleotide variants (SNVs) in tumours. Despite low SNV rates in their genomic neighbourhood, anchor points emerge as sites of evolutionary innovation, showing enrichment for structural variant (SV) breakpoints and a peak of SNVs at focal CTCF sites within the anchor points. Both CTCF-bound and non-CTCF anchor points harbour an excess of SV breakpoints in multiple tumour types and are prone to double-strand breaks in cell lines. Common fragile sites, which are hotspots for genome instability, also show elevated numbers of intersecting loop anchor points. Recurrently disrupted anchor points are enriched for genes with functions in cell cycle transitions and regions associated with predisposition to cancer. We also discover a novel class of CTCF-bound anchor points which overlap meiotic recombination hotspots and are enriched for the core PRDM9 binding motif, suggesting that the anchor points have been foci for diversity generated during recent human evolution. Conclusions We suggest that the unusual chromatin environment at loop anchor points underlies the elevated rates of variation observed, marking them as sites of regulatory importance but also genomic fragility
    corecore