Biologically informed risk scoring in schizophrenia based on genome-wide omics data

Extensive efforts in characterizing the biological architecture of schizophrenia have moved psychiatric research closer towards clinical application. As our understanding of psychiatric illness is slowly shifting towards a conceptualization as dimensional constructs that cut across traditional diagnostic boundaries, opportunities for personalized medicine applications that are afforded by the application of advanced data science methods on the increasingly available, large-scale and multimodal data repositories are starting to be more broadly recognized. A particularly intriguing phenomenon is the discrepancy between the high heritability of schizophrenia and the difficulty in identifying predictive genetic signatures, for which polygenic risk scores of common variants that explain approximately 18% of illness-associated variance remain the gold standard. A substantial body of research points towards two lines of investigation that may lead to a significant advance, resolve at least in part the ‘missing heritability’ phenomenon, and potentially provide the basis for more predictive, personalized clinical tools. First, it is paramount to better understand the impact of environmental factors on illness risk and elucidate the biology underlying their impact on altered brain function in schizophrenia. This thesis aims to close a major gap in our understanding of the multivariate, epigenetic landscape associated with schizophrenia, its interaction with polygenic risk and its association with DLPFC-HC connectivity, a well-established and robust neural intermediate phenotype of schizophrenia. As a basis for this, we have developed a novel biologically-informed machine learning framework by incorporating systems-level biological domain knowledge, i.e., gene ontological pathways, entitled ‘BioMM’ using genome-wide DNA methylation data obtained from whole blood samples. An epigenetic poly-methylation score termed ‘PMS’ was estimated at the individual level using BioMM, trained and validated using a total of 2230 whole-blood samples and 244 post-mortem brain samples. The pathways contributing most to this PMS were strongly associated with synaptic, neural and immune system-related functions. The identified PMS could be successfully validated in two independent cohorts, demonstrating the robust generalizability of the identified model. Furthermore, the PMS could significantly differentiate patients with schizophrenia from healthy controls when predicted in DLPFC post-mortem brain samples, suggesting that the epigenetic landscape of schizophrenia is to a certain extent shared between the central and peripheral tissues. Importantly, the peripheral PMS was associated with an intermediate neuroimaging phenotype (i.e., DLPFC-HC functional connectivity) in two independent imaging samples under the working memory paradigm. However, we did not find sufficient evidence for a combined genetic and epigenetic effect on brain function by integrating PRS derived from GWAS data, which suggested that DLPFC-HC coupling was predominantly impacted by environmental risk components, rather than polygenic risk of common variants. The epigenetic signature was further not associated with GWAS-derived risk scores implying the observed epigenetic effect did likely not depend on the underlying genetics, and this was further substantiated by investigation of data from unaffected first-degree relatives of patients with SCZ, BD, MDD and autism. In summary, the characterization of PMS through the systems-level integration of multimodal data elucidates the multivariate impact of epigenetic effects on schizophrenia-relevant brain function and its interdependence with genetic illness risk. Second, the limited predictive value of polygenic risk scores and the difficulty in identifying associations with heritable neural differences found in schizophrenia may be due to the possibility that the manifestation of the functional consequences of genetic risk is modulated by spatio-temporal as well as sex-specific effects. To address this, this thesis identifies sex-differences in the spatio-temporal expression trajectories during human development of genes that showed significant prefrontal co-expression with schizophrenia risk genes during the fetal phase and adolescence, consistent with a core developmental hypothesis of schizophrenia. More specifically, it was found that during these two time-periods, prefrontal expression was significantly more variable in males compared to females, a finding that could be validated in an independent data source and that was specific for schizophrenia compared to other psychiatric as well as somatic illnesses. Similar to the epigenetic differences described above, the genes underlying the risk-associated gene expression differences were significantly linked to synaptic function. Notably, individual genes with male-specific variability increases were distinct between the fetal phase and adolescence, potentially suggesting different risk associated mechanisms that converge on the shared synaptic involvement of these genes. These results provide substantial support to the hypothesis that the functional consequences of genetic risk show spatiotemporal specificity. Importantly, the temporal specificity was linked to the fetal phase and adolescence, time-periods that are thought to be of predominant importance for the brain-functional consequences of environmental risk exposure. Therefore, the presented results provide the basis for future studies exploring the polygenic risk architecture and its interaction with environmental effects in a multivariate and spatiotemporally stratified manner. In summary, the work presented in this thesis describes multivariate, multimodal approaches to characterize the (epi-)genetic basis of schizophrenia, explores its association with a well-established neural intermediate phenotype of the illness and investigates the spatio-temporal specificity of schizophrenia-relevant gene expression effects. This work expands our knowledge of the complex biology underlying schizophrenia and provides the basis for the future development of more predictive biological algorithms that may aid in advancing personalized medicine in psychiatry

A fully-nonlinear flow and quermassintegral inequalities in the sphere

This expository paper presents the current knowledge of particular fully nonlinear curvature flows with local forcing term, so-called locally constrained curvature flows. We focus on the spherical ambient space. The flows are designed to preserve a quermassintegral and to de-/increase the other quermassintegrals. The convergence of this flow to a round sphere would settle the full set of quermassintegral inequalities for convex domains of the sphere, but a full proof is still missing. Here we collect what is known and hope to attract wide attention to this interesting problem.Comment: 19 page

Mated progeny production is a biomarker of aging in Caenorhabditis elegans

The relationships between reproduction and aging are important for understanding the mechanisms of aging and evaluating evolutionary theories of aging. To investigate the effects of progeny production on reproductive and somatic aging, we conducted longitudinal studies of Caenorhabditis elegans hermaphrodites. For mated wild-type animals that were not sperm limited and survived past the end of the reproductive period, high levels of cross-progeny production were positively correlated with delayed reproductive and somatic aging. In this group of animals, individuals that generated more cross progeny also reproduced and lived longer than individuals that generated fewer cross progeny. These results indicate that progeny production does not accelerate reproductive or somatic aging. This longitudinal study demonstrated that cumulative cross progeny production through day four is an early-stage biomarker that is a positive predictor of longevity. Furthermore, in mated animals, high levels of early cross progeny production were positively correlated with high levels of late cross progeny production, indicating that early progeny production does not accelerate reproductive aging. The relationships between progeny production and aging were further evaluated by comparing self-fertile hermaphrodites that generated relatively few self progeny with mated hermaphrodites that generated many cross progeny. The timing of age-related somatic degeneration was similar in these groups, suggesting progeny production does not accelerate somatic aging. These studies rigorously define relationships between progeny production, reproductive aging, and somatic aging and identify new biomarkers of C. elegans aging. These results indicate that some mechanisms or pathways control age-related degeneration of both reproductive and somatic tissues in C. elegans

A System of Photocatalysis for NAD+ Regeneration of Product of (S)-1-Pheylethanol by Enzymic Catalysis

In this study, a system of photocatalysis for NAD+ regeneration of enzymatic catalysis was constructed. The optimal conditions for the coupling reaction of photocatalysis and biocatalysis were explored. Blue light was chosen for the efficient reaction and the optimal concentration of VB2 (vitamin B2, riboflavin) was determined. NAD+-dependent (R)-1-phenylethanol dehydrogenase was used in the reaction for transforming (R)-1-phenylethanol to acetophenone. The byproducts of the reaction were just H2O and O2 by means of catalase. The coupling reaction of catalysis and photocatalysis can be used for obtaining (S)-1-phenylethanol through racemization of 1-phenylethanol. Copyright © 2019 BCREC Group. All rights reserve

Brain state stability during working memory is explained by network control theory, modulated by dopamine D1/D2 receptor function, and diminished in schizophrenia

Dynamical brain state transitions are critical for flexible working memory but the network mechanisms are incompletely understood. Here, we show that working memory entails brainwide switching between activity states. The stability of states relates to dopamine D1 receptor gene expression while state transitions are influenced by D2 receptor expression and pharmacological modulation. Schizophrenia patients show altered network control properties, including a more diverse energy landscape and decreased stability of working memory representations

Longitudinal transcriptome-wide gene expression analysis of sleep deprivation treatment shows involvement of circadian genes and immune pathways

Therapeutic sleep deprivation (SD) rapidly induces robust, transient antidepressant effects in a large proportion of major mood disorder patients suffering from a depressive episode, but underlying biological factors remain poorly understood. Research suggests that these patients may have altered circadian molecular genetic 'clocks' and that SD functions through 'resetting' dysregulated genes;additional factors may be involved, warranting further investigation. Leveraging advances in microarray technology enabling the transcriptome-wide assessment of gene expression, this study aimed to examine gene expression changes accompanying SD and recovery sleep in patients suffering from an episode of depression. Patients (N = 78) and controls (N = 15) underwent SD, with blood taken at the same time of day before SD, after one night of SD and after recovery sleep. A transcriptome-wide gene-by-gene approach was used, with a targeted look also taken at circadian genes. Furthermore, gene set enrichment, and longitudinal gene set analyses including the time point after recovery sleep, were conducted. Circadian genes were significantly affected by SD, with patterns suggesting that molecular clocks of responders and non-responders, as well as patients and controls respond differently to chronobiologic stimuli. Notably, gene set analyses revealed a strong widespread effect of SD on pathways involved in immune function and inflammatory response, such as those involved in cytokine and especially in interleukin signalling. Longitudinal gene set analyses showed that in responders these pathways were upregulated after SD;in non-responders, little response was observed. Our findings emphasize the close relationship between circadian, immune and sleep systems and their link to etiology of depression at the transcriptomic level

Longitudinal transcriptome-wide gene expression analysis of sleep deprivation treatment shows involvement of circadian genes and immune pathways

Therapeutic sleep deprivation (SD) rapidly induces robust, transient antidepressant effects in a large proportion of major mood disorder patients suffering from a depressive episode, but underlying biological factors remain poorly understood. Research suggests that these patients may have altered circadian molecular genetic 'clocks' and that SD functions through 'resetting' dysregulated genes; additional factors may be involved, warranting further investigation. Leveraging advances in microarray technology enabling the transcriptome-wide assessment of gene expression, this study aimed to examine gene expression changes accompanying SD and recovery sleep in patients suffering from an episode of depression. Patients (N = 78) and controls (N = 15) underwent SD, with blood taken at the same time of day before SD, after one night of SD and after recovery sleep. A transcriptome-wide gene-by-gene approach was used, with a targeted look also taken at circadian genes. Furthermore, gene set enrichment, and longitudinal gene set analyses including the time point after recovery sleep, were conducted. Circadian genes were significantly affected by SD, with patterns suggesting that molecular clocks of responders and non-responders, as well as patients and controls respond differently to chronobiologic stimuli. Notably, gene set analyses revealed a strong widespread effect of SD on pathways involved in immune function and inflammatory response, such as those involved in cytokine and especially in interleukin signalling. Longitudinal gene set analyses showed that in responders these pathways were upregulated after SD; in non-responders, little response was observed. Our findings emphasize the close relationship between circadian, immune and sleep systems and their link to etiology of depression at the transcriptomic level