•LC-NE system is involved in motivation and cognition in humans.•This system participates in mechanisms of stress response.•LC-NE system may be connected to the cognitive and motivational deficits of ...SCZ.•A combination of methodological approaches is proposed to answer open questions.
Several lines of evidence have suggested for decades a role for norepinephrine (NE) in the pathophysiology and treatment of schizophrenia. Recent experimental findings reveal anatomical and physiological properties of the locus coeruleus-norepinephrine (LC-NE) system and its involvement in brain function and cognition. Here, we integrate these two lines of evidence. First, we review the functional and structural properties of the LC-NE system and its impact on functional brain networks, cognition, and stress, with special emphasis on recent experimental and theoretical advances. Subsequently, we present an update about the role of LC-associated functions for the pathophysiology of schizophrenia, focusing on the cognitive and motivational deficits. We propose that schizophrenia phenomenology, in particular cognitive symptoms, may be explained by an abnormal interaction between genetic susceptibility and stress-initiated LC-NE dysfunction. This in turn, leads to imbalance between LC activity modes, dysfunctional regulation of brain network integration and neural gain, and deficits in cognitive functions. Finally, we suggest how recent development of experimental approaches can be used to characterize LC function in schizophrenia.
Estimating the polygenicity (proportion of causally associated single nucleotide polymorphisms (SNPs)) and discoverability (effect size variance) of causal SNPs for human traits is currently of ...considerable interest. SNP-heritability is proportional to the product of these quantities. We present a basic model, using detailed linkage disequilibrium structure from a reference panel of 11 million SNPs, to estimate these quantities from genome-wide association studies (GWAS) summary statistics. We apply the model to diverse phenotypes and validate the implementation with simulations. We find model polygenicities (as a fraction of the reference panel) ranging from ≃ 2 × 10-5 to ≃ 4 × 10-3, with discoverabilities similarly ranging over two orders of magnitude. A power analysis allows us to estimate the proportions of phenotypic variance explained additively by causal SNPs reaching genome-wide significance at current sample sizes, and map out sample sizes required to explain larger portions of additive SNP heritability. The model also allows for estimating residual inflation (or deflation from over-correcting of z-scores), and assessing compatibility of replication and discovery GWAS summary statistics.
The macro- and microstructural architecture of human brain white matter undergoes substantial alterations throughout development and ageing. Most of our understanding of the spatial and temporal ...characteristics of these lifespan adaptations come from magnetic resonance imaging (MRI), including diffusion MRI (dMRI), which enables visualisation and quantification of brain white matter with unprecedented sensitivity and detail. However, with some notable exceptions, previous studies have relied on cross-sectional designs, limited age ranges, and diffusion tensor imaging (DTI) based on conventional single-shell dMRI. In this mixed cross-sectional and longitudinal study (mean interval: 15.2 months) including 702 multi-shell dMRI datasets, we combined complementary dMRI models to investigate age trajectories in healthy individuals aged 18 to 94 years (57.12% women). Using linear mixed effect models and machine learning based brain age prediction, we assessed the age-dependence of diffusion metrics, and compared the age prediction accuracy of six different diffusion models, including diffusion tensor (DTI) and kurtosis imaging (DKI), neurite orientation dispersion and density imaging (NODDI), restriction spectrum imaging (RSI), spherical mean technique multi-compartment (SMT-mc), and white matter tract integrity (WMTI). The results showed that the age slopes for conventional DTI metrics (fractional anisotropy FA, mean diffusivity MD, axial diffusivity AD, radial diffusivity RD) were largely consistent with previous research, and that the highest performing advanced dMRI models showed comparable age prediction accuracy to conventional DTI. Linear mixed effects models and Wilk's theorem analysis showed that the ‘FA fine’ metric of the RSI model and ‘orientation dispersion’ (OD) metric of the NODDI model showed the highest sensitivity to age. The results indicate that advanced diffusion models (DKI, NODDI, RSI, SMT mc, WMTI) provide sensitive measures of age-related microstructural changes of white matter in the brain that complement and extend the contribution of conventional DTI.
For over a century, psychiatric disorders have been defined by expert opinion and clinical observation. The modern DSM has relied on a consensus of experts to define categorical syndromes based on ...clusters of symptoms and signs, and, to some extent, external validators, such as longitudinal course and response to treatment. In the absence of an established etiology, psychiatry has struggled to validate these descriptive syndromes, and to define the boundaries between disorders and between normal and pathologic variation. Recent advances in genomic research, coupled with large-scale collaborative efforts like the Psychiatric Genomics Consortium, have identified hundreds of common and rare genetic variations that contribute to a range of neuropsychiatric disorders. At the same time, they have begun to address deeper questions about the structure and classification of mental disorders: To what extent do genetic findings support or challenge our clinical nosology? Are there genetic boundaries between psychiatric and neurologic illness? Do the data support a boundary between disorder and normal variation? Is it possible to envision a nosology based on genetically informed disease mechanisms? This review provides an overview of conceptual issues and genetic findings that bear on the relationships among and boundaries between psychiatric disorders and other conditions. We highlight implications for the evolving classification of psychopathology and the challenges for clinical translation.
Accumulating evidence from genome wide association studies (GWAS) suggests an abundance of shared genetic influences among complex human traits and disorders, such as mental disorders. Here we ...introduce a statistical tool, MiXeR, which quantifies polygenic overlap irrespective of genetic correlation, using GWAS summary statistics. MiXeR results are presented as a Venn diagram of unique and shared polygenic components across traits. At 90% of SNP-heritability explained for each phenotype, MiXeR estimates that 8.3 K variants causally influence schizophrenia and 6.4 K influence bipolar disorder. Among these variants, 6.2 K are shared between the disorders, which have a high genetic correlation. Further, MiXeR uncovers polygenic overlap between schizophrenia and educational attainment. Despite a genetic correlation close to zero, the phenotypes share 8.3 K causal variants, while 2.5 K additional variants influence only educational attainment. By considering the polygenicity, discoverability and heritability of complex phenotypes, MiXeR analysis may improve our understanding of cross-trait genetic architectures.
Schizophrenia is a severe psychiatric disorder with considerable morbidity and mortality. Although the past two decades have seen limited improvement in the treatment of schizophrenia, research into ...the genetic causes of this condition has made important advances that offer new insights into the aetiology of schizophrenia. This Review summarizes the evidence for a polygenic architecture of schizophrenia that involves a large number of risk alleles across the whole range of population frequencies. These genetic risk loci implicate biological processes related to neurodevelopment, neuronal excitability, synaptic function and the immune system in the pathogenesis of schizophrenia. Mathematical models also suggest a substantial overlap between schizophrenia and psychiatric, behavioural and cognitive traits, a situation that has implications for understanding its clinical epidemiology, psychiatric nosology and pathobiology. Looking ahead, further genetic discoveries are expected to lead to clinically relevant predictive approaches for identifying high-risk individuals, improved diagnostic accuracy, increased yield from drug development programmes and improved stratification strategies to address the heterogeneous disease course and treatment responses observed among affected patients.
Oxytocin is a neuropeptide involved in animal and human reproductive and social behavior. Three oxytocin signaling genes have been frequently implicated in human social behavior: OXT (structural gene ...for oxytocin), OXTR (oxytocin receptor), and CD38 (oxytocin secretion). Here, we characterized the distribution of OXT, OXTR, and CD38 mRNA across the human brain by creating voxel-by-voxel volumetric expression maps, and identified putative gene pathway interactions by comparing gene expression patterns across 20,737 genes. Expression of the three selected oxytocin pathway genes was enriched in subcortical and olfactory regions and there was high co-expression with several dopaminergic and muscarinic acetylcholine genes, reflecting an anatomical basis for critical gene pathway interactions. fMRI meta-analysis revealed that the oxytocin pathway gene maps correspond with the processing of anticipatory, appetitive, and aversive cognitive states. The oxytocin signaling system may interact with dopaminergic and muscarinic acetylcholine signaling to modulate cognitive state processes involved in complex human behaviors.
Epidemiological and clinical studies have found associations between depression and cardiovascular disease risk factors, and coronary artery disease patients with depression have worse prognosis. The ...genetic relationship between depression and these cardiovascular phenotypes is not known. We here investigated overlap at the genome-wide level and in individual loci between depression, coronary artery disease and cardiovascular risk factors. We used the bivariate causal mixture model (MiXeR) to quantify genome-wide polygenic overlap and the conditional/conjunctional false discovery rate (pleioFDR) method to identify shared loci, based on genome-wide association study summary statistics on depression (n = 450,619), coronary artery disease (n = 502,713) and nine cardiovascular risk factors (n = 204,402-776,078). Genetic loci were functionally annotated using FUnctional Mapping and Annotation (FUMA). Of 13.9K variants influencing depression, 9.5K (SD 1.0K) were shared with body-mass index. Of 4.4K variants influencing systolic blood pressure, 2K were shared with depression. ConjFDR identified 79 unique loci associated with depression and coronary artery disease or cardiovascular risk factors. Six genomic loci were associated jointly with depression and coronary artery disease, 69 with blood pressure, 49 with lipids, 9 with type 2 diabetes and 8 with c-reactive protein at conjFDR < 0.05. Loci associated with increased risk for depression were also associated with increased risk of coronary artery disease and higher total cholesterol, low-density lipoprotein and c-reactive protein levels, while there was a mixed pattern of effect direction for the other risk factors. Functional analyses of the shared loci implicated metabolism of alpha-linolenic acid pathway for type 2 diabetes. Our results showed polygenic overlap between depression, coronary artery disease and several cardiovascular risk factors and suggest molecular mechanisms underlying the association between depression and increased cardiovascular disease risk.
Recent advances in optical technologies such as multi-photon microscopy and optogenetics have revolutionized our ability to record and manipulate neuronal activity. Combining optical techniques with ...electrical recordings is of critical importance to connect the large body of neuroscience knowledge obtained from animal models to human studies mainly relying on electrophysiological recordings of brain-scale activity. However, integration of optical modalities with electrical recordings is challenging due to generation of light-induced artifacts. Here we report a transparent graphene microelectrode technology that eliminates light-induced artifacts to enable crosstalk-free integration of 2-photon microscopy, optogenetic stimulation, and cortical recordings in the same in vivo experiment. We achieve fabrication of crack- and residue-free graphene electrode surfaces yielding high optical transmittance for 2-photon imaging down to ~ 1 mm below the cortical surface. Transparent graphene microelectrode technology offers a practical pathway to investigate neuronal activity over multiple spatial scales extending from single neurons to large neuronal populations.
Schizophrenia is among the major causes of disability worldwide and the mortality from cardiovascular disease (CVD) is significantly elevated. There is a growing concern that this health challenge is ...not fully understood and efficiently addressed.
Non-systematic review using searches in PubMed on relevant topics as well as selection of references based on the authors' experience from clinical work and research in the field.
In most countries, the standardized mortality rate in schizophrenia is about 2.5, leading to a reduction in life expectancy between 15 and 20 years. A major contributor of the increased mortality is due to CVD, with CVD mortality ranging from 40 to 50% in most studies. Important causal factors are related to lifestyle, including poor diet, lack of physical activity, smoking, and substance abuse. Recent findings suggest that there are overlapping pathophysiology and genetics between schizophrenia and CVD-risk factors, further increasing the liability to CVD in schizophrenia. Many pharmacological agents used for treating psychotic disorders have side effects augmenting CVD risk. Although several CVD-risk factors can be effectively prevented and treated, the provision of somatic health services to people with schizophrenia seems inadequate. Further, there is a sparseness of studies investigating the effects of lifestyle interventions in schizophrenia, and there is little knowledge about effective programs targeting physical health in this population.
The risk for CVD and CVD-related deaths in people with schizophrenia is increased, but the underlying mechanisms are not fully known. Coordinated interventions in different health care settings could probably reduce the risk. There is an urgent need to develop and implement effective programs to increase life expectancy in schizophrenia, and we argue that mental health workers should be more involved in this important task.
PDF
