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Genetic risk for depressive disorders is poorly understood despite consistent suggestions of a high heritable component. Most genetic studies have focused on risk associated with single variants, a strategy which has so far only yielded small (often non-replicable) risks for depressive disorders. In this paper we argue that more substantial risks are likely to emerge from genetic variants acting in synergy within and across larger neurobiological systems (polygenic risk factors). We show how knowledge of major integrated neurobiological systems provides a robust basis for defining and testing theoretically defensible polygenic risk factors. We do this by describing the architecture of the overall stress response. Maladaptation via impaired stress responsiveness is central to the aetiology of depression and anxiety and provides a framework for a systems biology approach to candidate gene selection. We propose principles for identifying genes and gene networks within the neurosystems involved in the stress response and for defining polygenic risk factors based on the neurobiology of stress-related behaviour. We conclude that knowledge of the neurobiology of the stress response system is likely to play a central role in future efforts to improve genetic prediction of depression and related disorders.

Although first rank symptoms focus on positive symptoms of psychosis they are shared by a number of psychiatric conditions. The difficulty in differentiating bipolar disorder from schizophrenia with affective features has led to a third category of patients often loosely labeled as schizoaffective. Research in schizophrenia has attempted to render the presence or absence of negative symptoms and their relation to etiology and prognosis more explicit. A dichotomous population is a recurring theme in experimental paradigms. Thus, schizophrenia is defined as process or reactive, deficit or non-deficit and by the presence or absence of affective symptoms. Laboratory tests confirm the clinical impression showing conflicting responses to dexamethasone suppression and clearly defined differences in autonomic responsiveness, but their patho-physiological significance eludes mainstream theory. Added to this is the difficulty in agreeing to what exactly constitutes useful clinical features differentiating, for example, negative symptoms of a true deficit syndrome from features of depression. Two recent papers proposed that the general and specific cognitive features of schizophrenia and major depression result from a monoamine-cholinergic imbalance, the former due to a relative muscarinic receptor hypofunction and the latter, in contrast, to a muscarinic hypersensitivity exacerbated by monoamine depletion. Further development of these ideas will provide pharmacological principles for what is currently an incomplete and largely, descriptive nosology of psychosis. It will propose a dimensional view of affective and negative symptoms based on relative muscarinic integrity and is supported by several exciting intracellular signaling and gene expression studies. Bipolar disorder manifests both muscarinic and dopaminergic hypersensitivity. The greater the imbalance between these two receptor signaling systems, the more the clinical picture will resemble schizophrenia with bizarre, incongruent delusions and increasingly disorganized thought. The capacity for affective expression, by definition a non-deficit syndrome, will remain contingent on the degree of preservation of muscarinic signaling, which itself may be unstable and vary between trait and state examinations. At the extreme end of muscarinic impairment, a deficit schizophrenia subpopulation is proposed with a primary and fixed muscarinic receptor hypofunction.

The genomic profile of bipolar disorder and schizophrenia overlap and both have a common dopaminergic intracellular signaling which is hypersensitive to various stressors. It is proposed that the concomitant muscarinic receptor upregulation differentiates the syndromes, being marked in bipolar disorder and rather less so in schizophrenia. From a behavioral point of view non-deficit syndromes and bipolar disorder appear most proximate and could be reclassified as a spectrum of affective psychosis or schizoaffective disorders. Because of a profound malfunction of the muscarinic receptor, the deficit subgroup cannot express a comparable stress response. None -theless, a convergent principle of psychotic features across psychiatric disorders is a relative monoaminergic-muscarinic imbalance in signal transduction.

Many studies have analysed the impact of various variables on the ability of companies to raise capital. While most of these studies are sector-agnostic, literature on the effects of macroeconomic variables on sectors that established over the last 20 years like property technology and financial technology, is scarce. This study aims to identify macroeconomic factors that influence the ability of both sectors and is extended by real estate variables.

The impact of macroeconomic and real estate related factors is analysed using multiple linear regression and quantile regression. The sample covers 338 observations for PropTech and 595 for FinTech across 18 European countries and 5 deal types between 2000–2001 with each observation representing the capital invested per year for each deal type and country.

Besides confirming a significant impact of macroeconomic variables on the amount of capital invested, this study finds that additionally the real estate transaction volume positively impacts PropTech while the real estate yield-bond-gap negatively impacts FinTech.

For PropTech and FinTech companies and their investors it is critical to understand the dynamic with mac-ro variables and also the real estate industry. The direct connection identified in this paper is critical for a holistic understanding of the effects of measurable real estate variables on capital investments into both sectors.

The analysis fills the gap in the literature between variables affecting investment into firms and effects of the real estate industry on the investment activity into PropTech and FinTech.