Namour Philippe
email: philippe.namour@univ-lyon1.fr

Breil Pascal
email: pascal.breil@irstea.fr

Clément Yohann
email: yohann.clement@univ-lyon1.fr

Lanteri Pierre
email: pierre.lanteri@univ-lyon1.fr

Jaffrezic-Renault Nicole

Environmental monitoring and water safety are claiming innovative tools. La métrologie de l'environnement et la préservation de la ressource en eau nécessitent des outils novateurs

Keywords: Ecohydrology, high frequency measurement, hot moment, hot spot, sensor, water monitoring, wireless network

Notre objectif est de démontrer la nécessité de concevoir un nouveau type de mesures écologiquement pertinentes pour faire face aux défis de la DCE. Les rivières sont des systèmes écologiques structurés spatialement et temporellement présentant les points et les périodes actifs qui contribuant à leur état écologique général. Toutefois, les programmes actuels de contrôle de l'eau (échantillons ponctuels et analyses de laboratoire) sont basés sur la stratégie d'échantillonnage qui ne tiennent pas compte de cette hétérogénéité spatiale et temporelle. Pour tenir compte de leurs dynamiques réelles, un changement de paradigme est indispensable. Cela nécessite le développement de nouvelles stratégies de surveillance et donc de nouveaux instruments. Cette nouvelle instrumentation doit être capable de mesurer à des échelles de temps adaptées aux phénomènes suivis et à un coût suffisamment bas pour permettre un déploiement convenable de les plans d'eau. Nous proposons de renforcer le développement des réseaux sans fil autonomes de micro-capteurs associés à un traitement mathématique des données recueillies. La caractéristique essentiel d'un tel système intelligent provient du réseau complet de surveillance attendu, associant chimie des eaux de surface et souterraines, électronique et la récupération d'énergie au traitement de données intelligente visant à représenter dynamique des fonctions écologiques fondamentales.

INTRODUCTION

A clean and healthy environment is essential for human well-being. To limit environmental threats to human health, the EU took actions and made progress in various fields during the last decade, such as the implementation of the REACH chemicals legislation and the Water Framework Directive 2000/60/EC (WFD), and the agreement reached on the Industrial Emissions Directive. Environmental monitoring is the cornerstone of any policy for managing, protecting and restoring surface water and groundwater resources. The WFD requires that an integrated monitoring programme has to be established within each river basin district. Specifically, to meet the requirements of the WFD, two primary monitoring programmes are required: the Surveillance Monitoring (SM) and the Operational Monitoring (OM). This latest is used to determine the status of water bodies identified as being at risk, and to establish a programme of measures. Unfortunately, rivers being mistakenly conceived as homogeneous well-mixed systems, and also because the water quality data are expensive, these programmes are based on a few grab samples analysed at laboratory, despite wide recognition by scientists of spatial heterogeneity and temporal variability of rivers. [START_REF] Boulton | Ecology and management of the hyporheic zone: stream-groundwater interactions of running waters and their floodplains[END_REF][START_REF] Casper | Scales of heterogeneity of water quality in rivers: Insights from high resolution maps based on integrated geospatial, sensor and ROV technologies[END_REF][START_REF] Mcclain | Biogeochemical hot spots and hot moments at the interface of terrestrial and aquatic ecosystems[END_REF][START_REF] Stanford | An Ecosystem Perspective of Alluvial Rivers -Connectivity and the Hyporheic Corridor[END_REF][START_REF] Ward | Biodiversity of floodplain river ecosystems: Ecotones and connectivity[END_REF]. Only for France, the Programme of Measures is estimated to 24.4 billion euros, over the period 2012-2015, or more than 6 billion euros a year [START_REF] Meddtl | Mise en oeuvre de la DCE et politique locale de l'eau[END_REF]. And it's a safe bet that if our monitoring methods are not well suited to actual quality measurement of water bodies, this money will be spent in vain.

HOT SPOT & HOT MOMENT

In rivers, rates of biogeochemical processes vary in space and time to produce both hot spots and hot moments of elemental cycling. Indeed, at the intersection of hydrological fluxes with substrates or other fluxes containing complementary or missing reactants, some patches show disproportionately high biogeochemical reaction rates, relative to the surrounding. These areas of high activity are called hot spots. In a same way, at some periods of time, biogeochemical processes are enhanced and exhibit disproportionately high reaction rates relative to longer intervening time periods, when episodic hydrological fluxes reactivate and/or mobilize accumulated reactants: hot moments occur. Hot spots and hot moments often overlap and coincide with natural or anthropic disturbances. They need to be understood as a source and sink for Nitrogen and organic matter. These conditions often occur in riparian zones, stream channels and hyporheic zones, and several investigators have measured high rates of denitrification and nitrate decline in these locations [START_REF] Stelzer | The dark side of the hyporheic zone: depth profiles of nitrogen and its processing in stream sediments[END_REF].

In order to a mechanistic understanding, it is necessary to identify biogeochemical hot spots at broader spatiotemporal scales and to factor them into quantitative models. In particular, the water managers must incorporate both natural and anthropic created biogeochemical hot spots into their water quality management plans. However, an actual visualization and an adapted water sampling are essential to river quality management. Also, we need new robust and flexible tools able to detect the ephemeral nature and the particular locations of these hot moments and spots, to assess their importance in biogeochemistry of bioactive element cycles, to improve our ability to predict their occurrence, and finally to better manage water resource.

CHEMICAL STATUS

Nowadays, the state of the art with regard to the physicochemical and biological monitoring of rivers, that is to say what is technically applicable and available for the majority of water managers, is still dominated by the conventional protocol: the grab sampling, that is "send a technician; take an isolated sample, send it to the laboratory and analyse it" with at best, in conventional water chemistry, a daily average flow proportional composite sample. The ecological pertinence of such a procedure is more than problematic [START_REF] Greenwood | Introduction to emerging tools and their use in water monitoring[END_REF]. Indeed, this kind of protocol only provides information on pollutant contents at time t (usually during working hours) ignoring the hourly or daily variations in a pollutant discharge and the functioning of the natural environment itself, and is unable to provide information on the ecological or even chemical status of a water body [START_REF] Strobl | Network design for water quality monitoring of surface freshwaters: A review[END_REF]. Furthermore, the high cost of this protocol makes it impossible to obtain any satisfactory spatial representativeness. The average sample also obscures the essentially dynamic character of a polluting event and the average contents are devoid of any ecological realism. Biocenoses in rivers are never exposed to average contents, which have no actual existence as far as they are concerned. They are in reality exposed to changes in their physicochemical ambience. The greater and more sudden these changes, the more disturbance they cause. In terms of toxicology, fluctuation is a more important parameter than the average level and, in the present case, the peak maximum concentration reached by the pollutant is more important than the average concentration.

In fact, almost all transient polluting events do not fit the conventional protocol, whether these be urban discharges during rainy periods, and in particular those from combined sewer overflows, or polluting rural runoff generated during storm events, which are particularly destabilising for biocenoses. The time scale of many important water quality processes is on the order of minutes to hours (and not weeks to months), and ecological status is more the result of the dynamics of pollutant flows and especially of the contents of paroxysmal pollution peaks than of daily, fortnightly or even monthly average concentrations, as measured by integrative passive samplers [START_REF] Kot-Wasik | Advances in passive sampling in environmental studies[END_REF][START_REF] Soderstrom | Strategies for monitoring the emerging polar organic contaminants in water with emphasis on integrative passive sampling[END_REF][START_REF] Stuer-Lauridsen | Review of passive accumulation devices for monitoring organic micropollutants in the aquatic environment[END_REF]. Understanding the process linkage between watershed hydrology and stream water chemistry requires measurements on a time scale that is consistent with these processes [START_REF] Horsburgh | A sensor network for high frequency estimation of water quality constituent fluxes using surrogates[END_REF]. Thus, continuous monitoring is essential for properly determining the chemical and ecological statuses of a water body [START_REF] Kirchner | The fine structure of water-quality dynamics: the (high-frequency) wave of the future[END_REF]. Note that definition of the chemical status of water bodies, sensu WFD, is normative, as the texts call for a list of priority substances to be monitored. The scheduled revision will probably increase the number. However, the pertinence of such standardisation may be questioned. While it is true that a laboratory analysis deploys a wide range of analytical techniques for determining the exact content of specific analytes, in view of the high cost of the laboratory analyses required and the potential artefacts that may be introduced during the conventional sampling sequence, viz. collection-packaging-transport, it does not meet the ecological realism requirements prescribed by the WFD.

ECOLOGICAL STATUS

As far as ecological status is concerned, species lists alone cannot judge the biological quality in highly dynamic and anthropogenically impacted water bodies [START_REF] De Jonge | Marine monitoring: Its shortcomings and mismatch with the EU water framework directive's objectives[END_REF][START_REF] Moss | The Water Framework Directive: Total environment or political compromise?[END_REF]. But it should be stressed that the WFD defines ecological status (Art. 2, § 21) as "an expression of the quality of the structure and functioning of aquatic ecosystems" and does not enumerate any specific parameter in annex V. Rather, the "quality elements" used for classifying the ecological status are functional, such as "oxygenation conditions" instead of oxygen concentration, or "acidification status" instead of pH (Winkler et al., 2008b). On the one hand, this opens up the field to integrated technological innovation in terms of environmental monitoring, and on the other it may be interpreted as the need to access more complex information that a simple discontinuous record of more or less relevant parameters. Thus, measurement of driving pressures (physical and biochemical parameters continuously measured and with a greater accuracy than biological ones) as surrogates or proxies of ecological states, can be automated and used to produce, through data processing and modelling, synthetic quality indices or classes of water bodies [START_REF] Fellows | Benthic metabolism as an indicator of stream ecosystem health[END_REF][START_REF] Solimini | Towards holistic assessment of the functioning of ecosystems under the Water Framework Directive[END_REF], this is the avenue that we propose to explore.

The functional approach to aquatic environments is not a new concept. All the major conceptual river models published in the past three decades take such an approach. Examples include the: 'River Continuum' [START_REF] Vannote | The river continuum concept[END_REF], 'Resource Spiraling' [START_REF] Fisher | Material spiraling in stream corridors: A telescoping ecosystem model[END_REF][START_REF] Newbold | Organic carbon spiralling in stream ecosystems[END_REF][START_REF] Poole | Hydrologic spiralling: The role of multiple interactive flow paths in stream ecosystems[END_REF], 'Flood Pulse' [START_REF] Junk | The flood pulse concept of large rivers: learning from the tropics[END_REF], 'River Health' [START_REF] Boulton | An overview of river health assessment: Philosophies, practice, problems and prognosis[END_REF], or 'Riverine productivity model' [START_REF] Thorp | The riverine ecosystem synthesis: Biocomplexity in river networks across space and time[END_REF] and reviews published on the subject [START_REF] Ensign | Nutrient spiraling in streams and river networks[END_REF][START_REF] Grimm | Merging aquatic and terrestrial perspectives of nutrient biogeochemistry[END_REF][START_REF] Lorenz | Concepts in river ecology: Implications for indicator development[END_REF][START_REF] Young | Organic matter breakdown and ecosystem metabolism: functional indicators for assessing river ecosystem health[END_REF]. The expression of a recycling distance in the river corridor, as described in the "telescoping ecosystem model" [START_REF] Fisher | Material spiraling in stream corridors: A telescoping ecosystem model[END_REF] and validated in several publications, demonstrates that it is possible to determine the spatial and temporal dimensions of biodegradation processes in a river or stream, where the largest material fluxes come from organisms involved in the sediment food web [START_REF] Breil | Surface water groundwater exchanges processes and fluvial ecosystem function: An analysis of temporal and spatial scale dependency[END_REF].

To do this we propose to adopt the concept of "ecological ambience" [START_REF] Lafont | A conceptual approach to the biomonitoring of freshwater: the Ecological Ambience System[END_REF] based on the ranking of nested factors, with abiotic factors (functional unit) supporting the function (biocenosis). A functional unit is a physical-chemical coherent assembly supporting generic metabolic processes operating in a specific physicochemical context. The working hypothesis is therefore based on the existence of physicochemical ambiences, specific to each functional unit, that support a specific biocenosis (ecological ambience) and are modulated by trophic or toxic inflows. A precise description of this physicochemical context must therefore enable the various involved processes to be identified and the likely causes of any variations or alterations to be inferred.

Over the last 25 years, stream ecosystem theory has expanded to include explicitly the vertical dimension of surface-groundwater linkages via the hyporheic zone or hyporheon, defined as the saturated interstitial spaces below the streambed and adjacent stream banks that contain between 10 and 98% of channel water [START_REF] Triska | Retention and Transport of Nutrients in a Third-Order Stream in Northwestern California: Hyporheic Processes[END_REF]. This functional unit plays a major role in overall stream metabolism [START_REF] Boulton | Ecology and management of the hyporheic zone: stream-groundwater interactions of running waters and their floodplains[END_REF] and it can be viewed as a stream bed living reactor where hydrological, ecological, and biogeochemical processes interact. These interactions influence key stream ecosystem processes, such as primary productivity and nutrient cycling, and more especially in the sediments that harbour microbes and invertebrates and are used by some fish for spawning. Unfortunately, this major functional unit is not accessible to conventional analyses without disruption or modifications. Its study thus demands new measurement tools [START_REF] Bridge | High resolution in-situ monitoring of hyporheic zone biogeochemistry[END_REF]. We will focus on this key unit, indicator of the global metabolism in hydrosystems [START_REF] Boulton | Rivers as groundwater-dependent ecosystems: A review of degrees of dependency, riverine processes and management implications[END_REF][START_REF] Grimm | N retention and transformation in urban streams[END_REF] that will contribute to a better knowledge of the functioning of water bodies.

We propose to work on an elementary ecosystem referred to as a functional unit, that is to say a set of coherent interrelations between a biotope and a biocenosis. This functional unit will be chosen from environments that are in contact with the aquifer and are subject to unexpected anthropogenic or natural variations. Owing to the functional coherence inherent in any ecosystem, variations in physicochemical conditions (or physicochemical ambience) within a functional unit may be viewed not as random but as the responses of a structured environment adapting to modifications in environmental conditions. This coherence in environmental parameters due to the intrinsic dynamic balance of an ecosystem thus makes it possible to deduce a particular status from a set of measurements without necessarily having to measure it directly. In other words, it is to focus on elements acting as surrogates for ecosystem functioning. A good ecological status may therefore be defined as an initial approximation as that in which all levels of organisation of the system under study are working correctly, i.e. no malfunction, such as a drift in one or more parameters or an accumulation of protons or electrons can be observed at any level at all. Indeed, cell energy metabolism may ultimately be schematised as a self-regulating cybernetic system built on the flows of electrons and protons carried and exchanged by molecules such as ATP, NAD NADP or FAD and other cytochromes. Biological parameters that are difficult to measure would thus be estimated indirectly by investigating the structure of physicochemical data via non-linear statistical data modelling tools. The principle of this biomimetic approach is: a signal pattern from a sensor array, with different selectivities, is processed with multivariate data analysis for recognition and learning. This approach is an emerging technique also referred to as the virtual sensor [START_REF] Bourgeois | The use of sensor arrays for environmental monitoring: interests and limitations[END_REF][START_REF] Winquist | Voltammetric electronic tongues -basic principles and applications[END_REF], which bio-mimics the functioning of central nervous systems. Indeed, knowledge generation can be seen as data processing through transfer data from sensors into the brain where they are further processed and related to other information. There are already promising applications of sensors networks in the area of water resources management [START_REF] Yang | An online water quality monitoring and management system developed for the Liming River basin in Daqing, China[END_REF] or the definition of environmental condition indicators [START_REF] Marchini | F-IND: A framework to design fuzzy indices of environmental conditions[END_REF].

Statistical analysis of the structuring of continuously acquired data could thus lead to a relatively detailed typology of ways of functioning and alterations therein that could be extended to the characterisation of toxic metallic or organic ambiences. Analysing hydrobiological data as a function of physicochemical data is not original in itself. However, for two metrics to be compared they must have the same spatial and temporal representativeness. Indeed, because of the limits referred to above, the physicochemical data usually collected are localised in space and time (grab sampling). Comparing them with biological data that integrate the functioning of the environment over a period of weeks usually leads at best to tautologies: the biological data well explain the biological data [START_REF] Ocampo-Duque | A neural-fuzzy approach to classify the ecological status in surface waters[END_REF]. Given that, the distribution of aquatic organisms is closely subservient to physicochemical parameters [START_REF] Williams | The occurrence of benthos deep in the substratum of a stream[END_REF]. Our approach will therefore permit to compare comparable metrics, i.e. continuous physicochemical records and biological organisms, which by their nature, include physicochemical conditions experienced.

A REAL NEED OF NEW TOOLS

From 2004, Kirchner et al. pointed to the absurdity of some monitoring methods as stupid as trying to understand a symphony if one could only hear one note every minute or two! That is what we are trying to do when we infer the hydrochemical functioning of a catchment from weekly or monthly grab samples [START_REF] Kirchner | The fine structure of water-quality dynamics: the (high-frequency) wave of the future[END_REF]. Given this situation, automated monitoring systems are starting to be proposed. But, because of their complexity, cost and a few specific limitations (reliability and representatitivity), they are not yet used as much in water management as their potentials would allow. The deployment of networks of sensors covering all sensitive or nodal points for monitoring a water body involves miniaturising the sensors and lowering their unit cost. While current research into microsensors is leading to the emergence of many measuring principles, validation in real field conditions is still very rare. Furthermore, the micro-sensors that are marketed are based for the most part on UV-Visible technology and data processing, are generally controlled by proprietary programs that are totally unintelligible to the user and do not allow measurements to be optimised [START_REF] Rieger | Uncertainties of spectral in situ measurements in wastewater using different calibration approaches[END_REF].

Thus the specific requirements of remote water quality monitoring are not satisfied by existing microsensors [START_REF] Bertrand-Krajewski | Comparison of and uncertainties in raw sewage COD measurements by laboratory techniques and field UV-visible spectrometry[END_REF]Winkler et al., 2008a).

Consequently, faced with the magnitude of this metrological challenge and the urgency of the situation, a paradigm shift is required in order to imagine a new approach to the problem of water monitoring. A possible avenue that merits further exploration involves the deployment of low-cost instrumentation allowing massive data logging, as well as tools for subsequent data validation, management and interpretation. However, while this new type of instrumentation is possible, and even desirable, such deployment of sensors cannot at the present time cover all the WFD parameters.

An innovative feature of the WFD is its focus on ecological effects, which goes beyond the conventional notions of water quality estimating based on potentially harmful physical-chemical criteria. The quality of a particular environment, equivalent to its ecological status, is explicitly defined in terms of ecosystem structure and functions. This innovative framework calls thus for creativity and makes it essential to develop new approaches and new tools for monitoring the status of rivers at a reasonable cost (WFD, appendix III). To this end, we must develop a new environmental chemistry suitable for providing information on the quality and function of rivers and adapted to the hydrogeomorphological and dynamic characteristics of the water bodies monitored. Forsaking the vague expressions "undisturbed conditions" or "reference state" and others "pristine states" [START_REF] Dufour | From the Myth of a Lost Paradise to Targeted River Restoration: Forget Natural References and Focus on Human Benefits[END_REF], associated with good ecological status in the WFD, we propose to focus on the trophic structure, its function, and the changes induced by disturbing factors, in terms of the physical-chemical indicators.

Instead of taking individual and sporadic measurements of chemical and biological quality values, we propose a systemic approach in order to diagnose ecological states, by means of a wireless network of autonomous micro-sensors. The objective of its research phase is to establish rules for integrating the various types of information measured, followed in its industrial phase by the design of an automated warning and decision support system aiming at minimising environmental impacts. Thus, by using a bank of simple robust sensors, coupled to a mathematical data processing system, our aims are to identify critical zones and moments in order to guide and focus mitigating efforts specifically on these sensitive zones and at exactly the right time. Such a tool will also greatly facilitate our understanding of the ecological processes in water bodies in general and the water body management, in particular. There are some technological constrains to address as wireless, self powered, remote transfer of data and no harmful components for the environment. All these features are required to facilitating their implementation on field and creating observation networks.

We think that we need a Wireless Real-Time Monitoring System for continuous monitoring of water bodies, in the sense of the WFD, associating surface chemistry, electronics and energy harvesting with data processing.

Ecohydrology [START_REF] Zalewski | Ecohydrology -the scientific background to use ecosystem properties as management tools toward sustainability of water resources[END_REF][START_REF] Zalewski | Emerging opportunities for achieving the Millennium Development Goals[END_REF] (Fig. 1), a theory based on dual regulation of river health of water link flux of energy and biocenosis activity, would be the template to develop integrative knowledge and design strategy and equipments to mitigate anthropogenic pressure on the water resource as it can result form urban storm-water runoff.

Ecohydrology theory lies on three testable hypotheses [START_REF] Zalewski | Ecohydrology: A new paradigm for the sustainable use of aquatic resources[END_REF] that are: H1:

Hydrological processes generally regulate biota; H2:

Biota can be shaped as a tool to regulate hydrological processes; H3:

These two types of regulations (H1&H2) can be integrated with hydro-technical infrastructure to achieve sustainable water and ecosystem services.

Based on both currently available and new technologies, we will lay the groundwork for a new type of tool for surveillance and operational monitoring of water bodies. Its development will help to make significant improvements in real-time knowledge of their ecological status and help to quantify the results of efforts made to restore and rehabilitate rivers. From a more fundamental point of view, by bridging the gap between physicochemical determinants and biochemical functioning, we will pave the way for physical actions and biogeochemical stimulation measures with a view to restoring a good ecological status. Formally speaking, the aim is to support the field of restoration ecology for water systems, which involves studying their functioning and developing specific ecological engineering.

CONCLUSION

As environmental parameters present strong coherence due to the dynamic balances inherent in an ecosystem, a structured group of parameters can be exploited to deduce a particular quantity of them without necessarily measuring them directly. Also, there is emerging a new global approach, which, avoiding development of a more specific sensor, is centred on mathematical processing of signal from sensor network with the aim of deducing the monitored variable indirectly. This virtual sensor, otherwise known as "soft sensor" or "smart sensor", comprises an array of simple and reliable sensors that are not analyte specific but can be linked by a computer program to process certain sample features and build a proxy of the "unsensed" parameter. Virtual sensors will soon be able to measure a 'fingerprint' that can be analyzed by a pattern recognition system. Any sensor can be integrated into a virtual sensor system and its data pooled and processed. By deferring the sensor specificity to mathematical processing, smart sensor technology leads to a simplification of sensing elements and to a more robust sensor network.

The quality of this approach lies in how the data from the sensor networks is mathematically processed. These processing steps span chemometrics to artificial neural networks (ANNs) and genetic algorithms, and can be clustered under two main objectives:

1) Determine structure and data correlations using principal component analysis (PCA) and/or canonical analysis;

2) Establish a model from the data that can be used in predictive mode. In this second approach, the techniques used are projections to latent structures and partial least squares (PLS) regression that generalize and fuse the PCA, and the multiple regression methods, or ANNs.

Nowadays, the majority of the statistical treatments used bring only qualitative information, and not quantitative.

At present, the virtual sensor technology is still under development. But already, and despite the expected difficulties associated with this strongly transdisciplinary approach, some promising results have been obtained.

Sensor technologies have emerged from environmental sciences in the last couple of decades as a promising tool and are still in their infancy. They now require validation. Water quality monitoring is currently based on standardized laboratory methods. Sensors, despite being developed more recently, do not have the same recognition capacities and are only seldom used, despite their advantages. Field validations are needed in order to boost their credibility. ISO standard 15839 (released in 2003) provides a consistent protocol for characterizing these sensors, and should facilitate their adoption for routine use by regulatory bodies. Further work is required to increase their operational period, and particularly to prevent bio-fouling and clogging. Other technological challenges include miniaturization of on-chip modules, cutting energy consumption, developing in situ fuelling, eco-design, geolocation, communication checking, and data validation and transmission. It is equally imperative to improve data management. Clearly, there is plenty of room for progression.

Fig 1 :

 1 Fig 1: Dual regulation concept (adapted from[START_REF] Zalewski | Ecohydrology: A new paradigm for the sustainable use of aquatic resources[END_REF]),

ACKNOWLEDGMENTS

The authors thank the French National Research Agency (INVASION ANR n°08 CESA 022 and EPEC ANR n°10 ECOT 007) for their financial support.

LIST OF REFERENCES


Frank Bellivier

Pierre Alexis Geoffroy

Jan Scott

Franck Schurhoff

Marion Leboyer

Bruno Etain

Biomarkers of bipolar disorder: specific or shared with schizophrenia?

ABSTRACT

Kraepelin's observations of the differences in the course and outcome of dementia praecox and manic depression fundamentally influenced thinking about bipolar disorder (BP) and schizophrenia (SZ) for over a century. In modern times, there is increasing awareness that a greater understanding of the similarities between these two highly prevalent and disabling conditions can teach us as many lessons about the pathophysiology of severe mental disorders as does the pursuit of differentiating factors. We review publications on developmental, genetic, epidemiological, and outcome research that challenges the Kraepelian dichotomy. We highlight the increasing evidence of the overlap in genetic susceptibility. Neuro-developmental studies provide evidence of shared early pathological processes, whilst neurophysiological investigations also suggest that different genes may have a role in the development of both phenotypes. There is also evidence of overlapping neurocognitive phenotypes. It has become increasingly clear that a simple binary classification of these disorders represents an oversimplification. It may be more apposite to think in terms of genetic influences on six continuous symptom dimensions: neurobiological, cognitive, positive, negative, depressive and manic symptoms.

2.INTRODUCTION

"It is becoming increasingly obvious that we cannot satisfactorily distinguish these two diseases (dementia praecox and manic depression)." Emil Kraepelin, 1920. Schizophrenia (SZ) and bipolar disorder (BD) are frequently occurring conditions that are recognized as leading causes of lifetime disability [START_REF] Cr Bowie | Prediction of real-world functional disability in chronic mental disorders: a comparison of schizophrenia and bipolar disorder[END_REF]. Both disorders are characterized by abnormalities of thought, behaviour, cognition and mood. Based on careful clinical observations of differences in the clinical course and outcome of psychiatric cases presenting to asylums over a century ago, Kraepelin distinguished dementia praecox from manic depression. The separation of these two major mental disorders has cast a long shadow over psychiatry that has continued to shape but also to distort views about the classification of mental disorders up to the present day (2). However, what is often overlooked is that Kraepelin was also the first 'scientistpractitioner' to recognize the overlap and similarities in the presentation and clinical course in many cases of SZ and BD-an observation that we will discuss in the following review.

There are several well-established arguments that have been used to continue the support of the traditional Kraepelian dichotomy. For example, clinical descriptions indicated distinct phenomenology's and treatment outcomes such as the recurrent nature of affective disorders and the evidence of efficacy of antidepressants in depression and mood stabilizers in BD, compared with SZ, which is characterized by specific positive and negative symptoms, cognitive decline and response to treatments such as antipsychotics (which are mainly efficacious for positive symptoms). Some research also suggests that there are differences between SZ and BD on structural and functional neuro-imaging and neurocognitive assessment batteries (3) (4) [START_REF] Krabbendam | Cognitive functioning in patients with schizophrenia and bipolar disorder: a quantitative review[END_REF]. However, diagnostic classification systems are clearly inspired by the Kraepelinian dichotomy, and so for the most part, researchers have approached the disorders as distinct entities with assumed different aetiologies. Insel and others (6) have promoted the need to rethink investigative approaches and examine evidence of deficits or abnormalities in different research domains (eg cognitive, neuro-endocrine, neuro-imaging studies) to build a dimensional picture of clinical presentations. This strategy helps clinicians identify similarities as well as differences between disorders and is in keeping with emerging research such as the family genetic studies of Lichtenstein and colleagues [START_REF] Lichtenstein | Common genetic determinants of schizophrenia and bipolar disorder in Swedish families: a population-based study[END_REF]. This review highlights important overlaps between SZ and BD that suggest the need to reflect on the utility of the Kraepelian dichotomy in contemporary clinical and research practice.

THE KRAEPELINIAN DICHOTOMY REVISITED

Several observations challenged the Kraepelinian dichotomy such as diagnostic instability in both disorders, frequency of schizo-affective cases, familial co-aggregation and efficacy of new antipsychotics in both disorders. In addition, dissatisfaction with the Kraepelinian dichotomy in research has also been growing and recent evidences from developmental, genetic, cognitive, neuro-imaging suggest that the two diseases have much more in common than was previously thought. Finally, the "outcome" criteria that was supposed to discriminate between SZ and BD has been challenged by recent follow up studies that show that poor prognosis is not constant in SZ patients (8) and that for BD is not as good as previously thought [START_REF] Lee | The long-term outcome of Maudsley depressives[END_REF].

Family, high risk and twin studies

Family, high-risk, and twin studies provide evidence for the existence of both shared and specific vulnerabilities to SZ and affective psychosis [START_REF] Kerr | Concepts of Mental Disorder[END_REF] [START_REF] Ma Taylor | Are schizophrenia and affective disorder related? A selective literature review[END_REF] [START_REF] Berrettini | Evidence for shared susceptibility in bipolar disorder and schizophrenia[END_REF].

With regard to family studies, the Roscommon study showed clear co-aggregation of the two disorders suggesting that the familial vulnerability to SZ was at least in part a liability to develop psychosis in general [START_REF] Ks Kendler | The Roscommon Family Study: I. Methods, Diagnosis of Probands, and Risk of Schizophrenia in Relatives[END_REF]. The Mainz study showed an increased risk of unipolar depression in the relatives of schizophrenic patients [START_REF] Maier | Continuity and Discontinuity of Affective Disorders and Schizophrenia: Results of a Controlled Family Study[END_REF]. A Danish population-based study (2.1 million subjects) showed that the risk of BD was associated with a history of BD (OR=13.6) as well as SZ or schizo-affective disorder (OR=4.2) in parents or siblings [START_REF] Pb Mortensen | Individual and Familial Risk Factors for Bipolar Affective Disorders in Denmark[END_REF], again suggesting the existence of both shared and specific vulnerabilities to SZ and BD. However, the architecture of familial risk factors remains complex. Indeed, relatives of SZ patients have an increased risk for both disorders with a higher risk for SZ (10%) than for BD (8%) and relatives of BD patients have an increased risk for both disorders with a much higher risk for BD (10%) than for SZ (3.5%) [START_REF] Pb Mortensen | Individual and Familial Risk Factors for Bipolar Affective Disorders in Denmark[END_REF]. This is also illustrated by a recent family study that examined the prevalence of psychiatric disorders in the first-degree relatives of a sample of 103 inpatients with severe and chronic BD and in a matched control sample of 84 healthy individuals. The relative risks were 14.2 for BD and 4.9 for SZ. Furthermore, the presence of more than one patient with BD in a family increased the risk for SZ nearly fourfold (relative risk!3.5). Altogether, these results suggest that BD, characterized by a high familial loading, is associated with increased risk of SZ in the relatives [START_REF] Vallès | Increased morbid risk for schizophrenia in families of in-patients with bipolar illness[END_REF]. Perhaps the most important study to date was published by [START_REF] Lichtenstein | Common genetic determinants of schizophrenia and bipolar disorder in Swedish families: a population-based study[END_REF] [START_REF] Lichtenstein | Common genetic determinants of schizophrenia and bipolar disorder in Swedish families: a population-based study[END_REF] who identified more than 9 millions individuals in more than 2 million nuclear families in Sweden and investigated [START_REF] Cr Bowie | Prediction of real-world functional disability in chronic mental disorders: a comparison of schizophrenia and bipolar disorder[END_REF] the risks for SZ, BD for biological and adoptive parents, offspring and (2) the genetic and environmental contributions to liability for SZ and BD. Shared genetic effects for SZ that were in common with BD accounted for 52% of the genetic variance in SZ and for 69% in BD. Finally, the Roscommon family study also showed that the relatives of probands with nonpsychotic BD did not have an increased risk for SZ [START_REF] Ks Kendler | The Roscommon Family Study: I. Methods, Diagnosis of Probands, and Risk of Schizophrenia in Relatives[END_REF].

A 25-years follow up study of high risk subjects indicated that the risk of SZ (and related psychosis) and affective psychosis was increased both in subjects at risk for SZ and in subjects at risk for affective disorder [START_REF] Erlenmeyer-Kimling | The New York High-Risk Project. Prevalence and comorbidity of axis I disorders in offspring of schizophrenic parents at 25-year follow-up[END_REF]. However, the risk of non-psychotic affective illness was not elevated by comparison with the control group and not different in the two high-risk groups.

Twin studies also provide important evidence for both common and syndrome-specific genetic contributions to the variance in liability to SZ and BD. Indeed, the Maudsley Study that included all psychotic twins for over four decades also suggested the existence in such individuals of a predisposition to psychosis in general, as well as specific genetic factors for each syndrome [START_REF] Ag Cardno | Heritability estimates for psychotic disorders: the Maudsley twin psychosis series[END_REF]. The study of this cohort also indicated that vulnerability to schizo-affective disorder was shared with SZ and BD showing a degree of overlap in the genetic and non genetic familial factors contributing to both disorders [START_REF] Ag Cardno | A twin study of genetic relationships between psychotic symptoms[END_REF].

The interpretation of family and twin studies remains difficult due to heterogeneity of the groups compared in terms of the number of the family members available, their age at interview, other not controlled disease risk factors, and the correlations between measurements (due to the family members being related to each other) that influence the calculation of a morbid risk. Although many studies use sophisticated statistical approaches to minimize biases, these analyses performed in the context of diagnostic uncertainties and diagnostic instability between SZ and BD, mean that co-aggregation studies in SZ and BD could provide spurious evidence for familial co-aggregation [START_REF] Lin | Approaches for unraveling the joint genetic determinants of schizophrenia and bipolar disorder[END_REF] [START_REF] Ji Hudson | Multivariate logistic regression for familial aggregation of two disorders. I. Development of models and methods[END_REF].

Molecular Genetic studies

The evidence obtained of this strong family heritability in SZ and BD, much work has been done to identify susceptibility genes [START_REF] Berrettini | Bipolar disorder and schizophrenia: convergent molecular data[END_REF]. Several well-established linkages have emerged in both disorders (for review [START_REF] Craddock | The genetics of schizophrenia and bipolar disorder: dissecting psychosis[END_REF]). Recent findings emerging from molecular genetic studies show increasing evidence for an overlap in genetic liability across the traditional binary classification. Indeed, linkage studies and Genome Wide Association Studies (GWAS) have identified several overlapping regions of interest in both SZ and BD, including several regions on chromosome 1q, 13q, 22q, 6q, 8p and 18 [START_REF] Badner | Meta-analysis of whole-genome linkage scans of bipolar disorder and schizophrenia[END_REF] [START_REF] Berrettini | Evidence for shared susceptibility in bipolar disorder and schizophrenia[END_REF] [START_REF] Hamshere | Evidence for linkage (LOD = 3.54) at IQ42 close to DISC1 in a genome scan of functional psychosis pedigrees including at least one member with schizoaffective disorder of bipolar type (abstract)[END_REF]. Interpretation of overlaps in linkage studies of different syndromes are sometime difficult due to the size of the overlapping region identified by the linkage signal and statistical evidence for significant co-occurrence remain difficult to obtain. Interpretations of GWAS are also difficult with regard to the "common liability" hypothesis as these studies may identify single nucleotide polymorphisms (SNPs) that turn out to be associated to both syndromes or may reveal the existence of different SNPs in the same gene to be associated with each disorder.

Despite those methodological issues, additional evidence validates shared genetic susceptibility with genetic analyses of schizo-affective disorder which identified similar regions that SZ and BD have in common [START_REF] Ml Hamshere | Genomewide linkage scan in schizoaffective disorder: significant evidence for linkage at 1q42 close to DISC1, and suggestive evidence at 22q11 and 19p13[END_REF] suggesting that the pathophysiological processes involved in schizo-affective disorders correlate with those involved in both SZ and BD. The candidate gene approach provided a major contribution to this debate as polymorphisms of genes located in these "common" regions showed replicated association with both syndromes as well as association with schizo-affective disorder. Current evidence supports such hypothesis for DAOA (G30/G72) gene on chromosome 13q22-34, DTNBP1 gene on chromosome 6p22, NRG1 gene on chromosome 8p12, DISC1 gene on chromosome 1q42, COMT gene on chromosome 22q11 and to a lesser extend the BDNF gene on chromosome 11p13.

Consistent association and linkage results have been obtained between DAOA gene polymorphisms and SZ, BD and schizo-affective disorder (27) (28) (24) (29) [START_REF] Schumacher | Examination of G72 and D-amino-acid oxidase as genetic risk factors for schizophrenia and bipolar affective disorder[END_REF], but the data as they stand do not support that variations on DAOA increase the susceptibility to these syndromes per se. Instead, DAOA/G30 influences susceptibility to major mood episode across the classical SZ and BD diagnostic categories [START_REF] Williams | Variation at the DAOA/G30 locus influences susceptibility to major mood episodes but not psychosis in schizophrenia and bipolar disorder[END_REF]. Similarly, DAOA/G75 seems to be associated with psychotic symptoms in both categories [START_REF] Tg Schulze | Genotype-phenotype studies in bipolar disorder showing association between the DAOA/G30 locus and persecutory delusions: a first step toward a molecular genetic classification of psychiatric phenotypes[END_REF] [START_REF] Fs Goes | Mood-incongruent psychotic features in bipolar disorder: familial aggregation and suggestive linkage to 2p11-q14 and 13q21-33[END_REF]. A quite similar picture has been obtained with the DTNBP1. This gene polymorphism has been associated with psychotic features [START_REF] Raybould | Bipolar disorder and polymorphisms in the dysbindin gene (DTNBP1)[END_REF] and with negative symptoms rather than with the full syndrome [START_REF] Ah Fanous | Relationship between a high-risk haplotype in the DTNBP1 (dysbindin) gene and clinical features of schizophrenia[END_REF]. Strong evidence for linkage and association with the NRG1 gene polymorphism has been obtained in SZ (review [START_REF] Tosato | Association between the neuregulin 1 gene and schizophrenia: a systematic review[END_REF]. Of interest is the fact that association between this gene polymorphism and BD has been reported, in particular in the subgroup of patients with psychotic features, as well as in the subgroup of schizophrenic patients who experienced mania [START_REF] Ek Green | Operation of the schizophrenia susceptibility gene, neuregulin 1, across traditional diagnostic boundaries to increase risk for bipolar disorder[END_REF]. Recent studies reported association of two NRG1 haplotypes with SZ and BD in a Scottish case-control sample, but those findings need further studies since it wasn't wholly replicated in a second sample [START_REF] Pa Thomson | Association of Neuregulin 1 with schizophrenia and bipolar disorder in a second cohort from the Scottish population[END_REF] [START_REF] Walker | Association analysis of Neuregulin 1 candidate regions in schizophrenia and bipolar disorder[END_REF].

The DISC1 gene shows the strongest evidence for influencing the susceptibility to both SZ, BD and schizo-affective disorder [START_REF] Hennah | Genes and schizophrenia: beyond schizophrenia: the role of DISC1 in major mental illness[END_REF] [START_REF] Rs Devon | Identification of polymorphisms within Disrupted in Schizophrenia 1 and Disrupted in Schizophrenia 2, and an investigation of their association with schizophrenia and bipolar affective disorder[END_REF] [START_REF] Ca Hodgkinson | Disrupted in schizophrenia 1 (DISC1): association with schizophrenia, schizoaffective disorder, and bipolar disorder[END_REF] [START_REF] Ttjp Kockelkorn | Association study of polymorphisms in the 5' upstream region of human DISC1 gene with schizophrenia[END_REF] [START_REF] Pa Thomson | Association between the TRAX/DISC locus and both bipolar disorder and schizophrenia in the Scottish population[END_REF]. In addition, association studies and gene expression analyses of the DISC1-interacting molecules, pericentrin 2 (PCNT2) and DISC1-binding zinc finger protein (DBZ), showed association with both SZ and BD [START_REF] Anitha | Association studies and gene expression analyses of the DISC1-interacting molecules, pericentrin 2 (PCNT2) and DISC1-binding zinc finger protein (DBZ), with schizophrenia and with bipolar disorder[END_REF]. Further, GWAS analysis in SZ and BD found significant association evidence for polymorphisms in CACNA1C gene [START_REF] Ml Hamshere | Genome-wide significant associations in schizophrenia to ITIH3/4, CACNA1C and SDCCAG8, and extensive replication of associations reported by the Schizophrenia PGC[END_REF] [START_REF] Sklar | Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4[END_REF]. Findings with CACNA1C gene polymorphism suggested that the subphenotype of BD with psychosis may represent a clinical manifestation of shared genetic liability between BD and SZ [START_REF] Lett | ANK3, CACNA1C and ZNF804A gene variants in bipolar disorders and psychosis subphenotype[END_REF].

Results obtained with the COMT gene polymorphism show evidences for association and linkage with SZ and BD (24) (28) [START_REF] Ml Hamshere | Genomewide linkage scan in schizoaffective disorder: significant evidence for linkage at 1q42 close to DISC1, and suggestive evidence at 22q11 and 19p13[END_REF] [START_REF] Jb Potash | Suggestive linkage to chromosomal regions 13q31 and 22q12 in families with psychotic bipolar disorder[END_REF]. But these results do not support a simple role for this gene and an effect on the bipolar and schizophrenic phenotype ('phenotype modifier') rather than on the susceptibility to these disorders is likely. Indeed, an association between the functional Val/Met polymorphism of this gene and cognitive frontal lobe function have been reported and has been recently replicated in the two syndromes showing an association between the functional Val (158)Met polymorphism and working memory performance, with a particular vulnerability of SZ but not for BD subjects [START_REF] Kv Wirgenes | Catechol Omethyltransferase variants and cognitive performance in schizophrenia and bipolar disorder versus controls[END_REF]. In addition, the shared phenotype between SZ and BD associated with this gene is not yet identified, however a study found that the COMT Val allele was associated with greater positive symptomatology in SZ, whereas Met homozygosis was associated with greater positive symptomatology in BD [START_REF] Vm Goghari | Differential association of the COMT Val158Met polymorphism with clinical phenotypes in schizophrenia and bipolar disorder[END_REF]. These findings support that the COMT Val158Met polymorphism is conferring vulnerability for different clinical phenotypes in SZ and BD. Association and linkage with the BDNF gene polymorphism have also been reported, in particular with depression in SZ as well as rapid cycling in BD ( 52) [START_REF] Schumacher | Evidence for a relationship between genetic variants at the brain-derived neurotrophic factor (BDNF) locus and major depression[END_REF]. Evidence of an association between BDNF and BD and SZ has been recently confirmed [START_REF] Pae | Influence of BDNF variants on diagnosis and response to treatment in patients with major depression, bipolar disorder and schizophrenia[END_REF].

Results favouring the implication of common genetic variants in the susceptibility to BD and SZ emerged from disease-specific genome-wide association study (GWAS) but also from meta-analysis in pooled samples. Mühleisen et al found that a common variation in the gene neurocan (NCAN, rs1064395), which confers risk for BD, was significantly over-represented in SZ patients [START_REF] Tw Mühleisen | Association between schizophrenia and common variation in neurocan (NCAN), a genetic risk factor for bipolar disorder[END_REF]. Moreover, association between ZNF804A gene (encoding zinc-finger protein 804A) and both SZ and BD was found [START_REF] Hj Williams | Donovan: Fine mapping of ZNF804A and genome-wide significant evidence for its involvement in schizophrenia and bipolar disorder[END_REF]. Finally, the frontotemporal lobar degeneration risk gene progranulin (GRN) was analysed in both BD and SZ patients showing that GRN variability decreases the risk to develop both disorders [START_REF] Galimberti | Progranulin gene variability and plasma levels in bipolar disorder and schizophrenia[END_REF].

Although both disorders are complex and multifactorial models to test the contribution of polygenic variations have not been published until recently. Of interest is the recent work performed by the ISC (International Schizophrenia Consortium, ( 58)) that provide evidence for a common polygenic component in SZ and BD.

Beyond molecular genetics, the field of biomarkers in psychiatry has been enriched by approaches using molecular non-genetic markers. This approach aims at the identification of distinct molecular signatures in peripheral blood of patients and has particularly focused on peripheral gene expression or serum-based biomarkers ( 59) [START_REF] Schwarz | Identification of a blood-based biological signature in subjects with psychiatric disorders prior to clinical manifestation[END_REF]. The objective is to increase knowledge of the pathophysiological determinants of SZ and BD targeting molecular alterations that are thought to reflect the interaction between the underlying genetic predisposition and the environmental influences. For example, multiplex immunoassay analyses were carried out using serum from BD and SZ within 1 month before first symptoms of both disorders, and found shared but mostly distinct serum alterations in SZ and BD [START_REF] Schwarz | Identification of a blood-based biological signature in subjects with psychiatric disorders prior to clinical manifestation[END_REF].

In summary, molecular genetic findings strongly support genetic factors conferring susceptibility across a BD-SZ continuum. Results indicate that these polymorphisms may act as common vulnerability factors for the syndromes or as phenotype modifiers. None of the genes presented in this review has a specific risk variant replicated but potential effect on different aspects of psychopathology is likely. It also turns out that some genes may have a predominant effect on the "BD" phenotype (such as DAOA and BDNF), other on the "SZ" phenotype (such as DTNBP1) or on a "schizo-affective" phenotype (such as DISC1 or NRG1). Then, this is probably the very beginning of the story and the data should be interpreted with caution both for the implication on psychiatric nosology and to elucidate the pathophysiological pathways of these syndromes. But it has become increasing clear that the genetic data showed an overlap between the two diseases and are not compatible with a simple dichotomy of disorders.

Neuro-developmental studies

Several lines of evidence support the neuro-developmental hypothesis of SZ and BD where both diseases can be considered as pathophysiological processes starting early in life and resulting in pathological conditions during adulthood. This field of research also provided evidences of shared early pathological processes. As reviewed previously, the implication of common genetic vulnerability factors that may act early during development, event during foetal life, is consistent with this hypothesis. These common risk factors may have unspecific effects on the vulnerability to both syndromes. Developmental risk factors such as prenatal maternal nutritional deficiency [START_REF] Susser | Schizophrenia after prenatal famine. Further evidence[END_REF], season of birth [START_REF] Hare | Mental disorder and season of birth[END_REF], urbanity [START_REF] Lewis | Schizophrenia and city life[END_REF] and obstetrical complications (64) ( 65) have long been demonstrated in SZ. Of interest is that the implication of these factors has also been suggested in BD such as prenatal malnutrition [START_REF] Brown | Further evidence of relation between prenatal famine and major affective disorder[END_REF], neurological soft signs [START_REF] Jones | Child development risk factors for adult schizophrenia in the British 1946 birth cohort[END_REF] [START_REF] Van Os | Developmental precursors of affective illness in a general population birth cohort[END_REF], urbanicity [START_REF] Marcelis | Urbanization and psychosis: a study of 1942-1978 birth cohorts in The Netherlands[END_REF], pregnancy and obstetric complications (70) ( 71) and the same deviation on season of birth as the one observed in SZ [START_REF] Cm Hultman | Prenatal and perinatal risk factors for schizophrenia, affective psychosis, and reactive psychosis of early onset: case-control study[END_REF]. Most of these studies also indicate a gradient of severity of these development risk factors with a smaller effect size in BD by comparison with SZ, suggesting a continuum of severity between non affected and SZ, BD being an intermediate pathological condition [START_REF] Cm Hultman | Prenatal and perinatal risk factors for schizophrenia, affective psychosis, and reactive psychosis of early onset: case-control study[END_REF] [START_REF] Marcelis | Urbanization and psychosis: a study of 1942-1978 birth cohorts in The Netherlands[END_REF] [START_REF] Scott | Exposure to obstetric complications and subsequent development of bipolar disorder: Systematic review[END_REF] [START_REF] Kinney | Pre-and perinatal complications and risk for bipolar disorder: a retrospective study[END_REF]. Birth cohort studies also indicate that premorbid functioning during childhood was impaired in both disorders, but again the effect size was larger in SZ by comparison with affective disorders [START_REF] Jones | Child development risk factors for adult schizophrenia in the British 1946 birth cohort[END_REF] [START_REF] Van Os | Developmental precursors of affective illness in a general population birth cohort[END_REF]. The neurodevelopmental models of SZ and BD also include specific hypotheses regarding disruption of foetal development by prenatal maternal infection. A number of studies have suggested that exposure to infections, such as toxoplasma gondii or herpes simplex virus, as a risk factor for the development of both SZ and BD [START_REF] Prasad | Exposure to Herpes Simplex Virus Type 1 and Cognitive Impairments in Individuals With Schizophrenia[END_REF][START_REF] Bd Pearce | The Relationship Between Toxoplasma Gondii Infection and Mood Disorders in the Third National Health and Nutrition Survey[END_REF][START_REF] Sa Henriquez | Neuropsychiatric disease and Toxoplasma gondii infection[END_REF].

The classical Kraepelinian view suggesting that SZ was associated with a poorer outcome by comparison with affective disorder have also been revisited and recent studies show that poor outcome is not a rule during SZ [START_REF] Mason | The predictive validity of a diagnosis of schizophrenia. A report from the International Study of Schizophrenia (ISoS) coordinated by the World Health Organization and the Department of Psychiatry, University of Nottingham[END_REF] and that significant proportion of BD patients have a poor outcome [START_REF] Lee | The long-term outcome of Maudsley depressives[END_REF]. However, it should be acknowledged that many of the studies purporting to study BD often included significant proportions of cases with affective psychosis. This means that studies that show shared risk factors for the development of SZ of BD (eg research on obstetric complications), need to be reviewed carefully to ascertain whether they are reporting risk for psychotic symptoms or shared risk for different diagnostic syndromes.

Neuro-imaging studies 3.4.1. Structural neuro-imaging studies

There is compelling evidence for the existence of brain structural abnormalities in both SZ and BD [START_REF] De | Brain structural abnormalities at the onset of schizophrenia and bipolar disorder: a meta-analysis of controlled magnetic resonance imaging studies[END_REF]. Recent metaanalysis of De Peri et al. shows significant overall effect sizes for intracranial, whole brain, total grey and white matter volume reduction as well as for an increase of lateral ventricular volume at disease onset for both BD and SZ. This study is important as it suggests overlapping brain abnormalities are already present at the onset of both diseases [START_REF] De | Brain structural abnormalities at the onset of schizophrenia and bipolar disorder: a meta-analysis of controlled magnetic resonance imaging studies[END_REF]. However, both disorders may present neurodevelopmental specificities as whole grey matter volume deficits and lateral ventricular enlargement that appear to be more prominent in first-episode SZ, whereas white matter volume reduction seems more prominent in first-episode BD [START_REF] De | Brain structural abnormalities at the onset of schizophrenia and bipolar disorder: a meta-analysis of controlled magnetic resonance imaging studies[END_REF]. BD in comparison with SZ is associated with smaller lateral ventricular volume and enlarged amygdala volume [START_REF] Arnone | Magnetic resonance imaging studies in bipolar disorder and schizophrenia: meta-analysis[END_REF]. SZ seems to be characterized by progressive global cortical losses (80) [START_REF] Honea | Regional deficits in brain volume in schizophrenia: a meta-analysis of voxelbased morphometry studies[END_REF] whereas in BD, cortical volume losses are more focused and mostly located in prefrontal cortex and cingulate [START_REF] Fornito | Reconciling neuroimaging and neuropathological findings in schizophrenia and bipolar disorder[END_REF]. Genetic risk for BD and SZ are associated with specific grey matter but generic white matter endophenotypes that confirm a more complex picture than a simple Kraepelian dichotomy [START_REF] Mcdonald | Association of genetic risks for schizophrenia and bipolar disorder with specific and generic brain structural endophenotypes[END_REF].

Regarding subcortical structures, structural studies tend to show a decreased volume of the striatum, thalamus, hippocampus, parahippocampus, and amygdala in SZ [START_REF] Dc Glahn | Meta-analysis of gray matter anomalies in schizophrenia: application of anatomic likelihood estimation and network analysis[END_REF] [START_REF] Fornito | Reconciling neuroimaging and neuropathological findings in schizophrenia and bipolar disorder[END_REF]. These modifications are usually not observed in BD in which some structures implicated in mood regulation such as the limbic system may be increased in volume. More specifically, the pattern of amygdala volume increase seems specific to adult BD patients [START_REF] Hajek | Amygdala volumes in mood disorders--meta-analysis of magnetic resonance volumetry studies[END_REF].

For white matter, patients with SZ exhibit a fronto-temporal anatomical disconnection when studied by diffusion tensor MRI [START_REF] Ellison-Wright | Meta-analysis of diffusion tensor imaging studies in schizophrenia[END_REF], while BD is characterized by abnormalities in prefrontal-subcortical networks (87) [START_REF] Versace | Elevated left and reduced right orbitomedial prefrontal fractional anisotropy in adults with bipolar disorder revealed by tract-based spatial statistics[END_REF]. But, while genetic risks for SZ and BD are associated with different grey matter changes, they share common white matter endophenotypes [START_REF] Mcdonald | Association of genetic risks for schizophrenia and bipolar disorder with specific and generic brain structural endophenotypes[END_REF].

Altogether, the existence of both shared and specific anatomical biomarkers is likely. The interpretation of these data remains difficult due to the possible confounding effect of medication. Indeed, increased volume of some brain regions has been reported with the use of antipsychotics, which are prescribed in both diseases [START_REF] Stip | Increased grey matter densities in schizophrenia patients with negative symptoms after treatment with quetiapine: a voxel-based morphometry study[END_REF]. Psychotic BD may also be a confounding factor but most of the grey matter structural differences between BD and SZ persist even if the bipolar group is restricted to patients with psychotic features [START_REF] Mcdonald | Regional brain morphometry in patients with schizophrenia or bipolar disorder and their unaffected relatives[END_REF].

Functional neuro-imaging studies

The studies investigating resting blood flow in psychiatric patients using PET produced conflicting results, in particular with regard to the level of activation of the frontal cortex, both in SZ (91) (92) (93) [START_REF] Kp Ebmeier | Singlephoton emission computed tomography with 99mTc-exametazime in unmedicated schizophrenic patients[END_REF] and BD (95) (96) [START_REF] Wc Drevets | Neuroimaging abnormalities in the subgenual prefrontal cortex: implications for the pathophysiology of familial mood disorders[END_REF]. Thus, these studies failed to provide consistent evidence of differential (or similar) patterns between the two syndromes. Some data indicate that frontal blood flow may represent a state marker, with hypofrontality being associated with non-specific dimensions of depression and/or psychomotor retardation [START_REF] Rj Dolan | Dorsolateral prefrontal cortex dysfunction in the major psychoses; symptom or disease specificity?[END_REF]. Whilst most resting state PET studies in SZ indicated hypofrontality [START_REF] Hill | Hypofrontality in schizophrenia: a metaanalysis of functional imaging studies[END_REF], studies in BD demonstrate discrepant results depending on the thymic state of patients: altered frontal blood flow in depression and subcortical increased blood flow in mania (100). Overall, uncontrolled clinical state as well as difficulties in controlling for cognitive activity during the assessment may account for these inconsistencies.

Functional studies undertaken during cognitive activation have produced more consistent findings. Despite the fact that there are very few direct fMRI comparisons between BD and SZ (due to the difficulty to design an activation task relevant for both disorders), fMRI studies of executive functions report large prefrontal activation deficits in SZ (101) (102) with more disparate findings in BD, depending on the clinical state: prefrontal hypoactivation is reported in euthymic BD and relative increases in BD depression (103).

Using facial emotion processing tasks, fMRI studies show a pattern of prefrontal cortical hypoactivation common in SZ and BD (104) (105). Subcortical hypoactivations are also observed in such studies ( 105), but patients with BD usually show subcortical, limbic hyperactivations (104).

Of interest is a recent study of Hulshoff et al. that investigated whether BD and SZ twins display overlapping abnormalities in brain structures and whether these are caused by shared genetic or environmental influences (106). Authors found that higher genetic liabilities for SZ and BD were associated with smaller white matter volume, thinner right and left parahippocampus, thinner right orbitofrontal cortex, and thicker temporoparietal and left superior motor cortices (106). Such a study helps demonstrating that brain structures are likely to reflect the influence of genetic liabilities and neurodevelopmental factors to determine a shared vulnerability between SZ and BD. In summary, brain imaging studies remain inconclusive mainly because they have not been designed to specifically compare common or specific features of SZ and BD, but usually compare cases to controls. Most of our knowledge relies on the comparison of the results of studies of BD patients to studies of SZ patients. Another difficulty relies on the fact that brain imaging biomarkers appear to be largely influenced by several confounding factors such as the clinical state, medication, duration of the disease and age at assessment, IQ, that are difficult to control for (107).

Neurophysiological studies

The existence of neurophysiological deficits in SZ has been the subject of substantial research efforts for last decades. Most of these deficits have been also demonstrated in unaffected relatives of SZ patients and frequently occur before the onset of the disease. Of interest, is that most of these deficits have also been evidenced in bipolar patients and their unaffected relatives. In particular, several abnormalities in information processing have been associated with the two potential biomarkers: Smooth Eyes Movement abnormality (SEM), P300-evoked response latency (108) and amplitude (109) P50 auditory-evoked response suppression (110) (111), prepulse inhibition [START_REF] Perry | Sensorimotor gating deficits in bipolar disorder patients with acute psychotic mania[END_REF] and a mismatch negativity paradigm (113). In addition, preliminary data suggest linkage between some neurophysiological biomarkers and genetic vulnerability factors. Altogether it represents a very encouraging area of research for the identification of valid endophenotype biomarkers shared by SZ and BD.

Smooth Eyes movement abnormality has long been demonstrated in schizophrenic patients (114) (115) (116) and their unaffected relatives (for review (117)). This abnormality is mainly observed in SZ patients with negative symptoms (118) (119) as well as their unaffected relatives (118). SEM abnormality has also been reported in patients with affective disorders (120) (121) (122) as well as in unaffected relatives of bipolar patients (120) (123). Significant linkages of SEM abnormality have been obtained by two independent studies on chromosome 6p21-23, a common susceptibility region for SZ and BD (124) (125).

Deficit in the inhibition of a positive evoked potential occurring 50msec after a redundant stimulus (named sensory gating P50 deficits) has been the subject of numerous studies in SZ and BD. In SZ a recent meta-analysis clearly demonstrates the existence of sensory gating deficits in patients (28 studies) and relatives (6 studies) (126). They also indicated that between studies differences in effect size may be related to true variability in the participants studied as well as testing procedures (126). Diminished suppression of P50 auditory stimulus response has also been demonstrated in BD patients characterized by psychotic features only (110) (127). Deficits in P50 suppression have also been reported in the relatives of BD probands with psychotic features (128) (129) (130). No significant influence of medications or clinical state on these deficits has been reported (131) (132) [START_REF] Arango | Olanzapine effects on auditory sensory gating in schizophrenia[END_REF]. After Freedman et al. (1997) (134) reported a linkage between P50 inhibition deficits and markers on chromosome 15q14, subsequent associations between polymorphisms (in particular in the promoter region) of the alpha-7 nicotinic cholinergic receptor subunit gene and both SZ (135) and BD (136) was reported. These results are consistent with several physiological (135) and pharmacological (137) (138) studies indicating the implication of low affinity nicotinic receptors in the P50 gating.

The startle reflex is known to be in the normal range in SZ patients, but they generally show a reduced inhibition associated with the prepulse in the prepulse inhibition (PPI) paradigm (for review ( 139)). Although influenced by drugs, the sensori-motor deficit observed in SZ appears to be a trait marker and is not related to their treatment or their clinical state. In addition PPI impairment has also been evidenced in non-affected first-degree relatives of SZ patients (139). PPI deficits have also been reported in remitted BD patients (140) (141) (142) and in relatives of BD patients (140) (143) (144). However, PPI impairment is possibly aspecific since reported in several other neuropsychiatric diseases such as obsessive compulsive disorder, attention deficit hyperactivity disorder, tic and Huntington disease (for review in ( 139)). Genetic studies of PPI deficits include several interesting findings. A missense mutation in the NRG1 gene has been associated with PPI deficit in SZ patients as well as in control subjects (145), consistent with the findings in NRG1 KO mice. Although preliminary, other interesting association results have been obtained with polymorphisms in COMT, DRD3 and DAT1 genes (146) (147) (148). In summary, PPI impairment is present in SZ and BP patients and their relatives. Dopamine-related genes (COMT, DRD3 and DAT1) as well as NRG1 gene may play an important role in PPI deficits. The significance of PPI deficits in other pathological conditions remains hypothetical and includes: general psychopathological marker, influence of psychotropic treatment and state marker.

In a classical oddball paradigm, the P300 component of evoked potential (amplitude and latency) has been studied as a potential biomarker of the vulnerability to SZ and BD. Both reduced amplitude and increased latency have been reported in SZ patients (149) (150). Although, this biomarker is influenced by state-related factors and treatments ( 150), it appears highly heritable (heritability estimates 50-60%) (151) (152) (153) (154), consistent with the finding that relatives of SZ patients also exhibit these deficits [START_REF] Saitoh | Abnormalities in late positive components of event-related potentials may reflect a genetic predisposition to schizophrenia[END_REF] (156) (157). Although BD has been less well studied in that regard, bipolar patients and unaffected relatives present with the same patterns of deficits (reduced amplitude and prolonged latency) (158) (159) (109) (160) [START_REF] Pierson | Information processing deficits in relatives of manic depressive patients[END_REF]. Only one study reported differences between SZ and BP patients in the topography (109). Of note associations between P300 characteristics and several dopamine-related genes including DRD2, DRD3 and COMT have been reported (162) (163) (164). DISC1 and DISC2 genes have also been implicated in P300 characteristics in patients with SZ or BD (165).

In summary, neurophysiological studies have produced promising results. Several neurophysiological deficits are both observed in SZ and BD. These deficits are stable, independent of state-related factors and also present in unaffected relatives. Most of these neurophysiological biomarkers are heritable and for some of them association with candidate genes have been reported. Thus neurophysiological investigations suggest that numerous genes may have a role in the development of shared endophenotypes between SZ and BD. Those findings are also consistent with a multifactorial origin of both disorders. For example, as previously stated, it can be hypothesized that some genetic factors favor negative symptoms with specific neurophysiological deficits, whereas other underlie psychotic features.

Cognitive studies

We have reviewed evidence suggesting that organization of brain anatomy show neurodevelopmental deficits both in BD and SZ. Genetic influence in both disorders is likely to impact both structural and functional aspects of brain systems in ways that increase risk for the disorders. These may result in a cascade of events that manifest across a wide range of neurocognitive and affective abilities such as attention, executive function, working memory, affect regulation, affect-cognition integration, declarative memory, spatial processing, and psychomotor function (166). Those potential biomarkers may help to uncover vulnerability genes and to resolve questions about the etiology of both disorders. Further, the established heritability of cognitive abilities and the availability of highly reliable procedures to assess cognitive skills highlight the potential for cognitive measures to be appropriate endophenotypes in BD and SZ (167) (168). Many candidate vulnerability markers identified in SZ and BP are neurocognitive and those in common are likely to be useful for future share genetic research (166).

Neuropsychological deficits are recognized as a "generalized deficit" in SZ, thus characterized by impairments in a wide range of cognitive abilities (169) (170). Deficits are present during the first episode of psychosis and do not worsen dramatically during the illness course, even during acute episodes of psychosis (169) (171). For BD patients, cognitive functioning is often impaired even in inter-episode euthymic states (172). Cognitive deficits in BD are characterized by generalized moderate level of neuropsychological impairment with deficits in some specific domains such as attention, executive function, and to a lesser extent verbal memory and spatial working memory (173). Results also show that a subset of these deficits moderately worsens during acute disease states in BD (172). Meta-analysis revealed worse performance for SZ than BD in 9 of 11 cognitive domains [START_REF] Krabbendam | Cognitive functioning in patients with schizophrenia and bipolar disorder: a quantitative review[END_REF]. This is particularly true for premorbid and current intelligence quotient and also perhaps attention, verbal memory and executive functions (174). However, shared pattern of deficits has also been suggested (174) (175). In addition, neuropsychological performance appears over time to be less stable in BD compared with SZ (176). Psychiatric symptoms seem to have a larger impact on test performances in BD than in SZ patients, so level of acute psychopathology, number of episodes (especially of mania) and the influence of comorbidities (such as substance misuse) may also influence the level of cognitive performance and nature of long-term deficits in BD (177). This is also consistent with the hypothesis that cognitive deficits are sequelae due to major thymic episodes' neurotoxicity. Additional reports of improved performances (nonverbal memory, executive function, and sustained attention) after clinical stabilization in BD patients support this hypothesis (178) (179) (180). Cognitive deficits in SZ appear to be relatively stable, generalized, long lasting from illness onset and persisting after clinical stabilization in first-episode patients (177). Bora et al. provide interesting negative results from a metaanalysis comparing cognitive functioning across SZ, schizoaffective disorder and affective psychosis that did not show clear differences between SZ and other groups (181). Same authors in a supplementary meta-analysis showed that the pattern of cognitive impairments in affective psychosis was relatively more pronounced but common to euthymic patients with BD (182). Lastly, Bora et al. concluded that schizophrenic cognitive impairments are not specific and thus cannot differentiate the major psychosis and do not help in discriminating SZ from BD and affective psychosis (183).

Affective and social impairments have long been considered core characteristics of SZ. However, affective and social cognition studies show similar levels of dysfunction between both disorders for response to interpersonal stressors (184) (185) (186) and social activity (187). Poor premorbid social functioning in adolescence is associated with both disorders, with minimal differences for participation in social activities or frequency of social relations after illness onset (188). Studies of social cognition also show shared impairments in social knowledge (189) and social problem solving (190). However, overall SZ patients display greater levels of dysfunction than BD patients in the expression of anhedonia, when decoding facial expression or emotional cues in the prosody of speech (166). Therefore, these cognitive domains can't be considered as illness-specific phenotypes to date. In addition, in patients with SZ, schizoaffective disorder and BD, differences on physical anhedonia (higher scores in SZ) but not on social anhedonia were found (191) (192) (193). One study found deficits in facial affect matching in BD euthymic sample (194). Further, a recent study compared visual scanning of facial images between SZ and BD probands; which is widely reported to be abnormal in SZ. Emotional perception in SZ and BD showed no difference in eye movements when visually scanning the facial stimuli (195).

Therefore affective and social impairments have long been associated to SZ, several studies suggest deficits in BD too. Thus, even when measuring a dimension widely believed to separate the disorders, such as the nature of affective disturbances, the Kraepelinian dichotomy is less clear than previously assumed. The neuropsychological differences reported between both disorders could be due to the presence of psychotic features, to environmental factors or to differences during the neurodevelopmental phase (174). On the other hand, the presence of psychotic symptoms may also play a role in determining the severity and stability of cognitive deficits in BD as in SZ (196). Indeed, several recent investigations have reported that psychosis in BD is associated with more severe neuropsychological dysfunction compared with patients with no history of psychosis (166). In addition, subgroups of BD patients with psychotic symptoms displayed a neuropsychological profile qualitatively more similar to the profile of SZ patients (197) (198). Moreover, a similar pattern of cognitive impairment has also been observed in people with psychotic depression with dramatic differences in performance between the patients with psychotic depression and those with nonpsychotic depression (199). There appear to be parallel cognitive impairments in several disorders that can be associated with psychotic symptoms: SZ, schizoaffective disorder, BD, and psychotic major depression (200). A recent study also demonstrates that neurocognitive impairments in memory, executive functioning and language are common in individuals with first-episode psychosis (201). Altogether, these findings point to a marked distinction in neurocognitive function associated with the expression of psychosis and the lifetime presence of psychosis appears to be a key contributor to cognitive dysfunction, which is independent of affective symptoms (166). Early in their course, cognitive deficits are present in all psychotic disorders but are more severe and pervasive in SZ than BD and mania (202). Therefore, some suggest that psychotic disorders should be conceptualized as being on a continuum rather than as a group of categorically distinct illnesses (175). The same authors support the notion that BD and SZ show phenotypic similarity in terms of the nature than severity of their neuropsychological deficits (175). Determining the degree to which the risk for psychosis (with possible shared genetic vulnerability factors) accounts for overlapping patterns of neuropsychological dysfunction across those disorders is a key challenge for the future. As neurocognitive dysfunction is among the strongest predictors of clinical and functional outcomes in patients, efforts to better detect and treat these deficits, which have shown promise in SZ, should be extended to all patients with psychosis (197), even though it is possible there is a different genesis of cognitive deficits in the two disorders. Cognitive dysfunctions in SZ are very likely to be neurodevelopmental as they present in childhood and detectable premorbidly (169). On the other hand, BD (especially non-psychotic BD) shows less impairment premorbidly with clearer deficits emerging over time probably indicative of neuroprogression with the toxic effects of mania being particularly associated with cognitive impairment (203).

Studies of unaffected first degree relatives have been employed to try to minimize the effects of confounding factors such as medication, psychiatric comorbidities or residual symptoms that pollute cognitive measures in euthymic bipolar patients.

First-degree relatives share, 50% of their genes with probands thus it is expected that some unaffected relatives would also present with vulnerability characteristics including neurocognitive impairments. Neuropsychological dysfunction in BD probands and their unaffected relatives share similarities with SZ probands and their unaffected relatives (166). Keri et al. (204) observed verbal recall deficit in unaffected siblings of both BD and SZ patients, suggesting a common impairment of the frontohippocampal system. Whereas impairments in general intelligence, working memory, verbal fluency, reasoning, or abstraction distinguished the siblings of SZ patients from the siblings of individuals with BD (204), BD patients and their unaffected relatives were comparable to healthy controls on several executive function tests. The only exception may be a possible enhanced susceptibility to interference and reduced inhibition in the relatives of both BD and SZ patients (205). The authors suggest that susceptibility to interference and reduced inhibitory processing could be a transnosographical markers of shared familial vulnerability to both disorders (205). Moreover, similar memory impairments in SZ and BD probands were reported in unaffected relatives (206). A recent study of BD I patients and relatives from families with or without SZ or schizoaffective disorder lead to further explore the links between psychosis proneness and cognitive profile (207). The authors show that impaired psychomotor processing speed and executive functions may represent markers of susceptibility to BD I irrespective of psychopathology within the family (207). They suggest that generalized impairment in verbal memory may be more specifically associated with BD. Performances in attention regulation, working memory, episodic memory, and emotion processing offer potential for identifying shared neurocognitive phenotypes for SZ and BD. However, much less studies have evaluated neurocognitive dimensions in BD unaffected relatives, and systematic investigations of unaffected relatives of both disorders are still needed.

To conclude, evidence for shared neuropsychological deficits between BD and SZ are substantial whereas evidence for the existence of specific dysfunctions in each disorder is relatively sparse. Cognitive dysfunctions in SZ are very likely neurodevelopmental whereas deficits in BD are partly explained by neuroprogression and/or the presence of psychotic symptoms. Available evidence in both disorders (probands or their unaffected relatives) may help to identify shared and illness-specific phenotypes, although evidence for cognitive dysfunction as a marker of familial vulnerability is stronger for SZ than for BD (208). Bora et al. suggest the inclusion of cognitive impairment criteria in DSM-V would not provide a major advance in discriminating between both disorders and affective psychoses and propose to consider cognitive impairment as a specifier and to define cognitive impairments as a dimension within a hybrid categorical-dimensional system (183).

SUMMARY AND PERSPECTIVE

Hypotheses on a more direct association between related genetic characteristics and biomarkers, such as neurophysiological measures and cognitive processes, compared with the clinical expression, has generated enthusiasm and has stimulated the development of precise, reliable and accurate measures of candidate phenotypes in each disorder. The developing evidence-base has drawn attention to shared aspects of psychopathology, neurobiology, and mechanisms of treatment efficacy across the BD and SZ disorders. Genetic linkage findings offer a further challenge to the traditional Kraepelinian model of two distinct disorders, as they do not fully separate the vulnerability to each disorder. Thus, empirical support for a common pathogeny comes from genetic studies demonstrating shared genetic susceptibility. These shared genetic factors appear to be more common in psychotic BD patients and their family members, suggesting that psychosis-proneness may represent the phenotypic expression of this common physiopathology and symptom dimension. However, as most research is conducted on individuals who have crossed the 'diagnostic threshold' for caseness, these shared markers could of course represent transdiagnostic predictors of poor outcome. To date, unequivocal support for a shared phenotype approach in psychiatric genetics remains absent and needs further investigation.

The traditional dichotomous classification has formed the foundation of contemporary diagnostic systems. This has profoundly influenced conventional approaches to psychiatric research that usually proceed under the a priori assumption that SZ and BD are separate disease entities with different underlying etiologies. However, whilst we of course acknowledge that evidence for important differences exists, this review of the evolving literature shows several key findings, emerging from different research areas that do not support this model. As stated by Craddock and Owen (209), it seems that psychiatry is « (entering) a transitional period of several years during which psychiatry will need to move from using traditional descriptive diagnoses to clinical entities (categories and/or dimensions) that relate more closely to the underlying workings of the brain » Consequently, it may be more apposite to think in terms of genetic influences on continuous variations in six symptom dimensions: neurobiological, cognitive, positive, negative, depressive and manic symptoms (210). Therefore, rather than classifying patients into dichotomous categories of disorder, each patient can be described as having a unique combination of symptoms, which are the result of the effects of various risk factors operating across a psychosis and affective continuum. Thus both disorders can be integrated in a continuum of clinical expression that may express shared and specific vulnerabilities consistent with a multifactorial origin. Neurobiological and neurocognitive dysfunctions may represent symptom dimensions that spans diagnostic categories, and may reflect shared pathogenic processes. Figure 1 summarizes the possible clinical expressions of the simplified hypothesis of overlap between BD and SZ.

There are several implications of such dimensional models; especially for future research paradigms and future nosology [START_REF] Insel | Research domain criteria (RDoC): toward a new classification framework for research on mental disorders[END_REF]. These theoretical models may help the exploration of pathophysiological mechanisms, whilst data on shared phenotypes may help to resolve questions about the causal chain between gene expression and clinical expression. [START_REF] Ii Gottesman | The Endophenotype Concept in Psychiatry: Etymology and Strategic Intentions[END_REF] proposed the use of endophenotypes (211) as a measurable component with a better phenotype/genotype correlation. It is supposed to have a simpler genetic architecture than clinical diagnoses themselves. Studying common endophenotypes may circumvent the limitation of Kraepelinian diagnostic system posed on BD and SZ. Meanwhile, the conceptualization of common endophenotypes does not contradict the existence of specific phenotypes and vulnerabilities for both disorders.

In conclusion, there is growing evidence that BD and SZ, rather than being wholly distinct disorders as in Kraepelin's earliest observational model, may share genetic risk at several loci. Further, there is growing evidence of similarity in the patterns of neurobiological and cognitive expression, which may be consequences of these common genetic factors. Initial findings of similarities across probands with BD and SZ as well as unaffected family members warrant further investigation as potential intermediate trait markers. Finally, a diagnostic classification system that incorporates dimensional elements of both disorders, and that is more inclusive than what is planned for DSM-V would help in the delineation of modern nosology, better inform the exploration of pathophysiological mechanisms and ultimately lead to advances in translational research with the discovery of new trans-diagnostic treatments and drug discovery.

Figure 1 .

 1 Figure 1. Simplified hypothesis of overlap between Mood disorders and schizophrenia. This model proposes a dimensional approach of the traditional dichotomy between both prototypical mood disorder and schizophrenia based on six phenotypic dimensions: neurobiological, cognitive, positive, negative, manic and depressed symptoms. Most of the neurobiological and cognitive dysfunctions are shared and unspecific.

TABLE OF CONTENTS

 OF

	1. Abstract
	2. Introduction
	3. The Kraeplinian dichotomy revisited
	3.1 Family, Twin and High Risk studies
	3.2 Molecular Genetic studies
	3.3 Neuro-developmental Studies
	3.4 Neuro-imaging studies
	3.4.1. Structural neuro-imaging studies
	3.4.2. Functional neuro-imaging studies
	3.5 Neurophysiological Studies
	3.6 Cognitive studies
	4. Summary and perspective
	5. Acknowledgements
	6. References

ACKNOWLEDGEMENTS

There is no source of funding. Authors declare having no actual or potential conflict of interest that could influence, or be perceived to influence, this work.