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Offspring of parents with schizophrenia, bipolar disorder, and depression

a review of familial high-risk and molecular genetics studies

Sandstrom, Andreaa,,b; Sahiti, Qendresab,,c; Pavlova, Barbaraa,,b; Uher, Rudolfa,,b,,c

doi: 10.1097/YPG.0000000000000240
Review Articles

Offspring of parents with severe mental illness, including schizophrenia, bipolar disorder, and major depressive disorder, have a one-in-three risk of developing severe mental illness themselves. Over the last 60 years, three waves of familial high-risk studies examined the development of severe mental illness in offspring of affected parents. The first two waves established familial nature of schizophrenia, and demonstrated early impairment in offspring of affected parents. The most recent wave has added a focus on mood disorders and examined the transdiagnostic nature of familial risk. A synthesis of current knowledge on individuals at familial risk points to psychopathology, neurocognitive, neuroanatomical, and environmental factors involved in the familial transmission of severe mental illness. Although family history remains the single strongest predictor of illness, molecular genetic tools are becoming increasingly informative. The next decade may see family history and molecular genetics complementing each other to facilitate a transdiagnostic approach to early risk identification and prevention.

aDepartment of Psychiatry, Dalhousie University

bDepartment of Psychiatry, Nova Scotia Health Authority

cDepartment of Psychology & Neuroscience, Dalhousie University, Halifax, Nova Scotia, Canada

Received 3 June 2019 Accepted 1 August 2019

Correspondence to Rudolf Uher, MD, PhD, Dalhousie University, 5909 Veterans Memorial Lane, Halifax, Nova Scotia B3H 2E2, Canada Tel: +902 473- 2585; fax: +902 473 4887; e-mail:

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Major depressive disorder (MDD), bipolar disorder, and schizophrenia share common genetic and environmental risk factors as well as typical age of onset in late adolescence or early adulthood (Uher and Zwicker, 2017). After an early onset, these disorders tend to cause lifelong impairment (Kessler et al., 2005; Harvey, 2011). Consequently, the cost of these disorders to society is higher than the cost of physical diseases, which typically have a later onset (Ratnasingham et al., 2012). Because of their shared features and significant impact, these disorders are often jointly referred to as severe mental illness (SMI). Understanding the development of SMI is essential for designing effective prevention and treatment strategies, which may help alleviate the burden of SMI for both the individual and society.

Understanding the developmental precursors of SMI is particularly important. We use the term antecedents to describe early manifestations of psychopathology that do not meet diagnostic criteria for SMI but are known to precede and predict disease onset. Suspected antecedents of SMI are often retrospectively identified in individuals who are already affected with SMI; this does not allow distinguishing between precursors and consequences of SMI (Thapar and Rutter, 2019). For example, are the cognitive deficits observed in patients with schizophrenia a risk factor for the disorder or do they develop as a result of the illness? The way to establish whether a risk factor actually precedes SMI is to prospectively study individuals before the onset of SMI (Thapar and Rutter, 2019). Large prospective studies of the general population are informative regarding risk factors which precede common mental disorders, including anxiety disorders and attention-deficit/hyperactivity disorder (ADHD). However, general population studies may be less suited to detect antecedents to SMI, because only a small proportion of participants will end up developing truly severe illness and individuals at highest risk for SMI may actually be less likely to participate (Martin et al., 2016). Therefore, researchers aiming to prospectively study developmental antecedents to SMI may need to specifically target high-risk individuals.

The strongest known risk factors for SMI is having a parent with SMI, as one-in-three offspring of affected parents will develop MDD, bipolar disorder, or schizophrenia by early adulthood (Rasic et al., 2014). Therefore, studies in offspring of parents with SMI provide an opportunity to examine early manifestations of risk that are relevant to SMI.

The first familial high-risk studies were launched in the 1950s and 1960s. The rationale behind this design was the need to study individuals at genetic risk for SMI in order to identify antecedents that occurred before disease onset (Mednick and McNeil, 1968). At this point, family history was the only way to index genetic risk. Thus, studies in offspring of parents with SMI allowed researchers to disentangle the etiological factors of SMI from consequences which occur after the development of the disorder (Mednick et al., 1987). Significant advancements in molecular genetics over the past few decades now allow genetic risk for SMI to be assessed directly using polygenic risk scores (PRS) based on genome-wide association studies (Martin et al., 2018). PRS is the sum of alleles associated with a particular phenotype and provides an estimate of the likelihood of a specific trait based on multiple genetic variants. Thus, genetic vulnerability can now be estimated without knowing family history and separated from environmental factors that may also be shared within families and passed on from generation to generation. This development raises questions about the relative roles of familial high-risk studies and molecular genetic studies in further research on the causation, prediction, and prevention of mental illness. In this review, we provide a synthesis of familial high-risk studies, with the aim to inform future research in this field. We review completed and ongoing familial high-risk studies to provide a synthesis of current knowledge regarding psychopathology, cognitive, neuroimaging, genetics, and environmental factors in high-risk offspring. We then summarize research on interventions for offspring of parents with SMI, and finish by outlining future directions for the field.

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Historical perspective

As the efforts invested in familial high-risk studies have waxed and waned over the decades and each period of renewed interest brought new topics, we summarize familial high-risk studies as occurring in three waves (Fig. 1).

Fig. 1

Fig. 1

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Wave one

The trail-blazers of familial high-risk research launched the first studies in the 1950s and 1960s with a focus on schizophrenia. These longitudinal studies followed offspring of parents with schizophrenia beginning in infancy (Fish, 1987), childhood (Worland et al., 1984), or adolescence (Mednick et al., 1987). The Copenhagen high-risk project, initiated in 1962, followed more than 200 offspring of parents with schizophrenia and controls over 20 years (Mednick et al., 1987). The findings from these projects have transformed the understanding of schizophrenia. In addition to demonstrating that offspring of affected parents were at high risk for schizophrenia, they showed early impairments across a number of domains, including social problems and neurological difficulties (Fish, 1959; Mednick et al., 1987). These findings led to the realization that schizophrenia is a neurodevelopmental condition rather than a neurodegenerative condition, as previously believed (Murray and Lewis 1988).

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Wave two

A second generation of familial high-risk studies began in the 1970s and 1980s, and some of these studies have only recently completed the final rounds of data collection. Although the primary focus remained on schizophrenia, some of these studies also included offspring of parents with mood disorders. Notably, the three-generation project initiated in 1982 assessed depression and continued to track familial risk across three generations (Weissman et al., 2016). The Stony Brook High-Risk Project and the Emory University Project also included offspring of parents with depression and bipolar disorder as additional comparison groups to offspring of parents with schizophrenia (Goodman, 1987; Weintraub, 1987). These studies also found early impairment in offspring of parents with mood disorders, raising questions about the specificity of developmental precursors to schizophrenia (Goodman, 1987; Weintraub, 1987; Egeland et al., 2003). An excellent overview of this wave of studies in a special issue of Schizophrenia Bulletin (Asarnow, 1988) in 1988 was followed by a lull decade when few new studies were initiated.

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Wave three

Over the past two decades, familial high-risk research has regained momentum with a new focus on offspring of parents with bipolar disorder and on transdiagnostic approaches to SMI. Several large-scale projects include offspring of parents with different types of SMI, opening an opportunity to map both shared and disorder-specific antecedents for MDD, bipolar disorder and schizophrenia. The routine application of neuroimaging and molecular genetics in these studies expands the range of questions that can be answered.

Among the first to take a transdiagnostic approach was a study by Maziade et al. (2008) which followed relatives of people with schizophrenia or bipolar disorder over twenty years. Findings indicated that there was significant overlap in early risk factors and later mental disorder diagnoses between offspring of parents with schizophrenia and offspring of parents with bipolar disorder (Paccalet et al., 2016). Further evidence for a general rather than specific vulnerability associated with familial risk was established through a meta-analysis (Rasic et al., 2014), which has shown that offspring of parents with SMI are at increased risk for all psychiatric disorders.

There are currently at least three ongoing transdiagnostic familial high-risk studies; the Danish High Risk and Resilience Study-VIA (Ellersgaard et al., 2018), the Bipolar and Schizophrenia Young Offspring Study (Sanchez-Gistau et al., 2015) and Families Overcoming Risks and Building Opportunities for Wellbeing (Uher et al., 2014). In addition to furthering the study of etiology through direct examination of specificity and overlap between diagnoses, these studies are combining familial high-risk design with molecular genetic methodology and examining the potential of early interventions to reduce the risk of SMI among offspring of affected parents. More offspring of parents with SMI are being followed up in research studies at present than at any previous time point (Fig. 1).

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Synthesis of current knowledge

Antecedent psychopathology and childhood-onset disorders in offspring of affected parents

Years before the typical age of onset for major mood and psychotic disorders, antecedents of SMI are elevated in offspring of parents with SMI, including higher scores on parent-, teacher-, and observer-reports of psychopathology and increased rates of emotional and behavioral disorders (Ellersgaard et al., 2018; Sandstrom et al., 2019a). As familial risk is associated with both general and specific psychiatric liabilities, certain antecedents are shared across offspring of parents with MDD, bipolar disorder, and schizophrenia, whereas others are preferentially related to one type of parental illness.

The rates of childhood-onset mental and behavioral disorders are elevated in high-risk offspring from a young age. Increased rates of ADHD, anxiety, and disruptive behavior disorders are shared by offspring of parents with bipolar disorder and offspring of parents with schizophrenia (Rasic et al., 2014; Sanchez-Gistau et al., 2015; Ellersgaard et al., 2018). As these same disorders also predict later onset of both major mood disorders and of schizophrenia (Hans et al., 2004; Nurnberger et al., 2011; Rice et al., 2017; Duffy et al., 2018; Meier et al., 2018), childhood-onset ADHD and anxiety disorders may represent transdiagnostic antecedents of SMI. Unusual experiences including basic symptoms and psychotic-like experiences are also strong predictors of SMI (Poulton et al., 2000; Schultze-Lutter et al., 2012) and are elevated in offspring of parents with all types of SMI (Noguera et al., 2018; Aylott et al., 2019; Zwicker et al., 2019a). Certain aspects of temperament may also represent early manifestations of risk for SMI, as offspring of parents with SMI display less positive mood dimensions, adaptability (Díaz-Caneja et al., 2018) and greater behavioral inhibition (Rosenbaum et al., 2000; Hirshfeld-Becker et al., 2006a). As inhibited temperament is a strong risk factor for anxiety (Sandstrom et al., 2019b), which in turn predict SMI (Duffy et al., 2018; Meier et al., 2018), behavioral inhibition may also be an early antecedent for SMI.

Although some antecedents may be transdiagnostic, other precursors show disorder specificity. Mood instability and irritability are a cluster of related symptoms that are common in mood disorders (Balbuena et al., 2016). Propensity to sudden rapid changes in mood, referred to as mood instability or affective lability, is elevated in offspring of parents with mood disorders, but not offspring of parents with schizophrenia (Zwicker et al., 2019b). Mood instability and irritability also predict the onset of mood disorders in offspring of parents with MDD and bipolar disorder (Hafeman et al., 2016; Rice et al., 2017). Taken together, previous investigations suggest that mood instability and irritability may be antecedents that are relatively specific to mood disorders. Childhood sleep problems have also been implicated in offspring of parents with mood disorders (Wescott et al., 2019), and are associated with a two-fold increased risk for future bipolar disorder in offspring of parents with bipolar disorder (Levenson et al., 2015). Evidence for an association between sleep problems and family history of schizophrenia has not yet been established.

Antecedents often develop in childhood and adolescence and maybe the first indicators of risk for SMI in high-risk offspring beyond family history. In the coming years, transdiagnostic longitudinal studies of high-risk offspring will probe the relative specificity or transdiagnostic character of further antecedents and associated biomarkers. With accumulation of longitudinal data and assessment of various risk factors concurrently, we can also start examining how multiple antecedents and biomarkers may be combined to optimize the early identification of risk for SMI.

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Onsets of severe mental illness in offspring of affected parents

The rates of major mood and psychotic disorders among offspring of parents with SMI have been summarized in a meta-analysis (Rasic et al., 2014). Of offspring of parents with SMI who have been followed-up into adulthood, 32% have a diagnosis of MDD, bipolar disorder, or schizophrenia compared to 14% of control offspring of parents without SMI. Across age-groups, offspring of parents with SMI are at 2.5-fold increased risk for any SMI compared to offspring of parents with no SMI (Rasic et al., 2014). In addition, offspring of parents with SMI are also at a greater risk for almost all other psychiatric disorders including substance use and disruptive behavior disorder (Rasic et al., 2014). Since it is relatively rare for both biological parents to be affected with SMI and some high-risk studies have excluded families with two affected parents, the above rates apply primarily to children who have one biological parent with SMI and the other biological parent without mental illness. A Danish registry study shows that risk of SMI is further increased when both parents are affected (Gottesman et al., 2010). Future research on the risk for MDD, bipolar disorder, and schizophrenia when both parents have SMI is warranted.

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Staging model of severe mental illness

The progression to SMI is a complex and multistage process with early manifestations of illness emerging before disease onset. Thus, it is helpful to conceptualize SMI on a continuum with phases that differ in severity and specificity. The staging model (Fig. 2; McGorry & Nelson, 2016; Fusar-Poli et al., 2017), presents a framework for the trajectory of SMI occurring along this continuum. Stage 0 is the period when individuals are asymptomatic. Stage 1a occurs when distress disorders develop, which may include ADHD and oppositional defiant disorder. In some cases, manifestation of SMI risk will become increasingly specific and form a clinical at-risk state/prodrome for a mood or psychotic disorder (stage 1b). Stage 2 is marked by first episode onset of SMI. In some individuals, illness may progress and SMI may become recurrent (stage 3). Stage 4 occurs when the illness is chronic, treatment resistant, and causes severe impairment. Staging in offspring of parents with SMI is similar to individuals with no family history of major mental illness from stage 1a onwards. However, in the context of positive family history, antecedents that fall short of distress disorder diagnoses are also important predictors for future SMI. Thus, in Fig. 2 we present an adapted staging model for SMI in familial high-risk offspring, where we highlight the antecedent stage (stage 0.5) as a distinct phase from stage 0 and stage 1a. The inclusion of this stage has important implications for the timing of early intervention strategies in offspring of parents with SMI.

Fig. 2

Fig. 2

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Neurocognitive functioning

On average, offspring of parents with SMI perform less well on measures of cognitive functions than do control offspring. Lower intelligence quotient (IQ) has been found in offspring of parents with schizophrenia and bipolar disorder compared to controls (Klimes-Dougan et al., 2017; de Zwarte et al., 2018). Offspring of parents with schizophrenia also perform substantially lower than offspring of parents with bipolar disorder on IQ tests (Hemager et al., 2018). Thus, on average IQ decreases from offspring of parents with no SMI to offspring of parents with bipolar disorder to offspring of parents with schizophrenia. Offspring of parents with depression also perform less well on cognitive tests than offspring of parents without mental illness (MacKenzie et al., 2019). As IQ in childhood predicts psychiatric disorders (Mollon et al., 2018), lower IQ in high-risk offspring may be an early indicator of risk for SMI. Specific domains of cognition may index familial risk of SMI better than general cognitive ability. Offspring of parents with schizophrenia show greatest difficulties in verbal ability, visual memory, and attention (Hameed and Lewis, 2016). Offspring of parents with bipolar disorder also show on average lower cognitive functioning in processing speed, and visual memory (Klimes-Dougan et al., 2006; de la Serna et al., 2017). Out of tests of various cognitive functions, offspring of parents with MDD perform worst in tasks that depend on language and verbal ability (MacKenzie et al., 2019).

The usefulness of neurocognitive measures in predicting the onset of SMI in high-risk offspring has not yet been established. However, preliminary findings suggest cognitive deficits defined as impairment in verbal episodic memory, processing speed or visual episodic memory, may be associated with major affective and non-affective disorders in high-risk offspring (Berthelot et al., 2015). ‘Hot’ cognition that involves reasoning and thinking in emotionally-salient context may also index risk of mental illness independently of general cognitive ability. Emotional decision-making scores in offspring of parents with SMI may represent an early indicator of propensity to psychotic symptoms (McCormack et al., 2016; MacKenzie et al., 2017). Finally, low reward-seeking measured using the Cambridge Gambling Task from the Cambridge Neuropsychological Test Automated Battery has been found to predict depressive symptoms and depressive disorders in offspring of parents with MDD (Rawal et al., 2013).

The evidence from familial high-risk studies suggests that early cognitive deficits in high-risk offspring may represent antecedents to SMI. Future longitudinal research in high-risk offspring may indicate which cognitive domains may improve the prediction of SMI when used alone or in combination with other types of predictors.

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Brain imagining in high-risk offspring aims to identify deviations in brain structure and function, which may indicate biomarkers for SMI. The findings include both biomarkers that are specific to offspring of parents with a particular diagnosis and those that generalize to offspring of parents with different types of mental illness.

Studies of brain structure found cortical thinning in offspring of parents with all types SMI (Prasad et al., 2010; Talati et al., 2013; Hanford et al., 2016) suggesting that thinner cortex may be a transdiagnostic marker of familial risk. In contrast, increased volume and surface of the right inferior frontal gyrus has been reported as a replicable biomarker of familial risk for bipolar disorder (Hajek et al. 2013; Sariçiçek et al., 2015; Roberts et al., 2017; Drobinin et al., 2019). In addition, decreased volume in white matter across different brain regions has also been reported in offspring of parents with mood disorders (Nery et al., 2017; Ganzola et al., 2018; Versace et al., 2018).

Imaging of brain function has also demonstrated differences between offspring of parents with SMI and control offspring. The variety of procedures used to index brain function limits comparability of findings across studies. Recent trends include the applications of vastly multivariate methods, such as network analysis and graph theory, to capture the complex patterns of co-variation in function across brain regions and time points. So, for example, it has been reported that connectivity deficits in the brain’s central rich club system (Collin et al., 2017) and in the left basal ganglia resting-state network (Solé-Padullés et al., 2016) distinguish offspring of parents with schizophrenia from controls. Offspring of parents with MDD show reduced resting-state activity in the right parietal temporal hemisphere (Talati et al., 2013), and deficits in prefrontal connectivity have been found in offspring of parents with bipolar disorder (Singh et al., 2014; Roberts et al., 2017; Roberts et al., 2018). Taken together, these findings suggest that reduced connectivity in different brain regions may represent a genetic liability for SMI. However, because of variation in methods, lack of transdiagnostic comparisons and absence of replication attempts, it is currently unclear whether any of these functional features are specific to a particular parental diagnosis or are shared between different familial high-risk groups.

Brain imaging in offspring of parents with SMI indicates that certain abnormalities in brain structure may represent developmental markers of familial risk. Functional imagining techniques also suggest difference in brain connectivity in offspring of parents with SMI compared to controls, although where these differences occur may depend on the high-risk group. It remains to be determined whether early abnormalities in brain structure and function may predict later onset of SMI.

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The transmission of SMI from parent to child is to a large degree due to genetic factors. This genetic risk contributes to offspring’s vulnerability to develop mental disorders and may also manifest in subtle deviations of brain structure and cognitive abilities. The heritable risk of SMI is due to hundreds or thousands of genetic variants, of which each one contributes a small portion of liability to disease risk (Uher and Zwicker, 2017). PRS provides a cumulative measure of this vulnerability across thousands of genetic variants (Torkamani et al., 2018). PRS for schizophrenia, depression and bipolar disorder correlate with family history of SMI and distinguish offspring of parents with bipolar disorder or schizophrenia from controls (Fullerton et al., 2015; Neilson et al., 2018).

Recent findings have established there is considerable overlap in the genetic variants for different psychiatric disorders, with approximately two-thirds of genetic influences shared across schizophrenia, bipolar disorder and MDD (Cross-Disorder Group of the Psychiatric Genomics Consortium, 2013). Thus, the genetic risk for SMI may also be shared across offspring of parents with different psychiatric disorders. For example, polymorphisms in CACNA1C and SYNE associated with the risk of SMI are enriched in offspring of parents with both schizophrenia and bipolar disorder (Gassó et al., 2016). It is becoming increasingly possible to predict the risk of mental illness from PRS, and combining PRS for multiple disorders may be the most powerful approach (Maier et al., 2015; Taylor et al., 2018).

At present, family history remains a more powerful predictor of mental illness than PRS. However, as the samples of molecular genetic studies are growing, PRS are becoming more accurate in predicting mental illness. The combination of familial high-risk design with genome-wide genotyping will help test whether PRS meaningfully complement family history in predicting the onsets of major mood and psychotic disorders. This may be especially relevant in cases where family history is less informative because of small family size or missing information on biological relatives.

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Environment factors

Exposures to an adverse environment, which occur across the life course, also contribute to the development of SMI in high-risk offspring. Some of the earliest environmental risk factors in offspring of parents with SMI include birth complication and separation from family, which may occur more frequently for offspring of parents with mental illness (Mednick et al., 1987; Davidsen et al., 2015). Other family stressors including family conflict and instability are also more common in high-risk offspring and may contribute to vulnerability for SMI (Beardslee et al., 1998; Ferreira et al., 2013). In addition, parenting style may moderate risk, with warm and predictable parenting being protective and criticism and rejection being associated with later onset of mood disorders (Kemner et al., 2015). Other environmental exposures including socioeconomic status, economic disadvantage, psychosocial adversity, and stressful life events have all been found to predict SMI (Kemner et al., 2015; Rice et al., 2017; Noguera et al., 2018). Good-quality peer relationships act as a protective factor for mental health problems in offspring of parents with SMI (Collishaw et al., 2016) and poor social relationships and exposure to bullying may contribute to the development of SMI (Bowes et al., 2014; Singham et al., 2017).

Throughout development, children and youth experience a number of positive and negative environmental influences, which may moderate the risk for SMI. It is unlikely that one single exposure is enough to cause SMI. Instead, it is probable that a number of environmental risk factors interact to influence disease onset (Padmanabhan et al., 2017; Uher and Zwicker, 2017). Therefore, studying the cumulative effect of environmental exposures across development may be helpful to improve our understanding of how vulnerability develops in youth at low and high familial risk (Oliver et al., 2019).

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Pre-emptive early interventions

Offspring of parents with SMI are more likely to experience impairment across a number of domains and are at increased risk for all types of psychiatric disorders. Thus, offspring of parents with SMI represent a population in need who may benefit from early intervention. In the last decade, several familial high-risk studies have focused on opportunities for early intervention aiming to reduce the risk of developing mental illness. Some researchers have tested treatments typically used for acute mental illness. A few small open-label studies have used mood stabilizers or antipsychotics in offspring of parents with bipolar disorder, but results have been mixed and not replicated in randomized control trials (RCT) (Zalpuri and Singh, 2017). Furthermore, the use of medication in youth who are not diagnosed with a disorder may cause more harm than good. Consequently, most recent intervention studies in offspring of parents with SMI have focused on psychological approaches.

The strongest evidence for the effectiveness of psychological intervention in high-risk offspring comes from an RCT of cognitive-behavioral prevention in offspring of parents with depression (Garber et al., 2009). This study found that the intervention reduced the risk of depression onset over the initial short-term follow-up, and the benefits were maintained on long-term follow-up 6 years later (Brent et al., 2015). Other preliminary investigations suggest that Interpersonal and Social Rhythm Therapy (Goldstein et al., 2018) and Family-Focused Therapy (Miklowitz et al., 2013) may be beneficial for symptom reduction in offspring of parents with bipolar disorder. However, due to small sample size and short-term follow-up it is unclear whether either of these therapies may be effective at preventing bipolar disorder.

Two ongoing intervention projects: Skills for Wellness (SWELL; Uher et al., 2014) and VIA-family (Müller et al., 2019) have taken a transdiagnostic approach to prevention. SWELL is a multimodal antecedent-focused cognitive-behavioral training intervention for offspring of parents with MDD, schizophrenia, and bipolar disorder. The aim of SWELL is to reduce the risk of future psychiatric disorders by targeting the early antecedents of SMI (affective lability, anxiety, psychotic, and basic symptoms). Initial experiences in SWELL suggest good acceptability and short-term benefits. VIA-family is a multidisciplinary intervention for offspring of parents with SMI that provides intensive support and treatment strategies for the entire family. Initial response to VIA-family suggests that the intervention is acceptable and valued by participating families (A. Thorup 2019, personal communication, 19 April).

The staging model of SMI may allow matching intervention to each stage of illness (Fig. 2). In the absence of familial risk, the interventions typically begin at stage 1a, after individuals seek treatment for their symptoms. Knowledge of family history may allow moving the intervention efforts to even earlier stages (Fig. 2). Due to the increased risk associated with family history, proactive monitoring may present an alternative to restricting interventions to treatment-seeking individuals. Even symptoms falling short of distress disorder diagnoses may present an indication for early pre-emptive intervention during the antecedent stage (stage 0.5).

To date, few interventions have been tested for offspring of parents with SMI, and most of the existing studies are limited by small sample size and short-term follow-up periods. A broader transdiagnostic approach to prevention may be an important step for addressing the risk factors associated with family history.

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The earliest familial high-risk studies began because researchers wanted to study SMI in individuals who were known to have the genetic risk for these disorders. Almost 60 years later, researchers now have the ability to assess genetic risk without knowing family history. This brings us back to the question raised at the beginning of this review: what is the role of familial high-risk studies now that we can measure genetic risk directly?

Among the various designs available to study the development of mental illness, investigations in offspring of parents with SMI continue to provide essential information, due to concentration of risk, thoroughness of assessments, completeness of follow-up, and severity of outcomes. The familial high-risk design is powerful because it enriches for both genetic and environmental influences. However, for the same reason, it is less suited to differentiating genetic and environmental influences. The incorporation of genetic tools in studies of offspring of parents with SMI may combine advantages of both types of studies to provide a clearer picture of the causal mechanisms of SMI and distinguish between the role of environment and the role of genetics in the development of psychiatric disorders.

A recent investigation (Rice et al., 2019) in a population-based cohort explored the predictive value of PRS for neurodevelopmental disorders (ADHD and schizophrenia) and PRS for MDD on the age of onset of depressive symptoms. The researchers found that PRS for neurodevelopmental disorders was associated with earlier age of onset of depressive symptoms, whereas PRS of MDD predicted onset at typical age. These findings suggest that there may be distinct depressive trajectories based on genetic risk. These are intriguing findings with implications for prevention and treatment. However, this study is limited by high drop-out rate, which was not random but rather predicted by high genetic risk for psychiatric disorders (Taylor et al., 2018). Thus, the individuals we are most interested in studying are the ones who are most likely to be missing from population-based studies. As familial high-risk studies focus on exactly that segment of population and have better retention rates than investigations in the general population, using familial high-risk design will complement studies of general population and contribute to a better understanding of the genetic and environmental factors which are involved in the development of SMI.

Family history remains the most powerful predictor for SMI, and offspring of parents with MDD, bipolar disorder, and schizophrenia are at high risk for disease onset. Thus, offspring of parents with SMI represent a population in need and early interventions are essential. With one notable exception (Garber et al., 2009; Brent et al., 2015), interventions to date have been limited by small sample size and short-term follow-up. Recently accumulated knowledge is converging to suggest that taking a transdiagnostic approach to prevention may yield the best outcomes (McGorry and Nelson, 2016; Caspi and Moffitt, 2018).

Interventions have typically focused on targeting high-risk offspring in later childhood and adolescence. Prevention strategies which intervene at an earlier age maybe even more effective at reducing risk for SMI. Such interventions may take a parent-focused approach, as young children are not able to fully engage and learn from psychological intervention (Garber et al., 2016). Previous parent-focused interventions in mothers with depression and mothers with anxiety have shown promising results (Goodman and Garber, 2017; Howes Vallis et al., 2019). Another unexplored area is the use of genetic technology in preventive interventions. It remains to be determined whether the incorporation of genetic tools in early interventions may be an effective way to prevent SMI.

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This work was supported by the Canada Research Chairs Program (Grant number 231397), and the Nova Scotia Health Research Foundation (Grant number 833).

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Conflicts of interest

There are no conflicts of interest.

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Asarnow JR. Children at risk for schizophrenia: converging lines of evidence. Schizophr Bull. 1988; 14:613–631
Axelson D, Goldstein B, Goldstein T, Monk K, Yu H, Hickey MB, et al. Diagnostic precursors to bipolar disorder in offspring of parents with bipolar disorder: a longitudinal study. Am J Psychiatry. 2015; 172:638–646
Aylott A, Zwicker A, MacKenzie LE, Cumby J, Propper L, Abidi S, et al. Like father like daughter: sex-specific parent-of-origin effects in the transmission of liability for psychotic symptoms to offspring. J Dev Orig Health Dis. 2019; 10:100–107
Balbuena L, Bowen R, Baetz M, Marwaha S. Mood instability and irritability as core symptoms of major depression: an exploration using rasch analysis. Front Psychiatry. 2016; 7:174
Beardslee WR, Versage EM, Gladstone TR. Children of affectively ill parents: a review of the past 10 years. J Am Acad Child Adolesc Psychiatry. 1998; 37:1134–1141
Berthelot N, Paccalet T, Gilbert E, Moreau I, Mérette C, Gingras N, et al. Childhood abuse and neglect may induce deficits in cognitive precursors of psychosis in high-risk children. J Psychiatry Neurosci. 2015; 40:336–343
Biederman J, Rosenbaum JF, Bolduc-Murphy EA, Faraone SV, Chaloff J, Hirshfeld DR, Kagan J. A 3-year follow-up of children with and without behavioral inhibition. J Am Acad Child Adolesc Psychiatry. 1993; 32:814–821
Bowes L, Wolke D, Joinson C, Lereya ST, Lewis G. Sibling bullying and risk of depression, anxiety, and self-harm: a prospective cohort study. Pediatrics. 2014; 134:e1032–e1039
Brent DA, Brunwasser SM, Hollon SD, Weersing VR, Clarke GN, Dickerson JF, et al. Effect of a cognitive-behavioral prevention program on depression 6 years after implementation among at-risk adolescents: a randomized clinical trial. JAMA Psychiatry. 2015; 72:1110–1118
Caspi A, Moffitt TE. All for one and one for all: mental disorders in one dimension. Am J Psychiatry. 2018; 175:831–844
Collin G, Scholtens LH, Kahn RS, Hillegers MHJ, van den Heuvel MP. Affected anatomical rich club and structural-functional coupling in young offspring of schizophrenia and bipolar disorder patients. Biol Psychiatry. 2017; 82:746–755
Collishaw S, Hammerton G, Mahedy L, Sellers R, Owen MJ, Craddock N, et al. Mental health resilience in the adolescent offspring of parents with depression: a prospective longitudinal study. Lancet Psychiatry. 2016; 3:49–57
Cross-Disorder Group of the Psychiatric Genomics Consortium; Cross-Disorder Group of the Psychiatric Genomics Consortium. Identification of risk loci with shared effects on five major psychiatric disorders: a genome-wide analysis. Lancet. 2013; 381:1371–1379
Davidsen KA, Harder S, MacBeth A, Lundy JM, Gumley A. Mother-infant interaction in schizophrenia: transmitting risk or resilience? A systematic review of the literature. Soc Psychiatry Psychiatr Epidemiol. 2015; 50:1785–1798
Díaz-Caneja CM, Morón-Nozaleda MG, Vicente-Moreno RP, Rodríguez-Toscano E, Pina-Camacho L, de la Serna E, et al. Temperament in child and adolescent offspring of patients with schizophrenia and bipolar disorder. Eur Child Adolesc Psychiatry. 2018; 27:1459–1471
Drobinin V, Slaney C, Garnham J, Propper L, Uher R, Alda M, Hajek T. Larger right inferior frontal gyrus volume and surface area in participants at genetic risk for bipolar disorders. Psychol Med. 2019; 49:1308–1315
Duffy A, Goodday S, Keown-Stoneman C, Grof P. The emergent course of bipolar disorder: observations over two decades from the Canadian high-risk offspring cohort. Am J Psychiatry. 2018[Epub ahead of print]
Egeland JA, Shaw JA, Endicott J, Pauls DL, Allen CR, Hostetter AM, Sussex JN. Prospective study of prodromal features for bipolarity in well amish children. J Am Acad Child Adolesc Psychiatry. 2003; 42:786–796
Ellersgaard D, Jessica Plessen K, Richardt Jepsen J, Soeborg Spang K, Hemager N, Klee Burton B, et al. Psychopathology in 7-year-old children with familial high risk of developing schizophrenia spectrum psychosis or bipolar disorder - the danish high risk and resilience study - VIA 7, a population-based cohort study. World Psychiatry. 2018; 17:210–219
Erlenmeyer-Kimling L, Cornblatt B. The new york high-risk project: a followup report. Schizophr Bull. 1987; 13:451–461
Ferreira GS, Moreira CR, Kleinman A, Nader EC, Gomes BC, Teixeira AM, et al. Dysfunctional family environment in affected versus unaffected offspring of parents with bipolar disorder. Aust N Z J Psychiatry. 2013; 47:1051–1057
Fish B. Longitudinal observations of biological deviations in a schizophrenic infant. Am J Psychiatry. 1959; 116:25–31
Fish B. Infant predictors of the longitudinal course of schizophrenic development. Schizophr Bull. 1987; 13:395–409
Fullerton JM, Koller DL, Edenberg HJ, Foroud T, Liu H, Glowinski AL, et al; Bipolar High Risk Study Group, BiGS Consortium. Assessment of first and second degree relatives of individuals with bipolar disorder shows increased genetic risk scores in both affected relatives and young at-risk individuals. Am J Med Genet B Neuropsychiatr Genet. 2015; 168:617–629
Fusar-Poli P, Rutigliano G, Stahl D, Davies C, De Micheli A, Ramella-Cravaro V, et al. Long-term validity of the at risk mental state (ARMS) for predicting psychotic and non-psychotic mental disorders. Eur Psychiatry. 2017; 42:49–54
Ganzola R, McIntosh AM, Nickson T, Sprooten E, Bastin ME, Giles S, et al. Diffusion tensor imaging correlates of early markers of depression in youth at high-familial risk for bipolar disorder. J Child Psychol Psychiatry. 2018; 59:917–927
Garber J, Clarke GN, Weersing VR, Beardslee WR, Brent DA, Gladstone TR, et al. Prevention of depression in at-risk adolescents: a randomized controlled trial. Jama. 2009; 301:2215–2224
Garber J, Frankel SA, Herrington CG. Developmental demands of cognitive behavioral therapy for depression in children and adolescents: cognitive, social, and emotional processes. Annu Rev Clin Psychol. 2016; 12:181–216
Gassó P, Sánchez-Gistau V, Mas S, Sugranyes G, Rodríguez N, Boloc D, et al. Association of CACNA1C and SYNE1 in offspring of patients with psychiatric disorders. Psychiatry Res. 2016; 245:427–435
Goldstein TR, Merranko J, Krantz M, Garcia M, Franzen P, Levenson J, et al. Early intervention for adolescents at-risk for bipolar disorder: a pilot randomized trial of interpersonal and social rhythm therapy (IPSRT). J Affect Disord. 2018; 235:348–356
Goodman SH. Emory university project on children of disturbed parents. Schizophr Bull. 1987; 13:411–423
Goodman SH, Garber J. Evidence-based interventions for depressed mothers and their young children. Child Dev. 2017; 88:368–377
Gottesman II, Laursen TM, Bertelsen A, Mortensen PB. Severe mental disorders in offspring with 2 psychiatrically ill parents. Arch Gen Psychiatry. 2010; 67:252–257
Hafeman DM, Merranko J, Axelson D, Goldstein BI, Goldstein T, Monk K, et al. Toward the definition of a bipolar prodrome: dimensional predictors of bipolar spectrum disorders in at-risk youths. Am J Psychiatry. 2016; 173:695–704
Hajek T, Cullis J, Novak T, Kopecek M, Blagdon R, Propper L, et al. Brain structural signature of familial predisposition for bipolar disorder: replicable evidence for involvement of the right inferior frontal gyrus. Biol Psychiatry. 2013; 73:144–152
Hameed MA, Lewis AJ. Offspring of parents with schizophrenia: a systematic review of developmental features across childhood. Harv Rev Psychiatry. 2016; 24:104–117
Hanford LC, Sassi RB, Minuzzi L, Hall GB. Cortical thickness in symptomatic and asymptomatic bipolar offspring. Psychiatry Res Neuroimaging. 2016; 251:26–33
Hans SL, Auerbach JG, Styr B, Marcus J. Offspring of parents with schizophrenia: mental disorders during childhood and adolescence. Schizophr Bull. 2004; 30:303–315
Hanson DR, Gottesman II, Heston LL. Some possible childhood indicators of adult schizophrenia inferred from children of schizophrenics. Br J Psychiatry. 1976; 129:142–154
Harvey PD. Mood symptoms, cognition, and everyday functioning: in major depression, bipolar disorder, and schizophrenia. Innov Clin Neurosci. 2011; 8:14–18
Havinga PJ, Boschloo L, Bloemen AJ, Nauta MH, de Vries SO, Penninx BW, et al. Doomed for disorder? High incidence of mood and anxiety disorders in offspring of depressed and anxious patients: a prospective cohort study. J Clin Psychiatry. 2017; 78:e8–e17
Hemager N, Plessen KJ, Thorup A, Christiani C, Ellersgaard D, Spang KS, et al. Assessment of neurocognitive functions in 7-year-old children at familial high risk for schizophrenia or bipolar disorder: the danish high risk and resilience study VIA 7. JAMA Psychiatry. 2018; 75:844–852
Hirshfeld-Becker DR, Biederman J, Henin A, Faraone SV, Cayton GA, Rosenbaum JF. Laboratory-observed behavioral disinhibition in the young offspring of parents with bipolar disorder: a high-risk pilot study. Am J Psychiatry. 2006a; 163:265–271
Hirshfeld-Becker DR, Biederman J, Henin A, Faraone SV, Dowd ST, De Petrillo LA, et al. Psychopathology in the young offspring of parents with bipolar disorder: a controlled pilot study. Psychiatry Res. 2006b; 145:155–167
Howes Vallis E, Zwicker A, Uher R, Pavlova B. Cognitive-behavioral intervention for prevention and treatment of anxiety in preschool children: a systematic review and meta-analysis. 2019Submitted
Johnstone EC, Russell KD, Harrison LK, Lawrie SM. The edinburgh high risk study: current status and future prospects. World Psychiatry. 2003; 2:45–49
Kemner SM, Mesman E, Nolen WA, Eijckemans MJ, Hillegers MH. The role of life events and psychological factors in the onset of first and recurrent mood episodes in bipolar offspring: results from the dutch bipolar offspring study. Psychol Med. 2015; 45:2571–2581
Kessler RC, Berglund P, Demler O, Jin R, Merikangas KR, Walters EE. Lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the national comorbidity survey replication. Arch Gen Psychiatry. 2005; 62:593–602
Klimes-Dougan B, Ronsaville D, Wiggs EA, Martinez PE. Neuropsychological functioning in adolescent children of mothers with a history of bipolar or major depressive disorders. Biol Psychiatry. 2006; 60:957–965
Klimes-Dougan B, Jeong J, Kennedy KP, Allen TA. Intellectual functioning in offspring of parents with bipolar disorder: a review of the literature. Brain Sci. 2017; 7:143
Lau P, Hawes DJ, Hunt C, Frankland A, Roberts G, Wright A, et al. Family environment and psychopathology in offspring of parents with bipolar disorder. J Affect Disord. 2018; 226:12–20
Levenson JC, Axelson DA, Merranko J, Angulo M, Goldstein TR, Mullin BC, et al. Differences in sleep disturbances among offspring of parents with and without bipolar disorder: association with conversion to bipolar disorder. Bipolar Disord. 2015; 17:836–848
MacKenzie LE, Patterson VC, Zwicker A, Drobinin V, Fisher HL, Abidi S, et al. Hot and cold executive functions in youth with psychotic symptoms. Psychol Med. 2017; 47:2844–2853
MacKenzie LE, Uher R, Pavlova B. Cognitive performance in first-degree relatives of individuals with vs without major depressive disorder: a meta-analysis. JAMA Psychiatry. 2019; 76:297–305
Maier R, Moser G, Chen GB, Ripke S, Coryell W, Potash JB, et al; Cross-Disorder Working Group of the Psychiatric Genomics Consortium. Joint analysis of psychiatric disorders increases accuracy of risk prediction for schizophrenia, bipolar disorder, and major depressive disorder. Am J Hum Genet. 2015; 96:283–294
Martin J, Tilling K, Hubbard L, Stergiakouli E, Thapar A, Davey Smith G, et al. Association of genetic risk for schizophrenia with nonparticipation over time in a population-based cohort study. Am J Epidemiol. 2016; 183:1149–1158
Martin AR, Daly MJ, Robinson EB, Hyman SE, Neale BM. Predicting polygenic risk of psychiatric disorders. Biol Psychiatry. 2019; 86:97–109
Maziade M, Gingras N, Rouleau N, Poulin S, Jomphe V, Paradis ME, et al. Clinical diagnoses in young offspring from eastern québec multigenerational families densely affected by schizophrenia or bipolar disorder. Acta Psychiatr Scand. 2008; 117:118–126
McCormack C, Green MJ, Rowland JE, Roberts G, Frankland A, Hadzi-Pavlovic D, et al. Neuropsychological and social cognitive function in young people at genetic risk of bipolar disorder. Psychol Med. 2016; 46:745–758
McGorry P, Nelson B. Why we need a transdiagnostic staging approach to emerging psychopathology, early diagnosis, and treatment. JAMA Psychiatry. 2016; 73:191–192
Mednick SA, McNeil TF. Current methodology in research on the etiology of schizophrenia: serious difficulties which suggest the use of the high-risk-group method. Psychol Bull. 1968; 70:681–693
Mednick SA, Parnas J, Schulsinger F. The copenhagen high-risk project, 1962-86. Schizophr Bull. 1987; 13:485–495
Meier SM, Pavlova B, Dalsgaard S, Nordentoft M, Mors O, Mortensen PB, Uher R. Attention-deficit hyperactivity disorder and anxiety disorders as precursors of bipolar disorder onset in adulthood. Br J Psychiatry. 2018; 213:555–560
Mesman E, Youngstrom EA, Juliana NK, Nolen WA, Hillegers MHJ. Validation of the seven up seven down inventory in bipolar offspring: screening and prediction of mood disorders. Findings from the dutch bipolar offspring study. J Affect Disord. 2017; 207:95–101
Miklowitz DJ, Schneck CD, Singh MK, Taylor DO, George EL, Cosgrove VE, et al. Early intervention for symptomatic youth at risk for bipolar disorder: a randomized trial of family-focused therapy. J Am Acad Child Adolesc Psychiatry. 2013; 52:121–131
Mirsky AF, Kugelmass S, Ingraham LJ, Frenkel E, Nathan M. Overview and summary: twenty-five-year followup of high-risk children. Schizophr Bull. 1995; 21:227–239
Mollon J, David AS, Zammit S, Lewis G, Reichenberg A. Course of cognitive development from infancy to early adulthood in the psychosis spectrum. JAMA Psychiatry. 2018; 75:270–279
Müller AD, Gjøde ICT, Eigil MS, Busck H, Bonne M, Nordentoft M, Thorup AAE. VIA family-a family-based early intervention versus treatment as usual for familial high-risk children: a study protocol for a randomized clinical trial. Trials. 2019; 20:112
Murray RM, Lewis SW. Is schizophrenia a neurodevelopmental disorder? Br Med J (Clin Res Ed). 1988; 296:63
Neilson E, Bois C, Clarke TK, Hall L, Johnstone EC, Owens DGC, et al. Polygenic risk for schizophrenia, transition and cortical gyrification: a high-risk study. Psychol Med. 2018; 48:1532–1539
Nery FG, Norris M, Eliassen JC, Weber WA, Blom TJ, Welge JA, et al. White matter volumes in youth offspring of bipolar parents. J Affect Disord. 2017; 209:246–253
Nishida A, Sasaki T, Harada S, Fukuda M, Masui K, Nishimura Y, et al. Risk of developing schizophrenia among japanese high-risk offspring of affected parent: outcome of a twenty-four-year follow up. Psychiatry Clin Neurosci. 2009; 63:88–92
Noguera A, Castro-Fornieles J, Romero S, de la Serna E, Sugranyes G, Sánchez-Gistau V, et al. Attenuated psychotic symptoms in children and adolescent offspring of patients with schizophrenia. Schizophr Res. 2018; 193:354–358
Nurnberger JI Jr, McInnis M, Reich W, Kastelic E, Wilcox HC, Glowinski A, et al. A high-risk study of bipolar disorder. Childhood clinical phenotypes as precursors of major mood disorders. Arch Gen Psychiatry. 2011; 68:1012–1020
Oliver D, Radua J, Reichenberg A, Uher R, Fusar-Poli P. Psychosis polyrisk score (PPS) for the detection of individuals at-risk and the prediction of their outcomes. Front Psychiatry. 2019; 10:174
Paccalet T, Gilbert E, Berthelot N, Marquet P, Jomphe V, Lussier D, et al. Liability indicators aggregate many years before transition to illness in offspring descending from kindreds affected by schizophrenia or bipolar disorder. Schizophr Res. 2016; 175:186–192
Padmanabhan JL, Shah JL, Tandon N, Keshavan MS. The ‘polyenviromic risk score’: aggregating environmental risk factors predicts conversion to psychosis in familial high-risk subjects. Schizophr Res. 2017; 181:17–22
Post RM, Altshuler LL, Kupka R, McElroy SL, Frye MA, Rowe M, et al. More assortative mating in US compared to European parents and spouses of patients with bipolar disorder: implications for psychiatric illness in the offspring. Eur Arch Psychiatry Clin Neurosci. 2018[Epub ahead of print]
    Poulton R, Caspi A, Moffitt TE, Cannon M, Murray R, Harrington H. Children’s self-reported psychotic symptoms and adult schizophreniform disorder: a 15-year longitudinal study. Arch Gen Psychiatry. 2000; 57:1053–1058
    Prasad KM, Goradia D, Eack S, Rajagopalan M, Nutche J, Magge T, et al. Cortical surface characteristics among offspring of schizophrenia subjects. Schizophr Res. 2010; 116:143–151
    Rasic D, Hajek T, Alda M, Uher R. Risk of mental illness in offspring of parents with schizophrenia, bipolar disorder, and major depressive disorder: a meta-analysis of family high-risk studies. Schizophr Bull. 2014; 40:28–38
    Ratnasingham S, Cairney J, Rehm J, Manson H, Kurdyak PA. Opening eyes, opening minds: the ontario burden of mental illness and addictions report. ICES. 2012
    Rawal A, Collishaw S, Thapar A, Rice F. A direct method of assessing underlying cognitive risk for adolescent depression. J Abnorm Child Psychol. 2013; 41:1279–1288
    Rice F, Sellers R, Hammerton G, Eyre O, Bevan-Jones R, Thapar AK, et al. Antecedents of new-onset major depressive disorder in children and adolescents at high familial risk. JAMA Psychiatry. 2017; 74:153–160
    Rice F, Riglin L, Thapar AK, Heron J, Anney R, O’Donovan MC, Thapar A. Characterizing developmental trajectories and the role of neuropsychiatric genetic risk variants in early-onset depression. JAMA Psychiatry. 2019; 76:306–313
    Roberts G, Lord A, Frankland A, Wright A, Lau P, Levy F, et al. Functional dysconnection of the inferior frontal gyrus in young people with bipolar disorder or at genetic high risk. Biol Psychiatry. 2017; 81:718–727
    Roberts G, Perry A, Lord A, Frankland A, Leung V, Holmes-Preston E, et al. Structural dysconnectivity of key cognitive and emotional hubs in young people at high genetic risk for bipolar disorder. Mol Psychiatry. 2018; 23:413–421
    Rosenbaum JF, Biederman J, Hirshfeld-Becker DR, Kagan J, Snidman N, Friedman D, et al. A controlled study of behavioral inhibition in children of parents with panic disorder and depression. Am J Psychiatry. 2000; 157:2002–2010
    Sameroff A, Seifer R, Zax M, Barocas R. Early indicators of developmental risk: rochester longitudinal study. Schizophr Bull. 1987; 13:383–394
    Sanchez-Gistau V, Romero S, Moreno D, de la Serna E, Baeza I, Sugranyes G, et al. Psychiatric disorders in child and adolescent offspring of patients with schizophrenia and bipolar disorder: a controlled study. Schizophr Res. 2015; 168:197–203
    Sandstrom A, MacKenzie L, Pizzo A, Fine A, Rempel S, Howard C, et al. Observed psychopathology in offspring of parents with major depressive disorder, bipolar disorder and schizophrenia. Psychol Med. 2019a1–7[Epub ahead of print]
    Sandstrom A, Uher R, Pavlova B. Prospective association between childhood behavioral inhibition and anxiety: a meta-analysis. 2019bSubmitted
    Sariçiçek A, Yalin N, Hidiroğlu C, Çavuşoğlu B, Taş C, Ceylan D, et al. Neuroanatomical correlates of genetic risk for bipolar disorder: a voxel-based morphometry study in bipolar type I patients and healthy first degree relatives. J Affect Disord. 2015; 186:110–118
    Schubert EW, McNeil TF. Prospective study of adult mental disturbance in offspring of women with psychosis. Arch Gen Psychiatry. 2003; 60:473–480
    Schultze-Lutter F, Ruhrmann S, Fusar-Poli P, Bechdolf A, Schimmelmann BG, Klosterkötter J. Basic symptoms and the prediction of first-episode psychosis. Curr Pharm Des. 2012; 18:351–357
    de la Serna E, Sugranyes G, Sanchez-Gistau V, Rodriguez-Toscano E, Baeza I, Vila M, et al. Neuropsychological characteristics of child and adolescent offspring of patients with schizophrenia or bipolar disorder. Schizophr Res. 2017; 183:110–115
    Shah J, Eack SM, Montrose DM, Tandon N, Miewald JM, Prasad KM, Keshavan MS. Multivariate prediction of emerging psychosis in adolescents at high risk for schizophrenia. Schizophr Res. 2012; 141:189–196
    Singh MK, Kelley RG, Howe ME, Reiss AL, Gotlib IH, Chang KD. Reward processing in healthy offspring of parents with bipolar disorder. JAMA Psychiatry. 2014; 71:1148–1156
    Singham T, Viding E, Schoeler T, Arseneault L, Ronald A, Cecil CM, et al. Concurrent and longitudinal contribution of exposure to bullying in childhood to mental health: the role of vulnerability and resilience. JAMA Psychiatry. 2017; 74:1112–1119
    Solé-Padullés C, Castro-Fornieles J, de la Serna E, Romero S, Calvo A, Sánchez-Gistau V, et al. Altered cortico-striatal connectivity in offspring of schizophrenia patients relative to offspring of bipolar patients and controls. Plos One. 2016; 11:e0148045
    Sugranyes G, Solé-Padullés C, de la Serna E, Borras R, Romero S, Sanchez-Gistau V, et al. Cortical morphology characteristics of young offspring of patients with schizophrenia or bipolar disorder. J Am Acad Child Adolesc Psychiatry. 2017; 56:79–88
    Talati A, Weissman MM, Hamilton SP. Using the high-risk family design to identify biomarkers for major depression. Philos Trans R Soc Lond B Biol Sci. 2013; 368:20120129
    Taylor MJ, Martin J, Lu Y, Brikell I, Lundström S, Larsson H, Lichtenstein P. Association of genetic risk factors for psychiatric disorders and traits of these disorders in a swedish population twin sample. JAMA Psychiatry. 2018; 76:280–289
    Thapar A, Rutter M. Do natural experiments have an important future in the study of mental disorders? Psychol Med. 2019; 49:1079–1088
    Torkamani A, Wineinger NE, Topol EJ. The personal and clinical utility of polygenic risk scores. Nat Rev Genet. 2018; 19:581–590
    Uher R, Cumby J, MacKenzie LE, Morash-Conway J, Glover JM, Aylott A, et al. A familial risk enriched cohort as a platform for testing early interventions to prevent severe mental illness. BMC Psychiatry. 2014; 14:344
    Uher R, Zwicker A. Etiology in psychiatry: embracing the reality of poly-gene-environmental causation of mental illness. World Psychiatry. 2017; 16:121–129
    Vandeleur CL, Strippoli MF, Castelao E, Gholam-Rezaee M, Ferrero F, Marquet P, et al. The lausanne-geneva cohort study of offspring of parents with mood disorders: methodology, findings, current sample characteristics, and perspectives. Soc Psychiatry Psychiatr Epidemiol. 2017; 52:1041–1058
    Versace A, Ladouceur CD, Graur S, Acuff HE, Bonar LK, Monk K, et al. Diffusion imaging markers of bipolar versus general psychopathology risk in youth at-risk. Neuropsychopharmacology. 2018; 43:2212–2220
    Weintraub S. Risk factors in schizophrenia: the stony brook high-risk project. Schizophr Bull. 1987; 13:439–450
    Weissman MM, Berry OO, Warner V, Gameroff MJ, Skipper J, Talati A, et al. A 30-year study of 3 generations at high risk and low risk for depression. JAMA Psychiatry. 2016; 73:970–977
    Wescott DL, Morash-Conway J, Zwicker A, Cumby J, Uher R, Rusak B. Sleep in offspring of parents with mood disorders. Front Psychiatry. 2019; 10:225
    Worland J, Janes CL, Anthony EJ, McGinnis M, Cass L. Watt NF, Anthony EJ, Wynne LC, Rolf JE. St. Louis risk research project: comprehensive progress report of experimental studies. Children at risk for schizophrenia: A longitudinal perspective. 1984, New York, NY, US: Cambridge University Press105–147
    Wynne LC, Cole RE, Perkins P. University of rochester child and family study: risk research in progress. Schizophr Bull. 1987; 13:463–476
    Zalpuri I, Singh MK. Treatment of psychiatric symptoms among offspring of parents with bipolar disorder. Curr Treat Options Psychiatry. 2017; 4:341–356
    de Zwarte SMC, Brouwer RM, Tsouli A, Cahn W, Hillegers MHJ, Hulshoff Pol HE, et al. Running in the Family? Structural brain abnormalities and IQ in offspring, siblings, parents, and co-twins of patients with schizophrenia. Schizophrenia Bull. 2018[Epub ahead of print]
    Zwicker A, MacKenzie LE, Drobinin V, Howes Vallis E, Patterson VC, Stephens M, et al. Basic symptoms in offspring of parents with severe mental illness. BJPsych Open. 2019a; 5:e54
    Zwicker A, Drobinin V, Howes Vallis E, Patterson VC, Cumby J, Propper L, et al. Affective lability in offspring of parents with major depressive disorder, bipolar disorder and schizophrenia. Eur Child Adolesc Psychiatry. 2019b1–7[Epub ahead of print]

    bipolar disorder; familial high-risk; major depressive disorder; offspring; review; schizophrenia; youth

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