The Importance of Measuring Multi-level Risk and Illness Progression Markers in High-risk Youth From Well-characterized Bipolar Parents

Convergent evidence from longitudinal population and high-risk studies has supported that psychiatric disorders in adults typically onset in childhood and adolescence which not uncommonly debut as non-specific symptoms and syndromes (i.e. heterotypy) (Kim-Cohen et al., 2003Kim-Cohen J. Caspi A. Moffitt T.E. Harrington H. Milne B.J. Poulton R. Prior juvenile diagnoses in adults with mental disorder: developmental follow-back of a prospective-longitudinal cohort.Arch. Gen. Psychiatry. 2003; 60: 709-717Crossref PubMed Scopus (1550) Google Scholar, Duffy, 2015Duffy A. Early identification of recurrent mood disorders in youth: the importance of a developmental approach.Evid. Based Ment. Health. 2015; 18: 7-9Crossref PubMed Scopus (16) Google Scholar). Studying multiple indicators of illness risk and development longitudinally within high-risk subjects is increasingly recognized as important in order to differentiate vulnerability from burden of illness effects and to identify patterns of abnormalities associated with the clinical trajectory of illness development. Taken in this context, the paper in this issue of EBioMedicine by Lee and colleagues reports on findings of a cross-sectional study of neural correlates and clinical outcomes up to 2 years later in 44 offspring of bipolar parents (Lin et al., 2015Lin K. Xu G. Wong N.M.L. Wu H. Li T. Lu W. Chen K. Chen X. Lai B. Zhong L. So K. Lee T.M.C. A Multi-Dimensional and Integrative Approach to Examining the High-Risk and Ultra-High-Risk Stages of Bipolar Disorder.EBio. Med. 2015; 2: 917-926Summary Full Text Full Text PDF Scopus (26) Google Scholar). High-risk offspring were divided into subgroups comprising well (HR) or symptomatic/ultra-high-risk (UHR) compared to healthy controls (C). Structural and functional neuroimaging and neurocognitive performance (i.e. processing speed and visual spatial) and global functioning differences were found between the groups and interpreted as evidence of differential indicators of BD vulnerability and illness progression. This study demonstrates the current and important trend of incorporating a multidimensional approach to assessing interactive illness risk and progression processes in youth at confirmed high-risk (Lin et al., 2015Lin K. Xu G. Wong N.M.L. Wu H. Li T. Lu W. Chen K. Chen X. Lai B. Zhong L. So K. Lee T.M.C. A Multi-Dimensional and Integrative Approach to Examining the High-Risk and Ultra-High-Risk Stages of Bipolar Disorder.EBio. Med. 2015; 2: 917-926Summary Full Text Full Text PDF Scopus (26) Google Scholar). However, the interpretation of the specific findings should be taken as preliminary given several limitations. Firstly, the study of neural correlates was cross-sectional including only a small number of high-risk offspring of a relatively wide age range (i.e. 8–28 years) and with a limited clinical follow-up period (i.e. up to 2 years). The fact that offspring with a prior diagnosis were excluded, suggests that those included over age 20 may be resilient and different in measured outcomes from younger subjects. In fact, other high-risk studies have reported that the mean age of onset for major mood episodes is in mid-adolescence and early risk syndromes, such as full-blown anxiety or sleep disorders, manifest years earlier in mid-childhood (Duffy et al., 2010Duffy A. Alda M. Hajek T. Sherry S.B. Grof P. Early stages in the development of bipolar disorder.J. Affect. Disord. 2010; 121: 127-135Crossref PubMed Scopus (227) Google Scholar, Mesman et al., 2013Mesman E. Nolen W.A. Reichart C.G. Wals M. Hillegers M.H. The Dutch bipolar offspring study: 12-year follow-up.Am. J. Psychiatry. 2013; 170: 542-549Crossref PubMed Scopus (158) Google Scholar). Furthermore, in this study – as in most others – the nature of the subtype of BD in the parent is neglected (Lin et al., 2015Lin K. Xu G. Wong N.M.L. Wu H. Li T. Lu W. Chen K. Chen X. Lai B. Zhong L. So K. Lee T.M.C. A Multi-Dimensional and Integrative Approach to Examining the High-Risk and Ultra-High-Risk Stages of Bipolar Disorder.EBio. Med. 2015; 2: 917-926Summary Full Text Full Text PDF Scopus (26) Google Scholar). Yet, given the substantial heterogeneity of the BD diagnosis – subsuming different subtypes associated with characteristic differences in clinical, neurobiological and neurocognitive findings – this is a major oversight that has contributed to difficulties in replication of findings between studies (Alda, 2004Alda M. The phenotypic spectra of bipolar disorder.Neuropsychopharmacology. 2004; 14: 94-99Crossref Scopus (72) Google Scholar, Manchia et al., 2013Manchia M. Cullis J. Turecki G. Rouleau G.A. Uher R. Alda M. The impact of phenotypic and genetic heterogeneity on results of genome wide association studies of complex diseases.PLoS One. 2013; 8: e76295Crossref PubMed Scopus (136) Google Scholar). For example, heterogeneity of the subtype of BD segregating in the family may explain counter-intuitive and contradictory findings reported in this study (i.e. increased small-world properties in UHR). The smaller volumes in regions of interest in HR offspring in this paper seems counter to findings reported by Hajek et al. of increased right inferior frontal gyrus volumes in HR offspring and BD patients early in the illness course, while BD patients with substantial illness burden showed decreased volumes which appeared to be mitigated in those treated with lithium (Hajek et al., 2013Hajek T. Cullis J. Novak T. Kopecek M. Blagdon R. Propper L. Stopkova P. Duffy A. Hoschl C. Uher R. Paus T. Young L.T. Alda M. Brain structural signature of familial predisposition for bipolar disorder: replicable evidence for involvement of the right inferior frontal gyrus.Biol. Psychiatry. 2013; 73: 144-152Summary Full Text Full Text PDF PubMed Scopus (98) Google Scholar). Finally, this study divided high-risk offspring based on symptom status following an approach used in conversion to psychosis studies (Yung et al., 2004Yung A.R. Phillips L.J. Yuen H.P. McGorry P.D. Risk factors for psychosis in an ultra high-risk group: psychopathology and clinical features.Schizophr. Res. 2004; 67: 131-142Crossref PubMed Scopus (651) Google Scholar). The problem here is that the ultra-high-risk concept has typically been used to refer to clinical at risk groups of youth. Ideally, if the question is one of mapping biomarkers to clinical illness progression, offspring should ideally be re-assessed in remission or at their best level of functioning and their clinical course carefully documented to place them on a clinical continuum of risk (clinical staging) and map changes in outcomes to clinical progression taking into account burden of illness. These points notwithstanding, this study contributes to an important international effort to characterize markers of BD risk and development at the clinical, biological and psychological levels and to explore the relationship between these processes (Lin et al., 2015Lin K. Xu G. Wong N.M.L. Wu H. Li T. Lu W. Chen K. Chen X. Lai B. Zhong L. So K. Lee T.M.C. A Multi-Dimensional and Integrative Approach to Examining the High-Risk and Ultra-High-Risk Stages of Bipolar Disorder.EBio. Med. 2015; 2: 917-926Summary Full Text Full Text PDF Scopus (26) Google Scholar). It is an exciting and timely effort, and we will undoubtedly continue to learn from one another, comparing and contrasting similarities and differences in findings taken in context of the methods applied, in order to advance understanding. A single comprehensive clinical staging model based on the evidence from longitudinal prospective offspring studies specific to BD subtypes (rather than extrapolated from findings of studies of heterogeneous populations of psychotic youth), would be exceedingly helpful to this effort (Duffy, 2014Duffy A. Towards a comprehensive clinical staging model for bipolar disorder: integrating the evidence.Can. J. Psychiatry. 2014; 59Crossref PubMed Scopus (62) Google Scholar, Duffy, 2015Duffy A. Early identification of recurrent mood disorders in youth: the importance of a developmental approach.Evid. Based Ment. Health. 2015; 18: 7-9Crossref PubMed Scopus (16) Google Scholar). While there may be some similarities between different illness trajectories and associated risk indicators and processes across subtypes, it is important that we do not simply generalize from one disease model to the next or develop some one size fits all approach based on assumptive leaps rather than the evidence. This would be akin to lumping other illnesses together (i.e. Parkinson's disease and Alzheimer's dementia) based on some overlapping findings, despite important differences in etiology, clinical course and treatment response. The author declared no conflicts of interest. A Multi-Dimensional and Integrative Approach to Examining the High-Risk and Ultra-High-Risk Stages of Bipolar DisorderThe abnormalities observed in the HR offspring appear to be inherited, whereas those associated with the UHR offspring represent stage-specific changes predisposing them to developing the disorder. Full-Text PDF Open Access

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