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M8. Risk Trajectory of Children at Genetic Risk of Major Mood or Psychotic Disorders: Clustering of Risk Indicators as a Basis for a Preclinical Staging
Background: Research on “clinically at risk” (CHR) youths has thrived in the last decade, producing important findings on vulnerabilities to psychosis and opportunities for prevention. Yet, the CHR stage is more and more viewed as a late phase of risk (1). Investigating the earlier phases of risk in...
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| Published in: | Schizophrenia bulletin 2017-03, Vol.43 (suppl_1), p.S213-S214 |
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| Main Authors: | , , , , , , , |
| Format: | Article |
| Language: | English |
| Subjects: | |
| Online Access: | Get full text |
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| Summary: | Background:
Research on “clinically at risk” (CHR) youths has thrived in the last decade, producing important findings on vulnerabilities to psychosis and opportunities for prevention. Yet, the CHR stage is more and more viewed as a late phase of risk (1). Investigating the earlier phases of risk in children at genetic risk who carry developmental disorders and have a 15-fold increased risk of developing major psychoses (MP: schizophrenia, bipolar disorder, major depression), might thus be a key to understanding the neurodevelopmental roots of illness (2). In this view, recent findings have shown that the aggregation of risk indicators along the risk trajectory is highly predictive of future transition to illness in children born to affected parents from our Eastern Quebec Kindred Study (3) and in CHR youths from the NAPLS-2 study (4). We are now focusing ahead on the determinants, nature and timings of this clustering to decipher mechanisms and develop a clinical staging of the risk trajectory.
Methods:
We characterized the developmental trajectory of children at genetic risk with longitudinal assessments across a period of 11 years, with repeated measures of 5 established risk indicators: cognitive impairments, psychotic-like experiences, nonpsychotic DSM diagnosis, trauma and drug use. We assessed deteriorations of the trajectory in social functioning and transition to the disease. We hypothesized that the timing of the aggregation process determines the degree of later deterioration.
Results:
The predictive values of future transition for each risk indicator were low in these vulnerable offspring (relative risks RR~2). In contrast, transitioners accumulated more risk indicators in childhood-adolescence than non-transitioners (RR = 3.36). Around 60% of children remained stable over time in terms of aggregation, whereas 40% experienced changes in the number of risk indicators carried. We devised a model of preclinical staging to classify the children-adolescents using the increasing level of clustering of risk endophenotypes in a child. The model showed a satisfactory level of inter-individual and inter-sib variability.
Conclusion:
The accumulation of risk indicators in a child would predict deterioration in the trajectory and we observed change and stability over time in the clustering process. Such aggregations of risk markers have incidentally been also observed in other complex disorders such as metabolic-cardiovascular disorders (5). This may set th |
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| ISSN: | 0586-7614 1745-1701 |
| DOI: | 10.1093/schbul/sbx022.007 |