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Copy number variants (CNVs) have been associated with the risk of schizophrenia, autism and intellectual disability. However, little is known about their spectrum of psychopathology in adulthood.
We investigated the psychiatric phenotypes of adult CNV carriers and compared probands, who were ascertained through clinical genetics services, with carriers who were not. One hundred twenty-four adult participants (age 18–76), each bearing one of 15 rare CNVs, were recruited through a variety of sources including clinical genetics services, charities for carriers of genetic variants, and online advertising. A battery of psychiatric assessments was used to determine psychopathology.
The frequencies of psychopathology were consistently higher for the CNV group compared to general population rates. We found particularly high rates of neurodevelopmental disorders (NDDs) (48%), mood disorders (42%), anxiety disorders (47%) and personality disorders (73%) as well as high rates of psychiatric multimorbidity (median number of diagnoses: 2 in non-probands, 3 in probands). NDDs [odds ratio (OR) = 4.67, 95% confidence interval (CI) 1.32–16.51; p = 0.017) and psychotic disorders (OR = 6.8, 95% CI 1.3–36.3; p = 0.025) occurred significantly more frequently in probands (N = 45; NDD: 39[87%]; psychosis: 8[18%]) than non-probands (N = 79; NDD: 20 [25%]; psychosis: 3[4%]). Participants also had somatic diagnoses pertaining to all organ systems, particularly conotruncal cardiac malformations (in individuals with 22q11.2 deletion syndrome specifically), musculoskeletal, immunological, and endocrine diseases.
Adult CNV carriers had a markedly increased rate of anxiety and personality disorders not previously reported and high rates of psychiatric multimorbidity. Our findings support in-depth psychiatric and medical assessments of carriers of CNVs and the establishment of multidisciplinary clinical services.
The integration of molecular information in clinical decision making is becoming a reality. These changes are shaping the way clinical research is conducted, and as reality sets in, the challenges in conducting, managing and organising multi-disciplinary research become apparent. Clinical trials provide a platform to conduct translational research (TR) within the context of high quality clinical data accrual. Integrating TR objectives in trials allows the execution of pivotal studies that provide clinical evidence for biomarker-driven treatment strategies, targeting early drug development trials to a homogeneous and well defined patient population, supports the development of companion diagnostics and provides an opportunity for deepening our understanding of cancer biology and mechanisms of drug action. To achieve these goals within a clinical trial, developing translational research infrastructure and capabilities (TRIC) plays a critical catalytic role for translating preclinical data into successful clinical research and development. TRIC represents a technical platform, dedicated resources and access to expertise promoting high quality standards, logistical and operational support and unified streamlined procedures under an appropriate governance framework. TRIC promotes integration of multiple disciplines including biobanking, laboratory analysis, molecular data, informatics, statistical analysis and dissemination of results which are all required for successful TR projects and scientific progress. Such a supporting infrastructure is absolutely essential in order to promote high quality robust research, avoid duplication and coordinate resources. Lack of such infrastructure, we would argue, is one reason for the limited effect of TR in clinical practice beyond clinical trials.
The tumour suppressor gene encoding p53 has been shown from experimental studies to have a crucial role in how cells respond to DNA damage. p53 has important functions in apoptosis, cell-cycle arrest and DNA repair, largely mediated by its activity on gene transcription. However, despite this wealth of in vitro data, its role in how tumours respond to DNA damage induced by chemotherapeutic drugs remains controversial. In this review, we highlight some of the problems surrounding design and analysis of studies of p53 as a prognostic marker of clinical outcome, using ovarian cancer as an example. We aim to build on the knowledge of the published literature in ovarian cancer to identify criteria for clinical studies that should give a more definitive estimate of the role of p53 in clinical drug resistance. A search of three public databases using keywords combined with Boolean operators identified 64 clinical publications investigating the relationship of p53 to clinical outcome following chemotherapy in ovarian cancer. Although 43% of 215 published analyses from the 64 papers reported a significant correlation between p53 status and a clinical endpoint relevant to chemoresistance, only six analyses fulfil minimum criteria and none of these finds a statistically significant correlation of p53 with chemotherapy-resistance endpoints. The results from published clinical studies suggest a more complex role of p53 mutation in the mechanism of resistance in ovarian cancer than is suggested by in vitro studies.
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