Neurodevelopmental phenotype associated with CHD8-SUPT16H duplication

Microdeletions encompassing 14q11.2 locus, involving SUPT16H and CHD8, were shown to cause developmental delay, intellectual disability, autism spectrum disorders and macrocephaly. Variations leading to CHD8 haploinsufficiency or loss of function were also shown to lead to a similar phenotype. Recently, a 14q11.2 microduplication syndrome, encompassing CHD8 and SUPT16H, has been described, highlighting the importance of a tight control of at least CHD8 gene-dosage for a normal development. There have been only a few reports of 14q11.2 microduplications. Patients showed variable neurodevelopmental issues of variable severity. Breakpoints of the microduplications were non-recurrent, making interpretation of the CNV and determination of their clinical relevance difficult. Here, we report on two patients with 14q11.2 microduplication encompassing CHD8 and SUPT16H, one of whom had normal intelligence. Review of previous reports describing patients with comparable microduplications allowed for a more precise delineation of the condition and widening of the phenotypic spectrum.

     

Stability and change in family psychosocial risk over 6 months in pediatric cancer and its association with medical and psychosocial healthcare utilization

Purpose: Family psychosocial risk in pediatric oncology can be assessed using the Psychosocial Assessment Tool (PAT), a brief parent report screener based on the Pediatric Psychosocial Preventative Health Model (PPPHM; universal, targeted, and clinical). However, little is known about risk over the course of treatment and its association with medical and psychosocial healthcare utilization. Methods: Primary caregivers of children with cancer participated in this prospective multisite investigation, completing the PAT at diagnosis (T1; n = 396) and 6 months later (T2; n = 304). Healthcare utilization data were extracted from electronic health records. Results: The distribution of PPPHM risk levels at T1 and T2 was highly consistent for the samples. Two‐thirds of families remained at the same level of risk, 18% decreased and 16% increased risk level. Risk was not related to sociodemographic or treatment variables. The PAT risk score correlated with psychosocial contacts over the 6‐month period. Conclusions: Although the majority of families reported universal (low) risk on the PAT and were stable in their risk level over 6 months, reassessing risk is helpful in identifying those families who report higher level of risk during treatment than at diagnosis. PAT scores were related to psychosocial services that are provided to most but not all families and could be tailored more specifically to match risk and delivery of evidence‐based care.     

A Tool to Assess Patient and Surrogate Knowledge About the POLST (Physician Orders for Life-Sustaining Treatment) Program

ContextIt is especially important that patients are well informed when making high-stakes, preference-sensitive decisions like those on the Physician Orders for Life-Sustaining Treatment (POLST) form. However, there is currently no way to easily evaluate whether patients understand key concepts when making these important decisions.ObjectivesTo develop a POLST knowledge survey.MethodsExpert (n = 62) ratings of key POLST facts were used to select items for a POLST knowledge survey. The survey was administered to nursing facility residents (n = 97) and surrogate decision-makers (n = 112). A subset (n = 135) were re-administered the survey after a standardized advance care planning discussion to assess the scale's responsiveness to change.ResultsThe 19-item survey demonstrated adequate reliability (α = 0.72.). Residents' scores (x = 11.4, standard deviation 3.3) were significantly lower than surrogate scores (x = 14.7, standard deviation 2.5) (P < 0.001). Scores for both groups increased significantly after administration of a standardized advance care planning discussion (P < 0.001). Although being a surrogate, age, race, education, cognitive functioning, and health literacy were significantly associated with higher POLST Knowledge Survey scores in univariate analyses, only being a surrogate (P < 0.001) and being white (P = 0.028) remained significantly associated with higher scores in multivariate analyses.ConclusionThe 19-item POLST Knowledge Survey demonstrated adequate reliability and responsiveness to change. Findings suggest the survey could be used to identify knowledge deficits and provide targeted education to ensure adequate understanding of key clinical decisions when completing POLST.     

Automated classification of depression from structural brain measures across two independent community‐based cohorts

Major depressive disorder (MDD) has been the subject of many neuroimaging case–control classification studies. Although some studies report accuracies ≥80%, most have investigated relatively small samples of clinically‐ascertained, currently symptomatic cases, and did not attempt replication in larger samples. We here first aimed to replicate previously reported classification accuracies in a small, well‐phenotyped community‐based group of current MDD cases with clinical interview‐based diagnoses (from STratifying Resilience and Depression Longitudinally cohort, ‘STRADL’). We performed a set of exploratory predictive classification analyses with measures related to brain morphometry and white matter integrity. We applied three classifier types—SVM, penalised logistic regression or decision tree—either with or without optimisation, and with or without feature selection. We then determined whether similar accuracies could be replicated in a larger independent population‐based sample with self‐reported current depression (UK Biobank cohort). Additional analyses extended to lifetime MDD diagnoses—remitted MDD in STRADL, and lifetime‐experienced MDD in UK Biobank. The highest cross‐validation accuracy (75%) was achieved in the initial current MDD sample with a decision tree classifier and cortical surface area features. The most frequently selected decision tree split variables included surface areas of bilateral caudal anterior cingulate, left lingual gyrus, left superior frontal, right precentral and paracentral regions. High accuracy was not achieved in the larger samples with self‐reported current depression (53.73%), with remitted MDD (57.48%), or with lifetime‐experienced MDD (52.68–60.29%). Our results indicate that high predictive classification accuracies may not immediately translate to larger samples with broader criteria for depression, and may not be robust across different classification approaches.