Frameshift mutations at the C-terminus of HIST1H1E result in a specific DNA hypomethylation signature

BACKGROUND

We previously associated HIST1H1E mutations causing Rahman syndrome with a specific genome-wide methylation pattern.

RESULTS

Methylome analysis from peripheral blood samples of six affected subjects led us to identify a specific hypomethylated profile. This "episignature" was enriched for genes involved in neuronal system development and function. A computational classifier yielded full sensitivity and specificity in detecting subjects with Rahman syndrome. Applying this model to a cohort of undiagnosed probands allowed us to reach diagnosis in one subject.

CONCLUSIONS

We demonstrate an epigenetic signature in subjects with Rahman syndrome that can be used to reach molecular diagnosis.

The Tatton-Brown-Rahman Syndrome: A clinical study of 55 individuals with de novo constitutive DNMT3A variants

Tatton-Brown-Rahman syndrome (TBRS; OMIM 615879), also known as the DNMT3A-overgrowth syndrome, is an overgrowth intellectual disability syndrome first described in 2014 with a report of 13 individuals with constitutive heterozygous DNMT3A variants. Here we have undertaken a detailed clinical study of 55 individuals with de novoDNMT3A variants, including the 13 previously reported individuals. An intellectual disability and overgrowth were reported in >80% of individuals with TBRS and were designated major clinical associations. Additional frequent clinical associations (reported in 20-80% individuals) included an evolving facial appearance with low-set, heavy, horizontal eyebrows and prominent upper central incisors; joint hypermobility (74%); obesity (weight ³2SD, 67%); hypotonia (54%); behavioural/psychiatric issues (most frequently autistic spectrum disorder, 51%); kyphoscoliosis (33%) and afebrile seizures (22%). One individual was diagnosed with acute myeloid leukaemia in teenage years. Based upon the results from this study, we present our current management for individuals with TBRS

Early improvement in positive rather than negative emotion predicts remission from depression after pharmacotherapy

Knowledge on mechanisms involved in early prediction of response to antidepressant medication may help optimize clinical decision making. Recent studies regarding response to pharmacotherapy implicate resilience-like mechanisms and involvement of positive, rather than negative emotions. The aim of the current study is to examine the contribution of early change in positive affect to the prediction of response to pharmacotherapy. Positive and negative emotions were measured at baseline and during the first week of pharmacotherapy, using experience sampling techniques. The association between early change in positive and negative emotions and severity of depressive symptoms at week six was examined in a sample of 49 depressed patients. The added benefits of measuring early change in positive emotions compared to early Hamilton Depression Rating Scale (HDRS) change alone were evaluated through model comparisons. Early improvement in positive affect during the first week of treatment predicted the continuous HDRS score (β=-0.64, p<0.001), response (50% reduction; OR=4.32, p<0.01), and remission (HDRS≤7; OR=9.29, p<0.001) at week six with moderate to large effect sizes. Effects of early change in negative emotions were only half as large and disappeared when evaluated simultaneously with early change in positive emotions. When early change in positive emotions was added to the models including early HDRS change only, all three models improved significantly. In conclusion, early change in positive rather than negative emotions best predicted response to treatment, supporting the notion that antidepressants activate resilience-like mechanisms. Moreover, monitoring of positive emotions in early stages of treatment may improve clinical decision making.