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It is well established that children with familial high risk of schizophrenia (FHR-SZ) or bipolar disorder (FHR-BP) have a higher risk of developing mental disorders, however, little is known of to what degree the genetic and environmental vulnerabilities affect the quality of life and self-esteem of these children. We aimed to compare the quality of life and self-esteem between children with FHR-SZ or FHR-BP and controls. We used Danish nationwide registers to retrieve a cohort of 522 7-year-old children with FHR-SZ or FHR-BP and controls. Quality of life was assessed with the 'Health-related Quality of Life Screening Instrument', KIDSCREEN-27, and the scale 'Social Acceptance (Bullying)' from the KIDSCREEN-52. Self-esteem was assessed with the self-report scale 'I think I am'. Assessors were blind to familial risk status of the children. Children with FHR-SZ displayed lower levels of the general quality of life, as well as lower scores on the 'Psychological Well-being' scale and the 'School Environment' scale of the KIDSCREEN-27 compared with controls. Both children with FHR-SZ and FHR-BP reported more bullying victimization compared with controls. Children with FHR-SZ reported lower self-esteem on the total scale of 'I think I am', as well as on the 'Skills and talents', the 'Psychological well-being', and the 'Relationships with others' subscales compared with controls. The findings of lower quality of life and self-esteem in children with FHR-SZ together with more bullying victimization in both familial high-risk groups call for studies on low risk, early intervention strategies towards this group of vulnerable children.

Background Precision medicine may offer new strategies to treat migraine, and access to existing large cohorts may be a key resource to increase statistical power. Treatment response data is not routinely collected for large cohorts; however, such information could be extracted from pharmacy databases. Using a clinical migraine sample with treatment effect data, we assessed whether treatment response can be predicted based on the number of drug purchases. Methods A clinical cohort including 1913 migraineurs were interviewed using a semi-structured interview to retrieve treatment response data for acute and prophylactic migraine drugs. The purchase history was obtained from the Danish national pharmacy database. We assessed whether number of purchases at different thresholds could predict the specificity and sensitivity of treatment response. Results Purchase history of drugs was significantly associated with treatment response. For triptan treatment the specificity and sensitivity were above 80% for individuals with at least ten purchases. For prophylactic treatment (beta-blockers, angiotensin II antagonists or antiepileptic) we observed a sensitivity and specificity above 80% and 50% for individuals purchasing any prophylactic drug at least four times. In the Danish pharmacy database, 73% of the migraine patients have purchased at least ten triptans, while 55–63% have purchased at least one of the four prophylactic drugs. Conclusion Pharmacy databases are a valid source for identification of treatment response. Specifically for migraine drugs, we conclude that ten purchases of triptans or four purchases of prophylactic drugs are sufficient to predict a positive treatment response. Precision medicine may be accelerated with the use of pharmacy databases. Electronic supplementary material The online version of this article (10.1186/s10194-019-0987-y) contains supplementary material, which is available to authorized users.

The rapid increase in the availability of accurate 3D scanning devices has moved facial recognition and analysis into the 3D domain. 3D facial landmarks are often used as a simple measure of anatomy and it is crucial to have accurate algorithms for automatic landmark placement. The current state-of-the-art approaches have yet to gain from the dramatic increase in performance reported in human pose tracking and 2D facial landmark placement due to the use of deep convolutional neural networks (CNN). Development of deep learning approaches for 3D meshes has given rise to the new subfield called geometric deep learning, where one topic is the adaptation of meshes for the use of deep CNNs. In this work, we demonstrate how methods derived from geometric deep learning, namely multi-view CNNs, can be combined with recent advances in human pose tracking. The method finds 2D landmark estimates and propagates this information to 3D space, where a consensus method determines the accurate 3D face landmark position. We utilise the method on a standard 3D face dataset and show that it outperforms current methods by a large margin. Further, we demonstrate how models trained on 3D range scans can be used to accurately place anatomical landmarks in magnetic resonance images.

BACKGROUND: Migraine and Attention Deficit and Hyperactivity Disorder (ADHD) have been found to be associated in child and adolescent cohorts; however, the association has not been assessed in adults or otherwise healthy population. Assessing the comorbidity between ADHD and migraine may clarify the etiopathology of both diseases. Thus, the objective is to assess whether migraine (with and without visual disturbances) and ADHD are comorbid disorders.METHODS: Participants from the Danish Blood Donor Study (N = 26,456, age 18-65, 46% female) were assessed for migraine and ADHD using the ASRS ver 1.1 clinically validated questionnaire and self-reported migraine in a cross-sectional study. Logistic regression was used to examine the comorbidity between migraine and ADHD, and their associated endophenotypes.RESULTS: Migraine was strongly associated with ADHD (OR = 1.8, 95% CI = 1.5-2.1), (238/6152 vs 690/19,376). There was a significant interaction between age and gender, with comorbidity increasing with age and female sex. Post-hoc analysis showed that migraine with visual disturbance was generally associated with a marginally higher risk of ADHD and this was independent of ADHD endophenotypes.CONCLUSION: Migraine and ADHD were demonstrated to be comorbid disorders; the association with ADHD was most prominent for participants with migraine with visual disturbances. Future studies will elucidate which genetic and environmental factors contribute to migraine-ADHD comorbidity.