Background

Self-injuring acts are among the most dramatic behaviours exhibited by human beings. There is no known single cause and there is no universally agreed upon treatment. Sophisticated sequential and temporal analysis of behaviour has provided alternative descriptions of self-injury that provide new insights into its initiation and maintenance.

Method

Forty hours of observations for each of 32 participants were collected in a contiguous two-week period. Twenty categories of behavioural and environmental events were recorded electronically that captured the precise time each observation occurred. Temporal behavioural/environmental patterns associated with self-injurious events were revealed with a method (t-patterns; THEME) for detecting non-linear, real-time patterns.

Results

Results indicated that acts of self-injury contributed both to more patterns and to more complex patterns. Moreover, self-injury left its imprint on the organization of behaviour even when counts of self-injury were expelled from the continuous record.

Conclusions

Behaviour of participants was organized in a more diverse array of patterns with SIB was present. Self-injuring acts may function as singular points, increasing coherence within self-organizing patterns of behaviour.

Genome-wide association studies have identified thousands of single nucleotide variants and small indels that contribute to variation in hematologic traits. While structural variants are known to cause rare blood or hematopoietic disorders, the genome-wide contribution of structural variants to quantitative blood cell trait variation is unknown. Here we utilized whole genome sequencing data in ancestrally diverse participants of the NHLBI Trans Omics for Precision Medicine program (N = 50,675) to detect structural variants associated with hematologic traits. Using single variant tests, we assessed the association of common and rare structural variants with red cell-, white cell-, and platelet-related quantitative traits and observed 21 independent signals (12 common and 9 rare) reaching genome-wide significance. The majority of these associations (N = 18) replicated in independent datasets. In genome-editing experiments, we provide evidence that a deletion associated with lower monocyte counts leads to disruption of an S1PR3 monocyte enhancer and decreased S1PR3 expression.