Franklin, J. C. | Search bioRxiv

bioRxiv2019

Brain Abnormalities Associated with Self-Injurious Thoughts and Behaviors: A Meta-Analysis of Neuroimaging Studies

Self-injurious thoughts and behaviors (SITBs) have long been believed to result in part from brain abnormalities. This meta-analysis aims to evaluate whether the extant literature justifies any definitive conclusions about whether and how SITBs may be associated with aberrant findings. Sixty studies published through June 1st, 2017 that compared individuals with and without SITBs were included, resulting in 734 coordinates. A pooled meta-analysis assessing for general risk for SITBs indicated a lack of convergence on structural abnormalities. Functional abnormalities in the precuneus/posterior cingulate cortex (PCC), temporal-parietal junction, and rostral-lateral prefrontal cortex were significant using multi-level kernel density analysis but nonsignificant using activation-likelihood estimation. Separate analyses for types of SITBs suggested that deliberate self-harm might be associated with abnormalities in the precuneus/PCC. Some moderator effects were detected. Overall, the meta-analytic evidence was not robust. More studies are needed to reach definitive conclusions about whether SITBs are associated with brain abnormalities.

neuroscience↗

bioRxiv2018

Significant shared heritability underlies suicide attempt and clinically predicted probability of attempting suicide

Suicide accounts for nearly 800,000 deaths per year worldwide with rates of both deaths and attempts rising. Family studies have estimated substantial heritability of suicidal behavior; however, collecting the sample sizes necessary for successful genetic studies has remained a challenge. We utilized two different approaches in independent datasets to characterize the contribution of common genetic variation to suicide attempt. The first is a patient reported suicide attempt phenotype from genotyped samples in the UK Biobank (337,199 participants, 2,433 cases). The second leveraged electronic health record (EHR) data from the Vanderbilt University Medical Center (VUMC, 2.8 million patients, 3,250 cases) and machine learning to derive probabilities of attempting suicide in 24,546 genotyped patients. We identified significant and comparable heritability estimates of suicide attempt from both the patient reported phenotype in the UK Biobank (h2SNP = 0.035, p = 7.12x10-4) and the clinically predicted phenotype from VUMC (h2SNP = 0.046, p = 1.51x10-2). A significant genetic overlap was demonstrated between the two measures of suicide attempt in these independent samples through polygenic risk score analysis (t = 4.02, p = 5.75x10-5) and genetic correlation (rg = 1.073, SE = 0.36, p = 0.003). Finally, we show significant but incomplete genetic correlation of suicide attempt with insomnia (rg = 0.34 - 0.81) as well as several psychiatric disorders (rg = 0.26 - 0.79). This work demonstrates the contribution of common genetic variation to suicide attempt. It points to a genetic underpinning to clinically predicted risk of attempting suicide that is similar to the genetic profile from a patient reported outcome. Lastly, it presents an approach for using EHR data and clinical prediction to generate quantitative measures from binary phenotypes that improved power for our genetic study.

genomics↗