Four popular somatic single nucleotide variant (SNV) calling methods (Varscan, SomaticSniper, Strelka and MuTect2) were carefully evaluated on the real whole exome sequencing (WES, depth of ~50X) and ultra-deep targeted sequencing (UDT-Seq, depth of ~370X) data. The four tools returned poor consensus on candidates (only 20% of calls were with multiple hits by the callers). For both WES and UDT-Seq, MuTect2 and Strelka obtained the largest proportion of COSMIC entries as well as the lowest rate of dbSNP presence and high-alternative-alleles-in-control calls, demonstrating their superior sensitivity and accuracy. Combining different callers does increase reliability of candidates, but narrows the list down to very limited range of tumor read depth and variant allele frequency. Calling SNV on UDT-Seq data, which were of much higher read-depth, discovered additional true-positive variations, despite an even more tremendous growth in false positive predictions. Our findings not only provide valuable benchmark for state-of-the-art SNV calling methods, but also shed light on the access to more accurate SNV identification in the future.

BACKGROUND. Major depressive disorder (MDD) and posttraumatic stress disorder (PTSD) are highly comorbid and exhibit strong correlations with one another. We aimed to investigate mechanisms of underlying relationships between PTSD and 3 kinds of depressive phenotypes, namely, MDD, depressed affect (DAF), and depression (DEP, including both MDD and the broad definition of depression). METHODS. Genetic correlations between PTSD and the depressive phenotypes were tested using linkage disequilibrium score regression. Polygenic overlap analysis was used to estimate shared and trait-specific causal variants across a pair of traits. Causal relationships between PTSD and the depressive phenotypes were investigated using Mendelian randomization. Shared genomic loci between PTSD and MDD were identified using cross-trait meta-analysis. RESULTS. Genetic correlations of PTSD with the depressive phenotypes were in the range of 0.71–0.80. The estimated numbers of causal variants were 14,565, 12,965, 10,565, and 4,986 for MDD, DEP, DAF, and PTSD, respectively. In each case, causal variants contributing to PTSD were completely or largely covered by causal variants defining each of the depressive phenotypes. Mendelian randomization analysis indicated that the genetically determined depressive phenotypes confer a causal effect on PTSD (b = 0.21–0.31). Notably, genetically determined PTSD confers a causal effect on DEP (b = 0.14) and DAF (b = 0.15), but not MDD. Cross-trait meta-analysis of MDD and PTSD identified 47 genomic loci, including 29 loci shared between PTSD and MDD. CONCLUSION. Evidence from shared genetics suggests that PTSD is a subtype of MDD. This study provides support to the efforts in reducing diagnostic heterogeneity in psychiatric nosology. FUNDING. The National Key Research and Development Program of China and the National Natural Science Foundation of China.

Schizophrenia (SCZ) is a devastating genetic mental disorder. Identification of the SCZ risk genes in brains is helpful to understand this disease. Thus, we first used the minimum Redundancy-Maximum Relevance (mRMR) approach to integrate the genome-wide sequence analysis results on SCZ and the expression quantitative trait locus (eQTL) data from ten brain tissues to identify the genes related to SCZ. Second, we adopted the variance inflation factor regression algorithm to identify their interacting genes in brains. Third, using multiple analysis methods, we explored and validated their roles. By means of the aforementioned procedures, we have found that (1) the cerebellum may play a crucial role in the pathogenesis of SCZ and (2) ITIH4 may be utilized as a clinical biomarker for the diagnosis of SCZ. These interesting findings may stimulate novel strategy for developing new drugs against SCZ. It has not escaped our notice that the approach reported here is of use for studying many other genome diseases as well.

Objective: The epidemiological studies of Chinese developmental dyslexia (DD) in China are still limited. The current study aimed to investigate the prevalence rate, risk factors, and psychiatric comorbidities of Chinese DD in Guangzhou, a city in South China. Method: A total of 1661 students from second to fifth grades were recruited. The dyslexic students were identified by evaluating learning disability through the Pupil Rating Scale–Revised Screening for Learning Disability (PRS) scale by the head teachers and word recognition through the standard test. Students with a PRS score of <65 received the Raven’s test, and those with intelligence quotient scores below 80 in the Raven’s test were excluded. Psychiatric comorbidities were assessed by the Strength and Difficulties Questionnaire completed by parents. Results: The prevalence rate of Chinese DD was 4.9% in Guangzhou city. There were significant differences in gender, the paternal educational level, and reading experience before the age of 6 years between the DD group and the non-DD group. Male gender (odds ratio [OR] = 4.17), low paternal educational level (p = 0.045), and lack of reading experience before the age of 6 years (OR = 1.99) were the risk factors for DD. The DD cases had a higher risk of hyperactivity and inattention (OR = 3.21). Conclusion: This study showed that the prevalence rate of DD was 4.9% in Guangzhou city. Male gender, low paternal educational level, and lack of reading experience before the age of 6 years were the risk factors for Chinese DD. The high comorbidity rate of hyperactivity and inattention in the Chinese DD population needs further evaluation.

Background High blood pressure is a leading cardiovascular disease risk factor and considered to be associated with psychological factors. However, the causal relationships between blood pressure and anxiety, depressive symptoms, neuroticism and subjective well-being are not clear. Aims The current study explored the genetic causal relationships between blood pressure and anxiety, depressive symptoms, neuroticism and subjective well-being. Methods Mendelian randomisation (MR) analyses were performed using the generalised summary-data-based MR analysis method with eight large-scale genome-wide association study datasets for hypertension, systolic blood pressure (SBP), diastolic blood pressure (DBP), pulse pressure, anxiety, depressive symptoms, neuroticism and subjective well-being. Results A causal effect of DBP on neuroticism was found, and 1074 independent instrumental single nucleotide polymorphisms were identified by the incorporated Heterogeneity in Dependent Instruments-outlier test among the bidirectional causal relationship between blood pressure and the four psychological states. Conclusions DBP has a causal effect on neuroticism. Appropriate management of blood pressure may reduce neuroticism, neuroticism-inducing mood disorders and cardiovascular diseases.