Patterns of Convergence and Divergence Between Bipolar Disorder Type I and Type II: Evidence From Integrative Genomic Analyses

Aim: Genome-wide association studies (GWAS) analyses have revealed genetic evidence of bipolar disorder (BD), but little is known about the genetic structure of BD subtypes. We aimed to investigate the genetic overlap and distinction of bipolar type I (BD I) & type II (BD II) by conducting integrative post-GWAS analyses. Methods: We utilized single nucleotide polymorphism (SNP)-level approaches to uncover correlated and distinct genetic loci. Transcriptome-wide association analyses (TWAS) were then approached to pinpoint functional genes expressed in specific brain tissues and blood. Next, we performed cross-phenotype analysis, including exploring the potential causal associations between two BD subtypes and lithium responses and comparing the difference in genetic structures among four different psychiatric traits. Results: SNP-level evidence revealed three genomic loci, SLC25A17, ZNF184, and RPL10AP3, shared by BD I and II, and one locus (MAD1L1) and significant gene sets involved in calcium channel activity, neural and synapsed signals that distinguished two subtypes. TWAS data implicated different genes affecting BD I and II through expression in specific brain regions (nucleus accumbens for BD I). Cross-phenotype analyses indicated that BD I and II share continuous genetic structures with schizophrenia and major depressive disorder, which help fill the gaps left by the dichotomy of mental disorders. Conclusion: These combined evidences illustrate genetic convergence and divergence between BD I and II and provide an underlying biological and trans-diagnostic insight into major psychiatric disorders

Abnormal Alterations of Regional Spontaneous Neuronal Activity in Inferior Frontal Orbital Gyrus and Corresponding Brain Circuit Alterations: A Resting-State fMRI Study in Somatic Depression

Background: Major depressive disorders often involve somatic symptoms and have been found to have fundamental differences from non-somatic depression (NSD). However, the neural basis of this type of somatic depression (SD) is unclear. The aim of this study is to use the amplitude of low-frequency fluctuation (ALFF) and functional connectivity (FC) analyses to examine the abnormal, regional, spontaneous, neuronal activity and the corresponding brain circuits in SD patients.Methods: 35 SD patients, 25 NSD patients, and 27 matched healthy controls were selected to complete this study. The ALFF and seed-based FC analyses were employed, and the Pearson correlation was determined to observe possible clinical relevance.Results: Compared with NSD, the SD group showed a significant ALFF increase in the right inferior temporal gyrus; a significant ALFF decrease in left hippocampus, right inferior frontal orbital gyrus and left thalamus; and a significant decrease in the FC value between the right inferior frontal orbital gyrus and the left inferior parietal cortex (p < 0.05, corrected). Within the SD group, the mean ALFF value of the right inferior frontal orbital gyrus was associated with the anxiety factor scores (r = –0.431, p = 0.010, corrected).Conclusions: Our findings suggest that abnormal differences in the regional spontaneous neuronal activity of the right inferior frontal orbital gyrus were associated with dysfunction patterns of the corresponding brain circuits during rest in SD patients, including the limbic-cortical systems and the default mode network. This may be an important aspect of the underlying mechanisms for pathogenesis of SD at the neural level

TPH-2 Gene Polymorphism in Major Depressive Disorder Patients With Early-Wakening Symptom

Background: Sleep disturbances, such as early wakening, are frequently observed in patients with major depressive disorder (MDD). The suprachiasmatic nuclei (SCN), which controls circadian rhythm, is innervated by the raphe nucleus, a region where Tryptophan hydroxylase-2 (TPH-2) gene is primarily expressed. Although TPH-2 is often implicated in the pathophysiology of depression, few studies have applied a genetic and imaging technique to investigate the mechanism of early wakening symptom in MDD. We hypothesized that TPH-2 variants could influence the function of SCN in MDD patients with early wakening symptom.Methods: One hundred and eighty five MDD patients (62 patients without early wakening and 123 patients with early wakening) and 64 healthy controls participated in this study. Blood samples were collected and genotyping of rs4290270, rs4570625, rs11178998, rs7305115, rs41317118, and rs17110747 were performed by next-generation sequencing (NGS) technology. Logistic regression model was employed for genetic data analysis using the PLINK software. Based on the allele type, rs4290270, which was significant in the early wakening MDD group, participants were categorized into two groups (A allele and T carrier). All patients underwent whole brain resting-state functional magnetic resonance imaging (rs-fMRI) scanning and a voxel-wise functional connectivity comparison was performed between the groups.Results: rs4290270 was significantly linked to MDD patients who exhibited early wakening symptom. The functional connectivities of the right SCN with the right fusiform gyrus and right middle frontal gyrus were increased in the T carrier group compared to the A allele group. In addition, the functional connectivities of the left SCN with the right lingual gyrus and left calcarine sulcus were decreased in the T carrier group compared to the A allele group.Conclusion: These findings suggested that the TPH-2 gene variant, rs4290270, affected the circadian regulating function of SCN. The altered functional connectivities, observed between the SCN and right fusiform gyrus, right middle frontal gyrus, the right lingual gyrus and left calcarine sulcus, could highlight the neural mechanism by which SCN induces sleep-related circadian disruption in T carrier MDD patients. Hence, rs4290270 could potentially serve as a reliable biomarker to identify MDD patients with early wakening symptom

The interactions between host genome and gut microbiome increase the risk of psychiatric disorders: Mendelian randomization and biological annotation

BACKGROUND: The correlation between human gut microbiota and psychiatric diseases has long been recognized. Based on the heritability of the microbiome, genome-wide association studies on human genome and gut microbiome (mbGWAS) have revealed important host-microbiome interactions. However, establishing causal relationships between specific gut microbiome features and psychological conditions remains challenging due to insufficient sample sizes of previous studies of mbGWAS. METHODS: Cross-cohort meta-analysis (via METAL) and multi-trait analysis (via MTAG) were used to enhance the statistical power of mbGWAS for identifying genetic variants and genes. Using two large mbGWAS studies (7,738 and 5,959 participants respectively) and12 disease-specific studies from the Psychiatric Genomics Consortium (PGC), we performed bidirectional two-sample mendelian randomization (MR) analyses between microbial features and psychiatric diseases (up to 500,199 individuals). Additionally, we conducted downstream gene- and gene-set-based analyses to investigate the shared biology linking gut microbiota and psychiatric diseases. RESULTS: METAL and MTAG conducted in mbGWAS could boost power for gene prioritization and MR analysis. Increases in the number of lead SNPs and mapped genes were witnessed in 13/15 species and 5/10 genera after using METAL, and MTAG analysis gained an increase in sample size equivalent to expanding the original samples from 7% to 63%. Following METAL use, we identified a positive association between Bacteroides faecis and ADHD (OR, 1.09; 95 %CI, 1.02-1.16; P = 0.008). Bacteroides eggerthii and Bacteroides thetaiotaomicron were observed to be positively associated with PTSD (OR, 1.11; 95 %CI, 1.03-1.20; P = 0.007; OR, 1.11; 95 %CI, 1.01-1.23; P = 0.03). These findings remained stable across statistical models and sensitivity analyses. No genetic liabilities to psychiatric diseases may alter the abundance of gut microorganisms.Using biological annotation, we identified that those genes contributing to microbiomes (e.g., GRIN2A and RBFOX1) are expressed and enriched in human brain tissues. CONCLUSIONS: Our statistical genetics strategy helps to enhance the power of mbGWAS, and our genetic findings offer new insights into biological pleiotropy and causal relationship between microbiota and psychiatric diseases