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This review highlights the rational molecular structure design of mussel-inspired adhesive hydrogels and their applications in local immunomodulation.

Developing oral nanomedicines that suppress intestinal inflammation while modulating gut microbiota and brain interactions is essential for effectively treating inflammatory bowel disease. Here, we report an oral polyphenol-armored nanomedicine based on tumor necrosis factor–α (TNF-α)–small interfering RNA and gallic acid–mediated graphene quantum dot (GAGQD)–encapsulated bovine serum albumin nanoparticle, with a chitosan and tannin acid (CHI/TA) multilayer. Referred to “armor,” the CHI/TA multilayer resists the harsh environment of the gastrointestinal tract and adheres to inflamed colon sites in a targeted manner. TA provides antioxidative stress and prebiotic activities that modulate the diverse gut microbiota. Moreover, GAGQD protected TNF-α–siRNA delivery. Unexpectedly, the armored nanomedicine suppressed hyperactive immune responses and modulated bacterial gut microbiota homeostasis in a mouse model of acute colitis. Notably, the armored nanomedicine alleviated anxiety- and depression-like behaviors and cognitive impairment in mice with colitis. This armor strategy sheds light on the effect of oral nanomedicines on bacterial gut microbiome-brain interactions.

Introduction: Attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) commonly co-occur; both traits exert an influence on intelligence scores. Genetic relationships between these three traits are far from being clear. Methods: The summary results of genome-wide association studies of ADHD (20,183 cases and 35,191 controls), ASD (18,381 cases and 27,969 controls), and intelligence (269,867 participants) were used for the analyses. Local genetic correlation analysis and polygenic overlap analysis were used to explore the shared genetic components between ADHD, ASD, and intelligence. Mendelian randomization (MR) analysis was used to examine the causal associations between ADHD, ASD, and intelligence. A cross-trait meta-analysis was performed to identify pleiotropic genetic variants across the three traits. Results: Our results showed that intelligence has a positive and negative genetic correlation with ASD and ADHD, respectively, including three hub genomic regions showing correlated genetic effects across the three traits. Polygenic overlap analysis indicated that all the risk variants contributing to ADHD are overlapped with half of those for intelligence, and the majority of the shared variants have opposite effect directions between them. The majority of risk variants (80%) of ASD are overlapped with almost all the risk variants of intelligence (97%). Notably, some ASD/intelligence overlapping variants displayed opposing effects on these two conditions. MR analysis showed that the genetic liability to higher intelligence was associated with an increased risk for ASD (OR = 1.12) and a decreased risk for ADHD (OR = 0.78). Cross-trait meta-analyses identified 170 pleiotropic genomic loci across the three traits, including 12 novel loci. Functional analyses of the novel genes support their potential involvement in neurodevelopment. Conclusion: Our results suggest that ADHD is associated with inheriting a reduced set of low-intelligence alleles, whereas ASD results from incongruous effects from a mixture of high-intelligence and low-intelligence contributing alleles summed up with additional, ASD-specific risk variants not associated with intelligence.

Core–shell PEDOT@PZIF-71 nanoparticles as conductive nanofillers were homogeneously incorporated into a hydrophilic network to form conductive hydrogels for bio-electronics and bio-capacitors.

Genome editing tools have simplified the generation of knock-in gene fusions, which are widely used to study proteins in their natural context. However, strategies for tagging endogenous genes in primary cells are few and inefficient. In this study, we developed a one-step endogenous gene-tagging strategy by co-delivery of clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 ribonucleoprotein complexes and chemically modified donor DNA into cells. Upon CRISPR-Cas9 blunt-end double-strand breaks, highly efficient site-specific insertion of genetic materials (3 × FLAG or eGFP) was achieved in both cell lines and primary cells. We further optimized the gene-tagging efficiency and precision by using CRISPR-Cas12a, which produces a staggered cut with a 5' overhang and thus enables precise ligation of DNA donors with a complementary 3' overhang. With high efficiency and flexibility, this platform would be extremely useful for multiplex endogenous genes tagging and further exploration of protein functions in various cell types.

Despite considerable variation in disease manifestations observed among coronavirus disease 2019 (COVID-19) patients infected with severe acute respiratory syndrome coronavirus 2, the risk factors predicting disease severity remain elusive. Recent studies suggest that peripheral blood cells play a pivotal role in COVID-19 pathogenesis. Here, we applied two-sample Mendelian randomization (MR) analyses to evaluate the potential causal contributions of blood cell indices variation to COVID-19 severity, using single-nucleotide polymorphisms (SNPs) as instrumental variables for 17 indices from the UK Biobank and INTERVAL genome-wide association studies (N = 173 480). Data on the associations between the SNPs and very severe respiratory confirmed COVID-19 were obtained from the COVID-19 host genetics initiative (N = 8779/1 001 875). We observed significant negative association between hematocrit (HCT; odds ratio, OR = 0.775, 95% confidence interval, CI = 0.635-0.915, p = 3.48E-04) or red blood cell count (OR = 0.830, 95% CI = 0.728-0.932, p = 2.19E-03) and very severe respiratory confirmed COVID-19, as well as nominal negative association of hemoglobin concentration (OR = 0.808, 95% CI = 0.673-0.943, p = 3.95E-03) with very severe respiratory confirmed COVID-19 (no effect survived multiple correction). In conclusion, the MR study supports a protective effect of high HCT and red blood cell count from very severe respiratory confirmed COVID-19, suggesting potential strategies to ameliorate/treat clinical conditions in very severe respiratory confirmed COVID-19.

Summary Whole-genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci, which have not been reported previously. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, and G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3 bp indel p.Lys2169del (g.88717175_88717177TCT[4]) (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis (MIM: 194380 ), associated with higher mean corpuscular hemoglobin concentration (MCHC). In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.

Genome-wide association studies (GWAS) have uncovered thousands of genetic variants that influence risk for human diseases and traits. Yet understanding the mechanisms by which these genetic variants, mainly noncoding, have an impact on associated diseases and traits remains a significant hurdle. In this review, we discuss emerging experimental approaches that are being applied for functional studies of causal variants and translational advances from GWAS findings to disease prevention and treatment. We highlight the use of genome editing technologies in GWAS functional studies to modify genomic sequences, with proof-of-principle examples. We discuss the challenges in interrogating causal variants, points for consideration in experimental design and interpretation of GWAS locus mechanisms, and the potential for novel therapeutic opportunities. With the accumulation of knowledge of functional genetics, therapeutic genome editing based on GWAS discoveries will become increasingly feasible.

Background Ovarian cancer (OCa) is the most lethal gynecological malignant tumor, with few or no specific symptoms in its early stage. There are many signaling pathways involved in the process of OCa progression, among which the highly complex Wnt signaling pathway plays a unique role in the occurrence and development of OCa because of its functions of regulating gene expression, cell proliferation, migration, and invasion. Lipoprotein associated receptor protein 5/6 (LRP5/6) binds to activate this key pathway. Therefore, it is very important to study the mechanism of Wnt-LRP5 signaling pathway in the proliferation and migration of OCa. Methods In the present study, we have investigated the role of Wnt-LRP5 signaling pathway in OCa proliferation and migration for the first time using the dominant negative plasmid of LRP5 (DN-LRP5) and human OCa cells HO8910PM plus in a mouse model. Results Our data showed inactivation of LRP5 resulted in shift of epithelial-mesenchymal transition (EMT), rearrangement of the cytoskeleton, lowered activity of pro-proliferation and pro-migration cancer signaling pathways including Akt, p38 and NF-κB, eventually decreased proliferation and migration of OCa cells HO8910PM in vitro. Moreover, in vivo OCa-DN-LRP5 mouse model developed significantly smaller tumors as determined by inoculation of HO8910PM-DN-LRP5 cells into nude mice. Conclusions Collectively, our results demonstrate the dominant role of Wnt-LRP5 in OCa proliferation and migration and its potential as a valuable therapeutic target.

Genome-wide association studies (GWAS) have identified multiple genomic loci linked to blood cell traits, however understanding the biological relevance of these genetic loci has proven to be challenging. Here, we performed a transcriptome-wide association study (TWAS) integrating gene expression and splice junction usage in neutrophils (N = 196) with a neutrophil count GWAS (N = 173,480 individuals). We identified a total of 174 TWAS-significant genes enriched in target genes of master transcription factors governing neutrophil specification. Knockout of a TWAS candidate at chromosome 5q13.2, TAF9, in CD34+ hematopoietic and progenitor cells (HSPCs) using CRISPR/Cas9 technology showed a significant effect on neutrophil production in vitro. In addition, we identified 89 unique genes significant only for splice junction usage, thus emphasizing the importance of alternative splicing beyond gene expression underlying granulopoiesis. Our results highlight the advantages of TWAS, followed by gene editing, to determine the functions of GWAS loci implicated in hematopoiesis., Yao Yao et al. perform transcriptome-wide association analysis through integration of gene expression data and results of a previously-published genome-wide association study for neutrophil count. They find 34 independent genomic regions associated with expression changes and show that knockout of one candidate gene, TAF9, in CD34+ progenitor cells increases neutrophil maturation in vitro.

Major psychiatric traits are genetically inter-correlated with one another, but it not well known which genes play pleiotropic effects across different traits. We curated and compared genes identified from large-scale genome-wide association studies for seven psychiatric traits, including depression, bipolar disorder, schizophrenia, autism spectrum disorder, attention-deficit/hyperactivity disorder, anxiety and neuroticism. We then explored biological functions of the top pleiotropic genes. A total of 243 cross-trait genes were identified for the seven traits. Except for autism spectrum disorder, there was significant enrichment of overlapped genes across these psychiatric traits. Chromosome 5q14.3, 11q23.2, and 7p22.3 are the three genomic regions conferring highest pleiotropic effects for these psychiatric traits. The long non-coding gene LINC00461 showed the highest pleiotropic effects on five psychiatric traits. In silico and functional studies with mice support the vital role of LINC00461 in neurodevelopment. In sum, our study provides insights into the shared genetic liability among major psychiatric traits.

We aimed to investigate the genetic mechanisms associated with coronavirus disease of 2019 (COVID-19) outcomes in the host and to evaluate the possible associations between smoking and drinking behavior and three COVID-19 outcomes: severe COVID-19, hospitalized COVID-19 and COVID-19 infection. We described the genomic loci and risk genes associated with the COVID-19 outcomes, followed by functional analyses of the risk genes. Then, a summary data-based Mendelian randomization (SMR) analysis, and a transcriptome-wide association study (TWAS) were performed for the severe COVID-19 dataset. A two-sample Mendelian randomization (MR) analysis was used to evaluate the causal associations between various measures of smoking and alcohol consumption and the COVID-19 outcomes. A total of 26 protein-coding genes, enriched in chemokine binding, cytokine binding and senescence-related functions, were associated with either severe COVID-19 or hospitalized COVID-19. The SMR and the TWAS analyses highlighted functional implications of some GWAS hits and identified seven novel genes for severe COVID-19, including CCR5, CCR5AS, IL10RB, TAC4, RMI1 and TNFSF15, some of which are targets of approved or experimental drugs. According to our studies, increasing consumption of cigarettes per day by 1 standard deviation is related to a 2.3-fold increase in susceptibility to severe COVID-19 and a 1.6-fold increase in COVID-19-induced hospitalization. Contrarily, no significant links were found between alcohol consumption or binary smoking status and COVID-19 outcomes. Our study revealed some novel COVID-19 related genes and suggested that genetic liability to smoking may quantitatively contribute to an increased risk for a severe course of COVID-19.

We aimed to investigate the genetic mechanisms associated with coronavirus disease of 2019 (COVID-19) outcomes in the host and to evaluate the possible associations between smoking and drinking behavior and three COVID-19 outcomes: severe COVID-19, hospitalized COVID-19 and COVID-19 infection. We described the genomic loci and risk genes associated with the COVID-19 outcomes, followed by functional analyses of the risk genes. Then, a summary data-based Mendelian randomization (SMR) analysis, and a transcriptome-wide association study (TWAS) were performed for the severe COVID-19 dataset. A two-sample Mendelian randomization (MR) analysis was used to evaluate the causal associations between various measures of smoking and alcohol consumption and the COVID-19 outcomes. A total of 26 protein-coding genes, enriched in chemokine binding, cytokine binding and senescence-related functions, were associated with either severe COVID-19 or hospitalized COVID-19. The SMR and the TWAS analyses highlighted functional implications of some GWAS hits and identified seven novel genes for severe COVID-19, including CCR5, CCR5AS, IL10RB, TAC4, RMI1 and TNFSF15, some of which are targets of approved or experimental drugs. According to our studies, increasing consumption of cigarettes per day by 1 standard deviation is related to a 2.3-fold increase in susceptibility to severe COVID-19 and a 1.6-fold increase in COVID-19-induced hospitalization. Contrarily, no significant links were found between alcohol consumption or binary smoking status and COVID-19 outcomes. Our study revealed some novel COVID-19 related genes and suggested that genetic liability to smoking may quantitatively contribute to an increased risk for a severe course of COVID-19.

Hepatocellular carcinoma (HCC) is the leading cause of cancer mortality and without effective prognosis. Previous study has been confirmed that the abnormal expression of long non-coding RNAs (lncRNAs) TGFB2-AS1 was involved in tumorigenesis. However, the biological functions of TGFB2-AS1 in hepatocellular carcinoma (HCC) remain largely unclear. We comprehensively assess the clinical significance of TGFB2-AS1 and investigate the biological functions of TGFB2-AS1 on HCC HepG2 cells. We firstly confirmed the expression of TGFB2-AS1 between tumor and normal tissues using public available transcriptome data. We analyzed the clinical significance of TGFB2-AS1 using the TCGA HCC datasets. The biological functions of TGFB2-AS1 on HCC HepG2 cells were explored by multiple in vitro assays. We found that TGFB2-AS1 was remarkably increased in HCC tissues (P = 0.00148) and exhibited a potential predictive marker for HCC, with an area under curve (AUC) of 0.708 (P = 0.0034) using the fifty pairs of matched HCC tissues of TCGA. Besides, higher expression of TGFB2-AS1 in HCC tissues was identified as being positively associated with advanced tumor (P = 0.012) and disease stage (P = 0.009) in 355 HCC cases using independent sample nonparametric test. Downregulation of TGFB2-AS1 expression significantly restrained proliferation (P

NFKB1 was associated with treatment-refractory schizophrenia (SZ) and response to antipsychotics; however, the underlying mechanisms through which NFKB1 confers its risk for SZ are largely unknown. We aimed to investigate the potential role of NFKB1 in SZ.In the present study, we investigated the association of the risk SNP rs230529 of NFKB1 with gray matter density and with NFKB1 mRNA levels in various human brain regions. The spatiotemporal expression pattern of NFKB1 in human brains was explored. We constructed a miRNA-NFKB1-target gene regulatory network and analyzed its druggability through targeting NFKB1 for SZ treatment.NFKB1 showed the highest expression levels in the cerebellum, in which these levels were stratified by genotypes of rs230529. Interestingly, the allelic state of rs230529 was significantly associated with regional gray matter density in multiple brain regions (including the cerebellum), which also differed between patients with schizophrenia and controls. Furthermore, regulatory targets of NFKB1 were enriched among SZ susceptibility genes. A substantial proportion of NFKB1 target genes were subject to combinatorial regulation by NFKB1 and miRNAs, constituting a hybrid NFKB1-miRNA-gene regulatory network. Some components of this network showed expression changes relevant to both the disease and the treatment. Finally, we detected the dynamic changes of NFKB1-miR-155-5p-GSK3B and NFKB1-miR-155-5p/let-7a-5p-IL6 networks in course of the treatment of SZ.Taken together, our findings support the involvement of NFKB1-mediated dysregulation in the development of SZ.

Objections To review recent advances on Schizophrenia(SCZ) involving Long non-coding RNAs(lncRNAs) regulation, along with the consequences of lncRNAs deregulation for SCZ. Methods All sources of recent published papers and data including terms of SCZ and lncRNAs both in the literatures and in available databases including PubMed, SCOPUS, EMBASE, ISI Web of Knowledge and Google scholar were collected, and useful information and contents were extracted and organized into NPBR-styled review. Results LncRNAs are abundantly expressed in the brain, affecting neurogenesis, synaptic and stress responses, and neurotrophic and cognitive functions. Impaired expression of lncRNAs has been implicated in several forms of intellectual disability disorders including SCZ, and abnormal expression of certain specific lncRNAs will affect the occurrence and development of SCZ. Conclusions Schizophrenia(SCZ) is a common neurodevelopmental disorder worldwide with an around 1% prevalence, SCZ is usually characterized with either delusion and hallucinations or blunted affect and withdrawal or cognitive deficits. Long non-coding RNAs(lncRNAs) are a large fraction of the total ncRNAs pool with regulatory function. Growing evidences have suggested the involvement of lncRNAs in SCZ, highlighting the functional importance of this subclass of brain-enriched RNAs.

Whole genome sequencing (WGS), a powerful tool for detecting novel coding and non-coding disease-causing variants, has largely been applied to clinical diagnosis of inherited disorders. Here we leveraged WGS data in up to 62,653 ethnically diverse participants from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program and assessed statistical association of variants with seven red blood cell (RBC) quantitative traits. We discovered 14 single variant-RBC trait associations at 12 genomic loci. Several of the RBC trait-variant associations (RPN1, ELL2, MIDN, HBB, HBA1, PIEZO1, G6PD) were replicated in independent GWAS datasets imputed to the TOPMed reference panel. Most of these newly discovered variants are rare/low frequency, and several are observed disproportionately among non-European Ancestry (African, Hispanic/Latino, or East Asian) populations. We identified a 3bp indel p.Lys2169del (common only in the Ashkenazi Jewish population) of PIEZO1, a gene responsible for the Mendelian red cell disorder hereditary xerocytosis [OMIM 194380], associated with higher MCHC. In stepwise conditional analysis and in gene-based rare variant aggregated association analysis, we identified several of the variants in HBB, HBA1, TMPRSS6, and G6PD that represent the carrier state for known coding, promoter, or splice site loss-of-function variants that cause inherited RBC disorders. Finally, we applied base and nuclease editing to demonstrate that the sentinel variant rs112097551 (nearest gene RPN1) acts through a cis-regulatory element that exerts long-range control of the gene RUVBL1 which is essential for hematopoiesis. Together, these results demonstrate the utility of WGS in ethnically-diverse population-based samples and gene editing for expanding knowledge of the genetic architecture of quantitative hematologic traits and suggest a continuum between complex trait and Mendelian red cell disorders.

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 three 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 indicates 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 identifies 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 (2018YFC1314300) and the National Natural Science Foundation of China (81471364 and 81971255).

Severe congenital neutropenia (SCN) is a life-threatening disorder most often caused by dominant mutations of ELANE that interfere with neutrophil maturation. We conducted a pooled CRISPR screen in human hematopoietic stem and progenitor cells (HSPCs) that correlated ELANE mutations with neutrophil maturation potential. Highly efficient gene editing of early exons elicited nonsense-mediated decay (NMD), overcame neutrophil maturation arrest in HSPCs from ELANE-mutant SCN patients, and produced normal hematopoietic engraftment function. Conversely, terminal exon frameshift alleles that mimic SCN-associated mutations escaped NMD, recapitulated neutrophil maturation arrest, and established an animal model of ELANE-mutant SCN. Surprisingly, only -1 frame insertions or deletions (indels) impeded neutrophil maturation, whereas -2 frame late exon indels repressed translation and supported neutrophil maturation. Gene editing of primary HSPCs allowed faithful identification of variant pathogenicity to clarify molecular mechanisms of disease and encourage a universal therapeutic approach to ELANE-mutant neutropenia, returning normal neutrophil production and preserving HSPC function.

We conducted a cross-trait meta-analysis of genome-wide association study on schizophrenia (SCZ) (n = 65,967), bipolar disorder (BD) (n = 41,653), autism spectrum disorder (ASD) (n = 46,350), attention deficit hyperactivity disorder (ADHD) (n = 55,374), and depression (DEP) (n = 688,809). After the meta-analysis, the number of genomic loci increased from 14 to 19 in ADHD, from 3 to 10 in ASD, from 45 to 57 in DEP, from 8 to 54 in BD, and from 64 to 87 in SCZ. We observed significant enrichment of overlapping genes among different disorders and identified a panel of cross-disorder genes. A total of seven genes were found being commonly associated with four out of five psychiatric conditions, namely GABBR1, GLT8D1, HIST1H1B, HIST1H2BN, HIST1H4L, KCNB1, and DCC. The SORCS3 gene was highlighted due to the fact that it was involved in all the five conditions of study. Analysis of correlations unveiled the existence of two clusters of related psychiatric conditions, SCZ and BD that were separate from the other three traits, and formed another group. Our results may provide a new insight for genetic basis of the five psychiatric disorders.

Nerve growth factor (NGF) plays crucial roles in promoting neural growth and survival, and mediating synaptic and morphological plasticity. Several studies investigated the correlation between peripheral NGF levels and major psychiatric disorders, including schizophrenia (SCZ), major depressive disorder (MDD) and bipolar disorder (BPD); however, the findings were inconsistent. This meta-analysis sought to investigate blood NGF levels in patients with psychiatric disorders compared with healthy subjects and examined potential effects of blood fraction, medication and disease status. A total of 21 eligible studies, encompassing 1342 patients suffering from psychiatric disorders and 1225 healthy subjects, were enrolled in the present meta-analysis. No obvious publication bias was observed either for SCZ, MDD or BPD by the Begg's test (P 0.05). Random-effects meta-analysis showed that SCZ (Z = 2.14, P = 0.033, SMD = -1.08, 95% CI = -2.07 to -0.09) and MDD (Z = 2.57, P = 0.010, SMD = -0.61, 95% CI = -1.08 to -0.14) patients had significantly reduced NGF levels, compared with healthy controls. Notably, this decrease was enhanced in un-medicated patients of SCZ (P = 0.004) and medicated or chronic patients of MDD (P 0.001). No significant difference of NGF levels was observed between BPD patients and controls (P 0.05). These results supported an association between the reduction of NGF levels and psychiatric disorders. It remains unclear whether the change of NGF levels is a prerequisite for its function in psychiatric disorders development or merely an epiphenomenon unrelated to the pathophysiologic mechanisms.

Major psychiatric traits are genetically inter-correlated with one another, but it not well known which genes play pleiotropic effects across different traits. We curated and compared genes identified from large-scale genome-wide association studies for seven psychiatric traits, including depression, bipolar disorder, schizophrenia, autism spectrum disorder, attention-deficit/hyperactivity disorder, anxiety and neuroticism. We then explored biological functions of the top pleiotropic genes. A total of 243 cross-trait genes were identified for the seven traits. Except for autism spectrum disorder, there was significant enrichment of overlapped genes across these psychiatric traits. Chromosome 5q14.3, 11q23.2, and 7p22.3 are the three genomic regions conferring highest pleiotropic effects for these psychiatric traits. The long non-coding gene LINC00461 showed the highest pleiotropic effects on five psychiatric traits. In silico and functional studies with mice support the vital role of LINC00461 in neurodevelopment. In sum, our study provides insights into the shared genetic liability among major psychiatric traits.

Alzheimer's disease (AD) displays a long asymptomatic stage before dementia. We characterize AD stage-associated molecular networks by profiling 14,513 proteins and 34,173 phosphosites in the human brain with mass spectrometry, highlighting 173 protein changes in 17 pathways. The altered proteins are validated in two independent cohorts, showing partial RNA dependency. Comparisons of brain tissue and cerebrospinal fluid proteomes reveal biomarker candidates. Combining with 5xFAD mouse analysis, we determine 15 Aβ-correlated proteins (e.g., MDK, NTN1, SMOC1, SLIT2, and HTRA1). 5xFAD shows a proteomic signature similar to symptomatic AD but exhibits activation of autophagy and interferon response and lacks human-specific deleterious events, such as downregulation of neurotrophic factors and synaptic proteins. Multi-omics integration prioritizes AD-related molecules and pathways, including amyloid cascade, inflammation, complement, WNT signaling, TGF-β and BMP signaling, lipid metabolism, iron homeostasis, and membrane transport. Some Aβ-correlated proteins are colocalized with amyloid plaques. Thus, the multilayer omics approach identifies protein networks during AD progression.

Schizophrenia poses an evolutionary-genetic paradox as it exhibits strongly negative fitness effects (early mortality and decreased fecundity), yet it persists at a prevalence of approximately 1% worldwide. Evidence from several studies have suggested that schizophrenia is evolved and maintained in part as a maladaptive byproduct of recent positive selection and adaptive evolution in human beings. However, inconsistent results have been also proposed, challenging the recent positive selection theory to explain the high population frequency of schizophrenia-associated alleles. Here, we used public domain data to locate signatures of positive selection based on genetic diversity, derived allele frequency, differentiation between populations, and long haplotypes at schizophrenia-associated single nucleotide polymorphisms (SNPs) and randomly selected SNPs (as negative controls). We found evidence for positive selection at 10 out of the 105 schizophrenia-associated SNPs, while 5 of these SNPs involved positive selection for the protective allele. Taken together, the absence of widespread positive selection signals at the schizophrenia-associated SNPs, along with the fact that half of the positive selection favored the protective allele, provide little evidence supporting the positive selection theory in schizophrenia.

The progress of schizophrenia at various stages is an intriguing question, which has been explored to some degree using single-modality brain imaging data, e.g. gray matter (GM) or functional connectivity (FC). However it remains unclear how those changes from different modalities are correlated with each other and if the sensitivity to duration of illness and disease stages across modalities is different. In this work, we jointly analyzed FC, GM volume and single nucleotide polymorphisms (SNPs) data of 159 individuals including healthy controls (HC), drug-naïve first-episode schizophrenia (FESZ) and chronic schizophrenia patients (CSZ), aiming to evaluate the links among SNP, FC and GM patterns, and their sensitivity to duration of illness and disease stages in schizophrenia. Our results suggested: 1) both GM and FC highlighted impairments in hippocampal, temporal gyrus and cerebellum in schizophrenia, which were significantly correlated with genes like SATB2, GABBR2, PDE4B, CACNA1C etc. 2) GM and FC presented gradually decrease trend (HC > FESZ>CSZ), while SNP indicated a non-gradual variation trend with un-significant group difference observed between FESZ and CSZ; 3) Group difference between HC and FESZ of FC was more remarkable than GM, and FC presented a stronger negative correlation with duration of illness than GM (p = 0.0006). Collectively, these results highlight the benefit of leveraging multimodal data and provide additional clues regarding the impact of mental illness at various disease stages. Keywords: Multimodal fusion, SNP-FC-GM, Schizophrenia stages, Sensitivity, Duration of illness, ICA

Background: Typically, mental disorders are defined and classified based on clinical symptoms and syndromes. Although clinically useful, current diagnostic systems for psychiatry cause concerns due to the lack of biological mechanisms. Deciphering the relationships among psychiatric traits according to their genetic basis may facilitate understanding biological mechanisms of psychiatric disorders. Methods: Ten mental disorders were classified by genomic structural equation modeling (SEM) which leverages summary results of genome-wide association studies. Attention deficit/hyperactivity disorder (ADHD), anorexia nervosa (AN), anxiety disorder (ANX), autism spectrum disorder (ASD), bipolar disorder (BD), major depressive disorder (MDD), obsessive-compulsive disorder (OCD), posttraumatic stress disorder (PTSD), schizophrenia (SZ), and Tourette syndrome (TS) were included. Findings: Our analysis indicates that the ten psychiatric conditions were genetically inter-correlated with one another can be separated based on their general psychopathology. Most disorders have a close partner, forming pairs of traits, including SZ with BD, MDD with ANX, ADHD with ASD, and OCD with PTSD. TS and AN are two distinctive conditions, although both of them share some common components with OCD. At a higher level, MDD, ANX, ADHD, ASD, and PTSD cluster together, while OCD, AN, and TS cluster together. Together, the ten traits may constitute a hierarchical classificatory system. Interpretation: Our study allows inference of genetically determined classification of the ten mental disorders, which may biologically inform current diagnostic framework. Funding: National Natural Science Foundation of China and Primary Research & Development Plan of Jiangsu Province. Declaration of Interest: We declare no competing interests. Ethical Approval: Missing

Our previous genome-wide association study (CONVERGE sample) identified significant association between single nucleotide polymorphisms (SNPs) near the SIRT1 gene and major depressive disorder (MDD) in Chinese populations.To investigate whether SNPs across the SIRT1 gene locus affect regional grey matter density in the Han Chinese population.T1-weighted structural magnetic resonance imaging was conducted on 92 healthy participants from Eastern China. Grey matter was segmented from the image, which consisted of voxel-wise grey matter density. The effect of SIRT1 SNPs on grey matter density was determined by a multiple linear regression framework.SNP rs4746720 was significantly associated with grey matter density in two brain cortical regions: the orbital part of the right inferior frontal gyrus and the orbital part of the left inferior frontal gyrus (family-wise error-corrected P0.05; voxel-wise P0.001). Also, rs4746720 exceeded genome-wide significance in association with MDD in our CONVERGE sample (P = 3.32 × 10-08, odds ratio 1.161).Our results provided evidence for a potential role of the SIRT1 gene in the brain, implying a possible pathophysiological mechanism underlying susceptibility to MDD.

Schizophrenia is one of the most severe psychiatric disorders, with a high heritability of up to 80%. Several studies have reported telomere dysfunction in schizophrenia, and common variants in the telomerase reverse transcriptase (TERT) gene. TERT is a key component of the telomerase complex that maintains telomere length by addition of telomere repeats to telomere ends, and has repeatedly shown association with mean lymphocyte telomere length (LTL). Thus, we hypothesized that TERT may be a novel susceptibility gene for schizophrenia. Using a Taqman protocol, we genotyped eight tag SNPs from the TERT locus in 1,072 patients with paranoid schizophrenia and 1,284 control subjects from a Chinese Han population. We also measured mean LTL in 98 cases and 109 controls using a quantitative PCR-based technique. Chi-square tests showed that two SNPs, rs2075786 (P = 0.0009, OR = 0.76, 95%CI = 0.65-0.90) and rs4975605 (P = 0.0026, OR = 0.73, 95%CI = 0.60-0.90), were associated with a protective effect, while rs10069690 was associated with risk of paranoid schizophrenia (P = 0.0044, OR = 1.23, 95%CI = 1.07-1.42). Additionally, the rs2736118-rs2075786 haplotype showed significant association with paranoid schizophrenia (P = 0.0013). Moreover, mean LTL correlated with rs2075786 genotypes was significantly shorter in the patient group than the control group. The present results suggest that the TERT gene may be a novel candidate involved in the development of paranoid schizophrenia.

We conducted a cross-trait meta-analysis of genome-wide association study on schizophrenia (SCZ) (n = 65,967), bipolar disorder (BD) (n = 41,653), autism spectrum disorder (ASD) (n = 46,350), attention deficit hyperactivity disorder (ADHD) (n = 55,374), and depression (DEP) (n = 688,809). After the meta-analysis, the number of genomic loci increased from 14 to 19 in ADHD, from 3 to 10 in ASD, from 45 to 57 in DEP, from 8 to 54 in BD, and from 64 to 87 in SCZ. We observed significant enrichment of overlapping genes among different disorders and identified a panel of cross-disorder genes. A total of seven genes were found being commonly associated with four out of five psychiatric conditions, namely GABBR1, GLT8D1, HIST1H1B, HIST1H2BN, HIST1H4L, KCNB1, and DCC. The SORCS3 gene was highlighted due to the fact that it was involved in all the five conditions of study. Analysis of correlations unveiled the existence of two clusters of related psychiatric conditions, SCZ and BD that were separate from the other three traits, and formed another group. Our results may provide a new insight for genetic basis of the five psychiatric disorders.

Studies to date have reported hundreds of genes connected to bipolar disorder (BP). However, many studies identifying candidate genes have lacked replication, and their results have, at times, been inconsistent with one another. This paper, therefore, offers a computational workflow that can curate and evaluate BP-related genetic data. Our method integrated large-scale literature data and gene expression data that were acquired from both postmortem human brain regions (BP case/control: 45/50) and peripheral blood mononuclear cells (BP case/control: 193/593). To assess the pathogenic profiles of candidate genes, we conducted Pathway Enrichment, Sub-Network Enrichment, and Gene-Gene Interaction analyses, with 4 metrics proposed and validated for each gene. Our approach developed a scalable BP genetic database (BP_GD), including BP related genes, drugs, pathways, diseases and supporting references. The 4 metrics successfully identified frequently-studied BP genes (e.g. GRIN2A, DRD1, DRD2, HTR2A, CACNA1C, TH, BDNF, SLC6A3, P2RX7, DRD3, and DRD4) and also highlighted several recently reported BP genes (e.g. GRIK5, GRM1 and CACNA1A). The computational biology approach and the BP database developed in this study could contribute to a better understanding of the current stage of BP genetic research and assist further studies in the field.

Rs1344706 in the the zinc finger protein 804A (ZNF804A) gene has been identified to be associated with schizophrenia and bipolar disorder (BD) in Europeans. However, whether rs1344706 is associated with schizophrenia in Chinese populations remains inconclusive; furthermore, the association between rs1344706 and BD in Chinese populations has been rarely explored. To explore the association between rs1344706 and schizophrenia/BD in Chinese populations, we genotyped rs1344706 among 1128 Chinese subjects (537 patients with BD and 591 controls) and found that rs1344706 showed marginal allelic association with BD (P = 0.028) with T-allele being more prevalent in cases than that in controls (OR = 1.19, 95% CI 1.03–1.37). Meta-analysis of rs1344706 by pooling all available data showed that rs1344706 was significantly associated with BD (P = 0.001). Besides, positive association of rs1344706 with schizophrenia was observed in Northern Chinese (P = 0.005). Furthermore, ZNF804A is highly expressed in human and mouse brains, especially in prenatal stage.