Comparing GWAS and Brain Structure-Specific Gene Expression Profiles Identifies Psychiatric Disorder-Related Brain Structures at Different Developmental Stages.
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ABSTRACT:
SUBMITTER: Qi X
PROVIDER: S-EPMC7475161 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Substantial genetic liability is shared across psychiatric disorders but less is known about risk variants that are specific to a given disorder. We used multi-trait conditional and joint analysis (mtCOJO) to adjust GWAS summary statistics of one disorder for the effects of genetically correlated traits to identify putative disorder-specific SNP associations. We applied mtCOJO to summary statistics for five psychiatric disorders from the Psychiatric Genomics Consortium-schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), attention-deficit hyperactivity disorder (ADHD) and autism (AUT). Most genome-wide significant variants for these disorders had evidence of pleiotropy (i.e., impact on multiple psychiatric disorders) and hence have reduced mtCOJO conditional effect sizes. However, subsets of genome-wide significant variants had larger conditional effect sizes consistent with disorder-specific effects: 15 of 130 genome-wide significant variants for schizophrenia, 5 of 40 for major depression, 3 of 11 for ADHD and 1 of 2 for autism. We show that decreased expression of VPS29 in the brain may increase risk to SCZ only and increased expression of CSE1L is associated with SCZ and MD, but not with BIP. Likewise, decreased expression of PCDHA7 in the brain is linked to increased risk of MD but decreased risk of SCZ and BIP.
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Project description:Major depressive disorder (MDD) is the most prevalent mental disorder that affects more than 200 million people worldwide. Recent large-scale genome-wide association studies (GWAS) have identified multiple risk variants that show robust association with MDD. Nevertheless, how the identified risk variants confer risk of MDD remains largely unknown. To identify risk variants that are associated with gene expression in human brain and to identify genes whose expression change may contribute to the susceptibility of MDD, we systematically integrated the genetic associations from a large-scale MDD GWAS (N = 480,359) and brain expression quantitative trait loci (eQTL) data (N = 494) using a Bayesian statistical framework (Sherlock). Sherlock integrative analysis showed that FLOT1 was significantly associated with MDD (P = 6.02 × 10-6), suggesting that risk variants may contribute to MDD susceptibility through affecting FLOT1 expression. We further examined the expression level of FLOT1 in MDD cases and controls and found that FLOT1 was significantly upregulated in brains and peripheral blood of MDD cases compared with controls (European sample). Interestingly, we found that FLOT1 expression was also significantly upregulated in peripheral blood of first-episode drug-naive MDD cases compared with controls (P = 1.01 × 10-7, Chinese sample). Our study identified FLOT1 as a novel MDD risk gene whose expression level may play a role in MDD. In addition, our findings also suggest that risk variants may confer risk of MDD through affecting expression of FLOT1. Further functional investigation of FLOT1 may provide new insights for MDD pathogenesis.
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Project description:As psychiatric genetics enters an era where gene identification is finally yielding robust, replicable genetic associations and polygenic risk scores, it is important to consider next steps and delineate how that knowledge will be applied to ultimately ameliorate suffering associated with substance use and psychiatric disorders. Much of the post-genome-wide association study discussion has focused on the potential of genetic information to elucidate the underlying biology and use this information for the development of more effective pharmaceutical treatments. In this review we focus on additional areas of research that should follow gene identification. By taking genetic findings into longitudinal, developmental studies, we can map the pathways by which genetic risk manifests across development, elucidating the early behavioral manifestations of risk, and studying how various environments and interventions moderate that risk across developmental stages. The delineation of risk across development will advance our understanding of mechanism, sex differences and risk and resilience processes in different racial/ethnic groups. Here, we review how the extant twin study literature can be used to guide these efforts. Together, these new lines of research will enable us to develop more informed, tailored prevention and intervention efforts.
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Project description:ObjectiveIn both children and adults, psychiatric illness is associated with structural brain alterations, particularly in the prefrontal cortex (PFC). However, most studies compare gray matter volume (GMV) in healthy volunteers (HVs) to one psychiatric group. We compared GMV among youth with anxiety disorders, bipolar disorder (BD), disruptive mood dysregulation disorder (DMDD), attention-deficit/hyperactivity disorder (ADHD), and HVs.Method3-Tesla T1-weighted magnetic resonance imaging scans were acquired in 184 youths (39 anxious, 20 BD, 52 DMDD, 20 ADHD, and 53 HV). Voxel-based morphometry analyses were conducted. One-way analysis of variance tested GMV differences with whole-brain familywise error (p < .05) correction; secondary, exploratory whole-brain analyses used a threshold of p < .001, ≥200 voxels. Given recent frameworks advocating dimensional approaches in psychopathology research, we also tested GMV associations with continuous anxiety, irritability, and inattention symptoms.ResultsSpecificity emerged in the left dorsolateral PFC (dlPFC), which differed among youth with BD, anxiety, and HVs; GMV was increased in youth with anxiety, but decreased in BD, relative to HVs. Secondary analyses revealed BD-specific GMV decreases in the right lateral PFC, right dlPFC, and dorsomedial PFC, and also anxiety-specific GMV increases in the left dlPFC, right ventrolateral PFC, frontal pole, and right parahippocampal gyrus/lingual gyrus. Both BD and DMDD showed decreased GMV relative to HVs in the right dlPFC/superior frontal gyrus. GMV was not associated with dimensional measures of anxiety, irritability, or ADHD symptoms.ConclusionBoth disorder-specific and shared GMV differences manifest in pediatric psychopathology. Some differences were specific to anxiety disorders, others specific to BD, and others shared between BD and DMDD. Further developmental research might map commonalities and differences of structure and function in diverse pediatric psychopathologies.
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Project description:We show here that combining two existing genome wide association studies (GWAS) yields additional biologically relevant information, beyond that obtained by either GWAS separately. We propose Joint GWAS Analysis, a method that compares a pair of GWAS for similarity among the top SNP associations, top genes identified, gene functional clusters, and top biological pathways. We show that Joint GWAS Analysis identifies additional enriched biological pathways that would be missed by traditional Single-GWAS analysis. Furthermore, we examine the similarities of six complex genetic disorders at the SNP-level, gene-level, gene-cluster-level, and pathway-level. We make concrete hypotheses regarding novel pathway associations for several complex disorders considered, based on the results of Joint GWAS Analysis. Together, these results demonstrate that common complex disorders share substantially more genomic architecture than has been previously realized and that the meta-analysis of GWAS needs not be limited to GWAS of the same phenotype to be informative.
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Project description:BackgroundTo investigate the metabolic profiles in the follicular fluid (FF) samples from patients undergoing in vitro fertilization (IVF) and to analyze the correlations with follicular development.MethodsThe FF samples were obtained from participants (N = 26) who were receiving IVF under the gonadotropin-releasing hormone agonist (GnRH-a) long protocol stimulation and were collected separately from small (8-13 mm) and large (17-22 mm) follicles at the time of oocyte retrieval. Metabolomic analysis of the FF samples was performed using liquid chromatography-tandem mass spectrometry (LC-MS/MS).ResultsThe results demonstrated that the size of the follicle influences the metabolic signature of the FF according to the profile and differential metabolites. Dehydroepiandrosterone (DHEA), which is enriched in steroid hormone biosynthesis, correlated negatively with the oocyte maturation rate and the high-quality embryo rate, and thus could be used to estimate the predictive diagnostic potential of follicular development.ConclusionThe FF has different metabolic characteristics in different stages of follicular development. Exploring meaningful metabolites could predict follicular development, and modifications of these metabolites could influence follicular development.
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Project description:The pine moth Dendrolimus punctatus (Walker) is a common insect pest that confers serious damage to conifer forests in south of China. Extensive physiology and ecology studies on D. punctatus have been carried out, but the lack of genetic information has limited our understanding of the molecular mechanisms behind its development and resistance. Using RNA-seq approach, we characterized the transcriptome of this pine moth and investigated its developmental expression profiles during egg, larval, pupal, and adult stages. A total of 107.6 million raw reads were generated that were assembled into 70,664 unigenes. More than 30% unigenes were annotated by searching for homology in protein databases. To better understand the process of metamorphosis, we pairwise compared four developmental phases and obtained 17,624 differential expression genes. Functional enrichment analysis of differentially expressed genes showed positive correlation with specific physiological activities of each stage, and these results were confirmed by qRT-PCR experiments. This study provides a valuable genomic resource of D. punctatus covering all its developmental stages, and will promote future studies on biological processes at the molecular level.
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Project description: Not available
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Project description:After more than 10 years of accumulated efforts, genome-wide association studies (GWAS) have led to many findings, most of which have been deposited into the GWAS Catalog. Between GWAS's inception and March 2017, the GWAS Catalog has collected 2429 studies, 1818 phenotypes, and 28,462 associated SNPs. We reclassified the psychology-related phenotypes into 217 reclassified phenotypes, which accounted for 514 studies and 7052 SNPs. In total, 1223 of the SNPs reached genome-wide significance. Of these, 147 were replicated for the same psychological trait in different studies. Another 305 SNPs were replicated within one original study. The SNPs rs2075650 and rs4420638 were linked to the most replications within a single reclassified phenotype or very similar reclassified phenotypes; both were associated with Alzheimer's disease (AD). Schizophrenia was associated with 74 within-phenotype SNPs reported in independents studies. Alzheimer's disease and schizophrenia were both linked to some physical phenotypes, including cholesterol and body mass index, through common GWAS signals. Alzheimer's disease also shared risk SNPs with age-related phenotypes such as age-related macular degeneration and longevity. Smoking-related SNPs were linked to lung cancer and respiratory function. Alcohol-related SNPs were associated with cardiovascular and digestive system phenotypes and disorders. Two separate studies also identified a shared risk SNP for bipolar disorder and educational attainment. This review revealed a list of reproducible SNPs worthy of future functional investigation. Additionally, by identifying SNPs associated with multiple phenotypes, we illustrated the importance of studying the relationships among phenotypes to resolve the nature of their causal links. The insights within this review will hopefully pave the way for future evidence-based genetic studies.
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