Cell type-specific and cross-population polygenic risk score analyses of MIR137 gene pathway in schizophrenia.
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ABSTRACT:
SUBMITTER: Yao Y
PROVIDER: S-EPMC8283158 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Treatment-resistant schizophrenia (TRS) affects around one-third of individuals with schizophrenia. Although a number of sociodemographic and clinical predictors of TRS have been identified, data on the genetic risk of TRS are sparse. We aimed to investigate the association between a polygenic risk score for schizophrenia and treatment resistance in patients with schizophrenia. We conducted a nationwide, population-based follow-up study among all Danish individuals born after 1981 and with an incident diagnosis of schizophrenia between 1999 and 2007. Based on genome-wide data polygenic risk scores for schizophrenia were calculated in 862 individuals with schizophrenia. TRS was defined as either clozapine initiation or at least 2 periods of different antipsychotic monotherapies and still being hospitalized. We estimated hazard rate ratios (HRs) for TRS in relation to the polygenic risk score while adjusting for population stratification, age, sex, geographical area at birth, clinical treatment setting, psychiatric comorbidity, and calendar year. Among the 862 individuals with schizophrenia, 181 (21.0%) met criteria for TRS during 4674 person-years of follow-up. We found no significant association between the polygenic risk score and TRS, adjusted HR = 1.13 (95% CI: 0.95-1.35). Based on these results, the use of the polygenic risk score for schizophrenia to identify individuals with TRS is at present inadequate to be of clinical utility at the individual patient level. Future research should include larger genetic samples in combination with non-genetic markers. Moreover, a TRS-specific developed polygenic risk score would be of great interest towards early prediction of TRS.
| S-EPMC5581885 | biostudies-other
Project description:Polygenic risk scores (PRSs) have been among the leading advances in biomedicine in recent years. As a proxy of genetic liability, PRSs are utilised across multiple fields and applications. While numerous statistical and machine learning methods have been developed to optimise their predictive accuracy, these typically distil genetic liability to a single number based on aggregation of an individual's genome-wide risk alleles. This results in a key loss of information about an individual's genetic profile, which could be critical given the functional sub-structure of the genome and the heterogeneity of complex disease. In this manuscript, we introduce a 'pathway polygenic' paradigm of disease risk, in which multiple genetic liabilities underlie complex diseases, rather than a single genome-wide liability. We describe a method and accompanying software, PRSet, for computing and analysing pathway-based PRSs, in which polygenic scores are calculated across genomic pathways for each individual. We evaluate the potential of pathway PRSs in two distinct ways, creating two major sections: (1) In the first section, we benchmark PRSet as a pathway enrichment tool, evaluating its capacity to capture GWAS signal in pathways. We find that for target sample sizes of >10,000 individuals, pathway PRSs have similar power for evaluating pathway enrichment as leading methods MAGMA and LD score regression, with the distinct advantage of providing individual-level estimates of genetic liability for each pathway -opening up a range of pathway-based PRS applications, (2) In the second section, we evaluate the performance of pathway PRSs for disease stratification. We show that using a supervised disease stratification approach, pathway PRSs (computed by PRSet) outperform two standard genome-wide PRSs (computed by C+T and lassosum) for classifying disease subtypes in 20 of 21 scenarios tested. As the definition and functional annotation of pathways becomes increasingly refined, we expect pathway PRSs to offer key insights into the heterogeneity of complex disease and treatment response, to generate biologically tractable therapeutic targets from polygenic signal, and, ultimately, to provide a powerful path to precision medicine.
| S-EPMC9937466 | biostudies-literature
Project description:This study assessed genetic contributions to six cognitive domains, identified by the MATRICS Cognitive Consensus Battery as relevant for schizophrenia, cognition-enhancing, clinical trials. Psychiatric Genomics Consortium Schizophrenia polygenic risk scores showed significant negative correlations with each cognitive domain. Genome-wide association analyses identified loci associated with attention/vigilance (rs830786 within HNF4G), verbal memory (rs67017972 near NDUFS4), and reasoning/problem solving (rs76872642 within HDAC9). Gene set analysis identified unique and shared genes across cognitive domains. These findings suggest involvement of common and unique mechanisms across cognitive domains and may contribute to the discovery of new therapeutic targets to treat cognitive deficits in schizophrenia.
| S-EPMC6252137 | biostudies-literature
Project description:Schizophrenia is substantially comorbid with type 2 diabetes (T2D), but the molecular basis of this effect is incompletely understood. Here, we show that a cortical schizophrenia expression score predicts glycemic control from pancreatic islet cell expression. We used machine learning to identify a cortical expression signature in 212 schizophrenia patients and controls, which explained ~25% of the illness-associated variance. The algorithm was predicted in expression data from 51 subjects (9 with T2D), explained up to 26.3% of the variance in the glycemic control indicator HbA1c and could significantly differentiate T2D patients from controls. The cross-tissue prediction was driven by processes previously linked to diabetes. Genes contributing to this prediction were involved in the electron transport chain as well as kidney development and support oxidative stress as a molecular process underlying the comorbidity between both conditions. Together, the present results suggest a molecular commonality between schizophrenia and glycemic markers of type 2 diabetes.
| S-EPMC5802590 | biostudies-literature
Project description:The use of polygenic risk scores has become a practical translational approach to investigating the complex genetic architecture of schizophrenia, but the link between polygenic risk scores and pathophysiological components of this disorder has been the subject of limited research. We investigated in healthy volunteers whether schizophrenia polygenic risk score predicts hippocampal activity during simple memory encoding, which has been proposed as a risk-associated intermediate phenotype of schizophrenia. We analysed the relationship between polygenic risk scores and hippocampal activity in a discovery sample of 191 unrelated healthy volunteers from the USA and in two independent replication samples of 76 and 137 healthy unrelated participants from Europe and the USA, respectively. Polygenic risk scores for each individual were calculated as the sum of the imputation probability of reference alleles weighted by the natural log of odds ratio from the recent schizophrenia genome-wide association study. We examined hippocampal activity during simple memory encoding of novel visual stimuli assessed using blood oxygen level-dependent functional MRI. Polygenic risk scores were significantly associated with hippocampal activity in the discovery sample [P = 0.016, family-wise error (FWE) corrected within Anatomical Automatic Labeling (AAL) bilateral hippocampal-parahippocampal mask] and in both replication samples (P = 0.033, FWE corrected within AAL right posterior hippocampal-parahippocampal mask in Bari sample, and P = 0.002 uncorrected in the Duke Neurogenetics Study sample). The relationship between polygenic risk scores and hippocampal activity was consistently negative, i.e. lower hippocampal activity in individuals with higher polygenic risk scores, consistent with previous studies reporting decreased hippocampal-parahippocampal activity during declarative memory tasks in patients with schizophrenia and in their healthy siblings. Polygenic risk scores accounted for more than 8% of variance in hippocampal activity during memory encoding in discovery sample. We conclude that polygenic risk scores derived from the most recent schizophrenia genome-wide association study predict significant variability in hippocampal activity during memory encoding in healthy participants. Our findings validate mnemonic hippocampal activity as a genetic risk associated intermediate phenotype of schizophrenia, indicating that the aggregate neurobiological effect of schizophrenia risk alleles converges on this pattern of neural activity.awy004media15749593779001.
| S-EPMC5888989 | biostudies-literature
Project description:Based on the discovery by the Resilience Project (Chen R. et al. Nat Biotechnol 34:531-538, 2016) of rare variants that confer resistance to Mendelian disease, and protective alleles for some complex diseases, we posited the existence of genetic variants that promote resilience to highly heritable polygenic disorders1,0 such as schizophrenia. Resilience has been traditionally viewed as a psychological construct, although our use of the term resilience refers to a different construct that directly relates to the Resilience Project, namely: heritable variation that promotes resistance to disease by reducing the penetrance of risk loci, wherein resilience and risk loci operate orthogonal to one another. In this study, we established a procedure to identify unaffected individuals with relatively high polygenic risk for schizophrenia, and contrasted them with risk-matched schizophrenia cases to generate the first known "polygenic resilience score" that represents the additive contributions to SZ resistance by variants that are distinct from risk loci. The resilience score was derived from data compiled by the Psychiatric Genomics Consortium, and replicated in three independent samples. This work establishes a generalizable framework for finding resilience variants for any complex, heritable disorder.
| S-EPMC7058518 | biostudies-literature
Project description:Evidence suggests that there is shared genetic aetiology across the major psychiatric disorders conferred by additive effects of many common variants. Measuring their joint effects on brain function may identify common neural risk mechanisms. We investigated the effects of a cross-disorder polygenic risk score (PGRS), based on additive effects of genetic susceptibility to the five major psychiatric disorders, on brain activation during performance of a language-based executive task. We examined this relationship in healthy individuals with (n=82) and without (n=57) a family history of bipolar disorder to determine whether this effect was additive or interactive dependent on the presence of family history. We demonstrate a significant interaction for polygenic loading×group in left lateral frontal cortex (BA9, BA6). Further examination indicated that this was driven by a significant positive correlation in those without a family history (i.e. healthy unrelated volunteers), with no significant relationships in the familial group. We then examined the effect of the individual diagnoses contributing to the PGRS to determine evidence of disorder-specificity. We found a significant association with the schizophrenia polygenic score only, with no other significant relationships. These findings indicate differences in left lateral frontal brain activation in association with increased cross-disorder PGRS in individuals without a family history of psychiatric illness. Lack of effects in the familial group may reflect epistatic effects, shared environmental influences or effects not captured by the PGRS. The specific relationship with loading for schizophrenia is notably consistent with frontal cortical inefficiency as a circumscribed phenotype of psychotic disorders.
| S-EPMC4396692 | biostudies-literature
Project description:Objective: To investigate the effects of microRNA-137 (MIR137) polymorphisms (rs1198588 and rs2660304) on the risk of schizophrenia in a Han Chinese population. Methods: Schizophrenia was diagnosed according to the DSM-5. Clinical symptoms and cognitive functions were assessed with the Positive and Negative Symptom Scale (PANSS) and Brief Assessment of Cognition in Schizophrenia (BACS), respectively. The polymorphisms were genotyped by improved multiplex ligation detection reaction (iMLDR) technology in 1,116 patients with schizophrenia and 1,039 healthy controls. Results: Significant associations were found between schizophrenia and MIR137 in the distributions of genotypes (p = 0.037 for rs1198588; p = 0.037 for rs2660304, FDR corrected) and alleles (p = 0.043 for rs1198588; p = 0.043 for rs2660304, FDR corrected) of two SNPs. When the population was stratified by sex, we found female-specific associations between MIR137 and schizophrenia in terms of genotype and allele distributions of rs1198588 (? 2 = 4.41, p = 0.036 and ? 2 = 4.86, p = 0.029, respectively, FDR corrected) and rs2660304 (? 2 = 4.74, p=0.036 and ? 2 = 4.80, p = 0.029, respectively, FDR corrected). Analysis of the MIR137 haplotype rs1198588-rs2660304 showed a significant association with schizophrenia in haplotype T-T [? 2 = 4.60, p = 0.032, OR = 1.32, 95% CI (1.02-1.70)]. Then, significant female-specific associations were found with the haplotypes T-T and G-A [? 2 = 4.92, p = 0.027, OR = 1.62, 95% CI (1.05-2.50); ? 2 = 4.42, p = 0.035, OR = 0.62, 95% CI (0.39-0.97), respectively]. When the TT genotype of rs1198588 was compared to the GT+GG genotype, a clinical characteristics analysis also showed a female-specific association in category instances (t = 2.76, p = 0.042, FDR corrected). Conclusion: The polymorphisms within the MIR137 gene are associated with susceptibility to schizophrenia, and a female-specific association of MIR137 with schizophrenia was reported in a Han Chinese population.
| S-EPMC7942225 | biostudies-literature
Project description:Genome-wide association studies (GWAS) have strongly implicated MIR137 (the gene encoding the microRNA miR-137) in schizophrenia. A parsimonious hypothesis is that a pathway regulated by miR-137 is important in the etiology of schizophrenia. Full evaluation of this hypothesis requires more definitive knowledge about biological targets of miR-137, which is currently lacking. Our goals were to expand knowledge of the biology of miR-137 by identifying its empirical targets, and to test whether the resulting lists of direct and indirect targets were enriched for genes and pathways involved in risk for schizophrenia. We overexpressed miR-137 in a human neural stem cell line and analyzed gene expression changes at 24 and 48?h using RNA sequencing. Following miR-137 overexpression, 202 and 428 genes were differentially expressed after 24 and 48?h. Genes differentially expressed at 24?h were enriched for transcription factors and cell cycle genes, and differential expression at 48?h affected a wider variety of pathways. Pathways implicated in schizophrenia were upregulated in the 48?h findings (major histocompatibility complex, synapses, FMRP interacting RNAs and calcium channels). Critically, differentially expressed genes at 48?h were enriched for smaller association P-values in the largest published schizophrenia GWAS. This work provides empirical support for a role of miR-137 in the etiology of schizophrenia.
| S-EPMC4080323 | biostudies-literature
Project description:Development of schizophrenia relates to both genetic and environmental factors. Functional deficits in many cognitive domains, including the ability to communicate in social interactions and impaired recognition of facial expressions, are common for patients with schizophrenia and might also be present in individuals at risk of developing schizophrenia. Here we explore whether an individual's polygenic risk score (PRS) for schizophrenia is associated with the degree of interregional similarities in blood oxygen level-dependent (BOLD) signal and gray matter volume of the face-processing network and whether the exposure to early adversity moderates this association. A total of 90 individuals (mean age 22 years, both functional and structural data available) were used for discovery analyses, and 211 individuals (mean age 26 years, structural data available) were used for replication of the structural findings. Both samples were drawn from the Northern Finland Birth Cohort 1986. We found that the degree of interregional similarities in BOLD signal and gray matter volume vary as a function of PRS; lowest interregional correlation (both measures) was observed in individuals with high PRS. We also replicated the gray matter volume finding. We did not find evidence for an interaction between early adversity and PRS on the interregional correlation of BOLD signal and gray matter volume. We speculate that the observed group differences in PRS-related correlations in both modalities may result from differences in the concurrent functional engagement of the face-processing regions over time, eg, via differences in exposure to social interaction with other people.
| S-EPMC6581147 | biostudies-literature