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Schizophrenia Bulletin Sep 2022Schizophrenia has been robustly associated with multiple genetic and environmental risk factors. Childhood adversity is one of the most widely replicated environmental... (Meta-Analysis)
Meta-Analysis
BACKGROUND AND HYPOTHESIS
Schizophrenia has been robustly associated with multiple genetic and environmental risk factors. Childhood adversity is one of the most widely replicated environmental risk factors for schizophrenia, but it is unclear if schizophrenia genetic risk alleles contribute to this association.
STUDY DESIGN
In this systematic review and meta-analysis, we assessed the evidence for gene-environment correlation (genes influence likelihood of environmental exposure) between schizophrenia polygenic risk score (PRS) and reported childhood adversity. We also assessed the evidence for a gene-environment interaction (genes influence sensitivity to environmental exposure) in relation to the outcome of schizophrenia and/or psychosis. This study was registered on PROSPERO (CRD42020182812). Following PRISMA guidelines, a search for relevant literature was conducted using Cochrane, MEDLINE, PsycINFO, Web of Science, and Scopus databases until February 2022. All studies that examined the association between schizophrenia PRS and childhood adversity were included.
STUDY RESULTS
Seventeen of 650 identified studies met the inclusion criteria and were assessed against the Newcastle-Ottawa Scale for quality. The meta-analysis found evidence for gene-environment correlation between schizophrenia PRS and childhood adversity (r = .02; 95% CI = 0.01, 0.03; P = .001), but the effect was small and therefore likely to explain only a small proportion of the association between childhood adversity and psychosis. The 4 studies that investigated a gene-environment interaction between schizophrenia PRS and childhood adversity in increasing risk of psychosis reported inconsistent results.
CONCLUSIONS
These findings suggest that a gene-environment correlation could explain a small proportion of the relationship between reported childhood adversity and psychosis.
Topics: Adverse Childhood Experiences; Child; Gene-Environment Interaction; Humans; Multifactorial Inheritance; Risk; Schizophrenia
PubMed: 35674151
DOI: 10.1093/schbul/sbac049 -
International Journal of Molecular... Mar 2020Recent studies have led to considerable advances in the identification of genetic variants associated with type 1 and type 2 diabetes. An approach for converting genetic...
Recent studies have led to considerable advances in the identification of genetic variants associated with type 1 and type 2 diabetes. An approach for converting genetic data into a predictive measure of disease susceptibility is to add the risk effects of loci into a polygenic risk score. In order to summarize the recent findings, we conducted a systematic review of studies comparing the accuracy of polygenic risk scores developed during the last two decades. We selected 15 risk scores from three databases (Scopus, Web of Science and PubMed) enrolled in this systematic review. We identified three polygenic risk scores that discriminate between type 1 diabetes patients and healthy people, one that discriminate between type 1 and type 2 diabetes, two that discriminate between type 1 and monogenic diabetes and nine polygenic risk scores that discriminate between type 2 diabetes patients and healthy people. Prediction accuracy of polygenic risk scores was assessed by comparing the area under the curve. The actual benefits, potential obstacles and possible solutions for the implementation of polygenic risk scores in clinical practice were also discussed. Develop strategies to establish the clinical validity of polygenic risk scores by creating a framework for the interpretation of findings and their translation into actual evidence, are the way to demonstrate their utility in medical practice.
Topics: Diabetes Mellitus, Type 1; Diabetes Mellitus, Type 2; Genetic Predisposition to Disease; Humans; Multifactorial Inheritance
PubMed: 32131491
DOI: 10.3390/ijms21051703 -
Behavior Genetics Jul 2019Studies testing the effect of single genetic variants on substance use have had modest success. This paper reviewed 39 studies using polygenic measures to test...
Studies testing the effect of single genetic variants on substance use have had modest success. This paper reviewed 39 studies using polygenic measures to test interaction with any type of environmental exposure (G×E) in alcohol, tobacco, and cannabis use. Studies using haplotype combinations, sum scores of candidate-gene risk alleles, and polygenic scores (PS) were included. Overall study quality was moderate, with lower ratings for the polygenic methods in the haplotype and candidate-gene score studies. Heterogeneity in investigated environmental exposures, genetic factors, and outcomes was substantial. Most studies (N = 30) reported at least one significant G×E interaction, but overall evidence was weak. The majority (N = 26) found results in line with differential susceptibility and diathesis-stress frameworks. Future studies should pay more attention to methodological and statistical rigor, and focus on replication efforts. Additional work is needed before firm conclusions can be drawn about the importance of G×E in the etiology of substance use.
Topics: Alcohol Drinking; Alleles; Cannabis; Ethanol; Gene Frequency; Gene-Environment Interaction; Genetic Predisposition to Disease; Haplotypes; Humans; Marijuana Use; Multifactorial Inheritance; Risk Factors; Nicotiana; Tobacco Use
PubMed: 31111357
DOI: 10.1007/s10519-019-09958-7 -
Journal of Affective Disorders Jul 2018Identifying the phenotypic manifestations of increased genetic liability for depression (MDD) and bipolar disorder (BD) can enhance understanding of their aetiology. The... (Review)
Review
BACKGROUND
Identifying the phenotypic manifestations of increased genetic liability for depression (MDD) and bipolar disorder (BD) can enhance understanding of their aetiology. The polygenic risk score (PRS) derived using data from genome-wide-association-studies can be used to explore how genetic risk is manifest in different samples.
AIMS
In this systematic review, we review studies that examine associations between the MDD and BD polygenic risk scores and phenotypic outcomes.
METHODS
Following PRISMA guidelines, we searched EMBASE, Medline and PsycINFO (from August 2009 - 14th March 2016) and references of included studies. Study inclusion was based on predetermined criteria and data were extracted independently and in duplicate.
RESULTS
Twenty-five studies were included. Overall, both polygenic risk scores were associated with other psychiatric disorders (not the discovery sample disorder) such as depression, schizophrenia and bipolar disorder, greater symptom severity of depression, membership of a creative profession and greater educational attainment. Both depression and bipolar polygenic risk scores explained small amounts of variance in most phenotypes (< 2%).
LIMITATIONS
Many studies did not report standardised effect sizes. This prevented us from conducting a meta-analysis.
CONCLUSIONS
Polygenic risk scores for BD and MDD are associated with a range of phenotypes and outcomes. However, they only explain a small amount of the variation in these phenotypes. Larger discovery and adequately powered target samples are required to increase power of the PRS approach. This could elucidate how genetic risk for bipolar disorder and depression is manifest and contribute meaningfully to stratified medicine.
Topics: Bipolar Disorder; Depression; Depressive Disorder, Major; Humans; Multifactorial Inheritance; Phenotype; Risk Factors; Schizophrenia
PubMed: 29529547
DOI: 10.1016/j.jad.2018.02.005 -
Genetics in Medicine : Official Journal... Jun 2022Recently, preimplantation genetic testing (PGT) for polygenic conditions (PGT-P) has been introduced commercially. In view of the lack of specific guidance on this... (Review)
Review
PURPOSE
Recently, preimplantation genetic testing (PGT) for polygenic conditions (PGT-P) has been introduced commercially. In view of the lack of specific guidance on this development, we analyzed normative documents on PGT for monogenic conditions (PGT-M) to understand what we can learn from these documents for recommendations for PGT-P.
METHODS
We conducted a systematic review of normative guidelines and recommendations on PGT-M. The aim was to understand what the current consensus and disagreements are on ethical acceptability of PGT-M and how this compares with PGT-P.
RESULTS
We analyzed 38 documents by advisory committees at the national, European, and global level. In total, 2 themes were identified, which included the following: (1) what PGT is considered appropriate for and (2) who can make decisions regarding the use of PGT. Many aspects of PGT-M documents apply to PGT-P as well. Additional factors such as the fact that PGT-P screens for risk indications of multiple polygenic conditions increase ethical difficulties regarding severity, risk, autonomy, and informed decision-making.
CONCLUSION
On the basis of PGT-M normative documents, we conclude that ethical acceptability for PGT-P is limited. Our findings present various factors that have to be considered for the development of guidelines and the appropriateness of PGT.
Topics: Aneuploidy; Female; Genetic Testing; Humans; Morals; Multifactorial Inheritance; Pregnancy; Preimplantation Diagnosis
PubMed: 35341652
DOI: 10.1016/j.gim.2022.03.001 -
Molecular Psychiatry Mar 2022Schizophrenia is a severe, complex mental disorder characterized by a combination of positive symptoms, negative symptoms, and impaired cognitive function. Schizophrenia...
Schizophrenia is a severe, complex mental disorder characterized by a combination of positive symptoms, negative symptoms, and impaired cognitive function. Schizophrenia is highly heritable (~80%) with multifactorial etiology and complex polygenic genetic architecture. Despite the large number of genetic variants associated with schizophrenia, few causal variants have been established. Gaining insight into the mechanistic influences of these genetic variants may facilitate our ability to apply these findings to prevention and treatment. Though there have been more than 300 studies of gene expression in schizophrenia over the past 15 years, none of the studies have yielded consistent evidence for specific genes that contribute to schizophrenia risk. The aim of this work is to conduct a systematic review and synthesis of case-control studies of genome-wide gene expression in schizophrenia. Comprehensive literature searches were completed in PubMed, EmBase, and Web of Science, and after a systematic review of the studies, data were extracted from those that met the following inclusion criteria: human case-control studies comparing the genome-wide transcriptome of individuals diagnosed with schizophrenia to healthy controls published between January 1, 2000 and June 30, 2020 in the English language. Genes differentially expressed in cases were extracted from these studies, and overlapping genes were compared to previous research findings from the genome-wide association, structural variation, and tissue-expression studies. The transcriptome-wide analysis identified different genes than those previously reported in genome-wide association, exome sequencing, and structural variation studies of schizophrenia. Only one gene, GBP2, was replicated in five studies. Previous work has shown that this gene may play a role in immune function in the etiology of schizophrenia, which in turn could have implications for risk profiling, prevention, and treatment. This review highlights the methodological inconsistencies that impede valid meta-analyses and synthesis across studies. Standardization of the use of covariates, gene nomenclature, and methods for reporting results could enhance our understanding of the potential mechanisms through which genes exert their influence on the etiology of schizophrenia. Although these results are promising, collaborative efforts with harmonization of methodology will facilitate the identification of the role of genes underlying schizophrenia.
Topics: Case-Control Studies; Genetic Predisposition to Disease; Genome-Wide Association Study; Humans; Multifactorial Inheritance; Schizophrenia; Exome Sequencing
PubMed: 35091668
DOI: 10.1038/s41380-021-01420-7 -
Comprehensive Psychiatry Jan 2019Genome wide association studies (GWAS) of schizophrenia allow the generation of Polygenic Risk Scores (PRS). PRS can be used to determine the contribution to altered...
BACKGROUND
Genome wide association studies (GWAS) of schizophrenia allow the generation of Polygenic Risk Scores (PRS). PRS can be used to determine the contribution to altered brain structures in this disorder, which have been well described. However, findings from studies using PRS to predict brain structural changes in schizophrenia have been inconsistent. We therefore performed a systematic review to determine the association between schizophrenia PRS and brain structure.
METHODS
Following PRISMA systematic review guidelines, databases were searched for literature using key search terms. Inclusion criteria for the discovery sample required case-control schizophrenia GWAS summary statistics from European populations. The target sample was required to be of European ancestry, and have brain structure and genotype information. Quality assessment of the publications was conducted using the Mixed Methods Appraisal Tool for quantitative non-randomised studies.
MAIN FINDINGS
A total of seven studies were found to be eligible for review. Five studies found no significant association and two studies found a significant association of schizophrenia PRS with total brain, reduced white matter volume, and globus pallidus volume. However, the latter studies were conducted using smaller discovery (n = 9394 n = 12,462) and target samples compared to the studies with substantially larger discovery (n = 33,636 n = 43,008) and target samples where no association was observed. Taken together, the results suggest that schizophrenia PRS are not significantly associated with brain structural changes in this disorder.
CONCLUSIONS
The lack of significant association between schizophrenia PRS and brain structural changes may indicate that intermediate phenotypes other than brain structure should be the focus of future work. Alternatively, however, the lack of association found here may point to limitations of the current evidence-base, and so point to the need for future better powered studies.
Topics: Brain; Case-Control Studies; Female; Genetic Predisposition to Disease; Genome-Wide Association Study; Genotype; Humans; Male; Multifactorial Inheritance; Phenotype; Risk Factors; Schizophrenia
PubMed: 30529765
DOI: 10.1016/j.comppsych.2018.11.014 -
NeuroImage. Clinical 2020Diffusion magnetic resonance imaging (dMRI) is an imaging technique which probes the random motion of water molecules in tissues and has been widely applied to... (Review)
Review
Diffusion magnetic resonance imaging (dMRI) is an imaging technique which probes the random motion of water molecules in tissues and has been widely applied to investigate changes in white matter microstructure in Alzheimer's Disease. This paper aims to systematically review studies that examined the effect of Alzheimer's risk genes on white matter microstructure. We assimilated findings from 37 studies and reviewed their diffusion pre-processing and analysis methods. Most studies estimate the diffusion tensor (DT) and compare derived quantitative measures such as fractional anisotropy and mean diffusivity between groups. Those with increased AD genetic risk are associated with reduced anisotropy and increased diffusivity across the brain, most notably the temporal and frontal lobes, cingulum and corpus callosum. Structural abnormalities are most evident amongst those with established Alzheimer's Disease. Recent studies employ signal representations and analysis frameworks beyond DT MRI but show that dMRI overall lacks specificity to disease pathology. However, as the field advances, these techniques may prove useful in pre-symptomatic diagnosis or staging of Alzheimer's disease.
Topics: Alzheimer Disease; Anisotropy; Brain; Diffusion Magnetic Resonance Imaging; Diffusion Tensor Imaging; Humans; White Matter
PubMed: 32758801
DOI: 10.1016/j.nicl.2020.102359 -
Genetics in Medicine : Official Journal... Sep 2022Single-nucleotide variations (SNVs) (formerly single-nucleotide polymorphism [SNV]) influence genetic predisposition to endometrial cancer. We hypothesized that a...
PURPOSE
Single-nucleotide variations (SNVs) (formerly single-nucleotide polymorphism [SNV]) influence genetic predisposition to endometrial cancer. We hypothesized that a polygenic risk score (PRS) comprising multiple SNVs may improve endometrial cancer risk prediction for targeted screening and prevention.
METHODS
We developed PRSs from SNVs identified from a systematic review of published studies and suggestive SNVs from the Endometrial Cancer Association Consortium. These were tested in an independent study of 555 surgically-confirmed endometrial cancer cases and 1202 geographically-matched controls from Manchester, United Kingdom and validated in 1676 cases and 116,960 controls from the UK Biobank (UKBB).
RESULTS
Age and body mass index predicted endometrial cancer in both data sets (Manchester: area under the receiver operator curve [AUC] = 0.77, 95% CI = 0.74-0.80; UKBB: AUC = 0.74, 95% CI = 0.73-0.75). The AUC for PRS19, PRS24, and PRS72 were 0.58, 0.55, and 0.57 in the Manchester study and 0.56, 0.54, and 0.54 in UKBB, respectively. For PRS19, women in the third tertile had a 2.1-fold increased risk of endometrial cancer compared with those in the first tertile of the Manchester study (odds ratio = 2.08, 95% CI = 1.61-2.68, P = 5.75E-9). Combining PRS19 with age and body mass index improved discriminatory power (Manchester study: AUC = 0.79, 95% CI = 0.76-0.82; UKBB: AUC =0.75, 95% CI = 0.73-0.76).
CONCLUSION
An endometrial cancer risk prediction model incorporating a PRS derived from multiple SNVs may help stratify women for screening and prevention strategies.
Topics: Female; Humans; Endometrial Neoplasms; Genetic Predisposition to Disease; Genome-Wide Association Study; Multifactorial Inheritance; Polymorphism, Single Nucleotide; Risk Assessment; Risk Factors
PubMed: 35704044
DOI: 10.1016/j.gim.2022.05.014 -
Journal of Alzheimer's Disease : JAD 2020Late-onset Alzheimer's disease (AD) is highly heritable. The effect of many common genetic variants, single nucleotide polymorphisms (SNPs), confer risk. Variants are...
BACKGROUND
Late-onset Alzheimer's disease (AD) is highly heritable. The effect of many common genetic variants, single nucleotide polymorphisms (SNPs), confer risk. Variants are clustered in areas of biology, notably immunity and inflammation, cholesterol metabolism, endocytosis, and ubiquitination. Polygenic scores (PRS), which weight the sum of an individual's risk alleles, have been used to draw inferences about the pathological processes underpinning AD.
OBJECTIVE
This paper aims to systematically review how AD PRS are being used to study a range of outcomes and phenotypes related to neurodegeneration.
METHODS
We searched the literature from July 2008-July 2018 following PRISMA guidelines.
RESULTS
57 studies met criteria. The AD PRS can distinguish AD cases from controls. The ability of AD PRS to predict conversion from mild cognitive impairment (MCI) to AD was less clear. There was strong evidence of association between AD PRS and cognitive impairment. AD PRS were correlated with a number of biological phenotypes associated with AD pathology, such as neuroimaging changes and amyloid and tau measures. Pathway-specific polygenic scores were also associated with AD-related biologically relevant phenotypes.
CONCLUSION
PRS can predict AD effectively and are associated with cognitive impairment. There is also evidence of association between AD PRS and other phenotypes relevant to neurodegeneration. The associations between pathway specific polygenic scores and phenotypic changes may allow us to define the biology of the disease in individuals and indicate who may benefit from specific treatments. Longitudinal cohort studies are required to test the ability of PGS to delineate pathway-specific disease activity.
Topics: Alzheimer Disease; Genetic Predisposition to Disease; Genetic Testing; Humans; Multifactorial Inheritance; Precision Medicine
PubMed: 32250305
DOI: 10.3233/JAD-191233