Genome-wide Association Studies in Ancestrally Diverse Populations: Opportunities, Methods, Pitfalls, and Recommendations

Genome-wide association studies (GWASs) have focused primarily on populations of European descent, but it is essential that diverse populations become better represented. Increasing diversity among study participants will advance our understanding of genetic architecture in all populations and ensure that genetic research is broadly applicable. To facilitate and promote research in multi-ancestry and admixed cohorts, we outline key methodological considerations and highlight opportunities, challenges, solutions, and areas in need of development. Despite the perception that analyzing genetic data from diverse populations is difficult, it is scientifically and ethically imperative, and there is an expanding analytical toolbox to do it well

DNA methylation meta-analysis reveals cellular alterations in psychosis and markers of treatment-resistant schizophrenia

We performed a systematic analysis of blood DNA methylation profiles from 4,483 participants from seven independent cohorts identifying differentially methylated positions (DMPs) associated with psychosis, schizophrenia and treatment-resistant schizophrenia. Psychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNA methylation data, with the largest differences seen in treatment-resistant schizophrenia patients. We implemented a stringent pipeline to meta-analyze epigenome-wide association study (EWAS) results across datasets, identifying 95 DMPs associated with psychosis and 1,048 DMPs associated with schizophrenia, with evidence of colocalization to regions nominated by genetic association studies of disease. Many schizophrenia-associated DNA methylation differences were only present in patients with treatment-resistant schizophrenia, potentially reflecting exposure to the atypical antipsychotic clozapine. Our results highlight how DNA methylation data can be leveraged to identify physiological (e.g., differential cell counts) and environmental (e.g., smoking) factors associated with psychosis and molecular biomarkers of treatment-resistant schizophrenia

Development of multivariable models to predict change in Body Mass Index within a clinical trial population of psychotic individuals

Many antipsychotics promote weight gain, which can lead to non-compliance and relapse of psychosis. By developing models that accurately identify individuals at greater risk of weight gain, clinicians can make informed treatment decisions and target intervention measures. We examined clinical, genetic and expression data for 284 individuals with psychosis derived from a previously published randomised controlled trial (IMPACT). These data were used to develop regression and classification models predicting change in Body Mass Index (BMI) over one year. Clinical predictors included demographics, anthropometrics, cardiac and blood measures, diet and exercise, physical and mental health, medication and BMI outcome measures. We included genetic polygenic risk scores (PRS) for schizophrenia, bipolar disorder, BMI, waist-hip-ratio, insulin resistance and height, as well as gene co-expression modules generated by Weighted Gene Co-expression Network Analysis (WGCNA). The best performing predictive models for BMI and BMI gain after one year used clinical data only, which suggests expression and genetic data do not improve prediction in this cohort

Systematic meta-analyses and field synopsis of genetic association studies of violence and aggression

A large number of candidate gene studies for aggression and violence have been conducted. Successful identification of associations between genetic markers and aggression would contribute to understanding the neurobiology of antisocial behavior and potentially provide useful tools for risk prediction and therapeutic targets for high-risk groups of patients and offenders. We systematically reviewed the literature and assessed the evidence on genetic association studies of aggression and related outcomes in order to provide a field synopsis. We searched PubMed and Huge Navigator databases and sought additional data through reviewing reference lists and correspondence with investigators. Genetic association studies were included if outcome data on aggression or violent behavior either as a binary outcome or as a quantitative trait were provided. From 1331 potentially relevant investigations, 185 studies constituting 277 independent associations on 31 genes fulfilled the predetermined selection criteria. Data from variants investigated in three or more samples were combined in meta-analyses and potential sources of heterogeneity were investigated using subgroup analyses. In the primary analyses, which used relaxed inclusion criteria, we found no association between any polymorphism analyzed and aggression at the 5% level of significance. Subgroup analyses, including by severity of outcome, age group, characteristics of the sample and ethnicity, did not demonstrate any consistent findings. Current evidence does not support the use of such genes to predict dangerousness or as markers for therapeutic interventions

Evidence for PTGER4, PSCA, and MBOAT7 as risk genes for gastric cancer on the genome and transcriptome level

Genetic associations between variants on chromosome 5p13 and 8q24 and gastric cancer (GC) have been previously reported in the Asian population. We aimed to replicate these findings and to characterize the associations at the genome and transcriptome level. We performed a fine-mapping association study in 1926 GC patients and 2012 controls of European descent using high dense SNP marker sets on both chromosomal regions. Next, we performed expression quantitative trait locus (eQTL) analyses using gastric transcriptome data from 143 individuals focusing on the GC associated variants. On chromosome 5p13 the strongest association was observed at rs6872282 (P = 2.53 × 10-04) and on chromosome 8q24 at rs2585176 (P = 1.09 × 10-09). On chromosome 5p13 we found cis-eQTL effects with an upregulation of PTGER4 expression in GC risk allele carrier (P = 9.27 × 10-11). On chromosome 8q24 we observed cis-eQTL effects with an upregulation of PSCA expression in GC risk allele carrier (P = 2.17 × 10-47). In addition, we found trans-eQTL effects for the same variants on 8q24 with a downregulation of MBOAT7 expression in GC risk allele carrier (P = 3.11 × 10-09). In summary, we confirmed and refined the previously reported GC associations at both chromosomal regions. Our data point to shared etiological factors between Asians and Europeans. Furthermore, our data imply an upregulated expression of PTGER4 and PSCA as well as a downregulated expression of MBOAT7 in gastric tissue as risk-conferring GC pathomechanisms

High frequency of known copy number abnormalities and maternal duplication 15q11-q13 in patients with combined schizophrenia and epilepsy

<p>Abstract</p> <p>Background</p> <p>Many copy number variants (CNVs) are documented to be associated with neuropsychiatric disorders, including intellectual disability, autism, epilepsy, schizophrenia, and bipolar disorder. Chromosomal deletions of 1q21.1, 3q29, 15q13.3, 22q11.2, and <it>NRXN1 </it>and duplications of 15q11-q13 (maternal), 16p11, and 16p13.3 have the strongest association with schizophrenia. We hypothesized that cases with both schizophrenia and epilepsy would have a higher frequency of disease-associated CNVs and would represent an enriched sample for detection of other mutations associated with schizophrenia.</p> <p>Methods</p> <p>We used array comparative genomic hybridization (CGH) to analyze 235 individuals with both schizophrenia and epilepsy, 80 with bipolar disorder and epilepsy, and 191 controls.</p> <p>Results</p> <p>We detected 10 schizophrenia plus epilepsy cases in 235 (4.3%) with the above mentioned CNVs compared to 0 in 191 controls (p = 0.003). Other likely pathological findings in schizophrenia plus epilepsy cases included 1 deletion 16p13 and 1 duplication 7q11.23 for a total of 12/235 (5.1%) while a possibly pathogenic duplication of 22q11.2 was found in one control for a total of 1 in 191 (0.5%) controls (p = 0.008). The rate of abnormality in the schizophrenia plus epilepsy of 10/235 for the more definite CNVs compares to a rate of 75/7336 for these same CNVs in a series of unselected schizophrenia cases (p = 0.0004).</p> <p>Conclusion</p> <p>We found a statistically significant increase in the frequency of CNVs known or likely to be associated with schizophrenia in individuals with both schizophrenia and epilepsy compared to controls. We found an overall 5.1% detection rate of likely pathological findings which is the highest frequency of such findings in a series of schizophrenia patients to date. This evidence suggests that the frequency of disease-associated CNVs in patients with both schizophrenia and epilepsy is significantly higher than for unselected schizophrenia.</p

Identification of a Bipolar Disorder Vulnerable Gene CHDH at 3p21.1

Genome-wide analysis (GWA) is an effective strategy to discover extreme effects surpassing genome-wide significant levels in studying complex disorders; however, when sample size is limited, the true effects may fail to achieve genome-wide significance. In such case, there may be authentic results among the pools of nominal candidates, and an alternative approach is to consider nominal candidates but are replicable across different samples. Here, we found that mRNA expression of the choline dehydrogenase gene (CHDH) was uniformly upregulated in the brains of bipolar disorder (BPD) patients compared with healthy controls across different studies. Follow-up genetic analyses of CHDH variants in multiple independent clinical datasets (including 11,564 cases and 17,686 controls) identified a risk SNP rs9836592 showing consistent associations with BPD (P meta = 5.72 × 10(-4)), and the risk allele indicated an increased CHDH expression in multiple neuronal tissues (lowest P = 6.70 × 10(-16)). These converging results may identify a nominal but true BPD susceptibility gene CHDH. Further exploratory analysis revealed suggestive associations of rs9836592 with childhood intelligence (P = 0.044) and educational attainment (P = 0.0039), a 'proxy phenotype' of general cognitive abilities. Intriguingly, the CHDH gene is located at chromosome 3p21.1, a risk region implicated in previous BPD genome-wide association studies (GWAS), but CHDH is lying outside of the core GWAS linkage disequilibrium (LD) region, and our studied SNP rs9836592 is ∼1.2 Mb 3' downstream of the previous GWAS loci (e.g., rs2251219) with no LD between them; thus, the association observed here is unlikely a reflection of previous GWAS signals. In summary, our results imply that CHDH may play a previously unknown role in the etiology of BPD and also highlight the informative value of integrating gene expression and genetic code in advancing our understanding of its biological basis

Genetic copy number variants, cognition and psychosis: a meta-analysis and a family study

Article Open Access Published: 27 July 2020 Genetic copy number variants, cognition and psychosis: a meta-analysis and a family study Johan H. Thygesen, Amelia Presman, […]Elvira Bramon Molecular Psychiatry (2020)Cite this article 561 Accesses 10 Altmetric Metricsdetails Abstract The burden of large and rare copy number genetic variants (CNVs) as well as certain specific CNVs increase the risk of developing schizophrenia. Several cognitive measures are purported schizophrenia endophenotypes and may represent an intermediate point between genetics and the illness. This paper investigates the influence of CNVs on cognition. We conducted a systematic review and meta-analysis of the literature exploring the effect of CNV burden on general intelligence. We included ten primary studies with a total of 18,847 participants and found no evidence of association. In a new psychosis family study, we investigated the effects of CNVs on specific cognitive abilities. We examined the burden of large and rare CNVs (>200 kb, <1% MAF) as well as known schizophrenia-associated CNVs in patients with psychotic disorders, their unaffected relatives and controls (N = 3428) from the Psychosis Endophenotypes International Consortium (PEIC). The carriers of specific schizophrenia-associated CNVs showed poorer performance than non-carriers in immediate (P = 0.0036) and delayed (P = 0.0115) verbal recall. We found suggestive evidence that carriers of schizophrenia-associated CNVs had poorer block design performance (P = 0.0307). We do not find any association between CNV burden and cognition. Our findings show that the known high-risk CNVs are not only associated with schizophrenia and other neurodevelopmental disorders, but are also a contributing factor to impairment in cognitive domains such as memory and perceptual reasoning, and act as intermediate biomarkers of disease risk