Polygenic Risk Score Analysis Research Articles

Associations between polygenic risk score and covid-19 susceptibility and severity across ethnic groups: UK Biobank analysis

BackgroundCOVID-19 manifests with huge heterogeneity in susceptibility and severity outcomes. UK Black Asian and Minority Ethnic (BAME) groups have demonstrated disproportionate burdens. Some variability remains unexplained, suggesting potential genetic contribution. Polygenic Risk Scores (PRS) can determine genetic predisposition to disease based on Single Nucleotide Polymorphisms (SNPs) within the genome. COVID-19 PRS analyses within non-European samples are extremely limited. We applied a multi-ethnic PRS to a UK-based cohort to understand genetic contribution to COVID-19 variability.MethodsWe constructed two PRS for susceptibility and severity outcomes based on leading risk-variants from the COVID-19 Host Genetics Initiative. Scores were applied to 447,382 participants from the UK-Biobank. Associations with COVID-19 outcomes were assessed using binary logistic regression and discriminative power was validated using incremental area under receiver operating curve (ΔAUC). Variance explained was compared between ethnic groups via incremental pseudo-R2 (ΔR2).ResultsCompared to those at low genetic risk, those at high risk had a significantly greater risk of severe COVID-19 for White (odds ratio [OR] 1.57, 95% confidence interval [CI] 1.42–1.74), Asian (OR 2.88, 95% CI 1.63–5.09) and Black (OR 1.98, 95% CI 1.11–3.53) ethnic groups. Severity PRS performed best within Asian (ΔAUC 0.9%, ΔR2 0.98%) and Black (ΔAUC 0.6%, ΔR2 0.61%) cohorts. For susceptibility, higher genetic risk was significantly associated with COVID-19 infection risk for the White cohort (OR 1.31, 95% CI 1.26–1.36), but not for Black or Asian groups.ConclusionsSignificant associations between PRS and COVID-19 outcomes were elicited, establishing a genetic basis for variability in COVID-19. PRS showed utility in identifying high-risk individuals. The multi-ethnic approach allowed applicability of PRS to diverse populations, with the severity model performing well within Black and Asian cohorts. Further studies with larger sample sizes of non-White samples are required to increase statistical power and better assess impacts within BAME populations.

1403-P: Agent Orange Exposure and Type 2 Diabetes in Korean Veterans—An Epigenetic Association Study

Objective: There has been contradictory evidence about the relationship between Agent Orange (AO) exposure and type 2 diabetes. By combining DNA methylation and DNA genotyping analysis, we intended to determine if AO exposure is related with the development of type 2 diabetes and to confirm the causal association between AO exposure and type 2 diabetes. Research Designs and Methods: An epigenome-wide association analysis and DNA genotyping analyses were done on the blood of AO-exposed and AO-unexposed type 2 diabetes patients and healthy controls. To assess the causal influence of AO-exposure-identified CpGs on type 2 diabetes, methylation quantitative trait locus (meQTL) and Mendelian randomization (MR) studies were used. The risk of type 2 diabetes was compared between subgroups using polygenic risk score (PRS). Results: Hypermethylated CpG sites (cg20075319, cg21757266, cg05203217, cg20102280, cg26081717, and cg21878650) and one hypomethylated CpG site (cg07553761) were linked to type 2 diabetes in AO-exposed individuals. Methylation levels at some CpG sites (cg20075319, cg20102280, and cg2608171) were considerably different, according to meQTL analyses. CpG sites discovered in AO-exposed patients were causally linked to type 2 diabetes, according to MR analysis; The impact of the reverse causality was insignificant. A PRS analysis revealed no discernible difference in the risk of type 2 diabetes between AO-exposed and AO-unexposed groups. Conclusions: We validated a causal relationship between AO exposure and type 2 diabetes by identifying distinct epigenetic markers between AO-exposed and AO-unexposed patients with type 2 diabetes. These results highlight the need for more epigenetic research on the link between type 2 diabetes and AO exposure. Disclosure J.Seo: None. Y.Kim: None. Funding National Research Foundation of Korea (2022R1C1C1002929); Veterans Health Service Medical Center (VHSMC19033); National Institutes of Health; Centers for Disease Control and Prevention (2019-NG-053-02, 2022-NI-067-00)

Common genetic variants contribute to heritability of age at onset of schizophrenia

Schizophrenia (SCZ) is a complex disorder that typically arises in late adolescence or early adulthood. Age at onset (AAO) of SCZ is associated with long-term outcomes of the disease. We explored the genetic architecture of AAO with a genome-wide association study (GWAS), heritability, polygenic risk score (PRS), and copy number variant (CNV) analyses in 4 740 subjects of European ancestry. Although no genome-wide significant locus was identified, SNP-based heritability of AAO was estimated to be between 17 and 21%, indicating a moderate contribution of common variants. We also performed cross-trait PRS analyses with a set of mental disorders and identified a negative association between AAO and common variants for SCZ, childhood maltreatment and attention-deficit/hyperactivity disorder. We also investigated the role of copy number variants (CNVs) in AAO and found an association with the length and number of deletions (P-value = 0.03), whereas the presence of CNVs previously reported in SCZ was not associated with earlier onset. To our knowledge, this is the largest GWAS of AAO of SCZ to date in individuals from European ancestry, and the first study to determine the involvement of common variants in the heritability of AAO. Finally, we evidenced the role played by higher SCZ load in determining AAO but discarded the role of pathogenic CNVs. Altogether, these results shed light on the genetic architecture of AAO, which needs to be confirmed with larger studies.

Development and Replication of a Genome-Wide Polygenic Risk Score for Chronic Back Pain.

Chronic back pain (CBP) is a complex heritable trait and a major cause of disability worldwide. We developed and validated a genome-wide polygenic risk score (PRS) for CBP using a large-scale GWAS based on UK Biobank participants of European ancestry (N = 265,000). The PRS showed poor overall predictive ability (AUC = 0.56 and OR = 1.24 per SD, 95% CI: 1.22-1.26), but individuals from the 99th percentile of PRS distribution had a nearly two-fold increased risk of CBP (OR = 1.82, 95% CI: 1.60-2.06). We validated the PRS on an independent TwinsUK sample, obtaining a similar magnitude of effect. The PRS was significantly associated with various ICD-10 and OPCS-4 diagnostic codes, including chronic ischemic heart disease (OR = 1.1, p-value = 4.8 × 10-15), obesity, metabolism-related traits, spine disorders, disc degeneration, and arthritis-related disorders. PRS and environment interaction analysis with twelve known CBP risk factors revealed no significant results, suggesting that the magnitude of G × E interactions with studied factors is small. The limited predictive ability of the PRS that we developed is likely explained by the complexity, heterogeneity, and polygenicity of CBP, for which sample sizes of a few hundred thousand are insufficient to estimate small genetic effects robustly.

Psychiatric polygenic risk as a predictor of COVID-19 risk and severity: insight into the genetic overlap between schizophrenia and COVID-19

Despite the high contagion and mortality rates that have accompanied the coronavirus disease-19 (COVID-19) pandemic, the clinical presentation of the syndrome varies greatly from one individual to another. Potential host factors that accompany greater risk from COVID-19 have been sought and schizophrenia (SCZ) patients seem to present more severe COVID-19 than control counterparts, with certain gene expression similarities between psychiatric and COVID-19 patients reported. We used summary statistics from the last SCZ, bipolar disorder (BD), and depression (DEP) meta-analyses available on the Psychiatric Genomics Consortium webpage to calculate polygenic risk scores (PRSs) for a target sample of 11,977 COVID-19 cases and 5943 subjects with unknown COVID-19 status. Linkage disequilibrium score (LDSC) regression analysis was performed when positive associations were obtained from the PRS analysis. The SCZ PRS was a significant predictor in the case/control, symptomatic/asymptomatic, and hospitalization/no hospitalization analyses in the total and female samples; and of symptomatic/asymptomatic status in men. No significant associations were found for the BD or DEP PRS or in the LDSC regression analysis. SNP-based genetic risk for SCZ, but not for BD or DEP, may be associated with higher risk of SARS-CoV-2 infection and COVID-19 severity, especially among women; however, predictive accuracy barely exceeded chance level. We believe that the inclusion of sexual loci and rare variations in the analysis of genomic overlap between SCZ and COVID-19 will help to elucidate the genetic commonalities between these conditions.

Association of mitochondrial DNA variation with high myopia in a Han Chinese population

High myopia (HM), which is characterized by oxidative stress, is one of the leading causes of visual impairment and blindness across the world. Family and population genetic studies have uncovered nuclear-genome variants in proteins functioned in the mitochondria. However, whether mitochondrial DNA mutations are involved in HM remains unexplored. Here, we performed the first large-scale whole-mitochondrial genome study in 9613 HM cases and 9606 control subjects of Han Chinese ancestry for identifying HM-associated mitochondrial variants. The single-variant association analysis identified nine novel genetic variants associated with HM reaching the entire mitochondrial wide significance level, including rs370378529 in ND2 with an odds ratio (OR) of 5.25. Interestingly, eight out of nine variants were predominantly located in related sub-haplogroups, i.e. m.5261G > A in B4b1c, m.12280A > G in G2a4, m.7912G > A in D4a3b, m.94G > A in D4e1, m.14857 T > C in D4e3, m.14280A > G in D5a2, m.16272A > G in G2a4, m.8718A > G in M71 and F1a3, indicating that the sub-haplogroup background can increase the susceptible risk for high myopia. The polygenic risk score analysis of the target and validation cohorts indicated a high accuracy for predicting HM with mtDNA variants (AUC = 0.641). Cumulatively, our findings highlight the critical roles of mitochondrial variants in untangling the genetic etiology of HM.

A genome-wide association study of antidepressant-induced mania

Antidepressant-induced mania (AIM) is a side effect of antidepressant treatment that is characterized by mania or hypomania after the start of medication. It is likely polygenic, but its genetic component remains largely unexplored. We aim to conduct the first genome-wide association study of AIM in 814 bipolar disorder patients of European ancestry. We report no significant findings from our single-marker or gene-based analyses. Our polygenic risk score analyses also did not yield significant results with bipolar disorder, antidepressant response, or lithium response. Our suggestive findings on the hypothalamic-pituitary-adrenal axis and the opioid system in AIM require independent replications.

The relationship between cannabis use, schizophrenia, and bipolar disorder: a genetically informed study

The relationship between psychotic disorders and cannabis use is heavily debated. Shared underlying genetic risk is one potential explanation. We investigated the genetic association between psychotic disorders (schizophrenia and bipolar disorder) and cannabis phenotypes (lifetime cannabis use and cannabis use disorder). We used genome-wide association summary statistics from individuals with European ancestry from the Psychiatric Genomics Consortium, UK Biobank, and International Cannabis Consortium. We estimated heritability, polygenicity, and discoverability of each phenotype. We performed genome-wide and local genetic correlations. Shared loci were identified and mapped to genes, which were tested for functional enrichment. Shared genetic liabilities to psychotic disorders and cannabis phenotypes were explored using causal analyses and polygenic scores, using the Norwegian Thematically Organized Psychosis cohort. Psychotic disorders were more heritable than cannabis phenotypes and more polygenic than cannabis use disorder. We observed positive genome-wide genetic correlations between psychotic disorders and cannabis phenotypes (range 0·22-0·35) with a mixture of positive and negative local genetic correlations. Three to 27 shared loci were identified for the psychotic disorder and cannabis phenotype pairs. Enrichment of mapped genes implicated neuronal and olfactory cells as well as drug-gene targets for nicotine, alcohol, and duloxetine. Psychotic disorders showed a causal effect on cannabis phenotypes, and lifetime cannabis use had a causal effect on bipolar disorder. Of 2181 European participants from the Norwegian Thematically Organized Psychosis cohort applied in polygenic risk score analyses, 1060 (48·6%) were females and 1121 (51·4%) were males (mean age 33·1 years [SD 11·8]). 400 participants had bipolar disorder, 697 had schizophrenia, and 1044 were healthy controls. Within this sample, polygenic scores for cannabis phenotypes predicted psychotic disorders independently and improved prediction beyond the polygenic score for the psychotic disorders. A subgroup of individuals might have a high genetic risk of developing a psychotic disorder and using cannabis. This finding supports public health efforts to reduce cannabis use, particularly in individuals at high risk or patients with psychotic disorders. Identified shared loci and their functional implications could facilitate development of novel treatments. US National Institutes of Health, the Research Council Norway, the South-East Regional Health Authority, Stiftelsen Kristian Gerhard Jebsen, EEA-RO-NO-2018-0535, European Union's Horizon 2020 Research and Innovation Programme, the Marie Skłodowska-Curie Actions, and University of Oslo Life Science.

Adjusting for population stratification in polygenic risk score analyses: a guide for model specifications in the UK Biobank.

The current study was conducted to provide a general guidance for model specifications in polygenic risk score (PRS) analyses of the UK Biobank, such as adjusting for covariates (i.e. age, sex, recruitment centers, and genetic batch) and the number of principal components (PCs) that need to be included. To cover behavioral, physical and mental health outcomes, we evaluated three continuous outcomes (BMI, smoking, drinking) and two binary outcomes (Major Depressive Disorder and educational attainment). We applied 3280 (656 per phenotype) different models including different sets of covariates. We evaluated these different model specifications by comparing regression parameters such as R2, coefficients, and P values, as well as ANOVA tests. Findings suggest that only up to three PCs appears to be sufficient for controlling population stratification for most outcomes, whereas including other covariates (particularly age and sex) appears to be more essential for model performance.

Multiomics Analyses Reveal Microbiome-Gut-Brain Crosstalk Centered on Aberrant Gamma-Aminobutyric Acid and Tryptophan Metabolism in Drug-Naïve Patients with First-Episode Schizophrenia.

Schizophrenia (SCZ) is associated with complex crosstalk between the gut microbiota and host metabolism, but the underlying mechanism remains elusive. Investigating the aberrant neurotransmitter processes reflected by alterations identified using multiomics analysis is valuable to fully explain the pathogenesis of SCZ. We conducted an integrative analysis of multiomics data, including the serum metabolome, fecal metagenome, single nucleotide polymorphism data, and neuroimaging data obtained from a cohort of 127 drug-naïve, first-episode SCZ patients and 92 healthy controls to characterize the microbiome-gut-brain axis in SCZ patients. We used pathway-based polygenic risk score (PRS) analyses to determine the biological pathways contributing to genetic risk and mediation effect analyses to determine the important neuroimaging features. Additionally, a random forest model was generated for effective SCZ diagnosis. We found that the altered metabolome and dysregulated microbiome were associated with neuroactive metabolites, including gamma-aminobutyric acid (GABA), tryptophan, and short-chain fatty acids. Further structural and functional magnetic resonance imaging analyses highlighted that gray matter volume and functional connectivity disturbances mediate the relationships between Ruminococcus_torgues and Collinsella_aerofaciens and symptom severity and the relationships between species Lactobacillus_ruminis and differential metabolites l-2,4-diaminobutyric acid and N-acetylserotonin and cognitive function. Moreover, analyses of the Polygenic Risk Score (PRS) support that alterations in GABA and tryptophan neurotransmitter pathways are associated with SCZ risk, and GABA might be a more dominant contributor. This study provides new insights into systematic relationships among genes, metabolism, and the gut microbiota that affect brain functional connectivity, thereby affecting SCZ pathogenesis.

Polygenic risk scores analyses of psychiatric and metabolic traits with antipsychotic-induced weight gain in schizophrenia: an exploratory study.

Given the polygenic nature of antipsychotic-induced weight gain (AIWG), we investigated whether polygenic risk scores (PRS) for various psychiatric and metabolic traits were associated with AIWG. We included individuals with schizophrenia (SCZ) of European ancestry from two cohorts (N = 151, age = 40.3 ± 11.8 and N = 138, age = 36.5 ± 10.8). We investigated associations of AIWG defined as binary and continuous variables with PRS calculated from genome-wide association studies of body mass index (BMI), coronary artery disease (CAD), fasting glucose, fasting insulin, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol (LDL-C), triglycerides, type 1 and 2 diabetes mellitus, and SCZ, using regression models. We observed nominal associations (uncorrected p < 0.05) between PRSs for BMI, CAD, and LDL-C, type 1 diabetes, and SCZ with AIWG. While results became non-significant after correction for multiple testing, these preliminary results suggest that PRS analyses might contribute to identifying risk factors of AIWG and might help to elucidate mechanisms at play in AIWG.

Identifying high-impact variants and genes in exomes of Ashkenazi Jewish inflammatory bowel disease patients

Inflammatory bowel disease (IBD) is a group of chronic digestive tract inflammatory conditions whose genetic etiology is still poorly understood. The incidence of IBD is particularly high among Ashkenazi Jews. Here, we identify 8 novel and plausible IBD-causing genes from the exomes of 4453 genetically identified Ashkenazi Jewish IBD cases (1734) and controls (2719). Various biological pathway analyses are performed, along with bulk and single-cell RNA sequencing, to demonstrate the likely physiological relatedness of the novel genes to IBD. Importantly, we demonstrate that the rare and high impact genetic architecture of Ashkenazi Jewish adult IBD displays significant overlap with very early onset-IBD genetics. Moreover, by performing biobank phenome-wide analyses, we find that IBD genes have pleiotropic effects that involve other immune responses. Finally, we show that polygenic risk score analyses based on genome-wide high impact variants have high power to predict IBD susceptibility.

Cognitive Function in People With Familial Risk of Depression

Cognitive impairment in depression is poorly understood. Family history of depression is a potentially useful risk marker for cognitive impairment, facilitating early identification and targeted intervention in those at highest risk, even if they do not themselves have depression. Several research cohorts have emerged recently that enable findings to be compared according to varying depths of family history phenotyping, in some cases also with genetic data, across the life span. To investigate associations between familial risk of depression and cognitive performance in 4 independent cohorts with varied depth of assessment, using both family history and genetic risk measures. This study used data from the Three Generations at High and Low Risk of Depression Followed Longitudinally (TGS) family study (data collected from 1982 to 2015) and 3 large population cohorts, including the Adolescent Brain Cognitive Development (ABCD) study (data collected from 2016 to 2021), National Longitudinal Study of Adolescent to Adult Health (Add Health; data collected from 1994 to 2018), and UK Biobank (data collected from 2006 to 2022). Children and adults with or without familial risk of depression were included. Cross-sectional analyses were conducted from March to June 2022. Family history (across 1 or 2 prior generations) and polygenic risk of depression. Neurocognitive tests at follow-up. Regression models were adjusted for confounders and corrected for multiple comparisons. A total of 57 308 participants were studied, including 87 from TGS (42 [48%] female; mean [SD] age, 19.7 [6.6] years), 10 258 from ABCD (4899 [48%] female; mean [SD] age, 12.0 [0.7] years), 1064 from Add Health (584 [49%] female; mean [SD] age, 37.8 [1.9] years), and 45 899 from UK Biobank (23 605 [51%] female; mean [SD] age, 64.0 [7.7] years). In the younger cohorts (TGS, ABCD, and Add Health), family history of depression was primarily associated with lower performance in the memory domain, and there were indications that this may be partly associated with educational and socioeconomic factors. In the older UK Biobank cohort, there were associations with processing speed, attention, and executive function, with little evidence of education or socioeconomic influences. These associations were evident even in participants who had never been depressed themselves. Effect sizes between familial risk of depression and neurocognitive test performance were largest in TGS; the largest standardized mean differences in primary analyses were -0.55 (95% CI, -1.49 to 0.38) in TGS, -0.09 (95% CI, -0.15 to -0.03) in ABCD, -0.16 (95% CI, -0.31 to -0.01) in Add Health, and -0.10 (95% CI, -0.13 to -0.06) in UK Biobank. Results were generally similar in the polygenic risk score analyses. In UK Biobank, several tasks showed statistically significant associations in the polygenic risk score analysis that were not evident in the family history models. In this study, whether assessed by family history or genetic data, depression in prior generations was associated with lower cognitive performance in offspring. There are opportunities to generate hypotheses about how this arises through genetic and environmental determinants, moderators of brain development and brain aging, and potentially modifiable social and lifestyle factors across the life span.

Polygenic Risk Score in African populations: progress and challenges.

Polygenic Risk Score (PRS) analysis is a method that predicts the genetic risk of an individual towards targeted traits. Even when there are no significant markers, it gives evidence of a genetic effect beyond the results of Genome-Wide Association Studies (GWAS). Moreover, it selects single nucleotide polymorphisms (SNPs) that contribute to the disease with low effect size making it more precise at individual level risk prediction. PRS analysis addresses the shortfall of GWAS by taking into account the SNPs/alleles with low effect size but play an indispensable role to the observed phenotypic/trait variance. PRS analysis has applications that investigate the genetic basis of several traits, which includes rare diseases. However, the accuracy of PRS analysis depends on the genomic data of the underlying population. For instance, several studies show that obtaining higher prediction power of PRS analysis is challenging for non-Europeans. In this manuscript, we review the conventional PRS methods and their application to sub-Saharan African communities. We conclude that lack of sufficient GWAS data and tools is the limiting factor of applying PRS analysis to sub-Saharan populations. We recommend developing Africa-specific PRS methods and tools for estimating and analyzing African population data for clinical evaluation of PRSs of interest and predicting rare diseases.

Abstract 5234: Novel predictive biomarker SNPs and polygenic risk scores of immune-related genes for colorectal cancer survival in Korea

Abstract Background: One of the major topics about colorectal cancer (CRC) is the core role of various immune cells against cancer cells. To comprehensively understand genetic basis of immune system underlying CRC progression, association of single-nucleotide polymorphisms (SNPs) and polygenic risk scores (PRS) of immune-related genes were investigated with colorectal cancer survival. Methods: CRC patients enrolled in the Seoul National University Hospital with prospective follow-up were included in the study. From blood-derived DNA from CRC patients, genome-wide SNPs were genotyped by using the Korea Biobank Array (KoreanChip). 2,729 immune-related genes were selected from Ensembl, Gene Ontology (GO), and KEGG database and 37,398 mapped SNPs were extracted. SNP or PRS-based Cox proportional hazard models were fit for events of overall survival (OS) and progression-free survival (PFS) estimating effect sizes with hazard ratios (HRs). PRS was calculated as effect size weighted sum of risk alleles of individual patients and categorized into tertiles. To investigate enriched pathways, protein-protein interaction networks analysis was conducted. Bonferroni-corrected p-value (1.3 × 10−6) was used as statistically significance threshold. Results: Among 960 CRC patients, 154 (16.0%) occurred events of death and 245 (25.5%) of progression during the follow-up (median=1,698 days, range=7-2,563 days). For OS, a statistically significant associations were mapped to ACTR3B, ST6GAL1, COTL1, PRKCZ, and CAMK1D genes with the strongest SNP rs14808985 (HR=3.07, P=1.87 × 10−7). For PFS, marginal association was mapped to MECOM gene with the strongest SNP rs16854234 (HR=1.48, P=6.13 × 10−6). In PRS analysis, the highest tertile group showed the prominently increased risk for OS (HR=25.0, P&amp;lt;2.0 × 10−16 ) and PFS (HR=5.88, P&amp;lt;2.0 × 10−16 ) compared with the lowest group for a reference. In protein-protein interaction networks analysis, the strongest enrichments were shown in Th17 cell differentiation pathway for OS and in adherences junction for PFS. Conclusions: We identified novel predictive biomarker genetic variants in ACTR3B and MECOM genes associated with OS and PFS, respectively, among CRC patients. Additionally, we presented PRS as a useful biomarker for survival outcomes and suggested enriched biological pathways involved in CRC progression. These knowledges can promote the understanding of CRC survival and the development of immune-related therapeutic interventions for CRC patients in the future. Citation Format: Dabin Yun, Nan Song, Jin-Ah Sim, Min Jung Kim, Ji Won Park, Seung Yong Jeong, Aesun Shin. Novel predictive biomarker SNPs and polygenic risk scores of immune-related genes for colorectal cancer survival in Korea. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5234.

Genetic Associations Between Stress-Related Disorders and Autoimmune Disease.

Objective: Emerging evidence supports a bidirectional phenotypic association between stress-related disorders and autoimmune disease. However, the biological underpinnings remain unclear. Here, the authors examined whether and how shared genetics contribute to the observed phenotypic associations. Methods: Based on data from 4,123,631 individuals identified from Swedish nationwide registers, familial coaggregation of stress-related disorders (any disorder or posttraumatic stress disorder [PTSD]) and autoimmune disease were initially estimated in seven cohorts with different degrees of kinship. Polygenic risk score (PRS) analyses were then performed with individual-level genotyping data from 376,871 participants in the UK Biobank study. Finally, genetic correlation analyses and enrichment analyses were performed with genome-wide association study (GWAS) summary statistics. Results: Familial coaggregation analyses revealed decreasing odds of concurrence of stress-related disorders and autoimmune disease with descending kinship or genetic relatedness between pairs of relatives; adjusted odds ratios were 1.51 (95% CI=1.09–2.07), 1.28 (95% CI=0.97–1.68), 1.16 (95% CI=1.14–1.18), and 1.01 (95% CI=0.98–1.03) for monozygotic twins, dizygotic twins, full siblings, and half cousins, respectively. Statistically significant positive associations were observed between PRSs of stress-related disorders and autoimmune disease, as well as between PRSs of autoimmune disease and stress-related disorders. GWAS summary statistics revealed a genetic correlation of 0.26 (95% CI=0.14–0.38) between these two phenotypes and identified 10 common genes and five shared functional modules, including one module related to G-protein–coupled receptor pathways. Similar analyses performed for PTSD and specific autoimmune diseases (e.g., autoimmune thyroid disease) largely recapitulated the results of the main analyses. Conclusions: This study demonstrated familial coaggregation, genetic correlation, and common biological pathways between stress-related disorders and autoimmune disease.

Genetic correlations between Alzheimer’s disease and gut microbiome genera

A growing body of evidence suggests that dysbiosis of the human gut microbiota is associated with neurodegenerative diseases like Alzheimer’s disease (AD) via neuroinflammatory processes across the microbiota-gut-brain axis. The gut microbiota affects brain health through the secretion of toxins and short-chain fatty acids, which modulates gut permeability and numerous immune functions. Observational studies indicate that AD patients have reduced microbiome diversity, which could contribute to the pathogenesis of the disease. Uncovering the genetic basis of microbial abundance and its effect on AD could suggest lifestyle changes that may reduce an individual’s risk for the disease. Using the largest genome-wide association study of gut microbiota genera from the MiBioGen consortium, we used polygenic risk score (PRS) analyses with the “best-fit” model implemented in PRSice-2 and determined the genetic correlation between 119 genera and AD in a discovery sample (ADc12 case/control: 1278/1293). To confirm the results from the discovery sample, we next repeated the PRS analysis in a replication sample (GenADA case/control: 799/778) and then performed a meta-analysis with the PRS results from both samples. Finally, we conducted a linear regression analysis to assess the correlation between the PRSs for the significant genera and the APOE genotypes. In the discovery sample, 20 gut microbiota genera were initially identified as genetically associated with AD case/control status. Of these 20, three genera (Eubacterium fissicatena as a protective factor, Collinsella, and Veillonella as a risk factor) were independently significant in the replication sample. Meta-analysis with discovery and replication samples confirmed that ten genera had a significant correlation with AD, four of which were significantly associated with the APOE rs429358 risk allele in a direction consistent with their protective/risk designation in AD association. Notably, the proinflammatory genus Collinsella, identified as a risk factor for AD, was positively correlated with the APOE rs429358 risk allele in both samples. Overall, the host genetic factors influencing the abundance of ten genera are significantly associated with AD, suggesting that these genera may serve as biomarkers and targets for AD treatment and intervention. Our results highlight that proinflammatory gut microbiota might promote AD development through interaction with APOE. Larger datasets and functional studies are required to understand their causal relationships.

Polygenic Risk Score Effect on Violent Behavior in Schizophrenia.

Previous studies aiming to establish a correlation between schizophrenia (SCZ) and aggressive behavior have resulted in contradictory results. Despite this, a certain degree of evidence suggests a potential underlying genetic component to aggression in SCZ. Polygenic risk score (PRS) analysis is a novel technique to estimate the combined effect of multiple genetic influences on aggression. Our objective was to investigate whether PRS could determine a proclivity toward aggressive behavior in patients with SCZ. Community-dwelling patients diagnosed with a schizophrenia spectrum disorder (n = 205) were recruited from a nonforensic outpatient sample. Participants were assessed for aggression using a cross-sectional and retrospective design, and PRS was calculated using genomic DNA and the Illumina Omni 2.5 array. We did not detect any associations between lifetime physical aggression (P = 32), verbal aggression (P = 24), or aggression against property (P = 24) and the PRS for SCZ risk. There may be several reasons to explain our null findings. We recommend that future interaction analyses of PRSs in SCZ that investigate violence focus on forensic psychiatric patients with higher base rates of violence and use participant interviews to assess aggression.

A statistical genetic investigation of psychiatric resilience

ABSTRACT Background: Although trauma exposure (TE) is a transdiagnostic risk factor for many psychiatric disorders, not everyone who experiences TE develops a psychiatric disorder. Resilience may explain this heterogeneity; thus, it is critical to understand the etiologic underpinnings of resilience. Objective: The present study sought to examine the genetic underpinnings of psychiatric resilience using genome-wide association studies (GWAS), genome-wide complex trait analysis (GCTA), and polygenic risk score (PRS) analyses. Method: Participants were 6,634 trauma exposed college students attending a diverse, public university in the Mid Atlantic. GWAS and GCTA analyses were conducted, and using GWAS summary statistics from large genetic consortia, PRS analyses examined the shared genetic risk between resilience and various phenotypes. Results: Results demonstrate that nine single-nucleotide polymorphisms (SNPs) met the suggestive of significance threshold, heritability estimates for resilience were non-significant, and that there is genetic overlap between resilience and AD, as well as resilience and PTSD. Conclusion: Mixed findings from the present study suggest additional research to elucidate the etiological underpinnings of resilience, ideally with larger samples less biased by variables such as heterogeneity (i.e. clinical vs. population based) and population stratification. Genetic investigations of resilience have the potential to elucidate the molecular bases of stress-related psychopathology, suggesting new avenues for prevention and intervention efforts.

More bipolar than bipolar disorder – a polygenic risk score analysis of postpartum psychosis

IntroductionPostpartum psychosis is a rare psychiatric emergency, occurring days to weeks after 1-2 per 1000 deliveries. Its low prevalence makes it difficult to recruit enough participants to investigate the underlying pathophysiology. It is epidemiologically linked to bipolar disorder, which one study also found it to resemble in genetic susceptibility for psychiatric disorders (Di Florio et al. Lancet Psych 2021; 8: 1045–52).ObjectivesIn this study we aim to investigate polygenic liability for psychiatric disorders in two new Swedish postpartum psychosis cohorts.MethodsCases with postpartum psychosis, defined as a psychiatric hospitalization within 6 weeks after delivery, and/or receiving a diagnosis of F53.1 (ICD 10) or 294.40 (ICD 8.), parous women with severe mental illness without postpartum psychosis, and healthy parous controls were identified in two Swedish genetic studies: the Swedish bipolar collection (SWEBIC) and Predictors for ECT (PREFECT). Polygenic risk scores (PRS) were calculated from summary statistics from genome wide studies on bipolar disorder (Mullins et al. Nat Genet 2021; 53 817-829), schizophrenia (Trubetskoy et al. Nature 2022; 604 502-508) and major depression (Wray et al. Nat Genet. 2018; 50 668-681). The p-value thresholds best predicting their respective phenotype were used in logistic regression analyses with the first six principal components and genotyping platform as confounders.ResultsWe identified 176 patients with postpartum psychosis and genetic information (N(SWEBIC)=126, N(PREFECT)=50). Compared with healthy parous women, patients with postpartum psychosis had significantly higher PRS for bipolar disorder (SWEBIC: odds ratio [OR] 2.6 (95% confidence interval [CI] 1.9-3.5), PREFECT: OR 2.4 (95% CI 1.8-3.2), Figure 1.) and schizophrenia (SWEBIC: OR 1.6 (95% CI 1.2-2.2), PREFECT: OR 1.8 (95%; CI 1.3-2.5)). Patients with postpartum psychosis had significantly higher PRS for bipolar disorder (SWEBIC: OR 1.4 (95% CI 1.2-1.8), PREFECT: OR 1.5 (95% CI 1.1-2)) compared with parous women with severe mental illness without postpartum psychosis. We found no associations with major depression PRS in either cohort.Image:ConclusionsWe replicated previous findings of significantly higher PRS for bipolar disorder and schizophrenia in postpartum psychosis compared with healthy controls. In contrast to previous research, we find postpartum psychosis cases to have higher PRS for bipolar disorder than bipolar disorder cases. Our findings highlight the genetic influence in postpartum psychosis and support previous genetic and epidemiological evidence that postpartum psychosis lies on the bipolar spectrum.Disclosure of InterestNone Declared