Genetic predisposition and antipsychotic treatment effect on metabolic syndrome in schizophrenia: a ten-year follow-up study using the Estonian Biobank

Background

Schizophrenia (SCZ) patients exhibit 30% higher prevalence of metabolic syndrome (MetS) compared to the general population with its suboptimal management contributing to increased mortality. Large-scale studies providing real-world evidence of the underlying causes remain limited.

Methods

To address this gap, we used real-world health data from the Estonian Biobank, spanning a median follow-up of ten years, to investigate the impact of genetic predisposition and antipsychotic treatment on the development of MetS in SCZ patients. Specifically, we set out to characterize antipsychotic treatment patterns, genetic predisposition of MetS traits, MetS prognosis, and body mass index (BMI) trajectories, comparing SCZ cases (n = 677) to age- and sex-matched controls (n = 2708).

Findings

SCZ cases exhibited higher genetic predisposition to SCZ (OR = 1.75, 95% CI 1.58-1.94), but lower polygenic burden for increased BMI (OR = 0.88, 95% CI 0.88-0.96) and C-reactive protein (OR = 0.88, 95% CI 0.81-0.97) compared to controls. While SCZ cases showed worse prognosis of MetS (HR 1.95, 95% CI 1.54-2.46), higher antipsychotic adherence within the first treatment year was associated with reduced long-term MetS incidence. Linear mixed modelling, incorporating multiple BMI timepoints, underscored the significant contribution of both, antipsychotic medication, and genetic predisposition to higher BMI, driving the substantially upward trajectory of BMI in SCZ cases.

Interpretation

These findings contribute to refining clinical risk prediction and prevention strategies for MetS among SCZ patients and emphasize the significance of incorporating genetic information, long-term patient tracking, and employing diverse perspectives when analyzing real-world health data.

Funding

EU Horizon 2020, Swedish Research Council, Estonian Research Council, Estonian Ministry of Education and Research, University of Tartu.

Self- and informant-reported personality traits and vaccination against COVID-19

As COVID-19 vaccines' accessibility has grown, so has the role of personal choice in vaccination, and not everybody is willing to vaccinate. Exploring personality traits' associations with vaccination could highlight some person-level drivers of, and barriers to, vaccination. We used self- and informant-ratings of the Five-Factor Model domains and their subtraits (a) measured approximately at the time of vaccination with the 100 Nuances of Personality (100NP) item pool (N = 56,575) and (b) measured on average ten years before the pandemic with the NEO Personality Inventory-3 (NEO-PI-3; N = 3,168). We tested individual domains' and either items' (in the 100NP sample) or facets' (in the NEO-PI-3 sample) associations with vaccination, as well as their collective ability to predict vaccination using elastic net models trained and tested in independent sample partitions. Although the NEO-PI-3 domains and facets did not predict vaccination ten years later, the domains correlated with vaccination in the 100NP sample, with vaccinated people scoring slightly higher on neuroticism and agreeableness and lower on openness, controlling for age, sex, and education. Collectively, the five domains predicted vaccination with an accuracy of r = .08. Associations were stronger at the item level. Vaccinated people were, on average, more science-minded, politically liberal, respectful of rules and authority, and anxious but less spiritual, religious, and self-assured. The 100NP items collectively predicted vaccination with r = .31 accuracy. We conclude that unvaccinated people may be a psychologically heterogeneous group and highlight some potential areas for action in vaccination campaigns.

Genome-wide association study in Estonia reveals importance of vaginal epithelium associated genes in case of recurrent vaginitis

Recurrent vaginitis is a leading reason for visiting a gynaecologist, with bacterial vaginosis (BV) and vulvovaginal candidiasis (VVC) being the most common diagnoses. Reasons and mechanisms behind their recurrent nature are poorly understood. We conducted a genome-wide association study (GWAS) to find possible genetic risk factors for recurrent vaginitis using data from a large population-based biobank, the Estonian Biobank. The study included 6870 cases (at least two episodes of vaginitis) and 5945 controls (no vaginitis episodes). GWAS approach included single marker and gene-based analyses, followed by functional annotation of associated variants and candidate gene mapping.In single marker analysis, one statistically significant (P = 7.8 × 10-9) variant rs1036732378 was identified on chromosome 10. The gene-based association analysis identified one gene, KRT6A, that exceeded the recommended significance threshold (P = 2.6 × 10-6). This is a member of the keratin protein family and is expressed during differentiation in epithelial tissues.Functional mapping and annotation of genetic associations by using adjusted significance level identified 22 potential risk loci that may be associated with recurrent vaginitis phenotype. Comparison of our results with previous studies provided nominal support for LBP (associated with immune response to vaginal bacteria) and PRKCH genes (possible role in keratinocyte differentiation and susceptibility to candidiasis).In conclusion, this study is the first highlighting a potential role of the vaginal epithelium in recurrent vaginitis.

Genome-wide association study meta-analysis supports association between MUC1 and ectopic pregnancy

STUDY QUESTION

Can we identify genetic variants associated with ectopic pregnancy by undertaking the first genome-wide association study (GWAS) leveraging two large-scale biobank initiatives?

SUMMARY ANSWER

We identified two novel genome-wide significant associations with ectopic pregnancy, highlighting MUC1 (mucin 1) as the most plausible affected gene.

WHAT IS KNOWN ALREADY

Ectopic pregnancy is an important cause of maternal morbidity and mortality worldwide. Despite being a common early pregnancy complication, the genetic predisposition to this condition remains understudied and no large scale genetic studies have been performed so far.

STUDY DESIGN, SIZE, DURATION

A GWAS meta-analysis including 7070 women with ectopic pregnancy and 248 810 controls from Estonian Biobank and the FinnGen study.

PARTICIPANTS/MATERIALS, SETTING, METHODS

We identified ectopic pregnancy cases from national registers by ICD (International Classification of Disease) codes (ICD-10 O00), and all remaining women were considered controls. We carried out standard GWAS meta-analysis and additionally annotated GWAS signals, analysed co-localization with quantitative trait loci, estimated genetic correlations and identified associated phenotypes to characterize the genetic signals, as well as to analyse the genetic and phenotypic relationships with the condition.

MAIN RESULTS AND THE ROLE OF CHANCE

We identified two genome-wide significant loci on chromosomes 1 (rs4971091, P = 5.32×10-9) and 10 (rs11598956, P = 2.41×10-8) potentially associated with ectopic pregnancy. Follow-up analyses propose MUC1, which codes for an epithelial glycoprotein with an important role in barrier function, as the most likely candidate gene for the association on chromosome 1. We also characterize the phenotypic and genetic correlations with other phenotypes, identifying a genetic correlation with smoking and diseases of the (genito)urinary and gastrointestinal system, and phenotypic correlations with various reproductive health diagnoses, reflecting the previously known epidemiological associations.

LARGE SCALE DATA

The GWAS meta-analysis summary statistics are available from the GWAS Catalogue (GCST90272883).

LIMITATIONS, REASONS FOR CAUTION

The main limitation is that the findings are based on European-based ancestry populations, with limited data on other populations, and we only captured maternal genomes. Additionally, further larger meta-analysis or independent studies are needed to validate these findings.

WIDER IMPLICATIONS OF THE FINDINGS

This study encourages the use of large-scale genetic datasets to unravel genetic factors linked to ectopic pregnancy, which is difficult to study in experimental settings. Increased sample size might bring additional genetic factors associating with ectopic pregnancy and inform its heritability. Altogether, our results provide more insight into the biology of ectopic pregnancy and, accordingly, the biological processes governing embryo implantation.

STUDY FUNDING/COMPETING INTEREST(S)

N.P.G. was supported by MATER Marie Sklodowska-Curie which received funding from the European Union's Horizon 2020 research and innovation program under grant agreement No. 813707. This study was funded by European Union through the European Regional Development Fund Project No. 2014-2020.4.01.15-0012 GENTRANSMED. Computations were performed in the High-Performance Computing Center of University of Tartu. The authors declare no competing interests.

The Prevalence and Molecular Landscape of Lynch Syndrome in the Affected and General Population

BACKGROUND

Lynch syndrome (LS) is the most frequent genetically pre-disposed colorectal cancer (CRC) syndrome, accounting for 2-3% of all CRC cases. In Estonia, ~1000 new cases are diagnosed each year. This retroactive and prospective study aimed to estimate the prevalence of LS and describe disease-causing variants in mismatch repair (MMR) genes in a diagnostic setting and in the Estonian general population.

METHODS

LS data for the diagnostic cohort were gathered from 2012 to 2022 and data for the general population were acquired from the Estonian Biobank (EstBB). Furthermore, we conducted a pilot study to estimate the improvement of LS diagnostic yield by raising the age limit to >50 years for immunohistochemistry analysis of MMR genes.

RESULTS

We estimated LS live birth prevalence between 1930 and 2003 in Estonia at 1:8638 (95% CI: 1: 9859-7588). During the study period, we gathered 181 LS individuals. We saw almost a six-fold increase in case prevalence, probably deriving from better health awareness, improved diagnostic possibilities and the implementation of MMR IHC testing in a broader age group.

CONCLUSION

The most common genes affected in the diagnostic and EstBB cohorts were MLH1 and PMS2 genes, respectively. The LS diagnosis mean age was 44.8 years for index cases and 36.8 years (p = 0.003) for family members. In the MMR IHC pilot study, 29% had LS.

Cross-Ancestry Investigation of Venous Thromboembolism Genomic Predictors

BACKGROUND

Venous thromboembolism (VTE) is a life-threatening vascular event with environmental and genetic determinants. Recent VTE genome-wide association studies (GWAS) meta-analyses involved nearly 30 000 VTE cases and identified up to 40 genetic loci associated with VTE risk, including loci not previously suspected to play a role in hemostasis. The aim of our research was to expand discovery of new genetic loci associated with VTE by using cross-ancestry genomic resources.

METHODS

We present new cross-ancestry meta-analyzed GWAS results involving up to 81 669 VTE cases from 30 studies, with replication of novel loci in independent populations and loci characterization through in silico genomic interrogations.

RESULTS

In our genetic discovery effort that included 55 330 participants with VTE (47 822 European, 6320 African, and 1188 Hispanic ancestry), we identified 48 novel associations, of which 34 were replicated after correction for multiple testing. In our combined discovery-replication analysis (81 669 VTE participants) and ancestry-stratified meta-analyses (European, African, and Hispanic), we identified another 44 novel associations, which are new candidate VTE-associated loci requiring replication. In total, across all GWAS meta-analyses, we identified 135 independent genomic loci significantly associated with VTE risk. A genetic risk score of the significantly associated loci in Europeans identified a 6-fold increase in risk for those in the top 1% of scores compared with those with average scores. We also identified 31 novel transcript associations in transcriptome-wide association studies and 8 novel candidate genes with protein quantitative-trait locus Mendelian randomization analyses. In silico interrogations of hemostasis and hematology traits and a large phenome-wide association analysis of the 135 GWAS loci provided insights to biological pathways contributing to VTE, with some loci contributing to VTE through well-characterized coagulation pathways and others providing new data on the role of hematology traits, particularly platelet function. Many of the replicated loci are outside of known or currently hypothesized pathways to thrombosis.

CONCLUSIONS

Our cross-ancestry GWAS meta-analyses identified new loci associated with VTE. These findings highlight new pathways to thrombosis and provide novel molecules that may be useful in the development of improved antithrombosis treatments.

Omics-informed CNV calls reduce false-positive rates and improve power for CNV-trait associations

Copy-number variations (CNV) are believed to play an important role in a wide range of complex traits, but discovering such associations remains challenging. While whole-genome sequencing (WGS) is the gold-standard approach for CNV detection, there are several orders of magnitude more samples with available genotyping microarray data. Such array data can be exploited for CNV detection using dedicated software (e.g., PennCNV); however, these calls suffer from elevated false-positive and -negative rates. In this study, we developed a CNV quality score that weights PennCNV calls (pCNVs) based on their likelihood of being true positive. First, we established a measure of pCNV reliability by leveraging evidence from multiple omics data (WGS, transcriptomics, and methylomics) obtained from the same samples. Next, we built a predictor of omics-confirmed pCNVs, termed omics-informed quality score (OQS), using only PennCNV software output parameters. Promisingly, OQS assigned to pCNVs detected in close family members was up to 35% higher than the OQS of pCNVs not carried by other relatives (p < 3.0 × 10⁻⁹⁰), outperforming other scores. Finally, in an association study of four anthropometric traits in 89,516 Estonian Biobank samples, the use of OQS led to a relative increase in the trait variance explained by CNVs of up to 56% compared with published quality filtering methods or scores. Overall, we put forward a flexible framework to improve any CNV detection method leveraging multi-omics evidence, applied it to improve PennCNV calls, and demonstrated its utility by improving the statistical power for downstream association analyses.