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Abstract Genome-wide association studies (GWASs) based on common single nucleotide polymorphisms (SNPs) have identified several loci associated with the risk of monoclonal gammopathy of unknown significance (MGUS), a precursor condition for multiple myeloma (MM). We hypothesized that analyzing haplotypes might be more useful than analyzing individual SNPs, as it could identify functional chromosomal units that collectively contribute to MGUS risk. To test this hypothesis, we used data from our previous GWAS on 992 MGUS cases and 2910 controls from three European populations. We identified 23 haplotypes that were associated with the risk of MGUS at the genome-wide significance level (p

Abstract Background Lithium (Li) remains the treatment of choice for bipolar disorders (BP). Its mood-stabilizing effects help reduce the long-term burden of mania, depression and suicide risk in patients with BP. It also has been shown to have beneficial effects on disease-associated conditions, including sleep and cardiovascular disorders. However, the individual responses to Li treatment vary within and between diagnostic subtypes of BP (e.g. BP-I and BP-II) according to the clinical presentation. Moreover, long-term Li treatment has been linked to adverse side-effects that are a cause of concern and non-adherence, including the risk of developing chronic medical conditions such as thyroid and renal disease. In recent years, studies by the Consortium on Lithium Genetics (ConLiGen) have uncovered a number of genetic factors that contribute to the variability in Li treatment response in patients with BP. Here, we leveraged the ConLiGen cohort (N = 2064) to investigate the genetic basis of Li effects in BP. For this, we studied how Li response and linked genes associate with the psychiatric symptoms and polygenic load for medical comorbidities, placing particular emphasis on identifying differences between BP-I and BP-II. Results We found that clinical response to Li treatment, measured with the Alda scale, was associated with a diminished burden of mania, depression, substance and alcohol abuse, psychosis and suicidal ideation in patients with BP-I and, in patients with BP-II, of depression only. Our genetic analyses showed that a stronger clinical response to Li was modestly related to lower polygenic load for diabetes and hypertension in BP-I but not BP-II. Moreover, our results suggested that a number of genes that have been previously linked to Li response variability in BP differentially relate to the psychiatric symptomatology, particularly to the numbers of manic and depressive episodes, and to the polygenic load for comorbid conditions, including diabetes, hypertension and hypothyroidism. Conclusions Taken together, our findings suggest that the effects of Li on symptomatology and comorbidity in BP are partially modulated by common genetic factors, with differential effects between BP-I and BP-II.

Abstract There is a lack of knowledge regarding the relationship between proneness to dimensional psychopathological syndromes and the underlying pathogenesis across major psychiatric disorders, i.e., Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizoaffective Disorder (SZA), and Schizophrenia (SZ). Lifetime psychopathology was assessed using the OPerational CRITeria (OPCRIT) system in 1,038 patients meeting DSM-IV-TR criteria for MDD, BD, SZ, or SZA. The cohort was split into two samples for exploratory and confirmatory factor analyses. All patients were scanned with 3-T MRI, and data was analyzed with the CAT-12 toolbox in SPM12. Psychopathological factor scores were correlated with gray matter volume (GMV) and cortical thickness (CT). Finally, factor scores were used for exploratory genetic analyses including genome-wide association studies (GWAS) and polygenic risk score (PRS) association analyses. Three factors (paranoid-hallucinatory syndrome, PHS; mania, MA; depression, DEP) were identified and cross-validated. PHS was negatively correlated with four GMV clusters comprising parts of the hippocampus, amygdala, angular, middle occipital, and middle frontal gyri. PHS was also negatively associated with the bilateral superior temporal, left parietal operculum, and right angular gyrus CT. No significant brain correlates were observed for the two other psychopathological factors. We identified genome-wide significant associations for MA and DEP. PRS for MDD and SZ showed a positive effect on PHS, while PRS for BD showed a positive effect on all three factors. This study investigated the relationship of lifetime psychopathological factors and brain morphometric and genetic markers. Results highlight the need for dimensional approaches, overcoming the limitations of the current psychiatric nosology.

Abstract Lithium is the gold standard treatment for bipolar disorder (BD). However, its mechanism of action is incompletely understood, and prediction of treatment outcomes is limited. In our previous multi-omics study of the Pharmacogenomics of Bipolar Disorder (PGBD) sample combining transcriptomic and genomic data, we found that focal adhesion, the extracellular matrix (ECM), and PI3K-Akt signaling networks were associated with response to lithium. In this study, we replicated the results of our previous study using network propagation methods in a genome-wide association study of an independent sample of 2039 patients from the International Consortium on Lithium Genetics (ConLiGen) study. We identified functional enrichment in focal adhesion and PI3K-Akt pathways, but we did not find an association with the ECM pathway. Our results suggest that deficits in the neuronal growth cone and PI3K-Akt signaling, but not in ECM proteins, may influence response to lithium in BD.

Abstract Atopic dermatitis (AD) is a common inflammatory skin condition and prior genome-wide association studies (GWAS) have identified 71 associated loci. In the current study we conducted the largest AD GWAS to date (discovery N = 1,086,394, replication N = 3,604,027), combining previously reported cohorts with additional available data. We identified 81 loci (29 novel) in the European-only analysis (which all replicated in a separate European analysis) and 10 additional loci in the multi-ancestry analysis (3 novel). Eight variants from the multi-ancestry analysis replicated in at least one of the populations tested (European, Latino or African), while two may be specific to individuals of Japanese ancestry. AD loci showed enrichment for DNAse I hypersensitivity and eQTL associations in blood. At each locus we prioritised candidate genes by integrating multi-omic data. The implicated genes are predominantly in immune pathways of relevance to atopic inflammation and some offer drug repurposing opportunities.

Purpose BioMD-Y is a comprehensive biobank study of children and adolescents with major depression (MD) and their healthy peers in Germany, collecting a host of both biological and psychosocial information from the participants and their parents with the aim of exploring genetic and environmental risk and protective factors for MD in children and adolescents.Participants Children and adolescents aged 8–18 years are recruited to either the clinical case group (MD, diagnosis of MD disorder) or the typically developing control group (absence of any psychiatric condition).Findings to date To date, four publications on both genetic and environmental risk and resilience factors (including FKBP5, glucocorticoid receptor activation, polygenic risk scores, psychosocial and sociodemographic risk and resilience factors) have been published based on the BioMD-Y sample.Future plans Data collection is currently scheduled to continue into 2026. Research questions will be further addressed using available measures.

Abstract Objectives Bipolar disorder (BD) and major depressive disorder (MDD) are characterized by specific alterations of mood. In both disorders, alterations in cognitive domains such as impulsivity, decision‐making, and risk‐taking have been reported. Identification of similarities and differences of these domains in BD and MDD could give further insight into their etiology. The present study assessed impulsivity, decision‐making, and risk‐taking behavior in BD and MDD patients from bipolar multiplex families. Methods Eighty‐two participants (BD type I, n = 25; MDD, n = 26; healthy relatives (HR), n = 17; and healthy controls (HC), n = 14) underwent diagnostic interviews and selected tests of a cognitive battery assessing neurocognitive performance across multiple subdomains including impulsivity (response inhibition and delay aversion), decision‐making, and risk behavior. Generalized estimating equations (GEEs) were used to analyze whether the groups differed in the respective cognitive domains. Results Participants with BD and MDD showed higher impulsivity levels compared to HC; this difference was more pronounced in BD participants. BD participants also showed lower inhibitory control than MDD participants. Overall, suboptimal decision‐making was associated with both mood disorders (BD and MDD). In risk‐taking behavior, no significant impairment was found in any group. Limitations As sample size was limited, it is possible that differences between BD and MDD may have escaped detection due to lack of statistical power. Conclusions Our findings show that alterations of cognitive domains—while present in both disorders—are differently associated with BD and MDD. This underscores the importance of assessing such domains in addition to mere diagnosis of mood disorders.

Short telomeres are associated with cardiovascular disease (CVD). We aimed to investigate, if genetically determined telomere-length effects CVD-risk in the Heinz-Nixdorf-Recall study (HNRS) population. We selected 14 single-nucleotide polymorphisms (SNPs) associated with telomere-length (p

Abstract Background and aims Summarised in polygenic risk scores (PRS), the effect of common, low penetrant genetic variants associated with colorectal cancer (CRC), can be used for risk stratification. Methods To assess the combined impact of the PRS and other main factors on CRC risk, 163,516 individuals from the UK Biobank were stratified as follows: 1. carriers status for germline pathogenic variants (PV) in CRC susceptibility genes (APC, MLH1, MSH2, MSH6, PMS2), 2. low ( 80%), and 3. family history (FH) of CRC. Multivariable logistic regression and Cox proportional hazards models were applied to compare odds ratios and to compute the lifetime incidence, respectively. Results Depending on the PRS, the CRC lifetime incidence for non-carriers ranges between 6 and 22%, compared to 40% and 74% for carriers. A suspicious FH is associated with a further increase of the cumulative incidence reaching 26% for non-carriers and 98% for carriers. In non-carriers without FH, but high PRS, the CRC risk is doubled, whereas a low PRS even in the context of a FH results in a decreased risk. The full model including PRS, carrier status, and FH improved the area under the curve in risk prediction (0.704). Conclusion The findings demonstrate that CRC risks are strongly influenced by the PRS for both a sporadic and monogenic background. FH, PV, and common variants complementary contribute to CRC risk. The implementation of PRS in routine care will likely improve personalized risk stratification, which will in turn guide tailored preventive surveillance strategies in high, intermediate, and low risk groups.

(1) Background Pharmacological treatment for psychiatric disorders has shown to only be effective in about one-third of patients, as it is associated with frequent treatment failure, often because of side effects, and a long process of trial-and-error pharmacotherapy until an effective and tolerable treatment is found. This notion emphasizes the urgency for a personalized medicine approach in psychiatry. (2) Methods This prospective patient- and rater-blinded, randomized, controlled study will investigate the effect of dose-adjustment of antidepressants escitalopram and sertraline or antipsychotics risperidone and aripiprazole according to the latest state-of-the-art international dosing recommendations for CYP2C19 and CYP2D6 metabolizer status in patients with mood, anxiety, and psychotic disorders. A total sample of N = 2500 will be recruited at nine sites in seven countries (expected drop-out rate of 30%). Patients will be randomized to a pharmacogenetic group or a dosing-as-usual group and treated over a 24-week period with four study visits. The primary outcome is personal recovery using the Recovery Assessment Scale as assessed by the patient (RAS-DS), with secondary outcomes including clinical effects (response or symptomatic remission), side effects, general well-being, digital phenotyping, and psychosocial functioning. (3) Conclusions This is, to our knowledge, the first international, multi-center, non-industry-sponsored randomized controlled trial (RCT) that may provide insights into the effectiveness and utility of implementing pharmacogenetic-guided treatment of psychiatric disorders, and as such, results will be incorporated in already available dosing guidelines.

Abstract The diagnostic criteria for schizophrenia (SCZ) and bipolar disorder (BD) are based on clinical assessments of symptoms. In this pilot study, we applied high-throughput antibody-based protein profiling to serum samples of healthy controls and individuals with SCZ and BD with the aim of identifying differentially expressed proteins in these disorders. Moreover, we explored the influence of polygenic burden for SCZ and BD on the serum levels of these proteins. Serum samples from 113 individuals with SCZ and 125 with BD from the PsyCourse Study and from 44 healthy controls were analyzed by using a set of 155 antibodies in an antibody-based assay targeting a selected panel of 95 proteins. For the cases, genotyping and imputation were conducted for DNA samples and SCZ and BD polygenic risk scores (PRS) were calculated. Univariate linear and logistic models were used for association analyses. The comparison between SCZ and BD revealed two serum proteins that were significantly elevated in BD after multiple testing adjustment: “complement C9” and “Interleukin 1 Receptor Accessory Protein”. Moreover, the first principal component of variance in the proteomics dataset differed significantly between SCZ and BD. After multiple testing correction, SCZ-PRS, BD-PRS, and SCZ-vs-BD–PRS were not significantly associated with the levels of the individual proteins or the values of the proteome principal components indicating no detectable genetic effects. Overall, our findings contribute to the evidence suggesting that the analysis of circulating proteins could lead to the identification of distinctive biomarkers for SCZ and BD. Our investigation warrants replication in large-scale studies to confirm these findings.

A genome-wide association study on classic bladder exstrophy reveals eight genome-wide significant loci, most of which contained genes expressed in embryonic developmental bladder stages.

Abstract Bipolar disorder (BD) is a complex mood disorder with a strong genetic component. Recent studies suggest that microRNAs contribute to psychiatric disorder development. In BD, specific candidate microRNAs have been implicated, in particular miR-137, miR-499a, miR-708, miR-1908 and miR-2113. The aim of the present study was to determine the contribution of these five microRNAs to BD development. For this purpose, we performed: (i) gene-based tests of the five microRNA coding genes, using data from a large genome-wide association study of BD; (ii) gene-set analyses of predicted, brain-expressed target genes of the five microRNAs; (iii) resequencing of the five microRNA coding genes in 960 BD patients and 960 controls and (iv) in silico and functional studies for selected variants. Gene-based tests revealed a significant association with BD for MIR499A, MIR708, MIR1908 and MIR2113. Gene-set analyses revealed a significant enrichment of BD associations in the brain-expressed target genes of miR-137 and miR-499a-5p. Resequencing identified 32 distinct rare variants (minor allele frequency

Summary: Background: Gastric cancer (GC) is clinically heterogenous according to location (cardia/non-cardia) and histopathology (diffuse/intestinal). We aimed to characterize the genetic risk architecture of GC according to its subtypes. Another aim was to examine whether cardia GC and oesophageal adenocarcinoma (OAC) and its precursor lesion Barrett’s oesophagus (BO), which are all located at the gastro-oesophageal junction (GOJ), share polygenic risk architecture. Methods: We did a meta-analysis of ten European genome-wide association studies (GWAS) of GC and its subtypes. All patients had a histopathologically confirmed diagnosis of gastric adenocarcinoma. For the identification of risk genes among GWAS loci we did a transcriptome-wide association study (TWAS) and expression quantitative trait locus (eQTL) study from gastric corpus and antrum mucosa. To test whether cardia GC and OAC/BO share genetic aetiology we also used a European GWAS sample with OAC/BO. Findings: Our GWAS consisting of 5816 patients and 10,999 controls highlights the genetic heterogeneity of GC according to its subtypes. We newly identified two and replicated five GC risk loci, all of them with subtype-specific association. The gastric transcriptome data consisting of 361 corpus and 342 antrum mucosa samples revealed that an upregulated expression of MUC1, ANKRD50, PTGER4, and PSCA are plausible GC-pathomechanisms at four GWAS loci. At another risk locus, we found that the blood-group 0 exerts protective effects for non-cardia and diffuse GC, while blood-group A increases risk for both GC subtypes. Furthermore, our GWAS on cardia GC and OAC/BO (10,279 patients, 16,527 controls) showed that both cancer entities share genetic aetiology at the polygenic level and identified two new risk loci on the single-marker level. Interpretation: Our findings show that the pathophysiology of GC is genetically heterogenous according to location and histopathology. Moreover, our findings point to common molecular mechanisms underlying cardia GC and OAC/BO. Funding: German Research Foundation (DFG).

Summary: Genetics have nominated many schizophrenia risk genes and identified convergent signals between schizophrenia and neurodevelopmental disorders. However, functional interpretation of the nominated genes in the relevant brain cell types is often lacking. We executed interaction proteomics for six schizophrenia risk genes that have also been implicated in neurodevelopment in human induced cortical neurons. The resulting protein network is enriched for common variant risk of schizophrenia in Europeans and East Asians, is down-regulated in layer 5/6 cortical neurons of individuals affected by schizophrenia, and can complement fine-mapping and eQTL data to prioritize additional genes in GWAS loci. A sub-network centered on HCN1 is enriched for common variant risk and contains proteins (HCN4 and AKAP11) enriched for rare protein-truncating mutations in individuals with schizophrenia and bipolar disorder. Our findings showcase brain cell-type-specific interactomes as an organizing framework to facilitate interpretation of genetic and transcriptomic data in schizophrenia and its related disorders.

Abstract Alcohol Use Disorder (AUD) is a major contributor to global mortality and morbidity. Postmortem human brain tissue enables the investigation of molecular mechanisms of AUD in the neurocircuitry of addiction. We aimed to identify differentially expressed (DE) genes in the ventral and dorsal striatum between individuals with AUD and controls, and to integrate the results with findings from genome- and epigenome-wide association studies (GWAS/EWAS) to identify functionally relevant molecular mechanisms of AUD. DNA-methylation and gene expression (RNA-seq) data was generated from postmortem brain samples of 48 individuals with AUD and 51 controls from the ventral striatum (VS) and the dorsal striatal regions caudate nucleus (CN) and putamen (PUT). We identified DE genes using DESeq2, performed gene-set enrichment analysis (GSEA), and tested enrichment of DE genes in results of GWASs using MAGMA. Weighted correlation network analysis (WGCNA) was performed for DNA-methylation and gene expression data and gene overlap was tested. Differential gene expression was observed in the dorsal (FDR

Abstract Both environmental (e.g. interpersonal traumatization during childhood and adolescence) and genetic factors may contribute to the development of Borderline Personality Disorder (BPD). Twin studies assessing borderline personality symptoms/features in the general population indicate that genetic factors underlying these symptoms/features are shared in part with the personality traits of the Five Factor Model (FFM) of personality—the “Big Five”. In the present study, the genetic overlap of BPD with the Big Five -Openness to Experience, Conscientiousness, Extraversion, Agreeableness, and Neuroticism- was assessed. Linkage disequilibrium score regression was used to calculate genetic correlations between a genome-wide association study (GWAS) in central European populations on BPD (N = 2543) and GWAS on the Big Five (N = 76,551–122,886, Neuroticism N = 390,278). Polygenic scores (PGS) were calculated to test the association of the genetic disposition for the personality traits with BPD case-control status. Significant positive genetic correlations of BPD were found with Neuroticism (rg = 0.34, p = 6.3*10−5) and Openness (rg = 0.24, p = 0.036), but not with the other personality traits (all | rg | 0.30). A cluster and item-level analysis showed positive genetic correlations of BPD with the Neuroticism clusters “Depressed Affect” and “Worry”, and with a broad range of Neuroticism items (N = 348,219–376,352). PGS analyses confirmed the genetic correlations, and found an independent contribution of the personality traits to BPD risk. The observed associations indicate a partially shared genetic background of BPD and the personality traits Neuroticism and Openness. Larger GWAS of BPD and the “Big Five” are needed to further explore the role of personality traits in the etiology of BPD.

Background: Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction. Methods: Genome-wide analysis of remission (nremit = 1852, nnonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism–based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA. Results: Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism–based heritability was significantly different from zero for remission (h2 = 0.132, SE = 0.056) but not for percentage improvement (h2 = −0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response. Conclusions: This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizophrenia and educational attainment, and provides a useful resource for future research. Larger sample sizes are required to attain the potential of genetics for understanding and predicting antidepressant response.

Abstract Background Nonsyndromic cleft lip with/without cleft palate (nsCL/P) is a congenital malformation of multifactorial etiology. Research has identified >40 genome‐wide significant risk loci, which explain less than 40% of nsCL/P heritability. Studies show that some of the hidden heritability is explained by rare penetrant variants. Methods To identify new candidate genes, we searched for highly penetrant de novo variants (DNVs) in 50 nsCL/P patient/parent‐trios with a low polygenic risk for the phenotype (discovery). We prioritized DNV‐carrying candidate genes from the discovery for resequencing in independent cohorts of 1010 nsCL/P patients of diverse ethnicities and 1574 population‐matched controls (replication). Segregation analyses and rare variant association in the replication cohort, in combination with additional data (genome‐wide association data, expression, protein–protein‐interactions), were used for final prioritization. Conclusion In the discovery step, 60 DNVs were identified in 60 genes, including a variant in the established nsCL/P risk gene CDH1. Re‐sequencing of 32 prioritized genes led to the identification of 373 rare, likely pathogenic variants. Finally, MDN1 and PAXIP1 were prioritized as top candidates. Our findings demonstrate that DNV detection, including polygenic risk score analysis, is a powerful tool for identifying nsCL/P candidate genes, which can also be applied to other multifactorial congenital malformations.

BackgroundCocaine use disorder (CUD) is characterized by a loss of control over cocaine intake and is associated with structural, functional, and molecular alterations in the human brain. At the molecular level, epigenetic alterations are hypothesized to contribute to the higher-level functional and structural brain changes observed in CUD. Most evidence of cocaine-associated epigenetic changes comes from animal studies while only a few studies have been performed using human tissue.MethodsWe investigated epigenome-wide DNA methylation (DNAm) signatures of CUD in human post-mortem brain tissue of Brodmann area 9 (BA9). A total of N = 42 BA9 brain samples were obtained from N = 21 individuals with CUD and N = 21 individuals without a CUD diagnosis. We performed an epigenome-wide association study (EWAS) and analyzed CUD-associated differentially methylated regions (DMRs). To assess the functional role of CUD-associated differential methylation, we performed Gene Ontology (GO) enrichment analyses and characterized co-methylation networks using a weighted correlation network analysis. We further investigated epigenetic age in CUD using epigenetic clocks for the assessment of biological age.ResultsWhile no cytosine-phosphate-guanine (CpG) site was associated with CUD at epigenome-wide significance in BA9, we detected a total of 20 CUD-associated DMRs. After annotation of DMRs to genes, we identified Neuropeptide FF Receptor 2 (NPFFR2) and Kalirin RhoGEF Kinase (KALRN) for which a previous role in the behavioral response to cocaine in rodents is known. Three of the four identified CUD-associated co-methylation modules were functionally related to neurotransmission and neuroplasticity. Protein-protein interaction (PPI) networks derived from module hub genes revealed several addiction-related genes as highly connected nodes such as Calcium Voltage-Gated Channel Subunit Alpha1 C (CACNA1C), Nuclear Receptor Subfamily 3 Group C Member 1 (NR3C1), and Jun Proto-Oncogene, AP-1 Transcription Factor Subunit (JUN). In BA9, we observed a trend toward epigenetic age acceleration (EAA) in individuals with CUD remaining stable even after adjustment for covariates.ConclusionResults from our study highlight that CUD is associated with epigenome-wide differences in DNAm levels in BA9 particularly related to synaptic signaling and neuroplasticity. This supports findings from previous studies that report on the strong impact of cocaine on neurocircuits in the human prefrontal cortex (PFC). Further studies are needed to follow up on the role of epigenetic alterations in CUD focusing on the integration of epigenetic signatures with transcriptomic and proteomic data.

Abstract Environmental, genetic, and social factors are suggested to jointly influence monoclonal gammopathy of undetermined significance (MGUS), a precursor of multiple myeloma. Aim of this study was to investigate interactions between MGUS-related genetic variants and socioeconomic position (SEP) indicators education and income on MGUS in a population-based study. Two different MGUS-related genetic risk allele sum scores (GRS) were calculated based on recent genome-wide meta-analyses. Odds Ratios (OR) were estimated in 4329 participants including 238 MGUS cases to assess associations and multiplicative interaction. The relative excess risk due to interaction (RERI) was calculated to assess additive interaction. Both GRSs were associated with MGUS. A multiplicative interaction between one GRS and education was observed with genetic effects of OR 1.34 (95% CI 1.11–1.62) per risk allele in the highest and OR 1.06 (95% CI 0.86–1.31) in the lowest education group. A RERI of 0.10 (95% CI 0.05–0.14) also indicated additive interaction. Further, additive GRS by income interaction (RERI 0.07; 95% CI 0.01–0.13) for the same GRS was also indicated. Results indicate interaction between MGUS-related genetic risk and SEP. Non-genetic MGUS risk factors more common in higher education groups may influence the expression of MGUS-related genetic variants.

Genetic studies of eczema to date have mostly explored common genetic variation. Here, the authors perform a large meta-analysis for common and rare variants and discover 8 loci associated with eczema. Over 20% of the heritability of the condition is attributable to rare variants.

Abstract As early detection of symptoms in the subclinical to clinical psychosis spectrum may improve health outcomes, knowing the probabilistic susceptibility of developing a disorder could guide mitigation measures and clinical intervention. In this context, polygenic risk scores (PRSs) quantifying the additive effects of multiple common genetic variants hold the potential to predict complex diseases and index severity gradients. PRSs for schizophrenia (SZ) and bipolar disorder (BD) were computed using Bayesian regression and continuous shrinkage priors based on the latest SZ and BD genome-wide association studies (Psychiatric Genomics Consortium, third release). Eight well-phenotyped groups (n = 1580; 56% males) were assessed: control (n = 305), lower (n = 117) and higher (n = 113) schizotypy (both groups of healthy individuals), at-risk for psychosis (n = 120), BD type-I (n = 359), BD type-II (n = 96), schizoaffective disorder (n = 86), and SZ groups (n = 384). PRS differences were investigated for binary traits and the quantitative Positive and Negative Syndrome Scale. Both BD-PRS and SZ-PRS significantly differentiated controls from at-risk and clinical groups (Nagelkerke’s pseudo-R 2: 1.3–7.7%), except for BD type-II for SZ-PRS. Out of 28 pairwise comparisons for SZ-PRS and BD-PRS, 9 and 12, respectively, reached the Bonferroni-corrected significance. BD-PRS differed between control and at-risk groups, but not between at-risk and BD type-I groups. There was no difference between controls and schizotypy. SZ-PRSs, but not BD-PRSs, were positively associated with transdiagnostic symptomology. Overall, PRSs support the continuum model across the psychosis spectrum at the genomic level with possible irregularities for schizotypy. The at-risk state demands heightened clinical attention and research addressing symptom course specifiers. Continued efforts are needed to refine the diagnostic and prognostic accuracy of PRSs in mental healthcare.

Abstract Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium’s therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi+Gen; www.ConLiGen.org ). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD.

Abstract Background Postoperative delirium (POD) and postoperative cognitive dysfunction (POCD) are frequent and serious complications after surgery. We aim to investigate the association between genetic variants in cholinergic candidate genes according to the Kyoto encyclopedia of genes and genomes - pathway: cholinergic neurotransmission with the development of POD or POCD in elderly patients. Methods This analysis is part of the European BioCog project ( www.biocog.eu ), a prospective multicenter observational study with elderly surgical patients. Patients with a Mini-Mental-State-Examination score ≤ 23 points were excluded. POD was assessed up to seven days after surgery using the Nursing Delirium Screening Scale, Confusion Assessment Method and a patient chart review. POCD was assessed three months after surgery with a neuropsychological test battery. Genotyping was performed on the Illumina Infinium Global Screening Array. Associations with POD and POCD were analyzed using logistic regression analysis, adjusted for age, comorbidities and duration of anesthesia (for POCD analysis additionally for education). Odds ratios (OR) refer to minor allele counts (0, 1, 2). Results 745 patients could be included in the POD analysis, and 452 in the POCD analysis. The rate of POD within this group was 20.8% (155 patients), and the rate of POCD was 10.2% (46 patients). In a candidate gene approach three genetic variants of the cholinergic genes CHRM2 and CHRM4 were associated with POD (OR [95% confidence interval], rs8191992: 0.61[0.46; 0.80]; rs8191992: 1.60[1.22; 2.09]; rs2067482: 1.64[1.10; 2.44]). No associations were found for POCD. Conclusions We found an association between genetic variants of CHRM2 and CHRM4 and POD. Further studies are needed to investigate whether disturbances in acetylcholine release and synaptic plasticity are involved in the development of POD. Trial registration: ClinicalTrials.gov: NCT02265263.

Abstract Bipolar affective disorder (BD) is a severe psychiatric illness, for which lithium (Li) is the gold standard for acute and maintenance therapies. The therapeutic response to Li in BD is heterogeneous and reliable biomarkers allowing patients stratification are still needed. A GWAS performed by the International Consortium on Lithium Genetics (ConLiGen) has recently identified genetic markers associated with treatment responses to Li in the human leukocyte antigens (HLA) region. To better understand the molecular mechanisms underlying this association, we have genetically imputed the classical alleles of the HLA region in the European patients of the ConLiGen cohort. We found our best signal for amino-acid variants belonging to the HLA-DRB1*11:01 classical allele, associated with a better response to Li (p

Abstract High-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and total cholesterol (TC) levels are influenced by both genes and the environment. The aim was to investigate whether education and income as indicators of socioeconomic position (SEP) interact with lipid-increasing genetic effect allele scores (GES) in a population-based cohort. Using baseline data of 4516 study participants, age- and sex-adjusted linear regression models were fitted to investigate associations between GES and lipids stratified by SEP as well as including GES×SEP interaction terms. In the highest education group compared to the lowest stronger effects per GES standard deviation were observed for HDL-C (2.96 mg/dl [95%-CI: 2.19, 3.83] vs. 2.45 mg/dl [95%-CI: 1.12, 3.72]), LDL-C (6.57 mg/dl [95%-CI: 4.73, 8.37] vs. 2.66 mg/dl [95%-CI: −0.50, 5.76]) and TC (8.06 mg/dl [95%-CI: 6.14, 9.98] vs. 4.37 mg/dl [95%-CI: 0.94, 7.80]). Using the highest education group as reference, interaction terms showed indication of GES by low education interaction for LDL-C (ßGES×Education: −3.87; 95%-CI: −7.47, −0.32), which was slightly attenuated after controlling for GESLDL-C×Diabetes interaction (ßGES×Education: −3.42; 95%-CI: −6.98, 0.18). The present study showed stronger genetic effects on LDL-C in higher SEP groups and gave indication for a GESLDL-C×Education interaction, demonstrating the relevance of SEP for the expression of genetic health risks.

Abstract Major mental disorders are highly prevalent and make a substantial contribution to the global disease burden. It is known that mental disorders share clinical characteristics, and genome-wide association studies (GWASs) have recently provided evidence for shared genetic factors as well. Genetic overlaps are usually identified at the single-marker level. Here, we aimed to identify genetic overlaps at the gene level between 7 mental disorders (schizophrenia, autism spectrum disorder, major depressive disorder, anorexia nervosa, ADHD, bipolar disorder and anxiety), 8 brain morphometric traits, 2 cognitive traits (educational attainment and general cognitive function) and 9 personality traits (subjective well-being, depressive symptoms, neuroticism, extraversion, openness to experience, agreeableness and conscientiousness, children’s aggressive behaviour, loneliness) based on publicly available GWASs. We performed systematic conditional regression analyses to identify independent signals and select loci associated with more than one trait. We identified 48 genes containing independent markers associated with several traits (pleiotropy at the gene level). We also report 9 genes with different markers that show independent associations with single traits (allelic heterogeneity). This study demonstrates that mental disorders and related traits do show pleiotropy at the gene level as well as the single-marker level. The identification of these genes might be important for prioritizing further deep genotyping, functional studies, or drug targeting.

Abstract Among children, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections are typically mild. Here, we describe the case of a 3.5-year-old girl with an unusually severe presentation of coronavirus disease (COVID-19). The child had an autoinflammatory disorder of unknown etiology, which had been treated using prednisolone and methotrexate, and her parents were half cousins of Turkish descent. After 5 days of nonspecific viral infection symptoms, tonic-clonic seizures occurred followed by acute cardiac insufficiency, multi-organ insufficiency, and ultimate death. Trio exome sequencing identified a homozygous splice-variant in the gene TBK1, and a homozygous missense variant in the gene TNFRSF13B. Heterozygous deleterious variants in the TBK1 gene have been associated with severe COVID-19, and the variant in the TNFRSF13B gene has been associated with common variable immunodeficiency (CVID). We suggest that the identified variants, the autoinflammatory disorder and its treatment, or a combination of these factors probably predisposed to lethal COVID-19 in the present case.

Angioedema is a relatively rare but potentially life-threatening adverse reaction to angiotensin-converting enzyme inhibitors (ACEi) and angiotensin receptor blockers (ARBs). As with hereditary forms of angioedema (HAE), this adverse reaction is mediated by bradykinin. Research suggests that ACEi/ARB-induced angioedema has a multifactorial etiology. In addition, recent case reports suggest that some ACEi/ARB-induced angioedema patients may carry pathogenic HAE variants. The aim of the present study was to investigate the possible association between ACEi/ARB-induced angioedema and HAE genes via systematic molecular genetic screening in a large cohort of ACEi/ARB-induced angioedema cases. Targeted re-sequencing of five HAE-associated genes (SERPING1, F12, PLG, ANGPT1, and KNG1) was performed in 212 ACEi/ARB-induced angioedema patients recruited in Germany/Austria, Sweden, and Denmark, and in 352 controls from a German cohort. Among patients, none of the identified variants represented a known pathogenic variant for HAE. Moreover, no significant association with ACEi/ARB-induced angioedema was found for any of the identified common [minor allele frequency (MAF) >5%] or rare (MAF < 5%) variants. However, several non-significant trends suggestive of possible protective effects were observed. The lowest p-value for an individual variant was found in PLG (rs4252129, p.R523W, p = 0.057, p.adjust > 0.999, Fisher’s exact test). Variant p.R523W was found exclusively in controls and has previously been associated with decreased levels of plasminogen, a precursor of plasmin which is part of a pathway directly involved in bradykinin production. In addition, rare, potentially functional variants (MAF < 5%, Phred-scaled combined annotation dependent depletion score >10) showed a nominally significant enrichment in controls both: 1) across all five genes; and 2) in the F12 gene alone. However, these results did not withstand correction for multiple testing. In conclusion, our results suggest that HAE-associated mutations are, at best, a rare cause of ACEi/ARB-induced angioedema. Furthermore, we were unable to identify a significant association between ACEi/ARB-induced angioedema and other variants in the investigated genes. Further studies with larger sample sizes are warranted to draw more definite conclusions concerning variants with limited effect sizes, including protective variants.

Known genetic loci account for only a fraction of the genetic contribution to Alzheimer’s disease. Here, the authors have performed a large genome-wide meta-analysis comprising 409,435 individuals to discover 6 new loci and demonstrate the efficacy of an Alzheimer’s disease polygenic risk score.

Summary: Esophageal atresia with or without tracheoesophageal fistula (EA/TEF) is the most common congenital malformation of the upper digestive tract. This study represents the first genome-wide association study (GWAS) to identify risk loci for EA/TEF. We used a European case-control sample comprising 764 EA/TEF patients and 5,778 controls and observed genome-wide significant associations at three loci. On chromosome 10q21 within the gene CTNNA3 (p = 2.11 × 10−8; odds ratio [OR] = 3.94; 95% confidence interval [CI], 3.10–5.00), on chromosome 16q24 next to the FOX gene cluster (p = 2.25 × 10−10; OR = 1.47; 95% CI, 1.38–1.55) and on chromosome 17q12 next to the gene HNF1B (p = 3.35 × 10−16; OR = 1.75; 95% CI, 1.64–1.87). We next carried out an esophageal/tracheal transcriptome profiling in rat embryos at four selected embryonic time points. Based on these data and on already published data, the implicated genes at all three GWAS loci are promising candidates for EA/TEF development. We also analyzed the genetic EA/TEF architecture beyond the single marker level, which revealed an estimated single-nucleotide polymorphism (SNP)-based heritability of around 37% ± 14% standard deviation. In addition, we examined the polygenicity of EA/TEF and found that EA/TEF is less polygenic than other complex genetic diseases. In conclusion, the results of our study contribute to a better understanding on the underlying genetic architecture of ET/TEF with the identification of three risk loci and candidate genes.

Abstract A retrospective meta-analysis of magnetic resonance imaging voxel-based morphometry studies proposed that reduced gray matter volumes in the dorsal anterior cingulate and the left and right anterior insular cortex—areas that constitute hub nodes of the salience network—represent a common substrate for major psychiatric disorders. Here, we investigated the hypothesis that the common substrate serves as an intermediate phenotype to detect genetic risk variants relevant for psychiatric disease. To this end, after a data reduction step, we conducted genome-wide association studies of a combined common substrate measure in four population-based cohorts (n = 2271), followed by meta-analysis and replication in a fifth cohort (n = 865). After correction for covariates, the heritability of the common substrate was estimated at 0.50 (standard error 0.18). The top single-nucleotide polymorphism (SNP) rs17076061 was associated with the common substrate at genome-wide significance and replicated, explaining 1.2% of the common substrate variance. This SNP mapped to a locus on chromosome 5q35.2 harboring genes involved in neuronal development and regeneration. In follow-up analyses, rs17076061 was not robustly associated with psychiatric disease, and no overlap was found between the broader genetic architecture of the common substrate and genetic risk for major depressive disorder, bipolar disorder, or schizophrenia. In conclusion, our study identified that common genetic variation indeed influences the common substrate, but that these variants do not directly translate to increased disease risk. Future studies should investigate gene-by-environment interactions and employ functional imaging to understand how salience network structure translates to psychiatric disorder risk.

Abstract The two major subtypes of bipolar disorder (BD), BD-I and BD-II, are distinguished based on the presence of manic or hypomanic episodes. Historically, BD-II was perceived as a less severe form of BD-I. Recent research has challenged this concept of a severity continuum. Studies in large samples of unrelated patients have described clinical and genetic differences between the subtypes. Besides an increased schizophrenia polygenic risk load in BD-I, these studies also observed an increased depression risk load in BD-II patients. The present study assessed whether such clinical and genetic differences are also found in BD patients from multiplex families, which exhibit reduced genetic and environmental heterogeneity. Comparing 252 BD-I and 75 BD-II patients from the Andalusian Bipolar Family (ABiF) study, the clinical course, symptoms during depressive and manic episodes, and psychiatric comorbidities were analyzed. Furthermore, polygenic risk scores (PRS) for BD, schizophrenia, and depression were assessed. BD-I patients not only suffered from more severe symptoms during manic episodes but also more frequently showed incapacity during depressive episodes. A higher BD PRS was significantly associated with suicidal ideation. Moreover, BD-I cases exhibited lower depression PRS. In line with a severity continuum from BD-II to BD-I, our results link BD-I to a more pronounced clinical presentation in both mania and depression and indicate that the polygenic risk load of BD predisposes to more severe disorder characteristics. Nevertheless, our results suggest that the genetic risk burden for depression also shapes disorder presentation and increases the likelihood of BD-II subtype development.

Abstract Predicting lithium response (LiR) in bipolar disorder (BD) may inform treatment planning, but phenotypic heterogeneity complicates discovery of genomic markers. We hypothesized that patients with “exemplary phenotypes”—those whose clinical features are reliably associated with LiR and non-response (LiNR)—are more genetically separable than those with less exemplary phenotypes. Using clinical data collected from people with BD (n = 1266 across 7 centers; 34.7% responders), we computed a “clinical exemplar score,” which measures the degree to which a subject’s clinical phenotype is reliably predictive of LiR/LiNR. For patients whose genotypes were available (n = 321), we evaluated whether a subgroup of responders/non-responders with the top 25% of clinical exemplar scores (the “best clinical exemplars”) were more accurately classified based on genetic data, compared to a subgroup with the lowest 25% of clinical exemplar scores (the “poor clinical exemplars”). On average, the best clinical exemplars of LiR had a later illness onset, completely episodic clinical course, absence of rapid cycling and psychosis, and few psychiatric comorbidities. The best clinical exemplars of LiR and LiNR were genetically separable with an area under the receiver operating characteristic curve of 0.88 (IQR [0.83, 0.98]), compared to 0.66 [0.61, 0.80] (p = 0.0032) among poor clinical exemplars. Variants in the Alzheimer’s amyloid–secretase pathway, along with G-protein-coupled receptor, muscarinic acetylcholine, and histamine H1R signaling pathways were informative predictors. This study must be replicated on larger samples and extended to predict response to other mood stabilizers.

Abstract Tourette syndrome (TS) is a neuropsychiatric disorder of complex genetic architecture involving multiple interacting genes. Here, we sought to elucidate the pathways that underlie the neurobiology of the disorder through genome-wide analysis. We analyzed genome-wide genotypic data of 3581 individuals with TS and 7682 ancestry-matched controls and investigated associations of TS with sets of genes that are expressed in particular cell types and operate in specific neuronal and glial functions. We employed a self-contained, set-based association method (SBA) as well as a competitive gene set method (MAGMA) using individual-level genotype data to perform a comprehensive investigation of the biological background of TS. Our SBA analysis identified three significant gene sets after Bonferroni correction, implicating ligand-gated ion channel signaling, lymphocytic, and cell adhesion and transsynaptic signaling processes. MAGMA analysis further supported the involvement of the cell adhesion and trans-synaptic signaling gene set. The lymphocytic gene set was driven by variants in FLT3, raising an intriguing hypothesis for the involvement of a neuroinflammatory element in TS pathogenesis. The indications of involvement of ligand-gated ion channel signaling reinforce the role of GABA in TS, while the association of cell adhesion and trans-synaptic signaling gene set provides additional support for the role of adhesion molecules in neuropsychiatric disorders. This study reinforces previous findings but also provides new insights into the neurobiology of TS.

Abstract Predicting lithium response prior to treatment could both expedite therapy and avoid exposure to side effects. Since lithium responsiveness may be heritable, its predictability based on genomic data is of interest. We thus evaluate the degree to which lithium response can be predicted with a machine learning (ML) approach using genomic data. Using the largest existing genomic dataset in the lithium response literature (n = 2210 across 14 international sites; 29% responders), we evaluated the degree to which lithium response could be predicted based on 47,465 genotyped single nucleotide polymorphisms using a supervised ML approach. Under appropriate cross-validation procedures, lithium response could be predicted to above-chance levels in two constituent sites (Halifax, Cohen’s kappa 0.15, 95% confidence interval, CI [0.07, 0.24]; and Würzburg, kappa 0.2 [0.1, 0.3]). Variants with shared importance in these models showed over-representation of postsynaptic membrane related genes. Lithium response was not predictable in the pooled dataset (kappa 0.02 [− 0.01, 0.04]), although non-trivial performance was achieved within a restricted dataset including only those patients followed prospectively (kappa 0.09 [0.04, 0.14]). Genomic classification of lithium response remains a promising but difficult task. Classification performance could potentially be improved by further harmonization of data collection procedures.

Here the authors present a SARS-CoV2 seroepidemiological observational study from a random, household-based study population in a small town in Germany, showing the effect of a super-spreading event on infection rate, severity, and potentially infection fatality rate.

Abstract Background A Genetic risk score for coronary artery disease (CAD) improves the ability of predicting coronary heart disease (CHD). It is unclear whether i) the use of a CAD genetic risk score is superior to the measurement of coronary artery calcification (CAC) for CHD risk assessment and ii) the CHD risk assessment using a CAD genetic risk score differs between men and women. Methods We included 4041 participants (age-range: 45–76 years, 1919 men) of the Heinz Nixdorf Recall study without CHD or stroke at baseline. A standardized weighted CAD genetic risk score was constructed using 70 known genetic variants. The risk score was divided into quintiles (Q1-Q5). We specified low (Q1), intermediate (Q2-Q4) and high (Q5) genetic risk groups. Incident CHD was defined as fatal and non-fatal myocardial infarction, stroke and coronary death. The association between the genetic risk score and genetic risk groups with incident CHD was assessed using Cox models to estimate hazard ratios (HR) and 95%-confidence intervals (CI). The models were adjusted by age and sex (Model1), as well as by established CHD risk factors (RF) and CAC (Model2). The analyses were further stratified by sex and controlled for multiple testing. Results During a median follow-up time of 11.6 ± 3.7 years, 343 participants experienced CHD events (219 men). Per-standard deviation (SD) increase in the genetic risk score was associated with 18% increased risk for incident CHD (Model1: p = 0.002) which did not change after full adjustment (Model2: HR = 1.18 per-SD (p = 0.003)). In Model2 we observed a 60% increased CHD risk in the high (p = 0.009) compared to the low genetic risk group. Stratifying by sex, only men showed statistically significantly higher risk for CHD (Model2: HR = 1.23 per-SD (p = 0.004); intermediate: HR = 1.52 (p = 0.04) and high: HR = 1.88 (p = 0.008)) with no statistically significant risk observed in women. Conclusion Our results suggest that the CAD genetic risk score could be useful for CHD risk prediction, at least in men belonging to the higher genetic risk group, but it does not outbalance the value of CT-based quantification of CAC which works independently on both men and women and allows better risk stratification in both the genders.

Abstract Advanced paternal age (APA) is a risk factor for several neurodevelopmental disorders, including autism and schizophrenia. The potential mechanisms conferring this risk are poorly understood. Here, we show that the personality traits schizotypy and neuroticism correlated with paternal age in healthy subjects (N = 677). Paternal age was further positively associated with gray matter volume (VBM, N = 342) in the right prefrontal and the right medial temporal cortex. The integrity of fiber tracts (DTI, N = 222) connecting these two areas correlated positively with paternal age. Genome-wide methylation analysis in humans showed differential methylation in APA individuals, linking APA to epigenetic mechanisms. A corresponding phenotype was obtained in our rat model. APA rats displayed social-communication deficits and emitted fewer pro-social ultrasonic vocalizations compared to controls. They further showed repetitive and stereotyped patterns of behavior, together with higher anxiety during early development. At the neurobiological level, microRNAs miR-132 and miR-134 were both differentially regulated in rats and humans depending on APA. This study demonstrates associations between APA and social behaviors across species. They might be driven by changes in the expression of microRNAs and/or epigenetic changes regulating neuronal plasticity, leading to brain morphological changes and fronto-hippocampal connectivity, a network which has been implicated in social interaction.

Abstract Background To examine the association between lipoprotein(a) (Lp(a)) levels, LPA (rs10455872 and rs3798220) and IL1F9 (rs13415097) single nucleotide polymorphisms (SNPs) with coronary artery calcification (CAC), an important predictor for coronary artery disease (CAD). Methods We used data from 3799 (mean age ± SD: 59.0 ± 7.7 years, 47.1% men) Heinz Nixdorf Recall study participants. We applied linear regression models to explore the relation between the log-transformed Lp(a) levels and LPA and IL1F9 SNPs with loge (CAC + 1). The association between the SNPs and log-transformed Lp(a) levels was further assessed using linear regression. The models were adjusted for age and sex (Model 1) and additionally for Lp(a) levels (Model 2). Results We observed a statistically significant association between log-transformed Lp(a) levels and CAC (Model 1: beta per log-unit increase in Lp(a) levels = 0.11; 95% confidence interval [95% CI] [0.04; 0.18], p = 0.002). Furthermore, the LPA SNP rs10455872 showed a statistically significant association with CAC (Model 1: beta per allele = 0.37 [0.14; 0.61], p = 0.002). The association between rs10455872 and CAC was attenuated after adjustment for Lp(a) levels (Model 2: beta per allele = 0.26 [− 0.01; 0.53], p = 0.06). Both LPA SNPs also showed a statistically significant association with Lp(a) levels (Model 1: betars10455872 per allele: 1.56 [1.46; 1.65], p

Abstract Background Stressful life events influence the course of affective disorders, however, the mechanisms by which they bring about phenotypic change are not entirely known. Methods We explored the role of DNA methylation in response to recent stressful life events in a cohort of bipolar patients from the longitudinal PsyCourse study (n = 96). Peripheral blood DNA methylomes were profiled at two time points for over 850,000 methylation sites. The association between impact ratings of stressful life events and DNA methylation was assessed, first by interrogating methylation sites in the vicinity of candidate genes previously implicated in the stress response and, second, by conducting an exploratory epigenome-wide association analysis. Third, the association between epigenetic aging and change in stress and symptom measures over time was investigated. Results Investigation of methylation signatures over time revealed just over half of the CpG sites tested had an absolute difference in methylation of at least 1% over a 1-year period. Although not a single CpG site withstood correction for multiple testing, methylation at one site (cg15212455) was suggestively associated with stressful life events (p

Background: Cardiac autonomic dysfunction (CADF) is a major contributor to increased cardiac mortality in schizophrenia patients. The aberrant function of voltage-gated ion channels, which are widely distributed in the brain and heart, may link schizophrenia and CADF. In search of channel-encoding genes that are associated with both CADF and schizophrenia, CACNA1C and KCNH2 are promising candidates. In this study, we tested for associations between genetic findings in both genes and CADF parameters in schizophrenia patients whose heart functions were not influenced by psychopharmaceuticals. Methods: First, we searched the literature for single-nucleotide polymorphisms (SNPs) in CACNA1C and KCNH2 that showed genome-wide significant association with schizophrenia. Subsequently, we looked for such robust associations with CADF traits at these loci. A total of 5 CACNA1C SNPs and 9 KCNH2 SNPs were found and genotyped in 77 unmedicated schizophrenia patients and 144 healthy controls. Genotype-related impacts on heart rate (HR) dynamics and QT variability indices (QTvi) were analyzed separately in patients and healthy controls. Results: We observed significantly increased QTvi in unmedicated patients with CADF-associated risk in CACNA1C rs2283274 C and schizophrenia-associated risk in rs2239061 G compared to the non-risk allele in these patients. Moreover, unmedicated patients with previously identified schizophrenia risk alleles in KCNH2 rs11763131 A, rs3807373 A, rs3800779 C, rs748693 G, and 1036145 T showed increased mean HR and QTvi as compared to non-risk alleles. Conclusions: We propose a potential pleiotropic role for common variation in CACNA1C and KCNH2 associated with CADF in schizophrenia patients, independent of antipsychotic medication, that predisposes them to cardiac arrhythmias and premature death.

The hepatic Na+-taurocholate cotransporting polypeptide NTCP/SLC10A1 is important for the uptake of bile salts and selected drugs. Its inhibition results in increased systemic bile salt concentrations. NTCP is also the entry receptor for the hepatitis B/D virus. We investigated interindividual hepatic SLC10A1/NTCP expression using various omics technologies. SLC10A1/NTCP mRNA expression/protein abundance was quantified in well-characterized 143 human livers by real-time PCR and LC-MS/MS-based targeted proteomics. Genome-wide SNP arrays and SLC10A1 next-generation sequencing were used for genomic analyses. SLC10A1 DNA methylation was assessed through MALDI-TOF MS. Transcriptomics and untargeted metabolomics (UHPLC-Q-TOF-MS) were correlated to identify NTCP-related metabolic pathways. SLC10A1 mRNA and NTCP protein levels varied 44-fold and 10.4-fold, respectively. Non-genetic factors (e.g., smoking, alcohol consumption) influenced significantly NTCP expression. Genetic variants in SLC10A1 or other genes do not explain expression variability which was validated in livers (n = 50) from The Cancer Genome Atlas. The identified two missense SLC10A1 variants did not impair transport function in transfectants. Specific CpG sites in SLC10A1 as well as single metabolic alterations and pathways (e.g., peroxisomal and bile acid synthesis) were significantly associated with expression. Inter-individual variability of NTCP expression is multifactorial with the contribution of clinical factors, DNA methylation, transcriptional regulation as well as hepatic metabolism, but not genetic variation.