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Patients with schizophrenia have consistently shown brain volumetric abnormalities, implicating both etiological and pathological processes. However, the genetic relationship between schizophrenia and brain volumetric abnormalities remains poorly understood. Here, we applied novel statistical genetic approaches (MiXeR and conjunctional false discovery rate analysis) to investigate genetic overlap with mixed effect directions using independent genome-wide association studies of schizophrenia (n = 130,644) and brain volumetric phenotypes, including subcortical brain and intracranial volumes (n = 33,735). We found brain volumetric phenotypes share substantial genetic variants (74–96%) with schizophrenia, and observed 107 distinct shared loci with sign consistency in independent samples. Genes mapped by shared loci revealed (1) significant enrichment in neurodevelopmental biological processes, (2) three co-expression clusters with peak expression at the prenatal stage, and (3) genetically imputed thalamic expression of CRHR1 and ARL17A was associated with the thalamic volume as early as in childhood. Together, our findings provide evidence of shared genetic architecture between schizophrenia and brain volumetric phenotypes and suggest that altered early neurodevelopmental processes and brain development in childhood may be involved in schizophrenia development. acceptedVersion

ImportancePremenstrual disorders are heritable, clinically heterogenous, with a range of affective spectrum comorbidities. It is unclear whether genetic predispositions to affective spectrum disorders or other major psychiatric disorders are associated with symptoms of premenstrual disorders.ObjectiveTo assesss whether symptoms of premenstrual disorders are associated with the genetic liability for major psychiatric disorders, as indexed by polygenic risk scores (PRSs).Design, Setting, and ParticipantsWomen from the Norwegian Mother, Father and Child Cohort Study were included in this genetic association study. PRSs were used to determine whether genetic liability for major depression, bipolar disorder, schizophrenia, attention-deficit/hyperactivity disorder, and autism spectrum disorder were associated with the symptoms of premenstrual disorders, using the PRS for height as a somatic comparator. The sample was recruited across Norway between June 1999 and December 2008, and analyses were performed from July 1 to October 14, 2022.Main Outcomes and MeasuresThe symptoms of premenstrual disorders were assessed at recruitment at week 15 of pregnancy with self-reported severity of depression and irritability before menstruation. Logistic regression was applied to test for the association between the presence of premenstrual disorder symptoms and the PRSs for major psychiatric disorders.ResultsThe mean (SD) age of 56 725 women included in the study was 29.0 (4.6) years. Premenstrual disorder symptoms were present in 12 316 of 56 725 participants (21.7%). The symptoms of premenstrual disorders were associated with the PRSs for major depression (β = 0.13; 95% CI, 0.11-0.15; P = 1.21 × 10−36), bipolar disorder (β = 0.07; 95% CI, 0.05-0.09; P = 1.74 × 10−11), attention deficit/hyperactivity disorder (β = 0.07; 95% CI, 0.04-0.09; P = 1.58 × 10−9), schizophrenia (β = 0.11; 95% CI, 0.09-0.13; P = 7.61 × 10−25), and autism spectrum disorder (β = 0.03; 95% CI, 0.01-0.05; P = .02) but not with the PRS for height. The findings were confirmed in a subsample of women without a history of psychiatric diagnosis.ConclusionsThe results of this genetic association study show that genetic liability for both affective spectrum disorder and major psychiatric disorders was associated with symptoms of premenstrual disorders, indicating that premenstrual disorders have overlapping genetic foundations with major psychiatric disorders.

Low vitamin D (vitD) levels have been consistently reported in schizophrenia (SCZ) suggesting a role in the etiopathology. However, little is known about the role of underlying shared genetic mechanisms. We applied a conditional/conjunctional false discovery rate approach (FDR) on large, nonoverlapping genome-wide association studies for SCZ (N cases = 53 386, N controls = 77 258) and vitD serum concentration (N = 417 580) to evaluate shared common genetic variants. The identified genomic loci were characterized using functional analyses and biological repositories. We observed cross-trait SNP enrichment in SCZ conditioned on vitD and vice versa, demonstrating shared genetic architecture. Applying the conjunctional FDR approach, we identified 72 loci jointly associated with SCZ and vitD at conjunctional FDR

Psychiatric disorders and common epilepsies are heritable disorders with a high comorbidity and overlapping symptoms. However, the causative mechanisms underlying this relationship are poorly understood. Here we aimed to identify overlapping genetic loci between epilepsy and psychiatric disorders to gain a better understanding of their comorbidity and shared clinical features. We analysed genome-wide association study data for all epilepsies (n = 44 889), genetic generalized epilepsy (n = 33 446), focal epilepsy (n = 39 348), schizophrenia (n = 77 096), bipolar disorder (n = 406 405), depression (n = 500 199), attention deficit hyperactivity disorder (n = 53 293) and autism spectrum disorder (n = 46 350). First, we applied the MiXeR tool to estimate the total number of causal variants influencing the disorders. Next, we used the conjunctional false discovery rate statistical framework to improve power to discover shared genomic loci. Additionally, we assessed the validity of the findings in independent cohorts, and functionally characterized the identified loci. The epilepsy phenotypes were considerably less polygenic (1.0 K to 3.4 K causal variants) than the psychiatric disorders (5.6 K to 13.9 K causal variants), with focal epilepsy being the least polygenic (1.0 K variants), and depression having the highest polygenicity (13.9 K variants). We observed cross-trait genetic enrichment between genetic generalized epilepsy and all psychiatric disorders and between all epilepsies and schizophrenia and depression. Using conjunctional false discovery rate analysis, we identified 40 distinct loci jointly associated with epilepsies and psychiatric disorders at conjunctional false discovery rate The extensive genetic overlap with mixed effect directions between psychiatric disorders and common epilepsies demonstrates a complex genetic relationship between these disorders, in line with their bi-directional relationship, and indicates that overlapping genetic risk may contribute to shared pathophysiological and clinical features between epilepsy and psychiatric disorders.

Lithium (Li) is recommended for long-term treatment of bipolar disorder (BD). However, its mechanism of action is still poorly understood. Induced pluripotent stem cell (iPSC)-derived brain organoids have emerged as a powerful tool for modeling BD-related disease mechanisms. We studied the effects of 1 mM Li treatment for 1 month in iPSC-derived human cortical spheroids (hCS) from 10 healthy controls (CTRL) and 11 BD patients (6 Li-responders, Li-R, and 5 Li non-treated, Li-N). At day 180 of differentiation, BD hCS showed smaller size, reduced proportion of neurons, decreased neuronal excitability and reduced neural network activity compared to CTRL hCS. Li rescued excitability of BD hCS neurons by exerting an opposite effect in the two diagnostic groups, increasing excitability in BD hCS and decreasing it in CTRL hCS. We identified 132 Li-associated differentially expressed genes (DEGs), which were overrepresented in sodium ion homeostasis and kidney-related pathways. Moreover, Li regulated secretion of pro-inflammatory cytokines and increased mitochondrial reserve capacity in BD hCS. Through long-term Li treatment of a human 3D brain model, this study partly elucidates the functional and transcriptional mechanisms underlying the clinical effects of Li, such as rescue of neuronal excitability and neuroprotection. Our results also underscore the substantial influence of treatment duration in Li studies. Lastly, this study illustrates the potential of patient iPSC-derived 3D brain models for precision medicine in psychiatry.

Treatment resistant schizophrenia (TRS) is characterized by repeated treatment failure with antipsychotics. A recent genome-wide association study (GWAS) of TRS showed a polygenic architecture, but no significant loci were identified. Clozapine is shown to be the superior drug in terms of clinical effect in TRS; at the same time it has a serious side effect profile, including weight gain. Here, we sought to increase power for genetic discovery and improve polygenic prediction of TRS, by leveraging genetic overlap with Body Mass Index (BMI). We analysed GWAS summary statistics for TRS and BMI applying the conditional false discovery rate (cFDR) framework. We observed cross-trait polygenic enrichment for TRS conditioned on associations with BMI. Leveraging this cross-trait enrichment, we identified 2 novel loci for TRS at cFDR MAP2K1 and ZDBF2. Further, polygenic prediction based on the cFDR analysis explained more variance in TRS when compared to the standard TRS GWAS. These findings highlight putative molecular pathways which may distinguish TRS patients from treatment responsive patients. Moreover, these findings confirm that shared genetic mechanisms influence both TRS and BMI and provide new insights into the biological underpinnings of metabolic dysfunction and antipsychotic treatment.

Opioid use disorder (OUD) and mental disorders are often comorbid, with increased morbidity and mortality. The causes underlying this relationship are poorly understood. Although these conditions are highly heritable, their shared genetic vulnerabilities remain unaccounted for. We applied the conditional/conjunctional false discovery rate (cond/conjFDR) approach to analyse summary statistics from independent genome wide association studies of OUD, SCZ, BD and MD. Next, we characterized the identified shared loci using biological annotation resources. OUD data was obtained from the Million Veteran Program (15,756 cases 99,039 controls). SCZ (53,386 cases 77,258 controls), BD (41,917 cases 371,549 controls) and MD (170,756 cases 329,443 controls) data was provided by the Psychiatric Genomics Consortium. We discovered genetic enrichment for OUD conditional on associations with SCZ, BD, MD and vice versa, indicating polygenic overlap with identification of 14 novel OUD loci at condFDRDRD2 on chromosome 11 (BD and MD), at FURIN on chromosome 15 (SCZ, BD and MD), and at the major histocompatibility complex region (SCZ and MD). Our findings provide new insights into the shared genetic architecture between OUD and SCZ, BD, and MD, indicating a complex genetic relationship, suggesting overlapping neurobiological pathways.

Alcohol use disorder (AUD) is a pervasive and devastating mental illness with high comorbidity rates with other mental disorders. We aimed to characterize the sharedvs. unique polygenicity of AUD, alcohol consumption (AC) and mood instability (MOOD), a relevant transdiagnostic factor, using large genome-wide association studies (GWASs) data. We hypothesize that cross-analyzing these phenotypes would shed light on their unique and shared polygenicity, increase our knowledge regarding the genetic basis of the comorbidity between AUD and mood disorders, and boost discovery for jointly-associated loci. Summary statistics for MOOD, AC and AUD GWASs (Ns =363,705; 200,680 and 200,004; respectively) were analysed to characterize the cross-phenotype associations between MOOD and AC, MOOD and AUD and AC and AUD, respectively. To do so, we used a newly-established pipeline that combines (i) the bivariate causal mixture model (MiXeR) to quantify the cross-phenotype polygenic overlap and (ii) the conjunctional false discovery rate (conjFDR) to discover specific jointly-associated genomic loci. These loci were functionally characterized and mapped to genes and biological functions. We also performed validation in independent samples and phenotypic analyses. MOOD was highly polygenic (10,400 single nucleotide polymorphisms, SNPs) compared to AC and AUD (4,900 SNPs, SD =600 and 4,300 SNPs, SD =2,000; respectively). The polygenic overlap of MOOD and AC was much larger than that of MOOD and AUD (98%vs. 49%) and genetic correlation was opposite (−0.2vs. 0.23), which was confirmed in independent samples. MOOD&AUD causal SNPs were significantly enriched for brain genes, conversely to MOOD&AC. Among 38 loci identified in the joint analysis, sixteen were novel for MOOD, AC and AUD. Similarly distinct patterns were evidenced for SNP localization, function and previous GWAS associations outside of the phenotypes that were currently studied. MOOD, AC and AUD were also strongly associated at the phenotypic level. Overall, using multilevel polygenic quantification, joint loci discovery and functional annotation methods, we evidenced that the polygenic overlap between MOOD and AC/AUD implicated shared biological underpinnings but clearly distinct functional patterns between MOOD&AC and MOOD&AUD. Using the MOOD endophenotype, the current study suggests new mechanisms for the comorbidity of AUD with mood disorders.

Personality and cognition are heritable mental traits, and their genetic determinants may be distributed across interconnected brain functions. However, previous studies have employed univariate approaches which reduce complex traits to summary measures. We applied the “pleiotropy-informed” multivariate omnibus statistical test (MOSTest) to genome-wide association studies (GWAS) of 35 item and task-level measures of neuroticism and cognition from the UK Biobank (n=336,993). We identified 431 significant genetic loci and found evidence of abundant pleiotropy across personality and cognitive domains. Functional characterisation implicated genes with significant tissue-specific expression in all tested brain tissues and enriched in brain-specific gene-sets. We conditioned independent GWAS of the Big 5 personality traits and cognition on our multivariate findings, which boosted genetic discovery in other personality traits and improved polygenic prediction. These findings advance our understanding of the polygenic architecture of complex mental traits, indicating a prominence of pleiotropic genetic effects across higher-order domains of mental function.Graphical abstract

To mitigate the risk of erosion and nutrient runoff, reduced tillage has become more prevalent in Norway. Within within recent decades, there have been some years with relatively high occurrence of Fusarium head blight and mycotoxins in Norwegian cereal grain. This is thought to have been caused by an increased inoculum potential (IP) of Fusarium spp. due to larger amount of crop residues remaining on the soil surface, in combination with weather conditions promoting fungal growth and infection of cereal plants. The objective of this work was to elucidate the influence of different tillage practices on the IP of Fusarium spp. and the subsequent Fusarium-infection and mycotoxin contamination of spring wheat grain at harvest. Tillage trials were conducted at two locations in southeast Norway (Solør and Toten) over three years, 2010-2012. Residues of wheat from the previous year were collected in spring. Fusarium avenaceum and Fusarium graminearum were the most common Fusarium species recorded on wheat straw residues. IP was calculated as the percentage of the residues infested with Fusarium spp. multiplied by the proportion of the soil surface covered with residues. The IP of Fusarium spp. was lower in ploughed plots compared to those tilled with harrowing only. Ploughing in spring resulted in a similarly low IP as autumn ploughing. In contrast, harrowing in autumn generally reduced IP more than did spring harrowing. The mycotoxin levels in the harvested wheat were generally low, except for deoxynivalenol at high levels in Solør 2011. Despite a lower IP of ploughed versus harrowed plots, this was not reflected in the content of Fusarium and mycotoxins in harvested grain. The Fusarium species that dominated in the residues examined in this study were the same as those detected in the harvested grain, supporting the finding that residues are an important source of inoculum.

Contamination of rainwater by pesticides has been investigated by analyzing samples from three locations in Norway: Lista,A˚s, and Tromso. The samples were taken weekly, when possible, during the periods June–September in 1992 and May–September in 1993. The samples were analyzed for nine pesticides, including the five herbicides MCPA, dichlorprop, atrazine, simazine, and ioxynil (1992), the fungicide propiconazole, and the insecticides lindane (γ-HCH), dimethoate, and cypermethrin (1992). Residues were found in the samples from Lista andA˚s. The samples from Tromso, however, showed no residues of any pesticide. A total of 520 analyses for Lista andA˚s were performed, and every tenth sample showed measurable residues. The highest concentrations (ng/l) measured for MCPA, dichlorprop, atrazine, and lindane were 320, 250, 86, and 84, respectively. The level of pesticides stated in the EEC-directive 80/778 for the quality of water intended for human consuption is 100 ng/l. This level was exceeded twice for the herbicides MCPA and dichlorprop. On average, total deposition of the pesticides in 1992–1993 was 2.4 times higher atA˚s than at Lista. Atrazine and lindane were often found in precipitation when the wind was blowing from the east. As these chemicals were taken off the market before this investigation began, it seems reasonable to conclude that long-distance transport is the probable cause.

The gas chromatography mass spectrometry (GC–MS) deconvolution reporting software (DRS) from Agilent Technologies has been evaluated for its ability as a screening tool to detect a large number of pesticides in incurred and fortified samples extracted with acetone/dichloromethane/light petroleum (Mini-Luke method). The detection of pesticides is based on fixed retention times using retention time locking (RTL) and full scan mass spectral comparison with a partly customer built automated mass spectral deconvolution and identification system (AMDIS) database. The GC–MS was equipped with a programmable temperature vaporising (PTV) injector system which enables more sample to be injected. In a blind study of 52 real samples a total number of 158 incurred pesticides were found. In addition to the 85 pesticides found by manual interpretation of GC–NPD/ECD chromatograms, the DRS revealed 73 more pesticides (+46%). The DRS system also shows its potential to discover pesticides which are normally not searched for (EPN in long beans from Thailand). A spiking experiment was performed to blank matrices of apple, orange and lettuce with 177 different pesticides at concentration levels 0.02 and 0.1 mg/kg. The samples were analysed on GC–MS full scan and the AMDIS match factor was used as a mass spectral quality criterion. The threshold level of the AMDIS match factor was set at 20 to eliminate most of the false positives. AMDIS match factors from 20 up to 69 are regarded only as indication of a positive hit and must be followed by manual interpretation. Pesticides giving AMDIS match factors at ≥70 are regarded as identified. To simplify and decrease the large amount of data generated at each concentration level, the AMDIS match factors ≥20 was averaged (mean AMF) for each pesticide including the commodities and their replicates. Among 177 different pesticides spiked at 0.02 and 0.1 mg/kg level, the percentage of mean AMF values ≥70 were 23% and 80%, respectively. For 531 individual detections of pesticides (177 pesticides × 3 replicates) giving AMDIS match factor 20 in apple, orange and lettuce, the detection rates at 0.02 mg/kg were 71%, 63% and 72%, respectively. For the 0.1 mg/kg level the detection rates were 89%, 85% and 89%, respectively. In real samples some manual interpretation must be performed in addition. However, screening by GC–MS/DRS is about 5–10 times faster compared to screening with GC–NPD/ECD because the time used for manual interpretation is much shorter and there is no need for re-injection on GC–MS for the identification of suspect peaks found on GC–NPD/ECD.

Low recoveries of selenium(IV) added to technical sulphuric acid were obtained, although recoveries from the Suprapur acid were satisfactory. It is assumed that this is due to the different reactivity of the selenium present in the technical acid and the selenium added as standards.

Different methods of atomization of selenium from a platinum wire filament are described, including electrothermal heating of the filament and atomlzation in an argon-hydrogen flame. A combination of these approaches proved to give the best sensitivity and detection limit. The selenium was preconcentrated on the filament by electrolysis prior to the atomic absorption measurements to eliminate chemical interferences and improve the sensitivity of the method. The detection limit was 0.5 μg l -1 for a 5-min electrolysis, and 0.2 μg l -1 when the electrolysis time was 30 min.

Electrochemical preconcentration on a platinum filament, followed by atomization in an argon—hydrogen flame with simultaneous electrothermal heating of the filament, is used for the determination of selenium in technical sulphuric acid. The effect of experimental parameters such as acid concentration, deposition potential and temperature are described, and the speciation of selenium in sulphuric acid is discussed. The technical acids were found to contain selenium in the range 30–60 μg l -1 .

The separation of eight common, structurally closely related sterols on C8 and C18 reversed-phase columns with UV-detection at 206 nm is described. Good separation was obtained in less than 18 min on the C18 column using methanol-water as mobile phase and a column temperature of 30 C. Except for brassicasterol and cholesterol, the sterols also were readily separated on the C8 column. Applications of the method on sterols from natural sources are described.

The esters of (22 R )-22-hydroxycholesterol from the flowers of N. ossifragum are monoesters, esterified in the 3β-position only. The main components are cholest-5-en-3β,22 R -diol 3-caprate (47 %) and cholest-5-en-3β,22 R diol 3-laurate (44 %). The sterol has not been found in the free state in the plant.