Gene-environment interactions explain a substantial portion of variability of common neuropsychiatric disorders

Oxygen-induced stress reveals context-specific gene regulatory effects in human brain organoids

The interaction between genetic variants and environmental stressors is key to understanding the mechanisms underlying neurological diseases. In this study, we used human brain organoids to explore how varying oxygen levels expose context-dependent gene regulatory effects. By subjecting a genetically diverse panel of 21 brain organoids to hypoxic and hyperoxic conditions, we identified thousands of gene regulatory changes that are undetectable under baseline conditions, with 1,745 trait-associated genes showing regulatory effects only in response to oxygen stress. To capture more nuanced transcriptional patterns, we employed topic modeling, which revealed context-specific gene regulation linked to dynamic cellular processes and environmental responses, offering a deeper understanding of how gene regulation is modulated in the brain. These findings underscore the importance of genotype-environment interactions in genetic studies of neurological disorders and provide new insights into the hidden regulatory mechanisms influenced by environmental factors in the brain.

Genetic and Environmental Factors Co-Contributing to Behavioral Abnormalities in adnp/adnp2 Mutant Zebrafish

Human mutations of ADNP and ADNP2 are known to be associated with neural developmental disorders (NDDs), including autism spectrum disorders (ASDs) and schizophrenia (SZ). However, the underlying mechanisms remain elusive. In this study, using CRISPR/Cas9 gene editing technology, we generated adnp and adnp2 mutant zebrafish models, which exhibited developmental delays, brain deficits, and core behavioral features of NDDs. RNA sequencing analysis of adnpa-/-; adnpb-/- and adnp2a-/-; adnp2b-/- larval brains revealed altered gene expression profiles affecting synaptic transmission, autophagy, apoptosis, microtubule dynamics, hormone signaling, and circadian rhythm regulation. Validation using whole-mount in situ hybridization (WISH) and real-time quantitative PCR (qRT-PCR) corroborated these findings, supporting the RNA-seq results. Additionally, loss of adnp and adnp2 resulted in significant downregulation of pan-neuronal HuC and neuronal fiber network α-Tubulin signals. Importantly, prolonged low-dose exposure to environmental endocrine disruptors (EEDs) aggravated behavioral abnormalities in adnp and adnp2 mutants. This comprehensive approach enhances our understanding of the complex interplay between genetic mutations and environmental factors in NDDs. Our findings provide novel insights and experimental foundations into the roles of adnp and adnp2 in neurodevelopment and behavioral regulation, offering a framework for future preclinical drug screening aimed at elucidating the pathogenesis of NDDs and related conditions.

Gene‒environment interaction effect of hypothalamic‒pituitary‒adrenal axis gene polymorphisms and job stress on the risk of sleep disturbances

Background

Studies have shown that chronic exposure to job stress may increase the risk of sleep disturbances and that hypothalamic‒pituitary‒adrenal (HPA) axis gene polymorphisms may play an important role in the psychopathologic mechanisms of sleep disturbances. However, the interactions among job stress, gene polymorphisms and sleep disturbances have not been examined from the perspective of the HPA axis. This study aimed to know whether job stress is a risk factor for sleep disturbances and to further explore the effect of the HPA axis gene × job stress interaction on sleep disturbances among railway workers.

Methods

In this cross-sectional study, 671 participants (363 males and 308 females) from the China Railway Fuzhou Branch were included. Sleep disturbances were evaluated with the Pittsburgh Sleep Quality Index (PSQI), and job stress was measured with the Effort-Reward Imbalance scale (ERI). Generalized multivariate dimensionality reduction (GMDR) models were used to assess gene‒environment interactions.

Results

We found a significant positive correlation between job stress and sleep disturbances (P < 0.01). The FKBP5 rs1360780-T and rs4713916-A alleles and the CRHR1 rs110402-G allele were associated with increased sleep disturbance risk, with adjusted ORs (95% CIs) of 1.75 [1.38-2.22], 1.68 [1.30-2.18] and 1.43 [1.09-1.87], respectively. However, the FKBP5 rs9470080-T allele was a protective factor against sleep disturbances, with an OR (95% CI) of 0.65 [0.51-0.83]. GMDR analysis indicated that under job stress, individuals with the FKBP5 rs1368780-CT, rs4713916-GG, and rs9470080-CT genotypes and the CRHR1 rs110402-AA genotype had the greatest risk of sleep disturbances.

Conclusions

Individuals carrying risk alleles who experience job stress may be at increased risk of sleep disturbances. These findings may provide new insights into stress-related sleep disturbances in occupational populations.

Shifting the trajectory of therapeutic development for neurological and psychiatric disorders

Clinical trials for central nervous system disorders often enroll patients with unrecognized heterogeneous diseases, leading to costly trials that have high failure rates. Here, we discuss the potential of emerging technologies and datasets to elucidate disease mechanisms and identify biomarkers to improve patient stratification and monitoring of disease progression in clinical trials for neuropsychiatric disorders. Greater efforts must be centered on rigorously standardizing data collection and sharing of methods, datasets, and analytical tools across sectors. To address health care disparities in clinical trials, diversity of genetic ancestries and environmental exposures of research participants and associated biological samples must be prioritized.

Does Morphine Exposure Before Gestation Change Anxiety-Like Behavior During Morphine Dependence in Male Wistar Rats?

Background

Anxiety is one of the comorbid disorders of opioid addiction, which leads to opioid abuse or persuades people to engage in opioid abuse. Evidence revealed that morphine exposure before conception changes the offspring's phenotype. The current study aimed to investigate the influence of morphine dependence and abstinence on anxiety-like behavior in morphine-exposed and drug-naïve offspring.

Methods

Adult male and female rats were treated with morphine or vehicle for 21 days. Then, all rats were left without drug treatment for 10 days. A morphine-exposed female rat was mated with either a vehicle-exposed or morphine-abstinent male. According to parental morphine exposure, the offspring were categorized into four distinct groups: (1) control (both drug-naïve parents), (2) paternal morphine-exposed, (3) maternal morphine-exposed, and (4) biparental morphine-exposed. The anxiety-like behavior was measured in adult male offspring using open field and elevated plus-maze tests before morphine exposure (naïve), 21 days after morphine exposure (dependence), and ten days after the last morphine exposure (abstinence).

Findings

The results indicated that anxiety-like behavior increased before morphine exposure in maternal and biparental morphine-exposed offspring (P<0.05). However, after morphine exposure, the anxiety level did not change among the groups. Ten days after the last morphine exposure, anxiety-like behavior increased only in biparental morphine-exposed offspring (P<0.05).

Conclusion

The offspring of morphine-abstinent parents exhibited an anxious phenotype. Disruption of the HPA axis was seen in the progeny of maternal and biparental morphine-exposed rats. Indeed, morphine exposure for 21 days did not change anxiety-like behavior in these offspring which might be correlated to disruption of HPA axis in them.

Digital Twins for Predictive, Preventive Personalized, and Participatory Treatment of Immune-Mediated Diseases

Digital twins are computational models of complex systems, which aim to understand and optimize those systems more effectively than would be possible in real life. Ideally, digital twins can be translated to individual patients, to characterize and computationally treat their diseases with thousands of drugs, to select the drug or drugs that cure the patients. The background problem is that many patients do not respond adequately to drug treatment. This problem reflects a wide gap between the complexity of diseases and clinical practice. Each disease may involve altered interactions between thousands of genes that vary between different cell types in different organs. To our knowledge, these altered interactions have not been characterized on a genome-, cellulome-, and organ-wide scale in any disease. Thus, clinical translation of the digital twin ideal for predictive, preventive, personalized and participatory treatment involves formidable challenges, which are close to the limits of, or beyond today's technologies. Here, I discuss recent developments and challenges in relation to that ideal focusing on immune-mediated inflammatory diseases, as well as examples from other diseases.