Dissecting the genetic and causal relationship between sleep-related traits and common brain disorders

BACKGROUND

There is a profound connection between abnormal sleep patterns and brain disorders, suggesting a shared influential association. However, the shared genetic basis and potential causal relationships between sleep-related traits and brain disorders are yet to be fully elucidated.

METHODS

Utilizing linkage disequilibrium score regression (LDSC) and bidirectional two-sample univariable Mendelian Randomization (UVMR) analyses with large-scale GWAS datasets, we investigated the genetic correlations and causal associations across six sleep traits and 24 prevalent brain disorders. Additionally, a multivariable Mendelian Randomization (MVMR) analysis evaluated the cumulative effects of various sleep traits on each brain disorder, complemented by genetic loci characterization to pinpoint pertinent genes and pathways.

RESULTS

LDSC analysis identified significant genetic correlations in 66 out of 144 (45.8 %) pairs between sleep-related traits and brain disorders, with the most pronounced correlations observed in psychiatric disorders (66 %, 48/72). UVMR analysis identified 29 causal relationships (FDR<0.05) between sleep traits and brain disorders, with 19 associations newly discovered according to our knowledge. Notably, major depression, attention-deficit/hyperactivity disorder, bipolar disorder, cannabis use disorder, and anorexia nervosa showed bidirectional causal relations with sleep traits, especially insomnia's marked influence on major depression (IVW beta 0.468, FDR = 5.24E-09). MVMR analysis revealed a nuanced interplay among various sleep traits and their impact on brain disorders. Genetic loci characterization underscored potential genes, such as HOXB2, while further enrichment analyses illuminated the importance of synaptic processes in these relationships.

CONCLUSIONS

This study provides compelling evidence for the causal relationships and shared genetic backgrounds between common sleep-related traits and brain disorders.

Chimeric vaccine design against the epidemic Langya Henipavirus using immunoinformatics and validation via immune simulation approaches

In July 2022, a new virus called Langya virus (LayV) was discovered in China in patients who had a fever. This virus is a type of Henipavirus (HNV) and is considered a potential threat as it could spread from animals to humans. It causes respiratory disease with symptoms including fever, coughing, and fatigue and is closely linked to two other henipaviruses that are known to infect humans, namely Hendra and Nipah viruses. These viruses may cause fatal respiratory illnesses. Investigators believe that the LayV is spread by shrews, and may have infected humans directly or via an intermediary species. Thus, the use of vaccines or immunizations against LayV is an alternate strategy for disease prevention. In this study, we employed various immunoinformatics methods to predict B cell, HTL and T cell epitopes from the LayV proteome in order to find the most promising candidate for a LayV vaccine. The most potent epitopes that are immunogenic and non-allergenic were joined with each other through suitable linkers. Human β-defensin 2 was employed as an adjuvant to increase the immunogenicity of the vaccine construct. The final sequence of a multi-epitope vaccine construct was modelled for docking with TLRs. Concisely, our results suggest that the docked complexes of vaccine-TLRs seemed to be stable. Additionally, in silico cloning was done using E. coli as the host in order to validate the expression of our designed vaccine construct. The GC content of 54.39% and CAI value of 0.94 revealed that the vaccine component expresses efficiently in the host. This study presents the novel vaccine construct for LayV which will be essential for further experimental validations to confirm the immunogenicity and safety of the proposed vaccine structure, and eventually to treat HNV-related diseases.

Structural Comparison and Drug Screening of Spike Proteins of Ten SARS-CoV-2 Variants

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) has evolved many variants with stronger infectivity and immune evasion than the original strain, including Alpha, Beta, Gamma, Delta, Epsilon, Kappa, Iota, Lambda, and 21H strains. Amino acid mutations are enriched in the spike protein of SARS-CoV-2, which plays a crucial role in cell infection. However, the impact of these mutations on protein structure and function is unclear. Understanding the pathophysiology and pandemic features of these SARS-CoV-2 variants requires knowledge of the spike protein structures. Here, we obtained the spike protein structures of 10 main globally endemic SARS-CoV-2 strains using AlphaFold2. The clustering analysis based on structural similarity revealed the unique features of the mainly pandemic SARS-CoV-2 Delta variants, indicating that structural clusters can reflect the current characteristics of the epidemic more accurately than those based on the protein sequence. The analysis of the binding affinities of ACE2-RBD, antibody-NTD, and antibody-RBD complexes in the different variants revealed that the recognition of antibodies against S1 NTD and RBD was decreased in the variants, especially the Delta variant compared with the original strain, which may induce the immune evasion of SARS-CoV-2 variants. Furthermore, by virtual screening the ZINC database against a high-accuracy predicted structure of Delta spike protein and experimental validation, we identified multiple compounds that target S1 NTD and RBD, which might contribute towards the development of clinical anti-SARS-CoV-2 medicines. Our findings provided a basic foundation for future in vitro and in vivo investigations that might speed up the development of potential therapies for the SARS-CoV-2 variants.

Structural Analysis of the SARS-CoV-2 Omicron Variant Proteins

The spread of the latest SARS-CoV-2 variant Omicron is particularly concerning because of the large number of mutations present in its genome and lack of knowledge about how these mutations would affect the current SARS-CoV-2 vaccines and treatments. Here, by performing phylogenetic analysis using the Omicron spike (S) protein sequence, we found that the Omicron S protein presented the longest evolutionary distance in relation to the other SARS-CoV-2 variants. We predicted the structures of S, M, and N proteins of the Omicron variant using AlphaFold2 and investigated how the mutations have affected the S protein and its parts, S1 NTD and RBD, in detail. We found many amino acids on RBD were mutated, which may influence the interactions between the RBD and ACE2, while also showing the S309 antibody could still be capable of neutralizing Omicron RBD. The Omicron S1 NTD structures display significant differences from the original strain, which could lead to reduced recognition by antibodies resulting in potential immune escape and decreased effectiveness of the existing vaccines. However, this study of the Omicron variant was mainly limited to structural predictions, and these findings should be explored and verified by subsequent experiments. This study provided basic data of the Omicron protein structures that lay the groundwork for future studies related to the SARS-CoV-2 Omicron variant.

Elevated levels of IL-18 associated with schizophrenia and first episode psychosis: A systematic review and meta-analysis

AIM

To determine whether interleukin 18 (IL-18) is elevated in the blood of schizophrenia (SCZ) and first episode psychosis patients, as well as investigate whether this potential relationship is causal.

METHOD

We conducted a systematic review and meta-analysis of IL-18 levels in the blood of SCZ patients, comprising of both chronic and first episode psychosis (FEP) cohorts. To investigate causality, we undertook the two-sample Mendelian randomization (MR) study.

RESULTS

A total of eight studies were included in our meta-analysis, our results did indeed show an association between elevated levels of IL-18 and SCZ compared to healthy controls (Z = 3.50, P = .0005). This association remained significant in subsequent subgroup analyses for chronic (Z = 3.15, P = .002) and achieved borderline significance in FEP (Z = 1.93, P = .05) SCZ. Our MR analysis failed to detect any causal relationship between IL-18 levels and SCZ.

CONCLUSION

The results of our study demonstrate that even though IL-18 levels are elevated in SCZ patients, IL-18 levels do not seem to cause of the disorder itself. Our findings suggest that IL-18 may have utility as a biomarker of SCZ and aid in research into the early intervention of the disease.

Testosterone in Female Depression: A Meta-Analysis and Mendelian Randomization Study

Testosterone's role in female depression is not well understood, with studies reporting conflicting results. Here, we use meta-analytical and Mendelian randomization techniques to determine whether serum testosterone levels differ between depressed and healthy women and whether such a relationship is casual. Our meta-analysis shows a significant association between absolute serum testosterone levels and female depression, which remains true for the premenopausal group while achieving borderline significance in the postmenopausal group. The results from our Mendelian randomization analysis failed to show any causal relationship between testosterone and depression. Our results show that women with depression do indeed display significantly different serum levels of testosterone. However, the directions of the effect of this relationship are conflicting and may be due to menopausal status. Since our Mendelian randomization analysis was insignificant, the difference in testosterone levels between healthy and depressed women is most likely a manifestation of the disease itself. Further studies could be carried out to leverage this newfound insight into better diagnostic capabilities culminating in early intervention in female depression.

The Potential Effect of Aberrant Testosterone Levels on Common Diseases: A Mendelian Randomization Study

Testosterone has historically been linked to sexual dysfunction; however, it has recently been shown to affect other physical and mental attributes. We attempted to determine whether changes in serum testosterone could play a role in chronic or degenerative diseases. We used two separate genetic instruments comprising of variants from JMJD1C and SHBG regions and conducted a two-sample Mendelian randomization for type II diabetes (T2D), gout, rheumatoid arthritis (RA), schizophrenia, bipolar disorder, Alzheimer’s disease and depression. For the JMJD1C locus, one unit increase in log transformed testosterone was significantly associated with RA (OR = 1.69, p = 0.02), gout (OR = 0.469, p = 0.001) and T2D (OR = 0.769, p = 0.048). Similarly, one unit increase in log transformed testosterone using variants from the SHBG locus was associated with depression (OR = 1.02, p = 0.001), RA (OR = 1.32, p < 0.001) and T2D (OR = 0.88, p = 0.003). Our results show that low levels of serum testosterone levels may cause gout and T2D, while higher than normal levels of testosterone may result in RA and depression. Our findings suggest that fluctuations in testosterone levels may have severe consequences that warrant further investigation.