Association between plasma proteome and childhood neurodevelopmental disorders: A two-sample Mendelian randomization analysis

Association of cancer and schizophrenia, major depression and bipolar disorder: A Mendelian randomization study

BACKGROUND

Schizophrenia, bipolar disorder and major depression have been reported to be associated with some cancers. However, the magnitude of the causal relationship between them remains unclear. This study aims to explore the potential association between three major mental diseases and the risk of some cancers.

METHODS

We performed the two-sample Mendelian randomization(MR) analysis using publicly available genome-wide association studies (GWAS) statistics to investigate the causal relationship between these three mental diseases and some common types of cancers, including breast cancer, ovarian cancer, lung cancer, colorectal cancer, bladder cancer, prostate cancer, thyroid cancer, pancreatic cancer, malignant melanoma and glioma. We obtained genetic association estimates for schizophrenia, bipolar disorder and depression from the Psychiatric Genomics Consortium.The genetic association estimates for cancers were obtained from the UK Biobank, the MRC-IEU consortium and the GliomaScan consortium.

RESULTS

After correction for heterogeneity and horizontal pleiotropy, we detected suggestive evidence for the association between thyroid cancer and genetically predicted schizophrenia (OR = 1.543, 95% CI: 1.023-2.328, P = 0.039), and thyroid cancer and major depression (OR = 3.573, 95% CI: 1.068-11.953, P = 0.039). No evidence of causal effects of schizophrenia, major depression and bipolar disorder on other types of cancers.

CONCLUSIONS

Our findings suggest the association of schizophrenia and major depression and the development of thyroid cancer.

Gut microbiota linked to hydrocephalus through inflammatory factors: a Mendelian randomization study

Background

The gut microbiota (GM) has been implicated in neurological disorders, but the relationship with hydrocephalus, especially the underlying mechanistic pathways, is unclear. Using Mendelian randomization (MR), we aim to discover the mediating role of inflammatory factors in the relationship between GM and hydrocephalus.

Methods

After removing confounders, univariable and multivariable MR analyses were performed using summary statistics to assess the causal relationships between GM, inflammatory factors (IL-17A and IL-27), and types of hydrocephalus. Meta-analyses were used to reconcile the differences in MR results between different hydrocephalus sources. Finally, mediator MR analyses were applied to determine the mediating effect of inflammatory factors. Various sensitivity analysis methods were employed to ensure the reliability and stability of the results.

Results

After correction for P-values, Firmicutes (phylum) (OR, 0.34; 95%CI, 0.17-0.69; P = 2.71E-03, P FDR = 2.44E-02) significantly reduced the risk of obstructive hydrocephalus. The remaining 18 different taxa of GM had potential causal relationships for different types of hydrocephalus. In addition, Firmicutes (phylum) decreased the risk of obstructive hydrocephalus by increasing levels of IL-17A (mediating effect = 21.01%), while Eubacterium ruminantium group (genus) increased the risk of normal-pressure hydrocephalus by decreasing levels of IL-27 (mediating effect = 7.48%).

Conclusion

We reveal the connection between GM, inflammatory factors (IL-17A and IL-27), and hydrocephalus, which lays the foundation for unraveling the mechanism between GM and hydrocephalus.

Role of circulating inflammatory protein in the development of diabetic renal complications: proteome-wide Mendelian randomization and colocalization analyses

Background

Diabetes ranks among the most widespread diseases globally, with the kidneys being particularly susceptible to its vascular complications. The identification of proteins for pathogenesis and novel drug targets remains imperative. This study aims to investigate roles of circulating inflammatory proteins in diabetic renal complications.

Methods

Data on the proteins were derived from a genome-wide protein quantitative trait locus (pQTL) study, while data on diabetic renal complications came from the FinnGen study. In this study, proteome-wide Mendelian randomization (MR) and colocalization analyses were used to assess the relationship between circulating inflammatory proteins and diabetic renal complications.

Results

MR approach indicated that elevated levels of interleukin 12B (IL-12B) (OR 1.691, 95%CI 1.179-2.427, P=4.34×10-3) and LIF interleukin 6 family cytokine (LIF) (OR 1.349, 95%CI 1.010-1.801, P=4.23×10-2) increased the risk of type 1 diabetes (T1D) with renal complications, while higher levels of fibroblast growth factor 19 (FGF19) (OR 1.202, 95%CI 1.009-1.432, P=3.93×10-2), fibroblast growth factor 23 (FGF23) (OR 1.379, 95%CI 1.035-1.837, P=2.82×10-2), C-C motif chemokine ligand 7 (CCL7) (OR 1.385, 95%CI 1.111-1.725, P=3.76×10-3), and TNF superfamily member 14 (TNFSF14) (OR 1.244, 95%CI 1.066-1.451, P=5.63×10-3) indicated potential risk factors for type 2 diabetes (T2D) with renal complications. Colocalization analysis supported these findings, revealing that most identified proteins, except for DNER, likely share causal variants with diabetic renal complications.

Conclusion

Our study established associations between specific circulating inflammatory proteins and the risk of diabetic renal complications, suggesting these proteins as targets for further investigation into the pathogenesis and potential therapeutic interventions for T1D and T2D with renal complications.

Mendelian randomization analysis of the brain, cerebrospinal fluid, and plasma proteome identifies potential drug targets for attention deficit hyperactivity disorder

BACKGROUND

The need for new therapeutics for attention deficit hyperactivity disorder (ADHD) is evident. Brain, cerebrospinal fluid (CSF), and plasma protein biomarkers with causal genetic evidence could represent potential drug targets. However, a comprehensive screen of the proteome has not yet been conducted.

METHODS

We employed a three-pronged approach using Mendelian Randomization (MR) and Bayesian colocalization analysis. Firstly, we studied 608 brains, 214 CSF, and 612 plasma proteins as potential causal mediators of ADHD using MR analysis. Secondly, we analysed the consistency of the discovered biomarkers across three distinct subtypes of ADHD: childhood, persistent, and late-diagnosed ADHD. Finally, we extended our analysis to examine the correlation between identified biomarkers and Tourette syndrome and pervasive autism spectrum disorder (ASD), conditions often linked with ADHD. To validate the MR findings, we conducted sensitivity analysis. Additionally, we performed cell type analysis on the human brain to identify risk genes that are notably enriched in various brain cell types.

FINDINGS

After applying Bonferroni correction, we found that the risk of ADHD was increased by brain proteins GMPPB, NAA80, HYI, CISD2, and HYI, TIE1 in CSF and plasma. Proteins GMPPB, NAA80, ICA1L, CISD2, TIE1, and RMDN1 showed overlapped loci with ADHD risk through Bayesian colocalization. Overexpression of GMPPB protein was linked to an increase in the risk for all three ADHD subtypes. While ICA1L provided protection against both ASD and ADHD, CISD2 increased the probability of both disorders. Cell-specific studies revealed that GMPPB, NAA80, ICA1L, and CISD2 were predominantly present on the surface of excitatory-inhibitory neurons.

INTERPRETATION

Our comprehensive MR investigation of the brain, CSF, and plasma proteomes revealed seven proteins with causal connections to ADHD. Particularly, GMPPB and TIE1 emerged as intriguing targets for potential ADHD therapy.

FUNDING

This work was partly funded by the Key R & D Program of Zhejiang (T.L. 2022C03096); the National Natural Science Foundation of China Project (C.Z. 82001413); Postdoctoral Foundation of West China Hospital (C.Z. 2020HXBH163).

Mendelian randomization of circulating proteome identifies IFN-γ as a druggable target in aplastic anemia

BACKGROUND

Aplastic anemia (AA) is a kind of bone marrow failure (BMF) characterized by pancytopenia with hypoplasia/aplasia of bone marrow. Immunosuppressive therapy and bone marrow transplantation are effective methods to treat severe aplastic anemia. However, the efficacy is limited by complications and the availability of suitable donors. This study aimed to determine whether any circulating druggable protein levels may have causal effects on AA and provide potential novel drug targets for AA.

METHODS

Genetic variants strongly associated with circulating druggable protein levels to perform Mendelian randomization (MR) analyses were used. The effect of these druggable protein levels on AA risk was measured using the summary statistics from a large-scale proteomic genome-wide association study (GWAS) and FinnGen database ( https://www.finngen.fi/en/access_results ). Multivariable MR analyses were performed to statistically adjust for potential confounders, including platelet counts, reticulocyte counts, neutrophil counts, and proportions of hematopoietic stem cells.

RESULTS

The data showed that higher level of circulating IFN-γ levels was causally associated with AA susceptibility. The causal effects of circulating IFN-γ levels on the AA were broadly consistent, when adjusted for platelet counts, reticulocyte counts, neutrophil counts and proportions of hematopoietic stem cells.

CONCLUSIONS

High levels of circulating IFN-γ levels might increase the risk of AA and might provide a potential novel target for AA.

Blood metabolites and chronic kidney disease: a Mendelian randomization study

BACKGROUND

Human blood metabolites have demonstrated close associations with chronic kidney disease (CKD) in observational studies. Nonetheless, the causal relationship between metabolites and CKD is still unclear. This study aimed to assess the associations between metabolites and CKD risk.

METHODS

We applied a two-sample Mendelian randomization (MR) analysis to evaluate relationships between 1400 blood metabolites and eight phenotypes (outcomes) (CKD, estimated glomerular filtration rate(eGFR), urine albumin to creatinine ratio, rapid progress to CKD, rapid decline of eGFR, membranous nephropathy, immunoglobulin A nephropathy, and diabetic nephropathy). The inverse variance weighted (IVW), MR-Egger, and weighted median were used to investigate the causal relationship. Sensitivity analyses were performed with Cochran's Q, MR-Egger intercept, MR-PRESSO Global test, and leave-one-out analysis. Bonferroni correction was used to test the strength of the causal relationship.

RESULTS

Through the MR analysis of 1400 metabolites and eight clinical phenotypes, a total of 48 metabolites were found to be associated with various outcomes. Among them, N-acetylleucine (OR = 0.923, 95%CI: 0.89-0.957, PIVW = 1.450 × 10-5) has a strong causal relationship with lower risk of CKD after the Bonferroni-corrected test, whereas Glycine to alanine ratio has a strong causal relationship with higher risk of CKD (OR = 1.106, 95%CI: 1.063-1.151, PIVW = 5.850 × 10-7). No horizontal pleiotropy and heterogeneity were detected.

CONCLUSION

Our study offers groundbreaking insights into the integration of metabolomics and genomics to reveal the pathogenesis of and therapeutic strategies for CKD. It underscores 48 metabolites as potential causal candidates, meriting further investigation.

[Advances in Mendelian randomization studies on autism spectrum disorder]

Autism spectrum disorder (ASD) is a pervasive neurodevelopmental disorder with onset in infancy or early childhood. Mendelian randomization (MR) is a statistical method used to infer causal relationships between exposures and outcomes. This article summarizes MR studies related to ASD. Existing research supports a causal relationship between maternal inflammatory bowel disease in children with ASD, parental education levels, screen time exposure, obesity, insomnia, serum transferrin, decreased blood selenium, abnormal signals in brain functional MRI, interleukin-6, phosphodiesterase 2A, mitogen-activated protein kinase kinase 3, mitochondrial ribosomal protein L33, serotonin, and ASD. However, it does not support a causal relationship between parental rheumatoid arthritis, systemic lupus erythematosus, neonatal jaundice in children with ASD, cytomegalovirus infection, asthma, oral ulcers, vitamin D levels, and ASD. This article reviews the etiological factors related to ASD and MR studies, aiming to explore and deepen the understanding of the pathophysiology of ASD. It provides strong statistical support for the prevention, diagnosis, and treatment of ASD, and offers new methods and strategies for the etiological analysis of complex traits.

Pediatric massage therapy for treatment of tic disorders in children: A systematic review and meta-analysis of randomized controlled trials

BACKGROUND

Tic disorder is a common neurodevelopmental disorder in childhood, characterized primarily by motor or vocal tics. However, there is no systematic evaluation of pediatric massage therapy for children with Tic disorder. This study aims to evaluate the effectiveness and safety of massage therapy for children with tic disorder through a comprehensive meta-analysis and systematic review.

METHODS

We systematically searched relevant randomized controlled trials from various databases such as CBM, CNKI, VIP, Wanfang database, PubMed, Embase, Web of Science, Cochrane Library, and SINOMED, published up to October 2023. To collect randomized controlled trials on pediatric massage therapy or in combination with other therapies for the treatment of tic disorders in children. The risk of bias in the included articles was assessed using the Cochrane guideline. Meta-analyses were performed using Review Manager 5.4, and publication bias was evaluated by using Begg test and Egger test in Stata SE software.

RESULTS

This meta-analysis included 19 randomized controlled trials with 1423 patients. Pediatric massage therapy alone or in combination with conventional medication demonstrated a significant increase in clinical effectiveness rates [risk ratios = 1.15, 95% confidence interval [CI] (1.10, 1.20), Z = 6.54, P < .001], and reduced Yale Global Tie Severity Scale scores [standardized mean difference = -0.85, 95% CI (-1.50, -0.19), Z = 2.54, P = .01] and traditional Chinese medicine syndrome scores [standardized mean difference = -1.35, 95%CI (-2.08, -0.63), Z = 3.66, P = .0002]. In terms of adverse reactions, there was no statistical difference between the experimental and control groups [risk ratios = 0.26, 95% CI (0.14, 0.49), Z = 4.25, P < .001]. The Begg test and Egger test results indicated no publication bias.

CONCLUSION

Evidence suggests that pediatric massage therapy is effective in improving tic disorders in children.

Autism spectrum disorder: pathogenesis, biomarker, and intervention therapy

Autism spectrum disorder (ASD) has become a common neurodevelopmental disorder. The heterogeneity of ASD poses great challenges for its research and clinical translation. On the basis of reviewing the heterogeneity of ASD, this review systematically summarized the current status and progress of pathogenesis, diagnostic markers, and interventions for ASD. We provided an overview of the ASD molecular mechanisms identified by multi-omics studies and convergent mechanism in different genetic backgrounds. The comorbidities, mechanisms associated with important physiological and metabolic abnormalities (i.e., inflammation, immunity, oxidative stress, and mitochondrial dysfunction), and gut microbial disorder in ASD were reviewed. The non-targeted omics and targeting studies of diagnostic markers for ASD were also reviewed. Moreover, we summarized the progress and methods of behavioral and educational interventions, intervention methods related to technological devices, and research on medical interventions and potential drug targets. This review highlighted the application of high-throughput omics methods in ASD research and emphasized the importance of seeking homogeneity from heterogeneity and exploring the convergence of disease mechanisms, biomarkers, and intervention approaches, and proposes that taking into account individuality and commonality may be the key to achieve accurate diagnosis and treatment of ASD.

Genetic insights into associations of multisite chronic pain with common diseases and biomarkers using data from the UK Biobank

BACKGROUND

Chronic pain is a common, complex, and challenging condition, for which specialised healthcare is required. We investigated the relationship between multisite chronic pain (MCP) and different disease traits identify safe biomarker interventions that can prevent MCP.

METHODS

Univariable and multivariable Mendelian randomisation (MR) analysis were conducted to investigate associations between MCP and 36 common diseases in the UK Biobank. Subsequently, we estimated the potential effect of expression of 4774 proteins on MCP utilising existing plasma protein quantitative trait locus data. For the significant biomarkers, we performed phenome-wide MR (Phe-MR) with 1658 outcomes to predict potential safety profiles linked to biomarker intervention.

RESULTS

Multisite chronic pain had a substantial impact on psychiatric and neurodevelopmental traits (major depression and attention deficit hyperactivity disorder), cardiovascular diseases (myocardial infarction, coronary artery disease, and heart failure), respiratory outcomes (asthma, chronic obstructive pulmonary disease, and sleep apnoea), arthropathies, type 2 diabetes mellitus, and cholelithiasis. Higher genetically predicted levels of S100A6, DOCK9, ferritin, and ferritin light chain were associated with a risk of MCP, whereas PTN9 and NEUG were linked to decreased MCP risk. Phe-MR results suggested that genetic inhibition of DOCK9 increased the risk of 21 types of disease, whereas the other biomarker interventions were relatively safe.

CONCLUSIONS

We established that MCP has an effect on health conditions covering various physiological systems and identified six novel biomarkers for intervention. In particular, S100A6, PTN9, NEUG, and ferritin light chain represent promising targets for MCP prevention, as no significant side-effects were predicted in our study.

Exploring Causal Relationships between Leukocyte Telomere Length, Sex Hormone-Binding Globulin Levels, and Osteoporosis Using Univariable and Multivariable Mendelian Randomization

OBJECTIVE

Recent evidence supports that leukocyte telomere length (LTL) may be positively associated with healthy living and inversely correlated with the risk of age-related diseases, including osteoporosis. Furthermore, it is important to note that sex hormone-binding globulin (SHBG) levels play a crucial role in the regulation of osteoporosis by influencing the availability of sex hormones. Hence, this study holds significant importance as it aims to unravel the roles of LTL and SHBG levels and determine which one acts as a predominant intermediary factor in influencing osteoporosis. Using Mendelian randomization (MR), we can gain valuable insights into the intricate relationships between aging, sex hormones, and bone health.

METHODS

Univariable and multivariable and MR analyses were employed in this study. First, we used genetic variants associated with both LTL, as determined from a study involving 472,174 European participants by Codd et al., and SHBG levels, as identified in a study conducted by Ruth et al. with 370,125 participants, as instrumental variables (IVs). Then we aimed to establish a causal relationship between LTL and SHBG levels and their potential impact on osteoporosis using univariable MR. Finally, we conducted multivariable MR to provide insights into the independent and combined effects of LTL, SHBG levels on osteoporosis risk. We used various MR methods, with the primary analysis employing the inverse-variance weighted (IVW) model.

RESULTS

Univariable MR analysis reveals a potential causal effect of longer LTL on reduced risk of osteoporosis [odds ratio (OR): 0.85; 95% confidence interval (CI): 0.73-0.99; p = 0.03]. Conversely, higher genetically determined SHBG levels affect the risk of osteoporosis positively. (OR: 1.38; 95% CI: 1.09-1.75; p < 0.01). We observed a negative causal effect for LTL on the occurrence of SHBG (OR: 0.96; 95% CI 0.94-0.98, p < 0.01). After adjustment of using multivariable MR, the causal effect of LTL on osteoporosis (OR: 0.92; 95% CI: 0.84-1.03; p = 0.14), and the effect of SHBG on osteoporosis (OR: 1.43; 95% CI: 1.16-1.75; p < 0.01) were observed.

CONCLUSION

Longer LTL may confer a protective effect against osteoporosis. Additionally, the levels of SHBG appear to play a crucial role in mediating the relationship between LTL and osteoporosis. By understanding the interplay between these factors, we can gain valuable insights into the mechanisms underlying bone health and aging and potentially identify new avenues for prevention and intervention strategies.

Relationship between autism and brain cortex surface area: genetic correlation and a two-sample Mendelian randomization study

BACKGROUND

Alterations in surface area (SA) in specific regions of the cortex have been reported in many individuals with autism spectrum disorder (ASD), however, the genetic background between ASD and SA is still unclear. This study estimated the genetic correlation and causal effect of ASD and cortical SA.

METHODS

Summarized data of genome-wide association studies (GWAS) were separately downloaded from the Psychiatric Genomics Consortium (18,381 cases of ASD, and 27,969 controls) and the Enhancing Neuroimaging Genetics through Meta-Analysis Consortium (33,992 participants of Europeans). We used Linkage disequilibrium score regression (LDSC) and Heritability Estimation from Summary Statistics (HESS) to calculate the heritability of each trait. As for the genetic correlation between ASD and SA, LDSC was used for global correlation and HESS was used to examine the local genetic covariance further. We used three Mendelian randomization (MR) methods, Inverse-variance weighted, MR-Egger, and weighted median to estimate the causal relationship.

RESULTS

LDSC observed a nominal significant genetic correlation (rg = 0.1229, P-value = 0.0346) between ASD and SA of the rostral anterior cingulate gyrus whereas analysis through HESS did not reveal any significant loci having genetic covariance. Based on MR results, statistically meaningful estimations were found in the following areas, postcentral cortex (β (SE) = 21.82 (7.84) mm, 95% CI: 6.46 to 37.19 mm, PIVW = 5.38 × 10- 3, PFDR = 3.09 × 10- 2), posterior cingulate gyrus (β (SE) = 6.23 (2.69) mm, 95% CI: 0.96 to 11.49 mm, PIVW = 2.05 × 10- 2, PFDR = 4.26 × 10- 2), supramarginal gyrus (β (SE) = 19.25 (8.43) mm, 95% CI: 29.29 to 35.77 mm, PIVW = 2.24 × 10- 2, PFDR = 4.31 × 10- 2).

CONCLUSION

Our results provided genetic evidence to support the opinion that individuals with ASD tend to develop differences in cortical SA of special areas. The findings contributed to understanding the genetic relationship between ASD and cortical SA.

Prenatal prevalence and postnatal manifestations of 16p11.2 deletions: A new insights into neurodevelopmental disorders based on clinical investigations combined with multi-omics analysis

BACKGROUND

The 16p11.2 deletion is one of the most common genetic aetiologies of neurodevelopmental disorders (NDDs). The prenatal phenotype of 16p11.2 deletion and the potential mechanism associated with postnatal clinical manifestations were largely unknow. We revealed the developmental trajectories of 16p11.2 deletion from the prenatal to postnatal periods and to identify key signaling pathways and candidate genes contributing to neurodevelopmental abnormalities.

METHODS

In this 5-y retrospective cohort study, women with singleton pregnancies who underwent amniocentesis for chromosomal abnormalities were included. Test of copy-number variations (CNVs) involved single nucleotide polymorphism-array and CNV-seq was performed to detected 16p11.2 deletion. For infants born carrying the 16p11.2 deletion, neurological and intellectual evaluations using the Chinese version of the Gesell Development Scale. For patients observed to have vertebral malformations, Sanger sequencing for T-C-A haplotype of TBX6 was performed. For those infants with clinical manifestations, whole-exome sequencing was consecutively performed in trios to rule out single-gene diseases, and transcriptomics combined with untargeted metabolomics were performed.

RESULTS

The prevalence of 16p11.2 deletion was 0.063% (55/86,035) in the prenatal period. Up to 80% (20/25) of the 16p11.2 deletions were proven de novo by parental confirmation. Approximately half of 16p11.2 deletions (28/55) were detected with prenatal abnormal ultrasound findings. Vertebral malformations were identified as the most distinctive structural malformations and were enriched in fetuses with 16p11.2 deletions compared with controls (90.9‰ [5/55] vs. 8.4‰ [72/85,980]; P < 0.001). All 5 fetuses with vertebral malformations were confirmed to have the TBX6 haplotype of T-C-A. Overall, 47.6% (10/21) infants birthed were diagnosed with NDDs of different degrees. Language impairment was the predominant manifestation (7/10; 70.0%), followed by motor delay (5/10; 50%). Multi-omics analysis indicated that MAPK3 was the central hub of the differentially expressed gene (DEG) network. We firstly reported that histidine-associated metabolism may be the core metabolic pathway related to the 16p11.2 deletion.

CONCLUSION

We demonstrated the prenatal presentation, incomplete penetrance and variable expressivity of the 16p11.2 deletion. We identified vertebral malformations were the most distinctive prenatal phenotypes, and language impairment was the predominant postnatal manifestation. Most of the 16p11.2 deletion was de novo. Meanwhile, we suggested that MAPK3 and histidine-associated metabolism may contribute to neurodevelopmental abnormalities of 16p11.2 deletion.

Multiomic approach and Mendelian randomization analysis identify causal associations between blood biomarkers and subcortical brain structure volumes

Alterations in subcortical brain structure volumes have been found to be associated with several neurodegenerative and psychiatric disorders. At the same time, genome-wide association studies (GWAS) have identified numerous common variants associated with brain structure. In this study, we integrate these findings, aiming to identify proteins, metabolites, or microbes that have a putative causal association with subcortical brain structure volumes via a two-sample Mendelian randomization approach. This method uses genetic variants as instrument variables to identify potentially causal associations between an exposure and an outcome. The exposure data that we analyzed comprised genetic associations for 2994 plasma proteins, 237 metabolites, and 103 microbial genera. The outcome data included GWAS data for seven subcortical brain structure volumes including accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. Eleven proteins and six metabolites were found to have a significant association with subcortical structure volumes, with nine proteins and five metabolites replicated using independent exposure data. We found causal associations between accumbens volume and plasma protease c1 inhibitor as well as strong association between putamen volume and Agouti signaling protein. Among metabolites, urate had the strongest association with thalamic volume. No significant associations were detected between the microbial genera and subcortical brain structure volumes. We also observed significant enrichment for biological processes such as proteolysis, regulation of the endoplasmic reticulum apoptotic signaling pathway, and negative regulation of DNA binding. Our findings provide insights to the mechanisms through which brain volumes may be affected in the pathogenesis of neurodevelopmental and psychiatric disorders and point to potential treatment targets for disorders that are associated with subcortical brain structure volumes.

Integrative analysis of long noncoding RNAs dysregulation and synapse-associated ceRNA regulatory axes in autism

Autism spectrum disorder (ASD) is a complex disorder of neurodevelopment, the function of long noncoding RNA (lncRNA) in ASD remains essentially unknown. In the present study, gene networks were used to explore the ASD disease mechanisms integrating multiple data types (for example, RNA expression, whole-exome sequencing signals, weighted gene co-expression network analysis, and protein-protein interaction) and datasets (five human postmortem datasets). A total of 388 lncRNAs and five co-expression modules were found to be altered in ASD. The downregulated co-expression M4 module was significantly correlated with ASD, enriched with autism susceptibility genes and synaptic signaling. Integrating lncRNAs from the M4 module and microRNA (miRNA) dysregulation data from the literature identified competing endogenous RNA (ceRNA) network. We identified the downregulated mRNAs that interact with miRNAs by the miRTarBase, miRDB, and TargetScan databases. Our analysis reveals that MIR600HG was downregulated in multiple brain tissue datasets and was closely associated with 9 autism-susceptible miRNAs in the ceRNA network. MIR600HG and target mRNAs (EPHA4, MOAP1, MAP3K9, STXBP1, PRKCE, and SCAMP5) were downregulated in the peripheral blood by quantitative reverse transcription polymerase chain reaction analysis (false discovery rate <0.05). Subsequently, we assessed the role of lncRNA dysregulation in altered mRNA levels. Experimental verification showed that some synapse-associated mRNAs were downregulated after the MIR600HG knockdown. BrainSpan project showed that the expression patterns of MIR600HG (primate-specific lncRNA) and synapse-associated mRNA were similar in different human brain regions and at different stages of development. A combination of support vector machine and random forest machine learning algorithms retrieved the marker gene for ASD in the ceRNA network, and the area under the curve of the diagnostic nomogram was 0.851. In conclusion, dysregulation of MIR600HG, a novel specific lncRNA associated with ASD, is responsible for the ASD-associated miRNA-mRNA axes, thereby potentially regulating synaptogenesis.

Circulating Metabolites and Dental Traits: A Mendelian Randomization Study

It is of great importance to uncover causal biomarkers to gain insight into the pathogenesis of oral diseases and identify novel treatment targets for prevention and treatment thereof. This study aimed to systematically evaluate the causal effects of hundreds of metabolites on 10 dental traits using a 2-sample Mendelian randomization (MR) approach. Genetic variants from genome-wide association studies of 309 known metabolites were used as instrumental variables. We selected 10 dental traits, including clinical measures of dental diseases, from the Gene-Lifestyle Interactions in Dental Endpoints Consortium and self-reported oral health data from the UK Biobank. The causal relationships between metabolites and dental traits were inferred using the inverse variance-weighted approach and further controlled for horizontal pleiotropy using 5 additional MR methods. After correcting for multiple tests, 5 metabolites were identified as causal biomarkers. Genetically predicted increased levels of mannose were associated with lower risk of bleeding gums (odds ratio [OR] = 0.72; 95% confidence interval [CI], 0.61-0.85; P = 9.9 × 10-5). MR also indicated 4 metabolites on the causal pathway to dentures, with fructose (OR = 0.50; 95% CI, 0.36-0.70; P = 5.2 × 10-5) and 1-palmitoleoyl-glycerophosphocholine (OR = 0.67; 95% CI, 0.56-0.81; P = 4.8 × 10-5) as potential protective factors and glycine (OR = 1.22; 95% CI, 1.11-1.35; P = 5.6×10-5) and 1,5-anhydroglucitol (OR = 1.32; 95% CI, 1.14-1.52; P = 1.5 × 10-4) as risk factors. The causal associations were robust in various sensitivity analyses. We further observed some shared metabolites among different dental traits, implying similar biological mechanisms underlying the pathogenic processes. Finally, the pathway analysis revealed several significant metabolic pathways that may be involved in the development of dental disorders. Our study provides novel insights into the combination of metabolomics and genomics to reveal the pathogenesis of and therapeutic strategies for dental disorders. It highlighted 5 metabolites and several pathways as causal candidates, warranting further investigation.

Causal Associations between Gut Microbiota and Different Types of Dyslipidemia: A Two-Sample Mendelian Randomization Study

The determination of a causal association between gut microbiota and a range of dyslipidemia remains uncertain. To clarify these associations, we employed a two-sample Mendelian randomization (MR) analysis utilizing the inverse-variance weighted (IVW) method. This comprehensive analysis investigated the genetic variants that exhibited a significant association (p < 5 × 10-8) with 129 distinct gut microbiota genera and their potential link to different types of dyslipidemia. The results indicated a potential causal association between 22 gut microbiota genera and dyslipidemia in humans. Furthermore, these findings suggested that the impact of gut microbiota on dyslipidemia regulation is dependent on the specific phylum, family, and genus. Bacillota phylum demonstrated the greatest diversity, with 15 distinct genera distributed among eight families. Notably, gut microbiota-derived from the Lachnospiraceae and Lactobacillaceae families exhibit statistically significant associations with lipid levels that contribute to overall health (p < 0.05). The sensitivity analysis indicated that our findings possess robustness (p > 0.05). The findings of our investigation provide compelling evidence that substantiates a causal association between the gut microbiota and dyslipidemia in the human body. It is noteworthy to highlight the significant influence of the Bacillota phylum as a crucial regulator of lipid levels, and the families Lachnospiraceae and Lactobacillaceae should be recognized as probiotics that significantly contribute to this metabolic process.

Sleep disorders causally affect the brain cortical structure: A Mendelian randomization study

BACKGROUND

s: Previous studies have reported that patients with sleep disorders have altered brain cortical structures. However, the causality has not been determined. We performed a two-sample Mendelian randomization (MR) to reveal the causal effect of sleep disorders on brain cortical structure.

METHODS

We included as exposures 11 phenotypes of sleep disorders including subjective and objective sleep duration, insomnia symptom and poor sleep efficiency, daytime sleepiness (narcolepsy)/napping, morning/evening preference, and four sleep breathing related traits from nine European-descent genome-wide association studies (GWASs). Further, outcome variables were provided by ENIGMA Consortium GWAS for full brain and 34 region-specific cortical thickness (TH) and surface area (SA) of grey matter. Inverse-variance weighted (IVW) was used as the primary estimate whereas alternative MR methods were implemented as sensitivity analysis approaches to ensure results robustness.

RESULTS

At the global level, both self-reported or accelerometer-measured shorter sleep duration decreases the thickness of full brain both derived from self-reported data (βIVW = 0.03 mm, standard error (SE) = 0.02, P = 0.038; βIVW = 0.02 mm, SE = 0.01, P = 0.010). At the functional level, there were 66 associations of suggestive evidence of causality. Notably, one robust evidence after multiple testing correction (1518 tests) suggests the without global weighted SA of superior parietal lobule was influenced significantly by sleep efficiency (βIVW = -285.28 mm2, SE = 68.59, P = 3.2 × 10-5).

CONCLUSIONS

We found significant evidence that shorter sleep duration, as estimated by self-reported interview and accelerometer measurements, was causally associated with atrophy in the entire human brain.

New insights of metabolite abnormalities in the thalamus of rats with iminodiproprionitrile-induced tic disorders

Introduction

This study aimed to investigate pathological changes in the "Glutamate (Glu)-γ-aminobutyric acid (GABA)" loop and apply widely targeted metabolomic analysis technology to comprehensively explore metabolite abnormalities/ in the thalamus of rats with tic disorders (TD).

Methods

Wistar rats were randomized into control, TD, and tiapride (Tia) groups. Iminodipropionitrile (IDPN) was used to induce TD in rats. The Tia group was administered tiapride. Neurotransmitter levels in the thalamus of rats in the three groups were measured using UPLC-3Q MS. And, the protein expression levels of Glu decarboxylase (GAD65/67) and GABA transporter protein (GAD-T) were measured using western blotting. The mRNA expression levels of these genes were evaluated using real-time polymerase chain reaction. Lastly, other metabolites in the thalamus were detected by widely targeted metabolomic analysis between TD and Control group rats.

Results

The Glu level, Glu/GABA ratio, and Asp level in the TD group were significantly higher (all p < 0.001) than those of the Control group, whereas the GABA and Gly levels were lower (p < 0.001 and p = 0.009, respectively). The Tia group exhibited a significant reduction in the Glu level (p = 0.001) compared with the TD group. The protein expression level of GAD67 in TD group was higher (p = 0.009) and the mRNA expression levels of GAD65, GAD67, and GAT-1 were lower (p < 0.05) than those of the Control group. The Tia group did not display any differences in GAD65, GAD67, or GAT-1 expression. Widely targeted metabolomic analysis revealed that 34 substances were abnornal between the TD and Control groups (9 upregulated and 25 downregulated). Neurosteroids (progesterone, corticosterone) exhibited distinct differences. Metabolite analysis using the Kyoto encyclopedia for genes and genomes indicated that the steroid hormone biosynthesis pathway may be involved in TD pathogenesis.

Conclusion

This study revealed metabolic abnormalities in the thalamus of rats with TD. The interaction between neurotransmitters and neurosteroid biosynthesis represents a new direction for future studies.

Identifying Suitable Targets for Alzheimer's Disease and Other Eight Common Neurological Disorders Using the Human Plasma Proteome: A Mendelian Randomization Study

Background

Neurological disorders, such as Alzheimer's disease (AD), comprise a major cause of health-related disabilities in human. However, biomarkers towards pathogenesis or novel targets are still limited.

Objective

To identify the causality between plasma proteins and the risk of AD and other eight common neurological diseases using a Mendelian randomization (MR) study.

Methods

Exposure data were obtained from a genome-wide association study (GWAS) of 2,994 plasma proteins in 3,301 healthy adults, and outcome datasets included GWAS summary statistics of nine neurological disorders. Inverse variance-weighted MR method as the primary analysis was used to estimate causal effects.

Results

Higher genetically proxied plasma myeloid cell surface antigen CD33 level was found to be associated with increased risk of AD (odds ratio [OR] 1.079, 95% confidence interval [CI] 1.047-1.112, p = 8.39×10-7). We also discovered the causality between genetically proxied elevated prolactin and higher risk of epilepsy (OR = 1.068, 95% CI = 1.034-1.102; p = 5.46×10-5). Negative associations were identified between cyclin-dependent kinase 8 and ischemic stroke (OR = 0.927, 95% CI = 0.896-0.959, p = 9.32×10-6), between neuralized E3 ubiquitin-protein ligase 1 and migraine (OR = 0.914, 95% CI = 0.878-0.952, p = 1.48×10-5), and between Fc receptor-like protein 4 and multiple sclerosis (MS) (OR = 0.929, 95% CI = 0.897-0.963, p = 4.27×10-5).

Conclusion

The findings identified MR-level protein-disease associations for AD, epilepsy, ischemic stroke, migraine, and MS.

Causal effects of COVID-19 on structural changes in specific brain regions: a Mendelian randomization study

BACKGROUND

Previous studies have found a correlation between coronavirus disease 2019 (COVID-19) and changes in brain structure and cognitive function, but it remains unclear whether COVID-19 causes brain structural changes and which specific brain regions are affected. Herein, we conducted a Mendelian randomization (MR) study to investigate this causal relationship and to identify specific brain regions vulnerable to COVID-19.

METHODS

Genome-wide association study (GWAS) data for COVID-19 phenotypes (28,900 COVID-19 cases and 3,251,161 controls) were selected as exposures, and GWAS data for brain structural traits (cortical thickness and surface area from 51,665 participants and volume of subcortical structures from 30,717 participants) were selected as outcomes. Inverse-variance weighted method was used as the main estimate method. The weighted median, MR-Egger, MR-PRESSO global test, and Cochran's Q statistic were used to detect heterogeneity and pleiotropy.

RESULTS

The genetically predicted COVID-19 infection phenotype was nominally associated with reduced cortical thickness in the caudal middle frontal gyrus (β = - 0.0044, p = 0.0412). The hospitalized COVID-19 phenotype was nominally associated with reduced cortical thickness in the lateral orbitofrontal gyrus (β = - 0.0049, p = 0.0328) and rostral middle frontal gyrus (β = - 0.0022, p = 0.0032) as well as with reduced cortical surface area of the middle temporal gyrus (β = - 10.8855, p = 0.0266). These causal relationships were also identified in the severe COVID-19 phenotype. Additionally, the severe COVID-19 phenotype was nominally associated with reduced cortical thickness in the cuneus (β = - 0.0024, p = 0.0168); reduced cortical surface area of the pericalcarine (β = - 2.6628, p = 0.0492), superior parietal gyrus (β = - 5.6310, p = 0.0408), and parahippocampal gyrus (β = - 0.1473, p = 0.0297); and reduced volume in the hippocampus (β = - 15.9130, p = 0.0024).

CONCLUSIONS

Our study indicates a suggestively significant association between genetic predisposition to COVID-19 and atrophy in specific functional regions of the human brain. Patients with COVID-19 and cognitive impairment should be actively managed to alleviate neurocognitive symptoms and minimize long-term effects.

The causal associations between growth factors and constipation: a two-sample Mendelian randomization study

Introduction: Certain growth factors (GFs) are associated with constipation, but few studies has analyzed the causal associations between the two. Therefore, this study used two-sample Mendelian randomization (MR) to systematically analyze the causal associations between GF levels and constipation based on data from genome-wide association studies (GWAS). Methods: Both GF and constipation data were obtained from European populations. GFs, as an exposure variable, were obtained from a genetic map of the human plasma proteome containing 3,301 samples, another GWAS dataset on 90 circulating proteins containing 30,931 samples, and a GWAS dataset containing 3,788 samples. Constipation, as an outcome variable, was obtained from the FinnGen project containing 26,919 cases and 282,235 controls and another UK Biobank dataset containing 3,328 cases and 459,682 controls. Single-nucleotide polymorphisms strongly associated with GFs were regarded as instrumental variables. Inverse-variance weighting, MR-Egger regression, weight median, simple mode, and weight mode methods were used to determine genetic associations. Cochran's Q test, Egger intercept, and Mendelian Randomization Pleiotropy RESidual Sum and Outlier tests were used to analyze sensitivity. Results: The IVW analysis based on FinnGen showed that NGFI-A-binding protein 2 and vascular endothelial growth factor receptor 2 were inversely associated with constipation, and that fibroblast growth factor 7 and transforming growth factor beta receptor II levels were positively associated with constipation. The IVW analysis based on UK Biobank showed that proheparin-binding epidermal growth factor, platelet-derived growth factor AA, and vascular endothelial growth factor₁₂₁ were inversely associated with constipation. Conclusion: This study showed that some GFs are genetically associated with the risk of constipation.

Association between intake of the n-3 polyunsaturated fatty acid docosahexaenoic acid (n-3 PUFA DHA) and reduced risk of ovarian cancer: A systematic Mendelian Randomization study

BACKGROUND & AIMS

Whether the intake of docosahexaenoic acid (DHA), an n-3 polyunsaturated fatty acid, is beneficial for ovarian cancer (OC) remains controversial and we hope to disentangle this puzzle using genetic data from large-scale populations in European and Asian.

METHODS

We employed, for the first time, a systematic Mendelian randomization (MR) design to comprehensively evaluate the causal effect of plasma DHA levels, an objective biomarker of DHA intake, on OC risk in European and then verified the extrapolation of the results in the Asian. Data in the analysis included genetic association data obtained from large-scale genome-wide association studies with 13,499 individuals for plasma DHA measurements and 66,450 individuals for OC in the European population, and 1361 individuals for plasma DHA measurements and 61,457 individuals for OC in the Asian population. The causal relationship between DHA and OC was estimated using the inverse-variance weighted approach, together with extensive validation and sensitivity analyses to verify the main results.

RESULTS

In the European population, MR evidence suggested a causal relationship between higher plasma DHA levels and lower OC risk (OR, 0.89 for OC per one-SD increment in DHA; 95% CI, 0.83 to 0.96; P = 0.003). Subgroup analysis by histological type of OC indicated that this observed association was stronger among endometrioid ovarian cancer (EOC) (OR, 0.82; 95% CI, 0.69 to 0.96; P = 0.014). A similar causal association of borderline significance was reached in the Asian replication set. The above results were consistently supported by a series of validation and sensitivity analyses.

CONCLUSION

Our study provided robust genetic evidence for a protective association between plasma DHA levels and lower risk of OC, especially EOC, in the European population. These findings may inform prevention strategies and interventions directed towards DHA intake and OC.

Genetic insight into the putative causal proteins and druggable targets of osteoporosis: a large-scale proteome-wide mendelian randomization study

Background: Osteoporosis is a major causative factor of the global burden of disease and disability, characterized by low bone mineral density (BMD) and high risks of fracture. We aimed to identify putative causal proteins and druggable targets of osteoporosis. Methods: This study utilized the largest GWAS summary statistics on plasma proteins and estimated heel BMD (eBMD) to identify causal proteins of osteoporosis by mendelian randomization (MR) analysis. Different GWAS datasets were used to validate the results. Multiple sensitivity analyses were conducted to evaluate the robustness of primary MR findings. We have also performed an enrichment analysis for the identified causal proteins and evaluated their druggability. Results: After Bonferroni correction, 67 proteins were identified to be causally associated with estimated BMD (eBMD) (p < 4 × 10^-5). We further replicated 38 of the 67 proteins to be associated with total body BMD, lumbar spine BMD, femoral neck BMD as well as fractures, such as RSPO3, IDUA, SMOC2, and LRP4. The findings were supported by sensitivity analyses. Enrichment analysis identified multiple Gene Ontology items, including collagen-containing extracellular matrix (GO:0062023, p = 1.6 × 10^-10), collagen binding (GO:0005518, p = 8.6 × 10^-5), and extracellular matrix structural constituent (GO:0005201, p = 2.7 × 10^-5). Conclusion: The study identified novel putative causal proteins for osteoporosis which may serve as potential early screening biomarkers and druggable targets. Furthermore, the role of plasma proteins involved in collagen binding and extracellular matrix in the development of osteoporosis was highlighted. Further studies are warranted to validate our findings and investigate the underlying mechanism.

Association between circulating fatty acid metabolites and asthma risk: a two-sample bidirectional Mendelian randomization study

BACKGROUND

Fatty acids are involved in a wide range of immunological responses in humans. Supplementation of polyunsaturated fatty acids has been reported to help alleviate symptoms and airway inflammation in asthma patients, whereas the effects of fatty acids on the actual risk of asthma remain controversial. This study comprehensively investigated the causal effects of serum fatty acids on asthma risk using two-sample bidirectional Mendelian Randomization (MR) analysis.

METHODS

Genetic variants strongly associated with 123 circulating fatty acid metabolites were extracted as instrumental variables, and a large GWAS data of asthma was used to test effects of the metabolites on this outcome. The inverse-variance weighted method was used for primary MR analysis. The weighted median, MR-Egger regression, MR-PRESSO, and leave-one-out analyses were utilized to evaluate heterogeneity and pleiotropy. Potential confounders were adjusted by performing multivariable MR analyses. Reverse MR analysis was also conducted to estimate the causal effect of asthma on candidate fatty acid metabolites. Further, we performed colocalization analysis to examine the pleiotropy of variants within the fatty acid desaturase 1 (FADS1) locus between the significant metabolite traits and the risk of asthma. Cis-eQTL-MR and colocalization analysis were also performed to determine the association between RNA expression of FADS1 and asthma.

RESULTS

Genetically instrumented higher average number of methylene groups was causally associated with a lower risk of asthma in primary MR analysis, while inversely, the higher ratio of bis-allylic groups to double bonds and the higher ratio of bis-allylic groups to total fatty acids, were associated with higher probabilities of asthma. Consistent results were obtained in multivariable MR when adjusted for potential confounders. However, these effects were completely eliminated after SNPs correlated with the FADS1 gene were excluded. The reverse MR also found no causal association. The colocalization analysis suggested that the three candidate metabolite traits and asthma likely share causal variants within the FADS1 locus. In addition, the cis-eQTL-MR and colocalization analyses demonstrated a causal association and shared causal variants between FADS1 expression and asthma.

CONCLUSIONS

Our study supports a negative association between several PUFA traits and the risk of asthma. However, this association is largely attributed to the influence of FADS1 polymorphisms. The results of this MR study should be carefully interpreted given the pleiotropy of SNPs associated with FADS1.

Multiomic approach and Mendelian randomization analysis identify causal associations between blood biomarkers and subcortical brain structure volumes

Alterations in subcortical brain structure volumes have been found to be associated with several neurodegenerative and psychiatric disorders. At the same time, genome-wide association studies (GWAS) have identified numerous common variants associated with brain structure. In this study, we integrate these findings, aiming to identify proteins, metabolites, or microbes that have a putative causal association with subcortical brain structure volumes via a two-sample Mendelian randomization approach. This method uses genetic variants as instrument variables to identify potentially causal associations between an exposure and an outcome. The exposure data that we analyzed comprised genetic associations for 2,994 plasma proteins, 237 metabolites, and 103 microbial genera. The outcome data included GWAS data for seven subcortical brain structure volumes including accumbens, amygdala, caudate, hippocampus, pallidum, putamen, and thalamus. Eleven proteins and six metabolites were found to have a significant association with subcortical structure volumes. We found causal associations between amygdala volume and granzyme A as well as association between accumbens volume and plasma protease c1 inhibitor. Among metabolites, urate had the strongest association with thalamic volume. No significant associations were detected between the microbial genera and subcortical brain structure volumes. We also observed significant enrichment for biological processes such as proteolysis, regulation of the endoplasmic reticulum apoptotic signaling pathway, and negative regulation of DNA binding. Our findings provide insights to the mechanisms through which brain volumes may be affected in the pathogenesis of neurodevelopmental and psychiatric disorders and point to potential treatment targets for disorders that are associated with subcortical brain structure volumes.

Mendelian Randomization Analysis Provides Insights into the Pathogenesis of Serum Levels of Branched-Chain Amino Acids in Cardiovascular Disease

Several observational studies have indicated an association between high serum levels of branched-chain amino acids (BCAAs) and an increased risk of cardiovascular disease (CVD). To assess whether theses associations reflect causality, we carried out two-sample Mendelian randomization (MR). Single-nucleotide polymorphisms (SNPs) associated with BCAA were evaluated in 10 studies, including 24,925 participants. The association between SNPs and coronary artery disease (CAD) were assessed using summary estimates from the CARDIoGRAMplusC4D consortium. Further MR analysis of BCAAs and seven CVD outcomes was performed. The BCAA-raising gene functions were also analyzed. MR analyses revealed a risk-increasing causal relationship between serum BCAA concentrations and CAD (odds ratio 1.08; 95% confidence interval (CI) 1.02–1.14), which was partly mediated by blood pressure and type 2 diabetes. BCAA also demonstrated a causal relationship with ischemic CVD events induced by plaque rupture and thrombosis (false discovery rate <0.05). Two BCAA-raising genes (MRL33 and CBLN1) were preferentially associated with myocardial infarction risk in the presence of atherosclerosis (p < 0.003). Functional analysis of the BCAA-raising genes suggested the causal involvement of two pathophysiological pathways, including glucose metabolism (PPM1K and TRMT61A) related to plaque progression, and the newly discovered neuroendocrine disorders regulating blood pressure (MRPL33, CBLN1, and C2orf16) related to plaque rupture and thrombosis. This comprehensive MR analysis provided insights into the potential causal mechanisms linking BCAA with CVD risk and suggested targeting neuroendocrine disorders as a potential strategy for the prevention of CVD. These results warrant further studies to elucidate the mechanisms underlying these reported causal associations.

Mendelian Randomization Indicates a Causal Role for Omega-3 Fatty Acids in Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) is characterized by chronic inflammation of the gastrointestinal system. Omega-3 (ω₃) fatty acids are polyunsaturated fatty acids (PUFAs) that are largely obtained from diet and have been speculated to decrease the inflammatory response that is involved in IBD; however, the causality of this association has not been established. A two-sample Mendelian randomization (MR) was used to assess genetic associations between 249 circulating metabolites measured in the UK Biobank as exposures and IBD as the outcome. The genome-wide association study summary level data for metabolite measurements and IBD were derived from large European ancestry cohorts. We observed ω₃ fatty acids as a significant protective association with IBD, with multiple modes of MR evidence replicated in three IBD summary genetic datasets. The instrumental variables that were involved in the causal association of ω₃ fatty acids with IBD highlighted an intronic SNP, rs174564, in FADS2, a protein engaged in the first step of alpha-linolenic acid desaturation leading to anti-inflammatory EPA and thence DHA production. A low ratio of ω₃ to ω₆ fatty acids was observed to be a causal risk factor, particularly for Crohn's disease. ω₃ fatty acid supplementation may provide anti-inflammatory responses that are required to attenuate inflammation that is involved in IBD.

Genome Guided Personalized Drug Therapy in Attention Deficit Hyperactivity Disorder

ADHD is a common behavioral syndrome with a heritability of 70-80%. Genome wide sequencing and association studies indicate that ADHD risk variants are distributed across a wide range of allele frequencies and relative risks. Several common single nucleotide variants (SNPs) have been identified that increase the risk of ADHD with a few percent. Many of the reported risk genes and copy number variants are shared with other neuropsychiatric disorders. Moreover, ADHD often coexists with common or rare somatic diseases, including rare Mendelian neurometabolic diseases that can affect normal brain development and function. Some genetic/metabolic syndromes masquerading as common ADHD may lead to irreversible brain damage if not properly identified and treated during early childhood. As ADHD is such a heterogeneous condition in terms of severity, clinical features and most probably also underlying biology, it is crucial to offer individualized treatments. Recent progress in ADHD genetics is reviewed, prospects of using this information for targeted pharmacotherapy are discussed and critical knowledge gaps are identified. It is suggested that genome guided therapies could be introduced gradually, starting with rare ADHD syndromes with highly penetrant risk genes. Routine diagnostic application of whole exome or whole genome sequencing combined with metabolomic screening, and brain imaging may be needed in cases with suspected neurometabolic disorders. Identification and treatment of ADHD patients with defined neurometabolic aberrations could be a first step toward genome guided personalized treatment of ADHD. Possibly, screening for relevant biomarkers may gradually be implemented to guide treatment choices in larger patient groups.

Correlation research of susceptibility single nucleotide polymorphisms and the severity of clinical symptoms in attention deficit hyperactivity disorder

OBJECTIVE

To analyze the correlation between susceptibility single nucleotide polymorphisms (SNPs) and the severity of clinical symptoms in children with attention deficit hyperactivity disorder (ADHD), so as to supplement the clinical significance of gene polymorphism and increase our understanding of the association between genetic mutations and ADHD phenotypes.

METHODS

193 children with ADHD were included in our study from February 2017 to February 2020 in the Children's ADHD Clinic of the author's medical institution. 23 ADHD susceptibility SNPs were selected based on the literature, and multiple polymerase chain reaction (PCR) targeted capture sequencing technology was used for gene analysis. A series of ADHD-related questionnaires were used to reflect the severity of the disease, and the correlation between the SNPs of specific sites and the severity of clinical symptoms was evaluated. R software was used to search for independent risk factors by multivariate logistic regression and the "corplot" package was used for correlation analysis.

RESULTS

Among the 23 SNP loci of ADHD children, no mutation was detected in 6 loci, and 2 loci did not conform to Hardy-Weinberg equilibrium. Of the remaining 15 loci, there were 9 SNPs, rs2652511 (SLC6A3 locus), rs1410739 (OBI1-AS1 locus), rs3768046 (TIE1 locus), rs223508 (MANBA locus), rs2906457 (ST3GAL3 locus), rs4916723 (LINC00461 locus), rs9677504 (SPAG16 locus), rs1427829 (intron) and rs11210892 (intron), correlated with the severity of clinical symptoms of ADHD. Specifically, rs1410739 (OBI1-AS1 locus) was found to simultaneously affect conduct problems, control ability and abstract thinking ability of children with ADHD.

CONCLUSION

There were 9 SNPs significantly correlated with the severity of clinical symptoms in children with ADHD, and the rs1410739 (OBI1-AS1 locus) may provide a new direction for ADHD research. Our study builds on previous susceptibility research and further investigates the impact of a single SNP on the severity of clinical symptoms of ADHD. This can help improve the diagnosis, prognosis and treatment of ADHD.