RESUMEN

The causal effects of mental health problems on the risk of infectious diseases remain vague. Investigating them via observational study is challenging as it presents possible confounding factors. Therefore, the objective of this study was to utilize Mendelian randomization (MR) techniques to evaluate the causal relationship between mental health problems and the risk of infectious diseases. Multivariable MR analyses were performed using genome-wide association data for sleep disorders (N = 216,700), depression (N = 500,199), anxiety (N = 290,361), nervous feelings (N = 450,700), unspecified mental disorder (N = 218,792), pneumonia (N = 486,484), skin and subcutaneous tissue infection (SSTI; N = 218,792), intestinal infectious diseases (IIDs; N = 218,792), urinary tract infection (N = 463,010), and central nervous system (CNS) infections (N = 218,792) among individuals of European ancestry. Independent genetic variants significantly (P < 10-8) associated with each exposure were considered instruments. The primary analysis used an inverse variance-weighted method, followed by a series of sensitivity analyses. Genetically predicted sleep disorders were associated with an increased risk of SSTI (odds ratio [OR], 1.29 [95% confidence interval (CI), 1.05-1.59]; P = .017). Genetically predicted depression was linked with an increased risk of CNS infections (OR, 1.59 [95% CI, 1.00-2.53]; P = .049) and SSTI (1.24 [95% CI, 1.03-1.49]; P = .024). Genetically predicted anxiety was associated with IIDs (OR, 1.19 [95% CI, 1.03-1.37]; P = .017) and SSTI (OR, 1.21 [95% CI, 1.02-1.43]; P = .029). There was no significant causal evidence for genetic prediction of nervous feelings and unspecified mental disorders in IIDs, CNS infections, SSTI, pneumonia, or urinary tract infection. Sensitivity analyses showed that the above causal association estimates were robust. In this MR study, we demonstrated a causal relationship between sleep disorders, depression, anxiety, and the risk of infectious diseases. However, no evidence was found to support causality between nervous feelings, unspecified mental disorders, and the risk of infectious diseases.

Asunto(s)

RESUMEN

Suicidality remains a clear and present danger in society in general, and for mental health patients in particular. Lack of widespread use of objective and/or quantitative information has hampered treatment and prevention efforts. Suicidality is a spectrum of severity from vague thoughts that life is not worth living, to ideation, plans, attempts, and completion. Blood biomarkers that track suicidality risk provide a window into the biology of suicidality, as well as could help with assessment and treatment. Previous studies by us were positive. Here we describe new studies we conducted transdiagnostically in psychiatric patients, starting with the whole genome, to expand the identification, prioritization, validation and testing of blood gene expression biomarkers for suicidality, using a multiple independent cohorts design. We found new as well as previously known biomarkers that were predictive of high suicidality states, and of future psychiatric hospitalizations related to them, using cross-sectional and longitudinal approaches. The overall top increased in expression biomarker was SLC6A4, the serotonin transporter. The top decreased biomarker was TINF2, a gene whose mutations result in very short telomeres. The top biological pathways were related to apoptosis. The top upstream regulator was prednisolone. Taken together, our data supports the possibility that biologically, suicidality is an extreme stress-driven form of active aging/death. Consistent with that, the top subtypes of suicidality identified by us just based on clinical measures had high stress and high anxiety. Top therapeutic matches overall were lithium, clozapine and ketamine, with lithium stronger in females and clozapine stronger in males. Drug repurposing bioinformatic analyses identified the potential of renin-angiotensin system modulators and of cyclooxygenase inhibitors. Additionally, we show how patient reports for doctors would look based on blood biomarkers testing, personalized by gender. We also integrated with the blood biomarker testing social determinants and psychological measures (CFI-S, suicidal ideation), showing synergy. Lastly, we compared that to machine learning approaches, to optimize predictive ability and identify key features. We propose that our findings and comprehensive approach can have transformative clinical utility.

Asunto(s)

RESUMEN

BACKGROUND AND OBJECTIVES: Behavioral and neuropsychiatric symptoms are frequent in patients with genetic frontotemporal dementia (FTD). We aimed to describe behavioral and neuropsychiatric phenotypes in genetic FTD, quantify their temporal association, and investigate their regional association with brain atrophy. METHODS: We analyzed data of pathogenic variant carriers in the chromosome 9 open reading frame 72 (c9orf72), progranulin (GRN), or microtubule-associated protein tau (MAPT) gene from the Genetic Frontotemporal dementia Initiative cohort study that enrolls both symptomatic pathogenic variant carriers and first-degree relatives of known carriers. Principal component analysis was performed to identify behavioral and neuropsychiatric clusters that were compared with respect to frequency and severity between groups. Associations between neuropsychiatric clusters and MRI-assessed atrophy were determined using voxel-based morphometry. We applied linear mixed effects and generalized linear mixed effects models to assess the longitudinal course of symptoms. RESULTS: A total of 522 participants were included: 221 c9orf72 (138 presymptomatic), 213 GRN (157 presymptomatic), and 88 MAPT (62 presymptomatic) pathogenic variant carriers. Principal component analysis revealed 5 phenotypic clusters (67.6% of variance), labeled diverse behavioral, affective, psychotic, euphoric/hypersexual, and tactile hallucinations phenotype. In participants presenting behavioral or neuropsychiatric symptoms, affective symptoms were most frequent across groups (83.6%-88.1%), followed by diverse behavioral symptoms (68.4%-77.9%). In c9orf72 and GRN pathogenic variant carriers, psychotic symptoms (32.0% and 19.4%, respectively) were more frequent than euphoric/hypersexual symptoms (28.7% and 14.2%, respectively), which was the other way around in MAPT pathogenic variant carriers (28.6% and 23.8%). Although diverse behavioral symptoms were associated with gray and white matter frontotemporal atrophy, only a small atrophy cluster in the right thalamus was associated with psychotic symptoms. Euphoric/hypersexual symptoms were associated with atrophy in mesial temporal lobes, basal forebrain structures, and the striatum (p < 0.05). Estimated time to symptom onset, genetic group, education, and sex influenced behavioral and neuropsychiatric symptoms (p < 0.05). Particularly, in c9orf72 pathogenic variant carriers, psychotic symptoms may be starting decades before recognition of onset of illness. DISCUSSION: We identified multiple clusters of behavioral and neuropsychiatric symptoms in participants with genetic FTD that relate to distinct cerebral atrophy patterns. Their severity depends on time, affected gene, sex, and education. These clinical-genetic associations can guide diagnostic evaluations and the design of clinical trials for new disease-modifying and preventive treatments.

Asunto(s)

RESUMEN

BACKGROUND: Neurocognitive dysfunction is observationally associated with the risk of psychiatric disorders. Blood metabolites, which are readily accessible, may become highly promising biomarkers for brain disorders. However, the causal role of blood metabolites in neurocognitive function, and the biological pathways underlying their association with psychiatric disorders remain unclear. METHODS: To explore their putative causalities, we conducted bidirectional two-sample Mendelian randomization (MR) using genetic variants associated with 317 human blood metabolites (nmax = 215,551), g-Factor (an integrated index of multiple neurocognitive tests with nmax = 332,050), and 10 different psychiatric disorders (n = 9,725 to 807,553) from the large-scale genome-wide association studies of European ancestry. Mediation analysis was used to assess the potential causal pathway among the candidate metabolite, neurocognitive trait and corresponding psychiatric disorder. RESULTS: MR evidence indicated that genetically predicted acetylornithine was positively associated with g-Factor (0.035 standard deviation units increase in g-Factor per one standard deviation increase in acetylornithine level; 95% confidence interval, 0.021 to 0.049; P = 1.15 × 10-6). Genetically predicted butyrylcarnitine was negatively associated with g-Factor (0.028 standard deviation units decrease in g-Factor per one standard deviation increase in genetically proxied butyrylcarnitine; 95% confidence interval, -0.041 to -0.015; P = 1.31 × 10-5). There was no evidence of associations between genetically proxied g-Factor and metabolites. Furthermore, the mediation analysis via two-step MR revealed that the causal pathway from acetylornithine to bipolar disorder was partly mediated by g-Factor, with a mediated proportion of 37.1%. Besides, g-Factor mediated the causal pathway from butyrylcarnitine to schizophrenia, with a mediated proportion of 37.5%. Other neurocognitive traits from different sources provided consistent findings. CONCLUSION: Our results provide genetic evidence that acetylornithine protects against bipolar disorder through neurocognitive abilities, while butyrylcarnitine has an adverse effect on schizophrenia through neurocognition. These findings may provide insight into interventions at the metabolic level for risk of neurocognitive and related disorders.

Asunto(s)

Asunto(s)

RESUMEN

BACKGROUND: Increasing evidences suggest that nonalcoholic fatty liver disease (NAFLD) is associated with neuropsychiatric disorders. Nevertheless, whether there were causal associations between them remained vague. A causal association between neuropsychiatric disorders and NAFLD was investigated in this study. METHODS: We assessed the published genome-wide association study summary statistics for NAFLD, seven mental disorder-related diseases and six central nervous system dysfunction-related diseases. The causal relationships were first assessed using two-sample and multivariable Mendelian randomization (MR). Then, sensitivity analyses were performed, followed by a reverse MR analysis to determine whether reverse causality is possible. Finally, we performed replication analyses and combined the findings from the above studies. RESULTS: Our meta-analysis results showed NAFLD significantly increased the risk of anxiety disorders (OR = 1.016, 95% CI = 1.010-1.021, P value < 0.0001). In addition, major depressive disorder was the potential risk factor for NAFLD (OR = 1.233, 95% CI = 1.063-1.430, P value = 0.006). Multivariable MR analysis showed that the causal effect of major depressive disorder on NAFLD remained significant after considering body mass index, but the association disappeared after adjusting for the effect of waist circumference. Furthermore, other neuropsychiatric disorders and NAFLD were not found to be causally related. CONCLUSIONS: These results implied causal relationships of NAFLD with anxiety disorders and Major Depressive Disorder. This study highlighted the need to recognize and understand the connection between neuropsychiatric disorders and NAFLD to prevent the development of related diseases.

Asunto(s)

RESUMEN

Evidence from observational researches have suggested that mental diseases are able to affect thyroid diseases. However, the causal relationship between mental diseases and the risk of thyroid diseases still remains unclear. Herein, we conducted a two-sample Mendelian randomization (MR) statistical analysis method to assess the causality between mental diseases and thyroid diseases. Initially, publicly available genome-wide association studies summary data were leveraged to obtain single-nucleotide polymorphisms based on set parameters. Subsequently, a two-sample MR was utilized to analyze causal relationships between mental diseases (Alzheimer disease, bipolar disorder, major depressive disorder, Parkinson disease, schizophrenia) and thyroid diseases (hyperthyroidism/thyrotoxicosis, hypothyroidism) with removing outliers based on MR-PRESSO method. Finally, 8 regression MR methods (inverse variance weighted [IVW], IVW fixed effects, c, MR Egger, weighted median, penalized weighted median, simple mode, weighted mode) were performed to evaluate bias and effectiveness, of which IVW was considered as the primary method. Our results demonstrated that most of mental diseases have no causal relationships with thyroid diseases except bipolar disorder and hyperthyroidism/thyrotoxicosis based on IVW method [odds ratio: 0.999, 95% confidence interval: 0.998-1.000, P = .028], and bipolar disorder and hypothyroidism based on IVW method [odds ratio: 0.997, 95% confidence interval: 0.995-0.999, P = .002]. Then we subsequently conducted a consistent robustness analysis to assess heterogeneity and horizontal pleiotropy. Our method reports causal relationships exist mental diseases and the risk of thyroid diseases. Subsequent researches are still warranted to determine how mental diseases influence the development of thyroid diseases.

Asunto(s)

RESUMEN

Integrating protein quantitative trait loci (pQTL) data and summary statistics from genome-wide association studies (GWAS) of brain image-derived phenotypes (IDPs) can benefit in identifying IDP-related proteins. Here, we developed a systematic omics-integration analytic framework by sequentially using proteome-wide association study (PWAS), Mendelian randomization (MR), and colocalization (COLOC) analyses to identify the potentially causal brain and plasma proteins for IDPs, followed by pleiotropy analysis, mediation analysis, and drug exploration analysis to investigate potential mediation pathways of pleiotropic proteins to neuropsychiatric disorders (NDs) as well as candidate drug targets. A total of 201 plasma proteins and 398 brain proteins were significantly associated with IDPs from PWAS analysis. Subsequent MR and COLOC analyses further identified 313 potentially causal IDP-related proteins, which were significantly enriched in neural-related phenotypes, among which 91 were further identified as pleiotropic proteins associated with both IDPs and NDs, including EGFR, TMEM106B, GPT, and HLA-B. Drug prioritization analysis showed that 6.33% of unique pleiotropic proteins had drug targets or interactions with medications for NDs. Nine potential mediation pathways were identified to illustrate the mediating roles of the IDPs in the causal effect of the pleiotropic proteins on NDs, including the indirect effect of TMEM106B on Alzheimer's disease (AD) risk via radial diffusivity (RD) of the posterior limb of the internal capsule (PLIC), with the mediation proportion being 11.18%, and the indirect effect of EGFR on AD through RD of PLIC, RD of splenium of corpus callosum (SCC), and fractional anisotropy (FA) of SCC, with the mediation proportion being 18.99%, 22.79%, and 19.91%, respectively. These findings provide novel insights into pathogenesis, drug targets, and neuroimaging biomarkers of NDs.

Asunto(s)

RESUMEN

BACKGROUND: There is an association between obesity and psychological disorders such as depression, anxiety, and stress. Environmental factors and genetics play a crucial role in this regard. Several long non-coding RNAs (lncRNAs) are involved in the pathophysiology of the nervous system. Additionally, we intend to investigate how dietary glycemic index and load relate to psychological disorders in women with obesity and overweight by identifying the possible interaction with metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) and taurine upregulated gene 1 (TUG1). METHODS: 267 overweight or obese women between the ages of 18 and 48 were recruited for the current study. A reliable and validated food frequency questionnaire (FFQ) consisting of 147 items assessed food consumption, glycemic load (GL), and glycemic index (GI). Depression-Anxiety-Stress Scales (DASS-21) were used to assess mental well-being. A real-time polymerase chain reaction (PCR) was used to assess transcript levels for lncRNAs MALAT1 and TUG1. RESULTS: In obese and overweight women, a positive correlation was found between anxiety and MALAT1 mRNA levels (P = 0.007, CC = 0.178). Age, energy intake, physical activity, total fat, income, marriage, thyroid, and BMI were adjusted, and GI and TUG1 were positively correlated on DASS-21 (ß = 0.006, CI = 0.001, 0.01, P = 0.031), depression (ß = 0.002, CI = 0.001, 0.004, P = 0.019), Stress (ß = 0.003, CI = 0.001, 0.005, P = 0.027). The interaction of GL and TUG1 on stress was also observed (ß = 0.03, CI = 0.001, 0.07, P = 0.048). CONCLUSIONS: The lncRNA TUG1 appears to be associated with depression and stress through interaction with GI and correlated with stress by interaction with GL. To establish this concept, further research is required.

Asunto(s)

RESUMEN

BACKGROUND: Existing epidemiological studies have indicated a correlation between air pollutants and the occurrence of mental disorders. However, it is difficult to estimate the causal relationship between the two because of the limitations of traditional epidemiological research. In our study, we aimed to extensively explore the causal relationship between five types of air pollutants and four types of mental disorders. METHODS: Based on the IEU OPEN GWAS database, we performed a two-sample MR analysis. The primary analysis method utilized was the inverse variance weighted (IVW) method, supplemented by the MR-Egger method and the weighted median method. Additionally, we conducted sensitivity analyses with the Cochran's Q statistic method, the leave-one-out method, and the MR-Egger intercept. We chose at least 4 GWAS datasets for each of the four psychiatric diseases and conducted a meta-analysis of our results of the MR analysis. RESULTS: The meta-analysis's findings demonstrated a causal link between depression and PM2.5 (OR=1.020, 95 %CI: (1.010,1.030), P=0.001). PM10 and schizophrenia are also causally related (OR=1.136, 95 %CI: (1.034,1.248), P=0.008). Nitrogen oxides and bipolar disorder have a causal relationship (OR=1.002, 95 %CI: (1.000,1.003), P=0.022). Nitrogen oxides and schizophrenia have a high causal association (OR=1.439, 95 %CI: (1.183,1.752), P<0.001). CONCLUSION: This study observed a causal association between increased concentrations of PM2.5, PM10, and nitrogen oxides and the occurrence of depression, schizophrenia, and bipolar disorder. Our research findings have certain guiding implications for treating and preventing mental disorders.

Asunto(s)

RESUMEN

Scientific evidence shows that dietary patterns are a key environmental determinant of mental health. Dietary constituents can modify epigenetic patterns and thus the gene expression of relevant genetic variants in various mental health conditions. In the present work, we describe some nutrigenomic effects of dietary fiber, phenolic compounds (plant secondary metabolites), and fatty acids on mental health outcomes, with emphasis on their possible interactions with genetic and epigenetic aspects. Prebiotics, through their effects on the gut microbiota, have been associated with modulation in the neuroendocrine response to stress and the facilitation of the processing of positive emotions. Some of the genetic and epigenetic mechanisms include the serotonin neurotransmitter system (TPH1 gene) and the brain-derived neurotrophic factor (inhibition of histone deacetylases). The consumption of phenolic compounds exerts a positive role in neurocognitive domains. The evidence showing the involvement of genetic and epigenetic factors comes mainly from animal models, highlighting the role of epigenetic mechanisms through miRNAs and methyltransferases as well as the effect on the expression of apoptotic-related genes. Long-chain n-3 fatty acids (EPA and DHA) have been mainly related to psychotic and mood disorders, but the genetic and epigenetic evidence is scarce. Studies on the genetic and epigenetic basis of these interactions need to be promoted to move towards a precision and personalized approach to medicine.

Asunto(s)

RESUMEN

The disruption of brain energy metabolism, leading to alterations in synaptic signaling, neural circuitry, and neuroplasticity, has been implicated in severe mental illnesses such as schizophrenia, bipolar disorder, and major depressive disorder. The therapeutic potential of ketogenic interventions in these disorders suggests a link between metabolic disturbances and disease pathology; however, the precise mechanisms underlying these metabolic disturbances, and the therapeutic effects of metabolic ketogenic therapy, remain poorly understood. In this study, we conducted an in silico analysis of transcriptomic data to investigate perturbations in metabolic pathways in the brain across severe mental illnesses via gene expression profiling. We also examined dysregulation of the same pathways in rodent or cell culture models of ketosis, comparing these expression profiles to those observed in the disease states. Our analysis revealed significant perturbations across all metabolic pathways, with the greatest perturbations in glycolysis, the tricarboxylic acid (TCA) cycle, and the electron transport chain (ETC) across all three disorders. Additionally, we observed some discordant gene expression patterns between disease states and ketogenic intervention studies, suggesting a potential role for ketone bodies in modulating pathogenic metabolic changes. Our findings highlight the importance of understanding metabolic dysregulation in severe mental illnesses and the potential therapeutic benefits of ketogenic interventions in restoring metabolic homeostasis. This study provides insights into the complex relationship between metabolism and neuropsychiatric disorders and lays the foundation for further experimental investigations aimed at appreciating the implications of the present transcriptomic findings as well as developing targeted therapeutic strategies.

Asunto(s)

RESUMEN

In the past two decades, significant progress has been made in the development of polygenic scores (PGSs). One specific application of PGSs is the development and potential use of pharmacogenomic- scores (PGx-scores) to identify patients who can benefit from a specific medication or are likely to experience side effects. This systematic review comprehensively evaluates published PGx-score studies in psychiatry and provides insights into their potential clinical use and avenues for future development. A systematic literature search was conducted across PubMed, EMBASE, and Web of Science databases until 22 August 2023. This review included fifty-three primary studies, of which the majority (69.8%) were conducted using samples of European ancestry. We found that over 90% of PGx-scores in psychiatry have been developed based on psychiatric and medical diagnoses or trait variants, rather than pharmacogenomic variants. Among these PGx-scores, the polygenic score for schizophrenia (PGSSCZ) has been most extensively studied in relation to its impact on treatment outcomes (32 publications). Twenty (62.5%) of these studies suggest that individuals with higher PGSSCZ have negative outcomes from psychotropic treatment - poorer treatment response, higher rates of treatment resistance, more antipsychotic-induced side effects, or more psychiatric hospitalizations, while the remaining studies did not find significant associations. Although PGx-scores alone accounted for at best 5.6% of the variance in treatment outcomes (in schizophrenia treatment resistance), together with clinical variables they explained up to 13.7% (in bipolar lithium response), suggesting that clinical translation might be achieved by including PGx-scores in multivariable models. In conclusion, our literature review found that there are still very few studies developing PGx-scores using pharmacogenomic variants. Research with larger and diverse populations is required to develop clinically relevant PGx-scores, using biology-informed and multi-phenotypic polygenic scoring approaches, as well as by integrating clinical variables with these scores to facilitate their translation to psychiatric practice.

Asunto(s)

RESUMEN

Exosomes, natural nanovesicles that contain a cargo of biologically active molecules such as lipids, proteins, and nucleic acids, are released from cells to the extracellular environment. They then act as autocrine, paracrine, or endocrine mediators of communication between cells by delivering their cargo into recipient cells and causing downstream effects. Exosomes are greatly enriched in miRNAs, which are small non-coding RNAs that act both as cytoplasmic post-transcriptional repression agents, modulating the translation of mRNAs into proteins, as well as nuclear transcriptional gene activators. Neuronal exosomal miRNAs have important physiologic functions in the central nervous system (CNS), including cell-to-cell communication, synaptic plasticity, and neurogenesis, as well as modulating stress and inflammatory responses. Stress-induced changes in exosomal functions include effects on neurogenesis and neuroinflammation, which can lead to the appearance of various neuropsychiatric disorders such as schizophrenia, major depression, bipolar disorder, and Alzheimer's and Huntington's diseases. The current knowledge regarding the roles of exosomes in the pathophysiology of common mental disorders is discussed in this review.

Asunto(s)

Asunto(s)

RESUMEN

BACKGROUND: Medications prescribed for chronic diseases can lead to short-term neuropsychiatric symptoms, but their long-term effects on brain structures and psychiatric conditions remain unclear. METHODS: We comprehensively analyzed the FDA Adverse Event Reporting System database and conducted drug target Mendelian Randomization (MR) studies on six categories of common drugs, 477 brain imaging-derived phenotypes (IDPs) and eight psychiatric disorders. Genetic instruments were extracted from expression quantitative trait loci (eQTLs) in blood, brain, and other target tissues, protein quantitative trait loci (pQTLs) in blood, and genome-wide association studies (GWAS) of hemoglobin and cholesterol. Summary statistics for brain IDPs, psychiatric disorders, and gut microbiome were obtained from the BIG40, Psychiatric Genomics Consortium, and MiBioGen. A two-step MR and mediation analysis were employed to screen possible mediators of drug-IDP effects from 119 gut microbiota genera and identify their mediation proportions. FINDINGS: Among 19 drug classes, six drugs were found to be associated with higher risks of psychiatric adverse events, while 11 drugs were associated with higher risks of gastrointestinal adverse events in the FAERS analysis. We identified ten drug-psychiatric disorder associations, 202 drug-IDP associations, 16 drug-microbiota associations, and four drug-microbiota-IDP causal links. For example, PPARG activation mediated HbA1c reduction caused a higher risk of bipolar disorder (BD) II. Genetically proxied GLP-1R agonists were significantly associated with an increase in the volume of the CA3-head of the right hippocampus and the area of the left precuneus cortex, both of which have been shown to correlate with cognition in previous studies. INTERPRETATION: Common drugs may affect brain structure and risk of psychiatric disorder. Oral medications in particular may exert some of these effects by influencing gut microbiota. This study calls for greater attention to be paid to the neuropsychiatric adverse effects of drugs and encourages drug repurposing. FUNDING: National Natural Science Foundation of China (grant No. 82330035, 82130043, 82172685, and 82001223), National Natural Science Foundation of Hunan Province (grant No. 2021SK1010), and the Science Foundation for Distinguished Young Scholars of Changsha (grant No. kq2209006).

Asunto(s)

RESUMEN

BACKGROUND: Mitochondria is essential for cellular energy production, oxidative stress, and apoptosis. Mitochondrial DNA (mtDNA) encodes essential proteins for mitochondrial function. Although several studies have explored the association between changes in mtDNA copy number (mtDNA-CN) and risk of mental disorders, the results remain debated. This study used a bidirectional two-sample Mendelian randomization (MR) analysis to examine the genetic causality between mtDNA-CN and mental disorders. METHODS: Genome-wide association study (GWAS) data for mtDNA-CN were sourced from UK biobank, involving 383,476 European cases. GWAS data for seven mental disorders-attention deficit/hyperactivity disorder, autism spectrum disorder (ASD), schizophrenia, bipolar disorder, major depressive disorder, anxiety, and obsessive-compulsive disorder-were primarily obtained from the Psychiatric Genomics Consortium. Causal associations were assessed using inverse variance weighting, with sensitivity analyses via the weighted median and MR-Egger methods. Reverse MR considered the seven mental disorders as exposures. All analyses were replicated with additional mtDNA-CN GWAS data from 465,809 individuals in the Heart and Ageing Research in Genomic Epidemiology consortium and the UK Biobank. RESULTS: Forward MR observed a 27 % decrease in the risk of ASD per standard deviation increase in genetically determined blood mtDNA-CN (OR = 0.73, 95%CI: 0.58-0.92, p = 0.002), with no causal effects on other disorders. Additionally, reverse MR did not indicate a causal association between any of the mental disorders and mtDNA-CN. Validation analyses corroborated these findings, indicating their robustness. CONCLUSIONS: Our study supports the potential causal association between mtDNA-CN and the risk of ASD, suggesting that mtDNA-CN could serve as a promising biomarker for early screening of ASD.

Asunto(s)

RESUMEN

Early-life adversity (ELA) is characterized by exposure to traumatic events during early periods of life, particularly involving emotional, sexual and/or physical adversities during childhood. Mental disorders are strongly influenced by environmental and lifestyle-related risk factors including ELA. However, the molecular link between ELA and the risk of an adult mental disorder is still not fully understood. Evidence is emerging that long-lasting changes in the epigenetic processes regulating gene expression, such as DNA methylation, play an important role in the biological mechanisms linking ELA and mental disorders. Based on a recent study, we analyzed the DNA methylation of a specific CpG site within the gene PXDN-cg10888111-in blood in the context of ELA across a set of psychiatric disorders, namely Borderline Personality Disorder (BPD), Major Depressive Disorder (MDD) and Social Anxiety Disorder (SAD), and its potential contribution to their pathogenesis. We found significant hypermethylation in mentally ill patients with high levels of ELA compared to patients with low levels of ELA, whereas cg10888111 methylation in healthy control individuals was not affected by ELA. Further investigations revealed that this effect was driven by the MDD cohort. Providing a direct comparison of cg10888111 DNA methylation in blood in the context of ELA across three mental disorders, our results indicate the role of PXDN regulation in the response to ELA in the pathogenesis of mental disorders, especially MDD. Further studies will be needed to validate these results and decipher the corresponding biological network that is involved in the transmission of ELA to an adult mental disorder in general.

Asunto(s)

RESUMEN

Earlier studies have revealed microRNAs (miRNAs) as potential biomarkers for neurological conditions, however, such evidence on psychiatric outcomes is limited. We utilized the Normative Aging Study (NAS) cohort to investigate the associations between extracellular miRNAs (ex-miRNA) and psychiatric symptoms among a group of older male adults, along with the targeted genes and biological pathways. We studied 569 participants with miRNA profile primarily measured in extracellular vesicles isolated from plasma, and psychiatric symptoms reported over 1996-2014 with repeated measures. Global and dimension scales of psychiatric symptoms were measured via the administration of Brief Symptom Inventory (BSI) per visit covering nine aspects of psychiatric health, such as anxiety, depression, hostility, psychoticism, etc. Ex-miRNAs were profiled using small RNA sequencing. Associations of expression of 395 ex-miRNAs (present in >70% samples) with current mental status were assessed using single-miRNA as well as Least Absolute Shrinkage and Selection Operator (LASSO)-based multi-miRNAs linear mixed effects models adjusting for key demographic and behavioral factors. Biological functions were explored using pathway analyses. We identified ex-miRNAs associated with each BSI scale. In particular, hsa-miR-320d was consistently identified for two global scales. Similar overlapping miRNAs across global and dimension scores included hsa-miR-379-3p, hsa-miR-1976, hsa-miR-151a-5p, hsa-miR-151b, hsa-miR-144-3p, etc. Top KEGG pathways for identified miRNAs included p53 signaling, Hippo signaling, FoxO signaling, protein processing in endoplasmic reticulum and several pathways related with cancer and neurological diseases. This study provided early evidence supporting the associations between extracellular miRNAs and psychiatric conditions. MiRNAs may serve as biomarkers of subclinical psychiatric illness in older adults.

Asunto(s)

RESUMEN

The Krüppel-like factor (KLF) family represents a group of transcription factors (TFs) performing different biological processes that are crucial for proper neuronal function, including neuronal development, synaptic plasticity, and neuronal survival. As reported, genetic variants within the KLF family have been associated with a wide spectrum of neurodevelopmental and psychiatric symptoms. In a patient exhibiting attention deficit hyperactivity disorder (ADHD) combined with both neurodevelopmental and psychiatric symptoms, whole-exome sequencing (WES) analysis revealed a de novo heterozygous variant within the Krüppel-like factor 13 (KLF13) gene, which belongs to the KLF family and regulates axonal growth, development, and regeneration in mice. Moreover, in silico analyses pertaining to the likely pathogenic significance of the variant and the impact of the mutation on the KLF13 protein structure suggested a potential deleterious effect. In fact, the variant was localized in correspondence to the starting residue of the N-terminal domain of KLF13, essential for protein-protein interactions, DNA binding, and transcriptional activation or repression. This study aims to highlight the potential involvement of the KLF13 gene in neurodevelopmental and psychiatric disorders. Nevertheless, we cannot rule out that excluded variants, those undetectable by WES, or the polygenic risk may have contributed to the patient's phenotype given ADHD's high polygenic risk. However, further functional studies are required to validate its potential contribution to these disorders.

Asunto(s)