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Major depression and suicide are critical public health concerns, particularly in underrepresented populations with unique genetic and sociocultural contexts. The Maya-mestizo population presents the highest suicide rates in the country but remains understudied in psychiatric genetics. This study evaluated the association between three genetic variants, rs7305115 (TPH2), rs6265 (BDNF), and rs2428707 (HTR2C), and the presence of major depression, melancholic subtype, and suicide risk in Maya-mestizo adults. A total of 598 participants were recruited from urban and rural areas. Psychiatric evaluations were performed using the MINI 5.0 (DSM-IV), and functional status was assessed with the Karnofsky scale. Genotyping was performed with TaqMan assays, and ancestry was confirmed with ancestry-informative markers. Analyses included Hardy-Weinberg equilibrium testing and logistic regression models adjusted for sex and included age, body mass index, Karnofsky performance scale score, and sociodemographic variables as covariates. The prevalence of major depression was 38.9%, while suicide risk reached 24.7%. The rs2428707 variant of HTR2C was significantly associated with major depression (OR 2.31, 95% CI 1.03-5.18, p = 0.041). Variants in TPH2 and BDNF were associated with the melancholic subtype. No statistically significant associations were found with suicide risk, though overlap with depressive phenotypes suggests shared vulnerability. This first report of psychiatric genetics in the Maya-mestizo population highlights the need for culturally and genetically tailored interventions. Show less

Studies have reported that the prevalence of aggression is higher in individuals with schizophrenia compared to the general population. Various factors, including genetic variations, contribute to the emergence of aggression in patients with schizophrenia. Among these, the monoamine oxidase A (MAOA) and brain-derived neurotrophic factor (BDNF) genes are considered key genetic factors potentially influencing aggressive behavior in schizophrenia. This study investigated the association of BDNF rs6265 and MAOA rs1465108 polymorphisms with aggression in schizophrenia. A total of 150 patients diagnosed with schizophrenia were included in the study. The MAOA rs1465108 and BDNF rs6265 polymorphisms were analyzed using the Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) method. Aggression was evaluated using the Buss-Perry Aggression Questionnaire. Suicide risk, childhood trauma, and impulsivity which were related to aggression were evaluated using the Suicide Probability Scale, the Childhood Trauma Questionnaire, and the Barratt Impulsiveness Scale, respectively. Negative and positive symptoms of schizophrenia were assessed using the Scale for the Assessment of Negative Symptoms (SANS) and the Scale for the Assessment of Positive Symptoms (SAPS), respectively. No direct genotype associations were observed between aggression and the BDNF rs6265 and MAOA rs1465108 polymorphisms. However, impulsivity, SAPS, and SANS scores were significantly associated with aggression. These findings highlight that aggression in schizophrenia is primarily shaped by environmental and clinical factors rather than by BDNF or MAOA variants. Show less

Major Depressive Disorder (MDD) is a multifactorial psychiatric disease influenced by a combination of genetic and environmental factors. Among the genes linked to MDD, the Melanocortin 1 Receptor (MC1R), Catechol-O-Methyltransferase (COMT), Brain-Derived Neurotrophic Factor (BDNF), and the serotonin transporter (5-HTT) are of particular interest due to their critical roles in stress regulation and neural function. Despite their biological significance, the contribution of specific polymorphisms within these genes to MDD risk remains understudied. This retrospective observational case-control study included 87 Colombian patients diagnosed with MDD according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV). The control group comprised Latino/admixed individuals without, sourced from the gnomAD v2.1.1 database. The complete coding region of the MC1R gene and three polymorphisms: 5-HTTLPR Insertion/Deletion 44 bp, BDNF-c.196G>A, and COMT-c.472G>A were genotyped using PCR and Sanger sequencing. The polymorphisms rs885479 and rs4680 were identified as protective factors against MDD, while the polymorphisms rs796296176, rs779504604, rs1805005 were associated with an increased risk of developing MDD (OR:22.87, OR:51.26, OR: 1.97, respectively). Several of the analyzed polymorphisms (rs796296176, rs779504604, rs1805005) increase the risk for MDD. Notably, we provide novel evidence of these polymorphisms in MC1R as a risk to MDD. Show less

Facial and Emotional Recognition Systems are technologies that primarily use AI and machine learning to analyze various inputs like facial expression, speech, and physiological signals, to identify and classify human emotions and link them to a variety of epigenomic traits and states. We conducted a Meta-Meta Analysis via Pharmacogenomics (PGx) and Genome-Wide Association Studies (GWAS) across two separate manifestations, including facial physics and emotional expressions. Applying GWAS datasets, 10 GWAS datasets were included, and following multiple filtrations, a GWAS Meta-Meta analysis led to a Secondary Gene List (SGL) of 586 members. Additionally, various indepth silico analyses, such as Protein-Protein Interactions (PPIs), refined 300 genes into a unified network, then, by adding 10 GARS genes, 309 genes remained. A different analysis of PPIs uncovered 141 connected genes (Final Gene List: FGL); more precisely, we conducted a PGx-based approach on this FGL. Finally, 1,480 annotations were found, among them, 682 annotations were significant; thus, we considered the genes with at least one significant annotation and found 54 Pharmacogenes in FGL (PGx-FGL). Through this in-depth analysis, we identified strong, significant top phenotypic roles for both DRD2 and BDNF linking genes in 48,780,906 subjects. Our PGx-based GWAS meta-meta-analyses, coupled with genetic and epigenetic liability testing, connected Facial and Emotional Recognition Systems to Spectrum Disorders (Attention-Deficit Hyperactivity Disorder: ADHD and Autism), Schizophrenia, Depression, and Anxiety. We propose that these findings could have heuristic therapeutic targeting potential and, as such, require intensive further clinical support. Show less

A single nucleotide polymorphism in the brain derived neurotrophic factor (BDNF)-encoding gene leads to diminished BDNF signaling resulting from Val66Met and has been linked to obesity. Previous imaging studies regarding the impact of BDNF Val66Met on the central serotonin system, which is involved in behavior, cognition and control of satiety, have not focused on body weight or food-intake related behavior. We revisited a cohort of thirty non-depressed individuals with obesity and 15 normal-weight controls. 29 obese and 13 controls underwent [ Show less

Major Depressive Disorder (MDD) is a debilitating and multifactorial neuropsychiatric condition that significantly contributes to the global burden of disease. Its clinical spectrum encompasses persistent low mood, anhedonia, cognitive decline, neurovegetative disturbances, and suicidality. This review synthesizes current evidence on the neurovascular, neurochemical, genetic, and psychosocial mechanisms underlying MDD. A narrative review approach was employed, incorporating data from peer-reviewed publications retrieved through systematic searches in biomedical databases. Emphasis was placed on recent findings that elucidate the interplay between neurobiological dysfunction and systemic influences in MDD pathogenesis. MDD pathophysiology is intricately linked to dysregulation of monoaminergic neurotransmission, aberrant hypothalamic-pituitary-adrenal (HPA) axis activity, and chronic neuroinflammation. Glial cell impairment, particularly involving astrocytes and microglia, disrupts synaptic homeostasis and neurovascular integrity. Genetic analyses estimate a heritability range of 30-50%, with genome-wide association studies identifying susceptibility loci in synaptic and immune pathways. Epigenetic modifications and perturbations of the gut- brain axis modulate vulnerability and progression. Oxidative stress and attenuated neurotrophic signalling, especially involving brain-derived neurotrophic factor (BDNF), further exacerbate neural circuit dysfunction. Sociodemographic determinants, including sex, psychosocial stressors, and socioeconomic adversity, also shape disease onset and trajectory. Although therapeutic modalities exist, limitations in early detection, treatment response, and long-term remission underscore the need for individualized strategies. Emerging approaches integrating epigenetic biomarkers and systems biology hold potential for precision psychiatry. A systems-level, biopsychosocial understanding of MDD is essential to advance targeted, personalized interventions, ultimately improving clinical outcomes in this complex disorder. Show less

BackgroundAlthough the molecular basis of Alzheimer's disease (AD) is often studied in Caucasians, its genetic basis in Bangladesh remains elusive.ObjectiveWe explored the association between single-nucleotide variants (SNVs) of Apolipoprotein E ( Show less

Chemotherapy-induced peripheral neuropathy (CIPN) remains a major unmet challenge in oncology, affecting treatment adherence and patient quality of life. Despite its prevalence, reliable predictive biomarkers and targeted neuroprotective strategies remain elusive. This study integrates clinical data, whole-genome sequencing, and translational research to identify genetic determinants of CIPN susceptibility and validate therapeutic approaches. Through comprehensive analysis of patients with colorectal cancer, including neurophysiological evaluations and CIPN-specific quality-of-life assessments, we identified the Show less

Conflicting results on the association of the Using combinations of various key terms, articles in PubMed, Google Scholar, and Web of Science, written in English were collected until October 31, 2024. Data were extracted independently by two authors and analyzed using Review Manager 5.4. Fifteen studies that are compliant with the HWE, providing a total of 14,184 participants were included in this meta-analysis after applying predefined inclusion/exclusion criteria based on study design, DSM-based diagnosis, and availability of genotype counts. Most pooled models demonstrated low to moderate heterogeneity with significant associations in the recessive model only. In the subgroup analysis, a significant effect was observed in the PD-uncategorized cohort. The Our updated meta-analysis suggests that the Show less

Traumatic brain injury (TBI) is a well-recognized risk factor for late-life cognitive decline. However, few studies have examined individual differences in sex and genetics, which may modify risk. We examined sex differences in gene-TBI interactions for dementia risk genes apolipoprotein E (APOE) and selected brain-derived neurotrophic factor (BDNF) single-nucleotide polymorphisms (SNPs) in predicting late-life cognitive decline. We studied 4293 individuals without dementia at baseline (mean age: 74.93, SD: 6.87 years, 57% female). Approximately 25% reported a history of TBI. Linear mixed effects models examined associations between sex, TBI characteristics, APOE genotype, BDNF SNPs and their interactions, with cognitive decline. Compared to males, females experienced fewer TBIs across the lifespan, the majority occurring in late-life. Number of TBI interacted with sex and APOE genotype such that female APOE ε4 allele carriers with multiple TBIs exhibited worse outcomes on global cognition (P < .001; eg, ε4+/TBI2+ estimated marginal means [EMMs] from baseline to year 10 = -17.22 points compared with ε4-/TBI2+ = -7.21), whereas males did not exhibit differential decline by APOE ε4 alleles and TBI number. BDNF Val66Met genotype showed trend-level moderation of TBI history and cognitive decline, with slower decline experienced by heterozygous individuals with multiple TBIs compared with homozygous major allele carriers. There were few significant associations between timing and severity of TBI with cognitive outcomes. These results underscore the importance of considering individual differences of sex and APOE and BDNF-related gene variants on the long-term cognitive effects of TBI. Show less

Brain-derived neurotrophic factor (BDNF) has been suggested to support dopaminergic neuron's endurance and dopamine release. Its Val66Met polymorphism might modify Parkinson's disease (PD) evolution, although evidence in Asian populations remains limited. This study aimed to explore how the BDNF rs6265 genotypes are associated with the clinical characteristics and longitudinal progression patterns of PD patients in a Korean population. A total of 247 patients were enrolled and followed for a mean duration of 50.9 ± 23.9 months. Baseline and/or periodic assessments captured motor severity, non-motor burden, cognition, orthostatic stress, cardiac denervation, and presynaptic dopamine transporter availability. The repeated measures were manipulated to infer any genotypic differences in the trajectories of each clinical domain. Genotype frequencies were 31.2% (77/247) for Val/Val and 68.8% (170/247) for Met-allele carriers. Baseline clinical characteristics and presynaptic dopamine transporter availability were comparable between genotypes; however, Val homozygotes showed more preserved myocardial innervation and poorer non-frontal cognitive performance. Longitudinal analyses demonstrated genotype-specific increases in motor and cognitive severity. Compared to Met-allele carriers, the homozygous Val group exhibited accelerated motor progression and more rapid decline in frontal domain after three years of follow-up. The differences in myocardial denervation at diagnosis, cognitive profiles, and motor progression might suggest a potential modulatory role of BDNF polymorphism in PD progression in the Korean population. Show less

Growing evidence implicates accelerated biological aging in environmentally induced psychiatric disorders, yet its role in metal-associated depression remains unclear. Using NHANES data, we evaluated associations between heavy metal mixtures and depression. Bidirectional mediation analysis was used to assess reciprocal pathways linking heavy metals, biological aging, and depression. Simultaneously, candidate genes linking heavy metal exposure to depression and biological aging were identified by mining the Comparative Toxicogenomics Database, analyzing differentially expressed genes (DEGs) from the Gene Expression Omnibus, and integrating the resulting evidence within a toxicogenomic framework to explore potential molecular mechanisms. The prevalence of depression among participants was 8.66 %. Metal mixtures significantly increased depression risk. Notably, cadmium and antimony increased the risk of depression (OR: 1.52, 95 % CI: 1.19, 1.94 and OR: 1.54, 95 % CI: 1.22, 1.93). Both metals have low thresholds (0.227 μg/L and 0.053 μg/L, respectively). Additionally, lead, cobalt, and molybdenum showed positive associations in specific models. Although population-level exposure to heavy metals declined from 1999 to 2020, concentrations remained sufficient to elevate depression risk. Our correlation analysis also identified a strong correlation between PhenoAge and chronological age (r = 0.84, P < 0.001). Mechanistically, we found that accelerated PhenoAge partially mediated the associations of several metals with depression risk, including monomethylarsonic acid (β = 0.004; 95 %CI: 0.003,0.006), cadmium (β = 0.006; 95 %CI: 0.003, 0.010), lead (β = 0.009; 95 %CI: 0.006, 0.011), cobalt (β = 0.010; 95 %CI: 0.006, 0.013), molybdenum (β = 0.009; 95 %CI: 0.006, 0.011), and antimony (β = 0.008; 95 %CI: 0.005, 0.011). Pathway analysis and DEGs implicated the contribution of neurodegeneration-multiple diseases pathway, with core molecular targets centering on BDNF, IL6, GSK3B, PTGS2, and SOD1. These findings, which imply biological aging as a potential link between metal exposure and depression, call for revised safety thresholds and pinpoint molecular targets for intervention. Show less

Pharmacogenomics (PGx) is a scientific field that aims to understand how an individual's genetic code regulates drug metabolism and response. The response to many anesthetic drugs varies widely among patients due to many factors including, but not limited to, age, gender, and comorbidities. However, PGx contributes to this variability, particularly regarding adverse drug reactions. This review explores the influence of PGx on five commonly used induction agents in anesthesia: propofol, midazolam, ketamine, etomidate, and thiopental. Propofol metabolism is significantly affected by polymorphisms in CYP2B6, CYP2C9, and UGT1A9, influencing both efficacy and toxicity. Midazolam's PGx is mainly mediated by variations in CYP3A4, CYP3A5, and UDP-glucuronosyltransferase enzymes, with implications for sedation depth and drug clearance. Ketamine response is modulated by polymorphisms in metabolic enzymes (e.g. CYP2B6), as well as neurobiological targets such as brain-derived neurotrophic factor and gamma-aminobutyric acid (GABA) receptors, particularly in psychiatric applications. Etomidate shows less studied but emerging PGx associations, including single-nucleotide polymorphisms in GABA receptor subunits and metabolic enzymes, which may affect both sedative depth and cardiovascular stability. Thiopental is a rapid-acting metabolite whose effect stems from GABA-A receptor potentiation; no studies have yet identified specific genetic polymorphisms influencing its action. Overall, PGx provides a promising avenue for tailoring anesthetic management to improve patient safety and outcomes. However, clinical integration remains limited due to practical and infrastructural barriers. This review highlights the potential and current limitations of pharmacogenomic-guided anesthesia, underscoring its relevance in the era of precision medicine. Show less