Clinical and histological features of nonalcoholic steatohepatitis in Iranian patients

BACKGROUND: Although several studies have been performed on risk factors and natural course of NASH, it seems that NASH tends to be more than a disease confined to strict boundaries. The objective of this study was to assess the clinical and paraclinical features and risk factors for non-alcoholic steatohepatitis (NASH) patients in an Iranian population METHODS: Patients with histologically confirmed NASH who had elevated liver aminotransaminases, negative serologic markers of viral or autoimmune hepatitis and no findings in favor of metabolic liver disease were enrolled. A careful history was taken regarding alcohol intake. RESULTS: 53 patients consisting of 32 male and 21 female entered the study. The mean age was 37.8 ± 11.3 years. Twenty-six patients (55.3%) were overweight, 15 (31.9%) obese, 40 (75.5%) dyslipidemic, and three patients (5.7%) were diabetic. Liver biopsy showed mild steatosis in 35.7%, moderate steatosis in 53.6%, and severe forms in 10.7%. In 80.2% of patients, portal inflammation was present, and 9.4% had cirrhosis. The amount of increase in liver enzymes bore no relationship with fibrosis, portal inflammation, and degree of steatosis. CONCLUSIONS: The patients in our study showed a male predominancy and were somewhat younger than other studies

The Effect of Low-Power Laser Therapy on the TGF/β Signaling Pathway in Chronic Kidney Disease: A Review

Objective: The purpose of this study is to investigate the effects of low-power lasers on kidney disease by investigating several studies.Methods: A number of articles from 1998 to 2019 were chosen from the sources of PubMed, Scopus, and only the articles studying the effect of low-power lasers on kidney disease were investigated.Results: After reviewing the literature, 21 articles examining only the effects of low-power lasers on kidney disease were found. The results of these studies showed that the parameter of the low-power laser would result in different outcomes. So, a low-power laser with various parameters can be effective in the treatment of kidney diseases such as acute kidney disease, diabetes, glomerulonephritis, nephrectomy, metabolic syndrome, and kidney fibrosis. Most studies have shown that low-power lasers can affect TGFβ1 signaling which is the most important signaling in the treatment of renal fibrosis.Conclusion: Lasers can be effective in reducing or enhancing inflammatory responses, reducing fibrosis factors, and decreasing reactive oxygen species (ROS) levels in kidney disease and glomerular cell proliferation

Protective effect of Photobiomodulation Therapy and Bone Marrow Stromal Stem Cells Conditioned Media on Pheochromocytoma Cell Line 12 Against Oxidative Stress Induced by Hydrogen Peroxide

Introduction: Bone marrow stromal stem cells (BMSCs), a type of adult stem cells, secrete bioactive molecules such as trophic factors, growth factors, chemokine and cytokines that may be effective against oxidative stress in neurodegenerative diseases.In this study, we examined the protective effect of BMSCs conditioned media CM) and photobiomodulation therapy (PBMT) on PC12 cells exposed to H2O2 as an oxidative injury model.Methods: BMSCs were cultured and confirmed by flow cytometry analysis and underwent osteogenic and adipogenic differentiation. Then, PC12-H2O2 cells were co-treated with BMSCs-CM and PBMT. The effect of BMSCs-CM and PBMT (He-Ne laser, 632.8 nm, 3 mW, 1.2 J/cm2, 378 s) on Bax/Bcl2 expression, cell viability, was assessed by real-time PCR and MTT assay. The length of the Neurite and cell body areas were assessed by Cell A software.Results: Flowcytometry analysis, as well as osteogenic and adipogenic staining, confirmed the BMSCs. The length of the Neurite was the highest in the group which received CM+PBMT and cell body areas were significant in CM+PBMT compared to other groups. Based on our results, elevating H2O2 concentration increased cell death significantly and using concentrations of 250 μM resulted in a dramatic increase in the mortality compared to the other groups.Conclusion: Our result demonstrated that the combination of CM +PBMT has a protective effect on PC12 cells against oxidative stress

Pleiotropy with sex-specific traits reveals genetic aspects of sex differences in Parkinson's disease

Parkinson’s disease is an age-related neurodegenerative disorder with a higher incidence in males than females. The causes for this sex difference are unknown. Genome-wide association studies (GWAS) have identified 90 Parkinson’s disease risk loci, but the genetic studies have not found sex-specific differences in allele frequency on autosomal chromosomes or sex chromosomes. Genetic variants, however, could exert sex-specific effects on gene function and regulation of gene expression. To identify genetic loci that might have sex-specific effects, we studied pleiotropy between Parkinson’s disease and sex-specific traits. Summary statistics from GWASs were acquired from large-scale consortia for Parkinson’s disease (n cases = 13 708; n controls = 95 282), age at menarche (n = 368 888 females) and age at menopause (n = 69 360 females). We applied the conditional/conjunctional false discovery rate (FDR) method to identify shared loci between Parkinson’s disease and these sex-specific traits. Next, we investigated sex-specific gene expression differences in the superior frontal cortex of both neuropathologically healthy individuals and Parkinson’s disease patients (n cases = 61; n controls = 23). To provide biological insights to the genetic pleiotropy, we performed sex-specific expression quantitative trait locus (eQTL) analysis and sex-specific age-related differential expression analysis for genes mapped to Parkinson’s disease risk loci. Through conditional/conjunctional FDR analysis we found 11 loci shared between Parkinson’s disease and the sex-specific traits age at menarche and age at menopause. Gene-set and pathway analysis of the genes mapped to these loci highlighted the importance of the immune response in determining an increased disease incidence in the male population. Moreover, we highlighted a total of nine genes whose expression or age-related expression in the human brain is influenced by genetic variants in a sex-specific manner. With these analyses we demonstrated that the lack of clear sex-specific differences in allele frequencies for Parkinson’s disease loci does not exclude a gen- etic contribution to differences in disease incidence. Moreover, further studies are needed to elucidate the role that the candidate genes identified here could have in determining a higher incidence of Parkinson’s disease in the male population.publishedVersio

The genetic landscape of basal ganglia and implications for common brain disorders.

The basal ganglia are subcortical brain structures involved in motor control, cognition, and emotion regulation. We conducted univariate and multivariate genome-wide association analyses (GWAS) to explore the genetic architecture of basal ganglia volumes using brain scans obtained from 34,794 Europeans with replication in 4,808 white and generalization in 5,220 non-white Europeans. Our multivariate GWAS identified 72 genetic loci associated with basal ganglia volumes with a replication rate of 55.6% at P < 0.05 and 87.5% showed the same direction, revealing a distributed genetic architecture across basal ganglia structures. Of these, 50 loci were novel, including exonic regions of APOE, NBR1 and HLAA. We examined the genetic overlap between basal ganglia volumes and several neurological and psychiatric disorders. The strongest genetic overlap was between basal ganglia and Parkinsons disease, as supported by robust LD-score regression-based genetic correlations. Mendelian randomization indicated genetic liability to larger striatal volume as potentially causal for Parkinsons disease, in addition to a suggestive causal effect of greater genetic liability to Alzheimers disease on smaller accumbens. Functional analyses implicated neurogenesis, neuron differentiation and development in basal ganglia volumes. These results enhance our understanding of the genetic architecture and molecular associations of basal ganglia structure and their role in brain disorders

Charting the Landscape of Genetic Overlap Between Mental Disorders and Related Traits Beyond Genetic Correlation.

OBJECTIVE: Mental disorders are heritable and polygenic, and genome-wide genetic correlations (rg) have indicated widespread shared genetic risk across multiple disorders and related traits, mirroring their overlapping clinical characteristics. However, rg may underestimate the shared genetic underpinnings of mental disorders and related traits because it does not differentiate mixtures of concordant and discordant genetic effects from an absence of genetic overlap. Using novel statistical genetics tools, the authors aimed to evaluate the genetic overlap between mental disorders and related traits when accounting for mixed effect directions. METHODS: The authors applied the bivariate causal mixture model (MiXeR) to summary statistics for four mental disorders, four related mental traits, and height from genome-wide association studies (Ns ranged from 53,293 to 766,345). MiXeR estimated the number of causal variants for a given trait (polygenicity), the number of variants shared between traits, and the genetic correlation of shared variants (rgs). Local rg was investigated using LAVA. RESULTS: Among mental disorders, ADHD was the least polygenic (5.6K causal variants), followed by bipolar disorder (8.6K), schizophrenia (9.6K), and depression (14.5K). Most variants were shared across mental disorders (4.4K-9.3K) and between mental disorders and related traits (5.2K-12.8K), but with disorder-specific variations in rg and rgs. Overlap with height was small (0.7K-1.1K). MiXeR estimates correlated with LAVA local rg (r=0.88, p<0.001). CONCLUSIONS: There is extensive genetic overlap across mental disorders and related traits, with mixed effect directions and few disorder-specific variants. This suggests that genetic risk for mental disorders is predominantly differentiated by divergent effect distributions of pleiotropic genetic variants rather than disorder-specific variants. This represents a conceptual advance in our understanding of the landscape of shared genetic architecture across mental disorders, which may inform genetic discovery, biological characterization, nosology, and genetic prediction

Shared genetic loci between depression and cardiometabolic traits

Epidemiological and clinical studies have found associations between depression and cardiovascular disease risk factors, and coronary artery disease patients with depression have worse prognosis. The genetic relationship between depression and these cardiovascular phenotypes is not known. We here investigated overlap at the genome-wide level and in individual loci between depression, coronary artery disease and cardiovascular risk factors. We used the bivariate causal mixture model (MiXeR) to quantify genome-wide polygenic overlap and the conditional/conjunctional false discovery rate (pleioFDR) method to identify shared loci, based on genome-wide association study summary statistics on depression (n = 450,619), coronary artery disease (n = 502,713) and nine cardiovascular risk factors (n = 204,402–776,078). Genetic loci were functionally annotated using FUnctional Mapping and Annotation (FUMA). Of 13.9K variants influencing depression, 9.5K (SD 1.0K) were shared with body-mass index. Of 4.4K variants influencing systolic blood pressure, 2K were shared with depression. ConjFDR identified 79 unique loci associated with depression and coronary artery disease or cardiovascular risk factors. Six genomic loci were associated jointly with depression and coronary artery disease, 69 with blood pressure, 49 with lipids, 9 with type 2 diabetes and 8 with c-reactive protein at conjFDR < 0.05. Loci associated with increased risk for depression were also associated with increased risk of coronary artery disease and higher total cholesterol, low-density lipoprotein and c-reactive protein levels, while there was a mixed pattern of effect direction for the other risk factors. Functional analyses of the shared loci implicated metabolism of alpha-linolenic acid pathway for type 2 diabetes. Our results showed polygenic overlap between depression, coronary artery disease and several cardiovascular risk factors and suggest molecular mechanisms underlying the association between depression and increased cardiovascular disease risk.publishedVersio

Genetic Alterations in War-Related Post-Traumatic Stress Disorder: A Systematic Review

Objectives: This systematic review explored gene expression and DNA methylation patterns to identify key pathways and molecular targets associated with post-traumatic stress disorder (PTSD), particularly its war-related subtype.Methods: A comprehensive search of PubMed, Scopus, and Web of Science was conducted using keywords related to PTSD, gene expression, and DNA methylation. Studies published between 2000 to 2024 involving adult military personnel with confirmed PTSD based on the Diagnostic and Statistical Manual of Mental Disorders-5 (DSM-5) criteria were included. Animal studies, psychological interventions, and pharmacological research were excluded. Only cross-sectional, case-control, or cohort studies utilizing blood, saliva, or brain tissue samples were considered. Data from 28 studies were extracted using a predefined framework, focusing on population characteristics, study design, and identified hub genes.Results: Key findings revealed the upregulation of immune-related genes (e.g., CCL4, NF-κB) and hypomethylation of inflammation-related genes. Downregulation of neurodevelopmental genes, such as Brain-Derived Neurotropic Factor (BDNF) and Down syndrome cell adhesion molecule (DSCAM), highlighted disruptions in synaptic plasticity. The identified pathways suggested potential biomarkers and therapeutic targets for precision medicine approaches.Conclusion: This review highlighted the role of gene expression alterations in war-related PTSD. The identified genes might serve as candidates for personalized therapies. Further research is required to validate these findings and develop targeted interventions

Characterizing the Shared Genetic Underpinnings of Schizophrenia and Cardiovascular Disease Risk Factors

ObjectiveSchizophrenia is associated with increased risk of cardiovascular disease (CVD), although there is variation in risk among individuals. There are indications of shared genetic etiology between schizophrenia and CVD, but the nature of the overlap remains unclear. The aim of this study was to fill this gap in knowledge.MethodsOverlapping genetic architectures between schizophrenia and CVD risk factors were assessed by analyzing recent genome-wide association study (GWAS) results. The bivariate causal mixture model (MiXeR) was applied to estimate the number of shared variants and the conjunctional false discovery rate (conjFDR) approach was used to pinpoint specific shared loci.ResultsExtensive genetic overlap was found between schizophrenia and CVD risk factors, particularly smoking initiation (N=8.6K variants) and body mass index (BMI) (N=8.1K variants). Several specific shared loci were detected between schizophrenia and BMI (N=304), waist-to-hip ratio (N=193), smoking initiation (N=293), systolic (N=294) and diastolic (N=259) blood pressure, type 2 diabetes (N=147), lipids (N=471), and coronary artery disease (N=35). The schizophrenia risk loci shared with smoking initiation had mainly concordant effect directions, and the risk loci shared with BMI had mainly opposite effect directions. The overlapping loci with lipids, blood pressure, waist-to-hip ratio, type 2 diabetes, and coronary artery disease had mixed effect directions. Functional analyses implicated mapped genes that are expressed in brain tissue and immune cells.ConclusionsThese findings indicate a genetic propensity to smoking and a reduced genetic risk of obesity among individuals with schizophrenia. The bidirectional effects of the shared loci with the other CVD risk factors may imply differences in genetic liability to CVD across schizophrenia subgroups, possibly underlying the variation in CVD comorbidity

Dissecting the Shared Genetic Architecture of Common Epilepsies With Cortical Brain Morphology.

BACKGROUND AND OBJECTIVES: Epilepsies are associated with differences in cortical thickness (TH) and surface area (SA). However, the mechanisms underlying these relationships remain elusive. We investigated the extent to which these phenotypes share genetic influences. METHODS: We analyzed genome-wide association study data on common epilepsies (n = 69,995) and TH and SA (n = 32,877) using Gaussian mixture modeling MiXeR and conjunctional false discovery rate (conjFDR) analysis to quantify their shared genetic architecture and identify overlapping loci. We biologically interrogated the loci using a variety of resources and validated in independent samples. RESULTS: The epilepsies (2.4 k-2.9 k variants) were more polygenic than both SA (1.8 k variants) and TH (1.3 k variants). Despite absent genome-wide genetic correlations, there was a substantial genetic overlap between SA and genetic generalized epilepsy (GGE) (1.1 k), all epilepsies (1.1 k), and juvenile myoclonic epilepsy (JME) (0.7 k), as well as between TH and GGE (0.8 k), all epilepsies (0.7 k), and JME (0.8 k), estimated with MiXeR. Furthermore, conjFDR analysis identified 15 GGE loci jointly associated with SA and 15 with TH, 3 loci shared between SA and childhood absence epilepsy, and 6 loci overlapping between SA and JME. 23 loci were novel for epilepsies and 11 for cortical morphology. We observed a high degree of sign concordance in the independent samples. DISCUSSION: Our findings show extensive genetic overlap between generalized epilepsies and cortical morphology, indicating a complex genetic relationship with mixed-effect directions. The results suggest that shared genetic influences may contribute to cortical abnormalities in epilepsies