Fufang Baizhi tincture protects melanocytes from oxidative stress by targeting CASP7-mediated apoptosis and EP300-associated transcriptional regulation.

Genetically-predicted placental gene expression links to uterine fibroids and endometriosis.

OCA2, a melanosome transmembrane spanning protein, functions to regulate melanosomal pH, optimizing production of melanin pigment. OCA2 is one of eight non-syndromic autosomal recessive oculocutaneous albinism (OCA) loci and is the second most common cause of OCA worldwide. Genome wide association studies (GWAS) have identified OCA2 coding and regulatory variants linked to common skin and eye color pigment variation, skin cancer susceptibility, and retinal pigment epithelium tissue metrics. Within a cohort of 106 OCA2 probands with two biallelic OCA2 variants, a total of 74 distinct OCA2 rare variants were identified (11 large structural, 17 small indel/frameshift, 12 splice site, and 34 missense coding variants). Phase-validated haplotypes, comprised of both OCA2 common pigmentation trait GWAS alleles and rare variants, were obtained for 95/106 probands. In total, 41 distinct multi-allele OCA2 haplotypes were identified with 27 haplotypes containing either rs1800404-A and/or rs12913832-G alleles, each of which is known to reduce correct isoform splicing or gene expression by ~20%. These results find that common GWAS alleles with known OCA2 functional impact are present on haplotypes with variants of unknown significance in OCA2 probands and highlight the need for haplotype-based analysis at the OCA2 locus in addition to individual variant pathogenic assessment.

Integrating genome-wide association study and functional analysis identify PvPdcd6 and PvDnajc22 as two key regulators of Vibrio parahaemolyticus resistance in Penaeus vannamei.

Genomic medicine is transforming psychiatry by revealing the genetic aetiology of mental illness. The diversity of India’s population presents a singular opportunity to incorporate genomic information into psychiatric practice. This review discusses recent developments in psychiatric genomics, such as Genome-Wide Association Studies (GWAS), Polygenic Risk Scores (PRS), and pharmacogenomics, which facilitate more tailored mental health interventions. Pharmacogenomics promises to individualise treatments based on genetic profiles, whereas epigenetics and gene-environment interactions shed light on the biological underpinnings of mental health across various sociocultural settings. Genomic psychiatry in India has the potential to be applied in personalised medicine, early risk prediction, targeted therapies, and informing national mental health policy. Yet, the uptake of genomic psychiatry is hindered by infrastructure constraints, ethical as well as privacy issues, and the requirement of cultural competence. The proposed directions include increased research, combining genomic Learning Health Systems (gLHS), and use of Artificial Intelligence (AI) in predictive analytics. This review sums up with major recommendations for progressing genomic psychiatry in India through modifications in policy, funding for research, and public education efforts.

Causal relationship between recent feelings of depression and malignant lymphoma: A two-sample Mendelian randomization analysis.

Genome-wide association study reveals the genetic basis of meat quality traits in Sichuan Shelduck.

Causal associations between chronic obstructive pulmonary disease, pulmonary tuberculosis, asthma, and plasma metabolites: A bidirectional Mendelian randomization study.

Unmasking FCGR2B as a high-grade serous ovarian cancer specific marker of immune suppression and tumor progression through multi-omics mining.

Shared genetic structure between COVID-19 and migraine: insights from large-scale genome-wide cross-trait analysis.

Polygenic risk score for lower limb skeletal muscle mass and its interaction with protein and vitamin D intake in older adults.

Host-gut microbial metabolic crosstalk in postpartum depression: A multiomics insight linking blood metabolites to epigenetic modulation.

Prominent sex differences exist in severe mental illness (SMI), with increasing evidence pointing towards a pivotal role for sex hormones. Elucidation of these hormonal influences is crucial to tailor sex-specific prevention and treatment. To investigate potential shared genetics and bi-directional causal effects between sex hormone traits and SMI (depressive disorder, bipolar disorder and schizophrenia-spectrum disorder), we computed genetic correlations using linkage disequilibrium score regression and bi-directional summary-level Mendelian Randomization (MR). A range of sensitivity methods was applied and potential mediators were investigated using multivariable MR. Sex-stratified data from genome-wide association studies were used, if available further stratified on menopausal status. We also incorporated other sex hormone traits (progesterone, sex hormone-binding globulin, prolactin, age of menarche, age of menopause) in exploratory analyses. We found a widespread pattern of statistically significant, modest genetic correlations between oestrogen/testosterone levels and depressive disorder/schizophrenia-spectrum disorder, in both positive and negative directions and in both sexes (ranging between -0.22 and 0.13). With MR, evidence for causal effects was largely lacking; apart from weak evidence for a causal, increasing effect of testosterone levels on schizophrenia-spectrum disorder risk in males, which was mediated by CRP. Conversely, there was very weak evidence for a causal, increasing effect of liability to schizophrenia-spectrum disorder on testosterone levels in both sexes. This study offers new insights into the complex aetiology of SMI by comprehensively mapping genetic associations with sex hormone traits, emphasizing the need to further investigate sex hormones' impact on SMI using larger and more precisely phenotyped samples to identify individuals particularly vulnerable to hormonal disturbances.

Rice stem performs assimilate transport and promises sturdiness due to cell wall structure and composition. However, less is known about the genetic basis of its structural characteristics. In this study, for the first time, the scanning electron microscope (SEM) imaging technique was developed to capture digital phenotypes to assess 18 straw traits collected from the cross-sections of 147 rice accessions. Genome-wide association studies (GWAS) identified 54 significant single-nucleotide polymorphisms (SNPs; integrated into 28 quantitative trait loci) residing in the genic sequences of rice (promoter and coding DNA sequence), and classified into three groups: 1) cell wall-defining genes, 2) cell size-defining genes, and 3) transcription factors. DUF246 and DUF1218, galactose oxidase, mitochondrial Rho GTPase, WUSCHEL-related homeobox 5 and scarecrow-like 9 are the novel genes identified among the 21 candidate genes. These genes may play roles in stem development traits, specifically the distance from the vascular bundle to the end of the parenchymal cells (DVBEPC) and the thickness of the straw cell wall in the protruding part (TSCWP). Post-GWAS analyses showed one significant haplotype on chromosome 4 and 25 significant epistatic interactions. Most notably, nine TF families were repeatedly detected among the significant QTL. Os07g0644300 (XPA-binding protein 2), located in the q7-1 genomic segment and associated with DVBEPC, was found to have a missense mutation. Phenotyping via SEM imaging provides precise genome-phenome association in understanding rice stem cell size and cell wall architecture, which ultimately can define biomass and lodging resistance.

Elevated branched-chain amino acids (BCAAs; leucine, valine, isoleucine) are linked to type 2 diabetes (T2D) risk, characterised by defective insulin secretion in pancreatic β-cell and peripheral insulin resistance. Causative interaction between BCAA metabolism and these two diabetic pathogenesis remains unclear. Using publicly available datasets from the European population, we conducted a meta-analysis of genome-wide association studies (GWAS), followed by multi-trait analysis of GWAS (MTAG), to identify genetic loci associated with BCAAs and their catabolites. Two-sample bidirectional Mendelian Randomisation (MR) examined putative causal associations of genetically determined BCAAs and their catabolites with 10 traits related to insulin and glucose metabolism. Sensitivity analyses evaluated robustness and specificity of observed associations. MTAG identified 57.14%, 59.09%, and 63.41% novel genetic loci for circulating leucine, valine and isoleucine, respectively. Genetically elevated valine had a significant association with increased insulin fold change during oral glucose challenge test (OGTT) (β [95% CI] = 0.135 [0.045, 0.225]), False discovery rate adjusted p-value (p FDR = 0.022), and suggestive association with fasting glucose level (β [95% CI] = 0.031 [0.004, 0.058], inverse-variance weighted p-value [p IVW] = 0.025). In the reverse direction, genetically determined homeostasis model assessment of β-cell (HOMA-B) exhibited significant inverse associations with BCAAs (Leucine: β [95% CI] = -0.140 [-0.244, -0.036], p FDR = 0.034; Valine: β [95% CI] = -0.147 [-0.255, -0.040], p FDR = 0.030; Isoleucine: β [95% CI] = -0.149 [-0.248, -0.049], p FDR = 0.020). Moreover, β-hydroxyisovalerate, a leucine-derived catabolite, was inversely related to 2-h glucose level after OGTT (β [95% CI] = -0.149 [-0.227, -0.071], p FDR = 0.045). In the reverse direction, genetically predicted peak insulin response was suggestively associated with elevated isoleucine catabolite, 2-hydroxy-3-methylvalerate (β [95% CI] = 0.074 [0.018, 0.130], p IVW = 9.20 × 10-3). Our genetic analysis indicates BCAA catabolism and insulin secretion/action interact with each other; their aberrance might form a vicious cycle promoting T2D progression.

Immune dysfunction contributes to comorbid depression in patients with multiple sclerosis.

Impact of gut microbiome, plasma metabolites, peripheral immune cells, and circulating inflammatory protein on chronic spontaneous urticaria: Bidirectional 2-sample Mendelian randomization study and mediation analysis.

The AGPS regulatory variant rs113671272 confers esophageal squamous cell carcinoma susceptibility through allele-specific MEIS3 binding and NF-κB activation in Chinese populations.

Genomic Insights Into Inflammatory Bowel Disease in United States Hispanic Participants: An Ancestry-Focused Study.

Emerging biobank resources allow large-scale integration of eye-specific phenotypes with clinical, genomic, and multiomic data. This convergence enables unprecedented opportunities to systematically dissect the genetic architecture, epidemiology, and mechanistic pathways of both rare monogenic and common polygenic diseases. The review aims to critically examine how contemporary data extraction, multiomics, and analytic methodologies are reshaping disease classification, genetic discovery, and translational research in ophthalmology, while highlighting the associated challenges in leveraging these advanced tools. Recent literature demonstrates the utility of genome-wide and phenome-wide association studies, transcriptomic analyses, and artificial intelligence in uncovering novel risk loci, endophenotypes, and biomarkers relevant to eye diseases. Furthermore, advances in multiancestry sampling show substantial population-specific genetic variation, enriching disease models for conditions such as glaucoma and age-related macular degeneration. Finally. integrative approaches, including Mendelian randomization and enrichment analyses, are helping elucidate shared genetic architecture between ocular and systemic diseases, informing therapeutic target identification, and refining risk prediction models. The convergence of biobank-derived multimodal data and sophisticated analytic techniques is catalyzing a path to personalized medicine in ophthalmology. For these approaches to fully translate into clinical practice ensuring scientifically robust and equitable outcomes, future research must address cohort diversity, mechanistic validation, and practical cost-effectiveness.