👤 Sana Javaid Awan

Obesity is a highly complex, multifactorial disease influenced by dynamic interactions among genetic, epigenetic, environmental, and behavioral determinants that explicitly position genetics as the core. While advances in multi-omic integration have revolutionized our understanding of adiposity pathways, translation into personalized clinical nutrition remains a critical challenge. This review systematically consolidates emerging insights into the molecular and nutrigenomic architecture of obesity by integrating data from large-scale GWAS, functional epigenomics, nutrigenetic interactions, and microbiome-mediated metabolic programming. The primary aim is to systematically organize and synthesize recent genetic and genomic findings in obesity, while also highlighting how these discoveries can be contextualized within precision nutrition frameworks. A comprehensive literature search was conducted across PubMed, Scopus, and Web of Science up to July 2024 using MeSH terms, nutrigenomic-specific queries, and multi-omics filters. Eligible studies were classified into five domains: monogenic obesity, polygenic GWAS findings, epigenomic regulation, nutrigenomic signatures, and gut microbiome contributions. Over 127 candidate genes and 253 QTLs have been implicated in obesity susceptibility. Monogenic variants (e.g., Show less

Intellectual disability is a heterogeneous disorder, diagnosed using intelligence quotient (IQ) score criteria. Currently, no specific clinical test is available to diagnose the disease and its subgroups due to inadequate understanding of the pathophysiology. Therefore, current study was designed to explore the molecular mechanisms involved in disease perturbation, and to identify potential biomarkers for disease diagnosis and prognosis. A total of 250 participants were enrolled in this study, including 200 intellectually disabled (ID) subjects from the subgroups (mild, moderate, and severe) with age and gender matched healthy controls (n = 50). Initially, IQ testing score and biochemical profile of each subject was generated, followed by label-free quantitative proteomics of subgroups of IQ and healthy control group through nano-LC/MS- mass spectrometry. A total of 310 proteins were identified, among them198 proteins were common among all groups. Statistical analysis (ANOVA) of the subgroups of ID showed 142 differentially expressed proteins, in comparison to healthy control group. From these, 120 proteins were found to be common among all subgroups. The remaining 22 proteins were categorized as exclusive proteins found only in disease subgroups. Furthermore, the hierarchical cluster analysis (HCL) of common significant proteins was also performed, followed by PANTHER protein classification and GO functional enrichment analysis. Results provides that the datasets of differentially expressed proteins, belong to the categories of immune / defense proteins, transfer carrier proteins, apolipoproteins, complement proteins, protease inhibitors, hemoglobin proteins etc., they are known to involvein immune system, and complement and coagulation pathway cascade and cholesterol metabolism pathway. Exclusively expressed 22 proteins were found to be disease stage specific and strong PPI network specifically those that have significant role in platelets activation and degranulation, such as Filamin A (FLNA). Furthermore, to validate the mass spectrometric findings, four highly significant proteins (APOA4, SAP, FLNA, and SERPING) were quantified by ELISA in all the study subjects. AUROC analysis showed a significant association of APOA4 (0.830), FLNA (0.958), SAP (0.754) and SERPING (0.600) with the disease. Apolipoprotein A4 (APOA4) has a significant role in cholesterol transport, and in modulation of glucose and lipid metabolism in the CNS. Similarly, FLNA has a crucial role in the nervous system, especially in the functioning of synaptic network. Therefore, both APOA4, and FLNA proteins represent good potential for candidate biomarkers for the diagnosis and prognosis of the intellectual disability. Overall, serum proteome of ID patients provides valuable information of proteins/pathways that are altered during ID progression. Show less