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1.
Clin Genet ; 105(6): 639-654, 2024 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-38374498

RESUMO

The application of genomic technologies has led to unraveling of the complex genetic landscape of disorders of epilepsy, gaining insights into their underlying disease mechanisms, aiding precision medicine, and providing informed genetic counseling. We herein present the phenotypic and genotypic insights from 142 Indian families with epilepsy with or without comorbidities. Based on the electroclinical findings, epilepsy syndrome diagnosis could be made in 44% (63/142) of the families adopting the latest proposal for the classification by the ILAE task force (2022). Of these, 95% (60/63) of the families exhibited syndromes with developmental epileptic encephalopathy or progressive neurological deterioration. A definitive molecular diagnosis was achieved in 74 of 142 (52%) families. Infantile-onset epilepsy was noted in 81% of these families (61/74). Fifty-five monogenic, four chromosomal, and one imprinting disorder were identified in 74 families. The genetic variants included 65 (96%) single-nucleotide variants/small insertion-deletions, 1 (2%) copy-number variant, and 1 (2%) triplet-repeat expansion in 53 epilepsy-associated genes causing monogenic disorders. Of these, 35 (52%) variants were novel. Therapeutic implications were noted in 51% of families (38/74) with definitive diagnosis. Forty-one out of 66 families with monogenic disorders exhibited autosomal recessive and inherited autosomal dominant disorders with high risk of recurrence.


Assuntos
Epilepsia , Aconselhamento Genético , Fenótipo , Humanos , Epilepsia/genética , Epilepsia/epidemiologia , Epilepsia/diagnóstico , Índia/epidemiologia , Masculino , Feminino , Criança , Pré-Escolar , Lactente , Predisposição Genética para Doença , Linhagem , Idade de Início , Estudos de Associação Genética , Adolescente , Genótipo , Variações do Número de Cópias de DNA/genética
2.
Recent Adv Food Nutr Agric ; 13(1): 27-50, 2022 Nov 14.
Artigo em Inglês | MEDLINE | ID: mdl-36173075

RESUMO

The drug-food interaction brings forth changes in the clinical effects of drugs. While favourable interactions bring positive clinical outcomes, unfavourable interactions may lead to toxicity. This article reviews the impact of food intake on drug-food interactions, the clinical effects of drugs, and the effect of drug-food in correlation with diet and precision medicine. Emerging areas in drug-food interactions are the food-genome interface (nutrigenomics) and nutrigenetics. Understanding the molecular basis of food ingredients, including genomic sequencing and pharmacological implications of food molecules, helps to reduce the impact of drug-food interactions. Various strategies are being leveraged to alleviate drug-food interactions; measures including patient engagement, digital health, approaches involving machine intelligence, and big data are a few of them. Furthermore, delineating the molecular communications across dietmicrobiome- drug-food-drug interactions in a pharmacomicrobiome framework may also play a vital role in personalized nutrition. Determining nutrient-gene interactions aids in making nutrition deeply personalized and helps mitigate unwanted drug-food interactions, chronic diseases, and adverse events from their onset. Translational bioinformatics approaches could play an essential role in the next generation of drug-food interaction research. In this landscape review, we discuss important tools, databases, and approaches along with key challenges and opportunities in drug-food interaction and its immediate impact on precision medicine.


Assuntos
Big Data , Interações Alimento-Droga , Humanos , Nutrigenômica , Dieta , Inteligência Artificial
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