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10.2217/pgs-2021-0028 http://scihub22266oqcxt.onion/10.2217/pgs-2021-0028 34142560!8216321!34142560     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=34142560&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215       Pharmacogenomics 2021 ; 22 (10): 603-618 Nephropedia Template TP {{tp|p=34142560|t=2021. Pharmacogenomic landscape of COVID-19 therapies from Indian population genomes |pdf=|usr=}}{{34142560}} gab.com Text Pharmacogenomic landscape of COVID-19 therapies from Indian population genomes JO: Pharmacogenomics http://www.kidney.de/pget.php?&tw=1&pmid=34142560 #FOAvip Aim: Numerous drugs are being widely prescribed for COVID-19 treatment without any direct evidence for the drug safety/efficacy in patients across diverse ethnic populations. Materials & methods: We analyzed whole genomes of 1029 Indian individuals (IndiGen) to understand the extent of drug-gene (pharmacogenetic), drug-drug and drug-drug-gene interactions associated with COVID-19 therapy in the Indian population. Results: We identified 30 clinically significant pharmacogenetic variants and 73 predicted deleterious pharmacogenetic variants. COVID-19-associated pharmacogenes were substantially overlapped with those of metabolic disorder therapeutics. CYP3A4, ABCB1 and ALB are the most shared pharmacogenes. Fifteen COVID-19 therapeutics were predicted as likely drug-drug interaction candidates when used with four CYP inhibitor drugs. Conclusion: Our findings provide actionable insights for future validation studies and improved clinical decisions for COVID-19 therapy in Indians. Twit Text FOAVip Pharmacogenomic landscape of COVID-19 therapies from Indian population genomes ????Pharmacogenomics http://www.kidney.de/pget.php?&tw=1&pmid=34142560 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34142560 #FOAvip English Wikipedia <ref>{{Cite pmid|34142560}}</ref> Pharmacogenomic landscape of COVID-19 therapies from Indian population genomes #MMPMID34142560 Sahana S; Sivadas A; Mangla M; Jain A; Bhoyar RC; Pandhare K; Mishra A; Sharma D; Imran M; Senthivel V; Divakar MK; Rophina M; Jolly B; Batra A; Sharma S; Siwach S; Jadhao AG; Palande NV; Jha GN; Ashrafi N; Mishra PK; Vidhya AK; Jain S; Dash D; Kumar NS; Vanlallawma A; Sarma RJ; Chhakchhuak L; Kalyanaraman S; Mahadevan R; Kandasamy S; Devi P; Rajagopal RE; Ramya JE; Devi PN; Bajaj A; Gupta V; Mathew S; Goswami S; Prakash S; Joshi K; Kumla M; Sreedevi S; Gajjar D; Soraisham R; Yadav R; Devi YS; Gupta A; Mukerji M; Ramalingam S; Binukumar BK; Sivasubbu S; Scaria V Pharmacogenomics 2021[Jul]; 22 (10): 603-618 PMID34142560show ga Aim: Numerous drugs are being widely prescribed for COVID-19 treatment without any direct evidence for the drug safety/efficacy in patients across diverse ethnic populations. Materials & methods: We analyzed whole genomes of 1029 Indian individuals (IndiGen) to understand the extent of drug-gene (pharmacogenetic), drug-drug and drug-drug-gene interactions associated with COVID-19 therapy in the Indian population. Results: We identified 30 clinically significant pharmacogenetic variants and 73 predicted deleterious pharmacogenetic variants. COVID-19-associated pharmacogenes were substantially overlapped with those of metabolic disorder therapeutics. CYP3A4, ABCB1 and ALB are the most shared pharmacogenes. Fifteen COVID-19 therapeutics were predicted as likely drug-drug interaction candidates when used with four CYP inhibitor drugs. Conclusion: Our findings provide actionable insights for future validation studies and improved clinical decisions for COVID-19 therapy in Indians. |*COVID-19 Drug Treatment[MESH] |Antiviral Agents/therapeutic use[MESH] |Asian People[MESH] |COVID-19/*genetics[MESH] |Drug Interactions/genetics[MESH] |Genome/genetics[MESH] |Genotype[MESH] |Humans[MESH] |India[MESH] |Pharmacogenetics/methods[MESH] |Pharmacogenomic Testing/methods[MESH] |Pharmacogenomic Variants/genetics[MESH]Pharmacogenomic landscape of COVID-19 therapies from Indian population(epmc).pdf DeepDyve Pubget Overpricing