Landscape of pharmacogenetic variants associated with non-insulin antidiabetic drugs in the Indian population
© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ..
INTRODUCTION: Genetic variants contribute to differential responses to non-insulin antidiabetic drugs (NIADs), and consequently to variable plasma glucose control. Optimal control of plasma glucose is paramount to minimizing type 2 diabetes-related long-term complications. India's distinct genetic architecture and its exploding burden of type 2 diabetes warrants a population-specific survey of NIAD-associated pharmacogenetic (PGx) variants. The recent availability of large-scale whole genomes from the Indian population provides a unique opportunity to generate a population-specific map of NIAD-associated PGx variants.
RESEARCH DESIGN AND METHODS: We mined 1029 Indian whole genomes for PGx variants, drug-drug interaction (DDI) and drug-drug-gene interactions (DDGI) associated with 44 NIADs. Population-wise allele frequencies were estimated and compared using Fisher's exact test.
RESULTS: Overall, we found 76 known and 52 predicted deleterious common PGx variants associated with response to type 2 diabetes therapy among Indians. We report remarkable interethnic differences in the relative cumulative counts of decreased and increased response-associated alleles across NIAD classes. Indians and South Asians showed a significant excess of decreased metformin response-associated alleles compared with other global populations. Network analysis of shared PGx genes predicts high DDI risk during coadministration of NIADs with other metabolic disease drugs. We also predict an increased CYP2C19-mediated DDGI risk for CYP3A4/3A5-metabolized NIADs, saxagliptin, linagliptin and glyburide when coadministered with proton-pump inhibitors (PPIs).
CONCLUSIONS: Indians and South Asians have a distinct PGx profile for antidiabetes drugs, marked by an excess of poor treatment response-associated alleles for various NIAD classes. This suggests the possibility of a population-specific reduced drug response in atleast some NIADs. In addition, our findings provide an actionable resource for accelerating future diabetes PGx studies in Indians and South Asians and reconsidering NIAD dosing guidelines to ensure maximum efficacy and safety in the population.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:12 |
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| Enthalten in: |
BMJ open diabetes research & care - 12(2024), 2 vom: 12. März |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Sivadas, Ambily [VerfasserIn] |
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| Links: |
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| Themen: |
Diabetes Mellitus, Type 2 |
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| Anmerkungen: |
Date Completed 14.03.2024 Date Revised 15.04.2024 published: Electronic Citation Status MEDLINE |
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| doi: |
10.1136/bmjdrc-2023-003769 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM369613864 |
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| 245 | 1 | 0 | |a Landscape of pharmacogenetic variants associated with non-insulin antidiabetic drugs in the Indian population |
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| 500 | |a Date Completed 14.03.2024 | ||
| 500 | |a Date Revised 15.04.2024 | ||
| 500 | |a published: Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a © Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ. | ||
| 520 | |a INTRODUCTION: Genetic variants contribute to differential responses to non-insulin antidiabetic drugs (NIADs), and consequently to variable plasma glucose control. Optimal control of plasma glucose is paramount to minimizing type 2 diabetes-related long-term complications. India's distinct genetic architecture and its exploding burden of type 2 diabetes warrants a population-specific survey of NIAD-associated pharmacogenetic (PGx) variants. The recent availability of large-scale whole genomes from the Indian population provides a unique opportunity to generate a population-specific map of NIAD-associated PGx variants | ||
| 520 | |a RESEARCH DESIGN AND METHODS: We mined 1029 Indian whole genomes for PGx variants, drug-drug interaction (DDI) and drug-drug-gene interactions (DDGI) associated with 44 NIADs. Population-wise allele frequencies were estimated and compared using Fisher's exact test | ||
| 520 | |a RESULTS: Overall, we found 76 known and 52 predicted deleterious common PGx variants associated with response to type 2 diabetes therapy among Indians. We report remarkable interethnic differences in the relative cumulative counts of decreased and increased response-associated alleles across NIAD classes. Indians and South Asians showed a significant excess of decreased metformin response-associated alleles compared with other global populations. Network analysis of shared PGx genes predicts high DDI risk during coadministration of NIADs with other metabolic disease drugs. We also predict an increased CYP2C19-mediated DDGI risk for CYP3A4/3A5-metabolized NIADs, saxagliptin, linagliptin and glyburide when coadministered with proton-pump inhibitors (PPIs) | ||
| 520 | |a CONCLUSIONS: Indians and South Asians have a distinct PGx profile for antidiabetes drugs, marked by an excess of poor treatment response-associated alleles for various NIAD classes. This suggests the possibility of a population-specific reduced drug response in atleast some NIADs. In addition, our findings provide an actionable resource for accelerating future diabetes PGx studies in Indians and South Asians and reconsidering NIAD dosing guidelines to ensure maximum efficacy and safety in the population | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Diabetes Mellitus, Type 2 | |
| 650 | 4 | |a Genomics | |
| 650 | 4 | |a Indians | |
| 650 | 7 | |a Hypoglycemic Agents |2 NLM | |
| 650 | 7 | |a Insulin |2 NLM | |
| 650 | 7 | |a Insulin, Regular, Human |2 NLM | |
| 700 | 1 | |a Sahana, S |e verfasserin |4 aut | |
| 700 | 1 | |a Jolly, Bani |e verfasserin |4 aut | |
| 700 | 1 | |a Bhoyar, Rahul C |e verfasserin |4 aut | |
| 700 | 1 | |a Jain, Abhinav |e verfasserin |4 aut | |
| 700 | 1 | |a Sharma, Disha |e verfasserin |4 aut | |
| 700 | 1 | |a Imran, Mohamed |e verfasserin |4 aut | |
| 700 | 1 | |a Senthivel, Vigneshwar |e verfasserin |4 aut | |
| 700 | 1 | |a Divakar, Mohit Kumar |e verfasserin |4 aut | |
| 700 | 1 | |a Mishra, Anushree |e verfasserin |4 aut | |
| 700 | 1 | |a Mukhopadhyay, Arpita |e verfasserin |4 aut | |
| 700 | 1 | |a Gibson, Greg |e verfasserin |4 aut | |
| 700 | 1 | |a Narayan, Km Venkat |e verfasserin |4 aut | |
| 700 | 1 | |a Sivasubbu, Sridhar |e verfasserin |4 aut | |
| 700 | 1 | |a Scaria, Vinod |e verfasserin |4 aut | |
| 700 | 1 | |a Kurpad, Anura V |e verfasserin |4 aut | |
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