Literature DB >> 35962253

Pharmacogenetic profiling and individualised therapy in the treatment of degenerative spinal conditions.

Jake M McDonnell1, Brian Rigney2, James Storme2, Daniel P Ahern2,3, Gráinne Cunniffe2, Joseph S Butler2,4.   

Abstract

Patients presenting with degenerative spinal changes are often poor surgical candidates due to associated co-morbidities, frailty, or sarcopenia. Additionally, surgeries of a degenerative spine can prove difficult due to the distortion of normal surgical anatomy. Therefore, many patients are managed conservatively with a variety of modalities, including over-the-counter and prescription medications. Nevertheless, several patients do not experience adequate relief from pain with analgesic medications, precipitating multiple hospital visits, and usage of resources. As a result, back pain is regarded as a major economic burden, with total costs of associated treatment exceeding $100 billion annually. Pharmacogenetics is a relatively novel method of evaluating an individual's response to analgesic medications, through analysis of germline polymorphisms. It entails obtaining a genetic sample, often via buccal swab or peripheral blood sample, and genetic analysis achieved through either polymerase chain reaction +/- Sanger sequencing, microassays, restriction length fragment polymorphism analysis, or genetic library preparation and next generation sequencing. The potential efficacy of pharmacogenetic analysis has been highlighted across several specialities to date. However, a paucity of evidence exists regarding spine surgery populations. Nevertheless, regular prospective pharmacogenetic analysis may ultimately prove beneficial when concerning degenerative spinal cohorts due to aforementioned surgical and economic considerations. The purpose of this narrative review is to outline how metaboliser profile variants affect the pharmacokinetics of specific analgesia used to treat back pain, and to discuss the current potential and limitations of employing regular pharmacogenetic analysis for spine surgery populations with degenerative conditions.
© 2022. The Author(s), under exclusive licence to Royal Academy of Medicine in Ireland.

Entities:  

Keywords:  Degenerative disease; Genetic profiling; Pain; Pharmacogenetics; Spine

Year:  2022        PMID: 35962253     DOI: 10.1007/s11845-022-03112-9

Source DB:  PubMed          Journal:  Ir J Med Sci        ISSN: 0021-1265            Impact factor:   2.089


  68 in total

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Journal:  Trends Mol Med       Date:  2001-05       Impact factor: 11.951

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Review 3.  Real-time PCR in virology.

Authors:  Ian M Mackay; Katherine E Arden; Andreas Nitsche
Journal:  Nucleic Acids Res       Date:  2002-03-15       Impact factor: 16.971

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Authors:  D A EVANS; K A MANLEY; V A McKUSICK
Journal:  Br Med J       Date:  1960-08-13

5.  Practical innovations for high-throughput amplicon sequencing.

Authors:  Derek S Lundberg; Scott Yourstone; Piotr Mieczkowski; Corbin D Jones; Jeffery L Dangl
Journal:  Nat Methods       Date:  2013-09-01       Impact factor: 28.547

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Authors:  A D Roses
Journal:  Nature       Date:  2000-06-15       Impact factor: 49.962

7.  Direct detection of DNA methylation during single-molecule, real-time sequencing.

Authors:  Benjamin A Flusberg; Dale R Webster; Jessica H Lee; Kevin J Travers; Eric C Olivares; Tyson A Clark; Jonas Korlach; Stephen W Turner
Journal:  Nat Methods       Date:  2010-05-09       Impact factor: 28.547

Review 8.  Comparison of the Guidelines of the Clinical Pharmacogenetics Implementation Consortium and the Dutch Pharmacogenetics Working Group.

Authors:  P C D Bank; K E Caudle; J J Swen; R S Gammal; M Whirl-Carrillo; T E Klein; M V Relling; H-J Guchelaar
Journal:  Clin Pharmacol Ther       Date:  2017-10-10       Impact factor: 6.875

9.  Diagnostic gene sequencing panels: from design to report-a technical standard of the American College of Medical Genetics and Genomics (ACMG).

Authors:  Lora J H Bean; Birgit Funke; Colleen M Carlston; Jennifer L Gannon; Sibel Kantarci; Bryan L Krock; Shulin Zhang; Pinar Bayrak-Toydemir
Journal:  Genet Med       Date:  2019-11-16       Impact factor: 8.822

10.  Comparison of Exome and Genome Sequencing Technologies for the Complete Capture of Protein-Coding Regions.

Authors:  Stefan H Lelieveld; Malte Spielmann; Stefan Mundlos; Joris A Veltman; Christian Gilissen
Journal:  Hum Mutat       Date:  2015-06-11       Impact factor: 4.878

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