Author(s): Ramaimon Tunthong, Chonlaphat Sukasem, Apichaya Puangpetch, Pantep Angchaisuksiri, Thanyachai Sura, Adisorn Pathumarak, Sukit Yamwong, Sarana Boonbaichaiyapruck, Wasun Chantratita, Piyamitr Sritara and Prin Vathesatogkit
Page: [154 - 161] Pages: 8
* (Excluding Mailing and Handling)
This study was designed to determine the effect of CYP2C19 polymorphisms on platelet response in patients with atherothrombotic-risks receiving clopidogrel treatment. Ninety-five antiplatelet naive atherothrombotic-risk patients were enrolled consecutively. Clopidogrel at 75 mg/day was administered for 2 weeks, followed by a platelet function test (PFT). Non-responders were identified and randomized for receiving either 75 mg or 150 mg of clopidogrel for a further 2 weeks. Twenty-four subjects were non-responders with 75 mg/day, which correlated with poor metabolizer (PM) status (OR 5.69; 1.41-23.03, p = 0.015). However, the mean maximal platelet aggregation (MPA) in the 2nd test was significantly lower in the extensive metabolizers (EM) when compared to the intermediate metabolizers (IM) and PM (23.6 vs 28.1 vs 39.7; p = 0.0001). After randomizing to either 75mg or 150 mg of clopidogrel, no patient had an improved platelet response of more than 30%. However, after administering 150 mg of clopidogrel, MPA reduction (ΔMPA) was significantly greater in IM and PM when compared to that in EM (absolute ΔMPA 20.22% vs 2.6%, p 0.014; relative ΔMPA 45.07% vs 5.27%, p = 0.037). We report here the first pharmacogenetics study of clopidogrel response and show that the common CYP2C19 variants are an important determinant of ADP-stimulated platelet aggregation in Thailand. CYP2C19 genotype may be beneficial in assisting clinicians select the appropriate effective antiplatelet therapy and optimal dose for a given individual. These results collectively inform the emerging field of public health pharmacogenomics with attention to progress in the Asia-Pacific.
Keywords: Atherothrombotic-risks, CYP2C19, clopidogrel, non-responder, microarray, platelet aggregation, public health pharmacogenomics.
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CASE j.track WHEN 0 THEN false ELSE true END as tracksAccessByVolume,"article" as access_level, j.issue_id, j.article_id from `user_access_article_corporate` as `j` inner join `user_access_info` as `info` on `j`.`user_access_id` = `info`.`user_access_id` where ((j.from_ip <= 309614726 and j.to_ip >=309614726 )) and ((j.from_date <= 1736967877 and j.to_date >= 1736967877 and j.perpetual= 0) or (j.from_date is null and j.to_date is null and j.perpetual= 1)) and j.article_id = 52337) union (select j.user_access_id,j.volume_id,j.user_id,j.from_ip,j.to_ip,j.type,j.track,"Token Based Access" as access_base_text,
false as terms_popup,
"R" as content_download_type,
j.uc_id as restricted_user_access_key,
"v" as restricted_user_access_type,
CASE j.track WHEN 0 THEN false ELSE true END as tracksAccessByVolume,"article" as access_level, j.issue_id, j.article_id from `user_access_article_token` as `j` inner join `user_access_info` as `info` on `j`.`user_access_id` = `info`.`user_access_id` where ((j.from_ip <= 309614726 and j.to_ip >=309614726 )) and ((j.from_date <= 1736967877 and j.to_date >= 1736967877 and j.perpetual= 0) or (j.from_date is null and j.to_date is null and j.perpetual= 1)) and j.article_id = 52337)
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select * from `article` where `first_page` < '154' and is_uploaded = 1 and issue_id = 5154 order by cast(first_page as SIGNED) desc limit 1
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select * from `article` where `last_page` > '161' and is_uploaded = 1 and issue_id = 5154 order by cast(first_page as SIGNED) asc limit 1
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select `language_id` from `multilanguage` where `short_code` = 'en'
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select `source_lang_label`, `target_lang_label` from `multilanguage_labels` where `target_lang_id` = 1
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select `id` from `multilanguage_article` where `article_id` = 52337 limit 1
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select b.banner_link, b.banner_name, b.banner_script, b.banner_remarks, b.banner_file_name, b.banner_placement, bd.content_type, bd.content_id from `tbl_banner` as `b` inner join `tbl_banner_detail` as `bd` on `bd`.`banner_id` = `b`.`banner_id` inner join `users` as `u` on `u`.`id` = `b`.`updated_by` inner join `journal` as `j` on `j`.`journal_id` = `bd`.`content_id` where `b`.`banner_journal` = 1 and `bd`.`content_type` = 'J' and `bd`.`content_id` = 104 and `b`.`banner_from_date` <= 1736967877 and `b`.`banner_to_date` >= 1736967877 and `b`.`banner_status` = 'A' order by `b`.`banner_id` desc
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select count(*) as aggregate from `uc_cart_products` where cart_id='c737b3d7f1e0da6c49bfd0a39f9cd732'
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200
[]
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