Investigating Real-World Clopidogrel Pharmacogenetics in Stroke Using a Bioresource Linked to Electronic Medical Records

Clopidogrel efficacy is influenced by genetic variation of CYP2C19, however few studies have considered stroke patients. We used electronic medical records (EMR) linked to a bioresource to examine real-world implications of clopidogrel pharmacogenetics in stroke. Patients hospitalized for any arterial thrombo-occlusive event (ATO) who subsequently redeemed clopidogrel prescriptions in the community were entered into the study (n=651). During 24 months follow-up the primary endpoint of recurrent ATO or death occurred in 299 (46%) patients. CYP2C19*2 loss-of-function allele carriers had an increased risk, hazard ratio (HR) 1.29 (95% confidence interval 1.04-1.59, P=0.019). In the ischemic stroke subgroup (n=94) the estimate of risk was greater (HR 2.23, 95% confidence interval 1.17-4.24, P=0.015) further supported by a meta-analysis of available studies. In conclusion, we have demonstrated the clinical impact of CYP2C19*2 on clopidogrel efficacy using a purely EMR approach. This suggests that the risk in the ischemic stroke population may be particularly high.</p

BIOMECHANICAL STUDY OF JUMPING & LANDING TECHNIQUES: BALLET VS NON-BALLET ATHLETES

INTRODUCTION: The prevalence of ACL injuries is increasing in previous years. One of the most common studied kinematic risk factors related to ACL injuries is a resultant weak, leg axis alignment known as the dynamic knee valgus angle presented during a vertical drop jump [8, 14, 15]. Hewett et. al. concluded that a knee valgus angle was a primary predictor of the mechanism that leads to an ACL rupture [8]. By increasing the excessive knee valgus angle during a two-legged DVJ, an athlete is in turn increasing the possibility of a high knee valgus moment, which can increase the anterior tibial translation as well as the load on the ACL several-fold and the chances for an ACL tear [4]. METHODS: In our study, ten collegiate female participants, including ballet and non-ballet athletes performed two-legged DVJs for 6 different flexor and extensor muscles while digital recordings of knee valgus angle were captured at initial contact and push off with simultaneous collection of EMG data. RESULTS: Results displayed statistical significance for the average valgus angle to estimated GRF ratio for the non-dominant leg at push-off between the ballet and non-ballet athletes (0.8 ± 0.43 vs. 1.8 ± 0.33 degrees/N, p \u3c 0.05). In addition, we also found that the hip extensor activity significantly increased for the non-ballet group and that the lateral thigh CCI noticeably increased for the non-dominant leg for the non-ballet group, which could be indicative of the noticeable difference in the biceps femoris muscle activation for the non-ballet group when comparing sports type. In addition, statistically significant interactions between sports type and leg type for vastus medialis and gluteus maximus were produced. Observed results also indicated that there was an increase in overall variability for the dominant leg of the non-ballet athletes amongst all studied muscles and for the non-dominant leg for the ballet group specifically studying the gluteus maximus muscle activity. DISCUSSION: Relatively, the non-ballet group could be at a higher risk for increase in femoral adduction, hip adduction, and tibial external rotation, and overall predict a larger knee valgus moment; therefore, the non-ballet group could potentially be at a higher risk for an ACL injury than the ballet group. In addition, there is potential in continued research of neuromuscular differences between ballet and non-ballet athletes to further investigate the vastus medialis and the gluteus maximus muscle activations as well as to investigate the knee valgus moment values

Farmakogenetiikasta apua käytännön lääkärille

Farmakogenetiikka tutkii perinnöllisten erojen vaikutusta lääkehoitojen tehoon ja turvallisuuteen. Farmakogeneettisen testauksen tavoitteena on löytää yksittäiselle potilaalle suurimmalla todennäköisyydellä sopivin lääke tai annos. Käytännössä kliinisessä työssä on siirrytty yksittäisten geenien tutkimisesta farmakogeneettisiin paneelitutkimuksiin, joista saatava tieto on hyödynnettävissä myöhemminkin potilaan hoidossa. Farmakogenetiikalla on merkitystä useille laajasti käytetyille lääkkeille, kuten antitromboottisille lääkkeille, kipulääkkeille, masennuslääkkeille ja lipidilääkkeille. Paras hyöty farmakogenetiikasta saadaan, kun tieto voidaan hyödyntää silloin kun lääkehoitoa ollaan aloittamassa. Farmakogenetiikan käyttö tullee tulevaisuudessa lisääntymään merkittävästi, joten lääkkeen määrääjän on hyödyllistä tutustua farmakogeneettisiin suosituksiin erityisesti niiden lääkkeiden osalta, joita työssään käyttää

Asiakaspalveluprosessien automatisointi ChatGPT- ja RPA-ohjelmistoilla

Tässä opinnäytetyössä luotiin RPA-robotti UiPath-alustalla, joka mahdollisti asia kaspalveluvastausten automatisoinnin. Opinnäytetyön tavoitteena oli toteuttaa ja tutustua automatisoinnin mahdollisuuk siin asiakaspalvelun näkökulmasta. Vastaavia valmiita ratkaisuja kuten chat-bot teja markkinoilla onkin jo käytössä, mutta työn tuloksena haettiin lähinnä komp leksisiin vastauksiin ja mahdollisuuksiin perustuvaa toteutusta. Alustaksi valittiin ChatGPT-tekoäly ja UiPath RPA-alusta. Näiden valintaan vai kutti myös vahvasti työelämästä kertynyt kokemus molempien käytöstä. Kuiten kaan molempia ei ollut aiemmissa alan tehtävissä käytetty toisiinsa integroituna

Studies on CYP2C8-mediated drug interactions

Useiden lääkkeiden yhtäaikainen käyttö on nykyään hyvin yleistä, mikä lisää lääkeaineiden haitallisten yhteisvaikutusten riskiä. Lääkeaineiden poistumisessa elimistöstä ovat tärkeässä osassa niitä hajottavat (metaboloivat) maksan sytokromi P450 (CYP) entsyymit. Vasta aivan viime vuosina on havaittu, että CYP2C8-entsyymillä voi olla tärkeä merkitys mm. lääkeaineyhteisvaikutuksissa. Eräät lääkeaineet voivat estää (inhiboida) CYP2C8-entsyymin kautta tapahtuvaa metaboliaa. Tässä työssä selvitettiin CYP2C8-entsyymiä estävien lääkkeiden vaikutusta sellaisten lääkeaineiden pitoisuuksiin, joiden aikaisemman tiedon perusteella arveltiin metaboloituvan CYP2C8-välitteisesti. Näiden lääkeaineiden metaboliaa tutkittiin myös koeputkiolosuhteissa (in vitro -menetelmillä). Lisäksi CYP2C8-entsyymiä estävän lipidilääke gemfibrotsiilin yhteisvaikutusmekanismia tutkittiin selvittämällä interaktion säilymistä koehenkilöillä gemfibrotsiilin annostelun lopettamisen jälkeen. Yhteisvaikutuksia tutkittiin terveillä vapaaehtoisilla koehenkilöillä käyttäen vaihtovuoroista koeasetelmaa. Koehenkilöille annettiin CYP2C8-entsyymiä estävää lääkitystä muutaman päivän ajan ja tämän jälkeen kerta-annos tutkimuslääkettä. Koehenkilöiltä otettiin useita verinäytteitä, joista määritettiin lääkepitoisuudet nestekromatografisilla tai massaspektrometrisillä menetelmillä. Gemfibrotsiili nosti ripulilääke loperamidin pitoisuudet keskimäärin kaksinkertaiseksi. Gemfibrotsiili lisäsi, mutta vain hieman, kipulääke ibuprofeenin pitoisuuksia, eikä sillä ollut mitään vaikutusta unilääke tsopiklonin pitoisuuksiin toisin kuin aiemman kirjallisuuden perusteella oli odotettavissa. Toinen CYP2C8-estäjä, mikrobilääke trimetopriimi, nosti diabeteslääke pioglitatsonin pitoisuuksia keskimäärin noin 40 %. Gemfibrotsiili nosti diabeteslääke repaglinidin pitoisuudet 7-kertaiseksi ja tämä yhteisvaikutus säilyi lähes yhtä voimakkaana vielä 12 tunnin päähän viimeisestä gemfibrotsiiliannoksesta. Tehdyt havainnot ovat käytännön lääkehoidon kannalta merkittäviä ja ne selvittävät CYP2C8-entsyymin merkitystä useiden lääkkeiden metaboliassa. Gemfibrotsiilin tai muiden CYP2C8-entsyymiä estävien lääkkeiden yhteiskäyttö loperamidin kanssa voi lisätä loperamidin tehoa tai haittavaikutuksia. Toisaalta CYP2C8-entsyymin osuus tsopiklonin ja ibuprofeenin metaboliassa näyttää olevan pieni. Trimetopriimi nosti kohtalaisesti pioglitatsonin pitoisuuksia, ja kyseisten lääkkeiden yhteiskäyttö voi lisätä pioglitatsonin annosriippuvaisia haittavaikutuksia. Gemfibrotsiili-repaglinidi-yhteisvaikutuksen päämekanismi in vivo näyttää olevan CYP2C8-entsyymin palautumaton esto. Tämän vuoksi gemfibrotsiilin estovaikutus ja yhteisvaikutusriski säilyvät pitkään gemfibrotsiilin annostelun lopettamisen jälkeen, mikä tulee ottaa huomioon käytettäessä sitä CYP2C8-välitteisesti metaboloituvien lääkkeiden kanssa.Cytochrome P450 (CYP) 2C8 is involved in the metabolism of several clinically used drugs, including paclitaxel, repaglinide and rosiglitazone. Drug interactions caused by inhibition or induction of CYP2C8 can cause considerable variation in the effective exposure to its substrates. The aim of this work was to investigate the effect of model inhibitors of CYP2C8 on the pharmacokinetics of loperamide, zopiclone, ibuprofen and pioglitazone, in order to characterise the role of CYP2C8 in their metabolism. Gemfibrozil and trimethoprim were used as model inhibitors of CYP2C8. In addition, the effect of the CYP2C8*3 allele on the pharmacokinetics of pioglitazone was investigated. Finally, the effect of dosing interval between gemfibrozil and repaglinide was studied in relation to the gemfibrozil-repaglinide interaction. Studies I to V were randomised crossover studies with 2 to 5 phases. 10 to 16 healthy volunteers participated in each study. Pre-treatment with a clinically relevant dose of inhibitor (gemfibrozil, itraconazole or trimethoprim) was followed by a single oral dose of the study drug (loperamide, zopiclone, ibuprofen, pioglitazone or repaglinide). Thereafter, blood and urine samples were collected for the determination of drug concentrations. The pharmacodynamics of loperamide and zopiclone were assessed by psychomotor tests and subjective evaluations, and that of repaglinide by blood glucose measurements. Additionally, the metabolism of zopiclone and pioglitazone was studied in vitro in studies II and IV. Gemfibrozil, itraconazole and their combination raised the area under the concentration-time curve (AUC) of loperamide 2.2- (P < 0.05), 3.8- (P < 0.001) and 12.6-fold (P < 0.001), respectively, compared to placebo. Gemfibrozil had no effect on the pharmacokinetics of parent zopiclone. On the other hand, gemfibrozil raised the AUC of R-ibuprofen by 34% (P < 0.001) and increased its elimination half-life (t½) from 2.9 to 4.5 hours (P < 0.001), with only minor effects on the S-enantiomer of ibuprofen. Trimethoprim raised the AUC of pioglitazone by 42% (P < 0.001) and prolonged its dominant t½ from 3.9 to 5.1 hours (P < 0.001), but had no effect on its peak plasma concentration (Cmax). The CYP2C8*3 allele was associated with a decreased AUC of pioglitazone compared to the subjects with the reference genotype (CYP2C8*1/*1), and after correction for weight, this difference was statistically significant (P < 0.05). The gemfibrozil-repaglinide interaction persisted up to a 12 hour dosing interval between gemfibrozil and repaglinide. Gemfibrozil ingested simultaneously with or 3, 6, or 12 hours before repaglinide increased repaglinide AUC0-∞ 7.0-, 6.5-, 6.2- and 5.0-fold, respectively (P < 0.001), and the Cmax of repaglinide increased about two-fold in all gemfibrozil phases (P < 0.001), compared to control. During repaglinide administration, the mean blood glucose concentration from 0 to 9 hours decreased in each of the gemfibrozil phases, compared to control (P < 0.005), whereas the pharmacodynamics of loperamide and zopiclone were not affected by the pre-treatment drugs. In vitro, zopiclone (500 nM) elimination was not affected by the CYP2C8 inhibitors montelukast and gemfibrozil, but the CYP3A4 inhibitors itraconazole and ketoconazole markedly inhibited its elimination. Pioglitazone metabolite M-IV formation was inhibited by trimethoprim in pooled human liver microsomes (HLM) and recombinant human CYP2C8 (rhCYP2C8). At clinically relevant concentrations of pioglitazone, CYP2C8 was predominantly responsible for M-IV formation, whereas at higher concentrations the role of CYP3A4 increased. These studies clarify the role of CYP2C8 in the metabolism of several drugs. The concentrations of loperamide and R-ibuprofen were found to be increased by the CYP2C8 inhibitor gemfibrozil, indicating that CYP2C8 participates in the metabolism of these drugs in vivo. On the other hand, the metabolism of zopiclone at clinically relevant concentrations was not affected in vivo or in vitro by CYP2C8 inhibition. Trimethoprim moderately raised the plasma concentrations of pioglitazone by inhibiting its CYP2C8-mediated biotransformation. In addition, the CYP2C8*3 allele was associated with increased metabolic clearance of pioglitazone in vivo, which is in line with the results of pharmacogenetic studies on repaglinide and rosiglitazone. The inhibitory effect of gemfibrozil on CYP2C8 persists at least 12 hours, strongly suggesting that the main mechanism of the gemfibrozil-repaglinide interaction is irreversible mechanism-based inhibition of CYP2C8

Luonnollinen gradientti variaatio-Bayes-oppimisessa

Todennäköisyysmalleilla on hyvin tärkeä asema koneoppimisessa, ja näiden mallien tehokas oppiminen on tärkeä ongelma. Valitettavasti näiden mallien matemaattinen käsittely suoraan on usein mahdotonta, ja mallien oppimisessa joudutaankin turvautumaan erilaisiin approksimaatioihin. Eräs tällainen approksimaatio on variaatiol3ayes-menetelmä, jossa todellista posteriorijakaumaa approksimoidaan toisella jakaumalla ja näiden kahden jakauman välistä eroa pyritään minimoimaan. Variaatio-Bayes-oppimisessa voidaan käyttää monia eri optimointialgoritmeja. Tässä työssä keskitytään gradienttipohjaisiin algoritmeihin. Näillä algoritmeilla on kuitenkin tyypillisesti yksi heikkous. Yleensä nämä menetelmät olettavat, että avaruus, jossa funktiota optimoidaan, on geometrialtaan euklidinen. Tilastollisissa malleissa tämä ei usein pidä paikkaansa, vaan avaruus on todellisuudessa Riemannin monisto. Luonnolliseen gradienttiin pohjautuvat optimointialgoritmit ottavat tämän geometrisen ominaisuuden huomioon ja ovat usein huomattavasti nopeampia kuin perinteiset optimointialgoritmit. Eräs tehokas ja suhteellisen yksinkertainen menetelmä saadaan yleistämällä konjugaattigradienttialgoritmi Riemannin monistoille. Näin saatua menetelmää kutsutaan Riemannin konjugaattigradientiksi. Tässä työssä esitellään tehokas Riemannin konjugaattigradienttialgoritmi variaatio-Bayes-menetelmää käyttävien tilastollisten mallien oppimiseen. Esimerkkiongelmana käytetään epälineaarisia tila-avaruusmalleja, joita käytetään sekä keinotekoisten että todellisten data-aineistojen oppimiseen. Näistä kokeista saadut tulokset osoittavat että esitelty algoritmi on huomattavasti tehokkaampi kuin muut vertailussa käytetyt perinteisemmät algoritmit.Probabilistic models play a very important role in machine learning, and the efficient learning of such models is a very important problem. Unfortunately, the exact statistical treatment of probabilistic models is often impossible and therefore various approximations have to be used. One such approximation is given by variational Bayesian (VB) learning which uses another distribution to approximate the true posterior distribution and tries to minimise the misfit between the two distributions. Many different optimisation algorithms can be used for variational Bayesian learning. This thesis concentrates on gradient based optimisation algorithms. Most of these algorithms suffer from one significant shortcoming, however. Typically these methods assume that the geometry of the problem space is flat, whereas in reality the space is a curved Riemannian manifold. Natural-gradient-based optimisation algorithms take this property into account, and can often result in significant speedups compared to traditional optimisation methods. One particularly powerful and relatively simple algorithm can be derived by extending conjugate gradient to Riemannian manifolds. The resulting algorithm is known as Riemannian conjugate gradient. This thesis presents an efficient Riemannian conjugate gradient algorithm for learning probabilistic models where variational approximation is used. Nonlinear state-space models are used as a case study, and results from experiments with both synthetic and real-world data sets are presented. The results demonstrate that the proposed algorithm provides significant performance gains over the other compared methods

Digoxin use and outcomes after myocardial infarction in patients with atrial fibrillation

Digoxin is used for rate control in atrial fibrillation (AF), but evidence for its efficacy and safety after myocardial infarction (MI) is scarce and mixed. We studied post-MI digoxin use effects on AF patient outcomes in a nationwide registry follow-up study in Finland. Digoxin was used by 18.6% of AF patients after MI, with a decreasing usage trend during 2004-2014. Baseline differences in digoxin users (n = 881) and controls (n = 3898) were balanced with inverse probability of treatment weight adjustment. The median follow-up was 7.4 years. Patients using digoxin after MI had a higher cumulative all-cause mortality (77.4% vs. 72.3%; hazard ratio [HR]: 1.19; confidence interval [CI]: 1.07-1.32; p = 0.001) during a 10-year follow-up. Mortality differences were detected in a subgroup analysis of patients without baseline heart failure (HF) (HR: 1.23; p = 0.019) but not in patients with baseline HF (HR: 1.05; p = 0.413). Cumulative incidences of HF hospitalizations, stroke and new MI were similar between digoxin group and controls. In conclusion, digoxin use after MI is associated with increased mortality but not with HF hospitalizations, new MI or stroke in AF patients. Increased mortality was detected in patients without baseline HF. Results suggest caution with digoxin after MI in AF patients, especially in the absence of HF.Peer reviewe

Translational aspects of cytochrome P450-mediated drug-drug interactions : A case study with clopidogrel

Multimorbidity, polypharmacotherapy and drug interactions are increasingly common in the ageing population. Many drug-drug interactions (DDIs) are caused by perpetrator drugs inhibiting or inducing cytochrome P450 (CYP) enzymes, resulting in alterations of the plasma concentrations of a victim drug. DDIs can have a major negative health impact, and in the past, unrecognized DDIs have resulted in drug withdrawals from the market. Signals to investigate DDIs may emerge from a variety of sources. Nowadays, standard methods are widely available to identify and characterize the mechanisms of CYP-mediated DDIs in vitro. Clinical pharmacokinetic studies, in turn, provide experimental data on pharmacokinetic outcomes of DDIs. Physiologically based pharmacokinetic (PBPK) modelling utilizing both in vitro and in vivo data is a powerful tool to predict different DDI scenarios. Finally, epidemiological studies can provide estimates on the health outcomes of DDIs. Thus, to fully characterize the mechanisms, clinical effects and implications of CYP-mediated DDIs, translational research approaches are required. This minireview provides an overview of translational approaches to study CYP-mediated DDIs, going beyond regulatory DDI guidelines, and an illustrative case study of how the DDI potential of clopidogrel was unveiled by combining these different methods.Peer reviewe

A common missense variant of <i>LILRB₅</i> is associated with statin intolerance and myalgia

Aims A genetic variant in LILRB5 (leukocyte immunoglobulin-like receptor subfamily-B) (rs12975366: T > C: Asp247Gly) has been reported to be associated with lower creatine phosphokinase (CK) and lactate dehydrogenase (LDH) levels. Both biomarkers are released from injured muscle tissue, making this variant a potential candidate for susceptibility to muscle-related symptoms. We examined the association of this variant with statin intolerance ascertained from electronic medical records in the GoDARTS study. Methods and results In the GoDARTS cohort, the LILRB5 Asp247 variant was associated with statin intolerance (SI) phenotypes; one defined as having raised CK and being non-adherent to therapy [odds ratio (OR) 1.81; 95% confidence interval (CI): 1.34–2.45] and the other as being intolerant to the lowest approved dose of a statin before being switched to two or more other statins (OR 1.36; 95% CI: 1.07–1.73). Those homozygous for Asp247 had increased odds of developing both definitions of intolerance. Importantly the second definition did not rely on CK elevations. These results were replicated in adjudicated cases of statin-induced myopathy in the PREDICTION-ADR consortium (OR1.48; 95% CI: 1.05–2.10) and for the development of myalgia in the JUPITER randomized clinical trial of rosuvastatin (OR1.35, 95% CI: 1.10–1.68). A meta-analysis across the studies showed a consistent association between Asp247Gly and outcomes associated with SI (OR1.34; 95% CI: 1.16–1.54). Conclusion This study presents a novel immunogenetic factor associated with statin intolerance, an important risk factor for cardiovascular outcomes. The results suggest that true statin-induced myalgia and non-specific myalgia are distinct, with a potential role for the immune system in their development. We identify a genetic group that is more likely to be intolerant to their statins

Clinical Studies on Drug-Drug Interactions Involving Metabolism and Transport : Methodology, Pitfalls, and Interpretation

Many drug-drug interactions (DDIs) are based on alterations of the plasma concentrations of a victim drug due to another drug causing inhibition and/or induction of the metabolism or transporter-mediated disposition of the victim drug. In the worst case, such interactions cause more than tenfold increases or decreases in victim drug exposure, with potentially life-threatening consequences. There has been tremendous progress in the predictability and modeling of DDIs. Accordingly, the combination of modeling approaches and clinical studies is the current mainstay in evaluation of the pharmacokinetic DDI risks of drugs. In this paper, we focus on the methodology of clinical studies on DDIs involving drug metabolism or transport. We specifically present considerations related to general DDI study designs, recommended enzyme and transporter index substrates and inhibitors, pharmacogenetic perspectives, index drug cocktails, endogenous substrates, limited sampling strategies, physiologically-based pharmacokinetic modeling, complex DDIs, methodological pitfalls, and interpretation of DDI information.Peer reviewe