The association of antiepileptic drugs (AEDs) with bone disease, balance function, falls and fractures: studies of the risk

© 2012 Dr. Baemisla Shiek AhmadAims: Patients with epilepsy taking long-term anti-epileptic drug (AED) therapy have been reported to have an elevated risk of fractures, falls, balance impairment and bone disease. In the work for this thesis, four studies were undertaken which were designed to investigate the associations of AED therapy with the prevalence of falls and fractures in patients taking AEDs compared to non-AED users; to assess the level of patient awareness regarding AED-related bone health, falls and fracture risk; to examine potential associations of AED therapy, both recent and long-term, on bone measures; and to evaluate any association of chronic therapy on balance function. Included in the evaluation were risk factors including age, AED polytherapy, therapy length, gender and types of AED (enzyme-inducing vs. non-enzyme inducing). Methods: Data on falls, fracture history and associated risks were collected in 150 epilepsy outpatients taking AEDs and 506 controls, and analysed cross-sectionally by univariate and multivariate methods to assess the prevalence of falls and fractures, and associated factors. Baseline and follow-up bone assessments (separated by at least two years) were performed in two cohorts, including: i) 54 twin and sibling pairs discordant for chronic therapy, and ii) 57 newly-diagnosed epilepsy patients recently started on therapy and 54 controls, using dual energy X-ray absorptiometry, and peripheral quantitative computed tomography. Balance examinations were performed for 26 AED-discordant twin and sibling pairs, with re-assessment at least one year later. The annual rate of change of bone and balance measures were calculated. Cross-sectional and longitudinal data were analyzed by univariate and multivariate analyses. Results: Compared to controls, epilepsy outpatients had a higher risk of fractures at vertebrae (p = 0.037), clavicle (p = 0.019) and ankle sites (p = 0.048), and multiple fracture episodes (p = 0.008). Female users had more non-seizure falls (31% vs. 17%, p = 0.027) and multiple falls (18% vs. 5%, p = 0.028) compared to female non-users. Less than 30% of patients knew of the association of AED use with increased risk for fractures, reduced bone mineral density (BMD) or falls. Prolonged AED therapy (> 20 years) significantly predicted an increased rate of bone loss for forearm BMD (-0.53%/yr; p = 0.040) and whole-body BMD (-0.37%/yr; p = 0.043). AED therapy was a significant predictor of increased bone loss at whole-body BMC (-0.26%/year; p = 0.041). Use of enzyme-inducing AEDs was associated with increased bone loss at the total hip (-1.65%/yr; p = 0.013) and whole-body BMD (-1.41%/yr; p = 0.019). In the initial years of AED therapy carbamazepine monotherapy (an enzyme-inducer) was associated with increased bone loss at the total hip (p = 0.034) and inter-trochanteric regions (p = 0.035). Postural sway deterioration was greater in AED users than non-users, with anterior-posterior (A-P) tilting and a concurrent distraction task (p = 0.016), and medial-lateral tilting without distraction (p = 0.027). In females (but not in the small male subsample), sway deterioration was greater in users with the A-P tilting platform and a concurrent distraction task (p = 0.035). Lower limb muscle strength and gait did not deteriorate over time. Conclusions: AED users demonstrated a higher risk of fractures, particularly with prolonged therapy. Female users were at increased risk of falls than female non-users. Greater BMD loss was associated with prolonged therapy and enzyme-inducing AEDs. Carbamazepine use in early therapy predicted increased hip region bone loss. Postural stability deteriorated over time in AED users compared to non-users. Awareness amongst epilepsy patients of AED-related effects was low. Findings suggests an association between chronic therapy and progressive underlying pathophysiology, adversely affecting bone measures and balance, both risk factors for fractures. Patients may benefit from taking NEIAEDs, rather than EIAEDs, to reduce associated long-term risks of bone fragility. These risks need consideration when managing patients taking AEDs

Bone Mineral Changes in Epilepsy Patients During Initial Years of Antiepileptic Drug Therapy

Antiepileptic drug (AED) therapy is associated with decreased bone mineral density; however, the time course for this development is unclear. The aim of this study was to evaluate bone mineral changes during the initial years of AED therapy in AED-naive, newly diagnosed epilepsy patients compared with non-AED users. In 49 epilepsy patients newly started on AEDs and in 53 non-AED users of both genders, bone mineral density (BMD) and bone mineral content were measured using dual-energy X-ray absorptiometry at baseline (within the first year of therapy) and at least 1 yr later. Bone changes between the 2 assessments, adjusted for age, height, and weight, were calculated as the annual rate of change. The median duration of AED therapy was 3.5 mo at baseline and 27.6 mo at follow-up. No overall difference was found in mean BMD and bone mineral content measures between user and nonuser cohorts in both cross-sectional baseline and the annual rate of change (p > 0.05). However, users on carbamazepine monotherapy (n = 11) had an increased annual rate of total hip (−2.1% vs −0.8%, p = 0.020) and femoral neck BMD loss (−2.1% vs −0.6%, p = 0.032) compared to nonusers. They also had a marginally higher rate of femoral neck BMD loss (−2.1%, p  = 0.049) compared with valproate (−0.1%, n = 13) and levetiracetam users (+0.6%, n = 13). During the initial years of AED treatment for epilepsy, no difference was found in bone measures between AED users as a group and nonuser cohorts.However, the data suggested that carbamazepine monotherapy was associated with increased bone loss at the hip regions, compared to users of levetiracetam or valproate and nonusers. Larger studies of longer duration are warranted to better delineate the bone effects of specific AEDs, with further consideration of the role of early dual-energy X-ray absorptiometry scanning and careful AED selection in potentially minimizing the impact on bone health in these patients

Screening of Crucial Cytosolicproteins Interconnecting the Endoplasmic Reticulum and Mitochondria in Parkinson’s Disease and the Impact of Anti-Parkinson Drugs in the Preservation of Organelle Connectivity

Mitochondrial dysfunction is well-established in Parkinson’s disease (PD); however, its dysfunctions associating with cell organelle connectivity remain unknown. We aimed to establish the crucial cytosolic protein involved in organelle connectivity between mitochondria and the endopalmic reticulum (ER) through a computational approach by constructing an organelle protein network to extract functional clusters presenting the crucial PD protein connecting organelles. Then, we assessed the influence of anti-parkinsonism drugs (n = 35) on the crucial protein through molecular docking and molecular dynamic simulation and further validated its gene expression in PD participants under, istradefylline (n = 25) and amantadine (n = 25) treatment. Based on our investigation, D-aspartate oxidase (DDO )protein was found to be the critical that connects both mitochondria and the ER. Further, molecular docking showed that istradefylline has a high affinity (−9.073 kcal/mol) against DDO protein, which may disrupt mitochondrial-ER connectivity. While amantadine (−4.53 kcal/mol) shows negligible effects against DDO that contribute to conformational changes in drug binding, Successively, DDO gene expression was downregulated in istradefylline-treated PD participants, which elucidated the likelihood of an istradefylline off-target mechanism. Overall, our findings illuminate the off-target effects of anti-parkinsonism medications on DDO protein, enabling the recommendation of off-target-free PD treatments

Comparative Efficacy of Metformin and Glimepiride in Modulating Pharmacological Network to Increase BDNF Levels and Benefit Type 2 Diabetes-Related Cognitive Impairment

Cognitive impairment is anotable complication of type 2 diabetes (T2DM), accompanied by reduced brain-derived neurotrophic factor (BDNF) in the brain and blood. Anti-diabetic drugs reduce hyperglycemia, yet their effect on cognitive improvement is unknown. We aimed to investigate the effect of anti-diabetic drugs regulating BDNF in T2DM through computational and case-control study design. We obtained T2DMproteins viatext-mining to construct a T2DMprotein network. From the T2DMnetwork, the metformin and glimepiride interactomes and their crucial shortest-path-stimulating BDNF were identified. Using qRTPCR, the genes encoding the shortest-path proteins were assessed in four groups (untreated-T2DM, metformin-treated, glimepiride-treated, and healthy controls). Finally, ELISA was used to assess serum BDNF levels to validate drug efficacy. As a result of this investigation, aT2DMnetwork was constructed with 3683 text-mined proteins. Then, the T2DMnetwork was explored to generate a metformin and glimepiride interactome that establishes the critical shortest-path for BDNF stimulation. Metformin stimulates BDNF via APP binding to the PRKAB1 receptor. Whereas, glimepiride increases BDNF by binding to KCNJ11 via AP2M1 and ESR1 proteins. Both drug shortest-path encoding genes differed significantly between the groups. Unlike metformin, BDNF gene and protein expression rise significantly with glimepiride. Overall, glimepiride can effectively increase BDNF, which could benefit T2DM patients with cognitive deterioration

Bone loss with antiepileptic drug therapy: a twin and sibling study

© 2017 International Osteoporosis Foundation and National Osteoporosis FoundationSummary: Changes in areal bone mineral density (aBMD) and other predictors of bone loss were evaluated in 48 same-sex twin/age-matched sibling pairs discordant for antiepileptic drug (AED) use. AED users had reduced BMD at the hip regions. Prolonged AED users had greater aBMD loss, predicting a higher risk of bone fragility. Introduction: To investigate the longitudinal associations of bone mineral measures with antiepileptic drug (AED) use, including enzyme-inducing (EIAED) and non-enzyme-inducing (NEIAED) types, and other predictors of bone loss in a study of 48 same-sex twin/age-matched sibling pairs (40 female, 8 male) discordant for AED use. Methods: Using dual-energy X-ray absorptiometry (DXA), areal bone mineral density (aBMD) and content (BMC) at the hip regions, forearm, lumbar spine, and whole body were measured twice, at least 2 years apart. The mean within-pair difference (MWPD), MWPD%, and mean annual rate of aBMD change were adjusted for age, weight, and height. Predictors of bone loss were evaluated. Results: AED users, compared to non-users, at baseline and follow-up, respectively, had reduced aBMD at the total hip (MWPD% 3.8, 4.4%), femoral neck (4.7, 4.5%), and trochanter regions (4.1, 4.6%) (p < 0.05). For the whole cohort, the annual rate of change in all aBMD/BMC (p > 0.05) regions did not differ within pairs. Nevertheless, EIAED users had greater aBMD loss than non-users (n = 20 pairs) at the total hip (1.7 vs. 0.3%, p = 0.013) and whole body regions (0.7% loss vs. 0.1% BMD gain, p = 0.019), which was not found in NEIAED-discordant pairs (n = 16). AED use >20 years predicted higher aBMD loss at the forearm (p = 0.028), whole body (p = 0.010), and whole body BMC (p = 0.031). Conclusions: AED users had reduced aBMD at the hip regions. Prolonged users and EIAED users had greater aBMD loss, predicting a higher risk of bone fragility. Further prospective studies of AED effects on bone microarchitecture are needed

Associations Between Serum Sodium Concentration and Bone Health Measures in Individuals Who Use Antiepileptic Drugs : A Pilot Study

Hyponatraemia, defined as a serum sodium concentration ([Na+]) below 135 mmol/L, is the most common electrolyte disturbance observed in clinical practice (1). Hyponatraemia is associated with increased risk of osteoporosis (2,3), fractures (4,5), fractures independent of osteoporosis (3,5), and falls (4). One of the common medication classes that cause hyponatraemia is antiepileptic drugs (AEDs), which are often used lifelong in patients with epilepsy, and increasingly in other conditions. AEDs can be classified as hepatic CYP450 enzyme-inducing AEDs (EIAEDs) or non-enzyme-inducing AEDs (NEIAEDs). Certain AEDs, such as carbamazepine and oxcarbazepine, demonstrate stronger associations with hyponatraemia than other AEDs (6). Whilst inducing hyponatraemia, AEDs are also independently associated with increased risk of osteoporosis and fracture (7). However, the underlying mechanisms by which AEDs adversely affect the risk of fragility fracture, and also cause hyponatraemia remain uncertain and likely are multifactorial. A potential association between serum sodium concentration and the risk of fragility fracture in AED users appears not to have been explored previously and could help explain how AEDs are associated with impaired bone health. In this pilot study, we investigated the associations between the risk of fragility fracture (indicated by areal BMD (aBMD), fracture history, and falls history), and serum sodium concentrations in AED users. We hypothesised that AED use is associated with hyponatraemia, which is also associated with low aBMD and an increase in reported history of fractures and falls. Materials and Methods: This was a retrospective study including patients with epilepsy from 3 studies approved by the Human Research Ethics Committee (HREC) at Melbourne Health, Victoria, Australia. All participants provided written consent to participate in the studies

Elucidating the Histone Deacetylase Gene Expression Signatures in Peripheral Blood Mononuclear Cells That Correlate Essential Cardiac Function and Aid in Classifying Coronary Artery Disease through a Logistic Regression Model

A proinflammatory role of HDACs has been implicated in the pathogenesis of atherosclerosis as an emerging novel epigenetic diagnostic biomarker. However, its association with the clinical and cardiovascular function in coronary artery disease is largely unknown. The study aimed to profile the gene expression of HDAC1–11 in human peripheral blood mononuclear cells and to evaluate their influence on hematological, biochemical, and two-dimensional echocardiographic indices in CAD. The HDAC gene expression profiles were assessed in 62 angioproven CAD patients and compared with 62 healthy controls. Among the HDACs, upregulated HDACs 1,2, 4, 6, 8, 9, and 11 were upregulated, and HDAC3 was downregulated, which was significantly (p ≤ 0.05) linked with the hematological (basophils, lymphocytes, monocytes, and neutrophils), biochemical (LDL, HDL, and TGL), and echocardiographic parameters (cardiac function: biplane LVEF, GLS, MV E/A, IVRT, and PV S/D) in CAD. Furthermore, our constructed diagnostic model with the crucial HDACs establishes the most crucial HDACs in the classification of CAD from control with an excellent accuracy of 88.6%. Conclusively, our study has provided a novel perspective on the HDAC gene expression underlying cardiac function that is useful in developing molecular methods for CAD diagnosis

Artificial Intelligence in the Diagnosis of Oral Diseases: Applications and Pitfalls

Background: Machine learning (ML) is a key component of artificial intelligence (AI). The terms machine learning, artificial intelligence, and deep learning are erroneously used interchangeably as they appear as monolithic nebulous entities. This technology offers immense possibilities and opportunities to advance diagnostics in the field of medicine and dentistry. This necessitates a deep understanding of AI and its essential components, such as machine learning (ML), artificial neural networks (ANN), and deep learning (DP). Aim: This review aims to enlighten clinicians regarding AI and its applications in the diagnosis of oral diseases, along with the prospects and challenges involved. Review results: AI has been used in the diagnosis of various oral diseases, such as dental caries, maxillary sinus diseases, periodontal diseases, salivary gland diseases, TMJ disorders, and oral cancer through clinical data and diagnostic images. Larger data sets would enable AI to predict the occurrence of precancerous conditions. They can aid in population-wide surveillance and decide on referrals to specialists. AI can efficiently detect microfeatures beyond the human eye and augment its predictive power in critical diagnosis. Conclusion: Although studies have recognized the benefit of AI, the use of artificial intelligence and machine learning has not been integrated into routine dentistry. AI is still in the research phase. The coming decade will see immense changes in diagnosis and healthcare built on the back of this research. Clinical significance: This paper reviews the various applications of AI in dentistry and illuminates the shortcomings faced while dealing with AI research and suggests ways to tackle them. Overcoming these pitfalls will aid in integrating AI seamlessly into dentistry