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Fan HC, Chiang KL, Chang KH, Chen CM, Tsai JD. Epilepsy and Attention Deficit Hyperactivity Disorder: Connection, Chance, and Challenges. Int J Mol Sci 2023; 24:ijms24065270. [PMID: 36982345 PMCID: PMC10049646 DOI: 10.3390/ijms24065270] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 02/20/2023] [Accepted: 03/01/2023] [Indexed: 03/12/2023] Open
Abstract
Comorbidities are common in children with epilepsy, with nearly half of the patients having at least one comorbidity. Attention deficit hyperactivity disorder (ADHD) is a psychiatric disorder characterized by hyperactivity and inattentiveness level disproportional to the child’s developmental stage. The burden of ADHD in children with epilepsy is high and can adversely affect the patients’ clinical outcomes, psychosocial aspects, and quality of life. Several hypotheses were proposed to explain the high burden of ADHD in childhood epilepsy; the well-established bidirectional connection and shared genetic/non-genetic factors between epilepsy and comorbid ADHD largely rule out the possibility of a chance in this association. Stimulants are effective in children with comorbid ADHD, and the current body of evidence supports their safety within the approved dose. Nonetheless, safety data should be further studied in randomized, double-blinded, placebo-controlled trials. Comorbid ADHD is still under-recognized in clinical practice. Early identification and management of comorbid ADHD are crucial to optimize the prognosis and reduce the risk of adverse long-term neurodevelopmental outcomes. The identification of the shared genetic background of epilepsy and ADHD can open the gate for tailoring treatment options for these patients through precision medicine.
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Affiliation(s)
- Hueng-Chuen Fan
- Department of Pediatrics, Tungs’ Taichung Metroharbor Hospital, Wuchi, Taichung 435, Taiwan
- Department of Rehabilitation, Jen-Teh Junior College of Medicine, Nursing and Management, Miaoli 356, Taiwan
- Department of Life Sciences, Agricultural Biotechnology Center, National Chung Hsing University, Taichung 402, Taiwan
| | - Kuo-Liang Chiang
- Department of Pediatric Neurology, Kuang-Tien General Hospital, Taichung 433, Taiwan
- Department of Nutrition, Hungkuang University, Taichung 433, Taiwan
| | - Kuang-Hsi Chang
- Department of Medical Research, Tungs’ Taichung Metroharbor Hospital, Wuchi, Taichung 435, Taiwan
| | - Chuan-Mu Chen
- Department of Life Sciences, Agricultural Biotechnology Center, National Chung Hsing University, Taichung 402, Taiwan
- The iEGG and Animal Biotechnology Center, and Rong Hsing Research Center for Translational Medicine, National Chung Hsing University, Taichung 402, Taiwan
- Correspondence: (C.-M.C.); (J.-D.T.); Tel.: +886-4-22840319-701 (C.-M.C.); +886-4-24730022-21731 (J.-D.T.)
| | - Jeng-Dau Tsai
- School of Medicine, Chung Shan Medical University, Taichung 402, Taiwan
- Department of Pediatrics, Chung Shan Medical University Hospital, Taichung 402, Taiwan
- Correspondence: (C.-M.C.); (J.-D.T.); Tel.: +886-4-22840319-701 (C.-M.C.); +886-4-24730022-21731 (J.-D.T.)
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Nguyen TPP, Soprano SE, Hennessy S, Brensinger CM, Bilker WB, Miano TA, Acton EK, Horn JR, Chung SP, Dublin S, Oslin DW, Wiebe DJ, Leonard CE. Population-based signals of benzodiazepine drug interactions associated with unintentional traumatic injury. J Psychiatr Res 2022; 151:299-303. [PMID: 35526445 PMCID: PMC9513701 DOI: 10.1016/j.jpsychires.2022.04.033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 04/19/2022] [Accepted: 04/25/2022] [Indexed: 10/18/2022]
Abstract
Benzodiazepine receptor agonists and related medications, such as Z-drugs and dual orexin receptor antagonists (BZDs), have been associated with unintentional traumatic injury due to their central nervous system (CNS)-depressant effects. Drug-drug interactions (DDIs) may contribute to the known relationship between BZD use and unintentional traumatic injury, yet evidence is still lacking. We conducted high-throughput pharmacoepidemiologic screening using the self-controlled case series design in a large US commercial health insurance database to identify potentially clinically relevant DDI signals among new users of BZDs. We used conditional Poisson regression to estimate rate ratios (RRs) between each co-exposure (vs. not) and unintentional traumatic injury (primary outcome), typical hip fracture (secondary outcome), and motor vehicle crash (secondary outcome). We identified 48 potential DDI signals (1.1%, involving 39 unique co-dispensed drugs), i.e., with statistically significant elevated adjusted RRs for injury. Signals were strongest for DDI pairs involving zolpidem, lorazepam, temazepam, alprazolam, eszopiclone, triazolam, and clonazepam. We also identified four potential DDI signals for typical hip fracture, but none for motor vehicle crash. Many signals have biologically plausible explanations through additive or synergistic pharmacodynamic effects of co-dispensed antidepressants, opioids, or muscle relaxants on CNS depression, impaired psychomotor and cognitive function, and/or somnolence. While other signals that lack an obvious mechanism may represent true associations that place patients at risk of injury, it is also prudent to consider the roles of chance, reverse causation, and/or confounding by indication, which merit further exploration. Given the high-throughput nature of our investigation, findings should be interpreted as hypothesis generating.
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Affiliation(s)
- Thanh Phuong Pham Nguyen
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania (Philadelphia, PA, US),Translational Center of Excellence for Neuroepidemiology and Neurology Outcomes Research, Department of Neurology, Perelman School of Medicine, University of Pennsylvania (Philadelphia, PA, US)
| | - Samantha E. Soprano
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania (Philadelphia, PA, US),Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania (Philadelphia, PA, US)
| | - Sean Hennessy
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania (Philadelphia, PA, US),Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania (Philadelphia, PA, US),Department of Systems Pharmacology and Translational Therapeutics, Perelman School of Medicine, University of Pennsylvania (Philadelphia, PA, US),Leonard Davis Institute of Health Economics, University of Pennsylvania (Philadelphia, PA, US)
| | - Colleen M. Brensinger
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania (Philadelphia, PA, US),Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania (Philadelphia, PA, US)
| | - Warren B. Bilker
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania (Philadelphia, PA, US),Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania (Philadelphia, PA, US),Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania (Philadelphia, PA, US)
| | - Todd A. Miano
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania (Philadelphia, PA, US),Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania (Philadelphia, PA, US)
| | - Emily K. Acton
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania (Philadelphia, PA, US),Translational Center of Excellence for Neuroepidemiology and Neurology Outcomes Research, Department of Neurology, Perelman School of Medicine, University of Pennsylvania (Philadelphia, PA, US),Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania (Philadelphia, PA, US)
| | - John R. Horn
- Department of Pharmacy, School of Pharmacy, University of Washington (Seattle, WA, US)
| | | | - Sascha Dublin
- Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington (Seattle, WA, US),Department of Epidemiology, School of Public Health, University of Washington (Seattle, WA, US)
| | - David W. Oslin
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania (Philadelphia, PA, US),Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania (Philadelphia, PA, US),Mental Illness Research, Education, and Clinical Center, Corporal Michael J. Crescenz Veterans Administration Medical Center (Philadelphia, PA, US)
| | - Douglas J. Wiebe
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania (Philadelphia, PA, US),Leonard Davis Institute of Health Economics, University of Pennsylvania (Philadelphia, PA, US),Penn Injury Science Center, University of Pennsylvania (Philadelphia, PA, US)
| | - Charles E. Leonard
- Center for Pharmacoepidemiology Research and Training, Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania (Philadelphia, PA, US),Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania (Philadelphia, PA, US),Leonard Davis Institute of Health Economics, University of Pennsylvania (Philadelphia, PA, US)
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Bankstahl M, Bankstahl JP, Bloms-Funke P, Löscher W. Striking differences in proconvulsant-induced alterations of seizure threshold in two rat models. Neurotoxicology 2011; 33:127-37. [PMID: 22209701 DOI: 10.1016/j.neuro.2011.12.011] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2011] [Revised: 11/24/2011] [Accepted: 12/12/2011] [Indexed: 11/28/2022]
Abstract
During drug development, seizure threshold tests are widely used to identify potential proconvulsant activity of investigational drugs. The most commonly used tests in this respect are the timed intravenous pentylenetetrazole (PTZ) infusion seizure test and the maximal electroshock seizure threshold (MEST) test in mice or rats. To our knowledge, no study is available in which proconvulsant drug activities in these models are directly compared, which prompted us to perform such experiments in male Wistar rats. Five drugs with reported proconvulsant activity were tested in the two models: d-amphetamine, chlorpromazine, caffeine, theophylline, and tramadol. Furthermore, the anticonvulsant drug phenobarbital was included in the experiments. While phenobarbital exerted anticonvulsant activity in both models, the five proconvulsant drugs markedly differed in their effects. In the dose range tested, d-amphetamine significantly lowered the PTZ seizure threshold but increased the MEST, caffeine and theophylline did not alter the PTZ seizure threshold but decreased the MEST, and tramadol reduced the PTZ threshold but increased the MEST. These marked differences between seizure threshold tests are most likely a consequence of the mechanisms underlying seizure induction in these tests. Our data indicate that using only one seizure threshold model during preclinical drug development may pose the risk that potential proconvulsant activity of an investigational drug is overseen. However, the label "proconvulsant" may be misleading if such activity only occurs at doses high above the therapeutic range, but the drug is not proconvulsant or even exerts anticonvulsant effects at lower, therapeutically relevant doses.
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Affiliation(s)
- Marion Bankstahl
- Department of Pharmacology, Toxicology, and Pharmacy, University of Veterinary Medicine Hannover, Hannover, Germany
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Johannessen SI, Landmark CJ. Antiepileptic drug interactions - principles and clinical implications. Curr Neuropharmacol 2011; 8:254-67. [PMID: 21358975 PMCID: PMC3001218 DOI: 10.2174/157015910792246254] [Citation(s) in RCA: 220] [Impact Index Per Article: 16.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2009] [Revised: 05/10/2010] [Accepted: 05/26/2010] [Indexed: 02/06/2023] Open
Abstract
Antiepileptic drugs (AEDs) are widely used as long-term adjunctive therapy or as monotherapy in epilepsy and other indications and consist of a group of drugs that are highly susceptible to drug interactions. The purpose of the present review is to focus upon clinically relevant interactions where AEDs are involved and especially on pharmacokinetic interactions. The older AEDs are susceptible to cause induction (carbamazepine, phenobarbital, phenytoin, primidone) or inhibition (valproic acid), resulting in a decrease or increase, respectively, in the serum concentration of other AEDs, as well as other drug classes (anticoagulants, oral contraceptives, antidepressants, antipsychotics, antimicrobal drugs, antineoplastic drugs, and immunosupressants). Conversely, the serum concentrations of AEDs may be increased by enzyme inhibitors among antidepressants and antipsychotics, antimicrobal drugs (as macrolides or isoniazid) and decreased by other mechanisms as induction, reduced absorption or excretion (as oral contraceptives, cimetidine, probenicid and antacides). Pharmacokinetic interactions involving newer AEDs include the enzyme inhibitors felbamate, rufinamide, and stiripentol and the inducers oxcarbazepine and topiramate. Lamotrigine is affected by these drugs, older AEDs and other drug classes as oral contraceptives. Individual AED interactions may be divided into three levels depending on the clinical consequences of alterations in serum concentrations. This approach may point to interactions of specific importance, although it should be implemented with caution, as it is not meant to oversimplify fact matters. Level 1 involves serious clinical consequences, and the combination should be avoided. Level 2 usually implies cautiousness and possible dosage adjustments, as the combination may not be possible to avoid. Level 3 refers to interactions where dosage adjustments are usually not necessary. Updated knowledge regarding drug interactions is important to predict the potential for harmful or lacking effects involving AEDs.
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Affiliation(s)
- Svein I Johannessen
- The National Center for Epilepsy, Sandvika, and Department of Pharmacology, Oslo University Hospital, Oslo, Norway
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