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Džidić-Krivić A, Sher EK, Kusturica J, Farhat EK, Nawaz A, Sher F. Unveiling drug induced nephrotoxicity using novel biomarkers and cutting-edge preventive strategies. Chem Biol Interact 2024; 388:110838. [PMID: 38104745 DOI: 10.1016/j.cbi.2023.110838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 12/03/2023] [Accepted: 12/15/2023] [Indexed: 12/19/2023]
Abstract
Drug-induced nephrotoxicity is still a significant obstacle in pharmacotherapy of various diseases and it accounts for around 25 % of serious side-effects reported after drug administration. Furthermore, some groups of drugs such as nonsteroidal anti-inflammatory drugs, antibiotics, antiviral drugs, antifungal drugs, immunosuppressants, and chemotherapeutic drugs have the "preference" for damaging the kidney and are often referred to as the kidney's "silent killer". Clinically, the onset of acute kidney injury associated with drug administration is registered in approximately 20 % of patients and many of them develop chronic kidney disease vulnerability. However, current knowledge about the mechanisms underlying this dangerous phenomenon is still insufficient with many unknowns. Hence, the valuable use of these drugs in clinical practice is significantly limited. The main aim of this study is to draw attention to commonly prescribed nephrotoxic drugs by clinicians or drugs bought over the counter. In addition, the complex relationship between immunological, vascular and inflammatory events that promote kidney damage is discussed. The practical use of this knowledge could be implemented in the engineering of novel biomarkers for early detection of drug-associated kidney damage such as Kidney Injury Molecule (KIM-1), lipocalin associated with neutrophil gelatinase (NGAL) and various microRNAs. In addition, the utilization of artificial intelligence (AI) for the development of computer algorithms that could detect kidney damage at an early stage should be further explored. Therefore, this comprehensive review provides a new outlook on drug nephrotoxicity that opens the door for further clinical research of novel potential drugs or natural products for the prevention of drug-induced nephrotoxicity and accessible education.
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Affiliation(s)
- Amina Džidić-Krivić
- Department of Neurology, Cantonal Hospital Zenica, Zenica, 72000, Bosnia and Herzegovina; International Society of Engineering Science and Technology, Nottingham, United Kingdom
| | - Emina K Sher
- Department of Biosciences, School of Science and Technology, Nottingham Trent University, Nottingham, NG11 8NS, United Kingdom.
| | - Jasna Kusturica
- Faculty of Medicine,Univerisity of Sarajevo, Sarajevo, 71000, Bosnia and Herzegovina
| | - Esma K Farhat
- International Society of Engineering Science and Technology, Nottingham, United Kingdom; Department of Food and Nutrition Research, Faculty of Food Technology, Juraj Strossmayer University of Osijek, Osijek, 31000, Croatia
| | - Asma Nawaz
- International Society of Engineering Science and Technology, Nottingham, United Kingdom; Department of Biochemistry, University of Agriculture, Faisalabad, 38040, Pakistan
| | - Farooq Sher
- Department of Engineering, School of Science and Technology, Nottingham Trent University, Nottingham, NG11 8NS, United Kingdom.
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Abstract
Many patients under treatment for mood disorders, in particular patients with bipolar mood disorders, experience episodes of mood switching from one state to another. Various hypotheses have been proposed to explain the mechanism of mood switching, spontaneously or induced by drug treatment. Animal models have also been used to test the role of psychotropic drugs in the switching of mood states. We examine the possible relationship between the pharmacology of psychotropic drugs and their reported incidents of induced mood switching, with reference to the various hypotheses of mechanisms of mood switching.
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Kverno K. Lithium: Current Clinical Guidelines for Nurse Practitioners. J Psychosoc Nurs Ment Health Serv 2022; 60:6-9. [PMID: 34978941 DOI: 10.3928/02793695-20211207-02] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
Bipolar disorder is a serious neuroprogressive disorder associated with structural and functional brain changes, multiple comorbidities, and heightened risk for suicide. Lithium has been a first-line treatment for bipolar disorder for more than 50 years and recent research suggests that early identification and treatment of bipolar disorder with lithium can alter the progression of the illness. The purpose of the current article is to review evidence for lithium's neurotrophic and neuroprotective actions and clinical guidelines for safe and effective use. [Journal of Psychosocial Nursing and Mental Health Services, 60(1), 6-9.].
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Min HK, Sung SA, Chung W, Kim YH, Chae DW, Ahn C, Oh KH, Park SK, Lee SW. Polypharmacy and the Progression of Chronic Kidney Disease: Korean Cohort Study for Outcome in Patients with Chronic Kidney Disease. Kidney Blood Press Res 2021; 46:460-468. [PMID: 34091449 DOI: 10.1159/000516029] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 03/20/2021] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION The renal hazard of polypharmacy has never been evaluated in predialysis chronic kidney disease (CKD) patients. OBJECTIVE We aimed to analyze the renal hazard of polypharmacy in predialysis CKD patients with stage 1-5. METHOD The data of 2,238 patients from a large-scale multicenter prospective Korean study (2011-2016), excluding 325 patients with various missing data, were reviewed. Polypharmacy was defined as taking 6 or more medications at the time of enrollment; renal events were defined as a ≥50% decrease in kidney function from baseline values, doubling of the serum creatinine levels, or initiation of renal replacement treatment. Hazard ratio (HR) and 95% confidence interval (CI) were calculated using Cox proportional-hazard regression analysis. RESULTS Of the 1,913 patients, the mean estimated glomerular filtration rate was 53.6 mL/min/1.73 m2. The mean medication count was 4.1, and the prevalence of polypharmacy was 27.1%. During the average period of 3.6 years, 520 patients developed renal events (27.2%). Although increased medication counts were associated with increased renal hazard with HR (95% CI) of 1.056 (1.007-1.107, p = 0.025), even after adjusting for various confounders, adding comorbidity score and kidney function nullified the statistical significance. In mediation analysis, 55.6% (p = 0.016) of renal hazard in increased medication counts was mediated by the kidney function, and there was no direct effect of medication counts on renal event development. In subgroup analysis, the renal hazard of the medication counts was evident only in stage 1-3 of CKD patients (p for interaction = 0.014). CONCLUSIONS We cannot identify the direct renal hazard of multiple medications, and most of the potential renal hazard was derived from intimate relationship with disease burden and kidney function.
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Affiliation(s)
- Hyang Ki Min
- Department of Internal Medicine, Nowon Eulji Medical Center, Eulji University, Seoul, Republic of Korea
| | - Su Ah Sung
- Department of Internal Medicine, Nowon Eulji Medical Center, Eulji University, Seoul, Republic of Korea
| | - Wookyung Chung
- Department of Internal Medicine, Gachon University, Gil Hospital, Incheon, Republic of Korea
| | - Yeong Hoon Kim
- Department of Internal Medicine, Inje University, Busan Paik Hospital, Busan, Republic of Korea
| | - Dong-Wan Chae
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnamsi, Republic of Korea
| | - Curie Ahn
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Kook-Hwan Oh
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.,Department of Internal Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Sue K Park
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Republic of Korea.,Cancer Research Institute, Seoul National University, Seoul, Republic of Korea.,Department of Biomedical Science, Seoul National University Graduate School, Seoul, Republic of Korea
| | - Sung Woo Lee
- Department of Internal Medicine, Uijeongbu Eulji University Medical Center, Uijeongbu, Republic of Korea
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Nestsiarovich A, Kumar P, Lauve NR, Hurwitz NG, Mazurie AJ, Cannon DC, Zhu Y, Nelson SJ, Crisanti AS, Kerner B, Tohen M, Perkins DJ, Lambert CG. Using Machine Learning Imputed Outcomes to Assess Drug-Dependent Risk of Self-Harm in Patients with Bipolar Disorder: A Comparative Effectiveness Study. JMIR Ment Health 2021; 8:e24522. [PMID: 33688834 PMCID: PMC8100888 DOI: 10.2196/24522] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 02/08/2021] [Accepted: 03/09/2021] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Incomplete suicidality coding in administrative claims data is a known obstacle for observational studies. With most of the negative outcomes missing from the data, it is challenging to assess the evidence on treatment strategies for the prevention of self-harm in bipolar disorder (BD), including pharmacotherapy and psychotherapy. There are conflicting data from studies on the drug-dependent risk of self-harm, and there is major uncertainty regarding the preventive effect of monotherapy and drug combinations. OBJECTIVE The aim of this study was to compare all commonly used BD pharmacotherapies, as well as psychotherapy for the risk of self-harm, in a large population of commercially insured individuals, using self-harm imputation to overcome the known limitations of this outcome being underrecorded within US electronic health care records. METHODS The IBM MarketScan administrative claims database was used to compare self-harm risk in patients with BD following 65 drug regimens and drug-free periods. Probable but uncoded self-harm events were imputed via machine learning, with different probability thresholds examined in a sensitivity analysis. Comparators included lithium, mood-stabilizing anticonvulsants (MSAs), second-generation antipsychotics (SGAs), first-generation antipsychotics (FGAs), and five classes of antidepressants. Cox regression models with time-varying covariates were built for individual treatment regimens and for any pharmacotherapy with or without psychosocial interventions ("psychotherapy"). RESULTS Among 529,359 patients, 1.66% (n=8813 events) had imputed and/or coded self-harm following the exposure of interest. A higher self-harm risk was observed during adolescence. After multiple testing adjustment (P≤.012), the following six regimens had higher risk of self-harm than lithium: tri/tetracyclic antidepressants + SGA, FGA + MSA, FGA, serotonin-norepinephrine reuptake inhibitor (SNRI) + SGA, lithium + MSA, and lithium + SGA (hazard ratios [HRs] 1.44-2.29), and the following nine had lower risk: lamotrigine, valproate, risperidone, aripiprazole, SNRI, selective serotonin reuptake inhibitor (SSRI), "no drug," bupropion, and bupropion + SSRI (HRs 0.28-0.74). Psychotherapy alone (without medication) had a lower self-harm risk than no treatment (HR 0.56, 95% CI 0.52-0.60; P=8.76×10-58). The sensitivity analysis showed that the direction of drug-outcome associations did not change as a function of the self-harm probability threshold. CONCLUSIONS Our data support evidence on the effectiveness of antidepressants, MSAs, and psychotherapy for self-harm prevention in BD. TRIAL REGISTRATION ClinicalTrials.gov NCT02893371; https://clinicaltrials.gov/ct2/show/NCT02893371.
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Affiliation(s)
- Anastasiya Nestsiarovich
- Center for Global Health, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, United States
| | - Praveen Kumar
- Department of Computer Science, The University of New Mexico, Albuquerque, NM, United States
| | - Nicolas Raymond Lauve
- Department of Computer Science, The University of New Mexico, Albuquerque, NM, United States
| | | | | | | | - Yiliang Zhu
- Division of Epidemiology, Biostatistics, and Preventive Medicine, Department of Internal Medicine, The University of New Mexico Health Sciences Center, Albuquerque, NM, United States
| | - Stuart James Nelson
- Biomedical Informatics Center, George Washington University, Washington, DC, DC, United States
| | - Annette S Crisanti
- Department of Psychiatry & Behavioral Sciences, University of New Mexico Health Sciences Center, Albuquerque, NM, United States
| | - Berit Kerner
- Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, United States
| | - Mauricio Tohen
- Department of Psychiatry & Behavioral Sciences, University of New Mexico Health Sciences Center, Albuquerque, NM, United States
| | - Douglas J Perkins
- Center for Global Health, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, United States
| | - Christophe Gerard Lambert
- Center for Global Health, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, United States.,Division of Translational Informatics, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, United States
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Nestsiarovich A, Kerner B, Mazurie AJ, Cannon DC, Hurwitz NG, Zhu Y, Nelson SJ, Oprea TI, Crisanti AS, Tohen M, Perkins DJ, Lambert CG. Diabetes mellitus risk for 102 drugs and drug combinations used in patients with bipolar disorder. Psychoneuroendocrinology 2020; 112:104511. [PMID: 31744781 DOI: 10.1016/j.psyneuen.2019.104511] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 08/28/2019] [Accepted: 11/07/2019] [Indexed: 12/18/2022]
Abstract
OBJECTIVE To compare the largest set of bipolar disorder pharmacotherapies to date (102 drugs and drug combinations) for risk of diabetes mellitus (DM). METHODS The IBM MarketScan® database was used to retrospectively analyze data on 565,253 adults with bipolar disorder without prior glucose metabolism-related diagnoses. The pharmacotherapies compared were lithium, mood-stabilizing anticonvulsants, antipsychotics, and antidepressants (monotherapy and multi-class polypharmacy). Cox regression modeling included fixed pre-treatment covariates and time-varying drug exposure covariates to estimate the hazard ratio (HR) of each treatment versus "No drug". RESULTS The annual incidence of new-onset diabetes during the exposure period was 3.09 % (22,951 patients). The HR of drug-dependent DM ranged from 0.79 to 2.37. One-third of the studied pharmacotherapies, including most of the antipsychotic-containing regimens, had a significantly higher risk of DM compared to "No drug". A significantly lower DM risk was associated with lithium, lamotrigine, oxcarbazepine and bupropion monotherapies, selective serotonin reuptake inhibitors (SSRI) mono-class therapy and several drug combinations containing bupropion and an SSRI. As additional drugs were combined in more complex polypharmacy, higher HRs were consistently observed. CONCLUSIONS There is an increased risk of diabetes mellitus associated with antipsychotic and psychotropic polypharmacy use in bipolar disorder. The evidence of a lower-than-baseline risk of DM with lamotrigine, oxcarbazepine, lithium, and bupropion monotherapy should be further investigated.
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Affiliation(s)
- Anastasiya Nestsiarovich
- Center for Global Health, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA
| | - Berit Kerner
- Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, CA, USA
| | | | | | | | - Yiliang Zhu
- Division of Epidemiology, Biostatistics, and Preventive Medicine, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA
| | - Stuart J Nelson
- University of New Mexico Health Sciences Library and Informatics Center, Albuquerque, NM, USA; Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA
| | - Tudor I Oprea
- Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA
| | - Annette S Crisanti
- Department of Psychiatry & Behavioral Sciences, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Mauricio Tohen
- Department of Psychiatry & Behavioral Sciences, University of New Mexico Health Sciences Center, Albuquerque, New Mexico, USA
| | - Douglas J Perkins
- Center for Global Health, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA
| | - Christophe G Lambert
- Center for Global Health, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA; Translational Informatics Division, Department of Internal Medicine, University of New Mexico Health Sciences Center, Albuquerque, NM, USA.
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Del Giudice M. Invisible Designers: Brain Evolution Through the Lens of Parasite Manipulation. QUARTERLY REVIEW OF BIOLOGY 2019. [DOI: 10.1086/705038] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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