A Modified Approach to Use Escitalopram and Aripiprazole to Treat Bipolar Disorder in a Child with Autism Spectrum Disorder

2020 ◽  
Vol 7 (1) ◽  
pp. 37-41
Author(s):  
Alenezi , Shuliweeh M. ◽  
Suntharalingam , Sinthuja ◽  
Hilton , Tara Nicole
Open Biology ◽  
2018 ◽  
Vol 8 (5) ◽  
pp. 180031 ◽  
Author(s):  
Shani Stern ◽  
Sara Linker ◽  
Krishna C. Vadodaria ◽  
Maria C. Marchetto ◽  
Fred H. Gage

Personalized medicine has become increasingly relevant to many medical fields, promising more efficient drug therapies and earlier intervention. The development of personalized medicine is coupled with the identification of biomarkers and classification algorithms that help predict the responses of different patients to different drugs. In the last 10 years, the Food and Drug Administration (FDA) has approved several genetically pre-screened drugs labelled as pharmacogenomics in the fields of oncology, pulmonary medicine, gastroenterology, haematology, neurology, rheumatology and even psychiatry. Clinicians have long cautioned that what may appear to be similar patient-reported symptoms may actually arise from different biological causes. With growing populations being diagnosed with different psychiatric conditions, it is critical for scientists and clinicians to develop precision medication tailored to individual conditions. Genome-wide association studies have highlighted the complicated nature of psychiatric disorders such as schizophrenia, bipolar disorder, major depression and autism spectrum disorder. Following these studies, association studies are needed to look for genomic markers of responsiveness to available drugs of individual patients within the population of a specific disorder. In addition to GWAS, the advent of new technologies such as brain imaging, cell reprogramming, sequencing and gene editing has given us the opportunity to look for more biomarkers that characterize a therapeutic response to a drug and to use all these biomarkers for determining treatment options. In this review, we discuss studies that were performed to find biomarkers of responsiveness to different available drugs for four brain disorders: bipolar disorder, schizophrenia, major depression and autism spectrum disorder. We provide recommendations for using an integrated method that will use available techniques for a better prediction of the most suitable drug.


2019 ◽  
Vol 60 ◽  
pp. 79-85 ◽  
Author(s):  
Xue Gao ◽  
Ling-Xian Meng ◽  
Kai-Li Ma ◽  
Jie Liang ◽  
Hui Wang ◽  
...  

AbstractBackground:Several observational studies have investigated the association of insomnia with psychiatric disorders. Such studies yielded mixed results, and whether these associations are causal remains unclear. Thus, we aimed to identify the causal relationships between insomnia and five major psychiatric disorders.Methods:The analysis was implemented with six genome-wide association studies; one for insomnia and five for psychiatric disorders (attention-deficit/hyperactivity disorder, autism spectrum disorder, major depressive disorder, schizophrenia, and bipolar disorder). A heterogeneity in dependent instrument (HEIDI) approach was used to remove the pleiotropic instruments, Mendelian randomization (MR)-Egger regression was adopted to test the validity of the screened instruments, and bidirectional generalized summary data-based MR was performed to estimate the causal relationships between insomnia and these major psychiatric disorders.Results:We observed significant causal effects of insomnia on the risk of autism spectrum disorder and bipolar disorder, with odds ratios of 1.739 (95% confidence interval: 1.217–2.486, p = 0.002) and 1.786 (95% confidence interval: 1.396–2.285, p = 4.02 × 10−6), respectively. There was no convincing evidence of reverse causality for insomnia with these two disorders (p = 0.945 and 0.546, respectively). When insomnia was considered as either the exposure or outcome variable, causal estimates for the remaining three psychiatric disorders were not significant.Conclusions:Our results suggest a causal role of insomnia in autism spectrum disorder and bipolar disorder. Future disease models should include insomnia as a factor for these two disorders to develop effective interventions. More detailed mechanism studies may also be inspired by this causal inference.


2016 ◽  
Vol 55 (12) ◽  
pp. 1064-1072.e6 ◽  
Author(s):  
Xenia Borue ◽  
Carla Mazefsky ◽  
Brian T. Rooks ◽  
Michael Strober ◽  
Martin B. Keller ◽  
...  

2020 ◽  
pp. 1-11
Author(s):  
Anna Dunalska ◽  
Marcin Rzeszutek ◽  
Zuzanna Dębowska ◽  
Anita Bryńska

2021 ◽  
Vol 22 (3) ◽  
pp. 320-341
Author(s):  
Massoud Ahmadzadeh Asl ◽  
◽  
Ahmad Shojaee ◽  
Behnam Shariati ◽  
Maryam Rasoolian ◽  
...  

Objective: Patients with severe psychiatric diseases, due to the debilitating and chronic nature of these diseases, requires prolonged care by family and other rated people. In addition to the patient, these diseases affect the caregiver and create high psychological, social, and individual pressure to take care of themselves. This study aims to compare the burden of schizophrenia, Bipolar Disorder (BD) type 1, and Autism Spectrum Disorder (ASD) on the family caregivers in Iran. Materials & Methods: In this descriptive-analytical study, using the non-probability sampling method, 450 family caregivers of patients with schizophrenia, BD type 1, and ASD were selected based on the inclusion criteria. Data collection tools comprised a demographic checklist, short-form Zarit Burden Interview (ZBI-12), and the Depression, Anxiety, and Stress Scale (DASS). The questionnaires were distributed to the patients selected from the Psychiatric Institute of Tehran, Iran Psychiatric Hospital, and Ali Asghar Hospital. The collected data were analyzed using descriptive statistics, ANOVA for evaluating the relationship of demographic factors with the amount and severity of disease burden, and interclass correlation coefficient in SPSS v. 22. Results: The disease burden was higher on caregivers of ASD patients, followed by that of BD type 1 and schizophrenia patients. The highest and lowest hours of care were related to the ASD and schizophrenia groups, respectively. Women made up the majority of family caregivers. The educational level of family caregivers was higher in the BD type 1 group and was lower in the schizophrenia group. Most caregivers in the BD type 1 group were employed, while most of them in the schizophrenia group were housewives. The lowest and highest income levels were related to the family caregivers of ASD and schizophrenia groups, respectively. The highest and lowest hospitalization frequencies were seen in the BD type 1 and ASD groups, respectively. Conclusion: The burden of three diseases on the family caregivers is high. It is recommended that state-run consulting and screening centers be more active in this field. Because of the low-income level of some family caregivers, it is better to plan for more employment of family caregivers with the assistance of governmental and non-governmental organizations. It is better to hold strategic classes for the family caregivers to reduce their disease burden. Different methods to reduce the burden of diseases in caregivers, such as lowering care hours and using respite care and respite recess and dividing tasks between caregivers, using social or daycare services, can reduce their symptoms of depression and anxiety. Their depression and anxiety should be monitored, and pharmacological and non-pharmacological measures should be used for their treatment.


Sign in / Sign up

Export Citation Format

Share Document