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      Pharmacogenomics Factors Influencing the Effect of Risperidone on Prolactin Levels in Thai Pediatric Patients With Autism Spectrum Disorder

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          Abstract

          We investigated the association between genetic variations in pharmacodynamic genes and risperidone-induced increased prolactin levels in children and adolescents with autism spectrum disorder (ASD). In a retrospective study, variants of pharmacodynamic genes were analyzed in 124 ASD patients treated with a risperidone regimen for at least 3 months. To simplify genotype interpretation, we created an algorithm to calculate the dopamine D2 receptor ( DRD2) gene genetic risk score. There was no relationship between prolactin levels and single SNPs. However, the H1/H3 diplotype (A2/A2-Cin/Cin-A/G) of DRD2/ankyrin repeat and kinase domain containing 1 ( ANKK1) Taq1A, DRD2 -141C indel, and DRD2 -141A>G, which had a genetic risk score of 5.5, was associated with the highest median prolactin levels (23 ng/ml). As the dose-corrected plasma levels of risperidone, 9-OH-risperidone, and the active moiety increased, prolactin levels in patients carrying the H1/H3 diplotype were significantly higher than those of the other diplotypes. DRD2 diplotypes showed significantly high prolactin levels as plasma risperidone levels increased. Lower levels of prolactin were detected in patients who responded to risperidone. This is the first system for describing DRD2 haplotypes using genetic risk scores based on their protein expression. Clinicians should consider using pharmacogenetic-based decision-making in clinical practice to prevent prolactin increase.

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          Most cited references63

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          Accounting for decay of linkage disequilibrium in haplotype inference and missing-data imputation.

          Although many algorithms exist for estimating haplotypes from genotype data, none of them take full account of both the decay of linkage disequilibrium (LD) with distance and the order and spacing of genotyped markers. Here, we describe an algorithm that does take these factors into account, using a flexible model for the decay of LD with distance that can handle both "blocklike" and "nonblocklike" patterns of LD. We compare the accuracy of this approach with a range of other available algorithms in three ways: for reconstruction of randomly paired, molecularly determined male X chromosome haplotypes; for reconstruction of haplotypes obtained from trios in an autosomal region; and for estimation of missing genotypes in 50 autosomal genes that have been completely resequenced in 24 African Americans and 23 individuals of European descent. For the autosomal data sets, our new approach clearly outperforms the best available methods, whereas its accuracy in inferring the X chromosome haplotypes is only slightly superior. For estimation of missing genotypes, our method performed slightly better when the two subsamples were combined than when they were analyzed separately, which illustrates its robustness to population stratification. Our method is implemented in the software package PHASE (v2.1.1), available from the Stephens Lab Web site.
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            Polymorphisms in the dopamine D2 receptor gene and their relationships to striatal dopamine receptor density of healthy volunteers.

            The density of striatal dopamine D2 receptors has been shown to vary considerably among healthy subjects. This variability might be due to genetic or environmental factors. In the present analysis we searched for relationships between dopamine D2 receptor gene (DRD2) polymorphisms and striatal dopamine D2 receptor density in vivo, as measured by positron emission tomography and [11C]raclopride in 56 healthy subjects. There was a significant association between presence of a putative functional DRD2 promoter allele (-141C Del) and high striatal dopamine receptor density (t= 2.32, P= 0.02). In agreement with some previous studies the presence of the DRD2 TaqIA1 allele was associated with measures of low dopamine receptor density (t=2.58, P=0.01). Also the DRD2 TaqIB1 allele was associated with low dopamine receptor density (t= 2.58, P= 0.01) wheras there was no significant relationship between another common silent intronic DRD2 short tandem repeat polymorphism (STRP) and striatal dopamine D2 receptor density. The results suggest that DRD2 genotypes may participate differentially in the regulation of striatal dopamine D2 receptor density in healthy human subjects. The results should be interpreted with caution because of the limited sample size.
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              The Effects of Novel and Newly Approved Antipsychotics on Serum Prolactin Levels: A Comprehensive Review

              Since the 1970s, clinicians have increasingly become more familiar with hyperprolactinemia (HPRL) as a common adverse effect of antipsychotic medication, which remains the cornerstone of pharmacological treatment for patients with schizophrenia. Although treatment with second-generation antipsychotics (SGAs) as a group is, compared with use of the first-generation antipsychotics, associated with lower prolactin (PRL) plasma levels, the detailed effects on plasma PRL levels for each of these compounds in reports often remain incomplete or inaccurate. Moreover, at this moment, no review has been published about the effect of the newly approved antipsychotics asenapine, iloperidone and lurasidone on PRL levels. The objective of this review is to describe PRL physiology; PRL measurement; diagnosis, causes, consequences and mechanisms of HPRL; incidence figures of (new-onset) HPRL with SGAs and newly approved antipsychotics in adolescent and adult patients; and revisit lingering questions regarding this hormone. A literature search, using the MEDLINE database (1966–December 2013), was conducted to identify relevant publications to report on the state of the art of HPRL and to summarize the available evidence with respect to the propensity of the SGAs and the newly approved antipsychotics to elevate PRL levels. Our review shows that although HPRL usually is defined as a sustained level of PRL above the laboratory upper limit of normal, limit values show some degree of variability in clinical reports, making the interpretation and comparison of data across studies difficult. Moreover, many reports do not provide much or any data detailing the measurement of PRL. Although the highest rates of HPRL are consistently reported in association with amisulpride, risperidone and paliperidone, while aripiprazole and quetiapine have the most favorable profile with respect to this outcome, all SGAs can induce PRL elevations, especially at the beginning of treatment, and have the potential to cause new-onset HPRL. Considering the PRL-elevating propensity of the newly approved antipsychotics, evidence seems to indicate these agents have a PRL profile comparable to that of clozapine (asenapine and iloperidone), ziprasidone and olanzapine (lurasidone). PRL elevations with antipsychotic medication generally are dose dependant. However, antipsychotics having a high potential for PRL elevation (amisulpride, risperidone and paliperidone) can have a profound impact on PRL levels even at relatively low doses, while PRL levels with antipsychotics having a minimal effect on PRL, in most cases, can remain unchanged (quetiapine) or reduce (aripiprazole) over all dosages. Although tolerance and decreases in PRL values after long-term administration of PRL-elevating antipsychotics can occur, the elevations, in most cases, remain above the upper limit of normal. PRL profiles of antipsychotics in children and adolescents seem to be the same as in adults. The hyperprolactinemic effects of antipsychotic medication are mostly correlated with their affinity for dopamine D2 receptors at the level of the anterior pituitary lactotrophs (and probably other neurotransmitter mechanisms) and their blood–brain barrier penetrating capability. Even though antipsychotics are the most common cause of pharmacologically induced HPRL, recent research has shown that HPRL can be pre-existing in a substantial portion of antipsychotic-naïve patients with first-episode psychosis or at-risk mental state.
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                Author and article information

                Contributors
                Journal
                Front Pharmacol
                Front Pharmacol
                Front. Pharmacol.
                Frontiers in Pharmacology
                Frontiers Media S.A.
                1663-9812
                06 October 2021
                2021
                : 12
                : 743494
                Affiliations
                [ 1 ]Division of Pharmacogenomics and Personalized Medicine, Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand
                [ 2 ]Laboratory for Pharmacogenomics, Somdech Phra Debaratana Medical Center (SDMC), Ramathibodi Hospital, Bangkok, Thailand
                [ 3 ]Research and Development Laboratory, Bumrungrad International Hospital, Bangkok, Thailand
                [ 4 ]Division of Clinical Pharmacology, Toxicology and Therapeutic Innovation, Children’s Mercy Kansas City, Kanas City, MO, United States
                [ 5 ]School of Medicine, University of Missouri-Kansas City, Kansas City, MO, United States
                [ 6 ]Unit of PharmacoTherapy, Epidemiology and Economics, Groningen Research Institute of Pharmacy, University of Groningen, Groningen, Netherlands
                [ 7 ]Department of Clinical Pharmacy and Pharmacology, University of Groningen, University Medical Center Groningen, Groningen, Netherlands
                [ 8 ]Department of Mental Health Services, Yuwaprasart Waithayopathum Child and Adolescent Psychiatric Hospital, Ministry of Public Health, Samut Prakan, Thailand
                [ 9 ]Pharmacogenomics and Precision Medicine, Preventive Genomics and Family Check-up Services Center, Bumrungrad International Hospital, Bangkok, Thailand
                Author notes

                Edited by: Elena García-Martín, University of Extremadura, Spain

                Reviewed by: Balram Chowbay, National Cancer Centre Singapore, Singapore

                Julio Duarte, University of Florida, United States

                *Correspondence: Chonlaphat Sukasem, chonlaphat.suk@ 123456mahidol.ac.th

                This article was submitted to Pharmacogenetics and Pharmacogenomics, a section of the journal Frontiers in Pharmacology

                Article
                743494
                10.3389/fphar.2021.743494
                8527557
                34690776
                3b26ba7c-282a-4109-bfff-0156a67b0ee3
                Copyright © 2021 Hongkaew, Gaedigk, Wilffert, Gaedigk, Kittitharaphan, Ngamsamut, Limsila, Puangpetch, Sukprasong and Sukasem.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 18 July 2021
                : 14 September 2021
                Funding
                Funded by: Royal Golden Jubilee (RGJ) Ph.D. Programme , doi 10.13039/501100012309;
                Categories
                Pharmacology
                Original Research

                Pharmacology & Pharmaceutical medicine
                risperidone,prolactin,autism spectrum disorder,genetic risk score,dopamine d2 receptor (drd2)

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