New findings in pharmacogenetics of schizophrenia

Zai, Clement C.; Tiwari, Arun; Zai, Gwyneth; Maes, Miriam S.; Kennedy, James L.

doi:10.1097/yco.0000000000000417

Cited by 39 publications

(34 citation statements)

References 182 publications

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“…HLA-C*06:02-negative patients respond better to adalimumab than ustekinumab [36,37]. Other examples of NCDs which involve the use of GB for diagnosis or choice of therapy include cardiovascular disorders, diabetes, Parkinson's disease, age-related macular degeneration, inflammatory bowel diseases, autism spectrum disorder, and schizophrenia (Table 1) [38][39][40][41][42][43][44]. These examples are set to increase in the coming years according to the discovery of rare alleles [45].…”

Section: Genomic Biomarkers In Ncdsmentioning

confidence: 99%

Precision Medicine in Non-Communicable Diseases

et al. 2020

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The increase in life expectancy during the 20th century ranks as one of society’s greatest achievements, with massive growth in the numbers and proportion of the elderly, virtually occurring in every country of the world. The burden of chronic diseases is one of the main consequences of this phenomenon, severely hampering the quality of life of elderly people and challenging the efficiency and sustainability of healthcare systems. Non-communicable diseases (NCDs) are considered a global emergency responsible for over 70% of deaths worldwide. NCDs are also the basis for complex and multifactorial diseases such as hypertension, diabetes, and obesity. The epidemics of NCDs are a consequence of a complex interaction between health, economic growth, and development. This interaction includes the individual genome, the microbiome, the metabolome, the immune status, and environmental factors such as nutritional and chemical exposure. To counteract NCDs, it is therefore essential to develop an innovative, personalized, preventative, early care model through the integration of different molecular profiles of individuals to identify both the critical biomarkers of NCD susceptibility and to discover novel therapeutic targets.

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Section: Genomic Biomarkers In Ncdsmentioning

confidence: 99%

Precision Medicine in Non-Communicable Diseases

et al. 2020

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“…We designed synthetic probes for NGS, targeting genes associated with dementia, SCZ, and several pharmacogenetic targets. The selection of genes was based on a literature search for published works reporting an effect of common variations or rare variants in SCZ, dementia or drug response to different antipsychotics or antidementia drugs 6,7,[26][27][28][29][30][31][32][33][34][35][36] ; a list of the captured genes is reported in Supplementary Table 1. Gene capture was performed using the Haloplex target enrichment system (Agilent Technologies, USA) with 1.51Mb with 40754 amplicons.…”

Section: Targeted Ngsmentioning

confidence: 99%

Exploratory Analysis of Rare and Novel Variants in Mexican Patients Diagnosed with Schizophrenia and Dementia

Martínez‐Magaña

Genis‐Mendoza

González-Covarrubias

et al. 2019

RIC

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Background: Schizophrenia (SCZ) and dementia, often related, are two of the most common neuropsychiatric diseases; epidemiological studies have shown that SCZ patients present a 2-fold increased risk for dementia compared to non-schizophrenic individuals. We explored the presence of rare and novel damaging gene variants in patients diagnosed with late-onset dementia of Alzheimer's type (DAT) or SCZ. Methods: We included 7 DAT and 12 SCZ patients and performed high-depth targeted sequencing of 184 genes. Results: We found novel and rare damaging variants in 18 genes in these Mexican patients. Carriers of these variants showed extreme phenotypes, including, treatment-resistant SCZ or cognitive decline. Furthermore, we found a variation on ABCC1 as a possible link between psychosis and cognitive impairment. Discussion: As an exploratory analysis, we report some interesting variations that should be corroborated in larger sample size studies.

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“…The large variability can be attributed to a variety of complex factors, in which genetic factors may play a dominant role. Numerous studies on pharmacogenomics have been conducted to elucidate gene variants related to antipsychoticinduced weight gain or metabolic disturbances (Lett et al, 2011;Zhang et al, 2016;Zai et al, 2018). A meta-analysis has revealed that the genes of pharmacodynamic targets of antipsychotics like HTR2C, DRD2, ADRA2A and genes implicated in obesity such as MC4R, GNB3, FTO, LEP, LEPR, BDNF, and INSIG2 seem to be consistently relevant to antipsychotic-induced weight gain (Zhang et al, 2016).…”

Section: Introductionmentioning

confidence: 99%