Pharmacogenetic Prediction of Antipsychotic Induced Weight Gain

描述（由申请人提供）：NIMH战略目标强调制定个性化治疗策略的重要性，但目前还没有广泛使用的生物标志物来指导临床医生使用第二代抗精神病药（SGAs）。虽然大多数SGAs在治疗精神分裂症阳性症状方面有足够（尽管远非完美）的疗效，但患者、家属和临床医生主要关注的是抗精神病药物引起的体重增加（AIWG）的负担。此外，由于SGAs用于治疗儿童、青少年和成人非精神病性疾病的使用迅速增加，AIWG问题已成为一个日益严重的公共卫生问题。由于以下几个原因，迫切需要确定预测AIWG责任的生物标志物：1)多达五分之一的患者的AIWG程度可能非常严重（约为基线体重的14%）；2) AIWG可导致代谢综合征及相关发病；3) AIWG可能会给患者带来污名化，并导致进一步的心理痛苦；AIWG常导致药物不依从，从而增加复发和再次住院的风险。此外，AIWG的机制尚不清楚，而预测性生物标志物的鉴定可以帮助阐明潜在的药理学，从而帮助开发减轻AIWG负担的新型药物。该研究旨在通过分析6个队列（共n~1200人）的全基因组关联研究（GWAS）数据，确定AIWG的药物遗传生物标志物，这些队列均为前瞻性特征的SGA治疗患者，这些患者要么是抗精神病药物缺乏，要么之前接触过非常有限。为了适当地控制研究特定的变量，如

DESCRIPTION (provided by applicant): The NIMH strategic objectives emphasize the importance of developing strategies for personalized treatment, yet there are currently no widely utilized biomarkers to guide clinicians in the usage of second generation antipsychotic (SGAs). While most SGAs have adequate (though far from perfect) efficacy for the treatment of positive symptoms in schizophrenia, a major concern for patients, families, and clinicians is the burden of antipsychotic-induced weight gain (AIWG). Moreover, the problem of AIWG is a growing public health concern due to the rapidly accelerating use of SGAs for the treatment of non-psychotic conditions in children, adolescents, and adults. Identification of biomarkers predicting AIWG liability are urgently needed for several reasons: 1) the degree of AIWG can be extreme (>14% of baseline weight) in as many as one-fifth of all patients; 2) AIWG can lead to metabolic syndrome and related morbidity; 3) AIWG can be stigmatizing and cause further psychological suffering in patients; and 4) AIWG often leads to medication nonadherence resulting in increased risk of relapse and re-hospitalization. Additionally, the mechanisms underlying AIWG are poorly understood, and the identification of predictive biomarkers can help illuminate the underlying pharmacology, thereby aiding the development of novel medications with reduced AIWG burden. The proposed study aims to identify pharmacogenetic biomarkers for AIWG by analyzing genomewide association study (GWAS) data obtained on 6 cohorts (total n~1200) of prospectively-characterized, SGA- treated patients who are either antipsychotic-na¿ve or have very limited prior exposure. In order to appropriately control for study-specific variables such as study duration, treatment type, and demographics, GWAS (with appropriate covariates) will be performed in each cohort separately, with results combined via meta-analysis. The relationship of genotype to within-subject changes in BMI will be the primary outcome of interest; secondary outcomes will include antipsychotic-induced changes in other metabolic parameters, including triglyceride levels, cholesterol levels, hip and waist circumference, and fat mass, induced by SGA treatment. Note that no funds in the proposed study are used for subject recruitment, data collection, or genotyping. The proposed study builds upon our recent identification of a genetic biomarker that replicably predicts a doubling of AIWG in carriers of the risk genotype (~20 lbs of weight gain in 12 weeks, as compared to ~10 lbs), utilizing a GWAS based on a much smaller sample size (n=139).