Virtual systemic identification of drug targets of obesity candidate genes

在美国，超过40%的成年人肥胖。虽然减少热量摄入和/或增加体力活动可以 在一些人中短期内导致体重减轻，但长期来看它们会失去功效。减肥 手术是目前最持久和有效的治疗肥胖的方法， 被举报。用于治疗肥胖症的药物选择非常有限且无效。反 肥胖症药物通常靶向中枢神经系统（CNS）通路，该通路调节肥胖症患者的感觉。 饱腹感和饱胀感，或消化、代谢和脂肪生成的外周调节剂， 方面的影响.开发抗肥胖药物的主要挑战之一是我们的CNS（即，下丘脑， 脑干和边缘系统），调节食欲和食物摄入，基本上与那些 调节情绪、焦虑和行为。已开发的几种抑制食欲的CNS作用药物 对减肥有不良的行为影响。例如，利莫那班（内源性大麻素受体 拮抗剂）和Ecopipam（多巴胺受体拮抗剂）沉淀严重抑郁症和自杀意念; 和最近FDA批准的MC4R激动剂（Setmelanotide）用于携带致病性突变的个体， 沿着瘦素-黑皮质素途径的POMC、PCSK 1或LEPR基因沿着也会引起类似的精神作用， 26%的患者。所有这些都突出了靶向CNS抑制食欲的安全性问题。但 胰高血糖素样肽-1受体（GLP 1R）激动剂（利拉鲁肽，司麦谷肽，替泽帕肽， 等等）。和胰淀素类似物（卡格列林肽）治疗肥胖症而没有明显的CNS相关的副作用 证明了靶向中枢神经系统某些部位减肥是安全的，即， 针对GLP1R激动剂和胰淀素类似物的主要在脑干中的特定神经回路。它还 表明一个肥胖基因的子集可以在CNS中安全地被药物靶向。出现 在过去的20年里，肥胖和肥胖性状的遗传研究取得了巨大进展，特别是在我们的研究中， ANThropometric traits [GIANT]财团的遗传调查，该财团已确定了超过1，700个肥胖基因座。 这些努力为确定治疗肥胖的新药靶点提供了前所未有的机会，这一领域 迫切需要一个范式的转变。通过利用全面的GWAS资源， 和成瘾的风险行为，以及大规模生物库中丰富的表型信息，我们建议整合 使用全外显子组测序、全转录组测序和 全蛋白质组关联分析（Aim 1），预测使用靶向肥胖基因的药理学作用 药物靶点孟德尔随机化分析和基于基因的全表型关联分析（目标2）， 并在iPSC衍生的神经元中筛选肥胖药物靶基因的神经元效应， 基因组学（Aim 3）。我们的工作将确定新的肥胖药物靶点，既有效又安全，以填补 肥胖症药物治疗的关键未满足的需求。

Over 40% of adults are obese in the US. Although reducing caloric intake and/or increasing physical activity can lead to weight loss in the short to medium term in some people, they lose efficacy in the long term. Bariatric surgeries are currently the most durable and effective treatment for obesity but substantial complications have been reported. Pharmaceutical options for treating obesity have been very limited and not efficacious. Anti- obesity medications generally target either central nervous system (CNS) pathways that regulate sensations of satiety and fullness, or peripheral modulators of digestion, metabolism and lipogenesis that result in only modest effects. One of the major challenges in developing anti-obesity medications is that our CNS (i.e., hypothalamus, brainstem, and limbic system), which regulates appetite and food intake, substantially overlaps with those that modulate mood, anxiety and behavior. Several CNS-acting drugs that have been developed to suppress appetite for weight loss have adverse behavioral effects. For example, Rimonabant (endocannabinoid receptor antagonist) and Ecopipam (dopamine receptor antagonist) precipitate severe depression and suicide ideations; and the recent FDA-approved MC4R agonist (Setmelanotide) for individuals carrying pathogenic mutations in POMC, PCSK1 or LEPR genes along the leptin-melanocortin pathway also incurs similar psychiatric effects in 26% patients. All of these highlight safety issues in targeting the CNS for appetite suppression. However, the recent success of glucagon-like peptide-1 receptor (GLP1R) agonists (Liraglutide, Semagglutide, Tirzepatide, etc.) and amylin analogs (Cagrilintide) in treating obesity without apparent CNS-related adverse effects demonstrates the proof of principle that targeting certain parts of our CNS for weight loss can be safe, i.e., targeting specific neural circuits primarily in the brainstem for GLP1R agonists and amylin analogs. It also indicates that a subset of obesity genes can be safely targeted pharmaceutically in the CNS. There has been tremendous progress in genetic studies of obesity and adiposity traits in the past 20 years, especially led by our Genetic Investigation of ANThropometric traits [GIANT] consortium, which has identified >1,700 adiposity loci. These efforts offer an unprecedented opportunity to identify novel drug targets to treat obesity, a field that urgently needs a paradigm shift. By leveraging comprehensive GWAS resources for adiposity, psychiatric traits and addictive risk behaviors, and rich phenome information across large-scale biobanks, we propose to integrate multi-layers of omics to identify obesity genes using whole-exome sequencing, transcriptome-wide and proteome-wide association analyses (Aim 1), predict pharmacological effects upon targeting obesity genes using drug-target Mendelian randomization analyses and gene-based phenome-wide association analyses (Aim 2), and screen neuronal effects of obesity drug target genes in iPSC-derived neurons with CRISPR-based functional genomics (Aim 3). Our work will identify novel obesity drug targets that are both efficacious and safe to fill in the critical unmet need of pharmaceutical therapy of obesity.