Virtual systemic identification of drug targets of obesity candidate genes

在美国，超过40%的成年人肥胖。尽管减少卡路里摄入量和/或增加体力活动 会导致一些人在短期到中期内减肥，但从长远来看，他们会失去疗效。肥胖者 手术是目前治疗肥胖症最持久和最有效的方法，但严重的并发症 已经上报了。治疗肥胖症的药物选择非常有限，而且效果不佳。反- 肥胖药物通常针对调节感觉的中枢神经系统(CNS)通路 饱腹感，或消化、新陈代谢和脂肪生成的外周调节剂，只会导致适度的 效果。开发减肥药物的主要挑战之一是我们的中枢神经系统(即下丘脑， 脑干和边缘系统)，调节食欲和食物摄入量，基本上与 调节情绪、焦虑和行为。已经开发出的几种抑制食欲的中枢神经系统作用药物 因为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)和依科帕姆(多巴胺受体拮抗剂)会引发严重的抑郁和自杀念头； 以及最近FDA批准的MC4R激动剂(Setmelanoide)，用于携带致病突变的个体 沿着瘦素-黑素皮质素途径的POMC、PCSK1或LEPR基因也会在 26%的患者。所有这些都突显了以中枢神经系统为目标抑制食欲的安全问题。然而， 胰升糖素样肽-1受体(GLP1R)激动剂(利拉鲁肽、塞马谷肽、替赛肽、 等)和胰淀素类似物(卡瑞林肽)治疗肥胖症无明显中枢神经系统不良反应 展示了针对我们中枢神经系统的某些部分进行减肥是安全的原则证明，即 主要针对GLP1R激动剂和胰淀素类似物的脑干特定神经回路。它还 表明肥胖基因的一个子集可以安全地在中枢神经系统中被药物靶向。已经有了 在过去的20年里，肥胖和肥胖性状的遗传研究取得了巨大的进展，特别是在我们的领导下 人体测量特征的遗传研究[巨人]联盟，它已经确定了1,700个肥胖基因。 这些努力为确定治疗肥胖症的新药物靶点提供了前所未有的机会，该领域 迫切需要一种范式的转变。通过利用全面的GWA资源来研究肥胖、精神病学特征 和成瘾危险行为，以及大规模生物库中丰富的表象信息，我们建议整合 使用全外显子组测序、转录组范围和 蛋白质组范围的关联分析(AIM 1)，使用以下方法预测靶向肥胖基因的药理效应 药物靶标孟德尔随机化分析和基于基因的全基因组关联分析(目标2)， 并利用CRISPR功能筛选肥胖药物靶基因在IPSC来源神经元中的神经效应 基因组学(目标3)。我们的工作将确定新的减肥药物靶点，既有效又安全地填写 肥胖症药物治疗的严重需求未得到满足。

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.