Lalagkas Panagiotis N, Melamed Rachel D
University of Massachusetts Lowell.
Res Sq. 2024 Apr 19:rs.3.rs-4250176. doi: 10.21203/rs.3.rs-4250176/v1.
Drugs targeting disease causal genes are more likely to succeed for that disease. However, complex disease causal genes are not always clear. In contrast, Mendelian disease causal genes are well-known and druggable. Here, we seek an approach to exploit the well characterized biology of Mendelian diseases for complex disease drug discovery, by exploiting evidence of pathogenic processes shared between monogenic and complex disease. One way to find shared disease etiology is clinical association: some Mendelian diseases are known to predispose patients to specific complex diseases (comorbidity). Previous studies link this comorbidity to pleiotropic effects of the Mendelian disease causal genes on the complex disease.
In previous work studying incidence of 90 Mendelian and 65 complex diseases, we found 2,908 pairs of clinically associated (comorbid) diseases. Using this clinical signal, we can match each complex disease to a set of Mendelian disease causal genes. We hypothesize that the drugs targeting these genes are potential candidate drugs for the complex disease. We evaluate our candidate drugs using information of current drug indications or investigations.
Our analysis shows that the candidate drugs are enriched among currently investigated or indicated drugs for the relevant complex diseases (odds ratio = 1.84, p = 5.98e-22). Additionally, the candidate drugs are more likely to be in advanced stages of the drug development pipeline. We also present an approach to prioritize Mendelian diseases with particular promise for drug repurposing. Finally, we find that the combination of comorbidity and genetic similarity for a Mendelian disease and cancer pair leads to recommendation of candidate drugs that are enriched for those investigated or indicated.
Our findings suggest a novel way to take advantage of the rich knowledge about Mendelian disease biology to improve treatment of complex diseases.
针对疾病致病基因的药物在治疗该疾病时更有可能取得成功。然而,复杂疾病的致病基因并不总是清晰明确。相比之下,孟德尔疾病的致病基因是已知的且可成药。在此,我们寻求一种方法,通过利用单基因疾病和复杂疾病之间共享的致病过程证据,来利用孟德尔疾病已充分表征的生物学特性进行复杂疾病药物研发。找到共享疾病病因的一种方法是临床关联:已知一些孟德尔疾病会使患者易患特定的复杂疾病(共病)。先前的研究将这种共病现象与孟德尔疾病致病基因对复杂疾病的多效性作用联系起来。
在先前一项研究90种孟德尔疾病和65种复杂疾病发病率的工作中,我们发现了2908对临床相关(共病)疾病。利用这一临床信号,我们可以将每种复杂疾病与一组孟德尔疾病致病基因进行匹配。我们假设针对这些基因的药物是复杂疾病的潜在候选药物。我们利用当前药物适应症或研究信息来评估我们的候选药物。
我们的分析表明,候选药物在目前针对相关复杂疾病进行研究或有适应症的药物中富集(优势比 = 1.84,p = 5.98×10⁻²²)。此外,候选药物更有可能处于药物研发管道的后期阶段。我们还提出了一种方法,对在药物重新利用方面特别有前景的孟德尔疾病进行优先级排序。最后,我们发现孟德尔疾病与癌症配对时的共病和遗传相似性组合会导致推荐出在那些已研究或有适应症的药物中富集的候选药物。
我们的研究结果表明了一种利用关于孟德尔疾病生物学的丰富知识来改善复杂疾病治疗的新方法。