1
|
Liu H, Bing P, Zhang M, Tian G, Ma J, Li H, Bao M, He K, He J, He B, Yang J. MNNMDA: Predicting human microbe-disease association via a method to minimize matrix nuclear norm. Comput Struct Biotechnol J 2023; 21:1414-1423. [PMID: 36824227 PMCID: PMC9941872 DOI: 10.1016/j.csbj.2022.12.053] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Revised: 12/29/2022] [Accepted: 12/30/2022] [Indexed: 01/03/2023] Open
Abstract
Identifying the potential associations between microbes and diseases is the first step for revealing the pathological mechanisms of microbe-associated diseases. However, traditional culture-based microbial experiments are expensive and time-consuming. Thus, it is critical to prioritize disease-associated microbes by computational methods for further experimental validation. In this study, we proposed a novel method called MNNMDA, to predict microbe-disease associations (MDAs) by applying a Matrix Nuclear Norm method into known microbe and disease data. Specifically, we first calculated Gaussian interaction profile kernel similarity and functional similarity for diseases and microbes. Then we constructed a heterogeneous information network by combining the integrated disease similarity network, the integrated microbe similarity network and the known microbe-disease bipartite network. Finally, we formulated the microbe-disease association prediction problem as a low-rank matrix completion problem, which was solved by minimizing the nuclear norm of a matrix with a few regularization terms. We tested the performances of MNNMDA in three datasets including HMDAD, Disbiome, and Combined Data with small, medium and large sizes respectively. We also compared MNNMDA with 5 state-of-the-art methods including KATZHMDA, LRLSHMDA, NTSHMDA, GATMDA, and KGNMDA, respectively. MNNMDA achieved area under the ROC curves (AUROC) of 0.9536 and 0.9364 respectively on HDMAD and Disbiome, better than the AUCs of compared methods under the 5-fold cross-validation for all microbe-disease associations. It also obtained a relatively good performance with AUROC 0.8858 in the combined data. In addition, MNNMDA was also better than other methods in area under precision and recall curve (AUPR) under the 5-fold cross-validation for all associations, and in both AUROC and AUPR under the 5-fold cross-validation for diseases and the 5-fold cross-validation for microbes. Finally, the case studies on colon cancer and inflammatory bowel disease (IBD) also validated the effectiveness of MNNMDA. In conclusion, MNNMDA is an effective method in predicting microbe-disease associations. Availability The codes and data for this paper are freely available at Github https://github.com/Haiyan-Liu666/MNNMDA.
Collapse
Affiliation(s)
- Haiyan Liu
- Academician Workstation, Changsha Medical University, Changsha 410219, PR China,College of Information Engineering, Changsha Medical University, Changsha 410219, PR China,Hunan Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, Changsha Medical University, Changsha 410219, PR China
| | - Pingping Bing
- Academician Workstation, Changsha Medical University, Changsha 410219, PR China
| | - Meijun Zhang
- Geneis Beijing Co., Ltd., Beijing 100102, PR China
| | - Geng Tian
- Geneis Beijing Co., Ltd., Beijing 100102, PR China
| | - Jun Ma
- College of Information Engineering, Changsha Medical University, Changsha 410219, PR China
| | - Haigang Li
- Academician Workstation, Changsha Medical University, Changsha 410219, PR China,Hunan Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, Changsha Medical University, Changsha 410219, PR China,School of pharmacy, Changsha Medical University, Changsha 410219, PR China
| | - Meihua Bao
- Academician Workstation, Changsha Medical University, Changsha 410219, PR China,Hunan Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, Changsha Medical University, Changsha 410219, PR China,School of pharmacy, Changsha Medical University, Changsha 410219, PR China
| | - Kunhui He
- Academician Workstation, Changsha Medical University, Changsha 410219, PR China,Hunan Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, Changsha Medical University, Changsha 410219, PR China,School of pharmacy, Changsha Medical University, Changsha 410219, PR China
| | - Jianjun He
- Academician Workstation, Changsha Medical University, Changsha 410219, PR China,Hunan Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, Changsha Medical University, Changsha 410219, PR China,School of pharmacy, Changsha Medical University, Changsha 410219, PR China,Corresponding authors at: Academician Workstation, Changsha Medical University, Changsha 410219, PR China.
| | - Binsheng He
- Academician Workstation, Changsha Medical University, Changsha 410219, PR China,Hunan Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, Changsha Medical University, Changsha 410219, PR China,School of pharmacy, Changsha Medical University, Changsha 410219, PR China,Corresponding authors at: Academician Workstation, Changsha Medical University, Changsha 410219, PR China.
| | - Jialiang Yang
- Academician Workstation, Changsha Medical University, Changsha 410219, PR China,Hunan Key Laboratory of the Research and Development of Novel Pharmaceutical Preparations, Changsha Medical University, Changsha 410219, PR China,Geneis Beijing Co., Ltd., Beijing 100102, PR China,School of pharmacy, Changsha Medical University, Changsha 410219, PR China,Corresponding authors at: Academician Workstation, Changsha Medical University, Changsha 410219, PR China.
| |
Collapse
|
2
|
Moore JP, Mauler DJ, Narang GL, Stern KL, Humphreys MR, Keddis MT. Etiology, urine metabolic risk factors, and urine oxalate patterns in patients with significant hyperoxaluria and recurrent nephrolithiasis. Int Urol Nephrol 2022; 54:2819-2825. [PMID: 35917078 DOI: 10.1007/s11255-022-03311-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 07/17/2022] [Indexed: 11/25/2022]
Abstract
PURPOSE American Urology Association guidelines recommend genetic testing for patients with recurrent stones and urine oxalate > 75 mg/day. The goal of this study was to examine the treatment of patients in this category in a large multidisciplinary adult stone clinic. METHODS Patients were evaluated from a single institution between 2006 and 2019. Those with at least one level of urinary oxalate excretion (uOx) above 75 mg/day were identified. A chart review identified enteric risk factors and genetic testing results. Patients without an identifiable enteric cause were considered idiopathic. RESULTS A total of 4229 separate 24-h urine collections in 1302 patients were reviewed. At least one measurement of uOx above 75 mg/day was found in 103 (7.9%) patients. Enteric hyperoxaluria (EH) was seen in 28 (27%) and idiopathic hyperoxaluria (IH) in 76 (74%). 20 (71%) patients in the EH group had undergone gastric bypass. The median uOx was significantly higher level in the EH group (121.0 vs. 93.0 mg/day). For the entire cohort, there was a drop in uOx (- 33.8 mg/day) with medical and dietary therapy after a follow-up of 46.6 months. The final oxalate was higher in EH (88.9 vs. 60.1 mg/day). Only one patient had referral for genetic testing and was found to have primary hyperoxaluria type 2. CONCLUSIONS The most common cause of significant hyperoxaluria in patients with recurrent nephrolithiasis remains idiopathic. Patients with IH have more significant improvement in uOx compared to EH; however, both groups had hyperoxaluria at last follow-up. Rate of genetic testing is low despite guideline recommendations.
Collapse
Affiliation(s)
- Jonathan P Moore
- Department of Urologic Surgery, UC Davis Medical Center, Sacramento, CA, USA
| | - David J Mauler
- Department of Urology, Mayo Clinic Arizona, Phoenix, AZ, USA
| | - Gopal L Narang
- Department of Urology, University of North Carolina, Chapel Hill, NC, USA
| | - Karen L Stern
- Department of Urology, Mayo Clinic Arizona, Phoenix, AZ, USA.
| | | | - Mira T Keddis
- Department of Nephrology, Mayo Clinic Arizona, Phoenix, AZ, USA
| |
Collapse
|