Computational and Structural Biotechnology Journal (Jan 2021)
GPCards: An integrated database of genotype–phenotype correlations in human genetic diseases
- Bin Li,
- Zheng Wang,
- Qian Chen,
- Kuokuo Li,
- Xiaomeng Wang,
- Yijing Wang,
- Qian Zeng,
- Ying Han,
- Bin Lu,
- Yuwen Zhao,
- Rui Zhang,
- Li Jiang,
- Hongxu Pan,
- Tengfei Luo,
- Yi Zhang,
- Zhenghuan Fang,
- Xuewen Xiao,
- Xun Zhou,
- Rui Wang,
- Lu Zhou,
- Yige Wang,
- Zhenhua Yuan,
- Lu Xia,
- Jifeng Guo,
- Beisha Tang,
- Kun Xia,
- Guihu Zhao,
- Jinchen Li
Affiliations
- Bin Li
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China; Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China; Mobile Health Ministry of Education - China Mobile Joint Laboratory, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Zheng Wang
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Qian Chen
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Kuokuo Li
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
- Xiaomeng Wang
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
- Yijing Wang
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
- Qian Zeng
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Ying Han
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
- Bin Lu
- Department of Pathogen Biology, School of Basic Medical Sciences, Central South University, Changsha, Hunan 410008, China
- Yuwen Zhao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Rui Zhang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Li Jiang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Hongxu Pan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Tengfei Luo
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
- Yi Zhang
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Zhenghuan Fang
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
- Xuewen Xiao
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Xun Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Rui Wang
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
- Lu Zhou
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Yige Wang
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Zhenhua Yuan
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Lu Xia
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
- Jifeng Guo
- Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Beisha Tang
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China; Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China
- Kun Xia
- Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China
- Guihu Zhao
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China; Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China; Corresponding authors at: National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.
- Jinchen Li
- National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China; Center for Medical Genetics & Hunan Key Laboratory, School of Life Sciences, Central South University, Changsha Hunan 410008, China; Department of Neurology, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China; Corresponding authors at: National Clinical Research Center for Geriatric Disorders, Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan 410008, China.
- Journal volume & issue
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Vol. 19
pp. 1603 – 1611
Abstract
Genotype–phenotype correlations are the basis of precision medicine of human genetic diseases. However, it remains a challenge for clinicians and researchers to conveniently access detailed individual-level clinical phenotypic features of patients with various genetic variants. To address this urgent need, we manually searched for genetic studies in PubMed and catalogued 8,309 genetic variants in 1,288 genes from 17,738 patients with detailed clinical phenotypic features from 1,855 publications. Based on genotype–phenotype correlations in this dataset, we developed an user-friendly online database called GPCards (http://genemed.tech/gpcards/), which not only provided the association between genetic diseases and disease genes, but also the prevalence of various clinical phenotypes related to disease genes and the patient-level mapping between these clinical phenotypes and genetic variants. To accelerate the interpretation of genetic variants, we integrated 62 well-known variant-level and gene-level genomic data sources, including functional predictions, allele frequencies in different populations, and disease-related information. Furthermore, GPCards enables automatic analyses of users’ own genetic data, comprehensive annotation, prioritization of candidate functional variants, and identification of genotype–phenotype correlations using custom parameters. In conclusion, GPCards is expected to accelerate the interpretation of genotype–phenotype correlations, subtype classification, and candidate gene prioritisation in human genetic diseases.
