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Wang KW, Yuan YX, Zhu B, Zhang Y, Wei YF, Meng FS, Zhang S, Wang JX, Zhou JY. X chromosome-wide association study of quantitative biomarkers from the Alzheimer's Disease Neuroimaging Initiative study. Front Aging Neurosci 2023; 15:1277731. [PMID: 38035272 PMCID: PMC10682795 DOI: 10.3389/fnagi.2023.1277731] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Accepted: 10/20/2023] [Indexed: 12/02/2023] Open
Abstract
Introduction Alzheimer's disease (AD) is a complex neurodegenerative disease with high heritability. Compared to autosomes, a higher proportion of disorder-associated genes on X chromosome are expressed in the brain. However, only a few studies focused on the identification of the susceptibility loci for AD on X chromosome. Methods Using the data from the Alzheimer's Disease Neuroimaging Initiative Study, we conducted an X chromosome-wide association study between 16 AD quantitative biomarkers and 19,692 single nucleotide polymorphisms (SNPs) based on both the cross-sectional and longitudinal studies. Results We identified 15 SNPs statistically significantly associated with different quantitative biomarkers of the AD. For the cross-sectional study, six SNPs (rs5927116, rs4596772, rs5929538, rs2213488, rs5920524, and rs5945306) are located in or near to six genes DMD, TBX22, LOC101928437, TENM1, SPANXN1, and ZFP92, which have been reported to be associated with schizophrenia or neuropsychiatric diseases in literature. For the longitudinal study, four SNPs (rs4829868, rs5931111, rs6540385, and rs763320) are included in or near to two genes RAC1P4 and AFF2, which have been demonstrated to be associated with brain development or intellectual disability in literature, while the functional annotations of other five novel SNPs (rs12157031, rs428303, rs5953487, rs10284107, and rs5955016) have not been found. Discussion 15 SNPs were found statistically significantly associated with the quantitative biomarkers of the AD. Follow-up study in molecular genetics is needed to verify whether they are indeed related to AD. The findings in this article expand our understanding of the role of the X chromosome in exploring disease susceptibility, introduce new insights into the molecular genetics behind the AD, and may provide a mechanistic clue to further AD-related studies.
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Affiliation(s)
- Kai-Wen Wang
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Yu-Xin Yuan
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Bin Zhu
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Yi Zhang
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Yi-Fang Wei
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Fan-Shuo Meng
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Shun Zhang
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Jing-Xuan Wang
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
| | - Ji-Yuan Zhou
- State Key Laboratory of Organ Failure Research, Ministry of Education, Guangdong Provincial Key Laboratory of Tropical Disease Research, Department of Biostatistics, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
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Yang ZY, Liu W, Yuan YX, Kong YF, Zhao PZ, Fung WK, Zhou JY. Robust association tests for quantitative traits on the X chromosome. Heredity (Edinb) 2022; 129:244-256. [PMID: 36085362 PMCID: PMC9519943 DOI: 10.1038/s41437-022-00560-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2021] [Revised: 08/24/2022] [Accepted: 08/24/2022] [Indexed: 11/09/2022] Open
Abstract
The genome-wide association study is an elementary tool to assess the genetic contribution to complex human traits. However, such association tests are mainly proposed for autosomes, and less attention has been given to methods for identifying loci on the X chromosome due to their distinct biological features. In addition, the existing association tests for quantitative traits on the X chromosome either fail to incorporate the information of males or only detect variance heterogeneity. Therefore, we propose four novel methods, which are denoted as QXcat, QZmax, QMVXcat and QMVZmax. When using these methods, it is assumed that the risk alleles for females and males are the same and that the locus being studied satisfies the generalized genetic model for females. The first two methods are based on comparing the means of the trait value across different genotypes, while the latter two methods test for the difference of both means and variances. All four methods effectively incorporate the information of X chromosome inactivation. Simulation studies demonstrate that the proposed methods control the type I error rates well. Under the simulated scenarios, the proposed methods are generally more powerful than the existing methods. We also apply our proposed methods to data from the Minnesota Center for Twin and Family Research and find 10 single nucleotide polymorphisms that are statistically significantly associated with at least two traits at the significance level of 1 × 10-3.
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Affiliation(s)
- Zi-Ying Yang
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Wei Liu
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Yu-Xin Yuan
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China
| | - Yi-Fan Kong
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Pei-Zhen Zhao
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Wing Kam Fung
- Department of Statistics and Actuarial Science, The University of Hong Kong, Hong Kong, China.
| | - Ji-Yuan Zhou
- Department of Biostatistics, State Key Laboratory of Organ Failure Research, Ministry of Education, and Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China.
- Guangdong-Hong Kong-Macao Joint Laboratory for Contaminants Exposure and Health, Guangzhou, China.
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Wang YC, Wu Y, Choi J, Allington G, Zhao S, Khanfar M, Yang K, Fu PY, Wrubel M, Yu X, Mekbib KY, Ocken J, Smith H, Shohfi J, Kahle KT, Lu Q, Jin SC. Computational Genomics in the Era of Precision Medicine: Applications to Variant Analysis and Gene Therapy. J Pers Med 2022; 12:175. [PMID: 35207663 PMCID: PMC8878256 DOI: 10.3390/jpm12020175] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 01/18/2022] [Accepted: 01/24/2022] [Indexed: 02/04/2023] Open
Abstract
Rapid methodological advances in statistical and computational genomics have enabled researchers to better identify and interpret both rare and common variants responsible for complex human diseases. As we continue to see an expansion of these advances in the field, it is now imperative for researchers to understand the resources and methodologies available for various data types and study designs. In this review, we provide an overview of recent methods for identifying rare and common variants and understanding their roles in disease etiology. Additionally, we discuss the strategy, challenge, and promise of gene therapy. As computational and statistical approaches continue to improve, we will have an opportunity to translate human genetic findings into personalized health care.
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Affiliation(s)
- Yung-Chun Wang
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
| | - Yuchang Wu
- Department of Biostatistics & Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA;
| | - Julie Choi
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
| | - Garrett Allington
- Department of Pathology, Yale School of Medicine, New Haven, CT 06510, USA;
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA; (H.S.); (K.T.K.)
| | - Shujuan Zhao
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
| | - Mariam Khanfar
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
| | - Kuangying Yang
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
| | - Po-Ying Fu
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
| | - Max Wrubel
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
| | - Xiaobing Yu
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
- Department of Computer Science & Engineering, Washington University, St. Louis, MO 63130, USA
| | - Kedous Y. Mekbib
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT 06510, USA; (K.Y.M.); (J.O.); (J.S.)
| | - Jack Ocken
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT 06510, USA; (K.Y.M.); (J.O.); (J.S.)
| | - Hannah Smith
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA; (H.S.); (K.T.K.)
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT 06510, USA; (K.Y.M.); (J.O.); (J.S.)
| | - John Shohfi
- Department of Neurosurgery, Yale University School of Medicine, New Haven, CT 06510, USA; (K.Y.M.); (J.O.); (J.S.)
| | - Kristopher T. Kahle
- Department of Neurosurgery, Massachusetts General Hospital, Boston, MA 02114, USA; (H.S.); (K.T.K.)
- Division of Genetics and Genomics, Boston Children’s Hospital, Boston, MA 02115, USA
- Departments of Pediatrics and Neurology, Harvard Medical School, Boston, MA 02115, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Qiongshi Lu
- Department of Biostatistics & Medical Informatics, University of Wisconsin-Madison, Madison, WI 53706, USA;
| | - Sheng Chih Jin
- Department of Genetics, School of Medicine, Washington University, St. Louis, MO 63110, USA; (Y.-C.W.); (J.C.); (S.Z.); (M.K.); (K.Y.); (P.-Y.F.); (M.W.); (X.Y.)
- Department of Pediatrics, School of Medicine, Washington University, St. Louis, MO 63110, USA
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