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Zhou XY, Liu RK, Zeng CP. Exploring the novel SNPs in neuroticism and birth weight based on GWAS datasets. BMC Med Genomics 2023; 16:167. [PMID: 37454083 PMCID: PMC10349512 DOI: 10.1186/s12920-023-01591-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: 09/08/2022] [Accepted: 06/26/2023] [Indexed: 07/18/2023] Open
Abstract
OBJECTIVES Epidemiological studies have confirmed that low birth weight (BW) is related to neuroticism and they may have a common genetic mechanism based on phenotypic correlation research. We conducted our study on a European population with 159,208 neuroticism and 289,142 birth weight samples. In this study, we aimed to identify new neuroticism single nucleotide polymorphisms (SNPs) and pleiotropic SNPs associated with neuroticism and BW and to provide more theoretical basis for the pathogenesis of the disease. METHODS We estimated the pleiotropic enrichment between neuroticism and BW in two independent Genome-wide association studies (GWAS) when the statistical thresholds were Conditional False Discovery Rate (cFDR) < 0.01 and Conjunctional Conditional False Discovery Rate (ccFDR) < 0.05. We performed gene annotation and gene functional analysis on the selected significant SNPs to determine the biological role of gene function and pathogenesis. Two-sample Mendelian Randomization (TSMR) analysis was performed to explore the causal relationship between the neuroticism and BW. RESULTS The conditional quantile-quantile plots (Q-Q plot) indicated that neuroticism and BW have strong genetic pleiotropy enrichment trends. With the threshold of cFDR < 0.001, we identified 126 SNPs related to neuroticism and 172 SNPs related to BW. With the threshold of ccFDR < 0.05, we identified 62 SNPs related to both neuroticism and BW. Among these SNPs, rs8039305 and rs35755513 have eQTL (expressed quantitative trait loci) and meQTL (methylation quantitative trait loci) effects simultaneously. Through GO enrichment analysis we also found that the two pathways of positive regulation of "mesenchymal cell proliferation" and "DNA-binding transcription factor activity" were significantly enriched in neuroticism and BW. Mendelian randomization analysis results indicate that there is no obvious causal relationship between neuroticism and birth weight. CONCLUSION We found 126 SNPs related to neuroticism, 172 SNPs related to BW and 62 SNPs associated with both neuroticism and BW, which provided a theoretical basis for their genetic mechanism and novel potential targets for treatment/intervention development.
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Affiliation(s)
- Xiao-Ying Zhou
- Department of Endocrinology and Metabolism, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510330, China
- Department of Endocrinology and Metabolism, SSL Central Hospital of Dongguan City, No.1, Xianglong Road, Dongguan, 523326, China
| | - Rui-Ke Liu
- Department of Endocrinology and Metabolism, SSL Central Hospital of Dongguan City, No.1, Xianglong Road, Dongguan, 523326, China.
| | - Chun-Ping Zeng
- Department of Endocrinology and Metabolism, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510330, China.
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Peng C, Liu F, Su KJ, Lin X, Song YQ, Shen J, Hu SD, Chen QC, Yuan HH, Li WX, Zeng CP, Deng HW, Lou HL. Enhanced Identification of Novel Potential Variants for Appendicular Lean Mass by Leveraging Pleiotropy With Bone Mineral Density. Front Immunol 2021; 12:643894. [PMID: 33889153 PMCID: PMC8056257 DOI: 10.3389/fimmu.2021.643894] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Accepted: 03/09/2021] [Indexed: 11/22/2022] Open
Abstract
Strong relationships have been found between appendicular lean mass (ALM) and bone mineral density (BMD). It may be due to a shared genetic basis, termed pleiotropy. By leveraging the pleiotropy with BMD, the aim of this study was to detect more potential genetic variants for ALM. Using the conditional false discovery rate (cFDR) methodology, a combined analysis of the summary statistics of two large independent genome wide association studies (GWAS) of ALM (n = 73,420) and BMD (n = 10,414) was conducted. Strong pleiotropic enrichment and 26 novel potential pleiotropic SNPs were found for ALM and BMD. We identified 156 SNPs for ALM (cFDR <0.05), of which 74 were replicates of previous GWASs and 82 were novel SNPs potentially-associated with ALM. Eleven genes annotated by 31 novel SNPs (13 pleiotropic and 18 ALM specific) were partially validated in a gene expression assay. Functional enrichment analysis indicated that genes corresponding to the novel potential SNPs were enriched in GO terms and/or KEGG pathways that played important roles in muscle development and/or BMD metabolism (adjP <0.05). In protein–protein interaction analysis, rich interactions were demonstrated among the proteins produced by the corresponding genes. In conclusion, the present study, as in other recent studies we have conducted, demonstrated superior efficiency and reliability of the cFDR methodology for enhanced detection of trait-associated genetic variants. Our findings shed novel insight into the genetic variability of ALM in addition to the shared genetic basis underlying ALM and BMD.
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Affiliation(s)
- Cheng Peng
- Department of Geriatrics, National Key Clinical Specialty, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Feng Liu
- Department of Geriatrics, National Key Clinical Specialty, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Kuan-Jui Su
- Center for Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, Tulane University, New Orleans, LA, United States
| | - Xu Lin
- Shunde Hospital of Southern Medical University (The First People's Hospital of Shunde), Foshan City, China
| | - Yu-Qian Song
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China
| | - Jie Shen
- Shunde Hospital of Southern Medical University (The First People's Hospital of Shunde), Foshan City, China
| | - Shi-Di Hu
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China
| | - Qiao-Cong Chen
- Department of Geriatrics, National Key Clinical Specialty, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Hui-Hui Yuan
- Department of Geriatrics, National Key Clinical Specialty, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Wen-Xi Li
- Department of Geriatrics, National Key Clinical Specialty, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
| | - Chun-Ping Zeng
- Department of Endocrinology and Metabolism, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Hong-Wen Deng
- Center for Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, Tulane University, New Orleans, LA, United States
| | - Hui-Ling Lou
- Department of Geriatrics, National Key Clinical Specialty, Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, China
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Liu RK, Lin X, Wang Z, Greenbaum J, Qiu C, Zeng CP, Zhu YY, Shen J, Deng HW. Identification of novel functional CpG-SNPs associated with Type 2 diabetes and birth weight. Aging (Albany NY) 2021; 13:10619-10658. [PMID: 33835050 PMCID: PMC8064204 DOI: 10.18632/aging.202828] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Accepted: 03/04/2021] [Indexed: 12/18/2022]
Abstract
Genome-wide association studies (GWASs) have identified hundreds of genetic loci for type 2 diabetes (T2D) and birth weight (BW); however, a large proportion of the total trait heritability remains unexplained. The previous studies were generally focused on individual traits and largely failed to identify the majority of the variants that play key functional roles in the etiology of the disease. Here, we aim to identify novel functional loci for T2D, BW and the pleiotropic variants shared between them by performing a targeted conditional false discovery rate (cFDR) analysis that integrates two independent GWASs with summary statistics for T2D (n = 26,676 cases and 132,532 controls) and BW (n = 153,781) which entails greater statistical power than individual trait analyses. In this analysis, we considered CpG-SNPs, which are SNPs that may influence DNA methylation status, and are therefore considered to be functionally important. We identified 103 novel CpG-SNPs for T2D, 182 novel CpG-SNPs for BW (cFDR < 0.05), and 52 novel pleiotropic loci for both (conjunction cFDR [ccFDR] < 0.05). Among the identified novel CpG-SNPs, 33 were annotated as methylation quantitative trait loci (meQTLs) in whole blood, and 145 displayed at least some effects on meQTL, metabolic QTL (metaQTL), and/or expression QTL (eQTL). These findings may provide further insights into the shared biological mechanisms and functional genetic determinants that overlap between T2D and BW, thereby providing novel potential targets for treatment/intervention development.
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Affiliation(s)
- Rui-Ke Liu
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, China
- Department of Endocrinology and Metabolism, SSL Central Hospital of Dongguan City, Dongguan 523326, China
| | - Xu Lin
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, China
| | - Zun Wang
- Xiangya Nursing School, Central South University, Changsha 410013, China
| | - Jonathan Greenbaum
- Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Chuan Qiu
- Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Chun-Ping Zeng
- Department of Endocrinology and metabolism, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou 510330, China
| | - Yong-Yao Zhu
- Department of Endocrinology and Metabolism, SSL Central Hospital of Dongguan City, Dongguan 523326, China
| | - Jie Shen
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, China
| | - Hong-Wen Deng
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, China
- Tulane Center for Biomedical Informatics and Genomics, Deming Department of Medicine, School of Medicine, Tulane University, New Orleans, LA 70112, USA
- School of Basic Medical Sciences, Central South University, Changsha 410000, China
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Wu X, Lin X, Li Q, Wang Z, Zhang N, Tian M, Wang X, Deng H, Tan H. Identification of novel SNPs associated with coronary artery disease and birth weight using a pleiotropic cFDR method. Aging (Albany NY) 2020; 13:3618-3644. [PMID: 33411684 PMCID: PMC7906162 DOI: 10.18632/aging.202322] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2020] [Accepted: 11/11/2020] [Indexed: 11/30/2022]
Abstract
Objectives: Clinical and epidemiological findings indicate an association between coronary artery disease (CAD) and low birth weight (BW). However, the mechanisms underlying this relationship are largely unknown. Here, we aimed to identify novel single-nucleotide polymorphisms (SNPs) associated with CAD, BW, and their shared pleiotropic loci, and to detect the potential causal relationship between CAD and BW. Methods: We first applied a genetic pleiotropic conditional false discovery rate (cFDR) method to two independent genome-wide association studies (GWAS) summary statistics of CAD and BW to estimate the pleiotropic enrichment between them. Then, bi-directional Mendelian randomization (MR) analyses were performed to clarify the causal association between these two traits. Results: By incorporating related traits into a conditional analysis framework, we observed the significant pleiotropic enrichment between CAD and BW. By applying the cFDR level of 0.05, 109 variants were detected for CAD, 203 for BW, and 26 pleiotropic variants for both traits. We identified 11 CAD- and/or BW-associated SNPs that showed more than three of the metabolic quantitative trait loci (metaQTL), protein QTL (pQTL), methylation QTL (meQTL), or expression QTL (eQTL) effects. The pleiotropic SNP rs10774625, located at ATXN2, showed metaQTL, pQTL, meQTL, and eQTL effects simultaneously. Using the bi-directional MR approach, we found a negative association from BW to CAD (odds ratio [OR] = 0.68, 95% confidence interval [CI]: 0.59 to 0.80, p = 1.57× 10-6). Conclusion: We identified several pleiotropic loci between CAD and BW by leveraging GWAS results of related phenotypes and identified a potential causal relationship from BW to CAD. Our findings provide novel insights into the shared biological mechanisms and overlapping genetic heritability between CAD and BW.
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Affiliation(s)
- Xinrui Wu
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, China
| | - Xu Lin
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, China
| | - Qi Li
- Xiangxi Center for Disease Prevention and Control, Jishou 416000, China
| | - Zun Wang
- Xiangya Nursing School, Central South University, Changsha 410013, China
| | - Na Zhang
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, China
| | - Mengyuan Tian
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, China
| | - Xiaolei Wang
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, China
| | - Hongwen Deng
- School of Basic Medical Science, Central South University, Changsha 410013, China.,Tulane Center for Biomedical Informatics and Genomics, School of Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Hongzhuan Tan
- Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha 410078, China
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Identification of novel functional CpG-SNPs associated with type 2 diabetes and coronary artery disease. Mol Genet Genomics 2020; 295:607-619. [PMID: 32162118 DOI: 10.1007/s00438-020-01651-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2019] [Accepted: 02/03/2020] [Indexed: 02/08/2023]
Abstract
Genome-wide association studies (GWASs) have identified hundreds of single nucleotide polymorphisms (SNPs) associated with type 2 diabetes (T2D) and coronary artery disease (CAD), respectively. Nevertheless, these studies were generally performed for single-trait/disease and failed to assess the pleiotropic role of the identified variants. To identify novel functional loci and the pleiotropic relationship between CAD and T2D, the targeted cFDR analysis on CpG-SNPs was performed by integrating two independent large and multi-centered GWASs with summary statistics of T2D (26,676 cases and 132,532 controls) and CAD (60,801 cases and 123,504 controls). Applying the cFDR significance threshold of 0.05, we observed a pleiotropic enrichment between T2D and CAD by incorporating pleiotropic effects into a conditional analysis framework. We identified 79 novel CpG-SNPs for T2D, 61 novel CpG-SNPs for CAD, and 18 novel pleiotropic loci for both traits. Among these novel CpG-SNPs, 33 of them were annotated as methylation quantitative trait locus (meQTL) in whole blood, and ten of them showed expression QTL (eQTL), meQTL, and metabolic QTL (metaQTL) effects simultaneously. To the best of our knowledge, we performed the first targeted cFDR analysis on CpG-SNPs, and our findings provided novel insights into the shared biological mechanisms and overlapped genetic heritability between T2D and CAD.
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Olaiya MT, Wedekind LE, Hanson RL, Sinha M, Kobes S, Nelson RG, Baier LJ, Knowler WC. Birthweight and early-onset type 2 diabetes in American Indians: differential effects in adolescents and young adults and additive effects of genotype, BMI and maternal diabetes. Diabetologia 2019; 62:1628-1637. [PMID: 31111170 PMCID: PMC6679754 DOI: 10.1007/s00125-019-4899-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Accepted: 04/23/2019] [Indexed: 12/13/2022]
Abstract
AIMS/HYPOTHESIS The aim of this work was to estimate the impact of birthweight on early-onset (age <40 years) type 2 diabetes. METHODS A longitudinal study of American Indians, aged ≥5 years, was conducted from 1965 to 2007. Participants who had a recorded birthweight were followed until they developed diabetes or their last examination before the age of 40 years, whichever came first. Age- and sex-adjusted diabetes incidence rates were computed and Poisson regression was used to model the effect of birthweight on diabetes incidence, adjusted for sex, BMI, a type 2 diabetes susceptibility genetic risk score (GRS) and maternal covariates. RESULTS Among 3039 participants, there were 652 incident diabetes cases over a median follow-up of 14.3 years. Diabetes incidence increased with age and was greater in the lowest and highest quintiles of birthweight. Adjusted for covariates, the effect of birthweight on diabetes varied over time, with a non-linear effect at 10-19 years (p < 0.001) and a negative linear effect at older age intervals (20-29 years, p < 0.001; 30-39 years, p = 0.003). Higher GRS, greater BMI and maternal diabetes had additive but not interactive effects on the association between birthweight and diabetes incidence. CONCLUSIONS/INTERPRETATION In this high-risk population, both low and high birthweights were associated with increased type 2 diabetes risk in adolescence (age 10-19 years) but only low birthweight was associated with increased risk in young adulthood (20-39 years). Higher type 2 diabetes GRS, greater BMI and maternal diabetes added to the risk of early-onset diabetes.
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Affiliation(s)
- Muideen T Olaiya
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive Kidney Diseases, National Institutes of Health, 1550 East Indian School Road, Phoenix, AZ, 85014, USA.
| | - Lauren E Wedekind
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive Kidney Diseases, National Institutes of Health, 1550 East Indian School Road, Phoenix, AZ, 85014, USA
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Robert L Hanson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive Kidney Diseases, National Institutes of Health, 1550 East Indian School Road, Phoenix, AZ, 85014, USA
| | - Madhumita Sinha
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive Kidney Diseases, National Institutes of Health, 1550 East Indian School Road, Phoenix, AZ, 85014, USA
| | - Sayuko Kobes
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive Kidney Diseases, National Institutes of Health, 1550 East Indian School Road, Phoenix, AZ, 85014, USA
| | - Robert G Nelson
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive Kidney Diseases, National Institutes of Health, 1550 East Indian School Road, Phoenix, AZ, 85014, USA
| | - Leslie J Baier
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive Kidney Diseases, National Institutes of Health, 1550 East Indian School Road, Phoenix, AZ, 85014, USA
| | - William C Knowler
- Phoenix Epidemiology and Clinical Research Branch, National Institute of Diabetes and Digestive Kidney Diseases, National Institutes of Health, 1550 East Indian School Road, Phoenix, AZ, 85014, USA
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Improved detection of common variants in coronary artery disease and blood pressure using a pleiotropy cFDR method. Sci Rep 2019; 9:10340. [PMID: 31316127 PMCID: PMC6637206 DOI: 10.1038/s41598-019-46808-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Accepted: 07/04/2019] [Indexed: 11/24/2022] Open
Abstract
Plenty of genome-wide association studies (GWASs) have identified numerous single nucleotide polymorphisms (SNPs) for coronary artery disease (CAD) and blood pressure (BP). However, these SNPs only explain a small proportion of the heritability of two traits/diseases. Although high BP is a major risk factor for CAD, the genetic intercommunity between them remain largely unknown. To recognize novel loci associated with CAD and BP, a genetic-pleiotropy-informed conditional false discovery rate (cFDR) method was applied on two summary statistics of CAD and BP from existing GWASs. Stratified Q-Q and fold enrichment plots showed a high pleiotropic enrichment of SNPs associated with two traits. Adopting a cFDR of 0.05 as a threshold, 55 CAD-associated loci (25 variants being novel) and 47 BP loci (18 variants being novel) were identified, 25 of which were pleiotropic loci (13 variants being novel) for both traits. Among the 32 genes these 25 SNPs were annotated to, 20 genes were newly detected compared to previous GWASs. This study showed the cFDR approach could improve gene discovery by incorporating GWAS datasets of two related traits. These findings may provide novel understanding of etiology relationships between CAD and BP.
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Zeng CP, Lin X, Peng C, Zhou L, You HM, Shen J, Deng HW. Identification of novel genetic variants for type 2 diabetes, childhood obesity, and their pleiotropic loci. J Hum Genet 2019; 64:369-377. [PMID: 30816286 PMCID: PMC6712986 DOI: 10.1038/s10038-019-0577-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Revised: 12/27/2018] [Accepted: 01/31/2019] [Indexed: 12/11/2022]
Abstract
Obesity has result in increased prevalence of type 2 diabetes (T2D) in children. The genetic mechanisms underlying their relationship, however, are not fully understood. Here, we aim to identify novel SNPs associated with T2D and childhood obesity (CO), especially their pleiotropic loci. We integrated the summary statistics for two independent GWASs of T2D (n = 149,821) and childhood body mass index (CBMI) (n = 35,668) using the pleiotropy-informed conditional false discovery rate (cFDR) method. By leveraging the information of different levels of association for CBMI, we observed a strong enrichment of genetic variants associated with T2D. We identified 139 T2D-associated SNPs with 125 novel ones (cFDR < 0.05). Conditioned on T2D, we identified 37 significant SNPs for CBMI (cFDR < 0.05), including 25 novel ones. The conjunctional cFDR (ccFDR) analysis showed ten novel pleiotropic loci for T2D and CBMI (ccFDR < 0.05). Interestingly, the novel SNP rs1996023 is located at protein coding gene GNPDA2 (ccFDR = 1.28E-02), which has been reported to influence the risk of T2D and CO through central nervous system. Our findings may help to explain a greater proportion of the heritability for human traits and advance the understanding of the common pathophysiology between T2D and CO.
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Affiliation(s)
- Chun-Ping Zeng
- Department of Endocrinology and Metabolism, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
| | - Xu Lin
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China
| | - Cheng Peng
- Department of Geriatrics, National Key Clinical Specialty, Guangzhou First People's Hospital, Guangzhou Medical University, Guangzhou, 510180, PR China
| | - Lin Zhou
- Department of Endocrinology and Metabolism, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Hui-Min You
- Department of Endocrinology and Metabolism, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, China
| | - Jie Shen
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China
| | - Hong-Wen Deng
- Center for Bioinformatics and Genomics, Department of Biostatistics and Data Science, Tulane University, New Orleans, LA, USA.
- School of Basic Medical Sciences, Central South University, Changsha, 410000, China.
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9
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Zhou Z, Sun B, Huang S, Jia W, Yu D. The tRNA-associated dysregulation in diabetes mellitus. Metabolism 2019; 94:9-17. [PMID: 30711570 DOI: 10.1016/j.metabol.2019.01.017] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Revised: 01/26/2019] [Accepted: 01/30/2019] [Indexed: 12/26/2022]
Abstract
Diabetes mellitus (DM) is a complex endocrine and metabolic disorder for human health and well-being. Deregulated glucose and lipid metabolism are the primary underlying manifestations associated with this disease. Transfer RNAs (tRNAs) are considered to mainly participate in protein translation and may contribute to complex human pathologies. Although the molecular mechanisms remain, for the most part, unknown, accumulating evidence indicates that tRNAs play a vital role in the pathogenesis of DM. This paper reviews different aspects of tRNA-associated dysregulation in DM, such as tRNA mutations, tRNA modifications, tRNA aminoacylation and tRNA derivatives, aiming at a better understanding of the pathogenesis of DM and providing new ideas for the personalized treatment of this metabolism-associated disease.
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Affiliation(s)
- Zheng Zhou
- Department of Chinese Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450000, China
| | - Bao Sun
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410000, China; Hunan Key Laboratory of Pharmacogenetics, Institute of Clinical Pharmacology, Central South University, Changsha 410000, China
| | - Shiqiong Huang
- Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha 410000, China; Hunan Key Laboratory of Pharmacogenetics, Institute of Clinical Pharmacology, Central South University, Changsha 410000, China
| | - Wenrui Jia
- Department of Chinese Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450000, China
| | - Dongsheng Yu
- Department of Chinese Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450000, China.
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Chapman DE, Reddy BJN, Huy B, Bovyn MJ, Cruz SJS, Al-Shammari ZM, Han H, Wang W, Smith DS, Gross SP. Regulation of in vivo dynein force production by CDK5 and 14-3-3ε and KIAA0528. Nat Commun 2019; 10:228. [PMID: 30651536 PMCID: PMC6335402 DOI: 10.1038/s41467-018-08110-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Accepted: 12/18/2018] [Indexed: 12/17/2022] Open
Abstract
Single-molecule cytoplasmic dynein function is well understood, but there are major gaps in mechanistic understanding of cellular dynein regulation. We reported a mode of dynein regulation, force adaptation, where lipid droplets adapt to opposition to motion by increasing the duration and magnitude of force production, and found LIS1 and NudEL to be essential. Adaptation reflects increasing NudEL-LIS1 utilization; here, we hypothesize that such increasing utilization reflects CDK5-mediated NudEL phosphorylation, which increases the dynein-NudEL interaction, and makes force adaptation possible. We report that CDK5, 14-3-3ε, and CDK5 cofactor KIAA0528 together promote NudEL phosphorylation and are essential for force adaptation. By studying the process in COS-1 cells lacking Tau, we avoid confounding neuronal effects of CDK5 on microtubules. Finally, we extend this in vivo regulatory pathway to lysosomes and mitochondria. Ultimately, we show that dynein force adaptation can control the severity of lysosomal tug-of-wars among other intracellular transport functions involving high force. Dynein plays roles in vesicular, organelle, chromosomal and nuclear transport but so far it is unclear how dynein activity in cells is regulated. Here authors study several dynein cofactors and their role in force adaptation of dynein during lipid droplet, lysosomal, and mitochondrial transport.
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Affiliation(s)
- Dail E Chapman
- Developmental and Cell Biology and Physics, University of California, Irvine, CA, USA
| | - Babu J N Reddy
- Developmental and Cell Biology and Physics, University of California, Irvine, CA, USA
| | - Bunchhin Huy
- Developmental and Cell Biology and Physics, University of California, Irvine, CA, USA
| | - Matthew J Bovyn
- Developmental and Cell Biology and Physics, University of California, Irvine, CA, USA
| | - Stephen John S Cruz
- Developmental and Cell Biology and Physics, University of California, Irvine, CA, USA
| | - Zahraa M Al-Shammari
- Developmental and Cell Biology and Physics, University of California, Irvine, CA, USA
| | - Han Han
- Developmental and Cell Biology and Physics, University of California, Irvine, CA, USA
| | - Wenqi Wang
- Developmental and Cell Biology and Physics, University of California, Irvine, CA, USA
| | - Deanna S Smith
- Biological Sciences, University of South Carolina, Columbia, SC, USA
| | - Steven P Gross
- Developmental and Cell Biology and Physics, University of California, Irvine, CA, USA.
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Hu Y, Tan LJ, Chen XD, Greenbaum J, Deng HW. Identification of novel variants associated with osteoporosis, type 2 diabetes and potentially pleiotropic loci using pleiotropic cFDR method. Bone 2018; 117:6-14. [PMID: 30172742 PMCID: PMC6364698 DOI: 10.1016/j.bone.2018.08.020] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/02/2018] [Revised: 08/27/2018] [Accepted: 08/29/2018] [Indexed: 12/16/2022]
Abstract
AIMS Clinical and epidemiological findings point to an association between type 2 diabetes (T2D) and osteoporosis. Genome-wide association studies (GWASs) have been fruitful in identifying some loci potentially associated with osteoporosis and T2D respectively. However, the total genetic variance for each of these two diseases and the shared genetic determination between them are largely unknown. The aim of this study was to identify novel genetic variants for osteoporosis and/or T2D. METHODS First, using a pleiotropic conditional false discovery rate (cFDR) method, we analyzed two GWAS summary data of femoral neck bone mineral density (FN_BMD, n = 53,236) and T2D (n = 159,208) to identify novel shared genetic loci. FN_BMD is an important risk factor for osteoporosis. Next, to explore the potential functions of the identified potential pleiotropic genes, differential expression analysis was performed for them in monocytes and peripheral blood mononuclear cells (PBMCs) as these cells are relevant to the etiology of osteoporosis and/or T2D. Further, weighted gene co-expression analysis (WGCNA) was conducted to identify functional connections between novel pleiotropic genes and known osteoporosis/T2D susceptibility genes by using transcriptomic expression datasets in bone biopsies (E-MEXP-1618) and pancreatic islets (GSE50397). Finally, multi-trait fine mapping for the detected pleiotropic risk loci were conducted to identify the SNPs that have the highest probability of being causal for both FN_BMD and T2D. RESULTS We identified 27 significant SNPs with cFDR<0.05 for FN_BMD and 61 SNPs for T2D respectively. Four loci, rs7068487 (PLEKHA1), rs10885421 (TCF7L2), rs944082 (GNG12-AS1 (WLS)) and rs2065929 (PIFO||PGCP1), were found to be potentially pleiotropic and shared between FN_BMD and T2D (ccFDR<0.05). PLEKHA1 was found differentially expressed in circulating monocytes between high and low BMD subjects, and PBMCs between diabetic and non-diabetic conditions. WGCNA showed that PLEKHA1 and TCF7L2 were interconnected with multiple osteoporosis and T2D associated genes in bone biopsy and pancreatic islets, such as JAG, EN1 and CPE. Fine mapping showed that rs11200594 was a potentially causal variant in the locus of PLEKHA1. rs11200594 is also an eQTL of PLEKHA1 in multiple tissue (e.g. peripheral blood cells, adipose and ovary) and is in strong LD with a number of functional variants. CONCLUSIONS Four potential pleiotropic loci were identified for shared genetic determination of osteoporosis and T2D. Our study highlights PLEKHA1 as an important potentially pleiotropic gene. The findings may help us gain a better understanding of the shared genetic determination between these two important disorders.
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Affiliation(s)
- Yuan Hu
- Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, China
| | - Li-Jun Tan
- Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, China
| | - Xiang-Ding Chen
- Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, China
| | - Jonathan Greenbaum
- School of Basic Medical Sciences, Central South University, Changsha, Hunan 410013, China
| | - Hong-Wen Deng
- Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, China; School of Basic Medical Sciences, Central South University, Changsha, Hunan 410013, China; Center of Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA.
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12
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Zhang Q, Liu HM, Lv WQ, He JY, Xia X, Zhang WD, Deng HW, Sun CQ. Additional common variants associated with type 2 diabetes and coronary artery disease detected using a pleiotropic cFDR method. J Diabetes Complications 2018; 32:1105-1112. [PMID: 30270018 PMCID: PMC6743331 DOI: 10.1016/j.jdiacomp.2018.09.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/11/2017] [Revised: 04/11/2018] [Accepted: 09/02/2018] [Indexed: 12/27/2022]
Abstract
Genome-wide association studies (GWASs) have been performed extensively in diverse populations to identify single nucleotide polymorphisms (SNPs) associated with complex diseases or traits. However, to date, the SNPs identified fail to explain a large proportion of the variance of the traits/diseases. GWASs on type 2 diabetes (T2D) and coronary artery disease (CARD) are generally performed as single-trait studies, rather than analyzing the related traits simultaneously. Despite the extensive evidence suggesting that these two phenotypes share both genetic and environmental risk factors, the shared overlapping genetic biological mechanisms between these traits remain largely unexplored. Here, we adopted a recently developed genetic pleiotropic conditional false discovery rate (cFDR) approach to discover novel loci associated with T2D and CARD by incorporating the summary statistics from existing GWASs of these two traits. Applying the cFDR level of 0.05, 33 loci were identified for T2D and 34 loci for CARD, 9 of which for both. By incorporating pleiotropic effects into a conditional analysis framework, we observed that there is significant pleiotropic enrichment between T2D and CARD. These findings may provide novel insights into the etiology of T2D and CARD, as well as the processes that may influence disease development both individually and jointly.
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Affiliation(s)
- Qiang Zhang
- College of Public Health, Zhengzhou University, Zhengzhou, No. 100 Kexue Road, High-Tech Development Zone Of States, PR China
| | - Hui-Min Liu
- College of Public Health, Zhengzhou University, Zhengzhou, No. 100 Kexue Road, High-Tech Development Zone Of States, PR China
| | - Wan-Qiang Lv
- College of Public Health, Zhengzhou University, Zhengzhou, No. 100 Kexue Road, High-Tech Development Zone Of States, PR China
| | - Jing-Yang He
- College of Public Health, Zhengzhou University, Zhengzhou, No. 100 Kexue Road, High-Tech Development Zone Of States, PR China
| | - Xin Xia
- College of Public Health, Zhengzhou University, Zhengzhou, No. 100 Kexue Road, High-Tech Development Zone Of States, PR China
| | - Wei-Dong Zhang
- College of Public Health, Zhengzhou University, Zhengzhou, No. 100 Kexue Road, High-Tech Development Zone Of States, PR China
| | - Hong-Wen Deng
- College of Public Health, Zhengzhou University, Zhengzhou, No. 100 Kexue Road, High-Tech Development Zone Of States, PR China; Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Chang-Qing Sun
- College of Public Health, Zhengzhou University, Zhengzhou, No. 100 Kexue Road, High-Tech Development Zone Of States, PR China.
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13
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Lin X, Peng C, Greenbaum J, Li ZF, Wu KH, Ao ZX, Zhang T, Shen J, Deng HW. Identifying potentially common genes between dyslipidemia and osteoporosis using novel analytical approaches. Mol Genet Genomics 2018; 293:711-723. [PMID: 29327327 PMCID: PMC5949092 DOI: 10.1007/s00438-017-1414-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2017] [Accepted: 12/29/2017] [Indexed: 02/07/2023]
Abstract
Dyslipidemia (DL) is closely related to osteoporosis (OP), while the exact common genetic mechanisms are still largely unknown. We proposed to use novel genetic analysis methods with pleiotropic information to identify potentially novel and/or common genes for the potential shared pathogenesis associated with OP and/or DL. We assessed the pleiotropy between plasma lipid (PL) and femoral neck bone mineral density (FNK BMD). We jointly applied the conditional false discovery rate (cFDR) method and the genetic analysis incorporating pleiotropy and annotation (GPA) method to the summary statistics provided by genome-wide association studies (GWASs) of FNK BMD (n = 49,988) and PL (n = 188,577) to identify potentially novel and/or common genes for BMD/PL. We found strong pleiotropic enrichment between PL and FNK BMD. Two hundred and forty-five PL SNPs were identified as potentially novel SNPs by cFDR and GPA. The corresponding genes were enriched in gene ontology (GO) terms "phospholipid homeostasis" and "chylomicron remnant clearance". Three SNPs (rs2178950, rs9939318, and rs9368716) might be the pleiotropic ones and the corresponding genes NLRC5 (rs2178950) and TRPS1 (rs9939318) were involved in NF-κB signaling pathway and Wnt signaling pathway as well as inflammation and innate immune processes. Our study validated the pleiotropy between PL and FNK BMD, and corroborated the reliability and high-efficiency of cFDR and GPA methods in further analyses of existing GWASs with summary statistics. We identified potentially common and/or novel genes for PL and/or FNK BMD, which may provide new insight and direction for further research.
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Affiliation(s)
- Xu Lin
- Southern Medical University, No.1023, South Shatai Road, Baiyun District, Guangzhou, 510515, Guangdong, People's Republic of China
| | - Cheng Peng
- Department of Geriatrics, National Key Clinical Specialty, Guangzhou First People's Hospital, The Second Affiliated Hospital of South China University of Technology, Guangzhou, 510180, People's Republic of China
| | - Jonathan Greenbaum
- Center for Bioinformatics and Genomics, Department of Global Statistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Zhang-Fang Li
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510630, People's Republic of China
| | - Ke-Hao Wu
- Center for Bioinformatics and Genomics, Department of Global Statistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Zeng-Xin Ao
- Southern Medical University, No.1023, South Shatai Road, Baiyun District, Guangzhou, 510515, Guangdong, People's Republic of China
| | - Tong Zhang
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510630, People's Republic of China
| | - Jie Shen
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou, 510630, People's Republic of China
| | - Hong-Wen Deng
- Center for Bioinformatics and Genomics, Department of Global Statistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA.
- School of Basic Medical Sciences, Central South University, Changsha, 410000, People's Republic of China.
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14
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Liu HM, He JY, Zhang Q, Lv WQ, Xia X, Sun CQ, Zhang WD, Deng HW. Improved detection of genetic loci in estimated glomerular filtration rate and type 2 diabetes using a pleiotropic cFDR method. Mol Genet Genomics 2018; 293:225-235. [PMID: 29038864 PMCID: PMC5819009 DOI: 10.1007/s00438-017-1381-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2017] [Accepted: 10/06/2017] [Indexed: 01/19/2023]
Abstract
Genome-wide association studies (GWAS) have been shown to have the potential of explaining more of the "missing heritability" of complex human phenotypes by improving statistical approaches. Here, we applied a genetic-pleiotropy-informed conditional false discovery rate (cFDR) to capture additional polygenic effects associated with estimated glomerular filtration rate (creatinine) (eGFRcrea) and type 2 diabetes (T2D). The cFDR analysis improves the identification of pleiotropic variants by incorporating potentially shared genetic mechanisms between two related traits. The Q-Q and fold-enrichment plots were used to assess the enrichment of SNPs associated with eGFRcrea or T2D, and Manhattan plots were used for showing chromosomal locations of the significant loci detected. By applying the cFDR method, we newly identified 74 loci for eGFRcrea and 3 loci for T2D with the cFDR criterion of 0.05 compared with previous related GWAS studies. Four shared SNPs were detected to be associated with both eGFRcrea and T2D at the significant conjunction cFDR level of 0.05, and these shared SNPs had not been reported in previous studies. In addition, we used DAVID analysis to perform functional analysis of the shared SNPs' annotated genes and found their potential hidden associations with eGFRcrea and T2D. In this study, the cFDR method shows the feasibility to detect more genetic variants underlying the heritability of eGFRcrea and T2D, and the overlapping SNPs identified could be regarded as candidate loci that provide a thread of genetic mechanisms between eGFRcrea and T2D in future research.
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Affiliation(s)
- Hui-Min Liu
- College of Public Health Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China
| | - Jing-Yang He
- College of Public Health Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China
| | - Qiang Zhang
- College of Public Health Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China
| | - Wan-Qiang Lv
- College of Public Health Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China
| | - Xin Xia
- College of Public Health Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China
| | - Chang-Qing Sun
- College of Public Health Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China
| | - Wei-Dong Zhang
- College of Public Health Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China.
| | - Hong-Wen Deng
- College of Public Health Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China.
- Department of Biostatistics and Data Science, Tulane Center of Bioinformatics and Genomics, Tulane University School of Public Health and Tropical Medicine, New Orleans, LA, 70112, USA.
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15
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Hu Y, Tan LJ, Chen XD, Liu Z, Min SS, Zeng Q, Shen H, Deng HW. Identification of Novel Potentially Pleiotropic Variants Associated With Osteoporosis and Obesity Using the cFDR Method. J Clin Endocrinol Metab 2018; 103:125-138. [PMID: 29145611 PMCID: PMC6061219 DOI: 10.1210/jc.2017-01531] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/06/2017] [Accepted: 10/12/2017] [Indexed: 01/10/2023]
Abstract
CONTEXT Genome-wide association studies (GWASs) have been successful in identifying loci associated with osteoporosis and obesity. However, the findings explain only a small fraction of the total genetic variance. OBJECTIVE The aim of this study was to identify novel pleiotropic genes important in osteoporosis and obesity. DESIGN AND SETTING A pleiotropic conditional false discovery rate method was applied to three independent GWAS summary statistics of femoral neck bone mineral density, body mass index, and waist-to-hip ratio. Next, differential expression analysis was performed for the potentially pleiotropic genes, and weighted genes coexpression network analysis (WGCNA) was conducted to identify functional connections between the suggested pleiotropic genes and known osteoporosis/obesity genes using transcriptomic expression data sets in osteoporosis/obesity-related cells. RESULTS We identified seven potentially pleiotropic loci-rs3759579 (MARK3), rs2178950 (TRPS1), rs1473 (PUM1), rs9825174 (XXYLT1), rs2047937 (ZNF423), rs17277372 (DNM3), and rs335170 (PRDM6)-associated with osteoporosis and obesity. Of these loci, the PUM1 gene was differentially expressed in osteoporosis-related cells (B lymphocytes) and obesity-related cells (adipocytes). WGCNA showed that PUM1 positively interacted with several known osteoporosis genes (AKAP11, JAG1, and SPTBN1). ZNF423 was the highly connected intramodular hub gene and interconnected with 21 known osteoporosis-related genes, including JAG1, EN1, and FAM3C. CONCLUSIONS Our study identified seven potentially pleiotropic genes associated with osteoporosis and obesity. The findings may provide new insights into a potential genetic determination and codetermination mechanism of osteoporosis and obesity.
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Affiliation(s)
- Yuan Hu
- Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, China
| | - Li-Jun Tan
- Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, China
| | - Xiang-Ding Chen
- Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, China
| | - Zhen Liu
- Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, China
| | - Shi-Shi Min
- Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, China
| | - Qin Zeng
- Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, China
| | - Hui Shen
- Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
| | - Hong-Wen Deng
- Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan, China
- Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana
- Correspondence and Reprint Requests: Hong-Wen Deng, PhD, Department of Global Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, 1440 Canal Street, Suite 1610, New Orleans, Louisiana 70112. E-mail:
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16
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Konigorski S, Wang Y, Cigsar C, Yilmaz YE. Estimating and testing direct genetic effects in directed acyclic graphs using estimating equations. Genet Epidemiol 2017; 42:174-186. [PMID: 29265408 PMCID: PMC6619348 DOI: 10.1002/gepi.22107] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2017] [Revised: 10/26/2017] [Accepted: 11/14/2017] [Indexed: 12/12/2022]
Abstract
In genetic association studies, it is important to distinguish direct and indirect genetic effects in order to build truly functional models. For this purpose, we consider a directed acyclic graph setting with genetic variants, primary and intermediate phenotypes, and confounding factors. In order to make valid statistical inference on direct genetic effects on the primary phenotype, it is necessary to consider all potential effects in the graph, and we propose to use the estimating equations method with robust Huber-White sandwich standard errors. We evaluate the proposed causal inference based on estimating equations (CIEE) method and compare it with traditional multiple regression methods, the structural equation modeling method, and sequential G-estimation methods through a simulation study for the analysis of (completely observed) quantitative traits and time-to-event traits subject to censoring as primary phenotypes. The results show that CIEE provides valid estimators and inference by successfully removing the effect of intermediate phenotypes from the primary phenotype and is robust against measured and unmeasured confounding of the indirect effect through observed factors. All other methods except the sequential G-estimation method for quantitative traits fail in some scenarios where their test statistics yield inflated type I errors. In the analysis of the Genetic Analysis Workshop 19 dataset, we estimate and test genetic effects on blood pressure accounting for intermediate gene expression phenotypes. The results show that CIEE can identify genetic variants that would be missed by traditional regression analyses. CIEE is computationally fast, widely applicable to different fields, and available as an R package.
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Affiliation(s)
- Stefan Konigorski
- Molecular Epidemiology Research Group, Max Delbrück Center (MDC) for Molecular Medicine in the Helmholtz Association, Berlin, Germany.,Department of Mathematics and Statistics, Memorial University of Newfoundland, St. John's, Canada
| | - Yuan Wang
- Department of Mathematics and Statistics, Memorial University of Newfoundland, St. John's, Canada
| | - Candemir Cigsar
- Department of Mathematics and Statistics, Memorial University of Newfoundland, St. John's, Canada
| | - Yildiz E Yilmaz
- Department of Mathematics and Statistics, Memorial University of Newfoundland, St. John's, Canada.,Discipline of Genetics, Faculty of Medicine, Memorial University of Newfoundland, St. John's, Canada.,Discipline of Medicine, Faculty of Medicine, Memorial University of Newfoundland, St. John's, Canada
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17
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Zhang Q, Wu KH, He JY, Zeng Y, Greenbaum J, Xia X, Liu HM, Lv WQ, Lin X, Zhang WD, Xi YL, Shi XZ, Sun CQ, Deng HW. Novel Common Variants Associated with Obesity and Type 2 Diabetes Detected Using a cFDR Method. Sci Rep 2017; 7:16397. [PMID: 29180724 PMCID: PMC5703959 DOI: 10.1038/s41598-017-16722-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2017] [Accepted: 11/16/2017] [Indexed: 12/17/2022] Open
Abstract
Genome-wide association studies (GWASs) have been performed extensively in diverse populations to identify single nucleotide polymorphisms (SNPs) associated with complex diseases or traits. However, to date, the SNPs identified fail to explain a large proportion of the variance of the traits/diseases. GWASs on type 2 diabetes (T2D) and obesity are generally focused on individual traits independently, and genetic intercommunity (common genetic contributions or the product of over correlated phenotypic world) between them are largely unknown, despite extensive data showing that these two phenotypes share both genetic and environmental risk factors. Here, we applied a recently developed genetic pleiotropic conditional false discovery rate (cFDR) approach to discover novel loci associated with BMI and T2D by incorporating the summary statistics from existing GWASs of these two traits. Conditional Q-Q and fold enrichment plots were used to visually demonstrate the strength of pleiotropic enrichment. Adopting a cFDR nominal significance level of 0.05, 287 loci were identified for BMI and 75 loci for T2D, 23 of which for both traits. By incorporating related traits into a conditional analysis framework, we observed significant pleiotropic enrichment between obesity and T2D. These findings may provide novel insights into the etiology of obesity and T2D, individually and jointly.
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Affiliation(s)
- Qiang Zhang
- College of Public Health, Zhengzhou University, Zhengzhou, NO.100 Kexue Road, High-Tech Development Zone Of States, Zhengzhou, P.R. China
| | - Ke-Hao Wu
- Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Jing-Yang He
- College of Public Health, Zhengzhou University, Zhengzhou, NO.100 Kexue Road, High-Tech Development Zone Of States, Zhengzhou, P.R. China
| | - Yong Zeng
- Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA.,College of Sciences, Beijing Jiao Tong University, Beijing, China
| | - Jonathan Greenbaum
- Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Xin Xia
- College of Public Health, Zhengzhou University, Zhengzhou, NO.100 Kexue Road, High-Tech Development Zone Of States, Zhengzhou, P.R. China
| | - Hui-Min Liu
- College of Public Health, Zhengzhou University, Zhengzhou, NO.100 Kexue Road, High-Tech Development Zone Of States, Zhengzhou, P.R. China
| | - Wan-Qiang Lv
- College of Public Health, Zhengzhou University, Zhengzhou, NO.100 Kexue Road, High-Tech Development Zone Of States, Zhengzhou, P.R. China
| | - Xu Lin
- Department of Endocrinology and Metabolism, the Third Affiliated Hospital of Southern Medical University, Guang Zhou, P.R. China
| | - Wei-Dong Zhang
- College of Public Health, Zhengzhou University, Zhengzhou, NO.100 Kexue Road, High-Tech Development Zone Of States, Zhengzhou, P.R. China
| | - Yuan-Lin Xi
- College of Public Health, Zhengzhou University, Zhengzhou, NO.100 Kexue Road, High-Tech Development Zone Of States, Zhengzhou, P.R. China
| | - Xue-Zhong Shi
- College of Public Health, Zhengzhou University, Zhengzhou, NO.100 Kexue Road, High-Tech Development Zone Of States, Zhengzhou, P.R. China
| | - Chang-Qing Sun
- College of Public Health, Zhengzhou University, Zhengzhou, NO.100 Kexue Road, High-Tech Development Zone Of States, Zhengzhou, P.R. China.
| | - Hong-Wen Deng
- College of Public Health, Zhengzhou University, Zhengzhou, NO.100 Kexue Road, High-Tech Development Zone Of States, Zhengzhou, P.R. China. .,Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, 70112, USA.
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18
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Lv WQ, Zhang X, Zhang Q, He JY, Liu HM, Xia X, Fan K, Zhao Q, Shi XZ, Zhang WD, Sun CQ, Deng HW. Novel common variants associated with body mass index and coronary artery disease detected using a pleiotropic cFDR method. J Mol Cell Cardiol 2017; 112:1-7. [PMID: 28843344 PMCID: PMC5812278 DOI: 10.1016/j.yjmcc.2017.08.011] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Revised: 08/18/2017] [Accepted: 08/22/2017] [Indexed: 12/20/2022]
Abstract
Genome-wide association studies (GWAS) have been successfully applied in identifying single nucleotide polymorphisms (SNPs) associated with body mass index (BMI) and coronary heart disease (CAD). However, the SNPs to date can only explain a small percentage of the genetic variances of traits. Here, we applied a genetic pleiotropic conditional false discovery rate (cFDR) method that combines summary statistic p values from different multi-center GWAS datasets, to detect common genetic variants associated with these two traits. The enrichment of SNPs associated with BMI and CAD was assessed by conditional Q-Q plots and the common variants were identified by the cFDR method. By applying the cFDR level of 0.05, 7 variants were identified to be associated with CAD (2 variants being novel), 34 variants associated with BMI (11 variants being novel), and 3 variants associated with both BMI and CAD (2 variants being novel). The SNP rs653178 (ATXN2) is noteworthy as this variant was replicated in an independent analysis. SNP rs12411886 (CNNM2) and rs794356 (HIP1) were of note as the annotated genes may be associated with processes that are functionally important in lipid metabolism. In conclusion, the cFDR method identified novel variants associated with BMI and/or CAD by effectively incorporating different GWAS datasets.
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Affiliation(s)
- Wan-Qiang Lv
- College of Public Health, Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China
| | - Xue Zhang
- Department of Geriatrics, Renmin Hospital of Wuhan University, Hubei Zhang Road (Formerly Ziyang Road), Wuchang District No. 99 Jiefang Road 238, Wuhan 430060, People's Republic of China
| | - Qiang Zhang
- College of Public Health, Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China
| | - Jing-Yang He
- College of Public Health, Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China
| | - Hui-Min Liu
- College of Public Health, Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China
| | - Xin Xia
- College of Public Health, Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China
| | - Kun Fan
- College of Public Health, Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China
| | - Qi Zhao
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA; Center for Genomics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Xue-Zhong Shi
- College of Public Health, Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China
| | - Wei-Dong Zhang
- College of Public Health, Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China
| | - Chang-Qing Sun
- College of Public Health, Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China
| | - Hong-Wen Deng
- College of Public Health, Zhengzhou University, No.100 Kexue Road, High-Tech Development Zone of States, Zhengzhou, People's Republic of China; Center for Genomics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA.
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Peng C, Shen J, Lin X, Su KJ, Greenbaum J, Zhu W, Lou HL, Liu F, Zeng CP, Deng WF, Deng HW. Genetic sharing with coronary artery disease identifies potential novel loci for bone mineral density. Bone 2017; 103:70-77. [PMID: 28651948 PMCID: PMC5796548 DOI: 10.1016/j.bone.2017.06.016] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/10/2017] [Revised: 06/21/2017] [Accepted: 06/22/2017] [Indexed: 12/30/2022]
Abstract
Bone mineral density (BMD) is a complex trait with high missing heritability. Numerous evidences have shown that BMD variation has a relationship with coronary artery disease (CAD). This relationship may come from a common genetic basis called pleiotropy. By leveraging the pleiotropy with CAD, we may be able to improve the detection power of genetic variants associated with BMD. Using a recently developed conditional false discovery rate (cFDR) method, we jointly analyzed summary statistics from two large independent genome wide association studies (GWAS) of lumbar spine (LS) BMD and CAD. Strong pleiotropic enrichment and 7 pleiotropic SNPs were found for the two traits. We identified 41 SNPs for LS BMD (cFDR<0.05), of which 20 were replications of previous GWASs and 21 were potential novel SNPs that were not reported before. Four genes encompassed by 9 cFDR-significant SNPs were partially validated in the gene expression assay. Further functional enrichment analysis showed that genes corresponding to the cFDR-significant LS BMD SNPs were enriched in GO terms and KEGG pathways that played crucial roles in bone metabolism (adjP<0.05). In protein-protein interaction analysis, strong interactions were found between the proteins produced by the corresponding genes. Our study demonstrated the reliability and high-efficiency of the cFDR method on the detection of trait-associated genetic variants, the present findings shed novel insights into the genetic variability of BMD as well as the shared genetic basis underlying osteoporosis and CAD.
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Affiliation(s)
- Cheng Peng
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, China; Department of Geriatrics, National Key Clinical Specialty, Guangzhou First People's Hospital, Guangzhou Medical University, 510180, China
| | - Jie Shen
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, China
| | - Xu Lin
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, China
| | - Kuan-Jui Su
- Center for Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, Tulane University, New Orleans, LA, USA
| | - Jonathan Greenbaum
- Center for Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, Tulane University, New Orleans, LA, USA
| | - Wei Zhu
- Center for Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, Tulane University, New Orleans, LA, USA
| | - Hui-Ling Lou
- Department of Geriatrics, National Key Clinical Specialty, Guangzhou First People's Hospital, Guangzhou Medical University, 510180, China
| | - Feng Liu
- Department of Geriatrics, National Key Clinical Specialty, Guangzhou First People's Hospital, Guangzhou Medical University, 510180, China
| | - Chun-Ping Zeng
- Department of Endocrinology and Metabolism, Affiliated Nanhai Hospital of Southern Medical University, Guangzhou, China
| | | | - Hong-Wen Deng
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, China; Center for Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, Tulane University, New Orleans, LA, USA.
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Identification of novel genetic loci for osteoporosis and/or rheumatoid arthritis using cFDR approach. PLoS One 2017; 12:e0183842. [PMID: 28854271 PMCID: PMC5576737 DOI: 10.1371/journal.pone.0183842] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Accepted: 08/12/2017] [Indexed: 12/19/2022] Open
Abstract
There are co-morbidity between osteoporosis (OP) and rheumatoid arthritis (RA). Some genetic risk factors have been identified for these two phenotypes respectively in previous research; however, they accounted for only a small portion of the underlying total genetic variances. Here, we sought to identify additional common genetic loci associated with OP and/or RA. The conditional false discovery rate (cFDR) approach allows detection of additional genetic factors (those respective ones as well as common pleiotropic ones) for the two associated phenotypes. We collected and analyzed summary statistics provided by large, multi-center GWAS studies of FNK (femoral neck) BMD (a major risk factor for osteoporosis) (n = 53,236) and RA (n = 80,799). The conditional quantile-quantile (Q-Q) plots can assess the enrichment of SNPs related to FNK BMD and RA, respectively. Furthermore, we identified shared loci between FNK BMD and RA using conjunction cFDR (ccFDR). We found strong enrichment of p-values in FNK BMD when conditional Q-Q was done on RA and vice versa. We identified 30 novel OP-RA associated pleiotropic loci that have not been reported in previous OP or RA GWAS, 18 of which located in the MHC (major histocompatibility complex) region previously reported to play an important role in immune system and bone health. We identified some specific novel polygenic factors for OP and RA respectively, and identified 30 novel OP-RA associated pleiotropic loci. These discovery findings may offer novel pathobiological insights, and suggest new targets and pathways for drug development in OP and RA patients.
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Wang XF, Lin X, Li DY, Zhou R, Greenbaum J, Chen YC, Zeng CP, Peng LP, Wu KH, Ao ZX, Lu JM, Guo YF, Shen J, Deng HW. Linking Alzheimer's disease and type 2 diabetes: Novel shared susceptibility genes detected by cFDR approach. J Neurol Sci 2017; 380:262-272. [PMID: 28870582 DOI: 10.1016/j.jns.2017.07.044] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2017] [Revised: 06/29/2017] [Accepted: 07/28/2017] [Indexed: 02/08/2023]
Abstract
BACKGROUND Both type 2 diabetes (T2D) and Alzheimer's disease (AD) occur commonly in the aging populations and T2D has been considered as an important risk factor for AD. The heritability of both diseases is estimated to be over 50%. However, common pleiotropic single-nucleotide polymorphisms (SNPs)/loci have not been well-defined. The aim of this study is to analyze two large public accessible GWAS datasets to identify novel common genetic loci for T2D and/or AD. METHODS AND MATERIALS The recently developed novel conditional false discovery rate (cFDR) approach was used to analyze the summary GWAS datasets from International Genomics of Alzheimer's Project (IGAP) and Diabetes Genetics Replication And Meta-analysis (DIAGRAM) to identify novel susceptibility genes for AD and T2D. RESULTS We identified 78 SNPs (including 58 novel SNPs) that were associated with AD in Europeans conditional on T2D (cFDR<0.05). 66 T2D SNPs (including 40 novel SNPs) were identified by conditioning on SNPs association with AD (cFDR<0.05). A conjunction-cFDR (ccFDR) analysis detected 8 pleiotropic SNPs with a significance threshold of ccFDR<0.05 for both AD and T2D, of which 5 SNPs (rs6982393, rs4734295, rs7812465, rs10510109, rs2421016) were novel findings. Furthermore, among the 8 SNPs annotated at 6 different genes, 3 corresponding genes TP53INP1, TOMM40 and C8orf38 were related to mitochondrial dysfunction, critically involved in oxidative stress, which potentially contribute to the etiology of both AD and T2D. CONCLUSION Our study provided evidence for shared genetic loci between T2D and AD in European subjects by using cFDR and ccFDR analyses. These results may provide novel insight into the etiology and potential therapeutic targets of T2D and/or AD.
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Affiliation(s)
- Xia-Fang Wang
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, PR China
| | - Xu Lin
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, PR China
| | - Ding-You Li
- Department of Gastroenterology, Children's Mercy Kansas City, University of Missouri Kansas City School of Medicine, Kansas City MO 64108, USA
| | - Rou Zhou
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, PR China
| | - Jonathan Greenbaum
- Center for Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Yuan-Cheng Chen
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, PR China
| | - Chun-Ping Zeng
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, PR China
| | - Lin-Ping Peng
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, PR China
| | - Ke-Hao Wu
- Center for Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA
| | - Zeng-Xin Ao
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, PR China
| | - Jun-Min Lu
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, PR China
| | - Yan-Fang Guo
- Institute of Bioinformatics, School of Basic Medical Science, Southern Medical University, Guangzhou, Guangdong 510515, PR China
| | - Jie Shen
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, PR China
| | - Hong-Wen Deng
- Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou 510630, PR China; Center for Bioinformatics and Genomics, Department of Global Biostatistics and Data Science, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA.
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