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Bosman W, Franken GAC, de Las Heras J, Madariaga L, Barakat TS, Oostenbrink R, van Slegtenhorst M, Perdomo-Ramírez A, Claverie-Martín F, van Eerde AM, Vargas-Poussou R, Dubourg LD, González-Recio I, Martínez-Cruz LA, de Baaij JHF, Hoenderop JGJ. Hypomagnesaemia with varying degrees of extrarenal symptoms as a consequence of heterozygous CNNM2 variants. Sci Rep 2024; 14:6917. [PMID: 38519529 PMCID: PMC10959950 DOI: 10.1038/s41598-024-57061-7] [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: 08/03/2023] [Accepted: 03/14/2024] [Indexed: 03/25/2024] Open
Abstract
Variants in the CNNM2 gene are causative for hypomagnesaemia, seizures and intellectual disability, although the phenotypes can be variable. This study aims to understand the genotype-phenotype relationship in affected individuals with CNNM2 variants by phenotypic, functional and structural analysis of new as well as previously reported variants. This results in the identification of seven variants that significantly affect CNNM2-mediated Mg2+ transport. Pathogenicity of these variants is further supported by structural modelling, which predicts CNNM2 structure to be affected by all of them. Strikingly, seizures and intellectual disability are absent in 4 out of 7 cases, indicating these phenotypes are caused either by specific CNNM2 variant only or by additional risk factors. Moreover, in line with sporadic observations from previous reports, CNNM2 variants might be associated with disturbances in parathyroid hormone and Ca2+ homeostasis.
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Affiliation(s)
- Willem Bosman
- Department of Medical BioSciences, Radboudumc, Nijmegen, The Netherlands
| | - Gijs A C Franken
- Department of Medical BioSciences, Radboudumc, Nijmegen, The Netherlands
| | - Javier de Las Heras
- Division of Pediatric Metabolism, Cruces University Hospital, CIBER-ER, Metab-ERN, University of the Basque Country (UPV/EHU), Biobizkaia Health Research Institute, Barakaldo, Spain
| | - Leire Madariaga
- Pediatric Nephrology Department, Cruces University Hospital, CIBERDEM, CIBER-ER, Endo-ERN, Biocruces Bizkaia Health Research Institute and University of the Basque Country (UPV/EHU), Barakaldo, Spain
| | - Tahsin Stefan Barakat
- Deparment of Clinical Genetics, Erasmus MC, Rotterdam, The Netherlands
- Discovery Unit, Department of Clinical Genetics, Erasmus MC, Rotterdam, The Netherlands
- ENCORE Expertise Center for Neurodevelopmental Disorders, Erasmus MC, Rotterdam, The Netherlands
| | - Rianne Oostenbrink
- ENCORE Expertise Center for Neurodevelopmental Disorders, Erasmus MC, Rotterdam, The Netherlands
- Department of General Pediatrics, Erasmus Medical Center Sophia Children's Hospital, Rotterdam, The Netherlands
| | | | - Ana Perdomo-Ramírez
- Unidad de Investigación, Renal Tube Group, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
| | - Félix Claverie-Martín
- Unidad de Investigación, Renal Tube Group, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
| | | | - Rosa Vargas-Poussou
- Service de medecine genomique des maladies rares, AP-HP, universite Paris Cité, Paris, France
- Centre de reference des maladies renales hereditaires de l'enfant et de l'adulte MARHEA, hopital Européen Georges Pompidou, Paris, France
- CNRS, centre de recherche des Cordeliers, Inserm UMRS 1138, Sorbonne universite, universite Paris Cité, Paris, France
| | - Laurence Derain Dubourg
- Hôpital Édouard Herriot, Hospices civils de Lyon, service de nephrologie, dialyse, hypertension et exploration fonctionnelle renale, Lyon, France
- Centre de reference des maladies renales rares et phosphocalciques, Nephrogones, Hôpital Femme-Mère-Enfant Bron, Bron, France
- Faculté de medecine Lyon est, Université Claude Bernard Lyon 1, Villeurbanne, France
| | - Irene González-Recio
- Center for Cooperative Research in Biosciences (CIC bioGUNE), Bizkaia Science and Technology Park, Derio, Bizkaia, Spain
| | - Luis Alfonso Martínez-Cruz
- Center for Cooperative Research in Biosciences (CIC bioGUNE), Bizkaia Science and Technology Park, Derio, Bizkaia, Spain
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2
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Carmo-Silva S, Ferreira-Marques M, Nóbrega C, Botelho M, Costa D, Aveleira CA, Pulst SM, Pereira de Almeida L, Cavadas C. Ataxin-2 in the hypothalamus at the crossroads between metabolism and clock genes. J Mol Endocrinol 2023; 70:JME-21-0272. [PMID: 36103139 DOI: 10.1530/jme-21-0272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2022] [Accepted: 09/14/2022] [Indexed: 01/19/2023]
Abstract
ATXN2 gene, encoding for ataxin-2, is located in a trait locus for obesity. Atxn2 knockout (KO) mice are obese and insulin resistant; however, the cause for this phenotype is still unknown. Moreover, several findings suggest ataxin-2 as a metabolic regulator, but the role of this protein in the hypothalamus was never studied before. The aim of this work was to understand if ataxin-2 modulation in the hypothalamus could play a role in metabolic regulation. Ataxin-2 was overexpressed/re-established in the hypothalamus of C57Bl6/Atxn2 KO mice fed either a chow or a high-fat diet (HFD). This delivery was achieved through stereotaxic injection of lentiviral vectors encoding for ataxin-2. We show, for the first time, that HFD decreases ataxin-2 levels in mouse hypothalamus and liver. Specific hypothalamic ataxin-2 overexpression prevents HFD-induced obesity and insulin resistance. Ataxin-2 re-establishment in Atxn2 KO mice improved metabolic dysfunction without changing body weight. Furthermore, we observed altered clock gene expression in Atxn2 KO that might be causative of metabolic dysfunction. Interestingly, ataxin-2 hypothalamic re-establishment rescued these circadian alterations. Thus, ataxin-2 in the hypothalamus is a determinant for weight, insulin sensitivity and clock gene expression. Ataxin-2's potential role in the circadian clock, through the regulation of clock genes, might be a relevant mechanism to regulate metabolism. Overall, this work shows hypothalamic ataxin-2 as a new player in metabolism regulation, which might contribute to the development of new strategies for metabolic disorders.
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Affiliation(s)
- Sara Carmo-Silva
- CNC-UC - Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
- CIBB - Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
- MIA - Multidisciplinary Institute of Ageing, University of Coimbra, Coimbra, Portugal
| | - Marisa Ferreira-Marques
- CNC-UC - Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
- CIBB - Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
- Faculty of Pharmacy, University of Coimbra, Coimbra, Portugal
| | - Clévio Nóbrega
- CNC-UC - Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
- ABC-RI, Algarve Biomedical Center Research Institute, Faro, Portugal
- Faculdade de Medicina e Ciências Biomédicas, Universidade do Algarve, Faro, Portugal
| | - Mariana Botelho
- CNC-UC - Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
| | - Daniela Costa
- CNC-UC - Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
- CIBB - Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
- Faculty of Pharmacy, University of Coimbra, Coimbra, Portugal
| | - Célia A Aveleira
- CNC-UC - Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
- CIBB - Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
- MIA - Multidisciplinary Institute of Ageing, University of Coimbra, Coimbra, Portugal
| | - Stefan M Pulst
- Department of Neurology, University of Utah, Salt Lake City, Utah, USA
| | - Luís Pereira de Almeida
- CNC-UC - Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
- CIBB - Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
- Faculty of Pharmacy, University of Coimbra, Coimbra, Portugal
| | - Claudia Cavadas
- CNC-UC - Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal
- CIBB - Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
- Faculty of Pharmacy, University of Coimbra, Coimbra, Portugal
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Identification of potentially common loci between childhood obesity and coronary artery disease using pleiotropic approaches. Sci Rep 2022; 12:19513. [PMID: 36376549 PMCID: PMC9663585 DOI: 10.1038/s41598-022-24009-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 11/08/2022] [Indexed: 11/15/2022] Open
Abstract
Childhood obesity remains one of the most important issues in global health, which is implicated in many chronic diseases. Converging evidence suggests that a higher body mass index during childhood (CBMI) is significantly associated with increased coronary artery disease (CAD) susceptibility in adulthood, which may partly arise from the shared genetic determination. Despite genome-wide association studies (GWASs) have successfully identified some loci associated with CBMI and CAD individually, the genetic overlap and common biological mechanism between them remains largely unexplored. Here, relying on the results from the two large-scale GWASs (n = 35,668 for CBMI and n = 547,261 for CAD), linkage disequilibrium score regression (LDSC) was used to estimate the genetic correlation of CBMI and CAD in the first step. Then, we applied different pleiotropy-informed methods including conditional false discovery rate ([Formula: see text]) and genetic analysis incorporating pleiotropy and annotation (GPA) to detect potentially common loci for childhood obesity and CAD. By integrating the genetic information from the existing GWASs summary statistics, we found a significant positive genetic correlation ([Formula: see text] = 0.127, p = 2E-4) and strong pleiotropic enrichment between CBMI and CAD (LRT = 79.352, p = 5.2E-19). Importantly, 28 loci were simultaneously discovered to be associated with CBMI, and 13 of them were identified as potentially pleiotropic loci by [Formula: see text] and GPA. Those corresponding pleiotropic genes were enriched in trait-associated gene ontology (GO) terms "amino sugar catabolic process", "regulation of fat cell differentiation" and "synaptic transmission". Overall, the findings of the pleiotropic loci will help to further elucidate the common molecular mechanisms underlying the association of childhood obesity and CAD, and provide a theoretical direction for early disease prevention and potential therapeutic targets.
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Cataloging the potential SNPs (single nucleotide polymorphisms) associated with quantitative traits, viz. BMI (body mass index), IQ (intelligence quotient) and BP (blood pressure): an updated review. EGYPTIAN JOURNAL OF MEDICAL HUMAN GENETICS 2022. [DOI: 10.1186/s43042-022-00266-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Abstract
Background
Single nucleotide polymorphism (SNP) variants are abundant, persistent and widely distributed across the genome and are frequently linked to the development of genetic diseases. Identifying SNPs that underpin complex diseases can aid scientists in the discovery of disease-related genes by allowing for early detection, effective medication and eventually disease prevention.
Main body
Various SNP or polymorphism-based studies were used to categorize different SNPs potentially related to three quantitative traits: body mass index (BMI), intelligence quotient (IQ) and blood pressure, and then uncovered common SNPs for these three traits. We employed SNPedia, RefSNP Report, GWAS Catalog, Gene Cards (Data Bases), PubMed and Google Scholar search engines to find relevant material on SNPs associated with three quantitative traits. As a result, we detected three common SNPs for all three quantitative traits in global populations: SNP rs6265 of the BDNF gene on chromosome 11p14.1, SNP rs131070325 of the SL39A8 gene on chromosome 4p24 and SNP rs4680 of the COMT gene on chromosome 22q11.21.
Conclusion
In our review, we focused on the prevalent SNPs and gene expression activities that influence these three quantitative traits. These SNPs have been used to detect and map complex, common illnesses in communities for homogeneity testing and pharmacogenetic studies. High blood pressure, diabetes and heart disease, as well as BMI, schizophrenia and IQ, can all be predicted using common SNPs. Finally, the results of our work can be used to find common SNPs and genes that regulate these three quantitative features across the genome.
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Identification of PDXDC1 as a novel pleiotropic susceptibility locus shared between lumbar spine bone mineral density and birth weight. J Mol Med (Berl) 2022; 100:723-734. [PMID: 35314877 PMCID: PMC9110509 DOI: 10.1007/s00109-021-02165-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2021] [Revised: 10/13/2021] [Accepted: 11/04/2021] [Indexed: 02/04/2023]
Abstract
An increasing number of epidemiological studies have suggested that birth weight (BW) may be a determinant of bone health later in life, although the underlying genetic mechanism remains unclear. Here, we applied a pleiotropic conditional false discovery rate (cFDR) approach to the genome-wide association study (GWAS) summary statistics for lumbar spine bone mineral density (LS BMD) and BW, aiming to identify novel susceptibility variants shared between these two traits. We detected 5 novel potential pleiotropic loci which are located at or near 7 different genes (NTAN1, PDXDC1, CACNA1G, JAG1, FAT1P1, CCDC170, ESR1), among which PDXDC1 and FAT1P1 have not previously been linked to these phenotypes. To partially validate the findings, we demonstrated that the expression of PDXDC1 was dramatically reduced in ovariectomized (OVX) mice in comparison with sham-operated (SHAM) mice in both the growth plate and trabecula bone. Furthermore, immunohistochemistry assay with serial sections showed that both osteoclasts and osteoblasts express PDXDC1, supporting its potential role in bone metabolism. In conclusion, our study provides insights into some shared genetic mechanisms for BMD and BW as well as a novel potential therapeutic target for the prevention of OP in the early stages of the disease development. KEY MESSAGES : We investigated pleiotropy-informed enrichment between LS BMD and BW. We identified genetic variants related to both LS BMD and BW by utilizing a cFDR approach. PDXDC1 is a novel pleiotropic gene which may be related to both LS BMD and BW. Elevated expression of PDXDC1 is related to higher BMD and lower ratio n-6/n-3 PUFA indicating a bone protective effect of PDXDC1.
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Perry BI, Bowker N, Burgess S, Wareham NJ, Upthegrove R, Jones PB, Langenberg C, Khandaker GM. Evidence for Shared Genetic Aetiology Between Schizophrenia, Cardiometabolic, and Inflammation-Related Traits: Genetic Correlation and Colocalization Analyses. SCHIZOPHRENIA BULLETIN OPEN 2022; 3:sgac001. [PMID: 35156041 PMCID: PMC8827407 DOI: 10.1093/schizbullopen/sgac001] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
BACKGROUND Schizophrenia commonly co-occurs with cardiometabolic and inflammation-related traits. It is unclear to what extent the comorbidity could be explained by shared genetic aetiology. METHODS We used GWAS data to estimate shared genetic aetiology between schizophrenia, cardiometabolic, and inflammation-related traits: fasting insulin (FI), fasting glucose, glycated haemoglobin, glucose tolerance, type 2 diabetes (T2D), lipids, body mass index (BMI), coronary artery disease (CAD), and C-reactive protein (CRP). We examined genome-wide correlation using linkage disequilibrium score regression (LDSC); stratified by minor-allele frequency using genetic covariance analyzer (GNOVA); then refined to locus-level using heritability estimation from summary statistics (ρ-HESS). Regions with local correlation were used in hypothesis prioritization multi-trait colocalization to examine for colocalisation, implying common genetic aetiology. RESULTS We found evidence for weak genome-wide negative correlation of schizophrenia with T2D (rg = -0.07; 95% C.I., -0.03,0.12; P = .002) and BMI (rg = -0.09; 95% C.I., -0.06, -0.12; P = 1.83 × 10-5). We found a trend of evidence for positive genetic correlation between schizophrenia and cardiometabolic traits confined to lower-frequency variants. This was underpinned by 85 regions of locus-level correlation with evidence of opposing mechanisms. Ten loci showed strong evidence of colocalization. Four of those (rs6265 (BDNF); rs8192675 (SLC2A2); rs3800229 (FOXO3); rs17514846 (FURIN)) are implicated in brain-derived neurotrophic factor (BDNF)-related pathways. CONCLUSIONS LDSC may lead to downwardly-biased genetic correlation estimates between schizophrenia, cardiometabolic, and inflammation-related traits. Common genetic aetiology for these traits could be confined to lower-frequency common variants and involve opposing mechanisms. Genes related to BDNF and glucose transport amongst others may partly explain the comorbidity between schizophrenia and cardiometabolic disorders.
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Affiliation(s)
- Benjamin I Perry
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - Nicholas Bowker
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Rachel Upthegrove
- Institute for Mental Health, University of Birmingham, Birmingham, UK
| | - Peter B Jones
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Golam M Khandaker
- Department of Psychiatry, University of Cambridge School of Clinical Medicine, Cambridge, UK
- Cambridgeshire and Peterborough NHS Foundation Trust, Cambridge, UK
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Cyclin M2 (CNNM2) knockout mice show mild hypomagnesaemia and developmental defects. Sci Rep 2021; 11:8217. [PMID: 33859252 PMCID: PMC8050252 DOI: 10.1038/s41598-021-87548-6] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2020] [Accepted: 03/26/2021] [Indexed: 02/02/2023] Open
Abstract
Patients with mutations in Cyclin M2 (CNNM2) suffer from hypomagnesaemia, seizures, and intellectual disability. Although the molecular function of CNNM2 is under debate, the protein is considered essential for renal Mg2+ reabsorption. Here, we used a Cnnm2 knock out mouse model, generated by CRISPR/Cas9 technology, to assess the role of CNNM2 in Mg2+ homeostasis. Breeding Cnnm2+/- mice resulted in a Mendelian distribution at embryonic day 18. Nevertheless, only four Cnnm2-/- pups were born alive. The Cnnm2-/- pups had a significantly lower serum Mg2+ concentration compared to wildtype littermates. Subsequently, adult Cnnm2+/- mice were fed with low, control, or high Mg2+ diets for two weeks. Adult Cnnm2+/- mice showed mild hypomagnesaemia compared to Cnnm2+/+ mice and increased serum Ca2+ levels, independent of dietary Mg2+ intake. Faecal analysis displayed increased Mg2+ and Ca2+ excretion in the Cnnm2+/- mice. Transcriptional profiling of Trpm6, Trpm7, and Slc41a1 in kidneys and colon did not reveal effects based on genotype. Microcomputed tomography analysis of the femurs demonstrated equal bone morphology and density. In conclusion, CNNM2 is vital for embryonic development and Mg2+ homeostasis. Our data suggest a previously undescribed role of CNNM2 in the intestine, which may contribute to the Mg2+ deficiency in mice and patients.
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Long X, Xue H. Genetic-variant hotspots and hotspot clusters in the human genome facilitating adaptation while increasing instability. Hum Genomics 2021; 15:19. [PMID: 33741065 PMCID: PMC7976700 DOI: 10.1186/s40246-021-00318-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2020] [Accepted: 03/04/2021] [Indexed: 12/25/2022] Open
Abstract
Background Genetic variants, underlining phenotypic diversity, are known to distribute unevenly in the human genome. A comprehensive understanding of the distributions of different genetic variants is important for insights into genetic functions and disorders. Methods Herein, a sliding-window scan of regional densities of eight kinds of germline genetic variants, including single-nucleotide-polymorphisms (SNPs) and four size-classes of copy-number-variations (CNVs) in the human genome has been performed. Results The study has identified 44,379 hotspots with high genetic-variant densities, and 1135 hotspot clusters comprising more than one type of hotspots, accounting for 3.1% and 0.2% of the genome respectively. The hotspots and clusters are found to co-localize with different functional genomic features, as exemplified by the associations of hotspots of middle-size CNVs with histone-modification sites, work with balancing and positive selections to meet the need for diversity in immune proteins, and facilitate the development of sensory-perception and neuroactive ligand-receptor interaction pathways in the function-sparse late-replicating genomic sequences. Genetic variants of different lengths co-localize with retrotransposons of different ages on a “long-with-young” and “short-with-all” basis. Hotspots and clusters are highly associated with tumor suppressor genes and oncogenes (p < 10−10), and enriched with somatic tumor CNVs and the trait- and disease-associated SNPs identified by genome-wise association studies, exceeding tenfold enrichment in clusters comprising SNPs and extra-long CNVs. Conclusions In conclusion, the genetic-variant hotspots and clusters represent two-edged swords that spearhead both positive and negative genomic changes. Their strong associations with complex traits and diseases also open up a potential “Common Disease-Hotspot Variant” approach to the missing heritability problem. Supplementary Information The online version contains supplementary material available at 10.1186/s40246-021-00318-3.
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Affiliation(s)
- Xi Long
- Division of Life Science and Applied Genomics Centre, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China.,HKUST Shenzhen Research Institute, 9 Yuexing First Road, Nanshan, Shenzhen, China
| | - Hong Xue
- Division of Life Science and Applied Genomics Centre, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China. .,HKUST Shenzhen Research Institute, 9 Yuexing First Road, Nanshan, Shenzhen, China. .,Centre for Cancer Genomics, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, Jiangsu, China.
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9
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Lu H, Zhang J, Jiang Z, Zhang M, Wang T, Zhao H, Zeng P. Detection of Genetic Overlap Between Rheumatoid Arthritis and Systemic Lupus Erythematosus Using GWAS Summary Statistics. Front Genet 2021; 12:656545. [PMID: 33815486 PMCID: PMC8012913 DOI: 10.3389/fgene.2021.656545] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 03/01/2021] [Indexed: 01/04/2023] Open
Abstract
Background Clinical and epidemiological studies have suggested systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) are comorbidities and common genetic etiologies can partly explain such coexistence. However, shared genetic determinations underlying the two diseases remain largely unknown. Methods Our analysis relied on summary statistics available from genome-wide association studies of SLE (N = 23,210) and RA (N = 58,284). We first evaluated the genetic correlation between RA and SLE through the linkage disequilibrium score regression (LDSC). Then, we performed a multiple-tissue eQTL (expression quantitative trait loci) weighted integrative analysis for each of the two diseases and aggregated association evidence across these tissues via the recently proposed harmonic mean P-value (HMP) combination strategy, which can produce a single well-calibrated P-value for correlated test statistics. Afterwards, we conducted the pleiotropy-informed association using conjunction conditional FDR (ccFDR) to identify potential pleiotropic genes associated with both RA and SLE. Results We found there existed a significant positive genetic correlation (rg = 0.404, P = 6.01E-10) via LDSC between RA and SLE. Based on the multiple-tissue eQTL weighted integrative analysis and the HMP combination across various tissues, we discovered 14 potential pleiotropic genes by ccFDR, among which four were likely newly novel genes (i.e., INPP5B, OR5K2, RP11-2C24.5, and CTD-3105H18.4). The SNP effect sizes of these pleiotropic genes were typically positively dependent, with an average correlation of 0.579. Functionally, these genes were implicated in multiple auto-immune relevant pathways such as inositol phosphate metabolic process, membrane and glucagon signaling pathway. Conclusion This study reveals common genetic components between RA and SLE and provides candidate associated loci for understanding of molecular mechanism underlying the comorbidity of the two diseases.
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Affiliation(s)
- Haojie Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, China
| | - Jinhui Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, China
| | - Zhou Jiang
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, China
| | - Meng Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, China
| | - Ting Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, China.,Center for Medical Statistics and Data Analysis, School of Public Health, Xuzhou Medical University, Xuzhou, China
| | - Huashuo Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, China.,Center for Medical Statistics and Data Analysis, School of Public Health, Xuzhou Medical University, Xuzhou, China
| | - Ping Zeng
- Department of Epidemiology and Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, China.,Center for Medical Statistics and Data Analysis, School of Public Health, Xuzhou Medical University, Xuzhou, China
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Liley J, Wallace C. Accurate error control in high-dimensional association testing using conditional false discovery rates. Biom J 2021; 63:1096-1130. [PMID: 33682201 PMCID: PMC7612315 DOI: 10.1002/bimj.201900254] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2019] [Revised: 12/05/2020] [Accepted: 12/30/2020] [Indexed: 01/13/2023]
Abstract
High-dimensional hypothesis testing is ubiquitous in the biomedical sciences, and informative covariates may be employed to improve power. The conditional false discovery rate (cFDR) is a widely used approach suited to the setting where the covariate is a set of p-values for the equivalent hypotheses for a second trait. Although related to the Benjamini–Hochberg procedure, it does not permit any easy control of type-1 error rate and existing methods are over-conservative. We propose a newmethod for type-1 error rate control based on identifyingmappings from the unit square to the unit interval defined by the estimated cFDR and splitting observations so that each map is independent of the observations it is used to test. We also propose an adjustment to the existing cFDR estimator which further improves power. We show by simulation that the new method more than doubles potential improvement in power over unconditional analyses compared to existing methods. We demonstrate our method on transcriptome-wide association studies and show that the method can be used in an iterative way, enabling the use of multiple covariates successively. Our methods substantially improve the power and applicability of cFDR analysis.
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Affiliation(s)
- James Liley
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.,Department of Medicine, Addenbrookes Hospital, University of Cambridge, Cambridge, UK
| | - Chris Wallace
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK.,Department of Medicine, Addenbrookes Hospital, University of Cambridge, Cambridge, UK.,Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, UK
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Franken GAC, Müller D, Mignot C, Keren B, Lévy J, Tabet AC, Germanaud D, Tejada MI, Kroes HY, Nievelstein RAJ, Brimble E, Ruzhnikov M, Claverie-Martin F, Szczepańska M, Ćuk M, Latta F, Konrad M, Martínez-Cruz LA, Bindels RJM, Hoenderop JGJ, Schlingmann KP, de Baaij JHF. The phenotypic and genetic spectrum of patients with heterozygous mutations in cyclin M2 (CNNM2). Hum Mutat 2021; 42:473-486. [PMID: 33600043 PMCID: PMC8248058 DOI: 10.1002/humu.24182] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Revised: 02/05/2021] [Accepted: 02/10/2021] [Indexed: 12/21/2022]
Abstract
Hypomagnesemia, seizures, and intellectual disability (HSMR) syndrome is a rare disorder caused by mutations in the cyclin M2 (CNNM2) gene. Due to the limited number of cases, extensive phenotype analyses of these patients have not been performed, hindering early recognition of patients. In this study, we established the largest cohort of HSMR to date, aiming to improve recognition and diagnosis of this complex disorder. Eleven novel variants in CNNM2 were identified in nine single sporadic cases and in two families with suspected HSMR syndrome. 25Mg2+ uptake assays demonstrated loss‐of‐function in seven out of nine variants in CNNM2. Interestingly, the pathogenic mutations resulted in decreased plasma membrane expression. The phenotype of those affected by pathogenic CNNM2 mutations was compared with five previously reported cases of HSMR. All patients suffered from hypomagnesemia (0.44–0.72 mmol/L), which could not be fully corrected by Mg2+ supplementation. The majority of patients (77%) experienced generalized seizures and exhibited mild to moderate intellectual disability and speech delay. Moreover, severe obesity was present in most patients (89%). Our data establish hypomagnesemia, seizures, intellectual disability, and obesity as hallmarks of HSMR syndrome. The assessment of these major features offers a straightforward tool for the clinical diagnosis of HSMR.
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Affiliation(s)
- Gijs A C Franken
- Department of Physiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Dominik Müller
- Department of Pediatric Gastroenterology, Nephrology and Metabolism, Charité Universitäts Medizin, Berlin, Germany
| | - Cyril Mignot
- Département de Genetique, Centre de Référence Déficiences Intellectuelles de Causes Rares, Assistance Publique Hôpitaux de Paris, Paris, France
| | - Boris Keren
- Département de Génétique, Groupe Hospitalier, Pitié-Salpêtrière, Assistance Publique Hôpitaux de Paris, Paris, France
| | - Jonathan Lévy
- Genetics Department, AP-HP, Robert-Debré University Hospital, Paris, France
| | - Anne-Claude Tabet
- Genetics Department, AP-HP, Robert-Debré University Hospital, Paris, France
| | - David Germanaud
- Pediatric Neurology Department, Centre de Référence Déficiences Intellectuelles de Causes Rares, Service de Neurologie Pédiatrique, Hôpital Robert-Debré, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - María-Isabel Tejada
- Osakidetza Basque Health Service, Cruces University Hospital, Genetics Service and Biocruces Bizkaia Health Research Institute, Barakaldo, Spain.,Spanish Consortium for Research on Rare Diseases (CIBERER), Valencia, Spain
| | - Hester Y Kroes
- Department of Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Rutger A J Nievelstein
- Department of Pediatric Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Elise Brimble
- Department of Neurology and Neurological Sciences, Stanford Medicine, Stanford, California, USA
| | - Maria Ruzhnikov
- Department of Neurology and Neurological Sciences, Stanford Medicine, Stanford, California, USA
| | - Felix Claverie-Martin
- Unidad de Investigación, Hospital Universitario Nuestra Señora de Candelaria, Santa Cruz de Tenerife, Spain
| | - Maria Szczepańska
- Department of Pediatrics, Medical University of Silesia, Katowice, Poland
| | - Martin Ćuk
- Department of Pediatrics, Children's Hospital Zagreb, Zagreb, Croatia
| | - Femke Latta
- Department of Physiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Martin Konrad
- Department of General Pediatrics, University Children's Hospital, Münster, Germany
| | - Luis A Martínez-Cruz
- Structural Biology Unit, Center for Cooperative Research in Biosciences (CIC bioGUNE), Technology Park of Bizkaia, Derio, Spain
| | - René J M Bindels
- Department of Physiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Joost G J Hoenderop
- Department of Physiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Jeroen H F de Baaij
- Department of Physiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
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12
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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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13
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He P, Meng XH, Zhang X, Lin X, Zhang Q, Jiang RL, Schiller MR, Deng FY, Deng HW. Identifying Pleiotropic SNPs Associated With Femoral Neck and Heel Bone Mineral Density. Front Genet 2020; 11:772. [PMID: 32774344 PMCID: PMC7388689 DOI: 10.3389/fgene.2020.00772] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2020] [Accepted: 06/29/2020] [Indexed: 01/06/2023] Open
Abstract
Background Genome-wide association studies (GWASs) routinely identify loci associated with risk factors for osteoporosis. However, GWASs with relatively small sample sizes still lack sufficient power to ascertain the majority of genetic variants with small to modest effect size, which may together truly influence the phenotype. The loci identified only account for a small percentage of the heritability of osteoporosis. This study aims to identify novel genetic loci associated with DXA-derived femoral neck (FNK) bone mineral density (BMD) and quantitative ultrasound of the heel calcaneus estimated BMD (eBMD), and to detect shared/causal variants for the two traits, to assess whether the SNPs or putative causal SNPs associated with eBMD were also associated with FNK-BMD. Methods Novel loci associated with eBMD and FNK-BMD were identified by the genetic pleiotropic conditional false discovery rate (cFDR) method. Shared putative causal variants between eBMD and FNK-BMD and putative causal SNPs for each trait were identified by the colocalization method. Mendelian randomization analysis addresses the causal relationship between eBMD/FNK-BMD and fracture. Results We identified 9,500 (cFDR < 9.8E-6), 137 (cFDR < 8.9E-4) and 124 SNPs associated with eBMD, FNK-BMD, and both eBMD and FNK-BMD, respectively, with 37 genomic regions where there was a SNP that influences both eBMD and FNK-BMD. Most genomic regions only contained putative causal SNPs associated with eBMD and 3 regions contained two distinct putative causal SNPs influenced both traits, respectively. We demonstrated a causal effect of FNK-BMD/eBMD on fracture. Conclusion Most of SNPs or putative causal SNPs associated with FNK-BMD were also associated with eBMD. However, most of SNPs or putative causal SNPs associated with eBMD were not associated with FNK-BMD. The novel variants we identified may help to account for the additional proportion of variance of each trait and advance our understanding of the genetic mechanisms underlying osteoporotic fracture.
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Affiliation(s)
- Pei He
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, China.,Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States
| | - Xiang-He Meng
- Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States.,Center of Reproductive Health, System Biology and Data Information, School of Basic Medical Science, Central South University, Changsha, China.,Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, China
| | - Xiao Zhang
- Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States
| | - Xu Lin
- Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States.,Department of Endocrinology and Metabolism, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China
| | - Qiang Zhang
- Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States.,College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Ri-Li Jiang
- Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States
| | - Martin R Schiller
- Nevada Institute of Personalized Medicine, School of Life Sciences, University of Nevada, Las Vegas, Las Vegas, NV, United States
| | - Fei-Yan Deng
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, China
| | - Hong-Wen Deng
- Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States.,Center of Reproductive Health, System Biology and Data Information, School of Basic Medical Science, Central South University, Changsha, China.,Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, China
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14
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Aguilar Aldrete ME, López-Toledo S, Caballero Avendaño A, Villa Ruano N, Navarro Hernández RE, Flores Alvarado LJ, Keita H, Guzmán Lopez R, Ramírez Sánchez JC, Ramírez García SA. Association between nutritional risk markers and polymorphisms rs2291166 in TJP1 and VNTR (CAG)n in ATXN2 in an obese adolescent Mexican population. ACTA ACUST UNITED AC 2020; 68:99-108. [PMID: 32593738 DOI: 10.1016/j.endinu.2020.02.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2019] [Revised: 02/11/2020] [Accepted: 02/14/2020] [Indexed: 12/15/2022]
Abstract
OBJECTIVE To estimate the correlation between indices of diet quality (DQIs), insulin sensitivity (QUICKI) and resistance (HOMA-IR), waist circumference (WHR) and body mass (BMI) and the alleles and genotypes of the TJP1 SNP rs2291166 and the VNTR of ATXN2 in adolescent patients. SUBJECTS AND METHOD The study enrolled 85 subjects aged 10-20years, from the city of Tuxtepec, Oaxaca, Mexico, recruited in the period 2017-2018. DQIs, BMI, WHR, HOMA-IR, QUICKI, and diet quality index were measured. The rs2291166 polymorphism in TJP1 was determined by allele-specific PCR and the (CAG)n expansion in ATXN2 was determined by hot start PCR. PCR products were analyzed using 8% PAGE electrophoresis and silver nitrate staining. RESULTS A correlation was found of indices DQIs, HOMA-IR, WHR and BMI with the heterozygous genotype of the TJP1 SNP rs2291166 and the long and short repeats of the ATXN2 CAG repeat in obese adolescent patients. A very strong positive correlation was seen between the TJP1 SNP and the HOMA-IR index (P<.05). A positive correlation was also found between the ATXN2 CAG repeat and the QUICKI index (P=.000) (P<.05), while the DQIs index correlated more closely with BMI and WHR. CONCLUSIONS DQIs, TJP1 SNP rs2291166, and ATXN2 CAG repeat are determinants of obesity-related risk parameters such as BMI, WHR, QUICKI, and HOMA-IR in the adolescent population analyzed.
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Affiliation(s)
| | | | | | - Nemesio Villa Ruano
- Centro de Transferencia Tecnológica, Benemérita Universidad Autónoma de Puebla, Puebla, Puebla, México
| | - Rosa Elena Navarro Hernández
- Instituto de Investigación en Reumatología y del Sistema Músculo Esquelético, Universidad de Guadalajara, Guadalajara, Jalisco, México
| | | | - Hady Keita
- Instituto de Salud Pública, Universidad de la Sierra Sur, Miahuatlán de Porfirio Díaz, Oaxaca, México
| | - Rufina Guzmán Lopez
- Departamento de Nutrición, Universidad de la Sierra Sur, Miahuatlán de Porfirio Díaz, Oaxaca, México
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15
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Tang J, Mou M, Wang Y, Luo Y, Zhu F. MetaFS: Performance assessment of biomarker discovery in metaproteomics. Brief Bioinform 2020; 22:5854399. [PMID: 32510556 DOI: 10.1093/bib/bbaa105] [Citation(s) in RCA: 63] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2020] [Revised: 04/17/2020] [Accepted: 05/05/2020] [Indexed: 12/19/2022] Open
Abstract
Metaproteomics suffers from the issues of dimensionality and sparsity. Data reduction methods can maximally identify the relevant subset of significant differential features and reduce data redundancy. Feature selection (FS) methods were applied to obtain the significant differential subset. So far, a variety of feature selection methods have been developed for metaproteomic study. However, due to FS's performance depended heavily on the data characteristics of a given research, the well-suitable feature selection method must be carefully selected to obtain the reproducible differential proteins. Moreover, it is critical to evaluate the performance of each FS method according to comprehensive criteria, because the single criterion is not sufficient to reflect the overall performance of the FS method. Therefore, we developed an online tool named MetaFS, which provided 13 types of FS methods and conducted the comprehensive evaluation on the complex FS methods using four widely accepted and independent criteria. Furthermore, the function and reliability of MetaFS were systematically tested and validated via two case studies. In sum, MetaFS could be a distinguished tool for discovering the overall well-performed FS method for selecting the potential biomarkers in microbiome studies. The online tool is freely available at https://idrblab.org/metafs/.
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16
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Trifonova EA, Popovich AA, Bocharova AV, Vagaitseva KV, Stepanov VA. The Role of Natural Selection in the Formation of the Genetic Structure of Populations by SNP Markers in Association with Body Mass Index and Obesity. Mol Biol 2020. [DOI: 10.1134/s0026893320030176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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17
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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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18
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Jia X, Shi N, Feng Y, Li Y, Tan J, Xu F, Wang W, Sun C, Deng H, Yang Y, Shi X. Identification of 67 Pleiotropic Genes Associated With Seven Autoimmune/Autoinflammatory Diseases Using Multivariate Statistical Analysis. Front Immunol 2020; 11:30. [PMID: 32117227 PMCID: PMC7008725 DOI: 10.3389/fimmu.2020.00030] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Accepted: 01/08/2020] [Indexed: 12/19/2022] Open
Abstract
Although genome-wide association studies (GWAS) have a dramatic impact on susceptibility locus discovery, this univariate approach has limitations in detecting complex genotype-phenotype correlations. Multivariate analysis is essential to identify shared genetic risk factors acting through common biological mechanisms of autoimmune/autoinflammatory diseases. In this study, GWAS summary statistics, including 41,274 single nucleotide polymorphisms (SNPs) located in 11,516 gene regions, were analyzed to identify shared variants of seven autoimmune/autoinflammatory diseases using the metaCCA method. Gene-based association analysis was used to refine the pleiotropic genes. In addition, GO term enrichment analysis and protein-protein interaction network analysis were applied to explore the potential biological functions of the identified genes. A total of 4,962 SNPs (P < 1.21 × 10-6) and 1,044 pleotropic genes (P < 4.34 × 10-6) were identified by metaCCA analysis. By screening the results of gene-based P-values, we identified the existence of 27 confirmed pleiotropic genes and highlighted 40 novel pleiotropic genes that achieved statistical significance in the metaCCA analysis and were also associated with at least one autoimmune/autoinflammatory in the VEGAS2 analysis. Using the metaCCA method, we identified novel variants associated with complex diseases incorporating different GWAS datasets. Our analysis may provide insights for the development of common therapeutic approaches for autoimmune/autoinflammatory diseases based on the pleiotropic genes and common mechanisms identified.
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Affiliation(s)
- Xiaocan Jia
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Nian Shi
- Department of Physical Diagnosis, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Yu Feng
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Yifan Li
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Jiebing Tan
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Fei Xu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Wei Wang
- Department of Occupational and Environmental Health, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Changqing Sun
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Hongwen Deng
- Center for Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, United States
| | - Yongli Yang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
| | - Xuezhong Shi
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, China
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19
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Smeland OB, Frei O, Shadrin A, O'Connell K, Fan CC, Bahrami S, Holland D, Djurovic S, Thompson WK, Dale AM, Andreassen OA. Discovery of shared genomic loci using the conditional false discovery rate approach. Hum Genet 2019; 139:85-94. [PMID: 31520123 DOI: 10.1007/s00439-019-02060-2] [Citation(s) in RCA: 92] [Impact Index Per Article: 18.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Accepted: 08/08/2019] [Indexed: 02/07/2023]
Abstract
In recent years, genome-wide association study (GWAS) sample sizes have become larger, the statistical power has improved and thousands of trait-associated variants have been uncovered, offering new insights into the genetic etiology of complex human traits and disorders. However, a large fraction of the polygenic architecture underlying most complex phenotypes still remains undetected. We here review the conditional false discovery rate (condFDR) method, a model-free strategy for analysis of GWAS summary data, which has improved yield of existing GWAS and provided novel findings of genetic overlap between a wide range of complex human phenotypes, including psychiatric, cardiovascular, and neurological disorders, as well as psychological and cognitive traits. The condFDR method was inspired by Empirical Bayes approaches and leverages auxiliary genetic information to improve statistical power for discovery of single-nucleotide polymorphisms (SNPs). The cross-trait condFDR strategy analyses separate GWAS data, and leverages overlapping SNP associations, i.e., cross-trait enrichment, to increase discovery of trait-associated SNPs. The extension of the condFDR approach to conjunctional FDR (conjFDR) identifies shared genomic loci between two phenotypes. The conjFDR approach allows for detection of shared genomic associations irrespective of the genetic correlation between the phenotypes, often revealing a mixture of antagonistic and agonistic directional effects among the shared loci. This review provides a methodological comparison between condFDR and other relevant cross-trait analytical tools and demonstrates how condFDR analysis may provide novel insights into the genetic relationship between complex phenotypes.
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Affiliation(s)
- Olav B Smeland
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway.
| | - Oleksandr Frei
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway
| | - Alexey Shadrin
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway
| | - Kevin O'Connell
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway
| | - Chun-Chieh Fan
- Department of Cognitive Science, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.,Department of Radiology, University of California of San Diego, La Jolla, San Diego, CA, 92093, USA
| | - Shahram Bahrami
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway
| | - Dominic Holland
- Department of Radiology, University of California of San Diego, La Jolla, San Diego, CA, 92093, USA.,Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.,Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, San Diego, CA, 92037, USA
| | - Srdjan Djurovic
- Department of Medical Genetics, Oslo University Hospital, Oslo, Norway.,NORMENT Centre, Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Wesley K Thompson
- Department of Family Medicine and Public Health, University of California San Diego, La Jolla, San Diego, CA, 92093, USA
| | - Anders M Dale
- Department of Cognitive Science, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.,Department of Radiology, University of California of San Diego, La Jolla, San Diego, CA, 92093, USA.,Department of Neuroscience, University of California San Diego, La Jolla, San Diego, CA, 92093, USA.,Center for Multimodal Imaging and Genetics, University of California San Diego, La Jolla, San Diego, CA, 92037, USA
| | - Ole A Andreassen
- NORMENT Centre, Division of Mental Health and Addiction, Oslo University Hospital and Institute of Clinical Medicine, University of Oslo, Kirkeveien 166, 0424, Oslo, Norway.
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20
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Jia X, Yang Y, Chen Y, Xia Z, Zhang W, Feng Y, Li Y, Tan J, Xu C, Zhang Q, Deng H, Shi X. Multivariate analysis of genome-wide data to identify potential pleiotropic genes for type 2 diabetes, obesity and coronary artery disease using MetaCCA. Int J Cardiol 2019; 283:144-150. [DOI: 10.1016/j.ijcard.2018.10.102] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2018] [Revised: 10/17/2018] [Accepted: 10/29/2018] [Indexed: 01/26/2023]
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21
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Current Structural Knowledge on the CNNM Family of Magnesium Transport Mediators. Int J Mol Sci 2019; 20:ijms20051135. [PMID: 30845649 PMCID: PMC6429129 DOI: 10.3390/ijms20051135] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Revised: 02/28/2019] [Accepted: 03/01/2019] [Indexed: 02/06/2023] Open
Abstract
The cyclin and cystathionine β-synthase (CBS) domain magnesium transport mediators, CNNMs, are key players in maintaining the homeostasis of magnesium in different organs. The human family includes four members, whose impaired activity causes diseases such as Jalili Syndrome or Familial Hypomagnesemia, but is also linked to neuropathologic disorders, altered blood pressure, and infertility. Recent findings demonstrated that CNNMs are associated with the highly oncogenic phosphatases of the regenerating liver to promote tumor growth and metastasis, which has attracted renewed focus on their potential exploitation as targets for cancer treatment. However, the exact function of CNNMs remains unclear and is subject to debate, proposed as either direct transporters, sensors, or homeostatic factors. This review gathers the current structural knowledge on the CNNM family, highlighting similarities and differences with the closely related structural partners such as the bacterial Mg2+/Co2+ efflux protein CorC and the Mg2+ channel MgtE.
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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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Au Yeung SL, Schooling CM. Adiponectin and coronary artery disease risk: A bi-directional Mendelian randomization study. Int J Cardiol 2018; 268:222-226. [DOI: 10.1016/j.ijcard.2018.03.132] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Revised: 03/01/2018] [Accepted: 03/28/2018] [Indexed: 02/04/2023]
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Genetically driven adiposity traits increase the risk of coronary artery disease independent of blood pressure, dyslipidaemia, glycaemic traits. Eur J Hum Genet 2018; 26:1547-1553. [PMID: 29891878 DOI: 10.1038/s41431-018-0180-9] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2017] [Revised: 04/30/2018] [Accepted: 05/08/2018] [Indexed: 12/14/2022] Open
Abstract
Adiposity has been associated with the risk of coronary artery disease (CAD) in observational studies, but their association may differ according to specific characteristics of studies. In Mendelian randomization (MR) analyses, genetic variants are used as instrumental variables (IVs) of exposures to examine causal effects to overcome confounding factors and reverse causation. We performed MR analyses for adiposity (n = 322,154) on risk of CAD (60,801 cases and 123,504 controls) based on the currently largest genome-wide association studies. The estimated associations between adiposity traits and CAD were calculated by an inverse-variance weighted method with and without excluding the IVs, which are associated with the well-known risk factors of CAD. Genetic variants are identified to be associated with the well-known risk factors of CAD by a cross-phenotype meta-analysis method. Our results furnished strong evidence for a causal role of adiposity in risk of CAD, with the odds ratios (ORs) for CAD being 1.53 (95% CI 1.36-1.72) for body mass index (BMI), 1.48 (1.20-1.96) for waist-hip ratio (WHR), and 1.34 (1.07-1.59) for WHR adjusted for BMI (WHRadjBMI), respectively. After excluding mediators-associated IVs from the MR analyses, the corresponding ORs were 1.46 (1.28-1.67) for BMI, 1.39 (1.01-1.93) for WHR, and 1.38 (1.04-1.84) for WHRadjBMI, respectively. Furthermore, our results suggested that central adiposity and general adiposity might pose a similar risk for CAD. In summary, our data supported that genetically driven adiposity traits imposed the risk of CAD independent of blood pressure, dyslipidaemia, glycaemic traits, and type 2 diabetes.
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Assessing causal estimates of the association of obesity-related traits with coronary artery disease using a Mendelian randomization approach. Sci Rep 2018; 8:7146. [PMID: 29739994 PMCID: PMC5940685 DOI: 10.1038/s41598-018-25305-y] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Accepted: 04/11/2018] [Indexed: 12/21/2022] Open
Abstract
Obesity-related traits have been associated with coronary artery disease (CAD) in observational studies, but these associations may be biased by confounding factors and reverse causation. In this study, we specifically conducted two-sample Mendelian randomization (MR) analyses to overcome these limitations and test the associations of obesity-related traits (other than body mass index (BMI)) (n = 322,154) with CAD (22,233 cases and 64,762 controls) by using summary-level data from previous studies. The methods utilized to estimate these associations included the inverse-variance weighted method, the weighted median method and MR-Egger regression. Our results supported causal effects of BMI, hip circumference (HC), waist circumference (WC), and waist-hip ratio (WHR) on CAD. The associations of BMI-adjusted HC and WC with CAD were reversed, unlike that of WHR. In MR analyses excluding overlapping single nucleotide polymorphisms (SNPs) from obesity-related traits, the associations of these traits with CAD were preserved. The associations of BMI-adjusted HC and WC with CAD require further investigation, as collider stratification may be occurring. Additionally, central adiposity (measured by WHR) separated from general adiposity (measured by BMI) and general adiposity might pose similar risks for CAD. In clinical practice, physicians should pay attention to the potential effects of different obesity-related traits on CAD.
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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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Giménez-Mascarell P, Schirrmacher CE, Martínez-Cruz LA, Müller D. Novel Aspects of Renal Magnesium Homeostasis. Front Pediatr 2018; 6:77. [PMID: 29686978 PMCID: PMC5900390 DOI: 10.3389/fped.2018.00077] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Accepted: 03/13/2018] [Indexed: 12/29/2022] Open
Abstract
Magnesium (Mg2+) is indispensable for several vital functions, such as neurotransmission, cardiac conductance, blood glucose, blood pressure regulation, and proper function of more than 300 enzymes. Thus, Mg2+ homeostasis is subject to tight regulation. Besides the fast and immediate regulation of plasma Mg2+, a major part of Mg2+ homeostasis is realized by a concerted action of epithelial molecular structures that tightly control intestinal uptake and renal absorption. This mechanism is provided by a combination of para- and transcellular pathways. Whereas the first pathway provides the organism with a maximal amount of vital substances by a minimal energy expenditure, the latter enables controlling and fine-tuning by means of local and regional regulatory systems and also, hormonal control. The paracellular pathway is driven by an electrochemical gradient and realized in principal by the tight junction (TJ), a supramolecular organization of membrane-bound proteins and their adaptor and scaffolding proteins. TJ determinants are claudins (CLDN), a family of membrane spanning proteins that generate a barrier or a pore between two adjacent epithelial cells. Many insights into molecular mechanisms of Mg2+ handling have been achieved by the identification of alterations and mutations in human genes which cause disorders of paracellular Mg2+ pathways (CLDN10, CLDN14, CLDN16, CLDN19). Also, in the distal convoluted tubule, a basolateral protein, CNNM2, causes if mutated, familial dominant and also recessive renal Mg2+ wasting, albeit its true function has not been clarified yet, but is assumed to play a key role in the transcellular pathway. Moreover, mutations in human genes that are involved in regulating these proteins directly or indirectly cause, if mutated human diseases, mostly in combination with comorbidities as diabetes, cystic renal disease, or metabolic abnormalities. Generation and characterization of animal models harboring the corresponding mutations have further contributed to the elucidation of physiology and pathophysiology of Mg2+ disorders. Finally, high-end crystallization techniques allow understanding of Mg2+ handling in more detail. As this field is rapidly growing, we describe here the principles of physiology and pathophysiology of epithelial transport of renal Mg2+ homeostasis with emphasis on recently identified mechanisms involved.
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Affiliation(s)
| | - Carlotta Else Schirrmacher
- Department of Pediatric Gastroenterology, Nephrology and Metabolism, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | | | - Dominik Müller
- Department of Pediatric Gastroenterology, Nephrology and Metabolism, Charité - Universitätsmedizin Berlin, Berlin, Germany
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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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